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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Parallel Three-Dimensional Computation of Fluid Dynamics and Fluid-Structure Interactions of Ram-Air Parachutes

This is a final report as far as our work at University of Minnesota is concerned. The report describes our research progress and accomplishments in development of high performance computing methods and tools for 3D finite element computation of aerodynamic characteristics and fluid-structure interactions (FSI) arising in airdrop systems, namely ram-air parachutes and round parachutes. This class of simulations involves complex geometries, flexible structural components, deforming fluid domains, and unsteady flow patterns. The key components of our simulation toolkit are a stabilized finite element flow solver, a nonlinear structural dynamics solver, an automatic mesh moving scheme, and an interface between the fluid and structural solvers; all of these have been developed within a parallel message-passing paradigm.

Tezduyar, Tayfun E.↗
NASA NTRSDate not supplied

Fluid-Structure Interaction Simulations of the ASPIRE SR01 Supersonic Parachute

High-fidelity computational fluid dynamics (CFD) simulations have so far only played exploratory and supporting roles in the study and qualification of parachutes for planetary entry. The last few years have seen the maturation of coupled computational methods that are capable of modeling the complex fluid-structure interactions between a parachute canopy and the supersonic flow in the wake of an entry vehicle in flight conditions. One of the primary goals of these methods is to predict the peak opening load experienced by the parachute during inflation. The Launch, Ascent, and Vehicle Aerodynamics (LAVA)team is developing efficient, high-fidelity numerical methods to perform such challenging fluid-structure interaction simulations. A loose coupling approach is used to advance the solutions of a Cartesian ghost cell immersed boundary method CFD solver and a finite element computational structural dynamics (CSD) solver in space and time. The coupled solver is employed to simulate the ASPIRE SR01 flight test, where a build-to-print version of the Mars Science Laboratory parachute was inflated in supersonic conditions in the upper terrestrial atmosphere. The simulations conducted in the current paper predict a peak opening load that is within 10% of that from the flight test. Grid convergence with respect to the volume and structural domains is demonstrated, and less than 1% variation in the peak opening load is predicted between all grid resolutions.

ARMD↗
NASA NTRS1991

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

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

Belcastro, Christine M.↗
DOE OSTI2021

Artificial intelligence in the prediction of protein–ligand interactions: recent advances and future directions

Abstract New drug production, from target identification to marketing approval, takes over 12 years and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the urgent need for more powerful computational methods for drug discovery. Here, we review the computational approaches to predicting protein–ligand interactions in the context of drug discovery, focusing on methods using artificial intelligence (AI). We begin with a brief introduction to proteins (targets), ligands (e.g. drugs) and their interactions for nonexperts. Next, we review databases that are commonly used in the domain of protein–ligand interactions. Finally, we survey and analyze the machine learning (ML) approaches implemented to predict protein–ligand binding sites, ligand-binding affinity and binding pose (conformation) including both classical ML algorithms and recent deep learning methods. After exploring the correlation between these three aspects of protein–ligand interaction, it has been proposed that they should be studied in unison. We anticipate that our review will aid exploration and development of more accurate ML-based prediction strategies for studying protein–ligand interactions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Materials and technologies for interstellar flights and intra-galactic spread of life

Small automated spaceships are capable to deliver seeds, frozen ova and gametes to other planetary systems. A spaceship can be equipped with a freezer containing reproductive cells, an artificial uterus, a robotic nursery and school, and a collection of instruments and equipment. The whole spaceship will be frozen during a long interstellar flight. Approaching another star, a spaceship will generate electricity from light, warm up, slow down and land on a suitable planet (if any), give birth to a human, provide care and education. After schooling, the human will vacate the spaceship and either build more space for living (using local materials) or die. A vacant spaceship will supply more people, one at a time. Hopefully, they will collectively create a sustainable colony on a remote planet. Our Milky Way galaxy has hundreds billion stars (i.e., more stars than humans on Earth). Mass production of spacecrafts for intragalactic spread of life will make each spaceship cheaper, will improve employment and purposeful production on Earth, and will spread human life beyond the Solar System. If any spaceship will miss its target stellar system, it will fly to the next one, retaining ability to bring life to another planet. Which materials and technologies are needed for the interstellar life propagation? Materials age during a long interstellar flight, which can last from 10^4 to 10^10 years. We evaluate the computational methods (such as C2NEB, available from https://lib.dr.iastate.edu/ameslab_software/1) that are suitable for addressing materials aging at low temperatures and high radiation levels during the appropriately long-time scales.

Technologies↗
DOE OSTI2023

Design and fabrication of TiO 2 -based dye sensitized solar cells using plant-derived organic dyes

The utilization of solar energy, an abundant and renewable resource, shows great promise. Various technologies have been employed to capture this vast energy potential. In this study, the effectiveness of natural dye-sensitized solar cells (DSSCs) was explored through experimental and computational methods. Organic dyes derived from specific plant species were examined, with a solvent mixture of ethanol, methanol, and tetrahydrofuran used for extraction. A UV–vis spectrophotometer was utilized to measure the sensitizers’ optical characteristics. The study employed density functional theory (DFT), implemented in Gaussian 09 W software, to perform computational calculations. The B3LYP method and a basis set of 6-31G++(d,p) were chosen for optimizing the geometries and energetics of dye molecules. The DFT results indicated that the dye molecules had a bandgap in the range of 2.16–2.38 eV. The photochemical performance of all four fabricated DSSC-based devices was evaluated to be between 0.33% and 1.04%, and the Euryops pectinatus sensitizer demonstrated the highest efficiency of 1.04% among the studied sensitizers.

36 MATERIALS SCIENCE↗
DOE OSTI2026

ZEUS: An Efficient GPU Optimization Method Integrating PSO, BFGS, and Automatic Differentiation

We introduce a novel, efficient computational method, ZEUS, for numerical optimization, and provide an open-source implementation. It has four key ingredients: (1) particle swarm optimization (PSO), (2) the use of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) method, (3) automatic differentiation (AD), and (4) GPUs. Our approach addresses the computational challenges inherent in high-dimensional, non-convex optimization problems. In the first phase of the algorithm, we get a potentially good set of starting points using PSO. Thereafter, we run BFGS independently in parallel from these starting points. BFGS is one of the best-performing algorithms for numerical optimization. However, it requires the gradient of the function being optimized. ZEUS integrates automatic differentiation into BFGS thus avoiding the need for the user to calculate derivatives explicitly. The use of GPUs allows ZEUS to speed up the calculations substantially. We carry out systematic studies to explore the trade-offs between the number of PSO iterations taken, starting points, and BFGS iteration depth. We show that a handful of iterations of PSO can improve global convergence when combined with BFGS. We also present performance studies using common test functions. The source code can be found at https://github.com/fnal-numerics/global-optimizer-gpu.

Soos, Dominik [Old Dominion U.]↗
DOE OSTI2021

Multiscale design of nonlinear materials using a Eulerian shape optimization scheme

Motivated by recent advances in manufacturing, the design of materials is the focal point of interest in the material research community. One of the critical challenges in this field is finding optimal material microstructure for a desired macroscopic response. This work presents a computational method for the mesoscale-level design of particulate composites for an optimal macroscale-level response. The method relies on a custom shape optimization scheme to find the extrema of a nonlinear cost function subject to a set of constraints. Three key “modules” constitute the method: multiscale modeling, sensitivity analysis, and optimization. Multiscale modeling relies on a classical homogenization method and a nonlinear NURBS-based generalized finite element scheme to efficiently and accurately compute the structural response of particulate composites using a nonconformal discretization. A three-parameter isotropic damage law is used to model microstructure-level failure. An analytical sensitivity method is developed to compute the derivatives of the cost/constraint functions with respect to the design variables that control the microstructure's geometry. The derivation uncovers subtle but essential new terms contributing to the sensitivity of finite element shape functions and their spatial derivatives. Several structural problems are solved to demonstrate the applicability, performance, and accuracy of the method for the design of particulate composites with a desired macroscopic nonlinear stress-strain response.

42 ENGINEERING↗
DOE OSTI2023

A review on recent machine learning applications for imaging mass spectrometry studies

Imaging mass spectrometry (IMS) is a powerful analytical technique widely used in biology, chemistry, and materials science fields that continue to expand. IMS provides a qualitative compositional analysis and spatial mapping with high chemical specificity. The spatial mapping information can be 2D or 3D depending on the analysis technique employed. Due to the combination of complex mass spectra coupled with spatial information, large high-dimensional datasets (hyperspectral) are often produced. Therefore, the use of automated computational methods for an exploratory analysis is highly beneficial. The fast-paced development of artificial intelligence (AI) and machine learning (ML) tools has received significant attention in recent years. These tools, in principle, can enable the unification of data collection and analysis into a single pipeline to make sampling and analysis decisions on the go. There are various ML approaches that have been applied to IMS data over the last decade. Here, in this review, we discuss recent examples of the common unsupervised (principal component analysis, non-negative matrix factorization, k-means clustering, uniform manifold approximation and projection), supervised (random forest, logistic regression, XGboost, support vector machine), and other methods applied to various IMS datasets in the past five years. The information from this review will be useful for specialists from both IMS and ML fields since it summarizes current and representative studies of computational ML-based exploratory methods for IMS.

47 OTHER INSTRUMENTATION↗
NASA NTRS1989

Method to predict external store carriage loads at transonic speeds

A computational method for prediction of external store carriage loads at transonic speeds is described. The geometric flexibility required for treatment of isolated and underwing, pylon mounted stores is achieved by computing solutions on a five level embedded grid arrangement. A completely automated grid generation procedure facilitates applications. Store modeling capability consists of bodies of revolution with multiple fore and aft fins. A body conforming grid improves the accuracy of the computed store body flow field. A nonlinear finite difference relaxation scheme, developed specifically for modified transonic small disturbance flow equations, enhances numerical stability and accuracy. As a result, more accurate treatment of low aspect ratio, highly swept and tapered wing planforms is possible. A limited supersonic freestream capability is also provided. Pressure, load distribution, force and moment correlation show good agreement for several test cases.

Rosen, Bruce S.↗
NASA NTRS2000

Development and Application of Computational/In Vitro Toxicological Methods for Chemical Hazard Risk Reduction of New Materials for Advanced Weapon Systems

The development of quantitative structure-activity relationship (QSAR) is essential for reducing the chemical hazards of new weapon systems. The current collaboration between HEST (toxicology research and testing), MLPJ (computational chemistry) and PRS (computational chemistry, new propellant synthesis) is focusing R&D efforts on basic research goals that will rapidly transition to useful products for propellant development. Computational methods are being investigated that will assist in forecasting cellular toxicological end-points. Models developed from these chemical structure-toxicity relationships are useful for the prediction of the toxicological endpoints of new related compounds. Research is focusing on the evaluation tools to be used for the discovery of such relationships and the development of models of the mechanisms of action. Combinations of computational chemistry techniques, in vitro toxicity methods, and statistical correlations, will be employed to develop and explore potential predictive relationships; results for series of molecular systems that demonstrate the viability of this approach are reported. A number of hydrazine salts have been synthesized for evaluation. Computational chemistry methods are being used to elucidate the mechanism of action of these salts. Toxicity endpoints such as viability (LDH) and changes in enzyme activity (glutahoione peroxidase and catalase) are being experimentally measured as indicators of cellular damage. Extrapolation from computational/in vitro studies to human toxicity, is the ultimate goal. The product of this program will be a predictive tool to assist in the development of new, less toxic propellants.

Frazier, John M.↗
NASA NTRS1978

Solution of axisymmetric and two-dimensional inviscid flow over blunt bodies by the method of lines

Comparisons with experimental data and the results of other computational methods demonstrated that very accurate solutions can be obtained by using relatively few lines with the method of lines approach. This method is semidiscrete and has relatively low core storage requirements as compared with fully discrete methods since very little data were stored across the shock layer. This feature is very attractive for three dimensional problems because it enables computer storage requirements to be reduced by approximately an order of magnitude. In the present study it was found that nine lines was a practical upper limit for two dimensional and axisymmetric problems. This condition limits application of the method to smooth body geometries where relatively few lines would be adequate to describe changes in the flow variables around the body. Extension of the method to three dimensions was conceptually straightforward; however, three dimensional applications would also be limited to smooth body geometries although not necessarily to total of nine lines.

Hamilton, H. H., II↗
DOE OSTI2024

How Accurate Are Simulations and Experiments for the Lattice Energies of Molecular Crystals?

Molecular crystals play a central role in a wide range of scientific fields, including pharmaceuticals and organic semiconductor devices. However, they are challenging systems to model accurately with computational approaches because of a delicate interplay of intermolecular interactions such as hydrogen bonding and Van der Waals dispersion forces. Here, by exploiting recent algorithmic developments, we report the first set of diffusion Monte Carlo lattice energies for all 23 molecular crystals in the popular and widely used X23 dataset. Comparisons with previous state-of-the-art lattice energy predictions (on a subset of the dataset) and a careful analysis of experimental sublimation enthalpies reveals that high-accuracy computational methods are now at least as reliable as (computationally derived) experiments for the lattice energies of molecular crystals. Overall, this work demonstrates the feasibility of high-level explicitly correlated electronic structure methods for broad benchmarking studies in complex condensed phase systems, and signposts a route towards closer agreement between experiment and simulation. Published by the American Physical Society 2024

Physics↗
NASA NTRS1993

Tomographic methods in flow diagnostics

This report presents a viewpoint of tomography that should be well adapted to currently available optical measurement technology as well as the needs of computational and experimental fluid dynamists. The goals in mind are to record data with the fastest optical array sensors; process the data with the fastest parallel processing technology available for small computers; and generate results for both experimental and theoretical data. An in-depth example treats interferometric data as it might be recorded in an aeronautics test facility, but the results are applicable whenever fluid properties are to be measured or applied from projections of those properties. The paper discusses both computed and neural net calibration tomography. The report also contains an overview of key definitions and computational methods, key references, computational problems such as ill-posedness, artifacts, missing data, and some possible and current research topics.

Decker, Arthur J.↗
NASA NTRS1988

Method to predict external store carriage characteristics at transonic speeds

Development of a computational method for prediction of external store carriage characteristics at transonic speeds is described. The geometric flexibility required for treatment of pylon-mounted stores is achieved by computing finite difference solutions on a five-level embedded grid arrangement. A completely automated grid generation procedure facilitates applications. Store modeling capability consists of bodies of revolution with multiple fore and aft fins. A body-conforming grid improves the accuracy of the computed store body flow field. A nonlinear relaxation scheme developed specifically for modified transonic small disturbance flow equations enhances the method's numerical stability and accuracy. As a result, treatment of lower aspect ratio, more highly swept and tapered wings is possible. A limited supersonic freestream capability is also provided. Pressure, load distribution, and force/moment correlations show good agreement with experimental data for several test cases. A detailed computer program description for the Transonic Store Carriage Loads Prediction (TSCLP) Code is included.

Rosen, Bruce S.↗
NASA NTRS1996

Active Control of Fan Noise: Feasibility Study: Numerical Computation of Acoustic Mode Reflection Coefficients for an Unflanged Cylindrical Duct - Volume 5

A computational method to predict modal reflection coefficients in cylindrical ducts has been developed based on the work of Homicz, Lordi, and Rehm, which uses the Wiener-Hopf method to account for the boundary conditions at the termination of a thin cylindrical pipe. The purpose of this study is to develop a computational routine to predict the reflection coefficients of higher order acoustic modes impinging on the unflanged termination of a cylindrical duct. This effort was conducted wider Task Order 5 of the NASA Lewis LET Program, Active Noise Control of aircraft Engines: Feasibility Study, and will be used as part of the development of an integrated source noise, acoustic propagation, ANC actuator coupling, and control system algorithm simulation. The reflection coefficient prediction will be incorporated into an existing cylindrical duct modal analysis to account for the reflection of modes from the duct termination. This will provide a more accurate, rapid computation design tool for evaluating the effect of reflected waves on active noise control systems mounted in the duct, as well as providing a tool for the design of acoustic treatment in inlet ducts. As an active noise control system design tool, the method can be used preliminary to more accurate but more numerically intensive acoustic propagation models such as finite element methods. The resulting computer program has been shown to give reasonable results, some examples of which are presented. Reliable data to use for comparison is scarce, so complete checkout is difficult, and further checkout is needed over a wider range of system parameters. In future efforts the method will be adapted as a subroutine to the GEAE segmented cylindrical duct modal analysis program.

Kraft, R. E.↗
NASA NTRS1971

Graphical method for analyzing digital computer efficiency

Analysis method utilizes graph-theoretic approach for evaluating computation cost and makes logical distinction between linear graph of a computation and linear graph of a program. It applies equally well to other processes which depend on quatitative edge nomenclature and precedence relationships between edges.

Chan, S. P.↗
NASA NTRS2000

A Validation Summary of the NCC Turbulent Reacting/non-reacting Spray Computations

This pper provides a validation summary of the spray computations performed as a part of the NCC (National Combustion Code) development activity. NCC is being developed with the aim of advancing the current prediction tools used in the design of advanced technology combustors based on the multidimensional computational methods. The solution procedure combines the novelty of the application of the scalar Monte Carlo PDF (Probability Density Function) method to the modeling of turbulent spray flames with the ability to perform the computations on unstructured grids with parallel computing. The calculation procedure was applied to predict the flow properties of three different spray cases. One is a nonswirling unconfined reacting spray, the second is a nonswirling unconfined nonreacting spray, and the third is a confined swirl-stabilized spray flame. The comparisons involving both gas-phase and droplet velocities, droplet size distributions, and gas-phase temperatures show reasonable agreement with the available experimental data. The comparisons involve both the results obtained from the use of the Monte Carlo PDF method as well as those obtained from the conventional computational fluid dynamics (CFD) solution. Detailed comparisons in the case of a reacting nonswirling spray clearly highlight the importance of chemistry/turbulence interactions in the modeling of reacting sprays. The results from the PDF and non-PDF methods were found to be markedly different and the PDF solution is closer to the reported experimental data. The PDF computations predict that most of the combustion occurs in a predominantly diffusion-flame environment. However, the non-PDF solution predicts incorrectly that the combustion occurs in a predominantly vaporization-controlled regime. The Monte Carlo temperature distribution shows that the functional form of the PDF for the temperature fluctuations varies substantially from point to point. The results also bring to the fore some of the deficiencies associated with the use of assumed-shape PDF methods in spray computations.

Raju, M. S.↗