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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Middle Atmospheric Transport Properties of Assimilated Datasets

One of the most compelling reasons for performing data assimilation in the middle atmosphere is to obtain global, balanced datasets for studies of trace gas transport and chemistry. This is a major motivation behind the Goddard Earth observation System-Data Assimilation System (GEOS-DAS). Previous studies have shown that while this and other data assimilation systems can generally obtain good estimates of the extratropical rotational velocity field, the divergent part of the dynamical field is deficient; this impacts the "residual circulation" and leads to spurious trace gas transport on seasonal and interannual timescales. These problems are impacted by the quality and the method of use of the observational data and by deficiencies in the atmospheric general circulation model. Whichever the cause at any place and time, the "solution" is to introduce non-physical forcing terms into the system (the so-called incremental analysis updates); these can directly (thermal) or indirectly (mechanical) affect the residual circulation. This paper will illustrate how the divergent circulation is affected by deficiencies in both observations and models. Theoretical considerations will be illustrated with examples from the GEOS-DAS and from simplified numerical experiments. These are designed to isolate known problems, such as the inability of models to sustain a quasi-biennial oscillation and sparse observational constraints on tropical dynamics, or radiative inconsistencies in the presence of volcanic aerosols.

Pawson, Steven↗
DOE OSTI2021

Elucidating the Onset of Plasticity in Sliding Contacts Using Differential Computational Orientation Tomography

Abstract Depending on the mechanical and thermal energy introduced to a dry sliding interface, the near-surface regions of the mated bodies may undergo plastic deformation. In this work, we use large-scale molecular dynamics simulations to generate “differential computational orientation tomographs” (dCOT) and thus highlight changes to the microstructure near tribological FCC alloy surfaces, allowing us to detect subtle differences in lattice orientation and small distances in grain boundary migration. The analysis approach compares computationally generated orientation tomographs with their undeformed counterparts via a simple image analysis filter. We use our visualization method to discuss the acting microstructural mechanisms in a load- and time-resolved fashion, focusing on sliding conditions that lead to twinning, partial lattice rotation, and grain boundary-dominated processes. Extracting and laterally averaging the color saturation value of the generated tomographs allows us to produce quantitative time- and depth-resolved maps that give a good overview of the progress and severity of near-surface deformation. Corresponding maps of the lateral standard deviation in the color saturation show evidence of homogenization processes occurring in the tribologically loaded microstructure, frequently leading to the formation of a well-defined separation between deformed and undeformed regions. When integrated into a computational materials engineering framework, our approach could help optimize material design for tribological and other deformation problems. Graphic Abstract .

36 MATERIALS SCIENCE↗
DOE OSTI2025

Model-based Hierarchical Reinforcement Learning for Improved Physical Security Design: A Prototype

Prior work in FY24 developed an adversarial AI agent aid in path analysis of physical protection systems. This agent, trained using a model-based reinforcement learning algorithm, was able to successfully learn the most vulnerable path in facilities. It was able to extend the current state of practice for physical protection design by exhibiting dynamic behavior based on current environmental conditions. Whereas PathTrace largely performs a static, graph-based analysis, the AI agent was able to make decisions based on relative position in the facility, current conditions (was the adversarial agnet discovered?), and proximity to secondary targets. The agent demonstrated some novel capabilities, but had limitations that need to be resolved before it can be used for production purposes. For example, the adversarial agent generalizes poorly and takes a relatively long time to train. Nonetheless, there is still considerable promise for developing the adversarial agent further in order to explore even richer, more dynamic behaviors (e.g., adversary motivations, environmental debris, and more). This work considers a complementary idea; development of a planning agent. The planning agent is envisioned as an auto-complete-like tool that can help accelerate security system design by human experts. The agent would respect existing barriers and sensors placed by a human expert while offering cost-effective suggestions (i.e., implicitly balancing effectiveness with cost) to improve the design. The goal is for this agent to be part of an expert’s toolbox, not to totally upend the current state-of-practice, or to displace human experts. The ultimate goal would be concurrent training of both the adversarial and planning agent together, to learn entirely through self-play. This would represent an entirely new way of performing system deign. We selected a hierarchical, model-based reinforcement learning algorithm to serve as the planning agent. This is an extension of concepts used in the prior FY24 adversarial agent work. There, we had a single agent acting an environment. Here, we have two different sub-agents (policies), working together, to form a complete agent. There is a manager policy, which can select abstract goals on slower time scales, and a worker, which performs primitive actions to reach goals selected by the manager. It is worth noting that this class of algorithm is challenging to work with. From our understanding, our work is one of the first successful uses of model-based reinforcement learning (MBRL) in nuclear energy1 , and likely the first hierarchical model-based reinforcement learning application in nuclear energy. Further, this work is one of the first known attempts to apply AI to perform a design tasks in nuclear energy. Consequently, there were significant implementation challenges and the bulk of the work was focused on successful implementation and algorithm design. The results presented here are very low technology readiness level as a consequence of the lack of related literature, but still represent a significant step forward in the pursuit of applied AI for design.

42 ENGINEERING↗
NASA NTRS2011

System Identification Applied to Dynamic CFD Simulation and Wind Tunnel Data

Demanding aerodynamic modeling requirements for military and civilian aircraft have provided impetus for researchers to improve computational and experimental techniques. Model validation is a key component for these research endeavors so this study is an initial effort to extend conventional time history comparisons by comparing model parameter estimates and their standard errors using system identification methods. An aerodynamic model of an aircraft performing one-degree-of-freedom roll oscillatory motion about its body axes is developed. The model includes linear aerodynamics and deficiency function parameters characterizing an unsteady effect. For estimation of unknown parameters two techniques, harmonic analysis and two-step linear regression, were applied to roll-oscillatory wind tunnel data and to computational fluid dynamics (CFD) simulated data. The model used for this study is a highly swept wing unmanned aerial combat vehicle. Differences in response prediction, parameters estimates, and standard errors are compared and discussed

Murphy, Patrick C.↗
DOE OSTI2025

Exploring Domain-Wall Pinning in Ferroelectrics via Automated High-Throughput Atomic Force Microscopy

Domain-wall dynamics in ferroelectric materials are strongly position-dependent, since each polar interface is locked into a unique local microstructure. This necessitates spatially resolved studies of wall pinning using scanning-probe microscopy techniques. The pinning centers and pre-existing domain walls are usually sparse within the image plane, precluding the use of dense hyperspectral imaging modes and requiring time-consuming human experimentation. Here, a large-area epitaxial PbTiO 3 film on cubic KTaO 3 was investigated to quantify the electric-field-driven dynamics of the polar–strain domain structures using ML-controlled automated piezoresponse force microscopy. Analysis of 1500 switching events reveals that domain-wall displacement depends not only on field parameters but also on the local ferroelectric–ferroelastic configuration. For example, twin boundaries in polydomains regions, like a 1 – /c+ ∥ a 2 – /c – , stay pinned up to a certain level of bias magnitude and change only marginally as the bias increases from 20 to 30 V, whereas single-variant boundaries, like the a 2 + /c + ∥ a 2 – /c – stack, are already activated at 20 V. These statistics on the possible ferroelectric and ferroelastic wall orientations, together with the automated high-throughput AFM workflow, can be distilled into a predictive map that links domain configurations to pulse parameters. Here, this microstructure-specific rule set forms the foundation for the design of ferroelectric memories.

automated scanning probe microscopy↗
DOE OSTI2021

Efficacy of the Method of Four Coefficients to Determine Charge-Carrier Scattering

The investigation of the electronic properties of semiconductors from transport measurements (i.e., resistivity, Hall, and Seebeck coefficient measurements) is challenging due to the averaging of charge-carrier dynamics inherent in such measurements. Here, we investigate the incorporation of a fourth measurement of electronic transport, the Nernst coefficient, into the analysis, termed the method of four coefficients. This approach yields the Fermi level, effective mass, scattering exponent, and relaxation time prefactor. We begin with a review of the underlying mathematics and investigate the mapping between the four-dimensional material property and transport coefficient spaces. We then investigate how the traditional single-parabolic band method yields a single, potentially incorrect point on the solution subspace. This uncertainty can be resolved through Nernst coefficient measurements and we map the span of the ensuing subspace. We conclude with an investigation of how sensitive the analysis of transport coefficients is to experimental error for different sample types.

charge carriers↗
DOE OSTI2025

Floquet engineering of polaritonic amplification in dispersive photonic time crystals

In this study, we investigate the dynamics of dispersive photonic time crystals (PTCs) and their potential applications for controlling light-matter interaction. Using the Lorentz-Drude as dispersive material model, we analyze the effects of periodic modulation of dispersion parameters through both theoretical and numerical analysis, revealing the emergence of hybrid bandgaps from the interaction of polaritonic branches with distinctive characteristics. Our study demonstrates that dispersive PTCs offer novel excitation channels and amplification possibilities, that require lower modulation frequencies compared to nondispersive systems thus alleviating experimental challenges for the realization of PTCs in the optical regime. These findings pave the way for advancements in polaritonic lasing and resonant Raman scattering.

Classical optics↗
DOE OSTI2021

Sierra/SolidMechanics for Target Pulse Analysis

Sierra is a Multiphysics engineering simulation software suite developed and maintained by Sandia National Laboratories. Created for nuclear weapon needs, it is available to national laboratories with a foreign national restriction. The STS Target Systems analysis team is interested in using Sierra to perform explicit dynamics simulations of the tantalum clad tungsten target blocks as a response to sudden temperature changes induced by proton beam pulses. The capability already exists with Abaqus|Explicit, however, there are time and cost limitations due to licensing. The following document serves as a “quick-start” guide to the successful setup, simulation, and post-processing of a target model in Sierra on the OZ3 computing cluster at the Spallation Neutron Source.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Training Ultrasound Image Classification Deep-Learning Algorithms for Pneumothorax Detection Using a Synthetic Tissue Phantom Apparatus

Ultrasound (US) imaging is a critical tool in emergency and military medicine because of its portability and immediate nature. However, proper image interpretation requires skill, limiting its utility in remote applications for conditions such as pneumothorax (PTX) which requires rapid intervention. Artificial intelligence has the potential to automate ultrasound image analysis for various pathophysiological conditions. Training models require large data sets and a means of troubleshooting in real-time for ultrasound integration deployment, and they also require large animal models or clinical testing. Here, we detail the development of a dynamic synthetic tissue phantom model for PTX and its use in training image classification algorithms. The model comprises a synthetic gelatin phantom cast in a custom 3D-printed rib mold and a lung mimicking phantom. When compared to PTX images acquired in swine, images from the phantom were similar in both PTX negative and positive mimicking scenarios. We then used a deep learning image classification algorithm, which we previously developed for shrapnel detection, to accurately predict the presence of PTX in swine images by only training on phantom image sets, highlighting the utility for a tissue phantom for AI applications.

Boice, Emily N. (ORCID:0000000171802842)↗
NASA NTRS1973

Aeroelastic effects on space shuttle dynamics

A simplified analysis procedure for determining static and dynamic aeroelastic loads for the space shuttle and space shuttle configuration is presented. A computer program, originally developed for the Atlas launch vehicle, was modified for simplifying the turbulence response analysis approach. This approach is compared with a more detailed and time consuming approach to space shuttle response to turbulence which was developed earlier. The simplification in going from interference to lumped aerodynamic data was found to give adequate results for preliminary design aeroelastic analysis. Gust loads were found to be approximately 50% of the maximum static aeroelastic loads. The autopilot became unstable when ten elastic modes were included. Elastic effects were found to be less than 3% in the static aeroelastic analysis.

Source record↗
NASA NTRS1974

Development of technology for fluid-structure interaction modeling of a 1/8-scale dynamic model of shuttle External Tank (ET). Volume i: Technical report

A NASTRAN analysis of the external tank (ET) substructure of the 1/8-scale space shuttle structural dynamics model is described. The NASTRAN hydroelastic procedures were used to form a model of the liquid oxygen portion of the ET. Large computer storage requirements and running times were required unless these procedures were modified. Several possibilities were demonstrated including the substitution of the real for the complex eigenvalue routine and the use of the OMIT capability to reduce the number of fluid coordinates. A NASTRAN model of the complete ET was formed and reduced to 252 degrees of freedom. A review of the eigenvector extracted, using the unsymmetrical inverse power method, indicated that the structural OMIT's resulted in unsatisfactory modal deflections. Modifications to the NASTRAN hydroelastic capability appeared necessary to generate a successful ET model. An approach is described which, by assuming incompressibility, reduces the fluid representation to a symmetric mass matrix which can be added to the structural mass. The problem is solved using faster and more efficient eigenvalue routines. Using this approach the ET NASTRAN model was analyzed for three separate weight conditions.

Bernstein, M.↗
NASA NTRS1990

Factorization and the synthesis of optimal feedback gains for distributed parameter systems

An approach based on Volterra factorization leads to a new methodology for the analysis and synthesis of the optimal feedback gain in the finite-time linear quadratic control problem for distributed parameter systems. The approach circumvents the need for solving and analyzing Riccati equations and provides a more transparent connection between the system dynamics and the optimal gain. The general results are further extended and specialized for the case where the underlying state is characterized by autonomous differential-delay dynamics. Numerical examples are given to illustrate the second-order convergence rate that is derived for an approximation scheme for the optimal feedback gain in the differential-delay problem.

Milman, Mark H.↗
NASA NTRS1990

Statistical mechanics models for motion and force planning

The models of statistical mechanics provide an alternative to the methods of classical mechanics more traditionally used in robotics. They have a potential to: improve analysis of object collisions; handle kinematic and dynamic contact interactions within the same frmework; and reduce the need for perfect deterministic world model information. The statistical mechanics models characterize the state of the system as a probability density function (p.d.f.) whose time evolution is governed by a partial differential equation subject to boundary and initial conditions. The boundary conditions when rigid objects collide reflect the conservation of momentum. The models are being developed to embedd in remote semi-autonomous systems with a need to reason and interact with a multiobject environment.

Rodriguez, G.↗
NASA NTRS1991

CH4 and N2O photochemical lifetimes in the upper stratosphere - In situ estimates using SAMS data

Upper stratospheric photochemical lifetimes are estimated in situ for CH4 and N2O for the first time, based on an analysis technique using 3 years of satellite measurements from the Stratospheric And Mesospheric Sounder (SAMS) instrument. The technique involves investigation of the time dependence of tracers injected into high northern latitudes in late winter and their subsequent photochemical decay during the dynamically quiescent summer stratosphere. Dynamical corrections are made for mean meridional circulation contributions. The lifetimes for N2O at 2 and 7 hPa (about 43 and about 35 km altitude) are found to be 1.7 and 8.3 months, respectively. For CH4, 0.6 (about 52 km altitude) and 2 hPa lifetimes are 3.3 and 3.4 months, respectively. These observed values are in good agreement with model calculations by Solomon et al. (1986).

Stanford, J. L.↗
NASA NTRS1991

Numerical analysis of a nuclear fuel element for nuclear thermal propulsion

A computational fluid dynamics model with porosity and permeability formulations in the transport equations has been developed to study the concept of nuclear thermal propulsion through the analysis of a pulsed irradiation of a particle bed element (PIPE). The numerical model is a time-accurate pressure-based formulation. An adaptive upwind scheme is employed for spatial discretization. The upwind scheme is based on second- and fourth-order central differencing with adaptive artificial dissipation. Multiblocked porosity regions have been formulated to model the cold frit, particle bed, and hot frit. Multiblocked permeability regions have been formulated to describe the flow shaping effect from the thickness-varying cold frit. Computational results for several zero-power density PIPEs and an elevated-particle-temperature PIPE are presented. The implications of the computational results are discussed.

Wang, Ten-See↗
NASA NTRS1992

Dynamic modeling and simulation of planetary rovers

This paper documents a preliminary study into the dynamic modeling and computer simulation of wheeled surface vehicles. The research centered on the feasibility of using commercially available multibody dynamics codes running on engineering workstations to perform the analysis. The results indicated that physically representative vehicle mechanics can be modeled and simulated in state-of-the-art Computer Aided Engineering environments, but at excessive cost in modeling and computation time. The results lead to the recommendation for the development of an efficient rover mobility-specific software system. This system would be used for vehicle design and simulation in planetary environments; controls prototyping, design, and testing; as well as local navigation simulation and expectation planning.

Lindemann, Randel A.↗
NASA NTRS2000

Estimating the Ocean Flow Field From Combined Sea Surface Temperature and Sea Surface Height Data

The primary focus of this project was on the estimation of the three-dimensional, absolute and time-evolving general circulation of the global ocean from a combined analysis of remotely sensed fields of sea surface temperature (SST) and sea surface height (SSH). The synthesis of those two fields was performed with other relevant physical data, and appropriate dynamical ocean models with emphasis on constraining ocean general circulation models by a combination of both SST and SSH data. This effort is directly related to an attempt to describe the mechanisms which give rise to observed SST and its variability on seasonal and inter-annual timescales, its relation to ocean-atmosphere interaction, and the dynamical coupling between the ocean mixed layer and the deep interior ocean. This is one of the fundamental climate related questions being pursued currently under the CLIVAR Program. Because of the strong turbulent mixing associated with atmospheric fluxes of momentum, heat and freshwater through the sea surface, the ocean forms a shallow surface boundary layer, the mixed layer which is largely homogeneous in its constituents. The relation between the temperature of the remotely sensed "skin" and the bulk of the mixed layer is largely understood (Reynolds and Smith 1994; Emery et al., 1995). However, because the surface mixed layer is effectively decoupled from the underlying ocean dynamics, an interpretation of satellite SST observations in isolation and in direct use for dynamical studies is very difficult. As a result, the impact of SST data on the understanding of ocean variability.

Stammer, Detlef↗
NASA NTRS2007

Using Arctic Data for Magnetospheric Modeling: Current State and Future Perspectives

Geomagnetic storms are the most dramatic manifestations of solar influences on the magnetosphere. Storms are accompanied by substantial Space Weather effects. For these, as well as for scientific reasons, storms have been a special target of magnetospheric modeling for quite some time. Accordingly, there has been considerable interest and success in improving the application of magnetospheric models to storm-time dynamics, an to compare to data from arctic observatories. In this presentation, we present an overview of CCMC-studies of storm-time model capabilities, and we will provide an overall assessment of capabilities. In addition, we will present an analysis of future challenges, and we will suggest strategies for future model development.

Hesse, Michael↗