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At least 289 records · Page 16

Characterizing soil water content variability across spatial scales from optimized high-resolution distributed temperature sensing technique

Fiber-optic Distributed Temperature Sensing, when combined with the Single-probe Heat-pulse technique can measure soil moisture (θ) across spatial scales. The key limitation of this system is in obtaining the relationship between soil thermal conductivity (λ) and θ for a specific field. Using the Department of Energy Atmospheric Radiation Measurement (ARM) site, this study tested a new methodology to account for the spatial variability in the λ-θ relationship using a Gaussian processes model. The resulting accurate θ measurements (RMSE = 0.03 m 3 m –3 ) were used to characterize the spatial variability of θ across scales and to develop an empirical equation that can correct for the changes in the θ spatial variability observed at different spatial resolutions. In addition, the number of required samples to accurately characterize θ and its variability over scales ranging from 5 m and 350 m were estimated. Finally, these findings provide key information to scale soil moisture from centimeters to hundreds of meters for process understanding.

54 ENVIRONMENTAL SCIENCES↗

Coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) for engineering flow measurements

Increasingly, fully 3D experimental measurements of flow in complex engineering geometries are required to validate computational fluid dynamics models that support and inform reactor design and licensing. One barrier to such measurements is the complexity of typical reactor components and subsequent lack of optical access in these systems. To overcome this, the deployment of coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) is explored for flow measurement in reactor thermal hydraulic components and model (scaled) systems. Through this methodology, fully 3D flow information (via PEPT) and detailed internal geometry (via CT) are captured in opaque systems such as pipes, rod bundles, packed beds, etc. The reconstructed flow field and geometry can then be overlain to reveal detailed flow features around internal structures within a given test section. This is enabled through the use of a combined preclinical PET/CT scanner with overlapping PET and CT fields of view. Such measurements are useful for characterizing flow inside such intricate nuclear thermal hydraulic components as core geometries and heat exchangers, among others, and providing valuable 3D validation data for CFD models. In this work, basic tests of this 3D flow/geometry mapping are presented, and the implications of such measurements are discussed. Further, preliminary measurements are made with both point sources and flow in a simple pipe flow geometry to evaluate the capabilities of this technique. PEPT and CT features are coregistered with up to 0.1 mm precision, and pipe flow mean velocity and Reynolds stresses are reconstructed with similar accuracy to previous PEPT demonstrations. The utility of PEPT/CT is shown herein, and suggestions for future measurements are made.

3D flow measurement↗

Utilization of coupled eigenmodes in Akiyama atomic force microscopy probes for bimodal multifrequency sensing

Akiyama atomic force microscopy probes represent a unique means of combining several of the desirable properties of tuning fork and cantilever probe designs. As a hybridized mechanical resonator, the vibrational characteristics of Akiyama probes result from a complex coupling between the intrinsic vibrational eigenmodes of its constituent tuning fork and bridging cantilever components. Here, through a combination of finite element analysis modeling and experimental measurements of the thermal vibrations of Akiyama probes, we identify a complex series of vibrational eigenmodes and measure their frequencies, quality factors, and spring constants. We then demonstrate the viability of Akiyama probes to perform bimodal multi-frequency force sensing by performing a multimodal measurement of a surface's nanoscale photothermal response using photo-induced force microscopy imaging techniques. Further performing a parametric search over alternative Akiyama probe geometries, we propose two modified probe designs to enhance the capability of Akiyama probes to perform sensitive bimodal multifrequency force sensing measurements.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Semiconductor Nanostructures by Scientific Design (Final Technical Report)

We developed and used quantum simulation techniques to predict structural, electronic, optical and thermal properties affecting the scientific design of semiconductor nanostructures. We focused on the study of surfaces and interfaces at the nanoscale, in particular embedding and solvation of semiconductor nanoparticles, and provided a microscopic description of nanostructured materials in realistic environments, directly comparable with experimental conditions. We addressed three major problems: (i) the design of realistic structural models of integrated nanostructures, e.g. quantum dots embedded in solid matrices and nanostructures immersed in fluids; (ii) the development of efficient and accurate calculations to describe the excited state properties of nanostructures, beyond standard Density Functional Theory, so as to understand and predict electronic properties involved in renewable energy applications, for example solar conversion devices. In particular we developed and used methods based on a many body perturbation theory. (iii) the development of calculations of heat transport properties of nanostructured materials, for thermoelectric applications, including predictive calculations of thermal and electrical conductivity and of Seebeck coefficients. Specifically, we developed and used methods based on the Boltzmann transport equation and molecular dynamics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

On the applicability of the Redlich-Kister framework for viscosity estimation of molten halide salt mixtures

For molten halide salt mixtures already being utilized or under consideration for carbon-free energy production systems, it is crucial that their viscosity is well understood so that system thermal hydraulics can be reliably assessed. Because of the difficulty in accurately measuring molten halide viscosity and the sheer size of the matrix of possible higher order salt mixtures that may be of interest to the energy industry, there are several gaps in the quantified understanding of molten halide viscosity across this matrix. As such, both first-principles and semi-empirical modeling techniques may be crucial for rapidly assessing this broad, complex compositional domain. Herein, the Redlich-Kister framework is applied to assess the feasibility of broadly interpolating and estimating the viscosity of several pseudobinary and pseudoternary molten halide salt systems that may be of key interest to the energy industry. The framework is based on the assumption that an ideal component and a nonideal component collectively describe the viscosity as a function of composition and temperature for a given molten halide system. Three different ideal models were considered for the ideal component, including Grunburg-Nissan, Katti-Chaudhri, and Gambill methods. Regarding the pseudobinary interpolations, the Redlich-Kister models with either the Grunburg-Nissan or Katti-Chaudhri models as the ideal component resulted in either highly (average error less than 5%) or reasonably (average error less than 15%) accurate interpolations of pseudobinary halide viscosity; BeF 2 - or UF 4 -bearing salts tended to result in reasonably accurate interpolations, whereas other pseudobinary mixtures tended to show high accuracy. Regarding the pseudoternary extrapolations, the Redlich-Kister framework shows reasonable success at estimating the extent to which a pseudoternary system may indicate deviations from ideal Grunburg-Nissan mixing, where discrepancies with comparative experimental data generally stay within 30%. Finally, the primary reasons identified for such discrepancies are (1) inaccuracy in the underlying experimental data, (2) different complexation behavior in the higher order systems compared to the pseudobinary subsystems, and (3) extrapolation into temperatures too far out of the domain, which is valid for the underlying experimental data feeding the Redlich-Kister model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diagnosing nuclear power plant pipe wall thinning due to flow accelerated corrosion using a passive, thermal non-destructive evaluation method: Feasibility assessment via numerical experiments

Flow accelerated corrosion (FAC) in nuclear power plant pipes is one of the leading causes of accidents, fatalities, damage and outages. Current FAC identification methods employ expensive sensing technology and are “active” methods, where the response of the piping system to an externally-generated thermal, mechanical or optical excitation must be measured. As a result, these techniques require a disruptive and time-consuming setup. Here we propose a method that utilizes pipe surface temperature measurements to passively monitor for FAC-induced pipe wall thinning without the need for expensive equipment or post-installation setup time. This diagnostic method utilizes a simulation data-driven diagnostic model to estimate the amount of thickness reduction in a pipe based on changes in measured steady-state pipe temperatures. In order to reduce the computational burden of generating large, simulation-based datasets, the behavior of the insulation of the pipe was modeled using a suitably calibrated heat transfer boundary parameter. Additionally, global sensitivity analysis was performed to determine system parameter(s), such as the temperature of water flowing inside the pipe, which significantly affect the steady state pipe wall temperature and could cause errors in diagnosis. Two diagnostic models, one using only the change in steady-state temperature as an indicator for FAC-induced pipe wall thinning and the other using water temperature as an additional diagnostic model input were evaluated for their ability to estimate thickness reductions in a pipe using simulated pipe wall temperature data. For the numerical experiments conducted in this work, both models estimated wall thickness with errors within 0.5 mm, indicating that the proposed technique can potentially be used as a low-cost, first-pass method for FAC monitoring.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Entanglement Hamiltonian of Many-Body Dynamics in Strongly Correlated Systems

A powerful perspective in understanding nonequilibrium quantum dynamics is through the time evolution of its entanglement content. Yet apart from a few guiding principles for the entanglement entropy,to date, much less is known about the refined characteristics of entanglement propagation. In this paper we unveil signatures of the entanglement evolving and information propagating out of equilibrium, from the view of the entanglement Hamiltonian. We investigate quantum quench dynamics of prototypical Bose-Hubbard model using state-of-the-art numerical technique combined with conformal field theory. Before reaching equilibrium, it is found that a current operator emerges in the entanglement Hamiltonian, implying that entanglement spreading is carried by particle flow. In the long-time limit the subsystem enters a steady phase, evidenced by the dynamic convergence of the entanglement Hamiltonian to the expectation of a thermal ensemble. Importantly, the entanglement temperature in steady state is spatially independent,which provides an intuitive trait of equilibrium. These findings not only provide crucial information on how equilibrium statistical mechanics emerges in many-body dynamics, but also add a tool to exploring quantum dynamics from the perspective of the entanglement Hamiltonian.

36 MATERIALS SCIENCE↗

Feasibility of raised inner strike point equilibria scenario in ITER for detritiation from beryllium co-deposits

Abstract In ITER, tritium retention primarily occurs through co-deposition with beryllium. To avoid exceeding the strict tritium inventory limit, efficient tritium recovery techniques are essential. Baking is the ITER baseline for tritium recovery, but its effectiveness in removing tritium from thick beryllium layers is limited. A raised strike point scenario is considered an alternative method for removing tritium from the ITER inner vertical divertor target by heating components via plasma flux. This paper presents SOLPS-ITER code simulations conducted under various conditions, assessing the divertor performance and tritium outgassing of the raised strike point scenario. As the strike point is raised, recycled neutrals are not efficiently baffled by the dome and scrape-off layer, significantly changing the neutral trajectory and ionization source distribution. This improves detachment accessibility but worsens core-edge compatibility compared to the baseline scenario. However, in the partially detached condition, the impact of raising the strike point, perpendicular transport, and q 95 on target heat flux is not significant, as it primarily scales with the input power. Target heat flux is translated to target surface temperature using a simplified heat transfer model that considers the 3D target monoblock geometry and active cooling condition, excluding Be layer thermal properties. For partially detached divertor conditions, the bulk tungsten monoblock surface temperature remains below the baking temperature, which is insufficient for efficient tritium outgassing under the actively cooled ITER divertor condition. However, considering the potential thermal contact resistance between the beryllium and tungsten layers, which may significantly impact temperature distribution, the temperature of the beryllium layer can be raised to a level sufficient for efficient tritium outgassing. Therefore, the raised strike point scenario can be considered as an alternative in-vessel tritium removal technique.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Deep image reconstruction for background subtraction in heavy-ion collisions

Jet reconstruction in an ultrarelativistic heavy-ion collision suffers from a notoriously large, fluctuating thermal background. Traditional background‐subtraction methods struggle to remove this soft background while preserving the jet's hard substructure. In this Letter, we present DeepSub, a machine-learning-based approach for full-event background‐subtraction. DeepSub utilizes a model based on Swin Transformer layers to denoise jet images and disentangle hard jets from the heavy-ion background. DeepSub significantly outperforms existing subtraction techniques by reproducing key jet observables such as jet 𝑝 T and mass, and substructure observables such as girth and the energy correlation function, at the subpercent to percent level. As such, DeepSub paves the way for precision heavy-ion measurements in hitherto inaccessible kinematic regimes.

Qureshi, Umar Sohail [Stanford University, CA (Uni↗

Influence of pre-existing defects on thermal transport in nuclear graphite

Nuclear graphite is a critical material in high-temperature nuclear reactors due to its superior thermal and mechanical properties. The manufacturing process leaves multi-scale ‘pre-existing’ defects that can affect thermal transport characteristics. Because these defects are remnant of graphitization temperature, they cannot be thermally annealed. This study employs a non-thermal electron wind force (EWF) annealing technique to avoid this obstacle. 2 min of EWF treatment of the as-received graphite IG-110 at temperatures below 100 °C led up to 67% increase in thermal diffusivity and ~ 35% decrease in electrical resistivity in average. Differential scanning calorimetry also showed similar outcome for specific heat. X-ray diffraction characterization was performed by fitting a bi-modal crystallite size distribution model to reveal the enhancement in crystallinity after the EWF treatment. The findings emphasize the potential of EWF annealing for optimizing thermal performance in nuclear graphite and its implications for reactor efficiency and safety.

Annealing↗

Thermal transport across nanoscale damage profile in sapphire irradiated by swift heavy ions

In this work, we studied the degradation of thermal conductivity in single crystal sapphire (α-Al 2 O 3 ) irradiated by 167 MeV Xe swift heavy ions (SHIs) over the multiple fluences in the range of 10 12 –10 14 ions/cm 2 . Thermal conductivity was measured primarily in the cross-plane direction using a noncontact ultrafast optical pump-probe technique called picosecond time domain thermoreflectance (TDTR). Multiple samples with variable ion fluences allowed us to probe distinct regions resulting from different regimes of microstructure evolution caused by electronic energy loss. By tuning the penetration depth of the thermal waves using different modulation frequencies, two regions with distinct conductivities were identified and the values of which were found to be consistent with phonon-mediated thermal transport models while the microstructure was confirmed by electron microscopy characterization. These damaged regions were determined to be a several micrometer thick ion track region and several tens of nanometer-thick amorphous layer present only above 5.0 × 10 13 ions/cm 2 . These results demonstrate the applicability of TDTR to resolve thermal transport behavior in SHI irradiated oxides having nonhomogeneous damage profile on a nanometer scale. The presented approach facilitates future studies aiming at resolving the impact of distinct damage resulting from electronic and nuclear stopping regimes under irradiation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Godiva IV Simulated Radiation Field Characterization and Variance Reduction

Godiva IV is a system comprised of highly enriched uranium alloyed with molybdenum in the form of fuel plate rings. The reactor, along with its predecessors, was designed with the unique ability to satisfy interests in the super-prompt-critical reactor operation space. Originally, the reactor was part of the Los Alamos Critical Experiments Facility (LACEF) at Technical Area-18 (TA-18). The radiation field around Godiva at this facility was well characterized and understood. As a fast neutron system, the neutron spectrum in and around Godiva was close to a Watt Fission spectrum. The Kiva where Godiva IV was located at LACEF was made of thin, sheet metal walls which did not contribute significantly to the neutron spectrum. Following the transition of LACEF to the National Critical Experiments and Research Center (NCERC) in Nevada, Godiva-IV was moved from TA-18 to the Device Assembly Facility (DAF) at the Nevada National Security Site (NNSS). Part of this move brought renewed interest in radiation field characterization. The new facility introduced significant changes to the environment surrounding Godiva, and preliminary foil irradiation results suggested that the room contribution to the neutron spectrum was significant. Unlike at TA-18, a large thermal neutron signature was added to the fast spectrum from Godiva due to significant room return. A primary goal due to the additional complexity that the room return adds to the Godiva IV radiation emission spectrum was the development of an efficient Monte Carlo N-Particle (MCNP) calculation capable of characterizing the neutron spectrum anywhere in the room around Godiva. A campaign of activation foil irradiations and analysis were completed to support the validation of the MCNP model. The modeling of these foils in MCNP can be easily done with a standard volumetric neutron flux tally. However, given the multitude of locations and reaction rates to be modeled, further steps must be taken to increase the efficiency of these calculations in MCNP. During this study, a benchmark model currently under development for Godiva IV was used. A qualitative assessment of the thermal neutron contributors was performed using spatial neutron distribution plots. Additional detail was added to the model based on the qualitative results showing the thermal spectrum’s large sensitivity to hydrogenous material. Neutron energy spectra was evaluated at discrete locations in the room around Godiva to quantify the relative contribution of various components. It was discovered that the concrete walls are the largest contributor to the thermal signature, with minor contributions from plastic components surrounding Godiva. Following these results, two different variance reduction techniques were implemented to improve the problem efficiency in these calculations. In the first approach, an F5 point detector tally was implemented in the standard Godiva IV criticality problem. The second approach involved a weight-window generator implementation with an F5 point detector tally in a fixed source problem. The weight window implementation reduced the runtime from 42739.55 minutes to 1803.34 minutes (computer time), compared to the F5 KCODE implementation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels (Final Scientific/Technical Report)

The project, "Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels," represents a significant advancement in nuclear fuel recycling technology. It integrates cutting-edge multimodal sensor fusion, machine learning (ML), and digital twin (DT) technologies to address challenges in material safeguarding, process optimization, and regulatory compliance for pyroprocessing facilities. This research has significantly enhanced the understanding of pyrochemical fuel recycling processes by developing innovative tools and methodologies. The Multimodal Safeguards Monitoring Unit (MSMU) combines electroanalytical techniques, Raman spectroscopy, and differential thermal analysis (DTA) to enable high-fidelity, near-real-time material accountancy measurements. Machine learning techniques, such as Long Short-Term Memory (LSTM) autoencoders, are utilized to detect anomalies in material balances and sensor data, improving the reliability of safeguards monitoring. Additionally, digital twin technology has been established to provide real-time system-level monitoring and diagnostics, integrating physics-based models with sensor data to optimize process safety and efficiency.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

From phase decomposition to evaporation: A multi-modal evaluation of thermally degraded model lightweight high-entropy alloy

Lightweight high-entropy alloys (LHEAs) have the potential to replace conventional lightweight materials due to their superior mechanical properties and thermal stability. However, the thermal degradation pattern of LHEAs from phase decomposition to evaporation is not clear. We develop a new Al-based dual phase (FCC + HCP) LHEA—AlTi 0.45 CuZn, and further investigate its thermal degradation behavior for potential high-temperature structural applications. Using multimodal advanced characterization techniques such as differential scanning calorimetry/thermogravimetric analysis, scanning/transmission electron microscopy, and synchrotron X-ray diffraction/pair distribution function (XRD/PDF), a sequence of thermal degradation events beyond the thermal phase stability limit—between 250 and 360 °C—is observed. These include phase decomposition at ~360 °C, Zn evaporation at ~750 °C, and LHEA melting at 880 °C which results in ~25% cumulative weight loss. The formation of Al-Ti phase off the AlTi 0.45 CuZn matrix is due to the largest negative mixing enthalpy for Al-Ti than other binary pairs. Similarly, Zn evaporation from AlTi 0.45 CuZn LHEA is due to its faster evaporation rate than other constituent elements. The high-resolution synchrotron XRD and PDF results support the aforementioned observations; in addition, they reveal local atomic arrangements, local strain, and sluggish grain growth in the LHEA. Among other LHEAs of close density range (5.55 ≤ ρ ≤ 5.85 g/cc), the investigated LHEA exhibits outstanding nano-indentation hardness values due to the coupled grain size effect and HCP phase strengthening of the FCC matrix. As the search for LHEAs for lightweight applications grows, this study shows the potential use of AlTi 0.45 CuZn LHEA for structural applications even at elevated temperatures.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Differential multi-probe thermal transport measurements of multi-walled carbon nanotubes grown by chemical vapor deposition

Carbon nanotubes (CNTs) are quasi-one dimensional nanostructures that display both high thermal conductivity for potential thermal management applications and intriguing low-dimensional phonon transport phenomena. In comparison to the advances made in the theoretical calculation of the lattice thermal conductivity of CNTs, thermal transport measurements of CNTs have been limited by either the poor temperature sensitivity of Raman thermometry technique or the presence of contact thermal resistance errors in sensitive two-probe resistance thermometry measurements. Here we report advances in a multi-probe measurement of the intrinsic thermal conductivity of individual multi-walled CNT samples that are transferred from the growth substrate onto the measurement device. The sample-thermometer thermal interface resistance is directly measured by this multi-probe method and used to model the temperature distribution along the contacted sample segment. The detailed temperature profile helps to eliminate the contact thermal resistance error in the obtained thermal conductivity of the suspended sample segment. A differential electro-thermal bridge measurement method is established to enhance the signal-to-noise ratio and reduce the measurement uncertainty by over 40%. The obtained thermal resistances of multiple suspended segments of the same MWCNT samples increase nearly linearly with increasing length, revealing diffusive phonon transport as a result of phonon-defect scattering in these MWCNT samples. The measured thermal conductivity increases with temperature and reaches up to 390 ± 20 W m –1 K –1 at room temperature for a 9-walled MWCNT. In conclusion, theoretical analysis of the measurement results suggests submicron phonon mean free paths due to extrinsic phonon scattering by extended defects such as grain boundaries. The obtained thermal conductivity is decreased by a factor of 3 upon electron beam damage and surface contamination of the CNT sample.

42 ENGINEERING↗

Thermal Effects on Gas Pipelines

Irradiance from a nuclear weapon can be the source of heat on gas infrastructure. This exposure when sufficiently intense can result in failure. An estimation tool for this behavior is the object of this study. A lumped capacity technique is employed to estimate the system temperature rise. The temperature rise is related to three possible outcomes. Two of the outcomes are relatively certain failure and relatively certain lack of effect. A large range of exposures are assessed with the model, and a relatively small number of cases are in the uncertain range. This model is presented as a tool that can be used in conjunction with a structural assessment model to sensitivities to the overpressure and shock to screen potential outcomes from subject events .

02 PETROLEUM↗

Geometry-independent microstructure optimization for electron beam powder bed fusion additive manufacturing

The ability to manipulate the formation of microstructure is one of the potential advantages of additive manufacturing. Yet, the additive manufacturing process is riddled with complex interactions between processing parameters, geometry, and spot melting sequence which makes the task of controlling microstructure challenging. This paper proposes a method to solve the microstructure texture optimization problem by leveraging established optimization techniques and increasingly fast and accurate analytical heat transfer models. Respectively, we apply two different optimization algorithms, genetic algorithm and concurrent greedy line search, in order to induce arbitrarily shaped microstructure regions and we use a heat transfer model to evaluate the fitness of solutions in an iterative approach that is far more efficient than pure trial and error. The objective of the optimization algorithm is to control local thermal conditions – hence microstructure formation – during the melting process by manipulating the order and the dwell time of all the points of the infill pattern sequence. We then analyze the optimized sequence to determine important path characteristics that affect the microstructure formation. Through examples, we show that relative order and frequency, as measured by weighted average and variance of spot order, are important factors that influence the final characteristics.

36 MATERIALS SCIENCE↗

Empirical prediction of saline water atomization pressure loss and spray phase change using local flow pressure analysis

A pressure analysis technique was developed to obtain spray spatial evaporation profile in a thermal desalination process. The technique can replace temperature-based evaporation measurement methods that are challenged by liquid-phase interference. It also provides an alternative to optical methods with high cost and complexity. Fundamental analysis was developed to determine local humidity ratios from changes in local static and dynamic pressures. The analysis was applied to data obtained from an external mixing air-assist atomizer. An empirical model was developed for the pressure loss in atomization process and was used in the analysis of humidity ratio. The results were used to develop empirical correlations for local humidity ratio in spray mediums using inlet conditions. Utilizing inlet conditions to predict evaporation profiles is an important contribution as it eliminates the need to take local spray measurements. Obtaining local data is often difficult and expensive; Our method and correlation circumvent the need for that. Finally, the correlations presented in this paper apply to saline water sprays with total dissolved salt of 0-10 wt%. The salinity-specific correlations are accurate to within ±10% of experimental data. The individual models were aggregated into a unified correlation for salinities within 0-10 wt%. The unified correlation is accurate to within ±18% of experimental data.

42 ENGINEERING↗