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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Power Grid Behavioral Patterns and Risks of Generalization in Applied Machine Learning

Recent years have seen a rich literature of data-driven approaches designed for power grid applications. However, insufficient consideration of domain knowledge can impose a high risk to the practicality of the methods. Specifically, ignoring the grid-specific spatiotemporal patterns (in load, generation, and topology, etc.) can lead to outputting infeasible, unrealizable, or completely meaningless predictions on new inputs. To address this concern, this paper investigates real-world operational data to provide insights into power grid behavioral patterns, including the time-varying topology, load, and generation, as well as the spatial differences (in peak hours, diverse styles) between individual loads and generations. Then based on these observations, we evaluate the generalization risks in some existing ML works caused by ignoring these grid-specific patterns in model design and training.

Li, Shimiao↗
DOE OSTI2025

Application of Cyber-Informed Engineering for Protecting BESS

This white paper synthesizes an array of crucial grid services provided by BESS technology, assesses its architecture and communications, and presents a case study for analysis against the principles introduced by Cyber-Informed Engineering (CIE). Furthermore, in walking through the analysis, this paper presents a framework to evaluate risks and solutions when considering BESS components. Asset owners and buyers could perform this analysis to assess their BESS product implementations, alternative inverter-based resources (IBR), and energy management systems (EMS). Battery systems fulfill various roles contingent on the unique market demands and the specific challenges presented by regional grid infrastructures. These roles also vary due to the differing utility models for ownership and operation, which are adapted to meet regional and local capabilities and requirements. Concerns have been raised regarding the potential for adversaries to exploit knowledge of battery operational patterns to orchestrate decisive attacks. However, the security of operational data for these systems may not be the primary vulnerability, as much of this information is already well-understood within the community. Applying a modest degree of subject matter expertise can often yield valuable predictions regarding how a battery will respond under certain conditions, such as grid emergencies, high or low-temperature days, Public Safety Power Shutoff (PSPS) events, and outages. The operational characteristics of batteries are well-documented, and their capabilities, including the risks associated with misoperation and the resulting consequences, are published and understood within the industry. CIE practices represent the next step in gaining functional assurance and providing an acceptable level of risk, regardless of whether a battery vendor can support a trusted and validated supply chain. While this issue has exacerbated supply chain challenges, it is not an isolated condition. This foreign supply route is the primary source of BESS for the U.S. market. Significant efforts are underway through the Bipartisan Infrastructure Law (BIL) to change that. Still, strategic short-term operational mitigations are needed to ensure the security of our operational technology (OT) systems, which are enhanced by instilling trust and are separate from vendors implementing CIE principles.

25 ENERGY STORAGE↗
DOE OSTI2021

Validation and Verification for INL Modelica-based TEDS models Via Experimental Results

This report provides an overview on the verification and validation (V&V) of the Thermal Energy Distribution System (TEDS) model developed in the Modelica process modeling ecosystem using experimental data. Model development has led to the creation of a dynamic process model of the experimental TEDS facility housed within the Energy Systems Laboratory (ESL) at Idaho National Laboratory (INL). The model was then used during the preconstruction phase of the experimental effort to inform experimental design (e.g., insulation requirements, bypass line placement, expected performance of components) and to test innovative control schemes prior to the initial operation. The TEDS model developed in Modelica includes the primary components of the TEDS experimental unit: a 200kW Chromalox heater; a single-tank packed-bed thermal energy storage system filled with 0.125-inch alumina (Al2O3) beads; an ethylene-glycol-to-Therminol-66 heat exchanger; system piping; five control valves; and all associated temperature, pressure, and volumetric flow sensors. Using the Institute of Electrical and Electronics Engineers (IEEE) V&V methodologies, considered the gold standard in the engineering field, the model was verified using a combination of static analysis, spatial convergence, and regression tests. Then using dynamic time warping (DTW) initial runs to validate and tune the TEDS model versus the experiment were conducted. This tuning method was accomplished using the INL Risk Analysis Virtual ENvironment (RAVEN) software package. Tuning is required to account for physical phenomena that are less understood within the empirical heat transfer correlations. Through the commencement of this work, a systems-level model of TEDS with associated control systems, sensors, piping diameters, and component capabilities has been created. This model was utilized in the pre-experimental phase to inform system design, insulation thicknesses, and potential control schemes to operate the system effectively and safely. Then, initial experimental startup and operational data were used to demonstrate the validation and tuning methodology. This process demonstrates the classical two-step approach of a model informing experimental design followed by the experiment validation and tuning the model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Status of the OECD/NEA Watts Bar unit 1 benchmark and calculations of local reactor core power data of the Zero Power physics tests

The paper aims to provide an update on the status of the Organization for Economic Cooperation and Development (OECD) / the Nuclear Energy Agency (NEA) Tennessee Valley Authority (TVA) Watts Bar 1 (WB1) Multi-Physics Multi-Cycle depletion benchmark and the results associated with Exercise 1. The benchmark relies on the set of benchmark progression problems developed by the Department of Energy (DOE) Consortium for the Advanced Simulation of Light Water Reactors (CASL) for the Virtual Environment for Reactor (VERA), which are based on real plant design and operational data. The OECD/NEA TVA WB1 benchmark is designed for validation of both traditional and novel high-fidelity multi-physics codes to analyze Pressurized Water Reactors (PWR) depletion cycles. The activities are conducted under the Expert Group on Reactor Systems Multi-Physics (EGMUP) at NEA/OECD. In this work, we analyze Exercise 1 of the benchmark: stand-alone Three-Dimensional (3D) neutronics at Start-up Zero Power Physics Test (ZPPT) at Hot Zero Power Conditions (HZP) and the resulting power maps. The code used to model the exercise is the continuous energy Monte Carlo code Serpent 2.1.31 along with the nuclear data library ENDF/B-VII.1. Serpent results are compared with the high-fidelity deterministic code MPACT, which is part of VERA. The paper presents three selected results from power calculations required output. The results compared are the normalized axially integrated radial core power maps, the normalized axial averaged core power shapes, and the normalized core hottest and coldest assemblies radial power maps. The Root Mean Square Deviation (RMSD) between Serpent and MPACT is 0.51 % for the axially integrated radial core power map, 1.41 % for the axial averaged core power shape, 2.42 % for the hottest assembly axial power shape, 0.88 % for the coldest assembly axial integrated hottest assembly radial pin power map, and 0.17 % for the axially integrated coldest assembly radial pin power map. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Human reliability analysis studies from simulator experiments using Bayesian inference

Probabilistic Safety Assessment (PSA) of complex facilities is performed to arrive at the risk posed by them. PSA also accounts for the contribution of the human errors towards the overall risk through Human Reliability Analysis (HRA) in terms of Human Error Probability (HEP). Human operators are part of the system and do not work in isolation. Their performance is influenced by the context in which the actions are performed. As a result, quantification of HEP requires operator performance data under the given context. Some good sources of operator performance data are plant‘s operation data, simulator data and expert judgement. The plant operation data pertaining to HRA is generally sparse. In this situation, a full scope plant simulator provides a good alternative for operator performance data generation. Many of the currently practiced HRA methods have been developed by combining the empirical evidence with expert judgement and contain a lot of uncertainty in their estimates. Bayesian inference is suitable for updating the prior HRA estimates with the simulator evidence to obtain the posterior HEP. Here, posterior HEP has been calculated for postulated accident scenarios in advanced reactor (first of its kind) at design stage, using plant simulator.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data Center Waste Heat as an Emerging Urban Thermal Hazard: First Field Measurements of Neighborhood-Scale Air Temperature Impacts

Data centers are among the fastest-growing sources of concentrated anthropogenic heat in urban environments. Despite heat flux densities that exceed peak solar irradiance by a factor of 2–6, their thermal impacts on adjacent communities have never been directly measured or reported in the peer-reviewed literature. This short communication addresses that gap by presenting the first vehicle-based traverse measurements of air temperature in residential neighborhoods downwind of operational data centers. Five traverses at four facilities in the Phoenix, Arizona metropolitan area, ranging from a 36 MW single-building data center in Mesa to a 169 MW colocation campus in Chandler, reveal downwind air temperature warming as high as 2.2 °C, with average downwind air temperatures 0.7–0.9 °C warmer than corresponding upwind areas. Thermal signatures were detectable at distances up to 500 m from facility perimeters. The 36 MW Mesa facility rejects waste heat equivalent to the electricity consumption of approximately 40,000 households, while the 169 MW Chandler campus is equivalent to over 180,000 households, both concentrated into footprints smaller than a single residential subdivision. With U.S. data center capacity projected to more than double by 2030, these findings establish data center anthropogenic waste heat as a previously undocumented urban thermal hazard demanding attention from the data center and urban planning communities.

Phoenix↗
DOE OSTI2022

Scalable Predictive And Risk Technologies

The research involves developing scalable technologies for risk-informed predictive analytics to achieve condition-based monitoring and maintenance strategies to reduce overall maintenance costs. The research utilizes data (real-time data, periodic data, and institutional knowledge) related to a particular plant asset from a specific nuclear plant site to develop technologies to scale risk-informed predictive analytic algorithms across different plant assets at the plant site and across the nuclear fleet. The developed algorithms and codes are used to optimize the maintenance strategy and estimate/forecast generation costs based on the state of health of the plant asset. Developed codes specifically include 1. Parameter estimation using plant operation data 2. Federated and Transfer learning model 3. Feature group based Multi-kernel SVM 4. Three state markov model

Manjunatha, KoushikAraseethota↗
DOE OSTI2020

Secondary-Source Core Reload Modeling with VERA

The CASL reactor simulation package VERA has been adapted to provide high-fidelity simulation capabilities for modeling source range detector response during subcritical reactor configurations. New features include the activation and shuffling of secondary-source assemblies, use of burned fuel neutron emission data from the ORIGEN depletion solver to the MPACT deterministic neutron transport solver, allowance of user-defined sources in MPACT based on material composition, ability to solve the subcritical source-driven system with neutron multiplication using the MPACT diffusion solver, and transfer of the calculated fission source from MPACT to the continuous-energy Monte Carlo solver Shift for final detector response evaluation using the CADIS methodology for variance reduction. These new capabilities were benchmarked against Watts Bar Unit 1 plant operating data for the first few fuel loading steps and were found to demonstrate excellent agreement with the measured data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Control Strategies and Validation in the Hybrid Optimization and Performance Platform (HOPP)

The Hybrid Optimization and Performance Platform (HOPP) is a tool that simulates hybrid power plants in various configurations, and also calculates the financial feasibility of these plants. This report outlines an overview of HOPP and the energy storage dispatch strategies available. It then presents three case studies which demonstrate different applications of HOPP. The first case looks at the profitability of hybrid power plants in different locations in the USA. The second case examines the availability of hybrid power plants to provide energy reliability services. The third case presents a plant that produces both hydrogen and electricity, and demonstrates a dispatch strategy that chooses the most profitable energy vector based on price signals. The next section shows the validation of HOPP on operational data, using data from both unit-scale and utility-scale power plants. This validation process demonstrated that HOPP can simulate the power output of both wind and solar PV plants at both scales with comparable fidelity to an existing commercial software tool. Finally, HOPP is applied in a field test which applies an optimal dispatch strategy to a physical battery in a unit-scale hybrid plant at NREL. HOPP's optimal dispatch strategy, applied in a real-world setting, improved this hybrid plant's ability to meet a load signal while minimizing operational costs.

14 SOLAR ENERGY↗
DOE OSTI2021

Detector Instrumentation, Energy Reconstruction and Data Analysis in the DUNE and NOvA Neutrino Experiments

Neutrino oscillations are so far the only experimental observation beyond the standard model since its development four decades ago. The remaining fundamental questions that can be answered by long-baseline neutrino oscillations are (1) the CP violation (whether neutrinos and antineutrinos behave the same way in oscillation), and (2) the mass hierarchy ($m_3>m_{1,2}$ or $m_{1,2}>m_3$), and (3) the octant of $\theta_{23}$ ($\theta_{23}>45^\circ, =45^\circ$ or $<45^\circ$). The PI's group at UCI focuses on long-baseline neutrino experiments DUNE and NOvA, key components of DOE's Intensity Frontier program. NOvA is the current major U.S.-based long-baseline neutrino experiment aiming to solve the mass hierarchy and $\theta_{23}$ octant. It is taking $\nu$ and $\bar{\nu}$ data from the NuMI beam at Fermilab. DUNE is the next-generation flagship neutrino experiment in the U.S. which is designed to decisively determine neutrino CP violation, mass hierarchy and $\theta_{23}$ octant. DUNE is Fermilab's first priority, and has been established as an international collaboration. During the period covered by the report, the PI's group has been exceptionally productive, with leading contributions to DUNE argon-purity monitoring detectors, NOvA/DUNE deep-learning reconstruction, and NOvA oscillation and near detector (ND) analyses. The group also is actively involved in DUNE/NOvA detector operation, data production, calibration, software upgrade and maintenance, and ProtoDUNE cold electronic QA/QC. Specifically, we have made accomplishments in the following four research projects: 1) Purity monitor R\&D and data analysis for DUNE, 2) Deep-learning-based energy reconstruction at NOvA and DUNE, 3) Oscillation analysis at NOvA, and 4) $\nu$-e elastic scattering analysis at NOvA.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Digital Twin-Enabled Adaptive Control for Hydroelectric Systems: Turbine Governor and Voltage Regulation

This paper presents a comprehensive digital twin (DT) framework for hydroelectric systems that enables adaptive control of turbine governors and excitation systems without requiring detailed manufacturer specifications. The proposed framework integrates neural network-based system identification with stabilizing adaptive control laws for the installed turbine controller and middle-branch adaptive tuning for the installed voltage regulator. Using real operational data from Unit C-8 at Rocky Reach Dam (1,349 MW capacity), highfidelity neural network models are developed to capture turbine and generator dynamics without requiring detailed manufacturer specifications. The DT enables safe controller synthesis and validation in simulation before deployment. For turbine control, the proposed method achieves a 79.9% mean square error (MSE) reduction compared with that of an optimal controller. For voltage regulation, the adaptive excitation controller achieves approximately 42.6% MSE reduction while preserving installed protection logic. The results demonstrate that DT technology provides a practical pathway for modernizing hydropower control systems with minimal operational disruption.

Gui, Yonghao [ORNL] (ORCID:0000000250435534)↗
DOE OSTI2026

REFSafE: A RAG-Enabled Framework for Predictive Risk Analysis and Automated Safety Report Generation in Mission-Critical Environments

Operational safety in mission-critical environments requires AI systems that are accurate, interpretable, and resistant to hallucination. We present an agentic Retrieval-Augmented Generation (RAG) framework, REFSafe, for grounded hazard analysis and automated safety report generation. The system integrates Large Language Models (LLMs) with structured operational data, historical incident repositories, policy documents, and external authoritative sources. Through iterative agentic reasoning, the framework retrieves, verifies, and synthesizes evidence prior to generation, enforcing citation-backed outputs with explicit source attribution (documents, links, and prior events) to ensure traceability and trust. To mitigate hallucinations and unsupported claims, all risk assessments and forecasts are constrained to retrieved evidence, with confidence signals derived from retrieval relevance and source consistency. A transparent pipeline enables subject matter experts (SMEs) to validate predictions, and provide structured feedback, forming a continuous performance calibration loop. Preliminary deployment demonstrates improved reliability in hazard detection and safety/vulnerability report generation. This work advances trustworthy, evidence-grounded AI for predictive safety intelligence in mission-critical operations.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
DOE OSTI2026

Admissible Powertrain Alternatives for Heavy-Duty Fleets: A Case Study on Resiliency and Efficiency

Heavy-duty vehicles dominate global freight movement and primarily rely on fossil-derived diesel fuel. However, fluctuations in crude oil prices and evolving emissions regulations have prompted interest in alternative powertrains to enhance fleet energy resiliency. This study paired real-world operational data from a large commercial fleet with high-fidelity vehicle models to evaluate the potential for replacing diesel internal combustion engine (ICE) trucks with alternative powertrain architectures. The baseline vehicle for this analysis is a diesel-powered ICE truck. Alternatives include ICE trucks fueled by bio- and renewable diesel, compressed natural gas (CNG) or hydrogen (H 2 ), as well as plug-in hybrid (PHEV), fuel cell electric (FCEV), and battery electric vehicles (BEV). While most alternative powertrains resulted in some payload capacity loss, the overall fleetwide impact was negligible due to underutilized payload capacity for the specific fleet considered in this study. For sleeper cab trucks, CNG-powered trucks achieved the highest replacement potential, covering 85% of the fleet. In contrast, H 2 and BEV architectures could replace fewer than 10% and 1% of trucks, respectively. Day cab trucks, with shorter daily routes, showed higher replacement potential: 98% for CNG, 78% for H 2 , and 34% for BEVs. However, achieving full fleet replacement would still require significant operational changes such as route reassignment and enroute refueling, along with considerable improvements to onboard energy storage capacity. Additionally, the higher total cost of ownership (TCO) for alternative powertrains remains a key challenge. This study also evaluated lifecycle impacts across various fuel sources, both fossil and bio-derived. Bio-derived synthetic diesel fuels emerged as a practical option for diesel displacement without disrupting operations. Conversely, H 2 and electrified powertrains provide limited lifecycle impacts under the current energy scenario. This analysis highlights the complexity of replacing diesel ICE trucks with admissible alternatives while balancing fleet resiliency, operational demands, and emissions goals. These results reflect a US-based fleet’s duty cycles, payloads, GVWR allowances, and an assumption of depot-only refueling/recharging. Applicability to other fleets and regions may differ based on differing routing practices or technical features such as battery swapping.

BEV↗
DOE OSTI2024

Building ControlScore: General Service Administration Office Building Deployment

Improvements to building control systems can lead to energy savings and increased occupant comfort. In an optimized system, process variables such as air temperature will closely follow their desired setpoints and avoid excess energy use. Typically, experts must manually inspect individual control loops to identify poor performance and opportunities for improvement. However, this approach is difficult in modern buildings that have a prohibitively large number of controllers. To address this issue, Pacific Northwest National Laboratory (PNNL) created the ControlScore concept, which takes operating data from the many controllers within a building and generates standardized scores for each loop on a scale of 0 to 10 (a score of 0 indicates poor control, a score of 10 indicates good control). PNNL applied the Building ControlScore application to all available data from a General Services Administration office building within the period of January 1, 2023, to March 9, 2023. The building scored a 4.7 overall, with all 74 of the building’s loops fitting a roughly normal distribution centered around 5. These results indicate that the analyzed systems have below-average performance with room for improvement, especially in the poorly scored systems. Airflow loops tended to have much lower scores than zone temperature loops. The lowest and highest performing systems in the building section were identified, as were all loops with a score less than 1. While the ControlScore identifies loops and systems that aren’t meeting their designated setpoints, it does not indicate the cause of those issues. For example, consider a supply air terminal unit’s airflow loop that received a low score due to it delivering less air than specified by the setpoint. The lower-than-desired airflow could be due to equipment limitations (e.g., the terminal unit or duct serving is too small to accommodate that airflow), malfunctioning equipment (e.g., a stuck damper or bad sensor), or something else entirely. The ControlScore does not diagnose problems it simply identifies the symptoms that can be explored and addressed by building operators.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

North Dakota Integrated Carbon Storage Complex Feasibility Study. Final report

In spring 2017, the Energy & Environmental Research Center (EERC) initiated an effort to determine the feasibility of developing a commercial-scale CO 2 geologic storage complex able to store 50+ million tonnes (Mt) of CO 2 in central North Dakota safely, permanently, and economically. The objective was to fulfill the goals of the U.S. Department of Energy (DOE) Carbon Storage Assurance Facility Enterprise (CarbonSAFE) Initiative and address technical and nontechnical challenges specific to commercial-scale deployment of a CO2 storage project. The findings clearly show that the concept of capturing CO 2 from a lignite-fired electrical generation facility in central North Dakota and safely and permanently storing the CO 2 in the deep subsurface is indeed technically, economically, and socially feasible. This project evaluated two study areas and their respective geologic storage complexes located adjacent to separate coal-fired facilities in North Dakota: the Basin Electric Power Cooperative (BEPC)-owned Great Plains Synfuels Plant (GPSP) and the Minnkota Power Cooperative (Minnkota)-owned Milton R. Young Station (MRYS). These locations, one with CO 2 capture in place and an existing CO 2 pipeline, are bolstered by progressive North Dakota pore space ownership and long-term liability laws. These elements and a motivated team created an ideal synergistic scenario for ensuring success of the CarbonSAFE Initiative and promoting North Dakota’s statewide vision for carbon management. The project included drilling two new geologic characterization wells, integrating an existing 3-D seismic survey, creating a geologic model subsequently used for injection simulation, a risk assessment, public outreach, and generating a site development plan based on results. In addition, the performance of select National Risk Assessment Partnership tools was evaluated. The geologic characterization wells were drilled ~5600 feet deep to the Broom Creek Formation; ~350 feet of core was retrieved from each well. The core included the Broom Creek (targeted injection zone) and a portion of the overlying Opeche Shale (seal). The Flemmer-1 well, west of Beulah, North Dakota, yielded 169 feet of sandstone. The BNI-1 well located south of Center, North Dakota, yielded 124 feet of sandstone. In each case, laboratory analysis of the sandstone showed permeability in the 300–1000-mD range, with porosity of 20%–30%. The Flemmer-1 well was sited within the boundaries of an existing 3-D seismic survey. Colocating the well with the seismic survey maximized the relationship between new and legacy data and developed a first-of-its-kind interpretation of the geologic fabric of the Broom Creek. Geologic characterization data were integrated into a 5544-mi 2 geocellular model that encompassed both new wells and stratigraphy from the surface to the Amsden Formation (underlying the Broom Creek). The model was later expanded vertically to include the deeper Black Island–Deadwood interval to examine its potential viability as a storage target. The geocellular model provided the foundation for dynamic simulation of CO 2 into the Broom Creek. Results of the simulation suggest that the Broom Creek could accept the DOE target rate of 2 Mt/yr of CO 2 into as few as two wells. To bracket the expected capture from MRYS, simulations were also investigated for a 4-Mt/yr rate near MRYS. Although more wells are needed (two additional), the Broom Creek still has the storage resource to accept the CO 2 at the increased rate. A risk assessment exercise was conducted to identify and assess technical and nontechnical risks that could prevent potential candidate storage complexes within the study area from serving as commercial storage sites. The assessment identified and evaluated six technical risk categories: 1) CO 2 injectivity, 2) storage capacity, 3) lateral migration of CO 2 , 4) lateral pressure propagation, 5) vertical migration of CO 2 or formation brine, and 6) induced seismicity. Following two rounds of analysis and scoring, no risks were determined to preclude continued efforts to develop carbon capture, utilization, and storage (CCUS) in central North Dakota. The risk assessment results will be used to guide future site characterization, modeling and simulation, and monitoring activities. A specific nontechnical strategic risk based on challenges that may be realized in amalgamation of pore space resulted in vertically expanding the geologic model to incorporate the potential for stacked storage in multiple saline reservoirs. By including the Black Island–Deadwood interval (the basal sedimentary reservoir in this region), the amalgamated areal extent could be reduced by as much as 45%. Working with a smaller geographic area reduces risks and costs associated with monitoring and pore space leasing. An economic evaluation incorporating capture; transport (<5 mi); Class VI wells; permitting; and monitoring, verification, and accounting suggests implementing commercial-scale CCUS is economically attractive if the federal tax benefits of 45Q are included. This is validated by Minnkota’s continued pursuit of CO 2 capture and geologic storage at MRYS through its Project Tundra initiative, indicating that there is a business case for CCUS in central North Dakota. Currently, North Dakota is the only state with underground injection control (UIC) Class VI primacy. Built into the North Dakota Century Code is a series of regulatory requirements that guide the process to obtain a Class VI CO 2 storage facility permit. As part of this project, a site development plan was compiled to assure compliance with North Dakota’s requirements to permit a commercial-scale CO 2 storage operation and includes a prospective time line encompassing a general breakdown of activities. In total, an estimated 30 months would be needed to execute the necessary steps to attain a North Dakota CO 2 storage facility permit. Outreach was an integral part of the project and encompassed any project-related activity that had contact or exposure beyond the project team. The goals of outreach were to foster an environment from which stakeholders could make informed decisions about the project and gauge community receptiveness to a CCUS project. A consistent set of messages and outreach products were developed in conjunction with an outreach advisory board that integrated project partners and team members. To gauge public acceptability of geologically storing CO 2 , 5611 households in the project area were invited to participate in an online survey. The survey results indicate that the public attitude regarding CCUS is neutral to positive, with strong sentiment that CO 2 capture and storage may be an approach to maintain the economic vitality of the region. To achieve project objectives, critical support in the form of financial backing, engineering evaluations, site access, outreach collaboration, operations data, risk assessment/evaluation, and software access was provided by BEPC, the North Dakota Industrial Commission Lignite Research Council, ALLETE Clean Energy, BNI Energy, North American Coal Corporation, Minnkota, Prairie Public Broadcasting, Computer Modelling Group Ltd., and Schlumberger.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Bootstrapping boundaries and branes

The study of conformal boundary conditions for two-dimensional conformal field theories (CFTs) has a long history, ranging from the description of impurities in one-dimensional quantum chains to the formulation of D-branes in string theory. Nevertheless, the landscape of conformal boundaries is largely unknown, including in rational CFTs, where the local operator data is completely determined. We initiate a systematic bootstrap study of conformal boundaries in 2d CFTs by investigating the bootstrap equation that arises from the open-closed consistency condition of the annulus partition function with identical boundaries. We find that this deceivingly simple bootstrap equation, when combined with unitarity, leads to surprisingly strong constraints on admissible boundary states. In particular, we derive universal bounds on the tension (boundary entropy) of stable boundary conditions, which provide a rigorous diagnostic for potential D-brane decays. We also find unique solutions to the bootstrap problem of stable branes in a number of rational CFTs. Along the way, we observe a curious connection between the annulus bootstrap and the sphere packing problem, which is a natural extension of previous work on the modular bootstrap. We also derive bounds on the boundary entropy at large central charge. These potentially have implications for end-of-the-world branes in pure gravity on AdS 3 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗