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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

System Engineering & Integration (SE&I) In-Situ Resource Utilization (ISRU) Modeling and Analysis (SIMA)

NASA developed a flexible system modeling framework of integrated ISRU and ISRU related subsystem models: MAIT (Mission Analysis & Integration Tool) that enables point solutions, optimization, and/or parametric studies at the system level to predict mission architecture mass, power, and volume and provides accessible consolidated database that categorizes specific ISRU and ISRU related subsystem variables common between NASA & industry. Directly and indirectly addresses multiple STMD shortfalls: - ISRU-581 - ‘ISRU System Modeling’: Establish a modular end-to-end ISRU system modeling & analysis capability by leveraging and evolving prior, on-going, and future investments - More than an ISRU system modeling tool, MAIT integrates power, excavation, Environmental Control & Life Support System (ECLSS), Cryogenic Fluid Management (CFM) liquification, & compares surface ops & environments, to assist in the closure of other related ISRU shortfalls Adheres to governing NASA procedures for Models & Simulations (NASA-HDBK-7009) & AIAA standards for Mass Properties Control for Space Systems.

Modeling↗
NASA NTRS1992

Development of Test-Analysis Models (TAM) for correlation of dynamic test and analysis results

The primary objective of structural analysis of aerospace applications is to obtain a verified finite element model (FEM). The verified FEM can be used for loads analysis, evaluate structural modifications, or design control systems. Verification of the FEM is generally obtained as the result of correlating test and FEM models. A test analysis model (TAM) is very useful in the correlation process. A TAM is essentially a FEM reduced to the size of the test model, which attempts to preserve the dynamic characteristics of the original FEM in the analysis range of interest. Numerous methods for generating TAMs have been developed in the literature. The major emphasis of this paper is a description of the procedures necessary for creation of the TAM and the correlation of the reduced models with the FEM or the test results. Herein, three methods are discussed, namely Guyan, Improved Reduced System (IRS), and Hybrid. Also included are the procedures for performing these analyses using MSC/NASTRAN. Finally, application of the TAM process is demonstrated with an experimental test configuration of a ten bay cantilevered truss structure.

Angelucci, Filippo↗
NASA NTRS1986

Unified constitutive materials model development and evaluation for high-temperature structural analysis applications

Unified constitutive material models were developed for structural analyses of aircraft gas turbine engine hot section components with particular application to an isotropic material used for combustor liners. Differential forms of models independently developed were considered in this study. These models combine the interactions of time-dependent (creep) and time-independent (plasticity) inelastic behavior of a material. Predicted stress-strain responses from these models were evaluated against cyclic isothermal and nonisothermal test results for uniaxial specimens of a nickel-base superalloy. The unified models were implemented in a nonlinear structural analysis code. Two unique NASA Lewis test facilities were used in the evaluation of the models for complex geometry specimens and evaluation of advanced temperature and high-temperature strain measurement instrumentation. Predicted nonlinear structural responses from one of the models for a flat plate and a segment of a conventional combustor liner are presented.

Thompson, R. L.↗
NASA NTRS1980

A comprehensive analytical model of rotorcraft aerodynamics and dynamics. Part 1: Analysis development

Structural, inertia, and aerodynamic models were combined to form a comprehensive model of rotor aerodynamics and dynamics that is applicable to a wide range of problems and a wide class of vehicles. A digital computer program is used to calculate rotor performance, loads, and noise; helicopter vibration and gust response; flight dynamics and handling qualities; and system aeroelastic stability. The analysis is intended for use in the design, testing, and evaluation of rotors and rotorcraft, and to be a basis for further development of rotary wing theories.

Johnson, W.↗
NASA NTRS1974

Application of remote sensing for fishery resource assessment and monitoring

The author has identified the following significant results. A plot was drawn of the dolphin catch and the water discontinuities observed in the aerial photography. This plot was similar in format to the one made earlier on the white marlin catch relative to the water rips. Neither plot substantiates (as far as white marlin and dolphin are concerned) an opinion held by fishermen that better fishing may be found in the vicinity of the rips. Remotely inferred values for sea surface temperature, chlorophyll-a and turbidity were substituted for sea truth measurements in prediction models developed in previous analysis. Model performance, using the new values, was disappointing.

Savastano, K. J.↗
NASA NTRS1999

Solar Array Verification Analysis Tool (SAVANT) Developed

Modeling solar cell performance for a specific radiation environment to obtain the end-of-life photovoltaic array performance has become both increasingly important and, with the rapid advent of new types of cell technology, more difficult. For large constellations of satellites, a few percent difference in the lifetime prediction can have an enormous economic impact. The tool described here automates the assessment of solar array on-orbit end-of-life performance and assists in the development and design of ground test protocols for different solar cell designs. Once established, these protocols can be used to calculate on-orbit end-of-life performance from ground test results. The Solar Array Verification Analysis Tool (SAVANT) utilizes the radiation environment from the Environment Work Bench (EWB) model developed by the NASA Lewis Research Center s Photovoltaic and Space Environmental Effects Branch in conjunction with Maxwell Technologies. It then modifies and combines this information with the displacement damage model proposed by Summers et al. (ref. 1) of the Naval Research Laboratory to determine solar cell performance during the course of a given mission. The resulting predictions can then be compared with flight data. The Environment WorkBench (ref. 2) uses the NASA AE8 (electron) and AP8 (proton) models of the radiation belts to calculate the trapped radiation flux. These fluxes are integrated over the defined spacecraft orbit for the duration of the mission to obtain the total omnidirectional fluence spectra. Components such as the solar cell coverglass, adhesive, and antireflective coatings can slow and attenuate the particle fluence reaching the solar cell. In SAVANT, a continuous slowing down approximation is used to model this effect.

Bailey, Sheila G.↗
DOE OSTI2024

Quantifying Investment Risk: Analysis of the Purchase Decision of a Nuclear Power Plant (Presentation)

Cost overruns are an ill-fated part of the deployment history of nuclear power plants (NPPs) in the United States, and yet studies increasingly show the important role nuclear technologies must play in decarbonizing the U.S. economy. Paradoxically, then, a key piece of a coherent decarbonization strategy depends on attracting investor action to a purchase where historical cost overruns have been sizable. To address this challenge, this study aims to develop a financial model that quantifies the risk of cost overruns in the decision-making process for purchasing advanced reactor concepts. Using the concept of value at risk (VaR), the model is built to evaluate financial risk nuclear construction with the aim to identify risk mitigation strategies. The objective is to identify strategies to mitigate cost-risk challenges and assess the potential reduction in investor risk exposure. This paper presents the initial development and preliminary verification of the financial risk analysis model. The development of this model involved a comprehensive approach to estimating financial risk over the operating life of NPP that stems from construction uncertainties. By utilizing net present value (NPV) with discounted cash flows, the model captures the complex interconnections of project costs, construction timelines, revenue, and uncertainties. Verifying the model involved testing historical data from previous reactor construction projects against the construction project of Vogtle 3 and 4. This paper’s results present the comparison of the preconstruction cost overrun prediction with the current cost estimates from a nearly complete Vogtle 3 and 4.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Quantifying Investment Risk: Analysis of the Purchase Decision of a Nuclear Power Plant

Cost overruns are an ill-fated part of the deployment history of nuclear power plants (NPPs) in the United States, and yet studies increasingly show the important role nuclear technologies must play in decarbonizing the U.S. economy. Paradoxically, then, a key piece of a coherent decarbonization strategy depends on attracting investor action to a purchase where historical cost overruns have been sizeable. To address this challenge, this study aims to develop a financial model that quantifies risk of cost overruns in the decision-making process for purchasing advanced reactor concepts. Using the concept of Value at Risk (VaR), the model is built to evaluate financial risk nuclear construction with the aim to identify risk mitigation strategies. The objective is to identify strategies to mitigate cost-risk challenges and to assess the potential reduction in investor risk exposure. The paper presents the initial development and preliminary verification of the financial risk analysis model. The development of this model involved a comprehensive approach to estimating financial risk over the operating life of NPP that stems from construction uncertainties. By utilizing net present value (NPV) with discounted cash flows, the model captures the complex interconnections of project costs, construction timelines, revenue, and uncertainties. Verification of the model involved testing historical data from previous reactor construction projects against the construction project of Vogtle 3 and 4. The results of this paper present the comparison of the preconstruction cost overrun prediction with the current cost estimates from a nearly complete Vogtle 3 and 4.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2015

Initial Analysis of and Predictive Model Development for Weather Reroute Advisory Use

In response to severe weather conditions, traffic management coordinators (TMCs) reroute air traffic around regions of airspace affected by the severe weather. Presently, acceptable reroutes are specified by issuing reroute advisories. Advisories, based on reroutes published in the National Severe Weather Playbook, consist of several routes describing routing options. These reroutes are selected by TMCs based on their understanding of weather conditions and their previous experience dealing with similar weather conditions. Providing recommendations and analysis of available reroute options could assist the TMCs in making rerouting decisions. While reroute advisories have historically been based on Playbook plays, plays are frequently modified or combined to generate an advisory. Thus, it is natural to present rerouting suggestions to TMCs as modified Playbook plays. The challenge here is to compare advisory subroutes and play subroutes in a meaningful way in order to map advisories back to the Playbook plays upon which they may have been based. In this work, several subroute comparison metrics are presented and discussed. One of these metrics is then used to match advisories to Playbook plays. With the development and implementation of NextGen technologies, there is currently a trend of moving away from the pre-defined Playbook plays (and related advisories) in favor of a more precise specification of trajectories using GPS based navigation tools, such as area navigation (RNAV). Moving towards ubiquitous use of RNAV routes, the objective of rerouting flights will be met with more precisely specified and accurately flown RNAV routes. In the final version of this paper, significant RNAV routes will be identified by finding RNAV routes that are flown frequently. This will require a trajectory comparison technique to compare actually flown flight tracks to specified RNAV routes. The metrics developed here will be used or modified for this task.

weather required reroutes↗
DOE OSTI2024

Modern chemical graph theory

Abstract Graph theory has a long history in chemistry. Yet as the breadth and variety of chemical data is rapidly changing, so too do graph encoding methods and analyses that yield qualitative and quantitative insights. Using illustrative cases within a basic mathematical framework, we showcase modern chemical graph theory's utility in Chemists' analysis and model development toolkit. The encoding of both experimental and simulation data is discussed at various levels of granularity of information. This is followed by a discussion of the two major classes of graph theoretical analyses: identifying connectivity patterns and partitioning methods. Measures, metrics, descriptors, and topological indices are then introduced with an emphasis upon enhancing interpretability and incorporation into physical models. Challenging data cases are described that include strategies for studying time dependence. Throughout, we incorporate recent advancements in computer science and applied mathematics that are propelling chemical graph theory into new domains of chemical study. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism > Computational Materials Science Structure and Mechanism > Molecular Structures

Leite, Leonardo S. G.↗
NASA NTRS1977

Preliminary development of a fundamental analysis model for crack growth in a fiber reinforced composite material

A mathematical model for the strength of fiber reinforced composites containing specific flaws is described. The approach is to embed a local heterogeneous region surrounding the crack tip in an anisotropic elastic continuum. By consideration of the individual failure events activated near the flaw tip, a strength prediction can be made from basic properties of the composite constituents. Computations for arbitrary flaw size and orientation have been performed for unidirectional composites with linear elastic-brittle constituent behavior. The mechanical properties were those of graphite epoxy. With the rupture properties arbitrarily varied to test the capability of the model to reflect real fracture modes in fiber composites, it is shown that fiber breakage, matrix crazing, crack bridging, matrix-fiber debonding, and axial splitting all can occur during gradually increasing load prior to catastrophic fracture. Qualitative comparisons with experimental results on edge-notched unidirectional graphite epoxy specimens have also been made.

Kanninen, M. F.↗
NASA NTRS1993

Comprehensive analysis of bearingless rotors - Model development and experimental correlation of modes, response, trim and stability

A generic mathematical model that is capable of accurately modeling the multiple load path bearingless rotor blade is developed. A comprehensive, finite element based solution for the natural vibration of the rotor blade is developed. An iterative scheme based on harmonic balance is used to evaluate the nonlinear response of the rotor to control inputs and a Newton-Raphson procedure is employed to evaluate the trim of rotorcraft. Linearized perturbation model of the nonlinear system are presented. The model is validated by comparing with existing whirl tower, wind tunnel and flight test results of BMR/BO-105 helicopter. Frequencies of two bearingless rotor blades compare well with results from experiments. Nonlinear response and trim results are presented for the bearingless BMR/BO-105 rotor. Aeroelastic stability in forward flight, evaluated using floquet theory agrees with test data in general.

Jambunathan, V.↗
NASA NTRS1997

Assessment of a remote sensing-based model for predicting malaria transmission risk in villages of Chiapas, Mexico

A blind test of two remote sensing-based models for predicting adult populations of Anopheles albimanus in villages, an indicator of malaria transmission risk, was conducted in southern Chiapas, Mexico. One model was developed using a discriminant analysis approach, while the other was based on regression analysis. The models were developed in 1992 for an area around Tapachula, Chiapas, using Landsat Thematic Mapper (TM) satellite data and geographic information system functions. Using two remotely sensed landscape elements, the discriminant model was able to successfully distinguish between villages with high and low An. albimanus abundance with an overall accuracy of 90%. To test the predictive capability of the models, multitemporal TM data were used to generate a landscape map of the Huixtla area, northwest of Tapachula, where the models were used to predict risk for 40 villages. The resulting predictions were not disclosed until the end of the test. Independently, An. albimanus abundance data were collected in the 40 randomly selected villages for which the predictions had been made. These data were subsequently used to assess the models' accuracies. The discriminant model accurately predicted 79% of the high-abundance villages and 50% of the low-abundance villages, for an overall accuracy of 70%. The regression model correctly identified seven of the 10 villages with the highest mosquito abundance. This test demonstrated that remote sensing-based models generated for one area can be used successfully in another, comparable area.

Insect Vectors/growth & development↗
DOE OSTI2025

Towards a Robust Adaptive Digital Twin for Fusion Applications

The development of a digital twin system for fusion applications is essential for enhancing the prediction, analysis, and optimization of complex plasma processes. Machine learning (ML), particularly deep learning has demonstrated strong capabilities in modeling such highly nonlinear and intricate systems. However, two critical challenges limit the deployment of deep learning-based digital twins: Uncertainty Quantification (UQ) and data drift. UQ is vital for ensuring trustworthy predictions, especially in decision-support scenarios. Additionally, data-driven models are often sensitive to changes in the underlying data distribution, such as shot-to-shot variations in fusion experiments, which can lead to performance degradation over time. To address these challenges, we are developing an uncertainty-aware, adaptive digital twin framework. Our approach incorporates deep learning models enhanced with Gaussian Process approximations for predictive uncertainty estimation, coupled with an online learning mechanism that enables continuous model adaptation to new experimental data. This adaptive capability allows the data driven models to respond effectively to evolving plasma behaviors and equipment conditions. Specifically, to mitigate the effects of shot-to-shot drift, our system updates itself incrementally as new data becomes available, improving both robustness and fidelity. Our vision is to evolve this data driven model into a self-sustaining digital twin system that leverages UQ based feedback to continuously refine itself and potentially support real-time decision making. This presentation will cover a brief background on uncertainty quantification for ML, our ongoing effort on development of UQ capabilities for ML, our data science pipeline from data collection to model development and analysis and online learning framework for modeling coil deflection at DIII-D. I will also briefly touch upon opportunities and challenges in development of digital twin framework.

Sammuli, Brian [General Atomics]↗
NASA NTRS1994

A Knowledge-Based Representation Scheme for Environmental Science Models

One of the primary methods available for studying environmental phenomena is the construction and analysis of computational models. We have been studying how artificial intelligence techniques can be applied to assist in the development and use of environmental science models within the context of NASA-sponsored activities. We have identified several high-utility areas as potential targets for research and development: model development; data visualization, analysis, and interpretation; model publishing and reuse, training and education; and framing, posing, and answering questions. Central to progress on any of the above areas is a representation for environmental models that contains a great deal more information than is present in a traditional software implementation. In particular, a traditional software implementation is devoid of any semantic information that connects the code with the environmental context that forms the background for the modeling activity. Before we can build AI systems to assist in model development and usage, we must develop a representation for environmental models that adequately describes a model's semantics and explicitly represents the relationship between the code and the modeling task at hand. We have developed one such representation in conjunction with our work on the SIGMA (Scientists' Intelligent Graphical Modeling Assistant) environment. The key feature of the representation is that it provides a semantic grounding for the symbols in a set of modeling equations by linking those symbols to an explicit representation of the underlying environmental scenario.

Keller, Richard M.↗
DOE OSTI2020

Thermal Analysis Evaluations Using the Dry Cask Simulator

Different thermal analysis models were developed to simulate the dry cask simulator (DCS). The DCS is an experiment designed to simulate dry storage of a single boiling water reactor fuel assembly under a variety of heat loads and internal pressures. The DCS was set up and tested in both a vertical and horizontal configuration to determine cladding temperatures in vertical and horizontal dry cask storage systems. The models included a detailed STAR-CCM+ model with the fuel assembly geometry explicitly modeled, a porous STAR-CCM+ model with the fuel assembly geometry modeled as porous media region with calculated effective properties, and a COBRA-SFS model. COBRA-SFS is a thermal-hydraulic code developed for steady-state and transient analysis of multi assembly spent-fuel storage and transportation systems. STAR-CCM+ is a commercial computation fluid dynamics (CFD) code. Both a detailed and porous STARCCM+ model were developed to look at the effective thermal conductivity (keff) approach to modeling a fuel assembly. A keff fuel model is typically model in CFD thermal analyses due to its significantly lower computational costs. The models were run for a combination of low and high canister pressures (100 kPa and 800 kPa) and low and high internal heat loads (0.5 kW and 5 kW). Results from all three models were compared against experimental data taken from the DCS for the peak cladding temperature (PCT) and inlet air mass flow.

Suffield, Sarah R.↗