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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 OSTI2017

The Super DREAM Project

Despite the fact that DOE provided only a fraction of the requested funds, the goals we defined in the proposal on which award ER41783 was based were essentially all met. This was partially due to the fact that other funding agencies, which supported our collaborators (especially from Italy and Korea) contributed as well, and partially due to the effective solutions that were developed to compensate for the fact that the detector we had proposed to build had to be scaled down. The performance of the SuperDREAM calorimeter is better than anything that has been built or proposed so far. This has of course not gone unnoticed in the scientific community. Scientists who are preparing experiments for the proposed new generation of particle accelerators (FCCee, CPEC,..) are all very seriously considering the technology developed in this project. Several new collaborations have formed which aim to adapt the dual-readout calorimeter principles to the demands of a 4 environment. Preliminary measurements using silicon photomultipliers as light sensors have already been carried out. This type of readout would make it possible to operate this detector in a magnetic field, and it would also allow for a longitudinal segmentation into electromagnetic and hadronic sections, if so desired. In addition, SiPM readout would eliminate the need for “forests” of fibers sticking out of the rear end of the calorimeter (Figure 1), and obtain an arbitrary fine lateral segmentation, which might be very important for recognizing electrons inside jets. The improvements in our understanding of the fundamental structure of matter and the forces that govern its behavior have always hinged on the availability of detectors that make it possible to explore the possibilities of new, more powerful particle accelerators to the fullest extent. We believe that the SuperDREAM project has created a quantum leap in detector technology, which may turn out to be crucially important for future discoveries in particle physics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Institute for Sustained Performance, Energy, and Resilience (SuPER)

The University of Tennessee (UTK) and University of Texas at El Paso (UTEP) partnership supported the three main thrusts of the SUPER project---performance, energy, and resilience. The UTK-UTEP effort thus helped advance the main goal of SUPER, which was to ensure that DOE's computational scientists can successfully exploit the emerging generation of high performance computing (HPC) systems. This goal is being met by providing application scientists with strategies and tools to productively maximize performance, conserve energy, and attain resilience. The primary vehicle through which UTK provided performance measurement support to SUPER and the larger HPC community is the Performance Application Programming Interface (PAPI). PAPI is an ongoing project that provides a consistent interface and methodology for collecting hardware performance information from various hardware and software components, including most major CPUs, GPUs and accelerators, interconnects, I/O systems, and power interfaces, as well as virtual cloud environments. The PAPI software is widely used for performance modeling of scientific and engineering applications---for example, the HOMME (High Order Methods Modeling Environment) climate code, and the GAMESS and NWChem computational chemistry codes---on DOE supercomputers. PAPI is widely deployed as middleware for use by higher-level profiling, tracing, and sampling tools (e.g., CrayPat, HPCToolkit, Scalasca, Score-P, TAU, Vampir, PerfExpert), making it the de facto standard for hardware counter analysis. PAPI has established itself as fundamental software infrastructure in every application domain (spanning academia, government, and industry), where improving performance can be mission critical. Ultimately, as more application scientists migrate their applications to HPC platforms, they will benefit from the extended capabilities this grant brought to PAPI to analyze and optimize performance in these environments, whether they use PAPI directly, or via third-party performance tools. Capabilities added to PAPI through this grant include support for new architectures such as the lastest GPU and Xeon Phi accelerators, and advanced power measurement and management features. Another important topic for the UTK team was providing support for a rich ecosystem of different fault management strategies in the context of parallel computing. Our long term efforts have been oriented toward proposing flexible strategies and providing building boxes that application developers can use to build the most efficient fault management technique for their application. These efforts span across the entire software spectrum, from theoretical models of existing strategies to easily assess their performance, to algorithmic modifications to take advantage of specific mathematical properties for data redundancy and to extensions to widely used programming paradigms to empower the application developers to deal with all types of faults. We have also continued our tight collaborations with users to help them adopt these technologies to ensure their application always deliver meaningful scientific data. Large supercomputer systems are becoming more and more power and energy constrained, and future systems and applications running on them will need to be optimized to run under power caps and/or minimize energy consumption. The UTEP team contributed to the SUPER energy thrust by developing power modeling methodologies and investigating power management strategies. Scalability modeling results showed that some applications can scale better with respect to an increasing power budget than with respect to only the number of processors. Power management, in particular shifting power to processors on the critical path of an application execution, can reduce perturbation due to system noise and other sources of runtime variability, which are growing problems on large-scale power-constrained computer systems.

42 ENGINEERING↗
DOE OSTI2018

The Institute for Sustained Performance, Energy, and Resilience, University of North Carolina, Final Technical Report

This is the final report for the UNC component of the SciDAD Institute for Sustained Performance, Energy, and Resilience. In this report, we describe activities on the SUPER project at RENCI at the University of North Carolina at Chapel Hill. While we focus particularly on UNC, we touch on project-wide activities as well as, on interactions with, and impacts on, other projects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Project Final Report: The Institute for Sustained Performance, Energy, and Resilience (SUPER)

This project concentrated on various aspects of creating and applying tool infrastructure to make it easier to effectively use large-scale parallel computers. This project was collaborative with Argonne National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, Oak Ridge National Laboratory, U.C. San Diego, University of Maryland, University of North Carolina, University of Oregon, University Southern California, University of Tennessee, and University of Utah. The research conducted during this project at the University of Maryland is summarized in this report. The complete details of the work are available in the publications listed at the end of the report. Many of the concepts created during this project have been incorporated into tools and made available as freely downloadable software (www.dyninst.org/harmony). It also supported the studies of six graduate students, one undergraduate student, and two post-docs. The funding also provided summer support for the PI and part of the salary of a research staff member.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Development of ultra-pure gadolinium sulfate for the Super-Kamiokande gadolinium project

This paper reports the development and detailed properties of about 13 metric tons of gadolinium sulfate octahydrate, Gd 2 (SO 4 ) 3 • 8H 2 O⁠, which has been dissolved into Super-Kamiokande (SK) in the summer of 2020. We evaluate the impact of radioactive impurities in Gd 2 (SO 4 ) 3 • 8H 2 O on diffuse supernova neutrino background searches and solar neutrino observation and confirm the need to reduce radioactive and fluorescent impurities by about three orders of magnitude from commercially available high-purity Gd 2 (SO 4 ) 3 • 8H 2 O⁠. In order to produce ultra-high-purity Gd 2 (SO 4 ) 3 • 8H 2 O, we have developed a method to remove impurities from gadolinium oxide, Gd 2 O 3 , consisting of acid dissolution, solvent extraction, and pH control processes, followed by a high-purity sulfation process. All of the produced ultra-high-purity Gd 2 (SO 4 ) 3 • 8H 2 O is assayed by inductively coupled plasma mass spectrometry and high-purity germanium detectors to evaluate its quality. Because of the long measurement time of high-purity germanium detectors, we have employed several underground laboratories for making parallel measurements including the Laboratorio Subterráneo de Canfranc in Spain, Boulby in the UK, and Kamioka in Japan. In the first half of production, the measured batch purities were found to be consistent with the specifications. However, in the latter half, the Gd 2 (SO 4 ) 3 • 8H 2 O contained one order of magnitude more 228Ra than the budgeted mean contamination. This was correlated with the corresponding characteristics of the raw material Gd 2 O 3 , in which an intrinsically large contamination was present. Based on their modest impact on SK physics, they were nevertheless introduced into the detector. To reduce 228 Ra for the next stage of gadolinium loading to SK, a new process has been successfully established.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

FY26 Progress Report on the Operation of the Activated Materials Laboratory at the Advanced Photon Source as a Nuclear Science User Facilities Partner Facility

The Activated Materials Laboratory (AML), located in the Long Beamline Building of the Advanced Photon Source (APS) at Argonne National Laboratory (ANL), provides a centralized radiological capability for preparing, handling, and supporting synchrotron experiments on activated materials. As a Nuclear Science User Facilities (NSUF) partner facility, the AML enables the receipt of radioactive shipments, open-form sample handling, encapsulation, transport of specimens to and from APS beamlines, and experimentation with dedicated equipment. The partnership includes the APS 1-ID and 20-ID beamlines, which provide high-energy x-ray scattering, tomography, and diffraction microscopy techniques for ex-situ, in-situ, and grainresolved three-dimensional (3D) characterization. All samples supported through the AML and partner beamlines must meet radiological limits of less than 100 mrem/h at 30 cm. This FY26 progress report summarizes the first full year of AML operations as an NSUF partner facility and highlights progress in both user support and capability development. By the end of FY26, the AML had received a total of 10 NSUF-awarded projects, including 2 Consolidated Innovative Nuclear Research (CINR), 7 Rapid Turnaround Experiment (RTE), and 1 Super RTE projects. Beamtime was fully delivered for 3 RTE projects and partially delivered for 1 CINR project, demonstrating successful workflows for receipt, encapsulation, beamline transfer, and radiological experiment execution. These efforts demonstrated safe radiological experiments at APS beamlines for samples with dose rates above the historical 5 mrem/h threshold and now up to 100 mrem/h at 30 cm, marking an important milestone for neutron-irradiated materials research. During FY26, the AML also expanded its experimental capabilities. A Psylotech xTS load frame with in-grip rotation was deployed for room-temperature mechanical testing with threedimensional x-ray characterization during interrupted loading. A Linkam TS1500V vacuum heater was commissioned for thermally driven studies, and temperature calibration experiments were performed to establish specimen-relevant thermal profiles. In parallel, a customized split-tube furnace for high-temperature mechanical testing entered commissioning, and initial work began on robotic sample handling to reduce worker dose and improve operational efficiency. Data workflow and beamline operations continued to mature. Together, these developments demonstrate that the AML is becoming a unique national resource for safe, efficient, and scientifically advanced characterization of activated materials at the APS.

Zhang, Xuan↗
DOE OSTI2018

Toward Super Hot EGS: The Newberry Deep Drilling Project

Newberry Volcano in Central Oregon is an extensively studied volcano that contains one of the largest geothermal heat reservoirs in the western United States. The detailed characterization of this continental volcanic system reveals it is an excellent choice for drilling a well that will reach temperatures greater than 450°C at relatively shallow depths (< 5000 m). The main purpose of the Newberry Deep Drilling Project (NDDP) is to test the feasibility of super-hot EGS where super critical fluid can be produced with a higher energy compared to conventional EGS. NDDP will be located at an idle geothermal exploration well, NWG 46-16, drilled in 2008 on the western flank of the volcano. The project has several main goals: test EGS above the critical point of water; collect samples of rocks within the brittle-ductile transition zone; investigate volcanic hazards; study geomechanics in plastic rock and test technology for drilling, well completion, and geophysical monitoring. The well NWG 46-16, now 3500 m deep and 340-374°C at bottom, will be deepened another 1000 to 1300 m to reach 500°C into the supercritical region, and potentially approaching the brittle-ductile transition or even zones of partial melt. The original well was drilled with lost circulation zones only at very shallow depth and the temperature profile indicates conductive heat flow. Compared to other super-hot geothermal projects worldwide, this well would return more materials (cuttings, core and fluids) with more predictable drilling conditions, thus providing a suite of data near and across the brittle-ductile transition in silica-rich rocks. The well will be completed with casing and cement designed and tested to withstand the abuses of thermal cycling, hydraulic and thermal stimulation, and flow of supercritical fluids. Geothermal, volcanic, geophysical, and engineering information gained will be widely applicable to other magmatically active areas throughout the Pacific Rim and beyond.

EGS, supercritical, Newberry Volcano, brittle-duct↗
DOE OSTI2019

Accurate Taylor transfer maps for large aperture iron dominated magnets used in charged particle separators and spectrometers

For high-resolution separators like the projected Super-FRS at FAIR, an adapted and accurate ion-optical model considering realistic $B$-dependent magnet parameters is crucial in achieving the desired parameters (e.g. resolution) and to enable a fast optimization. Starting from the magnetic field measurements and simulations, rigidity-dependent Taylor transfer maps are generated for the Super-FRS preseparator dipole magnets. The effects of the magnetic saturation in the steel yoke on the image aberrations are analyzed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Super Hot EGS and the Newberry Deep Drilling Project

A productive geothermal well drilled into super-hot rock (SHR) with a temperature above 400°C will produce super-critical fluid. At a flow rate of 60 kg/s, a SHR well could produce 50 MWe compared to 5-7 MWe for the same flow at 200°C. Even though these deeper, super-hot wells will cost more, the high energy density means power produced by engineered geothermal systems (EGS) can meet the market ($46 MW-hr) by directly tapping the heat source. We propose a proof of concept where hot rock is close to the surface (~5 km), and the cost of drilling and EGS stimulation will be lowest. A suitable, ready-to-go SHR site is on Newberry Volcano, Oregon, one of the largest geothermal heat reservoirs in the USA, extensively studied for the last 40 years. Millions of dollars have already been invested in the site by private geothermal developers and the US Department of Energy (DOE), resulting in a ready-to-use facility with the necessary infrastructure, environmental permits, land commitments, and monitoring plans. The Newberry Deep Drilling Project (NDDP) will be located at an idle geothermal exploration well, NWG 46-16, drilled in 2008, 3500 m deep and 320°C at bottom, which will be deepened another 1000 to 1300 m to reach 500 °C. The original well was drilled with few lost circulation zones and the temperature profile indicates conductive heat flow. Compared to other SHR projects world-wide, this well would return more materials (cuttings, core and fluids) with more predictable drilling conditions, thus providing a suite of data near and across the brittle-ductile transition in silicarich rocks. After drilling, a hydraulic well stimulation will both change the pore pressure in fractures and cool the fracture walls resulting in permeability enhancement through both thermal fracturing, and hydro-shearing. The first step for the NDDP was an International Continental Drilling Program (ICDP) sponsored workshop held at the OSU-Cascades campus in Bend from Sept. 10-14, 2017. The workshop concluded by setting ambitious goals for NDDP: 1) test EGS above the critical point of water, 2) collect samples of rocks within the brittle-ductile transition, 3) investigate volcanic hazards, 4) study magmatic geomechanics, 5) calibrate geophysical imaging techniques, and 6) test technology for drilling, well completion, and geophysical monitoring in a very high temperature environment. The second step, completed January 15, 2018, was submitting a proposal to ICDP for 46-16 deepening. The next steps will be to continue building a team with project, technology, and investment partners to make NDDP a reality.

EGS, Geothermal, Newberry↗
DOE OSTI2022

Quantum Chemical Treatment of Strongly Correlated Magnetic Systems Based on Heavy Elements. Final Report

The objective of this project over the years has been to develop novel quantum chemical methods and employ them to study the chemistry of systems containing actinides, and transactinides. We have focused on their electronic and spectroscopic properties, their reactivity and utilization as single molecule magnets. We have developed wave-function based methods that are optimal to treat strongly correlated systems, namely systems with many electronic configurations that are all important and should be treated on an equal foot. Moreover, relativistic effects have to be included in the model, with special focus on spin-orbit coupling. We have derived our theories and developed our codes and made them available to the community as parts of open source packages. We have modelled systems in collaboration with experimentalists in the program, so that we could address some of the questions that are relevant to this community. We have also worked in collaboration with people at Lawrence Livermore National Laboratories on a project on super-heavy atoms. We hope that our theoretical predictions will inspire novel experiments. We have trained about 10 students/postdocs during this period, which are now faculty, researchers at national laboratories and in companies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Superstrong, Low-Cost Wood for Lightweight Vehicles

The research conducted in this project significantly contributes to the understanding of super wood manufacturing and its potential applications. By developing and optimizing the manufacturing process, we have advanced the knowledge in creating high-performance wood-based materials with enhanced properties. The investigation of lignin transport properties under various conditions provides valuable insights into the behavior of this crucial component in wood and helps us better comprehend the underlying mechanisms involved. This knowledge contributes to the development of more efficient and sustainable methods for producing super wood. The methods and techniques investigated in this project have demonstrated both technical effectiveness and economic feasibility. Through the development of Gen0, Gen1, and Gen2 processes, we have achieved successful manufacturing of super wood with improved properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ESM data downscaling: a comparison of super-resolution deep learning models

Abstract Climate projections at fine spatial resolutions are required to conduct accurate risk assessment for critical infrastructure and design adaptation planning. Generating these projections using advanced Earth system models (ESM) requires significant computational resources. To address this issue, various statistical downscaling techniques have been introduced to generate fine-resolution data from coarse-resolution simulations. In this study, we evaluate and compare five deep learning-based downscaling techniques, namely, super-resolution convolutional neural networks, fast super-resolution convolutional neural network ESM, efficient sub-pixel convolutional neural network, enhanced deep residual network (EDRN), and super-resolution generative adversarial network (SRGAN). These techniques are applied to a dataset generated by the Energy Exascale Earth System Model (E3SM), focusing on key surface variables such as surface temperature, shortwave heat flux, and longwave heat flux. Models are trained and validated using paired fine-resolution (0.25 $$^{\circ }$$ ∘ ) and coarse-resolution (1 $$^{\circ }$$ ∘ ) monthly data obtained from a 9-year simulation. Next, blind testing is performed using monthly data obtained from two different years outside of the training and validation set. To evaluate the efficiency of each technique, different statistical metrics are used, including mean squared error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS). The results show that EDRN outperforms other algorithms in terms of PSNR, SSIM, and MSE, but struggles to capture fine-scale features in the data. In contrast, SRGAN, a generative model that uses perceptual loss, excels in capturing fine details at boundaries and internal structures, resulting in lower LPIPS than other methods.

Pawar, Nikhil M. (ORCID:0000000211613289)↗
DOE OSTI2024

Novel Hot Gas Components for Gas Turbine Engines Enabled by Materials and Additive Manufacturing Process Development

Additive Manufacturing (AM), also known as 3D printing, has emerged as a manufacturing method that enables new design freedom for gas turbine engine manufacturers. However, the material selection for AM processable high-temperature super alloys is currently limited. Additionally, the heat transfer performance of AM enabled micro-cooling architectures is not yet well understood. Accordingly, in support of advanced manufacturing and engine performance development, Oak Ridge National Laboratory (ORNL)and Solar Turbines (Solar) conducted a multidisciplinary project to generate both AM super alloy material properties data and micro-channel performance data for two AM super alloys. The data supported the design and analysis of an internally cooled turbine hot section AM tip shoe component. This data was used to analytically predict the reduction in operating temperature of a gas turbine tip shoe. The work concluded that the cooling flow required to cool the tip shoe can be tuned to suit the efficiency improvements desired in an industrial gas turbine.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Spatial-Spectral Representation for X-Ray Fluorescence Image Super-Resolution

X-ray fluorescence (XRF) scanning of works of art is becoming an increasing popular nondestructive analyticalmethod. The high quality XRF spectra is necessary to obtain significant information on both major and minor elements used for characterization and provenance analysis. However, there is a tradeoff between the spatial resolution of an XRF scan and the signalto- noise ratio (SNR) of each pixel’s spectrum, due to the limited scanning time. In this project, we propose an XRF image super-resolution method to address this tradeoff; thus, obtaining a high spatial resolution XRF scan with high SNR. We fuse a lowresolution XRF image and a conventional RGB high-resolution image into a product of both high spatial and high spectral resolution XRF image. There is no guarantee of a one to one mapping between XRF spectrum and RGB color since, for instance, paintings with hidden layers cannot be detected in visible but can in X-ray wavelengths. We separate the XRF image into the visible and nonvisible components. The spatial resolution of the visible component is increased utilizing the high-resolution RGB image, whereas the spatial resolution of the non-visible component is increased using a total variation super-resolution method. Finally, the visible and nonvisible components are combined to obtain the final result.

Dai, Qiqin↗
DOE OSTI2018

Development of FARICH detector for particle identification system at accelerators

Aerogel has been successfully used as a radiator in Cherenkov detectors. In 2004, a multilayer aerogel providing Cherenkov ring focusing was proposed and produced. FARICH (Focusing Aerogel Rich Imaging CHerenkov) detectors such as ARICH for Belle-II (KEK, Japan), Forward RICH for PANDA detector (FAIR, Germany), and FARICH for the Super Charm-Tau factory project (BINP, Novosibirsk) have been developed based on this aerogel. Prototypes of FARICH detector based on MRS APD and Philips DPC photosensors were developed and tested in the framework of this project. An angular resolution for Cherenkov rings of 3.6 mrad was achieved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Neutrino constraints on inelastic dark matter captured in the Sun

Abstract The flux of neutrinos from annihilation of gravitationally captured dark matter in the Sun has significant constraints from direct-detection experiments. However, these constraints are relaxed for inelastic dark matter as inelastic dark matter interactions generate less energetic nuclear recoils compared to elastic dark matter interactions. In this paper, we explore the possibility for large volume underground neutrino experiments to detect the neutrino flux from captured inelastic dark matter in the Sun. The neutrino spectrum has two components: a mono-energetic “spike” from pion and kaon decays at rest and a broad-spectrum “shoulder” from prompt primary meson decays. We focus on detecting the shoulder neutrinos from annihilation of hadrophilic inelastic dark matter with masses in the range 4–100 GeV and the mass splittings in up to 300 keV. We determine the event selection criterion for DUNE to identify GeV-scale muon neutrinos and anti-neutrinos originating from hadrophilic dark matter annihilation in the Sun, and forecast the sensitivity from contained events. We also map the current bounds from Super-Kamiokande and IceCube on elastic dark matter, as well as the projected limits from Hyper-Kamiokande, to the parameter space of inelastic dark matter. We find that there is a region of parameter space that these neutrino experiments are more sensitive to than the direct-detection experiments. For dark matter annihilation to heavy-quarks, the projected sensitivity of DUNE is weaker than current (future) Super (Hyper) Kamiokande experiments. However, for the light-quark channel, only the spike is observable and DUNE will be the most sensitive experiment.

Astronomy & Astrophysics↗
DOE OSTI2022

Super-resolution image display using diffractive decoders

High-resolution image projection over a large field of view (FOV) is hindered by the restricted space-bandwidth product (SBP) of wavefront modulators. We report a deep learning–enabled diffractive display based on a jointly trained pair of an electronic encoder and a diffractive decoder to synthesize/project super-resolved images using low-resolution wavefront modulators. The digital encoder rapidly preprocesses the high-resolution images so that their spatial information is encoded into low-resolution patterns, projected via a low SBP wavefront modulator. The diffractive decoder processes these low-resolution patterns using transmissive layers structured using deep learning to all-optically synthesize/project super-resolved images at its output FOV. This diffractive image display can achieve a super-resolution factor of ~4, increasing the SBP by ~16-fold. We experimentally validate its success using 3D-printed diffractive decoders that operate at the terahertz spectrum. This diffractive image decoder can be scaled to operate at visible wavelengths and used to design large SBP displays that are compact, low power, and computationally efficient.

36 MATERIALS SCIENCE↗