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Prof. Xiaodong Sun and I are Guest Editors and have written a Foreword for the Journal. The Nuclear Science and Engineering Special Issue focuses on thermal hydraulics experiments and modelling, supporting verification and validation needs for advanced reactor development.
Since the U.S. Department of Energy (DOE)’s Office of Nuclear Energy (NE) initiated the Nuclear Energy University Program (NEUP) in 2009, a total of 30 NEUP projects focused on High-Temperature Gas-cooled Reactor (HTGR) thermal-fluid experiments were funded up to fiscal year (FY) 2021. This represents a total DOE investment of approximately $23M over the 12-year period, covering thermal fluid phenomena important to both pebble bed and prismatic HTGR designs. The NEUP projects have produced a large amount of high-quality experimental and computational data that were published in final project reports, journal articles, dissertations, and conference proceedings, but in most cases the actual data sets and supporting information such as facility and instrumentation descriptions were not publicly disseminated to the HTGR community. To the authors’ best knowledge, a data platform that organizes and summarizes these NEUP-funded projects for HTGR research does not currently exist. To improve access to this HTGR validation data and optimize the return on the significant investment made by DOE, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program started a survey of completed and ongoing HTGR NEUP projects with the aim of developing a public-access data platform that can be used to retrieve computational fluid dynamics (CFD) and system code validation data and guide future NEUP investments. This paper summarizes the status of the current ART-GCR database, provides an overview of the NEUP-funded HTGR-related research projects from FY2009 to FY2021 and identify validation knowledge gaps still existing in HTGR thermal-fluid research.
Because of the important role that fracture plays in the behavior of ceramic UO2 fuel in a nuclear reactor environment, fracture models are a major component of fuel performance codes. As with any aspect of fuel performance, it is crucial to validate these fracture models against experimental data; however, obtaining well-controlled data for conditions representative of a reactor environment is difficult. Quenching is proposed here as a relatively simple approach for using a laboratory environment to achieve conditions that approximate those of a reactor environment. In this paper, an experimental apparatus containing a single instrumented fuel pellet in a sealed section of copper tubing is developed. It is then applied to a series of seven experiments in which the apparatus is first heated to a high temperature (580-680°C) by immersion in a molten salt bath, then quenched in a cold bath (-10-4 °C). Development of these experiments was guided by numerical simulations, and post-test simulations were performed to aid in understanding the experimental behavior and assessing the accuracy of the predictions of fracture initiation and propagation. In addition, similar experiments were performed on solid copper rods to provide temperature-dependent heat transfer coefficients for use in simulations of these experiments. Here, this study demonstrates that quenching is a viable approach for generating thermal gradients representative of those in prototypical light-water reactor conditions at powers of about 5–10 kW/m. Fracture is expected to begin at these power levels, and moderate amounts of radial and axial cracking was observed in these quenching tests.
This presentation states that new TSLs in ENDF/B-VIII.0 will reduce the overprediction of the library for the most moderated cases. The differences between VII.1 and VIII.0 are driven by the 239 Pu changes and are consistently higher for all configurations. The VIII.0 239 Pu thermal cross sections were specifically adjusted lower to better predict plutonium thermal solutions criticality benchmarks, yet they overpredict the TEX thermal configurations, moderated by PE. Other, smaller differences have been seen for 240 Pu and 56 Fe. PMM-002 has shown utility in testing cross sections over a wide range of neutron energies.
This is a presentation for a dinner meeting for the Idaho section of the American Nuclear Society on April 13, 2023. It contains a summary of experimental work at TREAT in support of NASA's Nuclear Thermal Propulsion program.
Combining immersive virtual environment (IVE) with a controlled environment is a potential solution for analyzing human thermal experience during building design. Existing studies in this field have not adequately analyzed scenarios involving stabilized comfortable and uncomfortable temperature conditions using both thermal state votes and physiological responses, or the influence of the seasons. By combining IVE with a climate chamber, called mixed IVE (MIVE) in this study, experiments were conducted to test the hypothesis that participants' virtual experience did not significantly alter their thermal experience compared to their in-situ experience. Response variables were the control temperature distribution, the thermal state vote (at temperature steps 18.3 °C, 23.8 °C, and 29.4 °C), and physiological responses (heart rate and skin temperature). The results show that the first two response variables were not significantly different between the MIVE and in-situ settings (except for one case). Due to the heat development of the head mounted display device, the mean forehead skin temperature in the MIVE experiments was significantly higher than that in the in-situ experiments in most cases. Furthermore, such difference in skin temperature did not seem to affect general thermal state votes. In addition, significant skin temperature differences at some locations were also observed between the MIVE and in-situ settings.
Since 2009, the U.S. Department of Energy (DOE) Office of Nuclear Energy's Nuclear Energy University Program (NEUP) has been at the forefront of nuclear research, specifically concentrating on advancing high-temperature gas-cooled reactor (HTGR) technologies. By Fiscal Year 2024, NEUP has authorized 36 projects dedicated to HTGR research, each contributing significantly to the enhancement of our understanding of this technology. The outcomes of these diverse projects have been disseminated through final NEUP reports, peer-reviewed journal articles, and presentations at academic conferences, forming a comprehensive tapestry of knowledge. Despite the substantial value of these findings, their dissemination has been fragmented, posing challenges for accessibility to researchers and policymakers and leading to underutilization of DOE investments. Recognizing this critical gap and its potential consequences for the future of nuclear research, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program conducted an extensive survey of completed and ongoing HTGR NEUP projects. This survey enabled the compilation of crucial data, resulting in the development of a specialized public-access database tailored for computational fluid dynamics and system code validation, specifically designed for HTGR applications. However, the data collection process revealed a significant challenge in central data organization due to individual researchers from different institutes employing varying logics and preferences for recording and documenting experimental data. Consequently, an urgent need has been identified to establish a standardized reporting format for HTGR experimental projects. Addressing this issue is essential for enhancing collaboration, maximizing the impact of DOE investments, and ensuring the seamless advancement of HTGR technologies in nuclear research.
Since 2009, the U.S. Department of Energy (DOE) Office of Nuclear Energy's Nuclear Energy University Program (NEUP) has been at the forefront of nuclear research, specifically concentrating on advancing high-temperature gas-cooled reactor (HTGR) technologies. By Fiscal Year 2023, NEUP has authorized 35 projects dedicated to HTGR research, each contributing significantly to the enhancement of our understanding of this technology. The outcomes of these diverse projects have been disseminated through final NEUP reports, peer-reviewed journal articles, and presentations at academic conferences, forming a comprehensive tapestry of knowledge. Despite the substantial value of these findings, their dissemination has been fragmented, posing challenges for accessibility to researchers and policymakers and leading to underutilization of DOE investments. Recognizing this critical gap and its potential consequences for the future of nuclear research, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program conducted an extensive survey of completed and ongoing HTGR NEUP projects. This survey enabled the compilation of crucial data, resulting in the development of a specialized public-access database tailored for computational fluid dynamics and system code validation, specifically designed for HTGR applications. However, the data collection process revealed a significant challenge in central data organization due to individual researchers from different institutes employing varying logics and preferences for recording and documenting experimental data. Consequently, an urgent need has been identified to establish a standardized reporting format for HTGR experimental projects. Addressing this issue is essential for enhancing collaboration, maximizing the impact of DOE investments, and ensuring the seamless advancement of HTGR technologies in nuclear research.
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Los Alamos National Laboratory is a nuclear weapons laboratory supporting our nation's defense. In support of the mission is a high energy-density physics program in which we design and execute experiments to study radiation-hydrodynamics phenomena and improve the predictive capability of our large-scale multi-physics software codes on our supercomputers. The Radflow Project is maturing a unique spectroscopic measurement that yields a spatially dependent supersonic radiation wavefront profile. The spectroscopic measurement is much more constraining than the typically used radiography, which measures the density changes due to the shock as the radiation wave goes subsonic. Recently, the spectroscopic measurement has been applied to advanced targets with a detailed heterogeneity representing a single realization of a stochastic medium. The Radflow Project also conducts opacity experiments to explain the current conundrum of the experimental iron opacity differing from theory, which is important in modeling the sun. More than that, though, we need to be able to answer these science questions and be able to validate our theory and codes.
In addition to possessing the desirable properties of being a biodegradable and biocompatible polymer fabricated from renewable resources, poly (lactic acid) (PLA) has useful mechanical and thermal attributes that has enabled it to be one of the most widely-used plastics for medicine, manufacturing, and agriculture. Yet, PLA composites have not been heavily explored for use in 3D-printing applications, and the range of feasible materials for the technology is limited, which inhibits its potential growth and industry adoption. In this study, tunable, multifunctional antimicrobial PLA composite filaments for 3D-printing have been fabricated and tested via chemical, thermal, mechanical, and antimicrobial experiments. Thermally stable antimicrobial ceramics, ZnO and TiO2, were used as fillers up to 30 wt%, and poly (ethylene glycol) (PEG) was used as a plasticizer to tune the physical material properties. Results demonstrate that the PLA composite filaments exhibit the thermal phase behaviors and thermal stability suitable for 3D-printing. Additionally, PEG can be used to tune the mechanical properties while not affecting the antimicrobial efficacy that ZnO and TiO2 imbue.
This report documents the operations and testing that was performed at the Mechanisms Engineering Test Loop (METL) during FY2020. The METL facility had a very successful second year of operations having logged over 730 days (as of September 19, 2020) of operations with molten sodium either flowing or static. The METL piping and vessel system was filled with sodium on September 19, 2018 after a successful transfer of sodium from fifteen 55-gallon drums. FY2020 saw the successful reconditioning and insertion of the Gear Test Assembly (GTA) for its second round of testing, the full use of the 18-inch Flexi-Cask system, the second extraction of the GTA from METL, and the removal of sodium from the GTA test article by the carbonation process followed by an alcohol wash. In addition, METL is being prepared to support a second larger experiment, a thermal hydraulic experiment, called Thermal Hydraulic Experimental Test Article (THETA).
This paper evaluates experiment-based superposition thermal modeling for Laser Powder Bed Fusion (LPBF) with a pulsed laser. An analytical pulsed laser thermal model establishes the modeling procedure. The framework inverts a powder bed’s single pulse temperature response from experimental spatiotemporal Short-Wave Infrared (SWIR) camera data. Superimposing this response along a scan path simulates multi-pulse LPBF. Results show the experimentally informed superposition model rapidly and accurately predicts a layer’s temperature history. The model has applications in correction of thermally driven LPBF errors and in-situ part qualification.
This study investigates the dual-storage capability of a redox flow battery (RFB) system, enabling simultaneous storage of heat and electricity within a single platform. Through electrochemical and thermal experiments, we evaluated how heat storage affects battery performance and vice versa using a counterflow heat exchanger integrated in a conventional RFB configuration. The results show that incorporating heat storage had a minimal impact on the electrochemical charging and discharging processes. Further, the heat discharge operated independently of electrochemical storage, confirming that both functions can coexist without interference. The combined system also enhanced overall energy conversion efficiency, demonstrating its potential as an efficient solution for supplying both thermal and electrical energythe two most widely used energy forms.
Here, detailed thermal experiments using relative humidity- (RH) and temperature-controlled X-ray diffraction (XRD) and H 2 O adsorption/desorption measurements were applied to understand the dehydration/hydration behaviors of thenardite/mirabilite (Na 2 SO 4 /Na 2 SO 4 ·10H 2 O), tincalconite/borax (Na 2 B 4 O 7 ·5H 2 O/Na 2 B 4 O 7 ·10H 2 O), nahcolite (NaHCO 3 ), and qilianshanite (NaH 4 (BO 3 ) (CO 3 )·2H 2 O or NaHCO 3 ·H 3 BO 3 ·2H 2 O). The thermal behaviors of thenardite/mirabilite and tincalconite/borax were evaluated at room temperature as a function of RH. Hydration of thenardite to mirabilite is very sluggish and does not begin until at least 85 % RH, whereas dehydration of mirabilite to thenardite occurs at ~76 % RH. The reactions are accessible in the solid state and were not completely reversible on the time scale of these measurements. Qilianshanite appears stable under room conditions, as long as the RH is >20 %, supported by 2.5 months of observation during exposure to room air of known RH. Qilianshanite persists metastably for at least two days when exposed to both wet and 0% RH atmospheres at room temperature, observed during environment-controlled XRD. Below 20 % RH, qilianshanite sluggishly reacts to form tincalconite and nahcolite. When heated, qilianshanite broke down at 70 °C based on XRD results, and thermogravimetric analysis (TGA) confirmed a dehydration temperature of ~75 °C. Tincalconite hydrated to borax at 80 % RH, and dehydration from borax to tincalconite occurred at 40–50 % RH, illustrating the effective reversibility of the reaction under room conditions. The minor phase nahcolite originally in qilianshanite remained in the residue of decomposed qilianshanite after heating to 125 °C, demonstrated by continuous XRD measurements, whereas nahcolite was largely dehydrated when heated to ~100 °C during TGA. The difference can be attributed to the slower reaction kinetics in the environmental XRD. These results shed considerable light on the behavior of these minerals in the environment, particularly in evaporite deposits in Antarctica, where all of these minerals are reacting with the atmosphere on a diurnal-to-seasonal basis.
Identifying fluid flow maldistribution in planar geometries is a well–established problem in subsurface science/engineering. Of particular importance to the thermal performance of enhanced (or “engineered”) geothermal systems is identifying the existence of nonuniform (i.e., heterogeneous) permeability and subsequently predicting advective heat transfer. Here, machine learning via a genetic algorithm (GA) identifies the spatial distribution of an unknown permeability field in a two–dimensional Hele–Shaw geometry (i.e., parallel plates). The inverse problem is solved by minimizing the L2 norm between simulated residence time distribution (RTD) and measurements of an inert tracer breakthrough curve (BTC) (C–Dot nanoparticle). Principal component analysis (PCA) of spatially correlated permeability fields enabled reduction of the parameter space by more than a factor of 10 and restricted the inverse search to reservoir–scale permeability variations. Thermal experiments and tracer tests conducted at the mesoscale Altona Field Laboratory (AFL) demonstrate that the method accurately predicts the effects of extreme flow channeling on heat transfer in a single bedding–plane rock fracture. However, this is only true when the permeability distributions provide adequate matches to both tracer RTD and frictional pressure loss. Without good agreement to frictional pressure loss, it is still possible to match a simulated RTD to measurements, but subsequent predictions of heat transfer are grossly inaccurate. Here, the results of this study suggest that it is possible to anticipate the thermal effects of flow maldistribution, but only if both simulated RTDs and frictional pressure loss between fluid inlets and outlets are in good agreement with measurements.
Detecting internal defects in power electronics packages is critical for their performance and reliability, especially under extreme operating conditions, as these defects can lead to catastrophic failure if not properly addressed. Confocal scanning acoustic microscopy (C-SAM) plays a key role in the nondestructive evaluation of bond layer degradation within a power electronics package by detecting defects such as delamination, voids, and cracks. However, accurately quantifying and predicting these defects from C-SAM images remains a significant challenge due to the low noise-to-signal ratio, which typically arises from both imaging process and bond patterns itself. In this paper, we explore machine learning strategies for processing C-SAM images and providing predictive models of defect growth. We use C-SAM images of sintered copper and sintered silver samples, which are obtained under accelerated thermal experiments, as the representative dataset for our study. We investigate the effect of Fourier transforms and wavelet transforms on these datasets to remove high-frequency noise and address noise across multiple scales with histogram equalization to enhance the contrast and improve the visibility of defects. As a result, defect boundaries can be clearly distinguished, enabling more accurate tracking of their growth over time. We then employ different time-series forecasting algorithms on the denoised images to formulate an image-based lifetime prediction model. Statistical models and deep-learning techniques are trained on images obtained in the early stages of thermal shock, and defect growth in the later stages is predicted. Our work serves as a preliminary attempt to improve the accuracy of lifetime prediction models of power electronics packages, which is critical under extreme operating environments.
Abstract Silicon and molybdenum ( SiMo ) ductile iron is commonly used for exhaust manifolds because these components experience thermal cycling in oxidizing environment, which requires resistance to fatigue during transient thermomechanical loads. Previous studies have demonstrated that alloying elements, such as Al , to SiMo ductile iron reduces the amount of surface degradation during static high-temperature exposure. However, deterioration of sphericity of the graphite nodules and a decrease in ductility could affect the tendency of cracking during thermal cycling. In this article, the effect of Al alloying on static and transient thermomechanical behavior of SiMo ductile iron was investigated to optimize the amount of Al alloying. A thermodynamic approach was used to confirm the effect of the Al alloying on the phase transformations in two SiMo cast irons, alloyed by 1.8% Al and 3% Al . These two alloys were cast in a laboratory along with the baseline SiMo ductile iron. Several experimental methods were used to evaluate the dimensional stability, physical properties, static oxidation, and failure resistance during constrained thermal cycling testing to compare their high-temperature capability. Experimental results verified that Al alloying increases the temperature range and decreases volume change during eutectoid transformation, which together with enhancement of oxidation protection improved the dimensional stability. Thermocycling tests showed that the number of cycles to failure depends on the amount of Al alloying and the applied high-temperature exposure during each cycle. SEM/EDX, high-resolution TEM and µCT analysis were used to verify the mechanism resulting from the Al alloying protection. It was shown that an optimal level of Al alloying for balancing oxidation and thermal cracking resistance depends on thermomechanical conditions of application.