Search NASA⌕ Search

SEARCH · Search NASA

Results for “safe learning”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Predictive Modeling and Uncertainty Quantification in Condition Monitoring of Active Components: A Reactor Coolant Pump Use Case

This work develops data-driven models for onset of thermal barrier leakage in reactor coolant pumps. It incorporates uncertainty quantification to enhance the reliability and robustness of pre- dictions. Using synthetic data generated by the Generic Pressurized Water Reactor simulator, realistic degradation scenarios were simulated across lifecycle stages—beginning, middle, and end of life. Key variables, including differential pressure, flow rate, vibration, and temperatures, were analyzed using machine learning framework. The fully connected neural network models demonstrated exceptional performance, achieving R2 scores exceeding 0.99 and root mean square errors as low as around 8.23 × 10-2 gallon per minute (gpm) for the three stages of the lifecy- cle. UQ analysis further validated the model’s robustness, with narrow uncertainty bounds during steady-state operations and appropriately wider bounds during transitional phases, reflecting the physical behavior of the system. This work addresses important gaps in real-time condition moni- toring and regulatory compliance by integrating advanced condition monitoring technologies with UQ into IST programs. The ability to detect thermal barrier leakage early and quantify prediction reliability supports optimizing maintenance strategies while ensuring nuclear power plants’ safe and reliable operation.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Phenogenomics reveals the ecology and evolution of Trichoderma fungi for sustainable agriculture

Trichoderma fungi support sustainable agriculture by suppressing plant diseases and improving crop performance. However, emerging pathogenicity of Trichoderma warrants further ecological and genetic characterization. Here we used machine learning to correlate genomic data from 37 Trichoderma strains with over 140 phenotypic traits, spanning metabolic versatility, biotic interactions, stress tolerance and reproductive strategies. We determined Trichoderma to be an ancient, genetically cohesive and physiologically diverse genus with spores capable of germination in water and dispersal via air and water droplets. Metabolic preferences indicate universal adaptation to mycoparasitism and to niches like arboreal microbial mats, alongside broader saprotrophic versatility. Our analyses are consistent with character displacement among close relatives and convergent evolution in distant lineages, with both processes shaping ecological plasticity and traits including dispersal modes, terrestrialization or endophytism. Our findings reveal that while some Trichoderma species show traits of biosafety concern, its vast ecophysiological diversity enables the development of safe, targeted bioeffectors.

Steindorff, Andrei S. [USDOE Joint Genome Institut↗
DOE OSTI2024

CalWave's xWave Design for PacWave (Final Technical Report)

CalWave Inc. (CalWave) is developing a wave energy converter (WEC) technology that can generate electricity from ocean waves. CalWave’s design offers a unique approach to wave energy conversion that operates fully submerged and can actively adjust the wave excitation. This capability gives the architecture enhanced survivability in ocean storms without adding significant costs. Prior to this project, CalWave had completed a demonstration of a fully functional WEC system in an open ocean demonstration at nominal 1:5 scale under FOA 1663. The goal of this project was the detailed design, following relevant standards and industry best-practices, of a variant of the xWave WEC technology that can safely and efficiently operate at the DOE’s PacWave South test site for a targeted deployment of up two years. The WEC design and associated review processes proceeded in two distinct project phases: a ‘Preliminary’ and a ‘Final’ design phase. The first phase of the project consisted of the systematic design of the WEC’s key features with regards to appropriate IEC standards. The work resulted in a preliminary design of the xWave hull including structural and Power Take-Off (PTO) load estimates, as well as performance estimates for all ocean conditions the WEC would operate in at PacWave South. Following the first open-water demonstration of CalWave’s small-scale “x1” device under FOA 1663, lessons learned were fed directly into a comprehensive review of the xWave design in the second design phase of this FOA project. CalWave’s work was supported by Sandia National Lab (SNL) and the National Renewable Energy Lab (NREL) on the holistic WEC design, and detailed feedback from specialized partners on hull design, mooring and anchoring specification, and electrical grid interconnection. Optimization of the WEC system was performed using a novel numerical optimization tool developed by Sandia and optimization trends were confirmed via an experimental model scale tank test campaign. Performance estimates for PacWave and a detailed xWave design including integration of all relevant system components were concluded. The mooring design was also concluded in the Final design phase using the most up to date sea floor characterization (CPT) data.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Equivariant, safe and sensitive — graph networks for new physics

This study introduces a novel Graph Neural Network (GNN) architecture that leverages infrared and collinear (IRC) safety and equivariance to enhance the analysis of collider data for Beyond the Standard Model (BSM) discoveries. By integrating equivariance in the rapidity-azimuth plane with IRC-safe principles, our model significantly reduces computational overhead while ensuring theoretical consistency in identifying BSM scenarios amidst Quantum Chromodynamics backgrounds. The proposed GNN architecture demonstrates superior performance in tagging semi-visible jets, highlighting its potential as a robust tool for advancing BSM search strategies at high-energy colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Strategy to safely enable X-ray computed tomography examination of highly radioactive tristructural isotropic nuclear fuel

Nondestructive post-irradiation examination of nuclear fuels and materials is useful in collecting data to inform commercial licensing of new nuclear concepts. This work details the planning, shielding design, and workflow of an X-ray computed tomography examination of an irradiated AGR-5/6/7 fuel compact with a dose rate of 1318 R/hr on contact from both β and ɤ-ray radiation with 120 R/hr of the dose rate coming exclusively from ɤ-rays. Post-irradiation examination of highly radioactive samples can help reduce the timeframe from conceptualization of novel nuclear concepts to their commercial implementation as not only is less time spent waiting for experiments to decay away to acceptable levels for examinations, but data from these experiments can more quickly inform model efforts and subsequent experiments. While this work represents the hottest radiological sample that has been openly transported and examined at Idaho National Laboratory’s Irradiated Materials Characterization Laboratory to date, it is anticipated that this work and its lessons learned will facilitate future examinations of similar or even more radioactive specimens.

42 - ENGINEERING↗
DOE OSTI2026

Digitizing Today’s Buildings in the Real World: Lessons from Field Demonstrations

Digital twins, created by generating a virtual replica of a building, enable safe evaluation of operational scenarios and applications like fault detection and diagnosis and advanced controls. However, a prerequisite is the creation of a machine-readable digital representation of a building, currently hindered by fragmented information scattered across mechanical drawings, point lists, and natural language sequences. As a result, digital twin development remains labor-intensive, error-prone, and difficult to validate. To address these challenges, two efforts from ASHRAE aim to support the digitalization of buildings. ASHRAE s223 establishes a semantic model of buildings, representing system components, configuration, and data sources. ASHRAE s231 defines a vendor-neutral programming language for expressing their control logic. As the industry evaluates implementing them in their products, understanding the challenges that vendors and implementers may face is crucial. In this paper, we present findings and lessons learned from field demonstrations in five buildings that implemented control applications using ASHRAE s223 and s231. The demonstrations highlight how semantic modeling and formalized control descriptions can significantly reduce software development time, manual point mapping, and hard-coding. Beyond time efficiency, they enable reliable automation by minimizing human interpretation and providing a means for consistency across projects. We describe the processes and best practices for model creation and model usage, from translating heterogeneous building documentation into semantic representations to implementing control logic in real-world systems. Finally, we discuss the challenges that persist, including integration with legacy software environments, gaps in interoperability, and the level of expertise still required to effectively leverage semantic models.

Prakash, Anand Krishnan↗
DOE OSTI2024

FFTF HT9 Cladding Microstructure Characterization

The sodium-cooled fast reactor (SFR) is a promising candidate for next generation nuclear reactors, operating at extreme conditions which include high temperatures (>500?C core outlet temperature) and significant neutron damage. High-Cr martensitic HT9 steel is an excellent candidate for SFR cladding and duct material due to its compatibility with liquid sodium, good thermal conductivity, resistance to void swelling, and strong creep rupture strength [1-4].However, the harsh in-core environment of SFRs can cause complex microstructural changes and mechanical property degradation in HT-9. Ensuring the safe use of HT9 cladding for metallic fuel requires both a thorough understanding of its mechanical response to microstructure evolution as well as reliable microstructure-sensitive modeling predictions. Microstructure-sensitive modeling of high temperature creep behavior in HT9 cladding for SFR applications currently lack experimental data to model the phenomena accurately. To fill this need, methods to perform microstructural characterization have been developed and performed on HT9.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Pathway-based analyses of gene expression profiles at low doses of ionizing radiation

Radiation exposure poses a significant threat to human health. Emerging research indicates that even low-dose radiation once believed to be safe, may have harmful effects. This perception has spurred a growing interest in investigating the potential risks associated with low-dose radiation exposure across various scenarios. To comprehensively explore the health consequences of low-dose radiation, our study employs a robust statistical framework that examines whether specific groups of genes, belonging to known pathways, exhibit coordinated expression patterns that align with the radiation levels. Notably, our findings reveal the existence of intricate yet consistent signatures that reflect the molecular response to radiation exposure, distinguishing between low-dose and high-dose radiation. Moreover, we leverage a pathway-constrained variational autoencoder to capture the nonlinear interactions within gene expression data. By comparing these two analytical approaches, our study aims to gain valuable insights into the impact of low-dose radiation on gene expression patterns, identify pathways that are differentially affected, and harness the potential of machine learning to uncover hidden activity within biological networks. This comparative analysis contributes to a deeper understanding of the molecular consequences of low-dose radiation exposure.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Immersive Digital Twin Laboratory for Engineering Education (CRADA Final Report)

This project aimed to create an immersive digital twin laboratory that incorporates advanced tracking and visualization capabilities. In collaboration with Fort Lewis College, NREL designed a state-of-the-art physical visualization laboratory, developed a software platform to enable interaction with tracked physical objects in the laboratory, and provided proof-of-concept curricula that included manipulating these tracked objects. The project was initiated to address the growing need for innovative educational tools in engineering education. As renewable energy systems, particularly solar installations, become more complex, there is a pressing need to bridge the gap between theoretical knowledge and practical application. Traditional methods of teaching solar engineering concepts often fall short of providing students with a comprehensive, hands-on understanding. This immersive digital twin laboratory was conceived to fill that gap by creating a safe, non-energized setting where students can interact with augmented solar installation objects, gaining valuable insights into system performance, design, and maintenance. The project utilized extended reality (XR) technologies, including head-mounted displays (HMDs) and a whole-room optical motion tracking system, to connect physical objects with their digital twins in real time. The laboratory was equipped with MagicLeap 2 HMDs, supported by a Vicon Vero 2.2 Optical Tracking System, which provided precise 6-degrees-of-freedom (6-DOF) tracking. We developed a software platform to manage the interaction between the tracked physical objects and their virtual counterparts, enabling real-time data synchronization, object recognition, and virtual overlays. We designed the system to be flexible and extendable, allowing for future integration of additional objects and curriculum. This research advances the field of engineering education by demonstrating the potential of immersive digital twin environments. The laboratory provides a dynamic learning space where students can experiment, collaborate, and learn without the risks associated with live experimentation. The ability to simulate and manipulate solar installation objects under various conditions has broad implications for workforce development, particularly in renewable energy. The project also highlights the economic feasibility of using XR technologies in educational settings, offering a cost-effective solution for institutions looking to enhance their curriculum. By fostering a deeper understanding of solar energy systems, this work contributes to the broader goal of supporting the global energy transition and preparing the next generation of engineers and technicians.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Agentic artificial intelligence for multistage physics experiments at a large-scale user facility particle accelerator

We present a language-model-driven agentic artificial intelligence (AI) system to autonomously execute multistage physics experiments on a production synchrotron light source. Implemented at the Advanced Light Source particle accelerator, the system translates natural language user prompts into structured execution plans that combine archive data retrieval, control-system channel resolution, automated script generation, controlled machine interaction, and analysis. In a representative machine physics task, we show that preparation time was reduced by 2 orders of magnitude relative to manual scripting even for a system expert, while operator-standard safety constraints were strictly upheld. Core architectural features, plan-first orchestration, bounded tool access, and dynamic capability selection, enable transparent, auditable execution with fully reproducible artifacts. These results establish a blueprint for the safe integration of agentic AI into accelerator experiments and demanding machine physics studies, as well as routine operations, with direct portability across accelerators worldwide and, more broadly, to other large-scale scientific infrastructures.

Accelerator/storage ring control systems↗
DOE OSTI2024

Dynamic and Responsive Distributed Energy Resource Education Solutions for Building, Fire, and Safety Department Officials (Final Technical Report)

From April 2021 through March 2024, the Interstate Renewable Energy Council (IREC) led a collaborative project to develop a free online clearinghouse of educational resources about solar photovoltaics (PV), energy storage systems (ESS), electric vehicle supply equipment (EVSE), and grid-interactive efficient building (GEB) technologies. Two websites—the Clean Energy Clearinghouse and CleanEnergyTraining.org—housed over 70 educational resources. Over the course of the three-year project, 154,272 unique visitors accessed the learning materials. Learner feedback was overwhelmingly positive. Even through the end of the project, there was sustained demand for education and communication. A primary innovation of the project was to drive multiple complementary audiences to the same place. Building owners, designers, installation contractors and developers, authorities having jurisdiction (AHJs), and fire service personnel all benefit from a shared understanding of clean energy technologies, including safety and code-related requirements. When considering the impact on the target audience, the project team worked with partners and advisors to inform resource creation and delivery in such a way as to address key motivational factors of the target audience and compel each user to seek additional information on the topic and return to the Clean Energy Clearinghouse website as their central location for more information. Resources were intentionally developed to be concise—five to 15 minutes—and accessible, meaning not overly technical. Providing basic information demystified the technologies and invited the professional to explore additional learning opportunities. Awardee and partner collaboration was key to project success. IREC facilitated collaboration among the other Topic 2 awardees, Southface and New Buildings Institute (NBI). The three awardees shared relevant information gained through discovery and validation questionnaires that informed product development and reduced duplication of effort by coordinating the development of complementary, and not competing, educational resources. Inspired by this collaboration, IREC brought on additional partners even in the final year of the project. Five regional energy efficiency organizations were part of the project, which expanded the connection between efficiency and distributed energy resources. We also included resources on the Clearinghouse that were developed through other federally funded projects, such as the Buildings Energy Efficiency Frontiers & Innovation Technologies (BENEFIT) program. The website was developed with the learner in mind, and not solely the funding source. Feedback from stakeholders throughout the project, and especially in its final year, indicated the need for continued education and facilitated communication among stakeholders to further the safe and widespread adoption of clean energy.

14 SOLAR ENERGY↗
DOE OSTI2024

Creep and Creep Fracture Modeling with Surrogate Creep Models and the Extended Finite Element Method

Alloy components in advanced nuclear reactors will be subjected to environmental conditions that could include high temperatures, irradiation, and exposure to corrosive salts. These conditions could lead to the formation of crack-like defects, which could grow over time in a mechanism known as creep crack growth (CCG). Predicting growth rates of these defects is important for assessing the safe operating life of advanced reactors. This project documents progress toward developing and testing next-generation data-driven constitutive models for deformation creep. It also documents the application of the extended finite element method in conjunction with surrogate creep models to predict CCG parameters under a variety of conditions. These important incremental developments contribute to the longer-term objective of developing microstructure-aware constitutive models that can be used for predicting creep deformation and CCG at the component scale with improved accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Topology-Aware Reinforcement Learning for Voltage Control: Centralized and Decentralized Strategies

Volt-VAR control (VVC) methods based on deep reinforcement learning (DRL) can effectively control distribution grid voltage and minimize power loss by implementing corrective and preventive control measures on the reactive power output of inverter-based distributed energy resources (DERs). However, model-free DRL-based VVC approaches usually cannot capture the important topological feature of the power system since they use a fully-connected network (FCN) to deliver the action. Therefore, this paper proposes a graph convolutional network (GCN)-based DRL approach that can employ the topological information of the network to take better control action for regulating the voltage. Our implementation allows for both centralized and decentralized configurations, utilizing a single agent and multiple agents respectively. Although the centralized GCN-based DRL approach has its advantages of minimizing voltage fluctuation and power loss, it is not suitable for large scale power systems due to its challenges in terms of scalability, computation speed and potential single points of failure. Therefore, these problems can be resolved using the decentralized GCN-based DRL approach. Moreover, to ensure the safe operation of the model, our proposed approach incorporates an exponential barrier function while formulating the reward function for each agent. To validate performance of the proposed approaches, the proposed model is tested on modified IEEE test systems and the performances are measured in terms on voltage fluctuation reduction, minimization of power loss and computational speed. Finally, the results show that the proposed topology-aware approach outperforms the FCN-based DRL approach in terms of reducing voltage fluctuation and minimizing power loss of the network. Moreover, it is shown that the decentralized GCN-based DRL has faster computational speed than other approaches.

42 ENGINEERING↗
DOE OSTI2024

Overview of physics results from the ADITYA-U tokamak and future experiments

The ADITYA upgrade (ADITYA-U), a medium-sized (R 0 = 75 cm, a = 25 cm) conventional tokamak facility in India, has been consistently producing experiments findings by usingcircular and shaped-plasmas. Recognizing the plasma parameters aligning closely with the design parameters of circular limited plasmas, ADITYA-U shifted its focus toward exploring the operational regime for experimentation on saw-tooth and MHD phenomena. Moreover, ADITYA-U has made consistent advancements toward conducting preliminary plasma shaping experiments through the activation of top and bottom divertor coils utilizing hydrogen as well as deuterium fuels. Confinement is improved by a factor of ~1.5 in D 2 plasmas when compared to H 2 plasmas of ADITYA-U. Further, ADITYA-U operations emphasize preventing disruptions and runaway electrons (REs) to ensure safe operations for future fusion devices. Significant suppression of REs has been achieved in ADITYA-U with the application of pulsed localized vertical magnetic field (LVF) perturbation, thereby establishing the technique's independence from the tokamak device. The successful RE mitigation requires a critical threshold of LVF pulse magnitude, which is approximately 1% of the toroidal magnetic field, and a minimum duration of ~5 ms. Apart from this, several novel findings have been achieved in the ADITYA-U experiments, including the modification of sawtooth duration through gas-puff, the emergence of MHD-induced geodesic acoustic mode-like oscillations, the propagation of fast heat pulses induced by MHD activity, the control of RE dynamics through Gas-puffs, the propagation of pinch-driven cold-pulses, the transport and core accumulations of argon impurities, the mass dependency of plasma toroidal rotation and the detection of 'RICE' scaling, as well as the characterization of edge plasma using wall conditioning methods, such as glow discharge cleaning using a combination of Ar-H 2 mixture, localized wall cleaning by electron cyclotron resonant plasma, and the development of machine learning-based disruption predictions, will be discussed in this paper.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Fracture Network Quantification for Enhanced Reservoir Characterization in CO2 Storage Sites

Presentation slides on “Fracture Network Quantification for Enhanced Reservoir Characterization in CO2 Storage Sites” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. Accurate reservoir characterization is fundamental for the safe and efficient operation of carbon capture, utilization, and storage (CCUS) projects. This process is not only critical during initial site selection but also plays a key role in continuously updating reservoir geomodels throughout injection operations to effectively manage subsurface storage sites. Our primary objective is to develop a comprehensive understanding of fracture networks within CO2 injection reservoirs, which are critical for predicting the behavior of injected fluids, ensuring storage integrity post-injection, and mitigating risks such as leakage or induced seismicity.

artifical intelligence / machine learning (AI/ML)↗
DOE OSTI2024

Virtual Resource Management Framework (CRADA Final Report)

There is a need for advanced and widespread business automation within the nuclear industry to drive down operational costs while sustaining or improving safe operations. While there are many business process automation platforms commercially available, the difficulty is that business processes typically rely on a mixture of resource types to accomplish the desired activities and there is no universal software framework virtualizing diverse resource types for the purpose of automation. In this context, we are referring to any capability, physical or intangible, that can be used by an organization to achieve its objectives as a resource. To deploy business automation broadly and enable integrated operations for nuclear (ION), a framework is needed to represent all resource types and their associated disparate data within a plant and to enable seamless flow of resource information to the technologies used for process automation and resource optimization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Comprehensive defect evaluation of advanced nuclear fuels using high-resolution acoustic signals and optimized sensor separation

Graphite pebble composite structures based on TRistructural-ISOtropic (TRISO) particles are being developed as core nuclear fuels in advanced power reactors, promising safe operation at increased temperatures. Ensuring the structural integrity of these nuclear fuels requires comprehensive and accurate non-destructive evaluation (NDE) techniques to characterize defects and damage in the pebbles. However, traditional acoustic evaluation methods face limitations in defect characterization due to the highly attenuative, and geometrically and compositionally complex nature of these structures. This study proposes an improved acoustic NDE technique for accurate detection and classification of anticipated relevant defects and damage in graphite pebbles using high-resolution acoustic signals and optimized transmit-receive sensor networks. The proposed approach utilizes a triangular three-sensor network as the base unit, comprising three transmit-receive sensors. The sensor separation distance, as well as acoustic excitation center frequency, pulse-width, and bandwidth are optimized to enhance spatial resolution and improve signal-to-noise ratio, enabling effective characterization of the smallest size and widest range of defects in pebbles. Furthermore, the use of the triangular sensor configuration instead of a more conventional transmit-receive sensor pair expands the inspection region from a one-dimensional linear path to a two-dimensional area, increasing spatial coverage. To mitigate challenges associated with processing of complex acoustic signals arising from high-frequency, high-bandwidth excitation in these structures, a machine-learning-based signal processing algorithm is integrated with the sensor network. In the machine-learning-based algorithm, multi-domain features are extracted from the acoustic signals to capture intricate signal characteristics, significantly improving defect identification and classification compared to traditional approaches. The proposed acoustic NDE technique offers considerable promise for practical and reliable defect/damage diagnostics of advanced nuclear pebble fuels.

42 ENGINEERING↗
DOE OSTI2026

Development of a Test-Bed for Testing and Refining EarthEn’s Supercritical CO 2 Based Energy Storage System

EarthEn’s energy storage concept leverages supercritical carbon dioxide (sCO 2 ) as a working fluid and relies on compact, high-performance components operating at elevated pressures and temperatures. To accelerate component development and reduce technical risk prior to larger-scale demonstrations, Oak Ridge National Laboratory (ORNL) developed a 100 kW-scale sCO 2 test-bed under a Cooperative Research and Development Agreement with EarthEn (CRADA NO. NFE-24-10050). The objective of the work was to design and construct a flexible experimental facility capable of reproducing key thermodynamic state points and heat-transfer conditions relevant to EarthEn’s thermal energy storage (TES) cycle, with particular emphasis on enabling development and evaluation of next-generation heat exchangers and TES concepts. The test-bed consists of a closed-loop sCO 2 circulation system housed within an open-topped enclosure. In its as-installed configuration, dense-phase sCO 2 is recirculated through a printed circuit recuperator, an electrically heated section, a throttling device used to simulate turbine expansion, and a water-cooled printed circuit heat exchanger that rejects heat to the building chilled-water system before returning to the pump. The pump is driven by a variable frequency drive, enabling controlled adjustment of flow and operating point. A comprehensive instrumentation suite was integrated to support both safe operation and high-quality data collection. Installed sensors include Coriolis flow meters for sCO 2 flow rate and density, resistance temperature detectors and thermocouples distributed throughout the loop (including the heated section and key heat exchanger ports), and pressure transducers for absolute and differential pressure measurements. The facility was designed to support high-pressure (19 MPa nominal) and high-temperature (575°C nominal) operation with credited overpressure protection provided by a rupture disk. Nominal operating conditions were selected to support 100 kW-class testing while maintaining flexibility for non-heated and heated shakedown, control development, and future integration of advanced TES test sections. In parallel with facility development, a system-level thermal-hydraulic model was created using Modelica-based tools to support component sizing, anticipate performance over targeted test conditions, and establish a framework for future model calibration against experimental data. At the conclusion of the project performance period, the facility was in final assembly, and the pressure boundary was nearly completed. However, several practical challenges associated with high-pressure/high-temperature systems and specialized component procurement impacted schedule and prevented initial pump-driven operation and full commissioning within the available resources. This report documents the as-built design, operating capabilities, and instrumentation, and it summarizes key lessons learned related to heater fabrication and testing, first-of-a-kind assembly factors, specialty flange supply constraints, and fill pump corrective actions. Finally, it outlines a phased plan for future commissioning and experimental campaigns, including control and instrumentation shakedown, heater characterization, model calibration, and testing at state points representative of EarthEn’s TES cycle.

25 ENERGY STORAGE↗