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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Melt-Pool Temperature and Size Measurement During Direct Laser Sintering

Additive manufacturing has demonstrated the ability to fabricate complex geometries and components not possible with conventional casting and machining. In many cases, industry has demonstrated the ability to fabricate complex geometries with improved efficiency and performance. However, qualification and certification of processes is challenging, leaving companies to focus on certification of material though design allowable based approaches. This significantly reduces the business case for additive manufacturing. Therefore, real time monitoring of the melt pool can be used to detect the development of flaws, such as porosity or un-sintered powder and aid in the certification process. Characteristics of the melt pool in the Direct Laser Sintering (DLS) process is also of great interest to modelers who are developing simulation models needed to improve and perfect the DLS process. Such models could provide a means to rapidly develop the optimum processing parameters for new alloy powders and optimize processing parameters for specific part geometries. Stratonics’ ThermaViz system will be integrated with the Renishaw DLS system in order to demonstrate its ability to measure melt pool size, shape and temperature. These results will be compared with data from an existing IR camera to determine the best approach for the determination of these critical parameters.

42 ENGINEERING↗
NASA NTRS1994

Optimization for minimum sensitivity to uncertain parameters

A procedure to design a structure for minimum sensitivity to uncertainties in problem parameters is described. The approach is to minimize directly the sensitivity derivatives of the optimum design with respect to fixed design parameters using a nested optimization procedure. The procedure is demonstrated for the design of a bimetallic beam for minimum weight with insensitivity to uncertainties in structural properties. The beam is modeled with finite elements based on two dimensional beam analysis. A sequential quadratic programming procedure used as the optimizer supplies the Lagrange multipliers that are used to calculate the optimum sensitivity derivatives. The method was perceived to be successful from comparisons of the optimization results with parametric studies.

Pritchard, Jocelyn I.↗
NASA NTRS2014

Evaluating LSM-Based Water Budgets Over a West African Basin Assisted with a River Routing Scheme

Within the framework of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project phase 2 (ALMIP-2), this study evaluates the water balance simulated by the Interactions between Soil, Biosphere, and Atmosphere (ISBA) over the upper Oum River basin, in Benin, using a mesoscale river routing scheme (RRS). The RRS is based on the nonlinear Muskingum Cunge method coupled with two linear reservoirs that simulate the time delay of both surface runoff and base flow that are produced by land surface models. On the basis of the evidence of a deep water-table recharge in that region,a reservoir representing the deep-water infiltration (DWI) is introduced. The hydrological processes of the basin are simulated for the 2005-08 AMMA field campaign period during which rainfall and stream flow data were intensively collected over the study area. Optimal RRS parameter sets were determined for three optimization experiments that were performed using daily stream flow at five gauges within the basin. Results demonstrate that the RRS simulates stream flow at all gauges with relative errors varying from -22% to 3% and Nash-Sutcliffe coefficients varying from 0.62 to 0.90. DWI varies from 24% to 67% of the base flow as a function of the sub-basin. The relatively simple reservoir DWI approach is quite robust, and further improvements would likely necessitate more complex solutions (e.g., considering seasonality and soil type in ISBA); thus, such modifications are recommended for future studies. Although the evaluation shows that the simulated stream flows are generally satisfactory, further field investigations are necessary to confirm some of the model assumptions.

Multidisciplinary↗
DOE OSTI2024

autoGEMM: Pushing the Limits of Irregular Matrix Multiplication on Arm Architectures

This paper presents an open-source library that pushes the limits of performance portability for irregular General Matrix Multiplication (GEMM) on the widely-used Arm architectures. Our library, autoGEMM, is designed to support a wide range of Arm processors: from edge devices to HPC-grade CPUs. autoGEMM generates optimized kernels for various hardware configurations by auto-combining fragments of autogenerated micro-kernels that employ hand-written optimizations to maximize computational efficiency. We optimize the kernel pipeline by tuning the register reuse and the data load/store overlapping. In addition, we use a dynamic tiling scheme to generate balanced tile shapes. Finally, we position autoGEMM on top of the TVM framework where our dynamic tiling scheme prunes the search space for TVM to identify the optimal combination of parameters for code optimization. Evaluations on five different classes of Arm chips demonstrate the advantages of autoGEMM. For small matrices, autoGEMM achieves 98% of peak and up to 2.0x speedup over state-of-the-art libraries such as LIBXSMM and LibShalom. For irregular matrices (i.e. tall skinny and long rectangles), autoGEMM is 1.3-2.0x faster than widely-used libraries such as OpenBLAS and Eigen. autoGEMM is publicly available at: https://github.com/wudu98/autoGEMM.

Wu, Du↗
DOE OSTI2015

SU-E-J-120: Comparing 4D CT Computed Ventilation to Lung Function Measured with Hyperpolarized Xenon-129 MRI

Purpose: To correlate ventilation parameters computed from 4D CT to ventilation, profusion, and gas exchange measured with hyperpolarized Xenon-129 MRI for a set of lung cancer patients. Methods: Hyperpolarized Xe-129 MRI lung scans were acquired for lung cancer patients, before and after radiation therapy, measuring ventilation, perfusion, and gas exchange. In the standard clinical workflow, these patients also received 4D CT scans before treatment. Ventilation was computed from 4D CT using deformable image registration (DIR). All phases of the 4D CT scan were registered using a B-spline deformable registration. Ventilation at the voxel level was then computed for each phase based on a Jacobian volume expansion metric, yielding phase sorted ventilation images. Ventilation based upon 4D CT and Xe-129 MRI were co-registered, allowing qualitative visual comparison and qualitative comparison via the Pearson correlation coefficient. Results: Analysis shows a weak correlation between hyperpolarized Xe-129 MRI and 4D CT DIR ventilation, with a Pearson correlation coefficient of 0.17 to 0.22. Further work will refine the DIR parameters to optimize the correlation. The weak correlation could be due to the limitations of 4D CT, registration algorithms, or the Xe-129 MRI imaging. Continued development will refine parameters to optimize correlation. Conclusion: Current analysis yields a minimal correlation between 4D CT DIR and Xe-129 MRI ventilation. Funding provided by the 2014 George Amorino Pilot Grant in Radiation Oncology at the University of Virginia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Potential application of mono/bi-layer molybdenum disulfide (MoS{sub 2}) sheet as an efficient transparent conducting electrode in silicon heterojunction solar cells

In this paper, we have simulated the structure of n-type MoS{sub 2}/silicon heterojunction solar cell and studied its function under different conditions. The optimization of parameters of the cell's layer has been carried out by using AFORS-HET software. In the present study, MoS{sub 2} has been considered as 3-D in nature instead of the reported 2-D nature. In order to ensure the formation of Schottky junction, electric contact has been made along the c-axis to collect the minority charge carriers. After optimizing the various parameters of n-type single layer MoS{sub 2}, power efficiency of 12.44% has been achieved at the room temperature, which has further decreased to 9.042% as the layer number has increased up to 40. Furthermore, after optimizing the parameters of silicon wafer maximum efficiency of 16.4% has been achieved. Temperature dependence of the cell performance has also been studied and the maximum efficiency has been achieved at 300 K. In the present study, we have demonstrated that n-type ultrathin layer of MoS{sub 2} can be used as an excellent transparent conducting electrode.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Uncertainty Analysis in 3D Equilibrium Reconstruction

Reconstruction is an inverse process where a parameter space is searched to locate a set of parameters with the highest probability of describing experimental observations. Due to systematic errors and uncertainty in experimental measurements, this optimal set of parameters will contain some associated uncertainty. This uncertainty in the optimal parameters leads to uncertainty in models derived using those parameters. V3FIT is a three-dimensional (3D) equilibrium reconstruction code that propagates uncertainty from the input signals, to the reconstructed parameters, and to the final model. Here in this paper, we describe the methods used to propagate uncertainty in V3FIT. Using the results of whole shot 3D equilibrium reconstruction of the Compact Toroidal Hybrid, this propagated uncertainty is validated against the random variation in the resulting parameters. Two different model parameterizations demonstrate how the uncertainty propagation can indicate the quality of a reconstruction. As a proxy for random sampling, the whole shot reconstruction results in a time interval that will be used to validate the propagated uncertainty from a single time slice.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Optimal input design for aircraft parameter estimation using dynamic programming principles

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

Klein, Vladislav↗
NASA NTRS1990

Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

Morelli, Eugene A.↗
NASA NTRS1985

Interactive aircraft flight control and aeroelastic stabilization

An analytical model of a 3-D airfoil was used to study an optimization procedure formulated to enhance stability of an airfoil through integrated structural and control synthesis. This procedure is discussed together with preliminary results. These results show that a sensitivity derivative approach utilizing structural parameters, weighting matrix parameters and optimal control parameters (in this case, the design airspeed) is effective in determining the best structural/control design.

Weisshaar, T. A.↗
NASA NTRS1993

Aerodynamic configuration design using response surface methodology analysis

An investigation has been conducted to determine a set of optimal design parameters for a single-stage-to-orbit reentry vehicle. Several configuration geometry parameters which had a large impact on the entry vehicle flying characteristics were selected as design variables: the fuselage fineness ratio, the nose to body length ratio, the nose camber value, the wing planform area scale factor, and the wing location. The optimal geometry parameter values were chosen using a response surface methodology (RSM) technique which allowed for a minimum dry weight configuration design that met a set of aerodynamic performance constraints on the landing speed, and on the subsonic, supersonic, and hypersonic trim and stability levels. The RSM technique utilized, specifically the central composite design method, is presented, along with the general vehicle conceptual design process. Results are presented for an optimized configuration along with several design trade cases.

Engelund, Walter C.↗
NASA NTRS2018

Development and Application of a Tool for Optimizing Composite Matrix Viscoplastic Material Parameters

This document describes a recently developed analysis tool that enhances the resident capabilities of the Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) and its application. MAC/GMC is a composite material and laminate analysis software package developed at NASA Glenn Research Center. The primary focus of the current effort is to provide a graphical user interface (GUI) capability that helps users optimize highly nonlinear viscoplastic constitutive law parameters by fitting experimentally observed/measured stress-strain responses under various thermo-mechanical conditions for braided composites. The tool has been developed utilizing the MATrix LABoratory (MATLAB) (The Mathworks, Inc., Natick, MA) programming language. Illustrative examples shown are for a specific braided composite system wherein the matrix viscoplastic behavior is represented by a constitutive law described by seven parameters. The tool is general enough to fit any number of experimentally observed stress-strain responses of the material. The number of parameters to be optimized, as well as the importance given to each stress-strain response, are user choice. Three different optimization algorithms are included: (1) Optimization based on gradient method, (2) Genetic algorithm (GA) based optimization and (3) Particle Swarm Optimization (PSO). The user can mix and match the three algorithms. For example, one can start optimization with either 2 or 3 and then use the optimized solution to further fine tune with approach 1. The secondary focus of this paper is to demonstrate the application of this tool to optimize/calibrate parameters for a nonlinear viscoplastic matrix to predict stress-strain curves (for constituent and composite levels) at different rates, temperatures and/or loading conditions utilizing the Generalized Method of Cells. After preliminary validation of the tool through comparison with experimental results, a detailed virtual parametric study is presented wherein the combined effects of temperature and loading rate on the predicted response of a braided composite is investigated.

thermo-mechanical; MATLAB; GUI-Based Too↗
DOE OSTI2022

Effects of random forest modeling decisions on biogeochemical time series predictions

Abstract Random forests (RF) are an increasingly popular machine learning approach used to model biogeochemical processes in the Earth system. While RF models are robust to many assumptions that complicate deterministic models, there are several important parameterization decisions for appropriate use and optimal model fit. We explored the role that parameter decisions, including training/testing data splitting strategies, variable selection, and hyperparameters play on RF goodness‐of‐fit by constructing models using 1296 unique parameter combinations to predict concentrations of nitrate, a key nutrient for biogeochemical cycling in aquatic ecosystems. Models were built on long‐term, publicly available water quality and meteorology time series collected by the National Estuarine Research Reserve monitoring network for two contrasting ecosystems representing freshwater and brackish estuaries. We found that accounting for temporal dependence when splitting data into training and testing subsets was key for avoiding over‐estimation of model predictive power. In addition, variable selection, the ratio of training to testing data, and to a lesser degree, variables per split and number of trees, were significant parameters for optimizing RF goodness‐of‐fit. We also explored how model parameter decisions influenced interpretation of the relative importance of predictors to the model, and model predictor‐dependent variable relationships, with results suggesting that both data structure and model parameterization influence these factors. Because much of the current RF literature is written for the computational and statistical science communities, the primary goal of this study is to provide guidelines for aquatic scientists new to machine learning to apply RF techniques appropriately to aquatic biogeochemical datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Accelerating Lipidomic Method Development through in Silico Simulation

Judicious selection of mass spectrometry (MS) acquisition parameters is essential for effectively profiling the broad diversity and dynamic range of biomolecules. Typically, acquisition parameters are individually optimized to maximally characterize analytes from each new sample matrix. This time-consuming process often ignores the synergistic relationship between MS method parameters, producing suboptimal results. Here in this paper, we detail the creation of an algorithm which accurately simulates LC-MS/MS lipidomic data acquisition performance for a benchtop quadrupole-Orbitrap MS system. By coupling this simulation tool with a genetic algorithm for constrained parameter optimization, we demonstrate the efficient identification of LC-MS/MS method parameter sets individually suited for specific sample matrices. Finally, we utilize the in silico simulation to examine how continued developments in MS acquisition speed and sensitivity will further increase the power of MS lipidomics as a vital tool for impactful biochemical analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗