Journal articles: 'Python scripting'

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Hinsen, Konrad. "Parallel Scripting with Python." Computing in Science & Engineering 9, no. 6 (November 2007): 82–89. http://dx.doi.org/10.1109/mcse.2007.117.

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Bakker, Mark. "Python Scripting: The Return to Programming." Groundwater 52, no. 6 (September 16, 2014): 821–22. http://dx.doi.org/10.1111/gwat.12269.

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Dixon, Adam P. "Review of GIS Tutorial for Python Scripting." Cartographic Perspectives, no. 80 (August 18, 2015): 51–52. http://dx.doi.org/10.14714/cp80.1306.

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Ayer, Vidya M., Sheila Miguez, and Brian H. Toby. "Why scientists should learn to program in Python." Powder Diffraction 29, S2 (December 2014): S48—S64. http://dx.doi.org/10.1017/s0885715614000931.

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The importance of software continues to grow for all areas of scientific research, no less for powder diffraction. Knowing how to program a computer is a basic and useful skill for scientists. This paper explains the three approaches for programming languages and why scripting languages are preferred for non-expert programmers. The Python-scripting language is extremely efficient for science and its use by scientists is growing. Python is also one of the easiest languages to learn. The language is introduced, as well as a few of the many add-on packages available that extend its capabilities, for example, for numerical computations, scientific graphics, and graphical user interface programming. Resources for learning Python are also provided.

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Bakker, M., V. Post, C. D. Langevin, J. D. Hughes, J. T. White, J. J. Starn, and M. N. Fienen. "Scripting MODFLOW Model Development Using Python and FloPy." Groundwater 54, no. 5 (March 30, 2016): 733–39. http://dx.doi.org/10.1111/gwat.12413.

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Murfitt, M. F., C. E. Meyer, G. Skone, N. Dellby, and O. L. Krivanek. "Open-Source Python Scripting and Analysis with Nion Swift." Microscopy and Microanalysis 19, S2 (August 2013): 782–83. http://dx.doi.org/10.1017/s1431927613005904.

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Myers, Wayne L. "Scalable Shared Scripting for Spatial Structure of Regionalized Ratings." Land 10, no. 8 (August 16, 2021): 859. http://dx.doi.org/10.3390/land10080859.

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Incisive inquiry involving indicators of ecological and environmental integrity entails exploration of spatial structure at selected scales from landscape level to regional regimes. Conventional colorization of digital displays provides perspective but is largely lacking for localization, elaboration, and explication. An overall objective for recent research is explicit extraction of spatial structure as hyper-hills and proximal propensity. Shared scripting as a computational configuration affords analytical advantage, adaptability and availability. Conservation context captures challenges of changing conditions for complex components at several spatial scales. Hyper-hill hypotheses, relativized ratings, and post patterned nucleated networks supporting secondary scaling scenarios are current contributions. Computational concerns in indicant informatics are also addressed. Retrospective results are cogent comparators for change. Shared scripting couples R software with Python as R||Python (R in parallel with Python), which is supplemented by strategic sequencing of compilation capabilities in general GIS (geographic information systems). The specific research question(s) is/are what is the particular pattern of placement and propagation in intensification of an indicant of biodiversity (avian species richness), and how does this relate to some other co-located indicants of environmental effects. This is addressed in a legacy dataset for Pennsylvania, USA. Emergent emphasis is on truncated trees of topology and impaneled indicators. Shareable software has HIDN (hexagonal indicant dual networking) as an aggregate acronym with duly drawn disclaimers.

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Westad, Frank, Lars Gidskehaug, and Chuck Miller. "The best of two worlds." NIR news 31, no. 5-6 (August 19, 2020): 34–39. http://dx.doi.org/10.1177/0960336020944008.

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With the latest release of Unscrambler, Camo Analytics introduced support for Python scripting, giving users the best of two worlds. This Python extension allows users to tap into the vast ecosystem of Data Science tools that are continually being produced in the Python community, while still leveraging the familiar data handling, validation and visualization features of Unscrambler – all contained within a fully compliant framework. This paper discusses the value propositions that the Python extension can provide to Unscrambler users, and follows this up with some specific examples of common workflows that are enabled by this extension: Data Importing, Spectral Preprocessing and Innovative Modeling methods.

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O'Donnell, Jackson H., Robert B. Von Dreele, Maria K. Y. Chan, and Brian H. Toby. "A scripting interface for GSAS-II." Journal of Applied Crystallography 51, no. 4 (July 23, 2018): 1244–50. http://dx.doi.org/10.1107/s1600576718008075.

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The GSAS-II suite is a complete crystallographic analysis package for all types of X-ray and neutron diffraction data, suited for fitting models ranging from simple materials to proteins, and designed around an integrated graphical user interface. This article describes a new module within GSAS-II, GSASIIscriptable, which provides access to the GSAS-II data structures and an extensible mechanism to run a significant fraction of GSAS-II functionality, particularly for powder diffraction applications, from within Python scripts or directly from commands in a shell/batch script. This allows parallelization in a high-performance computing environment; near ideal speedup is seen with up to 240 simultaneous processes.

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Mihăilă, Paul, Titus Bălan, Radu Curpen, and Florin Sandu. "Network Automation and Abstraction using Python Programming Methods." MACRo 2015 2, no. 1 (October 1, 2017): 95–103. http://dx.doi.org/10.1515/macro-2017-0011.

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AbstractNetwork programmability is a trend, enhanced and inspired by Software Defined Networks, that are based on scripting methods and standard programming languages used for controlling and monitoring of network elements. This paper is illustrating some new methods in configuring network devices by using automation, reducing time for equipment configuration and easier maintenance. It also improves network security by recognizing and fixing security vulnerabilities and it increases the network stability. These methods represent the future of networks, allowing the management of an increased number of devices in a unitary way.

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Yavuz, Hande. "Computation of dimensional variations on the structural analysis of multi-cell aircraft box beams with python scripting." Aircraft Engineering and Aerospace Technology 93, no. 5 (June 10, 2021): 880–87. http://dx.doi.org/10.1108/aeat-03-2021-0077.

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Purpose Python codes are developed for the versatile structural analysis on a 3 spar multi-cell box beam by means of idealization approach. Design/methodology/approach Shear flow distribution, stiffener loads, location of shear center and location of geometric center are computed via numpy module. Data visualization is performed by using Matplotlib module. Findings Python scripts are developed for the structural analysis of multi-cell box beams in lieu of long hand solutions. In-house developed python codes are made available to be used with finite element analysis for verification purposes. Originality/value The use of python scripts for the structural analysis provides prompt visualization, especially once dimensional variations are concerned in the frame of aircraft structural design. The developed python scripts would serve as a practical tool that is widely applicable to various multi-cell wing boxes for stiffness purposes. This would be further extended to the structural integrity problems to cover the effect of gaps and/or cut-outs in shear flow distribution in box-beams.

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Guidi, G., C. Vecchi, N. Maffei, G. Gottardi, M. G. Mistretta, G. Baldazzi, and T. Costi. "PO-0923: Deformable registration using python scripting for adaptive RT automation." Radiotherapy and Oncology 111 (2014): S116. http://dx.doi.org/10.1016/s0167-8140(15)31041-0.

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Dysarz, Tomasz. "Application of Python Scripting Techniques for Control and Automation of HEC-RAS Simulations." Water 10, no. 10 (October 2, 2018): 1382. http://dx.doi.org/10.3390/w10101382.

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The purpose of the paper was to present selected techniques for the control of river flow and sediment transport computations with the programming language Python. The base software for modeling of river processes was the well-known and widely used HEC-RAS. The concepts were tested on two models created for a single reach of the Warta river located in the central part of Poland. The ideas described were illustrated with three examples. The first was a basic simulation of a steady flow run from the Python script. The second example presented automatic calibration of model roughness coefficients with Nelder-Mead simplex from the SciPy module. In the third example, the sediment transport was controlled by Python script. Sediment samples were accessed and changed in the sediment data file stored in XML format. The results of the sediment simulation were read from HDF5 files. The presented techniques showed good effectiveness of this approach. The paper compared the developed techniques with other, earlier approaches to control of HEC-RAS computations. Possible further developments were also discussed.

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Kraft, P., S. Multsch, K. B. Vaché, H. G. Frede, and L. Breuer. "Using Python as a coupling platform for integrated catchment models." Advances in Geosciences 27 (August 25, 2010): 51–56. http://dx.doi.org/10.5194/adgeo-27-51-2010.

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Abstract. Interdisciplinary sharing of knowledge is a key for understanding matter fluxes in landscapes. However, models of transport and reactive fluxes from different disciplines need to work seamlessly together, to capture the tight feedback loops between different compartments and process domains of a landscape. Techniques to facilitate the integration of model codes for integrated catchment modelling exist, but are still scarcely used. In this paper, we are testing a scripting language, Python as a model coupling platform, and demonstrates effects of feedback loops on a virtual agriculturally used hillslope.

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Petrova, N. K., A. P. Mukhachev, A. A. Zagidullin, and S. M. Koutsenko. "Creating an Electronic Course on Programming in Python for the Android Platform." Programmnaya Ingeneria 12, no. 4 (July 14, 2021): 216–22. http://dx.doi.org/10.17587/prin.12.216-222.

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The description and principles of developing a mobile application for the Android platform that provides free access to electronic courses on teaching the basic structures of the Python language and the construction of template programming algorithms based on them are presented. The content of the course is based on the principle of comparative analysis with the C++ language, one of the goals of which is to differentiate the tasks for which it is more efficient to use either the Python scripting language or the C++ compiler. The developed application is logically integral, allows the possibility of supplementing with new data — examples, types of algorithms — and, no less important, is free.

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Sauter, Nicholas K., Johan Hattne, Ralf W. Grosse-Kunstleve, and Nathaniel Echols. "New Python-based methods for data processing." Acta Crystallographica Section D Biological Crystallography 69, no. 7 (June 18, 2013): 1274–82. http://dx.doi.org/10.1107/s0907444913000863.

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Current pixel-array detectors produce diffraction images at extreme data rates (of up to 2 TB h−1) that make severe demands on computational resources. New multiprocessing frameworks are required to achieve rapid data analysis, as it is important to be able to inspect the data quickly in order to guide the experiment in real time. By utilizing readily available web-serving tools that interact with the Python scripting language, it was possible to implement a high-throughput Bragg-spot analyzer (cctbx.spotfinder) that is presently in use at numerous synchrotron-radiation beamlines. Similarly, Python interoperability enabled the production of a new data-reduction package (cctbx.xfel) for serial femtosecond crystallography experiments at the Linac Coherent Light Source (LCLS). Future data-reduction efforts will need to focus on specialized problems such as the treatment of diffraction spots on interleaved lattices arising from multi-crystal specimens. In these challenging cases, accurate modeling of close-lying Bragg spots could benefit from the high-performance computing capabilities of graphics-processing units.

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Yeda, Lian, Zhang Bing, and Wu Renqiang. "Application of Python language in UOE molding simulation of pipeline steel." MATEC Web of Conferences 242 (2018): 01018. http://dx.doi.org/10.1051/matecconf/201824201018.

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The ABAQUS plug-in interface based on Python language realizes geometrical design and automatic modeling of gas pipeline UOE molding, which solves the cumbersome problem of manually building complexgeometric models. In this study, the algorithm for different sizes of pipelines corresponding to different molds was designed. At the same time, as the ABAQUS kernel scripting program was written, a GUI interface was developed. The interface was used to realize automatic modeling and analysis and control of the calculation work, which laid a solid foundation for practical engineering application analysis.

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Savić, Filip, and Milan Vidaković. "Интеграција Mainflux платформе у систем за управљање енергетском потрошњом у паметној кући." Zbornik radova Fakulteta tehničkih nauka u Novom Sadu 36, no. 07 (June 26, 2021): 1167–70. http://dx.doi.org/10.24867/13be02savic.

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Zadatak rada jeste integracija Mainflux platforme u sistem za upravljanje energetskom potrošnjom u pametnoj kući. Mainflux platforma je korišćena zajedno sa Bash scripting-om da obezbijedi dostupnost podataka potrebnih za generisanje realne potrošnje električne energije. Simulacija je rađena pomoću Typhoon HIL softvera. Python programski jezik je korišćen za dobavljanje podataka sa Mainflux-a, stavljanje podataka u Typhoon HIL simulaciju, te upis realne energetske potrošnje u CSV datoteku.

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Weiss, Alec, and Atef Elsherbeni. "Computational Performance of MATLAB and Python for Electromagnetic Applications." Applied Computational Electromagnetics Society 35, no. 11 (February 5, 2021): 1394–95. http://dx.doi.org/10.47037/2020.aces.j.351166.

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MATLAB and Python are two commonly used scripting languages for prototyping electromagnetic problems today. Each of these languages provides access to computationally efficient functions allowing a user to easily run many math heavy problems with minimal programming. In this paper we will discuss the usage of MATLAB and a variety of libraries in Python capable of running these efficient computations. Tests will be run in both languages to compare both CPU and GPU computations. The runtimes of a variety of problems using each of these platforms will also be compared for a variety of mathematical operations typically used in electromagnetic problems. Finally, a simple angle of arrival calculation using conventional beamforming will be performed to show these speeds on a realistic problem.

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Huang, Jiacong, Junfeng Gao, Georg Hörmann, and Wolf M. Mooij. "Integrating three lake models into a Phytoplankton Prediction System for Lake Taihu (Taihu PPS) with Python." Journal of Hydroinformatics 14, no. 2 (November 7, 2011): 523–34. http://dx.doi.org/10.2166/hydro.2011.020.

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In the past decade, much work has been done on integrating different lake models using general frameworks to overcome model incompatibilities. However, a framework may not be flexible enough to support applications in different fields. To overcome this problem, we used Python to integrate three lake models into a Phytoplankton Prediction System for Lake Taihu (Taihu PPS). The system predicts the short-term (1–4 days) distribution of phytoplankton biomass in this large eutrophic lake in China. The object-oriented scripting language Python is used as the so-called ‘glue language’ (a programming language used for connecting software components). The distinguishing features of Python include rich extension libraries for spatial and temporal modelling, modular software architecture, free licensing and a high performance resulting in short execution time. These features facilitate efficient integration of the three models into Taihu PPS. Advanced tools (e.g. tools for statistics, 3D visualization and model calibration) could be developed in the future with the aid of the continuously updated Python libraries. Taihu PPS simulated phytoplankton biomass well and has already been applied to support decision making.

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Gu, Tian, Cheng Xi Lei, and Zhong Wen Xing. "Study on the Phase Transformation Simulation of Hot-Stamping." Advanced Materials Research 486 (March 2012): 492–96. http://dx.doi.org/10.4028/www.scientific.net/amr.486.492.

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The temperature fields in hot-stamping process for BR1500HS steel sheet was simulated under the ABAQUS environment. Python scripting language was used for post-processing module of ABAQUS for secondary development, to obtain the volume fraction of martensite based on the formulas proposed by Koistinen and Marburger. The comparison results between simulation and metallograph show that the simulation can predict the volume fraction of martensitic effectively and thus can provide the guidance for the optimizing process parameters.

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Nandy, Zenith. "Identification of Microcontroller Based Objects Using Image Classification in Python." International Journal for Research in Applied Science and Engineering Technology 9, no. 9 (September 30, 2021): 87–92. http://dx.doi.org/10.22214/ijraset.2021.37920.

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Abstract: In this paper, I built an AI model using deep learning, which identifies whether a given image is of an Arduino, a Beaglebone Black or a Jetson Nano. The identification of the object is based on prediction. The model is trained using 300 to 350 datasets of each category and is tested multiple times using different images at different angles, background colour and size. After multiple testing, the model is found to have 95 percent accuracy. Model used is Sequential and uses Convolution Neural Network (CNN) as its architecture. The activation function of each layer is RELU and for the output layer is Softmax. The output is a prediction and hence it is of probability type. This is a type of an application based project. The entire scripting is done using Python 3 programming language. Keywords: image classification, microcontroller boards, python, AI, deep learning, neural network

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Florian Wellmann, J., Adrian Croucher, and Klaus Regenauer-Lieb. "Python scripting libraries for subsurface fluid and heat flow simulations with TOUGH2 and SHEMAT." Computers & Geosciences 43 (June 2012): 197–206. http://dx.doi.org/10.1016/j.cageo.2011.10.011.

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Tang, Wei. "Application of ABAQUS Secondary Development in Finite Element Analysis of the Bend Roller." Advanced Materials Research 187 (February 2011): 609–13. http://dx.doi.org/10.4028/www.scientific.net/amr.187.609.

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Bend roller is a key component of belt conveyor. Its reliability and service life have serious impacts on the performance of conveyor. In this study, Python was used as the programming langrage to complete Secondary Development, mainly focused on complied User Interface and Scripting Program. Taking one meter bend roller as an example, its parametric analysis was accomplished, the results showed that program interface was friendly and feasible, and the design efficiency can be improved distinctly, further more it provided a theoretical basis for bend roller design and optimization.

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Kensek, Karen M. "TEACHING VISUAL SCRIPTING IN BIM: A CASE STUDY USING A PANEL CONTROLLED BY SOLAR ANGLES." Journal of Green Building 13, no. 1 (January 2018): 113–38. http://dx.doi.org/10.3992/1943-4618.13.1.113.

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Programming and scripting can be used to activate a 3D parametric model to create a more intelligent and flexible building information model. There has been a trend in the building industry towards the use of visual scripting that allow users to create customized, flexible, and powerful programs without having to first learn how to write traditional code. Using visual scripting, users graphically interact with program elements instead of typing lines of text-based code. Nodes are created and virtually wired together; they can be numbers, sliders for adjusting values, operators and functions, list manipulation tools, graphic creators, and other types. Text based coding programs such as Python can also be used for the creation of custom nodes when greater flexibility is desired. Examples from professional firms include scripts that help automate work in the office to increase efficiency and accuracy (e.g. create escape routes, renumber rooms by levels, create documentation), assist in form generation (e.g. parametric design of metal panels, rebar generation, coordination between Revit and Rhino), analyze BIM files (e.g. terminal airflow, visual loads and capacity), and provide analysis results (e.g. daylighting, thermal comfort, window optimization). One can learn the basic steps of learning a visual programming language through the use of Dynamo within Autodesk Revit. The example used is for a façade component that changes based on the sun's altitude.

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Acuña, Ruben, Jacques Chomilier, and Zoé Lacroix. "Managing and Documenting Legacy Scientific Workflows." Journal of Integrative Bioinformatics 12, no. 3 (September 1, 2015): 65–87. http://dx.doi.org/10.1515/jib-2015-277.

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Summary Scientific legacy workflows are often developed over many years, poorly documented and implemented with scripting languages. In the context of our cross-disciplinary projects we face the problem of maintaining such scientific workflows. This paper presents the Workflow Instrumentation for Structure Extraction (WISE) method used to process several ad-hoc legacy workflows written in Python and automatically produce their workflow structural skeleton. Unlike many existing methods, WISE does not assume input workflows to be preprocessed in a known workflow formalism. It is also able to identify and analyze calls to external tools. We present the method and report its results on several scientific workflows.

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Pal, Soumitra, and Teresa M. Przytycka. "Bioinformatics pipeline using JUDI: Just Do It!" Bioinformatics 36, no. 8 (December 27, 2019): 2572–74. http://dx.doi.org/10.1093/bioinformatics/btz956.

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Abstract Summary Large-scale data analysis in bioinformatics requires pipelined execution of multiple software. Generally each stage in a pipeline takes considerable computing resources and several workflow management systems (WMS), e.g. Snakemake, Nextflow, Common Workflow Language, Galaxy, etc. have been developed to ensure optimum execution of the stages across two invocations of the pipeline. However, when the pipeline needs to be executed with different settings of parameters, e.g. thresholds, underlying algorithms, etc. these WMS require significant scripting to ensure an optimal execution. We developed JUDI on top of DoIt, a Python based WMS, to systematically handle parameter settings based on the principles of database management systems. Using a novel modular approach that encapsulates a parameter database in each task and file associated with a pipeline stage, JUDI simplifies plug-and-play of the pipeline stages. For a typical pipeline with n parameters, JUDI reduces the number of lines of scripting required by a factor of O(n). With properly designed parameter databases, JUDI not only enables reproducing research under published values of parameters but also facilitates exploring newer results under novel parameter settings. Availability and implementation https://github.com/ncbi/JUDI Supplementary information Supplementary data are available at Bioinformatics online.

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Pospelov, Gennady, Walter Van Herck, Jan Burle, Juan M. Carmona Loaiza, Céline Durniak, Jonathan M. Fisher, Marina Ganeva, Dmitry Yurov, and Joachim Wuttke. "BornAgain: software for simulating and fitting grazing-incidence small-angle scattering." Journal of Applied Crystallography 53, no. 1 (February 1, 2020): 262–76. http://dx.doi.org/10.1107/s1600576719016789.

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BornAgain is a free and open-source multi-platform software framework for simulating and fitting X-ray and neutron reflectometry, off-specular scattering, and grazing-incidence small-angle scattering (GISAS). This paper concentrates on GISAS. Support for reflectometry and off-specular scattering has been added more recently, is still under intense development and will be described in a later publication. BornAgain supports neutron polarization and magnetic scattering. Users can define sample and instrument models through Python scripting. A large subset of the functionality is also available through a graphical user interface. This paper describes the software in terms of the realized non-functional and functional requirements. The web site https://www.bornagainproject.org/ provides further documentation.

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Lemenkova, Polina. "Dataset compilation by GRASS GIS for thematic mapping of Antarctica: Topographic surface, ice thickness, subglacial bed elevation and sediment thickness." Czech Polar Reports 11, no. 1 (August 24, 2021): 67–85. http://dx.doi.org/10.5817/cpr2021-1-6.

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This paper presents the GRASS GIS-based thematic mapping of Antarctica using scripting approach and associated datasets on topography and geophysics. The state-of-the art in cartographic development points at two important aspects. The first one comprises shell scripting promoted repeatability of the GIS technique, increased automatization in cartographic workflow, and compatibility of GRASS with Python, PROJ and GDAL libraries which enables advanced geospatial data processing: converting formats, re-projecting and spatial analysis. The second aspect is that data visualization greatly influences geologic research through improving the interpretation between the Antarctic glaciation and surface. This includes the machine learning algorithms of image classification enabling to distinguish between glacier and non-glacier surfaces through automatically partitioning data and analysis of various types of surfaces. Presented detailed maps of Antarctic include visualized datasets from the ETOPO1, GlobSed, EGM96 and Bedmap2 projects. The grids include bed and surface elevation, ETOPO1-based bathymetry and topography, bed, ice and sediment thickness, grounded bed uncertainty, subglacial bed elevation, geoid undulations, ice mask grounded and shelves. Data show the distribution of the present-day glacier, geophysical fields and topographic landforms for analysis of processes and correlations between the geophysical and geological phenomena. Advances in scripting cartography are significant contributions to the geological and glaciological research. Processing high-resolution datasets of Southern Ocean retrieved by remote sensing methods present new steps in automatization of the digital mapping, as presented in this research, and promotes comprehensive monitoring of geological, permafrost and glacial processes in Antarctica. All maps have been plotted using GRASS GIS version 7.8. with technical details of scripts described and interpreted.

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McPhillips, Timothy, Tianhong Song, Tyler Kolisnik, Steve Aulenbach, Khalid Belhajjame, R. Kyle Bocinsky, Yang Cao, et al. "YesWorkflow: A User-Oriented, Language-Independent Tool for Recovering Workflow Information from Scripts." International Journal of Digital Curation 10, no. 1 (May 21, 2015): 298–313. http://dx.doi.org/10.2218/ijdc.v10i1.370.

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Scientific workflow management systems offer features for composing complex computational pipelines from modular building blocks, executing the resulting automated workflows, and recording the provenance of data products resulting from workflow runs. Despite the advantages such features provide, many automated workflows continue to be implemented and executed outside of scientific workflow systems due to the convenience and familiarity of scripting languages (such as Perl, Python, R, and MATLAB), and to the high productivity many scientists experience when using these languages. YesWorkflow is a set of software tools that aim to provide such users of scripting languages with many of the benefits of scientific workflow systems. YesWorkflow requires neither the use of a workflow engine nor the overhead of adapting code to run effectively in such a system. Instead, YesWorkflow enables scientists to annotate existing scripts with special comments that reveal the computational modules and dataflows otherwise implicit in these scripts. YesWorkflow tools extract and analyze these comments, represent the scripts in terms of entities based on the typical scientific workflow model, and provide graphical renderings of this workflow-like view of the scripts. Future version of YesWorkflow will also allow the prospective provenance of the data products of these scripts to be queried in ways similar to those available to users of scientific workflow systems.

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Mora, Peter, Gabriele Morra, and David A. Yuen. "A concise python implementation of the lattice Boltzmann method on HPC for geo-fluid flow." Geophysical Journal International 220, no. 1 (September 26, 2019): 682–702. http://dx.doi.org/10.1093/gji/ggz423.

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SUMMARY The lattice Boltzmann method (LBM) is a method to simulate fluid dynamics based on modelling distributions of particles moving and colliding on a lattice. The Python scripting language provides a clean programming paradigm to develop codes based on the LBM, however in order to reach performance comparable to compiled languages, it needs to be carefully implemented, maximizing its vectorized tools, mostly integrated in the NumPy module. We present here the details of a Python implementation of a concise LBM code, with the purpose of offering a pedagogical tool for students and professionals in the geosciences who are approaching this technique for the first time. The first half of the paper focuses on how to vectorize a 2-D LBM code and show how if carefully done, this allows performance close to a compiled code. In the second part of the paper, we use the vectorization described earlier to naturally write a parallel implementation using MPI and test both weak and hard scaling up to 1280 cores. One benchmark, Poiseuille flow and two applications, one on sound wave propagation and another on fluid-flow through a simplified model of a rock matrix are finally shown.

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Burnley, Tom, Colin M. Palmer, and Martyn Winn. "Recent developments in theCCP-EMsoftware suite." Acta Crystallographica Section D Structural Biology 73, no. 6 (May 31, 2017): 469–77. http://dx.doi.org/10.1107/s2059798317007859.

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As part of its remit to provide computational support to the cryo-EM community, the Collaborative Computational Project for Electron cryo-Microscopy (CCP-EM) has produced a software framework which enables easy access to a range of programs and utilities. The resulting software suite incorporates contributions from different collaborators by encapsulating them in Python task wrappers, which are then made accessibleviaa user-friendly graphical user interface as well as a command-line interface suitable for scripting. The framework includes tools for project and data management. An overview of the design of the framework is given, together with a survey of the functionality at different levels. The currentCCP-EMsuite has particular strength in the building and refinement of atomic models into cryo-EM reconstructions, which is described in detail.

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Park, Sangjun, Kyoungho Ahn, Hesham A. Rakha, and Chungwon Lee. "Real-Time Emissions Modeling with Environmental Protection Agency MOVES." Transportation Research Record: Journal of the Transportation Research Board 2503, no. 1 (January 2015): 60–69. http://dx.doi.org/10.3141/2503-07.

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The objective of this study was to develop a framework for real-time emissions modeling to improve ecofriendly intelligent transportation system (ITS) applications. The proposed framework can be utilized for real-time ITS applications, such as ecorouting, and applications for the environment with a real-time information synthesis program. To develop a more efficient framework, a new interface with the motor vehicle emission simulator (MOVES) model was developed to enhance computational performance. In addition, a methodology that used a probe vehicle equipped with onboard equipment was suggested for collecting operating mode distribution through the network to generate input for the MOVES model. Through virtual implementation with a simulation environment developed with the Python scripting language, this study demonstrated that the proposed framework generally worked as designed. The study also investigated the effects of probe vehicle sampling size on estimation accuracy.

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Shui, Xiao Ju, Yi Du Zhang, and Qiong Wu. "Mesoscopic Model for SiC_P/Al Composites and Simulation on the Cutting Process." Applied Mechanics and Materials 487 (January 2014): 189–94. http://dx.doi.org/10.4028/www.scientific.net/amm.487.189.

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For deep application of the FEM on the study of cutting mechanism of SiCP/Al, the article completed the algorithm to generate the mesoscopic model of SiCP/Al with the parameterization of the shape and volume fraction of SiC based on the ABAQUS scripting language python. Two-dimensional randomly distributed circular particles model, circular mixed with regular polygon particles model and arbitrary polygon model are generated with volume fraction of 30% and cutting simulations were carried out on the models. Results show that cutting force of SiCP/Al with uniform distribution and size of circular particles will be relatively stable and during the cutting process, stress field changes with the shape and distribution of the particles and the relative position of the particles and tool. Poor surface quality was mainly caused by the interaction among the tool, the particles and the matrix material.

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Wellmann, J. Florian, Sam T. Thiele, Mark D. Lindsay, and Mark W. Jessell. "pynoddy 1.0: an experimental platform for automated 3-D kinematic and potential field modelling." Geoscientific Model Development 9, no. 3 (March 10, 2016): 1019–35. http://dx.doi.org/10.5194/gmd-9-1019-2016.

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Abstract. We present a novel methodology for performing experiments with subsurface structural models using a set of flexible and extensible Python modules. We utilize the ability of kinematic modelling techniques to describe major deformational, tectonic, and magmatic events at low computational cost to develop experiments testing the interactions between multiple kinematic events, effect of uncertainty regarding event timing, and kinematic properties. These tests are simple to implement and perform, as they are automated within the Python scripting language, allowing the encapsulation of entire kinematic experiments within high-level class definitions and fully reproducible results. In addition, we provide a link to geophysical potential-field simulations to evaluate the effect of parameter uncertainties on maps of gravity and magnetics. We provide relevant fundamental information on kinematic modelling and our implementation, and showcase the application of our novel methods to investigate the interaction of multiple tectonic events on a pre-defined stratigraphy, the effect of changing kinematic parameters on simulated geophysical potential fields, and the distribution of uncertain areas in a full 3-D kinematic model, based on estimated uncertainties in kinematic input parameters. Additional possibilities for linking kinematic modelling to subsequent process simulations are discussed, as well as additional aspects of future research. Our modules are freely available on github, including documentation and tutorial examples, and we encourage the contribution to this project.

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Wellmann, J. F., S. T. Thiele, M. D. Lindsay, and M. W. Jessell. "pynoddy 1.0: an experimental platform for automated 3-D kinematic and potential field modelling." Geoscientific Model Development Discussions 8, no. 11 (November 13, 2015): 10011–51. http://dx.doi.org/10.5194/gmdd-8-10011-2015.

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Abstract. We present a novel methodology for performing experiments with subsurface structural models using a set of flexible and extensible Python modules. We utilise the ability of kinematic modelling techniques to describe major deformational, tectonic, and magmatic events at low computational cost to develop experiments testing the interactions between multiple kinematic events, effect of uncertainty regarding event timing, and kinematic properties. These tests are simple to implement and perform, as they are automated within the Python scripting language, allowing the encapsulation of entire kinematic experiments within high-level class definitions and fully reproducible results. In addition, we provide a~link to geophysical potential-field simulations to evaluate the effect of parameter uncertainties on maps of gravity and magnetics. We provide relevant fundamental information on kinematic modelling and our implementation, and showcase the application of our novel methods to investigate the interaction of multiple tectonic events on a pre-defined stratigraphy, the effect of changing kinematic parameters on simulated geophysical potential-fields, and the distribution of uncertain areas in a full 3-D kinematic model, based on estimated uncertainties in kinematic input parameters. Additional possibilities for linking kinematic modelling to subsequent process simulations are discussed, as well as additional aspects of future research. Our modules are freely available on github, including documentation and tutorial examples, and we encourage the contribution to this project.

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He, Wen Tao, Jing Xi Liu, and De Xie. "Two-Dimensional Crack Growth Simulation under Mixed-Mode Loading." Applied Mechanics and Materials 577 (July 2014): 301–4. http://dx.doi.org/10.4028/www.scientific.net/amm.577.301.

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In this paper, an efficient simulation program (FCG-System) is proposed to simulate 2D fatigue crack growth under mixed-mode loading conditions. The simulation is basically an incremental crack extension procedure. An object-oriented modeling frame is proposed for simulating fatigue crack growth of complex structures. The modeling frame is developed in the context of the commercial FE code ABAQUS, utilizing Python language and ABAQUS Scripting Interface (ASI). The highly automatic finite element simulation method is not only used for a single crack tip, but also has been extended to the system of interactive multiple cracks. The robustness and the accuracy of the new simulation code will be shown by two examples, including single crack growth and multiple cracks growth. Those applications indicate that the implementation of the FCG-System, as proposed herein, can be a useful tool for this class of fatigue crack growth.

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Gough, Julia. "CALCULATION OF TIMES AND TEMPERATURES FOR PRESS VULCANIZATION OF THICK RUBBER PADS." Rubber Chemistry and Technology 90, no. 1 (March 1, 2017): 89–107. http://dx.doi.org/10.5254/rct.16.83774.

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ABSTRACT Rubber manufacturers need simple rules to enable them to find the correct cure time and temperature for thick articles. To this end finite element analysis, controlled by Python scripting, has been used to calculate press times that meet specifications for adequate cure for uniaxial heat flow through molded rubber pads over a range of thicknesses. Three press temperatures, the effect of first preheating the rubber, and the rate of cooling were investigated. A low press temperature, preheating of the rubber, and fast cooling were required to achieve a reasonably even state of cure through thick moldings. The heat of vulcanization was included in some of the models. Its effect was small. Unified plots of the simulation results for five commercial rubber compounds are presented, and simple equations are provided to enable the cure time at any cure temperature to be estimated. The applicability of the results to fast cures of thin sections is discussed.

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He, Lin, Cong Liu, and Zhen Yu Wu. "Parametric Modeling and Stability Analysis of Temporary Grandstand." Applied Mechanics and Materials 578-579 (July 2014): 907–16. http://dx.doi.org/10.4028/www.scientific.net/amm.578-579.907.

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Temporary grandstands bear crowd load, which is created when spectators jumping on the structure. The simplified loads applied to temporary grandstand have been obtained based on experiment data of human body jumping forces. By the ABAQUS software, the parametric and automatic modeling of three-dimensional (3D) temporary grandstand structures has been realized with Python scripting. The linear buckling analysis and nonlinear buckling analysis of the structure have been carried out. The ultimate bearing capacity and the structural deformation under crowd load have been acquired. Results show that the nonlinear effect of the structure under crowd load is very obvious; the linear buckling analysis cannot get the ultimate bearing capacity of the structure and the first order buckling mode cannot simulate the final deformation of the structure either. The research of this paper greatly improve the efficiency of the construction and automation design of temporary structures and reveal the mechanical behavior of such structure to a certain degree.

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Granell, Ignacio, Abel Ramos, and Alberto Carnicero. "A Geometry-Based Welding Distortion Prediction Tool." Materials 14, no. 17 (August 24, 2021): 4789. http://dx.doi.org/10.3390/ma14174789.

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The prediction of welding distortion requires expertise in computer simulation programs, a clear definition of the nonlinear material properties, and mesh settings together with the nonlinear solution settings of a coupled thermal–structural analysis. The purpose of this paper is to present the validation of an automatic simulation tool implemented in Ansys using Python scripting. This tool allows users to automate the preparation of the simulation model with a reduced number of inputs. The goal was, based on some assumptions, to provide an automated simulation setup that enables users to predict accurate distortion during the welding manufacturing process. Any geometry prepared in a CAD software can be used as the input, which gave us much geometrical flexibility in the shapes and sizes to be modeled. A thermomechanical loosely coupled analysis approach together with element birth and death technology was used to predict the distortions. The automation of the setup enables both simulation and manufacturing engineers to perform welding-induced distortion prediction. The results showed that the method proposed predicts distortion with 80–98% accuracy.

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Vodopyanov, Alexey S., Yury N. Khomyakov, Ruslan V. Pisanov, Angelina Yu Furina, Anton A. Lopatin, and Alexey K. Noskov. "Development of a program for automated recording of the results of polymerase chain reaction studies in real time in the conditions of a massive intake of biological material during the COVID-19 pandemic." Epidemiology and Infectious Diseases 25, no. 2 (November 23, 2020): 102–8. http://dx.doi.org/10.17816/eid46555.

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With regard to the rapid spread of the latest coronavirus infection (COVID-19) in the Russian Federation in 2020, 70 workplaces were organized in Antiplague Center of Rospotrebnadzor and were seconded by specialists from the Rospotrebnadzor research antiplague institutes. However, the round-the-clock three-shift mode of operation significantly complicates the organization and documentation of the studies and increases the risk of errors. Subsequently in Antiplague Center of Rospotrebnadzor, we have conducted the work to automate the most problematic stages of conducting polymerase chain reaction (PCR) studies for the latest coronavirus infection and to develop an algorithm for real-time monitoring of the results. The development of our own software solutions was carried out in Python 3.8.2. The initial data for automation were.xlsx files automatically generated by the thermocycler software and typical tabular templates filled in at the sample analysis and RNA extraction stages. The software we developed consolidated the data into a single file register to detect potential errors simultaneously (e.g., the presence of duplicates, differences in the lists of samples at different stages, etc.). Using the Python scripting language provides cross-platform functionality (the ability to work in any operating system) and allows you to easily and quickly modify the system when changing any parameters or input file structure. Thus, 7 days were spent on the development and commissioning of this software complex, which is particularly important when working in an emergency and high alert mode. Therefore, using the approach we developed made it possible to more quickly detect technical errors, discordant results, and samples requiring re-examination, which in turn reduced the time for issuing results.

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Gonçalves, G., N. Duro, E. Sousa, and I. Figueiredo. "AUTOMATIC EXTRACTION OF TIDE-COORDINATED SHORELINE USING OPEN SOURCE SOFTWARE AND LANDSAT IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 30, 2015): 953–57. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-953-2015.

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Due to both natural and anthropogenic causes, the coastal lines keeps changing dynamically and continuously their shape, position and extend over time. In this paper we propose an approach to derive a tide-coordinate shoreline from two extracted instantaneous shorelines corresponding to a nearly low tide and high tide events. First, all the multispectral images are panshaperned to meet the 15 meters spatial resolution of the panchromatic images. Second, by using the Modification of Normalized Difference Water Index (MNDWI) and the kmeans clustering method we extract the raster shoreline for each image acquisition time. Third, each raster shoreline is smoothed and vectorized using a penalized least square method. Fourth, a 2D constrained Delaunay triangulation is built from the two extracted instantaneous shorelines with their respective heights interpolated from a Tidal gauche station. Finally, the desired tide-coordinate shoreline is interpolated from the previous triangular intertidal surface. The results show that an automatic tide-coordinated extraction method can be efficiently implemented using free available remote sensing imagery data (Landsat 8) and open source software (QGIS and Orfeo toolbox) and python scripting for task automation and software integration.

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Jin, Xia, Lu Wei Zhuang, Yi Dong Bao, and Yong Kun Han. "Development of a Rubber Diaphragm Forming Simulation System Based on ABAQUS." Key Engineering Materials 725 (December 2016): 604–9. http://dx.doi.org/10.4028/www.scientific.net/kem.725.604.

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Rubber diaphragm forming is one of very important manufacture method in aircraft manufacturing. In order to achieve the purpose of precise forming and high efficient simulation of the rubber diaphragm forming for the aircraft sheet metal parts in CAE software of ABAQUS, first the blank design module is developed and embedded into ABAQUS in the use of one step inverse finite element method because there is no blank design algorithm in ABAQUS. Then according to the characteristics of the rubber diaphragm forming, development technology on ABAQUS is applied to develop a rubber diaphragm forming simulation system based on combining Graphical User Interface GUI and the scripting language of Python. In this system, the parameter definition plug-in and finite element modeling module are designed to save a lot of tedious steps, so the blank parameters and process parameters can be defined rapidly and the simulation process can be simplified in ABAQUS, which can greatly improve the analysis speed and improve the efficiency of the finite element method. Finally the accuracy and effectiveness of the rubber diaphragm forming simulation system are verified by the simulation of a typical part that is a door frame bracket of aircraft.

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Ying, Zhang, Lian Zhanghua, Wei Chenxin, and Nguejio Florent Brice. "Research on damage progression of drill string material based on the extended finite element method." Science Progress 104, no. 3 (July 2021): 003685042110422. http://dx.doi.org/10.1177/00368504211042258.

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In this paper, the process of crack propagation is investigated using the extended finite element method at the mesoscale to study the drill pipe fracture mechanism. Firstly, the property of the S135 drill pipe was analyzed through physical and chemical experiments and the scanning electron microscope method. After that, a grain distribution model of the drill pipe material at the mesoscale was established by the Python scripting language on ABAQUS platform. Furthermore, the extended finite element method was applied to study crack dynamic propagation. And the distribution of stress and strain during the crack propagation were obtained at the mesoscale grain model. Finally, by the mesomechanics “homogenization” method, the stress and strain of the crack propagation model at different times were analyzed, and the influence of crack propagation on drill pipe material was obtained. Simulation results show that, although drill pipe material at the macroscopic scale is in the elastic stage, plastic zone and micro-crack propagation may also exist at the mesoscale. The proposed method in this paper studied the stress distribution in the crack tip during the propagation, which is a benefit for exploring the fracture mechanism of drill pipe.

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Chiesa, Giacomo, Andrea Acquaviva, Mario Grosso, Lorenzo Bottaccioli, Maurizio Floridia, Edoardo Pristeri, and Edoardo Sanna. "Parametric Optimization of Window-to-Wall Ratio for Passive Buildings Adopting A Scripting Methodology to Dynamic-Energy Simulation." Sustainability 11, no. 11 (May 31, 2019): 3078. http://dx.doi.org/10.3390/su11113078.

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Counterbalancing climate change is one of the biggest challenges for engineers around the world. One of the areas in which optimization techniques can be used to reduce energy needs, and with that the pollution derived from its production, is building design. With this study of a generic office located both in a northern country and in a temperate/Mediterranean site, we want to introduce a coding approach to dynamic energy simulation, able to suggest, from the early-design phases when the main building forms are defined, optimal configurations considering the energy needs for heating, cooling and lighting. Generally, early-design considerations of energy need reduction focus on the winter season only, in line with the current regulations; nevertheless a more holistic approach is needed to include other high consumption voices, e.g., for space cooling and lighting. The main considered design parameter is the WWR (window-to-wall ratio), even if further variables are considered in a set of parallel analyses (level of insulation, orientation, activation of low-cooling strategies including shading devices and ventilative cooling). Finally, the effect of different levels of occupancy was included in the analysis to regress results and compare the WWR with corresponding heating and cooling needs. This approach is adapted to Passivhaus design optimization, working on energy need minimisation acting on envelope design choices. The results demonstrate that it is essential to include, from the early-design configurations, a larger set of variables in order to optimize the expected energy needs on the basis of different aspects (cooling, heating, lighting, design choices). Coding is performed using Python scripting, while dynamic energy simulations are based on EnergyPlus.

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Dysarz, Tomasz. "Development of RiverBox—An ArcGIS Toolbox for River Bathymetry Reconstruction." Water 10, no. 9 (September 17, 2018): 1266. http://dx.doi.org/10.3390/w10091266.

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The main purpose of the present research is to develop software for reconstruction of the river bed on the basis of sparse cross-section measurements. The tools prepared should support the process of hydrodynamic model preparation for simulation of river flow. Considering the formats of available data and the requirements of modern modeling techniques, the prepared software is fully integrated with the GIS environment. The scripting language Python 2.7 implemented in ArcGIS 10.5.1 was chosen for this purpose. Two study cases were selected to validate and test the prepared procedures. These are stream reaches in Poland. The first is located on the Warta river, and the second on the Ner river. The data necessary for the whole procedure are: a digital elevation model, measurements of the cross-sections in the form of points, and two polyline layers representing an arbitrary river centerline and river banks. In the presented research the concept of a channel-oriented coordinate system is applied. The elevations are linearly interpolated along the longitudinal and transversal directions. The interpolation along the channel is implemented in three computational schemes linking different tools available in ArcGIS and ArcToolbox. A simplified comparison of memory usage and computational time is presented. The scheme linking longitudinal and spatial interpolation algorithms seems to be the most advantageous.

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Abdelrahman, A. H. A., Siwei Liu, Yao-Peng Liu, and Siu-Lai Chan. "Simulation of Thin-Walled Members with Arbitrary-Shaped Cross-Sections for Static and Dynamic Analyses." International Journal of Structural Stability and Dynamics 20, no. 12 (October 10, 2020): 2050128. http://dx.doi.org/10.1142/s021945542050128x.

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The main objective of this paper is to validate a finite-element (FE) modeling protocol to simulate thin-walled members for static and dynamic analyses. Arbitrary-shaped cross-sections, including open, closed, and multicellular sections can be efficiently modeled for further advanced study. The framework is thoroughly validated and verified using the existing analytical and closed-form solutions, as well as experimental results available in literature. This work is motivated by the higher accuracy of the shell FE-based modeling to capture the local and global complex behaviors of thin-walled members with asymmetric sections. Higher computational expenses, however, are required for such sophisticated shell finite element models (SFEM). Accordingly, a framework hosted in MATLAB and implementing the python scripting technique in ABAQUS, is developed, which includes eigen buckling, static nonlinear, modal frequency and dynamic time-history analyses. For a more modeling convenience, various parameters are incorporated such as imperfections, residual stresses, material definitions, element choice, meshing control, and boundary conditions. Several examples are provided to illustrate the application of the proposed framework, and to prove the robustness and accuracy of the generated FE models. This paper concludes with the efficiency of implementing SFEMs for simulating thin-walled members; thereby, establishing a more accurate and advanced structural analysis.

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Mölder, Felix, Kim Philipp Jablonski, Brice Letcher, Michael B. Hall, Christopher H. Tomkins-Tinch, Vanessa Sochat, Jan Forster, et al. "Sustainable data analysis with Snakemake." F1000Research 10 (January 18, 2021): 33. http://dx.doi.org/10.12688/f1000research.29032.1.

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Data analysis often entails a multitude of heterogeneous steps, from the application of various command line tools to the usage of scripting languages like R or Python for the generation of plots and tables. It is widely recognized that data analyses should ideally be conducted in a reproducible way. Reproducibility enables technical validation and regeneration of results on the original or even new data. However, reproducibility alone is by no means sufficient to deliver an analysis that is of lasting impact (i.e., sustainable) for the field, or even just one research group. We postulate that it is equally important to ensure adaptability and transparency. The former describes the ability to modify the analysis to answer extended or slightly different research questions. The latter describes the ability to understand the analysis in order to judge whether it is not only technically, but methodologically valid. Here, we analyze the properties needed for a data analysis to become reproducible, adaptable, and transparent. We show how the popular workflow management system Snakemake can be used to guarantee this, and how it enables an ergonomic, combined, unified representation of all steps involved in data analysis, ranging from raw data processing, to quality control and fine-grained, interactive exploration and plotting of final results.

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Mölder, Felix, Kim Philipp Jablonski, Brice Letcher, Michael B. Hall, Christopher H. Tomkins-Tinch, Vanessa Sochat, Jan Forster, et al. "Sustainable data analysis with Snakemake." F1000Research 10 (April 19, 2021): 33. http://dx.doi.org/10.12688/f1000research.29032.2.

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Data analysis often entails a multitude of heterogeneous steps, from the application of various command line tools to the usage of scripting languages like R or Python for the generation of plots and tables. It is widely recognized that data analyses should ideally be conducted in a reproducible way. Reproducibility enables technical validation and regeneration of results on the original or even new data. However, reproducibility alone is by no means sufficient to deliver an analysis that is of lasting impact (i.e., sustainable) for the field, or even just one research group. We postulate that it is equally important to ensure adaptability and transparency. The former describes the ability to modify the analysis to answer extended or slightly different research questions. The latter describes the ability to understand the analysis in order to judge whether it is not only technically, but methodologically valid. Here, we analyze the properties needed for a data analysis to become reproducible, adaptable, and transparent. We show how the popular workflow management system Snakemake can be used to guarantee this, and how it enables an ergonomic, combined, unified representation of all steps involved in data analysis, ranging from raw data processing, to quality control and fine-grained, interactive exploration and plotting of final results.

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Ren, Fengyu, Jing Zhang, Zhihua Ouyang, and Hao Hu. "Calculation of Elastic Modulus for Fractured Rock Mass Using Dimensional Analysis Coupled with Numerical Simulation." Mathematical Problems in Engineering 2021 (February 12, 2021): 1–14. http://dx.doi.org/10.1155/2021/2803837.

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Underground mining activities make the fractures in the natural rock mass develop randomly. The elastic modulus of the fractured rock mass Em is changed with the redistribution and development of the fractures. An equivalent model of fractured rock mass is structured to represent the hydraulic conductivity and the rock mass strain because of the continuum theory. Dimensional analysis is very useful to build relationship of the parameters in complex physical phenomena. Based on the engineering phenomenon of groundwater flowing into the goaf along the fracture in the rock mass, a fuzzy expression among parameters such as the parameter Em, the seepage flow Q, and the exposed area of the goaf A is obtained using dimensionless analysis. To calculate the parameter Em, the fuzzy relationship is then characterized by Darcy’s law and numerical simulation. Under the scripting environment of Python, an automated program to realize the numerical simulation of all scenarios is established, which also provides convenience for drawing the dimensionless flux charts. The results show that the parameter Em can be calculated by the dimensional analysis coupled with numerical simulation. In addition, the parameter Em decreases with the increase of the parameter Q, and the integrity of rock mass is also worse. Finally, a mine example is used to verify the feasibility of the method.

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Journal articles on the topic 'Python scripting'

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