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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fixed Depth Hamiltonian Simulation via Cartan Decomposition

Simulating quantum dynamics on classical computers is challenging for large systems due to the significant memory requirements. Simulation on quantum computers is a promising alternative, but fully optimizing quantum circuits to minimize limited quantum resources remains an open problem. In this study, we tackle this problem by presenting a constructive algorithm, based on Cartan decomposition of the Lie algebra generated by the Hamiltonian, which generates quantum circuits with time-independent depth. We highlight our algorithm for special classes of models, including Anderson localization in one-dimensional transverse field $\mathrm{XY}$ model, where $\mathscr{O}$(n 2 )-gate circuits naturally emerge. Compared to product formulas with significantly larger gate counts, our algorithm drastically improves simulation precision. In addition to providing exact circuits for a broad set of spin and fermionic models, our algorithm provides broad analytic and numerical insight into optimal Hamiltonian simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1975

Computer aided flexible envelope designs

Computer aided design methods are presented for the design and construction of strong, lightweight structures which require complex and precise geometric definition. The first, flexible structures, is a unique system of modeling folded plate structures and space frames. It is possible to continuously vary the geometry of a space frame to produce large, clear spans with curvature. The second method deals with developable surfaces, where both folding and bending are explored with the observed constraint of available building materials, and what minimal distortion result in maximum design capability. Alternative inexpensive fabrication techniques are being developed to achieve computer defined enclosures which are extremely lightweight and mathematically highly precise.

Resch, R. D.↗
NASA NTRS1976

Numerical problems in the advection of pollutants

Prediction of pollutant transport involves solution of the advection equation numerically. Truncation errors arising from integrating the advection equation by using finite difference schemes are discussed. Numerical errors manifest themselves in artificial dissipation and dispersion of pollutants. Criteria for measuring the dissipation and dispersion are presented, and minimization of those errors is discussed. An alternative procedure by integration in the wavenumber space is examined. Examples illustrating quantitative discrepancy in actual forecasting are also shown.

Liu, C. Y.↗
NASA NTRS1990

Multiple Access Trade Study

The Personal Access Satellite System (PASS) strawman design uses a hybrid Time Division Multiple Access (TDMA)/Frequency Division Multiple Access (FDMA) implementation. TDMA is used for the forward direction (from Suppliers to Users), and FDMA for the return direction (from Users to Suppliers). An alternative architecture is proposed that will require minimal real time coordination and yet provide a fast access method by using random access Code Division Multiple Access (CDMA). The CDMA system issues are addressed such as connecting suppliers and users, both of whom may be located anywhere in the CONUS, when the user terminals are constrained in size and weight; and providing efficient traffic routing under highly variable traffic requirements. It is assumed that bandwidth efficiency is not of paramount importance. CDMA or Spread Spectrum Multiple Access (SSMA) communication is a method in which a group of carriers operate at the same nominal center frequency but are separable from each other by the low cross correlation of the spreading codes used. Interference and multipath rejection capability, ease of selective addressing and message screening, low density power spectra for signal hiding and security, and high resolution ranging are among the benefits of spread spectrum communications.

Motamedi, Masoud↗
NASA NTRS1994

Design of scaled down structural models

In the aircraft industry, full scale and large component testing is a very necessary, time consuming, and expensive process. It is essential to find ways by which this process can be minimized without loss of reliability. One possible alternative is the use of scaled down models in testing and use of the model test results in order to predict the behavior of the larger system, referred to herein as prototype. This viewgraph presentation provides justifications and motivation for the research study, and it describes the necessary conditions (similarity conditions) for two structural systems to be structurally similar with similar behavioral response. Similarity conditions provide the relationship between a scaled down model and its prototype. Thus, scaled down models can be used to predict the behavior of the prototype by extrapolating their experimental data. Since satisfying all similarity conditions simultaneously is in most cases impractical, distorted models with partial similarity can be employed. Establishment of similarity conditions, based on the direct use of the governing equations, is discussed and their use in the design of models is presented. Examples include the use of models for the analysis of cylindrical bending of orthotropic laminated beam plates, of buckling of symmetric laminated rectangular plates subjected to uniform uniaxial compression and shear, applied individually, and of vibrational response of the same rectangular plates. Extensions and future tasks are also described.

Simitses, George J.↗
NASA NTRS1999

PARAMESH: A Parallel Adaptive Mesh Refinement Community Toolkit

In this paper, we describe a community toolkit which is designed to provide parallel support with adaptive mesh capability for a large and important class of computational models, those using structured, logically cartesian meshes. The package of Fortran 90 subroutines, called PARAMESH, is designed to provide an application developer with an easy route to extend an existing serial code which uses a logically cartesian structured mesh into a parallel code with adaptive mesh refinement. Alternatively, in its simplest use, and with minimal effort, it can operate as a domain decomposition tool for users who want to parallelize their serial codes, but who do not wish to use adaptivity. The package can provide them with an incremental evolutionary path for their code, converting it first to uniformly refined parallel code, and then later if they so desire, adding adaptivity.

MacNeice, Peter↗
NASA NTRS2005

Parallel Adaptive Mesh Refinement Library

Parallel Adaptive Mesh Refinement Library (PARAMESH) is a package of Fortran 90 subroutines designed to provide a computer programmer with an easy route to extension of (1) a previously written serial code that uses a logically Cartesian structured mesh into (2) a parallel code with adaptive mesh refinement (AMR). Alternatively, in its simplest use, and with minimal effort, PARAMESH can operate as a domain-decomposition tool for users who want to parallelize their serial codes but who do not wish to utilize adaptivity. The package builds a hierarchy of sub-grids to cover the computational domain of a given application program, with spatial resolution varying to satisfy the demands of the application. The sub-grid blocks form the nodes of a tree data structure (a quad-tree in two or an oct-tree in three dimensions). Each grid block has a logically Cartesian mesh. The package supports one-, two- and three-dimensional models.

Mac-Neice, Peter↗
DOE OSTI2025

Machine Learning-Driven Optimization of Building Enclosures for Moisture Durability and Thermal Performance

The design of moisture-durable building enclosures with low embodied carbon often involves an iterative process of selecting the materials for the specific exposure conditions to meet the performance requirements. While hygrothermal simulations are commonly used to evaluate moisture durability, they often require advanced expertise for proper implementation. Machine learning (ML) provides a promising alternative by streamlining the design process and minimizing the reliance on complex simulations. This study presents a machine learning-based approach for predicting moisture durability in residential wall assemblies. The ML model was trained to estimate the mold index and maximum moisture content of various layers under typical exposure conditions. The model achieved a high predictive accuracy, with a coefficient of determination (R²) exceeding 0.90 when compared to traditional hygrothermal simulations on materials that were not part of training the ML model. Building on these results, the ML model was developed into a practical tool for optimizing wall assembly designs. This tool allows users to automatically optimize material selections based on energy, moisture, and carbon performance criteria. By incorporating multi-objective optimization, the tool identifies configurations that minimize embodied carbon while maintaining moisture safety and code-compliant thermal performance. Additionally, it provides insights into how material choices influence assembly durability, energy efficiency, and carbon reduction. The tool will be implemented in the Building Science Advisor (BSA) to enhance its performance and provide more granularity on the results. This research highlights the potential for ML-driven tools to simplify the design of high-performance building enclosures, offering architects and engineers a faster, more efficient way to balance critical performance factors.

Salonvaara, Mikael [ORNL] (ORCID:0000000318991554)↗
NASA NTRS2004

Micro-Scale Regenerative Heat Exchanger

A micro-scale regenerative heat exchanger has been designed, optimized and fabricated for use in a micro-Stirling device. Novel design and fabrication techniques enabled the minimization of axial heat conduction losses and pressure drop, while maximizing thermal regenerative performance. The fabricated prototype is comprised of ten separate assembled layers of alternating metal-dielectric composite. Each layer is offset to minimize conduction losses and maximize heat transfer by boundary layer disruption. A grating pattern of 100 micron square non-contiguous flow passages were formed with a nominal 20 micron wall thickness, and an overall assembled ten-layer thickness of 900 microns. Application of the micro heat exchanger is envisioned in the areas of micro-refrigerators/coolers, micropower devices, and micro-fluidic devices.

Moran, Matthew E.↗
DOE OSTI2022

Low temperature dry reforming of methane using Ru-Ni-Mg/ceria-zirconia catalysts: Effect of Ru loading and reduction temperature

Dry reforming catalysts, especially those with activity at moderate temperatures, have been intensely investigated to enhance the conversion of biogas. Here, Ru is evaluated as a promoter for Ni-Mg based catalysts. Catalysts based on 1.4 wt%Ni-1.0 wt%Mg-Ce 0.6 Zr 0.4 O 2 with Ru (0.02–0.32 wt%) were prepared using incipient wetness. The reducibility of the catalysts and conversions increased with increasing Ru content. Increases in conversions with increasing Ru loading was attributed to the additional active sites and synergistic effect between Ru and Ni, which weakened Ni-Mg interactions. Samples showed dry reforming activity at low temperatures (450–510 °C). Reaction rates and activation energies of higher loading Ru samples (1.4 wt%Ni-1.0 wt%Mg/Ce 0.6 Zr 0.4 O 2 with 0.16 and 0.32 wt%Ru) decreased when the reduction temperature was raised from 300 to 400 °C. A 20 h TOS study showed stable catalytic activity with minimal coke deposition. Furthermore, the results suggest that Ru is an alternative to Pt in promoting low temperature dry reforming of methane.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Development of an integrated model for energy systems planning and carbon dioxide mitigation under uncertainty – Tradeoffs between two-level decision makers

Highlights: • A bi-level model is developed for energy systems planning and carbon dioxide mitigation. • Tradeoffs between two-level decision-makers’ demands are quantified under uncertainty. • The energy and environmental impact of CO{sub 2} mitigation policy is analyzed for Beijing. • Results provide a range of decision alternatives between system optimality and reliability. A bi-level fuzzy programming (BFLP) method was developed for energy systems planning (ESP) and carbon dioxide (CO{sub 2}) mitigation under uncertainty. BFLP could handle fuzzy information and leader-follower problem in decision-making processes. It could also address the tradeoffs among different decision makers in two decision-making levels through prioritizing the most important goal. Then, a BFLP-ESP model was formulated for planning energy system of Beijing, in which the upper-level objective is to minimize CO{sub 2} emission and the lower-level objective is to minimize the system cost. Results provided a range of decision alternatives that corresponded to a tradeoff between system optimality and reliability under uncertainty. Compared to the single-level model with a target to minimize system cost, the amounts of pollutant/CO{sub 2} emissions from BFLP-ESP were reduced since the study system would prefer more clean energies (i.e. natural gas, LPG and electricity) to replace coal fuel. Decision alternatives from BFLP were more beneficial for supporting Beijing to adjust its energy mix and enact its emission-abatement policy. Results also revealed that the low-carbon policy for power plants (e.g., shutting down all coal-fired power plants) could lead to a potentially increment of imported energy for Beijing, which would increase the risk of energy shortage. The findings could help decision makers analyze the interactions between different stakeholders in ESP and provide useful information for policy design under uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units

Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the development of machine-learning (ML) models that make these predictions more efficiently. Training graph neural networks over large atomistic databases introduces unique computational challenges such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs such as social networks. We demonstrate a novel hardware-software co-design approach to scale up the training of atomistic graph neural networks (GNN) for structure and property prediction. First, to eliminate redundant computation and memory associated with alternative padding techniques and to improve throughput via minimizing communication, we formulate the effective coalescing of the batches of variable-size atomistic graphs as the bin packing problem and introduce a hardware-agnostic algorithm to pack these batches. In addition, we propose hardware-specific optimizations including a planner and vectorization for the gather-scatter operations targeted for Graphcore’s Intelligence Processing Unit (IPU), as well as model-specific optimizations such as merged communication collectives and optimized softplus. Putting these all together, we demonstrate the effectiveness of the proposed co-design approach by providing an implementation of a well-established atomistic GNN on the Graphcore IPUs. We evaluate the training performance on multiple atomistic graph databases with varying degrees of graph counts, sizes and sparsity. Here, we demonstrate that such a co-design approach can reduce the training time of atomistic GNNs and can improve the performance by up to 1.5× compared to the baseline implementation of the model on the IPUs. Additionally, we compare our IPU implementation with a Nvidia GPU-based implementation and show that our atomistic GNN implementation on the IPUs can run 1.8× faster on average compared to the execution time on the GPUs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Induction Heating for Tritium Storage Beds (FY19 PDRD Project Summary Report)

Metal hydride beds used for storing hydrogen isotopes at the Savannah River Site are conductively heated and cooled to desorb and absorb gases during storage cycling. While several storage bed configurations have been utilized over the years, many achieve heating by utilizing electric cartridge heaters positioned laterally along the longest axis of the storage bed (FACE Gen 2 Beds). Others achieve heating and cooling through hot and cold nitrogen flow (Gen 1 Beds). While these beds/heating configurations are well-designed for storage cycling operations, it is unclear if they can be regenerated to operating conditions once too much helium has accumulated in them. Full regeneration of hydride beds occurs around 625 - 650 °C. It is unclear if the currently employed electric cartridge heaters in Gen 2 beds can reach these temperatures. Furthermore, since swelling can occur during routine heating operations, it is unclear if existing cartridge heaters in Gen 2 beds can be swapped for higher-power cartridges that can reach 625 - 650 °C . Similarly, nitrogen air flow (to the best of our knowledge) cannot cause Gen 1 beds to reach these temperatures. Thus, existing Gen 1 and Gen 2 beds need to be heated through an alternative method to removal helium, so the beds can either return to normal operation or be disposed of. The goal of this PDRD was to investigate if induction heating can be used for various heating processes involving hydride storage beds (e.g. regeneration, gas cycling, helium heel removal). In the original call for proposals, this PDRD fell under "Gas Processing" area of interest # 3: "Develop methods to deploy alternate ways to heat existing process equipment to minimize impact to glove box environment."

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1976

Method and apparatus for background signal reduction in opto-acoustic absorption measurement

The sensitivity of an opto-acoustic absorption detector is increased to make it possible to measure trace amounts of constituent gases. A second beam radiation path is created through the sample cell identical to a first path except as to length, alternating the beam through the two paths and minimizing the detected pressure difference for the two paths while the beam wavelength is tuned away from the absorption lines of the sample. Then with the beam wavelength tuned to the absorption line of any constituent of interest, the pressure difference is a measure of trace amounts of the constituent. The same improved detector may also be used for measuring the absorption coefficient of known concentrations of absorbing gases.

Rosengren, L. G.↗
NASA NTRS1977

Applications of remote sensing to estuarine management

Remote sensing was used in the resolution of estuarine problems facing federal and Virginia governmental agencies. A prototype Elizabeth River Surface Circulation Atlas was produced from photogrammetry to aid in oil spill cleanup and source identification. Aerial photo analysis twice led to selection of alternative plans for dredging and spoil disposal which minimized marsh damage. Marsh loss due to a mud wave from a highway dyke was measured on sequential aerial photographs. An historical aerial photographic sequence gave basis to a potential Commonwealth of Virginia legal claim to accreting and migrating coastal islands.

Munday, J. C., Jr.↗
NASA NTRS1993

Polarimetric Multispectral Imaging Technology

The Jet Propulsion Laboratory is developing a remote sensing technology on which a new generation of compact, lightweight, high-resolution, low-power, reliable, versatile, programmable scientific polarimetric multispectral imaging instruments can be built to meet the challenge of future planetary exploration missions. The instrument is based on the fast programmable acousto-optic tunable filter (AOTF) of tellurium dioxide (TeO2) that operates in the wavelength range of 0.4-5 microns. Basically, the AOTF multispectral imaging instrument measures incoming light intensity as a function of spatial coordinates, wavelength, and polarization. Its operation can be in either sequential, random access, or multiwavelength mode as required. This provides observation flexibility, allowing real-time alternation among desired observations, collecting needed data only, minimizing data transmission, and permitting implementation of new experiments. These will result in optimization of the mission performance with minimal resources. Recently we completed a polarimetric multispectral imaging prototype instrument and performed outdoor field experiments for evaluating application potentials of the technology. We also investigated potential improvements on AOTF performance to strengthen technology readiness for applications. This paper will give a status report on the technology and a prospect toward future planetary exploration.

Cheng, L.-J.↗
NASA NTRS1993

A comparison of two methods for solving 3-D unsteady compressible viscous flows

Numerical solutions of 3D unsteady compressible flows for several steady and unsteady cases are obtained using two procedures - a noniterative Alternating Direction Implicit (ADI) scheme and a Generalized Minimal RESidual (GMRES) method. Results obtained are compared with each other and also with experimental data. It is found that the GMRES procedure can provide significant speedups compared to the noniterative ADI procedure.

Hixon, Ray↗
NASA NTRS1992

Solar powered multipurpose remotely powered aircraft

Increase in energy demands coupled with rapid depletion of natural energy resources have deemed solar energy as an attractive alternative source of power. The focus was to design and construct a solar powered, remotely piloted vehicle to demonstrate the feasibility of solar energy as an effective, alternate source of power. The final design included minimizing the power requirements and maximizing the strength-to-weight and lift-to-drag ratios. Given the design constraints, Surya (the code-name given to the aircraft), is a lightweight aircraft primarily built using composite materials and capable of achieving level flight powered entirely by solar energy.

Alexandrou, A. N.↗