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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13

Predicting future well performance for environmental remediation design using deep learning

Here in this study, we developed a deep learning (DL) framework with a multi-channel three-dimensional convolutional neural network (MC3D-CNN) to predict well performance and thereby assist future environmental remediation design. Such prediction of extraction well performance at designated locations is critical for configuring pump-and-treat (P&T) well network design and operation, setting reasonable target closure dates for overall remedying, and estimating remedy costs. The framework is developed with operational and monitoring data routinely collected during P&T remedy operations, including well extraction and injection rates as well as in situ contaminant concentrations. Traditionally, the collected data were rarely used for purposes other than assessing past well performance and the accuracy of the conceptual site model. However, recent advances in data-driven computational approaches enable better use of the large datasets to inform future well performance, enhance site characterization, and improve remediation planning. In this study, we established a DL framework to integrate transient three-dimensional contaminant plumes and multiple aquifer properties (e.g., hydraulic conductivity and hydrostratigraphic maps) to identify characteristic patterns controlling and representing extraction well mass recovery, aiming at providing future mass recovery estimates for existing wells and candidate wells at any proposed locations. We evaluated our framework by using a realistic synthetic dataset generated from a well-calibrated flow and transport model used in the 200 West Area of the U.S. Department of Energy’s Hanford Site in southeastern Washington state. The multi-channel feature in our framework allows integration of various types and temporal densities of training datasets for DL model development. Overall, we found that the trained DL model achieved an accuracy of over 90% in ranking extraction well performance in validation datasets, and over 80% in predicting high-performance-ranking well locations. This data-informed approach provides a flexible tool to support adaptive site management, streamline decision-making, and potentially reduce remediation time and costs. Our DL framework can be used as a filtering tool to improve the current P&T network optimization design by reducing the number of candidate well locations.

54 ENVIRONMENTAL SCIENCES↗

The physical meaning of the magnetic scalar potential and its use in the design of hermetic electromagnetic coils

The magnetic scalar potential U(r⃗) has an intuitive physical interpretation, representing the electric current I = ΔU, which must be directed between any pair of isocontours along the boundary of a region, differing in potential by ΔU, in order to generate the corresponding magnetic intensity H⃗=−∇⃗U inside the region with no tangential component outside the boundary. This physical significance is exploited to invert the design process of hermetic (fringeless) electromagnetic coils from standard iterative techniques (calculating the magnetic field of refined current distributions) to a procedure for calculating the exact surface currents required to generate a given field configuration. A practical construction algorithm is given to produce the prescribed field in a “Target” region (constrained only by Maxwell’s equations) while confining the fringe field to a specified hermetic “Return” region. Example coils are analyzed along with a discussion of the limits of precision of the constructed field.

Crawford, C. B. (ORCID:0000000219324334)↗

Design and performance of AI agents interfacing with an atomic layer deposition tool

In this work, we introduce the design of an atomic layer deposition (ALD) reactor augmented with an AI interface for autonomous materials synthesis. Our modular design encapsulates the particularities of the hardware behind a Python interface that communicates with the ALD control software via transmission control protocol. This interface is compatible with model context protocol interfaces used in agentic frameworks. We have integrated our tool with a simple AI agent that leverages a large language model to transform user-supplied queries into ALD processes that are then run in our reactor. Our approach uses a JavaScript object notation schema to encode ALD processes. Our experimental results show that the AI interface does not impose a significant overhead to our control software, at least within our fastest 10 ms scale. We also carried out a detailed evaluation of the agent performance using leading models in two classes of tasks: basic instruction and process discovery tasks, where the agent is presented with a target material and needs to identify the correct ALD process compatible with the reactor configuration. Despite the simplicity of our agent design, we observed that most of the advanced models excelled at the instruction tasks. However, only recent models, such as o1, o3, GPT-5, and Claude Opus 4, performed well in process discovery tasks. We also observed significant variability in the response for the hardest challenges. While the results obtained are promising, we identify areas where AI research could improve the performance of agents for ALD.

47 OTHER INSTRUMENTATION↗

Comparison of detachment in Ohmic plasmas with positive and negative triangularity

Abstract In recent years, negative triangularity (NT) has emerged as a potential high-confinement L-mode reactor solution. In this work, detachment is investigated using core density ramps in lower single null Ohmic L-mode plasmas across a wide range of upper, lower, and average triangularity (the mean of upper and lower triangularity: δ ) in the TCV tokamak. It is universally found that detachment is more difficult to access for NT shaping. The outer divertor leg of discharges with δ ≈ − 0.3 could not be cooled to below 5 eV through core density ramps alone. The behavior of the upstream plasma and geometrical divertor effects (e.g. a reduced connection length with negative lower triangularity) do not fully explain the challenges in detaching NT plasmas. Langmuir probe measurements of the target heat flux widths ( λ q ) were constant to within 30% across an upper triangularity scan, while the spreading factor S was lower by up to 50% for NT, indicating a generally lower integral scrape-off layer width, λ int . The line-averaged core density was typically higher for NT discharges for a given fuelling rate, possibly linked to higher particle confinement in NT. Conversely, the divertor neutral pressure and integrated particle fluxes to the targets were typically lower for the same line-averaged density, indicating that NT configurations may be closer to the sheath-limited regime than their PT counterparts, which may explain why NT is more challenging to detach.

Physics↗

Microfluidic platform for multiplexed detection in single cells and methods thereof

The present invention relates to a microfluidic device and platform configured to conduct multiplexed analysis within the device. In particular, the device allows multiple targets to be detected on a single-cell level. Also provided are methods of performing multiplexed analyses to detect one or more target nucleic acids, proteins, and post-translational modifications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Distributed multi-input multi-output control theoretic method to manage heterogeneous systems

A processing unit includes a plurality of subsystem control modules. Each subsystem control module includes a set of one or more inputs that receives a set of one or more external signals and a set of one or more monitored outputs from a hardware subsystem corresponding to the subsystem control module, and a set of configuration outputs for controlling one or more configuration settings of the hardware subsystem. The subsystem control module determines the one or more configuration settings based on the set of monitored outputs and on one or more targets derived from the set of external signals.

Pothukuchi, Raghavendra Pradyumna↗

Constraining the Beam Neutrino MC Flux Using the MINOS ND Data

This document describes a method to handle correlated systematic uncertainties from hadron production on the beam spectrum by using the neutrino ·data from the MINOS detector. We have developed a tuning function which can be applied after the fact to the Monte Carlo to force agreement with the CC neutrino energy spectra observed in the near detector and the beam MC. The method relies on the flexible NuMI beam, which can be configured so as to selectively sample pions. of different momenta and angles off the target. There is sufficient information in the neutrino data in a detector like MINOS to deduce the portion of the underlying spectrum of hadrons off the NuMI target which contribute to the NuMI flux.

Kopp, Sacha [U. Texas, Austin (main)]↗

Dual-Image Color Normalization to Enable High-Performance Concentrating Solar Optical Metrology

Concentrating Solar Power (CSP) requires precision mirrors, and these in turn require metrology systems to measure their optical slope. In this project we studied a color-based approach to the correspondence problem, which is the association of points on an optical target with their corresponding points seen in a reflection. This is a core problem in deflectometry-based metrology, and a color solution would enable important new capabilities. We modeled color as a vector in the [R,G,B] space measured by a digital camera, and explored a dual-image approach to compensate for inevitable changes in illumination color. Through a series of experiments including color target design and dual-image setups both indoors and outdoors, we collected reference/measurement image pairs for a variety of configurations and light conditions. We then analyzed the resulting image pairs by selecting example [R,G,B] pixels in the reference image, and seeking matching [R,G,B] pixels in the measurement image. Modulating a tolerance threshold enabled us to assess both match reliability and match ambiguity, and for some configurations, orthorectification enabled us to assess match accuracy. Using direct-direct imaging, we demonstrated color correspondence achieving average match accuracy values of 0.004 h, where h is the height of the color pattern. We found that wide-area two-dimensional and linear one-dimensional color targets outperformed hybrid linear/lateral gradient targets in the cases studied. Introducing a mirror degraded performance under our current techniques, and we did not have time to evaluate whether matches could be reliably achieved despite varying light conditions. Nonetheless, our results thus far are promising.

14 SOLAR ENERGY↗

Effects of divertor electrical drifts on particle distribution and detachment near the divertor target plate in DIII-D

Strong impacts of drifts on the divertor plasma in–out asymmetry and detachment are demonstrated in DIII-D with an open divertor configuration. For forward toroidal field, B T , i.e., with the ion B × ∇B drift toward the divertor, the particle flux to the inner divertor, as represented by the Langmuir probe measured ion saturation current (J sat ), exhibits a double peak structure, with electron temperature, lower at the inner target. Reversing the B T direction reverses both the radial and poloidal E × B flows, leading to a broad particle flux profile in the outboard scrape-off layer (SOL) with a similar double-peak structure to that observed at the inner target with forward B T . The correlation of a double peak structure with divertor temperature profiles confirms physical coupling between the drift flow and sheath boundary condition and their strong impact on divertor profiles. In addition, under reversed B T conditions, increasing the density flattens the target temperature profile. However, J sat remains high away from the strike point, rendering it difficult to achieve an “effective” detached plasma, i.e., with effective reduction in both peak heat flux and peak temperature (in the far SOL). In contrast, divertor detachment with a cold and flat temperature profile can be achieved at both target plates with the forward B T .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A method for examining ensemble averaging forms during the transition to turbulence in HED systems for application to RANS models

This paper discusses a strategy to initialize a two-dimensional (2D) Reynolds-averaged Navier–Stokes model [LANL's Besnard–Harlow–Rauenzahn (BHR) model] in order to describe an unsteady transitional Richtmyer–Meshkov (RM)-induced flow observed in on-going high-energy-density ensemble experiments performed on the OMEGA-EP facility. The experiments consist of a nominal single-mode perturbation (initial amplitude a 0 ≈ 10 and wavelength $λ$ = 100μm) with target-to-target variations in the surface roughness subjected to the RM instability with delayed Rayleigh–Taylor in a heavy-to-light configuration. Our strategy leverages high-resolution three-dimensional (3D) implicit large eddy simulations (ILES) simulations to initialize BHR-relevant parameters and subsequently validate the 2D BHR results against the 3D ILES simulations. A suite of five 3D ILES simulations corresponding to five experimental target profiles is undertaken to generate an ensemble dataset. Using ensemble averages from the 3D simulations to initialize the turbulent kinetic energy in the BHR model ( K 0 ) demonstrates the ability of the model to predict the time evolution of the interface as well as the density-specific-volume covariance, b . To quantify the sensitivity of the BHR results to the choice of K 0 and the initial turbulent length scale, S 0 , we execute a parameter sweep spanning four orders of magnitude for both S 0 and K 0 , generating a parameter space consisting of 26 simulations. The Pearson's correlation coefficient is used as a measure of discrepancy between the 2D BHR and 3D ILES simulations and reveals that the ranges 8≲S 0 ≲20 μm and 10 9 ≲K 0 ≲10 10 cm 2 /s 2 produce predictions that agree best with the 3D ILES results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

SYS-5620-Project - Achieving Robust Laser Performance utilizing Historical Shot Experiments - A Systems Engineering Proposal

The National Ignition Facility (NIF) at Lawrence Livermore National Laboratory precisely guides, amplifies, reflects, and focuses 192 powerful laser beams into a target about the size of a pencil eraser in a few billionths of a second, delivering more than 2 million joules of ultraviolet energy and 500 trillion watts of peak power. A crucial goal of the system is to trigger precise implosions of fuel capsules. This is achieved by delivering all 192 beams at user-specified times and locations on the target, minimizing any deviation from the requested performance. Power requirements can vary substantially on each experiment and the facility supports numerous amplifier pumping configurations and their attendant nonlinear effects. To achieve the tight performance required across such a broad array of configurations, constant comparison of measured and requested power delivery are tracked and long-term trends analyzed as a guide to understanding future performance. A very common question asked is given the current state of the laser today – how well would a similar experiment from the past perform today? Additionally, if one were to specify an alternate amplifier configuration using today’s model would and damage limits be exceeded and would there be an increase in performance. The physics model used to make these predictions and equipment protection checks is called the Virtual Beamline (VBL). VBL is used with an incoming desired pulse shape and energy to be delivered on target, and then does an iterative solve to predict the needed injected pulse in the front-end of the system to achieve this result. To effectively guide and predict future NIF experiment performance, laser scientists explore current amplifier configurations and compare them with historical data utilizing a tool called the Reverify Toolbox.

42 ENGINEERING↗

Neutron imaging the spatial progression of chemical oxidation of lithium-ion cathode material in a packed bed reactor

Emerging electrochemical systems relevant to energy applications including redox targeted flow batteries rely on chemical redox of solid electroactive materials using dissolved redox couples. One configuration to facilitate contact between the redox shuttles and solid material which is volume efficient is a packed bed reactor. While methods have been reported to assess the overall progression by analysis of the packed bed reactor effluent, herein analysis of the spatial progression of the chemical redox will be reported. Combination of neutron and x-ray tomography enabled assessing the pore and particle structure in the packed bed reactor and the spatial homogeneity of the reaction at different overall extents of conversion of the reactor bed. Finally, these characterization tools provide methods to probe the chemical redox processes occurring within the reactor environment.

25 ENERGY STORAGE↗

Rare‐Earth Reduction in High‐Speed PM‐Assisted Synchronous Reluctance Motors Using Hybrid Magnet Strategies and Design Optimisation for 800 V EVs

The trend towards electrifying transportation systems has stimulated research endeavours aimed at developing electric machines that are not only high speed and efficient but also low‐cost and compact. To support this transition, the US Department of Energy (DOE) has established ambitious targets of $7/kW cost and 12 kW/L power density for the electric drivetrains. This paper attempts to meet these targets by proposing high‐speed permanent magnet assisted synchronous reluctance machine (PMASynRM) topologies enabled by hybrid magnet strategies, combining rare‐earth (RE) magnets with low‐cost, RE‐free alternatives. Modified 2‐layer and 3‐layer U‐shaped rotor configurations, featuring structural reinforcements to withstand high mechanical stress at elevated speeds, are developed. A multi‐objective design optimisation framework is employed to optimise the rotor design, targeting reductions in RE magnet volume, magnet demagnetisation risk and torque ripple while achieving the desired electromagnetic performance. A comprehensive analysis of the optimised rotor designs, compared against a 16,000 rpm, 800 V baseline IPM motor, shows over 70% RE reduction, demagnetisation risk below 3.5% and torque ripple under 10%. Detailed analyses of performance trends across various magnet combinations and rotor configurations highlight the viability of hybrid magnet PMASynRM designs as cost‐effective, robust and energy‐efficient solutions for next‐generation EVs.

33 ADVANCED PROPULSION SYSTEMS↗

Development of prechamber enabled mixing-controlled combustion strategy for ultra-low methane emissions from lean burn natural gas engines

This numerical study explores the optimization of Prechamber Enabled Mixing-Controlled Combustion (PC-MCC) using natural gas in heavy-duty engines, aiming to enhance combustion efficiency to minimize methane slip and NOx emissions. The approach involves a prechamber ignition system, distinct from conventional spark ignition (SI) systems, to initiate combustion of direct injected natural gas. By leveraging the robust ignition characteristics of the prechamber, the PC-MCC method demonstrates significant potential in achieving efficient combustion akin to diesel engines but with lower greenhouse gas emissions. The research evaluates the effects of various geometric and operational parameters on the combustion process and emissions, including prechamber volume, nozzle diameter, direct injector (DI) geometry, and engine operating strategies. Computational Fluid Dynamics (CFD) simulations are utilized, focusing on a heavy-duty, single-cylinder engine modeled after the Caterpillar C9.3B engine. Key findings indicate that a prechamber volume of 3 cc, coupled with a nozzle diameter of 2.75 mm for two prechamber holes, strikes an optimal balance between combustion efficiency and emissions reduction. This configuration ensures robust combustion across a range of operating conditions while maintaining methane slip within targeted limits. Further investigation into DI geometry shows the significance of the injector umbrella angle and nozzle diameter in shaping the fuel-air mixing and combustion dynamics. An umbrella angle of 130° and a nozzle diameter of 300 microns are identified as optimal, promoting rapid and efficient combustion with minimized methane and NOx emissions. The study also investigates the impact of injection timing and pressure, highlighting their roles in controlling combustion timing and influencing emissions levels. Advanced injection timing is found to be crucial in achieving the desired low methane slip, whereas retarded injection timing assists to reduce NOx emissions while having a slight increase in methane emissions. Operating strategies incorporating various levels of Exhaust Gas Recirculation (EGR) are assessed for their effectiveness in further reducing emissions. The research demonstrates that a judicious combination of internal hot EGR and careful calibration of DI pressure and SOI timing can achieve significant reductions in NOx emissions while keeping methane slip under control. Specifically, an internal EGR level of 15%–25%, combined with DI pressures of 200–300 bar and injection timings at or after top dead center, is recommended. These findings contribute valuable insights into the development of advanced combustion techniques for natural gas engines, offering a viable pathway to reduce methane slip without compromising engine efficiency or performance. The PC-MCC system presents a promising solution for the future of heavy-duty natural gas engine technology to reduce methane emissions.

Nsaif, Osama↗

Methodology to Generate the Decay Gamma Source for a Second Target Station Target Wedge

This report details the specifics of applying the Position-Averaged Method methodology for the calculation of the rotating lasagna-style target wedge activation and the resulting decay gamma source terms. The methodology uses MCNP® Code Version 6.2.0 with the RNUCS patch coupled with CINDER2008 from the AARE V1.0 package. The process begins with model preparations that include ensuring impurities are included in the materials in the regions of interest along with segmentation of the geometry in order to capture the decay gamma source gradients. This report also details the physics models and other MCNP®, CINDER2008, and ADVANTG 3.2.0 related options used to calculate the decay gamma source terms. ADVANTG 3.2.0 is used to generate a weight window set to aid in convergence of the neutron fluxes in the initial MCNP® protons-on-target particle transport calculation to calculate the neutron fluxes and spallation products in the regions of interest. The neutron fluxes and spallation products are then used in the CINDER2008 transmutation calculation, and the decay gamma sources are generated by the AARE_GAMMA_SOURCE_SCRIPT as a part of the AARE V1.0 package. These decay gamma sources include the energy distributions as well as the necessary distributions to sample the location of the source using the cell rejection method. The gamma sources that are produced using the methodology may be used for a wide variety of analysis involving the target wedge. This report includes the material specifications, physics options, proton source term description, geometrical configuration, and post-processing details.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sensitivity of ATF Experiments in the Center Flux Trap of the Advanced Test Reactor to Adjacent Experiments

Irradiation experiments conducted in the Idaho National Laboratory’s Advanced Test Reactor are typically assumed to have little effect on one another. This assumption does not hold true for certain experiments in close proximity. To evaluate the impacts on safety and programmatic parameters of experiments in the center flux trap, the contents of the adjacent H and inner-A positions were modeled with a range of possible irradiation targets. First, neutron flux maps with experiments in those positions were compared against a baseline configuration. Next, several safety and programmatic parameters for a generic accident-tolerant fuel test train were calculated. It was shown that these parameters can exhibit considerable sensitivity to the contents of the H and A experiment positions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Prime Time for Model-Predictive Control? Assessing the Technical and Market Readiness of Advanced Controls in Buildings

Despite three decades of extensive research and field testing that have consistently validated the benefits of Model Predictive Control (MPC) in building applications, the technology has seen limited market adoption. This paper evaluates the readiness of MPC for widespread deployment, showcases recent demonstrations and field tests across diverse building types, including residential, small commercial, large commercial, and campus settings. Our results demonstrate that MPC can optimize system operations to achieve load shifting, minimize curtailment of on-site generation, and reduce energy costs by up to 80 %, while maintaining or improving occupant comfort. We also show that MPC can effectively control large assets, such as MW-sized thermal storage systems, and respond to dynamic pricing signals. However, achieving scale remains difficult due to labor-intensive workflows, reliance on a “PhD-in-the-loop” for MPC design and maintenance, susceptibility to fragile data infrastructure, and persistent workforce education and acceptance barriers. To bridge this gap, we outline a transition from bespoke, labor intensive prototypes toward streamlined, segment-targeted deployment strategies that leverage model templates, semantic tools, and generative AI. By automating control configuration and reducing engineering effort, these recommendations provide a pathway for transforming successful research demonstrations into scalable, market ready solutions for MPC-based controls.

Pritoni, Marco↗

High-Order Mesh Morphing for Boundary and Interface Fitting to Implicit Geometries

Here, we propose a method that morphs high-order meshes such that their boundaries and interfaces coincide/align with implicitly defined geometries. Our focus is particularly on the case when the target surface is prescribed as the zero isocontour of a smooth discrete function. Common examples of this scenario include using level set functions to represent material interfaces in multimaterial configurations, and evolving geometries in shape and topology optimization. The proposed method formulates the mesh optimization problem as a variational minimization of the sum of a chosen mesh-quality metric using the Target-Matrix Optimization Paradigm (TMOP) and a penalty term that weakly forces the selected faces of the mesh to align with the target surface. The distinct features of the method are use of a source mesh to represent the level set function with sufficient accuracy, and adaptive strategies for setting the penalization weight and selecting the faces of the mesh to be fit to the target isocontour of the level set field. We demonstrate that the proposed method is robust for generating boundary- and interface-fitted meshes for curvilinear domains using different element types in 2D and 3D.

97 MATHEMATICS AND COMPUTING↗