Joint probabilistic determination of earthquake location and velocity structure: application to local and regional events

NASA Astrophysics Data System (ADS)

Beucler, E.; Haugmard, M.; Mocquet, A.

2016-12-01

The most widely used inversion schemes to locate earthquakes are based on iterative linearized least-squares algorithms and using an a priori knowledge of the propagation medium. When a small amount of observations is available for moderate events for instance, these methods may lead to large trade-offs between outputs and both the velocity model and the initial set of hypocentral parameters. We present a joint structure-source determination approach using Bayesian inferences. Monte-Carlo continuous samplings, using Markov chains, generate models within a broad range of parameters, distributed according to the unknown posterior distributions. The non-linear exploration of both the seismic structure (velocity and thickness) and the source parameters relies on a fast forward problem using 1-D travel time computations. The a posteriori covariances between parameters (hypocentre depth, origin time and seismic structure among others) are computed and explicitly documented. This method manages to decrease the influence of the surrounding seismic network geometry (sparse and/or azimuthally inhomogeneous) and a too constrained velocity structure by inferring realistic distributions on hypocentral parameters. Our algorithm is successfully used to accurately locate events of the Armorican Massif (western France), which is characterized by moderate and apparently diffuse local seismicity.

Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model

NASA Astrophysics Data System (ADS)

Král, Petr; Hokeš, Filip; Hušek, Martin; Kala, Jiří; Hradil, Petr

2017-10-01

Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations, gradient based and nature inspired optimization algorithms and experimental data, the latter of which take the form of a load-extension curve obtained from the evaluation of uniaxial tensile test results. The aim of this research was to obtain material model parameters corresponding to the quasi-static tensile loading which may be further used for the research involving dynamic and high-speed tensile loading. Based on the obtained results it can be concluded that the set goal has been reached.

Optimal structure and parameter learning of Ising models

DOE PAGES

Lokhov, Andrey; Vuffray, Marc Denis; Misra, Sidhant; ...

2018-03-16

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. Here, we introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems. The algorithm provably achieves perfect graph structure recovery with an information-theoretically optimal number of samples, notably in the low-temperature regime, whichmore » is known to be the hardest for learning. Here, the efficacy of interaction screening is assessed through extensive numerical tests on synthetic Ising models of various topologies with different types of interactions, as well as on real data produced by a D-Wave quantum computer. Finally, this study shows that the interaction screening method is an exact, tractable, and optimal technique that universally solves the inverse Ising problem.« less

Optimal structure and parameter learning of Ising models

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

Lokhov, Andrey; Vuffray, Marc Denis; Misra, Sidhant

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. Here, we introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems. The algorithm provably achieves perfect graph structure recovery with an information-theoretically optimal number of samples, notably in the low-temperature regime, whichmore » is known to be the hardest for learning. Here, the efficacy of interaction screening is assessed through extensive numerical tests on synthetic Ising models of various topologies with different types of interactions, as well as on real data produced by a D-Wave quantum computer. Finally, this study shows that the interaction screening method is an exact, tractable, and optimal technique that universally solves the inverse Ising problem.« less

A LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) FOR NONLINEAR SYSTEM IDENTIFICATION

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Lofberg, Johan; Brenner, Martin J.

2006-01-01

Identification of parametric nonlinear models involves estimating unknown parameters and detecting its underlying structure. Structure computation is concerned with selecting a subset of parameters to give a parsimonious description of the system which may afford greater insight into the functionality of the system or a simpler controller design. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear systems. The LASSO minimises the residual sum of squares by the addition of a 1 penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. The performance of this LASSO structure detection method was evaluated by using it to estimate the structure of a nonlinear polynomial model. Applicability of the method to more complex systems such as those encountered in aerospace applications was shown by identifying a parsimonious system description of the F/A-18 Active Aeroelastic Wing using flight test data.

Analysis on pseudo excitation of random vibration for structure of time flight counter

NASA Astrophysics Data System (ADS)

Wu, Qiong; Li, Dapeng

2015-03-01

Traditional computing method is inefficient for getting key dynamical parameters of complicated structure. Pseudo Excitation Method(PEM) is an effective method for calculation of random vibration. Due to complicated and coupling random vibration in rocket or shuttle launching, the new staging white noise mathematical model is deduced according to the practical launch environment. This deduced model is applied for PEM to calculate the specific structure of Time of Flight Counter(ToFC). The responses of power spectral density and the relevant dynamic characteristic parameters of ToFC are obtained in terms of the flight acceptance test level. Considering stiffness of fixture structure, the random vibration experiments are conducted in three directions to compare with the revised PEM. The experimental results show the structure can bear the random vibration caused by launch without any damage and key dynamical parameters of ToFC are obtained. The revised PEM is similar with random vibration experiment in dynamical parameters and responses are proved by comparative results. The maximum error is within 9%. The reasons of errors are analyzed to improve reliability of calculation. This research provides an effective method for solutions of computing dynamical characteristic parameters of complicated structure in the process of rocket or shuttle launching.

Methods for the identification of material parameters in distributed models for flexible structures

NASA Technical Reports Server (NTRS)

Banks, H. T.; Crowley, J. M.; Rosen, I. G.

1986-01-01

Theoretical and numerical results are presented for inverse problems involving estimation of spatially varying parameters such as stiffness and damping in distributed models for elastic structures such as Euler-Bernoulli beams. An outline of algorithms used and a summary of computational experiences are presented.

Reanalysis, compatibility and correlation in analysis of modified antenna structures

NASA Technical Reports Server (NTRS)

Levy, R.

1989-01-01

A simple computational procedure is synthesized to process changes in the microwave-antenna pathlength-error measure when there are changes in the antenna structure model. The procedure employs structural modification reanalysis methods combined with new extensions of correlation analysis to provide the revised rms pathlength error. Mainframe finite-element-method processing of the structure model is required only for the initial unmodified structure, and elementary postprocessor computations develop and deal with the effects of the changes. Several illustrative computational examples are included. The procedure adapts readily to processing spectra of changes for parameter studies or sensitivity analyses.

Lifetime Reliability Evaluation of Structural Ceramic Parts with the CARES/LIFE Computer Program

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Janosik, Lesley A.; Gyekenyesi, John P.

1993-01-01

The computer program CARES/LIFE calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. This program is an extension of the CARES (Ceramics Analysis and Reliability Evaluation of Structures) computer program. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing the power law, Paris law, or Walker equation. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled using either the principle of independent action (PIA), Weibull's normal stress averaging method (NSA), or Batdorf's theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. Two example problems demonstrating cyclic fatigue parameter estimation and component reliability analysis with proof testing are included.

Aeroelastic Model Structure Computation for Envelope Expansion

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear aeroelastic systems. The LASSO minimises the residual sum of squares by the addition of an l(sub 1) penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 Active Aeroelastic Wing using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

Does the choice of the crystal structure influence the results of the periodic DFT calculations? A case of glycine alpha polymorph GIPAW NMR parameters computations.

PubMed

Szeleszczuk, Łukasz; Pisklak, Dariusz Maciej; Zielińska-Pisklak, Monika

2018-05-30

Glycine is a common amino acid with relatively complex chemistry in solid state. Although several polymorphs (α, β, δ, γ, ε) of crystalline glycine are known, for NMR spectroscopy the most important is a polymorph, which is used as a standard for calibration of spectrometer performance and therefore it is intensively studied by both experimental methods and theoretical computation. The great scientific interest in a glycine results in a large number of crystallographic information files (CIFs) deposited in Cambridge Structural Database (CSD). The aim of this study was to evaluate the influence of the chosen crystal structure of α glycine obtained in different crystallographic experimental conditions (temperature, pressure and source of radiation of α glycine) on the results of periodic DFT calculation. For this purpose the total of 136 GIPAW calculations of α glycine NMR parameters were performed, preceded by the four approaches ("SP", "only H", "full", "full+cell") of structure preparation. The analysis of the results of those computations performed on the representative group of 34 structures obtained at various experimental conditions revealed that though the structures were generally characterized by good accuracy (R < 0.05 for most of them) the results of the periodic DFT calculations performed using the unoptimized structures differed significantly. The values of the standard deviations of the studied NMR parameters were in most cases decreasing with the number of optimized parameters. The most accurate results (of the calculations) were in most cases obtained using the structures with solely hydrogen atoms positions optimized. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Crew/computer communications study. Volume 1: Final report. [onboard computerized communications system for spacecrews

NASA Technical Reports Server (NTRS)

Johannes, J. D.

1974-01-01

Techniques, methods, and system requirements are reported for an onboard computerized communications system that provides on-line computing capability during manned space exploration. Communications between man and computer take place by sequential execution of each discrete step of a procedure, by interactive progression through a tree-type structure to initiate tasks or by interactive optimization of a task requiring man to furnish a set of parameters. Effective communication between astronaut and computer utilizes structured vocabulary techniques and a word recognition system.

Blending Determinism with Evolutionary Computing: Applications to the Calculation of the Molecular Electronic Structure of Polythiophene.

PubMed

Sarkar, Kanchan; Sharma, Rahul; Bhattacharyya, S P

2010-03-09

A density matrix based soft-computing solution to the quantum mechanical problem of computing the molecular electronic structure of fairly long polythiophene (PT) chains is proposed. The soft-computing solution is based on a "random mutation hill climbing" scheme which is modified by blending it with a deterministic method based on a trial single-particle density matrix [P((0))(R)] for the guessed structural parameters (R), which is allowed to evolve under a unitary transformation generated by the Hamiltonian H(R). The Hamiltonian itself changes as the geometrical parameters (R) defining the polythiophene chain undergo mutation. The scale (λ) of the transformation is optimized by making the energy [E(λ)] stationary with respect to λ. The robustness and the performance levels of variants of the algorithm are analyzed and compared with those of other derivative free methods. The method is further tested successfully with optimization of the geometry of bipolaron-doped long PT chains.

Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models

USGS Publications Warehouse

Hooten, Mevin B.; Leeds, William B.; Fiechter, Jerome; Wikle, Christopher K.

2011-01-01

We present an approach for estimating physical parameters in nonlinear models that relies on an approximation to the mechanistic model itself for computational efficiency. The proposed methodology is validated and applied in two different modeling scenarios: (a) Simulation and (b) lower trophic level ocean ecosystem model. The approach we develop relies on the ability to predict right singular vectors (resulting from a decomposition of computer model experimental output) based on the computer model input and an experimental set of parameters. Critically, we model the right singular vectors in terms of the model parameters via a nonlinear statistical model. Specifically, we focus our attention on first-order models of these right singular vectors rather than the second-order (covariance) structure.

Adjoint sensitivity analysis of plasmonic structures using the FDTD method.

PubMed

Zhang, Yu; Ahmed, Osman S; Bakr, Mohamed H

2014-05-15

We present an adjoint variable method for estimating the sensitivities of arbitrary responses with respect to the parameters of dispersive discontinuities in nanoplasmonic devices. Our theory is formulated in terms of the electric field components at the vicinity of perturbed discontinuities. The adjoint sensitivities are computed using at most one extra finite-difference time-domain (FDTD) simulation regardless of the number of parameters. Our approach is illustrated through the sensitivity analysis of an add-drop coupler consisting of a square ring resonator between two parallel waveguides. The computed adjoint sensitivities of the scattering parameters are compared with those obtained using the accurate but computationally expensive central finite difference approach.

Sensitivity Analysis for Coupled Aero-structural Systems

NASA Technical Reports Server (NTRS)

Giunta, Anthony A.

1999-01-01

A novel method has been developed for calculating gradients of aerodynamic force and moment coefficients for an aeroelastic aircraft model. This method uses the Global Sensitivity Equations (GSE) to account for the aero-structural coupling, and a reduced-order modal analysis approach to condense the coupling bandwidth between the aerodynamic and structural models. Parallel computing is applied to reduce the computational expense of the numerous high fidelity aerodynamic analyses needed for the coupled aero-structural system. Good agreement is obtained between aerodynamic force and moment gradients computed with the GSE/modal analysis approach and the same quantities computed using brute-force, computationally expensive, finite difference approximations. A comparison between the computational expense of the GSE/modal analysis method and a pure finite difference approach is presented. These results show that the GSE/modal analysis approach is the more computationally efficient technique if sensitivity analysis is to be performed for two or more aircraft design parameters.

Characteristics of middle and upper tropospheric clouds as deduced from rawinsonde data

NASA Technical Reports Server (NTRS)

Starr, D. D. O.; Cox, S. K.

1982-01-01

The static environment of middle and upper tropospheric clouds is characterized. Computed relative humidity with respect to ice is used to diagnose the presence of cloud layer. The deduced seasonal mean cloud cover estimates based on this technique are shown to be reasonable. The cases are stratified by season and pressure thickness, and the dry static stability, vertical wind speed shear, and Richardson number are computed for three layers for each case. Mean values for each parameter are presented for each stratification and layer. The relative frequency of occurrence of various structures is presented for each stratification. The observed values of each parameter and the observed structure of each parameter are quite variable. Structures corresponding to any of a number of different conceptual models may be found. Moist adiabatic conditions are not commonly observed and the stratification based on thickness yields substantially different results for each group.

Model selection and parameter estimation in structural dynamics using approximate Bayesian computation

NASA Astrophysics Data System (ADS)

Ben Abdessalem, Anis; Dervilis, Nikolaos; Wagg, David; Worden, Keith

2018-01-01

This paper will introduce the use of the approximate Bayesian computation (ABC) algorithm for model selection and parameter estimation in structural dynamics. ABC is a likelihood-free method typically used when the likelihood function is either intractable or cannot be approached in a closed form. To circumvent the evaluation of the likelihood function, simulation from a forward model is at the core of the ABC algorithm. The algorithm offers the possibility to use different metrics and summary statistics representative of the data to carry out Bayesian inference. The efficacy of the algorithm in structural dynamics is demonstrated through three different illustrative examples of nonlinear system identification: cubic and cubic-quintic models, the Bouc-Wen model and the Duffing oscillator. The obtained results suggest that ABC is a promising alternative to deal with model selection and parameter estimation issues, specifically for systems with complex behaviours.

Estimation and Identifiability of Model Parameters in Human Nociceptive Processing Using Yes-No Detection Responses to Electrocutaneous Stimulation.

PubMed

Yang, Huan; Meijer, Hil G E; Buitenweg, Jan R; van Gils, Stephan A

2016-01-01

Healthy or pathological states of nociceptive subsystems determine different stimulus-response relations measured from quantitative sensory testing. In turn, stimulus-response measurements may be used to assess these states. In a recently developed computational model, six model parameters characterize activation of nerve endings and spinal neurons. However, both model nonlinearity and limited information in yes-no detection responses to electrocutaneous stimuli challenge to estimate model parameters. Here, we address the question whether and how one can overcome these difficulties for reliable parameter estimation. First, we fit the computational model to experimental stimulus-response pairs by maximizing the likelihood. To evaluate the balance between model fit and complexity, i.e., the number of model parameters, we evaluate the Bayesian Information Criterion. We find that the computational model is better than a conventional logistic model regarding the balance. Second, our theoretical analysis suggests to vary the pulse width among applied stimuli as a necessary condition to prevent structural non-identifiability. In addition, the numerically implemented profile likelihood approach reveals structural and practical non-identifiability. Our model-based approach with integration of psychophysical measurements can be useful for a reliable assessment of states of the nociceptive system.

SM-4 computer and CAMAC equipment in automating a ROMS-2A mass spectrometer

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

Bulgakov, R.Sh.; Gafurov, R.A.; Safin, D.N.

1988-05-01

A data acquisition system was developed which provides for measuring mass peaks on three parameters as well as measuring working parameters. The computer memory stores 40 kHz signals, with an ADC cycle time of 10 microsec. A structural diagram is given together with upgrades made in the CAMAC apparatus to improve the speed and extend the application. Working parameters such as the pressures in pipes and the temperature in the test zone can be monitored by splitting the measurements into two cycles alternating with a controlled frequency: gas composition and technological parameter measurement.

Some issues related to the novel spectral acceleration method for the fast computation of radiation/scattering from one-dimensional extremely large scale quasi-planar structures

NASA Astrophysics Data System (ADS)

Torrungrueng, Danai; Johnson, Joel T.; Chou, Hsi-Tseng

2002-03-01

The novel spectral acceleration (NSA) algorithm has been shown to produce an $[\\mathcal{O}]$(Ntot) efficient iterative method of moments for the computation of radiation/scattering from both one-dimensional (1-D) and two-dimensional large-scale quasi-planar structures, where Ntot is the total number of unknowns to be solved. This method accelerates the matrix-vector multiplication in an iterative method of moments solution and divides contributions between points into ``strong'' (exact matrix elements) and ``weak'' (NSA algorithm) regions. The NSA method is based on a spectral representation of the electromagnetic Green's function and appropriate contour deformation, resulting in a fast multipole-like formulation in which contributions from large numbers of points to a single point are evaluated simultaneously. In the standard NSA algorithm the NSA parameters are derived on the basis of the assumption that the outermost possible saddle point, φs,max, along the real axis in the complex angular domain is small. For given height variations of quasi-planar structures, this assumption can be satisfied by adjusting the size of the strong region Ls. However, for quasi-planar structures with large height variations, the adjusted size of the strong region is typically large, resulting in significant increases in computational time for the computation of the strong-region contribution and degrading overall efficiency of the NSA algorithm. In addition, for the case of extremely large scale structures, studies based on the physical optics approximation and a flat surface assumption show that the given NSA parameters in the standard NSA algorithm may yield inaccurate results. In this paper, analytical formulas associated with the NSA parameters for an arbitrary value of φs,max are presented, resulting in more flexibility in selecting Ls to compromise between the computation of the contributions of the strong and weak regions. In addition, a ``multilevel'' algorithm, decomposing 1-D extremely large scale quasi-planar structures into more than one weak region and appropriately choosing the NSA parameters for each weak region, is incorporated into the original NSA method to improve its accuracy.

A Fast Surrogate-facilitated Data-driven Bayesian Approach to Uncertainty Quantification of a Regional Groundwater Flow Model with Structural Error

NASA Astrophysics Data System (ADS)

Xu, T.; Valocchi, A. J.; Ye, M.; Liang, F.

2016-12-01

Due to simplification and/or misrepresentation of the real aquifer system, numerical groundwater flow and solute transport models are usually subject to model structural error. During model calibration, the hydrogeological parameters may be overly adjusted to compensate for unknown structural error. This may result in biased predictions when models are used to forecast aquifer response to new forcing. In this study, we extend a fully Bayesian method [Xu and Valocchi, 2015] to calibrate a real-world, regional groundwater flow model. The method uses a data-driven error model to describe model structural error and jointly infers model parameters and structural error. In this study, Bayesian inference is facilitated using high performance computing and fast surrogate models. The surrogate models are constructed using machine learning techniques to emulate the response simulated by the computationally expensive groundwater model. We demonstrate in the real-world case study that explicitly accounting for model structural error yields parameter posterior distributions that are substantially different from those derived by the classical Bayesian calibration that does not account for model structural error. In addition, the Bayesian with error model method gives significantly more accurate prediction along with reasonable credible intervals.

Aeroelastic Model Structure Computation for Envelope Expansion

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion that may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of non-linear aeroelastic systems. The LASSO minimises the residual sum of squares with the addition of an l(Sub 1) penalty term on the parameter vector of the traditional l(sub 2) minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudo-linear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Active Aeroelastic Wing project using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

Unsteady Aerodynamic Force Sensing from Strain Data

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi

2017-01-01

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm.

ESTIMATION OF PHYSIOCHEMICAL PROPERTIES OF ORGANIC COMPOUNDS BY SPARC

EPA Science Inventory

The computer program SPARC (SPARC Performs Automated Reasoning in Chemistry) has been under development for several years to estimate physical properties and chemical reactivity parameters of organic compounds strictly from molecular structure. SPARC uses computational algorithms...

Computational Benefits Using an Advanced Concatenation Scheme Based on Reduced Order Models for RF Structures

NASA Astrophysics Data System (ADS)

Heller, Johann; Flisgen, Thomas; van Rienen, Ursula

The computation of electromagnetic fields and parameters derived thereof for lossless radio frequency (RF) structures filled with isotropic media is an important task for the design and operation of particle accelerators. Unfortunately, these computations are often highly demanding with regard to computational effort. The entire computational demand of the problem can be reduced using decomposition schemes in order to solve the field problems on standard workstations. This paper presents one of the first detailed comparisons between the recently proposed state-space concatenation approach (SSC) and a direct computation for an accelerator cavity with coupler-elements that break the rotational symmetry.

On robust parameter estimation in brain-computer interfacing

NASA Astrophysics Data System (ADS)

Samek, Wojciech; Nakajima, Shinichi; Kawanabe, Motoaki; Müller, Klaus-Robert

2017-12-01

Objective. The reliable estimation of parameters such as mean or covariance matrix from noisy and high-dimensional observations is a prerequisite for successful application of signal processing and machine learning algorithms in brain-computer interfacing (BCI). This challenging task becomes significantly more difficult if the data set contains outliers, e.g. due to subject movements, eye blinks or loose electrodes, as they may heavily bias the estimation and the subsequent statistical analysis. Although various robust estimators have been developed to tackle the outlier problem, they ignore important structural information in the data and thus may not be optimal. Typical structural elements in BCI data are the trials consisting of a few hundred EEG samples and indicating the start and end of a task. Approach. This work discusses the parameter estimation problem in BCI and introduces a novel hierarchical view on robustness which naturally comprises different types of outlierness occurring in structured data. Furthermore, the class of minimum divergence estimators is reviewed and a robust mean and covariance estimator for structured data is derived and evaluated with simulations and on a benchmark data set. Main results. The results show that state-of-the-art BCI algorithms benefit from robustly estimated parameters. Significance. Since parameter estimation is an integral part of various machine learning algorithms, the presented techniques are applicable to many problems beyond BCI.

The J3 SCR model applied to resonant converter simulation

NASA Technical Reports Server (NTRS)

Avant, R. L.; Lee, F. C. Y.

1985-01-01

The J3 SCR model is a continuous topology computer model for the SCR. Its circuit analog and parameter estimation procedure are uniformly applicable to popular computer-aided design and analysis programs such as SPICE2 and SCEPTRE. The circuit analog is based on the intrinsic three pn junction structure of the SCR. The parameter estimation procedure requires only manufacturer's specification sheet quantities as a data base.

JPL control/structure interaction test bed real-time control computer architecture

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

1989-01-01

The Control/Structure Interaction Program is a technology development program for spacecraft that exhibit interactions between the control system and structural dynamics. The program objectives include development and verification of new design concepts - such as active structure - and new tools - such as combined structure and control optimization algorithm - and their verification in ground and possibly flight test. A focus mission spacecraft was designed based upon a space interferometer and is the basis for design of the ground test article. The ground test bed objectives include verification of the spacecraft design concepts, the active structure elements and certain design tools such as the new combined structures and controls optimization tool. In anticipation of CSI technology flight experiments, the test bed control electronics must emulate the computation capacity and control architectures of space qualifiable systems as well as the command and control networks that will be used to connect investigators with the flight experiment hardware. The Test Bed facility electronics were functionally partitioned into three units: a laboratory data acquisition system for structural parameter identification and performance verification; an experiment supervisory computer to oversee the experiment, monitor the environmental parameters and perform data logging; and a multilevel real-time control computing system. The design of the Test Bed electronics is presented along with hardware and software component descriptions. The system should break new ground in experimental control electronics and is of interest to anyone working in the verification of control concepts for large structures.

Automated dynamic analytical model improvement for damped structures

NASA Technical Reports Server (NTRS)

Fuh, J. S.; Berman, A.

1985-01-01

A method is described to improve a linear nonproportionally damped analytical model of a structure. The procedure finds the smallest changes in the analytical model such that the improved model matches the measured modal parameters. Features of the method are: (1) ability to properly treat complex valued modal parameters of a damped system; (2) applicability to realistically large structural models; and (3) computationally efficiency without involving eigensolutions and inversion of a large matrix.

The application of artificial intelligence in the optimal design of mechanical systems

NASA Astrophysics Data System (ADS)

Poteralski, A.; Szczepanik, M.

2016-11-01

The paper is devoted to new computational techniques in mechanical optimization where one tries to study, model, analyze and optimize very complex phenomena, for which more precise scientific tools of the past were incapable of giving low cost and complete solution. Soft computing methods differ from conventional (hard) computing in that, unlike hard computing, they are tolerant of imprecision, uncertainty, partial truth and approximation. The paper deals with an application of the bio-inspired methods, like the evolutionary algorithms (EA), the artificial immune systems (AIS) and the particle swarm optimizers (PSO) to optimization problems. Structures considered in this work are analyzed by the finite element method (FEM), the boundary element method (BEM) and by the method of fundamental solutions (MFS). The bio-inspired methods are applied to optimize shape, topology and material properties of 2D, 3D and coupled 2D/3D structures, to optimize the termomechanical structures, to optimize parameters of composites structures modeled by the FEM, to optimize the elastic vibrating systems to identify the material constants for piezoelectric materials modeled by the BEM and to identify parameters in acoustics problem modeled by the MFS.

Characterization of structural connections for multicomponent systems

NASA Technical Reports Server (NTRS)

Lawrence, Charles; Huckelbridge, Arthur A.

1988-01-01

This study explores combining Component Mode Synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection stiffness and damping properties are computed in terms of physical parameters so that the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model.

Fluid flow in porous media using image-based modelling to parametrize Richards' equation.

PubMed

Cooper, L J; Daly, K R; Hallett, P D; Naveed, M; Koebernick, N; Bengough, A G; George, T S; Roose, T

2017-11-01

The parameters in Richards' equation are usually calculated from experimentally measured values of the soil-water characteristic curve and saturated hydraulic conductivity. The complex pore structures that often occur in porous media complicate such parametrization due to hysteresis between wetting and drying and the effects of tortuosity. Rather than estimate the parameters in Richards' equation from these indirect measurements, image-based modelling is used to investigate the relationship between the pore structure and the parameters. A three-dimensional, X-ray computed tomography image stack of a soil sample with voxel resolution of 6 μm has been used to create a computational mesh. The Cahn-Hilliard-Stokes equations for two-fluid flow, in this case water and air, were applied to this mesh and solved using the finite-element method in COMSOL Multiphysics. The upscaled parameters in Richards' equation are then obtained via homogenization. The effect on the soil-water retention curve due to three different contact angles, 0°, 20° and 60°, was also investigated. The results show that the pore structure affects the properties of the flow on the large scale, and different contact angles can change the parameters for Richards' equation.

Summary of research in applied mathematics, numerical analysis, and computer sciences

NASA Technical Reports Server (NTRS)

1986-01-01

The major categories of current ICASE research programs addressed include: numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; control and parameter identification problems, with emphasis on effective numerical methods; computational problems in engineering and physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and computer systems and software, especially vector and parallel computers.

Simulation of Structural Transformations in Heating of Alloy Steel

NASA Astrophysics Data System (ADS)

Kurkin, A. S.; Makarov, E. L.; Kurkin, A. B.; Rubtsov, D. E.; Rubtsov, M. E.

2017-07-01

Amathematical model for computer simulation of structural transformations in an alloy steel under the conditions of the thermal cycle of multipass welding is presented. The austenitic transformation under the heating and the processes of decomposition of bainite and martensite under repeated heating are considered. Amethod for determining the necessary temperature-time parameters of the model from the chemical composition of the steel is described. Published data are processed and the results used to derive regression models of the temperature ranges and parameters of transformation kinetics of alloy steels. The method developed is used in computer simulation of the process of multipass welding of pipes by the finite-element method.

Acceleration and Velocity Sensing from Measured Strain

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Truax, Roger

2015-01-01

A simple approach for computing acceleration and velocity of a structure from the strain is proposed in this study. First, deflection and slope of the structure are computed from the strain using a two-step theory. Frequencies of the structure are computed from the time histories of strain using a parameter estimation technique together with an autoregressive moving average model. From deflection, slope, and frequencies of the structure, acceleration and velocity of the structure can be obtained using the proposed approach. Simple harmonic motion is assumed for the acceleration computations, and the central difference equation with a linear autoregressive model is used for the computations of velocity. A cantilevered rectangular wing model is used to validate the simple approach. Quality of the computed deflection, acceleration, and velocity values are independent of the number of fibers. The central difference equation with a linear autoregressive model proposed in this study follows the target response with reasonable accuracy. Therefore, the handicap of the backward difference equation, phase shift, is successfully overcome.

The RNA Newton polytope and learnability of energy parameters.

PubMed

Forouzmand, Elmirasadat; Chitsaz, Hamidreza

2013-07-01

Computational RNA structure prediction is a mature important problem that has received a new wave of attention with the discovery of regulatory non-coding RNAs and the advent of high-throughput transcriptome sequencing. Despite nearly two score years of research on RNA secondary structure and RNA-RNA interaction prediction, the accuracy of the state-of-the-art algorithms are still far from satisfactory. So far, researchers have proposed increasingly complex energy models and improved parameter estimation methods, experimental and/or computational, in anticipation of endowing their methods with enough power to solve the problem. The output has disappointingly been only modest improvements, not matching the expectations. Even recent massively featured machine learning approaches were not able to break the barrier. Why is that? The first step toward high-accuracy structure prediction is to pick an energy model that is inherently capable of predicting each and every one of known structures to date. In this article, we introduce the notion of learnability of the parameters of an energy model as a measure of such an inherent capability. We say that the parameters of an energy model are learnable iff there exists at least one set of such parameters that renders every known RNA structure to date the minimum free energy structure. We derive a necessary condition for the learnability and give a dynamic programming algorithm to assess it. Our algorithm computes the convex hull of the feature vectors of all feasible structures in the ensemble of a given input sequence. Interestingly, that convex hull coincides with the Newton polytope of the partition function as a polynomial in energy parameters. To the best of our knowledge, this is the first approach toward computing the RNA Newton polytope and a systematic assessment of the inherent capabilities of an energy model. The worst case complexity of our algorithm is exponential in the number of features. However, dimensionality reduction techniques can provide approximate solutions to avoid the curse of dimensionality. We demonstrated the application of our theory to a simple energy model consisting of a weighted count of A-U, C-G and G-U base pairs. Our results show that this simple energy model satisfies the necessary condition for more than half of the input unpseudoknotted sequence-structure pairs (55%) chosen from the RNA STRAND v2.0 database and severely violates the condition for ~ 13%, which provide a set of hard cases that require further investigation. From 1350 RNA strands, the observed 3D feature vector for 749 strands is on the surface of the computed polytope. For 289 RNA strands, the observed feature vector is not on the boundary of the polytope but its distance from the boundary is not more than one. A distance of one essentially means one base pair difference between the observed structure and the closest point on the boundary of the polytope, which need not be the feature vector of a structure. For 171 sequences, this distance is larger than two, and for only 11 sequences, this distance is larger than five. The source code is available on http://compbio.cs.wayne.edu/software/rna-newton-polytope.

RNA Thermodynamic Structural Entropy

PubMed Central

Garcia-Martin, Juan Antonio; Clote, Peter

2015-01-01

Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs). However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE) element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner’99 and Turner’04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http://bioinformatics.bc.edu/clotelab/RNAentropy, including source code and ancillary programs. PMID:26555444

RNA Thermodynamic Structural Entropy.

PubMed

Garcia-Martin, Juan Antonio; Clote, Peter

2015-01-01

Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs). However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE) element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner'99 and Turner'04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http://bioinformatics.bc.edu/clotelab/RNAentropy, including source code and ancillary programs.

Automated selection of computed tomography display parameters using neural networks

NASA Astrophysics Data System (ADS)

Zhang, Di; Neu, Scott; Valentino, Daniel J.

2001-07-01

A collection of artificial neural networks (ANN's) was trained to identify simple anatomical structures in a set of x-ray computed tomography (CT) images. These neural networks learned to associate a point in an image with the anatomical structure containing the point by using the image pixels located on the horizontal and vertical lines that ran through the point. The neural networks were integrated into a computer software tool whose function is to select an index into a list of CT window/level values from the location of the user's mouse cursor. Based upon the anatomical structure selected by the user, the software tool automatically adjusts the image display to optimally view the structure.

Ab-initio study of electronic, magnetic and thermoelectric behaviors of LiV2O4 and LiCr2O4 using modified Becke-Johson (mBJ) potential

NASA Astrophysics Data System (ADS)

Ali, Saima; Rashid, Muhammad; Hassan, M.; Noor, N. A.; Mahmood, Q.; Laref, A.; Haq, Bakhtiar Ul

2018-05-01

Owing to the large energy storage capacity and higher working voltage, the spinel oxides LiV2O4 and LiCr2O4, have remained under intense research attention for utilization as electrode materials in lithium-ion batteries. In this study, we explore the half-metallic nature and thermoelectric response in both LiV2O4 and LiCr2O4 spinel oxides using ab-initio density functional theory (DFT) based computations. The ground-state energies of these compounds have been studied at the optimized structural parameters in the ferromagnetic phase. In order to obtain a correct picture of the electronic structure and magnetic properties, the modified Becke-Johnson (mBJ) potential is applied to compute the electronic structures. The half-metallic behavior is confirmed by the spin-polarized electronic band structures and density of state plots. The magnetic nature is elucidated by computing the John-Teller energy, direct and indirect exchange and crystal field splitting energies. Our computations indicate strong hybridization decreasing the V/Cr site magnetic moments and increasing magnetic momenta at the nonmagnetic atomic sites. We also present the computed parameters significant for expressing the thermoelectric response, which are electrical conductivity, thermal conductivity, See-beck coefficient and power factor. The computed properties are of immense interest owing to the potential spintronics and Li-ion battery applications of the studied spinel materials.

Joint Model and Parameter Dimension Reduction for Bayesian Inversion Applied to an Ice Sheet Flow Problem

NASA Astrophysics Data System (ADS)

Ghattas, O.; Petra, N.; Cui, T.; Marzouk, Y.; Benjamin, P.; Willcox, K.

2016-12-01

Model-based projections of the dynamics of the polar ice sheets play a central role in anticipating future sea level rise. However, a number of mathematical and computational challenges place significant barriers on improving predictability of these models. One such challenge is caused by the unknown model parameters (e.g., in the basal boundary conditions) that must be inferred from heterogeneous observational data, leading to an ill-posed inverse problem and the need to quantify uncertainties in its solution. In this talk we discuss the problem of estimating the uncertainty in the solution of (large-scale) ice sheet inverse problems within the framework of Bayesian inference. Computing the general solution of the inverse problem--i.e., the posterior probability density--is intractable with current methods on today's computers, due to the expense of solving the forward model (3D full Stokes flow with nonlinear rheology) and the high dimensionality of the uncertain parameters (which are discretizations of the basal sliding coefficient field). To overcome these twin computational challenges, it is essential to exploit problem structure (e.g., sensitivity of the data to parameters, the smoothing property of the forward model, and correlations in the prior). To this end, we present a data-informed approach that identifies low-dimensional structure in both parameter space and the forward model state space. This approach exploits the fact that the observations inform only a low-dimensional parameter space and allows us to construct a parameter-reduced posterior. Sampling this parameter-reduced posterior still requires multiple evaluations of the forward problem, therefore we also aim to identify a low dimensional state space to reduce the computational cost. To this end, we apply a proper orthogonal decomposition (POD) approach to approximate the state using a low-dimensional manifold constructed using ``snapshots'' from the parameter reduced posterior, and the discrete empirical interpolation method (DEIM) to approximate the nonlinearity in the forward problem. We show that using only a limited number of forward solves, the resulting subspaces lead to an efficient method to explore the high-dimensional posterior.

Transfer-function-parameter estimation from frequency response data: A FORTRAN program

NASA Technical Reports Server (NTRS)

Seidel, R. C.

1975-01-01

A FORTRAN computer program designed to fit a linear transfer function model to given frequency response magnitude and phase data is presented. A conjugate gradient search is used that minimizes the integral of the absolute value of the error squared between the model and the data. The search is constrained to insure model stability. A scaling of the model parameters by their own magnitude aids search convergence. Efficient computer algorithms result in a small and fast program suitable for a minicomputer. A sample problem with different model structures and parameter estimates is reported.

Parameter optimization on the convergence surface of path simulations

NASA Astrophysics Data System (ADS)

Chandrasekaran, Srinivas Niranj

Computational treatments of protein conformational changes tend to focus on the trajectories themselves, despite the fact that it is the transition state structures that contain information about the barriers that impose multi-state behavior. PATH is an algorithm that computes a transition pathway between two protein crystal structures, along with the transition state structure, by minimizing the Onsager-Machlup action functional. It is rapid but depends on several unknown input parameters whose range of different values can potentially generate different transition-state structures. Transition-state structures arising from different input parameters cannot be uniquely compared with those generated by other methods. I outline modifications that I have made to the PATH algorithm that estimates these input parameters in a manner that circumvents these difficulties, and describe two complementary tests that validate the transition-state structures found by the PATH algorithm. First, I show that although the PATH algorithm and two other approaches to computing transition pathways produce different low-energy structures connecting the initial and final ground-states with the transition state, all three methods agree closely on the configurations of their transition states. Second, I show that the PATH transition states are close to the saddle points of free-energy surfaces connecting initial and final states generated by replica-exchange Discrete Molecular Dynamics simulations. I show that aromatic side-chain rearrangements create similar potential energy barriers in the transition-state structures identified by PATH for a signaling protein, a contractile protein, and an enzyme. Finally, I observed, but cannot account for, the fact that trajectories obtained for all-atom and Calpha-only simulations identify transition state structures in which the Calpha atoms are in essentially the same positions. The consistency between transition-state structures derived by different algorithms for unrelated protein systems argues that although functionally important protein conformational change trajectories are to a degree stochastic, they nonetheless pass through a well-defined transition state whose detailed structural properties can rapidly be identified using PATH. In the end, I outline the strategies that could enhance the efficiency and applicability of PATH.

Computational Algorithms or Identification of Distributed Parameter Systems

DTIC Science & Technology

1993-04-24

delay-differential equations, Volterra integral equations, and partial differential equations with memory terms . In particular we investigated a...tested for estimating parameters in a Volterra integral equation arising from a viscoelastic model of a flexible structure with Boltzmann damping. In...particular, one of the parameters identified was the order of the derivative in Volterra integro-differential equations containing fractional

A computational learning model for metrical phonology.

PubMed

Dresher, B E; Kaye, J D

1990-02-01

One of the major challenges to linguistic theory is the solution of what has been termed the "projection problem". Simply put, linguistics must account for the fact that starting from a data base that is both unsystematic and relatively small, a human child is capable of constructing a grammar that mirrors, for all intents and purposes, the adult system. In this article we shall address ourselves to the question of the learnability of a postulated subsystem of phonological structure: the stress system. We shall describe a computer program which is designed to acquire this subpart of linguistic structure. Our approach follows the "principles and parameters" model of Chomsky (1981a, b). This model is particularly interesting from both a computational point of view and with respect to the development of learning theories. We encode the relevant aspects of universal grammar (UG)--those aspects of linguistic structure that are presumed innate and thus present in every linguistic system. The learning process consists of fixing a number of parameters which have been shown to underlie stress systems and which should, in principle, lead the learner to the postulation of the system from which the primary linguistic data (i.e., the input to the learner) is drawn. We go on to explore certain formal and substantive properties of this learning system. Questions such as cross-parameter dependencies, determinism, subsets, and incremental versus all-at-once learning are raised and discussed in the article. The issues raised by this study provide another perspective on the formal structure of stress systems and the learnability of parameter systems in general.

Generation of anatomically realistic numerical phantoms for photoacoustic and ultrasonic breast imaging

NASA Astrophysics Data System (ADS)

Lou, Yang; Zhou, Weimin; Matthews, Thomas P.; Appleton, Catherine M.; Anastasio, Mark A.

2017-04-01

Photoacoustic computed tomography (PACT) and ultrasound computed tomography (USCT) are emerging modalities for breast imaging. As in all emerging imaging technologies, computer-simulation studies play a critically important role in developing and optimizing the designs of hardware and image reconstruction methods for PACT and USCT. Using computer-simulations, the parameters of an imaging system can be systematically and comprehensively explored in a way that is generally not possible through experimentation. When conducting such studies, numerical phantoms are employed to represent the physical properties of the patient or object to-be-imaged that influence the measured image data. It is highly desirable to utilize numerical phantoms that are realistic, especially when task-based measures of image quality are to be utilized to guide system design. However, most reported computer-simulation studies of PACT and USCT breast imaging employ simple numerical phantoms that oversimplify the complex anatomical structures in the human female breast. We develop and implement a methodology for generating anatomically realistic numerical breast phantoms from clinical contrast-enhanced magnetic resonance imaging data. The phantoms will depict vascular structures and the volumetric distribution of different tissue types in the breast. By assigning optical and acoustic parameters to different tissue structures, both optical and acoustic breast phantoms will be established for use in PACT and USCT studies.

Research in applied mathematics, numerical analysis, and computer science

NASA Technical Reports Server (NTRS)

1984-01-01

Research conducted at the Institute for Computer Applications in Science and Engineering (ICASE) in applied mathematics, numerical analysis, and computer science is summarized and abstracts of published reports are presented. The major categories of the ICASE research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers.

Hybrid, experimental and computational, investigation of mechanical components

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

1996-07-01

Computational and experimental methodologies have unique features for the analysis and solution of a wide variety of engineering problems. Computations provide results that depend on selection of input parameters such as geometry, material constants, and boundary conditions which, for correct modeling purposes, have to be appropriately chosen. In addition, it is relatively easy to modify the input parameters in order to computationally investigate different conditions. Experiments provide solutions which characterize the actual behavior of the object of interest subjected to specific operating conditions. However, it is impractical to experimentally perform parametric investigations. This paper discusses the use of a hybrid, computational and experimental, approach for study and optimization of mechanical components. Computational techniques are used for modeling the behavior of the object of interest while it is experimentally tested using noninvasive optical techniques. Comparisons are performed through a fringe predictor program used to facilitate the correlation between both techniques. In addition, experimentally obtained quantitative information, such as displacements and shape, can be applied in the computational model in order to improve this correlation. The result is a validated computational model that can be used for performing quantitative analyses and structural optimization. Practical application of the hybrid approach is illustrated with a representative example which demonstrates the viability of the approach as an engineering tool for structural analysis and optimization.

On the structure of existence regions for sinks of the Hénon map

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

Galias, Zbigniew, E-mail: galias@agh.edu.pl; Tucker, Warwick, E-mail: warwick@math.uu.se

2014-03-15

An extensive search for stable periodic orbits (sinks) for the Hénon map in a small neighborhood of the classical parameter values is carried out. Several parameter values which generate a sink are found and verified by rigorous numerical computations. Each found parameter value is extended to a larger region of existence using a simplex continuation method. The structure of these regions of existence is investigated. This study shows that for the Hénon map, there exist sinks close to the classical case.

Estimation of Unsteady Aerodynamic Models from Dynamic Wind Tunnel Data

NASA Technical Reports Server (NTRS)

Murphy, Patrick; Klein, Vladislav

2011-01-01

Demanding aerodynamic modelling requirements for military and civilian aircraft have motivated researchers to improve computational and experimental techniques and to pursue closer collaboration in these areas. Model identification and validation techniques are key components for this research. This paper presents mathematical model structures and identification techniques that have been used successfully to model more general aerodynamic behaviours in single-degree-of-freedom dynamic testing. Model parameters, characterizing aerodynamic properties, are estimated using linear and nonlinear regression methods in both time and frequency domains. Steps in identification including model structure determination, parameter estimation, and model validation, are addressed in this paper with examples using data from one-degree-of-freedom dynamic wind tunnel and water tunnel experiments. These techniques offer a methodology for expanding the utility of computational methods in application to flight dynamics, stability, and control problems. Since flight test is not always an option for early model validation, time history comparisons are commonly made between computational and experimental results and model adequacy is inferred by corroborating results. An extension is offered to this conventional approach where more general model parameter estimates and their standard errors are compared.

Progressive Fracture of Composite Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Minnetyan, Levon

2008-01-01

A new approach is described for evaluating fracture in composite structures. This approach is independent of classical fracture mechanics parameters like fracture toughness. It relies on computational simulation and is programmed in a stand-alone integrated computer code. It is multiscale, multifunctional because it includes composite mechanics for the composite behavior and finite element analysis for predicting the structural response. It contains seven modules; layered composite mechanics (micro, macro, laminate), finite element, updating scheme, local fracture, global fracture, stress based failure modes, and fracture progression. The computer code is called CODSTRAN (Composite Durability Structural ANalysis). It is used in the present paper to evaluate the global fracture of four composite shell problems and one composite built-up structure. Results show that the composite shells and the built-up composite structure global fracture are enhanced when internal pressure is combined with shear loads.

Approximate Bayesian computation in large-scale structure: constraining the galaxy-halo connection

NASA Astrophysics Data System (ADS)

Hahn, ChangHoon; Vakili, Mohammadjavad; Walsh, Kilian; Hearin, Andrew P.; Hogg, David W.; Campbell, Duncan

2017-08-01

Standard approaches to Bayesian parameter inference in large-scale structure assume a Gaussian functional form (chi-squared form) for the likelihood. This assumption, in detail, cannot be correct. Likelihood free inferences such as approximate Bayesian computation (ABC) relax these restrictions and make inference possible without making any assumptions on the likelihood. Instead ABC relies on a forward generative model of the data and a metric for measuring the distance between the model and data. In this work, we demonstrate that ABC is feasible for LSS parameter inference by using it to constrain parameters of the halo occupation distribution (HOD) model for populating dark matter haloes with galaxies. Using specific implementation of ABC supplemented with population Monte Carlo importance sampling, a generative forward model using HOD and a distance metric based on galaxy number density, two-point correlation function and galaxy group multiplicity function, we constrain the HOD parameters of mock observation generated from selected 'true' HOD parameters. The parameter constraints we obtain from ABC are consistent with the 'true' HOD parameters, demonstrating that ABC can be reliably used for parameter inference in LSS. Furthermore, we compare our ABC constraints to constraints we obtain using a pseudo-likelihood function of Gaussian form with MCMC and find consistent HOD parameter constraints. Ultimately, our results suggest that ABC can and should be applied in parameter inference for LSS analyses.

Identification and feedback control in structures with piezoceramic actuators

NASA Technical Reports Server (NTRS)

Banks, H. T.; Ito, K.; Wang, Y.

1992-01-01

In this lecture we give fundamental well-posedness results for a variational formulation of a class of damped second order partial differential equations with unbounded input or control coefficients. Included as special cases in this class are structures with piezoceramic actuators. We consider approximation techniques leading to computational methods in the context of both parameter estimation and feedback control problems for these systems. Rigorous convergence results for parameter estimates and feedback gains are discussed.

RNA secondary structure prediction using soft computing.

PubMed

Ray, Shubhra Sankar; Pal, Sankar K

2013-01-01

Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

Quantum Chemically Estimated Abraham Solute Parameters Using Multiple Solvent-Water Partition Coefficients and Molecular Polarizability.

PubMed

Liang, Yuzhen; Xiong, Ruichang; Sandler, Stanley I; Di Toro, Dominic M

2017-09-05

Polyparameter Linear Free Energy Relationships (pp-LFERs), also called Linear Solvation Energy Relationships (LSERs), are used to predict many environmentally significant properties of chemicals. A method is presented for computing the necessary chemical parameters, the Abraham parameters (AP), used by many pp-LFERs. It employs quantum chemical calculations and uses only the chemical's molecular structure. The method computes the Abraham E parameter using density functional theory computed molecular polarizability and the Clausius-Mossotti equation relating the index refraction to the molecular polarizability, estimates the Abraham V as the COSMO calculated molecular volume, and computes the remaining AP S, A, and B jointly with a multiple linear regression using sixty-five solvent-water partition coefficients computed using the quantum mechanical COSMO-SAC solvation model. These solute parameters, referred to as Quantum Chemically estimated Abraham Parameters (QCAP), are further adjusted by fitting to experimentally based APs using QCAP parameters as the independent variables so that they are compatible with existing Abraham pp-LFERs. QCAP and adjusted QCAP for 1827 neutral chemicals are included. For 24 solvent-water systems including octanol-water, predicted log solvent-water partition coefficients using adjusted QCAP have the smallest root-mean-square errors (RMSEs, 0.314-0.602) compared to predictions made using APs estimated using the molecular fragment based method ABSOLV (0.45-0.716). For munition and munition-like compounds, adjusted QCAP has much lower RMSE (0.860) than does ABSOLV (4.45) which essentially fails for these compounds.

Exact Scheffé-type confidence intervals for output from groundwater flow models: 2. Combined use of hydrogeologic information and calibration data

USGS Publications Warehouse

Cooley, Richard L.

1993-01-01

Calibration data (observed values corresponding to model-computed values of dependent variables) are incorporated into a general method of computing exact Scheffé-type confidence intervals analogous to the confidence intervals developed in part 1 (Cooley, this issue) for a function of parameters derived from a groundwater flow model. Parameter uncertainty is specified by a distribution of parameters conditioned on the calibration data. This distribution was obtained as a posterior distribution by applying Bayes' theorem to the hydrogeologically derived prior distribution of parameters from part 1 and a distribution of differences between the calibration data and corresponding model-computed dependent variables. Tests show that the new confidence intervals can be much smaller than the intervals of part 1 because the prior parameter variance-covariance structure is altered so that combinations of parameters that give poor model fit to the data are unlikely. The confidence intervals of part 1 and the new confidence intervals can be effectively employed in a sequential method of model construction whereby new information is used to reduce confidence interval widths at each stage.

Semiannual report, 1 April - 30 September 1991

NASA Technical Reports Server (NTRS)

1991-01-01

The major categories of the current Institute for Computer Applications in Science and Engineering (ICASE) research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification problems, with emphasis on effective numerical methods; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software for parallel computers. Research in these areas is discussed.

Homogenization-based interval analysis for structural-acoustic problem involving periodical composites and multi-scale uncertain-but-bounded parameters.

PubMed

Chen, Ning; Yu, Dejie; Xia, Baizhan; Liu, Jian; Ma, Zhengdong

2017-04-01

This paper presents a homogenization-based interval analysis method for the prediction of coupled structural-acoustic systems involving periodical composites and multi-scale uncertain-but-bounded parameters. In the structural-acoustic system, the macro plate structure is assumed to be composed of a periodically uniform microstructure. The equivalent macro material properties of the microstructure are computed using the homogenization method. By integrating the first-order Taylor expansion interval analysis method with the homogenization-based finite element method, a homogenization-based interval finite element method (HIFEM) is developed to solve a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters. The corresponding formulations of the HIFEM are deduced. A subinterval technique is also introduced into the HIFEM for higher accuracy. Numerical examples of a hexahedral box and an automobile passenger compartment are given to demonstrate the efficiency of the presented method for a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters.

On Finding and Using Identifiable Parameter Combinations in Nonlinear Dynamic Systems Biology Models and COMBOS: A Novel Web Implementation

PubMed Central

DiStefano, Joseph

2014-01-01

Parameter identifiability problems can plague biomodelers when they reach the quantification stage of development, even for relatively simple models. Structural identifiability (SI) is the primary question, usually understood as knowing which of P unknown biomodel parameters p 1,…, pi,…, pP are-and which are not-quantifiable in principle from particular input-output (I-O) biodata. It is not widely appreciated that the same database also can provide quantitative information about the structurally unidentifiable (not quantifiable) subset, in the form of explicit algebraic relationships among unidentifiable pi. Importantly, this is a first step toward finding what else is needed to quantify particular unidentifiable parameters of interest from new I–O experiments. We further develop, implement and exemplify novel algorithms that address and solve the SI problem for a practical class of ordinary differential equation (ODE) systems biology models, as a user-friendly and universally-accessible web application (app)–COMBOS. Users provide the structural ODE and output measurement models in one of two standard forms to a remote server via their web browser. COMBOS provides a list of uniquely and non-uniquely SI model parameters, and–importantly-the combinations of parameters not individually SI. If non-uniquely SI, it also provides the maximum number of different solutions, with important practical implications. The behind-the-scenes symbolic differential algebra algorithms are based on computing Gröbner bases of model attributes established after some algebraic transformations, using the computer-algebra system Maxima. COMBOS was developed for facile instructional and research use as well as modeling. We use it in the classroom to illustrate SI analysis; and have simplified complex models of tumor suppressor p53 and hormone regulation, based on explicit computation of parameter combinations. It’s illustrated and validated here for models of moderate complexity, with and without initial conditions. Built-in examples include unidentifiable 2 to 4-compartment and HIV dynamics models. PMID:25350289

Computational Simulation of Composite Structural Fatigue

NASA Technical Reports Server (NTRS)

Minnetyan, Levon; Chamis, Christos C. (Technical Monitor)

2005-01-01

Progressive damage and fracture of composite structures subjected to monotonically increasing static, tension-tension cyclic, pressurization, and flexural cyclic loading are evaluated via computational simulation. Constituent material properties, stress and strain limits are scaled up to the structure level to evaluate the overall damage and fracture propagation for composites. Damage initiation, growth, accumulation, and propagation to fracture due to monotonically increasing static and cyclic loads are included in the simulations. Results show the number of cycles to failure at different temperatures and the damage progression sequence during different degradation stages. A procedure is outlined for use of computational simulation data in the assessment of damage tolerance, determination of sensitive parameters affecting fracture, and interpretation of results with insight for design decisions.

Computational Simulation of Composite Structural Fatigue

NASA Technical Reports Server (NTRS)

Minnetyan, Levon

2004-01-01

Progressive damage and fracture of composite structures subjected to monotonically increasing static, tension-tension cyclic, pressurization, and flexural cyclic loading are evaluated via computational simulation. Constituent material properties, stress and strain limits are scaled up to the structure level to evaluate the overall damage and fracture propagation for composites. Damage initiation, growth, accumulation, and propagation to fracture due to monotonically increasing static and cyclic loads are included in the simulations. Results show the number of cycles to failure at different temperatures and the damage progression sequence during different degradation stages. A procedure is outlined for use of computational simulation data in the assessment of damage tolerance, determination of sensitive parameters affecting fracture, and interpretation of results with insight for design decisions.

Computation of Flow Through Water-Control Structures Using Program DAMFLO.2

USGS Publications Warehouse

Sanders, Curtis L.; Feaster, Toby D.

2004-01-01

As part of its mission to collect, analyze, and store streamflow data, the U.S. Geological Survey computes flow through several dam structures throughout the country. Flows are computed using hydraulic equations that describe flow through sluice and Tainter gates, crest gates, lock gates, spillways, locks, pumps, and siphons, which are calibrated using flow measurements. The program DAMFLO.2 was written to compute, tabulate, and plot flow through dam structures using data that describe the physical properties of dams and various hydraulic parameters and ratings that use time-varying data, such as lake elevations or gate openings. The program uses electronic computer files of time-varying data, such as lake elevation or gate openings, retrieved from the U.S. Geological Survey Automated Data Processing System. Computed time-varying flow data from DAMFLO.2 are output in flat files, which can be entered into the Automated Data Processing System database. All computations are made in units of feet and seconds. DAMFLO.2 uses the procedures and language developed by the SAS Institute Inc.

The role played by self-orientational properties in nematics of colloids with molecules axially symmetric.

PubMed

Alarcón-Waess, O

2010-04-14

The self-orientational structure factor as well as the short-time self-orientational diffusion coefficient is computed for colloids composed by nonspherical molecules. To compute the short-time dynamics the hydrodynamic interactions are not taken into account. The hard molecules with at least one symmetry axis considered are: rods, spherocylinders, and tetragonal parallelepipeds. Because both orientational properties in study are written in terms of the second and fourth order parameters, these automatically hold the features of the order parameters. That is, they present a discontinuity for first order transitions, determining in this way the spinodal line. In order to analyze the nematic phase only, we choose the appropriate values for the representative quantities that characterize the molecules. Different formalisms are used to compute the structural properties: de Gennes-Landau approach, Smoluchowski equation and computer simulations. Some of the necessary inputs are taken from literature. Our results show that the self-orientational properties play an important role in the characterization and the localization of axially symmetric phases. While the self-structure decreases throughout the nematics, the short-time self-diffusion does not decrease but rather increases. We study the evolution of the second and fourth order parameters; we find different responses for axial and biaxial nematics, predicting the possibility of a biaxial nematics in tetragonal parallelepiped molecules. By considering the second order in the axial-biaxial phase transition, with the support of the self-orientational structure factor, we are able to propose the density at which this occurs. The short-time dynamics is able to predict a different value in the axial and the biaxial phases. Because the different behavior of the fourth order parameter, the diffusion coefficient is lower for a biaxial phase than for an axial one. Therefore the self-structure factor is able to localize continuous phase transitions involving axially symmetric phases and the short-time self-orientational diffusion is able to distinguish the ordered phase by considering the degree of alignment, that is, axial or biaxial.

Fast computation of the multivariable stability margin for real interrelated uncertain parameters

NASA Technical Reports Server (NTRS)

Sideris, Athanasios; Sanchez Pena, Ricardo S.

1988-01-01

A novel algorithm for computing the multivariable stability margin for checking the robust stability of feedback systems with real parametric uncertainty is proposed. This method eliminates the need for the frequency search involved in another given algorithm by reducing it to checking a finite number of conditions. These conditions have a special structure, which allows a significant improvement on the speed of computations.

Quantum chemical parameters in QSAR: what do I use when?

USGS Publications Warehouse

Hickey, James P.; Ostrander, Gary K.

1996-01-01

This chapter provides a brief overview of the numerous quantum chemical parameters that have been/are currently being used in quantitative structure activity relationships (QSAR), along with a representative bibliography. The parameters will be grouped according to their mechanistic interpretations, and representative biological and physical chemical applications will be mentioned. Parmater computation methods and the appropriate software are highlighted, as are sources for software.

Wave tilt sounding of multilayered structures. [for probing of stratified planetary surface electrical properties and thickness

NASA Technical Reports Server (NTRS)

Warne, L.; Jaggard, D. L.; Elachi, C.

1979-01-01

The relationship between the wave tilt and the electrical parameters of a multilayered structure is investigated. Particular emphasis is placed on the inverse problem associated with the sounding planetary surfaces. An inversion technique, based on multifrequency wave tilt, is proposed and demonstrated with several computer models. It is determined that there is close agreement between the electrical parameters used in the models and those in the inversion values.

Simultaneous Aerodynamic and Structural Design Optimization (SASDO) for a 3-D Wing

NASA Technical Reports Server (NTRS)

Gumbert, Clyde R.; Hou, Gene J.-W.; Newman, Perry A.

2001-01-01

The formulation and implementation of an optimization method called Simultaneous Aerodynamic and Structural Design Optimization (SASDO) is shown as an extension of the Simultaneous Aerodynamic Analysis and Design Optimization (SAADO) method. It is extended by the inclusion of structure element sizing parameters as design variables and Finite Element Method (FEM) analysis responses as constraints. The method aims to reduce the computational expense. incurred in performing shape and sizing optimization using state-of-the-art Computational Fluid Dynamics (CFD) flow analysis, FEM structural analysis and sensitivity analysis tools. SASDO is applied to a simple. isolated, 3-D wing in inviscid flow. Results show that the method finds the saine local optimum as a conventional optimization method with some reduction in the computational cost and without significant modifications; to the analysis tools.

Buckling analysis of SMA bonded sandwich structure – using FEM

NASA Astrophysics Data System (ADS)

Katariya, Pankaj V.; Das, Arijit; Panda, Subrata K.

2018-03-01

Thermal buckling strength of smart sandwich composite structure (bonded with shape memory alloy; SMA) examined numerically via a higher-order finite element model in association with marching technique. The excess geometrical distortion of the structure under the elevated environment modeled through Green’s strain function whereas the material nonlinearity counted with the help of marching method. The system responses are computed numerically by solving the generalized eigenvalue equations via a customized MATLAB code. The comprehensive behaviour of the current finite element solutions (minimum buckling load parameter) is established by solving the adequate number of numerical examples including the given input parameter. The current numerical model is extended further to check the influence of various structural parameter of the sandwich panel on the buckling temperature including the SMA effect and reported in details.

The relationship between dental implant stability and trabecular bone structure using cone-beam computed tomography

PubMed Central

2016-01-01

Purpose The objective of this study was to investigate the relationships between primary implant stability as measured by impact response frequency and the structural parameters of trabecular bone using cone-beam computed tomography(CBCT), excluding the effect of cortical bone thickness. Methods We measured the impact response of a dental implant placed into swine bone specimens composed of only trabecular bone without the cortical bone layer using an inductive sensor. The peak frequency of the impact response spectrum was determined as an implant stability criterion (SPF). The 3D microstructural parameters were calculated from CT images of the bone specimens obtained using both micro-CT and CBCT. Results SPF had significant positive correlations with trabecular bone structural parameters (BV/TV, BV, BS, BSD, Tb.Th, Tb.N, FD, and BS/BV) (P<0.01) while SPF demonstrated significant negative correlations with other microstructural parameters (Tb.Sp, Tb.Pf, and SMI) using micro-CT and CBCT (P<0.01). Conclusions There was an increase in implant stability prediction by combining BV/TV and SMI in the stepwise forward regression analysis. Bone with high volume density and low surface density shows high implant stability. Well-connected thick bone with small marrow spaces also shows high implant stability. The combination of bone density and architectural parameters measured using CBCT can predict the implant stability more accurately than the density alone in clinical diagnoses. PMID:27127692

Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

NASA Astrophysics Data System (ADS)

Machado, M. R.; Adhikari, S.; Dos Santos, J. M. C.; Arruda, J. R. F.

2018-03-01

Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.

Mathematical form models of tree trunks

Treesearch

Rudolfs Ozolins

2000-01-01

Assortment structure analysis of tree trunks is a characteristic and proper problem that can be solved by using mathematical modeling and standard computer programs. Mathematical form model of tree trunks consists of tapering curve equations and their parameters. Parameters for nine species were obtained by processing measurements of 2,794 model trees and studying the...

Parameters of Models of Structural Transformations in Alloy Steel Under Welding Thermal Cycle

NASA Astrophysics Data System (ADS)

Kurkin, A. S.; Makarov, E. L.; Kurkin, A. B.; Rubtsov, D. E.; Rubtsov, M. E.

2017-05-01

A mathematical model of structural transformations in an alloy steel under the thermal cycle of multipass welding is suggested for computer implementation. The minimum necessary set of parameters for describing the transformations under heating and cooling is determined. Ferritic-pearlitic, bainitic and martensitic transformations under cooling of a steel are considered. A method for deriving the necessary temperature and time parameters of the model from the chemical composition of the steel is described. Published data are used to derive regression models of the temperature ranges and parameters of transformation kinetics in alloy steels. It is shown that the disadvantages of the active visual methods of analysis of the final phase composition of steels are responsible for inaccuracy and mismatch of published data. The hardness of a specimen, which correlates with some other mechanical properties of the material, is chosen as the most objective and reproducible criterion of the final phase composition. The models developed are checked by a comparative analysis of computational results and experimental data on the hardness of 140 alloy steels after cooling at various rates.

GVIPS Models and Software

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Gendy, Atef; Saleeb, Atef F.; Mark, John; Wilt, Thomas E.

2007-01-01

Two reports discuss, respectively, (1) the generalized viscoplasticity with potential structure (GVIPS) class of mathematical models and (2) the Constitutive Material Parameter Estimator (COMPARE) computer program. GVIPS models are constructed within a thermodynamics- and potential-based theoretical framework, wherein one uses internal state variables and derives constitutive equations for both the reversible (elastic) and the irreversible (viscoplastic) behaviors of materials. Because of the underlying potential structure, GVIPS models not only capture a variety of material behaviors but also are very computationally efficient. COMPARE comprises (1) an analysis core and (2) a C++-language subprogram that implements a Windows-based graphical user interface (GUI) for controlling the core. The GUI relieves the user of the sometimes tedious task of preparing data for the analysis core, freeing the user to concentrate on the task of fitting experimental data and ultimately obtaining a set of material parameters. The analysis core consists of three modules: one for GVIPS material models, an analysis module containing a specialized finite-element solution algorithm, and an optimization module. COMPARE solves the problem of finding GVIPS material parameters in the manner of a design-optimization problem in which the parameters are the design variables.

STEP and STEPSPL: Computer programs for aerodynamic model structure determination and parameter estimation

NASA Technical Reports Server (NTRS)

Batterson, J. G.

1986-01-01

The successful parametric modeling of the aerodynamics for an airplane operating at high angles of attack or sideslip is performed in two phases. First the aerodynamic model structure must be determined and second the associated aerodynamic parameters (stability and control derivatives) must be estimated for that model. The purpose of this paper is to document two versions of a stepwise regression computer program which were developed for the determination of airplane aerodynamic model structure and to provide two examples of their use on computer generated data. References are provided for the application of the programs to real flight data. The two computer programs that are the subject of this report, STEP and STEPSPL, are written in FORTRAN IV (ANSI l966) compatible with a CDC FTN4 compiler. Both programs are adaptations of a standard forward stepwise regression algorithm. The purpose of the adaptation is to facilitate the selection of a adequate mathematical model of the aerodynamic force and moment coefficients of an airplane from flight test data. The major difference between STEP and STEPSPL is in the basis for the model. The basis for the model in STEP is the standard polynomial Taylor's series expansion of the aerodynamic function about some steady-state trim condition. Program STEPSPL utilizes a set of spline basis functions.

MODY - calculation of ordered structures by symmetry-adapted functions

NASA Astrophysics Data System (ADS)

Białas, Franciszek; Pytlik, Lucjan; Sikora, Wiesława

2016-01-01

In this paper we focus on the new version of computer program MODY for calculations of symmetryadapted functions based on the theory of groups and representations. The choice of such a functional frame of coordinates for description of ordered structures leads to a minimal number of parameters which must be used for presentation of such structures and investigations of their properties. The aim of this work is to find those parameters, which are coefficients of a linear combination of calculated functions, leading to construction of different types of structure ordering with a given symmetry. A spreadsheet script for simplification of this work has been created and attached to the program.

Prediction of Environmental Impact of High-Energy Materials with Atomistic Computer Simulations

DTIC Science & Technology

2010-11-01

from a training set of compounds. Other methods include Quantitative Struc- ture-Activity Relationship ( QSAR ) and Quantitative Structure-Property...26 28 the development of QSPR/ QSAR models, in contrast to boiling points and critical parameters derived from empirical correlations, to improve...Quadratic Configuration Interaction Singles Doubles QSAR Quantitative Structure-Activity Relationship QSPR Quantitative Structure-Property

Investigation into discretization methods of the six-parameter Iwan model

NASA Astrophysics Data System (ADS)

Li, Yikun; Hao, Zhiming; Feng, Jiaquan; Zhang, Dingguo

2017-02-01

Iwan model is widely applied for the purpose of describing nonlinear mechanisms of jointed structures. In this paper, parameter identification procedures of the six-parameter Iwan model based on joint experiments with different preload techniques are performed. Four kinds of discretization methods deduced from stiffness equation of the six-parameter Iwan model are provided, which can be used to discretize the integral-form Iwan model into a sum of finite Jenkins elements. In finite element simulation, the influences of discretization methods and numbers of Jenkins elements on computing accuracy are discussed. Simulation results indicate that a higher accuracy can be obtained with larger numbers of Jenkins elements. It is also shown that compared with other three kinds of discretization methods, the geometric series discretization based on stiffness provides the highest computing accuracy.

Variation of the subsidence parameters, effective thermal conductivity, and mantle dynamics

NASA Astrophysics Data System (ADS)

Adam, C.; King, S. D.; Vidal, V.; Rabinowicz, M.; Jalobeanu, A.; Yoshida, M.

2015-09-01

The subsidence of young seafloor is generally considered to be a passive phenomenon related to the conductive cooling of the lithosphere after its creation at mid-oceanic ridges. Recent alternative theories suggest that the mantle dynamics plays an important role in the structure and depth of the oceanic lithosphere. However, the link between mantle dynamics and seafloor subsidence has still to be quantitatively assessed. Here we provide a statistical study of the subsidence parameters (subsidence rate and ridge depth) for all the oceans. These parameters are retrieved through two independent methods, the positive outliers method, a classical method used in signal processing, and through the MiFil method. From the subsidence rate, we compute the effective thermal conductivity, keff, which ranges between 1 and 7 W m-1 K-1. We also model the mantle flow pattern from the S40RTS tomography model. The density anomalies derived from S40RTS are used to compute the instantaneous flow in a global 3D spherical geometry. We show that departures from the keff = 3 Wm-1K-1 standard value are systematically related to mantle processes and not to lithospheric structure. Regions characterized by keff > 3 Wm-1K-1 are associated with mantle uplifts (mantle plumes or other local anomalies). Regions characterized by keff < 3 Wm-1K-1 are related to large-scale mantle downwellings such as the Australia-Antarctic Discordance (AAD) or the return flow from the South Pacific Superswell to the East Pacific Rise. This demonstrates that mantle dynamics plays a major role in the shaping of the oceanic seafloor. In particular, the parameters generally considered to quantify the lithosphere structure, such as the thermal conductivity, are not only representative of this structure but also incorporate signals from the mantle convection occurring beneath the lithosphere. The dynamic topography computed from the S40RTS tomography model reproduces the subsidence pattern observed in the bathymetry. Overall we find a good correlation between the subsidence parameters derived from the bathymetry and the dynamic topography. This demonstrates that these parameters are strongly dependent on mantle dynamics.

Total-energy Assisted Tight-binding Method Based on Local Density Approximation of Density Functional Theory

NASA Astrophysics Data System (ADS)

Fujiwara, Takeo; Nishino, Shinya; Yamamoto, Susumu; Suzuki, Takashi; Ikeda, Minoru; Ohtani, Yasuaki

2018-06-01

A novel tight-binding method is developed, based on the extended Hückel approximation and charge self-consistency, with referring the band structure and the total energy of the local density approximation of the density functional theory. The parameters are so adjusted by computer that the result reproduces the band structure and the total energy, and the algorithm for determining parameters is established. The set of determined parameters is applicable to a variety of crystalline compounds and change of lattice constants, and, in other words, it is transferable. Examples are demonstrated for Si crystals of several crystalline structures varying lattice constants. Since the set of parameters is transferable, the present tight-binding method may be applicable also to molecular dynamics simulations of large-scale systems and long-time dynamical processes.

Methods for evaluating the predictive accuracy of structural dynamic models

NASA Technical Reports Server (NTRS)

Hasselman, T. K.; Chrostowski, Jon D.

1990-01-01

Uncertainty of frequency response using the fuzzy set method and on-orbit response prediction using laboratory test data to refine an analytical model are emphasized with respect to large space structures. Two aspects of the fuzzy set approach were investigated relative to its application to large structural dynamics problems: (1) minimizing the number of parameters involved in computing possible intervals; and (2) the treatment of extrema which may occur in the parameter space enclosed by all possible combinations of the important parameters of the model. Extensive printer graphics were added to the SSID code to help facilitate model verification, and an application of this code to the LaRC Ten Bay Truss is included in the appendix to illustrate this graphics capability.

Multiscale Multifunctional Progressive Fracture of Composite Structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Minnetyan, L.

2012-01-01

A new approach is described for evaluating fracture in composite structures. This approach is independent of classical fracture mechanics parameters like fracture toughness. It relies on computational simulation and is programmed in a stand-alone integrated computer code. It is multiscale, multifunctional because it includes composite mechanics for the composite behavior and finite element analysis for predicting the structural response. It contains seven modules; layered composite mechanics (micro, macro, laminate), finite element, updating scheme, local fracture, global fracture, stress based failure modes, and fracture progression. The computer code is called CODSTRAN (Composite Durability Structural ANalysis). It is used in the present paper to evaluate the global fracture of four composite shell problems and one composite built-up structure. Results show that the composite shells. Global fracture is enhanced when internal pressure is combined with shear loads. The old reference denotes that nothing has been added to this comprehensive report since then.

Nonlinear, discrete flood event models, 1. Bayesian estimation of parameters

NASA Astrophysics Data System (ADS)

Bates, Bryson C.; Townley, Lloyd R.

1988-05-01

In this paper (Part 1), a Bayesian procedure for parameter estimation is applied to discrete flood event models. The essence of the procedure is the minimisation of a sum of squares function for models in which the computed peak discharge is nonlinear in terms of the parameters. This objective function is dependent on the observed and computed peak discharges for several storms on the catchment, information on the structure of observation error, and prior information on parameter values. The posterior covariance matrix gives a measure of the precision of the estimated parameters. The procedure is demonstrated using rainfall and runoff data from seven Australian catchments. It is concluded that the procedure is a powerful alternative to conventional parameter estimation techniques in situations where a number of floods are available for parameter estimation. Parts 2 and 3 will discuss the application of statistical nonlinearity measures and prediction uncertainty analysis to calibrated flood models. Bates (this volume) and Bates and Townley (this volume).

A Computational Approach for Model Update of an LS-DYNA Energy Absorbing Cell

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Jackson, Karen E.; Kellas, Sotiris

2008-01-01

NASA and its contractors are working on structural concepts for absorbing impact energy of aerospace vehicles. Recently, concepts in the form of multi-cell honeycomb-like structures designed to crush under load have been investigated for both space and aeronautics applications. Efforts to understand these concepts are progressing from tests of individual cells to tests of systems with hundreds of cells. Because of fabrication irregularities, geometry irregularities, and material properties uncertainties, the problem of reconciling analytical models, in particular LS-DYNA models, with experimental data is a challenge. A first look at the correlation results between single cell load/deflection data with LS-DYNA predictions showed problems which prompted additional work in this area. This paper describes a computational approach that uses analysis of variance, deterministic sampling techniques, response surface modeling, and genetic optimization to reconcile test with analysis results. Analysis of variance provides a screening technique for selection of critical parameters used when reconciling test with analysis. In this study, complete ignorance of the parameter distribution is assumed and, therefore, the value of any parameter within the range that is computed using the optimization procedure is considered to be equally likely. Mean values from tests are matched against LS-DYNA solutions by minimizing the square error using a genetic optimization. The paper presents the computational methodology along with results obtained using this approach.

Model verification of large structural systems. [space shuttle model response

NASA Technical Reports Server (NTRS)

Lee, L. T.; Hasselman, T. K.

1978-01-01

A computer program for the application of parameter identification on the structural dynamic models of space shuttle and other large models with hundreds of degrees of freedom is described. Finite element, dynamic, analytic, and modal models are used to represent the structural system. The interface with math models is such that output from any structural analysis program applied to any structural configuration can be used directly. Processed data from either sine-sweep tests or resonant dwell tests are directly usable. The program uses measured modal data to condition the prior analystic model so as to improve the frequency match between model and test. A Bayesian estimator generates an improved analytical model and a linear estimator is used in an iterative fashion on highly nonlinear equations. Mass and stiffness scaling parameters are generated for an improved finite element model, and the optimum set of parameters is obtained in one step.

An improved wavelet-Galerkin method for dynamic response reconstruction and parameter identification of shear-type frames

NASA Astrophysics Data System (ADS)

Bu, Haifeng; Wang, Dansheng; Zhou, Pin; Zhu, Hongping

2018-04-01

An improved wavelet-Galerkin (IWG) method based on the Daubechies wavelet is proposed for reconstructing the dynamic responses of shear structures. The proposed method flexibly manages wavelet resolution level according to excitation, thereby avoiding the weakness of the wavelet-Galerkin multiresolution analysis (WGMA) method in terms of resolution and the requirement of external excitation. IWG is implemented by this work in certain case studies, involving single- and n-degree-of-freedom frame structures subjected to a determined discrete excitation. Results demonstrate that IWG performs better than WGMA in terms of accuracy and computation efficiency. Furthermore, a new method for parameter identification based on IWG and an optimization algorithm are also developed for shear frame structures, and a simultaneous identification of structural parameters and excitation is implemented. Numerical results demonstrate that the proposed identification method is effective for shear frame structures.

A three-dimensional bioprinting system for use with a hydrogel-based biomaterial and printing parameter characterization.

PubMed

Song, Seung-Joon; Choi, Jaesoon; Park, Yong-Doo; Lee, Jung-Joo; Hong, So Young; Sun, Kyung

2010-11-01

Bioprinting is an emerging technology for constructing tissue or bioartificial organs with complex three-dimensional (3D) structures. It provides high-precision spatial shape forming ability on a larger scale than conventional tissue engineering methods, and simultaneous multiple components composition ability. Bioprinting utilizes a computer-controlled 3D printer mechanism for 3D biological structure construction. To implement minimal pattern width in a hydrogel-based bioprinting system, a study on printing characteristics was performed by varying printer control parameters. The experimental results showed that printing pattern width depends on associated printer control parameters such as printing flow rate, nozzle diameter, and nozzle velocity. The system under development showed acceptable feasibility of potential use for accurate printing pattern implementation in tissue engineering applications and is another example of novel techniques for regenerative medicine based on computer-aided biofabrication system. © 2010, Copyright the Authors. Artificial Organs © 2010, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Cumulutive reports and publications through December 31, 1984

NASA Technical Reports Server (NTRS)

1985-01-01

A complete list of the Institute for Computer Applications in Science and Engineering (ICASE) Reports are given. Since ICASE Reports are intended to be preprints of articles that will appear in journals or conference proceedings, the published reference is included when it is available. Topics include numerical methods, parameter identification, fluid dynamics, acoustics, structural analysis, and computers.

Computational study of the melting-freezing transition in the quantum hard-sphere system for intermediate densities. II. Structural features.

PubMed

Sesé, Luis M; Bailey, Lorna E

2007-04-28

The structural features of the quantum hard-sphere system in the region of the fluid-face-centered-cubic-solid transition, for reduced number densities 0.45

Analysis of the structural behaviour of colonic segments by inflation tests: Experimental activity and physio-mechanical model.

PubMed

Carniel, Emanuele L; Mencattelli, Margherita; Bonsignori, Gabriella; Fontanella, Chiara G; Frigo, Alessandro; Rubini, Alessandro; Stefanini, Cesare; Natali, Arturo N

2015-11-01

A coupled experimental and computational approach is provided for the identification of the structural behaviour of gastrointestinal regions, accounting for both elastic and visco-elastic properties. The developed procedure is applied to characterize the mechanics of gastrointestinal samples from pig colons. Experimental data about the structural behaviour of colonic segments are provided by inflation tests. Different inflation processes are performed according to progressively increasing top pressure conditions. Each inflation test consists of an air in-flow, according to an almost constant increasing pressure rate, such as 3.5 mmHg/s, up to a prescribed top pressure, which is held constant for about 300 s to allow the development of creep phenomena. Different tests are interspersed by 600 s of rest to allow the recovery of the tissues' mechanical condition. Data from structural tests are post-processed by a physio-mechanical model in order to identify the mechanical parameters that interpret both the non-linear elastic behaviour of the sample, as the instantaneous pressure-stretch trend, and the time-dependent response, as the stretch increase during the creep processes. The parameters are identified by minimizing the discrepancy between experimental and model results. Different sets of parameters are evaluated for different specimens from different pigs. A statistical analysis is performed to evaluate the distribution of the parameters and to assess the reliability of the experimental and computational activities. © IMechE 2015.

Variability of morphometric parameters of human trabecular tissue from coxo-arthritis and osteoporotic samples.

PubMed

Marinozzi, Franco; Marinozzi, Andrea; Bini, Fabiano; Zuppante, Francesca; Pecci, Raffaella; Bedini, Rossella

2012-01-01

Morphometric and architectural bone parameters change in diseases such as osteoarthritis and osteoporosis. The mechanical strength of bone is primarily influenced by bone quantity and quality. Bone quality is defined by parameters such as trabecular thickness, trabecular separation, trabecular density and degree of anisotropy that describe the micro-architectural structure of bone. Recently, many studies have validated microtomography as a valuable investigative technique to assess bone morphometry, thanks to micro-CT non-destructive, non-invasive and reliability features, in comparison to traditional techniques such as histology. The aim of this study is the analysis by micro-computed tomography of six specimens, extracted from patients affected by osteoarthritis and osteoporosis, in order to observe the tridimensional structure and calculate several morphometric parameters.

Long term pavement performance computed parameter : frost penetration

DOT National Transportation Integrated Search

2008-11-01

As the pavement design process moves toward mechanistic-empirical techniques, knowledge of seasonal changes in pavement structural characteristics becomes critical. Specifically, frost penetration information is necessary for determining the effect o...

Wind-US Unstructured Flow Solutions for a Transonic Diffuser

NASA Technical Reports Server (NTRS)

Mohler, Stanley R., Jr.

2005-01-01

The Wind-US Computational Fluid Dynamics flow solver computed flow solutions for a transonic diffusing duct. The calculations used an unstructured (hexahedral) grid. The Spalart-Allmaras turbulence model was used. Static pressures along the upper and lower wall agreed well with experiment, as did velocity profiles. The effect of the smoothing input parameters on convergence and solution accuracy was investigated. The meaning and proper use of these parameters are discussed for the benefit of Wind-US users. Finally, the unstructured solver is compared to the structured solver in terms of run times and solution accuracy.

Robust simulation of buckled structures using reduced order modeling

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Uniscale multi-view registration using double dog-leg method

NASA Astrophysics Data System (ADS)

Chen, Chao-I.; Sargent, Dusty; Tsai, Chang-Ming; Wang, Yuan-Fang; Koppel, Dan

2009-02-01

3D computer models of body anatomy can have many uses in medical research and clinical practices. This paper describes a robust method that uses videos of body anatomy to construct multiple, partial 3D structures and then fuse them to form a larger, more complete computer model using the structure-from-motion framework. We employ the Double Dog-Leg (DDL) method, a trust-region based nonlinear optimization method, to jointly optimize the camera motion parameters (rotation and translation) and determine a global scale that all partial 3D structures should agree upon. These optimized motion parameters are used for constructing local structures, and the global scale is essential for multi-view registration after all these partial structures are built. In order to provide a good initial guess of the camera movement parameters and outlier free 2D point correspondences for DDL, we also propose a two-stage scheme where multi-RANSAC with a normalized eight-point algorithm is first performed and then a few iterations of an over-determined five-point algorithm is used to polish the results. Our experimental results using colonoscopy video show that the proposed scheme always produces more accurate outputs than the standard RANSAC scheme. Furthermore, since we have obtained many reliable point correspondences, time-consuming and error-prone registration methods like the iterative closest points (ICP) based algorithms can be replaced by a simple rigid-body transformation solver when merging partial structures into a larger model.

Structure factor and radial distribution function of some liquid lanthanides using charged hard sphere

NASA Astrophysics Data System (ADS)

Patel, H. P.; Sonvane, Y. A.; Thakor, P. B.

2017-05-01

The structure factor S(q) and radial distribution function g(r) play vital role to study the various structural properties like electronic, dynamic, magnetic etc. The present paper deals with the structural studies of foresaid properties using our newly constructed parameter free model potential with the Charged Hard Sphere (CHS) approximation. The local field correction due to Sarkar et al. is used to incorporate exchange and correlation among the conduction electrons in dielectric screening. Here we report the S(q) and g(r) for some liquid lanthanides viz: La, Ce, Pr, Nd and Eu. Present computed results are compared with the available experimental data. Lastly we found that our parameter free model potential successfully explains the structural propertiesof4fliquidlanthanides.

A Computational Framework for Identifiability and Ill-Conditioning Analysis of Lithium-Ion Battery Models

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

López C, Diana C.; Wozny, Günter; Flores-Tlacuahuac, Antonio

2016-03-23

The lack of informative experimental data and the complexity of first-principles battery models make the recovery of kinetic, transport, and thermodynamic parameters complicated. We present a computational framework that combines sensitivity, singular value, and Monte Carlo analysis to explore how different sources of experimental data affect parameter structural ill conditioning and identifiability. Our study is conducted on a modified version of the Doyle-Fuller-Newman model. We demonstrate that the use of voltage discharge curves only enables the identification of a small parameter subset, regardless of the number of experiments considered. Furthermore, we show that the inclusion of a single electrolyte concentrationmore » measurement significantly aids identifiability and mitigates ill-conditioning.« less

Process model comparison and transferability across bioreactor scales and modes of operation for a mammalian cell bioprocess.

PubMed

Craven, Stephen; Shirsat, Nishikant; Whelan, Jessica; Glennon, Brian

2013-01-01

A Monod kinetic model, logistic equation model, and statistical regression model were developed for a Chinese hamster ovary cell bioprocess operated under three different modes of operation (batch, bolus fed-batch, and continuous fed-batch) and grown on two different bioreactor scales (3 L bench-top and 15 L pilot-scale). The Monod kinetic model was developed for all modes of operation under study and predicted cell density, glucose glutamine, lactate, and ammonia concentrations well for the bioprocess. However, it was computationally demanding due to the large number of parameters necessary to produce a good model fit. The transferability of the Monod kinetic model structure and parameter set across bioreactor scales and modes of operation was investigated and a parameter sensitivity analysis performed. The experimentally determined parameters had the greatest influence on model performance. They changed with scale and mode of operation, but were easily calculated. The remaining parameters, which were fitted using a differential evolutionary algorithm, were not as crucial. Logistic equation and statistical regression models were investigated as alternatives to the Monod kinetic model. They were less computationally intensive to develop due to the absence of a large parameter set. However, modeling of the nutrient and metabolite concentrations proved to be troublesome due to the logistic equation model structure and the inability of both models to incorporate a feed. The complexity, computational load, and effort required for model development has to be balanced with the necessary level of model sophistication when choosing which model type to develop for a particular application. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

Derivatives of buckling loads and vibration frequencies with respect to stiffness and initial strain parameters

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.; Cohen, Gerald A.; Mroz, Zenon

1990-01-01

A uniform variational approach to sensitivity analysis of vibration frequencies and bifurcation loads of nonlinear structures is developed. Two methods of calculating the sensitivities of bifurcation buckling loads and vibration frequencies of nonlinear structures, with respect to stiffness and initial strain parameters, are presented. A direct method requires calculation of derivatives of the prebuckling state with respect to these parameters. An adjoint method bypasses the need for these derivatives by using instead the strain field associated with the second-order postbuckling state. An operator notation is used and the derivation is based on the principle of virtual work. The derivative computations are easily implemented in structural analysis programs. This is demonstrated by examples using a general purpose, finite element program and a shell-of-revolution program.

Interplay of stereoelectronic and enviromental effects in tuning the structural and magnetic properties of a prototypical spin probe: further insights from a first principle dynamical approach.

PubMed

Pavone, Michele; Cimino, Paola; De Angelis, Filippo; Barone, Vincenzo

2006-04-05

The nitrogen isotropic hyperfine coupling constant (hcc) and the g tensor of a prototypical spin probe (di-tert-butyl nitroxide, DTBN) in aqueous solution have been investigated by means of an integrated computational approach including Car-Parrinello molecular dynamics and quantum mechanical calculations involving a discrete-continuum embedding. The quantitative agreement between computed and experimental parameters fully validates our integrated approach. Decoupling of the structural, dynamical, and environmental contributions acting onto the spectral observables allows an unbiased judgment of the role played by different effects in determining the overall experimental observables and highlights the importance of finite-temperature vibrational averaging. Together with their intrinsic interest, our results pave the route toward more reliable interpretations of EPR parameters of complex systems of biological and technological relevance.

Study of eigenfrequencies with the help of Prony's method

NASA Astrophysics Data System (ADS)

Drobakhin, O. O.; Olevskyi, O. V.; Olevskyi, V. I.

2017-10-01

Eigenfrequencies can be crucial in the design of a construction. They define many parameters that determine limit parameters of the structure. Exceeding these values can lead to the structural failure of an object. It is especially important in the design of structures which support heavy equipment or are subjected to the forces of airflow. One of the most effective ways to acquire the frequencies' values is a computer-based numerical simulation. The existing methods do not allow to acquire the whole range of needed parameters. It is well known that Prony's method, is highly effective for the investigation of dynamic processes. Thus, it is rational to adapt Prony's method for such investigation. The Prony method has advantage in comparison with other numerical schemes because it provides the possibility to process not only the results of numerical simulation, but also real experimental data. The research was carried out for a computer model of a steel plate. The input data was obtained by using the Dassault Systems SolidWorks computer package with the Simulation add-on. We investigated the acquired input data with the help of Prony's method. The result of the numerical experiment shows that Prony's method can be used to investigate the mechanical eigenfrequencies with good accuracy. The output of Prony's method not only contains the information about values of frequencies themselves, but also contains data regarding the amplitudes, initial phases and decaying factors of any given mode of oscillation, which can also be used in engineering.

A computational NMR study on zigzag aluminum nitride nanotubes

NASA Astrophysics Data System (ADS)

Bodaghi, Ali; Mirzaei, Mahmoud; Seif, Ahmad; Giahi, Masoud

2008-12-01

A computational nuclear magnetic resonance (NMR) study is performed to investigate the electronic structure properties of the single-walled zigzag aluminum nitride nanotubes (AlNNTs). The chemical-shielding (CS) tensors are calculated at the sites of Al-27 and N-15 nuclei in three structural forms of AlNNT including H-saturated, Al-terminated, and N-terminated ones. The structural forms are firstly optimized and then the calculated CS tensors in the optimized structures are converted to chemical-shielding isotropic (CSI) and chemical-shielding anisotropic (CSA) parameters. The calculated parameters reveal that various Al-27 and N-15 nuclei are divided into some layers with equivalent electrostatic properties; furthermore, Al and N can act as Lewis base and acid, respectively. In the Al-terminated and N-terminated forms of AlNNT, in which one mouth of the nanotube is terminated by aluminum and nitrogen nuclei, respectively, just the CS tensors of the nearest nuclei to the mouth of the nanotube are significantly changed due to removal of saturating hydrogen atoms. Density functional theory (DFT) calculations are performed using GAUSSIAN 98 package of program.

Real-time moving horizon estimation for a vibrating active cantilever

NASA Astrophysics Data System (ADS)

Abdollahpouri, Mohammad; Takács, Gergely; Rohaľ-Ilkiv, Boris

2017-03-01

Vibrating structures may be subject to changes throughout their operating lifetime due to a range of environmental and technical factors. These variations can be considered as parameter changes in the dynamic model of the structure, while their online estimates can be utilized in adaptive control strategies, or in structural health monitoring. This paper implements the moving horizon estimation (MHE) algorithm on a low-cost embedded computing device that is jointly observing the dynamic states and parameter variations of an active cantilever beam in real time. The practical behavior of this algorithm has been investigated in various experimental scenarios. It has been found, that for the given field of application, moving horizon estimation converges faster than the extended Kalman filter; moreover, it handles atypical measurement noise, sensor errors or other extreme changes, reliably. Despite its improved performance, the experiments demonstrate that the disadvantage of solving the nonlinear optimization problem in MHE is that it naturally leads to an increase in computational effort.

Structure simulation with calculated NMR parameters - integrating COSMOS into the CCPN framework.

PubMed

Schneider, Olaf; Fogh, Rasmus H; Sternberg, Ulrich; Klenin, Konstantin; Kondov, Ivan

2012-01-01

The Collaborative Computing Project for NMR (CCPN) has build a software framework consisting of the CCPN data model (with APIs) for NMR related data, the CcpNmr Analysis program and additional tools like CcpNmr FormatConverter. The open architecture allows for the integration of external software to extend the abilities of the CCPN framework with additional calculation methods. Recently, we have carried out the first steps for integrating our software Computer Simulation of Molecular Structures (COSMOS) into the CCPN framework. The COSMOS-NMR force field unites quantum chemical routines for the calculation of molecular properties with a molecular mechanics force field yielding the relative molecular energies. COSMOS-NMR allows introducing NMR parameters as constraints into molecular mechanics calculations. The resulting infrastructure will be made available for the NMR community. As a first application we have tested the evaluation of calculated protein structures using COSMOS-derived 13C Cα and Cβ chemical shifts. In this paper we give an overview of the methodology and a roadmap for future developments and applications.

Nonlinear finite element model updating for damage identification of civil structures using batch Bayesian estimation

NASA Astrophysics Data System (ADS)

Ebrahimian, Hamed; Astroza, Rodrigo; Conte, Joel P.; de Callafon, Raymond A.

2017-02-01

This paper presents a framework for structural health monitoring (SHM) and damage identification of civil structures. This framework integrates advanced mechanics-based nonlinear finite element (FE) modeling and analysis techniques with a batch Bayesian estimation approach to estimate time-invariant model parameters used in the FE model of the structure of interest. The framework uses input excitation and dynamic response of the structure and updates a nonlinear FE model of the structure to minimize the discrepancies between predicted and measured response time histories. The updated FE model can then be interrogated to detect, localize, classify, and quantify the state of damage and predict the remaining useful life of the structure. As opposed to recursive estimation methods, in the batch Bayesian estimation approach, the entire time history of the input excitation and output response of the structure are used as a batch of data to estimate the FE model parameters through a number of iterations. In the case of non-informative prior, the batch Bayesian method leads to an extended maximum likelihood (ML) estimation method to estimate jointly time-invariant model parameters and the measurement noise amplitude. The extended ML estimation problem is solved efficiently using a gradient-based interior-point optimization algorithm. Gradient-based optimization algorithms require the FE response sensitivities with respect to the model parameters to be identified. The FE response sensitivities are computed accurately and efficiently using the direct differentiation method (DDM). The estimation uncertainties are evaluated based on the Cramer-Rao lower bound (CRLB) theorem by computing the exact Fisher Information matrix using the FE response sensitivities with respect to the model parameters. The accuracy of the proposed uncertainty quantification approach is verified using a sampling approach based on the unscented transformation. Two validation studies, based on realistic structural FE models of a bridge pier and a moment resisting steel frame, are performed to validate the performance and accuracy of the presented nonlinear FE model updating approach and demonstrate its application to SHM. These validation studies show the excellent performance of the proposed framework for SHM and damage identification even in the presence of high measurement noise and/or way-out initial estimates of the model parameters. Furthermore, the detrimental effects of the input measurement noise on the performance of the proposed framework are illustrated and quantified through one of the validation studies.

NASA LeRC/Akron University Graduate Cooperative Fellowship Program and Graduate Student Researchers Program

NASA Technical Reports Server (NTRS)

Fertis, D. G.; Simon, A. L.

1981-01-01

The requisite methodology to solve linear and nonlinear problems associated with the static and dynamic analysis of rotating machinery, their static and dynamic behavior, and the interaction between the rotating and nonrotating parts of an engine is developed. Linear and nonlinear structural engine problems are investigated by developing solution strategies and interactive computational methods whereby the man and computer can communicate directly in making analysis decisions. Representative examples include modifying structural models, changing material, parameters, selecting analysis options and coupling with interactive graphical display for pre- and postprocessing capability.

Development of optimized techniques and requirements for computer enhancement of structural weld radiographs. Volume 1: Technical report

NASA Technical Reports Server (NTRS)

Adams, J. R.; Hawley, S. W.; Peterson, G. R.; Salinger, S. S.; Workman, R. A.

1971-01-01

A hardware and software specification covering requirements for the computer enhancement of structural weld radiographs was considered. Three scanning systems were used to digitize more than 15 weld radiographs. The performance of these systems was evaluated by determining modulation transfer functions and noise characteristics. Enhancement techniques were developed and applied to the digitized radiographs. The scanning parameters of spot size and spacing and film density were studied to optimize the information content of the digital representation of the image.

The use of three-parameter rating table lookup programs, RDRAT and PARM3, in hydraulic flow models

USGS Publications Warehouse

Sanders, C.L.

1995-01-01

Subroutines RDRAT and PARM3 enable computer programs such as the BRANCH open-channel unsteady-flow model to route flows through or over combinations of critical-flow sections, culverts, bridges, road- overflow sections, fixed spillways, and(or) dams. The subroutines also obstruct upstream flow to simulate operation of flapper-type tide gates. A multiplier can be applied by date and time to simulate varying numbers of tide gates being open or alternative construction scenarios for multiple culverts. The subroutines use three-parameter (headwater, tailwater, and discharge) rating table lookup methods. These tables may be manually prepared using other programs that do step-backwater computations or compute flow through bridges and culverts or over dams. The subroutine, therefore, precludes the necessity of incorporating considerable hydraulic computational code into the client program, and provides complete flexibility for users of the model for routing flow through almost any affixed structure or combination of structures. The subroutines are written in Fortran 77 language, and have minimal exchange of information with the BRANCH model or other possible client programs. The report documents the interpolation methodology, data input requirements, and software.

Macro- and micro-chaotic structures in the Hindmarsh-Rose model of bursting neurons

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

Barrio, Roberto, E-mail: rbarrio@unizar.es; Serrano, Sergio; Angeles Martínez, M.

2014-06-01

We study a plethora of chaotic phenomena in the Hindmarsh-Rose neuron model with the use of several computational techniques including the bifurcation parameter continuation, spike-quantification, and evaluation of Lyapunov exponents in bi-parameter diagrams. Such an aggregated approach allows for detecting regions of simple and chaotic dynamics, and demarcating borderlines—exact bifurcation curves. We demonstrate how the organizing centers—points corresponding to codimension-two homoclinic bifurcations—along with fold and period-doubling bifurcation curves structure the biparametric plane, thus forming macro-chaotic regions of onion bulb shapes and revealing spike-adding cascades that generate micro-chaotic structures due to the hysteresis.

Computational study of some fluoroquinolones: Structural, spectral and docking investigations

NASA Astrophysics Data System (ADS)

Sayin, Koray; Karakaş, Duran; Kariper, Sultan Erkan; Sayin, Tuba Alagöz

2018-03-01

Quantum chemical calculations are performed over norfloxacin, tosufloxacin and levofloxacin. The most stable structures for each molecule are determined by thermodynamic parameters. Then the best level for calculations is determined by benchmark analysis. M062X/6-31 + G(d) level is used in calculations. IR, UV-VIS and NMR spectrum are calculated and examined in detail. Some quantum chemical parameters are calculated and the tendency of activity is recommended. Additionally, molecular docking calculations are performed between related compounds and a protein (ID: 2J9N).

Dynamic properties of epidemic spreading on finite size complex networks

NASA Astrophysics Data System (ADS)

Li, Ying; Liu, Yang; Shan, Xiu-Ming; Ren, Yong; Jiao, Jian; Qiu, Ben

2005-11-01

The Internet presents a complex topological structure, on which computer viruses can easily spread. By using theoretical analysis and computer simulation methods, the dynamic process of disease spreading on finite size networks with complex topological structure is investigated. On the finite size networks, the spreading process of SIS (susceptible-infected-susceptible) model is a finite Markov chain with an absorbing state. Two parameters, the survival probability and the conditional infecting probability, are introduced to describe the dynamic properties of disease spreading on finite size networks. Our results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks. Also, knowledge about the dynamic character of virus spreading is helpful for adopting immunity policy.

Effects of computing parameters and measurement locations on the estimation of 3D NPS in non-stationary MDCT images.

PubMed

Miéville, Frédéric A; Bolard, Gregory; Bulling, Shelley; Gudinchet, François; Bochud, François O; Verdun, François R

2013-11-01

The goal of this study was to investigate the impact of computing parameters and the location of volumes of interest (VOI) on the calculation of 3D noise power spectrum (NPS) in order to determine an optimal set of computing parameters and propose a robust method for evaluating the noise properties of imaging systems. Noise stationarity in noise volumes acquired with a water phantom on a 128-MDCT and a 320-MDCT scanner were analyzed in the spatial domain in order to define locally stationary VOIs. The influence of the computing parameters in the 3D NPS measurement: the sampling distances bx,y,z and the VOI lengths Lx,y,z, the number of VOIs NVOI and the structured noise were investigated to minimize measurement errors. The effect of the VOI locations on the NPS was also investigated. Results showed that the noise (standard deviation) varies more in the r-direction (phantom radius) than z-direction plane. A 25 × 25 × 40 mm(3) VOI associated with DFOV = 200 mm (Lx,y,z = 64, bx,y = 0.391 mm with 512 × 512 matrix) and a first-order detrending method to reduce structured noise led to an accurate NPS estimation. NPS estimated from off centered small VOIs had a directional dependency contrary to NPS obtained from large VOIs located in the center of the volume or from small VOIs located on a concentric circle. This showed that the VOI size and location play a major role in the determination of NPS when images are not stationary. This study emphasizes the need for consistent measurement methods to assess and compare image quality in CT. Copyright © 2012 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Subspace algorithms for identifying separable-in-denominator 2D systems with deterministic-stochastic inputs

NASA Astrophysics Data System (ADS)

Ramos, José A.; Mercère, Guillaume

2016-12-01

In this paper, we present an algorithm for identifying two-dimensional (2D) causal, recursive and separable-in-denominator (CRSD) state-space models in the Roesser form with deterministic-stochastic inputs. The algorithm implements the N4SID, PO-MOESP and CCA methods, which are well known in the literature on 1D system identification, but here we do so for the 2D CRSD Roesser model. The algorithm solves the 2D system identification problem by maintaining the constraint structure imposed by the problem (i.e. Toeplitz and Hankel) and computes the horizontal and vertical system orders, system parameter matrices and covariance matrices of a 2D CRSD Roesser model. From a computational point of view, the algorithm has been presented in a unified framework, where the user can select which of the three methods to use. Furthermore, the identification task is divided into three main parts: (1) computing the deterministic horizontal model parameters, (2) computing the deterministic vertical model parameters and (3) computing the stochastic components. Specific attention has been paid to the computation of a stabilised Kalman gain matrix and a positive real solution when required. The efficiency and robustness of the unified algorithm have been demonstrated via a thorough simulation example.

Effect of Discontinuities and Uncertainties on the Response and Failure of Composite Structures

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Perry, Ferman W.; Poteat, Marcia M. (Technical Monitor)

2000-01-01

The overall goal of this research was to assess the effect of discontinuities and uncertainties on the nonlinear response and failure of composite structures subjected to combined mechanical and thermal loads. The four key elements of the study were: (1) development of simple and efficient procedures for the accurate determination of transverse shear and transverse normal stresses in structural sandwiches as well as in unstiffened and stiffened composite panels and shells; (2) study the effects of transverse stresses on the response, damage initiation and propagation in composite and sandwich structures; (3) use of hierarchical sensitivity coefficients to identify the major parameters that affect the response and damage in each of the different levels in the hierarchy (micro-mechanical, layer, panel, subcomponent and component levels); and (4) application of fuzzy set techniques to identify the range and variation of possible responses. The computational models developed were used in conjunction with experiments, to understand the physical phenomena associated with the nonlinear response and failure of composite and sandwich structures. A toolkit was developed for use in conjunction with deterministic analysis programs to help the designer in assessing the effect of uncertainties in the different computational model parameters on the variability of the response quantities.

In vitro flow assessment: from PC-MRI to computational fluid dynamics including fluid-structure interaction

NASA Astrophysics Data System (ADS)

Kratzke, Jonas; Rengier, Fabian; Weis, Christian; Beller, Carsten J.; Heuveline, Vincent

2016-04-01

Initiation and development of cardiovascular diseases can be highly correlated to specific biomechanical parameters. To examine and assess biomechanical parameters, numerical simulation of cardiovascular dynamics has the potential to complement and enhance medical measurement and imaging techniques. As such, computational fluid dynamics (CFD) have shown to be suitable to evaluate blood velocity and pressure in scenarios, where vessel wall deformation plays a minor role. However, there is a need for further validation studies and the inclusion of vessel wall elasticity for morphologies being subject to large displacement. In this work, we consider a fluid-structure interaction (FSI) model including the full elasticity equation to take the deformability of aortic wall soft tissue into account. We present a numerical framework, in which either a CFD study can be performed for less deformable aortic segments or an FSI simulation for regions of large displacement such as the aortic root and arch. Both of the methods are validated by means of an aortic phantom experiment. The computational results are in good agreement with 2D phase-contrast magnetic resonance imaging (PC-MRI) velocity measurements as well as catheter-based pressure measurements. The FSI simulation shows a characteristic vessel compliance effect on the flow field induced by the elasticity of the vessel wall, which the CFD model is not capable of. The in vitro validated FSI simulation framework can enable the computation of complementary biomechanical parameters such as the stress distribution within the vessel wall.

Does exposure to computers affect the routine parameters of semen quality?

PubMed

Sun, Yue-Lian; Zhou, Wei-Jin; Wu, Jun-Qing; Gao, Er-Sheng

2005-09-01

To assess whether exposure to computers harms the semen quality of healthy young men. A total of 178 subjects were recruited from two maternity and children healthcare centers in Shanghai, 91 with a history of exposure to computers (i.e., exposure for 20 h or more per week in the last 2 years) and 87 persons to act as control (no or little exposure to computers). Data on the history of exposure to computers and other characteristics were obtained by means of a structured questionnaire interview. Semen samples were collected by masturbation in the place where the semen samples were analyzed. No differences in the distribution of the semen parameters (semen volume, sperm density, percentage of progressive sperm, sperm viability and percentage of normal form sperm) were found between the exposed group and the control group. Exposure to computers was not found to be a risk factor for inferior semen quality after adjusting for potential confounders, including abstinence days, testicle size, occupation, history of exposure to toxic substances. The present study did not find that healthy men exposed to computers had inferior semen quality.

On the crystal structure of the vaterite polymorph of CaCO3: a calcium-43 solid-state NMR and computational assessment.

PubMed

Burgess, Kevin M N; Bryce, David L

2015-02-01

The vaterite polymorph of CaCO3 has puzzled crystallographers for decades in part due to difficulties in obtaining single crystals. The multiple proposed structures for the vaterite polymorph of CaCO3 are assessed using a combined (43)Ca solid-state nuclear magnetic resonance (SSNMR) spectroscopic and computational approach. A combination of improved experimental and computational methods, along with a calibrated chemical shift scale and (43)Ca nuclear quadrupole moment, allow for improved insights relative to our earlier work (Bryce et al., J. Am. Chem. Soc. 2008, 130, 9282). Here, we synthesize a (43)Ca isotopically-enriched sample of vaterite and perform high-resolution quadrupolar SSNMR experiments including magic-angle spinning (MAS), double-rotation (DOR), and multiple-quantum (MQ) MAS experiments at magnetic field strengths of 9.4 and 21.1T. We identify one crystallographically unique Ca(2+) site in vaterite with a slight distribution in both chemical shifts and quadrupolar parameters. Both the experimental (43)Ca electric field gradient tensor and the isotropic chemical shift for vaterite are compared to those calculated with the gauge-including projector-augmented-wave (GIPAW) DFT method in an attempt to identify the model that best represents the crystal structure of vaterite. Simulations of (43)Ca DOR and MAS NMR spectra based on the NMR parameters computed for a total of 18 structural models for vaterite allow us to distinguish between these models. Among these 18, the P3221 and C2 structures provide simulated spectra and diffractograms in best agreement with all experimental data. Copyright © 2014 Elsevier Inc. All rights reserved.

Development of probabilistic multimedia multipathway computer codes.

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

Yu, C.; LePoire, D.; Gnanapragasam, E.

2002-01-01

The deterministic multimedia dose/risk assessment codes RESRAD and RESRAD-BUILD have been widely used for many years for evaluation of sites contaminated with residual radioactive materials. The RESRAD code applies to the cleanup of sites (soils) and the RESRAD-BUILD code applies to the cleanup of buildings and structures. This work describes the procedure used to enhance the deterministic RESRAD and RESRAD-BUILD codes for probabilistic dose analysis. A six-step procedure was used in developing default parameter distributions and the probabilistic analysis modules. These six steps include (1) listing and categorizing parameters; (2) ranking parameters; (3) developing parameter distributions; (4) testing parameter distributionsmore » for probabilistic analysis; (5) developing probabilistic software modules; and (6) testing probabilistic modules and integrated codes. The procedures used can be applied to the development of other multimedia probabilistic codes. The probabilistic versions of RESRAD and RESRAD-BUILD codes provide tools for studying the uncertainty in dose assessment caused by uncertain input parameters. The parameter distribution data collected in this work can also be applied to other multimedia assessment tasks and multimedia computer codes.« less

Relationships and redundancies of selected hemodynamic and structural parameters for characterizing virtual treatment of cerebral aneurysms with flow diverter devices.

PubMed

Karmonik, C; Anderson, J R; Beilner, J; Ge, J J; Partovi, S; Klucznik, R P; Diaz, O; Zhang, Y J; Britz, G W; Grossman, R G; Lv, N; Huang, Q

2016-07-26

To quantify the relationship and to demonstrate redundancies between hemodynamic and structural parameters before and after virtual treatment with a flow diverter device (FDD) in cerebral aneurysms. Steady computational fluid dynamics (CFD) simulations were performed for 10 cerebral aneurysms where FDD treatment with the SILK device was simulated by virtually reducing the porosity at the aneurysm ostium. Velocity and pressure values proximal and distal to and at the aneurysm ostium as well as inside the aneurysm were quantified. In addition, dome-to-neck ratios and size ratios were determined. Multiple correlation analysis (MCA) and hierarchical cluster analysis (HCA) were conducted to demonstrate dependencies between both structural and hemodynamic parameters. Velocities in the aneurysm were reduced by 0.14m/s on average and correlated significantly (p<0.05) with velocity values in the parent artery (average correlation coefficient: 0.70). Pressure changes in the aneurysm correlated significantly with pressure values in the parent artery and aneurysm (average correlation coefficient: 0.87). MCA found statistically significant correlations between velocity values and between pressure values, respectively. HCA sorted velocity parameters, pressure parameters and structural parameters into different hierarchical clusters. HCA of aneurysms based on the parameter values yielded similar results by either including all (n=22) or only non-redundant parameters (n=2, 3 and 4). Hemodynamic and structural parameters before and after virtual FDD treatment show strong inter-correlations. Redundancy of parameters was demonstrated with hierarchical cluster analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo

PubMed Central

Golightly, Andrew; Wilkinson, Darren J.

2011-01-01

Computational systems biology is concerned with the development of detailed mechanistic models of biological processes. Such models are often stochastic and analytically intractable, containing uncertain parameters that must be estimated from time course data. In this article, we consider the task of inferring the parameters of a stochastic kinetic model defined as a Markov (jump) process. Inference for the parameters of complex nonlinear multivariate stochastic process models is a challenging problem, but we find here that algorithms based on particle Markov chain Monte Carlo turn out to be a very effective computationally intensive approach to the problem. Approximations to the inferential model based on stochastic differential equations (SDEs) are considered, as well as improvements to the inference scheme that exploit the SDE structure. We apply the methodology to a Lotka–Volterra system and a prokaryotic auto-regulatory network. PMID:23226583

Choosing order of operations to accelerate strip structure analysis in parameter range

NASA Astrophysics Data System (ADS)

Kuksenko, S. P.; Akhunov, R. R.; Gazizov, T. R.

2018-05-01

The paper considers the issue of using iteration methods in solving the sequence of linear algebraic systems obtained in quasistatic analysis of strip structures with the method of moments. Using the analysis of 4 strip structures, the authors have proved that additional acceleration (up to 2.21 times) of the iterative process can be obtained during the process of solving linear systems repeatedly by means of choosing a proper order of operations and a preconditioner. The obtained results can be used to accelerate the process of computer-aided design of various strip structures. The choice of the order of operations to accelerate the process is quite simple, universal and could be used not only for strip structure analysis but also for a wide range of computational problems.

Substructure analysis using NICE/SPAR and applications of force to linear and nonlinear structures. [spacecraft masts

NASA Technical Reports Server (NTRS)

Razzaq, Zia; Prasad, Venkatesh; Darbhamulla, Siva Prasad; Bhati, Ravinder; Lin, Cai

1987-01-01

Parallel computing studies are presented for a variety of structural analysis problems. Included are the substructure planar analysis of rectangular panels with and without a hole, the static analysis of space mast, using NICE/SPAR and FORCE, and substructure analysis of plane rigid-jointed frames using FORCE. The computations are carried out on the Flex/32 MultiComputer using one to eighteen processors. The NICE/SPAR runstream samples are documented for the panel problem. For the substructure analysis of plane frames, a computer program is developed to demonstrate the effectiveness of a substructuring technique when FORCE is enforced. Ongoing research activities for an elasto-plastic stability analysis problem using FORCE, and stability analysis of the focus problem using NICE/SPAR are briefly summarized. Speedup curves for the panel, the mast, and the frame problems provide a basic understanding of the effectiveness of parallel computing procedures utilized or developed, within the domain of the parameters considered. Although the speedup curves obtained exhibit various levels of computational efficiency, they clearly demonstrate the excellent promise which parallel computing holds for the structural analysis problem. Source code is given for the elasto-plastic stability problem and the FORCE program.

Sustainability of transport structures - some aspects of the nonlinear reliability assessment

NASA Astrophysics Data System (ADS)

Pukl, Radomír; Sajdlová, Tereza; Strauss, Alfred; Lehký, David; Novák, Drahomír

2017-09-01

Efficient techniques for both nonlinear numerical analysis of concrete structures and advanced stochastic simulation methods have been combined in order to offer an advanced tool for assessment of realistic behaviour, failure and safety assessment of transport structures. The utilized approach is based on randomization of the non-linear finite element analysis of the structural models. Degradation aspects such as carbonation of concrete can be accounted in order predict durability of the investigated structure and its sustainability. Results can serve as a rational basis for the performance and sustainability assessment based on advanced nonlinear computer analysis of the structures of transport infrastructure such as bridges or tunnels. In the stochastic simulation the input material parameters obtained from material tests including their randomness and uncertainty are represented as random variables or fields. Appropriate identification of material parameters is crucial for the virtual failure modelling of structures and structural elements. Inverse analysis using artificial neural networks and virtual stochastic simulations approach is applied to determine the fracture mechanical parameters of the structural material and its numerical model. Structural response, reliability and sustainability have been investigated on different types of transport structures made from various materials using the above mentioned methodology and tools.

Real-time seismic monitoring and functionality assessment of a building

USGS Publications Warehouse

Celebi, M.; ,

2005-01-01

This paper presents recent developments and approaches (using GPS technology and real-time double-integration) to obtain displacements and, in turn, drift ratios, in real-time or near real-time to meet the needs of the engineering and user community in seismic monitoring and assessing the functionality and damage condition of structures. Drift ratios computed in near real-time allow technical assessment of the damage condition of a building. Relevant parameters, such as the type of connections and story structural characteristics (including geometry) are used in computing drifts corresponding to several pre-selected threshold stages of damage. Thus, drift ratios determined from real-time monitoring can be compared to pre-computed threshold drift ratios. The approaches described herein can be used for performance evaluation of structures and can be considered as building health-monitoring applications.

Recent advances to obtain real - Time displacements for engineering applications

USGS Publications Warehouse

Celebi, M.

2005-01-01

This paper presents recent developments and approaches (using GPS technology and real-time double-integration) to obtain displacements and, in turn, drift ratios, in real-time or near real-time to meet the needs of the engineering and user community in seismic monitoring and assessing the functionality and damage condition of structures. Drift ratios computed in near real-time allow technical assessment of the damage condition of a building. Relevant parameters, such as the type of connections and story structural characteristics (including geometry) are used in computing drifts corresponding to several pre-selected threshold stages of damage. Thus, drift ratios determined from real-time monitoring can be compared to pre-computed threshold drift ratios. The approaches described herein can be used for performance evaluation of structures and can be considered as building health-monitoring applications.

Bayesian nonlinear structural FE model and seismic input identification for damage assessment of civil structures

NASA Astrophysics Data System (ADS)

Astroza, Rodrigo; Ebrahimian, Hamed; Li, Yong; Conte, Joel P.

2017-09-01

A methodology is proposed to update mechanics-based nonlinear finite element (FE) models of civil structures subjected to unknown input excitation. The approach allows to jointly estimate unknown time-invariant model parameters of a nonlinear FE model of the structure and the unknown time histories of input excitations using spatially-sparse output response measurements recorded during an earthquake event. The unscented Kalman filter, which circumvents the computation of FE response sensitivities with respect to the unknown model parameters and unknown input excitations by using a deterministic sampling approach, is employed as the estimation tool. The use of measurement data obtained from arrays of heterogeneous sensors, including accelerometers, displacement sensors, and strain gauges is investigated. Based on the estimated FE model parameters and input excitations, the updated nonlinear FE model can be interrogated to detect, localize, classify, and assess damage in the structure. Numerically simulated response data of a three-dimensional 4-story 2-by-1 bay steel frame structure with six unknown model parameters subjected to unknown bi-directional horizontal seismic excitation, and a three-dimensional 5-story 2-by-1 bay reinforced concrete frame structure with nine unknown model parameters subjected to unknown bi-directional horizontal seismic excitation are used to illustrate and validate the proposed methodology. The results of the validation studies show the excellent performance and robustness of the proposed algorithm to jointly estimate unknown FE model parameters and unknown input excitations.

A new impedance accounting for short- and long-range effects in mixed substructured formulations of nonlinear problems

NASA Astrophysics Data System (ADS)

Negrello, Camille; Gosselet, Pierre; Rey, Christian

2018-05-01

An efficient method for solving large nonlinear problems combines Newton solvers and Domain Decomposition Methods (DDM). In the DDM framework, the boundary conditions can be chosen to be primal, dual or mixed. The mixed approach presents the advantage to be eligible for the research of an optimal interface parameter (often called impedance) which can increase the convergence rate. The optimal value for this parameter is often too expensive to be computed exactly in practice: an approximate version has to be sought for, along with a compromise between efficiency and computational cost. In the context of parallel algorithms for solving nonlinear structural mechanical problems, we propose a new heuristic for the impedance which combines short and long range effects at a low computational cost.

Tutorial: Asteroseismic Stellar Modelling with AIMS

NASA Astrophysics Data System (ADS)

Lund, Mikkel N.; Reese, Daniel R.

The goal of aims (Asteroseismic Inference on a Massive Scale) is to estimate stellar parameters and credible intervals/error bars in a Bayesian manner from a set of asteroseismic frequency data and so-called classical constraints. To achieve reliable parameter estimates and computational efficiency, it searches through a grid of pre-computed models using an MCMC algorithm—interpolation within the grid of models is performed by first tessellating the grid using a Delaunay triangulation and then doing a linear barycentric interpolation on matching simplexes. Inputs for the modelling consist of individual frequencies from peak-bagging, which can be complemented with classical spectroscopic constraints. aims is mostly written in Python with a modular structure to facilitate contributions from the community. Only a few computationally intensive parts have been rewritten in Fortran in order to speed up calculations.

Time-dependent reliability analysis of ceramic engine components

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.

1993-01-01

The computer program CARES/LIFE calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. This program is an extension of the CARES (Ceramics Analysis and Reliability Evaluation of Structures) computer program. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing either the power or Paris law relations. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. Two example problems demonstrating proof testing and fatigue parameter estimation are given.

X-ray investigation of cross-breed silk in cocoon, yarn and fabric forms

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

Radhalakshmi, Y. C.; Kariappa,; Siddaraju, G. N.

2012-06-05

Recently Central Sericulture Research and Training Institute, Mysore developed many improved cross breeds and bivoltine hybrids. Newly developed cross breeds recorded fibre characteristics which are significantly superior over existing control hybrids. This aspect has been investigated using X-ray diffraction technique. We have employed line profile analysis to compute microstructural parameters. These parameters are compared with physical parameters of newly developed cross breed silk fibers for a better understanding of structure-property relation in these samples.

Progressive fracture of polymer matrix composite structures: A new approach

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Murthy, P. L. N.; Minnetyan, L.

1992-01-01

A new approach independent of stress intensity factors and fracture toughness parameters has been developed and is described for the computational simulation of progressive fracture of polymer matrix composite structures. The damage stages are quantified based on physics via composite mechanics while the degradation of the structural behavior is quantified via the finite element method. The approach account for all types of composite behavior, structures, load conditions, and fracture processes starting from damage initiation, to unstable propagation and to global structural collapse. Results of structural fracture in composite beams, panels, plates, and shells are presented to demonstrate the effectiveness and versatility of this new approach. Parameters and guidelines are identified which can be used as criteria for structural fracture, inspection intervals, and retirement for cause. Generalization to structures made of monolithic metallic materials are outlined and lessons learned in undertaking the development of new approaches, in general, are summarized.

Characterization and analysis of Porous, Brittle solid structures by X-ray micro computed tomography

NASA Astrophysics Data System (ADS)

Lin, C. L.; Videla, A. R.; Yu, Q.; Miller, J. D.

2010-12-01

The internal structure of porous, brittle solid structures, such as porous rock, foam metal and wallboard, is extremely complex. For example, in the case of wallboard, the air bubble size and the thickness/composition of the wall structure are spatial parameters that vary significantly and influence mechanical, thermal, and acoustical properties. In this regard, the complex geometry and the internal texture of material, such as wallboard, is characterized and analyzed in 3-D using cone beam x-ray micro computed tomography. Geometrical features of the porous brittle structure are quantitatively analyzed based on calibration of the x-ray linear attenuation coefficient, use of a 3-D watershed algorithm, and use of a 3-D skeletonization procedure. Several examples of the 3-D analysis for porous, wallboard structures are presented and the results discussed.

Non-invasive imaging of the crystalline structure within a human tooth.

PubMed

Egan, Christopher K; Jacques, Simon D M; Di Michiel, Marco; Cai, Biao; Zandbergen, Mathijs W; Lee, Peter D; Beale, Andrew M; Cernik, Robert J

2013-09-01

The internal crystalline structure of a human molar tooth has been non-destructively imaged in cross-section using X-ray diffraction computed tomography. Diffraction signals from high-energy X-rays which have large attenuation lengths for hard biomaterials have been collected in a transmission geometry. Coupling this with a computed tomography data acquisition and mathematically reconstructing their spatial origins, diffraction patterns from every voxel within the tooth can be obtained. Using this method we have observed the spatial variations of some key material parameters including nanocrystallite size, organic content, lattice parameters, crystallographic preferred orientation and degree of orientation. We have also made a link between the spatial variations of the unit cell lattice parameters and the chemical make-up of the tooth. In addition, we have determined how the onset of tooth decay occurs through clear amorphization of the hydroxyapatite crystal, and we have been able to map the extent of decay within the tooth. The described method has strong prospects for non-destructive probing of mineralized biomaterials. Copyright © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

FT-IR spectroscopic analyses of 2-(2-furanylmethylene) propanedinitrile

NASA Astrophysics Data System (ADS)

Soliman, H. S.; Eid, Kh. M.; Ali, H. A. M.; El-Mansy, M. A. M.; Atef, S. M.

2013-03-01

In the present work, a computational study for the optimized molecular structural parameters, thermo-chemical parameters, total dipole moment, HOMO-LUMO energy gap and a combined experimental and computational study for FT-IR spectra for 2-(2-furanylmethylene) propanedinitrile have been investigated using B3LYP utilizing 6-31G and 6-311G basis set. Our calculated results showed that the investigated compound possesses a dipole moment of 7.5 D and HOMO-LUMO energy gap of 3.92 eV using B3LYP/6-311G which indicates that our investigated compound is highly applicable for photovoltaic solar cell applications.

A Combined Experimental/Computational Investigation of a Rocket Based Combined Cycle Inlet

NASA Technical Reports Server (NTRS)

Smart, Michael K.; Trexler, Carl A.; Goldman, Allen L.

2001-01-01

A rocket based combined cycle inlet geometry has undergone wind tunnel testing and computational analysis with Mach 4 flow at the inlet face. Performance parameters obtained from the wind tunnel tests were the mass capture, the maximum back-pressure, and the self-starting characteristics of the inlet. The CFD analysis supplied a confirmation of the mass capture, the inlet efficiency and the details of the flowfield structure. Physical parameters varied during the test program were cowl geometry, cowl position, body-side bleed magnitude and ingested boundary layer thickness. An optimum configuration was determined for the inlet as a result of this work.

Zn- and Co-based layered double hydroxides: prediction of the a parameter from the fraction of trivalent cations and vice versa

PubMed Central

Richardson, Ian G.

2013-01-01

A recently proposed method to calculate the a parameter of the unit cell of layered double hydroxides from the fraction of trivalent cations is extended to Zn- and Co-based phases. It is shown to be useful as a sanity test for extant and future structure determinations and computer-simulation studies. PMID:23873067

An expert system for prediction of chemical toxicity

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino-Reader, Dora R.; Frank, Anthony M.

1992-01-01

The National Fisheries Research Center- Great Lakes has developed an interactive computer program that uses the structure of an organic molecule to predict its acute toxicity to four aquatic species. The expert system software, written in the muLISP language, identifies the skeletal structures and substituent groups of an organic molecule from a user-supplied standard chemical notation known as a SMILES string, and then generates values for four solvatochromic parameters. Multiple regression equations relate these parameters to the toxicities (expressed as log10LC50s and log10EC50s, along with 95% confidence intervals) for four species. The system is demonstrated by prediction of toxicity for anilide-type pesticides to the fathead minnow (Pimephales promelas). This software is designed for use on an IBM-compatible personal computer by personnel with minimal toxicology background for rapid estimation of chemical toxicity. The system has numerous applications, with much potential for use in the pharmaceutical industry

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

PubMed Central

Poleszczuk, Jan; Enderling, Heiko

2014-01-01

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner. PMID:25346862

Predicting CYP2C19 Catalytic Parameters for Enantioselective Oxidations Using Artificial Neural Networks and a Chirality Code

PubMed Central

Hartman, Jessica H.; Cothren, Steven D.; Park, Sun-Ha; Yun, Chul-Ho; Darsey, Jerry A.; Miller, Grover P.

2013-01-01

Cytochromes P450 (CYP for isoforms) play a central role in biological processes especially metabolism of chiral molecules; thus, development of computational methods to predict parameters for chiral reactions is important for advancing this field. In this study, we identified the most optimal artificial neural networks using conformation-independent chirality codes to predict CYP2C19 catalytic parameters for enantioselective reactions. Optimization of the neural networks required identifying the most suitable representation of structure among a diverse array of training substrates, normalizing distribution of the corresponding catalytic parameters (kcat, Km, and kcat/Km), and determining the best topology for networks to make predictions. Among different structural descriptors, the use of partial atomic charges according to the CHelpG scheme and inclusion of hydrogens yielded the most optimal artificial neural networks. Their training also required resolution of poorly distributed output catalytic parameters using a Box-Cox transformation. End point leave-one-out cross correlations of the best neural networks revealed that predictions for individual catalytic parameters (kcat and Km) were more consistent with experimental values than those for catalytic efficiency (kcat/Km). Lastly, neural networks predicted correctly enantioselectivity and comparable catalytic parameters measured in this study for previously uncharacterized CYP2C19 substrates, R- and S-propranolol. Taken together, these seminal computational studies for CYP2C19 are the first to predict all catalytic parameters for enantioselective reactions using artificial neural networks and thus provide a foundation for expanding the prediction of cytochrome P450 reactions to chiral drugs, pollutants, and other biologically active compounds. PMID:23673224

Effect of Helical Slow-Wave Circuit Variations on TWT Cold-Test Characteristics

NASA Technical Reports Server (NTRS)

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

1998-01-01

Recent advances in the state of the art of computer modeling offer the possibility for the first time to evaluate the effect that slow-wave structure parameter variations, such as manufacturing tolerances, have on the cold-test characteristics of helical traveling-wave tubes (TWT's). This will enable manufacturers to determine the cost effectiveness of controlling the dimensions of the component parts of the TWT, which is almost impossible to do experimentally without building a large number of tubes and controlling several parameters simultaneously. The computer code MAFIA is used in this analysis to determine the effect on dispersion and on-axis interaction impedance of several helical slow-wave circuit parameter variations, including thickness and relative dielectric constant of the support rods, tape width, and height of the metallized films deposited on the dielectric rods. Previous computer analyzes required so many approximations that accurate determinations of the effect of many relevant dimensions on tube performance were practically impossible.

Effect of Helical Slow-Wave Circuit Variations on TWT Cold-Test Characteristics

NASA Technical Reports Server (NTRS)

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

1997-01-01

Recent advances in the state of the art of computer modeling offer the possibility for the first time to evaluate the effect that slow-wave structure parameter variations, such as manufacturing tolerances, have on the cold-test characteristics of helical traveling-wave tubes (TWT's). This will enable manufacturers to determine the cost effectiveness of controlling the dimensions of the component parts of the TWT, which is almost impossible to do experimentally without building a large number of tubes and controlling several parameters simultaneously. The computer code MAFIA is used in this analysis to determine the effect on dispersion and on-axis interaction impedance of several helical slow-wave circuit parameter variations, including thickness and relative dielectric constant of the support rods, tape width, and height of the metallized films deposited on the dielectric rods. Previous computer analyses required so many approximations that accurate determinations of the effect of many relevant dimensions on tube performance were practically impossible.

Effect of Helical Slow-Wave Circuit Variations on TWT Cold-Test Characteristics

NASA Technical Reports Server (NTRS)

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

1998-01-01

Recent advances in the state of the art of computer modeling offer the possibility for the first time to evaluate the effect that slow-wave structure parameter variations, such'as manufacturing tolerances, have on the cold-test characteristics of helical traveling-wave tubes (TWT's). This will enable manufacturers to determine the cost effectiveness of controlling the dimensions of the component parts of the TWT, which is almost impossible to do experimentally without building a large number of tubes and controlling several parameters simultaneously. The computer code MAxwell's equations by the Finite Integration Algorithm (MAFIA) is used in this analysis to determine the effect on dispersion and on-axis interaction impedance of several helical slow-wave circuit parameter variations, including thickness and relative dielectric constant of the support rods, tape width, and height of the metallized films deposited on the dielectric rods. Previous computer analyzes required so many approximations that accurate determinations of the effect of many relevant dimensions on tube performance were practically impossible.

On the formulation of a minimal uncertainty model for robust control with structured uncertainty

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.; Chang, B.-C.; Fischl, Robert

1991-01-01

In the design and analysis of robust control systems for uncertain plants, representing the system transfer matrix in the form of what has come to be termed an M-delta model has become widely accepted and applied in the robust control literature. The M represents a transfer function matrix M(s) of the nominal closed loop system, and the delta represents an uncertainty matrix acting on M(s). The nominal closed loop system M(s) results from closing the feedback control system, K(s), around a nominal plant interconnection structure P(s). The uncertainty can arise from various sources, such as structured uncertainty from parameter variations or multiple unsaturated uncertainties from unmodeled dynamics and other neglected phenomena. In general, delta is a block diagonal matrix, but for real parameter variations delta is a diagonal matrix of real elements. Conceptually, the M-delta structure can always be formed for any linear interconnection of inputs, outputs, transfer functions, parameter variations, and perturbations. However, very little of the currently available literature addresses computational methods for obtaining this structure, and none of this literature addresses a general methodology for obtaining a minimal M-delta model for a wide class of uncertainty, where the term minimal refers to the dimension of the delta matrix. Since having a minimally dimensioned delta matrix would improve the efficiency of structured singular value (or multivariable stability margin) computations, a method of obtaining a minimal M-delta would be useful. Hence, a method of obtaining the interconnection system P(s) is required. A generalized procedure for obtaining a minimal P-delta structure for systems with real parameter variations is presented. Using this model, the minimal M-delta model can then be easily obtained by closing the feedback loop. The procedure involves representing the system in a cascade-form state-space realization, determining the minimal uncertainty matrix, delta, and constructing the state-space representation of P(s). Three examples are presented to illustrate the procedure.

Parameter Estimation in Atmospheric Data Sets

NASA Technical Reports Server (NTRS)

Wenig, Mark; Colarco, Peter

2004-01-01

In this study the structure tensor technique is used to estimate dynamical parameters in atmospheric data sets. The structure tensor is a common tool for estimating motion in image sequences. This technique can be extended to estimate other dynamical parameters such as diffusion constants or exponential decay rates. A general mathematical framework was developed for the direct estimation of the physical parameters that govern the underlying processes from image sequences. This estimation technique can be adapted to the specific physical problem under investigation, so it can be used in a variety of applications in trace gas, aerosol, and cloud remote sensing. As a test scenario this technique will be applied to modeled dust data. In this case vertically integrated dust concentrations were used to derive wind information. Those results can be compared to the wind vector fields which served as input to the model. Based on this analysis, a method to compute atmospheric data parameter fields will be presented. .

Hierarchical Order Parameters for Macromolecular Assembly Simulations I: Construction and Dynamical Properties of Order Parameters

PubMed Central

Singharoy, Abhishek; Sereda, Yuriy

2012-01-01

Macromolecular assemblies often display a hierarchical organization of macromolecules or their sub-assemblies. To model this, we have formulated a space warping method that enables capturing overall macromolecular structure and dynamics via a set of coarse-grained order parameters (OPs). This article is the first of two describing the construction and computational implementation of an additional class of OPs that has built into them the hierarchical architecture of macromolecular assemblies. To accomplish this, first, the system is divided into subsystems, each of which is described via a representative set of OPs. Then, a global set of variables is constructed from these subsystem-centered OPs to capture overall system organization. Dynamical properties of the resulting OPs are compared to those of our previous nonhierarchical ones, and implied conceptual and computational advantages are discussed for a 100ns, 2 million atom solvated Human Papillomavirus-like particle simulation. In the second article, the hierarchical OPs are shown to enable a multiscale analysis that starts with the N-atom Liouville equation and yields rigorous Langevin equations of stochastic OP dynamics. The latter is demonstrated via a force-field based simulation algorithm that probes key structural transition pathways, simultaneously accounting for all-atom details and overall structure. PMID:22661911

Static and dynamic structural-sensitivity derivative calculations in the finite-element-based Engineering Analysis Language (EAL) system

NASA Technical Reports Server (NTRS)

Camarda, C. J.; Adelman, H. M.

1984-01-01

The implementation of static and dynamic structural-sensitivity derivative calculations in a general purpose, finite-element computer program denoted the Engineering Analysis Language (EAL) System is described. Derivatives are calculated with respect to structural parameters, specifically, member sectional properties including thicknesses, cross-sectional areas, and moments of inertia. Derivatives are obtained for displacements, stresses, vibration frequencies and mode shapes, and buckling loads and mode shapes. Three methods for calculating derivatives are implemented (analytical, semianalytical, and finite differences), and comparisons of computer time and accuracy are made. Results are presented for four examples: a swept wing, a box beam, a stiffened cylinder with a cutout, and a space radiometer-antenna truss.

A modified PATH algorithm rapidly generates transition states comparable to those found by other well established algorithms

PubMed Central

Chandrasekaran, Srinivas Niranj; Das, Jhuma; Dokholyan, Nikolay V.; Carter, Charles W.

2016-01-01

PATH rapidly computes a path and a transition state between crystal structures by minimizing the Onsager-Machlup action. It requires input parameters whose range of values can generate different transition-state structures that cannot be uniquely compared with those generated by other methods. We outline modifications to estimate these input parameters to circumvent these difficulties and validate the PATH transition states by showing consistency between transition-states derived by different algorithms for unrelated protein systems. Although functional protein conformational change trajectories are to a degree stochastic, they nonetheless pass through a well-defined transition state whose detailed structural properties can rapidly be identified using PATH. PMID:26958584

Computational measurement of joint space width and structural parameters in normal hips.

PubMed

Nishii, Takashi; Shiomi, Toshiyuki; Sakai, Takashi; Takao, Masaki; Yoshikawa, Hideki; Sugano, Nobuhiko

2012-05-01

Joint space width (JSW) of hip joints on radiographs in normal population may vary by related factors, but previous investigations were insufficient due to limitations of sources of radiographs, inclusion of subjects with osteoarthritis, and manual measurement techniques. We investigated influential factors on JSW using semiautomatic computational software on pelvic radiographs in asymptomatic subjects without radiological osteoarthritic findings. Global and local JSW at the medial, middle, and lateral compartments, and the hip structural parameters were measured in asymptomatic, normal 150 cases (300 hips), using a customized computational software. Reliability of measurement in global and local JSWs was high with intraobserver reproducibility (intraclass correlation coefficient) ranging from 0.957 to 0.993 and interobserver reproducibility ranging from 0.925 to 0.985. There were significant differences among three local JSWs, with the largest JSW at the lateral compartment. Global and medial local JSWs were significantly larger in the right hip, and global, medial and middle local JSWs were significantly smaller in women. Global and local JSWs were inversely correlated with CE angle and positively correlated with horizontal distance of the head center, but not correlated with body mass index in men and women. They were positively correlated with age and inversely correlated with vertical distance of the head center only in men. There were interindividual variations of JSW in normal population, depending on sites of the weight-bearing area, side, gender, age, and hip structural parameters. For accurate diagnosis and assessment of hip osteoarthritis, consideration of those influential factors other than degenerative change is important.

Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine

NASA Astrophysics Data System (ADS)

Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei

2018-01-01

Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.

High temperature composite analyzer (HITCAN) user's manual, version 1.0

NASA Technical Reports Server (NTRS)

Lackney, J. J.; Singhal, S. N.; Murthy, P. L. N.; Gotsis, P.

1993-01-01

This manual describes 'how-to-use' the computer code, HITCAN (HIgh Temperature Composite ANalyzer). HITCAN is a general purpose computer program for predicting nonlinear global structural and local stress-strain response of arbitrarily oriented, multilayered high temperature metal matrix composite structures. This code combines composite mechanics and laminate theory with an internal data base for material properties of the constituents (matrix, fiber and interphase). The thermo-mechanical properties of the constituents are considered to be nonlinearly dependent on several parameters including temperature, stress and stress rate. The computation procedure for the analysis of the composite structures uses the finite element method. HITCAN is written in FORTRAN 77 computer language and at present has been configured and executed on the NASA Lewis Research Center CRAY XMP and YMP computers. This manual describes HlTCAN's capabilities and limitations followed by input/execution/output descriptions and example problems. The input is described in detail including (1) geometry modeling, (2) types of finite elements, (3) types of analysis, (4) material data, (5) types of loading, (6) boundary conditions, (7) output control, (8) program options, and (9) data bank.

Computing with volatile memristors: an application of non-pinched hysteresis

NASA Astrophysics Data System (ADS)

Pershin, Y. V.; Shevchenko, S. N.

2017-02-01

The possibility of in-memory computing with volatile memristive devices, namely, memristors requiring a power source to sustain their memory, is demonstrated theoretically. We have adopted a hysteretic graphene-based field emission structure as a prototype of a volatile memristor, which is characterized by a non-pinched hysteresis loop. A memristive model of the structure is developed and used to simulate a polymorphic circuit implementing stateful logic gates, such as the material implication. Specific regions of parameter space realizing useful logic functions are identified. Our results are applicable to other realizations of volatile memory devices, such as certain NEMS switches.

Computer analysis of railcar vibrations

NASA Technical Reports Server (NTRS)

Vlaminck, R. R.

1975-01-01

Computer models and techniques for calculating railcar vibrations are discussed along with criteria for vehicle ride optimization. The effect on vibration of car body structural dynamics, suspension system parameters, vehicle geometry, and wheel and rail excitation are presented. Ride quality vibration data collected on the state-of-the-art car and standard light rail vehicle is compared to computer predictions. The results show that computer analysis of the vehicle can be performed for relatively low cost in short periods of time. The analysis permits optimization of the design as it progresses and minimizes the possibility of excessive vibration on production vehicles.

Design of microstrip components by computer

NASA Technical Reports Server (NTRS)

Cisco, T. C.

1972-01-01

A number of computer programs are presented for use in the synthesis of microwave components in microstrip geometries. The programs compute the electrical and dimensional parameters required to synthesize couplers, filters, circulators, transformers, power splitters, diode switches, multipliers, diode attenuators and phase shifters. Additional programs are included to analyze and optimize cascaded transmission lines and lumped element networks, to analyze and synthesize Chebyshev and Butterworth filter prototypes, and to compute mixer intermodulation products. The programs are written in FORTRAN and the emphasis of the study is placed on the use of these programs and not on the theoretical aspects of the structures.

Evaluation of the influence of acquisition parameters of microtomography in image quality applied by carbonate rocks

NASA Astrophysics Data System (ADS)

Santos, T. M. P.; Machado, A. S.; Araújo, O. M. O.; Ferreira, C. G.; Lopes, R. T.

2018-03-01

X-ray computed microtomography is a powerful nondestructive technique for 2D and 3D structure analysis. However, parameters used in acquisition promote directs influence in qualitative and quantitative results in characterization of samples, due image resolution. The aim of this study is value the influence of theses parameters in results through of tests changing these parameters in different situations and system characterization. Results demonstrate those pixel size and detector matrixes are the main parameters that influence in resolution and image quality. Microtomography was considered an excellent technique for characterization using the best image resolution possible.

Computational Control of Flexible Aerospace Systems

NASA Technical Reports Server (NTRS)

Sharpe, Lonnie, Jr.; Shen, Ji Yao

1994-01-01

The main objective of this project is to establish a distributed parameter modeling technique for structural analysis, parameter estimation, vibration suppression and control synthesis of large flexible aerospace structures. This report concentrates on the research outputs produced in the last two years of the project. The main accomplishments can be summarized as follows. A new version of the PDEMOD Code had been completed. A theoretical investigation of the NASA MSFC two-dimensional ground-based manipulator facility by using distributed parameter modelling technique has been conducted. A new mathematical treatment for dynamic analysis and control of large flexible manipulator systems has been conceived, which may provide a embryonic form of a more sophisticated mathematical model for future modified versions of the PDEMOD Codes.

Theoretical calculations of Electron Paramagnetic Resonance parameters of liquid phase Orotic acid radical

NASA Astrophysics Data System (ADS)

Sarikaya, Ebru Karakaş; Dereli, Ömer

2017-02-01

To obtain liquid phase molecular structure, conformational analysis of Orotic acid was performed and six conformers were determined. For these conformations, eight possible radicals were modelled by using Density Functional Theory computations with respect to molecular structure. Electron Paramagnetic Resonance parameters of these model radicals were calculated and then they were compared with the experimental ones. Geometry optimizations of the molecule and modeled radicals were performed using Becke's three-parameter hybrid-exchange functional combined with the Lee-Yang-Parr correlation functional of Density Functional Theory and 6-311++G(d,p) basis sets in p-dioxane solution. Because Orotic acid can be mutagenic in mammalian somatic cells and it is also mutagenic for bacteria and yeast, it has been studied.

Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

NASA Astrophysics Data System (ADS)

Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

2015-04-01

This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

Performance review using sequential sampling and a practice computer.

PubMed

Difford, F

1988-06-01

The use of sequential sample analysis for repeated performance review is described with examples from several areas of practice. The value of a practice computer in providing a random sample from a complete population, evaluating the parameters of a sequential procedure, and producing a structured worksheet is discussed. It is suggested that sequential analysis has advantages over conventional sampling in the area of performance review in general practice.

Full-scale computation for all the thermoelectric property parameters of half-Heusler compounds

DOE PAGES

Hong, A. J.; Li, L.; He, R.; ...

2016-03-07

The thermoelectric performance of materials relies substantially on the band structures that determine the electronic and phononic transports, while the transport behaviors compete and counter-act for the power factor PF and figure-of-merit ZT. These issues make a full-scale computation of the whole set of thermoelectric parameters particularly attractive, while a calculation scheme of the electronic and phononic contributions to thermal conductivity remains yet challenging. In this work, we present a full-scale computation scheme based on the first-principles calculations by choosing a set of doped half- Heusler compounds as examples for illustration. The electronic structure is computed using the WIEN2k codemore » and the carrier relaxation times for electrons and holes are calculated using the Bardeen and Shockley’s deformation potential (DP) theory. The finite-temperature electronic transport is evaluated within the framework of Boltzmann transport theory. In sequence, the density functional perturbation combined with the quasi-harmonic approximation and the Klemens’ equation is implemented for calculating the lattice thermal conductivity of carrier-doped thermoelectric materials such as Tidoped NbFeSb compounds without losing a generality. The calculated results show good agreement with experimental data. Lastly, the present methodology represents an effective and powerful approach to calculate the whole set of thermoelectric properties for thermoelectric materials.« less

Full-scale computation for all the thermoelectric property parameters of half-Heusler compounds

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

Hong, A. J.; Li, L.; He, R.

The thermoelectric performance of materials relies substantially on the band structures that determine the electronic and phononic transports, while the transport behaviors compete and counter-act for the power factor PF and figure-of-merit ZT. These issues make a full-scale computation of the whole set of thermoelectric parameters particularly attractive, while a calculation scheme of the electronic and phononic contributions to thermal conductivity remains yet challenging. In this work, we present a full-scale computation scheme based on the first-principles calculations by choosing a set of doped half- Heusler compounds as examples for illustration. The electronic structure is computed using the WIEN2k codemore » and the carrier relaxation times for electrons and holes are calculated using the Bardeen and Shockley’s deformation potential (DP) theory. The finite-temperature electronic transport is evaluated within the framework of Boltzmann transport theory. In sequence, the density functional perturbation combined with the quasi-harmonic approximation and the Klemens’ equation is implemented for calculating the lattice thermal conductivity of carrier-doped thermoelectric materials such as Tidoped NbFeSb compounds without losing a generality. The calculated results show good agreement with experimental data. Lastly, the present methodology represents an effective and powerful approach to calculate the whole set of thermoelectric properties for thermoelectric materials.« less

Computing the structural influence matrix for biological systems.

PubMed

Giordano, Giulia; Cuba Samaniego, Christian; Franco, Elisa; Blanchini, Franco

2016-06-01

We consider the problem of identifying structural influences of external inputs on steady-state outputs in a biological network model. We speak of a structural influence if, upon a perturbation due to a constant input, the ensuing variation of the steady-state output value has the same sign as the input (positive influence), the opposite sign (negative influence), or is zero (perfect adaptation), for any feasible choice of the model parameters. All these signs and zeros can constitute a structural influence matrix, whose (i, j) entry indicates the sign of steady-state influence of the jth system variable on the ith variable (the output caused by an external persistent input applied to the jth variable). Each entry is structurally determinate if the sign does not depend on the choice of the parameters, but is indeterminate otherwise. In principle, determining the influence matrix requires exhaustive testing of the system steady-state behaviour in the widest range of parameter values. Here we show that, in a broad class of biological networks, the influence matrix can be evaluated with an algorithm that tests the system steady-state behaviour only at a finite number of points. This algorithm also allows us to assess the structural effect of any perturbation, such as variations of relevant parameters. Our method is applied to nontrivial models of biochemical reaction networks and population dynamics drawn from the literature, providing a parameter-free insight into the system dynamics.

Control Law Design in a Computational Aeroelasticity Environment

NASA Technical Reports Server (NTRS)

Newsom, Jerry R.; Robertshaw, Harry H.; Kapania, Rakesh K.

2003-01-01

A methodology for designing active control laws in a computational aeroelasticity environment is given. The methodology involves employing a systems identification technique to develop an explicit state-space model for control law design from the output of a computational aeroelasticity code. The particular computational aeroelasticity code employed in this paper solves the transonic small disturbance aerodynamic equation using a time-accurate, finite-difference scheme. Linear structural dynamics equations are integrated simultaneously with the computational fluid dynamics equations to determine the time responses of the structure. These structural responses are employed as the input to a modern systems identification technique that determines the Markov parameters of an "equivalent linear system". The Eigensystem Realization Algorithm is then employed to develop an explicit state-space model of the equivalent linear system. The Linear Quadratic Guassian control law design technique is employed to design a control law. The computational aeroelasticity code is modified to accept control laws and perform closed-loop simulations. Flutter control of a rectangular wing model is chosen to demonstrate the methodology. Various cases are used to illustrate the usefulness of the methodology as the nonlinearity of the aeroelastic system is increased through increased angle-of-attack changes.

Deep neural nets as a method for quantitative structure-activity relationships.

PubMed

Ma, Junshui; Sheridan, Robert P; Liaw, Andy; Dahl, George E; Svetnik, Vladimir

2015-02-23

Neural networks were widely used for quantitative structure-activity relationships (QSAR) in the 1990s. Because of various practical issues (e.g., slow on large problems, difficult to train, prone to overfitting, etc.), they were superseded by more robust methods like support vector machine (SVM) and random forest (RF), which arose in the early 2000s. The last 10 years has witnessed a revival of neural networks in the machine learning community thanks to new methods for preventing overfitting, more efficient training algorithms, and advancements in computer hardware. In particular, deep neural nets (DNNs), i.e. neural nets with more than one hidden layer, have found great successes in many applications, such as computer vision and natural language processing. Here we show that DNNs can routinely make better prospective predictions than RF on a set of large diverse QSAR data sets that are taken from Merck's drug discovery effort. The number of adjustable parameters needed for DNNs is fairly large, but our results show that it is not necessary to optimize them for individual data sets, and a single set of recommended parameters can achieve better performance than RF for most of the data sets we studied. The usefulness of the parameters is demonstrated on additional data sets not used in the calibration. Although training DNNs is still computationally intensive, using graphical processing units (GPUs) can make this issue manageable.

A grid-enabled web service for low-resolution crystal structure refinement.

PubMed

O'Donovan, Daniel J; Stokes-Rees, Ian; Nam, Yunsun; Blacklow, Stephen C; Schröder, Gunnar F; Brunger, Axel T; Sliz, Piotr

2012-03-01

Deformable elastic network (DEN) restraints have proved to be a powerful tool for refining structures from low-resolution X-ray crystallographic data sets. Unfortunately, optimal refinement using DEN restraints requires extensive calculations and is often hindered by a lack of access to sufficient computational resources. The DEN web service presented here intends to provide structural biologists with access to resources for running computationally intensive DEN refinements in parallel on the Open Science Grid, the US cyberinfrastructure. Access to the grid is provided through a simple and intuitive web interface integrated into the SBGrid Science Portal. Using this portal, refinements combined with full parameter optimization that would take many thousands of hours on standard computational resources can now be completed in several hours. An example of the successful application of DEN restraints to the human Notch1 transcriptional complex using the grid resource, and summaries of all submitted refinements, are presented as justification.

Simultaneous analysis and design

NASA Technical Reports Server (NTRS)

Haftka, R. T.

1984-01-01

Optimization techniques are increasingly being used for performing nonlinear structural analysis. The development of element by element (EBE) preconditioned conjugate gradient (CG) techniques is expected to extend this trend to linear analysis. Under these circumstances the structural design problem can be viewed as a nested optimization problem. There are computational benefits to treating this nested problem as a large single optimization problem. The response variables (such as displacements) and the structural parameters are all treated as design variables in a unified formulation which performs simultaneously the design and analysis. Two examples are used for demonstration. A seventy-two bar truss is optimized subject to linear stress constraints and a wing box structure is optimized subject to nonlinear collapse constraints. Both examples show substantial computational savings with the unified approach as compared to the traditional nested approach.

Damage Progression in Bolted Composites

NASA Technical Reports Server (NTRS)

Minnetyan, Levon; Chamis, Christos C.; Gotsis, Pascal K.

1998-01-01

Structural durability, damage tolerance, and progressive fracture characteristics of bolted graphite/epoxy composite laminates are evaluated via computational simulation. Constituent material properties and stress and strain limits are scaled up to the structure level to evaluate the overall damage and fracture propagation for bolted composites. Single and double bolted composite specimens with various widths and bolt spacings are evaluated. The effect of bolt spacing is investigated with regard to the structural durability of a bolted joint. Damage initiation, growth, accumulation, and propagation to fracture are included in the simulations. Results show the damage progression sequence and structural fracture resistance during different degradation stages. A procedure is outlined for the use of computational simulation data in the assessment of damage tolerance, determination of sensitive parameters affecting fracture, and interpretation of experimental results with insight for design decisions.

Damage Progression in Bolted Composites

NASA Technical Reports Server (NTRS)

Minnetyan, Levon; Chamis, Christos; Gotsis, Pascal K.

1998-01-01

Structural durability,damage tolerance,and progressive fracture characteristics of bolted graphite/epoxy composite laminates are evaluated via computational simulation. Constituent material properties and stress and strain limits are scaled up to the structure level to evaluate the overall damage and fracture propagation for bolted composites. Single and double bolted composite specimens with various widths and bolt spacings are evaluated. The effect of bolt spacing is investigated with regard to the structural durability of a bolted joint. Damage initiation, growth, accumulation, and propagation to fracture are included in the simulations. Results show the damage progression sequence and structural fracture resistance during different degradation stages. A procedure is outlined for the use of computational simulation data in the assessment of damage tolerance, determination of sensitive parameters affecting fracture, and interpretation of experimental results with insight for design decisions.

Computational modeling of high-entropy alloys: Structures, thermodynamics and elasticity

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

Gao, Michael C.; Gao, Pan; Hawk, Jeffrey A.

This study provides a short review on computational modeling on the formation, thermodynamics, and elasticity of single-phase high-entropy alloys (HEAs). Hundreds of predicted single-phase HEAs were re-examined using various empirical thermo-physical parameters. Potential BCC HEAs (CrMoNbTaTiVW, CrMoNbReTaTiVW, and CrFeMoNbReRuTaVW) were suggested based on CALPHAD modeling. The calculated vibrational entropies of mixing are positive for FCC CoCrFeNi, negative for BCC MoNbTaW, and near-zero for HCP CoOsReRu. The total entropies of mixing were observed to trend in descending order: CoCrFeNi > CoOsReRu > MoNbTaW. Calculated lattice parameters agree extremely well with averaged values estimated from the rule of mixtures (ROM) if themore » same crystal structure is used for the elements and the alloy. The deviation in the calculated elastic properties from ROM for select alloys is small but is susceptible to the choice used for the structures of pure components.« less

Computational modeling of high-entropy alloys: Structures, thermodynamics and elasticity

DOE PAGES

Gao, Michael C.; Gao, Pan; Hawk, Jeffrey A.; ...

2017-10-12

This study provides a short review on computational modeling on the formation, thermodynamics, and elasticity of single-phase high-entropy alloys (HEAs). Hundreds of predicted single-phase HEAs were re-examined using various empirical thermo-physical parameters. Potential BCC HEAs (CrMoNbTaTiVW, CrMoNbReTaTiVW, and CrFeMoNbReRuTaVW) were suggested based on CALPHAD modeling. The calculated vibrational entropies of mixing are positive for FCC CoCrFeNi, negative for BCC MoNbTaW, and near-zero for HCP CoOsReRu. The total entropies of mixing were observed to trend in descending order: CoCrFeNi > CoOsReRu > MoNbTaW. Calculated lattice parameters agree extremely well with averaged values estimated from the rule of mixtures (ROM) if themore » same crystal structure is used for the elements and the alloy. The deviation in the calculated elastic properties from ROM for select alloys is small but is susceptible to the choice used for the structures of pure components.« less

Scalability of surrogate-assisted multi-objective optimization of antenna structures exploiting variable-fidelity electromagnetic simulation models

NASA Astrophysics Data System (ADS)

Koziel, Slawomir; Bekasiewicz, Adrian

2016-10-01

Multi-objective optimization of antenna structures is a challenging task owing to the high computational cost of evaluating the design objectives as well as the large number of adjustable parameters. Design speed-up can be achieved by means of surrogate-based optimization techniques. In particular, a combination of variable-fidelity electromagnetic (EM) simulations, design space reduction techniques, response surface approximation models and design refinement methods permits identification of the Pareto-optimal set of designs within a reasonable timeframe. Here, a study concerning the scalability of surrogate-assisted multi-objective antenna design is carried out based on a set of benchmark problems, with the dimensionality of the design space ranging from six to 24 and a CPU cost of the EM antenna model from 10 to 20 min per simulation. Numerical results indicate that the computational overhead of the design process increases more or less quadratically with the number of adjustable geometric parameters of the antenna structure at hand, which is a promising result from the point of view of handling even more complex problems.

Quantum Monte Carlo for atoms and molecules

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

Barnett, R.N.

1989-11-01

The diffusion quantum Monte Carlo with fixed nodes (QMC) approach has been employed in studying energy-eigenstates for 1--4 electron systems. Previous work employing the diffusion QMC technique yielded energies of high quality for H{sub 2}, LiH, Li{sub 2}, and H{sub 2}O. Here, the range of calculations with this new approach has been extended to include additional first-row atoms and molecules. In addition, improvements in the previously computed fixed-node energies of LiH, Li{sub 2}, and H{sub 2}O have been obtained using more accurate trial functions. All computations were performed within, but are not limited to, the Born-Oppenheimer approximation. In our computations,more » the effects of variation of Monte Carlo parameters on the QMC solution of the Schroedinger equation were studied extensively. These parameters include the time step, renormalization time and nodal structure. These studies have been very useful in determining which choices of such parameters will yield accurate QMC energies most efficiently. Generally, very accurate energies (90--100% of the correlation energy is obtained) have been computed with single-determinant trail functions multiplied by simple correlation functions. Improvements in accuracy should be readily obtained using more complex trial functions.« less

Knowledge of damage identification about tensegrities via flexibility disassembly

NASA Astrophysics Data System (ADS)

Jiang, Ge; Feng, Xiaodong; Du, Shigui

2017-12-01

Tensegrity structures composing of continuous cables and discrete struts are under tension and compression, respectively. In order to determine the damage extents of tensegrity structures, a new method for tensegrity structural damage identification is presented based on flexibility disassembly. To decompose a tensegrity structural flexibility matrix into the matrix represention of the connectivity between degress-of-freedoms and the diagonal matrix comprising of magnitude informations. Step 1: Calculate perturbation flexibility; Step 2: Compute the flexibility connectivity matrix and perturbation flexibility parameters; Step 3: Calculate the perturbation stiffness parameters. The efficiency of the proposed method is demonstrated by a numeical example comprising of 12 cables and 4 struts with pretensioned. Accurate identification of local damage depends on the availability of good measured data, an accurate and reasonable algorithm.

An easily implemented static condensation method for structural sensitivity analysis

NASA Technical Reports Server (NTRS)

Gangadharan, S. N.; Haftka, R. T.; Nikolaidis, E.

1990-01-01

A black-box approach to static condensation for sensitivity analysis is presented with illustrative examples of a cube and a car structure. The sensitivity of the structural response with respect to joint stiffness parameter is calculated using the direct method, forward-difference, and central-difference schemes. The efficiency of the various methods for identifying joint stiffness parameters from measured static deflections of these structures is compared. The results indicate that the use of static condensation can reduce computation times significantly and the black-box approach is only slightly less efficient than the standard implementation of static condensation. The ease of implementation of the black-box approach recommends it for use with general-purpose finite element codes that do not have a built-in facility for static condensation.

Automatic high-throughput screening of colloidal crystals using machine learning

NASA Astrophysics Data System (ADS)

Spellings, Matthew; Glotzer, Sharon C.

Recent improvements in hardware and software have united to pose an interesting problem for computational scientists studying self-assembly of particles into crystal structures: while studies covering large swathes of parameter space can be dispatched at once using modern supercomputers and parallel architectures, identifying the different regions of a phase diagram is often a serial task completed by hand. While analytic methods exist to distinguish some simple structures, they can be difficult to apply, and automatic identification of more complex structures is still lacking. In this talk we describe one method to create numerical ``fingerprints'' of local order and use them to analyze a study of complex ordered structures. We can use these methods as first steps toward automatic exploration of parameter space and, more broadly, the strategic design of new materials.

Machine-learned and codified synthesis parameters of oxide materials

NASA Astrophysics Data System (ADS)

Kim, Edward; Huang, Kevin; Tomala, Alex; Matthews, Sara; Strubell, Emma; Saunders, Adam; McCallum, Andrew; Olivetti, Elsa

2017-09-01

Predictive materials design has rapidly accelerated in recent years with the advent of large-scale resources, such as materials structure and property databases generated by ab initio computations. In the absence of analogous ab initio frameworks for materials synthesis, high-throughput and machine learning techniques have recently been harnessed to generate synthesis strategies for select materials of interest. Still, a community-accessible, autonomously-compiled synthesis planning resource which spans across materials systems has not yet been developed. In this work, we present a collection of aggregated synthesis parameters computed using the text contained within over 640,000 journal articles using state-of-the-art natural language processing and machine learning techniques. We provide a dataset of synthesis parameters, compiled autonomously across 30 different oxide systems, in a format optimized for planning novel syntheses of materials.

Optimization of the molecular dynamics method for simulations of DNA and ion transport through biological nanopores.

PubMed

Wells, David B; Bhattacharya, Swati; Carr, Rogan; Maffeo, Christopher; Ho, Anthony; Comer, Jeffrey; Aksimentiev, Aleksei

2012-01-01

Molecular dynamics (MD) simulations have become a standard method for the rational design and interpretation of experimental studies of DNA translocation through nanopores. The MD method, however, offers a multitude of algorithms, parameters, and other protocol choices that can affect the accuracy of the resulting data as well as computational efficiency. In this chapter, we examine the most popular choices offered by the MD method, seeking an optimal set of parameters that enable the most computationally efficient and accurate simulations of DNA and ion transport through biological nanopores. In particular, we examine the influence of short-range cutoff, integration timestep and force field parameters on the temperature and concentration dependence of bulk ion conductivity, ion pairing, ion solvation energy, DNA structure, DNA-ion interactions, and the ionic current through a nanopore.

Parameter investigation with line-implicit lower-upper symmetric Gauss-Seidel on 3D stretched grids

NASA Astrophysics Data System (ADS)

Otero, Evelyn; Eliasson, Peter

2015-03-01

An implicit lower-upper symmetric Gauss-Seidel (LU-SGS) solver has been implemented as a multigrid smoother combined with a line-implicit method as an acceleration technique for Reynolds-averaged Navier-Stokes (RANS) simulation on stretched meshes. The computational fluid dynamics code concerned is Edge, an edge-based finite volume Navier-Stokes flow solver for structured and unstructured grids. The paper focuses on the investigation of the parameters related to our novel line-implicit LU-SGS solver for convergence acceleration on 3D RANS meshes. The LU-SGS parameters are defined as the Courant-Friedrichs-Lewy number, the left-hand side dissipation, and the convergence of iterative solution of the linear problem arising from the linearisation of the implicit scheme. The influence of these parameters on the overall convergence is presented and default values are defined for maximum convergence acceleration. The optimised settings are applied to 3D RANS computations for comparison with explicit and line-implicit Runge-Kutta smoothing. For most of the cases, a computing time acceleration of the order of 2 is found depending on the mesh type, namely the boundary layer and the magnitude of residual reduction.

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

Xu, Hongyi; Li, Yang; Zeng, Danielle

Process integration and optimization is the key enabler of the Integrated Computational Materials Engineering (ICME) of carbon fiber composites. In this paper, automated workflows are developed for two types of composites: Sheet Molding Compounds (SMC) short fiber composites, and multi-layer unidirectional (UD) composites. For SMC, the proposed workflow integrates material processing simulation, microstructure representation volume element (RVE) models, material property prediction and structure preformation simulation to enable multiscale, multidisciplinary analysis and design. Processing parameters, microstructure parameters and vehicle subframe geometry parameters are defined as the design variables; the stiffness and weight of the structure are defined as the responses. Formore » multi-layer UD structure, this work focuses on the discussion of different design representation methods and their impacts on the optimization performance. Challenges in ICME process integration and optimization are also summarized and highlighted. Two case studies are conducted to demonstrate the integrated process and its application in optimization.« less

Combined control-structure optimization

NASA Technical Reports Server (NTRS)

Salama, M.; Milman, M.; Bruno, R.; Scheid, R.; Gibson, S.

1989-01-01

An approach for combined control-structure optimization keyed to enhancing early design trade-offs is outlined and illustrated by numerical examples. The approach employs a homotopic strategy and appears to be effective for generating families of designs that can be used in these early trade studies. Analytical results were obtained for classes of structure/control objectives with linear quadratic Gaussian (LQG) and linear quadratic regulator (LQR) costs. For these, researchers demonstrated that global optima can be computed for small values of the homotopy parameter. Conditions for local optima along the homotopy path were also given. Details of two numerical examples employing the LQR control cost were given showing variations of the optimal design variables along the homotopy path. The results of the second example suggest that introducing a second homotopy parameter relating the two parts of the control index in the LQG/LQR formulation might serve to enlarge the family of Pareto optima, but its effect on modifying the optimal structural shapes may be analogous to the original parameter lambda.

Accurate detection of hierarchical communities in complex networks based on nonlinear dynamical evolution

NASA Astrophysics Data System (ADS)

Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

2018-04-01

One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community detection in complex networks.

Integral projection models for finite populations in a stochastic environment.

PubMed

Vindenes, Yngvild; Engen, Steinar; Saether, Bernt-Erik

2011-05-01

Continuous types of population structure occur when continuous variables such as body size or habitat quality affect the vital parameters of individuals. These structures can give rise to complex population dynamics and interact with environmental conditions. Here we present a model for continuously structured populations with finite size, including both demographic and environmental stochasticity in the dynamics. Using recent methods developed for discrete age-structured models we derive the demographic and environmental variance of the population growth as functions of a continuous state variable. These two parameters, together with the expected population growth rate, are used to define a one-dimensional diffusion approximation of the population dynamics. Thus, a substantial reduction in complexity is achieved as the dynamics of the complex structured model can be described by only three population parameters. We provide methods for numerical calculation of the model parameters and demonstrate the accuracy of the diffusion approximation by computer simulation of specific examples. The general modeling framework makes it possible to analyze and predict future dynamics and extinction risk of populations with various types of structure, and to explore consequences of changes in demography caused by, e.g., climate change or different management decisions. Our results are especially relevant for small populations that are often of conservation concern.

Probabilistic Assessment of Fracture Progression in Composite Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Minnetyan, Levon; Mauget, Bertrand; Huang, Dade; Addi, Frank

1999-01-01

This report describes methods and corresponding computer codes that are used to evaluate progressive damage and fracture and to perform probabilistic assessment in built-up composite structures. Structural response is assessed probabilistically, during progressive fracture. The effects of design variable uncertainties on structural fracture progression are quantified. The fast probability integrator (FPI) is used to assess the response scatter in the composite structure at damage initiation. The sensitivity of the damage response to design variables is computed. The methods are general purpose and are applicable to stitched and unstitched composites in all types of structures and fracture processes starting from damage initiation to unstable propagation and to global structure collapse. The methods are demonstrated for a polymer matrix composite stiffened panel subjected to pressure. The results indicated that composite constituent properties, fabrication parameters, and respective uncertainties have a significant effect on structural durability and reliability. Design implications with regard to damage progression, damage tolerance, and reliability of composite structures are examined.

On parameters identification of computational models of vibrations during quiet standing of humans

NASA Astrophysics Data System (ADS)

Barauskas, R.; Krušinskienė, R.

2007-12-01

Vibration of the center of pressure (COP) of human body on the base of support during quiet standing is a very popular clinical research, which provides useful information about the physical and health condition of an individual. In this work, vibrations of COP of a human body in forward-backward direction during still standing are generated using controlled inverted pendulum (CIP) model with a single degree of freedom (dof) supplied with proportional, integral and differential (PID) controller, which represents the behavior of the central neural system of a human body and excited by cumulative disturbance vibration, generated within the body due to breathing or any other physical condition. The identification of the model and disturbance parameters is an important stage while creating a close-to-reality computational model able to evaluate features of disturbance. The aim of this study is to present the CIP model parameters identification approach based on the information captured by time series of the COP signal. The identification procedure is based on an error function minimization. Error function is formulated in terms of time laws of computed and experimentally measured COP vibrations. As an alternative, error function is formulated in terms of the stabilogram diffusion function (SDF). The minimization of error functions is carried out by employing methods based on sensitivity functions of the error with respect to model and excitation parameters. The sensitivity functions are obtained by using the variational techniques. The inverse dynamic problem approach has been employed in order to establish the properties of the disturbance time laws ensuring the satisfactory coincidence of measured and computed COP vibration laws. The main difficulty of the investigated problem is encountered during the model validation stage. Generally, neither the PID controller parameter set nor the disturbance time law are known in advance. In this work, an error function formulated in terms of time derivative of disturbance torque has been proposed in order to obtain PID controller parameters, as well as the reference time law of the disturbance. The disturbance torque is calculated from experimental data using the inverse dynamic approach. Experiments presented in this study revealed that vibrations of disturbance torque and PID controller parameters identified by the method may be qualified as feasible in humans. Presented approach may be easily extended to structural models with any number of dof or higher structural complexity.

Active flutter suppression using optical output feedback digital controllers

NASA Technical Reports Server (NTRS)

1982-01-01

A method for synthesizing digital active flutter suppression controllers using the concept of optimal output feedback is presented. A convergent algorithm is employed to determine constrained control law parameters that minimize an infinite time discrete quadratic performance index. Low order compensator dynamics are included in the control law and the compensator parameters are computed along with the output feedback gain as part of the optimization process. An input noise adjustment procedure is used to improve the stability margins of the digital active flutter controller. Sample rate variation, prefilter pole variation, control structure variation and gain scheduling are discussed. A digital control law which accommodates computation delay can stabilize the wing with reasonable rms performance and adequate stability margins.

MDTS: automatic complex materials design using Monte Carlo tree search.

PubMed

M Dieb, Thaer; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

2017-01-01

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

MDTS: automatic complex materials design using Monte Carlo tree search

NASA Astrophysics Data System (ADS)

Dieb, Thaer M.; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

2017-12-01

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

Coarse-Grained Descriptions of Dynamics for Networks with Both Intrinsic and Structural Heterogeneities

PubMed Central

Bertalan, Tom; Wu, Yan; Laing, Carlo; Gear, C. William; Kevrekidis, Ioannis G.

2017-01-01

Finding accurate reduced descriptions for large, complex, dynamically evolving networks is a crucial enabler to their simulation, analysis, and ultimately design. Here, we propose and illustrate a systematic and powerful approach to obtaining good collective coarse-grained observables—variables successfully summarizing the detailed state of such networks. Finding such variables can naturally lead to successful reduced dynamic models for the networks. The main premise enabling our approach is the assumption that the behavior of a node in the network depends (after a short initial transient) on the node identity: a set of descriptors that quantify the node properties, whether intrinsic (e.g., parameters in the node evolution equations) or structural (imparted to the node by its connectivity in the particular network structure). The approach creates a natural link with modeling and “computational enabling technology” developed in the context of Uncertainty Quantification. In our case, however, we will not focus on ensembles of different realizations of a problem, each with parameters randomly selected from a distribution. We will instead study many coupled heterogeneous units, each characterized by randomly assigned (heterogeneous) parameter value(s). One could then coin the term Heterogeneity Quantification for this approach, which we illustrate through a model dynamic network consisting of coupled oscillators with one intrinsic heterogeneity (oscillator individual frequency) and one structural heterogeneity (oscillator degree in the undirected network). The computational implementation of the approach, its shortcomings and possible extensions are also discussed. PMID:28659781

Factorization and reduction methods for optimal control of distributed parameter systems

NASA Technical Reports Server (NTRS)

Burns, J. A.; Powers, R. K.

1985-01-01

A Chandrasekhar-type factorization method is applied to the linear-quadratic optimal control problem for distributed parameter systems. An aeroelastic control problem is used as a model example to demonstrate that if computationally efficient algorithms, such as those of Chandrasekhar-type, are combined with the special structure often available to a particular problem, then an abstract approximation theory developed for distributed parameter control theory becomes a viable method of solution. A numerical scheme based on averaging approximations is applied to hereditary control problems. Numerical examples are given.

Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems

PubMed Central

Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R

2006-01-01

Background We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. Results We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Conclusion Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems. PMID:17081289

Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems.

PubMed

Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R

2006-11-02

We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems.

Accelerating calculations of RNA secondary structure partition functions using GPUs

PubMed Central

2013-01-01

Background RNA performs many diverse functions in the cell in addition to its role as a messenger of genetic information. These functions depend on its ability to fold to a unique three-dimensional structure determined by the sequence. The conformation of RNA is in part determined by its secondary structure, or the particular set of contacts between pairs of complementary bases. Prediction of the secondary structure of RNA from its sequence is therefore of great interest, but can be computationally expensive. In this work we accelerate computations of base-pair probababilities using parallel graphics processing units (GPUs). Results Calculation of the probabilities of base pairs in RNA secondary structures using nearest-neighbor standard free energy change parameters has been implemented using CUDA to run on hardware with multiprocessor GPUs. A modified set of recursions was introduced, which reduces memory usage by about 25%. GPUs are fastest in single precision, and for some hardware, restricted to single precision. This may introduce significant roundoff error. However, deviations in base-pair probabilities calculated using single precision were found to be negligible compared to those resulting from shifting the nearest-neighbor parameters by a random amount of magnitude similar to their experimental uncertainties. For large sequences running on our particular hardware, the GPU implementation reduces execution time by a factor of close to 60 compared with an optimized serial implementation, and by a factor of 116 compared with the original code. Conclusions Using GPUs can greatly accelerate computation of RNA secondary structure partition functions, allowing calculation of base-pair probabilities for large sequences in a reasonable amount of time, with a negligible compromise in accuracy due to working in single precision. The source code is integrated into the RNAstructure software package and available for download at http://rna.urmc.rochester.edu. PMID:24180434

Metrology of deep trench etched memory structures using 3D scatterometry

NASA Astrophysics Data System (ADS)

Reinig, Peter; Dost, Rene; Moert, Manfred; Hingst, Thomas; Mantz, Ulrich; Moffitt, Jasen; Shakya, Sushil; Raymond, Christopher J.; Littau, Mike

2005-05-01

Scatterometry is receiving considerable attention as an emerging optical metrology in the silicon industry. One area of progress in deploying these powerful measurements in process control is performing measurements on real device structures, as opposed to limiting scatterometry measurements to periodic structures, such as line-space gratings, placed in the wafer scribe. In this work we will discuss applications of 3D scatterometry to the measurement of advanced trench memory devices. This is a challenging and complex scatterometry application that requires exceptionally high-performance computational abilities. In order to represent the physical device, the relatively tall structures require a high number of slices in the rigorous coupled wave analysis (RCWA) theoretical model. This is complicated further by the presence of an amorphous silicon hard mask on the surface, which is highly sensitive to reflectance scattering and therefore needs to be modeled in detail. The overall structure is comprised of several layers, with the trenches presenting a complex bow-shape sidewall that must be measured. Finally, the double periodicity in the structures demands significantly greater computational capabilities. Our results demonstrate that angular scatterometry is sensitive to the key parameters of interest. The influence of further model parameters and parameter cross correlations have to be carefully taken into account. Profile results obtained by non-library optimization methods compare favorably with cross-section SEM images. Generating a model library suitable for process control, which is preferred for precision, presents numerical throughput challenges. Details will be discussed regarding library generation approaches and strategies for reducing the numerical overhead. Scatterometry and SEM results will be compared, leading to conclusions about the feasibility of this advanced application.

The hierarchical expert tuning of PID controllers using tools of soft computing.

PubMed

Karray, F; Gueaieb, W; Al-Sharhan, S

2002-01-01

We present soft computing-based results pertaining to the hierarchical tuning process of PID controllers located within the control loop of a class of nonlinear systems. The results are compared with PID controllers implemented either in a stand alone scheme or as a part of conventional gain scheduling structure. This work is motivated by the increasing need in the industry to design highly reliable and efficient controllers for dealing with regulation and tracking capabilities of complex processes characterized by nonlinearities and possibly time varying parameters. The soft computing-based controllers proposed are hybrid in nature in that they integrate within a well-defined hierarchical structure the benefits of hard algorithmic controllers with those having supervisory capabilities. The controllers proposed also have the distinct features of learning and auto-tuning without the need for tedious and computationally extensive online systems identification schemes.

Anisotropic Effects on Constitutive Model Parameters of Aluminum Alloys

DTIC Science & Technology

2012-01-01

constants are required input to computer codes (LS-DYNA, DYNA3D or SPH ) to accurately simulate fragment impact on structural components made of high...different temperatures. These model constants are required input to computer codes (LS-DYNA, DYNA3D or SPH ) to accurately simulate fragment impact on...ADDRESS(ES) Naval Surface Warfare Center,4104Evans Way Suite 102,Indian Head,MD,20640 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING

Computer-Aided Process Model For Carbon/Phenolic Materials

NASA Technical Reports Server (NTRS)

Letson, Mischell A.; Bunker, Robert C.

1996-01-01

Computer program implements thermochemical model of processing of carbon-fiber/phenolic-matrix composite materials into molded parts of various sizes and shapes. Directed toward improving fabrication of rocket-engine-nozzle parts, also used to optimize fabrication of other structural components, and material-property parameters changed to apply to other materials. Reduces costs by reducing amount of laboratory trial and error needed to optimize curing processes and to predict properties of cured parts.

Computed parameters : moisture content for unbound materials at seasonal monitoring program sites

DOT National Transportation Integrated Search

2000-01-01

Moisture content plays a significant role in the performance of pavements. Variation in the amount of moisture in the subgrade can change the volume of swelling soil, which may result in detrimental deformation of the pavement structure. An increase ...

Unsteady Aerodynamic Force Sensing from Measured Strain

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi

2016-01-01

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm. A cantilevered rectangular wing built and tested at the NASA Langley Research Center (Hampton, Virginia, USA) in 1959 is used to validate the simple approach. Unsteady aerodynamic forces as well as wing deflections, velocities, accelerations, and strains are computed using the CFL3D computational fluid dynamics (CFD) code and an MSC/NASTRAN code (MSC Software Corporation, Newport Beach, California, USA), and these CFL3D-based results are assumed as measured quantities. Based on the measured strains, wing deflections, velocities, accelerations, and aerodynamic forces are computed using the proposed approach. These computed deflections, velocities, accelerations, and unsteady aerodynamic forces are compared with the CFL3D/NASTRAN-based results. In general, computed aerodynamic forces based on the lifting surface theory in subsonic speeds are in good agreement with the target aerodynamic forces generated using CFL3D code with the Euler equation. Excellent aeroelastic responses are obtained even with unsteady strain data under the signal to noise ratio of -9.8dB. The deflections, velocities, and accelerations at each sensor location are independent of structural and aerodynamic models. Therefore, the distributed strain data together with the current proposed approaches can be used as distributed deflection, velocity, and acceleration sensors. This research demonstrates the feasibility of obtaining induced drag and lift forces through the use of distributed sensor technology with measured strain data. An active induced drag control system thus can be designed using the two computed aerodynamic forces, induced drag and lift, to improve the fuel efficiency of an aircraft. Interpolation elements between structural finite element grids and the CFD grids and centroids are successfully incorporated with the unsteady aeroelastic computation scheme. The most critical technology for the success of the proposed approach is the robust on-line parameter estimator, since the least-squares curve fitting method depends heavily on aeroelastic system frequencies and damping factors.

Point Judith, Rhode Island, Breakwater Risk Assessment

DTIC Science & Technology

2015-08-01

output stations. Beach zones considered included the sandy beach to the west side of the HoR, which had significant dune features and was fronting...time dependency for crest height and wave parameters is assumed, hc = total damaged crest height of structure from toe , Lp is the local wave length...computed using linear wave theory and Tp, h is the toe depth, hc’ = total undamaged crest height of structure from toe , At = area of structure enclosed

Geometry motivated alternative view on local protein backbone structures.

PubMed

Zacharias, Jan; Knapp, Ernst Walter

2013-11-01

We present an alternative to the classical Ramachandran plot (R-plot) to display local protein backbone structure. Instead of the (φ, ψ)-backbone angles relating to the chemical architecture of polypeptides generic helical parameters are used. These are the rotation or twist angle ϑ and the helical rise parameter d. Plots with these parameters provide a different view on the nature of local protein backbone structures. It allows to display the local structures in polar (d, ϑ)-coordinates, which is not possible for an R-plot, where structural regimes connected by periodicity appear disconnected. But there are other advantages, like a clear discrimination of the handedness of a local structure, a larger spread of the different local structure domains--the latter can yield a better separation of different local secondary structure motives--and many more. Compared to the R-plot we are not aware of any major disadvantage to classify local polypeptide structures with the (d, ϑ)-plot, except that it requires some elementary computations. To facilitate usage of the new (d, ϑ)-plot for protein structures we provide a web application (http://agknapp.chemie.fu-berlin.de/secsass), which shows the (d, ϑ)-plot side-by-side with the R-plot. © 2013 The Protein Society.

Multi-objective shape optimization of plate structure under stress criteria based on sub-structured mixed FEM and genetic algorithms

NASA Astrophysics Data System (ADS)

Garambois, Pierre; Besset, Sebastien; Jézéquel, Louis

2015-07-01

This paper presents a methodology for the multi-objective (MO) shape optimization of plate structure under stress criteria, based on a mixed Finite Element Model (FEM) enhanced with a sub-structuring method. The optimization is performed with a classical Genetic Algorithm (GA) method based on Pareto-optimal solutions and considers thickness distributions parameters and antagonist objectives among them stress criteria. We implement a displacement-stress Dynamic Mixed FEM (DM-FEM) for plate structure vibrations analysis. Such a model gives a privileged access to the stress within the plate structure compared to primal classical FEM, and features a linear dependence to the thickness parameters. A sub-structuring reduction method is also computed in order to reduce the size of the mixed FEM and split the given structure into smaller ones with their own thickness parameters. Those methods combined enable a fast and stress-wise efficient structure analysis, and improve the performance of the repetitive GA. A few cases of minimizing the mass and the maximum Von Mises stress within a plate structure under a dynamic load put forward the relevance of our method with promising results. It is able to satisfy multiple damage criteria with different thickness distributions, and use a smaller FEM.

NMReDATA, a standard to report the NMR assignment and parameters of organic compounds.

PubMed

Pupier, Marion; Nuzillard, Jean-Marc; Wist, Julien; Schlörer, Nils E; Kuhn, Stefan; Erdelyi, Mate; Steinbeck, Christoph; Williams, Antony J; Butts, Craig; Claridge, Tim D W; Mikhova, Bozhana; Robien, Wolfgang; Dashti, Hesam; Eghbalnia, Hamid R; Farès, Christophe; Adam, Christian; Kessler, Pavel; Moriaud, Fabrice; Elyashberg, Mikhail; Argyropoulos, Dimitris; Pérez, Manuel; Giraudeau, Patrick; Gil, Roberto R; Trevorrow, Paul; Jeannerat, Damien

2018-04-14

Even though NMR has found countless applications in the field of small molecule characterization, there is no standard file format available for the NMR data relevant to structure characterization of small molecules. A new format is therefore introduced to associate the NMR parameters extracted from 1D and 2D spectra of organic compounds to the proposed chemical structure. These NMR parameters, which we shall call NMReDATA (for nuclear magnetic resonance extracted data), include chemical shift values, signal integrals, intensities, multiplicities, scalar coupling constants, lists of 2D correlations, relaxation times, and diffusion rates. The file format is an extension of the existing Structure Data Format, which is compatible with the commonly used MOL format. The association of an NMReDATA file with the raw and spectral data from which it originates constitutes an NMR record. This format is easily readable by humans and computers and provides a simple and efficient way for disseminating results of structural chemistry investigations, allowing automatic verification of published results, and for assisting the constitution of highly needed open-source structural databases. Copyright © 2018 John Wiley & Sons, Ltd.

Microwave Spectra of the Two Conformers of PROPENE-3-{d}_1 and a Semiexperimental Equilibrium Structure of Propene

NASA Astrophysics Data System (ADS)

Craig, Norman C.; Demaison, J.; Rudolph, Heinz Dieter; Gurusinghe, Ranil M.; Tubergen, Michael; Coudert, L. H.; Szalay, Peter; Császár, Attila

2017-06-01

FT microwave spectra have been observed and analyzed for the S (in-plane) and A (out-of-plane) conformers of propene-3-{d}_1 in the 10-22 GHz region. Both conformers display splittings due to deuterium quadrupole coupling; for the latter one only, a 19 MHz splitting due to internal rotation of the partially deuterated methyl group has been observed. In addition to rotational constants, the analysis yielded quadrupole coupling constants and parameters describing the tunneling splitting and its rotational dependence. Improved rotational constants for parent propene and the three ^{13}C_1 species are recently available. Use of vibration-rotation interaction constants computed at the MP2(FC)/cc-pVTZ level gave equilibrium rotational constants for these six species and for fourteen more deuterium isotopologues with diminished accuracy from early literature data. A semiexperimental equilibrium structure, r_e^{SE}, has been determined for propene by fitting fourteen structural parameters to the equilibrium rotational constants. The new r_e^{SE} structure compares well with an ab initio equilibrium structure computed with the all-electron CCSD(T)/cc-pV(Q,T)Z model and with a structure obtained using the mixed regression method with predicates and equilibrium rotational constants. N. C. Craig, P. Groner, A. R. Conrad, R. Gurusinghe, M. J. Tubergen J. Mol. Spectrosc. 248, 1-6 (2016).

Design for inadvertent damage in composite laminates

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.; Chamis, Christos C.

1992-01-01

Simplified predictive methods and models to computationally simulate durability and damage in polymer matrix composite materials/structures are described. The models include (1) progressive fracture, (2) progressively damaged structural behavior, (3) progressive fracture in aggressive environments, (4) stress concentrations, and (5) impact resistance. Several examples are included to illustrate applications of the models and to identify significant parameters and sensitivities. Comparisons with limited experimental data are made.

Protein folding, protein structure and the origin of life: Theoretical methods and solutions of dynamical problems

NASA Technical Reports Server (NTRS)

Weaver, D. L.

1982-01-01

Theoretical methods and solutions of the dynamics of protein folding, protein aggregation, protein structure, and the origin of life are discussed. The elements of a dynamic model representing the initial stages of protein folding are presented. The calculation and experimental determination of the model parameters are discussed. The use of computer simulation for modeling protein folding is considered.

Calculation of Weibull strength parameters, Batdorf flaw density constants and related statistical quantities using PC-CARES

NASA Technical Reports Server (NTRS)

Szatmary, Steven A.; Gyekenyesi, John P.; Nemeth, Noel N.

1990-01-01

This manual describes the operation and theory of the PC-CARES (Personal Computer-Ceramic Analysis and Reliability Evaluation of Structures) computer program for the IBM PC and compatibles running PC-DOS/MS-DOR OR IBM/MS-OS/2 (version 1.1 or higher) operating systems. The primary purpose of this code is to estimate Weibull material strength parameters, the Batdorf crack density coefficient, and other related statistical quantities. Included in the manual is the description of the calculation of shape and scale parameters of the two-parameter Weibull distribution using the least-squares analysis and maximum likelihood methods for volume- and surface-flaw-induced fracture in ceramics with complete and censored samples. The methods for detecting outliers and for calculating the Kolmogorov-Smirnov and the Anderson-Darling goodness-of-fit statistics and 90 percent confidence bands about the Weibull line, as well as the techniques for calculating the Batdorf flaw-density constants are also described.

On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.

PubMed

Yamazaki, Keisuke

2012-07-01

Parametric models for sequential data, such as hidden Markov models, stochastic context-free grammars, and linear dynamical systems, are widely used in time-series analysis and structural data analysis. Computation of the likelihood function is one of primary considerations in many learning methods. Iterative calculation of the likelihood such as the model selection is still time-consuming though there are effective algorithms based on dynamic programming. The present paper studies parameter learning in a simplified feature space to reduce the computational cost. Simplifying data is a common technique seen in feature selection and dimension reduction though an oversimplified space causes adverse learning results. Therefore, we mathematically investigate a condition of the feature map to have an asymptotically equivalent convergence point of estimated parameters, referred to as the vicarious map. As a demonstration to find vicarious maps, we consider the feature space, which limits the length of data, and derive a necessary length for parameter learning in hidden Markov models. Copyright © 2012 Elsevier Ltd. All rights reserved.

Fitting a Structured Juvenile-Adult Model for Green Tree Frogs to Population Estimates from Capture-Mark-Recapture Field Data

USGS Publications Warehouse

Ackleh, A.S.; Carter, J.; Deng, K.; Huang, Q.; Pal, N.; Yang, X.

2012-01-01

We derive point and interval estimates for an urban population of green tree frogs (Hyla cinerea) from capture-mark-recapture field data obtained during the years 2006-2009. We present an infinite-dimensional least-squares approach which compares a mathematical population model to the statistical population estimates obtained from the field data. The model is composed of nonlinear first-order hyperbolic equations describing the dynamics of the amphibian population where individuals are divided into juveniles (tadpoles) and adults (frogs). To solve the least-squares problem, an explicit finite difference approximation is developed. Convergence results for the computed parameters are presented. Parameter estimates for the vital rates of juveniles and adults are obtained, and standard deviations for these estimates are computed. Numerical results for the model sensitivity with respect to these parameters are given. Finally, the above-mentioned parameter estimates are used to illustrate the long-time behavior of the population under investigation. ?? 2011 Society for Mathematical Biology.

Cumulative reports and publications through December 31, 1989

NASA Technical Reports Server (NTRS)

1990-01-01

A complete list of reports from the Institute for Computer Applications in Science and Engineering (ICASE) is presented. The major categories of the current ICASE research program are: numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; control and parameter identification problems, with emphasis on effectual numerical methods; computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, structural analysis, and chemistry; computer systems and software, especially vector and parallel computers, microcomputers, and data management. Since ICASE reports are intended to be preprints of articles that will appear in journals or conference proceedings, the published reference is included when it is available.

Particle tracking acceleration via signed distance fields in direct-accelerated geometry Monte Carlo

DOE PAGES

Shriwise, Patrick C.; Davis, Andrew; Jacobson, Lucas J.; ...

2017-08-26

Computer-aided design (CAD)-based Monte Carlo radiation transport is of value to the nuclear engineering community for its ability to conduct transport on high-fidelity models of nuclear systems, but it is more computationally expensive than native geometry representations. This work describes the adaptation of a rendering data structure, the signed distance field, as a geometric query tool for accelerating CAD-based transport in the direct-accelerated geometry Monte Carlo toolkit. Demonstrations of its effectiveness are shown for several problems. The beginnings of a predictive model for the data structure's utilization based on various problem parameters is also introduced.

Inferring Nonlinear Neuronal Computation Based on Physiologically Plausible Inputs

PubMed Central

McFarland, James M.; Cui, Yuwei; Butts, Daniel A.

2013-01-01

The computation represented by a sensory neuron's response to stimuli is constructed from an array of physiological processes both belonging to that neuron and inherited from its inputs. Although many of these physiological processes are known to be nonlinear, linear approximations are commonly used to describe the stimulus selectivity of sensory neurons (i.e., linear receptive fields). Here we present an approach for modeling sensory processing, termed the Nonlinear Input Model (NIM), which is based on the hypothesis that the dominant nonlinearities imposed by physiological mechanisms arise from rectification of a neuron's inputs. Incorporating such ‘upstream nonlinearities’ within the standard linear-nonlinear (LN) cascade modeling structure implicitly allows for the identification of multiple stimulus features driving a neuron's response, which become directly interpretable as either excitatory or inhibitory. Because its form is analogous to an integrate-and-fire neuron receiving excitatory and inhibitory inputs, model fitting can be guided by prior knowledge about the inputs to a given neuron, and elements of the resulting model can often result in specific physiological predictions. Furthermore, by providing an explicit probabilistic model with a relatively simple nonlinear structure, its parameters can be efficiently optimized and appropriately regularized. Parameter estimation is robust and efficient even with large numbers of model components and in the context of high-dimensional stimuli with complex statistical structure (e.g. natural stimuli). We describe detailed methods for estimating the model parameters, and illustrate the advantages of the NIM using a range of example sensory neurons in the visual and auditory systems. We thus present a modeling framework that can capture a broad range of nonlinear response functions while providing physiologically interpretable descriptions of neural computation. PMID:23874185

A theoretical-electron-density databank using a model of real and virtual spherical atoms.

PubMed

Nassour, Ayoub; Domagala, Slawomir; Guillot, Benoit; Leduc, Theo; Lecomte, Claude; Jelsch, Christian

2017-08-01

A database describing the electron density of common chemical groups using combinations of real and virtual spherical atoms is proposed, as an alternative to the multipolar atom modelling of the molecular charge density. Theoretical structure factors were computed from periodic density functional theory calculations on 38 crystal structures of small molecules and the charge density was subsequently refined using a density model based on real spherical atoms and additional dummy charges on the covalent bonds and on electron lone-pair sites. The electron-density parameters of real and dummy atoms present in a similar chemical environment were averaged on all the molecules studied to build a database of transferable spherical atoms. Compared with the now-popular databases of transferable multipolar parameters, the spherical charge modelling needs fewer parameters to describe the molecular electron density and can be more easily incorporated in molecular modelling software for the computation of electrostatic properties. The construction method of the database is described. In order to analyse to what extent this modelling method can be used to derive meaningful molecular properties, it has been applied to the urea molecule and to biotin/streptavidin, a protein/ligand complex.

Optimization of structures undergoing harmonic or stochastic excitation. Ph.D. Thesis; [atmospheric turbulence and white noise

NASA Technical Reports Server (NTRS)

Johnson, E. H.

1975-01-01

The optimal design was investigated of simple structures subjected to dynamic loads, with constraints on the structures' responses. Optimal designs were examined for one dimensional structures excited by harmonically oscillating loads, similar structures excited by white noise, and a wing in the presence of continuous atmospheric turbulence. The first has constraints on the maximum allowable stress while the last two place bounds on the probability of failure of the structure. Approximations were made to replace the time parameter with a frequency parameter. For the first problem, this involved the steady state response, and in the remaining cases, power spectral techniques were employed to find the root mean square values of the responses. Optimal solutions were found by using computer algorithms which combined finite elements methods with optimization techniques based on mathematical programming. It was found that the inertial loads for these dynamic problems result in optimal structures that are radically different from those obtained for structures loaded statically by forces of comparable magnitude.

Left ventricular eccentricity index measured with SPECT myocardial perfusion imaging: An additional parameter of adverse cardiac remodeling.

PubMed

Gimelli, Alessia; Liga, Riccardo; Clemente, Alberto; Marras, Gavino; Kusch, Annette; Marzullo, Paolo

2017-01-12

Single-photon emission computed-tomography (SPECT) allows the quantification of LV eccentricity index (EI), a measure of cardiac remodeling. We sought to evaluate the feasibility of EI measurement with SPECT myocardial perfusion imaging and its interactions with relevant LV functional and structural parameters. Four-hundred and fifty-six patients underwent myocardial perfusion imaging on a Cadmium-Zinc-Telluride (CZT) camera. The summed rest, stress, and difference scores were calculated. From rest images, the LV end-diastolic (EDV) and end-systolic volumes, ejection fraction (EF), and peak filling rate (PFR) were calculated. In every patient, the EI, ranging from 0 (sphere) to 1 (line), was computed using a dedicated software (QGS/QPS; Cedars-Sinai Medical Center). Three-hundred and thirty-eight/456 (74%) patients showed a normal EF (>50%), while 26% had LV systolic dysfunction. The EI was computed from CZT images with excellent reproducibility (interclass correlation coefficient: 0.99, 95% CI 0.98-0.99). More impaired EI values correlated with the presence of a more abnormal LV perfusion (P < .001), function (EF and PFR, P < .001), and structure (EDV, P < .001). On multivariate analysis, higher EDV (P < .001) and depressed EF (P = .014) values were independent predictors of abnormal EI. The evaluation of LV eccentricity is feasible on gated CZT images. Abnormal EI associates with significant cardiac structural and functional abnormalities.

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

PubMed

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.

Bayesian Treatment of Uncertainty in Environmental Modeling: Optimization, Sampling and Data Assimilation Using the DREAM Software Package

NASA Astrophysics Data System (ADS)

Vrugt, J. A.

2012-12-01

In the past decade much progress has been made in the treatment of uncertainty in earth systems modeling. Whereas initial approaches has focused mostly on quantification of parameter and predictive uncertainty, recent methods attempt to disentangle the effects of parameter, forcing (input) data, model structural and calibration data errors. In this talk I will highlight some of our recent work involving theory, concepts and applications of Bayesian parameter and/or state estimation. In particular, new methods for sequential Monte Carlo (SMC) and Markov Chain Monte Carlo (MCMC) simulation will be presented with emphasis on massively parallel distributed computing and quantification of model structural errors. The theoretical and numerical developments will be illustrated using model-data synthesis problems in hydrology, hydrogeology and geophysics.

Be discs in coplanar circular binaries: Phase-locked variations of emission lines

NASA Astrophysics Data System (ADS)

Panoglou, Despina; Faes, Daniel M.; Carciofi, Alex C.; Okazaki, Atsuo T.; Baade, Dietrich; Rivinius, Thomas; Borges Fernandes, Marcelo

2018-01-01

In this paper, we present the first results of radiative transfer calculations on decretion discs of binary Be stars. A smoothed particle hydrodynamics code computes the structure of Be discs in coplanar circular binary systems for a range of orbital and disc parameters. The resulting disc configuration consists of two spiral arms, and this can be given as input into a Monte Carlo code, which calculates the radiative transfer along the line of sight for various observational coordinates. Making use of the property of steady disc structure in coplanar circular binaries, observables are computed as functions of the orbital phase. Some orbital-phase series of line profiles are given for selected parameter sets under various viewing angles, to allow comparison with observations. Flat-topped profiles with and without superimposed multiple structures are reproduced, showing, for example, that triple-peaked profiles do not have to be necessarily associated with warped discs and misaligned binaries. It is demonstrated that binary tidal effects give rise to phase-locked variability of the violet-to-red (V/R) ratio of hydrogen emission lines. The V/R ratio exhibits two maxima per cycle; in certain cases those maxima are equal, leading to a clear new V/R cycle every half orbital period. This study opens a way to identifying binaries and to constraining the parameters of binary systems that exhibit phase-locked variations induced by tidal interaction with a companion star.

An Improved Lattice Boltzmann Model for Non-Newtonian Flows with Applications to Solid-Fluid Interactions in External Flows

NASA Astrophysics Data System (ADS)

Adam, Saad; Premnath, Kannan

2016-11-01

Fluid mechanics of non-Newtonian fluids, which arise in numerous settings, are characterized by non-linear constitutive models that pose certain unique challenges for computational methods. Here, we consider the lattice Boltzmann method (LBM), which offers some computational advantages due to its kinetic basis and its simpler stream-and-collide procedure enabling efficient simulations. However, further improvements are necessary to improve its numerical stability and accuracy for computations involving broader parameter ranges. Hence, in this study, we extend the cascaded LBM formulation by modifying its moment equilibria and relaxation parameters to handle a variety of non-Newtonian constitutive equations, including power-law and Bingham fluids, with improved stability. In addition, we include corrections to the moment equilibria to obtain an inertial frame invariant scheme without cubic-velocity defects. After preforming its validation study for various benchmark flows, we study the physics of non-Newtonian flow over pairs of circular and square cylinders in a tandem arrangement, especially the wake structure interactions and their effects on resulting forces in each cylinder, and elucidate the effect of the various characteristic parameters.

The structure of the plasma sheet-lobe boundary in the Earth's magnetotail

NASA Technical Reports Server (NTRS)

Orsini, S.; Candidi, M.; Formisano, V.; Balsiger, H.; Ghielmetti, A.; Ogilvie, K. W.

1982-01-01

The structure of the magnetotail plasma sheet-plasma lobe boundary was studied by observing the properties of tailward flowing O+ ion beams, detected by the ISEE 2 plasma experiment inside the boundary during three time periods. The computed value of the north-south electric field component as well as the O+ parameters are shown to change at the boundary. The results are related to other observations made in this region. The O+ parameters and the Ez component behavior are shown to be consistent with that expected from the topology of the electric field lines in the tail as mapped from the ionosphere.

Basic research on design analysis methods for rotorcraft vibrations

NASA Technical Reports Server (NTRS)

Hanagud, S.

1991-01-01

The objective of the present work was to develop a method for identifying physically plausible finite element system models of airframe structures from test data. The assumed models were based on linear elastic behavior with general (nonproportional) damping. Physical plausibility of the identified system matrices was insured by restricting the identification process to designated physical parameters only and not simply to the elements of the system matrices themselves. For example, in a large finite element model the identified parameters might be restricted to the moduli for each of the different materials used in the structure. In the case of damping, a restricted set of damping values might be assigned to finite elements based on the material type and on the fabrication processes used. In this case, different damping values might be associated with riveted, bolted and bonded elements. The method itself is developed first, and several approaches are outlined for computing the identified parameter values. The method is applied first to a simple structure for which the 'measured' response is actually synthesized from an assumed model. Both stiffness and damping parameter values are accurately identified. The true test, however, is the application to a full-scale airframe structure. In this case, a NASTRAN model and actual measured modal parameters formed the basis for the identification of a restricted set of physically plausible stiffness and damping parameters.

Density functional calculations of the Mössbauer parameters in hexagonal ferrite SrFe12O19

NASA Astrophysics Data System (ADS)

Ikeno, Hidekazu

2018-03-01

Mössbauer parameters in a magnetoplumbite-type hexagonal ferrite, SrFe12O19, are computed using the all-electron band structure calculation based on the density functional theory. The theoretical isomer shift and quadrupole splitting are consistent with experimentally obtained values. The absolute values of hyperfine splitting parameters are found to be underestimated, but the relative scale can be reproduced. The present results validate the site-dependence of Mössbauer parameters obtained by analyzing experimental spectra of hexagonal ferrites. The results also show the usefulness of theoretical calculations for increasing the reliability of interpretation of the Mössbauer spectra.

Real-space processing of helical filaments in SPARX

PubMed Central

Behrmann, Elmar; Tao, Guozhi; Stokes, David L.; Egelman, Edward H.; Raunser, Stefan; Penczek, Pawel A.

2012-01-01

We present a major revision of the iterative helical real-space refinement (IHRSR) procedure and its implementation in the SPARX single particle image processing environment. We built on over a decade of experience with IHRSR helical structure determination and we took advantage of the flexible SPARX infrastructure to arrive at an implementation that offers ease of use, flexibility in designing helical structure determination strategy, and high computational efficiency. We introduced the 3D projection matching code which now is able to work with non-cubic volumes, the geometry better suited for long helical filaments, we enhanced procedures for establishing helical symmetry parameters, and we parallelized the code using distributed memory paradigm. Additional feature includes a graphical user interface that facilitates entering and editing of parameters controlling the structure determination strategy of the program. In addition, we present a novel approach to detect and evaluate structural heterogeneity due to conformer mixtures that takes advantage of helical structure redundancy. PMID:22248449

MrGrid: A Portable Grid Based Molecular Replacement Pipeline

PubMed Central

Reboul, Cyril F.; Androulakis, Steve G.; Phan, Jennifer M. N.; Whisstock, James C.; Goscinski, Wojtek J.; Abramson, David; Buckle, Ashley M.

2010-01-01

Background The crystallographic determination of protein structures can be computationally demanding and for difficult cases can benefit from user-friendly interfaces to high-performance computing resources. Molecular replacement (MR) is a popular protein crystallographic technique that exploits the structural similarity between proteins that share some sequence similarity. But the need to trial permutations of search models, space group symmetries and other parameters makes MR time- and labour-intensive. However, MR calculations are embarrassingly parallel and thus ideally suited to distributed computing. In order to address this problem we have developed MrGrid, web-based software that allows multiple MR calculations to be executed across a grid of networked computers, allowing high-throughput MR. Methodology/Principal Findings MrGrid is a portable web based application written in Java/JSP and Ruby, and taking advantage of Apple Xgrid technology. Designed to interface with a user defined Xgrid resource the package manages the distribution of multiple MR runs to the available nodes on the Xgrid. We evaluated MrGrid using 10 different protein test cases on a network of 13 computers, and achieved an average speed up factor of 5.69. Conclusions MrGrid enables the user to retrieve and manage the results of tens to hundreds of MR calculations quickly and via a single web interface, as well as broadening the range of strategies that can be attempted. This high-throughput approach allows parameter sweeps to be performed in parallel, improving the chances of MR success. PMID:20386612

Synthesis, spectroscopic investigation and computational study of 3-(1-(((methoxycarbonyl)oxy)imino)ethyl)-2H-chromen-2-one

NASA Astrophysics Data System (ADS)

Gokula Krishnan, K.; Sivakumar, R.; Thanikachalam, V.; Saleem, H.; Arockia doss, M.

2015-06-01

The molecular structure and vibrational modes of 3-acetylcoumarin oxime carbonate (abbreviated as 3-ACOC) have been investigated by FT-IR, FT-Raman, NMR spectra and also by computational methods using HF and B3LYP with 6-311++G(d,p) basis set. The optimized geometric parameters (bond lengths, bond angles and dihedral angles) were in good agreement with the corresponding experimental values of 3-ACOC. The calculated vibrational frequencies of normal modes from DFT method matched well with the experimental values. The complete assignments were made on the basis of the total energy distribution (TED) of the vibrational modes. NMR (1H and 13C) chemical shifts were calculated by GIAO method and the results were compared with the experimental values. The other parameters like dipole moment, polarizability, first order hyperpolarizability, zero-point vibrational energy, EHOMO, ELUMO, heat capacity and entropy have also been computed.

Uncertainty Quantification in Aeroelasticity

NASA Astrophysics Data System (ADS)

Beran, Philip; Stanford, Bret; Schrock, Christopher

2017-01-01

Physical interactions between a fluid and structure, potentially manifested as self-sustained or divergent oscillations, can be sensitive to many parameters whose values are uncertain. Of interest here are aircraft aeroelastic interactions, which must be accounted for in aircraft certification and design. Deterministic prediction of these aeroelastic behaviors can be difficult owing to physical and computational complexity. New challenges are introduced when physical parameters and elements of the modeling process are uncertain. By viewing aeroelasticity through a nondeterministic prism, where key quantities are assumed stochastic, one may gain insights into how to reduce system uncertainty, increase system robustness, and maintain aeroelastic safety. This article reviews uncertainty quantification in aeroelasticity using traditional analytical techniques not reliant on computational fluid dynamics; compares and contrasts this work with emerging methods based on computational fluid dynamics, which target richer physics; and reviews the state of the art in aeroelastic optimization under uncertainty. Barriers to continued progress, for example, the so-called curse of dimensionality, are discussed.

Bending of an Infinite beam on a base with two parameters in the absence of a part of the base

NASA Astrophysics Data System (ADS)

Aleksandrovskiy, Maxim; Zaharova, Lidiya

2018-03-01

Currently, in connection with the rapid development of high-rise construction and the improvement of joint operation of high-rise structures and bases models, the questions connected with the use of various calculation methods become topical. The rigor of analytical methods is capable of more detailed and accurate characterization of the structures behavior, which will affect the reliability of objects and can lead to a reduction in their cost. In the article, a model with two parameters is used as a computational model of the base that can effectively take into account the distributive properties of the base by varying the coefficient reflecting the shift parameter. The paper constructs the effective analytical solution of the problem of a beam of infinite length interacting with a two-parameter voided base. Using the Fourier integral equations, the original differential equation is reduced to the Fredholm integral equation of the second kind with a degenerate kernel, and all the integrals are solved analytically and explicitly, which leads to an increase in the accuracy of the computations in comparison with the approximate methods. The paper consider the solution of the problem of a beam loaded with a concentrated force applied at the point of origin with a fixed value of the length of the dip section. The paper gives the analysis of the obtained results values for various parameters of coefficient taking into account cohesion of the ground.

Accuracy in planar cutting of bones: an ISO-based evaluation.

PubMed

Cartiaux, Olivier; Paul, Laurent; Docquier, Pierre-Louis; Francq, Bernard G; Raucent, Benoît; Dombre, Etienne; Banse, Xavier

2009-03-01

Computer- and robot-assisted technologies are capable of improving the accuracy of planar cutting in orthopaedic surgery. This study is a first step toward formulating and validating a new evaluation methodology for planar bone cutting, based on the standards from the International Organization for Standardization. Our experimental test bed consisted of a purely geometrical model of the cutting process around a simulated bone. Cuts were performed at three levels of surgical assistance: unassisted, computer-assisted and robot-assisted. We measured three parameters of the standard ISO1101:2004: flatness, parallelism and location of the cut plane. The location was the most relevant parameter for assessing cutting errors. The three levels of assistance were easily distinguished using the location parameter. Our ISO methodology employs the location to obtain all information about translational and rotational cutting errors. Location may be used on any osseous structure to compare the performance of existing assistance technologies.

Stability assessment of structures under earthquake hazard through GRID technology

NASA Astrophysics Data System (ADS)

Prieto Castrillo, F.; Boton Fernandez, M.

2009-04-01

This work presents a GRID framework to estimate the vulnerability of structures under earthquake hazard. The tool has been designed to cover the needs of a typical earthquake engineering stability analysis; preparation of input data (pre-processing), response computation and stability analysis (post-processing). In order to validate the application over GRID, a simplified model of structure under artificially generated earthquake records has been implemented. To achieve this goal, the proposed scheme exploits the GRID technology and its main advantages (parallel intensive computing, huge storage capacity and collaboration analysis among institutions) through intensive interaction among the GRID elements (Computing Element, Storage Element, LHC File Catalogue, federated database etc.) The dynamical model is described by a set of ordinary differential equations (ODE's) and by a set of parameters. Both elements, along with the integration engine, are encapsulated into Java classes. With this high level design, subsequent improvements/changes of the model can be addressed with little effort. In the procedure, an earthquake record database is prepared and stored (pre-processing) in the GRID Storage Element (SE). The Metadata of these records is also stored in the GRID federated database. This Metadata contains both relevant information about the earthquake (as it is usual in a seismic repository) and also the Logical File Name (LFN) of the record for its later retrieval. Then, from the available set of accelerograms in the SE, the user can specify a range of earthquake parameters to carry out a dynamic analysis. This way, a GRID job is created for each selected accelerogram in the database. At the GRID Computing Element (CE), displacements are then obtained by numerical integration of the ODE's over time. The resulting response for that configuration is stored in the GRID Storage Element (SE) and the maximum structure displacement is computed. Then, the corresponding Metadata containing the response LFN, earthquake magnitude and maximum structure displacement is also stored. Finally, the displacements are post-processed through a statistically-based algorithm from the available Metadata to obtain the probability of collapse of the structure for different earthquake magnitudes. From this study, it is possible to build a vulnerability report for the structure type and seismic data. The proposed methodology can be combined with the on-going initiatives to build a European earthquake record database. In this context, Grid enables collaboration analysis over shared seismic data and results among different institutions.

Hydrodynamic Modeling and Its Application in AUC.

PubMed

Rocco, Mattia; Byron, Olwyn

2015-01-01

The hydrodynamic parameters measured in an AUC experiment, s(20,w) and D(t)(20,w)(0), can be used to gain information on the solution structure of (bio)macromolecules and their assemblies. This entails comparing the measured parameters with those that can be computed from usually "dry" structures by "hydrodynamic modeling." In this chapter, we will first briefly put hydrodynamic modeling in perspective and present the basic physics behind it as implemented in the most commonly used methods. The important "hydration" issue is also touched upon, and the distinction between rigid bodies versus those for which flexibility must be considered in the modeling process is then made. The available hydrodynamic modeling/computation programs, HYDROPRO, BEST, SoMo, AtoB, and Zeno, the latter four all implemented within the US-SOMO suite, are described and their performance evaluated. Finally, some literature examples are presented to illustrate the potential applications of hydrodynamics in the expanding field of multiresolution modeling. © 2015 Elsevier Inc. All rights reserved.

A methodology for formulating a minimal uncertainty model for robust control system design and analysis

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.; Chang, B.-C.; Fischl, Robert

1989-01-01

In the design and analysis of robust control systems for uncertain plants, the technique of formulating what is termed an M-delta model has become widely accepted and applied in the robust control literature. The M represents the transfer function matrix M(s) of the nominal system, and delta represents an uncertainty matrix acting on M(s). The uncertainty can arise from various sources, such as structured uncertainty from parameter variations or multiple unstructured uncertainties from unmodeled dynamics and other neglected phenomena. In general, delta is a block diagonal matrix, and for real parameter variations the diagonal elements are real. As stated in the literature, this structure can always be formed for any linear interconnection of inputs, outputs, transfer functions, parameter variations, and perturbations. However, very little of the literature addresses methods for obtaining this structure, and none of this literature addresses a general methodology for obtaining a minimal M-delta model for a wide class of uncertainty. Since have a delta matrix of minimum order would improve the efficiency of structured singular value (or multivariable stability margin) computations, a method of obtaining a minimal M-delta model would be useful. A generalized method of obtaining a minimal M-delta structure for systems with real parameter variations is given.

Model-based recovery of histological parameters from multispectral images of the colon

NASA Astrophysics Data System (ADS)

Hidovic-Rowe, Dzena; Claridge, Ela

2005-04-01

Colon cancer alters the macroarchitecture of the colon tissue. Common changes include angiogenesis and the distortion of the tissue collagen matrix. Such changes affect the colon colouration. This paper presents the principles of a novel optical imaging method capable of extracting parameters depicting histological quantities of the colon. The method is based on a computational, physics-based model of light interaction with tissue. The colon structure is represented by three layers: mucosa, submucosa and muscle layer. Optical properties of the layers are defined by molar concentration and absorption coefficients of haemoglobins; the size and density of collagen fibres; the thickness of the layer and the refractive indexes of collagen and the medium. Using the entire histologically plausible ranges for these parameters, a cross-reference is created computationally between the histological quantities and the associated spectra. The output of the model was compared to experimental data acquired in vivo from 57 histologically confirmed normal and abnormal tissue samples and histological parameters were extracted. The model produced spectra which match well the measured data, with the corresponding spectral parameters being well within histologically plausible ranges. Parameters extracted for the abnormal spectra showed the increase in blood volume fraction and changes in collagen pattern characteristic of the colon cancer. The spectra extracted from multi-spectral images of ex-vivo colon including adenocarcinoma show the characteristic features associated with normal and abnormal colon tissue. These findings suggest that it should be possible to compute histological quantities for the colon from the multi-spectral images.

DFTB Parameters for the Periodic Table, Part 2: Energies and Energy Gradients from Hydrogen to Calcium.

PubMed

Oliveira, Augusto F; Philipsen, Pier; Heine, Thomas

2015-11-10

In the first part of this series, we presented a parametrization strategy to obtain high-quality electronic band structures on the basis of density-functional-based tight-binding (DFTB) calculations and published a parameter set called QUASINANO2013.1. Here, we extend our parametrization effort to include the remaining terms that are needed to compute the total energy and its gradient, commonly referred to as repulsive potential. Instead of parametrizing these terms as a two-body potential, we calculate them explicitly from the DFTB analogues of the Kohn-Sham total energy expression. This strategy requires only two further numerical parameters per element. Thus, the atomic configuration and four real numbers per element are sufficient to define the DFTB model at this level of parametrization. The QUASINANO2015 parameter set allows the calculation of energy, structure, and electronic structure of all systems composed of elements ranging from H to Ca. Extensive benchmarks show that the overall accuracy of QUASINANO2015 is comparable to that of well-established methods, including PM7 and hand-tuned DFTB parameter sets, while coverage of a much larger range of chemical systems is available.

PSO (Particle Swarm Optimization) for Interpretation of Magnetic Anomalies Caused by Simple Geometrical Structures

NASA Astrophysics Data System (ADS)

Essa, Khalid S.; Elhussein, Mahmoud

2018-04-01

A new efficient approach to estimate parameters that controlled the source dimensions from magnetic anomaly profile data in light of PSO algorithm (particle swarm optimization) has been presented. The PSO algorithm has been connected in interpreting the magnetic anomaly profiles data onto a new formula for isolated sources embedded in the subsurface. The model parameters deciphered here are the depth of the body, the amplitude coefficient, the angle of effective magnetization, the shape factor and the horizontal coordinates of the source. The model parameters evaluated by the present technique, generally the depth of the covered structures were observed to be in astounding concurrence with the real parameters. The root mean square (RMS) error is considered as a criterion in estimating the misfit between the observed and computed anomalies. Inversion of noise-free synthetic data, noisy synthetic data which contains different levels of random noise (5, 10, 15 and 20%) as well as multiple structures and in additional two real-field data from USA and Egypt exhibits the viability of the approach. Thus, the final results of the different parameters are matched with those given in the published literature and from geologic results.

A radiosity model for heterogeneous canopies in remote sensing

NASA Astrophysics Data System (ADS)

GarcíA-Haro, F. J.; Gilabert, M. A.; Meliá, J.

1999-05-01

A radiosity model has been developed to compute bidirectional reflectance from a heterogeneous canopy approximated by an arbitrary configuration of plants or clumps of vegetation, placed on the ground surface in a prescribed manner. Plants are treated as porous cylinders formed by aggregations of layers of leaves. This model explicitly computes solar radiation leaving each individual surface, taking into account multiple scattering processes between leaves and soil, and occlusion of neighboring plants. Canopy structural parameters adopted in this study have served to simplify the computation of the geometric factors of the radiosity equation, and thus this model has enabled us to simulate multispectral images of vegetation scenes. Simulated images have shown to be valuable approximations of satellite data, and then a sensitivity analysis to the dominant parameters of discontinuous canopies (plant density, leaf area index (LAI), leaf angle distribution (LAD), plant dimensions, soil optical properties, etc.) and scene (sun/ view angles and atmospheric conditions) has been undertaken. The radiosity model has let us gain a deep insight into the radiative regime inside the canopy, showing it to be governed by occlusion of incoming irradiance, multiple scattering of radiation between canopy elements and interception of upward radiance by leaves. Results have indicated that unlike leaf distribution, other structural parameters such as LAI, LAD, and plant dimensions have a strong influence on canopy reflectance. In addition, concepts have been developed that are useful to understand the reflectance behavior of the canopy, such as an effective LAI related to leaf inclination.

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

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

Marzouk, Youssef

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesianmore » inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.« less

Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign

PubMed Central

2007-01-01

Background Joint alignment and secondary structure prediction of two RNA sequences can significantly improve the accuracy of the structural predictions. Methods addressing this problem, however, are forced to employ constraints that reduce computation by restricting the alignments and/or structures (i.e. folds) that are permissible. In this paper, a new methodology is presented for the purpose of establishing alignment constraints based on nucleotide alignment and insertion posterior probabilities. Using a hidden Markov model, posterior probabilities of alignment and insertion are computed for all possible pairings of nucleotide positions from the two sequences. These alignment and insertion posterior probabilities are additively combined to obtain probabilities of co-incidence for nucleotide position pairs. A suitable alignment constraint is obtained by thresholding the co-incidence probabilities. The constraint is integrated with Dynalign, a free energy minimization algorithm for joint alignment and secondary structure prediction. The resulting method is benchmarked against the previous version of Dynalign and against other programs for pairwise RNA structure prediction. Results The proposed technique eliminates manual parameter selection in Dynalign and provides significant computational time savings in comparison to prior constraints in Dynalign while simultaneously providing a small improvement in the structural prediction accuracy. Savings are also realized in memory. In experiments over a 5S RNA dataset with average sequence length of approximately 120 nucleotides, the method reduces computation by a factor of 2. The method performs favorably in comparison to other programs for pairwise RNA structure prediction: yielding better accuracy, on average, and requiring significantly lesser computational resources. Conclusion Probabilistic analysis can be utilized in order to automate the determination of alignment constraints for pairwise RNA structure prediction methods in a principled fashion. These constraints can reduce the computational and memory requirements of these methods while maintaining or improving their accuracy of structural prediction. This extends the practical reach of these methods to longer length sequences. The revised Dynalign code is freely available for download. PMID:17445273

SU-F-T-227: A Comprehensive Patient Specific, Structure Specific, Pre-Treatment 3D QA Protocol for IMRT, SBRT and VMAT - Clinical Experience

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

Gueorguiev, G; Cotter, C; Young, M

2016-06-15

Purpose: To present a 3D QA method and clinical results for 550 patients. Methods: Five hundred and fifty patient treatment deliveries (400 IMRT, 75 SBRT and 75 VMAT) from various treatment sites, planned on Raystation treatment planning system (TPS), were measured on three beam-matched Elekta linear accelerators using IBA’s COMPASS system. The difference between TPS computed and delivered dose was evaluated in 3D by applying three statistical parameters to each structure of interest: absolute average dose difference (AADD, 6% allowed difference), absolute dose difference greater than 6% (ADD6, 4% structure volume allowed to fail) and 3D gamma test (3%/3mm DTA,more » 4% structure volume allowed to fail). If the allowed value was not met for a given structure, manual review was performed. The review consisted of overlaying dose difference or gamma results with the patient CT, scrolling through the slices. For QA to pass, areas of high dose difference or gamma must be small and not on consecutive slices. For AADD to manually pass QA, the average dose difference in cGy must be less than 50cGy. The QA protocol also includes DVH analysis based on QUANTEC and TG-101 recommended dose constraints. Results: Figures 1–3 show the results for the three parameters per treatment modality. Manual review was performed on 67 deliveries (27 IMRT, 22 SBRT and 18 VMAT), for which all passed QA. Results show that statistical parameter AADD may be overly sensitive for structures receiving low dose, especially for the SBRT deliveries (Fig.1). The TPS computed and measured DVH values were in excellent agreement and with minimum difference. Conclusion: Applying DVH analysis and different statistical parameters to any structure of interest, as part of the 3D QA protocol, provides a comprehensive treatment plan evaluation. Author G. Gueorguiev discloses receiving travel and research funding from IBA for unrelated to this project work. Author B. Crawford discloses receiving travel funding from IBA for unrelated to this project work.« less

Prototyping of Dental Structures Using Laser Milling

NASA Astrophysics Data System (ADS)

Andreev, A. O.; Kosenko, M. S.; Petrovskiy, V. N.; Mironov, V. D.

2016-02-01

The results of experimental studies of the effect of an ytterbium fiber laser radiation parameters on processing efficiency and quality of ZrO2 ceramics widely used in stomatology are presented. Laser operating conditions with optimum characteristics for obtaining high quality final surfaces and rapid material removal of dental structures are determined. The ability of forming thin-walled ceramic structures by laser milling technology (a minimum wall thickness of 50 μm) is demonstrated. The examples of three-dimensional dental structures created in computer 3D-models of human teeth using laser milling are shown.

Emergent Intelligent Behavior through Integrated Investigation of Embodied Natural Language, Reasoning, Learning, Computer Vision, and Robotic Manipulation

DTIC Science & Technology

2011-10-11

developed a method for determining the structure (component logs and their 3D place- ment) of a LINCOLN LOG assembly from a single image from an uncalibrated...small a class of components. Moreover, we focus on determining the precise pose and structure of an assembly, including the 3D pose of each...medial axes are parallel to the work surface. Thus valid structures Fig. 1. The 3D geometric shape parameters of LINCOLN LOGS. have logs on

Planar doped barrier devices for subharmonic mixers

NASA Technical Reports Server (NTRS)

Lee, T. H.; East, J. R.; Haddad, G. I.

1991-01-01

An overview is given of planar doped barrier (PDB) devices for subharmonic mixer applications. A simplified description is given of PDB characteristics along with a more complete numerical analysis of the current versus voltage characteristics of typical structures. The analysis points out the tradeoffs between the device structure and the resulting characteristics that are important for mixer performance. Preliminary low-frequency characterization results are given for the device structures, and a computer analysis of subharmonic mixer parameters and performance is presented.

The formation of an ion beam in a vacuum neutron tube

NASA Astrophysics Data System (ADS)

Agafonov, A. V.; Tarakanov, V. P.

2014-09-01

The formation of a deuteron beam in a diode with a plasma emitter that is integrated into the structure of a vacuum neutron tube is considered. Computations are carried out for plasma with given time dependences of parameters (density, relative concentration, and expansion velocity) at the inlet to an accelerating gap. It is shown that it is possible to increase the ion-beam current possible by sectioning the diode at the given external parameters.

Macroscopic aspects of interfacial reactions

NASA Technical Reports Server (NTRS)

Heckel, R. W.

1976-01-01

The extent of interdiffusion and formation of new phases is determined by the constitution diagram of the alloy system, the interdiffusion coefficients of the phases present, and the thermal conditions (temperature and time) associated with the bonding process and/or subsequent use of the bonded structure. In many instance, the kinetics of interdiffusion and phase formation can be predicted from known parameters using numerical methods and computer techniques. Predictions are compared with experimentally determined parameters for a variety of metallurgical alloy systems.

Coupling MD Simulations and X-ray Absorption Spectroscopy to Study Ions in Solution

NASA Astrophysics Data System (ADS)

Marcos, E. Sánchez; Beret, E. C.; Martínez, J. M.; Pappalardo, R. R.; Ayala, R.; Muñoz-Páez, A.

2007-12-01

The structure of ionic solutions is a key-point in understanding physicochemical properties of electrolyte solutions. Among the reduced number of experimental techniques which can supply direct information on the ion environment, X-ray Absorption techniques (XAS) have gained importance during the last decades although they are not free of difficulties associated to the data analysis leading to provide reliable structures. Computer simulations of ions in solution is a theoretical alternative to provide information on the solvation structure. Thus, the use of computational chemistry can increase the understanding of these systems although an accurate description of ionic solvation phenomena represents nowadays a significant challenge to theoretical chemistry. We present: (a) the assignment of features in the XANES spectrum to well defined structural motif in the ion environment, (b) MD-based evaluation of EXAFS parameters used in the fitting procedure to make easier the structural resolution, and (c) the use of the agreement between experimental and simulated XANES spectra to help in the choice of a given intermolecular potential for Computer Simulations. Chemical problems examined are: (a) the identification of the second hydration shell in dilute aqueous solutions of highly-charged cations, such as Cr3+, Rh3+, Ir3+, (b) the invisibility by XAS of certain structures characterized by Computer Simulations but exhibiting high dynamical behavior and (c) the solvation of Br- in acetonitrile.

Coupling MD Simulations and X-ray Absorption Spectroscopy to Study Ions in Solution

NASA Astrophysics Data System (ADS)

Marcos, E. Sánchez; Beret, E. C.; Martínez, J. M.; Pappalardo, R. R.; Ayala, R.; Muñoz-Páez, A.

2007-11-01

The structure of ionic solutions is a key-point in understanding physicochemical properties of electrolyte solutions. Among the reduced number of experimental techniques which can supply direct information on the ion environment, X-ray Absorption techniques (XAS) have gained importance during the last decades although they are not free of difficulties associated to the data analysis leading to provide reliable structures. Computer simulations of ions in solution is a theoretical alternative to provide information on the solvation structure. Thus, the use of computational chemistry can increase the understanding of these systems although an accurate description of ionic solvation phenomena represents nowadays a significant challenge to theoretical chemistry. We present: (a) the assignment of features in the XANES spectrum to well defined structural motif in the ion environment, (b) MD-based evaluation of EXAFS parameters used in the fitting procedure to make easier the structural resolution, and (c) the use of the agreement between experimental and simulated XANES spectra to help in the choice of a given intermolecular potential for Computer Simulations. Chemical problems examined are: (a) the identification of the second hydration shell in dilute aqueous solutions of highly-charged cations, such as Cr3+, Rh3+, Ir3+, (b) the invisibility by XAS of certain structures characterized by Computer Simulations but exhibiting high dynamical behavior and (c) the solvation of Br- in acetonitrile.

Combined structures-controls optimization of lattice trusses

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1991-01-01

The role that distributed parameter model can play in CSI is demonstrated, in particular in combined structures controls optimization problems of importance in preliminary design. Closed form solutions can be obtained for performance criteria such as rms attitude error, making possible analytical solutions of the optimization problem. This is in contrast to the need for numerical computer solution involving the inversion of large matrices in traditional finite element model (FEM) use. Another advantage of the analytic solution is that it can provide much needed insight into phenomena that can otherwise be obscured or difficult to discern from numerical computer results. As a compromise in level of complexity between a toy lab model and a real space structure, the lattice truss used in the EPS (Earth Pointing Satellite) was chosen. The optimization problem chosen is a generic one: of minimizing the structure mass subject to a specified stability margin and to a specified upper bond on the rms attitude error, using a co-located controller and sensors. Standard FEM treating each bar as a truss element is used, while the continuum model is anisotropic Timoshenko beam model. Performance criteria are derived for each model, except that for the distributed parameter model, explicit closed form solutions was obtained. Numerical results obtained by the two model show complete agreement.

A multiplicative regularization for force reconstruction

NASA Astrophysics Data System (ADS)

Aucejo, M.; De Smet, O.

2017-02-01

Additive regularizations, such as Tikhonov-like approaches, are certainly the most popular methods for reconstructing forces acting on a structure. These approaches require, however, the knowledge of a regularization parameter, that can be numerically computed using specific procedures. Unfortunately, these procedures are generally computationally intensive. For this particular reason, it could be of primary interest to propose a method able to proceed without defining any regularization parameter beforehand. In this paper, a multiplicative regularization is introduced for this purpose. By construction, the regularized solution has to be calculated in an iterative manner. In doing so, the amount of regularization is automatically adjusted throughout the resolution process. Validations using synthetic and experimental data highlight the ability of the proposed approach in providing consistent reconstructions.

Performance dependence of hybrid x-ray computed tomography/fluorescence molecular tomography on the optical forward problem.

PubMed

Hyde, Damon; Schulz, Ralf; Brooks, Dana; Miller, Eric; Ntziachristos, Vasilis

2009-04-01

Hybrid imaging systems combining x-ray computed tomography (CT) and fluorescence tomography can improve fluorescence imaging performance by incorporating anatomical x-ray CT information into the optical inversion problem. While the use of image priors has been investigated in the past, little is known about the optimal use of forward photon propagation models in hybrid optical systems. In this paper, we explore the impact on reconstruction accuracy of the use of propagation models of varying complexity, specifically in the context of these hybrid imaging systems where significant structural information is known a priori. Our results demonstrate that the use of generically known parameters provides near optimal performance, even when parameter mismatch remains.

Computational investigations of low-emission burner facilities for char gas burning in a power boiler

NASA Astrophysics Data System (ADS)

Roslyakov, P. V.; Morozov, I. V.; Zaychenko, M. N.; Sidorkin, V. T.

2016-04-01

Various variants for the structure of low-emission burner facilities, which are meant for char gas burning in an operating TP-101 boiler of the Estonia power plant, are considered. The planned increase in volumes of shale reprocessing and, correspondingly, a rise in char gas volumes cause the necessity in their cocombustion. In this connection, there was a need to develop a burner facility with a given capacity, which yields effective char gas burning with the fulfillment of reliability and environmental requirements. For this purpose, the burner structure base was based on the staging burning of fuel with the gas recirculation. As a result of the preliminary analysis of possible structure variants, three types of early well-operated burner facilities were chosen: vortex burner with the supply of recirculation gases into the secondary air, vortex burner with the baffle supply of recirculation gases between flows of the primary and secondary air, and burner facility with the vortex pilot burner. Optimum structural characteristics and operation parameters were determined using numerical experiments. These experiments using ANSYS CFX bundled software of computational hydrodynamics were carried out with simulation of mixing, ignition, and burning of char gas. Numerical experiments determined the structural and operation parameters, which gave effective char gas burning and corresponded to required environmental standard on nitrogen oxide emission, for every type of the burner facility. The burner facility for char gas burning with the pilot diffusion burner in the central part was developed and made subject to computation results. Preliminary verification nature tests on the TP-101 boiler showed that the actual content of nitrogen oxides in burner flames of char gas did not exceed a claimed concentration of 150 ppm (200 mg/m3).

PREDICTION OF THE VAPOR PRESSURE, BOILING POINT, HEAT OF VAPORIZATION AND DIFFUSION COEFFICIENT OF ORGANIC COMPOUNDS

EPA Science Inventory

The prototype computer program SPARC has been under development for several years to estimate physical properties and chemical reactivity parameters of organic compounds strictly from molecular structure. SPARC solute-solute physical process models have been developed and tested...

Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks

NASA Astrophysics Data System (ADS)

Zhu, Shijia; Wang, Yadong

2015-12-01

Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is ‘stationarity’, and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings.

HARMONY: a server for the assessment of protein structures

PubMed Central

Pugalenthi, G.; Shameer, K.; Srinivasan, N.; Sowdhamini, R.

2006-01-01

Protein structure validation is an important step in computational modeling and structure determination. Stereochemical assessment of protein structures examine internal parameters such as bond lengths and Ramachandran (φ,ψ) angles. Gross structure prediction methods such as inverse folding procedure and structure determination especially at low resolution can sometimes give rise to models that are incorrect due to assignment of misfolds or mistracing of electron density maps. Such errors are not reflected as strain in internal parameters. HARMONY is a procedure that examines the compatibility between the sequence and the structure of a protein by assigning scores to individual residues and their amino acid exchange patterns after considering their local environments. Local environments are described by the backbone conformation, solvent accessibility and hydrogen bonding patterns. We are now providing HARMONY through a web server such that users can submit their protein structure files and, if required, the alignment of homologous sequences. Scores are mapped on the structure for subsequent examination that is useful to also recognize regions of possible local errors in protein structures. HARMONY server is located at PMID:16844999

Response surface method in geotechnical/structural analysis, phase 1

NASA Astrophysics Data System (ADS)

Wong, F. S.

1981-02-01

In the response surface approach, an approximating function is fit to a long running computer code based on a limited number of code calculations. The approximating function, called the response surface, is then used to replace the code in subsequent repetitive computations required in a statistical analysis. The procedure of the response surface development and feasibility of the method are shown using a sample problem in slop stability which is based on data from centrifuge experiments of model soil slopes and involves five random soil parameters. It is shown that a response surface can be constructed based on as few as four code calculations and that the response surface is computationally extremely efficient compared to the code calculation. Potential applications of this research include probabilistic analysis of dynamic, complex, nonlinear soil/structure systems such as slope stability, liquefaction, and nuclear reactor safety.

Intensity-based hierarchical clustering in CT-scans: application to interactive segmentation in cardiology

NASA Astrophysics Data System (ADS)

Hadida, Jonathan; Desrosiers, Christian; Duong, Luc

2011-03-01

The segmentation of anatomical structures in Computed Tomography Angiography (CTA) is a pre-operative task useful in image guided surgery. Even though very robust and precise methods have been developed to help achieving a reliable segmentation (level sets, active contours, etc), it remains very time consuming both in terms of manual interactions and in terms of computation time. The goal of this study is to present a fast method to find coarse anatomical structures in CTA with few parameters, based on hierarchical clustering. The algorithm is organized as follows: first, a fast non-parametric histogram clustering method is proposed to compute a piecewise constant mask. A second step then indexes all the space-connected regions in the piecewise constant mask. Finally, a hierarchical clustering is achieved to build a graph representing the connections between the various regions in the piecewise constant mask. This step builds up a structural knowledge about the image. Several interactive features for segmentation are presented, for instance association or disassociation of anatomical structures. A comparison with the Mean-Shift algorithm is presented.

CARES/LIFE Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Janosik, Lesley A.; Gyekenyesi, John P.

2003-01-01

This manual describes the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction (CARES/LIFE) computer program. The program calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. CARES/LIFE is an extension of the CARES (Ceramic Analysis and Reliability Evaluation of Structures) computer program. The program uses results from MSC/NASTRAN, ABAQUS, and ANSYS finite element analysis programs to evaluate component reliability due to inherent surface and/or volume type flaws. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing the power law, Paris law, or Walker law. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled by using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. The probabilistic time-dependent theories used in CARES/LIFE, along with the input and output for CARES/LIFE, are described. Example problems to demonstrate various features of the program are also included.

[The research on bidirectional reflectance computer simulation of forest canopy at pixel scale].

PubMed

Song, Jin-Ling; Wang, Jin-Di; Shuai, Yan-Min; Xiao, Zhi-Qiang

2009-08-01

Computer simulation is based on computer graphics to generate the realistic 3D structure scene of vegetation, and to simulate the canopy regime using radiosity method. In the present paper, the authors expand the computer simulation model to simulate forest canopy bidirectional reflectance at pixel scale. But usually, the trees are complex structures, which are tall and have many branches. So there is almost a need for hundreds of thousands or even millions of facets to built up the realistic structure scene for the forest It is difficult for the radiosity method to compute so many facets. In order to make the radiosity method to simulate the forest scene at pixel scale, in the authors' research, the authors proposed one idea to simplify the structure of forest crowns, and abstract the crowns to ellipsoids. And based on the optical characteristics of the tree component and the characteristics of the internal energy transmission of photon in real crown, the authors valued the optical characteristics of ellipsoid surface facets. In the computer simulation of the forest, with the idea of geometrical optics model, the gap model is considered to get the forest canopy bidirectional reflectance at pixel scale. Comparing the computer simulation results with the GOMS model, and Multi-angle Imaging SpectroRadiometer (MISR) multi-angle remote sensing data, the simulation results are in agreement with the GOMS simulation result and MISR BRF. But there are also some problems to be solved. So the authors can conclude that the study has important value for the application of multi-angle remote sensing and the inversion of vegetation canopy structure parameters.

Kinetic Monte Carlo and cellular particle dynamics simulations of multicellular systems

NASA Astrophysics Data System (ADS)

Flenner, Elijah; Janosi, Lorant; Barz, Bogdan; Neagu, Adrian; Forgacs, Gabor; Kosztin, Ioan

2012-03-01

Computer modeling of multicellular systems has been a valuable tool for interpreting and guiding in vitro experiments relevant to embryonic morphogenesis, tumor growth, angiogenesis and, lately, structure formation following the printing of cell aggregates as bioink particles. Here we formulate two computer simulation methods: (1) a kinetic Monte Carlo (KMC) and (2) a cellular particle dynamics (CPD) method, which are capable of describing and predicting the shape evolution in time of three-dimensional multicellular systems during their biomechanical relaxation. Our work is motivated by the need of developing quantitative methods for optimizing postprinting structure formation in bioprinting-assisted tissue engineering. The KMC and CPD model parameters are determined and calibrated by using an original computational-theoretical-experimental framework applied to the fusion of two spherical cell aggregates. The two methods are used to predict the (1) formation of a toroidal structure through fusion of spherical aggregates and (2) cell sorting within an aggregate formed by two types of cells with different adhesivities.

A simplified implementation of van der Waals density functionals for first-principles molecular dynamics applications

NASA Astrophysics Data System (ADS)

Wu, Jun; Gygi, François

2012-06-01

We present a simplified implementation of the non-local van der Waals correlation functional introduced by Dion et al. [Phys. Rev. Lett. 92, 246401 (2004)] and reformulated by Román-Pérez et al. [Phys. Rev. Lett. 103, 096102 (2009)]. The proposed numerical approach removes the logarithmic singularity of the kernel function. Complete expressions of the self-consistent correlation potential and of the stress tensor are given. Combined with various choices of exchange functionals, five versions of van der Waals density functionals are implemented. Applications to the computation of the interaction energy of the benzene-water complex and to the computation of the equilibrium cell parameters of the benzene crystal are presented. As an example of crystal structure calculation involving a mixture of hydrogen bonding and dispersion interactions, we compute the equilibrium structure of two polymorphs of aspirin (2-acetoxybenzoic acid, C9H8O4) in the P21/c monoclinic structure.

Hα3: an Hα imaging survey of HI selected galaxies from ALFALFA. IV. Structure of galaxies in the Local and Coma superclusters

NASA Astrophysics Data System (ADS)

Fossati, M.; Gavazzi, G.; Savorgnan, G.; Fumagalli, M.; Boselli, A.; Gutiérrez, L.; Hernández Toledo, H.; Giovanelli, R.; Haynes, M. P.

2013-05-01

Context. We present the analysis of the galaxy structural parameters from Hα3, an Hα narrow-band imaging follow-up survey of ~800 galaxies selected from the HI Arecibo Legacy Fast ALFA Survey (ALFALFA) in the Local supercluster, including the Virgo cluster, and in the Coma supercluster. Aims: Taking advantage of Hα3, which provides the complete census of the recent star-forming, HI-rich galaxies in the local universe, we aim to investigate the structural parameters of the young (<10 Myr) and the old (>1 Gyr) stellar populations. By comparing the sizes of these stellar components, we investigated the spatial scale on which galaxies are growing at the present cosmological epoch and the role of the environment in quenching the star-formation activity. Methods: We computed the concentration, asymmetry, and clumpiness (CAS) structural parameters for recently born and old stars. To quantify the sizes we computed half-light radii and a new parameter dubbed EW/r based on the half-light radius of the Hα equivalent width map. To highlight the environmental perturbation, we adopt an updated calibration of the HI-deficiency parameter (DefHI) that we use to divide the sample in unperturbed galaxies (DefHI ≤ 0.3) and perturbed galaxies (DefHI > 0.3). Results: The concentration index computed in the r band depends on the stellar mass and on the Hubble type these variables are related because most massive galaxies are bulge dominated therefore highly concentrated. Going toward later spirals and irregulars the concentration index and the mass decrease along with the bulge-to-disk ratio. Blue compact dwarfs (BCDs) are an exception because they have similar mass, but they are more concentrated than dwarf irregulars. The asymmetry and the clumpiness increase along the spiral sequence up to Sc-Sd, but they decrease going in the dwarf regime, where the light distribution is smooth and more symmetric. When measured on Hα images, the CAS parameters show no obvious correlations with Hubble type. Irrespective of whether we used the ratio between effective radii or the EW/r parameter, we found that the concentration index is the main parameter that describes the current growth of isolated galaxies but, for a fixed concentration, the stellar mass plays a second-order role. At the present epoch, massive galaxies are growing inside-out, conversely, the dwarfs are growing on the scale of their already assembled mass. Observations taken at the observatory of San Pedro Martir (Baja California, Mexico), belonging to the Mexican Observatorio Astronómico Nacional.Tables A.1 and A.2 are only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/553/A91

Experimental study of evaluation of mechanical parameters of heterogeneous porous structure

NASA Astrophysics Data System (ADS)

Gerasimov, O.; Koroleva, E.; Sachenkov, O.

2017-06-01

The paper deals with the problem of determining the mechanical macroparameters of the porous material in case of knowing the information about it’s structure. Fabric tensor and porosity was used to describe structure of the material. Experimental study presented. In research two-component liquid polyurethane plastics of cold curing Lasilcast (Lc-12) was used. Then samples was scanned on computer tomography. Resulting data was analyzed. Regular subvolume was cut out after analyses. Then mechanical tests was performed. As a result we get information about fabric tensor, porosity, Young’s modulus and Poisson ratio of the sample. In the abstract presented results for some samples. Taking into account the law of porosity variation, we considered the problem of evaluating the mechanical macro parameters depending on the nature of the porous structure. To evaluate the macroparameters, we built the dependence of the Young’s modules and Poisson ratio of the material on the rotation angle α and the pore ellipticity parameter λ. The sensitivity of the deformations to the elastic constants was also estimated.

Microgravity computing codes. User's guide

NASA Astrophysics Data System (ADS)

1982-01-01

Codes used in microgravity experiments to compute fluid parameters and to obtain data graphically are introduced. The computer programs are stored on two diskettes, compatible with the floppy disk drives of the Apple 2. Two versions of both disks are available (DOS-2 and DOS-3). The codes are written in BASIC and are structured as interactive programs. Interaction takes place through the keyboard of any Apple 2-48K standard system with single floppy disk drive. The programs are protected against wrong commands given by the operator. The programs are described step by step in the same order as the instructions displayed on the monitor. Most of these instructions are shown, with samples of computation and of graphics.

Process Integration and Optimization of ICME Carbon Fiber Composites for Vehicle Lightweighting: A Preliminary Development

DOE PAGES

Xu, Hongyi; Li, Yang; Zeng, Danielle

2017-01-02

Process integration and optimization is the key enabler of the Integrated Computational Materials Engineering (ICME) of carbon fiber composites. In this paper, automated workflows are developed for two types of composites: Sheet Molding Compounds (SMC) short fiber composites, and multi-layer unidirectional (UD) composites. For SMC, the proposed workflow integrates material processing simulation, microstructure representation volume element (RVE) models, material property prediction and structure preformation simulation to enable multiscale, multidisciplinary analysis and design. Processing parameters, microstructure parameters and vehicle subframe geometry parameters are defined as the design variables; the stiffness and weight of the structure are defined as the responses. Formore » multi-layer UD structure, this work focuses on the discussion of different design representation methods and their impacts on the optimization performance. Challenges in ICME process integration and optimization are also summarized and highlighted. Two case studies are conducted to demonstrate the integrated process and its application in optimization.« less

Optimization of Adaptive Intraply Hybrid Fiber Composites with Reliability Considerations

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1994-01-01

The reliability with bounded distribution parameters (mean, standard deviation) was maximized and the reliability-based cost was minimized for adaptive intra-ply hybrid fiber composites by using a probabilistic method. The probabilistic method accounts for all naturally occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry, and control-related parameters. Probabilistic sensitivity factors were computed and used in the optimization procedures. For actuated change in the angle of attack of an airfoil-like composite shell structure with an adaptive torque plate, the reliability was maximized to 0.9999 probability, with constraints on the mean and standard deviation of the actuation material volume ratio (percentage of actuation composite material in a ply) and the actuation strain coefficient. The reliability-based cost was minimized for an airfoil-like composite shell structure with an adaptive skin and a mean actuation material volume ratio as the design parameter. At a O.9-mean actuation material volume ratio, the minimum cost was obtained.

Bayes Factor Covariance Testing in Item Response Models.

PubMed

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

LIBP-Pred: web server for lipid binding proteins using structural network parameters; PDB mining of human cancer biomarkers and drug targets in parasites and bacteria.

PubMed

González-Díaz, Humberto; Munteanu, Cristian R; Postelnicu, Lucian; Prado-Prado, Francisco; Gestal, Marcos; Pazos, Alejandro

2012-03-01

Lipid-Binding Proteins (LIBPs) or Fatty Acid-Binding Proteins (FABPs) play an important role in many diseases such as different types of cancer, kidney injury, atherosclerosis, diabetes, intestinal ischemia and parasitic infections. Thus, the computational methods that can predict LIBPs based on 3D structure parameters became a goal of major importance for drug-target discovery, vaccine design and biomarker selection. In addition, the Protein Data Bank (PDB) contains 3000+ protein 3D structures with unknown function. This list, as well as new experimental outcomes in proteomics research, is a very interesting source to discover relevant proteins, including LIBPs. However, to the best of our knowledge, there are no general models to predict new LIBPs based on 3D structures. We developed new Quantitative Structure-Activity Relationship (QSAR) models based on 3D electrostatic parameters of 1801 different proteins, including 801 LIBPs. We calculated these electrostatic parameters with the MARCH-INSIDE software and they correspond to the entire protein or to specific protein regions named core, inner, middle, and surface. We used these parameters as inputs to develop a simple Linear Discriminant Analysis (LDA) classifier to discriminate 3D structure of LIBPs from other proteins. We implemented this predictor in the web server named LIBP-Pred, freely available at , along with other important web servers of the Bio-AIMS portal. The users can carry out an automatic retrieval of protein structures from PDB or upload their custom protein structural models from their disk created with LOMETS server. We demonstrated the PDB mining option performing a predictive study of 2000+ proteins with unknown function. Interesting results regarding the discovery of new Cancer Biomarkers in humans or drug targets in parasites have been discussed here in this sense.

First-principles study of crystal structure, elastic stiffness constants, piezoelectric constants, and spontaneous polarization of orthorhombic Pna21-M2O3 (M = Al, Ga, In, Sc, Y)

NASA Astrophysics Data System (ADS)

Shimada, Kazuhiro

2018-03-01

We perform first-principles calculations to investigate the crystal structure, elastic and piezoelectric properties, and spontaneous polarization of orthorhombic M2O3 (M = Al, Ga, In, Sc, Y) with Pna21 space group based on density functional theory. The lattice parameters, full elastic stiffness constants, piezoelectric stress and strain constants, and spontaneous polarization are successfully predicted. Comparison with available experimental and computational results indicates the validity of our computational results. Detailed analysis of the results clarifies the difference in the bonding character and the origin of the strong piezoelectric response and large spontaneous polarization.

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.

Computer code for controller partitioning with IFPC application: A user's manual

NASA Technical Reports Server (NTRS)

Schmidt, Phillip H.; Yarkhan, Asim

1994-01-01

A user's manual for the computer code for partitioning a centralized controller into decentralized subcontrollers with applicability to Integrated Flight/Propulsion Control (IFPC) is presented. Partitioning of a centralized controller into two subcontrollers is described and the algorithm on which the code is based is discussed. The algorithm uses parameter optimization of a cost function which is described. The major data structures and functions are described. Specific instructions are given. The user is led through an example of an IFCP application.

Investigation of Structure-Property Relationships in Systematic Series of Novel Polymers. [low frequency thermomechanical spectrometry of polymeric materials - computerized torsional braid experiments

NASA Technical Reports Server (NTRS)

Gillham, J. K.

1974-01-01

The results are discussed of the on-line interface of the Torsional Braid Analysis experiment to an Hierarchical Computer System for data acquisition, data reduction and control of experimental variables. Some experimental results are demonstrated and the data reduction procedures are outlined. Several modes of presentation of the final computer-reduced data are discussed in an attempt to elucidate possible interrelations between the thermal variation of the rigidity and loss parameters.

Obtaining valid geologic models from 3-D resistivity inversion of magnetotelluric data at Pahute Mesa, Nevada

USGS Publications Warehouse

Rodriguez, Brian D.; Sweetkind, Donald S.

2015-01-01

The 3-D inversion was generally able to reproduce the gross resistivity structure of the “known” model, but the simulated conductive volcanic composite unit horizons were often too shallow when compared to the “known” model. Additionally, the chosen computation parameters such as station spacing appear to have resulted in computational artifacts that are difficult to interpret but could potentially be removed with further refinements of the 3-D resistivity inversion modeling technique.

An efficient structural finite element for inextensible flexible risers

NASA Astrophysics Data System (ADS)

Papathanasiou, T. K.; Markolefas, S.; Khazaeinejad, P.; Bahai, H.

2017-12-01

A core part of all numerical models used for flexible riser analysis is the structural component representing the main body of the riser as a slender beam. Loads acting on this structural element are self-weight, buoyant and hydrodynamic forces, internal pressure and others. A structural finite element for an inextensible riser with a point-wise enforcement of the inextensibility constrain is presented. In particular, the inextensibility constraint is applied only at the nodes of the meshed arc length parameter. Among the virtues of the proposed approach is the flexibility in the application of boundary conditions and the easy incorporation of dissipative forces. Several attributes of the proposed finite element scheme are analysed and computation times for the solution of some simplified examples are discussed. Future developments aim at the appropriate implementation of material and geometric parameters for the beam model, i.e. flexural and torsional rigidity.

Self-Adaptive Stepsize Search Applied to Optimal Structural Design

NASA Astrophysics Data System (ADS)

Nolle, L.; Bland, J. A.

Structural engineering often involves the design of space frames that are required to resist predefined external forces without exhibiting plastic deformation. The weight of the structure and hence the weight of its constituent members has to be as low as possible for economical reasons without violating any of the load constraints. Design spaces are usually vast and the computational costs for analyzing a single design are usually high. Therefore, not every possible design can be evaluated for real-world problems. In this work, a standard structural design problem, the 25-bar problem, has been solved using self-adaptive stepsize search (SASS), a relatively new search heuristic. This algorithm has only one control parameter and therefore overcomes the drawback of modern search heuristics, i.e. the need to first find a set of optimum control parameter settings for the problem at hand. In this work, SASS outperforms simulated-annealing, genetic algorithms, tabu search and ant colony optimization.

An expert system for prediction of aquatic toxicity of contaminants

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino, Dora R. May; Frank, Anthony M.; Hushon, Judith M.

1990-01-01

The National Fisheries Research Center-Great Lakes has developed an interactive computer program in muLISP that runs on an IBM-compatible microcomputer and uses a linear solvation energy relationship (LSER) to predict acute toxicity to four representative aquatic species from the detailed structure of an organic molecule. Using the SMILES formalism for a chemical structure, the expert system identifies all structural components and uses a knowledge base of rules based on an LSER to generate four structure-related parameter values. A separate module then relates these values to toxicity. The system is designed for rapid screening of potential chemical hazards before laboratory or field investigations are conducted and can be operated by users with little toxicological background. This is the first expert system based on LSER, relying on the first comprehensive compilation of rules and values for the estimation of LSER parameters.

Optical analysis of AlGaInP laser diodes with real refractive index guided self-aligned structure

NASA Astrophysics Data System (ADS)

Xu, Yun; Zhu, Xiaopeng; Ye, Xiaojun; Kang, Xiangning; Cao, Qing; Guo, Liang; Chen, Lianghui

2004-05-01

Optical modes of AlGaInP laser diodes with real refractive index guided self-aligned (RISA) structure were analyzed theoretically on the basis of two-dimension semivectorial finite-difference methods (SV-FDMs) and the computed simulation results were presented. The eigenvalue and eigenfunction of this two-dimension waveguide were obtained and the dependence of the confinement factor and beam divergence angles in the direction of parallel and perpendicular to the pn junction on the structure parameters such as the number of quantum wells, the Al composition of the cladding layers, the ridge width, the waveguide thickness and the residual thickness of the upper P-cladding layer were investigated. The results can provide optimized structure parameters and help us design and fabricate high performance AlGaInP laser diodes with a low beam aspect ratio required for optical storage applications.

Experimental and calculated structural parameters of 5-trihalomethyl-4,5-dihydro-1 H-pyrazole derivatives, novel analgesic agents

NASA Astrophysics Data System (ADS)

Machado, Pablo; Campos, Patrick T.; Lima, Glauber R.; Rosa, Fernanda A.; Flores, Alex F. C.; Bonacorso, Helio G.; Zanatta, Nilo; Martins, Marcos A. P.

2009-01-01

The crystal structures of four novel analgesic agents, methyl 5-hydroxy-3- or 4-methyl-5-trichloro[trifluoro]methyl-4,5-dihydro-1 H-pyrazole-1-carboxylate, have been determined by X-ray diffractometry. The data demonstrated that the molecular packing was stabilized mainly by O sbnd H⋯O hydrogen bonds of the 5-hydroxy and 1-carboxymethyl groups. The 4,5-dihydro-1 H-pyrazole rings were obtained as almost planar structures showing RMS deviation at a range of 0.0052-0.0805 Å. Additionally, computational investigation using semi-empirical AM1 and PM3 methods were performed to find a correlation between experimental and calculated geometrical parameters. The data obtained suggest that the structural data furnished by the AM1 method is in better agreement with those experimentally determined for the above compounds.

Laminated Thin Shell Structures Subjected to Free Vibration in a Hygrothermal Environment

NASA Technical Reports Server (NTRS)

Gotsis, Pascal K.; Guptill, James D.

1994-01-01

Parametric studies were performed to assess the effects of various parameters on the free-vibration behavior (natural frequencies) of (+/- theta)(sub 2) angle-ply, fiber composite, thin shell structures in a hygrothermal environment. Knowledge of the natural frequencies of structures is important in considering their response to various kinds of excitation, especially when structures and force systems are complex and when excitations are not periodic. The three dimensional, finite element structural analysis computer code CSTEM was used in the Cray YMP computer environment. The fiber composite shell was assumed to be cylindrical and made from T300 graphite fibers embedded in an intermediate-modulus, high-strength matrix. The following parameters were investigated: the length and the laminate thickness of the shell, the fiber orientation, the fiber volume fraction, the temperature profile through the thickness of the laminate, and laminates with different ply thicknesses. The results indicate that the fiber orientation and the length of the laminated shell had significant effects on the natural frequencies. The fiber volume fraction, the laminate thickness, and the temperature profile through the shell thickness had weak effects on the natural frequencies. Finally, the laminates with different ply thicknesses had an insignificant influence on the behavior of the vibrated laminated shell. Also, a single through-the-thickness, eight-node, three dimensional composite finite element analysis appears to be sufficient for investigating the free-vibration behavior of thin, composite, angle-ply shell structures.

MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft

PubMed Central

Zhang, Jing

2015-01-01

This paper develops a novel state-tracking multivariable model reference adaptive control (MRAC) technique utilizing prior knowledge of plant models to recover control performance of an asymmetric structural damaged aircraft. A modification of linear model representation is given. With prior knowledge on structural damage, a polytope linear parameter varying (LPV) model is derived to cover all concerned damage conditions. An MRAC method is developed for the polytope model, of which the stability and asymptotic error convergence are theoretically proved. The proposed technique reduces the number of parameters to be adapted and thus decreases computational cost and requires less input information. The method is validated by simulations on NASA generic transport model (GTM) with damage. PMID:26180839

Structural reliability analysis of laminated CMC components

NASA Technical Reports Server (NTRS)

Duffy, Stephen F.; Palko, Joseph L.; Gyekenyesi, John P.

1991-01-01

For laminated ceramic matrix composite (CMC) materials to realize their full potential in aerospace applications, design methods and protocols are a necessity. The time independent failure response of these materials is focussed on and a reliability analysis is presented associated with the initiation of matrix cracking. A public domain computer algorithm is highlighted that was coupled with the laminate analysis of a finite element code and which serves as a design aid to analyze structural components made from laminated CMC materials. Issues relevant to the effect of the size of the component are discussed, and a parameter estimation procedure is presented. The estimation procedure allows three parameters to be calculated from a failure population that has an underlying Weibull distribution.

Design for a Crane Metallic Structure Based on Imperialist Competitive Algorithm and Inverse Reliability Strategy

NASA Astrophysics Data System (ADS)

Fan, Xiao-Ning; Zhi, Bo

2017-07-01

Uncertainties in parameters such as materials, loading, and geometry are inevitable in designing metallic structures for cranes. When considering these uncertainty factors, reliability-based design optimization (RBDO) offers a more reasonable design approach. However, existing RBDO methods for crane metallic structures are prone to low convergence speed and high computational cost. A unilevel RBDO method, combining a discrete imperialist competitive algorithm with an inverse reliability strategy based on the performance measure approach, is developed. Application of the imperialist competitive algorithm at the optimization level significantly improves the convergence speed of this RBDO method. At the reliability analysis level, the inverse reliability strategy is used to determine the feasibility of each probabilistic constraint at each design point by calculating its α-percentile performance, thereby avoiding convergence failure, calculation error, and disproportionate computational effort encountered using conventional moment and simulation methods. Application of the RBDO method to an actual crane structure shows that the developed RBDO realizes a design with the best tradeoff between economy and safety together with about one-third of the convergence speed and the computational cost of the existing method. This paper provides a scientific and effective design approach for the design of metallic structures of cranes.

Quantum mechanical computations and spectroscopy: from small rigid molecules in the gas phase to large flexible molecules in solution.

PubMed

Barone, Vincenzo; Improta, Roberto; Rega, Nadia

2008-05-01

Interpretation of structural properties and dynamic behavior of molecules in solution is of fundamental importance to understand their stability, chemical reactivity, and catalytic action. While information can be gained, in principle, by a variety of spectroscopic techniques, the interpretation of the rich indirect information that can be inferred from the analysis of experimental spectra is seldom straightforward because of the subtle interplay of several different effects, whose specific role is not easy to separate and evaluate. In such a complex scenario, theoretical studies can be very helpful at two different levels: (i) supporting and complementing experimental results to determine the structure of the target molecule starting from its spectral properties; (ii) dissecting and evaluating the role of different effects in determining the observed spectroscopic properties. This is the reason why computational spectroscopy is rapidly evolving from a highly specialized research field into a versatile and widespread tool for the assignment of experimental spectra and their interpretation in terms of chemical physical effects. In such a situation, it becomes important that both computationally and experimentally oriented chemists are aware that new methodological advances and integrated computational strategies are available, providing reliable estimates of fundamental spectral parameters not only for relatively small molecules in the gas phase but also for large and flexible molecules in condensed phases. In this Account, we review the most significant methodological contributions from our research group in this field, and by exploiting some recent results of their application to the computation of IR, UV-vis, NMR, and EPR spectral parameters, we discuss the microscopic mechanisms underlying solvent and vibrational effects on the spectral parameters. After reporting some recent achievements for the study of excited states by first principle quantum mechanical approaches, we focus on the treatment of environmental effects by means of mixed discrete-continuum solvent models and on effective methods for computing vibronic contributions to the spectra. We then discuss some new developments, mainly based on time-dependent approaches, allowing us to go beyond the determination of spectroscopic parameters toward the simulation of line widths and shapes. Although further developments are surely needed to improve the accuracy and effectiveness of several items in the proposed approach, we try to show that the first important steps toward a direct comparison between the results obtained in vitro and those obtained in silico have been made, making easier fruitful crossovers among experiments, computations and theoretical models, which would be decisive for a deeper understanding of the spectral behavior associated with complex systems and processes.

Diffused junction p(+)-n solar cells in bulk GaAs. II - Device characterization and modelling

NASA Technical Reports Server (NTRS)

Keeney, R.; Sundaram, L. M. G.; Rode, H.; Bhat, I.; Ghandhi, S. K.; Borrego, J. M.

1984-01-01

The photovoltaic characteristics of p(+)-n junction solar cells fabricated on bulk GaAs by an open tube diffusion technique are presented in detail. Quantum efficiency measurements were analyzed and compared to computer simulations of the cell structure in order to determine material parameters such as diffusion length, surface recombination velocity and junction depth. From the results obtained it is projected that proper optimization of the cell parameters can increase the efficiency of the cells to close to 20 percent.

Aerodynamic and structural studies of joined-wing aircraft

NASA Technical Reports Server (NTRS)

Kroo, Ilan; Smith, Stephen; Gallman, John

1991-01-01

A method for rapidly evaluating the structural and aerodynamic characteristics of joined-wing aircraft was developed and used to study the fundamental advantages attributed to this concept. The technique involves a rapid turnaround aerodynamic analysis method for computing minimum trimmed drag combined with a simple structural optimization. A variety of joined-wing designs are compared on the basis of trimmed drag, structural weight, and, finally, trimmed drag with fixed structural weight. The range of joined-wing design parameters resulting in best cruise performance is identified. Structural weight savings and net drag reductions are predicted for certain joined-wing configurations compared with conventional cantilever-wing configurations.

A semi-supervised learning approach for RNA secondary structure prediction.

PubMed

Yonemoto, Haruka; Asai, Kiyoshi; Hamada, Michiaki

2015-08-01

RNA secondary structure prediction is a key technology in RNA bioinformatics. Most algorithms for RNA secondary structure prediction use probabilistic models, in which the model parameters are trained with reliable RNA secondary structures. Because of the difficulty of determining RNA secondary structures by experimental procedures, such as NMR or X-ray crystal structural analyses, there are still many RNA sequences that could be useful for training whose secondary structures have not been experimentally determined. In this paper, we introduce a novel semi-supervised learning approach for training parameters in a probabilistic model of RNA secondary structures in which we employ not only RNA sequences with annotated secondary structures but also ones with unknown secondary structures. Our model is based on a hybrid of generative (stochastic context-free grammars) and discriminative models (conditional random fields) that has been successfully applied to natural language processing. Computational experiments indicate that the accuracy of secondary structure prediction is improved by incorporating RNA sequences with unknown secondary structures into training. To our knowledge, this is the first study of a semi-supervised learning approach for RNA secondary structure prediction. This technique will be useful when the number of reliable structures is limited. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effects of 3D Earth structure on W-phase CMT parameters

NASA Astrophysics Data System (ADS)

Morales, Catalina; Duputel, Zacharie; Rivera, Luis; Kanamori, Hiroo

2017-04-01

The source inversion of the W-phase has demonstrated a great potential to provide fast and reliable estimates of the centroid moment tensor (CMT) for moderate to large earthquakes. It has since been implemented in different operational environments (NEIC-USGS, PTWC, etc.) with the aim of providing rapid CMT solutions. These solutions are in particular useful for tsunami warning purposes. Computationally, W-phase waveforms are usually synthetized by summation of normal modes at long period (100 - 1000 s) for a spherical Earth model (e.g., PREM). Although the energy of these modes mainly stays in the mantle where lateral structural variations are relatively small, the impact of 3D heterogeneities on W-phase solutions have not yet been quantified. In this study, we investigate possible bias in W-phase source parameters due to unmodeled lateral structural heterogeneities. We generate a simulated dataset consisting of synthetic seismograms of large past earthquakes that accounts for the Earth's 3D structure. The W-phase algorithm is then used to invert the synthetic dataset for earthquake CMT parameters with and without added noise. Results show that the impact of 3D heterogeneities is generally larger for surface-waves than for W-phase waveforms. However, some discrepancies are noted between inverted W-phase parameters and target values. Particular attention is paid to the possible bias induced by the unmodeled 3D structure into the location of the W-phase centroid. Preliminary results indicate that the parameter that is most susceptible to 3D Earth structure seems to be the centroid depth.

Empirical optimization of DFT  +  U and HSE for the band structure of ZnO.

PubMed

Bashyal, Keshab; Pyles, Christopher K; Afroosheh, Sajjad; Lamichhane, Aneer; Zayak, Alexey T

2018-02-14

ZnO is a well-known wide band gap semiconductor with promising potential for applications in optoelectronics, transparent electronics, and spintronics. Computational simulations based on the density functional theory (DFT) play an important role in the research of ZnO, but the standard functionals, like Perdew-Burke-Erzenhof, result in largely underestimated values of the band gap and the binding energies of the Zn 3d electrons. Methods like DFT  +  U and hybrid functionals are meant to remedy the weaknesses of plain DFT. However, both methods are not parameter-free. Direct comparison with experimental data is the best way to optimize the computational parameters. X-ray photoemission spectroscopy (XPS) is commonly considered as a benchmark for the computed electronic densities of states. In this work, both DFT  +  U and HSE methods were parametrized to fit almost exactly the binding energies of electrons in ZnO obtained by XPS. The optimized parameterizations of DFT  +  U and HSE lead to significantly worse results in reproducing the ion-clamped static dielectric tensor, compared to standard high-level calculations, including GW, which in turn yield a perfect match for the dielectric tensor. The failure of our XPS-based optimization reveals the fact that XPS does not report the ground state electronic structure for ZnO and should not be used for benchmarking ground state electronic structure calculations.

Empirical optimization of DFT  +  U and HSE for the band structure of ZnO

NASA Astrophysics Data System (ADS)

Bashyal, Keshab; Pyles, Christopher K.; Afroosheh, Sajjad; Lamichhane, Aneer; Zayak, Alexey T.

2018-02-01

ZnO is a well-known wide band gap semiconductor with promising potential for applications in optoelectronics, transparent electronics, and spintronics. Computational simulations based on the density functional theory (DFT) play an important role in the research of ZnO, but the standard functionals, like Perdew-Burke-Erzenhof, result in largely underestimated values of the band gap and the binding energies of the Zn3d electrons. Methods like DFT  +  U and hybrid functionals are meant to remedy the weaknesses of plain DFT. However, both methods are not parameter-free. Direct comparison with experimental data is the best way to optimize the computational parameters. X-ray photoemission spectroscopy (XPS) is commonly considered as a benchmark for the computed electronic densities of states. In this work, both DFT  +  U and HSE methods were parametrized to fit almost exactly the binding energies of electrons in ZnO obtained by XPS. The optimized parameterizations of DFT  +  U and HSE lead to significantly worse results in reproducing the ion-clamped static dielectric tensor, compared to standard high-level calculations, including GW, which in turn yield a perfect match for the dielectric tensor. The failure of our XPS-based optimization reveals the fact that XPS does not report the ground state electronic structure for ZnO and should not be used for benchmarking ground state electronic structure calculations.

Software for Acoustic Rendering

NASA Technical Reports Server (NTRS)

Miller, Joel D.

2003-01-01

SLAB is a software system that can be run on a personal computer to simulate an acoustic environment in real time. SLAB was developed to enable computational experimentation in which one can exert low-level control over a variety of signal-processing parameters, related to spatialization, for conducting psychoacoustic studies. Among the parameters that can be manipulated are the number and position of reflections, the fidelity (that is, the number of taps in finite-impulse-response filters), the system latency, and the update rate of the filters. Another goal in the development of SLAB was to provide an inexpensive means of dynamic synthesis of virtual audio over headphones, without need for special-purpose signal-processing hardware. SLAB has a modular, object-oriented design that affords the flexibility and extensibility needed to accommodate a variety of computational experiments and signal-flow structures. SLAB s spatial renderer has a fixed signal-flow architecture corresponding to a set of parallel signal paths from each source to a listener. This fixed architecture can be regarded as a compromise that optimizes efficiency at the expense of complete flexibility. Such a compromise is necessary, given the design goal of enabling computational psychoacoustic experimentation on inexpensive personal computers.

Advanced computer-aided design for bone tissue-engineering scaffolds.

PubMed

Ramin, E; Harris, R A

2009-04-01

The design of scaffolds with an intricate and controlled internal structure represents a challenge for tissue engineering. Several scaffold-manufacturing techniques allow the creation of complex architectures but with little or no control over the main features of the channel network such as the size, shape, and interconnectivity of each individual channel, resulting in intricate but random structures. The combined use of computer-aided design (CAD) systems and layer-manufacturing techniques allows a high degree of control over these parameters with few limitations in terms of achievable complexity. However, the design of complex and intricate networks of channels required in CAD is extremely time-consuming since manually modelling hundreds of different geometrical elements, all with different parameters, may require several days to design individual scaffold structures. An automated design methodology is proposed by this research to overcome these limitations. This approach involves the investigation of novel software algorithms, which are able to interact with a conventional CAD program and permit the automated design of several geometrical elements, each with a different size and shape. In this work, the variability of the parameters required to define each geometry has been set as random, but any other distribution could have been adopted. This methodology has been used to design five cubic scaffolds with interconnected pore channels that range from 200 to 800 microm in diameter, each with an increased complexity of the internal geometrical arrangement. A clinical case study, consisting of an integration of one of these geometries with a craniofacial implant, is then presented.

Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations.

PubMed

Meshkat, Nicolette; Anderson, Chris; Distefano, Joseph J

2011-09-01

When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel. Copyright © 2011 Elsevier Inc. All rights reserved.

Computational design analysis for deployment of cardiovascular stents

NASA Astrophysics Data System (ADS)

Tammareddi, Sriram; Sun, Guangyong; Li, Qing

2010-06-01

Cardiovascular disease has become a major global healthcare problem. As one of the relatively new medical devices, stents offer a minimally-invasive surgical strategy to improve the quality of life for numerous cardiovascular disease patients. One of the key associative issues has been to understand the effect of stent structures on its deployment behaviour. This paper aims to develop a computational model for exploring the biomechanical responses to the change in stent geometrical parameters, namely the strut thickness and cross-link width of the Palmaz-Schatz stent. Explicit 3D dynamic finite element analysis was carried out to explore the sensitivity of these geometrical parameters on deployment performance, such as dog-boning, fore-shortening, and stent deformation over the load cycle. It has been found that an increase in stent thickness causes a sizeable rise in the load required to deform the stent to its target diameter, whilst reducing maximum dog-boning in the stent. An increase in the cross-link width showed that no change in the load is required to deform the stent to its target diameter, and there is no apparent correlation with dog-boning but an increased fore-shortening with increasing cross-link width. The computational modelling and analysis presented herein proves an effective way to refine or optimise the design of stent structures.

Reliability, Risk and Cost Trade-Offs for Composite Designs

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Singhal, Surendra N.; Chamis, Christos C.

1996-01-01

Risk and cost trade-offs have been simulated using a probabilistic method. The probabilistic method accounts for all naturally-occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry and loading conditions. The probability density function of first buckling load for a set of uncertain variables is computed. The probabilistic sensitivity factors of uncertain variables to the first buckling load is calculated. The reliability-based cost for a composite fuselage panel is defined and minimized with respect to requisite design parameters. The optimization is achieved by solving a system of nonlinear algebraic equations whose coefficients are functions of probabilistic sensitivity factors. With optimum design parameters such as the mean and coefficient of variation (representing range of scatter) of uncertain variables, the most efficient and economical manufacturing procedure can be selected. In this paper, optimum values of the requisite design parameters for a predetermined cost due to failure occurrence are computationally determined. The results for the fuselage panel analysis show that the higher the cost due to failure occurrence, the smaller the optimum coefficient of variation of fiber modulus (design parameter) in longitudinal direction.

Active subspace uncertainty quantification for a polydomain ferroelectric phase-field model

NASA Astrophysics Data System (ADS)

Leon, Lider S.; Smith, Ralph C.; Miles, Paul; Oates, William S.

2018-03-01

Quantum-informed ferroelectric phase field models capable of predicting material behavior, are necessary for facilitating the development and production of many adaptive structures and intelligent systems. Uncertainty is present in these models, given the quantum scale at which calculations take place. A necessary analysis is to determine how the uncertainty in the response can be attributed to the uncertainty in the model inputs or parameters. A second analysis is to identify active subspaces within the original parameter space, which quantify directions in which the model response varies most dominantly, thus reducing sampling effort and computational cost. In this investigation, we identify an active subspace for a poly-domain ferroelectric phase-field model. Using the active variables as our independent variables, we then construct a surrogate model and perform Bayesian inference. Once we quantify the uncertainties in the active variables, we obtain uncertainties for the original parameters via an inverse mapping. The analysis provides insight into how active subspace methodologies can be used to reduce computational power needed to perform Bayesian inference on model parameters informed by experimental or simulated data.

Results of an integrated structure/control law design sensitivity analysis

NASA Technical Reports Server (NTRS)

Gilbert, Michael G.

1989-01-01

A design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations is discussed. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changes in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient than finite difference methods for the computation of the equivalent sensitivity information.

Self-consistent Green's function embedding for advanced electronic structure methods based on a dynamical mean-field concept

NASA Astrophysics Data System (ADS)

Chibani, Wael; Ren, Xinguo; Scheffler, Matthias; Rinke, Patrick

2016-04-01

We present an embedding scheme for periodic systems that facilitates the treatment of the physically important part (here a unit cell or a supercell) with advanced electronic structure methods, that are computationally too expensive for periodic systems. The rest of the periodic system is treated with computationally less demanding approaches, e.g., Kohn-Sham density-functional theory, in a self-consistent manner. Our scheme is based on the concept of dynamical mean-field theory formulated in terms of Green's functions. Our real-space dynamical mean-field embedding scheme features two nested Dyson equations, one for the embedded cluster and another for the periodic surrounding. The total energy is computed from the resulting Green's functions. The performance of our scheme is demonstrated by treating the embedded region with hybrid functionals and many-body perturbation theory in the GW approach for simple bulk systems. The total energy and the density of states converge rapidly with respect to the computational parameters and approach their bulk limit with increasing cluster (i.e., computational supercell) size.

Effect of breed and sperm concentration on the changes in structural, functional and motility parameters of ram-lamb spermatozoa during storage at 4 degrees C.

PubMed

Kasimanickam, Ramanathan; Kasimanickam, Vanmathy; Pelzer, Kevin D; Dascanio, John J

2007-09-01

The objectives of this study were (1) to determine the changes in structural, functional and motility parameters of ram-lamb semen stored at two different concentrations at 4 degrees C for 8 days in egg-yolk based extender and (2) to determine the effect of breed of ram-lambs on the changes in structural, functional and motility parameters of ram-lamb semen from different breeds stored at two different concentrations at 4 degrees C for 8 days in egg-yolk based extender. Two different concentrations suitable for laparoscopic and cervical insemination were employed in this experiment. A total of 14 ram-lambs (Polled Dorset-5, Suffolk-5, Katahdin-4) with satisfactory breeding potential were selected. Semen samples were collected by electro-ejaculation. Semen samples were extended to 50 and 200 million sperm per ml with a commercial egg yolk based extender (Triladyl, Minitube of America, Verona, WI, USA) at room temperature and were stored at 4 degrees C. The sperm DNA fragmentation index (DFI), percentages of high mitochondrial membrane potential (hMMP) and plasma membrane integrity (PMI) were assessed using flow cytometry as part of structural and functional parameters on Days 0, 1, 4, 6, and 8. A computer assisted sperm analyser (HTM-IVOS, Version 10.8, Hamilton Thorne Research, Beverly, MA, USA) was used to assess the sperm motility parameters on Days 0, 1, 4, 6, and 8. PROC MIXED procedure was used to determine the effect of days of storage, concentration and breed. The concentration and days of storage significantly affected the sperm structural, functional and motility parameters (P<0.0001). Significant concentration x days of storage interaction was found for all structural and functional parameters. There was a significant concentration x days of storage interaction for average path velocity, curvilinear velocity, straightness and linearity. Overall changes in the sperm structural, functional and sperm motility parameters over the storage period were less dramatic in the 200 x 10(6) ml(-1) concentration when compared to 50 x 10(6) ml(-1) concentration. The hMMP and total progressive motility were influenced by breed. In conclusion, the quality of structural, functional and motility parameters declined as days of storage were increased and the magnitude of changes in the parameters was less dramatic at the higher concentration.

Chemical graphs, molecular matrices and topological indices in chemoinformatics and quantitative structure-activity relationships.

PubMed

Ivanciuc, Ovidiu

2013-06-01

Chemical and molecular graphs have fundamental applications in chemoinformatics, quantitative structureproperty relationships (QSPR), quantitative structure-activity relationships (QSAR), virtual screening of chemical libraries, and computational drug design. Chemoinformatics applications of graphs include chemical structure representation and coding, database search and retrieval, and physicochemical property prediction. QSPR, QSAR and virtual screening are based on the structure-property principle, which states that the physicochemical and biological properties of chemical compounds can be predicted from their chemical structure. Such structure-property correlations are usually developed from topological indices and fingerprints computed from the molecular graph and from molecular descriptors computed from the three-dimensional chemical structure. We present here a selection of the most important graph descriptors and topological indices, including molecular matrices, graph spectra, spectral moments, graph polynomials, and vertex topological indices. These graph descriptors are used to define several topological indices based on molecular connectivity, graph distance, reciprocal distance, distance-degree, distance-valency, spectra, polynomials, and information theory concepts. The molecular descriptors and topological indices can be developed with a more general approach, based on molecular graph operators, which define a family of graph indices related by a common formula. Graph descriptors and topological indices for molecules containing heteroatoms and multiple bonds are computed with weighting schemes based on atomic properties, such as the atomic number, covalent radius, or electronegativity. The correlation in QSPR and QSAR models can be improved by optimizing some parameters in the formula of topological indices, as demonstrated for structural descriptors based on atomic connectivity and graph distance.

An advection-diffusion-reaction size-structured fish population dynamics model combined with a statistical parameter estimation procedure: application to the Indian ocean skipjack tuna fishery.

PubMed

Faugeras, Blaise; Maury, Olivier

2005-10-01

We develop an advection-diffusion size-structured fish population dynamics model and apply it to simulate the skipjack tuna population in the Indian Ocean. The model is fully spatialized, and movements are parameterized with oceanographical and biological data; thus it naturally reacts to environment changes. We first formulate an initial-boundary value problem and prove existence of a unique positive solution. We then discuss the numerical scheme chosen for the integration of the simulation model. In a second step we address the parameter estimation problem for such a model. With the help of automatic differentiation, we derive the adjoint code which is used to compute the exact gradient of a Bayesian cost function measuring the distance between the outputs of the model and catch and length frequency data. A sensitivity analysis shows that not all parameters can be estimated from the data. Finally twin experiments in which pertubated parameters are recovered from simulated data are successfully conducted.

Structural Identifiability of Dynamic Systems Biology Models

PubMed Central

Villaverde, Alejandro F.

2016-01-01

A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas. PMID:27792726

Structural and functional changes during epileptogenesis in the mouse model of medial temporal lobe epilepsy.

PubMed

Dietrich, Yvan; Eliat, Pierre-Antoine; Dieuset, Gabriel; Saint-Jalmes, Herve; Pineau, Charles; Wendling, Fabrice; Martin, Benoit

2016-08-01

An important issue in epilepsy research is to understand the structural and functional modifications leading to chronic epilepsy, characterized by spontaneous recurrent seizures, after initial brain insult. To address this issue, we recorded and analyzed electroencephalography (EEG) and quantitative magnetic resonance imaging (MRI) data during epileptogenesis in the in vivo mouse model of Medial Temporal Lobe Epilepsy (MTLE, kainate). Besides, this model of epilepsy is a particular form of drug-resistant epilepsy. The results indicate that high-field (4.7T) MRI parameters (T2-weighted; T2-quantitative) allow to detect the gradual neuro-anatomical changes that occur during epileptogenesis while electrophysiological parameters (number and duration of Hippocampal Paroxysmal Discharges) allow to assess the dysfunctional changes through the quantification of epileptiform activity. We found a strong correlation between EEG-based markers (invasive recording) and MRI-based parameters (non-invasive) periodically computed over the `latent period' that spans over two weeks, on average. These results indicated that both structural and functional changes occur in the considered epilepsy model and are considered as biomarkers of the installation of epilepsy. Additionally, such structural and functional changes can also be observed in human temporal lobe epilepsy. Interestingly, MRI imaging parameters could be used to track early (day-7) structural changes (gliosis, cell loss) in the lesioned brain and to quantify the evolution of epileptogenesis after traumatic brain injury.

Structural convergence properties of amorphous InGaZnO4 from simulated liquid-quench methods.

PubMed

Buchanan, Jacob C; Fast, Dylan B; Hanken, Benjamin E; Mustard, Thomas J L; Laurita, Geneva; Chiang, Tsung-Han; Keszler, Douglas A; Subramanian, Mas A; Wager, John F; Dolgos, Michelle R; Rustad, James R; Cheong, Paul Ha-Yeon

2017-11-14

The study of structural properties of amorphous structures is complicated by the lack of long-range order and necessitates the use of both cutting-edge computer modeling and experimental techniques. With regards to the computer modeling, many questions on convergence arise when trying to assess the accuracy of a simulated system. What cell size maximizes the accuracy while remaining computationally efficient? More importantly, does averaging multiple smaller cells adequately describe features found in bulk amorphous materials? How small is too small? The aims of this work are: (1) to report a newly developed set of pair potentials for InGaZnO 4 and (2) to explore the effects of structural parameters such as simulation cell size and numbers on the structural convergence of amorphous InGaZnO 4 . The total number of formula units considered over all runs is found to be the critical factor in convergence as long as the cell considered contains a minimum of circa fifteen formula units. There is qualitative agreement between these simulations and X-ray total scattering data - peak trends and locations are consistently reproduced while intensities are weaker. These new IGZO pair potentials are a valuable starting point for future structural refinement efforts.

Modelling of flow processes of the structured two-phase disperse systems (solid phase-liquid medium).

PubMed

Uriev, N B; Kuchin, I V

2007-10-31

A review of the basic theories and models of shear flow of suspensions is presented and the results of modeling of structured suspensions under flow conditions. The physical backgrounds and conditions of macroscopic discontinuity in the behaviour of high-concentrated systems are analyzed. The use of surfactants and imposed vibration for regulation of rheological properties of suspensions are considered. A review of the recent approaches and methods of computer simulation of concentrated suspensions is undertaken and results of computer simulation of suspensions are presented. Formation and destruction of the structure of suspension under static and dynamic conditions (including imposed combined shear and orthogonal oscillations) are discussed. The influence of interaction of particles as well as of some parameters characterizing a type and intensity of external perturbations on suspensions behavior is demonstrated.

Survey of NASA research on crash dynamics

NASA Technical Reports Server (NTRS)

Thomson, R. G.; Carden, H. D.; Hayduk, R. J.

1984-01-01

Ten years of structural crash dynamics research activities conducted on general aviation aircraft by the National Aeronautics and Space Administration (NASA) are described. Thirty-two full-scale crash tests were performed at Langley Research Center, and pertinent data on airframe and seat behavior were obtained. Concurrent with the experimental program, analytical methods were developed to help predict structural behavior during impact. The effects of flight parameters at impact on cabin deceleration pulses at the seat/occupant interface, experimental and analytical correlation of data on load-limiting subfloor and seat configurations, airplane section test results for computer modeling validation, and data from emergency-locator-transmitter (ELT) investigations to determine probable cause of false alarms and nonactivations are assessed. Computer programs which provide designers with analytical methods for predicting accelerations, velocities, and displacements of collapsing structures are also discussed.

ICASE semiannual report, April 1 - September 30, 1989

NASA Technical Reports Server (NTRS)

1990-01-01

The Institute conducts unclassified basic research in applied mathematics, numerical analysis, and computer science in order to extend and improve problem-solving capabilities in science and engineering, particularly in aeronautics and space. The major categories of the current Institute for Computer Applications in Science and Engineering (ICASE) research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification problems, with emphasis on effective numerical methods; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers. ICASE reports are considered to be primarily preprints of manuscripts that have been submitted to appropriate research journals or that are to appear in conference proceedings.

Universal measurement-based quantum computation in two-dimensional symmetry-protected topological phases

NASA Astrophysics Data System (ADS)

Wei, Tzu-Chieh; Huang, Ching-Yu

2017-09-01

Recent progress in the characterization of gapped quantum phases has also triggered the search for a universal resource for quantum computation in symmetric gapped phases. Prior works in one dimension suggest that it is a feature more common than previously thought, in that nontrivial one-dimensional symmetry-protected topological (SPT) phases provide quantum computational power characterized by the algebraic structure defining these phases. Progress in two and higher dimensions so far has been limited to special fixed points. Here we provide two families of two-dimensional Z2 symmetric wave functions such that there exists a finite region of the parameter in the SPT phases that supports universal quantum computation. The quantum computational power appears to lose its universality at the boundary between the SPT and the symmetry-breaking phases.

A Frequency-Domain Multipath Parameter Estimation and Mitigation Method for BOC-Modulated GNSS Signals

PubMed Central

Sun, Chao; Feng, Wenquan; Du, Songlin

2018-01-01

As multipath is one of the dominating error sources for high accuracy Global Navigation Satellite System (GNSS) applications, multipath mitigation approaches are employed to minimize this hazardous error in receivers. Binary offset carrier modulation (BOC), as a modernized signal structure, is adopted to achieve significant enhancement. However, because of its multi-peak autocorrelation function, conventional multipath mitigation techniques for binary phase shift keying (BPSK) signal would not be optimal. Currently, non-parametric and parametric approaches have been studied specifically aiming at multipath mitigation for BOC signals. Non-parametric techniques, such as Code Correlation Reference Waveforms (CCRW), usually have good feasibility with simple structures, but suffer from low universal applicability for different BOC signals. Parametric approaches can thoroughly eliminate multipath error by estimating multipath parameters. The problems with this category are at the high computation complexity and vulnerability to the noise. To tackle the problem, we present a practical parametric multipath estimation method in the frequency domain for BOC signals. The received signal is transferred to the frequency domain to separate out the multipath channel transfer function for multipath parameter estimation. During this process, we take the operations of segmentation and averaging to reduce both noise effect and computational load. The performance of the proposed method is evaluated and compared with the previous work in three scenarios. Results indicate that the proposed averaging-Fast Fourier Transform (averaging-FFT) method achieves good robustness in severe multipath environments with lower computational load for both low-order and high-order BOC signals. PMID:29495589

Probabilistic structural analysis methods for improving Space Shuttle engine reliability

NASA Technical Reports Server (NTRS)

Boyce, L.

1989-01-01

Probabilistic structural analysis methods are particularly useful in the design and analysis of critical structural components and systems that operate in very severe and uncertain environments. These methods have recently found application in space propulsion systems to improve the structural reliability of Space Shuttle Main Engine (SSME) components. A computer program, NESSUS, based on a deterministic finite-element program and a method of probabilistic analysis (fast probability integration) provides probabilistic structural analysis for selected SSME components. While computationally efficient, it considers both correlated and nonnormal random variables as well as an implicit functional relationship between independent and dependent variables. The program is used to determine the response of a nickel-based superalloy SSME turbopump blade. Results include blade tip displacement statistics due to the variability in blade thickness, modulus of elasticity, Poisson's ratio or density. Modulus of elasticity significantly contributed to blade tip variability while Poisson's ratio did not. Thus, a rational method for choosing parameters to be modeled as random is provided.

Evolutionary optimization with data collocation for reverse engineering of biological networks.

PubMed

Tsai, Kuan-Yao; Wang, Feng-Sheng

2005-04-01

Modern experimental biology is moving away from analyses of single elements to whole-organism measurements. Such measured time-course data contain a wealth of information about the structure and dynamic of the pathway or network. The dynamic modeling of the whole systems is formulated as a reverse problem that requires a well-suited mathematical model and a very efficient computational method to identify the model structure and parameters. Numerical integration for differential equations and finding global parameter values are still two major challenges in this field of the parameter estimation of nonlinear dynamic biological systems. We compare three techniques of parameter estimation for nonlinear dynamic biological systems. In the proposed scheme, the modified collocation method is applied to convert the differential equations to the system of algebraic equations. The observed time-course data are then substituted into the algebraic system equations to decouple system interactions in order to obtain the approximate model profiles. Hybrid differential evolution (HDE) with population size of five is able to find a global solution. The method is not only suited for parameter estimation but also can be applied for structure identification. The solution obtained by HDE is then used as the starting point for a local search method to yield the refined estimates.

Optoelectronic transport properties in amorphous/crystalline silicon solar cell heterojunctions measured by frequency-domain photocarrier radiometry: multi-parameter measurement reliability and precision studies.

PubMed

Zhang, Y; Melnikov, A; Mandelis, A; Halliop, B; Kherani, N P; Zhu, R

2015-03-01

A theoretical one-dimensional two-layer linear photocarrier radiometry (PCR) model including the presence of effective interface carrier traps was used to evaluate the transport parameters of p-type hydrogenated amorphous silicon (a-Si:H) and n-type crystalline silicon (c-Si) passivated by an intrinsic hydrogenated amorphous silicon (i-layer) nanolayer. Several crystalline Si heterojunction structures were examined to investigate the influence of the i-layer thickness and the doping concentration of the a-Si:H layer. The experimental data of a series of heterojunction structures with intrinsic thin layers were fitted to PCR theory to gain insight into the transport properties of these devices. The quantitative multi-parameter results were studied with regard to measurement reliability (uniqueness) and precision using two independent computational best-fit programs. The considerable influence on the transport properties of the entire structure of two key parameters that can limit the performance of amorphous thin film solar cells, namely, the doping concentration of the a-Si:H layer and the i-layer thickness was demonstrated. It was shown that PCR can be applied to the non-destructive characterization of a-Si:H/c-Si heterojunction solar cells yielding reliable measurements of the key parameters.

Optoelectronic transport properties in amorphous/crystalline silicon solar cell heterojunctions measured by frequency-domain photocarrier radiometry: Multi-parameter measurement reliability and precision studies

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

Zhang, Y.; Institute of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094; Melnikov, A.

2015-03-15

A theoretical one-dimensional two-layer linear photocarrier radiometry (PCR) model including the presence of effective interface carrier traps was used to evaluate the transport parameters of p-type hydrogenated amorphous silicon (a-Si:H) and n-type crystalline silicon (c-Si) passivated by an intrinsic hydrogenated amorphous silicon (i-layer) nanolayer. Several crystalline Si heterojunction structures were examined to investigate the influence of the i-layer thickness and the doping concentration of the a-Si:H layer. The experimental data of a series of heterojunction structures with intrinsic thin layers were fitted to PCR theory to gain insight into the transport properties of these devices. The quantitative multi-parameter results weremore » studied with regard to measurement reliability (uniqueness) and precision using two independent computational best-fit programs. The considerable influence on the transport properties of the entire structure of two key parameters that can limit the performance of amorphous thin film solar cells, namely, the doping concentration of the a-Si:H layer and the i-layer thickness was demonstrated. It was shown that PCR can be applied to the non-destructive characterization of a-Si:H/c-Si heterojunction solar cells yielding reliable measurements of the key parameters.« less

Thermal transport properties of bulk and monolayer MoS2: an ab-initio approach

NASA Astrophysics Data System (ADS)

Bano, Amreen; Khare, Preeti; Gaur, N. K.

2017-05-01

The transport properties of semiconductors are key to the performance of many solid-state devices (transistors, data storage, thermoelectric cooling and power generation devices, etc). In recent years simulation tools based on first-principles calculations have been greatly improved, being able to obtain the fundamental ground-state properties of materials accurately. The quasi harmonic thermal properties of bulk and monolayer of MoS2 has been computed with ab initio periodic simulations based of density functional theory (DFT). The temperature dependence of bulk modulus, specific heat, thermal expansion and gruneisen parameter have been calculated in our work within the temperature range of 0K to 900K with projected augmented wave (PAW) method using generalized gradient approximation (GGA). Our results show that the optimized lattice parameters are in good agreement with the earlier reported works and also for thermoelastic parameter, i.e. isothermal bulk modulus (B) at 0K indicates that monolayer MoS2 (48.5 GPa)is more compressible than the bulk structure (159.23 GPa). The thermal expansion of monolayer structure is slightly less than the bulk. Similarly, other parameters like heat capacity and gruneisen parameter shows different nature which is due to the confinement of 3 dimensional structure to 2 dimension (2D) for improving its transport characteristics.

Analytical modeling of the structureborne noise path on a small twin-engine aircraft

NASA Technical Reports Server (NTRS)

Cole, J. E., III; Stokes, A. Westagard; Garrelick, J. M.; Martini, K. F.

1988-01-01

The structureborne noise path of a six passenger twin-engine aircraft is analyzed. Models of the wing and fuselage structures as well as the interior acoustic space of the cabin are developed and used to evaluate sensitivity to structural and acoustic parameters. Different modeling approaches are used to examine aspects of the structureborne path. These approaches are guided by a number of considerations including the geometry of the structures, the frequency range of interest, and the tractability of the computations. Results of these approaches are compared with experimental data.

Spatial localization in heterogeneous systems

NASA Astrophysics Data System (ADS)

Kao, Hsien-Ching; Beaume, Cédric; Knobloch, Edgar

2014-01-01

We study spatial localization in the generalized Swift-Hohenberg equation with either quadratic-cubic or cubic-quintic nonlinearity subject to spatially heterogeneous forcing. Different types of forcing (sinusoidal or Gaussian) with different spatial scales are considered and the corresponding localized snaking structures are computed. The results indicate that spatial heterogeneity exerts a significant influence on the location of spatially localized structures in both parameter space and physical space, and on their stability properties. The results are expected to assist in the interpretation of experiments on localized structures where departures from spatial homogeneity are generally unavoidable.

Probabilistic Fatigue Damage Program (FATIG)

NASA Technical Reports Server (NTRS)

Michalopoulos, Constantine

2012-01-01

FATIG computes fatigue damage/fatigue life using the stress rms (root mean square) value, the total number of cycles, and S-N curve parameters. The damage is computed by the following methods: (a) traditional method using Miner s rule with stress cycles determined from a Rayleigh distribution up to 3*sigma; and (b) classical fatigue damage formula involving the Gamma function, which is derived from the integral version of Miner's rule. The integration is carried out over all stress amplitudes. This software solves the problem of probabilistic fatigue damage using the integral form of the Palmgren-Miner rule. The software computes fatigue life using an approach involving all stress amplitudes, up to N*sigma, as specified by the user. It can be used in the design of structural components subjected to random dynamic loading, or by any stress analyst with minimal training for fatigue life estimates of structural components.

Simulation of ceramic materials relevant for nuclear waste management: Case of La1-xEuxPO4 solid solution

NASA Astrophysics Data System (ADS)

Kowalski, Piotr M.; Ji, Yaqi; Li, Yan; Arinicheva, Yulia; Beridze, George; Neumeier, Stefan; Bukaemskiy, Andrey; Bosbach, Dirk

2017-02-01

Using powerful computational resources and state-of-the-art methods of computational chemistry we contribute to the research on novel nuclear waste forms by providing atomic scale description of processes that govern the structural incorporation and the interactions of radionuclides in host materials. Here we present various results of combined computational and experimental studies on La1-xEuxPO4 monazite-type solid solution. We discuss the performance of DFT + U method with the Hubbard U parameter value derived ab initio, and the derivation of various structural, thermodynamic and radiation-damage related properties. We show a correlation between the cation displacement probabilities and the solubility data, indicating that the binding of cations is the driving factor behind both processes. The combined atomistic modeling and experimental studies result in a superior characterization of the investigated material.

Fine-grained parallel RNAalifold algorithm for RNA secondary structure prediction on FPGA

PubMed Central

Xia, Fei; Dou, Yong; Zhou, Xingming; Yang, Xuejun; Xu, Jiaqing; Zhang, Yang

2009-01-01

Background In the field of RNA secondary structure prediction, the RNAalifold algorithm is one of the most popular methods using free energy minimization. However, general-purpose computers including parallel computers or multi-core computers exhibit parallel efficiency of no more than 50%. Field Programmable Gate-Array (FPGA) chips provide a new approach to accelerate RNAalifold by exploiting fine-grained custom design. Results RNAalifold shows complicated data dependences, in which the dependence distance is variable, and the dependence direction is also across two dimensions. We propose a systolic array structure including one master Processing Element (PE) and multiple slave PEs for fine grain hardware implementation on FPGA. We exploit data reuse schemes to reduce the need to load energy matrices from external memory. We also propose several methods to reduce energy table parameter size by 80%. Conclusion To our knowledge, our implementation with 16 PEs is the only FPGA accelerator implementing the complete RNAalifold algorithm. The experimental results show a factor of 12.2 speedup over the RNAalifold (ViennaPackage – 1.6.5) software for a group of aligned RNA sequences with 2981-residue running on a Personal Computer (PC) platform with Pentium 4 2.6 GHz CPU. PMID:19208138

A computer program for the calculation of the flow field in supersonic mixed-compression inlets at angle of attack using the three-dimensional method of characteristics with discrete shock wave fitting

NASA Technical Reports Server (NTRS)

Vadyak, J.; Hoffman, J. D.; Bishop, A. R.

1978-01-01

The calculation procedure is based on the method of characteristics for steady three-dimensional flow. The bow shock wave and the internal shock wave system were computed using a discrete shock wave fitting procedure. The general structure of the computer program is discussed, and a brief description of each subroutine is given. All program input parameters are defined, and a brief discussion on interpretation of the output is provided. A number of sample cases, complete with data deck listings, are presented.

Reduced-Order Models for the Aeroelastic Analysis of Ares Launch Vehicles

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Vatsa, Veer N.; Biedron, Robert T.

2010-01-01

This document presents the development and application of unsteady aerodynamic, structural dynamic, and aeroelastic reduced-order models (ROMs) for the ascent aeroelastic analysis of the Ares I-X flight test and Ares I crew launch vehicles using the unstructured-grid, aeroelastic FUN3D computational fluid dynamics (CFD) code. The purpose of this work is to perform computationally-efficient aeroelastic response calculations that would be prohibitively expensive via computation of multiple full-order aeroelastic FUN3D solutions. These efficient aeroelastic ROM solutions provide valuable insight regarding the aeroelastic sensitivity of the vehicles to various parameters over a range of dynamic pressures.

Topological methods for the comparison of structures using LDR-brachytherapy of the prostate as an example.

PubMed

Schiefer, H; von Toggenburg, F; Seelentag, W W; Plasswilm, L; Ries, G; Schmid, H-P; Leippold, T; Krusche, B; Roth, J; Engeler, D

2009-08-21

The dose coverage of low dose rate (LDR)-brachytherapy for localized prostate cancer is monitored 4-6 weeks after intervention by contouring the prostate on computed tomography and/or magnetic resonance imaging sets. Dose parameters for the prostate (V100, D90 and D80) provide information on the treatment quality. Those depend strongly on the delineation of the prostate contours. We therefore systematically investigated the contouring process for 21 patients with five examiners. The prostate structures were compared with one another using topological procedures based on Boolean algebra. The coincidence number C(V) measures the agreement between a set of structures. The mutual coincidence C(i, j) measures the agreement between two structures i and j, and the mean coincidence C(i) compares a selected structure i with the remaining structures in a set. All coincidence parameters have a value of 1 for complete coincidence of contouring and 0 for complete absence. The five patients with the lowest C(V) values were discussed, and rules for contouring the prostate have been formulated. The contouring and assessment were repeated after 3 months for the same five patients. All coincidence parameters have been improved after instruction. This shows objectively that training resulted in more consistent contouring across examiners.

GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models.

PubMed

Ligon, Thomas S; Fröhlich, Fabian; Chis, Oana T; Banga, Julio R; Balsa-Canto, Eva; Hasenauer, Jan

2018-04-15

Mathematical modeling using ordinary differential equations is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ordinary differential equation models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability). GenSSI 2.0 is the first toolbox for structural identifiability analysis to implement Systems Biology Markup Language import, state/parameter transformations and multi-experiment structural identifiability analysis. In addition, GenSSI 2.0 supports a range of MATLAB versions and is computationally more efficient than its previous version, enabling the analysis of more complex models. GenSSI 2.0 is an open-source MATLAB toolbox and available at https://github.com/genssi-developer/GenSSI. thomas.ligon@physik.uni-muenchen.de or jan.hasenauer@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

Bone volume fraction and structural parameters for estimation of mechanical stiffness and failure load of human cancellous bone samples; in-vitro comparison of ultrasound transit time spectroscopy and X-ray μCT.

PubMed

Alomari, Ali Hamed; Wille, Marie-Luise; Langton, Christian M

2018-02-01

Conventional mechanical testing is the 'gold standard' for assessing the stiffness (N mm -1 ) and strength (MPa) of bone, although it is not applicable in-vivo since it is inherently invasive and destructive. The mechanical integrity of a bone is determined by its quantity and quality; being related primarily to bone density and structure respectively. Several non-destructive, non-invasive, in-vivo techniques have been developed and clinically implemented to estimate bone density, both areal (dual-energy X-ray absorptiometry (DXA)) and volumetric (quantitative computed tomography (QCT)). Quantitative ultrasound (QUS) parameters of velocity and attenuation are dependent upon both bone quantity and bone quality, although it has not been possible to date to transpose one particular QUS parameter into separate estimates of quantity and quality. It has recently been shown that ultrasound transit time spectroscopy (UTTS) may provide an accurate estimate of bone density and hence quantity. We hypothesised that UTTS also has the potential to provide an estimate of bone structure and hence quality. In this in-vitro study, 16 human femoral bone samples were tested utilising three techniques; UTTS, micro computed tomography (μCT), and mechanical testing. UTTS was utilised to estimate bone volume fraction (BV/TV) and two novel structural parameters, inter-quartile range of the derived transit time (UTTS-IQR) and the transit time of maximum proportion of sonic-rays (TTMP). μCT was utilised to derive BV/TV along with several bone structure parameters. A destructive mechanical test was utilised to measure the stiffness and strength (failure load) of the bone samples. BV/TV was calculated from the derived transit time spectrum (TTS); the correlation coefficient (R 2 ) with μCT-BV/TV was 0.885. For predicting mechanical stiffness and strength, BV/TV derived by both μCT and UTTS provided the strongest correlation with mechanical stiffness (R 2 =0.567 and 0.618 respectively) and mechanical strength (R 2 =0.747 and 0.736 respectively). When respective structural parameters were incorporated to BV/TV, multiple regression analysis indicated that none of the μCT histomorphometric parameters could improve the prediction of mechanical stiffness and strength, while for UTTS, adding TTMP to BV/TV increased the prediction of mechanical stiffness to R 2 =0.711 and strength to R 2 =0.827. It is therefore envisaged that UTTS may have the ability to estimate BV/TV along with providing an improved prediction of osteoporotic fracture risk, within routine clinical practice in the future. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamical susceptibility near a long-wavelength critical point with a nonconserved order parameter

NASA Astrophysics Data System (ADS)

Klein, Avraham; Lederer, Samuel; Chowdhury, Debanjan; Berg, Erez; Chubukov, Andrey

2018-04-01

We study the dynamic response of a two-dimensional system of itinerant fermions in the vicinity of a uniform (Q =0 ) Ising nematic quantum critical point of d - wave symmetry. The nematic order parameter is not a conserved quantity, and this permits a nonzero value of the fermionic polarization in the d - wave channel even for vanishing momentum and finite frequency: Π (q =0 ,Ωm)≠0 . For weak coupling between the fermions and the nematic order parameter (i.e., the coupling is small compared to the Fermi energy), we perturbatively compute Π (q =0 ,Ωm)≠0 over a parametrically broad range of frequencies where the fermionic self-energy Σ (ω ) is irrelevant, and use Eliashberg theory to compute Π (q =0 ,Ωm) in the non-Fermi-liquid regime at smaller frequencies, where Σ (ω )>ω . We find that Π (q =0 ,Ω ) is a constant, plus a frequency-dependent correction that goes as |Ω | at high frequencies, crossing over to |Ω| 1 /3 at lower frequencies. The |Ω| 1 /3 scaling holds also in a non-Fermi-liquid regime. The nonvanishing of Π (q =0 ,Ω ) gives rise to additional structure in the imaginary part of the nematic susceptibility χ″(q ,Ω ) at Ω >vFq , in marked contrast to the behavior of the susceptibility for a conserved order parameter. This additional structure may be detected in Raman scattering experiments in the d - wave geometry.

High dimensional model representation method for fuzzy structural dynamics

NASA Astrophysics Data System (ADS)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

Structural, vibrational and nuclear magnetic resonance investigations of 4-bromoisoquinoline by experimental and theoretical DFT methods.

PubMed

Arjunan, V; Thillai Govindaraja, S; Jayapraksh, A; Mohan, S

2013-04-15

Quantum chemical calculations of energy, structural parameters and vibrational wavenumbers of 4-bromoisoquinoline (4BIQ) were carried out by using B3LYP method using 6-311++G(**), cc-pVTZ and LANL2DZ basis sets. The optimised geometrical parameters obtained by DFT calculations are in good agreement with electron diffraction data. Interpretations of the experimental FTIR and FT-Raman spectra have been reported with the aid of the theoretical wavenumbers. The differences between the observed and scaled wavenumber values of most of the fundamentals are very small. The thermodynamic parameters have also been computed. Electronic properties of the molecule were discussed through the molecular electrostatic potential surface, HOMO-LUMO energy gap and NBO analysis. To provide precise assignments of (1)H and (13)CNMR spectra, isotropic shielding and chemical shifts were calculated with the Gauge-Invariant Atomic Orbital (GIAO) method. Copyright © 2013 Elsevier B.V. All rights reserved.

Seismic and Restoration Assessment of Monumental Masonry Structures

PubMed Central

Asteris, Panagiotis G.; Douvika, Maria G.; Apostolopoulou, Maria; Moropoulou, Antonia

2017-01-01

Masonry structures are complex systems that require detailed knowledge and information regarding their response under seismic excitations. Appropriate modelling of a masonry structure is a prerequisite for a reliable earthquake-resistant design and/or assessment. However, modelling a real structure with a robust quantitative (mathematical) representation is a very difficult, complex and computationally-demanding task. The paper herein presents a new stochastic computational framework for earthquake-resistant design of masonry structural systems. The proposed framework is based on the probabilistic behavior of crucial parameters, such as material strength and seismic characteristics, and utilizes fragility analysis based on different failure criteria for the masonry material. The application of the proposed methodology is illustrated in the case of a historical and monumental masonry structure, namely the assessment of the seismic vulnerability of the Kaisariani Monastery, a byzantine church that was built in Athens, Greece, at the end of the 11th to the beginning of the 12th century. Useful conclusions are drawn regarding the effectiveness of the intervention techniques used for the reduction of the vulnerability of the case-study structure, by means of comparison of the results obtained. PMID:28767073

Seismic and Restoration Assessment of Monumental Masonry Structures.

PubMed

Asteris, Panagiotis G; Douvika, Maria G; Apostolopoulou, Maria; Moropoulou, Antonia

2017-08-02

Masonry structures are complex systems that require detailed knowledge and information regarding their response under seismic excitations. Appropriate modelling of a masonry structure is a prerequisite for a reliable earthquake-resistant design and/or assessment. However, modelling a real structure with a robust quantitative (mathematical) representation is a very difficult, complex and computationally-demanding task. The paper herein presents a new stochastic computational framework for earthquake-resistant design of masonry structural systems. The proposed framework is based on the probabilistic behavior of crucial parameters, such as material strength and seismic characteristics, and utilizes fragility analysis based on different failure criteria for the masonry material. The application of the proposed methodology is illustrated in the case of a historical and monumental masonry structure, namely the assessment of the seismic vulnerability of the Kaisariani Monastery, a byzantine church that was built in Athens, Greece, at the end of the 11th to the beginning of the 12th century. Useful conclusions are drawn regarding the effectiveness of the intervention techniques used for the reduction of the vulnerability of the case-study structure, by means of comparison of the results obtained.

Differentiating Dark Triad Traits Within and Across Interpersonal Circumplex Surfaces.

PubMed

Dowgwillo, Emily A; Pincus, Aaron L

2017-01-01

Recent discussions surrounding the Dark Triad (narcissism, psychopathy, and Machiavellianism) have centered on areas of distinctiveness and overlap. Given that interpersonal dysfunction is a core feature of Dark Triad traits, the current study uses self-report data from 562 undergraduate students to examine the interpersonal characteristics associated with narcissism, psychopathy, and Machiavellianism on four interpersonal circumplex (IPC) surfaces. The distinctiveness of these characteristics was examined using a novel bootstrapping methodology for computing confidence intervals around circumplex structural summary method parameters. Results suggest that Dark Triad traits exhibit distinct structural summary method parameters with narcissism characterized by high dominance, psychopathy characterized by a blend of high dominance and low affiliation, and Machiavellianism characterized by low affiliation on the problems, values, and efficacies IPC surfaces. Additionally, there was some heterogeneity in findings for different measures of psychopathy. Gender differences in structural summary parameters were examined, finding similar parameter values despite mean-level differences in Dark Triad traits. Finally, interpersonal information was integrated across different IPC surfaces to create profiles associated with each Dark Triad trait and to provide a more in-depth portrait of associated interpersonal dynamics. © The Author(s) 2016.

MS-CASPT2 study of hole transfer in guanine-indole complexes using the generalized Mulliken-Hush method: effective two-state treatment.

PubMed

Butchosa, C; Simon, S; Blancafort, L; Voityuk, A

2012-07-12

Because hole transfer from nucleobases to amino acid residues in DNA-protein complexes can prevent oxidative damage of DNA in living cells, computational modeling of the process is of high interest. We performed MS-CASPT2 calculations of several model structures of π-stacked guanine and indole and derived electron-transfer (ET) parameters for these systems using the generalized Mulliken-Hush (GMH) method. We show that the two-state model commonly applied to treat thermal ET between adjacent donor and acceptor is of limited use for the considered systems because of the small gap between the ground and first excited states in the indole radical cation. The ET parameters obtained within the two-state GMH scheme can deviate significantly from the corresponding matrix elements of the two-state effective Hamiltonian based on the GMH treatment of three adiabatic states. The computed values of diabatic energies and electronic couplings provide benchmarks to assess the performance of less sophisticated computational methods.

On-Line Mu Method for Robust Flutter Prediction in Expanding a Safe Flight Envelope for an Aircraft Model Under Flight Test

NASA Technical Reports Server (NTRS)

Lind, Richard C. (Inventor); Brenner, Martin J.

2001-01-01

A structured singular value (mu) analysis method of computing flutter margins has robust stability of a linear aeroelastic model with uncertainty operators (Delta). Flight data is used to update the uncertainty operators to accurately account for errors in the computed model and the observed range of aircraft dynamics of the aircraft under test caused by time-varying aircraft parameters, nonlinearities, and flight anomalies, such as test nonrepeatability. This mu-based approach computes predict flutter margins that are worst case with respect to the modeling uncertainty for use in determining when the aircraft is approaching a flutter condition and defining an expanded safe flight envelope for the aircraft that is accepted with more confidence than traditional methods that do not update the analysis algorithm with flight data by introducing mu as a flutter margin parameter that presents several advantages over tracking damping trends as a measure of a tendency to instability from available flight data.

Multi-Dielectric Brownian Dynamics and Design-Space-Exploration Studies of Permeation in Ion Channels.

PubMed

Siksik, May; Krishnamurthy, Vikram

2017-09-01

This paper proposes a multi-dielectric Brownian dynamics simulation framework for design-space-exploration (DSE) studies of ion-channel permeation. The goal of such DSE studies is to estimate the channel modeling-parameters that minimize the mean-squared error between the simulated and expected "permeation characteristics." To address this computational challenge, we use a methodology based on statistical inference that utilizes the knowledge of channel structure to prune the design space. We demonstrate the proposed framework and DSE methodology using a case study based on the KcsA ion channel, in which the design space is successfully reduced from a 6-D space to a 2-D space. Our results show that the channel dielectric map computed using the framework matches with that computed directly using molecular dynamics with an error of 7%. Finally, the scalability and resolution of the model used are explored, and it is shown that the memory requirements needed for DSE remain constant as the number of parameters (degree of heterogeneity) increases.

Optical signal processing using photonic reservoir computing

NASA Astrophysics Data System (ADS)

Salehi, Mohammad Reza; Dehyadegari, Louiza

2014-10-01

As a new approach to recognition and classification problems, photonic reservoir computing has such advantages as parallel information processing, power efficient and high speed. In this paper, a photonic structure has been proposed for reservoir computing which is investigated using a simple, yet, non-partial noisy time series prediction task. This study includes the application of a suitable topology with self-feedbacks in a network of SOA's - which lends the system a strong memory - and leads to adjusting adequate parameters resulting in perfect recognition accuracy (100%) for noise-free time series, which shows a 3% improvement over previous results. For the classification of noisy time series, the rate of accuracy showed a 4% increase and amounted to 96%. Furthermore, an analytical approach was suggested to solve rate equations which led to a substantial decrease in the simulation time, which is an important parameter in classification of large signals such as speech recognition, and better results came up compared with previous works.

Clinical cone beam computed tomography compared to high-resolution peripheral computed tomography in the assessment of distal radius bone.

PubMed

de Charry, C; Boutroy, S; Ellouz, R; Duboeuf, F; Chapurlat, R; Follet, H; Pialat, J B

2016-10-01

Clinical cone beam computed tomography (CBCT) was compared to high-resolution peripheral quantitative computed tomography (HR-pQCT) for the assessment of ex vivo radii. Strong correlations were found for geometry, volumetric density, and trabecular structure. Using CBCT, bone architecture assessment was feasible but compared to HR-pQCT, trabecular parameters were overestimated whereas cortical ones were underestimated. HR-pQCT is the most widely used technique to assess bone microarchitecture in vivo. Yet, this technology has been only applicable at peripheral sites, in only few research centers. Clinical CBCT is more widely available but quantitative assessment of the bone structure is usually not performed. We aimed to compare the assessment of bone structure with CBCT (NewTom 5G, QR, Verona, Italy) and HR-pQCT (XtremeCT, Scanco Medical AG, Brüttisellen, Switzerland). Twenty-four distal radius specimens were scanned with these two devices with a reconstructed voxel size of 75 μm for Newtom 5G and 82 μm for XtremeCT, respectively. A rescaling-registration scheme was used to define the common volume of interest. Cortical and trabecular compartments were separated using a semiautomated double contouring method. Density and microstructure were assessed with the HR-pQCT software on both modality images. Strong correlations were found for geometry parameters (r = 0.98-0.99), volumetric density (r = 0.91-0.99), and trabecular structure (r = 0.94-0.99), all p < 0.001. Correlations were lower for cortical microstructure (r = 0.80-0.89), p < 0.001. However, absolute differences were observed between modalities for all parameters, with an overestimation of the trabecular structure (trabecular number, 1.62 ± 0.37 vs. 1.47 ± 0.36 mm(-1)) and an underestimation of the cortical microstructure (cortical porosity, 3.3 ± 1.3 vs. 4.4 ± 1.4 %) assessed on CBCT images compared to HR-pQCT images. Clinical CBCT devices are able to analyze large portions of distal bones with good spatial resolution and limited irradiation. However, compared to dedicated HR-pQCT, the assessment of microarchitecture by NewTom 5G dental CBCT showed some discrepancies, for density measurements mainly. Further technical developments are required to reach optimal assessment of bone characteristics.

Probabilistic inspection strategies for minimizing service failures

NASA Technical Reports Server (NTRS)

Brot, Abraham

1994-01-01

The INSIM computer program is described which simulates the 'limited fatigue life' environment in which aircraft structures generally operate. The use of INSIM to develop inspection strategies which aim to minimize service failures is demonstrated. Damage-tolerance methodology, inspection thresholds and customized inspections are simulated using the probability of failure as the driving parameter.

Hydrodynamic resistance parameters for ErPr rare-earth regenerator material under steady and periodic flow conditions

NASA Astrophysics Data System (ADS)

Pathak, M. G.; Helvensteijn, B. P.; Patel, V. C.; Ghiaasiaan, S. M.; Mulcahey, T. I.; Kashani, A.; Feller, J. R.

2014-01-01

The regenerator, typically a microporous structure that is subject to periodic flow of a cryogenic fluid, is a critical component of pulse tube or Stirling cryocoolers, which are widely used for high-demand aerospace and defense applications. In this investigation, experiments were conducted in which steady and oscillatory flows of helium were imposed on ErPr rare-Earth regenerator filler material and mass flow and pressure drop data were recorded under ambient temperature conditions. A computational fluid dynamics (CFD)-assisted method was applied for the analysis and interpretation of the experimental data. The permeability and inertial coefficients that lead to agreement between the experimental data and computational simulations were iteratively obtained. The Darcy permeability and Forchheimer inertial coefficients were obtained and were found to be functions of the system charge pressure, operating frequency, and compressor piston stroke within the studied range of interest. The results also exhibit that the periodic flow hydrodynamic resistance parameters are in general different than steady flow parameters.

Improved inference in Bayesian segmentation using Monte Carlo sampling: application to hippocampal subfield volumetry.

PubMed

Iglesias, Juan Eugenio; Sabuncu, Mert Rory; Van Leemput, Koen

2013-10-01

Many segmentation algorithms in medical image analysis use Bayesian modeling to augment local image appearance with prior anatomical knowledge. Such methods often contain a large number of free parameters that are first estimated and then kept fixed during the actual segmentation process. However, a faithful Bayesian analysis would marginalize over such parameters, accounting for their uncertainty by considering all possible values they may take. Here we propose to incorporate this uncertainty into Bayesian segmentation methods in order to improve the inference process. In particular, we approximate the required marginalization over model parameters using computationally efficient Markov chain Monte Carlo techniques. We illustrate the proposed approach using a recently developed Bayesian method for the segmentation of hippocampal subfields in brain MRI scans, showing a significant improvement in an Alzheimer's disease classification task. As an additional benefit, the technique also allows one to compute informative "error bars" on the volume estimates of individual structures. Copyright © 2013 Elsevier B.V. All rights reserved.

Improved Inference in Bayesian Segmentation Using Monte Carlo Sampling: Application to Hippocampal Subfield Volumetry

PubMed Central

Iglesias, Juan Eugenio; Sabuncu, Mert Rory; Leemput, Koen Van

2013-01-01

Many segmentation algorithms in medical image analysis use Bayesian modeling to augment local image appearance with prior anatomical knowledge. Such methods often contain a large number of free parameters that are first estimated and then kept fixed during the actual segmentation process. However, a faithful Bayesian analysis would marginalize over such parameters, accounting for their uncertainty by considering all possible values they may take. Here we propose to incorporate this uncertainty into Bayesian segmentation methods in order to improve the inference process. In particular, we approximate the required marginalization over model parameters using computationally efficient Markov chain Monte Carlo techniques. We illustrate the proposed approach using a recently developed Bayesian method for the segmentation of hippocampal subfields in brain MRI scans, showing a significant improvement in an Alzheimer’s disease classification task. As an additional benefit, the technique also allows one to compute informative “error bars” on the volume estimates of individual structures. PMID:23773521

A dimension-wise analysis method for the structural-acoustic system with interval parameters

NASA Astrophysics Data System (ADS)

Xu, Menghui; Du, Jianke; Wang, Chong; Li, Yunlong

2017-04-01

The interval structural-acoustic analysis is mainly accomplished by interval and subinterval perturbation methods. Potential limitations for these intrusive methods include overestimation or interval translation effect for the former and prohibitive computational cost for the latter. In this paper, a dimension-wise analysis method is thus proposed to overcome these potential limitations. In this method, a sectional curve of the system response surface along each input dimensionality is firstly extracted, the minimal and maximal points of which are identified based on its Legendre polynomial approximation. And two input vectors, i.e. the minimal and maximal input vectors, are dimension-wisely assembled by the minimal and maximal points of all sectional curves. Finally, the lower and upper bounds of system response are computed by deterministic finite element analysis at the two input vectors. Two numerical examples are studied to demonstrate the effectiveness of the proposed method and show that, compared to the interval and subinterval perturbation method, a better accuracy is achieved without much compromise on efficiency by the proposed method, especially for nonlinear problems with large interval parameters.

A computational investigation on the structure, global parameters and antioxidant capacity of a polyphenol, Gallic acid.

PubMed

Rajan, Vijisha K; Muraleedharan, K

2017-04-01

A computational DFT-B3LYP structural analysis of a poly phenol, Gallic acid (GA) has been performed by using 6-311++ G (df, p) basis set. The GA is a relatively stable molecule with considerable radical scavenging capacity. It is a well known antioxidant. The NBO analysis shows that the aromatic system is delocalized. The results reveal that the most stable radical is formed at O 3 -atom upon scavenging the free radicals. Global descriptive parameters show that GA acts as an acceptor center in charge transfer complex formation which is supported by ESP and contour diagrams and also by Q max value. The GA is a good antioxidant and it can be better understood by HAT and TMC mechanisms as it has low BDE, ΔH acidity and ΔG acidity values. The ΔBDE and ΔAIP values also confirm that the antioxidant capacity of GA can be explained through HAT rather than the SET-PT mechanism. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structural analysis of three space crane articulated-truss joint concepts

NASA Technical Reports Server (NTRS)

Wu, K. Chauncey; Sutter, Thomas R.

1992-01-01

Three space crane articulated truss joint concepts are studied to evaluate their static structural performance over a range of geometric design parameters. Emphasis is placed on maintaining the four longeron reference truss performance across the joint while allowing large angle articulation. A maximum positive articulation angle and the actuator length ratio required to reach the angle are computed for each concept as the design parameters are varied. Configurations with a maximum articulation angle less than 120 degrees or actuators requiring a length ratio over two are not considered. Tip rotation and lateral deflection of a truss beam with an articulated truss joint at the midspan are used to select a point design for each concept. Deflections for one point design are up to 40 percent higher than for the other two designs. Dynamic performance of the three point design is computed as a function of joint articulation angle. The two lowest frequencies of each point design are relatively insensitive to large variations in joint articulation angle. One point design has a higher maximum tip velocity for the emergency stop than the other designs.

Lanthanide and transition metal complexes of bioactive coumarins: molecular modeling and spectroscopic studies.

PubMed

Georgieva, I; Mihaylov, Tz; Trendafilova, N

2014-06-01

The present paper summarizes theoretical and spectroscopic investigations on a series of active coumarins and their lanthanide and transition metal complexes with application in medicine and pharmacy. Molecular modeling as well as IR, Raman, NMR and electronic spectral simulations at different levels of theory were performed to obtain important molecular descriptors: total energy, formation energy, binding energy, stability, conformations, structural parameters, electron density distribution, molecular electrostatic potential, Fukui functions, atomic charges, and reactive indexes. The computations are performed both in gas phase and in solution with consideration of the solvent effect on the molecular structural and energetic parameters. The investigations have shown that the advanced computational methods are reliable for prediction of the metal-coumarin binding mode, electron density distribution, thermodynamic properties as well as the strength and nature of the metal-coumarin interaction (not experimentally accessible) and correctly interpret the experimental spectroscopic data. Known results from biological tests for cytotoxic, antimicrobial, anti-fungal, spasmolytic and anti-HIV activities on the studied metal complexes are reported and discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

A closed-form solution to tensor voting: theory and applications.

PubMed

Wu, Tai-Pang; Yeung, Sai-Kit; Jia, Jiaya; Tang, Chi-Keung; Medioni, Gérard

2012-08-01

We prove a closed-form solution to tensor voting (CFTV): Given a point set in any dimensions, our closed-form solution provides an exact, continuous, and efficient algorithm for computing a structure-aware tensor that simultaneously achieves salient structure detection and outlier attenuation. Using CFTV, we prove the convergence of tensor voting on a Markov random field (MRF), thus termed as MRFTV, where the structure-aware tensor at each input site reaches a stationary state upon convergence in structure propagation. We then embed structure-aware tensor into expectation maximization (EM) for optimizing a single linear structure to achieve efficient and robust parameter estimation. Specifically, our EMTV algorithm optimizes both the tensor and fitting parameters and does not require random sampling consensus typically used in existing robust statistical techniques. We performed quantitative evaluation on its accuracy and robustness, showing that EMTV performs better than the original TV and other state-of-the-art techniques in fundamental matrix estimation for multiview stereo matching. The extensions of CFTV and EMTV for extracting multiple and nonlinear structures are underway.

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection

PubMed Central

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close “neighborhood” of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa. PMID:26327290

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection.

PubMed

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.

Acoustic environmental accuracy requirements for response determination

NASA Technical Reports Server (NTRS)

Pettitt, M. R.

1983-01-01

A general purpose computer program was developed for the prediction of vehicle interior noise. This program, named VIN, has both modal and statistical energy analysis capabilities for structural/acoustic interaction analysis. The analytic models and their computer implementation were verified through simple test cases with well-defined experimental results. The model was also applied in a space shuttle payload bay launch acoustics prediction study. The computer program processes large and small problems with equal efficiency because all arrays are dynamically sized by program input variables at run time. A data base is built and easily accessed for design studies. The data base significantly reduces the computational costs of such studies by allowing the reuse of the still-valid calculated parameters of previous iterations.

Robust Flutter Margin Analysis that Incorporates Flight Data

NASA Technical Reports Server (NTRS)

Lind, Rick; Brenner, Martin J.

1998-01-01

An approach for computing worst-case flutter margins has been formulated in a robust stability framework. Uncertainty operators are included with a linear model to describe modeling errors and flight variations. The structured singular value, mu, computes a stability margin that directly accounts for these uncertainties. This approach introduces a new method of computing flutter margins and an associated new parameter for describing these margins. The mu margins are robust margins that indicate worst-case stability estimates with respect to the defined uncertainty. Worst-case flutter margins are computed for the F/A-18 Systems Research Aircraft using uncertainty sets generated by flight data analysis. The robust margins demonstrate flight conditions for flutter may lie closer to the flight envelope than previously estimated by p-k analysis.

Determination of strain fields in porous shape memory alloys using micro-computed tomography

NASA Astrophysics Data System (ADS)

Bormann, Therese; Friess, Sebastian; de Wild, Michael; Schumacher, Ralf; Schulz, Georg; Müller, Bert

2010-09-01

Shape memory alloys (SMAs) belong to 'intelligent' materials since the metal alloy can change its macroscopic shape as the result of the temperature-induced, reversible martensite-austenite phase transition. SMAs are often applied for medical applications such as stents, hinge-less instruments, artificial muscles, and dental braces. Rapid prototyping techniques, including selective laser melting (SLM), allow fabricating complex porous SMA microstructures. In the present study, the macroscopic shape changes of the SMA test structures fabricated by SLM have been investigated by means of micro computed tomography (μCT). For this purpose, the SMA structures are placed into the heating stage of the μCT system SkyScan 1172™ (SkyScan, Kontich, Belgium) to acquire three-dimensional datasets above and below the transition temperature, i.e. at room temperature and at about 80°C, respectively. The two datasets were registered on the basis of an affine registration algorithm with nine independent parameters - three for the translation, three for the rotation and three for the scaling in orthogonal directions. Essentially, the scaling parameters characterize the macroscopic deformation of the SMA structure of interest. Furthermore, applying the non-rigid registration algorithm, the three-dimensional strain field of the SMA structure on the micrometer scale comes to light. The strain fields obtained will serve for the optimization of the SLM-process and, more important, of the design of the complex shaped SMA structures for tissue engineering and medical implants.

Fluid–Structure Interaction Analysis of Papillary Muscle Forces Using a Comprehensive Mitral Valve Model with 3D Chordal Structure

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

Toma, Milan; Jensen, Morten Ø.; Einstein, Daniel R.

2015-07-17

Numerical models of native heart valves are being used to study valve biomechanics to aid design and development of repair procedures and replacement devices. These models have evolved from simple two-dimensional approximations to complex three-dimensional, fully coupled fluid-structure interaction (FSI) systems. Such simulations are useful for predicting the mechanical and hemodynamic loading on implanted valve devices. A current challenge for improving the accuracy of these predictions is choosing and implementing modeling boundary conditions. In order to address this challenge, we are utilizing an advanced in-vitro system to validate FSI conditions for the mitral valve system. Explanted ovine mitral valves weremore » mounted in an in vitro setup, and structural data for the mitral valve was acquired with *CT. Experimental data from the in-vitro ovine mitral valve system were used to validate the computational model. As the valve closes, the hemodynamic data, high speed lea et dynamics, and force vectors from the in-vitro system were compared to the results of the FSI simulation computational model. The total force of 2.6 N per papillary muscle is matched by the computational model. In vitro and in vivo force measurements are important in validating and adjusting material parameters in computational models. The simulations can then be used to answer questions that are otherwise not possible to investigate experimentally. This work is important to maximize the validity of computational models of not just the mitral valve, but any biomechanical aspect using computational simulation in designing medical devices.« less

Fluid-Structure Interaction Analysis of Papillary Muscle Forces Using a Comprehensive Mitral Valve Model with 3D Chordal Structure.

PubMed

Toma, Milan; Jensen, Morten Ø; Einstein, Daniel R; Yoganathan, Ajit P; Cochran, Richard P; Kunzelman, Karyn S

2016-04-01

Numerical models of native heart valves are being used to study valve biomechanics to aid design and development of repair procedures and replacement devices. These models have evolved from simple two-dimensional approximations to complex three-dimensional, fully coupled fluid-structure interaction (FSI) systems. Such simulations are useful for predicting the mechanical and hemodynamic loading on implanted valve devices. A current challenge for improving the accuracy of these predictions is choosing and implementing modeling boundary conditions. In order to address this challenge, we are utilizing an advanced in vitro system to validate FSI conditions for the mitral valve system. Explanted ovine mitral valves were mounted in an in vitro setup, and structural data for the mitral valve was acquired with [Formula: see text]CT. Experimental data from the in vitro ovine mitral valve system were used to validate the computational model. As the valve closes, the hemodynamic data, high speed leaflet dynamics, and force vectors from the in vitro system were compared to the results of the FSI simulation computational model. The total force of 2.6 N per papillary muscle is matched by the computational model. In vitro and in vivo force measurements enable validating and adjusting material parameters to improve the accuracy of computational models. The simulations can then be used to answer questions that are otherwise not possible to investigate experimentally. This work is important to maximize the validity of computational models of not just the mitral valve, but any biomechanical aspect using computational simulation in designing medical devices.

Atomic Decay Data for Modeling K Lines of Iron Peak and Light Odd-Z Elements*

NASA Technical Reports Server (NTRS)

Palmeri, P.; Quinet, P.; Mendoza, C.; Bautista, M. A.; Garcia, J.; Witthoeft, M. C.; Kallman, T. R.

2012-01-01

Complete data sets of level energies, transition wavelengths, A-values, radiative and Auger widths and fluorescence yields for K-vacancy levels of the F, Na, P, Cl, K, Sc, Ti, V, Cr, Mn, Co, Cu and Zn isonuclear sequences have been computed by a Hartree-Fock method that includes relativistic corrections as implemented in Cowan's atomic structure computer suite. The atomic parameters for more than 3 million fine-structure K lines have been determined. Ions with electron number N greater than 9 are treated for the first time, and detailed comparisons with available measurements and theoretical data for ions with N less than or equal to 9 are carried out in order to estimate reliable accuracy ratings.

Material and Thickness Grading for Aeroelastic Tailoring of the Common Research Model Wing Box

NASA Technical Reports Server (NTRS)

Stanford, Bret K.; Jutte, Christine V.

2014-01-01

This work quantifies the potential aeroelastic benefits of tailoring a full-scale wing box structure using tailored thickness distributions, material distributions, or both simultaneously. These tailoring schemes are considered for the wing skins, the spars, and the ribs. Material grading utilizes a spatially-continuous blend of two metals: Al and Al+SiC. Thicknesses and material fraction variables are specified at the 4 corners of the wing box, and a bilinear interpolation is used to compute these parameters for the interior of the planform. Pareto fronts detailing the conflict between static aeroelastic stresses and dynamic flutter boundaries are computed with a genetic algorithm. In some cases, a true material grading is found to be superior to a single-material structure.

Robust prediction of consensus secondary structures using averaged base pairing probability matrices.

PubMed

Kiryu, Hisanori; Kin, Taishin; Asai, Kiyoshi

2007-02-15

Recent transcriptomic studies have revealed the existence of a considerable number of non-protein-coding RNA transcripts in higher eukaryotic cells. To investigate the functional roles of these transcripts, it is of great interest to find conserved secondary structures from multiple alignments on a genomic scale. Since multiple alignments are often created using alignment programs that neglect the special conservation patterns of RNA secondary structures for computational efficiency, alignment failures can cause potential risks of overlooking conserved stem structures. We investigated the dependence of the accuracy of secondary structure prediction on the quality of alignments. We compared three algorithms that maximize the expected accuracy of secondary structures as well as other frequently used algorithms. We found that one of our algorithms, called McCaskill-MEA, was more robust against alignment failures than others. The McCaskill-MEA method first computes the base pairing probability matrices for all the sequences in the alignment and then obtains the base pairing probability matrix of the alignment by averaging over these matrices. The consensus secondary structure is predicted from this matrix such that the expected accuracy of the prediction is maximized. We show that the McCaskill-MEA method performs better than other methods, particularly when the alignment quality is low and when the alignment consists of many sequences. Our model has a parameter that controls the sensitivity and specificity of predictions. We discussed the uses of that parameter for multi-step screening procedures to search for conserved secondary structures and for assigning confidence values to the predicted base pairs. The C++ source code that implements the McCaskill-MEA algorithm and the test dataset used in this paper are available at http://www.ncrna.org/papers/McCaskillMEA/. Supplementary data are available at Bioinformatics online.

Autonomous Modal Identification of the Space Shuttle Tail Rudder

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; James, George H., III; Zimmerman, David C.

1997-01-01

Autonomous modal identification automates the calculation of natural vibration frequencies, damping, and mode shapes of a structure from experimental data. This technology complements damage detection techniques that use continuous or periodic monitoring of vibration characteristics. The approach shown in the paper incorporates the Eigensystem Realization Algorithm (ERA) as a data analysis engine and an autonomous supervisor to condense multiple estimates of modal parameters using ERA's Consistent-Mode Indicator and correlation of mode shapes. The procedure was applied to free-decay responses of a Space Shuttle tail rudder and successfully identified the seven modes of the structure below 250 Hz. The final modal parameters are a condensed set of results for 87 individual ERA cases requiring approximately five minutes of CPU time on a DEC Alpha computer.

Evolution of structure and reactivity in a series of iconic carbenes.

PubMed

Zhang, Min; Moss, Robert A; Thompson, Jack; Krogh-Jespersen, Karsten

2012-01-20

We present experimental activation parameters for the reactions of six carbenes (CCl(2), CClF, CF(2), ClCOMe, FCOMe, and (MeO)(2)C) with six alkenes (tetramethylethylene, cyclohexene, 1-hexene, methyl acrylate, acrylonitrile, and α-chloroacrylonitrile). Activation energies range from -1 kcal/mol for the addition of CCl(2) to tetramethylethylene to 11 kcal/mol for the addition of FCOMe to acrylonitrile. A generally satisfactory analysis of major trends in the evolution of carbenic structure and reactivity is afforded by qualitative applications of frontier molecular orbital theory, although the observed entropies of activation appear to fall in a counterintuitive pattern. An analysis of computed cyclopropanation transition state parameters reveals significant nucleophilic selectivity of (MeO)(2)C toward α-chloroacrylonitrile.

A comparative study of experimental and simulated ultrasonic pulse-echo signals from multilayered structures

NASA Technical Reports Server (NTRS)

Abedin, M. N.; Prabhu, D. R.; Winfree, W. P.; Johnston, P. H.

1992-01-01

The effect on the system acoustic response of variations in the adhesive thickness, coupling thickness, and paint thickness is considered. Both simulations and experimental measurements are used to characterize and classify A-scans from test regions, and to study the effects of various parameters such as paint thickness and epoxy thickness on the variations in the reflected signals. A 1D model of sound propagation in multilayered structures is used to verify the validity of the measured signals, and is also used to computationally generate signals for a class of test locations with gradually varying parameters. This approach exploits the ability of numerical simulations to provide a good understanding of the ultrasonic pulses reflected at disbonds.

Approximated maximum likelihood estimation in multifractal random walks

NASA Astrophysics Data System (ADS)

Løvsletten, O.; Rypdal, M.

2012-04-01

We present an approximated maximum likelihood method for the multifractal random walk processes of [E. Bacry , Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.64.026103 64, 026103 (2001)]. The likelihood is computed using a Laplace approximation and a truncation in the dependency structure for the latent volatility. The procedure is implemented as a package in the r computer language. Its performance is tested on synthetic data and compared to an inference approach based on the generalized method of moments. The method is applied to estimate parameters for various financial stock indices.

Predicting loop–helix tertiary structural contacts in RNA pseudoknots

PubMed Central

Cao, Song; Giedroc, David P.; Chen, Shi-Jie

2010-01-01

Tertiary interactions between loops and helical stems play critical roles in the biological function of many RNA pseudoknots. However, quantitative predictions for RNA tertiary interactions remain elusive. Here we report a statistical mechanical model for the prediction of noncanonical loop–stem base-pairing interactions in RNA pseudoknots. Central to the model is the evaluation of the conformational entropy for the pseudoknotted folds with defined loop–stem tertiary structural contacts. We develop an RNA virtual bond-based conformational model (Vfold model), which permits a rigorous computation of the conformational entropy for a given fold that contains loop–stem tertiary contacts. With the entropy parameters predicted from the Vfold model and the energy parameters for the tertiary contacts as inserted parameters, we can then predict the RNA folding thermodynamics, from which we can extract the tertiary contact thermodynamic parameters from theory–experimental comparisons. These comparisons reveal a contact enthalpy (ΔH) of −14 kcal/mol and a contact entropy (ΔS) of −38 cal/mol/K for a protonated C+•(G–C) base triple at pH 7.0, and (ΔH = −7 kcal/mol, ΔS = −19 cal/mol/K) for an unprotonated base triple. Tests of the model for a series of pseudoknots show good theory–experiment agreement. Based on the extracted energy parameters for the tertiary structural contacts, the model enables predictions for the structure, stability, and folding pathways for RNA pseudoknots with known or postulated loop–stem tertiary contacts from the nucleotide sequence alone. PMID:20100813

An information driven strategy to support multidisciplinary design

NASA Technical Reports Server (NTRS)

Rangan, Ravi M.; Fulton, Robert E.

1990-01-01

The design of complex engineering systems such as aircraft, automobiles, and computers is primarily a cooperative multidisciplinary design process involving interactions between several design agents. The common thread underlying this multidisciplinary design activity is the information exchange between the various groups and disciplines. The integrating component in such environments is the common data and the dependencies that exist between such data. This may be contrasted to classical multidisciplinary analyses problems where there is coupling between distinct design parameters. For example, they may be expressed as mathematically coupled relationships between aerodynamic and structural interactions in aircraft structures, between thermal and structural interactions in nuclear plants, and between control considerations and structural interactions in flexible robots. These relationships provide analytical based frameworks leading to optimization problem formulations. However, in multidisciplinary design problems, information based interactions become more critical. Many times, the relationships between different design parameters are not amenable to analytical characterization. Under such circumstances, information based interactions will provide the best integration paradigm, i.e., there is a need to model the data entities and their dependencies between design parameters originating from different design agents. The modeling of such data interactions and dependencies forms the basis for integrating the various design agents.

A Probabilistic Design Method Applied to Smart Composite Structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1995-01-01

A probabilistic design method is described and demonstrated using a smart composite wing. Probabilistic structural design incorporates naturally occurring uncertainties including those in constituent (fiber/matrix) material properties, fabrication variables, structure geometry and control-related parameters. Probabilistic sensitivity factors are computed to identify those parameters that have a great influence on a specific structural reliability. Two performance criteria are used to demonstrate this design methodology. The first criterion requires that the actuated angle at the wing tip be bounded by upper and lower limits at a specified reliability. The second criterion requires that the probability of ply damage due to random impact load be smaller than an assigned value. When the relationship between reliability improvement and the sensitivity factors is assessed, the results show that a reduction in the scatter of the random variable with the largest sensitivity factor (absolute value) provides the lowest failure probability. An increase in the mean of the random variable with a negative sensitivity factor will reduce the failure probability. Therefore, the design can be improved by controlling or selecting distribution parameters associated with random variables. This can be implemented during the manufacturing process to obtain maximum benefit with minimum alterations.

Force Limited Vibration Testing: Computation C2 for Real Load and Probabilistic Source

NASA Astrophysics Data System (ADS)

Wijker, J. J.; de Boer, A.; Ellenbroek, M. H. M.

2014-06-01

To prevent over-testing of the test-item during random vibration testing Scharton proposed and discussed the force limited random vibration testing (FLVT) in a number of publications, in which the factor C2 is besides the random vibration specification, the total mass and the turnover frequency of the load(test item), a very important parameter. A number of computational methods to estimate C2 are described in the literature, i.e. the simple and the complex two degrees of freedom system, STDFS and CTDFS, respectively. Both the STDFS and the CTDFS describe in a very reduced (simplified) manner the load and the source (adjacent structure to test item transferring the excitation forces, i.e. spacecraft supporting an instrument).The motivation of this work is to establish a method for the computation of a realistic value of C2 to perform a representative random vibration test based on force limitation, when the adjacent structure (source) description is more or less unknown. Marchand formulated a conservative estimation of C2 based on maximum modal effective mass and damping of the test item (load) , when no description of the supporting structure (source) is available [13].Marchand discussed the formal description of getting C 2 , using the maximum PSD of the acceleration and maximum PSD of the force, both at the interface between load and source, in combination with the apparent mass and total mass of the the load. This method is very convenient to compute the factor C 2 . However, finite element models are needed to compute the spectra of the PSD of both the acceleration and force at the interface between load and source.Stevens presented the coupled systems modal approach (CSMA), where simplified asparagus patch models (parallel-oscillator representation) of load and source are connected, consisting of modal effective masses and the spring stiffnesses associated with the natural frequencies. When the random acceleration vibration specification is given the CMSA method is suitable to compute the valueof the parameter C 2 .When no mathematical model of the source can be made available, estimations of the value C2 can be find in literature.In this paper a probabilistic mathematical representation of the unknown source is proposed, such that the asparagus patch model of the source can be approximated. The computation of the value C2 can be done in conjunction with the CMSA method, knowing the apparent mass of the load and the random acceleration specification at the interface between load and source, respectively.Strength & stiffness design rules for spacecraft, instrumentation, units, etc. will be practiced, as mentioned in ECSS Standards and Handbooks, Launch Vehicle User's manuals, papers, books , etc. A probabilistic description of the design parameters is foreseen.As an example a simple experiment has been worked out.

A computer program for the calculation of the flow field including boundary layer effects for mixed-compression inlets at angle of attack

NASA Technical Reports Server (NTRS)

Vadyak, J.; Hoffman, J. D.

1982-01-01

A computer program was developed which is capable of calculating the flow field in the supersonic portion of a mixed compression aircraft inlet operating at angle of attack. The supersonic core flow is computed using a second-order three dimensional method-of-characteristics algorithm. The bow shock and the internal shock train are treated discretely using a three dimensional shock fitting procedure. The boundary layer flows are computed using a second-order implicit finite difference method. The shock wave-boundary layer interaction is computed using an integral formulation. The general structure of the computer program is discussed, and a brief description of each subroutine is given. All program input parameters are defined, and a brief discussion on interpretation of the output is provided. A number of sample cases, complete with data listings, are provided.

Robust controller design for flexible structures using normalized coprime factor plant descriptions

NASA Technical Reports Server (NTRS)

Armstrong, Ernest S.

1993-01-01

Stabilization is a fundamental requirement in the design of feedback compensators for flexible structures. The search for the largest neighborhood around a given design plant for which a single controller produces closed-loop stability can be formulated as an H(sub infinity) control problem. The use of normalized coprime factor plant descriptions, in which the plant perturbations are defined as additive modifications to the coprime factors, leads to a closed-form expression for the maximum neighborhood boundary allowing optimal and suboptimal H(sub infinity) compensators to be computed directly without the usual gamma iteration. A summary of the theory on robust stabilization using normalized coprime factor plant descriptions is presented, and the application of the theory to the computation of robustly stable compensators for the phase version of the Control-Structures Interaction (CSI) Evolutionary Model is described. Results from the application indicate that the suboptimal version of the theory has the potential of providing the bases for the computation of low-authority compensators that are robustly stable to expected variations in design model parameters and additive unmodeled dynamics.

Polymerization and Structure of Bio-Based Plastics: A Computer Simulation

NASA Astrophysics Data System (ADS)

Khot, Shrikant N.; Wool, Richard P.

2001-03-01

We recently examined several hundred chemical pathways to convert chemically functionalized plant oil triglycerides, monoglycerides and reactive diluents into high performance plastics with a broad range of properties (US Patent No. 6,121,398). The resulting polymers had linear, branched, light- and highly-crosslinked chain architectures and could be used as pressure sensitive adhesives, elastomers and high performance rigid thermoset composite resins. To optimize the molecular design and minimize the number of chemical trials in this system with excess degrees of freedom, we developed a computer simulation of the free radical polymerization process. The triglyceride structure, degree of chemical substitution, mole fractions, fatty acid distribution function, and reaction kinetic parameters were used as initial inputs on a 3d lattice simulation. The evolution of the network fractal structure was computed and used to measure crosslink density, dangling ends, degree of reaction and defects in the lattice. The molecular connectivity was used to determine strength via a vector percolation model of fracture. The simulation permitted the optimal design of new bio-based materials with respect to monomer selection, cure reaction conditions and desired properties. Supported by the National Science Foundation

A general software reliability process simulation technique

NASA Technical Reports Server (NTRS)

Tausworthe, Robert C.

1991-01-01

The structure and rationale of the generalized software reliability process, together with the design and implementation of a computer program that simulates this process are described. Given assumed parameters of a particular project, the users of this program are able to generate simulated status timelines of work products, numbers of injected anomalies, and the progress of testing, fault isolation, repair, validation, and retest. Such timelines are useful in comparison with actual timeline data, for validating the project input parameters, and for providing data for researchers in reliability prediction modeling.

Control of linear uncertain systems utilizing mismatched state observers

NASA Technical Reports Server (NTRS)

Goldstein, B.

1972-01-01

The control of linear continuous dynamical systems is investigated as a problem of limited state feedback control. The equations which describe the structure of an observer are developed constrained to time-invarient systems. The optimal control problem is formulated, accounting for the uncertainty in the design parameters. Expressions for bounds on closed loop stability are also developed. The results indicate that very little uncertainty may be tolerated before divergence occurs in the recursive computation algorithms, and the derived stability bound yields extremely conservative estimates of regions of allowable parameter variations.

Multiple robustness in factorized likelihood models.

PubMed

Molina, J; Rotnitzky, A; Sued, M; Robins, J M

2017-09-01

We consider inference under a nonparametric or semiparametric model with likelihood that factorizes as the product of two or more variation-independent factors. We are interested in a finite-dimensional parameter that depends on only one of the likelihood factors and whose estimation requires the auxiliary estimation of one or several nuisance functions. We investigate general structures conducive to the construction of so-called multiply robust estimating functions, whose computation requires postulating several dimension-reducing models but which have mean zero at the true parameter value provided one of these models is correct.

LASER APPLICATIONS AND OTHER TOPICS IN QUANTUM ELECTRONICS: Nanosize relief: from phase masks to antireflection coatings on quartz and silicon

NASA Astrophysics Data System (ADS)

Verevkin, Yu K.; Klimov, A. Yu; Gribkov, B. A.; Petryakov, V. N.; Koposova, E. V.; Olaizola, Santiago M.

2008-11-01

By using the interference of pulsed radiation and a complete lithographic cycle, phase masks on quartz and antireflection structures on quartz and silicon are produced. The transmission of radiation through a corrugated vacuum—solid interface is calculated by solving rigorously an integral equation with the help of a computer program for parameters close to experimental parameters. The results of measurements are in good agreement with calculations. The methods developed in the paper can be used for manufacturing optical and semiconductor devices.

Study of MoNbO(y) (y = 2-5) anion and neutral clusters using photoelectron spectroscopy and density functional theory calculations: impact of spin contamination on single point calculations.

PubMed

Waller, Sarah E; Mann, Jennifer E; Rothgeb, David W; Jarrold, Caroline C

2012-10-04

Results of a study combining anion photoelectron spectroscopy and density functional theory calculations on the heteronuclear MoNbO(y)(-) (y = 2-5) transition metal suboxide cluster series are reported and analyzed. The photoelectron spectra, which exhibit broad electronic bands with partially resolved vibrational structure, were compared to spectral simulations generated from calculated spectroscopic parameters for all computationally determined energetically competitive structures. Although computational results on the less oxidized clusters could not be satisfactorily reconciled with experimental spectra, possibly because of heavy spin contamination found in a large portion of the computational results, the results suggest that (1) neutral cluster electron affinity is a strong indicator of whether O-atoms are bound in M-O-M bridge positions or M═O terminal positions, (2) MoNbO(y) anions and neutrals have structures that can be described as intermediate with respect to the unary (homonuclear) Mo(2)O(y) and Nb(2)O(y) clusters, and (3) structures in which O-atoms preferentially bind to the Nb center are slightly more stable than alternative structures. Several challenges associated with the calculations are considered, including spin contamination, which appears to cause spurious single point calculations used to determine vertical detachment energies.

Comparison of measured and computed Strehl ratios for light propagated through a channel flow of a He N 2 mixing layer at high Reynolds numbers

NASA Astrophysics Data System (ADS)

Gardner, Patrick J.; Roggemann, Michael C.; Welsh, Byron M.; Bowersox, Rodney D.; Luke, Theodore E.

1997-04-01

A lateral shearing interferometer was used to measure the slope of perturbed wave fronts after they propagated through a He N 2 mixing layer in a rectangular channel. Slope measurements were used to reconstruct the phase of the turbulence-corrupted wave front. The random phase fluctuations induced by the mixing layer were captured in a large ensemble of wave-front measurements. Phase structure functions, computed from the reconstructed phase surfaces, were stationary in first increments. A five-thirds power law is shown to fit streamwise and cross-stream slices of the structure function, analogous to the Kolmogorov model for isotropic turbulence, which describes the structure function with a single parameter. Strehl ratios were computed from the phase structure functions and compared with a measured experiment obtained from simultaneous point-spread function measurements. Two additional Strehl ratios were calculated by using classical estimates that assume statistical isotropy throughout the flow. The isotropic models are a reasonable estimate of the optical degradation only within a few centimeters of the initial mixing, where the Reynolds number is low. At higher Reynolds numbers, Strehl ratios calculated from the structure functions match the experiment much better than Strehl ratio calculations that assume isotropic flow.

3DNALandscapes: a database for exploring the conformational features of DNA.

PubMed

Zheng, Guohui; Colasanti, Andrew V; Lu, Xiang-Jun; Olson, Wilma K

2010-01-01

3DNALandscapes, located at: http://3DNAscapes.rutgers.edu, is a new database for exploring the conformational features of DNA. In contrast to most structural databases, which archive the Cartesian coordinates and/or derived parameters and images for individual structures, 3DNALandscapes enables searches of conformational information across multiple structures. The database contains a wide variety of structural parameters and molecular images, computed with the 3DNA software package and known to be useful for characterizing and understanding the sequence-dependent spatial arrangements of the DNA sugar-phosphate backbone, sugar-base side groups, base pairs, base-pair steps, groove structure, etc. The data comprise all DNA-containing structures--both free and bound to proteins, drugs and other ligands--currently available in the Protein Data Bank. The web interface allows the user to link, report, plot and analyze this information from numerous perspectives and thereby gain insight into DNA conformation, deformability and interactions in different sequence and structural contexts. The data accumulated from known, well-resolved DNA structures can serve as useful benchmarks for the analysis and simulation of new structures. The collective data can also help to understand how DNA deforms in response to proteins and other molecules and undergoes conformational rearrangements.

Structural elucidation of antihemorrhage drug molecule Diethylammonium 2,5-dihydroxybenzene sulfonate - an insilico approach

NASA Astrophysics Data System (ADS)

Kumar, S. Anil; Bhaskar, BL

2018-02-01

Ab-initio computational study of antihemorrhage drug molecule diethylammonium 2,5-dihydroxybenzene sulfonate, popularly known as ethamsylate, has been attempted using Gaussian 09. The optimized molecular geometry has been envisaged using density functional theory method at B3LYP/6-311 basis set. Different geometrical parameters like bond lengths and bond angles were computed and compared against the experimental results available in literature. Fourier transform infrared scanning of the title molecule was performed and vibrational frequencies were also computed using Gaussian software. The presence of O-H---O hydrogen bonds between C6H5O5S- anions and N-H---O hydrogen bonds between anion and cation is evident in the computational studies also. In general, satisfactory agreement of concordance has been observed between computational and experimental results.

Role of IAC in large space systems thermal analysis

NASA Technical Reports Server (NTRS)

Jones, G. K.; Skladany, J. T.; Young, J. P.

1982-01-01

Computer analysis programs to evaluate critical coupling effects that can significantly influence spacecraft system performance are described. These coupling effects arise from the varied parameters of the spacecraft systems, environments, and forcing functions associated with disciplines such as thermal, structures, and controls. Adverse effects can be expected to significantly impact system design aspects such as structural integrity, controllability, and mission performance. One such needed design analysis capability is a software system that can integrate individual discipline computer codes into a highly user-oriented/interactive-graphics-based analysis capability. The integrated analysis capability (IAC) system can be viewed as: a core framework system which serves as an integrating base whereby users can readily add desired analysis modules and as a self-contained interdisciplinary system analysis capability having a specific set of fully integrated multidisciplinary analysis programs that deal with the coupling of thermal, structures, controls, antenna radiation performance, and instrument optical performance disciplines.

The vehicle design evaluation program - A computer-aided design procedure for transport aircraft

NASA Technical Reports Server (NTRS)

Oman, B. H.; Kruse, G. S.; Schrader, O. E.

1977-01-01

The vehicle design evaluation program is described. This program is a computer-aided design procedure that provides a vehicle synthesis capability for vehicle sizing, external load analysis, structural analysis, and cost evaluation. The vehicle sizing subprogram provides geometry, weight, and balance data for aircraft using JP, hydrogen, or methane fuels. The structural synthesis subprogram uses a multistation analysis for aerodynamic surfaces and fuselages to develop theoretical weights and geometric dimensions. The parts definition subprogram uses the geometric data from the structural analysis and develops the predicted fabrication dimensions, parts material raw stock buy requirements, and predicted actual weights. The cost analysis subprogram uses detail part data in conjunction with standard hours, realization factors, labor rates, and material data to develop the manufacturing costs. The program is used to evaluate overall design effects on subsonic commercial type aircraft due to parameter variations.

The ambivalent effect of lattice structure on a spatial game

NASA Astrophysics Data System (ADS)

Zhang, Hui; Gao, Meng; Li, Zizhen; Maa, Zhihui; Wang, Hailong

2011-06-01

The evolution of cooperation is studied in lattice-structured populations, in which each individual who adopts one of the following strategies ‘always defect' (ALLD), ‘tit-for-tat' (TFT), and ‘always cooperate' (ALLC) plays the repeated Prisoner's Dilemma game with its neighbors according to an asynchronous update rule. Computer simulations are applied to analyse the dynamics depending on major parameters. Mathematical analyses based on invasion probability analysis, mean-field approximation, as well as pair approximation are also used. We find that the lattice structure promotes the evolution of cooperation compared with a non-spatial population, this is also confirmed by invasion probability analysis in one dimension. Meanwhile, it also inhibits the evolution of cooperation due to the advantage of being spiteful, which indicates the key role of specific life-history assumptions. Mean-field approximation fails to predict the outcome of computer simulations. Pair approximation is accurate in two dimensions but fails in one dimension.

Damage level prediction of non-reshaped berm breakwater using ANN, SVM and ANFIS models

NASA Astrophysics Data System (ADS)

Mandal, Sukomal; Rao, Subba; N., Harish; Lokesha

2012-06-01

The damage analysis of coastal structure is very important as it involves many design parameters to be considered for the better and safe design of structure. In the present study experimental data for non-reshaped berm breakwater are collected from Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, NITK, Surathkal, India. Soft computing techniques like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference system (ANFIS) models are constructed using experimental data sets to predict the damage level of non-reshaped berm breakwater. The experimental data are used to train ANN, SVM and ANFIS models and results are determined in terms of statistical measures like mean square error, root mean square error, correla-tion coefficient and scatter index. The result shows that soft computing techniques i.e., ANN, SVM and ANFIS can be efficient tools in predicting damage levels of non reshaped berm breakwater.

Hot, cold, and annual reference atmospheres for Edwards Air Force Base, California (1975 version)

NASA Technical Reports Server (NTRS)

Johnson, D. L.

1975-01-01

Reference atmospheres pertaining to summer (hot), winter (cold), and mean annual conditions for Edwards Air Force Base, California, are presented from surface to 90 km altitude (700 km for the annual model). Computed values of pressure, kinetic temperature, virtual temperature, and density and relative differences percentage departure from the Edwards reference atmospheres, 1975 (ERA-75) of the atmospheric parameters versus altitude are tabulated in 250 m increments. Hydrostatic and gas law equations were used in conjunction with radiosonde and rocketsonde thermodynamic data in determining the vertical structure of these atmospheric models. The thermodynamic parameters were all subjected to a fifth degree least-squares curve-fit procedure, and the resulting coefficients were incorporated into Univac 1108 computer subroutines so that any quantity may be recomputed at any desired altitude using these subroutines.

Global identifiability of linear compartmental models--a computer algebra algorithm.

PubMed

Audoly, S; D'Angiò, L; Saccomani, M P; Cobelli, C

1998-01-01

A priori global identifiability deals with the uniqueness of the solution for the unknown parameters of a model and is, thus, a prerequisite for parameter estimation of biological dynamic models. Global identifiability is however difficult to test, since it requires solving a system of algebraic nonlinear equations which increases both in nonlinearity degree and number of terms and unknowns with increasing model order. In this paper, a computer algebra tool, GLOBI (GLOBal Identifiability) is presented, which combines the topological transfer function method with the Buchberger algorithm, to test global identifiability of linear compartmental models. GLOBI allows for the automatic testing of a priori global identifiability of general structure compartmental models from general multi input-multi output experiments. Examples of usage of GLOBI to analyze a priori global identifiability of some complex biological compartmental models are provided.

Examination of the nature of lattice matched III V semiconductor interfaces using computer simulated molecular beam epitaxial growth I. AC/BC interfaces

NASA Astrophysics Data System (ADS)

Thomsen, M.; Ghaisas, S. V.; Madhukar, A.

1987-07-01

A previously developed computer simulation of molecular beam epitaxial growth of III-V semiconductors based on the configuration dependent reactive incorporation (CDRI) model is extended to allow for two different cation species. Attention is focussed on examining the nature of interfaces formed in lattice matched quantum well structures of the form AC/BC/AC(100). We consider cation species with substantially different effective diffusion lengths, as is the case with Al and Ga during the growth of their respective As compounds. The degree of intermixing occuring at the interface is seen to be dependent upon, among other growth parameters, the pressure of the group V species during growth. Examination of an intraplanar order parameter at the interfaces reveals the existence of short range clustering of the cation species.

Applying a Particle-only Model to the HL Tau Disk

NASA Astrophysics Data System (ADS)

Tabeshian, Maryam; Wiegert, Paul A.

2018-04-01

Observations have revealed rich structures in protoplanetary disks, offering clues about their embedded planets. Due to the complexities introduced by the abundance of gas in these disks, modeling their structure in detail is computationally intensive, requiring complex hydrodynamic codes and substantial computing power. It would be advantageous if computationally simpler models could provide some preliminary information on these disks. Here we apply a particle-only model (that we developed for gas-poor debris disks) to the gas-rich disk, HL Tauri, to address the question of whether such simple models can inform the study of these systems. Assuming three potentially embedded planets, we match HL Tau’s radial profile fairly well and derive best-fit planetary masses and orbital radii (0.40, 0.02, 0.21 Jupiter masses for the planets orbiting a 0.55 M ⊙ star at 11.22, 29.67, 64.23 au). Our derived parameters are comparable to those estimated by others, except for the mass of the second planet. Our simulations also reproduce some narrower gaps seen in the ALMA image away from the orbits of the planets. The nature of these gaps is debated but, based on our simulations, we argue they could result from planet–disk interactions via mean-motion resonances, and need not contain planets. Our results suggest that a simple particle-only model can be used as a first step to understanding dynamical structures in gas disks, particularly those formed by planets, and determine some parameters of their hidden planets, serving as useful initial inputs to hydrodynamic models which are needed to investigate disk and planet properties more thoroughly.

Finite frequency shear wave splitting tomography: a model space search approach

NASA Astrophysics Data System (ADS)

Mondal, P.; Long, M. D.

2017-12-01

Observations of seismic anisotropy provide key constraints on past and present mantle deformation. A common method for upper mantle anisotropy is to measure shear wave splitting parameters (delay time and fast direction). However, the interpretation is not straightforward, because splitting measurements represent an integration of structure along the ray path. A tomographic approach that allows for localization of anisotropy is desirable; however, tomographic inversion for anisotropic structure is a daunting task, since 21 parameters are needed to describe general anisotropy. Such a large parameter space does not allow a straightforward application of tomographic inversion. Building on previous work on finite frequency shear wave splitting tomography, this study aims to develop a framework for SKS splitting tomography with a new parameterization of anisotropy and a model space search approach. We reparameterize the full elastic tensor, reducing the number of parameters to three (a measure of strength based on symmetry considerations for olivine, plus the dip and azimuth of the fast symmetry axis). We compute Born-approximation finite frequency sensitivity kernels relating model perturbations to splitting intensity observations. The strong dependence of the sensitivity kernels on the starting anisotropic model, and thus the strong non-linearity of the inverse problem, makes a linearized inversion infeasible. Therefore, we implement a Markov Chain Monte Carlo technique in the inversion procedure. We have performed tests with synthetic data sets to evaluate computational costs and infer the resolving power of our algorithm for synthetic models with multiple anisotropic layers. Our technique can resolve anisotropic parameters on length scales of ˜50 km for realistic station and event configurations for dense broadband experiments. We are proceeding towards applications to real data sets, with an initial focus on the High Lava Plains of Oregon.

Decentralized digital adaptive control of robot motion

NASA Technical Reports Server (NTRS)

Tarokh, M.

1990-01-01

A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.

Fatigue-Crack-Growth Structural Analysis

NASA Technical Reports Server (NTRS)

Newman, J. C., Jr.

1986-01-01

Elastic and plastic deformations calculated under variety of loading conditions. Prediction of fatigue-crack-growth lives made with FatigueCrack-Growth Structural Analysis (FASTRAN) computer program. As cyclic loads are applied to initial crack configuration, FASTRAN predicts crack length and other parameters until complete break occurs. Loads are tensile or compressive and of variable or constant amplitude. FASTRAN incorporates linear-elastic fracture mechanics with modifications of load-interaction effects caused by crack closure. FASTRAN considered research tool, because of lengthy calculation times. FASTRAN written in FORTRAN IV for batch execution.

Ab-initio study of electronic structure and elastic properties of ZrC

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

Mund, H. S., E-mail: hmoond@gmail.com; Ahuja, B. L.

2016-05-23

The electronic and elastic properties of ZrC have been investigated using the linear combination of atomic orbitals method within the framework of density functional theory. Different exchange-correlation functionals are taken into account within generalized gradient approximation. We have computed energy bands, density of states, elastic constants, bulk modulus, shear modulus, Young’s modulus, Poisson’s ratio, lattice parameters and pressure derivative of the bulk modulus by calculating ground state energy of the rock salt structure type ZrC.

Biologically important conformational features of DNA as interpreted by quantum mechanics and molecular mechanics computations of its simple fragments.

PubMed

Poltev, V; Anisimov, V M; Dominguez, V; Gonzalez, E; Deriabina, A; Garcia, D; Rivas, F; Polteva, N A

2018-02-01

Deciphering the mechanism of functioning of DNA as the carrier of genetic information requires identifying inherent factors determining its structure and function. Following this path, our previous DFT studies attributed the origin of unique conformational characteristics of right-handed Watson-Crick duplexes (WCDs) to the conformational profile of deoxydinucleoside monophosphates (dDMPs) serving as the minimal repeating units of DNA strand. According to those findings, the directionality of the sugar-phosphate chain and the characteristic ranges of dihedral angles of energy minima combined with the geometric differences between purines and pyrimidines determine the dependence on base sequence of the three-dimensional (3D) structure of WCDs. This work extends our computational study to complementary deoxydinucleotide-monophosphates (cdDMPs) of non-standard conformation, including those of Z-family, Hoogsteen duplexes, parallel-stranded structures, and duplexes with mispaired bases. For most of these systems, except Z-conformation, computations closely reproduce experimental data within the tolerance of characteristic limits of dihedral parameters for each conformation family. Computation of cdDMPs with Z-conformation reveals that their experimental structures do not correspond to the internal energy minimum. This finding establishes the leading role of external factors in formation of the Z-conformation. Energy minima of cdDMPs of non-Watson-Crick duplexes demonstrate different sequence-dependence features than those known for WCDs. The obtained results provide evidence that the biologically important regularities of 3D structure distinguish WCDs from duplexes having non-Watson-Crick nucleotide pairing.

Computational modeling of electrically conductive networks formed by graphene nanoplatelet-carbon nanotube hybrid particles

NASA Astrophysics Data System (ADS)

Mora, A.; Han, F.; Lubineau, G.

2018-04-01

One strategy to ensure that nanofiller networks in a polymer composite percolate at low volume fractions is to promote segregation. In a segregated structure, the concentration of nanofillers is kept low in some regions of the sample. In turn, the concentration in the remaining regions is much higher than the average concentration of the sample. This selective placement of the nanofillers ensures percolation at low average concentration. One original strategy to promote segregation is by tuning the shape of the nanofillers. We use a computational approach to study the conductive networks formed by hybrid particles obtained by growing carbon nanotubes (CNTs) on graphene nanoplatelets (GNPs). The objective of this study is (1) to show that the higher electrical conductivity of these composites is due to the hybrid particles forming a segregated structure and (2) to understand which parameters defining the hybrid particles determine the efficiency of the segregation. We construct a microstructure to observe the conducting paths and determine whether a segregated structure has indeed been formed inside the composite. A measure of efficiency is presented based on the fraction of nanofillers that contribute to the conductive network. Then, the efficiency of the hybrid-particle networks is compared to those of three other networks of carbon-based nanofillers in which no hybrid particles are used: only CNTs, only GNPs, and a mix of CNTs and GNPs. Finally, some parameters of the hybrid particle are studied: the CNT density on the GNPs, and the CNT and GNP geometries. We also present recommendations for the further improvement of a composite’s conductivity based on these parameters.

Ab Initio Molecular Dynamics Simulations and GIPAW NMR Calculations of a Lithium Borate Glass Melt.

PubMed

Ohkubo, Takahiro; Tsuchida, Eiji; Takahashi, Takafumi; Iwadate, Yasuhiko

2016-04-14

The atomic structure of a molten 0.3Li2O-0.7B2O3 glass at 1250 K was investigated using ab initio molecular dynamics (AIMD) simulations. The gauge including projector augmented wave (GIPAW) method was then employed for computing the chemical shift and quadrupolar coupling constant of (11)B, (17)O, and (7)Li from 764 AIMD derived structures. The chemical shift and quadrupolar coupling constant distributions were directly estimated from the dynamical structure of the molten glass. (11)B NMR parameters of well-known structural units such as the three-coordinated ring, nonring, and four-coordinated tetrahedron were found to be in good agreement with the experimental results. In this study, more detailed classification of B units was presented based on the number of O species bonded to the B atoms. This highlights the limitations of (11)B NMR sensitivity for resolving (11)B local environment using the experimentally obtained spectra only. The (17)O NMR parameter distributions can theoretically resolve the bridging and nonbridging O atoms with different structural units such as nonring, single boroxol ring, and double boroxol ring. Slight but clear differences in the number of bridging O atoms surrounding Li that have not been reported experimentally were observed in the theoretically obtained (7)Li NMR parameters.

Applications of AMPS-1D for solar cell simulation

NASA Astrophysics Data System (ADS)

Zhu, Hong; Kalkan, Ali Kaan; Hou, Jingya; Fonash, Stephen J.

1999-03-01

The AMPS-1D PC computer program is now used by over 70 groups world-wide for detector and solar cell analysis. It has proved to be a very powerful tool in understanding device operation and physics for single crystal, poly-crystalline and amorphous structures. For example, AMPS-1D has been successful in explaining the "red kink" [1] and the "transient effect" in CdS/CIGS poly-crystalline solar cells. It has been used to show that thin film poly-Si structures, with reasonable light trapping, are capable of competitive solar cell conversion efficiencies. In the case of a-Si:H structures, it has been used, for example, to settle the discrepancies in bandgap measurement, to predict the effective QE>1 phenomenon later seen in these materials [2], to determine the relative roles of interface and bulk properties, and to point the direction toward 16% triple junction structures. In general AMPS-1D is used for cell and detector design, material parameter sensitivity studies, and parameter extraction. Recently we have shown that it can be used to determine optimum structure and light and voltage biasing conditions in the material parameter extraction function. Information on AMPS can be found at www.psu.edu/dept/AMPS/amps_web/AMPS.html and at other web sites set up by user groups.

Kron-Branin modelling of ultra-short pulsed signal microelectrode

NASA Astrophysics Data System (ADS)

Xu, Zhifei; Ravelo, Blaise; Liu, Yang; Zhao, Lu; Delaroche, Fabien; Vurpillot, Francois

2018-06-01

An uncommon circuit modelling of microelectrode for ultra-short signal propagation is developed. The proposed model is based on the Tensorial Analysis of Network (TAN) using the Kron-Branin (KB) formalism. The systemic graph topology equivalent to the considered structure problem is established by assuming as unknown variables the branch currents. The TAN mathematical solution is determined after the KB characteristic matrix identification. The TAN can integrate various structure physical parameters. As proof of concept, via hole ended microelectrodes implemented on Kapton substrate were designed, fabricated and tested. The 0.1-MHz-to-6-GHz S-parameter KB model, simulation and measurement are in good agreement. In addition, time-domain analyses with nanosecond duration pulse signals were carried out to predict the microelectrode signal integrity. The modelled microstrip electrode is usually integrated in the atom probe tomography. The proposed unfamiliar KB method is particularly beneficial with respect to the computation speed and adaptability to various structures.

Method for computationally efficient design of dielectric laser accelerator structures

DOE PAGES

Hughes, Tyler; Veronis, Georgios; Wootton, Kent P.; ...

2017-06-22

Here, dielectric microstructures have generated much interest in recent years as a means of accelerating charged particles when powered by solid state lasers. The acceleration gradient (or particle energy gain per unit length) is an important figure of merit. To design structures with high acceleration gradients, we explore the adjoint variable method, a highly efficient technique used to compute the sensitivity of an objective with respect to a large number of parameters. With this formalism, the sensitivity of the acceleration gradient of a dielectric structure with respect to its entire spatial permittivity distribution is calculated by the use of onlymore » two full-field electromagnetic simulations, the original and ‘adjoint’. The adjoint simulation corresponds physically to the reciprocal situation of a point charge moving through the accelerator gap and radiating. Using this formalism, we perform numerical optimizations aimed at maximizing acceleration gradients, which generate fabricable structures of greatly improved performance in comparison to previously examined geometries.« less

Synthesis, spectral, structural prediction and computational studies of octylcarbazole ornamented 3-phenothiazinal

NASA Astrophysics Data System (ADS)

Karuppasamy, Ayyanar; Udhaya kumar, Chandran; Karthikeyan, Subramanian; Velayutham Pillai, Muthiah Pillai; Ramalingan, Chennan

2017-11-01

A novel conjugated octylcarbazole ornamented 3-phenothiazinal, 10-(9-octyl-9H-carbazol-3-yl)-10H-phenothiazine-3-carbaldehyde (OCPTC) was synthesized and fully characterized by 1H-NMR, 13C-NMR, elemental and single crystal XRD analyses. The optimized geometrical structure, vibrational frequencies and NMR have been computed with M06-2X method using 6-31+G(d,p) basis set. Total electronic energies and HOMO-LUMO energy gaps in gas phase are discussed. The geometrical parameters of the title compound obtained from single crystal XRD studies have been found in accord with the calculated (DFT) values. The experimental and theoretical FT-IR and NMR results of the title molecule have been investigated. The experimentally observed vibrational frequencies have been compared with the calculated ones, which are in good agreement with each other. Single crystal X-ray structural analysis of OCPTC, evidences the ''butterfly conformation'' of phenothiazine ring with nearly perpendicular orientation of the carbazole structural motif to the phenothiazine moiety.

Complex basis functions for molecular resonances: Methodology and applications

NASA Astrophysics Data System (ADS)

White, Alec; McCurdy, C. William; Head-Gordon, Martin

The computation of positions and widths of metastable electronic states is a challenge for molecular electronic structure theory because, in addition to the difficulty of the many-body problem, such states obey scattering boundary conditions. These resonances cannot be addressed with naïve application of traditional bound state electronic structure theory. Non-Hermitian electronic structure methods employing complex basis functions is one way that we may rigorously treat resonances within the framework of traditional electronic structure theory. In this talk, I will discuss our recent work in this area including the methodological extension from single determinant SCF-based approaches to highly correlated levels of wavefunction-based theory such as equation of motion coupled cluster and many-body perturbation theory. These approaches provide a hierarchy of theoretical methods for the computation of positions and widths of molecular resonances. Within this framework, we may also examine properties of resonances including the dependence of these parameters on molecular geometry. Some applications of these methods to temporary anions and dianions will also be discussed.

Discrete particle model for cement infiltration within open-cell structures: Prevention of osteoporotic fracture.

PubMed

Ramos-Infante, Samuel Jesús; Ten-Esteve, Amadeo; Alberich-Bayarri, Angel; Pérez, María Angeles

2018-01-01

This paper proposes a discrete particle model based on the random-walk theory for simulating cement infiltration within open-cell structures to prevent osteoporotic proximal femur fractures. Model parameters consider the cement viscosity (high and low) and the desired direction of injection (vertical and diagonal). In vitro and in silico characterizations of augmented open-cell structures validated the computational model and quantified the improved mechanical properties (Young's modulus) of the augmented specimens. The cement injection pattern was successfully predicted in all the simulated cases. All the augmented specimens exhibited enhanced mechanical properties computationally and experimentally (maximum improvements of 237.95 ± 12.91% and 246.85 ± 35.57%, respectively). The open-cell structures with high porosity fraction showed a considerable increase in mechanical properties. Cement augmentation in low porosity fraction specimens resulted in a lesser increase in mechanical properties. The results suggest that the proposed discrete particle model is adequate for use as a femoroplasty planning framework.

Design Aids for Real-Time Systems (DARTS)

NASA Technical Reports Server (NTRS)

Szulewski, P. A.

1982-01-01

Design-Aids for Real-Time Systems (DARTS) is a tool that assists in defining embedded computer systems through tree structured graphics, military standard documentation support, and various analyses including automated Software Science parameter counting and metrics calculation. These analyses provide both static and dynamic design quality feedback which can potentially aid in producing efficient, high quality software systems.

Evaluation of Available Software for Reconstruction of a Structure from its Imagery

DTIC Science & Technology

2017-04-01

Math . 2, 164–168. Lowe, D. G. (1999) Object recognition from local scale-invariant features, in Proc. Int. Conf. Computer Vision, Vol. 2, pp. 1150–1157...Marquardt, D. (1963) An algorithm for least-squares estimation of nonlinear parameters, SIAM J. Appl. Math . 11(2), 431–441. UNCLASSIFIED 11 DST-Group–TR

Tokamak experimental power reactor conceptual design. Volume II

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

Not Available

1976-08-01

Volume II contains the following appendices: (1) summary of EPR design parameters, (2) impurity control, (3) plasma computational models, (4) structural support system, (5) materials considerations for the primary energy conversion system, (6) magnetics, (7) neutronics penetration analysis, (8) first wall stress analysis, (9) enrichment of isotopes of hydrogen by cryogenic distillation, and (10) noncircular plasma considerations. (MOW)

Constraints on the Computation of Rigid Motion Parameters from Retinal Displacements.

DTIC Science & Technology

1985-10-01

field (two temporall . proximal frames) is, in general, ambiguous. two frames can recover structure "hen the moing surface satisfies the conditions of...8217(i.b) Furthermore the following identity holds Z(X + SX, . + 6 Y) = z(x + ax . + 6)’) (iii) Using the Taylor series expansion of the above Z(X + 8X Y

Interaction of Simple Ions with Water: Theoretical Models for the Study of Ion Hydration

ERIC Educational Resources Information Center

Gancheff, Jorge S.; Kremer, Carlos; Ventura, Oscar N.

2009-01-01

A computational experiment aimed to create and systematically analyze models of simple cation hydrates is presented. The changes in the structure (bond distances and angles) and the electronic density distribution of the solvent and the thermodynamic parameters of the hydration process are calculated and compared with the experimental data. The…

Earth and ocean modeling

NASA Technical Reports Server (NTRS)

Knezovich, F. M.

1976-01-01

A modular structured system of computer programs is presented utilizing earth and ocean dynamical data keyed to finitely defined parameters. The model is an assemblage of mathematical algorithms with an inherent capability of maturation with progressive improvements in observational data frequencies, accuracies and scopes. The Eom in its present state is a first-order approach to a geophysical model of the earth's dynamics.

nu-TRLan User Guide Version 1.0: A High-Performance Software Package for Large-Scale Harmitian Eigenvalue Problems

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

Yamazaki, Ichitaro; Wu, Kesheng; Simon, Horst

2008-10-27

The original software package TRLan, [TRLan User Guide], page 24, implements the thick restart Lanczos method, [Wu and Simon 2001], page 24, for computing eigenvalues {lambda} and their corresponding eigenvectors v of a symmetric matrix A: Av = {lambda}v. Its effectiveness in computing the exterior eigenvalues of a large matrix has been demonstrated, [LBNL-42982], page 24. However, its performance strongly depends on the user-specified dimension of a projection subspace. If the dimension is too small, TRLan suffers from slow convergence. If it is too large, the computational and memory costs become expensive. Therefore, to balance the solution convergence and costs,more » users must select an appropriate subspace dimension for each eigenvalue problem at hand. To free users from this difficult task, nu-TRLan, [LNBL-1059E], page 23, adjusts the subspace dimension at every restart such that optimal performance in solving the eigenvalue problem is automatically obtained. This document provides a user guide to the nu-TRLan software package. The original TRLan software package was implemented in Fortran 90 to solve symmetric eigenvalue problems using static projection subspace dimensions. nu-TRLan was developed in C and extended to solve Hermitian eigenvalue problems. It can be invoked using either a static or an adaptive subspace dimension. In order to simplify its use for TRLan users, nu-TRLan has interfaces and features similar to those of TRLan: (1) Solver parameters are stored in a single data structure called trl-info, Chapter 4 [trl-info structure], page 7. (2) Most of the numerical computations are performed by BLAS, [BLAS], page 23, and LAPACK, [LAPACK], page 23, subroutines, which allow nu-TRLan to achieve optimized performance across a wide range of platforms. (3) To solve eigenvalue problems on distributed memory systems, the message passing interface (MPI), [MPI forum], page 23, is used. The rest of this document is organized as follows. In Chapter 2 [Installation], page 2, we provide an installation guide of the nu-TRLan software package. In Chapter 3 [Example], page 3, we present a simple nu-TRLan example program. In Chapter 4 [trl-info structure], page 7, and Chapter 5 [trlan subroutine], page 14, we describe the solver parameters and interfaces in detail. In Chapter 6 [Solver parameters], page 21, we discuss the selection of the user-specified parameters. In Chapter 7 [Contact information], page 22, we give the acknowledgements and contact information of the authors. In Chapter 8 [References], page 23, we list reference to related works.« less

Unit cell geometry of multiaxial preforms for structural composites

NASA Technical Reports Server (NTRS)

Ko, Frank; Lei, Charles; Rahman, Anisur; Du, G. W.; Cai, Yun-Jia

1993-01-01

The objective of this study is to investigate the yarn geometry of multiaxial preforms. The importance of multiaxial preforms for structural composites is well recognized by the industry but, to exploit their full potential, engineering design rules must be established. This study is a step in that direction. In this work the preform geometry for knitted and braided preforms was studied by making a range of well designed samples and studying them by photo microscopy. The structural geometry of the preforms is related to the processing parameters. Based on solid modeling and B-spline methodology a software package is developed. This computer code enables real time structural representations of complex fiber architecture based on the rule of preform manufacturing. The code has the capability of zooming and section plotting. These capabilities provide a powerful means to study the effect of processing variables on the preform geometry. the code also can be extended to an auto mesh generator for downstream structural analysis using finite element method. This report is organized into six sections. In the first section the scope and background of this work is elaborated. In section two the unit cell geometries of braided and multi-axial warp knitted preforms is discussed. The theoretical frame work of yarn path modeling and solid modeling is presented in section three. The thin section microscopy carried out to observe the structural geometry of the preforms is the subject in section four. The structural geometry is related to the processing parameters in section five. Section six documents the implementation of the modeling techniques into the computer code MP-CAD. A user manual for the software is also presented here. The source codes and published papers are listed in the Appendices.

Correlation strength, Lifshitz transition, and the emergence of a two-dimensional to three-dimensional crossover in FeSe under pressure

NASA Astrophysics Data System (ADS)

Skornyakov, S. L.; Anisimov, V. I.; Vollhardt, D.; Leonov, I.

2018-03-01

We report a detailed theoretical study of the electronic structure, spectral properties, and lattice parameters of bulk FeSe under pressure using a fully charge self-consistent implementation of the density functional theory plus dynamical mean-field theory method (DFT+DMFT). In particular, we perform a structural optimization and compute the evolution of the lattice parameters (volume, c /a ratio, and the internal z position of Se) and the electronic structure of the tetragonal (space group P 4 /n m m ) unit cell of paramagnetic FeSe. Our results for the lattice parameters obtained by structural optimization using DFT+DMFT are in good quantitative agreement with experiment, implying a crucial importance of electron correlations in determining the correct lattice properties of FeSe. Most importantly, upon compression to 10 GPa our results reveal a topological change in the Fermi surface (Lifshitz transition) which is accompanied by a two- to three-dimensional crossover and a small reduction of the quasiparticle mass renormalization compared to ambient pressure. The behavior of the momentum-resolved magnetic susceptibility χ (q ) shows no topological changes of magnetic correlations under pressure but demonstrates a reduction of the degree of the in-plane (π ,π ) stripe-type nesting. Our results for the electronic structure and lattice parameters of FeSe are in good qualitative agreement with recent experiments on its isoelectronic counterpart FeSe1 -xSx .

CUDA-based acceleration and BPN-assisted automation of bilateral filtering for brain MR image restoration.

PubMed

Chang, Herng-Hua; Chang, Yu-Ning

2017-04-01

Bilateral filters have been substantially exploited in numerous magnetic resonance (MR) image restoration applications for decades. Due to the deficiency of theoretical basis on the filter parameter setting, empirical manipulation with fixed values and noise variance-related adjustments has generally been employed. The outcome of these strategies is usually sensitive to the variation of the brain structures and not all the three parameter values are optimal. This article is in an attempt to investigate the optimal setting of the bilateral filter, from which an accelerated and automated restoration framework is developed. To reduce the computational burden of the bilateral filter, parallel computing with the graphics processing unit (GPU) architecture is first introduced. The NVIDIA Tesla K40c GPU with the compute unified device architecture (CUDA) functionality is specifically utilized to emphasize thread usages and memory resources. To correlate the filter parameters with image characteristics for automation, optimal image texture features are subsequently acquired based on the sequential forward floating selection (SFFS) scheme. Subsequently, the selected features are introduced into the back propagation network (BPN) model for filter parameter estimation. Finally, the k-fold cross validation method is adopted to evaluate the accuracy of the proposed filter parameter prediction framework. A wide variety of T1-weighted brain MR images with various scenarios of noise levels and anatomic structures were utilized to train and validate this new parameter decision system with CUDA-based bilateral filtering. For a common brain MR image volume of 256 × 256 × 256 pixels, the speed-up gain reached 284. Six optimal texture features were acquired and associated with the BPN to establish a "high accuracy" parameter prediction system, which achieved a mean absolute percentage error (MAPE) of 5.6%. Automatic restoration results on 2460 brain MR images received an average relative error in terms of peak signal-to-noise ratio (PSNR) less than 0.1%. In comparison with many state-of-the-art filters, the proposed automation framework with CUDA-based bilateral filtering provided more favorable results both quantitatively and qualitatively. Possessing unique characteristics and demonstrating exceptional performances, the proposed CUDA-based bilateral filter adequately removed random noise in multifarious brain MR images for further study in neurosciences and radiological sciences. It requires no prior knowledge of the noise variance and automatically restores MR images while preserving fine details. The strategy of exploiting the CUDA to accelerate the computation and incorporating texture features into the BPN to completely automate the bilateral filtering process is achievable and validated, from which the best performance is reached. © 2017 American Association of Physicists in Medicine.

Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics

DOE PAGES

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

2015-03-11

Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with thesemore » quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.« less

Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics

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

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with thesemore » quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.« less

Associative image analysis: a method for automated quantification of 3D multi-parameter images of brain tissue

PubMed Central

Bjornsson, Christopher S; Lin, Gang; Al-Kofahi, Yousef; Narayanaswamy, Arunachalam; Smith, Karen L; Shain, William; Roysam, Badrinath

2009-01-01

Brain structural complexity has confounded prior efforts to extract quantitative image-based measurements. We present a systematic ‘divide and conquer’ methodology for analyzing three-dimensional (3D) multi-parameter images of brain tissue to delineate and classify key structures, and compute quantitative associations among them. To demonstrate the method, thick (~100 μm) slices of rat brain tissue were labeled using 3 – 5 fluorescent signals, and imaged using spectral confocal microscopy and unmixing algorithms. Automated 3D segmentation and tracing algorithms were used to delineate cell nuclei, vasculature, and cell processes. From these segmentations, a set of 23 intrinsic and 8 associative image-based measurements was computed for each cell. These features were used to classify astrocytes, microglia, neurons, and endothelial cells. Associations among cells and between cells and vasculature were computed and represented as graphical networks to enable further analysis. The automated results were validated using a graphical interface that permits investigator inspection and corrective editing of each cell in 3D. Nuclear counting accuracy was >89%, and cell classification accuracy ranged from 81–92% depending on cell type. We present a software system named FARSIGHT implementing our methodology. Its output is a detailed XML file containing measurements that may be used for diverse quantitative hypothesis-driven and exploratory studies of the central nervous system. PMID:18294697

Probabilistic Prognosis of Non-Planar Fatigue Crack Growth

NASA Technical Reports Server (NTRS)

Leser, Patrick E.; Newman, John A.; Warner, James E.; Leser, William P.; Hochhalter, Jacob D.; Yuan, Fuh-Gwo

2016-01-01

Quantifying the uncertainty in model parameters for the purpose of damage prognosis can be accomplished utilizing Bayesian inference and damage diagnosis data from sources such as non-destructive evaluation or structural health monitoring. The number of samples required to solve the Bayesian inverse problem through common sampling techniques (e.g., Markov chain Monte Carlo) renders high-fidelity finite element-based damage growth models unusable due to prohibitive computation times. However, these types of models are often the only option when attempting to model complex damage growth in real-world structures. Here, a recently developed high-fidelity crack growth model is used which, when compared to finite element-based modeling, has demonstrated reductions in computation times of three orders of magnitude through the use of surrogate models and machine learning. The model is flexible in that only the expensive computation of the crack driving forces is replaced by the surrogate models, leaving the remaining parameters accessible for uncertainty quantification. A probabilistic prognosis framework incorporating this model is developed and demonstrated for non-planar crack growth in a modified, edge-notched, aluminum tensile specimen. Predictions of remaining useful life are made over time for five updates of the damage diagnosis data, and prognostic metrics are utilized to evaluate the performance of the prognostic framework. Challenges specific to the probabilistic prognosis of non-planar fatigue crack growth are highlighted and discussed in the context of the experimental results.

Morphological texture assessment of oral bone as a screening tool for osteoporosis

NASA Astrophysics Data System (ADS)

Analoui, Mostafa; Eggertsson, Hafsteinn; Eckert, George

2001-07-01

Three classes of texture analysis approaches have been employed to assess the textural characteristic of oral bone. A set of linear structuring elements was used to compute granulometric features of trabecular bone. Multifractal analysis was also used to compute the fractal dimension of the corresponding tissues. In addition, some statistical features and histomorphometric parameters were computed. To assess the proposed approach we acquired digital intraoral radiographs of 47 subjects (14 males and 33 females). All radiographs were captured at 12 bits/pixel. Images were converted to binary form through a sliding locally adaptive thresholding approach. Each subject was scanned by DEXA for bone dosimetry. Subject were classified into one of the following three categories according World Health Organization (WHO) standard (1) healthy, (2) with osteopenia and (3) osteoporosis. In this study fractal dimension showed very low correlation with bone mineral density (BMD) measurements, which did not reach a level of statistical significance (p<0.5). However, entropy of pattern spectrum (EPS), along with statistical features and histomorphometric parameters, has shown correlation coefficients ranging from low to high, with statistical significance for both males and females. The results of this study indicate the utility of this approach for bone texture analysis. It is conjectured that designing a 2-D structuring element, specially tuned to trabecular bone texture, will increase the efficacy of the proposed method.

Original analytic solution of a half-bridge modelled as a statically indeterminate system

NASA Astrophysics Data System (ADS)

Oanta, Emil M.; Panait, Cornel; Raicu, Alexandra; Barhalescu, Mihaela

2016-12-01

The paper presents an original computer based analytical model of a half-bridge belonging to a circular settling tank. The primary unknown is computed using the force method, the coefficients of the canonical equation being calculated using either the discretization of the bending moment diagram in trapezoids, or using the relations specific to the polygons. A second algorithm based on the method of initial parameters is also presented. Analyzing the new solution we came to the conclusion that most of the computer code developed for other model may be reused. The results are useful to evaluate the behavior of the structure and to compare with the results of the finite element models.

FPGA accelerator for protein secondary structure prediction based on the GOR algorithm

PubMed Central

2011-01-01

Background Protein is an important molecule that performs a wide range of functions in biological systems. Recently, the protein folding attracts much more attention since the function of protein can be generally derived from its molecular structure. The GOR algorithm is one of the most successful computational methods and has been widely used as an efficient analysis tool to predict secondary structure from protein sequence. However, the execution time is still intolerable with the steep growth in protein database. Recently, FPGA chips have emerged as one promising application accelerator to accelerate bioinformatics algorithms by exploiting fine-grained custom design. Results In this paper, we propose a complete fine-grained parallel hardware implementation on FPGA to accelerate the GOR-IV package for 2D protein structure prediction. To improve computing efficiency, we partition the parameter table into small segments and access them in parallel. We aggressively exploit data reuse schemes to minimize the need for loading data from external memory. The whole computation structure is carefully pipelined to overlap the sequence loading, computing and back-writing operations as much as possible. We implemented a complete GOR desktop system based on an FPGA chip XC5VLX330. Conclusions The experimental results show a speedup factor of more than 430x over the original GOR-IV version and 110x speedup over the optimized version with multi-thread SIMD implementation running on a PC platform with AMD Phenom 9650 Quad CPU for 2D protein structure prediction. However, the power consumption is only about 30% of that of current general-propose CPUs. PMID:21342582

Rational selection of experimental readout and intervention sites for reducing uncertainties in computational model predictions.

PubMed

Flassig, Robert J; Migal, Iryna; der Zalm, Esther van; Rihko-Struckmann, Liisa; Sundmacher, Kai

2015-01-16

Understanding the dynamics of biological processes can substantially be supported by computational models in the form of nonlinear ordinary differential equations (ODE). Typically, this model class contains many unknown parameters, which are estimated from inadequate and noisy data. Depending on the ODE structure, predictions based on unmeasured states and associated parameters are highly uncertain, even undetermined. For given data, profile likelihood analysis has been proven to be one of the most practically relevant approaches for analyzing the identifiability of an ODE structure, and thus model predictions. In case of highly uncertain or non-identifiable parameters, rational experimental design based on various approaches has shown to significantly reduce parameter uncertainties with minimal amount of effort. In this work we illustrate how to use profile likelihood samples for quantifying the individual contribution of parameter uncertainty to prediction uncertainty. For the uncertainty quantification we introduce the profile likelihood sensitivity (PLS) index. Additionally, for the case of several uncertain parameters, we introduce the PLS entropy to quantify individual contributions to the overall prediction uncertainty. We show how to use these two criteria as an experimental design objective for selecting new, informative readouts in combination with intervention site identification. The characteristics of the proposed multi-criterion objective are illustrated with an in silico example. We further illustrate how an existing practically non-identifiable model for the chlorophyll fluorescence induction in a photosynthetic organism, D. salina, can be rendered identifiable by additional experiments with new readouts. Having data and profile likelihood samples at hand, the here proposed uncertainty quantification based on prediction samples from the profile likelihood provides a simple way for determining individual contributions of parameter uncertainties to uncertainties in model predictions. The uncertainty quantification of specific model predictions allows identifying regions, where model predictions have to be considered with care. Such uncertain regions can be used for a rational experimental design to render initially highly uncertain model predictions into certainty. Finally, our uncertainty quantification directly accounts for parameter interdependencies and parameter sensitivities of the specific prediction.

Subnanosecond breakdown in high-pressure gases

NASA Astrophysics Data System (ADS)

Naidis, George V.; Tarasenko, Victor F.; Babaeva, Natalia Yu; Lomaev, Mikhail I.

2018-01-01

Pulsed discharges in high-pressure gases are of considerable interest as sources of nonequilibrium plasma for various technological applications: pollution control, pumping of laser media, plasma-assisted combustion, etc. Recently, attention has been attracted to the use of subnanosecond voltage fronts, producing diffuse discharges with radii of several millimeters. Such plasma structures, similar to pulsed glow discharges, are of special interest for applications due to quasi-uniformity of plasma parameters in relatively large gas volumes. This review presents the results of experimental and computational study of subnanosecond diffuse discharge formation. A description of generators of short high-voltage pulses with subnanosecond fronts and of discharge setups is given. Diagnostic methods for the measurement of various discharge parameters with high temporal and spatial resolution are described. Obtained experimental data on plasma properties for a wide range of governing factors are discussed. A review of various theoretical approaches used for computational study of the dynamics and structure of fast ionization waves is given; the applicability of conventional fluid streamer models for simulation of subnanosecond ionization waves is discussed. Calculated spatial-temporal profiles of plasma parameters during streamer propagation are presented. The efficiency of subnanosecond discharges for the production of reactive species is evaluated. On the basis of the comparison of simulation results and experimental data the effects of various factors (voltage rise time, polarity, etc.) on discharge characteristics are revealed. The major physical phenomena governing the properties of subnanosecond breakdown are analyzed.

Nonlinear hybrid modal synthesis based on branch modes for dynamic analysis of assembled structure

NASA Astrophysics Data System (ADS)

Huang, Xing-Rong; Jézéquel, Louis; Besset, Sébastien; Li, Lin; Sauvage, Olivier

2018-01-01

This paper describes a simple and fast numerical procedure to study the steady state responses of assembled structures with nonlinearities along continuous interfaces. The proposed strategy is based on a generalized nonlinear modal superposition approach supplemented by a double modal synthesis strategy. The reduced nonlinear modes are derived by combining a single nonlinear mode method with reduction techniques relying on branch modes. The modal parameters containing essential nonlinear information are determined and then employed to calculate the stationary responses of the nonlinear system subjected to various types of excitation. The advantages of the proposed nonlinear modal synthesis are mainly derived in three ways: (1) computational costs are considerably reduced, when analyzing large assembled systems with weak nonlinearities, through the use of reduced nonlinear modes; (2) based on the interpolation models of nonlinear modal parameters, the nonlinear modes introduced during the first step can be employed to analyze the same system under various external loads without having to reanalyze the entire system; and (3) the nonlinear effects can be investigated from a modal point of view by analyzing these nonlinear modal parameters. The proposed strategy is applied to an assembled system composed of plates and nonlinear rubber interfaces. Simulation results have proven the efficiency of this hybrid nonlinear modal synthesis, and the computation time has also been significantly reduced.

Structural identifiability of cyclic graphical models of biological networks with latent variables.

PubMed

Wang, Yulin; Lu, Na; Miao, Hongyu

2016-06-13

Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and is thus of higher resolution in comparison with many existing approaches. Overall, this study provides a basis for systematic examination and refinement of graphical models of biological networks from the identifiability point of view, and it has a significant potential to be extended to more complex network structures or high-dimensional systems.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

PubMed

Karr, Jonathan R; Williams, Alex H; Zucker, Jeremy D; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A; Bot, Brian M; Hoff, Bruce R; Kellen, Michael R; Covert, Markus W; Stolovitzky, Gustavo A; Meyer, Pablo

2015-05-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models

PubMed Central

Karr, Jonathan R.; Williams, Alex H.; Zucker, Jeremy D.; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A.; Bot, Brian M.; Hoff, Bruce R.; Kellen, Michael R.; Covert, Markus W.; Stolovitzky, Gustavo A.; Meyer, Pablo

2015-01-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model’s structure and in silico “experimental” data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation. PMID:26020786

Vibronic Coupling Investigation to Compute Phosphorescence Spectra of Pt(II) Complexes.

PubMed

Vazart, Fanny; Latouche, Camille; Bloino, Julien; Barone, Vincenzo

2015-06-01

The present paper reports a comprehensive quantum mechanical investigation on the luminescence properties of several mono- and dinuclear platinum(II) complexes. The electronic structures and geometric parameters are briefly analyzed together with the absorption bands of all complexes. In all cases agreement with experiment is remarkable. Next, emission (phosphorescence) spectra from the first triplet states have been investigated by comparing different computational approaches and taking into account also vibronic effects. Once again, agreement with experiment is good, especially using unrestricted electronic computations coupled to vibronic contributions. Together with the intrinsic interest of the results, the robustness and generality of the approach open the opportunity for computationally oriented chemists to provide accurate results for the screening of large targets which could be of interest in molecular materials design.

Worst-Case Flutter Margins from F/A-18 Aircraft Aeroelastic Data

NASA Technical Reports Server (NTRS)

Lind, Rick; Brenner, Marty

1997-01-01

An approach for computing worst-case flutter margins has been formulated in a robust stability framework. Uncertainty operators are included with a linear model to describe modeling errors and flight variations. The structured singular value, micron, computes a stability margin which directly accounts for these uncertainties. This approach introduces a new method of computing flutter margins and an associated new parameter for describing these margins. The micron margins are robust margins which indicate worst-case stability estimates with respect to the defined uncertainty. Worst-case flutter margins are computed for the F/A-18 SRA using uncertainty sets generated by flight data analysis. The robust margins demonstrate flight conditions for flutter may lie closer to the flight envelope than previously estimated by p-k analysis.

Model Update of a Micro Air Vehicle (MAV) Flexible Wing Frame with Uncertainty Quantification

NASA Technical Reports Server (NTRS)

Reaves, Mercedes C.; Horta, Lucas G.; Waszak, Martin R.; Morgan, Benjamin G.

2004-01-01

This paper describes a procedure to update parameters in the finite element model of a Micro Air Vehicle (MAV) to improve displacement predictions under aerodynamics loads. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with Multidisciplinary Design Optimization (MDO) is used to modify key model parameters. Static test data collected using photogrammetry are used to correlate with model predictions. Results show significant improvements in model predictions after parameters are updated; however, computed probabilities values indicate low confidence in updated values and/or model structure errors. Lessons learned in the areas of wing design, test procedures, modeling approaches with geometric nonlinearities, and uncertainties quantification are all documented.

National Synchrotron Light Source annual report 1991

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

Hulbert, S.L.; Lazarz, N.M.

1992-04-01

This report discusses the following research conducted at NSLS: atomic and molecular science; energy dispersive diffraction; lithography, microscopy and tomography; nuclear physics; UV photoemission and surface science; x-ray absorption spectroscopy; x-ray scattering and crystallography; x-ray topography; workshop on surface structure; workshop on electronic and chemical phenomena at surfaces; workshop on imaging; UV FEL machine reviews; VUV machine operations; VUV beamline operations; VUV storage ring parameters; x-ray machine operations; x-ray beamline operations; x-ray storage ring parameters; superconducting x-ray lithography source; SXLS storage ring parameters; the accelerator test facility; proposed UV-FEL user facility at the NSLS; global orbit feedback systems; and NSLSmore » computer system.« less

Rosen's (M,R) system in process algebra.

PubMed

Gatherer, Derek; Galpin, Vashti

2013-11-17

Robert Rosen's Metabolism-Replacement, or (M,R), system can be represented as a compact network structure with a single source and three products derived from that source in three consecutive reactions. (M,R) has been claimed to be non-reducible to its components and algorithmically non-computable, in the sense of not being evaluable as a function by a Turing machine. If (M,R)-like structures are present in real biological networks, this suggests that many biological networks will be non-computable, with implications for those branches of systems biology that rely on in silico modelling for predictive purposes. We instantiate (M,R) using the process algebra Bio-PEPA, and discuss the extent to which our model represents a true realization of (M,R). We observe that under some starting conditions and parameter values, stable states can be achieved. Although formal demonstration of algorithmic computability remains elusive for (M,R), we discuss the extent to which our Bio-PEPA representation of (M,R) allows us to sidestep Rosen's fundamental objections to computational systems biology. We argue that the behaviour of (M,R) in Bio-PEPA shows life-like properties.

Computed a multiple band metamaterial absorber and its application based on the figure of merit value

NASA Astrophysics Data System (ADS)

Chen, Chao; Sheng, Yuping; Jun, Wang

2018-01-01

A high performed multiple band metamaterial absorber is designed and computed through the software Ansofts HFSS 10.0, which is constituted with two kinds of separated metal particles sub-structures. The multiple band absorption property of the metamaterial absorber is based on the resonance of localized surface plasmon (LSP) modes excited near edges of metal particles. The damping constant of gold layer is optimized to obtain a near-perfect absorption rate. Four kinds of dielectric layers is computed to achieve the perfect absorption perform. The perfect absorption perform of the metamaterial absorber is enhanced through optimizing the structural parameters (R = 75 nm, w = 80 nm). Moreover, a perfect absorption band is achieved because of the plasmonic hybridization phenomenon between LSP modes. The designed metamaterial absorber shows high sensitive in the changed of the refractive index of the liquid. A liquid refractive index sensor strategy is proposed based on the computed figure of merit (FOM) value of the metamaterial absorber. High FOM values (116, 111, and 108) are achieved with three liquid (Methanol, Carbon tetrachloride, and Carbon disulfide).

Research on the optical and EPR spectral data and the local structure for the trigonal Mn4+ centers in MgTiO3 crystal

NASA Astrophysics Data System (ADS)

Liao, Bi-Tao; Mei, Yang; Chen, Bo-Wei; Zheng, Wen-Chen

2017-07-01

The optical bands and EPR (or spin-Hamiltonian) parameters (g factors g//, g⊥ and zero-field splitting D) for Mn4+ ions at the trigonal octahedral Ti4+ site of MgTiO3 crystal are uniformly computed by virtue of the complete diagonalization (of energy matrix) method based on the two-spin-orbit-parameter model, where besides the effects of spin-orbit parameter of central dn ion on the spectral data (in the classical crystal field theory), those of ligands are also contained. The computed eight optical and EPR spectral data with four suitable adjustable parameters (note: differing from those in the previous work within cubic symmetry approximation where the used Racah parameters violate the nephelauxetic effect, the present Racah parameters obey the effect and hence are suitable) are rationally coincident with the experimental values. In particular, the calculated ground state splitting 2D, the first excited splitting ΔE(2E) and g-anisotropy Δg (=g//-g⊥) (they depend strongly on the angular distortion of d3 centers) are in excellent agreement with the observed values, suggesting that the angular distortions caused by the impurity-induced local lattice relaxation obtained from the above calculation for the trigonal Mn4+ impurity center in MgTiO3: Mn4+ crystal seem to be acceptable.

Determining Hypocentral Parameters for Local Earthquakes in 1-D Using a Genetic Algorithm and Two-point ray tracing

NASA Astrophysics Data System (ADS)

Kim, W.; Hahm, I.; Ahn, S. J.; Lim, D. H.

2005-12-01

This paper introduces a powerful method for determining hypocentral parameters for local earthquakes in 1-D using a genetic algorithm (GA) and two-point ray tracing. Using existing algorithms to determine hypocentral parameters is difficult, because these parameters can vary based on initial velocity models. We developed a new method to solve this problem by applying a GA to an existing algorithm, HYPO-71 (Lee and Larh, 1975). The original HYPO-71 algorithm was modified by applying two-point ray tracing and a weighting factor with respect to the takeoff angle at the source to reduce errors from the ray path and hypocenter depth. Artificial data, without error, were generated by computer using two-point ray tracing in a true model, in which velocity structure and hypocentral parameters were known. The accuracy of the calculated results was easily determined by comparing calculated and actual values. We examined the accuracy of this method for several cases by changing the true and modeled layer numbers and thicknesses. The computational results show that this method determines nearly exact hypocentral parameters without depending on initial velocity models. Furthermore, accurate and nearly unique hypocentral parameters were obtained, although the number of modeled layers and thicknesses differed from those in the true model. Therefore, this method can be a useful tool for determining hypocentral parameters in regions where reliable local velocity values are unknown. This method also provides the basic a priori information for 3-D studies. KEY -WORDS: hypocentral parameters, genetic algorithm (GA), two-point ray tracing

Study of Falling Roof Vibrations in a Production Face at Roof Support Resistance in the Form of Concentrated Force

NASA Astrophysics Data System (ADS)

Buyalich, G. D.; Buyalich, K. G.; Umrikhina, V. Yu

2016-08-01

One of the main reasons of roof support failures in production faces is mismatch of their parameters and parameters of dynamic impact on the metal structure from the falling roof during its secondary convergences. To assess the parameters of vibrational interaction of roof support with the roof, it was suggested to use computational models of forces application and a partial differential equation of fourth order describing this process, its numerical solution allowed to assess frequency, amplitude and speed of roof strata movement depending on physical and mechanical properties of the roof strata as well as on load bearing and geometry parameters of the roof support. To simplify solving of the differential equation, roof support response was taken as the concentrated force.

Theoretical prediction on corrugated sandwich panels under bending loads

NASA Astrophysics Data System (ADS)

Shu, Chengfu; Hou, Shujuan

2018-05-01

In this paper, an aluminum corrugated sandwich panel with triangular core under bending loads was investigated. Firstly, the equivalent material parameters of the triangular corrugated core layer, which could be considered as an orthotropic panel, were obtained by using Castigliano's theorem and equivalent homogeneous model. Secondly, contributions of the corrugated core layer and two face panels were both considered to compute the equivalent material parameters of the whole structure through the classical lamination theory, and these equivalent material parameters were compared with finite element analysis solutions. Then, based on the Mindlin orthotropic plate theory, this study obtain the closed-form solutions of the displacement for a corrugated sandwich panel under bending loads in specified boundary conditions, and parameters study and comparison by the finite element method were executed simultaneously.

New insights into galaxy structure from GALPHAT- I. Motivation, methodology and benchmarks for Sérsic models

NASA Astrophysics Data System (ADS)

Yoon, Ilsang; Weinberg, Martin D.; Katz, Neal

2011-06-01

We introduce a new galaxy image decomposition tool, GALPHAT (GALaxy PHotometric ATtributes), which is a front-end application of the Bayesian Inference Engine (BIE), a parallel Markov chain Monte Carlo package, to provide full posterior probability distributions and reliable confidence intervals for all model parameters. The BIE relies on GALPHAT to compute the likelihood function. GALPHAT generates scale-free cumulative image tables for the desired model family with precise error control. Interpolation of this table yields accurate pixellated images with any centre, scale and inclination angle. GALPHAT then rotates the image by position angle using a Fourier shift theorem, yielding high-speed, accurate likelihood computation. We benchmark this approach using an ensemble of simulated Sérsic model galaxies over a wide range of observational conditions: the signal-to-noise ratio S/N, the ratio of galaxy size to the point spread function (PSF) and the image size, and errors in the assumed PSF; and a range of structural parameters: the half-light radius re and the Sérsic index n. We characterize the strength of parameter covariance in the Sérsic model, which increases with S/N and n, and the results strongly motivate the need for the full posterior probability distribution in galaxy morphology analyses and later inferences. The test results for simulated galaxies successfully demonstrate that, with a careful choice of Markov chain Monte Carlo algorithms and fast model image generation, GALPHAT is a powerful analysis tool for reliably inferring morphological parameters from a large ensemble of galaxies over a wide range of different observational conditions.

A parameter optimization approach to controller partitioning for integrated flight/propulsion control application

NASA Technical Reports Server (NTRS)

Schmidt, Phillip; Garg, Sanjay; Holowecky, Brian

1992-01-01

A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.

A parameter optimization approach to controller partitioning for integrated flight/propulsion control application

NASA Technical Reports Server (NTRS)

Schmidt, Phillip H.; Garg, Sanjay; Holowecky, Brian R.

1993-01-01

A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.

Ab initio 27Al NMR chemical shifts and quadrupolar parameters for Al2O3 phases and their precursors

NASA Astrophysics Data System (ADS)

Ferreira, Ary R.; Küçükbenli, Emine; Leitão, Alexandre A.; de Gironcoli, Stefano

2011-12-01

The gauge-including projector augmented wave (GIPAW) method, within the density functional theory (DFT) generalized gradient approximation (GGA) framework, is applied to compute solid state NMR parameters for 27Al in the α, θ, and κ aluminium oxide phases and their gibbsite and boehmite precursors. The results for well established crystalline phases compare very well with available experimental data and provide confidence in the accuracy of the method. For γ-alumina, four structural models proposed in the literature are discussed in terms of their ability to reproduce the experimental spectra also reported in the literature. Among the considered models, the Fd3¯m structure proposed by Paglia [Phys. Rev. BPRBMDO1098-012110.1103/PhysRevB.71.224115 71, 224115 (2005)] shows the best agreement. We attempt to link the theoretical NMR parameters to the local geometry. Chemical shifts depend on coordination number but no further correlation is found with geometrical parameters. Instead, our calculations reveal that, within a given coordination number, a linear correlation exists between chemical shifts and Born effective charges.

Ares I-X In-Flight Modal Identification

NASA Technical Reports Server (NTRS)

Bartkowicz, Theodore J.; James, George H., III

2011-01-01

Operational modal analysis is a procedure that allows the extraction of modal parameters of a structure in its operating environment. It is based on the idealized premise that input to the structure is white noise. In some cases, when free decay responses are corrupted by unmeasured random disturbances, the response data can be processed into cross-correlation functions that approximate free decay responses. Modal parameters can be computed from these functions by time domain identification methods such as the Eigenvalue Realization Algorithm (ERA). The extracted modal parameters have the same characteristics as impulse response functions of the original system. Operational modal analysis is performed on Ares I-X in-flight data. Since the dynamic system is not stationary due to propellant mass loss, modal identification is only possible by analyzing the system as a series of linearized models over short periods of time via a sliding time-window of short time intervals. A time-domain zooming technique was also employed to enhance the modal parameter extraction. Results of this study demonstrate that free-decay time domain modal identification methods can be successfully employed for in-flight launch vehicle modal extraction.

Optimization of a centrifugal compressor impeller using CFD: the choice of simulation model parameters

NASA Astrophysics Data System (ADS)

Neverov, V. V.; Kozhukhov, Y. V.; Yablokov, A. M.; Lebedev, A. A.

2017-08-01

Nowadays the optimization using computational fluid dynamics (CFD) plays an important role in the design process of turbomachines. However, for the successful and productive optimization it is necessary to define a simulation model correctly and rationally. The article deals with the choice of a grid and computational domain parameters for optimization of centrifugal compressor impellers using computational fluid dynamics. Searching and applying optimal parameters of the grid model, the computational domain and solver settings allows engineers to carry out a high-accuracy modelling and to use computational capability effectively. The presented research was conducted using Numeca Fine/Turbo package with Spalart-Allmaras and Shear Stress Transport turbulence models. Two radial impellers was investigated: the high-pressure at ψT=0.71 and the low-pressure at ψT=0.43. The following parameters of the computational model were considered: the location of inlet and outlet boundaries, type of mesh topology, size of mesh and mesh parameter y+. Results of the investigation demonstrate that the choice of optimal parameters leads to the significant reduction of the computational time. Optimal parameters in comparison with non-optimal but visually similar parameters can reduce the calculation time up to 4 times. Besides, it is established that some parameters have a major impact on the result of modelling.

Normalized Cut Algorithm for Automated Assignment of Protein Domains

NASA Technical Reports Server (NTRS)

Samanta, M. P.; Liang, S.; Zha, H.; Biegel, Bryan A. (Technical Monitor)

2002-01-01

We present a novel computational method for automatic assignment of protein domains from structural data. At the core of our algorithm lies a recently proposed clustering technique that has been very successful for image-partitioning applications. This grap.,l-theory based clustering method uses the notion of a normalized cut to partition. an undirected graph into its strongly-connected components. Computer implementation of our method tested on the standard comparison set of proteins from the literature shows a high success rate (84%), better than most existing alternative In addition, several other features of our algorithm, such as reliance on few adjustable parameters, linear run-time with respect to the size of the protein and reduced complexity compared to other graph-theory based algorithms, would make it an attractive tool for structural biologists.

Spiking network simulation code for petascale computers.

PubMed

Kunkel, Susanne; Schmidt, Maximilian; Eppler, Jochen M; Plesser, Hans E; Masumoto, Gen; Igarashi, Jun; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus; Helias, Moritz

2014-01-01

Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and parameters of their constituents. At cellular resolution, the entities of theory are neurons and synapses and over the past decade researchers have learned to manage the heterogeneity of neurons and synapses with efficient data structures. Already early parallel simulation codes stored synapses in a distributed fashion such that a synapse solely consumes memory on the compute node harboring the target neuron. As petaflop computers with some 100,000 nodes become increasingly available for neuroscience, new challenges arise for neuronal network simulation software: Each neuron contacts on the order of 10,000 other neurons and thus has targets only on a fraction of all compute nodes; furthermore, for any given source neuron, at most a single synapse is typically created on any compute node. From the viewpoint of an individual compute node, the heterogeneity in the synaptic target lists thus collapses along two dimensions: the dimension of the types of synapses and the dimension of the number of synapses of a given type. Here we present a data structure taking advantage of this double collapse using metaprogramming techniques. After introducing the relevant scaling scenario for brain-scale simulations, we quantitatively discuss the performance on two supercomputers. We show that the novel architecture scales to the largest petascale supercomputers available today.

Spiking network simulation code for petascale computers

PubMed Central

Kunkel, Susanne; Schmidt, Maximilian; Eppler, Jochen M.; Plesser, Hans E.; Masumoto, Gen; Igarashi, Jun; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus; Helias, Moritz

2014-01-01

Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and parameters of their constituents. At cellular resolution, the entities of theory are neurons and synapses and over the past decade researchers have learned to manage the heterogeneity of neurons and synapses with efficient data structures. Already early parallel simulation codes stored synapses in a distributed fashion such that a synapse solely consumes memory on the compute node harboring the target neuron. As petaflop computers with some 100,000 nodes become increasingly available for neuroscience, new challenges arise for neuronal network simulation software: Each neuron contacts on the order of 10,000 other neurons and thus has targets only on a fraction of all compute nodes; furthermore, for any given source neuron, at most a single synapse is typically created on any compute node. From the viewpoint of an individual compute node, the heterogeneity in the synaptic target lists thus collapses along two dimensions: the dimension of the types of synapses and the dimension of the number of synapses of a given type. Here we present a data structure taking advantage of this double collapse using metaprogramming techniques. After introducing the relevant scaling scenario for brain-scale simulations, we quantitatively discuss the performance on two supercomputers. We show that the novel architecture scales to the largest petascale supercomputers available today. PMID:25346682

Quantification of uncertainties in the performance of smart composite structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1993-01-01

A composite wing with spars, bulkheads, and built-in control devices is evaluated using a method for the probabilistic assessment of smart composite structures. Structural responses (such as change in angle of attack, vertical displacements, and stresses in regular plies with traditional materials and in control plies with mixed traditional and actuation materials) are probabilistically assessed to quantify their respective scatter. Probabilistic sensitivity factors are computed to identify those parameters that have a significant influence on a specific structural response. Results show that the uncertainties in the responses of smart composite structures can be quantified. Responses such as structural deformation, ply stresses, frequencies, and buckling loads in the presence of defects can be reliably controlled to satisfy specified design requirements.

Motor-Skill Learning in an Insect Inspired Neuro-Computational Control System

PubMed Central

Arena, Eleonora; Arena, Paolo; Strauss, Roland; Patané, Luca

2017-01-01

In nature, insects show impressive adaptation and learning capabilities. The proposed computational model takes inspiration from specific structures of the insect brain: after proposing key hypotheses on the direct involvement of the mushroom bodies (MBs) and on their neural organization, we developed a new architecture for motor learning to be applied in insect-like walking robots. The proposed model is a nonlinear control system based on spiking neurons. MBs are modeled as a nonlinear recurrent spiking neural network (SNN) with novel characteristics, able to memorize time evolutions of key parameters of the neural motor controller, so that existing motor primitives can be improved. The adopted control scheme enables the structure to efficiently cope with goal-oriented behavioral motor tasks. Here, a six-legged structure, showing a steady-state exponentially stable locomotion pattern, is exposed to the need of learning new motor skills: moving through the environment, the structure is able to modulate motor commands and implements an obstacle climbing procedure. Experimental results on a simulated hexapod robot are reported; they are obtained in a dynamic simulation environment and the robot mimicks the structures of Drosophila melanogaster. PMID:28337138

Parallel Optimization of Polynomials for Large-scale Problems in Stability and Control

NASA Astrophysics Data System (ADS)

Kamyar, Reza

In this thesis, we focus on some of the NP-hard problems in control theory. Thanks to the converse Lyapunov theory, these problems can often be modeled as optimization over polynomials. To avoid the problem of intractability, we establish a trade off between accuracy and complexity. In particular, we develop a sequence of tractable optimization problems --- in the form of Linear Programs (LPs) and/or Semi-Definite Programs (SDPs) --- whose solutions converge to the exact solution of the NP-hard problem. However, the computational and memory complexity of these LPs and SDPs grow exponentially with the progress of the sequence - meaning that improving the accuracy of the solutions requires solving SDPs with tens of thousands of decision variables and constraints. Setting up and solving such problems is a significant challenge. The existing optimization algorithms and software are only designed to use desktop computers or small cluster computers --- machines which do not have sufficient memory for solving such large SDPs. Moreover, the speed-up of these algorithms does not scale beyond dozens of processors. This in fact is the reason we seek parallel algorithms for setting-up and solving large SDPs on large cluster- and/or super-computers. We propose parallel algorithms for stability analysis of two classes of systems: 1) Linear systems with a large number of uncertain parameters; 2) Nonlinear systems defined by polynomial vector fields. First, we develop a distributed parallel algorithm which applies Polya's and/or Handelman's theorems to some variants of parameter-dependent Lyapunov inequalities with parameters defined over the standard simplex. The result is a sequence of SDPs which possess a block-diagonal structure. We then develop a parallel SDP solver which exploits this structure in order to map the computation, memory and communication to a distributed parallel environment. Numerical tests on a supercomputer demonstrate the ability of the algorithm to efficiently utilize hundreds and potentially thousands of processors, and analyze systems with 100+ dimensional state-space. Furthermore, we extend our algorithms to analyze robust stability over more complicated geometries such as hypercubes and arbitrary convex polytopes. Our algorithms can be readily extended to address a wide variety of problems in control such as Hinfinity synthesis for systems with parametric uncertainty and computing control Lyapunov functions.

In silico designing of power conversion efficient organic lead dyes for solar cells using todays innovative approaches to assure renewable energy for future

NASA Astrophysics Data System (ADS)

Kar, Supratik; Roy, Juganta K.; Leszczynski, Jerzy

2017-06-01

Advances in solar cell technology require designing of new organic dye sensitizers for dye-sensitized solar cells with high power conversion efficiency to circumvent the disadvantages of silicon-based solar cells. In silico studies including quantitative structure-property relationship analysis combined with quantum chemical analysis were employed to understand the primary electron transfer mechanism and photo-physical properties of 273 arylamine organic dyes from 11 diverse chemical families explicit to iodine electrolyte. The direct quantitative structure-property relationship models enable identification of the essential electronic and structural attributes necessary for quantifying the molecular prerequisites of 11 classes of arylamine organic dyes, responsible for high power conversion efficiency of dye-sensitized solar cells. Tetrahydroquinoline, N,N'-dialkylaniline and indoline have been least explored classes under arylamine organic dyes for dye-sensitized solar cells. Therefore, the identified properties from the corresponding quantitative structure-property relationship models of the mentioned classes were employed in designing of "lead dyes". Followed by, a series of electrochemical and photo-physical parameters were computed for designed dyes to check the required variables for electron flow of dye-sensitized solar cells. The combined computational techniques yielded seven promising lead dyes each for all three chemical classes considered. Significant (130, 183, and 46%) increment in predicted %power conversion efficiency was observed comparing with the existing dye with highest experimental %power conversion efficiency value for tetrahydroquinoline, N,N'-dialkylaniline and indoline, respectively maintaining required electrochemical parameters.

Structural, mechanical and vibrational study of uranyl silicate mineral soddyite by DFT calculations

NASA Astrophysics Data System (ADS)

Colmenero, Francisco; Bonales, Laura J.; Cobos, Joaquín; Timón, Vicente

2017-09-01

Uranyl silicate mineral soddyite, (UO2)2(SiO4)·2(H2O), is a fundamental component of the paragenetic sequence of secondary phases that arises from the weathering of uraninite ore deposits and corrosion of spent nuclear fuel. In this work, soddyite was studied by first principle calculations based on the density functional theory. As far as we know, this is the first time that soddyite structure is determined theoretically. The computed structure of soddyite reproduces the one determined experimentally by X-Ray diffraction (orthorhombic symmetry, spatial group Fddd O2; lattice parameters a = 8.334 Å, b = 11.212 Å; c = 18.668 Å). Lattice parameters, bond lengths, bond angles and X-Ray powder pattern were found to be in very good agreement with their experimental counterparts. Furthermore, the mechanical properties were obtained and the satisfaction of the Born conditions for mechanical stability of the structure was demonstrated by means of calculations of the elasticity tensor. The equation of state of soddyite was obtained by fitting lattice volumes and pressures to a fourth order Birch-Murnahan equation of state. The Raman spectrum was also computed by means of density functional perturbation theory and compared with the experimental spectrum obtained from a natural soddyite sample. The results were also found in agreement with the experimental data. A normal mode analysis of the theoretical spectra was carried out and used in order to assign the main bands of the Raman spectrum.

Modeling, estimation and identification methods for static shape determination of flexible structures. [for large space structure design

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1986-01-01

This paper outlines methods for modeling, identification and estimation for static determination of flexible structures. The shape estimation schemes are based on structural models specified by (possibly interconnected) elliptic partial differential equations. The identification techniques provide approximate knowledge of parameters in elliptic systems. The techniques are based on the method of maximum-likelihood that finds parameter values such that the likelihood functional associated with the system model is maximized. The estimation methods are obtained by means of a function-space approach that seeks to obtain the conditional mean of the state given the data and a white noise characterization of model errors. The solutions are obtained in a batch-processing mode in which all the data is processed simultaneously. After methods for computing the optimal estimates are developed, an analysis of the second-order statistics of the estimates and of the related estimation error is conducted. In addition to outlining the above theoretical results, the paper presents typical flexible structure simulations illustrating performance of the shape determination methods.

Demagnetization Analysis in Excel (DAIE) - An open source workbook in Excel for viewing and analyzing demagnetization data from paleomagnetic discrete samples and u-channels

NASA Astrophysics Data System (ADS)

Sagnotti, Leonardo

2013-04-01

Modern rock magnetometers and stepwise demagnetization procedures result in the production of large datasets, which need a versatile and fast software for their display and analysis. Various software packages for paleomagnetic analyses have been recently developed to overcome the problems linked to the limited capability and the loss of operability of early codes written in obsolete computer languages and/or platforms, not compatible with modern 64 bit processors. The Demagnetization Analysis in Excel (DAIE) workbook is a new software that has been designed to make the analysis of demagnetization data easy and accessible on an application (Microsoft Excel) widely diffused and available on both the Microsoft Windows and Mac OS X operating systems. The widespread diffusion of Excel should guarantee a long term working life, since compatibility and functionality of current Excel files should be most likely maintained during the development of new processors and operating systems. DAIE is designed for viewing and analyzing stepwise demagnetization data of both discrete and u-channel samples. DAIE consists of a single file and has an open modular structure organized in 10 distinct worksheets. The standard demagnetization diagrams and various parameters of common use are shown on the same worksheet including selectable parameters and user's choices. The remanence characteristic components may be computed by principal component analysis (PCA) on a selected interval of demagnetization steps. Saving of the PCA data can be done both sample by sample, or in automatic by applying the selected choices to all the samples included in the file. The DAIE open structure allows easy personalization, development and improvement. The workbook has the following features which may be valuable for various users: - Operability in nearly all the computers and platforms; - Easy inputs of demagnetization data by "copy and paste" from ASCII files; - Easy export of computed parameters and demagnetization plots; - Complete control of the whole workflow and possibility of implementation of the workbook by any user; - Modular structure in distinct worksheets for each type of analyses and plots, in order to make implementation and personalization easier; - Opportunity to use the workbook for educational purposes, since all the computations and analyses are easily traceable and accessible; - Automatic and fast analysis of a large batch of demagnetization data, such as those measured on u-channel samples. The DAIE workbook and the "User manual" are available for download on a dedicated web site (http://roma2.rm.ingv.it/en/facilities/software/49/daie).

Probabilistic finite elements for fatigue and fracture analysis

NASA Astrophysics Data System (ADS)

Belytschko, Ted; Liu, Wing Kam

1993-04-01

An overview of the probabilistic finite element method (PFEM) developed by the authors and their colleagues in recent years is presented. The primary focus is placed on the development of PFEM for both structural mechanics problems and fracture mechanics problems. The perturbation techniques are used as major tools for the analytical derivation. The following topics are covered: (1) representation and discretization of random fields; (2) development of PFEM for the general linear transient problem and nonlinear elasticity using Hu-Washizu variational principle; (3) computational aspects; (4) discussions of the application of PFEM to the reliability analysis of both brittle fracture and fatigue; and (5) a stochastic computational tool based on stochastic boundary element (SBEM). Results are obtained for the reliability index and corresponding probability of failure for: (1) fatigue crack growth; (2) defect geometry; (3) fatigue parameters; and (4) applied loads. These results show that initial defect is a critical parameter.

Verification of Geometric Model-Based Plant Phenotyping Methods for Studies of Xerophytic Plants.

PubMed

Drapikowski, Paweł; Kazimierczak-Grygiel, Ewa; Korecki, Dominik; Wiland-Szymańska, Justyna

2016-06-27

This paper presents the results of verification of certain non-contact measurement methods of plant scanning to estimate morphological parameters such as length, width, area, volume of leaves and/or stems on the basis of computer models. The best results in reproducing the shape of scanned objects up to 50 cm in height were obtained with the structured-light DAVID Laserscanner. The optimal triangle mesh resolution for scanned surfaces was determined with the measurement error taken into account. The research suggests that measuring morphological parameters from computer models can supplement or even replace phenotyping with classic methods. Calculating precise values of area and volume makes determination of the S/V (surface/volume) ratio for cacti and other succulents possible, whereas for classic methods the result is an approximation only. In addition, the possibility of scanning and measuring plant species which differ in morphology was investigated.

Probabilistic finite elements for fatigue and fracture analysis

NASA Technical Reports Server (NTRS)

Belytschko, Ted; Liu, Wing Kam

1993-01-01

An overview of the probabilistic finite element method (PFEM) developed by the authors and their colleagues in recent years is presented. The primary focus is placed on the development of PFEM for both structural mechanics problems and fracture mechanics problems. The perturbation techniques are used as major tools for the analytical derivation. The following topics are covered: (1) representation and discretization of random fields; (2) development of PFEM for the general linear transient problem and nonlinear elasticity using Hu-Washizu variational principle; (3) computational aspects; (4) discussions of the application of PFEM to the reliability analysis of both brittle fracture and fatigue; and (5) a stochastic computational tool based on stochastic boundary element (SBEM). Results are obtained for the reliability index and corresponding probability of failure for: (1) fatigue crack growth; (2) defect geometry; (3) fatigue parameters; and (4) applied loads. These results show that initial defect is a critical parameter.

Durability evaluation of ceramic components using CARES/LIFE

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Janosik, Lesley A.; Gyekenyesi, John P.

1994-01-01

The computer program CARES/LIFE calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. This program is an extension of the CARES (Ceramics Analysis and Reliability Evaluation of Structures) computer program. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing the power law, Paris law, or Walker equation. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. Application of this design methodology is demonstrated using experimental data from alumina bar and disk flexure specimens which exhibit SCG when exposed to water.

Durability evaluation of ceramic components using CARES/LIFE

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

Nemeth, N.N.; Janosik, L.A.; Gyekenyesi, J.P.

1996-01-01

The computer program CARES/LIFE calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. This program is an extension of the CARES (Ceramics Analysis and Reliability Evaluation of Structures) computer program. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing the power law, Paris law, or Walker equation. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength andmore » fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. Application of this design methodology is demonstrated using experimental data from alumina bar and disk flexure specimens, which exhibit SCG when exposed to water.« less

Verification of Geometric Model-Based Plant Phenotyping Methods for Studies of Xerophytic Plants

PubMed Central

Drapikowski, Paweł; Kazimierczak-Grygiel, Ewa; Korecki, Dominik; Wiland-Szymańska, Justyna

2016-01-01

This paper presents the results of verification of certain non-contact measurement methods of plant scanning to estimate morphological parameters such as length, width, area, volume of leaves and/or stems on the basis of computer models. The best results in reproducing the shape of scanned objects up to 50 cm in height were obtained with the structured-light DAVID Laserscanner. The optimal triangle mesh resolution for scanned surfaces was determined with the measurement error taken into account. The research suggests that measuring morphological parameters from computer models can supplement or even replace phenotyping with classic methods. Calculating precise values of area and volume makes determination of the S/V (surface/volume) ratio for cacti and other succulents possible, whereas for classic methods the result is an approximation only. In addition, the possibility of scanning and measuring plant species which differ in morphology was investigated. PMID:27355949

Quicklook Constituent Abundance and Stretch Parameter Retrieval for the Juno Microwave Radiometer using Neural Networks

NASA Astrophysics Data System (ADS)

Bellotti, A.; Steffes, P. G.

2016-12-01

The Juno Microwave Radiometer (MWR) has six channels ranging from 1.36-50 cm and the ability to peer deep into the Jovian atmosphere. An Artifical Neural Network algorithm has been developed to rapidly perform inversion for the deep abundance of ammonia, the deep abundance of water vapor, and atmospheric "stretch" (a parameter that reflects the deviation from a wet adiabate in the higher atmosphere). This algorithm is "trained" by using simulated emissions at the six wavelengths computed using the Juno atmospheric microwave radiative transfer (JAMRT) model presented by Oyafuso et al. (This meeting). By exploiting the emission measurements conducted at six wavelengths and at various incident angles, the neural network can provide preliminary results to a useful precison in a computational method hundreds of times faster than conventional methods. This can quickly provide important insights into the variability and structure of the Jovian atmosphere.

Desensitizing Flame Structure and Exhaust Emissions to Flow Parameters in an Ultra-Compact Combustor

DTIC Science & Technology

2012-03-22

fuel .... 9 Figure 2.4: UNICORN model of hydrogen in air flame front propagation under the loading condition (a) 10 g’s and (b) 500 g’s...Lean Blowout ...................................................................................8 UNICORN Unsteady Ignition and Combustion with...computationally recreate Lewis’ experimental results. Using the Unsteady Ignition and 9 Combustion with Reactions ( UNICORN ) code, flame propagation

Image Display And Manipulation System (IDAMS), user's guide

NASA Technical Reports Server (NTRS)

Cecil, R. W.

1972-01-01

A combination operator's guide and user's handbook for the Image Display and Manipulation System (IDAMS) is reported. Information is presented to define how to operate the computer equipment, how to structure a run deck, and how to select parameters necessary for executing a sequence of IDAMS task routines. If more detailed information is needed on any IDAMS program, see the IDAMS program documentation.

Information-Decay Pursuit of Dynamic Parameters in Student Models

DTIC Science & Technology

1994-04-01

simple worked-through example). Commercially available computer programs for structuring and using Bayesian inference include ERGO ( Noetic Systems...Tukey, J.W. (1977). Data analysis and Regression: A second course in statistics. Reading, MA: Addison-Wesley. Noetic Systems, Inc. (1991). ERGO...Naval Academy Division of Educational Studies Annapolis MD 21402-5002 Elmory Univerity Dr Janice Gifford 210 Fiabburne Bldg University of

Investigations on the Phase Diagram and Interaction Parameter of Poly(styrene-b-1,3-cyclohexadiene) Copolymers

DOE PAGES

Misichronis, Konstantinos; Chen, Jihua; Imel, Adam; ...

2017-03-15

A series of linear diblock copolymers containing polystyrene (PS) and poly(1,3-cyclohexadiene) (PCHD) with high 1,4-microstructure (>87%) was synthesized by anionic polymerization and high vacuum techniques. Microphase separation in the bulk was examined in this paper by transmission electron microscopy (TEM) and small-angle X-ray scattering (SAXS) and compared to computational analysis of the predicted morphological phase diagram for this system. Because of the high conformational asymmetry between PS and PCHD, these materials self-assemble into typical morphologies expected for linear diblock copolymer systems and atypical structures. Rheological measurements were conducted and revealed order–disorder transition temperatures (T ODT), for the first time formore » PS-b-PCHD copolymers, resulting in a working expression for the effective interaction parameter χ eff = 32/T – 0.016. Furthermore, we performed computational studies that coincide with the experimental results. Finally, these copolymers exhibit well-ordered structures even at high temperatures (~260 °C) therefore providing a better insight concerning their microphase separation at the nanoscale which is important for their potential use in nanotechnology and/or nanolithography applications.« less

Probabilistic design of fibre concrete structures

NASA Astrophysics Data System (ADS)

Pukl, R.; Novák, D.; Sajdlová, T.; Lehký, D.; Červenka, J.; Červenka, V.

2017-09-01

Advanced computer simulation is recently well-established methodology for evaluation of resistance of concrete engineering structures. The nonlinear finite element analysis enables to realistically predict structural damage, peak load, failure, post-peak response, development of cracks in concrete, yielding of reinforcement, concrete crushing or shear failure. The nonlinear material models can cover various types of concrete and reinforced concrete: ordinary concrete, plain or reinforced, without or with prestressing, fibre concrete, (ultra) high performance concrete, lightweight concrete, etc. Advanced material models taking into account fibre concrete properties such as shape of tensile softening branch, high toughness and ductility are described in the paper. Since the variability of the fibre concrete material properties is rather high, the probabilistic analysis seems to be the most appropriate format for structural design and evaluation of structural performance, reliability and safety. The presented combination of the nonlinear analysis with advanced probabilistic methods allows evaluation of structural safety characterized by failure probability or by reliability index respectively. Authors offer a methodology and computer tools for realistic safety assessment of concrete structures; the utilized approach is based on randomization of the nonlinear finite element analysis of the structural model. Uncertainty of the material properties or their randomness obtained from material tests are accounted in the random distribution. Furthermore, degradation of the reinforced concrete materials such as carbonation of concrete, corrosion of reinforcement, etc. can be accounted in order to analyze life-cycle structural performance and to enable prediction of the structural reliability and safety in time development. The results can serve as a rational basis for design of fibre concrete engineering structures based on advanced nonlinear computer analysis. The presented methodology is illustrated on results from two probabilistic studies with different types of concrete structures related to practical applications and made from various materials (with the parameters obtained from real material tests).

An iterative hyperelastic parameters reconstruction for breast cancer assessment

NASA Astrophysics Data System (ADS)

Mehrabian, Hatef; Samani, Abbas

2008-03-01

In breast elastography, breast tissues usually undergo large compressions resulting in significant geometric and structural changes, and consequently nonlinear mechanical behavior. In this study, an elastography technique is presented where parameters characterizing tissue nonlinear behavior is reconstructed. Such parameters can be used for tumor tissue classification. To model the nonlinear behavior, tissues are treated as hyperelastic materials. The proposed technique uses a constrained iterative inversion method to reconstruct the tissue hyperelastic parameters. The reconstruction technique uses a nonlinear finite element (FE) model for solving the forward problem. In this research, we applied Yeoh and Polynomial models to model the tissue hyperelasticity. To mimic the breast geometry, we used a computational phantom, which comprises of a hemisphere connected to a cylinder. This phantom consists of two types of soft tissue to mimic adipose and fibroglandular tissues and a tumor. Simulation results show the feasibility of the proposed method in reconstructing the hyperelastic parameters of the tumor tissue.

Parameter motivated mutual correlation analysis: Application to the study of currency exchange rates based on intermittency parameter and Hurst exponent

NASA Astrophysics Data System (ADS)

Cristescu, Constantin P.; Stan, Cristina; Scarlat, Eugen I.; Minea, Teofil; Cristescu, Cristina M.

2012-04-01

We present a novel method for the parameter oriented analysis of mutual correlation between independent time series or between equivalent structures such as ordered data sets. The proposed method is based on the sliding window technique, defines a new type of correlation measure and can be applied to time series from all domains of science and technology, experimental or simulated. A specific parameter that can characterize the time series is computed for each window and a cross correlation analysis is carried out on the set of values obtained for the time series under investigation. We apply this method to the study of some currency daily exchange rates from the point of view of the Hurst exponent and the intermittency parameter. Interesting correlation relationships are revealed and a tentative crisis prediction is presented.

A density-functional study on the electronic and vibrational properties of layered antimony telluride.

PubMed

Stoffel, Ralf P; Deringer, Volker L; Simon, Ronnie E; Hermann, Raphaël P; Dronskowski, Richard

2015-03-04

We present a comprehensive survey of electronic and lattice-dynamical properties of crystalline antimony telluride (Sb2Te3). In a first step, the electronic structure and chemical bonding have been investigated, followed by calculations of the atomic force constants, phonon dispersion relationships and densities of states. Then, (macroscopic) physical properties of Sb2Te3 have been computed, namely, the atomic thermal displacement parameters, the Grüneisen parameter γ, the volume expansion of the lattice, and finally the bulk modulus B. We compare theoretical results from three popular and economic density-functional theory (DFT) approaches: the local density approximation (LDA), the generalized gradient approximation (GGA), and a posteriori dispersion corrections to the latter. Despite its simplicity, the LDA shows excellent performance for all properties investigated-including the Grüneisen parameter, which only the LDA is able to recover with confidence. In the absence of computationally more demanding hybrid DFT methods, the LDA seems to be a good choice for further lattice dynamical studies of Sb2Te3 and related layered telluride materials.

Impact of heat source/sink on radiative heat transfer to Maxwell nanofluid subject to revised mass flux condition

NASA Astrophysics Data System (ADS)

Khan, M.; Irfan, M.; Khan, W. A.

2018-06-01

Nanofluids retain noteworthy structure that have absorbed attentions of numerous investigators because of their exploration in nanotechnology and nanoscience. In this scrutiny a mathematical computation of 2D flows of Maxwell nanoliquid influenced by a stretched cylinder has been established. The heat transfer structure is conceded out in the manifestation of thermal radiation and heat source/sink. Moreover, the nanoparticles mass flux condition is engaged in this exploration. This newly endorsed tactic is more realistic where the conjecture is made that the nanoparticle flux is zero and nanoparticle fraction regulates itself on the restrictions consequently. By utilizing apposite conversion the governing PDEs are transformed into ODEs and then tackled analytically via HAM. The attained outcomes are plotted and deliberated in aspect for somatic parameters. It is remarked that with an intensification in the Deborah number β diminish the liquid temperature while it boosts for radiation parameter Rd . Furthermore, the concentration of Maxwell liquid has conflicting impact for Brownian motion Nb and thermophoresis parameters Nt .

Flying Cages in Traveling Wave Ion Mobility: Influence of the Instrumental Parameters on the Topology of the Host-Guest Complexes

NASA Astrophysics Data System (ADS)

Carroy, Glenn; Lemaur, Vincent; Henoumont, Céline; Laurent, Sophie; De Winter, Julien; De Pauw, Edwin; Cornil, Jérôme; Gerbaux, Pascal

2018-01-01

Supramolecular mass spectrometry has emerged in the last decade as an orthogonal method to access, at the molecular level, the structures of noncovalent complexes extracted from the condensed phase to the rarefied gas phase using electrospray ionization. It is often considered that the soft nature of the ESI source confers to the method the capability to generate structural data comparable to those in the condensed phase. In the present paper, using the ammonium ion/cucurbituril combination as a model system, we investigate using ion mobility and computational chemistry the influence of the instrumental parameters on the topology, i.e., internal versus external association, of gaseous host/guest complex ions. MS and theoretical data are confronted to condensed phase data derived from nuclear magnetic resonance spectroscopy to assess whether the instrumental parameters can play an insidious role when trying to derive condensed phase data from mass spectrometry results. [Figure not available: see fulltext.

A modern control theory based algorithm for control of the NASA/JPL 70-meter antenna axis servos

NASA Technical Reports Server (NTRS)

Hill, R. E.

1987-01-01

A digital computer-based state variable controller was designed and applied to the 70-m antenna axis servos. The general equations and structure of the algorithm and provisions for alternate position error feedback modes to accommodate intertarget slew, encoder referenced tracking, and precision tracking modes are descibed. Development of the discrete time domain control model and computation of estimator and control gain parameters based on closed loop pole placement criteria are discussed. The new algorithm was successfully implemented and tested in the 70-m antenna at Deep Space Network station 63 in Spain.

Treatment of atomic and molecular line blanketing by opacity sampling. [atmospheric optics - stellar atmospheres

NASA Technical Reports Server (NTRS)

Johnson, H. R.; Krupp, B. M.

1975-01-01

An opacity sampling (OS) technique for treating the radiative opacity of large numbers of atomic and molecular lines in cool stellar atmospheres is presented. Tests were conducted and results show that the structure of atmospheric models is accurately fixed by the use of 1000 frequency points, and 500 frequency points is often adequate. The effects of atomic and molecular lines are separately studied. A test model computed by using the OS method agrees very well with a model having identical atmospheric parameters computed by the giant line (opacity distribution function) method.

Wood Products Analysis

NASA Technical Reports Server (NTRS)

1990-01-01

Structural Reliability Consultants' computer program creates graphic plots showing the statistical parameters of glue laminated timbers, or 'glulam.' The company president, Dr. Joseph Murphy, read in NASA Tech Briefs about work related to analysis of Space Shuttle surface tile strength performed for Johnson Space Center by Rockwell International Corporation. Analysis led to a theory of 'consistent tolerance bounds' for statistical distributions, applicable in industrial testing where statistical analysis can influence product development and use. Dr. Murphy then obtained the Tech Support Package that covers the subject in greater detail. The TSP became the basis for Dr. Murphy's computer program PC-DATA, which he is marketing commercially.

Extension, validation and application of the NASCAP code

NASA Technical Reports Server (NTRS)

Katz, I.; Cassidy, J. J., III; Mandell, M. J.; Schnuelle, G. W.; Steen, P. G.; Parks, D. E.; Rotenberg, M.; Alexander, J. H.

1979-01-01

Numerous extensions were made in the NASCAP code. They fall into three categories: a greater range of definable objects, a more sophisticated computational model, and simplified code structure and usage. An important validation of NASCAP was performed using a new two dimensional computer code (TWOD). An interactive code (MATCHG) was written to compare material parameter inputs with charging results. The first major application of NASCAP was performed on the SCATHA satellite. Shadowing and charging calculation were completed. NASCAP was installed at the Air Force Geophysics Laboratory, where researchers plan to use it to interpret SCATHA data.

Bayesian Parameter Inference and Model Selection by Population Annealing in Systems Biology

PubMed Central

Murakami, Yohei

2014-01-01

Parameter inference and model selection are very important for mathematical modeling in systems biology. Bayesian statistics can be used to conduct both parameter inference and model selection. Especially, the framework named approximate Bayesian computation is often used for parameter inference and model selection in systems biology. However, Monte Carlo methods needs to be used to compute Bayesian posterior distributions. In addition, the posterior distributions of parameters are sometimes almost uniform or very similar to their prior distributions. In such cases, it is difficult to choose one specific value of parameter with high credibility as the representative value of the distribution. To overcome the problems, we introduced one of the population Monte Carlo algorithms, population annealing. Although population annealing is usually used in statistical mechanics, we showed that population annealing can be used to compute Bayesian posterior distributions in the approximate Bayesian computation framework. To deal with un-identifiability of the representative values of parameters, we proposed to run the simulations with the parameter ensemble sampled from the posterior distribution, named “posterior parameter ensemble”. We showed that population annealing is an efficient and convenient algorithm to generate posterior parameter ensemble. We also showed that the simulations with the posterior parameter ensemble can, not only reproduce the data used for parameter inference, but also capture and predict the data which was not used for parameter inference. Lastly, we introduced the marginal likelihood in the approximate Bayesian computation framework for Bayesian model selection. We showed that population annealing enables us to compute the marginal likelihood in the approximate Bayesian computation framework and conduct model selection depending on the Bayes factor. PMID:25089832

Can Computational Sediment Transport Models Reproduce the Observed Variability of Channel Networks in Modern Deltas?

NASA Astrophysics Data System (ADS)

Nesvold, E.; Mukerji, T.

2017-12-01

River deltas display complex channel networks that can be characterized through the framework of graph theory, as shown by Tejedor et al. (2015). Deltaic patterns may also be useful in a Bayesian approach to uncertainty quantification of the subsurface, but this requires a prior distribution of the networks of ancient deltas. By considering subaerial deltas, one can at least obtain a snapshot in time of the channel network spectrum across deltas. In this study, the directed graph structure is semi-automatically extracted from satellite imagery using techniques from statistical processing and machine learning. Once the network is labeled with vertices and edges, spatial trends and width and sinuosity distributions can also be found easily. Since imagery is inherently 2D, computational sediment transport models can serve as a link between 2D network structure and 3D depositional elements; the numerous empirical rules and parameters built into such models makes it necessary to validate the output with field data. For this purpose we have used a set of 110 modern deltas, with average water discharge ranging from 10 - 200,000 m3/s, as a benchmark for natural variability. Both graph theoretic and more general distributions are established. A key question is whether it is possible to reproduce this deltaic network spectrum with computational models. Delft3D was used to solve the shallow water equations coupled with sediment transport. The experimental setup was relatively simple; incoming channelized flow onto a tilted plane, with varying wave and tidal energy, sediment types and grain size distributions, river discharge and a few other input parameters. Each realization was run until a delta had fully developed: between 50 and 500 years (with a morphology acceleration factor). It is shown that input parameters should not be sampled independently from the natural ranges, since this may result in deltaic output that falls well outside the natural spectrum. Since we are interested in studying the patterns occurring in nature, ideas are proposed for how to sample computer realizations that match this distribution. By establishing a link between surface based patterns from the field with the associated subsurface structure from physics-based models, this is a step towards a fully Bayesian workflow in subsurface simulation.

Reliability analysis of composite structures

NASA Technical Reports Server (NTRS)

Kan, Han-Pin

1992-01-01

A probabilistic static stress analysis methodology has been developed to estimate the reliability of a composite structure. Closed form stress analysis methods are the primary analytical tools used in this methodology. These structural mechanics methods are used to identify independent variables whose variations significantly affect the performance of the structure. Once these variables are identified, scatter in their values is evaluated and statistically characterized. The scatter in applied loads and the structural parameters are then fitted to appropriate probabilistic distribution functions. Numerical integration techniques are applied to compute the structural reliability. The predicted reliability accounts for scatter due to variability in material strength, applied load, fabrication and assembly processes. The influence of structural geometry and mode of failure are also considerations in the evaluation. Example problems are given to illustrate various levels of analytical complexity.

Brute force meets Bruno force in parameter optimisation: introduction of novel constraints for parameter accuracy improvement by symbolic computation.

PubMed

Nakatsui, M; Horimoto, K; Lemaire, F; Ürgüplü, A; Sedoglavic, A; Boulier, F

2011-09-01

Recent remarkable advances in computer performance have enabled us to estimate parameter values by the huge power of numerical computation, the so-called 'Brute force', resulting in the high-speed simultaneous estimation of a large number of parameter values. However, these advancements have not been fully utilised to improve the accuracy of parameter estimation. Here the authors review a novel method for parameter estimation using symbolic computation power, 'Bruno force', named after Bruno Buchberger, who found the Gröbner base. In the method, the objective functions combining the symbolic computation techniques are formulated. First, the authors utilise a symbolic computation technique, differential elimination, which symbolically reduces an equivalent system of differential equations to a system in a given model. Second, since its equivalent system is frequently composed of large equations, the system is further simplified by another symbolic computation. The performance of the authors' method for parameter accuracy improvement is illustrated by two representative models in biology, a simple cascade model and a negative feedback model in comparison with the previous numerical methods. Finally, the limits and extensions of the authors' method are discussed, in terms of the possible power of 'Bruno force' for the development of a new horizon in parameter estimation.

Real-time flutter analysis

NASA Technical Reports Server (NTRS)

Walker, R.; Gupta, N.

1984-01-01

The important algorithm issues necessary to achieve a real time flutter monitoring system; namely, the guidelines for choosing appropriate model forms, reduction of the parameter convergence transient, handling multiple modes, the effect of over parameterization, and estimate accuracy predictions, both online and for experiment design are addressed. An approach for efficiently computing continuous-time flutter parameter Cramer-Rao estimate error bounds were developed. This enables a convincing comparison of theoretical and simulation results, as well as offline studies in preparation for a flight test. Theoretical predictions, simulation and flight test results from the NASA Drones for Aerodynamic and Structural Test (DAST) Program are compared.

Measuring watershed runoff capability with ERTS data. [Washita River Basin, Oklahoma

NASA Technical Reports Server (NTRS)

Blanchard, B. J.

1974-01-01

Parameters of most equations used to predict runoff from an ungaged area are based on characteristics of the watershed and subject to the biases of a hydrologist. Digital multispectral scanner, MSS, data from ERTS was reduced with the aid of computer programs and a Dicomed display. Multivariate analyses of the MSS data indicate that discrimination between watersheds with different runoff capabilities is possible using ERTS data. Differences between two visible bands of MSS data can be used to more accurately evaluate the parameters than present subjective methods, thus reducing construction cost due to overdesign of flood detention structures.

Generalized Processing Tree Models: Jointly Modeling Discrete and Continuous Variables.

PubMed

Heck, Daniel W; Erdfelder, Edgar; Kieslich, Pascal J

2018-05-24

Multinomial processing tree models assume that discrete cognitive states determine observed response frequencies. Generalized processing tree (GPT) models extend this conceptual framework to continuous variables such as response times, process-tracing measures, or neurophysiological variables. GPT models assume finite-mixture distributions, with weights determined by a processing tree structure, and continuous components modeled by parameterized distributions such as Gaussians with separate or shared parameters across states. We discuss identifiability, parameter estimation, model testing, a modeling syntax, and the improved precision of GPT estimates. Finally, a GPT version of the feature comparison model of semantic categorization is applied to computer-mouse trajectories.

Automated analysis of biological oscillator models using mode decomposition.

PubMed

Konopka, Tomasz

2011-04-01

Oscillating signals produced by biological systems have shapes, described by their Fourier spectra, that can potentially reveal the mechanisms that generate them. Extracting this information from measured signals is interesting for the validation of theoretical models, discovery and classification of interaction types, and for optimal experiment design. An automated workflow is described for the analysis of oscillating signals. A software package is developed to match signal shapes to hundreds of a priori viable model structures defined by a class of first-order differential equations. The package computes parameter values for each model by exploiting the mode decomposition of oscillating signals and formulating the matching problem in terms of systems of simultaneous polynomial equations. On the basis of the computed parameter values, the software returns a list of models consistent with the data. In validation tests with synthetic datasets, it not only shortlists those model structures used to generate the data but also shows that excellent fits can sometimes be achieved with alternative equations. The listing of all consistent equations is indicative of how further invalidation might be achieved with additional information. When applied to data from a microarray experiment on mice, the procedure finds several candidate model structures to describe interactions related to the circadian rhythm. This shows that experimental data on oscillators is indeed rich in information about gene regulation mechanisms. The software package is available at http://babylone.ulb.ac.be/autoosc/.

Absorbable energy monitoring scheme: new design protocol to test vehicle structural crashworthiness.

PubMed

Ofochebe, Sunday M; Enibe, Samuel O; Ozoegwu, Chigbogu G

2016-05-01

In vehicle crashworthiness design optimization detailed system evaluation capable of producing reliable results are basically achieved through high-order numerical computational (HNC) models such as the dynamic finite element model, mesh-free model etc. However the application of these models especially during optimization studies is basically challenged by their inherent high demand on computational resources, conditional stability of the solution process, and lack of knowledge of viable parameter range for detailed optimization studies. The absorbable energy monitoring scheme (AEMS) presented in this paper suggests a new design protocol that attempts to overcome such problems in evaluation of vehicle structure for crashworthiness. The implementation of the AEMS involves studying crash performance of vehicle components at various absorbable energy ratios based on a 2DOF lumped-mass-spring (LMS) vehicle impact model. This allows for prompt prediction of useful parameter values in a given design problem. The application of the classical one-dimensional LMS model in vehicle crash analysis is further improved in the present work by developing a critical load matching criterion which allows for quantitative interpretation of the results of the abstract model in a typical vehicle crash design. The adequacy of the proposed AEMS for preliminary vehicle crashworthiness design is demonstrated in this paper, however its extension to full-scale design-optimization problem involving full vehicle model that shows greater structural detail requires more theoretical development.

Specificity of foot configuration during bipedal stance in ballet dancers.

PubMed

Casabona, Antonino; Leonardi, Giuseppa; Aimola, Ettore; La Grua, Giovanni; Polizzi, Cristina Maria; Cioni, Matteo; Valle, Maria Stella

2016-05-01

Learning highly specialized upright postures may be of benefit for more common as well as for novel stances. In this study, we asked whether this generalization occurs with foot configurations previously trained or depends on a generic increase in balance difficulty. We also explored the possibility that the benefit may concern not only the level of postural performance but also the structural organization of the upright standing. Ten elite professional ballet dancers were compared to ten untrained subjects, measuring the motion of the center of pressure (COP) across a set of five stances with different foot configurations. The balance stability was measured computing the area, the sway path, and the root mean square of the COP motion, whereas the structure of the postural control was assessed by compute approximate entropy, fractal dimension and the mean power frequency. The foot position included common and challenging stances, with the level of difficulty changed across the configurations. Among these conditions, only one foot configuration was familiar to the dancers. Statistically significant differences between the two groups, for all the parameters, were observed only for the stance with the foot position familiar to the dancers. Stability and structural parameters exhibited comparable differences. We concluded that the benefit from classical ballet is limited to a specific foot configuration, regardless of the level of stance difficulty or the component of postural control. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Siauw, Timmy; Cunha, Adam; Berenson, Dmitry

Purpose: In this study, the authors introduce skew line needle configurations for high dose rate (HDR) brachytherapy and needle planning by integer program (NPIP), a computational method for generating these configurations. NPIP generates needle configurations that are specific to the anatomy of the patient, avoid critical structures near the penile bulb and other healthy structures, and avoid needle collisions inside the body. Methods: NPIP consisted of three major components: a method for generating a set of candidate needles, a needle selection component that chose a candidate needle subset to be inserted, and a dose planner for verifying that the finalmore » needle configuration could meet dose objectives. NPIP was used to compute needle configurations for prostate cancer data sets from patients previously treated at our clinic. NPIP took two user-parameters: a number of candidate needles, and needle coverage radius, {delta}. The candidate needle set consisted of 5000 needles, and a range of {delta} values was used to compute different needle configurations for each patient. Dose plans were computed for each needle configuration. The number of needles generated and dosimetry were analyzed and compared to the physician implant. Results: NPIP computed at least one needle configuration for every patient that met dose objectives, avoided healthy structures and needle collisions, and used as many or fewer needles than standard practice. These needle configurations corresponded to a narrow range of {delta} values, which could be used as default values if this system is used in practice. The average end-to-end runtime for this implementation of NPIP was 286 s, but there was a wide variation from case to case. Conclusions: The authors have shown that NPIP can automatically generate skew line needle configurations with the aforementioned properties, and that given the correct input parameters, NPIP can generate needle configurations which meet dose objectives and use as many or fewer needles than the current HDR brachytherapy workflow. Combined with robot assisted brachytherapy, this system has the potential to reduce side effects associated with treatment. A physical trial should be done to test the implant feasibility of NPIP needle configurations.« less

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks.

PubMed

Rumschinski, Philipp; Borchers, Steffen; Bosio, Sandro; Weismantel, Robert; Findeisen, Rolf

2010-05-25

Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates.

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks

PubMed Central

2010-01-01

Background Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. Results In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. Conclusions The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates. PMID:20500862

Variations of cosmic large-scale structure covariance matrices across parameter space

NASA Astrophysics Data System (ADS)

Reischke, Robert; Kiessling, Alina; Schäfer, Björn Malte

2017-03-01

The likelihood function for cosmological parameters, given by e.g. weak lensing shear measurements, depends on contributions to the covariance induced by the non-linear evolution of the cosmic web. As highly non-linear clustering to date has only been described by numerical N-body simulations in a reliable and sufficiently precise way, the necessary computational costs for estimating those covariances at different points in parameter space are tremendous. In this work, we describe the change of the matter covariance and the weak lensing covariance matrix as a function of cosmological parameters by constructing a suitable basis, where we model the contribution to the covariance from non-linear structure formation using Eulerian perturbation theory at third order. We show that our formalism is capable of dealing with large matrices and reproduces expected degeneracies and scaling with cosmological parameters in a reliable way. Comparing our analytical results to numerical simulations, we find that the method describes the variation of the covariance matrix found in the SUNGLASS weak lensing simulation pipeline within the errors at one-loop and tree-level for the spectrum and the trispectrum, respectively, for multipoles up to ℓ ≤ 1300. We show that it is possible to optimize the sampling of parameter space where numerical simulations should be carried out by minimizing interpolation errors and propose a corresponding method to distribute points in parameter space in an economical way.

Dynamic response analysis of structure under time-variant interval process model

NASA Astrophysics Data System (ADS)

Xia, Baizhan; Qin, Yuan; Yu, Dejie; Jiang, Chao

2016-10-01

Due to the aggressiveness of the environmental factor, the variation of the dynamic load, the degeneration of the material property and the wear of the machine surface, parameters related with the structure are distinctly time-variant. Typical model for time-variant uncertainties is the random process model which is constructed on the basis of a large number of samples. In this work, we propose a time-variant interval process model which can be effectively used to deal with time-variant uncertainties with limit information. And then two methods are presented for the dynamic response analysis of the structure under the time-variant interval process model. The first one is the direct Monte Carlo method (DMCM) whose computational burden is relative high. The second one is the Monte Carlo method based on the Chebyshev polynomial expansion (MCM-CPE) whose computational efficiency is high. In MCM-CPE, the dynamic response of the structure is approximated by the Chebyshev polynomials which can be efficiently calculated, and then the variational range of the dynamic response is estimated according to the samples yielded by the Monte Carlo method. To solve the dependency phenomenon of the interval operation, the affine arithmetic is integrated into the Chebyshev polynomial expansion. The computational effectiveness and efficiency of MCM-CPE is verified by two numerical examples, including a spring-mass-damper system and a shell structure.

Electronic structure and optical properties of metal doped tetraphenylporphyrins

NASA Astrophysics Data System (ADS)

Shah, Esha V.; Roy, Debesh R.

2018-05-01

A density functional scrutiny on the structure, electronic and optical properties of metal doped tetraphenylporphyrins MTPP (M=Fe, Co, Ni) is performed. The structural stability of the molecules is evaluated based on the electronic parameters like HOMO-LUMO gap (HLG), chemical hardness (η) and binding energy of the central metal atom to the molecular frame etc. The computed UltraViolet-Visible (UV-Vis) optical absorption spectra for all the compounds are also compared. The molecular structures reported are the lowest energy configurations. The entire calculations are carried out with a widely reliable functional, viz. B3LYP with a popular basis set which includes a scaler relativistic effect, viz. LANL2DZ.

Adaptable structural synthesis using advanced analysis and optimization coupled by a computer operating system

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.; Bhat, R. B.

1979-01-01

A finite element program is linked with a general purpose optimization program in a 'programing system' which includes user supplied codes that contain problem dependent formulations of the design variables, objective function and constraints. The result is a system adaptable to a wide spectrum of structural optimization problems. In a sample of numerical examples, the design variables are the cross-sectional dimensions and the parameters of overall shape geometry, constraints are applied to stresses, displacements, buckling and vibration characteristics, and structural mass is the objective function. Thin-walled, built-up structures and frameworks are included in the sample. Details of the system organization and characteristics of the component programs are given.

A Benchmark Problem for Development of Autonomous Structural Modal Identification

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; Woodard, Stanley E.; Juang, Jer-Nan

1996-01-01

This paper summarizes modal identification results obtained using an autonomous version of the Eigensystem Realization Algorithm on a dynamically complex, laboratory structure. The benchmark problem uses 48 of 768 free-decay responses measured in a complete modal survey test. The true modal parameters of the structure are well known from two previous, independent investigations. Without user involvement, the autonomous data analysis identified 24 to 33 structural modes with good to excellent accuracy in 62 seconds of CPU time (on a DEC Alpha 4000 computer). The modal identification technique described in the paper is the baseline algorithm for NASA's Autonomous Dynamics Determination (ADD) experiment scheduled to fly on International Space Station assembly flights in 1997-1999.

Structure of turbulent non-premixed flames modeled with two-step chemistry

NASA Technical Reports Server (NTRS)

Chen, J. H.; Mahalingam, S.; Puri, I. K.; Vervisch, L.

1992-01-01

Direct numerical simulations of turbulent diffusion flames modeled with finite-rate, two-step chemistry, A + B yields I, A + I yields P, were carried out. A detailed analysis of the turbulent flame structure reveals the complex nature of the penetration of various reactive species across two reaction zones in mixture fraction space. Due to this two zone structure, these flames were found to be robust, resisting extinction over the parameter ranges investigated. As in single-step computations, mixture fraction dissipation rate and the mixture fraction were found to be statistically correlated. Simulations involving unequal molecular diffusivities suggest that the small scale mixing process and, hence, the turbulent flame structure is sensitive to the Schmidt number.

An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks

PubMed Central

Xie, Xiurui; Qu, Hong; Liu, Guisong; Zhang, Malu; Kurths, Jürgen

2016-01-01

The spiking neural networks (SNNs) are the third generation of neural networks and perform remarkably well in cognitive tasks such as pattern recognition. The spike emitting and information processing mechanisms found in biological cognitive systems motivate the application of the hierarchical structure and temporal encoding mechanism in spiking neural networks, which have exhibited strong computational capability. However, the hierarchical structure and temporal encoding approach require neurons to process information serially in space and time respectively, which reduce the training efficiency significantly. For training the hierarchical SNNs, most existing methods are based on the traditional back-propagation algorithm, inheriting its drawbacks of the gradient diffusion and the sensitivity on parameters. To keep the powerful computation capability of the hierarchical structure and temporal encoding mechanism, but to overcome the low efficiency of the existing algorithms, a new training algorithm, the Normalized Spiking Error Back Propagation (NSEBP) is proposed in this paper. In the feedforward calculation, the output spike times are calculated by solving the quadratic function in the spike response model instead of detecting postsynaptic voltage states at all time points in traditional algorithms. Besides, in the feedback weight modification, the computational error is propagated to previous layers by the presynaptic spike jitter instead of the gradient decent rule, which realizes the layer-wised training. Furthermore, our algorithm investigates the mathematical relation between the weight variation and voltage error change, which makes the normalization in the weight modification applicable. Adopting these strategies, our algorithm outperforms the traditional SNN multi-layer algorithms in terms of learning efficiency and parameter sensitivity, that are also demonstrated by the comprehensive experimental results in this paper. PMID:27044001

Structural identifiability analysis of a cardiovascular system model.

PubMed

Pironet, Antoine; Dauby, Pierre C; Chase, J Geoffrey; Docherty, Paul D; Revie, James A; Desaive, Thomas

2016-05-01

The six-chamber cardiovascular system model of Burkhoff and Tyberg has been used in several theoretical and experimental studies. However, this cardiovascular system model (and others derived from it) are not identifiable from any output set. In this work, two such cases of structural non-identifiability are first presented. These cases occur when the model output set only contains a single type of information (pressure or volume). A specific output set is thus chosen, mixing pressure and volume information and containing only a limited number of clinically available measurements. Then, by manipulating the model equations involving these outputs, it is demonstrated that the six-chamber cardiovascular system model is structurally globally identifiable. A further simplification is made, assuming known cardiac valve resistances. Because of the poor practical identifiability of these four parameters, this assumption is usual. Under this hypothesis, the six-chamber cardiovascular system model is structurally identifiable from an even smaller dataset. As a consequence, parameter values computed from limited but well-chosen datasets are theoretically unique. This means that the parameter identification procedure can safely be performed on the model from such a well-chosen dataset. Thus, the model may be considered suitable for use in diagnosis. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

On the P 21/m and Pmmn pathways of the B1 B2 phase transition in NaCl: a quantum-mechanical study

NASA Astrophysics Data System (ADS)

Catti, Michele

2004-06-01

The monoclinic P 21/m and orthorhombic Pmmn (Watanabe et al' s-type) mechanisms of the high-pressure phase transition of NaCl between the B1 (rocksalt, Fm\\overline 3 m ) and B2 (CsCl-like, Pm\\overline 3 m ) cubic phases were investigated by ab initio DFT techniques with all-electron localized basis sets. Enthalpy profiles versus the order parameter were computed at constant pressures of 15, 26.3 (equilibrium) and 35 GPa for each pathway. The monoclinic path shows a lower activation enthalpy at the equilibrium pressure, but at different p values (hysteresis effects) the other mechanism becomes competitive. In the P 21/m case, sharp jumps of structural parameters are observed along the transformation coordinate, which can be explained by a mechanism based on discontinuous sliding of alternating pairs of (100) atomic layers. This accounts also for the predicted formation of a metastable intermediate Cmcm phase with TlI-like structure, similar to that observed experimentally at high pressure in AgCl, and the relations with the KOH structure are discussed, too. On the other hand, along the Pmmn pathway the structural parameters vary quite smoothly, indicating a continuous motion of neighbouring atomic planes within the constraint of the additional mirror symmetry.