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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Framework for Quantitative Evaluation of Resilience Solutions: An Approach to Determine the Value of Resilience for a Particular Site

The paper provides the approach to providing a benefit cost analysis of energy and water alternatives to provide resilience to extreme events. The approach estimates the costs and returns of providing greater resilience of water and energy infrastructure. Extreme events are defined as high impact, low-frequency events such as, but not limited to, hurricanes, floods, storm surges and earthquakes. The provides justification for hardening water and energy infrastructure. Resilience is defined as “the ability to prepare for and to withstand an extreme event with little or no damage, or to recover more quickly from an extreme event.” The approach can be summarized as follows. The approach requires the development of a baseline with which to compare alternatives. The baseline is used to evaluate the baseline’s resilience to hazards through the probability of the hazard(s), the likelihood of damage from that the hazard through a vulnerability analysis, and the consequence to calculate a cost of the damage. The approach then evaluates proposed mitigation alternatives that would improve the resilience of the system. Each alternative is evaluated based on probability of the hazard, probability of vulnerability and consequence to determine the reduced damage that each alternative presents. The approach includes any monetary and non-monetary benefits that can quantified for each of the alternatives. Non-quantifiable benefits are evaluated based on the relative importance of each alternative to the criteria used to determine how well the alternative meets the goals and objectives of the site/facility. Then, a life cycle cost analysis should be conducted for the baseline and alternatives. Finally, the results of the life cycle analysis should be presented in a decision matrix with cost, net present value, benefit/cost ratios, and any non-monetary criteria ranked to show how well the alternatives met the criteria, weighted with the decision maker’s weights and the results presented.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantifying co-benefits of water quality policies: An integrated assessment model of land and nitrogen management

Due to the nature of nitrogen cycling, policies designed to address water quality concerns have the potential to provide benefits beyond the targeted water quality improvements. For example, actions to protect water quality by reducing nitrate leaching from agriculture also reduce emissions of nitrous oxide, a potent greenhouse gas. These positive effects, which are incidental to the regulation's intended target, are termed “co-benefits.” To quantify the co-benefits associated with reduced nitrate leaching, we integrate an economic model of farmer decision making with a model of terrestrial nitrogen cycling for the watershed surrounding Lake Mendota, Wisconsin, USA. Our modeling approach provides a framework that links air and water pollutants in an agri-environmental system and offers a direction for future studies. Our model results highlight the finding that the co-benefits from nitrous oxide abatement are substantial, and their inclusion increases the benefit–cost ratio of water quality policies. Consideration of these co-benefits has the potential to reverse the conclusions of benefit–cost analysis in the assessment of current water quality policies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Techno-Economic Evaluation of a 600MW Pumped Storage Hydropower Plant using the Pumped Storage Hydropower Valuation Tool

This paper presents a techno-economic evaluation of the proposed 600 MW, 8-hour Craig – Hayden pumped storage hydropower project using the U.S. Department of Energy’s Pumped Storage Hydropower Valuation Tool. The analysis integrates plant technical characteristics, regional grid conditions, and market-based operating assumptions to quantify stacked value streams from energy arbitrage, capacity, ancillary services, transmission congestion relief, and reliability. Both price taker and price influencer frameworks are applied to examine the impact of market participation and system interactions on lifecycle economic performance using Benefit - Cost Analysis and Multi - Criteria Decision Analysis. The results show that the price taker approach provides higher revenue estimates based on exogenous price signals, while the price influencer approach captures production cost savings, renewable curtailment reduction, and market price formation, yielding more conservative but system-representative outcomes. The study demonstrates the strategic value of long-duration PSH for enhancing operational flexibility, resource adequacy, and grid reliability in a high-renewable Western Interconnection.

Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046↗
DOE OSTI2022

DIF3D-VARIANT Usage Guide

The DIF3D software is a key part of the legacy fast reactor analysis software package developed and maintained at Argonne National Laboratory. The DIF3D-VARIANT capability has been pushed to the forefront of usage in the last decade at ANL because of improved computing resources and the focus on reactors with significant leakage. The purpose of this document is to discuss when the DIF3D-VARIANT solver provides a solid benefit to analysis work and discuss the resource requirements and explain why they are so much greater than the other solver options in DIF3D. Additional discussion will be provided on solution accuracy and any deficiencies relative to other solvers available in the literature.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Beyond optimization—supervised learning applications in relativistic laser-plasma experiments

We explore the applications of machine learning techniques in relativistic laser-plasma experiments beyond optimization purposes. We predict the beam charge of electrons produced in a laser wakefield accelerator given the laser wavefront change caused by a deformable mirror. Machine learning enables feature analysis beyond merely searching for an optimal beam charge, showing that specific aberrations in the laser wavefront are favored in generating higher beam charges. Supervised learning models allow characterizing the measured data quality as well as recognizing irreproducible data and potential outliers. Furthermore, we also include virtual measurement errors in the experimental data to examine the model robustness under these conditions. This work demonstrates how machine learning methods can benefit data analysis and physics interpretation in a highly nonlinear problem of relativistic laser-plasma interaction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Machine Learning in the Context of Laser-Induced Breakdown Spectroscopy

The integration of machine learning (ML) with Laser-Induced Breakdown Spectroscopy (LIBS) has revolutionized the analytical capabilities of LIBS. The combi-nation of both methods enables more accurate and efficient data analysis. While LIBS itself is a powerful technique for elemental analysis, the vast amount of spectral data it generates can be hard to interpret. Machine learning addresses these challenges by leveraging algorithms that can learn from data, identify patterns, and make predictions without explicit programming for the interpretation of each specific task. In LIBS application, ML techniques are used to enhance various analytical processes. For example, ML algorithms can classify materials based on their spectral fingerprints, predict the concentration of elements in a sample, and identify underlying patterns within complex datasets. Here, this application improves the precision of LIBS analyses while significantly reducing the time required for data processing and interpretation. In this chapter, the fundamental concepts of ML will be discussed first. Following this, the process of data splitting and the importance of feature selection will be examined. Several machine learning methods will then be closely examined, exploring how each can benefit LIBS analysis and highlighting their respective advantages and shortcomings. This structured approach will provide a comprehensive understanding of the integration of ML in the context of LIBS analysis.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Particle signal considerations for isotope ratio analysis with single particle multi-collector inductively coupled plasma mass spectrometry

Particle analysis has benefitted from the advent of single particle inductively coupled plasma-mass spectrometry (spICP-MS) due to its robustness, sensitivity, and high-throughput nature. Previous methods of spICP-MS have typically utilized quadrupole or time-of-flight mass analyzers and therefore employ electron multiplier-based detectors (such as secondary electron multipliers or microchannel plates). However, to obtain precise measurements on elemental or isotopic ratios within individual particles, multi-collector ICP-MS (MC-ICP-MS) can be used. Here, we investigate Ce isotope ratios, specifically 142 Ce/ 140 Ce, by spMC-ICP-MS using an all-Faraday cup collector array. Using 1 μm (diameter) cerium dioxide particles, integration times of the Faraday cup detectors were varied from 50–500 ms. The signal from the cerium isotopes in the particles was used to determine isotope ratios, which closely matched the expected natural isotopic abundances. Due to the signal decay response from the Faraday cups, the signal from particles lasts much longer than the expected 1–2 ms (up to 100 s of ms). To explore this effect on isotope ratio analysis, multiple ratio analysis methods were used to determine how to obtain optimal precision and accuracy. Relative differences were around 2% for methods that calculated isotope ratios from summing the total signal of an individual particle before calculating the ratio (rather than using every data point individually). It was found that summing all data points per particle, or integrating under the signal peak, yielded both accurate and precise isotope ratios within the particle population. Particles were also sampled off a solid substrate via microextraction, and isotope ratios were determined with relative differences of 0.13% to 9%. This demonstrates the ability to use spMC-ICP-MS to obtain isotope ratios on particles, with little to no relative difference in comparison to the expected ratio, even when operating Faraday detectors at fast 50 ms integration times.

Szakas, Sarah E. [Oak Ridge National Laboratory (O↗
DOE OSTI2020

Feedback from International Decommissioning Planning Projects - 20269

Decommissioning of Nuclear Power Plants is an increasing reality in many countries with nuclear power. Already many years before final shutdown, planning of the decommissioning work is usually started in order to understand for example the costs, waste volume capacity and licensing work needed. In many countries it is required to have a final decommissioning plan before any decommissioning work is allowed to start. Westinghouse has been involved in international decommissioning planning for more than 30 years, where the first 20 years was mostly funding and preliminary plans due to that decommissioning was many years away. However, as many more plants are now moving into decommissioning, the focus has shifted to final decommissioning plans with budgets instead of funding plans, strategic decisions instead of choices, waste volume specifications instead of estimates and a defined approach instead of what ifs. Westinghouse has developed a methodology based on the planning and execution of many decommissioning projects in Europe, America and Asia. That international experience and understanding helps the customers to adopt a systematic planning process where strategy development is done with the end state in mind, where the goals are clearly outlined and the starting point described. The process and steps to reach the desired end state need to be clearly defined and all options/alternatives evaluated from a cost/benefit point of view. This is followed by a thorough and quantitative risk analysis in order to give solid recommendations and credible conclusions. One important feedback has been that real decommissioning experience from reference projects is invaluable for an efficient and timely progress in order not to spend unnecessary time and effort on understanding the barriers and links between different activities in decommissioning. Skilled project managers or engineers can drive the project forward, but without decommissioning experience previously gained, valuable lessons learned are not used and the same mistakes can be made again. Many utilities have invested in knowledge transfer from other decommissioning projects through site visits, exchange programs and supplier meetings, which is a valuable asset and way of implementing lessons learned from performed decommissioning projects into the planning process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Quantifying Rooftop Solar Benefits: A State-Level Value of Solar Analysis for India

Analyses that quantify the costs and benefits associated with rooftop solar (RTS) adoption and operation can inform decision-makers in the development and evaluation of RTS policies. One such analysis is a Value of Solar (VOS) study, which quantifies select costs and benefits surrounding RTS based on the electricity system context. These studies can drive changes to existing policies towards fairer, more cost-reflective RTS compensation or alternatively can provide confidence for the decision-maker to stay the course and largely maintain existing policies. This report provides a VOS analysis for two states in India: Gujarat and Jharkhand and provides details related to the methodology and key findings.

14 SOLAR ENERGY↗
DOE OSTI2024

Can section 45Q tax credit foster decarbonization? A case study of geologic carbon storage at Acid Gas Injection wells in the Permian Basin

Carbon capture, utilization, and storage (CCUS) is an important pathway for meeting climate mitigation goals. While the economic viability of CCUS is well understood, previous studies do not evaluate the economic feasibility of carbon capture and storage (CCS) in the Permian Basin specifically regarding the new Section 45Q tax credits. We developed a technoeconomic analysis method, evaluated the economic feasibility of CCS at the acid gas injection (AGI) wells, and assessed the implication of Section 45Q tax credits for CCS at the AGIs. We find that the compressors, well depth, and the permit and monitoring costs drive the facility costs. Compressors are the predominant contributors to capital and operating expenditure driving the levelized cost of CO 2 storage. Strategic cost reduction measures identified include 1) sourcing of low-cost electricity and 2) optimizing operational efficiency in well operations. In evaluating the impact of the tax credits on CCS projects, facility scale proved decisive. We found that facilities with an annual injection rate exceeding 10,000 MT storage capacity demonstrate economic viability contingent upon the procurement of inputs at the least cost. The new construction of AGI wells were found to be economically viable at a storage capacity of 100,000 MT. The basin is heavily focused on CCUS (tax credit – $\$$65/MT CO 2 ), which overshadows CCS ($\$$85/MT CO 2 ) opportunities. Balancing the dual objectives of CCS and CCUS requires planning and coordination for optimal resource and pore space utilization to attain the basin's decarbonization potential. We also found that CCS on AGI is a lower cost CCS option as compared to CCS on other industries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Economic Incentives for Agrivoltaics Systems with Commodity Crops in the Midwestern United States

Declining costs of photovoltaic (PV) technology and rising market and policy incentives are leading to the growing deployment of PV on cropland in the US Midwest, leading to concerns about the displacement of food and feed crop production. Agrivoltaic (AV) technology enables the dual use of land by co-locating PV energy and crop production, potentially reducing land-use competition with crop production. We develop a benefit-cost analysis framework to compare the net economic returns from AV to those with stand-alone PV and crop production on a representative field and show conditions under which AV can be more profitable for both a solar developer and a farmer. We integrate it with a crop and solar energy model to simulate the performance of various field designs and space and height configurations in AV systems to accommodate soybean production with conventional farm equipment under representative conditions in the US Midwest. We find that an AV system with soybean production is less profitable than PV alone for a solar developer due to the high capital costs of raising panel height, and less profitable for a farmer than leasing land for PV due to its adverse effects of shading on crop yield. We discuss the changes in technology and market prices of solar energy and soybeans that are necessary to make the AV system profitable for solar developers and farmers. We show that AV can worsen rather than mitigate the conflict between food crops and solar energy production in the Midwest.

14 SOLAR ENERGY↗
DOE OSTI2020

Capabilities of multivariate Bayesian inference toward seismic hazard assessment

Multivariate Bayesian analysis can bring significant benefits to seismic hazard analysis: Its multivariate feature enables computing scalar and vector hazard without making any approximations; Correlations between intensity measures are implicitly modeled, permitting direct simulation of ground motion selection tools such as the conditional mean spectrum and the generalized conditioning intensity measure; and Its updating feature enables a seamless integration of new ground motion data into the hazard results. Here, we first develop a multivariate Bayesian ground motion model through the NGA-West2 database. The model functional form considers fault-type, magnitude, and distance dependencies, and also the linear and the rock intensity dependent site response. We use a hybrid Markov Chain Monte Carlo sampling to perform Bayesian inference consisting of Gibbs step and a multilevel Metropolis-Hastings step. We then perform several checks on the model and note that its performance is satisfactory. Finally, we illustrate the merits of this multivariate Bayesian analysis, which include: ground motion model updating with ground motion data recorded in the last four years not part of the NGA-West2 database; computation of scalar and vector seismic hazard using the un-updated and updated ground motion models for Los Angeles, CA; and simulation of the conditional mean spectrum under scalar and vector IM conditioning while accounting for different sources of aleatoric and epistemic uncertainties.

58 GEOSCIENCES↗
DOE OSTI2020

Single-entity electrochemistry at confined sensing interfaces

Measurements at the single-entity level provide more precise diagnosis and understanding of basic biological and chemical processes. Recent advances in the chemical measurement provide a means for ultra-sensitive analysis. Confining the single analyte and electrons near the sensing interface can greatly enhance the sensitivity and selectivity. In this work, we summarize the recent progress in single-entity electrochemistry of single molecules, single particles, single cells and even brain analysis. The benefits of confining these entities to a compatible size sensing interface are exemplified. Finally, the opportunities and challenges of single entity electrochemistry are addressed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The economic and environmental costs and benefits of the renewable fuel standard

Abstract Mandates, like the renewable fuel standard (RFS), for biofuels from corn and cellulosic feedstocks, impact the environment in multiple ways by affecting land use, nitrogen (N)-leakage, and greenhouse gas (GHG) emissions. We analyze the differing trade-offs these different types of biofuels offer among these multi-dimensional environmental effects and convert them to a monetized value of environmental damages (or benefits) that can be compared with the economic costs of extending these mandates over the 2016–2030 period. The discounted values of cumulative net benefits (or costs) are then compared to those with a counterfactual level of biofuels that would have been produced in the absence of the RFS over this period. We find that maintaining the corn ethanol mandate at 56 billion l till 2030 will lead to a discounted cumulative value of an economic cost of $199 billion over the 2016–2030 period compared to the counterfactual scenario; this includes $109 billion of economic costs and $85 billion of net monetized environmental damages. The additional implementation of a cellulosic biofuel mandate for 60 billion l by 2030 will increase this economic cost by $69 billion which will be partly offset by the net discounted monetized value of environmental benefits of $20 billion, resulting in a net cost of $49 billion over the 2016–2030 period. We explore the sensitivity of these net (economic and environmental) costs to alternative values of the social costs of carbon and nitrogen and other technological and market parameters. We find that, unlike corn ethanol, cellulosic biofuels can result in positive net benefits if the monetary benefits of GHG mitigation are valued high and those of N-damages are not very high.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Comfort and Safety Metrics to Evaluate Customer Centric Resilience Enhancement Strategies

As the coincident events of extreme weather and major power outages continue to rise there is an increased need to implement resilience solutions. Many of these solutions are customer-centric, requiring the flexibility of demand, and many of the standard economic evaluations of these solutions do not include the benefits of resilience that are not easily quantified and monetized. Indoor air temperature has a large impact on the comfort and safety of building occupants during an extreme weather event. This work proposes metrics that can be used to compare the performance of resilience solutions in the context of comfort and safety.

Cost benefit analysis, Demand Side Management, Pow↗
DOE OSTI2022

A geo-visual analysis for exploring the socioeconomic benefits of the heating electrification using geothermal energy

In parallel to population growth and climate change, the rapid pace of urbanization worldwide has led to an enormous increase in energy demand and costs in urban areas. The subsequent energy burden has become an increasing concern for many households in the U.S. Previous studies have revealed that geothermal resources can effectively lower the electricity demand and carbon emissions in large cities. In this paper, we focus on the socioeconomic impacts of geothermal energy on urban systems by presenting an interactive visual analytics dashboard. The dashboard allows urban planners to spatially examine geothermal energy's practical benefits on energy affordability, urban livability, and resilience across the U.S. We compiled a list of socioeconomic metrics by integrating the simulation results from multiple geothermal and building models with multi-domain urban datasets (socioeconomic, demographic, and electricity utility). These metrics are created to characterize the benefits of the heating electrification of buildings using Geothermal Heat Pumps (GHP) for lowering the energy burden of middle-and low-income households nationwide. The visual dashboard employs a combination of multivariate, glyph-based, and geospatial visualization to reveal the variability and patterns in our metrics. We present a pilot study to demonstrate the GHPs' potential as a renewable and affordable solution for increasing the economic and energy grid resilience in U.S cities.

Xu, Haowen↗
DOE OSTI2020

BEPAM Model Code and CABBI Simulation Results for "The Economic and Environmental Costs and Benefits of the Renewable Fuel Standard"

This dataset contains BEPAM model code and input data to replicate the outcomes for "The Economic and Environmental Costs and Benefits of the Renewable Fuel Standard". The dataset consists of: (1) The replication codes and data for the BEPAM model. The code file is named as output.gms. (BEPAM-Social cost model-ERL.zip) (2) Simulation results from the BEPAM model (BEPAM_Simulation_Results.csv) * Item (1) is in GAMS format. Item (2) is in text format.

Cost-Benefit Analysis↗