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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
NASA NTRS1985

N/P GaAs concentrator solar cells with an improved grid and bushbar contact design

The major requirements for a solar cell used in space applications are high efficiency at AMO irradiance and resistance to high energy radiation. Gallium arsenide, with a band gap of 1.43 eV, is one of the most efficient sunlight to electricity converters (25%) when the the simple diode model is used to calculate efficiencies at AMO irradiance, GaAs solar cells are more radiation resistant than silicon solar cells and the N/P GaAs device has been reported to be more radiation resistant than similar P/N solar cells. This higher resistance is probably due to the fact that only 37% of the current is generated in the top N layer of the N/P cell compared to 69% in the top layer of a P/N solar cell. This top layer of the cell is most affected by radiation. It has also been theoretically calculated that the optimized N/P device will prove to have a higher efficiency than a similar P/N device. The use of a GaP window layer on a GaAs solar cell will avoid many of the inherent problems normally associated with a GaAlAs window while still proving good passivation of the GaAs surface. An optimized circular grid design for solar cell concentrators has been shown which incorporates a multi-layer metallization scheme. This multi-layer design allows for a greater current carrying capacity for a unit area of shading, which results in a better output efficiency.

Desalvo, G. C.↗
DOE OSTI2024

Grid-Aware Charging and Operational Optimization for Mixed-Fleet Public Transit

The rapid growth of urban populations and the increasing need for sustainable transportation solutions have prompted a shift towards electric buses in public transit systems. However, the effective management of mixed fleets consisting of both electric and diesel buses poses significant operational challenges. One major challenge is coping with dynamic electricity pricing, where charging costs vary throughout the day. Transit agencies must optimize charging assignments in response to such dynamism while accounting for secondary considerations such as seating constraints. This paper presents a comprehensive mixed-integer linear programming (MILP) model to address these challenges by jointly optimizing charging schedules and trip assignments for mixed (electric and diesel bus) fleets while considering factors such as dynamic electricity pricing, vehicle capacity, and route constraints. We address the potential computational intractability of the MILP formulation, which can arise even with relatively small fleets, by employing a hierarchical approach tailored to the fleet composition. By using real-world data from the city of Chattanooga, Tennessee, USA, we show that our approach can result in significant savings in the operating costs of the mixed transit fleets.

Sen, Rishav↗
DOE OSTI2024

CalWave's xWave Design for PacWave (Final Technical Report)

CalWave Inc. (CalWave) is developing a wave energy converter (WEC) technology that can generate electricity from ocean waves. CalWave’s design offers a unique approach to wave energy conversion that operates fully submerged and can actively adjust the wave excitation. This capability gives the architecture enhanced survivability in ocean storms without adding significant costs. Prior to this project, CalWave had completed a demonstration of a fully functional WEC system in an open ocean demonstration at nominal 1:5 scale under FOA 1663. The goal of this project was the detailed design, following relevant standards and industry best-practices, of a variant of the xWave WEC technology that can safely and efficiently operate at the DOE’s PacWave South test site for a targeted deployment of up two years. The WEC design and associated review processes proceeded in two distinct project phases: a ‘Preliminary’ and a ‘Final’ design phase. The first phase of the project consisted of the systematic design of the WEC’s key features with regards to appropriate IEC standards. The work resulted in a preliminary design of the xWave hull including structural and Power Take-Off (PTO) load estimates, as well as performance estimates for all ocean conditions the WEC would operate in at PacWave South. Following the first open-water demonstration of CalWave’s small-scale “x1” device under FOA 1663, lessons learned were fed directly into a comprehensive review of the xWave design in the second design phase of this FOA project. CalWave’s work was supported by Sandia National Lab (SNL) and the National Renewable Energy Lab (NREL) on the holistic WEC design, and detailed feedback from specialized partners on hull design, mooring and anchoring specification, and electrical grid interconnection. Optimization of the WEC system was performed using a novel numerical optimization tool developed by Sandia and optimization trends were confirmed via an experimental model scale tank test campaign. Performance estimates for PacWave and a detailed xWave design including integration of all relevant system components were concluded. The mooring design was also concluded in the Final design phase using the most up to date sea floor characterization (CPT) data.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Regulators’ Financial Toolbox: Leveraging Software as a Service, Cloud Computing, and Artificial Intelligence in Electric Utilities

The rapid evolution of Software as a Service (SaaS), cloud computing, and artificial intelligence (AI) is transforming the electric utility industry, reshaping operations, customer engagement, and financial models. This webinar introduced how utilities can deploy advanced software solutions and AI-driven analytics to improve grid efficiency, optimize asset management, and accurately forecast demand.

Bartlett, Phillip↗
DOE OSTI2025

Application of Machine Learning and Data Augmentation Algorithms in the Discovery of Metal Hydrides for Hydrogen Storage

The development of efficient and sustainable hydrogen storage materials is a key challenge for realizing hydrogen as a clean and flexible energy carrier. Among various options, metal hydrides offer high volumetric storage density and operational safety, yet their application is limited by thermodynamic, kinetic, and compositional constraints. In this work, we investigate the potential of machine learning (ML) to predict key thermodynamic properties—equilibrium plateau pressure, enthalpy, and entropy of hydride formation—based solely on alloy composition using Magpie-generated descriptors. We significantly expand an existing experimental dataset from ~400 to 806 entries and assess the impact of dataset size and data augmentation, using the PADRE algorithm, on model performance. Models including Support Vector Machines and Gradient Boosted Random Forests were trained and optimized via grid search and cross-validation. Results show a marked improvement in predictive accuracy with increased dataset size, while data augmentation benefits are limited to smaller datasets and do not improve accuracy in underrepresented pressure regimes. Furthermore, clustering and cross-validation analyses highlight the limited generalizability of models across different material classes, though high accuracy is achieved when training and testing within a single hydride family (e.g., AB2). The study demonstrates the viability and limitations of ML for accelerating hydride discovery, emphasizing the importance of dataset diversity and representation for robust property prediction.

augmentation↗
DOE OSTI2025

Characterizing Seasonal Variation of the Atmospheric Mixing Layer Height Using Machine Learning Approaches

As machine learning becomes more integrated into atmospheric science, XGBoost has gained popularity for its ability to assess the relative contributions of influencing factors in the atmospheric boundary layer height. To examine how these factors vary across seasons, a seasonal analysis is necessary. However, dividing data by season reduces the sample size, which can affect result reliability and complicate factor comparisons. To address these challenges, this study replaces default parameters with grid search optimization and incorporates cross-validation to mitigate dataset limitations. Using XGBoost with four years of data from the atmospheric radiation measurement (ARM) (Southern Great Plains (SGP) C1 site, cross-validation stabilizes correlation coefficient fluctuations from 0.3 to within 0.1. With optimized parameters, the R value can reach 0.81. Analysis of the C1 site reveals that the relative importance of different factors changes across seasons. Lower tropospheric stability (LTS, ~0.53) is the dominant factor at C1 throughout the year. However, during DJF, latent heat flux (LHF, 0.44) surpasses LTS (0.22). In SON, LTS (0.58) becomes more influential than LHF (0.18). Further comparisons among the four long-term SGP sites (C1, E32, E37, and E39) show seasonal variations in relative importance. Notably, during JJA, the differences in the relative importance of the three factors across all sites are lower than in other seasons. This suggests that boundary layer development in the summer is not dominated by a single factor, reflecting a more intricate process likely influenced by seasonal conditions such as enhanced convective activity, higher temperatures, and humidity, which collectively contribute to a balanced distribution of parameter impacts. Furthermore, the relative importance of LTS gradually increases from morning to noon, indicating that LTS becomes more significant as the boundary layer approaches its maximum height. Consequently, the LTS in the early morning in autumn exhibits greater relative importance compared to other seasons. This reflects a faster development of the mixing layer height (MLH) in autumn, suggesting that it is easier to retrieve the MLH from the previous day during this period. The findings enhance understanding of boundary layer evolution and contribute to improved boundary layer parameterization.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

NASTRAN maintenance and enhancement experiences

The current capability is described which includes isoparametric elements, optimization of grid point sequencing, and eigenvalue routine. Overlay and coding errors were corrected for cyclic symmetry, transient response, and differential stiffness rigid formats. Error corrections and program enhancements are discussed along with developments scheduled for the current year and a brief description of analyses being performed using the program.

Schmitz, R. P.↗
NASA NTRS1987

Navier Stokes solution of the flowfield over ice accretion shapes

The numerical simulation of flow about ice accretion shapes has been accomplished by solving the Navier-Stokes equations using MacCormack's explicit finite difference scheme. The computations were performed on a CRAY-XMP computer. The influence of turbulence is taken into account by means of an algebraic eddy-viscosity model. In order to optimize the grid spacing and to achieve near orthogonality at the surface of the complex ice shapes, a hyperbolic grid generation scheme is utilized. Particular attention is given to the heat transfer process for which good agreement between the numerical and experimental results is achieved. In addition, liquid water droplet trajectories are coupled within the flowfield along with the resulting collection efficiencies using a parabolized Navier-Stokes formulation.

Scott, J. N.↗
NASA NTRS1987

InP based solar cells for space application: Reduction of external losses

Although InP-based solar cells have considerable potential for space applications, it is necessary to improve efficiencies to around the level of GaAs or Si cells before their excellent radiation resistance can be regarded as a dominant advantage. The authors concentrate on indium-tin-oxide/InP cells, presenting data relating to reduction of the contact resistance of the rear surface metallization, reduction of reflectance losses by choosing indium-tin-oxide deposition conditions to give specific optical properties, and reduction of losses associated with the grid. Simultaneous optimization of all of these has led to improved values of Jsc. For devices of approximately 1 cm2 in area, the largest Jsc achieved to date is 28.1 mA/aq cm (AM1.5, SERI/NASA direct normal spectrum, 25 C, total area, 100 mW/sq cm). For this particular cell, the equivalent AM0 value of Jsc was 34.6 mA/sq cm, which appears to be the largest reported for any InP-based cell.

Wu, X.↗
NASA NTRS1994

Status of diffused junction p+n InP solar cells for space applications

Recently, we have succeeded in fabricating diffused junction p(sup +)n(Cd,S) InP solar cells with measured AMO, 25 C open circuit voltage (V(sub OC)) of 887.6 mV, which, to the best of our knowledge, is higher than previously reported V(sub OC) values for any InP homojunction solar cells. The experiment-based projected achievable efficiency of these cells using LEC grown substrates is 21.3 percent. The maximum AMO, 25 C internal losses due to date on bare cells is, however, only 13.2 percent. This is because of large external and internal losses due to non-optimized front grid design, antireflection (AR) coating and emitter thickness. This paper summarizes recent advances in the technology of fabrication of p(sup +)n InP diffused structures and solar cells, resulted from a study undertaken in an effort to increase the cell efficiency. The topics discussed in this paper include advances in: (1) the formation on thin p(sup +) InP:Cd emitter layers, (2) electroplated front contacts, (3) surface passivation and (4) the design of a new native oxide/Al2O3/MgF2 tree layer AR coating using a chemically-grown P-rich passivating oxide as a first layer. Based on the high radiation resistance and the excellent post-irradiation annealing and recovery demonstrated in the early tests done to date, as well as the projected high efficiency and low-cost high-volume fabricability, these cells show a very good potential for space photovoltaic applications.

Faur, Mircea↗
NASA NTRS1996

A wavelet-optimized, very high order adaptive grid and order numerical method

Differencing operators of arbitrarily high order can be constructed by interpolating a polynomial through a set of data followed by differentiation of this polynomial and finally evaluation of the polynomial at the point where a derivative approximation is desired. Furthermore, the interpolating polynomial can be constructed from algebraic, trigonometric, or, perhaps exponential polynomials. This paper begins with a comparison of such differencing operator construction. Next, the issue of proper grids for high order polynomials is addressed. Finally, an adaptive numerical method is introduced which adapts the numerical grid and the order of the differencing operator depending on the data. The numerical grid adaptation is performed on a Chebyshev grid. That is, at each level of refinement the grid is a Chebvshev grid and this grid is refined locally based on wavelet analysis.

Jameson, Leland↗
NASA NTRS1999

Parallel Computation of Sensitivity Derivatives with Application to Aerodynamic Optimization of a Wing

This paper focuses on the parallel computation of aerodynamic derivatives via automatic differentiation of the Euler/Navier-Stokes solver CFL3D. The comparison with derivatives obtained by finite differences is presented and the scaling of the time required to obtain the derivatives relative to the number of processors employed for the computation is shown. Finally, the derivative computations are coupled with an optimizer and surface/volume grid deformation tools to perform an optimization to reduce the drag of a three-dimensional wing.

Biedron, Robert T.↗
NASA NTRS1994

Status of Diffused Junction p(+)n InP Solar Cells for Space Applications

Recently, we have succeeded in fabricating diffused junction p(+)n(Cd,S) InP solar cells with measured AMO, 25 C open circuit voltage (V(sub OC)) of 887.6 mV, which, to the best of our knowledge, is higher than previously reported V(sub OC) values for any InP homojunction solar cells. The experiment-based projected achievable efficiency of these cells using LEC grown substrates is 21.3%. The maximum AMO, 25 C efficiency recorded to date on bare cells is, however, only 13.2%. This is because of large external and internal losses due to non-optimized front grid design, antireflection (AR) coating and emitter thickness. This paper summarizes recent advances in the technology of fabrication of p(+)n InP diffused structures and solar cells, resulted from a study undertaken in an effort to increase the cell efficiency. The topics discussed in this paper include advances in: 1) the formation of thin p(+) InP:Cd emitter layers, 2) electroplated front contacts, 3) surface passivation and 4) the design of a new native oxide/AI203/MgF2 three layer AR coating using a chemically-grown P-rich passivating oxide as a first layer. Based on the high radiation resistance and the excellent post-irradiation annealing and recovery demonstrated in the early tests done to date, as well as the projected high efficiency and low-cost high-volume fabricability, these cells show a very good potential for space photovoltaic applications.

Faur, Mircea↗
NASA NTRSDate not supplied

Hourly GPP Estimation In Australia Using Himawari-8 AHI Products

We extended the MODIS 17 algorithm to hourly Gross Primary Product (GPP) estimation for Australia in 2018. AHI 1-km data are available at NASA Earth Exchange (NEX) facility. The high-frequent observation of Advanced Himawari Imager (AHI) enabled us to calculate hourly GPP, which is corresponding to ground observation of carbon flux measured by TERN OzFlux. We interpolated the weather observation data to 1-km grid over Australia ingesting AHI reflectance and radiometric temperature data (NEX-Gridded Hourly Meteorology (NEX-GHM)). Then, we applied MODIS 17 algorithm to each grid with optimized climate regulation functions. The estimation of climate and GPP were well correlated with OzFlux ground observation data.

Himawari-8↗
NASA NTRS2021

Efficiency of Mixed-Element USM3D for Benchmark Three-Dimensional Flows

The unstructured, mixed-element, cell-centered, finite-volume flow solver USM3D is enhanced with new capabilities such as line generation for general unstructured grids and optimization of the iterative solver. The efficiency of the new developments is assessed in a massively parallel environment. The assessments are conducted using a baseline method and the recent hierarchical adaptive nonlinear iteration method framework. Three benchmark turbulent flows, namely, a subsonic separated flow around a three-dimensional hemisphere cylinder configuration, a transonic flow around the ONERA M6 wing, and a supersonic flow through a square duct are considered.

Mohagna J Pandya↗
NASA NTRSDate not supplied

Towards Aerodynamic Shape Optimization Using an Immersed Boundary Overset Grid Method

Traditional Reynolds-averaged Navier-Stokes grid methods applied to aerodynamic shapeoptimization can struggle with the deformation of surface and volume grids at componentintersections, such as at wing-fuselage junctions. To overcome this, we propose an approachwhich utilizes curvilinear overset grids for the discretization of the domain, with the presenceof the body modeled using an immersed boundary method. This approach handles complexgeometries without the need for their explicit integration into the grid. The goal of this approachis to reduce grid generation time and allow for greater geometric freedom for component-basedaerodynamic shape optimization. Two different methods are presented: a source-term-basedand a ghost-node-based immersed boundary method. Flow analyses and adjoint solutionsobtained using the proposed methods show promising comparisons with standard body-fittedgrid methods. Preliminary aerodynamic shape optimization results obtained using one of theimmersed boundary methods are also presented.

TTT↗