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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 OSTI2018

Predictive analytics tools to adjust and monitor performance metrics for the ATLAS Production System

Having information such as an estimation of the processing time or possibility of system outage (abnormal behaviour) helps to assist to monitor system performance and to predict its next state. The current cyber-infrastructure of the ATLAS Production System presents computing conditions in which contention for resources among high-priority data analyses happens routinely, that might lead to significant workload and data handling interruptions. The lack of the possibility to monitor and to predict the behaviour of the analysis process (its duration) and system's state itself provides motivation for a focus on design of the built-in situational awareness analytic tools.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Automated Testing System

The Automated Testing System (ATS) is an open-source, Python-based tool for automating the running of tests of an application across a broad range of high performance computers.

Dempsey, StephanieM.↗
DOE OSTI2013

Lorenz APIs and LORA/REST Services

Lorenz is a project aimed at using modern web technologies to make High Performance Computing (HPC) easier. It has been under development at Lawrence Livermore National Laboratory since the spring of 2010. Lorenz is tackling three broad areas: a system "dashboard" aimed at making information about the computing center easy to determine "at a glance", job management (submission and monitoring of batch jobs), and application portals which are loosely coupled pre- and post-processors to existing codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Using NVMe Gen3 PCIe SSD Cards in High-density Servers for High-performance Big Data Transfer Over Multiple Network Channels

This Technical Note describes how the Zettar team came up with a data transfer cluster design that convincingly proved the feasibility of using high-density servers for high-performance Big Data transfers. It then outlines the tests, operations, and observations that address a potential over-heating concern regarding the use of Non-Volatile Memory Host Controller Interface Specification (NVMHCI aka NVM Express or NVMe) Gen 3 PCIe SSD cards in high-density servers. Finally, it points out the possibility of developing a new generation of high-performance Science DMZ data transfer system for the data-intensive research community and commercial enterprises.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

HPE ultralit project (ARPA-E open program 2018) final report 15

The goal of the program was to build a fully integrated optical transceiver with >1 Tb/s and <1.5 pJ/bit operating at 50 ◦ C. Optical transceivers are critical components in high-performance-computers (HPC) and data centers, and the details of their implementation has a big impact on the total power consumption (energy efficiency) of an HPC system. Our proposed transceiver used three key enabling technologies. Firstly, SiGe avalanche photodetectors have record-low sensitivities, meaning that they can reach low bit error rates with very little light input. As a result, we can drive our lasers at a lower drive current, thus saving electrical power. Secondly, we use MOS-based capacitive tuning in our deinterleaver, modulator, and demultiplexer. Capacitive tuning allows for the tuning of photonic elements with zero static power consumption. Thirdly, we use quantum dots as the gain material in our light source. This allows us to efficiently use our light source at temperatures that are typically encountered in an HPCsystem. Our proposed optical transceiver consisted of a quantum dot comb laser as a light source, a booster SOA, MOS-based deinterleavers, MOS based ring modulators, MOS-based ring demultiplexers, and SiGe APDs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Evolution of HEP Processing Frameworks

HEP data-processing software must support the disparate physics needs of many experiments. For both collider and neutrino environments, HEP experiments typically use data-processing frameworks to manage the computational complexities of their large-scale data processing needs. Data-processing frameworks are being faced with new challenges this decade. The computing landscape has changed from the past three decades of homogeneous single-core x86 batch jobs running on grid sites. Frameworks must now work on a heterogeneous mixture of different platforms: multi-core machines, different CPU architectures, and computational accelerators; and different computing sites: grid, cloud, and high-performance computing. We describe these challenges in more detail and how frameworks may confront them. Given their historic success, frameworks will continue to be critical software systems that enable HEP experiments to meet their computing needs. Frameworks have weathered computing revolutions in the past; they will do so again with support from the HEP community

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

OpenACC unified programming environment for GPU and FPGA multi-hybrid acceleration

Attached accelerators have been frequently used in recent High Per- formance Computing (HPC) systems because of their high performance/power ratio. In particular, the Graphics Processing Unit (GPU) is the most popu- lar accelerator owing to its high peak FLOPS performance and high memory bandwidth supported by HBM2, etc. However, the performance of GPU depends highly on a large degree of SIMD parallelism and has difficulty sustaining a high performance on programs with frequent branch operations or a partially low degree of parallelism.By contrast, a Field Programmable Gate Array (FPGA) has received attention as a different type of accelerator than GPU as a fully reconfigurable processor fitting the target applications. The high performance of FPGA is mainly provided by a pipelined operation and optimized circuit suitable for any operation even with frequent conditional branches. We have been focusing on the flexibility of FPGA to compensate for the weakness of GPU. We believe that the coupling of GPU with FPGA can result in one of the most powerful accelerating platforms available.However, the program coding of GPU and FPGA coupling can be quite difficult for application users. Traditionally, CUDA by NVIDIA has been the most popular programming language with the largest share of GPUs used in HPC, whereas a hardware description language such as Verilog HDL has been used in FPGA programming. OpenCL coding has recently become available even on high-end FPGAs. Moreover, several recent studies have also enabled the OpenACC coding for use in FPGA. In this study, we provide a unified programming system based on OpenACC for a platform equipped with both GPU and FPGA aiming at the next-generation accelerated supercomputer framework. Our programming environment is called Multi-Hybrid OpenACC Translator (MHOAT), and in this paper, we describe the basic concept and prototype system of MHOAT based on an evaluation on the amount of coding required and the performance of a hybrid multi-device accelerated system.

Tsunashima, Ryuta↗
DOE OSTI2023

GAHLS: an optimized graph analytics based high level synthesis framework

The urgent need for low latency, high-compute and low power on-board intelligence in autonomous systems, cyber-physical systems, robotics, edge computing, evolvable computing, and complex data science calls for determining the optimal amount and type of specialized hardware together with reconfigurability capabilities. With these goals in mind, we propose a novel comprehensive graph analytics based high level synthesis (GAHLS) framework that efficiently analyzes complex high level programs through a combined compiler-based approach and graph theoretic optimization and synthesizes them into message passing domain-specific accelerators. This GAHLS framework first constructs a compiler-assisted dependency graph (CaDG) from low level virtual machine (LLVM) intermediate representation (IR) of high level programs and converts it into a hardware friendly description representation. Next, the GAHLS framework performs a memory design space exploration while account for the identified computational properties from the CaDG and optimizing the system performance for higher bandwidth. The GAHLS framework also performs a robust optimization to identify the CaDG subgraphs with similar computational structures and aggregate them into intelligent processing clusters in order to optimize the usage of underlying hardware resources. Finally, the GAHLS framework synthesizes this compressed specialized CaDG into processing elements while optimizing the system performance and area metrics. Evaluations of the GAHLS framework on several real-life applications (e.g., deep learning, brain machine interfaces) demonstrate that it provides 14.27× performance improvements compared to state-of-the-art approaches such as LegUp 6.2.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

NEAMS Workbench and Bison Fuel Performance Remote Application Configuration

The mission of the US Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program is to develop, apply, deploy, and support state-of-the-art predictive modeling and simulation tools for the design and analysis of current and future nuclear energy systems. This is accomplished using computing architectures that range from laptops to leadership class facilities. The NEAMS Workbench [1,2,3] initiative will facilitate the transition from conventional computer codes to high-fidelity ones by providing a common analysis environment and interface for model creation, review, execution, output review, and visualization for integrated codes. The BISON fuel performance code [4] is a finite element method (FEM)-based software being developed by multiple organizations led by the Idaho National Laboratory for the US Department of Energy Office of Nuclear Energy. BISON can simulate a variety of fuel and cladding compositions and geometries in varying dimensionalities, depending upon the problem type and complexity, including one-dimensional (1D), 1.5D, 2D axially symmetric (2D-rz), 2D radial-azimuthal (2D-rθ), or 3D models. The NEAMS Workbench allows execution of the BISON fuel performance code on local and remote compute resources. In this report, the detailed instructions of configuring the NEAMS Workbench for remote execution of the BISON fuel performance code on a portable batch system (PBS)-scheduled compute resource, as well the transfer of associated Bison files, is illustrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Advanced Output Coupling for High Power Gyrotrons

The Phase II program developed an internal RF coupler that transforms the whispering gallery RF mode produced in gyrotron cavities to an HE11 waveguide mode propagating in corrugated waveguide. This power is extracted from the vacuum using a broadband, chemical vapor deposited (CVD) diamond, Brewster angle window capable of transmitting more than 1.5 MW CW of RF power over a broad range of frequencies. This coupling system eliminates the Mirror Optical Units now required to externally couple Gaussian output power into corrugated waveguide, significantly reducing system cost and increasing efficiency. The program simulated the performance using a broad range of advanced computer codes to optimize the design. Both a direct coupler and Brewster angle window were built and tested at low and high power. Test results confirmed the performance of both devices and demonstrated they are capable of achieving the required performance for scientific, defense, industrial, and medical applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Toward integrating high-fidelity CFD approaches in the thermal-hydraulic analysis of turbulent dry cask systems

Nuclear power plants have been supplying resilient and reliable electricity for decades, contributing to energy independence of the U.S.. However, nuclear waste management remains one of the most significant challenges in the industry. The safety of dry cask storage systems relies heavily on their thermal-hydraulic performance. Computational Fluid Dynamics (CFD) simulations are often used to demonstrate this performance and ensure that the system design meets safety standards. This study presents reduced numerical models for various types of dry cask systems. These numerical models can produce efficient and fast results based on the employed modeling strategies. Additionally, the study uses a novel approach to high-fidelity simulations to evaluate modeling assumptions in dry cask modeling. Large Eddy Simulations (LES) are used for this purpose, particularly in regions where fluid velocity is relatively high and the turbulence characteristics become important. Furthermore, the results of these high-fidelity simulations will enhance the interpretation of outcomes produced from a lower-fidelity CFD model.

CFD↗
DOE OSTI2020

Improved Models of Long-Term Creep Behavior of High Performance Structural Alloys

In this program, QuesTek Innovations LLC, a leader in the field of computational materials design, proposes to develop a robust creep-modeling toolkit that expands its computational Materials by Design® technology, in order to predict the long-term creep performance of materials for base alloys and weldments in fossil energy systems under wide thermal and mechanical conditions. The Material Database Group of NIMS (National Institute for Material Science, JAPAN) provides reliable public data for long-term creep behavior over 300,000 hours (> 34 years) for a variety of materials including high Cr steels along with seminal work performed by EPRI (Electric Power Research Institute) on creep failure of these steels. QuesTek would rely on these premier institutions for experimental data needed to calibrate models. The developed tool has wider applications than the state-of-the-art modeling tools. It includes the effects of chemistry variations, microstructure variation (weldments) etc .which is lacking in many available models requiring the model to be calibrated to large number of datasets for accurate predictions. A model based on fundamental mechanism has promises in application to different materials, other than the demonstrated material (Grade 91 steels) in the current program. As a result of such an effort, we envision greatly advancing the state-of-the-art modeling tools for creep life assessments of different materials.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Adaptive Interface-PINNs (AdaI-PINNs) for transient diffusion: Applications to forward and inverse problems in heterogeneous media

We model transient diffusion in heterogeneous materials using a novel physics-informed neural networks framework (PINNs) termed Adaptive interface physics-informed neural networks or AdaI-PINNs (Roy et al. arXiv preprint arXiv:2406.04626, 2024). AdaI-PINNs utilize different activation functions with trainable slopes tailored to each material region within the computational domain, allowing for a fully automated and adaptive PINNs approach to model interface problems with strongly and weakly discontinuous solutions. To enhance its performance in highly heterogeneous transient diffusion systems, we prescribe a suite of robust practices, including appropriate non-dimensionalization of equations, a biased sampling method, Glorot initialization, and the hard enforcement of boundary and initial conditions. Here we evaluate the efficacy of the proposed method on several benchmark forward and inverse problems. Comparative studies on one-dimensional and two-dimensional benchmark problems reveal that the modified AdaI-PINNs outperform its unmodified counterpart, achieving root-mean-square errors that are at least two orders of magnitude better in forward problems. For inverse problems, the maximum errors in the approximated diffusion coefficients by modified AdaI-PINNs are four orders of magnitude better than those of the unmodified version. Additionally, modified AdaI-PINNs demonstrate improved stability in problems with large material mismatches.

42 ENGINEERING↗
DOE OSTI2015

Quantitative single-particle digital autoradiography with α-particle emitters for targeted radionuclide therapy using the iQID camera

Purpose: Alpha-emitting radionuclides exhibit a potential advantage for cancer treatments because they release large amounts of ionizing energy over a few cell diameters (50–80 μm), causing localized, irreparable double-strand DNA breaks that lead to cell death. Radioimmunotherapy (RIT) approaches using monoclonal antibodies labeled with α emitters may thus inactivate targeted cells with minimal radiation damage to surrounding tissues. Tools are needed to visualize and quantify the radioactivity distribution and absorbed doses to targeted and nontargeted cells for accurate dosimetry of all treatment regimens utilizing α particles, including RIT and others (e.g., Ra-223), especially for organs and tumors with heterogeneous radionuclide distributions. The aim of this study was to evaluate and characterize a novel single-particle digital autoradiography imager, the ionizing-radiation quantum imaging detector (iQID) camera, for use in α-RIT experiments. Methods: The iQID camera is a scintillator-based radiation detection system that images and identifies charged-particle and gamma-ray/x-ray emissions spatially and temporally on an event-by-event basis. It employs CCD-CMOS cameras and high-performance computing hardware for real-time imaging and activity quantification of tissue sections, approaching cellular resolutions. In this work, the authors evaluated its characteristics for α-particle imaging, including measurements of intrinsic detector spatial resolutions and background count rates at various detector configurations and quantification of activity distributions. The technique was assessed for quantitative imaging of astatine-211 ({sup 211}At) activity distributions in cryosections of murine and canine tissue samples. Results: The highest spatial resolution was measured at ∼20 μm full width at half maximum and the α-particle background was measured at a rate as low as (2.6 ± 0.5) × 10{sup −4} cpm/cm{sup 2} (40 mm diameter detector area). Simultaneous imaging of multiple tissue sections was performed using a large-area iQID configuration (ø 11.5 cm). Estimation of the {sup 211}At activity distribution was demonstrated at mBq/μg-levels. Conclusions: Single-particle digital autoradiography of α emitters has advantages over traditional film-based autoradiographic techniques that use phosphor screens, in terms of spatial resolution, sensitivity, and activity quantification capability. The system features and characterization results presented in this study show that the iQID is a promising technology for microdosimetry, because it provides necessary information for interpreting alpha-RIT outcomes and for predicting the therapeutic efficacy of cell-targeted approaches using α emitters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Development of mpi_EPIC model for global agroecosystem modeling

Models that address policy-maker concerns about multi-scale effects of food and bioenergy production systems are computationally demanding. We integrated the message passing interface algorithm into the process-based EPIC model to accelerate computation of ecosystem effects. Simulation performance was further enhanced by applying the Vampir framework. When this enhanced mpi_EPIC model was tested, total execution time for a global 30-year simulation of a switchgrass cropping system was shortened to less than 0.5 hours on a supercomputer. The results illustrate that mpi_EPIC using parallel design can balance simulation workloads and facilitate large-scale, high-resolution analysis of agricultural production systems, management alternatives and environmental effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

DESIGN AND EXPERIMENTAL STUDY OF A HIGH PRESSURE AND SUPERCRITICAL METHANE-OXYGEN BURNER

Directly heated supercritical oxy-fuel power cycles have potential to offer a higher thermal efficiency and lower pollutant emissions compared to existing power cycles. Recent thermodynamic analysis of the cycle performed by several groups including the UTEP-Air Liquide research team show that combustion in the vicinity of 300 bar pressure and 1000-1400 K temperature allows for relatively high system efficiencies while operating within the limit of practical combustor materials. However, the realization of directly heated supercritical power cycle requires combustion systems be designed to operate in supercritical conditions and at temperature far below the blowout limit of conventional flames (above 1500 K), where not only the thermodynamic properties but also the combustion properties and kinetics are unexplored. To minimize these knowledge gaps, some intermediate pressure ranges (up to 20 bar) are experimented and modeled using a CFD simulation tool. The knowledge obtained from the high pressure test will assist in understanding the combustion chamber pressurization mechanism, ignition and flame behavior at the elevated pressure. This is a systematic first step in testing at higher pressures of 100 and 300 bar pressures. The primary objective of this dissertation is to perform qualitative analysis on oxy-methane combustion at high pressure (< 20 bar) and compare to CFD model for future scale up to supercritical condition. For modeling of the system, a commercial computational fluid dynamics simulation tool, ANSYS Fluent, is used. The inlet conditions for the CFD analysis are obtained from the experiments. The geometry used for the study is same as the test apparatus and operates at the same power ratings. The expertise gained from this experimental study is important to accurately and safely design combustors at elevated pressures up to 300bar. A high pressure methane-oxygen fuel burner and combustor have been developed to accommodate oxycombustion environment. A detailed CFD analysis is conducted to understand the flame length and cooling phenomenon inside the combustor first at pressures up to 20 bar to compare to experiments then at supercritical pressure. The first part of the dissertation compares CFD results with high pressure burner experiments at pressures up to 20 bar. The test is conducted for 30 s within 150 kW – 250 kW thermal power inputs. Afterwards, based on the simulation results a cooling system is proposed for steady state high pressure combustion experiments. It is observed from the experimental study that the proposed pressurization mechanism able to pressurize the vessel up to 20 bar. It is also determined that the current combustor can operate up to 20 bar for short term. The steady state CFD simulation demonstrates that a cooling system must be incorporated for continuous operation. Additionally, the study focuses on the ignition delay due to added diluent during the combustion process. It is observed that as the carbon dioxide recirculation ratio increases the ignition delay time increases. Later part of the dissertation provides a preliminary guideline for developing a laboratory scale supercritical oxy combustor. The employment of supercritical fluid in gas turbine is fairly a new concept. Hence, there are many questions that need to be answered. During this dissertation study an investigation is performed to understand the impact of equation of state in the supercritical combustion simulation. Finally, a CFD model for developing supercritical oxy-methane burner and the combustor, incorporating real gas model, is presented. Although Lee-Kesler equation of state provides better accuracy than Peng Robinson, due to the computational time Peng Robinson equation of state is used for the simulation. It is found that existing knowledge is not enough to simulate combustion at supercritical phase. Detailed combustion chemistry at the supercritical condition must be developed and should be incorporated to accurately replicate the combustion phenomenon.

Chowdhury, ASM Arifur Rahim↗
DOE OSTI2016

Energy scaling advantages of resistive memory crossbar based computation and its application to sparse coding

In this study, the exponential increase in data over the last decade presents a significant challenge to analytics efforts that seek to process and interpret such data for various applications. Neural-inspired computing approaches are being developed in order to leverage the computational properties of the analog, low-power data processing observed in biological systems. Analog resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as well as a parallel write or a rank-1 update with high computational efficiency. For an N × N crossbar, these two kernels can be O(N) more energy efficient than a conventional digital memory-based architecture. If the read operation is noise limited, the energy to read a column can be independent of the crossbar size (O(1)). These two kernels form the basis of many neuromorphic algorithms such as image, text, and speech recognition. For instance, these kernels can be applied to a neural sparse coding algorithm to give an O(N) reduction in energy for the entire algorithm when run with finite precision. Sparse coding is a rich problem with a host of applications including computer vision, object tracking, and more generally unsupervised learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Xenon Recovery at Room Temperature using Metal-Organic Frameworks

Xenon is known to be a very efficient anesthetic gas but its cost prohibits the wider use in medical industry and other potential applications. It has been shown that Xe recovery and recycle from anesthetic gas mixture can significantly reduce its cost as anesthetic. The current technology uses series of adsorbent columns followed by low temperature distillation to recover Xe, which is expensive to use in medical facilities. Herein, we propose much efficient and simpler system to recover and recycle Xe from simulant exhale anesthetic gas mixture at room temperature using metal organic frameworks. Among the MOFs tested, PCN-12 exhibits unprecedented performance with high Xe capacity, Xe/N2 and Xe/O2 selectivity at room temperature. The in-situ synchrotron measurements suggest the Xe is occupied in the small pockets of PCN-12 compared to unsaturated metal centers (UMCs). Computational modeling of adsorption further supports our experimental observation of Xe binding sites in PCN-12.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗