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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 757 records · Page 42

Graphical User Interface (GUI) Implementation for Agent-Based Microbial Radiobiology Model

Sending human life past the Low Earth Orbit (LEO) to explore the Moon and Mars will be challenging. The Earth’s magnetic field naturally protects life from deep-space particle radiation such as Galactic Cosmic Rays (GCR) and Solar Particle Events (SPE); these will pose health risks to humans in deep space. Research has been done to investigate these effects, like BioSentinel, the first biological CubeSat to fly beyond the LEO, designed to culture yeast in a microfluidic device and record optical measurements of growth and metabolism. However, experiments can only report cell damage as bulk growth curves, while deep-space radiation causes damage that is heterogeneous among individual cells. AMMPER is an open-source, agent-based, computational model coded in Python to simulate the effects of deep-space radiation on individual yeast cells (Saccharomyces cerevisiae) to facilitate interpretation of biological radiation experiments. Version 1.0 of the code ran in a command line interface (CLI), limiting use to those familiar with modularization, object-oriented programming, and computational models. Here we present a graphical user interface (GUI) for AMMPER to increase its accessibility. GUI development included converting input points and UI files, designing an application and logo, and expanding program packages. Additionally, we added optical assistance that corresponded with simulation parameters, which included simulation type, cell type, ROS model, and radiation dosage, as well as customizable display and file exportation features. Following a pilot testing period, its structure was updated further to enhance abilities, adding increased runs, video visualization, data plotting, and an educational/tutorial component. Future work will include creating a bit installer and runtime environment for AMMPER. Ultimately, the creation of the GUI has two main goals: to facilitate the integration of computational models into the work of researchers in microbial radiobiology, and to act as an interactive and visual resource for space biology education.

yeast↗

Development of a second order closure model for computation of turbulent diffusion flames

A typical eddy box model for the second-order closure of turbulent, multispecies, reacting flows developed. The model structure was quite general and was valid for an arbitrary number of species. For the case of a reaction involving three species, the nine model parameters were determined from equations for nine independent first- and second-order correlations. The model enabled calculation of any higher-order correlation involving mass fractions, temperatures, and reaction rates in terms of first- and second-order correlations. Model predictions for the reaction rate were in very good agreement with exact solutions of the reaction rate equations for a number of assumed flow distributions.

Varma, A. K.↗

Numerical simulation of dynamics of brushless dc motors for aerospace and other applications. Volume 2: User's guide to computer EMA model

A description and user's guide of the computer program developed to simulate the dynamics of an electromechanical actuator for aerospace applications are presented. The effects of the stator phase currents on the permanent magnets of the rotor are examined. The voltage and current waveforms present in the power conditioner network during the motoring, regenerative braking, and plugging modes of operation are presented and discussed.

Demerdash, N. A. O.↗

A computational fluid dynamics model to estimate local quantities in firebrand char oxidation

Firebrand burning is a complex phenomenon that is influenced by several parameters which are difficult to fully explore experimentally. Computational fluid dynamics models capable of predicting local quantities are essential for accurate prediction of char oxidation in firebrands. This article presents a computational fluid dynamics model to estimate firebrand mass loss, diameter change, and surface temperature during char oxidation. The model was validated using previously conducted wind tunnel experiments. These experiments were conducted for firebrands of two different aspect ratios, which were arranged in three different configurations (single, horizontal array, and vertical array), and for four different wind speeds (0.5, 1, 1.5, and 2 m/s). The computational fluid dynamics results were compared with a previous 1 D model. In all the test cases, the computational fluid dynamics model predicted the physical phenomena with significantly improved accuracy compared to a 1 D model. The char oxidation model presented in this article can be coupled with other models to study firebrand generation and trajectory, biomass pyrolysis, fluidized bed reactors, and coal combustion.

Engineering↗

Innovative Natural Gas Technologies For Efficiency Gain In Reliable And Affordable Thermochemical Electricity Generation (INTEGRATE)

Hyper is a cutting-edge system that pairs computational models that simulate the response of different systems with physical components such as sensors and actuators to transfer said calculated response to the HyPer facility. Computational models must operate in real-time in order to resolve the system response when coupled to physical hardware. Real-time is defined by the minimal HyPer system response time of Δt = 0.080 s. The integration of these models serves as a foundation for performance characterization based on real-world SOFC hardware and paves the way for comprehensive fuel flexibility studies. This report underscores the innovative approach to cyber-physical system deployment at NETL’s HyPer Facility, highlighting the critical role of computational models in enhancing the performance and adaptability of energy technologies.

03 NATURAL GAS↗

Robust Combined Heat and Hybrid Power (CHHP) for High Electrical Efficiency Cogeneration

Georgia Tech (Prime Recipient), the University of Texas at El Paso (UTEP) and the National Energy Technology Laboratory (NETL) investigated a hybrid fuel cell/ gas turbine system concept as a combined heat and hybrid power (CHHP) system for both robust and high power-to-process heat ratio cogeneration. The novelty of the proposed system entailed the distinct, elevated electrical efficiencies it maintains while simultaneously supporting a broad span of heating needs (e.g., supply temperatures) demanded across variable heat loads. The scope included: 1) leveraging a pioneering national lab facility configured for dynamic system operability development of hybrid fuel cell/gas turbine cycles; 2) enabling technology development to adjust and modulate the quality and quantity of thermal supply to bottoming heat loads via novel extreme temperature gas bypass valves. Hybrid fuel cell/gas turbine systems have primarily been reduced-to-practice in a constrained (e.g., initial proof-of-concept) manner and have still demonstrated considerable electrical efficiencies. However, these pre-pilot systems have focused upon electrical efficiencies and electrical power generation as the exclusive energy demand. Such hybrid systems had not been extensively researched or developed for flexible and variable operation consisting of both power and heat demands; however, these variable combined power and heat demands are characteristic of many types of manufacturers such as animal/poultry processing, bakeries and milk/flour/pastry manufacturing, textile mills, and electrochemical processing. Commercially, developing the system into a working combined heat and power system benefits these types of manufacturers by allowing them to meet their power and heat demands at a lower cost, higher efficiency, and/or through onsite generation. Therefore, the technical scope of this project was largely to study and facilitate these hybrid systems as combined heat and hybrid power (CHHP) systems that include dynamic operability for variable heat and power loads and/or grid dynamics for various types of manufacturers. Simulation results were used to predict the performance of the CHHP system and conceptually develop it to achieve desired dynamic operability. Experimentally, the primary goal was to design, manufacture, and experiment upon a high-temperature bypass valve. Experimental data included air mass flow rates through the valve orifice when the valve was changed to variable extent between fully closed and fully open. The experimental data was then used to create a semi-empirical computational model of the bypass valve. Concluded simulation goals for the research included developing computational heat exchanger models for the hybrid system inclusive of the bottoming heat exchanger and the recuperative heat exchanger, and then combining the computational recuperator model with the computational valve model. Afterwards, the computational models were then integrated to predict the dynamic operation of hybrid fuel cell/gas turbine cycles throughout a design space and reporting such. The scope stated in the preceding paragraph was packaged into five specific goals: 1) enabling the simulation of dynamic combined heat and power through the creation of computational, modular heat exchanger models; 2) simulation and exploration of the CHHP system’s performance by integrating the heat exchanger models with the national lab’s pre-existing hybrid system (computational) simulation, but without the recuperator bypass valve concept in order to initially determine how the (baseline) system behaves and can be controlled in order to meet variable heat and power demands; 3) development and initial deployment of the high-temperature recuperator bypass valve technology in order to confirm and characterize the approach; 4) usage of the experimental data for the valve to create a semi-empirical computational model for the bypass valve which could then be combined with the heat exchanger computational models; 5) repeat of the second task of simulating and exploring the system’s performance, but this time including the bypass valve to resolve its efficacy. Tasks were successfully completed, and the general notion of flexibly operating, high electrical efficiency CHHP was further corroborated. Supportive details are provided in the report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding the Computing and Analysis Needs for Resiliency of Power Systems from Severe Weather Impacts

As the frequency and intensity of severe weather has increased, its effect on the electric grid has manifested in the form of significantly more and larger outages in the United States. This has become especially true for regions that were previously isolated from weather extremes. In this paper, we analyze the weather impacts on the electric power grid across a variety of weather conditions, draw correlations, and provide practical insights into the operational state of these systems. High resolution computational modeling of specific meteorological variables, computational approaches to solving power system models under these conditions, and the types of resiliency needs are highlighted as goal-oriented computing approaches are being built to address grid resiliency needs. An example analysis correlating outages to 1km day-ahead weather from two historical winter storms, calculated on a large cluster using a combination of interpolated and extrapolated inputs from multiple instrumented sites to workflows that produce primary meteorological outputs, is shown as initial proof of concept.

analysis↗

On the Solution of the Three-Dimensional Flowfield About a Flow-Through Nacelle

The solution of the three dimensional flow field for a flow through nacelle was studied. Both inviscid and viscous inviscid interacting solutions were examined. Inviscid solutions were obtained with two different computational procedures for solving the three dimensional Euler equations. The first procedure employs an alternating direction implicit numerical algorithm, and required the development of a complete computational model for the nacelle problem. The second computational technique employs a fourth order Runge-Kutta numerical algorithm which was modified to fit the nacelle problem. Viscous effects on the flow field were evaluated with a viscous inviscid interacting computational model. This model was constructed by coupling the explicit Euler solution procedure with a flag entrainment boundary layer solution procedure in a global iteration scheme. The computational techniques were used to compute the flow field for a long duct turbofan engine nacelle at free stream Mach numbers of 0.80 and 0.94 and angles of attack of 0 and 4 deg.

Compton, William Bernard↗

Experiments planned specifically for developing turbulence models in computations of flow fields around aerodynamic shapes

Building block experiments and companion numerical simulations intended to verify and guide turbulence modeling are described. A series of experiments and computations being used to enhance modeling development for the shock wave turbulent boundary layer interaction problem is emphasized. Results are given for transonic flow over a circular arc airfoil undergoing shock wave induced, boundary layer separation for supersonic flow along a tube wall undergoing normal shock wave induced, boundary layer separation. Experimental data which use the complete Navier-Stokes equations are discussed.

Marvin, J. G.↗

NASA/MSFC multilayer diffusion models and computer program for operational prediction of toxic fuel hazards

The NASA/MSFC multilayer diffusion models are discribed which are used in applying meteorological information to the estimation of toxic fuel hazards resulting from the launch of rocket vehicle and from accidental cold spills and leaks of toxic fuels. Background information, definitions of terms, description of the multilayer concept are presented along with formulas for determining the buoyant rise of hot exhaust clouds or plumes from conflagrations, and descriptions of the multilayer diffusion models. A brief description of the computer program is given, and sample problems and their solutions are included. Derivations of the cloud rise formulas, users instructions, and computer program output lists are also included.

Dumbauld, R. K.↗

Gamma Radiation-Induced Degradation of Acetohydroxamic Acid (AHA) in Aqueous Nitrate and Nitric Acid Solutions Evaluated by Multiscale Modelling

Acetohydroxamic acid (AHA) has been proposed for inclusion in advanced, single-cycle, used nuclear fuel reprocessing solvent systems for the reduction and complexation of plutonium and neptunium ions. For this application, a detailed description of the degradation of AHA in dilute aqueous nitric acid is required. To this end, we present a comprehensive, multiscale computer model for the coupled radiolytic and hydrolytic degradation of AHA in aqueous sodium nitrate and nitric acid solutions. Rate coefficients for the reactions of AHA and HA with the oxidizing nitrate radical were measured for the first time using pulsed electron radiolysis and used as inputs in the kinetic model. The computer model results are validated by comparison to experimental data from steady state gamma irradiations, for which the agreement is excellent. Here, the presented model accurately predicts the yields of the major degradation products of AHA: acetic acid, hydroxylamine, nitrous oxide, and molecular hydrogen.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Parameter estimation and error analysis in environmental modeling and computation

A method for the estimation of parameters and error analysis in the development of nonlinear modeling for environmental impact assessment studies is presented. The modular computer program can interactively fit different nonlinear models to the same set of data, dynamically changing the error structure associated with observed values. Parameter estimation techniques and sequential estimation algorithms employed in parameter identification and model selection are first discussed. Then, least-square parameter estimation procedures are formulated, utilizing differential or integrated equations, and are used to define a model for association of error with experimentally observed data.

Kalmaz, E. E.↗

Numerical Thermal Model of a 30-cm NSTAR Ion Thruster

A thermal computer model of the NSTAR (Nasa Solar Electric Propulsion Technology Applications Readiness) xenon ion thruster has been produced using a lumped parameter thermal nodal network scheme. This model contains 104 nodes on the thruster and was implemented using SINDA (Systems Improved Numerical Differencing Analyzer) and TRASYS (Thermal Radiation Analyzer System) on various UNIX workstations. The model includes radiation and conduction heat transfer, the effect of plasma interaction on the thruster, and an account for finely perforated surfaces. The model was developed in conjunction with an NSTAR thruster outfitted with approximately 20 thermocouples for thermal testing at the NASA Lewis Research Center. The results of these experiments were used to calibrate and confirm the computer model first without and then with the plasma interaction. The calibrated model was able to predict discharge chamber temperatures to within 10 C of measured temperatures. To demonstrate the ability of the model under various circumstances the heat flux was examined for a thruster operating in the environment of space.

VanNoord, Jon↗

Validation of Cryogenic Propellant Tank Self-Pressurization by Leveraging Reduced Order Modeling within Computational Fluid Dynamics Simulation

Validation of cryogenic propellant tank self-pressurization was performed using a hybrid Computational Fluid Dynamics (CFD) and reduced order modeling methodology. Data from a liquid hydrogen ground test conducted at the K-site facility at the National Aeronautics and Space Administration (NASA) Glenn Research Center was used for the validation effort. Liquid phase dynamics were explicitly resolved with a CFD tool. Vapor phase dynamics were modeled as a point mass that communicated heat from the tank wall to the liquid phase via a boundary condition used at the gas-liquid interface. The method proved to be more accurate, robust, and efficient than explicit resolution of the dynamics using a standard Volume of Fluid (VOF) methodology. The subject pressurization process was found to be heavily dependent upon both the relatively high liquid temperature gradient near the gas-liquid interface and the natural convection flow path. Modeling the gas-liquid interface as an immovable surface eliminated temperature gradient destroying gas-liquid interface velocities observed in VOF simulations, and correspondingly enabled more rapid simulation since interface advection was not allowed. The single phase computational domain also facilitated the ability to demonstrate spatial resolution convergence of natural convection cells within the liquid which significantly impacted the tank pressurization rate. This work was used to demonstrate the critical physics for tank self-pressurization and numerical methodologies that may be used to best resolve those physics. The findings informed development and operation of production level CFD tools used in the Fluid Dynamics Branch at NASA Marshall Space Flight Center.

J. M. Brodnick↗

Initial test results on state estimation on the SCOLE mast

Modal state estimation tests are performed on the SCOLE mast for the fixed Shuttle platform case. Kalman filter state estimation results from a five mode computer model of the SCOLE mast, developed from a finite element analysis, are compared with those state estimates obtained from laboratory tests. Two comparison runs are presented, one an excitation of the first two bending modes, another, an excitation of the first torsional mode of the mast. Results from both runs show poor agreement in modal estimation between the computer model simulations and the laboratory test data. At present, the reason(s) for this poor performance is unknown. Both the laboratory hardware and software and the computer model are being checked for possible sources of errors. Further computer simulations as well as laboratory testing will be performed.

Sparks, D., Jr.↗

An Integrated Model of the Cardiovascular and Central Nervous Systems for Analysis of Microgravity Induced Fluid Redistribution

A recognized side effect of prolonged microgravity exposure is visual impairment and intracranial pressure (VIIP) syndrome. The medical understanding of this phenomenon is at present preliminary, although it is hypothesized that the headward shift of bodily fluids in microgravity may be a contributor. Computational models can be used to provide insight into the origins of VIIP. In order to further investigate this phenomenon, NASAs Digital Astronaut Project (DAP) is developing an integrated computational model of the human body which is divided into the eye, the cerebrovascular system, and the cardiovascular system. This presentation will focus on the development and testing of the computational model of an integrated model of the cardiovascular system (CVS) and central nervous system (CNS) that simulates the behavior of pressures, volumes, and flows within these two physiological systems.

Space Adaptation Syndrome↗

UQpy: A general purpose Python package and development environment for uncertainty quantification

In this paper, we present the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.

97 MATHEMATICS AND COMPUTING↗