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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Economics of wind energy for utilities

Utility acceptance of this technology will be contingent upon the establishment of both its technical and economic feasibility. This paper presents preliminary results from a study currently underway to establish the economic value of central station wind energy to certain utility systems. The results for the various utilities are compared specifically in terms of three parameters which have a major influence on the economic value: (1) wind resource, (2) mix of conventional generation sources, and (3) specific utility financial parameters including projected fuel costs. The wind energy is derived from modeling either MOD-2 or MOD-0A wind turbines in wind resources determined by a year of data obtained from the DOE supported meteorological towers with a two-minute sampling frequency. In this paper, preliminary results for six of the utilities studied are presented and compared.

Mccabe, T. F.↗
DOE OSTI2024

Capital Structure for Techno-Economic Analysis of Hydrogen Projects

This report provides updated generally accepted accounting principles (GAAP) parameter estimates of assumptions that may be used to reflect the cost of financing hydrogen infrastructure deployment. The report also provides parameter estimation for more streamlined financial analysis frameworks such as discounted cash flow and annualized financial models. Parameter values are derived from industry feedback and are reflective of current macro-economic factors such as higher interest rates and higher risk profile of emerging hydrogen technologies, given a myriad of factors such as projects’ construction inexperience, capital costs, and rising inflation, among others.

08 HYDROGEN↗
DOE OSTI2021

REopt Lite User Manual

REopt Lite evaluates the economic viability of grid-connected solar photovoltaics, wind, combined heat and power, and electric and thermal storage at commercial and small industrial sites. It allows building owners to identify the system sizes and dispatch strategies that minimize the site’s life cycle cost of energy. REopt Lite also estimates the amount of time on-site generation and storage can sustain the site's critical load during a grid outage and allows the user the choice of optimizing for energy resilience. It is primarily used to inform project development decisions and to support research on the factors that drive project feasibility for market development and policy analysis. It is available through a web interface, application programing interface, and open-source code. This user manual provides an overview of the model, including its capabilities and typical applications; inputs and outputs; economic calculations; technology descriptions; and model parameters, variables, and equations. The model is highly flexible and is continually evolving to meet the needs of each analysis. Therefore, this report is not an exhaustive description of all capabilities, but rather a summary of the core components of the model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1972

Scatter factor and reliability of aircraft structures

The concept of time to first failure is utilized to perform a parameter study of scatter factors of aircraft structures. The Weibull distribution is used for estimation of characteristic and certifiable lives. Scatter factors for various Weibull-shaped parameters, fleet sizes and level of reliabilities are calculated. It is concluded that the currently used range of scatter factors (2 through 4) is too narrow for the estimation of a safe life and that a safe and economical design for structural materials with shape parameters less than 2 does not seem feasible except for very small fleet sizes and low levels of reliability.

Schueller, G. I.↗
DOE OSTI2025

FracML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage

Poster on “FRACML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. The accurate characterization of subsurface fracture networks is essential for the secure operation of carbon capture, utilization, and storage (CCUS) projects. A thorough understanding of the spatial distribution of subsurface faults and fractures is crucial for predicting CO2 plume evolution and minimizing risks such as potential leakage into overlying formations or induced seismicity. In this context, robust fracture network quantification plays a pivotal role in reservoir management, providing the data necessary to fine-tune operational parameters, and ensure the environmental and economic viability of CCUS projects. As part of the U.S. Department of Energy’s SMART (Science-informed Machine Learning for Accelerating Real-time Decisions in Subsurface Applications) initiative, we focused on the development and application of a machine learning-based tool (FRACML) designed to quantify and map fracture networks using real-world (non-synthetic) data from an active CO2 injection site. Our objective is to demonstrate the utility of this tool in improving operational efficiency and safety across CCUS sites.

artifical intelligence / machine learning (AI/ML)↗
NASA NTRS1973

Payload design requirements analysis (study 2.2). Volume 3. Guideline analysis

Payloads to be launched on the space shuttle/space tug/sortie lab combinations are discussed. The payloads are of four types: (1) expendable, (2) ground refurbishable, (3) on-orbit maintainable, and (4) sortie. Economic comparisons are limited to the four types of payloads described. Additional system guidelines were developed by analyzing two payloads parameterically and demonstrating the results on an example satellite. In addition to analyzing the selected guidelines, emphasis was placed on providing economic tradeoff data and identifying payload parameters influencing the low cost approaches.

Shiokari, T.↗
NASA NTRS1975

Computer mapping of turbidity and circulation patterns in Saginaw Bay, Michigan from LANDSAT data

The author has identified the following significant results. LANDSAT was used as a basis for producing geometrically-corrected, color-coded imagery of turbidity and circulation patterns in Saginaw Bay, Michigan (Lake Huron). This imagery shows nine discrete categories of turbidity, as indicated by nine Secchi depths between 0.3 and 3.3 meters. The categorized imagery provided an economical basis for extrapolating water quality parameters from point samples to unsample areas. LANDSAT furnished a synoptic view of water mass boundaries that no amount of ground sampling or monitoring could provide.

Rogers, R. H.↗
DOE OSTI2023

Development of Genetic Algorithm Based Multi-Objective Plant Reload Optimization Platform

The U.S. nuclear industry is facing a challenge in maintaining required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects of light-water reactor nuclear power plant operations. Safety can become more economical by using a risk-informed ecosystem, such as the one being developed in the Risk-Informed Systems Analysis Pathway under the U.S. Department of Energy Light Water Reactor Sustainability Program. The Light Water Reactor Sustainability Program promotes a wide range of research and development activities to maximize both the safety and economic efficiency of nuclear power plants through improved scientific understanding, especially given that many plants are now considering second license renewals. The Risk-Informed Systems Analysis Pathway has two main goals: Deploy methodologies and technologies that better represent safety margins and cost and safety factors; Develop advanced applications that enable cost-effective plant operations. The Plant Reload Optimization Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. This report summarizes genetic-algorithm-based multi-objective fuel reload optimization activities, specifically: Developing the non-dominated sorting genetic algorithm II optimizer in the Risk Analysis and Virtual ENviroment (RAVEN); Demonstrating and validating the developed non-dominated sorting genetic algorithm II optimizer using benchmark optimization problems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1992

Repair-level analysis for Space Station Freedom

To assign repair or discard-at-failure designations for orbital replacement units (ORUs) used on Space Station Freedom Electric Power System (SSFEPS), new algorithms and methods were required. Unique parameters, such as upmass costs, extravehicular activity costs and intravehicular activity (IVA) costs specific to Space Station Freedom's maintenance concept were incorporated into the Repair-Level Analysis (RLA). Additional outputs were also required of the SSFEPS RLA that were not required of previous RLAs. These outputs included recommendations for the number of launches that an ORU should be capable of attaining and an economic basis for condemnation rate. These unique parameters were not addressable using existing RLA models: therefore, a new approach was developed. In addition, it was found that preemptive analysis could be performed using spreadsheet-based Boolean expressions to represent the logical condition of the items under analysis.

Chadwick, M.↗
DOE OSTI2022

Development of Plant Reload Optimization Framework Capabilities for Core Design and Fuel Performance Analysis

The United States (U.S.) nuclear industry faces a challenge in maintaining required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects of light water reactor (LWR) nuclear power plant (NPP) operations. Safety can become more economical by using a risk-informed ecosystem, such as the one being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program promotes a wide range of research and development activities with the goal of maximizing both the safety and economic efficiency of NPPs through improved scientific understanding, especially given many plants are now considering second license renewals. The RISA Pathway has two main goals: (1) deploy methodologies and technologies that better represent safety margins and cost and safety factors and (2) develop advanced applications that enable cost-effective plant operation. The Plant Reload Optimization Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses, and also uses artificial intelligence to support optimization of core design solutions. This report summarizes Fiscal Year 2022 (FY-22) activity in platform capability developments in RAVEN. This platform performs simulations using industry codes for core design (i.e., PARCS) and fuel performance (i.e., TRANSURANUS) which will allow expansion of the capabilities to include advanced fuel designs such as accident-tolerant fuel (ATF)s with high burnup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Development and Demonstration of a Risk-Informed Approach to the Regulatory Required Fuel Reload Safety Analysis

The United States (U.S.) nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor (LWR) nuclear power plants (NPPs) and can be achieved more economically by using a risk-informed ecosystem such as that being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program is promoting a wide range of research and development (R&D) activities with the goal to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering second license renewal. The RISA Pathway has two main goals: (1) the deployment of methodologies and technologies that enable better representation of safety margins and the factors that contribute to cost and safety; and (2) the development of advanced applications that enable cost-effective plant operation. The plant reload optimization framework development project aims to build an artificial intelligence, i.e., Genetic Algorithm (GA), based reactor core designing tool taking into account reactor safety and fuel performance analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Safety Analysis of FeCrAl Accident-Tolerant Fuels with Increased Enrichment and Extended Burnup

The U.S. nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor nuclear power plants (NPPs), and it can be achieved more economically by using a risk-informed ecosystem, such as that being developed by the Risk-Informed Systems Analysis Pathway under the U.S. Department of Energy Light Water Reactor Sustainability Program. This program is promoting a wide range of research and development activities to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering a second license renewal. The Risk-Informed Systems Analysis Pathway has two main goals: (1) The deployment of methodologies and technologies that enable a better representation of the safety margins and factors that contribute to cost and safety, and (2) The development of advanced applications that enable cost-effective plant operation. As part of this pathway, the Enhanced Resilient Plant project refers to an NPP where safety is improved by implementing various measures, such as accident-tolerant fuels, diverse and flexible coping strategies, enhancements to plant components and systems, incorporation of augmented or new passive cooling systems, and utilization of advanced battery technologies. The objective of the Enhanced Resilient Plant project is to use novel methods and computational tools to enhance existing reactors’ safety while reducing operational costs. This report documents research and development conducted in support of deployment of accident-tolerant fuels. This project performed safety analyses for the steady-state normal operation, anticipated operational occurrences, and design-basis accidents of a representative four-loop pressurized water reactor model with Zr and FeCrAl accident-tolerant fuel clad with higher enrichment and burnup supporting plant refueling cycles of 18 and 24 months. The source terms and environmental impacts were studied for a large-break loss of coolant accident, including uncertainty analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Demonstration of the Plant Fuel Reload Process Optimization for an Operating PWR

The United States (U.S.) nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor (LWR) nuclear power plants (NPPs) and can be achieved more economically by using a risk-informed ecosystem such as that being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program is promoting a wide range of research and development (R&D) activities with the goal to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering second license renewal. The RISA Pathway has two main goals: (1) the deployment of methodologies and technologies that enable better representation of safety margins and the factors that contribute to cost and safety; and (2) the development of advanced applications that enable cost-effective plant operation. This report summarizes the research outcomes in FY-2021, which the project progressed from the planning and methodology development phase to the early demonstration phase. The highlights of these activities are: (1) the development of a multi-objective optimization process using Genetic Algorithms (GAs); (2) the development and test of an approach for optimization process acceleration using artificial intelligence (AI) that significantly reduces the computational burden; (3) the demonstration of the fuel reload optimization framework for a generic pressurized water reactor (PWR); and (4) the demonstration of limiting design basis accident (DBA) scenarios for evaluation of the transition from deterministic to risk-informed approach for fuel reload optimization.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Assessment of Modeling and Simulation Technical Gaps in Safety Analysis of High Burnup Accident-Tolerant Fuels

The United States nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor (LWR) nuclear power plants (NPPs), and it can be achieved more economically by using a risk-informed ecosystem, such as that being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program is promoting a wide range of research and development activities to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering second license renewal. The RISA Pathway has two main goals: The deployment of methodologies and technologies that enable better representation of safety margins and the factors that contribute to cost and safety, and; The development of advanced applications that enable cost-effective plant operation. As part of the RISA Pathway, the Enhanced Resilient Plant (ERP) project refers to an NPP where safety is improved by implementing various measures, such as accident-tolerant fuels (ATF), diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, incorporation of augmented or new passive cooling systems, and utilization of advanced battery technologies. The objective of the ERP research is to use novel methods and computational tools to enhance existing reactors’ safety while reducing operational costs. Many U.S. utilities are targeting implementation of ATFs instead of traditional fuel in the near future since ATFs offer benefits in terms of improved performance and cost savings. The robust properties of ATF make it possible to extend the refueling cycle from 18 to 24 months in addition to the opportunity to use less of fuel. Extensive safety assessments are required to support regulatory requirements and obtain the approvals to use ATFs and the ERP project support the industry by developing novel effective methodologies for safety evaluations. In this project, the technical gaps in the modeling and simulation of the high burnup (HBU) ATF were assessed in terms of the fuel cladding behavior during the postulated accident events. The issues were identified in modeling the cladding deformation, the hydrodynamic change due to cladding deformation and the critical heat flux (CHF). The RELAP5-3D cladding deformation model was assessed by multiple verification tests and validation with the instrumented fuel assembly (IFA) experiment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Role of peracetic acid on the disruption of lignin packing structure and its consequence on lignin depolymerisation

Peracetic acid (PAA) is an effective oxidant capable of solubilising lignin and efficiently depolymerising it to selective phenolic compounds; however, the specific role by which PAA initiates the depolymerisation is still elusive. Herein, interaction between PAA and the lignin macromolecule and the consequent structural changes of the latter were studied by characterising the lignin packing structure and its associated changes during the oxidation process. While the lignin packing structure and its changes associated with the PAA-mediated oxidation were probed by X-ray diffraction, the impact of the PAA on different chemical functionalities present in the lignin structure was established by 13 C and 1 H– 13 C heteronuclear single-quantum coherence nuclear magnetic resonance (NMR) spectroscopy. Further, combining the NMR spectroscopy results, and the product distribution, we conclude that the predominant reaction pathway for the oxidative depolymerisation of lignin with PAA is the Baeyer–Villiger oxidation of the ketone formed by the oxidation of the benzylic hydroxyl group adjacent to the β-O-4 linkage. The experimental evidence provided herein corroborated that PAA instigates oxygen insertion to the lignin macromolecule resulting in disruption of its packing structures and facilitates depolymerisation. We also investigated various metal oxide and mixed metal oxide catalysts to identify effective catalysts that further enhance the efficiency of PAA-mediated depolymerisation of lignin and produce selective monomeric phenolic compounds. Techno-economic analysis was also conducted to identify the key parameters associated with this oxidative process that need to be considered for possible commercial application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Impact of methane and black carbon mitigation on forcing and temperature: a multi-model scenario analysis

The relatively short atmospheric lifetimes of methane (CH 4 ) and black carbon (BC) have focused attention on the potential for reducing anthropogenic climate change by reducing Short-Lived Climate Forcer (SLCF) emissions. This paper examines radiative forcing and global mean temperature results from the Energy Modeling Forum (EMF)-30 multi-model suite of scenarios addressing CH 4 and BC mitigation, the two major short-lived climate forcers. Central estimates of temperature reductions in 2040 from an idealized scenario focused on reductions in methane and black carbon emissions ranged from 0.18–0.26 °C across the nine participating models. Reductions in methane emissions drive 60% or more of these temperature reductions by 2040, although the methane impact also depends on auxiliary reductions that depend on the economic structure of the model. Climate model parameter uncertainty has a large impact on results, with SLCF reductions resulting in as much as 0.3–0.7 °C by 2040. We find that the substantial overlap between a SLCF-focused policy and a stringent and comprehensive climate policy that reduces greenhouse gas emissions means that additional SLCF emission reductions result in, at most, a small additional benefit of ~ 0.1 °C in the 2030–2040 time frame.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The physics of gain relevant to inertial fusion energy target designs

In inertial confinement fusion, pellets of deuterium tritium fuel are compressed and heated to the conditions where they undergo fusion and release energy. The target gain (ratio of energy released from the fusion reactions to the energy in the drive source) is a key parameter in determining the power flow and economics of an inertial fusion energy (IFE) power plant. In this study, the physics of gain is explored for laser-direct-drive targets with driver energy at the megajoule scale. This analysis is performed with the assumption of next-generation laser technologies that are expected to increase convergent drive pressures to over 200 Mbar. This is possible with the addition of bandwidth to the laser spectrum and by employing focal-spot zooming. Simple physics arguments are used to derive scaling laws that describe target gain as a function of laser energy, adiabat, ablation pressure, and implosion velocity. Scaling laws are found for the unablated mass, ablation pressure, areal density, implosion velocity, and in-flight aspect ratio. Furthermore, those scaling laws are then used to explore the design space for IFE targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Solar-Thermal Ammonia Production: System Design and Technoeconomic Analysis [Slides]

CO 2 -neutral ammonia production with concentrated solar technology is theoretically possible based on advanced solar thermochemical looping technology. The parametric analysis points to the re-oxidation temperature and the H 3 yield as the most influential parameters in the energy balance. The cycle time and the nitride cost are the most influential parameters on the CAPEX. The techno-economics analysis shows the potential of the plant to achieve a target price <125 $\$$/tonne.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗