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EnergyPlus Version 7

EnergyPlus is a whole building energy simulation program that engineers, architects and researchers use to model energy and water use in buildings. Modeling the performance of a building with EnergyPlus enables building professionals to optimize the building design to use less energy and water. Each version of EnergyPlus is tested extensively before release. EnergyPlus models heating, cooling, lighting, ventilation, other energy flows, and water use. EnergyPlus includes many innovation simulation capabilities: time-steps less than an hour, modular systems and plant integrated with heat balance-based zone simulation, multizone air flow, thermal comfort, water use, natural ventilation, and photovoltaic systems. EnergyPlus runs on the Windows, Macintosh, and Linux platforms. Free add-ons and other third party software products are available for use with EnergyPlus.

Wetter, Michael↗

The Expanded Capabilities Of The Cementitious Barriers Partnership Software Toolbox Version 2.0 - 14331

The Cementitious Barriers Partnership (CBP) Project is a multi-disciplinary, multi-institutional collaboration supported by the U.S. Department of Energy (US DOE) Office of Tank Waste Management. The CBP program has developed a set of integrated tools (based on state-of-the-art models and leaching test methods) that help improve understanding and predictions of the long-term structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. The CBP Software Toolbox – “Version 1.0” was released early in FY2013 and was used to support DOE-EM performance assessments in evaluating various degradation mechanisms that included sulfate attack, carbonation and constituent leaching. The sulfate attack analysis predicted the extent and damage that sulfate ingress will have on concrete vaults over extended time (i.e., > 1000 years) and the carbonation analysis provided concrete degradation predictions from rebar corrosion. The new release “Version 2.0” includes upgraded carbonation software and a new software module to evaluate degradation due to chloride attack. Also included in the newer version are a dual regime module allowing evaluation of contaminant release in two regimes – both fractured and un-fractured. The integrated software package has also been upgraded with new plotting capabilities and many other features that increase the “user-friendliness” of the package. Experimental work has been generated to provide data to calibrate the models to improve the credibility of the analysis and reduce the uncertainty. Tools selected for and developed under this program have been used to evaluate and predict the behavior of cementitious barriers used in near-surface engineered waste disposal systems for periods of performance up to or longer than 100 years for operating facilities and longer than 1000 years for waste disposal. The CBP Software Toolbox is and will continue to produce tangible benefits to the working DOE Performance Assessment (PA) community.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Plant science decadal vision 2020–2030: Reimagining the potential of plants for a healthy and sustainable future

Abstract Plants, and the biological systems around them, are key to the future health of the planet and its inhabitants. The Plant Science Decadal Vision 2020–2030 frames our ability to perform vital and far‐reaching research in plant systems sciences, essential to how we value participants and apply emerging technologies. We outline a comprehensive vision for addressing some of our most pressing global problems through discovery, practical applications, and education. The Decadal Vision was developed by the participants at the Plant Summit 2019, a community event organized by the Plant Science Research Network. The Decadal Vision describes a holistic vision for the next decade of plant science that blends recommendations for research, people, and technology. Going beyond discoveries and applications, we, the plant science community, must implement bold, innovative changes to research cultures and training paradigms in this era of automation, virtualization, and the looming shadow of climate change. Our vision and hopes for the next decade are encapsulated in the phrase reimagining the potential of plants for a healthy and sustainable future. The Decadal Vision recognizes the vital intersection of human and scientific elements and demands an integrated implementation of strategies for research (Goals 1–4), people (Goals 5 and 6), and technology (Goals 7 and 8). This report is intended to help inspire and guide the research community, scientific societies, federal funding agencies, private philanthropies, corporations, educators, entrepreneurs, and early career researchers over the next 10 years. The research encompass experimental and computational approaches to understanding and predicting ecosystem behavior; novel production systems for food, feed, and fiber with greater crop diversity, efficiency, productivity, and resilience that improve ecosystem health; approaches to realize the potential for advances in nutrition, discovery and engineering of plant‐based medicines, and "green infrastructure." Launching the Transparent Plant will use experimental and computational approaches to break down the phytobiome into a "parts store" that supports tinkering and supports query, prediction, and rapid‐response problem solving. Equity, diversity, and inclusion are indispensable cornerstones of realizing our vision. We make recommendations around funding and systems that support customized professional development. Plant systems are frequently taken for granted therefore we make recommendations to improve plant awareness and community science programs to increase understanding of scientific research. We prioritize emerging technologies, focusing on non‐invasive imaging, sensors, and plug‐and‐play portable lab technologies, coupled with enabling computational advances. Plant systems science will benefit from data management and future advances in automation, machine learning, natural language processing, and artificial intelligence‐assisted data integration, pattern identification, and decision making. Implementation of this vision will transform plant systems science and ripple outwards through society and across the globe. Beyond deepening our biological understanding, we envision entirely new applications. We further anticipate a wave of diversification of plant systems practitioners while stimulating community engagement, underpinning increasing entrepreneurship. This surge of engagement and knowledge will help satisfy and stoke people's natural curiosity about the future, and their desire to prepare for it, as they seek fuller information about food, health, climate and ecological systems.

59 BASIC BIOLOGICAL SCIENCES↗

INTEGRATION OF DATA ANALYTICS WITH SYSTEM HEALTH PROGRAMS

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry developed and regulatory programs. However, these programs have proven to be labor intensive and expensive. There is an opportunity to significantly enhance the collection, analysis, and use of this information to provide more cost-effective plant operation. Additionally, there is an acute industry need to leverage advanced technology to reduce costs and improve operational effectiveness. The goal of this paper is to provide effective and efficient analytical methods and tools to support risk-informed decisions for the equipment reliability and asset management programs at nuclear power plants. This is accomplished by creating a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). Here we are supporting typical system engineer decisions regarding maintenance activity scheduling and component ageing management. This is performed in a risk-informed context where herein the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow. A challenge is that the structure of this workflow strongly depends on the decision that needs to be made, the type of data available, and the constraints that need to be considered. Current methods are designed to provide specific answers to specific problems; however, these methods might prove to be inadequate even when problem settings slightly change (e.g., different types of requirements, additional dependencies between system reliability and economics). We tackled this challenge by designing framework in a flexible and modular fashion such that the user can assemble and customize his/her own workflow that integrates SSC economic lifecycle models (e.g., maintenance and replacement costs), system reliability models, and optimization methods.

97 - MATHEMATICS AND COMPUTING↗

Report on all ARRA Funded Technical Work

The main focus of this American Recovery and Reinvestment Act of 2009 (ARRA) funded project was to design an energy efficient carbon capture and storage (CCS) process using the Recipients membrane system for H 2 separation and CO 2 capture. In the ARRA-funded project, the Recipient accelerated development and scale-up of ongoing hydrogen membrane technology research and development (R&D). Specifically, this project focused on accelerating the current R&D work scope of the base program-funded project, involving lab scale tests, detail design of a 250 lb/day H 2 process development unit (PDU), and scale-up of membrane tube and coating manufacturing. This project scope included the site selection and a Front End Engineering Design (FEED) study of a nominally 4 to 10 ton-per-day (TPD) Pre-Commercial Module (PCM) hydrogen separation membrane system. Process models and techno-economic analysis were updated to include studies on integration of this technology into an Integrated Gasification Combined Cycle (IGCC) power generation system with CCS.

08 HYDROGEN↗

LEVERAGING AGING MATERIALS DATA TO SUPPORT EXTENSION OF TRANSPORTATION SHIPPING PACKAGES SERVICE LIFE

Nuclear material inventories are increasingly being transferred to interim storage locations where they may reside for extended periods of time. Use of a shipping package to store nuclear materials after the transfer has become more common for a variety of reasons. Shipping packages are robust and have a qualified pedigree for performance in normal operation and accident conditions but are only certified over an approved transportation window. The continued use of shipping packages to contain nuclear material during interim storage will result in reduced overall costs and reduced exposure to workers. However, the shipping package materials of construction must maintain integrity as specified by the safety basis of the storage facility throughout the storage period, which is typically well beyond the certified transportation window. In many ways, the certification processes required for interim storage of nuclear materials in shipping packages is similar to life extension programs required for dry cask storage systems for commercial nuclear fuels. The storage of spent nuclear fuel in dry cask storage systems is federally-regulated, and over 1500 individual dry casks have been in successful service up to 20 years in the US. The uncertainty in final disposition will likely require extended storage of this fuel well beyond initial license periods and perhaps multiple re-licenses may be needed. Thus, both the shipping packages and the dry cask storage systems require materials integrity assessments and assurance of continued satisfactory materials performance over times not considered in the original evaluation processes. Test programs for the shipping packages have been established to obtain aging data on materials of construction to demonstrate continued system integrity. The collective data may be coupled with similar data for the dry cask storage systems and used to support extending the service life of shipping packages in both transportation and storage.

36 MATERIALS SCIENCE↗

Structural Integrity Program for the 300,000-Gallon Radioactive Liquid Waste Storage Tanks at the Idaho Nuclear Technology and Engineering Center

This report provides a record of the Structural Integrity Program for the 300,000-gal liquid waste storage tanks and associated equipment at the Idaho Nuclear Technology and Engineering Center, as required by U.S. Department of Energy M 435.1-1, “Radioactive Waste Management Manual.” This equipment is known collectively as the Tank Farm Facility. This report is an update, and replaces the previous report by the same title issued April 2003. The conclusion of this report is that the Tank Farm Facility tanks, vaults, and transfer systems that remain in service for storage are structurally adequate, and are expected to remain structurally adequate over the remainder of their planned service life through 2012. Recommendations are provided for continued monitoring of the Tank Farm Facility.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Electrification 2018 Annual Progress Report

During fiscal year 2018 (FY 2018), the U.S. Department of Energy (DOE) Vehicle Technologies Office (VTO) funded early stage research & development (R&D) projects that address batteries and electrification of the U.S. transportation sector. The VTO Electrification Sub-Program is composed of Electric Drive Technologies, and Grid Integration activities. The Electric Drive Technologies group conducts R&D projects that advance electric motors and power electronics technologies. The Grid and Charging Infrastructure group conducts R&D projects that advance grid modernization and electric vehicle charging technologies. This document presents a brief overview of the Electrification Sub-Program and progress reports for its R&D projects. Each of the progress reports provide a project overview and highlights of the technical results that were accomplished in FY 2018.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Kilopower - Powering the Future of Space Exploration [Poster]

The Kilopower Project was initiated by NASA’s Space Technology Mission Directorate to demonstrate subsystem-level technology readiness of small space fission power in a relevant environment (TRL 5) for space science and human exploration power needs. The Kilopower Project centerpiece is the Kilowatt Reactor Using Stirling Technology (KRUSTY) test, which consists of the development and testing of a ground technology demonstrator of a 1 kWe class fission power system. The technologies to be developed and validated by KRUSTY are extensible to space fission power systems from 1 to 10 kWe, which can enable modular surface fission power systems for human exploration, as well as higher power future potential deep space science missions.

42 ENGINEERING↗

Dynamic Event Tree Analysis Through RAVEN

Conventional Event-Tree (ET) based methodologies are extensively used as tools to perform reliability and safety assessment of complex and critical engineering systems. One of the disadvantages of these methods is that timing/sequencing of events and system dynamics is not explicitly accounted for in the analysis. In order to overcome these limitations several techniques, also know as Dynamic Probabilistic Risk Assessment (D-PRA), have been developed. Monte-Carlo (MC) and Dynamic Event Tree (DET) are two of the most widely used D-PRA methodologies to perform safety assessment of Nuclear Power Plants (NPP). In the past two years, the Idaho National Laboratory (INL) has developed its own tool to perform Dynamic PRA: RAVEN (Reactor Analysis and Virtual control ENvironment). RAVEN has been designed in a high modular and pluggable way in order to enable easy integration of different programming languages (i.e., C++, Python) and coupling with other application including the ones based on the MOOSE framework, developed by INL as well. RAVEN performs two main tasks: 1) control logic driver for the new Thermo-Hydraulic code RELAP-7 and 2) post-processing tool. In the first task, RAVEN acts as a deterministic controller in which the set of control logic laws (user defined) monitors the RELAP-7 simulation and controls the activation of specific systems. Moreover, RAVEN also models stochastic events, such as components failures, and performs uncertainty quantification. Such stochastic modeling is employed by using both MC and DET algorithms. In the second task, RAVEN processes the large amount of data generated by RELAP-7 using data-mining based algorithms. This paper focuses on the first task and shows how it is possible to perform the analysis of dynamic stochastic systems using the newly developed RAVEN DET capability. As an example, the Dynamic PRA analysis, using Dynamic Event Tree, of a simplified pressurized water reactor for a Station Black-Out scenario is presented.

42 ENGINEERING↗

2021 Annual Progress Report: Vertical GaN Device Development

This project is part of a multi-lab consortium that leverages U.S. research expertise and facilities at national labs and universities to significantly advance electric drive power density and reliability, while simultaneously reducing cost. The final objective of the consortium is to develop a 100 kW traction drive system that achieves 33 kW/L, has an operational life of 300,000 miles, and a cost of less than 6 dollars/kW. One element of the system is a 100 kW inverter with a power density of 100 kW/L and a cost of 2.7 dollars/kW. New materials such as wide-bandgap semiconductors, soft magnetic materials, and ceramic dielectrics, integrated using multi-objective co-optimization design techniques, will be utilized to achieve these program goals. This project focuses on a subset of the power electronics work within the consortium, specifically the design, fabrication, and evaluation of vertical GaN power devices suitable for automotive applications.

33 ADVANCED PROPULSION SYSTEMS↗

Recovery Act – Integrated Pilot-Scale Biorefinery for Producing Ethanol from Hybrid Algae

As a scientific and engineering endeavor, the Algenol IBR Biorefinery project has been a success by almost any measure. The vision for the system evolved significantly over the course of the project, always due to recognized opportunities for improved performance, lower energy consumption, and reduced costs. Our commitment to thorough, realistic, techno-economic and life cycle assessments has been an essential element for system innovation, technology guidance, and change management of the overall facility. The biological tools developed during this program for cyanobacteria are second to none, and are the primary reason for the remarkable improvements in organism performance. The breakthrough was the successful transformation of our most robust wild type organism (AB1) early in 2012. That was followed by a series of improvements over the next several years that produced strains wherein over 80% of the fixed carbon was converted into ethanol. At the same time, our expertise in cultivation, physiology, process engineering, CO2 management, and photobioreactor design and manufacturing grew at a comparable pace. We learned enormous amounts from the various upsets, weather variations, contamination events, and new technology related disappointments. We overcame those challenges to produce fuel grade ethanol with a low carbon footprint, and are within striking distance of economic viability even with the challenges of low fossil fuel prices.

09 BIOMASS FUELS↗

A superstructure optimization approach for process synthesis under complex reaction networks

Here in this work, we present mixed integer linear programming methods for the synthesis of processes that involve complex reaction networks. Specifically, we consider the modeling of reactors and interconnecting streams in systems where the composition of the reactor inlet streams can vary substantially, thereby making the determination of the limiting component as well as the calculation of the stream heating/cooling and power requirements challenging. First, towards the modeling of reactors, we develop an extent-based method which detects the limiting reactant of each reaction occurring in parallel with others, based on the inlet flows of the reactants. Second, we develop a computationally tractable method for the calculation of the work and heating/cooling duty needed to condition any stream of a process based on simple calculations that can be performed offline. Finally, we present how the two aforementioned components can be integrated in an optimization model generated based on a process superstructure. We demonstrate the application of the developed methods for the synthesis of a biorefinery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of HFE to the design and V and V of a computerized procedure system: benefits and challenges - 234

The application of Human Factors Engineering (HFE) practices to the Human Machine Interface design and subsequent Verification and Validation (V and V) is a widely applied practice when talking about the design of complete control rooms or important control room modernizations, but not so often applied to the design of computerized operator support systems. In order to overcome the challenges faced on designing a Computerized Operation Support System (COSS) that meets the process efficiency requirements and integrates seemingly with hybrid plant operation concept, the involvement of a HFE team early in the COSS design and implementation process along with operation, Instrumentation and Control (I and C) and cybersecurity experts will guarantee the project success. This paper documents the HFE process applied during the design and evaluation of a Computerized Procedure System (CPS) and how final product was shaped to ensure that the transition from paper to computerized procedures will help in meeting Delivering the Nuclear Promise (DNP) goals, improving plant efficiency. The HFE program included the following activities: 1. A review of existing operating experience 2. An analysis of functions and tasks associated to the use and maintenance of CPS 3. A design verification of the system to meet guidelines prescribed in the NUREG-0700 (Rev.2), requirements of the ISG-05 and cybersecurity criteria (NEI 08-09, IEC-62646, EPRI 1015313, these among others). 4. An integrated system validation in a full scope simulator The application of HFE practices in the design and implementation of COSS helps not only to ensure that efficiency and safety improvement requirements are met, but also to evaluate the potential return of the investment, that such tools should bring. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Supervisory Control and Data Acquisition for Electrochemical Separation Experimentation

The Python-based program is a laboratory automation tool designed to control and monitor electrochemical systems. The tool was developed for capacitive deionization (CDI) experiments, but it can be used for any system that requires controlled voltage or current segments and multi-parameter monitoring. The program integrates hardware components to run user-defined experimental parameters, providing operational control of a programmable power supply, peristaltic pump, and data acquisition devices. Currently, the program is structured with a workflow that includes an initialization (or pre-run) phase, a main loop, and a post-experiment stabilization (or post-run) phase. The initialization phase prepares and stabilizes the cell, ensuring that the electrodes and solution reach a baseline state before the experiment begins. The main loop consists of multiple voltage segments that repeat, controlling the experiment while recording key parameters such as time, voltage, current, pH, and conductivity. Finally, the post-experiment stabilization phase allows the system to stabilize after the experiment, returning the cell and solution to equilibrium conditions before ending the sequence. The program is designed with four variations, each tailored to different experimental needs. All variations include both the initialization and post-experiment stabilization stages, which run for a set amount of time, voltage, current, and flow rate before and after the main experiment block. The main loop runs for a set number of cycles, as defined by the user input, and each cycle is composed of 2 or 4 segments. The 4 program variations are described as follows: Program 1: The main program includes 2 segments. Each segment is defined to have a set duration, flow rate, voltage, and current. This program measures conductivity, flow rate, voltage, and current. Program 2: The main program expands Program 1 to include 4 segments. Each segment has a specified duration, flow rate, voltage, and current. Like Program 1, it measures conductivity, flow rate, voltage, and current. Program 3: The main program consists of 2 segments, each defined by time, flow rate, voltage, and current. In addition to conductivity, flow rate, voltage, and current, Program 3 collects pH and temperature data through a 4-channel data acquisition device. Program 4: This program independently controls two channels of a multi-channel power supply simultaneously. While conductivity can only be measured for one cell at a time, the dual-channel control makes it possible to operate two cells simultaneously under different voltage/current conditions. The main program includes 2 segments.For each program, all measurements are automatically logged and integrated into a single Excel output file. Data are displayed in numerical format and plotted, both in real time, to track system performance. A key feature of the program is its ability to synchronize all outputs so that every measurement shares a single timestamp, ensuring accurate alignment of voltage, current, pH, conductivity, and pH data.By combining hardware control, real-time monitoring, and unified data collection, this program significantly reduces manual workload and minimizes errors, making it a reliable platform for researchers, engineers, and laboratory technicians conducting CDI experiments, among other electrochemical tests.

Valentino, Lauren [Argonne National Laboratory (AN↗

Optimally Controlled Flexible Fuel Powertrain System

The primary objective of this project was to develop a true Flex Fuel Vehicle capable of running on any blend of ethanol from 0 to 85% with reduced penalty in usable vehicle range. A research and development program, targeting 10% improvement in fuel economy using a direct injection (DI) turbocharged spark ignition engine was conducted. In this project a gasoline-optimized high-technology engine was considered and the hardware and configuration modifications were defined for the engine, fueling system, and air path. Combined with a novel engine control strategy, control software, and calibration this resulted in a highly efficient and clean FFV concept. It was also intended to develop robust detection schemes of the ethanol content in the fuel integrated with adaptive control algorithms for optimized turbocharged direct injection engine combustion. The approach relies heavily on software-based adaptation and optimization striving for minimal modifications to the gasoline-optimized engine hardware system. Our ultimate objective was to develop a compact control methodology that takes advantage of any ethanol-based fuel mixture and not compromise the engine performance under gasoline operation.

02 PETROLEUM↗

Sodium Ion Expansion Power Block for Distributed CSP

The Sodium Ion Expansion Power Block for Distributed CSP was a three-plus-one-year effort under the Concentrating Solar Power: Advanced Projects Offering Low LCOE Opportunities (CSP: APOLLO) funding program within the U.S. Department of Energy Solar Energy Technologies Office. The primary objective of this project is to develop a dual-stage modular sodium thermal electrochemical converter (Na-TEC) heat engine power block, which can be potentially integrated with either a small-scale dish solar or large-scale heliostats and parabolic trough CSP. Na-TEC is a heat engine that generates electricity through the isothermal expansion of sodium ions. The Na-TEC is a closed system that can theoretically achieve conversion efficiencies above 45% when operating between thermal reservoirs at 1150 K and 550 K. However, thermal designs have confined previous single-stage devices to thermal efficiencies below 20%. To mitigate some of these limitations, we consider dividing the isothermal expansion into two stages; one at the evaporator temperature (1150 K) and another at an intermediate temperature (650 K –1050 K). This dual-stage Na-TEC takes advantage of regeneration and reheating, and could be amenable to better thermal management. In light of this, we first designed and developed a thermo-electrochemical model, and thermodynamically demonstrated how the dual-stage device can improve the efficiency by up to 8% points over the best performing single-stage device. We also established an application regime map for the single- and dual-stage Na-TEC in terms of the power density and the total thermal parasitic loss. Moreover, a thermal design of an axisymmetric dual-stage Na-TEC is developed to guide the scale-up and fabrication of sub-components of prototype module. A reduced-order finite-element model is used in conjunction with a Na-TEC thermodynamic model that was developed to determine the total parasitic heat loss of this dual-stage design. A number of simplifications are applied in the reduced-order model to decrease the computational time while maintaining acceptable accuracy. According to this analysis, a maximum efficiency of 29% and a maximum power output of 125 W can be achieved. Ultimately, we were able to demonstrate thermal efficiency improvements of the Na-TEC heat engine from 19% up to 40.3%, in a dual-stage (non-optimized) prototype module that we designed, fabricated, and tested with high temperature stage at 923 K. Furthermore, a cost-performance analysis for this improved dual-stage design was carried out for distributed-CSP systems. A high-level techno-economic analysis (TEA) explores four scenarios where a Na-TEC is used as the heat engine for a distributed-CSP system. Overnight capital cost and levelized cost of electricity (LCOE) are estimated for a system lifetime of 30 years, revealing that overnight capital costs in a range from $3.57 to $17.71 per We are feasible, which equate to LCOEs from 6.9 to 17.2 cents/kWh e -1 . This analysis makes a significant contribution by concurrently quantifying the efficiency and unit costs for a range of multistage configurations, and demonstrating that a Na-TEC may be a promising alternative to Stirling engines for distributed-CSP systems at residential scale of 1–5 kW e .

14 SOLAR ENERGY↗

Development of Analysis Methods that Integrate Numeric and Textual Equipment Reliability Data

Within the Light Water Reactor Sustainability (LWRS) program, the Risk-Informed Systems Analysis (RISA) Pathway is performing collaborative research on the development and deployment of technologies designed to assist operating nuclear power plants (NPPs) to reduce operating costs improve plant reliability and availability. One of the RISA research areas is focusing on the development of methods and tools designed to optimize plant operations (e.g., maintenance/replacement schedules, optimal maintenance postures for plant structures, systems, and components [SSCs]) in a manner that is more cost effective than current approaches and makes better use of available SSC health data. The Risk-Informed Asset Management (RIAM) project targets this research area by creating a direct bridge between component equipment reliability (ER) data and system engineer decision making regarding maintenance activity scheduling and component aging management. In this respect, one challenge that NPP system engineers are facing is that the amount of ER data being continuously generated is not only extremely large in size, but it comes in different forms: textual (e.g., condition or maintenance reports) and numeric (e.g., generated by monitoring systems). All these data elements provide them with valuable insights and information regarding: 1) the discovery of anomalous behaviors or degradation trends, 2) the identification of the possible causes behind such behaviors/trends, and 3) the prediction of their direct consequences. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers/databases), others are conceptual in nature: data elements come in different formats (e.g., numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). The activities performed by the RIAM project during FY23 directly tackles the need to simultaneously integrate the analysis of ER data in all its forms, numeric and textual. Note that such task has never been performed before due to the complexity of the systems under consideration but, most importantly, because of the technical challenges behind the harmonization of ER data formats and the lack of adequate computational methods to analyze them. Our approach borrows ideas and concepts from the medical field where integration of several data sources is vital to assist medical practitioners to perform correct diagnosis and indicate optimal treatments. In our view a NPP asset is equivalent to a patient in a medical context. The main difference is the complexity of a human body is a magnitude more complex when compared to typical assets commonly present in NPPs (e.g., centrifugal pumps, or motor operated valves). This simplifies our first requirement when analyzing heterogenous ER data formats: to put data into “context”. Context is here intended as the additional piece of information that is needed by ER data analysis tools to understand what these data elements are referring to, i.e., which king of knowledge they are generating. In our context, this knowledge can be translated into models that capture the form and functional architecture of assets/systems, their dependencies, and how they interact. These models actually emulate the knowledge that that NPP system engineers possess about assets and systems; this is their key of success when analyzing ER data, their challenge is ability to handle large amount of data. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional, i.e. cause-effect, relations. Then, ER data elements are processed by identifying first of all which elements of the developed MBSE elements they are referring to. For numeric ER data this task is fairly easy since it is possible to precisely pinpoint what MBSE elements the corresponding sensor are observing (e.g., bearing temperature of a centrifugal pump). Task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process as “knowledge extraction”. Once again, we borrow the experience in the medical field where methods to extract knowledge from textual data have been developed in the past decade. The missing element for us is the availability of a complete dictionary of NPP related concepts (in addition to the MBSE models presented earlier) that can put “text into context”. In FY23, such dictionary has been developed along with all the computational elements required for knowledge extraction. Lastly, once numeric and textual ER data elements have been processed and “understood”, then the last step is the discovery of possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if the

97 MATHEMATICS AND COMPUTING↗