accurately predict experimental: Topics by Science.gov

Sample records for accurately predict experimental

Convergence in parameters and predictions using computational experimental design.

PubMed

Hagen, David R; White, Jacob K; Tidor, Bruce

2013-08-06

Typically, biological models fitted to experimental data suffer from significant parameter uncertainty, which can lead to inaccurate or uncertain predictions. One school of thought holds that accurate estimation of the true parameters of a biological system is inherently problematic. Recent work, however, suggests that optimal experimental design techniques can select sets of experiments whose members probe complementary aspects of a biochemical network that together can account for its full behaviour. Here, we implemented an experimental design approach for selecting sets of experiments that constrain parameter uncertainty. We demonstrated with a model of the epidermal growth factor-nerve growth factor pathway that, after synthetically performing a handful of optimal experiments, the uncertainty in all 48 parameters converged below 10 per cent. Furthermore, the fitted parameters converged to their true values with a small error consistent with the residual uncertainty. When untested experimental conditions were simulated with the fitted models, the predicted species concentrations converged to their true values with errors that were consistent with the residual uncertainty. This paper suggests that accurate parameter estimation is achievable with complementary experiments specifically designed for the task, and that the resulting parametrized models are capable of accurate predictions.
Experimental evaluation of radiosity for room sound-field prediction.

PubMed

Hodgson, Murray; Nosal, Eva-Marie

2006-08-01

An acoustical radiosity model was evaluated for how it performs in predicting real room sound fields. This was done by comparing radiosity predictions with experimental results for three existing rooms--a squash court, a classroom, and an office. Radiosity predictions were also compared with those by ray tracing--a "reference" prediction model--for both specular and diffuse surface reflection. Comparisons were made for detailed and discretized echograms, sound-decay curves, sound-propagation curves, and the variations with frequency of four room-acoustical parameters--EDT, RT, D50, and C80. In general, radiosity and diffuse ray tracing gave very similar predictions. Predictions by specular ray tracing were often very different. Radiosity agreed well with experiment in some cases, less well in others. Definitive conclusions regarding the accuracy with which the rooms were modeled, or the accuracy of the radiosity approach, were difficult to draw. The results suggest that radiosity predicts room sound fields with some accuracy, at least as well as diffuse ray tracing and, in general, better than specular ray tracing. The predictions of detailed echograms are less accurate, those of derived room-acoustical parameters more accurate. The results underline the need to develop experimental methods for accurately characterizing the absorptive and reflective characteristics of room surfaces, possible including phase.
A Combined Experimental and Computational Study on Selected Physical Properties of Aminosilicones

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

Perry, RJ; Genovese, SE; Farnum, RL

2014-01-29

A number of physical properties of aminosilicones have been determined experimentally and predicted computationally. It was found that COSMO-RS predicted the densities of the materials under study to within about 4% of the experimentally determined values. Vapor pressure measurements were performed, and all of the aminosilicones of interest were found to be significantly less volatile than the benchmark MEA material. COSMO-RS was reasonably accurate for predicting the vapor pressures for aminosilicones that were thermally stable. The heat capacities of all aminosilicones tested were between 2.0 and 2.3 J/(g.degrees C); again substantially lower than a benchmark 30% aqueous MEA solution. Surfacemore » energies for the aminosilicones were found to be 23.3-28.3 dyne/cm and were accurately predicted using the parachor method.« less
Fractional viscoelasticity in fractal and non-fractal media: Theory, experimental validation, and uncertainty analysis

NASA Astrophysics Data System (ADS)

Mashayekhi, Somayeh; Miles, Paul; Hussaini, M. Yousuff; Oates, William S.

2018-02-01

In this paper, fractional and non-fractional viscoelastic models for elastomeric materials are derived and analyzed in comparison to experimental results. The viscoelastic models are derived by expanding thermodynamic balance equations for both fractal and non-fractal media. The order of the fractional time derivative is shown to strongly affect the accuracy of the viscoelastic constitutive predictions. Model validation uses experimental data describing viscoelasticity of the dielectric elastomer Very High Bond (VHB) 4910. Since these materials are known for their broad applications in smart structures, it is important to characterize and accurately predict their behavior across a large range of time scales. Whereas integer order viscoelastic models can yield reasonable agreement with data, the model parameters often lack robustness in prediction at different deformation rates. Alternatively, fractional order models of viscoelasticity provide an alternative framework to more accurately quantify complex rate-dependent behavior. Prior research that has considered fractional order viscoelasticity lacks experimental validation and contains limited links between viscoelastic theory and fractional order derivatives. To address these issues, we use fractional order operators to experimentally validate fractional and non-fractional viscoelastic models in elastomeric solids using Bayesian uncertainty quantification. The fractional order model is found to be advantageous as predictions are significantly more accurate than integer order viscoelastic models for deformation rates spanning four orders of magnitude.
Evaluation of Turbulence-Model Performance as Applied to Jet-Noise Prediction

NASA Technical Reports Server (NTRS)

Woodruff, S. L.; Seiner, J. M.; Hussaini, M. Y.; Erlebacher, G.

1998-01-01

The accurate prediction of jet noise is possible only if the jet flow field can be predicted accurately. Predictions for the mean velocity and turbulence quantities in the jet flowfield are typically the product of a Reynolds-averaged Navier-Stokes solver coupled with a turbulence model. To evaluate the effectiveness of solvers and turbulence models in predicting those quantities most important to jet noise prediction, two CFD codes and several turbulence models were applied to a jet configuration over a range of jet temperatures for which experimental data is available.
Using radiance predicted by the P3 approximation in a spherical geometry to predict tissue optical properties

NASA Astrophysics Data System (ADS)

Dickey, Dwayne J.; Moore, Ronald B.; Tulip, John

2001-01-01

For photodynamic therapy of solid tumors, such as prostatic carcinoma, to be achieved, an accurate model to predict tissue parameters and light dose must be found. Presently, most analytical light dosimetry models are fluence based and are not clinically viable for tissue characterization. Other methods of predicting optical properties, such as Monet Carlo, are accurate but far too time consuming for clinical application. However, radiance predicted by the P3-Approximation, an anaylitical solution to the transport equation, may be a viable and accurate alternative. The P3-Approximation accurately predicts optical parameters in intralipid/methylene blue based phantoms in a spherical geometry. The optical parameters furnished by the radiance, when introduced into fluence predicted by both P3- Approximation and Grosjean Theory, correlate well with experimental data. The P3-Approximation also predicts the optical properties of prostate tissue, agreeing with documented optical parameters. The P3-Approximation could be the clinical tool necessary to facilitate PDT of solid tumors because of the limited number of invasive measurements required and the speed in which accurate calculations can be performed.
Accurate thermoelastic tensor and acoustic velocities of NaCl

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

Marcondes, Michel L., E-mail: michel@if.usp.br; Chemical Engineering and Material Science, University of Minnesota, Minneapolis, 55455; Shukla, Gaurav, E-mail: shukla@physics.umn.edu

Despite the importance of thermoelastic properties of minerals in geology and geophysics, their measurement at high pressures and temperatures are still challenging. Thus, ab initio calculations are an essential tool for predicting these properties at extreme conditions. Owing to the approximate description of the exchange-correlation energy, approximations used in calculations of vibrational effects, and numerical/methodological approximations, these methods produce systematic deviations. Hybrid schemes combining experimental data and theoretical results have emerged as a way to reconcile available information and offer more reliable predictions at experimentally inaccessible thermodynamics conditions. Here we introduce a method to improve the calculated thermoelastic tensor bymore » using highly accurate thermal equation of state (EoS). The corrective scheme is general, applicable to crystalline solids with any symmetry, and can produce accurate results at conditions where experimental data may not exist. We apply it to rock-salt-type NaCl, a material whose structural properties have been challenging to describe accurately by standard ab initio methods and whose acoustic/seismic properties are important for the gas and oil industry.« less
Experimental and numerical study of physiological responses in hot environments.

PubMed

Yang, Jie; Weng, Wenguo; Zhang, Baoting

2014-10-01

This paper proposed a multi-node human thermal model to predict human thermal responses in hot environments. The model was extended based on the Tanabe's work by considering the effects of high temperature on heat production, blood flow rate, and heat exchange coefficients. Five healthy men dressed in shorts were exposed in thermal neutral (29 °C) and high temperature (45 °C) environments. The rectal temperatures and skin temperatures of seven human body segments were continuously measured during the experiment. Validation of this model was conducted with experimental data. The results showed that the current model could accurately predict the skin and core temperatures in terms of the tendency and absolute values. In the human body segments expect calf and trunk, the temperature differences between the experimental data and the predicted results in high temperature environment were smaller than those in the thermally neutral environment conditions. The extended model was proved to be capable of predicting accurately human physiological responses in hot environments. Copyright © 2014 Elsevier Ltd. All rights reserved.
Molecular determinants of blood-brain barrier permeation.

PubMed

Geldenhuys, Werner J; Mohammad, Afroz S; Adkins, Chris E; Lockman, Paul R

2015-01-01

The blood-brain barrier (BBB) is a microvascular unit which selectively regulates the permeability of drugs to the brain. With the rise in CNS drug targets and diseases, there is a need to be able to accurately predict a priori which compounds in a company database should be pursued for favorable properties. In this review, we will explore the different computational tools available today, as well as underpin these to the experimental methods used to determine BBB permeability. These include in vitro models and the in vivo models that yield the dataset we use to generate predictive models. Understanding of how these models were experimentally derived determines our accurate and predicted use for determining a balance between activity and BBB distribution.
Molecular determinants of blood–brain barrier permeation

PubMed Central

Geldenhuys, Werner J; Mohammad, Afroz S; Adkins, Chris E; Lockman, Paul R

2015-01-01

The blood–brain barrier (BBB) is a microvascular unit which selectively regulates the permeability of drugs to the brain. With the rise in CNS drug targets and diseases, there is a need to be able to accurately predict a priori which compounds in a company database should be pursued for favorable properties. In this review, we will explore the different computational tools available today, as well as underpin these to the experimental methods used to determine BBB permeability. These include in vitro models and the in vivo models that yield the dataset we use to generate predictive models. Understanding of how these models were experimentally derived determines our accurate and predicted use for determining a balance between activity and BBB distribution. PMID:26305616
Remaining dischargeable time prediction for lithium-ion batteries using unscented Kalman filter

NASA Astrophysics Data System (ADS)

Dong, Guangzhong; Wei, Jingwen; Chen, Zonghai; Sun, Han; Yu, Xiaowei

2017-10-01

To overcome the range anxiety, one of the important strategies is to accurately predict the range or dischargeable time of the battery system. To accurately predict the remaining dischargeable time (RDT) of a battery, a RDT prediction framework based on accurate battery modeling and state estimation is presented in this paper. Firstly, a simplified linearized equivalent-circuit-model is developed to simulate the dynamic characteristics of a battery. Then, an online recursive least-square-algorithm method and unscented-Kalman-filter are employed to estimate the system matrices and SOC at every prediction point. Besides, a discrete wavelet transform technique is employed to capture the statistical information of past dynamics of input currents, which are utilized to predict the future battery currents. Finally, the RDT can be predicted based on the battery model, SOC estimation results and predicted future battery currents. The performance of the proposed methodology has been verified by a lithium-ion battery cell. Experimental results indicate that the proposed method can provide an accurate SOC and parameter estimation and the predicted RDT can solve the range anxiety issues.
Aggregation Trade Offs in Family Based Recommendations

NASA Astrophysics Data System (ADS)

Berkovsky, Shlomo; Freyne, Jill; Coombe, Mac

Personalized information access tools are frequently based on collaborative filtering recommendation algorithms. Collaborative filtering recommender systems typically suffer from a data sparsity problem, where systems do not have sufficient user data to generate accurate and reliable predictions. Prior research suggested using group-based user data in the collaborative filtering recommendation process to generate group-based predictions and partially resolve the sparsity problem. Although group recommendations are less accurate than personalized recommendations, they are more accurate than general non-personalized recommendations, which are the natural fall back when personalized recommendations cannot be generated. In this work we present initial results of a study that exploits the browsing logs of real families of users gathered in an eHealth portal. The browsing logs allowed us to experimentally compare the accuracy of two group-based recommendation strategies: aggregated group models and aggregated predictions. Our results showed that aggregating individual models into group models resulted in more accurate predictions than aggregating individual predictions into group predictions.
A Physics-Based Engineering Methodology for Calculating Soft Error Rates of Bulk CMOS and SiGe Heterojunction Bipolar Transistor Integrated Circuits

NASA Astrophysics Data System (ADS)

Fulkerson, David E.

2010-02-01

This paper describes a new methodology for characterizing the electrical behavior and soft error rate (SER) of CMOS and SiGe HBT integrated circuits that are struck by ions. A typical engineering design problem is to calculate the SER of a critical path that commonly includes several circuits such as an input buffer, several logic gates, logic storage, clock tree circuitry, and an output buffer. Using multiple 3D TCAD simulations to solve this problem is too costly and time-consuming for general engineering use. The new and simple methodology handles the problem with ease by simple SPICE simulations. The methodology accurately predicts the measured threshold linear energy transfer (LET) of a bulk CMOS SRAM. It solves for circuit currents and voltage spikes that are close to those predicted by expensive 3D TCAD simulations. It accurately predicts the measured event cross-section vs. LET curve of an experimental SiGe HBT flip-flop. The experimental cross section vs. frequency behavior and other subtle effects are also accurately predicted.
A Comparison of Classical Force-Fields for Molecular Dynamics Simulations of Lubricants

PubMed Central

Ewen, James P.; Gattinoni, Chiara; Thakkar, Foram M.; Morgan, Neal; Spikes, Hugh A.; Dini, Daniele

2016-01-01

For the successful development and application of lubricants, a full understanding of their complex nanoscale behavior under a wide range of external conditions is required, but this is difficult to obtain experimentally. Nonequilibrium molecular dynamics (NEMD) simulations can be used to yield unique insights into the atomic-scale structure and friction of lubricants and additives; however, the accuracy of the results depend on the chosen force-field. In this study, we demonstrate that the use of an accurate, all-atom force-field is critical in order to; (i) accurately predict important properties of long-chain, linear molecules; and (ii) reproduce experimental friction behavior of multi-component tribological systems. In particular, we focus on n-hexadecane, an important model lubricant with a wide range of industrial applications. Moreover, simulating conditions common in tribological systems, i.e., high temperatures and pressures (HTHP), allows the limits of the selected force-fields to be tested. In the first section, a large number of united-atom and all-atom force-fields are benchmarked in terms of their density and viscosity prediction accuracy of n-hexadecane using equilibrium molecular dynamics (EMD) simulations at ambient and HTHP conditions. Whilst united-atom force-fields accurately reproduce experimental density, the viscosity is significantly under-predicted compared to all-atom force-fields and experiments. Moreover, some all-atom force-fields yield elevated melting points, leading to significant overestimation of both the density and viscosity. In the second section, the most accurate united-atom and all-atom force-field are compared in confined NEMD simulations which probe the structure and friction of stearic acid adsorbed on iron oxide and separated by a thin layer of n-hexadecane. The united-atom force-field provides an accurate representation of the structure of the confined stearic acid film; however, friction coefficients are consistently under-predicted and the friction-coverage and friction-velocity behavior deviates from that observed using all-atom force-fields and experimentally. This has important implications regarding force-field selection for NEMD simulations of systems containing long-chain, linear molecules; specifically, it is recommended that accurate all-atom potentials, such as L-OPLS-AA, are employed. PMID:28773773
A Comparison of Classical Force-Fields for Molecular Dynamics Simulations of Lubricants.

PubMed

Ewen, James P; Gattinoni, Chiara; Thakkar, Foram M; Morgan, Neal; Spikes, Hugh A; Dini, Daniele

2016-08-02

For the successful development and application of lubricants, a full understanding of their complex nanoscale behavior under a wide range of external conditions is required, but this is difficult to obtain experimentally. Nonequilibrium molecular dynamics (NEMD) simulations can be used to yield unique insights into the atomic-scale structure and friction of lubricants and additives; however, the accuracy of the results depend on the chosen force-field. In this study, we demonstrate that the use of an accurate, all-atom force-field is critical in order to; (i) accurately predict important properties of long-chain, linear molecules; and (ii) reproduce experimental friction behavior of multi-component tribological systems. In particular, we focus on n -hexadecane, an important model lubricant with a wide range of industrial applications. Moreover, simulating conditions common in tribological systems, i.e., high temperatures and pressures (HTHP), allows the limits of the selected force-fields to be tested. In the first section, a large number of united-atom and all-atom force-fields are benchmarked in terms of their density and viscosity prediction accuracy of n -hexadecane using equilibrium molecular dynamics (EMD) simulations at ambient and HTHP conditions. Whilst united-atom force-fields accurately reproduce experimental density, the viscosity is significantly under-predicted compared to all-atom force-fields and experiments. Moreover, some all-atom force-fields yield elevated melting points, leading to significant overestimation of both the density and viscosity. In the second section, the most accurate united-atom and all-atom force-field are compared in confined NEMD simulations which probe the structure and friction of stearic acid adsorbed on iron oxide and separated by a thin layer of n -hexadecane. The united-atom force-field provides an accurate representation of the structure of the confined stearic acid film; however, friction coefficients are consistently under-predicted and the friction-coverage and friction-velocity behavior deviates from that observed using all-atom force-fields and experimentally. This has important implications regarding force-field selection for NEMD simulations of systems containing long-chain, linear molecules; specifically, it is recommended that accurate all-atom potentials, such as L-OPLS-AA, are employed.
Competitive Abilities in Experimental Microcosms Are Accurately Predicted by a Demographic Index for R*

PubMed Central

Murrell, Ebony G.; Juliano, Steven A.

2012-01-01

Resource competition theory predicts that R*, the equilibrium resource amount yielding zero growth of a consumer population, should predict species' competitive abilities for that resource. This concept has been supported for unicellular organisms, but has not been well-tested for metazoans, probably due to the difficulty of raising experimental populations to equilibrium and measuring population growth rates for species with long or complex life cycles. We developed an index (Rindex) of R* based on demography of one insect cohort, growing from egg to adult in a non-equilibrium setting, and tested whether Rindex yielded accurate predictions of competitive abilities using mosquitoes as a model system. We estimated finite rate of increase (λ′) from demographic data for cohorts of three mosquito species raised with different detritus amounts, and estimated each species' Rindex using nonlinear regressions of λ′ vs. initial detritus amount. All three species' Rindex differed significantly, and accurately predicted competitive hierarchy of the species determined in simultaneous pairwise competition experiments. Our Rindex could provide estimates and rigorous statistical comparisons of competitive ability for organisms for which typical chemostat methods and equilibrium population conditions are impractical. PMID:22970128
Crystal engineering of ibuprofen compounds: From molecule to crystal structure to morphology prediction by computational simulation and experimental study

NASA Astrophysics Data System (ADS)

Zhang, Min; Liang, Zuozhong; Wu, Fei; Chen, Jian-Feng; Xue, Chunyu; Zhao, Hong

2017-06-01

We selected the crystal structures of ibuprofen with seven common space groups (Cc, P21/c, P212121, P21, Pbca, Pna21, and Pbcn), which was generated from ibuprofen molecule by molecular simulation. The predicted crystal structures of ibuprofen with space group P21/c has the lowest total energy and the largest density, which is nearly indistinguishable with experimental result. In addition, the XRD patterns for predicted crystal structure are highly consistent with recrystallization from solvent of ibuprofen. That indicates that the simulation can accurately predict the crystal structure of ibuprofen from the molecule. Furthermore, based on this crystal structure, we predicted the crystal habit in vacuum using the attachment energy (AE) method and considered solvent effects in a systematic way using the modified attachment energy (MAE) model. The simulation can accurately construct a complete process from molecule to crystal structure to morphology prediction. Experimentally, we observed crystal morphologies in four different polarity solvents compounds (ethanol, acetonitrile, ethyl acetate, and toluene). We found that the aspect ratio decreases of crystal habits in this ibuprofen system were found to vary with increasing solvent relative polarity. Besides, the modified crystal morphologies are in good agreement with the observed experimental morphologies. Finally, this work may guide computer-aided design of the desirable crystal morphology.
A comparative study between experimental results and numerical predictions of multi-wall structural response to hypervelocity impact

NASA Technical Reports Server (NTRS)

Schonberg, William P.; Peck, Jeffrey A.

1992-01-01

Over the last three decades, multiwall structures have been analyzed extensively, primarily through experiment, as a means of increasing the protection afforded to spacecraft structure. However, as structural configurations become more varied, the number of tests required to characterize their response increases dramatically. As an alternative, numerical modeling of high-speed impact phenomena is often being used to predict the response of a variety of structural systems under impact loading conditions. This paper presents the results of a preliminary numerical/experimental investigation of the hypervelocity impact response of multiwall structures. The results of experimental high-speed impact tests are compared against the predictions of the HULL hydrodynamic computer code. It is shown that the hypervelocity impact response characteristics of a specific system cannot be accurately predicted from a limited number of HULL code impact simulations. However, if a wide range of impact loadings conditions are considered, then the ballistic limit curve of the system based on the entire series of numerical simulations can be used as a relatively accurate indication of actual system response.
Aqueous solubility, effects of salts on aqueous solubility, and partitioning behavior of hexafluorobenzene: experimental results and COSMO-RS predictions.

PubMed

Schröder, Bernd; Freire, Mara G; Varanda, Fatima R; Marrucho, Isabel M; Santos, Luís M N B F; Coutinho, João A P

2011-07-01

The aqueous solubility of hexafluorobenzene has been determined, at 298.15K, using a shake-flask method with a spectrophotometric quantification technique. Furthermore, the solubility of hexafluorobenzene in saline aqueous solutions, at distinct salt concentrations, has been measured. Both salting-in and salting-out effects were observed and found to be dependent on the nature of the cationic/anionic composition of the salt. COSMO-RS, the Conductor-like Screening Model for Real Solvents, has been used to predict the corresponding aqueous solubilities at conditions similar to those used experimentally. The prediction results showed that the COSMO-RS approach is suitable for the prediction of salting-in/-out effects. The salting-in/-out phenomena have been rationalized with the support of COSMO-RS σ-profiles. The prediction potential of COSMO-RS regarding aqueous solubilities and octanol-water partition coefficients has been compared with typically used QSPR-based methods. Up to now, the absence of accurate solubility data for hexafluorobenzene hampered the calculation of the respective partition coefficients. Combining available accurate vapor pressure data with the experimentally determined water solubility, a novel air-water partition coefficient has been derived. Copyright © 2011 Elsevier Ltd. All rights reserved.
A Modified Isotropic-Kinematic Hardening Model to Predict the Defects in Tube Hydroforming Process

NASA Astrophysics Data System (ADS)

Jin, Kai; Guo, Qun; Tao, Jie; Guo, Xun-zhong

2017-11-01

Numerical simulations of tube hydroforming process of hollow crankshafts were conducted by using finite element analysis method. Moreover, the modified model involving the integration of isotropic-kinematic hardening model with ductile criteria model was used to more accurately optimize the process parameters such as internal pressure, feed distance and friction coefficient. Subsequently, hydroforming experiments were performed based on the simulation results. The comparison between experimental and simulation results indicated that the prediction of tube deformation, crack and wrinkle was quite accurate for the tube hydroforming process. Finally, hollow crankshafts with high thickness uniformity were obtained and the thickness distribution between numerical and experimental results was well consistent.

Investigation of composite materials property requirements for sonic fatigue research

NASA Technical Reports Server (NTRS)

Patrick, H. V. L.

1985-01-01

Experimental techniques for determining the extensional and bending stiffness characteristics for symmetric laminates are presented. Vibrational test techniques for determining the dynamic modulus and material damping are also discussed. Partial extensional stiffness results intially indicate that the laminate theory used for predicting stiffness is accurate. It is clearly shown that the laminate theory can only be as accurate as the physical characteristics describing the lamina, which may vary significantly. It is recommended that all of the stiffness characteristics in both extension and bending be experimentally determined to fully verify the laminate theory. Dynamic modulus should be experimentally evaluated to determine if static data adequately predicts dynamic behavior. Material damping should also be ascertained because laminate damping is an order of magnitude greater than found in common metals and can significantly effect the displacement response of composite panels.
Calculation of three-dimensional compressible laminar and turbulent boundary layers. An implicit finite-difference procedure for solving the three-dimensional compressible laminar, transitional, and turbulent boundary-layer equations

NASA Technical Reports Server (NTRS)

Harris, J. E.

1975-01-01

An implicit finite-difference procedure is presented for solving the compressible three-dimensional boundary-layer equations. The method is second-order accurate, unconditionally stable (conditional stability for reverse cross flow), and efficient from the viewpoint of computer storage and processing time. The Reynolds stress terms are modeled by (1) a single-layer mixing length model and (2) a two-layer eddy viscosity model. These models, although simple in concept, accurately predicted the equilibrium turbulent flow for the conditions considered. Numerical results are compared with experimental wall and profile data for a cone at an angle of attack larger than the cone semiapex angle. These comparisons clearly indicate that the numerical procedure and turbulence models accurately predict the experimental data with as few as 21 nodal points in the plane normal to the wall boundary.
Time travel, Clock Puzzles and Their Experimental Tests

NASA Astrophysics Data System (ADS)

Ciufolini, Ignazio

2013-09-01

Is time travel possible? What is Einstein's theory of relativity mathematically predicting in that regard? Is time travel related to the so-called clock `paradoxes' of relativity and if so how? Is there any accurate experimental evidence of the phenomena regarding the different flow of time predicted by General Relativity and is there any possible application of the temporal phenomena predicted by relativity to our everyday life? Which temporal phenomena are predicted in the vicinities of a rotating body and of a mass-energy current, and do we have any experimental test of the occurrence of these phenomena near a rotating body? In this paper, we address and answer some of these questions.
Functional analysis screening for multiple topographies of problem behavior.

PubMed

Bell, Marlesha C; Fahmie, Tara A

2018-04-23

The current study evaluated a screening procedure for multiple topographies of problem behavior in the context of an ongoing functional analysis. Experimenters analyzed the function of a topography of primary concern while collecting data on topographies of secondary concern. We used visual analysis to predict the function of secondary topographies and a subsequent functional analysis to test those predictions. Results showed that a general function was accurately predicted for five of six (83%) secondary topographies. A specific function was predicted and supported for a subset of these topographies. The experimenters discuss the implication of these results for clinicians who have limited time for functional assessment. © 2018 Society for the Experimental Analysis of Behavior.
Species and temperature predictions in a semi-industrial MILD furnace using a non-adiabatic conditional source-term estimation formulation

NASA Astrophysics Data System (ADS)

Labahn, Jeffrey William; Devaud, Cecile

2017-05-01

A Reynolds-Averaged Navier-Stokes (RANS) simulation of the semi-industrial International Flame Research Foundation (IFRF) furnace is performed using a non-adiabatic Conditional Source-term Estimation (CSE) formulation. This represents the first time that a CSE formulation, which accounts for the effect of radiation on the conditional reaction rates, has been applied to a large scale semi-industrial furnace. The objective of the current study is to assess the capabilities of CSE to accurately reproduce the velocity field, temperature, species concentration and nitrogen oxides (NOx) emission for the IFRF furnace. The flow field is solved using the standard k-ε turbulence model and detailed chemistry is included. NOx emissions are calculated using two different methods. Predicted velocity profiles are in good agreement with the experimental data. The predicted peak temperature occurs closer to the centreline, as compared to the experimental observations, suggesting that the mixing between the fuel jet and vitiated air jet may be overestimated. Good agreement between the species concentrations, including NOx, and the experimental data is observed near the burner exit. Farther downstream, the centreline oxygen concentration is found to be underpredicted. Predicted NOx concentrations are in good agreement with experimental data when calculated using the method of Peters and Weber. The current study indicates that RANS-CSE can accurately predict the main characteristics seen in a semi-industrial IFRF furnace.
Electrochemical carbon dioxide concentrator: Math model

NASA Technical Reports Server (NTRS)

Marshall, R. D.; Schubert, F. H.; Carlson, J. N.

1973-01-01

A steady state computer simulation model of an Electrochemical Depolarized Carbon Dioxide Concentrator (EDC) has been developed. The mathematical model combines EDC heat and mass balance equations with empirical correlations derived from experimental data to describe EDC performance as a function of the operating parameters involved. The model is capable of accurately predicting performance over EDC operating ranges. Model simulation results agree with the experimental data obtained over the prediction range.
USM3D Analysis of Low Boom Configuration

NASA Technical Reports Server (NTRS)

Carter, Melissa B.; Campbell, Richard L.; Nayani, Sudheer N.

2011-01-01

In the past few years considerable improvement was made in NASA's in house boom prediction capability. As part of this improved capability, the USM3D Navier-Stokes flow solver, when combined with a suitable unstructured grid, went from accurately predicting boom signatures at 1 body length to 10 body lengths. Since that time, the research emphasis has shifted from analysis to the design of supersonic configurations with boom signature mitigation In order to design an aircraft, the techniques for accurately predicting boom and drag need to be determined. This paper compares CFD results with the wind tunnel experimental results conducted on a Gulfstream reduced boom and drag configuration. Two different wind-tunnel models were designed and tested for drag and boom data. The goal of this study was to assess USM3D capability for predicting both boom and drag characteristics. Overall, USM3D coupled with a grid that was sheared and stretched was able to reasonably predict boom signature. The computational drag polar matched the experimental results for a lift coefficient above 0.1 despite some mismatch in the predicted lift-curve slope.
Predicting vapor-liquid phase equilibria with augmented ab initio interatomic potentials

NASA Astrophysics Data System (ADS)

Vlasiuk, Maryna; Sadus, Richard J.

2017-06-01

The ability of ab initio interatomic potentials to accurately predict vapor-liquid phase equilibria is investigated. Monte Carlo simulations are reported for the vapor-liquid equilibria of argon and krypton using recently developed accurate ab initio interatomic potentials. Seventeen interatomic potentials are studied, formulated from different combinations of two-body plus three-body terms. The simulation results are compared to either experimental or reference data for conditions ranging from the triple point to the critical point. It is demonstrated that the use of ab initio potentials enables systematic improvements to the accuracy of predictions via the addition of theoretically based terms. The contribution of three-body interactions is accounted for using the Axilrod-Teller-Muto plus other multipole contributions and the effective Marcelli-Wang-Sadus potentials. The results indicate that the predictive ability of recent interatomic potentials, obtained from quantum chemical calculations, is comparable to that of accurate empirical models. It is demonstrated that the Marcelli-Wang-Sadus potential can be used in combination with accurate two-body ab initio models for the computationally inexpensive and accurate estimation of vapor-liquid phase equilibria.
Predicting vapor-liquid phase equilibria with augmented ab initio interatomic potentials.

PubMed

Vlasiuk, Maryna; Sadus, Richard J

2017-06-28

The ability of ab initio interatomic potentials to accurately predict vapor-liquid phase equilibria is investigated. Monte Carlo simulations are reported for the vapor-liquid equilibria of argon and krypton using recently developed accurate ab initio interatomic potentials. Seventeen interatomic potentials are studied, formulated from different combinations of two-body plus three-body terms. The simulation results are compared to either experimental or reference data for conditions ranging from the triple point to the critical point. It is demonstrated that the use of ab initio potentials enables systematic improvements to the accuracy of predictions via the addition of theoretically based terms. The contribution of three-body interactions is accounted for using the Axilrod-Teller-Muto plus other multipole contributions and the effective Marcelli-Wang-Sadus potentials. The results indicate that the predictive ability of recent interatomic potentials, obtained from quantum chemical calculations, is comparable to that of accurate empirical models. It is demonstrated that the Marcelli-Wang-Sadus potential can be used in combination with accurate two-body ab initio models for the computationally inexpensive and accurate estimation of vapor-liquid phase equilibria.
Toward Fully in Silico Melting Point Prediction Using Molecular Simulations

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

Zhang, Y; Maginn, EJ

2013-03-01

Melting point is one of the most fundamental and practically important properties of a compound. Molecular computation of melting points. However, all of these methods simulation methods have been developed for the accurate need an experimental crystal structure as input, which means that such calculations are not really predictive since the melting point can be measured easily in experiments once a crystal structure is known. On the other hand, crystal structure prediction (CSP) has become an active field and significant progress has been made, although challenges still exist. One of the main challenges is the existence of many crystal structuresmore » (polymorphs) that are very close in energy. Thermal effects and kinetic factors make the situation even more complicated, such that it is still not trivial to predict experimental crystal structures. In this work, we exploit the fact that free energy differences are often small between crystal structures. We show that accurate melting point predictions can be made by using a reasonable crystal structure from CSP as a starting point for a free energy-based melting point calculation. The key is that most crystal structures predicted by CSP have free energies that are close to that of the experimental structure. The proposed method was tested on two rigid molecules and the results suggest that a fully in silico melting point prediction method is possible.« less
Hybrid experimental/analytical models of structural dynamics - Creation and use for predictions

NASA Technical Reports Server (NTRS)

Balmes, Etienne

1993-01-01

An original complete methodology for the construction of predictive models of damped structural vibrations is introduced. A consistent definition of normal and complex modes is given which leads to an original method to accurately identify non-proportionally damped normal mode models. A new method to create predictive hybrid experimental/analytical models of damped structures is introduced, and the ability of hybrid models to predict the response to system configuration changes is discussed. Finally a critical review of the overall methodology is made by application to the case of the MIT/SERC interferometer testbed.
Probing the geometry of copper and silver adatoms on magnetite: quantitative experiment versus theory† †Electronic supplementary information (ESI) available: Experimental and computational details, as well as further details on the results and analyses. See DOI: 10.1039/c7nr07319d

PubMed Central

Meier, Matthias; Jakub, Zdeněk; Balajka, Jan; Hulva, Jan; Bliem, Roland; Thakur, Pardeep K.; Lee, Tien-Lin; Franchini, Cesare; Schmid, Michael; Diebold, Ulrike; Allegretti, Francesco; Parkinson, Gareth S.

2018-01-01

Accurately modelling the structure of a catalyst is a fundamental prerequisite for correctly predicting reaction pathways, but a lack of clear experimental benchmarks makes it difficult to determine the optimal theoretical approach. Here, we utilize the normal incidence X-ray standing wave (NIXSW) technique to precisely determine the three dimensional geometry of Ag1 and Cu1 adatoms on Fe3O4(001). Both adatoms occupy bulk-continuation cation sites, but with a markedly different height above the surface (0.43 ± 0.03 Å (Cu1) and 0.96 ± 0.03 Å (Ag1)). HSE-based calculations accurately predict the experimental geometry, but the more common PBE + U and PBEsol + U approaches perform poorly. PMID:29334395
A comparison of the calculated and experimental off-design performance of a radial flow turbine

NASA Technical Reports Server (NTRS)

Tirres, Lizet

1992-01-01

Off design aerodynamic performance of the solid version of a cooled radial inflow turbine is analyzed. Rotor surface static pressure data and other performance parameters were obtained experimentally. Overall stage performance and turbine blade surface static to inlet total pressure ratios were calculated by using a quasi-three dimensional inviscid code. The off design prediction capability of this code for radial inflow turbines shows accurate static pressure prediction. Solutions show a difference of 3 to 5 points between the experimentally obtained efficiencies and the calculated values.
A comparison of the calculated and experimental off-design performance of a radial flow turbine

NASA Technical Reports Server (NTRS)

Tirres, Lizet

1991-01-01

Off design aerodynamic performance of the solid version of a cooled radial inflow turbine is analyzed. Rotor surface static pressure data and other performance parameters were obtained experimentally. Overall stage performance and turbine blade surface static to inlet total pressure ratios were calculated by using a quasi-three dimensional inviscid code. The off design prediction capability of this code for radial inflow turbines shows accurate static pressure prediction. Solutions show a difference of 3 to 5 points between the experimentally obtained efficiencies and the calculated values.
Prediction of coefficients of thermal expansion for unidirectional composites

NASA Technical Reports Server (NTRS)

Bowles, David E.; Tompkins, Stephen S.

1989-01-01

Several analyses for predicting the longitudinal, alpha(1), and transverse, alpha(2), coefficients of thermal expansion of unidirectional composites were compared with each other, and with experimental data on different graphite fiber reinforced resin, metal, and ceramic matrix composites. Analytical and numerical analyses that accurately accounted for Poisson restraining effects in the transverse direction were in consistently better agreement with experimental data for alpha(2), than the less rigorous analyses. All of the analyses predicted similar values of alpha(1), and were in good agreement with the experimental data. A sensitivity analysis was conducted to determine the relative influence of constituent properties on the predicted values of alpha(1), and alpha(2). As would be expected, the prediction of alpha(1) was most sensitive to longitudinal fiber properties and the prediction of alpha(2) was most sensitive to matrix properties.
Physics-based enzyme design: predicting binding affinity and catalytic activity.

PubMed

Sirin, Sarah; Pearlman, David A; Sherman, Woody

2014-12-01

Computational enzyme design is an emerging field that has yielded promising success stories, but where numerous challenges remain. Accurate methods to rapidly evaluate possible enzyme design variants could provide significant value when combined with experimental efforts by reducing the number of variants needed to be synthesized and speeding the time to reach the desired endpoint of the design. To that end, extending our computational methods to model the fundamental physical-chemical principles that regulate activity in a protocol that is automated and accessible to a broad population of enzyme design researchers is essential. Here, we apply a physics-based implicit solvent MM-GBSA scoring approach to enzyme design and benchmark the computational predictions against experimentally determined activities. Specifically, we evaluate the ability of MM-GBSA to predict changes in affinity for a steroid binder protein, catalytic turnover for a Kemp eliminase, and catalytic activity for α-Gliadin peptidase variants. Using the enzyme design framework developed here, we accurately rank the most experimentally active enzyme variants, suggesting that this approach could provide enrichment of active variants in real-world enzyme design applications. © 2014 Wiley Periodicals, Inc.
Accurate Identification of Fear Facial Expressions Predicts Prosocial Behavior

PubMed Central

Marsh, Abigail A.; Kozak, Megan N.; Ambady, Nalini

2009-01-01

The fear facial expression is a distress cue that is associated with the provision of help and prosocial behavior. Prior psychiatric studies have found deficits in the recognition of this expression by individuals with antisocial tendencies. However, no prior study has shown accuracy for recognition of fear to predict actual prosocial or antisocial behavior in an experimental setting. In 3 studies, the authors tested the prediction that individuals who recognize fear more accurately will behave more prosocially. In Study 1, participants who identified fear more accurately also donated more money and time to a victim in a classic altruism paradigm. In Studies 2 and 3, participants’ ability to identify the fear expression predicted prosocial behavior in a novel task designed to control for confounding variables. In Study 3, accuracy for recognizing fear proved a better predictor of prosocial behavior than gender, mood, or scores on an empathy scale. PMID:17516803
Accurate identification of fear facial expressions predicts prosocial behavior.

PubMed

Marsh, Abigail A; Kozak, Megan N; Ambady, Nalini

2007-05-01

The fear facial expression is a distress cue that is associated with the provision of help and prosocial behavior. Prior psychiatric studies have found deficits in the recognition of this expression by individuals with antisocial tendencies. However, no prior study has shown accuracy for recognition of fear to predict actual prosocial or antisocial behavior in an experimental setting. In 3 studies, the authors tested the prediction that individuals who recognize fear more accurately will behave more prosocially. In Study 1, participants who identified fear more accurately also donated more money and time to a victim in a classic altruism paradigm. In Studies 2 and 3, participants' ability to identify the fear expression predicted prosocial behavior in a novel task designed to control for confounding variables. In Study 3, accuracy for recognizing fear proved a better predictor of prosocial behavior than gender, mood, or scores on an empathy scale.
Impacts of Earth rotation parameters on GNSS ultra-rapid orbit prediction: Derivation and real-time correction

NASA Astrophysics Data System (ADS)

Wang, Qianxin; Hu, Chao; Xu, Tianhe; Chang, Guobin; Hernández Moraleda, Alberto

2017-12-01

Analysis centers (ACs) for global navigation satellite systems (GNSSs) cannot accurately obtain real-time Earth rotation parameters (ERPs). Thus, the prediction of ultra-rapid orbits in the international terrestrial reference system (ITRS) has to utilize the predicted ERPs issued by the International Earth Rotation and Reference Systems Service (IERS) or the International GNSS Service (IGS). In this study, the accuracy of ERPs predicted by IERS and IGS is analyzed. The error of the ERPs predicted for one day can reach 0.15 mas and 0.053 ms in polar motion and UT1-UTC direction, respectively. Then, the impact of ERP errors on ultra-rapid orbit prediction by GNSS is studied. The methods for orbit integration and frame transformation in orbit prediction with introduced ERP errors dominate the accuracy of the predicted orbit. Experimental results show that the transformation from the geocentric celestial references system (GCRS) to ITRS exerts the strongest effect on the accuracy of the predicted ultra-rapid orbit. To obtain the most accurate predicted ultra-rapid orbit, a corresponding real-time orbit correction method is developed. First, orbits without ERP-related errors are predicted on the basis of ITRS observed part of ultra-rapid orbit for use as reference. Then, the corresponding predicted orbit is transformed from GCRS to ITRS to adjust for the predicted ERPs. Finally, the corrected ERPs with error slopes are re-introduced to correct the predicted orbit in ITRS. To validate the proposed method, three experimental schemes are designed: function extrapolation, simulation experiments, and experiments with predicted ultra-rapid orbits and international GNSS Monitoring and Assessment System (iGMAS) products. Experimental results show that using the proposed correction method with IERS products considerably improved the accuracy of ultra-rapid orbit prediction (except the geosynchronous BeiDou orbits). The accuracy of orbit prediction is enhanced by at least 50% (error related to ERP) when a highly accurate observed orbit is used with the correction method. For iGMAS-predicted orbits, the accuracy improvement ranges from 8.5% for the inclined BeiDou orbits to 17.99% for the GPS orbits. This demonstrates that the correction method proposed by this study can optimize the ultra-rapid orbit prediction.
Study on elevated-temperature flow behavior of Ni-Cr-Mo-B ultra-heavy-plate steel via experiment and modelling

NASA Astrophysics Data System (ADS)

Gao, Zhi-yu; Kang, Yu; Li, Yan-shuai; Meng, Chao; Pan, Tao

2018-04-01

Elevated-temperature flow behavior of a novel Ni-Cr-Mo-B ultra-heavy-plate steel was investigated by conducting hot compressive deformation tests on a Gleeble-3800 thermo-mechanical simulator at a temperature range of 1123 K–1423 K with a strain rate range from 0.01 s‑1 to10 s‑1 and a height reduction of 70%. Based on the experimental results, classic strain-compensated Arrhenius-type, a new revised strain-compensated Arrhenius-type and classic modified Johnson-Cook constitutive models were developed for predicting the high-temperature deformation behavior of the steel. The predictability of these models were comparatively evaluated in terms of statistical parameters including correlation coefficient (R), average absolute relative error (AARE), average root mean square error (RMSE), normalized mean bias error (NMBE) and relative error. The statistical results indicate that the new revised strain-compensated Arrhenius-type model could give prediction of elevated-temperature flow stress for the steel accurately under the entire process conditions. However, the predicted values by the classic modified Johnson-Cook model could not agree well with the experimental values, and the classic strain-compensated Arrhenius-type model could track the deformation behavior more accurately compared with the modified Johnson-Cook model, but less accurately with the new revised strain-compensated Arrhenius-type model. In addition, reasons of differences in predictability of these models were discussed in detail.

Prediction of Reduction Potentials of Copper Proteins with Continuum Electrostatics and Density Functional Theory

PubMed Central

Fowler, Nicholas J.; Blanford, Christopher F.

2017-01-01

Abstract Blue copper proteins, such as azurin, show dramatic changes in Cu2+/Cu+ reduction potential upon mutation over the full physiological range. Hence, they have important functions in electron transfer and oxidation chemistry and have applications in industrial biotechnology. The details of what determines these reduction potential changes upon mutation are still unclear. Moreover, it has been difficult to model and predict the reduction potential of azurin mutants and currently no unique procedure or workflow pattern exists. Furthermore, high‐level computational methods can be accurate but are too time consuming for practical use. In this work, a novel approach for calculating reduction potentials of azurin mutants is shown, based on a combination of continuum electrostatics, density functional theory and empirical hydrophobicity factors. Our method accurately reproduces experimental reduction potential changes of 30 mutants with respect to wildtype within experimental error and highlights the factors contributing to the reduction potential change. Finally, reduction potentials are predicted for a series of 124 new mutants that have not yet been investigated experimentally. Several mutants are identified that are located well over 10 Å from the copper center that change the reduction potential by more than 85 mV. The work shows that secondary coordination sphere mutations mostly lead to long‐range electrostatic changes and hence can be modeled accurately with continuum electrostatics. PMID:28815759
Experimental Validation of a Coupled Fluid-Multibody Dynamics Model for Tanker Trucks

DTIC Science & Technology

2007-11-08

order to accurately predict the dynamic response of tanker trucks, the model must accurately account for the following effects : • Incompressible...computational code which uses a time- accurate explicit solution procedure is used to solve both the solid and fluid equations of motion. Many commercial...position vector, τ is the deviatoric stress tensor, D is the rate of deformation tensor, f r is the body force vector, r is the artificial
First-Principles Predictions of Near-Edge X-ray Absorption Fine Structure Spectra of Semiconducting Polymers

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

Su, Gregory M.; Patel, Shrayesh N.; Pemmaraju, C. D.

The electronic structure and molecular orientation of semiconducting polymers in thin films determine their ability to transport charge. Methods based on near-edge X-ray absorption fine structure (NEXAFS) spectroscopy can be used to probe both the electronic structure and microstructure of semiconducting polymers in both crystalline and amorphous films. However, it can be challenging to interpret NEXAFS spectra on the basis of experimental data alone, and accurate, predictive calculations are needed to complement experiments. Here, we show that first-principles density functional theory (DFT) can be used to model NEXAFS spectra of semiconducting polymers and to identify the nature of transitions inmore » complicated NEXAFS spectra. Core-level X-ray absorption spectra of a set of semiconducting polymers were calculated using the excited electron and core-hole (XCH) approach based on constrained-occupancy DFT. A comparison of calculations on model oligomers and periodic structures with experimental data revealed the requirements for accurate prediction of NEXAFS spectra of both conjugated homopolymers and donor–acceptor polymers. The NEXAFS spectra predicted by the XCH approach were applied to study molecular orientation in donor–acceptor polymers using experimental spectra and revealed the complexity of using carbon edge spectra in systems with large monomeric units. The XCH approach has sufficient accuracy in predicting experimental NEXAFS spectra of polymers that it should be considered for design and analysis of measurements using soft X-ray techniques, such as resonant soft X-ray scattering and scanning transmission X-ray microscopy.« less
Predictive and Experimental Approaches for Elucidating Protein–Protein Interactions and Quaternary Structures

PubMed Central

Nealon, John Oliver; Philomina, Limcy Seby

2017-01-01

The elucidation of protein–protein interactions is vital for determining the function and action of quaternary protein structures. Here, we discuss the difficulty and importance of establishing protein quaternary structure and review in vitro and in silico methods for doing so. Determining the interacting partner proteins of predicted protein structures is very time-consuming when using in vitro methods, this can be somewhat alleviated by use of predictive methods. However, developing reliably accurate predictive tools has proved to be difficult. We review the current state of the art in predictive protein interaction software and discuss the problem of scoring and therefore ranking predictions. Current community-based predictive exercises are discussed in relation to the growth of protein interaction prediction as an area within these exercises. We suggest a fusion of experimental and predictive methods that make use of sparse experimental data to determine higher resolution predicted protein interactions as being necessary to drive forward development. PMID:29206185
Thermogravimetric analysis for rapid assessment of moisture diffusivity in polydisperse powder and thin film matrices.

PubMed

Thirunathan, Praveena; Arnz, Patrik; Husny, Joeska; Gianfrancesco, Alessandro; Perdana, Jimmy

2018-03-01

Accurate description of moisture diffusivity is key to precisely understand and predict moisture transfer behaviour in a matrix. Unfortunately, measuring moisture diffusivity is not trivial, especially at low moisture values and/or elevated temperatures. This paper presents a novel experimental procedure to accurately measure moisture diffusivity based on thermogravimetric approach. The procedure is capable to measure diffusivity even at elevated temperatures (>70°C) and low moisture values (>1%). Diffusivity was extracted from experimental data based on "regular regime approach". The approach was tailored to determine diffusivity from thin film and from poly-dispersed powdered samples. Subsequently, measured diffusivity was validated by comparing to available literature data, showing good agreement. Ability of this approach to accurately measure diffusivity at a wider range of temperatures provides better insight on temperature dependency of diffusivity. Thus, this approach can be crucial to ensure good accuracy of moisture transfer description/prediction especially when involving elevated temperatures. Copyright © 2017 Elsevier Ltd. All rights reserved.
Control surface hinge moment prediction using computational fluid dynamics

NASA Astrophysics Data System (ADS)

Simpson, Christopher David

The following research determines the feasibility of predicting control surface hinge moments using various computational methods. A detailed analysis is conducted using a 2D GA(W)-1 airfoil with a 20% plain flap. Simple hinge moment prediction methods are tested, including empirical Datcom relations and XFOIL. Steady-state and time-accurate turbulent, viscous, Navier-Stokes solutions are computed using Fun3D. Hinge moment coefficients are computed. Mesh construction techniques are discussed. An adjoint-based mesh adaptation case is also evaluated. An NACA 0012 45-degree swept horizontal stabilizer with a 25% elevator is also evaluated using Fun3D. Results are compared with experimental wind-tunnel data obtained from references. Finally, the costs of various solution methods are estimated. Results indicate that while a steady-state Navier-Stokes solution can accurately predict control surface hinge moments for small angles of attack and deflection angles, a time-accurate solution is necessary to accurately predict hinge moments in the presence of flow separation. The ability to capture the unsteady vortex shedding behavior present in moderate to large control surface deflections is found to be critical to hinge moment prediction accuracy. Adjoint-based mesh adaptation is shown to give hinge moment predictions similar to a globally-refined mesh for a steady-state 2D simulation.
Engineering prediction of turbulent skin friction and heat transfer in high-speed flow

NASA Technical Reports Server (NTRS)

Cary, A. M., Jr.; Bertram, M. H.

1974-01-01

A large collection of experimental turbulent-skin-friction and heat-transfer data for flat plates and cones was used to determine the most accurate of six of the most popular engineering-prediction methods; the data represent a Mach number range from 4 to 13 and ratio of wall to total temperature ranging from 0.1 to 0.7. The Spalding and Chi method incorporating virtual-origin concepts was found to be the best prediction method for Mach numbers less than 10; the limited experimental data for Mach numbers greater than 10 were not well predicted by any of the engineering methods except the Coles method.
Overview of Aerothermodynamic Loads Definition Study

NASA Technical Reports Server (NTRS)

Povinelli, L. A.

1985-01-01

The Aerothermodynamic Loads Definition were studied to develop methods to more accurately predict the operating environment in the space shuttle main engine (SSME) components. Development of steady and time-dependent, three-dimensional viscous computer codes and experimental verification and engine diagnostic testing are considered. The steady, nonsteady, and transient operating loads are defined to accurately predict powerhead life. Improvements in the structural durability of the SSME turbine drive systems depends on the knowledge of the aerothermodynamic behavior of the flow through the preburner, turbine, turnaround duct, gas manifold, and injector post regions.
A numerical simulation of the NFAC (National Full-scale Aerodynamics Complex) open-return wind tunnel inlet flow

NASA Technical Reports Server (NTRS)

Kaul, U. K.; Ross, J. C.; Jacocks, J. L.

1985-01-01

The flow into an open return wind tunnel inlet was simulated using Euler equations. An explicit predictor-corrector method was employed to solve the system. The calculation is time-accurate and was performed to achieve a steady-state solution. The predictions are in reasonable agreement with the experimental data. Wall pressures are accurately predicted except in a region of recirculating flow. Flow-field surveys agree qualitatively with laser velocimeter measurements. The method can be used in the design process for open return wind tunnels.
End-of-Discharge and End-of-Life Prediction in Lithium-Ion Batteries with Electrochemistry-Based Aging Models

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Kulkarni, Chetan S.

2016-01-01

As batteries become increasingly prevalent in complex systems such as aircraft and electric cars, monitoring and predicting battery state of charge and state of health becomes critical. In order to accurately predict the remaining battery power to support system operations for informed operational decision-making, age-dependent changes in dynamics must be accounted for. Using an electrochemistry-based model, we investigate how key parameters of the battery change as aging occurs, and develop models to describe aging through these key parameters. Using these models, we demonstrate how we can (i) accurately predict end-of-discharge for aged batteries, and (ii) predict the end-of-life of a battery as a function of anticipated usage. The approach is validated through an experimental set of randomized discharge profiles.
Experimental investigation, model development and sensitivity analysis of rheological behavior of ZnO/10W40 nano-lubricants for automotive applications

NASA Astrophysics Data System (ADS)

Hemmat Esfe, Mohammad; Saedodin, Seyfolah; Rejvani, Mousa; Shahram, Jalal

2017-06-01

In the present study, rheological behavior of ZnO/10W40 nano-lubricant is investigated by an experimental approach. Firstly, ZnO nanoparticles of 10-30 nm were dispersed in 10W40 engine oil with solid volume fractions of 0.25-2%, then the viscosity of the composed nano-lubricant was measured in temperature ranges of 5-55 °C and in various shear rates. From analyzing the results, it was revealed that both of the base oil and nano-lubricants are non-Newtonian fluids which exhibit shear thinning behavior. Sensitivity of viscosity to the solid volume fraction enhancement was calculated by a new correlation which was proposed in terms of solid volume fraction and temperature. In order to attain an accurate model by which experimental data are predicted, an artificial neural network (ANN) with a hidden layer and 5 neurons was designed. This model was considerably accurate in predicting experimental data of dynamic viscosity as R-squared and average absolute relative deviation (AARD %) were respectively 0.9999 and 0.0502.
Multi-scale predictions of coniferous forest mortality in the northern hemisphere

NASA Astrophysics Data System (ADS)

McDowell, N. G.

2015-12-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our incomplete understanding of the fundamental physiological thresholds of vegetation mortality during drought limits our ability to accurately simulate future vegetation distributions and associated climate feedbacks. Here we integrate experimental evidence with models to show potential widespread loss of needleleaf evergreen trees (NET; ~ conifers) within the Southwest USA by 2100; with rising temperature being the primary cause of mortality. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ypd) thresholds (April-August mean) beyond which photosynthesis, stomatal and hydraulic conductance, and carbohydrate availability approached zero. Empirical and mechanistic models accurately predicted NET Ypd, and 91% of predictions (10/11) exceeded mortality thresholds within the 21st century due to temperature rise. Completely independent global models predicted >50% loss of northern hemisphere NET by 2100, consistent with the findings for Southwest USA. The global models disagreed with the ecosystem process models in regards to future mortality in Southwest USA, however, highlighting the potential underestimates of future NET mortality as simulated by the global models and signifying the importance of improving regional predictions. Taken together, these results from the validated regional predictions and the global simulations predict global-scale conifer loss in coming decades under projected global warming.
Tools for Early Prediction of Drug Loading in Lipid-Based Formulations

PubMed Central

2015-01-01

Identification of the usefulness of lipid-based formulations (LBFs) for delivery of poorly water-soluble drugs is at date mainly experimentally based. In this work we used a diverse drug data set, and more than 2,000 solubility measurements to develop experimental and computational tools to predict the loading capacity of LBFs. Computational models were developed to enable in silico prediction of solubility, and hence drug loading capacity, in the LBFs. Drug solubility in mixed mono-, di-, triglycerides (Maisine 35-1 and Capmul MCM EP) correlated (R2 0.89) as well as the drug solubility in Carbitol and other ethoxylated excipients (PEG400, R2 0.85; Polysorbate 80, R2 0.90; Cremophor EL, R2 0.93). A melting point below 150 °C was observed to result in a reasonable solubility in the glycerides. The loading capacity in LBFs was accurately calculated from solubility data in single excipients (R2 0.91). In silico models, without the demand of experimentally determined solubility, also gave good predictions of the loading capacity in these complex formulations (R2 0.79). The framework established here gives a better understanding of drug solubility in single excipients and of LBF loading capacity. The large data set studied revealed that experimental screening efforts can be rationalized by solubility measurements in key excipients or from solid state information. For the first time it was shown that loading capacity in complex formulations can be accurately predicted using molecular information extracted from calculated descriptors and thermal properties of the crystalline drug. PMID:26568134
Tools for Early Prediction of Drug Loading in Lipid-Based Formulations.

PubMed

Alskär, Linda C; Porter, Christopher J H; Bergström, Christel A S

2016-01-04

Identification of the usefulness of lipid-based formulations (LBFs) for delivery of poorly water-soluble drugs is at date mainly experimentally based. In this work we used a diverse drug data set, and more than 2,000 solubility measurements to develop experimental and computational tools to predict the loading capacity of LBFs. Computational models were developed to enable in silico prediction of solubility, and hence drug loading capacity, in the LBFs. Drug solubility in mixed mono-, di-, triglycerides (Maisine 35-1 and Capmul MCM EP) correlated (R(2) 0.89) as well as the drug solubility in Carbitol and other ethoxylated excipients (PEG400, R(2) 0.85; Polysorbate 80, R(2) 0.90; Cremophor EL, R(2) 0.93). A melting point below 150 °C was observed to result in a reasonable solubility in the glycerides. The loading capacity in LBFs was accurately calculated from solubility data in single excipients (R(2) 0.91). In silico models, without the demand of experimentally determined solubility, also gave good predictions of the loading capacity in these complex formulations (R(2) 0.79). The framework established here gives a better understanding of drug solubility in single excipients and of LBF loading capacity. The large data set studied revealed that experimental screening efforts can be rationalized by solubility measurements in key excipients or from solid state information. For the first time it was shown that loading capacity in complex formulations can be accurately predicted using molecular information extracted from calculated descriptors and thermal properties of the crystalline drug.
Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein-Ligand Residence Times.

PubMed

Mollica, Luca; Theret, Isabelle; Antoine, Mathias; Perron-Sierra, Françoise; Charton, Yves; Fourquez, Jean-Marie; Wierzbicki, Michel; Boutin, Jean A; Ferry, Gilles; Decherchi, Sergio; Bottegoni, Giovanni; Ducrot, Pierre; Cavalli, Andrea

2016-08-11

Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times.
Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

PubMed Central

2013-01-01

Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression. PMID:23369200
Accuracy of the actuator disc-RANS approach for predicting the performance and wake of tidal turbines.

PubMed

Batten, W M J; Harrison, M E; Bahaj, A S

2013-02-28

The actuator disc-RANS model has widely been used in wind and tidal energy to predict the wake of a horizontal axis turbine. The model is appropriate where large-scale effects of the turbine on a flow are of interest, for example, when considering environmental impacts, or arrays of devices. The accuracy of the model for modelling the wake of tidal stream turbines has not been demonstrated, and flow predictions presented in the literature for similar modelled scenarios vary significantly. This paper compares the results of the actuator disc-RANS model, where the turbine forces have been derived using a blade-element approach, to experimental data measured in the wake of a scaled turbine. It also compares the results with those of a simpler uniform actuator disc model. The comparisons show that the model is accurate and can predict up to 94 per cent of the variation in the experimental velocity data measured on the centreline of the wake, therefore demonstrating that the actuator disc-RANS model is an accurate approach for modelling a turbine wake, and a conservative approach to predict performance and loads. It can therefore be applied to similar scenarios with confidence.
Accurate experimental and theoretical comparisons between superconductor-insulator-superconductor mixers showing weak and strong quantum effects

NASA Technical Reports Server (NTRS)

Mcgrath, W. R.; Richards, P. L.; Face, D. W.; Prober, D. E.; Lloyd, F. L.

1988-01-01

A systematic study of the gain and noise in superconductor-insulator-superconductor mixers employing Ta based, Nb based, and Pb-alloy based tunnel junctions was made. These junctions displayed both weak and strong quantum effects at a signal frequency of 33 GHz. The effects of energy gap sharpness and subgap current were investigated and are quantitatively related to mixer performance. Detailed comparisons are made of the mixing results with the predictions of a three-port model approximation to the Tucker theory. Mixer performance was measured with a novel test apparatus which is accurate enough to allow for the first quantitative tests of theoretical noise predictions. It is found that the three-port model of the Tucker theory underestimates the mixer noise temperature by a factor of about 2 for all of the mixers. In addition, predicted values of available mixer gain are in reasonable agreement with experiment when quantum effects are weak. However, as quantum effects become strong, the predicted available gain diverges to infinity, which is in sharp contrast to the experimental results. Predictions of coupled gain do not always show such divergences.
Review of the BACKONE equation of state and its applications

NASA Astrophysics Data System (ADS)

Lai, Ngoc Anh; Phan, Thi Thu Huong

2017-06-01

This paper presents a review of the BACKONE equation of state (EOS) and its various applications in the study of pure fluid and mixtures as refrigerants, working fluids, natural gases and the study of heat pumps, refrigeration cycles, organic Rankine cycles, trilateral cycles and power flash cycles. It also presents an accurate parameterisation of the BACKONE EOS for the low global warming potential working fluid 3,3,3-trifluoropropene (HFO-1243zf). The average absolute deviations (AAD) between experimental vapour pressure and saturated liquid density data from those of the BACKONE EOS are 0.12% and 0.08%, respectively. The BACKONE EOS for HFO-1243zf also predicts thermodynamic data accurately. The AAD between the BACKONE predicted values and experimental data are 0.20% for sub-cooled liquid density and 0.56% for gaseous pressure.
Prediction of Reduction Potentials of Copper Proteins with Continuum Electrostatics and Density Functional Theory.

PubMed

Fowler, Nicholas J; Blanford, Christopher F; Warwicker, Jim; de Visser, Sam P

2017-11-02

Blue copper proteins, such as azurin, show dramatic changes in Cu 2+ /Cu + reduction potential upon mutation over the full physiological range. Hence, they have important functions in electron transfer and oxidation chemistry and have applications in industrial biotechnology. The details of what determines these reduction potential changes upon mutation are still unclear. Moreover, it has been difficult to model and predict the reduction potential of azurin mutants and currently no unique procedure or workflow pattern exists. Furthermore, high-level computational methods can be accurate but are too time consuming for practical use. In this work, a novel approach for calculating reduction potentials of azurin mutants is shown, based on a combination of continuum electrostatics, density functional theory and empirical hydrophobicity factors. Our method accurately reproduces experimental reduction potential changes of 30 mutants with respect to wildtype within experimental error and highlights the factors contributing to the reduction potential change. Finally, reduction potentials are predicted for a series of 124 new mutants that have not yet been investigated experimentally. Several mutants are identified that are located well over 10 Å from the copper center that change the reduction potential by more than 85 mV. The work shows that secondary coordination sphere mutations mostly lead to long-range electrostatic changes and hence can be modeled accurately with continuum electrostatics. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Prediction of the mass gain during high temperature oxidation of aluminized nanostructured nickel using adaptive neuro-fuzzy inference system

NASA Astrophysics Data System (ADS)

Hayati, M.; Rashidi, A. M.; Rezaei, A.

2012-10-01

In this paper, the applicability of ANFIS as an accurate model for the prediction of the mass gain during high temperature oxidation using experimental data obtained for aluminized nanostructured (NS) nickel is presented. For developing the model, exposure time and temperature are taken as input and the mass gain as output. A hybrid learning algorithm consists of back-propagation and least-squares estimation is used for training the network. We have compared the proposed ANFIS model with experimental data. The predicted data are found to be in good agreement with the experimental data with mean relative error less than 1.1%. Therefore, we can use ANFIS model to predict the performances of thermal systems in engineering applications, such as modeling the mass gain for NS materials.
Investigation of Periodic Pitching through the Static Stall Angle of Attack.

DTIC Science & Technology

1987-03-01

been completed to characterize and predict the dynamic stall process. In 1968 Ham (Ref 11) completed a study to explain the torsional oscillation of...peak values of l.:t and moment could be predicted accurately, but the model did not predict when the peaks would occur. Another problem with the...model was that it required input from experimental results to tell when leading edge vortex separation occurred. The prediction of when vortex shedding
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.
Investigation on the heat transfer characteristics during flow boiling of liquefied natural gas in a vertical micro-fin tube

NASA Astrophysics Data System (ADS)

Xu, Bin; Shi, Yumei; Chen, Dongsheng

2014-03-01

This paper presents an experimental investigation on the heat transfer characteristics of liquefied natural gas flow boiling in a vertical micro-fin tube. The effect of heat flux, mass flux and inlet pressure on the flow boiling heat transfer coefficients was analyzed. The Kim, Koyama, and two kinds of Wellsandt correlations with different Ftp coefficients were used to predict the flow boiling heat transfer coefficients. The predicted results showed that the Koyama correlation was the most accurate over the range of experimental conditions.
Using Machine Learning to Predict MCNP Bias

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

Grechanuk, Pavel Aleksandrovi

For many real-world applications in radiation transport where simulations are compared to experimental measurements, like in nuclear criticality safety, the bias (simulated - experimental k eff) in the calculation is an extremely important quantity used for code validation. The objective of this project is to accurately predict the bias of MCNP6 [1] criticality calculations using machine learning (ML) algorithms, with the intention of creating a tool that can complement the current nuclear criticality safety methods. In the latest release of MCNP6, the Whisper tool is available for criticality safety analysts and includes a large catalogue of experimental benchmarks, sensitivity profiles,more » and nuclear data covariance matrices. This data, coming from 1100+ benchmark cases, is used in this study of ML algorithms for criticality safety bias predictions.« less
Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

DOE PAGES

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.; ...

2018-01-17

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less
Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

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

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less
Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

PubMed Central

Hoyt, David W.; Nicora, Carrie D.; Kinmonth-Schultz, Hannah A.; Ward, Joy K.

2018-01-01

We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS2), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS2 approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases. PMID:29342073
Prediction of Scour below Flip Bucket using Soft Computing Techniques

NASA Astrophysics Data System (ADS)

Azamathulla, H. Md.; Ab Ghani, Aminuddin; Azazi Zakaria, Nor

2010-05-01

The accurate prediction of the depth of scour around hydraulic structure (trajectory spillways) has been based on the experimental studies and the equations developed are mainly empirical in nature. This paper evaluates the performance of the soft computing (intelligence) techiques, Adaptive Neuro-Fuzzy System (ANFIS) and Genetic expression Programming (GEP) approach, in prediction of scour below a flip bucket spillway. The results are very promising, which support the use of these intelligent techniques in prediction of highly non-linear scour parameters.
Deriving biomass models for small-diameter loblolly pine on the Crossett Experimental Forest

Treesearch

K.M. McElligott; D.C. Bragg

2013-01-01

Foresters and landowners have a growing interest in carbon sequestration and cellulosic biofuels in southern pine forests, and hence need to be able to accurately predict them. To this end, we derived a set of aboveground biomass models using data from 62 small-diameter loblolly pines (Pinus taeda) sampled on the Crossett Experimental Forest in...
Experimental and numerical simulation of a rotor/stator interaction event localized on a single blade within an industrial high-pressure compressor

NASA Astrophysics Data System (ADS)

Batailly, Alain; Agrapart, Quentin; Millecamps, Antoine; Brunel, Jean-François

2016-08-01

This contribution addresses a confrontation between the experimental simulation of a rotor/stator interaction case initiated by structural contacts with numerical predictions made with an in-house numerical strategy. Contrary to previous studies carried out within the low-pressure compressor of an aircraft engine, this interaction is found to be non-divergent: high amplitudes of vibration are experimentally observed and numerically predicted over a short period of time. An in-depth analysis of experimental data first allows for a precise characterization of the interaction as a rubbing event involving the first torsional mode of a single blade. Numerical results are in good agreement with experimental observations: the critical angular speed, the wear patterns on the casing as well as the blade dynamics are accurately predicted. Through out the article, the in-house numerical strategy is also confronted to another numerical strategy that may be found in the literature for the simulation of rubbing events: key differences are underlined with respect to the prediction of non-linear interaction phenomena.
Injection-Molded Long-Fiber Thermoplastic Composites: From Process Modeling to Prediction of Mechanical Properties

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

Nguyen, Ba Nghiep; Kunc, Vlastimil; Jin, Xiaoshi

2013-12-18

This article illustrates the predictive capabilities for long-fiber thermoplastic (LFT) composites that first simulate the injection molding of LFT structures by Autodesk® Simulation Moldflow® Insight (ASMI) to accurately predict fiber orientation and length distributions in these structures. After validating fiber orientation and length predictions against the experimental data, the predicted results are used by ASMI to compute distributions of elastic properties in the molded structures. In addition, local stress-strain responses and damage accumulation under tensile loading are predicted by an elastic-plastic damage model of EMTA-NLA, a nonlinear analysis tool implemented in ABAQUS® via user-subroutines using an incremental Eshelby-Mori-Tanaka approach. Predictedmore » stress-strain responses up to failure and damage accumulations are compared to the experimental results to validate the model.« less
First-principles calculation of intrinsic defect chemistry and self-doping in PbTe

DOE PAGES

Goyal, Anuj; Gorai, Prashun; Toberer, Eric S.; ...

2017-11-10

Semiconductor dopability is inherently limited by intrinsic defect chemistry. In many thermoelectric materials, narrow band gaps due to strong spin-orbit interactions make accurate atomic level predictions of intrinsic defect chemistry and self-doping computationally challenging. For this study, we use different levels of theory to model point defects in PbTe, and compare and contrast the results against each other and a large body of experimental data. We find that to accurately reproduce the intrinsic defect chemistry and known self-doping behavior of PbTe, it is essential to (a) go beyond the semi-local GGA approximation to density functional theory, (b) include spin-orbit coupling,more » and (c) utilize many-body GW theory to describe the positions of individual band edges. The hybrid HSE functional with spin-orbit coupling included, in combination with the band edge shifts from G0W0 is the only approach that accurately captures both the intrinsic conductivity type of PbTe as function of synthesis conditions as well as the measured charge carrier concentrations, without the need for experimental inputs. Our results reaffirm the critical role of the position of individual band edges in defect calculations, and demonstrate that dopability can be accurately predicted in such challenging narrow band gap materials.« less
First-principles calculation of intrinsic defect chemistry and self-doping in PbTe

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

Goyal, Anuj; Gorai, Prashun; Toberer, Eric S.

Semiconductor dopability is inherently limited by intrinsic defect chemistry. In many thermoelectric materials, narrow band gaps due to strong spin-orbit interactions make accurate atomic level predictions of intrinsic defect chemistry and self-doping computationally challenging. For this study, we use different levels of theory to model point defects in PbTe, and compare and contrast the results against each other and a large body of experimental data. We find that to accurately reproduce the intrinsic defect chemistry and known self-doping behavior of PbTe, it is essential to (a) go beyond the semi-local GGA approximation to density functional theory, (b) include spin-orbit coupling,more » and (c) utilize many-body GW theory to describe the positions of individual band edges. The hybrid HSE functional with spin-orbit coupling included, in combination with the band edge shifts from G0W0 is the only approach that accurately captures both the intrinsic conductivity type of PbTe as function of synthesis conditions as well as the measured charge carrier concentrations, without the need for experimental inputs. Our results reaffirm the critical role of the position of individual band edges in defect calculations, and demonstrate that dopability can be accurately predicted in such challenging narrow band gap materials.« less
First-principles calculation of intrinsic defect chemistry and self-doping in PbTe

NASA Astrophysics Data System (ADS)

Goyal, Anuj; Gorai, Prashun; Toberer, Eric S.; Stevanović, Vladan

2017-10-01

Semiconductor dopability is inherently limited by intrinsic defect chemistry. In many thermoelectric materials, narrow band gaps due to strong spin-orbit interactions make accurate atomic level predictions of intrinsic defect chemistry and self-doping computationally challenging. Here we use different levels of theory to model point defects in PbTe, and compare and contrast the results against each other and a large body of experimental data. We find that to accurately reproduce the intrinsic defect chemistry and known self-doping behavior of PbTe, it is essential to (a) go beyond the semi-local GGA approximation to density functional theory, (b) include spin-orbit coupling, and (c) utilize many-body GW theory to describe the positions of individual band edges. The hybrid HSE functional with spin-orbit coupling included, in combination with the band edge shifts from G0W0 is the only approach that accurately captures both the intrinsic conductivity type of PbTe as function of synthesis conditions as well as the measured charge carrier concentrations, without the need for experimental inputs. Our results reaffirm the critical role of the position of individual band edges in defect calculations, and demonstrate that dopability can be accurately predicted in such challenging narrow band gap materials.
Thermodynamic characterization of tandem mismatches found in naturally occurring RNA

PubMed Central

Christiansen, Martha E.; Znosko, Brent M.

2009-01-01

Although all sequence symmetric tandem mismatches and some sequence asymmetric tandem mismatches have been thermodynamically characterized and a model has been proposed to predict the stability of previously unmeasured sequence asymmetric tandem mismatches [Christiansen,M.E. and Znosko,B.M. (2008) Biochemistry, 47, 4329–4336], experimental thermodynamic data for frequently occurring tandem mismatches is lacking. Since experimental data is preferred over a predictive model, the thermodynamic parameters for 25 frequently occurring tandem mismatches were determined. These new experimental values, on average, are 1.0 kcal/mol different from the values predicted for these mismatches using the previous model. The data for the sequence asymmetric tandem mismatches reported here were then combined with the data for 72 sequence asymmetric tandem mismatches that were published previously, and the parameters used to predict the thermodynamics of previously unmeasured sequence asymmetric tandem mismatches were updated. The average absolute difference between the measured values and the values predicted using these updated parameters is 0.5 kcal/mol. This updated model improves the prediction for tandem mismatches that were predicted rather poorly by the previous model. This new experimental data and updated predictive model allow for more accurate calculations of the free energy of RNA duplexes containing tandem mismatches, and, furthermore, should allow for improved prediction of secondary structure from sequence. PMID:19509311
Fatigue crack growth and life prediction under mixed-mode loading

NASA Astrophysics Data System (ADS)

Sajith, S.; Murthy, K. S. R. K.; Robi, P. S.

2018-04-01

Fatigue crack growth life as a function of crack length is essential for the prevention of catastrophic failures from damage tolerance perspective. In damage tolerance design approach, principles of fracture mechanics are usually applied to predict the fatigue life of structural components. Numerical prediction of crack growth versus number of cycles is essential in damage tolerance design. For cracks under mixed mode I/II loading, modified Paris law (d/a d N =C (ΔKe q ) m ) along with different equivalent stress intensity factor (ΔKeq) model is used for fatigue crack growth rate prediction. There are a large number of ΔKeq models available for the mixed mode I/II loading, the selection of proper ΔKeq model has significant impact on fatigue life prediction. In the present investigation, the performance of ΔKeq models in fatigue life prediction is compared with respect to the experimental findings as there are no guidelines/suggestions available on the selection of these models for accurate and/or conservative predictions of fatigue life. Within the limitations of availability of experimental data and currently available numerical simulation techniques, the results of present study attempt to outline models that would provide accurate and conservative life predictions. Such a study aid the numerical analysts or engineers in the proper selection of the model for numerical simulation of the fatigue life. Moreover, the present investigation also suggests a procedure to enhance the accuracy of life prediction using Paris law.
Going Rogue in the Spatial Cuing Paradigm: High Spatial Validity Is Insufficient to Elicit Voluntary Shifts of Attention

ERIC Educational Resources Information Center

Davis, Gregory J.; Gibson, Bradley S.

2012-01-01

Voluntary shifts of attention are often motivated in experimental contexts by using well-known symbols that accurately predict the direction of targets. The authors report 3 experiments, which showed that the presentation of predictive spatial information does not provide sufficient incentive to elicit voluntary shifts of attention. For instance,…
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.
Thermophysical properties of liquid UO2, ZrO2 and corium by molecular dynamics and predictive models

NASA Astrophysics Data System (ADS)

Kim, Woong Kee; Shim, Ji Hoon; Kaviany, Massoud

2017-08-01

Predicting the fate of accident-melted nuclear fuel-cladding requires the understanding of the thermophysical properties which are lacking or have large scatter due to high-temperature experimental challenges. Using equilibrium classical molecular dynamics (MD), we predict the properties of melted UO2 and ZrO2 and compare them with the available experimental data and the predictive models. The existing interatomic potential models have been developed mainly for the polymorphic solid phases of these oxides, so they cannot be used to predict all the properties accurately. We compare and decipher the distinctions of those MD predictions using the specific property-related autocorrelation decays. The predicted properties are density, specific heat, heat of fusion, compressibility, viscosity, surface tension, and the molecular and electronic thermal conductivities. After the comparisons, we provide readily usable temperature-dependent correlations (including UO2-ZrO2 compounds, i.e. corium melt).

Quantum Universe

NASA Astrophysics Data System (ADS)

Mukhanov, V. F.

2016-10-01

In March 2013, following an accurate processing of available measurement data, the Planck Scientific Collaboration published the highest-resolution photograph ever of the early Universe when it was only a few hundred thousand years old. The photograph showed galactic seeds in sufficient detail to test some nontrivial theoretical predictions made more than thirty years ago. Most amazing was that all predictions were confirmed to be remarkably accurate. With no exaggeration, we may consider it established experimentally that quantum physics, which is normally assumed to be relevant on the atomic and subatomic scale, also works on the scale of the entire Universe, determining its structure with all its galaxies, stars, and planets.
Modified energy cascade model adapted for a multicrop Lunar greenhouse prototype

NASA Astrophysics Data System (ADS)

Boscheri, G.; Kacira, M.; Patterson, L.; Giacomelli, G.; Sadler, P.; Furfaro, R.; Lobascio, C.; Lamantea, M.; Grizzaffi, L.

2012-10-01

Models are required to accurately predict mass and energy balances in a bioregenerative life support system. A modified energy cascade model was used to predict outputs of a multi-crop (tomatoes, potatoes, lettuce and strawberries) Lunar greenhouse prototype. The model performance was evaluated against measured data obtained from several system closure experiments. The model predictions corresponded well to those obtained from experimental measurements for the overall system closure test period (five months), especially for biomass produced (0.7% underestimated), water consumption (0.3% overestimated) and condensate production (0.5% overestimated). However, the model was less accurate when the results were compared with data obtained from a shorter experimental time period, with 31%, 48% and 51% error for biomass uptake, water consumption, and condensate production, respectively, which were obtained under more complex crop production patterns (e.g. tall tomato plants covering part of the lettuce production zones). These results, together with a model sensitivity analysis highlighted the necessity of periodic characterization of the environmental parameters (e.g. light levels, air leakage) in the Lunar greenhouse.
Global Quantitative Modeling of Chromatin Factor Interactions

PubMed Central

Zhou, Jian; Troyanskaya, Olga G.

2014-01-01

Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896
Aerodynamic analysis of the Darrieus wind turbines including dynamic-stall effects

NASA Astrophysics Data System (ADS)

Paraschivoiu, Ion; Allet, Azeddine

Experimental data for a 17-m wind turbine are compared with aerodynamic performance predictions obtained with two dynamic stall methods which are based on numerical correlations of the dynamic stall delay with the pitch rate parameter. Unlike the Gormont (1973) model, the MIT model predicts that dynamic stall does not occur in the downwind part of the turbine, although it does exist in the upwind zone. The Gormont model is shown to overestimate the aerodynamic coefficients relative to the MIT model. The MIT model is found to accurately predict the dynamic-stall regime, which is characterized by a plateau oscillating near values of the experimental data for the rotor power vs wind speed at the equator.
Navier-Stokes and Comprehensive Analysis Performance Predictions of the NREL Phase VI Experiment

NASA Technical Reports Server (NTRS)

Duque, Earl P. N.; Burklund, Michael D.; Johnson, Wayne

2003-01-01

A vortex lattice code, CAMRAD II, and a Reynolds-Averaged Navier-Stoke code, OVERFLOW-D2, were used to predict the aerodynamic performance of a two-bladed horizontal axis wind turbine. All computations were compared with experimental data that was collected at the NASA Ames Research Center 80- by 120-Foot Wind Tunnel. Computations were performed for both axial as well as yawed operating conditions. Various stall delay models and dynamics stall models were used by the CAMRAD II code. Comparisons between the experimental data and computed aerodynamic loads show that the OVERFLOW-D2 code can accurately predict the power and spanwise loading of a wind turbine rotor.
Stress enhanced calcium kinetics in a neuron.

PubMed

Kant, Aayush; Bhandakkar, Tanmay K; Medhekar, Nikhil V

2018-02-01

Accurate modeling of the mechanobiological response of a Traumatic Brain Injury is beneficial toward its effective clinical examination, treatment and prevention. Here, we present a stress history-dependent non-spatial kinetic model to predict the microscale phenomena of secondary insults due to accumulation of excess calcium ions (Ca[Formula: see text]) induced by the macroscale primary injuries. The model is able to capture the experimentally observed increase and subsequent partial recovery of intracellular Ca[Formula: see text] concentration in response to various types of mechanical impulses. We further establish the accuracy of the model by comparing our predictions with key experimental observations.
Accurate prediction of secondary metabolite gene clusters in filamentous fungi.

PubMed

Andersen, Mikael R; Nielsen, Jakob B; Klitgaard, Andreas; Petersen, Lene M; Zachariasen, Mia; Hansen, Tilde J; Blicher, Lene H; Gotfredsen, Charlotte H; Larsen, Thomas O; Nielsen, Kristian F; Mortensen, Uffe H

2013-01-02

Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify supporting enzymes for key synthases one cluster at a time. In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 of 16 known clusters and nearly accurate for the remaining 3 clusters. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (superclusters), and validate this both with legacy data and experimentally by prediction and verification of a supercluster consisting of the synthase AN1242 and the prenyltransferase AN11080, as well as identification of the product compound nidulanin A. We have used A. nidulans for our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom.
SIFTER search: a web server for accurate phylogeny-based protein function prediction

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

Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less
SIFTER search: a web server for accurate phylogeny-based protein function prediction

DOE PAGES

Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

2015-05-15

We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less
An Improved Method of Predicting Extinction Coefficients for the Determination of Protein Concentration.

PubMed

Hilario, Eric C; Stern, Alan; Wang, Charlie H; Vargas, Yenny W; Morgan, Charles J; Swartz, Trevor E; Patapoff, Thomas W

2017-01-01

Concentration determination is an important method of protein characterization required in the development of protein therapeutics. There are many known methods for determining the concentration of a protein solution, but the easiest to implement in a manufacturing setting is absorption spectroscopy in the ultraviolet region. For typical proteins composed of the standard amino acids, absorption at wavelengths near 280 nm is due to the three amino acid chromophores tryptophan, tyrosine, and phenylalanine in addition to a contribution from disulfide bonds. According to the Beer-Lambert law, absorbance is proportional to concentration and path length, with the proportionality constant being the extinction coefficient. Typically the extinction coefficient of proteins is experimentally determined by measuring a solution absorbance then experimentally determining the concentration, a measurement with some inherent variability depending on the method used. In this study, extinction coefficients were calculated based on the measured absorbance of model compounds of the four amino acid chromophores. These calculated values for an unfolded protein were then compared with an experimental concentration determination based on enzymatic digestion of proteins. The experimentally determined extinction coefficient for the native proteins was consistently found to be 1.05 times the calculated value for the unfolded proteins for a wide range of proteins with good accuracy and precision under well-controlled experimental conditions. The value of 1.05 times the calculated value was termed the predicted extinction coefficient. Statistical analysis shows that the differences between predicted and experimentally determined coefficients are scattered randomly, indicating no systematic bias between the values among the proteins measured. The predicted extinction coefficient was found to be accurate and not subject to the inherent variability of experimental methods. We propose the use of a predicted extinction coefficient for determining the protein concentration of therapeutic proteins starting from early development through the lifecycle of the product. LAY ABSTRACT: Knowing the concentration of a protein in a pharmaceutical solution is important to the drug's development and posology. There are many ways to determine the concentration, but the easiest one to use in a testing lab employs absorption spectroscopy. Absorbance of ultraviolet light by a protein solution is proportional to its concentration and path length; the proportionality constant is the extinction coefficient. The extinction coefficient of a protein therapeutic is usually determined experimentally during early product development and has some inherent method variability. In this study, extinction coefficients of several proteins were calculated based on the measured absorbance of model compounds. These calculated values for an unfolded protein were then compared with experimental concentration determinations based on enzymatic digestion of the proteins. The experimentally determined extinction coefficient for the native protein was 1.05 times the calculated value for the unfolded protein with good accuracy and precision under controlled experimental conditions, so the value of 1.05 times the calculated coefficient was called the predicted extinction coefficient. Comparison of predicted and measured extinction coefficients indicated that the predicted value was very close to the experimentally determined values for the proteins. The predicted extinction coefficient was accurate and removed the variability inherent in experimental methods. © PDA, Inc. 2017.
Development of a Skin Burn Predictive Model adapted to Laser Irradiation

NASA Astrophysics Data System (ADS)

Sonneck-Museux, N.; Scheer, E.; Perez, L.; Agay, D.; Autrique, L.

2016-12-01

Laser technology is increasingly used, and it is crucial for both safety and medical reasons that the impact of laser irradiation on human skin can be accurately predicted. This study is mainly focused on laser-skin interactions and potential lesions (burns). A mathematical model dedicated to heat transfers in skin exposed to infrared laser radiations has been developed. The model is validated by studying heat transfers in human skin and simultaneously performing experimentations an animal model (pig). For all experimental tests, pig's skin surface temperature is recorded. Three laser wavelengths have been tested: 808 nm, 1940 nm and 10 600 nm. The first is a diode laser producing radiation absorbed deep within the skin. The second wavelength has a more superficial effect. For the third wavelength, skin is an opaque material. The validity of the developed models is verified by comparison with experimental results (in vivo tests) and the results of previous studies reported in the literature. The comparison shows that the models accurately predict the burn degree caused by laser radiation over a wide range of conditions. The results show that the important parameter for burn prediction is the extinction coefficient. For the 1940 nm wavelength especially, significant differences between modeling results and literature have been observed, mainly due to this coefficient's value. This new model can be used as a predictive tool in order to estimate the amount of injury induced by several types (couple power-time) of laser aggressions on the arm, the face and on the palm of the hand.
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.
Finite Element Model of the Knee for Investigation of Injury Mechanisms: Development and Validation

PubMed Central

Kiapour, Ali; Kiapour, Ata M.; Kaul, Vikas; Quatman, Carmen E.; Wordeman, Samuel C.; Hewett, Timothy E.; Demetropoulos, Constantine K.; Goel, Vijay K.

2014-01-01

Multiple computational models have been developed to study knee biomechanics. However, the majority of these models are mainly validated against a limited range of loading conditions and/or do not include sufficient details of the critical anatomical structures within the joint. Due to the multifactorial dynamic nature of knee injuries, anatomic finite element (FE) models validated against multiple factors under a broad range of loading conditions are necessary. This study presents a validated FE model of the lower extremity with an anatomically accurate representation of the knee joint. The model was validated against tibiofemoral kinematics, ligaments strain/force, and articular cartilage pressure data measured directly from static, quasi-static, and dynamic cadaveric experiments. Strong correlations were observed between model predictions and experimental data (r > 0.8 and p < 0.0005 for all comparisons). FE predictions showed low deviations (root-mean-square (RMS) error) from average experimental data under all modes of static and quasi-static loading, falling within 2.5 deg of tibiofemoral rotation, 1% of anterior cruciate ligament (ACL) and medial collateral ligament (MCL) strains, 17 N of ACL load, and 1 mm of tibiofemoral center of pressure. Similarly, the FE model was able to accurately predict tibiofemoral kinematics and ACL and MCL strains during simulated bipedal landings (dynamic loading). In addition to minimal deviation from direct cadaveric measurements, all model predictions fell within 95% confidence intervals of the average experimental data. Agreement between model predictions and experimental data demonstrates the ability of the developed model to predict the kinematics of the human knee joint as well as the complex, nonuniform stress and strain fields that occur in biological soft tissue. Such a model will facilitate the in-depth understanding of a multitude of potential knee injury mechanisms with special emphasis on ACL injury. PMID:24763546
Discriminative prediction of mammalian enhancers from DNA sequence

PubMed Central

Lee, Dongwon; Karchin, Rachel; Beer, Michael A.

2011-01-01

Accurately predicting regulatory sequences and enhancers in entire genomes is an important but difficult problem, especially in large vertebrate genomes. With the advent of ChIP-seq technology, experimental detection of genome-wide EP300/CREBBP bound regions provides a powerful platform to develop predictive tools for regulatory sequences and to study their sequence properties. Here, we develop a support vector machine (SVM) framework which can accurately identify EP300-bound enhancers using only genomic sequence and an unbiased set of general sequence features. Moreover, we find that the predictive sequence features identified by the SVM classifier reveal biologically relevant sequence elements enriched in the enhancers, but we also identify other features that are significantly depleted in enhancers. The predictive sequence features are evolutionarily conserved and spatially clustered, providing further support of their functional significance. Although our SVM is trained on experimental data, we also predict novel enhancers and show that these putative enhancers are significantly enriched in both ChIP-seq signal and DNase I hypersensitivity signal in the mouse brain and are located near relevant genes. Finally, we present results of comparisons between other EP300/CREBBP data sets using our SVM and uncover sequence elements enriched and/or depleted in the different classes of enhancers. Many of these sequence features play a role in specifying tissue-specific or developmental-stage-specific enhancer activity, but our results indicate that some features operate in a general or tissue-independent manner. In addition to providing a high confidence list of enhancer targets for subsequent experimental investigation, these results contribute to our understanding of the general sequence structure of vertebrate enhancers. PMID:21875935
An integrated physiology model to study regional lung damage effects and the physiologic response

PubMed Central

2014-01-01

Background This work expands upon a previously developed exercise dynamic physiology model (DPM) with the addition of an anatomic pulmonary system in order to quantify the impact of lung damage on oxygen transport and physical performance decrement. Methods A pulmonary model is derived with an anatomic structure based on morphometric measurements, accounting for heterogeneous ventilation and perfusion observed experimentally. The model is incorporated into an existing exercise physiology model; the combined system is validated using human exercise data. Pulmonary damage from blast, blunt trauma, and chemical injury is quantified in the model based on lung fluid infiltration (edema) which reduces oxygen delivery to the blood. The pulmonary damage component is derived and calibrated based on published animal experiments; scaling laws are used to predict the human response to lung injury in terms of physical performance decrement. Results The augmented dynamic physiology model (DPM) accurately predicted the human response to hypoxia, altitude, and exercise observed experimentally. The pulmonary damage parameters (shunt and diffusing capacity reduction) were fit to experimental animal data obtained in blast, blunt trauma, and chemical damage studies which link lung damage to lung weight change; the model is able to predict the reduced oxygen delivery in damage conditions. The model accurately estimates physical performance reduction with pulmonary damage. Conclusions We have developed a physiologically-based mathematical model to predict performance decrement endpoints in the presence of thoracic damage; simulations can be extended to estimate human performance and escape in extreme situations. PMID:25044032
Prediction of noise field of a propfan at angle of attack

NASA Technical Reports Server (NTRS)

Envia, Edmane

1991-01-01

A method for predicting the noise field of a propfan operating at an angle of attack to the oncoming flow is presented. The method takes advantage of the high-blade-count of the advanced propeller designs to provide an accurate and efficient formula for predicting their noise field. The formula, which is written in terms of the Airy function and its derivative, provides a very attractive alternative to the use of numerical integration. A preliminary comparison shows rather favorable agreement between the predictions from the present method and the experimental data.
Accuracy of color prediction of anthraquinone dyes in methanol solution estimated from first principle quantum chemistry computations.

PubMed

Cysewski, Piotr; Jeliński, Tomasz

2013-10-01

The electronic spectrum of four different anthraquinones (1,2-dihydroxyanthraquinone, 1-aminoanthraquinone, 2-aminoanthraquinone and 1-amino-2-methylanthraquinone) in methanol solution was measured and used as reference data for theoretical color prediction. The visible part of the spectrum was modeled according to TD-DFT framework with a broad range of DFT functionals. The convoluted theoretical spectra were validated against experimental data by a direct color comparison in terms of CIE XYZ and CIE Lab tristimulus model color. It was found, that the 6-31G** basis set provides the most accurate color prediction and there is no need to extend the basis set since it does not improve the prediction of color. Although different functionals were found to give the most accurate color prediction for different anthraquinones, it is possible to apply the same DFT approach for the whole set of analyzed dyes. Especially three functionals seem to be valuable, namely mPW1LYP, B1LYP and PBE0 due to very similar spectra predictions. The major source of discrepancies between theoretical and experimental spectra comes from L values, representing the lightness, and the a parameter, depicting the position on green→magenta axis. Fortunately, the agreement between computed and observed blue→yellow axis (parameter b) is very precise in the case of studied anthraquinone dyes in methanol solution. Despite discussed shortcomings, color prediction from first principle quantum chemistry computations can lead to quite satisfactory results, expressed in terms of color space parameters.
A link prediction approach to cancer drug sensitivity prediction.

PubMed

Turki, Turki; Wei, Zhi

2017-10-03

Predicting the response to a drug for cancer disease patients based on genomic information is an important problem in modern clinical oncology. This problem occurs in part because many available drug sensitivity prediction algorithms do not consider better quality cancer cell lines and the adoption of new feature representations; both lead to the accurate prediction of drug responses. By predicting accurate drug responses to cancer, oncologists gain a more complete understanding of the effective treatments for each patient, which is a core goal in precision medicine. In this paper, we model cancer drug sensitivity as a link prediction, which is shown to be an effective technique. We evaluate our proposed link prediction algorithms and compare them with an existing drug sensitivity prediction approach based on clinical trial data. The experimental results based on the clinical trial data show the stability of our link prediction algorithms, which yield the highest area under the ROC curve (AUC) and are statistically significant. We propose a link prediction approach to obtain new feature representation. Compared with an existing approach, the results show that incorporating the new feature representation to the link prediction algorithms has significantly improved the performance.
Experimental annotation of the human genome using microarray technology.

PubMed

Shoemaker, D D; Schadt, E E; Armour, C D; He, Y D; Garrett-Engele, P; McDonagh, P D; Loerch, P M; Leonardson, A; Lum, P Y; Cavet, G; Wu, L F; Altschuler, S J; Edwards, S; King, J; Tsang, J S; Schimmack, G; Schelter, J M; Koch, J; Ziman, M; Marton, M J; Li, B; Cundiff, P; Ward, T; Castle, J; Krolewski, M; Meyer, M R; Mao, M; Burchard, J; Kidd, M J; Dai, H; Phillips, J W; Linsley, P S; Stoughton, R; Scherer, S; Boguski, M S

2001-02-15

The most important product of the sequencing of a genome is a complete, accurate catalogue of genes and their products, primarily messenger RNA transcripts and their cognate proteins. Such a catalogue cannot be constructed by computational annotation alone; it requires experimental validation on a genome scale. Using 'exon' and 'tiling' arrays fabricated by ink-jet oligonucleotide synthesis, we devised an experimental approach to validate and refine computational gene predictions and define full-length transcripts on the basis of co-regulated expression of their exons. These methods can provide more accurate gene numbers and allow the detection of mRNA splice variants and identification of the tissue- and disease-specific conditions under which genes are expressed. We apply our technique to chromosome 22q under 69 experimental condition pairs, and to the entire human genome under two experimental conditions. We discuss implications for more comprehensive, consistent and reliable genome annotation, more efficient, full-length complementary DNA cloning strategies and application to complex diseases.
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.

Predicting Transport of 3,5,6-Trichloro-2-Pyridinol Into Saliva Using a Combination Experimental and Computational Approach

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

Smith, Jordan Ned; Carver, Zana A.; Weber, Thomas J.

A combination experimental and computational approach was developed to predict chemical transport into saliva. A serous-acinar chemical transport assay was established to measure chemical transport with non-physiological (standard cell culture medium) and physiological (using surrogate plasma and saliva medium) conditions using 3,5,6-trichloro-2-pyridinol (TCPy) a metabolite of the pesticide chlorpyrifos. High levels of TCPy protein binding was observed in cell culture medium and rat plasma resulting in different TCPy transport behaviors in the two experimental conditions. In the non-physiological transport experiment, TCPy reached equilibrium at equivalent concentrations in apical and basolateral chambers. At higher TCPy doses, increased unbound TCPy was observed,more » and TCPy concentrations in apical and basolateral chambers reached equilibrium faster than lower doses, suggesting only unbound TCPy is able to cross the cellular monolayer. In the physiological experiment, TCPy transport was slower than non-physiological conditions, and equilibrium was achieved at different concentrations in apical and basolateral chambers at a comparable ratio (0.034) to what was previously measured in rats dosed with TCPy (saliva:blood ratio: 0.049). A cellular transport computational model was developed based on TCPy protein binding kinetics and accurately simulated all transport experiments using different permeability coefficients for the two experimental conditions (1.4 vs 0.4 cm/hr for non-physiological and physiological experiments, respectively). The computational model was integrated into a physiologically based pharmacokinetic (PBPK) model and accurately predicted TCPy concentrations in saliva of rats dosed with TCPy. Overall, this study demonstrates an approach to predict chemical transport in saliva potentially increasing the utility of salivary biomonitoring in the future.« less
Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

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

Ansong, Charles; Tolic, Nikola; Purvine, Samuel O.

Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. For example systems biology-oriented genome scale modeling efforts greatly benefit from accurate annotation of protein-coding genes to develop proper functioning models. However, determining protein-coding genes for most new genomes is almost completely performed by inference, using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. With the ability to directly measure peptides arising from expressed proteins, mass spectrometry-based proteomics approaches can be used to augment and verify codingmore » regions of a genomic sequence and importantly detect post-translational processing events. In this study we utilized “shotgun” proteomics to guide accurate primary genome annotation of the bacterial pathogen Salmonella Typhimurium 14028 to facilitate a systems-level understanding of Salmonella biology. The data provides protein-level experimental confirmation for 44% of predicted protein-coding genes, suggests revisions to 48 genes assigned incorrect translational start sites, and uncovers 13 non-annotated genes missed by gene prediction programs. We also present a comprehensive analysis of post-translational processing events in Salmonella, revealing a wide range of complex chemical modifications (70 distinct modifications) and confirming more than 130 signal peptide and N-terminal methionine cleavage events in Salmonella. This study highlights several ways in which proteomics data applied during the primary stages of annotation can improve the quality of genome annotations, especially with regards to the annotation of mature protein products.« less
Secondary wastewater polishing with ultrafiltration membranes for unrestricted reuse: fouling and flushing modeling.

PubMed

Gillerman, Leonid; Bick, Amos; Buriakovsky, Nisan; Oron, Gideon

2006-11-01

The effects of operating parameters such astransmembrane pressure, retentate, and recirculation volumetric flow rates on the productivity of an ultrafiltration membrane were studied using field data and development of a management model. Correlation equations for predicting the volumetric permeate flow rates were derived from general membrane blocking laws and experimental data. The experimental data were obtained from a pilot study carried out in the Arad wastewater treatment system (a pilot plant operating in feed and bleed operation mode) located several kilometers west of the City of Arad, Israel. Correlation predictions were confirmed with the independent experimental results. The results enabled us to develop a mathematical expression accurately describing the decline in flux due to fouling.
From Pore to Core: Do Engineered Nanoparticles Violate Upscaling Assumptions? A Microtomographic Investigation

NASA Astrophysics Data System (ADS)

Molnar, I. L.; O'Carroll, D. M.; Gerhard, J.; Willson, C. S.

2014-12-01

The recent success in using Synchrotron X-ray Computed Microtomography (SXCMT) for the quantification of nanoparticle concentrations within real, three-dimensional pore networks [1] has opened up new opportunities for collecting experimental data of pore-scale flow and transport processes. One opportunity is coupling SXCMT with nanoparticle/soil transport experiments to provide unique insights into how pore-scale processes influence transport at larger scales. Understanding these processes is a key step in accurately upscaling micron-scale phenomena to the continuum-scale. Upscaling phenomena from the micron-scale to the continuum-scale typically involves the assumption that the pore space is well mixed. Using this 'well mixed assumption' it is implicitly assumed that the distribution of nanoparticles within the pore does not affect its retention by soil grains. This assumption enables the use of volume-averaged parameters in calculating transport and retention rates. However, in some scenarios, the well mixed assumption will likely be violated by processes such as deposition and diffusion. These processes can alter the distribution of the nanoparticles in the pore space and impact retention behaviour, leading to discrepancies between theoretical predictions and experimental observations. This work investigates the well mixed assumption by employing SXCMT to experimentally examine pore-scale mixing of silver nanoparticles during transport through sand packed columns. Silver nanoparticles were flushed through three different sands to examine the impact of grain distribution and nanoparticle retention rates on mixing: uniform silica (low retention), well graded silica sand (low retention) and uniform iron oxide coated silica sand (high retention). The SXCMT data identified diffusion-limited retention as responsible for violations of the well mixed assumption. A mathematical description of the diffusion-limited retention process was created and compared to the experimental data at the pore and column-scale. The mathematical description accurately predicted trends observed within the SXCMT-datasets such as concentration gradients away from grain surfaces and also accurately predicted total retention of nanoparticles at the column scale. 1. ES&T 2014, 48, (2), 1114-1122.
Overview of aerothermodynamic loads definition study

NASA Technical Reports Server (NTRS)

Gaugler, Raymond E.

1991-01-01

The objective of the Aerothermodynamic Loads Definition Study is to develop methods of accurately predicting the operating environment in advanced Earth-to-Orbit (ETO) propulsion systems, such as the Space Shuttle Main Engine (SSME) powerhead. Development of time averaged and time dependent three dimensional viscous computer codes as well as experimental verification and engine diagnostic testing are considered to be essential in achieving that objective. Time-averaged, nonsteady, and transient operating loads must all be well defined in order to accurately predict powerhead life. Described here is work in unsteady heat flow analysis, improved modeling of preburner flow, turbulence modeling for turbomachinery, computation of three dimensional flow with heat transfer, and unsteady viscous multi-blade row turbine analysis.
Current State and Future Perspectives in QSAR Models to Predict Blood- Brain Barrier Penetration in Central Nervous System Drug R&D.

PubMed

Morales, Juan F; Montoto, Sebastian Scioli; Fagiolino, Pietro; Ruiz, Maria E

2017-01-01

The Blood-Brain Barrier (BBB) is a physical and biochemical barrier that restricts the entry of certain drugs to the Central Nervous System (CNS), while allowing the passage of others. The ability to predict the permeability of a given molecule through the BBB is a key aspect in CNS drug discovery and development, since neurotherapeutic agents with molecular targets in the CNS should be able to cross the BBB, whereas peripherally acting agents should not, to minimize the risk of CNS adverse effects. In this review we examine and discuss QSAR approaches and current availability of experimental data for the construction of BBB permeability predictive models, focusing on the modeling of the biorelevant parameter unbound partitioning coefficient (Kp,uu). Emphasis is made on two possible strategies to overcome the current limitations of in silico models: considering the prediction of brain penetration as a multifactorial problem, and increasing experimental datasets through accurate and standardized experimental techniques.
Experimental verification of the Neuber relation at room and elevated temperatures. M.S. Thesis; [to predict stress-strain behavior in notched specimens of hastelloy x

NASA Technical Reports Server (NTRS)

Lucas, L. J.

1982-01-01

The accuracy of the Neuber equation at room temperature and 1,200 F as experimentally determined under cyclic load conditions with hold times. All strains were measured with an interferometric technique at both the local and remote regions of notched specimens. At room temperature, strains were obtained for the initial response at one load level and for cyclically stable conditions at four load levels. Stresses in notched members were simulated by subjecting smooth specimens to he same strains as were recorded on the notched specimen. Local stress-strain response was then predicted with excellent accuracy by subjecting a smooth specimen to limits established by the Neuber equation. Data at 1,200 F were obtained with the same experimental techniques but only in the cyclically stable conditions. The Neuber prediction at this temperature gave relatively accurate results in terms of predicting stress and strain points.
Research study demonstrates computer simulation can predict warpage and assist in its elimination

NASA Astrophysics Data System (ADS)

Glozer, G.; Post, S.; Ishii, K.

1994-10-01

Programs for predicting warpage in injection molded parts are relatively new. Commercial software for simulating the flow and cooling stages of injection molding have steadily gained acceptance; however, warpage software is not yet as readily accepted. This study focused on gaining an understanding of the predictive capabilities of the warpage software. The following aspects of this study were unique. (1) Quantitative results were found using a statistically designed set of experiments. (2) Comparisons between experimental and simulation results were made with parts produced in a well-instrumented and controlled injection molding machine. (3) The experimental parts were accurately measured on a coordinate measuring machine with a non-contact laser probe. (4) The effect of part geometry on warpage was investigated.
Experimental demonstration of Klyshko's advanced-wave picture using a coincidence-count based, camera-enabled imaging system

NASA Astrophysics Data System (ADS)

Aspden, Reuben S.; Tasca, Daniel S.; Forbes, Andrew; Boyd, Robert W.; Padgett, Miles J.

2014-04-01

The Klyshko advanced-wave picture is a well-known tool useful in the conceptualisation of parametric down-conversion (SPDC) experiments. Despite being well-known and understood, there have been few experimental demonstrations illustrating its validity. Here, we present an experimental demonstration of this picture using a time-gated camera in an image-based coincidence measurement. We show an excellent agreement between the spatial distributions as predicted by the Klyshko picture and those obtained using the SPDC photon pairs. An interesting speckle feature is present in the Klyshko predictive images due to the spatial coherence of the back-propagated beam in the multi-mode fibre. This effect can be removed by mechanically twisting the fibre, thus degrading the spatial coherence of the beam and time-averaging the speckle pattern, giving an accurate correspondence between the predictive and SPDC images.
Capabilities of LEWICE 1.6 and Comparison With Experimental Data

DOT National Transportation Integrated Search

1996-01-01

A research project is underway at NASA Lewis to produce a computer code which can accurately predict ice growth under any meteorological conditions for any aircraft surface. The most recent release of this code is LEWICE 1.6. This paper will demonstr...
A Summary of Validation Results for LEWICE 2.0

NASA Technical Reports Server (NTRS)

Wright, William B.

1998-01-01

A research project is underway at NASA Lewis to produce a computer code which can accurately predict ice growth under any meteorological conditions for any aircraft surface. This report will present results from version 2.0 of this code, which is called LEWICE. This version differs from previous releases due to its robustness and its ability to reproduce results accurately for different point spacing, and time step criteria across general computing platforms. It also differs in the extensive amount of effort undertaken to compare the results in a quantifiable manner against the database of ice shapes which have been generated in the NASA Lewis Icing, Research Tunnel (IRT), The complete set of data used for this comparison is available in a recent contractor report . The result of this comparison shows that the difference between the predicted ice shape from LEWICE 2.0 and the average of the experimental data is 7.2% while the variability of the experimental data is 2.5%.
Hybrid density functional theory band structure engineering in hematite

NASA Astrophysics Data System (ADS)

Pozun, Zachary D.; Henkelman, Graeme

2011-06-01

We present a hybrid density functional theory (DFT) study of doping effects in α-Fe2O3, hematite. Standard DFT underestimates the band gap by roughly 75% and incorrectly identifies hematite as a Mott-Hubbard insulator. Hybrid DFT accurately predicts the proper structural, magnetic, and electronic properties of hematite and, unlike the DFT+U method, does not contain d-electron specific empirical parameters. We find that using a screened functional that smoothly transitions from 12% exact exchange at short ranges to standard DFT at long range accurately reproduces the experimental band gap and other material properties. We then show that the antiferromagnetic symmetry in the pure α-Fe2O3 crystal is broken by all dopants and that the ligand field theory correctly predicts local magnetic moments on the dopants. We characterize the resulting band gaps for hematite doped by transition metals and the p-block post-transition metals. The specific case of Pd doping is investigated in order to correlate calculated doping energies and optical properties with experimentally observed photocatalytic behavior.
Investigation on temporal evolution of the grain refinement in copper under high strain rate loading via in-situ synchrotron measurement and predictive modeling

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

Shah, Pooja Nitin; Shin, Yung C.; Sun, Tao

Synchrotron X-rays are integrated with a modified Kolsky tension bar to conduct in situ tracking of the grain refinement mechanism operating during the dynamic deformation of metals. Copper with an initial average grain size of 36 μm is refined to 6.3 μm when loaded at a constant high strain rate of 1200 s -1. The synchrotron measurements revealed the temporal evolution of the grain refinement mechanism in terms of the initiation and rate of refinement throughout the loading test. A multiscale coupled probabilistic cellular automata based recrystallization model has been developed to predict the microstructural evolution occurring during dynamic deformationmore » processes. The model accurately predicts the initiation of the grain refinement mechanism with a predicted final average grain size of 2.4 μm. As a result, the model also accurately predicts the temporal evolution in terms of the initiation and extent of refinement when compared with the experimental results.« less
Investigation on temporal evolution of the grain refinement in copper under high strain rate loading via in-situ synchrotron measurement and predictive modeling

DOE PAGES

Shah, Pooja Nitin; Shin, Yung C.; Sun, Tao

2017-10-03

Synchrotron X-rays are integrated with a modified Kolsky tension bar to conduct in situ tracking of the grain refinement mechanism operating during the dynamic deformation of metals. Copper with an initial average grain size of 36 μm is refined to 6.3 μm when loaded at a constant high strain rate of 1200 s -1. The synchrotron measurements revealed the temporal evolution of the grain refinement mechanism in terms of the initiation and rate of refinement throughout the loading test. A multiscale coupled probabilistic cellular automata based recrystallization model has been developed to predict the microstructural evolution occurring during dynamic deformationmore » processes. The model accurately predicts the initiation of the grain refinement mechanism with a predicted final average grain size of 2.4 μm. As a result, the model also accurately predicts the temporal evolution in terms of the initiation and extent of refinement when compared with the experimental results.« less
Uncertainty quantification and validation of 3D lattice scaffolds for computer-aided biomedical applications.

PubMed

Gorguluarslan, Recep M; Choi, Seung-Kyum; Saldana, Christopher J

2017-07-01

A methodology is proposed for uncertainty quantification and validation to accurately predict the mechanical response of lattice structures used in the design of scaffolds. Effective structural properties of the scaffolds are characterized using a developed multi-level stochastic upscaling process that propagates the quantified uncertainties at strut level to the lattice structure level. To obtain realistic simulation models for the stochastic upscaling process and minimize the experimental cost, high-resolution finite element models of individual struts were reconstructed from the micro-CT scan images of lattice structures which are fabricated by selective laser melting. The upscaling method facilitates the process of determining homogenized strut properties to reduce the computational cost of the detailed simulation model for the scaffold. Bayesian Information Criterion is utilized to quantify the uncertainties with parametric distributions based on the statistical data obtained from the reconstructed strut models. A systematic validation approach that can minimize the experimental cost is also developed to assess the predictive capability of the stochastic upscaling method used at the strut level and lattice structure level. In comparison with physical compression test results, the proposed methodology of linking the uncertainty quantification with the multi-level stochastic upscaling method enabled an accurate prediction of the elastic behavior of the lattice structure with minimal experimental cost by accounting for the uncertainties induced by the additive manufacturing process. Copyright © 2017 Elsevier Ltd. All rights reserved.
High accuracy operon prediction method based on STRING database scores.

PubMed

Taboada, Blanca; Verde, Cristina; Merino, Enrique

2010-07-01

We present a simple and highly accurate computational method for operon prediction, based on intergenic distances and functional relationships between the protein products of contiguous genes, as defined by STRING database (Jensen,L.J., Kuhn,M., Stark,M., Chaffron,S., Creevey,C., Muller,J., Doerks,T., Julien,P., Roth,A., Simonovic,M. et al. (2009) STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res., 37, D412-D416). These two parameters were used to train a neural network on a subset of experimentally characterized Escherichia coli and Bacillus subtilis operons. Our predictive model was successfully tested on the set of experimentally defined operons in E. coli and B. subtilis, with accuracies of 94.6 and 93.3%, respectively. As far as we know, these are the highest accuracies ever obtained for predicting bacterial operons. Furthermore, in order to evaluate the predictable accuracy of our model when using an organism's data set for the training procedure, and a different organism's data set for testing, we repeated the E. coli operon prediction analysis using a neural network trained with B. subtilis data, and a B. subtilis analysis using a neural network trained with E. coli data. Even for these cases, the accuracies reached with our method were outstandingly high, 91.5 and 93%, respectively. These results show the potential use of our method for accurately predicting the operons of any other organism. Our operon predictions for fully-sequenced genomes are available at http://operons.ibt.unam.mx/OperonPredictor/.
A Computational Fluid Dynamics Study of Transitional Flows in Low-Pressure Turbines under a Wide Range of Operating Conditions

NASA Technical Reports Server (NTRS)

Suzen, Y. B.; Huang, P. G.; Ashpis, D. E.; Volino, R. J.; Corke, T. C.; Thomas, F. O.; Huang, J.; Lake, J. P.; King, P. I.

2007-01-01

A transport equation for the intermittency factor is employed to predict the transitional flows in low-pressure turbines. The intermittent behavior of the transitional flows is taken into account and incorporated into computations by modifying the eddy viscosity, mu(sub p) with the intermittency factor, gamma. Turbulent quantities are predicted using Menter's two-equation turbulence model (SST). The intermittency factor is obtained from a transport equation model which can produce both the experimentally observed streamwise variation of intermittency and a realistic profile in the cross stream direction. The model had been previously validated against low-pressure turbine experiments with success. In this paper, the model is applied to predictions of three sets of recent low-pressure turbine experiments on the Pack B blade to further validate its predicting capabilities under various flow conditions. Comparisons of computational results with experimental data are provided. Overall, good agreement between the experimental data and computational results is obtained. The new model has been shown to have the capability of accurately predicting transitional flows under a wide range of low-pressure turbine conditions.
Folding molecular dynamics simulations accurately predict the effect of mutations on the stability and structure of a vammin-derived peptide.

PubMed

Koukos, Panagiotis I; Glykos, Nicholas M

2014-08-28

Folding molecular dynamics simulations amounting to a grand total of 4 μs of simulation time were performed on two peptides (with native and mutated sequences) derived from loop 3 of the vammin protein and the results compared with the experimentally known peptide stabilities and structures. The simulations faithfully and accurately reproduce the major experimental findings and show that (a) the native peptide is mostly disordered in solution, (b) the mutant peptide has a well-defined and stable structure, and (c) the structure of the mutant is an irregular β-hairpin with a non-glycine β-bulge, in excellent agreement with the peptide's known NMR structure. Additionally, the simulations also predict the presence of a very small β-hairpin-like population for the native peptide but surprisingly indicate that this population is structurally more similar to the structure of the native peptide as observed in the vammin protein than to the NMR structure of the isolated mutant peptide. We conclude that, at least for the given system, force field, and simulation protocol, folding molecular dynamics simulations appear to be successful in reproducing the experimentally accessible physical reality to a satisfactory level of detail and accuracy.
Protein asparagine deamidation prediction based on structures with machine learning methods.

PubMed

Jia, Lei; Sun, Yaxiong

2017-01-01

Chemical stability is a major concern in the development of protein therapeutics due to its impact on both efficacy and safety. Protein "hotspots" are amino acid residues that are subject to various chemical modifications, including deamidation, isomerization, glycosylation, oxidation etc. A more accurate prediction method for potential hotspot residues would allow their elimination or reduction as early as possible in the drug discovery process. In this work, we focus on prediction models for asparagine (Asn) deamidation. Sequence-based prediction method simply identifies the NG motif (amino acid asparagine followed by a glycine) to be liable to deamidation. It still dominates deamidation evaluation process in most pharmaceutical setup due to its convenience. However, the simple sequence-based method is less accurate and often causes over-engineering a protein. We introduce structure-based prediction models by mining available experimental and structural data of deamidated proteins. Our training set contains 194 Asn residues from 25 proteins that all have available high-resolution crystal structures. Experimentally measured deamidation half-life of Asn in penta-peptides as well as 3D structure-based properties, such as solvent exposure, crystallographic B-factors, local secondary structure and dihedral angles etc., were used to train prediction models with several machine learning algorithms. The prediction tools were cross-validated as well as tested with an external test data set. The random forest model had high enrichment in ranking deamidated residues higher than non-deamidated residues while effectively eliminated false positive predictions. It is possible that such quantitative protein structure-function relationship tools can also be applied to other protein hotspot predictions. In addition, we extensively discussed metrics being used to evaluate the performance of predicting unbalanced data sets such as the deamidation case.
WIND Validation Cases: Computational Study of Thermally-perfect Gases

NASA Technical Reports Server (NTRS)

DalBello, Teryn; Georgiadis, Nick (Technical Monitor)

2002-01-01

The ability of the WIND Navier-Stokes code to predict the physics of multi-species gases is investigated in support of future high-speed, high-temperature propulsion applications relevant to NASA's Space Transportation efforts. Three benchmark cases are investigated to evaluate the capability of the WIND chemistry model to accurately predict the aerodynamics of multi-species chemically non-reacting (frozen) gases. Case 1 represents turbulent mixing of sonic hydrogen and supersonic vitiated air. Case 2 consists of heated and unheated round supersonic jet exiting to ambient. Case 3 represents 2-D flow through a converging-diverging Mach 2 nozzle. For Case 1, the WIND results agree fairly well with experimental results and that significant mixing occurs downstream of the hydrogen injection point. For Case 2, the results show that the Wilke and Sutherland viscosity laws gave similar results, and the available SST turbulence model does not predict round supersonic nozzle flows accurately. For Case 3, results show that experimental, frozen, and 1-D gas results agree fairly well, and that frozen, homogeneous, multi-species gas calculations can be approximated by running in perfect gas mode while specifying the mixture gas constant and Ratio of Specific Heats.

LES Modeling with Experimental Validation of a Compound Channel having Converging Floodplain

NASA Astrophysics Data System (ADS)

Mohanta, Abinash; Patra, K. C.

2018-04-01

Computational fluid dynamics (CFD) is often used to predict flow structures in developing areas of a flow field for the determination of velocity field, pressure, shear stresses, effect of turbulence and others. A two phase three-dimensional CFD model along with the large eddy simulation (LES) model is used to solve the turbulence equation. This study aims to validate CFD simulations of free surface flow or open channel flow by using volume of fluid method by comparing the data observed in hydraulics laboratory of the National Institute of Technology, Rourkela. The finite volume method with a dynamic sub grid scale was carried out for a constant aspect ratio and convergence condition. The results show that the secondary flow and centrifugal force influence flow pattern and show good agreement with experimental data. Within this paper over-bank flows have been numerically simulated using LES in order to predict accurate open channel flow behavior. The LES results are shown to accurately predict the flow features, specifically the distribution of secondary circulations both for in-bank channels as well as over-bank channels at varying depth and width ratios in symmetrically converging flood plain compound sections.
Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

PubMed Central

2014-01-01

Background Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. Results S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. Conclusions This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved. PMID:24444313
The Electromagnetic and Mechanical Properties of Structural Composites: A Theoretical and Experimental Design Study

DTIC Science & Technology

2014-08-22

higher frequencies due to weaves with smaller unit cells. A second predicts the dielectric properties of unidirectional composite fabrics and laminates ...effective dielectric properties of composite laminates within the X- band (8-12 GHz). The circuit analog method becomes less accurate as the...architectures and to multilayered laminates . In this project, experimental validation from 4-50 GHz is provided for single layers of dry structural grade
Discovery of a metastable Al20Sm4 phase

NASA Astrophysics Data System (ADS)

Ye, Z.; Zhang, F.; Sun, Y.; Mendelev, M. I.; Ott, R. T.; Park, E.; Besser, M. F.; Kramer, M. J.; Ding, Z.; Wang, C.-Z.; Ho, K.-M.

2015-03-01

We present an efficient genetic algorithm, integrated with experimental diffraction data, to solve a nanoscale metastable Al20Sm4 phase that evolves during crystallization of an amorphous magnetron sputtered Al90Sm10 alloy. The excellent match between calculated and experimental X-ray diffraction patterns confirms an accurate description of this metastable phase. Molecular dynamic simulations of crystal growth from the liquid phase predict the formation of disordered defects in the devitrified crystal.
Effective heating of magnetic nanoparticle aggregates for in vivo nano-theranostic hyperthermia.

PubMed

Wang, Chencai; Hsu, Chao-Hsiung; Li, Zhao; Hwang, Lian-Pin; Lin, Ying-Chih; Chou, Pi-Tai; Lin, Yung-Ya

2017-01-01

Magnetic resonance (MR) nano-theranostic hyperthermia uses magnetic nanoparticles to target and accumulate at the lesions and generate heat to kill lesion cells directly through hyperthermia or indirectly through thermal activation and control releasing of drugs. Preclinical and translational applications of MR nano-theranostic hyperthermia are currently limited by a few major theoretical difficulties and experimental challenges in in vivo conditions. For example, conventional models for estimating the heat generated and the optimal magnetic nanoparticle sizes for hyperthermia do not accurately reproduce reported in vivo experimental results. In this work, a revised cluster-based model was proposed to predict the specific loss power (SLP) by explicitly considering magnetic nanoparticle aggregation in in vivo conditions. By comparing with the reported experimental results of magnetite Fe 3 O 4 and cobalt ferrite CoFe 2 O 4 magnetic nanoparticles, it is shown that the revised cluster-based model provides a more accurate prediction of the experimental values than the conventional models that assume magnetic nanoparticles act as single units. It also provides a clear physical picture: the aggregation of magnetic nanoparticles increases the cluster magnetic anisotropy while reducing both the cluster domain magnetization and the average magnetic moment, which, in turn, shift the predicted SLP toward a smaller magnetic nanoparticle diameter with lower peak values. As a result, the heating efficiency and the SLP values are decreased. The improvement in the prediction accuracy in in vivo conditions is particularly pronounced when the magnetic nanoparticle diameter is in the range of ~10-20 nm. This happens to be an important size range for MR cancer nano-theranostics, as it exhibits the highest efficacy against both primary and metastatic tumors in vivo. Our studies show that a relatively 20%-25% smaller magnetic nanoparticle diameter should be chosen to reach the maximal heating efficiency in comparison with the optimal size predicted by previous models.
Effective heating of magnetic nanoparticle aggregates for in vivo nano-theranostic hyperthermia

PubMed Central

Wang, Chencai; Hsu, Chao-Hsiung; Li, Zhao; Hwang, Lian-Pin; Lin, Ying-Chih; Chou, Pi-Tai; Lin, Yung-Ya

2017-01-01

Magnetic resonance (MR) nano-theranostic hyperthermia uses magnetic nanoparticles to target and accumulate at the lesions and generate heat to kill lesion cells directly through hyperthermia or indirectly through thermal activation and control releasing of drugs. Preclinical and translational applications of MR nano-theranostic hyperthermia are currently limited by a few major theoretical difficulties and experimental challenges in in vivo conditions. For example, conventional models for estimating the heat generated and the optimal magnetic nanoparticle sizes for hyperthermia do not accurately reproduce reported in vivo experimental results. In this work, a revised cluster-based model was proposed to predict the specific loss power (SLP) by explicitly considering magnetic nanoparticle aggregation in in vivo conditions. By comparing with the reported experimental results of magnetite Fe3O4 and cobalt ferrite CoFe2O4 magnetic nanoparticles, it is shown that the revised cluster-based model provides a more accurate prediction of the experimental values than the conventional models that assume magnetic nanoparticles act as single units. It also provides a clear physical picture: the aggregation of magnetic nanoparticles increases the cluster magnetic anisotropy while reducing both the cluster domain magnetization and the average magnetic moment, which, in turn, shift the predicted SLP toward a smaller magnetic nanoparticle diameter with lower peak values. As a result, the heating efficiency and the SLP values are decreased. The improvement in the prediction accuracy in in vivo conditions is particularly pronounced when the magnetic nanoparticle diameter is in the range of ~10–20 nm. This happens to be an important size range for MR cancer nano-theranostics, as it exhibits the highest efficacy against both primary and metastatic tumors in vivo. Our studies show that a relatively 20%–25% smaller magnetic nanoparticle diameter should be chosen to reach the maximal heating efficiency in comparison with the optimal size predicted by previous models. PMID:28894366
An integrated Navier-Stokes - full potential - free wake method for rotor flows

NASA Astrophysics Data System (ADS)

Berkman, Mert Enis

1998-12-01

The strong wake shed from rotary wings interacts with almost all components of the aircraft, and alters the flow field thus causing performance and noise problems. Understanding and modeling the behavior of this wake, and its effect on the aerodynamics and acoustics of helicopters have remained as challenges. This vortex wake and its effect should be accurately accounted for in any technique that aims to predict rotor flow field and performance. In this study, an advanced and efficient computational technique for predicting three-dimensional unsteady viscous flows over isolated helicopter rotors in hover and in forward flight is developed. In this hybrid technique, the advantages of various existing methods have been combined to accurately and efficiently study rotor flows with a single numerical method. The flow field is viewed in three parts: (i) an inner zone surrounding each blade where the wake and viscous effects are numerically captured, (ii) an outer zone away from the blades where wake is modeled, and (iii) a Lagrangean wake which induces wake effects in the outer zone. This technique was coded in a flow solver and compared with experimental data for hovering and advancing rotors including a two-bladed rotor, the UH-60A rotor and a tapered tip rotor. Detailed surface pressure, integrated thrust and torque, sectional thrust, and tip vortex position predictions compared favorably against experimental data. Results indicated that the hybrid solver provided accurate flow details and performance information typically in one-half to one-eighth cost of complete Navier-Stokes methods.
Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks

PubMed Central

Khan, Komal Saifullah; Tariq, Muhammad

2014-01-01

Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models. PMID:25421739
Expanded modeling of temperature-dependent dielectric properties for microwave thermal ablation

PubMed Central

Ji, Zhen; Brace, Christopher L

2011-01-01

Microwaves are a promising source for thermal tumor ablation due to their ability to rapidly heat dispersive biological tissues, often to temperatures in excess of 100 °C. At these high temperatures, tissue dielectric properties change rapidly and, thus, so do the characteristics of energy delivery. Precise knowledge of how tissue dielectric properties change during microwave heating promises to facilitate more accurate simulation of device performance and helps optimize device geometry and energy delivery parameters. In this study, we measured the dielectric properties of liver tissue during high-temperature microwave heating. The resulting data were compiled into either a sigmoidal function of temperature or an integration of the time–temperature curve for both relative permittivity and effective conductivity. Coupled electromagnetic–thermal simulations of heating produced by a single monopole antenna using the new models were then compared to simulations with existing linear and static models, and experimental temperatures in liver tissue. The new sigmoidal temperature-dependent model more accurately predicted experimental temperatures when compared to temperature–time integrated or existing models. The mean percent differences between simulated and experimental temperatures over all times were 4.2% for sigmoidal, 10.1% for temperature–time integration, 27.0% for linear and 32.8% for static models at the antenna input power of 50 W. Correcting for tissue contraction improved agreement for powers up to 75 W. The sigmoidal model also predicted substantial changes in heating pattern due to dehydration. We can conclude from these studies that a sigmoidal model of tissue dielectric properties improves prediction of experimental results. More work is needed to refine and generalize this model. PMID:21791728
The DoE method as an efficient tool for modeling the behavior of monocrystalline Si-PV module

NASA Astrophysics Data System (ADS)

Kessaissia, Fatma Zohra; Zegaoui, Abdallah; Boutoubat, Mohamed; Allouache, Hadj; Aillerie, Michel; Charles, Jean-Pierre

2018-05-01

The objective of this paper is to apply the Design of Experiments (DoE) method to study and to obtain a predictive model of any marketed monocrystalline photovoltaic (mc-PV) module. This technique allows us to have a mathematical model that represents the predicted responses depending upon input factors and experimental data. Therefore, the DoE model for characterization and modeling of mc-PV module behavior can be obtained by just performing a set of experimental trials. The DoE model of the mc-PV panel evaluates the predictive maximum power, as a function of irradiation and temperature in a bounded domain of study for inputs. For the mc-PV panel, the predictive model for both one level and two levels were developed taking into account both influences of the main effect and the interactive effects on the considered factors. The DoE method is then implemented by developing a code under Matlab software. The code allows us to simulate, characterize, and validate the predictive model of the mc-PV panel. The calculated results were compared to the experimental data, errors were estimated, and an accurate validation of the predictive models was evaluated by the surface response. Finally, we conclude that the predictive models reproduce the experimental trials and are defined within a good accuracy.
Shock compression response of cold-rolled Ni/Al multilayer composites

DOE PAGES

Specht, Paul E.; Weihs, Timothy P.; Thadhani, Naresh N.

2017-01-06

Uniaxial strain, plate-on-plate impact experiments were performed on cold-rolled Ni/Al multilayer composites and the resulting Hugoniot was determined through time-resolved measurements combined with impedance matching. The experimental Hugoniot agreed with that previously predicted by two dimensional (2D) meso-scale calculations. Additional 2D meso-scale simulations were performed using the same computational method as the prior study to reproduce the experimentally measured free surface velocities and stress profiles. Finally, these simulations accurately replicated the experimental profiles, providing additional validation for the previous computational work.
PHOENIX: a scoring function for affinity prediction derived using high-resolution crystal structures and calorimetry measurements.

PubMed

Tang, Yat T; Marshall, Garland R

2011-02-28

Binding affinity prediction is one of the most critical components to computer-aided structure-based drug design. Despite advances in first-principle methods for predicting binding affinity, empirical scoring functions that are fast and only relatively accurate are still widely used in structure-based drug design. With the increasing availability of X-ray crystallographic structures in the Protein Data Bank and continuing application of biophysical methods such as isothermal titration calorimetry to measure thermodynamic parameters contributing to binding free energy, sufficient experimental data exists that scoring functions can now be derived by separating enthalpic (ΔH) and entropic (TΔS) contributions to binding free energy (ΔG). PHOENIX, a scoring function to predict binding affinities of protein-ligand complexes, utilizes the increasing availability of experimental data to improve binding affinity predictions by the following: model training and testing using high-resolution crystallographic data to minimize structural noise, independent models of enthalpic and entropic contributions fitted to thermodynamic parameters assumed to be thermodynamically biased to calculate binding free energy, use of shape and volume descriptors to better capture entropic contributions. A set of 42 descriptors and 112 protein-ligand complexes were used to derive functions using partial least-squares for change of enthalpy (ΔH) and change of entropy (TΔS) to calculate change of binding free energy (ΔG), resulting in a predictive r2 (r(pred)2) of 0.55 and a standard error (SE) of 1.34 kcal/mol. External validation using the 2009 version of the PDBbind "refined set" (n = 1612) resulted in a Pearson correlation coefficient (R(p)) of 0.575 and a mean error (ME) of 1.41 pK(d). Enthalpy and entropy predictions were of limited accuracy individually. However, their difference resulted in a relatively accurate binding free energy. While the development of an accurate and applicable scoring function was an objective of this study, the main focus was evaluation of the use of high-resolution X-ray crystal structures with high-quality thermodynamic parameters from isothermal titration calorimetry for scoring function development. With the increasing application of structure-based methods in molecular design, this study suggests that using high-resolution crystal structures, separating enthalpy and entropy contributions to binding free energy, and including descriptors to better capture entropic contributions may prove to be effective strategies toward rapid and accurate calculation of binding affinity.
An Accurate ab initio Quartic Force Field and Vibrational Frequencies for CH4 and Isotopomers

NASA Technical Reports Server (NTRS)

Lee, Timothy J.; Martin, Jan M. L.; Taylor, Peter R.

1995-01-01

A very accurate ab initio quartic force field for CH4 and its isotopomers is presented. The quartic force field was determined with the singles and doubles coupled-cluster procedure that includes a quasiperturbative estimate of the effects of connected triple excitations, CCSD(T), using the correlation consistent polarized valence triple zeta, cc-pVTZ, basis set. Improved quadratic force constants were evaluated with the correlation consistent polarized valence quadruple zeta, cc-pVQZ, basis set. Fundamental vibrational frequencies are determined using second-order perturbation theory anharmonic analyses. All fundamentals of CH4 and isotopomers for which accurate experimental values exist and for which there is not a large Fermi resonance, are predicted to within +/- 6 cm(exp -1). It is thus concluded that our predictions for the harmonic frequencies and the anharmonic constants are the most accurate estimates available. It is also shown that using cubic and quartic force constants determined with the correlation consistent polarized double zeta, cc-pVDZ, basis set in conjunction with the cc-pVQZ quadratic force constants and equilibrium geometry leads to accurate predictions for the fundamental vibrational frequencies of methane, suggesting that this approach may be a viable alternative for larger molecules. Using CCSD(T), core correlation is found to reduce the CH4 r(e), by 0.0015 A. Our best estimate for r, is 1.0862 +/- 0.0005 A.
Hot-spot identification on a broad class of proteins and RNA suggest unifying principles of molecular recognition

PubMed Central

Kulp, John L.; Cloudsdale, Ian S.; Kulp, John L.

2017-01-01

Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water. To test the generality of these concepts we used the computational technique of Simulated Annealing of Chemical Potential to design one small fragment to break the RecA-RecA protein-protein interaction and three fragments that inhibit peptide-deformylase via water-mediated multi-body interactions. Experiments confirm the predictions that 6-hydroxydopamine potently inhibits RecA and that PDF inhibition quantitatively tracks the water-mediated binding predictions. Additionally, the principles correctly predict the essential bound waters in HIV Protease, the surprisingly extensive binding site of elastase, the pinpoint location of electron transfer in dihydrofolate reductase, the HIV TAT-TAR protein-RNA interactions, and the MDM2-MDM4 differential binding to p53. The experimental confirmations of highly non-obvious predictions combined with the precise characterization of a broad range of known phenomena lend strong support to the generality of fragment-based methods for characterizing molecular recognition. PMID:28837642
Hot-spot identification on a broad class of proteins and RNA suggest unifying principles of molecular recognition.

PubMed

Kulp, John L; Cloudsdale, Ian S; Kulp, John L; Guarnieri, Frank

2017-01-01

Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water. To test the generality of these concepts we used the computational technique of Simulated Annealing of Chemical Potential to design one small fragment to break the RecA-RecA protein-protein interaction and three fragments that inhibit peptide-deformylase via water-mediated multi-body interactions. Experiments confirm the predictions that 6-hydroxydopamine potently inhibits RecA and that PDF inhibition quantitatively tracks the water-mediated binding predictions. Additionally, the principles correctly predict the essential bound waters in HIV Protease, the surprisingly extensive binding site of elastase, the pinpoint location of electron transfer in dihydrofolate reductase, the HIV TAT-TAR protein-RNA interactions, and the MDM2-MDM4 differential binding to p53. The experimental confirmations of highly non-obvious predictions combined with the precise characterization of a broad range of known phenomena lend strong support to the generality of fragment-based methods for characterizing molecular recognition.
The feasibility of an efficient drug design method with high-performance computers.

PubMed

Yamashita, Takefumi; Ueda, Akihiko; Mitsui, Takashi; Tomonaga, Atsushi; Matsumoto, Shunji; Kodama, Tatsuhiko; Fujitani, Hideaki

2015-01-01

In this study, we propose a supercomputer-assisted drug design approach involving all-atom molecular dynamics (MD)-based binding free energy prediction after the traditional design/selection step. Because this prediction is more accurate than the empirical binding affinity scoring of the traditional approach, the compounds selected by the MD-based prediction should be better drug candidates. In this study, we discuss the applicability of the new approach using two examples. Although the MD-based binding free energy prediction has a huge computational cost, it is feasible with the latest 10 petaflop-scale computer. The supercomputer-assisted drug design approach also involves two important feedback procedures: The first feedback is generated from the MD-based binding free energy prediction step to the drug design step. While the experimental feedback usually provides binding affinities of tens of compounds at one time, the supercomputer allows us to simultaneously obtain the binding free energies of hundreds of compounds. Because the number of calculated binding free energies is sufficiently large, the compounds can be classified into different categories whose properties will aid in the design of the next generation of drug candidates. The second feedback, which occurs from the experiments to the MD simulations, is important to validate the simulation parameters. To demonstrate this, we compare the binding free energies calculated with various force fields to the experimental ones. The results indicate that the prediction will not be very successful, if we use an inaccurate force field. By improving/validating such simulation parameters, the next prediction can be made more accurate.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Wosnik, Martin; Bachant, Pete; Neary, Vincent Sinclair

CACTUS, developed by Sandia National Laboratories, is an open-source code for the design and analysis of wind and hydrokinetic turbines. While it has undergone extensive validation for both vertical axis and horizontal axis wind turbines, and it has been demonstrated to accurately predict the performance of horizontal (axial-flow) hydrokinetic turbines, its ability to predict the performance of crossflow hydrokinetic turbines has yet to be tested. The present study addresses this problem by comparing the predicted performance curves derived from CACTUS simulations of the U.S. Department of Energy’s 1:6 scale reference model crossflow turbine to those derived by experimental measurements inmore » a tow tank using the same model turbine at the University of New Hampshire. It shows that CACTUS cannot accurately predict the performance of this crossflow turbine, raising concerns on its application to crossflow hydrokinetic turbines generally. The lack of quality data on NACA 0021 foil aerodynamic (hydrodynamic) characteristics over the wide range of angles of attack (AoA) and Reynolds numbers is identified as the main cause for poor model prediction. A comparison of several different NACA 0021 foil data sources, derived using both physical and numerical modeling experiments, indicates significant discrepancies at the high AoA experienced by foils on crossflow turbines. Users of CACTUS for crossflow hydrokinetic turbines are, therefore, advised to limit its application to higher tip speed ratios (lower AoA), and to carefully verify the reliability and accuracy of their foil data. Accurate empirical data on the aerodynamic characteristics of the foil is the greatest limitation to predicting performance for crossflow turbines with semi-empirical models like CACTUS. Future improvements of CACTUS for crossflow turbine performance prediction will require the development of accurate foil aerodynamic characteristic data sets within the appropriate ranges of Reynolds numbers and AoA.« less
Application of the Refined Integral Method in the mathematical modeling of drug delivery from one-layer torus-shaped devices.

PubMed

Helbling, Ignacio M; Ibarra, Juan C D; Luna, Julio A

2012-02-28

A mathematical modeling of controlled release of drug from one-layer torus-shaped devices is presented. Analytical solutions based on Refined Integral Method (RIM) are derived. The validity and utility of the model are ascertained by comparison of the simulation results with matrix-type vaginal rings experimental release data reported in the literature. For the comparisons, the pair-wise procedure is used to measure quantitatively the fit of the theoretical predictions to the experimental data. A good agreement between the model prediction and the experimental data is observed. A comparison with a previously reported model is also presented. More accurate results are achieved for small A/C(s) ratios. Copyright © 2011 Elsevier B.V. All rights reserved.
A Finite Element Model to Predict the Effect of Porosity on Elastic Modulus in Low-Porosity Materials

NASA Astrophysics Data System (ADS)

Morrissey, Liam S.; Nakhla, Sam

2018-07-01

The effect of porosity on elastic modulus in low-porosity materials is investigated. First, several models used to predict the reduction in elastic modulus due to porosity are compared with a compilation of experimental data to determine their ranges of validity and accuracy. The overlapping solid spheres model is found to be most accurate with the experimental data and valid between 3 and 10 pct porosity. Next, a FEM is developed with the objective of demonstrating that a macroscale plate with a center hole can be used to model the effect of microscale porosity on elastic modulus. The FEM agrees best with the overlapping solid spheres model and shows higher accuracy with experimental data than the overlapping solid spheres model.
Accurate Binding Free Energy Predictions in Fragment Optimization.

PubMed

Steinbrecher, Thomas B; Dahlgren, Markus; Cappel, Daniel; Lin, Teng; Wang, Lingle; Krilov, Goran; Abel, Robert; Friesner, Richard; Sherman, Woody

2015-11-23

Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.

An accurate and efficient method to predict the electronic excitation energies of BODIPY fluorescent dyes.

PubMed

Wang, Jia-Nan; Jin, Jun-Ling; Geng, Yun; Sun, Shi-Ling; Xu, Hong-Liang; Lu, Ying-Hua; Su, Zhong-Min

2013-03-15

Recently, the extreme learning machine neural network (ELMNN) as a valid computing method has been proposed to predict the nonlinear optical property successfully (Wang et al., J. Comput. Chem. 2012, 33, 231). In this work, first, we follow this line of work to predict the electronic excitation energies using the ELMNN method. Significantly, the root mean square deviation of the predicted electronic excitation energies of 90 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY) derivatives between the predicted and experimental values has been reduced to 0.13 eV. Second, four groups of molecule descriptors are considered when building the computing models. The results show that the quantum chemical descriptions have the closest intrinsic relation with the electronic excitation energy values. Finally, a user-friendly web server (EEEBPre: Prediction of electronic excitation energies for BODIPY dyes), which is freely accessible to public at the web site: http://202.198.129.218, has been built for prediction. This web server can return the predicted electronic excitation energy values of BODIPY dyes that are high consistent with the experimental values. We hope that this web server would be helpful to theoretical and experimental chemists in related research. Copyright © 2012 Wiley Periodicals, Inc.
Bed Morphology and Sediment Transport under Oscillatory Flow

ERIC Educational Resources Information Center

Pedocchi Miljan, Francisco

2009-01-01

Recent laboratory and field experiments have shown the inability of existing oscillatory flow ripple predictors to accurately predict both ripple size and planform geometry. However, at this time, only partial adaptations of these predictors have been proposed in the literature to account for the observed discrepancies with experimental data…
Validation Results for LEWICE 2.0

NASA Technical Reports Server (NTRS)

Wright, William B.; Rutkowski, Adam

1999-01-01

A research project is underway at NASA Lewis to produce a computer code which can accurately predict ice growth under any meteorological conditions for any aircraft surface. This report will present results from version 2.0 of this code, which is called LEWICE. This version differs from previous releases due to its robustness and its ability to reproduce results accurately for different spacing and time step criteria across computing platform. It also differs in the extensive amount of effort undertaken to compare the results in a quantified manner against the database of ice shapes which have been generated in the NASA Lewis Icing Research Tunnel (IRT). The results of the shape comparisons are analyzed to determine the range of meteorological conditions under which LEWICE 2.0 is within the experimental repeatability. This comparison shows that the average variation of LEWICE 2.0 from the experimental data is 7.2% while the overall variability of the experimental data is 2.5%.
Evaluating the use of electronegativity in band alignment models through the experimental slope parameter of lanthanum aluminate heterostructures

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

Liu, Z. Q.; Chim, W. K.; Chiam, S. Y

2011-11-01

In this work, photoelectron spectroscopy is used to characterize the band alignment of lanthanum aluminate heterostructures which possess a wide range of potential applications. It is found that our experimental slope parameter agrees with theory using the metal-induced gap states model while the interface induced gap states (IFIGS) model yields unsatisfactory results. We show that this discrepancy can be attributed to the correlation between the dielectric work function and the electronegativity in the IFIGS model. It is found that the original trend, as established largely by metals, may not be accurate for larger band gap materials. By using a newmore » correlation, our experimental data shows good agreement of the slope parameter using the IFIGS model. This correlation, therefore, plays a crucial role in heterostructures involving wider bandgap materials for accurate band alignment prediction using the IFIGS model.« less
Predicting the mechanical behaviour of Kevlar/epoxy and carbon/epoxy filament-wound tubes

NASA Astrophysics Data System (ADS)

Cazeneuve, C.; Joguet, P.; Maile, J. C.; Oytana, C.

1992-11-01

The axial, hoop and shear moduli and failure conditions of carbon/epoxy and Kevlar/epoxy filament-wound tubes have been determined through respective applications of internal pressure, tension and torsion. The introduction in the laminated plate theory of a gradual reduction in individual moduli makes it possible to overcome the limitations of the theory and enables accurate predictions to be made of the linear and non-linear stress/strain curves of 90 deg +/- 0/90 deg tubes. The existence of a dominant layer in the failure of the multilayered tubes has been shown experimentally. When associated with a failure criterion applied to the dominant layer, the new model permits the prediction of tube failure. Agreement between calculated and experimental data is better than 5 percent.
Estimation of whole lemon mass transfer parameters during hot air drying using different modelling methods

NASA Astrophysics Data System (ADS)

Torki-Harchegani, Mehdi; Ghanbarian, Davoud; Sadeghi, Morteza

2015-08-01

To design new dryers or improve existing drying equipments, accurate values of mass transfer parameters is of great importance. In this study, an experimental and theoretical investigation of drying whole lemons was carried out. The whole lemons were dried in a convective hot air dryer at different air temperatures (50, 60 and 75 °C) and a constant air velocity (1 m s-1). In theoretical consideration, three moisture transfer models including Dincer and Dost model, Bi- G correlation approach and conventional solution of Fick's second law of diffusion were used to determine moisture transfer parameters and predict dimensionless moisture content curves. The predicted results were then compared with the experimental data and the higher degree of prediction accuracy was achieved by the Dincer and Dost model.
BPP: a sequence-based algorithm for branch point prediction.

PubMed

Zhang, Qing; Fan, Xiaodan; Wang, Yejun; Sun, Ming-An; Shao, Jianlin; Guo, Dianjing

2017-10-15

Although high-throughput sequencing methods have been proposed to identify splicing branch points in the human genome, these methods can only detect a small fraction of the branch points subject to the sequencing depth, experimental cost and the expression level of the mRNA. An accurate computational model for branch point prediction is therefore an ongoing objective in human genome research. We here propose a novel branch point prediction algorithm that utilizes information on the branch point sequence and the polypyrimidine tract. Using experimentally validated data, we demonstrate that our proposed method outperforms existing methods. Availability and implementation: https://github.com/zhqingit/BPP. djguo@cuhk.edu.hk. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
New Equation for Prediction of Martensite Start Temperature in High Carbon Ferrous Alloys

NASA Astrophysics Data System (ADS)

Park, Jihye; Shim, Jae-Hyeok; Lee, Seok-Jae

2018-02-01

Since previous equations fail to predict M S temperature of high carbon ferrous alloys, we first propose an equation for prediction of M S temperature of ferrous alloys containing > 2 wt pct C. The presence of carbides (Fe3C and Cr-rich M 7C3) is thermodynamically considered to estimate the C concentration in austenite. Especially, equations individually specialized for lean and high Cr alloys very accurately reproduce experimental results. The chemical driving force for martensitic transformation is quantitatively analyzed based on the calculation of T 0 temperature.
An Anisotropic Hardening Model for Springback Prediction

NASA Astrophysics Data System (ADS)

Zeng, Danielle; Xia, Z. Cedric

2005-08-01

As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test.
Calculating Reuse Distance from Source Code

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

Narayanan, Sri Hari Krishna; Hovland, Paul

The efficient use of a system is of paramount importance in high-performance computing. Applications need to be engineered for future systems even before the architecture of such a system is clearly known. Static performance analysis that generates performance bounds is one way to approach the task of understanding application behavior. Performance bounds provide an upper limit on the performance of an application on a given architecture. Predicting cache hierarchy behavior and accesses to main memory is a requirement for accurate performance bounds. This work presents our static reuse distance algorithm to generate reuse distance histograms. We then use these histogramsmore » to predict cache miss rates. Experimental results for kernels studied show that the approach is accurate.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)

Deline, C.

Computer modeling is able to predict the performance of distributed power electronics (microinverters, power optimizers) in PV systems. However, details about partial shade and other mismatch must be known in order to give the model accurate information to go on. This talk will describe recent updates in NREL’s System Advisor Model program to model partial shading losses with and without distributed power electronics, along with experimental validation results. Computer modeling is able to predict the performance of distributed power electronics (microinverters, power optimizers) in PV systems. However, details about partial shade and other mismatch must be known in order tomore » give the model accurate information to go on. This talk will describe recent updates in NREL’s System Advisor Model program to model partial shading losses.« less
Information spreading by a combination of MEG source estimation and multivariate pattern classification.

PubMed

Sato, Masashi; Yamashita, Okito; Sato, Masa-Aki; Miyawaki, Yoichi

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of "information spreading" may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined.
Information spreading by a combination of MEG source estimation and multivariate pattern classification

PubMed Central

Sato, Masashi; Yamashita, Okito; Sato, Masa-aki

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of “information spreading” may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined. PMID:29912968
Multi-scale predictions of massive conifer mortality due to chronic temperature rise

NASA Astrophysics Data System (ADS)

McDowell, N. G.; Williams, A. P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, S.; Pangle, R.; Limousin, J.; Plaut, J.; Mackay, D. S.; Ogee, J.; Domec, J. C.; Allen, C. D.; Fisher, R. A.; Jiang, X.; Muss, J. D.; Breshears, D. D.; Rauscher, S. A.; Koven, C.

2016-03-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April-August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted >=50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.
Multi-scale predictions of massive conifer mortality due to chronic temperature rise

USGS Publications Warehouse

McDowell, Nathan G.; Williams, A.P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, Sanna; Pangle, R.; Limousin, J.; Plaut, J.J.; Mackay, D.S.; Ogee, J.; Domec, Jean-Christophe; Allen, Craig D.; Fisher, Rosie A.; Jiang, X.; Muss, J.D.; Breshears, D.D.; Rauscher, Sara A.; Koven, C.

2016-01-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.
Revisiting the blind tests in crystal structure prediction: accurate energy ranking of molecular crystals.

PubMed

Asmadi, Aldi; Neumann, Marcus A; Kendrick, John; Girard, Pascale; Perrin, Marc-Antoine; Leusen, Frank J J

2009-12-24

In the 2007 blind test of crystal structure prediction hosted by the Cambridge Crystallographic Data Centre (CCDC), a hybrid DFT/MM method correctly ranked each of the four experimental structures as having the lowest lattice energy of all the crystal structures predicted for each molecule. The work presented here further validates this hybrid method by optimizing the crystal structures (experimental and submitted) of the first three CCDC blind tests held in 1999, 2001, and 2004. Except for the crystal structures of compound IX, all structures were reminimized and ranked according to their lattice energies. The hybrid method computes the lattice energy of a crystal structure as the sum of the DFT total energy and a van der Waals (dispersion) energy correction. Considering all four blind tests, the crystal structure with the lowest lattice energy corresponds to the experimentally observed structure for 12 out of 14 molecules. Moreover, good geometrical agreement is observed between the structures determined by the hybrid method and those measured experimentally. In comparison with the correct submissions made by the blind test participants, all hybrid optimized crystal structures (apart from compound II) have the smallest calculated root mean squared deviations from the experimentally observed structures. It is predicted that a new polymorph of compound V exists under pressure.
Automation methodologies and large-scale validation for G W : Towards high-throughput G W calculations

NASA Astrophysics Data System (ADS)

van Setten, M. J.; Giantomassi, M.; Gonze, X.; Rignanese, G.-M.; Hautier, G.

2017-10-01

The search for new materials based on computational screening relies on methods that accurately predict, in an automatic manner, total energy, atomic-scale geometries, and other fundamental characteristics of materials. Many technologically important material properties directly stem from the electronic structure of a material, but the usual workhorse for total energies, namely density-functional theory, is plagued by fundamental shortcomings and errors from approximate exchange-correlation functionals in its prediction of the electronic structure. At variance, the G W method is currently the state-of-the-art ab initio approach for accurate electronic structure. It is mostly used to perturbatively correct density-functional theory results, but is, however, computationally demanding and also requires expert knowledge to give accurate results. Accordingly, it is not presently used in high-throughput screening: fully automatized algorithms for setting up the calculations and determining convergence are lacking. In this paper, we develop such a method and, as a first application, use it to validate the accuracy of G0W0 using the PBE starting point and the Godby-Needs plasmon-pole model (G0W0GN @PBE) on a set of about 80 solids. The results of the automatic convergence study utilized provide valuable insights. Indeed, we find correlations between computational parameters that can be used to further improve the automatization of G W calculations. Moreover, we find that G0W0GN @PBE shows a correlation between the PBE and the G0W0GN @PBE gaps that is much stronger than that between G W and experimental gaps. However, the G0W0GN @PBE gaps still describe the experimental gaps more accurately than a linear model based on the PBE gaps. With this paper, we hence show that G W can be made automatic and is more accurate than using an empirical correction of the PBE gap, but that, for accurate predictive results for a broad class of materials, an improved starting point or some type of self-consistency is necessary.
A combined-slip predictive control of vehicle stability with experimental verification

NASA Astrophysics Data System (ADS)

Jalali, Milad; Hashemi, Ehsan; Khajepour, Amir; Chen, Shih-ken; Litkouhi, Bakhtiar

2018-02-01

In this paper, a model predictive vehicle stability controller is designed based on a combined-slip LuGre tyre model. Variations in the lateral tyre forces due to changes in tyre slip ratios are considered in the prediction model of the controller. It is observed that the proposed combined-slip controller takes advantage of the more accurate tyre model and can adjust tyre slip ratios based on lateral forces of the front axle. This results in an interesting closed-loop response that challenges the notion of braking only the wheels on one side of the vehicle in differential braking. The performance of the proposed controller is evaluated in software simulations and is compared to a similar pure-slip controller. Furthermore, experimental tests are conducted on a rear-wheel drive electric Chevrolet Equinox equipped with differential brakes to evaluate the closed-loop response of the model predictive control controller.
Sliding contact fracture of dental ceramics: Principles and validation

PubMed Central

Ren, Linlin; Zhang, Yu

2014-01-01

Ceramic prostheses are subject to sliding contact under normal and tangential loads. Accurate prediction of the onset of fracture at two contacting surfaces holds the key to greater long-term performance of these prostheses. In this study, building on stress analysis of Hertzian contact and considering fracture criteria for linear elastic materials, a constitutive fracture mechanics relation was developed to incorporate the critical fracture load with the contact geometry, coefficient of friction and material fracture toughness. Critical loads necessary to cause fracture under a sliding indenter were calculated from the constitutive equation, and compared with the loads predicted from elastic stress analysis in conjunction with measured critical load for frictionless normal contact—a semi-empirical approach. The major predictions of the models were calibrated with experimentally determined critical loads of current and future dental ceramics after contact with a rigid spherical slider. Experimental results conform with the trends predicted by the models. PMID:24632538
Automated adaptive inference of phenomenological dynamical models.

PubMed

Daniels, Bryan C; Nemenman, Ilya

2015-08-21

Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved.

Forecasting Construction Cost Index based on visibility graph: A network approach

NASA Astrophysics Data System (ADS)

Zhang, Rong; Ashuri, Baabak; Shyr, Yu; Deng, Yong

2018-03-01

Engineering News-Record (ENR), a professional magazine in the field of global construction engineering, publishes Construction Cost Index (CCI) every month. Cost estimators and contractors assess projects, arrange budgets and prepare bids by forecasting CCI. However, fluctuations and uncertainties of CCI cause irrational estimations now and then. This paper aims at achieving more accurate predictions of CCI based on a network approach in which time series is firstly converted into a visibility graph and future values are forecasted relied on link prediction. According to the experimental results, the proposed method shows satisfactory performance since the error measures are acceptable. Compared with other methods, the proposed method is easier to implement and is able to forecast CCI with less errors. It is convinced that the proposed method is efficient to provide considerably accurate CCI predictions, which will make contributions to the construction engineering by assisting individuals and organizations in reducing costs and making project schedules.
Automated adaptive inference of phenomenological dynamical models

PubMed Central

Daniels, Bryan C.; Nemenman, Ilya

2015-01-01

Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved. PMID:26293508
Two-Dimensional Simulation of Left-Handed Metamaterial Flat Lens Using Remcon XFDTD

NASA Technical Reports Server (NTRS)

Wilson, Jeffrey D.; Reinert, Jason M.

2006-01-01

Remcom's XFDTD software was used to model the properties of a two-dimensional left-handed metamaterial (LHM) flat lens. The focusing capability and attenuation of the material were examined. The results showed strong agreement with experimental results and theoretical predictions of focusing effects and focal length. The inherent attenuation in the model corresponds well with the experimental results and implies that the code does a reasonably accurate job of modeling the actual metamaterial.
Accurate Prediction of Contact Numbers for Multi-Spanning Helical Membrane Proteins

PubMed Central

Li, Bian; Mendenhall, Jeffrey; Nguyen, Elizabeth Dong; Weiner, Brian E.; Fischer, Axel W.; Meiler, Jens

2017-01-01

Prediction of the three-dimensional (3D) structures of proteins by computational methods is acknowledged as an unsolved problem. Accurate prediction of important structural characteristics such as contact number is expected to accelerate the otherwise slow progress being made in the prediction of 3D structure of proteins. Here, we present a dropout neural network-based method, TMH-Expo, for predicting the contact number of transmembrane helix (TMH) residues from sequence. Neuronal dropout is a strategy where certain neurons of the network are excluded from back-propagation to prevent co-adaptation of hidden-layer neurons. By using neuronal dropout, overfitting was significantly reduced and performance was noticeably improved. For multi-spanning helical membrane proteins, TMH-Expo achieved a remarkable Pearson correlation coefficient of 0.69 between predicted and experimental values and a mean absolute error of only 1.68. In addition, among those membrane protein–membrane protein interface residues, 76.8% were correctly predicted. Mapping of predicted contact numbers onto structures indicates that contact numbers predicted by TMH-Expo reflect the exposure patterns of TMHs and reveal membrane protein–membrane protein interfaces, reinforcing the potential of predicted contact numbers to be used as restraints for 3D structure prediction and protein–protein docking. TMH-Expo can be accessed via a Web server at www.meilerlab.org. PMID:26804342
Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

PubMed Central

Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.

2016-01-01

The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally—a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process. PMID:26887592
Multi-scale modeling of tsunami flows and tsunami-induced forces

NASA Astrophysics Data System (ADS)

Qin, X.; Motley, M. R.; LeVeque, R. J.; Gonzalez, F. I.

2016-12-01

The modeling of tsunami flows and tsunami-induced forces in coastal communities with the incorporation of the constructed environment is challenging for many numerical modelers because of the scale and complexity of the physical problem. A two-dimensional (2D) depth-averaged model can be efficient for modeling of waves offshore but may not be accurate enough to predict the complex flow with transient variance in vertical direction around constructed environments on land. On the other hand, using a more complex three-dimensional model is much more computational expensive and can become impractical due to the size of the problem and the meshing requirements near the built environment. In this study, a 2D depth-integrated model and a 3D Reynolds Averaged Navier-Stokes (RANS) model are built to model a 1:50 model-scale, idealized community, representative of Seaside, OR, USA, for which existing experimental data is available for comparison. Numerical results from the two numerical models are compared with each other as well as experimental measurement. Both models predict the flow parameters (water level, velocity, and momentum flux in the vicinity of the buildings) accurately, in general, except for time period near the initial impact, where the depth-averaged models can fail to capture the complexities in the flow. Forces predicted using direct integration of predicted pressure on structural surfaces from the 3D model and using momentum flux from the 2D model with constructed environment are compared, which indicates that force prediction from the 2D model is not always reliable in such a complicated case. Force predictions from integration of the pressure are also compared with forces predicted from bare earth momentum flux calculations to reveal the importance of incorporating the constructed environment in force prediction models.
All-atom 3D structure prediction of transmembrane β-barrel proteins from sequences.

PubMed

Hayat, Sikander; Sander, Chris; Marks, Debora S; Elofsson, Arne

2015-04-28

Transmembrane β-barrels (TMBs) carry out major functions in substrate transport and protein biogenesis but experimental determination of their 3D structure is challenging. Encouraged by successful de novo 3D structure prediction of globular and α-helical membrane proteins from sequence alignments alone, we developed an approach to predict the 3D structure of TMBs. The approach combines the maximum-entropy evolutionary coupling method for predicting residue contacts (EVfold) with a machine-learning approach (boctopus2) for predicting β-strands in the barrel. In a blinded test for 19 TMB proteins of known structure that have a sufficient number of diverse homologous sequences available, this combined method (EVfold_bb) predicts hydrogen-bonded residue pairs between adjacent β-strands at an accuracy of ∼70%. This accuracy is sufficient for the generation of all-atom 3D models. In the transmembrane barrel region, the average 3D structure accuracy [template-modeling (TM) score] of top-ranked models is 0.54 (ranging from 0.36 to 0.85), with a higher (44%) number of residue pairs in correct strand-strand registration than in earlier methods (18%). Although the nonbarrel regions are predicted less accurately overall, the evolutionary couplings identify some highly constrained loop residues and, for FecA protein, the barrel including the structure of a plug domain can be accurately modeled (TM score = 0.68). Lower prediction accuracy tends to be associated with insufficient sequence information and we therefore expect increasing numbers of β-barrel families to become accessible to accurate 3D structure prediction as the number of available sequences increases.
A Combined Experimental and Computational Approach to Subject-Specific Analysis of Knee Joint Laxity

PubMed Central

Harris, Michael D.; Cyr, Adam J.; Ali, Azhar A.; Fitzpatrick, Clare K.; Rullkoetter, Paul J.; Maletsky, Lorin P.; Shelburne, Kevin B.

2016-01-01

Modeling complex knee biomechanics is a continual challenge, which has resulted in many models of varying levels of quality, complexity, and validation. Beyond modeling healthy knees, accurately mimicking pathologic knee mechanics, such as after cruciate rupture or meniscectomy, is difficult. Experimental tests of knee laxity can provide important information about ligament engagement and overall contributions to knee stability for development of subject-specific models to accurately simulate knee motion and loading. Our objective was to provide combined experimental tests and finite-element (FE) models of natural knee laxity that are subject-specific, have one-to-one experiment to model calibration, simulate ligament engagement in agreement with literature, and are adaptable for a variety of biomechanical investigations (e.g., cartilage contact, ligament strain, in vivo kinematics). Calibration involved perturbing ligament stiffness, initial ligament strain, and attachment location until model-predicted kinematics and ligament engagement matched experimental reports. Errors between model-predicted and experimental kinematics averaged <2 deg during varus–valgus (VV) rotations, <6 deg during internal–external (IE) rotations, and <3 mm of translation during anterior–posterior (AP) displacements. Engagement of the individual ligaments agreed with literature descriptions. These results demonstrate the ability of our constraint models to be customized for multiple individuals and simultaneously call attention to the need to verify that ligament engagement is in good general agreement with literature. To facilitate further investigations of subject-specific or population based knee joint biomechanics, data collected during the experimental and modeling phases of this study are available for download by the research community. PMID:27306137
Predicting mixture phase equilibria and critical behavior using the SAFT-VRX approach.

PubMed

Sun, Lixin; Zhao, Honggang; Kiselev, Sergei B; McCabe, Clare

2005-05-12

The SAFT-VRX equation of state combines the SAFT-VR equation with a crossover function that smoothly transforms the classical equation into a nonanalytical form close to the critical point. By a combinination of the accuracy of the SAFT-VR approach away from the critical region with the asymptotic scaling behavior seen at the critical point of real fluids, the SAFT-VRX equation can accurately describe the global fluid phase diagram. In previous work, we demonstrated that the SAFT-VRX equation very accurately describes the pvT and phase behavior of both nonassociating and associating pure fluids, with a minimum of fitting to experimental data. Here, we present a generalized SAFT-VRX equation of state for binary mixtures that is found to accurately predict the vapor-liquid equilibrium and pvT behavior of the systems studied. In particular, we examine binary mixtures of n-alkanes and carbon dioxide + n-alkanes. The SAFT-VRX equation accurately describes not only the gas-liquid critical locus for these systems but also the vapor-liquid equilibrium phase diagrams and thermal properties in single-phase regions.
Understanding the effect of side groups in ionic liquids on carbon-capture properties: a combined experimental and theoretical effort

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

Yan, Fangyong; Lartey, Michael; Damodaran, Krishnan

2013-01-01

Ionic liquids are an emerging class of materials with applications in a variety of fields. Steady progress has been made in the creation of ionic liquids tailored to specific applications. However, the understanding of the underlying structure–property relationships has been slower to develop. As a step in the effort to alleviate this deficiency, the influence of side groups on ionic liquid properties has been studied through an integrated approach utilizing synthesis, experimental determination of properties, and simulation techniques. To achieve this goal, a classical force field in the framework of OPLS/Amber force fields has been developed to predict ionic liquidmore » properties accurately. Cu(I)-catalyzed click chemistry was employed to synthesize triazolium-based ionic liquids with diverse side groups. Values of densities were predicted within 3% of experimental values, whereas self-diffusion coefficients were underestimated by about an order of magnitude though the trends were in excellent agreement, the activation energy calculated in simulation correlates well with experimental values. The predicted Henry coefficient for CO{sub 2} solubility reproduced the experimentally observed trends. This study highlights the importance of integrating experimental and computational approaches in property prediction and materials development, which is not only useful in the development of ionic liquids for CO{sub 2} capture but has application in many technological fields.« less
Understanding the effect of side groups in ionic liquids on carbon-capture properties: a combined experimental and theoretical effort

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

Yan, Fangyong; Lartey, Michael; Damodaran, Krishnan

Ionic liquids are an emerging class of materials with applications in a variety of fields. Steady progress has been made in the creation of ionic liquids tailored to specific applications. However, the understanding of the underlying structure–property relationships has been slower to develop. As a step in the effort to alleviate this deficiency, the influence of side groups on ionic liquid properties has been studied through an integrated approach utilizing synthesis, experimental determination of properties, and simulation techniques. To achieve this goal, a classical force field in the framework of OPLS/Amber force fields has been developed to predict ionic liquidmore » properties accurately. Cu(I)-catalyzed click chemistry was employed to synthesize triazolium-based ionic liquids with diverse side groups. Values of densities were predicted within 3% of experimental values, whereas self-diffusion coefficients were underestimated by about an order of magnitude though the trends were in excellent agreement, the activation energy calculated in simulation correlates well with experimental values. The predicted Henry coefficient for CO{sub 2} solubility reproduced the experimentally observed trends. This study highlights the importance of integrating experimental and computational approaches in property prediction and materials development, which is not only useful in the development of ionic liquids for CO{sub 2} capture but has application in many technological fields.« less
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 provide guidance on how to effectively reduce BDT and may be used to identifying deteriorating machine performance. © 2017 American Association of Physicists in Medicine.
Fraction of organic carbon predicts labile desorption rates of chlorinated organic pollutants in laboratory-spiked geosorbents.

PubMed

Ginsbach, Jake W; Killops, Kato L; Olsen, Robert M; Peterson, Brittney; Dunnivant, Frank M

2010-05-01

The resuspension of large volumes of sediments that are contaminated with chlorinated pollutants continues to threaten environmental quality and human health. Whereas kinetic models are more accurate for estimating the environmental impact of these events, their widespread use is substantially hampered by the need for costly, time-consuming, site-specific kinetics experiments. The present study investigated the development of a predictive model for desorption rates from easily measurable sorbent and pollutant properties by examining the relationship between the fraction of organic carbon (fOC) and labile release rates. Duplicate desorption measurements were performed on 46 unique combinations of pollutants and sorbents with fOC values ranging from 0.001 to 0.150. Labile desorption rate constants indicate that release rates predominantly depend upon the fOC in the geosorbent. Previous theoretical models, such as the macro-mesopore and organic matter (MOM) diffusion model, have predicted such a relationship but could not accurately predict the experimental rate constants collected in the present study. An empirical model was successfully developed to correlate the labile desorption rate constant (krap) to the fraction of organic material where log(krap)=0.291-0.785 . log(fOC). These results provide the first experimental evidence that kinetic pollution releases during resuspension events are governed by the fOC content in natural geosorbents. Copyright (c) 2010 SETAC.
Accurate prediction of vaccine stability under real storage conditions and during temperature excursions.

PubMed

Clénet, Didier

2018-04-01

Due to their thermosensitivity, most vaccines must be kept refrigerated from production to use. To successfully carry out global immunization programs, ensuring the stability of vaccines is crucial. In this context, two important issues are critical, namely: (i) predicting vaccine stability and (ii) preventing product damage due to excessive temperature excursions outside of the recommended storage conditions (cold chain break). We applied a combination of advanced kinetics and statistical analyses on vaccine forced degradation data to accurately describe the loss of antigenicity for a multivalent freeze-dried inactivated virus vaccine containing three variants. The screening of large amounts of kinetic models combined with a statistical model selection approach resulted in the identification of two-step kinetic models. Predictions based on kinetic analysis and experimental stability data were in agreement, with approximately five percentage points difference from real values for long-term stability storage conditions, after excursions of temperature and during experimental shipments of freeze-dried products. Results showed that modeling a few months of forced degradation can be used to predict various time and temperature profiles endured by vaccines, i.e. long-term stability, short time excursions outside the labeled storage conditions or shipments at ambient temperature, with high accuracy. Pharmaceutical applications of the presented kinetics-based approach are discussed. Copyright © 2018 The Author. Published by Elsevier B.V. All rights reserved.
Genome-Scale Screening of Drug-Target Associations Relevant to Ki Using a Chemogenomics Approach

PubMed Central

Cao, Dong-Sheng; Liang, Yi-Zeng; Deng, Zhe; Hu, Qian-Nan; He, Min; Xu, Qing-Song; Zhou, Guang-Hua; Zhang, Liu-Xia; Deng, Zi-xin; Liu, Shao

2013-01-01

The identification of interactions between drugs and target proteins plays a key role in genomic drug discovery. In the present study, the quantitative binding affinities of drug-target pairs are differentiated as a measurement to define whether a drug interacts with a protein or not, and then a chemogenomics framework using an unbiased set of general integrated features and random forest (RF) is employed to construct a predictive model which can accurately classify drug-target pairs. The predictability of the model is further investigated and validated by several independent validation sets. The built model is used to predict drug-target associations, some of which were confirmed by comparing experimental data from public biological resources. A drug-target interaction network with high confidence drug-target pairs was also reconstructed. This network provides further insight for the action of drugs and targets. Finally, a web-based server called PreDPI-Ki was developed to predict drug-target interactions for drug discovery. In addition to providing a high-confidence list of drug-target associations for subsequent experimental investigation guidance, these results also contribute to the understanding of drug-target interactions. We can also see that quantitative information of drug-target associations could greatly promote the development of more accurate models. The PreDPI-Ki server is freely available via: http://sdd.whu.edu.cn/dpiki. PMID:23577055
Evaluation of Test Methods for Triaxially Braided Composites using a Meso-Scale Finite Element Model

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

Zhang, Chao

The characterization of triaxially braided composite is complicate due to the nonuniformity of deformation within the unit cell as well as the possibility of the freeedge effect related to the large size of the unit cell. Extensive experimental investigation has been conducted to develop more accurate test approaches in characterizing the actual mechanical properties of the material we are studying. In this work, a meso-scale finite element model is utilized to simulate two complex specimens: notched tensile specimen and tube tensile specimen, which are designed to avoid the free-edge effect and free-edge effect induced premature edge damage. The full fieldmore » strain data is predicted numerically and compared with experimental data obtained by Digit Image Correlation. The numerically predicted tensile strength values are compared with experimentally measured results. The discrepancy between numerically predicted and experimentally measured data, the capability of different test approaches are analyzed and discussed. The presented numerical model could serve as assistance to the evaluation of different test methods, and is especially useful in identifying potential local damage events.« less
The Effects of Blade Count on Boundary Layer Development in a Low-Pressure Turbine

NASA Technical Reports Server (NTRS)

Dorney, Daniel J.; Flitan, Horia C.; Ashpis, David E.; Solomon, William J.

2000-01-01

Experimental data from jet-engine tests have indicated that turbine efficiencies at takeoff can be as much as two points higher than those at cruise conditions. Recent studies have shown that Reynolds number effects contribute to the lower efficiencies at cruise conditions. In the current study numerical simulations have been performed to study the boundary layer development in a two-stage low-pressure turbine, and to evaluate the models available for low Reynolds number flows in turbomachinery. In a previous study using the same geometry the predicted time-averaged boundary layer quantities showed excellent agreement with the experimental data, but the predicted unsteady results showed only fair agreement with the experimental data. It was surmised that the blade count approximation used in the numerical simulations generated more unsteadiness than was observed in the experiments. In this study a more accurate blade approximation has been used to model the turbine, and the method of post-processing the boundary layer information has been modified to more closely resemble the process used in the experiments. The predicted results show improved agreement with the unsteady experimental data.
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

A model-based controller for an artificial beta cell requires an accurate model of the glucose-insulin dynamics in type 1 diabetes subjects. To ensure the robustness of the controller for changing conditions (e.g., changes in insulin sensitivity due to illnesses, changes in exercise habits, or changes in stress levels), the model should be able to adapt to the new conditions by means of a recursive parameter estimation technique. Such an adaptive strategy will ensure that the most accurate model is used for the current conditions, and thus the most accurate model predictions are used in model-based control calculations. In a retrospective analysis, empirical dynamic autoregressive exogenous input (ARX) models were identified from glucose-insulin data for nine type 1 diabetes subjects in ambulatory conditions. Data sets consisted of continuous (5-minute) glucose concentration measurements obtained from a continuous glucose monitor, basal insulin infusion rates and times and amounts of insulin boluses obtained from the subjects' insulin pumps, and subject-reported estimates of the times and carbohydrate content of meals. Two identification techniques were investigated: nonrecursive, or batch methods, and recursive methods. Batch models were identified from a set of training data, whereas recursively identified models were updated at each sampling instant. Both types of models were used to make predictions of new test data. For the purpose of comparison, model predictions were compared to zero-order hold (ZOH) predictions, which were made by simply holding the current glucose value constant for p steps into the future, where p is the prediction horizon. Thus, the ZOH predictions are model free and provide a base case for the prediction metrics used to quantify the accuracy of the model predictions. In theory, recursive identification techniques are needed only when there are changing conditions in the subject that require model adaptation. Thus, the identification and 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-free ZOH predictions. Given the simplicity of the ARX models and the computational ease with which they are identified, however, even modest improvements may justify the use of these models in a model-based controller for an artificial beta cell. 2009 Diabetes Technology Society.
Assessment of predictive capabilities for aerodynamic heating in hypersonic flow

NASA Astrophysics Data System (ADS)

Knight, Doyle; Chazot, Olivier; Austin, Joanna; Badr, Mohammad Ali; Candler, Graham; Celik, Bayram; Rosa, Donato de; Donelli, Raffaele; Komives, Jeffrey; Lani, Andrea; Levin, Deborah; Nompelis, Ioannis; Panesi, Marco; Pezzella, Giuseppe; Reimann, Bodo; Tumuklu, Ozgur; Yuceil, Kemal

2017-04-01

The capability for CFD prediction of hypersonic shock wave laminar boundary layer interaction was assessed for a double wedge model at Mach 7.1 in air and nitrogen at 2.1 MJ/kg and 8 MJ/kg. Simulations were performed by seven research organizations encompassing both Navier-Stokes and Direct Simulation Monte Carlo (DSMC) methods as part of the NATO STO AVT Task Group 205 activity. Comparison of the CFD simulations with experimental heat transfer and schlieren visualization suggest the need for accurate modeling of the tunnel startup process in short-duration hypersonic test facilities, and the importance of fully 3-D simulations of nominally 2-D (i.e., non-axisymmmetric) experimental geometries.
Comparison of a quasi-3D analysis and experimental performance for three compact radial turbines

NASA Technical Reports Server (NTRS)

Simonyi, P. S.; Boyle, R. J.

1991-01-01

An experimental aerodynamic evaluation of three compact radial turbine builds was performed. Two rotors which were 40-50 percent shorter in axial length than conventional state-of-the-art radial rotors were tested. A single nozzle design was used. One rotor was tested with the nozzle at two stagger angle settings. A second rotor was tested with the nozzle in only the closed down setting. Experimental results were compared to predicted results from a quasi-3D inviscid and boundary layer analysis, called MTSB (Meridl/Tsonic/Blayer). This analysis was used to predict turbine performance. It has previously been calibrated only for axial, not radial, turbomachinery. The predicted and measured efficiencies were compared at the design point for the three turbines. At the design points the analysis overpredicted the efficiency by less than 1.7 points. Comparisons were also made at off-design operating points. The results of these comparisons showed the importance of an accurate clearance model for efficiency predictions and also that there are deficiencies in the incidence loss model used.

Comparison of a quasi-3D analysis and experimental performance for three compact radial turbines

NASA Technical Reports Server (NTRS)

Simonyi, P. S.; Boyle, R. J.

1991-01-01

An experimental aerodynamic evaluation of three compact radial turbine builds was performed. Two rotors which were 40 to 50 percent shorter in axial length than conventional state of the art radial rotors were tested. A single nozzle design was used. One rotor was tested with the nozzle at two stagger angle settings. A second rotor was tested with the nozzle in only the closed down setting. Experimental results were compared to predict results from a quasi-3D inviscid and boundary layer analysis, called Meridl/Tsonic/Blayer (MTSB). This analysis was used to predict turbine performance. It has previously been calibrated only for axial, not radial, turbomachinery. The predicted and measured efficiencies were compared at the design point for the three turbines. At the design points the analysis overpredicted the efficiency by less than 1.7 points. Comparisons were also made at off-design operating points. The results of these comparisons showed the importance of an accurate clearance model for efficiency predictions and also that there are deficiencies in the incidence loss model used.
Quantum Monte Carlo study of the phase diagram of solid molecular hydrogen at extreme pressures

PubMed Central

Drummond, N. D.; Monserrat, Bartomeu; Lloyd-Williams, Jonathan H.; Ríos, P. López; Pickard, Chris J.; Needs, R. J.

2015-01-01

Establishing the phase diagram of hydrogen is a major challenge for experimental and theoretical physics. Experiment alone cannot establish the atomic structure of solid hydrogen at high pressure, because hydrogen scatters X-rays only weakly. Instead, our understanding of the atomic structure is largely based on density functional theory (DFT). By comparing Raman spectra for low-energy structures found in DFT searches with experimental spectra, candidate atomic structures have been identified for each experimentally observed phase. Unfortunately, DFT predicts a metallic structure to be energetically favoured at a broad range of pressures up to 400 GPa, where it is known experimentally that hydrogen is non-metallic. Here we show that more advanced theoretical methods (diffusion quantum Monte Carlo calculations) find the metallic structure to be uncompetitive, and predict a phase diagram in reasonable agreement with experiment. This greatly strengthens the claim that the candidate atomic structures accurately model the experimentally observed phases. PMID:26215251
Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

NASA Astrophysics Data System (ADS)

Ko, P.; Kurosawa, S.

2014-03-01

The understanding and accurate prediction of the flow behaviour related to cavitation and pressure fluctuation in a Kaplan turbine are important to the design work enhancing the turbine performance including the elongation of the operation life span and the improvement of turbine efficiency. In this paper, high accuracy turbine and cavitation performance prediction method based on entire flow passage for a Kaplan turbine is presented and evaluated. Two-phase flow field is predicted by solving Reynolds-Averaged Navier-Stokes equations expressed by volume of fluid method tracking the free surface and combined with Reynolds Stress model. The growth and collapse of cavitation bubbles are modelled by the modified Rayleigh-Plesset equation. The prediction accuracy is evaluated by comparing with the model test results of Ns 400 Kaplan model turbine. As a result that the experimentally measured data including turbine efficiency, cavitation performance, and pressure fluctuation are accurately predicted. Furthermore, the cavitation occurrence on the runner blade surface and the influence to the hydraulic loss of the flow passage are discussed. Evaluated prediction method for the turbine flow and performance is introduced to facilitate the future design and research works on Kaplan type turbine.
Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO).

PubMed

Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

2017-08-01

A crucial and limiting factor in data reuse is the lack of accurate, structured, and complete descriptions of data, known as metadata. Towards improving the quantity and quality of metadata, we propose a novel metadata prediction framework to learn associations from existing metadata that can be used to predict metadata values. We evaluate our framework in the context of experimental metadata from the Gene Expression Omnibus (GEO). We applied four rule mining algorithms to the most common structured metadata elements (sample type, molecular type, platform, label type and organism) from over 1.3million GEO records. We examined the quality of well supported rules from each algorithm and visualized the dependencies among metadata elements. Finally, we evaluated the performance of the algorithms in terms of accuracy, precision, recall, and F-measure. We found that PART is the best algorithm outperforming Apriori, Predictive Apriori, and Decision Table. All algorithms perform significantly better in predicting class values than the majority vote classifier. We found that the performance of the algorithms is related to the dimensionality of the GEO elements. The average performance of all algorithm increases due of the decreasing of dimensionality of the unique values of these elements (2697 platforms, 537 organisms, 454 labels, 9 molecules, and 5 types). Our work suggests that experimental metadata such as present in GEO can be accurately predicted using rule mining algorithms. Our work has implications for both prospective and retrospective augmentation of metadata quality, which are geared towards making data easier to find and reuse. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
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
Forming limit prediction by an evolving non-quadratic yield criterion considering the anisotropic hardening and r-value evolution

NASA Astrophysics Data System (ADS)

Lian, Junhe; Shen, Fuhui; Liu, Wenqi; Münstermann, Sebastian

2018-05-01

The constitutive model development has been driven to a very accurate and fine-resolution description of the material behaviour responding to various environmental variable changes. The evolving features of the anisotropic behaviour during deformation, therefore, has drawn particular attention due to its possible impacts on the sheet metal forming industry. An evolving non-associated Hill48 (enHill48) model was recently proposed and applied to the forming limit prediction by coupling with the modified maximum force criterion. On the one hand, the study showed the significance to include the anisotropic evolution for accurate forming limit prediction. On the other hand, it also illustrated that the enHill48 model introduced an instability region that suddenly decreases the formability. Therefore, in this study, an alternative model that is based on the associated flow rule and provides similar anisotropic predictive capability is extended to chapter the evolving effects and further applied to the forming limit prediction. The final results are compared with experimental data as well as the results by enHill48 model.
Predicting intensity ranks of peptide fragment ions.

PubMed

Frank, Ari M

2009-05-01

Accurate modeling of peptide fragmentation is necessary for the development of robust scoring functions for peptide-spectrum matches, which are the cornerstone of MS/MS-based identification algorithms. Unfortunately, peptide fragmentation is a complex process that can involve several competing chemical pathways, which makes it difficult to develop generative probabilistic models that describe it accurately. However, the vast amounts of MS/MS data being generated now make it possible to use data-driven machine learning methods to develop discriminative ranking-based models that predict the intensity ranks of a peptide's fragment ions. We use simple sequence-based features that get combined by a boosting algorithm into models that make peak rank predictions with high accuracy. In an accompanying manuscript, we demonstrate how these prediction models are used to significantly improve the performance of peptide identification algorithms. The models can also be useful in the design of optimal multiple reaction monitoring (MRM) transitions, in cases where there is insufficient experimental data to guide the peak selection process. The prediction algorithm can also be run independently through PepNovo+, which is available for download from http://bix.ucsd.edu/Software/PepNovo.html.
Predicting Intensity Ranks of Peptide Fragment Ions

PubMed Central

Frank, Ari M.

2009-01-01

Accurate modeling of peptide fragmentation is necessary for the development of robust scoring functions for peptide-spectrum matches, which are the cornerstone of MS/MS-based identification algorithms. Unfortunately, peptide fragmentation is a complex process that can involve several competing chemical pathways, which makes it difficult to develop generative probabilistic models that describe it accurately. However, the vast amounts of MS/MS data being generated now make it possible to use data-driven machine learning methods to develop discriminative ranking-based models that predict the intensity ranks of a peptide's fragment ions. We use simple sequence-based features that get combined by a boosting algorithm in to models that make peak rank predictions with high accuracy. In an accompanying manuscript, we demonstrate how these prediction models are used to significantly improve the performance of peptide identification algorithms. The models can also be useful in the design of optimal MRM transitions, in cases where there is insufficient experimental data to guide the peak selection process. The prediction algorithm can also be run independently through PepNovo+, which is available for download from http://bix.ucsd.edu/Software/PepNovo.html. PMID:19256476
Failure Criteria for FRP Laminates in Plane Stress

NASA Technical Reports Server (NTRS)

Davila, Carlos G.; Camanho, Pedro P.

2003-01-01

A new set of six failure criteria for fiber reinforced polymer laminates is described. Derived from Dvorak's fracture mechanics analyses of cracked plies and from Puck's action plane concept, the physically-based criteria, denoted LaRC03, predict matrix and fiber failure accurately without requiring curve-fitting parameters. For matrix failure under transverse compression, the fracture plane is calculated by maximizing the Mohr-Coulomb effective stresses. A criterion for fiber kinking is obtained by calculating the fiber misalignment under load, and applying the matrix failure criterion in the coordinate frame of the misalignment. Fracture mechanics models of matrix cracks are used to develop a criterion for matrix in tension and to calculate the associated in-situ strengths. The LaRC03 criteria are applied to a few examples to predict failure load envelopes and to predict the failure mode for each region of the envelope. The analysis results are compared to the predictions using other available failure criteria and with experimental results. Predictions obtained with LaRC03 correlate well with the experimental results.
Comparison of LEWICE 1.6 and LEWICE/NS with IRT experimental data from modern air foil tests

DOT National Transportation Integrated Search

1998-01-01

A research project is underway at NASA Lewis to produce a computer code which can accurately predict ice growth under any meteorological conditions for any aircraft surface. The most recent release of this code is LEWICE 1.6. This code is modular in ...
Measurement Of Trailing Edge Noise using Directional Array and Coherent Output Power Methods

NASA Technical Reports Server (NTRS)

Hutcheson, Florence V.; Brooks, Thomas F.

2002-01-01

The use of a directional array of microphones for the measurement of trailing edge (TE) noise is described. The capabilities of this method are evaluated via measurements of TE noise from a NACA 63-215 airfoil model and from a cylindrical rod. This TE noise measurement approach is compared to one that is based on the cross spectral analysis of output signals from a pair of microphones (COP method). Advantages and limitations of both methods are examined. It is shown that the microphone array can accurately measures TE noise and captures its two-dimensional characteristic over a large frequency range for any TE configuration as long as noise contamination from extraneous sources is within bounds. The COP method is shown to also accurately measure TE noise but over a more limited frequency range that narrows for increased TE thickness. Finally, the applicability and generality of an airfoil self-noise prediction method was evaluated via comparison to the experimental data obtained using the COP and array measurement methods. The predicted and experimental results are shown to agree over large frequency ranges.
Effects of Freestream Turbulence on Turbine Blade Heat Transfer

NASA Technical Reports Server (NTRS)

Boyle, Robert J.; Giel, Paul W.; Ames, Forrest E.

2004-01-01

Experiments have shown that moderate turbulence levels can nearly double turbine blade stagnation region heat transfer. Data have also shown that heat transfer is strongly affected by the scale of turbulence as well as its level. In addition to the stagnation region, turbulence is often seen to increase pressure surface heat transfer. This is especially evident at low to moderate Reynolds numbers. Vane and rotor stagnation region, and vane pressure surface heat transfer augmentation is often seen in a pre-transition environment. Accurate predictions of transition and relaminarization are critical to accurately predicting blade surface heat transfer. An approach is described which incorporates the effects of both turbulence level and scale into a CFD analysis. The model is derived from experimental data for cylindrical and elliptical leadng edges. Results using this model are compared to experimental data for both vane and rotor geometries. The comparisons are made to illustrate that using a model which includes the effects of turbulence length scale improves agreement with data, and to illustrate where improvements in the modeling are needed.
Pseudoracemic amino acid complexes: blind predictions for flexible two-component crystals.

PubMed

Görbitz, Carl Henrik; Dalhus, Bjørn; Day, Graeme M

2010-08-14

Ab initio prediction of the crystal packing in complexes between two flexible molecules is a particularly challenging computational chemistry problem. In this work we present results of single crystal structure determinations as well as theoretical predictions for three 1 ratio 1 complexes between hydrophobic l- and d-amino acids (pseudoracemates), known from previous crystallographic work to form structures with one of two alternative hydrogen bonding arrangements. These are accurately reproduced in the theoretical predictions together with a series of patterns that have never been observed experimentally. In this bewildering forest of potential polymorphs, hydrogen bonding arrangements and molecular conformations, the theoretical predictions succeeded, for all three complexes, in finding the correct hydrogen bonding pattern. For two of the complexes, the calculations also reproduce the exact space group and side chain orientations in the best ranked predicted structure. This includes one complex for which the observed crystal packing clearly contradicted previous experience based on experimental data for a substantial number of related amino acid complexes. The results highlight the significant recent advances that have been made in computational methods for crystal structure prediction.
A Novel Method for Accurate Operon Predictions in All SequencedProkaryotes

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

Price, Morgan N.; Huang, Katherine H.; Alm, Eric J.

2004-12-01

We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83% accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacterpylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, andmore » its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from sixphylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC6803 has many operons even though it has unusually wide spacings between conserved adjacent genes.« less
Mathematics as a Conduit for Translational Research in Post-Traumatic Osteoarthritis

PubMed Central

Ayati, Bruce P.; Kapitanov, Georgi I.; Coleman, Mitchell C.; Anderson, Donald D.; Martin, James A.

2016-01-01

Biomathematical models offer a powerful method of clarifying complex temporal interactions and the relationships among multiple variables in a system. We present a coupled in silico biomathematical model of articular cartilage degeneration in response to impact and/or aberrant loading such as would be associated with injury to an articular joint. The model incorporates fundamental biological and mechanical information obtained from explant and small animal studies to predict post-traumatic osteoarthritis (PTOA) progression, with an eye toward eventual application in human patients. In this sense, we refer to the mathematics as a “conduit of translation”. The new in silico framework presented in this paper involves a biomathematical model for the cellular and biochemical response to strains computed using finite element analysis. The model predicts qualitative responses presently, utilizing system parameter values largely taken from the literature. To contribute to accurate predictions, models need to be accurately parameterized with values that are based on solid science. We discuss a parameter identification protocol that will enable us to make increasingly accurate predictions of PTOA progression using additional data from smaller scale explant and small animal assays as they become available. By distilling the data from the explant and animal assays into parameters for biomathematical models, mathematics can translate experimental data to clinically relevant knowledge. PMID:27653021
Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome.

PubMed

Li, Fuyi; Li, Chen; Marquez-Lago, Tatiana T; Leier, André; Akutsu, Tatsuya; Purcell, Anthony W; Smith, A Ian; Lithgow, Trevor; Daly, Roger J; Song, Jiangning; Chou, Kuo-Chen

2018-06-27

Kinase-regulated phosphorylation is a ubiquitous type of post-translational modification (PTM) in both eukaryotic and prokaryotic cells. Phosphorylation plays fundamental roles in many signalling pathways and biological processes, such as protein degradation and protein-protein interactions. Experimental studies have revealed that signalling defects caused by aberrant phosphorylation are highly associated with a variety of human diseases, especially cancers. In light of this, a number of computational methods aiming to accurately predict protein kinase family-specific or kinase-specific phosphorylation sites have been established, thereby facilitating phosphoproteomic data analysis. In this work, we present Quokka, a novel bioinformatics tool that allows users to rapidly and accurately identify human kinase family-regulated phosphorylation sites. Quokka was developed by using a variety of sequence scoring functions combined with an optimized logistic regression algorithm. We evaluated Quokka based on well-prepared up-to-date benchmark and independent test datasets, curated from the Phospho.ELM and UniProt databases, respectively. The independent test demonstrates that Quokka improves the prediction performance compared with state-of-the-art computational tools for phosphorylation prediction. In summary, our tool provides users with high-quality predicted human phosphorylation sites for hypothesis generation and biological validation. The Quokka webserver and datasets are freely available at http://quokka.erc.monash.edu/. Supplementary data are available at Bioinformatics online.
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.
MicroRNAfold: pre-microRNA secondary structure prediction based on modified NCM model with thermodynamics-based scoring strategy.

PubMed

Han, Dianwei; Zhang, Jun; Tang, Guiliang

2012-01-01

An accurate prediction of the pre-microRNA secondary structure is important in miRNA informatics. Based on a recently proposed model, nucleotide cyclic motifs (NCM), to predict RNA secondary structure, we propose and implement a Modified NCM (MNCM) model with a physics-based scoring strategy to tackle the problem of pre-microRNA folding. Our microRNAfold is implemented using a global optimal algorithm based on the bottom-up local optimal solutions. Our experimental results show that microRNAfold outperforms the current leading prediction tools in terms of True Negative rate, False Negative rate, Specificity, and Matthews coefficient ratio.
Increasing Prediction the Original Final Year Project of Student Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Saragih, Rijois Iboy Erwin; Turnip, Mardi; Sitanggang, Delima; Aritonang, Mendarissan; Harianja, Eva

2018-04-01

Final year project is very important forgraduation study of a student. Unfortunately, many students are not seriouslydidtheir final projects. Many of studentsask for someone to do it for them. In this paper, an application of genetic algorithms to predict the original final year project of a studentis proposed. In the simulation, the data of the final project for the last 5 years is collected. The genetic algorithm has several operators namely population, selection, crossover, and mutation. The result suggest that genetic algorithm can do better prediction than other comparable model. Experimental results of predicting showed that 70% was more accurate than the previous researched.
Superprism effect in a metal-clad terahertz photonic crystal slab.

PubMed

Prasad, Tushar; Colvin, Vicki L; Jian, Zhongping; Mittleman, Daniel M

2007-03-15

We report an experimental demonstration of the superprism effect in a photonic crystal slab at terahertz frequencies. For a 10% frequency variation around 0.28 THz, the refraction angle at the output facet of a wedge-shaped photonic crystal varies by about 15 degrees. A comparison with the predictions of a band structure calculation demonstrates that a three-dimensional treatment, accurately modeling the finite slab thickness and the metallic boundary conditions, is required for even a qualitative agreement with the experimental observations.

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

Jorgensen, S.

Testing the behavior of metals in extreme environments is not always feasible, so material scientists use models to try and predict the behavior. To achieve accurate results it is necessary to use the appropriate model and material-specific parameters. This research evaluated the performance of six material models available in the MIDAS database [1] to determine at which temperatures and strain-rates they perform best, and to determine to which experimental data their parameters were optimized. Additionally, parameters were optimized for the Johnson-Cook model using experimental data from Lassila et al [2].
Shock compression response of cold-rolled Ni/Al multilayer composites

NASA Astrophysics Data System (ADS)

Specht, Paul E.; Weihs, Timothy P.; Thadhani, Naresh N.

2017-01-01

Uniaxial strain, plate-on-plate impact experiments were performed on cold-rolled Ni/Al multilayer composites and the resulting Hugoniot was determined through time-resolved measurements combined with impedance matching. The experimental Hugoniot agreed with that previously predicted by two dimensional (2D) meso-scale calculations [Specht et al., J. Appl. Phys. 111, 073527 (2012)]. Additional 2D meso-scale simulations were performed using the same computational method as the prior study to reproduce the experimentally measured free surface velocities and stress profiles. These simulations accurately replicated the experimental profiles, providing additional validation for the previous computational work.
A numerical study of mixing in supersonic combustors with hypermixing injectors

NASA Technical Reports Server (NTRS)

Lee, J.

1993-01-01

A numerical study was conducted to evaluate the performance of wall mounted fuel-injectors designed for potential Supersonic Combustion Ramjet (SCRAM-jet) engine applications. The focus of this investigation was to numerically simulate existing combustor designs for the purpose of validating the numerical technique and the physical models developed. Three different injector designs of varying complexity were studied to fully understand the computational implications involved in accurate predictions. A dual transverse injection system and two streamwise injector designs were studied. The streamwise injectors were designed with swept ramps to enhance fuel-air mixing and combustion characteristics at supersonic speeds without the large flow blockage and drag contribution of the transverse injection system. For this study, the Mass-Average Navier-Stokes equations and the chemical species continuity equations were solved. The computations were performed using a finite-volume implicit numerical technique and multiple block structured grid system. The interfaces of the multiple block structured grid systems were numerically resolved using the flux-conservative technique. Detailed comparisons between the computations and existing experimental data are presented. These comparisons show that numerical predictions are in agreement with the experimental data. These comparisons also show that a number of turbulence model improvements are needed for accurate combustor flowfield predictions.
A numerical study of mixing in supersonic combustors with hypermixing injectors

NASA Technical Reports Server (NTRS)

Lee, J.

1992-01-01

A numerical study was conducted to evaluate the performance of wall mounted fuel-injectors designed for potential Supersonic Combustion Ramjet (SCRAM-jet) engine applications. The focus of this investigation was to numerically simulate existing combustor designs for the purpose of validating the numerical technique and the physical models developed. Three different injector designs of varying complexity were studied to fully understand the computational implications involved in accurate predictions. A dual transverse injection system and two streamwise injector designs were studied. The streamwise injectors were designed with swept ramps to enhance fuel-air mixing and combustion characteristics at supersonic speeds without the large flow blockage and drag contribution of the transverse injection system. For this study, the Mass-Averaged Navier-Stokes equations and the chemical species continuity equations were solved. The computations were performed using a finite-volume implicit numerical technique and multiple block structured grid system. The interfaces of the multiple block structured grid systems were numerically resolved using the flux-conservative technique. Detailed comparisons between the computations and existing experimental data are presented. These comparisons show that numerical predictions are in agreement with the experimental data. These comparisons also show that a number of turbulence model improvements are needed for accurate combustor flowfield predictions.
Intelligent Prediction of Fan Rotation Stall in Power Plants Based on Pressure Sensor Data Measured In-Situ

PubMed Central

Xu, Xiaogang; Wang, Songling; Liu, Jinlian; Liu, Xinyu

2014-01-01

Blower and exhaust fans consume over 30% of electricity in a thermal power plant, and faults of these fans due to rotation stalls are one of the most frequent reasons for power plant outage failures. To accurately predict the occurrence of fan rotation stalls, we propose a support vector regression machine (SVRM) model that predicts the fan internal pressures during operation, leaving ample time for rotation stall detection. We train the SVRM model using experimental data samples, and perform pressure data prediction using the trained SVRM model. To prove the feasibility of using the SVRM model for rotation stall prediction, we further process the predicted pressure data via wavelet-transform-based stall detection. By comparison of the detection results from the predicted and measured pressure data, we demonstrate that the SVRM model can accurately predict the fan pressure and guarantee reliable stall detection with a time advance of up to 0.0625 s. This superior pressure data prediction capability leaves significant time for effective control and prevention of fan rotation stall faults. This model has great potential for use in intelligent fan systems with stall prevention capability, which will ensure safe operation and improve the energy efficiency of power plants. PMID:24854057
On the critical temperature, normal boiling point, and vapor pressure of ionic liquids.

PubMed

Rebelo, Luis P N; Canongia Lopes, José N; Esperança, José M S S; Filipe, Eduardo

2005-04-07

One-stage, reduced-pressure distillations at moderate temperature of 1-decyl- and 1-dodecyl-3-methylimidazolium bistriflilamide ([Ntf(2)](-)) ionic liquids (ILs) have been performed. These liquid-vapor equilibria can be understood in light of predictions for normal boiling points of ILs. The predictions are based on experimental surface tension and density data, which are used to estimate the critical points of several ILs and their corresponding normal boiling temperatures. In contrast to the situation found for relatively unstable ILs at high-temperature such as those containing [BF(4)](-) or [PF(6)](-) anions, [Ntf(2)](-)-based ILs constitute a promising class in which reliable, accurate vapor pressure measurements can in principle be performed. This property is paramount for assisting in the development and testing of accurate molecular models.
A practical approach for predicting retention time shifts due to pressure and temperature gradients in ultra-high-pressure liquid chromatography.

PubMed

Åsberg, Dennis; Chutkowski, Marcin; Leśko, Marek; Samuelsson, Jörgen; Kaczmarski, Krzysztof; Fornstedt, Torgny

2017-01-06

Large pressure gradients are generated in ultra-high-pressure liquid chromatography (UHPLC) using sub-2μm particles causing significant temperature gradients over the column due to viscous heating. These pressure and temperature gradients affect retention and ultimately result in important selectivity shifts. In this study, we developed an approach for predicting the retention time shifts due to these gradients. The approach is presented as a step-by-step procedure and it is based on empirical linear relationships describing how retention varies as a function of temperature and pressure and how the average column temperature increases with the flow rate. It requires only four experiments on standard equipment, is based on straightforward calculations, and is therefore easy to use in method development. The approach was rigorously validated against experimental data obtained with a quality control method for the active pharmaceutical ingredient omeprazole. The accuracy of retention time predictions was very good with relative errors always less than 1% and in many cases around 0.5% (n=32). Selectivity shifts observed between omeprazole and the related impurities when changing the flow rate could also be accurately predicted resulting in good estimates of the resolution between critical peak pairs. The approximations which the presented approach are based on were all justified. The retention factor as a function of pressure and temperature was studied in an experimental design while the temperature distribution in the column was obtained by solving the fundamental heat and mass balance equations for the different experimental conditions. We strongly believe that this approach is sufficiently accurate and experimentally feasible for this separation to be a valuable tool when developing a UHPLC method. After further validation with other separation systems, it could become a useful approach in UHPLC method development, especially in the pharmaceutical industry where demands are high for robustness and regulatory oversight. Copyright © 2016 Elsevier B.V. All rights reserved.
Estimation of state and material properties during heat-curing molding of composite materials using data assimilation: A numerical study.

PubMed

Matsuzaki, Ryosuke; Tachikawa, Takeshi; Ishizuka, Junya

2018-03-01

Accurate simulations of carbon fiber-reinforced plastic (CFRP) molding are vital for the development of high-quality products. However, such simulations are challenging and previous attempts to improve the accuracy of simulations by incorporating the data acquired from mold monitoring have not been completely successful. Therefore, in the present study, we developed a method to accurately predict various CFRP thermoset molding characteristics based on data assimilation, a process that combines theoretical and experimental values. The degree of cure as well as temperature and thermal conductivity distributions during the molding process were estimated using both temperature data and numerical simulations. An initial numerical experiment demonstrated that the internal mold state could be determined solely from the surface temperature values. A subsequent numerical experiment to validate this method showed that estimations based on surface temperatures were highly accurate in the case of degree of cure and internal temperature, although predictions of thermal conductivity were more difficult.
An electrochemical modeling of lithium-ion battery nail penetration

NASA Astrophysics Data System (ADS)

Chiu, Kuan-Cheng; Lin, Chi-Hao; Yeh, Sheng-Fa; Lin, Yu-Han; Chen, Kuo-Ching

2014-04-01

Nail penetration into a battery pack, resulting in a state of short-circuit and thus burning, is likely to occur in electric car collisions. To demonstrate the behavior of a specific battery when subject to such incidents, a standard nail penetration test is usually performed; however, conducting such an experiment is money consuming. The purpose of this study is to propose a numerical electrochemical model that can simulate the test accurately. This simulation makes two accurate predictions. First, we are able to model short-circuited lithium-ion batteries (LIBs) via electrochemical governing equations so that the mass and charge transfer effect could be considered. Second, the temperature variation of the cell during and after nail penetration is accurately predicted with the help of simulating the temperature distribution of thermal runaway cells by thermal abuse equations. According to this nail penetration model, both the onset of battery thermal runaway and the cell temperature profile of the test are obtained, both of which are well fitted with our experimental results.
Accurate van der Waals force field for gas adsorption in porous materials.

PubMed

Sun, Lei; Yang, Li; Zhang, Ya-Dong; Shi, Qi; Lu, Rui-Feng; Deng, Wei-Qiao

2017-09-05

An accurate van der Waals force field (VDW FF) was derived from highly precise quantum mechanical (QM) calculations. Small molecular clusters were used to explore van der Waals interactions between gas molecules and porous materials. The parameters of the accurate van der Waals force field were determined by QM calculations. To validate the force field, the prediction results from the VDW FF were compared with standard FFs, such as UFF, Dreiding, Pcff, and Compass. The results from the VDW FF were in excellent agreement with the experimental measurements. This force field can be applied to the prediction of the gas density (H 2 , CO 2 , C 2 H 4 , CH 4 , N 2 , O 2 ) and adsorption performance inside porous materials, such as covalent organic frameworks (COFs), zeolites and metal organic frameworks (MOFs), consisting of H, B, N, C, O, S, Si, Al, Zn, Mg, Ni, and Co. This work provides a solid basis for studying gas adsorption in porous materials. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
An unexpected way forward: towards a more accurate and rigorous protein-protein binding affinity scoring function by eliminating terms from an already simple scoring function.

PubMed

Swanson, Jon; Audie, Joseph

2018-01-01

A fundamental and unsolved problem in biophysical chemistry is the development of a computationally simple, physically intuitive, and generally applicable method for accurately predicting and physically explaining protein-protein binding affinities from protein-protein interaction (PPI) complex coordinates. Here, we propose that the simplification of a previously described six-term PPI scoring function to a four term function results in a simple expression of all physically and statistically meaningful terms that can be used to accurately predict and explain binding affinities for a well-defined subset of PPIs that are characterized by (1) crystallographic coordinates, (2) rigid-body association, (3) normal interface size, and hydrophobicity and hydrophilicity, and (4) high quality experimental binding affinity measurements. We further propose that the four-term scoring function could be regarded as a core expression for future development into a more general PPI scoring function. Our work has clear implications for PPI modeling and structure-based drug design.
Experimental and analytical studies of a model helicopter rotor in hover

NASA Technical Reports Server (NTRS)

Caradonna, F. X.; Tung, C.

1981-01-01

A benchmark test to aid the development of various rotor performance codes was conducted. Simultaneous blade pressure measurements and tip vortex surveys were made for a wide range of tip Mach numbers including the transonic flow regime. The measured tip vortex strength and geometry permit effective blade loading predictions when used as input to a prescribed wake lifting surface code. It is also shown that with proper inflow and boundary layer modeling, the supercritical flow regime can be accurately predicted.
Simple optimized Brenner potential for thermodynamic properties of diamond

NASA Astrophysics Data System (ADS)

Liu, F.; Tang, Q. H.; Shang, B. S.; Wang, T. C.

2012-02-01

We have examined the commonly used Brenner potentials in the context of the thermodynamic properties of diamond. A simple optimized Brenner potential is proposed that provides very good predictions of the thermodynamic properties of diamond. It is shown that, compared to the experimental data, the lattice wave theory of molecular dynamics (LWT) with this optimized Brenner potential can accurately predict the temperature dependence of specific heat, lattice constant, Grüneisen parameters and coefficient of thermal expansion (CTE) of diamond.
The applicability of a computer model for predicting head injury incurred during actual motor vehicle collisions.

PubMed

Moran, Stephan G; Key, Jason S; McGwin, Gerald; Keeley, Jason W; Davidson, James S; Rue, Loring W

2004-07-01

Head injury is a significant cause of both morbidity and mortality. Motor vehicle collisions (MVCs) are the most common source of head injury in the United States. No studies have conclusively determined the applicability of computer models for accurate prediction of head injuries sustained in actual MVCs. This study sought to determine the applicability of such models for predicting head injuries sustained by MVC occupants. The Crash Injury Research and Engineering Network (CIREN) database was queried for restrained drivers who sustained a head injury. These collisions were modeled using occupant dynamic modeling (MADYMO) software, and head injury scores were generated. The computer-generated head injury scores then were evaluated with respect to the actual head injuries sustained by the occupants to determine the applicability of MADYMO computer modeling for predicting head injury. Five occupants meeting the selection criteria for the study were selected from the CIREN database. The head injury scores generated by MADYMO were lower than expected given the actual injuries sustained. In only one case did the computer analysis predict a head injury of a severity similar to that actually sustained by the occupant. Although computer modeling accurately simulates experimental crash tests, it may not be applicable for predicting head injury in actual MVCs. Many complicating factors surrounding actual MVCs make accurate computer modeling difficult. Future modeling efforts should consider variables such as age of the occupant and should account for a wider variety of crash scenarios.
FY17 Status Report on the Micromechanical Finite Element Modeling of Creep Fracture of Grade 91 Steel

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

Messner, M. C.; Truster, T. J.; Cochran, K. B.

Advanced reactors designed to operate at higher temperatures than current light water reactors require structural materials with high creep strength and creep-fatigue resistance to achieve long design lives. Grade 91 is a ferritic/martensitic steel designed for long creep life at elevated temperatures. It has been selected as a candidate material for sodium fast reactor intermediate heat exchangers and other advanced reactor structural components. This report focuses on the creep deformation and rupture life of Grade 91 steel. The time required to complete an experiment limits the availability of long-life creep data for Grade 91 and other structural materials. Design methodsmore » often extrapolate the available shorter-term experimental data to longer design lives. However, extrapolation methods tacitly assume the underlying material mechanisms causing creep for long-life/low-stress conditions are the same as the mechanisms controlling creep in the short-life/high-stress experiments. A change in mechanism for long-term creep could cause design methods based on extrapolation to be non-conservative. The goal for physically-based microstructural models is to accurately predict material response in experimentally-inaccessible regions of design space. An accurate physically-based model for creep represents all the material mechanisms that contribute to creep deformation and damage and predicts the relative influence of each mechanism, which changes with loading conditions. Ideally, the individual mechanism models adhere to the material physics and not an empirical calibration to experimental data and so the model remains predictive for a wider range of loading conditions. This report describes such a physically-based microstructural model for Grade 91 at 600° C. The model explicitly represents competing dislocation and diffusional mechanisms in both the grain bulk and grain boundaries. The model accurately recovers the available experimental creep curves at higher stresses and the limited experimental data at lower stresses, predominately primary creep rates. The current model considers only one temperature. However, because the model parameters are, for the most part, directly related to the physics of fundamental material processes, the temperature dependence of the properties are known. Therefore, temperature dependence can be included in the model with limited additional effort. The model predicts a mechanism shift for 600° C at approximately 100 MPa from a dislocation- dominated regime at higher stress to a diffusion-dominated regime at lower stress. This mechanism shift impacts the creep life, notch-sensitivity, and, likely, creep ductility of Grade 91. In particular, the model predicts existing extrapolation methods for creep life may be non-conservative when attempting to extrapolate data for higher stress creep tests to low stress, long-life conditions. Furthermore, the model predicts a transition from notchstrengthening behavior at high stress to notch-weakening behavior at lower stresses. Both behaviors may affect the conservatism of existing design methods.« less
DRA/NASA/ONERA Collaboration on Icing Research. Part 2; Prediction of Airfoil Ice Accretion

NASA Technical Reports Server (NTRS)

Wright, William B.; Gent, R. W.; Guffond, Didier

1997-01-01

This report presents results from a joint study by DRA, NASA, and ONERA for the purpose of comparing, improving, and validating the aircraft icing computer codes developed by each agency. These codes are of three kinds: (1) water droplet trajectory prediction, (2) ice accretion modeling, and (3) transient electrothermal deicer analysis. In this joint study, the agencies compared their code predictions with each other and with experimental results. These comparison exercises were published in three technical reports, each with joint authorship. DRA published and had first authorship of Part 1 - Droplet Trajectory Calculations, NASA of Part 2 - Ice Accretion Prediction, and ONERA of Part 3 - Electrothermal Deicer Analysis. The results cover work done during the period from August 1986 to late 1991. As a result, all of the information in this report is dated. Where necessary, current information is provided to show the direction of current research. In this present report on ice accretion, each agency predicted ice shapes on two dimensional airfoils under icing conditions for which experimental ice shapes were available. In general, all three codes did a reasonable job of predicting the measured ice shapes. For any given experimental condition, one of the three codes predicted the general ice features (i.e., shape, impingement limits, mass of ice) somewhat better than did the other two. However, no single code consistently did better than the other two over the full range of conditions examined, which included rime, mixed, and glaze ice conditions. In several of the cases, DRA showed that the user's knowledge of icing can significantly improve the accuracy of the code prediction. Rime ice predictions were reasonably accurate and consistent among the codes, because droplets freeze on impact and the freezing model is simple. Glaze ice predictions were less accurate and less consistent among the codes, because the freezing model is more complex and is critically dependent upon unsubstantiated heat transfer and surface roughness models. Thus, heat transfer prediction methods used in the codes became the subject for a separate study in this report to compare predicted heat transfer coefficients with a limited experimental database of heat transfer coefficients for cylinders with simulated glaze and rime ice shapes. The codes did a good job of predicting heat transfer coefficients near the stagnation region of the ice shapes. But in the region of the ice horns, all three codes predicted heat transfer coefficients considerably higher than the measured values. An important conclusion of this study is that further research is needed to understand the finer detail of of the glaze ice accretion process and to develop improved glaze ice accretion models.
Age differences in recall and predicting recall of action events and words.

PubMed

McDonald-Miszczak, L; Hubley, A M; Hultsch, D F

1996-03-01

Age differences in recall and prediction of recall were examined with different memory tasks. We asked 36 younger (19-28 yrs) and 36 older (60-81 yrs) women to provide both global and item-by-item predictions of their recall, and then to recall either (a) Subject Performance Tasks (SPTs), (b) verb-noun word-pairs memorized in list-like fashion (Word-Pairs), or (c) nonsense verb-noun word-pairs (Nonsense-Pairs) over three experimental trials. Based on previous research, we hypothesized that these tasks would vary in relative difficulty and flexibility of encoding. The results indicated that (a) age differences in global predictions (task specific self-efficacy) and recall performance across trials were minimized with SPT as compared with verbal materials, (b) global predictions were higher and more accurate for SPT as compared to verbal materials, and (c) item-by-item predictions were most accurate for materials encoded with the most flexibility (Nonsense Pairs). The results suggest that SPTs may provide some level of environmental support to reduce age differences in performance and task-specific self-efficacy, but that memory monitoring may depend on specific characteristics of the stimuli (i.e., flexibility of encoding) rather than their verbal or nonverbal nature.
Volatilization of benzene and eight alkyl-substituted benzene compounds from water

USGS Publications Warehouse

Rathbun, R.E.; Tai, D.Y.

1988-01-01

Predicting the fate of organic compounds in streams and rivers often requires knowledge of the volatilization characteristics of the compounds. The reference-substance concept, involving laboratory-determined ratios of the liquid-film coefficients for volatilization of the organic compounds to the liquid-film coefficient for oxygen absorption, is used to predict liquid-film coefficients for streams and rivers. In the absence of experimental data, two procedures have been used for estimating these liquid-film coefficient ratios. These procedures, based on the molecular-diffusion coefficient and on the molecular weight, have been widely used but never extensively evaluated. Liquid-film coefficients for the volatilization of benzene and eight alkyl-substituted benzene compounds (toluene through n-octylbenzene) from water were measured in a constant-temperature, stirred water bath. Liquid-film coefficients for oxygen absorption were measured simultaneously. A range of water mixing conditions was used with a water temperature of 298.2 K. The ratios of the liquid-film coefficients for volatilization to the liquid-film coefficient for oxygen absorption for all of the organic compounds were independent of mixing conditions in the water. Experimental ratios ranged from 0.606 for benzene to 0.357 for n-octylbenzene. The molecular-diffusion-coefficient procedure accurately predicted the ratios for ethylbenzene through n-pentylbenzene with a power dependence of 0.566 on the molecular-diffusion coefficient, in agreement with published values. Predicted ratios for benzene and toluene were slightly larger than the experimental ratios. These differences were attributed to possible interactions between the molecules of these compounds and the water molecules and to benzene-benzene interactions that form dimers. Because these interactions also are likely to occur in natural waters, it was concluded that the experimental ratios are more correct than the predicted ratios for application purposes in the reference-substance concept. Predicted ratios for n-hexylbenzene, n-heptylbenzene, and n-octylbenzene were larger than the experimental ratios. These differences were attributed to a sorption-desorption process between these compounds and the surfaces of the constant-temperature water bath. Other experimental problems associated with preparing water solutions of these slightly soluble compounds also may have contributed to the differences. Because these processes are not part of the true volatilization process, it was concluded that the predicted ratios for these three compounds are probably more correct than the experimental ratios for application purposes in the reference-substance concept. Any model of the fate of these compounds in streams and rivers would have to include terms accounting for sorption processes, however. The molecular-weight procedure accurately predicted the ratios for ethylbenzene through n-pentylbenzene, but only if the power dependence on the molecular weight was decreased from the commonly used -0.500 to -0.427. Deviations for the low- and high-molecular-weight compounds were similar to those observed for the molecular-diffusion-coefficient procedure.
A novel model for estimating organic chemical bioconcentration in agricultural plants

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

Hung, H.; Mackay, D.; Di Guardo, A.

1995-12-31

There is increasing recognition that much human and wildlife exposure to organic contaminants can be traced through the food chain to bioconcentration in vegetation. For risk assessment, there is a need for an accurate model to predict organic chemical concentrations in plants. Existing models range from relatively simple correlations of concentrations using octanol-water or octanol-air partition coefficients, to complex models involving extensive physiological data. To satisfy the need for a relatively accurate model of intermediate complexity, a novel approach has been devised to predict organic chemical concentrations in agricultural plants as a function of soil and air concentrations, without themore » need for extensive plant physiological data. The plant is treated as three compartments, namely, leaves, roots and stems (including fruit and seeds). Data readily available from the literature, including chemical properties, volume, density and composition of each compartment; metabolic and growth rate of plant; and readily obtainable environmental conditions at the site are required as input. Results calculated from the model are compared with observed and experimentally-determined concentrations. It is suggested that the model, which includes a physiological database for agricultural plants, gives acceptably accurate predictions of chemical partitioning between plants, air and soil.« less
Kinetic approach to degradation mechanisms in polymer solar cells and their accurate lifetime predictions

NASA Astrophysics Data System (ADS)

Arshad, Muhammad Azeem; Maaroufi, AbdelKrim

2018-07-01

A beginning has been made in the present study regarding the accurate lifetime predictions of polymer solar cells. Certain reservations about the conventionally employed temperature accelerated lifetime measurements test for its unworthiness of predicting reliable lifetimes of polymer solar cells are brought into light. Critical issues concerning the accelerated lifetime testing include, assuming reaction mechanism instead of determining it, and relying solely on the temperature acceleration of a single property of material. An advanced approach comprising a set of theoretical models to estimate the accurate lifetimes of polymer solar cells is therefore suggested in order to suitably alternate the accelerated lifetime testing. This approach takes into account systematic kinetic modeling of various possible polymer degradation mechanisms under natural weathering conditions. The proposed kinetic approach is substantiated by its applications on experimental aging data-sets of polymer solar materials/solar cells including, P3HT polymer film, bulk heterojunction (MDMO-PPV:PCBM) and dye-sensitized solar cells. Based on the suggested approach, an efficacious lifetime determination formula for polymer solar cells is derived and tested on dye-sensitized solar cells. Some important merits of the proposed method are also pointed out and its prospective applications are discussed.

Highly Efficient Design-of-Experiments Methods for Combining CFD Analysis and Experimental Data

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Haller, Harold S.

2009-01-01

It is the purpose of this study to examine the impact of "highly efficient" Design-of-Experiments (DOE) methods for combining sets of CFD generated analysis data with smaller sets of Experimental test data in order to accurately predict performance results where experimental test data were not obtained. The study examines the impact of micro-ramp flow control on the shock wave boundary layer (SWBL) interaction where a complete paired set of data exist from both CFD analysis and Experimental measurements By combining the complete set of CFD analysis data composed of fifteen (15) cases with a smaller subset of experimental test data containing four/five (4/5) cases, compound data sets (CFD/EXP) were generated which allows the prediction of the complete set of Experimental results No statistical difference were found to exist between the combined (CFD/EXP) generated data sets and the complete Experimental data set composed of fifteen (15) cases. The same optimal micro-ramp configuration was obtained using the (CFD/EXP) generated data as obtained with the complete set of Experimental data, and the DOE response surfaces generated by the two data sets were also not statistically different.
Comparisons Between Experimental and Semi-theoretical Cutting Forces of CCS Disc Cutters

NASA Astrophysics Data System (ADS)

Xia, Yimin; Guo, Ben; Tan, Qing; Zhang, Xuhui; Lan, Hao; Ji, Zhiyong

2018-05-01

This paper focuses on comparisons between the experimental and semi-theoretical forces of CCS disc cutters acting on different rocks. The experimental forces obtained from LCM tests were used to evaluate the prediction accuracy of a semi-theoretical CSM model. The results show that the CSM model reliably predicts the normal forces acting on red sandstone and granite, but underestimates the normal forces acting on marble. Some additional LCM test data from the literature were collected to further explore the ability of the CSM model to predict the normal forces acting on rocks of different strengths. The CSM model underestimates the normal forces acting on soft rocks, semi-hard rocks and hard rocks by approximately 38, 38 and 10%, respectively, but very accurately predicts those acting on very hard and extremely hard rocks. A calibration factor is introduced to modify the normal forces estimated by the CSM model. The overall trend of the calibration factor is characterized by an exponential decrease with increasing rock uniaxial compressive strength. The mean fitting ratios between the normal forces estimated by the modified CSM model and the experimental normal forces acting on soft rocks, semi-hard rocks and hard rocks are 1.076, 0.879 and 1.013, respectively. The results indicate that the prediction accuracy and the reliability of the CSM model have been improved.
STITCHER: Dynamic assembly of likely amyloid and prion β-structures from secondary structure predictions

PubMed Central

Bryan, Allen W; O’Donnell, Charles W; Menke, Matthew; Cowen, Lenore J; Lindquist, Susan; Berger, Bonnie

2012-01-01

The supersecondary structure of amyloids and prions, proteins of intense clinical and biological interest, are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Previous work has demonstrated that probability-based prediction of discrete β-strand pairs can offer insight into these structures. Here, we devise a system of energetic rules that can be used to dynamically assemble these discrete β-strand pairs into complete amyloid β-structures. The STITCHER algorithm progressively ‘stitches’ strand-pairs into full β-sheets based on a novel free-energy model, incorporating experimentally observed amino-acid side-chain stacking contributions, entropic estimates, and steric restrictions for amyloidal parallel β-sheet construction. A dynamic program computes the top 50 structures and returns both the highest scoring structure and a consensus structure taken by polling this list for common discrete elements. Putative structural heterogeneity can be inferred from sequence regions that compose poorly. Predictions show agreement with experimental models of Alzheimer’s amyloid beta peptide and the Podospora anserina Het-s prion. Predictions of the HET-s homolog HET-S also reflect experimental observations of poor amyloid formation. We put forward predicted structures for the yeast prion Sup35, suggesting N-terminal structural stability enabled by tyrosine ladders, and C-terminal heterogeneity. Predictions for the Rnq1 prion and alpha-synuclein are also given, identifying a similar mix of homogenous and heterogeneous secondary structure elements. STITCHER provides novel insight into the energetic basis of amyloid structure, provides accurate structure predictions, and can help guide future experimental studies. Proteins 2012. © 2011 Wiley Periodicals, Inc. PMID:22095906
STITCHER: Dynamic assembly of likely amyloid and prion β-structures from secondary structure predictions.

PubMed

Bryan, Allen W; O'Donnell, Charles W; Menke, Matthew; Cowen, Lenore J; Lindquist, Susan; Berger, Bonnie

2012-02-01

The supersecondary structure of amyloids and prions, proteins of intense clinical and biological interest, are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Previous work has demonstrated that probability-based prediction of discrete β-strand pairs can offer insight into these structures. Here, we devise a system of energetic rules that can be used to dynamically assemble these discrete β-strand pairs into complete amyloid β-structures. The STITCHER algorithm progressively 'stitches' strand-pairs into full β-sheets based on a novel free-energy model, incorporating experimentally observed amino-acid side-chain stacking contributions, entropic estimates, and steric restrictions for amyloidal parallel β-sheet construction. A dynamic program computes the top 50 structures and returns both the highest scoring structure and a consensus structure taken by polling this list for common discrete elements. Putative structural heterogeneity can be inferred from sequence regions that compose poorly. Predictions show agreement with experimental models of Alzheimer's amyloid beta peptide and the Podospora anserina Het-s prion. Predictions of the HET-s homolog HET-S also reflect experimental observations of poor amyloid formation. We put forward predicted structures for the yeast prion Sup35, suggesting N-terminal structural stability enabled by tyrosine ladders, and C-terminal heterogeneity. Predictions for the Rnq1 prion and alpha-synuclein are also given, identifying a similar mix of homogenous and heterogeneous secondary structure elements. STITCHER provides novel insight into the energetic basis of amyloid structure, provides accurate structure predictions, and can help guide future experimental studies. Copyright © 2011 Wiley Periodicals, Inc.
Sulphur hexaflouride: low energy (e,2e) experiments and molecular three-body distorted wave theory

NASA Astrophysics Data System (ADS)

Nixon, Kate L.; Murray, Andrew J.; Chaluvadi, H.; Ning, C. G.; Colgan, James; Madison, Don H.

2016-10-01

Experimental and theoretical triple differential ionisation cross-sections (TDCSs) are presented for the highest occupied molecular orbital of sulphur hexafluoride. These measurements were performed in the low energy regime, with outgoing electron energies ranging from 5 to 40 eV in a coplanar geometry, and with energies of 10 and 20 eV in a perpendicular geometry. Complementary theoretical predictions of the TDCS were calculated using the molecular three-body distorted wave formalism. Calculations were performed using a proper average over molecular orientations as well as the orientation-averaged molecular orbital approximation. This more sophisticated model was found to be in closer agreement with the experimental data, however neither model accurately predicts the TDCS over all geometries and energies.
Towards Principled Experimental Study of Autonomous Mobile Robots

NASA Technical Reports Server (NTRS)

Gat, Erann

1995-01-01

We review the current state of research in autonomous mobile robots and conclude that there is an inadequate basis for predicting the reliability and behavior of robots operating in unengineered environments. We present a new approach to the study of autonomous mobile robot performance based on formal statistical analysis of independently reproducible experiments conducted on real robots. Simulators serve as models rather than experimental surrogates. We demonstrate three new results: 1) Two commonly used performance metrics (time and distance) are not as well correlated as is often tacitly assumed. 2) The probability distributions of these performance metrics are exponential rather than normal, and 3) a modular, object-oriented simulation accurately predicts the behavior of the real robot in a statistically significant manner.
Aero-Optics Code Development: Experimental Databases and AVUS Code Improvements

DTIC Science & Technology

2009-03-01

direction, helped predict accurate Strouhal number. 62 5. References [1] Siegenthaler, J., Gordeyev , S., and Jumper , E., “Shear Layers and Aperture...approach . . . . . . . . . . . . . . . . . 44 55 Grid used for the transonic flow past NACA0012 airfoil . . . . . . . . . . . . . . . . . . . . . 46 56...layer problem (Configuration II) . . . . . . . . . . . . . . . . 60 vi Acknowledgements The author would like to acknowledge Drs. Eric Jumper and
Gaussian mixture models as flux prediction method for central receivers

NASA Astrophysics Data System (ADS)

Grobler, Annemarie; Gauché, Paul; Smit, Willie

2016-05-01

Flux prediction methods are crucial to the design and operation of central receiver systems. Current methods such as the circular and elliptical (bivariate) Gaussian prediction methods are often used in field layout design and aiming strategies. For experimental or small central receiver systems, the flux profile of a single heliostat often deviates significantly from the circular and elliptical Gaussian models. Therefore a novel method of flux prediction was developed by incorporating the fitting of Gaussian mixture models onto flux profiles produced by flux measurement or ray tracing. A method was also developed to predict the Gaussian mixture model parameters of a single heliostat for a given time using image processing. Recording the predicted parameters in a database ensures that more accurate predictions are made in a shorter time frame.
Large eddy simulation of shock train in a convergent-divergent nozzle

NASA Astrophysics Data System (ADS)

Mousavi, Seyed Mahmood; Roohi, Ehsan

2014-12-01

This paper discusses the suitability of the Large Eddy Simulation (LES) turbulence modeling for the accurate simulation of the shock train phenomena in a convergent-divergent nozzle. To this aim, we selected an experimentally tested geometry and performed LES simulation for the same geometry. The structure and pressure recovery inside the shock train in the nozzle captured by LES model are compared with the experimental data, analytical expressions and numerical solutions obtained using various alternative turbulence models, including k-ɛ RNG, k-ω SST, and Reynolds stress model (RSM). Comparing with the experimental data, we observed that the LES solution not only predicts the "locations of the first shock" precisely, but also its results are quite accurate before and after the shock train. After validating the LES solution, we investigate the effects of the inlet total pressure on the shock train starting point and length. The effects of changes in the back pressure, nozzle inlet angle (NIA) and wall temperature on the behavior of the shock train are investigated by details.
Probing ionization potential, electron affinity and self-energy effect on the spectral shape and exciton binding energy of quantum liquid water with self-consistent many-body perturbation theory and the Bethe-Salpeter equation.

PubMed

Ziaei, Vafa; Bredow, Thomas

2018-05-31

An accurate theoretical prediction of ionization potential (IP) and electron affinity (EA) is key in understanding complex photochemical processes in aqueous environments. There have been numerous efforts in literature to accurately predict IP and EA of liquid water, however with often conflicting results depending on the level of theory and the underlying water structures. In a recent study based on hybrid-non-self-consistent many-body perturbation theory (MBPT) Gaiduk et al (2018 Nat. Commun. 9 247) predicted an IP of 10.2 eV and EA of 0.2 eV, resulting in an electronic band gap (i.e. electronic gap (IP-EA) as measured by photoelectron spectroscopy) of about 10 eV, redefining the widely cited experimental gap of 8.7 eV in literature. In the present work, we show that GW self-consistency and an implicit vertex correction in MBPT considerably affect recently reported EA values by Gaiduk et al (2018 Nat. Commun. 9 247) by about 1 eV. Furthermore, the choice of pseudo-potential is critical for an accurate determination of the absolute band positions. Consequently, the self-consistent GW approach with an implicit vertex correction based on projector augmented wave (PAW) method on top of quantum water structures predicts an IP of 10.2, an EA of 1.1, a fundamental gap of 9.1 eV and an exciton binding (Eb) energy of 0.9 eV for the first absorption band of liquid water via the Bethe-Salpeter equation (BSE). Only within such a self-consistent approach a simultanously accurate prediction of IP, EA, Eg, Eb is possible.
Theoretical prediction of nuclear magnetic shieldings and indirect spin-spin coupling constants in 1,1-, cis-, and trans-1,2-difluoroethylenes

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

Nozirov, Farhod, E-mail: teobaldk@gmail.com, E-mail: farhod.nozirov@gmail.com; Stachów, Michał, E-mail: michal.stachow@gmail.com; Kupka, Teobald, E-mail: teobaldk@gmail.com, E-mail: farhod.nozirov@gmail.com

2014-04-14

A theoretical prediction of nuclear magnetic shieldings and indirect spin-spin coupling constants in 1,1-, cis- and trans-1,2-difluoroethylenes is reported. The results obtained using density functional theory (DFT) combined with large basis sets and gauge-independent atomic orbital calculations were critically compared with experiment and conventional, higher level correlated electronic structure methods. Accurate structural, vibrational, and NMR parameters of difluoroethylenes were obtained using several density functionals combined with dedicated basis sets. B3LYP/6-311++G(3df,2pd) optimized structures of difluoroethylenes closely reproduced experimental geometries and earlier reported benchmark coupled cluster results, while BLYP/6-311++G(3df,2pd) produced accurate harmonic vibrational frequencies. The most accurate vibrations were obtained using B3LYP/6-311++G(3df,2pd)more » with correction for anharmonicity. Becke half and half (BHandH) density functional predicted more accurate {sup 19}F isotropic shieldings and van Voorhis and Scuseria's τ-dependent gradient-corrected correlation functional yielded better carbon shieldings than B3LYP. A surprisingly good performance of Hartree-Fock (HF) method in predicting nuclear shieldings in these molecules was observed. Inclusion of zero-point vibrational correction markedly improved agreement with experiment for nuclear shieldings calculated by HF, MP2, CCSD, and CCSD(T) methods but worsened the DFT results. The threefold improvement in accuracy when predicting {sup 2}J(FF) in 1,1-difluoroethylene for BHandH density functional compared to B3LYP was observed (the deviations from experiment were −46 vs. −115 Hz)« less
Probing ionization potential, electron affinity and self-energy effect on the spectral shape and exciton binding energy of quantum liquid water with self-consistent many-body perturbation theory and the Bethe–Salpeter equation

NASA Astrophysics Data System (ADS)

Ziaei, Vafa; Bredow, Thomas

2018-05-01

An accurate theoretical prediction of ionization potential (IP) and electron affinity (EA) is key in understanding complex photochemical processes in aqueous environments. There have been numerous efforts in literature to accurately predict IP and EA of liquid water, however with often conflicting results depending on the level of theory and the underlying water structures. In a recent study based on hybrid-non-self-consistent many-body perturbation theory (MBPT) Gaiduk et al (2018 Nat. Commun. 9 247) predicted an IP of 10.2 eV and EA of 0.2 eV, resulting in an electronic band gap (i.e. electronic gap (IP-EA) as measured by photoelectron spectroscopy) of about 10 eV, redefining the widely cited experimental gap of 8.7 eV in literature. In the present work, we show that GW self-consistency and an implicit vertex correction in MBPT considerably affect recently reported EA values by Gaiduk et al (2018 Nat. Commun. 9 247) by about 1 eV. Furthermore, the choice of pseudo-potential is critical for an accurate determination of the absolute band positions. Consequently, the self-consistent GW approach with an implicit vertex correction based on projector augmented wave (PAW) method on top of quantum water structures predicts an IP of 10.2, an EA of 1.1, a fundamental gap of 9.1 eV and an exciton binding (Eb) energy of 0.9 eV for the first absorption band of liquid water via the Bethe–Salpeter equation (BSE). Only within such a self-consistent approach a simultanously accurate prediction of IP, EA, Eg, Eb is possible.
Evaluation and modeling of the eutectic composition of various drug-polyethylene glycol solid dispersions.

PubMed

Baird, Jared A; Taylor, Lynne S

2011-06-01

The purpose of this study was to gain a better understanding of which factors contribute to the eutectic composition of drug-polyethylene glycol (PEG) blends and to compare experimental values with predictions from the semi-empirical model developed by Lacoulonche et al. Eutectic compositions of various drug-PEG 3350 solid dispersions were predicted, assuming athermal mixing, and compared to experimentally determined eutectic points. The presence or absence of specific interactions between the drug and PEG 3350 were investigated using Fourier transform infrared (FT-IR) spectroscopy. The eutectic composition for haloperidol-PEG and loratadine-PEG solid dispersions was accurately predicted using the model, while predictions for aceclofenac-PEG and chlorpropamide-PEG were very different from those experimentally observed. Deviations in the model prediction from ideal behavior for the systems evaluated were confirmed to be due to the presence of specific interactions between the drug and polymer, as demonstrated by IR spectroscopy. Detailed analysis showed that the eutectic composition prediction from the model is interdependent on the crystal lattice energy of the drug compound (evaluated from the melting temperature and the heat of fusion) as well as the nature of the drug-polymer interactions. In conclusion, for compounds with melting points less than 200°C, the model is ideally suited for predicting the eutectic composition of systems where there is an absence of drug-polymer interactions.
Improved Modeling of Finite-Rate Turbulent Combustion Processes in Research Combustors

NASA Technical Reports Server (NTRS)

VanOverbeke, Thomas J.

1998-01-01

The objective of this thesis is to further develop and test a stochastic model of turbulent combustion in recirculating flows. There is a requirement to increase the accuracy of multi-dimensional combustion predictions. As turbulence affects reaction rates, this interaction must be more accurately evaluated. In this work a more physically correct way of handling the interaction of turbulence on combustion is further developed and tested. As turbulence involves randomness, stochastic modeling is used. Averaged values such as temperature and species concentration are found by integrating the probability density function (pdf) over the range of the scalar. The model in this work does not assume the pdf type, but solves for the evolution of the pdf using the Monte Carlo solution technique. The model is further developed by including a more robust reaction solver, by using accurate thermodynamics and by more accurate transport elements. The stochastic method is used with Semi-Implicit Method for Pressure-Linked Equations. The SIMPLE method is used to solve for velocity, pressure, turbulent kinetic energy and dissipation. The pdf solver solves for temperature and species concentration. Thus, the method is partially familiar to combustor engineers. The method is compared to benchmark experimental data and baseline calculations. The baseline method was tested on isothermal flows, evaporating sprays and combusting sprays. Pdf and baseline predictions were performed for three diffusion flames and one premixed flame. The pdf method predicted lower combustion rates than the baseline method in agreement with the data, except for the premixed flame. The baseline and stochastic predictions bounded the experimental data for the premixed flame. The use of a continuous mixing model or relax to mean mixing model had little effect on the prediction of average temperature. Two grids were used in a hydrogen diffusion flame simulation. Grid density did not effect the predictions except for peak temperature and tangential velocity. The hybrid pdf method did take longer and required more memory, but has a theoretical basis to extend to many reaction steps which cannot be said of current turbulent combustion models.
Sequential experimental design based generalised ANOVA

NASA Astrophysics Data System (ADS)

Chakraborty, Souvik; Chowdhury, Rajib

2016-07-01

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover, generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.
Sequential experimental design based generalised ANOVA

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

Chakraborty, Souvik, E-mail: csouvik41@gmail.com; Chowdhury, Rajib, E-mail: rajibfce@iitr.ac.in

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover,more » generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.« less
A comparison of experimental and theoretical results for labyrinth gas seals with honeycomb stators. M.S. Thesis

NASA Technical Reports Server (NTRS)

Hawkins, Lawrence Allen

1988-01-01

Experimental results for the rotordynamic stiffness and damping coefficients of a labyrinth -rotor honeycomb-stator seal are presented. The coefficients are compared to the coefficients of a labyrinth-rotor smooth-stator seal having the same geometry. The coefficients are compared to analytical results from a two-control-volume compressible flow model. The experimental results show that the honeycomb stator configuration is more stable than the smooth stator configuration at low rotor speeds. At high rotor speeds and low clearance, the smooth stator seal is more stable. The theoretical model predicts the cross-coupled stiffness of the honeycomb stator seal correctly within 25 percent of measured values. The model provides accurate predictions of direct damping for large clearance seals. Overall, the model does not perform as well for low clearance seals as for high clearance seals.
Wake Geometry Measurements and Analytical Calculations on a Small-Scale Rotor Model

NASA Technical Reports Server (NTRS)

Ghee, Terence A.; Berry, John D.; Zori, Laith A. J.; Elliott, Joe W.

1996-01-01

An experimental investigation was conducted in the Langley 14- by 22-Foot Subsonic Tunnel to quantify the rotor wake behind a scale model helicopter rotor in forward level flight at one thrust level. The rotor system in this test consisted of a four-bladed fully articulated hub with blades of rectangular planform and an NACA 0012 airfoil section. A laser light sheet, seeded with propylene glycol smoke, was used to visualize the vortex geometry in the flow in planes parallel and perpendicular to the free-stream flow. Quantitative measurements of wake geometric proper- ties, such as vortex location, vertical skew angle, and vortex particle void radius, were obtained as well as convective velocities for blade tip vortices. Comparisons were made between experimental data and four computational method predictions of experimental tip vortex locations, vortex vertical skew angles, and wake geometries. The results of these comparisons highlight difficulties of accurate wake geometry predictions.
Comparison of experimental and calculated chiroptical spectra for chiral molecular structure determination.

PubMed

Polavarapu, Prasad L; Covington, Cody L

2014-09-01

For three different chiroptical spectroscopic methods, namely, vibrational circular dichroism (VCD), electronic circular dichroism (ECD), and Raman optical activity (ROA), the measures of similarity of the experimental spectra to the corresponding spectra predicted using quantum chemical theories are summarized. In determining the absolute configuration and/or predominant conformations of chiral molecules, these similarity measures provide numerical estimates of agreement between experimental observations and theoretical predictions. Selected applications illustrating the similarity measures for absorption, circular dichroism, and corresponding dissymmetry factor (DF) spectra, in the case of VCD and ECD, and for Raman, ROA, and circular intensity differential (CID) spectra in the case of ROA, are presented. The analysis of similarity in DF or CID spectra is considered to be much more discerning and accurate than that in absorption (or Raman) and circular dichroism (or ROA) spectra, undertaken individually. © 2014 Wiley Periodicals, Inc.
Electrosurgical vessel sealing tissue temperature: experimental measurement and finite element modeling.

PubMed

Chen, Roland K; Chastagner, Matthew W; Dodde, Robert E; Shih, Albert J

2013-02-01

The temporal and spatial tissue temperature profile in electrosurgical vessel sealing was experimentally measured and modeled using finite element modeling (FEM). Vessel sealing procedures are often performed near the neurovascular bundle and may cause collateral neural thermal damage. Therefore, the heat generated during electrosurgical vessel sealing is of concern among surgeons. Tissue temperature in an in vivo porcine femoral artery sealed using a bipolar electrosurgical device was studied. Three FEM techniques were incorporated to model the tissue evaporation, water loss, and fusion by manipulating the specific heat, electrical conductivity, and electrical contact resistance, respectively. These three techniques enable the FEM to accurately predict the vessel sealing tissue temperature profile. The averaged discrepancy between the experimentally measured temperature and the FEM predicted temperature at three thermistor locations is less than 7%. The maximum error is 23.9%. Effects of the three FEM techniques are also quantified.

A new improved study of cyanotoxins presence from experimental cyanobacteria concentrations in the Trasona reservoir (Northern Spain) using the MARS technique.

PubMed

García Nieto, P J; Alonso Fernández, J R; Sánchez Lasheras, F; de Cos Juez, F J; Díaz Muñiz, C

2012-07-15

Cyanotoxins, a kind of poisonous substances produced by cyanobacteria, are responsible for health risks in drinking and recreational water uses. The aim of this study is to improve our previous and successful work about cyanotoxins prediction from some experimental cyanobacteria concentrations in the Trasona reservoir (Asturias, Northern Spain) using the multivariate adaptive regression splines (MARS) technique at a local scale. In fact, this new improvement consists of using not only biological variables, but also the physical-chemical ones. As a result, the coefficient of determination has improved from 0.84 to 0.94, that is to say, more accurate predictive calculations and a better approximation to the real problem were obtained. Finally the agreement of the MARS model with experimental data confirmed the good performance. Copyright © 2012 Elsevier B.V. All rights reserved.
Crack Growth Prediction Methodology for Multi-Site Damage: Layered Analysis and Growth During Plasticity

NASA Technical Reports Server (NTRS)

James, Mark Anthony

1999-01-01

A finite element program has been developed to perform quasi-static, elastic-plastic crack growth simulations. The model provides a general framework for mixed-mode I/II elastic-plastic fracture analysis using small strain assumptions and plane stress, plane strain, and axisymmetric finite elements. Cracks are modeled explicitly in the mesh. As the cracks propagate, automatic remeshing algorithms delete the mesh local to the crack tip, extend the crack, and build a new mesh around the new tip. State variable mapping algorithms transfer stresses and displacements from the old mesh to the new mesh. The von Mises material model is implemented in the context of a non-linear Newton solution scheme. The fracture criterion is the critical crack tip opening displacement, and crack direction is predicted by the maximum tensile stress criterion at the crack tip. The implementation can accommodate multiple curving and interacting cracks. An additional fracture algorithm based on nodal release can be used to simulate fracture along a horizontal plane of symmetry. A core of plane strain elements can be used with the nodal release algorithm to simulate the triaxial state of stress near the crack tip. Verification and validation studies compare analysis results with experimental data and published three-dimensional analysis results. Fracture predictions using nodal release for compact tension, middle-crack tension, and multi-site damage test specimens produced accurate results for residual strength and link-up loads. Curving crack predictions using remeshing/mapping were compared with experimental data for an Arcan mixed-mode specimen. Loading angles from 0 degrees to 90 degrees were analyzed. The maximum tensile stress criterion was able to predict the crack direction and path for all loading angles in which the material failed in tension. Residual strength was also accurately predicted for these cases.
Comparison of fluid dynamic numerical models for a clinical ventricular assist device and experimental validation

PubMed Central

Zhang, Jiafeng; Zhang, Pei; Fraser, Katharine H.; Griffith, Bartley P.; Wu, Zhongjun J.

2012-01-01

With the recent advances in computer technology, computational fluid dynamics (CFD) has become an important tool to design and improve blood contacting artificial organs, and to study the device-induced blood damage. Commercial CFD software packages are readily available, and multiple CFD models are provided by CFD software developers. However, the best approach of using CFD effectively to characterize fluid flow and to predict blood damage in these medical devices remains debatable. This study aimed to compare these CFD models and provide useful information on the accuracy of each model in modeling blood flow in circulatory assist devices. The laminar and five turbulence models (Spalart-Allmaras, k-ε (k-epsilon), k-ω (k-omega), SST (Menter’s Shear Stress Transport), and Reynolds Stress) were implemented to predict blood flow in a clinically used circulatory assist device, CentriMag® centrifugal blood pump (Thoratec, MA). In parallel, a transparent replica of the CentriMag® pump was constructed and selected views of the flow fields were measured with digital particle image velocimetry (DPIV). CFD results were compared with the DPIV experimental results. Compared with the experiment, all the selected CFD models predicted the flow pattern fairly well except the area of the outlet. However, quantitatively, the laminar model results were the most deviated from the experimental data. On the other hand, k-ε RNG models and Reynolds Stress model are the most accurate. In conclusion, for the circulatory assist devices, turbulence models provide more accurate results than laminar model. Among the selected turbulence models, k-ε and Reynolds Stress Method models are recommended. PMID:23441681
The production and measurement of sub-bandage pressure: Laplace's Law revisited.

PubMed

Thomas, S

2014-05-01

The present study was undertaken to demonstrate that the pressures produced by multiple layers of compression bandages applied to artificial limbs of known circumference with predetermined levels of tension can be predicted accurately using the modified Laplace equation. Up to four layers of different bandage types were applied in a carefully controlled fashion to cylinders of known circumference, with tensions ranging from around 200-2000 grams/10cm width. The pressures generated were measured using pneumatic pressure sensors previously shown to possess the required degree of accuracy for this type of experimental system. Good correlation was observed between the mean and standard deviation of each pair of experimental and calculated pressure values for all combinations of bandage type, application tension and cylinder circumference. Over the clinically relevant range of pressures, the difference between data sets was generally less than 1.0mmHg. The results of this experimental study unequivocally prove that provided accurate values for all the relevant variables are known, it is possible to predict the pressure that will be developed by a compression bandage on a limb of known size. However, it is important to recognise that other factors such as the elastomeric properties of the fabric will have a major effect upon the ability of a bandage system to sustain initial compression values. Furthermore, the variation in radius of curvature around a limb will mean that point pressures readings recorded at individual locations around the circumference may vary dramatically from the average value predicted by the modified Laplace equation, calling into question the value of sub-bandage pressure measuring devices for this application.
Improving Seasonal Crop Monitoring and Forecasting for Soybean and Corn in Iowa

NASA Astrophysics Data System (ADS)

Togliatti, K.; Archontoulis, S.; Dietzel, R.; VanLoocke, A.

2016-12-01

Accurately forecasting crop yield in advance of harvest could greatly benefit farmers, however few evaluations have been conducted to determine the effectiveness of forecasting methods. We tested one such method that used a combination of short-term weather forecasting from the Weather Research and Forecasting Model (WRF) to predict in season weather variables, such as, maximum and minimum temperature, precipitation and radiation at 4 different forecast lengths (2 weeks, 1 week, 3 days, and 0 days). This forecasted weather data along with the current and historic (previous 35 years) data from the Iowa Environmental Mesonet was combined to drive Agricultural Production Systems sIMulator (APSIM) simulations to forecast soybean and corn yields in 2015 and 2016. The goal of this study is to find the forecast length that reduces the variability of simulated yield predictions while also increasing the accuracy of those predictions. APSIM simulations of crop variables were evaluated against bi-weekly field measurements of phenology, biomass, and leaf area index from early and late planted soybean plots located at the Agricultural Engineering and Agronomy Research Farm in central Iowa as well as the Northwest Research Farm in northwestern Iowa. WRF model predictions were evaluated against observed weather data collected at the experimental fields. Maximum temperature was the most accurately predicted variable, followed by minimum temperature and radiation, and precipitation was least accurate according to RMSE values and the number of days that were forecasted within a 20% error of the observed weather. Our analysis indicated that for the majority of months in the growing season the 3 day forecast performed the best. The 1 week forecast came in second and the 2 week forecast was the least accurate for the majority of months. Preliminary results for yield indicate that the 2 week forecast is the least variable of the forecast lengths, however it also is the least accurate. The 3 day and 1 week forecast have a better accuracy, with an increase in variability.
A Robust Adaptive Autonomous Approach to Optimal Experimental Design

NASA Astrophysics Data System (ADS)

Gu, Hairong

Experimentation is the fundamental tool of scientific inquiries to understand the laws governing the nature and human behaviors. Many complex real-world experimental scenarios, particularly in quest of prediction accuracy, often encounter difficulties to conduct experiments using an existing experimental procedure for the following two reasons. First, the existing experimental procedures require a parametric model to serve as the proxy of the latent data structure or data-generating mechanism at the beginning of an experiment. However, for those experimental scenarios of concern, a sound model is often unavailable before an experiment. Second, those experimental scenarios usually contain a large number of design variables, which potentially leads to a lengthy and costly data collection cycle. Incompetently, the existing experimental procedures are unable to optimize large-scale experiments so as to minimize the experimental length and cost. Facing the two challenges in those experimental scenarios, the aim of the present study is to develop a new experimental procedure that allows an experiment to be conducted without the assumption of a parametric model while still achieving satisfactory prediction, and performs optimization of experimental designs to improve the efficiency of an experiment. The new experimental procedure developed in the present study is named robust adaptive autonomous system (RAAS). RAAS is a procedure for sequential experiments composed of multiple experimental trials, which performs function estimation, variable selection, reverse prediction and design optimization on each trial. Directly addressing the challenges in those experimental scenarios of concern, function estimation and variable selection are performed by data-driven modeling methods to generate a predictive model from data collected during the course of an experiment, thus exempting the requirement of a parametric model at the beginning of an experiment; design optimization is performed to select experimental designs on the fly of an experiment based on their usefulness so that fewest designs are needed to reach useful inferential conclusions. Technically, function estimation is realized by Bayesian P-splines, variable selection is realized by Bayesian spike-and-slab prior, reverse prediction is realized by grid-search and design optimization is realized by the concepts of active learning. The present study demonstrated that RAAS achieves statistical robustness by making accurate predictions without the assumption of a parametric model serving as the proxy of latent data structure while the existing procedures can draw poor statistical inferences if a misspecified model is assumed; RAAS also achieves inferential efficiency by taking fewer designs to acquire useful statistical inferences than non-optimal procedures. Thus, RAAS is expected to be a principled solution to real-world experimental scenarios pursuing robust prediction and efficient experimentation.
Kinetic modeling of the light-dependent photosynthetic activity of the green microalga Chlorella vulgaris.

PubMed

Yun, Yeoung-Sang; Park, Jong Moon

2003-08-05

Light-dependent photosynthesis of Chlorella vulgaris was investigated by using a novel photosynthesis measurement system that could cover wide ranges of incident light and cell density and reproduce accurate readings. Various photosynthesis models, which have been reported elsewhere, were classified and/or reformulated based upon the underlying hypotheses of the light dependence of the algal photosynthesis. Four types of models were derived, which contained distinct light-related variables such as the average or local photon flux density (APFD or LPFD) and the average or local photon absorption rate (APAR or LPAR). According to our experimental results, the LPFD and LPAR models could predict the experimental data more accurately although the APFD and APAR models have been widely used for the kinetic study of microalgal photosynthesis. Copyright 2003 Wiley Periodicals, Inc. Biotechnol Bioeng 83: 303-311, 2003.
MLFMA-accelerated Nyström method for ultrasonic scattering - Numerical results and experimental validation

NASA Astrophysics Data System (ADS)

Gurrala, Praveen; Downs, Andrew; Chen, Kun; Song, Jiming; Roberts, Ron

2018-04-01

Full wave scattering models for ultrasonic waves are necessary for the accurate prediction of voltage signals received from complex defects/flaws in practical nondestructive evaluation (NDE) measurements. We propose the high-order Nyström method accelerated by the multilevel fast multipole algorithm (MLFMA) as an improvement to the state-of-the-art full-wave scattering models that are based on boundary integral equations. We present numerical results demonstrating improvements in simulation time and memory requirement. Particularly, we demonstrate the need for higher order geom-etry and field approximation in modeling NDE measurements. Also, we illustrate the importance of full-wave scattering models using experimental pulse-echo data from a spherical inclusion in a solid, which cannot be modeled accurately by approximation-based scattering models such as the Kirchhoff approximation.
Predicting protein interactions by Brownian dynamics simulations.

PubMed

Meng, Xuan-Yu; Xu, Yu; Zhang, Hong-Xing; Mezei, Mihaly; Cui, Meng

2012-01-01

We present a newly adapted Brownian-Dynamics (BD)-based protein docking method for predicting native protein complexes. The approach includes global BD conformational sampling, compact complex selection, and local energy minimization. In order to reduce the computational costs for energy evaluations, a shell-based grid force field was developed to represent the receptor protein and solvation effects. The performance of this BD protein docking approach has been evaluated on a test set of 24 crystal protein complexes. Reproduction of experimental structures in the test set indicates the adequate conformational sampling and accurate scoring of this BD protein docking approach. Furthermore, we have developed an approach to account for the flexibility of proteins, which has been successfully applied to reproduce the experimental complex structure from the structure of two unbounded proteins. These results indicate that this adapted BD protein docking approach can be useful for the prediction of protein-protein interactions.
Prediction of clothing thermal insulation and moisture vapour resistance of the clothed body walking in wind.

PubMed

Qian, Xiaoming; Fan, Jintu

2006-11-01

Clothing thermal insulation and moisture vapour resistance are the two most important parameters in thermal environmental engineering, functional clothing design and end use of clothing ensembles. In this study, clothing thermal insulation and moisture vapour resistance of various types of clothing ensembles were measured using the walking-able sweating manikin, Walter, under various environmental conditions and walking speeds. Based on an extensive experimental investigation and an improved understanding of the effects of body activities and environmental conditions, a simple but effective direct regression model has been established, for predicting the clothing thermal insulation and moisture vapour resistance under wind and walking motion, from those when the manikin was standing in still air. The model has been validated by using experimental data reported in the previous literature. It has shown that the new models have advantages and provide very accurate prediction.
Identification of Extracellular Segments by Mass Spectrometry Improves Topology Prediction of Transmembrane Proteins.

PubMed

Langó, Tamás; Róna, Gergely; Hunyadi-Gulyás, Éva; Turiák, Lilla; Varga, Julia; Dobson, László; Várady, György; Drahos, László; Vértessy, Beáta G; Medzihradszky, Katalin F; Szakács, Gergely; Tusnády, Gábor E

2017-02-13

Transmembrane proteins play crucial role in signaling, ion transport, nutrient uptake, as well as in maintaining the dynamic equilibrium between the internal and external environment of cells. Despite their important biological functions and abundance, less than 2% of all determined structures are transmembrane proteins. Given the persisting technical difficulties associated with high resolution structure determination of transmembrane proteins, additional methods, including computational and experimental techniques remain vital in promoting our understanding of their topologies, 3D structures, functions and interactions. Here we report a method for the high-throughput determination of extracellular segments of transmembrane proteins based on the identification of surface labeled and biotin captured peptide fragments by LC/MS/MS. We show that reliable identification of extracellular protein segments increases the accuracy and reliability of existing topology prediction algorithms. Using the experimental topology data as constraints, our improved prediction tool provides accurate and reliable topology models for hundreds of human transmembrane proteins.
Intermolecular potentials and the accurate prediction of the thermodynamic properties of water

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

Shvab, I.; Sadus, Richard J., E-mail: rsadus@swin.edu.au

2013-11-21

The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g/cm{sup 3} for a wide range of temperatures (298–650 K) and pressures (0.1–700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC/E and TIP4P/2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys.more » 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC/E and TIP4P/2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.« less
Derivation and experimental verification of clock synchronization theory

NASA Technical Reports Server (NTRS)

Palumbo, Daniel L.

1994-01-01

The objective of this work is to validate mathematically derived clock synchronization theories and their associated algorithms through experiment. Two theories are considered, the Interactive Convergence Clock Synchronization Algorithm and the Mid-Point Algorithm. Special clock circuitry was designed and built so that several operating conditions and failure modes (including malicious failures) could be tested. Both theories are shown to predict conservative upper bounds (i.e., measured values of clock skew were always less than the theory prediction). Insight gained during experimentation led to alternative derivations of the theories. These new theories accurately predict the clock system's behavior. It is found that a 100% penalty is paid to tolerate worst case failures. It is also shown that under optimal conditions (with minimum error and no failures) the clock skew can be as much as 3 clock ticks. Clock skew grows to 6 clock ticks when failures are present. Finally, it is concluded that one cannot rely solely on test procedures or theoretical analysis to predict worst case conditions. conditions.
Experimental validation of clock synchronization algorithms

NASA Technical Reports Server (NTRS)

Palumbo, Daniel L.; Graham, R. Lynn

1992-01-01

The objective of this work is to validate mathematically derived clock synchronization theories and their associated algorithms through experiment. Two theories are considered, the Interactive Convergence Clock Synchronization Algorithm and the Midpoint Algorithm. Special clock circuitry was designed and built so that several operating conditions and failure modes (including malicious failures) could be tested. Both theories are shown to predict conservative upper bounds (i.e., measured values of clock skew were always less than the theory prediction). Insight gained during experimentation led to alternative derivations of the theories. These new theories accurately predict the behavior of the clock system. It is found that a 100 percent penalty is paid to tolerate worst-case failures. It is also shown that under optimal conditions (with minimum error and no failures) the clock skew can be as much as three clock ticks. Clock skew grows to six clock ticks when failures are present. Finally, it is concluded that one cannot rely solely on test procedures or theoretical analysis to predict worst-case conditions.
On the phenomenon of curved microcracks in /(S)/90n/s laminates - Their shapes, initiation angles and locations

NASA Technical Reports Server (NTRS)

Hu, Shoufeng; Bark, Jong S.; Nairn, John A.

1993-01-01

A variational analysis of the stress state in microcracked cross-ply laminates has been used to investigate the phenomenon of curved microcracking in /(S)/90n/s laminates. Previous investigators proposed that the initiation and orientation of curved microcracks are controlled by local maxima and stress trajectories of the principal stresses. We have implemented a principal stress model using a variational mechanics stress analysis and we were able to make predictions about curved microcracks. The predictions agree well with experimental observations and therefore support the assertion that the variational analysis gives an accurate stress state that is useful for modeling the microcracking properties of cross-ply laminates. An important prediction about curved microcracks is that they are a late stage of microcracking damage. They occur only when the crack density of straight microcracks exceeds the critical crack density for curved microcracking. The predicted critical crack density for curved microcracking agrees well with experimental observations.
Parameter Estimation for a Pulsating Turbulent Buoyant Jet Using Approximate Bayesian Computation

NASA Astrophysics Data System (ADS)

Christopher, Jason; Wimer, Nicholas; Lapointe, Caelan; Hayden, Torrey; Grooms, Ian; Rieker, Greg; Hamlington, Peter

2017-11-01

Approximate Bayesian Computation (ABC) is a powerful tool that allows sparse experimental or other ``truth'' data to be used for the prediction of unknown parameters, such as flow properties and boundary conditions, in numerical simulations of real-world engineering systems. Here we introduce the ABC approach and then use ABC to predict unknown inflow conditions in simulations of a two-dimensional (2D) turbulent, high-temperature buoyant jet. For this test case, truth data are obtained from a direct numerical simulation (DNS) with known boundary conditions and problem parameters, while the ABC procedure utilizes lower fidelity large eddy simulations. Using spatially-sparse statistics from the 2D buoyant jet DNS, we show that the ABC method provides accurate predictions of true jet inflow parameters. The success of the ABC approach in the present test suggests that ABC is a useful and versatile tool for predicting flow information, such as boundary conditions, that can be difficult to determine experimentally.
Modeling and prediction of extraction profile for microwave-assisted extraction based on absorbed microwave energy.

PubMed

Chan, Chung-Hung; Yusoff, Rozita; Ngoh, Gek-Cheng

2013-09-01

A modeling technique based on absorbed microwave energy was proposed to model microwave-assisted extraction (MAE) of antioxidant compounds from cocoa (Theobroma cacao L.) leaves. By adapting suitable extraction model at the basis of microwave energy absorbed during extraction, the model can be developed to predict extraction profile of MAE at various microwave irradiation power (100-600 W) and solvent loading (100-300 ml). Verification with experimental data confirmed that the prediction was accurate in capturing the extraction profile of MAE (R-square value greater than 0.87). Besides, the predicted yields from the model showed good agreement with the experimental results with less than 10% deviation observed. Furthermore, suitable extraction times to ensure high extraction yield at various MAE conditions can be estimated based on absorbed microwave energy. The estimation is feasible as more than 85% of active compounds can be extracted when compared with the conventional extraction technique. Copyright © 2013 Elsevier Ltd. All rights reserved.
Theory versus experiment for the rotordynamic coefficients of labyrinth gas seals. II - A comparison to experiment

NASA Technical Reports Server (NTRS)

Childs, D. W.; Scharrer, J. K.

1987-01-01

An experimental test facility is used to measure the leakage and rotordynamic coefficients of teeth-on-rotor and teeth-on-stator labyrinth gas seals. The test results are presented along with the theoretically predicted values for the two seal configurations at three different radial clearances and shaft speeds to 16,000 cpm. The test results show that the theory accurately predicts the cross-coupled stiffness for both seal configurations and shows improvement in the prediction of the direct damping for the teeth-on-rotor seal. The theory fails to predict a decrease in the direct damping coefficient for an increase in the radial clearance for the teeth-on-stator seal.
Expanding a dynamic flux balance model of yeast fermentation to genome-scale

PubMed Central

2011-01-01

Background Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints. Results Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol. Conclusion A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations. PMID:21595919
The study of heat penetration of kimchi soup on stationary and rotary retorts.

PubMed

Cho, Won-Il; Park, Eun-Ji; Cheon, Hee Soon; Chung, Myong-Soo

2015-03-01

The aim of this study was to determine the heat-penetration characteristics using stationary and rotary retorts to manufacture Kimchi soup. Both heat-penetration tests and computer simulation based on mathematical modeling were performed. The sterility was measured at five different positions in the pouch. The results revealed only a small deviation of F 0 among the different positions, and the rate of heat transfer was increased by rotation of the retort. The thermal processing of retort-pouched Kimchi soup was analyzed mathematically using a finite-element model, and optimum models for predicting the time course of the temperature and F 0 were developed. The mathematical models could accurately predict the actual heat penetration of retort-pouched Kimchi soup. The average deviation of the temperature between the experimental and mathematical predicted model was 2.46% (R(2)=0.975). The changes in nodal temperature and F 0 caused by microbial inactivation in the finite-element model predicted using the NISA program were very similar to that of the experimental data of for the retorted Kimchi soup during sterilization with rotary retorts. The correlation coefficient between the simulation using the NISA program and the experimental data was very high, at 99%.

The Study of Heat Penetration of Kimchi Soup on Stationary and Rotary Retorts

PubMed Central

Cho, Won-Il; Park, Eun-Ji; Cheon, Hee Soon; Chung, Myong-Soo

2015-01-01

The aim of this study was to determine the heat-penetration characteristics using stationary and rotary retorts to manufacture Kimchi soup. Both heat-penetration tests and computer simulation based on mathematical modeling were performed. The sterility was measured at five different positions in the pouch. The results revealed only a small deviation of F0 among the different positions, and the rate of heat transfer was increased by rotation of the retort. The thermal processing of retort-pouched Kimchi soup was analyzed mathematically using a finite-element model, and optimum models for predicting the time course of the temperature and F0 were developed. The mathematical models could accurately predict the actual heat penetration of retort-pouched Kimchi soup. The average deviation of the temperature between the experimental and mathematical predicted model was 2.46% (R2=0.975). The changes in nodal temperature and F0 caused by microbial inactivation in the finite-element model predicted using the NISA program were very similar to that of the experimental data of for the retorted Kimchi soup during sterilization with rotary retorts. The correlation coefficient between the simulation using the NISA program and the experimental data was very high, at 99%. PMID:25866751
Capturing anharmonicity in a lattice thermal conductivity model for high-throughput predictions

DOE PAGES

Miller, Samuel A.; Gorai, Prashun; Ortiz, Brenden R.; ...

2017-01-06

High-throughput, low-cost, and accurate predictions of thermal properties of new materials would be beneficial in fields ranging from thermal barrier coatings and thermoelectrics to integrated circuits. To date, computational efforts for predicting lattice thermal conductivity (κ L) have been hampered by the complexity associated with computing multiple phonon interactions. In this work, we develop and validate a semiempirical model for κ L by fitting density functional theory calculations to experimental data. Experimental values for κ L come from new measurements on SrIn 2O 4, Ba 2SnO 4, Cu 2ZnSiTe 4, MoTe 2, Ba 3In 2O 6, Cu 3TaTe 4, SnO,more » and InI as well as 55 compounds from across the published literature. Here, to capture the anharmonicity in phonon interactions, we incorporate a structural parameter that allows the model to predict κ L within a factor of 1.5 of the experimental value across 4 orders of magnitude in κ L values and over a diverse chemical and structural phase space, with accuracy similar to or better than that of computationally more expensive models.« less
The prediction of pressure distributions on an arrow-wing configuration including the effect of camber, twist, and a wing fin

NASA Technical Reports Server (NTRS)

Bobbitt, P. J.; Manro, M. E.; Kulfan, R. M.

1980-01-01

Wind tunnel tests of an arrow wing body configuration consisting of flat, twisted, and cambered twisted wings were conducted at Mach numbers from 0.40 to 2.50 to provide an experimental data base for comparison with theoretical methods. A variety of leading and trailing edge control surface deflections were included in these tests, and in addition, the cambered twisted wing was tested with an outboard vertical fin to determine its effect on wing and control surface loads. Theory experiment comparisons show that current state of the art linear and nonlinear attached flow methods were adequate at small angles of attack typical of cruise conditions. The incremental effects of outboard fin, wing twist, and wing camber are most accurately predicted by the advanced panel method PANAIR. Results of the advanced panel separated flow method, obtained with an early version of the program, show promise that accurate detailed pressure predictions may soon be possible for an aeroelasticity deformed wing at high angles of attack.
A unified internal model theory to resolve the paradox of active versus passive self-motion sensation

PubMed Central

Angelaki, Dora E

2017-01-01

Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated (‘passive’) movements. However, these neurons show reduced responses during self-generated (‘active’) movements, indicating that predicted sensory consequences of motor commands cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations during passive movements remain unknown. We construct a Kalman filter that incorporates motor commands into a previously established model of optimal passive self-motion estimation. The simulated sensory error and feedback signals match experimentally measured neuronal responses during active and passive head and trunk rotations and translations. We conclude that a single sensory internal model can combine motor commands with vestibular and proprioceptive signals optimally. Thus, although neurons carrying sensory prediction error or feedback signals show attenuated modulation, the sensory cues and internal model are both engaged and critically important for accurate self-motion estimation during active head movements. PMID:29043978
A fast and accurate method to predict 2D and 3D aerodynamic boundary layer flows

NASA Astrophysics Data System (ADS)

Bijleveld, H. A.; Veldman, A. E. P.

2014-12-01

A quasi-simultaneous interaction method is applied to predict 2D and 3D aerodynamic flows. This method is suitable for offshore wind turbine design software as it is a very accurate and computationally reasonably cheap method. This study shows the results for a NACA 0012 airfoil. The two applied solvers converge to the experimental values when the grid is refined. We also show that in separation the eigenvalues remain positive thus avoiding the Goldstein singularity at separation. In 3D we show a flow over a dent in which separation occurs. A rotating flat plat is used to show the applicability of the method for rotating flows. The shown capabilities of the method indicate that the quasi-simultaneous interaction method is suitable for design methods for offshore wind turbine blades.
Detecting circular RNAs: bioinformatic and experimental challenges

PubMed Central

Szabo, Linda; Salzman, Julia

2017-01-01

The pervasive expression of circular RNAs (circRNAs) is a recently discovered feature of gene expression in highly diverged eukaryotes. Numerous algorithms that are used to detect genome-wide circRNA expression from RNA sequencing (RNA-seq) data have been developed in the past few years, but there is little overlap in their predictions and no clear gold-standard method to assess the accuracy of these algorithms. We review sources of experimental and bioinformatic biases that complicate the accurate discovery of circRNAs and discuss statistical approaches to address these biases. We conclude with a discussion of the current experimental progress on the topic. PMID:27739534
Predicting perturbation patterns from the topology of biological networks.

PubMed

Santolini, Marc; Barabási, Albert-László

2018-06-20

High-throughput technologies, offering an unprecedented wealth of quantitative data underlying the makeup of living systems, are changing biology. Notably, the systematic mapping of the relationships between biochemical entities has fueled the rapid development of network biology, offering a suitable framework to describe disease phenotypes and predict potential drug targets. However, our ability to develop accurate dynamical models remains limited, due in part to the limited knowledge of the kinetic parameters underlying these interactions. Here, we explore the degree to which we can make reasonably accurate predictions in the absence of the kinetic parameters. We find that simple dynamically agnostic models are sufficient to recover the strength and sign of the biochemical perturbation patterns observed in 87 biological models for which the underlying kinetics are known. Surprisingly, a simple distance-based model achieves 65% accuracy. We show that this predictive power is robust to topological and kinetic parameter perturbations, and we identify key network properties that can increase up to 80% the recovery rate of the true perturbation patterns. We validate our approach using experimental data on the chemotactic pathway in bacteria, finding that a network model of perturbation spreading predicts with ∼80% accuracy the directionality of gene expression and phenotype changes in knock-out and overproduction experiments. These findings show that the steady advances in mapping out the topology of biochemical interaction networks opens avenues for accurate perturbation spread modeling, with direct implications for medicine and drug development.
Summary of Data from the First AIAA CFD Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Levy, David W.; Zickuhr, Tom; Vassberg, John; Agrawal, Shreekant; Wahls, Richard A.; Pirzadeh, Shahyar; Hemsch, Michael J.

2002-01-01

The results from the first AIAA CFD Drag Prediction Workshop are summarized. The workshop was designed specifically to assess the state-of-the-art of computational fluid dynamics methods for force and moment prediction. An impartial forum was provided to evaluate the effectiveness of existing computer codes and modeling techniques, and to identify areas needing additional research and development. The subject of the study was the DLR-F4 wing-body configuration, which is representative of transport aircraft designed for transonic flight. Specific test cases were required so that valid comparisons could be made. Optional test cases included constant-C(sub L) drag-rise predictions typically used in airplane design by industry. Results are compared to experimental data from three wind tunnel tests. A total of 18 international participants using 14 different codes submitted data to the workshop. No particular grid type or turbulence model was more accurate, when compared to each other, or to wind tunnel data. Most of the results overpredicted C(sub Lo) and C(sub Do), but induced drag (dC(sub D)/dC(sub L)(exp 2)) agreed fairly well. Drag rise at high Mach number was underpredicted, however, especially at high C(sub L). On average, the drag data were fairly accurate, but the scatter was greater than desired. The results show that well-validated Reynolds-Averaged Navier-Stokes CFD methods are sufficiently accurate to make design decisions based on predicted drag.
Tile prediction schemes for wide area motion imagery maps in GIS

NASA Astrophysics Data System (ADS)

Michael, Chris J.; Lin, Bruce Y.

2017-11-01

Wide-area surveillance, traffic monitoring, and emergency management are just several of many applications benefiting from the incorporation of Wide-Area Motion Imagery (WAMI) maps into geographic information systems. Though the use of motion imagery as a GIS base map via the Web Map Service (WMS) standard is not a new concept, effectively streaming imagery is particularly challenging due to its large scale and the multidimensionally interactive nature of clients that use WMS. Ineffective streaming from a server to one or more clients can unnecessarily overwhelm network bandwidth and cause frustratingly large amounts of latency in visualization to the user. Seamlessly streaming WAMI through GIS requires good prediction to accurately guess the tiles of the video that will be traversed in the near future. In this study, we present an experimental framework for such prediction schemes by presenting a stochastic interaction model that represents a human user's interaction with a GIS video map. We then propose several algorithms by which the tiles of the stream may be predicted. Results collected both within the experimental framework and using human analyst trajectories show that, though each algorithm thrives under certain constraints, the novel Markovian algorithm yields the best results overall. Furthermore, we make the argument that the proposed experimental framework is sufficient for the study of these prediction schemes.
Electronic stopping powers for heavy ions in SiC and SiO{sub 2}

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

Jin, K.; Xue, H.; Zhang, Y., E-mail: Zhangy1@ornl.gov

2014-01-28

Accurate information on electronic stopping power is fundamental for broad advances in materials science, electronic industry, space exploration, and sustainable energy technologies. In the case of slow heavy ions in light targets, current codes and models provide significantly inconsistent predictions, among which the Stopping and Range of Ions in Matter (SRIM) code is the most commonly used one. Experimental evidence, however, has demonstrated considerable errors in the predicted ion and damage profiles based on SRIM stopping powers. In this work, electronic stopping powers for Cl, Br, I, and Au ions are experimentally determined in two important functional materials, SiC andmore » SiO{sub 2}, based on a single ion technique, and new electronic stopping power values are derived over the energy regime from 0 to 15 MeV, where large deviations from the SRIM predictions are observed. As an experimental validation, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC for energies from 700 keV to 15 MeV. The measured ion distributions by both RBS and SIMS are considerably deeper than the SRIM predictions, but agree well with predictions based on our derived stopping powers.« less
Electronic Stopping Powers For Heavy Ions In SiC And SiO2

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

Jin, Ke; Zhang, Y.; Zhu, Zihua

2014-01-24

Accurate information on electronic stopping power is fundamental for broad advances in materials science, electronic industry, space exploration, and sustainable energy technologies. In the case of slow heavy ions in light targets, current codes and models provide significantly inconsistent predictions, among which the Stopping and Range of Ions in Matter (SRIM) code is the most commonly used one. Experimental evidence, however, has demonstrated considerable errors in the predicted ion and damage profiles based on SRIM stopping powers. In this work, electronic stopping powers for Cl, Br, I, and Au ions are experimentally determined in two important functional materials, SiC andmore » SiO2, based on a single ion technique, and new electronic stopping power values are derived over the energy regime from 0 to 15 MeV, where large deviations from the SRIM predictions are observed. As an experimental validation, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC for energies from 700 keV to 15MeV. The measured ion distributions by both RBS and SIMS are considerably deeper than the SRIM predictions, but agree well with predictions based on our derived stopping powers.« less
A Research Program for Improving Heat Transfer Prediction Capability for the Laminar to Turbulent Transition Region of Turbine Vanes/Blades

NASA Technical Reports Server (NTRS)

Simon, Frederick F.

2007-01-01

A program sponsored by the National Aeronautics and Space Administration (NASA) for the investigation of the heat transfer in the transition region of turbine vanes and blades with the object of improving the capability for predicting heat transfer is described,. The accurate prediction of gas-side heat transfer is important to the determination of turbine longevity, engine performance and developmental costs. The need for accurate predictions will become greater as the operating temperatures and stage loading levels of advanced turbine engines increase. The present methods for predicting transition shear stress and heat transfer on turbine blades are based on incomplete knowledge and are largely empirical. To meet the objectives of the NASA program, a team approach consisting of researchers from government, universities, a research institute, and a small business is presented. The research is divided into areas of experimentation, direct numerical simulation (DNS) and turbulence modeling. A summary of the results to date is given for the above research areas in a high-disturbance environment (bypass transition) with a discussion of the model development necessary for use in numerical codes.
Numerical simulation of turbulent gas flames in tubes.

PubMed

Salzano, E; Marra, F S; Russo, G; Lee, J H S

2002-12-02

Computational fluid dynamics (CFD) is an emerging technique to predict possible consequences of gas explosion and it is often considered a powerful and accurate tool to obtain detailed results. However, systematic analyses of the reliability of this approach to real-scale industrial configurations are still needed. Furthermore, few experimental data are available for comparison and validation. In this work, a set of well documented experimental data related to the flame acceleration obtained within obstacle-filled tubes filled with flammable gas-air mixtures, has been simulated. In these experiments, terminal steady flame speeds corresponding to different propagation regimes were observed, thus, allowing a clear and prompt characterisation of the numerical results with respect to numerical parameters, as grid definition, geometrical parameters, as blockage ratio and to mixture parameters, as mixture reactivity. The CFD code AutoReagas was used for the simulations. Numerical predictions were compared with available experimental data and some insights into the code accuracy were determined. Computational results are satisfactory for the relatively slower turbulent deflagration regimes and became fair when choking regime is observed, whereas transition to quasi-detonation or Chapman-Jogouet (CJ) were never predicted.
Comparison of Experimental Surface and Flow Field Measurements to Computational Results of the Juncture Flow Model

NASA Technical Reports Server (NTRS)

Roozeboom, Nettie H.; Lee, Henry C.; Simurda, Laura J.; Zilliac, Gregory G.; Pulliam, Thomas H.

2016-01-01

Wing-body juncture flow fields on commercial aircraft configurations are challenging to compute accurately. The NASA Advanced Air Vehicle Program's juncture flow committee is designing an experiment to provide data to improve Computational Fluid Dynamics (CFD) modeling in the juncture flow region. Preliminary design of the model was done using CFD, yet CFD tends to over-predict the separation in the juncture flow region. Risk reduction wind tunnel tests were requisitioned by the committee to obtain a better understanding of the flow characteristics of the designed models. NASA Ames Research Center's Fluid Mechanics Lab performed one of the risk reduction tests. The results of one case, accompanied by CFD simulations, are presented in this paper. Experimental results suggest the wall mounted wind tunnel model produces a thicker boundary layer on the fuselage than the CFD predictions, resulting in a larger wing horseshoe vortex suppressing the side of body separation in the juncture flow region. Compared to experimental results, CFD predicts a thinner boundary layer on the fuselage generates a weaker wing horseshoe vortex resulting in a larger side of body separation.
High Temperature, high pressure equation of state density correlations and viscosity correlations

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

Tapriyal, D.; Enick, R.; McHugh, M.

2012-07-31

Global increase in oil demand and depleting reserves has derived a need to find new oil resources. To find these untapped reservoirs, oil companies are exploring various remote and harsh locations such as deep waters in Gulf of Mexico, remote arctic regions, unexplored deep deserts, etc. Further, the depth of new oil/gas wells being drilled has increased considerably to tap these new resources. With the increase in the well depth, the bottomhole temperature and pressure are also increasing to extreme values (i.e. up to 500 F and 35,000 psi). The density and viscosity of natural gas and crude oil atmore » reservoir conditions are critical fundamental properties required for accurate assessment of the amount of recoverable petroleum within a reservoir and the modeling of the flow of these fluids within the porous media. These properties are also used to design appropriate drilling and production equipment such as blow out preventers, risers, etc. With the present state of art, there is no accurate database for these fluid properties at extreme conditions. As we have begun to expand this experimental database it has become apparent that there are neither equations of state for density or transport models for viscosity that can be used to predict these fundamental properties of multi-component hydrocarbon mixtures over a wide range of temperature and pressure. Presently, oil companies are using correlations based on lower temperature and pressure databases that exhibit an unsatisfactory predictive capability at extreme conditions (e.g. as great as {+-} 50%). From the perspective of these oil companies that are committed to safely producing these resources, accurately predicting flow rates, and assuring the integrity of the flow, the absence of an extensive experimental database at extreme conditions and models capable of predicting these properties over an extremely wide range of temperature and pressure (including extreme conditions) makes their task even more daunting.« less
A Dynamic Calibration Method for Experimental and Analytical Hub Load Comparison

NASA Technical Reports Server (NTRS)

Kreshock, Andrew R.; Thornburgh, Robert P.; Wilbur, Matthew L.

2017-01-01

This paper presents the results from an ongoing effort to produce improved correlation between analytical hub force and moment prediction and those measured during wind-tunnel testing on the Aeroelastic Rotor Experimental System (ARES), a conventional rotor testbed commonly used at the Langley Transonic Dynamics Tunnel (TDT). A frequency-dependent transformation between loads at the rotor hub and outputs of the testbed balance is produced from frequency response functions measured during vibration testing of the system. The resulting transformation is used as a dynamic calibration of the balance to transform hub loads predicted by comprehensive analysis into predicted balance outputs. In addition to detailing the transformation process, this paper also presents a set of wind-tunnel test cases, with comparisons between the measured balance outputs and transformed predictions from the comprehensive analysis code CAMRAD II. The modal response of the testbed is discussed and compared to a detailed finite-element model. Results reveal that the modal response of the testbed exhibits a number of characteristics that make accurate dynamic balance predictions challenging, even with the use of the balance transformation.
Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms

PubMed Central

Ding, Feng; Sharma, Shantanu; Chalasani, Poornima; Demidov, Vadim V.; Broude, Natalia E.; Dokholyan, Nikolay V.

2008-01-01

RNA molecules with novel functions have revived interest in the accurate prediction of RNA three-dimensional (3D) structure and folding dynamics. However, existing methods are inefficient in automated 3D structure prediction. Here, we report a robust computational approach for rapid folding of RNA molecules. We develop a simplified RNA model for discrete molecular dynamics (DMD) simulations, incorporating base-pairing and base-stacking interactions. We demonstrate correct folding of 150 structurally diverse RNA sequences. The majority of DMD-predicted 3D structures have <4 Å deviations from experimental structures. The secondary structures corresponding to the predicted 3D structures consist of 94% native base-pair interactions. Folding thermodynamics and kinetics of tRNAPhe, pseudoknots, and mRNA fragments in DMD simulations are in agreement with previous experimental findings. Folding of RNA molecules features transient, non-native conformations, suggesting non-hierarchical RNA folding. Our method allows rapid conformational sampling of RNA folding, with computational time increasing linearly with RNA length. We envision this approach as a promising tool for RNA structural and functional analyses. PMID:18456842
Predicting overload-affected fatigue crack growth in steels

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

Skorupa, M.; Skorupa, A.; Ladecki, B.

1996-12-01

The ability of semi-empirical crack closure models to predict the effect of overloads on fatigue crack growth in low-alloy steels has been investigated. With this purpose, the CORPUS model developed for aircraft metals and spectra has been checked first through comparisons between the simulated and observed results for a low-alloy steel. The CORPUS predictions of crack growth under several types of simple load histories containing overloads appeared generally unconservative which prompted the authors to formulate a new model, more suitable for steels. With the latter approach, the assumed evolution of the crack opening stress during the delayed retardation stage hasmore » been based on experimental results reported for various steels. For all the load sequences considered, the predictions from the proposed model appeared to be by far more accurate than those from CORPUS. Based on the analysis results, the capability of semi-empirical prediction concepts to cover experimentally observed trends that have been reported for sequences with overloads is discussed. Finally, possibilities of improving the model performance are considered.« less
Adaptive vehicle motion estimation and prediction

NASA Astrophysics Data System (ADS)

Zhao, Liang; Thorpe, Chuck E.

1999-01-01

Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.
Computational optimization and biological evolution.

PubMed

Goryanin, Igor

2010-10-01

Modelling and optimization principles become a key concept in many biological areas, especially in biochemistry. Definitions of objective function, fitness and co-evolution, although they differ between biology and mathematics, are similar in a general sense. Although successful in fitting models to experimental data, and some biochemical predictions, optimization and evolutionary computations should be developed further to make more accurate real-life predictions, and deal not only with one organism in isolation, but also with communities of symbiotic and competing organisms. One of the future goals will be to explain and predict evolution not only for organisms in shake flasks or fermenters, but for real competitive multispecies environments.

Predicting elastic properties of β-HMX from first-principles calculations.

PubMed

Peng, Qing; Rahul; Wang, Guangyu; Liu, Gui-Rong; Grimme, Stefan; De, Suvranu

2015-05-07

We investigate the performance of van der Waals (vdW) functions in predicting the elastic constants of β cyclotetramethylene tetranitramine (HMX) energetic molecular crystals using density functional theory (DFT) calculations. We confirm that the accuracy of the elastic constants is significantly improved using the vdW corrections with environment-dependent C6 together with PBE and revised PBE exchange-correlation functionals. The elastic constants obtained using PBE-D3(0) calculations yield the most accurate mechanical response of β-HMX when compared with experimental stress-strain data. Our results suggest that PBE-D3 calculations are reliable in predicting the elastic constants of this material.
Improved Formula for the Stress Intensity Factor of Semi-Elliptical Surface Cracks in Welded Joints under Bending Stress

PubMed Central

Peng, Yang; Wu, Chao; Zheng, Yifu; Dong, Jun

2017-01-01

Welded joints are prone to fatigue cracking with the existence of welding defects and bending stress. Fracture mechanics is a useful approach in which the fatigue life of the welded joint can be predicted. The key challenge of such predictions using fracture mechanics is how to accurately calculate the stress intensity factor (SIF). An empirical formula for calculating the SIF of welded joints under bending stress was developed by Baik, Yamada and Ishikawa based on the hybrid method. However, when calculating the SIF of a semi-elliptical crack, this study found that the accuracy of the Baik-Yamada formula was poor when comparing the benchmark results, experimental data and numerical results. The reasons for the reduced accuracy of the Baik-Yamada formula were identified and discussed in this paper. Furthermore, a new correction factor was developed and added to the Baik-Yamada formula by using theoretical analysis and numerical regression. Finally, the predictions using the modified Baik-Yamada formula were compared with the benchmark results, experimental data and numerical results. It was found that the accuracy of the modified Baik-Yamada formula was greatly improved. Therefore, it is proposed that this modified formula is used to conveniently and accurately calculate the SIF of semi-elliptical cracks in welded joints under bending stress. PMID:28772527
Radio Frequency Mass Gauging of Propellants

NASA Technical Reports Server (NTRS)

Zimmerli, Gregory A.; Vaden, Karl R.; Herlacher, Michael D.; Buchanan, David A.; VanDresar, Neil T.

2007-01-01

A combined experimental and computer simulation effort was conducted to measure radio frequency (RF) tank resonance modes in a dewar partially filled with liquid oxygen, and compare the measurements with numerical simulations. The goal of the effort was to demonstrate that computer simulations of a tank's electromagnetic eigenmodes can be used to accurately predict ground-based measurements, thereby providing a computational tool for predicting tank modes in a low-gravity environment. Matching the measured resonant frequencies of several tank modes with computer simulations can be used to gauge the amount of liquid in a tank, thus providing a possible method to gauge cryogenic propellant tanks in low-gravity. Using a handheld RF spectrum analyzer and a small antenna in a 46 liter capacity dewar for experimental measurements, we have verified that the four lowest transverse magnetic eigenmodes can be accurately predicted as a function of liquid oxygen fill level using computer simulations. The input to the computer simulations consisted of tank dimensions, and the dielectric constant of the fluid. Without using any adjustable parameters, the calculated and measured frequencies agree such that the liquid oxygen fill level was gauged to within 2 percent full scale uncertainty. These results demonstrate the utility of using electromagnetic simulations to form the basis of an RF mass gauging technology with the power to simulate tank resonance frequencies from arbitrary fluid configurations.
Modeling and validation of autoinducer-mediated bacterial gene expression in microfluidic environments

PubMed Central

Austin, Caitlin M.; Stoy, William; Su, Peter; Harber, Marie C.; Bardill, J. Patrick; Hammer, Brian K.; Forest, Craig R.

2014-01-01

Biosensors exploiting communication within genetically engineered bacteria are becoming increasingly important for monitoring environmental changes. Currently, there are a variety of mathematical models for understanding and predicting how genetically engineered bacteria respond to molecular stimuli in these environments, but as sensors have miniaturized towards microfluidics and are subjected to complex time-varying inputs, the shortcomings of these models have become apparent. The effects of microfluidic environments such as low oxygen concentration, increased biofilm encapsulation, diffusion limited molecular distribution, and higher population densities strongly affect rate constants for gene expression not accounted for in previous models. We report a mathematical model that accurately predicts the biological response of the autoinducer N-acyl homoserine lactone-mediated green fluorescent protein expression in reporter bacteria in microfluidic environments by accommodating these rate constants. This generalized mass action model considers a chain of biomolecular events from input autoinducer chemical to fluorescent protein expression through a series of six chemical species. We have validated this model against experimental data from our own apparatus as well as prior published experimental results. Results indicate accurate prediction of dynamics (e.g., 14% peak time error from a pulse input) and with reduced mean-squared error with pulse or step inputs for a range of concentrations (10 μM–30 μM). This model can help advance the design of genetically engineered bacteria sensors and molecular communication devices. PMID:25379076
Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions

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

Zuniga, Cristal; Li, Chien -Ting; Huelsman, Tyler

The green microalgae Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organismmore » to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Moreover, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine.« less
IPMP Global Fit - A one-step direct data analysis tool for predictive microbiology.

PubMed

Huang, Lihan

2017-12-04

The objective of this work is to develop and validate a unified optimization algorithm for performing one-step global regression analysis of isothermal growth and survival curves for determination of kinetic parameters in predictive microbiology. The algorithm is incorporated with user-friendly graphical interfaces (GUIs) to develop a data analysis tool, the USDA IPMP-Global Fit. The GUIs are designed to guide the users to easily navigate through the data analysis process and properly select the initial parameters for different combinations of mathematical models. The software is developed for one-step kinetic analysis to directly construct tertiary models by minimizing the global error between the experimental observations and mathematical models. The current version of the software is specifically designed for constructing tertiary models with time and temperature as the independent model parameters in the package. The software is tested with a total of 9 different combinations of primary and secondary models for growth and survival of various microorganisms. The results of data analysis show that this software provides accurate estimates of kinetic parameters. In addition, it can be used to improve the experimental design and data collection for more accurate estimation of kinetic parameters. IPMP-Global Fit can be used in combination with the regular USDA-IPMP for solving the inverse problems and developing tertiary models in predictive microbiology. Published by Elsevier B.V.
Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions

DOE PAGES

Zuniga, Cristal; Li, Chien -Ting; Huelsman, Tyler; ...

2016-07-02

The green microalgae Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organismmore » to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Moreover, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine.« less
Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

PubMed

Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

2016-09-01

The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. © 2016 American Society of Plant Biologists. All rights reserved.
Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions1

PubMed Central

Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten

2016-01-01

The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244
Metabolic and physiochemical responses to a whole-lake experimental increase in dissolved organic carbon in a north-temperate lake

Treesearch

Jacob A. Zwart; Nicola Craig; Patrick T. Kelly; Stephen D. Sebestyen; Christopher T. Solomon; Brian C. Weidel; Stuart E. Jones

2016-01-01

Over the last several decades, many lakes globally have increased in dissolved organic carbon (DOC), calling into question how lake functions may respond to increasing DOC. Unfortunately, our basis for making predictions is limited to spatial surveys, modeling, and laboratory experiments, which may not accurately capture important whole-ecosystem processes. In this...
Carbon pools and productivity in a 1-km2 heterogeneous forest and peatland mosaic in Minnesota, USA

Treesearch

Peter Weishampel; Randall Kolka; Jennifer Y. King

2009-01-01

Determining the magnitude of carbon (C) storage in forests and peatlands is an important step towards predicting how regional carbon balance will respond to climate change. However, spatial heterogeneity of dominant forest and peatland cover types can inhibit accurate C storage estimates. We evaluated ecosystem C pools and productivity in the Marcell Experimental...
Electrochemical carbon dioxide concentrator subsystem math model. [for manned space station

NASA Technical Reports Server (NTRS)

Marshall, R. D.; Carlson, J. N.; Schubert, F. H.

1974-01-01

A steady state computer simulation model has been developed to describe the performance of a total six man, self-contained electrochemical carbon dioxide concentrator subsystem built for the space station prototype. The math model combines expressions describing the performance of the electrochemical depolarized carbon dioxide concentrator cells and modules previously developed with expressions describing the performance of the other major CS-6 components. The model is capable of accurately predicting CS-6 performance over EDC operating ranges and the computer simulation results agree with experimental data obtained over the prediction range.
Assessment of CFD capability for prediction of hypersonic shock interactions

NASA Astrophysics Data System (ADS)

Knight, Doyle; Longo, José; Drikakis, Dimitris; Gaitonde, Datta; Lani, Andrea; Nompelis, Ioannis; Reimann, Bodo; Walpot, Louis

2012-01-01

The aerothermodynamic loadings associated with shock wave boundary layer interactions (shock interactions) must be carefully considered in the design of hypersonic air vehicles. The capability of Computational Fluid Dynamics (CFD) software to accurately predict hypersonic shock wave laminar boundary layer interactions is examined. A series of independent computations performed by researchers in the US and Europe are presented for two generic configurations (double cone and cylinder) and compared with experimental data. The results illustrate the current capabilities and limitations of modern CFD methods for these flows.
Modeling Dynamic Regulatory Processes in Stroke.

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

McDermott, Jason E.; Jarman, Kenneth D.; Taylor, Ronald C.

2012-10-11

The ability to examine in silico the behavior of biological systems can greatly accelerate the pace of discovery in disease pathologies, such as stroke, where in vivo experimentation is lengthy and costly. In this paper we describe an approach to in silico examination of blood genomic responses to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) relating regulators and functional clusters from the data. These ODEs were used to developmore » dynamic models that simulate the expression of regulated functional clusters using system dynamics as the modeling paradigm. The dynamic model has the considerable advantage of only requiring an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. The manipulation of input model parameters, such as changing the magnitude of gene expression, made it possible to assess the behavior of the networks through time under varying conditions. We report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different preconditioning paradigms.« less
Effect of Counterflow Jet on a Supersonic Reentry Capsule

NASA Technical Reports Server (NTRS)

Chang, Chau-Lyan; Venkatachari, Balaji Shankar; Cheng, Gary C.

2006-01-01

Recent NASA initiatives for space exploration have reinvigorated research on Apollo-like capsule vehicles. Aerothermodynamic characteristics of these capsule configurations during reentry play a crucial role in the performance and safety of the planetary entry probes and the crew exploration vehicles. At issue are the forebody thermal shield protection and afterbody aeroheating predictions. Due to the lack of flight or wind tunnel measurements at hypersonic speed, design decisions on such vehicles would rely heavily on computational results. Validation of current computational tools against experimental measurement thus becomes one of the most important tasks for general hypersonic research. This paper is focused on time-accurate numerical computations of hypersonic flows over a set of capsule configurations, which employ a counterflow jet to offset the detached bow shock. The accompanying increased shock stand-off distance and modified heat transfer characteristics associated with the counterflow jet may provide guidance for future design of hypersonic reentry capsules. The newly emerged space-time conservation element solution element (CESE) method is used to perform time-accurate, unstructured mesh Navier-Stokes computations for all cases investigated. The results show good agreement between experimental and numerical Schlieren pictures. Surface heat flux and aerodynamic force predictions of the capsule configurations are discussed in detail.
Calibration of a γ- Re θ transition model and its application in low-speed flows

NASA Astrophysics Data System (ADS)

Wang, YunTao; Zhang, YuLun; Meng, DeHong; Wang, GunXue; Li, Song

2014-12-01

The prediction of laminar-turbulent transition in boundary layer is very important for obtaining accurate aerodynamic characteristics with computational fluid dynamic (CFD) tools, because laminar-turbulent transition is directly related to complex flow phenomena in boundary layer and separated flow in space. Unfortunately, the transition effect isn't included in today's major CFD tools because of non-local calculations in transition modeling. In this paper, Menter's γ- Re θ transition model is calibrated and incorporated into a Reynolds-Averaged Navier-Stokes (RANS) code — Trisonic Platform (TRIP) developed in China Aerodynamic Research and Development Center (CARDC). Based on the experimental data of flat plate from the literature, the empirical correlations involved in the transition model are modified and calibrated numerically. Numerical simulation for low-speed flow of Trapezoidal Wing (Trap Wing) is performed and compared with the corresponding experimental data. It is indicated that the γ- Re θ transition model can accurately predict the location of separation-induced transition and natural transition in the flow region with moderate pressure gradient. The transition model effectively imporves the simulation accuracy of the boundary layer and aerodynamic characteristics.
Measurement of Trailing Edge Noise Using Directional Array and Coherent Output Power Methods

NASA Technical Reports Server (NTRS)

Hutcheson, Florence V.; Brooks, Thomas F.

2002-01-01

The use of a directional (or phased) array of microphones for the measurement of trailing edge (TE) noise is described and tested. The capabilities of this method arc evaluated via measurements of TE noise from a NACA 63-215 airfoil model and from a cylindrical rod. This TE noise measurement approach is compared to one that is based on thc cross spectral analysis of output signals from a pair of microphones placed on opposite sides of an airframe model (COP method). Advantages and limitations of both methods arc examined. It is shown that the microphone array can accurately measures TE noise and captures its two-dimensional characteristic over a large frequency range for any TE configuration as long as noise contamination from extraneous sources is within bounds. The COP method is shown to also accurately measure TE noise but over a more limited frequency range that narrows for increased TE thickness. Finally, the applicability and generality of an airfoil self-noise prediction method was evaluated via comparison to the experimental data obtained using the COP and array measurement methods. The predicted and experimental results are shown to agree over large frequency ranges.
Effects of environmental change on plant species density: Comparing predictions with experiments

USGS Publications Warehouse

Gough, L.; Grace, J.B.

1999-01-01

Ideally, general ecological relationships may be used to predict responses of natural communities to environmental change, but few attempts have been made to determine the reliability of predictions based on descriptive data. Using a previously published structural equation model (SEM) of descriptive data from a coastal marsh landscape, we compared these predictions against observed changes in plant species density resulting from field experiments (manipulations of soil fertility, flooding, salinity, and mammalian herbivory) in two areas within the same marsh. In general, observed experimental responses were fairly consistent with predictions. The largest discrepancy occurred when sods were transplanted from high- to low-salinity sites and herbivores selectively consumed a particularly palatable plant species in the transplanted sods. Individual plot responses to some treatments were predicted more accurately than others. Individual fertilized plot responses were not consistent with predictions (P > 0.05), nor were fenced plots (herbivore exclosures; R2 = 0.15) compared to unfenced plots (R2 = 0.53). For the remaining treatments, predictions reasonably matched responses (R2 = 0.63). We constructed an SEM for the experimental data; it explained 60% of the variance in species density and showed that fencing and fertilization led to decreases in species density that were not predicted from treatment effects on community biomass or observed disturbance levels. These treatments may have affected the ratio of live to dead biomass, and competitive exclusion likely decreased species density in fenced and fertilized plots. We conclude that experimental validation is required to determine the predictive value of comparative relationships derived from descriptive data.
Space vehicle acoustics prediction improvement for payloads. [space shuttle

NASA Technical Reports Server (NTRS)

Dandridge, R. E.

1979-01-01

The modal analysis method was extensively modified for the prediction of space vehicle noise reduction in the shuttle payload enclosure, and this program was adapted to the IBM 360 computer. The predicted noise reduction levels for two test cases were compared with experimental results to determine the validity of the analytical model for predicting space vehicle payload noise environments in the 10 Hz one-third octave band regime. The prediction approach for the two test cases generally gave reasonable magnitudes and trends when compared with the measured noise reduction spectra. The discrepancies in the predictions could be corrected primarily by improved modeling of the vehicle structural walls and of the enclosed acoustic space to obtain a more accurate assessment of normal modes. Techniques for improving and expandng the noise prediction for a payload environment are also suggested.
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 suggest that, in order to appropriately model early HIV/SIV dynamics, additional factors must be considered in the model development. These may include variability in monkey susceptibility to infection, within-host competition between different viruses for target cells at the initial site of virus replication in the mucosa, innate immune response, and possibly the inclusion of several different tissue compartments. The sobering news is that while an increase in model complexity is needed to explain the available experimental data, testing and rejection of more complex models may require more quantitative data than is currently available. PMID:25781919

Prediction of Stereochemistry using Q2MM

PubMed Central

2016-01-01

Conspectus The standard method of screening ligands for selectivity in asymmetric, transition metal-catalyzed reactions requires experimental testing of hundreds of ligands from ligand libraries. This “trial and error” process is costly in terms of time as well as resources and, in general, is scientifically and intellectually unsatisfying as it reveals little about the underlying mechanism behind the selectivity. The accurate computational prediction of stereoselectivity in enantioselective catalysis requires adequate conformational sampling of the selectivity-determining transition state but has to be fast enough to compete with experimental screening techniques to be useful for the synthetic chemist. Although electronic structure calculations are accurate and general, they are too slow to allow for sampling or fast screening of ligand libraries. The combined requirements can be fulfilled by using appropriately fitted transition state force fields (TSFFs) that represent the transition state as a minimum and allow fast conformational sampling using Monte Carlo. Quantum-guided molecular mechanics (Q2MM) is an automated force field parametrization method that generates accurate, reaction-specific TSFFs by fitting the functional form of an arbitrary force field using only electronic structure calculations by minimization of an objective function. A key feature that distinguishes the Q2MM method from many other automated parametrization procedures is the use of the Hessian matrix in addition to geometric parameters and relative energies. This alleviates the known problems of overfitting of TSFFs. After validation of the TSFF by comparison to electronic structure results for a test set and available experimental data, the stereoselectivity of a reaction can be calculated by summation over the Boltzman-averaged relative energies of the conformations leading to the different stereoisomers. The Q2MM method has been applied successfully to perform virtual ligand screens on a range of transition metal-catalyzed reactions that are important from both an industrial and an academic perspective. In this Account, we provide an overview of the continued improvement of the prediction of stereochemistry using Q2MM-derived TSFFs using four examples from different stages of development: (i) Pd-catalyzed allylation, (ii) OsO4-catalyzed asymmetric dihydroxylation (AD) of alkenes, (iii) Rh-catalyzed hydrogenation of enamides, and (iv) Ru-catalyzed hydrogenation of ketones. In the current form, correlation coefficients of 0.8–0.9 between calculated and experimental ee values are typical for a wide range of substrate–ligand combinations, and suitable ligands can be predicted for a given substrate with ∼80% accuracy. Although the generation of a TSFF requires an initial effort and will therefore be most useful for widely used reactions that require frequent screening campaigns, the method allows for a rapid virtual screen of large ligand libraries to focus experimental efforts on the most promising substrate–ligand combinations. PMID:27064579
Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana.

PubMed

Hansen, Bjoern Oest; Meyer, Etienne H; Ferrari, Camilla; Vaid, Neha; Movahedi, Sara; Vandepoele, Klaas; Nikoloski, Zoran; Mutwil, Marek

2018-03-01

Recent advances in gene function prediction rely on ensemble approaches that integrate results from multiple inference methods to produce superior predictions. Yet, these developments remain largely unexplored in plants. We have explored and compared two methods to integrate 10 gene co-function networks for Arabidopsis thaliana and demonstrate how the integration of these networks produces more accurate gene function predictions for a larger fraction of genes with unknown function. These predictions were used to identify genes involved in mitochondrial complex I formation, and for five of them, we confirmed the predictions experimentally. The ensemble predictions are provided as a user-friendly online database, EnsembleNet. The methods presented here demonstrate that ensemble gene function prediction is a powerful method to boost prediction performance, whereas the EnsembleNet database provides a cutting-edge community tool to guide experimentalists. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.
Identification of novel plant peroxisomal targeting signals by a combination of machine learning methods and in vivo subcellular targeting analyses.

PubMed

Lingner, Thomas; Kataya, Amr R; Antonicelli, Gerardo E; Benichou, Aline; Nilssen, Kjersti; Chen, Xiong-Yan; Siemsen, Tanja; Morgenstern, Burkhard; Meinicke, Peter; Reumann, Sigrun

2011-04-01

In the postgenomic era, accurate prediction tools are essential for identification of the proteomes of cell organelles. Prediction methods have been developed for peroxisome-targeted proteins in animals and fungi but are missing specifically for plants. For development of a predictor for plant proteins carrying peroxisome targeting signals type 1 (PTS1), we assembled more than 2500 homologous plant sequences, mainly from EST databases. We applied a discriminative machine learning approach to derive two different prediction methods, both of which showed high prediction accuracy and recognized specific targeting-enhancing patterns in the regions upstream of the PTS1 tripeptides. Upon application of these methods to the Arabidopsis thaliana genome, 392 gene models were predicted to be peroxisome targeted. These predictions were extensively tested in vivo, resulting in a high experimental verification rate of Arabidopsis proteins previously not known to be peroxisomal. The prediction methods were able to correctly infer novel PTS1 tripeptides, which even included novel residues. Twenty-three newly predicted PTS1 tripeptides were experimentally confirmed, and a high variability of the plant PTS1 motif was discovered. These prediction methods will be instrumental in identifying low-abundance and stress-inducible peroxisomal proteins and defining the entire peroxisomal proteome of Arabidopsis and agronomically important crop plants.
Contact thermal shock test of ceramics

NASA Technical Reports Server (NTRS)

Rogers, W. P.; Emery, A. F.

1992-01-01

A novel quantitative thermal shock test of ceramics is described. The technique employs contact between a metal-cooling rod and hot disk-shaped specimen. In contrast with traditional techniques, the well-defined thermal boundary condition allows for accurate analyses of heat transfer, stress, and fracture. Uniform equibiaxial tensile stresses are induced in the center of the test specimen. Transient specimen temperature and acoustic emission are monitored continuously during the thermal stress cycle. The technique is demonstrated with soda-lime glass specimens. Experimental results are compared with theoretical predictions based on a finite-element method thermal stress analysis combined with a statistical model of fracture. Material strength parameters are determined using concentric ring flexure tests. Good agreement is found between experimental results and theoretical predictions of failure probability as a function of time and initial specimen temperature.
Viscous/potential flow about multi-element two-dimensional and infinite-span swept wings: Theory and experiment

NASA Technical Reports Server (NTRS)

Olson, L. E.; Dvorak, F. A.

1975-01-01

The viscous subsonic flow past two-dimensional and infinite-span swept multi-component airfoils is studied theoretically and experimentally. The computerized analysis is based on iteratively coupled boundary layer and potential flow analysis. The method, which is restricted to flows with only slight separation, gives surface pressure distribution, chordwise and spanwise boundary layer characteristics, lift, drag, and pitching moment for airfoil configurations with up to four elements. Merging confluent boundary layers are treated. Theoretical predictions are compared with an exact theoretical potential flow solution and with experimental measures made in the Ames 40- by 80-Foot Wind Tunnel for both two-dimensional and infinite-span swept wing configurations. Section lift characteristics are accurately predicted for zero and moderate sweep angles where flow separation effects are negligible.
Modelling and simulation of a moving interface problem: freeze drying of black tea extract

NASA Astrophysics Data System (ADS)

Aydin, Ebubekir Sıddık; Yucel, Ozgun; Sadikoglu, Hasan

2017-06-01

The moving interface separates the material that is subjected to the freeze drying process as dried and frozen. Therefore, the accurate modeling the moving interface reduces the process time and energy consumption by improving the heat and mass transfer predictions during the process. To describe the dynamic behavior of the drying stages of the freeze-drying, a case study of brewed black tea extract in storage trays including moving interface was modeled that the heat and mass transfer equations were solved using orthogonal collocation method based on Jacobian polynomial approximation. Transport parameters and physical properties describing the freeze drying of black tea extract were evaluated by fitting the experimental data using Levenberg-Marquardt algorithm. Experimental results showed good agreement with the theoretical predictions.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Ke; Zhang, Yanwen; Zhu, Zihua

Accurate information of electronic stopping power is fundamental for broad advances in electronic industry, space exploration, national security, and sustainable energy technologies. The Stopping and Range of Ions in Matter (SRIM) code has been widely applied to predict stopping powers and ion distributions for decades. Recent experimental results have, however, shown considerable errors in the SRIM predictions for stopping of heavy ions in compounds containing light elements, indicating an urgent need to improve current stopping power models. The electronic stopping powers of 35Cl, 80Br, 127I, and 197Au ions are experimentally determined in two important functional materials, SiC and SiO2, frommore » tens to hundreds keV/u based on a single ion technique. By combining with the reciprocity theory, new electronic stopping powers are suggested in a region from 0 to 15 MeV, where large deviations from SRIM predictions are observed. For independent experimental validation of the electronic stopping powers we determined, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC with energies from 700 keV to 15 MeV. The measured ion distributions from both RBS and SIMS are considerably deeper (up to ~30%) than the predictions from the commercial SRIM code. In comparison, the new electronic stopping power values are utilized in a modified TRIM-85 (the original version of the SRIM) code, M-TRIM, to predict ion distributions, and the results are in good agreement with the experimentally measured ion distributions.« less
Experimentally assessing molecular dynamics sampling of the protein native state conformational distribution

PubMed Central

Hernández, Griselda; Anderson, Janet S.; LeMaster, David M.

2012-01-01

The acute sensitivity to conformation exhibited by amide hydrogen exchange reactivity provides a valuable test for the physical accuracy of model ensembles developed to represent the Boltzmann distribution of the protein native state. A number of molecular dynamics studies of ubiquitin have predicted a well-populated transition in the tight turn immediately preceding the primary site of proteasome-directed polyubiquitylation Lys 48. Amide exchange reactivity analysis demonstrates that this transition is 103-fold rarer than these predictions. More strikingly, for the most populated novel conformational basin predicted from a recent 1 ms MD simulation of bovine pancreatic trypsin inhibitor (at 13% of total), experimental hydrogen exchange data indicates a population below 10−6. The most sophisticated efforts to directly incorporate experimental constraints into the derivation of model protein ensembles have been applied to ubiquitin, as illustrated by three recently deposited studies (PDB codes 2NR2, 2K39 and 2KOX). Utilizing the extensive set of experimental NOE constraints, each of these three ensembles yields a modestly more accurate prediction of the exchange rates for the highly exposed amides than does a standard unconstrained molecular simulation. However, for the less frequently exposed amide hydrogens, the 2NR2 ensemble offers no improvement in rate predictions as compared to the unconstrained MD ensemble. The other two NMR-constrained ensembles performed markedly worse, either underestimating (2KOX) or overestimating (2K39) the extent of conformational diversity. PMID:22425325
Optimal experimental design in an epidermal growth factor receptor signalling and down-regulation model.

PubMed

Casey, F P; Baird, D; Feng, Q; Gutenkunst, R N; Waterfall, J J; Myers, C R; Brown, K S; Cerione, R A; Sethna, J P

2007-05-01

We apply the methods of optimal experimental design to a differential equation model for epidermal growth factor receptor signalling, trafficking and down-regulation. The model incorporates the role of a recently discovered protein complex made up of the E3 ubiquitin ligase, Cbl, the guanine exchange factor (GEF), Cool-1 (beta -Pix) and the Rho family G protein Cdc42. The complex has been suggested to be important in disrupting receptor down-regulation. We demonstrate that the model interactions can accurately reproduce the experimental observations, that they can be used to make predictions with accompanying uncertainties, and that we can apply ideas of optimal experimental design to suggest new experiments that reduce the uncertainty on unmeasurable components of the system.
Research into the rationality and the application scopes of different melting models of nanoparticles

NASA Astrophysics Data System (ADS)

Fu, Qingshan; Xue, Yongqiang; Cui, Zixiang; Duan, Huijuan

2017-07-01

A rational melting model is indispensable to address the fundamental issue regarding the melting of nanoparticles. To ascertain the rationality and the application scopes of the three classical thermodynamic models, namely Pawlow, Rie, and Reiss melting models, corresponding accurate equations for size-dependent melting temperature of nanoparticles were derived. Comparison of the melting temperatures of Au, Al, and Sn nanoparticles calculated by the accurate equations with available experimental results demonstrates that both Reiss and Rie melting models are rational and capable of accurately describing the melting behaviors of nanoparticles at different melting stages. The former (surface pre-melting) is applicable to the stage from initial melting to critical thickness of liquid shell, while the latter (solid particles surrounded by a great deal of liquid) from the critical thickness to complete melting. The melting temperatures calculated by the accurate equation based on Reiss melting model are in good agreement with experimental results within the whole size range of calculation compared with those by other theoretical models. In addition, the critical thickness of liquid shell is found to decrease with particle size decreasing and presents a linear variation with particle size. The accurate thermodynamic equations based on Reiss and Rie melting models enable us to quantitatively and conveniently predict and explain the melting behaviors of nanoparticles at all size range in the whole melting process. [Figure not available: see fulltext.
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.
Ab initio interatomic potentials and the thermodynamic properties of fluids

NASA Astrophysics Data System (ADS)

Vlasiuk, Maryna; Sadus, Richard J.

2017-07-01

Monte Carlo simulations with accurate ab initio interatomic potentials are used to investigate the key thermodynamic properties of argon and krypton in both vapor and liquid phases. Data are reported for the isochoric and isobaric heat capacities, the Joule-Thomson coefficient, and the speed of sound calculated using various two-body interatomic potentials and different combinations of two-body plus three-body terms. The results are compared to either experimental or reference data at state points between the triple and critical points. Using accurate two-body ab initio potentials, combined with three-body interaction terms such as the Axilrod-Teller-Muto and Marcelli-Wang-Sadus potentials, yields systematic improvements to the accuracy of thermodynamic predictions. The effect of three-body interactions is to lower the isochoric and isobaric heat capacities and increase both the Joule-Thomson coefficient and speed of sound. The Marcelli-Wang-Sadus potential is a computationally inexpensive way to utilize accurate two-body ab initio potentials for the prediction of thermodynamic properties. In particular, it provides a very effective way of extending two-body ab initio potentials to liquid phase properties.
Molecular acidity: An accurate description with information-theoretic approach in density functional reactivity theory.

PubMed

Cao, Xiaofang; Rong, Chunying; Zhong, Aiguo; Lu, Tian; Liu, Shubin

2018-01-15

Molecular acidity is one of the important physiochemical properties of a molecular system, yet its accurate calculation and prediction are still an unresolved problem in the literature. In this work, we propose to make use of the quantities from the information-theoretic (IT) approach in density functional reactivity theory and provide an accurate description of molecular acidity from a completely new perspective. To illustrate our point, five different categories of acidic series, singly and doubly substituted benzoic acids, singly substituted benzenesulfinic acids, benzeneseleninic acids, phenols, and alkyl carboxylic acids, have been thoroughly examined. We show that using IT quantities such as Shannon entropy, Fisher information, Ghosh-Berkowitz-Parr entropy, information gain, Onicescu information energy, and relative Rényi entropy, one is able to simultaneously predict experimental pKa values of these different categories of compounds. Because of the universality of the quantities employed in this work, which are all density dependent, our approach should be general and be applicable to other systems as well. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Morphological Awareness and Children's Writing: Accuracy, Error, and Invention

PubMed Central

McCutchen, Deborah; Stull, Sara

2014-01-01

This study examined the relationship between children's morphological awareness and their ability to produce accurate morphological derivations in writing. Fifth-grade U.S. students (n = 175) completed two writing tasks that invited or required morphological manipulation of words. We examined both accuracy and error, specifically errors in spelling and errors of the sort we termed morphological inventions, which entailed inappropriate, novel pairings of stems and suffixes. Regressions were used to determine the relationship between morphological awareness, morphological accuracy, and spelling accuracy, as well as between morphological awareness and morphological inventions. Linear regressions revealed that morphological awareness uniquely predicted children's generation of accurate morphological derivations, regardless of whether or not accurate spelling was required. A logistic regression indicated that morphological awareness was also uniquely predictive of morphological invention, with higher morphological awareness increasing the probability of morphological invention. These findings suggest that morphological knowledge may not only assist children with spelling during writing, but may also assist with word production via generative experimentation with morphological rules during sentence generation. Implications are discussed for the development of children's morphological knowledge and relationships with writing. PMID:25663748
Ab initio interatomic potentials and the thermodynamic properties of fluids.

PubMed

Vlasiuk, Maryna; Sadus, Richard J

2017-07-14

Monte Carlo simulations with accurate ab initio interatomic potentials are used to investigate the key thermodynamic properties of argon and krypton in both vapor and liquid phases. Data are reported for the isochoric and isobaric heat capacities, the Joule-Thomson coefficient, and the speed of sound calculated using various two-body interatomic potentials and different combinations of two-body plus three-body terms. The results are compared to either experimental or reference data at state points between the triple and critical points. Using accurate two-body ab initio potentials, combined with three-body interaction terms such as the Axilrod-Teller-Muto and Marcelli-Wang-Sadus potentials, yields systematic improvements to the accuracy of thermodynamic predictions. The effect of three-body interactions is to lower the isochoric and isobaric heat capacities and increase both the Joule-Thomson coefficient and speed of sound. The Marcelli-Wang-Sadus potential is a computationally inexpensive way to utilize accurate two-body ab initio potentials for the prediction of thermodynamic properties. In particular, it provides a very effective way of extending two-body ab initio potentials to liquid phase properties.
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
Accurate bond energies of hydrocarbons from complete basis set extrapolated multi-reference singles and doubles configuration interaction.

PubMed

Oyeyemi, Victor B; Pavone, Michele; Carter, Emily A

2011-12-09

Quantum chemistry has become one of the most reliable tools for characterizing the thermochemical underpinnings of reactions, such as bond dissociation energies (BDEs). The accurate prediction of these particular properties (BDEs) are challenging for ab initio methods based on perturbative corrections or coupled cluster expansions of the single-determinant Hartree-Fock wave function: the processes of bond breaking and forming are inherently multi-configurational and require an accurate description of non-dynamical electron correlation. To this end, we present a systematic ab initio approach for computing BDEs that is based on three components: 1) multi-reference single and double excitation configuration interaction (MRSDCI) for the electronic energies; 2) a two-parameter scheme for extrapolating MRSDCI energies to the complete basis set limit; and 3) DFT-B3LYP calculations of minimum-energy structures and vibrational frequencies to account for zero point energy and thermal corrections. We validated our methodology against a set of reliable experimental BDE values of CC and CH bonds of hydrocarbons. The goal of chemical accuracy is achieved, on average, without applying any empirical corrections to the MRSDCI electronic energies. We then use this composite scheme to make predictions of BDEs in a large number of hydrocarbon molecules for which there are no experimental data, so as to provide needed thermochemical estimates for fuel molecules. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Computational/Experimental Aeroheating Predictions for X-33. Phase 2; Vehicle

NASA Technical Reports Server (NTRS)

Hamilton, H. Harris, II; Weilmuenster, K. James; Horvath, Thomas J.; Berry, Scott A.

1998-01-01

Laminar and turbulent heating-rate calculations from an "engineering" code and laminar calculations from a "benchmark" Navier-Stokes code are compared with experimental wind-tunnel data obtained on several candidate configurations for the X-33 Phase 2 flight vehicle. The experimental data were obtained at a Mach number of 6 and a freestream Reynolds number ranging from 1 to 8 x 10(exp 6)/ft. Comparisons are presented along the windward symmetry plane and in a circumferential direction around the body at several axial stations at angles of attack from 20 to 40 deg. The experimental results include both laminar and turbulent flow. For the highest angle of attack some of the measured heating data exhibited a "non-laminar" behavior which caused the heating to increase above the laminar level long before "classical" transition to turbulent flow was observed. This trend was not observed at the lower angles of attack. When the flow was laminar, both codes predicted the heating along the windward symmetry plane reasonably well but under-predicted the heating in the chine region. When the flow was turbulent the LATCH code accurately predicted the measured heating rates. Both codes were used to calculate heating rates over the X-33 vehicle at the peak heating point on the design trajectory and they were found to be in very good agreement over most of the vehicle windward surface.
MnNiO3 revisited with modern theoretical and experimental methods

NASA Astrophysics Data System (ADS)

Dzubak, Allison L.; Mitra, Chandrima; Chance, Michael; Kuhn, Stephen; Jellison, Gerald E.; Sefat, Athena S.; Krogel, Jaron T.; Reboredo, Fernando A.

2017-11-01

MnNiO3 is a strongly correlated transition metal oxide that has recently been investigated theoretically for its potential application as an oxygen-evolution photocatalyst. However, there is no experimental report on critical quantities such as the band gap or bulk modulus. Recent theoretical predictions with standard functionals such as LDA+U and HSE show large discrepancies in the band gaps (about 1.23 eV), depending on the nature of the functional used. Hence there is clearly a need for an accurate quantitative prediction of the band gap to gauge its utility as a photocatalyst. In this work, we present a diffusion quantum Monte Carlo study of the bulk properties of MnNiO3 and revisit the synthesis and experimental properties of the compound. We predict quasiparticle band gaps of 2.0(5) eV and 3.8(6) eV for the majority and minority spin channels, respectively, and an equilibrium volume of 92.8 Å3, which compares well to the experimental value of 94.4 Å3. A bulk modulus of 217 GPa is predicted for MnNiO3. We rationalize the difficulty for the formation of ordered ilmenite-type structure with specific sites for Ni and Mn to be potentially due to the formation of antisite defects that form during synthesis, which ultimately affects the physical properties of MnNiO3.
Expediting SRM assay development for large-scale targeted proteomics experiments

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

Wu, Chaochao; Shi, Tujin; Brown, Joseph N.

2014-08-22

Due to their high sensitivity and specificity, targeted proteomics measurements, e.g. selected reaction monitoring (SRM), are becoming increasingly popular for biological and translational applications. Selection of optimal transitions and optimization of collision energy (CE) are important assay development steps for achieving sensitive detection and accurate quantification; however, these steps can be labor-intensive, especially for large-scale applications. Herein, we explored several options for accelerating SRM assay development evaluated in the context of a relatively large set of 215 synthetic peptide targets. We first showed that HCD fragmentation is very similar to CID in triple quadrupole (QQQ) instrumentation, and by selection ofmore » top six y fragment ions from HCD spectra, >86% of top transitions optimized from direct infusion on QQQ instrument are covered. We also demonstrated that the CE calculated by existing prediction tools was less accurate for +3 precursors, and a significant increase in intensity for transitions could be obtained using a new CE prediction equation constructed from the present experimental data. Overall, our study illustrates the feasibility of expediting the development of larger numbers of high-sensitivity SRM assays through automation of transitions selection and accurate prediction of optimal CE to improve both SRM throughput and measurement quality.« less

Impact of Upfront Cellular Enrichment by Laser Capture Microdissection on Protein and Phosphoprotein Drug Target Signaling Activation Measurements in Human Lung Cancer: Implications for Personalized Medicine

PubMed Central

Elisa, Baldelli; B., Haura Eric; Lucio, Crinò; Douglas, Cress W.; Vienna, Ludovini; B., Schabath Matthew; A., Liotta Lance; F., Petricoin Emanuel; Mariaelena, Pierobon

2015-01-01

Purpose The aim of this study was to evaluate whether upfront cellular enrichment via laser capture microdissection is necessary for accurately quantifying predictive biomarkers in non-small cell lung cancer tumors. Experimental design Fifteen snap frozen surgical biopsies were analyzed. Whole tissue lysate and matched highly enriched tumor epithelium via laser capture microdissection (LCM) were obtained for each patient. The expression and activation/phosphorylation levels of 26 proteins were measured by reverse phase protein microarray. Differences in signaling architecture of dissected and undissected matched pairs were visualized using unsupervised clustering analysis, bar graphs, and scatter plots. Results Overall patient matched LCM and undissected material displayed very distinct and differing signaling architectures with 93% of the matched pairs clustering separately. These differences were seen regardless of the amount of starting tumor epithelial content present in the specimen. Conclusions and clinical relevance These results indicate that LCM driven upfront cellular enrichment is necessary to accurately determine the expression/activation levels of predictive protein signaling markers although results should be evaluated in larger clinical settings. Upfront cellular enrichment of the target cell appears to be an important part of the workflow needed for the accurate quantification of predictive protein signaling biomarkers. Larger independent studies are warranted. PMID:25676683
Experimental study on the impact of temperature on the dissipation process of supersaturated total dissolved gas.

PubMed

Shen, Xia; Liu, Shengyun; Li, Ran; Ou, Yangming

2014-09-01

Water temperature not only affects the solubility of gas in water but can also be an important factor in the dissipation process of supersaturated total dissolved gas (TDG). The quantitative relationship between the dissipation process and temperature has not been previously described. This relationship affects the accurate evaluation of the dissipation process and the subsequent biological effects. This article experimentally investigates the impact of temperature on supersaturated TDG dissipation in static and turbulent conditions. The results show that the supersaturated TDG dissipation coefficient increases with the temperature and turbulence intensity. The quantitative relationship was verified by straight flume experiments. This study enhances our understanding of the dissipation of supersaturated TDG. Furthermore, it provides a scientific foundation for the accurate prediction of the dissipation process of supersaturated TDG in the downstream area and the negative impacts of high dam projects on aquatic ecosystems. Copyright © 2014. Published by Elsevier B.V.
Correlation Equations for Condensing Heat Exchangers Based on an Algorithmic Performance-Data Classification

NASA Astrophysics Data System (ADS)

Pacheco-Vega, Arturo

2016-09-01

In this work a new set of correlation equations is developed and introduced to accurately describe the thermal performance of compact heat exchangers with possible condensation. The feasible operating conditions for the thermal system correspond to dry- surface, dropwise condensation, and film condensation. Using a prescribed form for each condition, a global regression analysis for the best-fit correlation to experimental data is carried out with a simulated annealing optimization technique. The experimental data were taken from the literature and algorithmically classified into three groups -related to the possible operating conditions- with a previously-introduced Gaussian-mixture-based methodology. Prior to their use in the analysis, the correct data classification was assessed and confirmed via artificial neural networks. Predictions from the correlations obtained for the different conditions are within the uncertainty of the experiments and substantially more accurate than those commonly used.
Computational Assessment of Aft-Body Closure for the HSR Reference H Configuration

NASA Technical Reports Server (NTRS)

Londenberg, W. Kelly

1999-01-01

A study has been conducted to determine how well the USM3D unstructured Euler solver can be utilized to predict the flow over the High Speed Research (HSR) Reference H configuration with an ultimate goal of prediction of Sting interference so after body closure effects may be evaluated. This study has shown that the code can be used to predict the interference effects of a lower mounted blade sting with a high degree of confidence. It has been shown that wing and fuselage pressures, both levels and trends, can be predicted well. Force and moment levels are not predicted well but experimental trends are predicted. Based upon this, predicted force and moment increments are assumed to be predicted accurately. Deflection of the horizontal tail was found to cause a non-linear increment from the non-deflected sting interference effects.
Evaluating the accuracy of SHAPE-directed RNA secondary structure predictions

PubMed Central

Sükösd, Zsuzsanna; Swenson, M. Shel; Kjems, Jørgen; Heitsch, Christine E.

2013-01-01

Recent advances in RNA structure determination include using data from high-throughput probing experiments to improve thermodynamic prediction accuracy. We evaluate the extent and nature of improvements in data-directed predictions for a diverse set of 16S/18S ribosomal sequences using a stochastic model of experimental SHAPE data. The average accuracy for 1000 data-directed predictions always improves over the original minimum free energy (MFE) structure. However, the amount of improvement varies with the sequence, exhibiting a correlation with MFE accuracy. Further analysis of this correlation shows that accurate MFE base pairs are typically preserved in a data-directed prediction, whereas inaccurate ones are not. Thus, the positive predictive value of common base pairs is consistently higher than the directed prediction accuracy. Finally, we confirm sequence dependencies in the directability of thermodynamic predictions and investigate the potential for greater accuracy improvements in the worst performing test sequence. PMID:23325843
Grid-Adapted FUN3D Computations for the Second High Lift Prediction Workshop

NASA Technical Reports Server (NTRS)

Lee-Rausch, E. M.; Rumsey, C. L.; Park, M. A.

2014-01-01

Contributions of the unstructured Reynolds-averaged Navier-Stokes code FUN3D to the 2nd AIAA CFD High Lift Prediction Workshop are described, and detailed comparisons are made with experimental data. Using workshop-supplied grids, results for the clean wing configuration are compared with results from the structured code CFL3D Using the same turbulence model, both codes compare reasonably well in terms of total forces and moments, and the maximum lift is similarly over-predicted for both codes compared to experiment. By including more representative geometry features such as slat and flap brackets and slat pressure tube bundles, FUN3D captures the general effects of the Reynolds number variation, but under-predicts maximum lift on workshop-supplied grids in comparison with the experimental data, due to excessive separation. However, when output-based, off-body grid adaptation in FUN3D is employed, results improve considerably. In particular, when the geometry includes both brackets and the pressure tube bundles, grid adaptation results in a more accurate prediction of lift near stall in comparison with the wind-tunnel data. Furthermore, a rotation-corrected turbulence model shows improved pressure predictions on the outboard span when using adapted grids.
Thermal stability of mullite RMn₂O₅ (R = Bi, Y, Pr, Sm or Gd): combined density functional theory and experimental study.

PubMed

Li, Chenzhe; Thampy, Sampreetha; Zheng, Yongping; Kweun, Joshua M; Ren, Yixin; Chan, Julia Y; Kim, Hanchul; Cho, Maenghyo; Kim, Yoon Young; Hsu, Julia W P; Cho, Kyeongjae

2016-03-31

Understanding and effectively predicting the thermal stability of ternary transition metal oxides with heavy elements using first principle simulations are vital for understanding performance of advanced materials. In this work, we have investigated the thermal stability of mullite RMn2O5 (R = Bi, Pr, Sm, or Gd) structures by constructing temperature phase diagrams using an efficient mixed generalized gradient approximation (GGA) and the GGA + U method. Simulation predicted stability regions without corrections on heavy elements show a 4-200 K underestimation compared to our experimental results. We have found the number of d/f electrons in the heavy elements shows a linear relationship with the prediction deviation. Further correction on the strongly correlated electrons in heavy elements could significantly reduce the prediction deviations. Our corrected simulation results demonstrate that further correction of R-site elements in RMn2O5 could effectively reduce the underestimation of the density functional theory-predicted decomposition temperature to within 30 K. Therefore, it could produce an accurate thermal stability prediction for complex ternary transition metal oxide compounds with heavy elements.
Cold formability prediction by the modified maximum force criterion with a non-associated Hill48 model accounting for anisotropic hardening

NASA Astrophysics Data System (ADS)

Lian, J.; Ahn, D. C.; Chae, D. C.; Münstermann, S.; Bleck, W.

2016-08-01

Experimental and numerical investigations on the characterisation and prediction of cold formability of a ferritic steel sheet are performed in this study. Tensile tests and Nakajima tests were performed for the plasticity characterisation and the forming limit diagram determination. In the numerical prediction, the modified maximum force criterion is selected as the localisation criterion. For the plasticity model, a non-associated formulation of the Hill48 model is employed. With the non-associated flow rule, the model can result in a similar predictive capability of stress and r-value directionality to the advanced non-quadratic associated models. To accurately characterise the anisotropy evolution during hardening, the anisotropic hardening is also calibrated and implemented into the model for the prediction of the formability.
Antibody specific epitope prediction-emergence of a new paradigm.

PubMed

Sela-Culang, Inbal; Ofran, Yanay; Peters, Bjoern

2015-04-01

The development of accurate tools for predicting B-cell epitopes is important but difficult. Traditional methods have examined which regions in an antigen are likely binding sites of an antibody. However, it is becoming increasingly clear that most antigen surface residues will be able to bind one or more of the myriad of possible antibodies. In recent years, new approaches have emerged for predicting an epitope for a specific antibody, utilizing information encoded in antibody sequence or structure. Applying such antibody-specific predictions to groups of antibodies in combination with easily obtainable experimental data improves the performance of epitope predictions. We expect that further advances of such tools will be possible with the integration of immunoglobulin repertoire sequencing data. Copyright © 2015 Elsevier B.V. All rights reserved.
Application of a High-Fidelity Icing Analysis Method to a Model-Scale Rotor in Forward Flight

NASA Technical Reports Server (NTRS)

Narducci, Robert; Orr, Stanley; Kreeger, Richard E.

2012-01-01

An icing analysis process involving the loose coupling of OVERFLOW-RCAS for rotor performance prediction and with LEWICE3D for thermal analysis and ice accretion is applied to a model-scale rotor for validation. The process offers high-fidelity rotor analysis for the noniced and iced rotor performance evaluation that accounts for the interaction of nonlinear aerodynamics with blade elastic deformations. Ice accumulation prediction also involves loosely coupled data exchanges between OVERFLOW and LEWICE3D to produce accurate ice shapes. Validation of the process uses data collected in the 1993 icing test involving Sikorsky's Powered Force Model. Non-iced and iced rotor performance predictions are compared to experimental measurements as are predicted ice shapes.
Hadroproduction of t anti-t pair in association with an isolated photon at NLO accuracy matched with parton shower

NASA Astrophysics Data System (ADS)

Kardos, Adam; Trócsányi, Zoltán

2015-05-01

We simulate the hadroproduction of a -pair in association with a hard photon at LHC using the PowHel package. These events are almost fully inclusive with respect to the photon, allowing for any physically relevant isolation of the photon. We use the generated events, stored according to the Les-Houches event format, to make predictions for differential distributions formally at the next-to-leading order (NLO) accuracy and we compare these to existing predictions accurate at NLO using the smooth isolation prescription of Frixione. Our fixed-order predictions include the direct-photon contribution only. We also make predictions for distributions after full parton shower and hadronization using the standard experimental cone-isolation of the photon.
Prediction of Size Effects in Notched Laminates Using Continuum Damage Mechanics

NASA Technical Reports Server (NTRS)

Camanho, D. P.; Maimi, P.; Davila, C. G.

2007-01-01

This paper examines the use of a continuum damage model to predict strength and size effects in notched carbon-epoxy laminates. The effects of size and the development of a fracture process zone before final failure are identified in an experimental program. The continuum damage model is described and the resulting predictions of size effects are compared with alternative approaches: the point stress and the inherent flaw models, the Linear-Elastic Fracture Mechanics approach, and the strength of materials approach. The results indicate that the continuum damage model is the most accurate technique to predict size effects in composites. Furthermore, the continuum damage model does not require any calibration and it is applicable to general geometries and boundary conditions.
The impact of experimental measurement errors on long-term viscoelastic predictions. [of structural materials

NASA Technical Reports Server (NTRS)

Tuttle, M. E.; Brinson, H. F.

1986-01-01

The impact of flight error in measured viscoelastic parameters on subsequent long-term viscoelastic predictions is numerically evaluated using the Schapery nonlinear viscoelastic model. Of the seven Schapery parameters, the results indicated that long-term predictions were most sensitive to errors in the power law parameter n. Although errors in the other parameters were significant as well, errors in n dominated all other factors at long times. The process of selecting an appropriate short-term test cycle so as to insure an accurate long-term prediction was considered, and a short-term test cycle was selected using material properties typical for T300/5208 graphite-epoxy at 149 C. The process of selection is described, and its individual steps are itemized.
PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations

PubMed Central

Bendl, Jaroslav; Stourac, Jan; Salanda, Ondrej; Pavelka, Antonin; Wieben, Eric D.; Zendulka, Jaroslav; Brezovsky, Jan; Damborsky, Jiri

2014-01-01

Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp. PMID:24453961
Microstructural Characterization and Modeling of SLM Superalloy 718

NASA Technical Reports Server (NTRS)

Smith, Tim M.; Sudbrack, Chantal K.; Bonacuse, Pete; Rogers, Richard

2017-01-01

Superalloy 718 is an excellent candidate for selective laser melting (SLM) fabrication due to a combination of excellent mechanical properties and workability. Predicting and validating the microstructure of SLM-fabricated Superalloy 718 after potential post heat-treatment paths is an important step towards producing components comparable to those made using conventional methods. At present, obtaining accurate volume fraction and size measurements of gamma-double-prime, gamma-prime and delta precipitates has been challenging due to their size, low volume fractions, and similar chemistries. A technique combining high resolution distortion corrected SEM imaging and with x-ray energy dispersive spectroscopy has been developed to accurately and independently measure the size and volume fractions of the three precipitates. These results were further validated using x-ray diffraction and phase extraction methods and compared to the precipitation kinetics predicted by PANDAT and JMatPro. Discrepancies are discussed in context of materials properties, model assumptions, sampling, and experimental errors.
Numerical determination of lateral loss coefficients for subchannel analysis in nuclear fuel bundles

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

Sin Kim; Goon-Cherl Park

1995-09-01

An accurate prediction of cross-flow based on detailed knowledge of the velocity field in subchannels of a nuclear fuel assembly is of importance in nuclear fuel performance analysis. In this study, the low-Reynolds number {kappa}-{epsilon} turbulence model has been adopted in two adjacent subchannels with cross-flow. The secondary flow is estimated accurately by the anisotropic algebraic Reynolds stress model. This model was numerically calculated by the finite element method and has been verified successfully through comparison with existing experimental data. Finally, with the numerical analysis of the velocity field in such subchannel domain, an analytical correlation of the lateral lossmore » coefficient is obtained to predict the cross-flow rate in subchannel analysis codes. The correlation is expressed as a function of the ratio of the lateral flow velocity to the donor subchannel axial velocity, recipient channel Reynolds number and pitch-to-diameter.« less
Optimal Design of Experiments by Combining Coarse and Fine Measurements

NASA Astrophysics Data System (ADS)

Lee, Alpha A.; Brenner, Michael P.; Colwell, Lucy J.

2017-11-01

In many contexts, it is extremely costly to perform enough high-quality experimental measurements to accurately parametrize a predictive quantitative model. However, it is often much easier to carry out large numbers of experiments that indicate whether each sample is above or below a given threshold. Can many such categorical or "coarse" measurements be combined with a much smaller number of high-resolution or "fine" measurements to yield accurate models? Here, we demonstrate an intuitive strategy, inspired by statistical physics, wherein the coarse measurements are used to identify the salient features of the data, while the fine measurements determine the relative importance of these features. A linear model is inferred from the fine measurements, augmented by a quadratic term that captures the correlation structure of the coarse data. We illustrate our strategy by considering the problems of predicting the antimalarial potency and aqueous solubility of small organic molecules from their 2D molecular structure.
Prediction of Liquid Slosh Damping Using a High Resolution CFD Tool

NASA Technical Reports Server (NTRS)

Yang, H. Q.; Purandare, Ravi; Peugeot, John; West, Jeff

2012-01-01

Propellant slosh is a potential source of disturbance critical to the stability of space vehicles. The slosh dynamics are typically represented by a mechanical model of a spring mass damper. This mechanical model is then included in the equation of motion of the entire vehicle for Guidance, Navigation and Control analysis. Our previous effort has demonstrated the soundness of a CFD approach in modeling the detailed fluid dynamics of tank slosh and the excellent accuracy in extracting mechanical properties (slosh natural frequency, slosh mass, and slosh mass center coordinates). For a practical partially-filled smooth wall propellant tank with a diameter of 1 meter, the damping ratio is as low as 0.0005 (or 0.05%). To accurately predict this very low damping value is a challenge for any CFD tool, as one must resolve a thin boundary layer near the wall and must minimize numerical damping. This work extends our previous effort to extract this challenging parameter from first principles: slosh damping for smooth wall and for ring baffle. First the experimental data correlated into the industry standard for smooth wall were used as the baseline validation. It is demonstrated that with proper grid resolution, CFD can indeed accurately predict low damping values from smooth walls for different tank sizes. The damping due to ring baffles at different depths from the free surface and for different sizes of tank was then simulated, and fairly good agreement with experimental correlation was observed. The study demonstrates that CFD technology can be applied to the design of future propellant tanks with complex configurations and with smooth walls or multiple baffles, where previous experimental data is not available.
Network reconstruction based on proteomic data and prior knowledge of protein connectivity using graph theory.

PubMed

Stavrakas, Vassilis; Melas, Ioannis N; Sakellaropoulos, Theodore; Alexopoulos, Leonidas G

2015-01-01

Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein-protein interaction networks and to provide meaningful biological insights.
Modification of the MML turbulence model for adverse pressure gradient flows. M.S. Thesis - Akron Univ., 1993

NASA Technical Reports Server (NTRS)

Conley, Julianne M.

1994-01-01

Computational fluid dynamics is being used increasingly to predict flows for aerospace propulsion applications, yet there is still a need for an easy to use, computationally inexpensive turbulence model capable of accurately predicting a wide range of turbulent flows. The Baldwin-Lomax model is the most widely used algebraic model, even though it has known difficulties calculating flows with strong adverse pressure gradients and large regions of separation. The modified mixing length model (MML) was developed specifically to handle the separation which occurs on airfoils and has given significantly better results than the Baldwin-Lomax model. The success of these calculations warrants further evaluation and development of MML. The objective of this work was to evaluate the performance of MML for zero and adverse pressure gradient flows, and modify it as needed. The Proteus Navier-Stokes code was used for this study and all results were compared with experimental data and with calculations made using the Baldwin-Lomax algebraic model, which is currently available in Proteus. The MML model was first evaluated for zero pressure gradient flow over a flat plate, then modified to produce the proper boundary layer growth. Additional modifications, based on experimental data for three adverse pressure gradient flows, were also implemented. The adapted model, called MMLPG (modified mixing length model for pressure gradient flows), was then evaluated for a typical propulsion flow problem, flow through a transonic diffuser. Three cases were examined: flow with no shock, a weak shock and a strong shock. The results of these calculations indicate that the objectives of this study have been met. Overall, MMLPG is capable of accurately predicting the adverse pressure gradient flows examined in this study, giving generally better agreement with experimental data than the Baldwin-Lomax model.

Modeling the Effects of Interfacial Characteristics on Gas Permeation Behavior of Nanotube-Mixed Matrix Membranes.

PubMed

Chehrazi, Ehsan; Sharif, Alireza; Omidkhah, Mohammadreza; Karimi, Mohammad

2017-10-25

Theoretical approaches that accurately predict the gas permeation behavior of nanotube-containing mixed matrix membranes (nanotube-MMMs) are scarce. This is mainly due to ignoring the effects of nanotube/matrix interfacial characteristics in the existing theories. In this paper, based on the analogy of thermal conduction in polymer composites containing nanotubes, we develop a model to describe gas permeation through nanotube-MMMs. Two new parameters, "interfacial thickness" (a int ) and "interfacial permeation resistance" (R int ), are introduced to account for the role of nanotube/matrix interfacial interactions in the proposed model. The obtained values of a int , independent of the nature of the permeate gas, increased by increasing both the nanotubes aspect ratio and polymer-nanotube interfacial strength. An excellent correlation between the values of a int and polymer-nanotube interaction parameters, χ, helped to accurately reproduce the existing experimental data from the literature without the need to resort to any adjustable parameter. The data includes 10 sets of CO 2 /CH 4 permeation, 12 sets of CO 2 /N 2 permeation, 3 sets of CO 2 /O 2 permeation, and 2 sets of CO 2 /H 2 permeation through different nanotube-MMMs. Moreover, the average absolute relative errors between the experimental data and the predicted values of the proposed model are very small (less than 5%) in comparison with those of the existing models in the literature. To the best of our knowledge, this is the first study where such a systematic comparison between model predictions and such extensive experimental data is presented. Finally, the new way of assessing gas permeation data presented in the current work would be a simple alternative to complex approaches that are usually utilized to estimate interfacial thickness in polymer composites.
A computational approach for predicting off-target toxicity of antiviral ribonucleoside analogues to mitochondrial RNA polymerase.

PubMed

Freedman, Holly; Winter, Philip; Tuszynski, Jack; Tyrrell, D Lorne; Houghton, Michael

2018-06-22

In the development of antiviral drugs that target viral RNA-dependent RNA polymerases, off-target toxicity caused by the inhibition of the human mitochondrial RNA polymerase (POLRMT) is a major liability. Therefore, it is essential that all new ribonucleoside analogue drugs be accurately screened for POLRMT inhibition. A computational tool that can accurately predict NTP binding to POLRMT could assist in evaluating any potential toxicity and in designing possible salvaging strategies. Using the available crystal structure of POLRMT bound to an RNA transcript, here we created a model of POLRMT with an NTP molecule bound in the active site. Furthermore, we implemented a computational screening procedure that determines the relative binding free energy of an NTP analogue to POLRMT by free energy perturbation (FEP), i.e. a simulation in which the natural NTP molecule is slowly transformed into the analogue and back. In each direction, the transformation was performed over 40 ns of simulation on our IBM Blue Gene Q supercomputer. This procedure was validated across a panel of drugs for which experimental dissociation constants were available, showing that NTP relative binding free energies could be predicted to within 0.97 kcal/mol of the experimental values on average. These results demonstrate for the first time that free-energy simulation can be a useful tool for predicting binding affinities of NTP analogues to a polymerase. We expect that our model, together with similar models of viral polymerases, will be very useful in the screening and future design of NTP inhibitors of viral polymerases that have no mitochondrial toxicity. © 2018 Freedman et al.
Association Rule-based Predictive Model for Machine Failure in Industrial Internet of Things

NASA Astrophysics Data System (ADS)

Kwon, Jung-Hyok; Lee, Sol-Bee; Park, Jaehoon; Kim, Eui-Jik

2017-09-01

This paper proposes an association rule-based predictive model for machine failure in industrial Internet of things (IIoT), which can accurately predict the machine failure in real manufacturing environment by investigating the relationship between the cause and type of machine failure. To develop the predictive model, we consider three major steps: 1) binarization, 2) rule creation, 3) visualization. The binarization step translates item values in a dataset into one or zero, then the rule creation step creates association rules as IF-THEN structures using the Lattice model and Apriori algorithm. Finally, the created rules are visualized in various ways for users’ understanding. An experimental implementation was conducted using R Studio version 3.3.2. The results show that the proposed predictive model realistically predicts machine failure based on association rules.
Small-time Scale Network Traffic Prediction Based on Complex-valued Neural Network

NASA Astrophysics Data System (ADS)

Yang, Bin

2017-07-01

Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately
Predicting of the refractive index of haemoglobin using the Hybrid GA-SVR approach.

PubMed

Oyehan, Tajudeen A; Alade, Ibrahim O; Bagudu, Aliyu; Sulaiman, Kazeem O; Olatunji, Sunday O; Saleh, Tawfik A

2018-04-30

The optical properties of blood play crucial roles in medical diagnostics and treatment, and in the design of new medical devices. Haemoglobin is a vital constituent of the blood whose optical properties affect all of the optical properties of human blood. The refractive index of haemoglobin has been reported to strongly depend on its concentration which is a function of the physiology of biological cells. This makes the refractive index of haemoglobin an essential non-invasive bio-marker of diseases. Unfortunately, the complexity of blood tissue makes it challenging to experimentally measure the refractive index of haemoglobin. While a few studies have reported on the refractive index of haemoglobin, there is no solid consensus with the data obtained due to different measuring instruments and the conditions of the experiments. Moreover, obtaining the refractive index via an experimental approach is quite laborious. In this work, an accurate, fast and relatively convenient strategy to estimate the refractive index of haemoglobin is reported. Thus, the GA-SVR model is presented for the prediction of the refractive index of haemoglobin using wavelength, temperature, and the concentration of haemoglobin as descriptors. The model developed is characterised by an excellent accuracy and very low error estimates. The correlation coefficients obtained in these studies are 99.94% and 99.91% for the training and testing results, respectively. In addition, the result shows an almost perfect match with the experimental data and also demonstrates significant improvement over a recent mathematical model available in the literature. The GA-SVR model predictions also give insights into the influence of concentration, wavelength, and temperature on the RI measurement values. The model outcome can be used not only to accurately estimate the refractive index of haemoglobin but also could provide a reliable common ground to benchmark the experimental refractive index results. Copyright © 2018 Elsevier Ltd. All rights reserved.
High-temperature experimental and thermodynamic modelling research on the pyrometallurgical processing of copper

NASA Astrophysics Data System (ADS)

Hidayat, Taufiq; Shishin, Denis; Decterov, Sergei A.; Hayes, Peter C.; Jak, Evgueni

2017-01-01

Uncertainty in the metal price and competition between producers mean that the daily operation of a smelter needs to target high recovery of valuable elements at low operating cost. Options for the improvement of the plant operation can be examined and decision making can be informed based on accurate information from laboratory experimentation coupled with predictions using advanced thermodynamic models. Integrated high-temperature experimental and thermodynamic modelling research on phase equilibria and thermodynamics of copper-containing systems have been undertaken at the Pyrometallurgy Innovation Centre (PYROSEARCH). The experimental phase equilibria studies involve high-temperature equilibration, rapid quenching and direct measurement of phase compositions using electron probe X-ray microanalysis (EPMA). The thermodynamic modelling deals with the development of accurate thermodynamic database built through critical evaluation of experimental data, selection of solution models, and optimization of models parameters. The database covers the Al-Ca-Cu-Fe-Mg-O-S-Si chemical system. The gas, slag, matte, liquid and solid metal phases, spinel solid solution as well as numerous solid oxide and sulphide phases are included. The database works within the FactSage software environment. Examples of phase equilibria data and thermodynamic models of selected systems, as well as possible implementation of the research outcomes to selected copper making processes are presented.
Subcooled forced convection boiling of trichlorotrifluoroethane

NASA Technical Reports Server (NTRS)

Dougall, R. S.; Panian, D. J.

1972-01-01

Experimental heat-transfer data were obtained for the forced-convection boiling of trichlorotrifluoroethane (R-113 or Freon-113) in a vertical annular test annular test section. The 97 data points obtained covered heat transfer by forced convection, local boiling, and fully-developed boiling. Correlating methods were obtained which accurately predicted the heat flux as a function of wall superheat (boiling curve) over the range of parameters studied.
Evaluation of the thin deformable active optics mirror concept

NASA Technical Reports Server (NTRS)

Robertson, H. J.

1972-01-01

The active optics concept using a thin deformable mirror has been successfully demonstrated using a 30 in. diameter, 1/2 in. thick mirror and a 61 point matrix of forces for alignment. Many of the problems associated with the design, fabrication, and launch of large aperture diffraction-limited astronomical telescopes have been resolved and experimental data created that can provide accurate predictions of performance in orbit.
Prediction and validation of diffusion coefficients in a model drug delivery system using microsecond atomistic molecular dynamics simulation and vapour sorption analysis.

PubMed

Forrey, Christopher; Saylor, David M; Silverstein, Joshua S; Douglas, Jack F; Davis, Eric M; Elabd, Yossef A

2014-10-14

Diffusion of small to medium sized molecules in polymeric medical device materials underlies a broad range of public health concerns related to unintended leaching from or uptake into implantable medical devices. However, obtaining accurate diffusion coefficients for such systems at physiological temperature represents a formidable challenge, both experimentally and computationally. While molecular dynamics simulation has been used to accurately predict the diffusion coefficients, D, of a handful of gases in various polymers, this success has not been extended to molecules larger than gases, e.g., condensable vapours, liquids, and drugs. We present atomistic molecular dynamics simulation predictions of diffusion in a model drug eluting system that represent a dramatic improvement in accuracy compared to previous simulation predictions for comparable systems. We find that, for simulations of insufficient duration, sub-diffusive dynamics can lead to dramatic over-prediction of D. We present useful metrics for monitoring the extent of sub-diffusive dynamics and explore how these metrics correlate to error in D. We also identify a relationship between diffusion and fast dynamics in our system, which may serve as a means to more rapidly predict diffusion in slowly diffusing systems. Our work provides important precedent and essential insights for utilizing atomistic molecular dynamics simulations to predict diffusion coefficients of small to medium sized molecules in condensed soft matter systems.
Determination of Membrane-Insertion Free Energies by Molecular Dynamics Simulations

PubMed Central

Gumbart, James; Roux, Benoît

2012-01-01

The accurate prediction of membrane-insertion probability for arbitrary protein sequences is a critical challenge to identifying membrane proteins and determining their folded structures. Although algorithms based on sequence statistics have had moderate success, a complete understanding of the energetic factors that drive the insertion of membrane proteins is essential to thoroughly meeting this challenge. In the last few years, numerous attempts to define a free-energy scale for amino-acid insertion have been made, yet disagreement between most experimental and theoretical scales persists. However, for a recently resolved water-to-bilayer scale, it is found that molecular dynamics simulations that carefully mimic the conditions of the experiment can reproduce experimental free energies, even when using the same force field as previous computational studies that were cited as evidence of this disagreement. Therefore, it is suggested that experimental and simulation-based scales can both be accurate and that discrepancies stem from disparities in the microscopic processes being considered rather than methodological errors. Furthermore, these disparities make the development of a single universally applicable membrane-insertion free energy scale difficult. PMID:22385850
Solving the electron and electron-nuclear Schroedinger equations for the excited states of helium atom with the free iterative-complement-interaction method

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

Nakashima, Hiroyuki; Hijikata, Yuh; Nakatsuji, Hiroshi

2008-04-21

Very accurate variational calculations with the free iterative-complement-interaction (ICI) method for solving the Schroedinger equation were performed for the 1sNs singlet and triplet excited states of helium atom up to N=24. This is the first extensive applications of the free ICI method to the calculations of excited states to very high levels. We performed the calculations with the fixed-nucleus Hamiltonian and moving-nucleus Hamiltonian. The latter case is the Schroedinger equation for the electron-nuclear Hamiltonian and includes the quantum effect of nuclear motion. This solution corresponds to the nonrelativistic limit and reproduced the experimental values up to five decimal figures. Themore » small differences from the experimental values are not at all the theoretical errors but represent the physical effects that are not included in the present calculations, such as relativistic effect, quantum electrodynamic effect, and even the experimental errors. The present calculations constitute a small step toward the accurately predictive quantum chemistry.« less
Statistical validation of predictive TRANSP simulations of baseline discharges in preparation for extrapolation to JET D-T

NASA Astrophysics Data System (ADS)

Kim, Hyun-Tae; Romanelli, M.; Yuan, X.; Kaye, S.; Sips, A. C. C.; Frassinetti, L.; Buchanan, J.; Contributors, JET

2017-06-01

This paper presents for the first time a statistical validation of predictive TRANSP simulations of plasma temperature using two transport models, GLF23 and TGLF, over a database of 80 baseline H-mode discharges in JET-ILW. While the accuracy of the predicted T e with TRANSP-GLF23 is affected by plasma collisionality, the dependency of predictions on collisionality is less significant when using TRANSP-TGLF, indicating that the latter model has a broader applicability across plasma regimes. TRANSP-TGLF also shows a good matching of predicted T i with experimental measurements allowing for a more accurate prediction of the neutron yields. The impact of input data and assumptions prescribed in the simulations are also investigated in this paper. The statistical validation and the assessment of uncertainty level in predictive TRANSP simulations for JET-ILW-DD will constitute the basis for the extrapolation to JET-ILW-DT experiments.
Failure analysis of thick composite cylinders under external pressure

NASA Technical Reports Server (NTRS)

Caiazzo, A.; Rosen, B. W.

1992-01-01

Failure of thick section composites due to local compression strength and overall structural instability is treated. Effects of material nonlinearity, imperfect fiber architecture, and structural imperfections upon anticipated failure stresses are determined. Comparisons with experimental data for a series of test cylinders are described. Predicting the failure strength of composite structures requires consideration of stability and material strength modes of failure using linear and nonlinear analysis techniques. Material strength prediction requires the accurate definition of the local multiaxial stress state in the material. An elasticity solution for the linear static analysis of thick anisotropic cylinders and rings is used herein to predict the axisymmetric stress state in the cylinders. Asymmetric nonlinear behavior due to initial cylinder out of roundness and the effects of end closure structure are treated using finite element methods. It is assumed that local fiber or ply waviness is an important factor in the initiation of material failure. An analytical model for the prediction of compression failure of fiber composites, which includes the effects of fiber misalignments, matrix inelasticity, and multiaxial applied stresses is used for material strength calculations. Analytical results are compared to experimental data for a series of glass and carbon fiber reinforced epoxy cylinders subjected to external pressure. Recommendations for pretest characterization and other experimental issues are presented. Implications for material and structural design are discussed.
Comparison of experimentally and theoretically determined radiation characteristics of photosynthetic microorganisms

NASA Astrophysics Data System (ADS)

Kandilian, Razmig; Pruvost, Jérémy; Artu, Arnaud; Lemasson, Camille; Legrand, Jack; Pilon, Laurent

2016-05-01

This paper aims to experimentally and directly validate a recent theoretical method for predicting the radiation characteristics of photosynthetic microorganisms. Such predictions would facilitate light transfer analysis in photobioreactors (PBRs) to control their operation and to maximize their production of biofuel and other high-value products. The state of the art experimental method can be applied to microorganisms of any shape and inherently accounts for their non-spherical and heterogeneous nature. On the other hand, the theoretical method treats the microorganisms as polydisperse homogeneous spheres with some effective optical properties. The absorption index is expressed as the weighted sum of the pigment mass absorption cross-sections and the refractive index is estimated based on the subtractive Kramers-Kronig relationship given an anchor refractive index and wavelength. Here, particular attention was paid to green microalgae Chlamydomonas reinhardtii grown under nitrogen-replete and nitrogen-limited conditions and to Chlorella vulgaris grown under nitrogen-replete conditions. First, relatively good agreement was found between the two methods for determining the mass absorption and scattering cross-sections and the asymmetry factor of both nitrogen-replete and nitrogen-limited C. reinhardtii with the proper anchor point. However, the homogeneous sphere approximation significantly overestimated the absorption cross-section of C. vulgaris cells. The latter were instead modeled as polydisperse coated spheres consisting of an absorbing core containing pigments and a non-absorbing but strongly refracting wall made of sporopollenin. The coated sphere approximation gave good predictions of the experimentally measured integral radiation characteristics of C. vulgaris. In both cases, the homogeneous and coated sphere approximations predicted resonance in the scattering phase function that were not observed experimentally. However, these approximations were sufficiently accurate to predict the fluence rate and local rate of photon absorption in PBRs.
On interfacial properties of tetrahydrofuran: Atomistic and coarse-grained models from molecular dynamics simulation

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

Garrido, J. M.; Algaba, J.; Blas, F. J., E-mail: felipe@uhu.es

2016-04-14

We have determined the interfacial properties of tetrahydrofuran (THF) from direct simulation of the vapor-liquid interface. The molecules are modeled using six different molecular models, three of them based on the united-atom approach and the other three based on a coarse-grained (CG) approach. In the first case, THF is modeled using the transferable parameters potential functions approach proposed by Chandrasekhar and Jorgensen [J. Chem. Phys. 77, 5073 (1982)] and a new parametrization of the TraPPE force fields for cyclic alkanes and ethers [S. J. Keasler et al., J. Phys. Chem. B 115, 11234 (2012)]. In both cases, dispersive and coulombicmore » intermolecular interactions are explicitly taken into account. In the second case, THF is modeled as a single sphere, a diatomic molecule, and a ring formed from three Mie monomers according to the SAFT-γ Mie top-down approach [V. Papaioannou et al., J. Chem. Phys. 140, 054107 (2014)]. Simulations were performed in the molecular dynamics canonical ensemble and the vapor-liquid surface tension is evaluated from the normal and tangential components of the pressure tensor along the simulation box. In addition to the surface tension, we have also obtained density profiles, coexistence densities, critical temperature, density, and pressure, and interfacial thickness as functions of temperature, paying special attention to the comparison between the estimations obtained from different models and literature experimental data. The simulation results obtained from the three CG models as described by the SAFT-γ Mie approach are able to predict accurately the vapor-liquid phase envelope of THF, in excellent agreement with estimations obtained from TraPPE model and experimental data in the whole range of coexistence. However, Chandrasekhar and Jorgensen model presents significant deviations from experimental results. We also compare the predictions for surface tension as obtained from simulation results for all the models with experimental data. The three CG models predict reasonably well (but only qualitatively) the surface tension of THF, as a function of temperature, from the triple point to the critical temperature. On the other hand, only the TraPPE united-atoms models are able to predict accurately the experimental surface tension of the system in the whole temperature range.« less
Towards cleaner combustion engines through groundbreaking detailed chemical kinetic models

PubMed Central

Battin-Leclerc, Frédérique; Blurock, Edward; Bounaceur, Roda; Fournet, René; Glaude, Pierre-Alexandre; Herbinet, Olivier; Sirjean, Baptiste; Warth, V.

2013-01-01

In the context of limiting the environmental impact of transportation, this paper reviews new directions which are being followed in the development of more predictive and more accurate detailed chemical kinetic models for the combustion of fuels. In the first part, the performance of current models, especially in terms of the prediction of pollutant formation, is evaluated. In the next parts, recent methods and ways to improve these models are described. An emphasis is given on the development of detailed models based on elementary reactions, on the production of the related thermochemical and kinetic parameters, and on the experimental techniques available to produce the data necessary to evaluate model predictions under well defined conditions. PMID:21597604
Mathematics as a conduit for translational research in post-traumatic osteoarthritis.

PubMed

Ayati, Bruce P; Kapitanov, Georgi I; Coleman, Mitchell C; Anderson, Donald D; Martin, James A

2017-03-01

Biomathematical models offer a powerful method of clarifying complex temporal interactions and the relationships among multiple variables in a system. We present a coupled in silico biomathematical model of articular cartilage degeneration in response to impact and/or aberrant loading such as would be associated with injury to an articular joint. The model incorporates fundamental biological and mechanical information obtained from explant and small animal studies to predict post-traumatic osteoarthritis (PTOA) progression, with an eye toward eventual application in human patients. In this sense, we refer to the mathematics as a "conduit of translation." The new in silico framework presented in this paper involves a biomathematical model for the cellular and biochemical response to strains computed using finite element analysis. The model predicts qualitative responses presently, utilizing system parameter values largely taken from the literature. To contribute to accurate predictions, models need to be accurately parameterized with values that are based on solid science. We discuss a parameter identification protocol that will enable us to make increasingly accurate predictions of PTOA progression using additional data from smaller scale explant and small animal assays as they become available. By distilling the data from the explant and animal assays into parameters for biomathematical models, mathematics can translate experimental data to clinically relevant knowledge. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:566-572, 2017. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.
Application of Navier-Stokes code PAB3D with kappa-epsilon turbulence model to attached and separated flows

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.; Lakshmanan, B.; Carlson, John R.

1995-01-01

A three-dimensional Navier-Stokes solver was used to determine how accurately computations can predict local and average skin friction coefficients for attached and separated flows for simple experimental geometries. Algebraic and transport equation closures were used to model turbulence. To simulate anisotropic turbulence, the standard two-equation turbulence model was modified by adding nonlinear terms. The effects of both grid density and the turbulence model on the computed flow fields were also investigated and compared with available experimental data for subsonic and supersonic free-stream conditions.
An experimental comparison between the continuum and single jump descriptions of nonactin-mediated potassium transport through black lipid membranes.

PubMed Central

van Dijk, C; de Levie, R

1985-01-01

The continuum and single jump treatments of ion transport through black lipid membranes predict experimentally distinguishable results, even when the same mechanistic assumptions are made and the same potential-distance profile is used. On the basis of steady-state current-voltage curves for nonactin-mediated transport of potassium ions, we find that the continuum model describes the data accurately, whereas the single jump model fails to do so, for all cases investigated in which capacitance measurements indicate that the membrane thickness varies little with applied potential. PMID:3839420
Experimental study and constitutive modeling of the viscoelastic mechanical properties of the human prolapsed vaginal tissue.

PubMed

Peña, Estefania; Calvo, B; Martínez, M A; Martins, P; Mascarenhas, T; Jorge, R M N; Ferreira, A; Doblaré, M

2010-02-01

In this paper, the viscoelastic mechanical properties of vaginal tissue are investigated. Using previous results of the authors on the mechanical properties of biological soft tissues and newly experimental data from uniaxial tension tests, a new model for the viscoelastic mechanical properties of the human vaginal tissue is proposed. The structural model seems to be sufficiently accurate to guarantee its application to prediction of reliable stress distributions, and is suitable for finite element computations. The obtained results may be helpful in the design of surgical procedures with autologous tissue or prostheses.

An investigation of thermal comfort inside an automobile during the heating period.

PubMed

Kaynakli, Omer; Kilic, Muhsin

2005-05-01

This paper describes a combined theoretical and experimental study of thermal comfort during the heating period inside an automobile. To investigate the effects of thermal conditions on the human physiology and thermal comfort during the heating period, temperature, humidity and air velocity were measured at a number of points inside the automobile, so thermal conditions were accurately determined. The human body was divided into 16 sedentary segments, and the change of temperature was observed both experimentally and theoretically. During transient conditions of the heating period, heat and mass transfer between the human body and the interior environment of an automobile were simulated by a computational model, and predictions were compared with the measured data. It is shown that there is a good agreement between the model predictions and experimental results. By means of the present model, the effects of the fast transient conditions of the heating period on the sensible and latent heat transfer from the body, body segments skin temperatures and thermal sensation were investigated in detail.
Solubility of Carbon Dioxide in Secondary Butyl Alcohol at High Pressures: Experimental and Modeling with CPA.

PubMed

Raeissi, Sona; Haghbakhsh, Reza; Florusse, Louw J; Peters, Cor J

Mixtures of carbon dioxide and secondary butyl alcohol at high pressures are interesting for a range of industrial applications. Therefore, it is important to have trustworthy experimental data on the high-pressure phase behavior of this mixture over a wide range of temperatures. In addition, an accurate thermodynamic model is necessary for the optimal design and operation of processes. In this study, bubble points of binary mixtures of CO 2 + secondary butyl alcohol were measured using a synthetic method. Measurements covered a CO 2 molar concentration range of (0.10-0.57) % and temperatures from (293 to 370) K, with pressures reaching up to 11 MPa. The experimental data were modelled by the cubic plus association (CPA) equation of state (EoS), as well as the more simple Soave-Redlich-Kwong (SRK) EoS. Predictive and correlative modes were considered for both models. In the predictive mode, the CPA performs better than the SRK because it also considers associations.
Experimental investigation of springback in air bending process

NASA Astrophysics Data System (ADS)

Alhammadi, Aysha; Rafique, Hafsa; Alkaabi, Meera; Abu Qudeiri, Jaber

2018-03-01

Bending processes is one of the important processes in sheet metal forming. One of the challenge that faces the air bending process is springback, which happens due to the elastic recovery during unloading stage. An accurate analysis of springback during the bending process is crucial to achieve a required bend angle. This paper will investigate the springback experimentally by changing many parameters such as tested material, die opening, thickness, etc. and finding its effect on the value of springback. Additionally, the paper will investigate the effect of loading time at the end of loading stage on the springback by proposing a multistage bending technique (MBT). In MBT, the loading will stop during loading stage just before the end of this stage and it will restart again shortly after. In this study, three sheet metals with different thickness will be examined, namely stainless steel, aluminium and brass. Artificial neural network (ANN) will be utilized to develop a prediction model to predict springback based on the experimental results.
Model-based redesign of global transcription regulation

PubMed Central

Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso

2009-01-01

Synthetic biology aims to the design or redesign of biological systems. In particular, one possible goal could be the rewiring of the transcription regulation network by exchanging the endogenous promoters. To achieve this objective, we have adapted current methods to the inference of a model based on ordinary differential equations that is able to predict the network response after a major change in its topology. Our procedure utilizes microarray data for training. We have experimentally validated our inferred global regulatory model in Escherichia coli by predicting transcriptomic profiles under new perturbations. We have also tested our methodology in silico by providing accurate predictions of the underlying networks from expression data generated with artificial genomes. In addition, we have shown the predictive power of our methodology by obtaining the gene profile in experimental redesigns of the E. coli genome, where rewiring the transcriptional network by means of knockouts of master regulators or by upregulating transcription factors controlled by different promoters. Our approach is compatible with most network inference methods, allowing to explore computationally future genome-wide redesign experiments in synthetic biology. PMID:19188257
Simulation of CO2 Solubility in Polystyrene-b-Polybutadieneb-Polystyrene (SEBS) by artificial intelligence network (ANN) method

NASA Astrophysics Data System (ADS)

Sharudin, R. W.; AbdulBari Ali, S.; Zulkarnain, M.; Shukri, M. A.

2018-05-01

This study reports on the integration of Artificial Neural Network (ANNs) with experimental data in predicting the solubility of carbon dioxide (CO2) blowing agent in SEBS by generating highest possible value for Regression coefficient (R2). Basically, foaming of thermoplastic elastomer with CO2 is highly affected by the CO2 solubility. The ability of ANN in predicting interpolated data of CO2 solubility was investigated by comparing training results via different method of network training. Regards to the final prediction result for CO2 solubility by ANN, the prediction trend (output generate) was corroborated with the experimental results. The obtained result of different method of training showed the trend of output generated by Gradient Descent with Momentum & Adaptive LR (traingdx) required longer training time and required more accurate input to produce better output with final Regression Value of 0.88. However, it goes vice versa with Levenberg-Marquardt (trainlm) technique as it produced better output in quick detention time with final Regression Value of 0.91.
Coupled molecular dynamics and continuum electrostatic method to compute the ionization pKa's of proteins as a function of pH. Test on a large set of proteins.

PubMed

Vorobjev, Yury N; Scheraga, Harold A; Vila, Jorge A

2018-02-01

A computational method, to predict the pKa values of the ionizable residues Asp, Glu, His, Tyr, and Lys of proteins, is presented here. Calculation of the electrostatic free-energy of the proteins is based on an efficient version of a continuum dielectric electrostatic model. The conformational flexibility of the protein is taken into account by carrying out molecular dynamics simulations of 10 ns in implicit water. The accuracy of the proposed method of calculation of pKa values is estimated from a test set of experimental pKa data for 297 ionizable residues from 34 proteins. The pKa-prediction test shows that, on average, 57, 86, and 95% of all predictions have an error lower than 0.5, 1.0, and 1.5 pKa units, respectively. This work contributes to our general understanding of the importance of protein flexibility for an accurate computation of pKa, providing critical insight about the significance of the multiple neutral states of acid and histidine residues for pKa-prediction, and may spur significant progress in our effort to develop a fast and accurate electrostatic-based method for pKa-predictions of proteins as a function of pH.
Flowfield Comparisons from Three Navier-Stokes Solvers for an Axisymmetric Separate Flow Jet

NASA Technical Reports Server (NTRS)

Koch, L. Danielle; Bridges, James; Khavaran, Abbas

2002-01-01

To meet new noise reduction goals, many concepts to enhance mixing in the exhaust jets of turbofan engines are being studied. Accurate steady state flowfield predictions from state-of-the-art computational fluid dynamics (CFD) solvers are needed as input to the latest noise prediction codes. The main intent of this paper was to ascertain that similar Navier-Stokes solvers run at different sites would yield comparable results for an axisymmetric two-stream nozzle case. Predictions from the WIND and the NPARC codes are compared to previously reported experimental data and results from the CRAFT Navier-Stokes solver. Similar k-epsilon turbulence models were employed in each solver, and identical computational grids were used. Agreement between experimental data and predictions from each code was generally good for mean values. All three codes underpredict the maximum value of turbulent kinetic energy. The predicted locations of the maximum turbulent kinetic energy were farther downstream than seen in the data. A grid study was conducted using the WIND code, and comments about convergence criteria and grid requirements for CFD solutions to be used as input for noise prediction computations are given. Additionally, noise predictions from the MGBK code, using the CFD results from the CRAFT code, NPARC, and WIND as input are compared to data.
Referential Choice: Predictability and Its Limits

PubMed Central

Kibrik, Andrej A.; Khudyakova, Mariya V.; Dobrov, Grigory B.; Linnik, Anastasia; Zalmanov, Dmitrij A.

2016-01-01

We report a study of referential choice in discourse production, understood as the choice between various types of referential devices, such as pronouns and full noun phrases. Our goal is to predict referential choice, and to explore to what extent such prediction is possible. Our approach to referential choice includes a cognitively informed theoretical component, corpus analysis, machine learning methods and experimentation with human participants. Machine learning algorithms make use of 25 factors, including referent’s properties (such as animacy and protagonism), the distance between a referential expression and its antecedent, the antecedent’s syntactic role, and so on. Having found the predictions of our algorithm to coincide with the original almost 90% of the time, we hypothesized that fully accurate prediction is not possible because, in many situations, more than one referential option is available. This hypothesis was supported by an experimental study, in which participants answered questions about either the original text in the corpus, or about a text modified in accordance with the algorithm’s prediction. Proportions of correct answers to these questions, as well as participants’ rating of the questions’ difficulty, suggested that divergences between the algorithm’s prediction and the original referential device in the corpus occur overwhelmingly in situations where the referential choice is not categorical. PMID:27721800
Puzzle of magnetic moments of Ni clusters revisited using quantum Monte Carlo method.

PubMed

Lee, Hung-Wen; Chang, Chun-Ming; Hsing, Cheng-Rong

2017-02-28

The puzzle of the magnetic moments of small nickel clusters arises from the discrepancy between values predicted using density functional theory (DFT) and experimental measurements. Traditional DFT approaches underestimate the magnetic moments of nickel clusters. Two fundamental problems are associated with this puzzle, namely, calculating the exchange-correlation interaction accurately and determining the global minimum structures of the clusters. Theoretically, the two problems can be solved using quantum Monte Carlo (QMC) calculations and the ab initio random structure searching (AIRSS) method correspondingly. Therefore, we combined the fixed-moment AIRSS and QMC methods to investigate the magnetic properties of Ni n (n = 5-9) clusters. The spin moments of the diffusion Monte Carlo (DMC) ground states are higher than those of the Perdew-Burke-Ernzerhof ground states and, in the case of Ni 8-9 , two new ground-state structures have been discovered using the DMC calculations. The predicted results are closer to the experimental findings, unlike the results predicted in previous standard DFT studies.
A finite difference model used to predict the consolidation of a ceramic waste form produced from the electrometallurgical treatment of spent nuclear fuel.

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

Bateman, K. J.; Capson, D. D.

2004-03-29

Argonne National Laboratory (ANL) has developed a process to immobilize waste salt containing fission products, uranium, and transuranic elements as chlorides in a glass-bonded ceramic waste form. This salt was generated in the electrorefining operation used in the electrometallurgical treatment of spent Experimental Breeder Reactor-II (EBR-II) fuel. The ceramic waste process culminates with an elevated temperature operation. The processing conditions used by the furnace, for demonstration scale and production scale operations, are to be developed at Argonne National Laboratory-West (ANL-West). To assist in selecting the processing conditions of the furnace and to reduce the number of costly experiments, a finitemore » difference model was developed to predict the consolidation of the ceramic waste. The model accurately predicted the heating as well as the bulk density of the ceramic waste form. The methodology used to develop the computer model and a comparison of the analysis to experimental data is presented.« less
CFD Simulation and Experimental Validation of Fluid Flow and Particle Transport in a Model of Alveolated Airways

PubMed Central

Ma, Baoshun; Ruwet, Vincent; Corieri, Patricia; Theunissen, Raf; Riethmuller, Michel; Darquenne, Chantal

2009-01-01

Accurate modeling of air flow and aerosol transport in the alveolated airways is essential for quantitative predictions of pulmonary aerosol deposition. However, experimental validation of such modeling studies has been scarce. The objective of this study is to validate CFD predictions of flow field and particle trajectory with experiments within a scaled-up model of alveolated airways. Steady flow (Re = 0.13) of silicone oil was captured by particle image velocimetry (PIV), and the trajectories of 0.5 mm and 1.2 mm spherical iron beads (representing 0.7 to 14.6 μm aerosol in vivo) were obtained by particle tracking velocimetry (PTV). At twelve selected cross sections, the velocity profiles obtained by CFD matched well with those by PIV (within 1.7% on average). The CFD predicted trajectories also matched well with PTV experiments. These results showed that air flow and aerosol transport in models of human alveolated airways can be simulated by CFD techniques with reasonable accuracy. PMID:20161301
CFD Simulation and Experimental Validation of Fluid Flow and Particle Transport in a Model of Alveolated Airways.

PubMed

Ma, Baoshun; Ruwet, Vincent; Corieri, Patricia; Theunissen, Raf; Riethmuller, Michel; Darquenne, Chantal

2009-05-01

Accurate modeling of air flow and aerosol transport in the alveolated airways is essential for quantitative predictions of pulmonary aerosol deposition. However, experimental validation of such modeling studies has been scarce. The objective of this study is to validate CFD predictions of flow field and particle trajectory with experiments within a scaled-up model of alveolated airways. Steady flow (Re = 0.13) of silicone oil was captured by particle image velocimetry (PIV), and the trajectories of 0.5 mm and 1.2 mm spherical iron beads (representing 0.7 to 14.6 mum aerosol in vivo) were obtained by particle tracking velocimetry (PTV). At twelve selected cross sections, the velocity profiles obtained by CFD matched well with those by PIV (within 1.7% on average). The CFD predicted trajectories also matched well with PTV experiments. These results showed that air flow and aerosol transport in models of human alveolated airways can be simulated by CFD techniques with reasonable accuracy.
Electromagnetic modelling of Raman enhancement from nanoscale substrates: a route to estimation of the magnitude of the chemical enhancement mechanism in SERS.

PubMed

Brown, Richard J C; Wang, Jian; Tantra, Ratna; Yardley, Rachel E; Milton, Martin J T

2006-01-01

Despite widespread use for more than two decades, the SERS phenomenon has defied accurate physical and chemical explanation. The relative contributions from electronic and chemical mechanisms are difficult to quantify and are often not reproduced under nominally similar experimental conditions. This work has used electromagnetic modelling to predict the Raman enhancement expected from three configurations: metal nanoparticles, structured metal surfaces, and sharp metal tips interacting with metal surfaces. In each case, parameters such as artefact size, artefact separation and incident radiation wavelength have been varied and the resulting electromagnetic field modelled. This has yielded an electromagnetic description of these configurations with predictions of the maximum expected Raman enhancement, and hence a prediction of the optimum substrate configuration for the SERS process. When combined with experimental observations of the dependence of Raman enhancement with changing ionic strength, the modelling results have allowed a novel estimate of the size of the chemical enhancement mechanism to be produced.
Neural Network Based Models for Fusion Applications

NASA Astrophysics Data System (ADS)

Meneghini, Orso; Tema Biwole, Arsene; Luda, Teobaldo; Zywicki, Bailey; Rea, Cristina; Smith, Sterling; Snyder, Phil; Belli, Emily; Staebler, Gary; Canty, Jeff

2017-10-01

Whole device modeling, engineering design, experimental planning and control applications demand models that are simultaneously physically accurate and fast. This poster reports on the ongoing effort towards the development and validation of a series of models that leverage neural-Ânetwork (NN) multidimensional regression techniques to accelerate some of the most mission critical first principle models for the fusion community, such as: the EPED workflow for prediction of the H-Mode and Super H-Mode pedestal structure the TGLF and NEO models for the prediction of the turbulent and neoclassical particle, energy and momentum fluxes; and the NEO model for the drift-kinetic solution of the bootstrap current. We also applied NNs on DIII-D experimental data for disruption prediction and quantifying the effect of RMPs on the pedestal and ELMs. All of these projects were supported by the infrastructure provided by the OMFIT integrated modeling framework. Work supported by US DOE under DE-SC0012656, DE-FG02-95ER54309, DE-FC02-04ER54698.
Numerical simulation of jet aerodynamics using the three-dimensional Navier-Stokes code PAB3D

NASA Technical Reports Server (NTRS)

Pao, S. Paul; Abdol-Hamid, Khaled S.

1996-01-01

This report presents a unified method for subsonic and supersonic jet analysis using the three-dimensional Navier-Stokes code PAB3D. The Navier-Stokes code was used to obtain solutions for axisymmetric jets with on-design operating conditions at Mach numbers ranging from 0.6 to 3.0, supersonic jets containing weak shocks and Mach disks, and supersonic jets with nonaxisymmetric nozzle exit geometries. This report discusses computational methods, code implementation, computed results, and comparisons with available experimental data. Very good agreement is shown between the numerical solutions and available experimental data over a wide range of operating conditions. The Navier-Stokes method using the standard Jones-Launder two-equation kappa-epsilon turbulence model can accurately predict jet flow, and such predictions are made without any modification to the published constants for the turbulence model.
Analysis of metal transfer in gas metal arc welding

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

Kim, Y.S.; Eager, T.W.

1993-06-01

Droplet sizes produced in GMAW are predicted using both the static force balance theory and the pinch instability theory as a function of welding current, and the results are compared with experimental measurements. The causes for the deviation of predicted droplet size from measured size are discussed with suggestions for modification of the theories in order to more accurately model metal transfer in GMAW. The mechanism of repelled metal transfer is also discussed. The transition of metal transfer mode has been considered as a critical phenomenon which changes dramatically over a narrow range of welding current. This transition has beenmore » investigated experimentally using high-speed videography which shows that the transition is much more gradual than is generally believed. The mechanism of the transition is discussed using a modified static force balance theory.« less
Size Dependent Mechanical Properties of Monolayer Densely Arranged Polystyrene Nanospheres.

PubMed

Huang, Peng; Zhang, Lijing; Yan, Qingfeng; Guo, Dan; Xie, Guoxin

2016-12-13

In contrast to macroscopic materials, the mechanical properties of polymer nanospheres show fascinating scientific and application values. However, the experimental measurements of individual nanospheres and quantitative analysis of theoretical mechanisms remain less well performed and understood. We provide a highly efficient and accurate method with monolayer densely arranged honeycomb polystyrene (PS) nanospheres for the quantitatively mechanical characterization of individual nanospheres on the basis of atomic force microscopy (AFM) nanoindentation. The efficiency is improved by 1-2 orders, and the accuracy is also enhanced almost by half-order. The elastic modulus measured in the experiments increases with decreasing radius to the smallest nanospheres (25-35 nm in radius). A core-shell model is introduced to predict the size dependent elasticity of PS nanospheres, and the theoretical prediction agrees reasonably well with the experimental results and also shows a peak modulus value.
Predicting the effects of magnesium oxide nanoparticles and temperature on the thermal conductivity of water using artificial neural network and experimental data

NASA Astrophysics Data System (ADS)

Afrand, Masoud; Hemmat Esfe, Mohammad; Abedini, Ehsan; Teimouri, Hamid

2017-03-01

The current paper first presents an empirical correlation based on experimental results for estimating thermal conductivity enhancement of MgO-water nanofluid using curve fitting method. Then, artificial neural networks (ANNs) with various numbers of neurons have been assessed by considering temperature and MgO volume fraction as the inputs variables and thermal conductivity enhancement as the output variable to select the most appropriate and optimized network. Results indicated that the network with 7 neurons had minimum error. Eventually, the output of artificial neural network was compared with the results of the proposed empirical correlation and those of the experiments. Comparisons revealed that ANN modeling was more accurate than curve-fitting method in the predicting the thermal conductivity enhancement of the nanofluid.
Bubbles and denaturation in DNA

NASA Astrophysics Data System (ADS)

van Erp, T. S.; Cuesta-López, S.; Peyrard, M.

2006-08-01

The local opening of DNA is an intriguing phenomenon from a statistical-physics point of view, but is also essential for its biological function. For instance, the transcription and replication of our genetic code cannot take place without the unwinding of the DNA double helix. Although these biological processes are driven by proteins, there might well be a relation between these biological openings and the spontaneous bubble formation due to thermal fluctuations. Mesoscopic models, like the Peyrard-Bishop-Dauxois (PBD) model, have fairly accurately reproduced some experimental denaturation curves and the sharp phase transition in the thermodynamic limit. It is, hence, tempting to see whether these models could be used to predict the biological activity of DNA. In a previous study, we introduced a method that allows to obtain very accurate results on this subject, which showed that some previous claims in this direction, based on molecular-dynamics studies, were premature. This could either imply that the present PBD model should be improved or that biological activity can only be predicted in a more complex framework that involves interactions with proteins and super helical stresses. In this article, we give a detailed description of the statistical method introduced before. Moreover, for several DNA sequences, we give a thorough analysis of the bubble-statistics as a function of position and bubble size and the so-called l-denaturation curves that can be measured experimentally. These show that some important experimental observations are missing in the present model. We discuss how the present model could be improved.
Preliminary Analysis of Fluctuations in the Received Uplink-Beacon-Power Data Obtained From the GOLD Experiments

NASA Technical Reports Server (NTRS)

Jeganathan, M.; Wilson, K. E.; Lesh, J. R.

1996-01-01

Uplink data from recent free-space optical communication experiments carried out between the Table Mountain Facility and the Japanese Engineering Test Satellite are used to study fluctuations caused by beam propagation through the atmosphere. The influence of atmospheric scintillation, beam wander and jitter, and multiple uplink beams on the statistics of power received by the satellite is analyzed and compared to experimental data. Preliminary analysis indicates the received signal obeys an approximate lognormal distribution, as predicted by the weak-turbulence model, but further characterization of other sources of fluctuations is necessary for accurate link predictions.

Predicting charmonium and bottomonium spectra with a quark harmonic oscillator

NASA Technical Reports Server (NTRS)

Norbury, J. W.; Badavi, F. F.; Townsend, L. W.

1986-01-01

The nonrelativistic quark model is applied to heavy (nonrelativistic) meson (two-body) systems to obtain sufficiently accurate predictions of the spin-averaged mass levels of the charmonium and bottomonium spectra as an example of the three-dimensional harmonic oscillator. The present calculations do not include any spin dependence, but rather, mass values are averaged for different spins. Results for a charmed quark mass value of 1500 MeV/c-squared show that the simple harmonic oscillator model provides good agreement with experimental values for 3P states, and adequate agreement for the 3S1 states.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Livescu, Veronica; Bronkhorst, Curt Allan; Vander Wiel, Scott Alan

Many challenges exist with regard to understanding and representing complex physical processes involved with ductile damage and failure in polycrystalline metallic materials. Currently, the ability to accurately predict the macroscale ductile damage and failure response of metallic materials is lacking. Research at Los Alamos National Laboratory (LANL) is aimed at building a coupled experimental and computational methodology that supports the development of predictive damage capabilities by: capturing real distributions of microstructural features from real material and implementing them as digitally generated microstructures in damage model development; and, distilling structure-property information to link microstructural details to damage evolution under a multitudemore » of loading states.« less
Preliminary analysis of fluctuations in the received uplink-beacon-power data obtained from the GOLD experiments

NASA Technical Reports Server (NTRS)

Jeganathan, M.; Wilson, K. E.; Lesh, J. R.

1996-01-01

Uplink data from recent free-space optical communication experiments carried out between the Table Mountain Facility and the Japanese Engineering Test Satellite are used to study fluctuations caused by beam propagation through the atmosphere. The influence of atmospheric scintillation, beam wander and jitter, and multiple uplink beams on the statistics of power received by the satellite is analyzed and compared to experimental data. Preliminary analysis indicates the received signal obeys an approximate lognormal distribution, as predicted by the weak-turbulence model, but further characterization of other sources of fluctuations is necessary for accurate link predictions.
Cellular dosimetry of (111)In using monte carlo N-particle computer code: comparison with analytic methods and correlation with in vitro cytotoxicity.

PubMed

Cai, Zhongli; Pignol, Jean-Philippe; Chan, Conrad; Reilly, Raymond M

2010-03-01

Our objective was to compare Monte Carlo N-particle (MCNP) self- and cross-doses from (111)In to the nucleus of breast cancer cells with doses calculated by reported analytic methods (Goddu et al. and Farragi et al.). A further objective was to determine whether the MCNP-predicted surviving fraction (SF) of breast cancer cells exposed in vitro to (111)In-labeled diethylenetriaminepentaacetic acid human epidermal growth factor ((111)In-DTPA-hEGF) could accurately predict the experimentally determined values. MCNP was used to simulate the transport of electrons emitted by (111)In from the cell surface, cytoplasm, or nucleus. The doses to the nucleus per decay (S values) were calculated for single cells, closely packed monolayer cells, or cell clusters. The cell and nucleus dimensions of 6 breast cancer cell lines were measured, and cell line-specific S values were calculated. For self-doses, MCNP S values of nucleus to nucleus agreed very well with those of Goddu et al. (ratio of S values using analytic methods vs. MCNP = 0.962-0.995) and Faraggi et al. (ratio = 1.011-1.024). MCNP S values of cytoplasm and cell surface to nucleus compared fairly well with the reported values (ratio = 0.662-1.534 for Goddu et al.; 0.944-1.129 for Faraggi et al.). For cross doses, the S values to the nucleus were independent of (111)In subcellular distribution but increased with cluster size. S values for monolayer cells were significantly different from those of single cells and cell clusters. The MCNP-predicted SF for monolayer MDA-MB-468, MDA-MB-231, and MCF-7 cells agreed with the experimental data (relative error of 3.1%, -1.0%, and 1.7%). The single-cell and cell cluster models were less accurate in predicting the SF. For MDA-MB-468 cells, relative error was 8.1% using the single-cell model and -54% to -67% using the cell cluster model. Individual cell-line dimensions had large effects on S values and were needed to estimate doses and SF accurately. MCNP simulation compared well with the reported analytic methods in the calculation of subcellular S values for single cells and cell clusters. Application of a monolayer model was most accurate in predicting the SF of breast cancer cells exposed in vitro to (111)In-DTPA-hEGF.
Evaluation of CFD Turbulent Heating Prediction Techniques and Comparison With Hypersonic Experimental Data

NASA Technical Reports Server (NTRS)

Dilley, Arthur D.; McClinton, Charles R. (Technical Monitor)

2001-01-01

Results from a study to assess the accuracy of turbulent heating and skin friction prediction techniques for hypersonic applications are presented. The study uses the original and a modified Baldwin-Lomax turbulence model with a space marching code. Grid converged turbulent predictions using the wall damping formulation (original model) and local damping formulation (modified model) are compared with experimental data for several flat plates. The wall damping and local damping results are similar for hot wall conditions, but differ significantly for cold walls, i.e., T(sub w) / T(sub t) < 0.3, with the wall damping heating and skin friction 10-30% above the local damping results. Furthermore, the local damping predictions have reasonable or good agreement with the experimental heating data for all cases. The impact of the two formulations on the van Driest damping function and the turbulent eddy viscosity distribution for a cold wall case indicate the importance of including temperature gradient effects. Grid requirements for accurate turbulent heating predictions are also studied. These results indicate that a cell Reynolds number of 1 is required for grid converged heating predictions, but coarser grids with a y(sup +) less than 2 are adequate for design of hypersonic vehicles. Based on the results of this study, it is recommended that the local damping formulation be used with the Baldwin-Lomax and Cebeci-Smith turbulence models in design and analysis of Hyper-X and future hypersonic vehicles.
Identifying and Tracking Pedestrians Based on Sensor Fusion and Motion Stability Predictions

PubMed Central

Musleh, Basam; García, Fernando; Otamendi, Javier; Armingol, José Mª; de la Escalera, Arturo

2010-01-01

The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle. PMID:22163639
Identifying and tracking pedestrians based on sensor fusion and motion stability predictions.

PubMed

Musleh, Basam; García, Fernando; Otamendi, Javier; Armingol, José Maria; de la Escalera, Arturo

2010-01-01

The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle.
Octanol-Water Partition Coefficient from 3D-RISM-KH Molecular Theory of Solvation with Partial Molar Volume Correction.

PubMed

Huang, WenJuan; Blinov, Nikolay; Kovalenko, Andriy

2015-04-30

The octanol-water partition coefficient is an important physical-chemical characteristic widely used to describe hydrophobic/hydrophilic properties of chemical compounds. The partition coefficient is related to the transfer free energy of a compound from water to octanol. Here, we introduce a new protocol for prediction of the partition coefficient based on the statistical-mechanical, 3D-RISM-KH molecular theory of solvation. It was shown recently that with the compound-solvent correlation functions obtained from the 3D-RISM-KH molecular theory of solvation, the free energy functional supplemented with the correction linearly related to the partial molar volume obtained from the Kirkwood-Buff/3D-RISM theory, also called the "universal correction" (UC), provides accurate prediction of the hydration free energy of small compounds, compared to explicit solvent molecular dynamics [ Palmer , D. S. ; J. Phys.: Condens. Matter 2010 , 22 , 492101 ]. Here we report that with the UC reparametrized accordingly this theory also provides an excellent agreement with the experimental data for the solvation free energy in nonpolar solvent (1-octanol) and so accurately predicts the octanol-water partition coefficient. The performance of the Kovalenko-Hirata (KH) and Gaussian fluctuation (GF) functionals of the solvation free energy, with and without UC, is tested on a large library of small compounds with diverse functional groups. The best agreement with the experimental data for octanol-water partition coefficients is obtained with the KH-UC solvation free energy functional.
Parameter estimation for lithium ion batteries

NASA Astrophysics Data System (ADS)

Santhanagopalan, Shriram

With an increase in the demand for lithium based batteries at the rate of about 7% per year, the amount of effort put into improving the performance of these batteries from both experimental and theoretical perspectives is increasing. There exist a number of mathematical models ranging from simple empirical models to complicated physics-based models to describe the processes leading to failure of these cells. The literature is also rife with experimental studies that characterize the various properties of the system in an attempt to improve the performance of lithium ion cells. However, very little has been done to quantify the experimental observations and relate these results to the existing mathematical models. In fact, the best of the physics based models in the literature show as much as 20% discrepancy when compared to experimental data. The reasons for such a big difference include, but are not limited to, numerical complexities involved in extracting parameters from experimental data and inconsistencies in interpreting directly measured values for the parameters. In this work, an attempt has been made to implement simplified models to extract parameter values that accurately characterize the performance of lithium ion cells. The validity of these models under a variety of experimental conditions is verified using a model discrimination procedure. Transport and kinetic properties are estimated using a non-linear estimation procedure. The initial state of charge inside each electrode is also maintained as an unknown parameter, since this value plays a significant role in accurately matching experimental charge/discharge curves with model predictions and is not readily known from experimental data. The second part of the dissertation focuses on parameters that change rapidly with time. For example, in the case of lithium ion batteries used in Hybrid Electric Vehicle (HEV) applications, the prediction of the State of Charge (SOC) of the cell under a variety of road conditions is important. An algorithm to predict the SOC in time intervals as small as 5 ms is of critical demand. In such cases, the conventional non-linear estimation procedure is not time-effective. There exist methodologies in the literature, such as those based on fuzzy logic; however, these techniques require a lot of computational storage space. Consequently, it is not possible to implement such techniques on a micro-chip for integration as a part of a real-time device. The Extended Kalman Filter (EKF) based approach presented in this work is a first step towards developing an efficient method to predict online, the State of Charge of a lithium ion cell based on an electrochemical model. The final part of the dissertation focuses on incorporating uncertainty in parameter values into electrochemical models using the polynomial chaos theory (PCT).
Enthalpies of Formation of Hydrazine and Its Derivatives.

PubMed

Dorofeeva, Olga V; Ryzhova, Oxana N; Suchkova, Taisiya A

2017-07-20

Enthalpies of formation, Δ f H 298 ° , in both the gas and condensed phase, and enthalpies of sublimation or vaporization have been estimated for hydrazine, NH 2 NH 2 , and its 36 various derivatives using quantum chemical calculations. The composite G4 method has been used along with isodesmic reaction schemes to derive a set of self-consistent high-accuracy gas-phase enthalpies of formation. To estimate the enthalpies of sublimation and vaporization with reasonable accuracy (5-20 kJ/mol), the method of molecular electrostatic potential (MEP) has been used. The value of Δ f H 298 ° (NH 2 NH 2 ,g) = 97.0 ± 3.0 kJ/mol was determined from 75 isogyric reactions involving about 50 reference species; for most of these species, the accurate Δ f H 298 ° (g) values are available in Active Thermochemical Tables (ATcT). The calculated value is in excellent agreement with the reported results of the most accurate models based on coupled cluster theory (97.3 kJ/mol, the average of six calculations). Thus, the difference between the values predicted by high-level theoretical calculations and the experimental value of Δ f H 298 ° (NH 2 NH 2 ,g) = 95.55 ± 0.19 kJ/mol recommended in the ATcT and other comprehensive reference sources is sufficiently large and requires further investigation. Different hydrazine derivatives have been also considered in this work. For some of them, both the enthalpy of formation in the condensed phase and the enthalpy of sublimation or vaporization are available; for other compounds, experimental data for only one of these properties exist. Evidence of accuracy of experimental data for the first group of compounds was provided by the agreement with theoretical Δ f H 298 ° (g) value. The unknown property for the second group of compounds was predicted using the MEP model. This paper presents a systematic comparison of experimentally determined enthalpies of formation and enthalpies of sublimation or vaporization with the results of calculations. Because of relatively large uncertainty in the estimated enthalpies of sublimation, it was not always possible to evaluate the accuracy of the experimental values; however, this model allowed us to detect large errors in the experimental data, as in the case of 5,5'-hydrazinebistetrazole. The enthalpies of formation and enthalpies of sublimation or vaporization have been predicted for the first time for ten hydrazine derivatives with no experimental data. A recommended set of self-consistent experimental and calculated gas-phase enthalpies of formation of hydrazine derivatives can be used as reference Δ f H 298 ° (g) values to predict the enthalpies of formation of various hydrazines by means of isodesmic reactions.
Early prediction of student goals and affect in narrative-centered learning environments

NASA Astrophysics Data System (ADS)

Lee, Sunyoung

Recent years have seen a growing recognition of the role of goal and affect recognition in intelligent tutoring systems. Goal recognition is the task of inferring users' goals from a sequence of observations of their actions. Because of the uncertainty inherent in every facet of human computer interaction, goal recognition is challenging, particularly in contexts in which users can perform many actions in any order, as is the case with intelligent tutoring systems. Affect recognition is the task of identifying the emotional state of a user from a variety of physical cues, which are produced in response to affective changes in the individual. Accurately recognizing student goals and affect states could contribute to more effective and motivating interactions in intelligent tutoring systems. By exploiting knowledge of student goals and affect states, intelligent tutoring systems can dynamically modify their behavior to better support individual students. To create effective interactions in intelligent tutoring systems, goal and affect recognition models should satisfy two key requirements. First, because incorrectly predicted goals and affect states could significantly diminish the effectiveness of interactive systems, goal and affect recognition models should provide accurate predictions of user goals and affect states. When observations of users' activities become available, recognizers should make accurate early" predictions. Second, goal and affect recognition models should be highly efficient so they can operate in real time. To address key issues, we present an inductive approach to recognizing student goals and affect states in intelligent tutoring systems by learning goals and affect recognition models. Our work focuses on goal and affect recognition in an important new class of intelligent tutoring systems, narrative-centered learning environments. We report the results of empirical studies of induced recognition models from observations of students' interactions in narrative-centered learning environments. Experimental results suggest that induced models can make accurate early predictions of student goals and affect states, and they are sufficiently efficient to meet the real-time performance requirements of interactive learning environments.
A Performance Weighted Collaborative Filtering algorithm for personalized radiology education.

PubMed

Lin, Hongli; Yang, Xuedong; Wang, Weisheng; Luo, Jiawei

2014-10-01

Devising an accurate prediction algorithm that can predict the difficulty level of cases for individuals and then selects suitable cases for them is essential to the development of a personalized training system. In this paper, we propose a novel approach, called Performance Weighted Collaborative Filtering (PWCF), to predict the difficulty level of each case for individuals. The main idea of PWCF is to assign an optimal weight to each rating used for predicting the difficulty level of a target case for a trainee, rather than using an equal weight for all ratings as in traditional collaborative filtering methods. The assigned weight is a function of the performance level of the trainee at which the rating was made. The PWCF method and the traditional method are compared using two datasets. The experimental data are then evaluated by means of the MAE metric. Our experimental results show that PWCF outperforms the traditional methods by 8.12% and 17.05%, respectively, over the two datasets, in terms of prediction precision. This suggests that PWCF is a viable method for the development of personalized training systems in radiology education. Copyright © 2014. Published by Elsevier Inc.
Applicability of a panel method, which includes nonlinear effects, to a forward-swept-wing aircraft

NASA Technical Reports Server (NTRS)

Ross, J. C.

1984-01-01

The ability of a lower order panel method VSAERO, to accurately predict the lift and pitching moment of a complete forward-swept-wing/canard configuration was investigated. The program can simulate nonlinear effects including boundary-layer displacement thickness, wake roll up, and to a limited extent, separated wakes. The predictions were compared with experimental data obtained using a small-scale model in the 7- by 10- Foot Wind Tunnel at NASA Ames Research Center. For the particular configuration under investigation, wake roll up had only a small effect on the force and moment predictions. The effect of the displacement thickness modeling was to reduce the lift curve slope slightly, thus bringing the predicted lift into good agreement with the measured value. Pitching moment predictions were also improved by the boundary-layer simulation. The separation modeling was found to be sensitive to user inputs, but appears to give a reasonable representation of a separated wake. In general, the nonlinear capabilities of the code were found to improve the agreement with experimental data. The usefullness of the code would be enhanced by improving the reliability of the separated wake modeling and by the addition of a leading edge separation model.
The Effect of Electronic Structure on the Phases Present in High Entropy Alloys

PubMed Central

Leong, Zhaoyuan; Wróbel, Jan S.; Dudarev, Sergei L.; Goodall, Russell; Todd, Iain; Nguyen-Manh, Duc

2017-01-01

Multicomponent systems, termed High Entropy Alloys (HEAs), with predominantly single solid solution phases are a current area of focus in alloy development. Although different empirical rules have been introduced to understand phase formation and determine what the dominant phases may be in these systems, experimental investigation has revealed that in many cases their structure is not a single solid solution phase, and that the rules may not accurately distinguish the stability of the phase boundaries. Here, a combined modelling and experimental approach that looks into the electronic structure is proposed to improve accuracy of the predictions of the majority phase. To do this, the Rigid Band model is generalised for magnetic systems in prediction of the majority phase most likely to be found. Good agreement is found when the predictions are confronted with data from experiments, including a new magnetic HEA system (CoFeNiV). This also includes predicting the structural transition with varying levels of constituent elements, as a function of the valence electron concentration, n, obtained from the integrated spin-polarised density of states. This method is suitable as a new predictive technique to identify compositions for further screening, in particular for magnetic HEAs. PMID:28059106
The Effect of Electronic Structure on the Phases Present in High Entropy Alloys.

PubMed

Leong, Zhaoyuan; Wróbel, Jan S; Dudarev, Sergei L; Goodall, Russell; Todd, Iain; Nguyen-Manh, Duc

2017-01-06

Multicomponent systems, termed High Entropy Alloys (HEAs), with predominantly single solid solution phases are a current area of focus in alloy development. Although different empirical rules have been introduced to understand phase formation and determine what the dominant phases may be in these systems, experimental investigation has revealed that in many cases their structure is not a single solid solution phase, and that the rules may not accurately distinguish the stability of the phase boundaries. Here, a combined modelling and experimental approach that looks into the electronic structure is proposed to improve accuracy of the predictions of the majority phase. To do this, the Rigid Band model is generalised for magnetic systems in prediction of the majority phase most likely to be found. Good agreement is found when the predictions are confronted with data from experiments, including a new magnetic HEA system (CoFeNiV). This also includes predicting the structural transition with varying levels of constituent elements, as a function of the valence electron concentration, n, obtained from the integrated spin-polarised density of states. This method is suitable as a new predictive technique to identify compositions for further screening, in particular for magnetic HEAs.
Proof-test-based life prediction of high-toughness pressure vessels

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

Panontin, T.L.; Hill, M.R.

1996-02-01

The paper examines the problems associated with applying proof-test-based life prediction to vessels made of high-toughness metals. Two A106 Gr B pipe specimens containing long, through-wall circumferential flaws were tested. One failed during hydrostatic testing and the other during tension-tension cycling following a hydrostatic test. Quantitative fractography was used to verify experimentally obtained fatigue crack growth rates and a variety of LEFM and EPFM techniques were used to analyze the experimental results. The results show that: plastic collapse analysis provides accurate predictions of screened (initial) crack size when the flow stress is determined experimentally; LEFM analysis underestimates the crack sizemore » screened by the proof test and overpredicts the subsequent fatigue life of the vessel when retardation effects are small (i.e., low proof levels); and, at a high proof-test level (2.4 {times} operating pressure), the large retardation effect on fatigue crack growth due to the overload overwhelmed the deleterious effect on fatigue life from stable tearing during the proof test and alleviated the problem of screening only long cracks due to the high toughness of the metal.« less
Quantifying variability in delta experiments

NASA Astrophysics Data System (ADS)

Miller, K. L.; Berg, S. R.; McElroy, B. J.

2017-12-01

Large populations of people and wildlife make their homes on river deltas, therefore it is important to be able to make useful and accurate predictions of how these landforms will change over time. However, making predictions can be a challenge due to inherent variability of the natural system. Furthermore, when we extrapolate results from the laboratory to the field setting, we bring with it random and systematic errors of the experiment. We seek to understand both the intrinsic and experimental variability of river delta systems to help better inform predictions of how these landforms will evolve. We run exact replicates of experiments with steady sediment and water discharge and record delta evolution with overhead time lapse imaging. We measure aspects of topset progradation and channel dynamics and compare these metrics of delta morphology between the 6 replicated experimental runs. We also use data from all experimental runs collectively to build a large dataset to extract statistics of the system properties. We find that although natural variability exists, the processes in the experiments must have outcomes that no longer depend on their initial conditions after some time. Applying these results to the field scale will aid in our ability to make forecasts of how these landforms will progress.
Characterization of piezoelectric device for implanted pacemaker energy harvesting

NASA Astrophysics Data System (ADS)

Jay, Sunny; Caballero, Manuel; Quinn, William; Barrett, John; Hill, Martin

2016-10-01

Novel implanted cardiac pacemakers that are powered by energy harvesters driven by the cardiac motion and have a 40 year lifetime are currently under development. To satisfy space constraints and energy requirements of the device, silicon-based MEMS energy harvesters are being developed in the EU project (MANpower1). Such MEMS harvesters for vibration frequencies below 50 Hz have not been widely reported. In this paper, an analytical model and a 3D finite element model (FEM) to predict displacement and open circuit voltage, validated through experimental analysis using an off-the-shelf low frequency energy harvester, are presented. The harvester was excited through constant amplitude sinusoidal base displacement over a range of 20 to 70 Hz passing through its first mode natural frequency at 47 Hz. At resonance both models predict displacements with an error of less than 2% when compared to the experimental result. Comparing the two models, the application of the experimentally measured damping ratio differs for accurate displacement prediction and the differences in symmetry in the measured and modelled displacement and voltage data around the resonance frequency indicate the two piezoelectric voltage models use different fundamental equations.
Detection of free nickel monocarbonyl, NiCO: rotational spectrum and structure.

PubMed

Yamazaki, Emi; Okabayashi, Toshiaki; Tanimoto, Mitsutoshi

2004-02-04

Unsaturated transition metal carbonyls are important in processes such as organometallic synthesis, homogeneous catalysis, and photochemical decomposition of organometallics. In particular, a metal monocarbonyl offers a zeroth-order model for interpreting the chemisorption of a CO molecule on a metal surface in catalytic activation processes. Quite large numbers of theoretical papers have appeared which predict spectroscopic and structural properties of transition metal carbonyls. The nickel monocarbonyl NiCO has been one of the metal carbonyls most extensively studied by the theoretical calculations. At least 50 theoretical studies have been published on this simplest transition metal carbonyl up to the present time. However, experimental evidence of NiCO is much more sparse than theoretical predictions, and the actual structure of NiCO has never been determined by any experimental methods. This Communication reports the first preparation of free nickel monocarbonyl and observation of its rotational transitions. The NiCO molecule was generated by the sputtering reaction of a Ni cathode in the presence of CO. The accurate bond lengths of Ni-C and C-O were experimentally determined from isotopic data and were compared with the theoretical predictions for the first time.
Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis.

PubMed

You, Zhu-Hong; Lei, Ying-Ke; Zhu, Lin; Xia, Junfeng; Wang, Bing

2013-01-01

Protein-protein interactions (PPIs) play crucial roles in the execution of various cellular processes and form the basis of biological mechanisms. Although large amount of PPIs data for different species has been generated by high-throughput experimental techniques, current PPI pairs obtained with experimental methods cover only a fraction of the complete PPI networks, and further, the experimental methods for identifying PPIs are both time-consuming and expensive. Hence, it is urgent and challenging to develop automated computational methods to efficiently and accurately predict PPIs. We present here a novel hierarchical PCA-EELM (principal component analysis-ensemble extreme learning machine) model to predict protein-protein interactions only using the information of protein sequences. In the proposed method, 11188 protein pairs retrieved from the DIP database were encoded into feature vectors by using four kinds of protein sequences information. Focusing on dimension reduction, an effective feature extraction method PCA was then employed to construct the most discriminative new feature set. Finally, multiple extreme learning machines were trained and then aggregated into a consensus classifier by majority voting. The ensembling of extreme learning machine removes the dependence of results on initial random weights and improves the prediction performance. When performed on the PPI data of Saccharomyces cerevisiae, the proposed method achieved 87.00% prediction accuracy with 86.15% sensitivity at the precision of 87.59%. Extensive experiments are performed to compare our method with state-of-the-art techniques Support Vector Machine (SVM). Experimental results demonstrate that proposed PCA-EELM outperforms the SVM method by 5-fold cross-validation. Besides, PCA-EELM performs faster than PCA-SVM based method. Consequently, the proposed approach can be considered as a new promising and powerful tools for predicting PPI with excellent performance and less time.

Prediction of shear critical behavior of high-strength reinforced concrete columns using finite element methods

NASA Astrophysics Data System (ADS)

Alrasyid, Harun; Safi, Fahrudin; Iranata, Data; Chen-Ou, Yu

2017-11-01

This research shows the prediction of shear behavior of High-Strength Reinforced Concrete Columns using Finite-Element Method. The experimental data of nine half scale high-strength reinforced concrete were selected. These columns using specified concrete compressive strength of 70 MPa, specified yield strength of longitudinal and transverse reinforcement of 685 and 785 MPa, respectively. The VecTor2 finite element software was used to simulate the shear critical behavior of these columns. The combination axial compression load and monotonic loading were applied at this prediction. It is demonstrated that VecTor2 finite element software provides accurate prediction of load-deflection up to peak at applied load, but provide similar behavior at post peak load. The shear strength prediction provide by VecTor 2 are slightly conservative compare to test result.
Assessment of Geometry and In-Flow Effects on Contra-Rotating Open Rotor Broadband Noise Predictions

NASA Technical Reports Server (NTRS)

Zawodny, Nikolas S.; Nark, Douglas M.; Boyd, D. Douglas, Jr.

2015-01-01

Application of previously formulated semi-analytical models for the prediction of broadband noise due to turbulent rotor wake interactions and rotor blade trailing edges is performed on the historical baseline F31/A31 contra-rotating open rotor configuration. Simplified two-dimensional blade element analysis is performed on cambered NACA 4-digit airfoil profiles, which are meant to serve as substitutes for the actual rotor blade sectional geometries. Rotor in-flow effects such as induced axial and tangential velocities are incorporated into the noise prediction models based on supporting computational fluid dynamics (CFD) results and simplified in-flow velocity models. Emphasis is placed on the development of simplified rotor in-flow models for the purpose of performing accurate noise predictions independent of CFD information. The broadband predictions are found to compare favorably with experimental acoustic results.
Aeropropulsion 1987. Session 3: Internal Fluid Mechanics Research

NASA Technical Reports Server (NTRS)

1987-01-01

Internal fluid mechanics research at Lewis is directed toward an improved understanding of the important flow physics affecting aerospace propulsion systems, and applying this improved understanding to formulate accurate predictive codes. To this end, research is conducted involving detailed experimentation and analysis. The presentations in this session summarize ongoing work and indicated future emphasis in three major research thrusts: namely, inlets, ducts, and nozzles; turbomachinery; and chemical reacting flows.
Free energy landscape for the binding process of Huperzine A to acetylcholinesterase

PubMed Central

Bai, Fang; Xu, Yechun; Chen, Jing; Liu, Qiufeng; Gu, Junfeng; Wang, Xicheng; Ma, Jianpeng; Li, Honglin; Onuchic, José N.; Jiang, Hualiang

2013-01-01

Drug-target residence time (t = 1/koff, where koff is the dissociation rate constant) has become an important index in discovering better- or best-in-class drugs. However, little effort has been dedicated to developing computational methods that can accurately predict this kinetic parameter or related parameters, koff and activation free energy of dissociation (). In this paper, energy landscape theory that has been developed to understand protein folding and function is extended to develop a generally applicable computational framework that is able to construct a complete ligand-target binding free energy landscape. This enables both the binding affinity and the binding kinetics to be accurately estimated. We applied this method to simulate the binding event of the anti-Alzheimer’s disease drug (−)−Huperzine A to its target acetylcholinesterase (AChE). The computational results are in excellent agreement with our concurrent experimental measurements. All of the predicted values of binding free energy and activation free energies of association and dissociation deviate from the experimental data only by less than 1 kcal/mol. The method also provides atomic resolution information for the (−)−Huperzine A binding pathway, which may be useful in designing more potent AChE inhibitors. We expect this methodology to be widely applicable to drug discovery and development. PMID:23440190
Free energy landscape for the binding process of Huperzine A to acetylcholinesterase.

PubMed

Bai, Fang; Xu, Yechun; Chen, Jing; Liu, Qiufeng; Gu, Junfeng; Wang, Xicheng; Ma, Jianpeng; Li, Honglin; Onuchic, José N; Jiang, Hualiang

2013-03-12

Drug-target residence time (t = 1/k(off), where k(off) is the dissociation rate constant) has become an important index in discovering better- or best-in-class drugs. However, little effort has been dedicated to developing computational methods that can accurately predict this kinetic parameter or related parameters, k(off) and activation free energy of dissociation (ΔG(off)≠). In this paper, energy landscape theory that has been developed to understand protein folding and function is extended to develop a generally applicable computational framework that is able to construct a complete ligand-target binding free energy landscape. This enables both the binding affinity and the binding kinetics to be accurately estimated. We applied this method to simulate the binding event of the anti-Alzheimer's disease drug (-)-Huperzine A to its target acetylcholinesterase (AChE). The computational results are in excellent agreement with our concurrent experimental measurements. All of the predicted values of binding free energy and activation free energies of association and dissociation deviate from the experimental data only by less than 1 kcal/mol. The method also provides atomic resolution information for the (-)-Huperzine A binding pathway, which may be useful in designing more potent AChE inhibitors. We expect this methodology to be widely applicable to drug discovery and development.
Using Molecular Dynamics to quantify the electrical double layer and examine the potential for its direct observation in the in-situ TEM

DOE PAGES

Welch, David A.; Mehdi, Beata L.; Hatchell, Hanna J.; ...

2015-03-25

Understanding the fundamental processes taking place at the electrode-electrolyte interface in batteries will play a key role in the development of next generation energy storage technologies. One of the most fundamental aspects of the electrode-electrolyte interface is the electrical double layer (EDL). Given the recent development of high spatial resolution in-situ electrochemical cells for scanning transmission electron microscopy (STEM), there now exists the possibility that we can directly observe the formation and dynamics of the EDL. In this paper we predict electrolyte structure within the EDL using classical models and atomistic Molecular Dynamics (MD) simulations. The MD simulations show thatmore » the classical models fail to accurately reproduce concentration profiles that exist within the electrolyte. It is thus suggested that MD must be used in order to accurately predict STEM images of the electrode-electrolyte interface. Using MD and image simulations together for a high contrast electrolyte (the high atomic number CsCl electrolyte), it is determined that, for a smooth interface, concentration profiles within the EDL should be visible experimentally. When normal experimental parameters such as rough interfaces and low-Z electrolytes (like those used in Li-ion batteries) are considered, observation of the EDL appears to be more difficult.« less
Bona-fide method for the determination of short range order and transport properties in a ferro-aluminosilicate slag

PubMed Central

Karalis, Konstantinos T.; Dellis, Dimitrios; Antipas, Georgios S. E.; Xenidis, Anthimos

2016-01-01

The thermodynamics, structural and transport properties (density, melting point, heat capacity, thermal expansion coefficient, viscosity and electrical conductivity) of a ferro-aluminosilicate slag have been studied in the solid and liquid state (1273–2273 K) using molecular dynamics. The simulations were based on a Buckingham-type potential, which was extended here, to account for the presence of Cr and Cu. The potential was optimized by fitting pair distribution function partials to values determined by Reverse Monte Carlo modelling of X-ray and neutron diffraction experiments. The resulting short range order features and ring statistics were in tight agreement with experimental data and created consensus for the accurate prediction of transport properties. Accordingly, calculations yielded rational values both for the average heat capacity, equal to 1668.58 J/(kg·K), and for the viscosity, in the range of 4.09–87.64 cP. The potential was consistent in predicting accurate values for mass density (i.e. 2961.50 kg/m3 vs. an experimental value of 2940 kg/m3) and for electrical conductivity (5.3–233 S/m within a temperature range of 1273.15–2273.15 K). PMID:27455915
Assessing antibiotic sorption in soil: a literature review and new case studies on sulfonamides and macrolides

PubMed Central

2014-01-01

The increased use of veterinary antibiotics in modern agriculture for therapeutic uses and growth promotion has raised concern regarding the environmental impacts of antibiotic residues in soil and water. The mobility and transport of antibiotics in the environment depends on their sorption behavior, which is typically predicted by extrapolating from an experimentally determined soil-water distribution coefficient (Kd). Accurate determination of Kd values is important in order to better predict the environmental fate of antibiotics. In this paper, we examine different analytical approaches in assessing Kd of two major classes of veterinary antibiotics (sulfonamides and macrolides) and compare the existing literature data with experimental data obtained in our laboratory. While environmental parameters such as soil pH and organic matter content are the most significant factors that affect the sorption of antibiotics in soil, it is important to consider the concentrations used, the analytical method employed, and the transformations that can occur when determining Kd values. Application of solid phase extraction and liquid chromatography/mass spectrometry can facilitate accurate determination of Kd at environmentally relevant concentrations. Because the bioavailability of antibiotics in soil depends on their sorption behavior, it is important to examine current practices in assessing their mobility in soil. PMID:24438473
Finite element based model predictive control for active vibration suppression of a one-link flexible manipulator.

PubMed

Dubay, Rickey; Hassan, Marwan; Li, Chunying; Charest, Meaghan

2014-09-01

This paper presents a unique approach for active vibration control of a one-link flexible manipulator. The method combines a finite element model of the manipulator and an advanced model predictive controller to suppress vibration at its tip. This hybrid methodology improves significantly over the standard application of a predictive controller for vibration control. The finite element model used in place of standard modelling in the control algorithm provides a more accurate prediction of dynamic behavior, resulting in enhanced control. Closed loop control experiments were performed using the flexible manipulator, instrumented with strain gauges and piezoelectric actuators. In all instances, experimental and simulation results demonstrate that the finite element based predictive controller provides improved active vibration suppression in comparison with using a standard predictive control strategy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
A Demand-Driven Approach for a Multi-Agent System in Supply Chain Management

NASA Astrophysics Data System (ADS)

Kovalchuk, Yevgeniya; Fasli, Maria

This paper presents the architecture of a multi-agent decision support system for Supply Chain Management (SCM) which has been designed to compete in the TAC SCM game. The behaviour of the system is demand-driven and the agents plan, predict, and react dynamically to changes in the market. The main strength of the system lies in the ability of the Demand agent to predict customer winning bid prices - the highest prices the agent can offer customers and still obtain their orders. This paper investigates the effect of the ability to predict customer order prices on the overall performance of the system. Four strategies are proposed and compared for predicting such prices. The experimental results reveal which strategies are better and show that there is a correlation between the accuracy of the models' predictions and the overall system performance: the more accurate the prediction of customer order prices, the higher the profit.
The Use of Artificial Neural Network for Prediction of Dissolution Kinetics

PubMed Central

Elçiçek, H.; Akdoğan, E.; Karagöz, S.

2014-01-01

Colemanite is a preferred boron mineral in industry, such as boric acid production, fabrication of heat resistant glass, and cleaning agents. Dissolution of the mineral is one of the most important processes for these industries. In this study, dissolution of colemanite was examined in water saturated with carbon dioxide solutions. Also, prediction of dissolution rate was determined using artificial neural networks (ANNs) which are based on the multilayered perceptron. Reaction temperature, total pressure, stirring speed, solid/liquid ratio, particle size, and reaction time were selected as input parameters to predict the dissolution rate. Experimental dataset was used to train multilayer perceptron (MLP) networks to allow for prediction of dissolution kinetics. Developing ANNs has provided highly accurate predictions in comparison with an obtained mathematical model used through regression method. We conclude that ANNs may be a preferred alternative approach instead of conventional statistical methods for prediction of boron minerals. PMID:25028674
A Three-Dimensional Solution of Flows over Wings with Leading-Edge Vortex Separation. Part 1: Engineering Document

NASA Technical Reports Server (NTRS)

Brune, G. W.; Weber, J. A.; Johnson, F. T.; Lu, P.; Rubbert, P. E.

1975-01-01

A method of predicting forces, moments, and detailed surface pressures on thin, sharp-edged wings with leading-edge vortex separation in incompressible flow is presented. The method employs an inviscid flow model in which the wing and the rolled-up vortex sheets are represented by piecewise, continuous quadratic doublet sheet distributions. The Kutta condition is imposed on all wing edges. Computed results are compared with experimental data and with the predictions of the leading-edge suction analogy for a selected number of wing planforms over a wide range of angle of attack. These comparisons show the method to be very promising, capable of producing not only force predictions, but also accurate predictions of detailed surface pressure distributions, loads, and moments.
Prediction of Flow Stress in Cadmium Using Constitutive Equation and Artificial Neural Network Approach

NASA Astrophysics Data System (ADS)

Sarkar, A.; Chakravartty, J. K.

2013-10-01

A model is developed to predict the constitutive flow behavior of cadmium during compression test using artificial neural network (ANN). The inputs of the neural network are strain, strain rate, and temperature, whereas flow stress is the output. Experimental data obtained from compression tests in the temperature range -30 to 70 °C, strain range 0.1 to 0.6, and strain rate range 10-3 to 1 s-1 are employed to develop the model. A three-layer feed-forward ANN is trained with Levenberg-Marquardt training algorithm. It has been shown that the developed ANN model can efficiently and accurately predict the deformation behavior of cadmium. This trained network could predict the flow stress better than a constitutive equation of the type.
Intra- and Inter-Fractional Variation Prediction of Lung Tumors Using Fuzzy Deep Learning

PubMed Central

Park, Seonyeong; Lee, Suk Jin; Weiss, Elisabeth

2016-01-01

Tumor movements should be accurately predicted to improve delivery accuracy and reduce unnecessary radiation exposure to healthy tissue during radiotherapy. The tumor movements pertaining to respiration are divided into intra-fractional variation occurring in a single treatment session and inter-fractional variation arising between different sessions. Most studies of patients’ respiration movements deal with intra-fractional variation. Previous studies on inter-fractional variation are hardly mathematized and cannot predict movements well due to inconstant variation. Moreover, the computation time of the prediction should be reduced. To overcome these limitations, we propose a new predictor for intra- and inter-fractional data variation, called intra- and inter-fraction fuzzy deep learning (IIFDL), where FDL, equipped with breathing clustering, predicts the movement accurately and decreases the computation time. Through the experimental results, we validated that the IIFDL improved root-mean-square error (RMSE) by 29.98% and prediction overshoot by 70.93%, compared with existing methods. The results also showed that the IIFDL enhanced the average RMSE and overshoot by 59.73% and 83.27%, respectively. In addition, the average computation time of IIFDL was 1.54 ms for both intra- and inter-fractional variation, which was much smaller than the existing methods. Therefore, the proposed IIFDL might achieve real-time estimation as well as better tracking techniques in radiotherapy. PMID:27170914
Evaluation of Industry Standard Turbulence Models on an Axisymmetric Supersonic Compression Corner

NASA Technical Reports Server (NTRS)

DeBonis, James R.

2015-01-01

Reynolds-averaged Navier-Stokes computations of a shock-wave/boundary-layer interaction (SWBLI) created by a Mach 2.85 flow over an axisymmetric 30-degree compression corner were carried out. The objectives were to evaluate four turbulence models commonly used in industry, for SWBLIs, and to evaluate the suitability of this test case for use in further turbulence model benchmarking. The Spalart-Allmaras model, Menter's Baseline and Shear Stress Transport models, and a low-Reynolds number k- model were evaluated. Results indicate that the models do not accurately predict the separation location; with the SST model predicting the separation onset too early and the other models predicting the onset too late. Overall the Spalart-Allmaras model did the best job in matching the experimental data. However there is significant room for improvement, most notably in the prediction of the turbulent shear stress. Density data showed that the simulations did not accurately predict the thermal boundary layer upstream of the SWBLI. The effect of turbulent Prandtl number and wall temperature were studied in an attempt to improve this prediction and understand their effects on the interaction. The data showed that both parameters can significantly affect the separation size and location, but did not improve the agreement with the experiment. This case proved challenging to compute and should provide a good test for future turbulence modeling work.
Vfold: a web server for RNA structure and folding thermodynamics prediction.

PubMed

Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2014-01-01

The ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies. The Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization. The Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at "http://rna.physics.missouri.edu".
MnNiO 3 revisited with modern theoretical and experimental methods

DOE PAGES

Dzubak, Allison L.; Mitra, Chandrima; Chance, Michael; ...

2017-11-03

MnNiO 3 is a strongly correlated transition metal oxide that has recently been investigated theoretically for its potential application as an oxygen-evolution photocatalyst. However, there is no experimental report on critical quantities such as the band gap or bulk modulus. Recent theoretical predictions with standard functionals such as LDA+U and HSE show large discrepancies in the band gaps (about 1.23 eV), depending on the nature of the functional used. Hence there is clearly a need for an accurate quantitative prediction of the band gap to gauge its utility as a photocatalyst. In this work, we present a diffusion quantum Montemore » Carlo study of the bulk properties of MnNiO 3 and revisit the synthesis and experimental properties of the compound. We predict quasiparticle band gaps of 2.0(5) eV and 3.8(6) eV for the majority and minority spin channels, respectively, and an equilibrium volume of 92.8 Å 3, which compares well to the experimental value of 94.4 Å 3. A bulk modulus of 217 GPa is predicted for MnNiO 3. As a result, we rationalize the difficulty for the formation of ordered ilmenite-type structure with specific sites for Ni and Mn to be potentially due to the formation of antisite defects that form during synthesis, which ultimately affects the physical properties of MnNiO 3.« less
Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change.

PubMed

Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien

2015-10-01

Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates.
MnNiO 3 revisited with modern theoretical and experimental methods

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

Dzubak, Allison L.; Mitra, Chandrima; Chance, Michael

MnNiO 3 is a strongly correlated transition metal oxide that has recently been investigated theoretically for its potential application as an oxygen-evolution photocatalyst. However, there is no experimental report on critical quantities such as the band gap or bulk modulus. Recent theoretical predictions with standard functionals such as LDA+U and HSE show large discrepancies in the band gaps (about 1.23 eV), depending on the nature of the functional used. Hence there is clearly a need for an accurate quantitative prediction of the band gap to gauge its utility as a photocatalyst. In this work, we present a diffusion quantum Montemore » Carlo study of the bulk properties of MnNiO 3 and revisit the synthesis and experimental properties of the compound. We predict quasiparticle band gaps of 2.0(5) eV and 3.8(6) eV for the majority and minority spin channels, respectively, and an equilibrium volume of 92.8 Å 3, which compares well to the experimental value of 94.4 Å 3. A bulk modulus of 217 GPa is predicted for MnNiO 3. As a result, we rationalize the difficulty for the formation of ordered ilmenite-type structure with specific sites for Ni and Mn to be potentially due to the formation of antisite defects that form during synthesis, which ultimately affects the physical properties of MnNiO 3.« less
Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change

PubMed Central

Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien

2015-01-01

Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates. PMID:26501958

Fracture prediction using modified mohr coulomb theory for non-linear strain paths using AA3104-H19

NASA Astrophysics Data System (ADS)

Dick, Robert; Yoon, Jeong Whan

2016-08-01

Experiment results from uniaxial tensile tests, bi-axial bulge tests, and disk compression tests for a beverage can AA3104-H19 material are presented. The results from the experimental tests are used to determine material coefficients for both Yld2000 and Yld2004 models. Finite element simulations are developed to study the influence of materials model on the predicted earing profile. It is shown that only the YLD2004 model is capable of accurately predicting the earing profile as the YLD2000 model only predicts 4 ears. Excellent agreement with the experimental data for earing is achieved using the AA3104-H19 material data and the Yld2004 constitutive model. Mechanical tests are also conducted on the AA3104-H19 to generate fracture data under different stress triaxiality conditions. Tensile tests are performed on specimens with a central hole and notched specimens. Torsion of a double bridge specimen is conducted to generate points near pure shear conditions. The Nakajima test is utilized to produce points in bi-axial tension. The data from the experiments is used to develop the fracture locus in the principal strain space. Mapping from principal strain space to stress triaxiality space, principal stress space, and polar effective plastic strain space is accomplished using a generalized mapping technique. Finite element modeling is used to validate the Modified Mohr-Coulomb (MMC) fracture model in the polar space. Models of a hole expansion during cup drawing and a cup draw/reverse redraw/expand forming sequence demonstrate the robustness of the modified PEPS fracture theory for the condition with nonlinear forming paths and accurately predicts the onset of failure. The proposed methods can be widely used for predicting failure for the examples which undergo nonlinear strain path including rigid-packaging and automotive forming.
Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.
A Revised Validation Process for Ice Accretion Codes

NASA Technical Reports Server (NTRS)

Wright, William B.; Porter, Christopher E.

2017-01-01

A research project is underway at NASA Glenn to produce computer software that can accurately predict ice growth under any meteorological conditions for any aircraft surface. This report will present results from the latest LEWICE release, version 3.5. This program differs from previous releases in its ability to model mixed phase and ice crystal conditions such as those encountered inside an engine. It also has expanded capability to use structured grids and a new capability to use results from unstructured grid flow solvers. A quantitative comparison of the results against a database of ice shapes that have been generated in the NASA Glenn Icing Research Tunnel (IRT) has also been performed. This paper will extend the comparison of ice shapes between LEWICE 3.5 and experimental data from a previous paper. Comparisons of lift and drag are made between experimentally collected data from experimentally obtained ice shapes and simulated (CFD) data on simulated (LEWICE) ice shapes. Comparisons are also made between experimentally collected and simulated performance data on select experimental ice shapes to ensure the CFD solver, FUN3D, is valid within the flight regime. The results show that the predicted results are within the accuracy limits of the experimental data for the majority of cases.
Validation Process for LEWICE by Use of a Navier-Stokes Solver

NASA Technical Reports Server (NTRS)

Wright, William B.; Porter, Christopher E.

2017-01-01

A research project is underway at NASA Glenn to produce computer software that can accurately predict ice growth under any meteorological conditions for any aircraft surface. This report will present results from the latest LEWICE release, version 3.5. This program differs from previous releases in its ability to model mixed phase and ice crystal conditions such as those encountered inside an engine. It also has expanded capability to use structured grids and a new capability to use results from unstructured grid flow solvers. A quantitative comparison of the results against a database of ice shapes that have been generated in the NASA Glenn Icing Research Tunnel (IRT) has also been performed. This paper will extend the comparison of ice shapes between LEWICE 3.5 and experimental data from a previous paper. Comparisons of lift and drag are made between experimentally collected data from experimentally obtained ice shapes and simulated (CFD) data on simulated (LEWICE) ice shapes. Comparisons are also made between experimentally collected and simulated performance data on select experimental ice shapes to ensure the CFD solver, FUN3D, is valid within the flight regime. The results show that the predicted results are within the accuracy limits of the experimental data for the majority of cases.
Rotorcraft acoustic radiation prediction based on a refined blade-vortex interaction model

NASA Astrophysics Data System (ADS)

Rule, John Allen

1997-08-01

The analysis of rotorcraft aerodynamics and acoustics is a challenging problem, primarily due to the fact that a rotorcraft continually flies through its own wake. The generation mechanism for a rotorcraft wake, which is dominated by strong, concentrated blade-tip trailing vortices, is similar to that in fixed wing aerodynamics. However, following blades encounter shed vortices from previous blades before they are swept downstream, resulting in sharp, impulsive loading on the blades. The blade/wake encounter, known as Blade-Vortex Interaction, or BVI, is responsible for a significant amount of vibratory loading and the characteristic rotorcraft acoustic signature in certain flight regimes. The present work addressed three different aspects of this interaction at a fundamental level. First, an analytical model for the prediction of trailing vortex structure is discussed. The model as presented is the culmination of a lengthy research effort to isolate the key physical mechanisms which govern vortex sheet rollup. Based on the Betz model, properties of the flow such as mass flux, axial momentum flux, and axial flux of angular momentum are conserved on either a differential or integral basis during the rollup process. The formation of a viscous central core was facilitated by the assumption of a turbulent mixing process with final vortex velocity profiles chosen to be consistent with a rotational flow mixing model and experimental observation. A general derivation of the method is outlined, followed by a comparison of model predictions with experimental vortex measurements, and finally a viscous blade drag model to account for additional effects of aerodynamic drag on vortex structure. The second phase of this program involved the development of a new formulation of lifting surface theory with the ultimate goal of an accurate, reduced order hybrid analytical/numerical model for fast rotorcraft load calculations. Currently, accurate rotorcraft airload analyses are limited by the massive computational power required to capture the small time scale events associated with BVI. This problem has two primary facets: accurate knowledge of the wake geometry, and accurate resolution of the impulsive loading imposed by a tip vortex on a blade. The present work addressed the second facet, providing a mathematical framework for solving the impulsive loading problem analytically, then asymptotically matching this solution to a low-resolution numerical calculation. A method was developed which uses continuous sheets of integrated boundary elements to model the lifting surface and wake. Special elements were developed to capture local behavior in high-gradient regions of the flow, thereby reducing the burden placed on the surrounding numerical method. Unsteady calculations for several classical cases were made in both frequency and time domain to demonstrate the performance of the method. Finally, a new unsteady, compressible boundary element method was applied to the problem of BVI acoustic radiation prediction. This numerical method, combined with the viscous core trailing vortex model, was used to duplicate the geometry and flight configuration of a detailed experimental BVI study carried out at NASA Ames Research Center. Blade surface pressure and near- and far-field acoustic radiation calculations were made. All calculations were shown to compare favorably with experimentally measured values. The linear boundary element method with non-linear corrections proved sufficient over most of the rotor azimuth, and particular in the region of the blade vortex interaction, suggesting that full non-linear CFD schemes are not necessary for rotorcraft noise prediction.
Estimations of global warming potentials from computational chemistry calculations for CH(2)F(2) and other fluorinated methyl species verified by comparison to experiment.

PubMed

Blowers, Paul; Hollingshead, Kyle

2009-05-21

In this work, the global warming potential (GWP) of methylene fluoride (CH(2)F(2)), or HFC-32, is estimated through computational chemistry methods. We find our computational chemistry approach reproduces well all phenomena important for predicting global warming potentials. Geometries predicted using the B3LYP/6-311g** method were in good agreement with experiment, although some other computational methods performed slightly better. Frequencies needed for both partition function calculations in transition-state theory and infrared intensities needed for radiative forcing estimates agreed well with experiment compared to other computational methods. A modified CBS-RAD method used to obtain energies led to superior results to all other previous heat of reaction estimates and most barrier height calculations when the B3LYP/6-311g** optimized geometry was used as the base structure. Use of the small-curvature tunneling correction and a hindered rotor treatment where appropriate led to accurate reaction rate constants and radiative forcing estimates without requiring any experimental data. Atmospheric lifetimes from theory at 277 K were indistinguishable from experimental results, as were the final global warming potentials compared to experiment. This is the first time entirely computational methods have been applied to estimate a global warming potential for a chemical, and we have found the approach to be robust, inexpensive, and accurate compared to prior experimental results. This methodology was subsequently used to estimate GWPs for three additional species [methane (CH(4)); fluoromethane (CH(3)F), or HFC-41; and fluoroform (CHF(3)), or HFC-23], where estimations also compare favorably to experimental values.
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
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.
Molecular Modeling of Thermodynamic and Transport Properties for CO 2 and Aqueous Brines

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

Jiang, Hao; Economou, Ioannis G.; Panagiotopoulos, Athanassios Z.

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models formore » water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2, and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2-rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion–ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Lastly, another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.« less
Molecular Modeling of Thermodynamic and Transport Properties for CO2 and Aqueous Brines.

PubMed

Jiang, Hao; Economou, Ioannis G; Panagiotopoulos, Athanassios Z

2017-04-18

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models for water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2 , and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2 -rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion-ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.
Molecular Modeling of Thermodynamic and Transport Properties for CO 2 and Aqueous Brines

DOE PAGES

Jiang, Hao; Economou, Ioannis G.; Panagiotopoulos, Athanassios Z.

2017-02-24

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models formore » water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2, and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2-rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion–ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Lastly, another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.« less
Seismo-acoustic ray model benchmarking against experimental tank data.

PubMed

Camargo Rodríguez, Orlando; Collis, Jon M; Simpson, Harry J; Ey, Emanuel; Schneiderwind, Joseph; Felisberto, Paulo

2012-08-01

Acoustic predictions of the recently developed traceo ray model, which accounts for bottom shear properties, are benchmarked against tank experimental data from the EPEE-1 and EPEE-2 (Elastic Parabolic Equation Experiment) experiments. Both experiments are representative of signal propagation in a Pekeris-like shallow-water waveguide over a non-flat isotropic elastic bottom, where significant interaction of the signal with the bottom can be expected. The benchmarks show, in particular, that the ray model can be as accurate as a parabolic approximation model benchmarked in similar conditions. The results of benchmarking are important, on one side, as a preliminary experimental validation of the model and, on the other side, demonstrates the reliability of the ray approach for seismo-acoustic applications.
Scale Adaptive Simulation Model for the Darrieus Wind Turbine

NASA Astrophysics Data System (ADS)

Rogowski, K.; Hansen, M. O. L.; Maroński, R.; Lichota, P.

2016-09-01

Accurate prediction of aerodynamic loads for the Darrieus wind turbine using more or less complex aerodynamic models is still a challenge. One of the problems is the small amount of experimental data available to validate the numerical codes. The major objective of the present study is to examine the scale adaptive simulation (SAS) approach for performance analysis of a one-bladed Darrieus wind turbine working at a tip speed ratio of 5 and at a blade Reynolds number of 40 000. The three-dimensional incompressible unsteady Navier-Stokes equations are used. Numerical results of aerodynamic loads and wake velocity profiles behind the rotor are compared with experimental data taken from literature. The level of agreement between CFD and experimental results is reasonable.
Accurate electrostatic and van der Waals pull-in prediction for fully clamped nano/micro-beams using linear universal graphs of pull-in instability

NASA Astrophysics Data System (ADS)

Tahani, Masoud; Askari, Amir R.

2014-09-01

In spite of the fact that pull-in instability of electrically actuated nano/micro-beams has been investigated by many researchers to date, no explicit formula has been presented yet which can predict pull-in voltage based on a geometrically non-linear and distributed parameter model. The objective of present paper is to introduce a simple and accurate formula to predict this value for a fully clamped electrostatically actuated nano/micro-beam. To this end, a non-linear Euler-Bernoulli beam model is employed, which accounts for the axial residual stress, geometric non-linearity of mid-plane stretching, distributed electrostatic force and the van der Waals (vdW) attraction. The non-linear boundary value governing equation of equilibrium is non-dimensionalized and solved iteratively through single-term Galerkin based reduced order model (ROM). The solutions are validated thorough direct comparison with experimental and other existing results reported in previous studies. Pull-in instability under electrical and vdW loads are also investigated using universal graphs. Based on the results of these graphs, non-dimensional pull-in and vdW parameters, which are defined in the text, vary linearly versus the other dimensionless parameters of the problem. Using this fact, some linear equations are presented to predict pull-in voltage, the maximum allowable length, the so-called detachment length, and the minimum allowable gap for a nano/micro-system. These linear equations are also reduced to a couple of universal pull-in formulas for systems with small initial gap. The accuracy of the universal pull-in formulas are also validated by comparing its results with available experimental and some previous geometric linear and closed-form findings published in the literature.
Sound transmission loss of composite sandwich panels

NASA Astrophysics Data System (ADS)

Zhou, Ran

Light composite sandwich panels are increasingly used in automobiles, ships and aircraft, because of the advantages they offer of high strength-to-weight ratios. However, the acoustical properties of these light and stiff structures can be less desirable than those of equivalent metal panels. These undesirable properties can lead to high interior noise levels. A number of researchers have studied the acoustical properties of honeycomb and foam sandwich panels. Not much work, however, has been carried out on foam-filled honeycomb sandwich panels. In this dissertation, governing equations for the forced vibration of asymmetric sandwich panels are developed. An analytical expression for modal densities of symmetric sandwich panels is derived from a sixth-order governing equation. A boundary element analysis model for the sound transmission loss of symmetric sandwich panels is proposed. Measurements of the modal density, total loss factor, radiation loss factor, and sound transmission loss of foam-filled honeycomb sandwich panels with different configurations and thicknesses are presented. Comparisons between the predicted sound transmission loss values obtained from wave impedance analysis, statistical energy analysis, boundary element analysis, and experimental values are presented. The wave impedance analysis model provides accurate predictions of sound transmission loss for the thin foam-filled honeycomb sandwich panels at frequencies above their first resonance frequencies. The predictions from the statistical energy analysis model are in better agreement with the experimental transmission loss values of the sandwich panels when the measured radiation loss factor values near coincidence are used instead of the theoretical values for single-layer panels. The proposed boundary element analysis model provides more accurate predictions of sound transmission loss for the thick foam-filled honeycomb sandwich panels than either the wave impedance analysis model or the statistical energy analysis model.
Correlation of RNA secondary structure statistics with thermodynamic stability and applications to folding.

PubMed

Wu, Johnny C; Gardner, David P; Ozer, Stuart; Gutell, Robin R; Ren, Pengyu

2009-08-28

The accurate prediction of the secondary and tertiary structure of an RNA with different folding algorithms is dependent on several factors, including the energy functions. However, an RNA higher-order structure cannot be predicted accurately from its sequence based on a limited set of energy parameters. The inter- and intramolecular forces between this RNA and other small molecules and macromolecules, in addition to other factors in the cell such as pH, ionic strength, and temperature, influence the complex dynamics associated with transition of a single stranded RNA to its secondary and tertiary structure. Since all of the factors that affect the formation of an RNAs 3D structure cannot be determined experimentally, statistically derived potential energy has been used in the prediction of protein structure. In the current work, we evaluate the statistical free energy of various secondary structure motifs, including base-pair stacks, hairpin loops, and internal loops, using their statistical frequency obtained from the comparative analysis of more than 50,000 RNA sequences stored in the RNA Comparative Analysis Database (rCAD) at the Comparative RNA Web (CRW) Site. Statistical energy was computed from the structural statistics for several datasets. While the statistical energy for a base-pair stack correlates with experimentally derived free energy values, suggesting a Boltzmann-like distribution, variation is observed between different molecules and their location on the phylogenetic tree of life. Our statistical energy values calculated for several structural elements were utilized in the Mfold RNA-folding algorithm. The combined statistical energy values for base-pair stacks, hairpins and internal loop flanks result in a significant improvement in the accuracy of secondary structure prediction; the hairpin flanks contribute the most.
A polynomial chaos approach to the analysis of vehicle dynamics under uncertainty

NASA Astrophysics Data System (ADS)

Kewlani, Gaurav; Crawford, Justin; Iagnemma, Karl

2012-05-01

The ability of ground vehicles to quickly and accurately analyse their dynamic response to a given input is critical to their safety and efficient autonomous operation. In field conditions, significant uncertainty is associated with terrain and/or vehicle parameter estimates, and this uncertainty must be considered in the analysis of vehicle motion dynamics. Here, polynomial chaos approaches that explicitly consider parametric uncertainty during modelling of vehicle dynamics are presented. They are shown to be computationally more efficient than the standard Monte Carlo scheme, and experimental results compared with the simulation results performed on ANVEL (a vehicle simulator) indicate that the method can be utilised for efficient and accurate prediction of vehicle motion in realistic scenarios.
Dynamical scattering in coherent hard x-ray nanobeam Bragg diffraction

NASA Astrophysics Data System (ADS)

Pateras, A.; Park, J.; Ahn, Y.; Tilka, J. A.; Holt, M. V.; Kim, H.; Mawst, L. J.; Evans, P. G.

2018-06-01

Unique intensity features arising from dynamical diffraction arise in coherent x-ray nanobeam diffraction patterns of crystals having thicknesses larger than the x-ray extinction depth or exhibiting combinations of nanoscale and mesoscale features. We demonstrate that dynamical scattering effects can be accurately predicted using an optical model combined with the Darwin theory of dynamical x-ray diffraction. The model includes the highly divergent coherent x-ray nanobeams produced by Fresnel zone plate focusing optics and accounts for primary extinction, multiple scattering, and absorption. The simulation accurately reproduces the dynamical scattering features of experimental diffraction patterns acquired from a GaAs/AlGaAs epitaxial heterostructure on a GaAs (001) substrate.
Experimental Evaluation of Balance Prediction Models for Sit-to-Stand Movement in the Sagittal Plane

PubMed Central

Pena Cabra, Oscar David; Watanabe, Takashi

2013-01-01

Evaluation of balance control ability would become important in the rehabilitation training. In this paper, in order to make clear usefulness and limitation of a traditional simple inverted pendulum model in balance prediction in sit-to-stand movements, the traditional simple model was compared to an inertia (rotational radius) variable inverted pendulum model including multiple-joint influence in the balance predictions. The predictions were tested upon experimentation with six healthy subjects. The evaluation showed that the multiple-joint influence model is more accurate in predicting balance under demanding sit-to-stand conditions. On the other hand, the evaluation also showed that the traditionally used simple inverted pendulum model is still reliable in predicting balance during sit-to-stand movement under non-demanding (normal) condition. Especially, the simple model was shown to be effective for sit-to-stand movements with low center of mass velocity at the seat-off. Moreover, almost all trajectories under the normal condition seemed to follow the same control strategy, in which the subjects used extra energy than the minimum one necessary for standing up. This suggests that the safety considerations come first than the energy efficiency considerations during a sit to stand, since the most energy efficient trajectory is close to the backward fall boundary. PMID:24187580
Semi-supervised protein subcellular localization.

PubMed

Xu, Qian; Hu, Derek Hao; Xue, Hong; Yu, Weichuan; Yang, Qiang

2009-01-30

Protein subcellular localization is concerned with predicting the location of a protein within a cell using computational method. The location information can indicate key functionalities of proteins. Accurate predictions of subcellular localizations of protein can aid the prediction of protein function and genome annotation, as well as the identification of drug targets. Computational methods based on machine learning, such as support vector machine approaches, have already been widely used in the prediction of protein subcellular localization. However, a major drawback of these machine learning-based approaches is that a large amount of data should be labeled in order to let the prediction system learn a classifier of good generalization ability. However, in real world cases, it is laborious, expensive and time-consuming to experimentally determine the subcellular localization of a protein and prepare instances of labeled data. In this paper, we present an approach based on a new learning framework, semi-supervised learning, which can use much fewer labeled instances to construct a high quality prediction model. We construct an initial classifier using a small set of labeled examples first, and then use unlabeled instances to refine the classifier for future predictions. Experimental results show that our methods can effectively reduce the workload for labeling data using the unlabeled data. Our method is shown to enhance the state-of-the-art prediction results of SVM classifiers by more than 10%.

Experimental and Theoretical Study of Heat Conduction for Air up to 5000 K

NASA Technical Reports Server (NTRS)

Peng, Tzy-Cheng; Ahtye, Warren F.

1961-01-01

The theoretical value of the integral of thermal conductivity is compared with the experimental values from shock-tube measurements. The particular case considered is the one-dimensional nonsteady flow of heat through air at constant pressure. This approach has been previously described in NASA TR R-27. experiment was uncertain because of the large scatter in the experimental data. In this paper, an attempt is made to improve the correlation by use of a more refined calculation of the integral of thermal conductivity, and by use of improved experimental techniques and instrumentation. As a result of these changes, a much closer correlation is shown between the experimental and theoretical heat-flux potentials. This indicates that the predicted values of the coefficient of thermal conductivity for high-temperature air may be suitably accurate for many engineering needs, up to the limits of the test (4600 K).
The aerodynamic cost of flight in the short-tailed fruit bat (Carollia perspicillata): comparing theory with measurement

PubMed Central

von Busse, Rhea; Waldman, Rye M.; Swartz, Sharon M.; Voigt, Christian C.; Breuer, Kenneth S.

2014-01-01

Aerodynamic theory has long been used to predict the power required for animal flight, but widely used models contain many simplifications. It has been difficult to ascertain how closely biological reality matches model predictions, largely because of the technical challenges of accurately measuring the power expended when an animal flies. We designed a study to measure flight speed-dependent aerodynamic power directly from the kinetic energy contained in the wake of bats flying in a wind tunnel. We compared these measurements with two theoretical predictions that have been used for several decades in diverse fields of vertebrate biology and to metabolic measurements from a previous study using the same individuals. A high-accuracy displaced laser sheet stereo particle image velocimetry experimental design measured the wake velocities in the Trefftz plane behind four bats flying over a range of speeds (3–7 m s−1). We computed the aerodynamic power contained in the wake using a novel interpolation method and compared these results with the power predicted by Pennycuick's and Rayner's models. The measured aerodynamic power falls between the two theoretical predictions, demonstrating that the models effectively predict the appropriate range of flight power, but the models do not accurately predict minimum power or maximum range speeds. Mechanical efficiency—the ratio of aerodynamic power output to metabolic power input—varied from 5.9% to 9.8% for the same individuals, changing with flight speed. PMID:24718450
Fast flexible modeling of RNA structure using internal coordinates.

PubMed

Flores, Samuel Coulbourn; Sherman, Michael A; Bruns, Christopher M; Eastman, Peter; Altman, Russ Biagio

2011-01-01

Modeling the structure and dynamics of large macromolecules remains a critical challenge. Molecular dynamics (MD) simulations are expensive because they model every atom independently, and are difficult to combine with experimentally derived knowledge. Assembly of molecules using fragments from libraries relies on the database of known structures and thus may not work for novel motifs. Coarse-grained modeling methods have yielded good results on large molecules but can suffer from difficulties in creating more detailed full atomic realizations. There is therefore a need for molecular modeling algorithms that remain chemically accurate and economical for large molecules, do not rely on fragment libraries, and can incorporate experimental information. RNABuilder works in the internal coordinate space of dihedral angles and thus has time requirements proportional to the number of moving parts rather than the number of atoms. It provides accurate physics-based response to applied forces, but also allows user-specified forces for incorporating experimental information. A particular strength of RNABuilder is that all Leontis-Westhof basepairs can be specified as primitives by the user to be satisfied during model construction. We apply RNABuilder to predict the structure of an RNA molecule with 160 bases from its secondary structure, as well as experimental information. Our model matches the known structure to 10.2 Angstroms RMSD and has low computational expense.
Validating Inertial Confinement Fusion (ICF) predictive capability using perturbed capsules

NASA Astrophysics Data System (ADS)

Schmitt, Mark; Magelssen, Glenn; Tregillis, Ian; Hsu, Scott; Bradley, Paul; Dodd, Evan; Cobble, James; Flippo, Kirk; Offerman, Dustin; Obrey, Kimberly; Wang, Yi-Ming; Watt, Robert; Wilke, Mark; Wysocki, Frederick; Batha, Steven

2009-11-01

Achieving ignition on NIF is a monumental step on the path toward utilizing fusion as a controlled energy source. Obtaining robust ignition requires accurate ICF models to predict the degradation of ignition caused by heterogeneities in capsule construction and irradiation. LANL has embarked on a project to induce controlled defects in capsules to validate our ability to predict their effects on fusion burn. These efforts include the validation of feature-driven hydrodynamics and mix in a convergent geometry. This capability is needed to determine the performance of capsules imploded under less-than-optimum conditions on future IFE facilities. LANL's recently initiated Defect Implosion Experiments (DIME) conducted at Rochester's Omega facility are providing input for these efforts. Recent simulation and experimental results will be shown.
An efficient numerical procedure for thermohydrodynamic analysis of cavitating bearings

NASA Technical Reports Server (NTRS)

Vijayaraghavan, D.

1995-01-01

An efficient and accurate numerical procedure to determine the thermo-hydrodynamic performance of cavitating bearings is described. This procedure is based on the earlier development of Elrod for lubricating films, in which the properties across the film thickness are determined at Lobatto points and their distributions are expressed by collocated polynomials. The cavitated regions and their boundaries are rigorously treated. Thermal boundary conditions at the surfaces, including heat dissipation through the metal to the ambient, are incorporated. Numerical examples are presented comparing the predictions using this procedure with earlier theoretical predictions and experimental data. With a few points across the film thickness and across the journal and the bearing in the radial direction, the temperature profile is very well predicted.
Cloud computing approaches for prediction of ligand binding poses and pathways.

PubMed

Lawrenz, Morgan; Shukla, Diwakar; Pande, Vijay S

2015-01-22

We describe an innovative protocol for ab initio prediction of ligand crystallographic binding poses and highly effective analysis of large datasets generated for protein-ligand dynamics. We include a procedure for setup and performance of distributed molecular dynamics simulations on cloud computing architectures, a model for efficient analysis of simulation data, and a metric for evaluation of model convergence. We give accurate binding pose predictions for five ligands ranging in affinity from 7 nM to > 200 μM for the immunophilin protein FKBP12, for expedited results in cases where experimental structures are difficult to produce. Our approach goes beyond single, low energy ligand poses to give quantitative kinetic information that can inform protein engineering and ligand design.
A Model of BGA Thermal Fatigue Life Prediction Considering Load Sequence Effects

PubMed Central

Hu, Weiwei; Li, Yaqiu; Sun, Yufeng; Mosleh, Ali

2016-01-01

Accurate testing history data is necessary for all fatigue life prediction approaches, but such data is always deficient especially for the microelectronic devices. Additionally, the sequence of the individual load cycle plays an important role in physical fatigue damage. However, most of the existing models based on the linear damage accumulation rule ignore the sequence effects. This paper proposes a thermal fatigue life prediction model for ball grid array (BGA) packages to take into consideration the load sequence effects. For the purpose of improving the availability and accessibility of testing data, a new failure criterion is discussed and verified by simulation and experimentation. The consequences for the fatigue underlying sequence load conditions are shown. PMID:28773980
Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

NASA Technical Reports Server (NTRS)

Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

2011-01-01

A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.
An accurate ab initio quartic force field for ammonia

NASA Technical Reports Server (NTRS)

Martin, J. M. L.; Lee, Timothy J.; Taylor, Peter R.

1992-01-01

The quartic force field of ammonia is computed using basis sets of spdf/spd and spdfg/spdf quality and an augmented coupled cluster method. After correcting for Fermi resonance, the computed fundamentals and nu 4 overtones agree on average to better than 3/cm with the experimental ones except for nu 2. The discrepancy for nu 2 is principally due to higher-order anharmonicity effects. The computed omega 1, omega 3, and omega 4 confirm the recent experimental determination by Lehmann and Coy (1988) but are associated with smaller error bars. The discrepancy between the computed and experimental omega 2 is far outside the expected error range, which is also attributed to higher-order anharmonicity effects not accounted for in the experimental determination. Spectroscopic constants are predicted for a number of symmetric and asymmetric top isotopomers of NH3.
Testing and Analysis of NEXT Ion Engine Discharge Cathode Assembly Wear

NASA Technical Reports Server (NTRS)

Domonkos, Matthew T.; Foster, John E.; Soulas, George C.; Nakles, Michael

2003-01-01

Experimental and analytical investigations were conducted to predict the wear of the discharge cathode keeper in the NASA Evolutionary Xenon Thruster. The ion current to the keeper was found to be highly dependent upon the beam current, and the average beam current density was nearly identical to that of the NSTAR thruster for comparable beam current density. The ion current distribution was highly peaked toward the keeper orifice. A deterministic wear assessment predicted keeper orifice erosion to the same diameter as the cathode tube after processing 375 kg of xenon. A rough estimate of discharge cathode assembly life limit due to sputtering indicated that the current design exceeds the qualification goal of 405 kg. Probabilistic wear analysis showed that the plasma potential and the sputter yield contributed most to the uncertainty in the wear assessment. It was recommended that fundamental experimental and modeling efforts focus on accurately describing the plasma potential and the sputtering yield.
Modeling the Hydration Layer around Proteins: Applications to Small- and Wide-Angle X-Ray Scattering

PubMed Central

Virtanen, Jouko Juhani; Makowski, Lee; Sosnick, Tobin R.; Freed, Karl F.

2011-01-01

Small-/wide-angle x-ray scattering (SWAXS) experiments can aid in determining the structures of proteins and protein complexes, but success requires accurate computational treatment of solvation. We compare two methods by which to calculate SWAXS patterns. The first approach uses all-atom explicit-solvent molecular dynamics (MD) simulations. The second, far less computationally expensive method involves prediction of the hydration density around a protein using our new HyPred solvation model, which is applied without the need for additional MD simulations. The SWAXS patterns obtained from the HyPred model compare well to both experimental data and the patterns predicted by the MD simulations. Both approaches exhibit advantages over existing methods for analyzing SWAXS data. The close correspondence between calculated and observed SWAXS patterns provides strong experimental support for the description of hydration implicit in the HyPred model. PMID:22004761
Solution x-ray scattering and structure formation in protein dynamics

NASA Astrophysics Data System (ADS)

Nasedkin, Alexandr; Davidsson, Jan; Niemi, Antti J.; Peng, Xubiao

2017-12-01

We propose a computationally effective approach that builds on Landau mean-field theory in combination with modern nonequilibrium statistical mechanics to model and interpret protein dynamics and structure formation in small- to wide-angle x-ray scattering (S/WAXS) experiments. We develop the methodology by analyzing experimental data in the case of Engrailed homeodomain protein as an example. We demonstrate how to interpret S/WAXS data qualitatively with a good precision and over an extended temperature range. We explain experimental observations in terms of protein phase structure, and we make predictions for future experiments and for how to analyze data at different ambient temperature values. We conclude that the approach we propose has the potential to become a highly accurate, computationally effective, and predictive tool for analyzing S/WAXS data. For this, we compare our results with those obtained previously in an all-atom molecular dynamics simulation.
Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training Sets.

PubMed

Valenzuela, Loreto M; Knight, Doyle D; Kohn, Joachim

2016-01-01

Prediction of the dynamic properties of water uptake across polymer libraries can accelerate polymer selection for a specific application. We first built semiempirical models using Artificial Neural Networks and all water uptake data, as individual input. These models give very good correlations (R (2) > 0.78 for test set) but very low accuracy on cross-validation sets (less than 19% of experimental points within experimental error). Instead, using consolidated parameters like equilibrium water uptake a good model is obtained (R (2) = 0.78 for test set), with accurate predictions for 50% of tested polymers. The semiempirical model was applied to the 56-polymer library of L-tyrosine-derived polyarylates, identifying groups of polymers that are likely to satisfy design criteria for water uptake. This research demonstrates that a surrogate modeling effort can reduce the number of polymers that must be synthesized and characterized to identify an appropriate polymer that meets certain performance criteria.
Acoustic impedance of micro perforated membranes: Velocity continuity condition at the perforation boundary.

PubMed

Li, Chenxi; Cazzolato, Ben; Zander, Anthony

2016-01-01

The classic analytical model for the sound absorption of micro perforated materials is well developed and is based on a boundary condition where the velocity of the material is assumed to be zero, which is accurate when the material vibration is negligible. This paper develops an analytical model for finite-sized circular micro perforated membranes (MPMs) by applying a boundary condition such that the velocity of air particles on the hole wall boundary is equal to the membrane vibration velocity (a zero-slip condition). The acoustic impedance of the perforation, which varies with its position, is investigated. A prediction method for the overall impedance of the holes and the combined impedance of the MPM is also provided. The experimental results for four different MPM configurations are used to validate the model and good agreement between the experimental and predicted results is achieved.
Comparison of Aircraft Icing Growth Assessment Software

NASA Technical Reports Server (NTRS)

Wright, William; Potapczuk, Mark G.; Levinson, Laurie H.

2011-01-01

A research project is underway to produce computer software that can accurately predict ice growth under any meteorological conditions for any aircraft surface. An extensive comparison of the results in a quantifiable manner against the database of ice shapes that have been generated in the NASA Glenn Icing Research Tunnel (IRT) has been performed, including additional data taken to extend the database in the Super-cooled Large Drop (SLD) regime. The project shows the differences in ice shape between LEWICE 3.2.2, GlennICE, and experimental data. The project addresses the validation of the software against a recent set of ice-shape data in the SLD regime. This validation effort mirrors a similar effort undertaken for previous validations of LEWICE. Those reports quantified the ice accretion prediction capabilities of the LEWICE software. Several ice geometry features were proposed for comparing ice shapes in a quantitative manner. The resulting analysis showed that LEWICE compared well to the available experimental data.
Studies of turbulence models in a computational fluid dynamics model of a blood pump.

PubMed

Song, Xinwei; Wood, Houston G; Day, Steven W; Olsen, Don B

2003-10-01

Computational fluid dynamics (CFD) is used widely in design of rotary blood pumps. The choice of turbulence model is not obvious and plays an important role on the accuracy of CFD predictions. TASCflow (ANSYS Inc., Canonsburg, PA, U.S.A.) has been used to perform CFD simulations of blood flow in a centrifugal left ventricular assist device; a k-epsilon model with near-wall functions was used in the initial numerical calculation. To improve the simulation, local grids with special distribution to ensure the k-omega model were used. Iterations have been performed to optimize the grid distribution and turbulence modeling and to predict flow performance more accurately comparing to experimental data. A comparison of k-omega model and experimental measurements of the flow field obtained by particle image velocimetry shows better agreement than k-epsilon model does, especially in the near-wall regions.
The extrudate swell of HDPE: Rheological effects

NASA Astrophysics Data System (ADS)

Konaganti, Vinod Kumar; Ansari, Mahmoud; Mitsoulis, Evan; Hatzikiriakos, Savvas G.

2017-05-01

The extrudate swell of an industrial grade high molecular weight high-density polyethylene (HDPE) in capillary dies is studied experimentally and numerically using the integral K-BKZ constitutive model. The non-linear viscoelastic flow properties of the polymer resin are studied for a broad range of large step shear strains and high shear rates using the cone partitioned plate (CPP) geometry of the stress/strain controlled rotational rheometer. This allowed the determination of the rheological parameters accurately, in particular the damping function, which is proven to be the most important in simulating transient flows such as extrudate swell. A series of simulations performed using the integral K-BKZ Wagner model with different values of the Wagner exponent n, ranging from n=0.15 to 0.5, demonstrates that the extrudate swell predictions are extremely sensitive to the Wagner damping function exponent. Using the correct n-value resulted in extrudate swell predictions that are in excellent agreement with experimental measurements.
Molecular dynamics simulations and docking enable to explore the biophysical factors controlling the yields of engineered nanobodies.

PubMed

Soler, Miguel A; de Marco, Ario; Fortuna, Sara

2016-10-10

Nanobodies (VHHs) have proved to be valuable substitutes of conventional antibodies for molecular recognition. Their small size represents a precious advantage for rational mutagenesis based on modelling. Here we address the problem of predicting how Camelidae nanobody sequences can tolerate mutations by developing a simulation protocol based on all-atom molecular dynamics and whole-molecule docking. The method was tested on two sets of nanobodies characterized experimentally for their biophysical features. One set contained point mutations introduced to humanize a wild type sequence, in the second the CDRs were swapped between single-domain frameworks with Camelidae and human hallmarks. The method resulted in accurate scoring approaches to predict experimental yields and enabled to identify the structural modifications induced by mutations. This work is a promising tool for the in silico development of single-domain antibodies and opens the opportunity to customize single functional domains of larger macromolecules.
Molecular dynamics simulations and docking enable to explore the biophysical factors controlling the yields of engineered nanobodies

NASA Astrophysics Data System (ADS)

Soler, Miguel A.; De Marco, Ario; Fortuna, Sara

2016-10-01

Nanobodies (VHHs) have proved to be valuable substitutes of conventional antibodies for molecular recognition. Their small size represents a precious advantage for rational mutagenesis based on modelling. Here we address the problem of predicting how Camelidae nanobody sequences can tolerate mutations by developing a simulation protocol based on all-atom molecular dynamics and whole-molecule docking. The method was tested on two sets of nanobodies characterized experimentally for their biophysical features. One set contained point mutations introduced to humanize a wild type sequence, in the second the CDRs were swapped between single-domain frameworks with Camelidae and human hallmarks. The method resulted in accurate scoring approaches to predict experimental yields and enabled to identify the structural modifications induced by mutations. This work is a promising tool for the in silico development of single-domain antibodies and opens the opportunity to customize single functional domains of larger macromolecules.
Food Antioxidants: Chemical Insights at the Molecular Level.

PubMed

Galano, Annia; Mazzone, Gloria; Alvarez-Diduk, Ruslán; Marino, Tiziana; Alvarez-Idaboy, J Raúl; Russo, Nino

2016-01-01

In this review, we briefly summarize the reliability of the density functional theory (DFT)-based methods to accurately predict the main antioxidant properties and the reaction mechanisms involved in the free radical-scavenging reactions of chemical compounds present in food. The analyzed properties are the bond dissociation energies, in particular those involving OH bonds, electron transfer enthalpies, adiabatic ionization potentials, and proton affinities. The reaction mechanisms are hydrogen-atom transfer, proton-coupled electron transfer, radical adduct formation, single electron transfer, sequential electron proton transfer, proton-loss electron transfer, and proton-loss hydrogen-atom transfer. Furthermore, the chelating ability of these compounds and its role in decreasing or inhibiting the oxidative stress induced by Fe(III) and Cu(II) are considered. Comparisons between theoretical and experimental data confirm that modern theoretical tools are not only able to explain controversial experimental facts but also to predict chemical behavior.

Application of Response Surface Methods To Determine Conditions for Optimal Genomic Prediction

PubMed Central

Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.

2017-01-01

An epistatic genetic architecture can have a significant impact on prediction accuracies of genomic prediction (GP) methods. Machine learning methods predict traits comprised of epistatic genetic architectures more accurately than statistical methods based on additive mixed linear models. The differences between these types of GP methods suggest a diagnostic for revealing genetic architectures underlying traits of interest. In addition to genetic architecture, the performance of GP methods may be influenced by the sample size of the training population, the number of QTL, and the proportion of phenotypic variability due to genotypic variability (heritability). Possible values for these factors and the number of combinations of the factor levels that influence the performance of GP methods can be large. Thus, efficient methods for identifying combinations of factor levels that produce most accurate GPs is needed. Herein, we employ response surface methods (RSMs) to find the experimental conditions that produce the most accurate GPs. We illustrate RSM with an example of simulated doubled haploid populations and identify the combination of factors that maximize the difference between prediction accuracies of best linear unbiased prediction (BLUP) and support vector machine (SVM) GP methods. The greatest impact on the response is due to the genetic architecture of the population, heritability of the trait, and the sample size. When epistasis is responsible for all of the genotypic variance and heritability is equal to one and the sample size of the training population is large, the advantage of using the SVM method vs. the BLUP method is greatest. However, except for values close to the maximum, most of the response surface shows little difference between the methods. We also determined that the conditions resulting in the greatest prediction accuracy for BLUP occurred when genetic architecture consists solely of additive effects, and heritability is equal to one. PMID:28720710
Broadband impedance boundary conditions for the simulation of sound propagation in the time domain.

PubMed

Bin, Jonghoon; Yousuff Hussaini, M; Lee, Soogab

2009-02-01

An accurate and practical surface impedance boundary condition in the time domain has been developed for application to broadband-frequency simulation in aeroacoustic problems. To show the capability of this method, two kinds of numerical simulations are performed and compared with the analytical/experimental results: one is acoustic wave reflection by a monopole source over an impedance surface and the other is acoustic wave propagation in a duct with a finite impedance wall. Both single-frequency and broadband-frequency simulations are performed within the framework of linearized Euler equations. A high-order dispersion-relation-preserving finite-difference method and a low-dissipation, low-dispersion Runge-Kutta method are used for spatial discretization and time integration, respectively. The results show excellent agreement with the analytical/experimental results at various frequencies. The method accurately predicts both the amplitude and the phase of acoustic pressure and ensures the well-posedness of the broadband time-domain impedance boundary condition.
An inverse method for determining the spatially resolved properties of viscoelastic–viscoplastic three-dimensional printed materials

PubMed Central

Chen, X.; Ashcroft, I. A.; Wildman, R. D.; Tuck, C. J.

2015-01-01

A method using experimental nanoindentation and inverse finite-element analysis (FEA) has been developed that enables the spatial variation of material constitutive properties to be accurately determined. The method was used to measure property variation in a three-dimensional printed (3DP) polymeric material. The accuracy of the method is dependent on the applicability of the constitutive model used in the inverse FEA, hence four potential material models: viscoelastic, viscoelastic–viscoplastic, nonlinear viscoelastic and nonlinear viscoelastic–viscoplastic were evaluated, with the latter enabling the best fit to experimental data. Significant changes in material properties were seen in the depth direction of the 3DP sample, which could be linked to the degree of cross-linking within the material, a feature inherent in a UV-cured layer-by-layer construction method. It is proposed that the method is a powerful tool in the analysis of manufacturing processes with potential spatial property variation that will also enable the accurate prediction of final manufactured part performance. PMID:26730216
Systematic bioinformatics and experimental validation of yeast complexes reduces the rate of attrition during structural investigations.

PubMed

Brooks, Mark A; Gewartowski, Kamil; Mitsiki, Eirini; Létoquart, Juliette; Pache, Roland A; Billier, Ysaline; Bertero, Michela; Corréa, Margot; Czarnocki-Cieciura, Mariusz; Dadlez, Michal; Henriot, Véronique; Lazar, Noureddine; Delbos, Lila; Lebert, Dorothée; Piwowarski, Jan; Rochaix, Pascal; Böttcher, Bettina; Serrano, Luis; Séraphin, Bertrand; van Tilbeurgh, Herman; Aloy, Patrick; Perrakis, Anastassis; Dziembowski, Andrzej

2010-09-08

For high-throughput structural studies of protein complexes of composition inferred from proteomics data, it is crucial that candidate complexes are selected accurately. Herein, we exemplify a procedure that combines a bioinformatics tool for complex selection with in vivo validation, to deliver structural results in a medium-throughout manner. We have selected a set of 20 yeast complexes, which were predicted to be feasible by either an automated bioinformatics algorithm, by manual inspection of primary data, or by literature searches. These complexes were validated with two straightforward and efficient biochemical assays, and heterologous expression technologies of complex components were then used to produce the complexes to assess their feasibility experimentally. Approximately one-half of the selected complexes were useful for structural studies, and we detail one particular success story. Our results underscore the importance of accurate target selection and validation in avoiding transient, unstable, or simply nonexistent complexes from the outset. Copyright © 2010 Elsevier Ltd. All rights reserved.
An inverse method for determining the spatially resolved properties of viscoelastic-viscoplastic three-dimensional printed materials.

PubMed

Chen, X; Ashcroft, I A; Wildman, R D; Tuck, C J

2015-11-08

A method using experimental nanoindentation and inverse finite-element analysis (FEA) has been developed that enables the spatial variation of material constitutive properties to be accurately determined. The method was used to measure property variation in a three-dimensional printed (3DP) polymeric material. The accuracy of the method is dependent on the applicability of the constitutive model used in the inverse FEA, hence four potential material models: viscoelastic, viscoelastic-viscoplastic, nonlinear viscoelastic and nonlinear viscoelastic-viscoplastic were evaluated, with the latter enabling the best fit to experimental data. Significant changes in material properties were seen in the depth direction of the 3DP sample, which could be linked to the degree of cross-linking within the material, a feature inherent in a UV-cured layer-by-layer construction method. It is proposed that the method is a powerful tool in the analysis of manufacturing processes with potential spatial property variation that will also enable the accurate prediction of final manufactured part performance.
A study of hydrogen diffusion flames using PDF turbulence model

NASA Technical Reports Server (NTRS)

Hsu, Andrew T.

1991-01-01

The application of probability density function (pdf) turbulence models is addressed. For the purpose of accurate prediction of turbulent combustion, an algorithm that combines a conventional computational fluid dynamic (CFD) flow solver with the Monte Carlo simulation of the pdf evolution equation was developed. The algorithm was validated using experimental data for a heated turbulent plane jet. The study of H2-F2 diffusion flames was carried out using this algorithm. Numerical results compared favorably with experimental data. The computations show that the flame center shifts as the equivalence ratio changes, and that for the same equivalence ratio, similarity solutions for flames exist.
A study of hydrogen diffusion flames using PDF turbulence model

NASA Technical Reports Server (NTRS)

Hsu, Andrew T.

1991-01-01

The application of probability density function (pdf) turbulence models is addressed in this work. For the purpose of accurate prediction of turbulent combustion, an algorithm that combines a conventional CFD flow solver with the Monte Carlo simulation of the pdf evolution equation has been developed. The algorithm has been validated using experimental data for a heated turbulent plane jet. The study of H2-F2 diffusion flames has been carried out using this algorithm. Numerical results compared favorably with experimental data. The computuations show that the flame center shifts as the equivalence ratio changes, and that for the same equivalence ratio, similarity solutions for flames exist.
Do nuclear collisions create a locally equilibrated quark–gluon plasma?

DOE PAGES

Romatschke, P.

2017-01-10

Experimental results on azimuthal correlations in high energy nuclear collisions (nucleus–nucleus, proton–nucleus, and proton–proton) seem to be well described by viscous hydrodynamics. It is often argued that this agreement implies either local thermal equilibrium or at least local isotropy. In this note, I present arguments why this is not the case. Neither local near-equilibrium nor near-isotropy are required in order for hydrodynamics to offer a successful and accurate description of experimental results. However, I predict the breakdown of hydrodynamics at momenta of order seven times the temperature, corresponding to a smallest possible QCD liquid drop size of 0.15 fm.
Supersymmetry and Kaon physics

NASA Astrophysics Data System (ADS)

Yamamoto, Kei

2017-01-01

Kaon physics has played an essential role in testing the Standard Model and in searching for new physics with measurements of CP violation and rare decays. Current progress of lattice calculations enables us to predict kaon observables accurately, especially for the direct CP violation, ε‧/ε, and there is a discrepancy from the experimental data at the 2.9 σ level. On the experimental side, the rare kaon decays and are ongoing to be measured at the SM accuracy by KOTO at J-PARC and NA62 at CERN. These kaon observables are good probes for new physics. We study supersymmetric effects; the chargino and gluino contributions to Z penguin, in kaon observables.
Single-shot temporal characterization of kilojoule-level, picosecond pulses on OMEGA EP

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

Waxer, Leon; Dorrer, Christophe; Kalb, Adam

To achieve a variety of experimental conditions, the OMEGA EP laser provides kilojoule-level pulses over a pulse-width range of 0.6 to 100 ps. Precise knowledge of the pulse width is important for laser system safety and the interpretation of experimental results. This paper describes the development and implementation of a single-shot, ultrashort-pulse measurement diagnostic, which provides an accurate characterization of the output pulse shape. We also present a brief overview of the measurement algorithm; discuss design considerations necessary for implementation in a complex, user-facility environment; and review the results of the diagnostic commissioning shots, which demonstrated excellent agreement with predictions.
Single-shot temporal characterization of kilojoule-level, picosecond pulses on OMEGA EP

DOE PAGES

Waxer, Leon; Dorrer, Christophe; Kalb, Adam; ...

2018-02-19

To achieve a variety of experimental conditions, the OMEGA EP laser provides kilojoule-level pulses over a pulse-width range of 0.6 to 100 ps. Precise knowledge of the pulse width is important for laser system safety and the interpretation of experimental results. This paper describes the development and implementation of a single-shot, ultrashort-pulse measurement diagnostic, which provides an accurate characterization of the output pulse shape. We also present a brief overview of the measurement algorithm; discuss design considerations necessary for implementation in a complex, user-facility environment; and review the results of the diagnostic commissioning shots, which demonstrated excellent agreement with predictions.
A new approach to modeling the effective thermal conductivity of ceramics porous media using a generalized self-consistent method

NASA Astrophysics Data System (ADS)

Edrisi, Siroos; Bidhendi, Norollah Kasiri; Haghighi, Maryam

2017-01-01

Effective thermal conductivity of the porous media was modeled based on a self-consistent method. This model estimates the heat transfer between insulator surface and air cavities accurately. In this method, the pore size and shape, the temperature gradient and other thermodynamic properties of the fluid was taken into consideration. The results are validated by experimental data for fire bricks used in cracking furnaces at the olefin plant of Maroon petrochemical complexes well as data published for polyurethane foam (synthetic polymers) IPTM and IPM. The model predictions present a good agreement against experimental data with thermal conductivity deviating <1 %.
Predicting the bending properties of long bones: Insights from an experimental mouse model.

PubMed

Peacock, Sarah J; Coats, Brittney R; Kirkland, J Kyle; Tanner, Courtney A; Garland, Theodore; Middleton, Kevin M

2018-03-01

Analyses of bone cross-sectional geometry are frequently used by anthropologists and paleontologists to infer the loading histories of past populations. To address some underlying assumptions, we investigated the relative roles of genetics and exercise on bone cross-sectional geometry and bending mechanics in three mouse strains: high bone density (C3H/He), low bone density (C57BL/6), and a high-runner strain homozygous for the Myh4 Minimsc allele (MM). Weanlings of each strain were divided into exercise (wheel) or control (sedentary) treatment groups for a 7-week experimental period. Morphometrics of the femoral mid-diaphysis and mechanical testing were used to assess both theoretical and ex vivo bending mechanics. Across all measured morphological and bending traits, we found relatively small effects of exercise treatment compared to larger and more frequent interstrain differences. In the exercised group, total distance run over the experimental period was not a predictor of any morphological or bending traits. Cross-sectional geometry did not accurately predict bone response to loading. Results from this experimental model do not support hypothesized associations among extreme exercise, cross-sectional geometry, and bending mechanics. Our results suggest that analysis of cross-sectional geometry alone is insufficient to predict loading response, and questions the common assumption that cross-sectional geometry differences are indicative of differential loading history. © 2017 Wiley Periodicals, Inc.
Optimal rates for phylogenetic inference and experimental design in the era of genome-scale datasets.

PubMed

Dornburg, Alex; Su, Zhuo; Townsend, Jeffrey P

2018-06-25

With the rise of genome- scale datasets there has been a call for increased data scrutiny and careful selection of loci appropriate for attempting the resolution of a phylogenetic problem. Such loci are desired to maximize phylogenetic information content while minimizing the risk of homoplasy. Theory posits the existence of characters that evolve under such an optimum rate, and efforts to determine optimal rates of inference have been a cornerstone of phylogenetic experimental design for over two decades. However, both theoretical and empirical investigations of optimal rates have varied dramatically in their conclusions: spanning no relationship to a tight relationship between the rate of change and phylogenetic utility. Here we synthesize these apparently contradictory views, demonstrating both empirical and theoretical conditions under which each is correct. We find that optimal rates of characters-not genes-are generally robust to most experimental design decisions. Moreover, consideration of site rate heterogeneity within a given locus is critical to accurate predictions of utility. Factors such as taxon sampling or the targeted number of characters providing support for a topology are additionally critical to the predictions of phylogenetic utility based on the rate of character change. Further, optimality of rates and predictions of phylogenetic utility are not equivalent, demonstrating the need for further development of comprehensive theory of phylogenetic experimental design.
The Shock and Vibration Bulletin. Part 1. Welcome, Keynote Address, Invited Papers, Pyrotechnic Shock, and Shock Testing and Analysis

DTIC Science & Technology

1983-05-01

DESIGN PROCEDURE M. S. IIAndal, University of Vermont, Burlington, VT Machinery Dynamics ANALYTICAL AND EXPERIMENTAL INVESTIGATION OF ROTATING BLADE... methodology to accurately predict rotor vibratory loads and has recently been initiated for detail design and bench test- coupled rotor/airframe vibrations... design methodology , a trating on the basic disciplines of aerodynamics and struc. coupled rotor/airframe vibration analysis has been developed. tural
Information Processing and Collective Behavior in a Model Neuronal System

DTIC Science & Technology

2014-03-28

for an AFOSR project headed by Steve Reppert on Monarch Butterfly navigation. We visited the Reppert lab at the UMASS Medical School and have had many...developed a detailed mathematical model of the mammalian circadian clock. Our model can accurately predict diverse experimental data including the...i.e. P1 affects P2 which affects P3 …). The output of the system is calculated (measurements), and the interactions are forgotten. Based on
Adaptive control of the packet transmission period with solar energy harvesting prediction in wireless sensor networks.

PubMed

Kwon, Kideok; Yang, Jihoon; Yoo, Younghwan

2015-04-24

A number of research works has studied packet scheduling policies in energy scavenging wireless sensor networks, based on the predicted amount of harvested energy. Most of them aim to achieve energy neutrality, which means that an embedded system can operate perpetually while meeting application requirements. Unlike other renewable energy sources, solar energy has the feature of distinct periodicity in the amount of harvested energy over a day. Using this feature, this paper proposes a packet transmission control policy that can enhance the network performance while keeping sensor nodes alive. Furthermore, this paper suggests a novel solar energy prediction method that exploits the relation between cloudiness and solar radiation. The experimental results and analyses show that the proposed packet transmission policy outperforms others in terms of the deadline miss rate and data throughput. Furthermore, the proposed solar energy prediction method can predict more accurately than others by 6.92%.
A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.
Beam-column joint shear prediction using hybridized deep learning neural network with genetic algorithm

NASA Astrophysics Data System (ADS)

Mundher Yaseen, Zaher; Abdulmohsin Afan, Haitham; Tran, Minh-Tung

2018-04-01

Scientifically evidenced that beam-column joints are a critical point in the reinforced concrete (RC) structure under the fluctuation loads effects. In this novel hybrid data-intelligence model developed to predict the joint shear behavior of exterior beam-column structure frame. The hybrid data-intelligence model is called genetic algorithm integrated with deep learning neural network model (GA-DLNN). The genetic algorithm is used as prior modelling phase for the input approximation whereas the DLNN predictive model is used for the prediction phase. To demonstrate this structural problem, experimental data is collected from the literature that defined the dimensional and specimens’ properties. The attained findings evidenced the efficitveness of the hybrid GA-DLNN in modelling beam-column joint shear problem. In addition, the accurate prediction achived with less input variables owing to the feasibility of the evolutionary phase.
Predicting Microstructure and Microsegregation in Multicomponent Aluminum Alloys

NASA Astrophysics Data System (ADS)

Yan, Xinyan; Ding, Ling; Chen, ShuangLin; Xie, Fanyou; Chu, M.; Chang, Y. Austin

Accurate predictions of microstructure and microsegregation in metallic alloys are highly important for applications such as alloy design and process optimization. Restricted assumptions concerning the phase diagram could easily lead to erroneous predictions. The best approach is to couple microsegregation modeling with phase diagram computations. A newly developed numerical model for the prediction of microstructure and microsegregation in multicomponent alloys during dendritic solidification was introduced. The micromodel is directly coupled with phase diagram calculations using a user-friendly and robust phase diagram calculation engine-PANDAT. Solid state back diffusion, undercooling and coarsening effects are included in this model, and the experimentally measured cooling curves are used as the inputs to carry out the calculations. This model has been used to predict the microstructure and microsegregation in two multicomponent aluminum alloys, 2219 and 7050. The calculated values were confirmed using results obtained from directional solidification.

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.
Predicting the crystalline and porous equations of state for secondary explosives

NASA Astrophysics Data System (ADS)

Wixom, Ryan; Damm, David

2013-06-01

Accurate simulations of energetic material response necessitate accurate unreacted equations of state at pressures much higher than even the C-J state. Unfortunately, for reactive materials, experimental data at high pressures may be unattainable, and extrapolation from low-pressure data results in unacceptable uncertainty. In addition to being low-pressure, the available data is typically limited to the porous state. The fully-dense, or crystalline, equation of state is required for building mesoscale simulations of the dynamic response of energetic materials. We have used quantum molecular dynamics to predict the Hugoniots and 300 K isotherms of crystalline PETN, HNS, CL-20 and TATB up to pressures not attainable in experiments. The porous Hugoniots for these materials were then analytically obtained and are validated by comparison with available data. Our calculations for TATB confirm the presence of a kink in the Hugoniot, and the softening of the shock response is explained in terms of a change in molecular conformation and the loss of aromaticity.
Calculation of electromagnetic force in electromagnetic forming process of metal sheet

NASA Astrophysics Data System (ADS)

Xu, Da; Liu, Xuesong; Fang, Kun; Fang, Hongyuan

2010-06-01

Electromagnetic forming (EMF) is a forming process that relies on the inductive electromagnetic force to deform metallic workpiece at high speed. Calculation of the electromagnetic force is essential to understand the EMF process. However, accurate calculation requires complex numerical solution, in which the coupling between the electromagnetic process and the deformation of workpiece needs be considered. In this paper, an appropriate formula has been developed to calculate the electromagnetic force in metal work-piece in the sheet EMF process. The effects of the geometric size of coil, the material properties, and the parameters of discharge circuit on electromagnetic force are taken into consideration. Through the formula, the electromagnetic force at different time and in different positions of the workpiece can be predicted. The calculated electromagnetic force and magnetic field are in good agreement with the numerical and experimental results. The accurate prediction of the electromagnetic force provides an insight into the physical process of the EMF and a powerful tool to design optimum EMF systems.
New strategy for protein interactions and application to structure-based drug design

NASA Astrophysics Data System (ADS)

Zou, Xiaoqin

One of the greatest challenges in computational biophysics is to predict interactions between biological molecules, which play critical roles in biological processes and rational design of therapeutic drugs. Biomolecular interactions involve delicate interplay between multiple interactions, including electrostatic interactions, van der Waals interactions, solvent effect, and conformational entropic effect. Accurate determination of these complex and subtle interactions is challenging. Moreover, a biological molecule such as a protein usually consists of thousands of atoms, and thus occupies a huge conformational space. The large degrees of freedom pose further challenges for accurate prediction of biomolecular interactions. Here, I will present our development of physics-based theory and computational modeling on protein interactions with other molecules. The major strategy is to extract microscopic energetics from the information embedded in the experimentally-determined structures of protein complexes. I will also present applications of the methods to structure-based therapeutic design. Supported by NSF CAREER Award DBI-0953839, NIH R01GM109980, and the American Heart Association (Midwest Affiliate) [13GRNT16990076].
Numerical analysis of moving contact line with contact angle hysteresis using feedback deceleration technique

NASA Astrophysics Data System (ADS)

Park, Jun Kwon; Kang, Kwan Hyoung

2012-04-01

Contact angle (CA) hysteresis is important in many natural and engineering wetting processes, but predicting it numerically is difficult. We developed an algorithm that considers CA hysteresis when analyzing the motion of the contact line (CL). This algorithm employs feedback control of CA which decelerates CL speed to make the CL stationary in the hysteretic range of CA, and one control coefficient should be heuristically determined depending on characteristic time of the simulated system. The algorithm requires embedding only a simple additional routine with little modification of a code which considers the dynamic CA. The method is non-iterative and explicit, and also has less computational load than other algorithms. For a drop hanging on a wire, the proposed algorithm accurately predicts the theoretical equilibrium CA. For the drop impacting on a dry surface, the results of the proposed algorithm agree well with experimental results including the intermittent occurrence of the pinning of CL. The proposed algorithm is as accurate as other algorithms, but faster.
A novel phenomenological multi-physics model of Li-ion battery cells

NASA Astrophysics Data System (ADS)

Oh, Ki-Yong; Samad, Nassim A.; Kim, Youngki; Siegel, Jason B.; Stefanopoulou, Anna G.; Epureanu, Bogdan I.

2016-09-01

A novel phenomenological multi-physics model of Lithium-ion battery cells is developed for control and state estimation purposes. The model can capture electrical, thermal, and mechanical behaviors of battery cells under constrained conditions, e.g., battery pack conditions. Specifically, the proposed model predicts the core and surface temperatures and reaction force induced from the volume change of battery cells because of electrochemically- and thermally-induced swelling. Moreover, the model incorporates the influences of changes in preload and ambient temperature on the force considering severe environmental conditions electrified vehicles face. Intensive experimental validation demonstrates that the proposed multi-physics model accurately predicts the surface temperature and reaction force for a wide operational range of preload and ambient temperature. This high fidelity model can be useful for more accurate and robust state of charge estimation considering the complex dynamic behaviors of the battery cell. Furthermore, the inherent simplicity of the mechanical measurements offers distinct advantages to improve the existing power and thermal management strategies for battery management.
Development and experimental validation of computational methods to simulate abnormal thermal and structural environments

NASA Astrophysics Data System (ADS)

Moya, J. L.; Skocypec, R. D.; Thomas, R. K.

1993-09-01

Over the past 40 years, Sandia National Laboratories (SNL) has been actively engaged in research to improve the ability to accurately predict the response of engineered systems to abnormal thermal and structural environments. These engineered systems contain very hazardous materials. Assessing the degree of safety/risk afforded the public and environment by these engineered systems, therefore, is of upmost importance. The ability to accurately predict the response of these systems to accidents (to abnormal environments) is required to assess the degree of safety. Before the effect of the abnormal environment on these systems can be determined, it is necessary to ascertain the nature of the environment. Ascertaining the nature of the environment, in turn, requires the ability to physically characterize and numerically simulate the abnormal environment. Historically, SNL has demonstrated the level of safety provided by these engineered systems by either of two approaches: a purely regulatory approach, or by a probabilistic risk assessment (PRA). This paper will address the latter of the two approaches.
Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs.

PubMed

De Buck, Stefan S; Sinha, Vikash K; Fenu, Luca A; Nijsen, Marjoleen J; Mackie, Claire E; Gilissen, Ron A H J

2007-10-01

The aim of this study was to evaluate different physiologically based modeling strategies for the prediction of human pharmacokinetics. Plasma profiles after intravenous and oral dosing were simulated for 26 clinically tested drugs. Two mechanism-based predictions of human tissue-to-plasma partitioning (P(tp)) from physicochemical input (method Vd1) were evaluated for their ability to describe human volume of distribution at steady state (V(ss)). This method was compared with a strategy that combined predicted and experimentally determined in vivo rat P(tp) data (method Vd2). Best V(ss) predictions were obtained using method Vd2, providing that rat P(tp) input was corrected for interspecies differences in plasma protein binding (84% within 2-fold). V(ss) predictions from physicochemical input alone were poor (32% within 2-fold). Total body clearance (CL) was predicted as the sum of scaled rat renal clearance and hepatic clearance projected from in vitro metabolism data. Best CL predictions were obtained by disregarding both blood and microsomal or hepatocyte binding (method CL2, 74% within 2-fold), whereas strong bias was seen using both blood and microsomal or hepatocyte binding (method CL1, 53% within 2-fold). The physiologically based pharmacokinetics (PBPK) model, which combined methods Vd2 and CL2 yielded the most accurate predictions of in vivo terminal half-life (69% within 2-fold). The Gastroplus advanced compartmental absorption and transit model was used to construct an absorption-disposition model and provided accurate predictions of area under the plasma concentration-time profile, oral apparent volume of distribution, and maximum plasma concentration after oral dosing, with 74%, 70%, and 65% within 2-fold, respectively. This evaluation demonstrates that PBPK models can lead to reasonable predictions of human pharmacokinetics.
Genomic prediction of piglet response to infection with one of two porcine reproductive and respiratory syndrome virus isolates.

PubMed

Waide, Emily H; Tuggle, Christopher K; Serão, Nick V L; Schroyen, Martine; Hess, Andrew; Rowland, Raymond R R; Lunney, Joan K; Plastow, Graham; Dekkers, Jack C M

2018-02-01

Genomic prediction of the pig's response to the porcine reproductive and respiratory syndrome (PRRS) virus (PRRSV) would be a useful tool in the swine industry. This study investigated the accuracy of genomic prediction based on porcine SNP60 Beadchip data using training and validation datasets from populations with different genetic backgrounds that were challenged with different PRRSV isolates. Genomic prediction accuracy averaged 0.34 for viral load (VL) and 0.23 for weight gain (WG) following experimental PRRSV challenge, which demonstrates that genomic selection could be used to improve response to PRRSV infection. Training on WG data during infection with a less virulent PRRSV, KS06, resulted in poor accuracy of prediction for WG during infection with a more virulent PRRSV, NVSL. Inclusion of single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium with a major quantitative trait locus (QTL) on chromosome 4 was vital for accurate prediction of VL. Overall, SNPs that were significantly associated with either trait in single SNP genome-wide association analysis were unable to predict the phenotypes with an accuracy as high as that obtained by using all genotyped SNPs across the genome. Inclusion of data from close relatives into the training population increased whole genome prediction accuracy by 33% for VL and by 37% for WG but did not affect the accuracy of prediction when using only SNPs in the major QTL region. Results show that genomic prediction of response to PRRSV infection is moderately accurate and, when using all SNPs on the porcine SNP60 Beadchip, is not very sensitive to differences in virulence of the PRRSV in training and validation populations. Including close relatives in the training population increased prediction accuracy when using the whole genome or SNPs other than those near a major QTL.
The equation of state of predominant detonation products

NASA Astrophysics Data System (ADS)

Zaug, Joseph; Crowhurst, Jonathan; Bastea, Sorin; Fried, Laurence

2009-06-01

The equation of state of detonation products, when incorporated into an experimentally grounded thermochemical reaction algorithm can be used to predict the performance of explosives. Here we report laser based Impulsive Stimulated Light Scattering measurements of the speed of sound from a variety of polar and nonpolar detonation product supercritical fluids and mixtures. The speed of sound data are used to improve the exponential-six potentials employed within the Cheetah thermochemical code. We will discuss the improvements made to Cheetah in terms of predictions vs. measured performance data for common polymer blended explosives. Accurately computing the chemistry that occurs from reacted binder materials is one important step forward in our efforts.
The influences of tip clearance on the performance of nozzle blades of radial turbines - Experiment and performance prediction at three nozzle angles

NASA Astrophysics Data System (ADS)

Hyun, Yong-Ik; Yamaguchi, Michiteru; Hayami, Hiroshi; Senoo, Yasutoshi

1988-05-01

In order to study the influence of tip clearance on the turning angle and pressure loss of turbine nozzles, experimental results were obtained for nozzle angles at which the throat area was 0.8 and 1.4 times the rated condition. Contour maps of the total pressure loss and of the spanwise distributions of the mean exit-flow angle have been obtained. Although the two-layer flow model of Senoo et al., (1987) is shown to accurately predict the effects of tip clearance, it underestimates the clearance effect for a lightly loaded condition.
3D Microstructures for Materials and Damage Models

DOE PAGES

Livescu, Veronica; Bronkhorst, Curt Allan; Vander Wiel, Scott Alan

2017-02-01

Many challenges exist with regard to understanding and representing complex physical processes involved with ductile damage and failure in polycrystalline metallic materials. Currently, the ability to accurately predict the macroscale ductile damage and failure response of metallic materials is lacking. Research at Los Alamos National Laboratory (LANL) is aimed at building a coupled experimental and computational methodology that supports the development of predictive damage capabilities by: capturing real distributions of microstructural features from real material and implementing them as digitally generated microstructures in damage model development; and, distilling structure-property information to link microstructural details to damage evolution under a multitudemore » of loading states.« less
Predictive model for CO2 generation and decay in building envelopes

NASA Astrophysics Data System (ADS)

Aglan, Heshmat A.

2003-01-01

Understanding carbon dioxide generation and decay patterns in buildings with high occupancy levels is useful to identify their indoor air quality, air change rates, percent fresh air makeup, occupancy pattern, and how a variable air volume system to off-set undesirable CO2 level can be modulated. A mathematical model governing the generation and decay of CO2 in building envelopes with forced ventilation due to high occupancy is developed. The model has been verified experimentally in a newly constructed energy efficient healthy house. It was shown that the model accurately predicts the CO2 concentration at any time during the generation and decay processes.
Model for compressible turbulence in hypersonic wall boundary and high-speed mixing layers

NASA Astrophysics Data System (ADS)

Bowersox, Rodney D. W.; Schetz, Joseph A.

1994-07-01

The most common approach to Navier-Stokes predictions of turbulent flows is based on either the classical Reynolds-or Favre-averaged Navier-Stokes equations or some combination. The main goal of the current work was to numerically assess the effects of the compressible turbulence terms that were experimentaly found to be important. The compressible apparent mass mixing length extension (CAMMLE) model, which was based on measured experimental data, was found to produce accurate predictions of the measured compressible turbulence data for both the wall bounded and free mixing layer. Hence, that model was incorporated into a finite volume Navier-Stokes code.
Modeling ultrasound propagation through material of increasing geometrical complexity.

PubMed

Odabaee, Maryam; Odabaee, Mostafa; Pelekanos, Matthew; Leinenga, Gerhard; Götz, Jürgen

2018-06-01

Ultrasound is increasingly being recognized as a neuromodulatory and therapeutic tool, inducing a broad range of bio-effects in the tissue of experimental animals and humans. To achieve these effects in a predictable manner in the human brain, the thick cancellous skull presents a problem, causing attenuation. In order to overcome this challenge, as a first step, the acoustic properties of a set of simple bone-modeling resin samples that displayed an increasing geometrical complexity (increasing step sizes) were analyzed. Using two Non-Destructive Testing (NDT) transducers, we found that Wiener deconvolution predicted the Ultrasound Acoustic Response (UAR) and attenuation caused by the samples. However, whereas the UAR of samples with step sizes larger than the wavelength could be accurately estimated, the prediction was not accurate when the sample had a smaller step size. Furthermore, a Finite Element Analysis (FEA) performed in ANSYS determined that the scattering and refraction of sound waves was significantly higher in complex samples with smaller step sizes compared to simple samples with a larger step size. Together, this reveals an interaction of frequency and geometrical complexity in predicting the UAR and attenuation. These findings could in future be applied to poro-visco-elastic materials that better model the human skull. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Precise calibration of few-cycle laser pulses with atomic hydrogen

NASA Astrophysics Data System (ADS)

Wallace, W. C.; Kielpinski, D.; Litvinyuk, I. V.; Sang, R. T.

2017-12-01

Interaction of atoms and molecules with strong electric fields is a fundamental process in many fields of research, particularly in the emerging field of attosecond science. Therefore, understanding the physics underpinning those interactions is of significant interest to the scientific community. One crucial step in this understanding is accurate knowledge of the few-cycle laser field driving the process. Atomic hydrogen (H), the simplest of all atomic species, plays a key role in benchmarking strong-field processes. Its wide-spread use as a testbed for theoretical calculations allows the comparison of approximate theoretical models against nearly-perfect numerical solutions of the three-dimensional time-dependent Schrödinger equation. Until recently, relatively little experimental data in atomic H was available for comparison to these models, and was due mostly due to the difficulty in the construction and use of atomic H sources. Here, we review our most recent experimental results from atomic H interaction with few-cycle laser pulses and how they have been used to calibrate important laser pulse parameters such as peak intensity and the carrier-envelope phase (CEP). Quantitative agreement between experimental data and theoretical predictions for atomic H has been obtained at the 10% uncertainty level, allowing for accurate laser calibration intensity at the 1% level. Using this calibration in atomic H, both accurate CEP data and an intensity calibration standard have been obtained Ar, Kr, and Xe; such gases are in common use for strong-field experiments. This calibration standard can be used by any laboratory using few-cycle pulses in the 1014 W cm-2 intensity regime centered at 800 nm wavelength to accurately calibrate their peak laser intensity to within few-percent precision.
Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments.

PubMed

Park, Hahnbeom; Lee, Gyu Rie; Heo, Lim; Seok, Chaok

2014-01-01

Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.
Improved Model for Predicting the Free Energy Contribution of Dinucleotide Bulges to RNA Duplex Stability.

PubMed

Tomcho, Jeremy C; Tillman, Magdalena R; Znosko, Brent M

2015-09-01

Predicting the secondary structure of RNA is an intermediate in predicting RNA three-dimensional structure. Commonly, determining RNA secondary structure from sequence uses free energy minimization and nearest neighbor parameters. Current algorithms utilize a sequence-independent model to predict free energy contributions of dinucleotide bulges. To determine if a sequence-dependent model would be more accurate, short RNA duplexes containing dinucleotide bulges with different sequences and nearest neighbor combinations were optically melted to derive thermodynamic parameters. These data suggested energy contributions of dinucleotide bulges were sequence-dependent, and a sequence-dependent model was derived. This model assigns free energy penalties based on the identity of nucleotides in the bulge (3.06 kcal/mol for two purines, 2.93 kcal/mol for two pyrimidines, 2.71 kcal/mol for 5'-purine-pyrimidine-3', and 2.41 kcal/mol for 5'-pyrimidine-purine-3'). The predictive model also includes a 0.45 kcal/mol penalty for an A-U pair adjacent to the bulge and a -0.28 kcal/mol bonus for a G-U pair adjacent to the bulge. The new sequence-dependent model results in predicted values within, on average, 0.17 kcal/mol of experimental values, a significant improvement over the sequence-independent model. This model and new experimental values can be incorporated into algorithms that predict RNA stability and secondary structure from sequence.
An Arrhenius-type viscosity function to model sintering using the Skorohod Olevsky viscous sintering model within a finite element code.

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

Ewsuk, Kevin Gregory; Arguello, Jose Guadalupe, Jr.; Reiterer, Markus W.

2006-02-01

The ease and ability to predict sintering shrinkage and densification with the Skorohod-Olevsky viscous sintering (SOVS) model within a finite-element (FE) code have been improved with the use of an Arrhenius-type viscosity function. The need for a better viscosity function was identified by evaluating SOVS model predictions made using a previously published polynomial viscosity function. Predictions made using the original, polynomial viscosity function do not accurately reflect experimentally observed sintering behavior. To more easily and better predict sintering behavior using FE simulations, a thermally activated viscosity function based on creep theory was used with the SOVS model. In comparison withmore » the polynomial viscosity function, SOVS model predictions made using the Arrhenius-type viscosity function are more representative of experimentally observed viscosity and sintering behavior. Additionally, the effects of changes in heating rate on densification can easily be predicted with the Arrhenius-type viscosity function. Another attribute of the Arrhenius-type viscosity function is that it provides the potential to link different sintering models. For example, the apparent activation energy, Q, for densification used in the construction of the master sintering curve for a low-temperature cofire ceramic dielectric has been used as the apparent activation energy for material flow in the Arrhenius-type viscosity function to predict heating rate-dependent sintering behavior using the SOVS model.« less
Experimental measurement of interparticle acoustic radiation force in the Rayleigh limit

NASA Astrophysics Data System (ADS)

Mohapatra, Abhishek Ray; Sepehrirahnama, Shahrokh; Lim, Kian-Meng

2018-05-01

Acoustophoresis is a form of contact-free particle manipulation in microfluidic devices. The precision of manipulation can be enhanced with better understanding of the acoustic radiation force. In this paper we present the measurements of interparticle radiation force between a pair of polystyrene beads in the Rayleigh limit. The study is conducted for three different sizes of beads and the experimental results are of the same order of magnitude when compared with theoretical predictions. However, the experimental values are larger than the theoretical values. The trend of a decrease in the magnitude of the interparticle radiation force with decreasing particle size and increasing center-to-center distance between the particles is also observed experimentally. The experiments are conducted in the specific scenario where the pair of beads are in close proximity, but not in contact with each other, and the beads are approaching the pressure nodal plane with the center-to-center line aligned perpendicular to the incident wave. This scenario minimizes the presence of the primary radiation force, allowing accurate measurement of the interparticle force. The attractive nature of the interparticle force is observed, consistent with theoretical predictions.

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