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NuScale systems engineering program overview, including technical data management and model-based engineering, product structures, architecture views, and model-based systems engineering. Includes a discussion on technical risk and opportunity management and technical readiness levels, as well as risk-informed performance-based principles and methods.
The project uses system engineering principles to address the need of Boy Scout leaders for an integrated system to facilitate advancement and awards records, leader training and planning for meetings and activities. Existing products to address needs of Scout leaders and relevant stakeholders function to support record keeping and some communication functions but opportunity exists for a better system to fully integrate these functions with training delivery and recording, activity planning along with feedback and information gathering from stakeholders. Key stakeholders for the sytem include Scouts and their families, leaders, training providers, sellers of supplies and awards, content generators and facilities that serve Scout activities. Key performance parameters for the system are protection of personal information, availability of current information, information accuracy and information content that has depth. Implementation concepts considered for the system include (1) owned and operated by Boy Scouts of America, (2) Contracted out to a vendor (3) distributed system that functions with BSA managed interfaces. The selected concept is to contract out to a vendor to maximize the likelihood of successful integration and take advantage of the best technology. Development of requirements considers three key use cases (1) System facilitates planning a hike with training needed satisfied in advance and advancement recording real time (2) Scheduling and documenting in-person training, (3) Family interested in Scouting receives information and can request follow-up. Non-functional requirements are analyzed with the Quality Function Deployment tool. Requirement addressing frequency of backup, compatibility with legacy and new technology, language support, software update are developed to address system reliability and intuitive interface. System functions analyzed include update of activity database, maintenance of advancement status, archive of documents, and monitoring of content that is accessible. The study examines risks associated with information security, technological change and continued popularity of Scouting. Mitigation is based on system functions that are defined. The approach to developing an improved system for facilitating Boy Scout leader functions was iterative with insights into capabilities coming in the course of working through the used cases and sequence diagrams.
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he electric sector across North America is facing a transition. Both economics and policy decisions have pointed towards a broad retirement of fossil assets across markets. Owners are facing the problem of how to evolve the base of the electric sector from fossil asset to greener alternative. Coal-fired power plants built the modern electricity grid. Their rotating machinery are the beating heart of the grid, providing essential resiliency and reliability services. Power plant retirements are disruptive to plant workforces and cause outsized impacts on surrounding communities. The transition from thermal power plants that use rotating machinery to generate electricity (e.g., coal- and gas-fired plants) to variable, inverter-based generation (e.g., solar and wind) is affecting the reliability of the electric grid. Grid operators and national regulators have issued warnings about known and anticipated risk. In 2021, Malta Inc. was awarded a Department of Energy (DOE) grant to study how to integrate a Malta 100MW Pumped Heat Energy Storage (PHES) system with a retiring coal-fired power plant to meet emissions requirements, retain plant workforces, preserve communities, and maintain grid reliability. This presentation provides a summary of this study, focusing on how systems engineering approach was used to arrive at a proposed design concept that met multiple objectives and requirements. There will be three main parts for this presentation. The first part of the presentation will focus on how different systems engineering was applied for this work. In particular, the following areas: stakeholder engagement, site selection process, developing requirements and use cases for the integrated system, defining the system and its boundary, coming up with different system architecture/option, performing a techno-economic analysis to compare the different options and down selection of the preferred option, will be discusses. For these areas, discussion on the decisions on how much breadth and depth to go into each area will be provided. These discussions provide good insights into how to apply systems engineering. The second part of the presentation will provide a deeper dive into the two recommended integration options that repurpose coal-fired power plants with Malta PHES system. The comparison of the two options and general guidance of how to choose an option will be provided. This is particularly useful for utilities who are facing coal-plant retirements. The two options will be compared based on its performance (such as power output, efficiency), complexity, and cost. The social impact on local communities of the two options will also be discussed. The final part of the presentation will discuss the impact that this work has had, including Malta Inc. being invited to the White House to discuss progress and outcomes of this work with the Interagency Working Group on Coal and Power Plant Communities and Economic Revitalization. In summary, this presentation aims to provide a showcase of how sy
Advanced small modular reactors (AdvSMRs) will use advanced digital instrumentation and control systems, and make greater use of automation. These advances not only pose technical and operational challenges, but will inevitably have an effect on the operating and maintenance (O&M) cost of new plants. However, there is much uncertainty about the impact of AdvSMR designs on operational and human factors considerations, such as workload, situation awareness, human reliability, staffing levels, and the appropriate allocation of functions between the crew and various automated plant systems. Existing human factors and systems engineering design standards and methodologies are not current in terms of human interaction requirements for dynamic automated systems and are no longer suitable for the analysis of evolving operational concepts. New models and guidance for operational concepts for complex socio-technical systems need to adopt a state-of-the-art approach such as Cognitive Systems Engineering (CSE) that gives due consideration to the role of personnel. This approach we report on helps to identify and evaluate human challenges related to non-traditional concepts of operations. A framework - defining operational strategies was developed based on the operational analysis of Argonne National Laboratory’s Experimental Breeder Reactor-II (EBR-II), a small (20MWe) sodium-cooled reactor that was successfully operated for thirty years. Insights from the application of the systematic application of the methodology and its utility are reviewed and arguments for the formal adoption of CSE as a value-added part of the Systems Engineering process are presented.
The primary technical objective of this CRADA was for Sandia National Laboratories (SNL) and Northrop Grumman Systems Corporation, acting through Northrop Grumman Aerospace Systems (NGAS), to collaborate, as needed, to inform a Remote Sensing System (RSS) development, led by the NGAS CRADA partner, through its System Design Review (SDR) and subsequent Program Design Review (PDR) milestones. More specifically, tasks and deliverables involved SNL and NGAS collaborating in seven broad areas: System Engineering, System Modeling and Simulation, System and Component Design, Assessment and Implementation, System Integration and Testing, Data Path Design and Engineering and Collection Segment Processing Engineering and Implementation. The collaboration between SNL and NGAS has resulted in a benefit to both organizations, and the public/taxpayers, by ensuring that legacy knowledge is not lost to future developments and will be incorporated into ongoing and future U.S. sensor systems.
The US Department of Energy Office of Nuclear Energy (DOE-NE) Office of Spent Fuel and High-Level Waste Disposition is examining a set of system options and conducting supporting analyses to inform the development of an integrated waste management system, which may include one or more federal staging facilities (FSFs) for used nuclear fuel (UNF ) sited using a collaborative siting process. This paper focuses on the ongoing activities in two systems engineering and analysis work areas: (1) data and tools development, validation, and maintenance and (2) systems engineering execution. Within the first work area, the STANDARDS 5.0 UNF data and analysis tool, formerly known as UNF-ST&DARDS, is being developed as a foundational resource to assist in the management of UNF data. It has the key capability to model UNF throughout the entire back end of the fuel cycle. STANDARDS also includes several compatible analysis tools for the time-dependent characterization of UNF and related systems by interfacing with the SCALE code system for nuclear analysis and COBRA-SFS for thermal analysis. Also, within the data and tools area is the Next Generation System Analysis Model (NGSAM), which is an agent-based simulation software tool expressly designed to be capable of modeling the waste management system, including the transportation of UNF to and from a FSF. NGSAM has been developed to enable informed decision-making by providing the capability to analyze various potential system options for the management of UNF and high-level radioactive waste. Finally, in the systems engineering execution area, the team has begun to apply a disciplined systems engineering approach at the system level along with supporting analysis to guide the development of the FSF project requirements (including associated transportation infrastructure). Systems engineering principles and practices and their adaptation/application to design and development activities will ensure that the waste management system is effectively implemented as work proceeds. Other activities include investigating the implications of changes in various assumptions and parameters related to waste management systems, such as UNF acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, and different assumed facility operation start dates. Keywords: federal staging facility (FSF), used nuclear fuel (UNF), integrated waste management (IWM) system, Next Generation System Analysis Model (NGSAM), STANDARDS, systems engineering
Lidar-assisted control is a promising technology for reducing the levelized cost of energy from wind turbines, but quantifying its impact at the overall system level requires sophisticated systems engineering analysis and optimization frameworks. The joint workshop on Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering was held by the International Energy Agency Wind Task 32 (Lidar) and Task 37 (Systems Engineering) in October 2019 to address this challenge. This paper summarizes the outcome of the workshop and presents a road map for further research. The most promising applications of lidar-assisted control identified at the workshop and discussed here include 1) increasing annual energy production, 2) decreasing capital expenditure costs by reducing design loads, 3) extending turbine lifetime by reducing operating loads, and 4) enabling wind turbine class upgrades. For each application, we review the state of the art and highlight remaining research needs. Finally, we discuss strategies for addressing these research needs by conducting high-fidelity systems engineering optimizations.
The genesis for this systematic literature review was to search for industry case studies that could inform a decision of whether or not to support the change process, investment, training, and tools needed to implement an MBSE approach across the engineering enterprise. The question asked was, how the change from a document - based systems engineering approach (DBSE) to a model-based systems engineering approach (MBSE) is justified? The methodology employed for this systematic literature review was to conduct a document search of electronically published case studies by authors from the defense, space, and complex systems product engineering industries. The 67 case studies without metrics mainly attributed success to completeness, consistency, and communication of requirements. The 21 case studies with metrics on cost and schedule primarily attributed success to the ability of an MBSE approach to improve defect prevention strategies. The primary conclusion is that there is a significant advantage to project performance by applying an MBSE approach. An MBSE approach made the engineering processes on a complex system development effort more efficient by improving requirements completeness, consistency, and communication. These were seen in engineering processes involved in requirements management, concept exploration, design reuse, test and qualification, Verification and Validation, and margins analyses. An MBSE approach was most effective at improving defect prevention strategies. The approach was found to enhance the capability to find defects early in the system development life cycle (SDLC), when they could be fixed with less impact and prevented rework in later phases, thus mitigating risks to cost, schedule, and mission. However, if a program only employed an MBSE approach for requirements management, advantages from finding defects early could not be leveraged in later phases, where the savings in cost and schedule from rework prevention is realized. Significant performance success was achieved when the systems engineer (SE) held a leadership role over engineering process es. A number of the case studies addressed a general lack of skilled MBSE engineers as a major hindrance to implementing an MBSE approach successfully.
This paper introduces how an integrated set of Systems Engineering (SE) and Project Management (PM) processes were applied in a practical way, to address the challenges on a complex, highly technical, Engineering Procurement Construction project within the nuclear field. This approach was inspired by: - the principles contained in a Community of Practice on Lean in Program Management jointly established in May 2012 by MIT, PMI and INCOSE; - an opportunity to apply international standard ISO/IEC 15288:2008(E) Systems and software engineering - System life cycle processes on a real-life situation; - and the belief that there is great value in applying Systems Engineering and Project Management in an integrated manner on a project. The project offering this opportunity was the Detail Engineering, Procurement, Construction and Cold Commissioning (EPC) of the Silo Direct-encapsulation Plant (SDP). This project was undertaken by the Joint Venture (JV) formed by Areva, Mace and Atkins (a.m.a. Nuclear Ltd). Unfortunately, early termination of the project, at a stage when only a part of the processes and tools were being implemented, did not allow this integrated approach to be demonstrated in full. However, the benefits achieved in the early stages in aligning and forming an integrated project execution team, showed potential for great benefits. This paper covers an introductory analysis of the situation, the successes and benefits achieved from implementing an integrated SE - PM approach up to the stage when the project was terminated, and possible path forward had the project continued. (authors)
This report highlights journal articles published in 2016 by researchers in the Power Systems Engineering Center. NREL's Power Systems Engineering Center published 47 journal and magazine articles in the past year, highlighting recent research in grid modernization.
The application of Systems Engineering (SE) principles has emerged to manage complex systems from a concept to the successful realization and implementation of the system. Multiple Research and Development (R&D) programs at Sandia National Laboratories (SNL) have implemented these principles and have maximized their efforts in the realization of successful systems. The Primary Standards Laboratory (PSL) at SNL has avoided the full implementation of such principles which has stalled the development of new and efficient calibration systems. The objective of this project is to introduce SE to the PSL and develop a framework of best practices that can be utilized to expedite the development and deployment of accurate and efficient testing systems throughout the PSL. A Case Study will be presented for the principles of the SE development lifecycle in a R&D environment to maximize the PSL’s efforts in a requirements-driven environment.
With the goal of improving the performance and reliability of high dependable technological systems such as nuclear power plants, advanced monitoring and health management systems are employed to inform system engineers on observed degradation processes and anomalous behaviors of assets and components. This information is captured in the form of large amount of data which can be heterogenous in nature (e.g., numeric, textual). Such large data availability poses challenges when system engineers are required to parse and analyze them in order to track historic reliability performance of assets and components. This paper tackles directly this challenge by providing means to organize data in the form of a graph: a knowledge graph. The presented approach distinguish itself from current knowledge graph-based methods by the fact that model-based system engineering (MBSE) models are used to “put data into context”. In particular, MBSE models are used as skeleton of a knowledge graph; numeric and textual data elements, once processed, are associated to MBSE model elements. Thus, a knowledge graph captures both system architecture (though MBSE models) and health/performance data. Such feature opens the door to new data analytics methods designed to identify causal relations between observed phenomena.
A gaseous fuel engine system includes a hydrogen fuel supply, an engine housing having an intake port extending to a cylinder, and an intake runner. The intake runner includes a valve mount attached to a conduit and having a valve mounting face, and a gaseous fuel admission valve is mounted upon the valve mounting face. A hydrogen fuel passage extends from the valve mount through the conduit and is oriented angularly to at least one of a clamping face of the intake runner or the valve mounting face. Related apparatus and methodology is also disclosed.
Components for a transformative, high pressure, intermediate temperature solid oxide fuel cell (SOFC) and premixed compression ignition (PCI) engine system were developed. The resulting system is a 1 MWe natural gas fueled hybrid SOFC and reciprocating internal combustion engine system capable of achieving over 70% electrical efficiency at a cost of $0.87/W. To achieve 70% electric efficiency, the SOFC system operates at 80% fuel utilization; however, when operating at this high level of fuel utilization, fuel to the engine (anode tailgas) is extremely dilute. Accordingly, a substantial portion of the effort focused on development and assessment of the combustion strategy capable of consuming this dilute fuel mixture. The engine testing effort showed that pre-chamber assisted compression ignition provides the best combination of controllability, efficiency and emissions. The engine experiments showed that high efficiency combustion can be achieved with near zero criteria pollutants. It is likely that the engine system could operate with minimal aftertreatment requirements, reducing complexity, cost, and precious metal usage. System level modeling was used to assess the overall efficiency, determine cost and efficiency tradeoffs, and demonstrate the potential to perform load following with the hybrid system. Finally, advanced manufacturing was used to demonstrate the potential to fabricate heat exchangers needed for the hybrid system from low chromium materials, which addresses the issue of chromium poisoning of the SOFC stack material.
The high complexity and multiscale nature of many engineered systems—such as those in nuclear power plants—make representing and forecasting their dynamic behavior challenging. Physics-based models can be overly complex and computationally intractable, whereas machine learning (ML) tools are often data-hungry and prone to unphysical solutions. This study proposes a knowledge-informed ML-aided hybrid residual modeling approach that offers accurate and efficient time series forecasting for the operation of dynamical engineered systems. Hybrid residual modeling entails a baseline solution from domain knowledge and known physics expressions about the system dynamics integrated with an ML model to capture undiscovered information from the mismatch (i.e., residuals) between true states from measurements and baseline-predicted outputs. This study further quantifies the ML model uncertainty to provide trustworthy solutions. Real-time operational data from thermal-hydraulic flow loops of the cryogenic moderator system in Oak Ridge National Laboratory’s Spallation Neutron Source facility were used to demonstrate the potential of knowledge-informed uncertainty-aware ML in real-world applications. The state variables of the cryogenic helium loop were modeled with (1) first principles–based system identification (sysID), (2) long short-term memory (LSTM) neural network, and (3) hybrid sysID (baseline) + LSTM (residual). The superior predictive capability of the sysID+LSTM model versus stand-alone sysID and LSTM is confirmed by average performance metrics and individual data points across different prediction horizons. By creating a robust representation of the underlying physical system, the widely applicable hybrid residual modeling approach will enable the future development of digital twins for performance prediction, prognostics, and operation control.
In response to the challenges related to the increasing size and complexity of systems, organizations have recognized the need to integrate human considerations in the beginning stages of systems development. Human Systems Integration (HSI) seeks to accomplish this objective by incorporating human factors within systems engineering (SE) processes and methodologies, which is the focus of this paper. A representative set of HSI methods from multiple sources are organized, analyzed, and mapped to the systems engineering Vee-model. These methods are then consolidated and evaluated against the SE process and Models-Based Systems Engineering (MBSE) methodology to determine where and how they could integrate within systems development activities in the form of specific enhancements. Overall conclusions based on these evaluations are presented and future research areas are proposed.