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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Cooled Gas Turbine and Combined Cycle Analysis for NH 3 -CH 4 Fuel Mixes (Up to 100% NH 3 )

In this study, a cooled gas turbine (GT) analysis was conducted for varying levels of ammonia (NH 3 ) blends with methane. The ultimate goal is to have a gas turbine design that can be used for all the fuel blends (including 100% NH 3 ) without any changes to the system. The technological developments in the cooling system, gas turbine design, and materials that will be required for NH 3 combustion were identified and analyzed in this study to develop an advanced gas turbine design for NH 3 fuels. The study includes a combined cycle performance analysis with the NH 3 fuel blends using the advanced gas turbine design developed in this study. A techno-economic analysis was conducted for analyzing the impact of the NH 3 fuels on the levelized cost of electricity and cost sensitivities to fuel price and capacity factor.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2019

Predicting Cancer Risk from Ionizing Radiation

The ability to predict cancer risk associated with exposure to low doses of high-LET ionizing radiation (IR) remains a challenge. Epidemiological methods lack the sensitivity and power to provide detailed risk estimates for cancer and ignore individual variance in IR sensitivity. We have hypothesized that DNA repair capacity can be used as a marker to evaluate and differentiate individual radiation sensitivity. More specifically, this work is based on the concept that the combined time-dose dependence of radiation-induced foci (RIF) of p53-binding protein 1 (53BP1) following low-LET exposure contains sufficient information to infer sensitivity to any other LET. Our hypothesis was tested in 15 different mouse strains as well as in primary human immune cells. We first approached individual ionizing radiation sensitivity in a mouse model by culturing primary skin fibroblasts extracted from 76 mice of 15 different genetic backgrounds and exposing them to HZE particles and X-rays. This work is one of the most extensive studies on the kinetics and possible genetic underpinnings of radiation-induced DNA damage and repair. Our results is in agreement with a DNA repair model we previously postulated, where nearby DNA double strand breaks (DSB) in the nucleus are brought together for more efficient repair, leading to RIF clustering. Such mechanism was evidenced by a specific dose and LET dependence of RIF numbers. Briefly, RIF quantification after low-LET X-ray exposure showed an asymptotic saturation for doses between 1 Gy and 4 Gy 4 hours post-irradiation across all 15 strains. The clustering of DSB across all strains also led to more RIF/Gy for lower LET (X-ray and 350 MeV/n Ar) than for higher LET (600 MeV/n Fe) 4 hours post-exposure. Considering the fact that the number of DSB/Gy should be independent of LET, our data suggest there are more DSB in individual RIF as the LET increases. RIF numbers for 24 and 48 hours post-exposure led to the inverse trend, with more remaining RIF/Gy for higher LET (by 600 MeV/n Fe). This result suggests cells have more difficulty resolving RIF from higher LET as they the number DSB/RIF increases. Note that for most conditions, the variance of RIF/Gy was small within individual animals of the same strain and large between strains, suggesting a strong genetics component. Furthermore, we present our preliminary data from an ongoing study on human genetic associations with IR sensitivity. To address the human variability in responses to HZE particle irradiation in a maximally comprehensive manner, we are in the process of collecting and isolating primary blood mononuclear cells from 768 healthy subjects of European descent, 18-75 years of age, 50/50 male/female distribution. We have analyzed 53BP1+ RIF formation as well as oxidative stress and cell death in primary cells from 192 subjects in response to the same HZE particles as used in mice: 600 MeV/n Fe, 350 MeV/n Ar and 350 MeV/n Si, 1.1 and 3 particles/100m2, 4 and 24 hours after irradiation. We will next complete the quantification of HZE particle-induced DNA and cellular damage in the remaining subjects and compare it to their responses to low-LET irradiation. Finally, we will perform GWAS analysis to identify human genomic associations with IR sensitivity and potential targets for biomarker development.

High-LET radiation↗
NASA NTRS2021

Thermoelectric System Economics - The Apex: New Paradigms in Manufacturing and Interface Performance Relationships Driving System Cost Optimizations

Thermoelectric energy recovery systems require cost-optimized designs with high thermal and thermoelectric (TE) performance to surmount common commercialization barriers controlling the acceptance of thermoelectric generator (TEG) systems. Recent work has addressed this requirement with new analytic tools and paradigms that allow integrated TEG cost-performance analysis and optimization. New work herein has identified the existence of optimized TE element design (i.e., TE element length) for minimizing TEG cost and provides design guidelines associated with critical thermal and electrical contact resistance effects and TE manufacturing sensitivities. Once optimum hot-side heat flux criteria are satisfied, this work highlights the tradeoffs between interface resistance effects and manufacturing cost effects in determining optimum-cost TE element lengths, and then quantifies the increase in optimum-cost TE lengths as manufacturing costs become more sensitive to TE element lengths. Optimized TE element design criteria and key non-dimensional design parameters (i.e., [𝐶′′′LTE/𝐶′′], [TE/con], [con/(TE,aveLTE)]) driving the design are presented and explained showing the interdependencies between manufacturing cost parameters and thermal and electrical interface impacts on integrated TE cost-performance analysis and design. Comprehensive TEG system cost-performance relationships clearly demonstrate the two parameters that most greatly impact the TEG system cost are heat exchanger costs ($/(W/K)) and TE hot side heat flux. Reducing heat exhanger cost from $1/(W/K) to $0.5/(W/K) can decrease TEG system cost by $2/W to $4/W depending on TE hot side heat fluxes from 4-10 W/cm2. The impact of TE hot side heat flux on TEG system cost is larger; reducing TE system cost by factors of 2-4 as TE hot side heat flux increases from 4 W/cm2 to high levels around 18 W/cm2. The levels of thermal contact resistance and electrical contact resistance required to even approach the critical TEG system cost level of $1/W are characterized by con = 1.0 x 10-10 -m2 and r = 0.1, respectively. This not only lowers TEG costs, but it also makes the TEG system costs less sensitive to TE manufacturing dependences on TE element length. New design paradigms and relationships create holistic, integrated TE performance-cost models that enhance understanding of crucial interrelationships between component costs, TE design parameters and material properties, heat exchanger design parameters, interfacial heat flux, and now thermal and electrical interface effects in minimizing TEG system costs.

Hendricks, Terry J.↗
DOE OSTI2020

Capital Costs for Dual-Use Photovoltaic Installations: 2020 Benchmark for Ground-Mounted PV Systems with Pollinator-Friendly Vegetation, Grazing, and Crops

This report analyzes the installed system cost of various multi-land use PV system configurations. We used PV system bottom-up cost model accounting for all system and project-development costs incurred during the installation to model the costs for conventional PV systems, PV systems co-located with sheep grazing, PV systems co-located with pollinator friendly fields and PV systems co-located with crops. We also conducted extensive sensitivity analysis around different PV system design parameters given the nascent stage of this industry.

14 SOLAR ENERGY↗
DOE OSTI2021

Simulation of hardened cement degradation and estimation of uncertainty in predicted failure times with peridynamics

Modeling the degradation of cement-based infrastructure due to aqueous environmental conditions continues to be a challenge. In order to develop a capability to predict concrete infrastructure failure due to chemical degradation, here we created a chemomechanical model of the effects of long-term water exposure on cement paste. The model couples the mechanical static equilibrium balance with reactive–diffusive transport and incorporates fracture and failure via peridynamics (a meshless simulation method). The model includes fundamental aspects of degradation of ordinary Portland cement (OPC) paste, including the observed softening, reduced toughness, and shrinkage of the cement paste, and increased reactivity and transport with water induced degradation. This version of the model focuses on the first stage of cement paste decalcification, the dissolution of portlandite. Given unknowns in the cement paste degradation process and the cost of uncertainty quantification (UQ), we adopt a minimally complex model in two dimensions (2D) in order to perform sensitivity analysis and UQ. We calibrate the model to existing experimental data using simulations of common tests such as flexure, compression and diffusion. Then we calculate the global sensitivity and uncertainty of predicted failure times based on variation of eleven unique and fundamental material properties. We observed particularly strong sensitivities to the diffusion coefficient, the reaction rate, and the shrinkage with degradation. Also, the predicted time of first fracture is highly correlated with the time to total failure in compression, which implies fracture can indicate impending degradation induced failure; however, the distributions of the two events overlap so the lead time may be minimal. Extension of the model to include the multiple reactions that describe complete degradation, viscous relaxation, post-peak load mechanisms, and to three dimensions to explore the interactions of complex fracture patterns evoked by more realistic geometry is straightforward and ongoing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling and Analysis of a Thermophotovoltaic Integrated Self-Powered Furnace

This work investigates the energy efficiency and carbon reduction potential of self-powered residential building heating equipment using a thermodynamic modeling approach. An integrated thermophotovoltaic power module and residential scale furnace system (40,000 Btu/h) were modeled and studied in detail to assess the influence of different design configurations on primary energy efficiency. Operational characteristics such as total power generation, electrical efficiency, and heat recovery were examined in a self-powered system configuration. A sensitivity analysis was conducted to determine the influence of the electric grid’s carbon dioxide footprint (carbon intensity) and the cost of electricity on the environmental, as well as the economic, benefit associated with the self-powered configuration. Compared with a traditional furnace powered by an electric grid at a carbon intensity of 0.5 kg CO 2eq /kWh EL , the self-powered furnace was shown to decrease the annual carbon dioxide emissions by approximately 550 kg (~75% reduction), while also saving more than USD 200 in utility expenses, annually. Additionally, the carbon emission reduction potential of blending different concentrations of hydrogen in natural gas fuel was also studied.

14 SOLAR ENERGY↗
NASA NTRS1988

Recent developments in structural sensitivity analysis

Recent developments are reviewed in two major areas of structural sensitivity analysis: sensitivity of static and transient response; and sensitivity of vibration and buckling eigenproblems. Recent developments from the standpoint of computational cost, accuracy, and ease of implementation are presented. In the area of static response, current interest is focused on sensitivity to shape variation and sensitivity of nonlinear response. Two general approaches are used for computing sensitivities: differentiation of the continuum equations followed by discretization, and the reverse approach of discretization followed by differentiation. It is shown that the choice of methods has important accuracy and implementation implications. In the area of eigenproblem sensitivity, there is a great deal of interest and significant progress in sensitivity of problems with repeated eigenvalues. In addition to reviewing recent contributions in this area, the paper raises the issue of differentiability and continuity associated with the occurrence of repeated eigenvalues.

Haftka, Raphael T.↗
NASA NTRS2016

Adjoint-Based Aerodynamic Design of Complex Aerospace Configurations

An overview of twenty years of adjoint-based aerodynamic design research at NASA Langley Research Center is presented. Adjoint-based algorithms provide a powerful tool for efficient sensitivity analysis of complex large-scale computational fluid dynamics (CFD) simulations. Unlike alternative approaches for which computational expense generally scales with the number of design parameters, adjoint techniques yield sensitivity derivatives of a simulation output with respect to all input parameters at the cost of a single additional simulation. With modern large-scale CFD applications often requiring millions of compute hours for a single analysis, the efficiency afforded by adjoint methods is critical in realizing a computationally tractable design optimization capability for such applications.

Nielsen, Eric J.↗
NASA NTRS1972

Determination of aerothermodynamic environment uncertainties with application to space shuttle vehicles

In an effort to minimize the cost of the thermal protection system (TPS) for space shuttles, an analysis is made of environmental uncertainties. The basic categories of these uncertainties include aerodynamic heating, trajectory dispersions, atmospheric variations, and vehicle attitude variations. Also discussed are TPS design sensitivity to environmental uncertainties, and uncertainty profiles. Preliminary results indicate moderate TPS cost for a high confidence level environment may be obtained.

Scottoline, C. A.↗
DOE OSTI2025

Microreactor Optimization Using Simulation And Economics (mouse)

Microreactor Optimization Using Simulation and Economics (MOUSE) is a tool that integrates both nuclear microreactor design and reactor economics to provide comprehensive evaluations and optimizations. This tool enables stakeholders to explore the interplay between technical and economic variables, guiding them towards effective and competitive microreactor solutions. For the reactor core simulations, MOUSE leverages the OpenMC Monte Carlo Particle Transport Code to perform detailed core simulations for various microreactor designs. The included OpenMC models are 2D core designs of a Liquid Metal Thermal Microreactor (LMTR), a Gas-Cooled TRISO-Fueled Microreactor (GCMR), and a Heat Pipe Microreactor. Beyond core design, MOUSE includes simplified calculations for: - Calculating the masses of heat exchangers within the system. - Mechanical power of pumps. - Estimating the area occupied by various buildings within the nuclear plant. For the economic analysis, MOUSE provides detailed bottom-up cost estimates, encompassing a wide range of costs including preconstruction costs, direct costs, indirect costs, training costs, financial costs, operation & maintenance (O&M) costs, and fuel costs. These cost estimations are developed using data from the MARVEL project and additional literature sources, enabling the calculation of total capital costs and levelized cost of energy for both first-of-a-kind and nth-of-a-kind microreactors. MOUSE also enables analysis of the cost drivers and competitiveness in the electricity market. MOUSE allows users to modify a wide array of technical and economic parameters to evaluate different scenarios and their impacts. Examples of these parameters include: Fuels, coolants, or reflector materials Enrichment levels Control drum materials and geometry Fuel pin geometry and materials Moderator pin geometry and materials Reactor core and reflector dimensions Packing factor for the TRISO particles Nuclear reactor power and reactor burnup Number of sensors Shielding thickness Reactor vessel and guard vessel dimensions Operational staff requirements Number of emergency shutdowns Levelization period Interest rate Construction duration Since MOUSE is powered by the WATTS toolkit, it supports optimization studies, parametric analyses, and uncertainty calculations/propagation. The optimization techniques enable users to identify optimal design and economic configurations. The parametric analysis tools allow users to explore the sensitivity of various parameters, while uncertainty propagation helps quantify the impact of uncertainties on overall performance and cost. User Interface and Workflow: Currently, MOUSE is a command-line-based tool. Users can input various reactor design or economic parameters, modify the designs, run simulations, and visualize results through comprehensive data visualization and reporting capabilities. The typical workflow involves setting up the reactor model, defining economic parameters, running simulations, and analyzing the results to make informed decisions. By combining advanced design calculations with detailed economic modeling, MOUSE provides a robust framework for optimizing nuclear microreactor technologies, enhancing their competitiveness, and guiding stakeholders towards innovative and cost-effective solutions.

Hanna, Botros [Idaho National Laboratory (INL), Id↗
DOE OSTI2021

Nano-Engineered Catalyst Supported on Ceramic Hollow Fibers for the Utilization of CO 2 in Dry Reforming to Produce Syngas

The objective of this project was to develop a novel catalytic reactor containing nano-engineered catalysts for the utilization of CO 2 (captured from coal-fired power plants and other CO 2 emitting sources) in dry methane reforming (DMR) (CO 2 + CH 4 → 2 H 2 + 2 CO) to produce synthesis gas (syngas). The technology aims to reduce CO2 emissions by developing beneficial uses for CO 2 from coal-fired power plants. It also offers an alternative to mitigate CO 2 emissions in areas where geologic storage may not be an optimal solution and/or utilization could significantly offset the costs of carbon capture and sequestration. The nano-engineered Ni-based catalyst was prepared by atomic layer deposition (ALD). The Ni particles were as small as ~2-4 nm. The nano-engineered catalyst showed CH 4 conversion >95%, H 2 /CO ratio in the range of 0.7-1.0, and CH 4 reforming rate as high as 2,500 L/h/gNi at 850 ºC and pressure of 15-25 psia. The Ni-based ALD catalyst also showed good stability in DMR reaction during a 200-h continuous operation at 850 °C. This is due to strong bonding between the nanoparticles and substrates since the Ni nanoparticles were chemically bonded to the substrate during the ALD process. The high thermal stability maintains the high dispersion of Ni nanoparticles, which can inhibit coke formation because their step edges are small enough to limit carbon nucleation and growth. Technoeconomic analysis (TEA) indicates the levelized cost of syngas (LCOS) is $172/ton with our technology, which is lower than the equivalent (molar) cost of hydrogen produced by steam methane reforming (SMR) or autothermal reforming (ATR). The major operating cost is natural gas feed and fuel, and the levelized cost is highly sensitive to the price of natural gas and relatively insensitive to the CAPEX. Revenues from syngas could have a significant impact on the net cost of electricity (COE), depending on the cost of natural gas and the selling price of syngas, estimated at $36 per MWh if the syngas were sold at $195 per ton. Following DOE NETL’s guidance, a lifecycle analysis (LCA) was conducted to compare with SMR. The functional unit for the basis of comparison was defined as 1kg carbon monoxide in the product stream. The global warming potential (GWP) of our process was found to be 40% lower than the state-of-the-art SMR process. The sensitivity analysis confirms the emissions are most sensitive to the natural gas fuel requirements to deliver heat to the process.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

More buck-per-shot: Why learning trumps mitigation in noisy quantum sensing

Quantum sensing is one of the most promising applications for quantum technologies. However, reaching the ultimate sensitivities enabled by the laws of quantum mechanics can be a challenging task in realistic scenarios where noise is present. While several strategies have been proposed to deal with the detrimental effects of noise, these come at the cost of an extra shot budget. Given that shots are a precious resource for sensing – as infinite measurements could lead to infinite precision – care must be taken to truly guarantee that any shot not being used for sensing is actually leading to some metrological improvement. In this work, we study whether investing shots in error-mitigation, inference techniques, or combinations thereof, can improve the sensitivity of a noisy quantum sensor on a (shot) budget. We present a detailed bias–variance error analysis for various sensing protocols. Our results show that the costs of zero-noise extrapolation techniques outweigh their benefits. We also find that pre-characterizing a quantum sensor via inference techniques leads to the best performance, under the assumption that the sensor is sufficiently stable.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Integrated Crewed Mars Mission Analysis, Part II: The Trajectory Strikes Back

Crewed missions to Mars present a challenging problem involving strong interactions between a variety of spacecraft systems. Design and architecture decisions made by one system can have powerful implications for another. Siloed subsystem development and optimization efforts are unlikely to generate optimal results for the integrated system and may lead to counterproductive investments at the mission and system level. Mismatched assumptions between different subsystems can also negatively impact the final result. Integrated systems analysis, trade studies, and sensitivity analysis are a critical element of successful Mars mission design. Previous work examined the linkages between Environmental Control and Life Support System (ECLSS) loop closure, food water content, spares Probability of Sufficiency (POS), and other factors by performing an integrated mass and cost assessment of a variety of Mars habitat and transportation system designs. This paper expands upon that work by evaluating the impact of mission duration, trajectory, and propulsion technology alongside key habitat variables. Transportation system and trajectory design decisions have enormous impacts on overall system mass, and the impacts of those decisions are themselves sensitive to the mass of the habitat that is being transported. This paper examines a variety of mission cases and evaluates total departure mass for each case. An estimate of relative costs for specific cases is also provided. The results are discussed, with an emphasis on the sensitivity of mass, cost, and other figures of merit to key parameters. Interactions and dependencies between various decisions, particularly those that relate to technology investments, are also highlighted. Overall, the various elements, systems, and subsystems required to support human spaceflight should not be optimized and evaluated in isolation, but instead should be analyzed as part of an integrated system. This paper demonstrates how integrated analysis can improve system understanding and lead to more optimal and effective crewed exploration systems.

Human Spaceflight↗
NASA NTRSDate not supplied

Integrated Crewed Mars Mission Analysis, Part II: The Trajectory Strikes Back

Crewed missions to Mars present a challenging problem involving strong interactions between a variety of spacecraft systems. Design and architecture decisions made by one system can have powerful implications for another. Siloed subsystem development and optimization efforts are unlikely to generate optimal results for the integrated system and may lead to counterproductive investments at the mission and system level. Mismatched assumptions between different subsystems can also negatively impact the final result. Integrated systems analysis, trade studies, and sensitivity analysis are a critical element of successful Mars mission design. Previous work examined the linkages between Environmental Control and Life Support System (ECLSS) loop closure, food water content, spares Probability of Sufficiency (POS), and other factors by performing an integrated mass and cost assessment of a variety of Mars habitat and transportation system designs. This paper expands upon that work by evaluating the impact of mission duration, trajectory, and propulsion technology alongside key habitat variables. Transportation system and trajectory design decisions have enormous impacts on overall system mass, and the impacts of those decisions are themselves sensitive to the mass of the habitat that is being transported. This paper examines a variety of mission cases and evaluates total departure mass for each case. An estimate of relative costs for specific cases is also provided. The results are discussed, with an emphasis on the sensitivity of mass, cost, and other figures of merit to key parameters. Interactions and dependencies between various decisions, particularly those that relate to technology investments, are also highlighted. Overall, the various elements, systems, and subsystems required to support human spaceflight should not be optimized and evaluated in isolation, but instead should be analyzed as part of an integrated system. This paper demonstrates how integrated analysis can improve system understanding and lead to more optimal and effective crewed exploration systems.

Human Spaceflight↗
DOE OSTI2024

Core Design Optimization of the Westinghouse Lead Fast Reactor

Westinghouse is pursuing an advanced Nuclear Power Plant design based on Lead Fast Reactor (LFR) technology for global commercialization. To achieve an optimal combination of key attributes, such as safety, sustainability, and economic competitiveness, Westinghouse and ANL partnered in developing and applying a formalized core design optimization strategy. An LFR analysis workflow was developed to automate a suite of reactor physics, fuels performance, safety, and economics simulations on a selected LFR concept. The workflow streamlines analysis of a wide range of LFR designs with different dimensions and fuel types to assess their viability and economic performance, significantly reducing human processing time and risks of processing errors. The LFR optimization exercise was defined, resulting in selection of the design constraints (geometric, neutronics, thermo-mechanical, safety, thermal-hydraulics, and economics) and performance metrics researched (minimization of both the fuels LCOE and the first core inventory cost). A total of 14 varied design parameters were considered, including assembly dimensions, coolant temperature, and enrichment distribution throughout the core. The LFR analysis workflow was connected to DAKOTA for sensitivity and optimization analyses. Due to the extremely large size of the potential LFR optimization solution space relative to the computing time required to characterize one LFR solution, a multi-stage optimization approach was proposed to breakdown the problem into several stages with more reasonable sizes. This optimization approach enabled finding various viable core solutions with different cost tradeoffs that were considered by Westinghouse and justify selection of a smaller core with multi-batch 2-year cycle length.

Stauff, Nicolas E.↗
NASA NTRS2013

Characterizing Wheel-Soil Interaction Loads Using Meshfree Finite Element Methods: A Sensitivity Analysis for Design Trade Studies

A wheel experiencing sinkage and slippage events poses a high risk to planetary rover missions as evidenced by the mobility challenges endured by the Mars Exploration Rover (MER) project. Current wheel design practice utilizes loads derived from a series of events in the life cycle of the rover which do not include (1) failure metrics related to wheel sinkage and slippage and (2) performance trade-offs based on grouser placement/orientation. Wheel designs are rigorously tested experimentally through a variety of drive scenarios and simulated soil environments; however, a robust simulation capability is still in development due to myriad of complex interaction phenomena that contribute to wheel sinkage and slippage conditions such as soil composition, large deformation soil behavior, wheel geometry, nonlinear contact forces, terrain irregularity, etc. For the purposes of modeling wheel sinkage and slippage at an engineering scale, meshfree nite element approaches enable simulations that capture su cient detail of wheel-soil interaction while remaining computationally feasible. This study implements the JPL wheel-soil benchmark problem in the commercial code environment utilizing the large deformation modeling capability of Smooth Particle Hydrodynamics (SPH) meshfree methods. The nominal, benchmark wheel-soil interaction model that produces numerically stable and physically realistic results is presented and simulations are shown for both wheel traverse and wheel sinkage cases. A sensitivity analysis developing the capability and framework for future ight applications is conducted to illustrate the importance of perturbations to critical material properties and parameters. Implementation of the proposed soil-wheel interaction simulation capability and associated sensitivity framework has the potential to reduce experimentation cost and improve the early stage wheel design proce

terramechanics↗