scholarly journals Refinements of the Pin-Based Pointwise Energy Slowing-Down Method for Resonance Self-Shielding Calculation—I: Theory

2021 ◽  
Vol 9 ◽  
Author(s):  
Sooyoung Choi ◽  
Wonkyeong Kim ◽  
Deokjung Lee
Keyword(s):  
Temperature Profile ◽  
Power Distribution ◽  
Computing Time ◽  
Computation Time ◽  
Collision Probability ◽  
Fuel Pellet ◽  
Slowing Down ◽  
Probability Table ◽  
Equivalence Theory ◽  
Accuracy Assessments

The pin-based pointwise energy slowing-down method (PSM), which is a resonance self-shielding method, has been refined to treat the nonuniformity of material compositions and temperature profile in the fuel pellet by calculating the exact collision probability in the radially subdivided fuel pellet under the isolated system. The PSM has generated the collision probability table before solving the pointwise energy slowing-down equation. It is not exact if the fuel pellet has nonuniform material compositions or temperature profile in all the subdivided regions. In the refined PSM-CPM, the pre-generated table is not required for directly calculating the collision probability in all the subdivided regions of the fuel pellet while solving the slowing-down equation. There are an advantage and a disadvantage to the method. The advantage is to exactly consider the nonuniformity of the material compositions and temperature profile in the fuel pellet. The disadvantage is the longer computing time than that of the PSM when the fuel pellet has more than five subdivided regions. However, in the practical use for UO2 pin-cells, it is still comparable for the computation time with the PSM and the conventional equivalence theory methods. In this article, using simple light water reactor 17 × 17 F A problems with a uniform material composition and temperature profile, it is demonstrated that PSMs (PSM and PSM-CPM) exhibit consistent accuracy in calculating the multiplication factor and the pin power distribution with no compromise in the computation time. More detailed accuracy assessments with various test cases, including problems representing the nonuniformity, are presented in the accompanying article.

scholarly journals Refinements of Pin-Based Pointwise Energy Slowing-Down Method for Resonance Self-Shielding Calculation-II: Verifications

2021 ◽  
Vol 9 ◽  
Author(s):  
Wonkyeong Kim ◽  
Sooyoung Choi ◽  
Deokjung Lee
Keyword(s):  
Temperature Distribution ◽  
Cross Sections ◽  
Reaction Rates ◽  
Collision Probability ◽  
Fuel Pellet ◽  
Test Problems ◽  
Probability Method ◽  
Fuel Temperature ◽  
Slowing Down ◽  
The Difference

The pin-based pointwise energy slowing-down method (PSM) has been refined through eliminating the approximation for using the pre-tabulated collision probability during the slowing-down calculation. A collision probability table is generated by assuming that material composition and temperature are constant in the fuel pellet using the collision probability method (CPM). Refined PSM (PSM-CPM), which calculates the collision probability in the isolated fuel pellet during the slowing-down calculation using CPM, can consider nonuniform material and temperature distribution. For the methods, the extensive comparative analysis is performed with problems representing various possible conditions in a light water reactor (LWR) design. Conditions are categorized with the geometry, material distribution, temperature profile in the fuel pellet, and burnup. With test problems, PSMs (PSM and PSM-CPM) have been compared with conventional methods based on the equivalence theory. With overall calculation results, PSMs show the accuracy in the eigenvalue with differences in the order of 100 pcm compared to the reference results. There was no noticeable difference in the multigroup cross sections, reaction rates, and pin power distributions. However, PSM-CPM maintains the accuracy in the calculation of the fuel temperature coefficient under the condition with 200% power and nonuniform temperature distribution in the fuel pellet. PSM shows the difference in the eigenvalue in the order of 2,000 pcm for the fictitious pin-cell problem with highly steep temperature profiles and material compositions, but PSM-CPM shows the difference in the eigenvalue within 100 pcm.

Neutronic Analysis of Accident-Tolerant Fuel Assemblies With Silicon Carbide Cladding in Pressurized Water Reactors

2017 ◽  
Author(s):  
Zhixiong Tan ◽  
Jiejin Cai
Keyword(s):  
Silicon Carbide ◽  
Fuel Assembly ◽  
Power Distribution ◽  
Safety Margin ◽  
Severe Accident ◽  
Pressurized Water Reactors ◽  
Fuel Pellet ◽  
Pressurized Water ◽  
Neutronic Parameters ◽  
Water Reactors

After Fukushima Daiichi Nuclear Power Plant accident, alternative fuel-design to enhance tolerance for severe accident conditions becomes particularly important. Silicon carbide (SiC) cladding fuel assembly gain more safety margin as novel accident tolerant fuel. This paper focuses on the neutron properties of SiC cladding fuel assembly in pressurized water reactors. Annular fuel pellet was adopted in this paper. Two types of silicon carbide assemblies were evaluated via using lattice calculation code “dragon”. Type one was consisted of 0.057cm SiC cladding and conventional fuel. Type two was consisted of 0.089cm SiC cladding and BeO/UO2 fuel. Compared the results of SiC cladding fuel assembly neutronic parameters with conventional Zircaloy cladding fuel assembly, this paper analyzed the safety of neutronic parameters performance. Results demonstrate that assembly-level reactivity coefficient is kept negative, meanwhile, the numerical value got a relatively decrease. Other parameters are conformed to the design-limiting requirement. SiC kinds cladding show more flat power distribution. SiC cases also show the ability of reducing the enrichment of fuel pellets even though it has higher xenon concentration. These types of assembly have broadly agreement neutron performance with the conventional cladding fuel, which confirmed the acceptability of SiC cladding in the way of neutron physics analysis.

scholarly journals Coarse-grained tight-binding models

2021 ◽  
Author(s):  
Tianxiang Liu ◽  
Li Mao ◽  
Mats-Erik Pistol ◽  
Craig Pryor
Keyword(s):  
Quantum Well ◽  
Computing Time ◽  
Numerical Test ◽  
Tight Binding ◽  
Computation Time ◽  
Coarse Grained ◽  
Weakly Bound ◽  
Trade Offs ◽  
Full Calculation ◽  
Binding Models

Abstract Calculating the electronic structure of systems involving very different length scales presents a challenge. Empirical atomistic descriptions such as pseudopotentials or tight-binding models allow one to calculate the effects of atomic placements, but the computational burden increases rapidly with the size of the system, limiting the ability to treat weakly bound extended electronic states. Here we propose a new method to connect atomistic and quasi-continuous models, thus speeding up tight-binding calculations for large systems. We divide a structure into blocks consisting of several unit cells which we diagonalize individually. We then construct a tight-binding Hamiltonian for the full structure using a truncated basis for the blocks, ignoring states having large energy eigenvalues and retaining states with an energy close to the band edge energies. A numerical test using a GaAs/AlAs quantum well shows the computation time can be decreased to less than 5% of the full calculation with errors of less than 1%. We give data for the trade-offs between computing time and loss of accuracy. We also tested calculations of the density of states for a GaAs/AlAs quantum well and find a ten times speedup without much loss in accuracy.

Fast acquisition aperture correction in prestack depth migration using beamlet decomposition

Geophysics ◽  
2009 ◽  
Vol 74 (4) ◽  
pp. S67-S74 ◽  
Author(s):  
Jun Cao ◽  
Ru-Shan Wu
Keyword(s):  
Wave Equation ◽  
Correction Factor ◽  
Computing Time ◽  
Computation Time ◽  
Prestack Depth Migration ◽  
Depth Migration ◽  
Wavenumber Domain ◽  
Amplitude Correction ◽  
Local Wavenumber ◽  
Local Angle

Wave-equation-based acquisition aperture correction in the local angle domain can improve image amplitude significantly in prestack depth migration. However, its original implementation is inefficient because the wavefield decomposition uses the local slant stack (LSS), which is demanding computationally. We propose a faster method to obtain the image and amplitude correction factor in the local angle domain using beamlet decomposition in the local wavenumber domain. For a given frequency, the image matrix in the local wavenumber domain for all shots can be calculated efficiently. We then transform the shot-summed image matrix from the local wavenumber domain to the local angle domain (LAD). The LAD amplitude correction factor can be obtained with a similar strategy. Having a calculated image and correction factor, one can apply similar acquisition aperture corrections to the original LSS-based method. For the new implementation, we compare the accuracy and efficiency of two beamlet decompositions: Gabor-Daubechies frame (GDF) and local exponential frame (LEF). With both decompositions, our method produces results similar to the original LSS-based method. However, our method can be more than twice as fast as LSS and cost only twice the computation time of traditional one-way wave-equation-based migrations. The results from GDF decomposition are superior to those from LEF decomposition in terms of artifacts, although GDF requires a little more computing time.

Porous Media Modeling of Two-Phase Microchannel Cooling of Electronic Chips With Nonuniform Power Distribution

2014 ◽  
Vol 136 (2) ◽  
Author(s):  
Jun Jie Liu ◽  
Hua Zhang ◽  
S. C. Yao ◽  
Yubai Li
Keyword(s):  
Porous Media ◽  
Mass Flow ◽  
Flow Rate ◽  
Power Distribution ◽  
Heat Load ◽  
Computation Time ◽  
High Heat ◽  
Two Phase ◽  
Flow Rates ◽  
Microchannel Cooling

Compared to single-phase heat transfer, two-phase microchannel heat sinks utilize latent heat to reduce the needed flow rate and to maintain a rather uniform temperature close to the boiling temperature. The challenge in the application of cooling for electronic chips is the necessity of modeling a large number of microchannels using large number of meshes and extensive computation time. In the present study, a modified porous media method modeling of two-phase flow in microchannels is performed. Compared with conjugate method, which considers individual channels and walls, it saves computation effort and provides a more convenient means to perform optimization of channel geometry. The porous media simulation is applied to a real chip. The channels of high heat load will have higher qualities, larger flow resistances, and lower flow rates. At a constant available pressure drop over the channels, the low heat load channels show much higher mass flow rates than needed. To avoid this flow maldistribution, the channel widths on a chip are adjusted to ensure that the exit qualities and mass flow rate of channels are more uniform. As a result, the total flow rate on the chip is drastically reduced, and the temperature gradient is also minimized. However, it only gives a relatively small reduction on the maximum surface temperature of chip.

scholarly journals SparkRA: Enabling Big Data Scalability for the GATK RNA-seq Pipeline with Apache Spark

Genes ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 53
Author(s):  
Zaid Al-Ars ◽  
Saiyi Wang ◽  
Hamid Mushtaq
Keyword(s):  
Low Cost ◽  
Computing Time ◽  
Scale Up ◽  
Variant Calling ◽  
Computation Time ◽  
Apache Spark ◽  
Rna Seq ◽  
Single Node ◽  
Practical Applications ◽  
Computational Resources

The rapid proliferation of low-cost RNA-seq data has resulted in a growing interest in RNA analysis techniques for various applications, ranging from identifying genotype–phenotype relationships to validating discoveries of other analysis results. However, many practical applications in this field are limited by the available computational resources and associated long computing time needed to perform the analysis. GATK has a popular best practices pipeline specifically designed for variant calling RNA-seq analysis. Some tools in this pipeline are not optimized to scale the analysis to multiple processors or compute nodes efficiently, thereby limiting their ability to process large datasets. In this paper, we present SparkRA, an Apache Spark based pipeline to efficiently scale up the GATK RNA-seq variant calling pipeline on multiple cores in one node or in a large cluster. On a single node with 20 hyper-threaded cores, the original pipeline runs for more than 5 h to process a dataset of 32 GB. In contrast, SparkRA is able to reduce the overall computation time of the pipeline on the same single node by about 4×, reducing the computation time down to 1.3 h. On a cluster with 16 nodes (each with eight single-threaded cores), SparkRA is able to further reduce this computation time by 7.7× compared to a single node. Compared to other scalable state-of-the-art solutions, SparkRA is 1.2× faster while achieving the same accuracy of the results.

scholarly journals A Fast and Efficient Lossless Compression Technique for Greyscale Images

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Compression Ratio ◽  
Service Providers ◽  
Computing Time ◽  
Computation Time ◽  
Lossless Compression ◽  
Medical Data ◽  
Compression Technique ◽  
Scanning Method ◽  
Remote Healthcare ◽  
Encoding Method

The growth of cloud based remote healthcare and diagnosis services has resulted, Medical Service Providers (MSP) to share diagnositic data across diverse environement. This medical data are accessed across diverse platforms, such as, mobile and web services which needs huge memory for storage. Compression technique helps to address and solve storage requirements and provides for sharing medical data over transmission medium. Loss of data is not acceptable for medical image processing. As a result, this work considers lossless compression for medical in particular and in general any greyscale images. Modified Huffman encoding (MH) is one of the widely used technique for achieving lossless compression. However, due to longer bit length of codewords the existing Modified Huffman (MH) encoding technique is not efficient for medical imaging processing. Firstly, this work presents Modified Refined Huffman (MRH) for performing compression of greyscale and binary images by using diagonal scanning method. Secondly, to minimize the computing time parallel encoding method is used. Experiments are conducted for wide variety of images and performance is evaluated in terms of Compression Ratio, Computation Time and Memory Utilization. The proposed MRH achieves significant performance improvement in terms of Compression Ratio, Computation Time and Memory Usage over its state-of-the-art techniques, such as, LZW, CCITT G4, JBIG2 and Levenberg–Marquardt (LM) Neural Network algorithm. The overall results achieved show the applicability of MRH for different application services.

scholarly journals Particle Generation to Minimize the Computing Time of the Discrete Element Method for Particle Packing Simulation

2021 ◽  
Author(s):  
Jinsu Nam ◽  
Jaehee Lyu ◽  
Junyoung Park
Keyword(s):  
Computing Time ◽  
Computation Time ◽  
Coarse Graining ◽  
Particle Packing ◽  
Particle Generation ◽  
Powder Packing ◽  
Packing Model ◽  
Contact Models ◽  
Size Of Particles ◽  
Simulation Time

Abstract There are computation time constraints caused by the number and size of particles in the powder packing simulation using DEM. In this paper, newly suggested packing model transforms a general packing sequence –particle generation, stack, and compression – into particle generation and packing by growing particles. To verify the new packing model, it was compared using three contact models widely used in DEM, in terms of Radial Distribution Function, porosity, and Coordination Number. As a result, contact between particles showed a similar trend, and the pore distribution was also similar. Using the new packing model can reduce simulation time by 400% compared to the normal packing model without any other coarse graining methods. This model has only been applied to particle packing simulations in this paper, but it can be expanded to other simulations with complex domain based on DEM.

Sign in / Sign up

Export Citation Format

Share Document