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At least 667 records · Page 37

Development of the INL Thermal Energy Distribution System (TEDS) in the Modelica Eco-System for Validation and Verification

This report provides an overview on the development of the Thermal Energy Distribution System (TEDS) in the Modelica process model eco-system at Idaho National Laboratory as part of the integrated energy system initiative. Model development has led to the creation of a dynamic process model of the experimental TEDS facility housed within the Engineering Science Laboratory (ESL) at INL. The model was then used during the pre-construction phase of the experimental effort to inform experimental design (insulation requirements, bypass line placement, expected performance of components) and to test innovative control schemes prior to the initial operation. The TEDS model developed in Modelica includes the primary components of the TEDS experimental unit including: a 200kW Chromalox heater, a single-tank packed bed thermal energy storage system filled with 0.125 inch Alumina (Al 2 O 3 ), an ethylene-glycol to Therminol-66 heat exchanger, system piping, six control valves, and all associated temperature, pressure, and mass flow sensors. The model does not include nitrogen fill gas tanks, or associated overfill tanks, as these are not part of standard system control. Two simulation sets were run. The first is a five-hour test that operates as a shakedown test for the facility. This simulation puts the facility through all five potential operating modes and showcases the ability of valving, control sensors, and component controllers to meet the system demands. The second case imposes a typical summer day demand on the system from a region with mixed commercial and residential electrical needs where the generator alone cannot meet peak demand but instead requires the thermal storage unit to act as a peaking unit. Over the course of the fifteen-hour discharge cycle heat losses account for a heat loss of approximately 15°C in outlet temperature. Such heat losses would lead to a decrease in overall system efficiency and may lead to additional design changes for such designs in the future that may include a topping heater. Through commencement of this work, a systems level model of TEDS with associated control systems, sensors, piping diameters, and component capabilities has been created. This model has been utilized in the pre-experimental phase to inform system design, insulation thicknesses, and potential control schemes to operate the system effectively and safely. Once TEDS begins operation, this model will be refined, tuned, and used for validation and verification purposes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development and Validation of Two-Phase Flow Models in MOOSE for Molten Salt Reactor Application

Two-phase flow in Molten Salt Reactors (MSRs) is important as it impacts reactivity evolution, reactor transient response, and the removal of species dissolved in the molten salt through gas phase transfer. Therefore, accurately predicting the gas distribution and the associated liquid-gas interface area in MSRs is essential for their design and operation. Recently, we integrated two new models into Idaho National Laboratory (INL)’s Multiphysics Object-Oriented Simulation Environment (MOOSE): a multi-D generalization of a mixture drift-flux model and a Euler-Euler model. The Euler-Euler model offers higher fidelity, while the mixture drift-flux model provides greater computational efficiency, which is typically preferred for modeling reactor transients. However, the mixture model's accuracy in capturing void distribution and interfacial area in MSRs still needs to be assessed. This article begins with a description of the mathematical framework for the two-phase models implemented in MOOSE. It then presents validation of these models against relevant experimental data. Finally, both models are applied to the Molten Salt Reactor Experiment case study, analyzing various operational conditions such as different rates of fission product volatilization and diverse cover gas entrainment scenarios at the reactor pump. The article concludes by assessing the suitability of both models for capturing the two-phase flow dynamics critical to MSR operations.

42 - ENGINEERING↗

Machine learning for nonintrusive model order reduction of the parametric inviscid transonic flow past an airfoil

Fluid flow in the transonic regime finds relevance in aerospace engineering, particularly in the design of commercial air transportation vehicles. Computational fluid dynamics models of transonic flow for aerospace applications are computationally expensive to solve because of the high degrees of freedom as well as the coupled nature of the conservation laws. While these issues pose a bottleneck for the use of such models in aerospace design, computational costs can be significantly minimized by constructing special, structure-preserving surrogate models called reduced-order models. In this work, we propose a machine learning method to construct reduced-order models via deep neural networks and we demonstrate its ability to preserve accuracy with a significantly lower computational cost. In addition, our machine learning methodology is physics-informed and constrained through the utilization of an interpretable encoding by way of proper orthogonal decomposition. Application to the inviscid transonic flow past the RAE2822 airfoil under varying freestream Mach numbers and angles of attack, as well as airfoil shape parameters with a deforming mesh, shows that the proposed approach adapts to high-dimensional parameter variation well. Notably, the proposed framework precludes the knowledge of numerical operators utilized in the data generation phase, thereby demonstrating its potential utility in the fast exploration of design space for diverse engineering applications. Comparison against a projection-based nonintrusive model order reduction method demonstrates that the proposed approach produces comparable accuracy and yet is orders of magnitude computationally cheap to evaluate, despite being agnostic to the physics of the problem.

97 MATHEMATICS AND COMPUTING↗

White Laue and powder diffraction studies to reveal mechanisms of HCP-to-BCC phase transformation in single crystals of Mg under high pressure

Mechanisms of hexagonal close-packed (HCP) to body-centered cubic (BCC) phase transformation in Mg single crystals are observed using a combination of polychromatic beam Laue diffraction and monochromatic beam powder diffraction techniques under quasi-hydrostatic pressures of up to 58 ± 2 GPa at ambient temperature. Although experiments were performed with both He and Ne pressure media, crystals inevitably undergo plastic deformation upon loading to 40–44 GPa. The plasticity is accommodated by dislocation glide causing local misorientations of up to 1°–2°. The selected crystals are tracked by mapping Laue diffraction spots up to the onset of the HCP to BCC transformation, which is determined to be at a pressure of 56.6 ± 2 GPa. Intensity of the Laue reflections from HCP crystals rapidly decrease but no reflections from crystalline BCC phase are observed with a further increase of pressure. Nevertheless, the powder diffraction shows the formation of 110 BCC peak at 56.6 GPa. The peak intensity increases at 59.7 GPa. Upon the full transformation, a powder-like BCC aggregate is formed revealing the destructive nature of the HCP to BCC transformation in single crystals of Mg.

36 MATERIALS SCIENCE↗

3D Broadband, Noncontact, and Nonlinear Phased Array

Researchers at Los Alamos have developed a 3D broadband, noncontact, and nonlinear ultrasonic phased array technology that enables businesses to characterize and identify cracks and defects using laserbased sensing at ultra-high resolution. It can be applied to a wide range of commercial and industrial markets, e.g., aerospace, aeronautical, nuclear energy, oil and gas, and civil and material engineering and more broadly to those interested in the non-destructive evaluation (NDE) of materials and structures. Traditional phased-array technology for subsurface imaging operate over a narrow frequency range, with a limited number of sensors, using one type of ultrasonic waves which may decrease the likelihood of detecting a structural material crack. This technology fills the information gap by utilizing the potential of laser-based sensing to remove all these limitations. We are seeking a commercialization partner to license the technology or fund us through a Cooperative Research and Development Agreement (CRADA) to further develop a usable product for commercial purposes.

36 MATERIALS SCIENCE↗

ENABLING BUSINESS-DRIVEN INNOVATION THROUGH HUMAN FACTORS ENGINEERING IN NUCLEAR POWER PLANTS

For existing United States nuclear power plant fleet to remain economically viable, the nuclear industry needs to fundamentally change the way in which these plants are operated, maintained, and supported. A digital transformation is a key strategy to address this challenge. Though, guidance in this area is a continued effort. One framework to support innovation in the nuclear industry has taken a broader perspective by focusing on how technology can be used to meet specific business needs and work for the people and processes at hand. This work discusses the role and value of human factors engineering within this nuclear innovation framework. Human factors methods are presented here regarding how they address the phases of nuclear innovation. This work seeks to describe how human factors can be applied in nuclear innovation by strengthening the alignment of technology, people, processes, and regulations such that the needs of the business is addressed.

99 GENERAL AND MISCELLANEOUS↗

Anisotropic thermal-conductivity degradation in the phase-field method accounting for crack directionality

Dynamic loads applied to metals may lead to brittle or ductile fracture depending on the imposed strain rates, material properties, and specimen geometry. With an increase in the applied velocity, brittle to ductile failure mode transition may also be observed. Furthermore, at high strain rates, ductile fracture may be preceded by shear bands, which are narrow bands of intense plastic deformation, typically accompanied by a significant rise in temperature. Reliable models are needed to predict the response of metals subject to dynamic loads. In particular, capturing the interplay between heat conduction and crack propagation using the phase-field fracture method is still an open research field. To accurately capture the heat transfer physics across crack surfaces, damage models degrading thermal-conductivity are necessary. While isotropic thermal-conductivity degradation models were proposed, they may lead to errors as they are indifferent to crack directionality. In our current work, a new anisotropic approach is proposed in which thermal-conductivity, which depends on the phase-field gradient, is degraded solely across the crack. Here, it is shown that this approach improves the near-field approximation of temperature and heat flux compared with isotropic degradation, when taking the discontinuous crack solutions as reference. Additionally, the anisotropic degradation approach is implemented in a unified dynamic fracture model and a couple of examples demonstrate the viability of this approach.

42 ENGINEERING↗

On the prediction of critical heat flux using a physics-informed machine learning-aided framework

The critical heat flux (CHF) corresponding to the departure from nucleate boiling (DNB) crisis is essential to the design and safety of a two-phase flow boiling system. Despite the abundance of predictive tools available to the thermal engineering community, the path for an accurate, robust CHF model remains elusive due to lack of consensus on the DNB triggering mechanism. This work aims to apply a physics-informed machine learning (ML)-aided hybrid framework to achieve superior predictive capabilities. Such a hybrid approach takes advantage of existing understanding in the field of interest (i.e., domain knowledge) and uses ML to capture undiscovered information from the mismatch between the actual and domain knowledge-predicted target. A detailed case study is carried out with an extensive DNB-specific CHF database to demonstrate (1) the improved performance of the hybrid approach as compared to traditional domain knowledge-based models, and (2) the hybrid model’s superior generalization capabilities over standalone ML methods across a wide range of flow conditions. The hybrid framework could also readily extend its applicability domain and complexity on the fly, showing an elevated level of flexibility and robustness. Based on the case study conclusions, the window-type extrapolation mapping methodology is further proposed to better inform high-cost experimental work.

42 ENGINEERING↗

Persistent fatty acid catabolism during plant oil synthesis

Plant lipids are an essential energy source for diets and are a sustainable alternative to petroleum-based fuels and feedstocks. Fatty acid breakdown during seed germination is crucial for seedling establishment but unexpected during seed filling. Here, we demonstrate that the simultaneous biosynthesis and degradation of fatty acids begins early and continues across all phases of oil filling and throughout the photoperiod. Tests in camelina, rapeseed, and an engineered high-oil tobacco line confirmed that concomitant synthesis and breakdown in oil-producing tissues over development is the rule rather than the exception. Furthermore, we show that transgenics, designed to elevate fatty acid biosynthesis, failed to achieve anticipated increases in storage lipid levels due to increased degradation, potentially explaining the underperformance of engineered lines compared to expectations more generally.

coenzyme A↗

Machine-Learning-Guided Insights into Solid-Electrolyte Interphase Conductivity: Are Amorphous Lithium Fluorophosphates the Key?

Despite decades of study, the identity of the dominant Li + -conducting phase within the inorganic SEI of Li-ion batteries remains unresolved. While the mosaic model describes LiF/Li 2 O/Li 2 CO 3 nanocrystallites within a disordered matrix, these crystalline phases inherently offer limited ionic conductivity. Growing evidence suggests that interfaces, grain boundaries, and amorphous phases may instead host the primary fast-ion pathways. Using diffusion-based generative structure prediction and machine-learning interatomic potentials (MLIPs), we investigate lithium difluorophosphate (LiPO 2 F 2 ), a key mixed-anion decomposition product of phosphorus- and fluorine-containing electrolytes. We identify a stable crystalline polymorph and demonstrate that the amorphous counterpart is conductive, with projected room-temperature σ ≈ 0.18 mS cm –1 and E a ≈ 0.40 eV. Here, this enhancement stems from structural disorder flattening the Li site-energy landscape and a low formation energy for Li-interstitial defects, which supplies additional mobile carriers. We propose amorphous mixed-anion Li-P-O-F phases as a promising conducting medium in the SEI, offering a specific target for engineering improved battery interfaces.

Zhong, Peichen [University of California, Berkeley↗

Non-thermal resistive switching in Mott insulator nanowires

Abstract Resistive switching can be achieved in a Mott insulator by applying current/voltage, which triggers an insulator-metal transition (IMT). This phenomenon is key for understanding IMT physics and developing novel memory elements and brain-inspired technology. Despite this, the roles of electric field and Joule heating in the switching process remain controversial. Using nanowires of two archetypal Mott insulators—VO 2 and V 2 O 3 we unequivocally show that a purely non-thermal electrical IMT can occur in both materials. The mechanism behind this effect is identified as field-assisted carrier generation leading to a doping driven IMT. This effect can be controlled by similar means in both VO 2 and V 2 O 3 , suggesting that the proposed mechanism is generally applicable to Mott insulators. The energy consumption associated with the non-thermal IMT is extremely low, rivaling that of state-of-the-art electronics and biological neurons. These findings pave the way towards highly energy-efficient applications of Mott insulators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Visualization of the strain-induced topological phase transition in a quasi-one-dimensional superconductor TaSe 3

Control of the phase transition from topological to normal insulators can allow for an on/off switching of spin current. While topological phase transitions have been realized by elemental substitution in semiconducting alloys, such an approach requires preparation of materials with various compositions. Thus it is quite far from a feasible device application, which demands a reversible operation. In this work, we use angle-resolved photoemission spectroscopy and spin- and angle-resolved photoemission spectroscopy to visualize the strain-driven band-structure evolution of the quasi-one-dimensional superconductor TaSe 3 . We demonstrate that it undergoes reversible strain-induced topological phase transitions from a strong topological insulator phase with spin-polarized, quasi-one-dimensional topological surface states, to topologically trivial semimetal and band insulating phases. The quasi-one-dimensional superconductor TaSe 3 provides a suitable platform for engineering the topological spintronics, for example as an on/off switch for a spin current that is robust against impurity scattering.

36 MATERIALS SCIENCE↗

Electronic properties of epitaxial La 1- x Sr x RhO 3 thin films

Here, we report on the synthesis and electronic properties of epitaxial perovskite La 1- x Sr x RhO 3 thin films. Thin films with a Sr content ranging from $\textit{x}$ = 0 to 0.5 have been grown using molecular beam epitaxy. Transport and x-ray photoemission spectroscopy data reveal an insulator-metal-insulator transition, accompanied by a $\textit{p-}$ to $\textit{n}-$ type carrier change observed in Hall measurements. Combined with theoretical calculations, we find that the addition of Sr does not directly dope carriers into the conduction band, but rather induces localized Rh 4$\textit{d}$ states within the LaRhO 3 band gap. The bandwidth of the impurity band increases with Sr content, eventually causing the valence band (VB) and the localized Rh 4$\textit{d}$ band to overlap, which explains the first insulator-to-metal transition occurring at $\textit{x}$ = 0.35. For Sr content $\textit{x}$ > 0.4, possible cation ordering results in an increase of the gap between the VB and the Rh 4$\textit{d}$ band, leading to the second metal-to-insulator transition. We map out the electronic phase diagram of the Sr-doped LaRhO 3 system and suggest strategies to engineer the electronic states in rhodate systems via delocalizing the Rh 3+ states.

36 MATERIALS SCIENCE↗

Bicircular Light Floquet Engineering of Magnetic Symmetry and Topology and Its Application to the Dirac Semimetal Cd 3 As 2

Here, we show that bicircular light (BCL) is a versatile way to control magnetic symmetries and topology in materials. The electric field of BCL, which is a superposition of two circularly polarized light waves with frequencies that are integer multiples of each other, traces out a rose pattern in the polarization plane that can be chosen to break selective symmetries, including spatial inversion. Using a realistic low-energy model, we theoretically demonstrate that the three-dimensional Dirac semimetal Cd 3 As 2 is a promising platform for BCL Floquet engineering. Without strain, BCL irradiation induces a transition to a noncentrosymmetric magnetic Weyl semimetal phase with tunable energy separation between the Weyl nodes. In the presence of strain, we predict the emergence of a magnetic topological crystalline insulator with exotic unpinned surface Dirac states that are protected by a combination of twofold rotation and time reversal (2') and can be controlled by light.

36 MATERIALS SCIENCE↗

Probing exchange bias at the surface of a doped ferrimagnetic insulator

With the realization of stress-induced perpendicular magnetic anisotropy, efficient spin-orbit torque switching, and room temperature topological Hall effect, interest in rare earth iron garnets has been revived in recent years for their potential in spintronic applications. In this study, we investigate the magnetic properties of micrometer-thick Bi and Ga substituted thulium iron garnets (BiGa:TmIG) grown by the liquid-phase epitaxy method. Above the magnetization compensation (MC) temperature, anomalous triple hysteresis is observed in BiGa:TmIG/Pt heterostructures by anomalous Hall effect measurements. X-ray magnetic circular dichroism and energy dispersive spectroscopy measurements reveal its origin as an internal exchange bias (EB) effect arising from inhomogeneities localized at the surface of the film. Possibly depending on the difference in thickness and defect realization of the EB layer, two types of magnetization reversal mechanisms, namely, the Stoner-Wohlfarth type and the reversible domain-wall motion type, are observed. Furthermore, our results show that rich meta-magnetic phases exist in garnets close toMC, which can be robustly tuned by chemical composition engineering and conveniently probed by electrical transport measurements.

36 MATERIALS SCIENCE↗

Rapid activation of non-oriented mechanophores via shock loading and spallation

Mechanophores (MPs), stimuli-responsive molecules that respond chromatically to mechanochemical reactions, are important for understanding the coupling between mechanics and chemistry as well as in engineering applications. However, the atomic-level understanding of their activation originates from gas phase studies or under simple linear elongation forces directly on molecules or polymer chains containing MPs. The effect of many-body distortions, pervasive in condensed-phase applications, is not understood. Therefore, we performed large-scale molecular dynamics (MD) simulations of a poly(methyl methacrylate)-spiropyran copolymer under dynamic mechanical loading and studied the activation of the MP under various conditions from dynamical compression to tension during unloading. Detailed analysis of the all-atom MD trajectories shows that the MP blocks experience significant many-body intramolecular distortion that can significantly decrease the activation barrier as compared with when deformation rates are slow relative to molecular relaxation time scales. Here we find that the reactivity of MPs under material compression states is governed by many-body effects of intramolecular torsions, whereas under tension, the reactions are governed by tensile stresses.

36 MATERIALS SCIENCE↗

R-Stream

R-Stream version 3.21.3, including its TensorFlow front-end (TFRCC) and LLVM 9 front-end. This version includes the features developed in the Portacy Phase II contract. R-Stream is a source-to-source automatic parallelization engine. For usage, please refer to the manuals (In particular, user guide and release notes) available in the package.

Meister, Benoit [Reservoir Labs, Inc., Portland, O↗

Tailoring Nitinol for elastocaloric application

This study focuses on tailoring commercial Nitinol, the most commonly used elastocaloric material, for near-room-temperature cooling applications. Short heat treatments near 500 °C were used to fine-tune the material’s transition temperature, resulting in austenite finish temperatures ranging from 6.0 to 25.5°C and altered superelastic and elastocaloric properties. Plateau stresses decreased while temperature changes rose from 21.5°C up to 27.9°C at 6% strain. Significant variability in the Nitinol response when testing below its austenite finish temperature was observed. In conclusion, the effect of mechanical cycling on transition temperatures was also evaluated, demonstrating an increase for all the samples.

Efficiency↗