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At least 37 records · Page 2

Fast Quasi-Static Time-Series Simulation for Accurate PV Inverter Semiconductor Fatigue Analysis with a Long-Term Solar Profile

Power system simulations with long-term data typically have large time steps varying from one second to a few minutes. However, for PV inverter semiconductors, the minimum thermal stress cycle occurs over the fundamental grid frequency (50 or 60 Hz). This requires the time step of the fatigue simulation to be around 100 µs. This small time step requires long computation times to process yearly power production profiles. This paper proposes a fast fatigue simulation for inverter semiconductors using the quasi-static time series (QSTS) simulation concept. The proposed simulation calculates the steady state of the semiconductor junction temperature by using a Fast Fourier Transform (FFT). The small thermal cycling during a switching period and even over the fundamental waveform is disregarded to further accelerate the simulation speed. The resulting time step of the fatigue simulation is 15 minutes, which is consistent with the solar dataset. The error of the proposed simulation is 0.16% compared to the fatigue simulation results using the complete thermal stress profile. A PV inverter that responds to a Transactive Energy System (TES) is simulated to demonstrate the use of the proposed fatigue simulation. The proposed simulation has the potential to co-simulate with system level simulation tools that also adopt the QSTS concept.

Liu, Yunting↗

A New Perspective of Post-Weld Baking Effect on Al-Steel Resistance Spot Weld Properties through Machine Learning and Finite Element Modeling

The root cause of post-weld baking on the mechanical performance of Al-steel dissimilar resistance spot welds (RSWs) has been determined by machine learning (ML) and finite element modeling (FEM) in this study. A deep neural network (DNN) model was constructed to associate the spot weld performance with the joint attributes, stacking materials, and other conditions, using a comprehensive experimental dataset. The DNN model positively identified that the post-weld baking reduces the joint performance, and the extent of degradation depends on the thickness of stacking materials. A three-dimensional finite element (FE) model was then used to investigate the root cause and the mechanism of the baking effect. It revealed that the formation of high thermal stresses during baking, from the mismatch of thermal expansion between steel and Al alloy, causes damage and cracking of the brittle intermetallic compound (IMC) formed at the interface of the weld nugget during welding. This in turn reduces the joint performance by promoting undesirable interfacial fracture when the welds were subjected to externally applied loads. The FEM model further revealed that increase in structural stiffness, because of increase in steel sheet thickness, reduces the thermal stresses at the interface caused by the thermal expansion mismatch and consequently lessens the detrimental effect of post-weld baking on the joint performance.

36 MATERIALS SCIENCE↗

Development of Digital Twin Predictive Model for PWR Components: Updates on Multi Times Series Temperature Prediction Using Recurrent Neural Network, DMW Fatigue Tests, System Level Thermal-Mechanical-Stress Analysis

The long-term operation (LTO) of nuclear power plant (NPP) beyond their original design life of 40 years, can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Frequent NDE requirement may lead to frequent shutdown of the NPP. This in turn can lead to power outage and additional NDE-inspection-cost related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing more digital approach such as by using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. Towards this goal Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program is working on the development of a DT framework that can be used for real time environmental fatigue prediction of reactor components. The DT framework is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics such as finite element (FE) based modeling tools. Towards this overall goal, following are some of the major contributions made during the FY21: 1) Multiple 82/182 dissimilar metal weld (DMW) specimens (both solid-weld and joint-weld representing the actual reactor multi-metal nozzles) were fatigue tested. The resulting fatigue lives were compared to the NUREG-6909 based best-fit and design fatigue curves. Additionally, the results of 52/152 DMW fatigue specimens (which were recently tested at Republic of Korea under the sponsorship of International Nuclear Energy Research Initiative - INERI program) were compared to the NUREG-6909 based best-fit and design fatigue curves. From the comparison of 82/182 and 52/152 DMW test data with NUREG-6909 best-fit curve, most of the reported test data fall way away from the NUREG-6909 suggested best-fit or mean curve. The NUREG-6909 suggested best-fit curve is the best-fit curve of austenitic stainless steel and due to lack of enough data on Nickel-based welds, this is currently being used for predicting the life of Nickel-alloy-based welded components. However, the above observation may require higher scaling factor (e.g., ASME suggested factor of 20 on cycles rather than the current NUREG-6909 suggested factor of 12 on cycles) for scaling the austenitic-stainless-steel best-fit-curve for estimating the design or safe-life of a welded component. Accordingly, for example, if a DMW component experience a strain amplitude of 0.6% the PWR-water life of the component would be 52 cycles instead of 85 cycles. However, more DMW tests are required to further ascertain the above-mentioned observations. 2) A system level CAD and finite element model were developed which consists of reactor pressure vessel (RPV), part of steam generator (SG), part of pressurizer (PRZ), hot leg (HL), and surge line (SL). This is with detailed nozzle geometry and thermal-mechanical material properties of different metals to simulate realistic thermal-mechanical stress under connected system global thermal-mechanical boundary conditions. 3) Different system level heat transfer analyses were performed with estimation of relevant heat transfer coefficients. The resulting data were used in subsequent system level thermal-mechanical stress analysis and for generating spatial-temporal training and validation data for a system level digital-twin based temperature predictor. Transient heat transfer analyses were performed considering thermal boundary condition under design-basis (DB) loading and EDF (Électricité de France) data-based grid-load-following (EDF-GLF) loading cycles. 4) System level thermal-mechanical stress analysis was performed for identifying damage-prone hotspots and for future extension of the model for cyclic state prediction. From the system-level model simulation under DB loading cycle it is found that HL and the SL nozzle that connect to the HL can experience significant stress and strain and could be one of the weakest links in the overall reactor coolant system (RCS). 5) An AI/ML based DT model was developed for multi-time-series temperature prediction at any inside/outside thickness locations of PWR pressure boundary components. This is by using Recurrent-neural-network (RNN) and keras machine learning libraries. The RNN model was validated against two laboratory test-based data sets with one obtained through ANL’s in-air fatigue test system and other through PWR-water test loop. The experimentally validated DT model further validated against FE model results to predict thermal scarification related spatialtemporal temperatures at random locations of a component. The well validated DT model was then used for demonstrating spatial-temporal temperature prediction under 100+ years of reactor operation subjected to combined DB, EDF-GLF and randomized grid-load-following (RANDOMGLF) loading Cycles. The expert-elicitation DT model framework was developed assuming field/input/process measurements can be available from a few existing plant sensors and can readily be used by the NPP operators. The above temperature prediction model will feed to the next-step stress analysis model based on which the life of a component can be predicted in realtime, which is one of our future works.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Thermal and solubility effects on fault leakage during geologic carbon storage

Geologic carbon storage (GCS) is a promising method for reducing anthropogenic CO 2 emissions to the atmosphere. To safely deploy GCS in the field, it is necessary to assess risks and the effect of uncertainty on safe storage. The effect of uncertainty can be quantified using batches of simulations, but the high computational costs of high-resolution simulations necessitate use of reduced-order models (ROMs). Previous work involves ROMs for quantifying the risk of different potential leakage paths from storage reservoirs to shallow formations. However, previous studies on development of fault-leakage ROMs have limited numbers of uncertain parameters and do not explicitly examine impacts of CO 2 solubility and thermal stresses on fault reactivation, which can generate high-permeability pathways and compromise CO 2 storage. Here, we analyze an ensemble of simulations considering CO 2 leakage from a storage reservoir to a shallow aquifer through a fault while varying a number of uncertain parameters related to thermo-hydro-mechanical properties and CO 2 injection. We show the effects of solubility on: free-phase CO 2 -leakage rates, brine-leakage rates, and poroelastic fault destabilization. We find that CO 2 solubility is more important for estimating free-phase CO 2 -leakage rates compared to brine-leakage rates or poroelastic fault destabilization. We also find that thermal stresses and overpressures have different spatial distributions within the fault, indicating that the spatial variability of overpressures due to variation in flow parameters does not necessarily make the spatial variability of thermal stresses negligible. We suggest the use of the CO 2 phase-change path as a variable in future fault-leakage ROMs.

03 NATURAL GAS↗

Bulky Cation-Modified Interfaces for Thermally Stable Lead Halide Perovskite Solar Cells

Charged conjugated organic molecules offer promising prospects for reducing nonradiative recombination at interfaces in perovskite solar cells, while protecting the active layer from moisture. However, several studies have shown that the heat induced diffusion of these cations leads to irreversible solar cell degradation. Passivation molecules for perovskite can reconstruct the film surface into lower-dimensional phases when exposed to thermal stress, impeding charge extraction and affecting the photoconversion efficiency (PCE) of devices. In this work, we study how molecular interactions between passivation molecules and 3D CsFAPbI 3 perovskite impact stability and charge extraction at the perovskite/hole transport layer interfaces. Two model π- conjugated molecules are studied: 2-([2,2′-bithiophen]-5-yl)ethan-1-aminium iodide (2TI) and 2-(3‴,4′-dimethyl-[2,2′:5′,2″:5″,2‴- quaterthiophen]-5-yl)ethan-1-ammonium iodide (4TmI). We demonstrate that the speed of surface layer reconstruction under thermal stress can be controlled by the cation size and correlate these structural changes with the solar cell performance and stability. Devices treated with 2TI and 4TmI achieve PCEs over 21% and maintain their performance under thermal stress. Our findings demonstrate that thermal stability in PSCs can be achieved via the design engineering of passivation agents, offering a blueprint for developing next-generation passivation molecules.

36 MATERIALS SCIENCE↗

Scaling Behavior of Thermally Driven Fractures in Deep Low‐Permeability Formations: A Plane Strain Model With 1‐D Heat Conduction

Abstract Injection of cold fluids through/into deep formations may cause significant cooling, thermal stress, and possible thermal fracturing. In this study, the thermal fracturing of low‐permeability formations under one‐dimensional heat conduction was investigated using a plane strain model. Dimensionless governing equations, with dimensionless fracture length , aperture , spacing , time , and effective confining stress , were derived. Solution of single thermal fracture was derived analytically, while solution of multiple fractures with constant (or dynamic) spacing were obtained using the displacement discontinuity method (and stability analysis). For single fracture, increases nonlinearly with and then transitions to scaling law , indicating that late‐time fracture length increases linearly with the square root of cooling time. For constantly spaced fractures, deviates from the single‐fracture solution at a later for a larger , showing slower propagation under inter‐fracture stress interaction . For dynamically spaced fractures, fracture arrest induced by stress interaction was determined by the stability analysis; the fully transient solution provides evolution of dimensionless fracture length, spacing, aperture, and pattern; a similar scaling law, with , obtained shows the effect of both stress interaction and fracture arrest. The solution and scaling law provide fast predictions for all reservoir and cooling conditions using (single) model parameter . Application to a geothermal site with demonstrates that thermal fractures reach 0.67, 6.25, and 78.00 m in length, 0.49, 2.30, and 13.00 m in spacing, and 0.43, 2.09, and 12.19 mm in aperture at 1, 100, and 10,000 days.

Chen, Bin↗

Examining polymer‐protein biophysical interactions with small‐angle x‐ray scattering and quartz crystal microbalance with dissipation

Abstract Polymer‐protein hybrids can be deployed to improve protein solubility and stability in denaturing environments. While previous work used robotics and active machine learning to inform new designs, further biophysical information is required to ascertain structure–function behavior. Here, we show the value of tandem small‐angle x‐ray scattering (SAXS) and quartz crystal microbalance with dissipation (QCMD) experiments to reveal detailed polymer‐protein interactions with horseradish peroxidase (HRP) as a test case. Of particular interest was the process of polymer‐protein complex formation under thermal stress whereby SAXS monitors formation in solution while QCMD follows these dynamics at an interface. The radius of gyration ( R g ) of the protein as measured by SAXS does not change significantly in the presence of polymer under denaturing conditions, but thickness and dissipation changes were observed in QCMD data. SAXS data with and without thermal stress were utilized to create bead models of the potential complexes and denatured enzyme, and each model fit provided insight into the degree of interactions. Additionally, QCMD data demonstrated that HRP deforms by spreading upon surface adsorption at low concentration as shown by longer adsorption times and smaller frequency shifts. In contrast, thermally stressed and highly inactive HRP had faster adsorption kinetics. The combination of SAXS and QCMD serves as a framework for biophysical characterization of interactions between proteins and polymers which could be useful in designing polymer‐protein hybrids.

60 APPLIED LIFE SCIENCES↗

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗

Triiodide Attacks the Organic Cation in Hybrid Lead Halide Perovskites: Mechanism and Suppression

Molecular I 2 can be produced from iodide-based lead perovskites under thermal stress; triiodide, I 3 − , is formed from this I 2 and I − . Triiodide attacks protic cation MA + - or FA + -based lead halide perovskites (MA + , methylammonium; FA + , formamidinium) as explicated through solution-based nuclear magnetic resonance (NMR) studies: triiodide has strong hydrogen-bonding affinity for MA + or FA + , which leads to their deprotonation and perovskite decomposition. Triiodide is a catalyst for this decomposition that can be obviated through perovskite surface treatment with thiol reducing agents. In contrast to methods using thiol incorporation into perovskite precursor solutions, no penetration of the thiol into the bulk perovskite is observed, yet its surface application stabilizes the perovskite against triiodide-mediated thermal stress. Thiol applied to the interface between FAPbI 3 and Spiro-OMeTAD (“Spiro”) prevents oxidized iodine species penetration into Spiro and thus preserves its hole-transport efficacy. Surface-applied thiol affects the perovskite work function; it ameliorates hole injection into the Spiro overlayer, thus improving device performance. It helps to increase interfacial adhesion (“wetting”): fewer voids are observed at the Spiro/perovskite interface if thiols are applied. Perovskite solar cells (PSCs) incorporating interfacial thiol treatment maintain over 80% of their initial power conversion efficiency (PCE) after 300 h of 85 °C thermal stress.

36 MATERIALS SCIENCE↗

Thermal stress-induced depolarization compensation in wide-bandwidth, high-energy, high-repetition-rate multi-slab laser amplifiers

We present an innovative design for a two-head, gas-cooled multi-slab high-energy, high-repetition-rate amplifier aimed at mitigating thermally induced depolarization in a wide-bandwidth neodymium-doped glass gain medium. This architecture employs two quartz rotators (QRs) with opposite-handedness, strategically positioned within each multi-slab amplifier head, to enhance depolarization compensation. Theoretical modeling of this amplifier configuration demonstrates a 20× reduction in depolarization losses for a 70 mm beam operating at the central wavelength, compared to conventional approaches that utilize a single QR positioned between the amplifier heads. In addition, for a wide bandwidth source, the integration of QRs with opposite-handedness yields a 9× improvement in depolarization losses at the spectral extremes compared to the use of two QRs exhibiting the same optical handedness in both amplifier heads.

47 OTHER INSTRUMENTATION↗

Certifying the Performance of Fixative Technologies under Open Air Demolition Activities for D and D - 20096

Department of Energy (DOE) facilities undergoing deactivation and decommissioning (D and D) activities struggle with safety concerns of residual radioactive contamination leftover after gross decontamination efforts have concluded. The positive effects of implementing fixative technologies for decommissioning and maintenance is known across the DOE complex. However, there is no standardized metric in place that quantifies the performance of these technologies such as incombustible fixative platforms that immobilize the contamination in a solid polymer material under normal operating conditions or when exposed to stressors. The primary focus of this research is to provide the empirical data necessary to properly characterize the effects of implementing fixative technologies on mitigating the release of contamination. In addition, this effort has been used to identify and establish uniform testing protocols to quantify operational parameters of fixating platforms and properly credit such systems under a variety of operational conditions and stressors that can arise during open air demolition efforts (e.g. impact, water, thermal, etc.). The established protocols will be provided to the ASTM International E10.03 Subcommittee on Radiological Protection for Decontamination and Decommissioning of Nuclear Facilities and Components for the potential of formal standardization. Attributes to be addressed during testing are material compromise from impact stress, thermal stress for incombustible fixative materials, and immobilization factors (how well an immobilizing platform is capable of retaining fixated material during thermal and impact stressors). In developing these test methods, a greater understanding of the material's behavior under anticipated and unanticipated events, such as decommissioning activities and contingency events as outlined in the Basis of Interim Operations (BIO), can be successfully characterized. There are several key components of the experimental methodology that is essential in empirically certifying fixative technologies. A surrogate contaminant with a unique signature has been utilized with the implementation of a uniform contamination process of test coupons that is quantifiable and replicable for direct fixative comparisons. A modular test chamber has also been used to apply the various stressors of interest. Collection of released contamination that includes airborne and resettled contaminant particles and analyzed using mass spectrometry. This research directly supports DOE complex-wide concerns in terms of final disposition of nuclear facilities and the considerations made during their time between ceasing facility operation and final disposition. The results of this effort aims to provide a standardized road map and logical decision flow to better facilitate fixative technologies into D and D activities required to achieve the desired facility end state. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Investigation of thermal hydraulic behavior of the High Temperature Test Facility's lower plenum via large eddy simulation

A high-fidelity computational fluid dynamics (CFD) analysis was performed using the Large Eddy Simulation (LES) model for the lower plenum of the High–Temperature Test Facility (HTTF), a ¼ scale test facility of the modular high temperature gas-cooled reactor (MHTGR) managed by Oregon State University. In most next–generation nuclear reactors, thermal stress due to thermal striping is one of the risks to be curiously considered. This is also true for HTGRs, especially since the exhaust helium gas temperature is high. In order to evaluate these risks and performance, organizations in the United States led by the OECD NEA are conducting a thermal hydraulic code benchmark for HTGR, and the test facility used for this benchmark is HTTF. HTTF can perform experiments in both normal and accident situations and provide high-quality experimental data. However, it is difficult to provide sufficient data for benchmarking through experiments, and there is a problem with the reliability of CFD analysis results based on Reynolds–averaged Navier–Stokes to analyze thermal hydraulic behavior without verification. To solve this problem, high-fidelity 3-D CFD analysis was performed using the LES model for HTTF. It was also verified that the LES model can properly simulate this jet mixing phenomenon via a unit cell test that provides experimental information. As a result of CFD analysis, the lower the dependency of the sub-grid scale model, the closer to the actual analysis result. In the case of unit cell test CFD analysis and HTTF CFD analysis, the volume-averaged sub-grid scale model dependency was calculated to be 13.0% and 9.16%, respectively. As a result of HTTF analysis, quantitative data of the fluid inside the HTTF lower plenum was provided in this paper. As a result of qualitative analysis, the temperature was highest at the center of the lower plenum, while the temperature fluctuation was highest near the edge of the lower plenum wall. The power spectral density of temperature was analyzed via fast Fourier transform (FFT) for specific points on the center and side of the lower plenum. FFT results did not reveal specific frequency-dominant temperature fluctuations in the center part. It was confirmed that the temperature power spectral density (PSD) at the top increased from the center to the wake. The vortex was visualized using the well-known scalar Q-criterion, and as a result, the closer to the outlet duct, the greater the influence of the mainstream, so that the inflow jet vortex was dissipated and mixed at the top of the lower plenum. Additionally, FFT analysis was performed on the support structure near the corner of the lower plenum with large temperature fluctuations, and as a result, it was confirmed that the temperature fluctuation of the flow did not have a significant effect near the corner wall. In addition, the vortices generated from the lower plenum to the outlet duct were identified in this paper. It is considered that the quantitative and qualitative results presented in this paper will serve as reference data for the benchmark.

97 MATHEMATICS AND COMPUTING↗

A Computer Design Tool for Ceramic Receivers

Gen3 solar receivers and other components will experience a combination of high temperatures and high stress caused by thermal stress and internal pressure. Under these conditions metallic components, even those manufactured from nickel-based superalloys, have poor reliability. Engineering ceramics could be a solution, as these materials have excellent high temperature strength. However, accurately assessing the reliability of a ceramic component operating in these conditions requires an entirely different approach compared to metallic materials. This paper describes the implementation of statistical models for evaluating the reliability of high temperature ceramic components in srlife – an open-source software package for estimating the life of high temperature concentrating solar power equipment. This new capability allows users to make fair comparisons between competing metallic and ceramic component designs and to accurately assess the plant efficiency and economics of ceramic solar receivers and other components.

Messner, Mark (ORCID:0000000200404385)↗

Optimal Control Strategy With Efficiency and Reliability Improvement for Offshore DC Microgrids

Offshore microgrids, due to their remote location and lack of external energy support, face significant challenges in wide-range load operation and maintenance. Consequently, efficiency and reliability are critical concerns for converters in offshore dc microgrids. This article presents an optimal control strategy aimed at enhancing both efficiency and reliability. A normalized nonlinear relationship between power loss and thermal stress of a paralleled converter is first established. Based on this, a dual-objective optimization function with an active weight function as well as a system overall performance index is established. The active weight function dynamically adjusts the control priority based on converter efficiency and switching device thermal stress. Then, the optimal power-sharing strategy is derived by the Lagrange multiplier method with the proposed optimal function. Additionally, to accommodate a wide load range, an optimal selection strategy for operating converter combinations is proposed, requiring only low-bandwidth communication. Experiment verification is given to validate the effectiveness of the proposed control strategy. The experiment results demonstrate that the proposed control strategy can improve the overall performance of offshore microgrids by optimizing efficiency and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Thermal-striping analysis methodology for sodium-cooled reactor design

Computational fluid dynamics simulations have been performed to study the applicability of engineering CFD methods for thermals striping analysis. Thermal striping is the fluctuating temperature profile in a solid caused by fluctuating fluid temperature, and the resulting fluctuating thermal stresses cause high cycle fatigue and eventual material failure. Here this study presents the methodology for thermal striping analysis that including a transient conjugate heat transfer RANS model and benchmark the results against a sodium triple jet experiment. The multiphysics calculations are implemented to analyze the thermal stresses in the solid domain caused by the coupled heat transfer between the fluid and solid domains. Validation data from a liquid sodium triple jet experiment include time-averaged temperature measurements and power spectra of the temperature signal. The numerical results agree well with these experimental measures, demonstrating key features such as the dominant frequency of temperature fluctuations. The applicability of a low-cost wall treatment method is demonstrated, enabling key computational savings. Finally, the performance of two finite element stress analysis software packages is compared, and the validity of the lower-cost method is confirmed. These results demonstrate the applicability of engineering methods for computational thermal striping calculations, enabling thermal striping estimations in large fluid systems such as the core of a Sodium-cooled nuclear reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Separate-Effects Tests for Studying Temperature-Gradient-Driven Cracking in UO 2 Pellets

We report a variety of normal operation and accident scenarios can generate thermal stresses large enough to cause cracking in light-water reactor (LWR) fuel pellets. Cracking of fuel pellets can lead to reduced heat removal, higher centerline temperatures, and localized stress in cladding, all of which impact fuel performance. It is important to experimentally characterize the thermal and mechanical behavior in the pellet before and after cracking to improve cracking models in fuel performance codes. However, in-reactor observation and measurement of cracking is very challenging due to the harsh environment and logistics. Recently, an experimental pellet cracking test stand was developed for separate effects testing of normal operations and accident temperature conditions, using thermal imaging to capture the pellet surface temperature for evaluation of thermal stresses and optical imaging to capture the evolution of cracking in real time. Experiments were performed using depleted uranium dioxide (UO 2 ) pellets, which are useful for collecting data valuable for development and validation of cracking models. A combination of induction and resistance heating was used to create an average temperature gradient of 236°C/cm and 193°C/cm before and after cracking respectively. Characterization of the pellets were done before as well as after cracking. The cracking patterns are somewhat different than those expected in a typical reactor because of the differences in thermal conditions and pellet microstructure. However, if the actual conditions of these experiments are reproduced in computational models, these out-of-pile tests on UO 2 pellets provide relevant data for modeling purposes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fission gas retention of densely packed uranium carbonitride tristructural-isotropic fuel particles in a 3D printed SiC matrix

The Transformational Challenge Reactor (TCR) fuel form was designed to contain large, densely packed uranium carbonitride (UCN) tristructural-isotropic (TRISO) fuel particles within a 3D printed SiC matrix, increasing the uranium density compared to conventional TRISO fuel forms and offering full geometric freedom for core design. Here, this work summarizes initial low-burnup, high-power irradiation testing of TCR fuel materials, including loose UCN TRISO particles and integral fuel compacts with ~55% TRISO particles by volume, to evaluate fission gas retention. Fission gasses were fully retained in all loose particle tests and in integral compacts irradiated at low (<250 °C) surface temperatures. Initial testing at higher (~700–750 °C) fuel surface temperatures showed fission gas release (FGR) and complete fracture of three compacts, but no FGR was observed in later high temperature tests (~300–750 °C) of both fueled compacts and loose TRISO particles. Calculated thermal stresses in the failed compacts were far less than the measured strength of the SiC matrix and the stresses in some failed compacts were less than those in compacts that did not show FGR. Thermal stress-induced matrix cracks also would not cause complete fracture because the tensile stresses transition to compression in the higher temperature regions. Therefore, fuel failure was likely not caused by thermal stresses and may have been related to leakage currents from the electrical heaters and erratic fuel surface temperatures that were only observed in the test for which failure was observed. In any case, the matrix cracks propagated through the coatings of TRISO particles located in the high-density matrix regions on the peripheries of the compacts, resulting in measurable fission gas release. The discussion focuses on the importance of understanding matrix density distributions and the particle-matrix interface properties to prevent matrix cracks from causing TRISO particle failures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Dynamic Behavior of Oval-Twisted Helical Tube Heat Exchanger: Numerical Study with RELAP5-3D

Convective heat transfer characteristics and theoretical thermal stress behaviors are numerically calculated using RELAP5-3D for the helical-coiled once-through steam generator (H-OTSG) and the novel heat exchanger design known as the oval-twisted helically coiled heat exchanger (OTHCHX) under (1) fluctuating wall temperature conditions, (2) square-wave pulsating flow conditions, and (3) the combined effects of fluctuating wall temperature and square-wave pulsating flow conditions. Heat transfer coefficient models for the H-OTSG and OTHCHX were developed based on existing data and implemented into RELAP5-3D, successfully capturing the N⁢uavg behavior within 8% to 10% of the reported data. Under fluctuating wall temperature conditions, the OTHCHX displayed higher N⁢u avg behavior than the H-OTSG. As 𝑓 increased, the $𝜎^{𝑚⁢𝑎⁢𝑥}_{𝑡⁢ℎ}$ decreased. The $𝜎^{𝑚⁢𝑎⁢𝑥}_{𝑡⁢ℎ}$ was higher for the OTHCHX than for the H-OTSG under fluctuating wall temperature conditions. Under pulsating flow conditions, the H-OTSG and OTHCHX displayed much higher 𝑁⁢𝑢 𝑎𝑣𝑔 than under constant flow conditions. The H-OTSG displayed a higher $𝜎^{𝑚⁢𝑎⁢𝑥}_{𝑡⁢ℎ}$ over the OTHCHX. Under combined fluctuating wall temperature and pulsating flow conditions, the augmented heat transfer behavior from the pulsating flow was counteracted by the wall temperature fluctuations, producing slightly higher 𝑁⁢𝑢 𝑎𝑣𝑔 over constant wall temperature, constant flow conditions, but much lower than only constant pulsating flow under constant wall temperature conditions. The effects of simultaneous wall temperature fluctuations and square-wave pulsating flow caused higher $𝜎^{𝑚⁢𝑎⁢𝑥}_{𝑡⁢ℎ}$ than that of only wall temperature fluctuations or pulsating flow. As the Reynolds number (Re) increased, $𝜎^{𝑚⁢𝑎⁢𝑥}_{𝑡⁢ℎ}$ increased. However, when 𝑓=𝑓$_{\dot{m}}$, the $𝜎^{𝑚⁢𝑎⁢𝑥}_{𝑡⁢ℎ}$ showed decreasing values as Re increased. In conclusion, the results indicate that thermal-fluid resonance can help mitigate thermal stresses.

Thermal stress↗