The Computation of Orthogonal Independent Cluster Solutions and Their Oblique Analogs in Factor Analysis.

ERIC Educational Resources Information Center

Hofmann, Richard J.

A very general model for the computation of independent cluster solutions in factor analysis is presented. The model is discussed as being either orthogonal or oblique. Furthermore, it is demonstrated that for every orthogonal independent cluster solution there is an oblique analog. Using three illustrative examples, certain generalities are made…

Learning general phonological rules from distributional information: a computational model.

PubMed

Calamaro, Shira; Jarosz, Gaja

2015-04-01

Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony (Peperkamp, Le Calvez, Nadal, & Dupoux, 2006). This paper extends the model to account for learning of a broader set of phonological alternations and the formalization of these alternations as general rules. In Experiment 1, we apply the original model to new data in Dutch and demonstrate its limitations in learning nonallophonic rules. In Experiment 2, we extend the model to allow it to learn general rules for alternations that apply to a class of segments. In Experiment 3, the model is further extended to allow for generalization by context; we argue that this generalization must be constrained by linguistic principles. Copyright © 2014 Cognitive Science Society, Inc.

A Systematic Investigation of Computation Models for Predicting Adverse Drug Reactions (ADRs)

PubMed Central

Kuang, Qifan; Wang, MinQi; Li, Rong; Dong, YongCheng; Li, Yizhou; Li, Menglong

2014-01-01

Background Early and accurate identification of adverse drug reactions (ADRs) is critically important for drug development and clinical safety. Computer-aided prediction of ADRs has attracted increasing attention in recent years, and many computational models have been proposed. However, because of the lack of systematic analysis and comparison of the different computational models, there remain limitations in designing more effective algorithms and selecting more useful features. There is therefore an urgent need to review and analyze previous computation models to obtain general conclusions that can provide useful guidance to construct more effective computational models to predict ADRs. Principal Findings In the current study, the main work is to compare and analyze the performance of existing computational methods to predict ADRs, by implementing and evaluating additional algorithms that have been earlier used for predicting drug targets. Our results indicated that topological and intrinsic features were complementary to an extent and the Jaccard coefficient had an important and general effect on the prediction of drug-ADR associations. By comparing the structure of each algorithm, final formulas of these algorithms were all converted to linear model in form, based on this finding we propose a new algorithm called the general weighted profile method and it yielded the best overall performance among the algorithms investigated in this paper. Conclusion Several meaningful conclusions and useful findings regarding the prediction of ADRs are provided for selecting optimal features and algorithms. PMID:25180585

Computational study on cortical spreading depression based on a generalized cellular automaton model

NASA Astrophysics Data System (ADS)

Chen, Shangbin; Hu, Lele; Li, Bing; Xu, Changcheng; Liu, Qian

2009-02-01

Cortical spreading depression (CSD) is an important neurophysiological phenomenon correlating with some neural disorders, such as migraine, cerebral ischemia and epilepsy. By now, we are still not clear about the mechanisms of CSD's initiation and propagation, also the relevance between CSD and those neural diseases. Nevertheless, characterization of CSD, especially the spatiotemporal evolution, will promote the understanding of the CSD's nature and mechanisms. Besides the previous experimental work on charactering the spatiotemporal evolution of CSD in rats by optical intrinsic signal imaging, a computational study based on a generalized cellular automaton (CA) model was proposed here. In the model, we exploited a generalized neighborhood connection rule: a central CA cell is related with a group of surrounding CA cells with different weight coefficients. By selecting special parameters, the generalized CA model could be transformed to the traditional CA models with von Neumann, Moore and hexagon neighborhood connection means. Hence, the new model covered several properties of CSD simulated in traditional CA models: 1) expanding from the origin site like a circular wave; 2) annihilation of two waves traveling in opposite directions after colliding; 3) wavefront of CSD breaking and recovering when and after encountering an obstacle. By setting different refractory period in the different CA lattice field, different connection coefficient in different direction within the defined neighborhood, inhomogeneous propagation of CSD was simulated with high fidelity. The computational results were analogous to the reported time-varying CSD waves by optical imaging. So, the generalized CA model would be useful to study CSD because of its intuitive appeal and computational efficiency.

Evaluating a Computational Model of Social Causality and Responsibility

DTIC Science & Technology

2006-01-01

Evaluating a Computational Model of Social Causality and Responsibility Wenji Mao University of Southern California Institute for Creative...empirically evaluate a computa- tional model of social causality and responsibility against human social judgments. Results from our experimental...developed a general computational model of social cau- sality and responsibility [10, 11] that formalizes the factors people use in reasoning about

Computer Modeling and Simulation

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

Pronskikh, V. S.

2014-05-09

Verification and validation of computer codes and models used in simulation are two aspects of the scientific practice of high importance and have recently been discussed by philosophers of science. While verification is predominantly associated with the correctness of the way a model is represented by a computer code or algorithm, validation more often refers to model’s relation to the real world and its intended use. It has been argued that because complex simulations are generally not transparent to a practitioner, the Duhem problem can arise for verification and validation due to their entanglement; such an entanglement makes it impossiblemore » to distinguish whether a coding error or model’s general inadequacy to its target should be blamed in the case of the model failure. I argue that in order to disentangle verification and validation, a clear distinction between computer modeling (construction of mathematical computer models of elementary processes) and simulation (construction of models of composite objects and processes by means of numerical experimenting with them) needs to be made. Holding on to that distinction, I propose to relate verification (based on theoretical strategies such as inferences) to modeling and validation, which shares the common epistemology with experimentation, to simulation. To explain reasons of their intermittent entanglement I propose a weberian ideal-typical model of modeling and simulation as roles in practice. I suggest an approach to alleviate the Duhem problem for verification and validation generally applicable in practice and based on differences in epistemic strategies and scopes« less

Description of the General Equilibrium Model of Ecosystem Services (GEMES)

Treesearch

Travis Warziniack; David Finnoff; Jenny Apriesnig

2017-01-01

This paper serves as documentation for the General Equilibrium Model of Ecosystem Services (GEMES). GEMES is a regional computable general equilibrium model that is composed of values derived from natural capital and ecosystem services. It models households, producing sectors, and governments, linked to one another through commodity and factor markets. GEMES was...

NON-SPATIAL CALIBRATIONS OF A GENERAL UNIT MODEL FOR ECOSYSTEM SIMULATIONS. (R825792)

EPA Science Inventory

General Unit Models simulate system interactions aggregated within one spatial unit of resolution. For unit models to be applicable to spatial computer simulations, they must be formulated generally enough to simulate all habitat elements within the landscape. We present the d...

NON-SPATIAL CALIBRATIONS OF A GENERAL UNIT MODEL FOR ECOSYSTEM SIMULATIONS. (R827169)

EPA Science Inventory

General Unit Models simulate system interactions aggregated within one spatial unit of resolution. For unit models to be applicable to spatial computer simulations, they must be formulated generally enough to simulate all habitat elements within the landscape. We present the d...

First Order Fire Effects Model: FOFEM 4.0, user's guide

Treesearch

Elizabeth D. Reinhardt; Robert E. Keane; James K. Brown

1997-01-01

A First Order Fire Effects Model (FOFEM) was developed to predict the direct consequences of prescribed fire and wildfire. FOFEM computes duff and woody fuel consumption, smoke production, and fire-caused tree mortality for most forest and rangeland types in the United States. The model is available as a computer program for PC or Data General computer.

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

Farrell, Kathryn, E-mail: kfarrell@ices.utexas.edu; Oden, J. Tinsley, E-mail: oden@ices.utexas.edu; Faghihi, Danial, E-mail: danial@ices.utexas.edu

A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.

THE FUTURE OF COMPUTER-BASED TOXICITY PREDICTION: MECHANISM-BASED MODELS VS. INFORMATION MINING APPROACHES

EPA Science Inventory

The Future of Computer-Based Toxicity Prediction:
Mechanism-Based Models vs. Information Mining Approaches

When we speak of computer-based toxicity prediction, we are generally referring to a broad array of approaches which rely primarily upon chemical structure ...

Learning optimal quantum models is NP-hard

NASA Astrophysics Data System (ADS)

Stark, Cyril J.

2018-02-01

Physical modeling translates measured data into a physical model. Physical modeling is a major objective in physics and is generally regarded as a creative process. How good are computers at solving this task? Here, we show that in the absence of physical heuristics, the inference of optimal quantum models cannot be computed efficiently (unless P=NP ). This result illuminates rigorous limits to the extent to which computers can be used to further our understanding of nature.

Introductory Molecular Orbital Theory: An Honors General Chemistry Computational Lab as Implemented Using Three-Dimensional Modeling Software

ERIC Educational Resources Information Center

Ruddick, Kristie R.; Parrill, Abby L.; Petersen, Richard L.

2012-01-01

In this study, a computational molecular orbital theory experiment was implemented in a first-semester honors general chemistry course. Students used the GAMESS (General Atomic and Molecular Electronic Structure System) quantum mechanical software (as implemented in ChemBio3D) to optimize the geometry for various small molecules. Extended Huckel…

Computing Incompressible Flows With Free Surfaces

NASA Technical Reports Server (NTRS)

Kothe, D.

1994-01-01

RIPPLE computer program models transient, two-dimensional flows of incompressible fluids with surface tension on free surfaces of general shape. Surface tension modeled as volume force derived from continuum-surface-force model, giving RIPPLE both robustness and accuracy in modeling surface-tension effects at free surface. Also models wall adhesion effects. Written in FORTRAN 77.

Computers in aeronautics and space research at the Lewis Research Center

NASA Technical Reports Server (NTRS)

1991-01-01

This brochure presents a general discussion of the role of computers in aerospace research at NASA's Lewis Research Center (LeRC). Four particular areas of computer applications are addressed: computer modeling and simulation, computer assisted engineering, data acquisition and analysis, and computer controlled testing.

Accuracy assessment of the linear Poisson-Boltzmann equation and reparametrization of the OBC generalized Born model for nucleic acids and nucleic acid-protein complexes.

PubMed

Fogolari, Federico; Corazza, Alessandra; Esposito, Gennaro

2015-04-05

The generalized Born model in the Onufriev, Bashford, and Case (Onufriev et al., Proteins: Struct Funct Genet 2004, 55, 383) implementation has emerged as one of the best compromises between accuracy and speed of computation. For simulations of nucleic acids, however, a number of issues should be addressed: (1) the generalized Born model is based on a linear model and the linearization of the reference Poisson-Boltmann equation may be questioned for highly charged systems as nucleic acids; (2) although much attention has been given to potentials, solvation forces could be much less sensitive to linearization than the potentials; and (3) the accuracy of the Onufriev-Bashford-Case (OBC) model for nucleic acids depends on fine tuning of parameters. Here, we show that the linearization of the Poisson Boltzmann equation has mild effects on computed forces, and that with optimal choice of the OBC model parameters, solvation forces, essential for molecular dynamics simulations, agree well with those computed using the reference Poisson-Boltzmann model. © 2015 Wiley Periodicals, Inc.

A conceptual and computational model of moral decision making in human and artificial agents.

PubMed

Wallach, Wendell; Franklin, Stan; Allen, Colin

2010-07-01

Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for computational approaches to higher-order cognition. The need for increasingly autonomous artificial agents to factor moral considerations into their choices and actions has given rise to another new field of inquiry variously known as Machine Morality, Machine Ethics, Roboethics, or Friendly AI. In this study, we discuss how LIDA, an AGI model of human cognition, can be adapted to model both affective and rational features of moral decision making. Using the LIDA model, we will demonstrate how moral decisions can be made in many domains using the same mechanisms that enable general decision making. Comprehensive models of human cognition typically aim for compatibility with recent research in the cognitive and neural sciences. Global workspace theory, proposed by the neuropsychologist Bernard Baars (1988), is a highly regarded model of human cognition that is currently being computationally instantiated in several software implementations. LIDA (Franklin, Baars, Ramamurthy, & Ventura, 2005) is one such computational implementation. LIDA is both a set of computational tools and an underlying model of human cognition, which provides mechanisms that are capable of explaining how an agent's selection of its next action arises from bottom-up collection of sensory data and top-down processes for making sense of its current situation. We will describe how the LIDA model helps integrate emotions into the human decision-making process, and we will elucidate a process whereby an agent can work through an ethical problem to reach a solution that takes account of ethically relevant factors. Copyright © 2010 Cognitive Science Society, Inc.

Computer modeling of human decision making

NASA Technical Reports Server (NTRS)

Gevarter, William B.

1991-01-01

Models of human decision making are reviewed. Models which treat just the cognitive aspects of human behavior are included as well as models which include motivation. Both models which have associated computer programs, and those that do not, are considered. Since flow diagrams, that assist in constructing computer simulation of such models, were not generally available, such diagrams were constructed and are presented. The result provides a rich source of information, which can aid in construction of more realistic future simulations of human decision making.

Computational Toxicology: Application in Environmental Chemicals

EPA Science Inventory

This chapter provides an overview of computational models that describe various aspects of the source-to-health effect continuum. Fate and transport models describe the release, transportation, and transformation of chemicals from sources of emission throughout the general envir...

Ndarts

NASA Technical Reports Server (NTRS)

Jain, Abhinandan

2011-01-01

Ndarts software provides algorithms for computing quantities associated with the dynamics of articulated, rigid-link, multibody systems. It is designed as a general-purpose dynamics library that can be used for the modeling of robotic platforms, space vehicles, molecular dynamics, and other such applications. The architecture and algorithms in Ndarts are based on the Spatial Operator Algebra (SOA) theory for computational multibody and robot dynamics developed at JPL. It uses minimal, internal coordinate models. The algorithms are low-order, recursive scatter/ gather algorithms. In comparison with the earlier Darts++ software, this version has a more general and cleaner design needed to support a larger class of computational dynamics needs. It includes a frames infrastructure, allows algorithms to operate on subgraphs of the system, and implements lazy and deferred computation for better efficiency. Dynamics modeling modules such as Ndarts are core building blocks of control and simulation software for space, robotic, mechanism, bio-molecular, and material systems modeling.

General Algebraic Modeling System Tutorial | High-Performance Computing |

Science.gov Websites

power generation from two different fuels. The goal is to minimize the cost for one of the fuels while Here's a basic tutorial for modeling optimization problems with the General Algebraic Modeling System (GAMS). Overview The GAMS (General Algebraic Modeling System) package is essentially a compiler for a

A Digital Computer Simulation of Cardiovascular and Renal Physiology.

ERIC Educational Resources Information Center

Tidball, Charles S.

1979-01-01

Presents the physiological MACPEE, one of a family of digital computer simulations used in Canada and Great Britain. A general description of the model is provided, along with a sample of computer output format, options for making interventions, advanced capabilities, an evaluation, and technical information for running a MAC model. (MA)

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

PubMed Central

Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang

2011-01-01

An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows (“explaining away”) and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons. PMID:22219717

A School Finance Computer Simulation Model

ERIC Educational Resources Information Center

Boardman, Gerald R.

1974-01-01

Presents a description of the computer simulation model developed by the National Educational Finance Project for use by States in planning and evaluating alternative approaches for State support programs. Provides a general introduction to the model, a program operation overview, a sample run, and some conclusions. (Author/WM)

Assessment regarding the use of the computer aided analytical models in the calculus of the general strength of a ship hull

NASA Astrophysics Data System (ADS)

Hreniuc, V.; Hreniuc, A.; Pescaru, A.

2017-08-01

Solving a general strength problem of a ship hull may be done using analytical approaches which are useful to deduce the buoyancy forces distribution, the weighting forces distribution along the hull and the geometrical characteristics of the sections. These data are used to draw the free body diagrams and to compute the stresses. The general strength problems require a large amount of calculi, therefore it is interesting how a computer may be used to solve such problems. Using computer programming an engineer may conceive software instruments based on analytical approaches. However, before developing the computer code the research topic must be thoroughly analysed, in this way being reached a meta-level of understanding of the problem. The following stage is to conceive an appropriate development strategy of the original software instruments useful for the rapid development of computer aided analytical models. The geometrical characteristics of the sections may be computed using a bool algebra that operates with ‘simple’ geometrical shapes. By ‘simple’ we mean that for the according shapes we have direct calculus relations. In the set of ‘simple’ shapes we also have geometrical entities bounded by curves approximated as spline functions or as polygons. To conclude, computer programming offers the necessary support to solve general strength ship hull problems using analytical methods.

An overview of computer viruses in a research environment

NASA Technical Reports Server (NTRS)

Bishop, Matt

1991-01-01

The threat of attack by computer viruses is in reality a very small part of a much more general threat, specifically threats aimed at subverting computer security. Here, computer viruses are examined as a malicious logic in a research and development environment. A relation is drawn between the viruses and various models of security and integrity. Current research techniques aimed at controlling the threats posed to computer systems by threatening viruses in particular and malicious logic in general are examined. Finally, a brief examination of the vulnerabilities of research and development systems that malicious logic and computer viruses may exploit is undertaken.

A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems

NASA Astrophysics Data System (ADS)

Farrell, Kathryn; Oden, J. Tinsley; Faghihi, Danial

2015-08-01

A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.

Computation in generalised probabilisitic theories

NASA Astrophysics Data System (ADS)

Lee, Ciarán M.; Barrett, Jonathan

2015-08-01

From the general difficulty of simulating quantum systems using classical systems, and in particular the existence of an efficient quantum algorithm for factoring, it is likely that quantum computation is intrinsically more powerful than classical computation. At present, the best upper bound known for the power of quantum computation is that {{BQP}}\\subseteq {{AWPP}}, where {{AWPP}} is a classical complexity class (known to be included in {{PP}}, hence {{PSPACE}}). This work investigates limits on computational power that are imposed by simple physical, or information theoretic, principles. To this end, we define a circuit-based model of computation in a class of operationally-defined theories more general than quantum theory, and ask: what is the minimal set of physical assumptions under which the above inclusions still hold? We show that given only an assumption of tomographic locality (roughly, that multipartite states and transformations can be characterized by local measurements), efficient computations are contained in {{AWPP}}. This inclusion still holds even without assuming a basic notion of causality (where the notion is, roughly, that probabilities for outcomes cannot depend on future measurement choices). Following Aaronson, we extend the computational model by allowing post-selection on measurement outcomes. Aaronson showed that the corresponding quantum complexity class, {{PostBQP}}, is equal to {{PP}}. Given only the assumption of tomographic locality, the inclusion in {{PP}} still holds for post-selected computation in general theories. Hence in a world with post-selection, quantum theory is optimal for computation in the space of all operational theories. We then consider whether one can obtain relativized complexity results for general theories. It is not obvious how to define a sensible notion of a computational oracle in the general framework that reduces to the standard notion in the quantum case. Nevertheless, it is possible to define computation relative to a ‘classical oracle’. Then, we show there exists a classical oracle relative to which efficient computation in any theory satisfying the causality assumption does not include {{NP}}.

Strategy generalization across orientation tasks: testing a computational cognitive model.

PubMed

Gunzelmann, Glenn

2008-07-08

Humans use their spatial information processing abilities flexibly to facilitate problem solving and decision making in a variety of tasks. This article explores the question of whether a general strategy can be adapted for performing two different spatial orientation tasks by testing the predictions of a computational cognitive model. Human performance was measured on an orientation task requiring participants to identify the location of a target either on a map (find-on-map) or within an egocentric view of a space (find-in-scene). A general strategy instantiated in a computational cognitive model of the find-on-map task, based on the results from Gunzelmann and Anderson (2006), was adapted to perform both tasks and used to generate performance predictions for a new study. The qualitative fit of the model to the human data supports the view that participants were able to tailor a general strategy to the requirements of particular spatial tasks. The quantitative differences between the predictions of the model and the performance of human participants in the new experiment expose individual differences in sample populations. The model provides a means of accounting for those differences and a framework for understanding how human spatial abilities are applied to naturalistic spatial tasks that involve reasoning with maps. 2008 Cognitive Science Society, Inc.

Supersymmetric Sachdev-Ye-Kitaev models

DOE PAGES

Fu, Wenbo; Gaiotto, Davide; Maldacena, Juan; ...

2017-01-13

We discuss a supersymmetric generalization of the Sachdev-Ye-Kitaev (SYK) model. These are quantum mechanical models involving N Majorana fermions. The supercharge is given by a polynomial expression in terms of the Majorana fermions with random coefficients. The Hamiltonian is the square of the supercharge. The N = 1 model with a single supercharge has unbroken supersymmetry at large N , but nonperturbatively spontaneously broken supersymmetry in the exact theory. We analyze the model by looking at the large N equation, and also by performing numerical computations for small values of N . We also compute the large N spectrum ofmore » “singlet” operators, where we find a structure qualitatively similar to the ordinary SYK model. We also discuss an N = 2 version. In this case, the model preserves supersymmetry in the exact theory and we can compute a suitably weighted Witten index to count the number of ground states, which agrees with the large N computation of the entropy. In both cases, we discuss the supersymmetric generalizations of the Schwarzian action which give the dominant effects at low energies.« less

Some Useful Cost-Benefit Criteria for Evaluating Computer-Based Test Delivery Models and Systems

ERIC Educational Resources Information Center

Luecht, Richard M.

2005-01-01

Computer-based testing (CBT) is typically implemented using one of three general test delivery models: (1) multiple fixed testing (MFT); (2) computer-adaptive testing (CAT); or (3) multistage testing (MSTs). This article reviews some of the real cost drivers associated with CBT implementation--focusing on item production costs, the costs…

Real-time simulation of biological soft tissues: a PGD approach.

PubMed

Niroomandi, S; González, D; Alfaro, I; Bordeu, F; Leygue, A; Cueto, E; Chinesta, F

2013-05-01

We introduce here a novel approach for the numerical simulation of nonlinear, hyperelastic soft tissues at kilohertz feedback rates necessary for haptic rendering. This approach is based upon the use of proper generalized decomposition techniques, a generalization of PODs. Proper generalized decomposition techniques can be considered as a means of a priori model order reduction and provides a physics-based meta-model without the need for prior computer experiments. The suggested strategy is thus composed of an offline phase, in which a general meta-model is computed, and an online evaluation phase in which the results are obtained at real time. Results are provided that show the potential of the proposed technique, together with some benchmark test that shows the accuracy of the method. Copyright © 2013 John Wiley & Sons, Ltd.

Bayesian inference based on dual generalized order statistics from the exponentiated Weibull model

NASA Astrophysics Data System (ADS)

Al Sobhi, Mashail M.

2015-02-01

Bayesian estimation for the two parameters and the reliability function of the exponentiated Weibull model are obtained based on dual generalized order statistics (DGOS). Also, Bayesian prediction bounds for future DGOS from exponentiated Weibull model are obtained. The symmetric and asymmetric loss functions are considered for Bayesian computations. The Markov chain Monte Carlo (MCMC) methods are used for computing the Bayes estimates and prediction bounds. The results have been specialized to the lower record values. Comparisons are made between Bayesian and maximum likelihood estimators via Monte Carlo simulation.

Uncertainty quantification for environmental models

USGS Publications Warehouse

Hill, Mary C.; Lu, Dan; Kavetski, Dmitri; Clark, Martyn P.; Ye, Ming

2012-01-01

Environmental models are used to evaluate the fate of fertilizers in agricultural settings (including soil denitrification), the degradation of hydrocarbons at spill sites, and water supply for people and ecosystems in small to large basins and cities—to mention but a few applications of these models. They also play a role in understanding and diagnosing potential environmental impacts of global climate change. The models are typically mildly to extremely nonlinear. The persistent demand for enhanced dynamics and resolution to improve model realism [17] means that lengthy individual model execution times will remain common, notwithstanding continued enhancements in computer power. In addition, high-dimensional parameter spaces are often defined, which increases the number of model runs required to quantify uncertainty [2]. Some environmental modeling projects have access to extensive funding and computational resources; many do not. The many recent studies of uncertainty quantification in environmental model predictions have focused on uncertainties related to data error and sparsity of data, expert judgment expressed mathematically through prior information, poorly known parameter values, and model structure (see, for example, [1,7,9,10,13,18]). Approaches for quantifying uncertainty include frequentist (potentially with prior information [7,9]), Bayesian [13,18,19], and likelihood-based. A few of the numerous methods, including some sensitivity and inverse methods with consequences for understanding and quantifying uncertainty, are as follows: Bayesian hierarchical modeling and Bayesian model averaging; single-objective optimization with error-based weighting [7] and multi-objective optimization [3]; methods based on local derivatives [2,7,10]; screening methods like OAT (one at a time) and the method of Morris [14]; FAST (Fourier amplitude sensitivity testing) [14]; the Sobol' method [14]; randomized maximum likelihood [10]; Markov chain Monte Carlo (MCMC) [10]. There are also bootstrapping and cross-validation approaches.Sometimes analyses are conducted using surrogate models [12]. The availability of so many options can be confusing. Categorizing methods based on fundamental questions assists in communicating the essential results of uncertainty analyses to stakeholders. Such questions can focus on model adequacy (e.g., How well does the model reproduce observed system characteristics and dynamics?) and sensitivity analysis (e.g., What parameters can be estimated with available data? What observations are important to parameters and predictions? What parameters are important to predictions?), as well as on the uncertainty quantification (e.g., How accurate and precise are the predictions?). The methods can also be classified by the number of model runs required: few (10s to 1000s) or many (10,000s to 1,000,000s). Of the methods listed above, the most computationally frugal are generally those based on local derivatives; MCMC methods tend to be among the most computationally demanding. Surrogate models (emulators)do not necessarily produce computational frugality because many runs of the full model are generally needed to create a meaningful surrogate model. With this categorization, we can, in general, address all the fundamental questions mentioned above using either computationally frugal or demanding methods. Model development and analysis can thus be conducted consistently using either computation-ally frugal or demanding methods; alternatively, different fundamental questions can be addressed using methods that require different levels of effort. Based on this perspective, we pose the question: Can computationally frugal methods be useful companions to computationally demanding meth-ods? The reliability of computationally frugal methods generally depends on the model being reasonably linear, which usually means smooth nonlin-earities and the assumption of Gaussian errors; both tend to be more valid with more linear

Modeling Biodegradation and Reactive Transport: Analytical and Numerical Models

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

Sun, Y; Glascoe, L

The computational modeling of the biodegradation of contaminated groundwater systems accounting for biochemical reactions coupled to contaminant transport is a valuable tool for both the field engineer/planner with limited computational resources and the expert computational researcher less constrained by time and computer power. There exists several analytical and numerical computer models that have been and are being developed to cover the practical needs put forth by users to fulfill this spectrum of computational demands. Generally, analytical models provide rapid and convenient screening tools running on very limited computational power, while numerical models can provide more detailed information with consequent requirementsmore » of greater computational time and effort. While these analytical and numerical computer models can provide accurate and adequate information to produce defensible remediation strategies, decisions based on inadequate modeling output or on over-analysis can have costly and risky consequences. In this chapter we consider both analytical and numerical modeling approaches to biodegradation and reactive transport. Both approaches are discussed and analyzed in terms of achieving bioremediation goals, recognizing that there is always a tradeoff between computational cost and the resolution of simulated systems.« less

Solving large mixed linear models using preconditioned conjugate gradient iteration.

PubMed

Strandén, I; Lidauer, M

1999-12-01

Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.

A Home Computer Primer.

ERIC Educational Resources Information Center

Stone, Antonia

1982-01-01

Provides general information on currently available microcomputers, computer programs (software), hardware requirements, software sources, costs, computer games, and programing. Includes a list of popular microcomputers, providing price category, model, list price, software (cassette, tape, disk), monitor specifications, amount of random access…

Using generalized additive (mixed) models to analyze single case designs.

PubMed

Shadish, William R; Zuur, Alain F; Sullivan, Kristynn J

2014-04-01

This article shows how to apply generalized additive models and generalized additive mixed models to single-case design data. These models excel at detecting the functional form between two variables (often called trend), that is, whether trend exists, and if it does, what its shape is (e.g., linear and nonlinear). In many respects, however, these models are also an ideal vehicle for analyzing single-case designs because they can consider level, trend, variability, overlap, immediacy of effect, and phase consistency that single-case design researchers examine when interpreting a functional relation. We show how these models can be implemented in a wide variety of ways to test whether treatment is effective, whether cases differ from each other, whether treatment effects vary over cases, and whether trend varies over cases. We illustrate diagnostic statistics and graphs, and we discuss overdispersion of data in detail, with examples of quasibinomial models for overdispersed data, including how to compute dispersion and quasi-AIC fit indices in generalized additive models. We show how generalized additive mixed models can be used to estimate autoregressive models and random effects and discuss the limitations of the mixed models compared to generalized additive models. We provide extensive annotated syntax for doing all these analyses in the free computer program R. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

User's manual for BRI-STARS (BRIdge Stream Tube model for Alluvial River Simulation)

DOT National Transportation Integrated Search

1998-07-01

There is a need for a generalized water and sediment-routing computer model for solving complicated river engineering problems with limited data and resources. This program should have the following capabilities: to compute hydraulic parameters for o...

Parallel computing of a climate model on the dawn 1000 by domain decomposition method

NASA Astrophysics Data System (ADS)

Bi, Xunqiang

1997-12-01

In this paper the parallel computing of a grid-point nine-level atmospheric general circulation model on the Dawn 1000 is introduced. The model was developed by the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS). The Dawn 1000 is a MIMD massive parallel computer made by National Research Center for Intelligent Computer (NCIC), CAS. A two-dimensional domain decomposition method is adopted to perform the parallel computing. The potential ways to increase the speed-up ratio and exploit more resources of future massively parallel supercomputation are also discussed.

Application of Local Discretization Methods in the NASA Finite-Volume General Circulation Model

NASA Technical Reports Server (NTRS)

Yeh, Kao-San; Lin, Shian-Jiann; Rood, Richard B.

2002-01-01

We present the basic ideas of the dynamics system of the finite-volume General Circulation Model developed at NASA Goddard Space Flight Center for climate simulations and other applications in meteorology. The dynamics of this model is designed with emphases on conservative and monotonic transport, where the property of Lagrangian conservation is used to maintain the physical consistency of the computational fluid for long-term simulations. As the model benefits from the noise-free solutions of monotonic finite-volume transport schemes, the property of Lagrangian conservation also partly compensates the accuracy of transport for the diffusion effects due to the treatment of monotonicity. By faithfully maintaining the fundamental laws of physics during the computation, this model is able to achieve sufficient accuracy for the global consistency of climate processes. Because the computing algorithms are based on local memory, this model has the advantage of efficiency in parallel computation with distributed memory. Further research is yet desirable to reduce the diffusion effects of monotonic transport for better accuracy, and to mitigate the limitation due to fast-moving gravity waves for better efficiency.

Towards a framework for testing general relativity with extreme-mass-ratio-inspiral observations

NASA Astrophysics Data System (ADS)

Chua, A. J. K.; Hee, S.; Handley, W. J.; Higson, E.; Moore, C. J.; Gair, J. R.; Hobson, M. P.; Lasenby, A. N.

2018-07-01

Extreme-mass-ratio-inspiral observations from future space-based gravitational-wave detectors such as LISA will enable strong-field tests of general relativity with unprecedented precision, but at prohibitive computational cost if existing statistical techniques are used. In one such test that is currently employed for LIGO black hole binary mergers, generic deviations from relativity are represented by N deformation parameters in a generalized waveform model; the Bayesian evidence for each of its 2N combinatorial submodels is then combined into a posterior odds ratio for modified gravity over relativity in a null-hypothesis test. We adapt and apply this test to a generalized model for extreme-mass-ratio inspirals constructed on deformed black hole spacetimes, and focus our investigation on how computational efficiency can be increased through an evidence-free method of model selection. This method is akin to the algorithm known as product-space Markov chain Monte Carlo, but uses nested sampling and improved error estimates from a rethreading technique. We perform benchmarking and robustness checks for the method, and find order-of-magnitude computational gains over regular nested sampling in the case of synthetic data generated from the null model.

Rapid State Space Modeling Tool for Rectangular Wing Aeroservoelastic Studies

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Conyers, Howard J.; Mavris, Dimitri N.

2014-01-01

This paper introduces a modeling and simulation tool for aeroservoelastic analysis of rectangular wings with trailing edge control surfaces. The inputs to the code are planform design parameters such as wing span, aspect ratio and number of control surfaces. A doublet lattice approach is taken to compute generalized forces. A rational function approximation is computed. The output, computed in a few seconds, is a state space aeroservoelastic model which can be used for analysis and control design. The tool is fully parameterized with default information so there is little required interaction with the model developer. Although, all parameters can be easily modified if desired.The focus of this paper is on tool presentation, verification and validation. This process is carried out in stages throughout the paper. The rational function approximation is verified against computed generalized forces for a plate model. A model composed of finite element plates is compared to a modal analysis from commercial software and an independently conducted experimental ground vibration test analysis. Aeroservoelastic analysis is the ultimate goal of this tool. Therefore the flutter speed and frequency for a clamped plate are computed using V-g and V-f analysis. The computational results are compared to a previously published computational analysis and wind tunnel results for the same structure. Finally a case study of a generic wing model with a single control surface is presented. Verification of the state space model is presented in comparison to V-g and V-f analysis. This also includes the analysis of the model in response to a 1-cos gust.

Rapid State Space Modeling Tool for Rectangular Wing Aeroservoelastic Studies

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Conyers, Howard J.; Mavris, Dimitri N.

2015-01-01

This paper introduces a modeling and simulation tool for aeroservoelastic analysis of rectangular wings with trailing-edge control surfaces. The inputs to the code are planform design parameters such as wing span, aspect ratio, and number of control surfaces. Using this information, the generalized forces are computed using the doublet-lattice method. Using Roger's approximation, a rational function approximation is computed. The output, computed in a few seconds, is a state space aeroservoelastic model which can be used for analysis and control design. The tool is fully parameterized with default information so there is little required interaction with the model developer. All parameters can be easily modified if desired. The focus of this paper is on tool presentation, verification, and validation. These processes are carried out in stages throughout the paper. The rational function approximation is verified against computed generalized forces for a plate model. A model composed of finite element plates is compared to a modal analysis from commercial software and an independently conducted experimental ground vibration test analysis. Aeroservoelastic analysis is the ultimate goal of this tool, therefore, the flutter speed and frequency for a clamped plate are computed using damping-versus-velocity and frequency-versus-velocity analysis. The computational results are compared to a previously published computational analysis and wind-tunnel results for the same structure. A case study of a generic wing model with a single control surface is presented. Verification of the state space model is presented in comparison to damping-versus-velocity and frequency-versus-velocity analysis, including the analysis of the model in response to a 1-cos gust.

Rapid State Space Modeling Tool for Rectangular Wing Aeroservoelastic Studies

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Conyers, Howard Jason; Mavris, Dimitri N.

2015-01-01

This report introduces a modeling and simulation tool for aeroservoelastic analysis of rectangular wings with trailing-edge control surfaces. The inputs to the code are planform design parameters such as wing span, aspect ratio, and number of control surfaces. Using this information, the generalized forces are computed using the doublet-lattice method. Using Roger's approximation, a rational function approximation is computed. The output, computed in a few seconds, is a state space aeroservoelastic model which can be used for analysis and control design. The tool is fully parameterized with default information so there is little required interaction with the model developer. All parameters can be easily modified if desired. The focus of this report is on tool presentation, verification, and validation. These processes are carried out in stages throughout the report. The rational function approximation is verified against computed generalized forces for a plate model. A model composed of finite element plates is compared to a modal analysis from commercial software and an independently conducted experimental ground vibration test analysis. Aeroservoelastic analysis is the ultimate goal of this tool, therefore, the flutter speed and frequency for a clamped plate are computed using damping-versus-velocity and frequency-versus-velocity analysis. The computational results are compared to a previously published computational analysis and wind-tunnel results for the same structure. A case study of a generic wing model with a single control surface is presented. Verification of the state space model is presented in comparison to damping-versus-velocity and frequency-versus-velocity analysis, including the analysis of the model in response to a 1-cos gust.

Generalized Born Models of Macromolecular Solvation Effects

NASA Astrophysics Data System (ADS)

Bashford, Donald; Case, David A.

2000-10-01

It would often be useful in computer simulations to use a simple description of solvation effects, instead of explicitly representing the individual solvent molecules. Continuum dielectric models often work well in describing the thermodynamic aspects of aqueous solvation, and approximations to such models that avoid the need to solve the Poisson equation are attractive because of their computational efficiency. Here we give an overview of one such approximation, the generalized Born model, which is simple and fast enough to be used for molecular dynamics simulations of proteins and nucleic acids. We discuss its strengths and weaknesses, both for its fidelity to the underlying continuum model and for its ability to replace explicit consideration of solvent molecules in macromolecular simulations. We focus particularly on versions of the generalized Born model that have a pair-wise analytical form, and therefore fit most naturally into conventional molecular mechanics calculations.

Analytical approximate solutions for a general class of nonlinear delay differential equations.

PubMed

Căruntu, Bogdan; Bota, Constantin

2014-01-01

We use the polynomial least squares method (PLSM), which allows us to compute analytical approximate polynomial solutions for a very general class of strongly nonlinear delay differential equations. The method is tested by computing approximate solutions for several applications including the pantograph equations and a nonlinear time-delay model from biology. The accuracy of the method is illustrated by a comparison with approximate solutions previously computed using other methods.

Dynamic modeling and optimal joint torque coordination of advanced robotic systems

NASA Astrophysics Data System (ADS)

Kang, Hee-Jun

The development is documented of an efficient dynamic modeling algorithm and the subsequent optimal joint input load coordination of advanced robotic systems for industrial application. A closed-form dynamic modeling algorithm for the general closed-chain robotic linkage systems is presented. The algorithm is based on the transfer of system dependence from a set of open chain Lagrangian coordinates to any desired system generalized coordinate set of the closed-chain. Three different techniques for evaluation of the kinematic closed chain constraints allow the representation of the dynamic modeling parameters in terms of system generalized coordinates and have no restriction with regard to kinematic redundancy. The total computational requirement of the closed-chain system model is largely dependent on the computation required for the dynamic model of an open kinematic chain. In order to improve computational efficiency, modification of an existing open-chain KIC based dynamic formulation is made by the introduction of the generalized augmented body concept. This algorithm allows a 44 pct. computational saving over the current optimized one (O(N4), 5995 when N = 6). As means of resolving redundancies in advanced robotic systems, local joint torque optimization is applied for effectively using actuator power while avoiding joint torque limits. The stability problem in local joint torque optimization schemes is eliminated by using fictitious dissipating forces which act in the necessary null space. The performance index representing the global torque norm is shown to be satisfactory. In addition, the resulting joint motion trajectory becomes conservative, after a transient stage, for repetitive cyclic end-effector trajectories. The effectiveness of the null space damping method is shown. The modular robot, which is built of well defined structural modules from a finite-size inventory and is controlled by one general computer system, is another class of evolving, highly versatile, advanced robotic systems. Therefore, finally, a module based dynamic modeling algorithm is presented for the dynamic coordination of such reconfigurable modular robotic systems. A user interactive module based manipulator analysis program (MBMAP) has been coded in C language running on 4D/70 Silicon Graphics.

User's manual for the generalized computer program system. Open-channel flow and sedimentation, TABS-2. Main text

NASA Astrophysics Data System (ADS)

Thomas, W. A.; McAnally, W. H., Jr.

1985-07-01

TABS-2 is a generalized numerical modeling system for open-channel flows, sedimentation, and constituent transport. It consists of more than 40 computer programs to perform modeling and related tasks. The major modeling components--RMA-2V, STUDH, and RMA-4--calculate two-dimensional, depth-averaged flows, sedimentation, and dispersive transport, respectively. The other programs in the system perform digitizing, mesh generation, data management, graphical display, output analysis, and model interfacing tasks. Utilities include file management and automatic generation of computer job control instructions. TABS-2 has been applied to a variety of waterways, including rivers, estuaries, bays, and marshes. It is designed for use by engineers and scientists who may not have a rigorous computer background. Use of the various components is described in Appendices A-O. The bound version of the report does not include the appendices. A looseleaf form with Appendices A-O is distributed to system users.

Modeling coliform-bacteria concentrations and pH in the salt-wedge reach of the Duwamish River Estuary, King County, Washington

USGS Publications Warehouse

Haushild, W.L.; Prych, Edmund A.

1976-01-01

Total- and fecal-coliform bacteria, plus pH, alkalinity, and dissolved inorganic carbon are water-quality parameters that have been added to an existing numerical model of water quality in the salt-wedge reach of the Duwamish River estuary in Washington. The coliform bacteria are modeled using a first-order decay (death) rate, which is a function of the local salinity, temperature, and daily solar radiation. The pH is computed by solving a set of chemical-equilibrium equations for carbonate-bicarbonate buffered aqueous solutions. Concentrations of total- and fecal-coliform bacteria computed by the model for the Duwamish River estuary during June-September 1971 generally agreed with observed concentrations within about 40 and 60 percent, respectively. The computed pH generally agreed with observed pH within about a 0.2 pH unit; however, for one 3-week period the computed pH was about a 0.4 unit lower than the observed pH. (Woodard-USGS)

Comparison of 2D Finite Element Modeling Assumptions with Results From 3D Analysis for Composite Skin-Stiffener Debonding

NASA Technical Reports Server (NTRS)

Krueger, Ronald; Paris, Isbelle L.; OBrien, T. Kevin; Minguet, Pierre J.

2004-01-01

The influence of two-dimensional finite element modeling assumptions on the debonding prediction for skin-stiffener specimens was investigated. Geometrically nonlinear finite element analyses using two-dimensional plane-stress and plane-strain elements as well as three different generalized plane strain type approaches were performed. The computed skin and flange strains, transverse tensile stresses and energy release rates were compared to results obtained from three-dimensional simulations. The study showed that for strains and energy release rate computations the generalized plane strain assumptions yielded results closest to the full three-dimensional analysis. For computed transverse tensile stresses the plane stress assumption gave the best agreement. Based on this study it is recommended that results from plane stress and plane strain models be used as upper and lower bounds. The results from generalized plane strain models fall between the results obtained from plane stress and plane strain models. Two-dimensional models may also be used to qualitatively evaluate the stress distribution in a ply and the variation of energy release rates and mixed mode ratios with delamination length. For more accurate predictions, however, a three-dimensional analysis is required.

Influence of 2D Finite Element Modeling Assumptions on Debonding Prediction for Composite Skin-stiffener Specimens Subjected to Tension and Bending

NASA Technical Reports Server (NTRS)

Krueger, Ronald; Minguet, Pierre J.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

The influence of two-dimensional finite element modeling assumptions on the debonding prediction for skin-stiffener specimens was investigated. Geometrically nonlinear finite element analyses using two-dimensional plane-stress and plane strain elements as well as three different generalized plane strain type approaches were performed. The computed deflections, skin and flange strains, transverse tensile stresses and energy release rates were compared to results obtained from three-dimensional simulations. The study showed that for strains and energy release rate computations the generalized plane strain assumptions yielded results closest to the full three-dimensional analysis. For computed transverse tensile stresses the plane stress assumption gave the best agreement. Based on this study it is recommended that results from plane stress and plane strain models be used as upper and lower bounds. The results from generalized plane strain models fall between the results obtained from plane stress and plane strain models. Two-dimensional models may also be used to qualitatively evaluate the stress distribution in a ply and the variation of energy release rates and mixed mode ratios with lamination length. For more accurate predictions, however, a three-dimensional analysis is required.

An Educational Approach to Computationally Modeling Dynamical Systems

ERIC Educational Resources Information Center

Chodroff, Leah; O'Neal, Tim M.; Long, David A.; Hemkin, Sheryl

2009-01-01

Chemists have used computational science methodologies for a number of decades and their utility continues to be unabated. For this reason we developed an advanced lab in computational chemistry in which students gain understanding of general strengths and weaknesses of computation-based chemistry by working through a specific research problem.…

Nearly Supersymmetric Dark Atoms

DOE PAGES

Behbahani, Siavosh R.; Jankowiak, Martin; Rube, Tomas; ...

2011-01-01

Theories of dark matter that support bound states are an intriguing possibility for the identity of the missing mass of the Universe. This article proposes a class of models of supersymmetric composite dark matter where the interactions with the Standard Model communicate supersymmetry breaking to the dark sector. In these models, supersymmetry breaking can be treated as a perturbation on the spectrum of bound states. Using a general formalism, the spectrum with leading supersymmetry effects is computed without specifying the details of the binding dynamics. The interactions of the composite states with the Standard Model are computed, and several benchmarkmore » models are described. General features of nonrelativistic supersymmetric bound states are emphasized.« less

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.

MOUSE (MODULAR ORIENTED UNCERTAINTY SYSTEM): A COMPUTERIZED UNCERTAINTY ANALYSIS SYSTEM (FOR MICRO- COMPUTERS)

EPA Science Inventory

Environmental engineering calculations involving uncertainties; either in the model itself or in the data, are far beyond the capabilities of conventional analysis for any but the simplest of models. There exist a number of general-purpose computer simulation languages, using Mon...

The Performance Improvement of the Lagrangian Particle Dispersion Model (LPDM) Using Graphics Processing Unit (GPU) Computing

DTIC Science & Technology

2017-08-01

access to the GPU for general purpose processing .5 CUDA is designed to work easily with multiple programming languages , including Fortran. CUDA is a...Using Graphics Processing Unit (GPU) Computing by Leelinda P Dawson Approved for public release; distribution unlimited...The Performance Improvement of the Lagrangian Particle Dispersion Model (LPDM) Using Graphics Processing Unit (GPU) Computing by Leelinda

Development of Integrated Programs for Aerospace-vehicle design (IPAD): Integrated information processing requirements

NASA Technical Reports Server (NTRS)

Southall, J. W.

1979-01-01

The engineering-specified requirements for integrated information processing by means of the Integrated Programs for Aerospace-Vehicle Design (IPAD) system are presented. A data model is described and is based on the design process of a typical aerospace vehicle. General data management requirements are specified for data storage, retrieval, generation, communication, and maintenance. Information management requirements are specified for a two-component data model. In the general portion, data sets are managed as entities, and in the specific portion, data elements and the relationships between elements are managed by the system, allowing user access to individual elements for the purpose of query. Computer program management requirements are specified for support of a computer program library, control of computer programs, and installation of computer programs into IPAD.

A Comparative Analysis of a Generalized Lanchester Equation Model and a Stochastic Computer Simulation Model.

DTIC Science & Technology

1987-03-01

model is one in which words or numerical descriptions are used to represent an entity or process. An example of a symbolic model is a mathematical ...are the third type of model used in modeling combat attrition. Analytical models are symbolic models which use mathematical symbols and equations to...simplicity and the ease of tracing through the mathematical computations. In this section I will discuss some of the shortcoming which have been

Data mining in soft computing framework: a survey.

PubMed

Mitra, S; Pal, S K; Mitra, P

2002-01-01

The present article provides a survey of the available literature on data mining using soft computing. A categorization has been provided based on the different soft computing tools and their hybridizations used, the data mining function implemented, and the preference criterion selected by the model. The utility of the different soft computing methodologies is highlighted. Generally fuzzy sets are suitable for handling the issues related to understandability of patterns, incomplete/noisy data, mixed media information and human interaction, and can provide approximate solutions faster. Neural networks are nonparametric, robust, and exhibit good learning and generalization capabilities in data-rich environments. Genetic algorithms provide efficient search algorithms to select a model, from mixed media data, based on some preference criterion/objective function. Rough sets are suitable for handling different types of uncertainty in data. Some challenges to data mining and the application of soft computing methodologies are indicated. An extensive bibliography is also included.

Organizational Strategies for End-User Computing Support.

ERIC Educational Resources Information Center

Blackmun, Robert R.; And Others

1988-01-01

Effective support for end users of computers has been an important issue in higher education from the first applications of general purpose mainframe computers through minicomputers, microcomputers, and supercomputers. The development of end user support is reviewed and organizational models are examined. (Author/MLW)

Molecular Modeling and Computational Chemistry at Humboldt State University.

ERIC Educational Resources Information Center

Paselk, Richard A.; Zoellner, Robert W.

2002-01-01

Describes a molecular modeling and computational chemistry (MM&CC) facility for undergraduate instruction and research at Humboldt State University. This facility complex allows the introduction of MM&CC throughout the chemistry curriculum with tailored experiments in general, organic, and inorganic courses as well as a new molecular modeling…

User's manual for master: Modeling of aerodynamic surfaces by 3-dimensional explicit representation. [input to three dimensional computational fluid dynamics

NASA Technical Reports Server (NTRS)

Gibson, S. G.

1983-01-01

A system of computer programs was developed to model general three dimensional surfaces. Surfaces are modeled as sets of parametric bicubic patches. There are also capabilities to transform coordinates, to compute mesh/surface intersection normals, and to format input data for a transonic potential flow analysis. A graphical display of surface models and intersection normals is available. There are additional capabilities to regulate point spacing on input curves and to compute surface/surface intersection curves. Input and output data formats are described; detailed suggestions are given for user input. Instructions for execution are given, and examples are shown.

Computational Modeling for the Flow Over a Multi-Element Airfoil

NASA Technical Reports Server (NTRS)

Liou, William W.; Liu, Feng-Jun

1999-01-01

The flow over a multi-element airfoil is computed using two two-equation turbulence models. The computations are performed using the INS2D) Navier-Stokes code for two angles of attack. Overset grids are used for the three-element airfoil. The computed results are compared with experimental data for the surface pressure, skin friction coefficient, and velocity magnitude. The computed surface quantities generally agree well with the measurement. The computed results reveal the possible existence of a mixing-layer-like region of flow next to the suction surface of the slat for both angles of attack.

Computational Literacy and "The Big Picture" Concerning Computers in Mathematics Education

ERIC Educational Resources Information Center

diSessa, Andrea A.

2018-01-01

This article develops some ideas concerning the "big picture" of how using computers might fundamentally change learning, with an emphasis on mathematics (and, more generally, STEM education). I develop the big-picture model of "computation as a new literacy" in some detail and with concrete examples of sixth grade students…

Computing ordinary least-squares parameter estimates for the National Descriptive Model of Mercury in Fish

USGS Publications Warehouse

Donato, David I.

2013-01-01

A specialized technique is used to compute weighted ordinary least-squares (OLS) estimates of the parameters of the National Descriptive Model of Mercury in Fish (NDMMF) in less time using less computer memory than general methods. The characteristics of the NDMMF allow the two products X'X and X'y in the normal equations to be filled out in a second or two of computer time during a single pass through the N data observations. As a result, the matrix X does not have to be stored in computer memory and the computationally expensive matrix multiplications generally required to produce X'X and X'y do not have to be carried out. The normal equations may then be solved to determine the best-fit parameters in the OLS sense. The computational solution based on this specialized technique requires O(8p2+16p) bytes of computer memory for p parameters on a machine with 8-byte double-precision numbers. This publication includes a reference implementation of this technique and a Gaussian-elimination solver in preliminary custom software.

Generalized Advanced Propeller Analysis System (GAPAS). Volume 2: Computer program user manual

NASA Technical Reports Server (NTRS)

Glatt, L.; Crawford, D. R.; Kosmatka, J. B.; Swigart, R. J.; Wong, E. W.

1986-01-01

The Generalized Advanced Propeller Analysis System (GAPAS) computer code is described. GAPAS was developed to analyze advanced technology multi-bladed propellers which operate on aircraft with speeds up to Mach 0.8 and altitudes up to 40,000 feet. GAPAS includes technology for analyzing aerodynamic, structural, and acoustic performance of propellers. The computer code was developed for the CDC 7600 computer and is currently available for industrial use on the NASA Langley computer. A description of all the analytical models incorporated in GAPAS is included. Sample calculations are also described as well as users requirements for modifying the analysis system. Computer system core requirements and running times are also discussed.

Program for computer aided reliability estimation

NASA Technical Reports Server (NTRS)

Mathur, F. P. (Inventor)

1972-01-01

A computer program for estimating the reliability of self-repair and fault-tolerant systems with respect to selected system and mission parameters is presented. The computer program is capable of operation in an interactive conversational mode as well as in a batch mode and is characterized by maintenance of several general equations representative of basic redundancy schemes in an equation repository. Selected reliability functions applicable to any mathematical model formulated with the general equations, used singly or in combination with each other, are separately stored. One or more system and/or mission parameters may be designated as a variable. Data in the form of values for selected reliability functions is generated in a tabular or graphic format for each formulated model.

Development of spectral analysis math models and software program and spectral analyzer, digital converter interface equipment design

NASA Technical Reports Server (NTRS)

Hayden, W. L.; Robinson, L. H.

1972-01-01

Spectral analyses of angle-modulated communication systems is studied by: (1) performing a literature survey of candidate power spectrum computational techniques, determining the computational requirements, and formulating a mathematical model satisfying these requirements; (2) implementing the model on UNIVAC 1230 digital computer as the Spectral Analysis Program (SAP); and (3) developing the hardware specifications for a data acquisition system which will acquire an input modulating signal for SAP. The SAP computational technique uses extended fast Fourier transform and represents a generalized approach for simple and complex modulating signals.

Generalized image charge solvation model for electrostatic interactions in molecular dynamics simulations of aqueous solutions

PubMed Central

Deng, Shaozhong; Xue, Changfeng; Baumketner, Andriy; Jacobs, Donald; Cai, Wei

2013-01-01

This paper extends the image charge solvation model (ICSM) [J. Chem. Phys. 131, 154103 (2009)], a hybrid explicit/implicit method to treat electrostatic interactions in computer simulations of biomolecules formulated for spherical cavities, to prolate spheroidal and triaxial ellipsoidal cavities, designed to better accommodate non-spherical solutes in molecular dynamics (MD) simulations. In addition to the utilization of a general truncated octahedron as the MD simulation box, central to the proposed extension is an image approximation method to compute the reaction field for a point charge placed inside such a non-spherical cavity by using a single image charge located outside the cavity. The resulting generalized image charge solvation model (GICSM) is tested in simulations of liquid water, and the results are analyzed in comparison with those obtained from the ICSM simulations as a reference. We find that, for improved computational efficiency due to smaller simulation cells and consequently a less number of explicit solvent molecules, the generalized model can still faithfully reproduce known static and dynamic properties of liquid water at least for systems considered in the present paper, indicating its great potential to become an accurate but more efficient alternative to the ICSM when bio-macromolecules of irregular shapes are to be simulated. PMID:23913979

Towards anatomic scale agent-based modeling with a massively parallel spatially explicit general-purpose model of enteric tissue (SEGMEnT_HPC).

PubMed

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis.

Interactions of spatial strategies producing generalization gradient and blocking: A computational approach

PubMed Central

Dollé, Laurent; Chavarriaga, Ricardo

2018-01-01

We present a computational model of spatial navigation comprising different learning mechanisms in mammals, i.e., associative, cognitive mapping and parallel systems. This model is able to reproduce a large number of experimental results in different variants of the Morris water maze task, including standard associative phenomena (spatial generalization gradient and blocking), as well as navigation based on cognitive mapping. Furthermore, we show that competitive and cooperative patterns between different navigation strategies in the model allow to explain previous apparently contradictory results supporting either associative or cognitive mechanisms for spatial learning. The key computational mechanism to reconcile experimental results showing different influences of distal and proximal cues on the behavior, different learning times, and different abilities of individuals to alternatively perform spatial and response strategies, relies in the dynamic coordination of navigation strategies, whose performance is evaluated online with a common currency through a modular approach. We provide a set of concrete experimental predictions to further test the computational model. Overall, this computational work sheds new light on inter-individual differences in navigation learning, and provides a formal and mechanistic approach to test various theories of spatial cognition in mammals. PMID:29630600

Symbolic computation of equivalence transformations and parameter reduction for nonlinear physical models

NASA Astrophysics Data System (ADS)

Cheviakov, Alexei F.

2017-11-01

An efficient systematic procedure is provided for symbolic computation of Lie groups of equivalence transformations and generalized equivalence transformations of systems of differential equations that contain arbitrary elements (arbitrary functions and/or arbitrary constant parameters), using the software package GeM for Maple. Application of equivalence transformations to the reduction of the number of arbitrary elements in a given system of equations is discussed, and several examples are considered. The first computational example of generalized equivalence transformations where the transformation of the dependent variable involves an arbitrary constitutive function is presented. As a detailed physical example, a three-parameter family of nonlinear wave equations describing finite anti-plane shear displacements of an incompressible hyperelastic fiber-reinforced medium is considered. Equivalence transformations are computed and employed to radically simplify the model for an arbitrary fiber direction, invertibly reducing the model to a simple form that corresponds to a special fiber direction, and involves no arbitrary elements. The presented computation algorithm is applicable to wide classes of systems of differential equations containing arbitrary elements.

Modeling the dynamics of multipartite quantum systems created departing from two-level systems using general local and non-local interactions

NASA Astrophysics Data System (ADS)

Delgado, Francisco

2017-12-01

Quantum information is an emergent area merging physics, mathematics, computer science and engineering. To reach its technological goals, it is requiring adequate approaches to understand how to combine physical restrictions, computational approaches and technological requirements to get functional universal quantum information processing. This work presents the modeling and the analysis of certain general type of Hamiltonian representing several physical systems used in quantum information and establishing a dynamics reduction in a natural grammar for bipartite processing based on entangled states.

Flexible Approaches to Computing Mediated Effects in Generalized Linear Models: Generalized Estimating Equations and Bootstrapping

ERIC Educational Resources Information Center

Schluchter, Mark D.

2008-01-01

In behavioral research, interest is often in examining the degree to which the effect of an independent variable X on an outcome Y is mediated by an intermediary or mediator variable M. This article illustrates how generalized estimating equations (GEE) modeling can be used to estimate the indirect or mediated effect, defined as the amount by…

Empirical flow parameters - a tool for hydraulic model validity assessment : [summary].

DOT National Transportation Integrated Search

2013-10-01

Hydraulic modeling assembles models based on generalizations of parameter values from textbooks, professional literature, computer program documentation, and engineering experience. Actual measurements adjacent to the model location are seldom availa...

Computer and control applications in a vegetable processing plant

USDA-ARS?s Scientific Manuscript database

There are many advantages to the use of computers and control in food industry. Software in the food industry takes 2 forms - general purpose commercial computer software and software for specialized applications, such as drying and thermal processing of foods. Many applied simulation models for d...

37 CFR 1.96 - Submission of computer program listings.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Apple Macintosh; (ii) Operating System Compatibility: MS-DOS, MS-Windows, Unix, or Macintosh; (iii) Line... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Submission of computer... Models, Exhibits, Specimens § 1.96 Submission of computer program listings. (a) General. Descriptions of...

37 CFR 1.96 - Submission of computer program listings.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Apple Macintosh; (ii) Operating System Compatibility: MS-DOS, MS-Windows, Unix, or Macintosh; (iii) Line... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false Submission of computer... Models, Exhibits, Specimens § 1.96 Submission of computer program listings. (a) General. Descriptions of...

37 CFR 1.96 - Submission of computer program listings.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Apple Macintosh; (ii) Operating System Compatibility: MS-DOS, MS-Windows, Unix, or Macintosh; (iii) Line... 37 Patents, Trademarks, and Copyrights 1 2011-07-01 2011-07-01 false Submission of computer... Models, Exhibits, Specimens § 1.96 Submission of computer program listings. (a) General. Descriptions of...

37 CFR 1.96 - Submission of computer program listings.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Apple Macintosh; (ii) Operating System Compatibility: MS-DOS, MS-Windows, Unix, or Macintosh; (iii) Line... 37 Patents, Trademarks, and Copyrights 1 2013-07-01 2013-07-01 false Submission of computer... Models, Exhibits, Specimens § 1.96 Submission of computer program listings. (a) General. Descriptions of...

37 CFR 1.96 - Submission of computer program listings.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Apple Macintosh; (ii) Operating System Compatibility: MS-DOS, MS-Windows, Unix, or Macintosh; (iii) Line... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false Submission of computer... Models, Exhibits, Specimens § 1.96 Submission of computer program listings. (a) General. Descriptions of...

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

Mueller, Juliane

MISO is an optimization framework for solving computationally expensive mixed-integer, black-box, global optimization problems. MISO uses surrogate models to approximate the computationally expensive objective function. Hence, derivative information, which is generally unavailable for black-box simulation objective functions, is not needed. MISO allows the user to choose the initial experimental design strategy, the type of surrogate model, and the sampling strategy.

Learning General Phonological Rules from Distributional Information: A Computational Model

ERIC Educational Resources Information Center

Calamaro, Shira; Jarosz, Gaja

2015-01-01

Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony…

A Computational Model of Early Argument Structure Acquisition

ERIC Educational Resources Information Center

Alishahi, Afra; Stevenson, Suzanne

2008-01-01

How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in the cognitive science of language. Computational modeling is an important methodology in research aimed at addressing this issue. We must determine appropriate learning…

Three-dimensional computer model for the atmospheric general circulation experiment

NASA Technical Reports Server (NTRS)

Roberts, G. O.

1984-01-01

An efficient, flexible, three-dimensional, hydrodynamic, computer code has been developed for a spherical cap geometry. The code will be used to simulate NASA's Atmospheric General Circulation Experiment (AGCE). The AGCE is a spherical, baroclinic experiment which will model the large-scale dynamics of our atmosphere; it has been proposed to NASA for future Spacelab flights. In the AGCE a radial dielectric body force will simulate gravity, with hot fluid tending to move outwards. In order that this force be dominant, the AGCE must be operated in a low gravity environment such as Spacelab. The full potential of the AGCE will only be realized by working in conjunction with an accurate computer model. Proposed experimental parameter settings will be checked first using model runs. Then actual experimental results will be compared with the model predictions. This interaction between experiment and theory will be very valuable in determining the nature of the AGCE flows and hence their relationship to analytical theories and actual atmospheric dynamics.

On the computation of molecular surface correlations for protein docking using fourier techniques.

PubMed

Sakk, Eric

2007-08-01

The computation of surface correlations using a variety of molecular models has been applied to the unbound protein docking problem. Because of the computational complexity involved in examining all possible molecular orientations, the fast Fourier transform (FFT) (a fast numerical implementation of the discrete Fourier transform (DFT)) is generally applied to minimize the number of calculations. This approach is rooted in the convolution theorem which allows one to inverse transform the product of two DFTs in order to perform the correlation calculation. However, such a DFT calculation results in a cyclic or "circular" correlation which, in general, does not lead to the same result as the linear correlation desired for the docking problem. In this work, we provide computational bounds for constructing molecular models used in the molecular surface correlation problem. The derived bounds are then shown to be consistent with various intuitive guidelines previously reported in the protein docking literature. Finally, these bounds are applied to different molecular models in order to investigate their effect on the correlation calculation.

COEFUV: A Computer Implementation of a Generalized Unmanned Vehicle Cost Model.

DTIC Science & Technology

1978-10-01

78 T N OMBER . C A FEUCNTER CLASSIF lED DAS-TRRNL mh~hhhh~hhE DAS-TR-78-4 DAS-TR-78-4 coI COEFUV: A COMPUTER IMPLEMENTATION OF A IM GENERALIZED ...34 and the time to generate them are important. Many DAS participants supported this effort. The authors wish to acknow- ledge Richard H. Anderson for...conflict and the on-going COMBAT ANGEL program at Davis-Monthan Air Force Base, there is not a generally accepted costing methodology for unmanned vehicles

Progress in modeling and simulation.

PubMed

Kindler, E

1998-01-01

For the modeling of systems, the computers are more and more used while the other "media" (including the human intellect) carrying the models are abandoned. For the modeling of knowledges, i.e. of more or less general concepts (possibly used to model systems composed of instances of such concepts), the object-oriented programming is nowadays widely used. For the modeling of processes existing and developing in the time, computer simulation is used, the results of which are often presented by means of animation (graphical pictures moving and changing in time). Unfortunately, the object-oriented programming tools are commonly not designed to be of a great use for simulation while the programming tools for simulation do not enable their users to apply the advantages of the object-oriented programming. Nevertheless, there are exclusions enabling to use general concepts represented at a computer, for constructing simulation models and for their easy modification. They are described in the present paper, together with true definitions of modeling, simulation and object-oriented programming (including cases that do not satisfy the definitions but are dangerous to introduce misunderstanding), an outline of their applications and of their further development. In relation to the fact that computing systems are being introduced to be control components into a large spectrum of (technological, social and biological) systems, the attention is oriented to models of systems containing modeling components.

Predicting Pilot Error in Nextgen: Pilot Performance Modeling and Validation Efforts

NASA Technical Reports Server (NTRS)

Wickens, Christopher; Sebok, Angelia; Gore, Brian; Hooey, Becky

2012-01-01

We review 25 articles presenting 5 general classes of computational models to predict pilot error. This more targeted review is placed within the context of the broader review of computational models of pilot cognition and performance, including such aspects as models of situation awareness or pilot-automation interaction. Particular emphasis is placed on the degree of validation of such models against empirical pilot data, and the relevance of the modeling and validation efforts to Next Gen technology and procedures.

Computer Simulation in Undergraduate Instruction: A Symposium.

ERIC Educational Resources Information Center

Street, Warren R.; And Others

These symposium papers discuss the instructional use of computers in psychology, with emphasis on computer-produced simulations. The first, by Rich Edwards, briefly outlines LABSIM, a general purpose system of FORTRAN programs which simulate data collection in more than a dozen experimental models in psychology and are designed to train students…

Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models.

PubMed

Yock, Adam D; Rao, Arvind; Dong, Lei; Beadle, Beth M; Garden, Adam S; Kudchadker, Rajat J; Court, Laurence E

2014-05-01

The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: -11.6%-23.8%) and 14.6% (range: -7.3%-27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: -6.8%-40.3%) and 13.1% (range: -1.5%-52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: -11.1%-20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography images and facilitate improved treatment management.

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.

Predictive Models and Computational Toxicology

EPA Science Inventory

Understanding the potential health risks posed by environmental chemicals is a significant challenge elevated by the large number of diverse chemicals with generally uncharacterized exposures, mechanisms, and toxicities. The ToxCast computational toxicology research program was l...

System maintenance manual for master modeling of aerodynamic surfaces by three-dimensional explicit representation

NASA Technical Reports Server (NTRS)

Gibson, A. F.

1983-01-01

A system of computer programs has been developed to model general three-dimensional surfaces. Surfaces are modeled as sets of parametric bicubic patches. There are also capabilities to transform coordinate to compute mesh/surface intersection normals, and to format input data for a transonic potential flow analysis. A graphical display of surface models and intersection normals is available. There are additional capabilities to regulate point spacing on input curves and to compute surface intersection curves. Internal details of the implementation of this system are explained, and maintenance procedures are specified.

Error suppression for Hamiltonian quantum computing in Markovian environments

NASA Astrophysics Data System (ADS)

Marvian, Milad; Lidar, Daniel A.

2017-03-01

Hamiltonian quantum computing, such as the adiabatic and holonomic models, can be protected against decoherence using an encoding into stabilizer subspace codes for error detection and the addition of energy penalty terms. This method has been widely studied since it was first introduced by Jordan, Farhi, and Shor (JFS) in the context of adiabatic quantum computing. Here, we extend the original result to general Markovian environments, not necessarily in Lindblad form. We show that the main conclusion of the original JFS study holds under these general circumstances: Assuming a physically reasonable bath model, it is possible to suppress the initial decay out of the encoded ground state with an energy penalty strength that grows only logarithmically in the system size, at a fixed temperature.

An adaptive maneuvering logic computer program for the simulation of one-on-one air-to-air combat. Volume 1: General description

NASA Technical Reports Server (NTRS)

Burgin, G. H.; Fogel, L. J.; Phelps, J. P.

1975-01-01

A technique for computer simulation of air combat is described. Volume 1 decribes the computer program and its development in general terms. Two versions of the program exist. Both incorporate a logic for selecting and executing air combat maneuvers with performance models of specific fighter aircraft. In the batch processing version the flight paths of two aircraft engaged in interactive aerial combat and controlled by the same logic are computed. The realtime version permits human pilots to fly air-to-air combat against the adaptive maneuvering logic (AML) in Langley Differential Maneuvering Simulator (DMS). Volume 2 consists of a detailed description of the computer programs.

A computational modeling of semantic knowledge in reading comprehension: Integrating the landscape model with latent semantic analysis.

PubMed

Yeari, Menahem; van den Broek, Paul

2016-09-01

It is a well-accepted view that the prior semantic (general) knowledge that readers possess plays a central role in reading comprehension. Nevertheless, computational models of reading comprehension have not integrated the simulation of semantic knowledge and online comprehension processes under a unified mathematical algorithm. The present article introduces a computational model that integrates the landscape model of comprehension processes with latent semantic analysis representation of semantic knowledge. In three sets of simulations of previous behavioral findings, the integrated model successfully simulated the activation and attenuation of predictive and bridging inferences during reading, as well as centrality estimations and recall of textual information after reading. Analyses of the computational results revealed new theoretical insights regarding the underlying mechanisms of the various comprehension phenomena.

Computing Quantitative Characteristics of Finite-State Real-Time Systems

DTIC Science & Technology

1994-05-04

Current methods for verifying real - time systems are essentially decision procedures that establish whether the system model satisfies a given...specification. We present a general method for computing quantitative information about finite-state real - time systems . We have developed algorithms that...our technique can be extended to a more general representation of real - time systems , namely, timed transition graphs. The algorithms presented in this

A frequentist approach to computer model calibration

DOE PAGES

Wong, Raymond K. W.; Storlie, Curtis Byron; Lee, Thomas C. M.

2016-05-05

The paper considers the computer model calibration problem and provides a general frequentist solution. Under the framework proposed, the data model is semiparametric with a non-parametric discrepancy function which accounts for any discrepancy between physical reality and the computer model. In an attempt to solve a fundamentally important (but often ignored) identifiability issue between the computer model parameters and the discrepancy function, the paper proposes a new and identifiable parameterization of the calibration problem. It also develops a two-step procedure for estimating all the relevant quantities under the new parameterization. This estimation procedure is shown to enjoy excellent rates ofmore » convergence and can be straightforwardly implemented with existing software. For uncertainty quantification, bootstrapping is adopted to construct confidence regions for the quantities of interest. As a result, the practical performance of the methodology is illustrated through simulation examples and an application to a computational fluid dynamics model.« less

Susceptible-infected-susceptible epidemics on networks with general infection and cure times.

PubMed

Cator, E; van de Bovenkamp, R; Van Mieghem, P

2013-06-01

The classical, continuous-time susceptible-infected-susceptible (SIS) Markov epidemic model on an arbitrary network is extended to incorporate infection and curing or recovery times each characterized by a general distribution (rather than an exponential distribution as in Markov processes). This extension, called the generalized SIS (GSIS) model, is believed to have a much larger applicability to real-world epidemics (such as information spread in online social networks, real diseases, malware spread in computer networks, etc.) that likely do not feature exponential times. While the exact governing equations for the GSIS model are difficult to deduce due to their non-Markovian nature, accurate mean-field equations are derived that resemble our previous N-intertwined mean-field approximation (NIMFA) and so allow us to transfer the whole analytic machinery of the NIMFA to the GSIS model. In particular, we establish the criterion to compute the epidemic threshold in the GSIS model. Moreover, we show that the average number of infection attempts during a recovery time is the more natural key parameter, instead of the effective infection rate in the classical, continuous-time SIS Markov model. The relative simplicity of our mean-field results enables us to treat more general types of SIS epidemics, while offering an easier key parameter to measure the average activity of those general viral agents.

Susceptible-infected-susceptible epidemics on networks with general infection and cure times

NASA Astrophysics Data System (ADS)

Cator, E.; van de Bovenkamp, R.; Van Mieghem, P.

2013-06-01

The classical, continuous-time susceptible-infected-susceptible (SIS) Markov epidemic model on an arbitrary network is extended to incorporate infection and curing or recovery times each characterized by a general distribution (rather than an exponential distribution as in Markov processes). This extension, called the generalized SIS (GSIS) model, is believed to have a much larger applicability to real-world epidemics (such as information spread in online social networks, real diseases, malware spread in computer networks, etc.) that likely do not feature exponential times. While the exact governing equations for the GSIS model are difficult to deduce due to their non-Markovian nature, accurate mean-field equations are derived that resemble our previous N-intertwined mean-field approximation (NIMFA) and so allow us to transfer the whole analytic machinery of the NIMFA to the GSIS model. In particular, we establish the criterion to compute the epidemic threshold in the GSIS model. Moreover, we show that the average number of infection attempts during a recovery time is the more natural key parameter, instead of the effective infection rate in the classical, continuous-time SIS Markov model. The relative simplicity of our mean-field results enables us to treat more general types of SIS epidemics, while offering an easier key parameter to measure the average activity of those general viral agents.

Progressive matrix cracking in off-axis plies of a general symmetric laminate

NASA Technical Reports Server (NTRS)

Thomas, David J.; Wetherhold, Robert C.

1993-01-01

A generalized shear-lag model is derived to determine the average through-the-thickness stress state present in a layer undergoing transverse matrix cracking, by extending the method of Lee and Daniels (1991) to a general symmetric multilayered system. The model is capable of considering cracking in layers of arbitrary orientation, states of general in-plane applied loading, and laminates with a general symmetric stacking sequence. The model is included in a computer program designed for probabilistic laminate analysis, and the results are compared to those determined with the ply drop-off technique.

A general computation model based on inverse analysis principle used for rheological analysis of W/O rapeseed and soybean oil emulsions

NASA Astrophysics Data System (ADS)

Vintila, Iuliana; Gavrus, Adinel

2017-10-01

The present research paper proposes the validation of a rigorous computation model used as a numerical tool to identify rheological behavior of complex emulsions W/O. Considering a three-dimensional description of a general viscoplastic flow it is detailed the thermo-mechanical equations used to identify fluid or soft material's rheological laws starting from global experimental measurements. Analyses are conducted for complex emulsions W/O having generally a Bingham behavior using the shear stress - strain rate dependency based on a power law and using an improved analytical model. Experimental results are investigated in case of rheological behavior for crude and refined rapeseed/soybean oils and four types of corresponding W/O emulsions using different physical-chemical composition. The rheological behavior model was correlated with the thermo-mechanical analysis of a plane-plane rheometer, oil content, chemical composition, particle size and emulsifier's concentration. The parameters of rheological laws describing the industrial oils and the W/O concentrated emulsions behavior were computed from estimated shear stresses using a non-linear regression technique and from experimental torques using the inverse analysis tool designed by A. Gavrus (1992-2000).

Risk prediction and aversion by anterior cingulate cortex.

PubMed

Brown, Joshua W; Braver, Todd S

2007-12-01

The recently proposed error-likelihood hypothesis suggests that anterior cingulate cortex (ACC) and surrounding areas will become active in proportion to the perceived likelihood of an error. The hypothesis was originally derived from a computational model prediction. The same computational model now makes a further prediction that ACC will be sensitive not only to predicted error likelihood, but also to the predicted magnitude of the consequences, should an error occur. The product of error likelihood and predicted error consequence magnitude collectively defines the general "expected risk" of a given behavior in a manner analogous but orthogonal to subjective expected utility theory. New fMRI results from an incentivechange signal task now replicate the error-likelihood effect, validate the further predictions of the computational model, and suggest why some segments of the population may fail to show an error-likelihood effect. In particular, error-likelihood effects and expected risk effects in general indicate greater sensitivity to earlier predictors of errors and are seen in risk-averse but not risk-tolerant individuals. Taken together, the results are consistent with an expected risk model of ACC and suggest that ACC may generally contribute to cognitive control by recruiting brain activity to avoid risk.

A SCILAB Program for Computing General-Relativistic Models of Rotating Neutron Stars by Implementing Hartle's Perturbation Method

NASA Astrophysics Data System (ADS)

Papasotiriou, P. J.; Geroyannis, V. S.

We implement Hartle's perturbation method to the computation of relativistic rigidly rotating neutron star models. The program has been written in SCILAB (© INRIA ENPC), a matrix-oriented high-level programming language. The numerical method is described in very detail and is applied to many models in slow or fast rotation. We show that, although the method is perturbative, it gives accurate results for all practical purposes and it should prove an efficient tool for computing rapidly rotating pulsars.

Real longitudinal data analysis for real people: building a good enough mixed model.

PubMed

Cheng, Jing; Edwards, Lloyd J; Maldonado-Molina, Mildred M; Komro, Kelli A; Muller, Keith E

2010-02-20

Mixed effects models have become very popular, especially for the analysis of longitudinal data. One challenge is how to build a good enough mixed effects model. In this paper, we suggest a systematic strategy for addressing this challenge and introduce easily implemented practical advice to build mixed effects models. A general discussion of the scientific strategies motivates the recommended five-step procedure for model fitting. The need to model both the mean structure (the fixed effects) and the covariance structure (the random effects and residual error) creates the fundamental flexibility and complexity. Some very practical recommendations help to conquer the complexity. Centering, scaling, and full-rank coding of all the predictor variables radically improve the chances of convergence, computing speed, and numerical accuracy. Applying computational and assumption diagnostics from univariate linear models to mixed model data greatly helps to detect and solve the related computational problems. Applying computational and assumption diagnostics from the univariate linear models to the mixed model data can radically improve the chances of convergence, computing speed, and numerical accuracy. The approach helps to fit more general covariance models, a crucial step in selecting a credible covariance model needed for defensible inference. A detailed demonstration of the recommended strategy is based on data from a published study of a randomized trial of a multicomponent intervention to prevent young adolescents' alcohol use. The discussion highlights a need for additional covariance and inference tools for mixed models. The discussion also highlights the need for improving how scientists and statisticians teach and review the process of finding a good enough mixed model. (c) 2009 John Wiley & Sons, Ltd.

Development of a General Form CO 2 and Brine Flux Input Model

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

Mansoor, K.; Sun, Y.; Carroll, S.

2014-08-01

The National Risk Assessment Partnership (NRAP) project is developing a science-based toolset for the quantitative analysis of the potential risks associated with changes in groundwater chemistry from CO 2 injection. In order to address uncertainty probabilistically, NRAP is developing efficient, reduced-order models (ROMs) as part of its approach. These ROMs are built from detailed, physics-based process models to provide confidence in the predictions over a range of conditions. The ROMs are designed to reproduce accurately the predictions from the computationally intensive process models at a fraction of the computational time, thereby allowing the utilization of Monte Carlo methods to probemore » variability in key parameters. This report presents the procedures used to develop a generalized model for CO 2 and brine leakage fluxes based on the output of a numerical wellbore simulation. The resulting generalized parameters and ranges reported here will be used for the development of third-generation groundwater ROMs.« less

A Cohomological Perspective on Algebraic Quantum Field Theory

NASA Astrophysics Data System (ADS)

Hawkins, Eli

2018-05-01

Algebraic quantum field theory is considered from the perspective of the Hochschild cohomology bicomplex. This is a framework for studying deformations and symmetries. Deformation is a possible approach to the fundamental challenge of constructing interacting QFT models. Symmetry is the primary tool for understanding the structure and properties of a QFT model. This perspective leads to a generalization of the algebraic quantum field theory framework, as well as a more general definition of symmetry. This means that some models may have symmetries that were not previously recognized or exploited. To first order, a deformation of a QFT model is described by a Hochschild cohomology class. A deformation could, for example, correspond to adding an interaction term to a Lagrangian. The cohomology class for such an interaction is computed here. However, the result is more general and does not require the undeformed model to be constructed from a Lagrangian. This computation leads to a more concrete version of the construction of perturbative algebraic quantum field theory.

Computation of turbulent reacting flow in a solid-propellant ducted rocket

NASA Astrophysics Data System (ADS)

Chao, Yei-Chin; Chou, Wen-Fuh; Liu, Sheng-Shyang

1995-05-01

A mathematical model for computation of turbulent reacting flows is developed under general curvilinear coordinate systems. An adaptive, streamline grid system is generated to deal with the complex flow structures in a multiple-inlet solid-propellant ducted rocket (SDR) combustor. General tensor representations of the k-epsilon and algebraic stress (ASM) turbulence models are derived in terms of contravariant velocity components, and modification caused by the effects of compressible turbulence is also included in the modeling. The clipped Gaussian probability density function is incorporated in the combustion model to account for fluctuations of properties. Validation of the above modeling is first examined by studying mixing and reacting characteristics in a confined coaxial-jet problem. This is followed by study of nonreacting and reacting SDR combustor flows. The results show that Gibson and Launder's ASM incorporated with Sarkar's modification for compressible turbulence effects based on the general curvilinear coordinate systems yields the most satisfactory prediction for this complicated SDR flowfield.

Computation of turbulent reacting flow in a solid-propellant ducted rocket

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

Chao, Y.; Chou, W.; Liu, S.

1995-05-01

A mathematical model for computation of turbulent reacting flows is developed under general curvilinear coordinate systems. An adaptive, streamline grid system is generated to deal with the complex flow structures in a multiple-inlet solid-propellant ducted rocket (SDR) combustor. General tensor representations of the k-epsilon and algebraic stress (ASM) turbulence models are derived in terms of contravariant velocity components, and modification caused by the effects of compressible turbulence is also included in the modeling. The clipped Gaussian probability density function is incorporated in the combustion model to account for fluctuations of properties. Validation of the above modeling is first examined bymore » studying mixing and reacting characteristics in a confined coaxial-jet problem. This is followed by study of nonreacting and reacting SDR combustor flows. The results show that Gibson and Launder`s ASM incorporated with Sarkar`s modification for compressible turbulence effects based on the general curvilinear coordinate systems yields the most satisfactory prediction for this complicated SDR flowfield. 36 refs.« less

Regression Is a Univariate General Linear Model Subsuming Other Parametric Methods as Special Cases.

ERIC Educational Resources Information Center

Vidal, Sherry

Although the concept of the general linear model (GLM) has existed since the 1960s, other univariate analyses such as the t-test and the analysis of variance models have remained popular. The GLM produces an equation that minimizes the mean differences of independent variables as they are related to a dependent variable. From a computer printout…

Computation of turbulent flows-state-of-the-art, 1970

NASA Technical Reports Server (NTRS)

Reynolds, W. C.

1972-01-01

The state-of-the-art of turbulent flow computation is surveyed. The formulations were generalized to increase the range of their applicability, and the excitement of current debate on equation models was brought into the review. Some new ideas on the modeling of the pressure-strain term in the Reynolds stress equations are also suggested.

Computing maximum-likelihood estimates for parameters of the National Descriptive Model of Mercury in Fish

USGS Publications Warehouse

Donato, David I.

2012-01-01

This report presents the mathematical expressions and the computational techniques required to compute maximum-likelihood estimates for the parameters of the National Descriptive Model of Mercury in Fish (NDMMF), a statistical model used to predict the concentration of methylmercury in fish tissue. The expressions and techniques reported here were prepared to support the development of custom software capable of computing NDMMF parameter estimates more quickly and using less computer memory than is currently possible with available general-purpose statistical software. Computation of maximum-likelihood estimates for the NDMMF by numerical solution of a system of simultaneous equations through repeated Newton-Raphson iterations is described. This report explains the derivation of the mathematical expressions required for computational parameter estimation in sufficient detail to facilitate future derivations for any revised versions of the NDMMF that may be developed.

Towards Anatomic Scale Agent-Based Modeling with a Massively Parallel Spatially Explicit General-Purpose Model of Enteric Tissue (SEGMEnT_HPC)

PubMed Central

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis. PMID:25806784

Conditional Monte Carlo randomization tests for regression models.

PubMed

Parhat, Parwen; Rosenberger, William F; Diao, Guoqing

2014-08-15

We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.

The Utility of Cognitive Plausibility in Language Acquisition Modeling: Evidence From Word Segmentation.

PubMed

Phillips, Lawrence; Pearl, Lisa

2015-11-01

The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's cognitive plausibility. We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition model can aim to be cognitively plausible in multiple ways. We discuss these cognitive plausibility checkpoints generally and then apply them to a case study in word segmentation, investigating a promising Bayesian segmentation strategy. We incorporate cognitive plausibility by using an age-appropriate unit of perceptual representation, evaluating the model output in terms of its utility, and incorporating cognitive constraints into the inference process. Our more cognitively plausible model shows a beneficial effect of cognitive constraints on segmentation performance. One interpretation of this effect is as a synergy between the naive theories of language structure that infants may have and the cognitive constraints that limit the fidelity of their inference processes, where less accurate inference approximations are better when the underlying assumptions about how words are generated are less accurate. More generally, these results highlight the utility of incorporating cognitive plausibility more fully into computational models of language acquisition. Copyright © 2015 Cognitive Science Society, Inc.

User's guide for a general purpose dam-break flood simulation model (K-634)

USGS Publications Warehouse

Land, Larry F.

1981-01-01

An existing computer program for simulating dam-break floods for forecast purposes has been modified with an emphasis on general purpose applications. The original model was formulated, developed and documented by the National Weather Service. This model is based on the complete flow equations and uses a nonlinear implicit finite-difference numerical method. The first phase of the simulation routes a flood wave through the reservoir and computes an outflow hydrograph which is the sum of the flow through the dam 's structures and the gradually developing breach. The second phase routes this outflow hydrograph through the stream which may be nonprismatic and have segments with subcritical or supercritical flow. The results are discharge and stage hydrographs at the dam as well as all of the computational nodes in the channel. From these hydrographs, peak discharge and stage profiles are tabulated. (USGS)

Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks.

PubMed

Spirov, Alexander; Holloway, David

2013-07-15

This paper surveys modeling approaches for studying the evolution of gene regulatory networks (GRNs). Modeling of the design or 'wiring' of GRNs has become increasingly common in developmental and medical biology, as a means of quantifying gene-gene interactions, the response to perturbations, and the overall dynamic motifs of networks. Drawing from developments in GRN 'design' modeling, a number of groups are now using simulations to study how GRNs evolve, both for comparative genomics and to uncover general principles of evolutionary processes. Such work can generally be termed evolution in silico. Complementary to these biologically-focused approaches, a now well-established field of computer science is Evolutionary Computations (ECs), in which highly efficient optimization techniques are inspired from evolutionary principles. In surveying biological simulation approaches, we discuss the considerations that must be taken with respect to: (a) the precision and completeness of the data (e.g. are the simulations for very close matches to anatomical data, or are they for more general exploration of evolutionary principles); (b) the level of detail to model (we proceed from 'coarse-grained' evolution of simple gene-gene interactions to 'fine-grained' evolution at the DNA sequence level); (c) to what degree is it important to include the genome's cellular context; and (d) the efficiency of computation. With respect to the latter, we argue that developments in computer science EC offer the means to perform more complete simulation searches, and will lead to more comprehensive biological predictions. Copyright © 2013 Elsevier Inc. All rights reserved.

Generalization Through the Recurrent Interaction of Episodic Memories

PubMed Central

Kumaran, Dharshan; McClelland, James L.

2012-01-01

In this article, we present a perspective on the role of the hippocampal system in generalization, instantiated in a computational model called REMERGE (recurrency and episodic memory results in generalization). We expose a fundamental, but neglected, tension between prevailing computational theories that emphasize the function of the hippocampus in pattern separation (Marr, 1971; McClelland, McNaughton, & O'Reilly, 1995), and empirical support for its role in generalization and flexible relational memory (Cohen & Eichenbaum, 1993; Eichenbaum, 1999). Our account provides a means by which to resolve this conflict, by demonstrating that the basic representational scheme envisioned by complementary learning systems theory (McClelland et al., 1995), which relies upon orthogonalized codes in the hippocampus, is compatible with efficient generalization—as long as there is recurrence rather than unidirectional flow within the hippocampal circuit or, more widely, between the hippocampus and neocortex. We propose that recurrent similarity computation, a process that facilitates the discovery of higher-order relationships between a set of related experiences, expands the scope of classical exemplar-based models of memory (e.g., Nosofsky, 1984) and allows the hippocampus to support generalization through interactions that unfold within a dynamically created memory space. PMID:22775499

A computer program for condensing heat exchanger performance in the presence of noncondensable gases

NASA Technical Reports Server (NTRS)

Yendler, Boris

1994-01-01

A computer model has been developed which evaluates the performance of a heat exchanger. This model is general enough to be used to evaluate many heat exchanger geometries and a number of different operating conditions. The film approach is used to describe condensation in the presence of noncondensables. The model is also easily expanded to include other effects like fog formation or suction.

A Computer Model for Determining Operational Centers of Gravity

DTIC Science & Technology

2002-05-31

current state of AI. For the beginner , the student text Artificial Intelligence: An Executive Overview (USMA 1994) is still useful for surveying the... flowchart that guides the determination. In preparing the model, the authors consulted numerous sources of opinion on the topic, to include doctrine...the logic of the general model in this manner resulted in a compact, unambiguous flowchart -style representation. The depiction of the general model

Recursive Newton-Euler formulation of manipulator dynamics

NASA Technical Reports Server (NTRS)

Nasser, M. G.

1989-01-01

A recursive Newton-Euler procedure is presented for the formulation and solution of manipulator dynamical equations. The procedure includes rotational and translational joints and a topological tree. This model was verified analytically using a planar two-link manipulator. Also, the model was tested numerically against the Walker-Orin model using the Shuttle Remote Manipulator System data. The hinge accelerations obtained from both models were identical. The computational requirements of the model vary linearly with the number of joints. The computational efficiency of this method exceeds that of Walker-Orin methods. This procedure may be viewed as a considerable generalization of Armstrong's method. A six-by-six formulation is adopted which enhances both the computational efficiency and simplicity of the model.

Systems Analysis of Amphibious Landing Craft: Comparisons of Revised Designs of Advanced Landing Craft.

DTIC Science & Technology

AALC(AMPHIBIOUS ASSAULT LANDING CRAFT), AMPHIBIOUS ASSAULT LANDING CRAFT, DEBARKING, GAMUT MODEL, GENERAL PURPOSE SIMULATION SYSTEM, GPSS(GENERAL PURPOSE SIMULATION SYSTEM), IBM 360 COMPUTERS, LANDING CRAFT MIXES.

Dynamic regulation of erythropoiesis: A computer model of general applicability

NASA Technical Reports Server (NTRS)

Leonard, J. I.

1979-01-01

A mathematical model for the control of erythropoiesis was developed based on the balance between oxygen supply and demand at a renal oxygen detector which controls erythropoietin release and red cell production. Feedback regulation of tissue oxygen tension is accomplished by adjustments of hemoglobin levels resulting from the output of a renal-bone marrow controller. Special consideration was given to the determinants of tissue oxygenation including evaluation of the influence of blood flow, capillary diffusivity, oxygen uptake and oxygen-hemoglobin affinity. A theoretical analysis of the overall control system is presented. Computer simulations of altitude hypoxia, red cell infusion hyperoxia, and homolytic anemia demonstrate validity of the model for general human application in health and disease.

A primer for biomedical scientists on how to execute model II linear regression analysis.

PubMed

Ludbrook, John

2012-04-01

1. There are two very different ways of executing linear regression analysis. One is Model I, when the x-values are fixed by the experimenter. The other is Model II, in which the x-values are free to vary and are subject to error. 2. I have received numerous complaints from biomedical scientists that they have great difficulty in executing Model II linear regression analysis. This may explain the results of a Google Scholar search, which showed that the authors of articles in journals of physiology, pharmacology and biochemistry rarely use Model II regression analysis. 3. I repeat my previous arguments in favour of using least products linear regression analysis for Model II regressions. I review three methods for executing ordinary least products (OLP) and weighted least products (WLP) regression analysis: (i) scientific calculator and/or computer spreadsheet; (ii) specific purpose computer programs; and (iii) general purpose computer programs. 4. Using a scientific calculator and/or computer spreadsheet, it is easy to obtain correct values for OLP slope and intercept, but the corresponding 95% confidence intervals (CI) are inaccurate. 5. Using specific purpose computer programs, the freeware computer program smatr gives the correct OLP regression coefficients and obtains 95% CI by bootstrapping. In addition, smatr can be used to compare the slopes of OLP lines. 6. When using general purpose computer programs, I recommend the commercial programs systat and Statistica for those who regularly undertake linear regression analysis and I give step-by-step instructions in the Supplementary Information as to how to use loss functions. © 2011 The Author. Clinical and Experimental Pharmacology and Physiology. © 2011 Blackwell Publishing Asia Pty Ltd.

General Training System; GENTRAS. Final Report.

ERIC Educational Resources Information Center

International Business Machines Corp., Gaithersburg, MD. Federal Systems Div.

GENTRAS (General Training System) is a computer-based training model for the Marine Corps which makes use of a systems approach. The model defines the skill levels applicable for career growth and classifies and defines the training needed for this growth. It also provides a training cost subsystem which will provide a more efficient means of…

Computational reacting gas dynamics

NASA Technical Reports Server (NTRS)

Lam, S. H.

1993-01-01

In the study of high speed flows at high altitudes, such as that encountered by re-entry spacecrafts, the interaction of chemical reactions and other non-equilibrium processes in the flow field with the gas dynamics is crucial. Generally speaking, problems of this level of complexity must resort to numerical methods for solutions, using sophisticated computational fluid dynamics (CFD) codes. The difficulties introduced by reacting gas dynamics can be classified into three distinct headings: (1) the usually inadequate knowledge of the reaction rate coefficients in the non-equilibrium reaction system; (2) the vastly larger number of unknowns involved in the computation and the expected stiffness of the equations; and (3) the interpretation of the detailed reacting CFD numerical results. The research performed accepts the premise that reacting flows of practical interest in the future will in general be too complex or 'untractable' for traditional analytical developments. The power of modern computers must be exploited. However, instead of focusing solely on the construction of numerical solutions of full-model equations, attention is also directed to the 'derivation' of the simplified model from the given full-model. In other words, the present research aims to utilize computations to do tasks which have traditionally been done by skilled theoreticians: to reduce an originally complex full-model system into an approximate but otherwise equivalent simplified model system. The tacit assumption is that once the appropriate simplified model is derived, the interpretation of the detailed numerical reacting CFD numerical results will become much easier. The approach of the research is called computational singular perturbation (CSP).

Automated procedure for developing hybrid computer simulations of turbofan engines. Part 1: General description

NASA Technical Reports Server (NTRS)

Szuch, J. R.; Krosel, S. M.; Bruton, W. M.

1982-01-01

A systematic, computer-aided, self-documenting methodology for developing hybrid computer simulations of turbofan engines is presented. The methodology that is pesented makes use of a host program that can run on a large digital computer and a machine-dependent target (hybrid) program. The host program performs all the calculations and data manipulations that are needed to transform user-supplied engine design information to a form suitable for the hybrid computer. The host program also trims the self-contained engine model to match specified design-point information. Part I contains a general discussion of the methodology, describes a test case, and presents comparisons between hybrid simulation and specified engine performance data. Part II, a companion document, contains documentation, in the form of computer printouts, for the test case.

Hurricane Sandy Economic Impacts Assessment: A Computable General Equilibrium Approach and Validation

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

Boero, Riccardo; Edwards, Brian Keith

Economists use computable general equilibrium (CGE) models to assess how economies react and self-organize after changes in policies, technology, and other exogenous shocks. CGE models are equation-based, empirically calibrated, and inspired by Neoclassical economic theory. The focus of this work was to validate the National Infrastructure Simulation and Analysis Center (NISAC) CGE model and apply it to the problem of assessing the economic impacts of severe events. We used the 2012 Hurricane Sandy event as our validation case. In particular, this work first introduces the model and then describes the validation approach and the empirical data available for studying themore » event of focus. Shocks to the model are then formalized and applied. Finally, model results and limitations are presented and discussed, pointing out both the model degree of accuracy and the assessed total damage caused by Hurricane Sandy.« less

Pharmaceutical industry and trade liberalization using computable general equilibrium model.

PubMed

Barouni, M; Ghaderi, H; Banouei, Aa

2012-01-01

Computable general equilibrium models are known as a powerful instrument in economic analyses and widely have been used in order to evaluate trade liberalization effects. The purpose of this study was to provide the impacts of trade openness on pharmaceutical industry using CGE model. Using a computable general equilibrium model in this study, the effects of decrease in tariffs as a symbol of trade liberalization on key variables of Iranian pharmaceutical products were studied. Simulation was performed via two scenarios in this study. The first scenario was the effect of decrease in tariffs of pharmaceutical products as 10, 30, 50, and 100 on key drug variables, and the second was the effect of decrease in other sectors except pharmaceutical products on vital and economic variables of pharmaceutical products. The required data were obtained and the model parameters were calibrated according to the social accounting matrix of Iran in 2006. The results associated with simulation demonstrated that the first scenario has increased import, export, drug supply to markets and household consumption, while import, export, supply of product to market, and household consumption of pharmaceutical products would averagely decrease in the second scenario. Ultimately, society welfare would improve in all scenarios. We presents and synthesizes the CGE model which could be used to analyze trade liberalization policy issue in developing countries (like Iran), and thus provides information that policymakers can use to improve the pharmacy economics.

GPU-computing in econophysics and statistical physics

NASA Astrophysics Data System (ADS)

Preis, T.

2011-03-01

A recent trend in computer science and related fields is general purpose computing on graphics processing units (GPUs), which can yield impressive performance. With multiple cores connected by high memory bandwidth, today's GPUs offer resources for non-graphics parallel processing. This article provides a brief introduction into the field of GPU computing and includes examples. In particular computationally expensive analyses employed in financial market context are coded on a graphics card architecture which leads to a significant reduction of computing time. In order to demonstrate the wide range of possible applications, a standard model in statistical physics - the Ising model - is ported to a graphics card architecture as well, resulting in large speedup values.

Foundations for computer simulation of a low pressure oil flooded single screw air compressor

NASA Astrophysics Data System (ADS)

Bein, T. W.

1981-12-01

The necessary logic to construct a computer model to predict the performance of an oil flooded, single screw air compressor is developed. The geometric variables and relationships used to describe the general single screw mechanism are developed. The governing equations to describe the processes are developed from their primary relationships. The assumptions used in the development are also defined and justified. The computer model predicts the internal pressure, temperature, and flowrates through the leakage paths throughout the compression cycle of the single screw compressor. The model uses empirical external values as the basis for the internal predictions. The computer values are compared to the empirical values, and conclusions are drawn based on the results. Recommendations are made for future efforts to improve the computer model and to verify some of the conclusions that are drawn.

Capability of GPGPU for Faster Thermal Analysis Used in Data Assimilation

NASA Astrophysics Data System (ADS)

Takaki, Ryoji; Akita, Takeshi; Shima, Eiji

A thermal mathematical model plays an important role in operations on orbit as well as spacecraft thermal designs. The thermal mathematical model has some uncertain thermal characteristic parameters, such as thermal contact resistances between components, effective emittances of multilayer insulation (MLI) blankets, discouraging make up efficiency and accuracy of the model. A particle filter which is one of successive data assimilation methods has been applied to construct spacecraft thermal mathematical models. This method conducts a lot of ensemble computations, which require large computational power. Recently, General Purpose computing in Graphics Processing Unit (GPGPU) has been attracted attention in high performance computing. Therefore GPGPU is applied to increase the computational speed of thermal analysis used in the particle filter. This paper shows the speed-up results by using GPGPU as well as the application method of GPGPU.

Computers for real time flight simulation: A market survey

NASA Technical Reports Server (NTRS)

Bekey, G. A.; Karplus, W. J.

1977-01-01

An extensive computer market survey was made to determine those available systems suitable for current and future flight simulation studies at Ames Research Center. The primary requirement is for the computation of relatively high frequency content (5 Hz) math models representing powered lift flight vehicles. The Rotor Systems Research Aircraft (RSRA) was used as a benchmark vehicle for computation comparison studies. The general nature of helicopter simulations and a description of the benchmark model are presented, and some of the sources of simulation difficulties are examined. A description of various applicable computer architectures is presented, along with detailed discussions of leading candidate systems and comparisons between them.

Development of hybrid computer plasma models for different pressure regimes

NASA Astrophysics Data System (ADS)

Hromadka, Jakub; Ibehej, Tomas; Hrach, Rudolf

2016-09-01

With increased performance of contemporary computers during last decades numerical simulations became a very powerful tool applicable also in plasma physics research. Plasma is generally an ensemble of mutually interacting particles that is out of the thermodynamic equilibrium and for this reason fluid computer plasma models give results with only limited accuracy. On the other hand, much more precise particle models are often limited only on 2D problems because of their huge demands on the computer resources. Our contribution is devoted to hybrid modelling techniques that combine advantages of both modelling techniques mentioned above, particularly to their so-called iterative version. The study is focused on mutual relations between fluid and particle models that are demonstrated on the calculations of sheath structures of low temperature argon plasma near a cylindrical Langmuir probe for medium and higher pressures. Results of a simple iterative hybrid plasma computer model are also given. The authors acknowledge the support of the Grant Agency of Charles University in Prague (project 220215).

Crew appliance computer program manual, volume 1

NASA Technical Reports Server (NTRS)

Russell, D. J.

1975-01-01

Trade studies of numerous appliance concepts for advanced spacecraft galley, personal hygiene, housekeeping, and other areas were made to determine which best satisfy the space shuttle orbiter and modular space station mission requirements. Analytical models of selected appliance concepts not currently included in the G-189A Generalized Environmental/Thermal Control and Life Support Systems (ETCLSS) Computer Program subroutine library were developed. The new appliance subroutines are given along with complete analytical model descriptions, solution methods, user's input instructions, and validation run results. The appliance components modeled were integrated with G-189A ETCLSS models for shuttle orbiter and modular space station, and results from computer runs of these systems are presented.

Computer prediction of insecticide efficacy for western spruce budworm and Douglas-fir tussock moth

Treesearch

Jacqueline L. Robertson; Molly W. Stock

1986-01-01

A generalized interactive computer model that simulates and predicts insecticide efficacy, over seasonal development of western spruce budworm and Douglas-fir tussock moth, is described. This model can be used for any insecticide for which the user has laboratory-based concentration-response data. The program has four options, is written in BASIC, and can be operated...

Free surface profiles in river flows: Can standard energy-based gradually-varied flow computations be pursued?

NASA Astrophysics Data System (ADS)

Cantero, Francisco; Castro-Orgaz, Oscar; Garcia-Marín, Amanda; Ayuso, José Luis; Dey, Subhasish

2015-10-01

Is the energy equation for gradually-varied flow the best approximation for the free surface profile computations in river flows? Determination of flood inundation in rivers and natural waterways is based on the hydraulic computation of flow profiles. This is usually done using energy-based gradually-varied flow models, like HEC-RAS, that adopts a vertical division method for discharge prediction in compound channel sections. However, this discharge prediction method is not so accurate in the context of advancements over the last three decades. This paper firstly presents a study of the impact of discharge prediction on the gradually-varied flow computations by comparing thirteen different methods for compound channels, where both energy and momentum equations are applied. The discharge, velocity distribution coefficients, specific energy, momentum and flow profiles are determined. After the study of gradually-varied flow predictions, a new theory is developed to produce higher-order energy and momentum equations for rapidly-varied flow in compound channels. These generalized equations enable to describe the flow profiles with more generality than the gradually-varied flow computations. As an outcome, results of gradually-varied flow provide realistic conclusions for computations of flow in compound channels, showing that momentum-based models are in general more accurate; whereas the new theory developed for rapidly-varied flow opens a new research direction, so far not investigated in flows through compound channels.

Category-theoretic models of algebraic computer systems

NASA Astrophysics Data System (ADS)

Kovalyov, S. P.

2016-01-01

A computer system is said to be algebraic if it contains nodes that implement unconventional computation paradigms based on universal algebra. A category-based approach to modeling such systems that provides a theoretical basis for mapping tasks to these systems' architecture is proposed. The construction of algebraic models of general-purpose computations involving conditional statements and overflow control is formally described by a reflector in an appropriate category of algebras. It is proved that this reflector takes the modulo ring whose operations are implemented in the conventional arithmetic processors to the Łukasiewicz logic matrix. Enrichments of the set of ring operations that form bases in the Łukasiewicz logic matrix are found.

An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities.

PubMed

Matsubara, Takashi; Torikai, Hiroyuki

2016-04-01

Modeling and implementation approaches for the reproduction of input-output relationships in biological nervous tissues contribute to the development of engineering and clinical applications. However, because of high nonlinearity, the traditional modeling and implementation approaches encounter difficulties in terms of generalization ability (i.e., performance when reproducing an unknown data set) and computational resources (i.e., computation time and circuit elements). To overcome these difficulties, asynchronous cellular automaton-based neuron (ACAN) models, which are described as special kinds of cellular automata that can be implemented as small asynchronous sequential logic circuits have been proposed. This paper presents a novel type of such ACAN and a theoretical analysis of its excitability. This paper also presents a novel network of such neurons, which can mimic input-output relationships of biological and nonlinear ordinary differential equation model neural networks. Numerical analyses confirm that the presented network has a higher generalization ability than other major modeling and implementation approaches. In addition, Field-Programmable Gate Array-implementations confirm that the presented network requires lower computational resources.

Computer-aided-engineering system for modeling and analysis of ECLSS integration testing

NASA Technical Reports Server (NTRS)

Sepahban, Sonbol

1987-01-01

The accurate modeling and analysis of two-phase fluid networks found in environmental control and life support systems is presently undertaken by computer-aided engineering (CAE) techniques whose generalized fluid dynamics package can solve arbitrary flow networks. The CAE system for integrated test bed modeling and analysis will also furnish interfaces and subsystem/test-article mathematical models. Three-dimensional diagrams of the test bed are generated by the system after performing the requisite simulation and analysis.

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.

A comparison of turbulence models in computing multi-element airfoil flows

NASA Technical Reports Server (NTRS)

Rogers, Stuart E.; Menter, Florian; Durbin, Paul A.; Mansour, Nagi N.

1994-01-01

Four different turbulence models are used to compute the flow over a three-element airfoil configuration. These models are the one-equation Baldwin-Barth model, the one-equation Spalart-Allmaras model, a two-equation k-omega model, and a new one-equation Durbin-Mansour model. The flow is computed using the INS2D two-dimensional incompressible Navier-Stokes solver. An overset Chimera grid approach is utilized. Grid resolution tests are presented, and manual solution-adaptation of the grid was performed. The performance of each of the models is evaluated for test cases involving different angles-of-attack, Reynolds numbers, and flap riggings. The resulting surface pressure coefficients, skin friction, velocity profiles, and lift, drag, and moment coefficients are compared with experimental data. The models produce very similar results in most cases. Excellent agreement between computational and experimental surface pressures was observed, but only moderately good agreement was seen in the velocity profile data. In general, the difference between the predictions of the different models was less than the difference between the computational and experimental data.

Probabilistic graphs as a conceptual and computational tool in hydrology and water management

NASA Astrophysics Data System (ADS)

Schoups, Gerrit

2014-05-01

Originally developed in the fields of machine learning and artificial intelligence, probabilistic graphs constitute a general framework for modeling complex systems in the presence of uncertainty. The framework consists of three components: 1. Representation of the model as a graph (or network), with nodes depicting random variables in the model (e.g. parameters, states, etc), which are joined together by factors. Factors are local probabilistic or deterministic relations between subsets of variables, which, when multiplied together, yield the joint distribution over all variables. 2. Consistent use of probability theory for quantifying uncertainty, relying on basic rules of probability for assimilating data into the model and expressing unknown variables as a function of observations (via the posterior distribution). 3. Efficient, distributed approximation of the posterior distribution using general-purpose algorithms that exploit model structure encoded in the graph. These attributes make probabilistic graphs potentially useful as a conceptual and computational tool in hydrology and water management (and beyond). Conceptually, they can provide a common framework for existing and new probabilistic modeling approaches (e.g. by drawing inspiration from other fields of application), while computationally they can make probabilistic inference feasible in larger hydrological models. The presentation explores, via examples, some of these benefits.

Distributed Computing for Signal Processing: Modeling of Asynchronous Parallel Computation. Appendix G. On the Design and Modeling of Special Purpose Parallel Processing Systems.

DTIC Science & Technology

1985-05-01

unit in the data base, with knowing one generic assembly language. °-’--a 139 The 5-tuple describing single operation execution time of the operations...TSi-- generate , random eventi ( ,.0-15 tieit tmls - ((floa egus ()16 274 r Ispt imet imel I at :EVE’JS- II ktime=0.0; /0 present time 0/ rrs ptime=0.0...computing machinery capable of performing these tasks within a given time constraint. Because the majority of the available computing machinery is general

Airport Facility Queuing Model Validation

DOT National Transportation Integrated Search

1977-05-01

Criteria are presented for selection of analytic models to represent waiting times due to queuing processes. An existing computer model by M.F. Neuts which assumes general nonparametric distributions of arrivals per unit time and service times for a ...

A simulation model for forecasting downhill ski participation

Treesearch

Daniel J. Stynes; Daniel M. Spotts

1980-01-01

The purpose of this paper is to describe progress in the development of a general computer simulation model to forecast future levels of outdoor recreation participation. The model is applied and tested for downhill skiing in Michigan.

A Primer on High-Throughput Computing for Genomic Selection

PubMed Central

Wu, Xiao-Lin; Beissinger, Timothy M.; Bauck, Stewart; Woodward, Brent; Rosa, Guilherme J. M.; Weigel, Kent A.; Gatti, Natalia de Leon; Gianola, Daniel

2011-01-01

High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long, and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl, and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general-purpose computation on a graphics processing unit provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin–Madison, which can be leveraged for genomic selection, in terms of central processing unit capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general-purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of marker panels to realized genetic gain). Eventually, HTC may change our view of data analysis as well as decision-making in the post-genomic era of selection programs in animals and plants, or in the study of complex diseases in humans. PMID:22303303

Efficient calculation of general Voigt profiles

NASA Astrophysics Data System (ADS)

Cope, D.; Khoury, R.; Lovett, R. J.

1988-02-01

An accurate and efficient program is presented for the computation of OIL profiles, generalizations of the Voigt profile resulting from the one-interacting-level model of Ward et al. (1974). These profiles have speed dependent shift and width functions and have asymmetric shapes. The program contains an adjustable error control parameter and includes the Voigt profile as a special case, although the general nature of this program renders it slower than a specialized Voigt profile method. Results on accuracy and computation time are presented for a broad set of test parameters, and a comparison is made with previous work on the asymptotic behavior of general Voigt profiles.

The feasibility of using UML to compare the impact of different brands of computer system on the clinical consultation.

PubMed

Kumarapeli, Pushpa; de Lusignan, Simon; Koczan, Phil; Jones, Beryl; Sheeler, Ian

2007-01-01

UK general practice is universally computerised, with computers used in the consulting room at the point of care. Practices use a range of different brands of computer system, which have developed organically to meet the needs of general practitioners and health service managers. Unified Modelling Language (UML) is a standard modelling and specification notation widely used in software engineering. To examine the feasibility of UML notation to compare the impact of different brands of general practice computer system on the clinical consultation. Multi-channel video recordings of simulated consultation sessions were recorded on three different clinical computer systems in common use (EMIS, iSOFT Synergy and IPS Vision). User action recorder software recorded time logs of keyboard and mouse use, and pattern recognition software captured non-verbal communication. The outputs of these were used to create UML class and sequence diagrams for each consultation. We compared 'definition of the presenting problem' and 'prescribing', as these tasks were present in all the consultations analysed. Class diagrams identified the entities involved in the clinical consultation. Sequence diagrams identified common elements of the consultation (such as prescribing) and enabled comparisons to be made between the different brands of computer system. The clinician and computer system interaction varied greatly between the different brands. UML sequence diagrams are useful in identifying common tasks in the clinical consultation, and for contrasting the impact of the different brands of computer system on the clinical consultation. Further research is needed to see if patterns demonstrated in this pilot study are consistently displayed.

Applications of General Systems Theory to the Development of an Adjustable Tutorial Software Machine.

ERIC Educational Resources Information Center

Vos, Hans J.

1994-01-01

Describes the construction of a model of computer-assisted instruction using a qualitative block diagram based on general systems theory (GST) as a framework. Subject matter representation is discussed, and appendices include system variables and system equations of the GST model, as well as an example of developing flexible courseware. (Contains…

Markov Chain Monte Carlo Estimation of Item Parameters for the Generalized Graded Unfolding Model

ERIC Educational Resources Information Center

de la Torre, Jimmy; Stark, Stephen; Chernyshenko, Oleksandr S.

2006-01-01

The authors present a Markov Chain Monte Carlo (MCMC) parameter estimation procedure for the generalized graded unfolding model (GGUM) and compare it to the marginal maximum likelihood (MML) approach implemented in the GGUM2000 computer program, using simulated and real personality data. In the simulation study, test length, number of response…

Discrete is it enough? The revival of Piola-Hencky keynotes to analyze three-dimensional Elastica

NASA Astrophysics Data System (ADS)

Turco, Emilio

2018-04-01

Complex problems such as those concerning the mechanics of materials can be confronted only by considering numerical simulations. Analytical methods are useful to build guidelines or reference solutions but, for general cases of technical interest, they have to be solved numerically, especially in the case of large displacements and deformations. Probably continuous models arose for producing inspiring examples and stemmed from homogenization techniques. These techniques allowed for the solution of some paradigmatic examples but, in general, always require a discretization method for solving problems dictated by the applications. Therefore, and also by taking into account that computing powers are nowadays more largely available and cheap, the question arises: why not using directly a discrete model for 3D beams? In other words, it could be interesting to formulate a discrete model without using an intermediate continuum one, as this last, at the end, has to be discretized in any case. These simple considerations immediately evoke some very basic models developed many years ago when the computing powers were practically inexistent but the problem of finding simple solutions to beam deformation problem was already an emerging one. Actually, in recent years, the keynotes of Hencky and Piola attracted a renewed attention [see, one for all, the work (Turco et al. in Zeitschrift für Angewandte Mathematik und Physik 67(4):1-28, 2016)]: generalizing their results, in the present paper, a novel directly discrete three-dimensional beam model is presented and discussed, in the framework of geometrically nonlinear analysis. Using a stepwise algorithm based essentially on Newton's method to compute the extrapolations and on the Riks' arc-length method to perform the corrections, we could obtain some numerical simulations showing the computational effectiveness of presented model: Indeed, it presents a convenient balance between accuracy and computational cost.

Supercomputer optimizations for stochastic optimal control applications

NASA Technical Reports Server (NTRS)

Chung, Siu-Leung; Hanson, Floyd B.; Xu, Huihuang

1991-01-01

Supercomputer optimizations for a computational method of solving stochastic, multibody, dynamic programming problems are presented. The computational method is valid for a general class of optimal control problems that are nonlinear, multibody dynamical systems, perturbed by general Markov noise in continuous time, i.e., nonsmooth Gaussian as well as jump Poisson random white noise. Optimization techniques for vector multiprocessors or vectorizing supercomputers include advanced data structures, loop restructuring, loop collapsing, blocking, and compiler directives. These advanced computing techniques and superconducting hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations, by permitting the solution of large multibody problems. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random aerospace fluctuations.

Generalized fish life-cycle poplulation model and computer program

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

DeAngelis, D. L.; Van Winkle, W.; Christensen, S. W.

1978-03-01

A generalized fish life-cycle population model and computer program have been prepared to evaluate the long-term effect of changes in mortality in age class 0. The general question concerns what happens to a fishery when density-independent sources of mortality are introduced that act on age class 0, particularly entrainment and impingement at power plants. This paper discusses the model formulation and computer program, including sample results. The population model consists of a system of difference equations involving age-dependent fecundity and survival. The fecundity for each age class is assumed to be a function of both the fraction of females sexuallymore » mature and the weight of females as they enter each age class. Natural mortality for age classes 1 and older is assumed to be independent of population size. Fishing mortality is assumed to vary with the number and weight of fish available to the fishery. Age class 0 is divided into six life stages. The probability of survival for age class 0 is estimated considering both density-independent mortality (natural and power plant) and density-dependent mortality for each life stage. Two types of density-dependent mortality are included. These are cannibalism of each life stage by older age classes and intra-life-stage competition.« less

The computation of Laplacian smoothing splines with examples

NASA Technical Reports Server (NTRS)

Wendelberger, J. G.

1982-01-01

Laplacian smoothing splines (LSS) are presented as generalizations of graduation, cubic and thin plate splines. The method of generalized cross validation (GCV) to choose the smoothing parameter is described. The GCV is used in the algorithm for the computation of LSS's. An outline of a computer program which implements this algorithm is presented along with a description of the use of the program. Examples in one, two and three dimensions demonstrate how to obtain estimates of function values with confidence intervals and estimates of first and second derivatives. Probability plots are used as a diagnostic tool to check for model inadequacy.

Particle Transport through Scattering Regions with Clear Layers and Inclusions

NASA Astrophysics Data System (ADS)

Bal, Guillaume

2002-08-01

This paper introduces generalized diffusion models for the transport of particles in scattering media with nonscattering inclusions. Classical diffusion is known as a good approximation of transport only in scattering media. Based on asymptotic expansions and the coupling of transport and diffusion models, generalized diffusion equations with nonlocal interface conditions are proposed which offer a computationally cheap, yet accurate, alternative to solving the full phase-space transport equations. The paper shows which computational model should be used depending on the size and shape of the nonscattering inclusions in the simplified setting of two space dimensions. An important application is the treatment of clear layers in near-infrared (NIR) spectroscopy, an imaging technique based on the propagation of NIR photons in human tissues.

Purple Computational Environment With Mappings to ACE Requirements for the General Availability User Environment Capabilities

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

Barney, B; Shuler, J

2006-08-21

Purple is an Advanced Simulation and Computing (ASC) funded massively parallel supercomputer located at Lawrence Livermore National Laboratory (LLNL). The Purple Computational Environment documents the capabilities and the environment provided for the FY06 LLNL Level 1 General Availability Milestone. This document describes specific capabilities, tools, and procedures to support both local and remote users. The model is focused on the needs of the ASC user working in the secure computing environments at Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Sandia National Laboratories, but also documents needs of the LLNL and Alliance users working in the unclassified environment. Additionally,more » the Purple Computational Environment maps the provided capabilities to the Trilab ASC Computing Environment (ACE) Version 8.0 requirements. The ACE requirements reflect the high performance computing requirements for the General Availability user environment capabilities of the ASC community. Appendix A lists these requirements and includes a description of ACE requirements met and those requirements that are not met for each section of this document. The Purple Computing Environment, along with the ACE mappings, has been issued and reviewed throughout the Tri-lab community.« less

A local-circulation model for Darrieus vertical-axis wind turbines

NASA Astrophysics Data System (ADS)

Masse, B.

1986-04-01

A new computational model for the aerodynamics of the vertical-axis wind turbine is presented. Based on the local-circulation method generalized for curved blades, combined with a wake model for the vertical-axis wind turbine, it differs markedly from current models based on variations in the streamtube momentum and vortex models using the lifting-line theory. A computer code has been developed to calculate the loads and performance of the Darrieus vertical-axis wind turbine. The results show good agreement with experimental data and compare well with other methods.

Analysis of whisker-toughened CMC structural components using an interactive reliability model

NASA Technical Reports Server (NTRS)

Duffy, Stephen F.; Palko, Joseph L.

1992-01-01

Realizing wider utilization of ceramic matrix composites (CMC) requires the development of advanced structural analysis technologies. This article focuses on the use of interactive reliability models to predict component probability of failure. The deterministic William-Warnke failure criterion serves as theoretical basis for the reliability model presented here. The model has been implemented into a test-bed software program. This computer program has been coupled to a general-purpose finite element program. A simple structural problem is presented to illustrate the reliability model and the computer algorithm.

Variable Complexity Structural Optimization of Shells

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.; Venkataraman, Satchi

1999-01-01

Structural designers today face both opportunities and challenges in a vast array of available analysis and optimization programs. Some programs such as NASTRAN, are very general, permitting the designer to model any structure, to any degree of accuracy, but often at a higher computational cost. Additionally, such general procedures often do not allow easy implementation of all constraints of interest to the designer. Other programs, based on algebraic expressions used by designers one generation ago, have limited applicability for general structures with modem materials. However, when applicable, they provide easy understanding of design decisions trade-off. Finally, designers can also use specialized programs suitable for designing efficiently a subset of structural problems. For example, PASCO and PANDA2 are panel design codes, which calculate response and estimate failure much more efficiently than general-purpose codes, but are narrowly applicable in terms of geometry and loading. Therefore, the problem of optimizing structures based on simultaneous use of several models and computer programs is a subject of considerable interest. The problem of using several levels of models in optimization has been dubbed variable complexity modeling. Work under NASA grant NAG1-2110 has been concerned with the development of variable complexity modeling strategies with special emphasis on response surface techniques. In addition, several modeling issues for the design of shells of revolution were studied.

Variable Complexity Structural Optimization of Shells

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.; Venkataraman, Satchi

1998-01-01

Structural designers today face both opportunities and challenges in a vast array of available analysis and optimization programs. Some programs such as NASTRAN, are very general, permitting the designer to model any structure, to any degree of accuracy, but often at a higher computational cost. Additionally, such general procedures often do not allow easy implementation of all constraints of interest to the designer. Other programs, based on algebraic expressions used by designers one generation ago, have limited applicability for general structures with modem materials. However, when applicable, they provide easy understanding of design decisions trade-off. Finally, designers can also use specialized programs suitable for designing efficiently a subset of structural problems. For example, PASCO and PANDA2 are panel design codes, which calculate response and estimate failure much more efficiently than general-purpose codes, but are narrowly applicable in terms of geometry and loading. Therefore, the problem of optimizing structures based on simultaneous use of several models and computer programs is a subject of considerable interest. The problem of using several levels of models in optimization has been dubbed variable complexity modeling. Work under NASA grant NAG1-1808 has been concerned with the development of variable complexity modeling strategies with special emphasis on response surface techniques. In addition several modeling issues for the design of shells of revolution were studied.

Prediction of High-Lift Flows using Turbulent Closure Models

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Gatski, Thomas B.; Ying, Susan X.; Bertelrud, Arild

1997-01-01

The flow over two different multi-element airfoil configurations is computed using linear eddy viscosity turbulence models and a nonlinear explicit algebraic stress model. A subset of recently-measured transition locations using hot film on a McDonnell Douglas configuration is presented, and the effect of transition location on the computed solutions is explored. Deficiencies in wake profile computations are found to be attributable in large part to poor boundary layer prediction on the generating element, and not necessarily inadequate turbulence modeling in the wake. Using measured transition locations for the main element improves the prediction of its boundary layer thickness, skin friction, and wake profile shape. However, using measured transition locations on the slat still yields poor slat wake predictions. The computation of the slat flow field represents a key roadblock to successful predictions of multi-element flows. In general, the nonlinear explicit algebraic stress turbulence model gives very similar results to the linear eddy viscosity models.

Reinforcement learning in depression: A review of computational research.

PubMed

Chen, Chong; Takahashi, Taiki; Nakagawa, Shin; Inoue, Takeshi; Kusumi, Ichiro

2015-08-01

Despite being considered primarily a mood disorder, major depressive disorder (MDD) is characterized by cognitive and decision making deficits. Recent research has employed computational models of reinforcement learning (RL) to address these deficits. The computational approach has the advantage in making explicit predictions about learning and behavior, specifying the process parameters of RL, differentiating between model-free and model-based RL, and the computational model-based functional magnetic resonance imaging and electroencephalography. With these merits there has been an emerging field of computational psychiatry and here we review specific studies that focused on MDD. Considerable evidence suggests that MDD is associated with impaired brain signals of reward prediction error and expected value ('wanting'), decreased reward sensitivity ('liking') and/or learning (be it model-free or model-based), etc., although the causality remains unclear. These parameters may serve as valuable intermediate phenotypes of MDD, linking general clinical symptoms to underlying molecular dysfunctions. We believe future computational research at clinical, systems, and cellular/molecular/genetic levels will propel us toward a better understanding of the disease. Copyright © 2015 Elsevier Ltd. All rights reserved.

On a generalized laminate theory with application to bending, vibration, and delamination buckling in composite laminates

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

Barbero, E.J.

1989-01-01

In this study, a computational model for accurate analysis of composite laminates and laminates with including delaminated interfaces is developed. An accurate prediction of stress distributions, including interlaminar stresses, is obtained by using the Generalized Laminate Plate Theory of Reddy in which layer-wise linear approximation of the displacements through the thickness is used. Analytical as well as finite-element solutions of the theory are developed for bending and vibrations of laminated composite plates for the linear theory. Geometrical nonlinearity, including buckling and postbuckling are included and used to perform stress analysis of laminated plates. A general two dimensional theory of laminatedmore » cylindrical shells is also developed in this study. Geometrical nonlinearity and transverse compressibility are included. Delaminations between layers of composite plates are modelled by jump discontinuity conditions at the interfaces. The theory includes multiple delaminations through the thickness. Geometric nonlinearity is included to capture layer buckling. The strain energy release rate distribution along the boundary of delaminations is computed by a novel algorithm. The computational models presented herein are accurate for global behavior and particularly appropriate for the study of local effects.« less

A generalized global alignment algorithm.

PubMed

Huang, Xiaoqiu; Chao, Kun-Mao

2003-01-22

Homologous sequences are sometimes similar over some regions but different over other regions. Homologous sequences have a much lower global similarity if the different regions are much longer than the similar regions. We present a generalized global alignment algorithm for comparing sequences with intermittent similarities, an ordered list of similar regions separated by different regions. A generalized global alignment model is defined to handle sequences with intermittent similarities. A dynamic programming algorithm is designed to compute an optimal general alignment in time proportional to the product of sequence lengths and in space proportional to the sum of sequence lengths. The algorithm is implemented as a computer program named GAP3 (Global Alignment Program Version 3). The generalized global alignment model is validated by experimental results produced with GAP3 on both DNA and protein sequences. The GAP3 program extends the ability of standard global alignment programs to recognize homologous sequences of lower similarity. The GAP3 program is freely available for academic use at http://bioinformatics.iastate.edu/aat/align/align.html.

Prediction of pressure drop in fluid tuned mounts using analytical and computational techniques

NASA Technical Reports Server (NTRS)

Lasher, William C.; Khalilollahi, Amir; Mischler, John; Uhric, Tom

1993-01-01

A simplified model for predicting pressure drop in fluid tuned isolator mounts was developed. The model is based on an exact solution to the Navier-Stokes equations and was made more general through the use of empirical coefficients. The values of these coefficients were determined by numerical simulation of the flow using the commercial computational fluid dynamics (CFD) package FIDAP.

Documentation of a ground hydrology parameterization for use in the GISS atmospheric general circulation model

NASA Technical Reports Server (NTRS)

Lin, J. D.; Aleano, J.; Bock, P.

1978-01-01

The moisture transport processes related to the earth's surface relevant to the ground circulation model GCM are presented. The GHM parametrizations considered are: (1) ground wetness and soil parameters; (2) precipitation; (3) evapotranspiration; (4) surface storage of snow and ice; and (5) runout. The computational aspects of the GHM using computer programs and flow charts are described.

Quantum information processing by a continuous Maxwell demon

NASA Astrophysics Data System (ADS)

Stevens, Josey; Deffner, Sebastian

Quantum computing is believed to be fundamentally superior to classical computing; however quantifying the specific thermodynamic advantage has been elusive. Experimentally motivated, we generalize previous minimal models of discrete demons to continuous state space. Analyzing our model allows one to quantify the thermodynamic resources necessary to process quantum information. By further invoking the semi-classical limit we compare the quantum demon with its classical analogue. Finally, this model also serves as a starting point to study open quantum systems.

Consistency of Cluster Analysis for Cognitive Diagnosis: The Reduced Reparameterized Unified Model and the General Diagnostic Model.

PubMed

Chiu, Chia-Yi; Köhn, Hans-Friedrich

2016-09-01

The asymptotic classification theory of cognitive diagnosis (ACTCD) provided the theoretical foundation for using clustering methods that do not rely on a parametric statistical model for assigning examinees to proficiency classes. Like general diagnostic classification models, clustering methods can be useful in situations where the true diagnostic classification model (DCM) underlying the data is unknown and possibly misspecified, or the items of a test conform to a mix of multiple DCMs. Clustering methods can also be an option when fitting advanced and complex DCMs encounters computational difficulties. These can range from the use of excessive CPU times to plain computational infeasibility. However, the propositions of the ACTCD have only been proven for the Deterministic Input Noisy Output "AND" gate (DINA) model and the Deterministic Input Noisy Output "OR" gate (DINO) model. For other DCMs, there does not exist a theoretical justification to use clustering for assigning examinees to proficiency classes. But if clustering is to be used legitimately, then the ACTCD must cover a larger number of DCMs than just the DINA model and the DINO model. Thus, the purpose of this article is to prove the theoretical propositions of the ACTCD for two other important DCMs, the Reduced Reparameterized Unified Model and the General Diagnostic Model.

Testing alternative ground water models using cross-validation and other methods

USGS Publications Warehouse

Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.

2007-01-01

Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.

Empirical Performance Model-Driven Data Layout Optimization and Library Call Selection for Tensor Contraction Expressions

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

Lu, Qingda; Gao, Xiaoyang; Krishnamoorthy, Sriram

Empirical optimizers like ATLAS have been very effective in optimizing computational kernels in libraries. The best choice of parameters such as tile size and degree of loop unrolling is determined by executing different versions of the computation. In contrast, optimizing compilers use a model-driven approach to program transformation. While the model-driven approach of optimizing compilers is generally orders of magnitude faster than ATLAS-like library generators, its effectiveness can be limited by the accuracy of the performance models used. In this paper, we describe an approach where a class of computations is modeled in terms of constituent operations that are empiricallymore » measured, thereby allowing modeling of the overall execution time. The performance model with empirically determined cost components is used to perform data layout optimization together with the selection of library calls and layout transformations in the context of the Tensor Contraction Engine, a compiler for a high-level domain-specific language for expressing computational models in quantum chemistry. The effectiveness of the approach is demonstrated through experimental measurements on representative computations from quantum chemistry.« less

An interactive modeling program for the generation of planar polygons for boundary type solids representations of wire frame models

NASA Technical Reports Server (NTRS)

Ozsoy, T.; Ochs, J. B.

1984-01-01

The development of a general link between three dimensional wire frame models and rigid solid models is discussed. An interactive computer graphics program was developed to serve as a front end to an algorithm (COSMIC Program No. ARC-11446) which offers a general solution to the hidden line problem where the input data is either line segments of n-sided planar polygons of the most general type with internal boundaries. The program provides a general interface to CAD/CAM data bases and is implemented for models created on the Unigraphics VAX 11/780-based CAD/CAM systems with the display software written for DEC's VS11 color graphics devices.

A Generalized Information Theoretical Model for Quantum Secret Sharing

NASA Astrophysics Data System (ADS)

Bai, Chen-Ming; Li, Zhi-Hui; Xu, Ting-Ting; Li, Yong-Ming

2016-11-01

An information theoretical model for quantum secret sharing was introduced by H. Imai et al. (Quantum Inf. Comput. 5(1), 69-80 2005), which was analyzed by quantum information theory. In this paper, we analyze this information theoretical model using the properties of the quantum access structure. By the analysis we propose a generalized model definition for the quantum secret sharing schemes. In our model, there are more quantum access structures which can be realized by our generalized quantum secret sharing schemes than those of the previous one. In addition, we also analyse two kinds of important quantum access structures to illustrate the existence and rationality for the generalized quantum secret sharing schemes and consider the security of the scheme by simple examples.

On the sample complexity of learning for networks of spiking neurons with nonlinear synaptic interactions.

PubMed

Schmitt, Michael

2004-09-01

We study networks of spiking neurons that use the timing of pulses to encode information. Nonlinear interactions model the spatial groupings of synapses on the neural dendrites and describe the computations performed at local branches. Within a theoretical framework of learning we analyze the question of how many training examples these networks must receive to be able to generalize well. Bounds for this sample complexity of learning can be obtained in terms of a combinatorial parameter known as the pseudodimension. This dimension characterizes the computational richness of a neural network and is given in terms of the number of network parameters. Two types of feedforward architectures are considered: constant-depth networks and networks of unconstrained depth. We derive asymptotically tight bounds for each of these network types. Constant depth networks are shown to have an almost linear pseudodimension, whereas the pseudodimension of general networks is quadratic. Networks of spiking neurons that use temporal coding are becoming increasingly more important in practical tasks such as computer vision, speech recognition, and motor control. The question of how well these networks generalize from a given set of training examples is a central issue for their successful application as adaptive systems. The results show that, although coding and computation in these networks is quite different and in many cases more powerful, their generalization capabilities are at least as good as those of traditional neural network models.

Dynamics of convulsive seizure termination and postictal generalized EEG suppression

PubMed Central

Bauer, Prisca R.; Thijs, Roland D.; Lamberts, Robert J.; Velis, Demetrios N.; Visser, Gerhard H.; Tolner, Else A.; Sander, Josemir W.; Lopes da Silva, Fernando H.; Kalitzin, Stiliyan N.

2017-01-01

Abstract It is not fully understood how seizures terminate and why some seizures are followed by a period of complete brain activity suppression, postictal generalized EEG suppression. This is clinically relevant as there is a potential association between postictal generalized EEG suppression, cardiorespiratory arrest and sudden death following a seizure. We combined human encephalographic seizure data with data of a computational model of seizures to elucidate the neuronal network dynamics underlying seizure termination and the postictal generalized EEG suppression state. A multi-unit computational neural mass model of epileptic seizure termination and postictal recovery was developed. The model provided three predictions that were validated in EEG recordings of 48 convulsive seizures from 48 subjects with refractory focal epilepsy (20 females, age range 15–61 years). The duration of ictal and postictal generalized EEG suppression periods in human EEG followed a gamma probability distribution indicative of a deterministic process (shape parameter 2.6 and 1.5, respectively) as predicted by the model. In the model and in humans, the time between two clonic bursts increased exponentially from the start of the clonic phase of the seizure. The terminal interclonic interval, calculated using the projected terminal value of the log-linear fit of the clonic frequency decrease was correlated with the presence and duration of postictal suppression. The projected terminal interclonic interval explained 41% of the variation in postictal generalized EEG suppression duration (P < 0.02). Conversely, postictal generalized EEG suppression duration explained 34% of the variation in the last interclonic interval duration. Our findings suggest that postictal generalized EEG suppression is a separate brain state and that seizure termination is a plastic and autonomous process, reflected in increased duration of interclonic intervals that determine the duration of postictal generalized EEG suppression. PMID:28073789

Complex systems and health behavior change: insights from cognitive science.

PubMed

Orr, Mark G; Plaut, David C

2014-05-01

To provide proof-of-concept that quantum health behavior can be instantiated as a computational model that is informed by cognitive science, the Theory of Reasoned Action, and quantum health behavior theory. We conducted a synthetic review of the intersection of quantum health behavior change and cognitive science. We conducted simulations, using a computational model of quantum health behavior (a constraint satisfaction artificial neural network) and tested whether the model exhibited quantum-like behavior. The model exhibited clear signs of quantum-like behavior. Quantum health behavior can be conceptualized as constraint satisfaction: a mitigation between current behavioral state and the social contexts in which it operates. We outlined implications for moving forward with computational models of both quantum health behavior and health behavior in general.

Initial draft of CSE-UCLA evaluation model based on weighted product in order to optimize digital library services in computer college in Bali

NASA Astrophysics Data System (ADS)

Divayana, D. G. H.; Adiarta, A.; Abadi, I. B. G. S.

2018-01-01

The aim of this research was to create initial design of CSE-UCLA evaluation model modified with Weighted Product in evaluating digital library service at Computer College in Bali. The method used in this research was developmental research method and developed by Borg and Gall model design. The results obtained from the research that conducted earlier this month was a rough sketch of Weighted Product based CSE-UCLA evaluation model that the design had been able to provide a general overview of the stages of weighted product based CSE-UCLA evaluation model used in order to optimize the digital library services at the Computer Colleges in Bali.

Care 3 phase 2 report, maintenance manual

NASA Technical Reports Server (NTRS)

Bryant, L. A.; Stiffler, J. J.

1982-01-01

CARE 3 (Computer-Aided Reliability Estimation, version three) is a computer program designed to help estimate the reliability of complex, redundant systems. Although the program can model a wide variety of redundant structures, it was developed specifically for fault-tolerant avionics systems--systems distinguished by the need for extremely reliable performance since a system failure could well result in the loss of human life. It substantially generalizes the class of redundant configurations that could be accommodated, and includes a coverage model to determine the various coverage probabilities as a function of the applicable fault recovery mechanisms (detection delay, diagnostic scheduling interval, isolation and recovery delay, etc.). CARE 3 further generalizes the class of system structures that can be modeled and greatly expands the coverage model to take into account such effects as intermittent and transient faults, latent faults, error propagation, etc.

Nonlinear Real-Time Optical Signal Processing

DTIC Science & Technology

1990-09-01

pattern recognition. Additional work concerns the relationship of parallel computation paradigms to optical computing and halftone screen techniques...paradigms to optical computing and halftone screen techniques for implementing general nonlinear functions. 3\\ 2 Research Progress This section...Vol. 23, No. 8, pp. 34-57, 1986. 2.4 Nonlinear Optical Processing with Halftones : Degradation and Compen- sation Models This paper is concerned with

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.

A computational model of the cognitive impact of decorative elements on the perception of suspense

NASA Astrophysics Data System (ADS)

Delatorre, Pablo; León, Carlos; Gervás, Pablo; Palomo-Duarte, Manuel

2017-10-01

Suspense is a key narrative issue in terms of emotional gratification, influencing the way in which the audience experiences a story. Virtually all narrative media uses suspense as a strategy for reader engagement regardless of the technology or genre. Being such an important narrative component, computational creativity has tackled suspense in a number of automatic storytelling. These systems are mainly based on narrative theories, and in general lack a cognitive approach involving the study of empathy or emotional effect of the environment impact. With this idea in mind, this paper reports on a computational model of the influence of decorative elements on suspense. It has been developed as part of a more general proposal for plot generation based on cognitive aspects. In order to test and parameterise the model, an evaluation based on textual stories and an evaluation based on a 3D virtual environment was run. In both cases, results suggest a direct influence of emotional perception of decorative objects in the suspense of a scene.

Equations of motion for a spectrum-generating algebra: Lipkin Meshkov Glick model

NASA Astrophysics Data System (ADS)

Rosensteel, G.; Rowe, D. J.; Ho, S. Y.

2008-01-01

For a spectrum-generating Lie algebra, a generalized equations-of-motion scheme determines numerical values of excitation energies and algebra matrix elements. In the approach to the infinite particle number limit or, more generally, whenever the dimension of the quantum state space is very large, the equations-of-motion method may achieve results that are impractical to obtain by diagonalization of the Hamiltonian matrix. To test the method's effectiveness, we apply it to the well-known Lipkin-Meshkov-Glick (LMG) model to find its low-energy spectrum and associated generator matrix elements in the eigenenergy basis. When the dimension of the LMG representation space is 106, computation time on a notebook computer is a few minutes. For a large particle number in the LMG model, the low-energy spectrum makes a quantum phase transition from a nondegenerate harmonic vibrator to a twofold degenerate harmonic oscillator. The equations-of-motion method computes critical exponents at the transition point.

General Education Courses at the University of Botswana: Application of the Theory of Reasoned Action in Measuring Course Outcomes

ERIC Educational Resources Information Center

Garg, Deepti; Garg, Ajay K.

2007-01-01

This study applied the Theory of Reasoned Action and the Technology Acceptance Model to measure outcomes of general education courses (GECs) under the University of Botswana Computer and Information Skills (CIS) program. An exploratory model was validated for responses from 298 students. The results suggest that resources currently committed to…

Performance Analysis and Optimization on the UCLA Parallel Atmospheric General Circulation Model Code

NASA Technical Reports Server (NTRS)

Lou, John; Ferraro, Robert; Farrara, John; Mechoso, Carlos

1996-01-01

An analysis is presented of several factors influencing the performance of a parallel implementation of the UCLA atmospheric general circulation model (AGCM) on massively parallel computer systems. Several modificaitons to the original parallel AGCM code aimed at improving its numerical efficiency, interprocessor communication cost, load-balance and issues affecting single-node code performance are discussed.

Bioproducts and environmental quality: Biofuels, greenhouse gases, and water quality

NASA Astrophysics Data System (ADS)

Ren, Xiaolin

Promoting bio-based products is one oft-proposed solution to reduce GHG emissions because the feedstocks capture carbon, offsetting at least partially the carbon discharges resulting from use of the products. However, several life cycle analyses point out that while biofuels may emit less life cycle net carbon emissions than fossil fuels, they may exacerbate other parts of biogeochemical cycles, notably nutrient loads in the aquatic environment. In three essays, this dissertation explores the tradeoff between GHG emissions and nitrogen leaching associated with biofuel production using general equilibrium models. The first essay develops a theoretical general equilibrium model to calculate the second-best GHG tax with the existence of a nitrogen leaching distortion. The results indicate that the second-best GHG tax could be higher or lower than the first-best tax rates depending largely on the elasticity of substitution between fossil fuel and biofuel. The second and third essays employ computable general equilibrium models to further explore the tradeoff between GHG emissions and nitrogen leaching. The computable general equilibrium models also incorporate multiple biofuel pathways, i.e., biofuels made from different feedstocks using different processes, to identify the cost-effective combinations of biofuel pathways under different policies, and the corresponding economic and environmental impacts.

Highway infrastructure : FHWA's model for estimating highway needs is generally reasonable, despite limitations

DOT National Transportation Integrated Search

2000-06-01

The Highway Economic Requirements System (HERS) computer model estimates investment requirements for the nation's highways by adding together the costs of highway improvements that the model's benefit-cost analyses indicate are warranted. In making i...

A computational efficient modelling of laminar separation bubbles

NASA Technical Reports Server (NTRS)

Dini, Paolo; Maughmer, Mark D.

1990-01-01

In predicting the aerodynamic characteristics of airfoils operating at low Reynolds numbers, it is often important to account for the effects of laminar (transitional) separation bubbles. Previous approaches to the modelling of this viscous phenomenon range from fast but sometimes unreliable empirical correlations for the length of the bubble and the associated increase in momentum thickness, to more accurate but significantly slower displacement-thickness iteration methods employing inverse boundary-layer formulations in the separated regions. Since the penalty in computational time associated with the more general methods is unacceptable for airfoil design applications, use of an accurate yet computationally efficient model is highly desirable. To this end, a semi-empirical bubble model was developed and incorporated into the Eppler and Somers airfoil design and analysis program. The generality and the efficiency was achieved by successfully approximating the local viscous/inviscid interaction, the transition location, and the turbulent reattachment process within the framework of an integral boundary-layer method. Comparisons of the predicted aerodynamic characteristics with experimental measurements for several airfoils show excellent and consistent agreement for Reynolds numbers from 2,000,000 down to 100,000.

Generalized Maintenance Trainer Simulator: Development of Hardware and Software. Final Report.

ERIC Educational Resources Information Center

Towne, Douglas M.; Munro, Allen

A general purpose maintenance trainer, which has the potential to simulate a wide variety of electronic equipments without hardware changes or new computer programs, has been developed and field tested by the Navy. Based on a previous laboratory model, the Generalized Maintenance Trainer Simulator (GMTS) is a relatively low cost trainer that…

Simulation and evaluation of latent heat thermal energy storage

NASA Technical Reports Server (NTRS)

Sigmon, T. W.

1980-01-01

The relative value of thermal energy storage (TES) for heat pump storage (heating and cooling) as a function of storage temperature, mode of storage (hotside or coldside), geographic locations, and utility time of use rate structures were derived. Computer models used to simulate the performance of a number of TES/heat pump configurations are described. The models are based on existing performance data of heat pump components, available building thermal load computational procedures, and generalized TES subsystem design. Life cycle costs computed for each site, configuration, and rate structure are discussed.

A General-applications Direct Global Matrix Algorithm for Rapid Seismo-acoustic Wavefield Computations

NASA Technical Reports Server (NTRS)

Schmidt, H.; Tango, G. J.; Werby, M. F.

1985-01-01

A new matrix method for rapid wave propagation modeling in generalized stratified media, which has recently been applied to numerical simulations in diverse areas of underwater acoustics, solid earth seismology, and nondestructive ultrasonic scattering is explained and illustrated. A portion of recent efforts jointly undertaken at NATOSACLANT and NORDA Numerical Modeling groups in developing, implementing, and testing a new fast general-applications wave propagation algorithm, SAFARI, formulated at SACLANT is summarized. The present general-applications SAFARI program uses a Direct Global Matrix Approach to multilayer Green's function calculation. A rapid and unconditionally stable solution is readily obtained via simple Gaussian ellimination on the resulting sparsely banded block system, precisely analogous to that arising in the Finite Element Method. The resulting gains in accuracy and computational speed allow consideration of much larger multilayered air/ocean/Earth/engineering material media models, for many more source-receiver configurations than previously possible. The validity and versatility of the SAFARI-DGM method is demonstrated by reviewing three practical examples of engineering interest, drawn from ocean acoustics, engineering seismology and ultrasonic scattering.

Updated Panel-Method Computer Program

NASA Technical Reports Server (NTRS)

Ashby, Dale L.

1995-01-01

Panel code PMARC_12 (Panel Method Ames Research Center, version 12) computes potential-flow fields around complex three-dimensional bodies such as complete aircraft models. Contains several advanced features, including internal mathematical modeling of flow, time-stepping wake model for simulating either steady or unsteady motions, capability for Trefftz computation of drag induced by plane, and capability for computation of off-body and on-body streamlines, and capability of computation of boundary-layer parameters by use of two-dimensional integral boundary-layer method along surface streamlines. Investigators interested in visual representations of phenomena, may want to consider obtaining program GVS (ARC-13361), General visualization System. GVS is Silicon Graphics IRIS program created to support scientific-visualization needs of PMARC_12. GVS available separately from COSMIC. PMARC_12 written in standard FORTRAN 77, with exception of NAMELIST extension used for input.

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.

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

Wong, Raymond K. W.; Storlie, Curtis Byron; Lee, Thomas C. M.

The paper considers the computer model calibration problem and provides a general frequentist solution. Under the framework proposed, the data model is semiparametric with a non-parametric discrepancy function which accounts for any discrepancy between physical reality and the computer model. In an attempt to solve a fundamentally important (but often ignored) identifiability issue between the computer model parameters and the discrepancy function, the paper proposes a new and identifiable parameterization of the calibration problem. It also develops a two-step procedure for estimating all the relevant quantities under the new parameterization. This estimation procedure is shown to enjoy excellent rates ofmore » convergence and can be straightforwardly implemented with existing software. For uncertainty quantification, bootstrapping is adopted to construct confidence regions for the quantities of interest. As a result, the practical performance of the methodology is illustrated through simulation examples and an application to a computational fluid dynamics model.« less

Turbulence modeling of free shear layers for high-performance aircraft

NASA Technical Reports Server (NTRS)

Sondak, Douglas L.

1993-01-01

The High Performance Aircraft (HPA) Grand Challenge of the High Performance Computing and Communications (HPCC) program involves the computation of the flow over a high performance aircraft. A variety of free shear layers, including mixing layers over cavities, impinging jets, blown flaps, and exhaust plumes, may be encountered in such flowfields. Since these free shear layers are usually turbulent, appropriate turbulence models must be utilized in computations in order to accurately simulate these flow features. The HPCC program is relying heavily on parallel computers. A Navier-Stokes solver (POVERFLOW) utilizing the Baldwin-Lomax algebraic turbulence model was developed and tested on a 128-node Intel iPSC/860. Algebraic turbulence models run very fast, and give good results for many flowfields. For complex flowfields such as those mentioned above, however, they are often inadequate. It was therefore deemed that a two-equation turbulence model will be required for the HPA computations. The k-epsilon two-equation turbulence model was implemented on the Intel iPSC/860. Both the Chien low-Reynolds-number model and a generalized wall-function formulation were included.

Dynamic mechanistic explanation: computational modeling of circadian rhythms as an exemplar for cognitive science.

PubMed

Bechtel, William; Abrahamsen, Adele

2010-09-01

We consider computational modeling in two fields: chronobiology and cognitive science. In circadian rhythm models, variables generally correspond to properties of parts and operations of the responsible mechanism. A computational model of this complex mechanism is grounded in empirical discoveries and contributes a more refined understanding of the dynamics of its behavior. In cognitive science, on the other hand, computational modelers typically advance de novo proposals for mechanisms to account for behavior. They offer indirect evidence that a proposed mechanism is adequate to produce particular behavioral data, but typically there is no direct empirical evidence for the hypothesized parts and operations. Models in these two fields differ in the extent of their empirical grounding, but they share the goal of achieving dynamic mechanistic explanation. That is, they augment a proposed mechanistic explanation with a computational model that enables exploration of the mechanism's dynamics. Using exemplars from circadian rhythm research, we extract six specific contributions provided by computational models. We then examine cognitive science models to determine how well they make the same types of contributions. We suggest that the modeling approach used in circadian research may prove useful in cognitive science as researchers develop procedures for experimentally decomposing cognitive mechanisms into parts and operations and begin to understand their nonlinear interactions.

General Monte Carlo reliability simulation code including common mode failures and HARP fault/error-handling

NASA Technical Reports Server (NTRS)

Platt, M. E.; Lewis, E. E.; Boehm, F.

1991-01-01

A Monte Carlo Fortran computer program was developed that uses two variance reduction techniques for computing system reliability applicable to solving very large highly reliable fault-tolerant systems. The program is consistent with the hybrid automated reliability predictor (HARP) code which employs behavioral decomposition and complex fault-error handling models. This new capability is called MC-HARP which efficiently solves reliability models with non-constant failures rates (Weibull). Common mode failure modeling is also a specialty.

Conformal blocks from Wilson lines with loop corrections

NASA Astrophysics Data System (ADS)

Hikida, Yasuaki; Uetoko, Takahiro

2018-04-01

We compute the conformal blocks of the Virasoro minimal model or its WN extension with large central charge from Wilson line networks in a Chern-Simons theory including loop corrections. In our previous work, we offered a prescription to regularize divergences from loops attached to Wilson lines. In this paper, we generalize our method with the prescription by dealing with more general operators for N =3 and apply it to the identity W3 block. We further compute general light-light blocks and heavy-light correlators for N =2 with the Wilson line method and compare the results with known ones obtained using a different prescription. We briefly discuss general W3 blocks.

Space-Shuttle Emulator Software

NASA Technical Reports Server (NTRS)

Arnold, Scott; Askew, Bill; Barry, Matthew R.; Leigh, Agnes; Mermelstein, Scott; Owens, James; Payne, Dan; Pemble, Jim; Sollinger, John; Thompson, Hiram;

Next Generation Transport Phenomenology Model

NASA Technical Reports Server (NTRS)

Strickland, Douglas J.; Knight, Harold; Evans, J. Scott

2004-01-01

This report describes the progress made in Quarter 3 of Contract Year 3 on the development of Aeronomy Phenomenology Modeling Tool (APMT), an open-source, component-based, client-server architecture for distributed modeling, analysis, and simulation activities focused on electron and photon transport for general atmospheres. In the past quarter, column emission rate computations were implemented in Java, preexisting Fortran programs for computing synthetic spectra were embedded into APMT through Java wrappers, and work began on a web-based user interface for setting input parameters and running the photoelectron and auroral electron transport models.

Developmental and Life-Stage Physiologically-Based Pharmacokinetic (PBPK) Models in Humans and Animal Models.

EPA Science Inventory

PBPK models provide a computational framework for incorporating pertinent physiological and biochemical information to estimate in vivo levels of xenobiotics in biological tissues. In general, PBPK models are used to correlate exposures to target tissue levels of chemicals and th...

Guidelines and Procedures for Computing Time-Series Suspended-Sediment Concentrations and Loads from In-Stream Turbidity-Sensor and Streamflow Data

USGS Publications Warehouse

Rasmussen, Patrick P.; Gray, John R.; Glysson, G. Douglas; Ziegler, Andrew C.

2009-01-01

In-stream continuous turbidity and streamflow data, calibrated with measured suspended-sediment concentration data, can be used to compute a time series of suspended-sediment concentration and load at a stream site. Development of a simple linear (ordinary least squares) regression model for computing suspended-sediment concentrations from instantaneous turbidity data is the first step in the computation process. If the model standard percentage error (MSPE) of the simple linear regression model meets a minimum criterion, this model should be used to compute a time series of suspended-sediment concentrations. Otherwise, a multiple linear regression model using paired instantaneous turbidity and streamflow data is developed and compared to the simple regression model. If the inclusion of the streamflow variable proves to be statistically significant and the uncertainty associated with the multiple regression model results in an improvement over that for the simple linear model, the turbidity-streamflow multiple linear regression model should be used to compute a suspended-sediment concentration time series. The computed concentration time series is subsequently used with its paired streamflow time series to compute suspended-sediment loads by standard U.S. Geological Survey techniques. Once an acceptable regression model is developed, it can be used to compute suspended-sediment concentration beyond the period of record used in model development with proper ongoing collection and analysis of calibration samples. Regression models to compute suspended-sediment concentrations are generally site specific and should never be considered static, but they represent a set period in a continually dynamic system in which additional data will help verify any change in sediment load, type, and source.

Computer-Aided Communication Satellite System Analysis and Optimization.

ERIC Educational Resources Information Center

Stagl, Thomas W.; And Others

Various published computer programs for fixed/broadcast communication satellite system synthesis and optimization are discussed. The rationale for selecting General Dynamics/Convair's Satellite Telecommunication Analysis and Modeling Program (STAMP) in modified form to aid in the system costing and sensitivity analysis work in the Program on…

Analytical modeling of operating characteristics of premixing-prevaporizing fuel-air mixing passages. Volume 2: User's manual

NASA Technical Reports Server (NTRS)

Anderson, O. L.; Chiappetta, L. M.; Edwards, D. E.; Mcvey, J. B.

1982-01-01

A user's manual describing the operation of three computer codes (ADD code, PTRAK code, and VAPDIF code) is presented. The general features of the computer codes, the input/output formats, run streams, and sample input cases are described.

Method for nonlinear exponential regression analysis

NASA Technical Reports Server (NTRS)

Junkin, B. G.

1972-01-01

Two computer programs developed according to two general types of exponential models for conducting nonlinear exponential regression analysis are described. Least squares procedure is used in which the nonlinear problem is linearized by expanding in a Taylor series. Program is written in FORTRAN 5 for the Univac 1108 computer.

Computer Simulation in Social Science.

ERIC Educational Resources Information Center

Garson, G. David

From a base in military models, computer simulation has evolved to provide a wide variety of applications in social science. General purpose simulation packages and languages such as FIRM, DYNAMO, and others have made significant contributions toward policy discussion in the social sciences and have well-documented efficacy in instructional…

Computational models of epileptiform activity.

PubMed

Wendling, Fabrice; Benquet, Pascal; Bartolomei, Fabrice; Jirsa, Viktor

2016-02-15

We reviewed computer models that have been developed to reproduce and explain epileptiform activity. Unlike other already-published reviews on computer models of epilepsy, the proposed overview starts from the various types of epileptiform activity encountered during both interictal and ictal periods. Computational models proposed so far in the context of partial and generalized epilepsies are classified according to the following taxonomy: neural mass, neural field, detailed network and formal mathematical models. Insights gained about interictal epileptic spikes and high-frequency oscillations, about fast oscillations at seizure onset, about seizure initiation and propagation, about spike-wave discharges and about status epilepticus are described. This review shows the richness and complementarity of the various modeling approaches as well as the fruitful contribution of the computational neuroscience community in the field of epilepsy research. It shows that models have progressively gained acceptance and are now considered as an efficient way of integrating structural, functional and pathophysiological data about neural systems into "coherent and interpretable views". The advantages, limitations and future of modeling approaches are discussed. Perspectives in epilepsy research and clinical epileptology indicate that very promising directions are foreseen, like model-guided experiments or model-guided therapeutic strategy, among others. Copyright © 2015 Elsevier B.V. All rights reserved.

Transportation Impact Evaluation System

DOT National Transportation Integrated Search

1979-11-01

This report specifies a framework for spatial analysis and the general modelling steps required. It also suggests available urban and regional data sources, along with some typical existing urban and regional models. The goal is to develop a computer...

Tomography and generative training with quantum Boltzmann machines

NASA Astrophysics Data System (ADS)

Kieferová, Mária; Wiebe, Nathan

2017-12-01

The promise of quantum neural nets, which utilize quantum effects to model complex data sets, has made their development an aspirational goal for quantum machine learning and quantum computing in general. Here we provide methods of training quantum Boltzmann machines. Our work generalizes existing methods and provides additional approaches for training quantum neural networks that compare favorably to existing methods. We further demonstrate that quantum Boltzmann machines enable a form of partial quantum state tomography that further provides a generative model for the input quantum state. Classical Boltzmann machines are incapable of this. This verifies the long-conjectured connection between tomography and quantum machine learning. Finally, we prove that classical computers cannot simulate our training process in general unless BQP=BPP , provide lower bounds on the complexity of the training procedures and numerically investigate training for small nonstoquastic Hamiltonians.

Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

NASA Astrophysics Data System (ADS)

Lane, Peter C. R.; Gobet, Fernand

2013-03-01

Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.

On testing an unspecified function through a linear mixed effects model with multiple variance components

PubMed Central

Wang, Yuanjia; Chen, Huaihou

2012-01-01

Summary We examine a generalized F-test of a nonparametric function through penalized splines and a linear mixed effects model representation. With a mixed effects model representation of penalized splines, we imbed the test of an unspecified function into a test of some fixed effects and a variance component in a linear mixed effects model with nuisance variance components under the null. The procedure can be used to test a nonparametric function or varying-coefficient with clustered data, compare two spline functions, test the significance of an unspecified function in an additive model with multiple components, and test a row or a column effect in a two-way analysis of variance model. Through a spectral decomposition of the residual sum of squares, we provide a fast algorithm for computing the null distribution of the test, which significantly improves the computational efficiency over bootstrap. The spectral representation reveals a connection between the likelihood ratio test (LRT) in a multiple variance components model and a single component model. We examine our methods through simulations, where we show that the power of the generalized F-test may be higher than the LRT, depending on the hypothesis of interest and the true model under the alternative. We apply these methods to compute the genome-wide critical value and p-value of a genetic association test in a genome-wide association study (GWAS), where the usual bootstrap is computationally intensive (up to 108 simulations) and asymptotic approximation may be unreliable and conservative. PMID:23020801

On testing an unspecified function through a linear mixed effects model with multiple variance components.

PubMed

Wang, Yuanjia; Chen, Huaihou

2012-12-01

We examine a generalized F-test of a nonparametric function through penalized splines and a linear mixed effects model representation. With a mixed effects model representation of penalized splines, we imbed the test of an unspecified function into a test of some fixed effects and a variance component in a linear mixed effects model with nuisance variance components under the null. The procedure can be used to test a nonparametric function or varying-coefficient with clustered data, compare two spline functions, test the significance of an unspecified function in an additive model with multiple components, and test a row or a column effect in a two-way analysis of variance model. Through a spectral decomposition of the residual sum of squares, we provide a fast algorithm for computing the null distribution of the test, which significantly improves the computational efficiency over bootstrap. The spectral representation reveals a connection between the likelihood ratio test (LRT) in a multiple variance components model and a single component model. We examine our methods through simulations, where we show that the power of the generalized F-test may be higher than the LRT, depending on the hypothesis of interest and the true model under the alternative. We apply these methods to compute the genome-wide critical value and p-value of a genetic association test in a genome-wide association study (GWAS), where the usual bootstrap is computationally intensive (up to 10(8) simulations) and asymptotic approximation may be unreliable and conservative. © 2012, The International Biometric Society.

USER'S MANUAL FOR THE INSTREAM SEDIMENT-CONTAMINANT TRANSPORT MODEL SERATRA

EPA Science Inventory

This manual guides the user in applying the sediment-contaminant transport model SERATRA. SERATRA is an unsteady, two-dimensional code that uses the finite element computation method with the Galerkin weighted residual technique. The model has general convection-diffusion equatio...

A MATHEMATICAL MODEL OF ELECTROSTATIC PRECIPITATION. (REVISION 1): VOLUME I. MODELING AND PROGRAMMING

EPA Science Inventory

The report briefly describes the fundamental mechanisms and limiting factors involved in the electrostatic precipitation process. It discusses theories and procedures used in the computer model to describe the physical mechanisms, and generally describes the major operations perf...

A Hybrid Multiscale Framework for Subsurface Flow and Transport Simulations

DOE PAGES

Scheibe, Timothy D.; Yang, Xiaofan; Chen, Xingyuan; ...

2015-06-01

Extensive research efforts have been invested in reducing model errors to improve the predictive ability of biogeochemical earth and environmental system simulators, with applications ranging from contaminant transport and remediation to impacts of biogeochemical elemental cycling (e.g., carbon and nitrogen) on local ecosystems and regional to global climate. While the bulk of this research has focused on improving model parameterizations in the face of observational limitations, the more challenging type of model error/uncertainty to identify and quantify is model structural error which arises from incorrect mathematical representations of (or failure to consider) important physical, chemical, or biological processes, properties, ormore » system states in model formulations. While improved process understanding can be achieved through scientific study, such understanding is usually developed at small scales. Process-based numerical models are typically designed for a particular characteristic length and time scale. For application-relevant scales, it is generally necessary to introduce approximations and empirical parameterizations to describe complex systems or processes. This single-scale approach has been the best available to date because of limited understanding of process coupling combined with practical limitations on system characterization and computation. While computational power is increasing significantly and our understanding of biological and environmental processes at fundamental scales is accelerating, using this information to advance our knowledge of the larger system behavior requires the development of multiscale simulators. Accordingly there has been much recent interest in novel multiscale methods in which microscale and macroscale models are explicitly coupled in a single hybrid multiscale simulation. A limited number of hybrid multiscale simulations have been developed for biogeochemical earth systems, but they mostly utilize application-specific and sometimes ad-hoc approaches for model coupling. We are developing a generalized approach to hierarchical model coupling designed for high-performance computational systems, based on the Swift computing workflow framework. In this presentation we will describe the generalized approach and provide two use cases: 1) simulation of a mixing-controlled biogeochemical reaction coupling pore- and continuum-scale models, and 2) simulation of biogeochemical impacts of groundwater – river water interactions coupling fine- and coarse-grid model representations. This generalized framework can be customized for use with any pair of linked models (microscale and macroscale) with minimal intrusiveness to the at-scale simulators. It combines a set of python scripts with the Swift workflow environment to execute a complex multiscale simulation utilizing an approach similar to the well-known Heterogeneous Multiscale Method. User customization is facilitated through user-provided input and output file templates and processing function scripts, and execution within a high-performance computing environment is handled by Swift, such that minimal to no user modification of at-scale codes is required.« less

General relativistic spectra of accretion discs around rapidly rotating neutron stars: effect of light bending

NASA Astrophysics Data System (ADS)

Bhattacharyya, Sudip; Bhattacharya, Dipankar; Thampan, Arun V.

2001-08-01

We present computed spectra, as seen by a distant observer, from the accretion disc around a rapidly rotating neutron star. Our calculations are carried out in a fully general relativistic framework, with an exact treatment of rotation. We take into account the Doppler shift, gravitational redshift and light-bending effects in order to compute the observed spectrum. We find that light bending significantly modifies the high-energy part of the spectrum. Computed spectra for slowly rotating neutron stars are also presented. These results would be important for modelling the observed X-ray spectra of low-mass X-ray binaries containing fast-spinning neutron stars.

The Metadata Cloud: The Last Piece of a Distributed Data System Model

NASA Astrophysics Data System (ADS)

King, T. A.; Cecconi, B.; Hughes, J. S.; Walker, R. J.; Roberts, D.; Thieman, J. R.; Joy, S. P.; Mafi, J. N.; Gangloff, M.

2012-12-01

Distributed data systems have existed ever since systems were networked together. Over the years the model for distributed data systems have evolved from basic file transfer to client-server to multi-tiered to grid and finally to cloud based systems. Initially metadata was tightly coupled to the data either by embedding the metadata in the same file containing the data or by co-locating the metadata in commonly named files. As the sources of data multiplied, data volumes have increased and services have specialized to improve efficiency; a cloud system model has emerged. In a cloud system computing and storage are provided as services with accessibility emphasized over physical location. Computation and data clouds are common implementations. Effectively using the data and computation capabilities requires metadata. When metadata is stored separately from the data; a metadata cloud is formed. With a metadata cloud information and knowledge about data resources can migrate efficiently from system to system, enabling services and allowing the data to remain efficiently stored until used. This is especially important with "Big Data" where movement of the data is limited by bandwidth. We examine how the metadata cloud completes a general distributed data system model, how standards play a role and relate this to the existing types of cloud computing. We also look at the major science data systems in existence and compare each to the generalized cloud system model.

Nonlinear Visco-Elastic Response of Composites via Micro-Mechanical Models

NASA Technical Reports Server (NTRS)

Gates, Thomas S.; Sridharan, Srinivasan

2005-01-01

Micro-mechanical models for a study of nonlinear visco-elastic response of composite laminae are developed and their performance compared. A single integral constitutive law proposed by Schapery and subsequently generalized to multi-axial states of stress is utilized in the study for the matrix material. This is used in conjunction with a computationally facile scheme in which hereditary strains are computed using a recursive relation suggested by Henriksen. Composite response is studied using two competing micro-models, viz. a simplified Square Cell Model (SSCM) and a Finite Element based self-consistent Cylindrical Model (FECM). The algorithm is developed assuming that the material response computations are carried out in a module attached to a general purpose finite element program used for composite structural analysis. It is shown that the SSCM as used in investigations of material nonlinearity can involve significant errors in the prediction of transverse Young's modulus and shear modulus. The errors in the elastic strains thus predicted are of the same order of magnitude as the creep strains accruing due to visco-elasticity. The FECM on the other hand does appear to perform better both in the prediction of elastic constants and the study of creep response.

Coupled multipolar interactions in small-particle metallic clusters.

PubMed

Pustovit, Vitaly N; Sotelo, Juan A; Niklasson, Gunnar A

2002-03-01

We propose a new formalism for computing the optical properties of small clusters of particles. It is a generalization of the coupled dipole-dipole particle-interaction model and allows one in principle to take into account all multipolar interactions in the long-wavelength limit. The method is illustrated by computations of the optical properties of N = 6 particle clusters for different multipolar approximations. We examine the effect of separation between particles and compare the optical spectra with the discrete-dipole approximation and the generalized Mie theory.

Parallel Computation of the Regional Ocean Modeling System (ROMS)

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

Wang, P; Song, Y T; Chao, Y

2005-04-05

The Regional Ocean Modeling System (ROMS) is a regional ocean general circulation modeling system solving the free surface, hydrostatic, primitive equations over varying topography. It is free software distributed world-wide for studying both complex coastal ocean problems and the basin-to-global scale ocean circulation. The original ROMS code could only be run on shared-memory systems. With the increasing need to simulate larger model domains with finer resolutions and on a variety of computer platforms, there is a need in the ocean-modeling community to have a ROMS code that can be run on any parallel computer ranging from 10 to hundreds ofmore » processors. Recently, we have explored parallelization for ROMS using the MPI programming model. In this paper, an efficient parallelization strategy for such a large-scale scientific software package, based on an existing shared-memory computing model, is presented. In addition, scientific applications and data-performance issues on a couple of SGI systems, including Columbia, the world's third-fastest supercomputer, are discussed.« less

Improving science and mathematics education with computational modelling in interactive engagement environments

NASA Astrophysics Data System (ADS)

Neves, Rui Gomes; Teodoro, Vítor Duarte

2012-09-01

A teaching approach aiming at an epistemologically balanced integration of computational modelling in science and mathematics education is presented. The approach is based on interactive engagement learning activities built around computational modelling experiments that span the range of different kinds of modelling from explorative to expressive modelling. The activities are designed to make a progressive introduction to scientific computation without requiring prior development of a working knowledge of programming, generate and foster the resolution of cognitive conflicts in the understanding of scientific and mathematical concepts and promote performative competency in the manipulation of different and complementary representations of mathematical models. The activities are supported by interactive PDF documents which explain the fundamental concepts, methods and reasoning processes using text, images and embedded movies, and include free space for multimedia enriched student modelling reports and teacher feedback. To illustrate, an example from physics implemented in the Modellus environment and tested in undergraduate university general physics and biophysics courses is discussed.

Comparison and Computational Performance of Tsunami-HySEA and MOST Models for the LANTEX 2013 scenario

NASA Astrophysics Data System (ADS)

González-Vida, Jose M.; Macías, Jorge; Mercado, Aurelio; Ortega, Sergio; Castro, Manuel J.

2017-04-01

Tsunami-HySEA model is used to simulate the Caribbean LANTEX 2013 scenario (LANTEX is the acronym for Large AtlaNtic Tsunami EXercise, which is carried out annually). The numerical simulation of the propagation and inundation phases, is performed with both models but using different mesh resolutions and nested meshes. Some comparisons with the MOST tsunami model available at the University of Puerto Rico (UPR) are made. Both models compare well for propagating tsunami waves in open sea, producing very similar results. In near-shore shallow waters, Tsunami-HySEA should be compared with the inundation version of MOST, since the propagation version of MOST is limited to deeper waters. Regarding the inundation phase, a 1 arc-sec (approximately 30 m) resolution mesh covering all of Puerto Rico, is used, and a three-level nested meshes technique implemented. In the inundation phase, larger differences between model results are observed. Nevertheless, the most striking difference resides in computational time; Tsunami-HySEA is coded using the advantages of GPU architecture, and can produce a 4 h simulation in a 60 arcsec resolution grid for the whole Caribbean Sea in less than 4 min with a single general-purpose GPU and as fast as 11 s with 32 general-purpose GPUs. In the inundation stage with nested meshes, approximately 8 hours of wall clock time is needed for a 2-h simulation in a single GPU (versus more than 2 days for the MOST inundation, running three different parts of the island—West, Center, East—at the same time due to memory limitations in MOST). When domain decomposition techniques are finally implemented by breaking up the computational domain into sub-domains and assigning a GPU to each sub-domain (multi-GPU Tsunami-HySEA version), we show that the wall clock time significantly decreases, allowing high-resolution inundation modelling in very short computational times, reducing, for example, if eight GPUs are used, the wall clock time to around 1 hour. Besides, these computational times are obtained using general-purpose GPU hardware.

A Computational Framework for Realistic Retina Modeling.

PubMed

Martínez-Cañada, Pablo; Morillas, Christian; Pino, Begoña; Ros, Eduardo; Pelayo, Francisco

2016-11-01

Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different visual processing pathways. While many of these models share common computational stages, previous efforts have been more focused on fitting specific retina functions rather than generalizing them beyond a particular model. Here, we define a set of computational retinal microcircuits that can be used as basic building blocks for the modeling of different retina mechanisms. To validate the hypothesis that similar processing structures may be repeatedly found in different retina functions, we implemented a series of retina models simply by combining these computational retinal microcircuits. Accuracy of the retina models for capturing neural behavior was assessed by fitting published electrophysiological recordings that characterize some of the best-known phenomena observed in the retina: adaptation to the mean light intensity and temporal contrast, and differential motion sensitivity. The retinal microcircuits are part of a new software platform for efficient computational retina modeling from single-cell to large-scale levels. It includes an interface with spiking neural networks that allows simulation of the spiking response of ganglion cells and integration with models of higher visual areas.

User's manual for generalized ILSGLD-ILS glide slope performance prediction : multipath scattering

DOT National Transportation Integrated Search

1976-11-01

This manual presents the computer program package for the generalized ILSGLD scattering model. The text includes a complete description of the program itself as well as 3 brief descriptions : of the ILS system and antenna patterns. The program listin...

Regression modeling of ground-water flow

USGS Publications Warehouse

Cooley, R.L.; Naff, R.L.

1985-01-01

Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)

Probability, statistics, and computational science.

PubMed

Beerenwinkel, Niko; Siebourg, Juliane

2012-01-01

In this chapter, we review basic concepts from probability theory and computational statistics that are fundamental to evolutionary genomics. We provide a very basic introduction to statistical modeling and discuss general principles, including maximum likelihood and Bayesian inference. Markov chains, hidden Markov models, and Bayesian network models are introduced in more detail as they occur frequently and in many variations in genomics applications. In particular, we discuss efficient inference algorithms and methods for learning these models from partially observed data. Several simple examples are given throughout the text, some of which point to models that are discussed in more detail in subsequent chapters.

Use of a computer model in the understanding of erythropoietic control mechanisms

NASA Technical Reports Server (NTRS)

Dunn, C. D. R.

1978-01-01

During an eight-week visit approximately 200 simulations using the computer model for the regulation of erythopoiesis were carries out in four general areas: with the human model simulating hypoxia and dehydration, evaluation of the simulation of dehydration using the mouse model. The experiments led to two considerations for the models. Firstly, a direct relationship between erythropoietin concentration and bone marrow sensitivity to the hormone and, secondly, a partial correction of tissue hypoxia prior to compensation by an increased hematocrit. This latter change in particular produced a better simuation of the effects of hypoxia on plasma erythropoietin concentrations.

Description of a computer program and numerical techniques for developing linear perturbation models from nonlinear systems simulations

NASA Technical Reports Server (NTRS)

Dieudonne, J. E.

1978-01-01

A numerical technique was developed which generates linear perturbation models from nonlinear aircraft vehicle simulations. The technique is very general and can be applied to simulations of any system that is described by nonlinear differential equations. The computer program used to generate these models is discussed, with emphasis placed on generation of the Jacobian matrices, calculation of the coefficients needed for solving the perturbation model, and generation of the solution of the linear differential equations. An example application of the technique to a nonlinear model of the NASA terminal configured vehicle is included.

Computer studies of baroclinic flow. [Atmospheric General Circulation Experiment

NASA Technical Reports Server (NTRS)

Gall, R.

1985-01-01

Programs necessary for computing the transition curve on the regime diagram for the atmospheric general circulation experiment (AGOE) were completed and used to determine the regime diagram for the rotating annulus and some axisymmetric flows for one possible AGOE configuration. The effect of geometrical constraints on the size of eddies developing from a basic state is being examined. In AGOE, the geometric constraint should be the width of the shear zone or the baroclinic zone. Linear and nonlinear models are to be used to examine both barotropic and baroclinic flows. The results should help explain the scale selection mechanism of baroclinic eddies in the atmosphere experimental models such as AGOE, and the multiple vortex phenomenon in tornadoes.

Generative models for clinical applications in computational psychiatry.

PubMed

Frässle, Stefan; Yao, Yu; Schöbi, Dario; Aponte, Eduardo A; Heinzle, Jakob; Stephan, Klaas E

2018-05-01

Despite the success of modern neuroimaging techniques in furthering our understanding of cognitive and pathophysiological processes, translation of these advances into clinically relevant tools has been virtually absent until now. Neuromodeling represents a powerful framework for overcoming this translational deadlock, and the development of computational models to solve clinical problems has become a major scientific goal over the last decade, as reflected by the emergence of clinically oriented neuromodeling fields like Computational Psychiatry, Computational Neurology, and Computational Psychosomatics. Generative models of brain physiology and connectivity in the human brain play a key role in this endeavor, striving for computational assays that can be applied to neuroimaging data from individual patients for differential diagnosis and treatment prediction. In this review, we focus on dynamic causal modeling (DCM) and its use for Computational Psychiatry. DCM is a widely used generative modeling framework for functional magnetic resonance imaging (fMRI) and magneto-/electroencephalography (M/EEG) data. This article reviews the basic concepts of DCM, revisits examples where it has proven valuable for addressing clinically relevant questions, and critically discusses methodological challenges and recent methodological advances. We conclude this review with a more general discussion of the promises and pitfalls of generative models in Computational Psychiatry and highlight the path that lies ahead of us. This article is categorized under: Neuroscience > Computation Neuroscience > Clinical Neuroscience. © 2018 Wiley Periodicals, Inc.

Neural networks with multiple general neuron models: a hybrid computational intelligence approach using Genetic Programming.

PubMed

Barton, Alan J; Valdés, Julio J; Orchard, Robert

2009-01-01

Classical neural networks are composed of neurons whose nature is determined by a certain function (the neuron model), usually pre-specified. In this paper, a type of neural network (NN-GP) is presented in which: (i) each neuron may have its own neuron model in the form of a general function, (ii) any layout (i.e network interconnection) is possible, and (iii) no bias nodes or weights are associated to the connections, neurons or layers. The general functions associated to a neuron are learned by searching a function space. They are not provided a priori, but are rather built as part of an Evolutionary Computation process based on Genetic Programming. The resulting network solutions are evaluated based on a fitness measure, which may, for example, be based on classification or regression errors. Two real-world examples are presented to illustrate the promising behaviour on classification problems via construction of a low-dimensional representation of a high-dimensional parameter space associated to the set of all network solutions.

Modeling molecule-plasmon interactions using quantized radiation fields within time-dependent electronic structure theory

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

Nascimento, Daniel R.; DePrince, A. Eugene, E-mail: deprince@chem.fsu.edu

2015-12-07

We present a combined cavity quantum electrodynamics/ab initio electronic structure approach for simulating plasmon-molecule interactions in the time domain. The simple Jaynes-Cummings-type model Hamiltonian typically utilized in such simulations is replaced with one in which the molecular component of the coupled system is treated in a fully ab initio way, resulting in a computationally efficient description of general plasmon-molecule interactions. Mutual polarization effects are easily incorporated within a standard ground-state Hartree-Fock computation, and time-dependent simulations carry the same formal computational scaling as real-time time-dependent Hartree-Fock theory. As a proof of principle, we apply this generalized method to the emergence ofmore » a Fano-like resonance in coupled molecule-plasmon systems; this feature is quite sensitive to the nanoparticle-molecule separation and the orientation of the molecule relative to the polarization of the external electric field.« less

Massive parallelization of serial inference algorithms for a complex generalized linear model

PubMed Central

Suchard, Marc A.; Simpson, Shawn E.; Zorych, Ivan; Ryan, Patrick; Madigan, David

2014-01-01

Following a series of high-profile drug safety disasters in recent years, many countries are redoubling their efforts to ensure the safety of licensed medical products. Large-scale observational databases such as claims databases or electronic health record systems are attracting particular attention in this regard, but present significant methodological and computational concerns. In this paper we show how high-performance statistical computation, including graphics processing units, relatively inexpensive highly parallel computing devices, can enable complex methods in large databases. We focus on optimization and massive parallelization of cyclic coordinate descent approaches to fit a conditioned generalized linear model involving tens of millions of observations and thousands of predictors in a Bayesian context. We find orders-of-magnitude improvement in overall run-time. Coordinate descent approaches are ubiquitous in high-dimensional statistics and the algorithms we propose open up exciting new methodological possibilities with the potential to significantly improve drug safety. PMID:25328363

Comparison of SOM point densities based on different criteria.

PubMed

Kohonen, T

1999-11-15

Point densities of model (codebook) vectors in self-organizing maps (SOMs) are evaluated in this article. For a few one-dimensional SOMs with finite grid lengths and a given probability density function of the input, the numerically exact point densities have been computed. The point density derived from the SOM algorithm turned out to be different from that minimizing the SOM distortion measure, showing that the model vectors produced by the basic SOM algorithm in general do not exactly coincide with the optimum of the distortion measure. A new computing technique based on the calculus of variations has been introduced. It was applied to the computation of point densities derived from the distortion measure for both the classical vector quantization and the SOM with general but equal dimensionality of the input vectors and the grid, respectively. The power laws in the continuum limit obtained in these cases were found to be identical.

A Moderate Constructivist E-Learning Instructional Model Evaluated on Computer Specialists

ERIC Educational Resources Information Center

Alonso, Fernando; Manrique, Daniel; Vines, Jose M.

2009-01-01

This paper presents a novel instructional model for e-learning and an evaluation study to determine the effectiveness of this model for teaching Java language programming to information technology specialists working for the Spanish Public Administration. This is a general-purpose model that combines objectivist and constructivist learning…

Historical Development of Simulation Models of Recreation Use

Treesearch

Jan W. van Wagtendonk; David N. Cole

2005-01-01

The potential utility of modeling as a park and wilderness management tool has been recognized for decades. Romesburg (1974) explored how mathematical decision modeling could be used to improve decisions about regulation of wilderness use. Cesario (1975) described a computer simulation modeling approach that utilized GPSS (General Purpose Systems Simulator), a...

Generalized Fluid System Simulation Program (GFSSP) - Version 6

NASA Technical Reports Server (NTRS)

Majumdar, Alok; LeClair, Andre; Moore, Ric; Schallhorn, Paul

2015-01-01

The Generalized Fluid System Simulation Program (GFSSP) is a finite-volume based general-purpose computer program for analyzing steady state and time-dependent flow rates, pressures, temperatures, and concentrations in a complex flow network. The program is capable of modeling real fluids with phase changes, compressibility, mixture thermodynamics, conjugate heat transfer between solid and fluid, fluid transients, pumps, compressors, flow control valves and external body forces such as gravity and centrifugal. The thermo-fluid system to be analyzed is discretized into nodes, branches, and conductors. The scalar properties such as pressure, temperature, and concentrations are calculated at nodes. Mass flow rates and heat transfer rates are computed in branches and conductors. The graphical user interface allows users to build their models using the 'point, drag, and click' method; the users can also run their models and post-process the results in the same environment. The integrated fluid library supplies thermodynamic and thermo-physical properties of 36 fluids, and 24 different resistance/source options are provided for modeling momentum sources or sinks in the branches. Users can introduce new physics, non-linear and time-dependent boundary conditions through user-subroutine.

Generalized Fluid System Simulation Program, Version 6.0

NASA Technical Reports Server (NTRS)

Majumdar, A. K.; LeClair, A. C.; Moore, A.; Schallhorn, P. A.

2013-01-01

The Generalized Fluid System Simulation Program (GFSSP) is a finite-volume based general-purpose computer program for analyzing steady state and time-dependant flow rates, pressures, temperatures, and concentrations in a complex flow network. The program is capable of modeling real fluids with phase changes, compressibility, mixture thermodynamics, conjugate heat transfer between solid and fluid, fluid transients, pumps, compressors and external body forces such as gravity and centrifugal. The thermo-fluid system to be analyzed is discretized into nodes, branches, and conductors. The scalar properties such as pressure, temperature, and concentrations are calculated at nodes. Mass flow rates and heat transfer rates are computed in branches and conductors. The graphical user interface allows users to build their models using the 'point, drag, and click' method; the users can also run their models and post-process the results in the same environment. The integrated fluid library supplies thermodynamic and thermo-physical properties of 36 fluids, and 24 different resistance/source options are provided for modeling momentum sources or sinks in the branches. This Technical Memorandum illustrates the application and verification of the code through 25 demonstrated example problems.

Generalized Fluid System Simulation Program, Version 5.0-Educational

NASA Technical Reports Server (NTRS)

Majumdar, A. K.

2011-01-01

The Generalized Fluid System Simulation Program (GFSSP) is a finite-volume based general-purpose computer program for analyzing steady state and time-dependent flow rates, pressures, temperatures, and concentrations in a complex flow network. The program is capable of modeling real fluids with phase changes, compressibility, mixture thermodynamics, conjugate heat transfer between solid and fluid, fluid transients, pumps, compressors and external body forces such as gravity and centrifugal. The thermofluid system to be analyzed is discretized into nodes, branches, and conductors. The scalar properties such as pressure, temperature, and concentrations are calculated at nodes. Mass flow rates and heat transfer rates are computed in branches and conductors. The graphical user interface allows users to build their models using the point, drag and click method; the users can also run their models and post-process the results in the same environment. The integrated fluid library supplies thermodynamic and thermo-physical properties of 36 fluids and 21 different resistance/source options are provided for modeling momentum sources or sinks in the branches. This Technical Memorandum illustrates the application and verification of the code through 12 demonstrated example problems.

Application of geometric approximation to the CPMG experiment: Two- and three-site exchange.

PubMed

Chao, Fa-An; Byrd, R Andrew

2017-04-01

The Carr-Purcell-Meiboom-Gill (CPMG) experiment is one of the most classical and well-known relaxation dispersion experiments in NMR spectroscopy, and it has been successfully applied to characterize biologically relevant conformational dynamics in many cases. Although the data analysis of the CPMG experiment for the 2-site exchange model can be facilitated by analytical solutions, the data analysis in a more complex exchange model generally requires computationally-intensive numerical analysis. Recently, a powerful computational strategy, geometric approximation, has been proposed to provide approximate numerical solutions for the adiabatic relaxation dispersion experiments where analytical solutions are neither available nor feasible. Here, we demonstrate the general potential of geometric approximation by providing a data analysis solution of the CPMG experiment for both the traditional 2-site model and a linear 3-site exchange model. The approximate numerical solution deviates less than 0.5% from the numerical solution on average, and the new approach is computationally 60,000-fold more efficient than the numerical approach. Moreover, we find that accurate dynamic parameters can be determined in most cases, and, for a range of experimental conditions, the relaxation can be assumed to follow mono-exponential decay. The method is general and applicable to any CPMG RD experiment (e.g. N, C', C α , H α , etc.) The approach forms a foundation of building solution surfaces to analyze the CPMG experiment for different models of 3-site exchange. Thus, the geometric approximation is a general strategy to analyze relaxation dispersion data in any system (biological or chemical) if the appropriate library can be built in a physically meaningful domain. Published by Elsevier Inc.

An application of interactive computer graphics technology to the design of dispersal mechanisms

NASA Technical Reports Server (NTRS)

Richter, B. J.; Welch, B. H.

1977-01-01

Interactive computer graphics technology is combined with a general purpose mechanisms computer code to study the operational behavior of three guided bomb dispersal mechanism designs. These studies illustrate the use of computer graphics techniques to discover operational anomalies, to assess the effectiveness of design improvements, to reduce the time and cost of the modeling effort, and to provide the mechanism designer with a visual understanding of the physical operation of such systems.

Advanced Multiple Processor Configuration Study. Final Report.

ERIC Educational Resources Information Center

Clymer, S. J.

This summary of a study on multiple processor configurations includes the objectives, background, approach, and results of research undertaken to provide the Air Force with a generalized model of computer processor combinations for use in the evaluation of proposed flight training simulator computational designs. An analysis of a real-time flight…

Verification and Validation of a Three-Dimensional Generalized Composite Material Model

NASA Technical Reports Server (NTRS)

Hoffarth, Canio; Harrington, Joseph; Subramaniam, D. Rajan; Goldberg, Robert K.; Carney, Kelly S.; DuBois, Paul; Blankenhorn, Gunther

2014-01-01

A general purpose orthotropic elasto-plastic computational constitutive material model has been developed to improve predictions of the response of composites subjected to high velocity impact. The three-dimensional orthotropic elasto-plastic composite material model is being implemented initially for solid elements in LS-DYNA as MAT213. In order to accurately represent the response of a composite, experimental stress-strain curves are utilized as input, allowing for a more general material model that can be used on a variety of composite applications. The theoretical details are discussed in a companion paper. This paper documents the implementation, verification and qualitative validation of the material model using the T800- F3900 fiber/resin composite material.

Verification and Validation of a Three-Dimensional Generalized Composite Material Model

NASA Technical Reports Server (NTRS)

Hoffarth, Canio; Harrington, Joseph; Rajan, Subramaniam D.; Goldberg, Robert K.; Carney, Kelly S.; DuBois, Paul; Blankenhorn, Gunther

2015-01-01

A general purpose orthotropic elasto-plastic computational constitutive material model has been developed to improve predictions of the response of composites subjected to high velocity impact. The three-dimensional orthotropic elasto-plastic composite material model is being implemented initially for solid elements in LS-DYNA as MAT213. In order to accurately represent the response of a composite, experimental stress-strain curves are utilized as input, allowing for a more general material model that can be used on a variety of composite applications. The theoretical details are discussed in a companion paper. This paper documents the implementation, verification and qualitative validation of the material model using the T800-F3900 fiber/resin composite material

Automatic specification of reliability models for fault-tolerant computers

NASA Technical Reports Server (NTRS)

Liceaga, Carlos A.; Siewiorek, Daniel P.

1993-01-01

The calculation of reliability measures using Markov models is required for life-critical processor-memory-switch structures that have standby redundancy or that are subject to transient or intermittent faults or repair. The task of specifying these models is tedious and prone to human error because of the large number of states and transitions required in any reasonable system. Therefore, model specification is a major analysis bottleneck, and model verification is a major validation problem. The general unfamiliarity of computer architects with Markov modeling techniques further increases the necessity of automating the model specification. Automation requires a general system description language (SDL). For practicality, this SDL should also provide a high level of abstraction and be easy to learn and use. The first attempt to define and implement an SDL with those characteristics is presented. A program named Automated Reliability Modeling (ARM) was constructed as a research vehicle. The ARM program uses a graphical interface as its SDL, and it outputs a Markov reliability model specification formulated for direct use by programs that generate and evaluate the model.

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

van Rij, Jennifer A; Yu, Yi-Hsiang; Guo, Yi

This study explores and verifies the generalized body-modes method for evaluating the structural loads on a wave energy converter (WEC). Historically, WEC design methodologies have focused primarily on accurately evaluating hydrodynamic loads, while methodologies for evaluating structural loads have yet to be fully considered and incorporated into the WEC design process. As wave energy technologies continue to advance, however, it has become increasingly evident that an accurate evaluation of the structural loads will enable an optimized structural design, as well as the potential utilization of composites and flexible materials, and hence reduce WEC costs. Although there are many computational fluidmore » dynamics, structural analyses and fluid-structure-interaction (FSI) codes available, the application of these codes is typically too computationally intensive to be practical in the early stages of the WEC design process. The generalized body-modes method, however, is a reduced order, linearized, frequency-domain FSI approach, performed in conjunction with the linear hydrodynamic analysis, with computation times that could realistically be incorporated into the WEC design process. The objective of this study is to verify the generalized body-modes approach in comparison to high-fidelity FSI simulations to accurately predict structural deflections and stress loads in a WEC. Two verification cases are considered, a free-floating barge and a fixed-bottom column. Details for both the generalized body-modes models and FSI models are first provided. Results for each of the models are then compared and discussed. Finally, based on the verification results obtained, future plans for incorporating the generalized body-modes method into the WEC simulation tool, WEC-Sim, and the overall WEC design process are discussed.« less

Computational Modeling For The Transitional Flow Over A Multi-Element Airfoil

NASA Technical Reports Server (NTRS)

Liou, William W.; Liu, Feng-Jun; Rumsey, Chris L. (Technical Monitor)

2000-01-01

The transitional flow over a multi-element airfoil in a landing configuration are computed using a two equation transition model. The transition model is predictive in the sense that the transition onset is a result of the calculation and no prior knowledge of the transition location is required. The computations were performed using the INS2D) Navier-Stokes code. Overset grids are used for the three-element airfoil. The airfoil operating conditions are varied for a range of angle of attack and for two different Reynolds numbers of 5 million and 9 million. The computed results are compared with experimental data for the surface pressure, skin friction, transition onset location, and velocity magnitude. In general, the comparison shows a good agreement with the experimental data.

Multi-scaling modelling in financial markets

NASA Astrophysics Data System (ADS)

Liu, Ruipeng; Aste, Tomaso; Di Matteo, T.

2007-12-01

In the recent years, a new wave of interest spurred the involvement of complexity in finance which might provide a guideline to understand the mechanism of financial markets, and researchers with different backgrounds have made increasing contributions introducing new techniques and methodologies. In this paper, Markov-switching multifractal models (MSM) are briefly reviewed and the multi-scaling properties of different financial data are analyzed by computing the scaling exponents by means of the generalized Hurst exponent H(q). In particular we have considered H(q) for price data, absolute returns and squared returns of different empirical financial time series. We have computed H(q) for the simulated data based on the MSM models with Binomial and Lognormal distributions of the volatility components. The results demonstrate the capacity of the multifractal (MF) models to capture the stylized facts in finance, and the ability of the generalized Hurst exponents approach to detect the scaling feature of financial time series.

A survey of upwind methods for flows with equilibrium and non-equilibrium chemistry and thermodynamics

NASA Technical Reports Server (NTRS)

Grossman, B.; Garrett, J.; Cinnella, P.

1989-01-01

Several versions of flux-vector split and flux-difference split algorithms were compared with regard to general applicability and complexity. Test computations were performed using curve-fit equilibrium air chemistry for an M = 5 high-temperature inviscid flow over a wedge, and an M = 24.5 inviscid flow over a blunt cylinder for test computations; for these cases, little difference in accuracy was found among the versions of the same flux-split algorithm. For flows with nonequilibrium chemistry, the effects of the thermodynamic model on the development of flux-vector split and flux-difference split algorithms were investigated using an equilibrium model, a general nonequilibrium model, and a simplified model based on vibrational relaxation. Several numerical examples are presented, including nonequilibrium air chemistry in a high-temperature shock tube and nonequilibrium hydrogen-air chemistry in a supersonic diffuser.

The natural mathematics of behavior analysis.

PubMed

Li, Don; Hautus, Michael J; Elliffe, Douglas

2018-04-19

Models that generate event records have very general scope regarding the dimensions of the target behavior that we measure. From a set of predicted event records, we can generate predictions for any dependent variable that we could compute from the event records of our subjects. In this sense, models that generate event records permit us a freely multivariate analysis. To explore this proposition, we conducted a multivariate examination of Catania's Operant Reserve on single VI schedules in transition using a Markov Chain Monte Carlo scheme for Approximate Bayesian Computation. Although we found systematic deviations between our implementation of Catania's Operant Reserve and our observed data (e.g., mismatches in the shape of the interresponse time distributions), the general approach that we have demonstrated represents an avenue for modelling behavior that transcends the typical constraints of algebraic models. © 2018 Society for the Experimental Analysis of Behavior.

1D-3D hybrid modeling-from multi-compartment models to full resolution models in space and time.

PubMed

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator-which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics.

Software reliability models for fault-tolerant avionics computers and related topics

NASA Technical Reports Server (NTRS)

Miller, Douglas R.

1987-01-01

Software reliability research is briefly described. General research topics are reliability growth models, quality of software reliability prediction, the complete monotonicity property of reliability growth, conceptual modelling of software failure behavior, assurance of ultrahigh reliability, and analysis techniques for fault-tolerant systems.

Computing Thermal Effects of Cavitation in Cryogenic Liquids

NASA Technical Reports Server (NTRS)

Hosangadi, Ashvin; Ahuja, Vineet; Dash, Sanford M.

2005-01-01

A computer program implements a numerical model of thermal effects of cavitation in cryogenic fluids. The model and program were developed for use in designing and predicting the performances of turbopumps for cryogenic fluids. Prior numerical models used for this purpose do not account for either the variability of properties of cryogenic fluids or the thermal effects (especially, evaporative cooling) involved in cavitation. It is important to account for both because in a cryogenic fluid, the thermal effects of cavitation are substantial, and the cavitation characteristics are altered by coupling between the variable fluid properties and the phase changes involved in cavitation. The present model accounts for both thermal effects and variability of properties by incorporating a generalized representation of the properties of cryogenic fluids into a generalized compressible-fluid formulation for a cavitating pump. The model has been extensively validated for liquid nitrogen and liquid hydrogen. Using the available data on the properties of these fluids, the model has been shown to predict accurate temperature-depression values.

Generalized wall function and its application to compressible turbulent boundary layer over a flat plate

NASA Astrophysics Data System (ADS)

Liu, J.; Wu, S. P.

2017-04-01

Wall function boundary conditions including the effects of compressibility and heat transfer are improved for compressible turbulent boundary flows. Generalized wall function formulation at zero-pressure gradient is proposed based on coupled velocity and temperature profiles in the entire near-wall region. The parameters in the generalized wall function are well revised. The proposed boundary conditions are integrated into Navier-Stokes computational fluid dynamics code that includes the shear stress transport turbulence model. Numerical results are presented for a compressible boundary layer over a flat plate at zero-pressure gradient. Compared with experimental data, the computational results show that the generalized wall function reduces the first grid spacing in the directed normal to the wall and proves the feasibility and effectivity of the generalized wall function method.

Certification in Structural Health Monitoring Systems

DTIC Science & Technology

2011-09-01

validation [3,8]. This may be accomplished by computing the sum of squares of pure error ( SSPE ) and its associated squared correlation [3,8]. To compute...these values, a cross- validation sample must be established. In general, if the SSPE is high, the model does not predict well on independent data...plethora of cross- validation methods, some of which are more useful for certain models than others [3,8]. When possible, a disclosure of the SSPE

Control Theory and Statistical Generalizations.

ERIC Educational Resources Information Center

Powers, William T.

1990-01-01

Contrasts modeling methods in control theory to the methods of statistical generalizations in empirical studies of human or animal behavior. Presents a computer simulation that predicts behavior based on variables (effort and rewards) determined by the invariable (desired reward). Argues that control theory methods better reflect relationships to…

The general deterrence of driving while intoxicated. Volume 1, System analysis and computer-based simulation

DOT National Transportation Integrated Search

1978-01-01

A system analysis was completed of the general deterrence of driving while intoxicated (DWI). Elements which influence DWI decisions were identified and interrelated in a system model; then, potential countermeasures which might be employed in DWI ge...

Reconciliation of the cloud computing model with US federal electronic health record regulations

PubMed Central

2011-01-01

Cloud computing refers to subscription-based, fee-for-service utilization of computer hardware and software over the Internet. The model is gaining acceptance for business information technology (IT) applications because it allows capacity and functionality to increase on the fly without major investment in infrastructure, personnel or licensing fees. Large IT investments can be converted to a series of smaller operating expenses. Cloud architectures could potentially be superior to traditional electronic health record (EHR) designs in terms of economy, efficiency and utility. A central issue for EHR developers in the US is that these systems are constrained by federal regulatory legislation and oversight. These laws focus on security and privacy, which are well-recognized challenges for cloud computing systems in general. EHRs built with the cloud computing model can achieve acceptable privacy and security through business associate contracts with cloud providers that specify compliance requirements, performance metrics and liability sharing. PMID:21727204

Reconciliation of the cloud computing model with US federal electronic health record regulations.

PubMed

Schweitzer, Eugene J

2012-01-01

Cloud computing refers to subscription-based, fee-for-service utilization of computer hardware and software over the Internet. The model is gaining acceptance for business information technology (IT) applications because it allows capacity and functionality to increase on the fly without major investment in infrastructure, personnel or licensing fees. Large IT investments can be converted to a series of smaller operating expenses. Cloud architectures could potentially be superior to traditional electronic health record (EHR) designs in terms of economy, efficiency and utility. A central issue for EHR developers in the US is that these systems are constrained by federal regulatory legislation and oversight. These laws focus on security and privacy, which are well-recognized challenges for cloud computing systems in general. EHRs built with the cloud computing model can achieve acceptable privacy and security through business associate contracts with cloud providers that specify compliance requirements, performance metrics and liability sharing.

NASA Trapezoidal Wing Computations Including Transition and Advanced Turbulence Modeling

NASA Technical Reports Server (NTRS)

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

2012-01-01

Flow about the NASA Trapezoidal Wing is computed with several turbulence models by using grids from the first High Lift Prediction Workshop in an effort to advance understanding of computational fluid dynamics modeling for this type of flowfield. Transition is accounted for in many of the computations. In particular, a recently-developed 4-equation transition model is utilized and works well overall. Accounting for transition tends to increase lift and decrease moment, which improves the agreement with experiment. Upper surface flap separation is reduced, and agreement with experimental surface pressures and velocity profiles is improved. The predicted shape of wakes from upstream elements is strongly influenced by grid resolution in regions above the main and flap elements. Turbulence model enhancements to account for rotation and curvature have the general effect of increasing lift and improving the resolution of the wing tip vortex as it convects downstream. However, none of the models improve the prediction of surface pressures near the wing tip, where more grid resolution is needed.

A generalized methodology for identification of threshold for HRU delineation in SWAT model

NASA Astrophysics Data System (ADS)

M, J.; Sudheer, K.; Chaubey, I.; Raj, C.

2016-12-01

The distributed hydrological model, Soil and Water Assessment Tool (SWAT) is a comprehensive hydrologic model widely used for making various decisions. The simulation accuracy of the distributed hydrological model differs due to the mechanism involved in the subdivision of the watershed. Soil and Water Assessment Tool (SWAT) considers sub-dividing the watershed and the sub-basins into small computing units known as 'hydrologic response units (HRU). The delineation of HRU is done based on unique combinations of land use, soil types, and slope within the sub-watersheds, which are not spatially defined. The computations in SWAT are done at HRU level and are then aggregated up to the sub-basin outlet, which is routed through the stream system. Generally, the HRUs are delineated by considering a threshold percentage of land use, soil and slope are to be given by the modeler to decrease the computation time of the model. The thresholds constrain the minimum area for constructing an HRU. In the current HRU delineation practice in SWAT, the land use, soil and slope of the watershed within a sub-basin, which is less than the predefined threshold, will be surpassed by the dominating land use, soil and slope, and introduce some level of ambiguity in the process simulations in terms of inappropriate representation of the area. But the loss of information due to variation in the threshold values depends highly on the purpose of the study. Therefore this research studies the effects of threshold values of HRU delineation on the hydrological modeling of SWAT on sediment simulations and suggests guidelines for selecting the appropriate threshold values considering the sediment simulation accuracy. The preliminary study was done on Illinois watershed by assigning different thresholds for land use and soil. A general methodology was proposed for identifying an appropriate threshold for HRU delineation in SWAT model that considered computational time and accuracy of the simulation. The methodology can be adopted for identifying an appropriate threshold for SWAT model simulation in any watershed with a single simulation of the model with a zero-zero threshold.

1D-3D hybrid modeling—from multi-compartment models to full resolution models in space and time

PubMed Central

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M.; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator—which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics. PMID:25120463

A Simple and Resource-efficient Setup for the Computer-aided Drug Design Laboratory.

PubMed

Moretti, Loris; Sartori, Luca

2016-10-01

Undertaking modelling investigations for Computer-Aided Drug Design (CADD) requires a proper environment. In principle, this could be done on a single computer, but the reality of a drug discovery program requires robustness and high-throughput computing (HTC) to efficiently support the research. Therefore, a more capable alternative is needed but its implementation has no widespread solution. Here, the realization of such a computing facility is discussed, from general layout to technical details all aspects are covered. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computation of high Reynolds number internal/external flows

NASA Technical Reports Server (NTRS)

Cline, M. C.; Wilmoth, R. G.

1981-01-01

A general, user oriented computer program, called VNAP2, has been developed to calculate high Reynolds number, internal/external flows. VNAP2 solves the two-dimensional, time-dependent Navier-Stokes equations. The turbulence is modeled with either a mixing-length, a one transport equation, or a two transport equation model. Interior grid points are computed using the explicit MacCormack scheme with special procedures to speed up the calculation in the fine grid. All boundary conditions are calculated using a reference plane characteristic scheme with the viscous terms treated as source terms. Several internal, and internal/external flow calculations are presented.

Computation of high Reynolds number internal/external flows

NASA Technical Reports Server (NTRS)

Cline, M. C.; Wilmoth, R. G.

1981-01-01

A general, user oriented computer program, called VNAP2, was developed to calculate high Reynolds number, internal/ external flows. The VNAP2 program solves the two dimensional, time dependent Navier-Stokes equations. The turbulence is modeled with either a mixing-length, a one transport equation, or a two transport equation model. Interior grid points are computed using the explicit MacCormack Scheme with special procedures to speed up the calculation in the fine grid. All boundary conditions are calculated using a reference plane characteristic scheme with the viscous terms treated as source terms. Several internal, external, and internal/external flow calculations are presented.

Computation of high Reynolds number internal/external flows

NASA Technical Reports Server (NTRS)

Cline, M. C.; Wilmoth, R. G.

1981-01-01

A general, user oriented computer program, called VNAF2, developed to calculate high Reynolds number internal/external flows is described. The program solves the two dimensional, time dependent Navier-Stokes equations. Turbulence is modeled with either a mixing length, a one transport equation, or a two transport equation model. Interior grid points are computed using the explicit MacCormack scheme with special procedures to speed up the calculation in the fine grid. All boundary conditions are calculated using a reference plane characteristic scheme with the viscous terms treated as source terms. Several internal, external, and internal/external flow calculations are presented.

A tool for modeling concurrent real-time computation

NASA Technical Reports Server (NTRS)

Sharma, D. D.; Huang, Shie-Rei; Bhatt, Rahul; Sridharan, N. S.

1990-01-01

Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.

Generalized pipeline for preview and rendering of synthetic holograms

NASA Astrophysics Data System (ADS)

Pappu, Ravikanth; Sparrell, Carlton J.; Underkoffler, John S.; Kropp, Adam B.; Chen, Benjie; Plesniak, Wendy J.

1997-04-01

We describe a general pipeline for the computation and display of either fully-computed holograms or holographic stereograms using the same 3D database. A rendering previewer on a Silicon Graphics Onyx allows a user to specify viewing geometry, database transformations, and scene lighting. The previewer then generates one of two descriptions of the object--a series of perspective views or a polygonal model--which is then used by a fringe rendering engine to compute fringes specific to hologram type. The images are viewed on the second generation MIT Holographic Video System. This allows a viewer to compare holographic stereograms with fully-computed holograms originating from the same database and comes closer to the goal of a single pipeline being able to display the same data in different formats.

Overview of Risk Mitigation for Safety-Critical Computer-Based Systems

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2015-01-01

This report presents a high-level overview of a general strategy to mitigate the risks from threats to safety-critical computer-based systems. In this context, a safety threat is a process or phenomenon that can cause operational safety hazards in the form of computational system failures. This report is intended to provide insight into the safety-risk mitigation problem and the characteristics of potential solutions. The limitations of the general risk mitigation strategy are discussed and some options to overcome these limitations are provided. This work is part of an ongoing effort to enable well-founded assurance of safety-related properties of complex safety-critical computer-based aircraft systems by developing an effective capability to model and reason about the safety implications of system requirements and design.

A new hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer

NASA Technical Reports Server (NTRS)

Tamma, Kumar K.; Railkar, Sudhir B.

1988-01-01

This paper describes new and recent advances in the development of a hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer problems. The transfinite element methodology, while retaining the modeling versatility of contemporary finite element formulations, is based on application of transform techniques in conjunction with classical Galerkin schemes and is a hybrid approach. The purpose of this paper is to provide a viable hybrid computational methodology for applicability to general transient thermal analysis. Highlights and features of the methodology are described and developed via generalized formulations and applications to several test problems. The proposed transfinite element methodology successfully provides a viable computational approach and numerical test problems validate the proposed developments for conduction/convection/radiation thermal analysis.

HexSim - A general purpose framework for spatially-explicit, individual-based modeling

EPA Science Inventory

HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications. This talk will focus on a subset of those ap...

Estimating wildfire behavior and effects

Treesearch

Frank A. Albini

1976-01-01

This paper presents a brief survey of the research literature on wildfire behavior and effects and assembles formulae and graphical computation aids based on selected theoretical and empirical models. The uses of mathematical fire behavior models are discussed, and the general capabilities and limitations of currently available models are outlined.

DNA Microarray-based Ecotoxicological Biomarker Discovery in a Small Fish Model Species

EPA Science Inventory

This paper addresses several issues critical to use of zebrafish oligonucleotide microarrays for computational toxicology research on endocrine disrupting chemicals using small fish models, and more generally, the use of microarrays in aquatic toxicology.

Device 2E6 (ACMS) Air Combat Maneuvering Simulator Instructor Console Review.

DTIC Science & Technology

1983-12-01

While the device provides some new features which support training such as a debrief facility and a computer based instructor training module, the...Equipment Center, Orlando, FL (in printing). - 11 - -~.-. -- ~ --- NAVTRAEQUI PCEN 82-M-0767- 1 PROJECTORS DOE COMPUTER SYSTEMS Figure 1. General...arrangement (2E6) - 12 7 NAVTRAEQUIPCEN 82-M--0767-1 d. instructor stations, e. computer systems, ftarget model subsystem, g. debrief subsystem, h

A generalized threshold model for computing bed load grain size distribution

NASA Astrophysics Data System (ADS)

Recking, Alain

2016-12-01

For morphodynamic studies, it is important to compute not only the transported volumes of bed load, but also the size of the transported material. A few bed load equations compute fractional transport (i.e., both the volume and grain size distribution), but many equations compute only the bulk transport (a volume) with no consideration of the transported grain sizes. To fill this gap, a method is proposed to compute the bed load grain size distribution separately to the bed load flux. The method is called the Generalized Threshold Model (GTM), because it extends the flow competence method for threshold of motion of the largest transported grain size to the full bed surface grain size distribution. This was achieved by replacing dimensional diameters with their size indices in the standard hiding function, which offers a useful framework for computation, carried out for each indices considered in the range [1, 100]. New functions are also proposed to account for partial transport. The method is very simple to implement and is sufficiently flexible to be tested in many environments. In addition to being a good complement to standard bulk bed load equations, it could also serve as a framework to assist in analyzing the physics of bed load transport in future research.

Computational Methods for Structural Mechanics and Dynamics, part 1

NASA Technical Reports Server (NTRS)

Stroud, W. Jefferson (Editor); Housner, Jerrold M. (Editor); Tanner, John A. (Editor); Hayduk, Robert J. (Editor)

1989-01-01

The structural analysis methods research has several goals. One goal is to develop analysis methods that are general. This goal of generality leads naturally to finite-element methods, but the research will also include other structural analysis methods. Another goal is that the methods be amenable to error analysis; that is, given a physical problem and a mathematical model of that problem, an analyst would like to know the probable error in predicting a given response quantity. The ultimate objective is to specify the error tolerances and to use automated logic to adjust the mathematical model or solution strategy to obtain that accuracy. A third goal is to develop structural analysis methods that can exploit parallel processing computers. The structural analysis methods research will focus initially on three types of problems: local/global nonlinear stress analysis, nonlinear transient dynamics, and tire modeling.

The European computer model for optronic system performance prediction (ECOMOS)

NASA Astrophysics Data System (ADS)

Repasi, Endre; Bijl, Piet; Labarre, Luc; Wittenstein, Wolfgang; Bürsing, Helge

2017-05-01

ECOMOS is a multinational effort within the framework of an EDA Project Arrangement. Its aim is to provide a generally accepted and harmonized European computer model for computing nominal Target Acquisition (TA) ranges of optronic imagers operating in the Visible or thermal Infrared (IR). The project involves close co-operation of defence and security industry and public research institutes from France, Germany, Italy, The Netherlands and Sweden. ECOMOS uses and combines well-accepted existing European tools to build up a strong competitive position. This includes two TA models: the analytical TRM4 model and the image-based TOD model. In addition, it uses the atmosphere model MATISSE. In this paper, the central idea of ECOMOS is exposed. The overall software structure and the underlying models are shown and elucidated. The status of the project development is given as well as a short outlook on validation tests and the future potential of simulation for sensor assessment.

Mind the Noise When Identifying Computational Models of Cognition from Brain Activity.

PubMed

Kolossa, Antonio; Kopp, Bruno

2016-01-01

The aim of this study was to analyze how measurement error affects the validity of modeling studies in computational neuroscience. A synthetic validity test was created using simulated P300 event-related potentials as an example. The model space comprised four computational models of single-trial P300 amplitude fluctuations which differed in terms of complexity and dependency. The single-trial fluctuation of simulated P300 amplitudes was computed on the basis of one of the models, at various levels of measurement error and at various numbers of data points. Bayesian model selection was performed based on exceedance probabilities. At very low numbers of data points, the least complex model generally outperformed the data-generating model. Invalid model identification also occurred at low levels of data quality and under low numbers of data points if the winning model's predictors were closely correlated with the predictors from the data-generating model. Given sufficient data quality and numbers of data points, the data-generating model could be correctly identified, even against models which were very similar to the data-generating model. Thus, a number of variables affects the validity of computational modeling studies, and data quality and numbers of data points are among the main factors relevant to the issue. Further, the nature of the model space (i.e., model complexity, model dependency) should not be neglected. This study provided quantitative results which show the importance of ensuring the validity of computational modeling via adequately prepared studies. The accomplishment of synthetic validity tests is recommended for future applications. Beyond that, we propose to render the demonstration of sufficient validity via adequate simulations mandatory to computational modeling studies.

Numerical modeling tools for chemical vapor deposition

NASA Technical Reports Server (NTRS)

Jasinski, Thomas J.; Childs, Edward P.

1992-01-01

Development of general numerical simulation tools for chemical vapor deposition (CVD) was the objective of this study. Physical models of important CVD phenomena were developed and implemented into the commercial computational fluid dynamics software FLUENT. The resulting software can address general geometries as well as the most important phenomena occurring with CVD reactors: fluid flow patterns, temperature and chemical species distribution, gas phase and surface deposition. The physical models are documented which are available and examples are provided of CVD simulation capabilities.

Evaluating the Theoretic Adequacy and Applied Potential of Computational Models of the Spacing Effect.

PubMed

Walsh, Matthew M; Gluck, Kevin A; Gunzelmann, Glenn; Jastrzembski, Tiffany; Krusmark, Michael

2018-06-01

The spacing effect is among the most widely replicated empirical phenomena in the learning sciences, and its relevance to education and training is readily apparent. Yet successful applications of spacing effect research to education and training is rare. Computational modeling can provide the crucial link between a century of accumulated experimental data on the spacing effect and the emerging interest in using that research to enable adaptive instruction. In this paper, we review relevant literature and identify 10 criteria for rigorously evaluating computational models of the spacing effect. Five relate to evaluating the theoretic adequacy of a model, and five relate to evaluating its application potential. We use these criteria to evaluate a novel computational model of the spacing effect called the Predictive Performance Equation (PPE). Predictive Performance Equation combines elements of earlier models of learning and memory including the General Performance Equation, Adaptive Control of Thought-Rational, and the New Theory of Disuse, giving rise to a novel computational account of the spacing effect that performs favorably across the complete sets of theoretic and applied criteria. We implemented two other previously published computational models of the spacing effect and compare them to PPE using the theoretic and applied criteria as guides. Copyright © 2018 Cognitive Science Society, Inc.

Parallel Ray Tracing Using the Message Passing Interface

DTIC Science & Technology

2007-09-01

software is available for lens design and for general optical systems modeling. It tends to be designed to run on a single processor and can be very...Cameron, Senior Member, IEEE Abstract—Ray-tracing software is available for lens design and for general optical systems modeling. It tends to be designed to...National Aeronautics and Space Administration (NASA), optical ray tracing, parallel computing, parallel pro- cessing, prime numbers, ray tracing

Characterization of Stationary Distributions of Reflected Diffusions

DTIC Science & Technology

2014-01-01

Reiman , M. I. (2003). Fluid and heavy traffic limits for a generalized processor sharing model. Ann. Appl. Probab., 13, 100-139. [37] Ramanan, K. and... Reiman , M. I. (2008). The heavy traffic limit of an unbalanced generalized processor sharing model. Ann. Appl. Probab., 18, 22-58. [38] Reed, J. and...Control and Computing. [39] Reiman , M. I. and Williams, R. J. (1988). A boundary property of semimartingale reflecting Brownian motions. Probab. Theor

Nucleation and growth in one dimension. I. The generalized Kolmogorov-Johnson-Mehl-Avrami model

NASA Astrophysics Data System (ADS)

Jun, Suckjoon; Zhang, Haiyang; Bechhoefer, John

2005-01-01

Motivated by a recent application of the Kolmogorov-Johnson-Mehl-Avrami (KJMA) model to the study of DNA replication, we consider the one-dimensional (1D) version of this model. We generalize previous work to the case where the nucleation rate is an arbitrary function I(t) and obtain analytical results for the time-dependent distributions of various quantities (such as the island distribution). We also present improved computer simulation algorithms to study the 1D KJMA model. The analytical results and simulations are in excellent agreement.

Computation of Reacting Flows in Combustion Processes

NASA Technical Reports Server (NTRS)

Keith, Theo G., Jr.; Chen, Kuo-Huey

1997-01-01

The main objective of this research was to develop an efficient three-dimensional computer code for chemically reacting flows. The main computer code developed is ALLSPD-3D. The ALLSPD-3D computer program is developed for the calculation of three-dimensional, chemically reacting flows with sprays. The ALL-SPD code employs a coupled, strongly implicit solution procedure for turbulent spray combustion flows. A stochastic droplet model and an efficient method for treatment of the spray source terms in the gas-phase equations are used to calculate the evaporating liquid sprays. The chemistry treatment in the code is general enough that an arbitrary number of reaction and species can be defined by the users. Also, it is written in generalized curvilinear coordinates with both multi-block and flexible internal blockage capabilities to handle complex geometries. In addition, for general industrial combustion applications, the code provides both dilution and transpiration cooling capabilities. The ALLSPD algorithm, which employs the preconditioning and eigenvalue rescaling techniques, is capable of providing efficient solution for flows with a wide range of Mach numbers. Although written for three-dimensional flows in general, the code can be used for two-dimensional and axisymmetric flow computations as well. The code is written in such a way that it can be run in various computer platforms (supercomputers, workstations and parallel processors) and the GUI (Graphical User Interface) should provide a user-friendly tool in setting up and running the code.

Los Alamos National Laboratory Economic Analysis Capability Overview

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

Boero, Riccardo; Edwards, Brian Keith; Pasqualini, Donatella

Los Alamos National Laboratory has developed two types of models to compute the economic impact of infrastructure disruptions. FastEcon is a fast running model that estimates first-­order economic impacts of large scale events such as hurricanes and floods and can be used to identify the amount of economic activity that occurs in a specific area. LANL’s Computable General Equilibrium (CGE) model estimates more comprehensive static and dynamic economic impacts of a broader array of events and captures the interactions between sectors and industries when estimating economic impacts.

Modeling driver behavior in a cognitive architecture.

PubMed

Salvucci, Dario D

2006-01-01

This paper explores the development of a rigorous computational model of driver behavior in a cognitive architecture--a computational framework with underlying psychological theories that incorporate basic properties and limitations of the human system. Computational modeling has emerged as a powerful tool for studying the complex task of driving, allowing researchers to simulate driver behavior and explore the parameters and constraints of this behavior. An integrated driver model developed in the ACT-R (Adaptive Control of Thought-Rational) cognitive architecture is described that focuses on the component processes of control, monitoring, and decision making in a multilane highway environment. This model accounts for the steering profiles, lateral position profiles, and gaze distributions of human drivers during lane keeping, curve negotiation, and lane changing. The model demonstrates how cognitive architectures facilitate understanding of driver behavior in the context of general human abilities and constraints and how the driving domain benefits cognitive architectures by pushing model development toward more complex, realistic tasks. The model can also serve as a core computational engine for practical applications that predict and recognize driver behavior and distraction.

Combining Experiments and Simulations Using the Maximum Entropy Principle

PubMed Central

Boomsma, Wouter; Ferkinghoff-Borg, Jesper; Lindorff-Larsen, Kresten

2014-01-01

A key component of computational biology is to compare the results of computer modelling with experimental measurements. Despite substantial progress in the models and algorithms used in many areas of computational biology, such comparisons sometimes reveal that the computations are not in quantitative agreement with experimental data. The principle of maximum entropy is a general procedure for constructing probability distributions in the light of new data, making it a natural tool in cases when an initial model provides results that are at odds with experiments. The number of maximum entropy applications in our field has grown steadily in recent years, in areas as diverse as sequence analysis, structural modelling, and neurobiology. In this Perspectives article, we give a broad introduction to the method, in an attempt to encourage its further adoption. The general procedure is explained in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results that are at not in complete and quantitative accordance with experiments. A common solution to this problem is to explicitly ensure agreement between the two by perturbing the potential energy function towards the experimental data. So far, a general consensus for how such perturbations should be implemented has been lacking. Three very recent papers have explored this problem using the maximum entropy approach, providing both new theoretical and practical insights to the problem. We highlight each of these contributions in turn and conclude with a discussion on remaining challenges. PMID:24586124

Evolutionary inference via the Poisson Indel Process.

PubMed

Bouchard-Côté, Alexandre; Jordan, Michael I

2013-01-22

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.

Evolutionary inference via the Poisson Indel Process

PubMed Central

Bouchard-Côté, Alexandre; Jordan, Michael I.

2013-01-01

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114–124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments. PMID:23275296

A Parallel Sliding Region Algorithm to Make Agent-Based Modeling Possible for a Large-Scale Simulation: Modeling Hepatitis C Epidemics in Canada.

PubMed

Wong, William W L; Feng, Zeny Z; Thein, Hla-Hla

2016-11-01

Agent-based models (ABMs) are computer simulation models that define interactions among agents and simulate emergent behaviors that arise from the ensemble of local decisions. ABMs have been increasingly used to examine trends in infectious disease epidemiology. However, the main limitation of ABMs is the high computational cost for a large-scale simulation. To improve the computational efficiency for large-scale ABM simulations, we built a parallelizable sliding region algorithm (SRA) for ABM and compared it to a nonparallelizable ABM. We developed a complex agent network and performed two simulations to model hepatitis C epidemics based on the real demographic data from Saskatchewan, Canada. The first simulation used the SRA that processed on each postal code subregion subsequently. The second simulation processed the entire population simultaneously. It was concluded that the parallelizable SRA showed computational time saving with comparable results in a province-wide simulation. Using the same method, SRA can be generalized for performing a country-wide simulation. Thus, this parallel algorithm enables the possibility of using ABM for large-scale simulation with limited computational resources.

Time Advice and Learning Questions in Computer Simulations

ERIC Educational Resources Information Center

Rey, Gunter Daniel

2011-01-01

Students (N = 101) used an introductory text and a computer simulation to learn fundamental concepts about statistical analyses (e.g., analysis of variance, regression analysis and General Linear Model). Each learner was randomly assigned to one cell of a 2 (with or without time advice) x 3 (with learning questions and corrective feedback, with…

Using Intelligent Tutoring Design Principles To Integrate Cognitive Theory into Computer-Based Instruction.

ERIC Educational Resources Information Center

Orey, Michael A.; Nelson, Wayne A.

Arguing that the evolution of intelligent tutoring systems better reflects the recent theoretical developments of cognitive science than traditional computer-based instruction (CBI), this paper describes a general model for an intelligent tutoring system and suggests ways to improve CBI using design principles derived from research in cognitive…

Computational Nonlinear Morphology with Emphasis on Semitic Languages. Studies in Natural Language Processing.

ERIC Educational Resources Information Center

Kiraz, George Anton

This book presents a tractable computational model that can cope with complex morphological operations, especially in Semitic languages, and less complex morphological systems present in Western languages. It outlines a new generalized regular rewrite rule system that uses multiple finite-state automata to cater to root-and-pattern morphology,…

Environmental Factors Affecting Computer Assisted Language Learning Success: A Complex Dynamic Systems Conceptual Model

ERIC Educational Resources Information Center

Marek, Michael W.; Wu, Wen-Chi Vivian

2014-01-01

This conceptual, interdisciplinary inquiry explores Complex Dynamic Systems as the concept relates to the internal and external environmental factors affecting computer assisted language learning (CALL). Based on the results obtained by de Rosnay ["World Futures: The Journal of General Evolution", 67(4/5), 304-315 (2011)], who observed…

Combining-Ability Determinations for Incomplete Mating Designs

Treesearch

E.B. Snyder

1975-01-01

It is shown how general combining ability values (GCA's) from cross-, open-, and self-pollinated progeny can be derived in a single analysis. Breeding values are employed to facilitate explaining genetic models of the expected family means and the derivation of the GCA's. A FORTRAN computer program also includes computation of specific combining ability...

Idealness and similarity in goal-derived categories: a computational examination.

PubMed

Voorspoels, Wouter; Storms, Gert; Vanpaemel, Wolf

2013-02-01

The finding that the typicality gradient in goal-derived categories is mainly driven by ideals rather than by exemplar similarity has stood uncontested for nearly three decades. Due to the rather rigid earlier implementations of similarity, a key question has remained--that is, whether a more flexible approach to similarity would alter the conclusions. In the present study, we evaluated whether a similarity-based approach that allows for dimensional weighting could account for findings in goal-derived categories. To this end, we compared a computational model of exemplar similarity (the generalized context model; Nosofsky, Journal of Experimental Psychology. General 115:39-57, 1986) and a computational model of ideal representation (the ideal-dimension model; Voorspoels, Vanpaemel, & Storms, Psychonomic Bulletin & Review 18:1006-114, 2011) in their accounts of exemplar typicality in ten goal-derived categories. In terms of both goodness-of-fit and generalizability, we found strong evidence for an ideal approach in nearly all categories. We conclude that focusing on a limited set of features is necessary but not sufficient to account for the observed typicality gradient. A second aspect of ideal representations--that is, that extreme rather than common, central-tendency values drive typicality--seems to be crucial.

Majorization Minimization by Coordinate Descent for Concave Penalized Generalized Linear Models

PubMed Central

Jiang, Dingfeng; Huang, Jian

2013-01-01

Recent studies have demonstrated theoretical attractiveness of a class of concave penalties in variable selection, including the smoothly clipped absolute deviation and minimax concave penalties. The computation of the concave penalized solutions in high-dimensional models, however, is a difficult task. We propose a majorization minimization by coordinate descent (MMCD) algorithm for computing the concave penalized solutions in generalized linear models. In contrast to the existing algorithms that use local quadratic or local linear approximation to the penalty function, the MMCD seeks to majorize the negative log-likelihood by a quadratic loss, but does not use any approximation to the penalty. This strategy makes it possible to avoid the computation of a scaling factor in each update of the solutions, which improves the efficiency of coordinate descent. Under certain regularity conditions, we establish theoretical convergence property of the MMCD. We implement this algorithm for a penalized logistic regression model using the SCAD and MCP penalties. Simulation studies and a data example demonstrate that the MMCD works sufficiently fast for the penalized logistic regression in high-dimensional settings where the number of covariates is much larger than the sample size. PMID:25309048

Towards a framework for testing general relativity with extreme-mass-ratio-inspiral observations

NASA Astrophysics Data System (ADS)

Chua, A. J. K.; Hee, S.; Handley, W. J.; Higson, E.; Moore, C. J.; Gair, J. R.; Hobson, M. P.; Lasenby, A. N.

2018-04-01

Extreme-mass-ratio-inspiral observations from future space-based gravitational-wave detectors such as LISA will enable strong-field tests of general relativity with unprecedented precision, but at prohibitive computational cost if existing statistical techniques are used. In one such test that is currently employed for LIGO black-hole binary mergers, generic deviations from relativity are represented by N deformation parameters in a generalised waveform model; the Bayesian evidence for each of its 2N combinatorial submodels is then combined into a posterior odds ratio for modified gravity over relativity in a null-hypothesis test. We adapt and apply this test to a generalised model for extreme-mass-ratio inspirals constructed on deformed black-hole spacetimes, and focus our investigation on how computational efficiency can be increased through an evidence-free method of model selection. This method is akin to the algorithm known as product-space Markov chain Monte Carlo, but uses nested sampling and improved error estimates from a rethreading technique. We perform benchmarking and robustness checks for the method, and find order-of-magnitude computational gains over regular nested sampling in the case of synthetic data generated from the null model.

Bayesian generalized least squares regression with application to log Pearson type 3 regional skew estimation

NASA Astrophysics Data System (ADS)

Reis, D. S.; Stedinger, J. R.; Martins, E. S.

2005-10-01

This paper develops a Bayesian approach to analysis of a generalized least squares (GLS) regression model for regional analyses of hydrologic data. The new approach allows computation of the posterior distributions of the parameters and the model error variance using a quasi-analytic approach. Two regional skew estimation studies illustrate the value of the Bayesian GLS approach for regional statistical analysis of a shape parameter and demonstrate that regional skew models can be relatively precise with effective record lengths in excess of 60 years. With Bayesian GLS the marginal posterior distribution of the model error variance and the corresponding mean and variance of the parameters can be computed directly, thereby providing a simple but important extension of the regional GLS regression procedures popularized by Tasker and Stedinger (1989), which is sensitive to the likely values of the model error variance when it is small relative to the sampling error in the at-site estimator.

A general-purpose framework to simulate musculoskeletal system of human body: using a motion tracking approach.

PubMed

Ehsani, Hossein; Rostami, Mostafa; Gudarzi, Mohammad

2016-02-01

Computation of muscle force patterns that produce specified movements of muscle-actuated dynamic models is an important and challenging problem. This problem is an undetermined one, and then a proper optimization is required to calculate muscle forces. The purpose of this paper is to develop a general model for calculating all muscle activation and force patterns in an arbitrary human body movement. For this aim, the equations of a multibody system forward dynamics, which is considered for skeletal system of the human body model, is derived using Lagrange-Euler formulation. Next, muscle contraction dynamics is added to this model and forward dynamics of an arbitrary musculoskeletal system is obtained. For optimization purpose, the obtained model is used in computed muscle control algorithm, and a closed-loop system for tracking desired motions is derived. Finally, a popular sport exercise, biceps curl, is simulated by using this algorithm and the validity of the obtained results is evaluated via EMG signals.

GeoFramework: A Modeling Framework for Solid Earth Geophysics

NASA Astrophysics Data System (ADS)

Gurnis, M.; Aivazis, M.; Tromp, J.; Tan, E.; Thoutireddy, P.; Liu, Q.; Choi, E.; Dicaprio, C.; Chen, M.; Simons, M.; Quenette, S.; Appelbe, B.; Aagaard, B.; Williams, C.; Lavier, L.; Moresi, L.; Law, H.

2003-12-01

As data sets in geophysics become larger and of greater relevance to other earth science disciplines, and as earth science becomes more interdisciplinary in general, modeling tools are being driven in new directions. There is now a greater need to link modeling codes to one another, link modeling codes to multiple datasets, and to make modeling software available to non modeling specialists. Coupled with rapid progress in computer hardware (including the computational speed afforded by massively parallel computers), progress in numerical algorithms, and the introduction of software frameworks, these lofty goals of merging software in geophysics are now possible. The GeoFramework project, a collaboration between computer scientists and geoscientists, is a response to these needs and opportunities. GeoFramework is based on and extends Pyre, a Python-based modeling framework, recently developed to link solid (Lagrangian) and fluid (Eulerian) models, as well as mesh generators, visualization packages, and databases, with one another for engineering applications. The utility and generality of Pyre as a general purpose framework in science is now being recognized. Besides its use in engineering and geophysics, it is also being used in particle physics and astronomy. Geology and geophysics impose their own unique requirements on software frameworks which are not generally available in existing frameworks and so there is a need for research in this area. One of the special requirements is the way Lagrangian and Eulerian codes will need to be linked in time and space within a plate tectonics context. GeoFramework has grown beyond its initial goal of linking a limited number of exiting codes together. The following codes are now being reengineered within the context of Pyre: Tecton, 3-D FE Visco-elastic code for lithospheric relaxation; CitComS, a code for spherical mantle convection; SpecFEM3D, a SEM code for global and regional seismic waves; eqsim, a FE code for dynamic earthquake rupture; SNAC, a developing 3-D coded based on the FLAC method for visco-elastoplastic deformation; SNARK, a 3-D FE-PIC method for viscoplastic deformation; and gPLATES an open source paleogeographic/plate tectonics modeling package. We will demonstrate how codes can be linked with themselves, such as a regional and global model of mantle convection and a visco-elastoplastic representation of the crust within viscous mantle flow. Finally, we will describe how http://GeoFramework.org has become a distribution site for a suite of modeling software in geophysics.

Orbital maneuvering engine feed system coupled stability investigation

NASA Technical Reports Server (NTRS)

Kahn, D. R.; Schuman, M. D.; Hunting, J. K.; Fertig, K. W.

1975-01-01

A digital computer model used to analyze and predict engine feed system coupled instabilities over a frequency range of 10 to 1000 Hz was developed and verified. The analytical approach to modeling the feed system hydrodynamics, combustion dynamics, chamber dynamics, and overall engineering model structure is described and the governing equations in each of the technical areas are presented. This is followed by a description of the generalized computer model, including formulation of the discrete subprograms and their integration into an overall engineering model structure. The operation and capabilities of the engineering model were verified by comparing the model's theoretical predictions with experimental data from an OMS-type engine with a known feed system/engine chugging history.

Automatic Dynamic Aircraft Modeler (ADAM) for the Computer Program NASTRAN

NASA Technical Reports Server (NTRS)

Griffis, H.

1985-01-01

Large general purpose finite element programs require users to develop large quantities of input data. General purpose pre-processors are used to decrease the effort required to develop structural models. Further reduction of effort can be achieved by specific application pre-processors. Automatic Dynamic Aircraft Modeler (ADAM) is one such application specific pre-processor. General purpose pre-processors use points, lines and surfaces to describe geometric shapes. Specifying that ADAM is used only for aircraft structures allows generic structural sections, wing boxes and bodies, to be pre-defined. Hence with only gross dimensions, thicknesses, material properties and pre-defined boundary conditions a complete model of an aircraft can be created.

Introducing Seismic Tomography with Computational Modeling

NASA Astrophysics Data System (ADS)

Neves, R.; Neves, M. L.; Teodoro, V.

2011-12-01

Learning seismic tomography principles and techniques involves advanced physical and computational knowledge. In depth learning of such computational skills is a difficult cognitive process that requires a strong background in physics, mathematics and computer programming. The corresponding learning environments and pedagogic methodologies should then involve sets of computational modelling activities with computer software systems which allow students the possibility to improve their mathematical or programming knowledge and simultaneously focus on the learning of seismic wave propagation and inverse theory. To reduce the level of cognitive opacity associated with mathematical or programming knowledge, several computer modelling systems have already been developed (Neves & Teodoro, 2010). Among such systems, Modellus is particularly well suited to achieve this goal because it is a domain general environment for explorative and expressive modelling with the following main advantages: 1) an easy and intuitive creation of mathematical models using just standard mathematical notation; 2) the simultaneous exploration of images, tables, graphs and object animations; 3) the attribution of mathematical properties expressed in the models to animated objects; and finally 4) the computation and display of mathematical quantities obtained from the analysis of images and graphs. Here we describe virtual simulations and educational exercises which enable students an easy grasp of the fundamental of seismic tomography. The simulations make the lecture more interactive and allow students the possibility to overcome their lack of advanced mathematical or programming knowledge and focus on the learning of seismological concepts and processes taking advantage of basic scientific computation methods and tools.

Spectral stability of unitary network models

NASA Astrophysics Data System (ADS)

Asch, Joachim; Bourget, Olivier; Joye, Alain

2015-08-01

We review various unitary network models used in quantum computing, spectral analysis or condensed matter physics and establish relationships between them. We show that symmetric one-dimensional quantum walks are universal, as are CMV matrices. We prove spectral stability and propagation properties for general asymptotically uniform models by means of unitary Mourre theory.

Finite element meshing of ANSYS (trademark) solid models

NASA Technical Reports Server (NTRS)

Kelley, F. S.

1987-01-01

A large scale, general purpose finite element computer program, ANSYS, developed and marketed by Swanson Analysis Systems, Inc. is discussed. ANSYS was perhaps the first commercially available program to offer truly interactive finite element model generation. ANSYS's purpose is for solid modeling. This application is briefly discussed and illustrated.

Applying Automated Theorem Proving to Computer Security

DTIC Science & Technology

2008-03-01

CS96]”. Violations of policy can also be specified in this model. La Padula [Pad90] discusses a domain-independent formal model which imple- ments a...Science Laboratory, SRI International, Menlo Park, CA, September 1999. Pad90. L.J. La Padula . Formal modeling in a generalized framework for ac- cess

A model for calculating expected performance of the Apollo unified S-band (USB) communication system

NASA Technical Reports Server (NTRS)

Schroeder, N. W.

1971-01-01

A model for calculating the expected performance of the Apollo unified S-band (USB) communication system is presented. The general organization of the Apollo USB is described. The mathematical model is reviewed and the computer program for implementation of the calculations is included.

Division of Attention Relative to Response Between Attended and Unattended Stimuli.

ERIC Educational Resources Information Center

Kantowitz, Barry H.

Research was conducted to investigate two general classes of human attention models, early-selection models which claim that attentional selecting precedes memory and meaning extraction mechanisms, and late-selection models which posit the reverse. This research involved two components: (1) the development of simple, efficient, computer-oriented…

Receptor Surface Models in the Classroom: Introducing Molecular Modeling to Students in a 3-D World

ERIC Educational Resources Information Center

Geldenhuys, Werner J.; Hayes, Michael; Van der Schyf, Cornelis J.; Allen, David D.; Malan, Sarel F.

2007-01-01

A simple, novel and generally applicable method to demonstrate structure-activity associations of a group of biologically interesting compounds in relation to receptor binding is described. This method is useful for undergraduates and graduate students in medicinal chemistry and computer modeling programs.

Model implementation for dynamic computation of system cost

NASA Astrophysics Data System (ADS)

Levri, J.; Vaccari, D.

The Advanced Life Support (ALS) Program metric is the ratio of the equivalent system mass (ESM) of a mission based on International Space Station (ISS) technology to the ESM of that same mission based on ALS technology. ESM is a mission cost analog that converts the volume, power, cooling and crewtime requirements of a mission into mass units to compute an estimate of the life support system emplacement cost. Traditionally, ESM has been computed statically, using nominal values for system sizing. However, computation of ESM with static, nominal sizing estimates cannot capture the peak sizing requirements driven by system dynamics. In this paper, a dynamic model for a near-term Mars mission is described. The model is implemented in Matlab/Simulink' for the purpose of dynamically computing ESM. This paper provides a general overview of the crew, food, biomass, waste, water and air blocks in the Simulink' model. Dynamic simulations of the life support system track mass flow, volume and crewtime needs, as well as power and cooling requirement profiles. The mission's ESM is computed, based upon simulation responses. Ultimately, computed ESM values for various system architectures will feed into an optimization search (non-derivative) algorithm to predict parameter combinations that result in reduced objective function values.

Self-learning Monte Carlo method and cumulative update in fermion systems

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

Liu, Junwei; Shen, Huitao; Qi, Yang

2017-06-07

In this study, we develop the self-learning Monte Carlo (SLMC) method, a general-purpose numerical method recently introduced to simulate many-body systems, for studying interacting fermion systems. Our method uses a highly efficient update algorithm, which we design and dub “cumulative update”, to generate new candidate configurations in the Markov chain based on a self-learned bosonic effective model. From a general analysis and a numerical study of the double exchange model as an example, we find that the SLMC with cumulative update drastically reduces the computational cost of the simulation, while remaining statistically exact. Remarkably, its computational complexity is far lessmore » than the conventional algorithm with local updates.« less

Specialized computer architectures for computational aerodynamics

NASA Technical Reports Server (NTRS)

Stevenson, D. K.

1978-01-01

In recent years, computational fluid dynamics has made significant progress in modelling aerodynamic phenomena. Currently, one of the major barriers to future development lies in the compute-intensive nature of the numerical formulations and the relative high cost of performing these computations on commercially available general purpose computers, a cost high with respect to dollar expenditure and/or elapsed time. Today's computing technology will support a program designed to create specialized computing facilities to be dedicated to the important problems of computational aerodynamics. One of the still unresolved questions is the organization of the computing components in such a facility. The characteristics of fluid dynamic problems which will have significant impact on the choice of computer architecture for a specialized facility are reviewed.

Robust integration schemes for generalized viscoplasticity with internal-state variables. Part 2: Algorithmic developments and implementation

NASA Technical Reports Server (NTRS)

Li, Wei; Saleeb, Atef F.

1995-01-01

This two-part report is concerned with the development of a general framework for the implicit time-stepping integrators for the flow and evolution equations in generalized viscoplastic models. The primary goal is to present a complete theoretical formulation, and to address in detail the algorithmic and numerical analysis aspects involved in its finite element implementation, as well as to critically assess the numerical performance of the developed schemes in a comprehensive set of test cases. On the theoretical side, the general framework is developed on the basis of the unconditionally-stable, backward-Euler difference scheme as a starting point. Its mathematical structure is of sufficient generality to allow a unified treatment of different classes of viscoplastic models with internal variables. In particular, two specific models of this type, which are representative of the present start-of-art in metal viscoplasticity, are considered in applications reported here; i.e., fully associative (GVIPS) and non-associative (NAV) models. The matrix forms developed for both these models are directly applicable for both initially isotropic and anisotropic materials, in general (three-dimensional) situations as well as subspace applications (i.e., plane stress/strain, axisymmetric, generalized plane stress in shells). On the computational side, issues related to efficiency and robustness are emphasized in developing the (local) interative algorithm. In particular, closed-form expressions for residual vectors and (consistent) material tangent stiffness arrays are given explicitly for both GVIPS and NAV models, with their maximum sizes 'optimized' to depend only on the number of independent stress components (but independent of the number of viscoplastic internal state parameters). Significant robustness of the local iterative solution is provided by complementing the basic Newton-Raphson scheme with a line-search strategy for convergence. In the present second part of the report, we focus on the specific details of the numerical schemes, and associated computer algorithms, for the finite-element implementation of GVIPS and NAV models.

URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries.

PubMed

Drawert, Brian; Engblom, Stefan; Hellander, Andreas

2012-06-22

Experiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling. We have developed URDME, a flexible software framework for general stochastic reaction-transport modeling and simulation. URDME uses Unstructured triangular and tetrahedral meshes to resolve general geometries, and relies on the Reaction-Diffusion Master Equation formalism to model the processes under study. An interface to a mature geometry and mesh handling external software (Comsol Multiphysics) provides for a stable and interactive environment for model construction. The core simulation routines are logically separated from the model building interface and written in a low-level language for computational efficiency. The connection to the geometry handling software is realized via a Matlab interface which facilitates script computing, data management, and post-processing. For practitioners, the software therefore behaves much as an interactive Matlab toolbox. At the same time, it is possible to modify and extend URDME with newly developed simulation routines. Since the overall design effectively hides the complexity of managing the geometry and meshes, this means that newly developed methods may be tested in a realistic setting already at an early stage of development. In this paper we demonstrate, in a series of examples with high relevance to the molecular systems biology community, that the proposed software framework is a useful tool for both practitioners and developers of spatial stochastic simulation algorithms. Through the combined efforts of algorithm development and improved modeling accuracy, increasingly complex biological models become feasible to study through computational methods. URDME is freely available at http://www.urdme.org.

NASA general aviation crashworthiness seat development

NASA Technical Reports Server (NTRS)

Fasanella, E. L.; Alfaro-Bou, E.

1979-01-01

Three load limiting seat concepts for general aviation aircraft designed to lower the deceleration of the occupant in the event of a crash were sled tested and evaluated with reference to a standard seat. Dummy pelvis accelerations were reduced up to 50 percent with one of the concepts. Computer program MSOMLA (Modified Seat Occupant Model for Light Aircraft) was used to simulate the behavior of a dummy passenger in a NASA full-scale crash test of a twin engine light aircraft. A computer graphics package MANPLOT was developed to pictorially represent the occupant and seat motion.

Real-time data reduction capabilities at the Langley 7 by 10 foot high speed tunnel

NASA Technical Reports Server (NTRS)

Fox, C. H., Jr.

1980-01-01

The 7 by 10 foot high speed tunnel performs a wide range of tests employing a variety of model installation methods. To support the reduction of static data from this facility, a generalized wind tunnel data reduction program had been developed for use on the Langley central computer complex. The capabilities of a version of this generalized program adapted for real time use on a dedicated on-site computer are discussed. The input specifications, instructions for the console operator, and full descriptions of the algorithms are included.

ASKI: A modular toolbox for scattering-integral-based seismic full waveform inversion and sensitivity analysis utilizing external forward codes

NASA Astrophysics Data System (ADS)

Schumacher, Florian; Friederich, Wolfgang

Due to increasing computational resources, the development of new numerically demanding methods and software for imaging Earth's interior remains of high interest in Earth sciences. Here, we give a description from a user's and programmer's perspective of the highly modular, flexible and extendable software package ASKI-Analysis of Sensitivity and Kernel Inversion-recently developed for iterative scattering-integral-based seismic full waveform inversion. In ASKI, the three fundamental steps of solving the seismic forward problem, computing waveform sensitivity kernels and deriving a model update are solved by independent software programs that interact via file output/input only. Furthermore, the spatial discretizations of the model space used for solving the seismic forward problem and for deriving model updates, respectively, are kept completely independent. For this reason, ASKI does not contain a specific forward solver but instead provides a general interface to established community wave propagation codes. Moreover, the third fundamental step of deriving a model update can be repeated at relatively low costs applying different kinds of model regularization or re-selecting/weighting the inverted dataset without need to re-solve the forward problem or re-compute the kernels. Additionally, ASKI offers the user sensitivity and resolution analysis tools based on the full sensitivity matrix and allows to compose customized workflows in a consistent computational environment. ASKI is written in modern Fortran and Python, it is well documented and freely available under terms of the GNU General Public License (http://www.rub.de/aski).

Bayesian evidence computation for model selection in non-linear geoacoustic inference problems.

PubMed

Dettmer, Jan; Dosso, Stan E; Osler, John C

2010-12-01

This paper applies a general Bayesian inference approach, based on Bayesian evidence computation, to geoacoustic inversion of interface-wave dispersion data. Quantitative model selection is carried out by computing the evidence (normalizing constants) for several model parameterizations using annealed importance sampling. The resulting posterior probability density estimate is compared to estimates obtained from Metropolis-Hastings sampling to ensure consistent results. The approach is applied to invert interface-wave dispersion data collected on the Scotian Shelf, off the east coast of Canada for the sediment shear-wave velocity profile. Results are consistent with previous work on these data but extend the analysis to a rigorous approach including model selection and uncertainty analysis. The results are also consistent with core samples and seismic reflection measurements carried out in the area.

Progressive Failure of a Unidirectional Fiber-Reinforced Composite Using the Method of Cells: Discretization Objective Computational Results

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Bednarcyk, Brett A.; Waas, Anthony M.; Arnold, Steven M.

2012-01-01

The smeared crack band theory is implemented within the generalized method of cells and high-fidelity generalized method of cells micromechanics models to capture progressive failure within the constituents of a composite material while retaining objectivity with respect to the size of the discretization elements used in the model. An repeating unit cell containing 13 randomly arranged fibers is modeled and subjected to a combination of transverse tension/compression and transverse shear loading. The implementation is verified against experimental data (where available), and an equivalent finite element model utilizing the same implementation of the crack band theory. To evaluate the performance of the crack band theory within a repeating unit cell that is more amenable to a multiscale implementation, a single fiber is modeled with generalized method of cells and high-fidelity generalized method of cells using a relatively coarse subcell mesh which is subjected to the same loading scenarios as the multiple fiber repeating unit cell. The generalized method of cells and high-fidelity generalized method of cells models are validated against a very refined finite element model.

Computational models of music perception and cognition I: The perceptual and cognitive processing chain

NASA Astrophysics Data System (ADS)

Purwins, Hendrik; Herrera, Perfecto; Grachten, Maarten; Hazan, Amaury; Marxer, Ricard; Serra, Xavier

2008-09-01

We present a review on perception and cognition models designed for or applicable to music. An emphasis is put on computational implementations. We include findings from different disciplines: neuroscience, psychology, cognitive science, artificial intelligence, and musicology. The article summarizes the methodology that these disciplines use to approach the phenomena of music understanding, the localization of musical processes in the brain, and the flow of cognitive operations involved in turning physical signals into musical symbols, going from the transducers to the memory systems of the brain. We discuss formal models developed to emulate, explain and predict phenomena involved in early auditory processing, pitch processing, grouping, source separation, and music structure computation. We cover generic computational architectures of attention, memory, and expectation that can be instantiated and tuned to deal with specific musical phenomena. Criteria for the evaluation of such models are presented and discussed. Thereby, we lay out the general framework that provides the basis for the discussion of domain-specific music models in Part II.

Experiments in monthly mean simulation of the atmosphere with a coarse-mesh general circulation model

NASA Technical Reports Server (NTRS)

Lutz, R. J.; Spar, J.

1978-01-01

The Hansen atmospheric model was used to compute five monthly forecasts (October 1976 through February 1977). The comparison is based on an energetics analysis, meridional and vertical profiles, error statistics, and prognostic and observed mean maps. The monthly mean model simulations suffer from several defects. There is, in general, no skill in the simulation of the monthly mean sea-level pressure field, and only marginal skill is indicated for the 850 mb temperatures and 500 mb heights. The coarse-mesh model appears to generate a less satisfactory monthly mean simulation than the finer mesh GISS model.

Generic algorithms for high performance scalable geocomputing

NASA Astrophysics Data System (ADS)

de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek

2016-04-01

During the last decade, the characteristics of computing hardware have changed a lot. For example, instead of a single general purpose CPU core, personal computers nowadays contain multiple cores per CPU and often general purpose accelerators, like GPUs. Additionally, compute nodes are often grouped together to form clusters or a supercomputer, providing enormous amounts of compute power. For existing earth simulation models to be able to use modern hardware platforms, their compute intensive parts must be rewritten. This can be a major undertaking and may involve many technical challenges. Compute tasks must be distributed over CPU cores, offloaded to hardware accelerators, or distributed to different compute nodes. And ideally, all of this should be done in such a way that the compute task scales well with the hardware resources. This presents two challenges: 1) how to make good use of all the compute resources and 2) how to make these compute resources available for developers of simulation models, who may not (want to) have the required technical background for distributing compute tasks. The first challenge requires the use of specialized technology (e.g.: threads, OpenMP, MPI, OpenCL, CUDA). The second challenge requires the abstraction of the logic handling the distribution of compute tasks from the model-specific logic, hiding the technical details from the model developer. To assist the model developer, we are developing a C++ software library (called Fern) containing algorithms that can use all CPU cores available in a single compute node (distributing tasks over multiple compute nodes will be done at a later stage). The algorithms are grid-based (finite difference) and include local and spatial operations such as convolution filters. The algorithms handle distribution of the compute tasks to CPU cores internally. In the resulting model the low-level details of how this is done is separated from the model-specific logic representing the modeled system. This contrasts with practices in which code for distributing of compute tasks is mixed with model-specific code, and results in a better maintainable model. For flexibility and efficiency, the algorithms are configurable at compile-time with the respect to the following aspects: data type, value type, no-data handling, input value domain handling, and output value range handling. This makes the algorithms usable in very different contexts, without the need for making intrusive changes to existing models when using them. Applications that benefit from using the Fern library include the construction of forward simulation models in (global) hydrology (e.g. PCR-GLOBWB (Van Beek et al. 2011)), ecology, geomorphology, or land use change (e.g. PLUC (Verstegen et al. 2014)) and manipulation of hyper-resolution land surface data such as digital elevation models and remote sensing data. Using the Fern library, we have also created an add-on to the PCRaster Python Framework (Karssenberg et al. 2010) allowing its users to speed up their spatio-temporal models, sometimes by changing just a single line of Python code in their model. In our presentation we will give an overview of the design of the algorithms, providing examples of different contexts where they can be used to replace existing sequential algorithms, including the PCRaster environmental modeling software (www.pcraster.eu). We will show how the algorithms can be configured to behave differently when necessary. References Karssenberg, D., Schmitz, O., Salamon, P., De Jong, K. and Bierkens, M.F.P., 2010, A software framework for construction of process-based stochastic spatio-temporal models and data assimilation. Environmental Modelling & Software, 25, pp. 489-502, Link. Best Paper Award 2010: Software and Decision Support. Van Beek, L. P. H., Y. Wada, and M. F. P. Bierkens. 2011. Global monthly water stress: 1. Water balance and water availability. Water Resources Research. 47. Verstegen, J. A., D. Karssenberg, F. van der Hilst, and A. P. C. Faaij. 2014. Identifying a land use change cellular automaton by Bayesian data assimilation. Environmental Modelling & Software 53:121-136.

Factor Analysis by Generalized Least Squares.

ERIC Educational Resources Information Center

Joreskog, Karl G.; Goldberger, Arthur S.

Aitkin's generalized least squares (GLS) principle, with the inverse of the observed variance-covariance matrix as a weight matrix, is applied to estimate the factor analysis model in the exploratory (unrestricted) case. It is shown that the GLS estimates are scale free and asymptotically efficient. The estimates are computed by a rapidly…

Neural networks: further insights into error function, generalized weights and others

PubMed Central

2016-01-01

The article is a continuum of a previous one providing further insights into the structure of neural network (NN). Key concepts of NN including activation function, error function, learning rate and generalized weights are introduced. NN topology can be visualized with generic plot() function by passing a “nn” class object. Generalized weights assist interpretation of NN model with respect to the independent effect of individual input variables. A large variance of generalized weights for a covariate indicates non-linearity of its independent effect. If generalized weights of a covariate are approximately zero, the covariate is considered to have no effect on outcome. Finally, prediction of new observations can be performed using compute() function. Make sure that the feature variables passed to the compute() function are in the same order to that in the training NN. PMID:27668220

Nonlinear Unsteady Aerodynamic Modeling Using Wind Tunnel and Computational Data

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.; Klein, Vladislav; Frink, Neal T.

2016-01-01

Extensions to conventional aircraft aerodynamic models are required to adequately predict responses when nonlinear unsteady flight regimes are encountered, especially at high incidence angles and under maneuvering conditions. For a number of reasons, such as loss of control, both military and civilian aircraft may extend beyond normal and benign aerodynamic flight conditions. In addition, military applications may require controlled flight beyond the normal envelope, and civilian flight may require adequate recovery or prevention methods from these adverse conditions. These requirements have led to the development of more general aerodynamic modeling methods and provided impetus for researchers to improve both techniques and the degree of collaboration between analytical and experimental research efforts. In addition to more general mathematical model structures, dynamic test methods have been designed to provide sufficient information to allow model identification. This paper summarizes research to develop a modeling methodology appropriate for modeling aircraft aerodynamics that include nonlinear unsteady behaviors using both experimental and computational test methods. This work was done at Langley Research Center, primarily under the NASA Aviation Safety Program, to address aircraft loss of control, prevention, and recovery aerodynamics.

Towards a model of pion generalized parton distributions from Dyson-Schwinger equations

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

Moutarde, H.

2015-04-10

We compute the pion quark Generalized Parton Distribution H{sup q} and Double Distributions F{sup q} and G{sup q} in a coupled Bethe-Salpeter and Dyson-Schwinger approach. We use simple algebraic expressions inspired by the numerical resolution of Dyson-Schwinger and Bethe-Salpeter equations. We explicitly check the support and polynomiality properties, and the behavior under charge conjugation or time invariance of our model. We derive analytic expressions for the pion Double Distributions and Generalized Parton Distribution at vanishing pion momentum transfer at a low scale. Our model compares very well to experimental pion form factor or parton distribution function data.

Modeling for Battery Prognostics

NASA Technical Reports Server (NTRS)

Kulkarni, Chetan S.; Goebel, Kai; Khasin, Michael; Hogge, Edward; Quach, Patrick

2017-01-01

For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient, and is of suitable accuracy for reliable EOD prediction in a variety of operational profiles. The model can be considered an electrochemical engineering model, but unlike most such models found in the literature, certain approximations are done that allow to retain computational efficiency for online implementation of the model. Although the focus here is on Li-ion batteries, the model is quite general and can be applied to different chemistries through a change of model parameter values. Progress on model development, providing model validation results and EOD prediction results is being presented.

Emergence of Landauer transport from quantum dynamics: A model Hamiltonian approach

NASA Astrophysics Data System (ADS)

Pal, Partha Pratim; Ramakrishna, S.; Seideman, Tamar

2018-04-01

The Landauer expression for computing current-voltage characteristics in nanoscale devices is efficient but not suited to transient phenomena and a time-dependent current because it is applicable only when the charge carriers transition into a steady flux after an external perturbation. In this article, we construct a very general expression for time-dependent current in an electrode-molecule-electrode arrangement. Utilizing a model Hamiltonian (consisting of the subsystem energy levels and their electronic coupling terms), we propagate the Schrödinger wave function equation to numerically compute the time-dependent population in the individual subsystems. The current in each electrode (defined in terms of the rate of change of the corresponding population) has two components, one due to the charges originating from the same electrode and the other due to the charges initially residing at the other electrode. We derive an analytical expression for the first component and illustrate that it agrees reasonably with its numerical counterpart at early times. Exploiting the unitary evolution of a wavefunction, we construct a more general Landauer style formula and illustrate the emergence of Landauer transport from our simulations without the assumption of time-independent charge flow. Our generalized Landauer formula is valid at all times for models beyond the wide-band limit, non-uniform electrode density of states and for time and energy-dependent electronic coupling between the subsystems. Subsequently, we investigate the ingredients in our model that regulate the onset time scale of this steady state. We compare the performance of our general current expression with the Landauer current for time-dependent electronic coupling. Finally, we comment on the applicability of the Landauer formula to compute hot-electron current arising upon plasmon decoherence.

Emergence of Landauer transport from quantum dynamics: A model Hamiltonian approach.

PubMed

Pal, Partha Pratim; Ramakrishna, S; Seideman, Tamar

2018-04-14

The Landauer expression for computing current-voltage characteristics in nanoscale devices is efficient but not suited to transient phenomena and a time-dependent current because it is applicable only when the charge carriers transition into a steady flux after an external perturbation. In this article, we construct a very general expression for time-dependent current in an electrode-molecule-electrode arrangement. Utilizing a model Hamiltonian (consisting of the subsystem energy levels and their electronic coupling terms), we propagate the Schrödinger wave function equation to numerically compute the time-dependent population in the individual subsystems. The current in each electrode (defined in terms of the rate of change of the corresponding population) has two components, one due to the charges originating from the same electrode and the other due to the charges initially residing at the other electrode. We derive an analytical expression for the first component and illustrate that it agrees reasonably with its numerical counterpart at early times. Exploiting the unitary evolution of a wavefunction, we construct a more general Landauer style formula and illustrate the emergence of Landauer transport from our simulations without the assumption of time-independent charge flow. Our generalized Landauer formula is valid at all times for models beyond the wide-band limit, non-uniform electrode density of states and for time and energy-dependent electronic coupling between the subsystems. Subsequently, we investigate the ingredients in our model that regulate the onset time scale of this steady state. We compare the performance of our general current expression with the Landauer current for time-dependent electronic coupling. Finally, we comment on the applicability of the Landauer formula to compute hot-electron current arising upon plasmon decoherence.

CPMIP: measurements of real computational performance of Earth system models in CMIP6

NASA Astrophysics Data System (ADS)

Balaji, Venkatramani; Maisonnave, Eric; Zadeh, Niki; Lawrence, Bryan N.; Biercamp, Joachim; Fladrich, Uwe; Aloisio, Giovanni; Benson, Rusty; Caubel, Arnaud; Durachta, Jeffrey; Foujols, Marie-Alice; Lister, Grenville; Mocavero, Silvia; Underwood, Seth; Wright, Garrett

2017-01-01

A climate model represents a multitude of processes on a variety of timescales and space scales: a canonical example of multi-physics multi-scale modeling. The underlying climate system is physically characterized by sensitive dependence on initial conditions, and natural stochastic variability, so very long integrations are needed to extract signals of climate change. Algorithms generally possess weak scaling and can be I/O and/or memory-bound. Such weak-scaling, I/O, and memory-bound multi-physics codes present particular challenges to computational performance. Traditional metrics of computational efficiency such as performance counters and scaling curves do not tell us enough about real sustained performance from climate models on different machines. They also do not provide a satisfactory basis for comparative information across models. codes present particular challenges to computational performance. We introduce a set of metrics that can be used for the study of computational performance of climate (and Earth system) models. These measures do not require specialized software or specific hardware counters, and should be accessible to anyone. They are independent of platform and underlying parallel programming models. We show how these metrics can be used to measure actually attained performance of Earth system models on different machines, and identify the most fruitful areas of research and development for performance engineering. codes present particular challenges to computational performance. We present results for these measures for a diverse suite of models from several modeling centers, and propose to use these measures as a basis for a CPMIP, a computational performance model intercomparison project (MIP).

Technical description of space ultra reliable modular computer (SUMC), model 2 B

NASA Technical Reports Server (NTRS)

1975-01-01

The design features of the SUMC-2B computer, also called the IBM-HTC are described. It is general purpose digital computer implemented with flexible hardware elements and microprograming to enable low cost customizing to a wide range of applications. It executes the S/360 standard instruction set to maintain problem state compability. Memory technology, extended instruction sets, and I/O channel variations are among the available options.

Thrombosis in Cerebral Aneurysms and the Computational Modeling Thereof: A Review

PubMed Central

Ngoepe, Malebogo N.; Frangi, Alejandro F.; Byrne, James V.; Ventikos, Yiannis

2018-01-01

Thrombosis is a condition closely related to cerebral aneurysms and controlled thrombosis is the main purpose of endovascular embolization treatment. The mechanisms governing thrombus initiation and evolution in cerebral aneurysms have not been fully elucidated and this presents challenges for interventional planning. Significant effort has been directed towards developing computational methods aimed at streamlining the interventional planning process for unruptured cerebral aneurysm treatment. Included in these methods are computational models of thrombus development following endovascular device placement. The main challenge with developing computational models for thrombosis in disease cases is that there exists a wide body of literature that addresses various aspects of the clotting process, but it may not be obvious what information is of direct consequence for what modeling purpose (e.g., for understanding the effect of endovascular therapies). The aim of this review is to present the information so it will be of benefit to the community attempting to model cerebral aneurysm thrombosis for interventional planning purposes, in a simplified yet appropriate manner. The paper begins by explaining current understanding of physiological coagulation and highlights the documented distinctions between the physiological process and cerebral aneurysm thrombosis. Clinical observations of thrombosis following endovascular device placement are then presented. This is followed by a section detailing the demands placed on computational models developed for interventional planning. Finally, existing computational models of thrombosis are presented. This last section begins with description and discussion of physiological computational clotting models, as they are of immense value in understanding how to construct a general computational model of clotting. This is then followed by a review of computational models of clotting in cerebral aneurysms, specifically. Even though some progress has been made towards computational predictions of thrombosis following device placement in cerebral aneurysms, many gaps still remain. Answering the key questions will require the combined efforts of the clinical, experimental and computational communities. PMID:29670533

Thrombosis in Cerebral Aneurysms and the Computational Modeling Thereof: A Review.

PubMed

Ngoepe, Malebogo N; Frangi, Alejandro F; Byrne, James V; Ventikos, Yiannis

2018-01-01

Thrombosis is a condition closely related to cerebral aneurysms and controlled thrombosis is the main purpose of endovascular embolization treatment. The mechanisms governing thrombus initiation and evolution in cerebral aneurysms have not been fully elucidated and this presents challenges for interventional planning. Significant effort has been directed towards developing computational methods aimed at streamlining the interventional planning process for unruptured cerebral aneurysm treatment. Included in these methods are computational models of thrombus development following endovascular device placement. The main challenge with developing computational models for thrombosis in disease cases is that there exists a wide body of literature that addresses various aspects of the clotting process, but it may not be obvious what information is of direct consequence for what modeling purpose (e.g., for understanding the effect of endovascular therapies). The aim of this review is to present the information so it will be of benefit to the community attempting to model cerebral aneurysm thrombosis for interventional planning purposes, in a simplified yet appropriate manner. The paper begins by explaining current understanding of physiological coagulation and highlights the documented distinctions between the physiological process and cerebral aneurysm thrombosis. Clinical observations of thrombosis following endovascular device placement are then presented. This is followed by a section detailing the demands placed on computational models developed for interventional planning. Finally, existing computational models of thrombosis are presented. This last section begins with description and discussion of physiological computational clotting models, as they are of immense value in understanding how to construct a general computational model of clotting. This is then followed by a review of computational models of clotting in cerebral aneurysms, specifically. Even though some progress has been made towards computational predictions of thrombosis following device placement in cerebral aneurysms, many gaps still remain. Answering the key questions will require the combined efforts of the clinical, experimental and computational communities.

A general probabilistic model for group independent component analysis and its estimation methods

PubMed Central

Guo, Ying

2012-01-01

SUMMARY Independent component analysis (ICA) has become an important tool for analyzing data from functional magnetic resonance imaging (fMRI) studies. ICA has been successfully applied to single-subject fMRI data. The extension of ICA to group inferences in neuroimaging studies, however, is challenging due to the unavailability of a pre-specified group design matrix and the uncertainty in between-subjects variability in fMRI data. We present a general probabilistic ICA (PICA) model that can accommodate varying group structures of multi-subject spatio-temporal processes. An advantage of the proposed model is that it can flexibly model various types of group structures in different underlying neural source signals and under different experimental conditions in fMRI studies. A maximum likelihood method is used for estimating this general group ICA model. We propose two EM algorithms to obtain the ML estimates. The first method is an exact EM algorithm which provides an exact E-step and an explicit noniterative M-step. The second method is an variational approximation EM algorithm which is computationally more efficient than the exact EM. In simulation studies, we first compare the performance of the proposed general group PICA model and the existing probabilistic group ICA approach. We then compare the two proposed EM algorithms and show the variational approximation EM achieves comparable accuracy to the exact EM with significantly less computation time. An fMRI data example is used to illustrate application of the proposed methods. PMID:21517789

Superelement model based parallel algorithm for vehicle dynamics

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

Agrawal, O.P.; Danhof, K.J.; Kumar, R.

1994-05-01

This paper presents a superelement model based parallel algorithm for a planar vehicle dynamics. The vehicle model is made up of a chassis and two suspension systems each of which consists of an axle-wheel assembly and two trailing arms. In this model, the chassis is treated as a Cartesian element and each suspension system is treated as a superelement. The parameters associated with the superelements are computed using an inverse dynamics technique. Suspension shock absorbers and the tires are modeled by nonlinear springs and dampers. The Euler-Lagrange approach is used to develop the system equations of motion. This leads tomore » a system of differential and algebraic equations in which the constraints internal to superelements appear only explicitly. The above formulation is implemented on a multiprocessor machine. The numerical flow chart is divided into modules and the computation of several modules is performed in parallel to gain computational efficiency. In this implementation, the master (parent processor) creates a pool of slaves (child processors) at the beginning of the program. The slaves remain in the pool until they are needed to perform certain tasks. Upon completion of a particular task, a slave returns to the pool. This improves the overall response time of the algorithm. The formulation presented is general which makes it attractive for a general purpose code development. Speedups obtained in the different modules of the dynamic analysis computation are also presented. Results show that the superelement model based parallel algorithm can significantly reduce the vehicle dynamics simulation time. 52 refs.« less

Physically-Based Modelling and Real-Time Simulation of Fluids.

NASA Astrophysics Data System (ADS)

Chen, Jim Xiong

1995-01-01

Simulating physically realistic complex fluid behaviors presents an extremely challenging problem for computer graphics researchers. Such behaviors include the effects of driving boats through water, blending differently colored fluids, rain falling and flowing on a terrain, fluids interacting in a Distributed Interactive Simulation (DIS), etc. Such capabilities are useful in computer art, advertising, education, entertainment, and training. We present a new method for physically-based modeling and real-time simulation of fluids in computer graphics and dynamic virtual environments. By solving the 2D Navier -Stokes equations using a CFD method, we map the surface into 3D using the corresponding pressures in the fluid flow field. This achieves realistic real-time fluid surface behaviors by employing the physical governing laws of fluids but avoiding extensive 3D fluid dynamics computations. To complement the surface behaviors, we calculate fluid volume and external boundary changes separately to achieve full 3D general fluid flow. To simulate physical activities in a DIS, we introduce a mechanism which uses a uniform time scale proportional to the clock-time and variable time-slicing to synchronize physical models such as fluids in the networked environment. Our approach can simulate many different fluid behaviors by changing the internal or external boundary conditions. It can model different kinds of fluids by varying the Reynolds number. It can simulate objects moving or floating in fluids. It can also produce synchronized general fluid flows in a DIS. Our model can serve as a testbed to simulate many other fluid phenomena which have never been successfully modeled previously.

Electromagnetic axial anomaly in a generalized linear sigma model

NASA Astrophysics Data System (ADS)

Fariborz, Amir H.; Jora, Renata

2017-06-01

We construct the electromagnetic anomaly effective term for a generalized linear sigma model with two chiral nonets, one with a quark-antiquark structure, the other one with a four-quark content. We compute in the leading order of this framework the decays into two photons of six pseudoscalars: π0(137 ), π0(1300 ), η (547 ), η (958 ), η (1295 ) and η (1760 ). Our results agree well with the available experimental data.

Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy

NASA Astrophysics Data System (ADS)

Gil, D.; Garcia-Barnes, J.; Hernández-Sabate, A.; Marti, E.

2010-03-01

Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature.

A Computational Model of Reasoning from the Clinical Literature

PubMed Central

Rennels, Glenn D.

1986-01-01

This paper explores the premise that a formalized representation of empirical studies can play a central role in computer-based decision support. The specific motivations underlying this research include the following propositions: 1. Reasoning from experimental evidence contained in the clinical literature is central to the decisions physicians make in patient care. 2. A computational model, based upon a declarative representation for published reports of clinical studies, can drive a computer program that selectively tailors knowledge of the clinical literature as it is applied to a particular case. 3. The development of such a computational model is an important first step toward filling a void in computer-based decision support systems. Furthermore, the model may help us better understand the general principles of reasoning from experimental evidence both in medicine and other domains. Roundsman is a developmental computer system which draws upon structured representations of the clinical literature in order to critique plans for the management of primary breast cancer. Roundsman is able to produce patient-specific analyses of breast cancer management options based on the 24 clinical studies currently encoded in its knowledge base. The Roundsman system is a first step in exploring how the computer can help to bring a critical analysis of the relevant literature to the physician, structured around a particular patient and treatment decision.

Runway Scheduling Using Generalized Dynamic Programming

NASA Technical Reports Server (NTRS)

Montoya, Justin; Wood, Zachary; Rathinam, Sivakumar

2011-01-01

A generalized dynamic programming method for finding a set of pareto optimal solutions for a runway scheduling problem is introduced. The algorithm generates a set of runway fight sequences that are optimal for both runway throughput and delay. Realistic time-based operational constraints are considered, including miles-in-trail separation, runway crossings, and wake vortex separation. The authors also model divergent runway takeoff operations to allow for reduced wake vortex separation. A modeled Dallas/Fort Worth International airport and three baseline heuristics are used to illustrate preliminary benefits of using the generalized dynamic programming method. Simulated traffic levels ranged from 10 aircraft to 30 aircraft with each test case spanning 15 minutes. The optimal solution shows a 40-70 percent decrease in the expected delay per aircraft over the baseline schedulers. Computational results suggest that the algorithm is promising for real-time application with an average computation time of 4.5 seconds. For even faster computation times, two heuristics are developed. As compared to the optimal, the heuristics are within 5% of the expected delay per aircraft and 1% of the expected number of runway operations per hour ad can be 100x faster.

Verifying Stability of Dynamic Soft-Computing Systems

NASA Technical Reports Server (NTRS)

Wen, Wu; Napolitano, Marcello; Callahan, John

1997-01-01

Soft computing is a general term for algorithms that learn from human knowledge and mimic human skills. Example of such algorithms are fuzzy inference systems and neural networks. Many applications, especially in control engineering, have demonstrated their appropriateness in building intelligent systems that are flexible and robust. Although recent research have shown that certain class of neuro-fuzzy controllers can be proven bounded and stable, they are implementation dependent and difficult to apply to the design and validation process. Many practitioners adopt the trial and error approach for system validation or resort to exhaustive testing using prototypes. In this paper, we describe our on-going research towards establishing necessary theoretic foundation as well as building practical tools for the verification and validation of soft-computing systems. A unified model for general neuro-fuzzy system is adopted. Classic non-linear system control theory and recent results of its applications to neuro-fuzzy systems are incorporated and applied to the unified model. It is hoped that general tools can be developed to help the designer to visualize and manipulate the regions of stability and boundedness, much the same way Bode plots and Root locus plots have helped conventional control design and validation.

Computation of magnetic suspension of maglev systems using dynamic circuit theory

NASA Technical Reports Server (NTRS)

He, J. L.; Rote, D. M.; Coffey, H. T.

1992-01-01

Dynamic circuit theory is applied to several magnetic suspensions associated with maglev systems. These suspension systems are the loop-shaped coil guideway, the figure-eight-shaped null-flux coil guideway, and the continuous sheet guideway. Mathematical models, which can be used for the development of computer codes, are provided for each of these suspension systems. The differences and similarities of the models in using dynamic circuit theory are discussed in the paper. The paper emphasizes the transient and dynamic analysis and computer simulation of maglev systems. In general, the method discussed here can be applied to many electrodynamic suspension system design concepts. It is also suited for the computation of the performance of maglev propulsion systems. Numerical examples are presented in the paper.

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.

A Comparison of Alternative Approaches to the Analysis of Interrupted Time-Series.

ERIC Educational Resources Information Center

Harrop, John W.; Velicer, Wayne F.

1985-01-01

Computer generated data representative of 16 Auto Regressive Integrated Moving Averages (ARIMA) models were used to compare the results of interrupted time-series analysis using: (1) the known model identification, (2) an assumed (l,0,0) model, and (3) an assumed (3,0,0) model as an approximation to the General Transformation approach. (Author/BW)

Generalized Fluid System Simulation Program, Version 5.0-Educational. Supplemental Information for NASA/TM-2011-216470. Supplement

NASA Technical Reports Server (NTRS)

Majumdar, A. K.

2011-01-01

The Generalized Fluid System Simulation Program (GFSSP) is a finite-volume based general-purpose computer program for analyzing steady state and time-dependent flow rates, pressures, temperatures, and concentrations in a complex flow network. The program is capable of modeling real fluids with phase changes, compressibility, mixture thermodynamics, conjugate heat transfer between solid and fluid, fluid transients, pumps, compressors and external body forces such as gravity and centrifugal. The thermofluid system to be analyzed is discretized into nodes, branches, and conductors. The scalar properties such as pressure, temperature, and concentrations are calculated at nodes. Mass flow rates and heat transfer rates are computed in branches and conductors. The graphical user interface allows users to build their models using the point, drag and click method; the users can also run their models and post-process the results in the same environment. The integrated fluid library supplies thermodynamic and thermo-physical properties of 36 fluids and 21 different resistance/source options are provided for modeling momentum sources or sinks in the branches. This Technical Memorandum illustrates the application and verification of the code through 12 demonstrated example problems. This supplement gives the input and output data files for the examples.

Vectorized Jiles-Atherton hysteresis model

NASA Astrophysics Data System (ADS)

Szymański, Grzegorz; Waszak, Michał

2004-01-01

This paper deals with vector hysteresis modeling. A vector model consisting of individual Jiles-Atherton components placed along principal axes is proposed. The cross-axis coupling ensures general vector model properties. Minor loops are obtained using scaling method. The model is intended for efficient finite element method computations defined in terms of magnetic vector potential. Numerical efficiency is ensured by differential susceptibility approach.

Spreading dynamics on complex networks: a general stochastic approach.

PubMed

Noël, Pierre-André; Allard, Antoine; Hébert-Dufresne, Laurent; Marceau, Vincent; Dubé, Louis J

2014-12-01

Dynamics on networks is considered from the perspective of Markov stochastic processes. We partially describe the state of the system through network motifs and infer any missing data using the available information. This versatile approach is especially well adapted for modelling spreading processes and/or population dynamics. In particular, the generality of our framework and the fact that its assumptions are explicitly stated suggests that it could be used as a common ground for comparing existing epidemics models too complex for direct comparison, such as agent-based computer simulations. We provide many examples for the special cases of susceptible-infectious-susceptible and susceptible-infectious-removed dynamics (e.g., epidemics propagation) and we observe multiple situations where accurate results may be obtained at low computational cost. Our perspective reveals a subtle balance between the complex requirements of a realistic model and its basic assumptions.

Analytical modeling of helicopter static and dynamic induced velocity in GRASP

NASA Technical Reports Server (NTRS)

Kunz, Donald L.; Hodges, Dewey H.

1987-01-01

The methodology used by the General Rotorcraft Aeromechanical Stability Program (GRASP) to model the characteristics of the flow through a helicopter rotor in hovering or axial flight is described. Since the induced flow plays a significant role in determining the aeroelastic properties of rotorcraft, the computation of the induced flow is an important aspect of the program. Because of the combined finite-element/multibody methodology used as the basis for GRASP, the implementation of induced velocity calculations presented an unusual challenge to the developers. To preserve the modelling flexibility and generality of the code, it was necessary to depart from the traditional methods of computing the induced velocity. This is accomplished by calculating the actuator disc contributions to the rotor loads in a separate element called the air mass element, and then performing the calculations of the aerodynamic forces on individual blade elements within the aeroelastic beam element.

Water exchanges versus water works: Insights from a computable general equilibrium model for the Balearic Islands

NASA Astrophysics Data System (ADS)

Gómez, Carlos M.; Tirado, Dolores; Rey-Maquieira, Javier

2004-10-01

We present a computable general equilibrium model (CGE) for the Balearic Islands, specifically performed to analyze the welfare gains associated with an improvement in the allocation of water rights through voluntary water exchanges (mainly between the agriculture and urban sectors). For the implementation of the empirical model we built the social accounting matrix (SAM) from the last available input-output table of the islands (for the year 1997). Water exchanges provide an important alternative to make the allocation of water flexible enough to cope with the cyclical droughts that characterize the natural water regime on the islands. The main conclusion is that the increased efficiency provided by ``water markets'' makes this option more advantageous than the popular alternative of building new desalinization plants. Contrary to common opinion, a ``water market'' can also have positive and significant impacts on the agricultural income.

SCI Identification (SCIDNT) program user's guide. [maximum likelihood method for linear rotorcraft models

NASA Technical Reports Server (NTRS)

1979-01-01

The computer program Linear SCIDNT which evaluates rotorcraft stability and control coefficients from flight or wind tunnel test data is described. It implements the maximum likelihood method to maximize the likelihood function of the parameters based on measured input/output time histories. Linear SCIDNT may be applied to systems modeled by linear constant-coefficient differential equations. This restriction in scope allows the application of several analytical results which simplify the computation and improve its efficiency over the general nonlinear case.

Shuttle cryogenics supply system optimization study. Volume 5, B-3, part 2: Appendix to programmers manual for math model

NASA Technical Reports Server (NTRS)

1973-01-01

A computer programmer's manual for a digital computer which will permit rapid and accurate parametric analysis of current and advanced attitude control propulsion systems is presented. The concept is for a cold helium pressurized, subcritical cryogen fluid supplied, bipropellant gas-fed attitude control propulsion system. The cryogen fluids are stored as liquids under low pressure and temperature conditions. The mathematical model provides a generalized form for the procedural technique employed in setting up the analysis program.

Experimental Determination and Thermodynamic Modeling of Electrical Conductivity of SRS Waste Tank Supernate

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

Pike, J.; Reboul, S.

2015-06-01

SRS High Level Waste Tank Farm personnel rely on conductivity probes for detection of incipient overflow conditions in waste tanks. Minimal information is available concerning the sensitivity that must be achieved such that that liquid detection is assured. Overly sensitive electronics results in numerous nuisance alarms for these safety-related instruments. In order to determine the minimum sensitivity required of the probe, Tank Farm Engineering personnel need adequate conductivity data to improve the existing designs. Little or no measurements of liquid waste conductivity exist; however, the liquid phase of the waste consists of inorganic electrolytes for which the conductivity may bemore » calculated. Savannah River Remediation (SRR) Tank Farm Facility Engineering requested SRNL to determine the conductivity of the supernate resident in SRS waste Tank 40 experimentally as well as computationally. In addition, SRNL was requested to develop a correlation, if possible, that would be generally applicable to liquid waste resident in SRS waste tanks. A waste sample from Tank 40 was analyzed for composition and electrical conductivity as shown in Table 4-6, Table 4-7, and Table 4-9. The conductivity for undiluted Tank 40 sample was 0.087 S/cm. The accuracy of OLI Analyzer™ was determined using available literature data. Overall, 95% of computed estimates of electrical conductivity are within ±15% of literature values for component concentrations from 0 to 15 M and temperatures from 0 to 125 °C. Though the computational results are generally in good agreement with the measured data, a small portion of literature data deviates as much as ±76%. A simplified model was created that can be used readily to estimate electrical conductivity of waste solution in computer spreadsheets. The variability of this simplified approach deviates up to 140% from measured values. Generally, this model can be applied to estimate the conductivity within a factor of two. The comparison of the simplified model to pure component literature data suggests that the simplified model will tend to under estimate the electrical conductivity. Comparison of the computed Tank 40 conductivity with the measured conductivity shows good agreement within the range of deviation identified based on pure component literature data.« less

Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

NASA Astrophysics Data System (ADS)

Fiorini, Rodolfo A.; Dacquino, Gianfranco

2005-03-01

GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous, similar approaches are: 1) Progressive Automated Invariant Model Generation, 2) Invariant Minimal Complete Description Set for computational efficiency, 3) Arbitrary Model Precision for robust object description and identification.

Stochastic modelling of turbulent combustion for design optimization of gas turbine combustors

NASA Astrophysics Data System (ADS)

Mehanna Ismail, Mohammed Ali

The present work covers the development and the implementation of an efficient algorithm for the design optimization of gas turbine combustors. The purpose is to explore the possibilities and indicate constructive suggestions for optimization techniques as alternative methods for designing gas turbine combustors. The algorithm is general to the extent that no constraints are imposed on the combustion phenomena or on the combustor configuration. The optimization problem is broken down into two elementary problems: the first is the optimum search algorithm, and the second is the turbulent combustion model used to determine the combustor performance parameters. These performance parameters constitute the objective and physical constraints in the optimization problem formulation. The examination of both turbulent combustion phenomena and the gas turbine design process suggests that the turbulent combustion model represents a crucial part of the optimization algorithm. The basic requirements needed for a turbulent combustion model to be successfully used in a practical optimization algorithm are discussed. In principle, the combustion model should comply with the conflicting requirements of high fidelity, robustness and computational efficiency. To that end, the problem of turbulent combustion is discussed and the current state of the art of turbulent combustion modelling is reviewed. According to this review, turbulent combustion models based on the composition PDF transport equation are found to be good candidates for application in the present context. However, these models are computationally expensive. To overcome this difficulty, two different models based on the composition PDF transport equation were developed: an improved Lagrangian Monte Carlo composition PDF algorithm and the generalized stochastic reactor model. Improvements in the Lagrangian Monte Carlo composition PDF model performance and its computational efficiency were achieved through the implementation of time splitting, variable stochastic fluid particle mass control, and a second order time accurate (predictor-corrector) scheme used for solving the stochastic differential equations governing the particles evolution. The model compared well against experimental data found in the literature for two different configurations: bluff body and swirl stabilized combustors. The generalized stochastic reactor is a newly developed model. This model relies on the generalization of the concept of the classical stochastic reactor theory in the sense that it accounts for both finite micro- and macro-mixing processes. (Abstract shortened by UMI.)

Use of a Machine-learning Method for Predicting Highly Cited Articles Within General Radiology Journals.

PubMed

Rosenkrantz, Andrew B; Doshi, Ankur M; Ginocchio, Luke A; Aphinyanaphongs, Yindalon

2016-12-01

This study aimed to assess the performance of a text classification machine-learning model in predicting highly cited articles within the recent radiological literature and to identify the model's most influential article features. We downloaded from PubMed the title, abstract, and medical subject heading terms for 10,065 articles published in 25 general radiology journals in 2012 and 2013. Three machine-learning models were applied to predict the top 10% of included articles in terms of the number of citations to the article in 2014 (reflecting the 2-year time window in conventional impact factor calculations). The model having the highest area under the curve was selected to derive a list of article features (words) predicting high citation volume, which was iteratively reduced to identify the smallest possible core feature list maintaining predictive power. Overall themes were qualitatively assigned to the core features. The regularized logistic regression (Bayesian binary regression) model had highest performance, achieving an area under the curve of 0.814 in predicting articles in the top 10% of citation volume. We reduced the initial 14,083 features to 210 features that maintain predictivity. These features corresponded with topics relating to various imaging techniques (eg, diffusion-weighted magnetic resonance imaging, hyperpolarized magnetic resonance imaging, dual-energy computed tomography, computed tomography reconstruction algorithms, tomosynthesis, elastography, and computer-aided diagnosis), particular pathologies (prostate cancer; thyroid nodules; hepatic adenoma, hepatocellular carcinoma, non-alcoholic fatty liver disease), and other topics (radiation dose, electroporation, education, general oncology, gadolinium, statistics). Machine learning can be successfully applied to create specific feature-based models for predicting articles likely to achieve high influence within the radiological literature. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

A Comparison of Computer-Based Classification Testing Approaches Using Mixed-Format Tests with the Generalized Partial Credit Model

ERIC Educational Resources Information Center

Kim, Jiseon

2010-01-01

Classification testing has been widely used to make categorical decisions by determining whether an examinee has a certain degree of ability required by established standards. As computer technologies have developed, classification testing has become more computerized. Several approaches have been proposed and investigated in the context of…

Instructional Advice, Time Advice and Learning Questions in Computer Simulations

ERIC Educational Resources Information Center

Rey, Gunter Daniel

2010-01-01

Undergraduate students (N = 97) used an introductory text and a computer simulation to learn fundamental concepts about statistical analyses (e.g., analysis of variance, regression analysis and General Linear Model). Each learner was randomly assigned to one cell of a 2 (with or without instructional advice) x 2 (with or without time advice) x 2…

Neural nets on the MPP

NASA Technical Reports Server (NTRS)

Hastings, Harold M.; Waner, Stefan

1987-01-01

The Massively Parallel Processor (MPP) is an ideal machine for computer experiments with simulated neural nets as well as more general cellular automata. Experiments using the MPP with a formal model neural network are described. The results on problem mapping and computational efficiency apply equally well to the neural nets of Hopfield, Hinton et al., and Geman and Geman.

How the Use of Computer Types and Frequency Affects Adolescences towards Anger and Aggression

ERIC Educational Resources Information Center

Yagci, Emete; Caglar, Mehmet

2010-01-01

This study was conducted to research the relationship between use of computer types and frequency and anger and aggression in adolescents. The study was conducted among years 9, 10 and 11 students (secondary level) in 2008-2009 academic year. The general research tool for this study used was "Relationship research" model. The focal…

Climate Models

NASA Technical Reports Server (NTRS)

Druyan, Leonard M.

2012-01-01

Climate models is a very broad topic, so a single volume can only offer a small sampling of relevant research activities. This volume of 14 chapters includes descriptions of a variety of modeling studies for a variety of geographic regions by an international roster of authors. The climate research community generally uses the rubric climate models to refer to organized sets of computer instructions that produce simulations of climate evolution. The code is based on physical relationships that describe the shared variability of meteorological parameters such as temperature, humidity, precipitation rate, circulation, radiation fluxes, etc. Three-dimensional climate models are integrated over time in order to compute the temporal and spatial variations of these parameters. Model domains can be global or regional and the horizontal and vertical resolutions of the computational grid vary from model to model. Considering the entire climate system requires accounting for interactions between solar insolation, atmospheric, oceanic and continental processes, the latter including land hydrology and vegetation. Model simulations may concentrate on one or more of these components, but the most sophisticated models will estimate the mutual interactions of all of these environments. Advances in computer technology have prompted investments in more complex model configurations that consider more phenomena interactions than were possible with yesterday s computers. However, not every attempt to add to the computational layers is rewarded by better model performance. Extensive research is required to test and document any advantages gained by greater sophistication in model formulation. One purpose for publishing climate model research results is to present purported advances for evaluation by the scientific community.

Fiber orientation interpolation for the multiscale analysis of short fiber reinforced composite parts

NASA Astrophysics Data System (ADS)

Köbler, Jonathan; Schneider, Matti; Ospald, Felix; Andrä, Heiko; Müller, Ralf

2018-06-01

For short fiber reinforced plastic parts the local fiber orientation has a strong influence on the mechanical properties. To enable multiscale computations using surrogate models we advocate a two-step identification strategy. Firstly, for a number of sample orientations an effective model is derived by numerical methods available in the literature. Secondly, to cover a general orientation state, these effective models are interpolated. In this article we develop a novel and effective strategy to carry out this interpolation. Firstly, taking into account symmetry arguments, we reduce the fiber orientation phase space to a triangle in R^2 . For an associated triangulation of this triangle we furnish each node with an surrogate model. Then, we use linear interpolation on the fiber orientation triangle to equip each fiber orientation state with an effective stress. The proposed approach is quite general, and works for any physically nonlinear constitutive law on the micro-scale, as long as surrogate models for single fiber orientation states can be extracted. To demonstrate the capabilities of our scheme we study the viscoelastic creep behavior of short glass fiber reinforced PA66, and use Schapery's collocation method together with FFT-based computational homogenization to derive single orientation state effective models. We discuss the efficient implementation of our method, and present results of a component scale computation on a benchmark component by using ABAQUS ®.

Fiber orientation interpolation for the multiscale analysis of short fiber reinforced composite parts

NASA Astrophysics Data System (ADS)

Köbler, Jonathan; Schneider, Matti; Ospald, Felix; Andrä, Heiko; Müller, Ralf

2018-04-01

For short fiber reinforced plastic parts the local fiber orientation has a strong influence on the mechanical properties. To enable multiscale computations using surrogate models we advocate a two-step identification strategy. Firstly, for a number of sample orientations an effective model is derived by numerical methods available in the literature. Secondly, to cover a general orientation state, these effective models are interpolated. In this article we develop a novel and effective strategy to carry out this interpolation. Firstly, taking into account symmetry arguments, we reduce the fiber orientation phase space to a triangle in R^2 . For an associated triangulation of this triangle we furnish each node with an surrogate model. Then, we use linear interpolation on the fiber orientation triangle to equip each fiber orientation state with an effective stress. The proposed approach is quite general, and works for any physically nonlinear constitutive law on the micro-scale, as long as surrogate models for single fiber orientation states can be extracted. To demonstrate the capabilities of our scheme we study the viscoelastic creep behavior of short glass fiber reinforced PA66, and use Schapery's collocation method together with FFT-based computational homogenization to derive single orientation state effective models. We discuss the efficient implementation of our method, and present results of a component scale computation on a benchmark component by using ABAQUS ®.

Noise in Neuronal and Electronic Circuits: A General Modeling Framework and Non-Monte Carlo Simulation Techniques.

PubMed

Kilinc, Deniz; Demir, Alper

2017-08-01

The brain is extremely energy efficient and remarkably robust in what it does despite the considerable variability and noise caused by the stochastic mechanisms in neurons and synapses. Computational modeling is a powerful tool that can help us gain insight into this important aspect of brain mechanism. A deep understanding and computational design tools can help develop robust neuromorphic electronic circuits and hybrid neuroelectronic systems. In this paper, we present a general modeling framework for biological neuronal circuits that systematically captures the nonstationary stochastic behavior of ion channels and synaptic processes. In this framework, fine-grained, discrete-state, continuous-time Markov chain models of both ion channels and synaptic processes are treated in a unified manner. Our modeling framework features a mechanism for the automatic generation of the corresponding coarse-grained, continuous-state, continuous-time stochastic differential equation models for neuronal variability and noise. Furthermore, we repurpose non-Monte Carlo noise analysis techniques, which were previously developed for analog electronic circuits, for the stochastic characterization of neuronal circuits both in time and frequency domain. We verify that the fast non-Monte Carlo analysis methods produce results with the same accuracy as computationally expensive Monte Carlo simulations. We have implemented the proposed techniques in a prototype simulator, where both biological neuronal and analog electronic circuits can be simulated together in a coupled manner.

Development of an irrigation scheduling software based on model predicted crop water stress

USDA-ARS?s Scientific Manuscript database

Modern irrigation scheduling methods are generally based on sensor-monitored soil moisture regimes rather than crop water stress which is difficult to measure in real-time, but can be computed using agricultural system models. In this study, an irrigation scheduling software based on RZWQM2 model pr...

Reynolds-Averaged Navier-Stokes Analysis of Zero Efflux Flow Control over a Hump Model

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.

2006-01-01

The unsteady flow over a hump model with zero efflux oscillatory flow control is modeled computationally using the unsteady Reynolds-averaged Navier-Stokes equations. Three different turbulence models produce similar results, and do a reasonably good job predicting the general character of the unsteady surface pressure coefficients during the forced cycle. However, the turbulent shear stresses are underpredicted in magnitude inside the separation bubble, and the computed results predict too large a (mean) separation bubble compared with experiment. These missed predictions are consistent with earlier steady-state results using no-flow-control and steady suction, from a 2004 CFD validation workshop for synthetic jets.

Reynolds-Averaged Navier-Stokes Analysis of Zero Efflux Flow Control Over a Hump Model

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.

2006-01-01

The unsteady flow over a hump model with zero efflux oscillatory flow control is modeled computationally using the unsteady Reynolds-averaged Navier-Stokes equations. Three different turbulence models produce similar results, and do a reasonably good job predicting the general character of the unsteady surface pressure coefficients during the forced cycle. However, the turbulent shear stresses are underpredicted in magnitude inside the separation bubble, and the computed results predict too large a (mean) separation bubble compared with experiment. These missed predictions are consistent with earlier steady-state results using no-flow-control and steady suction, from a 2004 CFD validation workshop for synthetic jets.

Numerical study of a separating and reattaching flow by using Reynolds-stress tubulence closure

NASA Technical Reports Server (NTRS)

Amano, R. S.; Goel, P.

1983-01-01

The numerical study of the Reynolds-stress turbulence closure for separating, reattaching, recirculating and redeveloping flow is summarized. The calculations were made for two different closure models of pressure - strain correlation. The results were compared with the experimental data. Furthermore, these results were compared with the computations made by using the one layer and three layer treatment of k-epsilon turbulence model which were developed. Generally the computations by the Reynolds-stress model show better results than those by the k-epsilon model, in particular, some improvement was noticed in the redeveloping region of the separating and reattaching flow in a pipe with sudden expansion.

Modeled sulfate concentrations in North Dakota streams, 1993-2008, based on spatial basin characteristics

USGS Publications Warehouse

Galloway, Joel M.; Vecchia, Aldo V.

2014-01-01

Modeled sulfate concentrations generally were highest (greater than 750 milligrams per liter) in basins in western North Dakota and lowest (less than 250 milligrams per liter) in basins in the upper Sheyenne River and upper James River. Area-weighted means for the basin characteristics also were computed for 10-digit and 8-digit hydrologic units for streams in North Dakota and modeled sulfate concentrations were computed from the characteristics. The resulting distribution of modeled sulfate concentrations was similar to the distribution of estimates for the 12-digit hydrologic units, but less variable because the basin characteristics were averaged over larger areas.

A Computational Model of Human Table Tennis for Robot Application

NASA Astrophysics Data System (ADS)

Mülling, Katharina; Peters, Jan

Table tennis is a difficult motor skill which requires all basic components of a general motor skill learning system. In order to get a step closer to such a generic approach to the automatic acquisition and refinement of table tennis, we study table tennis from a human motor control point of view. We make use of the basic models of discrete human movement phases, virtual hitting points, and the operational timing hypothesis. Using these components, we create a computational model which is aimed at reproducing human-like behavior. We verify the functionality of this model in a physically realistic simulation of a Barrett WAM.

Temperature dependent nonlinear metal matrix laminae behavior

NASA Technical Reports Server (NTRS)

Barrett, D. J.; Buesking, K. W.

1986-01-01

An analytical method is described for computing the nonlinear thermal and mechanical response of laminated plates. The material model focuses upon the behavior of metal matrix materials by relating the nonlinear composite response to plasticity effects in the matrix. The foundation of the analysis is the unidirectional material model which is used to compute the instantaneous properties of the lamina based upon the properties of the fibers and matrix. The unidirectional model assumes that the fibers properties are constant with temperature and assumes that the matrix can be modelled as a temperature dependent, bilinear, kinematically hardening material. An incremental approach is used to compute average stresses in the fibers and matrix caused by arbitrary mechanical and thermal loads. The layer model is incorporated in an incremental laminated plate theory to compute the nonlinear response of laminated metal matrix composites of general orientation and stacking sequence. The report includes comparisons of the method with other analytical approaches and compares theoretical calculations with measured experimental material behavior. A section is included which describes the limitations of the material model.

Computational Intelligence‐Assisted Understanding of Nature‐Inspired Superhydrophobic Behavior

PubMed Central

Zhang, Xia; Ding, Bei; Dixon, Sebastian C.

2017-01-01

Abstract In recent years, state‐of‐the‐art computational modeling of physical and chemical systems has shown itself to be an invaluable resource in the prediction of the properties and behavior of functional materials. However, construction of a useful computational model for novel systems in both academic and industrial contexts often requires a great depth of physicochemical theory and/or a wealth of empirical data, and a shortage in the availability of either frustrates the modeling process. In this work, computational intelligence is instead used, including artificial neural networks and evolutionary computation, to enhance our understanding of nature‐inspired superhydrophobic behavior. The relationships between experimental parameters (water droplet volume, weight percentage of nanoparticles used in the synthesis of the polymer composite, and distance separating the superhydrophobic surface and the pendant water droplet in adhesive force measurements) and multiple objectives (water droplet contact angle, sliding angle, and adhesive force) are built and weighted. The obtained optimal parameters are consistent with the experimental observations. This new approach to materials modeling has great potential to be applied more generally to aid design, fabrication, and optimization for myriad functional materials. PMID:29375975

Breast tumor malignancy modelling using evolutionary neural logic networks.

PubMed

Tsakonas, Athanasios; Dounias, Georgios; Panagi, Georgia; Panourgias, Evangelia

2006-01-01

The present work proposes a computer assisted methodology for the effective modelling of the diagnostic decision for breast tumor malignancy. The suggested approach is based on innovative hybrid computational intelligence algorithms properly applied in related cytological data contained in past medical records. The experimental data used in this study were gathered in the early 1990s in the University of Wisconsin, based in post diagnostic cytological observations performed by expert medical staff. Data were properly encoded in a computer database and accordingly, various alternative modelling techniques were applied on them, in an attempt to form diagnostic models. Previous methods included standard optimisation techniques, as well as artificial intelligence approaches, in a way that a variety of related publications exists in modern literature on the subject. In this report, a hybrid computational intelligence approach is suggested, which effectively combines modern mathematical logic principles, neural computation and genetic programming in an effective manner. The approach proves promising either in terms of diagnostic accuracy and generalization capabilities, or in terms of comprehensibility and practical importance for the related medical staff.

Fast Learning for Immersive Engagement in Energy Simulations

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

Bush, Brian W; Bugbee, Bruce; Gruchalla, Kenny M

The fast computation which is critical for immersive engagement with and learning from energy simulations would be furthered by developing a general method for creating rapidly computed simplified versions of NREL's computation-intensive energy simulations. Created using machine learning techniques, these 'reduced form' simulations can provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost with response times - typically less than one minute of wall-clock time - suitable for real-time human-in-the-loop design and analysis. Additionally, uncertainty quantification techniques can document the accuracy of the approximate models and their domain of validity. Approximationmore » methods are applicable to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. These reduced-form representations cannot replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and quality assurance for large sets of simulations. We present an overview of the framework and methods we have implemented for developing these reduced-form representations.« less

Computational Intelligence-Assisted Understanding of Nature-Inspired Superhydrophobic Behavior.

PubMed

Zhang, Xia; Ding, Bei; Cheng, Ran; Dixon, Sebastian C; Lu, Yao

2018-01-01

In recent years, state-of-the-art computational modeling of physical and chemical systems has shown itself to be an invaluable resource in the prediction of the properties and behavior of functional materials. However, construction of a useful computational model for novel systems in both academic and industrial contexts often requires a great depth of physicochemical theory and/or a wealth of empirical data, and a shortage in the availability of either frustrates the modeling process. In this work, computational intelligence is instead used, including artificial neural networks and evolutionary computation, to enhance our understanding of nature-inspired superhydrophobic behavior. The relationships between experimental parameters (water droplet volume, weight percentage of nanoparticles used in the synthesis of the polymer composite, and distance separating the superhydrophobic surface and the pendant water droplet in adhesive force measurements) and multiple objectives (water droplet contact angle, sliding angle, and adhesive force) are built and weighted. The obtained optimal parameters are consistent with the experimental observations. This new approach to materials modeling has great potential to be applied more generally to aid design, fabrication, and optimization for myriad functional materials.

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

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less

MODEL DEVELOPMENT AND APPLICATION FOR ASSESSING HUMAN EXPOSURE AND DOSE TO TOXIC CHEMICALS AND POLLUTANTS

EPA Science Inventory

This project aims to strengthen the general scientific foundation of EPA's exposure and risk assessment processes by developing state-of-the-art exposure to dose computational models. This research will produce physiologically-based pharmacokinetic (PBPK) and pharmacodynamic (PD)...

Cartographic Modeling: Computer-assisted Analysis of Spatially Defined Neighborhoods

NASA Technical Reports Server (NTRS)

Berry, J. K.; Tomlin, C. D.

1982-01-01

Cartographic models addressing a wide variety of applications are composed of fundamental map processing operations. These primitive operations are neither data base nor application-specific. By organizing the set of operations into a mathematical-like structure, the basis for a generalized cartographic modeling framework can be developed. Among the major classes of primitive operations are those associated with reclassifying map categories, overlaying maps, determining distance and connectivity, and characterizing cartographic neighborhoods. The conceptual framework of cartographic modeling is established and techniques for characterizing neighborhoods are used as a means of demonstrating some of the more sophisticated procedures of computer-assisted map analysis. A cartographic model for assessing effective roundwood supply is briefly described as an example of a computer analysis. Most of the techniques described have been implemented as part of the map analysis package developed at the Yale School of Forestry and Environmental Studies.

Molecular Dynamics based on a Generalized Born solvation model: application to protein folding

NASA Astrophysics Data System (ADS)

Onufriev, Alexey

2004-03-01

An accurate description of the aqueous environment is essential for realistic biomolecular simulations, but may become very expensive computationally. We have developed a version of the Generalized Born model suitable for describing large conformational changes in macromolecules. The model represents the solvent implicitly as continuum with the dielectric properties of water, and include charge screening effects of salt. The computational cost associated with the use of this model in Molecular Dynamics simulations is generally considerably smaller than the cost of representing water explicitly. Also, compared to traditional Molecular Dynamics simulations based on explicit water representation, conformational changes occur much faster in implicit solvation environment due to the absence of viscosity. The combined speed-up allow one to probe conformational changes that occur on much longer effective time-scales. We apply the model to folding of a 46-residue three helix bundle protein (residues 10-55 of protein A, PDB ID 1BDD). Starting from an unfolded structure at 450 K, the protein folds to the lowest energy state in 6 ns of simulation time, which takes about a day on a 16 processor SGI machine. The predicted structure differs from the native one by 2.4 A (backbone RMSD). Analysis of the structures seen on the folding pathway reveals details of the folding process unavailable form experiment.

A geostationary Earth orbit satellite model using Easy Java Simulation

NASA Astrophysics Data System (ADS)

Wee, Loo Kang; Hwee Goh, Giam

2013-01-01

We develop an Easy Java Simulation (EJS) model for students to visualize geostationary orbits near Earth, modelled using a Java 3D implementation of the EJS 3D library. The simplified physics model is described and simulated using a simple constant angular velocity equation. We discuss four computer model design ideas: (1) a simple and realistic 3D view and associated learning in the real world; (2) comparative visualization of permanent geostationary satellites; (3) examples of non-geostationary orbits of different rotation senses, periods and planes; and (4) an incorrect physics model for conceptual discourse. General feedback from the students has been relatively positive, and we hope teachers will find the computer model useful in their own classes.

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

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

Lehman, Tom; Yang, Xi

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyber infrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum ofmore » compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyber infrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate, maintain, and distribute MRML based resource descriptions. Once all of the resource topologies are absorbed by the RCE, a connected graph of the full distributed system topology is constructed, which forms the basis for computation and workflow processing. The RCE includes a Modular Computation Element (MCE) framework which allows for tailoring of the computation process to the specific set of resources under control, and the services desired. The input and output of an MCE are both model data based on MRS/MRML ontology and schema. Some of the RAINS project accomplishments include: Development of general and extensible multi-resource modeling framework; Design of a Resource Computation Engine (RCE) system which includes the following key capabilities; Absorb a variety of multi-resource model types and build integrated models; Novel architecture which uses model based communications across the full stack for all Flexible provision of abstract or intent based user facing interfaces; Workflow processing based on model descriptions; Release of the RCE as an open source software; Deployment of RCE in the University of Maryland/Mid-Atlantic Crossroad ScienceDMZ in prototype mode with a plan under way to transition to production; Deployment at the Argonne National Laboratory DTN Facility in prototype mode; Selection of RCE by the DOE SENSE (SDN for End-to-end Networked Science at the Exascale) project as the basis for their orchestration service.« less

Effective description of general extensions of the Standard Model: the complete tree-level dictionary

NASA Astrophysics Data System (ADS)

de Blas, J.; Criado, J. C.; Pérez-Victoria, M.; Santiago, J.

2018-03-01

We compute all the tree-level contributions to the Wilson coefficients of the dimension-six Standard-Model effective theory in ultraviolet completions with general scalar, spinor and vector field content and arbitrary interactions. No assumption about the renormalizability of the high-energy theory is made. This provides a complete ultraviolet/infrared dictionary at the classical level, which can be used to study the low-energy implications of any model of interest, and also to look for explicit completions consistent with low-energy data.

The Fermi-Pasta-Ulam Problem and Its Underlying Integrable Dynamics: An Approach Through Lyapunov Exponents

NASA Astrophysics Data System (ADS)

Benettin, G.; Pasquali, S.; Ponno, A.

2018-05-01

FPU models, in dimension one, are perturbations either of the linear model or of the Toda model; perturbations of the linear model include the usual β -model, perturbations of Toda include the usual α +β model. In this paper we explore and compare two families, or hierarchies, of FPU models, closer and closer to either the linear or the Toda model, by computing numerically, for each model, the maximal Lyapunov exponent χ . More precisely, we consider statistically typical trajectories and study the asymptotics of χ for large N (the number of particles) and small ɛ (the specific energy E / N), and find, for all models, asymptotic power laws χ ˜eq Cɛ ^a, C and a depending on the model. The asymptotics turns out to be, in general, rather slow, and producing accurate results requires a great computational effort. We also revisit and extend the analytic computation of χ introduced by Casetti, Livi and Pettini, originally formulated for the β -model. With great evidence the theory extends successfully to all models of the linear hierarchy, but not to models close to Toda.

Cielo Computational Environment Usage Model With Mappings to ACE Requirements for the General Availability User Environment Capabilities Release Version 1.1

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

Vigil,Benny Manuel; Ballance, Robert; Haskell, Karen

Cielo is a massively parallel supercomputer funded by the DOE/NNSA Advanced Simulation and Computing (ASC) program, and operated by the Alliance for Computing at Extreme Scale (ACES), a partnership between Los Alamos National Laboratory (LANL) and Sandia National Laboratories (SNL). The primary Cielo compute platform is physically located at Los Alamos National Laboratory. This Cielo Computational Environment Usage Model documents the capabilities and the environment to be provided for the Q1 FY12 Level 2 Cielo Capability Computing (CCC) Platform Production Readiness Milestone. This document describes specific capabilities, tools, and procedures to support both local and remote users. The model ismore » focused on the needs of the ASC user working in the secure computing environments at Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory, or Sandia National Laboratories, but also addresses the needs of users working in the unclassified environment. The Cielo Computational Environment Usage Model maps the provided capabilities to the tri-Lab ASC Computing Environment (ACE) Version 8.0 requirements. The ACE requirements reflect the high performance computing requirements for the Production Readiness Milestone user environment capabilities of the ASC community. A description of ACE requirements met, and those requirements that are not met, are included in each section of this document. The Cielo Computing Environment, along with the ACE mappings, has been issued and reviewed throughout the tri-Lab community.« less

Editorial: Computational Creativity, Concept Invention, and General Intelligence

NASA Astrophysics Data System (ADS)

Besold, Tarek R.; Kühnberger, Kai-Uwe; Veale, Tony

2015-12-01

Over the last decade, computational creativity as a field of scientific investigation and computational systems engineering has seen growing popularity. Still, the levels of development between projects aiming at systems for artistic production or performance and endeavours addressing creative problem-solving or models of creative cognitive capacities is diverging. While the former have already seen several great successes, the latter still remain in their infancy. This volume collects reports on work trying to close the accrued gap.

Overview of Threats and Failure Models for Safety-Relevant Computer-Based Systems

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2015-01-01

This document presents a high-level overview of the threats to safety-relevant computer-based systems, including (1) a description of the introduction and activation of physical and logical faults; (2) the propagation of their effects; and (3) function-level and component-level error and failure mode models. These models can be used in the definition of fault hypotheses (i.e., assumptions) for threat-risk mitigation strategies. This document is a contribution to a guide currently under development that is intended to provide a general technical foundation for designers and evaluators of safety-relevant systems.

A study of reacting free and ducted hydrogen/air jets

NASA Technical Reports Server (NTRS)

Beach, H. L., Jr.

1975-01-01

The mixing and reaction of a supersonic jet of hydrogen in coaxial free and ducted high temperature test gases were investigated. The importance of chemical kinetics on computed results, and the utilization of free-jet theoretical approaches to compute enclosed flow fields were studied. Measured pitot pressure profiles were correlated by use of a parabolic mixing analysis employing an eddy viscosity model. All computations, including free, ducted, reacting, and nonreacting cases, use the same value of the empirical constant in the viscosity model. Equilibrium and finite rate chemistry models were utilized. The finite rate assumption allowed prediction of observed ignition delay, but the equilibrium model gave the best correlations downstream from the ignition location. Ducted calculations were made with finite rate chemistry; correlations were, in general, as good as the free-jet results until problems with the boundary conditions were encountered.

Discrete element weld model, phase 2

NASA Technical Reports Server (NTRS)

Prakash, C.; Samonds, M.; Singhal, A. K.

1987-01-01

A numerical method was developed for analyzing the tungsten inert gas (TIG) welding process. The phenomena being modeled include melting under the arc and the flow in the melt under the action of buoyancy, surface tension, and electromagnetic forces. The latter entails the calculation of the electric potential and the computation of electric current and magnetic field therefrom. Melting may occur at a single temperature or over a temperature range, and the electrical and thermal conductivities can be a function of temperature. Results of sample calculations are presented and discussed at length. A major research contribution has been the development of numerical methodology for the calculation of phase change problems in a fixed grid framework. The model has been implemented on CHAM's general purpose computer code PHOENICS. The inputs to the computer model include: geometric parameters, material properties, and weld process parameters.

Center for Parallel Optimization.

DTIC Science & Technology

1996-03-19

A NEW OPTIMIZATION BASED APPROACH TO IMPROVING GENERALIZATION IN MACHINE LEARNING HAS BEEN PROPOSED AND COMPUTATIONALLY VALIDATED ON SIMPLE LINEAR MODELS AS WELL AS ON HIGHLY NONLINEAR SYSTEMS SUCH AS NEURAL NETWORKS.

Algorithms for Efficient Computation of Transfer Functions for Large Order Flexible Systems

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Giesy, Daniel P.

1998-01-01

An efficient and robust computational scheme is given for the calculation of the frequency response function of a large order, flexible system implemented with a linear, time invariant control system. Advantage is taken of the highly structured sparsity of the system matrix of the plant based on a model of the structure using normal mode coordinates. The computational time per frequency point of the new computational scheme is a linear function of system size, a significant improvement over traditional, still-matrix techniques whose computational times per frequency point range from quadratic to cubic functions of system size. This permits the practical frequency domain analysis of systems of much larger order than by traditional, full-matrix techniques. Formulations are given for both open- and closed-loop systems. Numerical examples are presented showing the advantages of the present formulation over traditional approaches, both in speed and in accuracy. Using a model with 703 structural modes, the present method was up to two orders of magnitude faster than a traditional method. The present method generally showed good to excellent accuracy throughout the range of test frequencies, while traditional methods gave adequate accuracy for lower frequencies, but generally deteriorated in performance at higher frequencies with worst case errors being many orders of magnitude times the correct values.

Fault management for data systems

NASA Technical Reports Server (NTRS)

Boyd, Mark A.; Iverson, David L.; Patterson-Hine, F. Ann

1993-01-01

Issues related to automating the process of fault management (fault diagnosis and response) for data management systems are considered. Substantial benefits are to be gained by successful automation of this process, particularly for large, complex systems. The use of graph-based models to develop a computer assisted fault management system is advocated. The general problem is described and the motivation behind choosing graph-based models over other approaches for developing fault diagnosis computer programs is outlined. Some existing work in the area of graph-based fault diagnosis is reviewed, and a new fault management method which was developed from existing methods is offered. Our method is applied to an automatic telescope system intended as a prototype for future lunar telescope programs. Finally, an application of our method to general data management systems is described.

Nonlinear dynamics of laser systems with elements of a chaos: Advanced computational code

NASA Astrophysics Data System (ADS)

Buyadzhi, V. V.; Glushkov, A. V.; Khetselius, O. Yu; Kuznetsova, A. A.; Buyadzhi, A. A.; Prepelitsa, G. P.; Ternovsky, V. B.

2017-10-01

A general, uniform chaos-geometric computational approach to analysis, modelling and prediction of the non-linear dynamics of quantum and laser systems (laser and quantum generators system etc) with elements of the deterministic chaos is briefly presented. The approach is based on using the advanced generalized techniques such as the wavelet analysis, multi-fractal formalism, mutual information approach, correlation integral analysis, false nearest neighbour algorithm, the Lyapunov’s exponents analysis, and surrogate data method, prediction models etc There are firstly presented the numerical data on the topological and dynamical invariants (in particular, the correlation, embedding, Kaplan-York dimensions, the Lyapunov’s exponents, Kolmogorov’s entropy and other parameters) for laser system (the semiconductor GaAs/GaAlAs laser with a retarded feedback) dynamics in a chaotic and hyperchaotic regimes.

A Computational Model of Public Support for Insurgency and Terrorism: A Prototype for More-General Social-Science Modeling

DTIC Science & Technology

2013-01-01

PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) RAND...prototype model illustrating concretely a new approach. The prototype model itself should be seen not as a definitive end point, but rather as a...9 1 4 8 1 4 8 1 1 1 1 2 2 1 2 2 2 8 9 2 8 9 3 9 9 2 8 8 2 8 9 2 9 9 1 1 3 1 2 4 1 2 4 xviii A Computational Model of Public Support for Insurgency

Generalization techniques to reduce the number of volume elements for terrain effect calculations in fully analytical gravitational modelling

NASA Astrophysics Data System (ADS)

Benedek, Judit; Papp, Gábor; Kalmár, János

2018-04-01

Beyond rectangular prism polyhedron, as a discrete volume element, can also be used to model the density distribution inside 3D geological structures. The calculation of the closed formulae given for the gravitational potential and its higher-order derivatives, however, needs twice more runtime than that of the rectangular prism computations. Although the more detailed the better principle is generally accepted it is basically true only for errorless data. As soon as errors are present any forward gravitational calculation from the model is only a possible realization of the true force field on the significance level determined by the errors. So if one really considers the reliability of input data used in the calculations then sometimes the "less" can be equivalent to the "more" in statistical sense. As a consequence the processing time of the related complex formulae can be significantly reduced by the optimization of the number of volume elements based on the accuracy estimates of the input data. New algorithms are proposed to minimize the number of model elements defined both in local and in global coordinate systems. Common gravity field modelling programs generate optimized models for every computation points ( dynamic approach), whereas the static approach provides only one optimized model for all. Based on the static approach two different algorithms were developed. The grid-based algorithm starts with the maximum resolution polyhedral model defined by 3-3 points of each grid cell and generates a new polyhedral surface defined by points selected from the grid. The other algorithm is more general; it works also for irregularly distributed data (scattered points) connected by triangulation. Beyond the description of the optimization schemes some applications of these algorithms in regional and local gravity field modelling are presented too. The efficiency of the static approaches may provide even more than 90% reduction in computation time in favourable situation without the loss of reliability of the calculated gravity field parameters.

Nature as a network of morphological infocomputational processes for cognitive agents

NASA Astrophysics Data System (ADS)

Dodig-Crnkovic, Gordana

2017-01-01

This paper presents a view of nature as a network of infocomputational agents organized in a dynamical hierarchy of levels. It provides a framework for unification of currently disparate understandings of natural, formal, technical, behavioral and social phenomena based on information as a structure, differences in one system that cause the differences in another system, and computation as its dynamics, i.e. physical process of morphological change in the informational structure. We address some of the frequent misunderstandings regarding the natural/morphological computational models and their relationships to physical systems, especially cognitive systems such as living beings. Natural morphological infocomputation as a conceptual framework necessitates generalization of models of computation beyond the traditional Turing machine model presenting symbol manipulation, and requires agent-based concurrent resource-sensitive models of computation in order to be able to cover the whole range of phenomena from physics to cognition. The central role of agency, particularly material vs. cognitive agency is highlighted.

High performance hybrid functional Petri net simulations of biological pathway models on CUDA.

PubMed

Chalkidis, Georgios; Nagasaki, Masao; Miyano, Satoru

2011-01-01

Hybrid functional Petri nets are a wide-spread tool for representing and simulating biological models. Due to their potential of providing virtual drug testing environments, biological simulations have a growing impact on pharmaceutical research. Continuous research advancements in biology and medicine lead to exponentially increasing simulation times, thus raising the demand for performance accelerations by efficient and inexpensive parallel computation solutions. Recent developments in the field of general-purpose computation on graphics processing units (GPGPU) enabled the scientific community to port a variety of compute intensive algorithms onto the graphics processing unit (GPU). This work presents the first scheme for mapping biological hybrid functional Petri net models, which can handle both discrete and continuous entities, onto compute unified device architecture (CUDA) enabled GPUs. GPU accelerated simulations are observed to run up to 18 times faster than sequential implementations. Simulating the cell boundary formation by Delta-Notch signaling on a CUDA enabled GPU results in a speedup of approximately 7x for a model containing 1,600 cells.

A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence.

PubMed

Nikoloulopoulos, Aristidis K

2017-10-01

A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that it is superior to the standard generalized linear mixed model in this context. Here, we call trivariate vine copulas to extend the bivariate meta-analysis of diagnostic test accuracy studies by accounting for disease prevalence. Our vine copula mixed model includes the trivariate generalized linear mixed model as a special case and can also operate on the original scale of sensitivity, specificity, and disease prevalence. Our general methodology is illustrated by re-analyzing the data of two published meta-analyses. Our study suggests that there can be an improvement on trivariate generalized linear mixed model in fit to data and makes the argument for moving to vine copula random effects models especially because of their richness, including reflection asymmetric tail dependence, and computational feasibility despite their three dimensionality.

Self-evaluation of decision-making: A general Bayesian framework for metacognitive computation.

PubMed

Fleming, Stephen M; Daw, Nathaniel D

2017-01-01

People are often aware of their mistakes, and report levels of confidence in their choices that correlate with objective performance. These metacognitive assessments of decision quality are important for the guidance of behavior, particularly when external feedback is absent or sporadic. However, a computational framework that accounts for both confidence and error detection is lacking. In addition, accounts of dissociations between performance and metacognition have often relied on ad hoc assumptions, precluding a unified account of intact and impaired self-evaluation. Here we present a general Bayesian framework in which self-evaluation is cast as a "second-order" inference on a coupled but distinct decision system, computationally equivalent to inferring the performance of another actor. Second-order computation may ensue whenever there is a separation between internal states supporting decisions and confidence estimates over space and/or time. We contrast second-order computation against simpler first-order models in which the same internal state supports both decisions and confidence estimates. Through simulations we show that second-order computation provides a unified account of different types of self-evaluation often considered in separate literatures, such as confidence and error detection, and generates novel predictions about the contribution of one's own actions to metacognitive judgments. In addition, the model provides insight into why subjects' metacognition may sometimes be better or worse than task performance. We suggest that second-order computation may underpin self-evaluative judgments across a range of domains. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Self-Evaluation of Decision-Making: A General Bayesian Framework for Metacognitive Computation

PubMed Central

2017-01-01

People are often aware of their mistakes, and report levels of confidence in their choices that correlate with objective performance. These metacognitive assessments of decision quality are important for the guidance of behavior, particularly when external feedback is absent or sporadic. However, a computational framework that accounts for both confidence and error detection is lacking. In addition, accounts of dissociations between performance and metacognition have often relied on ad hoc assumptions, precluding a unified account of intact and impaired self-evaluation. Here we present a general Bayesian framework in which self-evaluation is cast as a “second-order” inference on a coupled but distinct decision system, computationally equivalent to inferring the performance of another actor. Second-order computation may ensue whenever there is a separation between internal states supporting decisions and confidence estimates over space and/or time. We contrast second-order computation against simpler first-order models in which the same internal state supports both decisions and confidence estimates. Through simulations we show that second-order computation provides a unified account of different types of self-evaluation often considered in separate literatures, such as confidence and error detection, and generates novel predictions about the contribution of one’s own actions to metacognitive judgments. In addition, the model provides insight into why subjects’ metacognition may sometimes be better or worse than task performance. We suggest that second-order computation may underpin self-evaluative judgments across a range of domains. PMID:28004960

Dental application of novel finite element analysis software for three-dimensional finite element modeling of a dentulous mandible from its computed tomography images.

PubMed

Nakamura, Keiko; Tajima, Kiyoshi; Chen, Ker-Kong; Nagamatsu, Yuki; Kakigawa, Hiroshi; Masumi, Shin-ich

2013-12-01

This study focused on the application of novel finite-element analysis software for constructing a finite-element model from the computed tomography data of a human dentulous mandible. The finite-element model is necessary for evaluating the mechanical response of the alveolar part of the mandible, resulting from occlusal force applied to the teeth during biting. Commercially available patient-specific general computed tomography-based finite-element analysis software was solely applied to the finite-element analysis for the extraction of computed tomography data. The mandibular bone with teeth was extracted from the original images. Both the enamel and the dentin were extracted after image processing, and the periodontal ligament was created from the segmented dentin. The constructed finite-element model was reasonably accurate using a total of 234,644 nodes and 1,268,784 tetrahedral and 40,665 shell elements. The elastic moduli of the heterogeneous mandibular bone were determined from the bone density data of the computed tomography images. The results suggested that the software applied in this study is both useful and powerful for creating a more accurate three-dimensional finite-element model of a dentulous mandible from the computed tomography data without the need for any other software.

In vitro molecular machine learning algorithm via symmetric internal loops of DNA.

PubMed

Lee, Ji-Hoon; Lee, Seung Hwan; Baek, Christina; Chun, Hyosun; Ryu, Je-Hwan; Kim, Jin-Woo; Deaton, Russell; Zhang, Byoung-Tak

2017-08-01

Programmable biomolecules, such as DNA strands, deoxyribozymes, and restriction enzymes, have been used to solve computational problems, construct large-scale logic circuits, and program simple molecular games. Although studies have shown the potential of molecular computing, the capability of computational learning with DNA molecules, i.e., molecular machine learning, has yet to be experimentally verified. Here, we present a novel molecular learning in vitro model in which symmetric internal loops of double-stranded DNA are exploited to measure the differences between training instances, thus enabling the molecules to learn from small errors. The model was evaluated on a data set of twenty dialogue sentences obtained from the television shows Friends and Prison Break. The wet DNA-computing experiments confirmed that the molecular learning machine was able to generalize the dialogue patterns of each show and successfully identify the show from which the sentences originated. The molecular machine learning model described here opens the way for solving machine learning problems in computer science and biology using in vitro molecular computing with the data encoded in DNA molecules. Copyright © 2017. Published by Elsevier B.V.

Generalized Ordinary Differential Equation Models 1

PubMed Central

Miao, Hongyu; Wu, Hulin; Xue, Hongqi

2014-01-01

Existing estimation methods for ordinary differential equation (ODE) models are not applicable to discrete data. The generalized ODE (GODE) model is therefore proposed and investigated for the first time. We develop the likelihood-based parameter estimation and inference methods for GODE models. We propose robust computing algorithms and rigorously investigate the asymptotic properties of the proposed estimator by considering both measurement errors and numerical errors in solving ODEs. The simulation study and application of our methods to an influenza viral dynamics study suggest that the proposed methods have a superior performance in terms of accuracy over the existing ODE model estimation approach and the extended smoothing-based (ESB) method. PMID:25544787

Generalized Ordinary Differential Equation Models.

PubMed

Miao, Hongyu; Wu, Hulin; Xue, Hongqi

2014-10-01

Existing estimation methods for ordinary differential equation (ODE) models are not applicable to discrete data. The generalized ODE (GODE) model is therefore proposed and investigated for the first time. We develop the likelihood-based parameter estimation and inference methods for GODE models. We propose robust computing algorithms and rigorously investigate the asymptotic properties of the proposed estimator by considering both measurement errors and numerical errors in solving ODEs. The simulation study and application of our methods to an influenza viral dynamics study suggest that the proposed methods have a superior performance in terms of accuracy over the existing ODE model estimation approach and the extended smoothing-based (ESB) method.

Models@Home: distributed computing in bioinformatics using a screensaver based approach.

PubMed

Krieger, Elmar; Vriend, Gert

2002-02-01

Due to the steadily growing computational demands in bioinformatics and related scientific disciplines, one is forced to make optimal use of the available resources. A straightforward solution is to build a network of idle computers and let each of them work on a small piece of a scientific challenge, as done by Seti@Home (http://setiathome.berkeley.edu), the world's largest distributed computing project. We developed a generally applicable distributed computing solution that uses a screensaver system similar to Seti@Home. The software exploits the coarse-grained nature of typical bioinformatics projects. Three major considerations for the design were: (1) often, many different programs are needed, while the time is lacking to parallelize them. Models@Home can run any program in parallel without modifications to the source code; (2) in contrast to the Seti project, bioinformatics applications are normally more sensitive to lost jobs. Models@Home therefore includes stringent control over job scheduling; (3) to allow use in heterogeneous environments, Linux and Windows based workstations can be combined with dedicated PCs to build a homogeneous cluster. We present three practical applications of Models@Home, running the modeling programs WHAT IF and YASARA on 30 PCs: force field parameterization, molecular dynamics docking, and database maintenance.

The Cognitive, Perceptual, and Neural Bases of Skilled Performance

DTIC Science & Technology

1988-09-01

shunting, masking field, bidirectional associative memory, Volterra - Lotka , Gilpin-Ayala, ani Eigen-Schuster models. The Cohen-Grossberg model thus...field, bidirectional associative memory, Volterra - Lotka , Gilpin-Ayala, and Eigen-Schuster models. A Liapunov functional method is described for...storage by neural networks: A general model and global Liapunov method. In E.L. Schwartz (Ed.), Computational neuroscience. Cambridge, MA: MIT Press

Efficient Transition Probability Computation for Continuous-Time Branching Processes via Compressed Sensing.

PubMed

Xu, Jason; Minin, Vladimir N

2015-07-01

Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the discrete state space is large or uncountable. Classical methods such as matrix exponentiation are infeasible for large or countably infinite state spaces, and sampling-based alternatives are computationally intensive, requiring integration over all possible hidden events. Recent work has successfully applied generating function techniques to computing transition probabilities for linear multi-type branching processes. While these techniques often require significantly fewer computations than matrix exponentiation, they also become prohibitive in applications with large populations. We propose a compressed sensing framework that significantly accelerates the generating function method, decreasing computational cost up to a logarithmic factor by only assuming the probability mass of transitions is sparse. We demonstrate accurate and efficient transition probability computations in branching process models for blood cell formation and evolution of self-replicating transposable elements in bacterial genomes.

Efficient Transition Probability Computation for Continuous-Time Branching Processes via Compressed Sensing

PubMed Central

Xu, Jason; Minin, Vladimir N.

2016-01-01

Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the discrete state space is large or uncountable. Classical methods such as matrix exponentiation are infeasible for large or countably infinite state spaces, and sampling-based alternatives are computationally intensive, requiring integration over all possible hidden events. Recent work has successfully applied generating function techniques to computing transition probabilities for linear multi-type branching processes. While these techniques often require significantly fewer computations than matrix exponentiation, they also become prohibitive in applications with large populations. We propose a compressed sensing framework that significantly accelerates the generating function method, decreasing computational cost up to a logarithmic factor by only assuming the probability mass of transitions is sparse. We demonstrate accurate and efficient transition probability computations in branching process models for blood cell formation and evolution of self-replicating transposable elements in bacterial genomes. PMID:26949377

Modeling the missile-launch tube problem in DYSCO

NASA Technical Reports Server (NTRS)

Berman, Alex; Gustavson, Bruce A.

1989-01-01

DYSCO is a versatile, general purpose dynamic analysis program which assembles equations and solves dynamics problems. The executive manages a library of technology modules which contain routines that compute the matrix coefficients of the second order ordinary differential equations of the components. The executive performs the coupling of the equations of the components and manages the solution of the coupled equations. Any new component representation may be added to the library if, given the state vector, a FORTRAN program can be written to compute M, C, K, and F. The problem described demonstrates the generality of this statement.

A comparative study of spherical and flat-Earth geopotential modeling at satellite elevations

NASA Technical Reports Server (NTRS)

Parrott, M. H.; Hinze, W. J.; Braile, L. W.; Vonfrese, R. R. B.

1985-01-01

Flat-Earth modeling is a desirable alternative to the complex spherical-Earth modeling process. These methods were compared using 2 1/2 dimensional flat-earth and spherical modeling to compute gravity and scalar magnetic anomalies along profiles perpendicular to the strike of variably dimensioned rectangular prisms at altitudes of 150, 300, and 450 km. Comparison was achieved with percent error computations (spherical-flat/spherical) at critical anomaly points. At the peak gravity anomaly value, errors are less than + or - 5% for all prisms. At 1/2 and 1/10 of the peak, errors are generally less than 10% and 40% respectively, increasing to these values with longer and wider prisms at higher altitudes. For magnetics, the errors at critical anomaly points are less than -10% for all prisms, attaining these magnitudes with longer and wider prisms at higher altitudes. In general, in both gravity and magnetic modeling, errors increase greatly for prisms wider than 500 km, although gravity modeling is more sensitive than magnetic modeling to spherical-Earth effects. Preliminary modeling of both satellite gravity and magnetic anomalies using flat-Earth assumptions is justified considering the errors caused by uncertainties in isolating anomalies.

Optimizing Spectral Wave Estimates with Adjoint-Based Sensitivity Maps

DTIC Science & Technology

2014-02-18

J, Orzech MD, Ngodock HE (2013) Validation of a wave data assimilation system based on SWAN. Geophys Res Abst, (15), EGU2013-5951-1, EGU General ...surface wave spectra. Sensitivity maps are generally constructed for a selected system indicator (e.g., vorticity) by computing the differential of...spectral action balance Eq. 2, generally initialized at the off- shore boundary with spectral wave and other outputs from regional models such as

Using soft computing techniques to predict corrected air permeability using Thomeer parameters, air porosity and grain density

NASA Astrophysics Data System (ADS)

Nooruddin, Hasan A.; Anifowose, Fatai; Abdulraheem, Abdulazeez

2014-03-01

Soft computing techniques are recently becoming very popular in the oil industry. A number of computational intelligence-based predictive methods have been widely applied in the industry with high prediction capabilities. Some of the popular methods include feed-forward neural networks, radial basis function network, generalized regression neural network, functional networks, support vector regression and adaptive network fuzzy inference system. A comparative study among most popular soft computing techniques is presented using a large dataset published in literature describing multimodal pore systems in the Arab D formation. The inputs to the models are air porosity, grain density, and Thomeer parameters obtained using mercury injection capillary pressure profiles. Corrected air permeability is the target variable. Applying developed permeability models in recent reservoir characterization workflow ensures consistency between micro and macro scale information represented mainly by Thomeer parameters and absolute permeability. The dataset was divided into two parts with 80% of data used for training and 20% for testing. The target permeability variable was transformed to the logarithmic scale as a pre-processing step and to show better correlations with the input variables. Statistical and graphical analysis of the results including permeability cross-plots and detailed error measures were created. In general, the comparative study showed very close results among the developed models. The feed-forward neural network permeability model showed the lowest average relative error, average absolute relative error, standard deviations of error and root means squares making it the best model for such problems. Adaptive network fuzzy inference system also showed very good results.

Training in Methods in Computational Neuroscience

DTIC Science & Technology

1992-08-29

in Tritonia. Roger Traub Models with realistic neurons , with an emphasis on large-scale modeling of epileptic phenomena in hippocampus. Rodolpho...Cell Model Plan: 1) Convert some of my simulations from NEURON to GENESIS (and thus learn GENESIS). 2) Develop a realistic inhibtory model . 3) Further...General Hospital, MA Course Project: Membrane Properties of a Neostriatal Neuron and Dopamine Modulation The purpose of my project was to model the

Implementing vertex dynamics models of cell populations in biology within a consistent computational framework.

PubMed

Fletcher, Alexander G; Osborne, James M; Maini, Philip K; Gavaghan, David J

2013-11-01

The dynamic behaviour of epithelial cell sheets plays a central role during development, growth, disease and wound healing. These processes occur as a result of cell adhesion, migration, division, differentiation and death, and involve multiple processes acting at the cellular and molecular level. Computational models offer a useful means by which to investigate and test hypotheses about these processes, and have played a key role in the study of cell-cell interactions. However, the necessarily complex nature of such models means that it is difficult to make accurate comparison between different models, since it is often impossible to distinguish between differences in behaviour that are due to the underlying model assumptions, and those due to differences in the in silico implementation of the model. In this work, an approach is described for the implementation of vertex dynamics models, a discrete approach that represents each cell by a polygon (or polyhedron) whose vertices may move in response to forces. The implementation is undertaken in a consistent manner within a single open source computational framework, Chaste, which comprises fully tested, industrial-grade software that has been developed using an agile approach. This framework allows one to easily change assumptions regarding force generation and cell rearrangement processes within these models. The versatility and generality of this framework is illustrated using a number of biological examples. In each case we provide full details of all technical aspects of our model implementations, and in some cases provide extensions to make the models more generally applicable. Copyright © 2013 Elsevier Ltd. All rights reserved.

The European computer model for optronic system performance prediction (ECOMOS)

NASA Astrophysics Data System (ADS)

Keßler, Stefan; Bijl, Piet; Labarre, Luc; Repasi, Endre; Wittenstein, Wolfgang; Bürsing, Helge

2017-10-01

ECOMOS is a multinational effort within the framework of an EDA Project Arrangement. Its aim is to provide a generally accepted and harmonized European computer model for computing nominal Target Acquisition (TA) ranges of optronic imagers operating in the Visible or thermal Infrared (IR). The project involves close co-operation of defence and security industry and public research institutes from France, Germany, Italy, The Netherlands and Sweden. ECOMOS uses and combines well-accepted existing European tools to build up a strong competitive position. This includes two TA models: the analytical TRM4 model and the image-based TOD model. In addition, it uses the atmosphere model MATISSE. In this paper, the central idea of ECOMOS is exposed. The overall software structure and the underlying models are shown and elucidated. The status of the project development is given as well as a short discussion of validation tests and an outlook on the future potential of simulation for sensor assessment.

Digital Simulation and Modelling.

ERIC Educational Resources Information Center

Hawthorne, G. B., Jr.

A basically tutorial point of view is taken in this general discussion. The author examines the basic concepts and principles of simulation and modelling and the application of digital computers to these tasks. Examples of existing simulations, a discussion of the applicability and feasibility of simulation studies, a review of simulation…

N = 1 supersymmetric indices and the four-dimensional A-model

NASA Astrophysics Data System (ADS)

Closset, Cyril; Kim, Heeyeon; Willett, Brian

2017-08-01

We compute the supersymmetric partition function of N = 1 supersymmetric gauge theories with an R-symmetry on M_4\\cong M_{g,p}× {S}^1 , a principal elliptic fiber bundle of degree p over a genus- g Riemann surface, Σ g . Equivalently, we compute the generalized supersymmetric index I_{M}{_{g,p}, with the supersymmetric three-manifold M_{g,p} as the spatial slice. The ordinary N = 1 supersymmetric index on the round three-sphere is recovered as a special case. We approach this computation from the point of view of a topological A-model for the abelianized gauge fields on the base Σ g . This A-model — or A-twisted two-dimensional N = (2 , 2) gauge theory — encodes all the information about the generalized indices, which are viewed as expectations values of some canonically-defined surface defects wrapped on T 2 inside Σ g × T 2. Being defined by compactification on the torus, the A-model also enjoys natural modular properties, governed by the four-dimensional 't Hooft anomalies. As an application of our results, we provide new tests of Seiberg duality. We also present a new evaluation formula for the three-sphere index as a sum over two-dimensional vacua.

STARS: An integrated general-purpose finite element structural, aeroelastic, and aeroservoelastic analysis computer program

NASA Technical Reports Server (NTRS)

Gupta, Kajal K.

1991-01-01

The details of an integrated general-purpose finite element structural analysis computer program which is also capable of solving complex multidisciplinary problems is presented. Thus, the SOLIDS module of the program possesses an extensive finite element library suitable for modeling most practical problems and is capable of solving statics, vibration, buckling, and dynamic response problems of complex structures, including spinning ones. The aerodynamic module, AERO, enables computation of unsteady aerodynamic forces for both subsonic and supersonic flow for subsequent flutter and divergence analysis of the structure. The associated aeroservoelastic analysis module, ASE, effects aero-structural-control stability analysis yielding frequency responses as well as damping characteristics of the structure. The program is written in standard FORTRAN to run on a wide variety of computers. Extensive graphics, preprocessing, and postprocessing routines are also available pertaining to a number of terminals.

Type I Error Inflation in the Traditional By-Participant Analysis to Metamemory Accuracy: A Generalized Mixed-Effects Model Perspective

ERIC Educational Resources Information Center

Murayama, Kou; Sakaki, Michiko; Yan, Veronica X.; Smith, Garry M.

2014-01-01

In order to examine metacognitive accuracy (i.e., the relationship between metacognitive judgment and memory performance), researchers often rely on by-participant analysis, where metacognitive accuracy (e.g., resolution, as measured by the gamma coefficient or signal detection measures) is computed for each participant and the computed values are…

PROTEUS two-dimensional Navier-Stokes computer code, version 1.0. Volume 2: User's guide

NASA Technical Reports Server (NTRS)

Towne, Charles E.; Schwab, John R.; Benson, Thomas J.; Suresh, Ambady

1990-01-01

A new computer code was developed to solve the two-dimensional or axisymmetric, Reynolds averaged, unsteady compressible Navier-Stokes equations in strong conservation law form. The thin-layer or Euler equations may also be solved. Turbulence is modeled using an algebraic eddy viscosity model. The objective was to develop a code for aerospace applications that is easy to use and easy to modify. Code readability, modularity, and documentation were emphasized. The equations are written in nonorthogonal body-fitted coordinates, and solved by marching in time using a fully-coupled alternating direction-implicit procedure with generalized first- or second-order time differencing. All terms are linearized using second-order Taylor series. The boundary conditions are treated implicitly, and may be steady, unsteady, or spatially periodic. Simple Cartesian or polar grids may be generated internally by the program. More complex geometries require an externally generated computational coordinate system. The documentation is divided into three volumes. Volume 2 is the User's Guide, and describes the program's general features, the input and output, the procedure for setting up initial conditions, the computer resource requirements, the diagnostic messages that may be generated, the job control language used to run the program, and several test cases.

Migration without migraines

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

Lines, L.; Burton, A.; Lu, H.X.

Accurate velocity models are a necessity for reliable migration results. Velocity analysis generally involves the use of methods such as normal moveout analysis (NMO), seismic traveltime tomography, or iterative prestack migration. These techniques can be effective, and each has its own advantage or disadvantage. Conventional NMO methods are relatively inexpensive but basically require simplifying assumptions about geology. Tomography is a more general method but requires traveltime interpretation of prestack data. Iterative prestack depth migration is very general but is computationally expensive. In some cases, there is the opportunity to estimate vertical velocities by use of well information. The well informationmore » can be used to optimize poststack migrations, thereby eliminating some of the time and expense of iterative prestack migration. The optimized poststack migration procedure defined here computes the velocity model which minimizes the depth differences between seismic images and formation depths at the well by using a least squares inversion method. The optimization methods described in this paper will hopefully produce ``migrations without migraines.``« less

Simulation of General Physics laboratory exercise

NASA Astrophysics Data System (ADS)

Aceituno, P.; Hernández-Aceituno, J.; Hernández-Cabrera, A.

2015-01-01

Laboratory exercises are an important part of general Physics teaching, both during the last years of high school and the first year of college education. Due to the need to acquire enough laboratory equipment for all the students, and the widespread access to computers rooms in teaching, we propose the development of computer simulated laboratory exercises. A representative exercise in general Physics is the calculation of the gravity acceleration value, through the free fall motion of a metal ball. Using a model of the real exercise, we have developed an interactive system which allows students to alter the starting height of the ball to obtain different fall times. The simulation was programmed in ActionScript 3, so that it can be freely executed in any operative system; to ensure the accuracy of the calculations, all the input parameters of the simulations were modelled using digital measurement units, and to allow a statistical management of the resulting data, measurement errors are simulated through limited randomization.

Highly fault-tolerant parallel computation

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

Spielman, D.A.

We re-introduce the coded model of fault-tolerant computation in which the input and output of a computational device are treated as words in an error-correcting code. A computational device correctly computes a function in the coded model if its input and output, once decoded, are a valid input and output of the function. In the coded model, it is reasonable to hope to simulate all computational devices by devices whose size is greater by a constant factor but which are exponentially reliable even if each of their components can fail with some constant probability. We consider fine-grained parallel computations inmore » which each processor has a constant probability of producing the wrong output at each time step. We show that any parallel computation that runs for time t on w processors can be performed reliably on a faulty machine in the coded model using w log{sup O(l)} w processors and time t log{sup O(l)} w. The failure probability of the computation will be at most t {center_dot} exp(-w{sup 1/4}). The codes used to communicate with our fault-tolerant machines are generalized Reed-Solomon codes and can thus be encoded and decoded in O(n log{sup O(1)} n) sequential time and are independent of the machine they are used to communicate with. We also show how coded computation can be used to self-correct many linear functions in parallel with arbitrarily small overhead.« less

Numerical investigation of airflow in an idealised human extra-thoracic airway: a comparison study

PubMed Central

Chen, Jie; Gutmark, Ephraim

2013-01-01

Large eddy simulation (LES) technique is employed to numerically investigate the airflow through an idealised human extra-thoracic airway under different breathing conditions, 10 l/min, 30 l/min, and 120 l/min. The computational results are compared with single and cross hot-wire measurements, and with time-averaged flow field computed by standard k-ω and k-ω-SST Reynolds averaged Navier-Stokes (RANS) models and the Lattice-Boltzmann method (LBM). The LES results are also compared to root-mean-square (RMS) flow field computed by the Reynolds stress model (RSM) and LBM. LES generally gives better prediction of the time-averaged flow field than RANS models and LBM. LES also provides better estimation of the RMS flow field than both the RSM and the LBM. PMID:23619907

An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio

USGS Publications Warehouse

Koltun, G.F.

2015-01-01

Streamflow hydrographs were plotted for modeled/computed time series for the Ohio River near the USGS Sardis gage and the Ohio River at the Hannibal Lock and Dam. In general, the time series at these two locations compared well. Some notable differences include the exclusive presence of short periods of negative streamflows in the USGS 15-minute time-series data for the gage on the Ohio River above Sardis, Ohio, and the occurrence of several peak streamflows in the USACE gate/hydropower time series for the Hannibal Lock and Dam that were appreciably larger than corresponding peaks in the other time series, including those modeled/computed for the downstream Sardis gage

JIGSAW-GEO (1.0): Locally Orthogonal Staggered Unstructured Grid Generation for General Circulation Modelling on the Sphere

NASA Technical Reports Server (NTRS)

Engwirda, Darren

2017-01-01

An algorithm for the generation of non-uniform, locally orthogonal staggered unstructured spheroidal grids is described. This technique is designed to generate very high-quality staggered VoronoiDelaunay meshes appropriate for general circulation modelling on the sphere, including applications to atmospheric simulation, ocean-modelling and numerical weather prediction. Using a recently developed Frontal-Delaunay refinement technique, a method for the construction of high-quality unstructured spheroidal Delaunay triangulations is introduced. A locally orthogonal polygonal grid, derived from the associated Voronoi diagram, is computed as the staggered dual. It is shown that use of the Frontal-Delaunay refinement technique allows for the generation of very high-quality unstructured triangulations, satisfying a priori bounds on element size and shape. Grid quality is further improved through the application of hill-climbing-type optimisation techniques. Overall, the algorithm is shown to produce grids with very high element quality and smooth grading characteristics, while imposing relatively low computational expense. A selection of uniform and non-uniform spheroidal grids appropriate for high-resolution, multi-scale general circulation modelling are presented. These grids are shown to satisfy the geometric constraints associated with contemporary unstructured C-grid-type finite-volume models, including the Model for Prediction Across Scales (MPAS-O). The use of user-defined mesh-spacing functions to generate smoothly graded, non-uniform grids for multi-resolution-type studies is discussed in detail.

JIGSAW-GEO (1.0): locally orthogonal staggered unstructured grid generation for general circulation modelling on the sphere

NASA Astrophysics Data System (ADS)

Engwirda, Darren

2017-06-01

An algorithm for the generation of non-uniform, locally orthogonal staggered unstructured spheroidal grids is described. This technique is designed to generate very high-quality staggered Voronoi-Delaunay meshes appropriate for general circulation modelling on the sphere, including applications to atmospheric simulation, ocean-modelling and numerical weather prediction. Using a recently developed Frontal-Delaunay refinement technique, a method for the construction of high-quality unstructured spheroidal Delaunay triangulations is introduced. A locally orthogonal polygonal grid, derived from the associated Voronoi diagram, is computed as the staggered dual. It is shown that use of the Frontal-Delaunay refinement technique allows for the generation of very high-quality unstructured triangulations, satisfying a priori bounds on element size and shape. Grid quality is further improved through the application of hill-climbing-type optimisation techniques. Overall, the algorithm is shown to produce grids with very high element quality and smooth grading characteristics, while imposing relatively low computational expense. A selection of uniform and non-uniform spheroidal grids appropriate for high-resolution, multi-scale general circulation modelling are presented. These grids are shown to satisfy the geometric constraints associated with contemporary unstructured C-grid-type finite-volume models, including the Model for Prediction Across Scales (MPAS-O). The use of user-defined mesh-spacing functions to generate smoothly graded, non-uniform grids for multi-resolution-type studies is discussed in detail.

PIFCGT: A PIF autopilot design program for general aviation aircraft

NASA Technical Reports Server (NTRS)

Broussard, J. R.

1983-01-01

This report documents the PIFCGT computer program. In FORTRAN, PIFCGT is a computer design aid for determing Proportional-Integral-Filter (PIF) control laws for aircraft autopilots implemented with a Command Generator Tracker (CGT). The program uses Linear-Quadratic-Regulator synthesis algorithms to determine feedback gains, and includes software to solve the feedforward matrix equation which is useful in determining the command generator tracker feedforward gains. The program accepts aerodynamic stability derivatives and computes the corresponding aerodynamic linear model. The nine autopilot modes that can be designed include four maneuver modes (ROLL SEL, PITCH SEL, HDG SEL, ALT SEL), four final approach models (APR GS, APR LOCI, APR LOCR, APR LOCP), and a BETA HOLD mode. The program has been compiled and executed on a CDC computer.

Modeling Ni-Cd performance. Planned alterations to the Goddard battery model

NASA Technical Reports Server (NTRS)

Jagielski, J. M.

1986-01-01

The Goddard Space Flight Center (GSFC) currently has a preliminary computer model to simulate a Nickel Cadmium (Ni-Cd) performance. The basic methodology of the model was described in the paper entitled Fundamental Algorithms of the Goddard Battery Model. At present, the model is undergoing alterations to increase its efficiency, accuracy, and generality. A review of the present battery model is given, and the planned charges of the model are described.

QuEST for malware type-classification

NASA Astrophysics Data System (ADS)

Vaughan, Sandra L.; Mills, Robert F.; Grimaila, Michael R.; Peterson, Gilbert L.; Oxley, Mark E.; Dube, Thomas E.; Rogers, Steven K.

2015-05-01

Current cyber-related security and safety risks are unprecedented, due in no small part to information overload and skilled cyber-analyst shortages. Advances in decision support and Situation Awareness (SA) tools are required to support analysts in risk mitigation. Inspired by human intelligence, research in Artificial Intelligence (AI) and Computational Intelligence (CI) have provided successful engineering solutions in complex domains including cyber. Current AI approaches aggregate large volumes of data to infer the general from the particular, i.e. inductive reasoning (pattern-matching) and generally cannot infer answers not previously programmed. Whereas humans, rarely able to reason over large volumes of data, have successfully reached the top of the food chain by inferring situations from partial or even partially incorrect information, i.e. abductive reasoning (pattern-completion); generating a hypothetical explanation of observations. In order to achieve an engineering advantage in computational decision support and SA we leverage recent research in human consciousness, the role consciousness plays in decision making, modeling the units of subjective experience which generate consciousness, qualia. This paper introduces a novel computational implementation of a Cognitive Modeling Architecture (CMA) which incorporates concepts of consciousness. We apply our model to the malware type-classification task. The underlying methodology and theories are generalizable to many domains.

Cloud immersion building shielding factors for US residential structures.

PubMed

Dickson, E D; Hamby, D M

2014-12-01

This paper presents validated building shielding factors designed for contemporary US housing-stock under an idealized, yet realistic, exposure scenario within a semi-infinite cloud of radioactive material. The building shielding factors are intended for use in emergency planning and level three probabilistic risk assessments for a variety of postulated radiological events in which a realistic assessment is necessary to better understand the potential risks for accident mitigation and emergency response planning. Factors are calculated from detailed computational housing-units models using the general-purpose Monte Carlo N-Particle computational code, MCNP5, and are benchmarked from a series of narrow- and broad-beam measurements analyzing the shielding effectiveness of ten common general-purpose construction materials and ten shielding models representing the primary weather barriers (walls and roofs) of likely US housing-stock. Each model was designed to scale based on common residential construction practices and include, to the extent practical, all structurally significant components important for shielding against ionizing radiation. Calculations were performed for floor-specific locations as well as for computing a weighted-average representative building shielding factor for single- and multi-story detached homes, both with and without basement, as well for single-wide manufactured housing-units.

Dealing with Diversity in Computational Cancer Modeling

PubMed Central

Johnson, David; McKeever, Steve; Stamatakos, Georgios; Dionysiou, Dimitra; Graf, Norbert; Sakkalis, Vangelis; Marias, Konstantinos; Wang, Zhihui; Deisboeck, Thomas S.

2013-01-01

This paper discusses the need for interconnecting computational cancer models from different sources and scales within clinically relevant scenarios to increase the accuracy of the models and speed up their clinical adaptation, validation, and eventual translation. We briefly review current interoperability efforts drawing upon our experiences with the development of in silico models for predictive oncology within a number of European Commission Virtual Physiological Human initiative projects on cancer. A clinically relevant scenario, addressing brain tumor modeling that illustrates the need for coupling models from different sources and levels of complexity, is described. General approaches to enabling interoperability using XML-based markup languages for biological modeling are reviewed, concluding with a discussion on efforts towards developing cancer-specific XML markup to couple multiple component models for predictive in silico oncology. PMID:23700360

Intentions of hospital nurses to work with computers: based on the theory of planned behavior.

PubMed

Shoham, Snunith; Gonen, Ayala

2008-01-01

The purpose of this study was to determine registered nurses' attitudes related to intent to use computers in the hospital setting as a predictor of their future behavior. The study was further aimed at identifying the relationship between these attitudes and selected sociological, professional, and personal factors and to describe a research model integrating these various factors. The study was based on the theory of planned behavior. A random sample of 411 registered nurses was selected from a single large medical center in Israel. The study tool was a Likert-style questionnaire. Nine different indices were used: (1) behavioral intention toward computer use; (2) general attitudes toward computer use; (3) nursing attitudes toward computer use; (4) threat involved in computer use; (5) challenge involved in computer use; (6) organizational climate; (7) departmental climate; (8) attraction to technological innovations/innovativeness; (9) self-efficacy, ability to control behavior. Strong significant positive correlations were found between the nurses' attitudes (general attitudes and nursing attitudes), self-efficacy, innovativeness, and intentions to use computers. Higher correlations were found between departmental climate and attitudes than between organizational climate and attitudes. The threat and challenge that are involved in computer use were shown as important mediating variables to the understanding of the process of predicting attitudes and intentions toward using computers.

A generalized computer code for developing dynamic gas turbine engine models (DIGTEM)

NASA Technical Reports Server (NTRS)

Daniele, C. J.

1984-01-01

This paper describes DIGTEM (digital turbofan engine model), a computer program that simulates two spool, two stream (turbofan) engines. DIGTEM was developed to support the development of a real time multiprocessor based engine simulator being designed at the Lewis Research Center. The turbofan engine model in DIGTEM contains steady state performance maps for all the components and has control volumes where continuity and energy balances are maintained. Rotor dynamics and duct momentum dynamics are also included. DIGTEM features an implicit integration scheme for integrating stiff systems and trims the model equations to match a prescribed design point by calculating correction coefficients that balance out the dynamic equations. It uses the same coefficients at off design points and iterates to a balanced engine condition. Transients are generated by defining the engine inputs as functions of time in a user written subroutine (TMRSP). Closed loop controls can also be simulated. DIGTEM is generalized in the aerothermodynamic treatment of components. This feature, along with DIGTEM's trimming at a design point, make it a very useful tool for developing a model of a specific turbofan engine.

A generalized computer code for developing dynamic gas turbine engine models (DIGTEM)

NASA Technical Reports Server (NTRS)

Daniele, C. J.

1983-01-01

This paper describes DIGTEM (digital turbofan engine model), a computer program that simulates two spool, two stream (turbofan) engines. DIGTEM was developed to support the development of a real time multiprocessor based engine simulator being designed at the Lewis Research Center. The turbofan engine model in DIGTEM contains steady state performance maps for all the components and has control volumes where continuity and energy balances are maintained. Rotor dynamics and duct momentum dynamics are also included. DIGTEM features an implicit integration scheme for integrating stiff systems and trims the model equations to match a prescribed design point by calculating correction coefficients that balance out the dynamic equations. It uses the same coefficients at off design points and iterates to a balanced engine condition. Transients are generated by defining the engine inputs as functions of time in a user written subroutine (TMRSP). Closed loop controls can also be simulated. DIGTEM is generalized in the aerothermodynamic treatment of components. This feature, along with DIGTEM's trimming at a design point, make it a very useful tool for developing a model of a specific turbofan engine.

Birch regeneration: a stochastic model

Treesearch

William B. Leak

1968-01-01

The regeneration of a clearcutting with paper or yellow birch is expressed as an elementary stochastic (probabalistic) model that is computationally similar to an absorbing Markov chain. In the general case, the model contains 29 states beginning with the development of a flower (ament) and terminating with the abortion of a flower or seed, or the development of an...

Global Weather Prediction and High-End Computing at NASA

NASA Technical Reports Server (NTRS)

Lin, Shian-Jiann; Atlas, Robert; Yeh, Kao-San

2003-01-01

We demonstrate current capabilities of the NASA finite-volume General Circulation Model an high-resolution global weather prediction, and discuss its development path in the foreseeable future. This model can be regarded as a prototype of a future NASA Earth modeling system intended to unify development activities cutting across various disciplines within the NASA Earth Science Enterprise.

Evaluating Social Causality and Responsibility Models: An Initial Report

DTIC Science & Technology

2005-01-01

ICT Technical Report ICT-TR-03-2005 Evaluating Social Causality and Responsibility ... social intelligent agents. In this report, we present a general computational model of social causality and responsibility , and empirical results of...2005 to 00-00-2005 4. TITLE AND SUBTITLE Evaluating Social Causality and Responsibility Models: An Initial Report 5a. CONTRACT NUMBER 5b. GRANT

Mesoscale Models of Fluid Dynamics

NASA Astrophysics Data System (ADS)

Boghosian, Bruce M.; Hadjiconstantinou, Nicolas G.

During the last half century, enormous progress has been made in the field of computational materials modeling, to the extent that in many cases computational approaches are used in a predictive fashion. Despite this progress, modeling of general hydrodynamic behavior remains a challenging task. One of the main challenges stems from the fact that hydrodynamics manifests itself over a very wide range of length and time scales. On one end of the spectrum, one finds the fluid's "internal" scale characteristic of its molecular structure (in the absence of quantum effects, which we omit in this chapter). On the other end, the "outer" scale is set by the characteristic sizes of the problem's domain. The resulting scale separation or lack thereof as well as the existence of intermediate scales are key to determining the optimal approach. Successful treatments require a judicious choice of the level of description which is a delicate balancing act between the conflicting requirements of fidelity and manageable computational cost: a coarse description typically requires models for underlying processes occuring at smaller length and time scales; on the other hand, a fine-scale model will incur a significantly larger computational cost.

Spherical harmonic analysis of a synoptic climatology generated with a global general circulation model

NASA Technical Reports Server (NTRS)

Christidis, Z. D.; Spar, J.

1980-01-01

Spherical harmonic analysis was used to analyze the observed climatological (C) fields of temperature at 850 mb, geopotential height at 500 mb, and sea level pressure. The spherical harmonic method was also applied to the corresponding "model climatological" fields (M) generated by a general circulation model, the "GISS climate model." The climate model was initialized with observed data for the first of December 1976 at 00. GMT and allowed to generate five years of meteorological history. Monthly means of the above fields for the five years were computed and subjected to spherical harmonic analysis. It was found from the comparison of the spectral components of both sets, M and C, that the climate model generated reasonable 500 mb geopotential heights. The model temperature field at 850 mb exhibited a generally correct structure. However, the meridional temperature gradient was overestimated and overheating of the continents was observed in summer.

Theoretical Comparison Between Candidates for Dark Matter

NASA Astrophysics Data System (ADS)

McKeough, James; Hira, Ajit; Valdez, Alexandra

2017-01-01

Since the generally-accepted view among astrophysicists is that the matter component of the universe is mostly dark matter, the search for dark matter particles continues unabated. The Large Underground Xenon (LUX) improvements, aided by advanced computer simulations at the U.S. Department of Energy's Lawrence Berkeley National Laboratory's (Berkeley Lab) National Energy Research Scientific Computing Center (NERSC) and Brown University's Center for Computation and Visualization (CCV), can potentially eliminate some particle models of dark matter. Generally, the proposed candidates can be put in three categories: baryonic dark matter, hot dark matter, and cold dark matter. The Lightest Supersymmetric Particle(LSP) of supersymmetric models is a dark matter candidate, and is classified as a Weakly Interacting Massive Particle (WIMP). Similar to the cosmic microwave background radiation left over from the Big Bang, there is a background of low-energy neutrinos in our Universe. According to some researchers, these may be the explanation for the dark matter. One advantage of the Neutrino Model is that they are known to exist. Dark matter made from neutrinos is termed ``hot dark matter''. We formulate a novel empirical function for the average density profile of cosmic voids, identified via the watershed technique in ΛCDM N-body simulations. This function adequately treats both void size and redshift, and describes the scale radius and the central density of voids. We started with a five-parameter model. Our research is mainly on LSP and Neutrino models.

BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments

DOE PAGES

Thomas, Brandon R.; Chylek, Lily A.; Colvin, Joshua; ...

2015-11-09

Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here in this paper, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive.

Pan evaporation modeling using six different heuristic computing methods in different climates of China

NASA Astrophysics Data System (ADS)

Wang, Lunche; Kisi, Ozgur; Zounemat-Kermani, Mohammad; Li, Hui

2017-01-01

Pan evaporation (Ep) plays important roles in agricultural water resources management. One of the basic challenges is modeling Ep using limited climatic parameters because there are a number of factors affecting the evaporation rate. This study investigated the abilities of six different soft computing methods, multi-layer perceptron (MLP), generalized regression neural network (GRNN), fuzzy genetic (FG), least square support vector machine (LSSVM), multivariate adaptive regression spline (MARS), adaptive neuro-fuzzy inference systems with grid partition (ANFIS-GP), and two regression methods, multiple linear regression (MLR) and Stephens and Stewart model (SS) in predicting monthly Ep. Long-term climatic data at various sites crossing a wide range of climates during 1961-2000 are used for model development and validation. The results showed that the models have different accuracies in different climates and the MLP model performed superior to the other models in predicting monthly Ep at most stations using local input combinations (for example, the MAE (mean absolute errors), RMSE (root mean square errors), and determination coefficient (R2) are 0.314 mm/day, 0.405 mm/day and 0.988, respectively for HEB station), while GRNN model performed better in Tibetan Plateau (MAE, RMSE and R2 are 0.459 mm/day, 0.592 mm/day and 0.932, respectively). The accuracies of above models ranked as: MLP, GRNN, LSSVM, FG, ANFIS-GP, MARS and MLR. The overall results indicated that the soft computing techniques generally performed better than the regression methods, but MLR and SS models can be more preferred at some climatic zones instead of complex nonlinear models, for example, the BJ (Beijing), CQ (Chongqing) and HK (Haikou) stations. Therefore, it can be concluded that Ep could be successfully predicted using above models in hydrological modeling studies.

Analysis Tools for Interconnected Boolean Networks With Biological Applications.

PubMed

Chaves, Madalena; Tournier, Laurent

2018-01-01

Boolean networks with asynchronous updates are a class of logical models particularly well adapted to describe the dynamics of biological networks with uncertain measures. The state space of these models can be described by an asynchronous state transition graph, which represents all the possible exits from every single state, and gives a global image of all the possible trajectories of the system. In addition, the asynchronous state transition graph can be associated with an absorbing Markov chain, further providing a semi-quantitative framework where it becomes possible to compute probabilities for the different trajectories. For large networks, however, such direct analyses become computationally untractable, given the exponential dimension of the graph. Exploiting the general modularity of biological systems, we have introduced the novel concept of asymptotic graph , computed as an interconnection of several asynchronous transition graphs and recovering all asymptotic behaviors of a large interconnected system from the behavior of its smaller modules. From a modeling point of view, the interconnection of networks is very useful to address for instance the interplay between known biological modules and to test different hypotheses on the nature of their mutual regulatory links. This paper develops two new features of this general methodology: a quantitative dimension is added to the asymptotic graph, through the computation of relative probabilities for each final attractor and a companion cross-graph is introduced to complement the method on a theoretical point of view.

Computer model to simulate testing at the National Transonic Facility

NASA Technical Reports Server (NTRS)

Mineck, Raymond E.; Owens, Lewis R., Jr.; Wahls, Richard A.; Hannon, Judith A.

1995-01-01

A computer model has been developed to simulate the processes involved in the operation of the National Transonic Facility (NTF), a large cryogenic wind tunnel at the Langley Research Center. The simulation was verified by comparing the simulated results with previously acquired data from three experimental wind tunnel test programs in the NTF. The comparisons suggest that the computer model simulates reasonably well the processes that determine the liquid nitrogen (LN2) consumption, electrical consumption, fan-on time, and the test time required to complete a test plan at the NTF. From these limited comparisons, it appears that the results from the simulation model are generally within about 10 percent of the actual NTF test results. The use of actual data acquisition times in the simulation produced better estimates of the LN2 usage, as expected. Additional comparisons are needed to refine the model constants. The model will typically produce optimistic results since the times and rates included in the model are typically the optimum values. Any deviation from the optimum values will lead to longer times or increased LN2 and electrical consumption for the proposed test plan. Computer code operating instructions and listings of sample input and output files have been included.

Universal quantum computation with little entanglement.

PubMed

Van den Nest, Maarten

2013-02-08

We show that universal quantum computation can be achieved in the standard pure-state circuit model while the entanglement entropy of every bipartition is small in each step of the computation. The entanglement entropy required for large-scale quantum computation even tends to zero. Moreover we show that the same conclusion applies to many entanglement measures commonly used in the literature. This includes e.g., the geometric measure, localizable entanglement, multipartite concurrence, squashed entanglement, witness-based measures, and more generally any entanglement measure which is continuous in a certain natural sense. These results demonstrate that many entanglement measures are unsuitable tools to assess the power of quantum computers.

Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates.

PubMed

LeDell, Erin; Petersen, Maya; van der Laan, Mark

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC.

Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates

PubMed Central

Petersen, Maya; van der Laan, Mark

2015-01-01

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC. PMID:26279737

The Nuclear Energy Advanced Modeling and Simulation Enabling Computational Technologies FY09 Report

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

Diachin, L F; Garaizar, F X; Henson, V E

2009-10-12

In this document we report on the status of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Enabling Computational Technologies (ECT) effort. In particular, we provide the context for ECT In the broader NEAMS program and describe the three pillars of the ECT effort, namely, (1) tools and libraries, (2) software quality assurance, and (3) computational facility (computers, storage, etc) needs. We report on our FY09 deliverables to determine the needs of the integrated performance and safety codes (IPSCs) in these three areas and lay out the general plan for software quality assurance to meet the requirements of DOE andmore » the DOE Advanced Fuel Cycle Initiative (AFCI). We conclude with a brief description of our interactions with the Idaho National Laboratory computer center to determine what is needed to expand their role as a NEAMS user facility.« less

Atmospheric Gravitational Torque Variations Based on Various Gravity Fields

NASA Technical Reports Server (NTRS)

Sanchez, Braulio V.; Rowlands, David; Smith, David E. (Technical Monitor)

2001-01-01

Advancements in the study of the Earth's variable rate of rotation and the motion of its rotation axis have given impetus to the analysis of the torques between the atmosphere, oceans and solid Earth. The output from global general circulation models of the atmosphere (pressure, surface stress) is being used as input to the torque computations. Gravitational torque between the atmosphere, oceans and solid Earth is an important component of the torque budget. Computation of the gravitational torque involves the adoption of a gravitational model from a wide variety available. The purpose of this investigation is to ascertain to what extent this choice might influence the results of gravitational torque computations.

General purpose simulation system of the data management system for Space Shuttle mission 18

NASA Technical Reports Server (NTRS)

Bengtson, N. M.; Mellichamp, J. M.; Smith, O. C.

1976-01-01

A simulation program for the flow of data through the Data Management System of Spacelab and Space Shuttle was presented. The science, engineering, command and guidance, navigation and control data were included. The programming language used was General Purpose Simulation System V (OS). The science and engineering data flow was modeled from its origin at the experiments and subsystems to transmission from Space Shuttle. Command data flow was modeled from the point of reception onboard and from the CDMS Control Panel to the experiments and subsystems. The GN&C data flow model handled data between the General Purpose Computer and the experiments and subsystems. Mission 18 was the particular flight chosen for simulation. The general structure of the program is presented, followed by a user's manual. Input data required to make runs are discussed followed by identification of the output statistics. The appendices contain a detailed model configuration, program listing and results.

Hypersonic Shock/Boundary-Layer Interaction Database

NASA Technical Reports Server (NTRS)

Settles, G. S.; Dodson, L. J.

1991-01-01

Turbulence modeling is generally recognized as the major problem obstructing further advances in computational fluid dynamics (CFD). A closed solution of the governing Navier-Stokes equations for turbulent flows of practical consequence is still far beyond grasp. At the same time, the simplified models of turbulence which are used to achieve closure of the Navier-Stokes equations are known to be rigorously incorrect. While these models serve a definite purpose, they are inadequate for the general prediction of hypersonic viscous/inviscid interactions, mixing problems, chemical nonequilibria, and a range of other phenomena which must be predicted in order to design a hypersonic vehicle computationally. Due to the complexity of turbulence, useful new turbulence models are synthesized only when great expertise is brought to bear and considerable intellectual energy is expended. Although this process is fundamentally theoretical, crucial guidance may be gained from carefully-executed basic experiments. Following the birth of a new model, its testing and validation once again demand comparisons with data of unimpeachable quality. This report concerns these issues which arise from the experimental aspects of hypersonic modeling and represents the results of the first phase of an effort to develop compressible turbulence models.

BUMPER: the Bayesian User-friendly Model for Palaeo-Environmental Reconstruction

NASA Astrophysics Data System (ADS)

Holden, Phil; Birks, John; Brooks, Steve; Bush, Mark; Hwang, Grace; Matthews-Bird, Frazer; Valencia, Bryan; van Woesik, Robert

2017-04-01

We describe the Bayesian User-friendly Model for Palaeo-Environmental Reconstruction (BUMPER), a Bayesian transfer function for inferring past climate and other environmental variables from microfossil assemblages. The principal motivation for a Bayesian approach is that the palaeoenvironment is treated probabilistically, and can be updated as additional data become available. Bayesian approaches therefore provide a reconstruction-specific quantification of the uncertainty in the data and in the model parameters. BUMPER is fully self-calibrating, straightforward to apply, and computationally fast, requiring 2 seconds to build a 100-taxon model from a 100-site training-set on a standard personal computer. We apply the model's probabilistic framework to generate thousands of artificial training-sets under ideal assumptions. We then use these to demonstrate both the general applicability of the model and the sensitivity of reconstructions to the characteristics of the training-set, considering assemblage richness, taxon tolerances, and the number of training sites. We demonstrate general applicability to real data, considering three different organism types (chironomids, diatoms, pollen) and different reconstructed variables. In all of these applications an identically configured model is used, the only change being the input files that provide the training-set environment and taxon-count data.

Hierarchical Bayesian Models of Subtask Learning

ERIC Educational Resources Information Center

Anglim, Jeromy; Wynton, Sarah K. A.

2015-01-01

The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…

Why environmental scientists are becoming Bayesians

Treesearch

James S. Clark

2005-01-01

Advances in computational statistics provide a general framework for the high dimensional models typically needed for ecological inference and prediction. Hierarchical Bayes (HB) represents a modelling structure with capacity to exploit diverse sources of information, to accommodate influences that are unknown (or unknowable), and to draw inference on large numbers of...

Confined Turbulent Swirling Recirculating Flow Predictions. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Abujelala, M. T.

1984-01-01

Turbulent swirling flow, the STARPIC computer code, turbulence modeling of turbulent flows, the k-xi turbulence model and extensions, turbulence parameters deduction from swirling confined flow measurements, extension of the k-xi to confined swirling recirculating flows, and general predictions for confined turbulent swirling flow are discussed.

Why Might Relative Fit Indices Differ between Estimators?

ERIC Educational Resources Information Center

Weng, Li-Jen; Cheng, Chung-Ping

1997-01-01

Relative fit indices using the null model as the reference point in computation may differ across estimation methods, as this article illustrates by comparing maximum likelihood, ordinary least squares, and generalized least squares estimation in structural equation modeling. The illustration uses a covariance matrix for six observed variables…

Generalization of value in reinforcement learning by humans

PubMed Central

Wimmer, G. Elliott; Daw, Nathaniel D.; Shohamy, Daphna

2012-01-01

Research in decision making has focused on the role of dopamine and its striatal targets in guiding choices via learned stimulus-reward or stimulus-response associations, behavior that is well-described by reinforcement learning (RL) theories. However, basic RL is relatively limited in scope and does not explain how learning about stimulus regularities or relations may guide decision making. A candidate mechanism for this type of learning comes from the domain of memory, which has highlighted a role for the hippocampus in learning of stimulus-stimulus relations, typically dissociated from the role of the striatum in stimulus-response learning. Here, we used fMRI and computational model-based analyses to examine the joint contributions of these mechanisms to RL. Humans performed an RL task with added relational structure, modeled after tasks used to isolate hippocampal contributions to memory. On each trial participants chose one of four options, but the reward probabilities for pairs of options were correlated across trials. This (uninstructed) relationship between pairs of options potentially enabled an observer to learn about options’ values based on experience with the other options and to generalize across them. We observed BOLD activity related to learning in the striatum and also in the hippocampus. By comparing a basic RL model to one augmented to allow feedback to generalize between correlated options, we tested whether choice behavior and BOLD activity were influenced by the opportunity to generalize across correlated options. Although such generalization goes beyond standard computational accounts of RL and striatal BOLD, both choices and striatal BOLD were better explained by the augmented model. Consistent with the hypothesized role for the hippocampus in this generalization, functional connectivity between the ventral striatum and hippocampus was modulated, across participants, by the ability of the augmented model to capture participants’ choice. Our results thus point toward an interactive model in which striatal RL systems may employ relational representations typically associated with the hippocampus. PMID:22487039

A versatile model for soft patchy particles with various patch arrangements.

PubMed

Li, Zhan-Wei; Zhu, You-Liang; Lu, Zhong-Yuan; Sun, Zhao-Yan

2016-01-21

We propose a simple and general mesoscale soft patchy particle model, which can felicitously describe the deformable and surface-anisotropic characteristics of soft patchy particles. This model can be used in dynamics simulations to investigate the aggregation behavior and mechanism of various types of soft patchy particles with tunable number, size, direction, and geometrical arrangement of the patches. To improve the computational efficiency of this mesoscale model in dynamics simulations, we give the simulation algorithm that fits the compute unified device architecture (CUDA) framework of NVIDIA graphics processing units (GPUs). The validation of the model and the performance of the simulations using GPUs are demonstrated by simulating several benchmark systems of soft patchy particles with 1 to 4 patches in a regular geometrical arrangement. Because of its simplicity and computational efficiency, the soft patchy particle model will provide a powerful tool to investigate the aggregation behavior of soft patchy particles, such as patchy micelles, patchy microgels, and patchy dendrimers, over larger spatial and temporal scales.

Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights.

PubMed

Pasolli, Edoardo; Truong, Duy Tin; Malik, Faizan; Waldron, Levi; Segata, Nicola

2016-07-01

Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the "healthy" microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly available at http://segatalab.cibio.unitn.it/tools/metaml.

TRAC posttest calculations of Semiscale Test S-06-3. [PWR

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

Ireland, J.R.; Bleiweis, P.B.

A comparison of Transient Reactor Analysis Code (TRAC) steady-state and transient results with Semiscale Test S-06-3 (US Standard Problem 8) experimental data is discussed. The TRAC model used employs fewer mesh cells than normal data comparison models so that TRAC's ability to obtain reasonable results with less computer time can be assessed. In general, the TRAC results are in good agreement with the data and the major phenomena found in the experiment are reproduced by the code with a substantial reduction in computing times.

Computational methods for inverse problems in geophysics: inversion of travel time observations

USGS Publications Warehouse

Pereyra, V.; Keller, H.B.; Lee, W.H.K.

1980-01-01

General ways of solving various inverse problems are studied for given travel time observations between sources and receivers. These problems are separated into three components: (a) the representation of the unknown quantities appearing in the model; (b) the nonlinear least-squares problem; (c) the direct, two-point ray-tracing problem used to compute travel time once the model parameters are given. Novel software is described for (b) and (c), and some ideas given on (a). Numerical results obtained with artificial data and an implementation of the algorithm are also presented. ?? 1980.

Synfuel program analysis. Volume 2: VENVAL users manual

NASA Astrophysics Data System (ADS)

Muddiman, J. B.; Whelan, J. W.

1980-07-01

This volume is intended for program analysts and is a users manual for the VENVAL model. It contains specific explanations as to input data requirements and programming procedures for the use of this model. VENVAL is a generalized computer program to aid in evaluation of prospective private sector production ventures. The program can project interrelated values of installed capacity, production, sales revenue, operating costs, depreciation, investment, dent, earnings, taxes, return on investment, depletion, and cash flow measures. It can also compute related public sector and other external costs and revenues if unit costs are furnished.

General Electromagnetic Model for the Analysis of Complex Systems (GEMACS) Computer Code Documentation (Version 3). Volume 3, Part 4.

DTIC Science & Technology

1983-09-01

6ENFRAL. ELECTROMAGNETIC MODEL FOR THE ANALYSIS OF COMPLEX SYSTEMS **%(GEMA CS) Computer Code Documentation ii( Version 3 ). A the BDM Corporation Dr...ANALYSIS FnlTcnclRpr F COMPLEX SYSTEM (GmCS) February 81 - July 83- I TR CODE DOCUMENTATION (Version 3 ) 6.PROMN N.REPORT NUMBER 5. CONTRACT ORGAT97...the ti and t2 directions on the source patch. 3 . METHOD: The electric field at a segment observation point due to the source patch j is given by 1-- lnA

An inverse problem strategy based on forward model evaluations: Gradient-based optimization without adjoint solves

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

Aguilo Valentin, Miguel Alejandro

2016-07-01

This study presents a new nonlinear programming formulation for the solution of inverse problems. First, a general inverse problem formulation based on the compliance error functional is presented. The proposed error functional enables the computation of the Lagrange multipliers, and thus the first order derivative information, at the expense of just one model evaluation. Therefore, the calculation of the Lagrange multipliers does not require the solution of the computationally intensive adjoint problem. This leads to significant speedups for large-scale, gradient-based inverse problems.

A simulation model for wind energy storage systems. Volume 1: Technical report

NASA Technical Reports Server (NTRS)

Warren, A. W.; Edsinger, R. W.; Chan, Y. K.

1977-01-01

A comprehensive computer program for the modeling of wind energy and storage systems utilizing any combination of five types of storage (pumped hydro, battery, thermal, flywheel and pneumatic) was developed. The level of detail of Simulation Model for Wind Energy Storage (SIMWEST) is consistent with a role of evaluating the economic feasibility as well as the general performance of wind energy systems. The software package consists of two basic programs and a library of system, environmental, and load components. The first program is a precompiler which generates computer models (in FORTRAN) of complex wind source storage application systems, from user specifications using the respective library components. The second program provides the techno-economic system analysis with the respective I/O, the integration of systems dynamics, and the iteration for conveyance of variables. SIMWEST program, as described, runs on the UNIVAC 1100 series computers.

Improved computer simulation of the TCAS 3 circular array mounted on an aircraft

NASA Astrophysics Data System (ADS)

Rojas, R. G.; Chen, Y. C.; Burnside, Walter D.

1989-03-01

The Traffic advisory and Collision Avoidance System (TCAS) is being developed by the Federal Aviation Administration (FAA) to assist aircraft pilots in mid-air collision avoidance. This report concentrates on the computer simulation of the enchanced TCAS 2 systems mounted on a Boeing 727. First, the moment method is used to obtain an accurate model for the enhanced TCAS 2 antenna array. Then, the OSU Aircraft Code is used to generate theoretical radiation patterns of this model mounted on a simulated Boeing 727 model. Scattering error curves obtained from these patterns can be used to evaluate the performance of this system in determining the angular position of another aircraft with respect to the TCAS-equipped aircraft. Finally, the tracking of another aircraft is simulated when the TCAS-equipped aircraft follows a prescribed escape curve. In short, the computer models developed in this report have generality, completeness and yield reasonable results.

Turbulent heat transfer performance of single stage turbine

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

Amano, R.S.; Song, B.

1999-07-01

To increase the efficiency and the power of modern power plant gas turbines, designers are continually trying to raise the maximum turbine inlet temperature. Here, a numerical study based on the Navier-Stokes equations on a three-dimensional turbulent flow in a single stage turbine stator/rotor passage has been conducted and reported in this paper. The full Reynolds-stress closure model (RSM) was used for the computations and the results were also compared with the computations made by using the Launder-Sharma low-Reynolds-number {kappa}-{epsilon} model. The computational results obtained using these models were compared in order to investigate the turbulence effect in the near-wallmore » region. The set of the governing equations in a generalized curvilinear coordinate system was discretized by using the finite volume method with non-staggered grids. The numerical modeling was performed to interact between the stator and rotor blades.« less

Continuous-time discrete-space models for animal movement

USGS Publications Warehouse

Hanks, Ephraim M.; Hooten, Mevin B.; Alldredge, Mat W.

2015-01-01

The processes influencing animal movement and resource selection are complex and varied. Past efforts to model behavioral changes over time used Bayesian statistical models with variable parameter space, such as reversible-jump Markov chain Monte Carlo approaches, which are computationally demanding and inaccessible to many practitioners. We present a continuous-time discrete-space (CTDS) model of animal movement that can be fit using standard generalized linear modeling (GLM) methods. This CTDS approach allows for the joint modeling of location-based as well as directional drivers of movement. Changing behavior over time is modeled using a varying-coefficient framework which maintains the computational simplicity of a GLM approach, and variable selection is accomplished using a group lasso penalty. We apply our approach to a study of two mountain lions (Puma concolor) in Colorado, USA.

Comparison of model results transporting the odd nitrogen family with results transporting separate odd nitrogen species

NASA Technical Reports Server (NTRS)

Douglass, Anne R.; Jackman, Charles H.; Stolarski, Richard S.

1989-01-01

A fast two-dimensional residual circulation stratospheric family transport model, designed to minimize computer requirements, is developed. The model was used to calculate the ambient and perturbed atmospheres in which odd nitrogen species are transported as a family, and the results were compared with calculations in which HNO3, N2O5, ClONO2, and HO2NO2 are transported separately. It was found that ozone distributions computed by the two models for a present-day atmosphere are nearly identical. Good agreement was also found between calculated species concentrations and the ozone response, indicating the general applicability of the odd-nitrogen family approximations.

Design and application of a technologically explicit hybrid energy-economy policy model with micro and macro economic dynamics

NASA Astrophysics Data System (ADS)

Bataille, Christopher G. F.

2005-11-01

Are further energy efficiency gains, or more recently greenhouse gas reductions, expensive or cheap? Analysts provide conflicting advice to policy makers based on divergent modelling perspectives, a 'top-down/bottom-up debate' in which economists use equation based models that equilibrate markets by maximizing consumer welfare, and technologists use technology simulation models that minimize the financial cost of providing energy services. This thesis summarizes a long term research project to find a middle ground between these two positions that is more useful to policy makers. Starting with the individual components of a behaviourally realistic and technologically explicit simulation model (ISTUM---Inter Sectoral Technology Use Model), or "hybrid", the individual sectors of the economy are linked using a framework of micro and macro economic feedbacks. These feedbacks are taken from the economic theory that informs the computable general equilibrium (CGE) family of models. Speaking in the languages of both economists and engineers, the resulting "physical" equilibrium model of Canada (CIMS---Canadian Integrated Modeling System), equilibrates energy and end-product markets, including imports and exports, for seven regions and 15 economic sectors, including primary industry, manufacturing, transportation, commerce, residences, governmental infrastructure and the energy supply sectors. Several different policy experiments demonstrate the value-added of the model and how its results compare to top-down and bottom-up practice. In general, the results show that technical adjustments make up about half the response to simulated energy policy, and macroeconomic demand adjustments the other half. Induced technical adjustments predominate with minor policies, while the importance of macroeconomic demand adjustment increases with the strength of the policy. Results are also shown for an experiment to derive estimates of future elasticity of substitution (ESUB) and autonomous energy efficiency indices (AEEI) from the model, parameters that could be used in long-run computable general equilibrium (CGE) analysis. The thesis concludes with a summary of the strengths and weakness of the new model as a policy tool, a work plan for its further improvement, and a discussion of the general potential for technologically explicit general equilibrium modelling.

Nonequilibrium flow computations. 1: An analysis of numerical formulations of conservation laws

NASA Technical Reports Server (NTRS)

Liu, Yen; Vinokur, Marcel

1988-01-01

Modern numerical techniques employing properties of flux Jacobian matrices are extended to general, nonequilibrium flows. Generalizations of the Beam-Warming scheme, Steger-Warming and van Leer Flux-vector splittings, and Roe's approximate Riemann solver are presented for 3-D, time-varying grids. The analysis is based on a thermodynamic model that includes the most general thermal and chemical nonequilibrium flow of an arbitrary gas. Various special cases are also discussed.

Model verification of large structural systems

NASA Technical Reports Server (NTRS)

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

1977-01-01

A methodology was formulated, and a general computer code implemented for processing sinusoidal vibration test data to simultaneously make adjustments to a prior mathematical model of a large structural system, and resolve measured response data to obtain a set of orthogonal modes representative of the test model. The derivation of estimator equations is shown along with example problems. A method for improving the prior analytic model is included.

Computer Simulation Performed for Columbia Project Cooling System

NASA Technical Reports Server (NTRS)

Ahmad, Jasim

2005-01-01

This demo shows a high-fidelity simulation of the air flow in the main computer room housing the Columbia (10,024 intel titanium processors) system. The simulation asseses the performance of the cooling system and identified deficiencies, and recommended modifications to eliminate them. It used two in house software packages on NAS supercomputers: Chimera Grid tools to generate a geometric model of the computer room, OVERFLOW-2 code for fluid and thermal simulation. This state-of-the-art technology can be easily extended to provide a general capability for air flow analyses on any modern computer room. Columbia_CFD_black.tiff

Principles of proteome allocation are revealed using proteomic data and genome-scale models

PubMed Central

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; Ebrahim, Ali; Saunders, Michael A.; Palsson, Bernhard O.

2016-01-01

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. This flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models. PMID:27857205

Adaptive reduction of constitutive model-form error using a posteriori error estimation techniques

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

Bishop, Joseph E.; Brown, Judith Alice

In engineering practice, models are typically kept as simple as possible for ease of setup and use, computational efficiency, maintenance, and overall reduced complexity to achieve robustness. In solid mechanics, a simple and efficient constitutive model may be favored over one that is more predictive, but is difficult to parameterize, is computationally expensive, or is simply not available within a simulation tool. In order to quantify the modeling error due to the choice of a relatively simple and less predictive constitutive model, we adopt the use of a posteriori model-form error-estimation techniques. Based on local error indicators in the energymore » norm, an algorithm is developed for reducing the modeling error by spatially adapting the material parameters in the simpler constitutive model. The resulting material parameters are not material properties per se, but depend on the given boundary-value problem. As a first step to the more general nonlinear case, we focus here on linear elasticity in which the “complex” constitutive model is general anisotropic elasticity and the chosen simpler model is isotropic elasticity. As a result, the algorithm for adaptive error reduction is demonstrated using two examples: (1) A transversely-isotropic plate with hole subjected to tension, and (2) a transversely-isotropic tube with two side holes subjected to torsion.« less

Adaptive reduction of constitutive model-form error using a posteriori error estimation techniques

DOE PAGES

Bishop, Joseph E.; Brown, Judith Alice

2018-06-15

In engineering practice, models are typically kept as simple as possible for ease of setup and use, computational efficiency, maintenance, and overall reduced complexity to achieve robustness. In solid mechanics, a simple and efficient constitutive model may be favored over one that is more predictive, but is difficult to parameterize, is computationally expensive, or is simply not available within a simulation tool. In order to quantify the modeling error due to the choice of a relatively simple and less predictive constitutive model, we adopt the use of a posteriori model-form error-estimation techniques. Based on local error indicators in the energymore » norm, an algorithm is developed for reducing the modeling error by spatially adapting the material parameters in the simpler constitutive model. The resulting material parameters are not material properties per se, but depend on the given boundary-value problem. As a first step to the more general nonlinear case, we focus here on linear elasticity in which the “complex” constitutive model is general anisotropic elasticity and the chosen simpler model is isotropic elasticity. As a result, the algorithm for adaptive error reduction is demonstrated using two examples: (1) A transversely-isotropic plate with hole subjected to tension, and (2) a transversely-isotropic tube with two side holes subjected to torsion.« less

Principles of proteome allocation are revealed using proteomic data and genome-scale models

DOE PAGES

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; ...

2016-11-18

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less

STRUCTURE-ACTIVITY RELATIONSHIPS--COMPUTERIZED SYSTEMS

EPA Science Inventory

This report discusses some important general strategies and issuesrelative to the application of computational SAR techniques formodeling genotoxicity and carcinogenicity endpoints. roblemsparticular to the SAR modeling of such endpoints pertain to: hecomplexity of the carcinogen...