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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 OSTI2023

Extending OpenSHMEM with Aggregation Support for Improved Message Rate Performance

OpenSHMEM is a highly efficient one-sided communication API that implements the PGAS parallel programming model, and is known for its low latency communication operations that can be mapped efficiently to RDMA capabilities of network interconnects. However, applications that use OpenSHMEM can be sensitive to point-to-point message rates, as many-to-many communication patterns can generate large amounts of small messages which tend to overwhelm network hardware that has predominantly been optimised for bandwidth over message rate. Additionally, many important emerging classes of problems such as data analytics are similarly troublesome for the irregular access patterns they employ. Message aggregation strategies have been proven to significantly enhance network performance, but their implementation often involves complex restructuring of user code, making them unwieldy. This paper shows how to combine the best qualities of message aggregation within the communication model of OpenSHMEM such that applications with small and irregular access patterns can improve network performance while maintaining their algorithmic simplicity. We do this by providing a path to a message aggregation framework called conveyors through a minimally intrusive OpenSHMEM extension introducing aggregation contexts that fit more naturally to the OpenSHMEM atomics, gets, and puts model. We test these extensions using four of the bale 3.0 applications which contain essential many-to-many access patterns to show how they can produce performance improvements of up to 65×.

Welch, Aaron↗
DOE OSTI2015

Performance upgrades to the MCNP6 burnup capability for large scale depletion calculations

The first MCNP based inline Monte Carlo depletion capability was officially released from the Radiation Safety Information and Computational Center as MCNPX 2.6.0. With the merger of MCNPX and MCNP5, MCNP6 combined the capability of both simulation tools, as well as providing new advanced technology, in a single radiation transport code. The new MCNP6 depletion capability was first showcased at the International Congress for Advancements in Nuclear Power Plants (ICAPP) meeting in 2012. At that conference the new capabilities addressed included the combined distributive and shared memory parallel architecture for the burnup capability, improved memory management, physics enhancements, and new predictability as compared to the H.B Robinson Benchmark. At Los Alamos National Laboratory, a special purpose cluster named “tebow,” was constructed such to maximize available RAM per CPU, as well as leveraging swap space with solid state hard drives, to allow larger scale depletion calculations (allowing for significantly more burnable regions than previously examined). As the MCNP6 burnup capability was scaled to larger numbers of burnable regions, a noticeable slowdown was realized.This paper details two specific computational performance strategies for improving calculation speedup: (1) retrieving cross sections during transport; and (2) tallying mechanisms specific to burnup in MCNP. To combat this slowdown new performance upgrades were developed and integrated into MCNP6 1.2.

42 ENGINEERING↗
DOE OSTI2023

Neglecting Model Parametric Uncertainty Can Drastically Underestimate Flood Risks

Abstract Floods drive dynamic and deeply uncertain risks for people and infrastructures. Uncertainty characterization is a crucial step in improving the predictive understanding of multi‐sector dynamics and the design of risk‐management strategies. Current approaches to estimate flood hazards often sample only a relatively small subset of the known unknowns, for example, the uncertainties surrounding the model parameters. This approach neglects the impacts of key uncertainties on hazards and system dynamics. Here we mainstream a recently developed method for Bayesian inference to calibrate a computationally expensive distributed hydrologic model. We compare three different calibration approaches: (a) stepwise line search, (b) precalibration or screening, and (c) the Fast Model Calibrations (FaMoS) approach. FaMoS deploys a particle‐based approach that takes advantage of the massive parallelization afforded by modern high‐performance computing systems. We quantify how neglecting parametric uncertainty and data discrepancy can drastically underestimate extreme flood events and risks. Precalibration improves prediction skill score over a stepwise line search. The Bayesian calibration improves the uncertainty characterization of model parameters and flood risk projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Demystifying asynchronous I/O Interference in HPC applications

With increasing complexity of HPC workflows, data management services need to perform expensive I/O operations asynchronously in the background, aiming to overlap the I/O with the application runtime. However, this may cause interference due to competition for resources: CPU, memory/network bandwidth. The advent of multi-core architectures has exacerbated this problem, as many I/O operations are issued concurrently, thereby competing not only with the application but also among themselves. Furthermore, the interference patterns can dynamically change as a response to variations in application behavior and I/O subsystems (e.g. multiple users sharing a parallel file system). Without a thorough understanding, I/O operations may perform suboptimally, potentially even worse than in the blocking case. To fill this gap, here we investigate the causes and consequences of interference due to asynchronous I/O on HPC systems. Specifically, we focus on multi-core CPUs and memory bandwidth, isolating the interference due to each resource. Then, we perform an in-depth study to explain the interplay and contention in a variety of resource sharing scenarios such as varying priority and number of background I/O threads and different I/O strategies: sendfile, read/write, mmap/write underlining trade-offs. The insights from this study are important both to enable guided optimizations of existing background I/O, as well as to open new opportunities to design advanced asynchronous I/O strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Neural Networks for Nuclear Reactions in MAESTROeX

We demonstrate the use of neural networks to accelerate the reaction steps in the MAESTROeX stellar hydrodynamics code. A traditional MAESTROeX simulation uses a stiff ODE integrator for the reactions; here, we employ a ResNet architecture and describe details relating to the architecture, training, and validation of our networks. Our customized approach includes options for the form of the loss functions, a demonstration that the use of parallel neural networks leads to increased accuracy, and a description of a perturbational approach in the training step that robustifies the model. We test our approach on millimeter-scale flames using a single-step, 3-isotope network describing the first stages of carbon fusion occurring in Type Ia supernovae. We train the neural networks using simulation data from a standard MAESTROeX simulation, and show that the resulting model can be effectively applied to different flame configurations. This work lays the groundwork for more complex networks, and iterative time-integration strategies that can leverage the efficiency of the neural networks.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Career Development through Discreet Simulation Modeling - 19009

The cleanup mission of the Department of Energy (DOE) Office of River Protection (ORP) at the Hanford Site is to immobilize 212,000 m3 (56 million gallons) of nuclear waste, currently stored in 177 underground tanks, at the Waste Treatment and Immobilization Plant (WTP) and associated supplemental treatment facilities. Waste transfers to and from the WTP utilize the intricate Hanford Waste Feed Delivery (WFD) system, a network composed of: double-shell tanks (DSTs), single shell tanks (SSTs), the effluent treatment facility (ETF), a large number of pumps, valves, and leak detectors, and thousands of feet of underground transfer lines. This equipment must be prepared to safely and reliably transfer waste to the WTP. This study used discrete event simulation modeling to explore the behavior of the waste transfer system to identify areas of improvement. Two models and their subsequent results are presented: the Effluent Treatment Facility and the next-to-be-retrieved single-shell tanks (A/AX Farms). This study focused on identifying throughput bottlenecks, operational constraints, choke-point analysis, and redundancy in equipment, process design, and operational strategy. Analysis performed on the ETF OR Model indicated that the existing facility operation strategy will not result in a sufficient throughput to prevent WTP melter idling. Furthermore, in the absence of equipment failures, the facility was still shown to be unable to reach the required throughput to prevent melter idling. It is concluded that ETF system maintenance events are currently the main bottlenecks in the ETF facility. Analysis performed on the SST (A/AX) OR model indicate that the main drivers of the retrieval schedule are the hard retrieval start dates for each SST tank. In addition, it was concluded that operating the ventilation trains in parallel results in 15 times less retrieval interruptions and shortens the retrieval durations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Direct Functionalization of Established 3D-Printed Aza-Michael Liquid Crystal Elastomers with Donor–Acceptor Stenhouse Adducts

Extrusion 3D printing has advanced the manufacturing of complex liquid crystal elastomer (LCE) architectures. In parallel, donor–acceptor Stenhouse adducts (DASAs), a class of white-light-responsive photoswitches, have enabled both photochemical and photothermal LCE actuation. However, DASA–LCEs have yet to be extruded and 3D-printed. Two key challenges exist: DASA’s inherent sensitivity to heat and radicals can lead to degradation during ink preparation and printing, and small changes in the concentration of the added DASA component impact the properties of the extrudable ink, requiring reoptimization of well-established 3D-printing protocols. To overcome these challenges, we present a post-printing functionalization strategy that circumvents these limitations. Residual secondary amines, inherent to inks synthesized via standard aza-Michael addition, serve as active sites for covalent attachment of DASA photoresponsive groups following printing and cross-linking. Our method means that DASAs can be directly grafted onto 3D-printed aza-Michael LCEs without modifying the ink formulation or processing. The resulting DASA–LCEs exhibit wavelength tunability within the visible range and a variety of photothermal and photochemical responses. The post-functionalization can occur within 2 min and enables spatial control of the DASA concentration, producing films with tunable color gradients and locally varied photothermal and photochemical responses under visible light. In conclusion, this approach enables the rapid fabrication of DASA-based light-responsive LCEs using established ink formulations with the potential for the design of complex 3D architectures.

3D printing↗
DOE OSTI2024

Switching Modes for Reduction of Peak Voltage Transients in GaN-Based Three Level ANPC Inverter

The switching pole voltage can transition between P,0, and N states in a three-level active neutral point clamped (ANPC) inverter. State transitions between 0-P and 0-N can be realized with different switching modes. Three switching modes- Short 1 , Short 2 , and Full are studied considering the effect of capacitive current paths. The role of clamping and inner switch on/off conditions is determined using simplified equivalent circuit models. Short 2 with clamping switch off is beneficial for turn-on overvoltage suppression but results in high turn-off overvoltage. Full mode with a parallel current sharing path is effective for turn-off overvoltage suppression but leads to high turn-on overvoltage. Hence, a Modified Full mode is proposed to achieve the simultaneous objective of overvoltage suppression at both turn-on and turn-off transient during high load currents. This benefits 3L ANPC operation at a low power factor with a high load current at fundamental voltage zero crossing points. Here, a 650V GaN-based three-level ANPC inverter prototype is designed and used to evaluate the switching modes and overvoltage suppression strategies through double pulse tests and continuous operation.

42 ENGINEERING↗
DOE OSTI2022

Cell-free Scaled Production and Adjuvant Addition to a Recombinant Major Outer Membrane Protein from Chlamydia muridarum for Vaccine Development

Subunit vaccines offer advantages over more traditional inactivated or attenuated whole-cell-derived vaccines in safety, stability, and standard manufacturing. To achieve an effective protein-based subunit vaccine, the protein antigen often needs to adopt a native-like conformation. This is particularly important for pathogensurface antigens that are membrane-bound proteins. Cell-free methods have been successfully used to produce correctly folded functional membrane protein through the co-translation of nanolipoprotein particles (NLPs), commonly known as nanodiscs. This strategy can be used to produce subunit vaccines consisting of membrane proteins in a lipid-bound environment. However, cell-free protein production is often limited to small scale (<1 mL). The amount of protein produced in small-scale production runs is usually sufficient for biochemical and biophysical studies. However, the cell-free process needs to be scaled up, optimized, and carefully tested to obtain enough protein for vaccine studies in animal models. Other processes involved in vaccine production, such as purification, adjuvant addition, and lyophilization, need to be optimized in parallel. This paper reports the development of a scaled-up protocol to express, purify, and formulate a membrane-bound protein subunit vaccine

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Peptide programming of supramolecular vinylidene fluoride ferroelectric phases

Ferroelectric structures have spontaneous macroscopic polarization that can be inverted using external electric fields and have potential applications including information storage, energy transduction, ultralow-power nanoelectronics and biomedical devices. These functions would benefit from nanoscale control of ferroelectric structure, the ability to switch polarization with lower applied fields (low coercive field) and biocompatibility. Soft ferroelectrics based on poly(vinylidene fluoride) (PVDF) have a thermodynamically unstable ferroelectric phase in the homopolymer, complex semi-crystalline structures, and high coercive fields. Here, in this work, we report on ferroelectric materials formed by water-soluble molecules containing only six VDF repeating units covalently conjugated to a tetrapeptide, with the propensity to assemble into the β-sheet structures that are ubiquitous in proteins. This led to the discovery of ribbon-shaped ferroelectric supramolecular assemblies that are thermodynamically stable with their long axes parallel to both the preferred hydrogen-bonding direction of β-sheets and the bistable polar axes of VDF hexamers. Relative to a commonly used ferroelectric copolymer, the biomolecular assemblies exhibit a coercive field that is two orders of magnitude lower, as the result of supramolecular dynamics, and a similar level of remnant polarization, despite having a peptide content of 49 wt%. Furthermore, the Curie temperature of the assemblies is about 40 °C higher than that of a copolymer containing a similar amount of VDF. This supramolecular system was created using a biologically inspired strategy that is attractive in terms of sustainability and that could lead to new functions for soft ferroelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Automation of Data Collection Methods for Online Monitoring of Nuclear Power Plants

Maintenance activities in the United States nuclear power industry are mainly centered on preventive and corrective maintenance. Predictive maintenance, which is a variable time basis maintenance strategy that is dependent on the condition of the equipment, is less utilized but potentially more effective. In the current maintenance practices, the nuclear power plants rely on manual processes to supply information to a human decision making process. The plants have several processes that generate information that is not typically used beyond the intended target for collecting that information. This information is a source of data that is manually collected by labor intensive tasks. The data is therefore expensive to collect, yet limited in use. The industry has realized the opportunity present in reducing the labor intensive tasks by automating them and increasing the uses of the data collected by either developing advanced predictive maintenance methods using data-driven decision making that could span from trending to machine learning and artificial intelligence. This shift in maintenance strategy may result in high cost saving impact. In addition to reducing labor requirements and frequency of maintenance activities, this shift in strategy will reduce the materials portion of the operations and maintenance cost as well. The aim of this specific effort is to focus on the automation of data collection process. It is part of a series of planned efforts to target multiple elements of migrating the current preventive maintenance approach in nuclear power plants to a data-driven approach. These elements include data collection, management, analysis, visualization, in addition to value analysis and change enabling. The other five elements of migration were not considered because they are planned to be explicitly studied in multiple parallel efforts. Challenges including regulations requirements or limitations are planned in a future effort that focuses on change enabling. The risk and benefit/cost of the approach shift is planned in another effort targeted towards value. The storage, communication, computational power, data architecture, and protection are part of the information infrastructure and are planned in dedicated data management effort. The best means to present the data for assisted human decision making is planned in a data visualization effort. The data interpretation and patterns recognition for machine decision making is planned through multiple efforts in data analytics over the following years. This work identified seventeen data sources collection methods in nuclear power plants that could be automated for an integrated data platform that enables comprehensive and informed decision making. For each of the identified seventeen data sources, the base, modern, and state of the art states were described. The current state of data collection used by most utilities was identified as the "base state". The current achievable state was identified as the "modern state", a state that has either been achieved by at least some US utilities or in other industries. The future state that requires research and development to reach was identified as the "state of the art" state. The described states used an out-of-the-box thinking approach. This effort found that there is a hug potential for task automation and data fidelity improvements by evolving the current industry data collection methods. The majority of the processes analyzed were found to be manual and labor intensive and fell in the base state. As a result, the modern state often targeted reducing the manual logging efforts by using electronic and semi-intelligent means or complementing the work with sensors and mobile or fixed technologies that can reduce the demand of labor activities. The state of the art state involved applications advanced methods of data correlation, data mining, and machine learning along with increasing the spatial distribution and fidelity of data, coupling multiple data sources, and enabling the use of sophisticated mobile devices and machine comprehension methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Single pot catalyst strategy to branched products via adhesive isomerization and hydrocracking of polyethylene over platinum tungstated zirconia

Hydrocracking is an insufficiently explored route for chemical recycling of plastics waste. Platinum tungstated zirconia (Pt-WZr) was used in a batch reactor at low temperatures of 250 °C and 30 bar H 2 pressure for 1-24 h reaction times using low-density polyethylene (LDPE, M w ~76 kDa). We find Pt-WZr is a bifunctional catalyst for LDPE hydrocracking leading to higher value branched fuel- and lubricant-ranged alkanes. Here we demonstrate that the catalyst metal-to-acid site molar ratio (MAB) shifts the product distribution to larger cracked products and increases the isomerization degree in the residual polymer. We propose a new adhesive isomerization mechanism between the metal and Brønsted acid sites in parallel with slow polymer chain cracking, caused by competitive adsorption of the polymer over the liquid products and stereochemical hindrance of methines. This study provides a blueprint on how to engineer effective catalysts for hydrocracking polyolefin plastic wastes using the MAB as a catalyst descriptor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Strategies for Energy-Efficient Resource Management of Hybrid Programming Models

Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. Furthermore, we apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Comparisons of RELAP5-3D Analyses to Experimental Data from the Natural Convection Shutdown Heat Removal Test Facility

The Reactor Cavity Cooling System (RCCS) is an important passive safety system being incorporated into the overall safety strategy for high temperature advanced reactor concepts such as the High Temperature Gas- Cooled Reactors (HTGR). The Natural Convection Shutdown Heat Removal Test Facility (NSTF) at Argonne National Laboratory (Argonne) reflects a 1/2-scale model of the primary features of one conceptual air-cooled RCCS design. The project conducts ex-vessel, passive heat removal experiments in support of Department of Energy Office of Nuclear Energy’s Advanced Reactor Technology (ART) program, while also generating data for code validation purposes. While experiments are being conducted at the NSTF to evaluate the feasibility of the passive RCCS, parallel modeling and simulation efforts are ongoing to support the design, fabrication, and operation of these natural convection systems. Both system-level and high fidelity computational fluid dynamics (CFD) analyses were performed to gain a complete understanding of the complex flow and heat transfer phenomena in natural convection systems. This paper provides a summary of the RELAP5-3D NSTF model development efforts and provides comparisons between simulation results and experimental data from the NSTF. Overall, the simulation results compared favorably to the experimental data, however, further analyses need to be conducted to investigate any identified differences.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Isoliquiritigenin, a flavonoid from licorice, blocks M2 macrophage polarization in colitis-associated tumorigenesis through downregulating PGE{sub 2} and IL-6

M2 macrophage polarization is implicated in colorectal cancer development. Isoliquiritigenin (ISL), a flavonoid from licorice, has been reported to prevent azoxymethane (AOM) induced colon carcinogenesis in animal models. Here, in a mouse model of colitis-associated tumorigenesis induced by AOM/dextran sodium sulfate (DSS), we investigated the chemopreventive effects of ISL and its mechanisms of action. Mice were treated with AOM/DSS and randomized to receive either vehicle or ISL (3, 15 and 75 mg/kg). Tumor load, histology, immunohistochemistry, and gene and protein expressions were determined. Intragastric administration of ISL for 12 weeks significantly decreased colon cancer incidence, multiplicity and tumor size by 60%, 55.4% and 42.6%, respectively. Moreover, ISL inhibited M2 macrophage polarization. Such changes were accompanied by downregulation of PGE{sub 2} and IL-6 signaling. Importantly, depletion of macrophages by clodronate (Clod) or zoledronic acid (ZA) reversed the effects of ISL. In parallel, in vitro studies also demonstrated that ISL limited the M2 polarization of RAW264.7 cells and mouse peritoneal macrophages with concomitant inactivation of PGE{sub 2}/PPARδ and IL-6/STAT3 signaling. Conversely, exogenous addition of PGE{sub 2} or IL-6, or overexpression of constitutively active STAT3 reversed ISL-mediated inhibition of M2 macrophage polarization. In summary, dietary flavonoid ISL effectively inhibits colitis-associated tumorigenesis through hampering M2 macrophage polarization mediated by the interplay between PGE{sub 2} and IL-6. Thus, inhibition of M2 macrophage polarization is likely to represent a promising strategy for chemoprevention of colorectal cancer. - Highlights: • Isoliquiritigenin (ISL) prevents colitis-associated tumorigenesis. • ISL inhibits M2 macrophage polarization in vivo and in vitro. • ISL inhibits PGE{sub 2} and IL-6 signaling in colitis-associated tumorigenesis. • ISL may be an attractive candidate agent for chemoprevention of colorectal cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Simulations of future particle accelerators: issues and mitigations

The ever increasing demands placed upon machine performance have resulted in the need for more comprehensive particle accelerator modeling. Computer simulations are key to the success of particle accelerators. Many aspects of particle accelerators rely on computer modeling at some point, sometimes requiring complex simulation tools and massively parallel supercomputing. Examples include the modeling of beams at extreme intensities and densities (toward the quantum degeneracy limit), and with ultra-fine control (down to the level of individual particles). In the future, adaptively tuned models might also be relied upon to provide beam measurements beyond the resolution of existing diagnostics. Much time and effort has been put into creating accelerator software tools, some of which are highly successful. However, there are also shortcomings such as the general inability of existing software to be easily modified to meet changing simulation needs. In this paper possible mitigating strategies are discussed for issues faced by the accelerator community as it endeavors to produce better and more comprehensive modeling tools. This includes lack of coordination between code developers, lack of standards to make codes portable and/or reusable, lack of documentation, among others.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

Task mapping for non-contiguous allocations.

This paper examines task mapping algorithms for non-contiguously allocated parallel jobs. Several studies have shown that task placement affects job running time for both contiguously and non-contiguously allocated jobs. Traditionally, work on task mapping either uses a very general model where the job has an arbitrary communication pattern or assumes that jobs are allocated contiguously, making them completely isolated from each other. A middle ground between these two cases is the mapping problem for non-contiguous jobs having a specific communication pattern. We propose several task mapping algorithms for jobs with a stencil communication pattern and evaluate them using experiments and simulations. Our strategies improve the running time of a MiniApp by as much as 30% over a baseline strategy. Furthermore, this improvement increases markedly with the job size, demonstrating the importance of task mapping as systems grow toward exascale.

Leung, Vitus Joseph↗
DOE OSTI2017

Multilevel acceleration of scattering-source iterations with application to electron transport

Acceleration/preconditioning strategies available in the SCEPTRE radiation transport code are described. A flexible transport synthetic acceleration (TSA) algorithm that uses a low-order discrete-ordinates (S N ) or spherical-harmonics (P N ) solve to accelerate convergence of a high-order S N source-iteration (SI) solve is described. Convergence of the low-order solves can be further accelerated by applying off-the-shelf incomplete-factorization or algebraic-multigrid methods. Also available is an algorithm that uses a generalized minimum residual (GMRES) iterative method rather than SI for convergence, using a parallel sweep-based solver to build up a Krylov subspace. TSA has been applied as a preconditioner to accelerate the convergence of the GMRES iterations. The methods are applied to several problems involving electron transport and problems with artificial cross sections with large scattering ratios. These methods were compared and evaluated by considering material discontinuities and scattering anisotropy. Observed accelerations obtained are highly problem dependent, but speedup factors around 10 have been observed in typical applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗