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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Life cycle cost assessment of future low heat rejection engines

The Adiabatic Diesel Engine Component Development (ADECD) represents a project which has the objective to accelerate the development of highway truck engines with advanced technology aimed at reduced fuel consumption. The project comprises three steps, including the synthesis of a number of engine candidate designs, the coupling of each with a number of systems for utilizing exhaust gas energy, and the evaluation of each combination in terms of desirability. Particular attention is given to the employed evaluation method and the development of this method. The objective of Life Cycle Cost (LCC) evaluation in the ADECD program was to select the best from among 42 different low heat rejection engine (LHRE)/exhaust energy recovery system configurations. The LCC model is discussed along with a maintenance cost model, the evaluation strategy, the selection of parameter ranges, and a full factorial analysis.

Petersen, D. R.↗
DOE OSTI2025

EverBESS

SF-25-113 This software is a website for the EverBESS model. This model examines the cost and environmental impacts related to end-of-life management of battery energy storage systems. Users input their system's specifications and the model returns estimates for the costs of decommissioning, transporting, and recycling the system.

Elias, Jakob [Argonne National Laboratory (ANL), A↗
DOE OSTI2023

Measuring environmental and cost benefits of riparian buffers for drinking water production in a Midwest watershed

Here, this study focuses on the economic value and carbon benefits of riparian buffers in urban drinking water production. The impact of riparian buffers on the waterworks operation in the Raccoon River watershed was quantified using the following metrics: nitrate concentration, days of nitrate removal operation, material and energy cost (based on 17 years of historical records with a watershed model), regression, and cost analysis. The findings indicate that the presence of riparian buffers in agricultural land can substantially decrease nitrate concentration in the water intake of the waterworks during the crop-growing season: 19% in April, 9% in May, and 11% in June. These reductions mean less nitrate treatment of the plant intake flow: 23% in April, 12% in May, and 3% in June. These changes lead to significant resource savings: 425 metric tons of sodium chloride (NaCl), 147 810 kWh of electricity, 253 metric tons of powdered activated carbon, and 20.8 million liters of fresh water. The buffers would also reduce greenhouse gas emissions by 86.9 metric tons (CO 2 equivalent) in 17 years. The total cost saving was estimated at $\$$327 326, with the highest potential savings in May ($\$$215 100), followed by April ($\$$65 465), and June ($\$$46 761). When factoring in buffer installation, cropland loss, nitrate removal, and cost associated with buffer harvest for biofuel in an established biomass market, the benefit to the entire watershed community would be $\$$2.63 million annually. The results underscore the significant cost benefits and environmental benefits associated with cropland riparian buffers in a watershed community. The approach employed in this study holds promise for assessing riparian buffer benefits in other watersheds, contributes to an understanding of sustainable water management practices, and provides a basis for decision making in a wide range of agricultural regions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Evaluation of Thompson-type trend and monthly weather data models for corn yields in Iowa, Illinois, and Indiana

An evaluation was made of Thompson-Type models which use trend terms (as a surrogate for technology), meteorological variables based on monthly average temperature, and total precipitation to forecast and estimate corn yields in Iowa, Illinois, and Indiana. Pooled and unpooled Thompson-type models were compared. Neither was found to be consistently superior to the other. Yield reliability indicators show that the models are of limited use for large area yield estimation. The models are objective and consistent with scientific knowledge. Timely yield forecasts and estimates can be made during the growing season by using normals or long range weather forecasts. The models are not costly to operate and are easy to use and understand. The model standard errors of prediction do not provide a useful current measure of modeled yield reliability.

French, V.↗
NASA NTRSDate not supplied

A Simplified Model of VIPER Thermal Management System. Part II: Integrated Vehicle

NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) thermal management system (TMS) relies on four loop heat pipes (LHPs) to transport electronic waste heat to the vehicle cooling radiative surface and avoid overheating. The TMS has also ten constant conductance heat pipes (CCHPs) dedicated to balance the thermal load within the internal environment where the avionics boxes are mounted, also called warm electronic box (WEB), and to transport the heat from two of the science payload instruments. The TMS also uses two thermal straps to thermally link the batteries to the WEB. These thermal components, in addition to heaters, thermostat, multi-layer insulation (MLIs), and isolators forms the core of the VIPER TMS. The complex heat transport balance managed by the TMS is challenging to characterize and model. The more fidelity and granularity of a model, the more costly the computational resources needed and the longer the simulation and modeling time. When the priority is to provide quick but reliable assessments of the thermal performance or real time thermal feedback for training of console operators, simplified modeling tools are needed. To satisfy that need, this paper describes the effort to develop and correlate a model of VIPER TMS based on control volume approach. The correlation effort in particular focuses on hibernation, cold thermal balance, and hot thermal balance data from the integrated vehicle thermal vacuum (TVAC) test. Thus, the correlated model captures the heat leaks during hibernations and the performance at two extremes, bounding, operating scenarios.

Loop Heat Pipe↗
NASA NTRSDate not supplied

A Simplified Model of VIPER Thermal Management System. Part II: Integrated Vehicle

NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) thermal management system (TMS) relies on four loop heat pipes (LHPs) to transport electronic waste heat to the vehicle cooling radiative surface and avoid overheating. The TMS has also ten constant conductance heat pipes (CCHPs) dedicated to balance the thermal load within the internal environment where the avionics boxes are mounted, also called warm electronic box (WEB), and to transport the heat from two of the science payload instruments. The TMS also uses two thermal straps to thermally link the batteries to the WEB. These thermal components, in addition to heaters, thermostat, multi-layer insulation (MLIs), and isolators forms the core of the VIPER TMS. The complex heat transport balance managed by the TMS is challenging to characterize and model. The more fidelity and granularity of a model, the more costly the computational resources needed and the longer the simulation and modeling time. When the priority is to provide quick but reliable assessments of the thermal performance or real time thermal feedback for training of console operators, simplified modeling tools are needed. To satisfy that need, this paper describes the effort to develop and correlate a model of VIPER TMS based on control volume approach. The correlation effort in particular focuses on hibernation, cold thermal balance, and hot thermal balance data from the integrated vehicle thermal vacuum (TVAC) test. Thus, the correlated model captures the heat leaks during hibernations and the performance at two extremes, bounding, operating scenarios.

Thermal Modeling↗
DOE OSTI2025

An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change

Abstract. This study investigated the computational benefits of using multi-fidelity statistical estimation (MFSE) algorithms to quantify uncertainty in the mass change of Humboldt Glacier, Greenland, between 2007 and 2100 using a single climate change scenario. The goal of this study was to determine whether MFSE can use multiple models of varying cost and accuracy to reduce the computational cost of estimating the mean and variance of the projected mass change of a glacier. The problem size and complexity were chosen to reflect the challenges posed by future continental-scale studies while still facilitating a computationally feasible investigation of MFSE methods. When quantifying uncertainty introduced by a high-dimensional parameterization of the basal friction field, MFSE was able to reduce the mean-squared error in the estimates of the statistics by well over an order of magnitude when compared to a single-fidelity approach that only used the highest-fidelity model. This significant reduction in computational cost was achieved despite the low-fidelity models used being incapable of capturing the local features of the ice-flow fields predicted by the high-fidelity model. The MFSE algorithms were able to effectively leverage the high correlation between each model's predictions of mass change, which all responded similarly to perturbations in the model inputs. Consequently, our results suggest that MFSE could be highly useful for reducing the cost of computing continental-scale probabilistic projections of sea-level rise due to ice-sheet mass change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

End-to-End Trade-Space Analysis for Designing Constellation

Multipoint measurement missions can provide a significant advancement in science return and this science interest coupled with as many recent technological advances are driving a growing trend in exploring distributed architectures for future NASA missions. Distributed Spacecraft Missions (DSMs) leverage multiple spacecraft to achieve one or more common goals. In particular, a constellation is the most general form of DSM with two or more spacecraft placed into specific orbit(s) for the purpose of serving a common objective (e.g., CYGNSS). Because a DSM architectural trade-space includes both monolithic and distributed design variables, DSM optimization is a large and complex problem with multiple conflicting objectives. Over the last two years, our team has been developing a Trade-space Analysis Tool for Constellations (TAT-C), implemented in common programming languages for pre-Phase A constellation mission analysis. By evaluating alternative mission architectures, TAT-C seeks to minimize cost and maximize performance for pre-defined science goals. This presentation will describe the overall architecture of TAT-C including: a User Interface (UI) at several levels of details and user expertise; Trade-space Search Requests that are created from the Science requirements gathered by the UI and validated by a Knowledge Base; a Knowledge Base to compare the current requests to prior mission concepts to potentially prune the trade-space; a Trade-space Search Iterator which, with inputs from the Knowledge Base, and, in collaboration with the Orbit & Coverage, Reduction & Metrics, and Cost& Risk modules, generates multiple potential architectures and their associated characteristics. TAT-C leverages the use of the Goddard Mission Analysis Tool (GMAT) to compute coverage and ancillary data, modeling orbits to balance accuracy and performance. The current version includes uniform and non-uniform Walker constellations as well as Ad-Hoc and precessing constellations, and its cost model represents an aggregate model consisting of Cost Estimating Relationships (CERs) from widely accepted models. The current GUI automatically generates graphics representing metrics such as average revisit time or coverage as a function of cost. The end-to-end system will be demonstrated as part of the presentation.

Mission Desig↗
NASA NTRS2016

Trade-Space Analysis Tool for Constellations (TAT-C)

Traditionally, space missions have relied on relatively large and monolithic satellites, but in the past few years, under a changing technological and economic environment, including instrument and spacecraft miniaturization, scalable launchers, secondary launches as well as hosted payloads, there is growing interest in implementing future NASA missions as Distributed Spacecraft Missions (DSM). The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. In this first version of our Trade-space Analysis Tool for Constellations (TAT-C), we are investigating questions such as: How many spacecraft should be included in the constellation? Which design has the best costrisk value? The main goals of TAT-C are to: Handle multiple spacecraft sharing a mission objective, from SmallSats up through flagships, Explore the variables trade space for pre-defined science, cost and risk goals, and pre-defined metrics Optimize cost and performance across multiple instruments and platforms vs. one at a time.This paper describes the overall architecture of TAT-C including: a User Interface (UI) interacting with multiple users - scientists, missions designers or program managers; an Executive Driver gathering requirements from UI, then formulating Trade-space Search Requests for the Trade-space Search Iterator first with inputs from the Knowledge Base, then, in collaboration with the Orbit Coverage, Reduction Metrics, and Cost Risk modules, generating multiple potential architectures and their associated characteristics. TAT-C leverages the use of the Goddard Mission Analysis Tool (GMAT) to compute coverage and ancillary data, streamlining the computations by modeling orbits in a way that balances accuracy and performance.TAT-C current version includes uniform Walker constellations as well as Ad-Hoc constellations, and its cost model represents an aggregate model consisting of Cost Estimating Relationships (CERs) from widely accepted models. The Knowledge Base supports both analysis and exploration, and the current GUI prototype automatically generates graphics representing metrics such as average revisit time or coverage as a function of cost.

Science Data Processing↗
NASA NTRS1993

Dynamic stall of an oscillating wing. Part 1: Evaluation of turbulence models

Unsteady flowfields of a two-dimensional oscillating wing are calculated using an implicit, finite-difference, Navier-Stokes numerical scheme using five widely used turbulence models. The objective of this study is to identify an appropriate turbulence model for accurate simulation of three-dimensional dynamic stall. Three unsteady flow conditions corresponding to attached flow, light-stall, and deep-stall of an oscillating wing experiment were chosen as test cases for computations. Results of unsteady airload hysteresis curves, harmonics of unsteady pressures, and instantaneous flow pictures are presented. Comparison of unsteady airloads with experiment show that all models are deficient in some sense and not a single model predicts all airloads consistently and in agreement with experiment for all flow conditions. For the attached flow condition, the Renormalization Group Theory (RNG), the Johnoson-King (J-K), and the Spalart-Allmaras (S-A) models have better performance. The Baldwin-Lomax (B-L) and the Baldwin-Barth (B-B) models fair poorly. At the light-stall condition, the results for the RNG, the J-K, and S-A models are in agreement with experiment for the upstroke but they all over predict the separation shown by the experiment and therefore have bigger hysteresis loops than experimental results. The B-B model results are also in good agreement for upstroke but have poor lift hysteresis for downstroke. It has superior drag and pitching-moment predictions. For deep-stall conditions, the airloads for the RNG, the B -B, and the S-A models have fair agreement with experiment, but the B-B model performed better at the extreme deep-stall condition. Overall, the RNG model provides significant improvement over the B-L model in all flow regimes with no additional computational cost. The Baldwin-Barth model is the most expensive of the models considered here, costing about 2.5 times that of the Baldwin-Lomax model. Finally, a brief discussion of the effects of grid density, time-step size, and numerical dissipation on the unsteady solutions are also presented.

Srinivasan, G. R.↗
DOE OSTI2023

The Potential Role for New Nuclear in the U.S. Power System: A View from Electricity System Modelers

There are diverse views on the role nuclear power might play in a decarbonized energy system, with some vocal viewpoints suggesting nuclear should either have no role or that nuclear should be a key pillar. Here we present a perspective on the role of nuclear power based on our collective experience in modeling nuclear power within the decarbonized U.S. power systems. We summarize the costs of current reactor development projects, and compare their stated costs with the costs that our models indicate is necessary in order to see deployment of new nuclear. We also discuss aspects of new nuclear deployment that are not included in our models but can influence decisions about whether to invest in new nuclear capacity.

decarbonization↗
DOE OSTI2021

Adsorbate Free Energies from DFT-Derived Translational Energy Landscapes

Adsorption free energies are fundamental to surface chemistry and catalysis. Standard models combine some assumed analytical form of the translational potential energy surface, often parameterized against density functional theory (DFT) calculations, with an analytical expression for the resultant translational densities of states (DOS), free energy, and entropy. Here we compare the performance of such models against numerical evaluations of the DOS and thermodynamic functions derived from solutions to the translational Schrodinger equation. We compare results for a translational potential energy surface (PES) derived from nudged eleastic band calculations with those obtained from adsorbate rastering across a series of monatomic (O, S, C, N, H) and polyatomic (NH x ) adsorbates on (100) Pt and Au facets. We find that analytical models as commonly parameterized have mixed performance for describing the translational PES and that the consequences for computed free energies are modest but potentially significant in microkinetic models. Here, numerical solutions are possible for modest to no additional computational cost over analytical models and thus should be considered when reliable free energy estimates are needed or translational potential energy surfaces are available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Developing Data-Driven Synthetic Infrastructure Models for Resilience Analysis

Research on infrastructure resilience has produced promising methods to simulate and optimize complex networks to improve performance. However, restrictions on sharing infrastructure models and the steep cost of developing and maintaining infrastructure models presents a roadblock to adoption. To overcome this limitation, this research focuses on methods to create data-driven infrastructure models that will help improve infrastructure resilience and security. The analysis couples incomplete utility data, geospatial data, machine learning, and synthetic network generation methods to rapidly develop and update infrastructure models. The methods are validated using realistic utility models and site-specific data, with a focus on Puerto Rico due to its unique infrastructure challenges and available data. This research highlights promising opportunities for the use of synthetic network generation and machine learning to create infrastructure models when very little data is available. Results demonstrate that hybrid methods, which combine sparse utility data with synthetic models, can enhance model accuracy, and machine learning can predict model attributes using training data from other models. However, the complexity of infrastructure systems means that even minor changes in network connectivity can significantly impact simulation results. Resilience analysis using synthetic infrastructure models shows that while some system behaviors are preserved, the magnitude of disruptions may not be accurately represented, indicating the need for more research and validation before using synthetic models for critical infrastructure investment decisions. The framework outlined in this report represents a significant advance to infrastructure model development and could be applied to additional domains and sites. Future research will continue to streamline and validate methods to help reduce roadblocks to resilience analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Catalytic Fast Pyrolysis Oil Stand-Alone and Co-Hydroprocessing Case Studies: Design, Cost, and Sustainability Based on Process Model Predictions

Refined liquid fuels provide conveniences for road, rail, air, and marine transportation due to high energy density, ease of transport and storage, and existing production and distribution infrastructure. Biomass conversion technologies can help diversify and increase the supply of liquid fuels towards a more robust energy future. The backbone of such development must include reliable, high-volume biomass supply chains and efficient utilization of those resources. These activities, if pursued, will lead to rural infrastructure development and new jobs.

09 BIOMASS FUELS↗
DOE OSTI2023

Measure This, Not That: Pareto Optimal Trade-Offs between Model-Based Information Content and Measurements Cost

The slides present a novel convex optimization formulation to compute the best set of measurements for multi-response dynamical systems with asynchronous time steps that maximize the Fisher information content subject to budget constraints. The trace (A-optimality) or determinant (D-optimality) of the Fisher Information Matrix (FIM) quantifies the information content. The framework supports arbitrary (positive semi-definite) variance and covariances between every pair of responses and their time steps.

Wang, Jialu↗