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Results for “design of computer experiments”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Structural Optimization of a Force Balance Using a Computational Experiment Design

This paper proposes a new approach to force balance structural optimization featuring a computational experiment design. Currently, this multi-dimensional design process requires the designer to perform a simplification by executing parameter studies on a small subset of design variables. This one-factor-at-a-time approach varies a single variable while holding all others at a constant level. Consequently, subtle interactions among the design variables, which can be exploited to achieve the design objectives, are undetected. The proposed method combines Modern Design of Experiments techniques to direct the exploration of the multi-dimensional design space, and a finite element analysis code to generate the experimental data. To efficiently search for an optimum combination of design variables and minimize the computational resources, a sequential design strategy was employed. Experimental results from the optimization of a non-traditional force balance measurement section are presented. An approach to overcome the unique problems associated with the simultaneous optimization of multiple response criteria is described. A quantitative single-point design procedure that reflects the designer's subjective impression of the relative importance of various design objectives, and a graphical multi-response optimization procedure that provides further insights into available tradeoffs among competing design objectives are illustrated. The proposed method enhances the intuition and experience of the designer by providing new perspectives on the relationships between the design variables and the competing design objectives providing a systematic foundation for advancements in structural design.

Parker, P. A.↗
DOE OSTI2020

Computational Experiment Design for Operations Model Simulation

Computer simulations that demonstrate the value of novel approaches are crucial to developing more flexible and robust power systems operations with high penetrations of renewable energy at multiple geographic and temporal scales. However, optimization-based simulations that depend on forecast data often face challenges in evaluating performance, reproducing results, and testing under realistic simulation scenarios. In this paper, we develop scientific computing best-practices for the validation and reproduction of power systems operational models. We then employ two case studies to demonstrate the proposed validation and reproduction framework.

MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND D↗
DOE OSTI2015

Maximum projection designs for computer experiments

Space-filling properties are important in designing computer experiments. The traditional maximin and minimax distance designs only consider space-filling in the full dimensional space. This can result in poor projections onto lower dimensional spaces, which is undesirable when only a few factors are active. Restricting maximin distance design to the class of Latin hypercubes can improve one-dimensional projections, but cannot guarantee good space-filling properties in larger subspaces. We propose designs that maximize space-filling properties on projections to all subsets of factors. We call our designs maximum projection designs. As a result, our design criterion can be computed at a cost no more than a design criterion that ignores projection properties.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2007

Space Shuttle Debris Impact Tool Assessment Using the Modern Design of Experiments

Complex computer codes are used to estimate thermal and structural reentry loads on the Shuttle Orbiter induced by ice and foam debris impact during ascent. Such debris can create cavities in the Shuttle Thermal Protection System. The sizes and shapes of these cavities are approximated to accommodate a code limitation that requires simple "shoebox" geometries to describe the cavities -- rectangular areas and planar walls that are at constant angles with respect to vertical. These approximations induce uncertainty in the code results. The Modern Design of Experiments (MDOE) has recently been applied to develop a series of resource-minimal computational experiments designed to generate low-order polynomial graduating functions to approximate the more complex underlying codes. These polynomial functions were then used to propagate cavity geometry errors to estimate the uncertainty they induce in the reentry load calculations performed by the underlying code. This paper describes a methodological study focused on evaluating the application of MDOE to future operational codes in a rapid and low-cost way to assess the effects of cavity geometry uncertainty.

DeLoach, Richard↗
DOE OSTI2020

Weighted greedy-optimal design of computer experiments for kernel-based and Gaussian process model emulation and calibration

This article is concerned with the approximation of high-dimensional functions by kernel-based methods. Motivated by uncertainty quantification, which often necessitates the construction of approximations that are accurate with respect to a probability density function of random variables, we aim at minimizing the approximation error with respect to a weighted $L^p$-norm. We present a greedy procedure for designing computer experiments based upon a weighted modification of the pivoted Cholesky factorization. The method successively generates nested samples with the goal of minimizing error in regions of high probability. Numerical experiments validate that this new importance sampling strategy is superior to other sampling approaches, especially when used with non-product probability density functions. We also show how to use the proposed algorithm to efficiently generate surrogates for inferring unknown model parameters from data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Space-filling designs for computer experiments: A review

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conducted for optimizing a milling process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A scalable framework for the global offline community land model ensemble simulation

Current earth system models have a large range of uncertainty, owing to differences in the simulation of feedbacks and insufficient information to constrain model parameters. Parameter disturbance experiment provides a straightforward method to quantify the variation (uncertainty) outputs caused by model inputs. Owing to the software complexity and computational intensity of earth system models, a large-scale simulation framework is needed to support ensemble simulation required by parameter disturbance experiment. This paper presents a parallel framework for the community land model ensemble simulation. After a software structure review of the community land model simulation, a single factor parameter disturbance experiment of a reference computational experiment design is used to demonstrate the software design principles, computational characteristics of individual application, parallel ensemble simulation implementation, as well as the weak scalability of this simulation framework on a high-end computer. Lastly, the paper discusses some preliminary diagnostic analysis results of the single factor parameter disturbance experiments. The framework design considerations and implementation details described in this paper can be beneficial to many other research programmes involving large scale, legacy modelling system.

58 GEOSCIENCES↗
DOE OSTI2015

On the benefit of using both hand calculation methods and computer experiments algorithms to solve complex nuclear criticality safety problems - 14299

A companion paper shows the 'anomalies', and even the safety issues, that may be raised by the very usual problem of making safe a fissile mass inside a controlled geometry. These anomalies mainly come from the solving of such problems which belong to the mathematical family of 'robust inversion' including two inversion parameters (the fissile mass and the geometry) and one nuisance parameter (the moderation ratio of the fissile material). Since a 'brute force' method of resolution requires a lot of calculations and since a 'smart' method of resolution requires a lot of engineer time, it is tempting to solve these problems by a 'custom made' approach rather than to achieve a 'whole' resolution. The present paper shows how one can use a hand calculation method (derivation of the one-speed diffusion theory) to perform the whole resolution of such kind of problems with a minimum calculations and human efforts. The powerful capability of predicting the 'anomalies' highlighted in the companion paper is shown. Then the limitations of such a method are discussed: limitation in the geometry of the problem and bias in absolute values prediction. Finally, new algorithms of computer experiments design, dedicated to solve robust inversion problems and based on Kriging surrogates, are tested to solve these problems with limiting calculations and human efforts. The performance of these new algorithms may supplement the one-speed diffusion theory limitations. (authors)

42 ENGINEERING↗
DOE OSTI2020

Modular performance prediction for scientific workflows using Machine Learning

Scientific workflows provide an opportunity for declarative computational experiment design in an intuitive and efficient way. A distributed workflow is typically executed on a variety of resources, and it uses a variety of computational algorithms or tools to achieve the desired outcomes. Such a variety imposes additional complexity in scheduling these workflows on large scale computers. As computation becomes more distributed, insights into expected workload that a workflow presents become critical for effective resource allocation. In this paper, we present a modular framework that leverages Machine Learning for creating precise performance predictions of a workflow. The central idea is to partition a workflow in such a way that makes the task of forecasting each atomic unit manageable and gives us a way to combine the individual predictions efficiently. We recognize a combination of an executable and a specific physical resource as a single module. This gives us a handle to characterize workload and machine power as a single unit of prediction. Overall, our modular technique of creating atomic modules and deployment of longest-path approach to estimate workflow performance, allows the framework to adapt to highly complex nested directed acyclic workflows and scale to new scenarios, since it does not make assumptions of underlying workflow structure. We present performance estimation results of independent workflow modules executed on the XSEDE SDSC Comet cluster using various Machine Learning algorithms. The results provide insights into the behavior and effectiveness of different algorithms in the context of scientific workflow performance prediction.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

Transonic aerodynamics; Transonic Perspective Symposium, Moffett Field, CA, February 18-20, 1981, Technical Papers

After an historical account of the development of transonic aerodynamics before 1940 and in the period 1945-1975, attention is given to the design for cruise performance efficiency of commercial transport aircraft, with emphasis on transonic wing design, the practical aerodynamic problems of military aircraft, with emphasis on store carriage and separation, experimental testing in transonic wind tunnels capable of Reynolds number simulation and aerodynamic flow visualization, and such mathematical techniques as potential equation methods for flow prediction and Reynolds-averaged Navier-Stokes computations of transonic flows. Also considered are transonic design using computational aerodynamics, the application of computation methods to transonic wing design, computational experience with advanced tactical aircraft, the evaluation of full potential flow methods, and the application of a shock-turbulent boundary layer interaction theory to transonic flowfield analysis.

Nixon, D.↗
NASA NTRS1993

Structure and dynamics of premixed flames in microgravity

In this report we describe the research performed at the Naval Research Laboratory in support of the NASA Microgravity Science and Applications Program over the past three years with emphasis on the work performed since February 1992, the beginning of the current project. The focus of our research has been on investigating fundamental combustion questions concerning the propagation and extinction of gas-phase flames in microgravity and earth-gravity environments. Our approach to resolving these fundamental questions has been to use detailed time-dependent, multidimensional numerical models to perform carefully designed computational experiments. The basic questions we have addressed, a general description of the numerical approach, and a summary of the results are described in this report. More detailed discussions are available in the papers published which are referenced herein.

Kailasanath, K.↗
NASA NTRS1995

Unsteady numerical simulations of the stability and dynamics of flames

In this report we describe the research performed at the Naval Research Laboratory in support of the NASA Microgravity Science and Applications Program over the past three years (from Feb. 1992) with emphasis on the work performed since the last microgravity combustion workshop. The primary objective of our research is to develop an understanding of the differences in the structure, stability, dynamics and extinction of flames in earth gravity and in microgravity environments. Numerical simulations, in which the various physical and chemical processes can be independently controlled, can significantly advance our understanding of these differences. Therefore, our approach is to use detailed time-dependent, multi-dimensional, multispecies numerical models to perform carefully designed computational experiments. The basic issues we have addressed, a general description of the numerical approach, and a summary of the results are described in this report. More detailed discussions are available in the papers published which are referenced herein. Some of the basic issues we have addressed recently are (1) the relative importance of wall losses and gravity on the extinguishment of downward-propagating flames; (2) the role of hydrodynamic instabilities in the formation of cellular flames; (3) effects of gravity on burner-stabilized flames, and (4) effects of radiative losses and chemical-kinetics on flames near flammability limits. We have also expanded our efforts to include hydrocarbon flames in addition to hydrogen flames and to perform simulations in support of other on-going efforts in the microgravity combustion sciences program. Modeling hydrocarbon flames typically involves a larger number of species and a much larger number of reactions when compared to hydrogen. In addition, more complex radiation models may also be needed. In order to efficiently compute such complex flames recent developments in parallel computing have been utilized to develop a state-of-the-art parallel flame code. This is discussed below in some detail after a brief discussion of the numerical models.

Kailasanath, K.↗
NASA NTRS1999

Detailed Multidimensional Simulations of the Structure and Dynamics of Flames

Numerical simulations in which the various physical and chemical processes can be independently controlled can significantly advance our understanding of the structure, stability, dynamics and extinction of flames. Therefore, our approach has been to use detailed time-dependent, multidimensional, multispecies numerical models to perform carefully designed computational experiments of flames on Earth and in microgravity environments. Some of these computational experiments are complementary to physical experiments performed under the Microgravity Program while others provide a fundamental understanding that cannot be obtained from physical experiments alone. In this report, we provide a brief summary of our recent research highlighting the contributions since the previous microgravity combustion workshop. There are a number of mechanisms that can cause flame instabilities and result in the formation of dynamic multidimensional structures. In the past, we have used numerical simulations to show that it is the thermo-diffusive instability rather than an instability due to preferential diffusion that is the dominant mechanism for the formation of cellular flames in lean hydrogen-air mixtures. Other studies have explored the role of gravity on flame dynamics and extinguishment, multi-step kinetics and radiative losses on flame instabilities in rich hydrogen-air flames, and heat losses on burner-stabilized flames in microgravity. The recent emphasis of our work has been on exploring flame-vortex interactions and further investigating the structure and dynamics of lean hydrogen-air flames in microgravity. These topics are briefly discussed after a brief discussion of our computational approach for solving these problems.

Patnaik, G.↗
DOE OSTI2023

ReaLigands: A Ligand Library Cultivated from Experiment and Intended for Molecular Computational Catalyst Design

Computational catalyst design requires identification of a metal and ligand that together result in the desired reaction reactivity and/or selectivity. A major impediment to translating computational designs to experiments is evaluating ligands that are likely to be synthesized. Here we provide a solution to this impediment with our ReaLigands library that contains >30,000 monodentate, bidentate (didentate), tridentate, and larger ligands cultivated by dismantling experimentally reported crystal structures. Individual ligands from mononuclear crystal structures were identified using a modified depth-first search algorithm and charge was assigned using a machine learning model based on quantum-chemical calculated features. In the library ligands are sorted based on direct ligand-to-metal atomic connections and on denticity. Representative principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) analyses were used to analyze several tridentate ligand categories, which revealed both the diversity of ligands and connections between ligand categories. Furthermore, we also demonstrated the utility of this library by implementing it with our building and optimization tools, which resulted in the very rapid generation of barriers for 750 bidentate ligands for Rh-hydride ethylene migratory insertion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1997

Numerical Optimization Using Computer Experiments

Engineering design optimization often gives rise to problems in which expensive objective functions are minimized by derivative-free methods. We propose a method for solving such problems that synthesizes ideas from the numerical optimization and computer experiment literatures. Our approach relies on kriging known function values to construct a sequence of surrogate models of the objective function that are used to guide a grid search for a minimizer. Results from numerical experiments on a standard test problem are presented.

Trosset, Michael W.↗