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At least 1,063 records · Page 59

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to purely data-driven methods, {PIML} models can be trained from additional information obtained by enforcing physical laws such as energy and mass conservation. More broadly, {PIML} models can include abstract properties and conditions such as stability, convexity, or invariance. The basic premise of {PIML} is that the integration of ML and physics can yield more effective, physically consistent, and data-efficient models. This paper aims to provide a tutorial-like overview of the recent advances in {PIML} for dynamical system modeling and control. Specifically, the paper covers an overview of the theory, fundamental concepts and methods, tools, and applications on topics of: 1) physics-informed learning for system identification; 2) physics-informed learning for control; 3) analysis and verification of {PIML} models; and 4) physics-informed digital twins. The paper is concluded with a perspective on open challenges and future research opportunities.

Nghiem, Truong↗

FALCON: Framework for Anomaly Detection in Industrial Control Systems

Industrial Control Systems (ICS) are used to control physical processes in critical infrastructure. These systems are used in a wide variety of operations such as water treatment, power generation and distribution, and manufacturing. While the safety and security of these systems are of serious concern, recent reports have shown an increase in targeted attacks aimed at manipulating physical processes to cause catastrophic consequences. This trend emphasizes the need for algorithms and tools that provide resilient and smart attack detection mechanisms to protect ICS. In this paper, we propose an anomaly detection framework for ICS based on a deep neural network. The proposed methodology uses dilated convolution and long short-term memory (LSTM) layers to learn temporal as well as long term dependencies within sensor and actuator data in an ICS. The sensor/actuator data are passed through a unique feature engineering pipeline where wavelet transformation is applied to the sensor signals to extract features that are fed into the model. Additionally, this paper explores four variations of supervised deep learning models, as well as an unsupervised support vector machine (SVM) model for this problem. The proposed framework is validated on Secure Water Treatment testbed results. This framework detects more attacks in a shorter period of time than previously published methods.

97 - MATHEMATICS AND COMPUTING↗

Spectrometer for Sky-Scanning Sun-Tracking Atmospheric Research (4STAR): Instrument Technology

The Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) combines airborne sun tracking and sky scanning with diffraction spectroscopy, to improve knowledge of atmospheric constituents and their links to air-pollution/climate. Direct beam hyper-spectral measurement of optical depth improves retrievals of gas constituents and determination of aerosol properties. Sky scanning enhances retrievals of aerosol type and size distribution. 4STAR measurements will tighten the closure between satellite and ground-based measurements. 4STAR incorporates a modular sun-tracking/ sky-scanning optical head with fiber optic signal transmission to rack mounted spectrometers, permitting miniaturization of the external optical head, and future detector evolution. Technical challenges include compact optical collector design, radiometric dynamic range and stability, and broad spectral coverage. Test results establishing the performance of the instrument against the full range of operational requirements are presented, along with calibration, engineering flight test, and scientific field campaign data and results.

atmosphere↗

Systems and methods for modeling and analyzing networks

The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.

97 MATHEMATICS AND COMPUTING↗

Field Test to Evaluate Deep Borehole Disposal.

The U.S. Department of Energy (DOE) has embarked on the Deep Borehole Field Test (DBFT), which will investigate whether conditions suitable for disposal of radioactive waste can be found at a depth of up to 5 km in the earth’s crust. As planned, the DBFT will demonstrate drilling and construction of two boreholes, one for initial scientific characterization, and the other at a larger diameter such as could be appropriate for waste disposal (the DBFT will not involve radioactive waste). A wide range of geoscience activities is planned for the Characterization Borehole, and an engineering demonstration of test package emplacement and retrieval is planned for the larger Field Test Borehole. Characterization activities will focus on measurements and samples that are important for evaluating the long-term isolation capability of the Deep Borehole Disposal (DBD) concept. Engineering demonstration activities will focus on providing data to evaluate the concept’s operational safety and practicality. Procurement of a scientifically acceptable DBFT site and a site management contractor is now underway. The concept of deep borehole disposal (DBD) for radioactive wastes is not new. It was considered by the National Academy of Science (NAS 1957) for liquid waste, studied in the 1980’s in the U.S. (Woodward–Clyde 1983), and has been evaluated by European waste disposal R&D programs in the past few decades (for example, Grundfelt and Crawford 2014; Grundfelt 2010). Deep injection of wastewater including hazardous wastes is ongoing in the U.S. and regulated by the Environmental Protection Agency (EPA 2001). The DBFT is being conducted with a view to use the DBD concept for future disposal of smaller-quantity, DOE-managed wastes from nuclear weapons production (i.e., Cs/Sr capsules and granular solid wastes). However, the concept may also have broader applicability for nations that have a need to dispose of limited amounts of spent fuel from nuclear power reactors. For such nations the cost for disposing of volumetrically limited waste streams could be lower than mined geologic repositories.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Carbon Mitigation Potential of Heat Pump Integrated with Thermal Storage for Grid-Interactive Residential Buildings

Residential buildings’ heating and cooling loads are associated with significant carbon emissions and peak electricity demand. Phase change material (PCM) based thermal energy storage (TES) can be used for space heating and cooling by embedding into the heat pump equipment. Past work on TES integrated with heat pumps (HP) has demonstrated significant load shifting and economic benefits. However, the potential for TES to reduce carbon emissions has not been widely explored. This study evaluates carbon mitigation potential of an ice-based TES coupled to HP (HP-TES) based on a simple rule-based control strategy accounting for electric grid emissions data. A vapor compression HP model using Engineering Equation Solver (EES). The modeled HP-TES system for single-family residential building demonstrates decreased carbon emissions with reduced peak utility cost.

Sultan, Sara↗

Resilience Metrics for Solar Photovoltaics

This workshop presentation proposes the development of solar photovoltaic (PV) system resilience metrics and a methodology and framework for evaluation of PV resilience metrics. PV resilience metrics are needed to establish a consistent basis for reporting, evaluation, and data collection by industry, evaluate performance of PV systems that have been subject to natural hazards, correlating resilience to system attributes, and predicting resilience for any PV system. PV resilience metrics can guide improved system design, standards, and insurance coverage. Establishing consistent metrics can foster data collection on impacts of natural hazards on PV systems.

14 SOLAR ENERGY↗

Analysis of Loss-of-Offsite-Power Events 1987-2018

Loss of offsite power (LOOP) can have a major negative impact on a power plant’s ability to achieve and maintain safe shutdown conditions. LOOP event frequencies and times required for subsequent restoration of offsite power are important inputs to plant probabilistic risk assessments. This report presents a statistical and engineering analysis of LOOP frequencies and durations at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience during calendar years 1987 through 2018. LOOP events during critical operation that do not result in a reactor trip are not included. Frequencies and durations were determined for four event categories: plant-centered, switchyard-centered, grid-related, and weather-related. No significant trends in critical operation LOOP frequencies over the most recent 10-year period are identified. Adverse trends in LOOP durations are identified for switchyard-centered and grid-related LOOPs, as well as overall LOOPs during critical operation and overall LOOPs during shutdown operation. Both grid-related and weather-related LOOP events are found to show statistically significant seasonality. The engineering analysis of LOOP data shows that human errors have been much less frequent since 1997 than in the 1987–1996 time period.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

AutoCheck: Automatically Identifying Variables for Checkpointing by Data Dependency Analysis

Checkpoint/Restart (C/R) has been widely deployed in numerous HPC systems, Clouds, and industrial data centers, which are typically operated by system engineers. Nevertheless, there is no existing approach that helps system engineers without domain expertise and domain scientists without system fault tolerance knowledge identify those critical variables accounted for correct application execution restoration in a failure for C/R. To address this problem, we propose an analytical model and a tool (AutoCheck) that can automatically identify critical variables to checkpoint for C/R. AutoCheck relies on first, analytically tracking and optimizing data dependency between variables and other application execution state, and second, a set of heuristics that identify critical variables for checkpointing from the refined data dependency graph (DDG). AutoCheck allows programmers to pinpoint critical variables to checkpoint quickly within a few minutes. We evaluate AutoCheck on 13 representative HPC benchmarks, demonstrating that AutoCheck can efficiently identify correct critical variables to checkpoint.

HPC↗

Analysis of Loss-of-Offsite-Power Events 1997-2015

Loss of offsite power (LOOP) can have a major negative impact on a power plant’s ability to achieve and maintain safe shutdown conditions. LOOP event frequencies and times required for subsequent restoration of offsite power are important inputs to plant probabilistic risk assessments. This report presents a statistical and engineering analysis of LOOP frequencies and durations at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience during calendar years 1997 through 2015. LOOP events during critical operation that do not result in a reactor trip, are not included. Frequencies and durations were determined for four event categories: plant-centered, switchyard-centered, grid-related, and weather-related. Emergency diesel generator reliability is also considered (failure to start, failure to load and run, and failure to run more than 1 hour). There is an adverse trend in LOOP durations. The previously reported adverse trend in LOOP frequency was not statistically significant for 2006-2015. Grid-related LOOPs happen predominantly in the summer. Switchyard-centered LOOPs happen predominantly in winter and spring. Plant-centered and weather-related LOOPs do not show statistically significant seasonality. The engineering analysis of LOOP data shows that human errors have been much less frequent since 1997 than in the 1986 -1996 time period.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cylinder-to-Cylinder Variations in Power Production in a Dual Fuel Internal Combustion Engine Leveraging Late Intake Valve Closings

Advanced internal combustion engines, although generally more efficient than conventional combustion engines, often encounter limitations in multi-cylinder applications due to variations in the combustion process. This study leverages experimental data from an inline 6-cylinder heavy-duty dual fuel engine equipped with a fully-flexible variable intake valve actuation system to study cylinder-to-cylinder variations in power production. The engine is operated with late intake valve closure timings in a dual-fuel combustion mode featuring a port-injection and a direct-injection fueling system in order to improve fuel efficiency and engine performance. Experimental results show increased cylinder-to-cylinder variation in IMEP as IVC timing moves from 570°ATDC to 610°ATDC, indicating an increasingly uneven fuel distribution between cylinders. These observations along with engine simulation models developed using GT-Power have been used to better understand the distribution of the port-injected fuel across cylinders under various operating conditions. This study revealed that the fuel distribution across cylinders in this dual fuel application is significantly affected by changes in the effective compression ratio as determined by the intake valve close timing as well as the design of the intake system (specifically the length of the intake runners). Late intake valve closures allow a portion of the trapped air and port injected fuel to flow back out of the cylinders into the intake manifold. The fuel that is pushed back in the intake manifold is then unevenly redistributed across the cylinders largely due to the dominating direction of the flow in the intake manifold. Experimental and simulation results discussing the impact of operating parameters on the fuel distribution are presented.

Kassa, Mateos↗

Sensitivity Analysis of Material Model Parameters to Reproduce Crushing of Composite Tubes

The ability to predict the behavior of composite structures under impact conditions is an important challenge for engineering analysis since it requires modeling beyond the elasticity and into failure initiation and propagation. Crushing of laminate composites is the result of a combination of several and complex failure mechanisms, which are not always possible to reproduce together in a single finite element analysis (FEA). In this paper, models based on lamina-level failure criteria have been used to predict the onset of damage; once failure initiates, the mechanisms of failure propagation require reducing the material properties using several degradation schemes. Among the composite material models available in LS-DYNA, MAT-ENHANCED-COMPOSITE-DAMAGE (MAT-54) has been chosen for modeling the axial crushing of composite tubes with various resistant sections and wall slope, given the reduced experimental input parameters to insert into the card definition. Comparison with experimental data shows that such material model is able to successfully reproduce the crushing behavior, even if the numerical results are strictly correlated with some model parameters which cannot be measured experimentally or are purely mathematical expedients. Therefore, extensive calibration of these parameters by trial-and-error is necessary to achieve successful simulation results. Once done it for a structure made of the same composite material, it is possible to adopt the same card configuration for all the other cases, obtaining good agreement between numerical and experimental results. After, the attempt to model the same geometries using the MAT-LAMINATED-COMPOSITE-FABRIC (MAT-58) card with the same parameter values previously calibrated has been done obtaining results comparable with the experimental data.

36 MATERIALS SCIENCE↗

MARVEL Reactor Digital Engineering Developments

The MARVEL reactor project has served to introduce a new generation of engineers to the processes required to transform a reactor design from simply an idea on paper into what will be an approved, constructed, and operational nuclear power system. Much as there have been advances in materials, analysis, and evaluation methodologies over the 50 years since the last reactor was built at INL, so too has the technology for managing the engineering process itself advanced. Digital Engineering tools and methods provide improved coordination between previously siloed engineering disciplines, reduced burdens of non-value-added data transcription processes and bring forward insights and improvements that might otherwise fall later in the design stage, where changes are much more costly. While the tools and techniques to support the full digital engineering vision are not yet complete, the MARVEL design processes provide valuable demonstrations and validations of key aspects and illuminate further areas for implementation by subsequent projects.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

A Revised Look at Relativistic Electrons in the Earth's Inner Radiation Zone and Slot Region

We describe a new, more accurate procedure for estimating and removing inner zone background contamination from Van Allen Probes Magnetic Electron Ion Spectrometer (MagEIS) radiation belt measurements. This new procedure is based on the underlying assumption that the primary source of background contamination in the electron measurements at L shells less than three, energetic inner belt protons, is relatively stable. Since a magnetic spectrometer can readily distinguish between foreground electrons and background signals, we are able to exploit the proton stability to construct a model of the background contamination in each MagEIS detector by only considering times when the measurements are known to be background dominated. We demonstrate, for relativistic electron measurements in the inner zone, that the new technique is a significant improvement upon the routine background corrections that are used in the standard MagEIS data processing, which can “overcorrect” and therefore remove real (but small) electron fluxes. As an example, we show that the previously reported 1-MeV injection into the inner zone that occurred in June of 2015 was distributed more broadly in L and persisted in the inner zone longer than suggested by previous estimates. Such differences can have important implications for both scientific studies and spacecraft engineering applications that make use of MagEIS electron data in the inner zone at relativistic energies. We compare these new results with prior work and present more recent observations that also show a 1-MeV electron injection into the inner zone following the September 2017 interplanetary shock passage.

79 ASTRONOMY AND ASTROPHYSICS↗

An automated integrated web-based smart tool for open stope design

The Stability Graph is a widely used tool for the design of open stopes in underground mining. Many users of the Stability Graph still apply this design method manually. Although the manual approach has benefits, using multiple graphs and stability number computation charts for each stope surface is time-consuming, even for the experienced mining engineer. Current practice in the use of the method also limits data sharing. This paper presents a StopeSoft web-based tool for open stope stability prediction that is developed on the basis of the Stability Graph method and is available at openstope.com. StopeSoft incorporates flexibility in terms of Stability Graph options and incorporates additional critical factors often overlooked. As a web-based tool, StopeSoft encourages and makes data sharing possible globally, focused on expanding the database and improving the current limitations of the Stability Graph to provide practical, reliable solutions for mining engineers, consultants, and academics. The StopeSoft automated process facilitates the process of open stope stability prediction, saving time and minimizing potential human errors. Statistical treatment of the data accounts for the variability of input parameters to emphasize the probabilistic nature of the Stability Graph method. The probabilistic interpretation of the stability states of stope surfaces eliminates the false feeling of absolute stope performance based on its location on the Stability Graph , as implied by the deterministic approach.

58 GEOSCIENCES↗

A comprehensive modeling procedure for estimating statistical properties of forced ignition

In this work, a comprehensive modeling procedure for estimating the probability of ignition with application to high altitude relights of aircraft combustors is developed. In these configurations, an ignitor is used to introduce high-enthalpy discharge into a fuel-laden but stratified flow. Because of the inherent variabilities inflow conditions, kernel discharge process, and the chaotic turbulent flow, ignition cannot be described deterministically, but only as a probabilistic measure. The proposed modeling framework consists of three components. The turbulent flow is represented using the large eddy simulation (LES) framework. The ignition process is modeled using a manifold approach, where the initial kernel evolution is represented using a homogeneous reactor while the latter part of the evolution is represented as a competition between diffusion and chemical reactions using a flamelet-type mapping. A combined lookup table that can track the evolution of the kernel through these two distinct reaction stages is developed. The table lookup variables are solved within the LES framework. The resulting simulation tool is then embedded within an uncertainty quantification approach, where variations in the turbulent flow, as well as operating and kernel properties, are simulated using a Monte-Carlo-based sampling approach. Techniques to reduce computational cost are used to obtain a robust, numerically accurate, and physically representative model for engine relight. The method is validated using experimental data for ignition of methane/air mixtures. Due to the comprehensive nature of the modeling procedure, it is found that the simulation tool reproduces experimentally observed ignition probabilities over a wide range of operating conditions.

42 ENGINEERING↗

FY 2016 Status Report: CIRFT Testing Data Analyses and Updated Curvature Measurements

This report provides a detailed description of FY15 test result corrections/analysis based on the FY16 Cyclic Integrated Reversible-Bending Fatigue Tester (CIRFT) test program methodology update used to evaluate the vibration integrity of spent nuclear fuel (SNF) under normal transportation conditions. The CIRFT consists of a U-frame testing setup and a real-time curvature measurement method. The three-component U-frame setup of the CIRFT has two rigid arms and linkages to a universal testing machine. The curvature of rod bending is obtained through a three-point deflection measurement method. Three linear variable differential transformers (LVDTs) are used and clamped to the side connecting plates of the U-frame to capture the deformation of the rod. The contact-based measurement, or three-LVDT-based curvature measurement system, on SNF rods has been proven to be quite reliable in CIRFT testing. However, how the LVDT head contacts the SNF rod may have a significant effect on the curvature measurement, depending on the magnitude and direction of rod curvature. It has been demonstrated that the contact/curvature issues can be corrected by using a correction on the sensor spacing. The sensor spacing defines the separation of the three LVDT probes and is a critical quantity in calculating the rod curvature once the deflections are obtained. The sensor spacing correction can be determined by using chisel-type probes. The method has been critically examined this year and has been shown to be difficult to implement in a hot cell environment, and thus cannot be implemented effectively. A correction based on the proposed equivalent gauge-length has the required flexibility and accuracy and can be appropriately used as a correction factor. The correction method based on the equivalent gauge length has been successfully demonstrated in CIRFT data analysis for the dynamic tests conducted on Limerick (LMK) (17 tests), North Anna (NA) (6 tests), and Catawba mixed oxide (MOX) (10 tests) SNF samples. These CIRFT tests were completed in FY14 and FY15. Specifically, the data sets obtained from measurement and monitoring were processed and analyzed. The fatigue life of rods has been characterized in terms of moment, curvature, and equivalent stress and strain..

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE High Performance Computing Operational Review (HPCOR): Enabling Data-Driven Scientific Discovery at HPC Facilities

U.S. Department of Energy (DOE) High Performance Computing (HPC) facilities are on the verge of a paradigm shift in the way they deliver systems and services to science and engineering teams. Research projects are producing a wide variety of data at unprecedented scale and level of complexity, with community-specific services that are part of the data collection and analysis workflow. On June 18-19, 2014 representatives from six DOE HPC centers met in Oakland, CA at the DOE High Performance Operational Review (HPCOR) to discuss how they can best provide facilities and services to enable large-scale data-driven scientific discovery at the DOE national laboratories. The report contains findings from that review.

97 MATHEMATICS AND COMPUTING↗