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Under direction from the DOE Office of Electricity, Sandia National Laboratories performed testing of the Viziv system to evaluate the quality of the Zenneck surface wave and potential application to long range power transfer. This report documents the test methodology as well as the test results. This includes an analysis of prior test data collected by Viziv.
The U.S. Department of Energy and National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset is part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with other energy technologies. This dataset contains inputs and outputs from simulations of a floating marine hydrokinetic turbine over approximately half a tidal cycle (~6.6 hours). Inflow conditions were derived from field measurements in Alaska’s Cook Inlet and represent a tidal environment in which the current speed ramps from near 0 m/s to a peak of 3 m/s and back. The original acoustic doppler current profiler dataset is publicly available on the Marine and Hydrokinetic Data Repository. In a full tidal cycle, the flow reverses and the rotor would reorient; this reversal was not modeled. In the Cook Inlet campaign , turbulence intensity was similar in both directions. Two inflow cases are included. In the first case, labeled “raw” in the files, the measured current time series was used directly in the InflowWind module of OpenFAST. Speed and direction were applied as a function of time and elevation, uniformly in the horizontal direction. With full spatial coherence, this approach captures high turbulent variability and results in pronounced power fluctuations, so it is considered a conservative, near-worst-case representation of loading. In the second case, labeled “average” in the files, a 30-minute moving average was applied to extract the slowly varying mean speed. The residual fluctuations about this mean were used to generate spatially varying, full-field turbulence inputs with TurbSim, giving a more physically realistic representation of the inflow across the rotor disk. Two random realizations were used to produce distinct inflow conditions for two OpenFAST simulations representing a two-turbine array. The same turbulence intensity is applied across the full time series, producing larger fluctuations at the start and end, where the mean speed is low. The second case is the more appropriate framework for performance and power assessment but overpredicts turbulence at lower flow speeds and underpredicts it at higher speeds. As the floating platform moves and the rotor changes its x-position, Taylor’s frozen turbulence hypothesis used by InflowWind assumes a constant rather than a time-varying mean velocity, introducing some inaccuracy in the velocity plane sampling. The turbine modeled is the 500-kW Reference Model 1, a horizontal-axis two-bladed hydrokinetic turbine on a four-column floating semisubmersible substructure . Simulations were performed using OpenFAST v4.1 with the Reference Open Source Controller (ROSCO) v2.10. All input files required to reproduce the simulations are included. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel . This unit supports up to 2.5 MW, but NLR has only a single 1.25-MW stack. The datasets report hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. The system controls hydrogen production by varying direct current applied to the stack, from a maximum of 3,000 A to a minimum safe operating current of 300 A, or 10%. Because the current–voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The simulated tidal turbine time series data was translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz. Each zip file represents a single tidal electrolysis experiment and is named: {technology}_{inflow method}_{number of 500 kW tidal turbines connected} For instance, “tidal-500kW-RM1_average_2.zip” is a 6-hour experiment using the 500-kW tidal reference model, scaled by 2x (1-MW) to better match the electrolyzer maximum of 1.25MW, fed with the 30-minute moving average current case. Each zip folder contains the following files: A .csv file of raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power. A .csv file combines all tidal profiles as "combined_tidal_experiments.csv." A separate experiment, “characterization_200.zip,” shows the MC250 electrolyzer steady-state response with 30-minute load steps over 5 hours and is accessible with this entry.
This paper presents the electrical characterization and drive cycle--based thermal analysis of an insulated metal substrate (IMS)--based silicon carbide power module for high-power traction inverters. The substrate was constructed using a thin layer of polymer--ceramic blend dielectric material with a thick copper core to improve transient thermal performance. The cooling performance of this module has already been validated with promising results. In this paper, an experimental test bed was set up to evaluate the dynamic and static electrical performance of the designed module under a wide range of operating conditions. The characterization results were then used to develop a drive cycle--based thermal model to validate the performance compared to the traditional direct bonded copper--based power module. The results indicate that the IMS-based power module is a suitable solution for high-power traction applications.
Though the convex optimization has been widely used in power systems, it still cannot guarantee to yield a tight (accurate) solution to some problems. To mitigate this issue, this paper proposes an ensemble learning based convex approximation for alternating current (AC) power flow equations that differs from the existing convex relaxations. The proposed approach is based on three-phase quadratic power flow equations in rectangular coordinates. To develop this data-driven convex approximation of power flows, the polynomial regression (PR) is first deployed as a basic learner to fit convex relationships between the independent and dependent variables. Then, ensemble learning algorithms such as gradient boosting (GB) and bagging are introduced to combine learners to boost model performance. Based on the learned convex approximation of power flow, optimal power flow (OPF) is formulated as a convex quadratic programming problem. The simulation results on IEEE standard cases of both balanced and unbalanced systems show that, in the context of solving OPF, the proposed data-driven convex approximation outperforms the conventional semi-definite programming (SDP) relaxation in both accuracy and computational efficiency, especially in the cases that the conventional SDP relaxation fails
This project aimed to design and manufacture a low-cost and high-performance, particle–to–sCO 2 heat exchanger (HX) for Concentrated Solar Power (CSP) using additive manufacturing (AM). Three enabling technologies will be integrated to achieve the targeted cost and performance. The first technology is the extreme high‐speed laser materials deposition (LMD) AM process known by its German acronym EHLA that was invented at the Fraunhofer Institute for Laser Technology. The EHLA process utilizes a specially designed powder-feeding nozzle that enables a laser to melt the powder particles above the melt pool, in contrast to the conventional LMD process where the powders are melted inside the melt pool. EHLA enables much faster deposition rate than conventional LMD without the need to wait for the powders to melt. The second technology is an innovative double-helical HX geometry that can be easily fabricated using the EHLA process by rotating a rod at a high-speed to take advantage of the high EHLA deposition rate. The double-helical fins separate the hot region (the hot particle side) and the cold region (the sCO 2 side) and provide large heat transfer surface area without a large pressure drop on the sCO 2 side. The particle side will have a larger gap to facilitate the particle flow. The outer rims of the double helixes can be sealed off using the same AM process. After sealing-off, additional double helixes can be built radially on top of the first set to improve HX performance. The HX can be installed vertically for gravity-driven flow of the hot particles if necessary. The third technology is a low-cost high-temperature alumina-forming austenitic (AFA) steel TMA-6350 that has creep and oxidation resistance up to 1100 °C. These technologies together will enable high-performance and low-cost HXs for particle–to–sCO 2 for CSP.
Water-gas shift (WGS) reaction followed by carbon dioxide (CO 2 ) separation is a critical step in the integrated gasification combined cycle (IGCC) process for fossil-fuel-fired electrical power generation with CO 2 capture. To intensify the IGCC process hydrogen-permselective zeolite membrane reactor offers promise to replace the conventional energy-intensive fixed-bed reactors and solvent-based CO 2 capture units. The objectives of this project were to develop a bench-scale zeolite membrane reactor (total membrane area: 932 cm 2 for a 21-tube membrane bundle) for the water-gas-shift reaction of raw syngas from an oxygen-blown coal-gasifier for H 2 production with simultaneous CO 2 separation at the capability of about 2 kilograms H 2 per day (equivalent to 2 kW IGCC power plant) and to demonstrate significant progress toward achieving overall performance goal of 90% CO 2 capture rate with 95% CO 2 purity at the cost of electricity 30% less than the baseline carbon capture approaches. This report summarizes results obtained in this project on scaling up the zeolite membrane reactor by a factor of 200 in membrane area, tests of the bench-scale zeolite membrane reactor for the water-gas-shift reaction at high temperature and high-pressure, and techno-economic analysis of the integration of the zeolite membrane reactor in IGCC power plant for the electrical generation with CO 2 capture. With effective pore modification by catalytic cracking deposition of MDES (methyldiethoxysilane), fabrication of MFI-type zeolite membranes was successfully scaled-up from a lab-scale disk type to bench-scale multiple-tube bundles on low-cost alumina supports. A Co-Mo based sour shift catalyst was evaluated and used in the zeolite membrane reactors for water-gas-shift reaction. The reaction kinetic and gas-permeation equations were developed and employed in mathematic models to guide/predict experiments/performance of zeolite membrane reactors for water-gas shift reaction. Multiple-tube zeolite membrane bundles and reactors were designed, fabricated and tested for gas separation and water-gas-shift reactions with real raw syngas from a coal-fired gasifier operated at high temperature and pressure. The zeolite membrane reactors demonstrated good long-term thermal and chemical stability and constant H 2 permeance (>300 GPU) together with a Knudsen selectivity (~4.7) for H 2 over CO 2 in the field test (cumulative time >28 hours) with high-sulfur coal-derived syngas. The zeolite-membrane-reactor integrated IGCC process was designed using the performance experimentally measured by the University of Cincinnati team with a single-tube zeolite membrane reactor that offers a CO conversion >98% with more than 90% of CO 2 and H 2 captured. With the above integrative approaches, a techno-economic analysis for a cost-benefit comparison was performed to uncover features that determine the power output, capital expenditure, operating expenditure, cost of electricity and cost of CO 2 capture in a 550-MW zeolite-membrane-reactor integrated IGCC process. The integration of the zeolite membrane reactor in IGCC could provide a significant reduction of 80% and 27% in the power consumption for Selexol™ Acid Gas Removal and CO 2 compression, respectively, which lowers the total auxiliary power consumption by 12.5%. However, the low pressure required at permeate stream for maintaining the driving force of hydrogen permeation through the zeolite membrane costs a huge power in permeate compressor, compensating the power consumption reduction achieved with the membrane reactor. Thus, for coal-fired IGCC for electricity generation with 90% CO 2 captured, the integration of the membrane reactor could provide a CO conversion ~99% and a significant drop in cost-of-electricity using zeolite membrane with H 2 permeance >600 GPU and the H 2 /CO 2 selectivity over 70.
This report documents the Resilience Enhancements through Deep Learning Yields (REDLY) project, a three-year effort to improve electrical grid resilience by developing scalable methods for system operators to protect the grid against threats leading to interrupted service or physical damage. The computational complexity and uncertain nature of current real-world contingency analysis presents significant barriers to automated, real-time monitoring. While there has been a significant push to explore the use of accurate, high-performance machine learning (ML) model surrogates to address this gap, their reliability is unclear when deployed in high-consequence applications such as power grid systems. Contemporary optimization techniques used to validate surrogate performance can exploit ML model prediction errors, which necessitates the verification of worst-case performance for the models.
The radiated power distribution is a crucial aspect of heat transport, heat load mitigation, and plasma exhaust performance. An imaging video bolometer camera has been installed to measure the plasma radiated power in the divertor region of the Wendelstein 7-X (W7-X) stellarator. This diagnostic offers a wide-angle (40° × 68°) sampling of the plasma volume in both the poloidal and toroidal directions. The field-of-view is covered with a large number (> 500) of bolometer channels, providing imaging capability. The diagnostic design is introduced here together with its data analysis procedure. A set of laboratory experiments is performed to assess the thermal properties of the gold absorber foil and their spatial uniformity. Following installation, a heat source originating from the inertially cooled front of the diagnostic is identified and filtered out. The discharge data indicate a satisfactory signal-to-noise ratio as well as spatiotemporal resolution. These represent the first toroidally resolved images of the line-integrated radiated power in the W7-X island divertor. The diagnostic was then upgraded with a thinner platinum absorber and adjusted mirrors. Early data from the most recent experimental campaign employing the upgraded design show a considerable improvement in the diagnostic performance with more bolometer channels (> 1400), extended coverage, and increased spatial resolution.
Hydrogen fuel cell-powered off-road vehicles can replace hydrocarbon-powered off-road vehicles to reduce carbon dioxide and criteria pollutant emissions in the agriculture, construction, and mining industries. Vehicle manufacturers and customers recognize health and environmental benefits of emissions reductions but are ultimately compelled by the total cost of ownership of their vehicles. In this study, we conduct a technoeconomic evaluation for three hallmark off-road vehicles, tractors, wheel loaders, and excavators, comparing vehicles with hydrogen fuel cell + battery hybrid powertrains to traditional diesel powertrains. Stakeholder-valued performance metrics include fuel cell engine power, engine durability, hydrogen consumption rate, hydrogen storage system volume, and energy-regenerative drivetrain efficiency. The total cost of ownership includes capital, operating and maintenance, fuel, and fuel storage costs. State-of-the-art fuel cell powered wheel loaders and excavators are currently cost competitive with diesel platforms. If targeted improvements to cost, performance, and durability improvements of fuel cell stacks and storage systems are achieved, fuel cell systems would be cost competitive for tractors and significantly lower total cost of ownership options for wheel loaders and excavators.
The tritium aspects of the DT fuel cycle embody some of the most challenging feasibility and attractiveness issues in the development of fusion systems. The review and analyses in this paper provide important information to understand and quantify these challenges and to define the phase space of plasma physics and fusion technology parameters and features that must guide a serious R&D in the world fusion program. We focus in particular on components, issues and R&D necessary to satisfy three 'principal requirements': (1) achieving tritium self-sufficiency within the fusion system, (2) providing a tritium inventory for the initial start-up of a fusion facility, and (3) managing the safety and biological hazards of tritium. A primary conclusion is that the physics and technology state-of-the-art will not enable DEMO and future power plants to satisfy these principal requirements. We quantify goals and define specific areas and ideas for physics and technology R&D to meet these requirements. A powerful fuel cycle dynamics model was developed to calculate time-dependent tritium inventories and flow rates in all parts and components of the fuel cycle for different ranges of parameters and physics and technology conditions. Dynamics modeling analyses show that the key parameters affecting tritium inventories, tritium start-up inventory, and tritium self-sufficiency are the tritium burn fraction in the plasma (f b ), fueling efficiency (η f ), processing time of plasma exhaust in the inner fuel cycle (t p ), reactor availability factor (AF), reserve time (tr) which determines the reserve tritium inventory needed in the storage system in order to keep the plant operational for time t r in case of any malfunction of any part of the tritium processing system, and the doubling time (t d ). Results show that η f f b > 2% and processing time of 1–4 h are required to achieve tritium self-sufficiency with reasonable confidence. For η f f b = 2% and processing time of 4 h, the tritium start-up inventory required for a 3 GW fusion reactor is ~11 kg, while it is <5 kg if η f f b = 5% and the processing time is 1 h. To achieve these stringent requirements, a serious R&D program in physics and technology is necessary. The EU-DEMO direct internal recycling concept that carries fuel directly from the plasma exhaust gas to the fueling systems without going through the isotope separation system reduces the overall processing time and tritium inventories and has positive effects on the required tritium breeding ratio (TBR R ). A significant finding is the strong dependence of tritium self-sufficiency on the reactor availability factor. Simulations show that tritium self-sufficiency is: impossible if AF < 10% for any η f f b , possible if AF > 30% and 1% ≤ η f f b ≤ 2%, and achievable with reasonable confidence if AF > 50% and η f f b > 2%. These results are of particular concern in light of the low availability factor predicted for the near-term plasma-based experimental facilities (e.g. FNSF, VNS, CTF), and can have repercussions on tritium economy in DEMO reactors as well, unless significant advancements in RAMI are made. There is a linear dependency between the tritium start-up inventory and the fusion power. The required tritium start-up inventory for a fusion facility of 100 MW fusion power is as small as 1 kg. Since fusion power plants will have large powers for better economics, it is important to maintain a 'reserve' tritium inventory in the tritium storage system to continue to fuel the plasma and avoid plant shutdown in case of malfunctions of some parts of the tritium processing lines. But our results show that a reserve time as short as 24 h leads to unacceptable reserve and start-up inventory requirements. Therefore, high reliability and fast maintainability of all components in the fuel cycle are necessary in order to avoid the need for storing reserve tritium inventory sufficient for continued fusion facility operation for more than a few hours. The physics aspects of plasma fueling, tritium burn fraction, and particle and power exhaust are highly interrelated and complex, and predictions for DEMO and power reactors are highly uncertain because of lack of experiments with burning plasma. Fueling by pellet injection on the high field side of tokamak has evolved to be the preferred method to fuel a burning plasma. Extrapolation from the DIII-D penetration scaling shows fueling efficiency expected in DEMO to be <25%, but such extrapolations are highly uncertain. The fueling efficiency of gas in a reactor relevant regime is expected to be extremely poor and not very useful for getting tritium into the core plasma efficiently. Gas fueling will nonetheless be useful for feedback control of the divertor operating parameters. Extensive modeling has been carried out to predict burn fraction, fueling requirements, and fueling efficiency for ITER, DEMO, and beyond. The fueling rate required to operate Q = 10 ITER plasmas in order to provide the required core fueling, helium exhaust and radiative divertor plasma conditions for acceptable divertor power loads was calculated. If this fueling is performed with a 50–50 DT mix, the tritium burn fraction in ITER would be ~0.36%, which is too low to satisfy the self-sufficiency conditions derived from the dynamics modeling for fusion reactors. Extrapolation to DEMO using this approach would also yield similarly low burn fraction. Extensive analysis presented shows that specific features of edge neutral dynamics in ITER and fusion reactors, which are different from present experiments, open possibilities for optimization of tritium fueling and thus to improve the burn fraction. Using only tritium in pellet fueling of the plasma core, and only deuterium for edge density, divertor power load and ELM control results in significant increase of the burn fraction to 1.8–3.6%. These estimates are performed with physics models whose results cannot be fully validated for ITER and DEMO plasma conditions since these cannot be achieved in present tokamak experiments. Thus, several uncertainties remain regarding particle transport and scenario requirements in ITER and DEMO. The safety standard requirements for protection of the public and release guidelines for tritium have been reviewed. General safety approaches including minimizing tritium inventories, reducing tritium permeation through materials, and decontaminating material for waste disposal have been suggested.
Power systems with high penetrations of renewable energy (e.g., wind power) require sophisticated approaches to optimize system performance due to uncertainty in short-term system generation capacity. In this paper, we combine a data-driven analog scenario selection method with importance sampling to create a novel scenario construction approach for two-stage stochastic economic dispatch problems with a large number of wind farms on a network. The proposed method produces scenarios with realistic physics by finding high-fidelity analogs that can describe future states of the system. We show how to extend this method to multi-period operations and demonstrate the effectiveness of this technique by simulating economic dispatch operations on a synthetic test system over the course of a week.
Rotary power take-offs (PTOs) promise many benefits for commercial wave energy converters (WECs), including longer power strokes/reduced end-stop concerns, deployment advantages, and controllability. However, these winch-type PTOs can impose millions of bending cycles on the belt or rope element every year, which may lead to a failure mode known as Cyclic Bend Over Sheave, or “CBOS”. Synthetic rope, though attractive due to its high strength, low elongation, and durability, suffers from comparatively poor CBOS performance and struggles to reach a million load cycles without failing. Using belts instead of ropes for winching elements should improve CBOS performance due to having a smaller thickness that undergoes bending. Unfortunately, belts have their own host of problems. Maintaining even tension across the width of a belt subject to twist or fleet angles is a challenge, especially for WECs which can move in all 6 degrees of freedom in the ocean. This study sought to quantify the CBOS performance of a belt constructed of steel tension members in a polyurethane matrix containing longitudinal profiles. Belt samples were tested to failure or up to two million bend-unbend cycles and subject to a range of fleet angles. This paper summarizes the utilized testing methodology and the resulting belt performance.
Various spectral control techniques can be applied to improve the performance of a thermophotovoltaic (TPV) device. For example, a back surface reflector (BSR) is a common structure to improve the performance of TPV devices. A conventional metal BSR structure enhances the photogeneration rate by increasing the absorption probability of photons via back surface reflections, affording a second chance for absorption. However, the effects of surface passivation and external luminescence introduced by BSR structures have been previously ignored, which potentially decreases the performance of TPV devices. Recently, a back gapped reflector (BGR) structure was proposed to greatly improve the performance of far-field TPV devices by reducing imperfect reflections at the semiconductor-metal interface. In the present work, the performance improvement on a thin-film, near-field InAs TPV device with a BGR is investigated, comparing its performance to that with a conventional metal BSR. Surface passivation conditions are also investigated to further improve the performance of TPV devices with back reflectors. Further, the output power and efficiency are calculated using an iterative model combining fluctuational electrodynamics and the full drift diffusion model. For the well-passivated condition, when the BSR is replaced by the BGR, the calculated conversion efficiency of the near-field TPV was improved from 16.4% to 21% and the output power was increased by 10%. Finally, the absorption of the back reflectors and external luminescence loss are analyzed to explain the performance improvement.
Recent progress in developing and implementing Pt-alloy cathode catalysts and thin (10-15 micron) low resistance membranes has enabled high performance state of art (SOA) membrane electrode assembly (MEA) with low Pt loading. However, these high performing MEAs do not meet durability requirements, especially at peak power, because of complex degradation mechanisms that are sensitive to the materials, MEA design, and fuel cell operating strategy. Specifically, power degradation of the cathode occurs via Pt and Co dissolution as well as deterioration of O 2 transport properties. Additionally, thin membranes are subject to failure due to manufacturing defects in the adjacent gas diffusion media and electrodes and the formation of membrane-attacking radical species caused by high gas crossover. In this project led by General Motors LLC (GM), the objective was to enhance the durability of SOA MEA through optimization of operating conditions, instead of new materials development. Along with our project partners, we have mapped the impact of operating conditions on the durability of SOA MEA. Output of the project include a low Pt loading SOA MEA that exceeds Department of Energy (DOE) 2020 target of >1 W/cm 2 at rated power and pathway to achieve >5000 h of durability. Durability studies in the project provide a detailed understanding of failure modes and operating condition sensitivity on cathode and membrane failure, critical for defining operating conditions and hybridization strategies that can guide system controls to maximize low-Pt MEA life. The project also generated and validated degradation models that will provide future research direction, critical for guiding future cycles of automotive MEA development.
As the U.S. grid evolves toward a lower-carbon system, fossil generation assets need to operate in energy markets with high variable renewable energy (VRE) penetration while also decreasing carbon emissions. Current carbon capture and storage (CCS) technologies suffer from high capital cost and an inability to operate flexibly during periods of oscillating demand. The ARPA-E FLECCS Program Phase 1 was created to fund designing and optimizing innovative CCS processes that enable flexibility on a high-VRE grid. To address this need, the Colorado State University (CSU) Team won funding to design a synergized system of thermal energy storage, power generation, and flexible carbon capture to enable breakthrough system performance that achieves an LCOE <$75/MWh with >99% capture rate. This approach will target new or existing natural gas combined cycle power plants. The proposed design utilizes novel hot and cold thermal energy storage (TES) technologies that store low-cost, off-peak electricity as thermal energy to power CCS solvent regeneration and boost plant output during periods of peak demand. The design provides an overall optimized net present value (NPV) by maximizing low carbon power to grid while prices are highest using Storworks Power’s concrete TES technology. The team also capitalizes on decades of ION Clean Energy’s (ION) development in low cost and flexible pioneering solvent technology, which has proven reductions in energy consumption and overall cost of 28% and 38%, respectively, compared with state-of-the-art CCS.
This report documents activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2023 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective, and secure DI&C technologies for digital upgrades/designs. A risk assessment-informed framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk informed capability to quantitatively estimate the safety margin obtained from plant modernization, especially for safety-related DI&C systems, (2) support and supplement existing risk informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of safety-related DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the LWRS-developed framework provides a means to address relevant technical issues by: (1) defining a risk informed analysis process for DI&C upgrade that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies in nuclear power plants (NPPs). Adding diversity within a system or components is the primary means to eliminate and mitigate CCFs, but diversity also increases system complexity and may not address all sources of systematic failures. Optimization of diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in safety-related DI&C systems of NPPs and supporting relevant design optimization, the proposed framework provides: (a) A best-estimate, risk informed capability to address new technical digital issues quantitatively, focusing on software CCFs in safety-related DI&C systems of NPPs; (b) A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to predict and prevent risk in the early design stage of DI&C systems; (c) Technical bases and risk informed insights to assist users address the risk informed alternatives for evaluation of CCFs in safety-related DI&C systems of NPPs; and (d) A risk informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The research and development efforts of this project in FY 2023 are focused on refining current methods on software CCF modeling and estimation and exploring additional innovative approaches to risk assessment of DI&C systems to enable a more comprehensive and complete assessment of various safety-related DI&C design architectures. The primary audience of this report are DI&C designers, engineers, and probabilistic risk assessment (PRA) practitioners. This includes stakeholders, such as the nuclear utilities and regulators who consider the deployment and upgrade of DI&C systems, DI&C software developers and reviewers, and cybersecurity specialists. It should be noted that all the analyses are performed for the demonstration of the methodology, not for the evaluation of an actual digital control system. Results are obtained based on limited design information and testing data.
This report summarizes the system-level modeling effort by Argonne National Laboratory (Argonne) of the Natural convection Shutdown heat removal Test Facility (NSTF) in FY22. As an extension of the effort from FY21, this year’s work focuses primarily on the two-phase modeling of the NSTF using RELAP5-3D, particularly with the inclusion of the cavity model. The results from simulations were used to compare against experimental data for benchmarking purposes of the RELAP5 deck. Additionally, RELAP5 was used as a predictive tool to guide planned test operations and identify expected system behaviors. In the first part of this report, details are provided of the cavity omitted model where heat flux is applied directly as a boundary condition to the risers. The general trend predicted by the RELAP5 model matches that from the experimental data when a single-phase natural circulation flow is first established, followed by an oscillatory two-phase period and finally a stable two-phase flow. However, the onset of oscillations is predicted early by the model due to the smaller thermal mixing region in the tank. However, by expanding the simulated thermal mixing region in the tank, the onset of oscillations predicted by the model is able to match that from the experiment. These oscillations where studied in depth and are deduced to be flashing-induced instability. The model was then modified to simulate an accident scenario case where a representative heat load based on the full-scale Framatome’s 625 MW t SC-HTGR was applied directly to the riser channels. The simulated initial and boundary conditions were identical to those performed experimentally, facilitating direct comparisons between the predicted and experimental results. It was determined that the results showed some discrepancies remain, likely due to the overprediction of vapor generation rate by the computer model. In the second part of this report, the cavity model is re-introduced where it is observed that the RELAP5 prediction is now able to capture the major trends of the observed flow commonly observed during two-phase conditions. However, the onset of oscillations is once again predicted early by the model, possibly caused by the underprediction of heat loss from the heater and cavity. This is likely due to the omission of support structures in the cavity that can act as additional pathways for heat to escape to the environment. To overcome the underprediction of heat loss, part of the insulation surrounding the cavity side panels and the back of the heaters are removed to allow heat to escape directly to the environment, which then improves the RELAP5 prediction. Parametric studies are also performed to investigate the effects of heater power, tank inventory level, and tank gas space pressure on flow behaviors, also in direct comparison to conditions tested experimentally. User option-61 in the RELAP5-3D input deck, which changes the heat transfer coefficient correlations used for calculating the vapor generation, is also investigated where it is found that by enabling the option, the overall duration of oscillations is increased and matches that from the experiment better. The RELAP5 model is further benchmarked with a header inlet- throttling case where it is observed that the prediction from the model fails to capture some major features observed in the experiment. By using a modified loss coefficient curve for the valve, the accuracy of the prediction is improved where most of the major features observed in the experiment are predicted by the model. Lastly, the model is benchmarked with an inventory depletion scenario where it is observed that despite the modeling limitation of RELAP5, the prediction shows good agreement with the experimental data where major trends and features are captured by the model. Future work will see continued development of the current RELAP5-3D input deck of the NSTF to both improve the accuracy of the model’s predictive capability and continuing serving the experimental program. The mutually beneficial relationship between analysis and experimental efforts has become integral to the parent NSTF program, and the greater objective to fully understand and accurately predict the heat removal performance of a full scale RCCS concept.
Marine and hydrokinetic (MHK) energy, including ocean waves, tidal current, ocean current and river current, has been recognized as a promising power source due to its full-day availability and high energy potential. At this stage, ocean current energy, tidal energy and ocean wave energy are currently the most competitive sourves among all the categories of MHK. The state of art MHK energy harvesting technology mainly focus on harvesting either ocean wave energy or current energy, but not both. However, a significant amount of ocean waves and tidal/ ocean current coexist in many sites and traditional devices that harvest from a single form of MHK energy, cannot make full use of the coexisting ocean energy. Furthermore, MHK energy harvesting devices need to advance to be cost-effective and competitive with other energy sources. This is difficult to achieve. Ocean wave excitation is irregular, which means that ocean wave height and wave periods are unpredictable and excitation forces on energy harvesting devices can have large variance in amplitude and frequency. Such problems/ restrictions can be possibly addressed by the concept of a hybrid energy converter. In this sense, a hybrid wave-current ocean energy conveter (HWCEC) that simutaneously harvests energy from current and wave with one single power takeoff (PTO) is designed.The wave energy is extracted through relative heaving motion between a floating buoy and a submerged second body, while the current energy is extracted using a marine current turbine (MCT). Energy from both sources are integrated by a hybrid PTO whose concept is based on a mechanical motion rectifier (MMR). In this study, different working modes are investigated together with switching criteria.Simulations were conducted with hydrodynamic coefficients obtained from computational fluid dynamics analysis and boundary element method. Tank tests were conducted for a HWCEC under coexisting wave and current inputs. For comparison, separate baseline tests of a turbine and a two-body point absorber, each acting in isolation, are conducted. Experimental results validate the dynamic modeling and show that a HWCEC can increase the output power with a range between 29-87 percent over either current turbine and wave energy converter acting individually, and it can reduce by up to 70 percent the peak-to-average power ratio compared with the wave energy converter on the tested conditions.Such results demonstrate the potential of the HWCEC as an efficient and cost-effective design.