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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 OSTI2015

Non-adiabatic molecular dynamics by accelerated semiclassical Monte Carlo

Non-adiabatic dynamics, where systems non-radiatively transition between electronic states, plays a crucial role in many photo-physical processes, such as fluorescence, phosphorescence, and photoisomerization. Methods for the simulation of non-adiabatic dynamics are typically either numerically impractical, highly complex, or based on approximations which can result in failure for even simple systems. Recently, the Semiclassical Monte Carlo (SCMC) approach was developed in an attempt to combine the accuracy of rigorous semiclassical methods with the efficiency and simplicity of widely used surface hopping methods. However, while SCMC was found to be more efficient than other semiclassical methods, it is not yet as efficient as is needed to be used for large molecular systems. Here, we have developed two new methods: the accelerated-SCMC and the accelerated-SCMC with re-Gaussianization, which reduce the cost of the SCMC algorithm up to two orders of magnitude for certain systems. In most cases shown here, the new procedures are nearly as efficient as the commonly used surface hopping schemes, with little to no loss of accuracy. This implies that these modified SCMC algorithms will be of practical numerical solutions for simulating non-adiabatic dynamics in realistic molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Data-driven learning of Mori–Zwanzig operators for isotropic turbulence

Developing reduced-order models for turbulent flows, which contain dynamics over a wide range of scales, is an extremely challenging problem. In statistical mechanics, the Mori–Zwanzig (MZ) formalism provides a mathematically exact procedure for constructing reduced-order representations of high-dimensional dynamical systems, where the effects due to the unresolved dynamics are captured in the memory kernel and orthogonal dynamics. Turbulence models based on MZ formalism have been scarce due to the limited knowledge of the MZ operators, which originates from the difficulty in deriving MZ kernels for complex nonlinear dynamical systems. In this work, we apply a recently developed data-driven learning algorithm, which is based on Koopman's description of dynamical systems and Mori's linear projection operator, on a set of fully resolved isotropic turbulence datasets to extract the Mori–Zwanzig operators. With data augmentation using known turbulence symmetries, the extracted Markov term, memory kernel, and orthogonal dynamics are statistically converged and the generalized fluctuation–dissipation relation can be verified. The properties of the memory kernel and orthogonal dynamics, and their dependence on the choices of observables are investigated to address the modeling assumptions that are commonly used in MZ-based models. A series of numerical experiments are then constructed using the extracted kernels to evaluate the memory effects on prediction. The results show that the prediction errors are strongly affected by the choice of observables and can be further reduced by including the past history of the observables in the memory kernel.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition) on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

An Integrated Risk Assessment Process for Digital Instrumentation and Control Upgrades of Nuclear Power Plants

Most of the existing nuclear power plants (NPPs) in the world rely on traditional analog instrumentation and control (I&C) systems for monitoring, control, and protection functions. With the industrial base largely moving to digital systems, the operation and maintenance of plants involves managing issues including lack of needed analog spare parts, increasing maintenance costs, and the loss of vendor support. Compared with existing analog I&C systems, digital I&C systems have significant functional advantages, such as reliable system performance in terms of accuracy and computational capability, high data handling and storage capabilities to fully measure and display operating conditions, and improved capabilities (e.g., fault tolerance, self-testing, signal validation, process system diagnostics). Therefore, the U.S. nuclear power industry has initiated the replacement of existing, aging analog systems with digital I&C technology, and is developing new designs for advanced plants using digital systems in integrated control rooms to provide modern control and protection systems. However, the qualification of digital I&C systems remains a challenge, especially the issue of software common cause failure (CCF), which has been difficult to address. A CCF is the malfunction of two or more plant components or functions due to a single failure source. CCFs have the potential to generate unanalyzed events or sequences that may not be bounded by previous plant accident analyses, therefore, to challenge the plant safety. Existing analyses on CCF in I&C systems are mainly focusing on hardware failures. With the application and upgrades of new digital I&C systems, software CCFs due to design flaws have become a potential threat to plant safety considering most redundancy designs are using the similar digital platforms or software in the operating and application systems. With complex multi-layer redundancy designs to meet the single failure criterion, these I&C safety systems are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. Therefore, there is a need to develop an integrated risk assessment strategy with digital CCF and plant transient responses considered to assure the long-term safety and reliability of vital digital systems and reduce uncertainties in costs, time, and support integration of digital systems in the plant. The overall goal of this project is to deliver a strong technical basis to support effective, licensable, and secure digital I&C technologies for the digital upgrades to existing NPPs. To deal with the expensive licensing justifications from regulatory insights, this technical basis is instructive for nuclear vendors and utilities to effectively lower the costs associated with digital compliance and speed-up industry advances by: (1) defining an integrated risk-informed analysis process for digital I&C upgrades including hazard analysis, reliability analysis, and consequence analysis; (2) applying systematic and risk-informed tools to address CCFs and quantify responding failure probabilities for digital I&C technologies; (3) evaluating the impact of digital failures at the individual level, system level, and plant level; and (4) providing insights and suggestions on designs to manage the risks, thus to support the development, licensing, and deployment of advanced digital I&C technologies on NPPs. Upgrading digital I&C (safety and non-safety related) systems in existing NPPs within a cost-effective and regulatory acceptable way offers the foremost means of performance improvements and cost-reductions for existing NPPs. One key outcome of this project is to perform plant-specific risk assessment to provide a sustainable scientific support for enabling industry to balance the digital-related risks, costs, reliability, and safety.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

Using the Domain Name System to Thwart Automated Client-Based Attacks

On the Internet, attackers can compromise systems owned by other people and then use these systems to launch attacks automatically. When attacks such as phishing or SQL injections are successful, they can have negative consequences including server downtime and the loss of sensitive information. Current methods to prevent such attacks are limited in that they are application-specific, or fail to block attackers. Phishing attempts can be stopped with email filters, but if the attacker manages to successfully bypass these filters, then the user must determine if the email is legitimate or not. Unfortunately, they often are unable to do so. Since attackers have a low success rate, they attempt to compensate for it in volume. In order to have this high throughput, attackers take shortcuts and break protocols. We use this knowledge to address these issues by implementing a system that can detect malicious activity and use it to block attacks. If the client fails to follow proper procedure, they can be classified as an attacker. Once an attacker has been discovered, they will be isolated and monitored. This can be accomplished using existing software in Ubuntu Linux applications, along with our custom wrapper application. After running the system and seeing its performance on three popular Web browsers Chromium, Firefox and Internet Explorer as well as two popular email clients, Thunderbird and Evolution, we found that not only is this system conceivable, it is effective and has low overhead.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2013

Fission matrix-based Monte Carlo criticality analysis of fuel storage pools

Standard Monte Carlo transport procedures experience difficulties in solving criticality problems in fuel storage pools. Because of the strong neutron absorption between fuel assemblies, source convergence can be very slow, leading to incorrect estimates of the eigenvalue and the eigenfunction. This study examines an alternative fission matrix-based Monte Carlo transport method that takes advantage of the geometry of a storage pool to overcome this difficulty. The method uses Monte Carlo transport to build (essentially) a fission matrix, which is then used to calculate the criticality and the critical flux. This method was tested using a test code on a simple problem containing 8 assemblies in a square pool. The standard Monte Carlo method gave the expected eigenfunction in 5 cases out of 10, while the fission matrix method gave the expected eigenfunction in all 10 cases. In addition, the fission matrix method provides an estimate of the error in the eigenvalue and the eigenfunction, and it allows the user to control this error by running an adequate number of cycles. Because of these advantages, the fission matrix method yields a higher confidence in the results than standard Monte Carlo. We also discuss potential improvements of the method, including the potential for variance reduction techniques. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

ACC/AATS/AHA/ASE/ASNC/HRS/SCAI/SCCT/SCMR/STS 2019 Appropriate Use Criteria for Multimodality Imaging in the Assessment of Cardiac Structure and Function in Nonvalvular Heart Disease

This document is the second of 2 companion appropriate use criteria (AUC) documents developed by the American College of Cardiology, American Association for Thoracic Surgery, American Heart Association, American Society of Echocardiography, American Society of Nuclear Cardiology, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance, and Society of Thoracic Surgeons. The first document (J Am Coll Cardiol 2017;70:1647-1672) addresses the evaluation and use of multimodality imaging in the diagnosis and management of valvular heart disease, whereas this document addresses this topic with regard to structural (nonvalvular) heart disease. While dealing with different subjects, the 2 documents do share a common structure and feature some clinical overlap. The goal of the companion AUC documents is to provide a comprehensive resource for multimodality imaging in the context of structural and valvular heart disease, encompassing multiple imaging modalities. Using standardized methodology, the clinical scenarios (indications) were developed by a diverse writing group to represent patient presentations encountered in everyday practice and included common applications and anticipated uses. Where appropriate, the scenarios were developed on the basis of the most current American College of Cardiology/American Heart Association Clinical Practice Guidelines. A separate, independent rating panel scored the 102 clinical scenarios in this document on a scale of 1 to 9. Scores of 7 to 9 indicate that a modality is considered appropriate for the clinical scenario presented. Midrange scores of 4 to 6 indicate that a modality may be appropriate for the clinical scenario, and scores of 1 to 3 indicate that a modality is considered rarely appropriate for the clinical scenario. The primary objective of the AUC is to provide a framework for the assessment of these scenarios by practices that will improve and standardize physician decision making. AUC publications reflect an ongoing effort by the American College of Cardiology to critically and systematically create, review, and categorize clinical situations in which diagnostic tests and procedures are utilized by physicians caring for patients with cardiovascular diseases. The process is based on the current understanding of the technical capabilities of the imaging modalities examined.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

On-Line Use of Three-Dimensional Marker Trajectory Estimation From Cone-Beam Computed Tomography Projections for Precise Setup in Radiotherapy for Targets With Respiratory Motion

Purpose: To develop and evaluate accurate and objective on-line patient setup based on a novel semiautomatic technique in which three-dimensional marker trajectories were estimated from two-dimensional cone-beam computed tomography (CBCT) projections. Methods and Materials: Seven treatment courses of stereotactic body radiotherapy for liver tumors were delivered in 21 fractions in total to 6 patients by a linear accelerator. Each patient had two to three gold markers implanted close to the tumors. Before treatment, a CBCT scan with approximately 675 two-dimensional projections was acquired during a full gantry rotation. The marker positions were segmented in each projection. From this, the three-dimensional marker trajectories were estimated using a probability based method. The required couch shifts for patient setup were calculated from the mean marker positions along the trajectories. A motion phantom moving with known tumor trajectories was used to examine the accuracy of the method. Trajectory-based setup was retrospectively used off-line for the first five treatment courses (15 fractions) and on-line for the last two treatment courses (6 fractions). Automatic marker segmentation was compared with manual segmentation. The trajectory-based setup was compared with setup based on conventional CBCT guidance on the markers (first 15 fractions). Results: Phantom measurements showed that trajectory-based estimation of the mean marker position was accurate within 0.3 mm. The on-line trajectory-based patient setup was performed within approximately 5 minutes. The automatic marker segmentation agreed with manual segmentation within 0.36 {+-} 0.50 pixels (mean {+-} SD; pixel size, 0.26 mm in isocenter). The accuracy of conventional volumetric CBCT guidance was compromised by motion smearing ({<=}21 mm) that induced an absolute three-dimensional setup error of 1.6 {+-} 0.9 mm (maximum, 3.2) relative to trajectory-based setup. Conclusions: The first on-line clinical use of trajectory estimation from CBCT projections for precise setup in stereotactic body radiotherapy was demonstrated. Uncertainty in the conventional CBCT-based setup procedure was eliminated with the new method.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Overview of New Tools to Perform Safety Analysis: BWR Station Black Out Test Case

Dynamic Probabilistic Risk Assessment (DPRA) methodologies couple system simulator codes (e.g., RELAP, MELCOR) with simulation controller codes (e.g., RAVEN, ADAPT). While system simulator codes accurately model system dynamics deterministically, simulation controller codes introduce both deterministic (e.g., system control logic, operating procedures) and stochastic (e.g., component failures, parameter uncertainties) elements into the simulation. Typically, a DPRA is performed by: 1) sampling values of a set of parameters from the uncertainty space of interest (using the simulation controller codes), and 2) simulating the system behavior for that specific set of parameter values (using the system simulator codes). For complex systems, one of the major challenges in using DPRA methodologies is to analyze the large amount of information (i.e., large number of scenarios ) generated, where clustering techniques are typically employed to allow users to better organize and interpret the data. In this paper, we focus on the analysis of a nuclear simulation dataset that is part of the Risk Informed Safety Margin Characterization (RISMC) Boiling Water Reactor (BWR) station blackout (SBO) case study. We apply a software tool that provides the domain experts with an interactive analysis and visualization environment for understanding the structures of such high-dimensional nuclear simulation datasets. Our tool encodes traditional and topology-based clustering techniques, where the latter partitions the data points into clusters based on their uniform gradient flow behavior. We demonstrate through our case study that both types of clustering techniques complement each other in bringing enhanced structural understanding of the data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Software Quality Assurance for the MOOSE-Based Open-Source Multiphysics Code Cardinal - An Expanded CI Testing Suite

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing and, maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program has been initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as a safety analysis tool. These gaps have been captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents a snapshot of the verification test cases currently available for Cardinal and NekRS in their assimilation into a Continuous Integration (CI) platform. Following the CI practice permits the integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. It should be noted that the SQA program itself, including the program plans, procedures, configuration management, and testing strategies, need to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm

Abstract We present a benchmark test suite and an automated machine learning procedure for evaluating supervised machine learning (ML) models for predicting properties of inorganic bulk materials. The test suite, Matbench, is a set of 13 ML tasks that range in size from 312 to 132k samples and contain data from 10 density functional theory-derived and experimental sources. Tasks include predicting optical, thermal, electronic, thermodynamic, tensile, and elastic properties given a material’s composition and/or crystal structure. The reference algorithm, Automatminer, is a highly-extensible, fully automated ML pipeline for predicting materials properties from materials primitives (such as composition and crystal structure) without user intervention or hyperparameter tuning. We test Automatminer on the Matbench test suite and compare its predictive power with state-of-the-art crystal graph neural networks and a traditional descriptor-based Random Forest model. We find Automatminer achieves the best performance on 8 of 13 tasks in the benchmark. We also show our test suite is capable of exposing predictive advantages of each algorithm—namely, that crystal graph methods appear to outperform traditional machine learning methods given ~10 4 or greater data points. We encourage evaluating materials ML algorithms on the Matbench benchmark and comparing them against the latest version of Automatminer.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Q-value (MeV/fission) Determination for the Advanced Test Reactor

This report documents a step-by-step procedure that can be used to calculate a Q-value for the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). The Q-value calculation here is an estimate of the total energy released per fission event in the ATR driver fuel in units of MeV/fission and is recognized as a reactor-specific Q-value for the ATR. Such a Q-value is needed INL ATR reactor physicists to normalize calculated fluxes and reaction rates to measured ATR total core and lobe powers. The calculated ATR Q-value and the procedure used to calculate this value are presented in a detailed manner so as to establish a credible basis, such that this single Q-value can be used consistently among all ATR reactor physicists. A Q-value is essentially the summation of all the kinetic energy from all radiation components released from a single fission event that ends up as heat in the reactor coolant. Estimation of a Q-value for a given reactor can theoretically be very complex because it is dependent on several variables, which include (1) the materials in the reactor core, (2) the neutron energy spectrum, and (3) the mix of actinide isotopes that are being simultaneously fissioned. Since these three variables can potentially change over time or with reactor burnup, this potentially makes the Q-value a time-dependent quantity. However, for ATR, we will invoke some simplifying assumptions, based on the unique features of the ATR core and supported by neutronic calculations, which will reduce the complexity of the problem and lead to a single time-independent Q-value. Of the three variables, the materials in the core have the greatest impact on the ATR Q-value. Since the materials in the core are most important, an array of components (materials) have been carefully selected to compose a typical ATR core configuration. It should be noted that the step-by-step procedure here for calculating a reactor-specific Q-value can be applied to any nuclear reactor. In a more general procedure, if one needed to include time-dependent spectral and actinide composition changes as a function of burnup for a specific reactor, this procedure can still be used, but at discrete time steps throughout the burnup. The result will be a set of discrete Q-values as a function of burnup. However, here we will apply the procedure to the ATR, as an example, and obtain a single Q-value that is valid for the ATR reactor as a function of burnup. In the evaluated nuclear data file (ENDF), Q-values for specific actinides are known for a reasonably high degree of accuracy, especially the major uranium and plutonium isotopes. The isotopic Q-values are composed of the kinetic energy of the fission fragments and the energies of the various radiation components emitted from the fission event. One complication is the fact that some of these energy components are dependent on the incident neutron energy (EINC) that induces the fission event (neutron energy spectrum dependence). For ATR, we will estimate an average neutron energy based on the neutron energy flux weighted by the fission cross sections and use this average neutron energy value in the ENDF formulas. This neutron energy dependence is one of two dependencies that make the final ATR Q-value a reactor-specific value. The second dependency, and the most important variable for ATR, involves the materials in the core and the de-excitation radiations produced from neutron radiative capture radiation; radiation energy that becomes heat in the reactor coolant. This important dependency is discussed in detail below. The third dependency, or the mix of fissioning actinides as a function of ATR burnup, is ignored because the bulk of the fissions over a cycle are always due to U-235 in the high-enriched ATR core. In a fission event, the fission energy is partitioned between the fission fragments and the radiation components that include neutrons, gamma rays, and beta particles. The main variable that makes the calculated Q-value reactor-specific is the amount of radiative capture energy produced in the core due to prompt and delayed neutron capture in the reactor core materials and the subsequent release of nuclear binding energy in the form of de-excitation gamma radiation energy in the reactor core. This energy component, neutron radiative capture energy, is not in the ENDF, because it depends on the reactor and its core materials. The radiative capture gamma energy release can be significant, or approximately 3–12 MeV/fission depending on the materials in the reactor core (fuel materials, cladding, structural components, coolant, targets, reflector, etc.). For the ATR, the energy released from radiative capture gamma radiation is calculated to be near the middle of the 3–12 MeV range. This makes the radiative capture radiation component an important and significant contribution to the total ATR Q-value. The ATR has unique reactor features that will allow us to simplify the complex procedure for determining an ATR reactor-specific Q-value. For example, the ATR is a thermal reactor and contains high-enriched fuel (93.15 wt% U-235). Consequently, the bulk of the fissions in the ATR core from beginning-of-cycle (BOC) to end-of-cycle are from U-235. Even though U-238 makes up approximately 7% of the uranium atoms in the fuel, the number of fissions relative to U-235 is insignificant, since U-238 is fertile and ATR is a thermal reactor. The same is true for U-234 and U-236 (both fertile). The ATR’s high-enriched uranium fuel also inhibits the buildup of large quantities of plutonium isotopes. So, even though there is some buildup of U-236, Np-237, and Pu-239 in the ATR driver fuel, the impact or contribution of these isotopes fissions on the ATR Q-value is minor compared to U-235. Nonetheless, we will include fission contributions from all the major uranium isotopes (U-234, U-235, U-236, and U-238) in the determination of an average isotopic Q-value that is used in the ATR Q-value determination. Although the ATR Q-value calculated here is based on BOC conditions (fresh fuel with no higher order actinide buildup), it is believed that the ATR Q-value is relatively constant with burnup or during any given ATR power cycle (14–60 days). The reason is that the vast majority of the core driver fuel fissions are always from U-235 during the cycle. Also, since we effectively assume instantaneous energy release for the fission product gammas and beta particles and delayed neutrons from a fission event, this corresponds to equilibrium conditions for all fission product concentrations in the ATR driver fuel too. The goal of this effort was to determine a specific numerical and core-average Q-value for the recoverable energy released by a single fission event (MeV/fission) for the ATR. This calculated value has the potential to help standardize and add credibility to not only the Monte Carlo tally normalization process used by many ATR core physics analysts, but also to the normalization process for all reactor physics calculation methods involving ATR analyses. Currently, the ATR core physics analysts use slightly different Q-values. Some values are known to be conservative for specific applications. However, sometimes a more accurate Q-value is needed for the calculation in which ATR test specimens require non-conservative and as-accurate-as-possible Q-values to estimate burnups, heat rates, neutron fluxes, nuclear reaction rates, etc., where corresponding measured post-irradiation examination data provides the ultimate validation for the calculated results. A detailed Q-value procedure was developed and is outlined in this document along with numerical values calculated specifically for the determination of the ATR Q-value. This report attempts to document in some detail the calculation methodology, nuclear data, computer code, computer model, code calculated results, hand calculations, assumptions, and logic that went into the determination of the ATR Q-value.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Coordinated Ramping Product and Regulation Reserve Procurements in CAISO and MISO using Multi-Scale Probabilistic Solar Power Forecasts (Pro2R)

How can probabilistic solar forecasts lower costs and improve reliability for independent system operator (ISO) markets? We tackle this question in three steps. First, we enhance an existing solar forecasting system to provide well-calibrated hours-ahead probabilistic forecasts. We then relate the degree of uncertainty in those forecasts to error distributions for net load ramps for the California ISO (CAISO) using statistical and machine learning methods. Projected net load errors conditioned on solar uncertainty are translated into flexible ramp requirements that therefore reflect real-time meteorological and solar conditions, improving on typical ISO procedures. Finally, a multi-period look-ahead production cost model quantifies how conditional ramp requirements can a) decrease operating costs by lowering requirements compared to often conservative unconditional methods, and b) reduce generation scarcity events and consequently improve reliability by increasing flexibility requirements at times when unconditional forecast-based requirements understate actual ramp uncertainty. In addition to the products just described (quantification of solar uncertainty, its translation into requirements for ramp capability product, and quantification of the benefits of more accurate ramp requirements), this project also developed a visualization system that alerts system operators of ramp and uncertainty conditions within the network based on solar forecasts. The system is called Resource Forecast and Ramp Visualization for Situational Awareness (RaVIS). These four products represent significant advances in the state-of-the-art of probabilistic solar forecasting, development of weather-informed reserve requirements, production costing methods for estimating the benefits of more accurate reserve requirements, and visualization of system status, respectively. Yet the products are also practical and can be immediately implemented, potentially enabling system operators to save millions of dollars in ramp product procurement costs per year.

14 SOLAR ENERGY↗
DOE OSTI2016

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the model, we design a two-step maximum likelihood optimization procedure that ensures the orthogonality of the projection matrix by exploiting recent results on the Stiefel manifold, i.e., the manifold of matrices with orthogonal columns. The additional benefit of our probabilistic formulation, is that it allows us to select the dimensionality of the AS via the Bayesian information criterion. We validate our approach by showing that it can discover the right AS in synthetic examples without gradient information using both noiseless and noisy observations. We demonstrate that our method is able to discover the same AS as the classical approach in a challenging one-hundred-dimensional problem involving an elliptic stochastic partial differential equation with random conductivity. Finally, we use our approach to study the effect of geometric and material uncertainties in the propagation of solitary waves in a one dimensional granular system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Evaluating the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks

In this work the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks is evaluated. The first one code based on traditional iterative procedures and called Neutron spectrometry and dosimetry from the Universidad Autonoma de Zacatecas (NSDUAZ) use the SPUNIT iterative algorithm and was designed to unfold neutron spectrum and calculate 15 dosimetric quantities and 7 IAEA survey meters. The main feature of this code is the automated selection of the initial guess spectrum trough a compendium of neutron spectrum compiled by the IAEA. The second one code known as Neutron spectrometry and dosimetry with artificial neural networks (NDSann) is a code designed using neural nets technology. The artificial intelligence approach of neural net does not solve mathematical equations. By using the knowledge stored at synaptic weights on a neural net properly trained, the code is capable to unfold neutron spectrum and to simultaneously calculate 15 dosimetric quantities, needing as entrance data, only the rate counts measured with a Bonner spheres system. Similarities of both NSDUAZ and NSDann codes are: they follow the same easy and intuitive user's philosophy and were designed in a graphical interface under the LabVIEW programming environment. Both codes unfold the neutron spectrum expressed in 60 energy bins, calculate 15 dosimetric quantities and generate a full report in HTML format. Differences of these codes are: NSDUAZ code was designed using classical iterative approaches and needs an initial guess spectrum in order to initiate the iterative procedure. In NSDUAZ, a programming routine was designed to calculate 7 IAEA instrument survey meters using the fluence-dose conversion coefficients. NSDann code use artificial neural networks for solving the ill-conditioned equation system of neutron spectrometry problem through synaptic weights of a properly trained neural network. Contrary to iterative procedures, in neural net approach it is possible to reduce the rate counts used to unfold the neutron spectrum. To evaluate these codes a computer tool called Neutron Spectrometry and dosimetry computer tool was designed. The results obtained with this package are showed. The codes here mentioned are freely available upon request to the authors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

High-order fully implicit solver for all-speed fluid dynamics: AUSM ride from nearly incompressible variable-density flows to shock dynamics

We introduce a novel Newton–Krylov (NK)-based fully implicit algorithm for solving fluid flows in a wide range of flow conditions—from variable density nearly incompressible to supersonic shock dynamics. The key enabling feature of our all-speed solver is the ability to efficiently solve conservation laws by choosing a set of independent variables that produce a well-conditioned Jacobian matrix for the linear iterations of the global nonlinear iterative solver. In particular, instead of choosing to discretize the conservative variables (density, momentum, total energy), which is traditionally used in Eulerian high-speed compressible fluid dynamics, we demonstrate superior performance by discretizing the primitive variables—pressure–velocity–temperature in the very low-Mach flow limits or density–velocity–temperature/entropy in the shock dynamics range. Moreover, our method allows us to avoid direct inversion of the mass matrix in discrete time derivatives, which is usually an additional source for stiffness, especially pronounced when going to very high-order schemes with non-orthogonal basis functions. Here, we show robust solutions obtained for discontinuous finite element discretization up to seventh-order accuracy. Another important aspect of the solution algorithm is the Advection Upstream Splitting Method (AUSM), adopted to compute numerical fluxes within our reconstructed discontinuous Galerkin (rDG) spatial discretization scheme. The use of the low-Mach modification of the hyperbolic flux operator is found to be necessary for enabling robust simulations of very stiff liquids and metals for Mach numbers below M=10 -5 , which is well known to be very computationally challenging for compressible solvers. We demonstrate that our fully implicit rDG-NK solver with the AUSM + -up flux treatment produces efficient and high-resolution numerical solutions at all speeds, ranging from vanishing Mach numbers to transonic and supersonic, without substantial modifications of the solution procedures. (At high speed, we add limiting and use a simpler preconditioning of the Krylov solver.) Numerical examples include nearly incompressible constant-property flow past a backward-facing step with heat transfer, low-Mach variable-property channel flow of water at supercritical state, phase change and melt pool dynamics for laser spot welding and selective laser melting in additive manufacturing, and Mach 3 flow in a wind tunnel with a step.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Evaluation of in vivo quantification accuracy of the Ingenuity-TF PET/MR

Purpose: The quantitative accuracy of standardized uptake values (SUVs) and tracer kinetic uptake parameters in patient investigations strongly depends on accurate determination of regional activity concentrations in positron emission tomography (PET) data. This determination rests on the assumption that the given scanner calibration is valid in vivo. In a previous study, we introduced a method to test this assumption. This method allows to identify discrepancies in quantitative accuracy in vivo by comparison of activity concentrations of urine samples measured in a well-counter with activity concentrations extracted from PET images of the bladder. In the present study, we have applied this method to the Philips Ingenuity-TF PET/MR since at the present stage, absolute quantitative accuracy of combined PET/MR systems is still under investigation. Methods: Twenty one clinical whole-body F18-FDG scans were included in this study. The bladder region was imaged as the last bed position and urine samples were collected afterward. PET images were reconstructed including MR-based attenuation correction with and without truncation compensation and 3D regions-of-interest (ROIs) of the bladder were delineated by three observers. To exclude partial volume effects, ROIs were concentrically shrunk by 8–10 mm. Then, activity concentrations were determined in the PET images for the bladder and for the urine by measuring the samples in a calibrated well-counter. In addition, linearity measurements of SUV vs singles rate and measurements of the stability of the coincidence rate of “true” events of the PET/MR system were performed over a period of 4 months. Results: The measured in vivo activity concentrations were significantly lower in PET/MR than in the well-counter with a ratio of the former to the latter of 0.756 ± 0.060 (mean ± std. dev.), a range of 0.604–0.858, and a P value of 3.9 ⋅ 10{sup −14}. While the stability measurements of the coincidence rate of “true” events showed no relevant deviation over time, the linearity scans revealed a systematic error of 8%–11% (avg. 9%) for the range of singles rates present in the bladder scans. After correcting for this systematic bias caused by shortcomings of the manufacturers calibration procedure, the PET to well-counter ratio increased to 0.832 ± 0.064 (0.668 –0.941), P = 1.1 ⋅ 10{sup −10}. After compensating for truncation of the upper extremities in the MR-based attenuation maps, the ratio further improved to 0.871 ± 0.069 (0.693–0.992), P = 3.9 ⋅ 10{sup −8}. Conclusions: Our results show that the Philips PET/MR underestimates activity concentrations in the bladder by 17%, which is 7 percentage points (pp.) larger than in the previously investigated PET and PET/CT systems. We attribute this increased underestimation to remaining limitations of the MR-based attenuation correction. Our results suggest that only a 2 pp. larger underestimation of activity concentrations compared to PET/CT can be observed if compensation of attenuation truncation of the upper extremities is applied. Thus, quantification accuracy of the Philips Ingenuity-TF PET/MR can be considered acceptable for clinical purposes given the ±10% error margin in the EANM guidelines. The comparison of PET images from the bladder region with urine samples has proven a useful method. It might be interesting for evaluation and comparison of the in vivo quantitative accuracy of PET, PET/CT, and especially PET/MR systems from different manufacturers or in multicenter trials.

60 APPLIED LIFE SCIENCES↗