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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Flight Testing an Iced Business Jet for Flight Simulation Model Validation

A flight test of a business jet aircraft with various ice accretions was performed to obtain data to validate flight simulation models developed through wind tunnel tests. Three types of ice accretions were tested: pre-activation roughness, runback shapes that form downstream of the thermal wing ice protection system, and a wing ice protection system failure shape. The high fidelity flight simulation models of this business jet aircraft were validated using a software tool called "Overdrive." Through comparisons of flight-extracted aerodynamic forces and moments to simulation-predicted forces and moments, the simulation models were successfully validated. Only minor adjustments in the simulation database were required to obtain adequate match, signifying the process used to develop the simulation models was successful. The simulation models were implemented in the NASA Ice Contamination Effects Flight Training Device (ICEFTD) to enable company pilots to evaluate flight characteristics of the simulation models. By and large, the pilots confirmed good similarities in the flight characteristics when compared to the real airplane. However, pilots noted pitch up tendencies at stall with the flaps extended that were not representative of the airplane and identified some differences in pilot forces. The elevator hinge moment model and implementation of the control forces on the ICEFTD were identified as a driver in the pitch ups and control force issues, and will be an area for future work.

Ratvasky, Thomas P.↗
DOE OSTI2020

Supporting Bioproducts Industry Growth with a System Dynamics Decision-Support Tool

A bio-based economy requires chemical products as well as fuels to be produced from biomass. Although a variety of universities, government agencies, start-ups and established firms have engaged in bioproduct development, many projects have failed to reach the point of commercialization and commercialized bioproducts struggle to capture and maintain market share. To date, there has been no general research into the factors that contribute to bioproduct failure or success. This work presents the Bioproduct Transition Dynamics (BTD) system dynamics model, a decision-support tool that simulates the bioproduct development process from pre-piloting research through construction of the first commercial-scale plant, as well as the processes of obtaining funding from investors and government agencies. The core of the BTD is a feedback loop between bioproduct developers and funders, which relates development progress measured with indicators such as net present value to funders’ decisions to continue investing. External factors such as feedstock prices, market size and growth, and the existence of bioproduct consumers also influence a development project’s chances of receiving follow-on funding. Virtually any bioproduct can be represented with the BTD: direct replacements, performance-advantaged products, niche and commodity markets can all be modeled. The goal of the BTD project is to inform decisions made by developers in both established firms and start-ups, investors, government agencies, and other stakeholders interested in growing the nascent U.S. bioproducts industry. This talk will cover the general structure and functionality of the BTD, and present results from an analysis performed with the BTD to demonstrate its use as a decision-support tool and the insights it can provide. The goal of the analysis is to identify the most critical factors that lead to direct replacement and performance-advantaged bioproduct projects emerging successfully from the “Valley of Death”, and to determine if these factors differ between the two bioproduct types.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1999

The Role of Data Assimilation in the Study of Regional and Global Variability of the Hydrological Cycle

In the coming years, researchers will have at their disposal a host of new observations from advanced space-based sensors (e.g. the Tropical Rainfall Measuring Mission, EOS Terra and PM missions) providing, among other things, a more complete and accurate description of various components of the Earth's hydrological cycle. Also, increasingly more sophisticated and comprehensive geophysical models will provide researchers better tools for simulating the hydrological cycle, and for carrying out mechanistic studies of the role of moist processes in the climate system. In addition, new data sets generated with global four-dimensional data assimilation (4DDA) systems will provide comprehensive and complete information on both the state and forcing of the climate system. Ideally, the 4DDA systems optimally incorporate all relevant information from the observations together with a first guess from a state-of-the-art geophysical model to produce a "best" estimate of the climate state. Furthermore, to the extent that the assimilating models are realistic and are constrained by the observations, they should provide reliable estimates of the associated physical processes or climate forcing fields. While operational weather centers now have a considerable history of providing reliable estimates of the basic atmospheric state variables, the associated processes or diagnostic fields (which are less well constrained by the observations and sensitive to errors in the model's physical parameterizations) are still considered experimental and of uncertain quality. In this study we will examine the current generation of reanalysis products to assess the capabilities of 4DDA systems to represent components of the hydrological cycle. The focus is on the role of the model in providing consistent estimates of moist processes. We will also assess whether current observations provide sufficient constraints on these model- generated fields.

Schubert, Siegfried↗
NASA NTRS2016

Operational Characteristics Identification and Simulation Model Verification for Incheon International Airport

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5% per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM(Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas/Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte/Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration - 2 (ATD-2) project for technology demonstration of Integrated Arrival/Departure/Surface (ADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement)/KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.

scheduling↗
NASA NTRSDate not supplied

CHP-PRA Proof-of-Concept [Simulation] Sensitivity Assessment

An effort is underway to establish a Crew Health and Performance system (CHP) tradespace tool using a Probabilistic Risk Assessment (PRA) modeling and simulation system. The goal of the CHP-PRA effort is to provide a means of quantifying the integrated influence of CHP functions and capabilities on risk outcome metrics associated with health, performance, and long-term health. These metrics can then be used to establish potential risk-based trades on CHP system designed functionality and capabilities. Previously, our team demonstrated a proof-of-concept PRA approach that estimated the integrated influence of exercise countermeasures on 8 human system risks (Figure 1a) with outcomes associated with health and medical risk metrics. We reported that the change in the integrated relative health risk was small (Figure 1b) and that the small change in overall risk resulted from compounding and competing contribution levels of the individual risks. This interesting observation illustrates the emergent complexity of even straightforward representations of the human health and performance risk space and the ability of PRA models to capture this balance of global risk concerns. A key question that is not addressed in the initial analysis is “even though the global risk is relatively nominal, do any of the local risks become unacceptable?” In essence, we seek to determine what relative change in the human system risks are contributing to the relatively muted sensitivity of the proof-of-concept model combined risk assessments. Evaluations at the component risk level should elucidate if any individual risk reaches a high level that is subsequentially balanced by reductions in other areas. To further understand the relative changes in the component risks in the proof-of-concept model, and to elucidate how future refinements can be targeted, a means of establishing the contributions of the robustness of the proof-of-concept approach will be demonstrated.

astronaut health↗
DOE OSTI2025

Integrated Molten Salt Reactor Modeling Capabilities in NEAMS Thermal Hydraulics Tools

The DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad range of advanced reactor concepts. The research and development approach under the thermal fluids technical area synergistically combines three length and time scales in a hierarchical multi-scale approach. To enable multi-scale thermal fluids capability using these codes, a key joint effort has been underway to develop an integrated system- and engineering-scale thermal fluids analysis capability, through integration of SAM and Pronghorn codes, both based on the MOOSE framework.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Develop and verify soil/structure interaction for pile/foundation interaction

Phase II of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project was used to verify the implementation of a new soil-structure interaction (SSI) model for use within offshore wind turbine modeling software. The REDWIN Macro-element model implemented and verified in this study enables a computationally efficient way to model the linear and nonlinear SSI problem, including hysteretic damping, of a monopile structure. The modeling approach was integrated into several modeling tools and a series of increasingly complex simulations was conducted using the IEA 10MW reference turbine mounted on a monopile support structure to verify the coupling between the tools and the REDWIN Macro-element SSI model. This campaign includes only numerical verification between various software and modeling approaches so no experimental measurements are available. The load cases (LC) considered include: LC1 – static response of the tower and substructure LC2 – frequency and mode-shape analysis of the tower and substructure LC3 – response of the tower and substructure due to wind-only loading LC4 – response of the tower and substructure due to wave-only loading LC5 – response of the tower and substructure due to wind and wave loading. Detailed properties of the modeled system are found in the following reference, “Bergua, Roger, Amy Robertson, Jason Jonkman, and Andy Platt. 2021. "Specification Document for OC6 Phase II: Verification of an Advanced Soil-Structure Interaction Model for Offshore Wind Turbines.” Golden, CO: National Renewable Energy Laboratory. NREL/TP-5000-79938. https://www.nlr.gov/docs/fy21osti/79938.pdf. Details on the results from the OC6 Phase II project can be found in the following reference, “Bergua R, Robertson A, Jonkman J, et al. OC6 Phase II: Integration and verification of a new soil–structure interaction model for offshore wind design.” Wind Energy. 2022;25(5):793-810. doi:10.1002/we.2698

17 WIND ENERGY↗
DOE OSTI2024

Modeling and Simulation of Electrostatics of Ge$_{\text{1-x}}$Sn$_{\text{x}}$ Layers Grown on Ge Substrates

This work introduces a comprehensive simulation tool that provides a robust 1D Schrödinger – Poisson solver for modeling the electrostatics of heterostructures with an arbitrary number of layers, and non-uniform doping profiles along with the treatment of partial ionization of dopants at low temperatures. The effective masses are derived from the first-principles calculations. The solver is used to characterize three Ge 1-x Sn x /Ge heterostructures with non-uniform doping profiles and determine the subband structure at various temperatures. Here, the simulation results of the sheet carrier densities show excellent agreement with the experimentally extracted data, thus demonstrating the capabilities of the solver.

42 ENGINEERING↗
NASA NTRS1988

Space Station pressure wall repair techniques

Space Station components are susceptible to hypervelocity impact damage from orbital debris and meteoroids. An especially vulnerable and critical space station component is the module pressure wall. Even with shielding, sufficiently large impacting particles can create penetrations ranging from pinholes to large jagged holes. This paper describes pressure wall damage repair patches along with procedures and tools for performing the repair. One patch incorporates an aluminum foil protected from the jagged hole edge with a Kevlar or foam pad. An adhesive holds the patch in place. Another patch uses a stiff plate held away from the damaged area by a low durrometer rubber ring which also seals the plate edge. An adhesive will also secure this patch in place. Procedures were developed to prepare the punctured wall surface and apply the patch under weightless and unpressurized conditions. The procedures were tested in a laboratory and in the MSFC Neutral Buoyancy Simulator with models of the patches and tools.

Gibbins, Martin N.↗
DOE OSTI2023

A new coupling of a GPU-resident large-eddy simulation code with a multiphysics wind turbine simulation tool

The development of new wind farm control strategies can benefit from combined analysis of flow dynamics in the farm and the behavior of individual turbines within one simulation environment. In this work, we present such an environment by developing a new coupling between the large-eddy simulation (LES) code GRASP and the multiphysics wind turbine simulation tool OpenFAST via an actuator line model (ALM). In addition, the implementation of the recently proposed filtered actuator line model (FALM) within the coupling is described. The new ALM implementation is cross-verified with results from four other commonly used research LES codes. The results for the blade loads and the near wake obtained with the new coupling are consistent with the other codes. Deviations are observed in the far wake. The results further indicate that the FALM is able to reduce the lift and power overprediction from which the traditional ALM suffers on coarse LES grids. This new simulation environment paves the way for future wind farm simulations under realistic weather conditions by leveraging GRASP's ability to impose data from large-scale meteorological models as boundary conditions.

17 WIND ENERGY↗
DOE OSTI2022

CyclusJS: A Distributed Web-based Fuel Cycle Visual Analytics. Research Performance (Final Report)

The overall aim of the CyclusJS project has been to design novel approaches that support fuel cycle simulations and empower decision-makers and researchers with better tools to compare and contrast results from multiple simulations to understand the landscape of potential outcomes better. In particular, nuclear fuel cycle simulations focus on modeling the nuclear industry and ecosystem at a macroscopic level, and the analysis tools connect such simulations with decision support systems. As a demonstration of the novelty and effectiveness of the proposed approach, we study scenarios for transitioning from one technology, Light Water Reactors (LWR), to a newer Sodium-cooled Fast breeder Reactor (SFR) technology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Multiphysics Simulation of KRUSTY Warm Critical Experiments Using MOOSE Tools

A series of critical experiments were performed during the Kilopower Reactor Using Stirling TechnologY (KRUSTY) project, producing valuable and unique data for the validation of corresponding microreactor models. In this paper, the development of a high-fidelity multiphysics model of the KRUSTY microreactor within the MOOSE ecosystem is presented, with a focus on the microreactor configuration during the warm critical experiments. The model was established by coupling a deterministic neutronics model using the Griffin code, with a BISON thermomechanical model. The multiphysics model successfully simulated the KRUSTY 15 ¢ and 30 ¢ warm critical reactivity insertion experiments in satisfactory agreement with the experimental measurement data. In conclusion, the modeling results demonstrated the performance of MOOSE-based multiphysics tools in microreactor simulations, and spotlighted the useful applications of these tools in supporting microreactor design, qualification, and licensing activities.

KRUSTY↗
DOE OSTI2025

Motion Dynamics of Motile Microbes in Pore-Networks and its Implications for Reactive Transport Processes

This report outlines new methods to improve simulations of microbial transport and microbially mediated reactions in porous media. A range of experimental, modeling, and machine learning tools are introduced to make these simulations faster, more reliable, and useful for real-world applications. At the microscopic level, the study investigates how different types of bacteria move through confined spaces. A new artificial intelligence tool called DeepTrackStat, is introduced to track motions dynamics as observed in videos of particles migrating through pore networks. This tool is especially helpful for studying fast-moving microbes and requires less computing power than traditional tracking methods. At larger scales, the research looks at how microbes and chemicals interact in zones where surface water and groundwater meet. To connect the small- and large-scale findings, the study presents a neural network model called STAMNet. This tool helps scale up detailed small-scale microbial motion behaviors to predict large-scale environmental changes more efficiently. By combining lab experiments, computer models, and artificial intelligence, the research presented supports smarter environmental decision-making, especially in bioremediation of contaminated groundwater and protection of water quality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Enabling Dynamic Probabilistic Risk Assessment of Physical Security Using EMRALD and MAAP (Presentation)

The optimization of physical security in nuclear power plants requires sophisticated methodologies that integrate operator actions and plant behavior through advanced simulation tools. Idaho National Laboratory has developed the Modeling and Analysis for Safety and Security using the Dynamic EMRALD Framework (MASS-DEF) methodology, an approach that integrates force-on-force simulations, dynamic probabilistic risk assessment, and thermal hydraulics modeling to enhance security planning while reducing costs. A reduced order model for thermal hydraulic simulations performed by the Modular Accident Analysis Program (MAAP) was developed to evaluate reactor core behavior during attack scenarios. MAAP simulations are computationally intensive and must be run in a secure environment, complicating analysis and validation. By pre-computed scenario outcomes for a small number of modified parameters, the reduced order model significantly decreases the computational cost and enables offsite review of the results.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Feedback density and causal complexity of simulation model structure

Measures of simulation model complexity generally focus on outputs; we propose measuring the complexity of a model’s causal structure to gain insight into its fundamental character. This article introduces tools for measuring causal complexity. First, we introduce a method for developing a model’s causal structure diagram, which characterises the causal interactions present in the code. Causal structure diagrams facilitate comparison of simulation models, including those from different paradigms. Next, we develop metrics for evaluating a model’s causal complexity using its causal structure diagram. We discuss cyclomatic complexity as a measure of the intricacy of causal structure and introduce two new metrics that incorporate the concept of feedback, a fundamental component of causal structure. The first new metric introduced here is feedback density, a measure of the cycle-based interconnectedness of causal structure. The second metric combines cyclomatic complexity and feedback density into a comprehensive causal complexity measure. Finally, we demonstrate these complexity metrics on simulation models from multiple paradigms and discuss potential uses and interpretations. These tools enable direct comparison of models across paradigms and provide a mechanism for measuring and discussing complexity based on a model’s fundamental assumptions and design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Coupling Subsurface and Above-Surface Models for Optimizing the Design of Borefields and District Heating and Cooling Systems

Accurate dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange for seasonal energy storage. Current modeling approaches in building and district energy simulation tools typically consider heat conduction through the ground between boreholes without flowing groundwater. While detailed simulation tools for subsurface heat and mass transfer exist, these fall short in simulating above-surface energy systems. To support the design and operation of such systems, the study developed a coupled model including a software package for building and district energy simulation, and software for detailed heat and mass transfer in the subsurface. For the first, it uses the open-source Modelica Buildings Library, which includes dynamic simulation models for building and district energy and control systems. For the heat and mass transfer in the soil, it uses the TOUGH simulator. The TOUGH family of codes can model heat and multi-phase, multi-component mass transport for a variety of fluid systems, as well as chemical reactions, in fractured porous media. The study validated the coupled modeling approach by comparing the simulation results with one from the g-function based ground response model. It then looked into effects when the water table and the regional groundwater flow are considered in the ground, from the perspective of heat exchange between borehole and ground, and the electrical consumption of the district heating and cooling systems. To access the simulation models, please find the links in the submission: -- For coupled approach validation: see model Buildings.Fluid.Geothermal.Borefields.Examples.BorefieldsWithTough and Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from the "Modelica Building Library" resource, branch issue1495_tough_interface, commit a2667c0. -- For the study of the effect of water table: see model Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO, commit 760de49. -- For the study of the effect of regional groundwater flow: see Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO_3D, commit c2a2d2a. The coupling interface script "GrounResponse.py" can be found from the above links in the folder Buildings/Resources/Python-Sources. Also, the needed files for TOUGH simulation are in the folder Buildings/Resources/Python-Sources/ToughFiles that can be accessed through the above links. A brief description of these files is given below; detailed specifications for the first three files may be found in the TOUGH3 Users Guide (Jung et al., 2018) https://tough.lbl.gov/documentation/tough-manuals/. (1) INCON - initial conditions for each grid block (2) INFILE - main input file with material properties and control parameters (3) MESH - description of the computational grid (4) readsave - Modelica/TOUGH interface program: read the final output of TOUGH simulation after TOUGH time step and prepare for transfer to Modelica for next Modelica time step (5) readsave.inp - input parameters for program readsave (6) writeincon - Modelica/TOUGH interface program: write the output of Modelica after Modelica time step and prepare for transfer to TOUGH as initial conditions for the next TOUGH step (7) writeincon.inp - input parameters for program writeincon

15 GEOTHERMAL ENERGY↗
NASA NTRS2009

Parametric Analysis of a Hover Test Vehicle using Advanced Test Generation and Data Analysis

Large complex aerospace systems are generally validated in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. This is due to the large parameter space, and complex, highly coupled nonlinear nature of the different systems that contribute to the performance of the aerospace system. We have addressed the factors deterring such an analysis by applying a combination of technologies to the area of flight envelop assessment. We utilize n-factor (2,3) combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. The data generated is automatically analyzed through a combination of unsupervised learning using a Bayesian multivariate clustering technique (AutoBayes) and supervised learning of critical parameter ranges using the machine-learning tool TAR3, a treatment learner. Covariance analysis with scatter plots and likelihood contours are used to visualize correlations between simulation parameters and simulation results, a task that requires tool support, especially for large and complex models. We present results of simulation experiments for a cold-gas-powered hover test vehicle.

Gundy-Burlet, Karen↗
DOE OSTI2024

Integrating Multi-Source Data for Bi-Level Traffic Simulator Calibration: A Literature Review and Highway Case Study

Traffic simulation serves as a powerful tool for pre-evaluating policies and technologies. In this context, simulation-based Dynamic traffic assignment (DTA) models are capable of capturing traffic dynamics. They are well-known as critical tools in controlling and predicting traffic situations. The reliability of simulation results heavily depends on the calibration process. Most studies in the literature formulate and calibrate simulators based on a single source of collected data or multiple data sets with the same spatiotemporal characteristics. However, in practice, traffic data is collected by various tools with usually different spatial and temporal resolutions. This study introduces a novel approach to taking into account diverse input data from a variety of sources. An iterative bi-level solution is proposed. to equally treat traffic flow and speed data. The upper level solves flow calibration with the exact solution method, and the lower level calibrates the speed with the simultaneous perturbation stochastic approximation (SPSA) algorithm. Subsequently, the effectiveness of the proposed model is investigated using data from a six-mile section of Nashville's I-24 highway in Tennessee. The results demonstrate that our proposed model creates an effective feedback loop between the optimizer and the simulator for calibrating flow and speed to reduce the error between simulated and real data.

42 ENGINEERING↗