Advanced Software Engineering Research Articles

Structural Analysis of an Off-Road Vehicle Suspension System Using CATIA and ANSYS

This project delves into the structural analysis of an off-road vehicle suspension system, employing cutting-edge software tools such as CATIA and ANSYS. Off-road vehicles necessitate robust suspension systems capable of withstanding harsh terrain conditions while ensuring vehicle stability, manoeuvrability, and passenger comfort. The study focuses on evaluating the structural integrity, performance, and behaviour of the suspension system under diverse load conditions and terrain scenarios. This project focuses on conducting a comprehensive structural analysis of an off-road vehicle suspension system using advanced engineering software tools, specifically CATIA and ANSYS. CATIA is a powerful computer-aided design (CAD) software known for its capabilities in creating detailed 3D models, while ANSYS is a leading finite element analysis (FEA) software used for simulating structural behaviour and analyzing mechanical systems. Keywords: suspension system, CATIA v5, ANSYS, iterations, FEA.

Detecting and resolving feature envy through automated machine learning and move method refactoring

Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.

Development of a 2-dimensional thermal calculation method to estimate silicone oil's temperature distribution in viscous torsional vibration dampers

AbstractHigh-performance internal combustion engines are subject to severe torsional vibrations which result from uneven gas and inertial loads. Fatigue damage occurs if the frequency of these undesired oscillations matches the resonance frequency of the crankshaft and the driven engine elements. This phenomenon can be avoided by the application of visco-dampers whose working fluid is high-viscosity silicone oil. Since silicone oil is exposed to a significant amount of heat load during operation, it is essential to calculate the temperature distribution in a relatively easy, quick, and cost-efficient way for lifetime estimation purposes. The aim of this article is to develop a reliable, fast, and accurate finite difference-based numerical method for steady-state thermal calculations for arbitrary damper sections. The developed MATLAB code calculates the temperature field of the damping fluid together with all components in a radial cross-section at given operational conditions. The accuracy of the developed thermal calculation method has been tested in a 3-dimensional – 2-dimensional two-step verification process by finite element and finite volume-based advanced engineering software in ANSYS environment. Furthermore, the original Iwamoto equation available in the literature has been updated to provide more accurate surface temperature results based on the simulations' outcome gained by the finite volume method.

AN INNOVATIVE METHODOLOGY TO DESIGN GYROID HEAT EXCHANGERS FOR METAL ADDITIVE MANUFACTURING

This study demonstrates an innovative approach to the automatic design of compact gyroid heat exchangers using the advanced engineering software nTopology, which is based on implicit modeling technology. The aim is to provide a modern enhancement to traditional 'Shell and Tube' type heat exchangers. Utilizing functions in implicit modeling and parametric design features, complex internal gyroid structures can be used as an alternative heat transfer interface in 'Shell and Tube' type heat exchangers. The most striking aspect of the methodology is its ability to fully automate the design process. By consolidating specific parameters into a single function block and entering scalar values, a fast and flexible workflow is activated, automatically generating the final geometry. Gyroid structures with high thermal performance and fluid dynamics are automatically adapted for various volumes and geometries. These structures can improve the overall efficiency of heat exchangers and offer significant advantages, especially in specialized application areas such as aerospace and space industries. In the design and sizing process of the gyroid heat exchanger, if manufacturing is planned, it is necessary to pay attention to the design principles for metal additive manufacturing. In conclusion, this study demonstrates that the advanced engineering software known as nTopology can create a synergistic effect in the rapid and easy design of gyroid heat exchangers and in establishing the automation of the design process.

Report from the 4th Int. Workshop on Education through Advanced Software Engineering and Artificial Intelligence (EASEAI '22)

The growth of digital technologies has drastically altered daily life. Both the general public and specialized groups must continuously acquire new knowledge and skills. The EASEAI workshop series addresses this issue by examining the fields of software engineering, education, and AI research to discover ways they can be integrated. This workshop gathers researchers, educators, and practitioners who apply advanced software engineering and AI in education, and allows for a cross-generational and interdisciplinary exchange of ideas among students, to examine current practices and establish new future goals. More details at https://easeai.github.io.

Computational Analysis of Liquid Hydrogen Storage Tanks for Aircraft Applications

During the last two decades, the use of hydrogen (H2) as fuel for aircraft applications has been drawing attention; more specifically, its storage in liquid state (LH2), which is performed in extreme cryogenic temperatures (-253 °C), is a matter of research. The motivation for this effort is enhanced by the predicted growth of the aviation sector; however, it is estimated that this growth could be sustainable only if the strategies and objectives set by global organizations for the elimination of greenhouse gas emissions during the next decades, such as the European Green Deal, are taken into consideration and, consequently, technologies such as hydrogen fuel are promoted. Regarding LH2 in aircraft, substantial effort is required to design, analyze and manufacture suitable tanks for efficient storage. Important tools in this process are computational methods provided by advanced engineering software (CAD/CAE). In the present work, a computational study with the finite element method is performed in order to parametrically analyze proper tanks, examining the effect of the LH2 level stored as well as the tank geometric configuration. In the process, the need for powerful numerical models is demonstrated, owing to the highly non-linear dependence on temperature of the involved materials. The present numerical models' efficiency could be further enhanced by integrating them as part of a total aircraft configuration design loop.

Study of selected properties of PLA used in 3D printing

This study focuses on determining the best possible structure of the orthosis made with FDM 3D printing technology. To produce the samples, a thermoplastic PLA material was selected that met the conditions of biodegradability, biocompatibility and non-toxicity. The samples produced were subjected to a tensile strength test and corrosion resistance.Studies based on FEM analysis were carried out using the advanced engineering software CAE - Inventor. The samples were designed in the CAD system, while the G-Code path was generated using the PrusaSlicer 2.5.0 program dedicated to the Prusa i3 MK3S+ printer, which was used to create the models. Surface morphology observations of PLA were carried out with a Zeiss SUPRA 35 scanning electron microscope (SEM). The static tensile test was performed on the Zwick/Roell z100 device based on the PN-EN ISO 527:1 standard. Electrochemical corrosion tests were carried out using the Autolab PGSTAT302N Multi BA potentiostat in Ringer solution at a temperature of 37C.The research allowed the appropriate structure of the orthosis made of PLA polymer material using 3D FDM printing technology. The static tensile test, SEM and corrosion tests confirmed the correct application of this material for the selected purpose. It was possible to determine that samples with holes of 10 mm had the highest strength properties. Due to the tensile tests, the average tensile strength of those samples was around 61 MPa. The corrosion parameters of PLA were determined using Tafel analysis.The research methodology proposed in work can be used to study other biomedical materials. The results presented can be the basis for further tests in order to search for the best orthopaedic stabiliser.The innovative part of the article are three different versions of structures intended for making orthoses used in medicine.

Preface

Computer and Communication Technology (CCT) are now involved in governmental, industrial, and business domains more than ever. Thus, it is important for CCT personnel to continue academic research to improve technology and its adoption to modern applications. The up-to-date research and technologies must be distributed to researchers and CCT community continuously to aid future development. The intent of the activity is to let the participants acquaint with transcendental growth, recent trends, innovations and security issues involved in the domain of communication technologies, high performance computing, big data, social media, hardware & software design, advanced software engineering, Internet of Things (IoT), e-governance etc. and their impact on societal applications through various brainstorming sessions. The conference will facilitate the young researchers, industries and research agencies especially, those, who are carrying out their research work in the aforesaid domain of Computer Science, Information Technology, Electronics and Communication Engineering with valuable discussions in order to make the outcomes more realistic. The technical committee of GC-RDCT 2022 (second edition) received 150+ papers, out of which 38 are shortlisted for the Conference for oral. Through this Conference, we have tried to bring in researchers from various universities and institutions to interact and deliberate within and get ideas for their future scientific endeavors. Due to the prevailing COVID-19 pandemic, the conference was organized in FULL VIRTUAL MODE. The conference was held in Google Meet online platform. All the speakers and the presenters have been connected through goggle meet platform and the inaugural function of the conference was held physically at AJIET and was live streamed through Google Meet and Youtube.I am pleased to acknowledge the unstinting support from my colleagues at AJIET, the International Advisory, the Technical Program, and the Local Organization Committee members. I am incredibly grateful to our Management, Principal & Administrative Staffs, for providing required support.List of Committees of GC-RDCT 2022 is available in this Pdf.

A model-based design of an onboard stereo vision system: obstacle motion estimation for cooperative automated vehicles

Cooperative automated vehicle software needs to use advanced software engineering design methodologies to manage the complexity of distributed software. This article presents a design model of a stereo vision system for cooperative automated vehicles based on object-oriented analysis and design methodologies and unified modeling language concepts. We use a rational unified process and the 4+1 architectural view model to design the stereo vision system. The designed model is a part of the perception system of the ego vehicle. The stereo vision system continuously perceives the traffic environment using an on-board front-facing stereo camera and sends information to the vehicle control system. The stereo vision system is developed on Ubuntu 16.04 LTS platform with the Nvidia DriveWorks framework using the C++ programming language, and it is deployed on Nvidia Drive PX2 automotive-grade embedded hardware platform. The designed and developed system is evaluated on the Carla simulation environment and the Renault Twizy cooperative automated vehicle research platform. The experimental results show that the approach is applicable, and the system is capable of running in real-time.

Assessing individual contributions to software engineering projects: a replication study

ABSTRACT Background and Context Assessing team members’ indivdiual contributions to software development projects poses a key problem for computing instructors. While instructors typically rely on subjective assessments, objective assessments could provide a more robust picture. To explore this possibility, In a 2020 paper, Buffardi presented a correlational analysis of objective metrics and subjective metrics in an advanced software engineering project course (n= 41 students and 10 teams), finding only two significant correlations. Objective To explore the robustness of Buffardi’s findings and gain further insight, we conducted a larger scale replication of the Buffardi study (n = 118 students and 25 teams) in three courses at three institutions. Method We collected the same data as in the Buffardi study and computed the same measures from those data. We replicated Buffardi’s exploratory, correlational and regression analyses of objective and subjective measures. Findings While replicating four of Buffardi’s five significant correlational findings and partially replicating the findings of Buffardi’s regression analyses, our results go beyond those of Buffardi by identifying eight additional significant correlations. Implications In contrast to Buffardi’s study, our larger scale study suggests that subjective and objective measures of individual performance in team software development projects can be fruitfully combined to provide consistent and complementary assessments of individual performance.

Report from the 3rd Int. Workshop on Education through Advanced Software Engineering and Artificial Intelligence (EASEAI '21)

With the development and widespread of digital technologies, ev- eryday life has been profoundly transformed. The general public, as well as specialized audiences, have to face an ever-increasing amount of knowledge and learn new abilities. The EASEAI work- shop series addresses that challenge by looking at software en- gineering, education, and arti cial intelligence research elds to explore how they can be combined. Speci cally, this workshop brings together researchers, teachers, and practitioners who use advanced software engineering tools and arti cial intelligence tech- niques in the education eld and through a transgenerational and transdisciplinary range of students to discuss the current state of the art and practices, and establish new future directions. More information at https://easeai.github.io.

Exploration of Software Engineering Talent Cultivation Based on Problem Orientation in the Construction of New Engineering Courses

Software talent training has the characteristics of strong professionalism and high practical requirements. Especially in the context of new engineering, the talent training of software engineering is facing great challenges. Starting from the current university education. The training of engineering professionals has the problems of insufficient industry counterpart, insufficient innovation of teaching models, lack of effectiveness of the teaching assessment system, and insufficient training of practical ability. This article starts with the analysis of measures to clarify talent training goals, innovate talent training methods, and improve the quality of professional teachers, and propose a project-driven organic integration of theory and practice training, and an advanced software engineering practice training system. The proposed software engineering talent training model can better adapt to the requirements of new engineering disciplines and improve the quality of software engineering talent training.

Preface

Computer and Communication Technology (CCT) are now involved in governmental, industrial, and business domains more than ever. Thus, it is important for CCT personnel to continue academic research to improve technology and its adoption to modern applications. The up-to-date research and technologies must be distributed to researchers and CCT community continuously to aid future development. The intent of the activity is to let the participants acquaint with transcendental growth, recent trends, innovations and security issues involved in the domain of communication technologies, high performance computing, big data, social media, hardware & software design, advanced software engineering, Internet of Things (IoT), e-governance etc. and their impact on societal applications through various brainstorming sessions. The conference will facilitate the young researchers, industries and research agencies especially, those, who are carrying out their research work in the aforesaid domain of Computer Science, Information Technology, Electronics and Communication Engineering with valuable discussions in order to make the outcomes more realistic. The technical committee of GC-RDCT received 135 papers, out of which 48 are shortlisted for the Conference for oral. Through this Conference, we have tried to bring in researchers from various universities and institutions to interact and deliberate within and get ideas for their future scientific endeavors. Due to the prevailing COVID-19 pandemic, the conference was organized in FULL VIRTUAL MODE. The conference was held in Google Meet online platform. All the speakers and the presenters have been connected through goggle meet platform and the inaugural function of the conference was held physically at AJIET and was live streamed through Google Meet and Youtube.I am pleased to acknowledge the unstinting support from my colleagues at AJIET, the International Advisory, the Technical Program, and the Local Organization Committee members. I am incredibly grateful to our Management, Principal & Administrative Staffs, for providing required support.Dr. Nagesh H ROrganizing Chair, GC-RDCT 2021Committee, Chief Patron, Patron, Conference Chair, Organizing Chair, Information Contact, Publicity and Promotions, Local Arrangements Committee, Finance Committee, Sponsorship Committee, Editorial Committee, Technical Program Committee – Chairs, Technical Program Committee are available in the pdf

Advanced Computing and Software Engineering

Advanced Computing and Software Engineering

Report from the 2nd Int. Workshop on Education through Advanced Software Engineering and Artificial Intelligence (EASEAI '20)

In the past years, with the development and widespread of digi- tal technologies, everyday life has been profoundly transformed. The general public, as well as specialized audiences, have to face an ever-increasing amount of knowledge and learn new abilities. The EASEAI workshop series addresses that challenge by look- ing at software engineering, education, and arti cial intelligence research elds to explore how they can be combined. Speci cally, this workshop brings together researchers, teachers, and practi- tioners who use advanced software engineering tools and arti cial intelligence techniques in the education eld and through a trans- generational and transdisciplinary range of students to discuss the current state of the art and practices, and establish new future directions. More information at https://easeai.github.io.

Knowledge Management for Change Prediction by the Integrated Multidisciplines: Computational Intelligence, Advanced Software Engineering, and Statistics

Knowledge Management for Change Prediction by the Integrated Multidisciplines: Computational Intelligence, Advanced Software Engineering, and Statistics

Report from the 1st Int. Workshop on Education through Advanced Software Engineering and Artificial Intelligence (EASEAI '19)

In the past years, everyday life has been profoundly transformed by the development and widespread of digital technologies. Gen- eral, as well as specialized audiences, have to face an ever-increasing amount of knowledge and learn new abilities. This rst edition of the EASEAI workshop tried to address that challenge by look- ing at software engineering, education, and arti cial intelligence research elds to explore how they can be combined. Speci cally, we brought together researchers, teachers, and practitioners who use advanced software engineering tools and arti cial intelligence techniques in education. And researchers and teachers in edu- cation science who address the problem of improving the aware- ness regarding digital technologies through a transgenerational and transdisciplinary range of students.

Ankle-foot orthosis design between the tradition and the computerized perspectives.

This study focuses on the drop foot case related to hyperthyroidism of the ankle joint resulting in the relaxation of the toes during walking. This condition requires treatment using an ankle-foot orthosis. Traditional orthosis techniques lack precision and depend on the skill of the fabricator. This research aims to make a bias in ankle-foot orthosis design and analysis methods, where a complete methodology of numerical design and testing has been proposed using advanced engineering software. A numerical model of the patient's foot was generated and used to design an ankle-foot orthosis model using SolidWorks. The designed model was mechanically analyzed by the finite element method using ANSYS Workbench 16.1 under different static and dynamic loading conditions. The ankle-foot orthosis model was numerically designed and analyzed before the manufacturing process. This is believed to reduce time and material loss and foster the use of numerical models in biomedical applications. This study suggests focusing on the design and analysis of orthoses according to the patient's measurements. This is expected to increase the comfort and raise the level of treatment. Numerical design methods also enable precise manufacturing using computerized devices such as three-dimensional printers.

Context-aware energy-efficient applications for cyber-physical systems

Software systems have a strong impact on the energy consumption of the hardware they use. This is especially important for cyber-physical systems where power consumption strongly influences the battery life. For this reason, software developers should be more aware of the energy consumed by their systems. Moreover, software systems should be developed to adapt their behavior to minimize the energy consumed during their execution. This can be done by monitoring the usage context of the system and having runtime support to react to those changes that impact the energy footprint negatively. Although both the hardware and the software parts of cyber-physical systems can be adapted to reduce its energy consumption, this paper focuses on software adaptation. Concretely, the paper illustrates how to address the problem of developing context-aware energy-efficient applications using a Green Eco-Assistant that makes use of advanced software engineering methods, such as Dynamic Software Product Lines and Separation of Concerns. The main steps of our approach are illustrated by applying them to a cyber-physical system case study.

Applying a maturity model during a software engineering course – How planning and task-solving processes influence the course performance

In industry, the benefit of maturity models is uncontested, and models like CMMI are normally taught in at least advanced software engineering courses. However, when not being part of real-world projects, the added values are difficult to be experienced on first hand by our students. In this paper we report on a study and teaching approach where, in three successive semesters and at two different institutions, we started rating the process-maturity of students solving tasks in our software engineering courses and transparently related the maturity levels to the task performances. It turned out that not only the quality of the students’ task preparation plays a crucial role, but that there is also a non-negligible correlation between the individual process maturity and performances. Considering this finding, the approach might yield to students’ process-improvement steps during our courses, help in fostering the understanding of the term process maturity, and finally, also might help in improving the overall students’ performances.