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At least 109 records · Page 6

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DOE OSTI2026

PDE-constrained high-order mesh optimization

Here, we present a novel framework for PDE-constrained r-adaptivity of high-order meshes. The proposed method formulates mesh movement as an optimization problem, with an objective function defined as a convex combination of a mesh quality metric and a measure of the accuracy of the PDE solution obtained via finite element discretization. The proposed formulation achieves optimized, well-defined high-order meshes by integrating mesh quality control, PDE solution accuracy, and robust gradient regularization. We adopt the Target-Matrix Optimization Paradigm to control geometric properties across the mesh, independent of the PDE of interest. To incorporate the accuracy of the PDE solution, we introduce error measures that control the finite element discretization error. The implicit dependence of these error measures on the mesh nodal positions is accurately captured by adjoint sensitivity analysis. Additionally, a convolution-based gradient regularization strategy is used to ensure stable and effective adaptation of high-order meshes. We demonstrate that the proposed framework can improve mesh quality and reduce the error by up to 10 times for the solution of Poisson and linear elasto-static problems. The approach is general with respect to the dimensionality, the order of the mesh, the types of mesh elements, and can be applied to any PDE that admits well-defined adjoint operators.

Computer science↗

DOE OSTI2024

The environmental impact of hydropower: a systematic review of the ecological effects of sub-daily flow variability on riverine fish

Hydropower can help facilitate power grid decarbonization because it can respond to short-term changes in power demand and is comparatively more reliable than intermittent wind and solar. However, flexible hydropower operations can create rapid and abnormal fluctuations in downstream flow conditions, which can negatively impact aquatic ecosystems. Accordingly, we conducted a systematic review on the ecological effects of hydropower-driven sub-daily flow variability (SDFV) on riverine fishes. We reviewed and synthesized 109 articles relevant to fish-SDFV relationships from seven sources, most of which focused on Salmonids in North America and northern and western Europe and were published in the last 15 years. We found strong agreement in the literature that SDFV increases fish stranding risk, destabilizes habitat, and decreases production and diversity. We found moderate agreement that SDFV interrupts fish reproduction, increases or has no impact on condition, and prompts or discourages movement depending on local channel conditions. We found little to no agreement for relationships between SDFV and mortality, physiology, and behavior. The effects of SDFV on riverine fish ecology are intertwined in the complex suite of biotic and abiotic characteristics that structure aquatic ecosystems and are highly site-, species-, and life stage-specific. Assessments of the impact of SDFV on fish ecology should first characterize local habitat and channel quality and fish community composition to identify specific, measurable ecological outcomes to sustain or enhance, and then design mitigation strategies tailored to those ecological objectives.

13 HYDRO ENERGY↗

DOE OSTI2024

Sensory integration for neuroprostheses: from functional benefits to neural correlates

In the field of sensory neuroprostheses, one ultimate goal is for individuals to perceive artificial somatosensory information and use the prosthesis with high complexity that resembles an intact system. To this end, research has shown that stimulation elicited somatosensory information improves prosthesis perception and task performance. While studies strive to achieve sensory integration, a crucial phenomenon that entails naturalistic interaction with the environment, this topic has not been commensurately reviewed. Therefore, here we present a perspective for understanding sensory integration in neuroprostheses. First, we review the engineering aspects and functional outcomes in sensory neuroprosthesis studies. In this context, we summarize studies that have suggested sensory integration. We focus on how they have used stimulation-elicited percepts to maximize and improve the reliability of somatosensory information. Next, we review studies that have suggested multisensory integration. These works have demonstrated that congruent and simultaneous multisensory inputs provided cognitive benefits such that an individual experiences a greater sense of authority over prosthesis movements (i.e., agency) and perceives the prosthesis as part of their own (i.e., ownership). Thereafter, we present the theoretical and neuroscience framework of sensory integration. We investigate how behavioral models and neural recordings have been applied in the context of sensory integration. Sensory integration models developed from intact-limb individuals have led the way to sensory neuroprosthesis studies to demonstrate multisensory integration. Neural recordings have been used to show how multisensory inputs are processed across cortical areas. Lastly, we discuss some ongoing research and challenges in achieving and understanding sensory integration in sensory neuroprostheses. Here, resolving these challenges would help to develop future strategies to improve the sensory feedback of a neuroprosthetic system.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

In-Situ Synchrotron X-Ray Diffraction of Ultrasonic Microstructural Refinement During Solidification in a Commercial Al–Si–Mg Alloy

This study reports the first use of in-situ synchrotron X-ray diffraction (SXRD) to study the effects of ultrasonic melt processing (USMP) on phase and grain size evolution during solidification in a commercial Al–Si–Mg casting alloy. USMP is a technique that, when applied to aluminum as it solidifies, can be used to refine the local microstructure of large-scale castings. Analysis of the in-situ SXRD data to estimate the average grain size of primary α-Al grains during USMP demonstrates that USMP slows the growth rate of α-Al grains and reduces grain size by 36 pct. Furthermore, there is also evidence that USMP causes the primary α-Al grains to move relative to the X-ray beam; such motion increases the probability of primary α-Al grains colliding and fragmenting. This movement becomes constrained at the onset of the Al–Si binary eutectic, suggesting that USMP ceases to effectively refine the microstructure once the Al–Si binary eutectic begins to form. Complementary laboratory-scale X-ray diffraction (XRD) data were used to correlate the lattice parameters of the α-Al and Si (D-A4) phases with temperature to estimate cooling rate during solidification. Thus, this study can guide the design of novel castings with spatially distributed fine-grained regions produced using local ultrasonic processing.

Aluminum Alloys↗

DOE OSTI2025

Asymmetrical cavity design that bypasses mode mixings in axion haloscope experiments

Microwave cavities used in axion haloscope experiments typically employ a tuning rod as a means to widen the range of resonance frequencies at which it is sensitive to axion-to-photon conversion. A realistic tuning mechanism requires a gap between the cavity end caps and the tuning rod to ensure movement, and causes some modes to hybridize with the resonant mode that is being tracked for the experiment. These so-called mode mixings lead to gaps in the frequency range that practically lose sensitivity to axions. Here, to solve this problem, we present a cavity design which, for two tuning rod configurations corresponding to a lower and higher frequency range, have a dielectric rod inserted at a specific location that makes the cavity asymmetrical. Moving the tuning rod closer to the dielectric insert changes the location and frequency of the mode mixing compared to when it is farther away from it. This design is easily realizable in practical experiments and makes possible an axion dark matter search with minimal loss in sensitivity due to mode mixings. We also show that the same design has the same desired effect when cavity dimensions are scaled down to be smaller and are at higher resonance frequencies.

Axion↗

DOE OSTI2026

Thermo-hydro-mechanical analysis of subsurface ice-based thermal energy storage

Ice-based thermal energy storage systems are widely utilized for cooling and managing peak electrical demand globally, offering daily or weekly storage capabilities for both individual homes and larger office buildings. However, scaling these systems for district-level cooling or integrating them with renewable energy sources presents challenges, especially in accommodating larger volumes and addressing seasonal storage requirements in densely populated urban areas. This paper proposes a novel solution by evaluating subsurface ice-based thermal energy storage, in which the underground is subjected to seasonal freeze/thaw cycles. However, these cycles may influence ground behavior, affecting pore pressure and inducing ground movement. To systematically investigate these challenges, we enhance the TOUGH-FLAC simulator by integrating water/ice phase change capabilities and updating the effective stress–strain constitutive relation. Both modifications are validated against analytical solutions or experimental data. Through numerical simulations spanning a decade with ten seasonal freeze/thaw cycles, we evaluate the performance and long-term stability of a generic subsurface ice-based thermal energy storage system, considering factors such as ground permeability, freezing pipe spacing, freeze/thaw damage, and glycol solution temperature. The simulations indicate that ice formation induces pore pressure variations that drive seasonal surface heave and settlement, controlled by ground permeability, pipe spacing, and glycol solution temperature, along with tensile and localized shear deformation around freeze pipes. This highlights the need for accurate ground property characterization and geomechanical analysis for subsurface ice-based thermal energy storage.

Ground freezing↗

DOE OSTI2024

Atomistic simulations to reveal HIP-bonding mechanisms of Al6061/Al6061

Molecular dynamics simulations were employed to understand the diffusion bonding process during hot isostatic pressing (HIP) of Al6061/Al6061 alloy. Simulations of the HIP process reveal atomistic phenomena that are difficult or unlikely to be observed experimentally and provide useful insights into the mechanism of diffusion and bonding. Here, the results reveal that at the start of the HIP process, a massive incursion of oxygen atoms occurs from the pre-existing γ-Al 2 O 3 to the 6061 region across the interphase interface. These oxygen atoms interact with the enriched Mg atom layer present at the existing γ-Al 2 O 3 and 6061 matrix to form a secondary complex Mg 2 Al 2 O 5 phase. Diffusion calculations also show that transport of atoms due to the applied pressure is 4–5 orders of magnitude higher than would occur in the absence of HIP conditions. The Mg 2 Al 2 O 5 phase also provides efficient pathways for the rapid transport of Mg atoms. Because of the higher diffusion coefficients observed for Mg within the phase, Mg atoms can move more swiftly compared to their diffusion within other phases such as γ-Al 2 O 3 . This accelerated mobility facilitates the rapid movement of Mg atoms across the interface, leading to changes in the local composition and the potential growth of the Mg 2 Al 2 O 5 phase.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Modeling powder spreadability in powder-based processes using the discrete element method

Powder-bed fusion (PBF) processes refer to a subset of Additive Manufacturing (AM) techniques where powder is spread on the build-plate before melting (by a laser or electron beam). While PBF processes are attractive due to their ability for realizing complex structures that are either difficult or impossible to create through conventional means, the parts fabricated with these techniques can exhibit defects such as pores, inclusions, and excessive surface roughness. To minimize these defects, much research has been dedicated towards process maturation by optimizing laser or electron beam parameters. However, these developmental efforts typically do not address the recoating process where achieving dense and uniform layers of powder is a necessity for ensuring process repeatability and part quality. While the recoating process can be studied through experimentation, the dynamics of particle movement are difficult to analyze experimentally. Therefore, here, in this study, powder spreading in PBF was simulated through the Discrete Element Method (DEM) to elucidate the mechanisms that control powder-bed quality. Utilizing the Buckingham Pi theorem, a dimensionless metric referred to as the spreading index is developed that combines powder-bed density, roughness, and particle size to assess the quality of powder layers. The formulated spreading index is then related to several dimensionless quantities that provide insight into the mechanisms dominating powder spreading in PBF. The DEM simulations conducted in this work focused on the scenario where powder is spread onto an existing powder bed and revealed that a reduction in the recoating velocity causes an increase in the spreading index while little to no impact on the spreading index was observed when varying layer thickness from 30 μm to 75 μm.Particle size effects on the powder-bed quality were also investigated.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Operando synchrotron X-ray analysis of melt pool dynamics in an Al-Sn immiscible alloy

The melt flow in an Al-50vol.% Sn immiscible alloy, produced by single-track laser melting of Al and Sn elemental powders, was studied in real time. High-speed synchrotron X-ray imaging was used to track Al and Sn liquids’ movements, and also to examine elemental distributions in the laser tracks, complimented by electron microscopy after solidification. Key aspects, including melt pool geometry, keyhole instability, and flow dynamics (flow pattern and velocity), were examined using digital image analysis. Relatively deeper melt pools formed at 400 W and 300 mm/s exhibited greater stability, with smooth surfaces, consistent outward flow, and minor vortices near the keyhole. In contrast, shallower pools produced at higher scanning speeds (>500 mm/s) demonstrated greater instability with increased surface waviness, and stronger velocity fluctuations, leading to numerous micro-vortices and increased Al-Sn heterogeneity. Velocity scale estimations, supported by experimental observations, examined the roles of vapour pressure, Marangoni effect, buoyancy, inertial, and surface tension forces in the flow. The results revealed that vapour pressure and mechanical waves dominated at high scanning speeds (shallow pools), while Marangoni forces were equally significant in deep pools at lower speeds (300 mm/s). Buoyancy was found to have minimal impact in both cases. Furthermore, the interaction between inertial and surface tension forces played a critical role in determining the degree of waviness of the pools’ surfaces. These findings offer valuable insights into melt pool dynamics during laser processing of immiscible alloys and other metallic systems using elemental powders, and provide guidance for developing high-fidelity computational fluid dynamics models.

immiscible alloys↗

DOE OSTI2026

Agentic traffic intelligence: Augmented human-in-the-loop scenario generation for microscopic traffic simulation

Traditional microscopic traffic simulation generation often relies on static datasets and manual design, limiting its ability to simulate complex conditions easily. This paper presents a novel framework, Agentic Traffic Intelligence, which combines human approval large language models (LLMs), the Real-Twin tool, and multi-agent systems to perform realistic microscopic traffic simulation scenario generation. The proposed framework incorporates human-in-the-loop (HIL) control, retrieval-augmented generation (RAG), and multi-agent control mechanisms. HIL mechanisms are used to guide multiple LLMs focused on attributes for microscopic simulation generation and to improve the interpretability and transparency of LLM execution for users. RAG enhances context extraction by dynamically integrating external knowledge sources for traffic scenario generation foundations. A multi-agent architecture with supervisory control coordinates the interaction of simulation components, including traffic simulators, control logic, and calibration tools. This enables the synthesis of simulation-ready scenarios that reflect dynamic demand profiles and behavior controls. Furthermore, the framework fuses multisource traffic data with unstructured context and supports iterative refinement through interactive user feedback. Validated through microscopic simulation using Simulation of Urban Mobility, the generated scenarios demonstrate high-fidelity network generation with inflow and turn movement and behavioral calibration, offering a robust and efficient tool for stress-testing and optimizing urban mobility systems.

Hierarchical multi-agent control↗

DOE OSTI2024

Innovative control mechanism for research and test reactors using mandrel-shaped control rods

Research and test reactors have historically played a pivotal role in supporting the initial development of nuclear reactors. They continue to provide essential data for enhancing fuel designs and material knowledge. However, with many such reactors aging and the growing demand for data to bolster advanced reactor development, it is more necessary to research potential design attributes of the next generation of research and test reactors. For test reactors dedicated to fuel and material testing, the design of control mechanisms significantly influences the stabilization of neutron flux levels in irradiation positions while sustaining criticality. This study presents an innovative control mechanism for potential research and test reactor designs. It employs small absorber rods that move in opposite axial directions to maintain axial symmetry of power and neutron flux during burnup cycles. These rods maximize reactivity worth while also offering flexibility to flatten the radial power distribution. An axial translation of the control mechanisms’ absorbers, as compared to the rotational movement of absorbers in control cylinders, also provides a benefit to available excess reactivity and cycle length. Additionally, this work utilizes a simplified core model of the Advanced Test Reactor to assess the performance of this control mechanism. Compared to the current control system based on rotating control cylinders, the new control mechanism has the potential to enhance, or at least maintain, neutronic performance parameters in this reactor design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Evaluation of color in digital nuclear power plant control room displays

Human system interface design in industrial process control is guided by industry standards, human factors best practices, and domain-specific conventions, and often there is a conflict between one or more of the sources of design input for specific design elements. In the nuclear domain, one design element for which conflict arises is the use of color to represent equipment state. Here, this study evaluates the tradeoffs associated with using color in a process control display versus using white and shades of gray. The performance metrics were response time, accuracy, and eye movement metrics using a simplified experimental task and professional operators. Results revealed that adhering to color conventions in nuclear power yielded small advantages in simple tasks, but did not exist for more complex tasks. The results did not provide strong evidence for or against using a particular color scheme and revealed the need for further research on the use of color for commercial nuclear power plants and other process control industries.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Prediction of α $IIb$ $β$ 3 integrin structures along its minimum free energy activation pathway

The adhesion protein integrin is a transmembrane heterodimer that plays a pivotal role in cellular processes such as cell signaling and cell migration. To execute its function, integrin undergoes extensive conformational changes from a bent-closed to an extended-open state. Resolving the structures across these changes remains a challenge with both experimental and computational methods, but it is crucial for understanding the activation mechanism of integrin. We address this challenge for the platelet integrin α IIb β 3 by employing finite temperature string method with structures of the images along the initial guess path generated by a multiscale data-driven framework. The full-length all-atom structures along the resulting minimum free energy path between the inactive bent-closed and active extended-open states of α IIb β 3 integrin are consistent with a variety of experimentally resolved structures. Changes in these predicted structures along the path show that the extension and separation of the α and β subunits from the bent-closed to the extended-open state require correlated movements between the subdomain pairs in α IIb β 3 . Furthermore, these results provide new insights into integrin activation mechanism, and the predicted structures have potential applications in guiding the design of integrin-targeting therapeutics.

Dasetty, Siva [University of Chicago, IL (United S↗

DOE OSTI2026

Effects of oxide surface chemistry on diffusioosmosis

Diffusioosmosis is the movement of fluid induced by gradients in solute concentration. Recent studies suggest that in low permeability rocks, it may be the dominant mode of reactant transport and thus control rates of diagenesis, which cannot be adequately explained by pressure-driven flow alone. In this paper we investigate how the equilibrium between an oxide mineral and the surrounding fluid phase influences the diffusioosmotic velocity. We have developed a theory for the case of a thin double layer, where the Debye length is smaller than the characteristic pore size. Several factors contribute to the total fluid velocity: the chemical structure of the mineral surface, the electrolyte type and concentration gradient, and the solution pH. Individual factors can act in concert or in opposition, leading to widely varying magnitudes and directions of the velocity. The numerical results are within the range of the limited experimental data. Our results highlight how surface charging and surface complexation impact the flow, and how they depend on pH.

Diagenesis↗

DOE OSTI2025

Development of an interatomic potential for the Ta–Li system

A new interatomic potential for the Ta–Li system is introduced to facilitate the study of phase stability, mechanical properties and non-equilibrium dynamics after Li implantation in Ta. Here, this potential is based on a generalization of the embedded atom method (GEAM) and includes contributions from embedding energy, explicit two- and three-body interactions, and nonlocal many-body interaction terms. The parameters of the potential are optimized using energies and atomic forces for a wide range of configurations obtained from ab initio density functional theory (DFT) calculations. The potential is rigorously validated across a range of physical properties, including elastic constants, equations of state, phonon dispersion curves, point defect properties, and melting temperatures for different compositions. Although our potential is trained on a small dataset, its accuracy is comparable to that of available machine learning potentials for Li and Ta. Our simulations show that at temperatures below 500 K, Li atoms in Ta–Li alloys form clusters separated by Ta-rich domains, and we find no evidence of ordered phase formation. For Li concentrations below a few percent, Li atoms preferentially segregate to surfaces and grain boundaries. However, in alloys containing more than ~10% Li, the accumulation of Li in symmetric-tilt grain boundaries can lead to one of the following effects: formation of amorphous-like regions, changes in grain boundary structural units, or lateral movement of the grain boundary.

GEAM potential↗

DOE OSTI2025

Coupled THM modeling of bentonite heating and hydration in tank tests with a new temperature-dependent water retention model

This study presents a coupled thermo-hydro-mechanical (THM) model for simulating the heating and hydration behavior of bentonite, a buffer material in deep geological repositories (DGRs). The model incorporates a new temperature-dependent soil water retention curve which captures the thermal-induced shift in water retention behavior. It also distinguishes between liquid and gas permeability, modeling intrinsic gas permeability as a function of accessible porosity to improve vapor transport and desaturation predictions. The model was validated against two large-scale tank tests, demonstrating good agreement with measured temperature, relative humidity, and water inflow data. It revealed a complex porosity evolution driven by thermal expansion, vapor movement, vapor condensation, and hydration-induced swelling during heating and hydration processes. The simulation results also suggest that the permeability of the hydration layer plays a critical role in controlling water intake. Clogging of this layer can significantly reduce the volume of water inflow during the hydration phase. Furthermore, while the model effectively captures key THM behavior, further development of the mechanical constitutive law is required to account for possible thermo-elasto-plastic volume changes and microstructural effects. Overall, the model provides a robust tool for evaluating the evolution of bentonite-based barrier material in DGRs.

Guo, Guanlong [Lawrence Berkeley National Laborato↗

DOE OSTI2025

Surviving nanoscale interfacial stability in extreme thermal expansion contrast Zn(CN) 2 -epoxy resin matrix composites

Here, we report the remarkable stability at the nanoscale matrix-filler interface in a series of overall low coefficient of thermal expansion (CTE) zinc cyanide (ZC)/epoxy resin composites. These interfaces demonstrate the stability of highly contrasting materials. These composites are designed to optimize the properties of both materials: epoxy resins are valued for their high strength, superb chemical resistance, low dielectric properties, and adhesive abilities. ZC, a model flexible framework, exhibits negative thermal expansion (NTE) behavior and compensates for the epoxy resin’s detrimentally large thermal expansion values. Filled resins minimize the native 65 ppm/°C CTE values to 19 ppm/° C over a wide temperature range while maintaining linearity, yielding composites compatible with typical metal and ceramic substrates’—commonly bonded to the resin— 0–20 ppm/° C CTE values. Additionally, with significant intrinsic differences in the materials, we use wide-angle X-ray diffraction and atomic force microscopy to elucidate thermal movement. The ZC/epoxy interface is surprisingly resilient over 1,000 cycles between -55° C and 75° C, extremes typical to aerospace applications. Further, we show that the resin viscosity remains less than 21 Pa*s at up to 30 vol% ZC, an important consideration for workability. We also discuss settling distribution, glass transition temperature, flexural strength, and longevity. All results point favorably towards practical implementation in low thermal expansion application needs: filling the gap in component design.

42 ENGINEERING↗

DOE OSTI2024

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗