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DOE OSTI2026

Dominant Controls on Preferential Flow and Their Implications for Future Soil Water Fluxes

Abstract Soil water flow, particularly preferential flow (PF), is a critical control on hydrological and biogeochemical processes, including groundwater recharge, contaminant transport, and carbon cycling. However, it remains challenging to predict PF occurrence across large environmental gradients. Here, we developed a deep learning (DL) model to estimate event‐scale soil water flow velocity and the probability of PF occurrence using high‐frequency soil moisture and precipitation data from 33 sites across the National Ecological Observatory Network. The model demonstrated high skill in predicting the binary occurrence of PF (91% F1‐score; 85% accuracy) but the performance was limited in predicting soil water velocity ( R 2 = 0.31). We found that precipitation characteristics (duration, volume, and intensity) were the most important predictors for soil water velocity. Among the non‐precipitation event variables, sand content showed relatively high predictive skill, though differences among non‐event climate variables were generally modest. Lower sand content was associated with increased predicted soil water velocity, a finding that highlights the role of soil structure in producing more non‐uniform flow, which contrasts with traditional uniform flow models. Projecting a reduced DL model under both moderate and high‐emissions future climate scenarios (2060–2099 Representative Concentration Pathways 4.5 and 8.5), we found ∼7.3% increase under RCP4.5 and ∼15% under RCP8.5 of soil water velocities compared to the historical simulation, while modeled likelihood of PF changed little. These findings suggest climate change is not making PF more frequent, but it is making existing PF pathways more efficient with important consequences for associated nutrient and contaminant transport under climate change. Plain Language Summary Water movement in soil is critical for water quality. While often modeled as a uniform flow process, in reality water moves rapidly through cracks and burrows in what is called “preferential flow” (PF), which limits natural filtration and can transport pollutants. We developed a deep learning model, trained on data from 33 U.S. sites, to predict when and how fast this PF occurs based on precipitation, soil, and climate data. The model showed that precipitation characteristics (duration, intensity, volume) were the most important predictors of PF. Lower soil sand content/higher clay content was associated with faster water flow, likely due to clay soils forming aggregates and cracks that water moves through rather than infiltrating uniformly. Further analyses based on climate projections suggest that the speed at which PF occurs will become more rapid under future climate scenarios compared to historical simulation. This highlights the need to represent PF in soil water models when assessing future water quality. Key Points The effect of precipitation peak intensity on soil water velocities declined with increasing precipitation intensity Antecedent soil moisture failed to predict preferential flow (PF), contrasting the high predictive power of sand content Climate predictions suggest that soil water velocities through PF paths will increase ∼15% by 2099

Li, Bonan↗

DOE OSTI2024

A method for generating quantitative vapor-phase infrared spectra of solids: results for phenol, camphor, menthol, syringol, dicyclopentadiene and naphthalene

Here, a method is presented to generate quantitative vapor-phase infrared spectra from substances that naturally occur as solids with moderate volatility. The solid is gravimetrically dissolved into a solvent that has few infrared spectral features, typically CS 2 and CCl 4 separately. The solution is flowed at a constant rate from a linearly pumped syringe into a metered stream of nitrogen carrier gas regulated by a mass flow controller. The analyte/solvent mix is flash vaporized by volatilizing the solution across a heated stainless-steel surface as it emanates from the syringe tip. The N 2 gas-solution mixture is flowed into a long-path White cell thermostatted at a desired temperature, the long optical path compensating for the modest analyte mixing ratio. A composite spectrum is generated from typically ten or more 760-Torr pressure-broadened spectra over the 600 to 6500 cm -1 spectral range at 0.1 cm -1 spectral resolution. The solid analytes reported here using this novel technique include dicyclopentadiene, menthol, syringol, phenol, camphor, and naphthalene.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗

DOE OSTI2026

Optimization techniques in self-similar compressible flow

We investigate the one-dimensional (1D) inviscid compressible flow equations for an ideal gas through the lens of optimization techniques. It is the case that, to our knowledge, optimization analysis applied to the so-called “linear velocity” solutions of the Euler compressible flow equations has not been previously conducted. Through both gradient-based and variational techniques, new variants of well-studied flow scenarios, i.e., self-similar, 1D, linear velocity solution class to idealized inviscid compressible flow equations, are determined, as encoded in both the kinematic and thermodynamic properties of this self-similar solution class. With the kinematics of the said solutions being driven by a self-similar “scale radius” and the thermodynamics being driven separately through the appearance of an arbitrary function, a myriad of new solution classes is possible. Acting as a guide to more realistic physical circumstances as well as discovery, it is the hope that the presented cases serve as the framework for future investigations into the intersection of self-similarity and optimization techniques. Fields of study that may find this work to be of interest include aerodynamic design, flow control, inertial confinement fusion, physics-informed neural networks, and other related areas of interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Hydrogen Recombiner Catalyst Evaluations for Waste Storage

Radiolysis of water in nuclear waste storage generates hydrogen gas that can accumulate within sludge style waste and be rapidly released during agitation events, creating a significant flammability hazard. Engineering controls are therefore required to limit hydrogen concentrations during both quiescent storage and transient disturbances. Catalytic recombination of hydrogen in waste storage offgas is a proven mitigation strategy, maintaining hydrogen levels below flammability limits and managing sudden concentration spikes. Conventional recombiners rely on platinum and/or palladium catalysts, with development efforts focused on extending service life, increasing active surface area, and ensuring safe deployment in radioactive environments. Savannah River National Laboratory (SRNL) is evaluating a newly developed hydrogen recombiner catalyst from Canadian Nuclear Laboratories as a cost-effective and durable alternative for nuclear waste applications. Testing was conducted in SRNL’s Shielded Cells facility, which enables reduced-scale experimental modeling under radiation fields and near-use-case conditions relevant to radioactive waste storage. Catalyst performance was evaluated using a custom offgas characterization system designed for near-zero flow conditions. The experimental apparatus consisted of a gas-tight 2.7 L PTFE vessel equipped with temperature monitoring, gas flow controls, and a variable-speed mixer to simulate sludge agitation. Offgas composition was monitored using a dedicated gas chromatograph with argon carrier gas and a krypton internal standard. Measurements were obtained for an empty vessel, the vessel containing a well characterized radioactive tank waste sample, and the same configuration with the candidate catalyst installed. Results demonstrate that the new catalyst effectively reduced hydrogen concentrations in the offgas within the constraints of the experimental design. In addition to confirming catalytic activity, the testing provided valuable insights into experimental optimization and considerations for future performance evaluations. These findings support the potential scalability of the technology and highlight its applicability to broader nuclear waste management operations, offering improved safety and reduced operational costs through enhanced catalyst durability and lower replacement frequency.

Tener, Zachary P. [Savannah River National Laborat↗

DOE OSTI2024

Experimental Operation of a Prototype 750C Advanced Chloride Molten Salt Bellows Valve

To achieve DOE 2030 SunShot targets that reduce the cost of liquid-based solar by an additional 40% to 70% beyond 2018 costs, a more reliable, highly manufacturable flow valve, capable of achieving operational temperatures of >700°C is required [1]. This paper investigates the development of an innovative high-temperature chloride molten salt valve, with operation up to 750°C. This valve is intended to be employed within Gen 3 CSP liquid-based thermal energy storage (TES) systems as well as Gen 4 modular salt reactor (MSR) technologies. This work details the general design and flow testing of a bellows-seal flow control valve (FCV). This design includes an integrated closed-loop thermal control system to ensure robust design for freeze-thaw cycles. The self-contained thermal management STM system, is unique in the salt valve industry since it is an integrated solution to provide a consistent, repeatable alternative to typical heat tracing. Additionally, the design includes the employment of a novel heat pipe valve stem to facilitate enhanced passive thermal management into the valve assembly. This valve stem heat pipe is designed to facilitate natural circulation within the bonnet to ensure robust operation, during both nominal and transient thermal operation. The valve body and trim will be designed using SS316H, consistent with Flowserve Corporation’s existing product base and is code qualified but will utilize clad material for materials corrosion, manufacturing cost reduction and compatibility to ensure design flexibility. A test campaign was performed in this investigation utilizing a novel 750°C ternary chloride (20%NaCl/40%MgCl2/40%KCl by mol. wt. %) molten salt flow loop. A discussion about the design and installation of the valves within this test bed is provided for this investigation. Valve test results from this study assessed Cv curves as well as multiple actuator cycles, under varying thermodynamic and operational mode conditions, which would be characteristic within a commercial molten salt facility. The results indicate nominal operation for the baseline design, though improved performance and reliability is expected with the full designed FCV.

Armijo, Kenneth (ORCID:0000000346832147)↗

DOE OSTI2025

Tunable shear thickening, aging, and rejuvenation in suspensions of shape-memory-endowed liquid crystalline particles

The morphological features of particles, notably shape anisotropy, critically influence the rheological properties of dense suspensions, spanning both natural and engineered systems. This work explores the potential of using shape memory particles to dynamically regulate suspension fluid flow through controllable shape transformations. First, we synthesize shape-memory particles with programmable anisotropy from liquid crystal elastomers, such that the stiffness and shapes of the particles can be tuned by manipulating temperature. Our findings reveal that suspensions from such particles exhibit significant tunability in shear thickening behavior, transitioning from discontinuous shear thickening to a Newtonian-like response within a narrow temperature range of 60 ° C. This capability to modulate rheological responses in situ presents an approach for addressing processing challenges in many applications where control over flow behavior is paramount. Furthermore, we also show that suspensions composed of these anisotropic particles can undergo physical aging, and evolve into a glassy state. This state can be escaped upon activation of the shape memory effect. This reversibility underscores the potential for using such materials to engineer systems that can enter or come out of kinetic arrest by leveraging internal mechanical responses to external stimuli. The insights gained here not only broaden our understanding of the interplay between particle geometry and suspension dynamics but also pave the way for leveraging ensembles of stimuli-responsive objects to precisely control collective behaviors in many-body systems.

Science & Technology - Other Topics↗

DOE OSTI2026

Memory-efficient nonsmooth dynamic optimization using adaptive randomized compression

Dynamic optimization problems arise in many applications including flow control, full waveform inversion, and medical imaging. These problems are plagued by significant computational challenges. One such challenge — and the focus of this work — is the memory limitation induced by the size of the underlying dynamical system. In particular, the entire dynamic trajectory is required for derivative computation and therefore must be stored or recomputed using, e.g., checkpointing. Although recent work demonstrated the use of adaptive randomized sketching to overcome the memory challenge, that work only applies to smooth unconstrained problems, prohibiting its use for nonsmooth regularized and constrained problems. The inclusion of nonsmooth regularizers and constraints is critical as they often arise in an attempt to preserve certain physical properties or to promote sparsity. To solve these problems, we introduce a trust-region algorithm for minimizing the sum of a smooth nonconvex function and a nonsmooth convex function that leverages randomized sketching to compress the dynamical system trajectories and adaptively adjust the sketch rank to satisfy a gradient inexactness condition. We prove convergence of this algorithm and demonstrate that it achieves substantial memory reduction on three discretized PDE-constrained optimization applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

A statistical and simulation-informed model for estimating permeability from pore size distribution in saturated geomaterials

Accurate permeability estimation is essential across subsurface engineering applications but remains challenging due to the complex pore structures of natural geomaterials. Traditional empirical methods and simplified theoretical models often inadequately capture the role of pore size distribution and connectivity. Here, this study develops a statistical and simulation-informed permeability model that collapses pore-scale complexity into a compact scaling of the form k = αϕμ d 2 , where ϕ is porosity, μ d is mean pore size, and α is a weakly varying coefficient. By combining pore network simulations with statistical analysis of unimodal and bimodal pore size distributions, we identify three key findings: (i) permeability is much more sensitive to mean pore size than to porosity; (ii) across extensive datasets, the ratio σ d /μ d (standard deviation to mean) clusters around a characteristic value ∼0.4, allowing the effects of the full pore size distribution to be represented by μ d and a narrowly varying α ≈ 0.05; and (iii) for bimodal systems, there exists a critical fraction of small pores ∼0.78 above which flow becomes small-pore dominated, enabling the definition of an effective flow-controlling pore population and facilitating simplified permeability estimation for such systems. The resulting model, which requires only porosity and a representative mean pore size as inputs, is validated against comprehensive experimental datasets (>1700 samples) spanning diverse soils and rocks and achieves good predictive accuracy. Overall, this work provides a physically grounded yet practically simple permeability estimator suitable for subsurface engineering, environmental protection, and resource management applications.

Permeability↗

DOE OSTI2026

Slow-Light Mid-IR Silicon Photonic Chips for NO 2 and CH 4 Gas Detection

A compact, chip-scale mid-infrared gas sensor is demonstrated, leveraging a two-dimensional photonic crystal waveguide (PCW) fabricated on a silicon-on-insulator (SOI) platform. The PCW comprises a hexagonal lattice with lattice constant a = 860 nm and hole radius r = 0.22a, incorporating a central line defect of reduced-radius holes (r s = 0.7r) to induce slow-light propagation near the photonic band edge with a group index of approximately 73, thereby enhancing light-matter interaction. The sensor operates at fundamental absorption wavelengths of 3.42 μm for nitrogen dioxide (NO 2 ) and 3.40 μm for methane (CH 4 ), utilizing the strongest molecular vibrational transitions for maximum sensitivity. Experimental validation was conducted using dynamically diluted gas mixtures generated by mass flow controllers, with signal acquisition performed by a liquid nitrogen-cooled InSb detector. For NO 2 , the sensor exhibited excellent linear response over 5–25 ppm (part per million) with coefficient of determination R 2 = 0.9934, achieving a detection limit of 210 ppb (part per billion)─representing the first reported silicon photonic-based NO 2 detection. For CH 4 , exposure to 25 ppm resulted in a 6.4% decrease in transmitted intensity, demonstrating multigas sensing capability. The CMOS-compatible fabrication process and compact 3 mm device footprint establish this SOI-PCW platform as a scalable, low-power solution for integrated mid-infrared gas sensing, with significant potential for environmental monitoring and industrial safety applications.

Crystals↗

DOE OSTI2026

DISARM: Target Electronic Device Informed Mitigation of Software Runtime Side-Channel Vulnerabilities

Program runtime/timing attacks exploit variations in a program’s execution times to extract sensitive information from the program (e.g. encryption keys, sensitive variable data, intellectual property). State-of-the-art solutions to runtime side-channel attacks attempt to balance the execution time of the sensitive code for different control flow paths to eliminate the timing leakage. However, during the mitigation process, most techniques do not consider the underlying hardware/device on which the target program is supposed to run on. This can lead to over-fixing (unnecessary extra operations), under-fixing (not solving the imbalance properly), and even failures. Here, we propose DISARM, a joint hardware-software methodology (unlike any existing solution) for mitigating runtime side-channel vulnerabilities that utilizes timing values from real embedded devices to generate targeted software fixes. We implement DISARM to support C/C++/Java source codes and validate it across 22 standard benchmarks. DISARM outperforms state-of-the-art solutions such as PENDULUM and DifFuzzaR in terms of execution time overhead, code size overhead, and correctness on five different embedded/edge devices.

Timing/runtime side-channel↗

DOE OSTI2024

Guest Editorial Special Section on Advanced Medium-Voltage Power Electronics for Grid Interactive Applications

Medium-voltage power electronics (MVPE) plays essential roles in power grid modernization and links the MV distribution grid with low-voltage consumers and prosumers. Various MVPE devices, such as solid-state transformers or circuit breakers, inverter-based resources, power flow controllers, etc., bring the benefits of voltage conversion and power regulation in small footprint, power quality and efficiency improvements, and enhancements of grid controllability, flexibility, stability, and resilience. The MVPE also makes it possible for sustainable energy systems, such as solar/wind farms and energy storage generating facilities, to directly access to MV grids without multistage conversions. With their intrinsic intelligence and communications, MVPE enables many new smart grid functions and applications, e.g., dc interconnections and electric vehicle charging, which were not envisioned by traditional power grids otherwise. In addition, the integration of physical power processing units with cyber components forms a cyber-physical system, which is essential for long-term sustainability, development, and environmental preservation. Nonetheless, technical challenges on MVPE device reliability, scalable and efficient converter topologies, control stability, large-scale modeling and simulation, to name a few, need to be addressed and advanced to the next level. In conclusion, this Special Section on Advanced MV Power Electronics for Grid Interactive Applications in IEEE Transactions on Power Electronics (TPEL) provides an insight on some of the recent advances in MVPE and emerging challenges and potential solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Helium recovery system at IB3a

The increasing need for optimal and sustainable use of cryogenic resources to support Fermilab’s scientific mission has highlighted the necessity of improving the Laboratory’s helium management practices. An assessment of cryogenic test facilities identified the Technical Division’s Industrial Building 3a (IB3A) as a key site requiring upgrades to integrate a helium recovery system. The IB3A facility is essential for characterizing and testing superconductors, cables, and coils for various R&D projects, including the US High-Luminosity LHC Accelerator Upgrade Project (AUP), Mu2e, and other external collaborations. Currently, the facility relies on 500 L helium Dewars and vents the vaporized helium directly into the atmosphere, leading to significant helium loss. Given the non-renewable nature of helium, recovering and reusing this resource is critical for the sustainability of Fermilab’s operations. To address this challenge, a project has been initiated to connect IB3A to an existing helium purification station and refrigeration system located in another building via a dedicated pipeline pass over the roof of several buildings. This solution will enable the efficient capture of vented helium, its transfer to the purification station, and subsequent liquefaction for reuse in future operations. The project includes a detailed design phase, specifying the pipeline route, flow control mechanisms, and integration with the existing cryogenic infrastructure, followed by phased implementation and commissioning. By implementing this pipeline connection and upgrading IB3A, Fermilab aims to significantly reduce helium waste, lower operational costs, and align with its commitment to sustainability. This initiative provides a model for resource-efficient cryogenic operations and reinforces the Laboratory’s capacity to support its science mission for the long term.

Porwisiak, D. [Fermilab]↗

DOE OSTI2024

Development of High Temperature (>700°C) Molten Salt Pump Technology for Generation 3 Solar Power Tower Systems

Bearings are required for long-shafted pumps historically used in concentrating solar thermal power applications. For molten chloride salts, bearings for such service conditions are not commercially available, nor has a design been demonstrated to work. Therefore, a project was sponsored by the Department of Energy’s Solar Energy Technologies Office for the development and demonstration of a submerged bearing for use in chloride salt pumps. This project’s tasks covered the tribological testing of candidate materials and the design, fabrication, testing, and post-test analysis of full-scale salt-compatible bearings. This work expands upon previous work. The effects of potential particulate in the salt were investigated through tribological bench testing. Through 11 tests, the MgO particulate size and concentration in a molten chloride salt were varied, and the effects on friction, wear rate, and wear characteristics were recorded. Novel journal bearings for chloride salt service were designed and fabricated based on these results. The bearings were of a relevant scale (i.e., for a 1.5 in. pump shaft) to demonstrate the technology with respect to further scale-up. The bearings were made of Haynes 244 and Yttria Partially Stabilized Zirconia. A custom bearing test rig, salt tanks, and associated infrastructure (e.g., heaters, tanks, transfer lines, gas flow control) were designed, procured, and installed. A few issues were encountered in the system fabrication process, resulting in delay of the project schedule. The system was successfully fabricated and assembled. Heating, cover gas, and pump motor systems were integrated into the control logic. This progress of the bearing test system represents a significant step forward towards demonstrating this promising technology. Nevertheless, the project ended before testing of the full-scale bearings could be performed.

14 SOLAR ENERGY↗

DOE OSTI2025

Exploring anomalous electron decay in nanosecond repetitively pulsed discharges

Nanosecond pulsed discharges (typical pulse duration of about 10 nanoseconds) have attracted widespread attention due to their wide range of applications in plasma-assisted combustion and aerodynamic flow control, biomedicine, nanotechnology, and materials processing. This project investigated the plasma dynamics of nanosecond discharges in a pin-to-pin configuration using a combined experimental and theoretical modeling approach, leveraging the expertise and resources of Purdue University and the Princeton Collaborative Research Facility (PCRF).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Mechanical Solutions Scan Report

Power lines, poles, and towers are the backbone of the United States (U.S.) electric-power grid. These transmission and distribution networks route electricity from generator to loads. The characteristics of these routes are rapidly changing -- trending towards decentralized renewable generation, electric heating, vehicle charging, and large data-center loads. Coupled with aging infrastructure and the increased frequency of extreme weather events, there is concern about the future reliability and transmission capacity of conductors and adjacent components. This scan report seeks to provide an overview of mechanical solutions to challenges caused by extreme weather events associated with components of transmission and distribution infrastructure, including conductor heat sag, ice accumulation, wind, and wildfire. Many options could increase transmission capacity or reliability, and these are at various stages of technological readiness. Some have only been lab tested, while some have been widely deployed in the U.S. or overseas for decades. The solution categories and providers featured in this report are intended to be comprehensive at the time of publication and to serve as a reference for decision-makers concerned about transmission and distribution reliability. There are two other categories of large, complex solutions, which are not covered in this report: replacing existing conductors with advanced conductors and implementing digital grid enhancing technologies. A separate scan report titled “Advanced Conductor Scan Report,” which discusses advanced carbon-core conductors, was published by the Idaho National Laboratory (INL) in 2023. Information on digital technologies, such as dynamic line ratings, power-flow controllers, and other power electronics and communications-based devices, can be found on the Grid- Enhancing Technologies landing page. Mechanical grid-enhancing technologies, or solutions covered in this report, often do not require full equipment replacement and do not rely on digital components. Mechanical technologies are overlooked because they may be older, simpler, or seemingly “more obvious” than digital or carbon-core technologies. However, it is wise to consider mechanical solutions in a thorough evaluation of grid enhancing technology solutions.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Development and Full Load Demonstration of a 900°C Solid Particle Receiver for Concentrating Solar Power Applications - noLimits

Sandia National Laboratories (SNL) and the German Aerospace Centre (DLR) are world leaders in the joint and separate development of very high temperature next generation solar concentrator systems using solid particles. This project “noLimits” is meant to provide the critical performance information needed to commercialize DLR’s CentRec® solar receiver and ancillary particle systems (conveying systems, storage vessels, flow control equipment etc.) developed at Sandia National Laboratories (SNL). Performance information (at power levels closer to a small scale Concentrating Solar Power (CSP) plant) will be obtained at full load conditions (2.5 MWt ) and at 900 °C-1000 °C particle outlet temperatures at the National Solar Thermal Test Facility (NSTTF) located at SNL. Heliogen was proposed to be joining the project as a commercial partner to provide the commercialization route for this receiver design, if successful, as Heliogen acquired the intellectual property (IP) from DLR.

14 SOLAR ENERGY↗

DOE OSTI2026

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗