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Generation Process and Analysis of Innovative Timberfabric Vaults

STRUCTURAL ENGINEERING INTERNATIONAL 2014年第2期24卷 254-264页

作者： Albenque, Etienne Hudert, Markus Humbert, Laurent Weinand, Yves Ecole Polytech Fed Lausanne Lab Timber Construct IBOIS Lausanne Switzerland

Timberfabric structures, developed at IBOIS, are a new family of timber constructions based on the logic and principles of man-made fabrics. Modular elements called "timberfabric modules" are generated by curving and connecting two thin wooden panels. This paper concerns the study of vaults obtained by assembling together several timberfabric modules. A parametric tool is presented which can generate automatically a three-dimensional (3D) finite element model of a structure for a given set of initial parameters. This tool assists the architectural design of such structures, providing insights into their geometry as well as into the construction stresses and the kinematic constraints between different constitutive elements.

关键词： timberfabric vaults innovative structures python script generative algorithm assembly process

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REMOTE ESTIMATION OF A MANAGED PINE FOREST EVAPOTRANSPIRATION WITH GEOSPATIAL TECHNOLOGY

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TRANSACTIONS OF THE ASABE 2016年第6期59卷 1695-1705页

作者： Panda, S. Amatya, D. M. Sun, G. Bowman, A. Univ North Georgia Inst Environm Spatial Anal 3820 Mundy Mill Rd Oakwood GA 30566 USA US Forest Serv USDA Ctr Forested Wetlands Res Cordesville SC USA US Forest Serv USDA Eastern Forest Environm Threat Assessment Ctr Raleigh NC USA

Remote sensing has increasingly been used to estimate evapotranspiration (ET) and its supporting parameters in a rapid, accurate, and cost-effective manner. The goal of this study was to develop remote sensing-based models for estimating ET and the biophysical parameters canopy conductance (g(c)), upper-canopy temperature, and soil moisture for a mature loblolly pine forest (Pinus taeda L.) in the Parker Tract in eastern North Carolina. To validate the remote sensing approach, we acquired long-term on-site eddy flux measurements, including micrometeorological variables and water and energy fluxes. Other measured and derived ET-associated parameters include forest g(c), leaf area index, canopy absorbed radiation, canopy temperature, and soil moisture. Multi-temporal cloud-free (<= 10% cloud cover) Landsat 7 ETM+ satellite images from 2006-2012 were acquired. Field data for the 2 h (12: 00 noon to 2: 00 p.m.) means were used in the model, coinciding with the image acquisition time. Individual Landsat bands (1 through 7) and developed image vegetation indices (NDVI, SAVI, and VVI) for the study site were obtained through automated geospatial models and were correlated to measured ET flux and related parameters. An excellent coefficient of determination (R-2 = 0.93, n = 42) was obtained for the upper-canopy temperature versus band 6 (thermal infrared) model. However, a low correlation (R-2 = 0.36, n = 6) was obtained for gc versus band 5 (mid-infrared) model. The correlation for soil moisture versus band 7 was poor (R-2 = 0.05, n = 42), perhaps due to heavy canopy and pine litter ground cover. However, the ET estimation model with multiple image information variables, such as bands 5 and 7, provided a good correlation (R-2 = 0.55, n = 35) with less spatial and temporal variation in the datasets, along with no data mining application in model building. Therefore, this study suggests that the remote sensing approach is promising for estimating ET with good accuracy (avera

关键词： Canopy conductance Canopy temperature Evapotranspiration Model builder NDVI python script SAVI Soil moisture Spatial analysis VVI

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A machine learning approach to predict the stress results of quadratic tetrahedral elements

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2022年第2期236卷 1128-1135页

作者： Mahesh, S. Marco, Schiffel Sharma, Ramesh S. Praveenkumar, M. K. Wadagavi, Vishal Subbarao, Lakshminarasimhan RV Coll Engn Dept Mech Engn Bangalore 560059 Karnataka India Robert Bosch Automot Steering Schwabisch Gmund Germany Robert Bosch Engn & Business Solut Pvt Ltd Bangalore Karnataka India

Industries are always looking for an effective and efficient way to reduce the computation time of simulation because of the huge expenditure involved. From basics of Finite Element Method (FEM), it is known that, linear order finite elements consume less computation time and are less accurate compared to higher order finite elements say quadratic elements. An approach to get the benefit of less computation cost of linear elements and the good accuracy of quadratic elements can be of a good thought. The methodology to get the accurate results of quadratic elements with the advantage of less simulation run time of linear elements is presented here. Machine Learning (ML) algorithms are found to be effective in making predictions based on some known data set. The present paper discusses a methodology to implement ML model to predict the results equivalent to that of quadratic elements based on the solutions obtained from the linear elements. Here, a ML model is developed using python code, the stress results from Finite Element (FE) model of linear tetrahedral elements is given as the input to it to predict the stress results of quadratic tetrahedral elements. Abaqus is used as the FEM tool to develop the FE models. A python script is used to extract the stresses and the corresponding node numbers. The results showed that the developed ML model is successful in prediction of the accurate stress results for the set of test data. The scatter plots showed that the Z-score method was effective in removing the singularities. The proposed methodology is effective to reduce the computation time for simulation.

关键词： Finite Element Method Machine Learning Abaqus python script linear and quadratic tetrahedral elements

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McCARD for neutronics design and analysis of research reactor cores

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ANNALS OF NUCLEAR ENERGY 2015年 82卷 48-53页

作者： Shim, Hyung Jin Park, Ho Jin Kwon, Soonwoo Seo, Geon Ho Kim, Chang Hyo Seoul Natl Univ Seoul 151744 South Korea Korea Atom Energy Res Inst Daejeon 305353 South Korea

McCARD is a Monte Carlo (MC) neutron photon transport simulation code developed exclusively for the neutronics design and analysis of nuclear reactor cores. McCARD is equipped with the hierarchical modeling and scripting functions, the CAD-based geometry processing module, the adjoint-weighted kinetics parameter and source multiplication factor estimation modules as well as the burnup analysis capability for the neutronics design and analysis of both research and power reactor cores. This paper highlights applicability of McCARD for the research reactor core neutronics analysis, as demonstrated for Kyoto University Critical Assembly, HANARO, and YALINA. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： McCARD Research reactor python script CAD-based geometry processing Kinetics parameter

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Exploring simple K-means clustering algorithm for automating segregation of colors in leaf of Axonopus compressus: Towards maintenance of an urban landscape

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021年第1期40卷 1219-1243页

作者： Singh, Lovepreet Huang, He Bordoloi, Sanandam Garg, Ankit Jiang, Mingjie Shantou Univ Dept Civil & Environm Engn Shantou Peoples R China Indian Inst Technol Dept Comp Sci & Engn Gandhinagar India IIT Guwahati Dept Civil Engn Gauhati India Guangxi Univ Dept Civil Engn & Architecture Nanning Peoples R China

Images of green infrastructure (gardens, green corridor, green roofs and grasslands) large area can be captured and processed to provide spatial and temporal variation in colours of plant leaves. This may indicate average variation in plant growth over large urban landscape (community gardens, green corridor etc). Towards this direction, this short technical note explores development of a simple automated machine learning program that can accurately segregate colors from plant leaves. In this newly developed program, a machine learning algorithm has been modified and adapted to give the proportion of different colors present in a leaf. python script is developed for an image processing. For validation, experiments are conducted in green house to grow Axonopus compressus. script first extracts different RGB (Red Green and Blue) colors present in the leaf using the K-means clustering algorithm. Appropriate centroids required for the clusters of leaf colors are formed by the K-means algorithm. The new program provides saves computation time and gives output in form of different colors proportion as a CSV (Comma-Separated Values) file. This study is the first step towards the demonstration of using automated programs for the segregation of colors from the leaf in order to access the growth of the plant in an urban landscape.

关键词： Color segregation K-means algorithm automation cluster analysis python script

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ParaView visualization of Abaqus output on the mechanical deformation of complex microstructures

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COMPUTERS & GEOSCIENCES 2017年 99卷 135-144页

作者： Liu, Qingbin Li, Jiang Liu, Jie Peking Univ Sch Earth & Space Sci Beijing 100871 Peoples R China Sun Yat Sen Univ Sch Earth Sci & Geol Engn Guangzhou 510275 Guangdong Peoples R China Natl Supercomp Ctr Guangzhou Guangzhou 510006 Guangdong Peoples R China Guangdong Prov Key Lab Mineral Resources & Geol P Guangzhou 510275 Guangdong Peoples R China

Abaqus (R) is a popular software suite for finite element analysis. It delivers linear and nonlinear analyses of mechanical and fluid dynamics, includes multi-body system and multi-physics coupling. However, the visualization capability of Abaqus using its CAE module is limited. Models from microtomography have extremely complicated structures, and datasets of Abaqus output are huge, requiring a visualization tool more powerful than Abaqus/CAE. We convert Abaqus output into the XML-based VTK format by developing a python script and then using ParaView to visualize the results. Such capabilities as volume rendering, tensor glyphs, superior animation and other filters allow ParaView to offer excellent visualizing manifestations. ParaView's parallel visualization makes it possible to visualize very big data. To support full parallel visualization, the python script achieves data partitioning by reorganizing all nodes, elements and the corresponding results on those nodes and elements. The data partition scheme minimizes data redundancy and works efficiently. Given its good readability and extendibility, the script can be extended to the processing of more different problems in Abaqus. We share the script with Abaqus users on GitHub.

关键词： Abaqus (R) Post-processing python script ParaView Parallel visualization

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A GIS method for volumetric assessments of erosion rills from digital surface models

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EUROPEAN JOURNAL OF REMOTE SENSING 2019年第sup1期52卷 96-107页

作者： Bacova, Marketa Krasa, Josef Devaty, Jan Kavka, Petr Czech Tech Univ Dept Landscape Water Conservat Prague Czech Republic

Modern non-contact methods for data acquisition are becoming widely used for monitoring soil erosion and for assessing soil degradation after rainfall events. Photogrammetric methods are especially favored to obtain a detailed and precise digital surface model (DSM) of the surveyed area. This paper introduces the algorithm and its python implementation as a tool for ArcGIS software, which makes efficient automatic calculations of the volume of erosion rills or gullies. The input parameters are a DSM, and the rill edge polygon. The method was tested on an artificially created rill, where the result acquired using presented method was compared to the real volume. The comparison showed that the algorithm may underestimate the volume by 10-15%. In addition, the influence of the position of the rill edge polygon was tested on two DSMs of erosion rills. The resulting volumes of the rills, calculated on the basis of eight different edge polygons, varied by 5%. The algorithm also automates interpolation of the surface prior to erosion, which simplifies its usage in firstly monitored regions. The algorithm can also be used for volumetric analyses in other research areas and it is made available as a supplement of the publication.

关键词： Soil erosion rill volume DSM photogrammetry python script GIS

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The python Book 2Nd Edition

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2017年

The python Book 2Nd Edition by published by

关键词： book create book python book work code code listing command create def edition file function import kunaldeo staff linux user module poker dice print python python book python script resources python

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Calibrating microparameters of DEM models by using CEM, DE, EFO, MFO, SSO algorithms and the optimal hyperparameters

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COMPUTATIONAL PARTICLE MECHANICS 2024年第2期11卷 839-852页

作者： Wang, Min Lu, Zhenxing Zhao, Yanlin Wan, Wen Hunan Univ Sci & Technol Sch Mech Engn Xiangtan Peoples R China Hunan Univ Sci & Technol Sch Resource Environm & Safety Engn Xiangtan Peoples R China

The Particle Flow Code is a typical DEM numerical software;however, the microparameters of DEM models need to be calibrated before numerical simulation. In most cases, the trial-and-error method is used;however, it takes a great deal of time and the results depend on the researchers' experience. To address this issue, the cross-entropy method (CEM), differential evolution (DE), electromagnetic field optimization (EFO), moth-flame optimization (MFO) and salp swarm optimization (SSO) algorithm have been used for microparameters calibration. We provide a numerical simulation example to verify the validity of these microparameter calibration methods;it turns out that the number of iterations was large. To reduce the computational effort of obtaining suitable microparameters of the DEM model, we determine the optimal hyperparameters of the CEM, DE, EFO, MFO and SSO microparameter calibrating techniques. Through the analysis of the results, the number of iterations of these algorithms was markedly reduced. Considering the number of iterations, the number of hyperparameters and the results of numerical simulation, we suggest SSO algorithm for microparameter calibration. We also give another numerical simulation example to verify the validity of the proposed method. We found that the number of iterations for obtaining suitable microparameters was less than 100, and only 1 hyperparameter needed to be determined. Compared with previous studies, the number of iterations decreased remarkably.

关键词： DEM Microparameter calibration Particle Flow Code (PFC) python script Optimal hyperparameters

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International chemical identifier for reactions (RInChI)

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JOURNAL OF CHEMINFORMATICS 2013年第1期5卷 1-9页

作者： Grethe, Guenter Goodman, Jonathan M. Allen, Chad H. G. Univ Cambridge Dept Chem Cambridge CB2 1EW England

The IUPAC International Chemical Identifier (InChI) provides a method to generate a unique text descriptor of molecular structures. Building on this work, we report a process to generate a unique text descriptor for reactions, RInChI. By carefully selecting the information that is included and by ordering the data carefully, different scientists studying the same reaction should produce the same RInChI. If differences arise, these are most likely the minor layers of the InChI, and so may be readily handled. RInChI provides a concise description of the key data in a chemical reaction, and will help enable the rapid searching and analysis of reaction databases.

关键词： Minor Layer python script Multistep Reaction Benzofuran Derivative Reaction Diagram

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