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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Full time-dependent SOLPS-ITER simulation of the SPARC tokamak: actuator design for particle and divertor condition control *

Abstract This paper presents the application of full time-dependent SOLPS-ITER simulations for actuator design in the SPARC tokamak. This study employs both the EIRENE module, a neutral solver, and the B2.5 plasma module in a time-dependent mode. This is in contrast to most SOLPS simulations, which focus on steady-state solutions, where the neutral distribution is evolved without any time limit or for a time step of 1 ⋅ 10 − 3 second, which is several orders of magnitude larger than the fluid plasma time step. The time-dependent EIRENE was tested with a fixed B2.5 background and compared with a simple conductance based model in a simplified pump chamber geometry. This comparison aimed to verify the reliability of the neutral relaxation timescale derived from the time-dependent EIRENE. Subsequently, a full time-dependent simulation was performed in a realistic geometry, with the Monte-Carlo neutral time step synchronized with the plasma fluid time step. The numerical setup of the code, including relative time steps and the size of the census data used to store Monte-Carlo particle information is considered. The full-time dependent simulations are then applied to inform the design of the SPARC louver structure, which affects divertor plasma parameters by regulating the neutral conductance from the divertor to the pump. The response of the plasma and neutral parameters was captured on a timescale that enables the design of the actuator to consider time-dependent control capability. It was found that changing the louver opacity has an equivalent effect as varying the gas throughput via puff actuation. Therefore, equivalent divertor plasma conditions can be obtained from both actuators, while the neutral pressure distribution in the pump and divertor differs for each actuator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Focused‐beam X‐ray fluorescence and diffraction microtomographies for mineralogical and chemical characterization of unsectioned extraterrestrial samples

Abstract This study describes the application of new synchrotron X‐ray fluorescence (XRF) and diffraction (XRD) microtomographies for the 3‐D visualization of chemical and mineralogical variations in unsectioned extraterrestrial samples. These improved methods have been applied to three compositionally diverse chondritic meteorite samples that were between 300 and 400 μm in diameter, including samples prepared from fragments of the CR2 chondrite LaPaz Icefield (LAP) 02342, H5 chondrite MacAlpine Hills (MAC) 88203, and the CM2 chondrite Murchison. The synchrotron‐based XRF and XRD tomographies used are focused‐beam techniques that measure the intensities of fluorescent and diffracted X‐rays in a sample simultaneously during irradiation by a high‐energy microfocused incident X‐ray beam. Measured sinograms of the emitted and diffracted intensities were then tomographically reconstructed to generate 2‐D slices of XRF and XRD intensity through the sample, with reconstructed pixel resolution of 1–2 μm, defined by the resolution of the focused incident X‐ray beam. For sample LAP 02342, primary mineral phases that were visualized in reconstructed slices using these techniques included isolated grains of α‐Fe, orthopyroxene, and olivine. For our sample of MAC 88203, XRF/XRD tomography allowed visualization of forsteritic olivine as a primary mineral phase, a vitrified fusion crust at the sample surface, identification of localized Cr‐rich spinels at spatial resolutions of several micrometers, and imaging of a plagioclase‐rich glassy matrix. In the sample of Murchison, major identifiable phases include clinoenstatite‐ and olivine‐rich chondrules, variable serpentine matrix minerals and small Cr‐rich spinels. Most notable in the tomographic analysis of Murchison is the ability to quantitatively distinguish and visualize the complex mixture of serpentine‐group minerals and associated tochilinite–cronstedtite intergrowths. These methods provide new opportunities for spatially resolved characterization of sample texture, mineralogy, crystal structure, and chemical state in unsectioned samples. This provides researchers an ability to characterize such samples internally with minimal disruption of sample micro‐structures and chemistry, possibly without the need for sample extraction from some types of sampling and capture media.

Geochemistry & Geophysics↗
DOE OSTI2020

System-Level Thermal Management and Reliability of Automotive Electronics: Goals and Opportunities Using Phase-Change Materials

Abstract Electronic packaging for automotive applications are at particular risk of thermomechanical failure due to the naturally harsh conditions it is exposed to. With the rise of electric and hybrid electric vehicles (EVs and HEVs), combined with a desire to miniaturize, the challenge of removing enough heat from electronic devices in automotive vehicles is evolving. This paper closely examines the new challenges in thermal management in various driving environments and aims to classify each existing cooling method in terms of performance. Particular focus is placed upon emerging solutions regarded to hold great potential, such as phase-change materials (PCMs). PCMs have been regarded for some time as a means of transferring heat quickly away from the region with the electronic components and are widely regarded as a possible means of carrying out cooling in large scale from small areas, because of their high latent heat of fusion, high specific heat, temperature stability, and small volume change during phase change, etc. They have already been utilized as a method of passive cooling in electronics in various ways, but their adoption in automotive power electronics, such as in traction inverters, has yet to be fulfilled. A brief discussion is made on some of the potential areas of application and challenges relating to more widespread adoption of PCMs, with reference to a case study using computational model of a commercially available power module used in automotive applications.

Engineering↗
DOE OSTI2022

Precursor prioritization for p-cymene production through synergistic integration of biology and chemistry

Abstract The strategy of synergistic application of biological and chemical catalysis is an important approach for efficiently converting renewable biomass into chemicals and fuels. In particular, the method of determining the appropriate intermediate between the two catalytic methods is critical. In this work, we demonstrate p -cymene production through the integration of biosynthesis and heterogenous catalysis and show how a preferred biologically derived precursor could be determined. On the biological side, we performed the limonene and 1,8-cineole production through the mevalonate pathway. Titers of 0.605 g/L and a 1.052 g/L were achieved, respectively. This difference is in agreement with the toxicity of these compounds toward the producing microorganisms, which has implications for subsequent development of the microbial platform. On the heterogeneous catalysis side, we performed the reaction with both biological precursors to allow for direct comparison. Using hydrogenation/dehydrogenation metals on supports with acid sites, both limonene and 1,8-cineole were converted to p -cymene with similar yields under equivalent reaction conditions. Thus, we could determine that the most promising strategy would be to target 1,8-cineole, the higher titer and lower toxicity bio-derived precursor with subsequent catalytic conversion to p -cymene. We further optimized the biological production of 1,8-cineole via fed-batch fermentation and reached the titer of 4.37 g/L which is the highest known 1,8-cineole titer from microbial production. This work provides a valuable paradigm for early stage considerations to determine the best route for the high-efficiency production of a target biobased molecule using an integration of biology and chemistry.

09 BIOMASS FUELS↗
DOE OSTI2021

Advances in engineering microbial biosynthesis of aromatic compounds and related compounds

Abstract Aromatic compounds have broad applications and have been the target of biosynthetic processes for several decades. New biomolecular engineering strategies have been applied to improve production of aromatic compounds in recent years, some of which are expected to set the stage for the next wave of innovations. Here, we will briefly complement existing reviews on microbial production of aromatic compounds by focusing on a few recent trends where considerable work has been performed in the last 5 years. The trends we highlight are pathway modularization and compartmentalization, microbial co-culturing, non-traditional host engineering, aromatic polymer feedstock utilization, engineered ring cleavage, aldehyde stabilization, and biosynthesis of non-standard amino acids. Throughout this review article, we will also touch on unmet opportunities that future research could address.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1985

Multishaker modal testing

A component mode synthesis method for damped structures was developed and modal test methods were explored which could be employed to determine the relevant parameters required by the component mode synthesis method. Research was conducted on the following topics: (1) Development of a generalized time-domain component mode synthesis technique for damped systems; (2) Development of a frequency-domain component mode synthesis method for damped systems; and (3) Development of a system identification algorithm applicable to general damped systems. Abstracts are presented of the major publications which have been previously issued on these topics.

Craig, R. R., Jr.↗
NASA NTRS1985

Experiments with Ada

A 1200-line Ada source code project simulating the most basic functions of an operations control center was developed. We selected George Cherry's Process Abstraction Methodology for Embedded Large Applications (PAMELA) and DEC's Ada Compilation System (ACS) under VAX/VMS to build the software from requirements to acceptance test. The system runs faster than its FORTRAN implementation and was produced on schedule and under budget with an overall productivity in excess of 30 lines of Ada source code per day.

Roy, D.↗
NASA NTRS1986

A software development environment utilizing PAMELA

Hardware capability and efficiency has increased dramatically since the invention of the computer, while software programmer productivity and efficiency has remained at a relatively low level. A user-friendly, adaptable, integrated software development environment is needed to alleviate this problem. The environment should be designed around the Ada language and a design methodology which takes advantage of the features of the Ada language as the Process Abstraction Method for Embedded Large Applications (PAMELA).

Flick, R. L.↗
NASA NTRS1991

Space Electrochemical Research and Technology

This document contains the proceedings of NASA's third Space Electrochemical Research and Technology (SERT) Conference, held at the NASA Lewis Research Center on April 9-10, 1991. The objective of the conference was to assess the present status and general thrust of research and development in those areas of electrochemical technology required to enable NASA missions into the next century. The conference provided a forum for the exchange of ideas and opinions of those actively involved in the field, in order to define new opportunities for the application of electrochemical processes in future NASA missions. Papers were presented in three technical areas: the electrochemical interface, the next generation in aerospace batteries and fuel cells, and electrochemistry for nonenergy storage applications. This document contains the abstracts of the papers presented.

Electrochemistry↗
NASA NTRS2013

SpF: Enabling Petascale Performance for Pseudospectral Dynamo Models

Pseudospectral (PS) methods possess a number of characteristics (e.g., efficiency, accuracy, natural boundary conditions) that are extremely desirable for dynamo models. Unfortunately, dynamo models based upon PS methods face a number of daunting challenges, which include exposing additional parallelism, leveraging hardware accelerators, exploiting hybrid parallelism, and improving the scalability of global memory transposes. Although these issues are a concern for most models, solutions for PS methods tend to require far more pervasive changes to underlying data and control structures. Further, improvements in performance in one model are difficult to transfer to other models, resulting in significant duplication of effort across the research community.We have developed an extensible software framework for pseudospectral methods called SpF that is intended to enable extreme scalability and optimal performance. High-level abstractions provided by SpF unburden applications of the responsibility of managing domain decomposition and load balance while reducing the changes in code required to adapt to new computing architectures. The key design concept in SpF is that each phase of the numerical calculation is partitioned into disjoint numerical kernels that can be performed entirely in-processor. The granularity of domain-decomposition provided by SpF is only constrained by the data-locality requirements of these kernels. SpF builds on top of optimized vendor libraries for common numerical operations such as transforms, matrix solvers, etc., but can also be configured to use open source alternatives for portability. SpF includes several alternative schemes for global data redistribution and is expected to serve as an ideal testbed for further research into optimal approaches for different network architectures.In this presentation, we will describe the basic architecture of SpF as well as preliminary performance data and experience with adapting legacy dynamo codes. We will conclude with a discussion of planned extensions to SpF that will provide pseudospectral applications with additional flexibility with regard to time integration, linear solvers, and discretization in the radial direction.

Pseudospectral (PS)↗
DOE OSTI2024

Empowering Geothermal Research: The Geothermal Data Repository's New AI Research Assistant: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has integrated a Large Language Model (LLM) with the metadata and supporting documents associated with GDR datasets to create an Artificially Intelligent (AI) research assistant. By leveraging work done to make GDR metadata machine-readable and an open-source LLM integration model called the Energy Language Model, developed by the National Renewable Energy Laboratory, AskGDR serves as a virtual research assistant to GDR users. It provides answers to a variety of user-provided questions using natural language processing and generative machine learning. Users can get answers to questions about specific datasets, including inquiries about the equipment, assumptions and methodologies used in the origination of the data; or more abstract questions, such as the applicability of data to specific research fields. AskGDR improves the discoverability of geothermal data by helping guide users to datasets beyond simple keyword searches. It enables users to find data based on properties of the data, discover information contained within supporting documents, and explore data from projects related to their research objectives.

access↗
DOE OSTI2025

Empowering Geothermal Research: The Geothermal Data Repository's New AI Research Assistant

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has integrated a Large Language Model (LLM) with the metadata and supporting documents associated with GDR datasets to create an Artificially Intelligent (AI) research assistant. By leveraging work done to make GDR metadata machine-readable and an open-source LLM integration model called the Energy Language Model, developed by the National Renewable Energy Laboratory, AskGDR serves as a virtual research assistant to GDR users. It provides answers to a variety of user-provided questions using natural language processing and generative machine learning. Users can get answers to questions about specific datasets, including inquiries about the equipment, assumptions and methodologies used in the origination of the data; or more abstract questions, such as the applicability of data to specific research fields. AskGDR improves the discoverability of geothermal data by helping guide users to datasets beyond simple keyword searches. It enables users to find data based on properties of the data, discover information contained within supporting documents, and explore data from projects related to their research objectives. This paper will outline the development, integration, output, and efficacy of the AskGDR LLM, including adherence to scientific rigor through improvements designed to increase the accuracy of generated answers, avoid speculation, and provide proper references for all resources used.

access↗
DOE OSTI2021

Transmission x-ray microscopy and its applications in battery material research—a short review

Abstract Transmission x-ray microscopy (TXM), which can provide morphological and chemical structural information inside of battery component materials at tens of nanometer scale, has become a powerful tool in battery research. This article presents a short review of the TXM, including its instrumentation, battery research applications, and the practical sample preparation and data analysis in the TXM applications. A brief discussion on the challenges and opportunities in the TXM applications is presented at the end.

25 ENERGY STORAGE↗