Sample records for accurate reduced models

  1. Determining Reduced Order Models for Optimal Stochastic Reduced Order Models

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bonney, Matthew S.; Brake, Matthew R.W.

    2015-08-01

    The use of parameterized reduced order models(PROMs) within the stochastic reduced order model (SROM) framework is a logical progression for both methods. In this report, five different parameterized reduced order models are selected and critiqued against the other models along with truth model for the example of the Brake-Reuss beam. The models are: a Taylor series using finite difference, a proper orthogonal decomposition of the the output, a Craig-Bampton representation of the model, a method that uses Hyper-Dual numbers to determine the sensitivities, and a Meta-Model method that uses the Hyper-Dual results and constructs a polynomial curve to better representmore » the output data. The methods are compared against a parameter sweep and a distribution propagation where the first four statistical moments are used as a comparison. Each method produces very accurate results with the Craig-Bampton reduction having the least accurate results. The models are also compared based on time requirements for the evaluation of each model where the Meta- Model requires the least amount of time for computation by a significant amount. Each of the five models provided accurate results in a reasonable time frame. The determination of which model to use is dependent on the availability of the high-fidelity model and how many evaluations can be performed. Analysis of the output distribution is examined by using a large Monte-Carlo simulation along with a reduced simulation using Latin Hypercube and the stochastic reduced order model sampling technique. Both techniques produced accurate results. The stochastic reduced order modeling technique produced less error when compared to an exhaustive sampling for the majority of methods.« less

  2. Low-dimensional, morphologically accurate models of subthreshold membrane potential

    PubMed Central

    Kellems, Anthony R.; Roos, Derrick; Xiao, Nan; Cox, Steven J.

    2009-01-01

    The accurate simulation of a neuron’s ability to integrate distributed synaptic input typically requires the simultaneous solution of tens of thousands of ordinary differential equations. For, in order to understand how a cell distinguishes between input patterns we apparently need a model that is biophysically accurate down to the space scale of a single spine, i.e., 1 μm. We argue here that one can retain this highly detailed input structure while dramatically reducing the overall system dimension if one is content to accurately reproduce the associated membrane potential at a small number of places, e.g., at the site of action potential initiation, under subthreshold stimulation. The latter hypothesis permits us to approximate the active cell model with an associated quasi-active model, which in turn we reduce by both time-domain (Balanced Truncation) and frequency-domain (ℋ2 approximation of the transfer function) methods. We apply and contrast these methods on a suite of typical cells, achieving up to four orders of magnitude in dimension reduction and an associated speed-up in the simulation of dendritic democratization and resonance. We also append a threshold mechanism and indicate that this reduction has the potential to deliver an accurate quasi-integrate and fire model. PMID:19172386

  3. Accurate lithography simulation model based on convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Watanabe, Yuki; Kimura, Taiki; Matsunawa, Tetsuaki; Nojima, Shigeki

    2017-07-01

    Lithography simulation is an essential technique for today's semiconductor manufacturing process. In order to calculate an entire chip in realistic time, compact resist model is commonly used. The model is established for faster calculation. To have accurate compact resist model, it is necessary to fix a complicated non-linear model function. However, it is difficult to decide an appropriate function manually because there are many options. This paper proposes a new compact resist model using CNN (Convolutional Neural Networks) which is one of deep learning techniques. CNN model makes it possible to determine an appropriate model function and achieve accurate simulation. Experimental results show CNN model can reduce CD prediction errors by 70% compared with the conventional model.

  4. Reduced Order Modeling Incompressible Flows

    NASA Technical Reports Server (NTRS)

    Helenbrook, B. T.

    2010-01-01

    The details: a) Need stable numerical methods; b) Round off error can be considerable; c) Not convinced modes are correct for incompressible flow. Nonetheless, can derive compact and accurate reduced-order models. Can be used to generate actuator models or full flow-field models

  5. An Accurate and Dynamic Computer Graphics Muscle Model

    NASA Technical Reports Server (NTRS)

    Levine, David Asher

    1997-01-01

    A computer based musculo-skeletal model was developed at the University in the departments of Mechanical and Biomedical Engineering. This model accurately represents human shoulder kinematics. The result of this model is the graphical display of bones moving through an appropriate range of motion based on inputs of EMGs and external forces. The need existed to incorporate a geometric muscle model in the larger musculo-skeletal model. Previous muscle models did not accurately represent muscle geometries, nor did they account for the kinematics of tendons. This thesis covers the creation of a new muscle model for use in the above musculo-skeletal model. This muscle model was based on anatomical data from the Visible Human Project (VHP) cadaver study. Two-dimensional digital images from the VHP were analyzed and reconstructed to recreate the three-dimensional muscle geometries. The recreated geometries were smoothed, reduced, and sliced to form data files defining the surfaces of each muscle. The muscle modeling function opened these files during run-time and recreated the muscle surface. The modeling function applied constant volume limitations to the muscle and constant geometry limitations to the tendons.

  6. Parameterized reduced-order models using hyper-dual numbers.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Fike, Jeffrey A.; Brake, Matthew Robert

    2013-10-01

    The goal of most computational simulations is to accurately predict the behavior of a real, physical system. Accurate predictions often require very computationally expensive analyses and so reduced order models (ROMs) are commonly used. ROMs aim to reduce the computational cost of the simulations while still providing accurate results by including all of the salient physics of the real system in the ROM. However, real, physical systems often deviate from the idealized models used in simulations due to variations in manufacturing or other factors. One approach to this issue is to create a parameterized model in order to characterize themore » effect of perturbations from the nominal model on the behavior of the system. This report presents a methodology for developing parameterized ROMs, which is based on Craig-Bampton component mode synthesis and the use of hyper-dual numbers to calculate the derivatives necessary for the parameterization.« less

  7. Fast and Accurate Circuit Design Automation through Hierarchical Model Switching.

    PubMed

    Huynh, Linh; Tagkopoulos, Ilias

    2015-08-21

    In computer-aided biological design, the trifecta of characterized part libraries, accurate models and optimal design parameters is crucial for producing reliable designs. As the number of parts and model complexity increase, however, it becomes exponentially more difficult for any optimization method to search the solution space, hence creating a trade-off that hampers efficient design. To address this issue, we present a hierarchical computer-aided design architecture that uses a two-step approach for biological design. First, a simple model of low computational complexity is used to predict circuit behavior and assess candidate circuit branches through branch-and-bound methods. Then, a complex, nonlinear circuit model is used for a fine-grained search of the reduced solution space, thus achieving more accurate results. Evaluation with a benchmark of 11 circuits and a library of 102 experimental designs with known characterization parameters demonstrates a speed-up of 3 orders of magnitude when compared to other design methods that provide optimality guarantees.

  8. Mental models accurately predict emotion transitions.

    PubMed

    Thornton, Mark A; Tamir, Diana I

    2017-06-06

    Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

  9. Mental models accurately predict emotion transitions

    PubMed Central

    Thornton, Mark A.; Tamir, Diana I.

    2017-01-01

    Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373

  10. Investigation on the Practicality of Developing Reduced Thermal Models

    NASA Technical Reports Server (NTRS)

    Lombardi, Giancarlo; Yang, Kan

    2015-01-01

    Throughout the spacecraft design and development process, detailed instrument thermal models are created to simulate their on-orbit behavior and to ensure that they do not exceed any thermal limits. These detailed models, while generating highly accurate predictions, can sometimes lead to long simulation run times, especially when integrated with a spacecraft observatory model. Therefore, reduced models containing less detail are typically produced in tandem with the detailed models so that results may be more readily available, albeit less accurate. In the current study, both reduced and detailed instrument models are integrated with their associated spacecraft bus models to examine the impact of instrument model reduction on run time and accuracy. Preexisting instrument bus thermal model pairs from several projects were used to determine trends between detailed and reduced thermal models; namely, the Mirror Optical Bench (MOB) on the Gravity and Extreme Magnetism Small Explorer (GEMS) spacecraft, Advanced Topography Laser Altimeter System (ATLAS) on the Ice, Cloud, and Elevation Satellite 2 (ICESat-2), and the Neutral Mass Spectrometer (NMS) on the Lunar Atmosphere and Dust Environment Explorer (LADEE). Hot and cold cases were run for each model to capture the behavior of the models at both thermal extremes. It was found that, though decreasing the number of nodes from a detailed to reduced model brought about a reduction in the run-time, a large time savings was not observed, nor was it a linear relationship between the percentage of nodes reduced and time saved. However, significant losses in accuracy were observed with greater model reduction. It was found that while reduced models are useful in decreasing run time, there exists a threshold of reduction where, once exceeded, the loss in accuracy outweighs the benefit from reduced model runtime.

  11. A methodology for reduced order modeling and calibration of the upper atmosphere

    NASA Astrophysics Data System (ADS)

    Mehta, Piyush M.; Linares, Richard

    2017-10-01

    Atmospheric drag is the largest source of uncertainty in accurately predicting the orbit of satellites in low Earth orbit (LEO). Accurately predicting drag for objects that traverse LEO is critical to space situational awareness. Atmospheric models used for orbital drag calculations can be characterized either as empirical or physics-based (first principles based). Empirical models are fast to evaluate but offer limited real-time predictive/forecasting ability, while physics based models offer greater predictive/forecasting ability but require dedicated parallel computational resources. Also, calibration with accurate data is required for either type of models. This paper presents a new methodology based on proper orthogonal decomposition toward development of a quasi-physical, predictive, reduced order model that combines the speed of empirical and the predictive/forecasting capabilities of physics-based models. The methodology is developed to reduce the high dimensionality of physics-based models while maintaining its capabilities. We develop the methodology using the Naval Research Lab's Mass Spectrometer Incoherent Scatter model and show that the diurnal and seasonal variations can be captured using a small number of modes and parameters. We also present calibration of the reduced order model using the CHAMP and GRACE accelerometer-derived densities. Results show that the method performs well for modeling and calibration of the upper atmosphere.

  12. Constrained reduced-order models based on proper orthogonal decomposition

    DOE PAGES

    Reddy, Sohail R.; Freno, Brian Andrew; Cizmas, Paul G. A.; ...

    2017-04-09

    A novel approach is presented to constrain reduced-order models (ROM) based on proper orthogonal decomposition (POD). The Karush–Kuhn–Tucker (KKT) conditions were applied to the traditional reduced-order model to constrain the solution to user-defined bounds. The constrained reduced-order model (C-ROM) was applied and validated against the analytical solution to the first-order wave equation. C-ROM was also applied to the analysis of fluidized beds. Lastly, it was shown that the ROM and C-ROM produced accurate results and that C-ROM was less sensitive to error propagation through time than the ROM.

  13. A hybrid solution using computational prediction and measured data to accurately determine process corrections with reduced overlay sampling

    NASA Astrophysics Data System (ADS)

    Noyes, Ben F.; Mokaberi, Babak; Mandoy, Ram; Pate, Alex; Huijgen, Ralph; McBurney, Mike; Chen, Owen

    2017-03-01

    Reducing overlay error via an accurate APC feedback system is one of the main challenges in high volume production of the current and future nodes in the semiconductor industry. The overlay feedback system directly affects the number of dies meeting overlay specification and the number of layers requiring dedicated exposure tools through the fabrication flow. Increasing the former number and reducing the latter number is beneficial for the overall efficiency and yield of the fabrication process. An overlay feedback system requires accurate determination of the overlay error, or fingerprint, on exposed wafers in order to determine corrections to be automatically and dynamically applied to the exposure of future wafers. Since current and future nodes require correction per exposure (CPE), the resolution of the overlay fingerprint must be high enough to accommodate CPE in the overlay feedback system, or overlay control module (OCM). Determining a high resolution fingerprint from measured data requires extremely dense overlay sampling that takes a significant amount of measurement time. For static corrections this is acceptable, but in an automated dynamic correction system this method creates extreme bottlenecks for the throughput of said system as new lots have to wait until the previous lot is measured. One solution is using a less dense overlay sampling scheme and employing computationally up-sampled data to a dense fingerprint. That method uses a global fingerprint model over the entire wafer; measured localized overlay errors are therefore not always represented in its up-sampled output. This paper will discuss a hybrid system shown in Fig. 1 that combines a computationally up-sampled fingerprint with the measured data to more accurately capture the actual fingerprint, including local overlay errors. Such a hybrid system is shown to result in reduced modelled residuals while determining the fingerprint, and better on-product overlay performance.

  14. Reduced-Order Modeling for Flutter/LCO Using Recurrent Artificial Neural Network

    NASA Technical Reports Server (NTRS)

    Yao, Weigang; Liou, Meng-Sing

    2012-01-01

    The present study demonstrates the efficacy of a recurrent artificial neural network to provide a high fidelity time-dependent nonlinear reduced-order model (ROM) for flutter/limit-cycle oscillation (LCO) modeling. An artificial neural network is a relatively straightforward nonlinear method for modeling an input-output relationship from a set of known data, for which we use the radial basis function (RBF) with its parameters determined through a training process. The resulting RBF neural network, however, is only static and is not yet adequate for an application to problems of dynamic nature. The recurrent neural network method [1] is applied to construct a reduced order model resulting from a series of high-fidelity time-dependent data of aero-elastic simulations. Once the RBF neural network ROM is constructed properly, an accurate approximate solution can be obtained at a fraction of the cost of a full-order computation. The method derived during the study has been validated for predicting nonlinear aerodynamic forces in transonic flow and is capable of accurate flutter/LCO simulations. The obtained results indicate that the present recurrent RBF neural network is accurate and efficient for nonlinear aero-elastic system analysis

  15. Variational asymptotic modeling of composite dimensionally reducible structures

    NASA Astrophysics Data System (ADS)

    Yu, Wenbin

    A general framework to construct accurate reduced models for composite dimensionally reducible structures (beams, plates and shells) was formulated based on two theoretical foundations: decomposition of the rotation tensor and the variational asymptotic method. Two engineering software systems, Variational Asymptotic Beam Sectional Analysis (VABS, new version) and Variational Asymptotic Plate and Shell Analysis (VAPAS), were developed. Several restrictions found in previous work on beam modeling were removed in the present effort. A general formulation of Timoshenko-like cross-sectional analysis was developed, through which the shear center coordinates and a consistent Vlasov model can be obtained. Recovery relations are given to recover the asymptotic approximations for the three-dimensional field variables. A new version of VABS has been developed, which is a much improved program in comparison to the old one. Numerous examples are given for validation. A Reissner-like model being as asymptotically correct as possible was obtained for composite plates and shells. After formulating the three-dimensional elasticity problem in intrinsic form, the variational asymptotic method was used to systematically reduce the dimensionality of the problem by taking advantage of the smallness of the thickness. The through-the-thickness analysis is solved by a one-dimensional finite element method to provide the stiffnesses as input for the two-dimensional nonlinear plate or shell analysis as well as recovery relations to approximately express the three-dimensional results. The known fact that there exists more than one theory that is asymptotically correct to a given order is adopted to cast the refined energy into a Reissner-like form. A two-dimensional nonlinear shell theory consistent with the present modeling process was developed. The engineering computer code VAPAS was developed and inserted into DYMORE to provide an efficient and accurate analysis of composite plates and

  16. Variational calculation of second-order reduced density matrices by strong N-representability conditions and an accurate semidefinite programming solver.

    PubMed

    Nakata, Maho; Braams, Bastiaan J; Fujisawa, Katsuki; Fukuda, Mituhiro; Percus, Jerome K; Yamashita, Makoto; Zhao, Zhengji

    2008-04-28

    The reduced density matrix (RDM) method, which is a variational calculation based on the second-order reduced density matrix, is applied to the ground state energies and the dipole moments for 57 different states of atoms, molecules, and to the ground state energies and the elements of 2-RDM for the Hubbard model. We explore the well-known N-representability conditions (P, Q, and G) together with the more recent and much stronger T1 and T2(') conditions. T2(') condition was recently rederived and it implies T2 condition. Using these N-representability conditions, we can usually calculate correlation energies in percentage ranging from 100% to 101%, whose accuracy is similar to CCSD(T) and even better for high spin states or anion systems where CCSD(T) fails. Highly accurate calculations are carried out by handling equality constraints and/or developing multiple precision arithmetic in the semidefinite programming (SDP) solver. Results show that handling equality constraints correctly improves the accuracy from 0.1 to 0.6 mhartree. Additionally, improvements by replacing T2 condition with T2(') condition are typically of 0.1-0.5 mhartree. The newly developed multiple precision arithmetic version of SDP solver calculates extraordinary accurate energies for the one dimensional Hubbard model and Be atom. It gives at least 16 significant digits for energies, where double precision calculations gives only two to eight digits. It also provides physically meaningful results for the Hubbard model in the high correlation limit.

  17. Accurate modelling of unsteady flows in collapsible tubes.

    PubMed

    Marchandise, Emilie; Flaud, Patrice

    2010-01-01

    The context of this paper is the development of a general and efficient numerical haemodynamic tool to help clinicians and researchers in understanding of physiological flow phenomena. We propose an accurate one-dimensional Runge-Kutta discontinuous Galerkin (RK-DG) method coupled with lumped parameter models for the boundary conditions. The suggested model has already been successfully applied to haemodynamics in arteries and is now extended for the flow in collapsible tubes such as veins. The main difference with cardiovascular simulations is that the flow may become supercritical and elastic jumps may appear with the numerical consequence that scheme may not remain monotone if no limiting procedure is introduced. We show that our second-order RK-DG method equipped with an approximate Roe's Riemann solver and a slope-limiting procedure allows us to capture elastic jumps accurately. Moreover, this paper demonstrates that the complex physics associated with such flows is more accurately modelled than with traditional methods such as finite difference methods or finite volumes. We present various benchmark problems that show the flexibility and applicability of the numerical method. Our solutions are compared with analytical solutions when they are available and with solutions obtained using other numerical methods. Finally, to illustrate the clinical interest, we study the emptying process in a calf vein squeezed by contracting skeletal muscle in a normal and pathological subject. We compare our results with experimental simulations and discuss the sensitivity to parameters of our model.

  18. Bottom-up coarse-grained models that accurately describe the structure, pressure, and compressibility of molecular liquids

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Dunn, Nicholas J. H.; Noid, W. G., E-mail: wnoid@chem.psu.edu

    2015-12-28

    The present work investigates the capability of bottom-up coarse-graining (CG) methods for accurately modeling both structural and thermodynamic properties of all-atom (AA) models for molecular liquids. In particular, we consider 1, 2, and 3-site CG models for heptane, as well as 1 and 3-site CG models for toluene. For each model, we employ the multiscale coarse-graining method to determine interaction potentials that optimally approximate the configuration dependence of the many-body potential of mean force (PMF). We employ a previously developed “pressure-matching” variational principle to determine a volume-dependent contribution to the potential, U{sub V}(V), that approximates the volume-dependence of the PMF.more » We demonstrate that the resulting CG models describe AA density fluctuations with qualitative, but not quantitative, accuracy. Accordingly, we develop a self-consistent approach for further optimizing U{sub V}, such that the CG models accurately reproduce the equilibrium density, compressibility, and average pressure of the AA models, although the CG models still significantly underestimate the atomic pressure fluctuations. Additionally, by comparing this array of models that accurately describe the structure and thermodynamic pressure of heptane and toluene at a range of different resolutions, we investigate the impact of bottom-up coarse-graining upon thermodynamic properties. In particular, we demonstrate that U{sub V} accounts for the reduced cohesion in the CG models. Finally, we observe that bottom-up coarse-graining introduces subtle correlations between the resolution, the cohesive energy density, and the “simplicity” of the model.« less

  19. Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Goldhaber, Steve; Holland, Marika

    The major goal of this project was to contribute improvements to the infrastructure of an Earth System Model in order to support research in the Multiscale Methods for Accurate, Efficient, and Scale-Aware models of the Earth System project. In support of this, the NCAR team accomplished two main tasks: improving input/output performance of the model and improving atmospheric model simulation quality. Improvement of the performance and scalability of data input and diagnostic output within the model required a new infrastructure which can efficiently handle the unstructured grids common in multiscale simulations. This allows for a more computationally efficient model, enablingmore » more years of Earth System simulation. The quality of the model simulations was improved by reducing grid-point noise in the spectral element version of the Community Atmosphere Model (CAM-SE). This was achieved by running the physics of the model using grid-cell data on a finite-volume grid.« less

  20. Accurate Modeling Method for Cu Interconnect

    NASA Astrophysics Data System (ADS)

    Yamada, Kenta; Kitahara, Hiroshi; Asai, Yoshihiko; Sakamoto, Hideo; Okada, Norio; Yasuda, Makoto; Oda, Noriaki; Sakurai, Michio; Hiroi, Masayuki; Takewaki, Toshiyuki; Ohnishi, Sadayuki; Iguchi, Manabu; Minda, Hiroyasu; Suzuki, Mieko

    This paper proposes an accurate modeling method of the copper interconnect cross-section in which the width and thickness dependence on layout patterns and density caused by processes (CMP, etching, sputtering, lithography, and so on) are fully, incorporated and universally expressed. In addition, we have developed specific test patterns for the model parameters extraction, and an efficient extraction flow. We have extracted the model parameters for 0.15μm CMOS using this method and confirmed that 10%τpd error normally observed with conventional LPE (Layout Parameters Extraction) was completely dissolved. Moreover, it is verified that the model can be applied to more advanced technologies (90nm, 65nm and 55nm CMOS). Since the interconnect delay variations due to the processes constitute a significant part of what have conventionally been treated as random variations, use of the proposed model could enable one to greatly narrow the guardbands required to guarantee a desired yield, thereby facilitating design closure.

  1. REVEAL: An Extensible Reduced Order Model Builder for Simulation and Modeling

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Agarwal, Khushbu; Sharma, Poorva; Ma, Jinliang

    2013-04-30

    Many science domains need to build computationally efficient and accurate representations of high fidelity, computationally expensive simulations. These computationally efficient versions are known as reduced-order models. This paper presents the design and implementation of a novel reduced-order model (ROM) builder, the REVEAL toolset. This toolset generates ROMs based on science- and engineering-domain specific simulations executed on high performance computing (HPC) platforms. The toolset encompasses a range of sampling and regression methods that can be used to generate a ROM, automatically quantifies the ROM accuracy, and provides support for an iterative approach to improve ROM accuracy. REVEAL is designed to bemore » extensible in order to utilize the core functionality with any simulator that has published input and output formats. It also defines programmatic interfaces to include new sampling and regression techniques so that users can ‘mix and match’ mathematical techniques to best suit the characteristics of their model. In this paper, we describe the architecture of REVEAL and demonstrate its usage with a computational fluid dynamics model used in carbon capture.« less

  2. An Accurate and Computationally Efficient Model for Membrane-Type Circular-Symmetric Micro-Hotplates

    PubMed Central

    Khan, Usman; Falconi, Christian

    2014-01-01

    Ideally, the design of high-performance micro-hotplates would require a large number of simulations because of the existence of many important design parameters as well as the possibly crucial effects of both spread and drift. However, the computational cost of FEM simulations, which are the only available tool for accurately predicting the temperature in micro-hotplates, is very high. As a result, micro-hotplate designers generally have no effective simulation-tools for the optimization. In order to circumvent these issues, here, we propose a model for practical circular-symmetric micro-hot-plates which takes advantage of modified Bessel functions, computationally efficient matrix-approach for considering the relevant boundary conditions, Taylor linearization for modeling the Joule heating and radiation losses, and external-region-segmentation strategy in order to accurately take into account radiation losses in the entire micro-hotplate. The proposed model is almost as accurate as FEM simulations and two to three orders of magnitude more computationally efficient (e.g., 45 s versus more than 8 h). The residual errors, which are mainly associated to the undesired heating in the electrical contacts, are small (e.g., few degrees Celsius for an 800 °C operating temperature) and, for important analyses, almost constant. Therefore, we also introduce a computationally-easy single-FEM-compensation strategy in order to reduce the residual errors to about 1 °C. As illustrative examples of the power of our approach, we report the systematic investigation of a spread in the membrane thermal conductivity and of combined variations of both ambient and bulk temperatures. Our model enables a much faster characterization of micro-hotplates and, thus, a much more effective optimization prior to fabrication. PMID:24763214

  3. 3ARM: A Fast, Accurate Radiative Transfer Model for Use in Climate Models

    NASA Technical Reports Server (NTRS)

    Bergstrom, R. W.; Kinne, S.; Sokolik, I. N.; Toon, O. B.; Mlawer, E. J.; Clough, S. A.; Ackerman, T. P.; Mather, J.

    1996-01-01

    A new radiative transfer model combining the efforts of three groups of researchers is discussed. The model accurately computes radiative transfer in a inhomogeneous absorbing, scattering and emitting atmospheres. As an illustration of the model, results are shown for the effects of dust on the thermal radiation.

  4. 3ARM: A Fast, Accurate Radiative Transfer Model for use in Climate Models

    NASA Technical Reports Server (NTRS)

    Bergstrom, R. W.; Kinne, S.; Sokolik, I. N.; Toon, O. B.; Mlawer, E. J.; Clough, S. A.; Ackerman, T. P.; Mather, J.

    1996-01-01

    A new radiative transfer model combining the efforts of three groups of researchers is discussed. The model accurately computes radiative transfer in a inhomogeneous absorbing, scattering and emitting atmospheres. As an illustration of the model, results are shown for the effects of dust on the thermal radiation.

  5. 3ARM: A Fast, Accurate Radiative Transfer Model For Use in Climate Models

    NASA Technical Reports Server (NTRS)

    Bergstrom, R. W.; Kinne, S.; Sokolik, I. N.; Toon, O. B.; Mlawer, E. J.; Clough, S. A.; Ackerman, T. P.; Mather, J.

    1996-01-01

    A new radiative transfer model combining the efforts of three groups of researchers is discussed. The model accurately computes radiative transfer in a inhomogeneous absorbing, scattering and emitting atmospheres. As an illustration of the model, results are shown for the effects of dust on the thermal radiation.

  6. Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach

    NASA Technical Reports Server (NTRS)

    Aguilo, Miguel A.; Warner, James E.

    2017-01-01

    This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.

  7. Can phenological models predict tree phenology accurately under climate change conditions?

    NASA Astrophysics Data System (ADS)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2014-05-01

    The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

  8. An Accurate Temperature Correction Model for Thermocouple Hygrometers 1

    PubMed Central

    Savage, Michael J.; Cass, Alfred; de Jager, James M.

    1982-01-01

    Numerous water relation studies have used thermocouple hygrometers routinely. However, the accurate temperature correction of hygrometer calibration curve slopes seems to have been largely neglected in both psychrometric and dewpoint techniques. In the case of thermocouple psychrometers, two temperature correction models are proposed, each based on measurement of the thermojunction radius and calculation of the theoretical voltage sensitivity to changes in water potential. The first model relies on calibration at a single temperature and the second at two temperatures. Both these models were more accurate than the temperature correction models currently in use for four psychrometers calibrated over a range of temperatures (15-38°C). The model based on calibration at two temperatures is superior to that based on only one calibration. The model proposed for dewpoint hygrometers is similar to that for psychrometers. It is based on the theoretical voltage sensitivity to changes in water potential. Comparison with empirical data from three dewpoint hygrometers calibrated at four different temperatures indicates that these instruments need only be calibrated at, e.g. 25°C, if the calibration slopes are corrected for temperature. PMID:16662241

  9. An accurate model for predicting high frequency noise of nanoscale NMOS SOI transistors

    NASA Astrophysics Data System (ADS)

    Shen, Yanfei; Cui, Jie; Mohammadi, Saeed

    2017-05-01

    A nonlinear and scalable model suitable for predicting high frequency noise of N-type Metal Oxide Semiconductor (NMOS) transistors is presented. The model is developed for a commercial 45 nm CMOS SOI technology and its accuracy is validated through comparison with measured performance of a microwave low noise amplifier. The model employs the virtual source nonlinear core and adds parasitic elements to accurately simulate the RF behavior of multi-finger NMOS transistors up to 40 GHz. For the first time, the traditional long-channel thermal noise model is supplemented with an injection noise model to accurately represent the noise behavior of these short-channel transistors up to 26 GHz. The developed model is simple and easy to extract, yet very accurate.

  10. Equivalent reduced model technique development for nonlinear system dynamic response

    NASA Astrophysics Data System (ADS)

    Thibault, Louis; Avitabile, Peter; Foley, Jason; Wolfson, Janet

    2013-04-01

    The dynamic response of structural systems commonly involves nonlinear effects. Often times, structural systems are made up of several components, whose individual behavior is essentially linear compared to the total assembled system. However, the assembly of linear components using highly nonlinear connection elements or contact regions causes the entire system to become nonlinear. Conventional transient nonlinear integration of the equations of motion can be extremely computationally intensive, especially when the finite element models describing the components are very large and detailed. In this work, the equivalent reduced model technique (ERMT) is developed to address complicated nonlinear contact problems. ERMT utilizes a highly accurate model reduction scheme, the System equivalent reduction expansion process (SEREP). Extremely reduced order models that provide dynamic characteristics of linear components, which are interconnected with highly nonlinear connection elements, are formulated with SEREP for the dynamic response evaluation using direct integration techniques. The full-space solution will be compared to the response obtained using drastically reduced models to make evident the usefulness of the technique for a variety of analytical cases.

  11. Determination of effective loss factors in reduced SEA models

    NASA Astrophysics Data System (ADS)

    Chimeno Manguán, M.; Fernández de las Heras, M. J.; Roibás Millán, E.; Simón Hidalgo, F.

    2017-01-01

    The definition of Statistical Energy Analysis (SEA) models for large complex structures is highly conditioned by the classification of the structure elements into a set of coupled subsystems and the subsequent determination of the loss factors representing both the internal damping and the coupling between subsystems. The accurate definition of the complete system can lead to excessively large models as the size and complexity increases. This fact can also rise practical issues for the experimental determination of the loss factors. This work presents a formulation of reduced SEA models for incomplete systems defined by a set of effective loss factors. This reduced SEA model provides a feasible number of subsystems for the application of the Power Injection Method (PIM). For structures of high complexity, their components accessibility can be restricted, for instance internal equipments or panels. For these cases the use of PIM to carry out an experimental SEA analysis is not possible. New methods are presented for this case in combination with the reduced SEA models. These methods allow defining some of the model loss factors that could not be obtained through PIM. The methods are validated with a numerical analysis case and they are also applied to an actual spacecraft structure with accessibility restrictions: a solar wing in folded configuration.

  12. Reduced Order Models for Dynamic Behavior of Elastomer Damping Devices

    NASA Astrophysics Data System (ADS)

    Morin, B.; Legay, A.; Deü, J.-F.

    2016-09-01

    In the context of passive damping, various mechanical systems from the space industry use elastomer components (shock absorbers, silent blocks, flexible joints...). The material of these devices has frequency, temperature and amplitude dependent characteristics. The associated numerical models, using viscoelastic and hyperelastic constitutive behaviour, may become computationally too expensive during a design process. The aim of this work is to propose efficient reduced viscoelastic models of rubber devices. The first step is to choose an accurate material model that represent the viscoelasticity. The second step is to reduce the rubber device finite element model to a super-element that keeps the frequency dependence. This reduced model is first built by taking into account the fact that the device's interfaces are much more rigid than the rubber core. To make use of this difference, kinematical constraints enforce the rigid body motion of these interfaces reducing the rubber device model to twelve dofs only on the interfaces (three rotations and three translations per face). Then, the superelement is built by using a component mode synthesis method. As an application, the dynamic behavior of a structure supported by four hourglass shaped rubber devices under harmonic loads is analysed to show the efficiency of the proposed approach.

  13. Estimation of zeta potential of electroosmotic flow in a microchannel using a reduced-order model.

    PubMed

    Park, H M; Hong, S M; Lee, J S

    2007-10-01

    A reduced-order model is derived for electroosmotic flow in a microchannel of nonuniform cross section using the Karhunen-Loève Galerkin (KLG) procedure. The resulting reduced-order model is shown to predict electroosmotic flows accurately with minimal consumption of computer time for a wide range of zeta potential zeta and dielectric constant epsilon. Using the reduced-order model, a practical method is devised to estimate zeta from the velocity measurements of the electroosmotic flow in the microchannel. The proposed method is found to estimate zeta with reasonable accuracy even with noisy velocity measurements.

  14. Development and application of accurate analytical models for single active electron potentials

    NASA Astrophysics Data System (ADS)

    Miller, Michelle; Jaron-Becker, Agnieszka; Becker, Andreas

    2015-05-01

    The single active electron (SAE) approximation is a theoretical model frequently employed to study scenarios in which inner-shell electrons may productively be treated as frozen spectators to a physical process of interest, and accurate analytical approximations for these potentials are sought as a useful simulation tool. Density function theory is often used to construct a SAE potential, requiring that a further approximation for the exchange correlation functional be enacted. In this study, we employ the Krieger, Li, and Iafrate (KLI) modification to the optimized-effective-potential (OEP) method to reduce the complexity of the problem to the straightforward solution of a system of linear equations through simple arguments regarding the behavior of the exchange-correlation potential in regions where a single orbital dominates. We employ this method for the solution of atomic and molecular potentials, and use the resultant curve to devise a systematic construction for highly accurate and useful analytical approximations for several systems. Supported by the U.S. Department of Energy (Grant No. DE-FG02-09ER16103), and the U.S. National Science Foundation (Graduate Research Fellowship, Grants No. PHY-1125844 and No. PHY-1068706).

  15. Physically-Based Reduced Order Modelling of a Uni-Axial Polysilicon MEMS Accelerometer

    PubMed Central

    Ghisi, Aldo; Mariani, Stefano; Corigliano, Alberto; Zerbini, Sarah

    2012-01-01

    In this paper, the mechanical response of a commercial off-the-shelf, uni-axial polysilicon MEMS accelerometer subject to drops is numerically investigated. To speed up the calculations, a simplified physically-based (beams and plate), two degrees of freedom model of the movable parts of the sensor is adopted. The capability and the accuracy of the model are assessed against three-dimensional finite element simulations, and against outcomes of experiments on instrumented samples. It is shown that the reduced order model provides accurate outcomes as for the system dynamics. To also get rather accurate results in terms of stress fields within regions that are prone to fail upon high-g shocks, a correction factor is proposed by accounting for the local stress amplification induced by re-entrant corners. PMID:23202031

  16. A Simple and Accurate Rate-Driven Infiltration Model

    NASA Astrophysics Data System (ADS)

    Cui, G.; Zhu, J.

    2017-12-01

    In this study, we develop a novel Rate-Driven Infiltration Model (RDIMOD) for simulating infiltration into soils. Unlike traditional methods, RDIMOD avoids numerically solving the highly non-linear Richards equation or simply modeling with empirical parameters. RDIMOD employs infiltration rate as model input to simulate one-dimensional infiltration process by solving an ordinary differential equation. The model can simulate the evolutions of wetting front, infiltration rate, and cumulative infiltration on any surface slope including vertical and horizontal directions. Comparing to the results from the Richards equation for both vertical infiltration and horizontal infiltration, RDIMOD simply and accurately predicts infiltration processes for any type of soils and soil hydraulic models without numerical difficulty. Taking into account the accuracy, capability, and computational effectiveness and stability, RDIMOD can be used in large-scale hydrologic and land-atmosphere modeling.

  17. Reduced-order surrogate models for Green's functions in black hole spacetimes

    NASA Astrophysics Data System (ADS)

    Galley, Chad; Wardell, Barry

    2016-03-01

    The fundamental nature of linear wave propagation in curved spacetime is encoded in the retarded Green's function (or propagator). Green's functions are useful tools because almost any field quantity of interest can be computed via convolution integrals with a source. In addition, perturbation theories involving nonlinear wave propagation can be expressed in terms of multiple convolutions of the Green's function. Recently, numerical solutions for propagators in black hole spacetimes have been found that are globally valid and accurate for computing physical quantities. However, the data generated is too large for practical use because the propagator depends on two spacetime points that must be sampled finely to yield accurate convolutions. I describe how to build a reduced-order model that can be evaluated as a substitute, or surrogate, for solutions of the curved spacetime Green's function equation. The resulting surrogate accurately and quickly models the original and out-of-sample data. I discuss applications of the surrogate, including self-consistent evolutions and waveforms of extreme mass ratio binaries. Green's function surrogate models provide a new and practical way to handle many old problems involving wave propagation and motion in curved spacetimes.

  18. Accurate electromagnetic modeling of terahertz detectors

    NASA Technical Reports Server (NTRS)

    Focardi, Paolo; McGrath, William R.

    2004-01-01

    Twin slot antennas coupled to superconducting devices have been developed over the years as single pixel detectors in the terahertz (THz) frequency range for space-based and astronomy applications. Used either for mixing or direct detection, they have been object of several investigations, and are currently being developed for several missions funded or co-funded by NASA. Although they have shown promising performance in terms of noise and sensitivity, so far they have usually also shown a considerable disagreement in terms of performance between calculations and measurements, especially when considering center frequency and bandwidth. In this paper we present a thorough and accurate electromagnetic model of complete detector and we compare the results of calculations with measurements. Starting from a model of the embedding circuit, the effect of all the other elements in the detector in the coupled power have been analyzed. An extensive variety of measured and calculated data, as presented in this paper, demonstrates the effectiveness and reliability of the electromagnetic model at frequencies between 600 GHz and 2.5THz.

  19. Utilizing Adjoint-Based Error Estimates for Surrogate Models to Accurately Predict Probabilities of Events

    DOE PAGES

    Butler, Troy; Wildey, Timothy

    2018-01-01

    In thist study, we develop a procedure to utilize error estimates for samples of a surrogate model to compute robust upper and lower bounds on estimates of probabilities of events. We show that these error estimates can also be used in an adaptive algorithm to simultaneously reduce the computational cost and increase the accuracy in estimating probabilities of events using computationally expensive high-fidelity models. Specifically, we introduce the notion of reliability of a sample of a surrogate model, and we prove that utilizing the surrogate model for the reliable samples and the high-fidelity model for the unreliable samples gives preciselymore » the same estimate of the probability of the output event as would be obtained by evaluation of the original model for each sample. The adaptive algorithm uses the additional evaluations of the high-fidelity model for the unreliable samples to locally improve the surrogate model near the limit state, which significantly reduces the number of high-fidelity model evaluations as the limit state is resolved. Numerical results based on a recently developed adjoint-based approach for estimating the error in samples of a surrogate are provided to demonstrate (1) the robustness of the bounds on the probability of an event, and (2) that the adaptive enhancement algorithm provides a more accurate estimate of the probability of the QoI event than standard response surface approximation methods at a lower computational cost.« less

  20. Utilizing Adjoint-Based Error Estimates for Surrogate Models to Accurately Predict Probabilities of Events

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Butler, Troy; Wildey, Timothy

    In thist study, we develop a procedure to utilize error estimates for samples of a surrogate model to compute robust upper and lower bounds on estimates of probabilities of events. We show that these error estimates can also be used in an adaptive algorithm to simultaneously reduce the computational cost and increase the accuracy in estimating probabilities of events using computationally expensive high-fidelity models. Specifically, we introduce the notion of reliability of a sample of a surrogate model, and we prove that utilizing the surrogate model for the reliable samples and the high-fidelity model for the unreliable samples gives preciselymore » the same estimate of the probability of the output event as would be obtained by evaluation of the original model for each sample. The adaptive algorithm uses the additional evaluations of the high-fidelity model for the unreliable samples to locally improve the surrogate model near the limit state, which significantly reduces the number of high-fidelity model evaluations as the limit state is resolved. Numerical results based on a recently developed adjoint-based approach for estimating the error in samples of a surrogate are provided to demonstrate (1) the robustness of the bounds on the probability of an event, and (2) that the adaptive enhancement algorithm provides a more accurate estimate of the probability of the QoI event than standard response surface approximation methods at a lower computational cost.« less

  1. Accurate Modeling of Ionospheric Electromagnetic Fields Generated by a Low Altitude VLF Transmitter

    DTIC Science & Technology

    2009-03-31

    AFRL-RV-HA-TR-2009-1055 Accurate Modeling of Ionospheric Electromagnetic Fields Generated by a Low Altitude VLF Transmitter ...m (or even 500 m) at mid to high latitudes . At low latitudes , the FDTD model exhibits variations that make it difficult to determine a reliable...Scientific, Final 3. DATES COVERED (From - To) 02-08-2006 – 31-12-2008 4. TITLE AND SUBTITLE Accurate Modeling of Ionospheric Electromagnetic Fields

  2. An accurate halo model for fitting non-linear cosmological power spectra and baryonic feedback models

    NASA Astrophysics Data System (ADS)

    Mead, A. J.; Peacock, J. A.; Heymans, C.; Joudaki, S.; Heavens, A. F.

    2015-12-01

    We present an optimized variant of the halo model, designed to produce accurate matter power spectra well into the non-linear regime for a wide range of cosmological models. To do this, we introduce physically motivated free parameters into the halo-model formalism and fit these to data from high-resolution N-body simulations. For a variety of Λ cold dark matter (ΛCDM) and wCDM models, the halo-model power is accurate to ≃ 5 per cent for k ≤ 10h Mpc-1 and z ≤ 2. An advantage of our new halo model is that it can be adapted to account for the effects of baryonic feedback on the power spectrum. We demonstrate this by fitting the halo model to power spectra from the OWLS (OverWhelmingly Large Simulations) hydrodynamical simulation suite via parameters that govern halo internal structure. We are able to fit all feedback models investigated at the 5 per cent level using only two free parameters, and we place limits on the range of these halo parameters for feedback models investigated by the OWLS simulations. Accurate predictions to high k are vital for weak-lensing surveys, and these halo parameters could be considered nuisance parameters to marginalize over in future analyses to mitigate uncertainty regarding the details of feedback. Finally, we investigate how lensing observables predicted by our model compare to those from simulations and from HALOFIT for a range of k-cuts and feedback models and quantify the angular scales at which these effects become important. Code to calculate power spectra from the model presented in this paper can be found at https://github.com/alexander-mead/hmcode.

  3. Development of Boundary Condition Independent Reduced Order Thermal Models using Proper Orthogonal Decomposition

    NASA Astrophysics Data System (ADS)

    Raghupathy, Arun; Ghia, Karman; Ghia, Urmila

    2008-11-01

    Compact Thermal Models (CTM) to represent IC packages has been traditionally developed using the DELPHI-based (DEvelopment of Libraries of PHysical models for an Integrated design) methodology. The drawbacks of this method are presented, and an alternative method is proposed. A reduced-order model that provides the complete thermal information accurately with less computational resources can be effectively used in system level simulations. Proper Orthogonal Decomposition (POD), a statistical method, can be used to reduce the order of the degree of freedom or variables of the computations for such a problem. POD along with the Galerkin projection allows us to create reduced-order models that reproduce the characteristics of the system with a considerable reduction in computational resources while maintaining a high level of accuracy. The goal of this work is to show that this method can be applied to obtain a boundary condition independent reduced-order thermal model for complex components. The methodology is applied to the 1D transient heat equation.

  4. Allele-sharing models: LOD scores and accurate linkage tests.

    PubMed

    Kong, A; Cox, N J

    1997-11-01

    Starting with a test statistic for linkage analysis based on allele sharing, we propose an associated one-parameter model. Under general missing-data patterns, this model allows exact calculation of likelihood ratios and LOD scores and has been implemented by a simple modification of existing software. Most important, accurate linkage tests can be performed. Using an example, we show that some previously suggested approaches to handling less than perfectly informative data can be unacceptably conservative. Situations in which this model may not perform well are discussed, and an alternative model that requires additional computations is suggested.

  5. Allele-sharing models: LOD scores and accurate linkage tests.

    PubMed Central

    Kong, A; Cox, N J

    1997-01-01

    Starting with a test statistic for linkage analysis based on allele sharing, we propose an associated one-parameter model. Under general missing-data patterns, this model allows exact calculation of likelihood ratios and LOD scores and has been implemented by a simple modification of existing software. Most important, accurate linkage tests can be performed. Using an example, we show that some previously suggested approaches to handling less than perfectly informative data can be unacceptably conservative. Situations in which this model may not perform well are discussed, and an alternative model that requires additional computations is suggested. PMID:9345087

  6. Fast and accurate calculation of dilute quantum gas using Uehling–Uhlenbeck model equation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Yano, Ryosuke, E-mail: ryosuke.yano@tokiorisk.co.jp

    The Uehling–Uhlenbeck (U–U) model equation is studied for the fast and accurate calculation of a dilute quantum gas. In particular, the direct simulation Monte Carlo (DSMC) method is used to solve the U–U model equation. DSMC analysis based on the U–U model equation is expected to enable the thermalization to be accurately obtained using a small number of sample particles and the dilute quantum gas dynamics to be calculated in a practical time. Finally, the applicability of DSMC analysis based on the U–U model equation to the fast and accurate calculation of a dilute quantum gas is confirmed by calculatingmore » the viscosity coefficient of a Bose gas on the basis of the Green–Kubo expression and the shock layer of a dilute Bose gas around a cylinder.« less

  7. Helicopter flight dynamics simulation with a time-accurate free-vortex wake model

    NASA Astrophysics Data System (ADS)

    Ribera, Maria

    This dissertation describes the implementation and validation of a coupled rotor-fuselage simulation model with a time-accurate free-vortex wake model capable of capturing the response to maneuvers of arbitrary amplitude. The resulting model has been used to analyze different flight conditions, including both steady and transient maneuvers. The flight dynamics model is based on a system of coupled nonlinear rotor-fuselage differential equations in first-order, state-space form. The rotor model includes flexible blades, with coupled flap-lag-torsion dynamics and swept tips; the rigid body dynamics are modeled with the non-linear Euler equations. The free wake models the rotor flow field by tracking the vortices released at the blade tips. Their behavior is described by the equations of vorticity transport, which is approximated using finite differences, and solved using a time-accurate numerical scheme. The flight dynamics model can be solved as a system of non-linear algebraic trim equations to determine the steady state solution, or integrated in time in response to pilot-applied controls. This study also implements new approaches to reduce the prohibitive computational costs associated with such complex models without losing accuracy. The mathematical model was validated for trim conditions in level flight, turns, climbs and descents. The results obtained correlate well with flight test data, both in level flight as well as turning and climbing and descending flight. The swept tip model was also found to improve the trim predictions, particularly at high speed. The behavior of the rigid body and the rotor blade dynamics were also studied and related to the aerodynamic load distributions obtained with the free wake induced velocities. The model was also validated in a lateral maneuver from hover. The results show improvements in the on-axis prediction, and indicate a possible relation between the off-axis prediction and the lack of rotor-body interaction

  8. Performance of a reduced-order FSI model for flow-induced vocal fold vibration

    NASA Astrophysics Data System (ADS)

    Chang, Siyuan; Luo, Haoxiang; Luo's lab Team

    2016-11-01

    Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which is often needed in procedures such as optimization and parameter estimation. In this work, we study the performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin. Supported by the NSF.

  9. Accurate Modeling of Galaxy Clustering on Small Scales: Testing the Standard ΛCDM + Halo Model

    NASA Astrophysics Data System (ADS)

    Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron; Scoccimarro, Roman

    2015-01-01

    The large-scale distribution of galaxies can be explained fairly simply by assuming (i) a cosmological model, which determines the dark matter halo distribution, and (ii) a simple connection between galaxies and the halos they inhabit. This conceptually simple framework, called the halo model, has been remarkably successful at reproducing the clustering of galaxies on all scales, as observed in various galaxy redshift surveys. However, none of these previous studies have carefully modeled the systematics and thus truly tested the halo model in a statistically rigorous sense. We present a new accurate and fully numerical halo model framework and test it against clustering measurements from two luminosity samples of galaxies drawn from the SDSS DR7. We show that the simple ΛCDM cosmology + halo model is not able to simultaneously reproduce the galaxy projected correlation function and the group multiplicity function. In particular, the more luminous sample shows significant tension with theory. We discuss the implications of our findings and how this work paves the way for constraining galaxy formation by accurate simultaneous modeling of multiple galaxy clustering statistics.

  10. Accurate path integration in continuous attractor network models of grid cells.

    PubMed

    Burak, Yoram; Fiete, Ila R

    2009-02-01

    Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.

  11. Creation of Anatomically Accurate Computer-Aided Design (CAD) Solid Models from Medical Images

    NASA Technical Reports Server (NTRS)

    Stewart, John E.; Graham, R. Scott; Samareh, Jamshid A.; Oberlander, Eric J.; Broaddus, William C.

    1999-01-01

    Most surgical instrumentation and implants used in the world today are designed with sophisticated Computer-Aided Design (CAD)/Computer-Aided Manufacturing (CAM) software. This software automates the mechanical development of a product from its conceptual design through manufacturing. CAD software also provides a means of manipulating solid models prior to Finite Element Modeling (FEM). Few surgical products are designed in conjunction with accurate CAD models of human anatomy because of the difficulty with which these models are created. We have developed a novel technique that creates anatomically accurate, patient specific CAD solids from medical images in a matter of minutes.

  12. Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

    DOE PAGES

    Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

    2015-02-14

    Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equationsmore » at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.« less

  13. Local Debonding and Fiber Breakage in Composite Materials Modeled Accurately

    NASA Technical Reports Server (NTRS)

    Bednarcyk, Brett A.; Arnold, Steven M.

    2001-01-01

    A prerequisite for full utilization of composite materials in aerospace components is accurate design and life prediction tools that enable the assessment of component performance and reliability. Such tools assist both structural analysts, who design and optimize structures composed of composite materials, and materials scientists who design and optimize the composite materials themselves. NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) software package (http://www.grc.nasa.gov/WWW/LPB/mac) addresses this need for composite design and life prediction tools by providing a widely applicable and accurate approach to modeling composite materials. Furthermore, MAC/GMC serves as a platform for incorporating new local models and capabilities that are under development at NASA, thus enabling these new capabilities to progress rapidly to a stage in which they can be employed by the code's end users.

  14. Accurate protein structure modeling using sparse NMR data and homologous structure information.

    PubMed

    Thompson, James M; Sgourakis, Nikolaos G; Liu, Gaohua; Rossi, Paolo; Tang, Yuefeng; Mills, Jeffrey L; Szyperski, Thomas; Montelione, Gaetano T; Baker, David

    2012-06-19

    While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 Å relative to the conventional determined NMR ensembles and of 0.9-1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.

  15. Performance of a reduced-order FSI model for flow-induced vocal fold vibration

    NASA Astrophysics Data System (ADS)

    Luo, Haoxiang; Chang, Siyuan; Chen, Ye; Rousseau, Bernard; PhonoSim Team

    2017-11-01

    Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which can be applied in procedures such as optimization and parameter estimation. In this work, we study performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model that is the same as in the full 3D model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin.

  16. Fast and Accurate Prediction of Numerical Relativity Waveforms from Binary Black Hole Coalescences Using Surrogate Models

    NASA Astrophysics Data System (ADS)

    Blackman, Jonathan; Field, Scott E.; Galley, Chad R.; Szilágyi, Béla; Scheel, Mark A.; Tiglio, Manuel; Hemberger, Daniel A.

    2015-09-01

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic -2Yℓm waveform modes resolved by the NR code up to ℓ=8 . We compare our surrogate model to effective one body waveforms from 50 M⊙ to 300 M⊙ for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).

  17. Fast and Accurate Prediction of Numerical Relativity Waveforms from Binary Black Hole Coalescences Using Surrogate Models.

    PubMed

    Blackman, Jonathan; Field, Scott E; Galley, Chad R; Szilágyi, Béla; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A

    2015-09-18

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _{-2}Y_{ℓm} waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M_{⊙} to 300M_{⊙} for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).

  18. Accurate modeling of the hose instability in plasma wakefield accelerators

    DOE PAGES

    Mehrling, T. J.; Benedetti, C.; Schroeder, C. B.; ...

    2018-05-20

    Hosing is a major challenge for the applicability of plasma wakefield accelerators and its modeling is therefore of fundamental importance to facilitate future stable and compact plasma-based particle accelerators. In this contribution, we present a new model for the evolution of the plasma centroid, which enables the accurate investigation of the hose instability in the nonlinear blowout regime. Lastly, it paves the road for more precise and comprehensive studies of hosing, e.g., with drive and witness beams, which were not possible with previous models.

  19. Accurate modeling of the hose instability in plasma wakefield accelerators

    NASA Astrophysics Data System (ADS)

    Mehrling, T. J.; Benedetti, C.; Schroeder, C. B.; Martinez de la Ossa, A.; Osterhoff, J.; Esarey, E.; Leemans, W. P.

    2018-05-01

    Hosing is a major challenge for the applicability of plasma wakefield accelerators and its modeling is therefore of fundamental importance to facilitate future stable and compact plasma-based particle accelerators. In this contribution, we present a new model for the evolution of the plasma centroid, which enables the accurate investigation of the hose instability in the nonlinear blowout regime. It paves the road for more precise and comprehensive studies of hosing, e.g., with drive and witness beams, which were not possible with previous models.

  20. Accurate modeling of the hose instability in plasma wakefield accelerators

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mehrling, T. J.; Benedetti, C.; Schroeder, C. B.

    Hosing is a major challenge for the applicability of plasma wakefield accelerators and its modeling is therefore of fundamental importance to facilitate future stable and compact plasma-based particle accelerators. In this contribution, we present a new model for the evolution of the plasma centroid, which enables the accurate investigation of the hose instability in the nonlinear blowout regime. Lastly, it paves the road for more precise and comprehensive studies of hosing, e.g., with drive and witness beams, which were not possible with previous models.

  1. Robust simulation of buckled structures using reduced order modeling

    NASA Astrophysics Data System (ADS)

    Wiebe, R.; Perez, R. A.; Spottswood, S. M.

    2016-09-01

    Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties.

  2. Accurate analytical modeling of junctionless DG-MOSFET by green's function approach

    NASA Astrophysics Data System (ADS)

    Nandi, Ashutosh; Pandey, Nilesh

    2017-11-01

    An accurate analytical model of Junctionless double gate MOSFET (JL-DG-MOSFET) in the subthreshold regime of operation is developed in this work using green's function approach. The approach considers 2-D mixed boundary conditions and multi-zone techniques to provide an exact analytical solution to 2-D Poisson's equation. The Fourier coefficients are calculated correctly to derive the potential equations that are further used to model the channel current and subthreshold slope of the device. The threshold voltage roll-off is computed from parallel shifts of Ids-Vgs curves between the long channel and short-channel devices. It is observed that the green's function approach of solving 2-D Poisson's equation in both oxide and silicon region can accurately predict channel potential, subthreshold current (Isub), threshold voltage (Vt) roll-off and subthreshold slope (SS) of both long & short channel devices designed with different doping concentrations and higher as well as lower tsi/tox ratio. All the analytical model results are verified through comparisons with TCAD Sentaurus simulation results. It is observed that the model matches quite well with TCAD device simulations.

  3. A new accurate quadratic equation model for isothermal gas chromatography and its comparison with the linear model

    PubMed Central

    Wu, Liejun; Chen, Maoxue; Chen, Yongli; Li, Qing X.

    2013-01-01

    The gas holdup time (tM) is a dominant parameter in gas chromatographic retention models. The difference equation (DE) model proposed by Wu et al. (J. Chromatogr. A 2012, http://dx.doi.org/10.1016/j.chroma.2012.07.077) excluded tM. In the present paper, we propose that the relationship between the adjusted retention time tRZ′ and carbon number z of n-alkanes follows a quadratic equation (QE) when an accurate tM is obtained. This QE model is the same as or better than the DE model for an accurate expression of the retention behavior of n-alkanes and model applications. The QE model covers a larger range of n-alkanes with better curve fittings than the linear model. The accuracy of the QE model was approximately 2–6 times better than the DE model and 18–540 times better than the LE model. Standard deviations of the QE model were approximately 2–3 times smaller than those of the DE model. PMID:22989489

  4. Calibration of Reduced Dynamic Models of Power Systems using Phasor Measurement Unit (PMU) Data

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhou, Ning; Lu, Shuai; Singh, Ruchi

    2011-09-23

    Accuracy of a power system dynamic model is essential to the secure and efficient operation of the system. Lower confidence on model accuracy usually leads to conservative operation and lowers asset usage. To improve model accuracy, identification algorithms have been developed to calibrate parameters of individual components using measurement data from staged tests. To facilitate online dynamic studies for large power system interconnections, this paper proposes a model reduction and calibration approach using phasor measurement unit (PMU) data. First, a model reduction method is used to reduce the number of dynamic components. Then, a calibration algorithm is developed to estimatemore » parameters of the reduced model. This approach will help to maintain an accurate dynamic model suitable for online dynamic studies. The performance of the proposed method is verified through simulation studies.« less

  5. Accurate monoenergetic electron parameters of laser wakefield in a bubble model

    NASA Astrophysics Data System (ADS)

    Raheli, A.; Rahmatallahpur, S. H.

    2012-11-01

    A reliable analytical expression for the potential of plasma waves with phase velocities near the speed of light is derived. The presented spheroid cavity model is more consistent than the previous spherical and ellipsoidal model and it explains the mono-energetic electron trajectory more accurately, especially at the relativistic region. As a result, the quasi-mono-energetic electrons output beam interacting with the laser plasma can be more appropriately described with this model.

  6. An Accurate Fire-Spread Algorithm in the Weather Research and Forecasting Model Using the Level-Set Method

    NASA Astrophysics Data System (ADS)

    Muñoz-Esparza, Domingo; Kosović, Branko; Jiménez, Pedro A.; Coen, Janice L.

    2018-04-01

    The level-set method is typically used to track and propagate the fire perimeter in wildland fire models. Herein, a high-order level-set method using fifth-order WENO scheme for the discretization of spatial derivatives and third-order explicit Runge-Kutta temporal integration is implemented within the Weather Research and Forecasting model wildland fire physics package, WRF-Fire. The algorithm includes solution of an additional partial differential equation for level-set reinitialization. The accuracy of the fire-front shape and rate of spread in uncoupled simulations is systematically analyzed. It is demonstrated that the common implementation used by level-set-based wildfire models yields to rate-of-spread errors in the range 10-35% for typical grid sizes (Δ = 12.5-100 m) and considerably underestimates fire area. Moreover, the amplitude of fire-front gradients in the presence of explicitly resolved turbulence features is systematically underestimated. In contrast, the new WRF-Fire algorithm results in rate-of-spread errors that are lower than 1% and that become nearly grid independent. Also, the underestimation of fire area at the sharp transition between the fire front and the lateral flanks is found to be reduced by a factor of ≈7. A hybrid-order level-set method with locally reduced artificial viscosity is proposed, which substantially alleviates the computational cost associated with high-order discretizations while preserving accuracy. Simulations of the Last Chance wildfire demonstrate additional benefits of high-order accurate level-set algorithms when dealing with complex fuel heterogeneities, enabling propagation across narrow fuel gaps and more accurate fire backing over the lee side of no fuel clusters.

  7. Hindered rotor models with variable kinetic functions for accurate thermodynamic and kinetic predictions

    NASA Astrophysics Data System (ADS)

    Reinisch, Guillaume; Leyssale, Jean-Marc; Vignoles, Gérard L.

    2010-10-01

    We present an extension of some popular hindered rotor (HR) models, namely, the one-dimensional HR (1DHR) and the degenerated two-dimensional HR (d2DHR) models, allowing for a simple and accurate treatment of internal rotations. This extension, based on the use of a variable kinetic function in the Hamiltonian instead of a constant reduced moment of inertia, is extremely suitable in the case of rocking/wagging motions involved in dissociation or atom transfer reactions. The variable kinetic function is first introduced in the framework of a classical 1DHR model. Then, an effective temperature and potential dependent constant is proposed in the cases of quantum 1DHR and classical d2DHR models. These methods are finally applied to the atom transfer reaction SiCl3+BCl3→SiCl4+BCl2. We show, for this particular case, that a proper accounting of internal rotations greatly improves the accuracy of thermodynamic and kinetic predictions. Moreover, our results confirm (i) that using a suitably defined kinetic function appears to be very adapted to such problems; (ii) that the separability assumption of independent rotations seems justified; and (iii) that a quantum mechanical treatment is not a substantial improvement with respect to a classical one.

  8. A pairwise maximum entropy model accurately describes resting-state human brain networks

    PubMed Central

    Watanabe, Takamitsu; Hirose, Satoshi; Wada, Hiroyuki; Imai, Yoshio; Machida, Toru; Shirouzu, Ichiro; Konishi, Seiki; Miyashita, Yasushi; Masuda, Naoki

    2013-01-01

    The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks. PMID:23340410

  9. De-embedding technique for accurate modeling of compact 3D MMIC CPW transmission lines

    NASA Astrophysics Data System (ADS)

    Pohan, U. H.; KKyabaggu, P. B.; Sinulingga, E. P.

    2018-02-01

    Requirement for high-density and high-functionality microwave and millimeter-wave circuits have led to the innovative circuit architectures such as three-dimensional multilayer MMICs. The major advantage of the multilayer techniques is that one can employ passive and active components based on CPW technology. In this work, MMIC Coplanar Waveguide(CPW)components such as Transmission Line (TL) are modeled in their 3D layouts. Main characteristics of CPWTL suffered from the probe pads’ parasitic and resonant frequency effects have been studied. By understanding the parasitic effects, then the novel de-embedding technique are developed accurately in order to predict high frequency characteristics of the designed MMICs. The novel de-embedding technique has shown to be critical in reducing the probe pad parasitic significantly from the model. As results, high frequency characteristics of the designed MMICs have been presented with minimumparasitic effects of the probe pads. The de-embedding process optimises the determination of main characteristics of Compact 3D MMIC CPW transmission lines.

  10. A reduced-form intensity-based model under fuzzy environments

    NASA Astrophysics Data System (ADS)

    Wu, Liang; Zhuang, Yaming

    2015-05-01

    The external shocks and internal contagion are the important sources of default events. However, the external shocks and internal contagion effect on the company is not observed, we cannot get the accurate size of the shocks. The information of investors relative to the default process exhibits a certain fuzziness. Therefore, using randomness and fuzziness to study such problems as derivative pricing or default probability has practical needs. But the idea of fuzzifying credit risk models is little exploited, especially in a reduced-form model. This paper proposes a new default intensity model with fuzziness and presents a fuzzy default probability and default loss rate, and puts them into default debt and credit derivative pricing. Finally, the simulation analysis verifies the rationality of the model. Using fuzzy numbers and random analysis one can consider more uncertain sources in the default process of default and investors' subjective judgment on the financial markets in a variety of fuzzy reliability so as to broaden the scope of possible credit spreads.

  11. A scalable and accurate method for classifying protein-ligand binding geometries using a MapReduce approach.

    PubMed

    Estrada, T; Zhang, B; Cicotti, P; Armen, R S; Taufer, M

    2012-07-01

    We present a scalable and accurate method for classifying protein-ligand binding geometries in molecular docking. Our method is a three-step process: the first step encodes the geometry of a three-dimensional (3D) ligand conformation into a single 3D point in the space; the second step builds an octree by assigning an octant identifier to every single point in the space under consideration; and the third step performs an octree-based clustering on the reduced conformation space and identifies the most dense octant. We adapt our method for MapReduce and implement it in Hadoop. The load-balancing, fault-tolerance, and scalability in MapReduce allow screening of very large conformation spaces not approachable with traditional clustering methods. We analyze results for docking trials for 23 protein-ligand complexes for HIV protease, 21 protein-ligand complexes for Trypsin, and 12 protein-ligand complexes for P38alpha kinase. We also analyze cross docking trials for 24 ligands, each docking into 24 protein conformations of the HIV protease, and receptor ensemble docking trials for 24 ligands, each docking in a pool of HIV protease receptors. Our method demonstrates significant improvement over energy-only scoring for the accurate identification of native ligand geometries in all these docking assessments. The advantages of our clustering approach make it attractive for complex applications in real-world drug design efforts. We demonstrate that our method is particularly useful for clustering docking results using a minimal ensemble of representative protein conformational states (receptor ensemble docking), which is now a common strategy to address protein flexibility in molecular docking. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Accurate, low-cost 3D-models of gullies

    NASA Astrophysics Data System (ADS)

    Onnen, Nils; Gronz, Oliver; Ries, Johannes B.; Brings, Christine

    2015-04-01

    Soil erosion is a widespread problem in arid and semi-arid areas. The most severe form is the gully erosion. They often cut into agricultural farmland and can make a certain area completely unproductive. To understand the development and processes inside and around gullies, we calculated detailed 3D-models of gullies in the Souss Valley in South Morocco. Near Taroudant, we had four study areas with five gullies different in size, volume and activity. By using a Canon HF G30 Camcorder, we made varying series of Full HD videos with 25fps. Afterwards, we used the method Structure from Motion (SfM) to create the models. To generate accurate models maintaining feasible runtimes, it is necessary to select around 1500-1700 images from the video, while the overlap of neighboring images should be at least 80%. In addition, it is very important to avoid selecting photos that are blurry or out of focus. Nearby pixels of a blurry image tend to have similar color values. That is why we used a MATLAB script to compare the derivatives of the images. The higher the sum of the derivative, the sharper an image of similar objects. MATLAB subdivides the video into image intervals. From each interval, the image with the highest sum is selected. E.g.: 20min. video at 25fps equals 30.000 single images. The program now inspects the first 20 images, saves the sharpest and moves on to the next 20 images etc. Using this algorithm, we selected 1500 images for our modeling. With VisualSFM, we calculated features and the matches between all images and produced a point cloud. Then, MeshLab has been used to build a surface out of it using the Poisson surface reconstruction approach. Afterwards we are able to calculate the size and the volume of the gullies. It is also possible to determine soil erosion rates, if we compare the data with old recordings. The final step would be the combination of the terrestrial data with the data from our aerial photography. So far, the method works well and we

  13. An Accurate Absorption-Based Net Primary Production Model for the Global Ocean

    NASA Astrophysics Data System (ADS)

    Silsbe, G.; Westberry, T. K.; Behrenfeld, M. J.; Halsey, K.; Milligan, A.

    2016-02-01

    As a vital living link in the global carbon cycle, understanding how net primary production (NPP) varies through space, time, and across climatic oscillations (e.g. ENSO) is a key objective in oceanographic research. The continual improvement of ocean observing satellites and data analytics now present greater opportunities for advanced understanding and characterization of the factors regulating NPP. In particular, the emergence of spectral inversion algorithms now permits accurate retrievals of the phytoplankton absorption coefficient (aΦ) from space. As NPP is the efficiency in which absorbed energy is converted into carbon biomass, aΦ measurements circumvents chlorophyll-based empirical approaches by permitting direct and accurate measurements of phytoplankton energy absorption. It has long been recognized, and perhaps underappreciated, that NPP and phytoplankton growth rates display muted variability when normalized to aΦ rather than chlorophyll. Here we present a novel absorption-based NPP model that parameterizes the underlying physiological mechanisms behind this muted variability, and apply this physiological model to the global ocean. Through a comparison against field data from the Hawaii and Bermuda Ocean Time Series, we demonstrate how this approach yields more accurate NPP measurements than other published NPP models. By normalizing NPP to satellite estimates of phytoplankton carbon biomass, this presentation also explores the seasonality of phytoplankton growth rates across several oceanic regions. Finally, we discuss how future advances in remote-sensing (e.g. hyperspectral satellites, LIDAR, autonomous profilers) can be exploited to further improve absorption-based NPP models.

  14. A Biomechanical Model of the Scapulothoracic Joint to Accurately Capture Scapular Kinematics during Shoulder Movements

    PubMed Central

    Seth, Ajay; Matias, Ricardo; Veloso, António P.; Delp, Scott L.

    2016-01-01

    The complexity of shoulder mechanics combined with the movement of skin relative to the scapula makes it difficult to measure shoulder kinematics with sufficient accuracy to distinguish between symptomatic and asymptomatic individuals. Multibody skeletal models can improve motion capture accuracy by reducing the space of possible joint movements, and models are used widely to improve measurement of lower limb kinematics. In this study, we developed a rigid-body model of a scapulothoracic joint to describe the kinematics of the scapula relative to the thorax. This model describes scapular kinematics with four degrees of freedom: 1) elevation and 2) abduction of the scapula on an ellipsoidal thoracic surface, 3) upward rotation of the scapula normal to the thoracic surface, and 4) internal rotation of the scapula to lift the medial border of the scapula off the surface of the thorax. The surface dimensions and joint axes can be customized to match an individual’s anthropometry. We compared the model to “gold standard” bone-pin kinematics collected during three shoulder tasks and found modeled scapular kinematics to be accurate to within 2mm root-mean-squared error for individual bone-pin markers across all markers and movement tasks. As an additional test, we added random and systematic noise to the bone-pin marker data and found that the model reduced kinematic variability due to noise by 65% compared to Euler angles computed without the model. Our scapulothoracic joint model can be used for inverse and forward dynamics analyses and to compute joint reaction loads. The computational performance of the scapulothoracic joint model is well suited for real-time applications; it is freely available for use with OpenSim 3.2, and is customizable and usable with other OpenSim models. PMID:26734761

  15. A Biomechanical Model of the Scapulothoracic Joint to Accurately Capture Scapular Kinematics during Shoulder Movements.

    PubMed

    Seth, Ajay; Matias, Ricardo; Veloso, António P; Delp, Scott L

    2016-01-01

    The complexity of shoulder mechanics combined with the movement of skin relative to the scapula makes it difficult to measure shoulder kinematics with sufficient accuracy to distinguish between symptomatic and asymptomatic individuals. Multibody skeletal models can improve motion capture accuracy by reducing the space of possible joint movements, and models are used widely to improve measurement of lower limb kinematics. In this study, we developed a rigid-body model of a scapulothoracic joint to describe the kinematics of the scapula relative to the thorax. This model describes scapular kinematics with four degrees of freedom: 1) elevation and 2) abduction of the scapula on an ellipsoidal thoracic surface, 3) upward rotation of the scapula normal to the thoracic surface, and 4) internal rotation of the scapula to lift the medial border of the scapula off the surface of the thorax. The surface dimensions and joint axes can be customized to match an individual's anthropometry. We compared the model to "gold standard" bone-pin kinematics collected during three shoulder tasks and found modeled scapular kinematics to be accurate to within 2 mm root-mean-squared error for individual bone-pin markers across all markers and movement tasks. As an additional test, we added random and systematic noise to the bone-pin marker data and found that the model reduced kinematic variability due to noise by 65% compared to Euler angles computed without the model. Our scapulothoracic joint model can be used for inverse and forward dynamics analyses and to compute joint reaction loads. The computational performance of the scapulothoracic joint model is well suited for real-time applications; it is freely available for use with OpenSim 3.2, and is customizable and usable with other OpenSim models.

  16. Technical Note: Using experimentally determined proton spot scanning timing parameters to accurately model beam delivery time.

    PubMed

    Shen, Jiajian; Tryggestad, Erik; Younkin, James E; Keole, Sameer R; Furutani, Keith M; Kang, Yixiu; Herman, Michael G; Bues, Martin

    2017-10-01

    To accurately model the beam delivery time (BDT) for a synchrotron-based proton spot scanning system using experimentally determined beam parameters. A model to simulate the proton spot delivery sequences was constructed, and BDT was calculated by summing times for layer switch, spot switch, and spot delivery. Test plans were designed to isolate and quantify the relevant beam parameters in the operation cycle of the proton beam therapy delivery system. These parameters included the layer switch time, magnet preparation and verification time, average beam scanning speeds in x- and y-directions, proton spill rate, and maximum charge and maximum extraction time for each spill. The experimentally determined parameters, as well as the nominal values initially provided by the vendor, served as inputs to the model to predict BDTs for 602 clinical proton beam deliveries. The calculated BDTs (T BDT ) were compared with the BDTs recorded in the treatment delivery log files (T Log ): ∆t = T Log -T BDT . The experimentally determined average layer switch time for all 97 energies was 1.91 s (ranging from 1.9 to 2.0 s for beam energies from 71.3 to 228.8 MeV), average magnet preparation and verification time was 1.93 ms, the average scanning speeds were 5.9 m/s in x-direction and 19.3 m/s in y-direction, the proton spill rate was 8.7 MU/s, and the maximum proton charge available for one acceleration is 2.0 ± 0.4 nC. Some of the measured parameters differed from the nominal values provided by the vendor. The calculated BDTs using experimentally determined parameters matched the recorded BDTs of 602 beam deliveries (∆t = -0.49 ± 1.44 s), which were significantly more accurate than BDTs calculated using nominal timing parameters (∆t = -7.48 ± 6.97 s). An accurate model for BDT prediction was achieved by using the experimentally determined proton beam therapy delivery parameters, which may be useful in modeling the interplay effect and patient throughput. The model may

  17. Reduced cost mission design using surrogate models

    NASA Astrophysics Data System (ADS)

    Feldhacker, Juliana D.; Jones, Brandon A.; Doostan, Alireza; Hampton, Jerrad

    2016-01-01

    This paper uses surrogate models to reduce the computational cost associated with spacecraft mission design in three-body dynamical systems. Sampling-based least squares regression is used to project the system response onto a set of orthogonal bases, providing a representation of the ΔV required for rendezvous as a reduced-order surrogate model. Models are presented for mid-field rendezvous of spacecraft in orbits in the Earth-Moon circular restricted three-body problem, including a halo orbit about the Earth-Moon L2 libration point (EML-2) and a distant retrograde orbit (DRO) about the Moon. In each case, the initial position of the spacecraft, the time of flight, and the separation between the chaser and the target vehicles are all considered as design inputs. The results show that sample sizes on the order of 102 are sufficient to produce accurate surrogates, with RMS errors reaching 0.2 m/s for the halo orbit and falling below 0.01 m/s for the DRO. A single function call to the resulting surrogate is up to two orders of magnitude faster than computing the same solution using full fidelity propagators. The expansion coefficients solved for in the surrogates are then used to conduct a global sensitivity analysis of the ΔV on each of the input parameters, which identifies the separation between the spacecraft as the primary contributor to the ΔV cost. Finally, the models are demonstrated to be useful for cheap evaluation of the cost function in constrained optimization problems seeking to minimize the ΔV required for rendezvous. These surrogate models show significant advantages for mission design in three-body systems, in terms of both computational cost and capabilities, over traditional Monte Carlo methods.

  18. Accurate pressure gradient calculations in hydrostatic atmospheric models

    NASA Technical Reports Server (NTRS)

    Carroll, John J.; Mendez-Nunez, Luis R.; Tanrikulu, Saffet

    1987-01-01

    A method for the accurate calculation of the horizontal pressure gradient acceleration in hydrostatic atmospheric models is presented which is especially useful in situations where the isothermal surfaces are not parallel to the vertical coordinate surfaces. The present method is shown to be exact if the potential temperature lapse rate is constant between the vertical pressure integration limits. The technique is applied to both the integration of the hydrostatic equation and the computation of the slope correction term in the horizontal pressure gradient. A fixed vertical grid and a dynamic grid defined by the significant levels in the vertical temperature distribution are employed.

  19. An analytic model for accurate spring constant calibration of rectangular atomic force microscope cantilevers.

    PubMed

    Li, Rui; Ye, Hongfei; Zhang, Weisheng; Ma, Guojun; Su, Yewang

    2015-10-29

    Spring constant calibration of the atomic force microscope (AFM) cantilever is of fundamental importance for quantifying the force between the AFM cantilever tip and the sample. The calibration within the framework of thin plate theory undoubtedly has a higher accuracy and broader scope than that within the well-established beam theory. However, thin plate theory-based accurate analytic determination of the constant has been perceived as an extremely difficult issue. In this paper, we implement the thin plate theory-based analytic modeling for the static behavior of rectangular AFM cantilevers, which reveals that the three-dimensional effect and Poisson effect play important roles in accurate determination of the spring constants. A quantitative scaling law is found that the normalized spring constant depends only on the Poisson's ratio, normalized dimension and normalized load coordinate. Both the literature and our refined finite element model validate the present results. The developed model is expected to serve as the benchmark for accurate calibration of rectangular AFM cantilevers.

  20. Reduced-order modeling for hyperthermia: an extended balanced-realization-based approach.

    PubMed

    Mattingly, M; Bailey, E A; Dutton, A W; Roemer, R B; Devasia, S

    1998-09-01

    Accurate thermal models are needed in hyperthermia cancer treatments for such tasks as actuator and sensor placement design, parameter estimation, and feedback temperature control. The complexity of the human body produces full-order models which are too large for effective execution of these tasks, making use of reduced-order models necessary. However, standard balanced-realization (SBR)-based model reduction techniques require a priori knowledge of the particular placement of actuators and sensors for model reduction. Since placement design is intractable (computationally) on the full-order models, SBR techniques must use ad hoc placements. To alleviate this problem, an extended balanced-realization (EBR)-based model-order reduction approach is presented. The new technique allows model order reduction to be performed over all possible placement designs and does not require ad hoc placement designs. It is shown that models obtained using the EBR method are more robust to intratreatment changes in the placement of the applied power field than those models obtained using the SBR method.

  1. A Multiscale Red Blood Cell Model with Accurate Mechanics, Rheology, and Dynamics

    PubMed Central

    Fedosov, Dmitry A.; Caswell, Bruce; Karniadakis, George Em

    2010-01-01

    Abstract Red blood cells (RBCs) have highly deformable viscoelastic membranes exhibiting complex rheological response and rich hydrodynamic behavior governed by special elastic and bending properties and by the external/internal fluid and membrane viscosities. We present a multiscale RBC model that is able to predict RBC mechanics, rheology, and dynamics in agreement with experiments. Based on an analytic theory, the modeled membrane properties can be uniquely related to the experimentally established RBC macroscopic properties without any adjustment of parameters. The RBC linear and nonlinear elastic deformations match those obtained in optical-tweezers experiments. The rheological properties of the membrane are compared with those obtained in optical magnetic twisting cytometry, membrane thermal fluctuations, and creep followed by cell recovery. The dynamics of RBCs in shear and Poiseuille flows is tested against experiments and theoretical predictions, and the applicability of the latter is discussed. Our findings clearly indicate that a purely elastic model for the membrane cannot accurately represent the RBC's rheological properties and its dynamics, and therefore accurate modeling of a viscoelastic membrane is necessary. PMID:20483330

  2. A dental vision system for accurate 3D tooth modeling.

    PubMed

    Zhang, Li; Alemzadeh, K

    2006-01-01

    This paper describes an active vision system based reverse engineering approach to extract the three-dimensional (3D) geometric information from dental teeth and transfer this information into Computer-Aided Design/Computer-Aided Manufacture (CAD/CAM) systems to improve the accuracy of 3D teeth models and at the same time improve the quality of the construction units to help patient care. The vision system involves the development of a dental vision rig, edge detection, boundary tracing and fast & accurate 3D modeling from a sequence of sliced silhouettes of physical models. The rig is designed using engineering design methods such as a concept selection matrix and weighted objectives evaluation chart. Reconstruction results and accuracy evaluation are presented on digitizing different teeth models.

  3. Novel parametric reduced order model for aeroengine blade dynamics

    NASA Astrophysics Data System (ADS)

    Yuan, Jie; Allegri, Giuliano; Scarpa, Fabrizio; Rajasekaran, Ramesh; Patsias, Sophoclis

    2015-10-01

    The work introduces a novel reduced order model (ROM) technique to describe the dynamic behavior of turbofan aeroengine blades. We introduce an equivalent 3D frame model to describe the coupled flexural/torsional mode shapes, with their relevant natural frequencies and associated modal masses. The frame configurations are identified through a structural identification approach based on a simulated annealing algorithm with stochastic tunneling. The cost functions are constituted by linear combinations of relative errors associated to the resonance frequencies, the individual modal assurance criteria (MAC), and on either overall static or modal masses. When static masses are considered the optimized 3D frame can represent the blade dynamic behavior with an 8% error on the MAC, a 1% error on the associated modal frequencies and a 1% error on the overall static mass. When using modal masses in the cost function the performance of the ROM is similar, but the overall error increases to 7%. The approach proposed in this paper is considerably more accurate than state-of-the-art blade ROMs based on traditional Timoshenko beams, and provides excellent accuracy at reduced computational time when compared against high fidelity FE models. A sensitivity analysis shows that the proposed model can adequately predict the global trends of the variations of the natural frequencies when lumped masses are used for mistuning analysis. The proposed ROM also follows extremely closely the sensitivity of the high fidelity finite element models when the material parameters are used in the sensitivity.

  4. Filtering Raw Terrestrial Laser Scanning Data for Efficient and Accurate Use in Geomorphologic Modeling

    NASA Astrophysics Data System (ADS)

    Gleason, M. J.; Pitlick, J.; Buttenfield, B. P.

    2011-12-01

    Terrestrial laser scanning (TLS) represents a new and particularly effective remote sensing technique for investigating geomorphologic processes. Unfortunately, TLS data are commonly characterized by extremely large volume, heterogeneous point distribution, and erroneous measurements, raising challenges for applied researchers. To facilitate efficient and accurate use of TLS in geomorphology, and to improve accessibility for TLS processing in commercial software environments, we are developing a filtering method for raw TLS data to: eliminate data redundancy; produce a more uniformly spaced dataset; remove erroneous measurements; and maintain the ability of the TLS dataset to accurately model terrain. Our method conducts local aggregation of raw TLS data using a 3-D search algorithm based on the geometrical expression of expected random errors in the data. This approach accounts for the estimated accuracy and precision limitations of the instruments and procedures used in data collection, thereby allowing for identification and removal of potential erroneous measurements prior to data aggregation. Initial tests of the proposed technique on a sample TLS point cloud required a modest processing time of approximately 100 minutes to reduce dataset volume over 90 percent (from 12,380,074 to 1,145,705 points). Preliminary analysis of the filtered point cloud revealed substantial improvement in homogeneity of point distribution and minimal degradation of derived terrain models. We will test the method on two independent TLS datasets collected in consecutive years along a non-vegetated reach of the North Fork Toutle River in Washington. We will evaluate the tool using various quantitative, qualitative, and statistical methods. The crux of this evaluation will include a bootstrapping analysis to test the ability of the filtered datasets to model the terrain at roughly the same accuracy as the raw datasets.

  5. Towards Accurate Modelling of Galaxy Clustering on Small Scales: Testing the Standard ΛCDM + Halo Model

    NASA Astrophysics Data System (ADS)

    Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron K.; Scoccimarro, Roman; Piscionere, Jennifer A.; Wibking, Benjamin D.

    2018-04-01

    Interpreting the small-scale clustering of galaxies with halo models can elucidate the connection between galaxies and dark matter halos. Unfortunately, the modelling is typically not sufficiently accurate for ruling out models statistically. It is thus difficult to use the information encoded in small scales to test cosmological models or probe subtle features of the galaxy-halo connection. In this paper, we attempt to push halo modelling into the "accurate" regime with a fully numerical mock-based methodology and careful treatment of statistical and systematic errors. With our forward-modelling approach, we can incorporate clustering statistics beyond the traditional two-point statistics. We use this modelling methodology to test the standard ΛCDM + halo model against the clustering of SDSS DR7 galaxies. Specifically, we use the projected correlation function, group multiplicity function and galaxy number density as constraints. We find that while the model fits each statistic separately, it struggles to fit them simultaneously. Adding group statistics leads to a more stringent test of the model and significantly tighter constraints on model parameters. We explore the impact of varying the adopted halo definition and cosmological model and find that changing the cosmology makes a significant difference. The most successful model we tried (Planck cosmology with Mvir halos) matches the clustering of low luminosity galaxies, but exhibits a 2.3σ tension with the clustering of luminous galaxies, thus providing evidence that the "standard" halo model needs to be extended. This work opens the door to adding interesting freedom to the halo model and including additional clustering statistics as constraints.

  6. Adaptive h -refinement for reduced-order models: ADAPTIVE h -refinement for reduced-order models

    DOE PAGES

    Carlberg, Kevin T.

    2014-11-05

    Our work presents a method to adaptively refine reduced-order models a posteriori without requiring additional full-order-model solves. The technique is analogous to mesh-adaptive h-refinement: it enriches the reduced-basis space online by ‘splitting’ a given basis vector into several vectors with disjoint support. The splitting scheme is defined by a tree structure constructed offline via recursive k-means clustering of the state variables using snapshot data. This method identifies the vectors to split online using a dual-weighted-residual approach that aims to reduce error in an output quantity of interest. The resulting method generates a hierarchy of subspaces online without requiring large-scale operationsmore » or full-order-model solves. Furthermore, it enables the reduced-order model to satisfy any prescribed error tolerance regardless of its original fidelity, as a completely refined reduced-order model is mathematically equivalent to the original full-order model. Experiments on a parameterized inviscid Burgers equation highlight the ability of the method to capture phenomena (e.g., moving shocks) not contained in the span of the original reduced basis.« less

  7. Accurate modeling of high-repetition rate ultrashort pulse amplification in optical fibers

    PubMed Central

    Lindberg, Robert; Zeil, Peter; Malmström, Mikael; Laurell, Fredrik; Pasiskevicius, Valdas

    2016-01-01

    A numerical model for amplification of ultrashort pulses with high repetition rates in fiber amplifiers is presented. The pulse propagation is modeled by jointly solving the steady-state rate equations and the generalized nonlinear Schrödinger equation, which allows accurate treatment of nonlinear and dispersive effects whilst considering arbitrary spatial and spectral gain dependencies. Comparison of data acquired by using the developed model and experimental results prove to be in good agreement. PMID:27713496

  8. Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter

    PubMed Central

    Chowdhury, Amor; Sarjaš, Andrej

    2016-01-01

    The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation. PMID:27649197

  9. Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter.

    PubMed

    Chowdhury, Amor; Sarjaš, Andrej

    2016-09-15

    The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation.

  10. Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models.

    PubMed

    Shah, A A; Xing, W W; Triantafyllidis, V

    2017-04-01

    In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.

  11. Modeling respiratory motion for reducing motion artifacts in 4D CT images.

    PubMed

    Zhang, Yongbin; Yang, Jinzhong; Zhang, Lifei; Court, Laurence E; Balter, Peter A; Dong, Lei

    2013-04-01

    Four-dimensional computed tomography (4D CT) images have been recently adopted in radiation treatment planning for thoracic and abdominal cancers to explicitly define respiratory motion and anatomy deformation. However, significant image distortions (artifacts) exist in 4D CT images that may affect accurate tumor delineation and the shape representation of normal anatomy. In this study, the authors present a patient-specific respiratory motion model, based on principal component analysis (PCA) of motion vectors obtained from deformable image registration, with the main goal of reducing image artifacts caused by irregular motion during 4D CT acquisition. For a 4D CT image set of a specific patient, the authors calculated displacement vector fields relative to a reference phase, using an in-house deformable image registration method. The authors then used PCA to decompose each of the displacement vector fields into linear combinations of principal motion bases. The authors have demonstrated that the regular respiratory motion of a patient can be accurately represented by a subspace spanned by three principal motion bases and their projections. These projections were parameterized using a spline model to allow the reconstruction of the displacement vector fields at any given phase in a respiratory cycle. Finally, the displacement vector fields were used to deform the reference CT image to synthesize CT images at the selected phase with much reduced image artifacts. The authors evaluated the performance of the in-house deformable image registration method using benchmark datasets consisting of ten 4D CT sets annotated with 300 landmark pairs that were approved by physicians. The initial large discrepancies across the landmark pairs were significantly reduced after deformable registration, and the accuracy was similar to or better than that reported by state-of-the-art methods. The proposed motion model was quantitatively validated on 4D CT images of a phantom and a

  12. Continuous piecewise-linear, reduced-order electrochemical model for lithium-ion batteries in real-time applications

    NASA Astrophysics Data System (ADS)

    Farag, Mohammed; Fleckenstein, Matthias; Habibi, Saeid

    2017-02-01

    Model-order reduction and minimization of the CPU run-time while maintaining the model accuracy are critical requirements for real-time implementation of lithium-ion electrochemical battery models. In this paper, an isothermal, continuous, piecewise-linear, electrode-average model is developed by using an optimal knot placement technique. The proposed model reduces the univariate nonlinear function of the electrode's open circuit potential dependence on the state of charge to continuous piecewise regions. The parameterization experiments were chosen to provide a trade-off between extensive experimental characterization techniques and purely identifying all parameters using optimization techniques. The model is then parameterized in each continuous, piecewise-linear, region. Applying the proposed technique cuts down the CPU run-time by around 20%, compared to the reduced-order, electrode-average model. Finally, the model validation against real-time driving profiles (FTP-72, WLTP) demonstrates the ability of the model to predict the cell voltage accurately with less than 2% error.

  13. Accurate modeling and evaluation of microstructures in complex materials

    NASA Astrophysics Data System (ADS)

    Tahmasebi, Pejman

    2018-02-01

    Accurate characterization of heterogeneous materials is of great importance for different fields of science and engineering. Such a goal can be achieved through imaging. Acquiring three- or two-dimensional images under different conditions is not, however, always plausible. On the other hand, accurate characterization of complex and multiphase materials requires various digital images (I) under different conditions. An ensemble method is presented that can take one single (or a set of) I(s) and stochastically produce several similar models of the given disordered material. The method is based on a successive calculating of a conditional probability by which the initial stochastic models are produced. Then, a graph formulation is utilized for removing unrealistic structures. A distance transform function for the Is with highly connected microstructure and long-range features is considered which results in a new I that is more informative. Reproduction of the I is also considered through a histogram matching approach in an iterative framework. Such an iterative algorithm avoids reproduction of unrealistic structures. Furthermore, a multiscale approach, based on pyramid representation of the large Is, is presented that can produce materials with millions of pixels in a matter of seconds. Finally, the nonstationary systems—those for which the distribution of data varies spatially—are studied using two different methods. The method is tested on several complex and large examples of microstructures. The produced results are all in excellent agreement with the utilized Is and the similarities are quantified using various correlation functions.

  14. Towards accurate modelling of galaxy clustering on small scales: testing the standard ΛCDM + halo model

    NASA Astrophysics Data System (ADS)

    Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron K.; Scoccimarro, Roman; Piscionere, Jennifer A.; Wibking, Benjamin D.

    2018-07-01

    Interpreting the small-scale clustering of galaxies with halo models can elucidate the connection between galaxies and dark matter haloes. Unfortunately, the modelling is typically not sufficiently accurate for ruling out models statistically. It is thus difficult to use the information encoded in small scales to test cosmological models or probe subtle features of the galaxy-halo connection. In this paper, we attempt to push halo modelling into the `accurate' regime with a fully numerical mock-based methodology and careful treatment of statistical and systematic errors. With our forward-modelling approach, we can incorporate clustering statistics beyond the traditional two-point statistics. We use this modelling methodology to test the standard Λ cold dark matter (ΛCDM) + halo model against the clustering of Sloan Digital Sky Survey (SDSS) seventh data release (DR7) galaxies. Specifically, we use the projected correlation function, group multiplicity function, and galaxy number density as constraints. We find that while the model fits each statistic separately, it struggles to fit them simultaneously. Adding group statistics leads to a more stringent test of the model and significantly tighter constraints on model parameters. We explore the impact of varying the adopted halo definition and cosmological model and find that changing the cosmology makes a significant difference. The most successful model we tried (Planck cosmology with Mvir haloes) matches the clustering of low-luminosity galaxies, but exhibits a 2.3σ tension with the clustering of luminous galaxies, thus providing evidence that the `standard' halo model needs to be extended. This work opens the door to adding interesting freedom to the halo model and including additional clustering statistics as constraints.

  15. A multiscale red blood cell model with accurate mechanics, rheology, and dynamics.

    PubMed

    Fedosov, Dmitry A; Caswell, Bruce; Karniadakis, George Em

    2010-05-19

    Red blood cells (RBCs) have highly deformable viscoelastic membranes exhibiting complex rheological response and rich hydrodynamic behavior governed by special elastic and bending properties and by the external/internal fluid and membrane viscosities. We present a multiscale RBC model that is able to predict RBC mechanics, rheology, and dynamics in agreement with experiments. Based on an analytic theory, the modeled membrane properties can be uniquely related to the experimentally established RBC macroscopic properties without any adjustment of parameters. The RBC linear and nonlinear elastic deformations match those obtained in optical-tweezers experiments. The rheological properties of the membrane are compared with those obtained in optical magnetic twisting cytometry, membrane thermal fluctuations, and creep followed by cell recovery. The dynamics of RBCs in shear and Poiseuille flows is tested against experiments and theoretical predictions, and the applicability of the latter is discussed. Our findings clearly indicate that a purely elastic model for the membrane cannot accurately represent the RBC's rheological properties and its dynamics, and therefore accurate modeling of a viscoelastic membrane is necessary. Copyright 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  16. Non-intrusive reduced order modeling of nonlinear problems using neural networks

    NASA Astrophysics Data System (ADS)

    Hesthaven, J. S.; Ubbiali, S.

    2018-06-01

    We develop a non-intrusive reduced basis (RB) method for parametrized steady-state partial differential equations (PDEs). The method extracts a reduced basis from a collection of high-fidelity solutions via a proper orthogonal decomposition (POD) and employs artificial neural networks (ANNs), particularly multi-layer perceptrons (MLPs), to accurately approximate the coefficients of the reduced model. The search for the optimal number of neurons and the minimum amount of training samples to avoid overfitting is carried out in the offline phase through an automatic routine, relying upon a joint use of the Latin hypercube sampling (LHS) and the Levenberg-Marquardt (LM) training algorithm. This guarantees a complete offline-online decoupling, leading to an efficient RB method - referred to as POD-NN - suitable also for general nonlinear problems with a non-affine parametric dependence. Numerical studies are presented for the nonlinear Poisson equation and for driven cavity viscous flows, modeled through the steady incompressible Navier-Stokes equations. Both physical and geometrical parametrizations are considered. Several results confirm the accuracy of the POD-NN method and show the substantial speed-up enabled at the online stage as compared to a traditional RB strategy.

  17. Beyond mean-field approximations for accurate and computationally efficient models of on-lattice chemical kinetics

    NASA Astrophysics Data System (ADS)

    Pineda, M.; Stamatakis, M.

    2017-07-01

    Modeling the kinetics of surface catalyzed reactions is essential for the design of reactors and chemical processes. The majority of microkinetic models employ mean-field approximations, which lead to an approximate description of catalytic kinetics by assuming spatially uncorrelated adsorbates. On the other hand, kinetic Monte Carlo (KMC) methods provide a discrete-space continuous-time stochastic formulation that enables an accurate treatment of spatial correlations in the adlayer, but at a significant computation cost. In this work, we use the so-called cluster mean-field approach to develop higher order approximations that systematically increase the accuracy of kinetic models by treating spatial correlations at a progressively higher level of detail. We further demonstrate our approach on a reduced model for NO oxidation incorporating first nearest-neighbor lateral interactions and construct a sequence of approximations of increasingly higher accuracy, which we compare with KMC and mean-field. The latter is found to perform rather poorly, overestimating the turnover frequency by several orders of magnitude for this system. On the other hand, our approximations, while more computationally intense than the traditional mean-field treatment, still achieve tremendous computational savings compared to KMC simulations, thereby opening the way for employing them in multiscale modeling frameworks.

  18. Accurate Energy Consumption Modeling of IEEE 802.15.4e TSCH Using Dual-BandOpenMote Hardware.

    PubMed

    Daneels, Glenn; Municio, Esteban; Van de Velde, Bruno; Ergeerts, Glenn; Weyn, Maarten; Latré, Steven; Famaey, Jeroen

    2018-02-02

    The Time-Slotted Channel Hopping (TSCH) mode of the IEEE 802.15.4e amendment aims to improve reliability and energy efficiency in industrial and other challenging Internet-of-Things (IoT) environments. This paper presents an accurate and up-to-date energy consumption model for devices using this IEEE 802.15.4e TSCH mode. The model identifies all network-related CPU and radio state changes, thus providing a precise representation of the device behavior and an accurate prediction of its energy consumption. Moreover, energy measurements were performed with a dual-band OpenMote device, running the OpenWSN firmware. This allows the model to be used for devices using 2.4 GHz, as well as 868 MHz. Using these measurements, several network simulations were conducted to observe the TSCH energy consumption effects in end-to-end communication for both frequency bands. Experimental verification of the model shows that it accurately models the consumption for all possible packet sizes and that the calculated consumption on average differs less than 3% from the measured consumption. This deviation includes measurement inaccuracies and the variations of the guard time. As such, the proposed model is very suitable for accurate energy consumption modeling of TSCH networks.

  19. Accurate Energy Consumption Modeling of IEEE 802.15.4e TSCH Using Dual-BandOpenMote Hardware

    PubMed Central

    Municio, Esteban; Van de Velde, Bruno; Latré, Steven

    2018-01-01

    The Time-Slotted Channel Hopping (TSCH) mode of the IEEE 802.15.4e amendment aims to improve reliability and energy efficiency in industrial and other challenging Internet-of-Things (IoT) environments. This paper presents an accurate and up-to-date energy consumption model for devices using this IEEE 802.15.4e TSCH mode. The model identifies all network-related CPU and radio state changes, thus providing a precise representation of the device behavior and an accurate prediction of its energy consumption. Moreover, energy measurements were performed with a dual-band OpenMote device, running the OpenWSN firmware. This allows the model to be used for devices using 2.4 GHz, as well as 868 MHz. Using these measurements, several network simulations were conducted to observe the TSCH energy consumption effects in end-to-end communication for both frequency bands. Experimental verification of the model shows that it accurately models the consumption for all possible packet sizes and that the calculated consumption on average differs less than 3% from the measured consumption. This deviation includes measurement inaccuracies and the variations of the guard time. As such, the proposed model is very suitable for accurate energy consumption modeling of TSCH networks. PMID:29393900

  20. Male body dissatisfaction scale (MBDS): proposal for a reduced model.

    PubMed

    da Silva, Wanderson Roberto; Marôco, João; Ochner, Christopher N; Campos, Juliana Alvares Duarte Bonini

    2017-09-01

    To evaluate the psychometric properties of the male body dissatisfaction scale (MBDS) in Brazilian and Portuguese university students; to present a reduced model of the scale; to compare two methods of computing global scores for participants' body dissatisfaction; and to estimate the prevalence of participants' body dissatisfaction. A total of 932 male students participated in this study. A confirmatory factor analysis (CFA) was used to assess the scale's psychometric properties. Multi-group analysis was used to test transnational invariance and invariance in independent samples. The body dissatisfaction score was calculated using two methods (mean and matrix of weights in the CFA), which were compared. Finally, individuals were classified according to level of body dissatisfaction, using the best method. The MBDS model did not show adequate fit for the sample and was, therefore, refined. Thirteen items were excluded and two factors were combined. A reduced model of 12 items and 2 factors was proposed and shown to have adequate psychometric properties. There was a significant difference (p < 0.001) between the methods for calculating the score for body dissatisfaction, since the mean overestimated the scores. Among student participants, the prevalence of body dissatisfaction with musculature and general appearance was 11.2 and 5.3%, respectively. The reduced bi-factorial model of the MBDS showed adequate validity, reliability, and transnational invariance and invariance in independent samples for Brazilian and Portuguese students. The new proposal for calculating the global score was able to more accurately show their body dissatisfaction. No level of evidence Basic Science.

  1. NNLOPS accurate associated HW production

    NASA Astrophysics Data System (ADS)

    Astill, William; Bizon, Wojciech; Re, Emanuele; Zanderighi, Giulia

    2016-06-01

    We present a next-to-next-to-leading order accurate description of associated HW production consistently matched to a parton shower. The method is based on reweighting events obtained with the HW plus one jet NLO accurate calculation implemented in POWHEG, extended with the MiNLO procedure, to reproduce NNLO accurate Born distributions. Since the Born kinematics is more complex than the cases treated before, we use a parametrization of the Collins-Soper angles to reduce the number of variables required for the reweighting. We present phenomenological results at 13 TeV, with cuts suggested by the Higgs Cross section Working Group.

  2. Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

    PubMed Central

    Noecker, Cecilia; Schaefer, Krista; Zaccheo, Kelly; Yang, Yiding; Day, Judy; Ganusov, Vitaly V.

    2015-01-01

    Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results

  3. Accurate Cold-Test Model of Helical TWT Slow-Wave Circuits

    NASA Technical Reports Server (NTRS)

    Kory, Carol L.; Dayton, James A., Jr.

    1997-01-01

    Recently, a method has been established to accurately calculate cold-test data for helical slow-wave structures using the three-dimensional electromagnetic computer code, MAFIA. Cold-test parameters have been calculated for several helical traveling-wave tube (TWT) slow-wave circuits possessing various support rod configurations, and results are presented here showing excellent agreement with experiment. The helical models include tape thickness, dielectric support shapes and material properties consistent with the actual circuits. The cold-test data from this helical model can be used as input into large-signal helical TWT interaction codes making it possible, for the first time, to design a complete TWT via computer simulation.

  4. A new approach for reducing beam hardening artifacts in polychromatic X-ray computed tomography using more accurate prior image.

    PubMed

    Wang, Hui; Xu, Yanan; Shi, Hongli

    2018-03-15

    Metal artifacts severely degrade CT image quality in clinical diagnosis, which are difficult to removed, especially for the beam hardening artifacts. The metal artifact reduction (MAR) based on prior images are the most frequently-used methods. However, there exists a lot misclassification in most prior images caused by absence of prior information such as spectrum distribution of X-ray beam source, especially when multiple or big metal are included. This work aims is to identify a more accurate prior image to improve image quality. The proposed method includes four steps. First, the metal image is segmented by thresholding an initial image, where the metal traces are identified in the initial projection data using the forward projection of the metal image. Second, the accurate absorbent model of certain metal image is calculated according to the spectrum distribution of certain X-ray beam source and energy-dependent attenuation coefficients of metal. Third, a new metal image is reconstructed by the general analytical reconstruction algorithm such as filtered back projection (FPB). The prior image is obtained by segmenting the difference image between the initial image and the new metal image into air, tissue and bone. Fourth, the initial projection data are normalized by dividing the projection data of prior image pixel to pixel. The final corrected image is obtained by interpolation, denormalization and reconstruction. Several clinical images with dental fillings and knee prostheses were used to evaluate the proposed algorithm and normalized metal artifact reduction (NMAR) and linear interpolation (LI) method. The results demonstrate the artifacts were reduced efficiently by the proposed method. The proposed method could obtain an exact prior image using the prior information about X-ray beam source and energy-dependent attenuation coefficients of metal. As a result, better performance of reducing beam hardening artifacts can be achieved. Moreover, the process of

  5. Generating Facial Expressions Using an Anatomically Accurate Biomechanical Model.

    PubMed

    Wu, Tim; Hung, Alice; Mithraratne, Kumar

    2014-11-01

    This paper presents a computational framework for modelling the biomechanics of human facial expressions. A detailed high-order (Cubic-Hermite) finite element model of the human head was constructed using anatomical data segmented from magnetic resonance images. The model includes a superficial soft-tissue continuum consisting of skin, the subcutaneous layer and the superficial Musculo-Aponeurotic system. Embedded within this continuum mesh, are 20 pairs of facial muscles which drive facial expressions. These muscles were treated as transversely-isotropic and their anatomical geometries and fibre orientations were accurately depicted. In order to capture the relative composition of muscles and fat, material heterogeneity was also introduced into the model. Complex contact interactions between the lips, eyelids, and between superficial soft tissue continuum and deep rigid skeletal bones were also computed. In addition, this paper investigates the impact of incorporating material heterogeneity and contact interactions, which are often neglected in similar studies. Four facial expressions were simulated using the developed model and the results were compared with surface data obtained from a 3D structured-light scanner. Predicted expressions showed good agreement with the experimental data.

  6. Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models

    PubMed Central

    Xing, W. W.; Triantafyllidis, V.

    2017-01-01

    In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach. PMID:28484327

  7. Rigorous joining of advanced reduced-dimensional beam models to three-dimensional finite element models

    NASA Astrophysics Data System (ADS)

    Song, Huimin

    In the aerospace and automotive industries, many finite element analyses use lower-dimensional finite elements such as beams, plates and shells, to simplify the modeling. These simplified models can greatly reduce the computation time and cost; however, reduced-dimensional models may introduce inaccuracies, particularly near boundaries and near portions of the structure where reduced-dimensional models may not apply. Another factor in creation of such models is that beam-like structures frequently have complex geometry, boundaries and loading conditions, which may make them unsuitable for modeling with single type of element. The goal of this dissertation is to develop a method that can accurately and efficiently capture the response of a structure by rigorous combination of a reduced-dimensional beam finite element model with a model based on full two-dimensional (2D) or three-dimensional (3D) finite elements. The first chapter of the thesis gives the background of the present work and some related previous work. The second chapter is focused on formulating a system of equations that govern the joining of a 2D model with a beam model for planar deformation. The essential aspect of this formulation is to find the transformation matrices to achieve deflection and load continuity on the interface. Three approaches are provided to obtain the transformation matrices. An example based on joining a beam to a 2D finite element model is examined, and the accuracy of the analysis is studied by comparing joint results with the full 2D analysis. The third chapter is focused on formulating the system of equations for joining a beam to a 3D finite element model for static and free-vibration problems. The transition between the 3D elements and beam elements is achieved by use of the stress recovery technique of the variational-asymptotic method as implemented in VABS (the Variational Asymptotic Beam Section analysis). The formulations for an interface transformation matrix and

  8. Reduced-order modeling for hyperthermia control.

    PubMed

    Potocki, J K; Tharp, H S

    1992-12-01

    This paper analyzes the feasibility of using reduced-order modeling techniques in the design of multiple-input, multiple-output (MIMO) hyperthermia temperature controllers. State space thermal models are created based upon a finite difference expansion of the bioheat transfer equation model of a scanned focused ultrasound system (SFUS). These thermal state space models are reduced using the balanced realization technique, and an order reduction criterion is tabulated. Results show that a drastic reduction in model dimension can be achieved using the balanced realization. The reduced-order model is then used to design a reduced-order optimal servomechanism controller for a two-scan input, two thermocouple output tissue model. In addition, a full-order optimal servomechanism controller is designed for comparison and validation purposes. These two controllers are applied to a variety of perturbed tissue thermal models to test the robust nature of the reduced-order controller. A comparison of the two controllers validates the use of open-loop balanced reduced-order models in the design of MIMO hyperthermia controllers.

  9. Numerically accurate computational techniques for optimal estimator analyses of multi-parameter models

    NASA Astrophysics Data System (ADS)

    Berger, Lukas; Kleinheinz, Konstantin; Attili, Antonio; Bisetti, Fabrizio; Pitsch, Heinz; Mueller, Michael E.

    2018-05-01

    Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy

  10. An Equation-Free Reduced-Order Modeling Approach to Tropical Pacific Simulation

    NASA Astrophysics Data System (ADS)

    Wang, Ruiwen; Zhu, Jiang; Luo, Zhendong; Navon, I. M.

    2009-03-01

    The “equation-free” (EF) method is often used in complex, multi-scale problems. In such cases it is necessary to know the closed form of the required evolution equations about oscopic variables within some applied fields. Conceptually such equations exist, however, they are not available in closed form. The EF method can bypass this difficulty. This method can obtain oscopic information by implementing models at a microscopic level. Given an initial oscopic variable, through lifting we can obtain the associated microscopic variable, which may be evolved using Direct Numerical Simulations (DNS) and by restriction, we can obtain the necessary oscopic information and the projective integration to obtain the desired quantities. In this paper we apply the EF POD-assisted method to the reduced modeling of a large-scale upper ocean circulation in the tropical Pacific domain. The computation cost is reduced dramatically. Compared with the POD method, the method provided more accurate results and it did not require the availability of any explicit equations or the right-hand side (RHS) of the evolution equation.

  11. Fast prediction and evaluation of eccentric inspirals using reduced-order models

    NASA Astrophysics Data System (ADS)

    Barta, Dániel; Vasúth, Mátyás

    2018-06-01

    A large number of theoretically predicted waveforms are required by matched-filtering searches for the gravitational-wave signals produced by compact binary coalescence. In order to substantially alleviate the computational burden in gravitational-wave searches and parameter estimation without degrading the signal detectability, we propose a novel reduced-order-model (ROM) approach with applications to adiabatic 3PN-accurate inspiral waveforms of nonspinning sources that evolve on either highly or slightly eccentric orbits. We provide a singular-value decomposition-based reduced-basis method in the frequency domain to generate reduced-order approximations of any gravitational waves with acceptable accuracy and precision within the parameter range of the model. We construct efficient reduced bases comprised of a relatively small number of the most relevant waveforms over three-dimensional parameter-space covered by the template bank (total mass 2.15 M⊙≤M ≤215 M⊙ , mass ratio 0.01 ≤q ≤1 , and initial orbital eccentricity 0 ≤e0≤0.95 ). The ROM is designed to predict signals in the frequency band from 10 Hz to 2 kHz for aLIGO and aVirgo design sensitivity. Beside moderating the data reduction, finer sampling of fiducial templates improves the accuracy of surrogates. Considerable increase in the speedup from several hundreds to thousands can be achieved by evaluating surrogates for low-mass systems especially when combined with high-eccentricity.

  12. Accurate and scalable social recommendation using mixed-membership stochastic block models.

    PubMed

    Godoy-Lorite, Antonia; Guimerà, Roger; Moore, Cristopher; Sales-Pardo, Marta

    2016-12-13

    With increasing amounts of information available, modeling and predicting user preferences-for books or articles, for example-are becoming more important. We present a collaborative filtering model, with an associated scalable algorithm, that makes accurate predictions of users' ratings. Like previous approaches, we assume that there are groups of users and of items and that the rating a user gives an item is determined by their respective group memberships. However, we allow each user and each item to belong simultaneously to mixtures of different groups and, unlike many popular approaches such as matrix factorization, we do not assume that users in each group prefer a single group of items. In particular, we do not assume that ratings depend linearly on a measure of similarity, but allow probability distributions of ratings to depend freely on the user's and item's groups. The resulting overlapping groups and predicted ratings can be inferred with an expectation-maximization algorithm whose running time scales linearly with the number of observed ratings. Our approach enables us to predict user preferences in large datasets and is considerably more accurate than the current algorithms for such large datasets.

  13. Accurate and scalable social recommendation using mixed-membership stochastic block models

    PubMed Central

    Godoy-Lorite, Antonia; Moore, Cristopher

    2016-01-01

    With increasing amounts of information available, modeling and predicting user preferences—for books or articles, for example—are becoming more important. We present a collaborative filtering model, with an associated scalable algorithm, that makes accurate predictions of users’ ratings. Like previous approaches, we assume that there are groups of users and of items and that the rating a user gives an item is determined by their respective group memberships. However, we allow each user and each item to belong simultaneously to mixtures of different groups and, unlike many popular approaches such as matrix factorization, we do not assume that users in each group prefer a single group of items. In particular, we do not assume that ratings depend linearly on a measure of similarity, but allow probability distributions of ratings to depend freely on the user’s and item’s groups. The resulting overlapping groups and predicted ratings can be inferred with an expectation-maximization algorithm whose running time scales linearly with the number of observed ratings. Our approach enables us to predict user preferences in large datasets and is considerably more accurate than the current algorithms for such large datasets. PMID:27911773

  14. A reduced theoretical model for estimating condensation effects in combustion-heated hypersonic tunnel

    NASA Astrophysics Data System (ADS)

    Lin, L.; Luo, X.; Qin, F.; Yang, J.

    2018-03-01

    As one of the combustion products of hydrocarbon fuels in a combustion-heated wind tunnel, water vapor may condense during the rapid expansion process, which will lead to a complex two-phase flow inside the wind tunnel and even change the design flow conditions at the nozzle exit. The coupling of the phase transition and the compressible flow makes the estimation of the condensation effects in such wind tunnels very difficult and time-consuming. In this work, a reduced theoretical model is developed to approximately compute the nozzle-exit conditions of a flow including real-gas and homogeneous condensation effects. Specifically, the conservation equations of the axisymmetric flow are first approximated in the quasi-one-dimensional way. Then, the complex process is split into two steps, i.e., a real-gas nozzle flow but excluding condensation, resulting in supersaturated nozzle-exit conditions, and a discontinuous jump at the end of the nozzle from the supersaturated state to a saturated state. Compared with two-dimensional numerical simulations implemented with a detailed condensation model, the reduced model predicts the flow parameters with good accuracy except for some deviations caused by the two-dimensional effect. Therefore, this reduced theoretical model can provide a fast, simple but also accurate estimation of the condensation effect in combustion-heated hypersonic tunnels.

  15. Ensemble predictive model for more accurate soil organic carbon spectroscopic estimation

    NASA Astrophysics Data System (ADS)

    Vašát, Radim; Kodešová, Radka; Borůvka, Luboš

    2017-07-01

    A myriad of signal pre-processing strategies and multivariate calibration techniques has been explored in attempt to improve the spectroscopic prediction of soil organic carbon (SOC) over the last few decades. Therefore, to come up with a novel, more powerful, and accurate predictive approach to beat the rank becomes a challenging task. However, there may be a way, so that combine several individual predictions into a single final one (according to ensemble learning theory). As this approach performs best when combining in nature different predictive algorithms that are calibrated with structurally different predictor variables, we tested predictors of two different kinds: 1) reflectance values (or transforms) at each wavelength and 2) absorption feature parameters. Consequently we applied four different calibration techniques, two per each type of predictors: a) partial least squares regression and support vector machines for type 1, and b) multiple linear regression and random forest for type 2. The weights to be assigned to individual predictions within the ensemble model (constructed as a weighted average) were determined by an automated procedure that ensured the best solution among all possible was selected. The approach was tested at soil samples taken from surface horizon of four sites differing in the prevailing soil units. By employing the ensemble predictive model the prediction accuracy of SOC improved at all four sites. The coefficient of determination in cross-validation (R2cv) increased from 0.849, 0.611, 0.811 and 0.644 (the best individual predictions) to 0.864, 0.650, 0.824 and 0.698 for Site 1, 2, 3 and 4, respectively. Generally, the ensemble model affected the final prediction so that the maximal deviations of predicted vs. observed values of the individual predictions were reduced, and thus the correlation cloud became thinner as desired.

  16. On the study of control effectiveness and computational efficiency of reduced Saint-Venant model in model predictive control of open channel flow

    NASA Astrophysics Data System (ADS)

    Xu, M.; van Overloop, P. J.; van de Giesen, N. C.

    2011-02-01

    Model predictive control (MPC) of open channel flow is becoming an important tool in water management. The complexity of the prediction model has a large influence on the MPC application in terms of control effectiveness and computational efficiency. The Saint-Venant equations, called SV model in this paper, and the Integrator Delay (ID) model are either accurate but computationally costly, or simple but restricted to allowed flow changes. In this paper, a reduced Saint-Venant (RSV) model is developed through a model reduction technique, Proper Orthogonal Decomposition (POD), on the SV equations. The RSV model keeps the main flow dynamics and functions over a large flow range but is easier to implement in MPC. In the test case of a modeled canal reach, the number of states and disturbances in the RSV model is about 45 and 16 times less than the SV model, respectively. The computational time of MPC with the RSV model is significantly reduced, while the controller remains effective. Thus, the RSV model is a promising means to balance the control effectiveness and computational efficiency.

  17. Dynamic sensing model for accurate delectability of environmental phenomena using event wireless sensor network

    NASA Astrophysics Data System (ADS)

    Missif, Lial Raja; Kadhum, Mohammad M.

    2017-09-01

    Wireless Sensor Network (WSN) has been widely used for monitoring where sensors are deployed to operate independently to sense abnormal phenomena. Most of the proposed environmental monitoring systems are designed based on a predetermined sensing range which does not reflect the sensor reliability, event characteristics, and the environment conditions. Measuring of the capability of a sensor node to accurately detect an event within a sensing field is of great important for monitoring applications. This paper presents an efficient mechanism for even detection based on probabilistic sensing model. Different models have been presented theoretically in this paper to examine their adaptability and applicability to the real environment applications. The numerical results of the experimental evaluation have showed that the probabilistic sensing model provides accurate observation and delectability of an event, and it can be utilized for different environment scenarios.

  18. Getting a Picture that Is Both Accurate and Stable: Situation Models and Epistemic Validation

    ERIC Educational Resources Information Center

    Schroeder, Sascha; Richter, Tobias; Hoever, Inga

    2008-01-01

    Text comprehension entails the construction of a situation model that prepares individuals for situated action. In order to meet this function, situation model representations are required to be both accurate and stable. We propose a framework according to which comprehenders rely on epistemic validation to prevent inaccurate information from…

  19. Accurate Treatment of Collision and Water-Delivery in Models of Terrestrial Planet Formation

    NASA Astrophysics Data System (ADS)

    Haghighipour, N.; Maindl, T. I.; Schaefer, C. M.; Wandel, O.

    2017-08-01

    We have developed a comprehensive approach in simulating collisions and growth of embryos to terrestrial planets where we use a combination of SPH and N-body codes to model collisions and the transfer of water and chemical compounds accurately.

  20. Modeling of capacitor charging dynamics in an energy harvesting system considering accurate electromechanical coupling effects

    NASA Astrophysics Data System (ADS)

    Bagheri, Shahriar; Wu, Nan; Filizadeh, Shaahin

    2018-06-01

    This paper presents an iterative numerical method that accurately models an energy harvesting system charging a capacitor with piezoelectric patches. The constitutive relations of piezoelectric materials connected with an external charging circuit with a diode bridge and capacitors lead to the electromechanical coupling effect and the difficulty of deriving accurate transient mechanical response, as well as the charging progress. The proposed model is built upon the Euler-Bernoulli beam theory and takes into account the electromechanical coupling effects as well as the dynamic process of charging an external storage capacitor. The model is validated through experimental tests on a cantilever beam coated with piezoelectric patches. Several parametric studies are performed and the functionality of the model is verified. The efficiency of power harvesting system can be predicted and tuned considering variations in different design parameters. Such a model can be utilized to design robust and optimal energy harvesting system.

  1. Model's sparse representation based on reduced mixed GMsFE basis methods

    NASA Astrophysics Data System (ADS)

    Jiang, Lijian; Li, Qiuqi

    2017-06-01

    In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in random porous

  2. Model's sparse representation based on reduced mixed GMsFE basis methods

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn; Li, Qiuqi, E-mail: qiuqili@hnu.edu.cn

    2017-06-01

    In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a largemore » number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in random

  3. Obtaining Accurate Probabilities Using Classifier Calibration

    ERIC Educational Resources Information Center

    Pakdaman Naeini, Mahdi

    2016-01-01

    Learning probabilistic classification and prediction models that generate accurate probabilities is essential in many prediction and decision-making tasks in machine learning and data mining. One way to achieve this goal is to post-process the output of classification models to obtain more accurate probabilities. These post-processing methods are…

  4. Validation of an Accurate Three-Dimensional Helical Slow-Wave Circuit Model

    NASA Technical Reports Server (NTRS)

    Kory, Carol L.

    1997-01-01

    The helical slow-wave circuit embodies a helical coil of rectangular tape supported in a metal barrel by dielectric support rods. Although the helix slow-wave circuit remains the mainstay of the traveling-wave tube (TWT) industry because of its exceptionally wide bandwidth, a full helical circuit, without significant dimensional approximations, has not been successfully modeled until now. Numerous attempts have been made to analyze the helical slow-wave circuit so that the performance could be accurately predicted without actually building it, but because of its complex geometry, many geometrical approximations became necessary rendering the previous models inaccurate. In the course of this research it has been demonstrated that using the simulation code, MAFIA, the helical structure can be modeled with actual tape width and thickness, dielectric support rod geometry and materials. To demonstrate the accuracy of the MAFIA model, the cold-test parameters including dispersion, on-axis interaction impedance and attenuation have been calculated for several helical TWT slow-wave circuits with a variety of support rod geometries including rectangular and T-shaped rods, as well as various support rod materials including isotropic, anisotropic and partially metal coated dielectrics. Compared with experimentally measured results, the agreement is excellent. With the accuracy of the MAFIA helical model validated, the code was used to investigate several conventional geometric approximations in an attempt to obtain the most computationally efficient model. Several simplifications were made to a standard model including replacing the helical tape with filaments, and replacing rectangular support rods with shapes conforming to the cylindrical coordinate system with effective permittivity. The approximate models are compared with the standard model in terms of cold-test characteristics and computational time. The model was also used to determine the sensitivity of various

  5. PconsD: ultra rapid, accurate model quality assessment for protein structure prediction.

    PubMed

    Skwark, Marcin J; Elofsson, Arne

    2013-07-15

    Clustering methods are often needed for accurately assessing the quality of modeled protein structures. Recent blind evaluation of quality assessment methods in CASP10 showed that there is little difference between many different methods as far as ranking models and selecting best model are concerned. When comparing many models, the computational cost of the model comparison can become significant. Here, we present PconsD, a fast, stream-computing method for distance-driven model quality assessment that runs on consumer hardware. PconsD is at least one order of magnitude faster than other methods of comparable accuracy. The source code for PconsD is freely available at http://d.pcons.net/. Supplementary benchmarking data are also available there. arne@bioinfo.se Supplementary data are available at Bioinformatics online.

  6. A Reduced-Order Model For Zero-Mass Synthetic Jet Actuators

    NASA Technical Reports Server (NTRS)

    Yamaleev, Nail K.; Carpenter, Mark H.; Vatsa, Veer S.

    2007-01-01

    Accurate details of the general performance of fluid actuators is desirable over a range of flow conditions, within some predetermined error tolerance. Designers typically model actuators with different levels of fidelity depending on the acceptable level of error in each circumstance. Crude properties of the actuator (e.g., peak mass rate and frequency) may be sufficient for some designs, while detailed information is needed for other applications (e.g., multiple actuator interactions). This work attempts to address two primary objectives. The first objective is to develop a systematic methodology for approximating realistic 3-D fluid actuators, using quasi-1-D reduced-order models. Near full fidelity can be achieved with this approach at a fraction of the cost of full simulation and only a modest increase in cost relative to most actuator models used today. The second objective, which is a direct consequence of the first, is to determine the approximate magnitude of errors committed by actuator model approximations of various fidelities. This objective attempts to identify which model (ranging from simple orifice exit boundary conditions to full numerical simulations of the actuator) is appropriate for a given error tolerance.

  7. Accurately modeling Gaussian beam propagation in the context of Monte Carlo techniques

    NASA Astrophysics Data System (ADS)

    Hokr, Brett H.; Winblad, Aidan; Bixler, Joel N.; Elpers, Gabriel; Zollars, Byron; Scully, Marlan O.; Yakovlev, Vladislav V.; Thomas, Robert J.

    2016-03-01

    Monte Carlo simulations are widely considered to be the gold standard for studying the propagation of light in turbid media. However, traditional Monte Carlo methods fail to account for diffraction because they treat light as a particle. This results in converging beams focusing to a point instead of a diffraction limited spot, greatly effecting the accuracy of Monte Carlo simulations near the focal plane. Here, we present a technique capable of simulating a focusing beam in accordance to the rules of Gaussian optics, resulting in a diffraction limited focal spot. This technique can be easily implemented into any traditional Monte Carlo simulation allowing existing models to be converted to include accurate focusing geometries with minimal effort. We will present results for a focusing beam in a layered tissue model, demonstrating that for different scenarios the region of highest intensity, thus the greatest heating, can change from the surface to the focus. The ability to simulate accurate focusing geometries will greatly enhance the usefulness of Monte Carlo for countless applications, including studying laser tissue interactions in medical applications and light propagation through turbid media.

  8. Bayesian parameter estimation of a k-ε model for accurate jet-in-crossflow simulations

    DOE PAGES

    Ray, Jaideep; Lefantzi, Sophia; Arunajatesan, Srinivasan; ...

    2016-05-31

    Reynolds-averaged Navier–Stokes models are not very accurate for high-Reynolds-number compressible jet-in-crossflow interactions. The inaccuracy arises from the use of inappropriate model parameters and model-form errors in the Reynolds-averaged Navier–Stokes model. In this study, the hypothesis is pursued that Reynolds-averaged Navier–Stokes predictions can be significantly improved by using parameters inferred from experimental measurements of a supersonic jet interacting with a transonic crossflow.

  9. Reduced order modeling and active flow control of an inlet duct

    NASA Astrophysics Data System (ADS)

    Ge, Xiaoqing

    dynamical model to augment the linear input/output model. Thus, the full system is decomposed into a dominant linear subsystem and a low order nonlinear subsystem. The hybrid model is then used for control design and compared with other modeling methods in CFD simulations. Numerical results indicate that the hybrid model accurately predicts the nonlinear behavior of the flow for a 2D diffuser contraction section model. It also performs best in terms of feedback control design and learning control. Since some outputs of interest (e.g., the AIP pressure recovery) are not observable during normal operations, static and dynamic estimators are designed to recreate the information from available sensor measurements. The latter also provides a state estimation for feedback controller. Based on the reduced order models and estimators, different controllers are designed to improve the aerodynamic performance of the contraction section and inlet duct. The integrated control methodology is evaluated with CFD simulations. Numerical results demonstrate the feasibility and efficacy of the active flow control based on reduced order models. Our reduced order models not only generate a good approximation of the nonlinear flow dynamics over a wide input range, but also help to design controllers that significantly improve the flow response. The tools developed for model reduction, estimator and control design can also be applied to wind tunnel experiment.

  10. Accurate modeling of defects in graphene transport calculations

    NASA Astrophysics Data System (ADS)

    Linhart, Lukas; Burgdörfer, Joachim; Libisch, Florian

    2018-01-01

    We present an approach for embedding defect structures modeled by density functional theory into large-scale tight-binding simulations. We extract local tight-binding parameters for the vicinity of the defect site using Wannier functions. In the transition region between the bulk lattice and the defect the tight-binding parameters are continuously adjusted to approach the bulk limit far away from the defect. This embedding approach allows for an accurate high-level treatment of the defect orbitals using as many as ten nearest neighbors while keeping a small number of nearest neighbors in the bulk to render the overall computational cost reasonable. As an example of our approach, we consider an extended graphene lattice decorated with Stone-Wales defects, flower defects, double vacancies, or silicon substitutes. We predict distinct scattering patterns mirroring the defect symmetries and magnitude that should be experimentally accessible.

  11. Accurate Modelling of Surface Currents and Internal Tides in a Semi-enclosed Coastal Sea

    NASA Astrophysics Data System (ADS)

    Allen, S. E.; Soontiens, N. K.; Dunn, M. B. H.; Liu, J.; Olson, E.; Halverson, M. J.; Pawlowicz, R.

    2016-02-01

    The Strait of Georgia is a deep (400 m), strongly stratified, semi-enclosed coastal sea on the west coast of North America. We have configured a baroclinic model of the Strait of Georgia and surrounding coastal waters using the NEMO ocean community model. We run daily nowcasts and forecasts and publish our sea-surface results (including storm surge warnings) to the web (salishsea.eos.ubc.ca/storm-surge). Tides in the Strait of Georgia are mixed and large. The baroclinic model and previous barotropic models accurately represent tidal sea-level variations and depth mean currents. The baroclinic model reproduces accurately the diurnal but not the semi-diurnal baroclinic tidal currents. In the Southern Strait of Georgia, strong internal tidal currents at the semi-diurnal frequency are observed. Strong semi-diurnal tides are also produced in the model, but are almost 180 degrees out of phase with the observations. In the model, in the surface, the barotropic and baroclinic tides reinforce, whereas the observations show that at the surface the baroclinic tides oppose the barotropic. As such the surface currents are very poorly modelled. Here we will present evidence of the internal tidal field from observations. We will discuss the generation regions of the tides, the necessary modifications to the model required to correct the phase, the resulting baroclinic tides and the improvements in the surface currents.

  12. Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots.

    PubMed

    Hajdin, Christine E; Bellaousov, Stanislav; Huggins, Wayne; Leonard, Christopher W; Mathews, David H; Weeks, Kevin M

    2013-04-02

    A pseudoknot forms in an RNA when nucleotides in a loop pair with a region outside the helices that close the loop. Pseudoknots occur relatively rarely in RNA but are highly overrepresented in functionally critical motifs in large catalytic RNAs, in riboswitches, and in regulatory elements of viruses. Pseudoknots are usually excluded from RNA structure prediction algorithms. When included, these pairings are difficult to model accurately, especially in large RNAs, because allowing this structure dramatically increases the number of possible incorrect folds and because it is difficult to search the fold space for an optimal structure. We have developed a concise secondary structure modeling approach that combines SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) experimental chemical probing information and a simple, but robust, energy model for the entropic cost of single pseudoknot formation. Structures are predicted with iterative refinement, using a dynamic programming algorithm. This melded experimental and thermodynamic energy function predicted the secondary structures and the pseudoknots for a set of 21 challenging RNAs of known structure ranging in size from 34 to 530 nt. On average, 93% of known base pairs were predicted, and all pseudoknots in well-folded RNAs were identified.

  13. Accurate coarse-grained models for mixtures of colloids and linear polymers under good-solvent conditions

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    D’Adamo, Giuseppe, E-mail: giuseppe.dadamo@sissa.it; Pelissetto, Andrea, E-mail: andrea.pelissetto@roma1.infn.it; Pierleoni, Carlo, E-mail: carlo.pierleoni@aquila.infn.it

    2014-12-28

    A coarse-graining strategy, previously developed for polymer solutions, is extended here to mixtures of linear polymers and hard-sphere colloids. In this approach, groups of monomers are mapped onto a single pseudoatom (a blob) and the effective blob-blob interactions are obtained by requiring the model to reproduce some large-scale structural properties in the zero-density limit. We show that an accurate parametrization of the polymer-colloid interactions is obtained by simply introducing pair potentials between blobs and colloids. For the coarse-grained (CG) model in which polymers are modelled as four-blob chains (tetramers), the pair potentials are determined by means of the iterative Boltzmannmore » inversion scheme, taking full-monomer (FM) pair correlation functions at zero-density as targets. For a larger number n of blobs, pair potentials are determined by using a simple transferability assumption based on the polymer self-similarity. We validate the model by comparing its predictions with full-monomer results for the interfacial properties of polymer solutions in the presence of a single colloid and for thermodynamic and structural properties in the homogeneous phase at finite polymer and colloid density. The tetramer model is quite accurate for q ≲ 1 (q=R{sup ^}{sub g}/R{sub c}, where R{sup ^}{sub g} is the zero-density polymer radius of gyration and R{sub c} is the colloid radius) and reasonably good also for q = 2. For q = 2, an accurate coarse-grained description is obtained by using the n = 10 blob model. We also compare our results with those obtained by using single-blob models with state-dependent potentials.« less

  14. The slow-scale linear noise approximation: an accurate, reduced stochastic description of biochemical networks under timescale separation conditions

    PubMed Central

    2012-01-01

    Background It is well known that the deterministic dynamics of biochemical reaction networks can be more easily studied if timescale separation conditions are invoked (the quasi-steady-state assumption). In this case the deterministic dynamics of a large network of elementary reactions are well described by the dynamics of a smaller network of effective reactions. Each of the latter represents a group of elementary reactions in the large network and has associated with it an effective macroscopic rate law. A popular method to achieve model reduction in the presence of intrinsic noise consists of using the effective macroscopic rate laws to heuristically deduce effective probabilities for the effective reactions which then enables simulation via the stochastic simulation algorithm (SSA). The validity of this heuristic SSA method is a priori doubtful because the reaction probabilities for the SSA have only been rigorously derived from microscopic physics arguments for elementary reactions. Results We here obtain, by rigorous means and in closed-form, a reduced linear Langevin equation description of the stochastic dynamics of monostable biochemical networks in conditions characterized by small intrinsic noise and timescale separation. The slow-scale linear noise approximation (ssLNA), as the new method is called, is used to calculate the intrinsic noise statistics of enzyme and gene networks. The results agree very well with SSA simulations of the non-reduced network of elementary reactions. In contrast the conventional heuristic SSA is shown to overestimate the size of noise for Michaelis-Menten kinetics, considerably under-estimate the size of noise for Hill-type kinetics and in some cases even miss the prediction of noise-induced oscillations. Conclusions A new general method, the ssLNA, is derived and shown to correctly describe the statistics of intrinsic noise about the macroscopic concentrations under timescale separation conditions. The ssLNA provides a

  15. Improvements to Fidelity, Generation and Implementation of Physics-Based Lithium-Ion Reduced-Order Models

    NASA Astrophysics Data System (ADS)

    Rodriguez Marco, Albert

    Battery management systems (BMS) require computationally simple but highly accurate models of the battery cells they are monitoring and controlling. Historically, empirical equivalent-circuit models have been used, but increasingly researchers are focusing their attention on physics-based models due to their greater predictive capabilities. These models are of high intrinsic computational complexity and so must undergo some kind of order-reduction process to make their use by a BMS feasible: we favor methods based on a transfer-function approach of battery cell dynamics. In prior works, transfer functions have been found from full-order PDE models via two simplifying assumptions: (1) a linearization assumption--which is a fundamental necessity in order to make transfer functions--and (2) an assumption made out of expedience that decouples the electrolyte-potential and electrolyte-concentration PDEs in order to render an approach to solve for the transfer functions from the PDEs. This dissertation improves the fidelity of physics-based models by eliminating the need for the second assumption and, by linearizing nonlinear dynamics around different constant currents. Electrochemical transfer functions are infinite-order and cannot be expressed as a ratio of polynomials in the Laplace variable s. Thus, for practical use, these systems need to be approximated using reduced-order models that capture the most significant dynamics. This dissertation improves the generation of physics-based reduced-order models by introducing different realization algorithms, which produce a low-order model from the infinite-order electrochemical transfer functions. Physics-based reduced-order models are linear and describe cell dynamics if operated near the setpoint at which they have been generated. Hence, multiple physics-based reduced-order models need to be generated at different setpoints (i.e., state-of-charge, temperature and C-rate) in order to extend the cell operating range. This

  16. Development of an Anatomically Accurate Finite Element Human Ocular Globe Model for Blast-Related Fluid-Structure Interaction Studies

    DTIC Science & Technology

    2017-02-01

    ARL-TR-7945 ● FEB 2017 US Army Research Laboratory Development of an Anatomically Accurate Finite Element Human Ocular Globe...ARL-TR-7945 ● FEB 2017 US Army Research Laboratory Development of an Anatomically Accurate Finite Element Human Ocular Globe Model... Finite Element Human Ocular Globe Model for Blast-Related Fluid-Structure Interaction Studies 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM

  17. Accurate, efficient, and (iso)geometrically flexible collocation methods for phase-field models

    NASA Astrophysics Data System (ADS)

    Gomez, Hector; Reali, Alessandro; Sangalli, Giancarlo

    2014-04-01

    We propose new collocation methods for phase-field models. Our algorithms are based on isogeometric analysis, a new technology that makes use of functions from computational geometry, such as, for example, Non-Uniform Rational B-Splines (NURBS). NURBS exhibit excellent approximability and controllable global smoothness, and can represent exactly most geometries encapsulated in Computer Aided Design (CAD) models. These attributes permitted us to derive accurate, efficient, and geometrically flexible collocation methods for phase-field models. The performance of our method is demonstrated by several numerical examples of phase separation modeled by the Cahn-Hilliard equation. We feel that our method successfully combines the geometrical flexibility of finite elements with the accuracy and simplicity of pseudo-spectral collocation methods, and is a viable alternative to classical collocation methods.

  18. BEYOND ELLIPSE(S): ACCURATELY MODELING THE ISOPHOTAL STRUCTURE OF GALAXIES WITH ISOFIT AND CMODEL

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ciambur, B. C., E-mail: bciambur@swin.edu.au

    2015-09-10

    This work introduces a new fitting formalism for isophotes that enables more accurate modeling of galaxies with non-elliptical shapes, such as disk galaxies viewed edge-on or galaxies with X-shaped/peanut bulges. Within this scheme, the angular parameter that defines quasi-elliptical isophotes is transformed from the commonly used, but inappropriate, polar coordinate to the “eccentric anomaly.” This provides a superior description of deviations from ellipticity, better capturing the true isophotal shape. Furthermore, this makes it possible to accurately recover both the surface brightness profile, using the correct azimuthally averaged isophote, and the two-dimensional model of any galaxy: the hitherto ubiquitous, but artificial,more » cross-like features in residual images are completely removed. The formalism has been implemented into the Image Reduction and Analysis Facility tasks Ellipse and Bmodel to create the new tasks “Isofit,” and “Cmodel.” The new tools are demonstrated here with application to five galaxies, chosen to be representative case-studies for several areas where this technique makes it possible to gain new scientific insight. Specifically: properly quantifying boxy/disky isophotes via the fourth harmonic order in edge-on galaxies, quantifying X-shaped/peanut bulges, higher-order Fourier moments for modeling bars in disks, and complex isophote shapes. Higher order (n > 4) harmonics now become meaningful and may correlate with structural properties, as boxyness/diskyness is known to do. This work also illustrates how the accurate construction, and subtraction, of a model from a galaxy image facilitates the identification and recovery of over-lapping sources such as globular clusters and the optical counterparts of X-ray sources.« less

  19. Production of Accurate Skeletal Models of Domestic Animals Using Three-Dimensional Scanning and Printing Technology

    ERIC Educational Resources Information Center

    Li, Fangzheng; Liu, Chunying; Song, Xuexiong; Huan, Yanjun; Gao, Shansong; Jiang, Zhongling

    2018-01-01

    Access to adequate anatomical specimens can be an important aspect in learning the anatomy of domestic animals. In this study, the authors utilized a structured light scanner and fused deposition modeling (FDM) printer to produce highly accurate animal skeletal models. First, various components of the bovine skeleton, including the femur, the…

  20. An accurate potential model for the a3Σu+ state of the alkali dimers Na2, K2, Rb2, and Cs2

    NASA Astrophysics Data System (ADS)

    Lau, Jascha A.; Toennies, J. Peter; Tang, K. T.

    2016-11-01

    A modified semi-empirical Tang-Toennies potential model is used to describe the a3Σu+ potentials of the alkali dimers. These potentials are currently of interest in connection with the laser manipulation of the ultracold alkali gases. The fully analytical model is based on three experimental parameters, the well depth De, well location Re, and the harmonic vibrational frequency ωe of which the latter is only slightly optimized within the range of the literature values. Comparison with the latest spectroscopic data shows good agreement for Na2, K2, Rb2, and Cs2, comparable to that found with published potential models with up to 55 parameters. The differences between the reduced potential of Li2 and the conformal reduced potentials of the heavier dimers are analyzed together with why the model describes Li2 less accurately. The new model potential provides a test of the principle of corresponding states and an excellent first order approximation for further optimization to improve the fits to the spectroscopic data and describe the scattering lengths and Feshbach resonances at ultra-low temperatures.

  1. A model-updating procedure to stimulate piezoelectric transducers accurately.

    PubMed

    Piranda, B; Ballandras, S; Steichen, W; Hecart, B

    2001-09-01

    The use of numerical calculations based on finite element methods (FEM) has yielded significant improvements in the simulation and design of piezoelectric transducers piezoelectric transducer utilized in acoustic imaging. However, the ultimate precision of such models is directly controlled by the accuracy of material characterization. The present work is dedicated to the development of a model-updating technique adapted to the problem of piezoelectric transducer. The updating process is applied using the experimental admittance of a given structure for which a finite element analysis is performed. The mathematical developments are reported and then applied to update the entries of a FEM of a two-layer structure (a PbZrTi-PZT-ridge glued on a backing) for which measurements were available. The efficiency of the proposed approach is demonstrated, yielding the definition of a new set of constants well adapted to predict the structure response accurately. Improvement of the proposed approach, consisting of the updating of material coefficients not only on the admittance but also on the impedance data, is finally discussed.

  2. Accurate modeling of switched reluctance machine based on hybrid trained WNN

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Song, Shoujun, E-mail: sunnyway@nwpu.edu.cn; Ge, Lefei; Ma, Shaojie

    2014-04-15

    According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, themore » nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.« less

  3. Reduced order model based on principal component analysis for process simulation and optimization

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lang, Y.; Malacina, A.; Biegler, L.

    2009-01-01

    It is well-known that distributed parameter computational fluid dynamics (CFD) models provide more accurate results than conventional, lumped-parameter unit operation models used in process simulation. Consequently, the use of CFD models in process/equipment co-simulation offers the potential to optimize overall plant performance with respect to complex thermal and fluid flow phenomena. Because solving CFD models is time-consuming compared to the overall process simulation, we consider the development of fast reduced order models (ROMs) based on CFD results to closely approximate the high-fidelity equipment models in the co-simulation. By considering process equipment items with complicated geometries and detailed thermodynamic property models,more » this study proposes a strategy to develop ROMs based on principal component analysis (PCA). Taking advantage of commercial process simulation and CFD software (for example, Aspen Plus and FLUENT), we are able to develop systematic CFD-based ROMs for equipment models in an efficient manner. In particular, we show that the validity of the ROM is more robust within well-sampled input domain and the CPU time is significantly reduced. Typically, it takes at most several CPU seconds to evaluate the ROM compared to several CPU hours or more to solve the CFD model. Two case studies, involving two power plant equipment examples, are described and demonstrate the benefits of using our proposed ROM methodology for process simulation and optimization.« less

  4. A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection

    NASA Astrophysics Data System (ADS)

    Bechet, P.; Mitran, R.; Munteanu, M.

    2013-08-01

    Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact.

  5. Reducing the Anaerobic Digestion Model No. 1 for its application to an industrial wastewater treatment plant treating winery effluent wastewater.

    PubMed

    García-Diéguez, Carlos; Bernard, Olivier; Roca, Enrique

    2013-03-01

    The Anaerobic Digestion Model No. 1 (ADM1) is a complex model which is widely accepted as a common platform for anaerobic process modeling and simulation. However, it has a large number of parameters and states that hinder its calibration and use in control applications. A principal component analysis (PCA) technique was extended and applied to simplify the ADM1 using data of an industrial wastewater treatment plant processing winery effluent. The method shows that the main model features could be obtained with a minimum of two reactions. A reduced stoichiometric matrix was identified and the kinetic parameters were estimated on the basis of representative known biochemical kinetics (Monod and Haldane). The obtained reduced model takes into account the measured states in the anaerobic wastewater treatment (AWT) plant and reproduces the dynamics of the process fairly accurately. The reduced model can support on-line control, optimization and supervision strategies for AWT plants. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Accurate Induction Energies for Small Organic Molecules. 2. Development and Testing of Distributed Polarizability Models against SAPT(DFT) Energies.

    PubMed

    Misquitta, Alston J; Stone, Anthony J; Price, Sarah L

    2008-01-01

    In part 1 of this two-part investigation we set out the theoretical basis for constructing accurate models of the induction energy of clusters of moderately sized organic molecules. In this paper we use these techniques to develop a variety of accurate distributed polarizability models for a set of representative molecules that include formamide, N-methyl propanamide, benzene, and 3-azabicyclo[3.3.1]nonane-2,4-dione. We have also explored damping, penetration, and basis set effects. In particular, we have provided a way to treat the damping of the induction expansion. Different approximations to the induction energy are evaluated against accurate SAPT(DFT) energies, and we demonstrate the accuracy of our induction models on the formamide-water dimer.

  7. Parameterized reduced order models from a single mesh using hyper-dual numbers

    NASA Astrophysics Data System (ADS)

    Brake, M. R. W.; Fike, J. A.; Topping, S. D.

    2016-06-01

    In order to assess the predicted performance of a manufactured system, analysts must consider random variations (both geometric and material) in the development of a model, instead of a single deterministic model of an idealized geometry with idealized material properties. The incorporation of random geometric variations, however, potentially could necessitate the development of thousands of nearly identical solid geometries that must be meshed and separately analyzed, which would require an impractical number of man-hours to complete. This research advances a recent approach to uncertainty quantification by developing parameterized reduced order models. These parameterizations are based upon Taylor series expansions of the system's matrices about the ideal geometry, and a component mode synthesis representation for each linear substructure is used to form an efficient basis with which to study the system. The numerical derivatives required for the Taylor series expansions are obtained via hyper-dual numbers, and are compared to parameterized models constructed with finite difference formulations. The advantage of using hyper-dual numbers is two-fold: accuracy of the derivatives to machine precision, and the need to only generate a single mesh of the system of interest. The theory is applied to a stepped beam system in order to demonstrate proof of concept. The results demonstrate that the hyper-dual number multivariate parameterization of geometric variations, which largely are neglected in the literature, are accurate for both sensitivity and optimization studies. As model and mesh generation can constitute the greatest expense of time in analyzing a system, the foundation to create a parameterized reduced order model based off of a single mesh is expected to reduce dramatically the necessary time to analyze multiple realizations of a component's possible geometry.

  8. POD/DEIM reduced-order strategies for efficient four dimensional variational data assimilation

    NASA Astrophysics Data System (ADS)

    Ştefănescu, R.; Sandu, A.; Navon, I. M.

    2015-08-01

    This work studies reduced order modeling (ROM) approaches to speed up the solution of variational data assimilation problems with large scale nonlinear dynamical models. It is shown that a key requirement for a successful reduced order solution is that reduced order Karush-Kuhn-Tucker conditions accurately represent their full order counterparts. In particular, accurate reduced order approximations are needed for the forward and adjoint dynamical models, as well as for the reduced gradient. New strategies to construct reduced order based are developed for proper orthogonal decomposition (POD) ROM data assimilation using both Galerkin and Petrov-Galerkin projections. For the first time POD, tensorial POD, and discrete empirical interpolation method (DEIM) are employed to develop reduced data assimilation systems for a geophysical flow model, namely, the two dimensional shallow water equations. Numerical experiments confirm the theoretical framework for Galerkin projection. In the case of Petrov-Galerkin projection, stabilization strategies must be considered for the reduced order models. The new reduced order shallow water data assimilation system provides analyses similar to those produced by the full resolution data assimilation system in one tenth of the computational time.

  9. POD/DEIM reduced-order strategies for efficient four dimensional variational data assimilation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ştefănescu, R., E-mail: rstefane@vt.edu; Sandu, A., E-mail: sandu@cs.vt.edu; Navon, I.M., E-mail: inavon@fsu.edu

    2015-08-15

    This work studies reduced order modeling (ROM) approaches to speed up the solution of variational data assimilation problems with large scale nonlinear dynamical models. It is shown that a key requirement for a successful reduced order solution is that reduced order Karush–Kuhn–Tucker conditions accurately represent their full order counterparts. In particular, accurate reduced order approximations are needed for the forward and adjoint dynamical models, as well as for the reduced gradient. New strategies to construct reduced order based are developed for proper orthogonal decomposition (POD) ROM data assimilation using both Galerkin and Petrov–Galerkin projections. For the first time POD, tensorialmore » POD, and discrete empirical interpolation method (DEIM) are employed to develop reduced data assimilation systems for a geophysical flow model, namely, the two dimensional shallow water equations. Numerical experiments confirm the theoretical framework for Galerkin projection. In the case of Petrov–Galerkin projection, stabilization strategies must be considered for the reduced order models. The new reduced order shallow water data assimilation system provides analyses similar to those produced by the full resolution data assimilation system in one tenth of the computational time.« less

  10. Escherichia coli growth under modeled reduced gravity

    NASA Technical Reports Server (NTRS)

    Baker, Paul W.; Meyer, Michelle L.; Leff, Laura G.

    2004-01-01

    Bacteria exhibit varying responses to modeled reduced gravity that can be simulated by clino-rotation. When Escherichia coli was subjected to different rotation speeds during clino-rotation, significant differences between modeled reduced gravity and normal gravity controls were observed only at higher speeds (30-50 rpm). There was no apparent affect of removing samples on the results obtained. When E. coli was grown in minimal medium (at 40 rpm), cell size was not affected by modeled reduced gravity and there were few differences in cell numbers. However, in higher nutrient conditions (i.e., dilute nutrient broth), total cell numbers were higher and cells were smaller under reduced gravity compared to normal gravity controls. Overall, the responses to modeled reduced gravity varied with nutrient conditions; larger surface to volume ratios may help compensate for the zone of nutrient depletion around the cells under modeled reduced gravity.

  11. Energy balance and mass conservation in reduced order models of fluid flows

    NASA Astrophysics Data System (ADS)

    Mohebujjaman, Muhammad; Rebholz, Leo G.; Xie, Xuping; Iliescu, Traian

    2017-10-01

    In this paper, we investigate theoretically and computationally the conservation properties of reduced order models (ROMs) for fluid flows. Specifically, we investigate whether the ROMs satisfy the same (or similar) energy balance and mass conservation as those satisfied by the Navier-Stokes equations. All of our theoretical findings are illustrated and tested in numerical simulations of a 2D flow past a circular cylinder at a Reynolds number Re = 100. First, we investigate the ROM energy balance. We show that using the snapshot average for the centering trajectory (which is a popular treatment of nonhomogeneous boundary conditions in ROMs) yields an incorrect energy balance. Then, we propose a new approach, in which we replace the snapshot average with the Stokes extension. Theoretically, the Stokes extension produces an accurate energy balance. Numerically, the Stokes extension yields more accurate results than the standard snapshot average, especially for longer time intervals. Our second contribution centers around ROM mass conservation. We consider ROMs created using two types of finite elements: the standard Taylor-Hood (TH) element, which satisfies the mass conservation weakly, and the Scott-Vogelius (SV) element, which satisfies the mass conservation pointwise. Theoretically, the error estimates for the SV-ROM are sharper than those for the TH-ROM. Numerically, the SV-ROM yields significantly more accurate results, especially for coarser meshes and longer time intervals.

  12. Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles

    USDA-ARS?s Scientific Manuscript database

    To improve climate change impact estimates, multi-model ensembles (MMEs) have been suggested. MMEs enable quantifying model uncertainty, and their medians are more accurate than that of any single model when compared with observations. However, multi-model ensembles are costly to execute, so model i...

  13. Accurate and self-consistent procedure for determining pH in seawater desalination brines and its manifestation in reverse osmosis modeling.

    PubMed

    Nir, Oded; Marvin, Esra; Lahav, Ori

    2014-11-01

    Measuring and modeling pH in concentrated aqueous solutions in an accurate and consistent manner is of paramount importance to many R&D and industrial applications, including RO desalination. Nevertheless, unified definitions and standard procedures have yet to be developed for solutions with ionic strength higher than ∼0.7 M, while implementation of conventional pH determination approaches may lead to significant errors. In this work a systematic yet simple methodology for measuring pH in concentrated solutions (dominated by Na(+)/Cl(-)) was developed and evaluated, with the aim of achieving consistency with the Pitzer ion-interaction approach. Results indicate that the addition of 0.75 M of NaCl to NIST buffers, followed by assigning a new standard pH (calculated based on the Pitzer approach), enabled reducing measured errors to below 0.03 pH units in seawater RO brines (ionic strength up to 2 M). To facilitate its use, the method was developed to be both conceptually and practically analogous to the conventional pH measurement procedure. The method was used to measure the pH of seawater RO retentates obtained at varying recovery ratios. The results matched better the pH values predicted by an accurate RO transport model. Calibrating the model by the measured pH values enabled better boron transport prediction. A Donnan-induced phenomenon, affecting pH in both retentate and permeate streams, was identified and quantified. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. A POD reduced order model for resolving angular direction in neutron/photon transport problems

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Buchan, A.G., E-mail: andrew.buchan@imperial.ac.uk; Calloo, A.A.; Goffin, M.G.

    2015-09-01

    This article presents the first Reduced Order Model (ROM) that efficiently resolves the angular dimension of the time independent, mono-energetic Boltzmann Transport Equation (BTE). It is based on Proper Orthogonal Decomposition (POD) and uses the method of snapshots to form optimal basis functions for resolving the direction of particle travel in neutron/photon transport problems. A unique element of this work is that the snapshots are formed from the vector of angular coefficients relating to a high resolution expansion of the BTE's angular dimension. In addition, the individual snapshots are not recorded through time, as in standard POD, but instead theymore » are recorded through space. In essence this work swaps the roles of the dimensions space and time in standard POD methods, with angle and space respectively. It is shown here how the POD model can be formed from the POD basis functions in a highly efficient manner. The model is then applied to two radiation problems; one involving the transport of radiation through a shield and the other through an infinite array of pins. Both problems are selected for their complex angular flux solutions in order to provide an appropriate demonstration of the model's capabilities. It is shown that the POD model can resolve these fluxes efficiently and accurately. In comparison to high resolution models this POD model can reduce the size of a problem by up to two orders of magnitude without compromising accuracy. Solving times are also reduced by similar factors.« less

  15. An accurate and efficient laser-envelope solver for the modeling of laser-plasma accelerators

    DOE PAGES

    Benedetti, C.; Schroeder, C. B.; Geddes, C. G. R.; ...

    2017-10-17

    Detailed and reliable numerical modeling of laser-plasma accelerators (LPAs), where a short and intense laser pulse interacts with an underdense plasma over distances of up to a meter, is a formidably challenging task. This is due to the great disparity among the length scales involved in the modeling, ranging from the micron scale of the laser wavelength to the meter scale of the total laser-plasma interaction length. The use of the time-averaged ponderomotive force approximation, where the laser pulse is described by means of its envelope, enables efficient modeling of LPAs by removing the need to model the details ofmore » electron motion at the laser wavelength scale. Furthermore, it allows simulations in cylindrical geometry which captures relevant 3D physics at 2D computational cost. A key element of any code based on the time-averaged ponderomotive force approximation is the laser envelope solver. In this paper we present the accurate and efficient envelope solver used in the code INF & RNO (INtegrated Fluid & paRticle simulatioN cOde). The features of the INF & RNO laser solver enable an accurate description of the laser pulse evolution deep into depletion even at a reasonably low resolution, resulting in significant computational speed-ups.« less

  16. An accurate and efficient laser-envelope solver for the modeling of laser-plasma accelerators

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Benedetti, C.; Schroeder, C. B.; Geddes, C. G. R.

    Detailed and reliable numerical modeling of laser-plasma accelerators (LPAs), where a short and intense laser pulse interacts with an underdense plasma over distances of up to a meter, is a formidably challenging task. This is due to the great disparity among the length scales involved in the modeling, ranging from the micron scale of the laser wavelength to the meter scale of the total laser-plasma interaction length. The use of the time-averaged ponderomotive force approximation, where the laser pulse is described by means of its envelope, enables efficient modeling of LPAs by removing the need to model the details ofmore » electron motion at the laser wavelength scale. Furthermore, it allows simulations in cylindrical geometry which captures relevant 3D physics at 2D computational cost. A key element of any code based on the time-averaged ponderomotive force approximation is the laser envelope solver. In this paper we present the accurate and efficient envelope solver used in the code INF & RNO (INtegrated Fluid & paRticle simulatioN cOde). The features of the INF & RNO laser solver enable an accurate description of the laser pulse evolution deep into depletion even at a reasonably low resolution, resulting in significant computational speed-ups.« less

  17. An accurate and efficient laser-envelope solver for the modeling of laser-plasma accelerators

    NASA Astrophysics Data System (ADS)

    Benedetti, C.; Schroeder, C. B.; Geddes, C. G. R.; Esarey, E.; Leemans, W. P.

    2018-01-01

    Detailed and reliable numerical modeling of laser-plasma accelerators (LPAs), where a short and intense laser pulse interacts with an underdense plasma over distances of up to a meter, is a formidably challenging task. This is due to the great disparity among the length scales involved in the modeling, ranging from the micron scale of the laser wavelength to the meter scale of the total laser-plasma interaction length. The use of the time-averaged ponderomotive force approximation, where the laser pulse is described by means of its envelope, enables efficient modeling of LPAs by removing the need to model the details of electron motion at the laser wavelength scale. Furthermore, it allows simulations in cylindrical geometry which captures relevant 3D physics at 2D computational cost. A key element of any code based on the time-averaged ponderomotive force approximation is the laser envelope solver. In this paper we present the accurate and efficient envelope solver used in the code INF&RNO (INtegrated Fluid & paRticle simulatioN cOde). The features of the INF&RNO laser solver enable an accurate description of the laser pulse evolution deep into depletion even at a reasonably low resolution, resulting in significant computational speed-ups.

  18. An accurate behavioral model for single-photon avalanche diode statistical performance simulation

    NASA Astrophysics Data System (ADS)

    Xu, Yue; Zhao, Tingchen; Li, Ding

    2018-01-01

    An accurate behavioral model is presented to simulate important statistical performance of single-photon avalanche diodes (SPADs), such as dark count and after-pulsing noise. The derived simulation model takes into account all important generation mechanisms of the two kinds of noise. For the first time, thermal agitation, trap-assisted tunneling and band-to-band tunneling mechanisms are simultaneously incorporated in the simulation model to evaluate dark count behavior of SPADs fabricated in deep sub-micron CMOS technology. Meanwhile, a complete carrier trapping and de-trapping process is considered in afterpulsing model and a simple analytical expression is derived to estimate after-pulsing probability. In particular, the key model parameters of avalanche triggering probability and electric field dependence of excess bias voltage are extracted from Geiger-mode TCAD simulation and this behavioral simulation model doesn't include any empirical parameters. The developed SPAD model is implemented in Verilog-A behavioral hardware description language and successfully operated on commercial Cadence Spectre simulator, showing good universality and compatibility. The model simulation results are in a good accordance with the test data, validating high simulation accuracy.

  19. Reduced Moment-Based Models for Oxygen Precipitates and Dislocation Loops in Silicon

    NASA Astrophysics Data System (ADS)

    Trzynadlowski, Bart

    The demand for ever smaller, higher-performance integrated circuits and more efficient, cost-effective solar cells continues to push the frontiers of process technology. Fabrication of silicon devices requires extremely precise control of impurities and crystallographic defects. Failure to do so not only reduces performance, efficiency, and yield, it threatens the very survival of commercial enterprises in today's fiercely competitive and price-sensitive global market. The presence of oxygen in silicon is an unavoidable consequence of the Czochralski process, which remains the most popular method for large-scale production of single-crystal silicon. Oxygen precipitates that form during thermal processing cause distortion of the surrounding silicon lattice and can lead to the formation of dislocation loops. Localized deformation caused by both of these defects introduces potential wells that trap diffusing impurities such as metal atoms, which is highly desirable if done far away from sensitive device regions. Unfortunately, dislocations also reduce the mechanical strength of silicon, which can cause wafer warpage and breakage. Engineers must negotiate this and other complex tradeoffs when designing fabrication processes. Accomplishing this in a complex, modern process involving a large number of thermal steps is impossible without the aid of computational models. In this dissertation, new models for oxygen precipitation and dislocation loop evolution are described. An oxygen model using kinetic rate equations to evolve the complete precipitate size distribution was developed first. This was then used to create a reduced model tracking only the moments of the size distribution. The moment-based model was found to run significantly faster than its full counterpart while accurately capturing the evolution of oxygen precipitates. The reduced model was fitted to experimental data and a sensitivity analysis was performed to assess the robustness of the results. Source

  20. A computationally fast, reduced model for simulating landslide dynamics and tsunamis generated by landslides in natural terrains

    NASA Astrophysics Data System (ADS)

    Mohammed, F.

    2016-12-01

    Landslide hazards such as fast-moving debris flows, slow-moving landslides, and other mass flows cause numerous fatalities, injuries, and damage. Landslide occurrences in fjords, bays, and lakes can additionally generate tsunamis with locally extremely high wave heights and runups. Two-dimensional depth-averaged models can successfully simulate the entire lifecycle of the three-dimensional landslide dynamics and tsunami propagation efficiently and accurately with the appropriate assumptions. Landslide rheology is defined using viscous fluids, visco-plastic fluids, and granular material to account for the possible landslide source materials. Saturated and unsaturated rheologies are further included to simulate debris flow, debris avalanches, mudflows, and rockslides respectively. The models are obtained by reducing the fully three-dimensional Navier-Stokes equations with the internal rheological definition of the landslide material, the water body, and appropriate scaling assumptions to obtain the depth-averaged two-dimensional models. The landslide and tsunami models are coupled to include the interaction between the landslide and the water body for tsunami generation. The reduced models are solved numerically with a fast semi-implicit finite-volume, shock-capturing based algorithm. The well-balanced, positivity preserving algorithm accurately accounts for wet-dry interface transition for the landslide runout, landslide-water body interface, and the tsunami wave flooding on land. The models are implemented as a General-Purpose computing on Graphics Processing Unit-based (GPGPU) suite of models, either coupled or run independently within the suite. The GPGPU implementation provides up to 1000 times speedup over a CPU-based serial computation. This enables simulations of multiple scenarios of hazard realizations that provides a basis for a probabilistic hazard assessment. The models have been successfully validated against experiments, past studies, and field data

  1. Double Cluster Heads Model for Secure and Accurate Data Fusion in Wireless Sensor Networks

    PubMed Central

    Fu, Jun-Song; Liu, Yun

    2015-01-01

    Secure and accurate data fusion is an important issue in wireless sensor networks (WSNs) and has been extensively researched in the literature. In this paper, by combining clustering techniques, reputation and trust systems, and data fusion algorithms, we propose a novel cluster-based data fusion model called Double Cluster Heads Model (DCHM) for secure and accurate data fusion in WSNs. Different from traditional clustering models in WSNs, two cluster heads are selected after clustering for each cluster based on the reputation and trust system and they perform data fusion independently of each other. Then, the results are sent to the base station where the dissimilarity coefficient is computed. If the dissimilarity coefficient of the two data fusion results exceeds the threshold preset by the users, the cluster heads will be added to blacklist, and the cluster heads must be reelected by the sensor nodes in a cluster. Meanwhile, feedback is sent from the base station to the reputation and trust system, which can help us to identify and delete the compromised sensor nodes in time. Through a series of extensive simulations, we found that the DCHM performed very well in data fusion security and accuracy. PMID:25608211

  2. Regression-based reduced-order models to predict transient thermal output for enhanced geothermal systems

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mudunuru, Maruti Kumar; Karra, Satish; Harp, Dylan Robert

    Reduced-order modeling is a promising approach, as many phenomena can be described by a few parameters/mechanisms. An advantage and attractive aspect of a reduced-order model is that it is computational inexpensive to evaluate when compared to running a high-fidelity numerical simulation. A reduced-order model takes couple of seconds to run on a laptop while a high-fidelity simulation may take couple of hours to run on a high-performance computing cluster. The goal of this paper is to assess the utility of regression-based reduced-order models (ROMs) developed from high-fidelity numerical simulations for predicting transient thermal power output for an enhanced geothermal reservoirmore » while explicitly accounting for uncertainties in the subsurface system and site-specific details. Numerical simulations are performed based on equally spaced values in the specified range of model parameters. Key sensitive parameters are then identified from these simulations, which are fracture zone permeability, well/skin factor, bottom hole pressure, and injection flow rate. We found the fracture zone permeability to be the most sensitive parameter. The fracture zone permeability along with time, are used to build regression-based ROMs for the thermal power output. The ROMs are trained and validated using detailed physics-based numerical simulations. Finally, predictions from the ROMs are then compared with field data. We propose three different ROMs with different levels of model parsimony, each describing key and essential features of the power production curves. The coefficients in the proposed regression-based ROMs are developed by minimizing a non-linear least-squares misfit function using the Levenberg–Marquardt algorithm. The misfit function is based on the difference between numerical simulation data and reduced-order model. ROM-1 is constructed based on polynomials up to fourth order. ROM-1 is able to accurately reproduce the power output of numerical simulations

  3. Regression-based reduced-order models to predict transient thermal output for enhanced geothermal systems

    DOE PAGES

    Mudunuru, Maruti Kumar; Karra, Satish; Harp, Dylan Robert; ...

    2017-07-10

    Reduced-order modeling is a promising approach, as many phenomena can be described by a few parameters/mechanisms. An advantage and attractive aspect of a reduced-order model is that it is computational inexpensive to evaluate when compared to running a high-fidelity numerical simulation. A reduced-order model takes couple of seconds to run on a laptop while a high-fidelity simulation may take couple of hours to run on a high-performance computing cluster. The goal of this paper is to assess the utility of regression-based reduced-order models (ROMs) developed from high-fidelity numerical simulations for predicting transient thermal power output for an enhanced geothermal reservoirmore » while explicitly accounting for uncertainties in the subsurface system and site-specific details. Numerical simulations are performed based on equally spaced values in the specified range of model parameters. Key sensitive parameters are then identified from these simulations, which are fracture zone permeability, well/skin factor, bottom hole pressure, and injection flow rate. We found the fracture zone permeability to be the most sensitive parameter. The fracture zone permeability along with time, are used to build regression-based ROMs for the thermal power output. The ROMs are trained and validated using detailed physics-based numerical simulations. Finally, predictions from the ROMs are then compared with field data. We propose three different ROMs with different levels of model parsimony, each describing key and essential features of the power production curves. The coefficients in the proposed regression-based ROMs are developed by minimizing a non-linear least-squares misfit function using the Levenberg–Marquardt algorithm. The misfit function is based on the difference between numerical simulation data and reduced-order model. ROM-1 is constructed based on polynomials up to fourth order. ROM-1 is able to accurately reproduce the power output of numerical simulations

  4. Approaching system equilibrium with accurate or not accurate feedback information in a two-route system

    NASA Astrophysics Data System (ADS)

    Zhao, Xiao-mei; Xie, Dong-fan; Li, Qi

    2015-02-01

    With the development of intelligent transport system, advanced information feedback strategies have been developed to reduce traffic congestion and enhance the capacity. However, previous strategies provide accurate information to travelers and our simulation results show that accurate information brings negative effects, especially in delay case. Because travelers prefer to the best condition route with accurate information, and delayed information cannot reflect current traffic condition but past. Then travelers make wrong routing decisions, causing the decrease of the capacity and the increase of oscillations and the system deviating from the equilibrium. To avoid the negative effect, bounded rationality is taken into account by introducing a boundedly rational threshold BR. When difference between two routes is less than the BR, routes have equal probability to be chosen. The bounded rationality is helpful to improve the efficiency in terms of capacity, oscillation and the gap deviating from the system equilibrium.

  5. A two-dimensional composite grid numerical model based on the reduced system for oceanography

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Xie, Y.F.; Browning, G.L.; Chesshire, G.

    The proper mathematical limit of a hyperbolic system with multiple time scales, the reduced system, is a system that contains no high-frequency motions and is well posed if suitable boundary conditions are chosen for the initial-boundary value problem. The composite grid method, a robust and efficient grid-generation technique that smoothly and accurately treats general irregular boundaries, is used to approximate the two-dimensional version of the reduced system for oceanography on irregular ocean basins. A change-of-variable technique that substantially increases the accuracy of the model and a method for efficiently solving the elliptic equation for the geopotential are discussed. Numerical resultsmore » are presented for circular and kidney-shaped basins by using a set of analytic solutions constructed in this paper.« less

  6. Accurate atomistic potentials and training sets for boron-nitride nanostructures

    NASA Astrophysics Data System (ADS)

    Tamblyn, Isaac

    Boron nitride nanotubes exhibit exceptional structural, mechanical, and thermal properties. They are optically transparent and have high thermal stability, suggesting a wide range of opportunities for structural reinforcement of materials. Modeling can play an important role in determining the optimal approach to integrating nanotubes into a supporting matrix. Developing accurate, atomistic scale models of such nanoscale interfaces embedded within composites is challenging, however, due to the mismatch of length scales involved. Typical nanotube diameters range from 5-50 nm, with a length as large as a micron (i.e. a relevant length-scale for structural reinforcement). Unlike their carbon-based counterparts, well tested and transferable interatomic force fields are not common for BNNT. In light of this, we have developed an extensive training database of BN rich materials, under conditions relevant for BNNT synthesis and composites based on extensive first principles molecular dynamics simulations. Using this data, we have produced an artificial neural network potential capable of reproducing the accuracy of first principles data at significantly reduced computational cost, allowing for accurate simulation at the much larger length scales needed for composite design.

  7. Wind Farm Flow Modeling using an Input-Output Reduced-Order Model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Annoni, Jennifer; Gebraad, Pieter; Seiler, Peter

    Wind turbines in a wind farm operate individually to maximize their own power regardless of the impact of aerodynamic interactions on neighboring turbines. There is the potential to increase power and reduce overall structural loads by properly coordinating turbines. To perform control design and analysis, a model needs to be of low computational cost, but retains the necessary dynamics seen in high-fidelity models. The objective of this work is to obtain a reduced-order model that represents the full-order flow computed using a high-fidelity model. A variety of methods, including proper orthogonal decomposition and dynamic mode decomposition, can be used tomore » extract the dominant flow structures and obtain a reduced-order model. In this paper, we combine proper orthogonal decomposition with a system identification technique to produce an input-output reduced-order model. This technique is used to construct a reduced-order model of the flow within a two-turbine array computed using a large-eddy simulation.« less

  8. A hamster model for Marburg virus infection accurately recapitulates Marburg hemorrhagic fever

    PubMed Central

    Marzi, Andrea; Banadyga, Logan; Haddock, Elaine; Thomas, Tina; Shen, Kui; Horne, Eva J.; Scott, Dana P.; Feldmann, Heinz; Ebihara, Hideki

    2016-01-01

    Marburg virus (MARV), a close relative of Ebola virus, is the causative agent of a severe human disease known as Marburg hemorrhagic fever (MHF). No licensed vaccine or therapeutic exists to treat MHF, and MARV is therefore classified as a Tier 1 select agent and a category A bioterrorism agent. In order to develop countermeasures against this severe disease, animal models that accurately recapitulate human disease are required. Here we describe the development of a novel, uniformly lethal Syrian golden hamster model of MHF using a hamster-adapted MARV variant Angola. Remarkably, this model displayed almost all of the clinical features of MHF seen in humans and non-human primates, including coagulation abnormalities, hemorrhagic manifestations, petechial rash, and a severely dysregulated immune response. This MHF hamster model represents a powerful tool for further dissecting MARV pathogenesis and accelerating the development of effective medical countermeasures against human MHF. PMID:27976688

  9. A hamster model for Marburg virus infection accurately recapitulates Marburg hemorrhagic fever.

    PubMed

    Marzi, Andrea; Banadyga, Logan; Haddock, Elaine; Thomas, Tina; Shen, Kui; Horne, Eva J; Scott, Dana P; Feldmann, Heinz; Ebihara, Hideki

    2016-12-15

    Marburg virus (MARV), a close relative of Ebola virus, is the causative agent of a severe human disease known as Marburg hemorrhagic fever (MHF). No licensed vaccine or therapeutic exists to treat MHF, and MARV is therefore classified as a Tier 1 select agent and a category A bioterrorism agent. In order to develop countermeasures against this severe disease, animal models that accurately recapitulate human disease are required. Here we describe the development of a novel, uniformly lethal Syrian golden hamster model of MHF using a hamster-adapted MARV variant Angola. Remarkably, this model displayed almost all of the clinical features of MHF seen in humans and non-human primates, including coagulation abnormalities, hemorrhagic manifestations, petechial rash, and a severely dysregulated immune response. This MHF hamster model represents a powerful tool for further dissecting MARV pathogenesis and accelerating the development of effective medical countermeasures against human MHF.

  10. Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break.

    PubMed

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean-Michel; García de Cortázar-Atauri, Iñaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2016-10-01

    The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. The effect of temperature on plant phenology is, however, not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future. © 2016 John Wiley & Sons Ltd.

  11. Strategies for Reduced-Order Models in Uncertainty Quantification of Complex Turbulent Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Qi, Di

    Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are

  12. Fast and accurate focusing analysis of large photon sieve using pinhole ring diffraction model.

    PubMed

    Liu, Tao; Zhang, Xin; Wang, Lingjie; Wu, Yanxiong; Zhang, Jizhen; Qu, Hemeng

    2015-06-10

    In this paper, we developed a pinhole ring diffraction model for the focusing analysis of a large photon sieve. Instead of analyzing individual pinholes, we discuss the focusing of all of the pinholes in a single ring. An explicit equation for the diffracted field of individual pinhole ring has been proposed. We investigated the validity range of this generalized model and analytically describe the sufficient conditions for the validity of this pinhole ring diffraction model. A practical example and investigation reveals the high accuracy of the pinhole ring diffraction model. This simulation method could be used for fast and accurate focusing analysis of a large photon sieve.

  13. Branch and bound algorithm for accurate estimation of analytical isotropic bidirectional reflectance distribution function models.

    PubMed

    Yu, Chanki; Lee, Sang Wook

    2016-05-20

    We present a reliable and accurate global optimization framework for estimating parameters of isotropic analytical bidirectional reflectance distribution function (BRDF) models. This approach is based on a branch and bound strategy with linear programming and interval analysis. Conventional local optimization is often very inefficient for BRDF estimation since its fitting quality is highly dependent on initial guesses due to the nonlinearity of analytical BRDF models. The algorithm presented in this paper employs L1-norm error minimization to estimate BRDF parameters in a globally optimal way and interval arithmetic to derive our feasibility problem and lower bounding function. Our method is developed for the Cook-Torrance model but with several normal distribution functions such as the Beckmann, Berry, and GGX functions. Experiments have been carried out to validate the presented method using 100 isotropic materials from the MERL BRDF database, and our experimental results demonstrate that the L1-norm minimization provides a more accurate and reliable solution than the L2-norm minimization.

  14. Pre-Modeling Ensures Accurate Solid Models

    ERIC Educational Resources Information Center

    Gow, George

    2010-01-01

    Successful solid modeling requires a well-organized design tree. The design tree is a list of all the object's features and the sequential order in which they are modeled. The solid-modeling process is faster and less prone to modeling errors when the design tree is a simple and geometrically logical definition of the modeled object. Few high…

  15. An automatic and accurate method of full heart segmentation from CT image based on linear gradient model

    NASA Astrophysics Data System (ADS)

    Yang, Zili

    2017-07-01

    Heart segmentation is an important auxiliary method in the diagnosis of many heart diseases, such as coronary heart disease and atrial fibrillation, and in the planning of tumor radiotherapy. Most of the existing methods for full heart segmentation treat the heart as a whole part and cannot accurately extract the bottom of the heart. In this paper, we propose a new method based on linear gradient model to segment the whole heart from the CT images automatically and accurately. Twelve cases were tested in order to test this method and accurate segmentation results were achieved and identified by clinical experts. The results can provide reliable clinical support.

  16. An accurate fatigue damage model for welded joints subjected to variable amplitude loading

    NASA Astrophysics Data System (ADS)

    Aeran, A.; Siriwardane, S. C.; Mikkelsen, O.; Langen, I.

    2017-12-01

    Researchers in the past have proposed several fatigue damage models to overcome the shortcomings of the commonly used Miner’s rule. However, requirements of material parameters or S-N curve modifications restricts their practical applications. Also, application of most of these models under variable amplitude loading conditions have not been found. To overcome these restrictions, a new fatigue damage model is proposed in this paper. The proposed model can be applied by practicing engineers using only the S-N curve given in the standard codes of practice. The model is verified with experimentally derived damage evolution curves for C 45 and 16 Mn and gives better agreement compared to previous models. The model predicted fatigue lives are also in better correlation with experimental results compared to previous models as shown in earlier published work by the authors. The proposed model is applied to welded joints subjected to variable amplitude loadings in this paper. The model given around 8% shorter fatigue lives compared to Eurocode given Miner’s rule. This shows the importance of applying accurate fatigue damage models for welded joints.

  17. Identification of Reduced-Order Thermal Therapy Models Using Thermal MR Images: Theory and Validation

    PubMed Central

    2013-01-01

    In this paper, we develop and validate a method to identify computationally efficient site- and patient-specific models of ultrasound thermal therapies from MR thermal images. The models of the specific absorption rate of the transduced energy and the temperature response of the therapy target are identified in the reduced basis of proper orthogonal decomposition of thermal images, acquired in response to a mild thermal test excitation. The method permits dynamic reidentification of the treatment models during the therapy by recursively utilizing newly acquired images. Such adaptation is particularly important during high-temperature therapies, which are known to substantially and rapidly change tissue properties and blood perfusion. The developed theory was validated for the case of focused ultrasound heating of a tissue phantom. The experimental and computational results indicate that the developed approach produces accurate low-dimensional treatment models despite temporal and spatial noises in MR images and slow image acquisition rate. PMID:22531754

  18. Identification of reduced-order thermal therapy models using thermal MR images: theory and validation.

    PubMed

    Niu, Ran; Skliar, Mikhail

    2012-07-01

    In this paper, we develop and validate a method to identify computationally efficient site- and patient-specific models of ultrasound thermal therapies from MR thermal images. The models of the specific absorption rate of the transduced energy and the temperature response of the therapy target are identified in the reduced basis of proper orthogonal decomposition of thermal images, acquired in response to a mild thermal test excitation. The method permits dynamic reidentification of the treatment models during the therapy by recursively utilizing newly acquired images. Such adaptation is particularly important during high-temperature therapies, which are known to substantially and rapidly change tissue properties and blood perfusion. The developed theory was validated for the case of focused ultrasound heating of a tissue phantom. The experimental and computational results indicate that the developed approach produces accurate low-dimensional treatment models despite temporal and spatial noises in MR images and slow image acquisition rate.

  19. A Two-Phase Space Resection Model for Accurate Topographic Reconstruction from Lunar Imagery with PushbroomScanners

    PubMed Central

    Xu, Xuemiao; Zhang, Huaidong; Han, Guoqiang; Kwan, Kin Chung; Pang, Wai-Man; Fang, Jiaming; Zhao, Gansen

    2016-01-01

    Exterior orientation parameters’ (EOP) estimation using space resection plays an important role in topographic reconstruction for push broom scanners. However, existing models of space resection are highly sensitive to errors in data. Unfortunately, for lunar imagery, the altitude data at the ground control points (GCPs) for space resection are error-prone. Thus, existing models fail to produce reliable EOPs. Motivated by a finding that for push broom scanners, angular rotations of EOPs can be estimated independent of the altitude data and only involving the geographic data at the GCPs, which are already provided, hence, we divide the modeling of space resection into two phases. Firstly, we estimate the angular rotations based on the reliable geographic data using our proposed mathematical model. Then, with the accurate angular rotations, the collinear equations for space resection are simplified into a linear problem, and the global optimal solution for the spatial position of EOPs can always be achieved. Moreover, a certainty term is integrated to penalize the unreliable altitude data for increasing the error tolerance. Experimental results evidence that our model can obtain more accurate EOPs and topographic maps not only for the simulated data, but also for the real data from Chang’E-1, compared to the existing space resection model. PMID:27077855

  20. A Two-Phase Space Resection Model for Accurate Topographic Reconstruction from Lunar Imagery with PushbroomScanners.

    PubMed

    Xu, Xuemiao; Zhang, Huaidong; Han, Guoqiang; Kwan, Kin Chung; Pang, Wai-Man; Fang, Jiaming; Zhao, Gansen

    2016-04-11

    Exterior orientation parameters' (EOP) estimation using space resection plays an important role in topographic reconstruction for push broom scanners. However, existing models of space resection are highly sensitive to errors in data. Unfortunately, for lunar imagery, the altitude data at the ground control points (GCPs) for space resection are error-prone. Thus, existing models fail to produce reliable EOPs. Motivated by a finding that for push broom scanners, angular rotations of EOPs can be estimated independent of the altitude data and only involving the geographic data at the GCPs, which are already provided, hence, we divide the modeling of space resection into two phases. Firstly, we estimate the angular rotations based on the reliable geographic data using our proposed mathematical model. Then, with the accurate angular rotations, the collinear equations for space resection are simplified into a linear problem, and the global optimal solution for the spatial position of EOPs can always be achieved. Moreover, a certainty term is integrated to penalize the unreliable altitude data for increasing the error tolerance. Experimental results evidence that our model can obtain more accurate EOPs and topographic maps not only for the simulated data, but also for the real data from Chang'E-1, compared to the existing space resection model.

  1. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints

    PubMed Central

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-01-01

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108

  2. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints.

    PubMed

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-02-24

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.

  3. Reduced-Order Modeling of 3D Rayleigh-Benard Turbulent Convection

    NASA Astrophysics Data System (ADS)

    Hassanzadeh, Pedram; Grover, Piyush; Nabi, Saleh

    2017-11-01

    Accurate Reduced-Order Models (ROMs) of turbulent geophysical flows have broad applications in science and engineering; for example, to study the climate system or to perform real-time flow control/optimization in energy systems. Here we focus on 3D Rayleigh-Benard turbulent convection at the Rayleigh number of 106 as a prototype for turbulent geophysical flows, which are dominantly buoyancy driven. The purpose of the study is to evaluate and improve the performance of different model reduction techniques using this setting. One-dimensional ROMs for horizontally averaged temperature are calculated using several methods. Specifically, the Linear Response Function (LRF) of the system is calculated from a large DNS dataset using Dynamic Mode Decomposition (DMD) and Fluctuation-Dissipation Theorem (FDT). The LRF is also calculated using the Green's function method of Hassanzadeh and Kuang (2016, J. Atmos. Sci.), which is based on using numerous forced DNS runs. The performance of these LRFs in estimating the system's response to weak external forcings or controlling the time-mean flow are compared and contrasted. The spectral properties of the LRFs and the scaling of the accuracy with the length of the dataset (for the data-driven methods) are also discussed.

  4. A reduced-dimensional model for near-wall transport in cardiovascular flows

    PubMed Central

    Hansen, Kirk B.

    2015-01-01

    Near-wall mass transport plays an important role in many cardiovascular processes, including the initiation of atherosclerosis, endothelial cell vasoregulation, and thrombogenesis. These problems are characterized by large Péclet and Schmidt numbers as well as a wide range of spatial and temporal scales, all of which impose computational difficulties. In this work, we develop an analytical relationship between the flow field and near-wall mass transport for high-Schmidt-number flows. This allows for the development of a wall-shear-stress-driven transport equation that lies on a codimension-one vessel-wall surface, significantly reducing computational cost in solving the transport problem. Separate versions of this equation are developed for the reaction-rate-limited and transport-limited cases, and numerical results in an idealized abdominal aortic aneurysm are compared to those obtained by solving the full transport equations over the entire domain. The reaction-rate-limited model matches the expected results well. The transport-limited model is accurate in the developed flow regions, but overpredicts wall flux at entry regions and reattachment points in the flow. PMID:26298313

  5. Accurate pointing of tungsten welding electrodes

    NASA Technical Reports Server (NTRS)

    Ziegelmeier, P.

    1971-01-01

    Thoriated-tungsten is pointed accurately and quickly by using sodium nitrite. Point produced is smooth and no effort is necessary to hold the tungsten rod concentric. The chemically produced point can be used several times longer than ground points. This method reduces time and cost of preparing tungsten electrodes.

  6. Development of a Reduced-Order Model for Reacting Gas-Solids Flow using Proper Orthogonal Decomposition

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    McDaniel, Dwayne; Dulikravich, George; Cizmas, Paul

    2017-11-27

    This report summarizes the objectives, tasks and accomplishments made during the three year duration of this research project. The report presents the results obtained by applying advanced computational techniques to develop reduced-order models (ROMs) in the case of reacting multiphase flows based on high fidelity numerical simulation of gas-solids flow structures in risers and vertical columns obtained by the Multiphase Flow with Interphase eXchanges (MFIX) software. The research includes a numerical investigation of reacting and non-reacting gas-solids flow systems and computational analysis that will involve model development to accelerate the scale-up process for the design of fluidization systems by providingmore » accurate solutions that match the full-scale models. The computational work contributes to the development of a methodology for obtaining ROMs that is applicable to the system of gas-solid flows. Finally, the validity of the developed ROMs is evaluated by comparing the results against those obtained using the MFIX code. Additionally, the robustness of existing POD-based ROMs for multiphase flows is improved by avoiding non-physical solutions of the gas void fraction and ensuring that the reduced kinetics models used for reactive flows in fluidized beds are thermodynamically consistent.« less

  7. Model predictive control based on reduced order models applied to belt conveyor system.

    PubMed

    Chen, Wei; Li, Xin

    2016-11-01

    In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Communication: Accurate higher-order van der Waals coefficients between molecules from a model dynamic multipole polarizability

    DOE PAGES

    Tao, Jianmin; Rappe, Andrew M.

    2016-01-20

    Due to the absence of the long-range van der Waals (vdW) interaction, conventional density functional theory (DFT) often fails in the description of molecular complexes and solids. In recent years, considerable progress has been made in the development of the vdW correction. However, the vdW correction based on the leading-order coefficient C 6 alone can only achieve limited accuracy, while accurate modeling of higher-order coefficients remains a formidable task, due to the strong non-additivity effect. Here, we apply a model dynamic multipole polarizability within a modified single-frequency approximation to calculate C 8 and C 10 between small molecules. We findmore » that the higher-order vdW coefficients from this model can achieve remarkable accuracy, with mean absolute relative deviations of 5% for C 8 and 7% for C 10. As a result, inclusion of accurate higher-order contributions in the vdW correction will effectively enhance the predictive power of DFT in condensed matter physics and quantum chemistry.« less

  9. Developments toward more accurate molecular modeling of liquids

    NASA Astrophysics Data System (ADS)

    Evans, Tom J.

    2000-12-01

    The general goal of this research has been to improve upon existing combined quantum mechanics/molecular mechanics (QM/MM) methodologies. Error weighting functions have been introduced into the perturbative Monte Carlo (PMC) method for use with QM/MM. The PMC approach, introduced earlier, provides a means to reduce the number of full self-consistent field (SCF) calculations in simulations using the QM/MM potential by evoking perturbation theory to calculate energy changes due to displacements of a MM molecule. This will allow the ab initio QM/MM approach to be applied to systems that require more advanced, computationally demanding treatments of the QM and/or MM regions. Efforts have also been made to improve the accuracy of the representation of the solvent molecules usually represented by MM force fields. Results from an investigation of the applicability of the embedded density functional theory (EDFT) for studying physical properties of solutions will be presented. In this approach, the solute wavefunction is solved self- consistently in the field of individually frozen electron-density solvent molecules. To test its accuracy, the potential curves for interactions between Li+, Cl- and H2O with a single frozen-density H 2O molecule in different orientations have been calculated. With the development of the more sophisticated effective fragment potential (EFP) representation of solvent molecules, a QM/EFP technique was created. This hybrid QM/EFP approach was used to investigate the solvation of Li + by small clusters of water, as a test case for larger ionic dusters. The EFP appears to provide an accurate representation of the strong interactions that exist between Li+ and H2O. With the QM/EFP methodology comes an increased computational expense, resulting in an even greater need to rely on the PMC approach. However, while including the PMC into the hybrid QM/EFP technique, it was discovered that the previous implementation of the PMC was done incorrectly

  10. A Critical Review for Developing Accurate and Dynamic Predictive Models Using Machine Learning Methods in Medicine and Health Care.

    PubMed

    Alanazi, Hamdan O; Abdullah, Abdul Hanan; Qureshi, Kashif Naseer

    2017-04-01

    Recently, Artificial Intelligence (AI) has been used widely in medicine and health care sector. In machine learning, the classification or prediction is a major field of AI. Today, the study of existing predictive models based on machine learning methods is extremely active. Doctors need accurate predictions for the outcomes of their patients' diseases. In addition, for accurate predictions, timing is another significant factor that influences treatment decisions. In this paper, existing predictive models in medicine and health care have critically reviewed. Furthermore, the most famous machine learning methods have explained, and the confusion between a statistical approach and machine learning has clarified. A review of related literature reveals that the predictions of existing predictive models differ even when the same dataset is used. Therefore, existing predictive models are essential, and current methods must be improved.

  11. Cross hole GPR traveltime inversion using a fast and accurate neural network as a forward model

    NASA Astrophysics Data System (ADS)

    Mejer Hansen, Thomas

    2017-04-01

    Probabilistic formulated inverse problems can be solved using Monte Carlo based sampling methods. In principle both advanced prior information, such as based on geostatistics, and complex non-linear forward physical models can be considered. However, in practice these methods can be associated with huge computational costs that in practice limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error, that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival travel time inversion of cross hole ground-penetrating radar (GPR) data. An accurate forward model, based on 2D full-waveform modeling followed by automatic travel time picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the full forward model, and considerably faster, and more accurate, than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of the types of inverse problems that can be solved using non-linear Monte Carlo sampling techniques.

  12. Can hydraulic-modelled rating curves reduce uncertainty in high flow data?

    NASA Astrophysics Data System (ADS)

    Westerberg, Ida; Lam, Norris; Lyon, Steve W.

    2017-04-01

    Flood risk assessments rely on accurate discharge data records. Establishing a reliable rating curve for calculating discharge from stage at a gauging station normally takes years of data collection efforts. Estimation of high flows is particularly difficult as high flows occur rarely and are often practically difficult to gauge. Hydraulically-modelled rating curves can be derived based on as few as two concurrent stage-discharge and water-surface slope measurements at different flow conditions. This means that a reliable rating curve can, potentially, be derived much faster than a traditional rating curve based on numerous stage-discharge gaugings. In this study we compared the uncertainty in discharge data that resulted from these two rating curve modelling approaches. We applied both methods to a Swedish catchment, accounting for uncertainties in the stage-discharge gauging and water-surface slope data for the hydraulic model and in the stage-discharge gauging data and rating-curve parameters for the traditional method. We focused our analyses on high-flow uncertainty and the factors that could reduce this uncertainty. In particular, we investigated which data uncertainties were most important, and at what flow conditions the gaugings should preferably be taken. First results show that the hydraulically-modelled rating curves were more sensitive to uncertainties in the calibration measurements of discharge than water surface slope. The uncertainty of the hydraulically-modelled rating curves were lowest within the range of the three calibration stage-discharge gaugings (i.e. between median and two-times median flow) whereas uncertainties were higher outside of this range. For instance, at the highest observed stage of the 24-year stage record, the 90% uncertainty band was -15% to +40% of the official rating curve. Additional gaugings at high flows (i.e. four to five times median flow) would likely substantially reduce those uncertainties. These first results show

  13. Model diagnostics in reduced-rank estimation

    PubMed Central

    Chen, Kun

    2016-01-01

    Reduced-rank methods are very popular in high-dimensional multivariate analysis for conducting simultaneous dimension reduction and model estimation. However, the commonly-used reduced-rank methods are not robust, as the underlying reduced-rank structure can be easily distorted by only a few data outliers. Anomalies are bound to exist in big data problems, and in some applications they themselves could be of the primary interest. While naive residual analysis is often inadequate for outlier detection due to potential masking and swamping, robust reduced-rank estimation approaches could be computationally demanding. Under Stein's unbiased risk estimation framework, we propose a set of tools, including leverage score and generalized information score, to perform model diagnostics and outlier detection in large-scale reduced-rank estimation. The leverage scores give an exact decomposition of the so-called model degrees of freedom to the observation level, which lead to exact decomposition of many commonly-used information criteria; the resulting quantities are thus named information scores of the observations. The proposed information score approach provides a principled way of combining the residuals and leverage scores for anomaly detection. Simulation studies confirm that the proposed diagnostic tools work well. A pattern recognition example with hand-writing digital images and a time series analysis example with monthly U.S. macroeconomic data further demonstrate the efficacy of the proposed approaches. PMID:28003860

  14. Model diagnostics in reduced-rank estimation.

    PubMed

    Chen, Kun

    2016-01-01

    Reduced-rank methods are very popular in high-dimensional multivariate analysis for conducting simultaneous dimension reduction and model estimation. However, the commonly-used reduced-rank methods are not robust, as the underlying reduced-rank structure can be easily distorted by only a few data outliers. Anomalies are bound to exist in big data problems, and in some applications they themselves could be of the primary interest. While naive residual analysis is often inadequate for outlier detection due to potential masking and swamping, robust reduced-rank estimation approaches could be computationally demanding. Under Stein's unbiased risk estimation framework, we propose a set of tools, including leverage score and generalized information score, to perform model diagnostics and outlier detection in large-scale reduced-rank estimation. The leverage scores give an exact decomposition of the so-called model degrees of freedom to the observation level, which lead to exact decomposition of many commonly-used information criteria; the resulting quantities are thus named information scores of the observations. The proposed information score approach provides a principled way of combining the residuals and leverage scores for anomaly detection. Simulation studies confirm that the proposed diagnostic tools work well. A pattern recognition example with hand-writing digital images and a time series analysis example with monthly U.S. macroeconomic data further demonstrate the efficacy of the proposed approaches.

  15. Improved image quality in pinhole SPECT by accurate modeling of the point spread function in low magnification systems

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Pino, Francisco; Roé, Nuria; Aguiar, Pablo, E-mail: pablo.aguiar.fernandez@sergas.es

    2015-02-15

    Purpose: Single photon emission computed tomography (SPECT) has become an important noninvasive imaging technique in small-animal research. Due to the high resolution required in small-animal SPECT systems, the spatially variant system response needs to be included in the reconstruction algorithm. Accurate modeling of the system response should result in a major improvement in the quality of reconstructed images. The aim of this study was to quantitatively assess the impact that an accurate modeling of spatially variant collimator/detector response has on image-quality parameters, using a low magnification SPECT system equipped with a pinhole collimator and a small gamma camera. Methods: Threemore » methods were used to model the point spread function (PSF). For the first, only the geometrical pinhole aperture was included in the PSF. For the second, the septal penetration through the pinhole collimator was added. In the third method, the measured intrinsic detector response was incorporated. Tomographic spatial resolution was evaluated and contrast, recovery coefficients, contrast-to-noise ratio, and noise were quantified using a custom-built NEMA NU 4–2008 image-quality phantom. Results: A high correlation was found between the experimental data corresponding to intrinsic detector response and the fitted values obtained by means of an asymmetric Gaussian distribution. For all PSF models, resolution improved as the distance from the point source to the center of the field of view increased and when the acquisition radius diminished. An improvement of resolution was observed after a minimum of five iterations when the PSF modeling included more corrections. Contrast, recovery coefficients, and contrast-to-noise ratio were better for the same level of noise in the image when more accurate models were included. Ring-type artifacts were observed when the number of iterations exceeded 12. Conclusions: Accurate modeling of the PSF improves resolution, contrast, and

  16. Do dual-route models accurately predict reading and spelling performance in individuals with acquired alexia and agraphia?

    PubMed

    Rapcsak, Steven Z; Henry, Maya L; Teague, Sommer L; Carnahan, Susan D; Beeson, Pélagie M

    2007-06-18

    Coltheart and co-workers [Castles, A., Bates, T. C., & Coltheart, M. (2006). John Marshall and the developmental dyslexias. Aphasiology, 20, 871-892; Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J. (2001). DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108, 204-256] have demonstrated that an equation derived from dual-route theory accurately predicts reading performance in young normal readers and in children with reading impairment due to developmental dyslexia or stroke. In this paper, we present evidence that the dual-route equation and a related multiple regression model also accurately predict both reading and spelling performance in adult neurological patients with acquired alexia and agraphia. These findings provide empirical support for dual-route theories of written language processing.

  17. Fast and accurate computation of system matrix for area integral model-based algebraic reconstruction technique

    NASA Astrophysics Data System (ADS)

    Zhang, Shunli; Zhang, Dinghua; Gong, Hao; Ghasemalizadeh, Omid; Wang, Ge; Cao, Guohua

    2014-11-01

    Iterative algorithms, such as the algebraic reconstruction technique (ART), are popular for image reconstruction. For iterative reconstruction, the area integral model (AIM) is more accurate for better reconstruction quality than the line integral model (LIM). However, the computation of the system matrix for AIM is more complex and time-consuming than that for LIM. Here, we propose a fast and accurate method to compute the system matrix for AIM. First, we calculate the intersection of each boundary line of a narrow fan-beam with pixels in a recursive and efficient manner. Then, by grouping the beam-pixel intersection area into six types according to the slopes of the two boundary lines, we analytically compute the intersection area of the narrow fan-beam with the pixels in a simple algebraic fashion. Overall, experimental results show that our method is about three times faster than the Siddon algorithm and about two times faster than the distance-driven model (DDM) in computation of the system matrix. The reconstruction speed of our AIM-based ART is also faster than the LIM-based ART that uses the Siddon algorithm and DDM-based ART, for one iteration. The fast reconstruction speed of our method was accomplished without compromising the image quality.

  18. Intra-patient comparison of reduced-dose model-based iterative reconstruction with standard-dose adaptive statistical iterative reconstruction in the CT diagnosis and follow-up of urolithiasis.

    PubMed

    Tenant, Sean; Pang, Chun Lap; Dissanayake, Prageeth; Vardhanabhuti, Varut; Stuckey, Colin; Gutteridge, Catherine; Hyde, Christopher; Roobottom, Carl

    2017-10-01

    To evaluate the accuracy of reduced-dose CT scans reconstructed using a new generation of model-based iterative reconstruction (MBIR) in the imaging of urinary tract stone disease, compared with a standard-dose CT using 30% adaptive statistical iterative reconstruction. This single-institution prospective study recruited 125 patients presenting either with acute renal colic or for follow-up of known urinary tract stones. They underwent two immediately consecutive scans, one at standard dose settings and one at the lowest dose (highest noise index) the scanner would allow. The reduced-dose scans were reconstructed using both ASIR 30% and MBIR algorithms and reviewed independently by two radiologists. Objective and subjective image quality measures as well as diagnostic data were obtained. The reduced-dose MBIR scan was 100% concordant with the reference standard for the assessment of ureteric stones. It was extremely accurate at identifying calculi of 3 mm and above. The algorithm allowed a dose reduction of 58% without any loss of scan quality. A reduced-dose CT scan using MBIR is accurate in acute imaging for renal colic symptoms and for urolithiasis follow-up and allows a significant reduction in dose. • MBIR allows reduced CT dose with similar diagnostic accuracy • MBIR outperforms ASIR when used for the reconstruction of reduced-dose scans • MBIR can be used to accurately assess stones 3 mm and above.

  19. A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance.

    PubMed

    Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu

    2015-09-01

    Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Accurate modeling and inversion of electrical resistivity data in the presence of metallic infrastructure with known location and dimension

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Johnson, Timothy C.; Wellman, Dawn M.

    2015-06-26

    Electrical resistivity tomography (ERT) has been widely used in environmental applications to study processes associated with subsurface contaminants and contaminant remediation. Anthropogenic alterations in subsurface electrical conductivity associated with contamination often originate from highly industrialized areas with significant amounts of buried metallic infrastructure. The deleterious influence of such infrastructure on imaging results generally limits the utility of ERT where it might otherwise prove useful for subsurface investigation and monitoring. In this manuscript we present a method of accurately modeling the effects of buried conductive infrastructure within the forward modeling algorithm, thereby removing them from the inversion results. The method ismore » implemented in parallel using immersed interface boundary conditions, whereby the global solution is reconstructed from a series of well-conditioned partial solutions. Forward modeling accuracy is demonstrated by comparison with analytic solutions. Synthetic imaging examples are used to investigate imaging capabilities within a subsurface containing electrically conductive buried tanks, transfer piping, and well casing, using both well casings and vertical electrode arrays as current sources and potential measurement electrodes. Results show that, although accurate infrastructure modeling removes the dominating influence of buried metallic features, the presence of metallic infrastructure degrades imaging resolution compared to standard ERT imaging. However, accurate imaging results may be obtained if electrodes are appropriately located.« less

  1. Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.

    PubMed

    Yang, Qian; Sing-Long, Carlos A; Reed, Evan J

    2017-08-01

    We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.

  2. Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

    PubMed Central

    Sing-Long, Carlos A.

    2017-01-01

    We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates. PMID:28989618

  3. Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

    DOE PAGES

    Yang, Qian; Sing-Long, Carlos A.; Reed, Evan J.

    2017-06-19

    Here, we propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. Conversely, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our methodmore » on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. Furthermore, we describe a framework in this work that paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.« less

  4. A Mixed Phase Tale: New Ways of using in-situ cloud observations to reduce climate model biases in Southern Ocean

    NASA Astrophysics Data System (ADS)

    Gettelman, A.; Stith, J. L.

    2014-12-01

    Southern ocean clouds are a critical part of the earth's energy budget, and significant biases in the climatology of these clouds exist in models used to predict climate change. We compare in situ measurements of cloud microphysical properties of ice and liquid over the S. Ocean with constrained output from the atmospheric component of an Earth System Model. Observations taken during the HIAPER (the NSF/NCAR G-V aircraft) Pole-to-Pole Observations (HIPPO) multi-year field campaign are compared with simulations from the atmospheric component of the Community Earth System Model (CESM). Remarkably, CESM is able to accurately simulate the locations of cloud formation, and even cloud microphysical properties are comparable between the model and observations. Significantly, the simulations do not predict sufficient supercooled liquid. Altering the model cloud and aerosol processes to better reproduce the observations of supercooled liquid acts to reduce long-standing biases in S. Ocean clouds in CESM, which are typical of other models. Furthermore, sensitivity tests show where better observational constraints on aerosols and cloud microphysics can reduce uncertainty and biases in global models. These results are intended to show how we can connect large scale simulations with field observations in the S. Ocean to better understand Southern Ocean cloud processes and reduce biases in global climate simulations.

  5. Efficient and accurate approach to modeling the microstructure and defect properties of LaCoO3

    NASA Astrophysics Data System (ADS)

    Buckeridge, J.; Taylor, F. H.; Catlow, C. R. A.

    2016-04-01

    Complex perovskite oxides are promising materials for cathode layers in solid oxide fuel cells. Such materials have intricate electronic, magnetic, and crystalline structures that prove challenging to model accurately. We analyze a wide range of standard density functional theory approaches to modeling a highly promising system, the perovskite LaCoO3, focusing on optimizing the Hubbard U parameter to treat the self-interaction of the B-site cation's d states, in order to determine the most appropriate method to study defect formation and the effect of spin on local structure. By calculating structural and electronic properties for different magnetic states we determine that U =4 eV for Co in LaCoO3 agrees best with available experiments. We demonstrate that the generalized gradient approximation (PBEsol +U ) is most appropriate for studying structure versus spin state, while the local density approximation (LDA +U ) is most appropriate for determining accurate energetics for defect properties.

  6. Accurate Modeling of Dark-Field Scattering Spectra of Plasmonic Nanostructures.

    PubMed

    Jiang, Liyong; Yin, Tingting; Dong, Zhaogang; Liao, Mingyi; Tan, Shawn J; Goh, Xiao Ming; Allioux, David; Hu, Hailong; Li, Xiangyin; Yang, Joel K W; Shen, Zexiang

    2015-10-27

    Dark-field microscopy is a widely used tool for measuring the optical resonance of plasmonic nanostructures. However, current numerical methods for simulating the dark-field scattering spectra were carried out with plane wave illumination either at normal incidence or at an oblique angle from one direction. In actual experiments, light is focused onto the sample through an annular ring within a range of glancing angles. In this paper, we present a theoretical model capable of accurately simulating the dark-field light source with an annular ring. Simulations correctly reproduce a counterintuitive blue shift in the scattering spectra from gold nanodisks with a diameter beyond 140 nm. We believe that our proposed simulation method can be potentially applied as a general tool capable of simulating the dark-field scattering spectra of plasmonic nanostructures as well as other dielectric nanostructures with sizes beyond the quasi-static limit.

  7. Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical Calculations

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Dral, Pavlo O.; von Lilienfeld, O. Anatole; Thiel, Walter

    2015-05-12

    We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempiricalmore » OM2 method using a set of 6095 constitutional isomers C7H10O2, for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules.« less

  8. Machine learning of parameters for accurate semiempirical quantum chemical calculations

    DOE PAGES

    Dral, Pavlo O.; von Lilienfeld, O. Anatole; Thiel, Walter

    2015-04-14

    We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempiricalmore » OM2 method using a set of 6095 constitutional isomers C 7H 10O 2, for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules.« less

  9. Adding-point strategy for reduced-order hypersonic aerothermodynamics modeling based on fuzzy clustering

    NASA Astrophysics Data System (ADS)

    Chen, Xin; Liu, Li; Zhou, Sida; Yue, Zhenjiang

    2016-09-01

    Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.

  10. Towards more accurate wind and solar power prediction by improving NWP model physics

    NASA Astrophysics Data System (ADS)

    Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo

    2014-05-01

    The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during

  11. A new algebraic turbulence model for accurate description of airfoil flows

    NASA Astrophysics Data System (ADS)

    Xiao, Meng-Juan; She, Zhen-Su

    2017-11-01

    We report a new algebraic turbulence model (SED-SL) based on the SED theory, a symmetry-based approach to quantifying wall turbulence. The model specifies a multi-layer profile of a stress length (SL) function in both the streamwise and wall-normal directions, which thus define the eddy viscosity in the RANS equation (e.g. a zero-equation model). After a successful simulation of flat plate flow (APS meeting, 2016), we report here further applications of the model to the flow around airfoil, with significant improvement of the prediction accuracy of the lift (CL) and drag (CD) coefficients compared to other popular models (e.g. BL, SA, etc.). Two airfoils, namely RAE2822 airfoil and NACA0012 airfoil, are computed for over 50 cases. The results are compared to experimental data from AGARD report, which shows deviations of CL bounded within 2%, and CD within 2 counts (10-4) for RAE2822 and 6 counts for NACA0012 respectively (under a systematic adjustment of the flow conditions). In all these calculations, only one parameter (proportional to the Karmen constant) shows slight variation with Mach number. The most remarkable outcome is, for the first time, the accurate prediction of the drag coefficient. The other interesting outcome is the physical interpretation of the multi-layer parameters: they specify the corresponding multi-layer structure of turbulent boundary layer; when used together with simulation data, the SED-SL enables one to extract physical information from empirical data, and to understand the variation of the turbulent boundary layer.

  12. Towards accurate modeling of noncovalent interactions for protein rigidity analysis.

    PubMed

    Fox, Naomi; Streinu, Ileana

    2013-01-01

    Protein rigidity analysis is an efficient computational method for extracting flexibility information from static, X-ray crystallography protein data. Atoms and bonds are modeled as a mechanical structure and analyzed with a fast graph-based algorithm, producing a decomposition of the flexible molecule into interconnected rigid clusters. The result depends critically on noncovalent atomic interactions, primarily on how hydrogen bonds and hydrophobic interactions are computed and modeled. Ongoing research points to the stringent need for benchmarking rigidity analysis software systems, towards the goal of increasing their accuracy and validating their results, either against each other and against biologically relevant (functional) parameters. We propose two new methods for modeling hydrogen bonds and hydrophobic interactions that more accurately reflect a mechanical model, without being computationally more intensive. We evaluate them using a novel scoring method, based on the B-cubed score from the information retrieval literature, which measures how well two cluster decompositions match. To evaluate the modeling accuracy of KINARI, our pebble-game rigidity analysis system, we use a benchmark data set of 20 proteins, each with multiple distinct conformations deposited in the Protein Data Bank. Cluster decompositions for them were previously determined with the RigidFinder method from Gerstein's lab and validated against experimental data. When KINARI's default tuning parameters are used, an improvement of the B-cubed score over a crude baseline is observed in 30% of this data. With our new modeling options, improvements were observed in over 70% of the proteins in this data set. We investigate the sensitivity of the cluster decomposition score with case studies on pyruvate phosphate dikinase and calmodulin. To substantially improve the accuracy of protein rigidity analysis systems, thorough benchmarking must be performed on all current systems and future

  13. Towards accurate modeling of noncovalent interactions for protein rigidity analysis

    PubMed Central

    2013-01-01

    Background Protein rigidity analysis is an efficient computational method for extracting flexibility information from static, X-ray crystallography protein data. Atoms and bonds are modeled as a mechanical structure and analyzed with a fast graph-based algorithm, producing a decomposition of the flexible molecule into interconnected rigid clusters. The result depends critically on noncovalent atomic interactions, primarily on how hydrogen bonds and hydrophobic interactions are computed and modeled. Ongoing research points to the stringent need for benchmarking rigidity analysis software systems, towards the goal of increasing their accuracy and validating their results, either against each other and against biologically relevant (functional) parameters. We propose two new methods for modeling hydrogen bonds and hydrophobic interactions that more accurately reflect a mechanical model, without being computationally more intensive. We evaluate them using a novel scoring method, based on the B-cubed score from the information retrieval literature, which measures how well two cluster decompositions match. Results To evaluate the modeling accuracy of KINARI, our pebble-game rigidity analysis system, we use a benchmark data set of 20 proteins, each with multiple distinct conformations deposited in the Protein Data Bank. Cluster decompositions for them were previously determined with the RigidFinder method from Gerstein's lab and validated against experimental data. When KINARI's default tuning parameters are used, an improvement of the B-cubed score over a crude baseline is observed in 30% of this data. With our new modeling options, improvements were observed in over 70% of the proteins in this data set. We investigate the sensitivity of the cluster decomposition score with case studies on pyruvate phosphate dikinase and calmodulin. Conclusion To substantially improve the accuracy of protein rigidity analysis systems, thorough benchmarking must be performed on all

  14. Reduced-Order Modeling: New Approaches for Computational Physics

    NASA Technical Reports Server (NTRS)

    Beran, Philip S.; Silva, Walter A.

    2001-01-01

    In this paper, we review the development of new reduced-order modeling techniques and discuss their applicability to various problems in computational physics. Emphasis is given to methods ba'sed on Volterra series representations and the proper orthogonal decomposition. Results are reported for different nonlinear systems to provide clear examples of the construction and use of reduced-order models, particularly in the multi-disciplinary field of computational aeroelasticity. Unsteady aerodynamic and aeroelastic behaviors of two- dimensional and three-dimensional geometries are described. Large increases in computational efficiency are obtained through the use of reduced-order models, thereby justifying the initial computational expense of constructing these models and inotivatim,- their use for multi-disciplinary design analysis.

  15. Cumulative atomic multipole moments complement any atomic charge model to obtain more accurate electrostatic properties

    NASA Technical Reports Server (NTRS)

    Sokalski, W. A.; Shibata, M.; Ornstein, R. L.; Rein, R.

    1992-01-01

    The quality of several atomic charge models based on different definitions has been analyzed using cumulative atomic multipole moments (CAMM). This formalism can generate higher atomic moments starting from any atomic charges, while preserving the corresponding molecular moments. The atomic charge contribution to the higher molecular moments, as well as to the electrostatic potentials, has been examined for CO and HCN molecules at several different levels of theory. The results clearly show that the electrostatic potential obtained from CAMM expansion is convergent up to R-5 term for all atomic charge models used. This illustrates that higher atomic moments can be used to supplement any atomic charge model to obtain more accurate description of electrostatic properties.

  16. Fast and accurate modeling of stray light in optical systems

    NASA Astrophysics Data System (ADS)

    Perrin, Jean-Claude

    2017-11-01

    The first problem to be solved in most optical designs with respect to stray light is that of internal reflections on the several surfaces of individual lenses and mirrors, and on the detector itself. The level of stray light ratio can be considerably reduced by taking into account the stray light during the optimization to determine solutions in which the irradiance due to these ghosts is kept to the minimum possible value. Unhappily, the routines available in most optical design software's, for example CODE V, do not permit all alone to make exact quantitative calculations of the stray light due to these ghosts. Therefore, the engineer in charge of the optical design is confronted to the problem of using two different software's, one for the design and optimization, for example CODE V, one for stray light analysis, for example ASAP. This makes a complete optimization very complex . Nevertheless, using special techniques and combinations of the routines available in CODE V, it is possible to have at its disposal a software macro tool to do such an analysis quickly and accurately, including Monte-Carlo ray tracing, or taking into account diffraction effects. This analysis can be done in a few minutes, to be compared to hours with other software's.

  17. Calibration of aero-structural reduced order models using full-field experimental measurements

    NASA Astrophysics Data System (ADS)

    Perez, R.; Bartram, G.; Beberniss, T.; Wiebe, R.; Spottswood, S. M.

    2017-03-01

    The structural response of hypersonic aircraft panels is a multi-disciplinary problem, where the nonlinear structural dynamics, aerodynamics, and heat transfer models are coupled. A clear understanding of the impact of high-speed flow effects on the structural response, and the potential influence of the structure on the local environment, is needed in order to prevent the design of overly-conservative structures, a common problem in past hypersonic programs. The current work investigates these challenges from a structures perspective. To this end, the first part of this investigation looks at the modeling of the response of a rectangular panel to an external heating source (thermo-structural coupling) where the temperature effect on the structure is obtained from forward looking infrared (FLIR) measurements and the displacement via 3D-digital image correlation (DIC). The second part of the study uses data from a previous series of wind-tunnel experiments, performed to investigate the response of a compliant panel to the effects of high-speed flow, to train a pressure surrogate model. In this case, the panel aero-loading is obtained from fast-response pressure sensitive paint (PSP) measurements, both directly and from the pressure surrogate model. The result of this investigation is the use of full-field experimental measurements to update the structural model and train a computational efficient model of the loading environment. The use of reduced order models, informed by these full-field physical measurements, is a significant step toward the development of accurate simulation models of complex structures that are computationally tractable.

  18. Predicting laser weld reliability with stochastic reduced-order models. Predicting laser weld reliability

    DOE PAGES

    Emery, John M.; Field, Richard V.; Foulk, James W.; ...

    2015-05-26

    Laser welds are prevalent in complex engineering systems and they frequently govern failure. The weld process often results in partial penetration of the base metals, leaving sharp crack-like features with a high degree of variability in the geometry and material properties of the welded structure. Furthermore, accurate finite element predictions of the structural reliability of components containing laser welds requires the analysis of a large number of finite element meshes with very fine spatial resolution, where each mesh has different geometry and/or material properties in the welded region to address variability. We found that traditional modeling approaches could not bemore » efficiently employed. Consequently, a method is presented for constructing a surrogate model, based on stochastic reduced-order models, and is proposed to represent the laser welds within the component. Here, the uncertainty in weld microstructure and geometry is captured by calibrating plasticity parameters to experimental observations of necking as, because of the ductility of the welds, necking – and thus peak load – plays the pivotal role in structural failure. The proposed method is exercised for a simplified verification problem and compared with the traditional Monte Carlo simulation with rather remarkable results.« less

  19. Reduced-order model for dynamic optimization of pressure swing adsorption processes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Agarwal, A.; Biegler, L.; Zitney, S.

    2007-01-01

    Over the past decades, pressure swing adsorption (PSA) processes have been widely used as energy-efficient gas and liquid separation techniques, especially for high purity hydrogen purification from refinery gases. The separation processes are based on solid-gas equilibrium and operate under periodic transient conditions. Models for PSA processes are therefore multiple instances of partial differential equations (PDEs) in time and space with periodic boundary conditions that link the processing steps together. The solution of this coupled stiff PDE system is governed by steep concentrations and temperature fronts moving with time. As a result, the optimization of such systems for either designmore » or operation represents a significant computational challenge to current differential algebraic equation (DAE) optimization techniques and nonlinear programming algorithms. Model reduction is one approach to generate cost-efficient low-order models which can be used as surrogate models in the optimization problems. The study develops a reduced-order model (ROM) based on proper orthogonal decomposition (POD), which is a low-dimensional approximation to a dynamic PDE-based model. Initially, a representative ensemble of solutions of the dynamic PDE system is constructed by solving a higher-order discretization of the model using the method of lines, a two-stage approach that discretizes the PDEs in space and then integrates the resulting DAEs over time. Next, the ROM method applies the Karhunen-Loeve expansion to derive a small set of empirical eigenfunctions (POD modes) which are used as basis functions within a Galerkin's projection framework to derive a low-order DAE system that accurately describes the dominant dynamics of the PDE system. The proposed method leads to a DAE system of significantly lower order, thus replacing the one obtained from spatial discretization before and making optimization problem computationally-efficient. The method has been applied to the

  20. Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformations.

    PubMed

    Porebski, Przemyslaw Jerzy; Cymborowski, Marcin; Pasenkiewicz-Gierula, Marta; Minor, Wladek

    2016-02-01

    Improvements in crystallographic hardware and software have allowed automated structure-solution pipelines to approach a near-`one-click' experience for the initial determination of macromolecular structures. However, in many cases the resulting initial model requires a laborious, iterative process of refinement and validation. A new method has been developed for the automatic modeling of side-chain conformations that takes advantage of rotamer-prediction methods in a crystallographic context. The algorithm, which is based on deterministic dead-end elimination (DEE) theory, uses new dense conformer libraries and a hybrid energy function derived from experimental data and prior information about rotamer frequencies to find the optimal conformation of each side chain. In contrast to existing methods, which incorporate the electron-density term into protein-modeling frameworks, the proposed algorithm is designed to take advantage of the highly discriminatory nature of electron-density maps. This method has been implemented in the program Fitmunk, which uses extensive conformational sampling. This improves the accuracy of the modeling and makes it a versatile tool for crystallographic model building, refinement and validation. Fitmunk was extensively tested on over 115 new structures, as well as a subset of 1100 structures from the PDB. It is demonstrated that the ability of Fitmunk to model more than 95% of side chains accurately is beneficial for improving the quality of crystallographic protein models, especially at medium and low resolutions. Fitmunk can be used for model validation of existing structures and as a tool to assess whether side chains are modeled optimally or could be better fitted into electron density. Fitmunk is available as a web service at http://kniahini.med.virginia.edu/fitmunk/server/ or at http://fitmunk.bitbucket.org/.

  1. Reduced Order Podolsky Model

    NASA Astrophysics Data System (ADS)

    Thibes, Ronaldo

    2017-02-01

    We perform the canonical and path integral quantizations of a lower-order derivatives model describing Podolsky's generalized electrodynamics. The physical content of the model shows an auxiliary massive vector field coupled to the usual electromagnetic field. The equivalence with Podolsky's original model is studied at classical and quantum levels. Concerning the dynamical time evolution, we obtain a theory with two first-class and two second-class constraints in phase space. We calculate explicitly the corresponding Dirac brackets involving both vector fields. We use the Senjanovic procedure to implement the second-class constraints and the Batalin-Fradkin-Vilkovisky path integral quantization scheme to deal with the symmetries generated by the first-class constraints. The physical interpretation of the results turns out to be simpler due to the reduced derivatives order permeating the equations of motion, Dirac brackets and effective action.

  2. Design of multivariable feedback control systems via spectral assignment using reduced-order models and reduced-order observers

    NASA Technical Reports Server (NTRS)

    Mielke, R. R.; Tung, L. J.; Carraway, P. I., III

    1984-01-01

    The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The full state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system rmain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

  3. Design of multivariable feedback control systems via spectral assignment using reduced-order models and reduced-order observers

    NASA Technical Reports Server (NTRS)

    Mielke, R. R.; Tung, L. J.; Carraway, P. I., III

    1985-01-01

    The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The fulll state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system remain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

  4. Reduced modeling of signal transduction – a modular approach

    PubMed Central

    Koschorreck, Markus; Conzelmann, Holger; Ebert, Sybille; Ederer, Michael; Gilles, Ernst Dieter

    2007-01-01

    Background Combinatorial complexity is a challenging problem in detailed and mechanistic mathematical modeling of signal transduction. This subject has been discussed intensively and a lot of progress has been made within the last few years. A software tool (BioNetGen) was developed which allows an automatic rule-based set-up of mechanistic model equations. In many cases these models can be reduced by an exact domain-oriented lumping technique. However, the resulting models can still consist of a very large number of differential equations. Results We introduce a new reduction technique, which allows building modularized and highly reduced models. Compared to existing approaches further reduction of signal transduction networks is possible. The method also provides a new modularization criterion, which allows to dissect the model into smaller modules that are called layers and can be modeled independently. Hallmarks of the approach are conservation relations within each layer and connection of layers by signal flows instead of mass flows. The reduced model can be formulated directly without previous generation of detailed model equations. It can be understood and interpreted intuitively, as model variables are macroscopic quantities that are converted by rates following simple kinetics. The proposed technique is applicable without using complex mathematical tools and even without detailed knowledge of the mathematical background. However, we provide a detailed mathematical analysis to show performance and limitations of the method. For physiologically relevant parameter domains the transient as well as the stationary errors caused by the reduction are negligible. Conclusion The new layer based reduced modeling method allows building modularized and strongly reduced models of signal transduction networks. Reduced model equations can be directly formulated and are intuitively interpretable. Additionally, the method provides very good approximations especially for

  5. Reduced Order Modeling of Combustion Instability in a Gas Turbine Model Combustor

    NASA Astrophysics Data System (ADS)

    Arnold-Medabalimi, Nicholas; Huang, Cheng; Duraisamy, Karthik

    2017-11-01

    Hydrocarbon fuel based propulsion systems are expected to remain relevant in aerospace vehicles for the foreseeable future. Design of these devices is complicated by combustion instabilities. The capability to model and predict these effects at reduced computational cost is a requirement for both design and control of these devices. This work focuses on computational studies on a dual swirl model gas turbine combustor in the context of reduced order model development. Full fidelity simulations are performed utilizing URANS and Hybrid RANS-LES with finite rate chemistry. Following this, data decomposition techniques are used to extract a reduced basis representation of the unsteady flow field. These bases are first used to identify sensor locations to guide experimental interrogations and controller feedback. Following this, initial results on developing a control-oriented reduced order model (ROM) will be presented. The capability of the ROM will be further assessed based on different operating conditions and geometric configurations.

  6. High-resolution LES of the rotating stall in a reduced scale model pump-turbine

    NASA Astrophysics Data System (ADS)

    Pacot, Olivier; Kato, Chisachi; Avellan, François

    2014-03-01

    Extending the operating range of modern pump-turbines becomes increasingly important in the course of the integration of renewable energy sources in the existing power grid. However, at partial load condition in pumping mode, the occurrence of rotating stall is critical to the operational safety of the machine and on the grid stability. The understanding of the mechanisms behind this flow phenomenon yet remains vague and incomplete. Past numerical simulations using a RANS approach often led to inconclusive results concerning the physical background. For the first time, the rotating stall is investigated by performing a large scale LES calculation on the HYDRODYNA pump-turbine scale model featuring approximately 100 million elements. The computations were performed on the PRIMEHPC FX10 of the University of Tokyo using the overset Finite Element open source code FrontFlow/blue with the dynamic Smagorinsky turbulence model and the no-slip wall condition. The internal flow computed is the one when operating the pump-turbine at 76% of the best efficiency point in pumping mode, as previous experimental research showed the presence of four rotating cells. The rotating stall phenomenon is accurately reproduced for a reduced Reynolds number using the LES approach with acceptable computing resources. The results show an excellent agreement with available experimental data from the reduced scale model testing at the EPFL Laboratory for Hydraulic Machines. The number of stall cells as well as the propagation speed corroborates the experiment.

  7. Controller design via structural reduced modeling by FETM

    NASA Technical Reports Server (NTRS)

    Yousuff, Ajmal

    1987-01-01

    The Finite Element-Transfer Matrix (FETM) method has been developed to reduce the computations involved in analysis of structures. This widely accepted method, however, has certain limitations, and does not address the issues of control design. To overcome these, a modification of the FETM method has been developed. The new method easily produces reduced models tailored toward subsequent control design. Other features of this method are its ability to: (1) extract open loop frequencies and mode shapes with less computations, (2) overcome limitations of the original FETM method, and (3) simplify the design procedures for output feedback, constrained compensation, and decentralized control. This report presents the development of the new method, generation of reduced models by this method, their properties, and the role of these reduced models in control design. Examples are included to illustrate the methodology.

  8. Reduced-Order Model Based Feedback Control For Modified Hasegawa-Wakatani Model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Goumiri, I. R.; Rowley, C. W.; Ma, Z.

    2013-01-28

    In this work, the development of model-based feedback control that stabilizes an unstable equilibrium is obtained for the Modi ed Hasegawa-Wakatani (MHW) equations, a classic model in plasma turbulence. First, a balanced truncation (a model reduction technique that has proven successful in ow control design problems) is applied to obtain a low dimensional model of the linearized MHW equation. Then a modelbased feedback controller is designed for the reduced order model using linear quadratic regulators (LQR). Finally, a linear quadratic gaussian (LQG) controller, which is more resistant to disturbances is deduced. The controller is applied on the non-reduced, nonlinear MHWmore » equations to stabilize the equilibrium and suppress the transition to drift-wave induced turbulence.« less

  9. Fast and accurate Monte Carlo modeling of a kilovoltage X-ray therapy unit using a photon-source approximation for treatment planning in complex media.

    PubMed

    Zeinali-Rafsanjani, B; Mosleh-Shirazi, M A; Faghihi, R; Karbasi, S; Mosalaei, A

    2015-01-01

    To accurately recompute dose distributions in chest-wall radiotherapy with 120 kVp kilovoltage X-rays, an MCNP4C Monte Carlo model is presented using a fast method that obviates the need to fully model the tube components. To validate the model, half-value layer (HVL), percentage depth doses (PDDs) and beam profiles were measured. Dose measurements were performed for a more complex situation using thermoluminescence dosimeters (TLDs) placed within a Rando phantom. The measured and computed first and second HVLs were 3.8, 10.3 mm Al and 3.8, 10.6 mm Al, respectively. The differences between measured and calculated PDDs and beam profiles in water were within 2 mm/2% for all data points. In the Rando phantom, differences for majority of data points were within 2%. The proposed model offered an approximately 9500-fold reduced run time compared to the conventional full simulation. The acceptable agreement, based on international criteria, between the simulations and the measurements validates the accuracy of the model for its use in treatment planning and radiobiological modeling studies of superficial therapies including chest-wall irradiation using kilovoltage beam.

  10. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    DOE PAGES

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; ...

    2013-03-07

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of chargedmore » peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.« less

  11. Accurate characterisation of hole size and location by projected fringe profilometry

    NASA Astrophysics Data System (ADS)

    Wu, Yuxiang; Dantanarayana, Harshana G.; Yue, Huimin; Huntley, Jonathan M.

    2018-06-01

    The ability to accurately estimate the location and geometry of holes is often required in the field of quality control and automated assembly. Projected fringe profilometry is a potentially attractive technique on account of being non-contacting, of lower cost, and orders of magnitude faster than the traditional coordinate measuring machine. However, we demonstrate in this paper that fringe projection is susceptible to significant (hundreds of µm) measurement artefacts in the neighbourhood of hole edges, which give rise to errors of a similar magnitude in the estimated hole geometry. A mechanism for the phenomenon is identified based on the finite size of the imaging system’s point spread function and the resulting bias produced near to sample discontinuities in geometry and reflectivity. A mathematical model is proposed, from which a post-processing compensation algorithm is developed to suppress such errors around the holes. The algorithm includes a robust and accurate sub-pixel edge detection method based on a Fourier descriptor of the hole contour. The proposed algorithm was found to reduce significantly the measurement artefacts near the hole edges. As a result, the errors in estimated hole radius were reduced by up to one order of magnitude, to a few tens of µm for hole radii in the range 2–15 mm, compared to those from the uncompensated measurements.

  12. Anchoring the Population II Distance Scale: Accurate Ages for Globular Clusters

    NASA Technical Reports Server (NTRS)

    Chaboyer, Brian C.; Chaboyer, Brian C.; Carney, Bruce W.; Latham, David W.; Dunca, Douglas; Grand, Terry; Layden, Andy; Sarajedini, Ataollah; McWilliam, Andrew; Shao, Michael

    2004-01-01

    The metal-poor stars in the halo of the Milky Way galaxy were among the first objects formed in our Galaxy. These Population II stars are the oldest objects in the universe whose ages can be accurately determined. Age determinations for these stars allow us to set a firm lower limit, to the age of the universe and to probe the early formation history of the Milky Way. The age of the universe determined from studies of Population II stars may be compared to the expansion age of the universe and used to constrain cosmological models. The largest uncertainty in estimates for the ages of stars in our halo is due to the uncertainty in the distance scale to Population II objects. We propose to obtain accurate parallaxes to a number of Population II objects (globular clusters and field stars in the halo) resulting in a significant improvement in the Population II distance scale and greatly reducing the uncertainty in the estimated ages of the oldest stars in our galaxy. At the present time, the oldest stars are estimated to be 12.8 Gyr old, with an uncertainty of approx. 15%. The SIM observations obtained by this key project, combined with the supporting theoretical research and ground based observations outlined in this proposal will reduce the estimated uncertainty in the age estimates to 5%).

  13. Machine learning to construct reduced-order models and scaling laws for reactive-transport applications

    NASA Astrophysics Data System (ADS)

    Mudunuru, M. K.; Karra, S.; Vesselinov, V. V.

    2017-12-01

    The efficiency of many hydrogeological applications such as reactive-transport and contaminant remediation vastly depends on the macroscopic mixing occurring in the aquifer. In the case of remediation activities, it is fundamental to enhancement and control of the mixing through impact of the structure of flow field which is impacted by groundwater pumping/extraction, heterogeneity, and anisotropy of the flow medium. However, the relative importance of these hydrogeological parameters to understand mixing process is not well studied. This is partially because to understand and quantify mixing, one needs to perform multiple runs of high-fidelity numerical simulations for various subsurface model inputs. Typically, high-fidelity simulations of existing subsurface models take hours to complete on several thousands of processors. As a result, they may not be feasible to study the importance and impact of model inputs on mixing. Hence, there is a pressing need to develop computationally efficient models to accurately predict the desired QoIs for remediation and reactive-transport applications. An attractive way to construct computationally efficient models is through reduced-order modeling using machine learning. These approaches can substantially improve our capabilities to model and predict remediation process. Reduced-Order Models (ROMs) are similar to analytical solutions or lookup tables. However, the method in which ROMs are constructed is different. Here, we present a physics-informed ML framework to construct ROMs based on high-fidelity numerical simulations. First, random forests, F-test, and mutual information are used to evaluate the importance of model inputs. Second, SVMs are used to construct ROMs based on these inputs. These ROMs are then used to understand mixing under perturbed vortex flows. Finally, we construct scaling laws for certain important QoIs such as degree of mixing and product yield. Scaling law parameters dependence on model inputs are

  14. Accurate and efficient modeling of the detector response in small animal multi-head PET systems.

    PubMed

    Cecchetti, Matteo; Moehrs, Sascha; Belcari, Nicola; Del Guerra, Alberto

    2013-10-07

    In fully three-dimensional PET imaging, iterative image reconstruction techniques usually outperform analytical algorithms in terms of image quality provided that an appropriate system model is used. In this study we concentrate on the calculation of an accurate system model for the YAP-(S)PET II small animal scanner, with the aim to obtain fully resolution- and contrast-recovered images at low levels of image roughness. For this purpose we calculate the system model by decomposing it into a product of five matrices: (1) a detector response component obtained via Monte Carlo simulations, (2) a geometric component which describes the scanner geometry and which is calculated via a multi-ray method, (3) a detector normalization component derived from the acquisition of a planar source, (4) a photon attenuation component calculated from x-ray computed tomography data, and finally, (5) a positron range component is formally included. This system model factorization allows the optimization of each component in terms of computation time, storage requirements and accuracy. The main contribution of this work is a new, efficient way to calculate the detector response component for rotating, planar detectors, that consists of a GEANT4 based simulation of a subset of lines of flight (LOFs) for a single detector head whereas the missing LOFs are obtained by using intrinsic detector symmetries. Additionally, we introduce and analyze a probability threshold for matrix elements of the detector component to optimize the trade-off between the matrix size in terms of non-zero elements and the resulting quality of the reconstructed images. In order to evaluate our proposed system model we reconstructed various images of objects, acquired according to the NEMA NU 4-2008 standard, and we compared them to the images reconstructed with two other system models: a model that does not include any detector response component and a model that approximates analytically the depth of interaction

  15. Accurate and efficient modeling of the detector response in small animal multi-head PET systems

    NASA Astrophysics Data System (ADS)

    Cecchetti, Matteo; Moehrs, Sascha; Belcari, Nicola; Del Guerra, Alberto

    2013-10-01

    In fully three-dimensional PET imaging, iterative image reconstruction techniques usually outperform analytical algorithms in terms of image quality provided that an appropriate system model is used. In this study we concentrate on the calculation of an accurate system model for the YAP-(S)PET II small animal scanner, with the aim to obtain fully resolution- and contrast-recovered images at low levels of image roughness. For this purpose we calculate the system model by decomposing it into a product of five matrices: (1) a detector response component obtained via Monte Carlo simulations, (2) a geometric component which describes the scanner geometry and which is calculated via a multi-ray method, (3) a detector normalization component derived from the acquisition of a planar source, (4) a photon attenuation component calculated from x-ray computed tomography data, and finally, (5) a positron range component is formally included. This system model factorization allows the optimization of each component in terms of computation time, storage requirements and accuracy. The main contribution of this work is a new, efficient way to calculate the detector response component for rotating, planar detectors, that consists of a GEANT4 based simulation of a subset of lines of flight (LOFs) for a single detector head whereas the missing LOFs are obtained by using intrinsic detector symmetries. Additionally, we introduce and analyze a probability threshold for matrix elements of the detector component to optimize the trade-off between the matrix size in terms of non-zero elements and the resulting quality of the reconstructed images. In order to evaluate our proposed system model we reconstructed various images of objects, acquired according to the NEMA NU 4-2008 standard, and we compared them to the images reconstructed with two other system models: a model that does not include any detector response component and a model that approximates analytically the depth of interaction

  16. Enforcing elemental mass and energy balances for reduced order models

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ma, J.; Agarwal, K.; Sharma, P.

    2012-01-01

    Development of economically feasible gasification and carbon capture, utilization and storage (CCUS) technologies requires a variety of software tools to optimize the designs of not only the key devices involved (e., g., gasifier, CO{sub 2} adsorber) but also the entire power generation system. High-fidelity models such as Computational Fluid Dynamics (CFD) models are capable of accurately simulating the detailed flow dynamics, heat transfer, and chemistry inside the key devices. However, the integration of CFD models within steady-state process simulators, and subsequent optimization of the integrated system, still presents significant challenges due to the scale differences in both time and length,more » as well the high computational cost. A reduced order model (ROM) generated from a high-fidelity model can serve as a bridge between the models of different scales. While high-fidelity models are built upon the principles of mass, momentum, and energy conservations, ROMs are usually developed based on regression-type equations and hence their predictions may violate the mass and energy conservation laws. A high-fidelity model may also have the mass and energy balance problem if it is not tightly converged. Conservations of mass and energy are important when a ROM is integrated to a flowsheet for the process simulation of the entire chemical or power generation system, especially when recycle streams are connected to the modeled device. As a part of the Carbon Capture Simulation Initiative (CCSI) project supported by the U.S. Department of Energy, we developed a software framework for generating ROMs from CFD simulations and integrating them with Process Modeling Environments (PMEs) for system-wide optimization. This paper presents a method to correct the results of a high-fidelity model or a ROM such that the elemental mass and energy are conserved perfectly. Correction factors for the flow rates of individual species in the product streams are solved using a

  17. Multi-fidelity machine learning models for accurate bandgap predictions of solids

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab

    Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelitymore » quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.« less

  18. Multi-fidelity machine learning models for accurate bandgap predictions of solids

    DOE PAGES

    Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab

    2016-12-28

    Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelitymore » quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.« less

  19. Scaling laws and reduced-order models for mixing and reactive-transport in heterogeneous anisotropic porous media

    NASA Astrophysics Data System (ADS)

    Mudunuru, M. K.; Karra, S.; Nakshatrala, K. B.

    2016-12-01

    Fundamental to enhancement and control of the macroscopic spreading, mixing, and dilution of solute plumes in porous media structures is the topology of flow field and underlying heterogeneity and anisotropy contrast of porous media. Traditionally, in literature, the main focus was limited to the shearing effects of flow field (i.e., flow has zero helical density, meaning that flow is always perpendicular to vorticity vector) on scalar mixing [2]. However, the combined effect of anisotropy of the porous media and the helical structure (or chaotic nature) of the flow field on the species reactive-transport and mixing has been rarely studied. Recently, it has been experimentally shown that there is an irrefutable evidence that chaotic advection and helical flows are inherent in porous media flows [1,2]. In this poster presentation, we present a non-intrusive physics-based model-order reduction framework to quantify the effects of species mixing in-terms of reduced-order models (ROMs) and scaling laws. The ROM framework is constructed based on the recent advancements in non-negative formulations for reactive-transport in heterogeneous anisotropic porous media [3] and non-intrusive ROM methods [4]. The objective is to generate computationally efficient and accurate ROMs for species mixing for different values of input data and reactive-transport model parameters. This is achieved by using multiple ROMs, which is a way to determine the robustness of the proposed framework. Sensitivity analysis is performed to identify the important parameters. Representative numerical examples from reactive-transport are presented to illustrate the importance of the proposed ROMs to accurately describe mixing process in porous media. [1] Lester, Metcalfe, and Trefry, "Is chaotic advection inherent to porous media flow?," PRL, 2013. [2] Ye, Chiogna, Cirpka, Grathwohl, and Rolle, "Experimental evidence of helical flow in porous media," PRL, 2015. [3] Mudunuru, and Nakshatrala, "On

  20. Evaluation of Geometrically Nonlinear Reduced Order Models with Nonlinear Normal Modes

    DOE PAGES

    Kuether, Robert J.; Deaner, Brandon J.; Hollkamp, Joseph J.; ...

    2015-09-15

    Several reduced-order modeling strategies have been developed to create low-order models of geometrically nonlinear structures from detailed finite element models, allowing one to compute the dynamic response of the structure at a dramatically reduced cost. But, the parameters of these reduced-order models are estimated by applying a series of static loads to the finite element model, and the quality of the reduced-order model can be highly sensitive to the amplitudes of the static load cases used and to the type/number of modes used in the basis. Our paper proposes to combine reduced-order modeling and numerical continuation to estimate the nonlinearmore » normal modes of geometrically nonlinear finite element models. Not only does this make it possible to compute the nonlinear normal modes far more quickly than existing approaches, but the nonlinear normal modes are also shown to be an excellent metric by which the quality of the reduced-order model can be assessed. Hence, the second contribution of this work is to demonstrate how nonlinear normal modes can be used as a metric by which nonlinear reduced-order models can be compared. Moreover, various reduced-order models with hardening nonlinearities are compared for two different structures to demonstrate these concepts: a clamped–clamped beam model, and a more complicated finite element model of an exhaust panel cover.« less

  1. Accurate object tracking system by integrating texture and depth cues

    NASA Astrophysics Data System (ADS)

    Chen, Ju-Chin; Lin, Yu-Hang

    2016-03-01

    A robust object tracking system that is invariant to object appearance variations and background clutter is proposed. Multiple instance learning with a boosting algorithm is applied to select discriminant texture information between the object and background data. Additionally, depth information, which is important to distinguish the object from a complicated background, is integrated. We propose two depth-based models that can compensate texture information to cope with both appearance variants and background clutter. Moreover, in order to reduce the risk of drifting problem increased for the textureless depth templates, an update mechanism is proposed to select more precise tracking results to avoid incorrect model updates. In the experiments, the robustness of the proposed system is evaluated and quantitative results are provided for performance analysis. Experimental results show that the proposed system can provide the best success rate and has more accurate tracking results than other well-known algorithms.

  2. Lung ultrasound accurately detects pneumothorax in a preterm newborn lamb model.

    PubMed

    Blank, Douglas A; Hooper, Stuart B; Binder-Heschl, Corinna; Kluckow, Martin; Gill, Andrew W; LaRosa, Domenic A; Inocencio, Ishmael M; Moxham, Alison; Rodgers, Karyn; Zahra, Valerie A; Davis, Peter G; Polglase, Graeme R

    2016-06-01

    Pneumothorax is a common emergency affecting extremely preterm. In adult studies, lung ultrasound has performed better than chest x-ray in the diagnosis of pneumothorax. The purpose of this study was to determine the efficacy of lung ultrasound (LUS) examination to detect pneumothorax using a preterm animal model. This was a prospective, observational study using newborn Border-Leicester lambs at gestational age = 126 days (equivalent to gestational age = 26 weeks in humans) receiving mechanical ventilation from birth to 2 h of life. At the conclusion of the experiment, LUS was performed, the lambs were then euthanised and a post-mortem exam was immediately performed. We used previously published ultrasound techniques to identify pneumothorax. Test characteristics of LUS to detect pneumothorax were calculated, using the post-mortem exam as the 'gold standard' test. Nine lambs (18 lungs) were examined. Four lambs had a unilateral pneumothorax, all of which were identified by LUS with no false positives. This was the first study to use post-mortem findings to test the efficacy of LUS to detect pneumothorax in a newborn animal model. Lung ultrasound accurately detected pneumothorax, verified by post-mortem exam, in premature, newborn lambs. © 2016 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

  3. Projection-Based Reduced Order Modeling for Spacecraft Thermal Analysis

    NASA Technical Reports Server (NTRS)

    Qian, Jing; Wang, Yi; Song, Hongjun; Pant, Kapil; Peabody, Hume; Ku, Jentung; Butler, Charles D.

    2015-01-01

    This paper presents a mathematically rigorous, subspace projection-based reduced order modeling (ROM) methodology and an integrated framework to automatically generate reduced order models for spacecraft thermal analysis. Two key steps in the reduced order modeling procedure are described: (1) the acquisition of a full-scale spacecraft model in the ordinary differential equation (ODE) and differential algebraic equation (DAE) form to resolve its dynamic thermal behavior; and (2) the ROM to markedly reduce the dimension of the full-scale model. Specifically, proper orthogonal decomposition (POD) in conjunction with discrete empirical interpolation method (DEIM) and trajectory piece-wise linear (TPWL) methods are developed to address the strong nonlinear thermal effects due to coupled conductive and radiative heat transfer in the spacecraft environment. Case studies using NASA-relevant satellite models are undertaken to verify the capability and to assess the computational performance of the ROM technique in terms of speed-up and error relative to the full-scale model. ROM exhibits excellent agreement in spatiotemporal thermal profiles (<0.5% relative error in pertinent time scales) along with salient computational acceleration (up to two orders of magnitude speed-up) over the full-scale analysis. These findings establish the feasibility of ROM to perform rational and computationally affordable thermal analysis, develop reliable thermal control strategies for spacecraft, and greatly reduce the development cycle times and costs.

  4. Optimal Cluster Mill Pass Scheduling With an Accurate and Rapid New Strip Crown Model

    NASA Astrophysics Data System (ADS)

    Malik, Arif S.; Grandhi, Ramana V.; Zipf, Mark E.

    2007-05-01

    Besides the requirement to roll coiled sheet at high levels of productivity, the optimal pass scheduling of cluster-type reversing cold mills presents the added challenge of assigning mill parameters that facilitate the best possible strip flatness. The pressures of intense global competition, and the requirements for increasingly thinner, higher quality specialty sheet products that are more difficult to roll, continue to force metal producers to commission innovative flatness-control technologies. This means that during the on-line computerized set-up of rolling mills, the mathematical model should not only determine the minimum total number of passes and maximum rolling speed, it should simultaneously optimize the pass-schedule so that desired flatness is assured, either by manual or automated means. In many cases today, however, on-line prediction of strip crown and corresponding flatness for the complex cluster-type rolling mills is typically addressed either by trial and error, by approximate deflection models for equivalent vertical roll-stacks, or by non-physical pattern recognition style models. The abundance of the aforementioned methods is largely due to the complexity of cluster-type mill configurations and the lack of deflection models with sufficient accuracy and speed for on-line use. Without adequate assignment of the pass-schedule set-up parameters, it may be difficult or impossible to achieve the required strip flatness. In this paper, we demonstrate optimization of cluster mill pass-schedules using a new accurate and rapid strip crown model. This pass-schedule optimization includes computations of the predicted strip thickness profile to validate mathematical constraints. In contrast to many of the existing methods for on-line prediction of strip crown and flatness on cluster mills, the demonstrated method requires minimal prior tuning and no extensive training with collected mill data. To rapidly and accurately solve the multi-contact problem

  5. Accurate 3d Textured Models of Vessels for the Improvement of the Educational Tools of a Museum

    NASA Astrophysics Data System (ADS)

    Soile, S.; Adam, K.; Ioannidis, C.; Georgopoulos, A.

    2013-02-01

    Besides the demonstration of the findings, modern museums organize educational programs which aim to experience and knowledge sharing combined with entertainment rather than to pure learning. Toward that effort, 2D and 3D digital representations are gradually replacing the traditional recording of the findings through photos or drawings. The present paper refers to a project that aims to create 3D textured models of two lekythoi that are exhibited in the National Archaeological Museum of Athens in Greece; on the surfaces of these lekythoi scenes of the adventures of Odysseus are depicted. The project is expected to support the production of an educational movie and some other relevant interactive educational programs for the museum. The creation of accurate developments of the paintings and of accurate 3D models is the basis for the visualization of the adventures of the mythical hero. The data collection was made by using a structured light scanner consisting of two machine vision cameras that are used for the determination of geometry of the object, a high resolution camera for the recording of the texture, and a DLP projector. The creation of the final accurate 3D textured model is a complicated and tiring procedure which includes the collection of geometric data, the creation of the surface, the noise filtering, the merging of individual surfaces, the creation of a c-mesh, the creation of the UV map, the provision of the texture and, finally, the general processing of the 3D textured object. For a better result a combination of commercial and in-house software made for the automation of various steps of the procedure was used. The results derived from the above procedure were especially satisfactory in terms of accuracy and quality of the model. However, the procedure was proved to be time consuming while the use of various software packages presumes the services of a specialist.

  6. Hybrid reduced order modeling for assembly calculations

    DOE PAGES

    Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; ...

    2015-08-14

    While the accuracy of assembly calculations has greatly improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the usemore » of the reduced order modeling for a single physics code, such as a radiation transport calculation. This paper extends those works to coupled code systems as currently employed in assembly calculations. Finally, numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.« less

  7. Reduced-Order Biogeochemical Flux Model for High-Resolution Multi-Scale Biophysical Simulations

    NASA Astrophysics Data System (ADS)

    Smith, K.; Hamlington, P.; Pinardi, N.; Zavatarelli, M.; Milliff, R. F.

    2016-12-01

    Biogeochemical tracers and their interactions with upper ocean physical processes such as submesoscale circulations and small-scale turbulence are critical for understanding the role of the ocean in the global carbon cycle. These interactions can cause small-scale spatial and temporal heterogeneity in tracer distributions which can, in turn, greatly affect carbon exchange rates between the atmosphere and interior ocean. For this reason, it is important to take into account small-scale biophysical interactions when modeling the global carbon cycle. However, explicitly resolving these interactions in an earth system model (ESM) is currently infeasible due to the enormous associated computational cost. As a result, understanding and subsequently parametrizing how these small-scale heterogeneous distributions develop and how they relate to larger resolved scales is critical for obtaining improved predictions of carbon exchange rates in ESMs. In order to address this need, we have developed the reduced-order, 17 state variable Biogeochemical Flux Model (BFM-17). This model captures the behavior of open-ocean biogeochemical systems without substantially increasing computational cost, thus allowing the model to be combined with computationally-intensive, fully three-dimensional, non-hydrostatic large eddy simulations (LES). In this talk, we couple BFM-17 with the Princeton Ocean Model and show good agreement between predicted monthly-averaged results and Bermuda testbed area field data (including the Bermuda-Atlantic Time Series and Bermuda Testbed Mooring). Through these tests, we demonstrate the capability of BFM-17 to accurately model open-ocean biochemistry. Additionally, we discuss the use of BFM-17 within a multi-scale LES framework and outline how this will further our understanding of turbulent biophysical interactions in the upper ocean.

  8. Reduced-order model based feedback control of the modified Hasegawa-Wakatani model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Goumiri, I. R.; Rowley, C. W.; Ma, Z.

    2013-04-15

    In this work, the development of model-based feedback control that stabilizes an unstable equilibrium is obtained for the Modified Hasegawa-Wakatani (MHW) equations, a classic model in plasma turbulence. First, a balanced truncation (a model reduction technique that has proven successful in flow control design problems) is applied to obtain a low dimensional model of the linearized MHW equation. Then, a model-based feedback controller is designed for the reduced order model using linear quadratic regulators. Finally, a linear quadratic Gaussian controller which is more resistant to disturbances is deduced. The controller is applied on the non-reduced, nonlinear MHW equations to stabilizemore » the equilibrium and suppress the transition to drift-wave induced turbulence.« less

  9. A Simple Iterative Model Accurately Captures Complex Trapline Formation by Bumblebees Across Spatial Scales and Flower Arrangements

    PubMed Central

    Reynolds, Andrew M.; Lihoreau, Mathieu; Chittka, Lars

    2013-01-01

    Pollinating bees develop foraging circuits (traplines) to visit multiple flowers in a manner that minimizes overall travel distance, a task analogous to the travelling salesman problem. We report on an in-depth exploration of an iterative improvement heuristic model of bumblebee traplining previously found to accurately replicate the establishment of stable routes by bees between flowers distributed over several hectares. The critical test for a model is its predictive power for empirical data for which the model has not been specifically developed, and here the model is shown to be consistent with observations from different research groups made at several spatial scales and using multiple configurations of flowers. We refine the model to account for the spatial search strategy of bees exploring their environment, and test several previously unexplored predictions. We find that the model predicts accurately 1) the increasing propensity of bees to optimize their foraging routes with increasing spatial scale; 2) that bees cannot establish stable optimal traplines for all spatial configurations of rewarding flowers; 3) the observed trade-off between travel distance and prioritization of high-reward sites (with a slight modification of the model); 4) the temporal pattern with which bees acquire approximate solutions to travelling salesman-like problems over several dozen foraging bouts; 5) the instability of visitation schedules in some spatial configurations of flowers; 6) the observation that in some flower arrays, bees' visitation schedules are highly individually different; 7) the searching behaviour that leads to efficient location of flowers and routes between them. Our model constitutes a robust theoretical platform to generate novel hypotheses and refine our understanding about how small-brained insects develop a representation of space and use it to navigate in complex and dynamic environments. PMID:23505353

  10. Parallel kinetic Monte Carlo simulation framework incorporating accurate models of adsorbate lateral interactions

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Nielsen, Jens; D’Avezac, Mayeul; Hetherington, James

    2013-12-14

    Ab initio kinetic Monte Carlo (KMC) simulations have been successfully applied for over two decades to elucidate the underlying physico-chemical phenomena on the surfaces of heterogeneous catalysts. These simulations necessitate detailed knowledge of the kinetics of elementary reactions constituting the reaction mechanism, and the energetics of the species participating in the chemistry. The information about the energetics is encoded in the formation energies of gas and surface-bound species, and the lateral interactions between adsorbates on the catalytic surface, which can be modeled at different levels of detail. The majority of previous works accounted for only pairwise-additive first nearest-neighbor interactions. Moremore » recently, cluster-expansion Hamiltonians incorporating long-range interactions and many-body terms have been used for detailed estimations of catalytic rate [C. Wu, D. J. Schmidt, C. Wolverton, and W. F. Schneider, J. Catal. 286, 88 (2012)]. In view of the increasing interest in accurate predictions of catalytic performance, there is a need for general-purpose KMC approaches incorporating detailed cluster expansion models for the adlayer energetics. We have addressed this need by building on the previously introduced graph-theoretical KMC framework, and we have developed Zacros, a FORTRAN2003 KMC package for simulating catalytic chemistries. To tackle the high computational cost in the presence of long-range interactions we introduce parallelization with OpenMP. We further benchmark our framework by simulating a KMC analogue of the NO oxidation system established by Schneider and co-workers [J. Catal. 286, 88 (2012)]. We show that taking into account only first nearest-neighbor interactions may lead to large errors in the prediction of the catalytic rate, whereas for accurate estimates thereof, one needs to include long-range terms in the cluster expansion.« less

  11. Accurate Treatment of Collisions and Water-Delivery in Models of Terrestrial Planet Formation

    NASA Astrophysics Data System (ADS)

    Haghighipour, Nader; Maindl, Thomas; Schaefer, Christoph

    2017-10-01

    It is widely accepted that collisions among solid bodies, ignited by their interactions with planetary embryos is the key process in the formation of terrestrial planets and transport of volatiles and chemical compounds to their accretion zones. Unfortunately, due to computational complexities, these collisions are often treated in a rudimentary way. Impacts are considered to be perfectly inelastic and volatiles are considered to be fully transferred from one object to the other. This perfect-merging assumption has profound effects on the mass and composition of final planetary bodies as it grossly overestimates the masses of these objects and the amounts of volatiles and chemical elements transferred to them. It also entirely neglects collisional-loss of volatiles (e.g., water) and draws an unrealistic connection between these properties and the chemical structure of the protoplanetary disk (i.e., the location of their original carriers). We have developed a new and comprehensive methodology to simulate growth of embryos to planetary bodies where we use a combination of SPH and N-body codes to accurately model collisions as well as the transport/transfer of chemical compounds. Our methodology accounts for the loss of volatiles (e.g., ice sublimation) during the orbital evolution of their careers and accurately tracks their transfer from one body to another. Results of our simulations show that traditional N-body modeling of terrestrial planet formation overestimates the amount of the mass and water contents of the final planets by over 60% implying that not only the amount of water they suggest is far from being realistic, small planets such as Mars can also form in these simulations when collisions are treated properly. We will present details of our methodology and discuss its implications for terrestrial planet formation and water delivery to Earth.

  12. Reduced quasilinear models for energetic particles interaction with Alfvenic eigenmodes

    NASA Astrophysics Data System (ADS)

    Ghantous, Katy

    The Line Broadened Quasilinear (LBQ) and the 1.5D reduced models are able to predict the effect of Alfvenic eigenmodes' interaction with energetic particles in burning plasmas. This interaction can result in energetic-particle losses that can damage the first wall, deteriorate the plasma performance, and even prevent ignition. The 1.5D model assumes a broad spectrum of overlapping modes and, based on analytic expressions for the growth and damping rates, calculates the pressure profiles that the energetic particles relax to upon interacting with the modes. 1.5D is validated with DIII-D experiments and predicted neutron losses consistent with observation. The model is employed to predict alpha-particle fusion-product losses in a large-scale operational parameter-space for burning plasmas. The LBQ model captures the interaction both in the regime of isolated modes as well as in the conventional regime of overlapping modes. Rules were established that allow quasilinear equations to replicate the expected steady-state saturation levels of isolated modes. The fitting formula is improved and the model is benchmarked with a Vlasov code, BOT. The saturation levels are accurately predicted and the mode evolution is well-replicated in the case of steady-state evolution where the collisions are high enough that coherent structures do not form. When the collisionality is low, oscillatory behavior can occur. LBQ can also exhibit non-steady behavior, but the onset of oscillations occurs for much higher collisional rates in BOT than in LBQ. For certain parameters of low collisionality, hole-clump creation and frequency chirping can occur which are not captured by the LBQ model. Also, there are cases of non-steady evolution without chirping which is possible for LBQ to study. However the results are inconclusive since the periods and amplitudes of the oscillations in the mode evolution are not well-replicated. If multiple modes exist, they can grow to the point of overlap which

  13. Exchange-Hole Dipole Dispersion Model for Accurate Energy Ranking in Molecular Crystal Structure Prediction.

    PubMed

    Whittleton, Sarah R; Otero-de-la-Roza, A; Johnson, Erin R

    2017-02-14

    Accurate energy ranking is a key facet to the problem of first-principles crystal-structure prediction (CSP) of molecular crystals. This work presents a systematic assessment of B86bPBE-XDM, a semilocal density functional combined with the exchange-hole dipole moment (XDM) dispersion model, for energy ranking using 14 compounds from the first five CSP blind tests. Specifically, the set of crystals studied comprises 11 rigid, planar compounds and 3 co-crystals. The experimental structure was correctly identified as the lowest in lattice energy for 12 of the 14 total crystals. One of the exceptions is 4-hydroxythiophene-2-carbonitrile, for which the experimental structure was correctly identified once a quasi-harmonic estimate of the vibrational free-energy contribution was included, evidencing the occasional importance of thermal corrections for accurate energy ranking. The other exception is an organic salt, where charge-transfer error (also called delocalization error) is expected to cause the base density functional to be unreliable. Provided the choice of base density functional is appropriate and an estimate of temperature effects is used, XDM-corrected density-functional theory is highly reliable for the energetic ranking of competing crystal structures.

  14. Damage Detection in Flexible Plates through Reduced-Order Modeling and Hybrid Particle-Kalman Filtering

    PubMed Central

    Capellari, Giovanni; Eftekhar Azam, Saeed; Mariani, Stefano

    2015-01-01

    Health monitoring of lightweight structures, like thin flexible plates, is of interest in several engineering fields. In this paper, a recursive Bayesian procedure is proposed to monitor the health of such structures through data collected by a network of optimally placed inertial sensors. As a main drawback of standard monitoring procedures is linked to the computational costs, two remedies are jointly considered: first, an order-reduction of the numerical model used to track the structural dynamics, enforced with proper orthogonal decomposition; and, second, an improved particle filter, which features an extended Kalman updating of each evolving particle before the resampling stage. The former remedy can reduce the number of effective degrees-of-freedom of the structural model to a few only (depending on the excitation), whereas the latter one allows to track the evolution of damage and to locate it thanks to an intricate formulation. To assess the effectiveness of the proposed procedure, the case of a plate subject to bending is investigated; it is shown that, when the procedure is appropriately fed by measurements, damage is efficiently and accurately estimated. PMID:26703615

  15. Reverse time migration by Krylov subspace reduced order modeling

    NASA Astrophysics Data System (ADS)

    Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali

    2018-04-01

    Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.

  16. Comparing and improving proper orthogonal decomposition (POD) to reduce the complexity of groundwater models

    NASA Astrophysics Data System (ADS)

    Gosses, Moritz; Nowak, Wolfgang; Wöhling, Thomas

    2017-04-01

    reduced model space, thereby allowing the recalculation of system matrices at every time-step necessary for non-linear models while retaining the speed of the reduced model. This makes POD-DEIM applicable for groundwater models simulating unconfined aquifers. However, in our analysis, the method struggled to reproduce variable river boundaries accurately and gave no advantage for variable Dirichlet boundaries compared to the original POD method. We have developed another extension for POD that targets to address these remaining problems by performing a second POD operation on the model matrix on the left-hand side of the equation. The method aims to at least reproduce the accuracy of the other methods where they are applicable while outperforming them for setups with changing river boundaries or variable Dirichlet boundaries. We compared the new extension with original POD and POD-DEIM for different combinations of model structures and boundary conditions. The new method shows the potential of POD extensions for applications to non-linear groundwater systems and complex boundary conditions that go beyond the current, relatively limited range of applications. References: Siade, A. J., Putti, M., and Yeh, W. W.-G. (2010). Snapshot selection for groundwater model reduction using proper orthogonal decomposition. Water Resour. Res., 46(8):W08539. Stanko, Z. P., Boyce, S. E., and Yeh, W. W.-G. (2016). Nonlinear model reduction of unconfined groundwater flow using pod and deim. Advances in Water Resources, 97:130 - 143.

  17. Reduced order modeling of fluid/structure interaction.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Barone, Matthew Franklin; Kalashnikova, Irina; Segalman, Daniel Joseph

    2009-11-01

    This report describes work performed from October 2007 through September 2009 under the Sandia Laboratory Directed Research and Development project titled 'Reduced Order Modeling of Fluid/Structure Interaction.' This project addresses fundamental aspects of techniques for construction of predictive Reduced Order Models (ROMs). A ROM is defined as a model, derived from a sequence of high-fidelity simulations, that preserves the essential physics and predictive capability of the original simulations but at a much lower computational cost. Techniques are developed for construction of provably stable linear Galerkin projection ROMs for compressible fluid flow, including a method for enforcing boundary conditions that preservesmore » numerical stability. A convergence proof and error estimates are given for this class of ROM, and the method is demonstrated on a series of model problems. A reduced order method, based on the method of quadratic components, for solving the von Karman nonlinear plate equations is developed and tested. This method is applied to the problem of nonlinear limit cycle oscillations encountered when the plate interacts with an adjacent supersonic flow. A stability-preserving method for coupling the linear fluid ROM with the structural dynamics model for the elastic plate is constructed and tested. Methods for constructing efficient ROMs for nonlinear fluid equations are developed and tested on a one-dimensional convection-diffusion-reaction equation. These methods are combined with a symmetrization approach to construct a ROM technique for application to the compressible Navier-Stokes equations.« less

  18. Magnetic gaps in organic tri-radicals: From a simple model to accurate estimates.

    PubMed

    Barone, Vincenzo; Cacelli, Ivo; Ferretti, Alessandro; Prampolini, Giacomo

    2017-03-14

    The calculation of the energy gap between the magnetic states of organic poly-radicals still represents a challenging playground for quantum chemistry, and high-level techniques are required to obtain accurate estimates. On these grounds, the aim of the present study is twofold. From the one side, it shows that, thanks to recent algorithmic and technical improvements, we are able to compute reliable quantum mechanical results for the systems of current fundamental and technological interest. From the other side, proper parameterization of a simple Hubbard Hamiltonian allows for a sound rationalization of magnetic gaps in terms of basic physical effects, unraveling the role played by electron delocalization, Coulomb repulsion, and effective exchange in tuning the magnetic character of the ground state. As case studies, we have chosen three prototypical organic tri-radicals, namely, 1,3,5-trimethylenebenzene, 1,3,5-tridehydrobenzene, and 1,2,3-tridehydrobenzene, which differ either for geometric or electronic structure. After discussing the differences among the three species and their consequences on the magnetic properties in terms of the simple model mentioned above, accurate and reliable values for the energy gap between the lowest quartet and doublet states are computed by means of the so-called difference dedicated configuration interaction (DDCI) technique, and the final results are discussed and compared to both available experimental and computational estimates.

  19. Anatomically accurate individual face modeling.

    PubMed

    Zhang, Yu; Prakash, Edmond C; Sung, Eric

    2003-01-01

    This paper presents a new 3D face model of a specific person constructed from the anatomical perspective. By exploiting the laser range data, a 3D facial mesh precisely representing the skin geometry is reconstructed. Based on the geometric facial mesh, we develop a deformable multi-layer skin model. It takes into account the nonlinear stress-strain relationship and dynamically simulates the non-homogenous behavior of the real skin. The face model also incorporates a set of anatomically-motivated facial muscle actuators and underlying skull structure. Lagrangian mechanics governs the facial motion dynamics, dictating the dynamic deformation of facial skin in response to the muscle contraction.

  20. Magnetic field line random walk in models and simulations of reduced magnetohydrodynamic turbulence

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Snodin, A. P.; Ruffolo, D.; Oughton, S.

    2013-12-10

    The random walk of magnetic field lines is examined numerically and analytically in the context of reduced magnetohydrodynamic (RMHD) turbulence, which provides a useful description of plasmas dominated by a strong mean field, such as in the solar corona. A recently developed non-perturbative theory of magnetic field line diffusion is compared with the diffusion coefficients obtained by accurate numerical tracing of magnetic field lines for both synthetic models and direct numerical simulations of RMHD. Statistical analysis of an ensemble of trajectories confirms the applicability of the theory, which very closely matches the numerical field line diffusion coefficient as a functionmore » of distance z along the mean magnetic field for a wide range of the Kubo number R. This theory employs Corrsin's independence hypothesis, sometimes thought to be valid only at low R. However, the results demonstrate that it works well up to R = 10, both for a synthetic RMHD model and an RMHD simulation. The numerical results from the RMHD simulation are compared with and without phase randomization, demonstrating a clear effect of coherent structures on the field line random walk for a very low Kubo number.« less

  1. Adaptive tracking for complex systems using reduced-order models

    NASA Technical Reports Server (NTRS)

    Carnigan, Craig R.

    1990-01-01

    Reduced-order models are considered in the context of parameter adaptive controllers for tracking workspace trajectories. A dual-arm manipulation task is used to illustrate the methodology and provide simulation results. A parameter adaptive controller is designed to track a payload trajectory using a four-parameter model instead of the full-order, nine-parameter model. Several simulations with different payload-to-arm mass ratios are used to illustrate the capabilities of the reduced-order model in tracking the desired trajectory.

  2. A Method for Generating Reduced Order Linear Models of Supersonic Inlets

    NASA Technical Reports Server (NTRS)

    Chicatelli, Amy; Hartley, Tom T.

    1997-01-01

    For the modeling of high speed propulsion systems, there are at least two major categories of models. One is based on computational fluid dynamics (CFD), and the other is based on design and analysis of control systems. CFD is accurate and gives a complete view of the internal flow field, but it typically has many states and runs much slower dm real-time. Models based on control design typically run near real-time but do not always capture the fundamental dynamics. To provide improved control models, methods are needed that are based on CFD techniques but yield models that are small enough for control analysis and design.

  3. A Reduced-order NLTE Kinetic Model for Radiating Plasmas of Outer Envelopes of Stellar Atmospheres

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Munafò, Alessandro; Mansour, Nagi N.; Panesi, Marco, E-mail: munafo@illinois.edu, E-mail: nagi.n.mansour@nasa.gov, E-mail: m.panesi@illinois.edu

    The present work proposes a self-consistent reduced-order NLTE kinetic model for radiating plasmas found in the outer layers of stellar atmospheres. A detailed collisional-radiative kinetic mechanism is constructed by leveraging the most up-to-date set of ab initio and experimental data available in the literature. This constitutes the starting point for the derivation of a reduced-order model, obtained by lumping the bound energy states into groups. In order to determine the needed thermo-physical group properties, uniform and Maxwell–Boltzmann energy distributions are used to reconstruct the energy population of each group. Finally, the reduced set of governing equations for the material gasmore » and the radiation field is obtained based on the moment method. Applications consider the steady flow across a shock wave in partially ionized hydrogen. The results clearly demonstrate that adopting a Maxwell–Boltzmann grouping allows, on the one hand, for a substantial reduction of the number of unknowns and, on the other, to maintain accuracy for both gas and radiation quantities. Also, it is observed that, when neglecting line radiation, the use of two groups already leads to a very accurate resolution of the photo-ionization precursor, internal relaxation, and radiative cooling regions. The inclusion of line radiation requires adopting just one additional group to account for optically thin losses in the α , β , and γ lines of the Balmer and Paschen series. This trend has been observed for a wide range of shock wave velocities.« less

  4. Adaptive tracking for complex systems using reduced-order models

    NASA Technical Reports Server (NTRS)

    Carignan, Craig R.

    1990-01-01

    Reduced-order models are considered in the context of parameter adaptive controllers for tracking workspace trajectories. A dual-arm manipulation task is used to illustrate the methodology and provide simulation results. A parameter adaptive controller is designed to track the desired position trajectory of a payload using a four-parameter model instead of a full-order, nine-parameter model. Several simulations with different payload-to-arm mass ratios are used to illustrate the capabilities of the reduced-order model in tracking the desired trajectory.

  5. Demonstration of reduced-order urban scale building energy models

    DOE PAGES

    Heidarinejad, Mohammad; Mattise, Nicholas; Dahlhausen, Matthew; ...

    2017-09-08

    The aim of this study is to demonstrate a developed framework to rapidly create urban scale reduced-order building energy models using a systematic summary of the simplifications required for the representation of building exterior and thermal zones. These urban scale reduced-order models rely on the contribution of influential variables to the internal, external, and system thermal loads. OpenStudio Application Programming Interface (API) serves as a tool to automate the process of model creation and demonstrate the developed framework. The results of this study show that the accuracy of the developed reduced-order building energy models varies only up to 10% withmore » the selection of different thermal zones. In addition, to assess complexity of the developed reduced-order building energy models, this study develops a novel framework to quantify complexity of the building energy models. Consequently, this study empowers the building energy modelers to quantify their building energy model systematically in order to report the model complexity alongside the building energy model accuracy. An exhaustive analysis on four university campuses suggests that the urban neighborhood buildings lend themselves to simplified typical shapes. Specifically, building energy modelers can utilize the developed typical shapes to represent more than 80% of the U.S. buildings documented in the CBECS database. One main benefits of this developed framework is the opportunity for different models including airflow and solar radiation models to share the same exterior representation, allowing a unifying exchange data. Altogether, the results of this study have implications for a large-scale modeling of buildings in support of urban energy consumption analyses or assessment of a large number of alternative solutions in support of retrofit decision-making in the building industry.« less

  6. Demonstration of reduced-order urban scale building energy models

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Heidarinejad, Mohammad; Mattise, Nicholas; Dahlhausen, Matthew

    The aim of this study is to demonstrate a developed framework to rapidly create urban scale reduced-order building energy models using a systematic summary of the simplifications required for the representation of building exterior and thermal zones. These urban scale reduced-order models rely on the contribution of influential variables to the internal, external, and system thermal loads. OpenStudio Application Programming Interface (API) serves as a tool to automate the process of model creation and demonstrate the developed framework. The results of this study show that the accuracy of the developed reduced-order building energy models varies only up to 10% withmore » the selection of different thermal zones. In addition, to assess complexity of the developed reduced-order building energy models, this study develops a novel framework to quantify complexity of the building energy models. Consequently, this study empowers the building energy modelers to quantify their building energy model systematically in order to report the model complexity alongside the building energy model accuracy. An exhaustive analysis on four university campuses suggests that the urban neighborhood buildings lend themselves to simplified typical shapes. Specifically, building energy modelers can utilize the developed typical shapes to represent more than 80% of the U.S. buildings documented in the CBECS database. One main benefits of this developed framework is the opportunity for different models including airflow and solar radiation models to share the same exterior representation, allowing a unifying exchange data. Altogether, the results of this study have implications for a large-scale modeling of buildings in support of urban energy consumption analyses or assessment of a large number of alternative solutions in support of retrofit decision-making in the building industry.« less

  7. Dynamic test/analysis correlation using reduced analytical models

    NASA Technical Reports Server (NTRS)

    Mcgowan, Paul E.; Angelucci, A. Filippo; Javeed, Mehzad

    1992-01-01

    Test/analysis correlation is an important aspect of the verification of analysis models which are used to predict on-orbit response characteristics of large space structures. This paper presents results of a study using reduced analysis models for performing dynamic test/analysis correlation. The reduced test-analysis model (TAM) has the same number and orientation of DOF as the test measurements. Two reduction methods, static (Guyan) reduction and the Improved Reduced System (IRS) reduction, are applied to the test/analysis correlation of a laboratory truss structure. Simulated test results and modal test data are used to examine the performance of each method. It is shown that selection of DOF to be retained in the TAM is critical when large structural masses are involved. In addition, the use of modal test results may provide difficulties in TAM accuracy even if a large number of DOF are retained in the TAM.

  8. Reduced-Order Biogeochemical Flux Model for High-Resolution Multi-Scale Biophysical Simulations

    NASA Astrophysics Data System (ADS)

    Smith, Katherine; Hamlington, Peter; Pinardi, Nadia; Zavatarelli, Marco

    2017-04-01

    Biogeochemical tracers and their interactions with upper ocean physical processes such as submesoscale circulations and small-scale turbulence are critical for understanding the role of the ocean in the global carbon cycle. These interactions can cause small-scale spatial and temporal heterogeneity in tracer distributions that can, in turn, greatly affect carbon exchange rates between the atmosphere and interior ocean. For this reason, it is important to take into account small-scale biophysical interactions when modeling the global carbon cycle. However, explicitly resolving these interactions in an earth system model (ESM) is currently infeasible due to the enormous associated computational cost. As a result, understanding and subsequently parameterizing how these small-scale heterogeneous distributions develop and how they relate to larger resolved scales is critical for obtaining improved predictions of carbon exchange rates in ESMs. In order to address this need, we have developed the reduced-order, 17 state variable Biogeochemical Flux Model (BFM-17) that follows the chemical functional group approach, which allows for non-Redfield stoichiometric ratios and the exchange of matter through units of carbon, nitrate, and phosphate. This model captures the behavior of open-ocean biogeochemical systems without substantially increasing computational cost, thus allowing the model to be combined with computationally-intensive, fully three-dimensional, non-hydrostatic large eddy simulations (LES). In this talk, we couple BFM-17 with the Princeton Ocean Model and show good agreement between predicted monthly-averaged results and Bermuda testbed area field data (including the Bermuda-Atlantic Time-series Study and Bermuda Testbed Mooring). Through these tests, we demonstrate the capability of BFM-17 to accurately model open-ocean biochemistry. Additionally, we discuss the use of BFM-17 within a multi-scale LES framework and outline how this will further our understanding

  9. Parametric reduced models for the nonlinear Schrödinger equation

    NASA Astrophysics Data System (ADS)

    Harlim, John; Li, Xiantao

    2015-05-01

    Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

  10. Parametric reduced models for the nonlinear Schrödinger equation.

    PubMed

    Harlim, John; Li, Xiantao

    2015-05-01

    Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

  11. THE EFFECTS OF VIDEO MODELING WITH VOICEOVER INSTRUCTION ON ACCURATE IMPLEMENTATION OF DISCRETE-TRIAL INSTRUCTION

    PubMed Central

    Vladescu, Jason C; Carroll, Regina; Paden, Amber; Kodak, Tiffany M

    2012-01-01

    The present study replicates and extends previous research on the use of video modeling (VM) with voiceover instruction to train staff to implement discrete-trial instruction (DTI). After staff trainees reached the mastery criterion when teaching an adult confederate with VM, they taught a child with a developmental disability using DTI. The results showed that the staff trainees' accurate implementation of DTI remained high, and both child participants acquired new skills. These findings provide additional support that VM may be an effective method to train staff members to conduct DTI. PMID:22844149

  12. The effects of video modeling with voiceover instruction on accurate implementation of discrete-trial instruction.

    PubMed

    Vladescu, Jason C; Carroll, Regina; Paden, Amber; Kodak, Tiffany M

    2012-01-01

    The present study replicates and extends previous research on the use of video modeling (VM) with voiceover instruction to train staff to implement discrete-trial instruction (DTI). After staff trainees reached the mastery criterion when teaching an adult confederate with VM, they taught a child with a developmental disability using DTI. The results showed that the staff trainees' accurate implementation of DTI remained high, and both child participants acquired new skills. These findings provide additional support that VM may be an effective method to train staff members to conduct DTI.

  13. Accurate Magnetometer/Gyroscope Attitudes Using a Filter with Correlated Sensor Noise

    NASA Technical Reports Server (NTRS)

    Sedlak, J.; Hashmall, J.

    1997-01-01

    Magnetometers and gyroscopes have been shown to provide very accurate attitudes for a variety of spacecraft. These results have been obtained, however, using a batch-least-squares algorithm and long periods of data. For use in onboard applications, attitudes are best determined using sequential estimators such as the Kalman filter. When a filter is used to determine attitudes using magnetometer and gyroscope data for input, the resulting accuracy is limited by both the sensor accuracies and errors inherent in the Earth magnetic field model. The Kalman filter accounts for the random component by modeling the magnetometer and gyroscope errors as white noise processes. However, even when these tuning parameters are physically realistic, the rate biases (included in the state vector) have been found to show systematic oscillations. These are attributed to the field model errors. If the gyroscope noise is sufficiently small, the tuned filter 'memory' will be long compared to the orbital period. In this case, the variations in the rate bias induced by field model errors are substantially reduced. Mistuning the filter to have a short memory time leads to strongly oscillating rate biases and increased attitude errors. To reduce the effect of the magnetic field model errors, these errors are estimated within the filter and used to correct the reference model. An exponentially-correlated noise model is used to represent the filter estimate of the systematic error. Results from several test cases using in-flight data from the Compton Gamma Ray Observatory are presented. These tests emphasize magnetometer errors, but the method is generally applicable to any sensor subject to a combination of random and systematic noise.

  14. Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems.

    PubMed

    Sapsis, Themistoklis P; Majda, Andrew J

    2013-08-20

    A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra.

  15. Reduced-order modeling of fluids systems, with applications in unsteady aerodynamics

    NASA Astrophysics Data System (ADS)

    Dawson, Scott T. M.

    This thesis focuses on two major themes: modeling and understanding the dynamics of rapidly pitching airfoils, and developing methods that can be used to extract models and pertinent features from datasets obtained in the study of these and other systems in fluid mechanics and aerodynamics. Much of the work utilizes in some capacity dynamic mode decomposition (DMD), a recently developed method to extract dynamical features and models from data. The investigation of pitching airfoils includes both wind tunnel experiments and direct numerical simulations. Experiments are performed on a NACA 0012 airfoil undergoing rapid pitching motion, with the focus on developing a switched linear modeling framework that can accurately predict unsteady aerodynamic forces and pressure distributions throughout arbitrary pitching motions. Numerical simulations are used to study the behavior of sinusoidally pitching airfoils. By systematically varying the amplitude, frequency, mean angle and axis of pitching, a comprehensive database of results is acquired, from which interesting regions in parameter space are identified and studied. Attention is given to pitching at "preferred" frequencies, where vortex shedding in the wake is excited or amplified, leading to larger lift forces. More generally, the ability to extract nonlinear models that describe the behavior of complex fluids systems can assist in not only understanding the dominant features of such systems, but also to achieve accurate prediction and control. One potential avenue to achieve this objective is through numerical approximation of the Koopman operator, an infinite-dimensional linear operator capable of describing finite-dimensional nonlinear systems, such as those that might describe the dominant dynamics of fluids systems. This idea is explored by showing that algorithms designed to approximate the Koopman operator can indeed be utilized to accurately model nonlinear fluids systems, even when the data available is

  16. Generalization of the normal-exponential model: exploration of a more accurate parametrisation for the signal distribution on Illumina BeadArrays.

    PubMed

    Plancade, Sandra; Rozenholc, Yves; Lund, Eiliv

    2012-12-11

    Illumina BeadArray technology includes non specific negative control features that allow a precise estimation of the background noise. As an alternative to the background subtraction proposed in BeadStudio which leads to an important loss of information by generating negative values, a background correction method modeling the observed intensities as the sum of the exponentially distributed signal and normally distributed noise has been developed. Nevertheless, Wang and Ye (2012) display a kernel-based estimator of the signal distribution on Illumina BeadArrays and suggest that a gamma distribution would represent a better modeling of the signal density. Hence, the normal-exponential modeling may not be appropriate for Illumina data and background corrections derived from this model may lead to wrong estimation. We propose a more flexible modeling based on a gamma distributed signal and a normal distributed background noise and develop the associated background correction, implemented in the R-package NormalGamma. Our model proves to be markedly more accurate to model Illumina BeadArrays: on the one hand, it is shown on two types of Illumina BeadChips that this model offers a more correct fit of the observed intensities. On the other hand, the comparison of the operating characteristics of several background correction procedures on spike-in and on normal-gamma simulated data shows high similarities, reinforcing the validation of the normal-gamma modeling. The performance of the background corrections based on the normal-gamma and normal-exponential models are compared on two dilution data sets, through testing procedures which represent various experimental designs. Surprisingly, we observe that the implementation of a more accurate parametrisation in the model-based background correction does not increase the sensitivity. These results may be explained by the operating characteristics of the estimators: the normal-gamma background correction offers an improvement

  17. Accurate dipole moment curve and non-adiabatic effects on the high resolution spectroscopic properties of the LiH molecule

    NASA Astrophysics Data System (ADS)

    Diniz, Leonardo G.; Kirnosov, Nikita; Alijah, Alexander; Mohallem, José R.; Adamowicz, Ludwik

    2016-04-01

    A very accurate dipole moment curve (DMC) for the ground X1Σ+ electronic state of the 7LiH molecule is reported. It is calculated with the use of all-particle explicitly correlated Gaussian functions with shifted centers. The DMC - the most accurate to our knowledge - and the corresponding highly accurate potential energy curve are used to calculate the transition energies, the transition dipole moments, and the Einstein coefficients for the rovibrational transitions with ΔJ = - 1 and Δv ⩽ 5 . The importance of the non-adiabatic effects in determining these properties is evaluated using the model of a vibrational R-dependent effective reduced mass in the rovibrational calculations introduced earlier (Diniz et al., 2015). The results of the present calculations are used to assess the quality of the two complete linelists of 7LiH available in the literature.

  18. Accurate Time-Dependent Traveling-Wave Tube Model Developed for Computational Bit-Error-Rate Testing

    NASA Technical Reports Server (NTRS)

    Kory, Carol L.

    2001-01-01

    The phenomenal growth of the satellite communications industry has created a large demand for traveling-wave tubes (TWT's) operating with unprecedented specifications requiring the design and production of many novel devices in record time. To achieve this, the TWT industry heavily relies on computational modeling. However, the TWT industry's computational modeling capabilities need to be improved because there are often discrepancies between measured TWT data and that predicted by conventional two-dimensional helical TWT interaction codes. This limits the analysis and design of novel devices or TWT's with parameters differing from what is conventionally manufactured. In addition, the inaccuracy of current computational tools limits achievable TWT performance because optimized designs require highly accurate models. To address these concerns, a fully three-dimensional, time-dependent, helical TWT interaction model was developed using the electromagnetic particle-in-cell code MAFIA (Solution of MAxwell's equations by the Finite-Integration-Algorithm). The model includes a short section of helical slow-wave circuit with excitation fed by radiofrequency input/output couplers, and an electron beam contained by periodic permanent magnet focusing. A cutaway view of several turns of the three-dimensional helical slow-wave circuit with input/output couplers is shown. This has been shown to be more accurate than conventionally used two-dimensional models. The growth of the communications industry has also imposed a demand for increased data rates for the transmission of large volumes of data. To achieve increased data rates, complex modulation and multiple access techniques are employed requiring minimum distortion of the signal as it is passed through the TWT. Thus, intersymbol interference (ISI) becomes a major consideration, as well as suspected causes such as reflections within the TWT. To experimentally investigate effects of the physical TWT on ISI would be

  19. Underwater drag-reducing effect of superhydrophobic submarine model.

    PubMed

    Zhang, Songsong; Ouyang, Xiao; Li, Jie; Gao, Shan; Han, Shihui; Liu, Lianhe; Wei, Hao

    2015-01-01

    To address the debates on whether superhydrophobic coatings can reduce fluid drag for underwater motions, we have achieved an underwater drag-reducing effect of large superhydrophobic submarine models with a feature size of 3.5 cm × 3.7 cm × 33.0 cm through sailing experiments of submarine models, modified with and without superhydrophobic surface under similar power supply and experimental conditions. The drag reduction rate reached as high as 15%. The fabrication of superhydrophobic coatings on a large area of submarine model surfaces was realized by immobilizing hydrophobic copper particles onto a precross-linked polydimethylsiloxane (PDMS) surface. The pre-cross-linking time was optimized at 20 min to obtain good superhydrophobicity for the underwater drag reduction effect by investigating the effect of pre-cross-linking on surface wettability and water adhesive property. We do believe that superhydrophobic coatings may provide a promising application in the field of drag-reducing of vehicle motions on or under the water surface.

  20. The effect of reduced gravity on cryogenic nitrogen boiling and pipe chilldown.

    PubMed

    Darr, Samuel; Dong, Jun; Glikin, Neil; Hartwig, Jason; Majumdar, Alok; Leclair, Andre; Chung, Jacob

    2016-01-01

    Manned deep space exploration will require cryogenic in-space propulsion. Yet, accurate prediction of cryogenic pipe flow boiling heat transfer is lacking, due to the absence of a cohesive reduced gravity data set covering the expected flow and thermodynamic parameter ranges needed to validate cryogenic two-phase heat transfer models. This work provides a wide range of cryogenic chilldown data aboard an aircraft flying parabolic trajectories to simulate reduced gravity. Liquid nitrogen is used to quench a 1.27 cm diameter tube from room temperature. The pressure, temperature, flow rate, and inlet conditions are reported from 10 tests covering liquid Reynolds number from 2,000 to 80,000 and pressures from 80 to 810 kPa. Corresponding terrestrial gravity tests were performed in upward, downward, and horizontal flow configurations to identify gravity and flow direction effects on chilldown. Film boiling heat transfer was lessened by up to 25% in reduced gravity, resulting in longer time and more liquid to quench the pipe to liquid temperatures. Heat transfer was enhanced by increasing the flow rate, and differences between reduced and terrestrial gravity diminished at high flow rates. The new data set will enable the development of accurate and robust heat transfer models of cryogenic pipe chilldown in reduced gravity.

  1. The effect of reduced gravity on cryogenic nitrogen boiling and pipe chilldown

    PubMed Central

    Darr, Samuel; Dong, Jun; Glikin, Neil; Hartwig, Jason; Majumdar, Alok; Leclair, Andre; Chung, Jacob

    2016-01-01

    Manned deep space exploration will require cryogenic in-space propulsion. Yet, accurate prediction of cryogenic pipe flow boiling heat transfer is lacking, due to the absence of a cohesive reduced gravity data set covering the expected flow and thermodynamic parameter ranges needed to validate cryogenic two-phase heat transfer models. This work provides a wide range of cryogenic chilldown data aboard an aircraft flying parabolic trajectories to simulate reduced gravity. Liquid nitrogen is used to quench a 1.27 cm diameter tube from room temperature. The pressure, temperature, flow rate, and inlet conditions are reported from 10 tests covering liquid Reynolds number from 2,000 to 80,000 and pressures from 80 to 810 kPa. Corresponding terrestrial gravity tests were performed in upward, downward, and horizontal flow configurations to identify gravity and flow direction effects on chilldown. Film boiling heat transfer was lessened by up to 25% in reduced gravity, resulting in longer time and more liquid to quench the pipe to liquid temperatures. Heat transfer was enhanced by increasing the flow rate, and differences between reduced and terrestrial gravity diminished at high flow rates. The new data set will enable the development of accurate and robust heat transfer models of cryogenic pipe chilldown in reduced gravity. PMID:28725740

  2. An accurate real-time model of maglev planar motor based on compound Simpson numerical integration

    NASA Astrophysics Data System (ADS)

    Kou, Baoquan; Xing, Feng; Zhang, Lu; Zhou, Yiheng; Liu, Jiaqi

    2017-05-01

    To realize the high-speed and precise control of the maglev planar motor, a more accurate real-time electromagnetic model, which considers the influence of the coil corners, is proposed in this paper. Three coordinate systems for the stator, mover and corner coil are established. The coil is divided into two segments, the straight coil segment and the corner coil segment, in order to obtain a complete electromagnetic model. When only take the first harmonic of the flux density distribution of a Halbach magnet array into account, the integration method can be carried out towards the two segments according to Lorenz force law. The force and torque analysis formula of the straight coil segment can be derived directly from Newton-Leibniz formula, however, this is not applicable to the corner coil segment. Therefore, Compound Simpson numerical integration method is proposed in this paper to solve the corner segment. With the validation of simulation and experiment, the proposed model has high accuracy and can realize practical application easily.

  3. Neuromodulation impact on nonlinear firing behavior of a reduced model motoneuron with the active dendrite

    PubMed Central

    Kim, Hojeong; Heckman, C. J.

    2014-01-01

    Neuromodulatory inputs from brainstem systems modulate the normal function of spinal motoneurons by altering the activation properties of persistent inward currents (PICs) in their dendrites. However, the effect of the PIC on firing outputs also depends on its location in the dendritic tree. To investigate the interaction between PIC neuromodulation and PIC location dependence, we used a two-compartment model that was biologically realistic in that it retains directional and frequency-dependent electrical coupling between the soma and the dendrites, as seen in multi-compartment models based on full anatomical reconstructions of motoneurons. Our two-compartment approach allowed us to systematically vary the coupling parameters between the soma and the dendrite to accurately reproduce the effect of location of the dendritic PIC on the generation of nonlinear (hysteretic) motoneuron firing patterns. Our results show that as a single parameter value for PIC activation was either increased or decreased by 20% from its default value, the solution space of the coupling parameter values for nonlinear firing outputs was drastically reduced by approximately 80%. As a result, the model tended to fire only in a linear mode at the majority of dendritic PIC sites. The same results were obtained when all parameters for the PIC activation simultaneously changed only by approximately ±10%. Our results suggest the democratization effect of neuromodulation: the neuromodulation by the brainstem systems may play a role in switching the motoneurons with PICs at different dendritic locations to a similar mode of firing by reducing the effect of the dendritic location of PICs on the firing behavior. PMID:25309410

  4. Reduced complexity modeling of Arctic delta dynamics

    NASA Astrophysics Data System (ADS)

    Piliouras, A.; Lauzon, R.; Rowland, J. C.

    2017-12-01

    How water and sediment are routed through deltas has important implications for our understanding of nutrient and sediment fluxes to the coastal ocean. These fluxes may be especially important in Arctic environments, because the Arctic ocean receives a disproportionately large amount of river discharge and high latitude regions are expected to be particularly vulnerable to climate change. The Arctic has some of the world's largest but least studied deltas. This lack of data is due to remote and hazardous conditions, sparse human populations, and limited remote sensing resources. In the absence of data, complex models may be of limited scientific utility in understanding Arctic delta dynamics. To overcome this challenge, we adapt the reduced complexity delta-building model DeltaRCM for Arctic environments to explore the influence of sea ice and permafrost on delta morphology and dynamics. We represent permafrost by increasing the threshold for sediment erosion, as permafrost has been found to increase cohesion and reduce channel migration rates. The presence of permafrost in the model results in the creation of more elongate channels, fewer active channels, and a rougher shoreline. We consider several effects of sea ice, including introducing friction which increases flow resistance, constriction of flow by landfast ice, and changes in effective water surface elevation. Flow constriction and increased friction from ice results in a rougher shoreline, more frequent channel switching, decreased channel migration rates, and enhanced deposition offshore of channel mouths. The reduced complexity nature of the model is ideal for generating a basic understanding of which processes unique to Arctic environments may have important effects on delta evolution, and it allows us to explore a variety of rules for incorporating those processes into the model to inform future Arctic delta modelling efforts. Finally, we plan to use the modeling results to determine how the presence

  5. The importance of accurate muscle modelling for biomechanical analyses: a case study with a lizard skull

    PubMed Central

    Gröning, Flora; Jones, Marc E. H.; Curtis, Neil; Herrel, Anthony; O'Higgins, Paul; Evans, Susan E.; Fagan, Michael J.

    2013-01-01

    Computer-based simulation techniques such as multi-body dynamics analysis are becoming increasingly popular in the field of skull mechanics. Multi-body models can be used for studying the relationships between skull architecture, muscle morphology and feeding performance. However, to be confident in the modelling results, models need to be validated against experimental data, and the effects of uncertainties or inaccuracies in the chosen model attributes need to be assessed with sensitivity analyses. Here, we compare the bite forces predicted by a multi-body model of a lizard (Tupinambis merianae) with in vivo measurements, using anatomical data collected from the same specimen. This subject-specific model predicts bite forces that are very close to the in vivo measurements and also shows a consistent increase in bite force as the bite position is moved posteriorly on the jaw. However, the model is very sensitive to changes in muscle attributes such as fibre length, intrinsic muscle strength and force orientation, with bite force predictions varying considerably when these three variables are altered. We conclude that accurate muscle measurements are crucial to building realistic multi-body models and that subject-specific data should be used whenever possible. PMID:23614944

  6. Unconditionally stable, second-order accurate schemes for solid state phase transformations driven by mechano-chemical spinodal decomposition

    DOE PAGES

    Sagiyama, Koki; Rudraraju, Shiva; Garikipati, Krishna

    2016-09-13

    Here, we consider solid state phase transformations that are caused by free energy densities with domains of non-convexity in strain-composition space; we refer to the non-convex domains as mechano-chemical spinodals. The non-convexity with respect to composition and strain causes segregation into phases with different crystal structures. We work on an existing model that couples the classical Cahn-Hilliard model with Toupin’s theory of gradient elasticity at finite strains. Both systems are represented by fourth-order, nonlinear, partial differential equations. The goal of this work is to develop unconditionally stable, second-order accurate time-integration schemes, motivated by the need to carry out large scalemore » computations of dynamically evolving microstructures in three dimensions. We also introduce reduced formulations naturally derived from these proposed schemes for faster computations that are still second-order accurate. Although our method is developed and analyzed here for a specific class of mechano-chemical problems, one can readily apply the same method to develop unconditionally stable, second-order accurate schemes for any problems for which free energy density functions are multivariate polynomials of solution components and component gradients. Apart from an analysis and construction of methods, we present a suite of numerical results that demonstrate the schemes in action.« less

  7. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

    PubMed

    Wang, Sheng; Sun, Siqi; Li, Zhen; Zhang, Renyu; Xu, Jinbo

    2017-01-01

    Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact-assisted models also have

  8. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

    PubMed Central

    Li, Zhen; Zhang, Renyu

    2017-01-01

    Motivation Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. Method This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Results Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact

  9. Production of accurate skeletal models of domestic animals using three-dimensional scanning and printing technology.

    PubMed

    Li, Fangzheng; Liu, Chunying; Song, Xuexiong; Huan, Yanjun; Gao, Shansong; Jiang, Zhongling

    2018-01-01

    Access to adequate anatomical specimens can be an important aspect in learning the anatomy of domestic animals. In this study, the authors utilized a structured light scanner and fused deposition modeling (FDM) printer to produce highly accurate animal skeletal models. First, various components of the bovine skeleton, including the femur, the fifth rib, and the sixth cervical (C6) vertebra were used to produce digital models. These were then used to produce 1:1 scale physical models with the FDM printer. The anatomical features of the digital models and three-dimensional (3D) printed models were then compared with those of the original skeletal specimens. The results of this study demonstrated that both digital and physical scale models of animal skeletal components could be rapidly produced using 3D printing technology. In terms of accuracy between models and original specimens, the standard deviations of the femur and the fifth rib measurements were 0.0351 and 0.0572, respectively. All of the features except the nutrient foramina on the original bone specimens could be identified in the digital and 3D printed models. Moreover, the 3D printed models could serve as a viable alternative to original bone specimens when used in anatomy education, as determined from student surveys. This study demonstrated an important example of reproducing bone models to be used in anatomy education and veterinary clinical training. Anat Sci Educ 11: 73-80. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.

  10. Accurate Spectral Fits of Jupiter's Great Red Spot: VIMS Visual Spectra Modelled with Chromophores Created by Photolyzed Ammonia Reacting with Acetyleneχ±

    NASA Astrophysics Data System (ADS)

    Baines, Kevin; Sromovsky, Lawrence A.; Fry, Patrick M.; Carlson, Robert W.; Momary, Thomas W.

    2016-10-01

    We report results incorporating the red-tinted photochemically-generated aerosols of Carlson et al (2016, Icarus 274, 106-115) in spectral models of Jupiter's Great Red Spot (GRS). Spectral models of the 0.35-1.0-micron spectrum show good agreement with Cassini/VIMS near-center-meridian and near-limb GRS spectra for model morphologies incorporating an optically-thin layer of Carlson (2016) aerosols at high altitudes, either at the top of the tropospheric GRS cloud, or in a distinct stratospheric haze layer. Specifically, a two-layer "crème brûlée" structure of the Mie-scattering Carlson et al (2016) chromophore attached to the top of a conservatively scattering (hereafter, "white") optically-thick cloud fits the spectra well. Currently, best agreement (reduced χ2 of 0.89 for the central-meridian spectrum) is found for a 0.195-0.217-bar, 0.19 ± 0.02 opacity layer of chromophores with mean particle radius of 0.14 ± 0.01 micron. As well, a structure with a detached stratospheric chromophore layer ~0.25 bar above a white tropospheric GRS cloud provides a good spectral match (reduced χ2 of 1.16). Alternatively, a cloud morphology with the chromophore coating white particles in a single optically- and physically-thick cloud (the "coated-shell model", initially explored by Carlson et al 2016) was found to give significantly inferior fits (best reduced χ2 of 2.9). Overall, we find that models accurately fit the GRS spectrum if (1) most of the optical depth of the chromophore is in a layer near the top of the main cloud or in a distinct separated layer above it, but is not uniformly distributed within the main cloud, (2) the chromophore consists of relatively small, 0.1-0.2-micron-radius particles, and (3) the chromophore layer optical depth is small, ~ 0.1-0.2. Thus, our analysis supports the exogenic origin of the red chromophore consistent with the Carlson et al (2016) photolytic production mechanism rather than an endogenic origin, such as upwelling of material

  11. A reduced-order nonlinear sliding mode observer for vehicle slip angle and tyre forces

    NASA Astrophysics Data System (ADS)

    Chen, Yuhang; Ji, Yunfeng; Guo, Konghui

    2014-12-01

    In this paper, a reduced-order sliding mode observer (RO-SMO) is developed for vehicle state estimation. Several improvements are achieved in this paper. First, the reference model accuracy is improved by considering vehicle load transfers and using a precise nonlinear tyre model 'UniTire'. Second, without the reference model accuracy degraded, the computing burden of the state observer is decreased by a reduced-order approach. Third, nonlinear system damping is integrated into the SMO to speed convergence and reduce chattering. The proposed RO-SMO is evaluated through simulation and experiments based on an in-wheel motor electric vehicle. The results show that the proposed observer accurately predicts the vehicle states.

  12. Controller design via structural reduced modeling by FETM

    NASA Technical Reports Server (NTRS)

    Yousuff, A.

    1986-01-01

    The Finite Element - Transfer Matrix (FETM) method has been developed to reduce the computations involved in analysis of structures. This widely accepted method, however, has certain limitations, and does not directly produce reduced models for control design. To overcome these shortcomings, a modification of FETM method has been developed. The modified FETM method easily produces reduced models that are tailored toward subsequent control design. Other features of this method are its ability to: (1) extract open loop frequencies and mode shapes with less computations, (2) overcome limitations of the original FETM method, and (3) simplify the procedures for output feedback, constrained compensation, and decentralized control. This semi annual report presents the development of the modified FETM, and through an example, illustrates its applicability to an output feedback and a decentralized control design.

  13. Developing an Accurate CFD Based Gust Model for the Truss Braced Wing Aircraft

    NASA Technical Reports Server (NTRS)

    Bartels, Robert E.

    2013-01-01

    The increased flexibility of long endurance aircraft having high aspect ratio wings necessitates attention to gust response and perhaps the incorporation of gust load alleviation. The design of civil transport aircraft with a strut or truss-braced high aspect ratio wing furthermore requires gust response analysis in the transonic cruise range. This requirement motivates the use of high fidelity nonlinear computational fluid dynamics (CFD) for gust response analysis. This paper presents the development of a CFD based gust model for the truss braced wing aircraft. A sharp-edged gust provides the gust system identification. The result of the system identification is several thousand time steps of instantaneous pressure coefficients over the entire vehicle. This data is filtered and downsampled to provide the snapshot data set from which a reduced order model is developed. A stochastic singular value decomposition algorithm is used to obtain a proper orthogonal decomposition (POD). The POD model is combined with a convolution integral to predict the time varying pressure coefficient distribution due to a novel gust profile. Finally the unsteady surface pressure response of the truss braced wing vehicle to a one-minus-cosine gust, simulated using the reduced order model, is compared with the full CFD.

  14. Multigrid time-accurate integration of Navier-Stokes equations

    NASA Technical Reports Server (NTRS)

    Arnone, Andrea; Liou, Meng-Sing; Povinelli, Louis A.

    1993-01-01

    Efficient acceleration techniques typical of explicit steady-state solvers are extended to time-accurate calculations. Stability restrictions are greatly reduced by means of a fully implicit time discretization. A four-stage Runge-Kutta scheme with local time stepping, residual smoothing, and multigridding is used instead of traditional time-expensive factorizations. Some applications to natural and forced unsteady viscous flows show the capability of the procedure.

  15. The role of public policies in reducing smoking prevalence: results from the Michigan SimSmoke tobacco policy simulation model.

    PubMed

    Levy, David T; Huang, An-Tsun; Havumaki, Joshua S; Meza, Rafael

    2016-05-01

    Michigan has implemented several of the tobacco control policies recommended by the World Health Organization MPOWER goals. We consider the effect of those policies and additional policies consistent with MPOWER goals on smoking prevalence and smoking-attributable deaths (SADs). The SimSmoke tobacco control policy simulation model is used to examine the effect of past policies and a set of additional policies to meet the MPOWER goals. The model is adapted to Michigan using state population, smoking, and policy data starting in 1993. SADs are estimated using standard attribution methods. Upon validating the model, SimSmoke is used to distinguish the effect of policies implemented since 1993 against a counterfactual with policies kept at their 1993 levels. The model is then used to project the effect of implementing stronger policies beginning in 2014. SimSmoke predicts smoking prevalence accurately between 1993 and 2010. Since 1993, a relative reduction in smoking rates of 22 % by 2013 and of 30 % by 2054 can be attributed to tobacco control policies. Of the 22 % reduction, 44 % is due to taxes, 28 % to smoke-free air laws, 26 % to cessation treatment policies, and 2 % to youth access. Moreover, 234,000 SADs are projected to be averted by 2054. With additional policies consistent with MPOWER goals, the model projects that, by 2054, smoking prevalence can be further reduced by 17 % with 80,000 deaths averted relative to the absence of those policies. Michigan SimSmoke shows that tobacco control policies, including cigarette taxes, smoke-free air laws, and cessation treatment policies, have substantially reduced smoking and SADs. Higher taxes, strong mass media campaigns, and cessation treatment policies would further reduce smoking prevalence and SADs.

  16. Reducing Spatial Data Complexity for Classification Models

    NASA Astrophysics Data System (ADS)

    Ruta, Dymitr; Gabrys, Bogdan

    2007-11-01

    Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the

  17. Accurate evaluation of exchange fields in finite element micromagnetic solvers

    NASA Astrophysics Data System (ADS)

    Chang, R.; Escobar, M. A.; Li, S.; Lubarda, M. V.; Lomakin, V.

    2012-04-01

    Quadratic basis functions (QBFs) are implemented for solving the Landau-Lifshitz-Gilbert equation via the finite element method. This involves the introduction of a set of special testing functions compatible with the QBFs for evaluating the Laplacian operator. The results by using QBFs are significantly more accurate than those via linear basis functions. QBF approach leads to significantly more accurate results than conventionally used approaches based on linear basis functions. Importantly QBFs allow reducing the error of computing the exchange field by increasing the mesh density for structured and unstructured meshes. Numerical examples demonstrate the feasibility of the method.

  18. Reducing uncertainty for estimating forest carbon stocks and dynamics using integrated remote sensing, forest inventory and process-based modeling

    NASA Astrophysics Data System (ADS)

    Poulter, B.; Ciais, P.; Joetzjer, E.; Maignan, F.; Luyssaert, S.; Barichivich, J.

    2015-12-01

    Accurately estimating forest biomass and forest carbon dynamics requires new integrated remote sensing, forest inventory, and carbon cycle modeling approaches. Presently, there is an increasing and urgent need to reduce forest biomass uncertainty in order to meet the requirements of carbon mitigation treaties, such as Reducing Emissions from Deforestation and forest Degradation (REDD+). Here we describe a new parameterization and assimilation methodology used to estimate tropical forest biomass using the ORCHIDEE-CAN dynamic global vegetation model. ORCHIDEE-CAN simulates carbon uptake and allocation to individual trees using a mechanistic representation of photosynthesis, respiration and other first-order processes. The model is first parameterized using forest inventory data to constrain background mortality rates, i.e., self-thinning, and productivity. Satellite remote sensing data for forest structure, i.e., canopy height, is used to constrain simulated forest stand conditions using a look-up table approach to match canopy height distributions. The resulting forest biomass estimates are provided for spatial grids that match REDD+ project boundaries and aim to provide carbon estimates for the criteria described in the IPCC Good Practice Guidelines Tier 3 category. With the increasing availability of forest structure variables derived from high-resolution LIDAR, RADAR, and optical imagery, new methodologies and applications with process-based carbon cycle models are becoming more readily available to inform land management.

  19. Fast and Accurate Hybrid Stream PCRTMSOLAR Radiative Transfer Model for Reflected Solar Spectrum Simulation in the Cloudy Atmosphere

    NASA Technical Reports Server (NTRS)

    Yang, Qiguang; Liu, Xu; Wu, Wan; Kizer, Susan; Baize, Rosemary R.

    2016-01-01

    A hybrid stream PCRTM-SOLAR model has been proposed for fast and accurate radiative transfer simulation. It calculates the reflected solar (RS) radiances with a fast coarse way and then, with the help of a pre-saved matrix, transforms the results to obtain the desired high accurate RS spectrum. The methodology has been demonstrated with the hybrid stream discrete ordinate (HSDO) radiative transfer (RT) model. The HSDO method calculates the monochromatic radiances using a 4-stream discrete ordinate method, where only a small number of monochromatic radiances are simulated with both 4-stream and a larger N-stream (N = 16) discrete ordinate RT algorithm. The accuracy of the obtained channel radiance is comparable to the result from N-stream moderate resolution atmospheric transmission version 5 (MODTRAN5). The root-mean-square errors are usually less than 5x10(exp -4) mW/sq cm/sr/cm. The computational speed is three to four-orders of magnitude faster than the medium speed correlated-k option MODTRAN5. This method is very efficient to simulate thousands of RS spectra under multi-layer clouds/aerosols and solar radiation conditions for climate change study and numerical weather prediction applications.

  20. The role of public policies in reducing smoking: the Minnesota SimSmoke tobacco policy model.

    PubMed

    Levy, David T; Boyle, Raymond G; Abrams, David B

    2012-11-01

    Following the landmark lawsuit and settlement with the tobacco industry, Minnesota pursued the implementation of stricter tobacco control policies, including tax increases, mass media campaigns, smokefree air laws, and cessation treatment policies. Modeling is used to examine policy effects on smoking prevalence and smoking-attributable deaths. To estimate the effect of tobacco control policies in Minnesota on smoking prevalence and smoking-attributable deaths using the SimSmoke simulation model. Minnesota data starting in 1993 are applied to SimSmoke, a simulation model used to examine the effect of tobacco control policies over time on smoking initiation and cessation. Upon validating the model against smoking prevalence, SimSmoke is used to distinguish the effect of policies implemented since 1993 on smoking prevalence. Using standard attribution methods, SimSmoke also estimates deaths averted as a result of the policies. SimSmoke predicts smoking prevalence accurately between 1993 and 2011. Since 1993, a relative reduction in smoking rates of 29% by 2011 and of 41% by 2041 can be attributed to tobacco control policies, mainly tax increases, smokefree air laws, media campaigns, and cessation treatment programs. Moreover, 48,000 smoking-attributable deaths will be averted by 2041. Minnesota SimSmoke demonstrates that tobacco control policies, especially taxes, have substantially reduced smoking prevalence and smoking-attributable deaths. Taxes, smokefree air laws, mass media, cessation treatment policies, and youth-access enforcement contributed to the decline in prevalence and deaths averted, with the strongest component being taxes. With stronger policies, for example, increasing cigarette taxes to $4.00 per pack, Minnesota's smoking rate could be reduced by another 13%, and 7200 deaths could be averted by 2041. Copyright © 2012 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

  1. An accurate model for the computation of the dose of protons in water.

    PubMed

    Embriaco, A; Bellinzona, V E; Fontana, A; Rotondi, A

    2017-06-01

    The accurate and fast calculation of the dose in proton radiation therapy is an essential ingredient for successful treatments. We propose a novel approach with a minimal number of parameters. The approach is based on the exact calculation of the electromagnetic part of the interaction, namely the Molière theory of the multiple Coulomb scattering for the transversal 1D projection and the Bethe-Bloch formula for the longitudinal stopping power profile, including a gaussian energy straggling. To this e.m. contribution the nuclear proton-nucleus interaction is added with a simple two-parameter model. Then, the non gaussian lateral profile is used to calculate the radial dose distribution with a method that assumes the cylindrical symmetry of the distribution. The results, obtained with a fast C++ based computational code called MONET (MOdel of ioN dosE for Therapy), are in very good agreement with the FLUKA MC code, within a few percent in the worst case. This study provides a new tool for fast dose calculation or verification, possibly for clinical use. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  2. Use of a clay modeling task to reduce chocolate craving.

    PubMed

    Andrade, Jackie; Pears, Sally; May, Jon; Kavanagh, David J

    2012-06-01

    Elaborated Intrusion theory (EI theory; Kavanagh, Andrade, & May, 2005) posits two main cognitive components in craving: associative processes that lead to intrusive thoughts about the craved substance or activity, and elaborative processes supporting mental imagery of the substance or activity. We used a novel visuospatial task to test the hypothesis that visual imagery plays a key role in craving. Experiment 1 showed that spending 10 min constructing shapes from modeling clay (plasticine) reduced participants' craving for chocolate compared with spending 10 min 'letting your mind wander'. Increasing the load on verbal working memory using a mental arithmetic task (counting backwards by threes) did not reduce craving further. Experiment 2 compared effects on craving of a simpler verbal task (counting by ones) and clay modeling. Clay modeling reduced overall craving strength and strength of craving imagery, and reduced the frequency of thoughts about chocolate. The results are consistent with EI theory, showing that craving is reduced by loading the visuospatial sketchpad of working memory but not by loading the phonological loop. Clay modeling might be a useful self-help tool to help manage craving for chocolate, snacks and other foods. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Can AERONET data be used to accurately model the monochromatic beam and circumsolar irradiances under cloud-free conditions in desert environment?

    NASA Astrophysics Data System (ADS)

    Eissa, Y.; Blanc, P.; Wald, L.; Ghedira, H.

    2015-07-01

    Routine measurements of the beam irradiance at normal incidence (DNI) include the irradiance originating from within the extent of the solar disc only (DNIS) whose angular extent is 0.266° ± 1.7 %, and that from a larger circumsolar region, called the circumsolar normal irradiance (CSNI). This study investigates if the spectral aerosol optical properties of the AERONET stations are sufficient for an accurate modelling of the monochromatic DNIS and CSNI under cloud-free conditions in a desert environment. The data from an AERONET station in Abu Dhabi, United Arab Emirates, and a collocated Sun and Aureole Measurement (SAM) instrument which offers reference measurements of the monochromatic profile of solar radiance, were exploited. Using the AERONET data both the radiative transfer models libRadtran and SMARTS offer an accurate estimate of the monochromatic DNIS, with a relative root mean square error (RMSE) of 5 %, a relative bias of +1 % and acoefficient of determination greater than 0.97. After testing two configurations in SMARTS and three in libRadtran for modelling the monochromatic CSNI, libRadtran exhibits the most accurate results when the AERONET aerosol phase function is presented as a Two Term Henyey-Greenstein phase function. In this case libRadtran exhibited a relative RMSE and a bias of respectively 22 and -19 % and a coefficient of determination of 0.89. The results are promising and pave the way towards reporting the contribution of the broadband circumsolar irradiance to standard DNI measurements.

  4. Prediction of a Francis turbine prototype full load instability from investigations on the reduced scale model

    NASA Astrophysics Data System (ADS)

    Alligné, S.; Maruzewski, P.; Dinh, T.; Wang, B.; Fedorov, A.; Iosfin, J.; Avellan, F.

    2010-08-01

    The growing development of renewable energies combined with the process of privatization, lead to a change of economical energy market strategies. Instantaneous pricings of electricity as a function of demand or predictions, induces profitable peak productions which are mainly covered by hydroelectric power plants. Therefore, operators harness more hydroelectric facilities at full load operating conditions. However, the Francis Turbine features an axi-symmetric rope leaving the runner which may act under certain conditions as an internal energy source leading to instability. Undesired power and pressure fluctuations are induced which may limit the maximum available power output. BC Hydro experiences such constraints in a hydroelectric power plant consisting of four 435 MW Francis Turbine generating units, which is located in Canada's province of British Columbia. Under specific full load operating conditions, one unit experiences power and pressure fluctuations at 0.46 Hz. The aim of the paper is to present a methodology allowing prediction of this prototype's instability frequency from investigations on the reduced scale model. A new hydro acoustic vortex rope model has been developed in SIMSEN software, taking into account the energy dissipation due to the thermodynamic exchange between the gas and the surrounding liquid. A combination of measurements, CFD simulations and computation of eigenmodes of the reduced scale model installed on test rig, allows the accurate calibration of the vortex rope model parameters at the model scale. Then, transposition of parameters to the prototype according to similitude laws is applied and stability analysis of the power plant is performed. The eigenfrequency of 0.39 Hz related to the first eigenmode of the power plant is determined to be unstable. Predicted frequency of the full load power and pressure fluctuations at the unit unstable operating point is found to be in general agreement with the prototype measurements.

  5. Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases.

    PubMed

    Pagán, Josué; Risco-Martín, José L; Moya, José M; Ayala, José L

    2016-08-01

    Prediction of symptomatic crises in chronic diseases allows to take decisions before the symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of medical alarms. The prediction horizon is in this case an important parameter in order to fulfill the pharmacokinetics of medications, or the time response of medical services. This paper presents a study about the prediction limits of a chronic disease with symptomatic crises: the migraine. For that purpose, this work develops a methodology to build predictive migraine models and to improve these predictions beyond the limits of the initial models. The maximum prediction horizon is analyzed, and its dependency on the selected features is studied. A strategy for model selection is proposed to tackle the trade off between conservative but robust predictive models, with respect to less accurate predictions with higher horizons. The obtained results show a prediction horizon close to 40min, which is in the time range of the drug pharmacokinetics. Experiments have been performed in a realistic scenario where input data have been acquired in an ambulatory clinical study by the deployment of a non-intrusive Wireless Body Sensor Network. Our results provide an effective methodology for the selection of the future horizon in the development of prediction algorithms for diseases experiencing symptomatic crises. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Can AERONET data be used to accurately model the monochromatic beam and circumsolar irradiances under cloud-free conditions in desert environment?

    NASA Astrophysics Data System (ADS)

    Eissa, Y.; Blanc, P.; Wald, L.; Ghedira, H.

    2015-12-01

    Routine measurements of the beam irradiance at normal incidence include the irradiance originating from within the extent of the solar disc only (DNIS), whose angular extent is 0.266° ± 1.7 %, and from a larger circumsolar region, called the circumsolar normal irradiance (CSNI). This study investigates whether the spectral aerosol optical properties of the AERONET stations are sufficient for an accurate modelling of the monochromatic DNIS and CSNI under cloud-free conditions in a desert environment. The data from an AERONET station in Abu Dhabi, United Arab Emirates, and the collocated Sun and Aureole Measurement instrument which offers reference measurements of the monochromatic profile of solar radiance were exploited. Using the AERONET data both the radiative transfer models libRadtran and SMARTS offer an accurate estimate of the monochromatic DNIS, with a relative root mean square error (RMSE) of 6 % and a coefficient of determination greater than 0.96. The observed relative bias obtained with libRadtran is +2 %, while that obtained with SMARTS is -1 %. After testing two configurations in SMARTS and three in libRadtran for modelling the monochromatic CSNI, libRadtran exhibits the most accurate results when the AERONET aerosol phase function is presented as a two-term Henyey-Greenstein phase function. In this case libRadtran exhibited a relative RMSE and a bias of respectively 27 and -24 % and a coefficient of determination of 0.882. Therefore, AERONET data may very well be used to model the monochromatic DNIS and the monochromatic CSNI. The results are promising and pave the way towards reporting the contribution of the broadband circumsolar irradiance to standard measurements of the beam irradiance.

  7. On the proper use of the reduced speed of light approximation

    DOE PAGES

    Gnedin, Nickolay Y.

    2016-12-07

    I show that the Reduced Speed of Light (RSL) approximation, when used properly (i.e. as originally designed - only for the local sources but not for the cosmic background), remains a highly accurate numerical method for modeling cosmic reionization. Simulated ionization and star formation histories from the "Cosmic Reionization On Computers" (CROC) project are insensitive to the adopted value of the reduced speed of light for as long as that value does not fall below about 10% of the true speed of light. Here, a recent claim of the failure of the RSL approximation in the Illustris reionization model appearsmore » to be due to the effective speed of light being reduced in the equation for the cosmic background too, and, hence, illustrates the importance of maintaining the correct speed of light in modeling the cosmic background.« less

  8. On the proper use of the reduced speed of light approximation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Gnedin, Nickolay Y.

    I show that the Reduced Speed of Light (RSL) approximation, when used properly (i.e. as originally designed - only for the local sources but not for the cosmic background), remains a highly accurate numerical method for modeling cosmic reionization. Simulated ionization and star formation histories from the "Cosmic Reionization On Computers" (CROC) project are insensitive to the adopted value of the reduced speed of light for as long as that value does not fall below about 10% of the true speed of light. Here, a recent claim of the failure of the RSL approximation in the Illustris reionization model appearsmore » to be due to the effective speed of light being reduced in the equation for the cosmic background too, and, hence, illustrates the importance of maintaining the correct speed of light in modeling the cosmic background.« less

  9. Intraspecific differences in bacterial responses to modelled reduced gravity

    NASA Technical Reports Server (NTRS)

    Baker, P. W.; Leff, L. G.

    2005-01-01

    AIMS: Bacteria are important residents of water systems, including those of space stations which feature specific environmental conditions, such as lowered effects of gravity. The purpose of this study was to compare responses with modelled reduced gravity of space station, water system bacterial isolates with other isolates of the same species. METHODS AND RESULTS: Bacterial isolates, Stenotrophomonas paucimobilis and Acinetobacter radioresistens, originally recovered from the water supply aboard the International Space Station (ISS) were grown in nutrient broth under modelled reduced gravity. Their growth was compared with type strains S. paucimobilis ATCC 10829 and A. radioresistens ATCC 49000. Acinetobacter radioresistens ATCC 49000 and the two ISS isolates showed similar growth profiles under modelled reduced gravity compared with normal gravity, whereas S. paucimobilis ATCC 10829 was negatively affected by modelled reduced gravity. CONCLUSIONS: These results suggest that microgravity might have selected for bacteria that were able to thrive under this unusual condition. These responses, coupled with impacts of other features (such as radiation resistance and ability to persist under very oligotrophic conditions), may contribute to the success of these water system bacteria. SIGNIFICANCE AND IMPACT OF THE STUDY: Water quality is a significant factor in many environments including the ISS. Efforts to remove microbial contaminants are likely to be complicated by the features of these bacteria which allow them to persist under the extreme conditions of the systems.

  10. Accurate Modeling of the Terrestrial Gamma-Ray Background for Homeland Security Applications

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sandness, Gerald A.; Schweppe, John E.; Hensley, Walter K.

    2009-10-24

    Abstract–The Pacific Northwest National Laboratory has developed computer models to simulate the use of radiation portal monitors to screen vehicles and cargo for the presence of illicit radioactive material. The gamma radiation emitted by the vehicles or cargo containers must often be measured in the presence of a relatively large gamma-ray background mainly due to the presence of potassium, uranium, and thorium (and progeny isotopes) in the soil and surrounding building materials. This large background is often a significant limit to the detection sensitivity for items of interest and must be modeled accurately for analyzing homeland security situations. Calculations ofmore » the expected gamma-ray emission from a disk of soil and asphalt were made using the Monte Carlo transport code MCNP and were compared to measurements made at a seaport with a high-purity germanium detector. Analysis revealed that the energy spectrum of the measured background could not be reproduced unless the model included gamma rays coming from the ground out to distances of at least 300 m. The contribution from beyond about 50 m was primarily due to gamma rays that scattered in the air before entering the detectors rather than passing directly from the ground to the detectors. These skyshine gamma rays contribute tens of percent to the total gamma-ray spectrum, primarily at energies below a few hundred keV. The techniques that were developed to efficiently calculate the contributions from a large soil disk and a large air volume in a Monte Carlo simulation are described and the implications of skyshine in portal monitoring applications are discussed.« less

  11. The Role of Public Policies in Reducing Smoking Prevalence: Results from the Michigan SimSmoke Tobacco Policy Simulation Model

    PubMed Central

    Levy, David T.; Huang, An-Tsun; Havumaki, Joshua S.; Meza, Rafael

    2016-01-01

    Introduction Michigan has implemented several of the tobacco control policies recommended by the World Health Organization MPOWER goals. We consider the effect of those policies and additional policies consistent with MPOWER goals on smoking prevalence and smoking-attributable deaths (SADs). Methods The SimSmoke tobacco control policy simulation model is used to examine the effect of past policies and a set of additional policies to meet the MPOWER goals. The model is adapted to Michigan using state population, smoking and policy data starting in 1993. SADs are estimated using standard attribution methods. Upon validating the model, SimSmoke is used to distinguish the effect of policies implemented since 1993 against a counterfactual with policies kept at their 1993 levels. The model is then used to project the effect of implementing stronger policies beginning in 2014. Results SimSmoke predicts smoking prevalence accurately between 1993 and 2010. Since 1993, a relative reduction in smoking rates of 22% by 2013 and of 30% by 2054 can be attributed to tobacco control policies. Of the 22% reduction, 44% is due to taxes, 28% to smoke-free air laws, 26% to cessation treatment policies, and 2% to youth access. Moreover, 234,000 smoking-attributable deaths are projected to be averted by 2054. With additional policies consistent with MPOWER goals, the model projects that, by 2054, smoking prevalence can be further reduced by 17% with 80,000 deaths averted relative to the absence of those policies. Conclusions Michigan SimSmoke shows that tobacco control policies, including cigarette taxes, smoke-free air laws and cessation treatment policies, have substantially reduced smoking and smoking-attributable deaths. Higher taxes, strong mass media campaigns and cessation treatment policies would further reduce smoking prevalence and smoking-attributable deaths. PMID:26983616

  12. Regional climate models reduce biases of global models and project smaller European summer warming

    NASA Astrophysics Data System (ADS)

    Soerland, S.; Schar, C.; Lüthi, D.; Kjellstrom, E.

    2017-12-01

    The assessment of regional climate change and the associated planning of adaptation and response strategies are often based on complex model chains. Typically, these model chains employ global and regional climate models (GCMs and RCMs), as well as one or several impact models. It is a common belief that the errors in such model chains behave approximately additive, thus the uncertainty should increase with each modeling step. If this hypothesis were true, the application of RCMs would not lead to any intrinsic improvement (beyond higher-resolution detail) of the GCM results. Here, we investigate the bias patterns (offset during the historical period against observations) and climate change signals of two RCMs that have downscaled a comprehensive set of GCMs following the EURO-CORDEX framework. The two RCMs reduce the biases of the driving GCMs, reduce the spread and modify the amplitude of the GCM projected climate change signal. The GCM projected summer warming at the end of the century is substantially reduced by both RCMs. These results are important, as the projected summer warming and its likely impact on the water cycle are among the most serious concerns regarding European climate change.

  13. Normal forms for reduced stochastic climate models

    PubMed Central

    Majda, Andrew J.; Franzke, Christian; Crommelin, Daan

    2009-01-01

    The systematic development of reduced low-dimensional stochastic climate models from observations or comprehensive high-dimensional climate models is an important topic for atmospheric low-frequency variability, climate sensitivity, and improved extended range forecasting. Here techniques from applied mathematics are utilized to systematically derive normal forms for reduced stochastic climate models for low-frequency variables. The use of a few Empirical Orthogonal Functions (EOFs) (also known as Principal Component Analysis, Karhunen–Loéve and Proper Orthogonal Decomposition) depending on observational data to span the low-frequency subspace requires the assessment of dyad interactions besides the more familiar triads in the interaction between the low- and high-frequency subspaces of the dynamics. It is shown below that the dyad and multiplicative triad interactions combine with the climatological linear operator interactions to simultaneously produce both strong nonlinear dissipation and Correlated Additive and Multiplicative (CAM) stochastic noise. For a single low-frequency variable the dyad interactions and climatological linear operator alone produce a normal form with CAM noise from advection of the large scales by the small scales and simultaneously strong cubic damping. These normal forms should prove useful for developing systematic strategies for the estimation of stochastic models from climate data. As an illustrative example the one-dimensional normal form is applied below to low-frequency patterns such as the North Atlantic Oscillation (NAO) in a climate model. The results here also illustrate the short comings of a recent linear scalar CAM noise model proposed elsewhere for low-frequency variability. PMID:19228943

  14. An algorithm to extract more accurate stream longitudinal profiles from unfilled DEMs

    NASA Astrophysics Data System (ADS)

    Byun, Jongmin; Seong, Yeong Bae

    2015-08-01

    Morphometric features observed from a stream longitudinal profile (SLP) reflect channel responses to lithological variation and changes in uplift or climate; therefore, they constitute essential indicators in the studies for the dynamics between tectonics, climate, and surface processes. The widespread availability of digital elevation models (DEMs) and their processing enable semi-automatic extraction of SLPs as well as additional stream profile parameters, thus reducing the time spent for extracting them and simultaneously allowing regional-scale studies of SLPs. However, careful consideration is required to extract SLPs directly from a DEM, because the DEM must be altered by depression filling process to ensure the continuity of flows across it. Such alteration inevitably introduces distortions to the SLP, such as stair steps, bias of elevation values, and inaccurate stream paths. This paper proposes a new algorithm, called maximum depth tracing algorithm (MDTA), to extract more accurate SLPs using depression-unfilled DEMs. The MDTA supposes that depressions in DEMs are not necessarily artifacts to be removed, and that elevation values within them are useful to represent more accurately the real landscape. To ensure the continuity of flows even across the unfilled DEM, the MDTA first determines the outlet of each depression and then reverses flow directions of the cells on the line of maximum depth within each depression, beginning from the outlet and toward the sink. It also calculates flow accumulation without disruption across the unfilled DEM. Comparative analysis with the profiles extracted by the hydrologic functions implemented in the ArcGIS™ was performed to illustrate the benefits from the MDTA. It shows that the MDTA provides more accurate stream paths on depression areas, and consequently reduces distortions of the SLPs derived from the paths, such as exaggerated elevation values and negatively biased slopes that are commonly observed in the SLPs

  15. Catalyzing Novel Approaches to Rapid, Accurate, and Affordable Early Cancer Detection.

    PubMed

    Dhar, Asif; Meagher, Beth; Ryscavage, Andrew

    Inspired by the Cancer Moonshot, a dedicated team of professionals worked with leaders across the cancer ecosystem to look for an opportunity to radically reduce cancer mortality globally by focusing on early cancer detection. After an initial survey of cancer innovation, progress, and pitfalls, the team believed that if new rapid, affordable, and accurate early detection solutions were appropriately brought to market, it would be possible to intervene earlier when cancer is most treatable.An extensive process began, informed by dozens of experts in the cancer ecosystem. The Cancer XPRIZE team designed a prize competition where "the winning team will develop a means to rapidly, accurately, and affordably screen for early cancers where intervention can reduce human suffering."The following outlines the Cancer XPRIZE's experience using a powerful approach-the radical prize design-to catch more cancers in time to make a difference saving lives, dollars, and suffering.

  16. A more accurate scheme for calculating Earth's skin temperature

    NASA Astrophysics Data System (ADS)

    Tsuang, Ben-Jei; Tu, Chia-Ying; Tsai, Jeng-Lin; Dracup, John A.; Arpe, Klaus; Meyers, Tilden

    2009-02-01

    The theoretical framework of the vertical discretization of a ground column for calculating Earth’s skin temperature is presented. The suggested discretization is derived from the evenly heat-content discretization with the optimal effective thickness for layer-temperature simulation. For the same level number, the suggested discretization is more accurate in skin temperature as well as surface ground heat flux simulations than those used in some state-of-the-art models. A proposed scheme (“op(3,2,0)”) can reduce the normalized root-mean-square error (or RMSE/STD ratio) of the calculated surface ground heat flux of a cropland site significantly to 2% (or 0.9 W m-2), from 11% (or 5 W m-2) by a 5-layer scheme used in ECMWF, from 19% (or 8 W m-2) by a 5-layer scheme used in ECHAM, and from 74% (or 32 W m-2) by a single-layer scheme used in the UCLA GCM. Better accuracy can be achieved by including more layers to the vertical discretization. Similar improvements are expected for other locations with different land types since the numerical error is inherited into the models for all the land types. The proposed scheme can be easily implemented into state-of-the-art climate models for the temperature simulation of snow, ice and soil.

  17. Generating Accurate 3d Models of Architectural Heritage Structures Using Low-Cost Camera and Open Source Algorithms

    NASA Astrophysics Data System (ADS)

    Zacharek, M.; Delis, P.; Kedzierski, M.; Fryskowska, A.

    2017-05-01

    These studies have been conductedusing non-metric digital camera and dense image matching algorithms, as non-contact methods of creating monuments documentation.In order toprocess the imagery, few open-source software and algorithms of generating adense point cloud from images have been executed. In the research, the OSM Bundler, VisualSFM software, and web application ARC3D were used. Images obtained for each of the investigated objects were processed using those applications, and then dense point clouds and textured 3D models were created. As a result of post-processing, obtained models were filtered and scaled.The research showedthat even using the open-source software it is possible toobtain accurate 3D models of structures (with an accuracy of a few centimeters), but for the purpose of documentation and conservation of cultural and historical heritage, such accuracy can be insufficient.

  18. The QSE-Reduced Nuclear Reaction Network for Silicon Burning

    NASA Astrophysics Data System (ADS)

    Hix, W. Raphael; Parete-Koon, Suzanne T.; Freiburghaus, Christian; Thielemann, Friedrich-Karl

    2007-09-01

    Iron and neighboring nuclei are formed in massive stars shortly before core collapse and during their supernova outbursts, as well as during thermonuclear supernovae. Complete and incomplete silicon burning are responsible for the production of a wide range of nuclei with atomic mass numbers from 28 to 64. Because of the large number of nuclei involved, accurate modeling of silicon burning is computationally expensive. However, examination of the physics of silicon burning has revealed that the nuclear evolution is dominated by large groups of nuclei in mutual equilibrium. We present a new hybrid equilibrium-network scheme which takes advantage of this quasi-equilibrium in order to reduce the number of independent variables calculated. This allows accurate prediction of the nuclear abundance evolution, deleptonization, and energy generation at a greatly reduced computational cost when compared to a conventional nuclear reaction network. During silicon burning, the resultant QSE-reduced network is approximately an order of magnitude faster than the full network it replaces and requires the tracking of less than a third as many abundance variables, without significant loss of accuracy. These reductions in computational cost and the number of species evolved make QSE-reduced networks well suited for inclusion within hydrodynamic simulations, particularly in multidimensional applications.

  19. Accurate upwind methods for the Euler equations

    NASA Technical Reports Server (NTRS)

    Huynh, Hung T.

    1993-01-01

    A new class of piecewise linear methods for the numerical solution of the one-dimensional Euler equations of gas dynamics is presented. These methods are uniformly second-order accurate, and can be considered as extensions of Godunov's scheme. With an appropriate definition of monotonicity preservation for the case of linear convection, it can be shown that they preserve monotonicity. Similar to Van Leer's MUSCL scheme, they consist of two key steps: a reconstruction step followed by an upwind step. For the reconstruction step, a monotonicity constraint that preserves uniform second-order accuracy is introduced. Computational efficiency is enhanced by devising a criterion that detects the 'smooth' part of the data where the constraint is redundant. The concept and coding of the constraint are simplified by the use of the median function. A slope steepening technique, which has no effect at smooth regions and can resolve a contact discontinuity in four cells, is described. As for the upwind step, existing and new methods are applied in a manner slightly different from those in the literature. These methods are derived by approximating the Euler equations via linearization and diagonalization. At a 'smooth' interface, Harten, Lax, and Van Leer's one intermediate state model is employed. A modification for this model that can resolve contact discontinuities is presented. Near a discontinuity, either this modified model or a more accurate one, namely, Roe's flux-difference splitting. is used. The current presentation of Roe's method, via the conceptually simple flux-vector splitting, not only establishes a connection between the two splittings, but also leads to an admissibility correction with no conditional statement, and an efficient approximation to Osher's approximate Riemann solver. These reconstruction and upwind steps result in schemes that are uniformly second-order accurate and economical at smooth regions, and yield high resolution at discontinuities.

  20. Accurate diode behavioral model with reverse recovery

    NASA Astrophysics Data System (ADS)

    Banáš, Stanislav; Divín, Jan; Dobeš, Josef; Paňko, Václav

    2018-01-01

    This paper deals with the comprehensive behavioral model of p-n junction diode containing reverse recovery effect, applicable to all standard SPICE simulators supporting Verilog-A language. The model has been successfully used in several production designs, which require its full complexity, robustness and set of tuning parameters comparable with standard compact SPICE diode model. The model is like standard compact model scalable with area and temperature and can be used as a stand-alone diode or as a part of more complex device macro-model, e.g. LDMOS, JFET, bipolar transistor. The paper briefly presents the state of the art followed by the chapter describing the model development and achieved solutions. During precise model verification some of them were found non-robust or poorly converging and replaced by more robust solutions, demonstrated in the paper. The measurement results of different technologies and different devices compared with a simulation using the new behavioral model are presented as the model validation. The comparison of model validation in time and frequency domains demonstrates that the implemented reverse recovery effect with correctly extracted parameters improves the model simulation results not only in switching from ON to OFF state, which is often published, but also its impedance/admittance frequency dependency in GHz range. Finally the model parameter extraction and the comparison with SPICE compact models containing reverse recovery effect is presented.

  1. Reduced-order modeling of soft robots

    PubMed Central

    Chenevier, Jean; González, David; Aguado, J. Vicente; Chinesta, Francisco

    2018-01-01

    We present a general strategy for the modeling and simulation-based control of soft robots. Although the presented methodology is completely general, we restrict ourselves to the analysis of a model robot made of hyperelastic materials and actuated by cables or tendons. To comply with the stringent real-time constraints imposed by control algorithms, a reduced-order modeling strategy is proposed that allows to minimize the amount of online CPU cost. Instead, an offline training procedure is proposed that allows to determine a sort of response surface that characterizes the response of the robot. Contrarily to existing strategies, the proposed methodology allows for a fully non-linear modeling of the soft material in a hyperelastic setting as well as a fully non-linear kinematic description of the movement without any restriction nor simplifying assumption. Examples of different configurations of the robot were analyzed that show the appeal of the method. PMID:29470496

  2. Time Accurate Unsteady Pressure Loads Simulated for the Space Launch System at a Wind Tunnel Condition

    NASA Technical Reports Server (NTRS)

    Alter, Stephen J.; Brauckmann, Gregory J.; Kleb, Bil; Streett, Craig L; Glass, Christopher E.; Schuster, David M.

    2015-01-01

    Using the Fully Unstructured Three-Dimensional (FUN3D) computational fluid dynamics code, an unsteady, time-accurate flow field about a Space Launch System configuration was simulated at a transonic wind tunnel condition (Mach = 0.9). Delayed detached eddy simulation combined with Reynolds Averaged Naiver-Stokes and a Spallart-Almaras turbulence model were employed for the simulation. Second order accurate time evolution scheme was used to simulate the flow field, with a minimum of 0.2 seconds of simulated time to as much as 1.4 seconds. Data was collected at 480 pressure taps at locations, 139 of which matched a 3% wind tunnel model, tested in the Transonic Dynamic Tunnel (TDT) facility at NASA Langley Research Center. Comparisons between computation and experiment showed agreement within 5% in terms of location for peak RMS levels, and 20% for frequency and magnitude of power spectral densities. Grid resolution and time step sensitivity studies were performed to identify methods for improved accuracy comparisons to wind tunnel data. With limited computational resources, accurate trends for reduced vibratory loads on the vehicle were observed. Exploratory methods such as determining minimized computed errors based on CFL number and sub-iterations, as well as evaluating frequency content of the unsteady pressures and evaluation of oscillatory shock structures were used in this study to enhance computational efficiency and solution accuracy. These techniques enabled development of a set of best practices, for the evaluation of future flight vehicle designs in terms of vibratory loads.

  3. Reduced Complexity Modelling of Urban Floodplain Inundation

    NASA Astrophysics Data System (ADS)

    McMillan, H. K.; Brasington, J.; Mihir, M.

    2004-12-01

    Significant recent advances in floodplain inundation modelling have been achieved by directly coupling 1d channel hydraulic models with a raster storage cell approximation for floodplain flows. The strengths of this reduced-complexity model structure derive from its explicit dependence on a digital elevation model (DEM) to parameterize flows through riparian areas, providing a computationally efficient algorithm to model heterogeneous floodplains. Previous applications of this framework have generally used mid-range grid scales (101-102 m), showing the capacity of the models to simulate long reaches (103-104 m). However, the increasing availability of precision DEMs derived from airborne laser altimetry (LIDAR) enables their use at very high spatial resolutions (100-101 m). This spatial scale offers the opportunity to incorporate the complexity of the built environment directly within the floodplain DEM and simulate urban flooding. This poster describes a series of experiments designed to explore model functionality at these reduced scales. Important questions are considered, raised by this new approach, about the reliability and representation of the floodplain topography and built environment, and the resultant sensitivity of inundation forecasts. The experiments apply a raster floodplain model to reconstruct a 1:100 year flood event on the River Granta in eastern England, which flooded 72 properties in the town of Linton in October 2001. The simulations use a nested-scale model to maintain efficiency. A 2km by 4km urban zone is represented by a high-resolution DEM derived from single-pulse LIDAR data supplied by the UK Environment Agency, together with surveyed data and aerial photography. Novel methods of processing the raw data to provide the individual structure detail required are investigated and compared. This is then embedded within a lower-resolution model application at the reach scale which provides boundary conditions based on recorded flood stage

  4. Accurate Estimation of Target amounts Using Expanded BASS Model for Demand-Side Management

    NASA Astrophysics Data System (ADS)

    Kim, Hyun-Woong; Park, Jong-Jin; Kim, Jin-O.

    2008-10-01

    The electricity demand in Korea has rapidly increased along with a steady economic growth since 1970s. Therefore Korea has positively propelled not only SSM (Supply-Side Management) but also DSM (Demand-Side Management) activities to reduce investment cost of generating units and to save supply costs of electricity through the enhancement of whole national energy utilization efficiency. However study for rebate, which have influence on success or failure on DSM program, is not sufficient. This paper executed to modeling mathematically expanded Bass model considering rebates, which have influence on penetration amounts for DSM program. To reflect rebate effect more preciously, the pricing function using in expanded Bass model directly reflects response of potential participants for rebate level.

  5. Accurate quantification of fluorescent targets within turbid media based on a decoupled fluorescence Monte Carlo model.

    PubMed

    Deng, Yong; Luo, Zhaoyang; Jiang, Xu; Xie, Wenhao; Luo, Qingming

    2015-07-01

    We propose a method based on a decoupled fluorescence Monte Carlo model for constructing fluorescence Jacobians to enable accurate quantification of fluorescence targets within turbid media. The effectiveness of the proposed method is validated using two cylindrical phantoms enclosing fluorescent targets within homogeneous and heterogeneous background media. The results demonstrate that our method can recover relative concentrations of the fluorescent targets with higher accuracy than the perturbation fluorescence Monte Carlo method. This suggests that our method is suitable for quantitative fluorescence diffuse optical tomography, especially for in vivo imaging of fluorophore targets for diagnosis of different diseases and abnormalities.

  6. Ensemble MD simulations restrained via crystallographic data: Accurate structure leads to accurate dynamics

    PubMed Central

    Xue, Yi; Skrynnikov, Nikolai R

    2014-01-01

    Currently, the best existing molecular dynamics (MD) force fields cannot accurately reproduce the global free-energy minimum which realizes the experimental protein structure. As a result, long MD trajectories tend to drift away from the starting coordinates (e.g., crystallographic structures). To address this problem, we have devised a new simulation strategy aimed at protein crystals. An MD simulation of protein crystal is essentially an ensemble simulation involving multiple protein molecules in a crystal unit cell (or a block of unit cells). To ensure that average protein coordinates remain correct during the simulation, we introduced crystallography-based restraints into the MD protocol. Because these restraints are aimed at the ensemble-average structure, they have only minimal impact on conformational dynamics of the individual protein molecules. So long as the average structure remains reasonable, the proteins move in a native-like fashion as dictated by the original force field. To validate this approach, we have used the data from solid-state NMR spectroscopy, which is the orthogonal experimental technique uniquely sensitive to protein local dynamics. The new method has been tested on the well-established model protein, ubiquitin. The ensemble-restrained MD simulations produced lower crystallographic R factors than conventional simulations; they also led to more accurate predictions for crystallographic temperature factors, solid-state chemical shifts, and backbone order parameters. The predictions for 15N R1 relaxation rates are at least as accurate as those obtained from conventional simulations. Taken together, these results suggest that the presented trajectories may be among the most realistic protein MD simulations ever reported. In this context, the ensemble restraints based on high-resolution crystallographic data can be viewed as protein-specific empirical corrections to the standard force fields. PMID:24452989

  7. Advanced Fluid Reduced Order Models for Compressible Flow.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Tezaur, Irina Kalashnikova; Fike, Jeffrey A.; Carlberg, Kevin Thomas

    This report summarizes fiscal year (FY) 2017 progress towards developing and implementing within the SPARC in-house finite volume flow solver advanced fluid reduced order models (ROMs) for compressible captive-carriage flow problems of interest to Sandia National Laboratories for the design and qualification of nuclear weapons components. The proposed projection-based model order reduction (MOR) approach, known as the Proper Orthogonal Decomposition (POD)/Least- Squares Petrov-Galerkin (LSPG) method, can substantially reduce the CPU-time requirement for these simulations, thereby enabling advanced analyses such as uncertainty quantification and de- sign optimization. Following a description of the project objectives and FY17 targets, we overview briefly themore » POD/LSPG approach to model reduction implemented within SPARC . We then study the viability of these ROMs for long-time predictive simulations in the context of a two-dimensional viscous laminar cavity problem, and describe some FY17 enhancements to the proposed model reduction methodology that led to ROMs with improved predictive capabilities. Also described in this report are some FY17 efforts pursued in parallel to the primary objective of determining whether the ROMs in SPARC are viable for the targeted application. These include the implemen- tation and verification of some higher-order finite volume discretization methods within SPARC (towards using the code to study the viability of ROMs on three-dimensional cavity problems) and a novel structure-preserving constrained POD/LSPG formulation that can improve the accuracy of projection-based reduced order models. We conclude the report by summarizing the key takeaways from our FY17 findings, and providing some perspectives for future work.« less

  8. Application of thin plate splines for accurate regional ionosphere modeling with multi-GNSS data

    NASA Astrophysics Data System (ADS)

    Krypiak-Gregorczyk, Anna; Wielgosz, Pawel; Borkowski, Andrzej

    2016-04-01

    GNSS-derived regional ionosphere models are widely used in both precise positioning, ionosphere and space weather studies. However, their accuracy is often not sufficient to support precise positioning, RTK in particular. In this paper, we presented new approach that uses solely carrier phase multi-GNSS observables and thin plate splines (TPS) for accurate ionospheric TEC modeling. TPS is a closed solution of a variational problem minimizing both the sum of squared second derivatives of a smoothing function and the deviation between data points and this function. This approach is used in UWM-rt1 regional ionosphere model developed at UWM in Olsztyn. The model allows for providing ionospheric TEC maps with high spatial and temporal resolutions - 0.2x0.2 degrees and 2.5 minutes, respectively. For TEC estimation, EPN and EUPOS reference station data is used. The maps are available with delay of 15-60 minutes. In this paper we compare the performance of UWM-rt1 model with IGS global and CODE regional ionosphere maps during ionospheric storm that took place on March 17th, 2015. During this storm, the TEC level over Europe doubled comparing to earlier quiet days. The performance of the UWM-rt1 model was validated by (a) comparison to reference double-differenced ionospheric corrections over selected baselines, and (b) analysis of post-fit residuals to calibrated carrier phase geometry-free observational arcs at selected test stations. The results show a very good performance of UWM-rt1 model. The obtained post-fit residuals in case of UWM maps are lower by one order of magnitude comparing to IGS maps. The accuracy of UWM-rt1 -derived TEC maps is estimated at 0.5 TECU. This may be directly translated to the user positioning domain.

  9. Accurate measurement of junctional conductance between electrically coupled cells with dual whole-cell voltage-clamp under conditions of high series resistance.

    PubMed

    Hartveit, Espen; Veruki, Margaret Lin

    2010-03-15

    Accurate measurement of the junctional conductance (G(j)) between electrically coupled cells can provide important information about the functional properties of coupling. With the development of tight-seal, whole-cell recording, it became possible to use dual, single-electrode voltage-clamp recording from pairs of small cells to measure G(j). Experiments that require reduced perturbation of the intracellular environment can be performed with high-resistance pipettes or the perforated-patch technique, but an accompanying increase in series resistance (R(s)) compromises voltage-clamp control and reduces the accuracy of G(j) measurements. Here, we present a detailed analysis of methodologies available for accurate determination of steady-state G(j) and related parameters under conditions of high R(s), using continuous or discontinuous single-electrode voltage-clamp (CSEVC or DSEVC) amplifiers to quantify the parameters of different equivalent electrical circuit model cells. Both types of amplifiers can provide accurate measurements of G(j), with errors less than 5% for a wide range of R(s) and G(j) values. However, CSEVC amplifiers need to be combined with R(s)-compensation or mathematical correction for the effects of nonzero R(s) and finite membrane resistance (R(m)). R(s)-compensation is difficult for higher values of R(s) and leads to instability that can damage the recorded cells. Mathematical correction for R(s) and R(m) yields highly accurate results, but depends on accurate estimates of R(s) throughout an experiment. DSEVC amplifiers display very accurate measurements over a larger range of R(s) values than CSEVC amplifiers and have the advantage that knowledge of R(s) is unnecessary, suggesting that they are preferable for long-duration experiments and/or recordings with high R(s). Copyright (c) 2009 Elsevier B.V. All rights reserved.

  10. A reduced-order adaptive neuro-fuzzy inference system model as a software sensor for rapid estimation of five-day biochemical oxygen demand

    NASA Astrophysics Data System (ADS)

    Noori, Roohollah; Safavi, Salman; Nateghi Shahrokni, Seyyed Afshin

    2013-07-01

    The five-day biochemical oxygen demand (BOD5) is one of the key parameters in water quality management. In this study, a novel approach, i.e., reduced-order adaptive neuro-fuzzy inference system (ROANFIS) model was developed for rapid estimation of BOD5. In addition, an uncertainty analysis of adaptive neuro-fuzzy inference system (ANFIS) and ROANFIS models was carried out based on Monte-Carlo simulation. Accuracy analysis of ANFIS and ROANFIS models based on both developed discrepancy ratio and threshold statistics revealed that the selected ROANFIS model was superior. Pearson correlation coefficient (R) and root mean square error for the best fitted ROANFIS model were 0.96 and 7.12, respectively. Furthermore, uncertainty analysis of the developed models indicated that the selected ROANFIS had less uncertainty than the ANFIS model and accurately forecasted BOD5 in the Sefidrood River Basin. Besides, the uncertainty analysis also showed that bracketed predictions by 95% confidence bound and d-factor in the testing steps for the selected ROANFIS model were 94% and 0.83, respectively.

  11. Novel Framework for Reduced Order Modeling of Aero-engine Components

    NASA Astrophysics Data System (ADS)

    Safi, Ali

    The present study focuses on the popular dynamic reduction methods used in design of complex assemblies (millions of Degrees of Freedom) where numerous iterations are involved to achieve the final design. Aerospace manufacturers such as Rolls Royce and Pratt & Whitney are actively seeking techniques that reduce computational time while maintaining accuracy of the models. This involves modal analysis of components with complex geometries to determine the dynamic behavior due to non-linearity and complicated loading conditions. In such a case the sub-structuring and dynamic reduction techniques prove to be an efficient tool to reduce design cycle time. The components whose designs are finalized can be dynamically reduced to mass and stiffness matrices at the boundary nodes in the assembly. These matrices conserve the dynamics of the component in the assembly, and thus avoid repeated calculations during the analysis runs for design modification of other components. This thesis presents a novel framework in terms of modeling and meshing of any complex structure, in this case an aero-engine casing. In this study the affect of meshing techniques on the run time are highlighted. The modal analysis is carried out using an extremely fine mesh to ensure all minor details in the structure are captured correctly in the Finite Element (FE) model. This is used as the reference model, to compare against the results of the reduced model. The study also shows the conditions/criteria under which dynamic reduction can be implemented effectively, proving the accuracy of Criag-Bampton (C.B.) method and limitations of Static Condensation. The study highlights the longer runtime needed to produce the reduced matrices of components compared to the overall runtime of the complete unreduced model. Although once the components are reduced, the assembly run is significantly. Hence the decision to use Component Mode Synthesis (CMS) is to be taken judiciously considering the number of

  12. MaMR: High-performance MapReduce programming model for material cloud applications

    NASA Astrophysics Data System (ADS)

    Jing, Weipeng; Tong, Danyu; Wang, Yangang; Wang, Jingyuan; Liu, Yaqiu; Zhao, Peng

    2017-02-01

    With the increasing data size in materials science, existing programming models no longer satisfy the application requirements. MapReduce is a programming model that enables the easy development of scalable parallel applications to process big data on cloud computing systems. However, this model does not directly support the processing of multiple related data, and the processing performance does not reflect the advantages of cloud computing. To enhance the capability of workflow applications in material data processing, we defined a programming model for material cloud applications that supports multiple different Map and Reduce functions running concurrently based on hybrid share-memory BSP called MaMR. An optimized data sharing strategy to supply the shared data to the different Map and Reduce stages was also designed. We added a new merge phase to MapReduce that can efficiently merge data from the map and reduce modules. Experiments showed that the model and framework present effective performance improvements compared to previous work.

  13. Reduced Order Modeling in General Relativity

    NASA Astrophysics Data System (ADS)

    Tiglio, Manuel

    2014-03-01

    Reduced Order Modeling is an emerging yet fast developing filed in gravitational wave physics. The main goals are to enable fast modeling and parameter estimation of any detected signal, along with rapid matched filtering detecting. I will focus on the first two. Some accomplishments include being able to replace, with essentially no lost of physical accuracy, the original models with surrogate ones (which are not effective ones, that is, they do not simplify the physics but go on a very different track, exploiting the particulars of the waveform family under consideration and state of the art dimensional reduction techniques) which are very fast to evaluate. For example, for EOB models they are at least around 3 orders of magnitude faster than solving the original equations, with physically equivalent results. For numerical simulations the speedup is at least 11 orders of magnitude. For parameter estimation our current numbers are about bringing ~100 days for a single SPA inspiral binary neutron star Bayesian parameter estimation analysis to under a day. More recently, it has been shown that the full precessing problem for, say, 200 cycles, can be represented, through some new ideas, by a remarkably compact set of carefully chosen reduced basis waveforms (~10-100, depending on the accuracy requirements). I will highlight what I personally believe are the challenges to face next in this subarea of GW physics and where efforts should be directed. This talk will summarize work in collaboration with: Harbir Antil (GMU), Jonathan Blackman (Caltech), Priscila Canizares (IoA, Cambridge, UK), Sarah Caudill (UWM), Jonathan Gair (IoA. Cambridge. UK), Scott Field (UMD), Chad R. Galley (Caltech), Frank Herrmann (Germany), Han Hestahven (EPFL, Switzerland), Jason Kaye (Brown, Stanford & Courant). Evan Ochsner (UWM), Ricardo Nochetto (UMD), Vivien Raymond (LIGO, Caltech), Rory Smith (LIGO, Caltech) Bela Ssilagyi (Caltech) and MT (UMD & Caltech).

  14. Perceived Physician-informed Weight Status Predicts Accurate Weight Self-Perception and Weight Self-Regulation in Low-income, African American Women.

    PubMed

    Harris, Charlie L; Strayhorn, Gregory; Moore, Sandra; Goldman, Brian; Martin, Michelle Y

    2016-01-01

    Obese African American women under-appraise their body mass index (BMI) classification and report fewer weight loss attempts than women who accurately appraise their weight status. This cross-sectional study examined whether physician-informed weight status could predict weight self-perception and weight self-regulation strategies in obese women. A convenience sample of 118 low-income women completed a survey assessing demographic characteristics, comorbidities, weight self-perception, and weight self-regulation strategies. BMI was calculated during nurse triage. Binary logistic regression models were performed to test hypotheses. The odds of obese accurate appraisers having been informed about their weight status were six times greater than those of under-appraisers. The odds of those using an "approach" self-regulation strategy having been physician-informed were four times greater compared with those using an "avoidance" strategy. Physicians are uniquely positioned to influence accurate weight self-perception and adaptive weight self-regulation strategies in underserved women, reducing their risk for obesity-related morbidity.

  15. Antenna modeling considerations for accurate SAR calculations in human phantoms in close proximity to GSM cellular base station antennas.

    PubMed

    van Wyk, Marnus J; Bingle, Marianne; Meyer, Frans J C

    2005-09-01

    International bodies such as International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the Institute for Electrical and Electronic Engineering (IEEE) make provision for human exposure assessment based on SAR calculations (or measurements) and basic restrictions. In the case of base station exposure this is mostly applicable to occupational exposure scenarios in the very near field of these antennas where the conservative reference level criteria could be unnecessarily restrictive. This study presents a variety of critical aspects that need to be considered when calculating SAR in a human body close to a mobile phone base station antenna. A hybrid FEM/MoM technique is proposed as a suitable numerical method to obtain accurate results. The verification of the FEM/MoM implementation has been presented in a previous publication; the focus of this study is an investigation into the detail that must be included in a numerical model of the antenna, to accurately represent the real-world scenario. This is accomplished by comparing numerical results to measurements for a generic GSM base station antenna and appropriate, representative canonical and human phantoms. The results show that it is critical to take the disturbance effect of the human phantom (a large conductive body) on the base station antenna into account when the antenna-phantom spacing is less than 300 mm. For these small spacings, the antenna structure must be modeled in detail. The conclusion is that it is feasible to calculate, using the proposed techniques and methodology, accurate occupational compliance zones around base station antennas based on a SAR profile and basic restriction guidelines. (c) 2005 Wiley-Liss, Inc.

  16. Reducing the Complexity of an Agent-Based Local Heroin Market Model

    PubMed Central

    Heard, Daniel; Bobashev, Georgiy V.; Morris, Robert J.

    2014-01-01

    This project explores techniques for reducing the complexity of an agent-based model (ABM). The analysis involved a model developed from the ethnographic research of Dr. Lee Hoffer in the Larimer area heroin market, which involved drug users, drug sellers, homeless individuals and police. The authors used statistical techniques to create a reduced version of the original model which maintained simulation fidelity while reducing computational complexity. This involved identifying key summary quantities of individual customer behavior as well as overall market activity and replacing some agents with probability distributions and regressions. The model was then extended to allow external market interventions in the form of police busts. Extensions of this research perspective, as well as its strengths and limitations, are discussed. PMID:25025132

  17. Animals Do Not Induce or Reduce Attentional Blinking, But They Are Reported More Accurately in a Rapid Serial Visual Presentation Task

    PubMed Central

    2017-01-01

    Evolutionary psychologists have suggested that modern humans have evolved to automatically direct their attention toward animal stimuli. Although this suggestion has found support in several attentional paradigms, it is not without controversy. Recently, a study employing methods customary to studying the attentional blink has shown inconclusive support for the prioritization of animals in attention. This showed an advantage for reporting animals as second targets within the typical window of the attentional blink, but it remained unclear whether this advantage was really due to a reduction of the attentional blink. We reassessed for the presence of a reduced attentional blink for animals compared with artifacts by using three disparate stimuli sets. A general advantage for animals was found but no indication of a reduction of the attentional blink for animals. There was no support for the prediction that animal distractors should lead to spontaneous inductions of attentional blinks when presented as critical distractors before single targets. Another experiment with single targets still showed that animals were reported more accurately than artifacts. A final experiment showed that when animals were first target, they did not generate stronger attentional blinks. In summary, we did find a general advantage for animal images in the rapid serial visual presentation task, but animal images did not either induce or reduce attentional blinks. This set of results is in line with conclusions from previous research showing no evidence for a special role of animals in attention. PMID:29085619

  18. Reduced-form air quality modeling for community-scale ...

    EPA Pesticide Factsheets

    Transportation plays an important role in modern society, but its impact on air quality has been shown to have significant adverse effects on public health. Numerous reviews (HEI, CDC, WHO) summarizing findings of hundreds of studies conducted mainly in the last decade, conclude that exposures to traffic emissions near roads are a public health concern. The Community LINE Source Model (C-LINE) is a web-based model designed to inform the community user of local air quality impacts due to roadway vehicles in their region of interest using a simplified modeling approach. Reduced-form air quality modeling is a useful tool for examining what-if scenarios of changes in emissions, such as those due to changes in traffic volume, fleet mix, or vehicle speed. Examining various scenarios of air quality impacts in this way can identify potentially at-risk populations located near roadways, and the effects that a change in traffic activity may have on them. C-LINE computes dispersion of primary mobile source pollutants using meteorological conditions for the region of interest and computes air-quality concentrations corresponding to these selected conditions. C-LINE functionality has been expanded to model emissions from port-related activities (e.g. ships, trucks, cranes, etc.) in a reduced-form modeling system for local-scale near-port air quality analysis. This presentation describes the Community modeling tools C-LINE and C-PORT that are intended to be used by local gove

  19. Reducing uncertainty in risk modeling for methylmercury exposure

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ponce, R.; Egeland, G.; Middaugh, J.

    The biomagnification and bioaccumulation of methylmercury in marine species represents a challenge for risk assessment related to the consumption of subsistence foods in Alaska. Because of the profound impact that food consumption advisories have on indigenous peoples seeking to preserve a way of life, there is a need to reduce uncertainty in risk assessment. Thus, research was initiated to reduce the uncertainty in assessing the health risks associated with the consumption of subsistence foods. Because marine subsistence foods typically contain elevated levels of methylmercury, preliminary research efforts have focused on methylmercury as the principal chemical of concern. Of particular interestmore » are the antagonistic effects of selenium on methylmercury toxicity. Because of this antagonism, methylmercury exposure through the consumption of marine mammal meat (with high selenium) may not be as toxic as comparable exposures through other sources of dietary intake, such as in the contaminated bread episode of Iraq (containing relatively low selenium). This hypothesis is supported by animal experiments showing reduced toxicity of methylmercury associated with marine mammal meat, by the antagonistic influence of selenium on methylmercury toxicity, and by negative clinical findings in adult populations exposed to methylmercury through a marine diet not subject to industrial contamination. Exploratory model development is underway to identify potential improvements and applications of current deterministic and probabilistic models, particularly by incorporating selenium as an antagonist in risk modeling methods.« less

  20. Construction of energy-stable Galerkin reduced order models.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kalashnikova, Irina; Barone, Matthew Franklin; Arunajatesan, Srinivasan

    2013-05-01

    This report aims to unify several approaches for building stable projection-based reduced order models (ROMs). Attention is focused on linear time-invariant (LTI) systems. The model reduction procedure consists of two steps: the computation of a reduced basis, and the projection of the governing partial differential equations (PDEs) onto this reduced basis. Two kinds of reduced bases are considered: the proper orthogonal decomposition (POD) basis and the balanced truncation basis. The projection step of the model reduction can be done in two ways: via continuous projection or via discrete projection. First, an approach for building energy-stable Galerkin ROMs for linear hyperbolicmore » or incompletely parabolic systems of PDEs using continuous projection is proposed. The idea is to apply to the set of PDEs a transformation induced by the Lyapunov function for the system, and to build the ROM in the transformed variables. The resulting ROM will be energy-stable for any choice of reduced basis. It is shown that, for many PDE systems, the desired transformation is induced by a special weighted L2 inner product, termed the %E2%80%9Csymmetry inner product%E2%80%9D. Attention is then turned to building energy-stable ROMs via discrete projection. A discrete counterpart of the continuous symmetry inner product, a weighted L2 inner product termed the %E2%80%9CLyapunov inner product%E2%80%9D, is derived. The weighting matrix that defines the Lyapunov inner product can be computed in a black-box fashion for a stable LTI system arising from the discretization of a system of PDEs in space. It is shown that a ROM constructed via discrete projection using the Lyapunov inner product will be energy-stable for any choice of reduced basis. Connections between the Lyapunov inner product and the inner product induced by the balanced truncation algorithm are made. Comparisons are also made between the symmetry inner product and the Lyapunov inner product. The performance of ROMs

  1. Hyperspectral imaging-based spatially-resolved technique for accurate measurement of the optical properties of horticultural products

    NASA Astrophysics Data System (ADS)

    Cen, Haiyan

    Hyperspectral imaging-based spatially-resolved technique is promising for determining the optical properties and quality attributes of horticultural and food products. However, considerable challenges still exist for accurate determination of spectral absorption and scattering properties from intact horticultural products. The objective of this research was, therefore, to develop and optimize hyperspectral imaging-based spatially-resolved technique for accurate measurement of the optical properties of horticultural products. Monte Carlo simulations and experiments for model samples of known optical properties were performed to optimize the inverse algorithm of a single-layer diffusion model and the optical designs, for extracting the absorption (micro a) and reduced scattering (micros') coefficients from spatially-resolved reflectance profiles. The logarithm and integral data transformation and the relative weighting methods were found to greatly improve the parameter estimation accuracy with the relative errors of 10.4%, 10.7%, and 11.4% for micro a, and 6.6%, 7.0%, and 7.1% for micros', respectively. More accurate measurements of optical properties were obtained when the light beam was of Gaussian type with the diameter of less than 1 mm, and the minimum and maximum source-detector distances were 1.5 mm and 10--20 transport mean free paths, respectively. An optical property measuring prototype was built, based on the optimization results, and evaluated for automatic measurement of absorption and reduced scattering coefficients for the wavelengths of 500--1,000 nm. The instrument was used to measure the optical properties, and assess quality/maturity, of 500 'Redstar' peaches and 1039 'Golden Delicious' (GD) and 1040 'Delicious' (RD) apples. A separate study was also conducted on confocal laser scanning and scanning electron microscopic image analysis and compression test of fruit tissue specimens to measure the structural and mechanical properties of 'Golden

  2. An Accurate Projector Calibration Method Based on Polynomial Distortion Representation

    PubMed Central

    Liu, Miao; Sun, Changku; Huang, Shujun; Zhang, Zonghua

    2015-01-01

    In structure light measurement systems or 3D printing systems, the errors caused by optical distortion of a digital projector always affect the precision performance and cannot be ignored. Existing methods to calibrate the projection distortion rely on calibration plate and photogrammetry, so the calibration performance is largely affected by the quality of the plate and the imaging system. This paper proposes a new projector calibration approach that makes use of photodiodes to directly detect the light emitted from a digital projector. By analyzing the output sequence of the photoelectric module, the pixel coordinates can be accurately obtained by the curve fitting method. A polynomial distortion representation is employed to reduce the residuals of the traditional distortion representation model. Experimental results and performance evaluation show that the proposed calibration method is able to avoid most of the disadvantages in traditional methods and achieves a higher accuracy. This proposed method is also practically applicable to evaluate the geometric optical performance of other optical projection system. PMID:26492247

  3. A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina

    PubMed Central

    Maturana, Matias I.; Apollo, Nicholas V.; Hadjinicolaou, Alex E.; Garrett, David J.; Cloherty, Shaun L.; Kameneva, Tatiana; Grayden, David B.; Ibbotson, Michael R.; Meffin, Hamish

    2016-01-01

    Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron’s electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. PMID:27035143

  4. Validation of a new noniterative method for accurate position determination of a scanning laser vibrometer

    NASA Astrophysics Data System (ADS)

    Pauwels, Steven; Boucart, Nick; Dierckx, Benoit; Van Vlierberghe, Pieter

    2000-05-01

    The use of a scanning laser Doppler vibrometer for vibration testing is becoming a popular instrument. The scanning laser Doppler vibrometer is a non-contacting transducer that can measure many points at a high spatial resolution in a short time. Manually aiming the laser beam at the points that need to be measured is very time consuming. In order to use it effectively, the position of the laser Doppler vibrometer needs to be determined relative to the structure. If the position of the laser Doppler vibrometer is known, any visible point on the structure can be hit and measured automatically. A new algorithm for this position determination is developed, based on a geometry model of the structure. After manually aiming the laser beam at 4 or more known points, the laser position and orientation relative to the structure is determined. Using this calculated position and orientation a list with the mirror angles for every measurement point is generated, which is used during the measurement. The algorithm is validated using 3 practical cases. In the first case a plate is used of which the points are measured very accurately, so the geometry model is assumed to be perfect. The second case is a brake disc. Here the geometry points are measured with a ruler, thus not so accurate. The final validation is done on a body in white of a car. A reduced finite element model is used as geometry model. This calibration shows that the new algorithm is very effective and practically usable.

  5. Development of a New Model for Accurate Prediction of Cloud Water Deposition on Vegetation

    NASA Astrophysics Data System (ADS)

    Katata, G.; Nagai, H.; Wrzesinsky, T.; Klemm, O.; Eugster, W.; Burkard, R.

    2006-12-01

    Scarcity of water resources in arid and semi-arid areas is of great concern in the light of population growth and food shortages. Several experiments focusing on cloud (fog) water deposition on the land surface suggest that cloud water plays an important role in water resource in such regions. A one-dimensional vegetation model including the process of cloud water deposition on vegetation has been developed to better predict cloud water deposition on the vegetation. New schemes to calculate capture efficiency of leaf, cloud droplet size distribution, and gravitational flux of cloud water were incorporated in the model. Model calculations were compared with the data acquired at the Norway spruce forest at the Waldstein site, Germany. High performance of the model was confirmed by comparisons of calculated net radiation, sensible and latent heat, and cloud water fluxes over the forest with measurements. The present model provided a better prediction of measured turbulent and gravitational fluxes of cloud water over the canopy than the Lovett model, which is a commonly used cloud water deposition model. Detailed calculations of evapotranspiration and of turbulent exchange of heat and water vapor within the canopy and the modifications are necessary for accurate prediction of cloud water deposition. Numerical experiments to examine the dependence of cloud water deposition on the vegetation species (coniferous and broad-leaved trees, flat and cylindrical grasses) and structures (Leaf Area Index (LAI) and canopy height) are performed using the presented model. The results indicate that the differences of leaf shape and size have a large impact on cloud water deposition. Cloud water deposition also varies with the growth of vegetation and seasonal change of LAI. We found that the coniferous trees whose height and LAI are 24 m and 2.0 m2m-2, respectively, produce the largest amount of cloud water deposition in all combinations of vegetation species and structures in the

  6. Estimating Gravity Biases with Wavelets in Support of a 1-cm Accurate Geoid Model

    NASA Astrophysics Data System (ADS)

    Ahlgren, K.; Li, X.

    2017-12-01

    Systematic errors that reside in surface gravity datasets are one of the major hurdles in constructing a high-accuracy geoid model at high resolutions. The National Oceanic and Atmospheric Administration's (NOAA) National Geodetic Survey (NGS) has an extensive historical surface gravity dataset consisting of approximately 10 million gravity points that are known to have systematic biases at the mGal level (Saleh et al. 2013). As most relevant metadata is absent, estimating and removing these errors to be consistent with a global geopotential model and airborne data in the corresponding wavelength is quite a difficult endeavor. However, this is crucial to support a 1-cm accurate geoid model for the United States. With recently available independent gravity information from GRACE/GOCE and airborne gravity from the NGS Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project, several different methods of bias estimation are investigated which utilize radial basis functions and wavelet decomposition. We estimate a surface gravity value by incorporating a satellite gravity model, airborne gravity data, and forward-modeled topography at wavelet levels according to each dataset's spatial wavelength. Considering the estimated gravity values over an entire gravity survey, an estimate of the bias and/or correction for the entire survey can be found and applied. In order to assess the accuracy of each bias estimation method, two techniques are used. First, each bias estimation method is used to predict the bias for two high-quality (unbiased and high accuracy) geoid slope validation surveys (GSVS) (Smith et al. 2013 & Wang et al. 2017). Since these surveys are unbiased, the various bias estimation methods should reflect that and provide an absolute accuracy metric for each of the bias estimation methods. Secondly, the corrected gravity datasets from each of the bias estimation methods are used to build a geoid model. The accuracy of each geoid model

  7. A strategy for reducing gross errors in the generalized Born models of implicit solvation

    PubMed Central

    Onufriev, Alexey V.; Sigalov, Grigori

    2011-01-01

    The “canonical” generalized Born (GB) formula [C. Still, A. Tempczyk, R. C. Hawley, and T. Hendrickson, J. Am. Chem. Soc. 112, 6127 (1990)] is known to provide accurate estimates for total electrostatic solvation energies ΔGel of biomolecules if the corresponding effective Born radii are accurate. Here we show that even if the effective Born radii are perfectly accurate, the canonical formula still exhibits significant number of gross errors (errors larger than 2kBT relative to numerical Poisson equation reference) in pairwise interactions between individual atomic charges. Analysis of exact analytical solutions of the Poisson equation (PE) for several idealized nonspherical geometries reveals two distinct spatial modes of the PE solution; these modes are also found in realistic biomolecular shapes. The canonical GB Green function misses one of two modes seen in the exact PE solution, which explains the observed gross errors. To address the problem and reduce gross errors of the GB formalism, we have used exact PE solutions for idealized nonspherical geometries to suggest an alternative analytical Green function to replace the canonical GB formula. The proposed functional form is mathematically nearly as simple as the original, but depends not only on the effective Born radii but also on their gradients, which allows for better representation of details of nonspherical molecular shapes. In particular, the proposed functional form captures both modes of the PE solution seen in nonspherical geometries. Tests on realistic biomolecular structures ranging from small peptides to medium size proteins show that the proposed functional form reduces gross pairwise errors in all cases, with the amount of reduction varying from more than an order of magnitude for small structures to a factor of 2 for the largest ones. PMID:21528947

  8. A Reduced-Order Model for Efficient Simulation of Synthetic Jet Actuators

    NASA Technical Reports Server (NTRS)

    Yamaleev, Nail K.; Carpenter, Mark H.

    2003-01-01

    A new reduced-order model of multidimensional synthetic jet actuators that combines the accuracy and conservation properties of full numerical simulation methods with the efficiency of simplified zero-order models is proposed. The multidimensional actuator is simulated by solving the time-dependent compressible quasi-1-D Euler equations, while the diaphragm is modeled as a moving boundary. The governing equations are approximated with a fourth-order finite difference scheme on a moving mesh such that one of the mesh boundaries coincides with the diaphragm. The reduced-order model of the actuator has several advantages. In contrast to the 3-D models, this approach provides conservation of mass, momentum, and energy. Furthermore, the new method is computationally much more efficient than the multidimensional Navier-Stokes simulation of the actuator cavity flow, while providing practically the same accuracy in the exterior flowfield. The most distinctive feature of the present model is its ability to predict the resonance characteristics of synthetic jet actuators; this is not practical when using the 3-D models because of the computational cost involved. Numerical results demonstrating the accuracy of the new reduced-order model and its limitations are presented.

  9. Generating Converged Accurate Free Energy Surfaces for Chemical Reactions with a Force-Matched Semiempirical Model.

    PubMed

    Kroonblawd, Matthew P; Pietrucci, Fabio; Saitta, Antonino Marco; Goldman, Nir

    2018-04-10

    We demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using density functional theory (DFT) is a highly accurate approach to generate free energy surfaces for chemical reactions, but the extreme computational cost often limits the time scales and range of thermodynamic states that can feasibly be studied. In contrast, DFTB is a semiempirical quantum method that affords up to a thousandfold reduction in cost and can recover DFT-level accuracy. Here, we show that a force-matched DFTB model for aqueous glycine condensation reactions yields free energy surfaces that are consistent with experimental observations of reaction energetics. Convergence analysis reveals that multiple nanoseconds of combined trajectory are needed to reach a steady-fluctuating free energy estimate for glycine condensation. Predictive accuracy of force-matched DFTB is demonstrated by direct comparison to DFT, with the two approaches yielding surfaces with large regions that differ by only a few kcal mol -1 .

  10. Generating Converged Accurate Free Energy Surfaces for Chemical Reactions with a Force-Matched Semiempirical Model

    DOE PAGES

    Kroonblawd, Matthew P.; Pietrucci, Fabio; Saitta, Antonino Marco; ...

    2018-03-15

    Here, we demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using density functional theory (DFT) is a highly accurate approach to generate free energy surfaces for chemical reactions, but the extreme computational cost often limits the time scales and range of thermodynamic states that can feasibly be studied. In contrast, DFTB is a semiempirical quantum method that affords up to a thousandfold reduction in cost and can recover DFT-level accuracy. Here, we show that a force-matched DFTBmore » model for aqueous glycine condensation reactions yields free energy surfaces that are consistent with experimental observations of reaction energetics. Convergence analysis reveals that multiple nanoseconds of combined trajectory are needed to reach a steady-fluctuating free energy estimate for glycine condensation. Predictive accuracy of force-matched DFTB is demonstrated by direct comparison to DFT, with the two approaches yielding surfaces with large regions that differ by only a few kcal mol –1.« less

  11. Generating Converged Accurate Free Energy Surfaces for Chemical Reactions with a Force-Matched Semiempirical Model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kroonblawd, Matthew P.; Pietrucci, Fabio; Saitta, Antonino Marco

    Here, we demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using density functional theory (DFT) is a highly accurate approach to generate free energy surfaces for chemical reactions, but the extreme computational cost often limits the time scales and range of thermodynamic states that can feasibly be studied. In contrast, DFTB is a semiempirical quantum method that affords up to a thousandfold reduction in cost and can recover DFT-level accuracy. Here, we show that a force-matched DFTBmore » model for aqueous glycine condensation reactions yields free energy surfaces that are consistent with experimental observations of reaction energetics. Convergence analysis reveals that multiple nanoseconds of combined trajectory are needed to reach a steady-fluctuating free energy estimate for glycine condensation. Predictive accuracy of force-matched DFTB is demonstrated by direct comparison to DFT, with the two approaches yielding surfaces with large regions that differ by only a few kcal mol –1.« less

  12. Reduced Order Models for Reactions of Energetic Materials

    NASA Astrophysics Data System (ADS)

    Kober, Edward

    The formulation of reduced order models for the reaction chemistry of energetic materials under high pressures is needed for the development of mesoscale models in the areas of initiation, deflagration and detonation. Phenomenologically, 4-8 step models have been formulated from the analysis of cook-off data by analyzing the temperature rise of heated samples. Reactive molecular dynamics simulations have been used to simulate many of these processes, but reducing the results of those simulations to simple models has not been achieved. Typically, these efforts have focused on identifying molecular species and detailing specific chemical reactions. An alternative approach is presented here that is based on identifying the coordination geometries of each atom in the simulation and tracking classes of reactions by correlated changes in these geometries. Here, every atom and type of reaction is documented for every time step; no information is lost from unsuccessful molecular identification. Principal Component Analysis methods can then be used to map out the effective chemical reaction steps. For HMX and TATB decompositions simulated with ReaxFF, 90% of the data can be explained by 4-6 steps, generating models similar to those from the cook-off analysis. By performing these simulations at a variety of temperatures and pressures, both the activation and reaction energies and volumes can then be extracted.

  13. Determining accurate distances to nearby galaxies

    NASA Astrophysics Data System (ADS)

    Bonanos, Alceste Zoe

    2005-11-01

    Determining accurate distances to nearby or distant galaxies is a very simple conceptually, yet complicated in practice, task. Presently, distances to nearby galaxies are only known to an accuracy of 10-15%. The current anchor galaxy of the extragalactic distance scale is the Large Magellanic Cloud, which has large (10-15%) systematic uncertainties associated with it, because of its morphology, its non-uniform reddening and the unknown metallicity dependence of the Cepheid period-luminosity relation. This work aims to determine accurate distances to some nearby galaxies, and subsequently help reduce the error in the extragalactic distance scale and the Hubble constant H 0 . In particular, this work presents the first distance determination of the DIRECT Project to M33 with detached eclipsing binaries. DIRECT aims to obtain a new anchor galaxy for the extragalactic distance scale by measuring direct, accurate (to 5%) distances to two Local Group galaxies, M31 and M33, with detached eclipsing binaries. It involves a massive variability survey of these galaxies and subsequent photometric and spectroscopic follow-up of the detached binaries discovered. In this work, I also present a catalog of variable stars discovered in one of the DIRECT fields, M31Y, which includes 41 eclipsing binaries. Additionally, we derive the distance to the Draco Dwarf Spheroidal galaxy, with ~100 RR Lyrae found in our first CCD variability study of this galaxy. A "hybrid" method of discovering Cepheids with ground-based telescopes is described next. It involves applying the image subtraction technique on the images obtained from ground-based telescopes and then following them up with the Hubble Space Telescope to derive Cepheid period-luminosity distances. By re-analyzing ESO Very Large Telescope data on M83 (NGC 5236), we demonstrate that this method is much more powerful for detecting variability, especially in crowded fields. I finally present photometry for the Wolf-Rayet binary WR 20a

  14. Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: implications for three-dimensional modeling.

    PubMed

    Bhaskara, Ramachandra M; Padhi, Amrita; Srinivasan, Narayanaswamy

    2014-07-01

    With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. © 2013 Wiley Periodicals, Inc.

  15. Reduced complexity structural modeling for automated airframe synthesis

    NASA Technical Reports Server (NTRS)

    Hajela, Prabhat

    1987-01-01

    A procedure is developed for the optimum sizing of wing structures based on representing the built-up finite element assembly of the structure by equivalent beam models. The reduced-order beam models are computationally less demanding in an optimum design environment which dictates repetitive analysis of several trial designs. The design procedure is implemented in a computer program requiring geometry and loading information to create the wing finite element model and its equivalent beam model, and providing a rapid estimate of the optimum weight obtained from a fully stressed design approach applied to the beam. The synthesis procedure is demonstrated for representative conventional-cantilever and joined wing configurations.

  16. Memory conformity affects inaccurate memories more than accurate memories.

    PubMed

    Wright, Daniel B; Villalba, Daniella K

    2012-01-01

    After controlling for initial confidence, inaccurate memories were shown to be more easily distorted than accurate memories. In two experiments groups of participants viewed 50 stimuli and were then presented with these stimuli plus 50 fillers. During this test phase participants reported their confidence that each stimulus was originally shown. This was followed by computer-generated responses from a bogus participant. After being exposed to this response participants again rated the confidence of their memory. The computer-generated responses systematically distorted participants' responses. Memory distortion depended on initial memory confidence, with uncertain memories being more malleable than confident memories. This effect was moderated by whether the participant's memory was initially accurate or inaccurate. Inaccurate memories were more malleable than accurate memories. The data were consistent with a model describing two types of memory (i.e., recollective and non-recollective memories), which differ in how susceptible these memories are to memory distortion.

  17. Predicting Statistical Response and Extreme Events in Uncertainty Quantification through Reduced-Order Models

    NASA Astrophysics Data System (ADS)

    Qi, D.; Majda, A.

    2017-12-01

    A low-dimensional reduced-order statistical closure model is developed for quantifying the uncertainty in statistical sensitivity and intermittency in principal model directions with largest variability in high-dimensional turbulent system and turbulent transport models. Imperfect model sensitivity is improved through a recent mathematical strategy for calibrating model errors in a training phase, where information theory and linear statistical response theory are combined in a systematic fashion to achieve the optimal model performance. The idea in the reduced-order method is from a self-consistent mathematical framework for general systems with quadratic nonlinearity, where crucial high-order statistics are approximated by a systematic model calibration procedure. Model efficiency is improved through additional damping and noise corrections to replace the expensive energy-conserving nonlinear interactions. Model errors due to the imperfect nonlinear approximation are corrected by tuning the model parameters using linear response theory with an information metric in a training phase before prediction. A statistical energy principle is adopted to introduce a global scaling factor in characterizing the higher-order moments in a consistent way to improve model sensitivity. Stringent models of barotropic and baroclinic turbulence are used to display the feasibility of the reduced-order methods. Principal statistical responses in mean and variance can be captured by the reduced-order models with accuracy and efficiency. Besides, the reduced-order models are also used to capture crucial passive tracer field that is advected by the baroclinic turbulent flow. It is demonstrated that crucial principal statistical quantities like the tracer spectrum and fat-tails in the tracer probability density functions in the most important large scales can be captured efficiently with accuracy using the reduced-order tracer model in various dynamical regimes of the flow field with

  18. Fixed-Wing Micro Aerial Vehicle for Accurate Corridor Mapping

    NASA Astrophysics Data System (ADS)

    Rehak, M.; Skaloud, J.

    2015-08-01

    In this study we present a Micro Aerial Vehicle (MAV) equipped with precise position and attitude sensors that together with a pre-calibrated camera enables accurate corridor mapping. The design of the platform is based on widely available model components to which we integrate an open-source autopilot, customized mass-market camera and navigation sensors. We adapt the concepts of system calibration from larger mapping platforms to MAV and evaluate them practically for their achievable accuracy. We present case studies for accurate mapping without ground control points: first for a block configuration, later for a narrow corridor. We evaluate the mapping accuracy with respect to checkpoints and digital terrain model. We show that while it is possible to achieve pixel (3-5 cm) mapping accuracy in both cases, precise aerial position control is sufficient for block configuration, the precise position and attitude control is required for corridor mapping.

  19. SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models

    PubMed Central

    2014-01-01

    Background Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. Results SnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data. Conclusions SnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/. PMID:24980894

  20. Quantitative cardiac SPECT reconstruction with reduced image degradation due to patient anatomy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Tsui, B.M.W.; Zhao, X.D.; Gregoriou, G.K.

    1994-12-01

    Patient anatomy has complicated effects on cardiac SPECT images. The authors investigated reconstruction methods which substantially reduced these effects for improved image quality. A 3D mathematical cardiac-torso (MCAT) phantom which models the anatomical structures in the thorax region were used in the study. The phantom was modified to simulate variations in patient anatomy including regions of natural thinning along the myocardium, body size, diaphragmatic shape, gender, and size and shape of breasts for female patients. Distributions of attenuation coefficients and Tl-201 uptake in different organs in a normal patient were also simulated. Emission projection data were generated from the phantomsmore » including effects of attenuation and detector response. The authors have observed the attenuation-induced artifacts caused by patient anatomy in the conventional FBP reconstructed images. Accurate attenuation compensation using iterative reconstruction algorithms and attenuation maps substantially reduced the image artifacts and improved quantitative accuracy. They conclude that reconstruction methods which accurately compensate for non-uniform attenuation can substantially reduce image degradation caused by variations in patient anatomy in cardiac SPECT.« less

  1. Accurate Structural Correlations from Maximum Likelihood Superpositions

    PubMed Central

    Theobald, Douglas L; Wuttke, Deborah S

    2008-01-01

    The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biomolecular mechanisms and for relating structure to function. Here we report a highly accurate technique for inferring the major modes of structural correlation in macromolecules using likelihood-based statistical analysis of sets of structures. This method is generally applicable to any ensemble of related molecules, including families of nuclear magnetic resonance (NMR) models, different crystal forms of a protein, and structural alignments of homologous proteins, as well as molecular dynamics trajectories. Dominant modes of structural correlation are determined using principal components analysis (PCA) of the maximum likelihood estimate of the correlation matrix. The correlations we identify are inherently independent of the statistical uncertainty and dynamic heterogeneity associated with the structural coordinates. We additionally present an easily interpretable method (“PCA plots”) for displaying these positional correlations by color-coding them onto a macromolecular structure. Maximum likelihood PCA of structural superpositions, and the structural PCA plots that illustrate the results, will facilitate the accurate determination of dynamic structural correlations analyzed in diverse fields of structural biology. PMID:18282091

  2. Accurate prediction of personalized olfactory perception from large-scale chemoinformatic features.

    PubMed

    Li, Hongyang; Panwar, Bharat; Omenn, Gilbert S; Guan, Yuanfang

    2018-02-01

    The olfactory stimulus-percept problem has been studied for more than a century, yet it is still hard to precisely predict the odor given the large-scale chemoinformatic features of an odorant molecule. A major challenge is that the perceived qualities vary greatly among individuals due to different genetic and cultural backgrounds. Moreover, the combinatorial interactions between multiple odorant receptors and diverse molecules significantly complicate the olfaction prediction. Many attempts have been made to establish structure-odor relationships for intensity and pleasantness, but no models are available to predict the personalized multi-odor attributes of molecules. In this study, we describe our winning algorithm for predicting individual and population perceptual responses to various odorants in the DREAM Olfaction Prediction Challenge. We find that random forest model consisting of multiple decision trees is well suited to this prediction problem, given the large feature spaces and high variability of perceptual ratings among individuals. Integrating both population and individual perceptions into our model effectively reduces the influence of noise and outliers. By analyzing the importance of each chemical feature, we find that a small set of low- and nondegenerative features is sufficient for accurate prediction. Our random forest model successfully predicts personalized odor attributes of structurally diverse molecules. This model together with the top discriminative features has the potential to extend our understanding of olfactory perception mechanisms and provide an alternative for rational odorant design.

  3. An accurate front capturing scheme for tumor growth models with a free boundary limit

    NASA Astrophysics Data System (ADS)

    Liu, Jian-Guo; Tang, Min; Wang, Li; Zhou, Zhennan

    2018-07-01

    We consider a class of tumor growth models under the combined effects of density-dependent pressure and cell multiplication, with a free boundary model as its singular limit when the pressure-density relationship becomes highly nonlinear. In particular, the constitutive law connecting pressure p and density ρ is p (ρ) = m/m-1 ρ m - 1, and when m ≫ 1, the cell density ρ may evolve its support according to a pressure-driven geometric motion with sharp interface along its boundary. The nonlinearity and degeneracy in the diffusion bring great challenges in numerical simulations. Prior to the present paper, there is lack of standard mechanism to numerically capture the front propagation speed as m ≫ 1. In this paper, we develop a numerical scheme based on a novel prediction-correction reformulation that can accurately approximate the front propagation even when the nonlinearity is extremely strong. We show that the semi-discrete scheme naturally connects to the free boundary limit equation as m → ∞. With proper spatial discretization, the fully discrete scheme has improved stability, preserves positivity, and can be implemented without nonlinear solvers. Finally, extensive numerical examples in both one and two dimensions are provided to verify the claimed properties in various applications.

  4. Towards Relaxing the Spherical Solar Radiation Pressure Model for Accurate Orbit Predictions

    NASA Astrophysics Data System (ADS)

    Lachut, M.; Bennett, J.

    2016-09-01

    The well-known cannonball model has been used ubiquitously to capture the effects of atmospheric drag and solar radiation pressure on satellites and/or space debris for decades. While it lends itself naturally to spherical objects, its validity in the case of non-spherical objects has been debated heavily for years throughout the space situational awareness community. One of the leading motivations to improve orbit predictions by relaxing the spherical assumption, is the ongoing demand for more robust and reliable conjunction assessments. In this study, we explore the orbit propagation of a flat plate in a near-GEO orbit under the influence of solar radiation pressure, using a Lambertian BRDF model. Consequently, this approach will account for the spin rate and orientation of the object, which is typically determined in practice using a light curve analysis. Here, simulations will be performed which systematically reduces the spin rate to demonstrate the point at which the spherical model no longer describes the orbital elements of the spinning plate. Further understanding of this threshold would provide insight into when a higher fidelity model should be used, thus resulting in improved orbit propagations. Therefore, the work presented here is of particular interest to organizations and researchers that maintain their own catalog, and/or perform conjunction analyses.

  5. Accurate calculation and modeling of the adiabatic connection in density functional theory

    NASA Astrophysics Data System (ADS)

    Teale, A. M.; Coriani, S.; Helgaker, T.

    2010-04-01

    AC. When parametrized in terms of the same input data, the AC-CI model offers improved performance over the corresponding AC-D model, which is shown to be the lowest-order contribution to the AC-CI model. The utility of the accurately calculated AC curves for the analysis of standard density functionals is demonstrated for the BLYP exchange-correlation functional and the interaction-strength-interpolation (ISI) model AC integrand. From the results of this analysis, we investigate the performance of our proposed two-parameter AC-D and AC-CI models when a simple density functional for the AC at infinite interaction strength is employed in place of information at the fully interacting point. The resulting two-parameter correlation functionals offer a qualitatively correct behavior of the AC integrand with much improved accuracy over previous attempts. The AC integrands in the present work are recommended as a basis for further work, generating functionals that avoid spurious error cancellations between exchange and correlation energies and give good accuracy for the range of densities and types of correlation contained in the systems studied here.

  6. An Accurately Controlled Antagonistic Shape Memory Alloy Actuator with Self-Sensing

    PubMed Central

    Wang, Tian-Miao; Shi, Zhen-Yun; Liu, Da; Ma, Chen; Zhang, Zhen-Hua

    2012-01-01

    With the progress of miniaturization, shape memory alloy (SMA) actuators exhibit high energy density, self-sensing ability and ease of fabrication, which make them well suited for practical applications. This paper presents a self-sensing controlled actuator drive that was designed using antagonistic pairs of SMA wires. Under a certain pre-strain and duty cycle, the stress between two wires becomes constant. Meanwhile, the strain to resistance curve can minimize the hysteresis gap between the heating and the cooling paths. The curves of both wires are then modeled by fitting polynomials such that the measured resistance can be used directly to determine the difference between the testing values and the target strain. The hysteresis model of strains to duty cycle difference has been used as compensation. Accurate control is demonstrated through step response and sinusoidal tracking. The experimental results show that, under a combination control program, the root-mean-square error can be reduced to 1.093%. The limited bandwidth of the frequency is estimated to be 0.15 Hz. Two sets of instruments with three degrees of freedom are illustrated to show how this type actuator could be potentially implemented. PMID:22969368

  7. Chasing Perfection: Should We Reduce Model Uncertainty in Carbon Cycle-Climate Feedbacks

    NASA Astrophysics Data System (ADS)

    Bonan, G. B.; Lombardozzi, D.; Wieder, W. R.; Lindsay, K. T.; Thomas, R. Q.

    2015-12-01

    Earth system model simulations of the terrestrial carbon (C) cycle show large multi-model spread in the carbon-concentration and carbon-climate feedback parameters. Large differences among models are also seen in their simulation of global vegetation and soil C stocks and other aspects of the C cycle, prompting concern about model uncertainty and our ability to faithfully represent fundamental aspects of the terrestrial C cycle in Earth system models. Benchmarking analyses that compare model simulations with common datasets have been proposed as a means to assess model fidelity with observations, and various model-data fusion techniques have been used to reduce model biases. While such efforts will reduce multi-model spread, they may not help reduce uncertainty (and increase confidence) in projections of the C cycle over the twenty-first century. Many ecological and biogeochemical processes represented in Earth system models are poorly understood at both the site scale and across large regions, where biotic and edaphic heterogeneity are important. Our experience with the Community Land Model (CLM) suggests that large uncertainty in the terrestrial C cycle and its feedback with climate change is an inherent property of biological systems. The challenge of representing life in Earth system models, with the rich diversity of lifeforms and complexity of biological systems, may necessitate a multitude of modeling approaches to capture the range of possible outcomes. Such models should encompass a range of plausible model structures. We distinguish between model parameter uncertainty and model structural uncertainty. Focusing on improved parameter estimates may, in fact, limit progress in assessing model structural uncertainty associated with realistically representing biological processes. Moreover, higher confidence may be achieved through better process representation, but this does not necessarily reduce uncertainty.

  8. ON THE PROPER USE OF THE REDUCED SPEED OF LIGHT APPROXIMATION

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Gnedin, Nickolay Y., E-mail: gnedin@fnal.gov

    I show that the reduced speed of light (RSL) approximation, when used properly (i.e., as originally designed—only for local sources but not for the cosmic background), remains a highly accurate numerical method for modeling cosmic reionization. Simulated ionization and star formation histories from the “Cosmic Reionization on Computers” project are insensitive to the adopted value of the RSL for as long as that value does not fall below about 10% of the true speed of light. A recent claim of the failure of the RSL approximation in the Illustris reionization model appears to be due to the effective speed ofmore » light being reduced in the equation for the cosmic background too and hence illustrates the importance of maintaining the correct speed of light in modeling the cosmic background.« less

  9. A Reduced Model for the Magnetorotational Instability

    NASA Astrophysics Data System (ADS)

    Jamroz, Ben; Julien, Keith; Knobloch, Edgar

    2008-11-01

    The magnetorotational instability is investigated within the shearing box approximation in the large Elsasser number regime. In this regime, which is of fundamental importance to astrophysical accretion disk theory, shear is the dominant source of energy, but the instability itself requires the presence of a weaker vertical magnetic field. Dissipative effects are weaker still. However, they are sufficiently large to permit a nonlinear feedback mechanism whereby the turbulent stresses generated by the MRI act on and modify the local background shear in the angular velocity profile. To date this response has been omitted in shearing box simulations and is captured by a reduced pde model derived here from the global MHD fluid equations using multiscale asymptotic perturbation theory. Results from numerical simulations of the reduced pde model indicate a linear phase of exponential growth followed by a nonlinear adjustment to algebraic growth and decay in the fluctuating quantities. Remarkably, the velocity and magnetic field correlations associated with these algebraic growth and decay laws conspire to achieve saturation of the angular momentum transport. The inclusion of subdominant ohmic dissipation arrests the algebraic growth of the fluctuations on a longer, dissipative time scale.

  10. Transport coefficient computation based on input/output reduced order models

    NASA Astrophysics Data System (ADS)

    Hurst, Joshua L.

    The guiding purpose of this thesis is to address the optimal material design problem when the material description is a molecular dynamics model. The end goal is to obtain a simplified and fast model that captures the property of interest such that it can be used in controller design and optimization. The approach is to examine model reduction analysis and methods to capture a specific property of interest, in this case viscosity, or more generally complex modulus or complex viscosity. This property and other transport coefficients are defined by a input/output relationship and this motivates model reduction techniques that are tailored to preserve input/output behavior. In particular Singular Value Decomposition (SVD) based methods are investigated. First simulation methods are identified that are amenable to systems theory analysis. For viscosity, these models are of the Gosling and Lees-Edwards type. They are high order nonlinear Ordinary Differential Equations (ODEs) that employ Periodic Boundary Conditions. Properties can be calculated from the state trajectories of these ODEs. In this research local linear approximations are rigorously derived and special attention is given to potentials that are evaluated with Periodic Boundary Conditions (PBC). For the Gosling description LTI models are developed from state trajectories but are found to have limited success in capturing the system property, even though it is shown that full order LTI models can be well approximated by reduced order LTI models. For the Lees-Edwards SLLOD type model nonlinear ODEs will be approximated by a Linear Time Varying (LTV) model about some nominal trajectory and both balanced truncation and Proper Orthogonal Decomposition (POD) will be used to assess the plausibility of reduced order models to this system description. An immediate application of the derived LTV models is Quasilinearization or Waveform Relaxation. Quasilinearization is a Newton's method applied to the ODE operator

  11. AN OVERVIEW OF REDUCED ORDER MODELING TECHNIQUES FOR SAFETY APPLICATIONS

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mandelli, D.; Alfonsi, A.; Talbot, P.

    2016-10-01

    The RISMC project is developing new advanced simulation-based tools to perform Computational Risk Analysis (CRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermal-hydraulic behavior of the reactors primary and secondary systems, but also external event temporal evolution and component/system ageing. Thus, this is not only a multi-physics problem being addressed, but also a multi-scale problem (both spatial, µm-mm-m, and temporal, seconds-hours-years). As part of the RISMC CRA approach, a large amount of computationally-expensive simulation runs may be required. An important aspect is that even though computational power is growing, themore » overall computational cost of a RISMC analysis using brute-force methods may be not viable for certain cases. A solution that is being evaluated to assist the computational issue is the use of reduced order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RISMC analysis computational cost by decreasing the number of simulation runs; for this analysis improvement we used surrogate models instead of the actual simulation codes. This article focuses on the use of reduced order modeling techniques that can be applied to RISMC analyses in order to generate, analyze, and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (microseconds instead of hours/days).« less

  12. Mixture models reveal multiple positional bias types in RNA-Seq data and lead to accurate transcript concentration estimates.

    PubMed

    Tuerk, Andreas; Wiktorin, Gregor; Güler, Serhat

    2017-05-01

    Accuracy of transcript quantification with RNA-Seq is negatively affected by positional fragment bias. This article introduces Mix2 (rd. "mixquare"), a transcript quantification method which uses a mixture of probability distributions to model and thereby neutralize the effects of positional fragment bias. The parameters of Mix2 are trained by Expectation Maximization resulting in simultaneous transcript abundance and bias estimates. We compare Mix2 to Cufflinks, RSEM, eXpress and PennSeq; state-of-the-art quantification methods implementing some form of bias correction. On four synthetic biases we show that the accuracy of Mix2 overall exceeds the accuracy of the other methods and that its bias estimates converge to the correct solution. We further evaluate Mix2 on real RNA-Seq data from the Microarray and Sequencing Quality Control (MAQC, SEQC) Consortia. On MAQC data, Mix2 achieves improved correlation to qPCR measurements with a relative increase in R2 between 4% and 50%. Mix2 also yields repeatable concentration estimates across technical replicates with a relative increase in R2 between 8% and 47% and reduced standard deviation across the full concentration range. We further observe more accurate detection of differential expression with a relative increase in true positives between 74% and 378% for 5% false positives. In addition, Mix2 reveals 5 dominant biases in MAQC data deviating from the common assumption of a uniform fragment distribution. On SEQC data, Mix2 yields higher consistency between measured and predicted concentration ratios. A relative error of 20% or less is obtained for 51% of transcripts by Mix2, 40% of transcripts by Cufflinks and RSEM and 30% by eXpress. Titration order consistency is correct for 47% of transcripts for Mix2, 41% for Cufflinks and RSEM and 34% for eXpress. We, further, observe improved repeatability across laboratory sites with a relative increase in R2 between 8% and 44% and reduced standard deviation.

  13. Highly accurate nephelometric titrimetry.

    PubMed

    Zhan, Xiancheng; Li, Chengrong; Li, Zhiyi; Yang, Xiucen; Zhong, Shuguang; Yi, Tao

    2004-02-01

    A method that accurately indicates the end-point of precipitation reactions by the measurement of the relative intensity of the scattered light in the titrate is presented. A new nephelometric titrator with an internal nephelometric sensor has been devised. The work of the titrator including the sensor and change in the turbidity of the titrate and intensity of the scattered light are described. The accuracy of the nephelometric titrimetry is discussed theoretically. The titration of NaCl with AgNO(3) serves as a model. A relative error as well as deviation is within 0.2% under the experimental conditions. The applicability of the titrimetry in pharmaceutical analyses, for example, phenytoin sodium and procaine hydrochloride, is generally illustrated. Copyright 2004 Wiley-Liss, Inc. and the American Pharmacists Association

  14. A novel medical information management and decision model for uncertain demand optimization.

    PubMed

    Bi, Ya

    2015-01-01

    Accurately planning the procurement volume is an effective measure for controlling the medicine inventory cost. Due to uncertain demand it is difficult to make accurate decision on procurement volume. As to the biomedicine sensitive to time and season demand, the uncertain demand fitted by the fuzzy mathematics method is obviously better than general random distribution functions. To establish a novel medical information management and decision model for uncertain demand optimization. A novel optimal management and decision model under uncertain demand has been presented based on fuzzy mathematics and a new comprehensive improved particle swarm algorithm. The optimal management and decision model can effectively reduce the medicine inventory cost. The proposed improved particle swarm optimization is a simple and effective algorithm to improve the Fuzzy interference and hence effectively reduce the calculation complexity of the optimal management and decision model. Therefore the new model can be used for accurate decision on procurement volume under uncertain demand.

  15. High Frequency QRS ECG Accurately Detects Cardiomyopathy

    NASA Technical Reports Server (NTRS)

    Schlegel, Todd T.; Arenare, Brian; Poulin, Gregory; Moser, Daniel R.; Delgado, Reynolds

    2005-01-01

    High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing

  16. Towards a More Accurate Solar Power Forecast By Improving NWP Model Physics

    NASA Astrophysics Data System (ADS)

    Köhler, C.; Lee, D.; Steiner, A.; Ritter, B.

    2014-12-01

    The growing importance and successive expansion of renewable energies raise new challenges for decision makers, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the uncertainties associated with the large share of weather-dependent power sources. Precise power forecast, well-timed energy trading on the stock market, and electrical grid stability can be maintained. The research project EWeLiNE is a collaboration of the German Weather Service (DWD), the Fraunhofer Institute (IWES) and three German transmission system operators (TSOs). Together, wind and photovoltaic (PV) power forecasts shall be improved by combining optimized NWP and enhanced power forecast models. The conducted work focuses on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. Not only the representation of the model cloud characteristics, but also special events like Sahara dust over Germany and the solar eclipse in 2015 are treated and their effect on solar power accounted for. An overview of the EWeLiNE project and results of the ongoing research will be presented.

  17. High-order accurate finite-volume formulations for the pressure gradient force in layered ocean models

    NASA Astrophysics Data System (ADS)

    Engwirda, Darren; Kelley, Maxwell; Marshall, John

    2017-08-01

    Discretisation of the horizontal pressure gradient force in layered ocean models is a challenging task, with non-trivial interactions between the thermodynamics of the fluid and the geometry of the layers often leading to numerical difficulties. We present two new finite-volume schemes for the pressure gradient operator designed to address these issues. In each case, the horizontal acceleration is computed as an integration of the contact pressure force that acts along the perimeter of an associated momentum control-volume. A pair of new schemes are developed by exploring different control-volume geometries. Non-linearities in the underlying equation-of-state definitions and thermodynamic profiles are treated using a high-order accurate numerical integration framework, designed to preserve hydrostatic balance in a non-linear manner. Numerical experiments show that the new methods achieve high levels of consistency, maintaining hydrostatic and thermobaric equilibrium in the presence of strongly-sloping layer geometries, non-linear equations-of-state and non-uniform vertical stratification profiles. These results suggest that the new pressure gradient formulations may be appropriate for general circulation models that employ hybrid vertical coordinates and/or terrain-following representations.

  18. Achieving perceptually-accurate aural telepresence

    NASA Astrophysics Data System (ADS)

    Henderson, Paul D.

    degrees for speech and less than 4 degrees with a pink noise burst. The results allow for the density of WFS systems to be selected from the required localization accuracy. Also, by exploiting the ventriloquist effect, the angular resolution of an audio rendering may be reduced when combined with spatially-accurate video.

  19. What makes an accurate and reliable subject-specific finite element model? A case study of an elephant femur

    PubMed Central

    Panagiotopoulou, O.; Wilshin, S. D.; Rayfield, E. J.; Shefelbine, S. J.; Hutchinson, J. R.

    2012-01-01

    Finite element modelling is well entrenched in comparative vertebrate biomechanics as a tool to assess the mechanical design of skeletal structures and to better comprehend the complex interaction of their form–function relationships. But what makes a reliable subject-specific finite element model? To approach this question, we here present a set of convergence and sensitivity analyses and a validation study as an example, for finite element analysis (FEA) in general, of ways to ensure a reliable model. We detail how choices of element size, type and material properties in FEA influence the results of simulations. We also present an empirical model for estimating heterogeneous material properties throughout an elephant femur (but of broad applicability to FEA). We then use an ex vivo experimental validation test of a cadaveric femur to check our FEA results and find that the heterogeneous model matches the experimental results extremely well, and far better than the homogeneous model. We emphasize how considering heterogeneous material properties in FEA may be critical, so this should become standard practice in comparative FEA studies along with convergence analyses, consideration of element size, type and experimental validation. These steps may be required to obtain accurate models and derive reliable conclusions from them. PMID:21752810

  20. Reduced order models for assessing CO 2 impacts in shallow unconfined aquifers

    DOE PAGES

    Keating, Elizabeth H.; Harp, Dylan H.; Dai, Zhenxue; ...

    2016-01-28

    Risk assessment studies of potential CO 2 sequestration projects consider many factors, including the possibility of brine and/or CO 2 leakage from the storage reservoir. Detailed multiphase reactive transport simulations have been developed to predict the impact of such leaks on shallow groundwater quality; however, these simulations are computationally expensive and thus difficult to directly embed in a probabilistic risk assessment analysis. Here we present a process for developing computationally fast reduced-order models which emulate key features of the more detailed reactive transport simulations. A large ensemble of simulations that take into account uncertainty in aquifer characteristics and CO 2/brinemore » leakage scenarios were performed. Twelve simulation outputs of interest were used to develop response surfaces (RSs) using a MARS (multivariate adaptive regression splines) algorithm (Milborrow, 2015). A key part of this study is to compare different measures of ROM accuracy. We then show that for some computed outputs, MARS performs very well in matching the simulation data. The capability of the RS to predict simulation outputs for parameter combinations not used in RS development was tested using cross-validation. Again, for some outputs, these results were quite good. For other outputs, however, the method performs relatively poorly. Performance was best for predicting the volume of depressed-pH-plumes, and was relatively poor for predicting organic and trace metal plume volumes. We believe several factors, including the non-linearity of the problem, complexity of the geochemistry, and granularity in the simulation results, contribute to this varied performance. The reduced order models were developed principally to be used in probabilistic performance analysis where a large range of scenarios are considered and ensemble performance is calculated. We demonstrate that they effectively predict the ensemble behavior. But, the performance of the RSs

  1. Scramjet Combustor Simulations Using Reduced Chemical Kinetics for Practical Fuels

    DTIC Science & Technology

    2003-12-01

    the aerospace industry in reducing prototype and testing costs and the time needed to bring products to market . Accurate simulation of chemical...JP-8 kinetics and soot models into the UNICORN CFD code (Montgomery et al., 2003a) NSF Phase I and II SBIRs for development of a computer-assisted...divided by diameter QSS quasi-steady state REI Reaction Engineering International UNICORN UNsteady Ignition and COmbustion with ReactioNs VULCAN Viscous Upwind aLgorithm for Complex flow ANalysis

  2. Time accurate application of the MacCormack 2-4 scheme on massively parallel computers

    NASA Technical Reports Server (NTRS)

    Hudson, Dale A.; Long, Lyle N.

    1995-01-01

    Many recent computational efforts in turbulence and acoustics research have used higher order numerical algorithms. One popular method has been the explicit MacCormack 2-4 scheme. The MacCormack 2-4 scheme is second order accurate in time and fourth order accurate in space, and is stable for CFL's below 2/3. Current research has shown that the method can give accurate results but does exhibit significant Gibbs phenomena at sharp discontinuities. The impact of adding Jameson type second, third, and fourth order artificial viscosity was examined here. Category 2 problems, the nonlinear traveling wave and the Riemann problem, were computed using a CFL number of 0.25. This research has found that dispersion errors can be significantly reduced or nearly eliminated by using a combination of second and third order terms in the damping. Use of second and fourth order terms reduced the magnitude of dispersion errors but not as effectively as the second and third order combination. The program was coded using Thinking Machine's CM Fortran, a variant of Fortran 90/High Performance Fortran, and was executed on a 2K CM-200. Simple extrapolation boundary conditions were used for both problems.

  3. High Order Accurate Finite Difference Modeling of Seismo-Acoustic Wave Propagation in a Moving Atmosphere and a Heterogeneous Earth Model Coupled Across a Realistic Topography

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Petersson, N. Anders; Sjogreen, Bjorn

    Here, we develop a numerical method for simultaneously simulating acoustic waves in a realistic moving atmosphere and seismic waves in a heterogeneous earth model, where the motions are coupled across a realistic topography. We model acoustic wave propagation by solving the linearized Euler equations of compressible fluid mechanics. The seismic waves are modeled by the elastic wave equation in a heterogeneous anisotropic material. The motion is coupled by imposing continuity of normal velocity and normal stresses across the topographic interface. Realistic topography is resolved on a curvilinear grid that follows the interface. The governing equations are discretized using high ordermore » accurate finite difference methods that satisfy the principle of summation by parts. We apply the energy method to derive the discrete interface conditions and to show that the coupled discretization is stable. The implementation is verified by numerical experiments, and we demonstrate a simulation of coupled wave propagation in a windy atmosphere and a realistic earth model with non-planar topography.« less

  4. High Order Accurate Finite Difference Modeling of Seismo-Acoustic Wave Propagation in a Moving Atmosphere and a Heterogeneous Earth Model Coupled Across a Realistic Topography

    DOE PAGES

    Petersson, N. Anders; Sjogreen, Bjorn

    2017-04-18

    Here, we develop a numerical method for simultaneously simulating acoustic waves in a realistic moving atmosphere and seismic waves in a heterogeneous earth model, where the motions are coupled across a realistic topography. We model acoustic wave propagation by solving the linearized Euler equations of compressible fluid mechanics. The seismic waves are modeled by the elastic wave equation in a heterogeneous anisotropic material. The motion is coupled by imposing continuity of normal velocity and normal stresses across the topographic interface. Realistic topography is resolved on a curvilinear grid that follows the interface. The governing equations are discretized using high ordermore » accurate finite difference methods that satisfy the principle of summation by parts. We apply the energy method to derive the discrete interface conditions and to show that the coupled discretization is stable. The implementation is verified by numerical experiments, and we demonstrate a simulation of coupled wave propagation in a windy atmosphere and a realistic earth model with non-planar topography.« less

  5. Reduced modeling of flexible structures for decentralized control

    NASA Technical Reports Server (NTRS)

    Yousuff, A.; Tan, T. M.; Bahar, L. Y.; Konstantinidis, M. F.

    1986-01-01

    Based upon the modified finite element-transfer matrix method, this paper presents a technique for reduced modeling of flexible structures for decentralized control. The modeling decisions are carried out at (finite-) element level, and are dictated by control objectives. A simply supported beam with two sets of actuators and sensors (linear force actuator and linear position and velocity sensors) is considered for illustration. In this case, it is conjectured that the decentrally controlled closed loop system is guaranteed to be at least marginally stable.

  6. Reduced-Order Modeling: Cooperative Research and Development at the NASA Langley Research Center

    NASA Technical Reports Server (NTRS)

    Silva, Walter A.; Beran, Philip S.; Cesnik, Carlos E. S.; Guendel, Randal E.; Kurdila, Andrew; Prazenica, Richard J.; Librescu, Liviu; Marzocca, Piergiovanni; Raveh, Daniella E.

    2001-01-01

    Cooperative research and development activities at the NASA Langley Research Center (LaRC) involving reduced-order modeling (ROM) techniques are presented. Emphasis is given to reduced-order methods and analyses based on Volterra series representations, although some recent results using Proper Orthogonal Deco in position (POD) are discussed as well. Results are reported for a variety of computational and experimental nonlinear systems to provide clear examples of the use of reduced-order models, particularly within the field of computational aeroelasticity. The need for and the relative performance (speed, accuracy, and robustness) of reduced-order modeling strategies is documented. The development of unsteady aerodynamic state-space models directly from computational fluid dynamics analyses is presented in addition to analytical and experimental identifications of Volterra kernels. Finally, future directions for this research activity are summarized.

  7. Seeing and Being Seen: Predictors of Accurate Perceptions about Classmates’ Relationships

    PubMed Central

    Neal, Jennifer Watling; Neal, Zachary P.; Cappella, Elise

    2015-01-01

    This study examines predictors of observer accuracy (i.e. seeing) and target accuracy (i.e. being seen) in perceptions of classmates’ relationships in a predominantly African American sample of 420 second through fourth graders (ages 7 – 11). Girls, children in higher grades, and children in smaller classrooms were more accurate observers. Targets (i.e. pairs of children) were more accurately observed when they occurred in smaller classrooms of higher grades and involved same-sex, high-popularity, and similar-popularity children. Moreover, relationships between pairs of girls were more accurately observed than relationships between pairs of boys. As a set, these findings suggest the importance of both observer and target characteristics for children’s accurate perceptions of classroom relationships. Moreover, the substantial variation in observer accuracy and target accuracy has methodological implications for both peer-reported assessments of classroom relationships and the use of stochastic actor-based models to understand peer selection and socialization processes. PMID:26347582

  8. Modeling the influence of a reduced equator-to-pole sea surface temperature gradient on the distribution of water isotopes in the Early/Middle Eocene

    NASA Astrophysics Data System (ADS)

    Speelman, Eveline N.; Sewall, Jacob O.; Noone, David; Huber, Matthew; von der Heydt, Anna; Damsté, Jaap Sinninghe; Reichart, Gert-Jan

    2010-09-01

    Proxy-based climate reconstructions suggest the existence of a strongly reduced equator-to-pole temperature gradient during the Azolla interval in the Early/Middle Eocene, compared to modern. Changes in the hydrological cycle, as a consequence of a reduced temperature gradient, are expected to be reflected in the isotopic composition of precipitation (δD, δ 18O). The interpretation of water isotopic records to quantitatively reconstruct past precipitation patterns is, however, hampered by a lack of detailed information on changes in their spatial and temporal distribution. Using the isotope-enabled version of the National Center for Atmospheric Research (NCAR) atmospheric general circulation model, Community Atmosphere Model v.3 (isoCAM3), relationships between water isotopes and past climates can be simulated. Here we examine the influence of an imposed reduced meridional sea surface temperature gradient on the spatial distribution of precipitation and its isotopic composition in an Early/Middle Eocene setting. As a result of the applied forcings, the Eocene simulation predicts the occurrence of less depleted high latitude precipitation, with δD values ranging only between 0 and -140‰ (compared to Present-day 0 to -300‰). Comparison with Early/Middle Eocene-age isotopic proxy data shows that the simulation accurately captures the main features of the spatial distribution of the isotopic composition of Early/Middle Eocene precipitation over land in conjunction with the aspects of the modeled Early/Middle Eocene climate. Hence, the included stable isotope module quantitatively supports the existence of a reduced meridional temperature gradient during this interval.

  9. Accurate numerical forward model for optimal retracking of SIRAL2 SAR echoes over open ocean

    NASA Astrophysics Data System (ADS)

    Phalippou, L.; Demeestere, F.

    2011-12-01

    The SAR mode of SIRAL-2 on board Cryosat-2 has been designed to measure primarily sea-ice and continental ice (Wingham et al. 2005). In 2005, K. Raney (KR, 2005) pointed out the improvements brought by SAR altimeter for open ocean. KR results were mostly based on 'rule of thumb' considerations on speckle noise reduction due to the higher PRF and to speckle decorrelation after SAR processing. In 2007, Phalippou and Enjolras (PE,2007) provided the theoretical background for optimal retracking of SAR echoes over ocean with a focus on the forward modelling of the power-waveforms. The accuracies of geophysical parameters (range, significant wave heights, and backscattering coefficient) retrieved from SAR altimeter data were derived accounting for SAR echo shape and speckle noise accurate modelling. The step forward to optimal retracking using numerical forward model (NFM) was also pointed out. NFM of the power waveform avoids analytical approximation, a warranty to minimise the geophysical dependent biases in the retrieval. NFM have been used for many years, in operational meteorology in particular, for retrieving temperature and humidity profiles from IR and microwave radiometers as the radiative transfer function is complex (Eyre, 1989). So far this technique was not used in the field of ocean conventional altimetry as analytical models (e.g. Brown's model for instance) were found to give sufficient accuracy. However, although NFM seems desirable even for conventional nadir altimetry, it becomes inevitable if one wish to process SAR altimeter data as the transfer function is too complex to be approximated by a simple analytical function. This was clearly demonstrated in PE 2007. The paper describes the background to SAR data retracking over open ocean. Since PE 2007 improvements have been brought to the forward model and it is shown that the altimeter on-ground and in flight characterisation (e.g antenna pattern range impulse response, azimuth impulse response

  10. Predictive models reduce talent development costs in female gymnastics.

    PubMed

    Pion, Johan; Hohmann, Andreas; Liu, Tianbiao; Lenoir, Matthieu; Segers, Veerle

    2017-04-01

    This retrospective study focuses on the comparison of different predictive models based on the results of a talent identification test battery for female gymnasts. We studied to what extent these models have the potential to optimise selection procedures, and at the same time reduce talent development costs in female artistic gymnastics. The dropout rate of 243 female elite gymnasts was investigated, 5 years past talent selection, using linear (discriminant analysis) and non-linear predictive models (Kohonen feature maps and multilayer perceptron). The coaches classified 51.9% of the participants correct. Discriminant analysis improved the correct classification to 71.6% while the non-linear technique of Kohonen feature maps reached 73.7% correctness. Application of the multilayer perceptron even classified 79.8% of the gymnasts correctly. The combination of different predictive models for talent selection can avoid deselection of high-potential female gymnasts. The selection procedure based upon the different statistical analyses results in decrease of 33.3% of cost because the pool of selected athletes can be reduced to 92 instead of 138 gymnasts (as selected by the coaches). Reduction of the costs allows the limited resources to be fully invested in the high-potential athletes.

  11. Analysing reduced tillage practices within a bio-economic modelling framework.

    PubMed

    Townsend, Toby J; Ramsden, Stephen J; Wilson, Paul

    2016-07-01

    Sustainable intensification of agricultural production systems will require changes in farm practice. Within arable cropping systems, reducing the intensity of tillage practices (e.g. reduced tillage) potentially offers one such sustainable intensification approach. Previous researchers have tended to examine the impact of reduced tillage on specific factors such as yield or weed burden, whilst, by definition, sustainable intensification necessitates a system-based analysis approach. Drawing upon a bio-economic optimisation model, 'MEETA', we quantify trade-off implications between potential yield reductions, reduced cultivation costs and increased crop protection costs. We extend the MEETA model to quantify farm-level net margin, in addition to quantifying farm-level gross margin, net energy, and greenhouse gas emissions. For the lowest intensity tillage system, zero tillage, results demonstrate financial benefits over a conventional tillage system even when the zero tillage system includes yield penalties of 0-14.2% (across all crops). Average yield reductions from zero tillage literature range from 0 to 8.5%, demonstrating that reduced tillage offers a realistic and attainable sustainable intensification intervention, given the financial and environmental benefits, albeit that yield reductions will require more land to compensate for loss of calories produced, negating environmental benefits observed at farm-level. However, increasing uptake of reduced tillage from current levels will probably require policy intervention; an extension of the recent changes to the CAP ('Greening') provides an opportunity to do this.

  12. A time accurate prediction of the viscous flow in a turbine stage including a rotor in motion

    NASA Astrophysics Data System (ADS)

    Shavalikul, Akamol

    In this current study, the flow field in the Pennsylvania State University Axial Flow Turbine Research Facility (AFTRF) was simulated. This study examined four sets of simulations. The first two sets are for an individual NGV and for an individual rotor. The last two sets use a multiple reference frames approach for a complete turbine stage with two different interface models: a steady circumferential average approach called a mixing plane model, and a time accurate flow simulation approach called a sliding mesh model. The NGV passage flow field was simulated using a three-dimensional Reynolds Averaged Navier-Stokes finite volume solver (RANS) with a standard kappa -- epsilon turbulence model. The mean flow distributions on the NGV surfaces and endwall surfaces were computed. The numerical solutions indicate that two passage vortices begin to be observed approximately at the mid axial chord of the NGV suction surface. The first vortex is a casing passage vortex which occurs at the corner formed by the NGV suction surface and the casing. This vortex is created by the interaction of the passage flow and the radially inward flow, while the second vortex, the hub passage vortex, is observed near the hub. These two vortices become stronger towards the NGV trailing edge. By comparing the results from the X/Cx = 1.025 plane and the X/Cx = 1.09 plane, it can be concluded that the NGV wake decays rapidly within a short axial distance downstream of the NGV. For the rotor, a set of simulations was carried out to examine the flow fields associated with different pressure side tip extension configurations, which are designed to reduce the tip leakage flow. The simulation results show that significant reductions in tip leakage mass flow rate and aerodynamic loss reduction are possible by using suitable tip platform extensions located near the pressure side corner of the blade tip. The computations used realistic turbine rotor inlet flow conditions in a linear cascade arrangement

  13. Creating Digital Elevation Model Using a Mobile Device

    NASA Astrophysics Data System (ADS)

    Durmaz, A. İ.

    2017-11-01

    DEM (Digital Elevation Models) is the best way to interpret topography on the ground. In recent years, lidar technology allows to create more accurate elevation models. However, the problem is this technology is not common all over the world. Also if Lidar data are not provided by government agencies freely, people have to pay lots of money to reach these point clouds. In this article, we will discuss how we can create digital elevation model from less accurate mobile devices' GPS data. Moreover, we will evaluate these data on the same mobile device which we collected data to reduce cost of this modeling.

  14. Reduced order modeling of head related transfer functions for virtual acoustic displays

    NASA Astrophysics Data System (ADS)

    Willhite, Joel A.; Frampton, Kenneth D.; Grantham, D. Wesley

    2003-04-01

    The purpose of this work is to improve the computational efficiency in acoustic virtual applications by creating and testing reduced order models of the head related transfer functions used in localizing sound sources. State space models of varying order were generated from zero-elevation Head Related Impulse Responses (HRIRs) using Kungs Single Value Decomposition (SVD) technique. The inputs to the models are the desired azimuths of the virtual sound sources (from minus 90 deg to plus 90 deg, in 10 deg increments) and the outputs are the left and right ear impulse responses. Trials were conducted in an anechoic chamber in which subjects were exposed to real sounds that were emitted by individual speakers across a numbered speaker array, phantom sources generated from the original HRIRs, and phantom sound sources generated with the different reduced order state space models. The error in the perceived direction of the phantom sources generated from the reduced order models was compared to errors in localization using the original HRIRs.

  15. Adaptive System Modeling for Spacecraft Simulation

    NASA Technical Reports Server (NTRS)

    Thomas, Justin

    2011-01-01

    This invention introduces a methodology and associated software tools for automatically learning spacecraft system models without any assumptions regarding system behavior. Data stream mining techniques were used to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). Evaluation on historical ISS telemetry data shows that adaptive system modeling reduces simulation error anywhere from 50 to 90 percent over existing approaches. The purpose of the methodology is to outline how someone can create accurate system models from sensor (telemetry) data. The purpose of the software is to support the methodology. The software provides analysis tools to design the adaptive models. The software also provides the algorithms to initially build system models and continuously update them from the latest streaming sensor data. The main strengths are as follows: Creates accurate spacecraft system models without in-depth system knowledge or any assumptions about system behavior. Automatically updates/calibrates system models using the latest streaming sensor data. Creates device specific models that capture the exact behavior of devices of the same type. Adapts to evolving systems. Can reduce computational complexity (faster simulations).

  16. Implementation of a numerical holding furnace model in foundry and construction of a reduced model

    NASA Astrophysics Data System (ADS)

    Loussouarn, Thomas; Maillet, Denis; Remy, Benjamin; Dan, Diane

    2016-09-01

    Vacuum holding induction furnaces are used for the manufacturing of turbine blades by loss wax foundry process. The control of solidification parameters is a key factor for the manufacturing of these parts in according to geometrical and structural expectations. The definition of a reduced heat transfer model with experimental identification through an estimation of its parameters is required here. In a further stage this model will be used to characterize heat exchanges using internal sensors through inverse techniques to optimize the furnace command and the optimization of its design. Here, an axisymmetric furnace and its load have been numerically modelled using FlexPDE, a finite elements code. A detailed model allows the calculation of the internal induction heat source as well as transient radiative transfer inside the furnace. A reduced lumped body model has been defined to represent the numerical furnace. The model reduction and the estimation of the parameters of the lumped body have been made using a Levenberg-Marquardt least squares minimization algorithm with Matlab, using two synthetic temperature signals with a further validation test.

  17. The CPA Equation of State and an Activity Coefficient Model for Accurate Molar Enthalpy Calculations of Mixtures with Carbon Dioxide and Water/Brine

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Myint, P. C.; Hao, Y.; Firoozabadi, A.

    2015-03-27

    Thermodynamic property calculations of mixtures containing carbon dioxide (CO 2) and water, including brines, are essential in theoretical models of many natural and industrial processes. The properties of greatest practical interest are density, solubility, and enthalpy. Many models for density and solubility calculations have been presented in the literature, but there exists only one study, by Spycher and Pruess, that has compared theoretical molar enthalpy predictions with experimental data [1]. In this report, we recommend two different models for enthalpy calculations: the CPA equation of state by Li and Firoozabadi [2], and the CO 2 activity coefficient model by Duanmore » and Sun [3]. We show that the CPA equation of state, which has been demonstrated to provide good agreement with density and solubility data, also accurately calculates molar enthalpies of pure CO 2, pure water, and both CO 2-rich and aqueous (H 2O-rich) mixtures of the two species. It is applicable to a wider range of conditions than the Spycher and Pruess model. In aqueous sodium chloride (NaCl) mixtures, we show that Duan and Sun’s model yields accurate results for the partial molar enthalpy of CO 2. It can be combined with another model for the brine enthalpy to calculate the molar enthalpy of H 2O-CO 2-NaCl mixtures. We conclude by explaining how the CPA equation of state may be modified to further improve agreement with experiments. This generalized CPA is the basis of our future work on this topic.« less

  18. Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Korkali, Mert; Veneman, Jason G.; Tivnan, Brian F.

    Increased coupling between critical infrastructure networks, such as power and communication systems, has important implications for the reliability and security of these systems. To understand the effects of power-communication coupling, several researchers have studied models of interdependent networks and reported that increased coupling can increase vulnerability. However, these conclusions come largely from models that have substantially different mechanisms of cascading failure, relative to those found in actual power and communication networks, and that do not capture the benefits of connecting systems with complementary capabilities. In order to understand the importance of these details, this paper compares network vulnerability in simplemore » topological models and in models that more accurately capture the dynamics of cascading in power systems. First, we compare a simple model of topological contagion to a model of cascading in power systems and find that the power grid model shows a higher level of vulnerability, relative to the contagion model. Second, we compare a percolation model of topological cascading in coupled networks to three different models of power networks coupled to communication systems. Again, the more accurate models suggest very different conclusions than the percolation model. In all but the most extreme case, the physics-based power grid models indicate that increased power-communication coupling decreases vulnerability. This is opposite from what one would conclude from the percolation model, in which zero coupling is optimal. Only in an extreme case, in which communication failures immediately cause grid failures, did we find that increased coupling can be harmful. Together, these results suggest design strategies for reducing the risk of cascades in interdependent infrastructure systems.« less

  19. Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence

    DOE PAGES

    Korkali, Mert; Veneman, Jason G.; Tivnan, Brian F.; ...

    2017-03-20

    Increased coupling between critical infrastructure networks, such as power and communication systems, has important implications for the reliability and security of these systems. To understand the effects of power-communication coupling, several researchers have studied models of interdependent networks and reported that increased coupling can increase vulnerability. However, these conclusions come largely from models that have substantially different mechanisms of cascading failure, relative to those found in actual power and communication networks, and that do not capture the benefits of connecting systems with complementary capabilities. In order to understand the importance of these details, this paper compares network vulnerability in simplemore » topological models and in models that more accurately capture the dynamics of cascading in power systems. First, we compare a simple model of topological contagion to a model of cascading in power systems and find that the power grid model shows a higher level of vulnerability, relative to the contagion model. Second, we compare a percolation model of topological cascading in coupled networks to three different models of power networks coupled to communication systems. Again, the more accurate models suggest very different conclusions than the percolation model. In all but the most extreme case, the physics-based power grid models indicate that increased power-communication coupling decreases vulnerability. This is opposite from what one would conclude from the percolation model, in which zero coupling is optimal. Only in an extreme case, in which communication failures immediately cause grid failures, did we find that increased coupling can be harmful. Together, these results suggest design strategies for reducing the risk of cascades in interdependent infrastructure systems.« less

  20. Totally Implantable Wireless Ultrasonic Doppler Blood Flowmeters: Toward Accurate Miniaturized Chronic Monitors.

    PubMed

    Rothfuss, Michael A; Unadkat, Jignesh V; Gimbel, Michael L; Mickle, Marlin H; Sejdić, Ervin

    2017-03-01

    Totally implantable wireless ultrasonic blood flowmeters provide direct-access chronic vessel monitoring in hard-to-reach places without using wired bedside monitors or imaging equipment. Although wireless implantable Doppler devices are accurate for most applications, device size and implant lifetime remain vastly underdeveloped. We review past and current approaches to miniaturization and implant lifetime extension for wireless implantable Doppler devices and propose approaches to reduce device size and maximize implant lifetime for the next generation of devices. Additionally, we review current and past approaches to accurate blood flow measurements. This review points toward relying on increased levels of monolithic customization and integration to reduce size. Meanwhile, recommendations to maximize implant lifetime should include alternative sources of power, such as transcutaneous wireless power, that stand to extend lifetime indefinitely. Coupling together the results will pave the way for ultra-miniaturized totally implantable wireless blood flow monitors for truly chronic implantation. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

  1. Use of machine learning methods to reduce predictive error of groundwater models.

    PubMed

    Xu, Tianfang; Valocchi, Albert J; Choi, Jaesik; Amir, Eyal

    2014-01-01

    Quantitative analyses of groundwater flow and transport typically rely on a physically-based model, which is inherently subject to error. Errors in model structure, parameter and data lead to both random and systematic error even in the output of a calibrated model. We develop complementary data-driven models (DDMs) to reduce the predictive error of physically-based groundwater models. Two machine learning techniques, the instance-based weighting and support vector regression, are used to build the DDMs. This approach is illustrated using two real-world case studies of the Republican River Compact Administration model and the Spokane Valley-Rathdrum Prairie model. The two groundwater models have different hydrogeologic settings, parameterization, and calibration methods. In the first case study, cluster analysis is introduced for data preprocessing to make the DDMs more robust and computationally efficient. The DDMs reduce the root-mean-square error (RMSE) of the temporal, spatial, and spatiotemporal prediction of piezometric head of the groundwater model by 82%, 60%, and 48%, respectively. In the second case study, the DDMs reduce the RMSE of the temporal prediction of piezometric head of the groundwater model by 77%. It is further demonstrated that the effectiveness of the DDMs depends on the existence and extent of the structure in the error of the physically-based model. © 2013, National GroundWater Association.

  2. Combining Structural Modeling with Ensemble Machine Learning to Accurately Predict Protein Fold Stability and Binding Affinity Effects upon Mutation

    PubMed Central

    Garcia Lopez, Sebastian; Kim, Philip M.

    2014-01-01

    Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT) algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases. PMID:25243403

  3. Fast and Accurate Radiative Transfer Calculations Using Principal Component Analysis for (Exo-)Planetary Retrieval Models

    NASA Astrophysics Data System (ADS)

    Kopparla, P.; Natraj, V.; Shia, R. L.; Spurr, R. J. D.; Crisp, D.; Yung, Y. L.

    2015-12-01

    Radiative transfer (RT) computations form the engine of atmospheric retrieval codes. However, full treatment of RT processes is computationally expensive, prompting usage of two-stream approximations in current exoplanetary atmospheric retrieval codes [Line et al., 2013]. Natraj et al. [2005, 2010] and Spurr and Natraj [2013] demonstrated the ability of a technique using principal component analysis (PCA) to speed up RT computations. In the PCA method for RT performance enhancement, empirical orthogonal functions are developed for binned sets of inherent optical properties that possess some redundancy; costly multiple-scattering RT calculations are only done for those few optical states corresponding to the most important principal components, and correction factors are applied to approximate radiation fields. Kopparla et al. [2015, in preparation] extended the PCA method to a broadband spectral region from the ultraviolet to the shortwave infrared (0.3-3 micron), accounting for major gas absorptions in this region. Here, we apply the PCA method to a some typical (exo-)planetary retrieval problems. Comparisons between the new model, called Universal Principal Component Analysis Radiative Transfer (UPCART) model, two-stream models and line-by-line RT models are performed, for spectral radiances, spectral fluxes and broadband fluxes. Each of these are calculated at the top of the atmosphere for several scenarios with varying aerosol types, extinction and scattering optical depth profiles, and stellar and viewing geometries. We demonstrate that very accurate radiance and flux estimates can be obtained, with better than 1% accuracy in all spectral regions and better than 0.1% in most cases, as compared to a numerically exact line-by-line RT model. The accuracy is enhanced when the results are convolved to typical instrument resolutions. The operational speed and accuracy of UPCART can be further improved by optimizing binning schemes and parallelizing the codes, work

  4. PredSTP: a highly accurate SVM based model to predict sequential cystine stabilized peptides.

    PubMed

    Islam, S M Ashiqul; Sajed, Tanvir; Kearney, Christopher Michel; Baker, Erich J

    2015-07-05

    Numerous organisms have evolved a wide range of toxic peptides for self-defense and predation. Their effective interstitial and macro-environmental use requires energetic and structural stability. One successful group of these peptides includes a tri-disulfide domain arrangement that offers toxicity and high stability. Sequential tri-disulfide connectivity variants create highly compact disulfide folds capable of withstanding a variety of environmental stresses. Their combination of toxicity and stability make these peptides remarkably valuable for their potential as bio-insecticides, antimicrobial peptides and peptide drug candidates. However, the wide sequence variation, sources and modalities of group members impose serious limitations on our ability to rapidly identify potential members. As a result, there is a need for automated high-throughput member classification approaches that leverage their demonstrated tertiary and functional homology. We developed an SVM-based model to predict sequential tri-disulfide peptide (STP) toxins from peptide sequences. One optimized model, called PredSTP, predicted STPs from training set with sensitivity, specificity, precision, accuracy and a Matthews correlation coefficient of 94.86%, 94.11%, 84.31%, 94.30% and 0.86, respectively, using 200 fold cross validation. The same model outperforms existing prediction approaches in three independent out of sample testsets derived from PDB. PredSTP can accurately identify a wide range of cystine stabilized peptide toxins directly from sequences in a species-agnostic fashion. The ability to rapidly filter sequences for potential bioactive peptides can greatly compress the time between peptide identification and testing structural and functional properties for possible antimicrobial and insecticidal candidates. A web interface is freely available to predict STP toxins from http://crick.ecs.baylor.edu/.

  5. Accurate modeling of plasma acceleration with arbitrary order pseudo-spectral particle-in-cell methods

    DOE PAGES

    Jalas, S.; Dornmair, I.; Lehe, R.; ...

    2017-03-20

    Particle in Cell (PIC) simulations are a widely used tool for the investigation of both laser- and beam-driven plasma acceleration. It is a known issue that the beam quality can be artificially degraded by numerical Cherenkov radiation (NCR) resulting primarily from an incorrectly modeled dispersion relation. Pseudo-spectral solvers featuring infinite order stencils can strongly reduce NCR - or even suppress it - and are therefore well suited to correctly model the beam properties. For efficient parallelization of the PIC algorithm, however, localized solvers are inevitable. Arbitrary order pseudo-spectral methods provide this needed locality. Yet, these methods can again be pronemore » to NCR. Here in this paper, we show that acceptably low solver orders are sufficient to correctly model the physics of interest, while allowing for parallel computation by domain decomposition.« less

  6. Model and algorithm based on accurate realization of dwell time in magnetorheological finishing.

    PubMed

    Song, Ci; Dai, Yifan; Peng, Xiaoqiang

    2010-07-01

    Classically, a dwell-time map is created with a method such as deconvolution or numerical optimization, with the input being a surface error map and influence function. This dwell-time map is the numerical optimum for minimizing residual form error, but it takes no account of machine dynamics limitations. The map is then reinterpreted as machine speeds and accelerations or decelerations in a separate operation. In this paper we consider combining the two methods in a single optimization by the use of a constrained nonlinear optimization model, which regards both the two-norm of the surface residual error and the dwell-time gradient as an objective function. This enables machine dynamic limitations to be properly considered within the scope of the optimization, reducing both residual surface error and polishing times. Further simulations are introduced to demonstrate the feasibility of the model, and the velocity map is reinterpreted from the dwell time, meeting the requirement of velocity and the limitations of accelerations or decelerations. Indeed, the model and algorithm can also apply to other computer-controlled subaperture methods.

  7. A comparison of reduced-order modelling techniques for application in hyperthermia control and estimation.

    PubMed

    Bailey, E A; Dutton, A W; Mattingly, M; Devasia, S; Roemer, R B

    1998-01-01

    Reduced-order modelling techniques can make important contributions in the control and state estimation of large systems. In hyperthermia, reduced-order modelling can provide a useful tool by which a large thermal model can be reduced to the most significant subset of its full-order modes, making real-time control and estimation possible. Two such reduction methods, one based on modal decomposition and the other on balanced realization, are compared in the context of simulated hyperthermia heat transfer problems. The results show that the modal decomposition reduction method has three significant advantages over that of balanced realization. First, modal decomposition reduced models result in less error, when compared to the full-order model, than balanced realization reduced models of similar order in problems with low or moderate advective heat transfer. Second, because the balanced realization based methods require a priori knowledge of the sensor and actuator placements, the reduced-order model is not robust to changes in sensor or actuator locations, a limitation not present in modal decomposition. Third, the modal decomposition transformation is less demanding computationally. On the other hand, in thermal problems dominated by advective heat transfer, numerical instabilities make modal decomposition based reduction problematic. Modal decomposition methods are therefore recommended for reduction of models in which advection is not dominant and research continues into methods to render balanced realization based reduction more suitable for real-time clinical hyperthermia control and estimation.

  8. Testing of a novel pin array guide for accurate three-dimensional glenoid component positioning.

    PubMed

    Lewis, Gregory S; Stevens, Nicole M; Armstrong, April D

    2015-12-01

    A substantial challenge in total shoulder replacement is accurate positioning and alignment of the glenoid component. This challenge arises from limited intraoperative exposure and complex arthritic-driven deformity. We describe a novel pin array guide and method for patient-specific guiding of the glenoid central drill hole. We also experimentally tested the hypothesis that this method would reduce errors in version and inclination compared with 2 traditional methods. Polymer models of glenoids were created from computed tomography scans from 9 arthritic patients. Each 3-dimensional (3D) printed scapula was shrouded to simulate the operative situation. Three different methods for central drill alignment were tested, all with the target orientation of 5° retroversion and 0° inclination: no assistance, assistance by preoperative 3D imaging, and assistance by the pin array guide. Version and inclination errors of the drill line were compared. Version errors using the pin array guide (3° ± 2°) were significantly lower than version errors associated with no assistance (9° ± 7°) and preoperative 3D imaging (8° ± 6°). Inclination errors were also significantly lower using the pin array guide compared with no assistance. The new pin array guide substantially reduced errors in orientation of the central drill line. The guide method is patient specific but does not require rapid prototyping and instead uses adjustments to an array of pins based on automated software calculations. This method may ultimately provide a cost-effective solution enabling surgeons to obtain accurate orientation of the glenoid. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

  9. Total inpatient treatment costs in patients with severe burns: towards a more accurate reimbursement model.

    PubMed

    Mehra, Tarun; Koljonen, Virve; Seifert, Burkhardt; Volbracht, Jörk; Giovanoli, Pietro; Plock, Jan; Moos, Rudolf Maria

    2015-01-01

    Reimbursement systems have difficulties depicting the actual cost of burn treatment, leaving care providers with a significant financial burden. Our aim was to establish a simple and accurate reimbursement model compatible with prospective payment systems. A total of 370 966 electronic medical records of patients discharged in 2012 to 2013 from Swiss university hospitals were reviewed. A total of 828 cases of burns including 109 cases of severe burns were retained. Costs, revenues and earnings for severe and nonsevere burns were analysed and a linear regression model predicting total inpatient treatment costs was established. The median total costs per case for severe burns was tenfold higher than for nonsevere burns (179 949 CHF [167 353 EUR] vs 11 312 CHF [10 520 EUR], interquartile ranges 96 782-328 618 CHF vs 4 874-27 783 CHF, p <0.001). The median of earnings per case for nonsevere burns was 588 CHF (547 EUR) (interquartile range -6 720 - 5 354 CHF) whereas severe burns incurred a large financial loss to care providers, with median earnings of -33 178 CHF (30 856 EUR) (interquartile range -95 533 - 23 662 CHF). Differences were highly significant (p <0.001). Our linear regression model predicting total costs per case with length of stay (LOS) as independent variable had an adjusted R2 of 0.67 (p <0.001 for LOS). Severe burns are systematically underfunded within the Swiss reimbursement system. Flat-rate DRG-based refunds poorly reflect the actual treatment costs. In conclusion, we suggest a reimbursement model based on a per diem rate for treatment of severe burns.

  10. Accurate Arabic Script Language/Dialect Classification

    DTIC Science & Technology

    2014-01-01

    Army Research Laboratory Accurate Arabic Script Language/Dialect Classification by Stephen C. Tratz ARL-TR-6761 January 2014 Approved for public...1197 ARL-TR-6761 January 2014 Accurate Arabic Script Language/Dialect Classification Stephen C. Tratz Computational and Information Sciences...Include area code) Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39.18 January 2014 Final Accurate Arabic Script Language/Dialect Classification

  11. Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mandelli, Diego; Smith, Curtis L.; Alfonsi, Andrea

    2015-09-01

    The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, themore » overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.« less

  12. Thermosyphon Flooding in Reduced Gravity Environments Test Results

    NASA Technical Reports Server (NTRS)

    Gibson, Marc A.; Jaworske, Donald A.; Sanzi, Jim; Ljubanovic, Damir

    2013-01-01

    The condenser flooding phenomenon associated with gravity aided two-phase thermosyphons was studied using parabolic flights to obtain the desired reduced gravity environment (RGE). The experiment was designed and built to test a total of twelve titanium water thermosyphons in multiple gravity environments with the goal of developing a model that would accurately explain the correlation between gravitational forces and the maximum axial heat transfer limit associated with condenser flooding. Results from laboratory testing and parabolic flights are included in this report as part I of a two part series. The data analysis and correlations are included in a follow on paper.

  13. PSI/TM-Coffee: a web server for fast and accurate multiple sequence alignments of regular and transmembrane proteins using homology extension on reduced databases.

    PubMed

    Floden, Evan W; Tommaso, Paolo D; Chatzou, Maria; Magis, Cedrik; Notredame, Cedric; Chang, Jia-Ming

    2016-07-08

    The PSI/TM-Coffee web server performs multiple sequence alignment (MSA) of proteins by combining homology extension with a consistency based alignment approach. Homology extension is performed with Position Specific Iterative (PSI) BLAST searches against a choice of redundant and non-redundant databases. The main novelty of this server is to allow databases of reduced complexity to rapidly perform homology extension. This server also gives the possibility to use transmembrane proteins (TMPs) reference databases to allow even faster homology extension on this important category of proteins. Aside from an MSA, the server also outputs topological prediction of TMPs using the HMMTOP algorithm. Previous benchmarking of the method has shown this approach outperforms the most accurate alignment methods such as MSAProbs, Kalign, PROMALS, MAFFT, ProbCons and PRALINE™. The web server is available at http://tcoffee.crg.cat/tmcoffee. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Johnson, Brian B; Purba, Victor; Jafarpour, Saber

    Next-generation power networks will contain large numbers of grid-connected inverters satisfying a significant fraction of system load. Since each inverter model has a relatively large number of dynamic states, it is impractical to analyze complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loopmore » for grid synchronization. We outline a structure-preserving reduced-order inverter model with lumped parameters for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. We show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as any individual inverter in the system. Numerical simulations validate the reduced-order model.« less

  15. The Bern Simple Climate Model (BernSCM) v1.0: an extensible and fully documented open-source re-implementation of the Bern reduced-form model for global carbon cycle-climate simulations

    NASA Astrophysics Data System (ADS)

    Strassmann, Kuno M.; Joos, Fortunat

    2018-05-01

    The Bern Simple Climate Model (BernSCM) is a free open-source re-implementation of a reduced-form carbon cycle-climate model which has been used widely in previous scientific work and IPCC assessments. BernSCM represents the carbon cycle and climate system with a small set of equations for the heat and carbon budget, the parametrization of major nonlinearities, and the substitution of complex component systems with impulse response functions (IRFs). The IRF approach allows cost-efficient yet accurate substitution of detailed parent models of climate system components with near-linear behavior. Illustrative simulations of scenarios from previous multimodel studies show that BernSCM is broadly representative of the range of the climate-carbon cycle response simulated by more complex and detailed models. Model code (in Fortran) was written from scratch with transparency and extensibility in mind, and is provided open source. BernSCM makes scientifically sound carbon cycle-climate modeling available for many applications. Supporting up to decadal time steps with high accuracy, it is suitable for studies with high computational load and for coupling with integrated assessment models (IAMs), for example. Further applications include climate risk assessment in a business, public, or educational context and the estimation of CO2 and climate benefits of emission mitigation options.

  16. Systematic development of reduced reaction mechanisms for dynamic modeling

    NASA Technical Reports Server (NTRS)

    Frenklach, M.; Kailasanath, K.; Oran, E. S.

    1986-01-01

    A method for systematically developing a reduced chemical reaction mechanism for dynamic modeling of chemically reactive flows is presented. The method is based on the postulate that if a reduced reaction mechanism faithfully describes the time evolution of both thermal and chain reaction processes characteristic of a more complete mechanism, then the reduced mechanism will describe the chemical processes in a chemically reacting flow with approximately the same degree of accuracy. Here this postulate is tested by producing a series of mechanisms of reduced accuracy, which are derived from a full detailed mechanism for methane-oxygen combustion. These mechanisms were then tested in a series of reactive flow calculations in which a large-amplitude sinusoidal perturbation is applied to a system that is initially quiescent and whose temperature is high enough to start ignition processes. Comparison of the results for systems with and without convective flow show that this approach produces reduced mechanisms that are useful for calculations of explosions and detonations. Extensions and applicability to flames are discussed.

  17. Numerical modeling of the SNS H{sup −} ion source

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Veitzer, Seth A.; Beckwith, Kristian R. C.; Kundrapu, Madhusudhan

    Ion source rf antennas that produce H- ions can fail when plasma heating causes ablation of the insulating coating due to small structural defects such as cracks. Reducing antenna failures that reduce the operating capabilities of the Spallation Neutron Source (SNS) accelerator is one of the top priorities of the SNS H- Source Program at ORNL. Numerical modeling of ion sources can provide techniques for optimizing design in order to reduce antenna failures. There are a number of difficulties in developing accurate models of rf inductive plasmas. First, a large range of spatial and temporal scales must be resolved inmore » order to accurately capture the physics of plasma motion, including the Debye length, rf frequencies on the order of tens of MHz, simulation time scales of many hundreds of rf periods, large device sizes on tens of cm, and ion motions that are thousands of times slower than electrons. This results in large simulation domains with many computational cells for solving plasma and electromagnetic equations, short time steps, and long-duration simulations. In order to reduce the computational requirements, one can develop implicit models for both fields and particle motions (e.g. divergence-preserving ADI methods), various electrostatic models, or magnetohydrodynamic models. We have performed simulations using all three of these methods and have found that fluid models have the greatest potential for giving accurate solutions while still being fast enough to perform long timescale simulations in a reasonable amount of time. We have implemented a number of fluid models with electromagnetics using the simulation tool USim and applied them to modeling the SNS H- ion source. We found that a reduced, single-fluid MHD model with an imposed magnetic field due to the rf antenna current and the confining multi-cusp field generated increased bulk plasma velocities of > 200 m/s in the region of the antenna where ablation is often observed in the SNS source. We

  18. A systematic approach for the accurate non-invasive estimation of blood glucose utilizing a novel light-tissue interaction adaptive modelling scheme

    NASA Astrophysics Data System (ADS)

    Rybynok, V. O.; Kyriacou, P. A.

    2007-10-01

    Diabetes is one of the biggest health challenges of the 21st century. The obesity epidemic, sedentary lifestyles and an ageing population mean prevalence of the condition is currently doubling every generation. Diabetes is associated with serious chronic ill health, disability and premature mortality. Long-term complications including heart disease, stroke, blindness, kidney disease and amputations, make the greatest contribution to the costs of diabetes care. Many of these long-term effects could be avoided with earlier, more effective monitoring and treatment. Currently, blood glucose can only be monitored through the use of invasive techniques. To date there is no widely accepted and readily available non-invasive monitoring technique to measure blood glucose despite the many attempts. This paper challenges one of the most difficult non-invasive monitoring techniques, that of blood glucose, and proposes a new novel approach that will enable the accurate, and calibration free estimation of glucose concentration in blood. This approach is based on spectroscopic techniques and a new adaptive modelling scheme. The theoretical implementation and the effectiveness of the adaptive modelling scheme for this application has been described and a detailed mathematical evaluation has been employed to prove that such a scheme has the capability of extracting accurately the concentration of glucose from a complex biological media.

  19. Modelling mitigation options to reduce diffuse nitrogen water pollution from agriculture.

    PubMed

    Bouraoui, Fayçal; Grizzetti, Bruna

    2014-01-15

    Agriculture is responsible for large scale water quality degradation and is estimated to contribute around 55% of the nitrogen entering the European Seas. The key policy instrument for protecting inland, transitional and coastal water resources is the Water Framework Directive (WFD). Reducing nutrient losses from agriculture is crucial to the successful implementation of the WFD. There are several mitigation measures that can be implemented to reduce nitrogen losses from agricultural areas to surface and ground waters. For the selection of appropriate measures, models are useful for quantifying the expected impacts and the associated costs. In this article we review some of the models used in Europe to assess the effectiveness of nitrogen mitigation measures, ranging from fertilizer management to the construction of riparian areas and wetlands. We highlight how the complexity of models is correlated with the type of scenarios that can be tested, with conceptual models mostly used to evaluate the impact of reduced fertilizer application, and the physically-based models used to evaluate the timing and location of mitigation options and the response times. We underline the importance of considering the lag time between the implementation of measures and effects on water quality. Models can be effective tools for targeting mitigation measures (identifying critical areas and timing), for evaluating their cost effectiveness, for taking into consideration pollution swapping and considering potential trade-offs in contrasting environmental objectives. Models are also useful for involving stakeholders during the development of catchments mitigation plans, increasing their acceptability. © 2013.

  20. 3D acquisition and modeling for flint artefacts analysis

    NASA Astrophysics Data System (ADS)

    Loriot, B.; Fougerolle, Y.; Sestier, C.; Seulin, R.

    2007-07-01

    In this paper, we are interested in accurate acquisition and modeling of flint artefacts. Archaeologists needs accurate geometry measurements to refine their understanding of the flint artefacts manufacturing process. Current techniques require several operations. First, a copy of a flint artefact is reproduced. The copy is then sliced. A picture is taken for each slice. Eventually, geometric information is manually determined from the pictures. Such a technique is very time consuming, and the processing applied to the original, as well as the reproduced object, induces several measurement errors (prototyping approximations, slicing, image acquisition, and measurement). By using 3D scanners, we significantly reduce the number of operations related to data acquisition and completely suppress the prototyping step to obtain an accurate 3D model. The 3D models are segmented into sliced parts that are then analyzed. Each slice is then automatically fitted by mathematical representation. Such a representation offers several interesting properties: geometric features can be characterized (e.g. shapes, curvature, sharp edges, etc), and a shape of the original piece of stone can be extrapolated. The contributions of this paper are an acquisition technique using 3D scanners that strongly reduces human intervention, acquisition time and measurement errors, and the representation of flint artefacts as mathematical 2D sections that enable accurate analysis.

  1. Physical and Numerical Model Studies of Cross-flow Turbines Towards Accurate Parameterization in Array Simulations

    NASA Astrophysics Data System (ADS)

    Wosnik, M.; Bachant, P.

    2014-12-01

    Cross-flow turbines, often referred to as vertical-axis turbines, show potential for success in marine hydrokinetic (MHK) and wind energy applications, ranging from small- to utility-scale installations in tidal/ocean currents and offshore wind. As turbine designs mature, the research focus is shifting from individual devices to the optimization of turbine arrays. It would be expensive and time-consuming to conduct physical model studies of large arrays at large model scales (to achieve sufficiently high Reynolds numbers), and hence numerical techniques are generally better suited to explore the array design parameter space. However, since the computing power available today is not sufficient to conduct simulations of the flow in and around large arrays of turbines with fully resolved turbine geometries (e.g., grid resolution into the viscous sublayer on turbine blades), the turbines' interaction with the energy resource (water current or wind) needs to be parameterized, or modeled. Models used today--a common model is the actuator disk concept--are not able to predict the unique wake structure generated by cross-flow turbines. This wake structure has been shown to create "constructive" interference in some cases, improving turbine performance in array configurations, in contrast with axial-flow, or horizontal axis devices. Towards a more accurate parameterization of cross-flow turbines, an extensive experimental study was carried out using a high-resolution turbine test bed with wake measurement capability in a large cross-section tow tank. The experimental results were then "interpolated" using high-fidelity Navier--Stokes simulations, to gain insight into the turbine's near-wake. The study was designed to achieve sufficiently high Reynolds numbers for the results to be Reynolds number independent with respect to turbine performance and wake statistics, such that they can be reliably extrapolated to full scale and used for model validation. The end product of

  2. Complex functionality with minimal computation: Promise and pitfalls of reduced-tracer ocean biogeochemistry models

    NASA Astrophysics Data System (ADS)

    Galbraith, Eric D.; Dunne, John P.; Gnanadesikan, Anand; Slater, Richard D.; Sarmiento, Jorge L.; Dufour, Carolina O.; de Souza, Gregory F.; Bianchi, Daniele; Claret, Mariona; Rodgers, Keith B.; Marvasti, Seyedehsafoura Sedigh

    2015-12-01

    Earth System Models increasingly include ocean biogeochemistry models in order to predict changes in ocean carbon storage, hypoxia, and biological productivity under climate change. However, state-of-the-art ocean biogeochemical models include many advected tracers, that significantly increase the computational resources required, forcing a trade-off with spatial resolution. Here, we compare a state-of-the art model with 30 prognostic tracers (TOPAZ) with two reduced-tracer models, one with 6 tracers (BLING), and the other with 3 tracers (miniBLING). The reduced-tracer models employ parameterized, implicit biological functions, which nonetheless capture many of the most important processes resolved by TOPAZ. All three are embedded in the same coupled climate model. Despite the large difference in tracer number, the absence of tracers for living organic matter is shown to have a minimal impact on the transport of nutrient elements, and the three models produce similar mean annual preindustrial distributions of macronutrients, oxygen, and carbon. Significant differences do exist among the models, in particular the seasonal cycle of biomass and export production, but it does not appear that these are necessary consequences of the reduced tracer number. With increasing CO2, changes in dissolved oxygen and anthropogenic carbon uptake are very similar across the different models. Thus, while the reduced-tracer models do not explicitly resolve the diversity and internal dynamics of marine ecosystems, we demonstrate that such models are applicable to a broad suite of major biogeochemical concerns, including anthropogenic change. These results are very promising for the further development and application of reduced-tracer biogeochemical models that incorporate "sub-ecosystem-scale" parameterizations.

  3. Complex functionality with minimal computation. Promise and pitfalls of reduced-tracer ocean biogeochemistry models

    DOE PAGES

    Galbraith, Eric D.; Dunne, John P.; Gnanadesikan, Anand; ...

    2015-12-21

    Earth System Models increasingly include ocean biogeochemistry models in order to predict changes in ocean carbon storage, hypoxia, and biological productivity under climate change. However, state-of-the-art ocean biogeochemical models include many advected tracers, that significantly increase the computational resources required, forcing a trade-off with spatial resolution. Here, we compare a state-of the art model with 30 prognostic tracers (TOPAZ) with two reduced-tracer models, one with 6 tracers (BLING), and the other with 3 tracers (miniBLING). The reduced-tracer models employ parameterized, implicit biological functions, which nonetheless capture many of the most important processes resolved by TOPAZ. All three are embedded inmore » the same coupled climate model. Despite the large difference in tracer number, the absence of tracers for living organic matter is shown to have a minimal impact on the transport of nutrient elements, and the three models produce similar mean annual preindustrial distributions of macronutrients, oxygen, and carbon. Significant differences do exist among the models, in particular the seasonal cycle of biomass and export production, but it does not appear that these are necessary consequences of the reduced tracer number. With increasing CO2, changes in dissolved oxygen and anthropogenic carbon uptake are very similar across the different models. Thus, while the reduced-tracer models do not explicitly resolve the diversity and internal dynamics of marine ecosystems, we demonstrate that such models are applicable to a broad suite of major biogeochemical concerns, including anthropogenic change. Lastly, these results are very promising for the further development and application of reduced-tracer biogeochemical models that incorporate ‘‘sub-ecosystem-scale’’ parameterizations.« less

  4. A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

    NASA Astrophysics Data System (ADS)

    Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; Zhang, Guannan; Ye, Ming; Wu, Jianfeng; Wu, Jichun

    2017-12-01

    Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we develop a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.

  5. 38 CFR 4.46 - Accurate measurement.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate... indispensable in examinations conducted within the Department of Veterans Affairs. Muscle atrophy must also be...

  6. 38 CFR 4.46 - Accurate measurement.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate... indispensable in examinations conducted within the Department of Veterans Affairs. Muscle atrophy must also be...

  7. 38 CFR 4.46 - Accurate measurement.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate... indispensable in examinations conducted within the Department of Veterans Affairs. Muscle atrophy must also be...

  8. 38 CFR 4.46 - Accurate measurement.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate... indispensable in examinations conducted within the Department of Veterans Affairs. Muscle atrophy must also be...

  9. 38 CFR 4.46 - Accurate measurement.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate... indispensable in examinations conducted within the Department of Veterans Affairs. Muscle atrophy must also be...

  10. Accurate Segmentation of CT Male Pelvic Organs via Regression-based Deformable Models and Multi-task Random Forests

    PubMed Central

    Gao, Yaozong; Shao, Yeqin; Lian, Jun; Wang, Andrew Z.; Chen, Ronald C.

    2016-01-01

    Segmenting male pelvic organs from CT images is a prerequisite for prostate cancer radiotherapy. The efficacy of radiation treatment highly depends on segmentation accuracy. However, accurate segmentation of male pelvic organs is challenging due to low tissue contrast of CT images, as well as large variations of shape and appearance of the pelvic organs. Among existing segmentation methods, deformable models are the most popular, as shape prior can be easily incorporated to regularize the segmentation. Nonetheless, the sensitivity to initialization often limits their performance, especially for segmenting organs with large shape variations. In this paper, we propose a novel approach to guide deformable models, thus making them robust against arbitrary initializations. Specifically, we learn a displacement regressor, which predicts 3D displacement from any image voxel to the target organ boundary based on the local patch appearance. This regressor provides a nonlocal external force for each vertex of deformable model, thus overcoming the initialization problem suffered by the traditional deformable models. To learn a reliable displacement regressor, two strategies are particularly proposed. 1) A multi-task random forest is proposed to learn the displacement regressor jointly with the organ classifier; 2) an auto-context model is used to iteratively enforce structural information during voxel-wise prediction. Extensive experiments on 313 planning CT scans of 313 patients show that our method achieves better results than alternative classification or regression based methods, and also several other existing methods in CT pelvic organ segmentation. PMID:26800531

  11. Feedback about More Accurate versus Less Accurate Trials: Differential Effects on Self-Confidence and Activation

    ERIC Educational Resources Information Center

    Badami, Rokhsareh; VaezMousavi, Mohammad; Wulf, Gabriele; Namazizadeh, Mahdi

    2012-01-01

    One purpose of the present study was to examine whether self-confidence or anxiety would be differentially affected by feedback from more accurate rather than less accurate trials. The second purpose was to determine whether arousal variations (activation) would predict performance. On Day 1, participants performed a golf putting task under one of…

  12. Adaptation of hidden Markov models for recognizing speech of reduced frame rate.

    PubMed

    Lee, Lee-Min; Jean, Fu-Rong

    2013-12-01

    The frame rate of the observation sequence in distributed speech recognition applications may be reduced to suit a resource-limited front-end device. In order to use models trained using full-frame-rate data in the recognition of reduced frame-rate (RFR) data, we propose a method for adapting the transition probabilities of hidden Markov models (HMMs) to match the frame rate of the observation. Experiments on the recognition of clean and noisy connected digits are conducted to evaluate the proposed method. Experimental results show that the proposed method can effectively compensate for the frame-rate mismatch between the training and the test data. Using our adapted model to recognize the RFR speech data, one can significantly reduce the computation time and achieve the same level of accuracy as that of a method, which restores the frame rate using data interpolation.

  13. A model for reducing health care employee turnover.

    PubMed

    Nowak, Paul; Holmes, Gary; Murrow, Jim

    2010-01-01

    Explaining the rationale as to why employees leave their jobs has led to many different strategies to retain employees. The model presented here seeks to explain why employees choose to stay or to leave their place of employment. The information from the analysis will provide managers with well-tested tools to reduce turnover and to ascertain what employees value from their work environment in order to help the organization to retain those employees. The model identifies key factors that management can utilize to provide barriers to exit and retain professional employees in their health care units. Recommendations are provided that reward loyalty and build barriers to exit.

  14. Reduced-Order Direct Numerical Simulation of Solute Transport in Porous Media

    NASA Astrophysics Data System (ADS)

    Mehmani, Yashar; Tchelepi, Hamdi

    2017-11-01

    Pore-scale models are an important tool for analyzing fluid dynamics in porous materials (e.g., rocks, soils, fuel cells). Current direct numerical simulation (DNS) techniques, while very accurate, are computationally prohibitive for sample sizes that are statistically representative of the porous structure. Reduced-order approaches such as pore-network models (PNM) aim to approximate the pore-space geometry and physics to remedy this problem. Predictions from current techniques, however, have not always been successful. This work focuses on single-phase transport of a passive solute under advection-dominated regimes and delineates the minimum set of approximations that consistently produce accurate PNM predictions. Novel network extraction (discretization) and particle simulation techniques are developed and compared to high-fidelity DNS simulations for a wide range of micromodel heterogeneities and a single sphere pack. Moreover, common modeling assumptions in the literature are analyzed and shown that they can lead to first-order errors under advection-dominated regimes. This work has implications for optimizing material design and operations in manufactured (electrodes) and natural (rocks) porous media pertaining to energy systems. This work was supported by the Stanford University Petroleum Research Institute for Reservoir Simulation (SUPRI-B).

  15. [Accurate 3D free-form registration between fan-beam CT and cone-beam CT].

    PubMed

    Liang, Yueqiang; Xu, Hongbing; Li, Baosheng; Li, Hongsheng; Yang, Fujun

    2012-06-01

    Because the X-ray scatters, the CT numbers in cone-beam CT cannot exactly correspond to the electron densities. This, therefore, results in registration error when the intensity-based registration algorithm is used to register planning fan-beam CT and cone-beam CT. In order to reduce the registration error, we have developed an accurate gradient-based registration algorithm. The gradient-based deformable registration problem is described as a minimization of energy functional. Through the calculus of variations and Gauss-Seidel finite difference method, we derived the iterative formula of the deformable registration. The algorithm was implemented by GPU through OpenCL framework, with which the registration time was greatly reduced. Our experimental results showed that the proposed gradient-based registration algorithm could register more accurately the clinical cone-beam CT and fan-beam CT images compared with the intensity-based algorithm. The GPU-accelerated algorithm meets the real-time requirement in the online adaptive radiotherapy.

  16. a Semi-Empirical Topographic Correction Model for Multi-Source Satellite Images

    NASA Astrophysics Data System (ADS)

    Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei

    2018-04-01

    Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.

  17. Training Maneuver Evaluation for Reduced Order Modeling of Stability & Control Properties Using Computational Fluid Dynamics

    DTIC Science & Technology

    2013-03-01

    reduced order model is created. Finally, previous research in this area of study will be examined, and its application to this research will be...TRAINING MANEUVER EVALUATION FOR REDUCED ORDER MODELING OF STABILITY & CONTROL PROPERTIES USING COMPUTATIONAL FLUID DYNAMICS THESIS Craig Curtis...Government and is not subject to copyright protection in the United States. AFIT-ENY-13-M-28 TRAINING MANEUVER EVALUATION FOR REDUCED ORDER MODELING OF

  18. Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

    PubMed

    Jeong, Jenny; Frohberg, Nicholas J; Zhou, Enlu; Sulchek, Todd; Qiu, Peng

    2018-01-01

    Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

  19. Hybrid Reduced Order Modeling Algorithms for Reactor Physics Calculations

    NASA Astrophysics Data System (ADS)

    Bang, Youngsuk

    Reduced order modeling (ROM) has been recognized as an indispensable approach when the engineering analysis requires many executions of high fidelity simulation codes. Examples of such engineering analyses in nuclear reactor core calculations, representing the focus of this dissertation, include the functionalization of the homogenized few-group cross-sections in terms of the various core conditions, e.g. burn-up, fuel enrichment, temperature, etc. This is done via assembly calculations which are executed many times to generate the required functionalization for use in the downstream core calculations. Other examples are sensitivity analysis used to determine important core attribute variations due to input parameter variations, and uncertainty quantification employed to estimate core attribute uncertainties originating from input parameter uncertainties. ROM constructs a surrogate model with quantifiable accuracy which can replace the original code for subsequent engineering analysis calculations. This is achieved by reducing the effective dimensionality of the input parameter, the state variable, or the output response spaces, by projection onto the so-called active subspaces. Confining the variations to the active subspace allows one to construct an ROM model of reduced complexity which can be solved more efficiently. This dissertation introduces a new algorithm to render reduction with the reduction errors bounded based on a user-defined error tolerance which represents the main challenge of existing ROM techniques. Bounding the error is the key to ensuring that the constructed ROM models are robust for all possible applications. Providing such error bounds represents one of the algorithmic contributions of this dissertation to the ROM state-of-the-art. Recognizing that ROM techniques have been developed to render reduction at different levels, e.g. the input parameter space, the state space, and the response space, this dissertation offers a set of novel

  20. Wind Turbine Modeling Overview for Control Engineers

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Moriarty, P. J.; Butterfield, S. B.

    2009-01-01

    Accurate modeling of wind turbine systems is of paramount importance for controls engineers seeking to reduce loads and optimize energy capture of operating turbines in the field. When designing control systems, engineers often employ a series of models developed in the different disciplines of wind energy. The limitations and coupling of each of these models is explained to highlight how these models might influence control system design.

  1. Reverse radiance: a fast accurate method for determining luminance

    NASA Astrophysics Data System (ADS)

    Moore, Kenneth E.; Rykowski, Ronald F.; Gangadhara, Sanjay

    2012-10-01

    Reverse ray tracing from a region of interest backward to the source has long been proposed as an efficient method of determining luminous flux. The idea is to trace rays only from where the final flux needs to be known back to the source, rather than tracing in the forward direction from the source outward to see where the light goes. Once the reverse ray reaches the source, the radiance the equivalent forward ray would have represented is determined and the resulting flux computed. Although reverse ray tracing is conceptually simple, the method critically depends upon an accurate source model in both the near and far field. An overly simplified source model, such as an ideal Lambertian surface substantially detracts from the accuracy and thus benefit of the method. This paper will introduce an improved method of reverse ray tracing that we call Reverse Radiance that avoids assumptions about the source properties. The new method uses measured data from a Source Imaging Goniometer (SIG) that simultaneously measures near and far field luminous data. Incorporating this data into a fast reverse ray tracing integration method yields fast, accurate data for a wide variety of illumination problems.

  2. Accurate and general treatment of electrostatic interaction in Hamiltonian adaptive resolution simulations

    NASA Astrophysics Data System (ADS)

    Heidari, M.; Cortes-Huerto, R.; Donadio, D.; Potestio, R.

    2016-10-01

    In adaptive resolution simulations the same system is concurrently modeled with different resolution in different subdomains of the simulation box, thereby enabling an accurate description in a small but relevant region, while the rest is treated with a computationally parsimonious model. In this framework, electrostatic interaction, whose accurate treatment is a crucial aspect in the realistic modeling of soft matter and biological systems, represents a particularly acute problem due to the intrinsic long-range nature of Coulomb potential. In the present work we propose and validate the usage of a short-range modification of Coulomb potential, the Damped shifted force (DSF) model, in the context of the Hamiltonian adaptive resolution simulation (H-AdResS) scheme. This approach, which is here validated on bulk water, ensures a reliable reproduction of the structural and dynamical properties of the liquid, and enables a seamless embedding in the H-AdResS framework. The resulting dual-resolution setup is implemented in the LAMMPS simulation package, and its customized version employed in the present work is made publicly available.

  3. New explicit equations for the accurate calculation of the growth and evaporation of hydrometeors by the diffusion of water vapor

    NASA Technical Reports Server (NTRS)

    Srivastava, R. C.; Coen, J. L.

    1992-01-01

    The traditional explicit growth equation has been widely used to calculate the growth and evaporation of hydrometeors by the diffusion of water vapor. This paper reexamines the assumptions underlying the traditional equation and shows that large errors (10-30 percent in some cases) result if it is used carelessly. More accurate explicit equations are derived by approximating the saturation vapor-density difference as a quadratic rather than a linear function of the temperature difference between the particle and ambient air. These new equations, which reduce the error to less than a few percent, merit inclusion in a broad range of atmospheric models.

  4. Quasi-closed phase forward-backward linear prediction analysis of speech for accurate formant detection and estimation.

    PubMed

    Gowda, Dhananjaya; Airaksinen, Manu; Alku, Paavo

    2017-09-01

    Recently, a quasi-closed phase (QCP) analysis of speech signals for accurate glottal inverse filtering was proposed. However, the QCP analysis which belongs to the family of temporally weighted linear prediction (WLP) methods uses the conventional forward type of sample prediction. This may not be the best choice especially in computing WLP models with a hard-limiting weighting function. A sample selective minimization of the prediction error in WLP reduces the effective number of samples available within a given window frame. To counter this problem, a modified quasi-closed phase forward-backward (QCP-FB) analysis is proposed, wherein each sample is predicted based on its past as well as future samples thereby utilizing the available number of samples more effectively. Formant detection and estimation experiments on synthetic vowels generated using a physical modeling approach as well as natural speech utterances show that the proposed QCP-FB method yields statistically significant improvements over the conventional linear prediction and QCP methods.

  5. Reduced-order modeling of piezoelectric energy harvesters with nonlinear circuits under complex conditions

    NASA Astrophysics Data System (ADS)

    Xiang, Hong-Jun; Zhang, Zhi-Wei; Shi, Zhi-Fei; Li, Hong

    2018-04-01

    A fully coupled modeling approach is developed for piezoelectric energy harvesters in this work based on the use of available robust finite element packages and efficient reducing order modeling techniques. At first, the harvester is modeled using finite element packages. The dynamic equilibrium equations of harvesters are rebuilt by extracting system matrices from the finite element model using built-in commands without any additional tools. A Krylov subspace-based scheme is then applied to obtain a reduced-order model for improving simulation efficiency but preserving the key features of harvesters. Co-simulation of the reduced-order model with nonlinear energy harvesting circuits is achieved in a system level. Several examples in both cases of harmonic response and transient response analysis are conducted to validate the present approach. The proposed approach allows to improve the simulation efficiency by several orders of magnitude. Moreover, the parameters used in the equivalent circuit model can be conveniently obtained by the proposed eigenvector-based model order reduction technique. More importantly, this work establishes a methodology for modeling of piezoelectric energy harvesters with any complicated mechanical geometries and nonlinear circuits. The input load may be more complex also. The method can be employed by harvester designers to optimal mechanical structures or by circuit designers to develop novel energy harvesting circuits.

  6. Applying Recursive Sensitivity Analysis to Multi-Criteria Decision Models to Reduce Bias in Defense Cyber Engineering Analysis

    DTIC Science & Technology

    2015-10-28

    techniques such as regression analysis, correlation, and multicollinearity assessment to identify the change and error on the input to the model...between many of the independent or predictor variables, the issue of multicollinearity may arise [18]. VII. SUMMARY Accurate decisions concerning

  7. Method of and apparatus for modeling interactions

    DOEpatents

    Budge, Kent G.

    2004-01-13

    A method and apparatus for modeling interactions can accurately model tribological and other properties and accommodate topological disruptions. Two portions of a problem space are represented, a first with a Lagrangian mesh and a second with an ALE mesh. The ALE and Lagrangian meshes are constructed so that each node on the surface of the Lagrangian mesh is in a known correspondence with adjacent nodes in the ALE mesh. The interaction can be predicted for a time interval. Material flow within the ALE mesh can accurately model complex interactions such as bifurcation. After prediction, nodes in the ALE mesh in correspondence with nodes on the surface of the Lagrangian mesh can be mapped so that they are once again adjacent to their corresponding Lagrangian mesh nodes. The ALE mesh can then be smoothed to reduce mesh distortion that might reduce the accuracy or efficiency of subsequent prediction steps. The process, from prediction through mapping and smoothing, can be repeated until a terminal condition is reached.

  8. Crop Model Improvement Reduces the Uncertainty of the Response to Temperature of Multi-Model Ensembles

    NASA Technical Reports Server (NTRS)

    Maiorano, Andrea; Martre, Pierre; Asseng, Senthold; Ewert, Frank; Mueller, Christoph; Roetter, Reimund P.; Ruane, Alex C.; Semenov, Mikhail A.; Wallach, Daniel; Wang, Enli

    2016-01-01

    To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT worldwide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures greater than 24 C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.

  9. A manufacturing error measurement methodology for a rotary vector reducer cycloidal gear based on a gear measuring center

    NASA Astrophysics Data System (ADS)

    Li, Tianxing; Zhou, Junxiang; Deng, Xiaozhong; Li, Jubo; Xing, Chunrong; Su, Jianxin; Wang, Huiliang

    2018-07-01

    A manufacturing error of a cycloidal gear is the key factor affecting the transmission accuracy of a robot rotary vector (RV) reducer. A methodology is proposed to realize the digitized measurement and data processing of the cycloidal gear manufacturing error based on the gear measuring center, which can quickly and accurately measure and evaluate the manufacturing error of the cycloidal gear by using both the whole tooth profile measurement and a single tooth profile measurement. By analyzing the particularity of the cycloidal profile and its effect on the actual meshing characteristics of the RV transmission, the cycloid profile measurement strategy is planned, and the theoretical profile model and error measurement model of cycloid-pin gear transmission are established. Through the digital processing technology, the theoretical trajectory of the probe and the normal vector of the measured point are calculated. By means of precision measurement principle and error compensation theory, a mathematical model for the accurate calculation and data processing of manufacturing error is constructed, and the actual manufacturing error of the cycloidal gear is obtained by the optimization iterative solution. Finally, the measurement experiment of the cycloidal gear tooth profile is carried out on the gear measuring center and the HEXAGON coordinate measuring machine, respectively. The measurement results verify the correctness and validity of the measurement theory and method. This methodology will provide the basis for the accurate evaluation and the effective control of manufacturing precision of the cycloidal gear in a robot RV reducer.

  10. A fourth order accurate finite difference scheme for the computation of elastic waves

    NASA Technical Reports Server (NTRS)

    Bayliss, A.; Jordan, K. E.; Lemesurier, B. J.; Turkel, E.

    1986-01-01

    A finite difference for elastic waves is introduced. The model is based on the first order system of equations for the velocities and stresses. The differencing is fourth order accurate on the spatial derivatives and second order accurate in time. The model is tested on a series of examples including the Lamb problem, scattering from plane interf aces and scattering from a fluid-elastic interface. The scheme is shown to be effective for these problems. The accuracy and stability is insensitive to the Poisson ratio. For the class of problems considered here it is found that the fourth order scheme requires for two-thirds to one-half the resolution of a typical second order scheme to give comparable accuracy.

  11. Does a pneumotach accurately characterize voice function?

    NASA Astrophysics Data System (ADS)

    Walters, Gage; Krane, Michael

    2016-11-01

    A study is presented which addresses how a pneumotach might adversely affect clinical measurements of voice function. A pneumotach is a device, typically a mask, worn over the mouth, in order to measure time-varying glottal volume flow. By measuring the time-varying difference in pressure across a known aerodynamic resistance element in the mask, the glottal volume flow waveform is estimated. Because it adds aerodynamic resistance to the vocal system, there is some concern that using a pneumotach may not accurately portray the behavior of the voice. To test this hypothesis, experiments were performed in a simplified airway model with the principal dimensions of an adult human upper airway. A compliant constriction, fabricated from silicone rubber, modeled the vocal folds. Variations of transglottal pressure, time-averaged volume flow, model vocal fold vibration amplitude, and radiated sound with subglottal pressure were performed, with and without the pneumotach in place, and differences noted. Acknowledge support of NIH Grant 2R01DC005642-10A1.

  12. Can we Use Low-Cost 360 Degree Cameras to Create Accurate 3d Models?

    NASA Astrophysics Data System (ADS)

    Barazzetti, L.; Previtali, M.; Roncoroni, F.

    2018-05-01

    360 degree cameras capture the whole scene around a photographer in a single shot. Cheap 360 cameras are a new paradigm in photogrammetry. The camera can be pointed to any direction, and the large field of view reduces the number of photographs. This paper aims to show that accurate metric reconstructions can be achieved with affordable sensors (less than 300 euro). The camera used in this work is the Xiaomi Mijia Mi Sphere 360, which has a cost of about 300 USD (January 2018). Experiments demonstrate that millimeter-level accuracy can be obtained during the image orientation and surface reconstruction steps, in which the solution from 360° images was compared to check points measured with a total station and laser scanning point clouds. The paper will summarize some practical rules for image acquisition as well as the importance of ground control points to remove possible deformations of the network during bundle adjustment, especially for long sequences with unfavorable geometry. The generation of orthophotos from images having a 360° field of view (that captures the entire scene around the camera) is discussed. Finally, the paper illustrates some case studies where the use of a 360° camera could be a better choice than a project based on central perspective cameras. Basically, 360° cameras become very useful in the survey of long and narrow spaces, as well as interior areas like small rooms.

  13. Reduced atomic pair-interaction design (RAPID) model for simulations of proteins.

    PubMed

    Ni, Boris; Baumketner, Andrij

    2013-02-14

    Increasingly, theoretical studies of proteins focus on large systems. This trend demands the development of computational models that are fast, to overcome the growing complexity, and accurate, to capture the physically relevant features. To address this demand, we introduce a protein model that uses all-atom architecture to ensure the highest level of chemical detail while employing effective pair potentials to represent the effect of solvent to achieve the maximum speed. The effective potentials are derived for amino acid residues based on the condition that the solvent-free model matches the relevant pair-distribution functions observed in explicit solvent simulations. As a test, the model is applied to alanine polypeptides. For the chain with 10 amino acid residues, the model is found to reproduce properly the native state and its population. Small discrepancies are observed for other folding properties and can be attributed to the approximations inherent in the model. The transferability of the generated effective potentials is investigated in simulations of a longer peptide with 25 residues. A minimal set of potentials is identified that leads to qualitatively correct results in comparison with the explicit solvent simulations. Further tests, conducted for multiple peptide chains, show that the transferable model correctly reproduces the experimentally observed tendency of polyalanines to aggregate into β-sheets more strongly with the growing length of the peptide chain. Taken together, the reported results suggest that the proposed model could be used to succesfully simulate folding and aggregation of small peptides in atomic detail. Further tests are needed to assess the strengths and limitations of the model more thoroughly.

  14. Accurate and precise determination of isotopic ratios by MC-ICP-MS: a review.

    PubMed

    Yang, Lu

    2009-01-01

    For many decades the accurate and precise determination of isotope ratios has remained a very strong interest to many researchers due to its important applications in earth, environmental, biological, archeological, and medical sciences. Traditionally, thermal ionization mass spectrometry (TIMS) has been the technique of choice for achieving the highest accuracy and precision. However, recent developments in multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) have brought a new dimension to this field. In addition to its simple and robust sample introduction, high sample throughput, and high mass resolution, the flat-topped peaks generated by this technique provide for accurate and precise determination of isotope ratios with precision reaching 0.001%, comparable to that achieved with TIMS. These features, in combination with the ability of the ICP source to ionize nearly all elements in the periodic table, have resulted in an increased use of MC-ICP-MS for such measurements in various sample matrices. To determine accurate and precise isotope ratios with MC-ICP-MS, utmost care must be exercised during sample preparation, optimization of the instrument, and mass bias corrections. Unfortunately, there are inconsistencies and errors evident in many MC-ICP-MS publications, including errors in mass bias correction models. This review examines "state-of-the-art" methodologies presented in the literature for achievement of precise and accurate determinations of isotope ratios by MC-ICP-MS. Some general rules for such accurate and precise measurements are suggested, and calculations of combined uncertainty of the data using a few common mass bias correction models are outlined.

  15. Disambiguating past events: Accurate source memory for time and context depends on different retrieval processes.

    PubMed

    Persson, Bjorn M; Ainge, James A; O'Connor, Akira R

    2016-07-01

    Current animal models of episodic memory are usually based on demonstrating integrated memory for what happened, where it happened, and when an event took place. These models aim to capture the testable features of the definition of human episodic memory which stresses the temporal component of the memory as a unique piece of source information that allows us to disambiguate one memory from another. Recently though, it has been suggested that a more accurate model of human episodic memory would include contextual rather than temporal source information, as humans' memory for time is relatively poor. Here, two experiments were carried out investigating human memory for temporal and contextual source information, along with the underlying dual process retrieval processes, using an immersive virtual environment paired with a 'Remember-Know' memory task. Experiment 1 (n=28) showed that contextual information could only be retrieved accurately using recollection, while temporal information could be retrieved using either recollection or familiarity. Experiment 2 (n=24), which used a more difficult task, resulting in reduced item recognition rates and therefore less potential for contamination by ceiling effects, replicated the pattern of results from Experiment 1. Dual process theory predicts that it should only be possible to retrieve source context from an event using recollection, and our results are consistent with this prediction. That temporal information can be retrieved using familiarity alone suggests that it may be incorrect to view temporal context as analogous to other typically used source contexts. This latter finding supports the alternative proposal that time since presentation may simply be reflected in the strength of memory trace at retrieval - a measure ideally suited to trace strength interrogation using familiarity, as is typically conceptualised within the dual process framework. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Experimental evaluation of a recursive model identification technique for type 1 diabetes.

    PubMed

    Finan, Daniel A; Doyle, Francis J; Palerm, Cesar C; Bevier, Wendy C; Zisser, Howard C; Jovanovic, Lois; Seborg, Dale E

    2009-09-01

    validation techniques were performed with both "normal" data and data collected during conditions of reduced insulin sensitivity. The latter were achieved by having the subjects self-administer a medication, prednisone, for 3 consecutive days. The recursive models were allowed to adapt to this condition of reduced insulin sensitivity, while the batch models were only identified from normal data. Data from nine type 1 diabetes subjects in ambulatory conditions were analyzed; six of these subjects also participated in the prednisone portion of the study. For normal test data, the batch ARX models produced 30-, 45-, and 60-minute-ahead predictions that had average root mean square error (RMSE) values of 26, 34, and 40 mg/dl, respectively. For test data characterized by reduced insulin sensitivity, the batch ARX models produced 30-, 60-, and 90-minute-ahead predictions with average RMSE values of 27, 46, and 59 mg/dl, respectively; the recursive ARX models demonstrated similar performance with corresponding values of 27, 45, and 61 mg/dl, respectively. The identified ARX models (batch and recursive) produced more accurate predictions than the model-free ZOH predictions, but only marginally. For test data characterized by reduced insulin sensitivity, RMSE values for the predictions of the batch ARX models were 9, 5, and 5% more accurate than the ZOH predictions for prediction horizons of 30, 60, and 90 minutes, respectively. In terms of RMSE values, the 30-, 60-, and 90-minute predictions of the recursive models were more accurate than the ZOH predictions, by 10, 5, and 2%, respectively. In this experimental study, the recursively identified ARX models resulted in predictions of test data that were similar, but not superior, to the batch models. Even for the test data characteristic of reduced insulin sensitivity, the batch and recursive models demonstrated similar prediction accuracy. The predictions of the identified ARX models were only marginally more accurate than the model

  17. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Gan, Yangzhou; Zhao, Qunfei; Xia, Zeyang, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn

    Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slicemore » and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0

  18. Wall Shear Stress Distribution in a Patient-Specific Cerebral Aneurysm Model using Reduced Order Modeling

    NASA Astrophysics Data System (ADS)

    Han, Suyue; Chang, Gary Han; Schirmer, Clemens; Modarres-Sadeghi, Yahya

    2016-11-01

    We construct a reduced-order model (ROM) to study the Wall Shear Stress (WSS) distributions in image-based patient-specific aneurysms models. The magnitude of WSS has been shown to be a critical factor in growth and rupture of human aneurysms. We start the process by running a training case using Computational Fluid Dynamics (CFD) simulation with time-varying flow parameters, such that these parameters cover the range of parameters of interest. The method of snapshot Proper Orthogonal Decomposition (POD) is utilized to construct the reduced-order bases using the training CFD simulation. The resulting ROM enables us to study the flow patterns and the WSS distributions over a range of system parameters computationally very efficiently with a relatively small number of modes. This enables comprehensive analysis of the model system across a range of physiological conditions without the need to re-compute the simulation for small changes in the system parameters.

  19. A HYBRID MODE MODEL OF THE BLAZHKO EFFECT, SHOWN TO ACCURATELY FIT KEPLER DATA FOR RR Lyr

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bryant, Paul H., E-mail: pbryant@ucsd.edu

    2014-03-01

    The waveform for Blazhko stars can be substantially different during the ascending and descending parts of the Blazhko cycle. A hybrid model, consisting of two component oscillators of the same frequency, is proposed as a means to fit the data over the entire cycle. One component exhibits a sawtooth-like velocity waveform while the other is nearly sinusoidal. One method of generating such a hybrid is presented: a nonlinear model is developed for the first overtone mode, which, if excited to large amplitude, is found to drop strongly in frequency and become highly non-sinusoidal. If the frequency drops sufficiently to becomemore » equal to the fundamental frequency, the two can become phase locked and form the desired hybrid. A relationship is assumed between the hybrid mode velocity and the observed light curve, which is approximated as a power series. An accurate fit of the hybrid model is made to actual Kepler data for RR Lyr. The sinusoidal component may tend to stabilize the period of the hybrid which is found in real Blazhko data to be extremely stable. It is proposed that the variations in amplitude and phase might result from a nonlinear interaction with a third mode, possibly a nonradial mode at 3/2 the fundamental frequency. The hybrid model also applies to non-Blazhko RRab stars and provides an explanation for the light curve bump. A method to estimate the surface gravity is also proposed.« less

  20. Accurate segmentation framework for the left ventricle wall from cardiac cine MRI

    NASA Astrophysics Data System (ADS)

    Sliman, H.; Khalifa, F.; Elnakib, A.; Soliman, A.; Beache, G. M.; Gimel'farb, G.; Emam, A.; Elmaghraby, A.; El-Baz, A.

    2013-10-01

    We propose a novel, fast, robust, bi-directional coupled parametric deformable model to segment the left ventricle (LV) wall borders using first- and second-order visual appearance features. These features are embedded in a new stochastic external force that preserves the topology of LV wall to track the evolution of the parametric deformable models control points. To accurately estimate the marginal density of each deformable model control point, the empirical marginal grey level distributions (first-order appearance) inside and outside the boundary of the deformable model are modeled with adaptive linear combinations of discrete Gaussians (LCDG). The second order visual appearance of the LV wall is accurately modeled with a new rotationally invariant second-order Markov-Gibbs random field (MGRF). We tested the proposed segmentation approach on 15 data sets in 6 infarction patients using the Dice similarity coefficient (DSC) and the average distance (AD) between the ground truth and automated segmentation contours. Our approach achieves a mean DSC value of 0.926±0.022 and AD value of 2.16±0.60 compared to two other level set methods that achieve 0.904±0.033 and 0.885±0.02 for DSC; and 2.86±1.35 and 5.72±4.70 for AD, respectively.

  1. Development and application of a technique for reducing airframe finite element models for dynamics analysis

    NASA Technical Reports Server (NTRS)

    Hashemi-Kia, Mostafa; Toossi, Mostafa

    1990-01-01

    A computational procedure for the reduction of large finite element models was developed. This procedure is used to obtain a significantly reduced model while retaining the essential global dynamic characteristics of the full-size model. This reduction procedure is applied to the airframe finite element model of AH-64A Attack Helicopter. The resulting reduced model is then validated by application to a vibration reduction study.

  2. Data-assisted reduced-order modeling of extreme events in complex dynamical systems

    PubMed Central

    Koumoutsakos, Petros

    2018-01-01

    The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in

  3. Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

    PubMed

    Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis

    2018-01-01

    The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in

  4. Construction of Optimally Reduced Empirical Model by Spatially Distributed Climate Data

    NASA Astrophysics Data System (ADS)

    Gavrilov, A.; Mukhin, D.; Loskutov, E.; Feigin, A.

    2016-12-01

    We present an approach to empirical reconstruction of the evolution operator in stochastic form by space-distributed time series. The main problem in empirical modeling consists in choosing appropriate phase variables which can efficiently reduce the dimension of the model at minimal loss of information about system's dynamics which consequently leads to more robust model and better quality of the reconstruction. For this purpose we incorporate in the model two key steps. The first step is standard preliminary reduction of observed time series dimension by decomposition via certain empirical basis (e. g. empirical orthogonal function basis or its nonlinear or spatio-temporal generalizations). The second step is construction of an evolution operator by principal components (PCs) - the time series obtained by the decomposition. In this step we introduce a new way of reducing the dimension of the embedding in which the evolution operator is constructed. It is based on choosing proper combinations of delayed PCs to take into account the most significant spatio-temporal couplings. The evolution operator is sought as nonlinear random mapping parameterized using artificial neural networks (ANN). Bayesian approach is used to learn the model and to find optimal hyperparameters: the number of PCs, the dimension of the embedding, the degree of the nonlinearity of ANN. The results of application of the method to climate data (sea surface temperature, sea level pressure) and their comparing with the same method based on non-reduced embedding are presented. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS).

  5. Accurate Measurements of the Local Deuterium Abundance from HST Spectra

    NASA Technical Reports Server (NTRS)

    Linsky, Jeffrey L.

    1996-01-01

    An accurate measurement of the primordial value of D/H would provide a critical test of nucleosynthesis models for the early universe and the baryon density. I briefly summarize the ongoing HST observations of the interstellar H and D Lyman-alpha absorption for lines of sight to nearby stars and comment on recent reports of extragalactic D/H measurements.

  6. A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

    DOE PAGES

    Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; ...

    2017-12-27

    Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we developmore » a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.« less

  7. A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing

    Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we developmore » a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.« less

  8. Accurate, Streamlined Analysis of mRNA Translation by Sucrose Gradient Fractionation

    PubMed Central

    Aboulhouda, Soufiane; Di Santo, Rachael; Therizols, Gabriel; Weinberg, David

    2017-01-01

    The efficiency with which proteins are produced from mRNA molecules can vary widely across transcripts, cell types, and cellular states. Methods that accurately assay the translational efficiency of mRNAs are critical to gaining a mechanistic understanding of post-transcriptional gene regulation. One way to measure translational efficiency is to determine the number of ribosomes associated with an mRNA molecule, normalized to the length of the coding sequence. The primary method for this analysis of individual mRNAs is sucrose gradient fractionation, which physically separates mRNAs based on the number of bound ribosomes. Here, we describe a streamlined protocol for accurate analysis of mRNA association with ribosomes. Compared to previous protocols, our method incorporates internal controls and improved buffer conditions that together reduce artifacts caused by non-specific mRNA–ribosome interactions. Moreover, our direct-from-fraction qRT-PCR protocol eliminates the need for RNA purification from gradient fractions, which greatly reduces the amount of hands-on time required and facilitates parallel analysis of multiple conditions or gene targets. Additionally, no phenol waste is generated during the procedure. We initially developed the protocol to investigate the translationally repressed state of the HAC1 mRNA in S. cerevisiae, but we also detail adapted procedures for mammalian cell lines and tissues. PMID:29170751

  9. A tractable and accurate electronic structure method for static correlations: The perfect hextuples model

    NASA Astrophysics Data System (ADS)

    Parkhill, John A.; Head-Gordon, Martin

    2010-07-01

    We present the next stage in a hierarchy of local approximations to complete active space self-consistent field (CASSCF) model in an active space of one active orbital per active electron based on the valence orbital-optimized coupled-cluster (VOO-CC) formalism. Following the perfect pairing (PP) model, which is exact for a single electron pair and extensive, and the perfect quadruples (PQ) model, which is exact for two pairs, we introduce the perfect hextuples (PH) model, which is exact for three pairs. PH is an approximation to the VOO-CC method truncated at hextuples containing all correlations between three electron pairs. While VOO-CCDTQ56 requires computational effort scaling with the 14th power of molecular size, PH requires only sixth power effort. Our implementation also introduces some techniques which reduce the scaling to fifth order and has been applied to active spaces roughly twice the size of the CASSCF limit without any symmetry. Because PH explicitly correlates up to six electrons at a time, it can faithfully model the static correlations of molecules with up to triple bonds in a size-consistent fashion and for organic reactions usually reproduces CASSCF with chemical accuracy. The convergence of the PP, PQ, and PH hierarchy is demonstrated on a variety of examples including symmetry breaking in benzene, the Cope rearrangement, the Bergman reaction, and the dissociation of fluorine.

  10. From Spiking Neuron Models to Linear-Nonlinear Models

    PubMed Central

    Ostojic, Srdjan; Brunel, Nicolas

    2011-01-01

    Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates. PMID:21283777

  11. From spiking neuron models to linear-nonlinear models.

    PubMed

    Ostojic, Srdjan; Brunel, Nicolas

    2011-01-20

    Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.

  12. Beating Heart Motion Accurate Prediction Method Based on Interactive Multiple Model: An Information Fusion Approach

    PubMed Central

    Xie, Weihong; Yu, Yang

    2017-01-01

    Robot-assisted motion compensated beating heart surgery has the advantage over the conventional Coronary Artery Bypass Graft (CABG) in terms of reduced trauma to the surrounding structures that leads to shortened recovery time. The severe nonlinear and diverse nature of irregular heart rhythm causes enormous difficulty for the robot to realize the clinic requirements, especially under arrhythmias. In this paper, we propose a fusion prediction framework based on Interactive Multiple Model (IMM) estimator, allowing each model to cover a distinguishing feature of the heart motion in underlying dynamics. We find that, at normal state, the nonlinearity of the heart motion with slow time-variant changing dominates the beating process. When an arrhythmia occurs, the irregularity mode, the fast uncertainties with random patterns become the leading factor of the heart motion. We deal with prediction problem in the case of arrhythmias by estimating the state with two behavior modes which can adaptively “switch” from one to the other. Also, we employed the signal quality index to adaptively determine the switch transition probability in the framework of IMM. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The test results indicate that the new proposed approach reduces prediction errors significantly. PMID:29124062

  13. Beating Heart Motion Accurate Prediction Method Based on Interactive Multiple Model: An Information Fusion Approach.

    PubMed

    Liang, Fan; Xie, Weihong; Yu, Yang

    2017-01-01

    Robot-assisted motion compensated beating heart surgery has the advantage over the conventional Coronary Artery Bypass Graft (CABG) in terms of reduced trauma to the surrounding structures that leads to shortened recovery time. The severe nonlinear and diverse nature of irregular heart rhythm causes enormous difficulty for the robot to realize the clinic requirements, especially under arrhythmias. In this paper, we propose a fusion prediction framework based on Interactive Multiple Model (IMM) estimator, allowing each model to cover a distinguishing feature of the heart motion in underlying dynamics. We find that, at normal state, the nonlinearity of the heart motion with slow time-variant changing dominates the beating process. When an arrhythmia occurs, the irregularity mode, the fast uncertainties with random patterns become the leading factor of the heart motion. We deal with prediction problem in the case of arrhythmias by estimating the state with two behavior modes which can adaptively "switch" from one to the other. Also, we employed the signal quality index to adaptively determine the switch transition probability in the framework of IMM. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The test results indicate that the new proposed approach reduces prediction errors significantly.

  14. Aspirin reduces lipopolysaccharide-induced pulmonary inflammation in human models of ARDS.

    PubMed

    Hamid, U; Krasnodembskaya, A; Fitzgerald, M; Shyamsundar, M; Kissenpfennig, A; Scott, C; Lefrancais, E; Looney, M R; Verghis, R; Scott, J; Simpson, A J; McNamee, J; McAuley, D F; O'Kane, C M

    2017-11-01

    Platelets play an active role in the pathogenesis of acute respiratory distress syndrome (ARDS). Animal and observational studies have shown aspirin's antiplatelet and immunomodulatory effects may be beneficial in ARDS. To test the hypothesis that aspirin reduces inflammation in clinically relevant human models that recapitulate pathophysiological mechanisms implicated in the development of ARDS. Healthy volunteers were randomised to receive placebo or aspirin 75  or 1200 mg (1:1:1) for seven days prior to lipopolysaccharide (LPS) inhalation, in a double-blind, placebo-controlled, allocation-concealed study. Bronchoalveolar lavage (BAL) was performed 6 hours after inhaling 50 µg of LPS. The primary outcome measure was BAL IL-8. Secondary outcome measures included markers of alveolar inflammation (BAL neutrophils, cytokines, neutrophil proteases), alveolar epithelial cell injury, systemic inflammation (neutrophils and plasma C-reactive protein (CRP)) and platelet activation (thromboxane B2, TXB2). Human lungs, perfused and ventilated ex vivo (EVLP) were randomised to placebo or 24 mg aspirin and injured with LPS. BAL was carried out 4 hours later. Inflammation was assessed by BAL differential cell counts and histological changes. In the healthy volunteer (n=33) model, data for the aspirin groups were combined. Aspirin did not reduce BAL IL-8. However, aspirin reduced pulmonary neutrophilia and tissue damaging neutrophil proteases (Matrix Metalloproteinase (MMP)-8/-9), reduced BAL concentrations of tumour necrosis factor α and reduced systemic and pulmonary TXB2. There was no difference between high-dose and low-dose aspirin. In the EVLP model, aspirin reduced BAL neutrophilia and alveolar injury as measured by histological damage. These are the first prospective human data indicating that aspirin inhibits pulmonary neutrophilic inflammation, at both low and high doses. Further clinical studies are indicated to assess the role of aspirin in the

  15. Comparison of Predictive Modeling Methods of Aircraft Landing Speed

    NASA Technical Reports Server (NTRS)

    Diallo, Ousmane H.

    2012-01-01

    Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

  16. Challenges in reducing the computational time of QSTS simulations for distribution system analysis.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Deboever, Jeremiah; Zhang, Xiaochen; Reno, Matthew J.

    The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modelling and impact analysis. Unlike conventional scenario - based studies , quasi - static time - series (QSTS) simulation s can realistically model time - dependent voltage controllers and the diversity of potential impacts that can occur at different times of year . However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1 - second resolution is often required , which could take conventional computers a computational time of 10more » to 120 hours when an actual unbalanced distribution feeder is modeled . This computational burden is a clear l imitation to the adoption of QSTS simulation s in interconnection studies and for determining optimal control solutions for utility operations . Our ongoing research to improve the speed of QSTS simulation has revealed many unique aspects of distribution system modelling and sequential power flow analysis that make fast QSTS a very difficult problem to solve. In this report , the most relevant challenges in reducing the computational time of QSTS simulations are presented: number of power flows to solve, circuit complexity, time dependence between time steps, multiple valid power flow solutions, controllable element interactions, and extensive accurate simulation analysis.« less

  17. Characterization of protein-folding pathways by reduced-space modeling.

    PubMed

    Kmiecik, Sebastian; Kolinski, Andrzej

    2007-07-24

    Ab initio simulations of the folding pathways are currently limited to very small proteins. For larger proteins, some approximations or simplifications in protein models need to be introduced. Protein folding and unfolding are among the basic processes in the cell and are very difficult to characterize in detail by experiment or simulation. Chymotrypsin inhibitor 2 (CI2) and barnase are probably the best characterized experimentally in this respect. For these model systems, initial folding stages were simulated by using CA-CB-side chain (CABS), a reduced-space protein-modeling tool. CABS employs knowledge-based potentials that proved to be very successful in protein structure prediction. With the use of isothermal Monte Carlo (MC) dynamics, initiation sites with a residual structure and weak tertiary interactions were identified. Such structures are essential for the initiation of the folding process through a sequential reduction of the protein conformational space, overcoming the Levinthal paradox in this manner. Furthermore, nucleation sites that initiate a tertiary interactions network were located. The MC simulations correspond perfectly to the results of experimental and theoretical research and bring insights into CI2 folding mechanism: unambiguous sequence of folding events was reported as well as cooperative substructures compatible with those obtained in recent molecular dynamics unfolding studies. The correspondence between the simulation and experiment shows that knowledge-based potentials are not only useful in protein structure predictions but are also capable of reproducing the folding pathways. Thus, the results of this work significantly extend the applicability range of reduced models in the theoretical study of proteins.

  18. Toward accurate and valid estimates of greenhouse gas reductions from bikeway projects.

    DOT National Transportation Integrated Search

    2016-07-31

    We sought to accurately and validly model emissions generating and activities, including changes in traveler behavior and thus GHG : emissions in the wake of bikeway projects. We wanted the results to be applicable to practice and policy in Californi...

  19. Fitting neuron models to spike trains.

    PubMed

    Rossant, Cyrille; Goodman, Dan F M; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K; Brette, Romain

    2011-01-01

    Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input-output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model.

  20. Fitting Neuron Models to Spike Trains

    PubMed Central

    Rossant, Cyrille; Goodman, Dan F. M.; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K.; Brette, Romain

    2011-01-01

    Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input–output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model. PMID:21415925

  1. Jacobian projection reduced-order models for dynamic systems with contact nonlinearities

    NASA Astrophysics Data System (ADS)

    Gastaldi, Chiara; Zucca, Stefano; Epureanu, Bogdan I.

    2018-02-01

    In structural dynamics, the prediction of the response of systems with localized nonlinearities, such as friction dampers, is of particular interest. This task becomes especially cumbersome when high-resolution finite element models are used. While state-of-the-art techniques such as Craig-Bampton component mode synthesis are employed to generate reduced order models, the interface (nonlinear) degrees of freedom must still be solved in-full. For this reason, a new generation of specialized techniques capable of reducing linear and nonlinear degrees of freedom alike is emerging. This paper proposes a new technique that exploits spatial correlations in the dynamics to compute a reduction basis. The basis is composed of a set of vectors obtained using the Jacobian of partial derivatives of the contact forces with respect to nodal displacements. These basis vectors correspond to specifically chosen boundary conditions at the contacts over one cycle of vibration. The technique is shown to be effective in the reduction of several models studied using multiple harmonics with a coupled static solution. In addition, this paper addresses another challenge common to all reduction techniques: it presents and validates a novel a posteriori error estimate capable of evaluating the quality of the reduced-order solution without involving a comparison with the full-order solution.

  2. SPARC: MASS MODELS FOR 175 DISK GALAXIES WITH SPITZER PHOTOMETRY AND ACCURATE ROTATION CURVES

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lelli, Federico; McGaugh, Stacy S.; Schombert, James M., E-mail: federico.lelli@case.edu

    2016-12-01

    We introduce SPARC ( Spitzer Photometry and Accurate Rotation Curves): a sample of 175 nearby galaxies with new surface photometry at 3.6  μ m and high-quality rotation curves from previous H i/H α studies. SPARC spans a broad range of morphologies (S0 to Irr), luminosities (∼5 dex), and surface brightnesses (∼4 dex). We derive [3.6] surface photometry and study structural relations of stellar and gas disks. We find that both the stellar mass–H i mass relation and the stellar radius–H i radius relation have significant intrinsic scatter, while the H i   mass–radius relation is extremely tight. We build detailedmore » mass models and quantify the ratio of baryonic to observed velocity ( V {sub bar}/ V {sub obs}) for different characteristic radii and values of the stellar mass-to-light ratio (ϒ{sub ⋆}) at [3.6]. Assuming ϒ{sub ⋆} ≃ 0.5 M {sub ⊙}/ L {sub ⊙} (as suggested by stellar population models), we find that (i) the gas fraction linearly correlates with total luminosity; (ii) the transition from star-dominated to gas-dominated galaxies roughly corresponds to the transition from spiral galaxies to dwarf irregulars, in line with density wave theory; and (iii)  V {sub bar}/ V {sub obs} varies with luminosity and surface brightness: high-mass, high-surface-brightness galaxies are nearly maximal, while low-mass, low-surface-brightness galaxies are submaximal. These basic properties are lost for low values of ϒ{sub ⋆} ≃ 0.2 M {sub ⊙}/ L {sub ⊙} as suggested by the DiskMass survey. The mean maximum-disk limit in bright galaxies is ϒ{sub ⋆} ≃ 0.7 M {sub ⊙}/ L {sub ⊙} at [3.6]. The SPARC data are publicly available and represent an ideal test bed for models of galaxy formation.« less

  3. Can Raters with Reduced Job Descriptive Information Provide Accurate Position Analysis Questionnaire (PAQ) Ratings?

    ERIC Educational Resources Information Center

    Friedman, Lee; Harvey, Robert J.

    1986-01-01

    Job-naive raters provided with job descriptive information made Position Analysis Questionnaire (PAQ) ratings which were validated against ratings of job analysts who were also job content experts. None of the reduced job descriptive information conditions enabled job-naive raters to obtain either acceptable levels of convergent validity with…

  4. Coarse-Graining Polymer Field Theory for Fast and Accurate Simulations of Directed Self-Assembly

    NASA Astrophysics Data System (ADS)

    Liu, Jimmy; Delaney, Kris; Fredrickson, Glenn

    To design effective manufacturing processes using polymer directed self-assembly (DSA), the semiconductor industry benefits greatly from having a complete picture of stable and defective polymer configurations. Field-theoretic simulations are an effective way to study these configurations and predict defect populations. Self-consistent field theory (SCFT) is a particularly successful theory for studies of DSA. Although other models exist that are faster to simulate, these models are phenomenological or derived through asymptotic approximations, often leading to a loss of accuracy relative to SCFT. In this study, we employ our recently-developed method to produce an accurate coarse-grained field theory for diblock copolymers. The method uses a force- and stress-matching strategy to map output from SCFT simulations into parameters for an optimized phase field model. This optimized phase field model is just as fast as existing phenomenological phase field models, but makes more accurate predictions of polymer self-assembly, both in bulk and in confined systems. We study the performance of this model under various conditions, including its predictions of domain spacing, morphology and defect formation energies. Samsung Electronics.

  5. Startle reduces recall of a recently learned internal model.

    PubMed

    Wright, Zachary; Patton, James L; Ravichandran, Venn

    2011-01-01

    Recent work has shown that preplanned motor programs are released early from subcortical areas by the using a startling acoustic stimulus (SAS). Our question is whether this response might also contain a recently learned internal model, which draws on experience to predict and compensate for expected perturbations in a feedforward manner. Studies of adaptation to robotic forces have shown some evidence of this, but were potentially confounded by cocontraction caused by startle. We performed a new adaptation experiment using a visually distorted field that could not be confounded by cocontraction. We found that in all subjects that exhibited startle, the startle stimulus (1) reduced performance of the recently learned task (2) reduced after-effect magnitudes. Because startle reduced but did not eliminate the recall of learned control, we suggest that multiple neural centers (cortical and subcortical) are involved in such learning and adaptation, which can impact training areas such as piloting, teleoperation, sports, and rehabilitation. © 2011 IEEE

  6. A reduced order, test verified component mode synthesis approach for system modeling applications

    NASA Astrophysics Data System (ADS)

    Butland, Adam; Avitabile, Peter

    2010-05-01

    Component mode synthesis (CMS) is a very common approach used for the generation of large system models. In general, these modeling techniques can be separated into two categories: those utilizing a combination of constraint modes and fixed interface normal modes and those based on a combination of free interface normal modes and residual flexibility terms. The major limitation of the methods utilizing constraint modes and fixed interface normal modes is the inability to easily obtain the required information from testing; the result of this limitation is that constraint mode-based techniques are primarily used with numerical models. An alternate approach is proposed which utilizes frequency and shape information acquired from modal testing to update reduced order finite element models using exact analytical model improvement techniques. The connection degrees of freedom are then rigidly constrained in the test verified, reduced order model to provide the boundary conditions necessary for constraint modes and fixed interface normal modes. The CMS approach is then used with this test verified, reduced order model to generate the system model for further analysis. A laboratory structure is used to show the application of the technique with both numerical and simulated experimental components to describe the system and validate the proposed approach. Actual test data is then used in the approach proposed. Due to typical measurement data contaminants that are always included in any test, the measured data is further processed to remove contaminants and is then used in the proposed approach. The final case using improved data with the reduced order, test verified components is shown to produce very acceptable results from the Craig-Bampton component mode synthesis approach. Use of the technique with its strengths and weaknesses are discussed.

  7. Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters: Preprint

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Johnson, Brian B; Purba, Victor; Jafarpour, Saber

    Given that next-generation infrastructures will contain large numbers of grid-connected inverters and these interfaces will be satisfying a growing fraction of system load, it is imperative to analyze the impacts of power electronics on such systems. However, since each inverter model has a relatively large number of dynamic states, it would be impractical to execute complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the pointmore » of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. That is, we show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as an individual inverter in the paralleled system. Numerical simulations validate the reduced-order models.« less

  8. Accurate classical short-range forces for the study of collision cascades in Fe–Ni–Cr

    DOE PAGES

    Béland, Laurent Karim; Tamm, Artur; Mu, Sai; ...

    2017-05-10

    The predictive power of a classical molecular dynamics simulation is largely determined by the physical validity of its underlying empirical potential. In the case of high-energy collision cascades, it was recently shown that correctly modeling interactions at short distances is necessary to accurately predict primary damage production. An ab initio based framework is introduced for modifying an existing embedded-atom method FeNiCr potential to handle these short-range interactions. Density functional theory is used to calculate the energetics of two atoms approaching each other, embedded in the alloy, and to calculate the equation of state of the alloy as it is compressed.more » The pairwise terms and the embedding terms of the potential are modi ed in accordance with the ab initio results. Using this reparametrized potential, collision cascades are performed in Ni 50Fe 50, Ni 80Cr 20 and Ni 33Fe 33Cr 33. The simulations reveal that alloying Ni and NiCr to Fe reduces primary damage production, in agreement with some previous calculations. Alloying Ni and NiFe to Cr does not reduce primary damage production, in contradiction with previous calculations.« less

  9. Validation of a reduced-order jet model for subsonic and underexpanded hydrogen jets

    DOE PAGES

    Li, Xuefang; Hecht, Ethan S.; Christopher, David M.

    2016-01-01

    Much effort has been made to model hydrogen releases from leaks during potential failures of hydrogen storage systems. A reduced-order jet model can be used to quickly characterize these flows, with low computational cost. Notional nozzle models are often used to avoid modeling the complex shock structures produced by the underexpanded jets by determining an “effective” source to produce the observed downstream trends. In our work, the mean hydrogen concentration fields were measured in a series of subsonic and underexpanded jets using a planar laser Rayleigh scattering system. Furthermore, we compared the experimental data to a reduced order jet modelmore » for subsonic flows and a notional nozzle model coupled to the jet model for underexpanded jets. The values of some key model parameters were determined by comparisons with the experimental data. Finally, the coupled model was also validated against hydrogen concentrations measurements for 100 and 200 bar hydrogen jets with the predictions agreeing well with data in the literature.« less

  10. Tools for Accurate and Efficient Analysis of Complex Evolutionary Mechanisms in Microbial Genomes. Final Report

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Nakhleh, Luay

    I proposed to develop computationally efficient tools for accurate detection and reconstruction of microbes' complex evolutionary mechanisms, thus enabling rapid and accurate annotation, analysis and understanding of their genomes. To achieve this goal, I proposed to address three aspects. (1) Mathematical modeling. A major challenge facing the accurate detection of HGT is that of distinguishing between these two events on the one hand and other events that have similar "effects." I proposed to develop a novel mathematical approach for distinguishing among these events. Further, I proposed to develop a set of novel optimization criteria for the evolutionary analysis of microbialmore » genomes in the presence of these complex evolutionary events. (2) Algorithm design. In this aspect of the project, I proposed to develop an array of e cient and accurate algorithms for analyzing microbial genomes based on the formulated optimization criteria. Further, I proposed to test the viability of the criteria and the accuracy of the algorithms in an experimental setting using both synthetic as well as biological data. (3) Software development. I proposed the nal outcome to be a suite of software tools which implements the mathematical models as well as the algorithms developed.« less

  11. Coral reefs reduce tsunami impact in model simulations

    NASA Astrophysics Data System (ADS)

    Kunkel, Catherine M.; Hallberg, Robert W.; Oppenheimer, Michael

    2006-12-01

    Significant buffering of the impact of tsunamis by coral reefs is suggested by limited observations and some anecdotal reports, particularly following the 2004 Indian Ocean tsunami. Here we simulate tsunami run-up on idealized topographies in one and two dimensions using a nonlinear shallow water model and show that a sufficiently wide barrier reef within a meter or two of the surface reduces run-up on land on the order of 50%. We studied topographies representative of volcanic islands (islands with no continental shelf) but our conclusions may pertain to other topographies. Effectiveness depends on the amplitude and wavelength of the incident tsunami, as well as the geometry and health of the reef and the offshore distance of the reef. Reducing the threat to reefs from anthropogenic nutrients, sedimentation, fishing practices, channel-building, and global warming would help to protect some islands against tsunamis.

  12. Improving Empirical Magnetic Field Models by Fitting to In Situ Data Using an Optimized Parameter Approach

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Brito, Thiago V.; Morley, Steven K.

    A method for comparing and optimizing the accuracy of empirical magnetic field models using in situ magnetic field measurements is presented in this paper. The optimization method minimizes a cost function—τ—that explicitly includes both a magnitude and an angular term. A time span of 21 days, including periods of mild and intense geomagnetic activity, was used for this analysis. A comparison between five magnetic field models (T96, T01S, T02, TS04, and TS07) widely used by the community demonstrated that the T02 model was, on average, the most accurate when driven by the standard model input parameters. The optimization procedure, performedmore » in all models except TS07, generally improved the results when compared to unoptimized versions of the models. Additionally, using more satellites in the optimization procedure produces more accurate results. This procedure reduces the number of large errors in the model, that is, it reduces the number of outliers in the error distribution. The TS04 model shows the most accurate results after the optimization in terms of both the magnitude and direction, when using at least six satellites in the fitting. It gave a smaller error than its unoptimized counterpart 57.3% of the time and outperformed the best unoptimized model (T02) 56.2% of the time. Its median percentage error in |B| was reduced from 4.54% to 3.84%. Finally, the difference among the models analyzed, when compared in terms of the median of the error distributions, is not very large. However, the unoptimized models can have very large errors, which are much reduced after the optimization.« less

  13. Improving Empirical Magnetic Field Models by Fitting to In Situ Data Using an Optimized Parameter Approach

    DOE PAGES

    Brito, Thiago V.; Morley, Steven K.

    2017-10-25

    A method for comparing and optimizing the accuracy of empirical magnetic field models using in situ magnetic field measurements is presented in this paper. The optimization method minimizes a cost function—τ—that explicitly includes both a magnitude and an angular term. A time span of 21 days, including periods of mild and intense geomagnetic activity, was used for this analysis. A comparison between five magnetic field models (T96, T01S, T02, TS04, and TS07) widely used by the community demonstrated that the T02 model was, on average, the most accurate when driven by the standard model input parameters. The optimization procedure, performedmore » in all models except TS07, generally improved the results when compared to unoptimized versions of the models. Additionally, using more satellites in the optimization procedure produces more accurate results. This procedure reduces the number of large errors in the model, that is, it reduces the number of outliers in the error distribution. The TS04 model shows the most accurate results after the optimization in terms of both the magnitude and direction, when using at least six satellites in the fitting. It gave a smaller error than its unoptimized counterpart 57.3% of the time and outperformed the best unoptimized model (T02) 56.2% of the time. Its median percentage error in |B| was reduced from 4.54% to 3.84%. Finally, the difference among the models analyzed, when compared in terms of the median of the error distributions, is not very large. However, the unoptimized models can have very large errors, which are much reduced after the optimization.« less

  14. Development of a High Resolution 3D Infant Stomach Model for Surgical Planning

    NASA Astrophysics Data System (ADS)

    Chaudry, Qaiser; Raza, S. Hussain; Lee, Jeonggyu; Xu, Yan; Wulkan, Mark; Wang, May D.

    Medical surgical procedures have not changed much during the past century due to the lack of accurate low-cost workbench for testing any new improvement. The increasingly cheaper and powerful computer technologies have made computer-based surgery planning and training feasible. In our work, we have developed an accurate 3D stomach model, which aims to improve the surgical procedure that treats the infant pediatric and neonatal gastro-esophageal reflux disease (GERD). We generate the 3-D infant stomach model based on in vivo computer tomography (CT) scans of an infant. CT is a widely used clinical imaging modality that is cheap, but with low spatial resolution. To improve the model accuracy, we use the high resolution Visible Human Project (VHP) in model building. Next, we add soft muscle material properties to make the 3D model deformable. Then we use virtual reality techniques such as haptic devices to make the 3D stomach model deform upon touching force. This accurate 3D stomach model provides a workbench for testing new GERD treatment surgical procedures. It has the potential to reduce or eliminate the extensive cost associated with animal testing when improving any surgical procedure, and ultimately, to reduce the risk associated with infant GERD surgery.

  15. In pursuit of an accurate spatial and temporal model of biomolecules at the atomistic level: a perspective on computer simulation.

    PubMed

    Gray, Alan; Harlen, Oliver G; Harris, Sarah A; Khalid, Syma; Leung, Yuk Ming; Lonsdale, Richard; Mulholland, Adrian J; Pearson, Arwen R; Read, Daniel J; Richardson, Robin A

    2015-01-01

    Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.

  16. TOPICA: an accurate and efficient numerical tool for analysis and design of ICRF antennas

    NASA Astrophysics Data System (ADS)

    Lancellotti, V.; Milanesio, D.; Maggiora, R.; Vecchi, G.; Kyrytsya, V.

    2006-07-01

    The demand for a predictive tool to help in designing ion-cyclotron radio frequency (ICRF) antenna systems for today's fusion experiments has driven the development of codes such as ICANT, RANT3D, and the early development of TOPICA (TOrino Polytechnic Ion Cyclotron Antenna) code. This paper describes the substantive evolution of TOPICA formulation and implementation that presently allow it to handle the actual geometry of ICRF antennas (with curved, solid straps, a general-shape housing, Faraday screen, etc) as well as an accurate plasma description, accounting for density and temperature profiles and finite Larmor radius effects. The antenna is assumed to be housed in a recess-like enclosure. Both goals have been attained by formally separating the problem into two parts: the vacuum region around the antenna and the plasma region inside the toroidal chamber. Field continuity and boundary conditions allow formulating of a set of two coupled integral equations for the unknown equivalent (current) sources; then the equations are reduced to a linear system by a method of moments solution scheme employing 2D finite elements defined over a 3D non-planar surface triangular-cell mesh. In the vacuum region calculations are done in the spatial (configuration) domain, whereas in the plasma region a spectral (wavenumber) representation of fields and currents is adopted, thus permitting a description of the plasma by a surface impedance matrix. Owing to this approach, any plasma model can be used in principle, and at present the FELICE code has been employed. The natural outcomes of TOPICA are the induced currents on the conductors (antenna, housing, etc) and the electric field in front of the plasma, whence the antenna circuit parameters (impedance/scattering matrices), the radiated power and the fields (at locations other than the chamber aperture) are then obtained. An accurate model of the feeding coaxial lines is also included. The theoretical model and its TOPICA

  17. Simplified biased random walk model for RecA-protein-mediated homology recognition offers rapid and accurate self-assembly of long linear arrays of binding sites

    NASA Astrophysics Data System (ADS)

    Kates-Harbeck, Julian; Tilloy, Antoine; Prentiss, Mara

    2013-07-01

    Inspired by RecA-protein-based homology recognition, we consider the pairing of two long linear arrays of binding sites. We propose a fully reversible, physically realizable biased random walk model for rapid and accurate self-assembly due to the spontaneous pairing of matching binding sites, where the statistics of the searched sample are included. In the model, there are two bound conformations, and the free energy for each conformation is a weakly nonlinear function of the number of contiguous matched bound sites.

  18. An Adaptive QSE-reduced Nuclear Reaction Network for Silicon Burning

    NASA Astrophysics Data System (ADS)

    Parete-Koon, Suzanne; Hix, W.; Thielemann, F.

    2008-03-01

    The nuclei of the "iron peak" are formed in massive stars shortly before core collapse and during their supernova outbursts as well as during thermonuclear supernovae. Complete and incomplete silicon burning during these events are responsible for the production of a wide range of nuclei with atomic mass numbers from 28 to 64. Because of the large number of nuclei involved, accurate modeling of silicon burning is computationally expensive. However, examination of the physics of silicon burning has revealed that the nuclear evolution is dominated by large groups of nuclei in mutual equilibrium. We present an improvement on our hybrid equilibrium-network scheme which takes advantage of this quasi-equilibrium in order to reduce the number of independent variables calculated. Because the size and membership of these groups vary as the temperature, density and electron faction change, achieving maximal efficiency requires dynamic adjustment of group number and membership. Toward this end, we are implementing a scheme beginning with a single QSE (NSE) group at appropriately high temperature, then progressing through 2, 3 and 4 group stages (with successively more independent variables) as temperature declines. This combination allows accurate prediction of the nuclear abundance evolution, deleptonization and energy generation at a further reduced computational cost when compared to a conventional nuclear reaction network or our previous 3 fixed group QSE-reduced network. During silicon burning, the resultant QSE-reduced network is up to 20 times faster than the full network it replaces without significant loss of accuracy. These reductions in computational cost and the number of species evolved make QSE-reduced networks well suited for inclusion within hydrodynamic simulations, particularly in multi-dimensional applications. This work has been supported by the National Science Foundation, by the Department of Energy's Scientic Discovery through Advanced Computing

  19. Image charge models for accurate construction of the electrostatic self-energy of 3D layered nanostructure devices.

    PubMed

    Barker, John R; Martinez, Antonio

    2018-04-04

    Efficient analytical image charge models are derived for the full spatial variation of the electrostatic self-energy of electrons in semiconductor nanostructures that arises from dielectric mismatch using semi-classical analysis. The methodology provides a fast, compact and physically transparent computation for advanced device modeling. The underlying semi-classical model for the self-energy has been established and validated during recent years and depends on a slight modification of the macroscopic static dielectric constants for individual homogeneous dielectric regions. The model has been validated for point charges as close as one interatomic spacing to a sharp interface. A brief introduction to image charge methodology is followed by a discussion and demonstration of the traditional failure of the methodology to derive the electrostatic potential at arbitrary distances from a source charge. However, the self-energy involves the local limit of the difference between the electrostatic Green functions for the full dielectric heterostructure and the homogeneous equivalent. It is shown that high convergence may be achieved for the image charge method for this local limit. A simple re-normalisation technique is introduced to reduce the number of image terms to a minimum. A number of progressively complex 3D models are evaluated analytically and compared with high precision numerical computations. Accuracies of 1% are demonstrated. Introducing a simple technique for modeling the transition of the self-energy between disparate dielectric structures we generate an analytical model that describes the self-energy as a function of position within the source, drain and gated channel of a silicon wrap round gate field effect transistor on a scale of a few nanometers cross-section. At such scales the self-energies become large (typically up to ~100 meV) close to the interfaces as well as along the channel. The screening of a gated structure is shown to reduce the self

  20. Image charge models for accurate construction of the electrostatic self-energy of 3D layered nanostructure devices

    NASA Astrophysics Data System (ADS)

    Barker, John R.; Martinez, Antonio

    2018-04-01

    Efficient analytical image charge models are derived for the full spatial variation of the electrostatic self-energy of electrons in semiconductor nanostructures that arises from dielectric mismatch using semi-classical analysis. The methodology provides a fast, compact and physically transparent computation for advanced device modeling. The underlying semi-classical model for the self-energy has been established and validated during recent years and depends on a slight modification of the macroscopic static dielectric constants for individual homogeneous dielectric regions. The model has been validated for point charges as close as one interatomic spacing to a sharp interface. A brief introduction to image charge methodology is followed by a discussion and demonstration of the traditional failure of the methodology to derive the electrostatic potential at arbitrary distances from a source charge. However, the self-energy involves the local limit of the difference between the electrostatic Green functions for the full dielectric heterostructure and the homogeneous equivalent. It is shown that high convergence may be achieved for the image charge method for this local limit. A simple re-normalisation technique is introduced to reduce the number of image terms to a minimum. A number of progressively complex 3D models are evaluated analytically and compared with high precision numerical computations. Accuracies of 1% are demonstrated. Introducing a simple technique for modeling the transition of the self-energy between disparate dielectric structures we generate an analytical model that describes the self-energy as a function of position within the source, drain and gated channel of a silicon wrap round gate field effect transistor on a scale of a few nanometers cross-section. At such scales the self-energies become large (typically up to ~100 meV) close to the interfaces as well as along the channel. The screening of a gated structure is shown to reduce the self