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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Assessing the impacts of air-sealing on the sizing, operation, and economic feasibility of ground-source heat pumps for electrifying single-family houses in the US

According to recent studies and reports, in single-family houses (SFHs), air-sealing can significantly lower the thermal loads for space heating and cooling. Thus, air-sealing in SFHs could reduce the required size and cost of ground source heat pump (GSHP) systems for electrifying SFHs. Here, this study investigated the costs and benefits of integrating air-sealing with GSHPs for retrofitting existing SFHs when compared with air-source heat pumps. A whole building energy simulation tool integrated with an advanced design tool for modeling ground heat exchangers was used to calculate changes in required GSHP capacity, total borehole length, and building energy consumption with and without air-sealing in SFHs in 16 US climatic regions. The results from this study showed that reducing outdoor air infiltration from 0.8 air changes per hour (ACH) to the minimum ventilation requirement (0.35 ACH) can significantly reduce borehole length (up to 55 %), GSHP capacity (up to 48 %), and total heating electricity reduction, especially in cold climates (up to 44 %). The results also showed that for airtight homes (0.03 ACH infiltration) with a direct outdoor air system, the minimum required borehole length, GSHP capacity, and total heating electricity consumption can be reduced up to 70 %, 68 %, and 67 %, respectively, when compared with SFHs with 0.8 ACH infiltration. Moreover, the life cycle cost analysis showed that air-sealing in conjunction with a GSHP is more profitable than replacing the existing system with an air-source heat pump, even without any incentives for most climatic regions in the US (except for some hot regions).

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Accelerating multilevel Markov Chain Monte Carlo using machine learning models

Here, this work presents an efficient approach for accelerating multilevel Markov Chain Monte Carlo (MCMC) sampling for large-scale problems using low-fidelity machine learning models. While conventional techniques for large-scale Bayesian inference often substitute computationally expensive high-fidelity models with machine learning models, thereby introducing approximation errors, our approach offers a computationally efficient alternative by augmenting high-fidelity models with low-fidelity ones within a hierarchical framework. The multilevel approach utilizes the low-fidelity machine learning model (MLM) for inexpensive evaluation of proposed samples thereby improving the acceptance of samples by the high-fidelity model. The hierarchy in our multilevel algorithm is derived from geometric multigrid hierarchy. We utilize an MLM to accelerate the coarse level sampling. Training machine learning model for the coarsest level significantly reduces the computational cost associated with generating training data and training the model. We present an MCMC algorithm to accelerate the coarsest level sampling using MLM and account for the approximation error introduced. We provide theoretical proofs of detailed balance and demonstrate that our multilevel approach constitutes a consistent MCMC algorithm. Additionally, we derive the expression for cost reduction due to machine learning model to facilitate cost analysis of the hierarchical sampling algorithm. Our technique is demonstrated on a standard benchmark inference problem in groundwater flow, where we estimate the probability density of a quantity of interest using a four-level MCMC algorithm. Our proposed algorithm accelerates multilevel sampling by a factor of two while achieving similar accuracy compared to sampling using the standard multilevel algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Defining the 50-Year Module: Luck, Design, or Both?

Poster presenting a new Duramat project that will develop a science-based definition of a "50-year solar panel" by combining reliability data, climate risks, design choices, and long-term cost analysis. The work aims to clarify what is needed to enable longer-lasting, high-value solar systems.

14 SOLAR ENERGY↗
DOE OSTI2026

Comparison of ammonia with methanol, liquefied natural gas and conventional marine transportation fuels through life cycle cost and emissions analysis

This work evaluates ammonia as a potential marine fuel for a SUEZMAX tanker and compares it with methanol, liquefied natural gas, and conventional fuel oils. The motivation arises from the need to identify low-emission, cost-competitive fuel options that can reduce greenhouse gas emissions from international shipping. The central hypothesis is that ammonia produced from renewable energy sources can achieve lower well-to-wake greenhouse gas emissions with varying life cycle costs based on the region. Life cycle assessment and techno-economic analysis were performed for a thirty-year vessel lifetime on two representative trade routes: from Saudi Arabia to Japan and from Saudi Arabia to the Netherlands. Four ammonia production pathways were assessed: natural gas, natural gas with carbon capture, natural gas pyrolysis, and renewable electricity–based synthesis. Results show that wind-based ammonia produced in Saudi Arabia achieved the lowest life cycle well-to-wake greenhouse gas emissions, between 0.58 and 0.64 million metric tons, among all fuels when using regional grid process electricity. With renewable process electricity, ammonia produced from natural gas pyrolysis in Saudi Arabia showed comparable emissions of 0.37 to 0.44 million metric tons with wind-based ammonia of 0.37 to 0.43 million metric tons. Liquefied natural gas exhibited the lowest life cycle cost, between 402 and 412 million United States dollars, and the only negative carbon abatement cost, ranging from −277 to –322 United States dollars per metric ton of greenhouse gas, compared with high sulfur fuel oil. The findings indicate that renewable ammonia offers a promising long-term pathway for reducing shipping emissions, while liquefied natural gas remains the most cost-effective option in the near term.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Western Interconnection Baseline Study

The purpose of the baseline study is to evaluate the degree to which current industry planning processes meet the national 2035 decarbonization goals for the Western Interconnection. This analysis serves as a comparative baseline for the scenario analysis conducted in the NTP Study using a Western Interconnection dataset that is readily available to industry. This baseline analysis differs from the production cost modeling analysis and power flow analysis in the main NTP Study report (forthcoming). In particular, the analysis presented in this report reflects a business-as-usual future with an optimistic build out of specific planned transmission projects and foreseeable generation. In contrast, the NTP Study models a future generation and transmission expansion based on optimization from a capacity expansion model. The analysis presented herein also reflects a 2030 timeframe, whereas the main NTP Study production cost modeling analysis and power flow analysis reflect a 2035 time frame. This baseline analysis utilizes industry’s most reliable data to account for future transmission projects across various stages of development, with a particular focus on those in the permitting stage. Additionally, it incorporates projections for changes in generation capacity (both additions and retirements). This baseline analysis outlines a probable trajectory, given current process and practice, for the future of the bulk power system with a horizon extending to 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Low-cost calculation and analysis of 2D IR spectra of model diiron trinitrosyl complexes in the NO stretch region with vibrational perturbation theory

Two-dimensional infrared spectroscopy offers unique capabilities for probing vibrational coupling in complex metal–ligand systems. In this paper, we combine two-dimensional infrared spectroscopy with vibrational perturbation theory to investigate vibrational coupling in a diiron trinitrosyl complex across three stable redox states. Although these systems are challenging for electronic structure methods, we demonstrate that key features of experimental 2D IR spectra can be accurately reproduced using reduced-dimensional anharmonic calculations with a small harmonic frequency scaling. Analysis reveals that N–O stretching modes maintain high locality across all redox states, with coupling patterns that directly reflect variations in Fe–N bond strength. Using curvilinear coordinate analysis, we demonstrate these differences result from systematic changes in cubic anharmonic force constants rather than mode delocalization. Our results establish N–O stretches as sensitive probes of metal–ligand bonding strength, expanding the toolkit for studying biologically relevant nitrosyl complexes.

Moran, Hayden A. [Texas A&M University, College St↗
DOE OSTI2025

A Scalable Solution for Grid Optimization and DER Integration (CRADA Final Report)

Utilidata Inc. is an energy software company that provides clean energy and digital solutions for utilities. This work was the result of Utilidata Inc. being awarded a New York State Energy Research and Development Agency award to integrate Utilidata volt-VAR optimization (VVO) software with smart inverters to explore enhanced voltage control. This project was conducted in partnership with Utilidata Inc., National Grid, the New York State Energy and Research Development Authority, and the National Renewable Energy Laboratory (NREL). As part of the project NREL conducted modeling and simulation analysis, developed cost-benefit analysis framework, and conducted laboratory testing to understand the potential for smart inverter integration to a centralized VVO control scheme. The remainder of the report provides an executive summary of the work, an introduction to the challenges, sections detailing specific aspects of the work, and the overall findings and conclusions.

14 SOLAR ENERGY↗
DOE OSTI2024

HyBlend: Pipeline CRADA Cost and Emissions Analysis

This presentation provides an overview of National Renewable Energy Laboratory and Argonne National Laboratory research as part of the pipeline blending CRADA (a HyBlend project) to the DOE's 2024 Annual Merit Review.

BlendPATH↗
DOE OSTI2026

Uncertainty Quantification and Sensitivity Analysis of Nuclear Construction Cost Reduction Pathways

High construction costs have plagued recent nuclear projects and they hamper the widespread deployment of nuclear technology. The Nuclear Cost Reduction Tool is a plant economic framework that quantifies the impact that various plant design and construction attributes have on construction costs and cost overruns and shows the positive effects of learning over a series of deployments. However, a downside of the current model is that all model outputs and capabilities are deterministic. To provide a more comprehensive view, this study evaluated the impact of model parameter uncertainty through a sensitivity analysis applied to 18 model parameters. This approach quantified the impact of model uncertainty on the output variables of Net Overnight Capital Cost (Net OCC), Construction Duration (CD), and Levelized Cost of Electricity (LCOE). Monte Carlo analysis revealed uncertainty distributions for these variables, showing that absolute uncertainty decreases over a series of deployments. A local sensitivity analysis showed that even small parameter perturbations (5%) can have a significant impact on project execution, highlighting areas that could reduce costs by billions across an order book of plants. The results of this study have improved the understanding of the model and identified the most impactful model parameters and construction attributes.

Levelized Cost of Electricity↗
DOE OSTI2026

Value of Geothermal Energy Storage for Supply-Side and Demand-Side Applications

This report presents the results of a study examining the value potential for geothermal energy storage (GES), a long-duration energy storage resource that stores thermal and/or geomechanical energy in the subsurface. GES could benefit the overall U.S. power system by temporally shifting electricity generation (supply-side) or meeting building heating and cooling load (demand-side). This report analyzes supply-side and demand-side opportunities independently because of differences in applications and models. Currently there is significant uncertainty about the development costs for GES, with only a limited number of demonstration plants for electric energy storage and building heating and cooling storage developments. In this report, we estimate the value of supply-side and demand-side GES to the bulk power system in the contiguous United States. Because of the significant uncertainty about GES development costs, this analysis does not consider GES deployment costs but instead focuses on the value of GES to the U.S. electricity system. The estimated values of GES provide reference points for economically competitive commercial cost targets. Supply-side GES is modeled as part of an enhanced geothermal system (EGS) generation plant in NREL's Regional Energy Deployment System (ReEDS) capacity expansion model (Ho et al. 2021). In contrast to conventional geothermal plants, which generate constant power, EGS plants have unique features that may allow for in-reservoir energy storage for flexible generation. Demand-side GES for heating and cooling, including seasonal hot and cold storage and short-duration heat pump storage, is incorporated into a price-taker model using Cambium electricity marginal cost projections. To establish an upper bound for the value of GES, analysis focused on favorable scenarios for storage with high generation from zero marginal cost, variable renewable energy resources. High penetrations of variable renewable energy generation can increase hourly electricity price variability, which increases the value of temporal energy arbitrage for storage technologies like GES.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Leveraging NREL's ResStock & ComStock Dataset to Evaluate Building Stock Electrification: Preprint

Residential and commercial buildings accounted for 40% of U.S. energy consumption in 2022 and represent a significant opportunity for decarbonization through energy efficiency and electrification, and for grid planning. Building stock energy modeling is a powerful tool that can evaluate what-if scenarios as utilities, municipalities, policymakers, building owners and others work towards equitable building decarbonization and climate goals. This presentation will highlight several high-impact use cases of the National Renewable Energy Laboratory (NREL)'s highly granular, bottom-up building stock energy modeling tools, ResStock and ComStock. These use cases cover a wide range of project scale, from neighborhood electrification analysis and municipality long-term energy planning, to state energy code development and national policy evaluation. This presentation will showcase specific real-world applications for which ResStock and ComStock have been utilized across the country, including California codes and standards cost-effectiveness analysis, New York City affordable housing electrification cost gap analysis, and California targeted electrification and gas decommissioning analysis. For each use case, this presentation will illustrate how ResStock and ComStock played a crucial role in accurately characterizing regional building stocks, providing discrete and aggregated end-use load shapes, and calculating lifecycle consumption, emissions, and costs for a variety of building electrification strategies and scenarios. Finally, this presentation will demonstrate how the data provided by ResStock and ComStock can help unlock significant outcomes for these use cases, including but not limited to, customer bill impact, incentive and program design, and energy equity analyses.

building stock modeling↗
DOE OSTI2024

A Reduced-form Cost Model for Prefeasibility Analysis of Hydropower at Non-Powered Dams

This study presents a reduced-form model to support a better understanding of the capacity potential and drivers of costs for hydropower development at U.S. non-powered dams (NPD), which are existing dams that are not currently used for hydropower. With information on nineteen reference sites, a set of reduced-form design and cost equations were estimated to enable rapid assessments of aggregate costs and their components for a large number of NPD sites. The model was then applied to 36,000+ potential U.S. NPD sites using the limited data commonly available. Although the cost estimates span a wide range, there exists a significant amount of U.S. NPD hydropower capacity potential, which are considered cost-competitive in the current market using baseline technologies.

13 HYDRO ENERGY↗
DOE OSTI2024

Complete resolution across the neodymium/samarium isotopic envelope with a liquid sampling‐atmospheric pressure glow discharge — Orbitrap mass spectrometer

Rationale Nd and Sm isotope ratios play an important role in geological dating and as nuclear forensic signatures; however, the overlap of the respective 144, 148, 150 Nd/Sm isobars requires prior separations to be performed before analysis on typical MS platforms. The work presented here overcomes these isobaric interferences using ultrahigh‐mass resolution to alleviate interference without prior chemical separations. Methods A liquid sampling‐atmospheric pressure glow discharge ion source was coupled to a standard, QExactive Focus Orbitrap mass spectrometer, providing a mass resolution of ~80 k. A Spectroswiss FTMS booster X2 data acquisition package was used to collect extended transients, providing much higher mass resolution; ~230 k and ~600 k are employed here for Nd and Sm isotopes. Results While the standard Orbitrap resolution is far greater than typical “atomic” MS platforms, it was insufficient to alleviate all isobars. The use of a resolution of ~230 k resulted in baseline separation across the entire isotopic envelope for both Nd and Sm. Isotope ratios obtained from Nd:Sm mixtures using high‐resolution were equivalent to those found for individual‐element solutions, while isotope ratios obtained at a resolution of ~80 k (standard for the OEM data system) showed large deviations. Conclusions Use of ultrahigh‐resolution is an attractive alternative to extensive chemical separations to alleviate severe isobaric interferences. Sufficient mass resolution greatly reduces/eliminates the need for sample manipulations (separations) before analysis while reducing costs and total analysis times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

AL-CRADA-2025-01 Final Report: American-Made Wind Turbine Materials Recycling Prize Accelerate! Phase 2

This report summarizes the Phase 2 achievements of the Wind Turbine Materials Recycling Prize project led by Critical Materials Recycling (CMR) in partnership with Ames National Laboratory. The team demonstrated the technical feasibility and economic viability of recovering and reusing rare-earth Nd-Fe-B magnets from end-of-life (EOL) wind turbine generators. Through mechanical disassembly, demagnetization, and precision processing, magnets were harvested and characterized to assess structural, compositional, and magnetic properties. Results showed that recovered magnets performed on par with commercial-grade counterparts, enabling their integration into actuator and motor prototypes without redesign. System-level modeling and finite-element simulations validated operational performance, while Life Cycle Cost (LCC) analysis revealed up to 20% material cost savings and 2–3% reductions in overall motor system costs. Life Cycle Assessment (LCA) further confirmed substantial environmental benefits, including a ~94% reduction in global warming potential relative to virgin magnet production. The project’s success was enabled by a tightly integrated partnership between industry and national lab experts, illustrating a viable path for domestic magnet-to-magnet recycling. These findings support a scalable, circular solution for rare-earth material recovery, reducing dependence on imported critical minerals and advancing sustainable clean energy technologies.

Lograsso, Thomas [Ames Laboratory (AMES), Ames, IA↗
DOE OSTI2025

Evaluating Acoustic vs. AI-Based Satellite Leak Detection in Aging US Water Infrastructure: A Cost and Energy Savings Analysis

The aging water distribution system in the United States, constructed mainly during the 1970s with some pipes dating back 125 years, is experiencing significant deterioration leading to substantial water losses. Along with the potential for water loss savings, improvements in the distribution system by using leak detection technologies can create net energy and cost savings. In this work, a new framework has been presented to calculate the economic level of leakage within water supply and distribution systems for two primary leak detection technologies (acoustic vs. satellite). In this work, a new framework is presented to calculate the economic level of leakage (ELL) within water supply and distribution systems to support smart infrastructure in smart cities. A case study focused using water audit data from Atlanta, Georgia, compared the costs of two leak mitigation technologies: conventional acoustic leak detection and artificial intelligence–assisted satellite leak detection technology, which employs machine learning algorithms to identify potential leak signatures from satellite imagery. The ELL results revealed that conducting one survey would be optimum for an acoustic survey, whereas the method suggested that it would be expensive to utilize satellite-based leak detection technology. However, results for cumulative financial analysis over a 3-year period for both technologies revealed both to be economically favorable with conventional acoustic leak detection technology generating higher net economic benefits of USD 2.4 million, surpassing satellite detection by 50%. A broader national analysis was conducted to explore the potential benefits of US water infrastructure mirroring the exemplary conditions of Germany and The Netherlands. Achieving similar infrastructure leakage index (ILI) values could result in annual cost savings of $\$4$–$\$4.8$ billion and primary energy savings of 1.6–1.9 TWh. These results demonstrate the value of combining economic modeling with advanced leak detection technologies to support sustainable, cost-efficient water infrastructure strategies in urban environments, contributing to more sustainable smart living outcomes.

acoustic leak detection↗
DOE OSTI2024

FECM/NETL CO2 Saline Storage Cost Model CO2_S_COM 2024 (v4)

The U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM), in collaboration with the National Energy Technology Laboratory (NETL), has developed the FECM/NETL CO2 Saline Storage Cost Model (CO2_S_COM). This Excel-based tool provides a comprehensive framework for estimating the costs and breakeven prices associated with storing carbon dioxide (CO2) in deep saline formations. Designed from the perspective of a CO2 storage site owner, the CO2_S_COM incorporates four integrated modules—project management, financial analysis, activity cost estimation, and geological evaluation—to deliver fast, robust and actionable insights for screening project finances.

CO2 storage↗
DOE OSTI2024

Carbon Capture, Transport, And Storage (CTS) Cost Modeling Of The Onshore Gulf Coast

The onshore Gulf of Mexico region presents significant opportunities for CO2 capture, transport, and storage due to its numerous CO2 sources, such as power plants, refineries, and its substantial CO2 storage potential. However, operators face critical decisions in designing an efficient and cost-effective CO2 pipeline network. This study examines the economic implications of two primary strategies: constructing a trunkline with excess initial capacity versus developing dedicated pipelines incrementally as new CO2 sources come online. Building a trunkline first offers the advantage of future-proofing the network, allowing for the accommodation of increased CO2 volumes from various sources over time. However, this approach incurs higher upfront costs and risks underutilizing the transport capacity in the initial stages, potentially resulting in economic inefficiencies. Conversely, constructing dedicated pipelines for each new CO2 source as it becomes operational may avoid the initial overcapacity issue but fails to capitalize on the economies of scale. This could lead to higher overall costs due to the duplication of infrastructure and increased complexity in network management. This research employs a comprehensive cost-benefit analysis, integrating factors such as capital expenditure, operational costs, projected CO2 volumes, and potential economies of scale. Through this analysis, we aim to provide operators with insights into the most economically viable strategy for CO2 pipeline network design in the region. The findings underscore the importance of strategic planning and highlight the trade-offs between immediate capacity utilization and long-term cost savings, ultimately guiding stakeholders towards informed decision-making in the development of CO2 transport infrastructure. Presented at the 41st USAEE/IAEE North American Conference, 3-6 November 2024, Baton Rouge, LA, United States.

Shih, Chung Yan↗