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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Offshore Advanced Infrastructure Integrity Model (AIIM) Dashboard

The Advanced Infrastructure Integrity Model (AIIM) is a multivariate, multi-machine learning modeling technology applied to evaluate the integrity of offshore energy infrastructure (e.g., pipelines, platforms) in the U.S Gulf Region. Offshore energy infrastructure plays an essential role in ensuring access to safe and secure energy for the United States. According to the U.S. Energy Information Administration (EIA), production in the U.S. Gulf Region accounts for 15% of total crude and 5% of total natural gas from the United States. Many of these structures have been operating for close to or past their design life, while others have the chance of attrition before return on investment. To better understand the potential for reuse or life extension opportunities, an assessment of the infrastructure integrity is critical to inform safe decision making. Assessing structural integrity, AIIM provides key insights that inform infrastructure use and reuse, as well as hazard prevention planning, in support of stakeholders including researchers and industry.

Advanced Infrastructure Integrity Model↗
DOE OSTI2025

Life-cycle greenhouse gas emissions analysis of battery-grade lithium production in Finland

Various countries are undertaking initiatives to domestically produce battery-related critical materials. Within Finland, Keliber Technology Oy is developing capabilities for battery-grade lithium hydroxide monohydrate (LHM) production from spodumene ores. A detailed life-cycle assessment (LCA) of this pathway is conducted to determine its life-cycle GHG impacts using Argonne's R&D GREET (Research and Development Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model. The analysis shows life-cycle GHG emissions of similar to 9.2 kg CO 2-eq /kg LHM, dominated by contributions from three energy sources - diesel, natural gas, and electricity - and two material inputs - lime (CaO) and soda ash (Na 2 CO 3 ). Sensitivity analyses highlight the potential to reduce these impacts using low-carbon electricity, sequestration of process CO 2 emissions generated during CaO and Na 2 CO 3 production, and bio-based energy for LHM production (by similar to 15 % each). A comparative analysis shows lower impacts for Keliber's LHM than for existing LHM production from Australian spodumene ores processed in China (by similar to 40 %).

CCS↗
DOE OSTI2025

Life-cycle analysis of microalgae-based polyurethane foams

Polyurethane plastics are essential in many consumer and commercial products such as insulation, furniture, automotive interiors, and clothing. Pathways for producing polyurethane from microalgae offer an opportunity to reduce greenhouse gas emissions and other environmental impacts and can incorporate processes that avoid the use of toxic isocyanates typically used in conventional polyurethane production processes. In this study, the greenhouse gas emissions, fossil energy, and water consumption of biobased polyurethane and biobased non-isocyanate polyurethane were evaluated via life-cycle analysis using the R&D Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies model. Microalgae-based polyurethane foam was found to achieve greenhouse gas emission reductions of up to 79% compared with conventional polyurethane foam production. The greenhouse gas reductions for the non-isocyanate microalgae polyurethane pathway are slightly lower at 58% compared with conventional polyurethane foam. However, it offers additional benefits by reducing toxicity potential compared to the isocyanate polyurethane pathway. The analysis also included a biorefinery-level analysis to evaluate the impact of incorporating polyurethane production into fuel-processing microalgae biorefineries. The sensitivity analyses conducted in this study reveal that improved algae cultivation strategies can lead to decreases of up to 127% and 80% in GHG emissions from the baseline process of Bio-PU and Bio-NIPU, respectively. Likewise, implementation of renewable electricity can result in up to 128% and 74% lower GHG emissions compared to the baseline production of Bio-PU and Bio-NIPU, respectively. Finally, the analysis evaluated different coproduct handling methods including displacement and allocation (based on mass, energy, and market-value). The results suggest that it is important to consider both the displacement and allocation methods as these led to significant differences in the environmental impacts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Life‐cycle greenhouse gas emissions associated with nuclear power generation in the United States

Under the 2022 Inflation Reduction Act, tax credits of up to $3/kgH 2 are available to hydrogen producers if they generate emissions at levels below 0.45 kgCO 2 e/kgH 2 , spurring producers to explore how hydrogen production via electrolysis using electricity generated by nuclear power may qualify for such tax credits. With uranium as a primary fuel for nuclear power plants (NPPs) and no on-site emissions, the upstream emissions associated with nuclear fuel supply chains largely determine the carbon intensity of nuclear energy. Using the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model, we evaluated the life-cycle greenhouse gas (GHG) emissions of uranium production and the use of uranium to generate electricity in light water reactor (LWR) NPPs. We evaluated the process chemicals and energy inputs throughout the nuclear fuel supply chain to identify the major contributors to nuclear fuel cycle GHG emissions. Such emissions are estimated at 3.0 gCO 2 e/kWh at NPPs in the United States. The greatest share of nuclear fuel cycle GHG emissions—comprising 53% of total emissions—are associated with electricity consumption throughout the fuel supply chain. We extended the analysis to include an evaluation of the carbon intensity of H 2 production via electrolysis using nuclear power from LWRs. Finally, we examined the impact of future (2035 and 2050) electricity supply chain scenarios on nuclear fuel cycle GHG emissions. Our analysis revealed a decrease of 33% (2035) and 46% (2050) in the carbon intensity of nuclear electricity relative to current nuclear fuel cycle GHG emissions.

greenhouse gas emissions↗
DOE OSTI2021

Task Parallelism to Optimize Performance of Environmental Modeling Software

Climate modeling is an integral part of environmental research, from studying rare phenomena to predicting future climate trends. The need for more accurate models is only growing, but as climate modeling capabilities advance, existing workflows require optimization to recoup performance. A solution comes in the form of task parallelism, a novel programming capability that provides an opportunity for optimization at execution time by allowing tasks to be executed in parallel, reducing runtime significantly. Using Parsl, an intuitive and scalable parallel scripting library for Python, we implement task parallelism within support software to aid in the continuous advancement of climate modeling technology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Life-Cycle Inventory of Critical Materials: Nickel, Copper, Titanium, and Rare-Earth Elements

The United States has developed a list of critical minerals/materials whose sustained and reliable supply is pivotal to the robust functioning of critical industrial sectors. A key concern with these minerals is their environmental effects as a function of their production location. This requires material and energy flow details for their processing steps. This report provides a life-cycle inventory (LCI) for producing four critical minerals and/or material systems (nickel, copper, titanium, and rare-earth elements) incorporated in the updated GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model. For these systems, we provide an LCI as a function of production location – domestic (within the United States) and international (geographies from where the US imports these minerals). Our LCI also considers variations in ore grades for nickel and copper. This report also provides an LCI for all intermediate materials used to produce these critical materials.

58 GEOSCIENCES↗
DOE OSTI2024

End-Use Savings Shapes Measure Documentation: Advanced Rooftop Unit Control

This technical report documents the Advanced Rooftop Unit Control End Use Savings Shapes (EUSS) measure, including providing a description of the technology, modeling methods, and the energy savings calculated from applying the measure to applicable across the US commercial building stock using ComStock to quantify its potential. Advanced rooftop unit controls (ARC) generally consist of a supply fan VFD, and controls to implement demand controlled ventilation (DCV) and air-side economizing, as a retrofit to improve energy efficiency of existing rooftop units (RTUs).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Educational Consortium for Energy-related Data Science & Computation in Building Engineering Programs

The project spearheaded by Pennsylvania State University aims to address the growing need for integrating energy-focused computation and data science into building engineering education. As the demand for energy-efficient building designs and operations increases, the educational sector must adapt to equip future engineers with the necessary skills. This initiative responds to this need by developing a consortium that unites multiple institutions to enhance curriculum development, dataset curation, and resource sharing, thereby ensuring students are well-prepared for the evolving energy sector. The primary goal of the project is to establish a consortium that will develop and disseminate educational materials and training programs focused on energy-related data science and computation. Key accomplishments include the creation of a beta website for resource sharing, the development of training programs and standalone modules, and the curation of datasets accessible to the public. This effort will culminate in a curriculum that incorporates advanced modeling technologies and data science skills into building engineering programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Stability Analysis of Power Systems with High Penetration of State-of-the-Art Inverter Technologies

With the increasing level of inverter-based resources (IBRs) in modern power systems, this paper presents a small-signal stability analysis for power systems comprising synchronous generators (SGs) and IBRs. Four types of inverter controls are considered: two grid-following (GFL) controls, with or without grid support functions; droop-based grid-forming (GFM) controls; and virtual oscillator control-based GFM. We also analyze the impact of STATCOM and synchronous condensers on system stability to assess their role in the energy mix transition. With the small-signal dynamic behavior of the major technologies modeled, this paper provides stringent stability assessments using the IEEE 39-bus benchmark system modified to simulate future power systems. The exhaustive test cases allow for (a) assessing the impacts of different types and controls of generation and supplementary grid assets, as well as system inertia and line impedance on grid stability, and (b) elucidating pathways for the stabilization of IBR-dominated power systems. The analysis also indicates that future power systems can be stabilized with only a fraction of the total generation as voltage sources without SGs or significant system inertia if they are well distributed. This study provides insights into future power system operations with a high level of IBRs that can also be used for planning and operation studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Digital fabrication of a small diameter polymer optical waveguide

A novel polymer optical waveguide and method of manufacturing is presented herein. A digitally manufactured process is described which utilizes a micro-dispensed UV optical adhesive as the contour guiding cladding, a fused deposition modeling technology for creating a core, and a subtractive laser process to finish the two ends of the optical interconnect. The optical waveguide can be printed directly on a circuit board in some embodiments. Alternatively, using a slightly modified process including a step to bond the optical fiber to the substrate, the optical interconnect can be manufactured on a flexible substrate.

Bhethanabotla, Venkat Rama↗
DOE OSTI2022

A solar energy desalination analysis tool, sedat, with data and models for selecting technologies and regions

Abstract There is interest for desalination technologies powered by solar energy as arid areas are typically bestowed with good solar potential. In response to a US DOE call for solar desalination analysis tools, we developed an open-source solar energy desalination analysis tool, sedat , for techno-economical evaluation of desalination technologies and selection of regions with the highest potential for using solar energy to power desalination plants. It is expected that this software will simplify the planning, design, and valuation of solar desalination systems in the U.S. and worldwide. Sedat uses Dash for integrating various layers of large volumes of GIS data with Python-based models of solar energy generation and desalination technologies. It derives time-series of energy generation and water production, with details of plant performance and suggestions for improving the solar-desalination coupling. This paper summarizes the various phases of the tool’s development, presents example results showing the potential, under multiple objectives, of solar desalination in parts of the U.S. southwest, and discusses method details that would be useful for future model development.

14 SOLAR ENERGY↗
DOE OSTI2024

CIGS Technology Advancement via Fundamental Modeling of Defect/Impurity Interactions (Final Technical Report)

The primary goals of the proposed work were to provide modeling tools (and the associated insight which comes along with model development) for design and optimization of CuIn x Ga 1-x Se 2 (CIGS) and CdSeTe (CST) solar cell manufacturing processes and to establish the foundation for comprehensive end-to-end predictive modeling tools to enable optimization of thin film photovoltaic technology for performance, cost, yield, and reliability. The initial focus of efforts within this project was to develop coupled process/optical/device models for CIGS PV technology and to work with Siva Power to apply that TCAD (technology computer-aided design) system to improve the efficiency and reduce manufacturing costs for CIGS solar cells. Our approach to that end was to generate an extensive database of DFT calculations and to use those calculations via statistical thermodynamics methods and Monte Carlo simulation to develop and characterize models for the behavior of native defects as well as intentional and unintentional impurities, including the redistribution of the primary components of CIGS films. Increased effort went toward coupling those models for defect behavior and composition evolution to the performance of multicrystalline CIGS solar cells via prediction of doping level and recombination lifetime as function of manufacturing process. In the second budget period, the project pivoted to developing a similar system for the CdSeTe system, focused especially on understanding the role of Se/Te alloy concentration. Execution of the project resulted in the successful development of TCAD systems for both CIGS and CdSeTe thin film PV within the Synopsys Sentaurus framework by utilizing the Alagator interface. In the first budget period of the project, we developed quantitative models for the major components of CIGS PV and implemented them within a framework that couples process, optical, and device simulation. From the insights we have gained, we identified novel opportunities for enhancing CIGS solar cell performance and have laid the groundwork to further optimize the layer structure, composition profile, and thermal cycles for substantially improved efficiency and lower manufacturing costs. For the CIGS system, process changes to achieve greater than 1% absolute enhancement in efficiency were identified, but testing of those approaches was stymied by lack of a domestic CIGS manufacturing partner after the closure of Siva Power as well as Miasole. For CdSeTe, a fully capable TCAD system only became ready to apply near the end of the project period, so substantial opportunities remain to apply those models to enhance the leading thin film PV technology.

14 SOLAR ENERGY↗
DOE OSTI2020

Innovations in Building Energy Modeling: Research and Development Opportunities for Emerging Technologies

Building energy modeling (BEM) is a multipurpose tool for building energy efficiency (EE). The U.S. Department of Energy Building Technologies Office (BTO) seeks to expand the use and effectiveness of BEM in the design and operation of commercial and residential buildings with the goal of achieving lasting reductions in total and peak energy use. This report identifies gaps and outlines recommended initiatives to achieve this goal, based on a combination of technical analysis and stakeholder input. In addition to BTO, this report can benefit BEM professionals (architects, mechanical engineers, energy consultants, building auditors, equipment manufacturers, and BEM software vendors) and BEM clients (building owners and operators, EE program administrators, EE service providers, policymakers, and policy and code jurisdictions such as states and cities). This report was developed in two phases. In the first, BTO worked with a team from Navigant Consulting (now Guidehouse) to characterize objectives, opportunities, and current activities; identify gaps and barriers; and define initiatives. To collect input, Navigant conducted telephone interviews and workshops with industry experts. The initial phase produced a draft report, which was released for public review in 2016 and yielded over 400 comments. Based on these comments, BTO compiled a second draft report that addressed many of those comments while acknowledging changes that had occurred both at BTO and in the industry. Unlike the first draft report, the second focused much more heavily on BTO’s own role, portfolio, and activities. BTO is a direct player in the BEM field - it funds the development of several significant software packages that are embedded in commercial products - and transparency about its goals and future plans is requisite. BTO recognizes that a great number of other public and private organizations contribute to the BEM enterprise. With the second draft report, BTO did not attempt to produce a blueprint for the industry as a whole, but rather a working document BTO can use to iteratively solicit stakeholder input and synthesize it into a program. BTO released the second draft report for public review in 2019. The second round of review generated 83 pages of feedback and comments - almost exactly the length of the draft report itself - a significant portion of which was collected and synthesized by IBPSA-USA Advocacy Committee. This final report incorporates this feedback. This report does not address the use of BEM in support of building-based grid services, a recent BTO initiative called Grid-interactive Efficient Buildings (GEB). In 2019, BTO published a report that specifically addresses the role of BEM - and other “integration” technologies - in GEB.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

TEMPEST (Thermo-Electric Model for Powering Energy Storage Technologies)

NREL's TEMPEST model combines electrical and thermal modeling for residential-scale battery systems. The model and default parameters are based off of two common commercial residential batteries. Key inputs to the model include house load, temperature of the battery location, and the solar profile. The key output of the TEMPEST model is the battery profile and internal battery temperature. If internal battery temperature exceeds limits, a derating will occur and this will be reflected in the battery profile. In addition to thermal modeling, the TEMPEST model uses realistic operating principals that are common in today's residential batteries. Mainly, the TEMPEST model incorporates "modes" of operation that constrain battery setpoint based on house load, solar output, and state of charge. The TEMPEST model can be used to analyze the effect of battery temperature, deratings, and mode setpoints on utility network loading and customer bills.

Blonsky, Michael↗
DOE OSTI2023

Core Model Proposal #359: Hydrogen and Transportation Technology Update

This core model proposal updates modeling structures, key technology assumptions, and data sources for a detailed representation of hydrogen in GCAM’s energy system, including production, transmission and distribution, and consumption in hydrogen end-use sectors (buildings, transportation, industry).

08 HYDROGEN↗
DOE OSTI2020

Methods for R&D Portfolio Analysis and Evaluation (Workshop Report)

The Workshop on Methods for R&D Portfolio Analysis and Evaluation convened on 17–18 July 2019 at the National Renewable Energy Laboratory in Golden, Colorado, and examined strengths and weaknesses of the various methodologies applicable to R&D portfolio modeling, analysis, and decision support, given pragmatic constraints such as data availability, uncertainties in estimating the impact of R&D spending, and practical operational overheads. Participants employed their deep expertise in approaches such as stochastic optimization, real options, Monte-Carlo analysis, Bayesian networks, decision theory, complex systems analysis, deep uncertainty, and technology-evolution modeling to critique the initial example models developed by the project’s core team and to conduct thought experiments grounded in real-life technology models, progress data, expert elicitation, and portfolio information. This engagement of participants’ methodological expertise with the practical requirements of real-life portfolio decision support yielded ideas for improved approaches, alternative methodological hypotheses, and hybridization of methodologies that are well-grounded theoretically, computationally sound, and realistically executable given data availability and other practical constraints.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗