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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

GR-Athena++: General-relativistic Magnetohydrodynamics Simulations of Neutron Star Spacetimes

We present the extension of GR-Athena++ to general-relativistic magnetohydrodynamics (GRMHD) for applications to neutron star spacetimes. The new solver couples the constrained transport implementation of Athena++ to the Z4c formulation of the Einstein equations to simulate dynamical spacetimes with GRMHD using oct-tree adaptive mesh refinement. We consider benchmark problems for isolated and binary neutron star spacetimes demonstrating stable and convergent results at relatively low resolutions and without grid symmetries imposed. The code correctly captures magnetic field instabilities in nonrotating stars with total relative violation of the divergence-free constraint of 10 –16 . It handles evolutions with a microphysical equation of state and black hole formation in the gravitational collapse of a rapidly rotating star. For binaries, we demonstrate correctness of the evolution under the gravitational radiation reaction and show convergence of gravitational waveforms. We showcase the use of adaptive mesh refinement to resolve the Kelvin–Helmholtz instability at the collisional interface in a merger of magnetised binary neutron stars. GR-Athena++ shows strong scaling efficiencies above 80% in excess of 10 5 CPU cores and excellent weak scaling is shown up to ~5 × 10 5 CPU cores in a realistic production setup. GR-Athena++ allows for the robust simulation of GRMHD flows in strong and dynamical gravity with exa-scale computers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Multiscale design of nonlinear materials using a Eulerian shape optimization scheme

Motivated by recent advances in manufacturing, the design of materials is the focal point of interest in the material research community. One of the critical challenges in this field is finding optimal material microstructure for a desired macroscopic response. This work presents a computational method for the mesoscale-level design of particulate composites for an optimal macroscale-level response. The method relies on a custom shape optimization scheme to find the extrema of a nonlinear cost function subject to a set of constraints. Three key “modules” constitute the method: multiscale modeling, sensitivity analysis, and optimization. Multiscale modeling relies on a classical homogenization method and a nonlinear NURBS-based generalized finite element scheme to efficiently and accurately compute the structural response of particulate composites using a nonconformal discretization. A three-parameter isotropic damage law is used to model microstructure-level failure. An analytical sensitivity method is developed to compute the derivatives of the cost/constraint functions with respect to the design variables that control the microstructure's geometry. The derivation uncovers subtle but essential new terms contributing to the sensitivity of finite element shape functions and their spatial derivatives. Several structural problems are solved to demonstrate the applicability, performance, and accuracy of the method for the design of particulate composites with a desired macroscopic nonlinear stress-strain response.

42 ENGINEERING↗
DOE OSTI2025

On-chip pulse shaping of entangled photons

The miniaturization of optical systems via integrated photonics is critical to the ultimate scalability and performance of photonic quantum processors, yet many longstanding optical signal processing capabilities—such as Fourier-transform pulse shaping—remain unrealized on chip. In this work, we demonstrate on-chip spectral shaping of entangled photons using a multichannel microring-resonator-based silicon photonic pulse shaper. Achieving line-by-line phase control on a 3 GHz grid for two frequency-bin-entangled qudits, the pulse shaper's fine spectral resolution enables control of nanosecond-scale temporal features, which are observed by direct coincidence detection of biphoton correlation functions that show excellent agreement with theory. This work marks a demonstration of biphoton pulse shaping using an integrated spectral shaper and holds significant promise for applications in photonic quantum information processing.

Entanglement manipulation↗
DOE OSTI2023

Micropatterning of alumina tubular membranes via laser carving for enhanced direct air capture

An approach for preparing and applying micropatterned alumina tubular membranes was developed for improved gas-liquid contact at low air pressure drop in direct air capture application. The paper demonstrated that the laser carving of micropatterns on the outer surface of the alumina tubular membranes could greatly increase their outer surface area and enhance gas-liquid turbulence for a reduced diffusion mass transfer resistance. Six kinds of micropattern configurations were fabricated and studied, including random and regular micropatterns. By introducing a 500-μm solid grid micropattern, the outer surface area doubles and enhances carbon dioxide capture efficiency from 61% to 97% after the membrane was hydrophobically modified with fluoroalkylsilane. Here, the air pressure drop through the tube lumen remained low even when the packing density increased from 382 to 906 m 2 /m 3 . The liquid entry pressure of this micropatterned membrane was the same after testing for 220 h running with the help of periodic drying.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Towards exascale for wind energy simulations

We examine large-eddy-simulation modeling approaches and computational performance of two open-source computational fluid dynamics codes for the simulation of atmospheric boundary layer flows that are of direct relevance to wind energy production. The first code, NekRS, is a high-order, unstructured-grid, spectral element code. The second code, AMR-Wind, is a second-order, block-structured, finite-volume code with adaptive mesh refinement capabilities. The objective of this study is to co-develop these codes in order to improve model fidelity and performance for each. These features will be critical for running ABL-based applications such as wind farm analysis on advanced computing architectures. To this end, we investigate the performance of NekRS and AMR-Wind on the Oak Ridge Leadership Facility supercomputers Summit, using 4 to 800 nodes (24 to 4,800 NVIDIA V100 GPUs), and Crusher, the testbed for the Frontier exascale system, using 18 to 384 Graphics Compute Dies on AMD MI250X GPUs. We compare strong- and weak-scaling capabilities, linear solver performance, and time to solution. We also identify leading inhibitors to parallel scaling.

17 WIND ENERGY↗
DOE OSTI2024

CW copper injector for SRF industrial cryomodules

Compact SRF industrial linacs can provide unique parameters of the beam (>1 MW and >1-10 MeV) hardly achievable by normal conducting linacs within limited space. SRF technology was prohibitively expensive until the development of conduction cooling which opened the way for compact stand alone SRF systems suitable for industrial and research applications. Limited cooling capacity puts strict requirements on the beam parameters with zero losses of the beam on the SRF cavity walls. This implies strict requirements on the beam energy to be accepted by the cryomodule and most importantly the beam bunching with zero particles in between. We designed a CW normal conducting RF injector which consists of a gridded RF gun integrated with a first cell of a copper booster cavity to satisfy these requirements. Here we present a complete design of a booster cavity including beam dynamics, RF, thermomechanical and engineering design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Open Building Operating System: An Open-Source Grid Responsive Control Platform for Buildings

Grid-interactive efficient buildings (GEBs) with flexible loads are a promising method to decarbonize buildings, shift loads during peak hours, and lower energy use and electricity costs. Despite the promising benefits of GEBs, automation systems that manage flexible loads in response to energy prices or other grid signals are still uncommon in small and medium commercial buildings. Recent literature demonstrates such control solutions, but they often rely on custom integrations lacking the tools and drivers needed for scalability. To address these gaps, our team has created a fully open-source software stack capable of integrating heterogeneous flexible building loads and implementing integrated portable control applications called the Open Building Operating System (OpenBOS). The software can be deployed over existing control architecture with a small capital cost. OpenBOS leverages semantic models, which have been the subject of recent investigations to facilitate application portability. The use of semantic data reduces the labor and expense required to deploy and update smart control applications, increasing scalability. In this paper, the semantic modeling schema "Brick" was used, but the proposed approach can also be applied to ASHRAE standard 223P, when released. This paper describes the methodology and software components of OpenBOS and demonstrates its functionality with a rule-based demand flexibility control application configured using a semantic model. This application was tested at a real building in NY that uses a dual-fuel heating system made up of five ductless heat pump mini-splits and a central furnace serving a single zone. The demonstration reduced electricity costs at the site by 27%, demand during a shed event by 49%, and furnace usage by 35%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Abstract for CRADA among NETL, Ohio University, and MetalKraft Technologies, LLC

The electrical grid faces challenges for meeting accelerated electricity demand arising from the electrification of building and transportation sectors. According to the DOE Grid Development Office, 70% of transmission lines are approaching the end of their lifecycle. The aging grid and insufficient transmission capacity necessitate the development of new technologies to improve overall grid performance. The conventional conductors used for electrical transmission lines suffer from substantial energy losses, high costs and low durability. These inefficiencies result in higher operational costs, increased energy waste, and difficulties in managing power flow. Improving the grid will require metals and composites with higher electrical conductivity and strength than the materials currently used. This CRADA will develop technologies to improve the grid by fabricating carbon metal composites with improved electrical, structural, and mechanical properties in comparison to metals that do not contain carbon additives. The composites will be made by incorporating carbon materials (graphite, graphene) into aluminum, copper, and other metals. The work will focus primarily on improving material properties that enhance the performance of these materials in electrical conductor applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

An arbitrarily high-order three-dimensional Cartesian-grid method for reconstructing interfaces from volume fraction fields

Here Tthis work describes a newly developed, arbitrarily high-order Cartesian-grid method for reconstructing material interfaces from a volume fraction field. The method begins by identifying all of the grid cells in the volume fraction field that are intersected by the interface and need to be approximated by the reconstruction scheme. Finite-differences are used to calculate the gradient of the volume fraction field and provide an estimate of the surface normal in all of the interfacial grid cells. Groups of connected grid cells are then identified which all have the same dominant component of the normal vector. This grouping by orientation determines the proper dependent variable to use in the surface reconstruction (e.g. for a 2D curve, this step determines if the surface will be approximated by a function of x or y). A cumulative integral over the surface is constructed and fit using b-splines for two-dimensional problems or tensor-product b-splines for three-dimensional problems. This construction allows for the interface to be recovered through application of the second fundamental theorem of calculus. Fitting the cumulative integral with $\mathscr{N}$ th-order b-splines (or tensor-product b-splines) yields an ($\mathscr{N}$-1) th-order convergence rate of the interface shape. Differentiation of the b-spline interface function(s) allows for the high-order approximation of the normal vector and curvature to be obtained directly anywhere along b-spline. Together, the proposed reconstruction technique can achieve arbitrarily high mesh convergence rates. Validation tests are presented with mesh convergence rates ranging from fourth- to tenth-order.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

OR-AGENT framework – Architecting electrified heavy-duty drayage applications

The widespread adoption of zero-emission vehicles in heavy-duty (HD) commercial freight transportation faces considerable technoeconomic challenges. For heavy-duty trucks, ensuring high uptime, cost parity with diesel, and safety standards is especially critical as these vehicles operate over long distances with heavy loads, where any downtime or off-nominal behaviors significantly impacts logistics, productivity, and the total cost of ownership. Unlike traditional diesel refueling, BEV charging infrastructure must be co-optimized with vehicle deployment, operational demands, and grid capacity to ensure cost-effective and reliable freight operations. However, the lack of a standardized ownership and service model has led to a fragmented approach—where commercial vehicle operators may invest in, own, and maintain both vehicle/batteries and charging/energy infrastructure. This disconnect may exclude energy service providers from the equation, forcing fleet operators to explore ‘behind-the-fence’ energy solutions that increase capital investment, operational downtime, overhead costs, and, in some cases, net carbon emissions. To address these issues, this study introduces OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport), a comprehensive modeling framework that integrates powertrain architectures, charging infrastructures, and energy backbone systems into a cohesive strategy. In this paper, OR-AGENT is applied to develop an interconnected systems architecture for energy efficiency and resiliency enhancement of heavy-duty drayage vehicles at the Port of Savannah, GA. This framework showcases an interconnected systems approach to electrifying heavy-duty drayage vehicles at the Port of Savannah, GA. The study assessed BEVs with 400–1200 kWh battery capacities, accounting for seasonal variations in weather and freight routing. A diverse charging mix (150 kW–1250 kW) was evaluated alongside grid capacity constraints, cost, and carbon intensity analysis, leading to the development of a strategic microgrid/Distributed Energy Resources (DER) deployment architecture to ensure a reliable and sustainable transition. However, the findings also highlight the need for alternative zero-emission solutions for remaining trips, such as larger batteries, electrified roadways, hydrogen powertrains, or net-zero emission fuels. In conclusion, the findings are incorporated into a Total Cost of Ownership (TCO) model to identify optimal architectures for an interconnected electrified ecosystem.

Commercial vehicles↗
DOE OSTI2021

GIS Resource Compilation Map Package - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups include: new/revised datasets (paleo-geothermal features, geochemistry, geophysics, heat flow, slip and dilation, potential structures, geothermal power plants, positive and negative test sites), machine learning model input grids, machine learning models (Artificial Neural Network (ANN), Extreme Learning Machine (ELM), Bayesian Neural Network (BNN), Principal Component Analysis (PCA/PCAk), Non-negative Matrix Factorization (NMF/NMFk) - supervised and unsupervised), original NV Play Fairway data and models, and NV cultural/reference data. See layer descriptions for additional metadata. Smaller GIS resource packages (by category) can be found in the related datasets section of this submission. A submission linking the full codebase for generating machine learning output models is available through the "Related Datasets" link on this page, and contains results beyond the top picks present in this compilation.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Performance of 8 × 8 × 32 and 10 × 10 × 32 mm 3 CdZnTe position-sensitive virtual Frisch-grid detectors for high-energy gamma ray cameras

CdZnTe (CZT) crystals with thicknesses up to 20 mm and diameters up to 75 mm have become available from Redlen Technologies, Inc. for making large-volume gamma-ray detectors. The modified growth and optimized annealing conditions allowed Redlen to minimize the dark current and improve the uniformity of CZT crystals. Two detector designs, pixelated (H3D) and position-sensitive virtual Frisch-grid (VFG), have greatly benefitted from the availability of such big crystals. Encouraging results from testing of 40×40×15 mm 3 pixelated detectors were recently reported by the University of Michigan. In this work, we evaluated the spectroscopic properties of 8×8×32 and 10×10×32 mm 3 crystals configured as position-sensitive VFG detectors. Both digitized waveforms and an analog ASIC were used to read and process the signals from the detectors and test their spectral- and spatial-resolution. The VFG design provides the flexibility to scale-up the dimensions of the detectors for the desired efficiency, while the position information allows for correcting the detectors' response non-uniformity caused by crystal defects and devices geometry, thereby reducing the instrument cost and making them more feasible for emerging applications in gamma-ray astronomy, nonproliferation, portal screening and nuclear safeguards, where large detector arrays are often required.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Dynamic Transmission Line Switching Amid Wildfire-Prone Weather Under Decision-Dependent Uncertainty

During dry and windy seasons, environmental conditions significantly increase the risk of wildfires, exposing power grids to disruptions caused by transmission line failures. Wildfire propagation exacerbates grid vulnerability, potentially leading to prolonged power outages. To address this challenge, we propose a multistage optimization model that dynamically adjusts transmission grid topology in response to wildfire propagation, aiming to develop an optimal response policy. By accounting for decision-dependent uncertainty, where line survival probabilities depend on usage, we employ distributionally robust optimization to model uncertainty in line survival distributions. We adapt the stochastic nested decomposition algorithm and derive a deterministic upper bound for its finite convergence. To enhance computational efficiency, we exploit the Lagrangian dual problem structure for a faster generation of Lagrangian cuts. Using realistic data from the California transmission grid, we demonstrate the superior performance of dynamic response policies against two-stage alternatives through a comprehensive case study. In addition, after solving the multistage formulation, we construct easy-to-implement policies that significantly reduce computational burden while maintaining good performance in real-time deployment. History: Accepted by Russell Bent, Area Editor for Network Optimization: Algorithms and Applications. Funding: This work was supported by the U.S. Department of Energy, Office of Electricity [Grant DE-AC02-05CH11231]. The work of R. Jiang was supported in part by the U.S. National Science Foundation, Division of Electrical, Communications and Cyber Systems [Grant ECCS-1845980] and the U.S. Air Force Office of Scientific Research [Grant FA9550-23-1-0323]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2025.1210 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2025.1210 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Estrada-Garcia, Juan-Alberto↗
DOE OSTI2020

A Closed-Loop Distribution System Restoration Tool for Natural Disaster Recovery. Final CRADA report

We propose to continue the development of the restoration algorithms and the tool’s user interface, both of which have been developed under the GMLC-0131 project. This project aims to develop a distribution restoration decision support tool that will assist utilities in performing distribution restoration after extreme weather events in an optimal and efficient manner. The tool will integrate the weather information/forecasts and system fragility assessment together with the field measurement data to improve the situational awareness and estimate the system damage status. Advanced optimization models will be leveraged to dispatch repair crews and associated resources. New resources (e.g., automatic switches and distributed generators (DGs)) enabled by distribution automation and smart grid development will be utilized to reconfigure distribution grids and pick up loads promptly to reduce the outage sizes and durations. The closed-loop feature of the tool will make the tool adaptive to the evolving weather events and varying restoration capabilities. In this CRADA, we will collaborate with S&C Electric Company (S&C) to refine ANL-1060 (07/17/2019) the restoration algorithms that can be potentially applicable for any utility systems and vendor products, including: 1) Customizable information from both utility users and vendor users; 2) User interface design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Photovoltaic Cable Jackets: A Comparison of Representative Products Using Combined-Accelerated Stress Testing [Slides]

Photovoltaic (PV) cables facilitate the distribution of electricity collected from modules to the energy grid. Durable cabling enables continuous operation of PV installations, whereas cables with a lifetime less than the modules must be replaced - reducing electricity generation and adding to the operating expense. This study primarily focusses on the aging of the key cable types using the combined-accelerated stress testing (C-AST) protocol. Representative cables for utility, building, and control/auxiliary applications were examined. Cable jacket materials examined include: polyolefin, polyethylene, polyamide, poly(vinyl chloride), chlorinated polyethylene, thermoplastic elastomer, and ethylene propylene diene monomer rubber. Specimen characterizations applied include: optical microscopy, mechanical profilometry, instrumented indentation, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). A variety of performance and durability characteristics were observed, depending on the base material, polymer formulation, and jacket color. The results from C-AST are analyzed and discussed relative to a recent industry survey on electronic balance of system components in addition to a recent study where similar cables were aged using steady state ultraviolet weathering (International Electrotechnical Commission Technical Specification 62788-7-2). Recommendations are made for the screening, industry qualification, and service life prediction of PV cable jackets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

IS BLOCKCHAIN A SUITABLE TECHNOLOGY FOR ENSURING THE INTEGRITY OF DATA SHARED BY LIGHTING AND OTHER BUILDING SYSTEMS?

Increasing amounts of data are available from lighting and other building systems. In commercial buildings, these data can be used to improve system and energy performance, detect and diagnose faults, and facilitate maintenance. Building data are not only of interest to owners and operators of the building systems, however. Owners and operators of similar buildings, manufacturers of building systems, utilities, and city agencies also have interesting use cases. Energy data can, for example, be used to verify the performance of energy-conservation measures, issue renewableenergy certificates, and financially settle grid services. Increased data sharing, however, significantly expands the cyber-attack surface, creating new challenges. In this work, blockchain is explored as an option for ensuring the integrity of data that are shared by lighting and other building systems. Blockchain fundamentals and variants are briefly reviewed, and value propositions relevant to building systems are discussed. A recently developed blockchain applicability framework (BAF) that builds upon and addresses the limitations of previous applicability models is also briefly reviewed. The BAF is used to assess the suitability of blockchain over other technologies or approaches for building-data applications, using emerging connected lighting systems as an example use case.

blockchain, connected lighting system, data integr↗
DOE OSTI2021

Stochastic parametric skeletal dosimetry model for humans: General approach and application to active marrow exposure from bone-seeking beta-particle emitters

The objective of this study is to develop a skeleton model for assessing active marrow dose from bone-seeking beta-emitting radionuclides. This article explains the modeling methodology which accounts for individual variability of the macro- and microstructure of bone tissue. Bone sites with active hematopoiesis are assessed by dividing them into small segments described by simple geometric shapes. Spongiosa, which fills the segments, is modeled as an isotropic three-dimensional grid (framework) of rod-like trabeculae that “run through” the bone marrow. Randomized multiple framework deformations are simulated by changing the positions of the grid nodes and the thickness of the rods. Model grid parameters are selected in accordance with the parameters of spongiosa microstructures taken from the published papers. Stochastic modeling of radiation transport in heterogeneous media simulating the distribution of bone tissue and marrow in each of the segments is performed by Monte Carlo methods. Model output for the human femur at different ages is provided as an example. The uncertainty of dosimetric characteristics associated with individual variability of bone structure was evaluated. An advantage of this methodology for the calculation of doses absorbed in the marrow from bone-seeking radionuclides is that it does not require additional studies of autopsy material. The biokinetic model results will be used in the future to calculate individual doses to members of a cohort exposed to 89,90 Sr from liquid radioactive waste discharged to the Techa River by the Mayak Production Association in 1949–1956. Further study of these unique cohorts provides an opportunity to gain more in-depth knowledge about the effects of chronic radiation on the hematopoietic system. In addition, the proposed model can be used to assess the doses to active marrow under any other scenarios of 90 Sr and 89 Sr intake to humans.

59 BASIC BIOLOGICAL SCIENCES↗