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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
DOE OSTI2024

A Bayesian Multi-fidelity Neural Network to Predict Nonlinear Frequency Backbone Curves

The use of structural mechanics models during the design process often leads to the development of models of varying fidelity. Often low-fidelity models are efficient to simulate but lack accuracy, while the high-fidelity counterparts are accurate with less efficiency. Here, this paper presents a multi-fidelity surrogate modeling approach that combines the accuracy of a high-fidelity finite element model with the efficiency of a low-fidelity model to train an even faster surrogate model that parameterizes the design space of interest. The objective of these models is to predict the nonlinear frequency backbone curves of the Tribomechadynamics Research Challenge benchmark structure which exhibits simultaneous nonlinearities from frictional contact and geometric nonlinearity. The surrogate model consists of an ensemble of neural networks that learn the mapping between low and high-fidelity data through nonlinear transformations. Bayesian neural networks are used to assess the surrogate model's uncertainty. Once trained, the multi-fidelity neural network is used to perform sensitivity analysis to assess the influence of the design parameters on the predicted backbone curves. Additionally, Bayesian calibration is performed to update the input parameter distributions to correlate the model parameters to the collection of experimentally measured backbone curves.

42 ENGINEERING↗
DOE OSTI2015

SU-E-J-234: Application of a Breathing Motion Model to ViewRay Cine MR Images

Purpose: A respiratory motion model previously used to generate breathing-gated CT images was used with cine MR images. Accuracy and predictive ability of the in-plane models were evaluated. Methods: Sagittalplane cine MR images of a patient undergoing treatment on a ViewRay MRI/radiotherapy system were acquired before and during treatment. Images were acquired at 4 frames/second with 3.5 × 3.5 mm resolution and a slice thickness of 5 mm. The first cine frame was deformably registered to following frames. Superior/inferior component of the tumor centroid position was used as a breathing surrogate. Deformation vectors and surrogate measurements were used to determine motion model parameters. Model error was evaluated and subsequent treatment cines were predicted from breathing surrogate data. A simulated CT cine was created by generating breathing-gated volumetric images at 0.25 second intervals along the measured breathing trace, selecting a sagittal slice and downsampling to the resolution of the MR cines. A motion model was built using the first half of the simulated cine data. Model accuracy and error in predicting the remaining frames of the cine were evaluated. Results: Mean difference between model predicted and deformably registered lung tissue positions for the 28 second preview MR cine acquired before treatment was 0.81 +/− 0.30 mm. The model was used to predict two minutes of the subsequent treatment cine with a mean accuracy of 1.59 +/− 0.63 mm. Conclusion: Inplane motion models were built using MR cine images and evaluated for accuracy and ability to predict future respiratory motion from breathing surrogate measurements. Examination of long term predictive ability is ongoing. The technique was applied to simulated CT cines for further validation, and the authors are currently investigating use of in-plane models to update pre-existing volumetric motion models used for generation of breathing-gated CT planning images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-AB-303-06: Does Online Adaptive Radiation Therapy Mean Zero Margin for Intermediate-Risk Prostate Cancer? An Intra-Fractional Seminal Vesicles Motion Analysis

Purpose: To provide benchmark for seminal vesicles (SVs) margin selection to account for intra-fractional motion; and to investigate the effectiveness of two motion surrogates in predicting intra-fractional SV underdosage. Methods: 9 prostate SBRT patients were studied; each has five pairs of pre-treatment and post-treatment cone-beam CTs (CBCTs). Each pair of CBCTs was registered based on fiducial markers in the prostate. To provide “ground truth” for coverage evaluation, all pre-treatment SVs were expanded with isotropic margin of 1,2,3,5 and 8mm, and their overlap with post-treatment SVs were used to quantify intra-fractional coverage. Two commonly used motion surrogates, the center-of-mass (COM) and the border of contour (the most distal points in SI/AP/LR directions) were evaluated using Receiver-Operating Characteristic (ROC) analyses for predicting SV underdosage due to intra-fractional motion. Action threshold of determining underdosage for each surrogate was calculated by selecting the optimal balancing between sensitivity and specificity. For comparison, margin for each surrogate was also calculated based on traditional margin recipe. Results: 90% post-treatment SV coverage can be achieved in 47%, 82%, 91%, 98% and 98% fractions for 1,2,3,5 and 8mm margins. 3mm margin ensured the 90% intra-fractional SV coverage in 90% fractions when prostate was aligned. The ROC analysis indicated the AUC for COM and border were 0.88 and 0.72. The underdosage threshold was 2.9mm for COM and 4.1mm for border. The Van Herk’s margin recipe recommended 0.5, 0 and 1.8mm margin in LR, AP and SI direction based on COM and for border, the corresponding margin was 2.1, 4.5 and 3mm. Conclusion: 3mm isotropic margin is the minimum required to mitigate the intra-fractional SV motion when prostate is aligned. ROC analysis reveals that both COM and border are acceptable predictors for SV underdosage with 2.9mm and 4.1mm action threshold. Traditional margin calculation is less reliable for this application. This work is partially supported a master research grant from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Accelerated iterative beam angle selection in IMRT

Purpose: Iterative methods for beam angle selection (BAS) for intensity-modulated radiation therapy (IMRT) planning sequentially construct a beneficial ensemble of beam directions. In a naïve implementation, the nth beam is selected by adding beam orientations one-by-one from a discrete set of candidates to an existing ensemble of (n − 1) beams. The best beam orientation is identified in a time consuming process by solving the fluence map optimization (FMO) problem for every candidate beam and selecting the beam that yields the largest improvement to the objective function value. This paper evaluates two alternative methods to accelerate iterative BAS based on surrogates for the FMO objective function value. Methods: We suggest to select candidate beams not based on the FMO objective function value after convergence but (1) based on the objective function value after five FMO iterations of a gradient based algorithm and (2) based on a projected gradient of the FMO problem in the first iteration. The performance of the objective function surrogates is evaluated based on the resulting objective function values and dose statistics in a treatment planning study comprising three intracranial, three pancreas, and three prostate cases. Furthermore, iterative BAS is evaluated for an application in which a small number of noncoplanar beams complement a set of coplanar beam orientations. This scenario is of practical interest as noncoplanar setups may require additional attention of the treatment personnel for every couch rotation. Results: Iterative BAS relying on objective function surrogates yields similar results compared to naïve BAS with regard to the objective function values and dose statistics. At the same time, early stopping of the FMO and using the projected gradient during the first iteration enable reductions in computation time by approximately one to two orders of magnitude. With regard to the clinical delivery of noncoplanar IMRT treatments, we could show that optimized beam ensembles using only a few noncoplanar beam orientations often approach the plan quality of fully noncoplanar ensembles. Conclusions: We conclude that iterative BAS in combination with objective function surrogates can be a viable option to implement automated BAS at clinically acceptable computation times.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Preliminary results on the feasibility of using ultrasound to monitor intrafractional motion during radiation therapy for pancreatic cancer

Purpose: Substantial intrafraction organ motion during radiation therapy (RT) for pancreatic cancer is well recognized as a major limiting factor for accurate delivery of RT. The aim of this work is to determine the feasibility of monitoring the intrafractional motion of the pancreas or surrounding structures using ultrasound for RT delivery. Methods: Transabdominal ultrasound (TAUS) and 4DCT data were acquired on ten pancreatic cancer patients during radiation therapy process in a prospective study. In addition, TAUS and MRI were collected for five healthy volunteers. The portal vein (PV) and the head of the pancreas (HP) along with other structures were contoured on these images. Volume changes, distance between the HP and PV, and motion difference between the HP and PV were measured to examine whether PV can be used as a motion surrogate for HP. TAUS images were acquired and processed using a research version of the Clarity autoscan ultrasound system (CAUS). Motion monitoring was performed with the ultrasound probe mounted on an arm fixed to the couch. Video segments of the monitoring sessions were captured. Results: On TAUS, PV is better visualized than HP. The measured mean volume deviation for all patients for the HP and PV was 1.4 and 0.6 ml, respectively. The distance between the HP and PV was close to a constant with 0.22 mm mean deviation throughout the ten breathing phases. The mean of the absolute motion difference for all patients was 1.7 ± 0.8 mm in LR, 1.5 ± 0.5 mm in AP, and 2.3 ± 0.7 mm in SI, suggesting that the PV is a good surrogate for HP motion estimation. By using this surrogate, the HP motion tracking using TAUS was demonstrated. Conclusions: Large intrafractional organ motion due to respiratory and/or bowel motion is a limiting factor in administering curative radiation doses to pancreatic tumors. The authors investigate the use of real-time ultrasound to track pancreas motion. Due to the poor visibility of the pancreas head on an ultrasound image, the portal vein is identified as a surrogate. The authors have demonstrated the feasibility of tracking HP motion through the localization of the PV using TAUS. This will potentially allow real-time tracking of intrafractional motion to justify small PTV-margins and to account for unusual motions, thus, improving normal tissue sparing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Tencoder: tensor-product encoder-decoder architecture for predicting solutions of PDEs with variable boundary data

It is widely hoped that artificial intelligence will boost data-driven surrogate models in science and engineering. However, fundamental spatial aspects of AI surrogate models remain under-studied. We investigate the ability of neural-network surrogate models to predict solutions to PDEs under variable boundary values. We do not wish to retrain the model when the boundary values change but to make them inputs to the model and infer the solution of the PDE under those boundary conditions. Such a capability is essential to making AI-based surrogate models practically useful. While simple feedforward networks are used for one-dimensional (1D) Poisson equation, an encoder-decoder architecture with a tensor-product layer is developed for the two-dimensional Poisson equation posed on a rectangular domain. We show that it is indeed possible to infer solutions to PDEs from variable boundary data using neural networks in this relatively simple setting, and point to future directions.

Kashi, Aditya↗
DOE OSTI2023

Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation

Abstract This study proposes and assesses a methodology to obtain high-quality probabilistic predictions and uncertainty information of near-landfall tropical cyclone–driven (TC-driven) storm tide and inundation with limited time and resources. Forecasts of TC track, intensity, and size are perturbed according to quasi-random Korobov sequences of historical forecast errors with assumed Gaussian and uniform statistical distributions. These perturbations are run in an ensemble of hydrodynamic storm tide model simulations. The resulting set of maximum water surface elevations are dimensionality reduced using Karhunen–Loève expansions and then used as a training set to develop a polynomial chaos (PC) surrogate model from which global sensitivities and probabilistic predictions can be extracted. The maximum water surface elevation is extrapolated over dry points incorporating energy head loss with distance to properly train the surrogate for predicting inundation. We find that the surrogate constructed with third-order PCs using elastic net penalized regression with leave-one-out cross validation provides the most robust fit across training and test sets. Probabilistic predictions of maximum water surface elevation and inundation area by the surrogate model at 48-h lead time for three past U.S. landfalling hurricanes (Irma in 2017, Florence in 2018, and Laura in 2020) are found to be reliable when compared to best track hindcast simulation results, even when trained with as few as 19 samples. The maximum water surface elevation is most sensitive to perpendicular track-offset errors for all three storms. Laura is also highly sensitive to storm size and has the least reliable prediction. Significance Statement The purpose of this study is to develop and evaluate a methodology that can be used to provide high-quality probabilistic predictions of hurricane-induced storm tide and inundation with limited time and resources. This is important for emergency management purposes during or after the landfall of hurricanes. Our results show that sampling forecast errors using quasi-random sequences combined with machine learning techniques that fit polynomial functions to the data are well suited to this task. The polynomial functions also have the benefit of producing exact sensitivity indices of storm tide and inundation to the forecasted hurricane properties such as path, intensity, and size, which can be used for uncertainty estimation. The code implementing the presented methodology is publicly available on GitHub.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Uncertainty quantification in elastic constants of SiC f /SiC m tubular composites using global sensitivity analysis

Silicon carbide fiber and silicon carbide matrix (SiC f /SiC m ) tubes produced through the chemical vapor infiltration process have become a candidate cladding material in nuclear applications. The performance of this composite is influenced by many variables such as braiding angle, porosity, material properties, etc., which vary over a range of values due to the inherent fluctuations in the manufacturing process. In this study, the variability in elastic constants of SiC f /SiC m composite has been quantified through multiscale finite element (FE) simulations, variable screening, and high-fidelity surrogate modeling. The key variables dominantly affecting the elastic constants of SiC f /SiC m tubes were identified using global sensitivity analysis. A surrogate to the high-fidelity FE-based model was used in Monte Carlo simulations to generate a hundred thousand samples from which the uncertainty in elastic constants was assessed. It turned out that the coefficient of variation was less than 10%.

Materials Science↗
DOE OSTI2014

Reversal bending fatigue test system for investigating vibration integrity of spent nuclear fuel during transportation

Transportation packages for spent nuclear fuel (SNF) must meet safety requirements under normal and accident conditions as specified by federal regulations. During transportation, SNF experiences unique conditions and challenges to cladding integrity due to the vibrational and impact loading during road or rail shipment. Oak Ridge National Laboratory (ORNL) has been developing testing capabilities that can be used to improve the understanding of the impacts on SNF integrity due to vibration loading, especially for high burn-up SNF in normal transportation operation conditions. This information can be used to meet the nuclear industry and U.S.Nuclear Regulatory Commission needs in the area of safety and security of SNF storage and transportation operations. The ORNL developed test system can perform reversal bending fatigue testing to evaluate both the static and dynamic mechanical response of SNF rods under simulated loads. The testing apparatus is also designed to meet the challenges of hot cell operation, including remote installation and detachment of the SNF test specimen, in situ test specimen deformation measurement, and implementation of a driving system suitable for use in a hot cell. The system contains a U frame set-up equipped with uniquely designed grip rigs to protect the SNF rod sample and to ensure valid test results, and uses three specially designed linear variable differential transformers to obtain the in situ curvature measurement. A variety of surrogate test rods have been used to develop and calibrate the test system as well as in performing a series of systematic cyclic fatigue tests. The surrogate rods include stainless steel (SS) cladding, SS cladding with cast epoxy and SS cladding with alumina pellet inserts simulating fuel pellets. Testing to date has shown that the interface bonding between the SS cladding and the alumina pellets has a significant impact on the bending response of the test rods as well as their fatigue strength. The failure behaviours observed from tested surrogate rods provide a fundamental understanding of the underlying failure mechanisms of the SNF surrogate rod under vibration,which has not been achieved previously. The newly developed device is scheduled to be installed in the hot cell in summer 2013 to test high burn-up SNF.

high burn up fuel↗
DOE OSTI2013

Tuning a RANS k-e model for jet-in-crossflow simulations.

We develop a novel calibration approach to address the problem of predictive k e RANS simulations of jet-incrossflow. Our approach is based on the hypothesis that predictive k e parameters can be obtained by estimating them from a strongly vortical flow, specifically, flow over a square cylinder. In this study, we estimate three k e parameters, C%CE%BC, Ce2 and Ce1 by fitting 2D RANS simulations to experimental data. We use polynomial surrogates of 2D RANS for this purpose. We conduct an ensemble of 2D RANS runs using samples of (C%CE%BC;Ce2;Ce1) and regress Reynolds stresses to the samples using a simple polynomial. We then use this surrogate of the 2D RANS model to infer a joint distribution for the k e parameters by solving a Bayesian inverse problem, conditioned on the experimental data. The calibrated (C%CE%BC;Ce2;Ce1) distribution is used to seed an ensemble of 3D jet-in-crossflow simulations. We compare the ensemble's predictions of the flowfield, at two planes, to PIV measurements and estimate the predictive skill of the calibrated 3D RANS model. We also compare it against 3D RANS predictions using the nominal (uncalibrated) values of (C%CE%BC;Ce2;Ce1), and find that calibration delivers a significant improvement to the predictive skill of the 3D RANS model. We repeat the calibration using surrogate models based on kriging and find that the calibration, based on these more accurate models, is not much better that those obtained with simple polynomial surrogates. We discuss the reasons for this rather surprising outcome.

Lefantzi, Sophia↗
DOE OSTI2014

Fuel assembly shaker and truck test simulation

This study continues the modeling support of the SNL shaker table task from 2013 and includes analysis of the SNL 2014 truck test campaign. Detailed finite element models of the fuel assembly surrogate used by SNL during testing form the basis of the modeling effort. Additional analysis was performed to characterize and filter the accelerometer data collected during the SNL testing. The detailed fuel assembly finite element model was modified to improve the performance and accuracy of the original surrogate fuel assembly model in an attempt to achieve a closer agreement with the low strains measured during testing. The revised model was used to recalculate the shaker table load response from the 2013 test campaign. As it happened, the results remained comparable to the values calculated with the original fuel assembly model. From this it is concluded that the original model was suitable for the task and the improvements to the model were not able to bring the calculated strain values down to the extremely low level recorded during testing. The model needs more precision to calculate strains that are so close to zero. The truck test load case had an even lower magnitude than the shaker table case. Strain gage data from the test was compared directly to locations on the model. Truck test strains were lower than the shaker table case, but the model achieved a better relative agreement of 100-200 microstrains (or 0.0001-0.0002 mm/mm). The truck test data included a number of accelerometers at various locations on the truck bed, surrogate basket, and surrogate fuel assembly. This set of accelerometers allowed an evaluation of the dynamics of the conveyance system used in testing. It was discovered that the dynamic load transference through the conveyance has a strong frequency-range dependency. This suggests that different conveyance configurations could behave differently and transmit different magnitudes of loads to the fuel even when traveling down the same road at the same speed. It is recommended that the SNL conveyance system used in testing be characterized through modal analysis and frequency response analysis to provide context and assist in the interpretation of the strain data that was collected during the truck test campaign.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

L3.PHI.CTF.P10.02-rev2 Coupling of Subchannel T/H (CTF) and CRUD Chemistry (MAMBA1D)

The purpose of this milestone is to create a preliminary capability for modeling light water reactor (LWR) thermal-hydraulic (T/H) and CRUD growth using the CTF subchannel code and the subgrid version of the MAMBA CRUD chemistry code, MAMBA1D. In part, this is a follow-on to Milestone L3.PHI.VCS.P9.01, which is documented in Report CASL-U-2014-0188-000, titled "Development of CTF Capability for Modeling Reactor Operating Cycles with Crud Growth". As the title suggests, the previous milestone set up a framework for modeling reactor operation cycles with CTF. The framework also facilitated coupling to a CRUD chemistry capability for modeling CRUD growth throughout the reactor operating cycle. To demonstrate the capability, a simple CRUD \surrogate" tool was developed and coupled to CTF; however, it was noted that CRUD growth predictions by the surrogate were not considered realistic. This milestone builds on L3.PHI.VCS.P9.01 by replacing this simple surrogate tool with the more advanced MAMBA1D CRUD chemistry code. Completing this task involves addressing unresolved tasks from Milestone L3.PHI.VCS.P9.01, setting up an interface to MAMBA1D, and extracting new T/H information from CTF that was not previously required in the simple surrogate tool. Speci c challenges encountered during this milestone include (1) treatment of the CRUD erosion model, which requires local turbulent kinetic energy (TKE) (a value that CTF does not calculate) and (2) treatment of the MAMBA1D CRUD chimney boiling model in the CTF rod heat transfer solution. To demonstrate this new T/H, CRUD modeling capability, two sets of simulations were performed: (1) an 18 month cycle simulation of a quarter symmetry model of Watts Bar and (2) a simulation of Assemblies G69 and G70 from Seabrook Cycle 5. The Watts Bar simulation is merely a demonstration of the capability. The simulation of the Seabrook cycle, which had experienced CRUD-related fuel rod failures, had actual CRUD-scrape data to compare with results. As results show, the initial CTF/MAMBA1D-predicted CRUD thicknesses were about half of their expected values, so further investigation will be required for this simulation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Partnership for Edge Physics (EPSI), University of Texas Final Report

Simulations of tokamak plasmas require a number of inputs whose values are uncertain. The effects of these input uncertainties on the reliability of model predictions is of great importance when validating predictions by comparison to experimental observations, and when using the predictions for design and operation of devices. However, high fidelity simulation of tokamak plasmas, particular those aimed at characterization of the edge plasma physics, are computationally expensive, so lower cost surrogates are required to enable practical uncertainty estimates. Two surrogate modeling techniques have been explored in the context of tokamak plasma simulations using the XGC family of plasma simulation codes. The first is a response surface surrogate, and the second is an augmented surrogate relying on scenario extrapolation. In addition, to reduce the costs of the XGC simulations, a particle resampling algorithm was developed, which allows marker particle distributions to be adjusted to maintain optimal importance sampling. This means that the total number of particles in and therefore the cost of a simulation can be reduced while maintaining the same accuracy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Demonstrate Benchtop Measurement of Recrystallization

The Mechanical Property Microscope (MPM) was used to monitor grain restructuring (recrystallization) of a metallic fuel surrogate sample. The MPM is a laser ultrasonic instrument used to measure the elastic and anelastic response of a material. The MPM has been used previously to measure the elastic constants of UZr system both as a function of composition and temperature. In this study we extend the capability of the MPM to make measurements of the resonant response a small metallic fuel surrogate as function of temperature. The fuel surrogate consists of a highly textured copper sample. By tracking specific resonant modes as a function of temperature we demonstrate that the MPM is well suited to measure grain restructuring in metallic fuel surrogates.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Addressing Model Form Error for Time-Dependent Conservation Equations

Model form error of the type considered here is error due to an approximate or incorrect representation of physics by a computational model. Typical approaches to adjust a model based on observed differences between experiment and prediction are to calibrate the model parameters utilizing the observed discrepancies and to develop parameterized additive corrections to the model output. These approaches are generally not suitable if significant physics is missing from the model and the desired quantities of interest for an application are different than those used for calibration. The approach developed here is to build a corrected surrogate solver through a multi- step process: 1) Sampled simulation results are used to develop a surrogate computational solver that maintains the overall conservative principles of the unmodified governing equations, 2) the surrogate solver is applied to candidate linear and non-linear corrector terms to develop corrections that are consistent with the original conservative principles, 3) constant multipliers on the these terms are calibrated using the experimental observations, and 4) the resulting surrogate solver is used to predict application response for the quantity of interest. This approach and several other calibration-based approaches were applied to an example problem based on the diffusive Burgers' equation. While all the approaches provided some model correction when the measure/calibration quantity was the same as that for an application, only the present approach was able to adequately correct the CompSim results when the prediction quantity was different from the calibration quantity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Criticality Control Overpack Fire Testing (Phase III)

This report will describe the one test conducted during phase III of the Pipe Overpack Container (POC) test campaign, present preliminary results from these tests, and discuss implications for the Criticality Control Overpack (CCO). The goal of this test was to see if aerosol surrogate material inside the Criticality Control Container (CCC) gets released when the drum lid of the CCO comes off during a thirty-minute long, fully-engulfing, fire test. As expected from POC tests conducted in Phase I and II of this test campaign, the CCO drum lid is ejected about one minute after the drum is exposed to fully-engulfing flames. The remaining pressure inside the drum is high enough to eject the top plywood dunnage a considerable distance from the drum. Subsequently, most of the bottom plywood dunnage supporting the CCC burns off during and after the fire. High pressure buildup inside the CCC and inside two primary containers holding the surrogate powder also results in damage to the filter media of the CCC and the filter-house, thread attachment of the primary canisters. No discernable release of surrogate powder material was detected from the two primary containers when pre- and post-test average mass were compared. However, when the average masses are corrected to account for possible uncertainties in mass measurements, error overlap does not preclude the possibility that some surrogate powder mass may have been lost from these primary canisters. Still, post-test conditions of the secondary canisters enclosing these two primary canisters suggest it is very unlikely this mass loss would have escaped into the CCC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Methods for Computing Physically Realistic Estimates of Electric Water Heater Demand Response Resource Suitable for Bulk Power System Planning Models

Demand response is commonly called on to reduce load during system peak times or to respond to contingency events. In future power systems with higher shares of wind and solar generation (which we describe together as variable generation [VG]), demand response could have more opportunities to provide energy shifting or operating reserve services. This report evaluates the ability of residential electric water heaters, both electric resistance water heaters (ERWHs) and heat pump water heaters (HPWHs), to provide such services starting from detailed whole-building energy models that realistically represent New England single family home stock. We use a parsimonious surrogate model to represent operational flexibility in a form suitable for linear and mixed integer programming. This enables relatively fast determination of aggregate contingency reserve resource, price-taking energy shifting outcomes, and in some cases the determination of aggregate models at the megawatt (MW) scale that can be directly included in large-scale grid models. After selecting modeling methods and parameters through various computational experiments, we find interquartile ranges of contingency reserve resource in ISO-NE for about 603,400 ERWHs of 45 MW - 69 MW for Claim10 (50 minute responses provided with 10 minutes of advanced notification) and 65 MW - 102 MW for Claim30 (30 minute responses provided with 30 minutes of advanced notification), and for about 619,000 HPWHs of 48 MW - 88 MW for Claim10 and 52 MW - 90 MW for Claim30. The overall reserve resource is up to 32% of total load for ERWHs providing Claim10 service, 47% for ERWHs providing Claim30 service, 93% for HPWHs providing Claim10 service, and 97% for HPWHs providing Claim30 service. More work is required to determine if HPWHs are inherently more suitable than ERWHs for providing contingency reserve or if these results reflect idiosyncrasies of the single family home stock model used in this study. The value of this contingency resource in a Near-term VG model of ISO-NE is $\$ 0.40$ to $\$1.20$ per water heater-year, and significantly larger, $\$ 3.80$ to $\$ 5.30$ per water heater-year in a Mid-term VG model of ISONE. Aggregating surrogate models to the MW-scale for energy shifting service is more challenging than for contingency service and we only present such results for ERWHs, because we were unable to determine satisfactory ways to deal with HPWHs' time-varying and path dependent operational characteristics. Individual surrogate models suitable for evaluating the energy shifting resource from both ERWHs and HPWHs are created, however, and dispatched against day-ahead prices from the Near-Term VG and Mid-Term VG models of ISO-NE. The individual surrogate models are able to access and potentially shift all 640 GWh of HPWH load and 1,547 GWh of ERWH load we modeled in two different single family home stock models. In contrast, the most effective model of aggregate ERWH shifting resource we created only captured 34.7% of the total ERWH load. Energy shifting affected by price-taking dispatch against modeled day-ahead energy prices produces per water heater year profits of $\$19.44$ - $\$22.93$ for individual HPWHs, $\$39.11$ - $\$40.54$ for individual ERWHs, and up to $\$4.00$ - $\$4.24$ for aggregated ERWHs, with the variations mainly due to grid conditions (more or less VG). When the supply-side response to these changes is accounted for, the per water heater year production cost savings for ISO-NE are $\$7.50$ to $\$17.70$ for the most effective set of endogenously dispatched aggregate ERWHs, $\$15.60$ to $\$15.70$ for individual ERWHs dispatched against the DA prices, and $\$10.70$ to $\$11.20$ for individual HPWHs dispatched against DA prices. Those ranges primarily represent the difference between Near-Term VG and Mid-Term VG grid conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Photofission Validation Measurements for Active Interrogation Standards

Executive Summary PNNL has been developing technical standards for the detection of special nuclear material (SNM) in cargo containers using active interrogation approaches. Since the use of kilogram-scale quantities of SNM is impractical for standards testing, the work focused on designing surrogates that provided similar signature as the SNM. There are many active interrogation approaches to detect SNM; the standards development considered photofission, differential die-away and nuclear resonance fluorescence. Of these approaches, photofission currently carries the most interest. However, uncertainties in the photofission cross sections are as large as 50%, so that validation measurements are necessary to provide confidence that the surrogate will perform similarly to the SNM. This document describes approaches for conducting those validation measurements as well as provides a rough order-of-magnitude cost estimate for performing them. Photofission provides many observables for the detection of SNM. The standards development considered prompt neutrons, delayed neutrons and delayed gamma rays as possible detected particles. The surrogates, which consist primarily of depleted uranium (DU), were designed to reproduce the strength of these particles for a targeted quantity of 2 kg of HEU. Different surrogates are required for different measurement approaches because of the difference in cross section between 235 U and 238 U. For the standards validations, the relative strength of the detected particles for HEU and DU must be measured. To avoid measurements with kilogram-sized SNM, the validation approach is focused on two comparisons. In the first comparison, the relative rates for approximately 10 g samples of DU and HEU will be measured. This comparison will provide the basis for validating the relative strength of the detected particles for HEU and DU. In the second comparison, the relative rates for the approximately 10 g and 1 kg sample of DU will be measured. This comparison will enable the validation of secondary processes that occur after photofission that impact the measurement for kilogram-scale samples. For instance, for 2 kg of HEU, as much as 50% of the fission induced in the sample is induced from fission neutrons generated through photofission. There is a limited range of facilities in the U.S. that have both the necessary accelerator capability and the ability and willingness to handle SNM. Two such facilities, the Idaho Accelerator Center at Idaho State University and the Nuclear Engineering Program at the University of Michigan, have both expressed an interest in participating in such measurements. Both would need to amend their licensing to handle the 10 g of HEU proposed for these measurements. The rough order-of-magnitude cost estimate for all three validation measurements is $1.1M, spread over three years. Each of the three measurements could be performed separately, at approximately one-third of that cost. There are a number of critical assumptions in these cost estimate that will need to be confirmed before a more reliable cost estimate can be established. PNNL will manage the effort to ensure that the overall objective of the validation measurements can be achieved and will fabricate the 10 g samples of HEU and DU. Most the labor for the measurements will be provided by two collaborating universities as research opportunities for students. The successful completion of these validation measurements will reduce the uncertainties in the proposed standards from about 50% to 5%. The measurements would also provide some much-needed nuclear data on photofission.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗