Search NASA⌕ Search

SEARCH · Search NASA

Results for “methods and applications”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Recent advances and applications of deep learning methods in materials science

Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large materials databases has fueled the application of DL methods in atomistic prediction in particular. In contrast, advances in image and spectral data have largely leveraged synthetic data enabled by high-quality forward models as well as by generative unsupervised DL methods. In this article, we present a high-level overview of deep learning methods followed by a detailed discussion of recent developments of deep learning in atomistic simulation, materials imaging, spectral analysis, and natural language processing. For each modality we discuss applications involving both theoretical and experimental data, typical modeling approaches with their strengths and limitations, and relevant publicly available software and datasets. We conclude the review with a discussion of recent cross-cutting work related to uncertainty quantification in this field and a brief perspective on limitations, challenges, and potential growth areas for DL methods in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Rapid particle generation from an STL file and related issues in the application of material point methods to complex objects

Abstract In this paper, we focus on three issues related to applications of material point methods (MPMs) to objects with complex geometries. They are material point generation, compatibility of material points with a mesh, and sensitivity to mesh orientation. An efficient method of generating material points from a stereolithography (STL) file is introduced. This material point generation method is independent of the mesh used in MPM calculations. The compatibility between the material points and the mesh is then studied. We also show that the original MPM and the dual domain material point (DDMP) method are sensitive to mesh orientation. These issues are related to the calculation of the internal force and are concerns of the MPMs. They become more prominent when MPMs are applied to complex geometries. Our numerical results show that the recently developed local stress difference (LSD) algorithm (Perez et al. in J Comp Phys 498:112681, 2024) can be used to effectively address them.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A PROVEN APPROACH FOR EFFECTIVE COMPUTER SECURITY SELF-ASSESSMENTS AT NUCLEAR FACILITIES

A proven method for conducting cybersecurity self-assessments at nuclear power plants is now available for international use. This method was originally developed by Pacific Northwest National Laboratory, under the sponsorship of the U.S. Nuclear Regulatory Commission (NRC), for use at U.S. nuclear power plants. The “Method,” described in NUREG/CR-6847 “Cyber Security Self-Assessment Method for U.S. Nuclear Power Plants,” was originally a limited release document that was withheld from public disclosure but is now publicly available. The Method provides a systematic, phased, and risk-informed approach to help decision makers and security specialists understand their relative cybersecurity posture. Completed Method assessments may be used to support or validate selection of computer security controls to mitigate cyber threats as well as demonstrate compliance with regulations or statutes enacted by competent authorities. The Method assesses the cybersecurity posture of key systems at a nuclear facility with a focus on protection of design base functions. It considers both physical and digital elements of system vulnerabilities and the resulting potential consequences from exploitation. It is well-suited for addressing blended cyberattacks. A semi-quantitative analytical approach is used in the evaluation of potential vulnerabilities, consequences, and risks and provides a technical basis for the selection of security controls to mitigate cyberattacks. The Method’s application at U.S. nuclear power plants has been very encouraging. The only nuclear plant in the United States that did not have adverse findings during its initial NRC computer security inspection prepared for inspection through the diligent application of this self-assessment method and the implementation of recommendations that came out of that self-assessment. Nuclear facilities around the world might find application of the Method extremely helpful for making cost-effective, risk-based decisions regarding computer security and for preparing to pass computer security inspections by their competent authorities.

Cyber security, Nuclear security, Self-assessment↗
DOE OSTI2021

Reduced scaling formulation of CASPT2 analytical gradients using the supporting subspace method

We present a reduced scaling and exact reformulation of state specific complete active space second-order perturbation (CASPT2) analytical gradients in terms of the MP2 and Fock derivatives using the supporting subspace method. This work follows naturally from the supporting subspace formulation of the CASPT2 energy in terms of the MP2 energy using dressed orbitals and Fock builds. For a given active space configuration, the terms corresponding to the MP2-gradient can be evaluated with O(N5) operations, while the rest of the calculations can be computed with O(N3) operations using Fock builds, Fock gradients, and linear algebra. When tensor-hyper-contraction is applied simultaneously, the computational cost can be further reduced to O(N4) for a fixed active space size. The new formulation enables efficient implementation of CASPT2 analytical gradients by leveraging the existing graphical processing unit (GPU)-based MP2 and Fock routines. We present benchmark results that demonstrate the accuracy and performance of the new method. Example applications of the new method in ab initio molecular dynamics simulation and constrained geometry optimization are given.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Methods of fabricating porous ceramic electrodes for solid state battery applications

Compositions and methods for the fabrication of electrode and porous lithium-garnet electrolyte scaffolds for use in solid state batteries and other devices are provided. The methods produce porous structures using phase inversion or high shear compaction processes to fabricate a solid-state battery electrode material from LLZO electrolytes. Engineered electrode structures with a porous scaffold of solid electrolyte material provide lower interfacial resistances and a mechanical support for a thin solid electrode layer improving performance.

Tucker, Michael↗
DOE OSTI2021

EXAGRAPH: Graph and combinatorial methods for enabling exascale applications

Combinatorial algorithms in general and graph algorithms in particular play a critical enabling role in numerous scientific applications. However, the irregular memory access nature of these algorithms makes them one of the hardest algorithmic kernels to implement on parallel systems. With tens of billions of hardware threads and deep memory hierarchies, the exascale computing systems in particular pose extreme challenges in scaling graph algorithms. The codesign center on combinatorial algorithms, ExaGraph, was established to design and develop methods and techniques for efficient implementation of key combinatorial (graph) algorithms chosen from a diverse set of exascale applications. Algebraic and combinatorial methods have a complementary role in the advancement of computational science and engineering, including playing an enabling role on each other. In this paper, we survey the algorithmic and software development activities performed under the auspices of ExaGraph from both a combinatorial and an algebraic perspective. In particular, we detail our recent efforts in porting the algorithms to manycore accelerator (GPU) architectures. We also provide a brief survey of the applications that have benefited from the scalable implementations of different combinatorial algorithms to enable scientific discovery at scale. We believe that several applications will benefit from the algorithmic and software tools developed by the ExaGraph team.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Do optimization methods in deep learning applications matter?

With advances in deep learning, exponential data growth and increasing model complexity, developing efficient optimization methods are attracting much research attention. Several implementations favor the use of Conjugate Gradient (CG) and Stochastic Gradient Descent (SGD) as being practical and elegant solutions to achieve quick convergence, however, these optimization processes also present many limitations in learning across deep learning applications. Recent research is exploring higher-order optimization functions as better approaches, but these present very complex computational challenges for practical use. Comparing first and higher-order optimization functions, in this paper, our experiments reveal that Levemberg-Marquardt (LM) significantly supersedes optimal convergence but suffers from very large processing time increasing the training complexity of both, classification and reinforcement learning problems. Our experiments compare off-the-shelf optimization functions(CG, SGD, LM and L-BFGS) in standard CIFAR, MNIST, CartPole and FlappyBird experiments.The paper presents arguments on which optimization functions to use and further, which functions would benefit from parallelization efforts to improve pretraining time and learning rate convergence.

Ozyildirim, Buse Melis↗
DOE OSTI2019

CO{sub 2} laser-induced micro-plume treatment of silicon: technique and application

A method for treating the surface of crystalline silicon (α-Si) covered with a fused silica (SiO{sub 2}) plate by a laser-induced plume arising from the absorption of CO{sub 2} laser radiation in glass is presented. The mechanism of micro-plume formation and the effect of this micro-plume on α-Si sample are considered. The α-Si processing regimes were determined that relate the depth of the formed relief to the radiation power density, the temperature of the micro-plume formed during SiO{sub 2} irradiation was measured and reached 3000 K. The diffraction phase gratings were designed, manufactured on silicon, and tested, they successfully split 10.6 μm laser beam at 0 and ± 1 diffraction orders. The method belongs to the group of direct writing methods and is easily adapted to different types of diffraction elements on the surface of Si and other materials transparent to 10 μm irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Protective aluminum oxide surface coatings and low-temperature forming process for high-temperature applications

A method of both coating a substrate with aluminum oxide and infusing the substrate with elemental aluminum is disclosed. In one example, the method includes providing a metal powder/polymer binder slurry, the slurry having a solvent, an organic binder, metal granules and a seed element, wherein the metal granules include Al; dispersing the slurry upon a Cr-containing surface; after dispersing the slurry, exposing the slurry to air and maintaining the temperature of the slurry and substrate below 110° C. to remove at least a portion of the solvent from the slurry; and, in a combined step, both exposing the binder, metal granules and substrate to air and heating the remaining slurry and substrate at a temperature less than or equal to 1000° C. to both diffuse at least a portion of the metal of the metal granules into the substrate and coat the substrate with aluminum oxide.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Tunable anisotropy of co-based nanocomposites for magnetic field sensing and inductor applications

A method includes producing an amorphous precursor to a nanocomposite, performing devitrification of the amorphous precursor, forming, based on the devitrification, the nanocomposite comprising an induced magnetic anisotropy, and for a first portion of the nanocomposite, determining a desired value of a magnetic permeability of the first portion, tuning, based on the desired value, the induced magnetic anisotropy for the first portion, and adjusting, based on the tuning of the induced magnetic anisotropy of the first portion, a first magnetic permeability value of the first portion of the nanocomposite, wherein the first magnetic permeability value is different from a second magnetic permeability value for a second portion of the nanocomposite.

Leary, Alex M.↗
DOE OSTI2023

Tunable anisotropy of co-based nanocomposites for magnetic field sensing and inductor applications

A method includes producing an amorphous precursor to a nanocomposite, the amorphous precursor comprising a material that is substantially without crystals not exceeding 20% volume fraction; performing devitrification of the amorphous precursor, wherein the devitrification comprises a process of crystallization; forming, based on the devitrification, the nanocomposite with nano-crystals that contains an induced magnetic anisotropy; tuning, based on one or more of composition, temperature, configuration, and magnitude of stress applied during annealing and modification, the magnetic anisotropy of the nanocomposite; and adjusting, based on the tuned magnetic anisotropy, a magnetic permeability of the nanocomposite.

Leary, Alex M.↗
DOE OSTI2024

RF cured nanocomposite adhesives for multi-material joining applications

A method for fabricating, and curing, nanocomposite adhesives including introducing nanoheater elements into a heat-curing adhesive to fabricate a nanocomposite adhesive, and providing a radio-frequency (RF) electromagnetic wave to the nanocomposite adhesive to heat, and cure the nanocomposite adhesive. The nanocomposite adhesive is physically applied to first and second materials to bond the first and second materials upon curing of the nanocomposite adhesive, and the RF electromagnetic wave has a frequency in the radio-frequency range, having energy that is transferred to the nanoheater elements by electromagnetic wave interactions with permanent and induced dipoles, intrinsic photon-phonon interaction, or interactions with nanoheater defects and grain structures.

Zhang, Yuepeng↗
DOE OSTI2022

A machine learning inversion scheme for determining interaction from scattering

Small angle scattering techniques have now been routinely used to quantitatively determine the potential of mean force in colloidal suspensions. However the numerical accuracy of data interpretation is often compounded by the approximations adopted by liquid state analytical theories. To circumvent this long standing issue, here we outline a machine learning strategy for determining the effective interaction in the condensed phases of matter using scattering. Via a case study of colloidal suspensions, we show that the effective potential can be probabilistically inferred from the scattering spectra without any restriction imposed by model assumptions. Comparisons to existing parametric approaches demonstrate the superior performance of this method in accuracy, efficiency, and applicability. This method can effectively enable quantification of interaction in highly correlated systems using scattering and diffraction experiments.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Risk-Informed Analysis for an Enhanced Resilient PWR with ATF, FLEX, and Passive Cooling

This report documents the activities performed by Idaho National Laboratory (INL) during the fiscal year (FY) 2019 for the DOE Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of Accident Tolerant Fuel (ATF), optimal use of Diverse and Flexible Coping Strategy (FLEX), enhancements to plant components and systems, and the incorporation of augmented or new passive cooling systems, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors safety features (both active and passive) and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. The FY 2019 efforts documented in this report is an extension of those conducted in FY 2018. The same analysis process, risk analysis approaches, and analysis tools as in FY 2018 are used for near-term ATF cladding [i.e., Iron-Chromium-Aluminum (FeCrAl) cladding and Chromium (Cr) coated cladding] designs under the postulated loss of feedwater (LOFW) and steam generator tube rupture (SGTR) accident scenarios. In addition, FLEX analysis was presented for an overview of FLEX equipment and strategies implemented in nuclear industry after Fukushima accident. A FLEX model was developed and incorporated into the generic SAPHIRE model to assess the risk impact from FLEX. FLEX HRA analysis was performed which suggested an approach to HRA with FLEX strategies. Passive cooling system analysis includes an overview of the DNC system, the RELAP5-3D simulations of the DNC system in selected SBO scenarios, and the evaluation of the DNC system risk impact using the generic PRA model.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Risk-Informed ATF and FLEX Analysis for an Enhanced Resilient BWR Under Design-Basis and Beyond-Design-Basis Accidents

This report documents the activities performed by the Idaho National Laboratory (INL) during fiscal year (FY) 2020 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of accident-tolerant fuel (ATF), optimal use of diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, and the incorporation of augmented or new passive cooling systems, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors’ safety features (both active and passive) and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. One main focus of the FY 2020 efforts documented in this report was to extend the analyses conducted in FYs 2018 and 2019 for a pressurized water reactor (PWR) to a boiling water reactor (BWR). The same analysis process, risk analysis approaches, and analysis tools as in the previous work for PWR were used for a generic BWR with near-term ATF cladding (i.e., Iron-Chromium-Aluminum [FeCrAl] cladding and Chromium [Cr]-coated cladding) designs under the postulated station blackout (SBO) and medium loss-of-coolant (MLOCA) accident scenarios. In addition, a FLEX model was developed and incorporated into a generic BWR probabilistic risk assessment (PRA) model using the INL-developed software tool, Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE), to assess the risk impact from FLEX. The other main focus of the FY 2020 efforts was to advance analysis methods, including developing dynamic approach for FLEX human reliability analysis (HRA) using the INL-developed software tool, Event Modeling Risk Assessment using Linked Diagrams (EMRALD), as well as developing a multicriterion benefit evaluation (MCBE) method for evaluating costs and benefits of safety enhancements in nuclear power plants (NPPs). As a case study, the MCBE method was applied to evaluate the costs and benefits brought by FLEX implementation.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Risk-Informed Analysis for Enhanced Resilient Nuclear Power Plant with Initiatives including ATF, FLEX, and Advanced Battery Technology

This report documents the activities performed by the Idaho National Laboratory (INL) during fiscal year (FY) 2021 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk-Informed Systems Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of accident-tolerant fuel (ATF), optimal use of diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, the incorporation of augmented or new passive cooling systems, the advanced battery technology with extended capacity, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors? safety features and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. The ERP R&D efforts in FY 2021 are focused on three industry initiatives, including accident-tolerant fuel (ATF), optimal use of diverse and flexible coping strategy (FLEX), and advanced battery technology with extended capacity.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Review of Amendment Delivery and Distribution Methods, and Relevance to Potential In Situ Source Area Treatment at the Hanford Site

The U.S. Department of Energy’s Hanford Site in southeastern Washington State is a complex of multiple facilities where historical release events in the Central Plateau area have resulted in subsurface contamination of the vadose zone, a perched-water zone, and underlying aquifer. Although some contaminants have already migrated through the vadose zone into the groundwater, contaminants remaining in the unsaturated zone are a potential long-term risk as a source for further groundwater contamination. Moreover, a perched-water zone located in the 200-DV-1 Operable Unit at Hanford creates further remediation difficulties. Remediation options are limited for contaminants located in the vadose and perched-water zones within the Central Plateau due to considerable depth, co-located contaminants, and complexities associated with physical and biogeochemical heterogeneities. Existing comprehensive reviews discuss potential remedial technologies relevant to Hanford Site conditions (e.g., deep vadose zone and perched water) and provide treatment technology recommendations. Many of the recommended in situ remediation technologies rely on introduction of amendments into the subsurface to achieve remedial goals. However, there are currently few review or guidance documents that provide a comprehensive look at mechanisms and considerations related to amendment delivery and distribution. This document summarizes amendment types, delivery techniques, subsurface access methods, and the applicability of delivery methods and amendments for specific subsurface target zones, including in the context of Hanford Central Plateau applications. Guidance on the appropriateness of a remedial technology for a specific site and contaminant is not included within this document. Rather, this document is intended to be used when considering remediation technologies and the associated amendments. An overview of amendment types (i.e., liquid, gas, and solids) and access/distribution methods used in subsurface remediation is provided, along with discussion of the maturity level (low, medium, or high), advantages, and limitations that relate to the potential effectiveness of each approach in the context of site-specific factors (subsurface geology, geochemistry, contaminant properties, etc.). There are many Hanford Site-specific factors that influence the suitability and appropriateness of amendment delivery strategies. Excluding amendment delivery approaches that are unsuitable for the Hanford context, each approach was assessed for applicability to the following target zones: unsaturated high permeability, unsaturated low permeability, perched water, saturated high permeability, and saturated low permeability zones. This compilation and discussion related to amendment delivery mechanisms provides a useful resource for evaluating remedial alternatives for source area contamination in the Hanford Central Plateau.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Phase-based velocity extraction method for photonic Doppler velocimetry with potential higher time resolution

We present an extension of the [Takeda et al., J. Opt. Soc. Am. 72, 156 (1982)] phase extraction method to heterodyne photonic Doppler velocimetry applications. The method yields results equivalent to those obtained by the short-time Fourier transform (STFT), while offering potential improvements in time resolution. Unlike STFT, which relies on window functions, such as the Hamming window, that emphasize central data points and diminish the influence of edges, the extended Takeda method utilizes all data uniformly. This uniform treatment allows for the derivation of empirical equations that directly relate velocity error to the actual time resolution rather than to the local analysis duration. The established equation provides a useful metric for both optimizing hardware configuration and guiding data analysis. Simulation and experimental results confirm that, for a given dataset, specifying a target time resolution yields consistent velocity errors for both methods. These findings underscore the Takeda method’s advantages, particularly its potential higher time resolution and reduced computational burden, making it a valuable tool for high-throughput applications such as laser dynamic compression experiments.

Computer simulation↗