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DOE OSTI2025

Voltage cycling as a dynamic operation mode for high temperature electrolysis solid oxide cells

Solid Oxide Electrolysis Cells (SOECs) have emerged as a promising technology for the efficient production of H2 via high-temperature electrolysis. However, power input from dynamic energy sources remains a significant challenge for their long-term stability. It is important to analyze the tolerance of cells under dynamic operation conditions. This study focuses on evaluating the impact of voltage cycling on the performance and durability of electrode-supported SOECs. We explore the operational limits and degradation mechanisms of SOECs subjected to various voltage conditions and find that the cells have high tolerance for dynamic voltage. Voltage cycling between 1.3 V and 1.5 V for 9000 cycles does not damage the cell. Conversely, cycling to higher voltages (≥1.7 V) results in accelerated degradation. Advanced characterization is used to screen for various degradation modes post operation. Within the oxygen electrode, XRD and STEM EDS find compositional and phase evolution in all voltage cycled samples including increased decomposition of the air electrode resulting in cation migration. Microstructural analysis of the fuel electrode from nano-CT data shows minimal change throughout the sample set and no evidence of Ni migration, indicating the fuel electrode is stable and not impacted by cycling to higher voltages within the timeframe studied.

Zhu, Zhikuan↗

NASA NTRS1995

The large discretization step method for time-dependent partial differential equations

A new method for the acceleration of linear and nonlinear time dependent calculations is presented. It is based on the Large Discretization Step (LDS) approximation, defined in this work, which employs an extended system of low accuracy schemes to approximate a high accuracy discrete approximation to a time dependent differential operator. Error bounds on such approximations are derived. These approximations are efficiently implemented in the LDS methods for linear and nonlinear hyperbolic equations, presented here. In these algorithms the high and low accuracy schemes are interpreted as the same discretization of a time dependent operator on fine and coarse grids, respectively. Thus, a system of correction terms and corresponding equations are derived and solved on the coarse grid to yield the fine grid accuracy. These terms are initialized by visiting the fine grid once in many coarse grid time steps. The resulting methods are very general, simple to implement and may be used to accelerate many existing time marching schemes.

Haras, Zigo↗

NASA NTRSDate not supplied

A Multi-Architecture Approach for Implicit Computational Fluid Dynamics on Unstructured Grids

High-performance computing (HPC) architectures are trending toward manycore paradigms such as graphics processing units (GPUs). Approximately half of the top 100 publicly disclosed supercomputers in the world utilize GPU accelerators for performance. This is in contrast to a decade ago, where there were only a few such machines in the top 100. It is not currently possible to compile and run legacy central processing unit (CPU) software efficiently on GPUs without significant refactoring. Though a number of frameworks offering performance portability exist, none offer a standardized specification that is supported by all major hardware vendors. Additionally, experiences show that obtaining a high percentage of peak performance often requires architecture-specific code. This work details a pragmatic multi-architecture computational fluid dynamics library focused on aerospace problems across the speed range from low subsonic to hypersonic flows involving thermochemical nonequilibrium. A thin abstraction layer above NVIDIA CUDA C++ is utilized, which enables primarily single-source software currently capable of running efficiently on multicore CPUs, NVIDIA GPUs, AMD GPUs, and Intel GPUs. Results on various problems of interest across the speed range are presented and performance is compared between various architectures.

GPU↗

NASA NTRSDate not supplied

A Multi-Architecture Approach for Implicit Computational Fluid Dynamics on Unstructured Grids

GPU↗

DOE OSTI2015

SU-E-T-543: Measurement of Neutron Activation From Different High Energy Varian Linear Accelerators

Purpose: Linear accelerators producing photons above 10 MeV may induce photonuclear reactions in high Z components of the accelerator. These liberated neutrons can then activate the structural components of the accelerator and other materials in the beam path through neutron capture reactions. The induced activity within the accelerator may contribute to additional dose to both patients and personnel. This project seeks to determine the total activity and activity per activated isotope following irradiation in different Varian accelerators at energies above 10 MeV. Methods: A Varian 21IX accelerator was used to irradiate a 30 cm × 30 cm × 20 cm solid water phantom with 15 MV x-rays. The phantom was placed at an SSD of 100 cm and at the center of a 20 cm × 20 cm field. Activation induced gamma spectra were acquired over a 5 minute interval after 1 and 15 minutes from completion of the irradiation. All measurements were made using a CANBERRA Falcon 5000 Portable HPGe detector. The majority of measurements were made in scattering geometry with the detector situated at 90° to the incident beam, 30 cm from the side of the phantom and approximately 10 cm from the top. A 5 minute background count was acquired and automatically subtracted from all subsequent measurements. Photon spectra were acquired for both open and MLC fields. Results: Based on spectral signatures, nuclides have been identified and their activities calculated for both open and MLC fields. Preliminary analyses suggest that activities from the activation products in the microcurie range. Conclusion: Activation isotopes have been identified and their relative activities determined. These activities are only gross estimates since efficiencies have not been determined for this source-detector geometry. Current efforts are focused on accurate determination of detector efficiencies using Monte Carlo calculations.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2014

High Performance Computing Data Center [Fact Sheet]

The high performance computing (HPC) data center in the Energy Systems Integration Facility (ESIF) is designed to be one of the most energy efficient data centers in the world, featuring warm-water liquid cooling and waste heat capture and re-use. Its HPC capabilities support the breadth of research at NREL, leading to increased efficiency and lower costs for important technologies including solar photovoltaics, wind energy, energy storage, electric vehicles, and the large-scale integration of renewables with the grid. With its state-of-the-art computational modeling and predictive simulation capabilities, the HPC data center will reduce the risks and uncertainty that are often barriers to industry adopting new and innovative technologies, thereby accelerating the transformation of our nation’s energy system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Electronic Bottleneck Suppression in Next‐Generation Networks with Integrated Photonic Digital‐to‐Analog Converters

Digital‐to‐analog converters (DAC) are indispensable functional units in signal processing instrumentation and wide‐band telecommunication links for both civil and military applications. As photonic systems are capable of high data throughput and low latency, an increasingly found system limitation stems from the required domain crossing such as digital to analog and electronic to optical. A photonic DAC implementation, in contrast, enables a seamless signal conversion with respect to both energy efficiency and short signal delay, often requiring bulky discrete optical components and electric–optic transformation, hence introducing inefficiencies. Herein, a novel coherent parallel photonic DAC concept along with a 4‐bit experimental prototype capable of performing this DAC without optic–electric–optic domain crossing is introduced. This new paradigm guarantees a linear intensity weighting among bits when operating at high sampling rates (50 GHz), featuring an exceptional sampling efficiency (> 100 GS ) and small footprint (≈1 mm 2 ) in an 8‐bit implementation. Importantly, this photonic DAC enables seamless interfaces of next‐generation data processing hardware with high relevance in data centers, task‐specific compute accelerators such as neuromorphic engines, and network edge processing applications.

Meng, Jiawei↗

DOE OSTI2026

Multi-task Parallelism for Robust Pre-training of Graph Foundation Models on Multi-source, Multi-fidelity Atomistic Modeling Data

Graph foundation models using graph neural networks promise sustainable, efficient atomistic modeling. To tackle challenges of processing multi-source, multi-fidelity data during pre-training, recent studies employ multi-task learning, in which shared message passing layers initially process input atomistic structures regardless of source, then route them to multiple decoding heads that predict data-specific outputs. This approach stabilizes pre-training and enhances a model’s transferability to unexplored chemical regions. Preliminary results on approximately four million structures are encouraging, yet questions remain about generalizability to larger, more diverse datasets and scalability on supercomputers. We propose a multi-task parallelism method that distributes each head across computing resources with GPU acceleration. Implemented in the open-source HydraGNN architecture, our method was trained on over 24 million structures from five datasets and tested on the Perlmutter, Aurora, and Frontier supercomputers, demonstrating efficient scaling on all three highly heterogeneous super-computing architectures.

Lupo Pasini, Massimiliano [ORNL] (ORCID:0000000249↗

DOE OSTI2019

Overview: Additive Manufacturing Enabled Accelerated Design of Ni-based Alloys for Improved Fatigue Life

An in-depth overview on an emerging area of the additive-manufacturing-enabled, accelerated design of Ni-based alloys for improved high-cycle and very-high-cycle fatigue life is presented. Existing literature on the subject is critically reviewed, and key knowledge gaps are identified. Here, an efficient life-cycle approach, integrating the model-make-measure-verify strategy in the design of these alloys is introduced and discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Balancing DNA repair to prevent ageing and cancer

DNA damage is a constant stressor to the cell. Persistent damage to the DNA over time results in an increased risk of mutation and an accumulation of mutations with age. Loss of efficient DNA damage repair can lead to accelerated ageing phenotypes or an increased cancer risk, and the trade-off between cancer susceptibility and longevity is often driven by the cell's response to DNA damage. High levels of mutations in DNA repair mutants often leads to excessive cell death and stem cell exhaustion which may promote premature ageing. Stem cells themselves have distinct characteristics that enable them to retain low mutation rates. However, when mutations do arise, stem cell clonal expansion can also contribute to age-related tissue dysfunction as well as heightened cancer risk. In this review, we will highlight increasing DNA damage and mutation accumulation as hallmarks common to both ageing and cancer. We will propose that anti-ageing interventions might be cancer preventative and discuss the mechanisms through which they may act.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Single-Objective Airy Light-Sheet Imaging

Despite its massive potential, standard light-sheet imaging (LSI) faces key challenges, such as the incompatibility with common sample mounting techniques and low-resolution imaging. Single-objective LSI attempts to address these issues but often suffers from limited fields-of-view and throughput rates, or requires multiple optics that increase costs, alignment complexity, and losses. To overcome these challenges of standard single-objective LSI, we introduce single-objective Airy light-sheet imaging (SoALSI). SoALSI leverages the extraordinary self-acceleration properties of the Airy beam, achieving 5× higher imaging rates and enhanced imaging efficiency than standard single-objective LSI. Here, we demonstrate SoALSI’s versatility through rigorous contrast and resolution characterizations and by high-resolution imaging of diverse biological specimens, including malaria parasite-infected red blood cells and plant root tissue. SoALSI seamlessly integrates with any standard inverted microscope frame, enabling broader accessibility for the bioimaging community to explore biological processes in a wide range of specimens with enhanced resolution and imaging contrast.

airy beam↗

DOE OSTI2019

Development of High-Q SRF Structures by Nitrogen Doping for Superconducting Electron Linacs

One of the most exciting recent developments in superconducting RF technology has been the discovery of a nitrogen-doping process which can reliably increase the superconducting quality factor of niobium resonators well above 10 10 at high frequency (>1 GHz). This process is now well demonstrated in particular for TESLA-style 9-cell cavities at 1.3 GHz. Nitrogen doping can significantly increase efficiency of the cavities as well as the cryogenic efficiency accelerators, and allowing significant capital cost reductions. This project will expand the application of nitrogen doping into the low-frequency regime and investigate and quantify effects on the quality factor in low frequency superconducting structures from the nitrogen doping process.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Low-energy H- beam injectors for particle accelerators: upgrade requirements, challenges and future plans [Slides]

High brightness, negative hydrogen ion sources are used extensively in large, accelerator-based, user facilities operating worldwide. Negative hydrogen beams have become the preferred means of filling circular accelerators and storage rings as well as enabling efficient extraction from cyclotrons. Much larger beams of H- ions are also utilized for neutral beams injection into fusion machines and will be discussed in a separate companion presentation. Some of the accelerator facilities include the US Spallation Neutron Source (SNS), Japan Proton Accelerator Research Complex (J-PARC), Rutherford Appleton Laboratory (RAL-ISIS), Los Alamos Neutron Science Center (LANSCE), Fermi National Accelerator Laboratory (FNAL), Brookhaven National Laboratory (BNL), the CERN LHC injector, the Chinese Spallation Neutron Source (CSNS) as well as numerous installations of D-Pace (licenced by TRIUMF) ion sources used mainly with cyclotrons. Many facilities are currently working on various improvement / upgrade projects, both in the near and long term, which are driving further development of their ion source and LEBT (Low Energy Beam Transport) and, in some cases, their overall front end injector system. This report will first provide a simple description of each facilities existing ion source and LEBT and summarize the operational parameters which are currently being routinely injected into their accelerators. Next, the parametric goals of each of the facilities upgrade projects are specified as well as development efforts currently underway to meet these requirement and improvement goals. It is hoped that that this work will not only capture the current state-of-the-art of worldwide H- beam injectors and clarify the research goals and efforts of the community in general but will also encourage further inter laboratory collaborations.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Bridging Cloud and Edge Computing at NREL Using CONNECT: Cloud Optimized Networking for Next-Gen Edge Computing Technologies [Slides]

CONNECT is an innovative on-premise hardware and software solution that integrates edge and cloud computing infrastructure at NREL. Built on the AWS Greengrass middleware and leveraging the MQTT protocol, CONNECT enables real-time data streaming from IoT devices and gateways to both cloud and local services, empowering researchers to rapidly capture, analyze, and act upon edge-generated data while leveraging cloud capabilities. The platform addresses research infrastructure challenges by providing a pre-approved platform which is already configured with the correct networking and cybersecurity baselines thus eliminating procurement delays and enabling on-demand availability. CONNECT's hybrid architecture efficiently manages burstable workloads, allowing research teams to dynamically scale computational capacity, handle peak data loads, and reduce operational bottlenecks. Advanced capabilities include built-in GPU support for executing machine learning models which enables low-latency inference at the edge from models trained in the cloud. This architecture supports real-time analytics and filtering, providing a mechanism to allow only transmitting and processing high-value data. Cloud-based configuration management permits engineers to manage on-premise systems remotely, optimizing operational efficiency. By bridging edge and cloud computing, CONNECT provides NREL researchers with a flexible, scalable platform that accelerates scientific discovery while maintaining robust security and performance standards.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1988

Atomic oxygen studies on polymers

The purpose was to study the effects of atomic oxygen on the erosion of polymer based materials. The development of an atomic oxygen neutral beam facility using a SURFATRON surface wave launcher that can produce beam energies between 2 and 3 eV at flux levels as high as approx. 10 to the 17th power atoms/cm (2)-sec is described. Thin film dielectric materials were studied to determine recession rates and and reaction efficiencies as a function of incident beam energy and fluence. Accelerated testing was also accomplished and the values of reaction efficiency compared to available space flight data. Electron microscope photomicrographs of the samples' surface morphology were compared to flight test specimens.

Morison, W. D.↗

NASA NTRS1990

Acceleration and torque feedback for robotic control - Experimental results

Gross motion control of robotic manipulators typically requires significant on-line computations to compensate for nonlinear dynamics due to gravity, Coriolis, centripetal, and friction nonlinearities. One controller proposed by Luo and Saridis avoids these computations by feeding back joint acceleration and torque. This study implements the controller on a Puma 600 robotic manipulator. Joint acceleration measurement is obtained by measuring linear accelerations of each joint, and deriving a computationally efficient transformation from the linear measurements to the angular accelerations. Torque feedback is obtained by using the previous torque sent to the joints. The implementation has stability problems on the Puma 600 due to the extremely high gains inherent in the feedback structure. Since these high gains excite frequency modes in the Puma 600, the algorithm is modified to decrease the gain inherent in the feedback structure. The resulting compensator is stable and insensitive to high frequency unmodeled dynamics. Moreover, a second compensator is proposed which uses acceleration and torque feedback, but still allows nonlinear terms to be fed forward. Thus, by feeding the increment in the easily calculated gravity terms forward, improved responses are obtained. Both proposed compensators are implemented, and the real time results are compared to those obtained with the computed torque algorithm.

Mclnroy, John E.↗

NASA NTRS1992

The design and implementation of a parallel unstructured Euler solver using software primitives

This paper is concerned with the implementation of a 3D unstructured-grid Euler-solver on massively parallel distributed-memory computer architectures. The goal is to minimize solution time by achieving high computational rates with a numerically efficient algorithm. An unstructured multigrid algorithm with an edge-based data-structure has been adopted, and a number of optimizations have been devised and implemented in order to accelerate the parallel computational rates. The implementation is carried out by creating a set of software tools, which ease the implementation of computational problems on parallel architecture machines by relieving the user of the low-level machine specific issues. The quantitative effect of the various optimizations are demonstrated, and we show that the combined effect of these optimizations leads to roughly a factor of three performance improvement. The overall solution efficiency is compared with that obtained on the CRAY-YMP vector supercomputer.

Das, R.↗

NASA NTRS2000

Parallel performance investigations of an unstructured mesh Navier-Stokes solver

A Reynolds-averaged Navier-Stokes solver based on unstructured mesh techniques for analysis of high-lift configurations is described. The method makes use of an agglomeration multigrid solver for convergence acceleration. Implicit line-smoothing is employed to relieve the stiffness associated with highly stretched meshes. A GMRES technique is also implemented to speed convergence at the expense of additional memory usage. The solver is cache efficient and fully vectorizable, and is parallelized using a two-level hybrid MPI-OpenMP implementation suitable for shared and/or distributed memory architectures, as well as clusters of shared memory machines. Convergence and scalability results are illustrated for various high-lift cases.

Mavriplis, Dimitri J.↗