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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-burnup boiling water reactor steady-state operating conditions and fuel performance analysis

The primary operational costs for existing nuclear reactors are plant operation costs, maintenance costs, and fuel costs, all of which are influenced by the materials used and the design of the reactor core. Optimizing core design parameters—including burnup limits and enrichment levels—can lengthen cycles, reduce outages, reduce reload batch fractions and spent fuel storage requirements, and lower maintenance and operating expenses, thereby enhancing economic viability. Furthermore, developing higher-fidelity tools to simulate these parameters enables better identification of the available margin, improves overall plant safety, and improves the understanding a given plant’s responses to accident scenarios. Here, in the US, much of the research and development focus has traditionally been on pressurized water reactors (PWRs), but boiling water reactors (BWRs) comprise approximately one-third of the US reactor fleet. Modeling and simulation advances for BWRs and PWRs—particularly those achieved through the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program—are crucial to the long-term viability of the light–water reactor industry. A key research area of the high burnup and increased enriched fuel initiative is focused on addressing issues related to postulated loss-of-coolant accident (LOCA) scenarios. NEAMS has dedicated significant effort to enhancing tools to better support BWRs. A current focus is showcasing the BWR framework for high-burnup LOCA analysis. This high-fidelity steady-state analysis is a first step toward demonstrating a best-estimate, pin-by-pin high-burnup BWR LOCA analysis to assess full-core cladding rupture behavior for a representative BWR. The objective of this effort is to provide a modeling capability that will help elucidate and provide a best-estimate evaluation for cladding rupture susceptibility in BWRs. This modeling capability could then be used to prevent and/or mitigate cladding ruptures in postulated accident scenarios without penalizing operational parameters. Additionally, the results of this work will help identify strategies for finding additional margins or potentially limiting cladding ruptures through core design optimizations to enable more efficient core designs.

Capps, Nathan [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2025

Preliminary studies on diversion and misuse for TRISO-fueled heat-pipe-cooled microreactors

Microreactors are being developed by multiple reactor designers to mass-produce nuclear facilities for worldwide deployment. Including microreactors in a country’s energy portfolio introduces new concerns for international safeguards regarding the number of reactor locations. Microreactors have smaller quantities of nuclear material compared to current light-water reactors, which makes diverting enough material for clandestine purposes difficult for a single reactor. Diversion or misuse of multiple microreactors to obtain a significant quantity introduces a new acquisition pathway. This work examines diversion and misuse scenarios for a realistic heat-pipe-cooled microreactor to understand how these scenarios would effect reactor operations to determine if monitoring key parameters could reduce the burden of inspection on monitoring agencies. Here, we determined misuse caused too drastic of an effect on core operations to be a valid acquisition pathway for the realistic heat-pipe-cooled microreactor. Diversion was explored across varying levels of severity, where potential diversion scenarios could yield one significant quantity of material from between six and eleven microreactors. Through examining the critical control drum angle, excess reactivity, control drum worth, and power distribution changes from nominal were detected over the operational lifetime, which could indicate a divergence from normal operations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Nationwide HVAC Energy-Saving Potential Quantification for Office Buildings with Occupant-Centric Controls in Various Climates

The occupant-centric control (OCC) is receiving an increasing attention due to its ability to reduce building heating ventilation and air-conditioning (HVAC) system energy consumptions while not affecting the occupant thermal comfort. This paper aims to investigate and quantify the nationwide energy-saving potential of implementing the occupant-centric HVAC controls in typical office buildings using a whole building simulation software EnergyPlus. First, the medium office and large office from the Department of Energy (DOE) Commercial Prototype Building Models (CBPM) were enhanced to have detailed layouts and dynamic occupancy schedules. Then, a comprehensive simulation plan was created by incorporating the multiple zone-level and system-level occupant-centric building HVAC controls recommended by the updated ASHRAE Standard 90.1 – 2019 and ASHRAE Guideline 36 – 2018. Three control scenarios with different occupancy sensing methods were identified in this simulation plan. A nation-wide parametric analysis which includes two building types, three occupancy sensing scenarios, two building code versions, and 16 U.S. climate zones was carried out. The simulation results of the key control variables and HVAC energy consumption suggest that generally, both the occupancy presence sensor and occupant counting sensor could achieve energy savings for the office buildings in majority of the scenarios. However, compared with the occupancy presence sensor, which could support both the temperature setpoint reset and operational breathing zone airflow rate reset for the unoccupied zones, the occupant counting sensor only brings a marginal benefit. Besides, a higher HVAC energy-saving ratio could be achieved in the heating-dominated zone, since the energy reduction brought with the minimum outdoor airflow rate reset is stronger in the heating mode.

Pang, Zhihong↗
DOE OSTI2020

Assessing geothermal/solar hybridization – Integrating a solar thermal topping cycle into a geothermal bottoming cycle with energy storage

Geothermal and concentrating solar power (CSP) technologies typically use heat at different temperatures in their commercial deployments. This enables a technically viable hybridization of a solar topping cycle and a geothermal bottoming cycle at locations where both resources are available. In this article, an underperforming geothermal power system based at Burley, Idaho is used as a baseline to investigate the technical and economic potential of such a hybrid cycle. A direct thermal energy storage (TES) system is also integrated to overcome the intermittency of the solar resource. Design and off-design behavior of key components are modelled to simulate the annual performance of the hybrid system on an hourly basis. The sizing of the solar field and thermal storage is investigated and is seen to significantly impact the annual electricity generation and efficiency. Various cost scenarios for the solar field and thermal energy storage are investigated. An economic metric - levelized cost of electricity (LCOE) - is used to optimize the solar field sizing and TES capacity. The hybrid plant converts the additional solar heat input into additional work with an efficiency of 32.9%. Retrofitting a geothermal plant with solar and eight hours of energy storage can achieve an LCOE of 0.136 $/kWhe in current cost scenarios and 0.081 $/kWhe in a future cost reduction scenario. Although the hybrid system cannot directly compete with current PV systems without batteries, it has an LCOE 32% lower than that of a PV-battery system. This paper provides insights into the research and development of the future grid with a high renewable energy penetration and encourages further study of energy hybridization for improved efficiencies and economics.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Quantifying health benefits of sustainable aviation fuels: Modeling decreased ultrafine particle emissions and associated impacts on communities near the Seattle-Tacoma International Airport

Exposure to ultrafine particles (UFP, ≤100 nm) is an emerging health concern linked to premature mortality, with jet fuel combustion identified as a significant source of UFPs near airports. Sustainable aviation fuel (SAF) adoption has the potential to reduce aviation-related UFPs and may particularly benefit populations who reside nearby. However, assessing aviation-specific impacts on health remains challenging due to the lack of tools capable of addressing: fine-scale exposure evaluation, novel ambient pollutants, and groups with increased exposure or susceptibility. We develop and apply a method to estimate reductions in mortality associated with aviation-related UFP reductions at the Seattle-Tacoma (SEA-TAC) International Airport under SAF adoption scenarios, with a focus on near-airport communities. Using UFP exposure surfaces generated from AERMOD modeling, flight count data, and UFP measurements, we evaluated UFP reductions under various control scenarios. We estimated mortality reductions by combining this with population data, baseline mortality, and a hazard ratio of 1.012 (95 % confidence interval: 1.010, 1.015) per interquartile range increment of 2723 particles/cm 3 . Our analysis included 412 census tracts representing almost 1.5 million adults. Baseline aviation-related UFP exposures averaged 1145 (SD: 277) particles/cm 3 . The highest baseline concentrations and subsequent reductions under SAF scenarios were near SEA-TAC. Mortality case reductions averaged between 3.1 (95 % range: 2.5–3.7) for a 5 % UFP reduction to 31.0 (24.6–37.4) for a 50 % reduction, with corresponding mortality rate reductions of 0.2 (0.2–0.3) to 2.1 (1.7–2.5) cases per 100,000 people per year. Mortality rate reductions were larger among populations residing closer to SEA-TAC, including those that were Hispanic or Latino, below-poverty, and did not identify as White. Reducing aviation-related UFPs through SAF adoption could lead to lower mortality, particularly in near-airport communities. This reproducible approach can be adapted to other settings to evaluate health benefits from aviation-related UFP reductions.

Aviation-related air pollution↗
DOE OSTI2021

Global Biodiversity Implications of Alternative Electrification Strategies Under the Shared Socioeconomic Pathways

Addressing climate mitigation while meeting global electrification goals will require major transitions from fossil-fuel dependence to large-scale renewable energy deployment. However, renewables require significant land assets per unit energy and could come at high cost to ecosystems, creating potential conflicts between global climate mitigation and biodiversity conservation. Here, we explore the potential biodiversity implications of alternative future global electrification pathways as depicted under the Shared Socioeconomic Scenarios (SSPs), i.e., alternative trends in societal development. We examined the intersection of high-resolution estimates of global energy densities for ten renewable and conventional technologies with global richness data to estimate technology-specific biodiversity footprints (species per GWh), whereas a Cumulative Biodiversity Impact (CBI) score was used to assess land and biodiversity outcomes of alternative scenarios. Downscaled electricity generation scenarios (2020-2100) were also constrained by alternative land conservation and energy development policies. Unexpectedly, variation among SSPs did not exhibit a clear tradeoff between global climate mitigation and CBI. Rather, CBIs were an outcome of total infrastructure development to meet electricity demand (from population growth and GDP) and the total magnitude of renewable energy development and storage technologies. Renewables assembled along a spectrum from land sharing to sparing. At the land sharing end, biomass-powered electricity from dedicated crops contributed the most to biodiversity impacts due to low energy density, whereas land-sparing technologies (solar) caused more-intense land degradation, but in smaller areas. Our results suggest that local land conservation practices and strategies promoting energy diversification could have greater implications for future biodiversity conflicts than global socioeconomic drivers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Techno-economic analysis and life cycle analysis of renewable natural gas production from brewery wastewater via ex-situ methanation processes

As sustainability becomes increasingly critical, the brewing industry encounters challenges in managing high-organic-content wastewater, a promising renewable energy source. This study evaluates the economic feasibility and environmental impacts of converting brewery wastewater into renewable natural gas (RNG) through anaerobic digestion and biogas upgrading, with an emphasis on different hydrogen sources for biomethanation. Four scenarios were analyzed: Scenario 1 uses purchased hydrogen, while Scenarios 2–4 use renewable hydrogen from microbial electrolysis cells and water electrolyzers. Results show that capital investments for processing 139 MT/h of wastewater, yielding 208 m 3 /h of RNG, range from 10.6 M to 31.9M USD, with estimated minimum selling prices of RNG between 2.25 and 4.37 USD/m 3 . Life cycle greenhouse gas (GHG) emissions span from -21 to 32g CO 2 -equivalent per MJ of RNG. Further, this study presents key economic and environmental metrics for RNG production from brewery wastewater, offering insights to enhance sustainability in brewery wastewater management.

03 NATURAL GAS↗
DOE OSTI2023

Techno-economic assessment and life cycle assessment of three potential pathways for biomass liquefaction

Biomass liquefaction can enhance corn-stover slurry transportation by reducing yield stress and overall viscosity, easing biomass handling, especially for slurries at high solids loading (≥30 % (w/v). Implementing a liquefaction process at the front-end of the biorefinery could reduce downtime caused by equipment fouling. Furthermore, liquefaction reduces process complexity by transforming high fiber mass into a pumpable slurry. Three scenarios for liquefaction of corn stover pellets: enzyme process, enzyme mimetic process, and a combined process of enzyme and enzyme mimetic were assessed. The ideal process will have the best performance-to-cost ratio, with minimal impact on the environment. Techno-economic and life-cycle analyses were used to understand the economic and environmental effects of the three liquefaction scenarios and to determine if one or more can achieve cost parity. Here, results show that the enzyme process had the best performance in terms of cost and emissions (gCO 2 -equivalent/kg slurry)compared to the other scenarios.

09 BIOMASS FUELS↗
DOE OSTI2021

Long-term carbon emission reduction potential of building retrofits with dynamically changing electricity emission factors

Buildings account for approximately 36% of the United States' total carbon emissions and building retrofits have great potential to reduce carbon emissions. Current research adopts a constant electricity emission factor although it changes over time due to the increase of renewable energy generation. Here, to accurately predict emission reduction potential of building retrofits, this study develops a novel method by using dynamically changing electricity emission factors. Using medium office buildings as an example, we predicted emission reduction of eight building retrofit measures from 2020 to 2050 in five locations in the U.S. with distinct climates and renewable adoption rates. To evaluate emission reduction potential sensitivity to the compositions of electricity generation, five scenarios for renewable energy adoptions are investigated. The results reveal several new phenomena on emission reduction potential of building retrofits for medium offices in the U.S.: (1) it decreases from 2026 to 2050; (2) it has the same trend with coal usage; and (3) it reaches the maximum under the high renewable cost scenario. Based on the results, it is recommended that building retrofits should focus on 1) improving lighting and equipment efficiency; 2) locations with higher coal usage rate, and 3) buildings under the high renewable cost scenario. The new method can also be used for predicting emission reduction potential of the building sector in the U.S. by applying to other building types and regions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Framework to select robust energy retrofit measures for residential communities

Residential building energy retrofits are essential for enhancing environmental sustainability and reducing energy costs. The selection of retrofit measures is influenced by factors such as building systems, occupant behavior, government policy, weather variability, and climate change, all of which can significantly impact energy performance. Compared to retrofitting individual homes, evaluating and selecting optimal retrofit solutions for an entire community is challenging due to diverse residential compositions and variability present. Therefore, engineering robustness is crucial for ensuring consistent energy performance and resilience across different conditions. In this context, robustness refers to the ability of a retrofit measure to maintain its functionality and remain an optimal choice despite external disturbances or changes in inputs and conditions. This study presents a framework for evaluating the robustness of multiple retrofit measures across various building systems, occupant behaviors, and environmental scenarios at the community level. The framework comprises five key steps: scenario model development, integration of the National Residential Efficiency Measures database, energy performance simulation, cost-benefit aggregation, and retrofit solution selection. Each step enhances the framework’s robustness by incorporating the diversity of building characteristics, occupant behaviors, environmental conditions, retrofit options, and evaluation criteria. The framework’s effectiveness is demonstrated through a case study in southern Michigan in the United States, which includes 63 one-story single-family houses, 121 two-story single-family houses, and 8 townhouses. The study identifies furnace retrofits as the most robust solution for the entire community, consistently achieving source energy reductions of 4.7 %–8.0 % and payback period of 10–20 years across various scenarios. These findings are consistent with previous research, indicating the framework’s potential for broader applications in optimizing community-scale residential energy retrofits.

Shu, Lei↗
DOE OSTI2026

AI-Based Analytics and Energy Modeling Framework for Characterizing Urban Energy Systems

Developing location-specific district energy models is essential for understanding energy patterns and supporting efficient management and planning decisions. However, accurately characterizing these models remains challenging due to gaps in building characteristics and labor-intensive traditional modeling workflows. To address these challenges, we develop an AI-based framework that integrates top-down and bottom-up building energy data to automate urban energy model characterization. The framework trains multimodal deep learning models using heterogeneous ResStockTM datasets to infer missing building characteristics from varying levels of known information and generate simulation-ready inputs for district-scale energy modeling. It also employs a conditioning-based injection approach to generate ”what-if” scenarios, enabling users to explore retrofit, efficiency, and technology-upgrade pathways. Integrated within URBANoptTM, a bottom-up district energy modeling platform for simulating co-located buildings, the framework infers detailed building-level inputs required for bottom-up simulations. Both localized and generalized AI models are developed to learn relationships across categorical, numerical, and time-series data, enabling reconstruction of missing attributes and generation of targeted upgrade scenarios. We demonstrate this methodology on a residential neighborhood in Baltimore, MD, assessing internal consistency against ResStock reference data and URBANopt simulation, and comparing selected attributes against real-world building characteristics. Results show strong overall predictive accuracy in data completion and scenario generation, with localized and generalized models offering complementary trade-offs between precision and scalability. Overall, our automated framework streamlines energy modeling and provides a reliable framework for urban building energy characterization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

CO 2 conversion to syngas via electrification of endothermal reactors: Process design and environmental impact analysis

CO 2 utilization via reverse water gas shift (rWGS) reaction has been proposed as a path to the sustainable utilization. Here this work presents a detailed process modelling study where steam methane reforming (SMR) generated hydrogen was combined with rWGS to produce syngas (CO + H 2 ) with various hydrogen-to-carbon oxide ratios. To further decrease CO 2 emissions that may offset the benefits of CO 2 converted in rWGS, electrification of endothermal reactors, both SMR and rWGS was considered where CO 2 emitting fuel burning in the furnace was replaced by the emerging ohmic (resistive) heating. Material and energy inventory obtained from process design calculations was used to perform Life Cycle Analysis (LCA) to calculate environmental impacts of CO 2 consumption and reactor electrification. The results showed that greenhouse gas emissions, in CO 2 kg equivalent, were the lowest when both SMR and rWGS were heated using wind-generated electricity, decreasing from 25 to 10 kg CO 2 equivalent for H 2 :CO = 2:1 while the conventional electricity mix used for furnace electrical heating across the board of scenarios generated highest environmental impacts, much higher than those that used natural gas as fuel. Process economics calculations suggested that, when both SMR and rWGS were electrically heated, the process only showed product syngas cost parity with the conventional fuel heated design when electricity cost was ~$0.008/kWh. This suggests that CO 2 utilization scenarios involving process electrification need to be carefully considered from the total design perspective so they do not produce more greenhouse gases than in conventional non-electrified scenarios.

42 ENGINEERING↗
DOE OSTI2022

Integration of cryogenic energy storage with renewables and power plants: Optimal strategies and cost analysis

Energy storage is critical for overcoming challenges associated with the intermittency and the variable availability of renewable sources for decarbonizing the energy sector. Cryogenic energy storage (CES) is of interest due to its high technology readiness level, no geographical limitations, and moderate round-trip efficiency. The time-varying nature of demands and renewable availability needs to be considered at the design and integration stages of energy storage. We develop a mixed-integer nonlinear program (MINLP) model to obtain the energy storage costs on a daily basis for different scenarios that typically arise over an entire year. Using this optimization-based framework, we address key decision-making questions towards energy transition: What is the energy cost when CES is integrated with renewables and power plants? How does each scenario affect the overall energy cost? How much storage is needed for complete transition to renewables? What is the optimal integration towards 100% renewable energy? What are the optimal storage designs for both renewables and fossil-based power generation with current and future energy demands? Here, we discuss different scenarios and solutions to these questions.

25 ENERGY STORAGE↗
DOE OSTI2020

The prospective impacts of 2019 state energy policies on the U.S. electricity system

Over the past several years state energy policies have been evolving rapidly, and are more frequently including higher targets, including 100% clean energy targets. This study assesses the aggregate impacts of state clean energy standards and emissions policies on national electricity generation, power sector carbon dioxide (CO 2 ) emissions, and electricity prices and system costs. To do so, we apply the Regional Energy Deployment System (ReEDS) model, which is a detailed electric sector capacity expansion model, to evaluate scenarios with and without state policies and using a range of renewable energy technology cost projections. Across the scenarios analyzed, we find that the state policies drive 1.9%–10.7% of total nationwide clean energy and reduce cumulative power sector CO 2 emissions by 2.6%–5.4% over the 2020–2050 study period. This incremental generation is predominantly, but not exclusively, from renewable energy technologies. In most cases, the state policies result in increases to electricity prices and electricity system costs, and policy costs are sensitive to the future cost of clean energy technologies. Across all scenarios, the levelized cost of incremental policy-driven clean energy generation is estimated to be $17–38/MWh and the average cost of CO 2 abatement from the state-level policies is estimated to be $29–74/metric ton.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Techno-Economic Analysis of Recycling Strategies for Catalyst and Acid During Catalytic Graphitization

With the aim of meeting the urgent demand for active anode materials (AAM) in energy storage systems, bio-based graphite (biographite) emerges as an affordable solution to de-risk the turbulent supply chain of critical minerals. Anode grade biographite requires high crystallinity and purity, which can be achieved by catalytic graphitization with iron, followed by acid washing. Therefore, a well-conceived process integration that recycles catalyst can be the starting point to commercialization. This study evaluates closed-loop catalyst recovery, and byproducts valorization scenarios through a technoeconomic framework to help understand the scale-up potential of biographite. For the acid washing, three reactors in series meet the required biographite purity at 99.95%. Iron and acid recovery can reduce material consumption and waste generation by ~95%, albeit at the expense of ~80% increase in capital costs. Recovery scenarios present similar capital and operational expenses, yielding minimum selling prices (MSP) near $6 kg-1 of biographite. Monte Carlo methodology reveals that feedstock price accounts for ~60% of MSP variance, followed by plant capacity ~20%. The likelihood of reaching a competitive profit margin of 30% in the U.S. AAM market sits at 85% average for recovery scenarios, and 103% when iron oxide is sold as byproduct. Additionally, an IRR >= 15% can be achieved for half of Monte Carlo simulations, representing promising early-stage results. Biographite production offers a strategic pathway to stabilize the anode market beyond China by integrating established technologies for a scalable, economically viable, and sustainable process. The role of catalyst recovery and byproducts utilization is critical for advancing the biomaterials industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

FIND: A Synthetic weather generator to control drought Frequency, Intensity, and Duration

Water systems worldwide are experiencing climate change-induced shifts in drought properties like frequency, intensity, and duration, affecting water security and reliability. To develop and test effective drought preparedness plans, researchers often use synthetic weather generators to create hydrological scenarios that explore drought variability beyond historical records. Existing weather generators typically allow users to adjust streamflow statistics like percentiles or temporal correlation but do not directly control drought properties of frequency, intensity, and duration. To fill this gap, we propose FIND (Frequency, INtensity, and Duration) synthetic weather generator. FIND incorporates a standardized drought index to directly and in dependently control drought frequency, intensity, and duration in generated streamflow time series while preserving observed hydrological variability. Use cases for FIND include i) water systems analysis applications that seek to train and test drought strategies under historical and plausible future drought conditions, and ii) bottom-up vulnerability studies relating system vulnerability outcomes to specific changes in drought properties of frequency, intensity, and duration. Here, we demonstrate FIND’s versatility through three experiments: replicating historically observed drought properties, generating streamflow scenarios for multiple sites preserving correlation between their drought conditions, and generating a set of scenarios with direct and independent changes in drought properties. FIND source code is openly available for applications beyond the scope of this paper.

42 ENGINEERING↗
DOE OSTI2027

Nodal capacity expansion planning with flexible large-scale load siting

We propose explicitly incorporating large-scale load siting into a stochastic nodal power system capacity expansion planning model that concurrently co-optimizes generation, transmission, and storage expansion. The potential operational flexibility of some of these large loads is also taken into account by considering them as consisting of a set of tranches with different reliability requirements, which are modeled as a constraint on expected served energy across operational scenarios. We implement our model as a two-stage stochastic mixed-integer optimization problem with cross-scenario expectation constraints. To overcome the challenge of scalability, we build upon existing work to implement this model on a high performance computing platform and exploit scenario parallelization using an augmented Progressive Hedging Algorithm. The algorithm is implemented using the bounding features of mpisppy, which have shown to provide satisfactory provable optimality gaps despite the absence of theoretical guarantees of convergence. We test our approach and assess the value of this proactive planning framework on total system cost and reliability metrics using realistic testcases geographically assigned to San Diego and South Carolina, with datacenter and direct air capture facilities as large loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗