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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Convection equation modeling: A non-iterative direct matrix solution algorithm for use with SINDA

The determination of the boundary conditions for a component-level analysis, applying discrete finite element and finite difference modeling techniques often requires an analysis of complex coupled phenomenon that cannot be described algebraically. For example, an analysis of the temperature field of a coldplate surface with an integral fluid loop requires a solution to the parabolic heat equation and also requires the boundary conditions that describe the local fluid temperature. However, the local fluid temperature is described by a convection equation that can only be solved with the knowledge of the locally-coupled coldplate temperatures. Generally speaking, it is not computationally efficient, and sometimes, not even possible to perform a direct, coupled phenomenon analysis of the component-level and boundary condition models within a single analysis code. An alternative is to perform a disjoint analysis, but transmit the necessary information between models during the simulation to provide an indirect coupling. For this approach to be effective, the component-level model retains full detail while the boundary condition model is simplified to provide a fast, first-order prediction of the phenomenon in question. Specifically for the present study, the coldplate structure is analyzed with a discrete, numerical model (SINDA) while the fluid loop convection equation is analyzed with a discrete, analytical model (direct matrix solution). This indirect coupling allows a satisfactory prediction of the boundary condition, while not subjugating the overall computational efficiency of the component-level analysis. In the present study a discussion of the complete analysis of the derivation and direct matrix solution algorithm of the convection equation is presented. Discretization is analyzed and discussed to extend of solution accuracy, stability and computation speed. Case studies considering a pulsed and harmonic inlet disturbance to the fluid loop are analyzed to assist in the discussion of numerical dissipation and accuracy. In addition, the issues of code melding or integration with standard class solvers such as SINDA are discussed to advise the user of the potential problems to be encountered.

Schrage, Dean S.↗
DOE OSTI2025

Deep Learning for Subsurface Flow: A Comparative Study of U‐Net, Fourier Neural Operators, and Transformers in Underground Hydrogen Storage

Subsurface flow research is essential for the sustainable management of natural resources and the environment. Deep learning (DL) has significantly advanced this field by developing efficient and accurate surrogate models to replace computationally expensive physics‐based simulations. These surrogate models are commonly used to predict the spatiotemporal evolution of state variables, such as gas saturation and reservoir pressure, in heterogeneous geological formations. Despite the various DL models applied to this task, there is a lack of studies systematically comparing their performance. This absence of comparative analysis leads to somewhat arbitrary DL model selection in subsurface flow research, resulting in suboptimal performance and potentially inaccurate predictions. To bridge this gap, we conduct a systematic comparison study of three popular DL architectures—U‐Net, Fourier Neural Operators (FNO), and Segmentation Transformer (SETR)—in surrogate modeling of underground hydrogen storage (UHS). We focus on UHS due to its promise of enhancing clean energy resilience and its cyclic operational conditions that represent common scenarios in various subsurface applications. We evaluate the models based on accuracy, training cost, and inference speed. The comparison shows that U‐Net achieves the highest accuracy, followed by SETR and FNO. Despite its lower accuracy, FNO has the highest inference speed. SETR offers competitive accuracy with the least training memory usage, demonstrating the potential of transformers in learning subsurface flow. Our results provide guidance for selecting DL models for surrogate modeling in a wide range of subsurface flow problems.

42 ENGINEERING↗
DOE OSTI2022

Assessing high fidelity multi-component models to facilitate safeguards at Gas Centrifuge Enrichment Plants

We report that the International Atomic Energy Agency (IAEA) inspectors routinely carry out environmental sampling (ES) as a verification method. Collection of environmental swipe samples at various locations in Gas Centrifuge Enrichment Facilities (GCEPs) is an important process in detecting misuse of a declared facility and possibly the existence of undeclared nuclear material. These samples are measured for isotopic composition in uranium containing particles by Thermal Ionization Mass Spectrometry (TIMS) or Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Even though ES is highly effective in detecting the absolute value of enrichments and their deviations from the declared values, it cannot explain the cause of those changes. Several potential explanations can serve as possibilities for particles detected above or other than the declared enrichment. These include normal and non-malicious events such as the design of the enrichment cascades, unintentional failures of the machines, or overshoot during startup of a cascade. It can also be the result of deliberate misuse by the facility operators. The primary objective of this work is to understand how these factors affect the enrichments produced by a cascade and quantify anticipated multi-isotopic concentrations for each case. The following methodology is employed to determine signatures at a particular facility. 1) Utilize a new two-dimensional multi-component diffusion code to obtain centrifuge performance data and use that information to design and perform cascade analysis. Compare and contrast the results with previous 1-D radially averaged solutions from the Pancake code. 2) Design a GCEP cascade with the production goal of 19.75% 235 U for each set of machine data above. Investigate two cascade scenarios that include enrichment of natural uranium (NU) feed to 19.75% 235U in a single cascade compared to a two-step process of NU to 5% and then 5% to 19.75%. 3) Simulate the intentional vs. unintentional off-normal scenarios in the cascades to assess the differences in isotopic concentrations. A non-ideal squared-off cascade model developed at the University of Virginia is used to calculate flow rates and isotopic concentrations of the process gas. The analysis is performed using the Rome machine model operated at 600 m/s rotor speed. The upper and lower bounds of normal and abnormal enrichments in a typical facility are used in conjunction with ES results to understand the root causes of such observations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Modeling delayed thermal runaway in nitric acid-soaked cat litter mixed with radioactive waste

Thermal ignition of radioactive waste within a 55-gallon drum was simulated by using a pressure-dependent waste decomposition model (Hobbs et al. in Process Saf Environ Prot https://doi.org/10.1016/j.psep.2022.09.047, 2022) calibrated with data from full-scale drum experiments (Parker et al. in The thermolytic response of a surrogate RNS waste mixture at the drum scale. Los Alamos National Laboratory Report LA-UR-16-21760, 2016) and validated with experiments from multiple laboratories (Hobbs et al. in Thermal analysis of aged nitric acid-soaked kitty litter in TRU waste drums-23370.WM2023 Conference, Phoenix, AZ, 2023). The acceleration of nitric acid chemistry reacting with an organic cat litter leading to thermal ignition was likely triggered by a restricted vent in the drum. Here, we address whether the form of the rate equation in (Hobbs et al. in Process Saf Environ Prot https://doi.org/10.1016/j.psep.2022.09.047, 2022) is sufficient to extrapolate thermal ignition within aged drums of similar content that have been stored in Texas for over nine years by investigating four different reaction rate forms for waste decomposition. A critical reaction rate reduction analysis is performed on each of these models to determine if delayed thermal runaway within vented aged waste is possible after nine years. We found that a pressure-dependent first-order rate expression not only predicted the accidental ignition of the waste drum, but the form also matches multiple experiments from different laboratories. Even though the waste composition decreases over time, the model predicts that acceleration leading to thermal runaway is possible if the waste is confined, even after 9 years. In conclusion, waste containing oxidizers such as nitric acid should not be mixed with organic adsorbents, especially if the waste is confined.

cookoff↗
NASA NTRS2012

Characterization of Deficiencies in the Frequency Domain Forced Response Analysis Technique for Supersonic Turbine Bladed Disks

Turbine blades in rocket and jet engine turbomachinery experience enormous harmonic loading conditions. These loads result from the integer number of upstream and downstream stator vanes as well as the other turbine stages. Assessing the blade structural integrity is a complex task requiring an initial characterization of whether resonance is possible and then performing a forced response analysis if that condition is met. The standard technique for forced response analysis in rocket engine turbines is to decompose a computational fluid dynamics (CFD).generated flow field into its harmonic components, and to then perform a frequency response analysis at the problematic natural frequencies using cyclically symmetric structural dynamic models. Recent CFD analysis and water-flow testing at NASA/MSFC, though, indicates that this technique may miss substantial harmonic and non ]harmonic excitation sources that become present in complex flows. This complex content can only be captured by a CFD flow field encompassing at least an entire revolution. A substantial development effort to create a series of software programs to enable application of the 360 degree forcing function in a frequency response analysis on cyclic symmetric models has been completed (to be described in a future paper), but the question still remains whether the frequency response analysis itself is capable of capturing the excitation content sufficiently. Two studies comparing frequency response analysis with transient response analysis, therefore, of bladed-disks undergoing this complex flow environment have been performed. The first is of a bladed disk with each blade modeled by simple beam elements and the disk modeled with plates (using the finite element code MSC/NASTRAN). The focus of this model is to be representative of response of realistic bladed disks, and so the dimensions are roughly equivalent to the new J2X rocket engine 1st stage fuel pump turbine. The simplicity of the model allows the CFD load to be able to be readily applied, along with analytical and experimental variations in both the temporal and spatial fourier components of the excitation. In addition, this model is a first step in identifying response differences between transient and frequency forced response analysis techniques. The second phase assesses this difference for a much more realistic solid model of a bladed-disk in order to evaluate the effect of the spatial variation in loading on blade dominated modes. Neither research on the accuracy of the frequency response method when used in this context or a comprehensive study of the effect of test-observed variation on blade forced response have been found in the literature, so this research is a new contribution to practical structural dynamic analysis of gas turbines. The primary excitation of the upstream nozzles interacts with the blades on fuel pump of the J2X causes the 5th Nodal diameter modes to be excited, as explained by Tyler and Sofrin1, so a modal analysis was first performed on the beam/plate model and the 5ND bladed-disk mode at 40167 hz was identified and chosen to be the one excited at resonance (see figure 1). The first forced response analysis with this model focuses on identifying differences between frequency and transient response analyses. A hypothesis going into the analysis was that perhaps the frequency response was enforcing a temporal periodicity that did not really exist, and so therefore it would overestimate the response. As high dynamic response was a considerable source of stress in the J2X, examining this concept could potentially be beneficial for the program.

Brown, Andrew M.↗
DOE OSTI2023

Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction

Abstract Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases). Graphical Abstract

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Incorporating Valve Switching Losses Into a Static Optimal Control Algorithm for the Hybrid Hydraulic-Electric Architecture (HHEA)

The Hybrid Hydraulic-Electric Architecture (HHEA) has, in recent years, been proposed as an energy efficient alternative to conventional load-sensing architectures in mobile machines such as excavators and wheel-loaders. HHEA leverages the advantages of hydraulic power and electric power to eliminate throttling valves while also improving the energy and control performance of the system. The architecture utilizes a set of common pressure rails to provide a majority of power and and a small electric motor driven pump to modulate this power to meet the exact demand. Previous work has developed a computationally efficient Lagrange Multiplier approach for determining the optimal pressure rail selections that minimizes the energy losses in the system. The static model used considers only the energy use for each pressure rail selection but not the losses associated with the valves during the transition. This paper presents an approach to include the switching losses in the model and in the optimization procedure. To capture the switching losses, switching events between different rails and at various input and output flow rates were simulated with consideration of valve spool dynamics. A parameterized model that summarizes the losses is then obtained, allowing switching losses to be added to the previous energy analysis. The performance of the switching loss model was compared with reference data obtained from a high-fidelity simulation model. To incorporate the switching losses into optimal control algorithm, an efficient dynamic programming approach that prevents frequent switching is adopted in place of the Lagrange multiplier approach. The overall effect of switching losses on the energy consumption and optimal control decisions is presented. In general, switching losses contribute to about 9–10% of input energy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2011

Evaluation of Progressive Failure Analysis and Modeling of Impact Damage in Composite Pressure Vessels

NASA White Sands Test Facility (WSTF) is leading an evaluation effort in advanced destructive and nondestructive testing of composite pressure vessels and structures. WSTF is using progressive finite element analysis methods for test design and for confirmation of composite pressure vessel performance. Using composite finite element analysis models and failure theories tested in the World-Wide Failure Exercise, WSTF is able to estimate the static strength of composite pressure vessels. Additionally, test and evaluation on composites that have been impact damaged is in progress so that models can be developed to estimate damage tolerance and the degradation in static strength.

Sanchez, Christopher M.↗
DOE OSTI2025

Advancements in Constitutive Model Calibration: Leveraging the Power of Full‐Field DIC Measurements and In Situ Load Path Selection for Reliable Parameter Inference

Accurate material characterization and model calibration are essential for computationally supported high-consequence engineering decisions. Historically, characterization and calibration methods (1) use simplified test specimen geometries and global data, (2) cannot guarantee that sufficient characterization data are collected for a specific model of interest, (3) use deterministic methods that provide best-fit parameter values with no uncertainty quantification, and (4) are sequential, inflexible, and time-consuming. This work brings together several recent advancements into an improved workflow called interlaced characterization and calibration (ICC) that advances the state-of-the-art in constitutive model calibration. The ICC paradigm (1) employs tools to efficiently use full-field data to calibrate high-fidelity material models, (2) aligns the data needed with the data collected by adopting an optimal experimental design protocol, (3) quantifies parameter uncertainty through Bayesian inference and (4) incorporates these advancements into a quasi real-time feedback loop. The ICC framework is demonstrated here on the calibration of a material model using simulated full-field data for an aluminium cruciform specimen being deformed biaxially. The cruciform is actively driven through the myopically preferred load path using Bayesian optimal experimental design, which selects load steps that yield the maximum expected information gain (EIG). Principal component analysis (PCA) is performed on the model predictions of full-field displacements, and fast surrogate models are built to approximate the input-output relationships of the expensive finite element model. Furthermore, the tools developed and demonstrated here show that high-fidelity constitutive models can be efficiently and reliably calibrated with quantified uncertainty, thus supporting credible decision-making and potentially increasing the agility of solid mechanics modelling by enabling utilization of computational simulations at earlier stages of the design cycle.

Bayesian optimal experimental design↗
NASA NTRS1998

Development of the X-33 Aerodynamic Uncertainty Model

An aerodynamic uncertainty model for the X-33 single-stage-to-orbit demonstrator aircraft has been developed at NASA Dryden Flight Research Center. The model is based on comparisons of historical flight test estimates to preflight wind-tunnel and analysis code predictions of vehicle aerodynamics documented during six lifting-body aircraft and the Space Shuttle Orbiter flight programs. The lifting-body and Orbiter data were used to define an appropriate uncertainty magnitude in the subsonic and supersonic flight regions, and the Orbiter data were used to extend the database to hypersonic Mach numbers. The uncertainty data consist of increments or percentage variations in the important aerodynamic coefficients and derivatives as a function of Mach number along a nominal trajectory. The uncertainty models will be used to perform linear analysis of the X-33 flight control system and Monte Carlo mission simulation studies. Because the X-33 aerodynamic uncertainty model was developed exclusively using historical data rather than X-33 specific characteristics, the model may be useful for other lifting-body studies.

Cobleigh, Brent R.↗
NASA NTRSDate not supplied

Application of the NASA Multiscale Analysis Tool: Multiscale Integration and Interoperability

In order to demonstrate NASMAT’s multiscale operability, a series of illustrative examples will be presented that focus on the application of NASMAT to practical problems. First, the multiscale integration and data recursion is demonstrated by performing a multiscale analysis using only built-in micromechanics methods. NASMAT’s integration is then highlighted by running a multiscale analysis where an external finite element software calls NASMAT. In this case, at each integration point within the finite element model, a local NASMAT analysis is performed to account for failure behavior at the constituent scale. In a similar example, an external program is called from within NASMAT. This case would be relevant for a user wanting to implement an outside micromechanics technique. A combination of these examples is then presented to further illustrate the code’s flexibility when interfacing with outside codes in a multiscale framework. For all examples, data is presented using a custom-developed visualization tool. Additional potential use cases are also addressed. Finally, the plan for upcoming features and added capabilities is discussed.

NASMAT↗
NASA NTRS2011

Modeling Pilot State in Next Generation Aircraft Alert Systems

The Next Generation Air Transportation System will introduce new, advanced sensor technologies into the cockpit that must convey a large number of potentially complex alerts. Our work focuses on the challenges associated with prioritizing aircraft sensor alerts in a quick and efficient manner, essentially determining when and how to alert the pilot This "alert decision" becomes very difficult in NextGen due to the following challenges: 1) the increasing number of potential hazards, 2) the uncertainty associated with the state of potential hazards as well as pilot slate , and 3) the limited time to make safely-critical decisions. In this paper, we focus on pilot state and present a model for anticipating duration and quality of pilot behavior, for use in a larger system which issues aircraft alerts. We estimate pilot workload, which we model as being dependent on factors including mental effort, task demands. and task performance. We perform a mathematically rigorous analysis of the model and resulting alerting plans. We simulate the model in software and present simulated results with respect to manipulation of the pilot measures.

Carlin, Alan S.↗
NASA NTRS2018

International Space Station Future Correlation Analysis Improvements

Ongoing modal analyses and model correlation are performed on different configurations of the International Space Station (ISS). These analyses utilize on-orbit dynamic measurements collected using four main ISS instrumentation systems: External Wireless Instrumentation System (EWIS), Internal Wireless Instrumentation System (IWIS), Space Acceleration Measurement System (SAMS), and Structural Dynamic Measurement System (SDMS). Remote Sensor Units (RSUs) are network relay stations that acquire flight data from sensors. Measured data is stored in the Remote Sensor Unit (RSU) until it receives a command to download data via RF to the Network Control Unit (NCU). Since each RSU has its own clock, it is necessary to synchronize measurements before analysis. Imprecise synchronization impacts analysis results. A study was performed to evaluate three different synchronization techniques: (i) measurements visually aligned to analytical time-response data using model comparison, (ii) Frequency Domain Decomposition (FDD), and (iii) lag from cross-correlation to align measurements. This paper presents the results of this study.

time synchronization↗
NASA NTRSDate not supplied

Comprehensive Analysis Aeroelastic Stability Predictions for the Mars Sample Recovery Helicopters and Ingenuity

A rotorcraft comprehensive analysis was used to generate aeroelastic stability predictions for both Ingenuity and the Mars Sample Recovery Helicopters. The analysis was performed multiple times for each rotor system with sequential increases to the level of modeling complexity. Initial cases used an independent blade analysis, trim inflow distribution, no airframe degrees of freedom, and a hover condition (a time-invariant problem). The final model used all blades, dynamic inflow, airframe degrees of freedom, and a Floquet theory approach to the flutter analysis. The approach of sequentially increasing modeling complexity was employed to ensure the causes of any observed instabilities could be identified. For each case, stability results were determined across a range of air densities, tip Mach numbers, and rotor collective pitch settings. For the Sample Recovery Helicopter, a forward flight condition analysis with the highest level of modeling complexity was also performed. The aeroelastic stability predictions showed both the Ingenuity and Sample Recovery Helicopter rotor systems to be stable for all analyzed conditions. Parameter excursions of structural properties were performed to explore conditions resulting in aeroelastic instabilities.

Aeroelastic↗
DOE OSTI2024

On the Representativity of Electrode Microstructure Parameters and Their Electrochemical Response for Lithium Ion Batteries

Lithium-ion battery electrochemical models require an accurate description of the electrodes microstructures to be predictive that can be achieved through nanoscale imaging. Such observations are however limited by their field of view (FOV), as they provide only a subset of the whole electrode volume that does not necessarily represent the whole electrode microstructure heterogeneity, and therefore can bias the microstructure analysis. A microstructure scale electrochemical model was used to investigate lithium plating onset, material non-uniform utilization, and in-plane heterogeneities for an NMC-graphite full cell. To evaluate the representativeness, and thus relevance, of these model predictions, a coupled representativity analysis has been performed on the microstructure parameters and, in a novel way, on the full cell electrochemical response. Electrode microstructure parameters representativeness has been first quantified using the representative volume element (RVE) methodology. The RVE major flaw is that ultimately it can only conclude if a FOV contains representative subvolumes of the FOV, but not if the FOV itself is representative of the electrode volume. Analysis can conclude negatively ('FOV is not representative'), but not positively ('FOV is representative'). One major contribution of this work was to quantify the convergence of the RVE size with the FOV, to actually investigate the FOV representativeness and thus partly remedy this intrinsic limitation. The analysis determined that performing a standard RVE calculation, without exploring its FOV convergence, is likely to strongly underestimate the actual RVE size. The new RVE methodology has been automated in the NREL open-source Microstructure Analysis Toolbox (MATBOX) and is available to the battery community. Representativeness of microstructure parameters is however only an intermediate step, as the end-results of an electrochemical model are performances predictions. Indeed, what is the practical consequence of a given deviation for a microstructure parameter? The microstructure parameter deviation propagations to the 3D microstructure scale electrochemical response have been then quantified for different charge rates. This defines a threshold for the microstructure parameters FOV for a desired maximum deviation of the electrochemical response. Such deviation propagation analysis is analogous to error propagation analysis and is necessary to determine the relevance of microstructure scale model predictions for macroscale predictions. Electrochemical model shows cell representative section areas are increasing with C-rate, due to higher in-plane heterogeneities, indicating larger FOVs are required specifically for fast charge modeling. Therefore, we introduced the novel concept of electrochemical RVE (eRVE) that is a function of the operating conditions (thus defined as a dynamic RVE), with an increasing dependence with the C-rate. Representativity analysis of the investigated cell determined a FOV of 144.4 x 54.4 m2 is large enough to establish a convergence on the representative section areas for low to intermediate C-rate (=2.5C), but not large enough to conclude for higher rates. This work aims to emphasize the importance of representativity analysis for LIB electrode microstructures, as it is required to estimate the error, and thus the relevance, of microstructure parameters intended to be used in macroscale models. The methodology and results can help researchers to select the relevant imaging and associated FOV required to provide accurate enough microstructure parameters.

ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1987

Validation of an interior noise prediction model for a composite cylinder

An acoustic modal analysis has been performed in the cavity of a composite cylinder model of an aircraft fuselage. The filament wound, composite shell is 12 feet long and 5.5 feet in diameter. A one-half-in. thick plywood floor is attached to the shell 69 deg from the vertical centerline through the bottom of the shell. The acoustic modal frequencies were obtained from a sound pressure level and phase survey conducted throughout the interior volume bounded by the floor, endcaps and stiffened shell, while being excited by white noise from a loudspeaker source. The measured acoustic resonance frequencies and mode shapes compare well with analytical predictions from the Propeller Aircraft Interior Noise (PAIN) model. Details of the theory and derivation of the acoustic characteristics have been included. Reverberation time measurements, using the integrated impulse technique, have been performed to determine acoustic loss factors. These measured loss factors have been input to the PAIN program in order to more accurately predict the space-averaged interior noise of the composite cylinder.

Beyer, Todd B.↗
NASA NTRS2013

Automated Loads Analysis System (ATLAS)

ATLAS is a generalized solution that can be used for launch vehicles. ATLAS is used to produce modal transient analysis and quasi-static analysis results (i.e., accelerations, displacements, and forces) for the payload math models on a specific Shuttle Transport System (STS) flight using the shuttle math model and associated forcing functions. This innovation solves the problem of coupling of payload math models into a shuttle math model. It performs a transient loads analysis simulating liftoff, landing, and all flight events between liftoff and landing. ATLAS utilizes efficient and numerically stable algorithms available in MSC/NASTRAN.

Gardner, Stephen↗
DOE OSTI2022

Tritium Transport Modeling at the Pore Scale in Ceramic Breeder Materials Using TMAP8

Fusion reactors depend on the blanket material to breed and release tritium at the same rate or faster than it is consumed by the fusion reaction. Cellular ceramic breeders (CCBs) are dense materials that can maintain a high tritium breeding ratio while promoting tritium release because of highly connected pores. Assessing the tritium breeding capabilities of these materials requires a combination of extensive experimental and modeling efforts. In this work, we develop and calibrate a multiphysics model of tritium transport. This novel model accounts for ceramic and pore diffusion, trapping and detrapping, and several surface reactions at the pore surface. We perform a sensitivity analysis and calibrate the model by comparing its predictions against experimental measurements of deuterium absorption. The calibrated model is then used to model tritium absorption in samples with different pore microstructures to investigate the effect of pore interconnectivity on tritium absorption. The model is part of the development of the multiscale, multiphysics framework for tritium transport [i.e., the Tritium Migration Analysis Program (TMAP8)], which is itself built on top of the finite-element multiphysics framework multiphysics object-oriented simulation environment (MOOSE). This study demonstrates some of TMAP8’s capabilities and is the first step toward assessing the tritium breeding capabilities of ceramic breeder material designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗