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Rational-RC: A Python package for probabilistic life-cycle deterioration modelling of reinforced concrete structures Rational-RC：用于钢筋混凝土结构的概率寿命周期退化建模的Python包
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-26 DOI: 10.1016/j.softx.2025.102238
Gang Li , Jim Zacaruk , Moh Boulfiza
{"title":"Rational-RC: A Python package for probabilistic life-cycle deterioration modelling of reinforced concrete structures","authors":"Gang Li ,&nbsp;Jim Zacaruk ,&nbsp;Moh Boulfiza","doi":"10.1016/j.softx.2025.102238","DOIUrl":"10.1016/j.softx.2025.102238","url":null,"abstract":"<div><div>Maintaining the durability of reinforced concrete (RC) structures is crucial for sustainable infrastructure management. Rational-RC is a Python package that provides a probabilistic framework for modelling the life-cycle deterioration of RC structures. Designed with a modular, object-oriented architecture, it enables flexible integration of key deterioration processes, including membrane degradation, chloride ingress, carbonation, corrosion, and cracking within a unified limit-state reliability framework. Using site-specific field data, users can calibrate deterioration models to generate staged probabilities of failure, informing condition-based maintenance strategies that optimize costs and extend service life. The framework can be extended to interact with structural models, and scaled for simulation at both the element and network levels. Its visualization tools and extensible design make it a powerful tool for researchers and practitioners aiming to tackle the challenges of aging infrastructure with advanced computational approaches.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102238"},"PeriodicalIF":2.4,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
MCSim: A Multi-access Edge Computing Mobile CrowdSensing simulator MCSim：多接入边缘计算移动人群感知模拟器
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-26 DOI: 10.1016/j.softx.2025.102229
Dimitri Belli, Paolo Barsocchi, Antonino Crivello, Davide La Rosa, Michele Girolami
{"title":"MCSim: A Multi-access Edge Computing Mobile CrowdSensing simulator","authors":"Dimitri Belli,&nbsp;Paolo Barsocchi,&nbsp;Antonino Crivello,&nbsp;Davide La Rosa,&nbsp;Michele Girolami","doi":"10.1016/j.softx.2025.102229","DOIUrl":"10.1016/j.softx.2025.102229","url":null,"abstract":"<div><div>This paper introduces MCSim, a modular and extensible simulator designed to support the planning and evaluation of Mobile CrowdSensing (MCS) campaigns in urban environments. MCSim integrates a useful approximation of urban mobility patterns based on real-world street networks, as well as the simulation of task execution effectiveness within configurable data transmission ranges. Unlike other simulators, MCSim is built to accommodate future extensions, such as edge/fog computing architectures. The current version of the software offers a user-friendly interface, customizable configuration options, and robust output analysis. By combining realistic mobility modeling, configurable task logic, and architectural flexibility, MCSim provides researchers and practitioners with a powerful tool for optimizing MCS strategies while minimizing deployment costs and risks.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102229"},"PeriodicalIF":2.4,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
TensorConvolutionPlus: A python package for distribution system flexibility area estimation TensorConvolutionPlus：一个用于配电系统灵活性面积估计的python包
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-26 DOI: 10.1016/j.softx.2025.102241
Demetris Chrysostomou, José Luis Rueda Torres, Jochen Lorenz Cremer
{"title":"TensorConvolutionPlus: A python package for distribution system flexibility area estimation","authors":"Demetris Chrysostomou,&nbsp;José Luis Rueda Torres,&nbsp;Jochen Lorenz Cremer","doi":"10.1016/j.softx.2025.102241","DOIUrl":"10.1016/j.softx.2025.102241","url":null,"abstract":"<div><div>Power system operators need new, efficient operational tools to use the flexibility of distributed resources and deal with the challenges of highly uncertain and variable power systems. Transmission system operators can consider the available flexibility in distribution systems (DSs) without breaching the DS constraints through flexibility areas. However, there is an absence of open-source packages for flexibility area estimation. This paper introduces TensorConvolutionPlus, a user-friendly Python-based package for flexibility area estimation. The main features of TensorConvolutionPlus include estimating flexibility areas using the TensorConvolution+ algorithm, the power flow-based algorithm, an exhaustive PF-based algorithm, and an optimal power flow-based algorithm. Additional features include adapting flexibility area estimations from different operating conditions and including flexibility service providers offering discrete setpoints of flexibility. The TensorConvolutionPlus package facilitates a broader adaptation of flexibility estimation algorithms by system operators and power system researchers.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102241"},"PeriodicalIF":2.4,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DEXi Suite: DEXi decision modelling software DEXi Suite: DEXi决策建模软件
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-25 DOI: 10.1016/j.softx.2025.102240
Marko Bohanec
{"title":"DEXi Suite: DEXi decision modelling software","authors":"Marko Bohanec","doi":"10.1016/j.softx.2025.102240","DOIUrl":"10.1016/j.softx.2025.102240","url":null,"abstract":"<div><div>DEX (Decision EXpert) is a qualitative multi-criteria decision modelling method, and DEXi is software that supports the development of DEX models and their use for the evaluation and analysis of decision alternatives. We present DEXi Suite, a new generation of DEXi software, aimed at replacing the reliable and trusted, but dated, DEXi Classic software. DEXi Suite has been designed to employ a more modern and flexible software architecture and support extended functionality, while still remaining user-friendly and free to use. Currently, DEXi Suite consists of a DEXi modelling class library (DEXiLibrary), interactive desktop model editing and decision analysis software (DEXiWin) and a command-line evaluator (DEXiEval).</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102240"},"PeriodicalIF":2.4,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DMCpy: A powder and single crystal neutron diffraction software for the DMC diffractometer DMCpy：用于DMC衍射仪的粉末和单晶中子衍射软件
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-25 DOI: 10.1016/j.softx.2025.102237
Jakob Lass , Samuel Harrison Moody , Øystein Slagtern Fjellvåg
{"title":"DMCpy: A powder and single crystal neutron diffraction software for the DMC diffractometer","authors":"Jakob Lass ,&nbsp;Samuel Harrison Moody ,&nbsp;Øystein Slagtern Fjellvåg","doi":"10.1016/j.softx.2025.102237","DOIUrl":"10.1016/j.softx.2025.102237","url":null,"abstract":"<div><div>The recently upgraded DMC diffractometer at SINQ, Paul Scherrer Institute, Switzerland, equipped with a state-of-the-art 2D <span><math><msup><mrow></mrow><mrow><mn>3</mn></mrow></msup></math></span>He detector, enables high-resolution neutron diffraction experiments optimized for both powder and single-crystal studies. To address the increased complexity and volume of data produced by this instrument, we developed <span>DMCPy</span>, a Python-based software library tailored specifically to enable data analysis for DMC. <span>DMCPy</span> facilitates seamless data reduction and visualization, supporting conversion to reciprocal space, normalization, and masking of detector artifacts. Its modular architecture integrates tools for analyzing both powder diffraction patterns and single-crystal datasets, including advanced visualization features like 3D reciprocal space mapping and interactive scan inspection. By streamlining workflows and enhancing data interpretation, <span>DMCPy</span> empowers researchers to unlock the full potential of the DMC instrument for probing nuclear and magnetic structures in condensed matter systems.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102237"},"PeriodicalIF":2.4,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Pantera: A PIC-MCC-DSMC software for the simulation of rarefied gases and plasmas Pantera：用于模拟稀薄气体和等离子体的pic - mc - dsmc软件
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-25 DOI: 10.1016/j.softx.2025.102244
P. Parodi , S. Boccelli , F. Bariselli , T.E. Magin
{"title":"Pantera: A PIC-MCC-DSMC software for the simulation of rarefied gases and plasmas","authors":"P. Parodi ,&nbsp;S. Boccelli ,&nbsp;F. Bariselli ,&nbsp;T.E. Magin","doi":"10.1016/j.softx.2025.102244","DOIUrl":"10.1016/j.softx.2025.102244","url":null,"abstract":"<div><div>We present <span>Pantera</span>, an open-source, parallel, particle-based code for the simulation of rarefied gases and plasmas. The code uses the Particle-in-Cell (PIC) method for the solution of ionized flows in the electrostatic approximation, coupled to the Direct Simulation Monte Carlo (DSMC) method for particle–particle interactions, and Monte Carlo Collisions (MCC) technique for the interaction of particles with a fixed background. It uses unstructured grids, which allows for the representation of complex geometries. Various models are available for elastic collisions, reactions, and gas–surface interaction. Semi- and fully-implicit, energy-conserving PIC schemes are available, as well as a Boltzmann-fluid model for electrons, to improve numerical stability and speed up the simulations. The code is designed to be easily understandable and extensible to include new models and algorithms for aerospace applications and beyond.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102244"},"PeriodicalIF":2.4,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
SDSL-Mobile: Enabling space-efficient data structures for mobile applications SDSL-Mobile：为移动应用程序启用空间高效的数据结构
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-25 DOI: 10.1016/j.softx.2025.102234
Alexander Barquero , Anisha Wadhwani , Tyler Pencinger , Aaron Hong , Jaime Ruiz , Mattia Prosperi , Christina Boucher
{"title":"SDSL-Mobile: Enabling space-efficient data structures for mobile applications","authors":"Alexander Barquero ,&nbsp;Anisha Wadhwani ,&nbsp;Tyler Pencinger ,&nbsp;Aaron Hong ,&nbsp;Jaime Ruiz ,&nbsp;Mattia Prosperi ,&nbsp;Christina Boucher","doi":"10.1016/j.softx.2025.102234","DOIUrl":"10.1016/j.softx.2025.102234","url":null,"abstract":"<div><div>This paper presents the process and results of porting the Succinct Data Structure Library 2.0 (SDSL-lite), a robust and well-established open-source C++11 library, to Android platforms. The resulting library, called SDSL-Mobile, implements space-efficient data structures, including wavelet trees, compressed suffix arrays, and bit vectors, which are essential for handling large datasets in domains such as bioinformatics and information retrieval. Although originally designed for desktop environments, the library is extended to Android using the Android Native Development Kit (NDK) to enable integration into mobile platforms. Functionality is evaluated by implementing wavelet forests within an Android application, and performance is compared against a desktop implementation. The results demonstrate the feasibility of deploying succinct data structures on mobile devices, highlighting new possibilities for advanced data processing in resource-constrained environments.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102234"},"PeriodicalIF":2.4,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
TomoSAM: A 3D Slicer extension using SAM for tomography segmentation TomoSAM：使用SAM进行断层扫描分割的3D切片器扩展
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-24 DOI: 10.1016/j.softx.2025.102218
Federico Semeraro , Alexandre M. Quintart , Sergio Fraile Izquierdo , Joseph C. Ferguson
{"title":"TomoSAM: A 3D Slicer extension using SAM for tomography segmentation","authors":"Federico Semeraro ,&nbsp;Alexandre M. Quintart ,&nbsp;Sergio Fraile Izquierdo ,&nbsp;Joseph C. Ferguson","doi":"10.1016/j.softx.2025.102218","DOIUrl":"10.1016/j.softx.2025.102218","url":null,"abstract":"<div><div>TomoSAM has been developed to integrate the cutting-edge Segment Anything Model (SAM) into 3D Slicer, a highly capable software platform used for 3D image processing and visualization. SAM is a promptable deep learning model that is able to identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process. The source code associated with this article can be found at <span><span>https://github.com/fsemerar/SlicerTomoSAM</span><svg><path></path></svg></span> (see detailed code metadata).</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102218"},"PeriodicalIF":2.4,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144365651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
GeneralizIT: A Python Solution for Generalizability Theory Computations 泛化理论计算的Python解决方案
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-24 DOI: 10.1016/j.softx.2025.102235
Tyler J. Smith , Theresa J.B. Kline , Adrienne Kline
{"title":"GeneralizIT: A Python Solution for Generalizability Theory Computations","authors":"Tyler J. Smith ,&nbsp;Theresa J.B. Kline ,&nbsp;Adrienne Kline","doi":"10.1016/j.softx.2025.102235","DOIUrl":"10.1016/j.softx.2025.102235","url":null,"abstract":"<div><div>GeneralizIT is a Python package designed to streamline the application of Generalizability Theory (G-Theory) in research and practice. G-Theory extends classical test theory by estimating multiple sources of error variance, providing a more flexible and detailed approach to reliability assessment. Despite its advantages, G-Theory’s complexity can present a significant barrier to researchers. GeneralizIT addresses this challenge by offering an intuitive, user-friendly mechanism to calculate variance components, relative and absolute generalizability coefficients, and to perform decision (D) studies. D-Studies allow users to make decisions about potential study designs and target improvements in the reliability of certain facets. The package supports all univariate design types, including unbalanced designs, and allows for missing data, enabling users to perform in-depth reliability analysis with minimal coding effort. With built-in visualization tools and detailed reporting functions, GeneralizIT empowers researchers across disciplines, such as education, psychology, healthcare, and the social sciences, to harness the power of G-Theory for robust evidence-based insights. Whether applied to small or large datasets, GeneralizIT offers an accessible and computationally efficient solution to improve measurement reliability in complex data environments.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102235"},"PeriodicalIF":2.4,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144365656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
TensorFlores: An enhanced Python-based TinyML framework TensorFlores：一个增强的基于python的TinyML框架
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-23 DOI: 10.1016/j.softx.2025.102224
Thommas K.S. Flores , Daniel G. Costa , Ivanovitch Silva
{"title":"TensorFlores: An enhanced Python-based TinyML framework","authors":"Thommas K.S. Flores ,&nbsp;Daniel G. Costa ,&nbsp;Ivanovitch Silva","doi":"10.1016/j.softx.2025.102224","DOIUrl":"10.1016/j.softx.2025.102224","url":null,"abstract":"<div><div>The TensorFlores framework is a Python-based tool designed to optimize machine learning deployment in resource-constrained environments. It introduces evolving clustering-based quantization, supporting both quantization-aware training and post-training quantization while maintaining model accuracy. TensorFlores converts TensorFlow MLP models into optimized formats and generates platform-agnostic C++ code for embedded systems. Its modular architecture minimizes memory usage and computational overhead, enabling efficient real-time inference. By combining clustering-based quantization and automated code generation, TensorFlores enhances TinyML applications, making it a robust solution for low-power and edge AI scenarios in embedded and IoT systems.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102224"},"PeriodicalIF":2.4,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144365041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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