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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 433 records · Page 24

What Lies Beneath Can Be Imaged

The Hanford Site was quickly established to help end World War II, making history for producing the plutonium used in the world’s first nuclear weapons. Throughout the Cold War years, Hanford employees produced plutonium for most of the more than 60,000 weapons in the U.S. nuclear arsenal stockpile. Today, the once highly active nuclear reactors are shut down. And the mission at Hanford turned full-circle as scientists, engineers and specialists work to clean up our nation’s most contaminated nuclear site. PNNL Computational Geophysicist Tim Johnson is helping decision-makers understand the complexity and breadth of the contamination in soils at Hanford. Tim and others are applying remote, high-resolution geophysical imaging to determine the extent of contamination in the soil below the surface and understand the processes controlling its movement. They also provide real-time imaging of remediation processes that are working to limit the movement of contaminants below the surface and toward water resources. Geophysical imaging simply means that PNNL scientists are combining the techniques of geology, physics, mathematics and chemistry with supercomputer modeling to create three-dimensional images of the waste and its movement. These real-time, remote images are essential in reducing the uncertainty associated with cleanup costs and remediation technologies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Train, Inform, Borrow, or Combine? Approaches to Process–Guided Deep Learning for Groundwater–Influenced Stream Temperature Prediction

Although groundwater discharge is a critical stream temperature control process, it is not explicitly represented in many stream temperature models, an omission that may reduce predictive accuracy, hinder management of aquatic habitat, and decrease user confidence. We assessed the performance of a previously-described process-guided deep learning model of stream temperature in the Delaware River Basin (USA). We found lower accuracy (root mean square error [RMSE] of 1.71 versus 1.35°C) and stronger seasonal bias (absolute mean monthly bias of 1.06 vs. 0.68°C) for reaches primarily influenced by deep groundwater as compared to atmospheric conditions. We then tested four approaches for improving groundwater process representation: (a) a custom loss function leveraging the unique patterns of air and water temperature coupling characteristic of different temperature drivers, (b) inclusion of additional groundwater-relevant catchment attributes, (c) incorporation of additional process model outputs, and (d) a composite model. The custom loss function and the additional attributes significantly improved the predictive accuracy in groundwater-dominated reaches (RMSE of 1.37 and 1.26°C) and reduced the seasonal bias (absolute mean monthly bias of 0.44 and 0.48°C), but neither approach could identify holdout groundwater reaches. Variable importance analysis indicates the custom loss function nudges the model to use the existing inputs more efficiently, whereas with the added features the model relies on a broader suite of inputs. This analysis is a substantial step toward more accurately representing groundwater discharge processes in stream temperature models and will improve predictive accuracy and inform habitat management.

54 ENVIRONMENTAL SCIENCES↗

Manganese uptake by red maples in response to mineral dissolution rates in soil

Manganese (Mn) is an essential plant micronutrient that influences photosynthesis, ecosystem productivity, and soil carbon storage. Our objective was to quantify how Mn uptake by forest vegetation relates to Mn release into soil solution through mineral dissolution. In this work, a greenhouse pot experiment was conducted to quantify Mn uptake by red maple saplings as a function of mineral solubility to test whether Mn uptake was limited by the supply of Mn to soil solution. Differences in soil microbial community composition between treatments, particularly amongst Mn cycling bacteria and fungi, were also evaluated to assess potential microbial impacts on observed Mn fluxes. Plant Mn uptake was highest in systems supplied with dissolved Mn(II) because it was not kinetically limited by mineral weathering. Mn uptake was also higher in systems supplied with a fast-weathering substrate (shale containing Mn(II)-bearing pyrite) than a slow-weathering substrate (Mn(IV)-oxide). However, vegetation accumulated a decreasing proportion of available Mn with increasing solubility, indicating that uptake was tempered relative to solubility. The presence of bacterial phyla containing known Mn-oxidizing bacteria indicates the potential for Mn-oxidizing bacteria to influence Mn solubility within Mn-oxide and dissolved Mn treatments. A relatively low abundance of these bacteria points to their limited capacity to oxidize and retain Mn in the shale treatments, consistent with substantial Mn leaching. We conclude that Mn uptake was primarily controlled by dissolution rates of Mn-bearing minerals but modified by biological processes. The quantitative framework presented here can guide understanding of how biogeochemical processes control element cycling between plants and soils.

59 BASIC BIOLOGICAL SCIENCES↗

On optimal control of hybrid dynamical systems using complementarity constraints

Optimal control for switch-based dynamical systems is a challenging problem in the process control literature. In this study, we model these systems as hybrid dynamical systems with finite number of unknown switching points and reformulate them using non-smooth and non-convex complementarity constraints as a mathematical program with complementarity constraints (MPCC). We utilize a moving finite element based strategy to discretize the differential equation system to accurately locate the unknown switching points at the finite element boundary and achieve high-order accuracy at intermediate non-collocation points. We propose a globalization approach to solve the discretized MPCC problem using a mixed NLP/MILP-based strategy to converge to a non-spurious first-order optimal solution. The method is tested on three dynamic optimization examples, including a gas–liquid tank model and an optimal control problem with a sliding mode solution.

97 MATHEMATICS AND COMPUTING↗

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗

A numerical study comparing the combustion and emission characteristics of biodiesel with petrodiesel.

Combustion and emission characteristics of compression ignition engines strongly depend upon inner-nozzle flow and spray behavior. These processes control the fuel-air mixing, which in turn is critical for the combustion process. Previous studies by us highlighted the differences in the physical and chemical properties of petrodiesel and biodiesel, which significantly altered the inner-nozzle flow and spray structure. The current study is another step in this direction to gain a fundamental understanding on the influence of fuel properties on the combustion and emission characteristics of the compression ignition engine. n-Heptane and methyl butanoate were selected as surrogates for diesel and biodiesel fuels, respectively, because the chemical kinetic pathways were well-understood. Liquid length and flame lift-off length for diesel and biodiesel fuels were validated against data available in the literature. Liquid lengths were always higher for biodiesel because of its higher heat of vaporization, which resulted in increased interplay between spray and combustion processes under all conditions investigated. Ambient air entrainment was also lower for biodiesel mainly because of slower atomization and breakup. The mechanism for flame stabilization is further analyzed by estimating the turbulent burning velocity for both of the fuels. This analysis revealed that neither flame propagation nor isolated ignition kernels upstream and detached from high-temperature regions can be the mechanism for flame stabilization. Flame propagation speeds were observed to be similar for both fuels. Biodiesel predicted lower soot concentrations, which were also reflected in reduced C{sub 2}H{sub 2} mole fractions. Although prompt NO{sub x} was higher for biodiesel, total NO{sub x} was lower because of reduced thermal NO{sub x}. The ignition delay and NO{sub x} emissions predicted by these simulations do not agree with trends reported in the literature; hence, this study highlights the need for better fuel surrogates for diesel and biodiesel fuels.

33 ADVANCED PROPULSION SYSTEMS↗

Rapid control of mold temperature during injection molding process

The control of mold surface temperature is an important factor that determines surface morphology and its dimension in thickness direction. It can also affect the frozen molecular orientation and the mold surface replicability in injection molded products. In this work, thin thermally active films were used to quickly control the mold surface temperature. In particular, an active high electrical conductivity carbon black loaded polyimide composites sandwiched between two insulating thin polymeric layers was used to condition the mold surface. By controlling the heating time, it was possible to control precisely the temporal variation of the mold temperature surface during the entire cycle. The surface heating rate was about 40°C/s and upon contact with the polymer the surface temperature decreased back to 40°C within about 5 s; the overall cycle time increased only slightly. The effect on cross section sample morphology of samples of iPP were analyzed and discussed on the basis of the recorded temperature evolution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Updated Conceptual Model for the 300 Area Uranium Groundwater Plume

The 300 Area uranium groundwater plume in the 300-FF-5 Operable Unit is residual from past discharge of nuclear fuel fabrication wastes to a number of liquid (and solid) disposal sites. The source zones in the disposal sites were remediated by excavation and backfilled to grade, but sorbed uranium remains in deeper, unexcavated vadose zone sediments. In spite of source term removal, the groundwater plume has shown remarkable persistence, with concentrations exceeding the drinking water standard over an area of approximately 1 km2. The plume resides within a coupled vadose zone, groundwater, river zone system of immense complexity and scale. Interactions between geologic structure, the hydrologic system driven by the Columbia River, groundwater-river exchange points, and the geochemistry of uranium contribute to persistence of the plume. The U.S. Department of Energy (DOE) recently completed a Remedial Investigation/Feasibility Study (RI/FS) to document characterization of the 300 Area uranium plume and plan for beginning to implement proposed remedial actions. As part of the RI/FS document, a conceptual model was developed that integrates knowledge of the hydrogeologic and geochemical properties of the 300 Area and controlling processes to yield an understanding of how the system behaves and the variables that control it. Recent results from the Hanford Integrated Field Research Challenge site and the Subsurface Biogeochemistry Scientific Focus Area Project funded by the DOE Office of Science were used to update the conceptual model and provide an assessment of key factors controlling plume persistence.

300 Area↗

Fermilab’s horizontal test stand upgrade overview and commissioning

Cryo-assemblies with the low-beta Nb3Sn quadrupoles for the High Luminosity LHC (HL-LHC) upgrade will be tested at Fermilab’s magnet test facility. Total of 10 cryo-assemblies will be delivered to CERN within the US HL-LHC Accelerator Upgrade Project (AUP). The horizontal test stand at Fermilab already has been used for testing the existing LHC inner-triplet quadrupoles, but the stand and corresponding electrical and cryogenic sub-systems were not operational more than a decade. In order to restore the test stand functions and meet the design and test requirements for the high luminosity LHC magnets, the existing horizontal test facility at Fermilab underwent a significant refurbishment of the cryogenic and mechanical components. Most of the upgrades were completed and verified during so called zero-magnet test by late 2020, and then final commissioning of the upgraded test stand was completed during the first cryo-assembly test in 2023. These tests verified all the cryo-mechanical installations, as well as the test stand operations, including controlled cooldown and operation at 1.9 K, the helium recovery capabilities, magnet protection and process controls.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dynamic frequency control in power networks

Node controllers in power distribution networks in accordance with embodiments of the invention enable dynamic frequency control. One embodiment includes a node controller comprising a network interface a processor; and a memory containing a frequency control application; and a plurality of node operating parameters describing the operating parameters of a node, where the node is selected from a group consisting of at least one generator node in a power distribution network wherein the processor is configured by the frequency control application to calculate a plurality of updated node operating parameters using a distributed process to determine the updated node operating parameter using the node operating parameters, where the distributed process controls network frequency in the power distribution network; and adjust the node operating parameters.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Monitoring and Control of Chemical Composition of InGaN Layers During MOCVD

This Department of Energy SBIR Phase II grant targets the inefficiency of the epitaxial processes used to deposit wide band-gap semiconductor thin films that are an essential part of the next generation high-brightness LEDs for solid state lighting. Non-uniformity of the layers over a single wafer and non-repeatability over the wafers in a single batch, separate batches and separate reactors are some of the primary source of reduced manufacturing yield. The team performed extensive research, development and validation of an in-situ spectroscopic optical monitoring and epitaxial process control system. The system monitors the LED thin films as they grow on the individual wafers inside the epitaxial reactor, records the signal in a broad spectral range and processes the information to retrieve essential film quality parameters and their variation over a single wafer, all the wafers in a batch and multiple batches. A novel software algorithm is implemented, which performs real-time spectral pattern recognition and displays any abnormalities or differences in the deposition, which is used by the engineer to optimize the epitaxial process. The project resulted in the optimization of the LED film growth and improvement of its uniformity and repeatability, reducing the cost of the final LED devices.

36 MATERIALS SCIENCE↗

Monitoring, Controlling and Safeguarding Radiochemical Streams at Spent Fuel Reprocessing Facilities, Part 1: Optical Spectroscopic Methods

Abstract: The International Atomic Energy Agency (IAEA) has established international safeguards standards for fissionable material at spent fuel reprocessing plants to ensure that significant quantities of weapons-useable nuclear material are not diverted from these facilities. For large throughput nuclear facilities, it is difficult to satisfy the IAEA safeguards accountancy goal for detection of abrupt diversion. Currently, methods to verify material control and accountancy (MC&A) at these facilities require time-consuming and resource-intensive destructive assay (DA). Leveraging new on-line non-destructive assay (NDA) process monitoring techniques in conjunction with the traditional and highly precise DA methods may provide an additional measure to nuclear material accountancy which would potentially result in a more timely, cost-effective and resource efficient means for safeguards verification at such facilities. By monitoring process control measurements (e.g. flowrates, temperatures, or concentrations of reagents, products or wastes), abnormal plant operations can be detected. Pacific Northwest National Laboratory (PNNL) is developing on-line NDA process monitoring technologies based upon gamma-ray and optical spectroscopic measurements to potentially reduce the time and resource burden associated with current techniques. The Multi-Isotope Process (MIP) Monitor uses gamma spectroscopy and multivariate analysis to identify off-normal conditions in process streams. The spectroscopic monitor continuously measures chemical compositions of the process streams including actinide metal ions (U, Pu, Np), selected fission products, and major stable flowsheet reagents using UV-Vis, Near IR and Raman spectroscopy. Multi-variate analysis is also applied to the optical measurements in order to quantify concentrations of analytes of interest within a complex array of radiochemical streams. This paper will provide an overview of these methods and reports on-going efforts to develop and demonstrate the technologies. This paper is Part 1 of a two part series, and focuses on the optical spectroscopy based process monitoring methods.

material control and accountancy, process monitor,↗

Correlations between thermal history and keyhole porosity in laser powder bed fusion

Additive manufacturing has the potential to revolutionize the production of metallic components as it yields near net shape parts with complex geometries and minimizes waste. At the present day, additively manufactured components face qualification and certification challenges due to the difficulty in controlling defects. This has driven a significant research effort aimed at better understanding and improving processing controls – yielding a plethora of in-situ measurements aimed at correlating defects with material quality metrics of interest. In this work, we develop machine-learning methods to learn correlations between thermal history and subsurface porosity for a variety of print conditions in laser powder bed fusion. Un-normalized surface temperatures (in the form of black-body radiances) are obtained using high-speed infrared imaging and porosity formation is observed in the sample cross-section through synchrotron x-ray imaging. To demonstrate the predictive power of these features, we present four statistical machine-learning models that correlate temperature histories to subsurface porosity formation in laser fused Ti-6Al4V powder.

36 MATERIALS SCIENCE↗

Enhancing microsegregation during rapid directional solidification through ternary microalloying

The nano-cellular dendritic microstructure formed during rapid directional solidification in powder bed fusion additive manufacturing creates unique properties such as simultaneous improvement in strength and ductility. However, process control of microsegregation features remains challenging due to low sensitivity of critical solidification mechanisms to process parameters. This study leverages microalloying to achieve large changes in dendrite composition, microstructure, and interdendritic zone width during laser powder bed fusion without modifying process parameters. CALPHAD simulations predict that the addition of Zr significantly steepens the solidus line of the dilute Cu-Cr alloy system, leading to enhanced Cr rejection into the melt and greater than 95% reduction in solubility of Cr in the solidified Cu matrix. Experimental validation using time-of-flight secondary ion mass spectrometry and Kelvin probe force microscopy reveals that the ternary alloy containing 0.01 wt% Zr exhibited wider interdendritic regions compared to the binary, a significantly higher number of Cr-rich particles within interdendritic regions, near-complete ejection of oxygen impurities from the matrix, and greater nanoscale work function contrast. These features indicate more aggressive Cr segregation in the presence of Zr and a purer Cu matrix and provide a potentially robust method for engineering the nano-cellular dendritic solidification microstructure.

CALPHAD↗

Bridging the Gap Between Modern UX Design and Particle Accelerator Control Room Interfaces

Accelerator control systems often represent relatively complex and safety-sensitive human-machine interfaces within process control industries. These systems are technically robust and reflect the cumulative integration of solutions built and adapted across decades. One of the regular, unfortunate casualties of provisional accelerator control system updates is their human-system interfaces (HSIs) which often lag behind modern usability and design standards. An additional challenge is that although there is a multitude of established human factors (HF), and user experience (UX) principles for everyday digital applications, there are very few (if any) established principles for complex and safety-critical applications for an accelerator. This paper argues for the importance of established HF and UX principles (herein referred to as human-centered design principles) into the development of accelerator HSIs, emphasizing the need for clarity, consistency, responsiveness, and cognitive accessibility. Drawing from HF/UX best practices and human-centered design, this paper discusses how these approaches can enhance operator performance, reduce human error, and improve accelerator personnel collaboration. Case studies from Accelerator Control Operations Research Network (ACORN) at Fermilab are explored to demonstrate how interfaces built with human-centered design principles can scale with system complexity while remaining intuitive and efficient for diverse user roles including operators, machine experts, and engineers. By bridging the gap between traditional control system design and modern human-centered design methods, this paper provides a roadmap for evolving accelerator HSIs into more usable, maintainable, and effective tools.

Hill, Rachael [Idaho Natl. Lab.]↗

Mitochondrial quality control pathways: PINK1 acts as a gatekeeper

Highlights: • A well-defined network of mitochondria quality control processes are required to maintain a functional and healthy pool of mitochondria within the cells. • Activation of proteins involved in mitochondrial quality control pathways, such as Parkin, Mfn2, DRP1 and Miro; is regulated by the mitochondrial kinase PINK1. • It is proposed that PINK1 acts as a gatekeeper of mitochondrial quality control mechanisms. Mitochondria have a pivotal role in the maintenance of cell homeostasis and survival. Mitochondria are involved in processes such as ATP production, reactive oxygen species production, apoptosis induction, calcium homeostasis and protein degradation. Thus, mechanisms that regulate the intrinsic quality of mitochondria have a crucial role in dictating overall cell fate. The importance of these well-regulated mechanisms is highlighted in disease scenarios such as neurodegeneration, cancer and neuromuscular atrophy. How mitochondria senses and regulates their intrinsic quality control, and consequently cell survival, is still not fully understood. In this review, we discuss the pathways that are at present considered as state-of-the-art for mitochondria quality control regulation, and highlight a mitochondrial protein–PINK1–that has revealed to act as a mitochondrial gatekeeper able to sense the presence of healthy or damaged mitochondria.

60 APPLIED LIFE SCIENCES↗

Optimisation of the Kaplan hydropower system via PID 2 and digital twin

Here, this paper proposes a proportional–integral-double–derivative (PID 2 ) optimisation method for the Kaplan hydropower system by building a digital twin. The study first uses one multilayer perceptron (MLP) to model the hydroturbine dynamic and then adopts three connected MLPs to model the generator dynamic, both in an open-loop fashion. Inspired by stochastic distribution control (SDC) theory, we regard the training of the turbine's neural network model as a process control problem, and we propose minimising entropy loss to update the network parameters. The next step is to build the digital twin by connecting the neural network models with a PID 2 controller and a lead-lag exciter and run the whole model in a closed-loop fashion. After that, a binary search approach is applied to optimise the PID 2 parameters based on the obtained digital twin model. The simulation results show that the proposed method can reduce the mean square tracking error by more than 90%. Furthermore, the method is extended to jointly optimise the PID 2 controller and excitation system gains through multiobjective optimisation, leveraging Pareto frontier analysis to balance active power and voltage tracking performance. Simulation results confirm the effectiveness of the proposed method, achieving a 83.46% reduction in relative mean square error of active power, a 47.13% reduction in terminal voltage tracking error, and an 82.78% improvement in the overall scalarized objective.

Hydropower system↗