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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Water quality changes in acid mine drainage streams in Gangneung, Korea, 10 years after treatment with limestone

To determine the long-term effectiveness of the limestone treatment for acid mine drainage (AMD) in Gangneung, Korea, we investigated the elemental distribution in streams impacted by AMD and compared the results of previous studies before and approximately 10 years after the addition of limestone. Addition of limestone in 1999 leads to a pH increase in 2008, and with the exception of Ca, the elemental concentrations (e.g., Fe, Mn, Mg, Sr, Ni, Zn, S) in the streams decreased. The pH was 2.5–3 before the addition of limestone and remained stable at around 4.5–5 from 2008 to 2011, suggesting the reactivity of the added limestone was diminished and that an alternative approach is needed to increase the pH up to circumneutral range and maintain effective long-term treatment. To identify the processes causing the decrease in the elemental concentrations, we also examined the spatial (approximately 7 km) distribution over three different types of streams affected by the AMD. Lastly, the elemental distribution was mainly controlled by physicochemical processes including redox reactions, dilution on mixing, and co-precipitation/adsorption with Fe (hydr)oxides.

58 GEOSCIENCES↗
DOE OSTI2024

Fractionation of critical metals from authentic acid mine drainage using a multi-bed immobilized amine sorbent setup: A field site study

Here for the first time reported, a flow-through multi-fixed bed immobilized amine/silica sorbent strategy was employed to fractionate purified critical metals from authentic acid mine drainage (AMD). The U.S. Department of Energy’s (DOE) National Energy Technology Laboratory’s (NETL) patent-pending Multi-functional Sorbent Technology (MUST) sorbents were used to recover critical metals from AMD at the Pittsburgh Botanic Garden (Pittsburgh, PA USA). By adjusting the AMD/sorbent ratio, we recovered > 80% of pure adsorbed Mn (by adsorbed metal weight) and >90% pure adsorbed Al at lab-scale. Further optimizing the weight hourly space velocity (WHSV) enhanced the rate of adsorbed Al recovery by over five times, justifying a field site test. After treating >100 L of AMD at the field site, the optimized polyamine/epoxysilane/aminosilane sorbent recovered approximately 0.7 wt% adsorbed Al at > 90% purity. A tangible amount of purified aluminum hydroxide [Al(OH) 3 ] and aluminum sulfate [Al 2 (SO 4 ) 3 ] solids were then recovered after eluting and precipitating the previously adsorbed metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Rapidity distributions of Z = 1 isotopes and the nuclear symmetry energy from Sn+Sn collisions with radioactive beams at 270 MeV/nucleon

The rapidity distributions of hydrogen isotopes emitted from central collisions of neutron-rich 132 Sn+ 124 Sn and neutron-deficient 108 Sn+ 112 Sn systems at 270 MeV/nucleon were investigated at RIKEN-RIBF. The data are compared with antisymmetrized molecular dynamics (AMD) calculations and the rapidity distributions can be reproduced after adjusting the in-medium nucleon-nucleon cross sections. The double ratios between the two reaction systems taken for the relative yields of deuteron to proton (d/p) and triton to proton (t/p) are further examined in the midrapidity domain, where the adjustments in the AMD calculations do not affect much on them. The d/p and t/p double ratios at midrapidity agree well with the ratio of the system neutron numbers and its squared value, respectively, and the rapidity dependence of these double ratios is consistent with a picture of partial mixing of colliding nuclei. By comparing with the AMD model which shows a strong symmetry energy dependence of the t/p double ratio, the experimental result in the midrapidity domain favors the calculation with a symmetry-energy slope parameter around L = 46 MeV rather than L = 108 MeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Puerarin inhibits amyloid β-induced NLRP3 inflammasome activation in retinal pigment epithelial cells via suppressing ROS-dependent oxidative and endoplasmic reticulum stresses

Amyloid β (Aβ) is a critical stimulator that promotes the progression of age-related macular degeneration (AMD). NLRP3 inflammasome activation induced by Aβ is estimated to be responsible for retinal pigment epithelium (RPE) dysfunction in such disease. Puerarin, one of the major active constituents of Kudzu root, has been widely used in the clinical treatment of AMD in China for decades; however, the detailed molecular mechanism remains far from clear. In this study, we investigated the protective effect and underlying mechanism of puerarin against Aβ{sub 1–40}-induced NLRP3 inflammasome activation in LPS-primed ARPE-19 cells. The results showed that Aβ{sub 1–40} induced NLRP3 inflammasome activation mainly via triggering ROS-dependent oxidative stress, particularly lipid peroxidation, and endoplasmic reticulum stress in LPS-primed ARPE-19 cells; however, such effect could be significantly reversed by puerarin in a dose-dependent manner. Furthermore, the effect of puerarin was potentially mediated through activating Nrf2/HO-1 antioxidant signaling pathway and inhibiting Aβ{sub 1–40}-induced phosphorylation of IRE1 and PERK as well as nuclear expression of ATF6α. Therefore, the significance of the current study is to reveal the novel mechanism of puerarin in the prevention of AMD. - Highlights: • Puerarin attenuates Aβ{sub 1-40}-induced NLRP3 inflammasome activation in ARPE-19 cells. • Puerarin attenuates NLRP3 inflammasome activation via suppressing ROS-dependent oxidative and endoplasmic reticulum stresses. • The protective effect of puerarin is mediated through activating Nrf2/HO-1 and inhibiting IRE1/PERK/ATF6 signaling pathways.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Predicting taxonomic and functional structure of microbial communities in acid mine drainage

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Precursor dependent nucleation and growth of ruthenium films during chemical vapor deposition

Nucleation and film growth characteristics are reported during chemical vapor deposition of Ru on SiO{sub 2} using triruthenium dodecacarbonyl [Ru{sub 3}(CO){sub 12}] and ruthenium bis(di-t-butylacetamidinate) dicarbonyl [Ru({sup t}Bu-Me-amd){sub 2}(CO){sub 2}]. Films grown from Ru{sub 3}(CO){sub 12} follow the three dimensional (3D) Volmer–Weber growth mode. In contrast, films grown from Ru({sup t}Bu-Me-amd){sub 2}(CO){sub 2} follow the pseudo-layer-by-layer growth mode with two dimensional wetting layer islands forming before 3D particle growth is observed on the islands. A relationship between free isolated hydroxyl [(Si-OH){sub i}] group density and Ru nucleation density is found for Ru{sub 3}(CO){sub 12} and is associated with (Si-OH){sub i} acting as the reaction sites for activation of Ru{sub 3}(CO){sub 12} and in turn generating an adjustable adatom concentration. Carbon monoxide and ammonia addition to the gas phase during film growth from Ru({sup t}Bu-Me-amd){sub 2}(CO){sub 2} lead to smoother films by inducing surface reconstructions during the 3D phase of pseudo-layer-by-layer growth; these gases also lead to films with lower resistivity and lower crystalline character.

42 ENGINEERING↗
DOE OSTI2023

Performance-Portable GPU Acceleration of the EFIT Tokamak Plasma Equilibrium Reconstruction Code

This paper presents the steps followed to GPU-offload parts of the core solver of EFIT-AI, an equilibrium reconstruction code suitable for tokamak experiments and burning plasmas. For this work, we will focus on the fitting procedure that consists of a Grad–Shafranov (GS) equation inverse solver that calculates equilibrium reconstructions on a grid. We will show profiling results of the original code (CPU-baseline), as well as the directives used to GPU-offload the most time-consuming function, initially to compare OpenACC and OpenMP on NVIDIA and AMD GPUs and later on to assess OpenMP performance portability on NVIDIA, AMD and Intel GPUs. We will make a performance comparison for different spatial grid sizes and show the speedup achieved on NVIDIA A100 (Perlmutter-NERSC), AMD MI250X (Frontier-OLCF) and Intel PVC GPUs (Sunspot-ALCF). Finally, we will draw some conclusions and recommendations to achieve high-performance portability for an equilibrium reconstruction code on the new HPC architectures

GPU↗
DOE OSTI2025

Mojo: MLIR-based Performance-Portable HPC Science Kernels on GPUs for the Python Ecosystem

We explore the performance and portability of the novel Mojo language for scientific computing workloads on GPUs. As the first language based on the LLVM’s Multi-Level Intermediate Representation (MLIR) compiler infrastructure, Mojo aims to close performance and productivity gaps by combining Python’s interoperability and CUDA-like syntax for compile-time portable GPU programming. We target four scientific workloads: a seven-point stencil (memory-bound), BabelStream (memory-bound), miniBUDE (compute-bound), and Hartree–Fock (compute-bound with atomic operations); and compare their performance against vendor baselines on NVIDIA H100 and AMD MI300A GPUs. We show that Mojo’s performance is competitive with CUDA and HIP for memory-bound kernels, whereas gaps exist on AMD GPUs for atomic operations and for fast-math compute-bound kernels on both AMD and NVIDIA GPUs. Although the learning curve and programming requirements are still fairly low-level, Mojo can close significant gaps in the fragmented Python ecosystem in the convergence of scientific computing and AI.

Godoy, William [ORNL] (ORCID:0000000225905178)↗
DOE OSTI2021

NWQ-sim

NWQSim is a quantum circuit simulation environment developed at PNNL. It currently includes two major components: a state-vector simulator (SV-Sim) and a density matrix simulator (DM-Sim) and we may add more components, such as a Clifford simulator, in the future effort. NWQSim has two language interface: C/C++ and Python. It supports Q#/QDK frontend through QIR and QIR-runtime. It supports Qiskit and Cirq frontends through OpenQASM. NWQSim runs on several backends: Intel-CPU, Intel-Xeon-Phi, AMD-CPU, AMD-GPU, NVIDIA-GPU, and IBM-CPU. It supports three modes: (1) single processor, such as a single CPU (with and without AVX2 and AVX512 acceleration), a single NVIDIA GPU or a single AMD GPU; (2) single-node-multi-processors, such as multi-CPUs/Xeon-Phis, multi-NVIDA/AMD GPUs; (3) multi-nodes, such as a CPU cluster, a Xeon-Phi cluster (e.g., ANL Theta, NERSC Cori), an NVIDIA cluster (e.g., ORNL Summit, NERSC Perlmutter).

Li, Ang↗
DOE OSTI2017

Subretinal Pigment Epithelial Deposition of Drusen Components Including Hydroxyapatite in a Primary Cell Culture Model

Extracellular deposits containing hydroxyapatite, lipids, proteins, and trace metals that form between the basal lamina of the RPE and the inner collagenous layer of Bruch’s membrane are hallmarks of early AMD. We examined whether cultured RPE cells could produce extracellular deposits containing all of these molecular components. Retinal pigment epithelium cells isolated from freshly enucleated porcine eyes were cultured on Transwell membranes for up to 6 months. Deposit composition and structure were characterized using light, fluorescence, and electron microscopy; synchrotron x-ray diffraction and x-ray fluorescence; secondary ion mass spectroscopy; and immunohistochemistry. Apparently functional primary RPE cells, when cultured on 10-lm-thick inserts with 0.4-lm-diameter pores, can produce sub-RPE deposits that contain hydroxyapatite, lipids, proteins, and trace elements, without outer segment supplementation, by 12 weeks. In conclusion, the data suggest that sub-RPE deposit formation is initiated, and probably regulated, by the RPE, as well as the loss of permeability of the Bruch’s membrane and choriocapillaris complex associated with age and early AMD. This cell culture model of early AMD lesions provides a novel system for testing new therapeutic interventions against sub-RPE deposit formation, an event occurring well in advance of the onset of vision loss.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Use of Shared Automated Vehicles for First-Mile Last-Mile Service: Micro-Simulation of Rail-Transit Connections in Austin, Texas

Shared fleets of fully automated vehicles (SAVs) coupled with real-time ride-sharing to and from transit stations are of interest to cities and nations in delivering more sustainable transportation systems. By providing first-mile last-mile (FMLM) connections to key transit stations, SAVs can replace walk-to-transit, drive-to-transit, and drive-only trips. Using the SUMO (Simulation of Urban MObility) toolkit, this paper examines mode splits, wait times, and other system features by micro-simulating two fleets of SAVs providing an FMLM ride-sharing service to 10% of central Austin’s trip-makers near five light-rail transit stations. These trips either start or end within two geofenced areas (called automated mobility districts [AMDs]), and travel time and wait time feedbacks affect mode choices. With rail service headways of 15?min, and 15 SAVs serving FMLM connections to and from each AMD, simulations predict that 3.7% of the person-trip-making will shift from driving alone to transit use in a 3?mi?×?6?mi central Austin area. During a 3-h morning peak, 30 SAVs serve about 10 person-trips each (to or from the stations), with 3.4?min average wait time for SAVs, and an average vehicle occupancy of 0.74 persons (per SAV mile-traveled), as a result of empty SAV driving between riders. Sensitivity analysis of transit headways (from 5 to 20?min) and fleet sizes (from 5 to 20 vehicles in each AMD) shows an increase in FMLM mode share with more frequent transit service and larger fleet size, but total travel time served as the biggest determinant in trip-makers’ mode share.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Performance Analysis of PIConGPU: Particle-in-Cell on GPUs using NVIDIA’s NSight Systems and NSight Compute

PIConGPU, Particle In Cell on GPUs, is an open source simulations framework for plasma and laser-plasma physics used to develop advanced particle accelerators for radiation therapy of cancer, high energy physics and photon science. While PIConGPU has been optimized for at least 5 years to run well on NVIDIA GPU-based clusters, there has been limited exploration by the development team of potential scalability bottlenecks using recently updated and new tools including NVIDIA’s NVProf tool and the brand-new NVIDIA NSight Suite (Systems and Compute) tools. PIConGPU is a highly optimized application that runs production jobs at scale on a system Oak Ridge Leadership Facility’s (OLCF) Summit supercomputer (using the full machine at 4600 nodes; at 98% of GPU utilization on all ~28000 NVIDIA Volta GPUs). PIConGPU has been selected as one of the the eight applications for OLCF’s coveted Center for Accelerated Application Readiness (CAAR) program aimed at the facility’s Frontier supercomputer (OLCF’s first exascale system to launch in 2021), to partner with our vendors (primary vendors: AMD and Cray/HPE) ensuring that Frontier will be able to perform large-scale science when it opens to users in 2022. To this effect, performance engineers on the PIConGPU team wanted to dive deep into the application to understand at the finest granularity, which portions of the code could be further optimized to exploit the hardware on Summit at it’s maximum potential and also to elucidate which key kernels should be tracked and optimized for the CAAR effort to port this code to Frontier. Any bottlenecks that are observed via performance profiling on Summit are likely to also impact scalability on the Frontier-dev system and the Frontier Early Access (EA) system. Additionally, the engineers wanted to take a closer look at the newest NVIDIA profiling tools which allows us to identify the most useful features on these tools and will provide an opportunity to compare it to new AMD and Cray’s performance analysis tool releases and provide feedback to our vendor partners on what features are most important and mission critical for CAAR efforts. The primary goal of this report is to focus on the evaluation of PIConGPU’s most time-intensive kernels using NVProf and NSight Suite. Three kernels, Current Deposition (also known as Compute Current), Particle Push (Move and Mark), and Shift Particles are known to be some of the most time-consuming kernels in PIConGPU. The Current xi Deposition kernel and Particle Push kernel both set up the particle attributes for running any physics simulation with PIConGPU, so it is crucial to improve the performance of these two kernels. In this report, we measure single GPU metrics for the three kernels, offer high level takeaways from the conducted analysis, and compare the profiling data from NSight Compute to that of NVProf. This analysis was performed using a grid size of 240 x 272 x 224, and 10 time steps with the Mid-November Figure of Merit (FOM) run setup. The Traveling Wave Electron Acceleration (TWEAC) science case used in this run is a representative science case for PIConGPU. This execution can also be used for baseline analysis on AMD MI50/ MI60 systems. As of the time of writing, the PIConGPU application has limited use for features of NSight Systems, so this report will mainly focus on insights garnered from NSight Compute. For this analysis, we run the “full” metric set available in NSight Compute version 2020.1.2 and use NSight Systems version 2020.3.1 to generate the application timeline.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

The Automated Mobility District Implementation Catalog, 2nd Edition: Safe and Efficient Automated Vehicle Fleet Operations for Public Mobility

This second volume of the Automated Mobility District (AMD) Implementation Catalog series has been prepared in three parts to assist readers in their review and understanding of the technical information herein. The material may be more easily ingested if each of the three parts is read and then contemplated for its ramifications to the specific interest of the reader before continuing to the next part. Further, each part has been prepared with the intent that it could be read independently from the others. Part 1 is Progress of Automated Vehicle R&D for Deployments in Passenger Service; Part 2 is 10 Early Deployment Sites as Prototypes of AMD Implementation; Part 3 is Five Cardinal Principles for AMD Implementation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

ExaSGD: 2022 Kernel Thrust Activities

The Kernel Thrust milestone ADSE22-407 covers the development of device-capable optimization algorithms and solvers technologies required by the ExaSGD project’s software stack in order to solve security-constrained alternating current optimal power flow (SC-ACOPF) problems on emerging exascale architectures. To this extent, in FY22 the main objective of the Kernel Thrust was (i) provide sparse optimization solver that runs efficiently on hardware accelerator devices (i.e., NVIDIA and AMD GPUs) to perform intra-node computations, (ii) strengthen the reliability and increase the performance of the mixed-dense sparse (MDS) solver of HiOp for deployment on the FY22 target architectures, Summit and Crusher, and (iii) increase performance by improving the mathematical algorithm and refining the parallel MPI-based implementation of the coarse-grain parallel solver HiOp-PriDec for capabilities deployment on the FY22 target architectures, Summit and Crusher. This document presents the developments and contributions done by the Kernels Thrust Team in FY22 toward completion of the above-mentioned objectives. These contributions progressed along four main development (sub)thrusts: (1) Design and implementation of a sparse optimization solver for use on hardware accelerators; (2) Improvement of the mathematical algorithm and of the parallel implementation of HiOp-PriDec to ensure readiness and efficient coarse-grain parallelism for FY23 target exascale machine; and (3) Support Software and Application Development Thrusts of the exaSGD project in their deployment of the project’s software stack on AMD- and NVIDIA-based architectures. The development of the sparse optimization solver (thrust 1 above) was new in FY22 and resulted in a new sparse solver in HiOp (available as of version 0.6). The second development thrust was a continuation of the efforts from FY21 and improved the mathematical algorithm and the communication strategy of the HiOp-PriDec solver. The last developement thrust is a large collaborative effort. Namely, the project’s teams from multiple labs (LLNL, PNNL, ORNL, and NREL) performed large-scale demonstration of the ExaSGD software stack, namely the optimization solvers of HiOp interfaced with the modeling front-end ExaGO and the stochastic sampler PowerScenarios. These demonstration efforts solved large-scale instances of the SC-ACOPF challenge problem of medium network sizes (10, 000-bus system) and large number of contingencies on Summit (NVIDIA accelerators) and Crusher (AMD accelerators) systems at ORNL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Identifying Critical Mineral Binding Mechanisms and Distribution in Acid Mine Drainage Treatment Solids to Inform Targeted Recovery Methods

In this study, micro-X-ray Fluorescence and micro/bulk X-ray Adsorption Near Edge Spectroscopy were collected at Stanford Synchrotron Radiation Lightsource and the Advanced Photon Source to: (1) gain a detailed characterization of critical minerals in Fe/Mn (hydr)oxide host phases; and (2) investigate the Co/Ni coordination and redox speciation associated with Fe/Mn (hydr)oxides phases in AMD solids with diverse composition (e.g., Al-rich, Mn-rich, Al/Mn/Fe-rich). Preliminary results show co-location of Co/Ni within Mn-rich hotspots, while Fe-rich hotspots were associated with heavy REEs. In Al-rich solids, Mn speciation was mostly comprised of Mn+3/+4 oxides, while the Mn-rich solids contain predominately Mn+4. These results suggest the AMD matrix plays an important role in how Co/Ni are coordinated, which aids in evaluating the efficacy to utilize AMD solids as a resource, and informs other novel sorbent and recovery technologies.

Hoffman, Colleen↗
DOE OSTI2024

Performance Results on CPU/GPU Exascale Architectures for OMEGA: The Ocean Model for E3SM Global Applications

The US Department of Energy (DOE) conducts climate simulations on some of the world’s largest supercomputers. These exascale machines use heterogeneous architectures with both CPUs and GPUs, and scientific codes must adapt to make full use of this computing power. Los Alamos National Lab is developing Omega: The Ocean Model for E3SM Global Applications, which is specifically designed for modern exascale computers. It uses external libraries that have been optimized for a variety of architectures to run on different supercomputers. Omega is an unstructured-mesh ocean model based on TRiSK numerical methods. It will be the new ocean component of the DOE’s Energy Exascale Earth System Model (E3SM). The algorithms in Omega follow those of the current ocean component, MPAS-Ocean, but it will be written in C++ rather than Fortran to take advantage of the Kokkos performance portability library. Omega spatial operators are written as Kokkos kernels to run efficiently on both CPUs and GPUs. Work on Omega began in 2023 with a new C++ framework for unstructured mesh partitioning, halo exchanges, parallel IO, and Kokkos interfaces. The current version, Omega-0, is being developed to solve the shallow water equations and at present includes all of the tendency terms but not time stepping. Here we share the results of Omega-0 verification and performance testing. Verification includes unit tests implemented with CTest as well as convergence tests in Polaris, an in-house python package with a large suite of test problems. Performance tests compare simulations conducted on CPUs versus GPUs and across different architectures: tests are run on Frontier, which has AMD “Optimized 3rd Gen EPYC” CPUs and AMD MI250X GPUs, as well as Perlmutter, which is composed of AMD EPYC 7763 CPUs and NVIDIA A100 GPUs.

58 GEOSCIENCES↗