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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

Electric vehicle fast charging infrastructure planning in urban networks considering daily travel and charging behavior

Electric vehicles are a sustainable substitution to conventional vehicles. This work introduces an integrated framework for urban fast charging infrastructure to address the range anxiety issue. A mesoscopic simulation tool is developed to generate trip trajectories, and simulate charging behavior based on various trip attributes. The resulting charging demand is the key input to a mixed-integer nonlinear program that seeks charging station configuration. The model minimizes the total system cost including charging station and charger installation costs, and charging, queuing, and detouring delays. The problem is solved using a decomposition technique incorporating a commercial solver for small networks, and a heuristic algorithm for large-scale networks, in addition to the Golden Section method. The solution quality and significant superiority in the computational efficiency of the decomposition approach are confirmed in comparison with the implicit enumeration approach. Furthermore, the required infrastructure to support urban trips is explored for future market shares and technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Multi-pronged approach to improving carbon utilization by cyanobacterial cultures

The goal of this project was to increase the efficiency of carbon utilization by a Synechocystis biofuel production strain in a photobioreactor system by at least 50% using a multi-pronged approach that combined the best features of both biological and physicochemical CO 2 capture technologies to: 1) increase rates and extent of CO 2 absorption into the culture medium by addition of biocompatible amine solvents and a nanobubble gas delivery system, and 2) increase cellular rates of inorganic carbon uptake and carbon fixation through genetic engineering. In addition, the project plan included evaluating the use of fermentation effluent gases as a CO 2 source and demonstrating performance under outdoor conditions in closed-pond photobioreactor systems. These combined efforts would be guided by integrated technoeconomic and life-cycle analyses. Both physicochemical CO 2 capture technologies explored proved to be successful. The amine solvent monoethanolamine (MEA) was found to be biocompatible with a Synechocystis laurate production strain. Using an adaptive evolution strategy, an MEA-tolerant laurate production strain was developed that showed significantly increased carbon utilization over the parent strain. To our knowledge this was the first time nanobubble (NB) technology had been used as a carbon delivery system for algae production and it also proved quite successful as a proof of concept. Solutions containing CO 2 nanobubbles (Nano-BG11) at concentrations significantly higher than the aqueous CO 2 concentrations achieved with gas sparging were successfully generated and characterized with regard to bubble size (nm), concentration (NB/L), and pH stability as per project plan. Growth studies proved challenging. However, once the source of a puzzling growth defect was found and remedied Synechocystis was able to grow somewhat better in Nano-BG11 than in standard BG11 medium.

09 BIOMASS FUELS↗
DOE OSTI2022

Variation in Proton Craniospinal Irradiation Practice Patterns in the United States: A Pediatric Proton Consortium Registry (PPCR) Study

Craniospinal irradiation (CSI) is commonly used for pediatric brain tumors with a propensity for spread in craniospinal fluid, principally medulloblastoma. Evolving technology has led to the use of highly conformal radiation therapy (RT) techniques for CSI, including proton therapy. Target delineation and plan coverage are critical for CSI, but there is ongoing controversy and variability in these realms, with little available data on practice patterns. We sought to characterize proton CSI practice patterns in the United States by examining CSI plans in the Pediatric Proton/Photon Consortium Registry (PPCR).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Cosmic Muon Veto for the mini-ICAL detector at IICHEP, Madurai

A 51-kiloton magnetised Iron Calorimeter (ICAL) detector, using Resistive Plate Chambers (RPCs) as active detector elements, aims to study atmospheric neutrinos. A prototype - 1/600 of the weight of ICAL, called mini-ICAL was installed in the INO transit campus at Madurai. A modest proof-of-principle cosmic muon veto detector of about 1 m × 1 m × 0.3 m dimensions was setup a few years ago, using scintillator paddles. The measured cosmic muon veto efficiency of 99.98% and simulation studies of muon-induced background events in the ICAL detector surrounded by an efficient veto detector were promising. This led to the idea of constructing a bigger cosmic muon veto around the mini-ICAL detector. Details of the design and construction of the detector including the electronics, trigger and DAQ systems planned will be briefly presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Dark matter detection capabilities of a large multipurpose Liquid Argon Time Projection Chamber

Liquid Argon Time Projection Chambers are planned to comprise a central role in the future of the U.S. High Energy Physics neutrino program. In particular, this detector technology will form the basis for the 40 kton Deep Underground Neutrino Experiment (DUNE) . Here in this paper we take as a starting point the dual phase far detector design proposed by the DUNE experiment and ask what changes are necessary to allow one of the four 10 kt modules to be sensitive to heavy Weakly Interacting Massive Particle (WIMP) dark matter. We show that with control over backgrounds and the use of low radioactivity argon, which may be commercially available on that timescale, along with a significant increase in light detection, one DUNE-like module gives a competitive WIMP detection sensitivity, particularly above a dark matter mass of 100 GeV.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

PV DMFA [SWR-21-105]

The Photovoltaic Dynamic Material Flow Assessment (PV DMFA) model (also referred to here as “The model”) is a computational framework written in Python based on utility-scale PV electricity generation to quantify time-series stocks and flows of PV materials primarily in crystalline silicon PV technologies. The model evaluates cradle-to-cradle life cycle of utility-scale solar PV systems in the United States in the period 2000-2100. PV DMFA serves as a sustainability analysis tool to assess the impacts of different material circularity practices (i.e., reduce, reuse/refurbish, remanufacture, and recycle), PV module design shifts and sensitivity of material processing and technology related parameters to material installations, waste creation and raw material depletion in PV material supply chains. This tool enables advanced planning for future material needs and informs sustainable pathways for PV material management in the circular economy. This tool could be helpful to a wide range of stakeholders; Particularly, researchers and manufacturers looking for technoeconomic and/or environmental life cycle analysis (LCA) feedback for renewable energy (RE) systems.

Khalifa, SherifA.↗
DOE OSTI2020

Qualification and Re-Qualification of NDA Instruments

Non-Destructive Assay (NDA) instruments are a large component of nuclear material (NM) measurement at LANL. Nuclear Material Control and Accountability Group (SAFE-NMCA) personnel in the Safeguards Division are responsible for oversight of the instruments used for material accountability measurements. It is the responsibility of SAFE-NMCA to ensure that all instruments are operating as expected and can produce quality measurements to provide assurance that requirements of the DOE approved NMCA Plan are being met.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Modernizing Fermilab s Control Hardware

Modernizing the Fermilab accelerator control system is essential to future operations of the laboratory's accelerator complex. The existing control system has evolved over four decades and uses hardware that is no longer available. The Accelerator Controls Operations Research Network (ACORN) Project will modernize the control system and replace end-of-life power supplies to enable future accelerator complex operations with megawatt particle beams. The ACORN project is planning to replace Fermilab’s obsolete CAMAC crate-and-card controls hardware with modern MicroTCA hardware. There are over 2,000 CAMAC cards and over 250 CAMAC crates serving various functions in Fermilab’s control system. We will present an overview of the existing CAMAC hardware and the proposed MicroTCA replacement plan.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Leverage modern artificial intelligence (AI) enabled systems for waste reduction

Manufacturing industries continue to face challenges in reducing waste, as upstream strategies such as source reduction and product redesign require a deeper understanding of processes compared to conventional recycling methods. Recent advancements in artificial intelligence (AI) and machine learning (ML) have opened new opportunities to integrate modern computational techniques with traditional waste minimization strategies. This paper explores AI-enabled approaches for product redesign, source reduction, and recycling that can significantly reduce waste generation while improving efficiency and sustainability. AI-driven material substitution and lightweighting in product design enable discovery of novel materials with optimized properties, reducing waste without compromising performance. Reinforcement learning models optimize process parameters, raw material specifications, and machine sequencing to minimize production losses, while Industrial Internet of Things (IIoT) systems paired with AI analytics enhance real-time waste tracking, predictive maintenance, and quality inspection. Furthermore, AI-based demand forecasting and production planning reduce overproduction and excess inventory, as demonstrated in industrial applications. In recycling, ML-powered pattern recognition and robotic sorting technologies achieve higher accuracy in waste segregation, directly improving recycling efficiency. Complementary solutions such as smart bins and AI-enabled waste pickup scheduling optimize collection logistics, reducing both costs and emissions. Although implementation requires upfront investment in infrastructure and training, the long-term benefits include higher material efficiency, reduced waste, improved product quality, and stronger sustainability outcomes across the supply chain. By leveraging AI-enabled systems, manufacturers can align waste minimization efforts with circular economy principles, creating scalable solutions for both industry and society.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Craig Energy Center Feasibility Study

Tri-State Generation and Transmission Association Inc. (“Tri-State”) provides wholesale electric power to its member cooperatives and public power districts that collectively deliver electricity to more than a million consumers in Colorado, Nebraska, New Mexico and Wyoming. The Craig Power Station has been an integral part of Tri-State’s dispatchable generation fleet that ensures an affordable, reliable and resilient energy supply for its members. The ownership of the Craig Station Unit 1&2 is a collaborative between Tri-State, Salt River Project Agricultural Improvement and Power District, Platte River Power Authority, PacifiCorp, and Public Service Company of Colorado and is known as the Yampa Project. Tri-State owns all of Craig Unit 3 and is the operator of all three units. All three of the Craig units have planned retirement dates that will not extend beyond 2028 and Tri-State Generation wanted to evaluate carbon-neutral emitting technologies that could provide approximately 300 megawatts (“MWs) of capacity and energy that will be lost after Unit 3 ceases operation, as well as provide a similar level of economic benefits to the Craig community. This report is to serve as a technology feasibility study constrained to the current land area available at the Craig site and was conducted based on the limitations of the region.

25 ENERGY STORAGE↗
DOE OSTI2023

Modeling Systems’ Disruption and Social Acceptance—A Proof-of-Concept Leveraging Reinforcement Learning

As the need for a just and equitable energy transition accelerates, disruptive clean energy technologies are becoming more visible to the public. Clean energy technologies, such as solar photovoltaics and wind power, can substantially contribute to a more sustainable world and have been around for decades. However, the fast pace at which they are projected to be deployed in the United States (US) and the world poses numerous technical and nontechnical challenges, such as in terms of their integration into the electricity grid, public opposition and competition for land use. For instance, as more land-based wind turbines are built across the US, contention risks may become more acute. This article presents a methodology based on reinforcement learning (RL) that minimizes contention risks and maximizes renewable energy production during siting decisions. As a proof-of-concept, the methodology is tested on a case study of wind turbine siting in Illinois during the 2022–2035 period. Results show that using RL halves potential delays due to contention compared to a random decision process. This approach could be further developed to study the acceptance of offshore wind projects or other clean energy technologies.

17 WIND ENERGY↗
DOE OSTI2026

Integrating Data Centers and Grid Technologies at Scale

This presentation focuses on the challenge of integrating AI-driven data centers with the power grid at scale. It examines the AI data center capacity challenge and the role of new Medium Voltage Direct Current (MVDC) and other grid-enhancing technologies in enabling efficient and reliable power delivery. The session will highlight the National Laboratory of the Rockies' ARIES capabilities and planning tools, along with collaborative examples involving Verrus, Compass, and Schneider through the Agora test bed for grid-friendly data center evaluations, and ON. Energy for UPS evaluation. It will showcase the NLR Stable Grid Platform for studying oscillations caused by large-scale data centers, along with planning tools to assess grid security and reliability. Additionally, the presentation covers reconductoring strategies to increase grid capacity and explores innovative data center architectures, including the Advanced DC Architectures with Power-electronic Transformers (ADAPT) platform, which enables testing of complete DC architectures for data centers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

BETO 2021 Peer Review - Feasibility Study of Utilizing Electricity to Produce Intermediates from CO2 and Biomass

Capturing and converting CO2 generated from bioethanol facilities into valuable products, leveraging renewable electricity as the primary energy input, could increase overall biorefinery carbon utilization by as much as 40% and provide a means to decarbonize fuels and chemicals production. However, significant uncertainty exists around the costs, carbon intensity, risks, and technical challenges associated with electron-driven CO2 reduction. Thus, the overarching objective of this project is to guide existing and future research and development efforts by addressing these knowledge gaps for utilizing renewable electricity and CO2 to improve biorefinery economics and carbon utilization. By September 2023, this project will develop and publish a comprehensive design report for the integration of CO2 utilization into two existing conceptual biorefinery designs, which will include conceptual process models, pioneer and nth plant economics, identification and quantification of technological risks, and projections for future cost reductions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Sustainable, Net-Zero Carbon Steelmaking Utilizing Nuclear and Renewable-based Integrated Energy Systems

Decarbonizing Steelmaking: Emissions Background Industrial processes (including power) account for 28% of global CO2 emissions dominated by steel, cement, NH3, ethylene. Steel accounts for 7% of global CO2 emissions (25% of Industrial), 2-3 Gigatonnes annually. Given long asset life and large investments in steel industry, recommend: Detailed analysis, materials R&D and pre-pilot technology integration required by 2030 to position U.S. industry for an investment decision for building first net-zero integrated steel plan Symposium site: https://www.aiche.org/cei/conferences/competitive-energy-systems/2021

08 HYDROGEN↗
DOE OSTI2022

A Co-Simulation Framework to Study Future Energy-Economy Interactions

Energy-economy interactions are often studied using top-down integrated assessment or economy models that have broad scope but lack the resolution and process detail to consider complex emerging trends across the energy sector. This presentation describes an approach to maintain both detail and scope by linking NREL's highly resolved models of the electricity, transportation, and buildings sectors with a MIT's USREP computable general equilibrium model of the U.S. economy. We will discuss strategies for linking across disparate models along with preliminary results describing the economy-wide impacts of future energy technology innovation.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

FORCE Development Status Update: Vertical Integration and Benchmarking of System Dynamics

Recent efforts to establish effective models for grid energy analysis, especially given the increase in variable renewable energy (VRE) sources and the economic challenges faced by traditional nuclear energy, have generated new technological considerations. One effort to improve the economic viability of nuclear power involves investigating integrated energy systems (IES) which include secondary energy systems that introduce flexibility and secondary market possibilities to existing and perceived future nuclear energy generation technologies. To analyze the technical and economic potential of IES, the Framework for Optimization of Resources and Economics (FORCE) tool suite was developed through a collaboration among national laboratories. Within the FORCE tool suite, the Holistic Energy Resource Optimization Network (HERON) provides algorithms for analyzing the long-term viability of potential IES technologies, while HYBRID provides algorithms and models to achieve high-resolution analysis of coupling physics over a short time period. Continued maturing of the FORCE tool suite requires further interconnections between the various tools in the suite in order to ensure consistent analysis. Analyses performed by applying HYBRID to transient process modeling should be easily harvestable as inputs to HERON analyses. The first item in this status update is a demonstration of an automated data pipeline for loading data from HYBRID into HERON analyses. Application of HYBRID results to HERON, as part of using the FORCE tool suite, relies on robust modeling assumptions for the various models included in HYBRID. The second result of this status update is the benchmarking and validation of cost and operational data, with a particular focus on natural gas energy generators. These generators are benchmarked with a focus on contrasting them with proposed thermal energy storage (TES) technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Invite the Chaos Monkey: Test Effect Payloads for Tuning ICS Incident Response

In 2010, when Netflix moved their operational systems to the cloud, they developed a pseudo-random mechanism to cause deliberate outages and failures of key system elements to ensure that automated systems for detecting and remediating outages were mature and fully functional. This Chaos Monkey spawned an entire Simian Army designed to ensure system resilience and enable failure response before issues became outages. Through the DARPA RADICS program, Provatech, INL, and other researchers have developed a mechanism for creating controllable failures via Test Effect Payloads (TEPs) for Industrial Control Systems in order to enable an asset owner to tune network and process sensor technology, increase the effectiveness of incident response and remediation, and highlight areas where resilient technology could bring benefit to Operational Technology. This talk will explore what a TEP is, how to create a TEP, and suggest what a systematic system resilience plan using TEP’s might look like. We will also discuss how regulated entities might employ TEP’s in a compliant resilience strategy.

42 ENGINEERING↗
DOE OSTI2025

Scaling the Offshore Wind Industry and Optimizing Turbine Size

NYSERDA's Offshore Wind team is hosting an educational webinar series to connect the public with independent experts in key topics in offshore wind, including wind farm technologies, development practices, regulatory processes, and research initiatives. The presentation focuses on the challenges and opportunities of wind turbine upscaling in the global offshore wind market place. It addresses key concerns about risks of new technology and the opportunity cost of increasing turbine size too rapidly.

ENERGY PLANNING, POLICY, AND ECONOMY,WIND ENERGY↗