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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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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 332-332页

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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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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Optimal control method for power system reactive power management considering real-time uncertainties

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OPTIMAL CONTROL APPLICATIONS & METHODS 2022年第4期43卷 1283-1311页

作者： Anandam, Preethi Vela Alagarsamy, Shunmugalatha Kuppusamy, Babulal Chittu Velammal Coll Engn & Technol Dept Elect & Elect Engn Madurai 625009 Tamil Nadu India Thiagarajar Coll Engn Dept Elect & Elect Engn Madurai Tamil Nadu India

This article investigates multi-objective reactive power management while accounting for real-time generation and load uncertainties. The primary goal of this research is to investigate the effects of uncertainties on reactive power dispatch, while taking into account multiple objectives at the same time and keeping operational constraints in mind. The optimal reactive power dispatch (ORPD) problem is solved using an "indicator-based evolutionary technique" called "ISDE+," which considers two different goal functions: real power loss minimization and voltage deviation minimization. IEEE 30 and IEEE 57 bus test systems are taken into account in the simulation. ISDE+ generates a set of non-dominated optimal solutions, from which the best compromise solution is extracted using the "S" shaped fuzzy membership function. A hyper-volume indicator is used to evaluate the optimizer's performance. In addition, this work proposes a stochastic ORPD problem for tri-objective optimization with load demand and wind power uncertainty. The Weibull probability distribution function was used to model stochastic wind power using real-time wind speed data gathered from the National Institute of Wind Energy. Furthermore, to obtain a generalized wind speed set, a scenario-based reduction technique based on the python programming language is developed. The outcomes of simulations in deterministic and stochastic instances were studied and compared using ISDE+, which outperforms other methods documented in the literature.

关键词： fuzzy decision-making indicator-based evolutionary algorithm optimal reactive power dispatch python programming language renewable energy

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An Object-Oriented class design for the Generalized Finite Element Method programming

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LATIN AMERICAN JOURNAL OF SOLIDS AND STRUCTURES 2013年第6期10卷 1267-1291页

作者： Piedade Neto, Dorival Costa Ferreira, Manoel Denis Baroncini Proenca, Sergio Persival Univ Sao Paulo Dept Struct Engn Sch Engn Sao Carlos Sao Carlos SP Brazil

The Generalized Finite Element Method (GFEM) is a numerical method based on the Finite Element Method (FEM), presenting as its main feature the possibility of improving the solution by means of local enrichment functions. In spite of its advantages, the method demands a complex data structure, which can be especially benefited by the Object-Oriented programming (OOP). Even though the OOP for the traditional FEM has been extensively described in the technical literature, specific design issues related to the GFEM are yet little discussed and not clearly defined. In the present article it is described an Object-Oriented (OO) class design for the GFEM, aiming to achieve a computational code that presents a flexible class structure, circumventing the difficulties associated to the method characteristics. The proposed design is evaluated by means of some numerical examples, computed using a code implemented in python programming language.

关键词： Object-Oriented programming Generalized Finite Element Method python programming language

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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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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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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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Automatic assessment of object oriented programming assignments with unit testing in python and a real case assignment

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COMPUTER APPLICATIONS IN ENGINEERING EDUCATION 2023年第5期31卷 1321-1338页

作者： Climent, Laura Arbelaez, Alejandro Univ Autonoma Madrid UAM Dept Ingn Informat Madrid Spain

In this paper, we focus on developing automatic assessment (AA) for a topic that has some difficulties in its practical assessment: object oriented programming (OOP). For evaluating that the OOP principles have been correctly applied to a real application, we use unit testing. In this paper, we focus on prioritizing that the students understand and apply correctly complex OOP principles and that they design properly the classes (including their relationships). In addition, we focus on the python programming language rather than the typical previous works' focus in this area. Thus, we present a real case study of a practical assignment, in which the students have to implement characters for a video game. This assignment has the particularities and advantages that it is incremental and that it applies all four OOP principles within a single assignment. We also present its solution with the UML class diagram description. Furthermore, we provide unit testing for this case study and give general advice for generalizing the unit tests to other real case scenarios. Finally, we corroborate the effectiveness of our approach with positive student evaluations.

关键词： automatic assessment object oriented programming python programming language unit testing

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