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At least 289 records · Page 16

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DOE OSTI2025

Automating Anomaly Detection for Target systems at Spallation Neutron Source

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory, produces the world’s most intense pulse neutrons beams. An accelerated proton beam is directed into a mercury target to generate neutrons via spallation. The target system accounted for over 40% of the overall downtime of the facility in 2022. Thus, early detection in anomalies in the target systems can enable taking corrective actions to avoid failures and reduce downtime. Fault prognostics and anomaly detection in accelerators, both at SNS and outside, has largely focused on the beam side. This paper presents one the first studies exploring leveraging machine learning to automate the detection of anomalies in the target system. The target system consists of over 30 different interconnected subsystems, and the present work focuses on the mercury process system as a use case. Analyzing data from 28 process variables from 2022 and 2023, tree-based and reconstruction-based algorithms are employed to detect anomalies in archived data. The algorithms detected previously unreported anomalies, several of which were deemed alert worthy by human experts, particularly those found by reconstruction-based algorithms. Using data from each production run in the accelerator increased the generalizability of the models in time. Efforts are now underway to implement a workflow for incorporating human feedback to update the models and evaluating performance on unseen data. The models will eventually be integrated into the existing System Tracking and Reliability system with a web interface for automated anomaly detection and reporting along with a pathway for incorporating human feedback for model updates.

Raj, Anant [ORNL] (ORCID:0000000306711244)↗

DOE OSTI2025

Synergistic heat pumped thermal storage and flexible carbon capture system

A power plant system is disclosed. The power plant system includes a combustor configured, a turbine configured to generate electricity, a heat exchanger and a steam turbine, a carbon capture system configured to remove at least a portion of carbon-based gasses from the flue gas downstream from the heat recovery steam generator, and a thermal storage system including a hot storage unit configured to store thermal energy at a hot temperature, the hot temperature greater than ambient temperature. The power plant is configured to operate in at least a first mode for storing thermal energy in the thermal storage system and a second mode for releasing the stored thermal energy from the thermal storage system and during the second mode, heat stored in the hot storage unit is transferred to the carbon capture system.

Bandhauer, Todd M.↗

DOE OSTI2025

Implementation and Demonstration of the Digital Twin Certification System Remote Operations Framework

Microreactors are one promising advanced-reactor concept being pursued by the nuclear industry. They are distinguished by a relatively low power output of 20 MWth or less. These microreactors are intended for deployment in applications where conventional small-capacity power solutions, such as diesel generators, are either economically unfeasible or logistically challenging. Such applications include providing electric power and/or heat for remote communities, mining sites, defense installations, and humanitarian and disaster-relief missions. An important feature for the successful deployment of microreactors is their capability to be operated remotely. This capability can significantly reduce staffing costs by eliminating the need for licensed operators to be physically present at each reactor site. Instead, operators can be centralized in a single remote operations center placed in an economically advantageous location, thereby optimizing resources by consolidating expertise and enhancing operational efficiency. However, the implementation of a remote operation system for nuclear reactors raises new concerns regarding the security, reliability, and resilience of such a system. One way in which remote operations can be supported in a manner that maintains system security, reliability, and resilience is through the use of digital twins in a novel framework designed to verify and validate sensor data and commands communicated between the remote operations center and reactor. This framework, known as the Digital Twin Certification System (DTCS), has previously been proposed as an operations architecture that can bring security and resiliency levels of remote nuclear-reactor operations to a level acceptable for commercial deployment. This paper moves the proposed DTCS architecture from concept to reality by presenting the implementation and testing of the system. The rationale and implementation of the DTCS using tools such as DeepLynx and Apache Airflow, is covered in-depth. This is followed by a demonstration of the DTCS by applying the implemented system architecture to the Single Primary Heat Extraction and Removal Emulator, a small-scale non-nuclear test bed that emulates thermal behavior of a microreactor. The demonstration includes both normal and abnormal operating scenarios to highlight how the DTCS can increase the security, reliability, and resilience of a remote operations system.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Implementation and Demonstration of the Digital Twin Certification System Remote Operations Framework

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Control System Upgrade for Battery State-of-Charge Indications

The Advanced Test Reactor (ATR) Complex at Idaho National Laboratory (INL) relies on Battery Backed Power (BBP) systems and Uninterruptible Power Supplies (UPS) to ensure continuous power supply to critical components. This project aims to enhance the reliability and functionality of the battery monitoring and control systems by updating the State-of-Charge (SOC) system, Programmable Logic Controller (PLC), and Human-Machine Interface (HMI) for the nuclear safety-related battery banks. The current system, while functional, has areas for improvement, particularly in recharging calculations and alarm functions. The project objectives include developing flow charts, programming the new PLC and HMI, conducting bench tests, and updating design documentation. Additionally, the project ensures compliance with safety standards, develops training materials, creates comprehensive documentation, and integrates seamlessly with existing ATR infrastructure. The new SOC system is designed to be scalable for future upgrades, improve efficiency, enhance data accuracy, implement redundancy features, and achieve project goals within budget constraints while considering environmental impact. The methodology involved familiarizing with BBP and UPS systems, collecting current readings, rescaling signals, learning ladder logic, and updating the HMI. The transition from SLC 5/03 PLC using RS Logix 500 to CompactLogix 5380 using Studio 5000 was a key step. Despite challenges in transferring outdated PLC ladder logic and HMI code, starting from scratch led to a more accurate and efficient monitoring system, contributing to improved safety and operational efficiency. The project is currently awaiting approval of the Engineering Calculation and Analysis Report (ECAR) before implementation.

42 - ENGINEERING↗

DOE OSTI2025

Spent Nuclear Fuel Receipt Rate Analysis within an Integrated Waste Manage-ment System Architecture that Includes Consolidated Interim Storage

A key parameter in analyzing the performance of an integrated waste management system (IWMS) architecture for the disposition of spent nuclear fuel (SNF) is the SNF receipt rate from reactor and other custodian sites. The introduction of one or more federal consolidated interim storage facilities (CISFs) into the IWMS architecture can enable the receipt rate profile as a function of time to be accelerated relative to system architectures without a CISF. The question then arises as to what an optimal SNF receipt rate profile for an IWMS architecture might be in view of practical constraints and desired system performance attributes and associated metrics. This paper describes a sensitivity study on SNF receipt rates and the associated results for a selected set of IWMS scenarios aimed an in-forming near-term planning for interim storage capabilities and transportation assets. Two different strategies are compared, one that fills an initial CISF quickly and then idles the transportation system while a disposal system is prepared, and a second strategy that aims to provide a more continuous use of transportation assets and receipt capabilities at the IWMS while the disposal system is readied for SNF receipt. Cost considerations and other factors such as impact on timing of clearing reactor sites of SNF, efficient use of capital assets, and other metrics, including those which may be important to a CISF host community, are examined. Based on the analysis, an initial approach is presented targeting a continuous receipt strategy while having the flexibility to step up receipt capabilities to a reasonable degree when needed and beneficial within overall system constraints.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Post-Event Fault Identification with Machine Learning for Protection System Validation

Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by accidental improper relay settings or deliberate malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that their performance falls within expectations. Relays that fail to isolate a fault or trip when there is no system disturbance can be flagged for settings review in situations where this behavior may not have been noticed due to manual restoration or backup protection operations. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by identifying fault events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

DEVELOPMENT OF AN INTEGRATED SECURITY AND SAFETY MONITORING SYSTEM FOR SPENT NUCLEAR FUEL AND HIGH-LEVEL WASTE TRANSPORTATION

This paper provides an overview of the progress to date, and discussion of the path forward, related to designing, fabricating, and testing an integrated security and safety monitoring system (ISSMS) for railcars used to transport spent nuclear fuel (SNF) and high-level radioactive waste (HLW) in the United States. The system will comply with the US Department of Energy’s (DOE) Order 460.2B “Departmental Materials Transportation Management” and the Association of American Railroads’ (AAR) standard S-2043 “Performance Specification for Trains Used to Carry High-level Radioactive Material” [1] developed specifically for railcars used to transport high-level radioactive material (HLRM). DOE is in the process of developing and testing an ISSMS that will satisfy both DOE requirements and AAR standards. DOE has already developed railcar designs for transportation of HLRM. In 2024, DOE’s Atlas railcar project completed the design, fabrication and testing of three railcar types: transportation cask-carrying, buffer, and security escort, resulting in AAR conditional approval to operate on freight rail networks in North America. DOE decided to combine the required security and safety systems into one system, and this combined system is the subject of the current effort. DOE is developing and proposes to implement the ISSMS for these railcars as part of the build out of the railcar fleet. DOE began planning for development of the ISSMS in February 2020. The project is divided into seven phases starting with conceptual design and continuing through production design, as shown in Figure 1. An earlier version of the system was tested as part of the Atlas railcar consist demonstration test run in 2023. This paper describes the design features and system testing using the Atlas project railcars, and laboratory testing completed to date. The paper will also describe the activities planned to support the DOE project to ship the High Burn-Up Research Cask (HBRC) in 2027.

Schultze, Michael [ORNL] (ORCID:0000000283205671)↗

DOE OSTI2025

Recommendations for Comprehensive and Independent Evaluation of Machine Learning‐Based Earth System Models

Abstract Machine learning (ML) is a revolutionary technology with demonstrable applications across multiple disciplines. Within the Earth science community, ML has been most visible for weather forecasting, producing forecasts that rival modern physics‐based models. Given the importance of deepening our understanding and improving predictions of the Earth system on all time scales, efforts are now underway to develop Earth‐system models (ESMs) capable of representing all components of the coupled Earth system (or their aggregated behavior) and their response to external changes over long timescales. Building trust in ESMs is a much more difficult problem than for weather forecast models, not least because the model must represent the alternate (e.g., future or paleoclimatic) coupled states of the system for which there are no direct observations. Given that the physical principles that enable predictions about the response of the Earth system are often not explicitly coded in these ML‐based models, demonstrating the credibility of ML‐based ESMs thus requires us to build evidence of their consistency with the physical system. To this end, this paper puts forward five recommendations to enhance comprehensive, standardized, and independent evaluation of ML‐based ESMs to strengthen their credibility and promote their wider use.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Consensus-Based Control and Optimization of Power System Inertia

The integration of distributed energy resources (DERs), such as solar, wind, and energy storage systems, into power grids through inverter-based resources reduces power system inertia, leading to faster frequency dynamics and potential grid instability. To address this challenge, this paper proposes a distributed, consensus-based approach for the real-time control and optimization of inertia sources (synchronous generators and/or DERs) during system disturbances, enhancing both system stability and economic performance. The distributed control and optimization approach assumes each inertia source exchanges information solely with its neighbor ones, making it easily scalable to large power grid networks. The impacts of the communication connectivity among the inertia sources as well as their generation capacity limits on the distributed approach are investigated. We also demonstrate the approach’s robustness in scenarios involving communication time delays and packet losses, validating its effectiveness through numerical simulations on a 4-bus test system and a two-area 8-bus test system.

Power system inertia↗

DOE OSTI2026

Safe Deep Reinforcement Learning for Active Distribution System Model Predictive Control with EVs and DERs

The temporal and spatial mismatch between PV generation and electric vehicle (EV) charging and discharging may cause voltage violations in active distribution networks. Despite the widespread use of deep reinforcement learning (DRL) in power system optimization and control, it lacks guarantees on constraint satisfaction during both training and deployment. This paper proposes a Lagrangian-based safe DRL approach for model predictive control (MPC) of active distribution systems with large-scale integration of PVs, EVs, and energy storage systems (ESSs). A Transformer-LSTM time-series model is proposed to forecast EV charging demand, which is then formulated as a constraint to ensure charging requirements are met. Using this prediction, a Lagrangian-based safe soft actor-critic (SAC) framework is developed for real-time control in a three-phase unbalanced distribution system, enforcing voltage safety constraints while optimizing the cumulative net reward. By integrating the forecasting model with multi-period constraints, the proposed framework jointly coordinates PV systems, EV charging and discharging, and ESS scheduling within the MPC horizon. Numerical experiments on a modified IEEE 123-bus system with real-world data show that, under a high PV penetration scenario, the proposed method increases the net reward by 30.74% and reduces average voltage violations from 0.0011 p.u. to 0.0002 p.u. compared with standard SAC. Compared with the optimal power flow (OPF) approach, it achieves similar voltage security while yielding lower line losses. It also maintains real-time control capability, reducing operation latency to 53.21 ms per 15-minute control interval. The proposed method remains effective under varying PV/EV penetrations and load conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Misalignment Tolerant Three-phase Wireless Fast Charging System for Electric Vehicles

This project proposes improving the technology level of the three-phase wireless charging technology developed at Oak Ridge National Laboratory (ORNL). Successful commercialization of wireless charging systems require that they meet strict safety standards for electromagnetic field emissions and interoperability with other wireless charging technology. ORNL has previously demonstrated a 50kW three-phase wireless power transfer system with 95% efficiency. This prototype system weighed less than 50% of similar high-power wireless charging system while simultaneously exhibiting better safety characteristics. Due to better material utilization, the reduction in mass is expected to translate into similar cost reduction for the magnetic coupler. Additionally, the smaller footprint of the system can ease vehicle integration difficulties that would be encountered using other technology. Furthermore, the three-phase design can be made to operate with existing single-phase coupler design more easily and without intentional physical misalignment which would otherwise pose safety issues.This project developed ORNL’s WPT technology to satisfy the specifications and requirements for electric vehicle (EV) charging. The result of the project will be a prototype and reference design for a high-power wireless charging system—including magnetics, power electronics, and controls—serving as a baseline for product development.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Integrated Steady-State System Package for Nuclear Thermal Propulsion Analysis Using Multi-Dimensional Thermal Hydraulics and Dimensionless Turbopump Treatment

Nuclear thermal propulsion is an evolving technology that can be utilized for long-distance space travel. This technology yields the advantage of a high thrust and specific impulse, but requires an examination of the potential design adjustments necessary to enhance its feasibility. The development of nuclear thermal propulsion requires a comprehensive understanding of the system-level behavior during transient and steady-state operation. This paper extends our previous research by including the proper handling of turbomachinery with multi-channel thermal hydraulic simulations only for steady-state solutions. The system-level approach presented here enables the treatment of the turbopump components through non-dimensional analysis that eliminates the assumption of constant efficiencies. All the other components within the system (e.g., reflector and core) can be discretized to multiple channels and layers, in which the full thermal hydraulic solution is established. The approach chosen here enables the realistic modeling of the propellant flow within the expander cycle by capturing the pressure losses, mass flow rate splits, and enthalpy gain for various operational conditions. The verification of the package is completed through point comparisons of previous investigations into similar system designs. Furthermore, sensitivity studies are used to benchmark the capabilities of the package and investigate solution variations due to the perturbation of operational conditions and regimes. The sensitivity studies performed here are important to capture variation in flow characteristics (e.g., temperature, pressure, mass flow rates) for different design objectives such as the thrust and specific impulse. This work demonstrates that system-level simulations lacking multi-channel capability and proper turbomachinery treatment may yield higher uncertainties in understanding the engine’s response and characteristics to changing various requirements. This is extremely important when screening the design space of such propulsion systems and when transient simulations are required.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Understanding Line Losses and Transformer Losses in Rural Isolated Distribution Systems: Preprint

Rural, isolated power systems in the mainland U.S. and in states like Alaska and Hawaii are powered by assets like diesel generators. These rural, isolated power systems also cannot operate at the higher band of medium voltage (like 69kV). They are primarily in the 12 to 14 kV range to keep the cost of the distribution investments lower. Because of this mid-band medium voltage range, the line losses and distribution transformers losses consume significant diesel consumption (almost 10 percent of the peak load). This work considers one such power system powering an isolated system and presents key findings online losses, and transformer losses. Understanding and documenting the impacts is critical for these communities operating their power systems and take actions to reduce expensive diesel consumption. In this paper, we will present one such typical grid and model it in electromagnetic transients (EMT) domain. We used the tower structure, under ground cabling installation to develop high fidelity models of lines. We also used high fidelity models of distribution transformers to present the no-load losses and full load loses. We will also present technical solutions available commercially off-the-shelf to reduce these losses and reduce diesel consumption. This work will be a primer for communities to understand the technical challenges and to understand the possible solution available to solve such challenges for rural, isolated power system operators.

blackstart↗

DOE OSTI2024

Decarbonization of heat pump dual fuel systems using a practical model predictive control: Field demonstration in a small commercial building

In the transition from fossil fuel to electrified heating, a concerning trend is emerging in certain regions of the US. Owners of buildings with gas-based systems leave them in place after adding heat pumps (HPs). Existing control solutions for these hybrid (dual fuel) systems are rudimentary and fall short of realizing the full carbon reduction potential of these systems. Model predictive control (MPC) is often regarded as the benchmark for achieving optimal control in integrated systems. However, in the case of small-medium commercial buildings (SMCBs), the control and communication infrastructure required to facilitate the implementation of such advanced controls is often lacking. This paper presents a field implementation of easy-to-deploy MPC for a dual fuel heating system consisting of HPs and a gas-fired furnace (GF) for SMCBs. The control system is deployed on an open-source middleware platform and utilizes low-cost sensor devices to be used for real SMCBs without major retrofits. Here, we demonstrated this MPC in a real office building with 5 HPs and 1 GF for 2 months. The test results showed that MPC reduced 27% of cost while completely eliminating GF usage by shifting 23% of the thermal load from occupied-peak time to non-occupied-non-peak times.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Technical, economic, and load-following capabilities assessment of grid-connected geothermal and geothermal-solar hybrid systems

The technical and economic performance as well as the load-following capabilities of grid-connected geothermal hybrid systems were assessed in this work. The analyzed geothermal hybrid configuration is composed of a binary geothermal plant integrated with a concentrating solar-thermal system and underground thermal energy storage (UTES) through a primary heat exchanger. Physics-based models for the hybrid system for plant generation capacities of 1, 25, and 50 MW were developed from validated models for each subsystem. Also, an economic model was developed that accounts for different hybrid system capabilities, solar field sizes, and thermal storage duration. The advantage of the geothermal hybrid system was assessed by comparing the performance with the baseline benchmark geothermal plant with a similar configuration and generation capacity. It was found that hybridizing geothermal plants with concentrating solar and thermal energy storage not only improves the thermal efficiency by up to 8 percentage points when additional heat from the solar-UTES loop rises the evaporator temperatures from 70 to 125 °C, but also enhances the load-following capability for the geothermal plant, which can meet a typical residential load profile with a power rate of change 0.25 kW/s with an absolute error under 13 kW for a 1 MW plant. Other benefits of hybridization include resource preservation and a potential LCOE reduction of up to 56% for a 50 MW geothermal hybrid plant having a 50% solar share, a 1.4 solar multiple, and 24-h storage capacity. The results presented in this work demonstrate that hybridizing geothermal systems transforms them into a flexible and cost-effective solution for addressing the dynamic requirements of modern electric grids.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Data-driven reduced-order models for port-Hamiltonian systems with operator inference

Hamiltonian operator inference has been developed in Sharma et al. (2022) to learn structure-preserving reduced-order models (ROMs) for Hamiltonian systems. The method constructs a low-dimensional model using only data and knowledge of the functional form of the Hamiltonian. The resulting ROMs preserve the intrinsic structure of the system, ensuring that the mechanical and physical properties of the system are maintained. In this work, we extend this approach to port-Hamiltonian systems, which generalize Hamiltonian systems by including energy dissipation, external input, and output. Based on snapshots of the system’s state and output, together with the information about the functional form of the Hamiltonian, reduced operators are inferred through optimization and are then used to construct data-driven ROMs. To further alleviate the complexity of evaluating nonlinear terms in the ROMs, a hyper-reduction method via discrete empirical interpolation is applied. Accordingly, we derive error estimates for the ROM approximations of the state and output. Lastly, we demonstrate the structure preservation, as well as the accuracy of the proposed port-Hamiltonian operator inference framework, through numerical experiments on a linear mass–spring-damper problem and a nonlinear Toda lattice problem.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

The power reliability event simulator tool (PRESTO): A novel approach to distribution system reliability analysis and applications

The growing interest in onsite solar photovoltaic and energy storage systems is partially motivated by customer concerns regarding grid reliability. However, accurately assessing the effectiveness of PVESS in mitigating these interruptions requires a comprehensive understanding of location-specific outage patterns and the ability to simulate realistic scenarios. To address the gap, we introduce the Power Reliability Event Simulation TOol (PRESTO), the first publicly available tool that simulates location-specific power interruptions at the county level. PRESTO allows for a more realistic assessment of system reliability by considering the unpredictability and location-specific patterns of power interruptions. We applied PRESTO in a case study of a single-family home across three U.S. counties, examining the performance of a solar photovoltaic system with 10kWh of battery storage during short-duration power interruptions. Our findings show that this system reliably met 93% of energy demand for essential non-heating and cooling loads, fully serving these loads in 84% of events, despite the constraints of daily time-of-use bill management which limits the battery's state-of-charge reserve. However, when heating and cooling loads were included, system performance decreased significantly, with only 70% of demand met and full service in 43% of events. These results highlight the challenges of using solar photovoltaic and energy storage systems for short-duration outages, emphasizing the need to consider factors like battery size and grid charging strategies to improve reliability. Our study demonstrates the practical applications of PRESTO, providing valuable insights into potential mitigation strategies including grid charging and optimizing battery size.

14 SOLAR ENERGY↗