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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
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 OSTI2015

Validation of a reduced-order jet model for subsonic and underexpanded hydrogen jets

Much effort has been made to model hydrogen releases from leaks during potential failures of hydrogen storage systems. A reduced-order jet model can be used to quickly characterize these flows, with low computational cost. Notional nozzle models are often used to avoid modeling the complex shock structures produced by the underexpanded jets by determining an “effective” source to produce the observed downstream trends. In our work, the mean hydrogen concentration fields were measured in a series of subsonic and underexpanded jets using a planar laser Rayleigh scattering system. Furthermore, we compared the experimental data to a reduced order jet model for subsonic flows and a notional nozzle model coupled to the jet model for underexpanded jets. The values of some key model parameters were determined by comparisons with the experimental data. Finally, the coupled model was also validated against hydrogen concentrations measurements for 100 and 200 bar hydrogen jets with the predictions agreeing well with data in the literature.

08 HYDROGEN↗
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 OSTI2016

The AskIT Service Desk: A Model for Improving Productivity and Reducing Costs

This was prepared for the business process improvement presentation to the Department of Energy. Los Alamos National Laboratory provides a single point of contact, the AskIT Service Desk, to address issues that impact customer productivity. At the most basic level, what customers want is for their calls to be received, to get a response from a knowledgeable analyst, and to have their issues resolved and their requests fulfilled. Providing a centralized, single point of contact service desk makes initiating technical or business support simple for the customer and improves the odds of immediately resolving the issue or correctly escalating the request to the next support level when necessary. Fulfilling customer requests through automated workflow also improves customer productivity and reduces costs. Finally, customers should be provided the option to solve their own problems through easy access to self-help resources such as frequently asked questions (FAQs) and how-to guides. To accomplish this, everyone who provides and supports services must understand how these processes and functions work together. Service providers and those who support services must “speak the same language” and share common objectives. The Associate Directorate for Business Innovation (ADBI) began the journey to improve services by selecting a known service delivery framework (Information Technology Infrastructure Library, or ITIL). From this framework, components that contribute significant business value were selected.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
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↗
DOE OSTI2024

Representative Period Selection for Robust Capacity Expansion Planning in Low-carbon Grids

With the increasing urgency to decarbonize power systems, while mitigating extreme events, capacity expansion models can play a vital role in reliably planning the expansion of power systems and facilitating the integration of renewable energy sources. Optimizing capacity expansion generally involves selecting surrogate representative days from forecasts of load and the generation profiles of variable renewable energy resources. To properly select those representative days, we propose a novel input-based approach in combination with the k-means clustering algorithm that utilize three unique operational inputs: load shedding, renewable curtailment, and transmission congestion. The proposed method allows for more robust and cost-effective capacity planning. The method is validated using a capacity expansion model and a production cost model based on California Independent System Operator (CAISO)'s decarbonization goals, and results in reduced costs and drastically lower load shedding.

Anderson, Osten P.↗
DOE OSTI2019

Update on Evaluation of Steam Cycle Upgrades to Improve the Competitiveness of U.S. Coal Power Plants

Under an award issued by the U.S. Department of Energy (DE-FE0031535), the Electric Power Research Institute (EPRI) is leading project to examine the technical and economic feasibility of a series of steam cycle upgrades to the two most prevalent types of U.S. coal power plants (including both subcritical and supercritical cycle configurations). The retrofit upgrade options are focused on evaluating increasing main steam and reheat steam temperatures from 1000°F (538°C) to hotter temperatures, ranging from ultra-supercritical (USC) (i.e., 1100°F or 593°C) to advanced USC (AUSC) conditions (≥1300° or 704°C) while maintaining steam pressures at their original values. By maintaining the original operating steam pressures as well as the original boiler and furnace enclosure envelopes, we aim to minimize the modifications required to the existing power plant, while still providing a significant improvement in heat rate. A unique aspect of this study is that the economic value of the heat rate improvement of each technically feasible option will be determined by detailed modeling of unit dispatch, over the remaining future plant life, in several regional power markets, using EPRI’s US-REGEN model. The capital cost estimates will be compared to the increased revenue estimated by the dispatch modeling to determine the overall economic attractiveness of each upgrade option. The results of this study have the potential to be applicable at up to 80% of the existing U.S. coal-fired power generation fleet. The project team, led by the Electric Power Research Institute, has completed the technical feasibility evaluation, and is currently executing the unit dispatch and capital cost evaluation portions of the work scope. This will describe the motivation for the project, explain the project’s structure and schedule, and provide details on the work scope and preliminary results of the technical feasibility evaluation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

Centipod WEC, Advanced Controls, Baseline LCOE

Project baseline levelized cost of energy (LCOE) model for the Centipod WEC containing annual energy production (AEP) data, a cost breakdown structure (CBS), model documentation, and the LCOE content model. This baseline was built for comparison with the resultant LCOE model, built after implementation of the model predictive control (MPC) controller.

16 TIDAL AND WAVE POWER↗
NASA NTRSDate not supplied

On the Application of an Actuator Line Model for Rotorcraft Outwash Predictions

As the next generation of Vertical Take-Off and Landing (VTOL) vehicles develops and the VTOL industry makes significant progress in utilizing them for public transportation, it is crucial to have validated and cost-effective computational models accessible to both industry professionals and academics in the rotorcraft community. This study investigates the implementation of a new actuator line model within NASA’s OVERFLOW computational fluid dynamics (CFD) solver, with a focus on predicting rotorcraft outwash. This reduced-order rotor model was developed to provide reasonably accurate outwash predictions while reducing computational costs compared to traditional blade-resolved CFD simulations. To validate the actuator line model for outwash predictions, the model was compared against existing experimental data across three validation cases: single rotor Out-of-Ground Effect (OGE), single rotor In-Ground Effect (IGE), and tandem rotor IGE. All three cases were based on the rotor geometry and configuration of the CH-47D. To evaluate the feasibility and advantages of using an actuator line model for outwash predictions the results were compared to a series of high-fidelity blade-resolved CFD simulations as well as comprehensive analyses simulations based on CHARM predictions. The results of this study demonstrate the feasibility of leveraging this new actuator line model for reasonably accurate outwash predictions. The outwash results obtained from the actuator line model closely matched those from high-fidelity blade-resolved simulations while significantly reducing the overall computational costs of the simulations. Results from this study further demonstrated the feasibility of using CHARM for efficient, and reasonably accurate time-averaged outwash predictions for multi-rotor configurations.

CFD↗