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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
DOE OSTI2022

An extrapolation method to remove spurious stress concentration in micromechanical analyses of composites using pixel-based meshes

It is easier to generate a finite element mesh of complicated geometries with voxel-based meshes compared to conformal meshes. However, the local stresses in voxel-based meshes are higher owing to artificial stress concentration caused due to jagged lines that approximate a curve. Here, we propose a method that accounts for this anomaly which would lead to accurate prediction of maximum von Mises stress in voxel-based meshes. The method is based on the variation of reciprocal of stresses and associated numerical gradient. The prediction of the proposed method is compared against the results of a conformal mesh by considering four two-dimensional example problems. The accuracy of the proposed method is verified using different mesh densities, material properties, and integration schemes. The proposed method was also implemented on a conformal mesh to verify that it filters out just the spurious stress concentration and not the realistic stress concentration.

36 MATERIALS SCIENCE↗
NASA NTRS1982

Galactic cosmic ray gradients, field-aligned and latitudinal, among Voyagers 1/2 and IMP-8

The present investigation represents a summary of a comprehensive analysis of the same subject conducted by Roelof et al. (1981). It is pointed out that the tandem earth-Jupiter trajectories of the Voyager 1/2 spacecraft, combined with baseline measurements from the earth-orbiting IMP 7/8 spacecraft, provide the first opportunity for unambiguously separating latitude from radial or field-aligned effects in galactic cosmic ray gradients. Attention is given to the method of data analysis, and the separation of field-aligned and latitudinal gradients. It is found that latitudinal gradients approximately equal to or greater than 1 percent per deg in the cosmic ray intensity were a common feature of the interplanetary medium between 1 and 5 AU in 1977-78. Except in the most disturbed periods, cosmic ray intensities are well-ordered in field-aligned structures.

Roelof, E. C.↗
DOE OSTI2024

Semantic Stealth: Crafting Covert Adversarial Patches for Sentiment Classifiers Using Large Language Models

Deep learning models have been shown to be vulnerable to adversarial attacks, in which perturbations to their inputs cause the model to produce incorrect predictions. As opposed to adversarial attacks in computer vision, where small changes introduced to pixel values can drastically alter a model's output while remaining imperceptible to humans, text-based attacks are difficult to conceal due to the discrete nature of tokens. Consequently, unconstrained gradient-based attacks often produce adversarial examples that lack semantic meaning, rendering them detectable through visual inspection or perplexity filters. In contrast to methods that rely on gradient-based optimization in the embedding space, we propose an approach that leverages a Large Language Model's ability to generate grammatically correct and semantically meaningful text to craft adversarial patches that seamlessly blend in with the original input text. These patches can be used to alter the behavior of a target model, such as a text classifier. Since our approach does not rely on gradient backpropagation, it only requires access to the target model's confidence scores, making it a grey-box attack. We demonstrate the feasibility of our approach using open-source LLMs, including Intel's Neural Chat, Llama2, and Mistral-Instruct, to generate adversarial patches capable of altering the predictions of a distilBERT model fine-tuned on the IMDB reviews dataset for sentiment classification.

Roa Carvajal, Maria↗
DOE OSTI2025

A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching

Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.

Metamaterial↗
NASA NTRS1992

A spectral overlay method for dissimilar materials

The spectral overlay method is applied to examine the stress distribution along the interface between the two different materials. The essential feature of the spectral overlay method is that the high resolution of localized steep gradients can be achieved by overlaying a spectral interpolant on a standard finite element mesh. In order to evaluate this method and compare it with conventional finite element method, a test problem with high gradients in Poisson equation has been devised. The results show that this method is very powerful in capturing the shape of the gradient field and its peak value. Solutions for two problems with interfaces between dissimilar materials are then given to illustrate the effectiveness of this method.

Belytschko, T.↗
DOE OSTI2021

Prediction of the Thermal Runaway Limit and Optimal Operation of Heat Transfer-Limited, Fixed-Bed Reactor Systems

Here, we derive a new prediction for thermal runaway starting from the alpha model for fixed-bed reactor systems. This method accounts for thermal resistance internal to the reactor tube and the radial temperature gradients that result. To showcase our method, we compare its predictions to other common criteria for thermal runaway using o-xylene oxidation as the example chemistry. Even in systems where internal heat transfer is negligible, the empirical practical design criterion for thermal runaway is inaccurate. For cases where internal heat transfer is relevant, our runaway limit is more stringent than limits derived from simpler 1-D models. To augment our work, we optimize the product yield with the thermal runaway constraint using orthogonal collocation. Using the alpha model, the results illustrate that the thermal runaway limit can be accurately determined using either numerical or analytical methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Toward continuum gyrokinetic study of high-field mirrors

High-temperature superconducting (HTS) magnetic mirrors under development exploit strong fields with high mirror ratio to compress loss cones and enhance confinement and may offer cheaper, more compact fusion power plant candidates. This new class of devices could exhibit largely unexplored interchange and gradient-driven modes. Such instabilities, and methods to stabilize them, can be studied with gyrokinetics, given the strong magnetization and prevalence of kinetic effects. Our focus here is to (a) determine if oft-used gyrokinetic models for open field lines produce the electron-confining (Pastukhov) electrostatic potential and (b) examine and address challenges faced by gyrokinetic codes in studying HTS mirrors. Here, we show that a one-dimensional limit of said models self-consistently develops a potential qualitatively approaching the analytical Pastukhov level. Additionally, we describe the computational challenges of studying high mirror ratios with open field line gyrokinetic solvers and offer a force softening method to mitigate small time steps needed for time integration in colossal magnetic field gradients produced by HTS coils, providing a 19X speedup.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

PyTREES

PyTREES (Python tool for Training/Testing Robust Explainable Ensembles on Spectra) is software that implements a data-driven approach to predicting the amount of specific oxides present in materials samples of laser-induced breakdown spectroscopy (LIBS); such as from the ChemCam instrument suite onboard the NASA Curiosity rover. PyTREES is designed to input LIBS data in the format provided by the ChemCam team [1]. PyTREES then applies appropriate pre-processing to this data [2], and implements several regression methods for predicting oxides from spectra. The regression methods include: ensemble methods (random forest, extra trees, and gradient boosting regression) and blended submodels using the “double blending” technique. PyTREES additionally implements methods for quantifying the importance of features in regression model: (1) mean decrease in impurity (MDI) and (2) permutation importance to investigate the wavelengths used by the regression methods. [1] Gasda et al. (2021). Spectrochim Acta B, 181, 106223. [2] Clegg et al. (2017). Spectrochim Acta B , 129, 64–85.

Oyen, Diane↗
NASA NTRS1974

Parameter estimation for terrain modeling from gradient data

This paper developes a method for mathematically modeling terrain surfaces for use on an unmanned Martian vehicle. The data collected by the vehicle consists of terrain height and two directional slopes at each data point. The parameters for the mathematical terrain model are stochastically determined by using least square approximations.-

Shen, C. N.↗
NASA NTRS1985

The formation of stable pH gradients with weak monovalent buffers for isoelectric focusing in free solution

Two methods which utilize simple buffers for the generation of stable pH gradients (useful for preparative isoelectric focusing) are compared and contrasted. The first employs preformed gradients comprised of two simple buffers in density-stabilized free solution. The second method utilizes neutral membranes to isolate electrolyte reservoirs of constant composition from the separation column. It is shown by computer simulation that steady-state gradients can be formed at any pH range with any number of components in such a system.

Mosher, Richard A.↗
DOE OSTI2020

Multireference Electron Correlation Methods: Journeys along Potential Energy Surfaces

Multireference electron correlation methods describe static and dynamical electron correlation in a balanced way and, therefore, can yield accurate and predictive results even when single-reference methods or multiconfigurational self-consistent field theory fails. One of their most prominent applications in quantum chemistry is the exploration of potential energy surfaces. This includes the optimization of molecular geometries, such as equilibrium geometries and conical intersections and on-the-fly photodynamics simulations, both of which depend heavily on the ability of the method to properly explore the potential energy surface. Because such applications require nuclear gradients and derivative couplings, the availability of analytical nuclear gradients greatly enhances the scope of quantum chemical methods. This review focuses on the developments and advances made in the past two decades. A detailed account of the analytical nuclear gradient and derivative coupling theories is presented. Emphasis is given to the software infrastructure that allows one to make use of these methods. Notable applications of multireference electron correlation methods to chemistry, including geometry optimizations and on-the-fly dynamics, are summarized at the end followed by a discussion of future prospects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1983

A study of cell electrophoresis as a means of purifying growth hormone secreting cells

Growth hormone secreting cells of the rat anterior pituitary are heavily laden with granules of growth hormone and can be partialy purified on the basis of their resulting high density. Two methods of preparative cell electrophoresis were investigated as methods of enhancing the purification of growth hormone producing cells: density gradient electrophoresis and continuous flow electrophoresis. Both methods provided a two- to four-fold enrichment in growth hormone production per cell relative to that achieved by previous methods. Measurements of electrophoretic mobilities by two analytical methods, microscopic electrophoresis and laser-tracking electrophoresis, revealed very little distinction between unpurified anterior pituitary cell suspensions and somatotroph-enriched cell suspensions. Predictions calculated on the basis of analytical electrophoretic data are consistent with the hypothesis that sedimentation plays a significant role in both types of preparative electrophoresis and the electrophoretic mobility of the growth hormone secreting subpopulation of cells remains unknown.

Plank, Lindsay D.↗
NASA NTRS1981

Improved method for calculating transonic velocities on blade-to-blade stream surfaces of a turbomachine

A method was developed to improve the accuracy of an existing computer program used to calculate transonic velocities on a blade-to-blade surface of a turbomachine. The method eliminates problems encountered in obtaining solutions with the velocity gradient equation when large gradients in velocity occur through the blade row. With the improved method, results indicate that the transonic solution can be obtained by scaling the velocities obtained at the reduced mass flow rate where all velocities are subsonic thereby eliminating the need for a solution of the velocity gradient equation. Solutions obtained with the scaling method on a two dimensional compressor cascade and an axial turbine stator show good agreement with experimental data. The results obtained for the stationary blade rows and comparison of analytical results obtained with and without the present method suggest that the method will yield an improved solution for centrifugal compressor impellers.

Wood, J. R.↗
DOE OSTI2021

Ab initio molecular dynamics on quantum computers

Ab initio molecular dynamics (AIMD) is a valuable technique for studying molecules and materials at finite temperatures where the nuclei evolve on potential energy surfaces obtained from accurate electronic structure calculations. In this work, we present an approach to running AIMD simulations on noisy intermediate-scale quantum (NISQ)-era quantum computers. The electronic energies are calculated on a quantum computer using the variational quantum eigensolver (VQE) method. Algorithms for computation of analytical gradients entirely on a quantum computer require quantum fault-tolerant hardware, which is beyond NISQ-era. Therefore, we compute the energy gradients numerically using finite differences, the Hellmann-Feynman theorem, and a correlated sampling technique. This method only requires additional classical calculations of electron integrals for each degree of freedom without any additional computations on a quantum computer beyond the initial VQE run. As a proof of concept, AIMD simulations are demonstrated for the H-2 molecule on IBM quantum devices. In addition, we demonstrate the validity of the method for larger molecules using full configuration interaction wave functions. As quantum hardware and noise mitigation techniques continue to improve, the method can be utilized for studying larger molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Review of high-throughput techniques for detecting solid phase Transformation from material libraries produced by combinatorial methods

High-throughput measurement techniques are reviewed for solid phase transformation from materials produced by combinatorial methods, which are highly efficient concepts to fabricate large variety of material libraries with different compositional gradients on a single wafer. Combinatorial methods hold high potential for reducing the time and costs associated with the development of new materials, as compared to time-consuming and labor-intensive conventional methods that test large batches of material, one- composition at a time. These high-throughput techniques can be automated to rapidly capture and analyze data, using the entire material library on a single wafer, thereby accelerating the pace of materials discovery and knowledge generation for solid phase transformations. The review covers experimental techniques that are applicable to inorganic materials such as shape memory alloys, graded materials, metal hydrides, ferric materials, semiconductors and industrial alloys.

Lee, Jonathan A.↗