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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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DOE OSTI2025

Revenue-Maximizing Shared Parking and Electric Vehicle Charging Management in Multi-Unit Dwellings

In urban areas, searching for parking and electric vehicle (EV) charging can result in cruising, congestion, and environmental externalities. Recognizing the business opportunity of offering private parking and charging infrastructure access within multi-unit dwellings (MUDs) during daytime, we model a shared parking and EV charging management system. We maximize the revenue of MUD charging hubs in mixed land use, catering to public demand. Our approach accounts for the objectives of the two stakeholders involved: a demand model is fitted on the choices of EV charging users, and the supply model optimizes the allocation of parking and charging requests in an MUD parking lot. A binary integer linear programming model for the allocation of parking and charging spaces with a rolling horizon is integrated with matching rules that handle both parking and charging requests. In our numerical experiments in a neighborhood of Chicago, Illinois, we estimate the performance of the MUD parking and charging system with metrics that include revenue, number of matchings, and utilization rates. At any given time, MUDs with lower prices attract more charging requests, particularly those of longer duration, resulting in higher revenue and greater charging utilization. Dynamic pricing facilitates a more equitable distribution of requests; as MUD parking lots reach capacity and their fees increase, other MUDs become more competitive, attracting additional requests. Comparing our method against first-come-first-served and optimal-solution benchmarks, we demonstrate our model’s effectiveness in dynamically managing mixed parking and charging demand in MUD charging hubs.

electric vehicle, multi-unit dwelling, charging in↗
DOE OSTI2018

A Guide for Selecting Appropriate Human Factors Methods and Measures in Control Room Modernization Efforts in Nuclear Power Plants

Abstract. Many of the U.S. nuclear power plants are approaching the end of their 60-year licensing period. The U.S. Department of Energy Light Water Reactor Sustainability Program is conducting targeted research to extend the lives and ensure long-term reliability, productivity, safety, and security of these plants through targeted research, such as with integrating advanced digital instrumentation and control technologies in the main control room. There are many challenges to this, one being the integration of human factors engineering in the design and evaluation of these upgrades. This paper builds upon recent efforts in developing utility-specific guidance for integrating human factors engineering in the control room modernization process by providing commonly used data collection methods that are applicable at various phases of the upgrade process. Advantages and disadvantages of each method is provided for consideration of an optimal human factors evaluation plan to be used throughout the lifespan of the upgrade process.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

2016 DOE Vehicle Technologies Office Annual Merit Review

The 2016 U.S. Department of Energy (DOE) Hydrogen and Fuel Cells Program and Vehicle Technologies Office (VTO) Annual Merit Review and Peer Evaluation Meeting (AMR) was held June 6-9, 2016, in Washington, DC. The review encompassed work done by the Hydrogen and Fuel Cells Program and VTO: 226 individual activities were reviewed for VTO, by 171 reviewers. A total of 1,044 individual review responses were received for the VTO technical reviews. The objective of the meeting was to review the accomplishments and plans for VTO over the previous 12 months, and provide an opportunity for industry, government, and academia to give inputs to DOE with a structured and formal methodology. The meeting also provided attendees with a forum for interaction and technology information transfer.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Autonomous Sampling Platform Development: Radiological Contamination Mapping at SRS

From 1961 to 1964, radioactive elements were released from the Savannah River Site into local bodies of water via cooling water charges from the reactors on site. In 1983, the extent of the radioactive contamination was first studied, and elements such as 137 Cs, 90 Sr, 238 Pu, 241 Am, 244 Cm, and tritium were found to have seeped from local bodies of water into sediment and the surrounding flora and fauna. The current method of tracking and monitoring radioactive contamination at the SRS is to gather samples and conduct measurements in a laboratory. A cheaper, and safer, method to conduct such measurements would be to automate the process by using an autonomous boat that can travel to locations, conduct measurements, and return home all without human intervention. To introduce this idea, the construction of an autonomous boat prototype was completed to demonstrate the practicality and feasibility of such an idea. The prototype travels to a set of waypoints, stops at each waypoint, and returns when all waypoints have been reached. It does this by employing a simple battery-powered boat with an Arduino controller that steers the boat using a steering algorithm incorporated into a Proportional Integral Derivative (PID) function. A total of three tests were conducted at two different bodies of water; and after working out some hardware problems, the boat drone was able to successfully steer and reach all programmed waypoints. With the prototype complete, the next steps to realizing the final product of the boat drone will include adopting a processing unit with higher-bit architecture, using a bigger boat with a more powerful trolling motor, and incorporating a solar panel for continuous power and round-the-clock performance.

42 ENGINEERING↗
DOE OSTI2013

Dry Storage of Research Reactor Spent Nuclear Fuel - 13321

Spent fuel from domestic and foreign research reactors is received and stored at the Savannah River Site's L Area Material Storage (L Basin) Facility. This DOE-owned fuel consists primarily of highly enriched uranium in metal, oxide or silicide form with aluminum cladding. Upon receipt, the fuel is unloaded and transferred to basin storage awaiting final disposition. Disposition alternatives include processing via the site's H Canyon facility for uranium recovery, or packaging and shipment of the spent fuel to a waste repository. A program has been developed to provide a phased approach for dry storage of the L Basin fuel. The initial phase of the dry storage program will demonstrate loading, drying, and storage of fuel in twelve instrumented canisters to assess fuel performance. After closure, the loaded canisters are transferred to pad-mounted concrete overpacks, similar to those used for dry storage of commercial fuel. Unlike commercial spent fuel, however, the DOE fuel has high enrichment, very low to high burnup, and low decay heat. The aluminum cladding presents unique challenges due to the presence of an oxide layer that forms on the cladding surface, and corrosion degradation resulting from prolonged wet storage. The removal of free and bound water is essential to the prevention of fuel corrosion and radiolytic generation of hydrogen. The demonstration will validate models predicting pressure, temperature, gas generation, and corrosion performance, provide an engineering scale demonstration of fuel handling, drying, leak testing, and canister backfill operations, and establish 'road-ready' storage of fuel that is suitable for offsite repository shipment or retrievable for onsite processing. Implementation of the Phase I demonstration can be completed within three years. Phases II and III, leading to the de-inventory of L Basin, would require an additional 750 canisters and 6-12 years to complete. Transfer of the fuel from basin storage to dry storage requires integration with current facility operations, and selection of equipment that will allow safe operation within the constraints of existing facility conditions. Examples of such constraints that are evaluated and addressed by the dry storage program include limited basin depth, varying fuel lengths up to 4 m, (13 ft), fissile loading limits, canister closure design, post-load drying and closure of the canisters, instrument selection and installation, and movement of the canisters to storage casks. The initial pilot phase restricts the fuels to shorter length fuels that can be loaded to the canister directly underwater; subsequent phases will require use of a shielded transfer system. Removal of the canister from the basin, followed by drying, inerting, closure of the canister, and transfer of the canister to the storage cask are completed with remotely operated equipment and appropriate shielding to reduce personnel radiation exposure. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

DE-FE0031180 Final Report - LGFCS Prototype System Testing - R0

In the project, LGFCS assembled and tested its modular SOFC Power System that incorporates all critical technology improvements identified for its “product-like” demonstration. This product demonstrator is expected to meet customer and LGFCS performance expectations for operation, availability, durability and serviceability. The principal technology improvements are aimed at increasing the fuel cell power output and reducing the stack degradation rate. Improvements were also made for added system robustness and increased reliability. The objective of this program is to test a 250kWe thermally self-sustaining modular solid oxide fuel cell (SOFC) Power System for a minimum of 5,000 hours while advancing this commercial prototype product demonstrator to a Technical Readiness Level (TRL) 7. The SOFC system was tested on a site provided by Stark State College in North Canton, Ohio. System performance and degradation as well as cost estimates were compared to established SOFC Program performance metrics to assess progress. The major achievements were to assemble, and QA qualify 70 fuel cell strips for 12 integrated blocks into a fuel cell vessel and install it into a generator module with the fuel and power electronics modules on the test site. Performance to date included over 1800 hours on load at 250 KW-AC to the grid with a DC efficiency of 61% and AC efficiency of 55%. Power degradation was less than 0.4% per 1000 hours and NOx emissions met standards. The LGFCS SOFC Prototype System (GEN0) was demonstrated in an operational environment and therefore achieving Technical Readiness Level 7. The work presented here represents the efforts of all the employees of LG Fuel Cell Systems. Their dedication and hard work made GEN0 possible and successful.

03 NATURAL GAS↗
DOE OSTI2023

Functional composites by programming entropy-driven nanosheet growth

Here, nanomaterials must be systematically designed to be technologically viable. Driven by optimizing intermolecular interactions, current designs are too rigid to plug in new chemical functionalities and cannot mitigate condition differences during integration. Despite extensive optimization of building blocks and treatments, accessing nanostructures with the required feature sizes and chemistries is difficult. Programming their growth across the nano-to-macro hierarchy also remains challenging, if not impossible. To address these limitations, we should shift to entropy-driven assemblies to gain design flexibility, as seen in high-entropy alloys, and program nanomaterial growth to kinetically match target feature sizes to the mobility of the system during processing. In tis report, following a micro-then-nano growth sequence in ternary composite blends composed of block-copolymer-based supramolecules, small molecules and nanoparticles, we successfully fabricate high-performance barrier materials composed of more than 200 stacked nanosheets (125 nm sheet thickness) with a defect density less than 0.056 µm -2 and about 98% efficiency in controlling the defect type. Contrary to common perception, polymer-chain entanglements are advantageous to realize long-range order, accelerate the fabrication process (<30 min) and satisfy specific requirements to advance multilayered film technology. This study showcases the feasibility, necessity and unlimited opportunities to transform laboratory nanoscience into nanotechnology through systems engineering of self-assembly.

42 ENGINEERING↗
DOE OSTI2019

Wide Band Gap Chalcopyrite Photoelectrodes for Direct Water Splitting (Final Technical Report)

The chalcopyrite material class, typically identified by its most popular alloy CuInGaSe 2 , provides exceptionally good candidates for photoelectrochemical (PEC) water splitting and has the potential to meet DoE EERE’s targets in terms of hydrogen production costs (less than $2/gge). Some key advantages of this class include remarkable photon-to-electron conversion efficiency and a high Faradaic efficiency for the hydrogen evolution reaction, two characteristics essential for efficient PEC water splitting. However, the band gaps of commonly used chalcopyrites in the photovoltaic field (1.0-1.6 eV) are too narrow to be compatible with the multi-junction approach for efficient PEC hydrogen production, in which a stack of solar absorbers generates the bias required for water splitting. Nonetheless, previous studies performed by our team demonstrated that chalcopyrites’ narrow band gaps could be effectively widened using simple conversion steps, leading to functional chalcopyrite-based PEC electrodes with optical band gap in the 1.8-2.4 eV range, making this class highly suitable for renewable hydrogen production via water splitting. This multi-disciplinary research program lead by the University of Hawai’i/Hawai’i Natural Energy Institute combined unique analytical techniques (UNLV), state-of-the-art theoretical modeling (LLNL) with advanced thin film materials synthesis (HNEI, NREL and Stanford) to provide deeper understanding of wide band gap chalcopyrite-based PEC materials and engineer high performance/corrosion-resistant photocathodes with tunable energetics and compatible with the multi-junction approach. The goals of this project were to demonstrate photoelectrochemical (PEC) solar-hydrogen production using a dual absorber system with a solar-to-hydrogen conversion efficiency of at least 15% with an operational life up to 2,000 hours and capable of generating at least 3 liters of hydrogen in 8 hours. After a brief introduction (Section 1) and description of our work plan (Section 2), we present in Section 3 our results on the development of new wide bandgap copper chalcopyrites absorbers for PEC waters splitting. We first show through modeling how alloying can be used to tailor the optical properties and/or surface energetics of various material candidates. We also present how specific defects (e.g., GaCu) can lead to recombination centers within the forbidden gap of copper-poor chalcopyrites. Then, we present our efforts to synthesize high efficiency wide band gap CuGa 3 Se 5 , CuGa(S,Se) 2 and Cu(In,Ga)S 2 photocathodes capable of generating photocurrent density over 10 mA/cm 2 . We also demonstrate that Cu-rich absorbers should be avoided as they lead to poor sub-band gap optical transmission. In Section 4, we first report on our efforts to tune the energetics of chalcopyrites toward the hydrogen evolution reaction. First, we quantified the energetics of wide band gap chalcopyrites interfaced with conventional CdS buffer layer, as measured with X-ray photoelectron spectroscopy techniques, and evidence the presence of a large (and undesirable) conduction band offset at this interface. Then, we highlight some of the work performed with alternative buffer layers, including In 2 S 3 . Durability improvements with various ultra-thin protective layers are presented in Section 5. Our data show that TiO 2 combined with MoS 2 can significantly improve chalcopyrites lifetime up to 350 hours under continuous operation at 8 mA/cm 2 . Finally, in Section 6 we report strategies to integrate chalcopyrite photocathodes into standalone tandem PEC devices. Although promising methods were proposed for both mechanical and monolithic stacking with narrow band gap PV drivers, no functional device was fabricated on time to fulfill the program end goals.

08 HYDROGEN↗
DOE OSTI2024

OpenFacadeControl: enabling integration of automated facades with other building systems

Automated facades are, for the most part, still considered as separate from other building systems throughout the design, installation, commissioning, operation, and maintenance cycle. This takes place despite the fact that their energy and comfort performance are deeply interlinked with the operation of lighting and HVAC systems. Over the last two decades, research has shown that there are significant advantages from operating facades as an integrated system with the rest of the building. Nevertheless, significant barriers prevent this type of integration becoming more common. One of them is the lack of a platform that is inexpensive to implement and that easily allows the practical implementation of integrated control algorithms across fenestration and other building systems, using a variety of communications protocols. This is particularly challenging when automated facades are installed in existing buildings, where interaction with legacy building systems that were installed over the past lifetime of the building can require a high degree of interoperability. OpenFacadeControl (OFC) is an open-source controls framework aimed at unified control of facades and other building systems, including the sharing of third-party sensor information. Through leveraging the Volttron controls platform, it allows the integration of systems and sensors that are manufactured by different companies and that use different communications protocols into an ensemble that functions as a single system. OFC is designed to enable integrated control algorithms of varying degrees of complexity, ranging from simple, heuristic controls to more sophisticated approaches like model-predictive control. Use of a research version to test advanced lighting and shading strategies in a full-scale experimental testbed has demonstrated the ease of deploying advanced control solutions using OpenFacadeControl. This paper presents the structure of OpenFacadeControl and a demonstration case showing the use of OFC in laboratory tests of advanced lighting and fenestration controls that coordinated motorized shades communicating via the BACnet building communications standard and lights communicating via internet-protocol-based application programming interface (API), based on the readings of a shared light level sensor communicating via a different API.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Obstacles to Practical Digital Supply Chain Risk Management in the Energy Sector

Cyber supply chain risk management (C-SCRM) programs must consider operations that depend on the lifecycles of digital components such as hardware, firmware, software, and services. We integrate academic literature, historical incidents, and existing standards to identify obstacles faced by C-SCRM programs.

Business Process Management & Integration↗
DOE OSTI2021

Scoreboard

Emerging HPC machines have given rise to enhanced compute power that far outstrips the machine's ability to save large scale results for post-processing. To combat this, in situ data analysis techniques are slowly being adopted. With in situ data management favoring workflows composed of multiple simulations and analyses connected in transit on heterogeneous machines, scientists and engineers need a tool that enables them to create data extracts, visualizations, and interactively monitor and steer their simulations. Scoreboard Phase II is a next generation analysis software that supports composite in transit workflows on heterogeneous architectures and restores interactivity to in situ data analysis through simulation monitoring and computational steering. Scoreboard provides a simulation dashboard with graphs of metrics over time, controls for setting custom simulation steering parameters, controls for managing the set of data extracts being produced in the simulation, as well as the ability to explore data extracts, all from a web browser. Realizing the vision outlined in this project required research into making a system that integrates end to end from simulations all the way to the user. In situ tools generally suffer from complexity and excessive software dependencies. Scoreboard, by contrast, is easy to build and integrate into simulation codes and it provides first class FORTRAN support. The Scoreboard library is capable of in situ and in transit data analysis that can produce data extracts commonly needed for Computational Fluid Dynamics (CFD) analysis. Simulations can transparently stage data in transit to a Scoreboard Endpoint program, which can accept their data and produce the requested data extracts. This lets simulations return to their work while the Endpoint works on the analysis. Efficiently staging the data at scale was a topic of this research. Scoreboard provides the means to let the user manage data extracts and monitor/steer many simulations from a web browser. This area of the research focused on discovery of in transit network components to expose and control their steering parameters within an interactive browser-based user interface that includes: system topology, gathered metrics, notifications, dynamically-generated steering controls, and exploration of visualization data products.

Whitlock, BradJoseph [Intelligent Light] (00000001↗
DOE OSTI2019

Data-driven cyber attack detection and mitigation for decentralized wide-area protection and control in smart grids

Modern power systems have already evolved into complicated cyber physical systems (CPS), often referred to as smart grids, due to the continuous expansion of the electrical infrastructure, the augmentation of the number of heterogeneous system components and players, and the consequential application of a diversity of information and telecommunication technologies to facilitate the Wide Area Monitoring, Protection and Control (WAMPAC) of the day-to-day power system operation. Because of the reliance on cyber technologies, WAMPAC, among other critical functions, is prone to various malicious cyber attacks. Successful cyber attacks, especially those sabotage the operation of Bulk Electric System (BES), can cause great financial losses and social panics. Application of conventional IT security solutions is indispensable, but it often turns out to be insufficient to mitigate sophisticated attacks that deploy zero-day vulnerabilities or social engineering tactics. To further improve the resilience of the operation of smart grids when facing cyber attacks, it is desirable to make the WAMPAC functions per se capable of detecting various anomalies automatically, carrying out adaptive activity adjustments in time and thus staying unimpaired even under attack. Most of the existing research efforts attempt to achieve this by adding novel functional modules, such as model-based anomaly detectors, to the legacy centralized WAMPAC functions. In contrast, this dissertation investigates the application of data-driven algorithms in cyber attack detection and mitigation within a decentralized architecture aiming at improving the situational awareness and self-adaptiveness of WAMPAC. First part of the research focuses on the decentralization of System Integrity Protection Scheme (SIPS) with Multi-Agent System (MAS), within which the data-driven anomaly detection and optimal adaptive load shedding are further explored. An algorithm named as Support Vector Machine embedded Layered Decision Tree (SVMLDT) is proposed for the anomaly detection, which provides satisfactory detection accuracy as well as decision-making interpretability. The adaptive load shedding is carried out by every agent individually with dynamic programming. The load shedding relies on the load profile propagation among peer agents and the attack adaptiveness is accomplished by maintaining the historical mean of load shedding proportion. Load shedding only takes place after the consensus pertaining to the anomaly detection is achieved among all interconnected agents and it serves the purpose of mitigating certain cyber attacks. The attack resilience of the decentralized SIPS is evaluated using IEEE 39 bus model. It is shown that, unlike the traditional centralized SIPS, the proposed solution is able to carry out the remedial actions under most Denial of Service (DoS) attacks. The second part investigates the clustering based anomalous behavior detection and peer-assisted mitigation for power system generation control. To reduce the dimensionality of the data, three metrics are designed to interpret the behavior conformity of generator within the same balancing area. Semi-supervised K-means clustering and a density sensitive clustering algorithm based on Hierarchical DBSCAN (HDBSCAN) are both applied in clustering in the 3D feature space. Aiming to mitigate the cyber attacks targeting the generation control commands, a peer-assisted strategy is proposed. When the control commands from control center is detected as anomalous, i.e. either missing or the payload of which have been manipulated, the generating unit utilizes the peer data to infer and estimate a new generation adjustment value as replacement. Linear regression is utilized to obtain the relation of control values received by different generating units, Moving Target Defense (MTD) is adopted during the peer selection and 1-dimensional clustering is performed with the inferred control values, which are followed by the final control value estimation. The mitigation strategy proposed requires that generating units can communicate with each other in a peer-to-peer manner. Evaluation results suggest the efficacy of the proposed solution in counteracting data availability and data integrity attacks targeting the generation controls. However, the strategy stays effective only if less than half of the generating units are compromised and it is not able to mitigate cyber attacks targeting the measurements involved in the generation control.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Convex Optimization of Integrated Power-Gas Energy Flow Model With Applications to Probabilistic Energy Flow

Energy flow calculation is a fundamental problem of the integrated power and gas system (IPGS) operation and planning. However, the nonlinear gas flow model introduces major challenges to the energy flow calculation. In this paper, we propose a tractably convex optimization model to solve the energy flow problem in IPGSs. It is demonstrated that the proposed optimization model has the same optimal solution as the original nonlinear steady energy flow model. Also, piecewise linearization is adopted to tightly linearize the nonlinear objective function of the model, which transforms the formulated convex optimization into a linear program one. Thus, the computation complexity of the proposed energy flow model is significantly reduced as compared with the existing methods. In addition, the proposed model can be extended to probabilistic energy flow estimation. Extensive case studies are conducted to validate the effectiveness of the proposed energy flow model using three IPGSs.

42 ENGINEERING↗
DOE OSTI2022

Developments and Challenges in the Design of the ITER DRGA

We report the ITER Diagnostic Residual Gas Analyzer (DRGA) will measure the distribution of gas species, i.e., deuterium (D), tritium (T), and impurities, in the divertor exhaust stream and in the plasma periphery, with time resolution relevant to fusion plasma–wall particle dynamics. The uniqueness of the DRGA, over previous implementations of plasma dynamics residual gas analysis, is an integrated approach, combining mass and low-temperature plasma-activated optical spectroscopy, in a differentially pumped analysis station. A further unique feature of the ITER divertor-specific DRGA is an ~8-m separation of the analysis station from the sampled pumping duct, while still maintaining a ~1-s response time for hydrogen isotopic concentrations. ITER DRGA final design activities are strongly benefiting from testing of prototypical DRGA components and methods on present fusion devices, most currently on JET and W7-X. DRGA systems are implemented on both these devices and include sensors (and pumping methods) that are directly relevant to the ITER DRGA design. The recent JET-DTE2 campaign has provided the first experience on operating the combined ITER DRGA sensors with D-T plasmas. While enhancing system design for ITER, this experience on operating devices has also revealed additional engineering challenges, which further guide the continuing final design project. Meanwhile, the recent determination that the ITER DRGA, with slight optimization, will resolve the helium isotopes well enough to support an ITER pre-DT, He-3-based heating scheme, has greatly increased ITER Research Program interest in the DRGA and its implementation well ahead of the DT phase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Sensor Network Demonstration for In Situ Decommissioning - 13332

Florida International University's (FIU's) Applied Research Center is currently supporting the Department of Energy's (DOE) Environmental Management Office of D and D and Facility Engineering program. FIU is supporting DOE's initiative to improve safety, reduce technical risks, and limit uncertainty within D and D operations by identifying technologies suitable to meet specific facility D and D requirements, assessing the readiness of those technologies for field deployment, and conducting feasibility studies and large scale demonstrations of promising technologies. During FY11, FIU collaborated with Savannah River National Laboratory in the development of an experimental test site for the demonstration of multiple sensor systems for potential use in the in situ decommissioning process. In situ decommissioning is a process in which the above ground portion of a facility is dismantled and removed, and the underground portion is filled with a cementious material such as grout. In such a scenario, the question remains on how to effectively monitor the structural health of the grout (cracking, flexing, and sinking), as well as track possible migration of contaminants within and out of the grouted monolith. The right types of sensors can aid personnel in better understanding the conditions within the entombed structure. Without sensors embedded in and around the monolith, it will be very difficult to estimate structural integrity and contaminant transport. Yet, to fully utilize the appropriate sensors and the provided data, their performance and reliability must be evaluated outside a laboratory setting. To this end, a large scale experimental setup and demonstration was conducted at FIU. In order to evaluate a large suite of sensor systems, FIU personnel designed and purchased a pre-cast concrete open-top cube, which served as a mock-up of an in situ DOE decommissioned facility. The inside of the cube measures 10 ft x 10 ft x 8 ft. In order to ensure that the individual sensors would be immobilized during the grout pouring activities, a set of nine sensor racks were designed. The 270 sensors provided by Idaho National Laboratory (INL), Mississippi State University (MSU), University of Houston (UH), and University of South Carolina (USC) were secured to these racks based on predetermined locations. Once sensor racks were installed inside the test cube, connected and debugged, approximately 32 cubic yards of special grout material was used to entomb the sensors. MSU provided and demonstrated four types of fiber loop ring-down (FLR) sensors for detection of water, temperature, cracks, and movement of fluids. INL provided and demonstrated time differenced 3D electrical resistivity tomography (ERT), advanced tensiometers for moisture content, and thermocouples for temperature measurements. University of Houston provided smart aggregate (SA) sensors, which detect crack severity and water presence. An additional UH sensor system demonstrated was a Fiber Bragg Grating (FBG) fiber optic system measuring strain, presence of water, and temperature. USC provided a system which measured acoustic emissions during cracking, as well as temperature and pH sensors. All systems were connected to a Sensor Remote Access System (SRAS) data networking and collection system designed, developed and provided by FIU. The purpose of SRAS was to collect and allow download of the raw sensor data from all the sensor system, as well as allow upload of the processed data and any analysis reports and graphs. All this information was made available to the research teams via the Deactivation and Decommissioning Knowledge Management and Information Tool (D and D KM-IT). As a current research effort, FIU is performing an energy analysis, and transferring several sensor systems to a Photovoltaic (PV) System to continuously monitor energy consumption parameters and overall power demands. Also, One final component of this research is focusing on developing an integrated data network to capture, log and analyze sensor system data in near real time from a single interface. FIU personnel and DOE Fellows monitored the progress and condition of the sensors for a period of six months. During this time, the sensors recorded data pertaining to strain, compression, temperature, crack detection, moisture presence, fluid mobility, shock resistance, monolith movement, and electrical resistivity. In addition, FIU regularly observed the curing process of the grout and documented the cube condition via the nine racks of sensors. The sensors held up throughout the curing process, withstood the natural elements for six months, and monitored the integrity of the grout. The large scale experiment and demonstration conducted at FIU was the first of its kind to demonstrate the feasibility of state of the art sensors for in situ decommissioning applications. These efforts successfully measured the durability, performance, and precision of the sensors in question as well as monitored and recorded the curing process of the selected grout material under natural environmental conditions. The current energy analysis work is resulting in data on the constraints placed by some of the sensor systems on a power network that requires high reliability and low losses. In addition, a sensor system demonstration has determined that it is feasible to develop an integrated data network where data can be accessed in near real-time from all systems, thereby allowing for larger-scale integrated system testing to be performed. Information collected during the execution of this research project will aid decision makers in the identification of sensors to be used in nuclear facilities selected for in situ decommissioning. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Data for A Hybrid Biophysical-Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

AI/ML↗
DOE OSTI2023

Digital Twin for Hydropower System Object Modeling: Alder Dam (FY2023)

Hydropower is the world's largest source of renewable electricity, and hydropower plants are distributed all over the world. Typical major components of a hydropower plant are the governor, excitation, generator, thrust bearing, hydraulic turbine, transformer, the main lead, metering and control, tailwater depression, and dissolved oxygen. For each component, various measures are taken. The measurements are acquired by various heterogeneous systems, including standalone sensors, programmable logic controllers (PLC), Supervisory control and data acquisition (SCADA), Internet of Things (IoT), and data acquisition and integration platforms such as OSI/PI. The measured data are often archived within the plant by a data management platform, and many institutions have cloud-based archive systems, such as Hydropower Research Institution (HRI), U.S. Army Corps of Engineers (USACE), and Columbia River Data Access in Real Time (DART). Object Modeling is a general framework for designing information systems. It focuses on objects, the actions they perform, and the messages they send to one another to cause those actions to be taken. The major differences among object modeling, network modeling, data modeling, and process modeling are that in the first we focus on the actions in response to information, objects which form the system, the actions they perform, and how they pass information to one another, while in the second we concentrate on where, when and how much information is moved, while in the third we focus on what information is moved and where it is moved, while in the last we focus on how it is moved and when it is moved. Object modeling was developed basically as a method to develop object-oriented systems and to support object-oriented programming. It describes the static structure of the system. The object Modeling Technique is easy to draw and use. That is why we choose object modeling to connect physical hydropower plants to Digital Twin. It recognizes the objects and the relationship between them. It identifies the attributes and functions of each class. Dynamic Modeling: It explains how objects respond to events. Functional Modeling indicates the processes executed in an object and how data changes when it moves to objects. It has been used in many applications like telecommunication, transportation, etc.

13 HYDRO ENERGY↗
DOE OSTI2015

Engineering management challenges of the CIGeO Project - 15576

After being involved for years in the conceptual studies on the French Deep Geological Repository's (DGR) design for ANDRA, INGeROP (www.ingerop.com) is carrying out since 2012 the global project management and the technical integration of the preliminary, basic and detailed design of the Cigeo project, within the framework of GAIYA consortium. The article presents some particular organizational aspects that turned out to be more challenging than foreseen in the course of our activities. Starting from the presentation of real examples, some lessons learned are derived as well as practices of interest in solving analogue issues in similar projects, with focus on their application to the engineering phase of geological repositories in different countries. Finally, the paper concludes with some avenues for reflection on the 'reversibility' - including 'retrievability' - requirement asked for by the French public and government and its consequences on the engineering choices, on the expected lifetime of components and structures and on the (increased) complexity of CIGeO systems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗