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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Calibration of elastoplastic constitutive model parameters from full-field data with automatic differentiation-based sensitivities

Here, we present a framework for calibration of parameters in elastoplastic constitutive models that is based on the use of automatic differentiation (AD). The model calibration problem is posed as a partial differential equation-constrained optimization problem where a finite element (FE) model of the coupled equilibrium equation and constitutive model evolution equations serves as the constraint. The objective function quantifies the mismatch between the displacement predicted by the FE model and full-field digital image correlation data, and the optimization problem is solved using gradient-based optimization algorithms. Forward and adjoint sensitivities are used to compute the gradient at considerably less cost than its calculation from finite difference approximations. Through the use of AD, we need only to write the constraints in terms of AD objects, where all of the derivatives required for the forward and inverse problems are obtained by appropriately seeding and evaluating these quantities. We present three numerical examples that verify the correctness of the gradient, demonstrate the AD approach's parallel computation capabilities via application to a large-scale FE model, and highlight the formulation's ease of extensibility to other classes of constitutive models.

42 ENGINEERING↗
DOE OSTI2024

Emulator-Based Bayesian Calibration of the CISNET Colorectal Cancer Models

Purpose To calibrate Cancer Intervention and Surveillance Modeling Network (CISNET)'s SimCRC, MISCAN-Colon, and CRC-SPIN simulation models of the natural history colorectal cancer (CRC) with an emulator-based Bayesian algorithm and internally validate the model-predicted outcomes to calibration targets.Methods We used Latin hypercube sampling to sample up to 50,000 parameter sets for each CISNET-CRC model and generated the corresponding outputs. We trained multilayer perceptron artificial neural networks (ANNs) as emulators using the input and output samples for each CISNET-CRC model. We selected ANN structures with corresponding hyperparameters (i.e., number of hidden layers, nodes, activation functions, epochs, and optimizer) that minimize the predicted mean square error on the validation sample. We implemented the ANN emulators in a probabilistic programming language and calibrated the input parameters with Hamiltonian Monte Carlo-based algorithms to obtain the joint posterior distributions of the CISNET-CRC models' parameters. We internally validated each calibrated emulator by comparing the model-predicted posterior outputs against the calibration targets.Results The optimal ANN for SimCRC had 4 hidden layers and 360 hidden nodes, MISCAN-Colon had 4 hidden layers and 114 hidden nodes, and CRC-SPIN had 1 hidden layer and 140 hidden nodes. The total time for training and calibrating the emulators was 7.3, 4.0, and 0.66 h for SimCRC, MISCAN-Colon, and CRC-SPIN, respectively. The mean of the model-predicted outputs fell within the 95% confidence intervals of the calibration targets in 98 of 110 for SimCRC, 65 of 93 for MISCAN, and 31 of 41 targets for CRC-SPIN.Conclusions Using ANN emulators is a practical solution to reduce the computational burden and complexity for Bayesian calibration of individual-level simulation models used for policy analysis, such as the CISNET CRC models. In this work, we present a step-by-step guide to constructing emulators for calibrating 3 realistic CRC individual-level models using a Bayesian approach.

artificial neural networks↗
DOE OSTI2026

APOLLO: a facility-scale differentiable virtual accelerator for Fermilab

As the design complexity of modern accelerators grows, there is more interest in using advanced simulations that have fast execution time or yield additional insights like gradients. The FAST/IOTA facility has been working on implementing and experimentally validating an end-to-end digital twin that is both fast and gradient-aware, allowing for rapid prototyping of new software and experiments with minimal beam time costs. Our framework integrates physics and ML codes for linac and ring simulation through a set of generic interfaces between surrogate and physics-based sections. To reproduce device inputs and outputs, system state is exposed as a deterministic discrete event simulator. Because Fermilab is undergoing control system transition, both EPICS and ACNET frontends are supported. Recently, we have begun transitioning to a new community lattice standard, PALS, as well as developing standardized infrastructure for data ingest and normalization to prepare for model calibration during FAST proton injector commissioning. We discuss implementation details as well as challenges, and future plans to extend modelling to main complex proton accelerators like PIPII and Booster.

Kuklev, Nikita [Fermilab]↗
NASA NTRS1975

An experimental summary of plasma arc exposures of space shuttle high-temperature reusable surface insulation tile array with a single missing tile (conducted at the Ames Research Center)

A space shuttle high temperature reusable surface insulation (HRSI) tile array with a single missing or lost tile was exposed to a hot gas simulated reentry environment to investigate the heating conditions in and around the vicinity of the missing HRSI tile. Heat flux and pressure data for the lost tile condition were obtained by the use of a water cooled lost tile calibration model. The maximum aluminum substrate temperature obtained during the simulated reentry was 128 C (263 F). The lost tile calibration data indicated a maximum heat flux in the lost tile cavity region of 63 percent of the upstream reference value. This test was conducted at the Ames Research Center in the 20 MW semielliptical thermal protection system (TPS) pilot plasma arc test facility.

Galanter, S. A.↗
NASA NTRS1989

Predictions Of Fatigue Damage From Strain Histories

Semiempirical mathematical model of fatigue damage in stressed objects uses experimental histories of strains in those objects to predict fatigue lives. Accounts for initiation and propagation of fatigue cracks on cycle-by-cycle basis. Measured strain history first digitized, then converted to history of turning-point strains for purposes of analysis. Data between turning points not used. When model calibrated against proper test data for each type of object characterized, its predictions of fatigue lives superior to statistical models as one based on root-mean-square strain.

Sire, Robert A.↗
NASA NTRS1989

Characterizations of the Earth Radiation Budget Experiment (ERBE) scanning radiometers

NASA's Earth Radiation Budget Experiment employs the Earth Radiation Budget Satellite and the NOAA 9 and 10 spacecraft to obtain absolute measurements of incoming solar radiation, shortwave earth-reflected solar radiation, and longwave earth-emitted radiation, using both scanning and nonscanning radiometers. Each of the three remote-sensing spacecraft carry narrow FOV scanning radiometers whose detection sensors are thermistor bolometers. Attention is presently given to the calibration models and methods employed in characterizing the scanning radiometers' output signals; the design features of the scanners and flight calibration systems are presented.

Lee, Robert B., III↗
DOE OSTI2021

Estimating the value of jointly optimized electric power generation and end use: a study of ISO-scale load shaping applied to the residential building stock

A generation-to-load simulation estimated the impact, in terms of production costs and CO2 emissions, attributable to the joint optimization of electric power generation and flexible end uses to support increasing penetrations of renewable energy. Newly conceived, evaluated, and foundational in developing a U.S. National Standard was a transaction-less yet continuous demand response system based on a day-ahead optimum load shape (OLS) designed to encourage Internet-connected devices to autonomously and voluntarily explore options to favour lowest cost generators - without requiring two-way communications, personally identifiable information, or customer opt-in. Boundary conditions used for model calibration included historical weather, residential building stock construction attributes, home appliance and device empirical operating schedules, prototypical power distribution feeder models, thermal generator heat rates, startup and ramping constraints, and fuel costs. Results of an hourly-based annual case study of Texas indicate a 1/3 reduction in production costs and a 1/5 reduction in CO2 emissions are possible.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Modeling reaction histories to study chemical pathways in condensed phase detonation

The estimation of pressure and temperature histories, which are required to understand chemical pathways in condensed phase explosives during detonation, is discussed. We argue that estimates made from continuum models, calibrated by macroscopic experiments, are essential to inform modern, atomistic-based reactive chemistry simulations at detonation pressures and temperatures. We present easy to implement methods for general equation of state and arbitrarily complex chemical reaction schemes that can be used to compute reactive flow histories for the constant volume, the energy process, and the expansion process on the Rayleigh line of a steady Chapman-Jouguet detonation. A brief review of state-of-the-art of two-component reactive flow models is given that highlights the Ignition and Growth model of Lee and Tarver [Phys. Fluids 23, 2362 (1980)] and the Wide-Ranging Equation of State model of Wescott, Stewart, and Davis [J. Appl. Phys. 98, 053514 (2005)]. We discuss evidence from experiments and reactive molecular dynamic simulations that motivate models that have several components, instead of the two that have traditionally been used to describe the results of macroscopic detonation experiments. We present simplified examples of a formulation for a hypothetical explosive that uses simple (ideal) equation of state forms and detailed comparisons. Then, we estimate pathways computed from two-component models of real explosive materials that have been calibrated with macroscopic experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Advanced Models of LWR Pressure Vessel Embrittlement for Low Flux-High Fluence Conditions

Neutron embrittlement of reactor pressure vessels (RPVs) is an unresolved issue for light water reactor life extension, especially since transition temperature shifts (TTS) must be predicted for high 80-year fluence levels up to approximately 1,020 n/cm 2 , far beyond the current surveillance database. Unfortunately, TTS may accelerate at high fluence, and may be further amplified by the formation of late blooming phases that result in severe embrittlement even in low-copper (Cu) steels. Embrittlement by this mechanism is a potentially significant degradation phenomenon that is not predicted by current regulatory models. This project will focus on accurately predicting transition temperature shifts at high fluence using advanced physically based, empirically validated and calibrated models. A major challenge is to develop models that can adjust test reactor data to account for flux effects. Since transition temperature shifts depend on synergistic combinations of many variables, flux-effects cannot be treated in isolation. The best current models systematically and significantly under-predict transition temperature at high fluence, although predominantly for irradiations at much higher flux than actual RPV service. This project will integrate surveillance, test reactor and mechanism data with advanced models to address a number of outstanding RPV embrittlement issues. The effort will include developing new databases and preliminary models of flux effects for irradiation conditions ranging from very low (e.g., boiling water reactor) to high (e.g., accelerated test reactor). The team will also develop a database and physical models to help predict the conditions for the formation of Mn-Ni-Si late blooming phases and to guide future efforts to fully resolve this issue. Researchers will carry out other tasks on a best-effort basis, including prediction of transition temperature shift attenuation through the vessel wall, remediation of embrittlement by annealing, and fracture toughness master curve issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Comparison of temperature adaptive calibration methods for laser induced fluorescence based fuel-in-oil instrument

Fuel dilution of engine oil (or fuel-in-oil, FiO) is an important issue as multiple and late-cycle fuel injection, integral to many combustion efficiency and emissions improvements (e.g., downsized boosted gasoline engines and catalyst thermal management) increases FiO rate. In addition to causing general wear and corrosion in engine due to decreased oil viscosity and pH buffering, FiO is also believed to cause destructive low speed pre-ignition (or super knock) in boosted SI engines. To understand the effects of engine operating conditions on the FiO rate, an optical diagnostic capable of measuring transient FiO on minute timescales was recently developed and demonstrated on a modified GM Ecotech engine system (Neupane et al., Applied Spectroscopy 2021). The measurement is based on adding a dye to the fuel and monitoring for its presence in oil via laser-induced fluorescence (LIF). The measured LIF signal is related to FiO concentration via pre-determined calibration factors using a multivariate classical least square (CLS) method.Since fluorescence quantum yield is a function of temperature, measured LIF intensity not only depends on FiO concentration but also oil temperature. To expand the applicability of the FiO diagnostic to transient oil-temperature conditions (e.g., cold start in practical engines), this study develops a method to account for oil-temperature variations. The effect of oil temperature (20°C - 95°C) on the LIF spectra of eight FiO samples ranging from ~0.8-15% was investigated. LIF intensities of the FiO samples decreased linearly with increasing temperature; the reductions being more significant at dye peaks. We develop a new calibration model (T-adaptive CLS) incorporating the temperature (T) effects on LIF intensity that enables simultaneous calculation of FiO and oil temperature. The improved FiO diagnostic with T-adaptive calibration is more robust, and applicable to varying oil-temperature conditions. For example, when strategies such as multiple/late fuel injections are applied to overcome cold-start instability due to use of low vaporization bio-based fuels such as ethanol, FiO rate is expected to be very high; the improved T-adaptive FiO diagnostic is hence relevant for engine- and fuel-system calibration and optimization. The diagnostic could also provide validation data for flow-field and spray interaction CFD models, further broadening the diagnostic’s utility for advancing engine technology and efficiency.

Neupane, Sneha↗
NASA NTRS1985

Chronology of surface units on the icy satellites of Saturn

Because the impact flux history in the Saturnian system has been similar in its general form to that for the inner solar system and Jupiter, it is possible to develop an absolute calibration model for the relative ages derived from the density of impact craters. This has been done by identifying the density at which the crater populations change characteristics from that during post-accretion heavy bombardment to a later population of low but continuous flux. The transition between these two populations occurred at a known time throughout the solar system, 3.9 by, and provides an absolute calibration point on which to construct a calibration curve. Results based on calibrating relative age data to this absolute flux model suggest that most surfaces are ancient, greater than 3.9 by (or within several 100 million years). Only Enceladus and Dione have had prolonged activity that has resulted in resurfacing. The activity on Enceladus was probably driven by tidal forces, whereas the mechanism for driving resurfacing on Dione has yet to be identified.

Boyce, J. M.↗
NASA NTRS2016

Simple Parametric Model for Intensity Calibration of Cassini Composite Infrared Spectrometer Data

Accurate intensity calibration of a linear Fourier-transform spectrometer typically requires the unknown science target and the two calibration targets to be acquired under identical conditions. We present a simple model suitable for vector calibration that enables accurate calibration via adjustments of measured spectral amplitudes and phases when these three targets are recorded at different detector or optics temperatures. Our model makes calibration more accurate both by minimizing biases due to changing instrument temperatures that are always present at some level and by decreasing estimate variance through incorporating larger averages of science and calibration interferogram scans.

Brasunas, J.↗
DOE OSTI2020

Characterization of Partially Observed Epidemics - Application to COVID-19

This report documents a statistical method for the "real-time" characterization of partially observed epidemics. Observations consist of daily counts of symptomatic patients, diagnosed with the disease. Characterization, in this context, refers to estimation of epidemiological parameters that can be used to provide short-term forecasts of the ongoing epidemic, as well as to provide gross information for the time-dependent infection rate. The characterization problem is formulated as a Bayesian inverse problem, and is predicated on a model for the distribution of the incubation period. The model parameters are estimated as distributions using a Markov Chain Monte Carlo (MCMC) method, thus quantifying the uncertainty in the estimates. The method is applied to the COVID-19 pandemic of 2020, using data at the country, provincial (e.g., states) and regional (e.g. county) levels. The epidemiological model includes a stochastic component due to uncertainties in the incubation period. This model-form uncertainty is accommodated by a pseudo-marginal Metropolis-Hastings MCMC sampler, which produces posterior distributions that reflect this uncertainty. We approximate the discrepancy between the data and the epidemiological model using Gaussian and negative binomial error models; the latter was motivated by the over-dispersed count data. For small daily counts we find the performance of the calibrated models to be similar for the two error models. For large daily counts the negative-binomial approximation is numerically unstable unlike the Gaussian error model. Application of the model at the country level (for the United States, Germany, Italy, etc.) generally provided accurate forecasts, as the data consisted of large counts which suppressed the day-to-day variations in the observations. Further, the bulk of the data is sourced over the duration before the relaxation of the curbs on population mixing, and is not confounded by any discernible country-wide second wave of infections. At the state-level, where reporting was poor or which evinced few infections (e.g., New Mexico), the variance in the data posed some, though not insurmountable, difficulties, and forecasts were able to capture the data with large uncertainty bounds. The method was found to be sufficiently sensitive to discern the flattening of the infection and epidemic curve due to shelter-in-place orders after around 90% quantile for the incubation distribution (about 10 days for COVID-19). The proposed model was also used at a regional level to compare the forecasts for the central and north-west regions of New Mexico. Modeling the data for these regions illustrated different disease spread dynamics captured by the model. While in the central region the daily counts peaked in the late April, in the north-west region the ramp-up continued for approximately three more weeks.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

Tidal disruption of Periodic Comet Shoemaker-Levy 9 and a constraint on its mean density

The apparent tidal disruption of Periodic Comet Shoemaker-Levy 9 (1993e) during a close encounter within approximately 1.62 planetary radii of Jupiter can be used along with theoretical models of tidal disruption to place an upper bound on the density of the predisruption body. Depending on the theoretical model used, these upper bounds range from rho(sub c) less than 0.702 +/- 0.080 g/cu cm for a simple analytical model calibrated by numerical smoothed particle hydrodynamics (SPH) simulations to rho(sub c) less than 1.50 +/- 0.17 g/cu cm for a detailed semianalytical model. The quoted uncertainties stem from an assumed uncertainty in the perijove radius. However, the uncertainty introduced by the different theoretical models is the major source of error; this uncertainty could be eliminated by future SPH simulations specialized to cometary disruptions, including the effects of initially prolate, spinning comets. If the SPH-based upper bound turns out to be most appropriate, it would be consistent with the predisruption body being a comet with a relatively low density and porous structure, as has been asserted previously based on observations of cometary outgassing. Regardless of which upper bound is preferable, the models all agree that the predisruption body could not have been a relatively high-density body, such as an asteroid with rho approximately = 2 g/cu cm.

Boss, Alan P.↗
DOE OSTI2022

Microstructure-Sensitive Uncertainty Quantification for Crystal Plasticity Finite Element Constitutive Models Using Stochastic Collocation Methods

Uncertainty quantification (UQ) plays a major role in verification and validation for computational engineering models and simulations, and establishes trust in the predictive capability of computational models. In the materials science and engineering context, where the process-structure-property-performance linkage is well known to be the only road mapping from manufacturing to engineering performance, numerous integrated computational materials engineering (ICME) models have been developed across a wide spectrum of length-scales and time-scales to relieve the burden of resource-intensive experiments. Within the structure-property linkage, crystal plasticity finite element method (CPFEM) models have been widely used since they are one of a few ICME toolboxes that allows numerical predictions, providing the bridge from microstructure to materials properties and performances. Several constitutive models have been proposed in the last few decades to capture the mechanics and plasticity behavior of materials. While some UQ studies have been performed, the robustness and uncertainty of these constitutive models have not been rigorously established. In this work, we apply a stochastic collocation (SC) method, which is mathematically rigorous and has been widely used in the field of UQ, to quantify the uncertainty of three most commonly used constitutive models in CPFEM, namely phenomenological models (with and without twinning), and dislocation-density-based constitutive models, for three different types of crystal structures, namely face-centered cubic (fcc) copper (Cu), body-centered cubic (bcc) tungsten (W), and hexagonal close packing (hcp) magnesium (Mg). Our numerical results not only quantify the uncertainty of these constitutive models in stress-strain curve, but also analyze the global sensitivity of the underlying constitutive parameters with respect to the initial yield behavior, which may be helpful for robust constitutive model calibration works in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advancing the Representation of Human Actions in Large‐Scale Hydrological Models: Challenges and Future Research Directions

Characterizing the impact of human actions on terrestrial water fluxes and storages at multi-basin, continental, and global scales has long been on the agenda of scientists engaged in climate science, hydrology, and water resources systems analysis. This need has resulted in a variety of modeling efforts focused on the representation of water infrastructure operations. Yet, the representation of human-water interactions in large-scale hydrological models is still relatively crude, fragmented across models, and often achieved at coarse resolutions (~10–100 km) that cannot capture local water management decisions. In this commentary, we argue that the concomitance of four drivers and innovations is poised to change the status quo: “hyper-resolution” hydrological models (~0.1–1 km), multi-sector modeling, satellite missions able to monitor the outcome of human actions, and machine learning are creating a fertile environment for human-water research to flourish. We then outline four challenges that chart future research in hydrological modeling: (a) creating hyper-resolution global data sets of water management practices, (b) improving the characterization of anthropogenic interventions on water quantity, stream temperature, and sediment transport, (c) improving model calibration and diagnostic evaluation, and (d) reducing the computational requirements associated with the successful exploration of these challenges. Overcoming them will require addressing modeling, computational, and data development needs that cut across the hydrology community, thereby requiring a major communal effort.

catchment hydrology↗
DOE OSTI2021

A synthetic building operation dataset

Abstract This paper presents a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with 1395 annual simulations using the U.S. DOE detailed medium-sized reference office building, and 30 years’ historical weather data in three typical climates including Miami, San Francisco, and Chicago. Three energy efficiency levels of the building and systems are considered. Assumptions regarding occupant movements, occupants’ diverse temperature preferences, lighting, and MELs are adopted to reflect realistic building operations. A semantic building metadata schema - BRICK, is used to store the building metadata. The dataset is saved in a 1.2 TB of compressed HDF5 file. This dataset can be used in various applications, including building energy and load shape benchmarking, energy model calibration, evaluation of occupant and weather variability and their influences on building performance, algorithm development and testing for thermal and energy load prediction, model predictive control, policy development for reinforcement learning based building controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗