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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrating HPC, AI, and Workflows for Scientific Data Analysis: Report from Dagstuhl Seminar 23352

The Dagstuhl Seminar 23352, titled “Integrating HPC, AI, and Workflows for Scientific Data Analysis,” held from August 27 to September 1, 2023, was a significant event focusing on the synergy between High-Performance Computing (HPC), Artificial Intelligence (AI), and scientific workflow technologies. The seminar recognized that modern Big Data analysis in science rests on three pillars: workflow technologies for reproducibility and steering, AI and Machine Learning (ML) for versatile analysis, and HPC for handling large data sets. These elements, while crucial, have traditionally been researched separately, leading to gaps in their integration. The seminar aimed to bridge these gaps, acknowledging the challenges and opportunities at the intersection of these technologies. The event highlighted the complex interplay between HPC, workflows, and ML, noting how ML has increasingly been integrated into scientific workflows, thereby enhancing resource demands and bringing new requirements to HPC architectures, like support for GPUs and iterative computations. The seminar also addressed the challenges in adapting HPC for large-scale ML tasks, including in areas like deep learning, and the need for workflow systems to evolve to leverage ML in data analysis fully. Moreover, the seminar explored how ML could optimize scientific workflow systems and HPC operations, such as through improved scheduling and fault tolerance. A key focus was on identifying prestigious use cases of ML in HPC and understanding their unique, unmet requirements. The stochastic nature of ML and its impact on the reproducibility of data analysis on HPC systems was also a topic of discussion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

CFD Simulation of Aerobic Gas Fermentation to Enable Commercial Conversion of CO 2 into Aquaculture and Animal Feed: Cooperative Research and Development (Final Report)

NovoNutrients’ fermentation technology uses energy from hydrogen to transform industrial CO2 emissions into premium animal feed ingredients and other valuable products. A single NovoNutrients’ commercial manufacturing plant will capture and convert over 200,000 tons/yr of CO2 into over 100,000 tons/yr of high-protein feed. Key to the rapid and widespread deployment of the technology is maximization of its productivity and energy efficiency. Robust, physically based computational models of the technology will significantly increase productivity and efficiency, accelerating NovoNutrients’ technology to manufacturing scale. NREL has unique capabilities for creating and running such computational models. NREL's existing aerobic bioreaction computational fluid dynamics (CFD) models will be adapted to NovoNutrients’ gas fermentation (CO2, H2, O2) technology. The multiphysics CFD simulations require thousands of high-performance computing (HPC) node hours to simulate the complex geometries and contents of NovoNutrients’ industrial bioreactors. The experimentally validated CFD models were used to identify optimally efficient and productive bioreactor designs and operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Streaming Readout and Data-Stream Processing With ERSAP

With the exponential growth in the volume and complexity of data generated at high-energy physics and nuclear physics research facilities, there is an imperative demand for innovative strategies to process this data in real or near-real-time. Given the surge in the requirement for high-performance computing, it becomes pivotal to reassess the adaptability of current data processing architectures in integrating new technologies and managing streaming data. This paper introduces the ERSAP framework, a modern solution that synergizes flow-based programming with the reactive actor model, paving the way for distributed, reactive, and high performance in data stream processing applications. Additionally, we unveil a novel algorithm focused on time-based clustering and event identification in data streams. The efficacy of this approach is further exemplified through the data-stream processing outcomes obtained from the recent beam tests of the EIC prototype calorimeter at DESY.

Vardan, Gyurjyan↗
DOE OSTI2022

Effective Selective Area Doping for GaN Vertical Power Transistors Enabled by Innovative Materials Engineering

GaN vertical power transistors have emerged as promising candidates for future high efficiency high power electronic applications, with the potential to outperform conventional GaN lateral power devices in terms of power, breakdown, and avalanche characteristics. However, the development of current GaN vertical power transistors is seriously hindered by the poor materials performance of selective area doped p-n junctions. A mechanistic understanding of these fundamental materials issues is essential in order to achieve high performance selective area doped p-n junctions and consequently to advance the GaN vertical power transistor technology. To address this challenge, we carried out a comprehensive research program that advance fundamental knowledge in the selective area doping for GaN materials, and which will lead to the development of high performance GaN vertical power transistors. First, we developed innovative fabrication processes, including novel surface etching, surface passivation, and metalorganic chemical vapor deposition (MOCVD) growth, which provided enhanced opportunities for solving the unique challenges of selective area doping in GaN materials. Second, we performed a fundamental materials study using powerful characterization methods including transmission electron microscopy (TEM), ultraviolet (UV-), x-ray and angle-resolved photoelectron spectroscopy (UPS/XPS/ARPES), electron holography, and cathodoluminescence (CL); Third, we investigated several related issues, including Mg incorporation, polarization effects in carrier transport, and non-ideal material effects, which have rarely been explored so far. At the end of this project, we successfully demonstrated (1) fundamental understanding of selective area etching, regrowth, and doping of GaN, and associated knowledge on defects, interface, and breakdown properties. (2) Effective etch and regrowth processing recipes to achieve etch/regrowth GaN p-n diodes with very low leakage of 3.5 nA at 600 V, which meets the ARPA-E target. (2) High performance vertical GaN p-n didoes and vertical junction termination extension (JTE) devices with breakdown voltage of ~ 2 kV, and breakdown electric field of ~ 3.5 MV/cm, which are close to the performance limit of GaN. The successful outcome has resulted in new fundamental understandings in the selective area doping and regrowth process for GaN, which will lead to groundbreaking GaN vertical transistors for high performance next generation power electronics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

REFRACTORY COMPACT HEAT EXCHANGERS WITH EMBEDDED SENSORS ENABLED BY HYBRID ADVANCED SINTERING AND ADDITIVE APPROACH

Structural health monitoring (SHM) of compact heat exchangers (CHXs) operating in extreme environments is essential for ensuring system reliability, safety, and longevity. This study presents the development of high-temperature sensors fabricated via aerosol jet printing (AJP) using platinum ink, selected for its exceptional thermal stability, oxidation resistance, and electrical conductivity. AJP enables precise deposition of fine-feature sensor patterns onto complex geometries, making it well-suited for integration within CHX architectures. To enhance sensor durability, an alumina-based ceramic protective layer was printed over the platinum sensing elements. The sensors demonstrated stable, repeatable performance up to 900?°C during extended thermal cycling. A custom test setup was developed to evaluate sensor accuracy and robustness under steady-state and transient conditions. Substrate screening identified HG-1 ceramic-coated stainless steel as the most effective platform, offering strong adhesion and low resistance. Furthermore, electric field-assisted sintering (EFAS) was employed to embed the sensors into stainless steel 316L matrices without degrading their functionality. Post-embedding electrical tests confirmed sensor integrity, and initial characterization suggests strong potential for in-situ monitoring. This work provides a scalable strategy for integrating high-performance temperature sensors directly into refractory components, advancing embedded SHM technologies for harsh operating environments.

36 - MATERIALS SCIENCE↗
DOE OSTI2021

High-impact innovations for high-salinity membrane desalination

Significance Researchers lack the tools for quantitatively evaluating the impact of their research on technology costs, especially when those technologies comprise multiple components or when the component costs are highly uncertain. We propose a suite of tools to aid in evaluating technology platforms, setting system- and component-level research targets and identifying high-impact innovation trajectories. These tools are applicable to any technology composed of multiple components whose performance or cost will benefit from innovation, but they are especially valuable for membrane systems in which the high interdependence in components amplifies or dampens the effects of innovation in nonintuitive ways.

Dudchenko, Alexander V.↗
DOE OSTI2023

Channeling Engineering of Hydroxide Ion Exchange Polymers and Reinforced Membranes

In this project, a team of researchers from Rensselaer Polytechnic Institute developed high performance alkaline conductors which can improve efficiency and lower cost of energy storage and conversion technology. The Rensselaer Polytechnic Institute team has developed a highly ion conductive, chemically stable, and mechanically durable alkaline membrane materials. Such membranes will serve as a critical component in electrochemical devices when energy was generated from renewable sources (e.g., sun and wind) or hydrogen fuel. The use of alkaline membrane in electrochemical reactions allows to replace expensive platinum catalyst to less expensive, earth abundant metals as catalysts, offering huge economic advantages in renewable energy technology.

08 HYDROGEN↗
DOE OSTI2020

Analysis of a Fluidized-Bed Particle/Supercritical-CO2 Heat Exchanger in a Concentrating Solar Power System

Concentrating solar power (CSP) development has focused on increasing the energy conversion efficiency and lowering the capital cost. To improve performance, CSP research is moving to high-temperature and high-efficiency designs. One technology approach is to use inexpensive, high-temperature heat transfer fluids and storage, integrated with a high-efficiency power cycle such as the supercritical carbon dioxide (sCO 2 ) Brayton power cycle. The sCO 2 Brayton power cycle has strong potential to achieve performance targets of 50% thermal-to-electric efficiency and dry cooling at an ambient temperature of up to 40 °C and to reduce the cost of power generation. Solid particles have been proposed as a possible high-temperature heat transfer or storage medium that is inexpensive and stable at high temperatures above 1000 °C. The particle/sCO 2 heat exchanger (HX) provides a connection between the particles and sCO 2 fluid in emerging sCO 2 power cycles. This article presents heat transfer modeling to analyze the particle/sCO 2 HX design and assess design tradeoffs including the HX cost. The heat transfer process was modeled based on a particle/sCO 2 counterflow configuration, and empirical heat transfer correlations for the fluidized bed and sCO 2 were used to calculate heat transfer area and estimate the HX cost. A computational fluid dynamics simulation was applied to characterize particle distribution and fluidization. This article shows a path to achieve the cost and performance objectives for a particle/sCO 2 HX design by using fluidized-bed technology.

14 SOLAR ENERGY↗
DOE OSTI2020

High Capacity for Mg 2+ Deintercalation in Spinel Vanadium Oxide Nanocrystals

Nonaqueous Mg batteries can theoretically reach high energy density with cost-effective materials, yet no such device to date has performance competitive with Li-ion technologies. A major barrier is the need for oxide cathodes that combine high capacity and voltage. Very few oxides have shown intrinsic ability for Mg 2+ intercalation in electrolytes with acceptably low content of H2O. Herein, we demonstrate that nanocrystals of MgV 2 O 4 can reach high capacity for Mg 2+ deintercalation with a mechanism that preserves their spinel framework, validated through measurements with different chemical and structural sensitivity. The structural stability contrasts with other phases where reaching high capacity required distortions that introduce undesirable mechanical strain. The favorable properties of the oxide allowed cycling in a full cell with Mg metal. This work reveals new insights into the viability of multivalent intercalation in oxides, meeting a milestone toward the feasibility of high-voltage batteries with either Mg metal or Mg-ion anodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Automotive Power Electronics Cooling Technology Research at NREL

This presentation describes power electronics thermal management technologies used for on-road EVs. Examples are provided and heat exchangers are described. Advanced cooling technologies developed are NREL to enable increased power density and enable high WBG temperature operation are then presented. The performance (e.g., thermal resistance, pumping power) of the advanced power electronics cooling technologies are compared to the performance of current, on-road technology.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Power Electronics Cooling Technology Research at NREL

This presentation describes power electronics thermal management technologies used for on-road EVs. Examples are provided and heat exchangers are described. Advanced cooling technologies developed are NREL to enable increased power density and enable high WBG temperature operation are then presented. The performance (e.g., thermal resistance, pumping power) of the advanced power electronics cooling technologies are compared to the performance of current, on-road technology.

DIRECT ENERGY CONVERSION↗
DOE OSTI2025

The Viskores User's Guide, Release 1.1

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created Viskores: the visualization toolkit for multi/many-core architectures. Viskores supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. Viskores also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although Viskores provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The Viskores User's Guide (V.1.0)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created Viskores: the visualization toolkit for multi-/many-core architectures. Viskores supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. Viskores also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although Viskores provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

High Performance Solvent for NGCC Flue Gas CO 2 Capture (Final Technical Report)

Amine-based solvent absorption is the most mature and reliable technology for large scale CO 2 capture, dating back to the 1930s when monoethanolamine (MEA) was used to treat acid gases from oil refineries. However, while strategic advancements have optimized the CO2 capture process, the cost of capture remains high, where current estimates suggest that CO 2 capture costs are around $\$$72/tonne of CO 2 . To address this, solvent development and optimization have become a focus of current research. This project sought to develop a high-performance solvent to reduce the overall cost of CO 2 capture from NGCC flue gas. Here, solvent optimization focused on: (1) reducing the energy required for CO 2 desorption in a reboiler, (2) improving CO 2 absorption and desorption reaction kinetics, (3) improving solvent stability, and (4) reducing environmental impacts. Susteon has developed and evaluated a promoted solvent, Sustenol™, for NGCC flue gas CO 2 capture. The optimized Sustenol™ also shows a higher dynamic CO 2 absorption capacity of ~0.5 mol CO2 /mol amine compared to 0.25 mol CO2 /mol amine for 30 wt% MEA. Additionally, the solvent is oxidatively, thermally and hydrothermally stable, which leads to lower solvent loss and emissions. These advancements have resulted in a solvent regeneration energy of 2.16 GJ/tonne of CO 2 which is >30% lower than current state-of-the-art commercial and emerging solvents. Combined with empirical data from the bench and pilot scale testing, this preliminary TEA study indicated the cost of CO 2 capture by Sustenol™ for 97% CO 2 removal at $\$$54/tonne and for 90% removal at $\$$49/tonne, with a pathway to achieve $\$$45/tonne of CO 2 with continued process and solvent advancements. Susteon has developed a technology roadmap to reduce the cost of CO 2 capture to <$\$$45/tonne for NGCC flue gas. Susteon plans to derisk this technology for commercial deployment through comprehensive solvent degradation testing, long-term testing in a pilot plant at 5 tonne CO2 /day and demonstration scale testing at 100 tonne CO2 /day with NGCC flue gas and engineering design studies to qualify Sustenol™ as a drop-in replacement solvent.

03 NATURAL GAS↗
DOE OSTI2021

VTK-m User's' Guide (V.1.7)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Consider the listings in Figure 1.1 that compares the size of the implementation for the Marching Cubes algorithm in VTK-m with the equivalent reference implementation in the CUDA software development kit. Because VTK-m internally manages the parallel distribution of work and data, the VTK-m implementation is shorter and easier to maintain. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.This book includes contributions from the VTK-m community including the VTK-m development team and the user community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The VTK-m Users' Guide (V.1.9)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Consider the listings in Figure 1.1 that compares the size of the implementation for the Marching Cubes algorithm in VTK-m with the equivalent reference implementation in the CUDA software development kit. Because VTK-m internally manages the parallel distribution of work and data, the VTK-m implementation is shorter and easier to maintain. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.

97 MATHEMATICS AND COMPUTING↗