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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Techno-economic design of a linear Fresnel reflector for industrial process heat

A techno-economic model of a Concentrating Solar Thermal (CST) system using a Linear Fresnel Reflector (LFR) has been developed. LFRs can deliver process heat suitable for a range of industries, including food and beverage production. This model uses an adaptive algorithm to calculate the optimal secondary reflector shape given the geometry and optical properties of the rest of the system. A ray-tracing program is used to calculate optical efficiency over a wide range of longitudinal and transversal incidence angles and subsequently evaluate the annual efficiency at a given geographical location. A specific LFR design developed by Hyperlight Energy was modelled, and this industrial partner provided a detailed cost breakdown which was used as the basis of an economic model. Combining the technical and economic data facilitates the calculation of the Levelized Cost of Heat (LCOH). The influence of a number of parameters on the annual efficiency and LCOH is explored; notable parameters include the absorber height, the number, width, and spacing of the primary mirrors, the aim point, and the secondary reflector shape and width. By identifying an optimal combination of these parameters, we reduce the LCOH of the industry partner’s system design by 9.2%, from 14.4 $\$/MWh_{th}$ to 13.0 $\$/MWh_{th}$. In comparison, the LCOH of a natural gas boiler delivering the same annual quantity of heat is 29 $\$/MWh_{th}$, which indicates that LFRs can be a competitive heat source for industrial processes.

14 SOLAR ENERGY↗
DOE OSTI2023

Techno-Economic Analysis and Market Potential of Geological Thermal Energy Storage (GeoTES) Charged With Solar Thermal and Heat Pumps into Depleted Oil/Gas Reservoirs and Shallow Reservoirs: A Technology Overview: Preprint

Depleted oil/gas reservoirs represent a waste of underground resources and investments of drilling, and also a potential risk to the earth's environment. Geologic thermal energy storage (GeoTES) is proposed as a solution to convert depleted oil/gas reservoirs into long-term seasonal energy storage. GeoTES can be hybridized with other techniques for viable commercial deployment, such as 1) concentrating solar power (CSP) collectors and 2) heat pumps with excess renewable energy. Here, a technology overview is given on the two GeoTES technologies, which includes system overview, techno-economic models, and case study. Both GeoTES technologies show great potential in the economics of individual project deployment and applicability across the US.

concentrating solar power↗
DOE OSTI2020

Assessing the Additional Carbon Savings with Biofuel

A recent study claims that corn used for ethanol should not be considered to be inherently biogenically carbon-neutral because not all that corn was grown additional to the level otherwise. By assessing the extent of carbon neutrality of corn for ethanol using the reference point baseline approach and historical data that study concluded that the carbon intensity of US corn ethanol is 27% higher than that of gasoline. We develop a framework to determine the carbon neutrality of corn for ethanol by assessing the additional carbon uptake by crops using an anticipated baseline approach. We also apply this framework to determine the additional corn produced for ethanol and include the direct life cycle carbon emissions of only that portion of corn in the direct life cycle carbon intensity of corn ethanol. We implement this framework by integrating an economic model of the agricultural sector in the USA with a biogenic carbon model and life cycle analysis to quantify biogenic carbon uptake and direct life cycle emissions with and without corn ethanol expansion over the 2007–2027 period. We find that the combined biogenic carbon emissions and direct life cycle carbon emission intensity of corn ethanol (not including indirect land use related emissions) is 21% lower than gasoline. In conclusion, the lower value of this carbon intensity of corn ethanol compared with gasoline is robust to a wide range of parametric assumptions.

09 BIOMASS FUELS↗
DOE OSTI2025

Singlet-doublet dark matter revisited

The singlet-doublet model is an economical model of weakly interacting dark matter. We revisit it in light of improved dark matter direct detection limits. We characterize the now well-defined regions of remaining parameter space with suppressed direct detection cross sections and discuss features of the spectrum accessible at the Large Hadron Collider. We discuss when and how parameters in these special regions might be realized as the result of renormalization group evolution when starting with generic ultraviolet initial conditions.

Particle dark matter↗
NASA NTRS1998

The Aviation System Analysis Capability Airport Capacity and Delay Models

The ASAC Airport Capacity Model and the ASAC Airport Delay Model support analyses of technologies addressing airport capacity. NASA's Aviation System Analysis Capability (ASAC) Airport Capacity Model estimates the capacity of an airport as a function of weather, Federal Aviation Administration (FAA) procedures, traffic characteristics, and the level of technology available. Airport capacity is presented as a Pareto frontier of arrivals per hour versus departures per hour. The ASAC Airport Delay Model allows the user to estimate the minutes of arrival delay for an airport, given its (weather dependent) capacity. Historical weather observations and demand patterns are provided by ASAC as inputs to the delay model. The ASAC economic models can translate a reduction in delay minutes into benefit dollars.

Lee, David A.↗
NASA NTRS2008

The Supercritical Pile Model: Prompt Emission Across the Electromagnetic Spectrum

The "Supercritical Pile" GRB model is an economical model that provides the dissipation necessary to convert explosively the energy stored in relativistic protons in the blast wave of a GRB into radiation; at the same time it produces spectra whose luminosity peaks at ~1 MeV in the lab frame, the result of the kinematics of the proton-photon - pair production reaction that effects the conversion of proton energy to radiation. We outline the fundamental notions behind the "Supercritical Pile" model and discuss the resulting spectra of the prompt emission from optical to gamma-ray energies of order Gamma^2 m_ec^2, (Gamma is the Lorentz factor of the blast wave) present even in the absence of an accelerated particle distribution and compare our results to bursts that cover this entire energy range. Particular emphasis is given on the emission at the GLAST energy range both in the prompt and the afterglow stages of the burst.

Kazanas, Demos↗
DOE OSTI2026

Carbon dioxide pipeline network transportation cost model: evaluating economic and geographic factors for efficient carbon capture, storage, and utilization

This study presents a comprehensive pipeline network modeling framework to estimate the CO 2 delivery cost for CO 2 utilization and geologic CO 2 storage across the United States. We developed a Python-based CO 2 pipeline transportation cost model leveraging Argonne National Laboratory’s pipeline engineering expertise and detailed natural gas transmission pipeline cost data across U.S. regions. Using existing road corridors as practical routing guides, the model designs pipeline networks that aggregate CO 2 from one or multiple sources and deliver it to selected destinations. It then minimizes the total transportation cost by optimizing pipeline diameters and incorporating booster pumps. A key contribution is the incorporation of up-to-date, region-specific cost factors with itemized components for materials, labor, miscellaneous construction expenses, and right-of-way acquisition. Results emphasize that regional variation and economies of scale associated with CO 2 pipeline costs are significant and should be explicitly accounted for in screening and planning studies. By combining realistic routing constraints with regionalized cost inputs, the model provides transparent design methodology and location-specific insights into source–destination delivery costs, including the effects of routing complexity along existing road networks. We demonstrate the model with two illustrative case studies – one for CO 2 storage and one for CO 2 utilization – in which the model designs pipeline networks spanning hundreds of miles across the states, collecting CO 2 from multiple sources and delivering it to designated endpoints while minimizing levelized cost of delivery via diameter and compression optimization. The model offers a practical, scalable approach for alternative design option screening and early-stage CO 2 transportation planning.

CCS↗
NASA NTRS1974

The economic impact of remote sensing data as the source of nonpoint pollution monitoring and control

Nonpoint pollution of streams with sediment as a result of runoff from alternative uses of land has become a socially unacceptable product of economic activity. This report describes a research approach to economically achieve correction of the nonpoint pollution problem. The research approach integrates the economic model with those data which may be obtainable from remotely sensed sources. The economic problem involves measurement of the direct benefits and costs associated with the changes in land management activities necessary to reduce the level of nonpoint pollution. Remotely sensed data from ERTS-1 may provide some of the information required for the economic model which indicates efficient solutions to the nonpoint pollution problem. Three classes of data (i.e., soil categories, vegetative cover, and water turbidity) have the potential to be measured by ERTS-1 systems. There is substantial research which indicates the ability of ERTS-1 to measure these classes of data under selected conditions.

Miller, W. L.↗
DOE OSTI2022

Integrated Heat Pump Thermal Storage and Power Cycle for CSP (Final Technical Report)

Pumped thermal energy storage (PTES) is a storage system that stores electricity in thermal reservoirs. In this project, methods of integrating PTES with concentrating solar power (CSP) systems were investigated and their feasibility evaluated. Hybrid "solar-PTES" devices can provide both flexible renewable power generation as well as a variety of electricity storage services. Techno-economic models of PTES and solar-PTES were developed and used to assess their performance, cost, and commercial viability. Systems were optimized using multi-objective optimization techniques. The value that these storage devices provide to the grid was estimated using production cost modelling. Key advances made in this project include the development of detailed techno-economic models that improve state-of-the-art assessments of these technologies. Off-design models were developed and used in grid-analysis models. This work describes for the first time how PTES and solar-PTES behave over a range of operating points and assesses the value that these systems can provide to the electrical grid. Feedback was obtained from experts in the field, which clarified key technological and economic barriers that must be addressed to improve the feasibility of these devices.

14 SOLAR ENERGY↗
NASA NTRS2019

A Crop Yield Change Emulator for Use in GCAM and Similar Models: Persephone v1.0

Future changes in Earth system state will impact agricultural yields and, through these changed yields, can have profound impacts on the global economy. Global gridded crop models estimate the influence of these Earth system changes on future crop yields but are often too computationally intensive to dynamically couple into global multisector economic models, such as the Global Change Assessment Model (GCAM) and other similar-in-scale models. Yet, generalizing a faster site-specific crop model’s results to be used globally will introduce inaccuracies, and the question of which model to use is unclear given the wide variation in yield response across crop models. To examine the feedback loop among socioeconomics, Earth system changes, and crop yield changes, rapidly generated yield responses with some quantification of crop response uncertainty are desirable. The Persephone v1.0 response functions presented in this work are based on the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Climate-Crop Modeling Project (C3MP) sensitivity test data set and are focused on providing GCAM and similar models with a tractable number of rapid to evaluate dynamic yield response functions corresponding to a range of the yield response sensitivities seen in the C3MP data set. With the Persephone response functions, a new variety of agricultural impact experiments will be open to GCAM and other economic models: for example, examining the economic impacts of a multi-year drought in a key agricultural region and how economic changes in response to the drought can, in turn, impact the drought.

Snyder, Abigail↗
DOE OSTI2026

A Systematic Review and Integrated Approach to Modeling of Aging Utility Scale PV Systems

The growing deployment of utility-scale photovoltaic (PV) systems has increased the importance of techno-economic modeling operational photovoltaic (PV) systems for predicting energy yield, optimizing asset management, and informing financial decisions. Through a systematic review of literature and current industry practices, we review the different common modeling practices of a system's configuration and age, performance and degradation, operation and maintenance (O&M), while also focusing on specific considerations for repowering, revamping, and decommissioning. Building on the synthesis, we develop a structured framework for techno-economic modeling of operating PV systems that integrate performance and degradation analysis, a decommissioning and repowering cost model that estimates the system's end-of-life costs to reduce uncertainty quantifications and improve consistency across the sector. This research contributes to improved modeling methodologies and potentially to reduced financial performance requirements by providing practitioners with input resources and practical approaches to estimate performance, degradation, and costs associated with continued operation, revamping, repowering, or decommissioning decisions.

14 SOLAR ENERGY↗
DOE OSTI2022

Modeling the Economic and Environmental Impacts of Land Scarcity Under Deep Uncertainty

Abstract Land scarcity is increasing over time, driven by complex multisector dynamics. The impacts of land scarcity on the economy and environment are multi‐faceted and regional, so any action to convert land will contain inherent tradeoffs. These impacts are complicated by the deeply uncertain evolution of the various sectors influencing land scarcity. A need therefore exists to provide multi‐metric and multi‐sector assessments that are robust to myriad uncertainties. Land conservation effectively limits the supply of productive land, while biofuel consumption increases the demand and competition for that land, and how these dynamics individually and jointly propagate to economic and environmental impacts is an important open question. To address this, we adopt the Global Change Analysis Model (GCAM) that has representations of various important systems including the climate, macroeconomic, energy, agriculture and land, and water resources systems. Various scenarios of increased land demand (from biofuels) and decreased land supply (from conservation) under various socioeconomic scenarios drawn from the SSPs were simulated using GCAM. We find that while biofuel consumption and land conservation reduce carbon emissions, this comes at the cost of higher food prices, reduced crop production, and increased water withdrawals. Additionally, some regions experience these tradeoffs more severely than others and are more heavily impacted from the same biofuel mandate or by an additional percent of protected land. These and other findings highlight the importance of multisector modeling frameworks that capture many cross‐sector linkages, and acknowledge the important uncertainties confronting the human‐Earth system when making any analysis of land scarcity impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Comparative Analysis of HEATNETS for Geothermal Network Performance

Thermal energy networks (TENs), also known as 5th generation district energy systems, or more specifically geothermal networks when exchanging heat with geothermal boreholes, are an important technology for decarbonization. In these networks an ambient loop connects buildings and thermal sources, such as a borehole field, to exchange energy and maintain a desired loop temperature. Water-source heat pumps are used at the buildings to connect to the ambient or thermal loop to meet to the building heating and cooling loads and maintain comfort. A semi-transient, reduced-order technical model and techno-economic model, called HEATNETS, has been developed at NREL that captures the flow of energy around a TEN. In this work, a comparison of the HEATNETS technical model and a well-known coding platform used for modeling geothermal networks, TRNSYS, has been completed for a proposed geothermal network as a verification and validation process. Hourly data provided from the TRNSYS simulation included building loads, pumping power, heat pump power, temperature entering and leaving the borehole field, and mass flow rates. The hourly borehole temperatures were used to create a linear regression model utilized in HEATNETS to estimate the borehole field heat exchange. The building loads and mass flow rates were direct inputs to HEATNETS while the pumping power, heat pump power, borehole temperatures, and coefficients of performance were all simulated and calculated by HEATNETS, allowing for direct comparison of the thermal energy transfer HEATNETS considers the full process from design inputs to economic outputs and can provide modeling options for high-level initial system design and operational optimization. This study focuses on a validation of HEATNETS using results from TRNSYS. HEATNETS is not intended to replace other modeling tools, but this work demonstrates, via a comparison with an industry standard code, that HEATNETS can be a unique, high-level and rapid modeling tool for estimating the performance of a full geothermal network system.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Comparative Analysis of HEATNETS for Geothermal Network Performance: Preprint

Thermal energy networks (TENs), also known as 5th generation district energy systems, or more specifically geothermal networks when exchanging heat with geothermal boreholes, are an important technology for decarbonization. In these networks an ambient loop connects buildings and thermal sources, such as a borehole field, to exchange energy and maintain a desired loop temperature. Water-source heat pumps are used at the buildings to connect to the ambient or thermal loop to meet to the building heating and cooling loads and maintain comfort. A semi-transient, reduced-order technical model and techno-economic model, called HEATNETS, has been developed at NREL that captures the flow of energy around a TEN. In this work, a comparison of the HEATNETS technical model and a well-known coding platform used for modeling geothermal networks, TRNSYS, has been completed for a proposed geothermal network as a verification process. Hourly data provided from the TRNSYS simulation included building loads, pumping power, heat pump power, temperature entering and leaving the borehole field, and mass flow rates. The hourly borehole temperatures were used to create a linear regression model utilized in HEATNETS to estimate the borehole field heat exchange. The building loads and mass flow rates were direct inputs to HEATNETS while the pumping power, heat pump power, borehole temperatures, and coefficients of performance were all simulated and calculated by HEATNETS, allowing for direct comparison of the thermal energy transfer, rather than also comparing control systems responses. HEATNETS considers the full process from design inputs to economic outputs and can provide modeling options for high-level initial system design and operational optimization. This study shows that HEATNETS, while not intended to replace other modeling tools, can be a unique modeling tool for the performance of a full geothermal network system.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Bundling measures for food systems transformation: a global, multimodel assessment

Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.

Sundiang, Marina [Cornell Univ., Ithaca, NY (Unite↗
NASA NTRS2015

Perspectives on Climate Effects on Agriculture: The International Efforts of AgMIP in Sub-Saharan Africa

Agriculture in Sub-Saharan Africa (SSA) is experiencing climate change-related effects that call for integrated regional assessments, yet capacity for these assessments has been low. The Agricultural Model Intercomparison and Improvement Project (AgMIP) is advancing research on integrated regional assessments of climate change that include climate, crop, and economic modeling and analysis. Through AgMIP, regional integrated assessments are increasingly gaining momentum in SSA, and multi-institutional regional research teams (RRTs) centered in East, West, and Southern· Africa are generating new information on climate change impacts and adaptation in selected agricultural systems. The research in Africa is organized into four RRTs and a coordination team. Each of the RRTs in SSA is composed of scientists from the Consultative Group of International Agricultural Research (CGIAR) institutions, National Agriculture Research institutes (NARs), and universities consisting of experts in crop and economic modeling, climate, and information technology. Stakeholder involvement to inform specific agricultural systems to be evaluated, key outputs, and the representative agricultural pathways (RAPs), is undertaken at two levels: regional and national, in order to contribute to decision making at these levels. Capacity building for integrated assessment (lA) is a key component that is undertaken continuously through interaction with experts in regional and SSA-wide workshops, and through joint creation of tools. Many students and research affiliates have been identified and entrained as part of capacity building in IA. Bi-monthly updates on scholarly publications in climate change in Africa also serve as a vehicle for knowledge-sharing. With 60 scientists already trained and actively engaged in IA and over 80 getting monthly briefs on the latest information on climate change, a climate-informed community of experts is gradually taking shape in SSA. (See Part 2, Appendices 3-5 in this volume for AgMIP Regional Workshop reports.)

Kihara, Job↗
DOE OSTI2025

Core design and performance of the Westinghouse lead fast reactor with UO 2 and MOX configurations

For this work, Westinghouse partnered with Argonne National Laboratory to design, model and optimize UO 2 - and MOX-fueled core designs for a medium size (950 MWt) Lead Fast Reactor that was pursued by Westinghouse. Using Argonne’s suite of reactor analysis codes together with Westinghouse fuel cost economic models, thousands of candidate cores were considered to achieve the economics-optimized cores presented in this paper. This optimization process considered detailed reactor physics, fuel performance, transient performance, and fuel economics models. The reactor performance of the resulting optimized UO 2 - and MOX-fueled core designs are described and compared in this paper. Both cores show fuel performance and transient behavior that is considered acceptable for the optimization presented herein, while further testing campaigns on material performance in high-temperature liquid lead will be required to confirm acceptability at the operating conditions chosen. A multi-batch strategy was selected for the UO 2 core for best fuel utilization with minimum fuel inventory costs. A single-batch fuel management was instead selected for the MOX core to maximize cycle length and minimize the impact of the longer refueling outage resulting from the higher decay heat of the discharged MOX fuel relative to the discharged UO 2 fuel, requiring a longer cooling time before dry-lift of discharged fuel could take place.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗