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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Los Angeles 100% Renewable Energy Study (LA100): Chapter 12. Synthesis

The City of Los Angeles has set ambitious goals to transform its electricity supply, aiming to achieve a 100% renewable energy power system by 2045, along with aggressive electrification targets for buildings and vehicles. To reach these goals, and assess the implications for jobs, electricity rates, the environment, and environmental justice, the Los Angeles City Council passed a series of motions directing the Los Angeles Department of Water and Power (LADWP) to determine the technical feasibility and investment pathways of a 100% renewable energy portfolio standard. The Los Angeles 100% Renewable Energy Study (LA100) is a first-of-its-kind objective, rigorous, and science-based power systems analysis to determine what investments could be made to achieve these goals. The LA100 final report is presented as a collection of 12 chapters and an executive summary, each of which is available as an individual download. This chapter reviews high-level findings, costs, benefits, and lessons learned from integrating this diverse suite of models and conducting a high-fidelity 100% renewable energy study.

100% Renewable↗
DOE OSTI2025

GlideinBenchmark: collecting resource information to optimize provisioning

Choosing the right resource can speed up job completion, better utilize the available hardware, and visibly reduce costs, especially when renting computers in the cloud. This was demonstrated in earlier studies on HEPCloud. However, the benchmarking of the resources proved to be a laborious and time-consuming process. This paper presents GlideinBenchmark, a new Web application leveraging the pilot infrastructure of GlideinWMS to benchmark resources, and it shows how to use the data collected and published by GlideinBenchmark to automate the optimal selection of resources. An experiment can select the benchmark or the set of benchmarks that most closely evaluate the performance of its workflows. GlideinBenchmark, with the help of the GlideinWMS Factory, controls the benchmark execution. Finally, a scheduler like HEPCloud's Decision Engine can use the results to optimize resource provisioning.

Mambelli, Marco [Fermilab] (ORCID:0000000294892681↗
DOE OSTI2024

GlideinBenchmark: collecting resource information to optimize provisioning

Choosing the right resource can speedup jobs completion, better utilize the available hardware and visibly reduce costs, especially when renting computers on the cloud. This was demonstrated in earlier studies on HEPCloud. But the benchmarking of the resources proved to be a laborious and time-consuming process. This paper presents GlideinBenchmark, a new Web application leveraging the pilot infrastructure of GlideinWMS to benchmark resources, and shows how to use the data collected and published by GlideinBenchmark to automate the optimal selection of resources. An experiment can select the benchmark or the set of benchmarks that most closely evaluate the performance of its workflows. With GlideinBenchmark and the help of the GldieinWMS Factory it controls the benchmark execution. Finally, a scheduler like HEPCloud’s Decision Engine can use the results to optimize resource provisioning.

Mambelli, Marco↗
DOE OSTI2024

Utah FORGE: Wells 16A(78)-32 and 16B(78)-32 Stimulation Program Report - May 2024

This dataset consists of a comprehensive report documenting the stimulation program conducted in May 2024 on Utah FORGE wells 16A(78)-32 and 16B(78)-32. It includes detailed accounts of operational and scientific objectives, stimulation methodologies, and testing outcomes. The report describes the hydraulic fracturing activities, equipment setups, proppant and fluid usage, and the execution of a nine-hour circulation test. It also includes observations from seismic and fiber optic monitoring systems, providing data on microseismic activity and fracture propagation. Detailed parameters for each stimulation stage are provided, alongside operational challenges and solutions. The dataset includes analyses of injection and production rates, well temperatures, and pressure data, supported by graphical illustrations and logs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Southwest Wind Power R&D Test Site Development at the National Wind Technology Center (CRADA CRD-12-00472 Final Report)

Southwest Windpower, Inc. (SWWP) has been designing and distributing small wind turbines for more than 22 years and is the recognized global leader in the design, manufacturing and distribution of small wind systems (400-3000 watts). The company has been a pioneer in the development of wind technology and has built and shipped more than 170,000 wind turbines to over 120 countries worldwide. Headquartered in Flagstaff AZ, SWWP has sales representatives in over 88 countries. Applications for SWWP systems include residential homes, commercial properties, micro grids, remote cabins, telecom transmitters, offshore platforms, water pumping and sailboats. In addition, U.S. Department of Defense uses SWWP’s products in Forward Operating Bases (FOB’s), USGS uses them for remote monitoring of glacier movements and the CIA uses them to provide power seismic monitoring. Today, SWWP plans development of new technologies to address distributed energy market needs and become even more aggressive in international markets. This strategy includes extensive Research, Development, Demonstration & Deployment (RDD&D) activities to improve existing production line into more simple, reliable, and cost-effective wind turbine systems. Important part of such activities is the field testing of the new systems, which should provide: (i) validation of the reliable operation of hardware and software; (ii) validation of numerical models of the system and its components; (iii) field comparison of various control and optimization strategies; (iv) customized reliability testing; (v) customized monitoring and analysis testing; and (vi) IEC certification testing (vii) filed demonstration of system performance and reliability. Such field testing facility should encompass multiple towers and appropriate data acquisition systems. SWWP is exploring to move part of the engineering department to Colorado, and execute its RDD&D strategies in this new location. Partnership with NREL will provide great insights into SWWP’s RDD&D processes and more efficient commercialization by utilizing NWTC as the field testing site, and working close with NREL personnel. NWTC is ideally suited to strain the design. NREL is very experienced with customized and IEC testing. During this project, Southwest Windpower aims to improve the value proposition of distributed renewable energy, and make it a competitive choice in the energy markets. As of today, more then 170,000 small wind turbines, manufactured in the U.S., are installed in more then 180 countries. With the improved value proposition, Southwest Windpower wants to create and address new market needs, substantially increase its sales domestically and internationally, which should have positive impact on the creation of American jobs, competitiveness of U.S. economy, export or U.S. products, and the use of renewable energy.

17 WIND ENERGY↗
DOE OSTI2024

Supercharge NY

The Energy Program for Innovation Clusters (EPIC) Supercharge NY enabled The Clean Fight to execute an inaugural accelerator program focused on enabling world-class, growth-stage energy storage companies to successfully scale deployments and establish domestic manufacturing pathways in New York State. The Clean Fight has developed and tested a successful accelerator model designed to reduce the barriers growth-stage climate tech companies face by collapsing the sales cycle to scaling solutions at speed. The Clean Fight’s Supercharge NY project allowed for the exploration into the understanding of New York-focused energy storage opportunities, challenges, and methods for enabling successful projects. The Clean Fight’s Supercharge NY project enabled high-touch matchmaking with industry leading customer and capital partners, technical assistance to facilitate scaling supply chain and manufacturing capacity, and access to non-dilutive funding for first-of-a-kind or demonstration projects in New York State. The results of the program provide a public benefit by accelerating deployments of energy storage to provide value-added energy services and sustainability benefits to communities while boosting economic opportunity and job creation for all.

25 ENERGY STORAGE↗
DOE OSTI2020

Workflow Submit Nodes as a Service on Leadership Class Systems

DOE scientists, today, have access to high performance computing (HPC) facilities with very powerful systems that enable them to execute their computations faster, more efficiently, and at greater scales than ever before. To further their knowledge and produce new discoveries, scientists rely on workflows - sometimes very complex - that provide them with an easy way to automate, reproduce and verify their computations. However, historically, creating workflow submission environments in large HPC facilities has been cumbersome, requires expertise and many man-hours of effort due to the peculiarities, policies, and the restrictions that these systems present. In this paper we discuss the approach a large DOE facility (OLCF) is taking in order to provide containers as a service to its users. This capability is used to create Pegasus workflow management system submit nodes as a service (WSaaS) at the Oak Ridge Leadership Computing Facilities (OLCF), targeting the Summit supercomputer. This deployment builds upon the Kubernetes/Openshift cluster (Slate) that exists within OLCF’s DMZ and its automation triggers. Additionally, we evaluate our approach’s overhead and effort to deploy the solution as compared to previous solutions, such as setting up a Pegasus submission environment on OLCF’s login nodes or submitting jobs remotely via the rvGAHP.

Papadimitriou, George↗
DOE OSTI2025

Low Carbon Intensity Formic Acid Chemical Synthesis from Direct Air Captured CO 2 Utilizing Chemical Plant Waste Heat - Final Technical Report

The primary objective of Low Carbon Intensity Formic Acid Chemical Synthesis from Direct Air Captured CO 2 Utilizing Chemical Plant Waste Heat (ChemFADAC) is to execute and complete a FEED study for an integrated direct air capture (DAC) and carbon conversion system (together, the DACUS system) co-located at a Nutrien nitric acid production facility in Kennewick, WA capable of capturing and converting a minimum of 5,000 MT/year net atmospheric CO 2 to low carbon intensity formic acid (FA) using industrial waste heat and renewable electricity. The goal will be achieved through the completion of four objectives using a collaborative approach with community stakeholders. Objective 1. Conduct a FEED study and Class 3 project cost estimate for the proposed DACUS system that maximizes use of thermal energy from the Nutrien KFO host site to produce low carbon intensity FA from atmospheric CO 2 . Objective 2. Perform a cradle-to-gate life-cycle analysis of the DACUS system to determine the environmental sustainability and carbon intensity (CI) of the proposed project and product from the results of the FEED study. Objective 3. Perform a business case analysis from results of the LCA, FEED study and cost estimate to justify investment to build the DACUS project at the Nutrien KFO site. Objective 4. Quantify how deployment of the proposed technology will promote and prepare a ready workforce for clean energy and manufacturing jobs and coordinate with community stakeholders to perform an environmental justice and a preliminary economic revitalization and job creation outcomes analysis.

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

Industrial Carbon Capture from a Cement Facility Using the Cryocap FG Process (FE0032136)

The project's objective was to execute and complete front-end engineering and design (FEED) studies for commercial-scale, carbon capture projects that separate 95% of the total CO2 emissions at an industrial facility, producing at least 100,000 metric tonnes/year of CO2 for sequestration. The industrial facility selected is the Holcim (US) Ste. Genevieve cement manufacturing facility (the largest single kiln line in the world), while the carbon capture system selected is Pressure Swing Adsorption system (PSA) assisted Cryocap™ technology developed by Air Liquide. The impact of the project on Environmental Justice and the regional economy was also analyzed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Industrial Carbon Capture from a Cement Facility Using the CryocapTM FG Process (2023 FECM/NETL Conference Proceeding)

The project's objective was to execute and complete front-end engineering and design (FEED) studies for commercial-scale, carbon capture projects that separate 95% of the total CO2 emissions at an industrial facility, producing at least 100,000 metric tonnes/year of CO2 for sequestration. The industrial facility selected is the Holcim (US) Ste. Genevieve cement manufacturing facility (the largest single kiln line in the world), while the carbon capture system selected is Pressure Swing Adsorption system (PSA) assisted Cryocap™ technology developed by Air Liquide. The impact of the project on Environmental Justice and the regional economy was also analyzed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Demonstration of Electrolyzer Operation at a Nuclear Plant to Allow for Dynamic Participation in an Organized Electricity Market and In-House Hydrogen Supply

This document details the execution of Cooperative Agreement DE-EE0008849, “demonstration of electrolyzer operation at a nuclear plant to allow for dynamic participation in an organized electricity market and in-house hydrogen supply” during the performance period of 10/1/2019 – 9/30/2024. The project was funded by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE). Constellation Energy Generation, LLC (formerly Exelon Generation Company, LLC) is the prime recipient of the award. Other members of the project team are INL, NREL, ANL and Nel Hydrogen. The main project objective was to demonstrate an end-to-end integrated grid-scale carbon-free H 2 production, storage and utilization pilot plant at a nuclear generating facility. The project also aimed to evaluate market opportunities and regulatory requirements related to the participation of integrated hydrogen production and nuclear plant facilities in organized power markets, by demonstrating dynamic control and operation of the electrolyzer and assessing the economics of dynamic participation combined with the revenue streams from hydrogen production. On March 7th , 2023 Constellation started hydrogen production at it’s Nine Mile Point Nuclear Plant in Oswego, New York. The PEM electrolyzer operating at Nine Mile Point uses 1.25 megawatt of nuclear electricity to produce 560 kilograms of clean hydrogen per day, more than enough to meet the plant’s operational hydrogen use. It will also help set the stage for possible large-scale deployments at other clean energy centers in Constellation’s fleet that would couple clean hydrogen production with storage and other on-site uses. Employing the lessons learned from the 1.25 MW demonstration-scale, nuclear-powered clean hydrogen production facility at Nine Mile Point, Constellation was a major participant in the MachH2 hydrogen hub recently selected for up to $\$$1 billion by the Department of Energy (DOE) as part of the bipartisan Infrastructure Investment and Jobs Act. Constellation will use a portion of the hub funding to build the world’s largest nuclear-powered clean hydrogen production facility at its LaSalle Clean Energy Center in Illinois. The project was featured in a number of news articles and press releases and received 2 awards. At the 2023 DOE HFTO’s Annual Merit Review meeting, the P.I. Dr. Uuganbayar Otgonbaatar and project manager Robert Beaumont were recognized for “outstanding achievements in the development and demonstration of a first-of-a-kind clean hydrogen production facility, powered by carbon-free nuclear energy, at the Nine Mile Point Nuclear Station in Oswego, New York.” The project was also awarded 2023 Nuclear Energy Institute’s Top Innovative Practice award.

08 HYDROGEN↗
DOE OSTI2024

Industrial Carbon Capture from a Cement Facility Using the Cryocap™ FG Process

The objective of the project was to execute and complete front-end engineering and design (FEED) studies for commercial-scale, carbon capture projects that separate 95% of the total CO 2 emissions at an industrial facility, producing at least 100,000 metric tonnes/year of CO 2 for sequestration. The industrial facility selected is the Holcim (US) Ste. Genevieve cement manufacturing facility (the largest single kiln line in the world), while the carbon capture system selected is Pressure Swing Adsorption system (PSA) assisted Cryocap™ technology developed by Air Liquide. The industrial host site emits approximately 3 million tonnes CO 2 /year based on plant data from 2020-2022. The captured CO 2 will meet the requirements of transport (Pipeline Grade) and geological storage, and the geological storage facilities within 80 miles of the CO 2 source. The impact of the project on Environmental Justice and the regional economy was also analyzed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

AutoLabs: cognitive multi-agent systems with self-correction for autonomous chemical experimentation

The automation of chemical research through self-driving laboratories (SDLs) promises to accelerate scientific discovery, yet the reliability and granular performance of the underlying AI agents remain critical, under-examined challenges. In this work, we introduce AutoLabs, a self-correcting, multi-agent architecture designed to autonomously translate natural-language instructions into executable protocols for a high-throughput liquid handler. The system engages users in dialogue, decomposes experimental goals into discrete tasks for specialized agents, performs tool-assisted stoichiometric calculations, and iteratively self-corrects its output before generating a hardware-ready file. We present a comprehensive evaluation framework featuring five benchmark experiments of increasing complexity, from simple sample preparation to multi-plate timed syntheses. Through a systematic ablation study of 20 agent configurations, we assess the impact of reasoning capacity, architectural design (single- vs. multi-agent), tool use, and self-correction mechanisms. Our results demonstrate that agent reasoning capacity is the most critical factor for success, reducing quantitative errors in chemical amounts (nRMSE) by over 85% in complex tasks. When combined with a multi-agent architecture and iterative self-correction, AutoLabs approaches expert-authored reference procedures on the benchmark (F1-score > 0.89) on challenging multi-plate syntheses. These findings establish a clear blueprint for developing robust and trustworthy AI partners for autonomous laboratories, highlighting the synergistic effects of modular design, advanced reasoning, and self-correction to ensure both performance and reliability in high-stakes scientific applications. Code: https://github.com/pnnl/autolabs

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Performance Analysis of PIConGPU: Particle-in-Cell on GPUs using NVIDIA’s NSight Systems and NSight Compute

PIConGPU, Particle In Cell on GPUs, is an open source simulations framework for plasma and laser-plasma physics used to develop advanced particle accelerators for radiation therapy of cancer, high energy physics and photon science. While PIConGPU has been optimized for at least 5 years to run well on NVIDIA GPU-based clusters, there has been limited exploration by the development team of potential scalability bottlenecks using recently updated and new tools including NVIDIA’s NVProf tool and the brand-new NVIDIA NSight Suite (Systems and Compute) tools. PIConGPU is a highly optimized application that runs production jobs at scale on a system Oak Ridge Leadership Facility’s (OLCF) Summit supercomputer (using the full machine at 4600 nodes; at 98% of GPU utilization on all ~28000 NVIDIA Volta GPUs). PIConGPU has been selected as one of the the eight applications for OLCF’s coveted Center for Accelerated Application Readiness (CAAR) program aimed at the facility’s Frontier supercomputer (OLCF’s first exascale system to launch in 2021), to partner with our vendors (primary vendors: AMD and Cray/HPE) ensuring that Frontier will be able to perform large-scale science when it opens to users in 2022. To this effect, performance engineers on the PIConGPU team wanted to dive deep into the application to understand at the finest granularity, which portions of the code could be further optimized to exploit the hardware on Summit at it’s maximum potential and also to elucidate which key kernels should be tracked and optimized for the CAAR effort to port this code to Frontier. Any bottlenecks that are observed via performance profiling on Summit are likely to also impact scalability on the Frontier-dev system and the Frontier Early Access (EA) system. Additionally, the engineers wanted to take a closer look at the newest NVIDIA profiling tools which allows us to identify the most useful features on these tools and will provide an opportunity to compare it to new AMD and Cray’s performance analysis tool releases and provide feedback to our vendor partners on what features are most important and mission critical for CAAR efforts. The primary goal of this report is to focus on the evaluation of PIConGPU’s most time-intensive kernels using NVProf and NSight Suite. Three kernels, Current Deposition (also known as Compute Current), Particle Push (Move and Mark), and Shift Particles are known to be some of the most time-consuming kernels in PIConGPU. The Current xi Deposition kernel and Particle Push kernel both set up the particle attributes for running any physics simulation with PIConGPU, so it is crucial to improve the performance of these two kernels. In this report, we measure single GPU metrics for the three kernels, offer high level takeaways from the conducted analysis, and compare the profiling data from NSight Compute to that of NVProf. This analysis was performed using a grid size of 240 x 272 x 224, and 10 time steps with the Mid-November Figure of Merit (FOM) run setup. The Traveling Wave Electron Acceleration (TWEAC) science case used in this run is a representative science case for PIConGPU. This execution can also be used for baseline analysis on AMD MI50/ MI60 systems. As of the time of writing, the PIConGPU application has limited use for features of NSight Systems, so this report will mainly focus on insights garnered from NSight Compute. For this analysis, we run the “full” metric set available in NSight Compute version 2020.1.2 and use NSight Systems version 2020.3.1 to generate the application timeline.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗