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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Intersymbol Interference Investigations Using a 3D Time-Dependent Traveling Wave Tube Model

For the first time, a physics based computational model has been used to provide a direct description of the effects of the TWT (Traveling Wave Tube) on modulated digital signals. The TWT model comprehensively takes into account the effects of frequency dependent AM/AM and AM/PM conversion; gain and phase ripple; drive-induced oscillations; harmonic generation; intermodulation products; and backward waves. Thus, signal integrity can be investigated in the presence of these sources of potential distortion as a function of the physical geometry of the high power amplifier and the operational digital signal. This method promises superior predictive fidelity compared to methods using TWT models based on swept amplitude and/or swept frequency data. The fully three-dimensional (3D), time-dependent, TWT interaction model using the electromagnetic code MAFIA is presented. This model is used to investigate assumptions made in TWT black box models used in communication system level simulations. In addition, digital signal performance, including intersymbol interference (ISI), is compared using direct data input into the MAFIA model and using the system level analysis tool, SPW (Signal Processing Worksystem).

Kory, Carol L.↗
NASA NTRS2012

GERMcode: A Stochastic Model for Space Radiation Risk Assessment

A new computer model, the GCR Event-based Risk Model code (GERMcode), was developed to describe biophysical events from high-energy protons and high charge and energy (HZE) particles that have been studied at the NASA Space Radiation Laboratory (NSRL) for the purpose of simulating space radiation biological effects. In the GERMcode, the biophysical description of the passage of HZE particles in tissue and shielding materials is made with a stochastic approach that includes both particle track structure and nuclear interactions. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections. For NSRL applications, the GERMcode evaluates a set of biophysical properties, such as the Poisson distribution of particles or delta-ray hits for a given cellular area and particle dose, the radial dose on tissue, and the frequency distribution of energy deposition in a DNA volume. By utilizing the ProE/Fishbowl ray-tracing analysis, the GERMcode will be used as a bi-directional radiation transport model for future spacecraft shielding analysis in support of Mars mission risk assessments. Recent radiobiological experiments suggest the need for new approaches to risk assessment that include time-dependent biological events due to the signaling times for activation and relaxation of biological processes in cells and tissue. Thus, the tracking of the temporal and spatial distribution of events in tissue is a major goal of the GERMcode in support of the simulation of biological processes important in GCR risk assessments. In order to validate our approach, basic radiobiological responses such as cell survival curves, mutation, chromosomal aberrations, and representative mouse tumor induction curves are implemented into the GERMcode. Extension of these descriptions to other endpoints related to non-targeted effects and biochemical pathway responses will be discussed.

Kim, Myung-Hee Y.↗
DOE OSTI2022

Goal-oriented a-posteriori estimation of model error as an aid to parameter estimation

In this work, a Bayesian model calibration framework is presented that utilizes goal-oriented a-posterior error estimates in quantities of interest (QoIs) for classes of high-fidelity models characterized by PDEs. It is shown that for a large class of computational models, it is possible to develop a computationally inexpensive procedure for calibrating parameters of high-fidelity models of physical events when the parameters of low-fidelity (surrogate) models are known with acceptable accuracy. The main ingredients in the proposed model calibration scheme are goal-oriented a-posteriori estimates of error in QoIs computed using a so-called lower fidelity model compared to those of an uncalibrated higher fidelity model. The estimates of error in QoIs are used to define likelihood functions in Bayesian inversion analysis. A standard Bayesian approach is employed to compute the posterior distribution of model parameters of high-fidelity models. As applications, parameters in a quasi-linear second-order elliptic boundary-value problem (BVP) are calibrated using a second-order linear elliptic BVP. In a second application, parameters of a tumor growth model involving nonlinear time-dependent PDEs are calibrated using a lower fidelity linear tumor growth model with known parameter values.

A-posterior estimates↗
NASA NTRS2013

Predicting Bone Mechanical State During Recovery After Long-Duration Skeletal Unloading Using QCT and Finite Element Modeling

During long-duration missions at the International Space Station, astronauts experience weightlessness leading to skeletal unloading. Unloading causes a lack of a mechanical stimulus that triggers bone cellular units to remove mass from the skeleton. A mathematical system of the cellular dynamics predicts theoretical changes to volume fractions and ash fraction in response to temporal variations in skeletal loading. No current model uses image technology to gather information about a skeletal site s initial properties to calculate bone remodeling changes and then to compare predicted bone strengths with the initial strength. The goal of this study is to use quantitative computed tomography (QCT) in conjunction with a computational model of the bone remodeling process to establish initial bone properties to predict changes in bone mechanics during bone loss and recovery with finite element (FE) modeling. Input parameters for the remodeling model include bone volume fraction and ash fraction, which are both computed from the QCT images. A non-destructive approach to measure ash fraction is also derived. Voxel-based finite element models (FEM) created from QCTs provide initial evaluation of bone strength. Bone volume fraction and ash fraction outputs from the computational model predict changes to the elastic modulus of bone via a two-parameter equation. The modulus captures the effect of bone remodeling and functions as the key to evaluate of changes in strength. Application of this time-dependent modulus to FEMs and composite beam theory enables an assessment of bone mechanics during recovery. Prediction of bone strength is not only important for astronauts, but is also pertinent to millions of patients with osteoporosis and low bone density.

Chang, Katarina L.↗
DOE OSTI2020

Whole cell simulator

A whole cell model (WCM) is a comprehensive multi-scale computational model representing all the known biochemical processes in a cell. It relies on a variety of intracellular pathway models and omics data. This computational framework enables seamless integration of diverse simulation methods used in WCM such as stochastic simulation algorithm (SSA), ordinary differential equations (ODE), flux balance analysis (FBA), and logic-based approaches. These methods run simultaneously, not only for whole pathways but also for subsets of reactions. Furthermore, we aim to enable dynamic switching between the methods when beneficial. Is

GEORGAKOUDIS, GIORGIS↗
DOE OSTI2023

Dynamics of electrified liquid metal surface using shallow water model

A shallow water model that incorporates surface tension and electric field effects is developed to investigate the dynamics of an electrified liquid surface. The computational model is verified against the Zakharov–Kuznetsov equation and is applied to study the growth and damping of the electrified liquid surface. A linear wave analysis is performed under a shallow water theory assuming an analytic solution of the electric field, similar to the Tonks–Frenkel instability. The electrified liquid surface grows or dampens based on the balance of the electric field, surface tension, and gravitational forces. As a result, the numerical results obtained from the electrified shallow water solver are in good agreement with the theoretical analysis.

Computational models↗
DOE OSTI2021

Prediction of PbLi fluid flow and temperature field in a thermal convection loop for qualification of fusion materials

Two modeling tools, a thermohydraulics code and a computational model in COMSOL Multiphysics, have been developed, tested and then applied to the analysis of fluid flow and heat transfer in a thermal convection loop (TCL). Such a device has recently been used to experimentally evaluate corrosion compatibility of APMT (Fe–21Cr–5Al–3Mo) steel with high-temperature molten eutectic lead-lithium (PbLi) alloy at Oak Ridge National Lab, TN, USA. Here, the 1-D thermohydraulics code allows for rapid calculations of the loop parameters as a function of the applied heat flux. The supplemental COMSOL finite-element computations provide detailed 3-D velocity and temperature field data but are much more time consuming. Both modelling tools demonstrate an excellent agreement in the computed circulation velocity as well as maximum and minimum temperatures. The performed TCL analysis focuses on flow development in the “hot” and “cold” legs, formation of Dean vortices in corner regions, blocking effect of the immersed samples, and radiative and convective cooling effects under the experiment-relevant conditions for Prandtl number Pr = 0.015, Grashof numbers Gr ~10 7 , and Reynolds numbers Re ~10 4 .

36 MATERIALS SCIENCE↗
NASA NTRS1980

Atmospheric turbulence simulation techniques with application to flight analysis

Statistical modeling of atmospheric turbulence is discussed. The statistical properties of atmospheric turbulence, in particular the probability distribution, the spectra, and the coherence are reviewed. Different atmospheric turbulence simulation models are investigated, and appropriate statistical analyses are carried out to verify their validity. The models for simulation are incorporated into a computer model of aircraft flight dynamics. Statistical results of computer simulated landings for an aircraft having characteristics of a DC-8 are reported for the different turbulence simulation techniques. The significance of various degrees of sophistication in the turbulence simulation techniques on the landing performance of the aircraft is discussed.

Wang, S. T.↗
DOE OSTI2018

Rational Design of a Catalyst for the Selective Monoborylation of Methane

Combined computational and experimental studies elucidate the mechanism and suggest rational design and optimization strategies of a bis(phosphine)-supported iridium-catalyst for methane monoborylation. The activation of the C–H bond in methane via oxidative addition using tris(boryl) iridium(III) complexes bearing bis-chelating supporting ligands is modeled computationally. This model shows that the use of the soft Lewis base ligand such as 1,2-bis(dimethylphosphino)ethane (dmpe) lowers the activation barrier of the rate-determining step as it facilitates polarization of the metal-center, lowering the barrier of the oxidative addition to afford a seven-coordinate iridium(V) intermediate. The experimental optimization of this reaction using high-throughput methods shows that up to 170 turnovers can be achieved at 150 °C (500 psi) within 16 h using bis(pinacolato)diboron, a well-defined homogeneous and monomeric catalyst (dmpe)Ir(COD)Cl that is readily available from commercial precursors, with selectivity for the monoborylation product. High-boiling cyclic aliphatic solvents decalin and cyclooctane also prove suitable for this reaction, while being inert toward borylation. In accordance with the lower calculated activation barrier, catalytic turnover is also observed at 120 °C with up to 50 turnovers over the course of 4 days in cyclohexane solvent. Here, it was found that the borylation of methane is only achieved via one catalytic cycle, and buildup of pinacolborane, a side-product from methane borylation with bis(pinacolato)diboron, inhibits catalytic activity.

computational molecular modeling↗
DOE OSTI2015

Predicting Ecological Roles in the Rhizosphere Using Metabolome and Transportome Modeling

The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. However, new algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad's ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter of plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism's transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Coupled EM-PIC/Radiation Transport Simulations of HERMES Courtyard Experiments

A suite of coupled computational models for simulating the radiation, plasma, and electromagnetic (EM) environment in the High-Energy Radiation Megavolt Electron Source (HERMES) courtyard has been developed. In principle, this provides a predictive forward-simulation capability based solely on measured upstream anode and cathode current waveforms in the Magnetically Insulated Transmission Line (MITL). First, 2D R-Z ElectroMagnetic Particle-in-Cell (EM-PIC) simulations model the MITL and diode to compute a history of all electrons incident on the converter. Next, radiation transport simulations use these electrons as a source to compute the time-dependent dose rate and volumetric electron production in the courtyard. Finally, the radiation transport output is used as sources for EM-PIC simulations of the courtyard to com- pute electromagnetic responses. This suite has been applied to the November 2016 trials, shots 10268-10313. Modeling and experiment differ in significant ways. This is just the first iteration of a long process to improve the agreement, as outlined in the summary.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

7th World Congress on Integrated Computational Materials Engineering (ICME 2023) (Final Technical Report)

Integrated Computational Materials Engineering (ICME) has received international attention due to its potential to shorten product development time, while lowering cost and improving design and manufacturing outcomes. ICME is an approach to designing materials solutions for specific applications that use computer modeling programs to predict the behavior of materials and integrate this information into the overall materials, processing, and manufacturing design cycle. The 7th World Congress on Integrated Computational Materials Engineering (ICME 2023) was held in Orlando, Florida from May 21–25, 2023 with the goal to convene stakeholders from across all areas of modeling and simulation, experimental specialization, and design, as well as from across academia, government, and industry, to address ICME tools and techniques and their integration, as well as to examine their application in engineering. This atmosphere facilitated rich interactions between the experimentalists, modelers, and computational and design, from academia, government, and industry, to discuss ICME tools and techniques and their application in engineering.

36 MATERIALS SCIENCE↗
NASA NTRS2018

Modeling Principles Using the Relation Between Lagrange Multipliers and Bond Graphs

Final document is attached. Modeling dynamic systems by bond graphs has become state of the art technology since hundreds of researchers around the world have incorporated the technology in many fields of engineering and science. The legacy of its invertor Prof. Henry Paynter at MIT in 1959 is now a fundamental and practical technique to understand reality by building computer models. This paper addresses a particular aspect of this technology when modeling of mechanical systems require relaxation of constraints by means of Lagrange principles. Lagrange's equations are a useful means of describing and solving systems with kinematic constraints. Lagrange multipliers are variables used in equations to find the extremes of multivariate functions. Here we explore the relation of Lagrange multipliers to solve modeling difficulties of a space vehicle with equations with dependent derivatives. Lagrange multipliers were used in conjunction with bond graphs to simulate a system where joints of kinematic linkages produce dependent derivatives. NASA's Morpheus Project lunar lander was used as a case study. The Morpheus Project is a terrestrial test vehicle designed to fly the terminal descent trajectory of a lunar lander to advance the Autonomous Landing Hazard Avoidance Technology (ALHAT). An objective of this study is to apply the modeling approach herein to capture the dynamic movement of the lander as the propellant is sloshed and consumed. This paper expands further the analysis presented by (Granda, J J. Nguyen, L, Carlson, T, Sahragard-Monfared, G., Fornalski, E., Brocker 2016). Using an automated approach bond graph models of state space equations were generated using the Computer Aided Modeling Program (CAMPG). Integral causality models and derivative causality models were considered in order to find the simpler solution for the mathematical dependencies produced in modeling this vehicle.

Granda, Jose J.↗
DOE OSTI2015

Tracking radioactivity content in the spent fuel pool in PWRS - 15150

Over the last decade, significant progress has been made in managing radioisotopes generated in the PWR primary systems. These include limiting the use of cobalt containing materials, along with improved fuel performance and zinc injection to passivate the corrosion layers to limit the accumulation of Co-58 and Co-60 on primary coolant surfaces. Attention here is directed to the spent fuel pool where accumulation of spent fuel and activated material represents a growing source of mobile radioactivity supplemented with periodic exchanges of water from the reactor cooling system. Characterization of this source is increasingly important to effective management of disposal options. This paper examines the radioactive resin source term as determined from routine sampling of the coolant and fuel pool liquids. Targeted resin stream sampling and radiochemical analyses conducted at Diablo Canyon serve to inform and provide context for this examination. This examination is supplemented with computer modelling using the DW James Consulting computer program, 3R-SCAN. At most operating plants daily reactor coolant samples are counted using gamma spectroscopy and recorded. These samples serve to track fuel performance and maintain water chemistry. A secondary use for this data is to maintain a day to day tracking of releases of radioisotopes important to waste disposal. Given the coolant concentrations, plant operating history, and corroborative mathematical models and sampling, accumulation of these radioisotopes in coolant cleanup system ion-exchangers can be predicted. Fuel pool sampling is less frequent, but at the same time, things change more slowly there. The fuel pool contains about ten times the volume of the reactor coolant but its cleanup system process rate is comparable to reactor coolant letdown, i.e. 5.047 - 8.833 liters per second [lps] (80-140 gallons per minute [gpm]). A spent fuel pool clean-up demineralizer flow rate is typically about 5.047 lps (80 gpm). Concentrations of longer lived radioisotopes in the spent fuel pool can be comparable to those in reactor coolant. Releases of corrosion products and fission products from the stored fuel occur at a low rate but given the overall inventory can be significant. Recognized scaling factor ratios, particularly those to Co-60, are skewed by the aging of the material in the pool. An additional consideration stems from refueling operations themselves. Prior to refueling, it is common practice to conduct a forced oxidation of the corrosion films within the reactor. This spikes the activity within the reactor coolant. Most of this activity is removed by the reactor coolant purification system prior to removing the reactor head. This paper examines the accumulation of activity in the fuel pool purification ion exchange resins and how it impacts the overall classification of those ion exchange resins. The following discussion focuses on the transport of nickel and cobalt isotopes particularly as it relates to determination of Ni-63 which has become increasingly prominent in disposal classification. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Computational Design of Batteries from Materials to Systems

Computer models are helping to accelerate the design and validation of next generation batteries and provide valuable insights not possible through experimental testing alone. Validated 3-D physics-based models exist for predicting electrochemical performance, thermal and mechanical response of cells and packs under normal and abuse scenarios. The talk describes present efforts to make the models better suited for engineering design, including improving their computation speed, developing faster processes for model parameter identification including under aging, and predicting the performance of a proposed electrode material recipe a priori using microstructure models.

25 ENERGY STORAGE↗
DOE OSTI2016

Modeling Analysis for Nuclear Material Transport Package

This paper describes the computational models for the thermal analyses for 9975 nuclear material package under the Normal Conditions of Transport (NCT) and the Hypothetical Accident Conditions (HAC). The package 9975 is a DOE certified package that has been used in the DOE complex for transportation and long term storage of radioactive material. The NCT and HAC thermal analyses for the 9975 package were performed here by taking a computational heat transfer method. The HAC thermal models described here are identical to the models in the current DOE certified 9975 package. Thermal models in this work are for an undamaged package to meet all the regulatory requirements during an HAC thermal event. The model was created using modified shielding where the lead was encapsulated in a 0.036 inches stainless steel casing. The impact of this casing was studied earlier when the modification was proposed and it was found to have minimal impact on the component temperatures. Therefore, the analyses in this paper are good for packages with or without the shielding modifications. Analytical studies show that the realistic value for the solar absorptivity for the stainless steel surface fabricated from the rolling operation is about 0.5. The NCT analyses documented in this report use an absorptivity value of 0.5 to get more realistic component temperature results. Sensitivity studies were also performed to assess the impact of variability in the solar absorptivity for drum surface in the previous work for the NRC certification. The analysis in this paper is based on PuO{sub 2} in a food can. The food can is considered uncredited convenience containers inside the Primary Containment Vessel (PCV) of the 9975 package. PCV is located inside Secondary Containment Vessel (SCV). PuO{sub 2} has a density of 2 g/cc and a heat generation rate of 19 watts. This calculation evaluates the thermal performance for 9975 package with food can configuration during NCT and HAC per NRC regulations in 10 CFR Part 71. The objective of the calculation is to demonstrate that the maximum component temperatures are below their design limits. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Geometry dependence of the fluctuation intensity in gyrokinetic turbulence

The findings of an investigation into the properties of the three dimensional (3D) saturated fluctuation intensity of the electric potential in gyrokinetic turbulence simulations is presented. Scans in flux surface elongation and Shafranov shift are used to isolate the tokamak geometric dependencies. The potential intensity required in order to compute exact fluxes by a quasilinear method is determined using linear eigenmodes computed with the gyrokinetic code. A model of this non-linear intensity is constructed using the linear eigenmode properties and the geometry shape functions obtained from the 3D intensity spectrum. The model computes the poloidal wavenumber spectrum of the electron and ion energy fluxes with unprecedented accuracy. In conclusion, new insights are gained into the way zonal flow mixing saturates ion-scale turbulence by controlling the radial wavenumber width of the turbulence spectrum.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and model complexity according to AIC{sub c}. With parameters fixed, the model reasonably predicted detectability of human observers in blended FBP-IMR images. Semianalytic internal noise computation gave results equivalent to Monte Carlo, greatly speeding parameter estimation. Using Model-k4, the authors found an average detectability improvement of 2.7 ± 0.4 times that of FBP. IMR showed greater improvements in detectability with larger signals and relatively consistent improvements across signal contrast and x-ray dose. In the phantom tested, Model-k4 predicted an 82% dose reduction compared to FBP, verified with physical CT scans at 80% reduced dose. Conclusions: IMR improves detectability over FBP and may enable significant dose reductions. A channelized Hotelling observer with internal noise proportional to channel output standard deviation agreed well with human observers across a wide range of variables, even across reconstructions with drastically different image characteristics. Utility of the model observer was demonstrated by predicting the effect of image processing (blending), analyzing detectability improvements with IMR across dose, size, and contrast, and in guiding real CT scan dose reduction experiments. Such a model observer can be applied in optimizing parameters in advanced iterative reconstruction algorithms as well as guiding dose reduction protocols in physical CT experiments.

60 APPLIED LIFE SCIENCES↗