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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

1.1 eV GaInAs Cell Development for Dual-Use Solar and 1070 nm Laser Power Converters

Dual-use photovoltaic cells can receive solar and laser power simultaneously to generate current, an application relevant to space and terrestrial industries. This study investigates two concepts of solar cells optimized for dual-use 1070 nm laser and solar power conversion, a single-junction and triple-junction cell. The cell designs are based upon the 3- junction inverted metamorphic solar cell, previously shown highly efficient for solar conversion. Because it is closely bandgap-tuned for a 1070 nm laser, the 1 eV bottom junction is incorporated into each of the two designs, making its development key to the success of both concepts. However, each design requires some modification for efficient dual use. The single-junction device requires optimization to reduce short wavelength absorption of the broad solar spectrum. In both devices, the graded buffer layers in the GaInAs cell affect the cell's performance by reducing threading dislocations in the active junction. However, the buffer in the three-junction device also acts as a lateral transport layer and so affects the fill factor depending on its sheet resistance. By varying the buffer thickness, we demonstrate a direct relationship between buffer thickness and sheet resistance reduction, while considering implications to open-circuit voltages. We also performed resistance modeling to determine the optimal grid spacing and thickness of the grid fingers to minimize losses due to sheet resistance and grid shading. Efficiency data for a one junction GaInAs cell demonstrates a laser conversion efficiency of 38% at 1070 nm wavelength without an anti-reflection coating.

dual-use↗
DOE OSTI2025

Computational Algorithms for Unit Commitment with AC Power Flows (Final Report)

Security-constrained unit commitment (SCUC) is a key component in power system operations. When AC power flow constraints are considered in the SCUC model (AC-SCUC), the problem becomes extremely difficult due to its discrete and non-convex nature, as described in “Grid Optimization Competition Challenge 3 Problem Formulation (GOCC)”. There are four main challenges: (i) Discrete decisions regarding unit online/offline status and start-up/shut-down procedures for every single unit. The number of discrete decision variables increases considerably when a system integrates multiple generators; (ii) Configuration-based combined-cycle formulations, and multi-commodity models that include ramping products, spin/non-spin products, and regulation up/down products. The combined-cycle units introduce additional discrete decision variables and auxiliary service products further complicate the model by connecting multi-commodity products’ continuous and discrete variables; (iii) SCUC models with AC power flow constraints are far more complex due to massive bilinear terms in the large-scale nonlinear power balance equations. The nonlinear power balance equations are further complicated by the discrete step control variables of shunts; (iv) N − 1 contingency analysis. The size of the model increases linearly with the number of contingencies considered, greatly increasing the size of the optimization model. Accordingly, there is an emergent need to develop a robust algorithm capable of deriving a high-quality solution in a short time and passing through contingency tests simultaneously. In this project, we explore innovative techniques to address this challenging problem by integrating advanced polyhedral theory, approximation methods, relaxation strategies, decomposition techniques, and parallel computing. Each technique approaches the problem from a different perspective, leveraging its specific strengths to tackle distinct challenges. Each individual method has demonstrated its effectiveness in the PI’s previous research. Their integration is expected to significantly reduce the computational time required to solve the proposed complex problem. Successful completion of this project has the potential to transform the industry by enhancing optimization solvers capable of handling large-scale day-ahead energy market clearing models within strict time constraints, while incorporating AC power flow constraints. This advancement will lead to reduced overall generation costs and, consequently, increased social welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Addressing Rising Energy Demand Through Innovation

The U.S. is facing a significant increase in energy demand, driven by AI advancements, the rapid expansion of data centers, manufacturing and industrial growth, and the electrification of transportation and buildings. Buildings alone account for approximately 75% of U.S. electricity consumption and 40% of total energy use. To address these challenges, NLR leverages its state-of-the-art research facilities, advanced energy modeling, hardware-in-the-loop emulation, and real-world demonstrations to provide data-driven insights that de-risk emerging energy solutions, increase efficiency and demand flexibility, optimize grid controls, and identify vulnerabilities to enhance energy security. This presentation will highlight our research ecosystem and its role in supporting a more reliable, affordable, and adaptive energy infrastructure in the face of accelerating demand.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Learning from Arctic Microgrids: Cost and Resiliency Projections for Renewable Energy Expansion with Hydrogen and Battery Storage

Electricity in rural Alaska is provided by more than 200 standalone microgrid systems powered predominantly by diesel generators. Incorporating renewable energy generation and storage to these systems can reduce their reliance on costly imported fuel and improve sustainability; however, uncertainty remains about optimal grid architectures to minimize cost, including how and when to incorporate long-duration energy storage. This study implements a novel, multi-pronged approach to assess the techno-economic feasibility of future energy pathways in the community of Kotzebue, which has already successfully deployed solar photovoltaics, wind turbines, and battery storage systems. Using real community load, resource, and generation data, we develop a series of comparison models using the HOMER Pro software tool to evaluate microgrid architectures to meet over 90% of the annual community electricity demand with renewable generation, considering both battery and hydrogen energy storage. We find that near-term planned capacity expansions in the community could enable over 50% renewable generation and reduce the total cost of energy. Additional build-outs to reach 75% renewable generation are shown to be competitive with current costs, but further capacity expansion is not currently economical. We additionally include a cost sensitivity analysis and a storage capacity sizing assessment that suggest hydrogen storage may be economically viable if battery costs increase, but large-scale seasonal storage via hydrogen is currently unlikely to be cost-effective nor practical for the region considered. While these findings are based on data and community priorities in Kotzebue, we expect this approach to be relevant to many communities in the Arctic and Sub-Arctic regions working to improve energy reliability, sustainability, and security.

25 ENERGY STORAGE↗
NASA NTRS1985

Computational methods for hypersonic viscous flow over finite ellipsoid-cones at incidence

A numerical method, which is simpler than others currently in use, is proposed for determining the full viscous flow over a finite body in hypersonic stream at high altitude. It treats the shock layer surrounding the blunt foebody and the near wake behind the base simultaneously by formulating the Navier-Stokes equations in conformal and azimuthal-angle coordinates. The computational domain is confined to the body wall, outflow surface and the bow shock, which is adjusted along the coordinate normal to the wall in the course of iterations. Because of the optimal grid and a well developed alternating direction implicit factorization technique for the governing equations, reasonably accurate results can be obtained on a 30 by 36 by 6 grid with 400 time-marching iterations. Results for body shapes belonging to the ellipsoid-cone family are compared with the experimental data for the Apollo command module and the Viking aeroshell. Validation of the method based on self-consistency is also discussed.

Li, C. P.↗
NASA NTRS1985

Numerical procedure for three-dimensional hypersonic viscous flow over aerobrake configuration

A numerical method, which is simpler and more efficient than others currently in use, is proposed for the computation of the full viscous flow over an aerobrake body in hypersonic stream at high altitude. It treats the shock layer surrounding the blunt forebody and the near wake behind the base simultaneously by formulating the Navier-Stokes equations in conformal and azimuthal-angle coordinates. The computational domain is confined by the body wall, outflow surface and the shock, which is adjusted along the coordinate normal to the wall in the course of iterations. Because of the optimal grid and a well developed alternating direction implicit factorization technique for the governing equations, reasonably accurate results can be obtained with a 28 x 36 x 7 grid and 400 time-marching iterations. Excellent agreement of shock location is found between the present result and the schlieren photograph. Details of the base flow and shear layer impingement on the cylindrical aft body are presented for an adiabatic wall case.

Li, C. P.↗
NASA NTRS1988

28 percent efficient GaAs concentrator solar cells

AlGaAs/GaAs heteroface solar concentrator cells which exhibit efficiencies in excess of 27 percent at high solar concentrations (over 400 suns, AM1.5D, 100 mW/sq cm) have been fabricated with both n/p and p/n configurations. The best n/p cell achieved an efficiency of 28.1 percent around 400 suns, and the best p/n cell achieved an efficiency of 27.5 percent around 1000 suns. The high performance of these GaAs concentrator cells compared to earlier high-efficiency cells was due to improved control of the metal-organic chemical vapor deposition growth conditions and improved cell fabrication procedures (gridline definition and edge passivation). The design parameters of the solar cell structures and optimized grid pattern were determined with a realistic computer modeling program. An evaluation of the device characteristics and a discussion of future GaAs concentrator cell development are presented.

Macmillan, H. F.↗
NASA NTRSDate not supplied

OVERFLOW Analysis of Supersonic Retropropulsion Testing on a Blunt Mars Entry Vehicle Concept

Supersonic Retropropulsion (SRP) flow over a Hypersonic Inflatable Aerodynamic Decelerator (HIAD) blunt-body vehicle was simulated using the OVERFLOW Computational Fluid Dynamics (CFD) solver. Two nozzle configurations were tested (1E and 1F) as a subset of the seven total configurations in the Descent Systems Study (DSS) testing campaign. A generalized, Adaptive Mesh Refinement (AMR) shock capturing and plume refinement technique was developed and calibrated for producing automatic and optimized grid systems unique to any given testing condition. Simulations were subjected to successive levels of grid refinement in order to determine solution independence from grid resolution. OVERFLOW Reynolds Averaged Navier-Stokes (RANS) solutions produced realistic SRP flow phenomena, including Mach disk normal shocks contained in high-thrust plumes and bow shock triple-points. Solutions for the 1E nozzle configuration were steady. Conversely, a subset of the 1F test conditions were unsteady and exhibited periodic, non-sinsoidal expansions and contractions of the streamwise-oriented plume, resulting in unsteady aerodynamic loads on the vehicle.

Supersonic Retropropulsion↗
DOE OSTI2024

1.1 eV GaInAs Cell Development for Dual-Use Solar and 1075 nm Laser Power Converters

Dual-use power converter cells can receive solar and laser power simultaneously to generate current, an application relevant to space and terrestrial industries. This study investigates two concepts of solar cells optimized for dual- use 1070 nm laser and solar power conversion, a single-junction and triple-junction cell. Because it is bandgap-tuned for a 1070 nm laser, the 1.1 eV junction is incorporated into each of the two designs, making its development key to the success of both concepts. Efficiency data for a one junction GaInAs cell demonstrates a laser conversion efficiency of 38% at 1070nm wavelength without an anti-reflection coating. However, the single-junction device requires optimization to reduce short wavelength absorption of the broad solar spectrum. In both devices, the graded buffer layers in the GaInAs cell affects the cell's performance by reducing threading dislocations in the active junction. However, the buffer in the three-junction device also acts as a lateral transport layer and so affects the fill factor depending on its sheet resistance. By varying the buffer thickness, we demonstrate a direct relationship between buffer thickness and sheet resistance reduction, while considering implications to open-circuit voltages. We also performed resistance modeling to determine the optimal grid spacing and thickness of the grid fingers to minimize losses due to sheet resistance and grid shading.

dual-use↗
DOE OSTI2025

Short-Term Electric Load Forecasting for a Residential Household in Alaska

Accurate short-term load forecasting at a fine scale is essential for demand response programs, peak shaving, and load-shedding strategies [1]. While traditionally, only aggregate short-term consumption data was available, advanced metering infrastructure (AMI) now provides data at the individual consumer level [1]. There is increasing interest in utilizing this data for short-term load forecasting (from an hour to a few days) to optimize grid operations. Electricity consumption in individual households is highly influenced by residents’ personal behaviors [2]. As a result, unlike aggregate loads, electrical power usage in single households often shows significant volatility, making meter-level load forecasting for individual users particularly challenging [3], [4]. Deep learning methods, with their strong ability to model nonlinear data, have become popular for improving the accuracy of household electricity consumption forecasting [4]. Notably, the Long ShortTerm Memory (LSTM) has attracted significant attention [5], [6].

42 ENGINEERING↗
DOE OSTI2026

Convex Optimization with Smart Grid Examples

In this talk, we give an overview of the field of convex optimization and work through four canonical problems that relate to electrical power systems and smart grids. The purpose of these examples is to demonstrate the breadth of applications of convex optimization in energy research and to show that toy versions of these problems can be solved in just a few lines of code, indicating the scale and complexity of problems that can be tackled with a more detailed treatment. We emphasize the cvxpy modeling language as a foundational technology that enables rapid development and prototyping of convex optimization problems, allowing researchers to focus on model development rather than get caught in the weeds of numerical and code implementation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Selecting Critical Scenarios of DER Adoption in Distribution Grids Using Bayesian Optimization

We develop a new methodology to select scenarios of DER adoption most critical for distribution grids. Anticipating risks of future voltage and line flow violations due to additional PV adopters is central for utility investment planning but continues to rely on deterministic or ad hoc scenario selection. We propose a highly efficient search framework based on multi-objective Bayesian Optimization. We treat underlying grid stress metrics as computationally expensive black-box functions, approximated via Gaussian Process surrogates and design an acquisition function based on probability of scenarios being Pareto-critical across a collection of line- and bus-based violation objectives. Our approach provides a statistical guarantee and offers an order of magnitude speed-up relative to a conservative exhaustive search. Case studies on realistic feeders with 200-400 buses demonstrate the effectiveness and accuracy of our approach.

Mulkin, Olivier↗
NASA NTRS1984

Shape optimization including finite element grid adaptation

The prediction of optimal shape design for structures depends on having a sufficient level of precision in the computation of structural response. These requirements become critical in situations where the region to be designed includes stress concentrations or unilateral contact surfaces, for example. In the approach to shape optimization discussed here, a means to obtain grid adaptation is incorporated into the finite element procedures. This facility makes it possible to maintain a level of quality in the computational estimate of response that is surely adequate for the shape design problem.

Kikuchi, N.↗
NASA NTRS1998

Geometry Modeling and Grid Generation for Design and Optimization

Geometry modeling and grid generation (GMGG) have played and will continue to play an important role in computational aerosciences. During the past two decades, tremendous progress has occurred in GMGG; however, GMGG is still the biggest bottleneck to routine applications for complicated Computational Fluid Dynamics (CFD) and Computational Structures Mechanics (CSM) models for analysis, design, and optimization. We are still far from incorporating GMGG tools in a design and optimization environment for complicated configurations. It is still a challenging task to parameterize an existing model in today's Computer-Aided Design (CAD) systems, and the models created are not always good enough for automatic grid generation tools. Designers may believe their models are complete and accurate, but unseen imperfections (e.g., gaps, unwanted wiggles, free edges, slivers, and transition cracks) often cause problems in gridding for CSM and CFD. Despite many advances in grid generation, the process is still the most labor-intensive and time-consuming part of the computational aerosciences for analysis, design, and optimization. In an ideal design environment, a design engineer would use a parametric model to evaluate alternative designs effortlessly and optimize an existing design for a new set of design objectives and constraints. For this ideal environment to be realized, the GMGG tools must have the following characteristics: (1) be automated, (2) provide consistent geometry across all disciplines, (3) be parametric, and (4) provide sensitivity derivatives. This paper will review the status of GMGG for analysis, design, and optimization processes, and it will focus on some emerging ideas that will advance the GMGG toward the ideal design environment.

Samareh, Jamshid A.↗
NASA NTRS2006

Adjoint-Based Algorithms for Adaptation and Design Optimizations on Unstructured Grids

Schemes based on discrete adjoint algorithms present several exciting opportunities for significantly advancing the current state of the art in computational fluid dynamics. Such methods provide an extremely efficient means for obtaining discretely consistent sensitivity information for hundreds of design variables, opening the door to rigorous, automated design optimization of complex aerospace configuration using the Navier-Stokes equation. Moreover, the discrete adjoint formulation provides a mathematically rigorous foundation for mesh adaptation and systematic reduction of spatial discretization error. Error estimates are also an inherent by-product of an adjoint-based approach, valuable information that is virtually non-existent in today's large-scale CFD simulations. An overview of the adjoint-based algorithm work at NASA Langley Research Center is presented, with examples demonstrating the potential impact on complex computational problems related to design optimization as well as mesh adaptation.

Nielsen, Eric J.↗
NASA NTRS1993

Three-dimensional unstructured grid refinement and optimization using edge-swapping

This paper presents a three-dimensional (3-D) 'edge-swapping method based on local transformations. This method extends Lawson's edge-swapping algorithm into 3-D. The 3-D edge-swapping algorithm is employed for the purpose of refining and optimizing unstructured meshes according to arbitrary mesh-quality measures. Several criteria including Delaunay triangulations are examined. Extensions from two to three dimensions of several known properties of Delaunay triangulations are also discussed.

Gandhi, Amar↗
NASA NTRS1999

Structure Damage Simulations Accounting for Inertial Effects and Impact and Optimization of Grid-Stiffened Non-Circular Shells

The goal of this research project is to develop modelling and analysis strategy for the penetration of aluminium plates impacted by titanium impactors. Finite element analysis is used to study the penetration of aluminium plates impacted by titanium impactors in order to study the effect of such uncontained engine debris impacts on aircraft-like skin panels. LS-DYNA3D) is used in the simulations to model the impactor, test fixture frame and target barrier plate. The effects of mesh refinement, contact modeling, and impactor initial velocity and orientation were studied. The research project also includes development of a design tool for optimum design of grid-stiffened non-circular shells or panels subjected to buckling.

Mei, Chuh↗