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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

MULTI-MODAL global surveillance methodology for predictive and on-demand characterization of localized processes using cube satellite platforms and deep learning techniques

This paper presents the work completed towards the development of a multi-modal global surveillance methodology using cube satellite (CubeSat) platforms and novel data analysis techniques. A CubeSat system equipped with adequate sensors and data analytics capabilities can autonomously characterize various phenomena of interest on the Earth’s surface. CubeSats are advantageous over conventional satellites in certain remote monitoring applications because of their reduced construction costs (due to the availability of commercially-off-the-shelf components) and are easier to launch. The CubeSat surveillance system developed in this paper focused on phenomena of interest surrounding the nuclear fuel cycle in support of nuclear non-proliferation and emergency response. To observe the phenomena, a constellation of 3U and 6U CubeSats deployed from the ISS with adequate components was chosen. Four different sensor configurations were identified for remote sensing: panchromatic/multispectral in the visible and near-infrared spectrum, multispectral in infrared spectrum, hyperspectral in infrared spectrum, and multispectral in ultraviolet spectrum. While a panchromatic/multispectral sensor configuration has CubeSat flight heritage at the required spatial resolutions, the other three sensor types need future 3 development to meet signature and system requirements. Once each sensor onboard the CubeSat system collects data on a target of interest, the onboard computers would then apply the deep learning-based characterization methodology developed in this paper to identify phenomena. Four surrogate datasets containing representative simplified “images” were created for each sensor type to train the characterization methodology. A convolutional neural network was applied to each dataset and produced recall rates for the phenomena between 89.7% - 99.3% and precision rates between 92.3% - 99.9%. Each phenomenon’s presence probability from each network is then combined into a final characterization solution for a target area. This paper covers multiple interdisciplinary areas to develop the foundation for a CubeSat surveillance system focused on phenomena surrounding the nuclear fuel cycle.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Abatement of ionizing radiation for superconducting quantum devices

Ionizing radiation has been shown to reduce the performance of superconducting quantum circuits. In this report, we evaluate the expected contributions of different sources of ambient radioactivity for typical superconducting qubit experiment platforms. Our assessment of radioactivity inside a typical cryostat highlights the importance of selecting appropriate materials for the experiment components nearest to qubit devices, such as packaging and electrical interconnects. We present a shallow underground facility (30-meter water equivalent) to reduce the flux of cosmic rays and a lead shielded cryostat to abate the naturally occurring radiogenic gamma-ray flux in the laboratory environment. We predict that superconducting qubit devices operated in this facility could experience a reduced rate of correlated multi-qubit errors by a factor of approximately 20 relative to the rate in a typical above-ground, unshielded facility. Finally, we outline overall design improvements that would be required to further reduce the residual ionizing radiation rate, down to the limit of current generation direct detection dark matter experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Magnetic contribution of itinerant electrons to neutron diffraction in the topological antiferromagnet CeAlGe

We report a neutron diffraction study of the magnetic structure of CeAlGe, a candidate topological semimetal that hosts a noncollinear, multi-𝐤 magnetic phase. By measuring both low- and high-momentum-transfer magnetic Bragg peaks within a single experimental setup, we refine a magnetic structure model based solely on localized Ce moments. This model, which differs from that obtained using only high-𝑄 data, quantitatively reproduces the observed intensities, including the (000) zeroth-order magnetic satellites that are especially sensitive to subtle components of the modulation. While a contribution from itinerant electrons to the zeroth satellite cannot be definitively excluded, our analysis reveals no unambiguous evidence for such effects within experimental uncertainty. The refined magnetic structures exhibit topologically nontrivial winding patterns, derived from the fitted magnetic parameters, that support localized, particle-like spin textures with half-integer topological charges. These features provide a natural microscopic origin for the observed topological Hall effect, establishing CeAlGe as a model system where magnetism and topology are intimately linked.

Magnetic coupling↗
DOE OSTI2017

Final Technical Report for "Nuclear Technologies for Near Term Fusion Devices"

Over approximately 18 years, this project evolved to focus on a number of related topics, all tied to the nuclear analysis of fusion energy systems. For the earliest years, the University of Wisconsin (UW)’s effort was in support of the Advanced Power Extraction (APEX) study to investigate high power density first wall and blanket systems. A variety of design concepts were studied before this study gave way to a design effort for a US Test Blanket Module (TBM) to be installed in ITER. Simultaneous to this TBM project, nuclear analysis supported the conceptual design of a number of fusion nuclear science facilities that might fill a role in the path to fusion energy. Beginning in approximately 2005, this project added a component focused on the development of novel radiation transport software capability in support of the above nuclear analysis needs. Specifically, a clear need was identified to support neutron and photon transport on the complex geometries associated with Computer-Aided Design (CAD). Following the initial development of the Direct Accelerated Geoemtry Monte Carlo (DAGMC) capability, additional features were added, including unstructured mesh tallies and multi-physics analysis such as the Rigorous 2-Step (R2S) methodology for Shutdown Dose Rate (SDR) prediction. Throughout the project, there were also smaller tasks in support of the fusion materials community and for the testing of changes to the nuclear data that is fundamental to this kind of nuclear analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Multi-resolution Arctic Shrub Cover Dataset Derived from UAS and Airborne SfM and LiDAR (2013-2025)

We synthesized 177 unoccupied aerial system flights and 77 airborne flights across the Arctic and created a multi-resolution benchmark data of low-to-tall shrub fractional cover leveraging Structure-from-Motion and Light Detection and Ranging. The resulting dataset covered a total of 1899 km2 across Alaska, Western Canada, Sweden, and Siberian Arctic, including key sites from the Oro Arctic to the High Arctic. The dataset is organized into 6 primary data collection directories (“Abisko,” “AWI,” “ERE,” “Fairbanks,” “NGEE,” “Toolik”), each containing site and flight subdirectories. Flight directories include shrub cover rasters (*.tifs) at 1 m, 5 m, and 30 m resolution, the canopy height model at 1 m resolution (*.tifs), and a bounding box *.kml file. For the AWI, Abisko, NGEE, and Fairbanks collections, we also include the GCC raster at 1 m resolution (*.tif). Files are organized by Collection > Site > Flight Name > Data Files. Flight rasters are in the local UTM zone and the .kml files are in the geographic coordinate system EPSG 4326. We also include a .csv file that details the source datasets for every flight. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

canopy height model↗
DOE OSTI2017

Multi-Higgs doublet models: physical parametrization, sum rules and unitarity bounds

If the scalar sector of the Standard Model is non-minimal, one might expect multiple generations of the hypercharge-1/2 scalar doublet analogous to the generational structure of the fermions. In this work, we examine the structure of a Higgs sector consisting of N Higgs doublets (where N ≥ 2). It is particularly convenient to work in the so-called charged Higgs basis, in which the neutral Higgs vacuum expectation value resides entirely in the first Higgs doublet, and the charged components of remaining N - 1 Higgs doublets are mass-eigenstate fields. We elucidate the interactions of the gauge bosons with the physical Higgs scalars and the Goldstone bosons and show that they are determined by an N × 2N matrix. This matrix depends on (N - 1)(2N - 1) real parameters that are associated with the mixing of the neutral Higgs fields in the charged Higgs basis. Among these parameters, N - 1 are unphysical (and can be removed by rephasing the physical charged Higgs fields), and the remaining 2(N - 1) 2 parameters are physical. We also demonstrate a particularly simple form for the cubic interaction and some of the quartic interactions of the Goldstone bosons with the physical Higgs scalars. These results are applied in the derivation of Higgs coupling sum rules and tree-level unitarity bounds that restrict the size of the quartic scalar couplings. In particular, new applications to three Higgs doublet models with an order-4 CP symmetry and with a Z 3 symmetry, respectively, are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Chapter 6: Recent Advances in Perovskite Tandem Devices

Organic-inorganic halide perovskites have recently emerged as a new class of light absorbers in solar conversion applications. The power conversion efficiency of single-junction perovskite solar cells (PSCs) has already surpassed conventional polycrystalline thin-film solar cell technologies and is even projected to be competitive with single-crystalline solar cells. Along with the continued effort on further advancing single-junction PSC technology, many research groups have started to develop perovskite-based tandem devices with the ultimate goal to move beyond the Shockley-Queisser limit for single-junction devices. In this book chapter, we first discuss basic concepts and ideas for general tandem devices in photovoltaic (PV) and photo-electrochemical (PEC) applications, spectrum and current matching, and typical device architectures (monolithic vs. multi-terminal). We then focus on the advantages and the main challenges of using perovskite materials, both in tandem with existing PV materials and in all-perovskite tandem devices. Bandgap engineering is essential to achieve efficient perovskite tandem devices. We discuss several strategies of bandgap engineering through composition alloying as well as existing issues in both intrinsic material properties and material processing difficulties. A key component to tandem devices is the transparent interconnection layers/electrodes. We review and comment on some possible candidates of this interconnection layer. Finally, we review the current status and provide future prospective in this field by summarizing state-of-the-art perovskite tandem PV and PEC devices.

14 SOLAR ENERGY↗
DOE OSTI2025

Urban weather modeling using WRF: linking physical assumptions, code implementation, and observational needs

The Weather Research and Forecasting (WRF) model includes urban schemes that simulate the influence of urban surfaces on the atmosphere using parameterizations for flux, and radiative exchanges. Three core schemes – the Bulk urban parameterization, Single-Layer Urban Canopy Model (SLUCM), and Multi-Layer Urban Canopy Model (MLUCM) – represent increasing levels of complexity. Although the parameterizations within these urban schemes are described in the literature, their specific implementation remains poorly documented, thus slowing down model development efforts. This manuscript provides a roadmap to the three urban schemes in WRF version 4.5.2, presenting equations using the same symbols as in the model code, along with references to code lines, and including graphics and explanations that connect the code to its physical foundations. Our thorough review of the urban parameterizations implemented in WRF version 4.5.2 highlighted a handful of parameters that may introduce discontinuities in simulations: (i) in the SLUCM, a 1 mm h −1 rain rate threshold is employed to switch between two minimum moisture availability parameterizations, thus impacting latent heat flux calculations; (ii) in the SLUCM a threshold is used to partition shortwave radiation into direct and diffuse components; (iii) in all three urban schemes, the bulk Richardson number is employed to select the similarity function, which influences the vertical distribution of heat and momentum. We also identified a highly simplified treatment of the radiative balance on roof surfaces. The implications of these simplifications can be assessed through targeted observations across relevant conditions, including varying precipitation rates, cloud cover, and transitions between stability regimes. Furthermore, the widespread application of the Monin-Obukhov similarity theory in these urban schemes warrants model evaluation under highly stable and unstable conditions and in heterogeneous urban settings with variable land cover and building heights on scales finer than model resolution. To address these challenges, we offer guidance on observational strategies, emphasizing the need for multi-parametric measurements to capture potential compensating biases and multi-height measurements that align with the levels where quantities are diagnostic and prognosed in the model (i.e., the lowest atmospheric level of the WRF model). Finally, our inspection of the code revealed implementation bugs that have now been corrected in WRF versions 4.6.0 and 4.6.1. Sensitivity tests over the Atlanta urban area show that these corrections affect surface temperatures, underscoring the importance of performing rigorous documentation and verification of the implementation of parameterizations in model code.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Daytime urban heat stress in North America reduced by irrigation

There is considerable uncertainty regarding the impact of irrigation on heat stress, partly stemming from the choice of heat stress index. Moreover, existing simulations are at scales that cannot appropriately resolve population centres or clouds and thus the potential for human impacts. Using multi-year convection-permitting and urban-resolving regional climate simulations, we demonstrate that irrigation alleviates summertime heat stress across more than 1,600 urban clusters in North America. This holds true for most physiologically relevant heat stress indices. The impact of irrigation varies by climate zone, with more notable irrigation signals seen for arid urban clusters that are situated near heavily irrigated fields. Through a component attribution framework, we show that irrigation-induced changes in wet-bulb temperature, often used as a moist heat stress proxy in the geosciences, exhibit an opposite sign to the corresponding changes in wet bulb globe temperature—a more complete index for assessing both indoor and outdoor heat risk—across climate zones. In contrast, the local changes in both wet-bulb and wet bulb globe temperature due to urbanization have the same sign. Here, our results demonstrate a complex relationship between irrigation and heat stress, highlighting the importance of using appropriate heat stress indices when assessing the potential for population-scale human impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

SIERRA Code Coupling Module: Arpeggio User Manual (Version 4.48)

The SNL Sierra Mechanics code suite is designed to enable simulation of complex multi-physics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Machine Learning Enabled Sensor Fusion for In-Situ Defect Detection in Laser Powder Bed Fusion

Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. The current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques such as X-Ray Computed Tomography (XCT), which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. RTX Technologies Research Center (RTRC) has licensed ORNL’s Peregrine software package – a printer- and camera-agnostic data analytics tool designed specifically for detecting process anomalies using in situ data collected during powder bed printing. The goal of this project was to feed temporally rich, multi-modal sensor data, including visible light, integrated near infrared (NIR), and spatially mapped co-axial melt pool thermal emission data into Peregrine to enable detection of subsurface flaws. XCT data was used as ground truth training data to allow Peregrine’s deep learning algorithms to recognize anomalies in these complex data streams in both test artifacts and industrially relevant geometries. Completion of this program has seen the successful implementation of multi-modal, multi-layer sensor data footprints for training of machine learning models in Peregrine. Flaws detected in XCT data have been successfully detected directly from this in situ data footprint, and initial analyses of the in situ probability-of-detection has been conducted, showing performance levels commensurate with traditional non-destructive evaluation (NDE) methods. The in situ monitoring methodology was then applied to an industrially relevant component that was using post-build NDE, highlighting the utility of the proposed method for hard-to-inspect AM components. As a direct result of this program, two journal manuscripts [1], [2] have been published in Additive Manufacturing, with additional manuscripts planned following program completion.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electromagnetic Energy-Assisted Thermal Conversion of Fossil-Based Hydrocarbons to Low-Cost Hydrogen

The goal of this project was to develop and optimize catalysts for methane decomposition, particularly focusing on regeneration via an electromagnetic energy-assisted mechanism, to produce hydrogen more cost-effectively compared to electrolysis routes. To achieve this goal, the project pursued several key objectives. The project began with the preparation and testing of various catalysts. A nickel-silica based catalyst was identified as the most promising material for the pyrolysis of methane into carbon and hydrogen. Kinetic parameters for methane decomposition were determined, aiding in computational modeling efforts. Structured catalysts were investigated, highlighting the need for frequent cleaning or regeneration to maintain performance, with methane conversion rates exceeding 70% in tube furnace tests. Computational fluid dynamics modeling was employed to optimize reactor designs and electrode angles, leading the project team to propose a multi-compartment thermal conversion system for larger setups. This modeling work was important in understanding reaction characteristics, carbon deposition rates, and temperature profiles under various conditions. A bench-scale reactor system was assembled to evaluate catalyst regeneration using electromagnetic energy-assisted mechanisms. Experiments demonstrated the potential for carbon removal, though further optimization is needed. The carbon produced from the methane conversion process was evaluated for potential use in lithium-ion battery electrodes. The carbon exhibited properties similar to commercially available high-purity multi-walled carbon nanotubes and nanofibers, with a carbon content greater than 95%. Coin cell batteries assembled with this carbon showed that lower replacement levels (10% to 33%) outperformed the control group, improving specific capacity density and stability. However, higher replacement levels (100%) demonstrated poorer performance, suggesting that excessive carbon substitution negatively impacts battery performance. These findings indicate the potential marketability of the produced carbon as a component in lithium-ion batteries, though further testing is necessary to confirm long-term advantages and disadvantages associated with the use of the carbon product. These results however justified further technoeconomic assessments to determine if the process can provide low-cost hydrogen. The economic feasibility and technical performance of methane decomposition for hydrogen production were assessed, focusing on three plant configurations: 100E (electrically heated), 100C (combustion heated using produced hydrogen), and PE-Hybrid (a combination of pyrolysis (indicating decomposition) and electrolysis). The Levelized Cost of Hydrogen (LCOH) for the pyrolysis configurations was found to be approximately 25% lower than that of electrolysis. The 100E configuration had the lowest LCOH at $\$$3.12/kg. Including carbon product sales significantly improved the economics, with the 100C configuration achieving a negative LCOH of -$\$$0.35/kg. The PE-Hybrid configuration was not economically advantageous compared to pure pyrolysis plants due to its complexity and additional equipment requirements. Ultimately, methane pyrolysis presents a viable method for near carbon dioxide-free hydrogen production, with significant economic advantages over electrolysis, especially when considering the sale of carbon byproducts. The 100E and 100C configurations showed the most promise, with the choice between them ultimately depending on the prices of power and natural gas. In conclusion, this technology has the potential to lower hydrogen production costs by leveraging the methane decomposition process with the sale of valuable carbon byproducts. By optimizing catalyst performance and integrating electromagnetic energy-assisted regeneration, the process can achieve higher efficiency and economic viability, making it a competitive alternative to traditional hydrogen production methods.

08 HYDROGEN↗
DOE OSTI2021

Sensor array and apparatus for simultaneous observation of tissue electrophysiology, contractility, and growth

A sensor array for simultaneously measuring electrophysiological responses and contractility responses of a tissue includes: a substrate; a multi-electrode array (MEA) disposed in or on the substrate; and a plurality of interdigitized electrodes (IDEs) disposed in or on the substrate. The MEA and the IDEs are interpenetrating within a plane substantially parallel to an upper surface of the substrate. Systems for measuring such responses using the sensor array may also include contacts and/or connectors for interfacing with external control devices, electrodes, and cell culture components such as a chamber and lid. Fabrication techniques for making such systems include: forming a sensor array comprising an interpenetrating arrangement of IDEs and electrodes of a MEA in or on a substrate surface; forming a plurality of contacts for interfacing the system with one or more external devices in or on the substrate surface; and forming leads between the plurality of contacts and the sensor array.

Qian, Fang↗
DOE OSTI2019

Building Towards Discovery: Preparing for New Physics at the LHC [Final papers]

Particle physics today is at a crossroads. The Standard Model (SM) has survived four decades of experimental scrutiny and spurred multiple landmark discoveries, culminating with the 2012 discovery of the Higgs boson at the Large Hadron Collider (LHC). Yet we know that this model is incomplete. We live in a universe dominated by matter and energy unaccounted for by the SM– and the Higgs boson itself is improbably light. It falls to the current generation of high-energy physicists to go beyond the model and enter a new era of discovery. Andeen is leading a new research group at the University of Texas at Austin (UT-Austin) that is endeavoring to reveal novel physical phenomena through the discovery of new particles with the ATLAS detector at the LHC. A key element of our experience thus far has been collaborating closely with theorists to identify both interesting new physics models. In addition we work closely with electrical engineers in detector development. Our approach is therefore unique in its integration of theory, analysis and instrumentation, and is encapsulated in a three-pronged strategy. First is the essential task of analyzing our rapidly expanding dataset. I am directing my group in searches for vector-like quarks (VLQs). Should they exist, these hypothetical particles would indicate physics scenarios beyond the SM. Experimental constraints suggest VLQs decay preferentially to a third generation quark and a Higgs, W or Z boson. Today at 13 TeV, both multi-lepton (electron and muon) and jet substructure signatures are sensitive to identifying the VLQ decay products. The large Run 2 dataset (collected through 2018) of up to 150 fb -1 will allow us to simultaneously use multi-lepton signatures with jet-substructure in searches for new physics. UT-Austin is well positioned to be a leader in this area. Prof. P. Onyisi’s postdoctoral researchers and graduate students are searching for ttH signatures in three- and four-lepton channels and we benefit from their experience. We are also aided by the availability of the Texas Advanced Computing Center, which provides us with easy access to several high performance computing (HPC) systems. My previous experience in VLQ searches propels the work today. I have published both the first investigation into the single production of top partners (signatures of composite Higgs Models) of any LHC experiment 1 as well as one of the first analyses utilizing jet-substructure techniques to search for the single production of vector-like quarks. 2 Adding to this is my group’s work with the Liquid Argon (LAr) calorimeter, the primary instrument we use in detecting electrons. Second, my group is contributing to the operations of the LAr calorimeter while preparing to install and commission new electronic hardware (the Phase 1 upgrade) to this crucial component of the ATLAS detector. I have played a leading role in the development of a critical, radiation-hard, high-speed Analog-to-Digital Convertor (ADC) that is essential inselecting data collected by the LAr calorimeter. 3 This upgrade will improve the e!ciency with which we can select events in our detector. Postdoctoral researcher N. Nikiforou (based at CERN May 2016 onward) and graduate students (one based at CERN from the start of 2018 onward, with one additional graduate students from summer 2018) are growing our already deep experience in the operation of the LAr calorimeter to prepare for installation and commissioning of the new trigger readout in 2018-2019. My group will then be positioned to be the first to exploit the potential of the improved triggers in our multi-lepton searches for new physics. Third, a suite of preparations for a major detector upgrade, scheduled to be completed in 2024, are underway. My group is building hardware that will improve the electronic readout of the ATLAS detector. I am partnering with a group in the Electrical and Computer Engineering (ECE) Department at UT-Austin (Prof. N. Sun) to employ his work at the cutting edge of ADC research. We will support an ECE grad student for the layout of this design, and collaborate with engineering groups at Nevis Laboratory and the Electrical Engineering Department (Prof. P. Kinget) at Columbia University to integrate our ADC with gain selection circuits. We will provide this critical component of the ASIC at the challenging boundary of the analog and digital signals in the LAr calorimeter readout chain. Furthermore UT-Austin will lead the testing of this device during development and production (approximately 55,000 four-channel chips). This effort compliments my work as the deliverables manager for the LAr front-end ASICs for the US ATLAS HL-LHC project and strengthens the US commitment to that upgrade.In so doing, my group at the UT-Austin will be at the forefront of efforts to probe the structure of the universe to an unmatched degree both at the current LHC and with its future upgrades. Through both the ongoing analysis of data at the ATLAS detector and improvements to the detector itself, an answer to what lies beyond the SM may come within our grasp. My background in instrumentation and analysis allows my group to establish a singular research effort on the ATLAS experiment. In addition to answering fundamental questions about the subatomic world, the technologies developed could advance the broader scientific community and result in valuable spin-offs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Materials 2018 Annual Progress Report

The Materials Technology Program supports the Vehicles Technologies Office’s mission to help consumers and businesses reduce their transportation energy costs while meeting or exceeding vehicle performance expectations. The propulsion materials research portfolio seeks to develop higher performance materials that can withstand increasingly extreme environments and address the future properties needs of a variety of high-efficiency powertrain types, sizes, fueling concepts, and combustion modes. Advanced lightweight materials enable improvements in fuel economy by providing properties that are equal to or better than traditional materials at a lower weight. Because it takes less energy to accelerate a lighter object, replacing cast-iron and traditional steel components with lightweight materials such as high-strength steel, magnesium (Mg), aluminum (Al), and polymer composites can directly reduce a vehicle’s fuel consumption. Materials technology activities focus on the following cost and performance targets: (1) enable a 25% weight reduction for light-duty (LD) vehicles including body, chassis, and interior as compared to a model year 2012 baseline at no more than a $\$$5/lb-saved increase in cost; and (2) validate a 25% improvement in high-temperature (300°C) development of engine exhaust catalyst materials strength relative to components made with 2010 baseline cast Al alloys (A319 or A356) for improved efficiency LD engines.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

A Scalable Reduced‐Order Model for the Steady Navier–Stokes Equations

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional numerical methods are computationally intractable even for intermediate pilot plant scales. Recently, the component reduced order modeling method has been developed to tackle this challenge by combining projection reduced order modeling and discontinuous Galerkin domain decomposition. However, while many scientific or engineering applications involve nonlinear physics, this method has only been demonstrated for various linear systems. In this work, the component reduced order modeling method is extended to steady Navier–Stokes flow, with application to general nonlinear physics in view. The large‐scale, global domain is decomposed into a combination of small‐scale unit component. Linear subspaces for flow velocity and pressure are identified via proper orthogonal decomposition over sample snapshots collected from each small‐scale unit component. Velocity bases are augmented with a pressure supremizer to satisfy the inf–sup condition for stable pressure prediction. Two different nonlinear reduced order modeling methods are employed and compared for efficient evaluation of nonlinear advection: A third‐order tensor projection operator and the empirical quadrature procedure. The proposed method is demonstrated on the flow over arrays of five different unit objects, achieving a 23‐fold speedup with less than 4% relative error in domains up to 256 times larger than the unit components. Furthermore, a numerical experiment with the pressure supremizer strongly indicates the need for a supremizer for stable pressure prediction. A comparison between the tensorial approach and the empirical quadrature procedure revealed a slight advantage of the empirical quadrature procedure. The framework is compared with an alternating Schwarz‐based reduced‐order approach, demonstrating improved efficiency and robustness for the DG‐based global solver while retaining flexibility for sub‐scale iterative solvers. The method is further extended to a coupled advection–diffusion and Navier–Stokes system, illustrating its applicability to multi‐physics problems and its potential for more general, inter‐coupled nonlinear systems.

42 ENGINEERING↗
DOE OSTI2018

Evolving Robust and Reconfigurable Multi-objective Controllers for Advanced Power Systems

Motivation: To meet the ever-increasing power requirements of our society, as well as minimize emissions and environmental impact, the efficiency, reliability, performance, and robustness of power plants need to improve significantly. As a consequence, research on all aspects of power plants, ranging from combustion, gasification, turbines, fuel cells, gas cleaning and separation and carbon dioxide separation and capture is being conducted. But it is not sufficient to simply provide advances in any (or all) of these areas. Advances in each of these areas increases the complexity of every component of a power system, and their integration creates fundamentally new problems in the areas of modeling, sensing, optimization and control.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Optical design for the single crystal neutron diffractometer Pioneer

Pioneer is a single-crystal neutron diffractometer optimized for small-volume samples and weak signals at the Second Target Station at Oak Ridge National Laboratory. This paper presents the preliminary optical design progress, focusing on the rationale behind key design choices. It covers the T 0 and bandwidth disk choppers, guide and beam control system, incident-beam polarizer, scattering beam collimators, and additional strategies. The chopper locations are selected to maximize neutron transport while taking advantage of standardized shielding structures. To accommodate the maintenance shield, operational shutter, and polarizing V-cavity, the guide design includes significant gaps. When these optical components are moved out of the beam path, oversized collimators, rather than guides, will be translated in. Pioneer will utilize slit packages to control beam size and divergence and a translatable polarizing V-cavity. Absorbing panels are strategically placed near the end station to minimize background. An oscillating radial collimator, operating in a shift mode, will be used with the vertical cylindrical detector, while a fixed multi-cone collimator will be used with the bottom flat detector. In conclusion, these collimators will enable the detection of weak signals when complex sample environments are used.

47 OTHER INSTRUMENTATION↗