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Energy Intensity Baselining and Tracking Guidance

Each company joining the U.S. Department of Energy’s (DOE’s) Better Buildings, Better Plants Program (Better Plants) commits to establishing an energy consumption and energy intensity (EI) baseline and to tracking its energy performance over a 10-year period against that baseline. The baseline must reflect a company’s energy consumption over a 12-month period, covering all its U.S.-based operations. Energy consumption is calculated by fuel type in terms of primary energy (also known as source energy). EI is broadly defined as the amount of energy consumed per unit of output produced. For this guidance document and for the program, the term energy performance represents an evaluation of a facility’s capacity to use energy efficiently. Metrics used to assess a facility’s energy performance can include EI, energy consumption, improvements in EI, etc. Establishing an energy baseline and tracking system is a critical first step in effectively managing energy use. Developing a baseline can help a company understand energy use within the corporation and give it a point of comparison to evaluate future efforts to improve energy performance. It can also support efforts to validate a company’s energy management activities, improve comparative analyses when using benchmarks, and help in predicting future energy needs. In addition, a company that normalizes its performance data can determine highly defensible measures of energy savings generated through implemented energy efficiency projects. Establishing a baseline and tracking energy performance is also a requirement for ISO 50001 certification. Although basic energy data can be collected through utility bills, most manufacturers will have to perform additional analyses to develop accurate and robust energy baselines and tracking systems. Energy is consumed in many ways within the manufacturing sector and can come from multiple sources. Energy is sometimes generated and sold to other parties or captured and reused on-site. External events can exert a significant impact on a facility or company’s energy use independent of any purposeful efforts to improve energy efficiency. Operational changes, such as production shifts—which may be inevitable for some companies over the 10-year period covered by the program—can also make a big difference in energy use. Since Better Plants asks companies to account for all their U.S.-based operations, mergers, acquisitions, and divestitures can also have significant implications for a company’s energy metrics. This document aims to demystify the sometimes complex baselining process. It devotes special attention to the task of normalizing and adjusting energy consumption to account for external factors, such as weather and production changes. A key recommendation is that companies use regression analysis to normalize their energy consumption data whenever possible. Regression analysis is a statistical technique that estimates the dependence of a variable (i.e., energy use in the context of Better Plants) on one or more independent variables such as ambient temperature, while controlling for the influence of other variables at the same time. A properly developed regression analysis can provide a reliable estimate of energy savings resulting from energy improvement strategies and projects by accounting for the effects of variables such as annual production levels and weather. DOE has developed a companion Energy Performance Indicator software tool (EnPI) to simplify the baselining process. This tool can run regression models, calculate changes in EI at the facility level, and automatically compile facility-level data into a corporate-wide metric. Note that although the relevant equations used to calculate EI are provided in this document, the EnPI tool will automatically perform most calculations for the user. Additionally, Better Plants Partners (Partners) can call on their Technical Account Manager (TAM) to help them establish a baseline and assist with the necessary calculations to track progress.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Process Mining in Healthcare - A Case Study for the Corporate Data Warehouse of the Veterans Affairs Office

Researchers at Oak Ridge National Laboratory are working with the Veteran’s Affairs Administration Office (VA) on a series of studies having the objective of detecting harmful anomalies (i.e., hazards) in VA health information technology systems using its Corporate Data Warehouse (CDW). This progress report describes an ORNL study focused on applying a process mining methodology to that CDW database. In the approach presented herein, process mining methodology is combined with additional software tools, metrics, and filters to permit a quick examination of large volumes of data to address specific research questions. In this work, a case study is presented in which the performance of the combined ORNL approach is evaluated by applying it to the CDW database. We performed an evidence-based study to effectively identify process models and to define metrics of frequency and performance for four health care domains: Consults, Radiology, Laboratory, and Outpatient Medication (RxOut) orders. Additionally, we classified the termination classes of the different cases by mapping to the OASIS Human Task Specification standard. We demonstrated, via process mining, that extracted raw data can aid the understanding of the flow of information in different clinical order processes. We showed that using the stepby- step approach described herein to discover processes in raw electronic health record data can be extremely effective in revealing irregular state transitions in the data and understanding clinical order information flows that are not apparent in analyzing the CDW as it is, without feature extraction.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Particle Sensitivity Analysis

We propose to develop a computational sensitivity analysis capability for Monte Carlo sampling-based particle simulation relevant to Aleph, Cheetah-MC, Empire, Emphasis, ITS, SPARTA, and LAMMPS codes. These software tools model plasmas, radiation transport, low-density fluids, and molecular motion. Our report demonstrates how adjoint optimization methods can be combined with Monte Carlo sampling-based adjoint particle simulation. Our goal is to develop a sensitivity analysis to drive robust design-based optimization for Monte Carlo sampling-based particle simulation - a currently unavailable capability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Open Source Suite for Advanced Synchrophasor Analysis

The report presents the results of the development of the open-source suite of applications for synchrophasor analysis. The suite includes several software tools for oscillation analysis, power plant model validation, and frequency response analysis using synchrophasor measurements. All tools are based on the common framework and data sources. The developed tools have been used by different electrical utilities for synchrophasor analysis. The report includes several use cases based on the actual system PMU data.

20 FOSSIL-FUELED POWER PLANTS↗

Hanford Surface Barrier Design Guidance

This status report presents results of progress made during fiscal year 2019 towards developing a software tool for designing surface barriers in the Central Plateau. This tool is intended to be used to support feasibility studies and remedy applications. This status report summarizes the methodology followed to develop preliminary vadose zone reduced order models (VZ-ROMs) for use in such a tool. The ROM development process required generation of a training and testing dataset representing an example waste site in the Central Plateau. This training data was prepared via eSTOMP simulations that simulated variable drainage through hypothetical surface barriers into waste sites within the Central Plateau. Prior to regression analysis, these numerical results were analyzed to understand the behavior of contaminant solutes under different drainage conditions in the vadose zone. Results from eSTOMP simulations provided an understanding of the effectiveness of hypothetical surface barriers in isolating the subsurface system and mitigating contaminant transport. The primary objective of the work was to establish an appropriate ROM methodology. Further development is required to adapt the ROMs presented here to appropriately couple surface barrier construction design. Future iterations will be used to predict the performance of different surface barrier engineering designs. Future development will follow a similar process to the one demonstrated in this document.

54 ENVIRONMENTAL SCIENCES↗

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume I – Predicting Initial Microstructures

This report summarizes the current state of modeling and simulation methods for predicting the initial structure and properties of material in components assembled using advanced manufacturing technologies (AMTs). The report is the first volume in a two-volume series. This first volume focuses on predicting initial microstructures of AM material. The second volume discusses predicting material properties given the initial microstructure. The focus is on technologies of particular relevance to the design and manufacture of nuclear reactor components. The purpose of the report is to help develop the technical knowledge base to support regulatory decisions that will be needed to assess nuclear components manufactured with AMTs as these components are installed at nuclear power plants (NPPs). The report develops a list of AMTs of particular interest to the NRC and summarizes the key microstructural features and corresponding processing parameters relevant to each technology. Further sections describe available physically-based and data-driven prediction methods and survey widely available software tools. The report concludes with a summary of gaps that may be of particular interest to the NRC when evaluating modeling and simulation methods for AMTs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

BISON TRISO Modeling Advancements and Validation to AGR-1 Data

BISON is a finite element-based nuclear fuel performance code. Among its unique characteristics are its ability to model 1D, 2D, and 3D geometries and its applicability to a wide variety of nuclear fuels. For the last eight years, BISON has included a beginning capability to model tri-structural isotropic (TRISO) fuel. Recently, interest in TRISO fuel has grown, and a significant effort has been made to improve BISON’s capabilities in this area. Capability development has occurred for each material present in TRISO fuel particles: the buffer, inner pyrolytic carbon, silicon carbide, and outer pyrolytic carbon layers, as well as the fuel kernel. New elastic, creep, swelling, thermal expansion, thermal conductivity, and fission gas release (FGR) models are available. New models for the graphite matrix are also now available. Another important addition is the ability to perform statistical failure analysis of large samples of fuel particles. This new capability, which continues to grow, enables evaluation of failure due to pressure or crack formation by analyzing many thousands of particles. This enables realistic calculations of fission product release from the many particles in a TRISO-fueled reactor. These capabilities were checked via regression and verification tests. A large number of code benchmarking problems were also run, showing that BISON’s results closely match those of other software tools. Finally, a significant validation effort was completed in which fission product release, measured as part of the AGR-1 capsule experiments, was compared to BISON outputs. BISON outputs compared very well to the experimental data and to PARFUME results. Interest in BISON’s TRISO capabilities is growing, with the U.S. Nuclear Regulatory Commission (NRC) and Westinghouse Electric Company receiving training during the past year. Multiple other entities have expressed interest in or are actively using BISON. Kairos Power, LLC, has a strong partnership with Idaho National Laboratory (INL) regarding the use of BISON for TRISO analysis. While its capabilities still continue to grow, BISON has already become a powerful tool for TRISO analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

U.S. Industrial and Commercial Motor System Market Assessment Report Volume 1: Characteristics of the Installed Base

Motor systems are an integral part of our industrial and commercial facilities. They provide the motive force behind the fans, pumps, compressors, chillers, and conveyors in these facilities. Given their centrality to any facility’s operations, they are a critical energy end use to understand, particularly when developing technologies and policies to meet sustainability goals, improve productivity, and enhance resilience. In the late 1990s, the U.S. Department of Energy (DOE) conducted two seminal studies to better understand the installed stock and energy savings opportunities of industrial and commercial motor systems. In the industrial sector, The United States Industrial Electric Motor Systems Market Opportunities Assessment used primary data collected through onsite assessments and led to a greater understanding of the installed base of motor systems, their characteristics, and the opportunities for energy savings (U.S. Department of Energy, 2002). Notable findings included the following: Industrial motor systems consumed 679 billion kilowatt-hours (kWh) in 1994, representing 23 percent of U.S. electricity consumption. Cost-effective energy efficiency measures could result in 62-104 billion kWh of energy savings annually. Sixty-two percent of the energy savings potential was from fan, pump, and compressor end use equipment. Nearly half of motor system electricity consumption was attributable to approximately 3,500 facilities, or 1.5 percent of U.S. manufacturing facilities. Opportunities for Energy Savings in the Residential and Commercial Sectors with High Efficiency Electric Motors provided an evaluation of the installed stock of motor driven equipment in U.S. commercial and residential buildings and opportunities for utilization of high efficiency motors and variable speed technologies (Arthur D. Little, 1999). Notable findings included the following: Commercial motor systems consumed 343 billion kWh in 1995, with refrigeration and space conditioning constituting 93 percent of the total. Cost-effective energy efficiency measures could result in 51 billion kWh of energy savings annually. Due in no small part to these seminal studies, motor system technologies and usage characteristics have changed drastically since the late 1990s. Greater awareness of cost-effective strategies for reducing motor system electricity consumption have been developed and deployed. This includes several software tools, literature, and utility and government programs promoting energy efficiency improvements in motor driven systems. Additionally, several rounds of energy efficiency standards have been enacted, resulting in improved installed motor efficiency. The cost of variable speed drives has dropped substantially, and combined with utility rebate programs, has led to their greater adoption. Further, since these results were published, the U.S. manufacturing sector has undergone a massive transformation. Due to global competition, some sectors have relocated operations overseas. Others have brought operations onshore to avail low cost and abundant natural gas. Additionally, automation and robotics have pervaded the entire sector. Consequently, these two reports likely do not represent the current state of motor driven systems in U.S. industrial and commercial facilities. As cited in recent studies, the lack of current information on motor system electricity consumption and use characteristics limits the ability to conduct analysis on energy savings potential, develop technologies to address energy and productivity gaps, and develop programs to promote energy efficiency practices and technologies for motor systems (International Energy Agency, 2007; UNIDO, 2010; McKane and Hasanbeigi, 2011; Waide and Brunner, 2011). Specifically, the lack of information affects a range of stakeholders: Governments must rely on outdated information when setting research agendas, developing policies, and designing energy efficiency programs and offerings. Utilities and energy efficiency programs cannot identify the current market needs or potential impact when designing rebate and energy efficiency programs. Electric grid planners cannot identify motor system usage characteristics when developing plans to support the resilience of the electric grid. Manufacturers of motors, motor driven equipment, and drives are hampered when developing technologies to meet the needs of their market. Motor system end users are limited in their ability to identify energy saving opportunities within their own facilities because they do not have reliable benchmark information. In response to the lack of current information and analysis on industrial and commercial motor systems, the DOE initiated an update to these two studies. Launched in 2016 and led by Lawrence Berkeley National Laboratory (LBNL), the Motor System Market Assessment (MSMA) provides an updated, more comprehensive assessment of the installed stock of motor systems in both the industrial and commercial sectors, a review of the supply chains supporting motor and drives in the U.S., and the performance improvement opportunity available from using best available technologies and maintenance and operation practices. The outcomes of the MSMA are documented in three U.S. Industrial and Commercial Motor System Market Assessment reports, with this report being the first listed: 1. Volume 1: Characteristics of the Installed Base (this report) documents the findings on the installed base of motor systems in the U.S. industrial and commercial sectors. Quantification of energy savings potential is not documented in this report but in Volume 3. 2. Volume 2: Motors and Drives Supply Chain Review reviews the state of supply chains for motors and drives installed in U.S. industrial and commercial facilities, focusing on advanced motor and drive technologies and their constituent materials. 3. Volume 3: Energy Savings Opportunity analyzes the energy performance improvement opportunity for the installed base of U.S. industrial and commercial motor systems. This report has been prepared as a reference for motor system stakeholders. It provides factual information as could be best determined by the assessment results and avoids speculating on any findings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Scalable Solution Framework for Stochastic Transmission and Generation Planning Problems. Draft

Current commercial software tools for transmission and generation investment planning have limited stochastic modeling capabilities. Because of this limitation, electric power utilities generally rely on scenario planning heuristics to identify potentially robust and cost effective investment plans for a broad range of system, economic, and policy conditions. Several research studies have shown that stochastic models perform significantly better than deterministic or heuristic approaches, in terms of overall costs. However, there is a lack of practical solution approaches to solve such models. In this paper we propose a scalable decomposition algorithm to solve stochastic transmission and generation planning problems, respectively considering discrete and continuous decision variables for transmission and generation investments. Given stochasticity restricted to loads and wind, solar, and hydro power output, we develop a simple scenario reduction framework based on a clustering algorithm, to yield a more tractable model. The resulting stochastic optimization model is decomposed on a scenario basis and solved using a variant of the Progressive Hedging (PH) algorithm. We perform numerical experiments using a 240-bus network representation of the Western Electricity Coordinating Council in the US. Although convergence of PH to an optimal solution is not guaranteed for mixed-integer linear optimization models, we find that it is possible to obtain solutions with acceptable optimality gaps for practical applications. Our numerical simulations are performed both on a commodity workstation and on a high-performance cluster. The results indicate that large-scale problems can be solved to a high degree of accuracy in at most two hours of wall clock time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Accelerator physics at NSLS-II: research accomplishments in 2020

NSLS-II accelerator physicists provide scientific support for user operations, as well as for improvements and developments of the accelerator systems. This work includes optimization of the NSLS-II performance with high beam current and low vertical emittance, improvement of the beam stability, development of new software tools for operations and beam studies. The accelerator physicists productively worked on a number of research activities such as the conceptual design of NSLS-II accelerator upgrade; design and optimization of advanced low-emittance lattices; development of novel methods to study nonlinear beam dynamics; ultrafast electron diffraction and microscopy. The physicists also contributed to the BNL electron-ion collider project, to the APS and ALS upgrade projects. Research accomplishments achieved in 2020, are summarized in this report.

43 PARTICLE ACCELERATORS↗

Enhancing Performance Contracts with Monitoring-Based Commissioning (MBCx)

To support federal and commercial building owners in understanding, procuring, and implementing monitoring-based commissioning (MBCx) software tools, this report provides an overview of their capabilities, the MBCx process, and how MBCx can be integrated into—and benefit—each phase of a performance contract. This report is intended to spur increased use of MBCx in performance contracts, whether an agency has previously installed or is considering adding MBCx at the time of their project. Additionally, case studies illustrate successful experiences using MBCx within performance contracts at a university campus and across a large number of buildings managed by the General Services Administration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

COTS Data Analytics Software User Manual: Version 1.0

Large volumes of data are being collected by Sandia National Laboratories as part of an active commercial-off-the-shelf (COTS) part testing and surveillance program. This user manual documents Python-based COTS Data Analytics software that has been developed for standardizing, displaying, visualizing, and analyzing the resulting COTS part testing and surveillance data. It is the objective of these software tools to streamline the analysis of COTS testing and surveillance data and improve the efficiency with which test engineers and data analytics experts can pinpoint possible performance and reliability problems in COTS parts.

42 ENGINEERING↗

Fixed-Energy Response-Function Analysis with Multi-Efficiency (FRAM) Software, Version 6

Researchers at Los Alamos National Laboratory have developed FixedEnergy Response- Function Analysis with Multiple Efficiency (FRAM), a powerful software tool for gamma-ray spectrometry isotopic analysis. This tool leverages Los Alamos expertise in nuclear safeguards, radiation detection systems, and related analysis techniques. A household name in the non-destructive assay community for over two decades, FRAM determines a special nuclear material source's isotopic composition by analyzing gamma-ray spectra. Los Alamos researchers have released the latest version of FRAM that incorporates several updates to the 2013 major release of FRAM, Version 5.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

TEAM Project Review, Year 2

This report summarizes our research activities within the TEAM project between December 2020 and December 2021, funded by the ASCR Advanced Research in Quantum Computing program. During the reporting period the LLNL-MSU team has made progress on several fronts. An overarching goal of the team is to provide a comprehensive suite of software tools that can be used for the Characterize-Optimize-Compute loop needed to implement and execute algorithms on quantum devices. We are concurrently developing lightweight solvers that can be used on desktop computers to find optimal control pulses and to characterize small quantum systems (consisting of a few transmons and cavities). However, desktop computers are insufficient for simulating and characterizing larger quantum systems. We have therefore also developed parallel, distributed memory, simulators and optimization solvers, both for open and closed quantum systems. These parallel solvers have, for example, been used to study quantum optimal control for pure-state preparation, utilizing 1000’s of cores on a modern high-performance computing (HPC) platform.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Detector and Beamline Simulation for Next-Generation High Energy Physics Experiments

The success of high energy physics programs relies heavily on accurate detector simulations and beam interaction modeling. The increasingly complex detector geometries and beam dynamics require sophisticated techniques in order to meet the demands of current and future experiments. Common software tools used today are unable to fully utilize modern computational resources, while data-recording rates are often orders of magnitude larger than what can be produced via simulation. In this paper, we describe the state, current and future needs of high energy physics detector and beamline simulations and related challenges, and we propose a number of possible ways to address them.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

OTERR User Manual

OTERR (Optimization of TEst Reactor Reloading) is a software tool created to assist in the determination of optimal fuel reloading patterns for test reactors. The intended application is for the Versatile Test Reactor (VTR) program, but it provides functions that could be useful for analysis and optimization of many types of fast reactors. OTERR does not perform neutron/gamma transport, heat transfer, thermal hydraulics, or depletion calculations. Instead, it acts as a wrapper around codes that provide these capabilities, with a native genetic algorithm optimization capability. At this time, wrapping is only implemented for Argonne Reactor Computation (ARC) codes DIF3D, REBUS, and GAMSOR, and SE2-ANL. OTERR also has capabilities to facilitate input creation for DASSH, a thermal hydraulics code similar to SE2- ANL being developed for the VTR program.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Primer for OTERR Core Reloading Optimization

OTERR (Optimization of Test Reactor Reloading) is a software tool which assists in finding optimal fuel assembly reloading patterns for nuclear reactors. It was created specifically to support the Versatile Test Reactor (VTR) program, but its functionality is general enough to be applied to most fast spectrum reactors which use hexagonal prismatic fuel elements. This document is meant to be a primer for new users of OTERR to walk through example workflows for core reloading optimization cases. Simple cases are followed step-by-step to discuss what needs to be done to complete a reloading optimization sequence. Note that the intent of this document is to provide practical examples for users to follow along with so they can quickly start using OTERR and then make changes to fit their own modeling needs. Detail is limited in terms of addressing additional features not used in these examples and especially lacking in discussion of theory used in the code. To better address these points, users are highly encouraged to refer to the OTERR User Manual and the OTERR Theory Manual.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

An Open-Source Framework for the Computational Analysis and Design of Autothermal Chemical Processes

The main project object was to develop software tools for simulating non-equilibrium autothermal processes, improving the prospects for identifying and designing such systems. The project demonstrates the use of these tools to simulate autothermal pyrolysis, a process recently developed at the pilot-plant scale at Iowa State University. In such process, instead of externally heating a reactor to pro-vide the enthalpy of pyrolysis, sufficient oxygen in the form of air is introduced into the reactor to support partial oxidation of reactants and products with the exothermic energy released supporting endothermic pyrolysis reactions. A fluidized bed is used to assure good mixing of biomass and oxidant and provide an isothermal reaction environment. The amount of oxygen required depends upon the kind of biomass being pyrolyzed and parasitic heat losses from the reactor. For example, for woody biomass pyrolyzed under conditions that simulate adiabatic operation, equivalence ratios can be as low as 0.06, compared to 0.20 or higher for autothermal gasifiers. By removing the heat transfer bottleneck of conventional pyrolysis, operation in autothermal mode allowed a significant increase in reactor throughput process, approaching five times the throughput of the conventionally operated pyrolyzer. Different simulation strategies were considered and developed: a zero-dimensional chemistry model was used to verify the applicability of kinetic schemes to predict biomass fast pyrolysis in autothermal conditions. Conventional chemical reactor models such as the plug flow reactor and the partially stirred reactor were used to investigate the role of mixing in the fluidized bed pyrolyzer and to establish the impact of mixing time on the gas-phase reactions. A comprehensive multiphase computational fluid dynamics (mCFD) framework, including polydisperse granular phase modeling and detailed chemical kinetics was formulated and used to model the experimental setup for autothermal biomass fast pyrolysis at ISU. Multiphase CFD was also used to investigate the role of biomass feed positioning on the mixing of biomass in the pyrolizer. Finally, a reduced order model (ROM), suitable to be implemented in process simulators was obtained. Both the mCFD and the ROM were validated against experiments.

09 BIOMASS FUELS↗