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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Hydrodynamic Analysis and Optimization of Aquantis Marine Turbine: Cooperative Research and Development (Final Report)

The primary aim of this proposal is to improve the accurate prediction of hydrodynamic performance and dynamic load responses of the AQ10 floating axial-flow tidal turbine with a tri-cat mooring configuration. The validation of reduced-order modeling approaches with high-fidelity model will be implemented. Additionally, the frequency response domain, Response Amplitude Floating Wind (RAFT) toolbox plus an optimizer expanded for marine hydrokinetic turbines under the Submarine Hydrokinetic And Riverine Kilo-megawatt. Systems (SHARKS) program will be used for designing and exploring different key design parameters (platform dimension, mooring layout and its parameters) of next marine hydrokinetic (MHK) turbine generation.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer Based Hydrogen Production Facility

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at NREL's Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗
DOE OSTI2026

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer-Based Hydrogen Production Facility: Preprint

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at the National Renewable Energy Laboratory (NREL)'s Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗
DOE OSTI2019

Positron Emission Tomography in Water Resources and Subsurface Energy Resources Engineering Research

Recent studies have demonstrated that positron emission tomography (PET) is a valuable tool for in-situ characterization of fluid transport in porous and fractured geologic media at the laboratory scale. While PET imaging is routinely used for clinical cancer diagnosis and preclinical medical research—and therefore imaging facilities are available at most research institutes—widespread adoption for applications in water resources and subsurface energy resources engineering have been limited by real and perceived challenges of working with this technique. In this study we discuss and address these challenges, and provide detailed analysis highlighting how positron emission tomography can complement and improve laboratory characterization of different subsurface fluid transport problems. The physics of PET are reviewed to provide a fundamental understanding of the sources of noise, resolution limits, and safety considerations. We then layout the methodology required to perform laboratory experiments imaged with PET, including a new protocol for radioactivity dosing optimization for imaging in geologic materials. Signal-to-noise and sensitivity analysis comparisons between PET and clinical X-ray computed tomography are performed to highlight how PET data can complement more traditional characterization methods, particularly for solute transport problems. Lastly, prior work is critically reviewed and discussed to provide a better understanding of the strengths and weakness of PET and how to best utilize PET-derived data for future studies.

02 PETROLEUM↗
DOE OSTI2024

Dual-energy electron storage ring

A dual-energy electron storage ring is a novel concept initially proposed to cool hadron beams at high energies. The design consists of two closed rings operating at significantly different energies: the low-energy ring and the high-energy ring. These two rings are connected by an energy recovery linac (ERL) that provides the necessary energy difference. The ERL features superconducting radio-frequency (SRF) cavities that first accelerate the beam from the low energy E L to the high energy E H and then decelerate the beam from E H to E L in the next pass. The different SRF cavities in the ERL section can be adjusted based on the applications. In this paper, we present a possible layout of a dual-energy electron storage ring. The preliminary optics of the ring is designed to optimize chromaticity correction, dynamic aperture, momentum aperture, beam lifetime, radiation damping, and intrabeam scattering effects. The primary focus of this paper is on the stability conditions and beam dynamics studies associated with this storage ring. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Glprof: A Gprof inspired, Callgraph-oriented Per-Object Disseminating Memory Access Multi-Cache Profiler

Application analysis is facilitated through a number of program profiling tools. The tools vary in their complexity, ease of deployment, design, and profiling detail. Specifically, understand- ing, analyzing, and optimizing is of particular importance for scientific applications where minor changes in code paths and data-structure layout can have profound effects. Understanding how intricate data-structures are accessed and how a given memory system responds is a complex task. In this paper we describe a trace profiling tool, Glprof, specifically aimed to lessen the burden of the programmer to pin-point heavily involved data-structures during an application's run-time, and understand data-structure run-time usage. Moreover, we showcase the tool's modularity using additional cache simulation components. We elaborate on the tool's design, and features. Finally we demonstrate the application of our tool in the context of Spec bench- marks using the Glprof profiler and two concurrently running cache simulators, PPC440 and AMD Interlagos.

Janjusic, Tommy↗
DOE OSTI2021

Analysis and Optimization of a Multi-Layer Integrated Organic Substrate for High Current GaN HEMT-Based Power Module

In this paper, analysis and optimization of a multi-layer organic substrate for high current GaN HEMT based power module are discussed. The organic multi-layer substrates can provide high electrical performance in terms of low parasitic inductance in the power loop by providing vertical layout, and shielding for reduction of common-mode noise, a common problem in fast switching power converters. Furthermore, high performance cooling solutions, such as micro-channel heat sinks, can be directly bonded to the substrate for optimum thermal management. The structure of the proposed architecture, thermal analysis and optimization of layer thickness, thermo-mechanical stress analysis of the GaN HEMT and development of a high-performance heat sink are discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Liquid-Cooled Heat Sink Optimization for Thermal Imbalance Mitigation in Wide-Bandgap Power Modules

Power semiconductor die placement on substrates used in high-power modules is generally optimized to minimize electrical parasitic (e.g., stray inductance, common-mode capacitance), taking into account the minimum spacing between semiconductor dies for thermal decoupling. The layout assumes sufficient heat spreading and transfer from dies to the cooling structure. Insulated metal substrate-based power module designs may lead to asymmetrical thermal resistance across the dies, which may cause significant temperature differences among the devices. Such unintentional thermal asymmetries can lead to oversizing the cooling system design or underusing the semiconductor power processing capability. This article proposes a thermal imbalance mitigation method that uses evolutionary optimized liquid-cooled heat sinks to improve the thermal loading among devices.

42 ENGINEERING↗
DOE OSTI2017

Optimizing Performance of Combustion Chemistry Solvers on Intel's Many Integrated Core (MIC) Architectures

This work investigates novel algorithm designs and optimization techniques for restructuring chemistry integrators in zero and multidimensional combustion solvers, which can then be effectively used on the emerging generation of Intel's Many Integrated Core/Xeon Phi processors. These processors offer increased computing performance via large number of lightweight cores at relatively lower clock speeds compared to traditional processors (e.g. Intel Sandybridge/Ivybridge) used in current supercomputers. This style of processor can be productively used for chemistry integrators that form a costly part of computational combustion codes, in spite of their relatively lower clock speeds. Performance commensurate with traditional processors is achieved here through the combination of careful memory layout, exposing multiple levels of fine grain parallelism and through extensive use of vendor supported libraries (Cilk Plus and Math Kernel Libraries). Important optimization techniques for efficient memory usage and vectorization have been identified and quantified. These optimizations resulted in a factor of ~ 3 speed-up using Intel 2013 compiler and ~ 1.5 using Intel 2017 compiler for large chemical mechanisms compared to the unoptimized version on the Intel Xeon Phi. The strategies, especially with respect to memory usage and vectorization, should also be beneficial for general purpose computational fluid dynamics codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Central Receiver Optimization

Sandia National Laboratories (Sandia) and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) collaborated to optimize central receivers in the temperature range of 600-900°C suitable for advanced power cycles. It was recognized that significant cost reductions can be made in concentrating solar power (CSP) if efficiency was substantially improved. Advanced cycles such as supercritical CO 2 (sCO 2 ) power cycles offer the potential for high efficiency, but the solar collector and receiver geometry must be considered together to ensure the required inlet conditions for the turbine can be met in a cost-effective manner. This project investigated heliostat life cycle costs, heliostat field layout and associated receiver geometry to better understand the optical and thermodynamic relationship between these components in this temperature range of interest, allowing subsequent optimization. This work will assist the mission of Sandia, the Department of Energy (DOE), and CSIRO to develop sustainable, cost-competitive energy technologies for public use. The purpose of this work was to investigate factors affecting performance and costs of heliostats, including in-field heliostat testing. Alternative receiver designs designed to achieve high temperatures (900 °C and above) were also explored in conjunction with the heliostat field.

Ho, Clifford K.↗
DOE OSTI2026

Elastic-wave sensitivity-guided adaptive seismic survey design for cost-effective monitoring of geological carbon storage

Effective seismic monitoring is essential for verifying CO₂ containment, detecting potential leakage, and optimizing operational decisions in geologic carbon storage. Here, this study presents a time-adaptive, elastic-wave sensitivity-guided framework for designing cost-effective seismic monitoring layouts for tracking CO₂ plume migration. The method is based on elastic-wave sensitivity analysis, which quantifies how variations in subsurface properties impact seismic wavefields. Two complementary design strategies are developed: one based on selecting a fixed number of seismic sources (Method A), and the other based on selecting source–receiver pairs contributing to a fixed fraction of cumulative elastic-wave sensitivity energy (Method B). The optimization workflow to identify source–receiver configurations with the highest detection potential is demonstrated using a hypothetical GCS scenario at the Kimberlina site in California using simulations of elastic-wave sensitivity data at multiple post-injection timesteps. Results show that both strategies adapt to evolving plume geometries and wavefield sensitivities, with Method B offering broader spatial coverage and Method A ensuring simpler deployment. This framework enables site-specific, cost-effective, and risk-informed seismic survey designs, enhancing the ability to monitor CO₂ migration over time in evolving geological environments

58 GEOSCIENCES↗
DOE OSTI2023

AutoTG: Reinforcement Learning-Based Symbolic Optimization for AI-Assisted Power Converter Design

Power converters are pervasive in modern electronic component design. They can be found in all electronic devices from household appliances and cellphone chargers to vehicles. Currently, designing new circuit topologies is hard because it requires human expertise based on experience and is difficult to automate. However, artificial-intelligence-assisted design can significantly facilitate the development of new power converters and/or improve the final result. Intelligently designed highly efficient power converters can have a significant effect on many important attributes, such as power efficiency, layout size, cost, heat dissemination, energy requirements, etc. We propose Autonomous Topology Generator (AutoTG), a reinforcement-learning-based framework that generates power converter topology candidates based on user specifications, optimized for user preferences. By modeling power converter design as a symbolic optimization problem, we sequentially sample components in an autoregressive manner until new topologies are formed, providing both the topology specification and the sizing (magnitude of each component parameter) of the proposed power converter. Here, we provide an empirical evaluation and show that AutoTG is able to generate varied high-efficiency topologies within component restrictions based on user input and show that previously unknown topologies can be found for further evaluation.

(AI)-based design↗
DOE OSTI2024

Surf-Deformer: Mitigating Dynamic Defects on Surface Code via Adaptive Deformation

In this paper, we introduce Surf-Deformer, a code deformation framework that seamlessly integrates adaptive defect mitigation functionality into the current surface code workflow. It crafts several basic deformation instructions based on fundamental gauge transformations, which can be combined to explore a larger design space than previous methods. This enables more optimized deformation processes tailored to specific defect situations, restoring the QEC capability of deformed codes more efficiently with minimal qubit resources. Additionally, we design an adaptive code layout that accommodates our defect mitigation strategy while ensuring efficient execution of logical operations. Our evaluation shows that Surf-Deformer outperforms previous methods by significantly reducing the end-to-end failure rate of various quantum programs by 35× to 70×, while requiring only about 50% of the qubit resources compared to the previous method to achieve the same level of failure rate. Ablation studies show that Surf-Deformer surpasses previous defect removal methods in preserving QEC capability and facilitates surface code communication by achieving nearly optimal throughput.

Yin, Keyi↗
DOE OSTI2024

Optimization Methodology of Polar Direct-Drive Illumination for the National Ignition Facility

Improved laser illumination uniformity drives shocks and implosions to create more extreme high energy density environments. Predominantly, the geometry of experiments that can be performed is dictated by the layout of beams at laser facilities, limiting inter-facility and multiscale investigations. This Letter presents the first automated, algorithmic approach for generating illumination configurations for high energy density experiments. The method is demonstrated in comparison to a polar direct drive solid target experiment at the National Ignition Facility. The new illumination configuration is simulated to create greater than ×3 higher peak pressure and almost ×2 higher density by maintaining better shock uniformity. Furthermore, the optimization process is performed with reduced computational expense and isotropic plasma profiles, while accounting for the impact of cross-beam energy transfer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Mapping Arbitrarily Sparse Two-body Interactions on One-dimensional Quantum Circuits

We consider an assignment problem arising in Fermionic-swap based mapping of the one-body and two-body interaction terms in simulating time evolution of a sparse second-quantized electronic structure Hamiltonian on a quantum computer. Relative efficiency of different swap networks depends on the relative costs of performing a swap layer and computing a Hamiltonian interaction term. Under the assumption that the interaction term cost dominates the computation, we develop an iterative algorithm that uses hypergraph optimal linear arrangement (HOLA) and partial distance-2 coloring to exploit arbitrary sparsity in the Hamiltonian for efficient computation using swap networks. Using a set of 122 problems from computational chemistry, we demonstrate performance improvements up to 100% relative to the state-of-the-art approaches for one-body terms and up to 86% utilization for two-body terms relative to a theoretical peak utilization. To the best of our knowledge, this is the first study to exploit arbitrary sparsity in orbital interactions for efficient computation on one-dimensional qubit connectivity layouts. The proposed algorithms form the basis for extension to map general k-body interactions that arise in other domains onto generalized qubit connectivity layouts.

quantum computing, Combinatorial Optimization, hyp↗
DOE OSTI2023

Magnetic design of the commutational magnet and quadrupoles for PERLE accelerator

ER@CEBAF is an effort to demonstrate multi-GeV multipass energy recovery with a low beam current in CEBAF. The CEBAF race-track-shaped geometry allows its linacs to accommodate multiple energy beams simultaneously. However, five energy recovery passes complicate the beamline optics design process. Individual recirculating arcs each transport one beam energy, and are shared between accelerating/decelerating beams. This paper presents a CEBAF optics redesign to accommodate the ER@CEBAF multi-pass ER scheme. Isochronous arcs were retuned to match into optics solutions for optimized 10-pass linacs. In this paper, we discuss the optics re-design process for ER@CEBAF based on the existing CEBAF layout.

Neththikumara, I.↗
DOE OSTI2016

Chama v. 0.1 (beta version)

Chama is a python package which includes mixed-integer, stochastic programming formulations to determine sensor locations and technology that maximize the effectiveness of a detection program. The software includes the ability to (1) generate concentration profiles using a Gaussian Plume model, (2), define a wide range of sensor technology, including stationary and mobile sensors, point detectors and cameras, (3) optimize sensor location and type using coverage or impact statistics, and (4) generate maps of the site that include concentration plumes and sensor layout.

Klise, Katherine↗
DOE OSTI2014

A 4H Silicon Carbide Gate Buffer for Integrated Power Systems

A gate buffer fabricated in a 2-mu m 4H silicon carbide (SiC) process is presented. The circuit is composed of an input buffer stage with a push-pull output stage, and is fabricated using enhancement mode N-channel FETs in a process optimized for SiC power switching devices. Simulation and measurement results of the fabricated gate buffer are presented and compared for operation at various voltage supply levels, with a capacitive load of 2 nF. Details of the design including layout specifics, simulation results, and directions for future improvement of this buffer are presented. In addition, plans for its incorporation into an isolated high-side/low-side gate-driver architecture, fully integrated with power switching devices in a SiC process, are briefly discussed. This letter represents the first reported MOSFET-based gate buffer fabricated in 4H SiC.

Ericson, N↗