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A general-purpose development environment for intelligent computer-aided training systems

Space station training will be a major task, requiring the creation of large numbers of simulation-based training systems for crew, flight controllers, and ground-based support personnel. Given the long duration of space station missions and the large number of activities supported by the space station, the extension of space shuttle training methods to space station training may prove to be impractical. The application of artificial intelligence technology to simulation training can provide the ability to deliver individualized training to large numbers of personnel in a distributed workstation environment. The principal objective of this project is the creation of a software development environment which can be used to build intelligent training systems for procedural tasks associated with the operation of the space station. Current NASA Johnson Space Center projects and joint projects with other NASA operational centers will result in specific training systems for existing space shuttle crew, ground support personnel, and flight controller tasks. Concurrently with the creation of these systems, a general-purpose development environment for intelligent computer-aided training systems will be built. Such an environment would permit the rapid production, delivery, and evolution of training systems for space station crew, flight controllers, and other support personnel. The widespread use of such systems will serve to preserve task and training expertise, support the training of many personnel in a distributed manner, and ensure the uniformity and verifiability of training experiences. As a result, significant reductions in training costs can be realized while safety and the probability of mission success can be enhanced.

Savely, Robert T.↗

Management of Knowledge Representation Standards Activities

Ever since the mid-seventies, researchers have recognized that capturing knowledge is the key to building large and powerful AI systems. In the years since, we have also found that representing knowledge is difficult and time consuming. In spite of the tools developed to help with knowledge acquisition, knowledge base construction remains one of the major costs in building an Al system: For almost every system we build, a new knowledge base must be constructed from scratch. As a result, most systems remain small to medium in size. Even if we build several systems within a general area, such as medicine or electronics diagnosis, significant portions of the domain must be represented for every system we create. The cost of this duplication of effort has been high and will become prohibitive as we attempt to build larger and larger systems. To overcome this barrier we must find ways of preserving existing knowledge bases and of sharing, re-using, and building on them. This report describes the efforts undertaken over the last two years to identify the issues underlying the current difficulties in sharing and reuse, and a community wide initiative to overcome them. First, we discuss four bottlenecks to sharing and reuse, present a vision of a future in which these bottlenecks have been ameliorated, and describe the efforts of the initiative's four working groups to address these bottlenecks. We then address the supporting technology and infrastructure that is critical to enabling the vision of the future. Finally, we consider topics of longer-range interest by reviewing some of the research issues raised by our vision.

Patil, Ramesh S.↗

Development and Testing of Automatically Generated ACS Flight Software for the MAP Spacecraft

By integrating the attitude determination and control system (ACS) analysis and design, flight software development, and flight software testing processes, it is possible to improve the overall spacecraft development cycle, as well as allow for more thorough software testing. One of the ways to achieve this integration is to use code-generation tools to automatically generate components of the ACS flight software directly from a high-fidelity (HiFi) simulation. In the development of the Microwave Anisotropy Probe (MAP) spacecraft, currently underway at the NASA Goddard Space Flight Center, approximately 1/3 of the ACS flight software was automatically generated. In this paper, we will examine each phase of the ACS subsystem and flight software design life cycle: analysis, design, and testing. In the analysis phase, we scoped how much software we would automatically generate and created the initial interface. The design phase included parallel development of the HiFi simulation and the hand-coded flight software components. Everything came together in the test phase, in which the flight software was tested, using results from the HiFi simulation as one of the bases of comparison for testing. Because parts of the spacecraft HiFi simulation were converted into flight software, more care needed to be put into its development and configuration control to support both the HiFi simulation and flight software. The components of the HiFi simulation from which code was generated needed to be designed based on the fact that they would become flight software. This process involved such considerations as protecting against mathematical exceptions, using acceptable module and parameter naming conventions, and using an input/output interface compatible with the rest of the flight software. Maintaining good configuration control was an issue for the HiFi simulation and the flight software, and a way to track the two systems was devised. Finally, an integrated test approach was devised to support flight software testing at both the unit- and build-test levels using the HiFi simulation to generate data for performance verification. Another benefit of the simulation and code-generation application used on the MAP project is that it supported bringing flight software and test data into the HiFi simulation environment. It was possible to integrate parts of the hand-coded flight software into the HiFi simulation, and also possible to import flight software test data for comparison and performance verification. This capability was used to incorporate the flight software Kalman filter into the HiFi simulation. This enabled us to greatly increase the amount of testing that could be done on the filter, because we could exert a greater degree of control over the software-only simulation than over the flight software test environment. Also, since the simulation could be used to run the Kalman filter faster than real time, our testing efficiency was greatly increased. We will conclude our discussion with a summary of the lessons learned thus far using automatically- generated code for the MAP project, and the spacecraft status as we work towards our scheduled launch in the year 2000.

ODonnell, James R., Jr.↗

National Campaign Partner Demonstration Team Annual Review April 2023

- NASA developed the Advanced Air Mobility Project (AAM) and the National Campaign (NC) series to identify and address challenges ahead for advanced air mobility concepts. - NC seeks to challenge industry as follows; - Execute progressively more difficult ecosystem-wide system-level safety and integration scenarios - Demonstrate practical and scalable system concepts - Build a knowledge base for development of requirements and standards - There are currently three focus areas within the NASA AAM NC Portfolio - Vehicle Development and Operations: test and inform capabilities that are critical enablers for AAM such as electric aircraft propulsion and increasing levels of automation - Airspace Design and Operations: develop and validate an operational concept to integrate and manage AAM traffic safely and efficiently - Community Integration: understand and address critical barriers to community integration, such as public acceptance (noise, security, privacy, etc.), supporting infrastructure, and local regulation

Eric N Becker↗

Model-Free Building Temperature Control and Power Allocation Under Measurement Time Delays

Taking a step towards a greener planet has created an increased need for a higher integration of renewable energy resources into the electric grid. Nonetheless, the intermittency and uncertainty associated with renewable generation have slowed down this integration. Demand response (DR) has been recently adopted to address this challenge by utilizing demand side flexibility and enabling the participation of many grid-interactive efficient buildings (GEBs). However, existing DR methods require significant modeling and/or training efforts and are computationally expensive. To address the aforementioned issues, we propose a model-free control (MFC)-based strategy that is robust to the time delays in the temperature measurements of the thermostatically controlled loads (TCLs). It assigns to each GEB a local controller to maintain the TCLs’ temperatures within desired comfort levels, while the load aggregator (LA) allocates the assigned reference power provided by the distribution system operator (DSO) to support a specific grid service, such as demand peak reduction, load shifting, balancing supply and demand, and consuming the solar photovoltaic power locally. We investigate the effects of such loss of information on the local control action as well as on meeting the power allocation constraint. We conclude that, for an appropriate choice of design parameters, the proposed MFC controller is satisfactorily robust to measurement time delays.

Telsang, Bhagyashri↗

Complex Decision-Making Applications for the NASA Space Launch System

The Space Shuttle program is ending and elements of the Constellation Program are either being cancelled or transitioned to new NASA exploration endeavors. The National Aeronautics and Space Administration (NASA) has worked diligently to select an optimum configuration for the Space Launch System (SLS), a heavy lift vehicle that will provide the foundation for future beyond low earth orbit (LEO) large-scale missions for the next several decades. Thus, multiple questions must be addressed: Which heavy lift vehicle will best allow the agency to achieve mission objectives in the most affordable and reliable manner? Which heavy lift vehicle will allow for a sufficiently flexible exploration campaign of the solar system? Which heavy lift vehicle configuration will allow for minimizing risk in design, test, build and operations? Which heavy lift vehicle configuration will be sustainable in changing political environments? Seeking to address these questions drove the development of an SLS decision-making framework. From Fall 2010 until Spring 2011, this framework was formulated, tested, fully documented, and applied to multiple SLS vehicle concepts at NASA from previous exploration architecture studies. This was a multistep process that involved performing figure of merit (FOM)-based assessments, creating Pass/Fail gates based on draft threshold requirements, performing a margin-based assessment with supporting statistical analyses, and performing sensitivity analysis on each. This paper discusses the various methods of this process that allowed for competing concepts to be compared across a variety of launch vehicle metrics. The end result was the identification of SLS launch vehicle candidates that could successfully meet the threshold requirements in support of the SLS Mission Concept Review (MCR) milestone.

Lyles, Garry↗

Exploration Medical Capability Clinical Decision Support System Architecture Recommendation

A new era in space exploration has arrived with the goal of establishing a long-term presence on the Moon and using those learning to take the next giant leap: sending the first astronauts to Mars. These ambitious goals will require significant changes in in-flight medical care due to constraints on mass, volume, power, crew time, and medical evacuation capabilities. Furthermore, while crews currently rely on real-time communications with ground-based medical providers, as distance from Earth increases, so do communication delays and disruptions. The crew will need to autonomously detect, diagnose, treat, and prevent medical events. These constraints require development of transformative solutions and new technologies. Through participation in the Human Research Program’s (HRP) Exploration Medical Capability (ExMC) research, NASA has developed and demonstrated a Medical Data Architecture (MDA), a platform upon which a robust capability of Clinical Decision Support (CDS) can be built. As a result, NASA is now positioned to build an advanced autonomous CDS System (CDSS) which will aid in crew health decision-making. The CDSS combines data management aspects of a system that would lead to the autonomy required by NASA-STD-3001, Section 3, Health and Medical Care Standards. The project addresses the ExMC gap Medical-701: We need to increase inflight medical capabilities and identify new capabilities that (a) maximize benefit and/or (b) reduce “costs” on human system/mission/vehicle resources. This architecture recommendation document introduces an integrated data architecture that provides self-sufficient medical care for crews on long-duration spaceflight missions.

ExMC↗

Energetics of the lattice: packing elements in crystals of four-stranded intercalated cytosine-rich DNA molecules

Condensation of single molecules from solution into crystals represents a transition between distinct energetic states. In solution, the atomic interactions within the molecule dominate. In the crystalline state, however, a set of additional interactions are formed between molecules in close contact in the lattice--these are the packing interactions. The crystal structures of d(CCCT), d(TAACCC), d(CCCAAT), and d(AACCCC) have in common a four-stranded intercalated cytosine segment, built by stacked layers of cytosine.cytosine+ (C.C+) base pairs coming from two parallel duplexes that intercalate into each other with opposite polarity. The intercalated cytosine segments in these structures are similar in their geometry, even though the sequences crystallized in different space groups. In the crystals, adenine and thymine residues of the sequences are used to build the three-dimensional crystal lattice by elaborately interacting with symmetry-related molecules. The packing elements observed provide novel insight about the copious ways in which nucleic acid molecules can interact with each other--for example, when folded in more complicated higher order structures, such as mRNA and chromatin.

Non-NASA Center↗

West Africa Battery Energy Storage Systems (BESS) Capacity Building - Discussion of BESS Tariffs: Payment Structures and Case Studies [Slides]

Battery Energy Storage Systems (BESS) are emerging as critical assets for enhancing grid reliability, integrating renewable energy, and enabling system flexibility. Yet, the regulatory and financial frameworks that determine how BESS projects are compensated vary widely across jurisdictions. This presentation explores international case studies - from Honduras, Costa Rica, Chile, South Africa, Mexico, and Brazil - to illustrate how tariff design and payment structures are evolving to support large-scale BESS deployment. The cases highlight a range of ownership and revenue models, including cost-of-service mechanisms, energy and capacity payments, and market-based arbitrage, as well as hybrid approaches under development. The discussion will examine key challenges such as defining remuneration for ancillary services, addressing double charging, and accounting for efficiency losses and degradation over time. By comparing experiences across markets, the presentation identifies emerging best practices for valuing BESS and designing tariffs that align technical performance with economic incentives, providing insights for regulators, utilities, and policymakers pursuing storage integration.

25 ENERGY STORAGE↗

Refining seasonal performance metrics for room air-conditioning in emerging markets: Integrating building simulations with real-world equipment performance data

Buildings significantly impact worldwide energy consumption, emphasizing the need to reduce the cooling energy demand, especially in warm climates. Minimum energy performance standards (MEPS) and seasonal performance metrics such as the Cooling Seasonal Performance Factor (CSPF) are crucial for improving room air conditioning (RAC) efficiency. However, challenges remain, particularly in emerging markets like Brazil, where seasonal performance metrics have recently been introduced. This study assesses the factors influencing country-level seasonal efficiency metrics and proposes a framework to refine these calculations by considering local climates and expected RAC usage in real-world households via building simulations. Key considerations include outdoor air temperature binning for different climates, RAC usage patterns (i.e., daytime and nighttime usages), envelope thermal performance of households, and urban heat island (UHI) effects. The results reveal that CSPF values can vary significantly based on climate conditions, with observed CSPF ranging from 4.10 to 11.59 Wh/Wh across 577 Brazilian climates. The inclusion of UHI effects led to a reduction in CSPF values by up to 29% during nighttime operations in hot urban areas. Additionally, building envelope efficiency showed contrasting impacts on RAC performance, with CSPFs reaching up to 15.35 Wh/Wh under specific optimized conditions. These findings highlight the need for transparent policymaking in RAC performance databases, facilitating the application of approaches like those proposed in this study and supporting diverse stakeholders in decision-making.

Bavaresco, Mateus↗

Surrogate model evaluation and building energy benchmarking for commercial buildings

Building energy consumption benchmarking involves challenges associated with various energy patterns for different building types; heating, ventilating, and air-conditioning (HVAC) system types; and climates. Given significant variation in energy use patterns, accurate prediction of long-term energy use using surrogate models remains challenging. Multiple linear regression (MLR) is commonly used for building energy benchmarking because of its simple structure; however, it lacks accuracy compared to other black-box models. Although many studies have compared surrogate models and offer guidance on model selection based on metrics, they do not provide detailed analysis on improving the surrogate model accuracy. In this paper, we implement a surrogate model using polynomial ridge regression (i.e., MLR with interaction terms combined with ridge regularization) for small office and retail strip mall buildings across six HVAC system types and all climate zones, for electricity and natural gas in baseline and proposed scenarios. A simulation workflow is developed using OpenStudio TM /EnergyPlus TM to generate simulation data using measures over a wide range of efficiency inputs. Enhancements based on statistical insights are used for improving the model accuracy using filters, input transformations, and change points. Surrogate models achieved average coefficient of variation of the root mean squared error (CVRMSE) values of 2.17, 1.06, 2.05, and 3.26 for proposed electricity, proposed natural gas, baseline electricity, and baseline natural gas, respectively, with enhancements reducing CVRMSE by an average of 14.9% across all combinations. We provide model interpretation via Shapley additive explanations to determine which input variables most influence energy consumption and provide supportive arguments for enhancements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Factors Influencing Building Demand Flexibility

The U.S. Department of Energy’s National Roadmap for Grid-interactive Efficient Buildings (GEB) acknowledged that building demand flexibility (DF) is both an important strategy to decarbonizing the buildings sector and an important resource for meeting the changing needs of the electrical grid such as improving grid reliability. However, understanding the complexity and uncertainties in real building field performance of DF strategies is a large gap hindering stakeholders on both grid and buildings side to make investments on deploying such strategies. The research work in this report intended to advance understanding of the variability and influential factors in building demand flexibility. Adding such knowledge based on lab testing results and measured performance data from real buildings is an important contribution. The report uses standardized metrics and methods to quantify DF performance from field-measured DF datasets of two significant building groups of big-box retail and medium office buildings to present the challenge of building DF variability in multiple dimensions. The report presents findings related to how several key factors influence building demand flexibility from implementing a common, cost-effective DF control strategy (i.e., adjusting zone temperatures). The findings are supported by full-scale lab testing, field data analysis and simulation research. The authors also provided application-oriented recommendations to stakeholders such as building aggregators, utility program design professionals, sophisticated building portfolio owners, and more.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Williston Basin Resource Study for Commercial-Scale Subsurface Hydrogen Storage

The Energy & Environmental Research Center (EERC), in partnership with the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), the EERC’s State Energy Research Center (SERC), MPLX Operations LLC, and TC Energy Development Holdings Inc. (a subsidiary of TC Energy Corporation), studied the potential for subsurface hydrogen storage and recovery in the Williston Basin of western North Dakota. The project’s goal was to evaluate the feasibility of large-scale, secure geologic H 2 storage to support future hydrogen generation, storage, and use. This work included laboratory testing, H 2 –rock–fluid exposure experiments, literature reviews on H 2 embrittlement, and reservoir modeling and simulations. The study included an assessment of storage potential across three types of storage reservoirs using both reservoir simulation and DOE’s web-based tool SHASTA-HELP (Subsurface Hydrogen Assessment, Storage, and Technology Acceleration – Hydrogen Estimator for Logistical Planning), as well as investigation of potential H 2 production and markets for commercial-scale deployment. Building on prior EERC gas storage research, three storage options were selected for detailed evaluation: the Broom Creek Formation (a clastic saline reservoir), the Dickinson Lodgepole Mounds (DLM) complex (carbonate mud mound structures) of the Lodgepole Formation (an active oil and gas producing reservoir), and the Dunham Salt Interval of the Piper Formation (to be used for engineered salt cavern development). These targets were prioritized based on prior EERC research using datasets related to seal capacity, reservoir quality, mechanical integrity, and injectivity. Exposure tests on Broom Creek and DLM samples showed mineral dissolution and precipitation that increased brine salinity and altered reservoir rock surfaces. Although these results provide useful insight, they are limited by small sample sizes and short-term (30-day) exposure, requiring further study to assess long-term storage integrity. Salt formations were not tested because of their known nonreactivity and established mechanical stability. Results of reservoir simulations performed for a single site demonstrated that the Broom Creek Formation may be capable of receiving up to 42,000 tonnes of injected H 2 over 7 months via one well. H 2 recovery took place over 5 months, resulting in approximately 26,000 tonnes (~62% without cushion gas [CG]). This work suggests water production may be important and subsequent cycles of injection and production may perform more efficiently; however, significant site-specific work in the future is needed to assess actual reservoir performance of injection and withdrawal of H 2 storage. For oil reservoir potential, a multiple-well model was used to simulate injection of approximately 32,000 tonnes of H 2 into a single wellbore while simultaneously producing in place reservoir fluids from four offset wells to maintain reservoir pressure. The simulation results suggested a high recovery (~98%); in addition, cost advantages through existing infrastructure could be realized. Challenges in this reservoir include vi managing gas purity and leakage risks. In both scenarios, production of H 2 takes place in a single-well scenario with 10 cycles (7 months of injection and 5 months of production) over 10 years. Finally, the use of engineered caverns in the Dunhan Salt was evaluated, and the results suggest that while they have a smaller capacity (<1000 tonnes per cavern), they exhibit nearly complete gas recovery (>99%), fast response times, and low purity risk. While caverns in North Dakota may be smaller in capacity, fields can be developed in galleries to accommodate the volumetric needs and rapid turnaround times necessary to meet market demands. Geographic limitations and thin salt intervals in North Dakota may represent less total storage potential than salt domes elsewhere, but significant opportunities exist to expand this market for gas storage in North Dakota. A basinwide assessment was performed to estimate a first-of-its-kind value for H 2 storage on a large scale. DOE’s SHASTA-HELP, combined with EERC simulation work, was used to perform the assessment. Estimated H 2 storage potential varied widely for each formation type. The Broom Creek saline formation was estimated to have a storage potential of approximately 1.7–90.5 million tonnes (MMt). The DLM oil reservoirs were estimated to have 0.07–0.19 MMt of capacity. Notably, each of these estimates relies on significant assumptions regarding reservoir thickness, porosity, permeability, and CG needed for operation. Much research is needed to understand the true site-specific storage resource potential of each formation. Using the Dunham Salt Interval for cavern development may result in as much as 4.79 MMt (up to 2.87 MMt working gas) of H 2 storage potential. An important note for consideration is that the values presented here need significantly more geological characterization and engineering assessments prior to gaining confidence in performance. This will be a focal point for future research and development needs. The basinwide evaluation also indicated that North Dakota has significant H 2 generation potential, with estimates up to a possible 13 MMt annually, suggesting a substantial opportunity for H 2 market development and thus the need for commercial-scale H 2 storage to facilitate growth and resilience. Key Recommendations 1. Conduct detailed site characterization (3D seismic, well logs, core sampling) to reduce geologic uncertainty. 2. Perform techno-economic analyses incorporating market, regulatory, and incentive frameworks. 3. Investigate long-term interactions among H 2 , CGs, well materials, and formations to assess risks. 4. Develop pilot- and field-scale demonstrations to validate models and establish best practices.

03 NATURAL GAS↗

Paintable Reflective Coatings (CRADA Final Report)

As part of the Cyclotron Road LEEP, the Cypris Materials project team conducted research on the viability of a new reflective coating technology based on a novel advanced materials platform. Building off of nearly a decade of academic research spanning multiple institutions, research efforts were designed to tackle the familiar problem of maturing a project into a minimum viable product. Fundamental technologies spawned from academic research are fraught with both scientific and technical risk, as the barriers to a successful peer reviewed publication are much lower than a commercial product with a paying customer base. It is common, especially when maturing chemical or material innovations, to encounter a number of critical assumptions or features that support the performance of the technology in an unsustainable fashion. At the outset of the project, the platform technology of Cypris Materials was no different. Specific research thrusts regarding scale-up, process optimization, technoeconomic modeling, market specific weathering performance, and market specific optical performance were tackled during the CRADA project.

36 MATERIALS SCIENCE↗

YAM- A Framework for Rapid Software Development

YAM is a software development framework with tools for facilitating the rapid development and integration of software in a concurrent software development environment. YAM provides solutions for thorny development challenges associated with software reuse, managing multiple software configurations, the development of software product-lines, multiple platform development and build management. YAM uses release-early, release-often development cycles to allow developers to incrementally integrate their changes into the system on a continual basis. YAM facilitates the creation and merging of branches to support the isolated development of immature software to avoid impacting the stability of the development effort. YAM uses modules and packages to organize and share software across multiple software products. It uses the concepts of link and work modules to reduce sandbox setup times even when the code-base is large. One side-benefit is the enforcement of a strong module-level encapsulation of a module s functionality and interface. This increases design transparency, system stability as well as software reuse. YAM is in use by several mid-size software development teams including ones developing mission-critical software.

simulations↗

Commercialization is Required for Sustainable Space Exploration and Development

The U.S. Space Exploration policy outlines an exciting new direction in space for human and robotic exploration and development beyond low Earth orbit. Pressed by this new visionary guidance, human civilization will be able to methodically build capabilities to move off Earth and into the solar system in a step-by-step manner, gradually increasing the capability for humans to stay longer in space and move further away from Earth. The new plans call for an implementation that would create an affordable and sustainable program in order to span over generations of explorers, each new generation pushing back the boundaries and building on the foundations laid by the earlier. To create a sustainable program it is important to enable and encourage the development of a selfsupporting commercial space industry leveraging both traditional and non-traditional segments of the industrial base. Governments will not be able to open the space frontier on their own because their goals change over relatively short timescales and because the large costs associated with human spaceflight cannot be sustained. A strong space development industrial sector is needed that can one day support the needs of commercial space enterprises as well as provide capabilities that the National Aeronautics and Space Administration (NASA) and other national space agencies can buy to achieve their exploration goals. This new industrial space sector will someday provide fundamental capabilities like communications, power, logistics, and even cargo and human space transportation, just as commercial companies are able to provide these services on Earth today. To help develop and bolster this new space industrial sector, NASA and other national space agencies can enable and facilitate it in many ways, including reducing risk by developing important technologies necessary for commercialization of space, and as a paying customer, partner, or anchor tenant. This transition from all or mostly government developed and operated facilities and services to commercial supplied facilities and services should be considered from the very earliest stages of planning. This paper will first discuss the importance of space commercialization to fulfilling national goals and the associated policy and strategic objectives that will enable space exploration and development. Then the paper will offer insights into how government can provide leadership to promote the nascent commercial space industry. In addition, the paper describes programs and policies already in place at NASA and offers five important principles government can use to strengthen space industry.

Martin, Gary L.↗

Meta-Analysis of Advanced Nuclear Reactor Cost Estimations

Supporting Data can be downloaded at: https://gain.inl.gov/content/uploads/4/2024/06/INL-RPT-24-77048-R1.xlsx Nuclear energy is a critical cornerstone of the current United States clean energy supply and may play a larger role in the future in support of a transition to a net-zero economy. The current fleet of nuclear reactors predominantly consists of large light-water reactors (LWRs), while many of the reactor designs under consideration are smaller and/or different technologies. Because these new designs have not yet been built, there is a high degree of uncertainty associated with their cost. This complicates energy-planning efforts because cost projections are not always standardized, consistent, and centralized in an easily accessible location. To help support energy planning in the US, this report provides advanced nuclear cost ranges using a transparent methodology along with other relevant information that can be used to help support decision making and energy planning. The purpose of this work was to conduct a methodical process for cost evaluation using only public information that was vetted with the end-goal to provide reference cost projections for nuclear energy. To provide a solid basis for these values, the approach and assumptions are explicitly laid out throughout the report allowing any user of the data to challenge or reconsider them. Because future US nuclear-reactor costs are still unknown due to little recent observed data, the report opted to compile a comprehensive list of bottom-up estimates and evaluate averages/trends within the data to identify reference ranges. This was deemed preferable to opining on the robustness or validity of one cost estimation versus another. To that end, the work evaluated thousands of lines of cost subaccounts from several bottom-up cost estimates. A wide variety of different reactor types captured in the data are of various sizes and technologies. Some of these reactors will be representative of advanced reactors under development while others will not. Thus, the results here are dependent on the data that are available and the accuracy of the estimates that are used. Each bottom-up estimate was reviewed to determine whether it was complete. Incomplete data sets were corrected to ensure an adequate basis of cross-comparison. The report is not without limitations and should be interpreted as an initial step to develop cost ranges for nuclear technology. Ultimately, future work can build upon the methodology with refined cost estimates to reduce uncertainty. US-based overnight capital cost (OCC) estimates were compiled from extensive data sets into ranges for both large and small reactor sizes for 2030. To project the cost declines over time, learning rates were sampled from literature sources. No SMRs were previously built; hence, learning rates based on bottom-up approaches (e.g., by quantifying the impact stemming from fabrication of different components, modular work, site construction, commissioning) were prioritized. For larger reactors, actual learning rates from deployments were used to project future costs (adjusted to account for standardization or lack thereof between designs). Other costs included are fixed and variable operations and maintenance costs. The final variables were capacity factors and ramp rates to support energy planning.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

FY2020 LDRD Annual Report

The Laboratory Directed Research and Development (LDRD) program funds scientific efforts to build upon the unique knowledge base of Savannah River National Laboratory (SRNL). The program yields foundational scientific research and development (R&D) essential to SRNL’s core business areas, while aligning optimally and continuously with SRNL’s Strategic Plan and providing long-term benefits to DOE and the National Nuclear Security Administration (NNSA), other customers, and stakeholders. While fiscal year (FY) 2020 presented unprecedented challenges due to the COVID-19 global pandemic, the SRNL research team continued to advance science and further technology through the support of the LDRD program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗