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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 703 records · Page 39

Large-Scale NASA Science Applications on the Columbia Supercluster

Columbia, NASA's newest 61 teraflops supercomputer that became operational late last year, is a highly integrated Altix cluster of 10,240 processors, and was named to honor the crew of the Space Shuttle lost in early 2003. Constructed in just four months, Columbia increased NASA's computing capability ten-fold, and revitalized the Agency's high-end computing efforts. Significant cutting-edge science and engineering simulations in the areas of space and Earth sciences, as well as aeronautics and space operations, are already occurring on this largest operational Linux supercomputer, demonstrating its capacity and capability to accelerate NASA's space exploration vision. The presentation will describe how an integrated environment consisting not only of next-generation systems, but also modeling and simulation, high-speed networking, parallel performance optimization, and advanced data analysis and visualization, is being used to reduce design cycle time, accelerate scientific discovery, conduct parametric analysis of multiple scenarios, and enhance safety during the life cycle of NASA missions. The talk will conclude by discussing how NAS partnered with various NASA centers, other government agencies, computer industry, and academia, to create a national resource in large-scale modeling and simulation.

Brooks, Walter↗

A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining

Transformers are considered one of the most important deep learning models since 2018, in part because it establishes state-of-the-art (SOTA) records and could potentially replace existing Deep Neural Networks (DNNs). Despite the remarkable triumphs, the prolonged turnaround time of Transformer models is a widely recognized roadblock. The variety of sequence lengths imposes additional computing overhead where inputs need to be zero-padded to the maximum sentence length in the batch to accommodate the parallel computing platforms. This paper targets the field-programmable gate array (FPGA) and proposes a coherent sequence length adaptive algorithm–hardware co-design for Transformer acceleration. Particularly, we develop a hardware-friendly sparse attention operator and a length-aware hardware resource scheduling algorithm. The proposed sparse attention operator brings the complexity of attention-based models down to linear complexity and alleviates the off-chip memory traffic. The proposed length-aware resource hardware scheduling algorithm dynamically allocates the hardware resources to fill up the pipeline slots and eliminates bubbles for NLP tasks. Experiments show that our design has very small accuracy loss and has 80.2 × and 2.6 × speedup compared to CPU and GPU implementation, and 4 × higher energy efficiency than state-of-the-art GPU accelerator optimized via CUBLAS GEMM.

Peng, Hongwu↗

High-gradient performance of a prototype accelerator cavity for a 3 GeV proton radiography booster

This paper reports the design, fabrication, and results of the high-gradient conditioning and testing for a two-cell, π -mode, standing wave normal-conducting prototype booster cavity for the proposed 3 GeV proton linac upgrade at Los Alamos Neutron Science Center. Increasing the energy of proton beam from the existing 800 MeV to 3 GeV will improve resolution of the proton radiography by up to 10 times. The proposed energy boost can be achieved with a compact normal-conducting high-gradient radio-frequency (rf) linac section. The C-band section of the booster linac was designed with optimized-shaped copper accelerator cavities with distributed rf coupling. A short two-cell test prototype structure was designed for the frequency of 5.712 GHz, fabricated, and tested at the C-band Engineering Research Test Facility in New Mexico (CERF-NM) at Los Alamos National Laboratory. The maximum klystron power coupled into the test structure was 8.3 MW with 1 μ s pulse length and 100 Hz repetition rate. The breakdown probabilities were recorded as functions of the accelerating gradient and peak surface fields. Operation of the test cavity at accelerating gradients of up to 100 MV / m was demonstrated. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Dynamics near equilibrium for intense beams in a nonlinear integrable focusing channel

Accelerator storage ring designs based on nonlinear integrable Hamiltonian systems provide a novel test-bed for studying the interplay between nonlinear dynamics and space charge at high intensity. In this work, the structure of beam Vlasov equilibria is explored for a constant focusing channel based on the nonlinear focusing potential of the Integrable Optics Test Accelerator. Finally, the dynamics of the single-particle orbits is explored in the combined space charge and external focusing fields as a function of beam current, and the self-consistent relaxation of a mismatched beam to equilibrium is characterized.

43 PARTICLE ACCELERATORS↗

Microgravity acceleration measurement and environment characterization science (17-IML-1)

The Space Acceleration Measurement System (SAMS) is a general purpose instrumentation system designed to measure the accelerations onboard the Shuttle Orbiter and Shuttle/Spacelab vehicles. These measurements are used to support microgravity experiments and investigation into the microgravity environment of the vehicle. Acceleration measurements can be made at locations remote from the SAMS main instrumentation unit by the use of up to three remote triaxial sensor heads. The prime objective for SAMS on the International Microgravity Lab (IML-1) mission will be to measure the accelerations experienced by the Fluid Experiment System (FES). The SAMS acceleration measurements for FES will be complemented by low level, low frequency acceleration measurements made by the Orbital Acceleration Research Experiment (OARE) installed on the shuttle. Secondary objectives for SAMS will be to measure accelerations at several specific locations to enable the acceleration transfer function of the Spacelab module to be analyzed. This analysis effort will be in conjunction with similar measurements analyses on other Spacelab missions.

Source record↗

Environmental Protection Coating System for Refractory Metal Alloys (EPCS for RMAs)

As part of ARPA-E’s Ultra High Temperature Impervious Materials Advancing Turbine Efficiency (UITIMATE) program, this project aims to develop an environmental protection coating system (EPCS) for refractory metal alloys (RMAs) – which will provide radical improvement in long term protection for ultra-high temperature refractory metal components in harsh gas-turbine environments. The drive for higher fuel efficiency and higher core power of gas turbines used in electric power generation and in aircraft propulsion requires higher peak operation temperatures. The temperature capability of state-of-the-art materials cannot meet the new requirements. Refractory metal alloys have desirable capabilities for achieving the required peak temperatures, but most of them are subject to oxidation in the gas turbine environment. Thus, there is a strong need to develop novel environmental protective coatings that enable the refractory metals to operate in an ultra-high temperature engine environment. This project is composed of four major technical innovations that can provide a potentially transformational solution in providing environmental protection for refractory metal alloys over a wide range of temperature. 1) Multi-layer self-healing environmental barrier coating (EBC) that provides protection against combustion gas environment. 2) Oxidation resistant diffusion barrier (DB) on the alloy surface to enhance coating stability. 3) Synergistic integration of the multi-layer self-healing EBC with the diffusion barrier to extend coating life. 4) Guidance of physics-based modeling to accelerate coating development and optimization. Our team has successfully developed a multi-layer self-healing environmental protection coating system (EPCS) that can provide oxidation protection for commercially available molybdenum based refractory metal alloys over a wide temperature range of up to 1600 °C for fuel-efficient gas turbine applications. The team also developed a multi-layer high temperature coating design tool to accelerate coating development and optimization based on physics-based modeling. The team also engaged RTX business unite, notable Pratt and Whitney, for future commercialization of this technology. The successful completion of this Phase I effort led to the selection of performing Phase II of the program. In Phase II, the team plans to apply the EPCS in the protection of a newly discovered molybdenum-based metal alloy which has the potential of superior high temperature properties to the commercial products. Th coating will be evaluated under test conditions and environment that mimic gas turbine operation.

36 MATERIALS SCIENCE↗

FASDA: An FPGA-Aided, Scalable and Distributed Accelerator for Range-Limited Molecular Dynamics

Conducting long-term simulations of small molecules using Molecular Dynamics (MD) is crucial in drug design. However, traditional methods to accelerate the process including ASICs or GPUs, have limitations. ASICs are difficult to access, while publicly accessible GPU packages for MD have issues with more GPUs when processing small molecules, causing decreased performance. Conversely, FPGAs are renowned for their scalability and have been commonly used as accelerators for various applications, making them suitable for the task. Moreover, with the availability of FPGAs in the cloud, pharmaceutical developers can now access FPGA devices. The only missing piece is a design deployed for MD acceleration. Therefore, we present FASDA, the first FPGA-based MD accelerator available for community development. FASDA is designed to evaluate range-limited MD, which is the most resource-intensive and computationally demanding component in MD. It outperforms the state of-the-art GPU solution by 4.67x, significantly reducing the time for MD in drug design.

Wu, Chunshu↗

Deep learning workflow for the inverse design of molecules with specific optoelectronic properties

The inverse design of novel molecules with a desirable optoelectronic property requires consideration of the vast chemical spaces associated with varying chemical composition and molecular size. First principles-based property predictions have become increasingly helpful for assisting the selection of promising candidate chemical species for subsequent experimental validation. However, a brute-force computational screening of the entire chemical space is decidedly impossible. To alleviate the computational burden and accelerate rational molecular design, we here present an iterative deep learning workflow that combines (i) the density-functional tight-binding method for dynamic generation of property training data, (ii) a graph convolutional neural network surrogate model for rapid and reliable predictions of chemical and physical properties, and (iii) a masked language model. As proof of principle, we employ our workflow in the iterative generation of novel molecules with a target energy gap between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO).

97 MATHEMATICS AND COMPUTING↗

Future Battery Material Demand Analysis Based on U.S. Department of Energy R&D Targets

The U.S. Department of Energy’s Vehicle Technologies Office (VTO) supports research, development, and deployment of efficient, sustainable transportation technologies that will improve energy efficiency and fuel economy, and enable America to use less petroleum. To accelerate the development and adoption of new technologies, VTO has developed specific targets for a wide range of powertrain components, including the energy storage system. In this study, we use Autonomie, Argonne National Laboratory’s (Argonne’s) vehicle system simulation tool to evaluate future energy storage requirements (power, energy, etc.) for different vehicle classes, powertrains, component technologies and timeframes. BatPac, Argonne’s tool dedicated to energy storage pack design and costs, is then used to quantify the materials required for each pack. Market penetrations are then used to estimate the overall material demand worldwide and in the United States, with or without recycling. The results demonstrate that the positive impact of VTO research and development will lead to significant reduction in material compared to business-as-usual due to new anode and cathode designs, along with acceleration in battery cell chemistry penetrations. In terms of material demands, it is observed that lithium demand reaches about 80,000 tons (by a factor of 42–45), nickel demand reaches about 500,000 tons (by a factor of 47–56), manganese demand reaches about 30,000–50,000 tons (by a factor of 20–34), and cobalt demand reaches about 30,000 tons (by a factor of 13–28) in the future by 2050. The individual material demand per unit energy, however, decreases significantly in the future due to advances in VTO research and development activities. The increase in battery material demands is mostly driven by increased electrified vehicle fleet penetration in the markets.

25 ENERGY STORAGE↗

Compact Coaxial HOM Damper for SRF Cavities

SRF technology enable particle accelerators operate with greater average beam currents and higher duty cycles. In these regimes parasitic excitation of the cavity HOM spectrum become the limiting factor due to extra RF losses and instabilities appearing in the beam. We discuss the limitations of HOMs for large accelerator projects as the Fermilab MI upgrade and the proposed future circular and linear colliders EIC and ILC. A new compact HOM damper concept is suggested providing required HOM suppression. The idea is based on an oversized coaxial line with radial sections, which is directly connected to the axial region of the SRF cavity. Such radially sectioned coaxial works as a filter for the operating mode, while being transparent for the HOMs. Implementations of this design for the accelerator and crab cavities developed for the MI and EIC machines, respectively, are discussed.

Lunin, A. [Fermilab]↗

Progress on the Electron Gun Design for a McMillan Electron Lens in the Fermilab Integrable Optics Test Accelerator (IOTA)

This paper covers the progress made so far in designing the first McMillan electron lens for the Fermilab IOTA ring. The novel design allows for an increase in tune spread without limiting the dynamic aperture due to its integrability. Shown are simulations for an electron gun design to generate the specific required current density distribution for the nonlinear integrable system in IOTA.

43 PARTICLE ACCELERATORS↗

The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques. JARVIS is motivated by the Materials Genome Initiative (MGI) principles of developing open-access databases and tools to reduce the cost and development time of materials discovery, optimization, and deployment. The major features of JARVIS are: JARVIS-DFT, JARVIS-FF, JARVIS-ML, and JARVIS-tools. To date, JARVIS consists of ≈40,000 materials and ≈1 million calculated properties in JARVIS-DFT, ≈500 materials and ≈110 force-fields in JARVIS-FF, and ≈25 ML models for material-property predictions in JARVIS-ML, all of which are continuously expanding. JARVIS-tools provides scripts and workflows for running and analyzing various simulations. We compare our computational data to experiments or high-fidelity computational methods wherever applicable to evaluate error/uncertainty in predictions. In addition to the existing workflows, the infrastructure can support a wide variety of other technologically important applications as part of the data-driven materials design paradigm. The JARVIS datasets and tools are publicly available at the website: https://jarvis.nist.gov .

36 MATERIALS SCIENCE↗

Design of the Fermilab Pre-Series Cold Mass for the HL-LHC Accelerator Upgrade Project

Here as part of the U.S. contribution to the HL-LHC Accelerator Upgrade Project (AUP), Fermilab is designing and building cold masses suitable for use in the LHC interaction regions. The cold mass provides a vacuum-tight helium enclosure for the magnets. Two magnets are aligned both axially and in cross section at Fermilab based on survey and warm magnetic measurements. Bus work and instrumentation is added. A welded stainless steel vacuum-tight shell surrounds the two magnets, and the structure is prepared for insertion into the cryostat. This paper summarizes the design of the cold mass including alignment, bus work, weld details, and instrumentation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

CEAZ: Accelerating Parallel I/O Via Hardware-Algorithm Co-Designed Adaptive Lossy Compression

As supercomputers continue to grow to exa-scale, the amount of data that needs to be saved or transmitted is exploding. To this end, many previous works have studied using error-bounded lossy compressors to reduce the data size and improve the I/O performance. However, little work has been done for effectively offloading lossy compression onto FPGA-based SmartNICs to reduce the compression overhead. In this paper, we propose a hardware-algorithm co-design of efficient and adaptive lossy compressor for scientific data on FPGAs (called CEAZ) to accelerate parallel I/O. Our contribution is fourfold: (1) We propose an efficient Huffman coding approach that can adaptively update Huffman codewords online based on codewords generated offline (from a variety of representative scientific datasets). (2) We derive a theoretical analysis to support a precise control of compression ratio under an error-bounded compression mode, enabling accurate offline Huffman codewords generation. This also help us create a fixed-ratio compression mode for consistent throughput. (3) We develop an efficient compression pipeline by adopting cuSZ’s dual-quantization algorithm to our hardware use case. (4) We evaluate CEAC on five real-world datasets with both a single FPGA board and 256 nodes from Bridges2 supercomputer. Experiments show that CEAZ outperforms the second-best FPGA-based lossy compressor by 2× of throughput and 9.6× of compression ratio. It also improves MPI_File_write and MPI_Gather throughputs by up to 32.7× and 31.4×, respectively.

Zhang, Chengming↗

ORBUMP Pulsed Dipole Magnet Design for Fermilab Booster

Fermilab initiated the accelerator magnet system upgrade project PIP-II for future neutrino experiments. Old ORBUMP pulsed dipoles should be replaced with new stronger magnets occupying the same space as old ones. Four of these magnets connected in series form dogleg type of proton beam orbit. The magnet field and 19 kA current pulse length are close to 1 ms. Old magnet cores were based on a ferrite material. For new magnets, a magnet gap field is above 0.4 T, which completely saturates ferrite material. So, for the magnet core, 0.127 mm thick laminations of low carbon steel with inorganic coating, as the magnet were placed in a vacuum box. There were investigated transient magnet parameters including skin effect in the iron core and in the single-turn copper coil. The integrated field homogeneity was improved by the copper coil shimming. Simulated by OPERA3D power losses were used for the thermal analysis by ANSYS code. The magnet performance is strongly coupled with the power source. The dynamic magnet inductance and resistance were included in the pulsed power source design. Finally, the paper presented the ORBUMP magnet system design.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Beam Dynamics Study in a Dual Energy Storage Ring for Ion Beam Cooling

A dual energy storage ring designed for beam cooling consists of two closed rings with significantly different energies: the cooling and damping rings. These two rings are connected by an energy recovering superconducting RF structure that provides the necessary energy difference. In our design, the RF acceleration has a main linac and harmonic cavities both running at crest that at first accelerates the beam from low energy E_{L} to high energy E_{H} and then decelerates the beam from E_{H} to E_{L} in the next pass. The purpose of the harmonic cavities is to extend the bunch length in a dual energy storage ring as such a longer bunch length may be very useful in a cooling application. Besides these cavities, a bunching cavity running on zero-crossing phase is used outside of the common beamline to provide the necessary longitudinal focusing for the system. In this paper, we present a preliminary lattice design along with the fundamental beam dynamics study in such a dual energy storage ring.

Dhital, B.↗

Performance Testing of a Moving Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends to Generate White Hydrogen

The objective of this DOE-funded project by the Electric Power Research Institute, Inc. (EPRI), Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), is to qualify coal, biomass, and plastic waste blends based on performance testing of selected pellet recipes in a pilot-scale updraft moving-bed gasifier. The testing provides relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of the waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are a focus. The gasifier is Hamilton Mauer International, Inc. (HMI)’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips. However, mixtures of these fuels with plastic wastes had not yet been prepared and gasified together. The feedstocks were prepared by California Pellet Mill (CPM) under contract to HMI. The technical tasks for this research project included: • Feed Procurement and Preparation: Nine different feedstocks were prepared from varying compositions of PRB coal, corn stover biomass, and car fluff waste plastics. Fuel pellets were produced by California Pellet Mill (CPM) and shipped to Sotacarbo’s test facility in Italy. • Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different tests that were run, instrumentation used, extractive samples taken, and relevant figures of merit. • Gasifier Testing: Tests were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstocks generated from varying mixtures of coal, biomass, and plastic wastes. The testing provides information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design. This task will also included work to reassemble the gasifier at Sotacarbo and perform a baseline 100% coal run. • Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results was reported. The results can be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends. The tri-fuel pelletizing conducted at CPM and gasification testing results from Sotacarbo’s 30mm up draft moving bed gasifier are significant. Providing data for an established gasifier to help accelerate its updated design to be able to accommodate feedstocks composed of coal, biomass, and plastic waste. This should ultimately lead to development and commercialization of a lower cost, white hydrogen generation system.

01 COAL, LIGNITE, AND PEAT↗