Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “code optimization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Sensitivity Analysis of Cf-252 (sf) Neutron and Gamma Observables in CGMF

CGMF is a Monte Carlo code that simulates the decay of primary fission fragments by emission of neutrons and gamma rays, according to the Hauser-Feshbach equations. As the CGMF code was recently integrated into the MCNP6.2 transport code, great emphasis has been placed on providing optimal parameters to CGMF such that many different observables are accurately represented. Of these observables, the prompt neutron spectrum, prompt neutron multiplicity, prompt gamma spectrum, and prompt gamma multiplicity are crucial for accurate transport simulations of criticality and nonproliferation applications. This contribution to the ongoing efforts to improve CGMF presents a study of the sensitivity of various neutron and gamma observables to several input parameters for Californium-252 spontaneous fission. Among the most influential parameters are those that affect the input yield distributions in fragment mass and total kinetic energy (TKE). A new scheme for representing Y(A,TKE) was implemented in CGMF using three fission modes, S1, S2 and SL. The sensitivity profiles were calculated for 17 total parameters, which show that the neutron multiplicity distribution is strongly affected by the TKE distribution of the fragments. The total excitation energy (TXE) of the fragments is shared according to a parameter RT, which is defined as the ratio of the light to heavy initial temperatures. The sensitivity profile of the neutron multiplicity shows a second order effect of RT on the mean neutron multiplicity. A final sensitivity profile was produced for the parameter alpha, which affects the spin of the fragments. Higher values of alpha lead to higher fragment spins, which inhibit the emission of neutrons. Understanding the sensitivity of the prompt neutron and gamma observables to the many CGMF input parameters provides a platform for the optimization of these parameters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Kokkos Training Bootcamp WBS STPM12 Milestone 4

This report documents the completion of milestone STPM12-4 Kokkos Training Bootcamp. The goal of this milestone was to hold a combined tutorial and hackathon bootcamp event for the Kokkos community and prospective users. The Kokkos Bootcamp event was held on-site at Oak Ridge National Lab from July 24 — July 27, 2018. There were over 40 registered participants from 12 institutions, including 7 Kokkos project staff from SNL, LANL, and ORNL. The event consisted of a roughly a two-day tutorial session including hands exercises, followed by 1.5 days of intensive porting work on codes that the participants brought explore, port, and optimize the use of Kokkos with the help of Kokkos project experts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

IER 489: Critical Unresolved Region Integral Experiment (CURIE) CEDT Phase-2 Final Design

The final design for the CURIE integral benchmark experiment is presented in this report. Measurements will be performed on the Comet vertical assembly machine and include various critical configurations consisting of High Enriched Uranium (HEU) metal plates and Teflon moderator plates surrounded by a thick copper reflector. The various configurations with different Teflon plate thickness planned allow for complimentary measurements with differing nuclear data sensitivity in the Unresolved Resonance Region (URR). Similar to previously performed Zeus experiments, the proposed work will serve to validate vital nuclear data quantities and uncertainties and identify deficiencies in current radiation transport codes. Additionally, it will assess the applicability of optimization approaches to nuclear critical experiment design. The final experiment design is detailed in this report and includes design, optimization, uncertainty and continuous-energy nuclear data sensitivity analysis for the final experimental configurations that will provide the basis for a future benchmark evaluation intended for submission to the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook [1]. This document discusses the method, approach, considerations and final design chosen with conclusions. It also includes cost and schedule. The basis and principles of this document come from the preliminary design report [2]. Section 2 discusses the content and potential impact; section 3 gives an overview of the nuclear data and unresolved resonance region; section 4 gives a summary of the work done during the preliminary design; section 5 discusses the machine learning method and principles used for final design; section 6 summaries the results from final design; section 7 provides conclusions and the range of configurations chosen to carry forward to experiment execution; and section 8 includes a summary of costs.

42 ENGINEERING↗
DOE OSTI2018

Stress and tangent update equations for combined time-hardening creep and J 2 plasticity in an implicit hypo-elastic formulation

This work is motivated by the need to analyze the behavior of metallic nuclear fuels which under normal operating conditions build up stresses due to non-homogeneous thermal expansion, fission gas and solid product swelling among other phenomena that are simultaneously relaxed by creep and plastic flow. This report details the stress and tangent update equations for combined J 2 based rate independent plasticity and time-hardening creep effects in a fully implicit hypo-elastic formulation involving two cases: pure creep without plasticity where the yield criterion has not yet been met and the combined effect of both creep and plasticity beyond yield. Closed form expressions for the consistent material tangent to be used in both cases are derived which can be used in implicit codes and is expected to help in obtaining optimal convergence rates.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

A general constitutive framework for the combined creep, plasticity and swelling behavior of nuclear fuels in an implicit hypoelastic formulation

This work is motivated by the need to analyze the behavior of nuclear fuels which under normal operating conditions build up stresses due to non-homogeneous thermal expansion, fission gas and solid product swelling among other phenomena that are simultaneously relaxed by creep and plastic flow. This report details the stress and tangent update equations for combined J2 based rate independent plasticity, timehardening creep and fission gas induced swelling e ects in a fully implicit hypo-elastic formulation involving two cases: pure creep without plasticity where the yield criterion has not yet been met and the combined e ect of both creep and plasticity beyond yield. Closed form expressions for the consistent material tangent to be used in both cases are derived which can be used in implicit codes and is expected to help in obtaining optimal convergence rates.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Dakota Driver

This code connects the SANDIA’a C++-based DAKOTA optimization and analyis tool with NASA’s python-based openMDAO systems engineering framework. It allows DAKOTA to be used as an openMDAO “Driver”. DAKOTA contains a wide array of advanced sensitivity, uncertainty quantification, and optimization methods. These are now available in a “pluggable” way to any openMDAO based workflow.

Graf, Peter↗
DOE OSTI2021

Optimal Decision Making in High-Throughput Virtual Screening Pipelines

ABSTRACT Effective selection of the potential candidates that meet certain conditions in a tremendously large search space has been one of the major concerns in many real-world applications. In addition to the nearly infinitely large search space, rigorous evaluation of a sample based on the reliable experimental or computational platform is often prohibitively expensive, making the screening problem more challenging. In such a case, constructing a high-throughput screening (HTS) pipeline that pre-sifts the samples expected to be potential candidates through the efficient earlier stages, results in a significant amount of savings in resources. However, to the best of our knowledge, despite many successful applications, no one has studied optimal pipeline design or optimal pipeline operations. In this study, we propose two optimization frameworks, applying to most (if not all) screening campaigns involving experimental or/and computational evaluations, for optimally determining the screening thresholds of an HTS pipeline. We validate the proposed frameworks on both analytic and practical scenarios. In particular, we consider the optimal computational campaign for the long non-coding RNA (lncRNA) classification as a practical example. To accomplish this, we built the high-throughput virtual screening (HTVS) pipeline for classifying the lncRNA. The simulation results demonstrate that the proposed frameworks significantly reduce the effective selection cost per potential candidate and make the HTS pipelines less sensitive to their structural variations. In addition to the validation, we provide insights on constructing a better HTS pipeline based on the simulation results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Template engine applied to rapid modeling

Modeling complex problems can require a significant effort, be subject to human error, and contain repeated patterns of input. SCALE 6.2 and the Used Nuclear Fuel-Storage, Transportation and Disposal Analysis Resource and Data System (UNF-ST-DARDS) have attempted to mitigate these problems with the use of a template engine and template syntax. The template syntax allows redundant input to be consolidated into its simplest pattern and parameterized on the parts that change, reducing effort and likelihood of errors and encapsulating user experience into a reusable model component. This paper presents a summary of rapid modeling benefits and techniques that are facilitated when using templates. Specifically, this paper will discuss how these are applied in conducting as-loaded spent nuclear fuel canister criticality calculations using UNF-ST-DARDS and model perturbation and sampling using SCALE 6.2. (authors)

42 ENGINEERING↗
DOE OSTI2014

Development of CSG-based radiation shielding module for ARCHER: preliminary results for photons - Paper 126

ARCHER is a parallel Monte Carlo radiation transport code being developed for various hardware platforms including multi-core CPUs, the emerging Nvidia graphics processing units (GPUs) and Intel Xeon Phi coprocessors. Previous studies have demonstrated the accuracy and speed for CT imaging and radiotherapy dosimetry applications. Radiation shielding applications, however, require ARCHER to be more flexible in defining and handling geometries, in addition to the voxel phantom geometries that are commonly used in medical physics calculations. In this paper, we present the development of a general geometry module used for radiation protection and shielding problems in ARCHER. The methods of geometry design and particle transport for the GPUs are introduced. Preliminary results comparing against the MCNP code for cases involving Cs-137 0.662 MeV gammas are reported. The radiation shielding design module of ARCHER has been developed, which supports general geometry setups in the CSG format. The code was implemented using CUDA on Nvidia GPUs, and the performance was benchmarked against the MCNP code for a simple radiation shielding problem. Results showed that ARCHER worked properly and achieved impressive speedup due to highly parallel computing nature of the Nvidia GPUs compared to the MCNP code running on multi-core CPUs. Further optimization of the geometry module will be carried out using advanced geometry structures and variance reduction techniques to improve the precision and performance of ARCHER. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Neutronic design and fuel cycle analysis of a fluoride salt-cooled High Temperature Reactor (FHR)

The Fluoride salt-cooled High temperature Reactor (FHR) is a new Gen IV reactor concept that can operate under near atmospheric pressure circumstances and further enhance the inherent safety. In this study, an FHR core design with 165 megawatts of thermal output (MWth) is proposed. The reactor core employs tri-structural-isotropic (TRISO) particle fuel within prismatic graphite blocks as the basic fuel form, FLiBe (2 {sup 7}LiF-BeF{sub 2}) as the primary coolant, and a three-batch fuel cycle scheme. Sensitivity analyses on various parameters were performed to optimize the cycle length and neutronic parameters. The fuel cycle of this core design was evaluated in detail from 4 aspects: cycle length, power peaking factor (PPF), discharge burnup, and temperature coefficient. It was found that larger fuel channel pitch (FCP) would have a relatively harder neutron spectrum, and yield relatively longer cycle length, lower, better fuel temperature coefficient (FTC), and moderator temperature coefficient (MTC). In addition, burnable poison (BP), Er{sub 2}O{sub 3}, can effectively reduce PPF, hold down the multiplication factor, and more importantly it can improve the MTC. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

OpenACC to FPGA: A Framework for Directive-based High-Performance Reconfigurable Computing

This paper presents a directive-based, high-level programming framework for high-performance reconfigurable computing. It takes a standard, portable OpenACC C program as input and generates a hardware configuration file for execution on FPGAs. We implemented this prototype system using our open-source OpenARC compiler; it performs source-to-source translation and optimization of the input OpenACC program into an OpenCL code, which is further compiled into a FPGA program by the backend Altera Offline OpenCL compiler. Internally, the design of OpenARC uses a high- level intermediate representation that separates concerns of program representation from underlying architectures, which facilitates portability of OpenARC. In fact, this design allowed us to create the OpenACC-to-FPGA translation framework with minimal extensions to our existing system. In addition, we show that our proposed FPGA-specific compiler optimizations and novel OpenACC pragma extensions assist the compiler in generating more efficient FPGA hardware configuration files. Our empirical evaluation on an Altera Stratix V FPGA with eight OpenACC benchmarks demonstrate the benefits of our strategy. To demonstrate the portability of OpenARC, we show results for the same benchmarks executing on other heterogeneous platforms, including NVIDIA GPUs, AMD GPUs, and Intel Xeon Phis. This initial evidence helps support the goal of using a directive-based, high-level programming strategy for performance portability across heterogeneous HPC architectures.

Lee, Seyong↗
DOE OSTI2021

Cost- and Risk-Based Seismic Design Optimization of Nuclear Power Plant Safety Systems

Seismic analysis, design, and qualification of systems, structures, and components (SSCs) is a significant contributor to the capital cost of a nuclear power plant. To reduce capital costs of advanced nuclear power plants and make commercial nuclear energy more competitive, innovations are needed in their structural design and construction, and not just in the reactor core and associated systems. Seismic isolation has been identified as an important cost-cutting technology that enables standardization of equipment across various sites. This paper develops and demonstrates a cost- and risk-based seismic design optimization of a representative safety system in a nuclear power plant with the dual goals of minimizing overnight capital cost and meeting safety goals. The design optimization can also include component seismic isolation, in which case, the optimized design includes a set of equipment that needs to be seismically isolated to minimize capital cost. The open-source codes MASTODON and Dakota are used for seismic probabilistic risk assessment and design optimization, respectively. A generic nuclear facility with a safety system comprising SSCs that are common to nuclear power plants is considered for the demonstration of the design optimization and is assumed to be located at the Idaho National Laboratory site. Generic costs and seismic design cost functions are assumed for the SSCs of the safety system. The sum of the costs of the SSCs is minimized in the optimization process, while the risk of failure of the safety system is provided as a constraint. Furthermore, results show that the optimization process reduces capital costs significantly while automatically prioritizing the safety of SSCs that contribute most to the risk of the safety system.

42 ENGINEERING↗
DOE OSTI2025

Strong Scalability Analysis of the Albany Land Ice code on HPC Architectures

Scalability is a critical factor in High-Performance Computing (HPC), where optimizing resource usage has a direct impact on cost-effectiveness and time-efficiency. This report presents a strong scaling performance study of the Albany Land Ice (ALI) code across different HPC architectures, towards determining the best configuration to use when running large-scale simulation ensembles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2010

Microscopically based energy density functionals for nuclei using the density matrix expansion: Implementation and pre-optimization

In a recent series of articles, Gebremariam, Bogner, and Duguet derived a microscopically based nuclear energy density functional by applying the density matrix expansion (DME) to the Hartree-Fock energy obtained from chiral effective field theory two- and three-nucleon interactions. Owing to the structure of the chiral interactions, each coupling in the DME functional is given as the sum of a coupling constant arising from zero-range contact interactions and a coupling function of the density arising from the finite-range pion exchanges. Because the contact contributions have essentially the same structure as those entering empirical Skyrme functionals, a microscopically guided Skyrme phenomenology has been suggested in which the contact terms in the DME functional are released for optimization to finite-density observables to capture short-range correlation energy contributions from beyond Hartree-Fock. The present article is the first attempt to assess the ability of the newly suggested DME functional, which has a much richer set of density dependencies than traditional Skyrme functionals, to generate sensible and stable results for nuclear applications. The results of the first proof-of-principle calculations are given, and numerous practical issues related to the implementation of the new functional in existing Skyrme codes are discussed. Using a restricted singular value decomposition optimization procedure, it is found that the new DME functional gives numerically stable results and exhibits a small but systematic reduction of our test {chi}{sup 2} function compared to standard Skyrme functionals, thus justifying its suitability for future global optimizations and large-scale calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

GPU Acceleration of Large-Scale Full-Frequency GW Calculations

Many-body perturbation theory is a powerful method to simulate electronic excitations in molecules and materials starting from the output of density functional theory calculations. By implementing the theory efficiently so as to run at scale on the latest leadership high-performance computing systems it is possible to extend the scope of GW calculations. Here, we present a GPU acceleration study of the full-frequency GW method as implemented in the WEST code. Excellent performance is achieved through the use of (i) optimized GPU libraries, e.g., cuFFT and cuBLAS, (ii) a hierarchical parallelization strategy that minimizes CPU-CPU, CPU-GPU, and GPU-GPU data transfer operations, (iii) nonblocking MPI communications that overlap with GPU computations, and (iv) mixed precision in selected portions of the code. A series of performance benchmarks has been carried out on leadership high-performance computing systems, showing a substantial speedup of the GPU-accelerated version of WEST with respect to its CPU version. Good strong and weak scaling is demonstrated using up to 25 920 GPUs. Finally, we showcase the capability of the GPU version of WEST for large-scale, full-frequency GW calculations of realistic systems, e.g., a nanostructure, an interface, and a defect, comprising up to 10 368 valence electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this framework, the project team has focused on optimizing resource allocation for improving numerical models through further code development and experimentation. Related to further code development, we have developed a code prioritization index (CPI) for coupled numerical models. CPI is implemented to effectively improve the predictive capability of the coupled model by increasing the sophistication of constituent codes. In relation to designing new experiments, we investigated the information gained by the addition of each new experiment used for calibration and bias correction of a simulation model. Additionally, the variability of ‘information gain’ through the design domain has been investigated in order to identify the experiment settings where maximum information gain occurs and thus guide the experimenters in the selection of the experiment settings. This idea was extended to evaluate the information gain from each experiment can be improved by intelligently selecting the experiments, leading to the development of the Batch Sequential Design (BSD) technique. Additionally, we evaluated the importance of sufficiently exploring the domain of applicability in experiment-based validation of high-consequence modeling and simulation by developing a new metric to quantify coverage. This metric has also been incorporated into the design of new experiments. Finally, we have proposed a data-aware calibration approach for the calibration of numerical models. This new method considers the complexity of a numerical model (the number of parameters to be calibrated, parameter uncertainty, and form of the model) and seeks to identify the number of experiments necessary to calibrate the model based on the level of sophistication of the physics. The final component in the project team’s work to improve model calibration and validation methods is the incorporation of robustness to non-probabilistic uncertainty in the input parameters. This is an improvement to model validation and uncertainty quantification stemming beyond the originally proposed scope of the project. We have introduced a new metric for incorporating the concept of robustness into experiment-based validation of numerical models. This project has accounted for the graduation of two Ph.D. students (Kendra Van Buren and Josh Hegenderfer) and two M.S. students (Matthew Egeberg and Parker Shields). One of the doctoral students is now working in the nuclear engineering field and the other one is a post-doctoral fellow at the Los Alamos National Laboratory. Additionally, two more Ph.D. students (Garrison Stevens and Tunc Kulaksiz) who are working towards graduation have been supported by this project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Performance Portability Evaluation of Fluid-Structure Interaction Simulations on Heterogeneous Platforms

The rapid proliferation of heterogeneous programming languages and multi-vendor hardware has underscored the critical need to evaluate the performance portability of scientific applications. In this work, we present the systematic porting and optimization of a massively parallel fluid-structure interaction code across multiple heterogeneous programming frameworks for deployment on leadership-class supercomputers from major vendors. Our analysis focuses on at-scale performance for simulations involving hundreds of millions of deformable cells, executed on a combination of CPUs and GPUs spanning thousands of nodes on exascale machines. We benchmark the performance of each implementation, highlighting the trade-offs inherent in adopting diverse programming models. Key insights regarding the portability of CUDA on multi-vendor platforms, the superior multi-core CPU performance from SYCL, and architectural considerations on performance optimization are distilled from our experience, offering guidance to other users of high performance computing based on our findings.

Martin, Aristotle [Duke University]↗
DOE OSTI2025

Cardinal: Seismic and Geoacoustic Array Processing

Data collected via seismic and infrasound array deployments are leveraged in the geosciences to detect and characterize a myriad of natural and anthropogenic sources. These deployments consist of numerous sensors placed in a predetermined configuration to amplify signal strength and improve the efficacy of array processing techniques used to measure signal directionality and waveform coherence. High‐fidelity feature extraction is often predicated on interstation distance as well as the frequency content and wavelength of an incident signal. Numerous array processing softwares analyze data in sequential frequency bands to obtain a more detailed characterization of a signal. However, current algorithms are limited in their ability to determine optimal array configuration for each band. We introduce an open‐source Python code, called Cardinal, to process seismic and infrasound array data in discretized time–frequency space with the option of applying an adaptive array design to determine optimal subarray configuration for each frequency band. To reduce computational time, the array processing step can be run in parallel using multithreading. Furthermore, the software has the capability to aggregate array processing results from different time–frequency pixels to produce separate sets of detections, or families, with added utility via the application of an adaptive semblance threshold, which aids in isolating signals‐of‐interest from coherent background noise. Upon appropriate configuration, Cardinal exhibits the potential to combine distinct seismic and infrasound phases into separate families.

Adaptive Array↗