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DynPy-python Library for Mechanical and Electrical Engineering: An Assessment with Coupled Electro-Mechanical Direct Current Motor Model

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ENERGIES 2025年第2期18卷

作者： Sierocinski, Damian Chilinski, Bogumil Gawinski, Franciszek Radomski, Amadeusz Przybylowicz, Piotr Warsaw Univ Technol Inst Machine Design Fundamentals Fac Automot & Construct Machinery Engn Dept Comp Tech PL-02524 Warsaw Poland Warsaw Univ Technol Fac Automot & Construct Machinery Engn PL-02524 Warsaw Poland Warsaw Univ Technol Inst Machine Design Fundamentals Fac Automot & Construct Machinery Engn Dept Mech PL-02524 Warsaw Poland

DynPy is an open-source library implemented in python (version 3.10.12) programming language which aims to provide a versatile set of functionalities for mechanical and electrical engineers. It enables the user to model, solve, simulate, and report analysis of dynamic systems with the use of a single environment. The DynPy library comes with a predefined collection of ready-to-use mechanical and electrical systems. A proprietary approach to creating new systems by combining independent elements defined as classes, such as masses, springs, dampers, resistors, capacitors, inductors, and more, allows for the quick creation of new, or the modification of existing systems. In the paper examples for obtaining analytical and numerical solutions of the systems described with ordinary differential equations were presented. The assessment of solver accuracy was conducted utilising a coupled electro-mechanical model of a direct current motor, with MATLAB/Simulink (R2022b) used as a reference tool. The model was solved in DynPy with the hybrid analytical-numerical method and fully analytically, while in MATLAB/Simulink strictly numerical simulations were run. The comparison of the results obtained from both tools not only proved the credibility of the developed library but also showed its superiority in specific conditions.

关键词： coupled electro-mechanical model software tools for mechanical engineering software tools for circuit simulation solving methods numerical techniques analytical solution python programming language direct current motor

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New Method for Microstructure Segmentation and Automatic Grain Size Determination Using Computer Vision Technology during the Hot Deformation of an Al-Zn-Mg Powder Metallurgy Alloy

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JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE 2025年第1期34卷 121-131页

作者： Harikrishna, Katika Davidson, Maharajan Joseph Reddy, Gottim Dhanush Natl Inst Technol Warangal Dept Mech Engn Hanamkonda 506004 India

The microstructure plays a crucial role in material properties, with grain size analysis being essential. Thus, this study introduces a novel approach that utilizes the OpenCV, SciPy, and NumPy libraries in python, enabling efficient microstructure segmentation and automatic determination of the ASTM grain size number, while clearly defining grains, pores, and boundary regions. In our experiments, an Al-Zn-Mg alloy examined, which underwent deformation at different temperatures (300, 400, and 500 degrees C) and various strain levels, all at a constant strain rate. Firstly, convert red, green, and blue (RGB) images to grayscale and then, apply median blur to smooth them. The Otsu method was then used to distinguish grains from boundaries using thresholding. This yielded a binary image with differentiated grains and boundaries. Then, further divided the grains accurately using erosion and dilation filters. The binary image underwent additional processing to eliminate noise and classify it into three categories: grains, grain boundaries, and pores. Connected components analysis was employed to identify and label distinct regions in the image, helping determine the number of grains present. By comparing the automated counting method to manual counting, an average relative error of 3.07% was achieved for grain count validation. Furthermore, ASTM grain sizes were calculated based on the number of grains in the optical images, resulting in a high success rate of 99%. These results highlight the effectiveness of the approach in accurately characterizing microstructures and acquiring essential information regarding material properties.

关键词： automated grain counting computer vision microstructure OpenCV powder metallurgy python programming language

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Automated microstructural segmentation and grain size measurement of Al plus SiC nanocomposites using advanced image processing techniques on backscattered electron images

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MATERIALS CHARACTERIZATION 2025年 222卷

作者： Harikrishna, Katika Nithin, Abeyram Davidson, M. J. Shri Vishnu Engn Coll Women Dept Mech Engn Bhimavaram 534202 India Sreenidhi Inst Sci & Technol Dept Mech Engn Hyderabad 501301 India Natl Inst Technol Dept Mech Engn Warangal 506004 India

Grain size analysis is crucial for understanding material properties, yet traditional manual methods are often time-consuming and labor-intensive. This study presents a novel approach utilizing python's OpenCV, SciPy, and NumPy libraries for automated microstructure segmentation and grain size analysis of Al + SiC nanocomposites fabricated through powder metallurgy (PM). When segmenting backscattered electron (BSE) images, challenges such as noise, local contrast variations, inaccurate thresholding, fused grains, edge grain removal, and grain boundary separation arise. To address these, advanced image processing techniques were employed: Gaussian filtering reduced noise, and Contrast Limited Adaptive Histogram Equalization (CLAHE) enhanced local contrast, making grain boundaries more distinct. Automated thresholding was performed using Otsu's method to differentiate grains and boundaries, while morphological operations (erosion and dilation) refined the separation of fused grains. Edge grains were excluded using ***(), and the distance transform function clearly delineated grains and boundaries. Connected components analysis was used to identify and label distinct regions in the image, aiding in the determination of the number of grains. The algorithm was tested on multiple BSE images for robustness, with results compared to manual grain size measurements according to ASTM standards. A Bland-Altman plot and Pearson correlation were used to validate the algorithm, showing that the error is within the limits of agreement and the correlation coefficient of 0.98 demonstrates high accuracy in predicting grain sizes, maintaining a reasonable level of precision.

关键词： Automated grain size measurement Image processing python programming language Microstructure segmentation OpenCV Powder metallurgy

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eminus - pythonic electronic structure theory

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SOFTWAREX 2025年 29卷

作者： Schulze, Wanja Timm Schwalbe, Sebastian Trepte, Kai Graefe, Stefanie Friedrich Schiller Univ Inst Phys Chem D-07743 Jena Germany Ctr Adv Syst Understanding D-02826 Gorlitz Germany Helmholtz Zentrum Dresden Rossendorf D-01328 Dresden Germany Taiwan Semicond Mfg Co North Amer San Jose CA USA

In current electronic structure research endeavors such as warm dense matter or machine learning applications, efficient development necessitates non-monolithic software, providing an extendable and flexible interface. The open-source idea offers the advantage of having a source code base that can be reviewed and modified by the community. However, practical implementations can often diverge significantly from their theoretical counterpart. Leveraging the efforts of recent theoretical formulations and the features of python, we try to mitigate these problems. We present eminus, an education- and development-friendly electronic structure package designed for convenient and customizable workflows, yet built with intelligible and modular implementations.

关键词： Density functional theory Electronic structure Education python programming language

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kegg_pull: a software package for the RESTful access and pulling from the Kyoto Encyclopedia of Gene and Genomes

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BMC BIOINFORMATICS 2023年第1期24卷 1-17页

作者： Huckvale, Erik Moseley, Hunter N. B. Univ Kentucky Markey Canc Ctr Lexington KY 40536 USA Univ Kentucky Dept Mol & Cellular Biochem Lexington KY 40536 USA Univ Kentucky Inst Biomed Informat Lexington KY 40536 USA

BackgroundThe Kyoto Encyclopedia of Genes and Genomes (KEGG) provides organized genomic, biomolecular, and metabolic information and knowledge that is reasonably current and highly useful for a wide range of analyses and modeling. KEGG follows the principles of data stewardship to be findable, accessible, interoperable, and reusable (FAIR) by providing RESTful access to their database entries via their web-accessible KEGG API. However, the overall FAIRness of KEGG is often limited by the library and software package support available in a given programming language. While R library support for KEGG is fairly strong, python library support has been lacking. Moreover, there is no software that provides extensive command line level support for KEGG access and *** present kegg_pull, a package implemented in the python programming language that provides better KEGG access and utilization functionality than previous libraries and software packages. Not only does kegg_pull include an application programming interface (API) for python programming, it also provides a command line interface (CLI) that enables utilization of KEGG for a wide range of shell scripting and data analysis pipeline use-cases. As kegg_pull's name implies, both the API and CLI provide versatile options for pulling (downloading and saving) an arbitrary (user defined) number of database entries from the KEGG API. Moreover, this functionality is implemented to efficiently utilize multiple central processing unit cores as demonstrated in several performance tests. Many options are provided to optimize fault-tolerant performance across a single or multiple processes, with recommendations provided based on extensive testing and practical network *** new kegg_pull package enables new flexible KEGG retrieval use cases not available in previous software packages. The most notable new feature that kegg_pull provides is its ability to robustly pull an arbitrary number o

关键词： KEGG REST Application programming interface python programming language Command line interface

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CellSys: An open-source tool for building initial structures for bio-membranes and drug-delivery systems

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JOURNAL OF COMPUTATIONAL CHEMISTRY 2022年第5期43卷 331-339页

作者： Abbasi, Ali Amjad-Iranagh, Sepideh Dabir, Bahram Amirkabir Univ Technol Dept Chem Engn Tehran Iran Amirkabir Univ Technol Dept Mat & Met Engn Tehran 158754313 Iran

Since phospholipids are the most important components in the structure of biomembranes, they deserve to be considered with a lot of attention in both experimental and computational theoretical studies using molecular simulation methods related to the research in the fields of drug design and drug delivery where they involve knowledge about the interactions of drug molecules with cell membranes. To employ the molecular simulation approach for this purpose the essential requirement is having information about the initial structure of phospholipids and how they interact with the drugs. Therefore in this article, we introduce an open-source software package in python programming language for utilizing data manipulation for generation and developing the initial structure of biomolecular cells to provide the needed information for investigation in drug delivery systems. In addition, the proposed software package can be used for the efficient storage of membrane structural data to be exploited in designing new drug delivery systems. To verify the performance of the code and the results of the simulations, several analyses have been done, such as the calculation of area per lipid and self-diffusion coefficient, in addition to lipid order parameter. The results were in complete agreement with the references.

关键词： cell membranes molecular dynamics simulations phospholipid membranes python programming language

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Evolutionary-based multi-objective optimal power flow considering real-time uncertainties in wind farms and load demand

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ELECTRICAL ENGINEERING 2024年第3期106卷 3283-3303页

作者： Preethi, V. A. Shunmugalatha, A. Babulal, C. K. Anna Univ SNS Coll Engn Dept Elect & Elect Engn Kurumbapalayam Post Coimbatore Tamil Nadu India Anna Univ Velammal Coll Engn & Technol Elect & Elect Engn Dept Madurai Tamil Nadu India Anna Univ Thiagarajar Coll Engn Elect & Elect Engn Dept Madurai Tamil Nadu India

This study presents a multi-objective solving indicator-based evolutionary algorithm (IBEA) to solve the optimal power flow (OPF) problem with multiple and competing objectives. The objective functions for the multi-objective OPF (MOOPF) are active power loss, aggregate voltage deviation, total generation cost, and emission pollution. This algorithm combines the shift-based density estimation method with a weighted sum approach to produce a set of non-dominated solutions on each objective space. Moreover, an S-shaped fuzzy membership approach is used to extract the best compromise solution from the obtained non-dominated solutions. To validate the IBEA's performance, standard IEEE 30-bus and IEEE 57-bus test systems with nine different cases are being used. This paper also presents a stochastic optimal power flow problem for two-objective optimization with load demand and wind power uncertainty.

关键词： Multi-objective optimal power flow Cost Emission Evolutionary algorithm Fuzzy decision-making Renewable energy python programming language

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A python toolbox for computing solutions to canonical problems in electromagnetics

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IEEE ANTENNAS AND PROPAGATION MAGAZINE 2006年第3期48卷 78-81页

作者： Swartz, Julian P. Univ Stellenbosch Dept Elect & Elect Engn ZA-7600 Stellenbosch South Africa

One of the most important steps in the development of any numerical code is the validation of the implementation by comparison of the results obtained for a set of test cases to the exact solution. In the context of codes developed for high-frequency electromagnetics, this usually means comparing computed results to analytical solutions. Obtaining these analytical solutions can be a nontrivial problem, although fortunately it need only be implemented once, and can then be used repeatedly to validate any new code. This paper concentrates on finding the analytical solution to eigenvalue problems for a range of standard geometries, as well as the near-field solution for plane-wave scattering from a PEC sphere. The solutions are implemented using the python programming language and the SciPy library of scientific functions.

关键词： electromagnetic scattering eigenvalues software verification and validation python programming language SciPy numerical library sphere cavity resonators

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Machine learning modeling of base flow generation potential: A case study of the combined application of BWM and Fallback bargaining algorithm

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JOURNAL OF HYDROLOGY 2024年 636卷

作者： Khiavi, Ali Nasiri Tarbiat Modares Univ Fac Nat Resources & Marine Sci Dept Watershed Management Engn Noor 46414356 Iran

The study of base flow is essential for sustainable water management. By understanding the dynamics of base flow, policymakers can make informed decisions to ensure the long-term health and availability of water resources. This study was conducted with the aim of modeling the spatial changes of Base Flow Generation Potential (BFGP) using integrated Machine Learning Algorithms (MLAs) including Decision Tree Regression (DTR), K-Nearest Neighbors (KNN), Na & iuml;ve Bayes (NB), Random Forest (RF), Simple Linear Regression (SLR), Support Vector Machine (SVM) and Support Vector Regression (SVR) and optimal Multi-Criteria Decision Making (MCDM) methods including Best-Worst Method (BWM) and Fallback bargaining in the Cheshmeh-Kileh watershed, Iran. BFGP conditioning factors were selected for the Sub-Watershed (SW) and weighed using MCDM (BWM and Fallback bargaining algorithm) methods. BFGP maps of five classes were generated and analyzed. MCDM methods were also integrated with ML algorithms for optimum performance evaluation of the integrated unit. Based on the results, in the integrated model of BWM and Fallback bargaining algorithm with ML algorithms, SVR and RF algorithms was selected as the optimal model, respectively. In BWM in the Sehezar River, the upstream had the highest BFGP. The pattern of spatial changes based on the Fallback bargaining algorithm in the upstream of Sehezar River was similar to BWM. The combined approach of RF-GTA with the factors of minimum temperature (Tn), NDSI and elevation showed the highest correlation. It was observed that that the Fallback bargaining algorithm and BWM of the MCDM exhibited similarity in output of regarding the spatial change patterns of the BFGP. Also, Fallback bargaining exhibited a 67% similarity with the integrated RF-GTA in BFGP prioritization of the SWs, while BWM performed poorly. This suggests that the Fallback bargaining algorithm was more effective than BWM of the MCDM methods for SWs BFGP prioritization. The ge

关键词： Artificial Intelligence (AI) Environmental Flow Optimal Decision Making python programming language Water Resources Management (WRM)

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Spacing and block volume estimation in discontinuous rock masses using image processing technique: a case study

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ENVIRONMENTAL EARTH SCIENCES 2021年第14期80卷 1-13页

作者： Azarafza, Mohammad Kockar, Mustafa K. Faramarzi, Lohrasb Hacettepe Univ Dept Civil Engn Ankara Turkey Isfahan Univ Technol Dept Min Engn Esfahan Iran

Application of the image processing techniques (IPT) to identify rock mass geometry provides more fast information about discontinuity properties used in geo-engineering characteristics. In this regard, the field survey can be improved using IPT. This study has utilised the IPT to identify the discontinuity and block volume characteristics in a discontinuous rock mass. For this purpose, a visual evaluation of the rock mass outcrop with discontinuities from a road slope cut located in the South Pars Special Zone, Assalouyeh, Iran, was considered. A three-step IPT analysis (i.e. pre-processing, main processing, and post-processing) was conducted to extract the features through the python programming language. Regarding the IPT methodology, the studied rock mass characteristics consist of four major discontinuity sets and rock block volumes between the intersections of the discontinuities, as confirmed with a scan-line field survey. The evaluated data indicated that the maximum, minimum, and average block volumes processed by the IPT were 1.068, 0.479, and 1.055 m(3), and their field measurement results were 1.092, 0.479, and 1.065 m(3), respectively. Additionally, the orientations of the estimated discontinuity properties and their spacings determined by IPT for the rock mass ranging between 32 and 69.9 degrees and 0.5 and 2.18 m, respectively. Similarly, the orientations of the field measurement results were also obtained between 33 and 71 degrees and 0.58 and 2.25 m, respectively. The results of the IPT and the field survey were close, which revealed that the IPT is a reliable method for determining discontinuity spacing and rock block volume along large cut slopes. This approach provided rapid data processing with spatial extensions in a short period, making it possible to achieve accurate results in discontinuity network characteristics.

关键词： Image processing technique Artificial intelligence python programming language Rock engineering

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