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At least 901 records · Page 50

Plutonium Production Reactor Progression Problems: Magnox Neutronics Benchmarks

The goal of this document is to provide a set of comprehensive benchmarking neutronics problems for gas-cooled, graphite-moderated reactors. The problems are designed to be representative problems that increase in complexity to test performance of various codes. For the simulation of the benchmarking problems, the Shift Monte Carlo code and MPACT deterministic code are chosen because of their state-of-the-art capabilities, which are optimized for various reactor designs. Because these codes have been developed primarily for light water reactor applications, their application to graphite-moderated, gas-cooled reactors has not been extensively explored. This report attempts to evaluate benchmarks for a Magnox-style reactor, one that is graphite-moderated and gas-cooled. Parameters that are calculated and presented in this benchmark include the eigenvalue, peaking factors, and isotope concentrations. Results show good agreement between Shift and MPACT, and demonstrate the capability of MPACT to model graphite-moderated systems well.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Evaluation of PGAS communication paradigms with geometric multigrid

Partitioned Global Address Space (PGAS) languages and one-sided communication enable application developers to select the communication paradigm that balances the performance needs of applications with the productivity desires of programmers. In this paper, we evaluate three different one-sided communication paradigms in the context of geometric multigrid using the miniGMG benchmark. Although miniGMG's static, regular,and predictable communication does not exploit the ultimate potential of PGAS models, multigrid solvers appear in many contemporary applications and represent one of the most important communication patterns. We use UPC++, a PGAS extension of C++, as the vehicle for our evaluation, though our work is applicable to any of the existing PGAS languages and models. We compare performance with the highly tuned MPI baseline, and the results indicate that the most promising approach towards achieving performance and ease of programming is to use high-level abstractions, such as the multidimensional arrays provided by UPC++, that hide data aggregation and messaging in the runtime library.

Shan, H↗

Graphical models for optimal power flow

Optimal power flow (OPF) is the central optimization problem in electric power grids. Although solved routinely in the course of power grid operations, it is known to be strongly NP-hard in general, and weakly NP-hard over tree networks. In this paper, we formulate the optimal power flow problem over tree networks as an inference problem over a tree-structured graphical model where the nodal variables are low-dimensional vectors. We adapt the standard dynamic programming algorithm for inference over a tree-structured graphical model to the OPF problem. Combining this with an interval discretization of the nodal variables, we develop an approximation algorithm for the OPF problem. Further, we use techniques from constraint programming (CP) to perform interval computations and adaptive bound propagation to obtain practically efficient algorithms. Compared to previous algorithms that solve OPF with optimality guarantees using convex relaxations, our approach is able to work for arbitrary tree-structured distribution networks and handle mixed-integer optimization problems. Further, it can be implemented in a distributed message-passing fashion that is scalable and is suitable for “smart grid” applications like control of distributed energy resources. In conclusion, numerical evaluations on several benchmark networks show that practical OPF problems can be solved effectively using this approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A benchmarking study of Geant4 for Auger electrons emitted by medical radioisotopes

Auger emitting radioisotopes are of great interest in targeted radiotherapy because, once internalised in the tumour cells, they can deliver dose locally to the radiation sensitive targets, while not affecting surrounding cells. Geant4 is a Monte Carlo code widely used to characterise the physics mechanism at the basis of targeted radiotherapy. Here, we benchmarked the modelling of the emission of Auger electrons in Geant4 deriving from the decay of 123 I, 124 I, 125 I radionuclides against existing theoretical approaches. We also compared Geant4 against reference data in the case of 131 Cs, which is of interest for brachytherapy. In the case of 125 I and 131 Cs, the simulation results are compared to experimental measurements as well. Good agreement was found between Geant4 and the reference data. As far as we know, this is the first study aimed to benchmark against experimental measurements the emission of Auger electrons in Geant4 for radiotherapy applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Decomposing causality into its synergistic, unique, and redundant components

Causality lies at the heart of scientific inquiry, serving as the fundamental basis for understanding interactions among variables in physical systems. Despite its central role, current methods for causal inference face significant challenges due to nonlinear dependencies, stochastic interactions, self-causation, collider effects, and influences from exogenous factors, among others. While existing methods can effectively address some of these challenges, no single approach has successfully integrated all these aspects. Here, we address these challenges with SURD: Synergistic-Unique-Redundant Decomposition of causality. SURD quantifies causality as the increments of redundant, unique, and synergistic information gained about future events from past observations. The formulation is non-intrusive and applicable to both computational and experimental investigations, even when samples are scarce. We benchmark SURD in scenarios that pose significant challenges for causal inference and demonstrate that it offers a more reliable quantification of causality compared to previous methods.

applied mathematics↗

Reduced scaling formulation of CASPT2 analytical gradients using the supporting subspace method

We present a reduced scaling and exact reformulation of state specific complete active space second-order perturbation (CASPT2) analytical gradients in terms of the MP2 and Fock derivatives using the supporting subspace method. This work follows naturally from the supporting subspace formulation of the CASPT2 energy in terms of the MP2 energy using dressed orbitals and Fock builds. For a given active space configuration, the terms corresponding to the MP2-gradient can be evaluated with O(N5) operations, while the rest of the calculations can be computed with O(N3) operations using Fock builds, Fock gradients, and linear algebra. When tensor-hyper-contraction is applied simultaneously, the computational cost can be further reduced to O(N4) for a fixed active space size. The new formulation enables efficient implementation of CASPT2 analytical gradients by leveraging the existing graphical processing unit (GPU)-based MP2 and Fock routines. We present benchmark results that demonstrate the accuracy and performance of the new method. Example applications of the new method in ab initio molecular dynamics simulation and constrained geometry optimization are given.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analytic evaluation of energy first derivatives for spin–orbit coupled-cluster singles and doubles augmented with noniterative triples method: General formulation and an implementation for first-order properties

The paper reports a formulation of analytic energy first derivatives for the coupled-cluster singles and doubles augmented with noniterative triples [CCSD(T)] method with spin–orbit coupling included at the orbital level and an implementation for evaluation of first-order properties. Here, the new development extends the applicability of relativistic coupled cluster methods for heavy-element chemistry and spectroscopy. Benchmark calculations of first-order properties including dipole moments and electric-field gradients using the corresponding exact two-component property integrals are presented for heavy-element containing molecules to demonstrate the usefulness of the present analytic scheme.

97 MATHEMATICS AND COMPUTING↗

Diffusion Monte Carlo: A pathway towards an accurate theoretical description of manganese oxides

Here, we present diffusion Monte Carlo (DMC) results for equation of state and quasiparticle gaps of manganese binary oxides MnO and MnO 2 and the ternary oxide LaMnO 3 . Owing to the limited approximations made and the direct treatment of electronic correlations, our DMC-based study correctly describes structural properties such as the lattice constant, bulk moduli, and cohesive energies. It correctly predicts the ground-state phase of these oxides, which have different valences. Our study demonstrates the capability of DMC methods to predict the structural properties of highly correlated systems, which have been identified as suitable candidates for many applications ranging from catalysis to electronic devices. Our study also serves as a benchmark for both the manganese pseudopotential and other methodological choices to be used in calculations of similar oxides.

36 MATERIALS SCIENCE↗

Trinity Acceptance Tests Performance Summary.

Ensuring Real Applications perform well on Trinity is key to success. Four components: ASC applications, Sustained System Performance (SSP), Extra-Large MiniApplications problems, and Micro-benchmarks.

97 MATHEMATICS AND COMPUTING↗

Measurement and Characterization of Haswell Power and Energy Consumption

This is a presentation intended for the NMC seminar. Its primary objective was to understand power-performance of Haswell EP for HPC; test four benchmark programs on PowerEdge R730 with control knobs; as well as test more applications, use more compute nodes, examine the effects of control knobs, and implement power capping.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms

This paper proposes a new approach to construct high quality space-filling sample designs. First, we propose a novel technique to quantify the space-filling property and optimally trade-off uniformity and randomness in sample designs in arbitrary dimensions. Second, we connect the proposed metric (defined in the spatial domain) to the quality metric of the design performance (defined in the spectral domain). This connection serves as an analytic framework for evaluating the qualitative properties of space-filling designs in general. Using the theoretical insights provided by this spatial-spectral analysis, we derive the notion of optimal space-filling designs, which we refer to as space-filling spectral designs. Third, we propose an efficient estimator to evaluate the space-filling properties of sample designs in arbitrary dimensions and use it to develop an optimization framework for generating high quality space-filling designs. Finally, we carry out a detailed performance comparison on two different applications in varying dimensions: a) image reconstruction and b) surrogate modeling for several benchmark optimization functions and a physics simulation code for inertial confinement fusion (ICF). Our results clearly evidence the superiority of the proposed space-filling designs over existing approaches, particularly in high dimensions.

97 MATHEMATICS AND COMPUTING↗

Construction and Utilization of a Beowulf Computing Cluster: A User's Perspective

Lockheed Martin Space Operations - Stennis Programs (LMSO) at the John C Stennis Space Center (NASA/SSC) has designed and built a Beowulf computer cluster which is owned by NASA/SSC and operated by LMSO. The design and construction of the cluster are detailed in this paper. The cluster is currently used for Computational Fluid Dynamics (CFD) simulations. The CFD codes in use and their applications are discussed. Examples of some of the work are also presented. Performance benchmark studies have been conducted for the CFD codes being run on the cluster. The results of two of the studies are presented and discussed. The cluster is not currently being utilized to its full potential; therefore, plans are underway to add more capabilities. These include the addition of structural, thermal, fluid, and acoustic Finite Element Analysis codes as well as real-time data acquisition and processing during test operations at NASA/SSC. These plans are discussed as well.

Woods, Judy L.↗

Proceedings of the 2004 NASA/ONR Circulation Control Workshop, Part 1

As technological advances influence the efficiency and effectiveness of aerodynamic and hydrodynamic applications, designs and operations, this workshop was intended to address the technologies, systems, challenges and successes specific to Coanda driven circulation control in aerodynamics and hydrodynamics. A major goal of this workshop was to determine the 2004 state-of-the-art in circulation control and understand the roadblocks to its application. The workshop addressed applications, CFD, and experiments related to circulation control, emphasizing fundamental physics, systems analysis, and applied research. The workshop consisted of 34 single session oral presentations and written papers that focused on Naval hydrodynamic vehicles (e.g. submarines), Fixed Wing Aviation, V/STOL platforms, propulsion systems (including wind turbine systems), ground vehicles (automotive and trucks) and miscellaneous applications (e.g., poultry exhaust systems and vacuum systems). Several advanced CFD codes were benchmarked using a two-dimensional NCCR circulation control airfoil. The CFD efforts highlighted inconsistencies in turbulence modeling, separation and performance predictions.

Jones, Gregory S.↗

Implementation of Two Local Correlation-Based Transition Models in OVERFLOW 2.3e

Accurate prediction of the laminar-to-turbulent boundary layer transition is highlighted as a vital component of NASA's CFD Vision 2030 Study. With an increased emphasis on greener air transports and sustainable aviation, transition modeling is anticipated to have an added significance, particularly in the applications related to laminar flow technology. However, unmanned aerial vehicles, crewed reentry vehicles, and ground-to-flight extrapolation all benefit from transition models. It is useful to incorporate a variety of models in CFD solvers because there isn't a single transition model that is ideal for the complete spectrum of applications. While the Langtry-Menter γ–Reθt model has been widely used for CFD predictions of flows with laminar, transitional, and turbulent boundary layers, it does not meet the criteria for Galilean invariance, a desirable attribute for rotorcraft applications. To help overcome that limitation, we have implemented Menter's SST-based γ transition model within NASA’s OVERFLOW Overset CFD code (version 2.3e). In addition, an SA-based implementation of the Langtry-Menter γ–Reθt transition model has also been implemented in view of the increased robustness of the SA-turbulence model for external aerodynamic applications. An initial assessment of the implemented models has been carried out using benchmark 2D test cases involving flat plates and the NLF-0416 airfoil, focusing on bypass, Tollmien-Schlichting, and laminar separation bubble-induced transition scenarios. In comparison to the Langtry-Menter γ–Reθt model, both models were found to produce increased computation efficiency, principally as a result of the decrease from four to three auxiliary transport equations. Results from the initial analysis will be presented, along with additional details pertaining to the deployment of these models.

CFD modeling↗

Applications of Flow Control to Wing High-Lift Leading Edge Devices on a Commercial Aircraft

Active flow control was applied to the leading edge region of a representative future short/medium-range twin-engine airplane to improve aerodynamic performance during high-lift operations. The study is aimed at enhanced lift over the practical angle of attack range, including stall, and at reduced drag. These benefits translate to airplane performance improvements, such as longer range or larger payload. Various flow control applications were explored using Computational Fluid Dynamics and the aerodynamic performance enhancements were benchmarked against the baseline configuration. The computational analyses are used to quantify aerodynamic benefits, as well as the input required for actuation. The results were used in a system integration study for identifying potential practical implementations, which are described in a companion paper. Combined with the integration analysis, the objective of this project is to identify the most promising flow control candidates that potentially provide material net airplane level enhancements using onboard fluidic sources. Depending on the implementation of active flow control, the current study indicates that up to 1.5% net improvement in L/D at takeoff and 4% increase in maximum lift during landing are potentially achievable, after accounting for factors of system integration.

CFD↗

Large Matched-Index-of-Refraction (MIR) Flow Systems for Thermal Engineering Education

In recent international collaboration, Idaho National Laboratory (INL) and University of Erlangen-Nuremberg (UE) have developed large MIR flow systems which are ideal for joint graduate student education and research. The benefit of the MIR technique is that it permits optical measurements to determine flow characteristics in complex passages and around objects to be obtained without locating a disturbing transducer in the flow field and without distortion of the optical paths. The MIR technique is not new itself; others employed it earlier. The innovation of these MIR systems is their large size relative to previous experiments, yielding improved spatial and temporal resolution. This article will discuss the benefits of the technique, characteristics of the systems and some examples of their applications to complex situations. Typically their experiments have provided new fundamental understanding plus benchmark data for assessment and validation of computational thermal fluid dynamic codes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Optimized Hypervisor Scheduler for Parallel Discrete Event Simulations on Virtual Machine Platforms

With the advent of virtual machine (VM)-based platforms for parallel computing, it is now possible to execute parallel discrete event simulations (PDES) over multiple virtual machines, in contrast to executing in native mode directly over hardware as is traditionally done over the past decades. While mature VM-based parallel systems now offer new, compelling benefits such as serviceability, dynamic reconfigurability and overall cost effectiveness, the runtime performance of parallel applications can be significantly affected. In particular, most VM-based platforms are optimized for general workloads, but PDES execution exhibits unique dynamics significantly different from other workloads. Here we first present results from experiments that highlight the gross deterioration of the runtime performance of VM-based PDES simulations when executed using traditional VM schedulers, quantitatively showing the bad scaling properties of the scheduler as the number of VMs is increased. The mismatch is fundamental in nature in the sense that any fairness-based VM scheduler implementation would exhibit this mismatch with PDES runs. We also present a new scheduler optimized specifically for PDES applications, and describe its design and implementation. Experimental results obtained from running PDES benchmarks (PHOLD and vehicular traffic simulations) over VMs show over an order of magnitude improvement in the run time of the PDES-optimized scheduler relative to the regular VM scheduler, with over 20 reduction in run time of simulations using up to 64 VMs. The observations and results are timely in the context of emerging systems such as cloud platforms and VM-based high performance computing installations, highlighting to the community the need for PDES-specific support, and the feasibility of significantly reducing the runtime overhead for scalable PDES on VM platforms.

Yoginath, Srikanth B↗