Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “power plant model validation”

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 OSTI2022

Generation of group constants at GRS for the Rostov-2 benchmark

The OECD/NEA benchmark entitled 'Reactivity compensation of boron dilution by stepwise insertion of control rod cluster into the VVER-1000 core' aims at validating and assessing high fidelity multi-physics simulation code capabilities by comparison with the high-quality measurements performed at the nuclear power plant Rostov unit 2. The benchmark is divided into 2 phases: assembly wise and pin-by-pin resolution of the multi-physics problems. Multi-physics simulation requires the generation of an accurate parametrized few-group cross-section library, and so this benchmark offers an opportunity to validate the methodology for their generation. Based on the specifications of the benchmark, the core simulator KMACS developed at GRS was used to generate a library of cross-sections as well as the burnup distribution required to model the transient scenario of the benchmark at the assembly level. The assessment of the library is performed through comparison with measured values obtained at the initial state of the transient. Good agreement was obtained in terms of critical boron concentration, peaking factors and power profiles. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Renewable energy integration and system operation challenge: control and optimization of millions of devices

The electric power infrastructure, originally designed and built on large-scale power plants, is evolving into a more resilient power generation and delivery system in which millions of smaller units of distributed energy generation resources units will be installed in sub-transmission and distribution networks. In order to control, manage and optimize the future grid, a hierarchical design is presented in this chapter which enables the distributed control on grid edge while inheriting the existing centralized control structure. This layered design of large-scale power system operation and control uses the following principle: reactive power control is treated as a primary control for voltage stability, and the real power control is primarily a grid-level control but can also be a supplementary control for voltage support in the case of insufficient reactive power control capacity. For the purpose of active control and operation at the distribution level, a recursive power network model is derived from nodal injection and branch power flow models. Based on the model, the proposed algorithms of hierarchical control, grid-edge inference and dynamic hosting allowance are developed and presented for multi-level controlled operation. And, a co-simulation architecture of integrated T&D system is presented to validate and demonstrate the feasibility and scalability of proposed algorithms.

Xu, Ying↗
DOE OSTI2025

Integration of renewable energy generation and storage systems for emissions reduction in an islanded campus microgrid

Microgrid connected building communities are projected to play an integral part in the clean energy transition. These types of systems, when integrated with distributed energy resources (DERs) such as combined heat and power (CHP), district heating and cooling, renewable generation, and energy storage, can provide clean, reliable power to critical facilities and vulnerable communities. The intermittent nature of renewable generation is a challenge when integrating renewables into any grid system, but particularly in islanded microgrids. The University of Texas at Austin (UT) operates an islanded microgrid powered by a CHP plant, while also utilizing district heating and cooling systems and thermal energy storage (TES). High fidelity operating data was used to develop a validated reduced order model of UT’s integrated campus energy systems to serve as a testbed for use in a case study. Hypothetical renewable energy installations on land owned by UT in west Texas were modeled and integrated into the validated campus models along with battery energy storage (BES). Simulations showed that a combination of renewable energy from wind, and optimally controlled 24-hour thermal and battery storage systems could reduce carbon dioxide emissions on campus by 45.4%. The additional retrofit of burner systems to utilize hydrogen natural gas blends resulted in an overall annual emissions reduction of 54.7%. Carbon capture and storage eliminated the majority of the remaining emissions with increased plant energy expenditure. The presented simulations display the practical limitations of a CHP system complemented by renewable generation and short-term storage in eliminating emissions. Furthermore, results highlight the need for further research and development in long duration storage technologies and hydrogen fueled turbines to increase penetration of renewable energy and reduce emissions.

CHP↗
DOE OSTI2026

Applying Particle Swarm Optimization and Extended Kalman Filtering to Model Kaplan Generation Dynamics for Hydropower Systems

Variable renewable generation is increasing the need for hydropower plants to provide fast and flexible grid support, which places new demands on plant-level dynamic models used for monitoring, control, and operational decision-making. This need is especially important for hydroelectric systems, where turbine and generator dynamics are strongly coupled, nonlinear, and time-varying, making accurate real-time representation difficult. To address this problem, this paper develops a digital twin (DT) framework for a synchronous generator–Kaplan turbine system using an explicit separation of slow turbine dynamics and fast generator dynamics. The turbine subsystem is represented by a six-coefficient model, whose parameters are identified offline using particle swarm optimization, while the generator subsystem is updated online through an extended Kalman filter for real-time state and parameter estimation. These models are integrated within a closed-loop simulation that includes a proportional–integral–derivative–double-derivative governor and excitation system, allowing the DT to track plant behavior under realistic operating conditions. Unlike prior studies that treat turbine and generator modeling separately or rely mainly on simulated inputs, the proposed framework is validated using real operational data from a hydropower plant. Results show that the DT reproduces terminal voltage, active power, and reactive power with a normalized root mean square error of approximately 5%. This hybrid offline–online formulation constitutes the main contribution of the work, providing an adaptive and practically deployable DT for hydropower systems with direct relevance to control improvement, performance monitoring, and grid-support applications under high renewable penetration.

13 HYDRO ENERGY↗
DOE OSTI2021

Operating Characteristics of Metal Hydride-Based Solar Energy Storage Systems

Thermochemical energy storage systems, based on a high-temperature metal hydride coupled with a low-temperature metal hydride, represent a valid option to store thermal energy for concentrating solar power plant applications. The operating characteristics are investigated for a tandem hydride bed energy storage system, using a transient lumped parameter model developed to identify the technical performance of the proposed system. The results show that, without operational control, the system undergoes a thermal ratcheting process, causing the metal hydride concentrations to accumulate hydrogen in the high-temperature bed over time, and deplete hydrogen in the low temperature. This unbalanced system is compared with a ’thermally balanced’ system, where the thermal ratcheting is mitigated by thermally balancing the overall system. The analysis indicates that thermally balanced systems stabilize after the first few cycles and remain so for long-term operation, demonstrating their potential for practical thermal energy storage system applications.

25 ENERGY STORAGE↗
DOE OSTI2023

SAS4A/SASSYS-1 Validation with EBR-II Tests Performed During the SHRT Testing Program (Rev. 2)

The EBR-II sodium-cooled fast reactor supported a wide range of fast reactor research activities. The final fifteen years of operations at EBR-II were used for experiments and tests to demonstrate the importance of passive safety in liquid metal reactors and the capability of such systems to provide strong passive responses during off-normal conditions. The Shutdown Heat Removal Test program at EBR-II provided test data supporting the validation of computer codes for design, licensing, and operation of LMRs, among other objectives. The program included nearly sixty tests, most of which were protected and unprotected loss of flow and loss of heat sink tests run at various initial powers and flow rates. This report documents the results of modeling and simulation of tests from the Shutdown Heat Removal Test program to support validation of Argonne’s SAS4A/SASSYS-1 fast reactor safety analysis code. SHRT-17 and SHRT-6 were protected loss of flow tests where a loss of electrical power to all sodium coolant pumps was simulated to demonstrate the effectiveness of natural circulation cooling characteristics. SHRT-45R, SHRT-39, and SHRT-43R were unprotected loss of flow tests where the control rod scram function of the plant protection system was disabled to demonstrate the effectiveness of EBR-II’s passive reactivity feedbacks. BOP-301 and BOP-302R were unprotected loss of heat sink tests that demonstrated how reactivity feedback effects driven by changes to the core inlet temperature can shut down the fission process. PICT-5/6 demonstrated how core power could be increased and decreased via changes in the intermediate sodium and feedwater flow rates. This validation activity leverages modeling and simulation efforts that originated under an International Atomic Energy Agency Coordinated Research Project for benchmark analysis of the EBR-II Shutdown Heat Removal Tests. The SAS4A/SASSYS-1 models originally developed for the CRP have been modernized to utilize new code features and modeling practices. Differences between the predicted and measured test data were explored and the causes of these differences were identified as being due to modeling approximations, uncertainty in transient component behavior, and instrumentation uncertainties. Overall, it was concluded that for all tests simulated there was good agreement between the flow, power, and temperature predictions and the measured data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

A Qualitative Strategy for Fusion of Physics into Empirical Models for Process Anomaly Detection

To facilitate the automated online monitoring of power plants, a systematic and qualitative strategy for anomaly detection is presented. This strategy is essential to provide credible reasoning on why and when an empirical versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. Empirical methods are usually based on pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The presented strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability, and suitability for training and testing, cause-effect, entropy inference, and model fitting. The strategy is demonstrated through a pilot use case for the application of anomaly detection to capture a valve packing leak at the high-pressure coolant injection system of a nuclear power plant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Design and Operability of a Pressurized Oxy Combustion System

Fossil fuel powers more than two-thirds of the world’s electricity, a significant share of which is derived from coal power plants. Despite coal being an abundant and energy-rich fuel, the major halt to its progress is greenhouse gas emissions. Pressurized oxy-combustion cycles can achieve theoretically high thermal efficiencies along with a 90% carbon capture rate. Additionally, the high energy density allows smaller turbomachinery and save capital cost. Thus, the primary objective of this dissertation is to present the design and operability of a pressurized oxy-combustor system. The initial part of the dissertation investigates different thermodynamic cycles and presents a model that can be adapted for existing power plants. The thermodynamic model will be used in the later part to design the proposed combustor. The two cycles analyzed are ENEL and TIPS. This study focuses on qualitative analyses of the cycles using a commercially available software called Aspen Plus®. A detailed benchmark study has been performed to validate the modeling process. ENEL and TIPS cycles are designed in the software, adopting the same principles. Recirculation ratio and pressures are varied to find the efficiency range of the cycles. Power calculations are done to find overall and net efficiency for a fixed recirculation ratio. The efficiencies of the cycles are compared to select an optimum cycle. A recirculation ratio of 50% is selected for implementation. The comparison shows that ENEL is marginally efficient over TIPS, at the cost of a pressure difference of about 70bars. Technology Readiness Level analysis is performed to present the availability of the specialized equipment for the cycles. From the TRL analysis, it is seen that the cost and availability of high viii pressure equipment surmount the edge of TIPS over ENEL. Thus, ENEL is chosen as the better cycle for investigating a scaled experiment considering efficiency and viability. The later part of the dissertation focuses on developing the combustor's design for a pressurized oxy-combustion cycle. The proposed combustor is a powerhead-mounted design aimed to produce 1MW of thermal outputThe different aspects of the design of a down-fired pressurized swirl combustor are presented in this dissertation.

Chowdhury, Mehrin↗
DOE OSTI2024

Photovoltaic inverter-based quantification of snow conditions and power loss

Snow is a significant challenge for photovoltaic (PV) systems at northern latitudes, where the pace of deployment is rapid but snow-related power losses can exceed 30% of annual production. Accurate snow-related power loss estimation methods for utility-scale sites can support snow mitigation strategies, inform resource planning and validate predictive snow-loss models. This study builds on our previous work on inverter-based detection of snow, and its implications for utility-scale power production, by validating the accuracy of our snow-loss method across different PV sites and system designs and highlighting its value in bringing greater visibility to PV plant operations in winter. Our estimation method is both novel and scalable, requiring only standard monitoring data to correlate snow-related losses with meteorological data. As demonstrated here, our validation method involved three main steps: 1) estimation of performance losses for multiple systems by comparing measured inverter data to modeled data; 2) application of a detection framework to identify which performance losses are snow-related; and 3) comparison of snow-related losses among three utility-scale sites differing in tilt angle. Results show that utility-scale systems at higher tilt angles consistently shed snow more quickly/completely than their lower-tilt counterparts. Further, monthly and seasonal snow losses are inversely and non-linearly correlated with tilt angle when normalized for cumulative snowfall. These results are consistent with the findings of previous studies and support the broad applicability of this method to fixed-tilt utility-scale PV systems around the world that routinely experience snow-related performance losses.

Cooper, Emma C. (ORCID:0000000190554098)↗
DOE OSTI2025

Machine learning modeling and model predictive control of a closed-circuit reverse osmosis system

Closed-circuit reverse osmosis (CCRO) offers a flexible and energy-efficient alternative to conventional reverse osmosis by operating in a semi-batch mode that recycles brine, enabling higher recovery rates and reduced specific energy consumption (SEC). However, developing accurate, system-level dynamic models for CCRO remains challenging due to its nonlinear, multi-phase operation and sensitivity to variable feed water conditions. Traditional modeling approaches, such as NARMAX (nonlinear autoregressive moving average with exogenous inputs), often struggle to generalize across varying inlet feed concentrations, necessitating frequent parameter re-estimation and limiting their utility for real-time control applications. To address these limitations, we developed a long short-term memory (LSTM) neural network model trained on an extensive experimental data set from a CCRO pilot plant. The model accepts three inputs, feed flow rate, recirculation flow rate, and initial feed conductivity, and predicts three key outputs: reject conductivity, feed pump power draw, and recirculation pump power draw. We validated the LSTM model against experimental data, demonstrating its ability to distinguish between different feed conductivities and adapt to variable flow rates. Subsequently, we incorporated the LSTM model within a nonlinear model predictive control (MPC) scheme and conducted closed-loop simulations to optimize the integrated SEC (iSEC). In conclusion, the results project up to a 6% reduction in iSEC by using MPC to optimize performance over the entire experiment duration, without requiring any random excitation for data collection or parameter re-estimation.

Desalination↗
DOE OSTI2024

Hydropower Black Start: A Guidebook for Retrofitting Grid Dependent Hydropower

Not all United States (US) hydropower plants were designed to provide black start, but they are increasingly needed to uphold resilience in the evolving electric grid. This guidance is designed to help understand the minimal retrofits required for grid dependent hydropower (GDH) plants behind the point of interconnection (POI). For distribution connected hydropower plants or those with dedicated cranking paths, such upgrades can be sufficient for the plant to provide black start. For others, more coordination with the transmission system operator will be needed. This guidebook answers a number of questions relevant to retrofitting hydropower plants with black start capabilities. For example, the guidebook answers: • How flexible do the wicket gate controls need to be? • Who needs to do hydro governor model validation, why, and how? • How robust and flexible do the excitation and AVR controls need to be? • What protection settings need to be adjusted? • What relay(s) will need to be bypassed or overridden and at what risk? • What is the electrical energy demand of the station load or auxiliary power systems? • What should the strategy to energize transformer(s) along cranking path to address inrush currents be? • How should the critical load restoration be sequenced? In addition to outlining the specifications that hydropower plants need to meet for each component to be able to perform black start, this guidebook provides a set of case studies for specific upgrades needed at actual plants. Between the case studies of plants that have already performed black start retrofits and the examples of how this guidebook can be applied to scope future retrofits, five key themes have been identified for retrofit needs. 1. Protection needs “black start” mode: hydropower plants that are not designed with black start capabilities will have protections that prevent them from interconnecting to a “dead bus.” These protections will need to be overridden in every retrofit case and a separate black start mode should be established so that operators can safely switch between black start and grid connected modes, minimizing the risk to the plant. 2. Wicket gates need modern controls: digital governors accelerate the parameter tuning process and gate position sensors improve controllability, so plants with mechanical governors should be upgraded. Furthermore, a black start and islanding mode should be established for controls to maximize plant performance. 3. Robust excitation support: the DC system or excitation generator needs to be reliable enough to form and sustain the rotor electromagnetic field. These systems are typically undersized in plants that were not designed for black start, so they will need to be upgraded. 4. Turbine-governor model validation and operator training: validation of a standard hydro governor model is needed to characterize the dynamic response (i.e., inertial and primary frequency response) of the GDH. This is required for control development and old hydropower plants often have outdated or incorrect models. Operator training is also typically required to ensure the hardware retrofits are utilized correctly during the black start process. 5. Transformer and cranking path energization: any upgradation and control adjustment in front of the POI will depend upon the existing interconnection. Coordination with the transmission or distribution operator may be required.

13 HYDRO ENERGY↗
DOE OSTI2022

Characterization of Long-Term Service Coal Combustion Power Plant Extreme Environment Materials

The objective of this DOE-sponsored project was to develop a comprehensive database of mechanical properties, alloy microstructures, and to a lesser extent, the oxidation/corrosion behaviors of coal-fired power plant components, such as boiler tubing, steam headers, and steam piping, which had been in service for at least 100,000 operating hours (preferably more than 200,000 operating hours) under the operating conditions of high temperatures and high mechanical stresses where creep, fatigue, steam-side oxidation, and fireside corrosion were life-limiting factors. The components included in this database consisted of ferritic steels, creep strength enhanced ferritic (CSEF) steels, and 300-series H-grade stainless steels, as well as dissimilar metal welds (DMWs) among these types of materials. As a result of extensive metallurgical characterization and mechanical testing performed in this project, a comprehensive database on mechanical properties and detailed quantitative microstructural information was successfully developed for several long-term serviced EEM components. Such a database can be used by material research communities to develop, calibrate, refine, and validate mechanical behaviors, models, and other assessment tools for accurate prediction of remaining life of major components under similar EEM operating conditions.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Hydrogen Production System Scaling Using a High-Fidelity Simulation-Optimization Framework

Proton exchange membrane (PEM) electrolyzers are widely used for hydrogen production, yet few validated, high-fidelity tools can reliably guide scale-up. Using measured performance from a 50-hour hardware-in-the-loop pilot test, a physics-based, plant-level model of a 1.25 MW PEM electrolyzer and its balance-of-plant (BoP) subsystems is developed and validated. The model couples electrochemistry and thermal/flow submodels and is calibrated against pilot test data via a genetic algorithm (GA) workflow. Validation yields a mean absolute percentage error (APE) of 0.43% for cell voltage and stack power. Two scale-out strategies are then benchmarked under a common 7-day wind-and-photovoltaic (PV) profile: (i) linear duplication of 1.25 MW blocks and (ii) shared-BoP architectures. Sharing BoP between stacks reduces BoP energy by 27% at 10 MW and 34% at 100 MW (vs. linear duplication) and improves system specific energy consumption (SEC) to 52.9 and 52.6 kWh/kg, respectively (from 54.0 kWh/kg with linear duplication). Partial-load studies (25-100% set-point) show that cumulative hydrogen production remains nearly constant down to 50% load because all cases use the same weekly renewable-energy input. Below 50%, the power cap limits how much energy can be used within 168 h, which reduces hydrogen output. The model further indicates that the practical operating optimum lies between 50% and 85% load, where efficiency gains begin to appear without significant loss in hydrogen output. Moreover, the efficiency gains at lower loads are offset by reduced production. The validated framework supports scenario-based engineering trade-off studies for large configurations (10-100 MW) and for operating policies under variable renewables.

08 HYDROGEN↗
DOE OSTI2024

Analysis of thermal and mechanical properties with inventory level of the molten salt storage tank in central receiver concentrating solar power plants

Molten salt thermal energy storage (TES) tanks ensure steady power output of concentrating solar power (CSP) plants; however, recent tank failures have highlighted the need for further analysis. Current studies primarily focus on analyzing the molten salt flow, heat transfer, and thermal efficiency. Additionally, research on the latest tank structures is limited and lacks newest experimental validation. This study measures temperature and molten salt inventory levels in the high-temperature tank at a 50 MW central receiver CSP plant, connected to the power grid in 2019. A multi-physics model was developed to evaluate thermal and mechanical properties of TES tanks by combining computational fluid dynamics and finite element modeling using real plant data. Heat loss, temperature, displacement, and stress distribution of the tank at different inventory levels were investigated. Results show that ambient air velocity near the tank roof reaches 2.14 m/s, much higher than 0.2 m/s near the wall. The temperatures of inventory fluid and tank are close, varying slightly at different levels due to thermal conduction and radiation. Because the heat loss strongly depends on temperature, the total tank loss remains nearly constant across inventory levels. Larger temperature gradients and thermal stresses are primarily localized along the tank floor edge and the air-salt interface. Notably, the maximum thermal stress at the tank edge is three times higher than that at the interface. The magnitude of total stress changes by less than 5 MPa with and without thermal load, indicating that high temperatures exert only a minor impact on tank stress. In contrast, thermal load significantly affects tank deformation, particularly at the roof edge, where values exceed 150 mm. Despite the large variation in molten salt levels, tank wall temperatures and displacements present a minor change, suggesting a weak correlation with inventory levels. In conclusion, the findings obtained in this study provide important insights on the TES tank that could be used to optimize tank design and operation strategies.

14 SOLAR ENERGY↗
DOE OSTI2022

Forecasted Dynamic Line Ratings for Regional Transmission Lines

This report was prepared for the Wind Energy Technology Office for the FY 2022, quarter 3 deliverable. This details the use of forecasted dynamic line rating as an improvement over static rating for three transmission lines in three regions of interest. A selection of wind plants across Idaho, the Columbia River Gorge and offshore wind in the NYSERDA territory were modeled for their concurrent cooling effects for dynamic line rating. Regional transmission lines for the wind plant interconnections were determined and a CFD domain was created to determine local wind flows over the lines. A dynamic line rating for each of the lines was calculated for both weather observation data and HRRR model forecast data. The comparison of peaks in the wind power production were compared to the DLR peaks. It was determined that for shorter regional transmission lines, the effect of concurrent cooling that commonly occur with gen-tie lines were still valid. Concurrent cooling effects drop as the length of the regional transmission lines increase in distance from the wind plants. In addition, the accuracy of the forecasted ampacity to the weather observation data for ampacity was assessed. In general, the accuracy was best for the INL region with the NOAA-maintained sites. The Columbia River Gorge and Long Island sites showed similar levels of accuracy for the forecasted DLR. The accuracy levels were around 11% for the INL region, 15% for Columbia River Gorge and 7% for New York Long Island. The higher error for the Columbia Gorge region is likely due to the sparse availability of weather stations available, whereas both the INL site and Long Island are well instrumented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2012

Data Assimilation of Photosynthetic Light-use Efficiency using Multi-angular Satellite Data: II Model Implementation and Validation

Spatially explicit and temporally continuous estimates of photosynthesis will be of great importance for increasing our understanding of and ultimately closing the terrestrial carbon cycle. Current capabilities to model photosynthesis, however, are limited by accurate enough representations of the complexity of the underlying biochemical processes and the numerous environmental constraints imposed upon plant primary production. A potentially powerful alternative to model photosynthesis through these indirect observations is the use of multi-angular satellite data to infer light-use efficiency (ε) directly from spectral reflectance properties in connection with canopy shadow fractions. Hall et al. (this issue) introduced a new approach for predicting gross ecosystem production that would allow the use of such observations in a data assimilation mode to obtain spatially explicit variations in ε from infrequent polar-orbiting satellite observations, while meteorological data are used to account for the more dynamic responses of ε to variations in environmental conditions caused by changes in weather and illumination. In this second part of the study we implement and validate the approach of Hall et al. (this issue) across an ecologically diverse array of eight flux-tower sites in North America using data acquired from the Compact High Resolution Imaging Spectroradiometer (CHRIS) and eddy-flux observations. Our results show significantly enhanced estimates of ε and therefore cumulative gross ecosystem production (GEP) over the course of one year at all examined sites. We also demonstrate that ε is greatly heterogeneous even across small study areas. Data assimilation and direct inference of GEP from space using a new, proposed sensor could therefore be a significant step towards closing the terrestrial carbon cycle.

Hilker, Thomas↗
DOE OSTI2024

Quantification of Residual Water in Spent Fuel Dry Storage Canisters Using Mass Spectrometry

The purpose of this report is to document updates on the apparatus to simulate commercial vacuum drying procedures at the Nuclear Energy Work Complex at Sandia National Laboratories. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system during subsequent storage and disposal, such as fuel degradation; cladding corrosion, embrittlement, or breaching; and the creation of a flammable environment via radiolysis of water. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates well-designed investigations of drying process efficacy and water retention. Scaled tests that incorporate relevant physics and well-controlled boundary conditions are essential to provide insight and guidance to the simulation of prototypic systems undergoing drying processes. This report documents details on the quantification of residual water in the Advanced Drying Cycle Simulator (ADCS), an apparatus built to simulate commercial drying procedures and quantify the amount of residual water remaining in a pressurized water reactor (PWR) fuel assembly after drying. The ADCS was constructed with a prototypic 17×17 PWR fuel skeleton and waterproof heater rods to simulate decay heat. The ADCS is outfitted with thermocouples to measure the thermal response of the ADCS to simulated decay heats and internal helium fill pressures relevant to commercial drying procedures. The ADCS is also instrumented with pressure transducers to measure the pressures and vacuum levels observed during simulated commercial drying. The most unique instrumentation used for quantifying residual water in the ADCS is a Hiden Analytical HPR-30 mass spectrometer (MS), which measures gas compositions of the ADCS internal free volume, based on partial pressures calculated from relative proportions of gas molecules detected by the MS. This report details the methodology used to implement MS measurements in quantifying residual water in the ADCS. This methodology includes the calibration of the HPR-30 MS to a Buck Research Instruments CR-4 chilled mirror hygrometer, which itself is calibrated to a NIST-traceable standard. Data collected by both the MS and the chilled mirror hygrometer from water/helium mixtures ranging from 150 to 500,000 ppmv water in helium were used to generate calibration curves, establishing a source of verification of MS measured water contents. Details regarding water content measurement uncertainties are included in this report, defining the accuracy and verifiability of the HPR-30 MS in measuring residual water content in simulated dry storage canister environments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Assessment of Mechanical Draft Cooling Tower Thermal Emissions from Visual Images of Plumes

Using a one-dimensional code, we computed the power (enthalpy discharge rate) of a twelve-cell mechanical draft cooling tower (MDCT) using over two hundred visible condensed water vapor plume volume measurements derived from images, weather data, and tower operating conditions. The plume images were simultaneously captured by multiple stationary digital cameras surrounding the cooling tower. An analysis technique combining structure from motion (SfM), a neural-network-based image segmentation algorithm, and space carving was used to quantify the volumes. Afterwards, the power output was computed using novel techniques in the one-dimensional code that included cooling tower exhaust plume adjacency effects implemented with a modified version of the entrainment function, weather data averaged from eleven stations, and fan operations at the times when plume volumes were measured. The model was then compared with the averaged observed power output, and it validated well with an average error ranging from 6 to 12%, depending on the meteorological data used in the simulations. This methodology can possibly determine power plant fuel consumption rates by applying visible imagery.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗