M. Granata, Benedetta Fontana, Marco Rosone, Giovanni Culotta
In steel tied arch bridges where the hangers are made of rigid bars, the replacement of damaged hangers is rather complex. In fact, while generally the cable hangers are already prepared with anchors at the ends and their replacement traces the initial stages of construction with their prestressing, on the contrary, the rigid bars are welded to the arch and the deck, so their replacement must include the design of a new suspension system that allows the insertion of a pretension where this had never been considered. To check the reliability of this new system, a prototype of tensioner was studied for the case of a steel arch bridge in which the high level of corrosion made it necessary to replace all the original hangers with new ones. This entailed the need to test the tensioner performance with the aim of ensuring the axial force transmission between the two hanger segments without slippage in the threads, as well as to test the correct tension setting before construction and putting into service the hangers to be replaced. For this reason, a predictive experimental campaign was carried out on a prototype by means of tests for the mechanical characterization of the materials used, tensile tests of the system, and tensioning tests under load, measuring the displacements and strains of the system elements. The results of the tests, with slippage in the threads limited to the 2% of total elongation, and the turnaround-stressing curves were useful for the definition of the pieces to be assembled during on-site work and for addressing the operating procedures of the tensioning phases on-site during hanger replacement. Validation with the on-site monitoring of stressing operation was conducted at the end; the monitoring of tension through dynamic tests confirmed the agreement of on-site results with the predictive loading tests of the experimental campaign on the tensioner prototype.
{"title":"Experimental Behaviour of Tensioner for Rigid Hangers of Arch Bridges","authors":"M. Granata, Benedetta Fontana, Marco Rosone, Giovanni Culotta","doi":"10.3390/designs8030055","DOIUrl":"https://doi.org/10.3390/designs8030055","url":null,"abstract":"In steel tied arch bridges where the hangers are made of rigid bars, the replacement of damaged hangers is rather complex. In fact, while generally the cable hangers are already prepared with anchors at the ends and their replacement traces the initial stages of construction with their prestressing, on the contrary, the rigid bars are welded to the arch and the deck, so their replacement must include the design of a new suspension system that allows the insertion of a pretension where this had never been considered. To check the reliability of this new system, a prototype of tensioner was studied for the case of a steel arch bridge in which the high level of corrosion made it necessary to replace all the original hangers with new ones. This entailed the need to test the tensioner performance with the aim of ensuring the axial force transmission between the two hanger segments without slippage in the threads, as well as to test the correct tension setting before construction and putting into service the hangers to be replaced. For this reason, a predictive experimental campaign was carried out on a prototype by means of tests for the mechanical characterization of the materials used, tensile tests of the system, and tensioning tests under load, measuring the displacements and strains of the system elements. The results of the tests, with slippage in the threads limited to the 2% of total elongation, and the turnaround-stressing curves were useful for the definition of the pieces to be assembled during on-site work and for addressing the operating procedures of the tensioning phases on-site during hanger replacement. Validation with the on-site monitoring of stressing operation was conducted at the end; the monitoring of tension through dynamic tests confirmed the agreement of on-site results with the predictive loading tests of the experimental campaign on the tensioner prototype.","PeriodicalId":53150,"journal":{"name":"Designs","volume":"339 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141386151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to address the Multi-Objective Optimization Problem (MOOP) in building a two-stage helical gearbox, this work presents a novel application of the Multi-Criterion Decision-Making (MCDM) method. The aim of the study is to determine the optimal primary design factors that will increase gearbox efficiency while decreasing gearbox volume. Three main design parameters were chosen for assessment in this work: the first stage’s gear ratio, and the first and second stages’ Coefficients of Wheel Face Width (CWFW). In addition, the MOOP is divided into two phases: phase 1 solves the single-objective optimization problem to reduce the gap between variable levels, and phase 2 solves the MOOP to determine the optimal primary design factors. Furthermore, the Entropy approach was picked to compute the weight criteria, and the MARCOS method was chosen as an MCDM method to handle the multi-objective optimization issue. The following are important characteristics of the study: Firstly, the MCDM method (MARCOS technique) was successfully applied to solve a MOOP for the first time. Secondly, this work has looked into power losses during idle motion to calculate the efficiency of a two-stage helical gearbox. The results of the study were used in the design of a two-stage helical gearbox in order to identify the optimal values for three important design parameters.
{"title":"Multi-Objective Optimization of a Two-Stage Helical Gearbox Using MARCOS Method","authors":"Van-Thanh Dinh, Huu-Danh Tran, Quoc-Hung Tran, D. Vu, Duong Vu, Ngoc-Pi Vu, Thanh-Tu Nguyen","doi":"10.3390/designs8030053","DOIUrl":"https://doi.org/10.3390/designs8030053","url":null,"abstract":"In order to address the Multi-Objective Optimization Problem (MOOP) in building a two-stage helical gearbox, this work presents a novel application of the Multi-Criterion Decision-Making (MCDM) method. The aim of the study is to determine the optimal primary design factors that will increase gearbox efficiency while decreasing gearbox volume. Three main design parameters were chosen for assessment in this work: the first stage’s gear ratio, and the first and second stages’ Coefficients of Wheel Face Width (CWFW). In addition, the MOOP is divided into two phases: phase 1 solves the single-objective optimization problem to reduce the gap between variable levels, and phase 2 solves the MOOP to determine the optimal primary design factors. Furthermore, the Entropy approach was picked to compute the weight criteria, and the MARCOS method was chosen as an MCDM method to handle the multi-objective optimization issue. The following are important characteristics of the study: Firstly, the MCDM method (MARCOS technique) was successfully applied to solve a MOOP for the first time. Secondly, this work has looked into power losses during idle motion to calculate the efficiency of a two-stage helical gearbox. The results of the study were used in the design of a two-stage helical gearbox in order to identify the optimal values for three important design parameters.","PeriodicalId":53150,"journal":{"name":"Designs","volume":"313 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141386262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Manuel Mejía Rodríguez, O. González-Estrada, D. Villegas-Bermúdez
This work presents the study of the thickness vs. stiffness relationship for different materials (PMMA and PEEK) in patient-specific cranial implants, as a criterion for the selection of biomaterials from a mechanical perspective. The geometry of the implant is constructed from the reconstruction of the cranial lesion using image segmentation obtained from computed axial tomography. Different design parameters such as thickness and perforations are considered to obtain displacement distributions under critical loading conditions using finite element analysis. The models consider quasi-static loads with linear elastic materials. The null hypothesis underlying this research asserts that both biomaterials exhibit the minimum mechanical characteristics necessary to withstand direct impact trauma at the implant center, effectively averting critical deformations higher than 2 mm. In this way, the use of PMMA cranioplasties is justified in most cases where a PEEK implant cannot be accessed.
{"title":"Finite Element Analysis of Patient-Specific Cranial Implants under Different Design Parameters for Material Selection","authors":"Manuel Mejía Rodríguez, O. González-Estrada, D. Villegas-Bermúdez","doi":"10.3390/designs8020031","DOIUrl":"https://doi.org/10.3390/designs8020031","url":null,"abstract":"This work presents the study of the thickness vs. stiffness relationship for different materials (PMMA and PEEK) in patient-specific cranial implants, as a criterion for the selection of biomaterials from a mechanical perspective. The geometry of the implant is constructed from the reconstruction of the cranial lesion using image segmentation obtained from computed axial tomography. Different design parameters such as thickness and perforations are considered to obtain displacement distributions under critical loading conditions using finite element analysis. The models consider quasi-static loads with linear elastic materials. The null hypothesis underlying this research asserts that both biomaterials exhibit the minimum mechanical characteristics necessary to withstand direct impact trauma at the implant center, effectively averting critical deformations higher than 2 mm. In this way, the use of PMMA cranioplasties is justified in most cases where a PEEK implant cannot be accessed.","PeriodicalId":53150,"journal":{"name":"Designs","volume":"95 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140377533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Indonesia is situated on the Ring of Fire, which causes a lot of earthquakes. On the 28 September 2018, there was an earthquake in Palu, Sulawesi Island, Indonesia, which was one of the strongest shakings since 1980. Surprisingly, most traditional houses in Sulawesi survived. There has been some research on adapting traditional house structures to modern residential buildings. The limited availability of wood and complicated construction make adapting wood structures to current conditions challenging. The purpose of this study is to analyze space organization in ten traditional South Sulawesi house designs. A possible evacuation route can be found through the analysis as the first space for expeditiously escaping from an earthquake. In addition, modernizing the layout of a traditional South Sulawesi house and introducing it to local people was easy since they were familiar with the design. A deep analysis of spatial organization and its interrelations can help develop realistic designs, plans, and knowledge, thus improving the quality of residential projects. A descriptive qualitative method was used as a research method. Data were collected from field observations, brief interviews, and literature reviews. In order to analyz thee data, ORA-LITE was used to redraw the data and create the charts. It was found that different cultures have different evacuation spaces, in this case the Bugis tribe and the Toraja tribe. A corridor and kitchen were the most strategically located areas that could possibly be used for evacuation. Considering the differences in culture among tribes, designing evacuation spaces based on local culture was important. A recommendation based on this finding can also be made to the government of South Sulawesi in the design of residential houses.
{"title":"The Design of Earthquake Evacuation Spaces Based on Local Wisdom: A Case Study of Traditional Houses in South Sulawesi","authors":"D. P. Sari, Mutmainnah Sudirman, Andi Asmuliany","doi":"10.3390/designs8020030","DOIUrl":"https://doi.org/10.3390/designs8020030","url":null,"abstract":"Indonesia is situated on the Ring of Fire, which causes a lot of earthquakes. On the 28 September 2018, there was an earthquake in Palu, Sulawesi Island, Indonesia, which was one of the strongest shakings since 1980. Surprisingly, most traditional houses in Sulawesi survived. There has been some research on adapting traditional house structures to modern residential buildings. The limited availability of wood and complicated construction make adapting wood structures to current conditions challenging. The purpose of this study is to analyze space organization in ten traditional South Sulawesi house designs. A possible evacuation route can be found through the analysis as the first space for expeditiously escaping from an earthquake. In addition, modernizing the layout of a traditional South Sulawesi house and introducing it to local people was easy since they were familiar with the design. A deep analysis of spatial organization and its interrelations can help develop realistic designs, plans, and knowledge, thus improving the quality of residential projects. A descriptive qualitative method was used as a research method. Data were collected from field observations, brief interviews, and literature reviews. In order to analyz thee data, ORA-LITE was used to redraw the data and create the charts. It was found that different cultures have different evacuation spaces, in this case the Bugis tribe and the Toraja tribe. A corridor and kitchen were the most strategically located areas that could possibly be used for evacuation. Considering the differences in culture among tribes, designing evacuation spaces based on local culture was important. A recommendation based on this finding can also be made to the government of South Sulawesi in the design of residential houses.","PeriodicalId":53150,"journal":{"name":"Designs","volume":" 92","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140384340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. M. Tavares, João A. Ribeiro, Bruno A. Ribeiro, P. D. de Castro
Numerical modeling tools are essential in aircraft structural design, yet they face challenges in accurately reflecting real-world behavior due to factors like material properties scatter and manufacturing-induced deviations. This article addresses the potential impact of digital twins on overcoming these limitations and enhancing model reliability through advanced updating techniques based on machine learning. Digital twins, which are virtual replicas of physical systems, offer a promising solution by integrating sensor data, operational inputs, and historical records. Machine learning techniques enable the calibration and validation of models, combining experimental inputs with simulations through continuous updating processes that refine digital twins, improving their accuracy in predicting structural behavior and performance throughout an aircraft’s life cycle. These refined models enable real-time monitoring and precise damage assessment, supporting decision making in diverse contexts. By integrating sensor data and updating techniques, digital twins contribute to improved design and maintenance operations by providing valuable insights into structural health, safety, and reliability. Ultimately, this approach leads to more efficient and safer aviation operations, demonstrating the potential of digital twins to revolutionize aircraft structural analysis and design. This article explores various advancements and methodologies applicable to structural assessment, leveraging machine learning tools. These include the utilization of physics-informed neural networks, which enable the handling of diverse uncertainties. Such approaches empower a more informed and adaptive strategy, contributing to the assurance of structural integrity and safety in aircraft structures throughout their operational life.
{"title":"Aircraft Structural Design and Life-Cycle Assessment through Digital Twins","authors":"S. M. Tavares, João A. Ribeiro, Bruno A. Ribeiro, P. D. de Castro","doi":"10.3390/designs8020029","DOIUrl":"https://doi.org/10.3390/designs8020029","url":null,"abstract":"Numerical modeling tools are essential in aircraft structural design, yet they face challenges in accurately reflecting real-world behavior due to factors like material properties scatter and manufacturing-induced deviations. This article addresses the potential impact of digital twins on overcoming these limitations and enhancing model reliability through advanced updating techniques based on machine learning. Digital twins, which are virtual replicas of physical systems, offer a promising solution by integrating sensor data, operational inputs, and historical records. Machine learning techniques enable the calibration and validation of models, combining experimental inputs with simulations through continuous updating processes that refine digital twins, improving their accuracy in predicting structural behavior and performance throughout an aircraft’s life cycle. These refined models enable real-time monitoring and precise damage assessment, supporting decision making in diverse contexts. By integrating sensor data and updating techniques, digital twins contribute to improved design and maintenance operations by providing valuable insights into structural health, safety, and reliability. Ultimately, this approach leads to more efficient and safer aviation operations, demonstrating the potential of digital twins to revolutionize aircraft structural analysis and design. This article explores various advancements and methodologies applicable to structural assessment, leveraging machine learning tools. These include the utilization of physics-informed neural networks, which enable the handling of diverse uncertainties. Such approaches empower a more informed and adaptive strategy, contributing to the assurance of structural integrity and safety in aircraft structures throughout their operational life.","PeriodicalId":53150,"journal":{"name":"Designs","volume":" 39","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140211514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Total knee arthroplasty (TKA) stands out as one of the most widely employed surgical procedures, establishing itself as the preferred method for addressing advanced osteoarthritis of the knee. However, current knee prostheses require refined design solutions. This research work focuses on a computational analysis of both the mechanical behavior of a knee joint implant and the bone remodeling process in the tibia following implantation. This research study delves into how specific design parameters, particularly the stem geometry, impact the prosthesis’s performance. Utilizing a computed tomography scan of a tibia, various TKA configurations were simulated to conduct analyses employing advanced discretization techniques, such as the finite element method (FEM) and the radial point interpolation method (RPIM). The findings reveal that the introduction of the implant leads to a marginal increase in the stress values within the tibia, accompanied by a reduction in the displacement field values. The insertion of the longest tested implant increased the maximum stress from 5.0705 MPa to 6.1584 MPa, leading to a displacement reduction from 0.016 mm to 0.0142 mm. Finally, by combining the FEM with a bone remodeling algorithm, the bone remodeling process of the tibia due to an implant insertion was simulated.
{"title":"The Biomechanical Analysis of Tibial Implants Using Meshless Methods: Stress and Bone Tissue Remodeling Analysis","authors":"Ana Pais, Catarina Moreira, Jorge Belinha","doi":"10.3390/designs8020028","DOIUrl":"https://doi.org/10.3390/designs8020028","url":null,"abstract":"Total knee arthroplasty (TKA) stands out as one of the most widely employed surgical procedures, establishing itself as the preferred method for addressing advanced osteoarthritis of the knee. However, current knee prostheses require refined design solutions. This research work focuses on a computational analysis of both the mechanical behavior of a knee joint implant and the bone remodeling process in the tibia following implantation. This research study delves into how specific design parameters, particularly the stem geometry, impact the prosthesis’s performance. Utilizing a computed tomography scan of a tibia, various TKA configurations were simulated to conduct analyses employing advanced discretization techniques, such as the finite element method (FEM) and the radial point interpolation method (RPIM). The findings reveal that the introduction of the implant leads to a marginal increase in the stress values within the tibia, accompanied by a reduction in the displacement field values. The insertion of the longest tested implant increased the maximum stress from 5.0705 MPa to 6.1584 MPa, leading to a displacement reduction from 0.016 mm to 0.0142 mm. Finally, by combining the FEM with a bone remodeling algorithm, the bone remodeling process of the tibia due to an implant insertion was simulated.","PeriodicalId":53150,"journal":{"name":"Designs","volume":"22 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140226945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lung cancer is identified by the uncontrolled proliferation of cells in lung tissues. The timely detection of malignant cells in the lungs, crucial for processes such as oxygen provision and carbon dioxide elimination in the human body, is imperative. The application of deep learning for discerning lymph node involvement in CT scans and histopathological images has garnered widespread attention due to its potential impact on patient diagnosis and treatment. This paper suggests employing DenseNet for lung cancer detection, leveraging its ability to transmit learned features backward through each layer continuously. This characteristic not only reduces model parameters but also enhances the learning of local features, facilitating a better comprehension of the structural complexity and uneven distribution in CT scans and histopathological cancer images. Furthermore, DenseNet accompanied by an attention mechanism (ATT-DenseNet) allows the model to focus on specific parts of an image, giving more weight to relevant regions. Compared to existing algorithms, the ATT-DenseNet demonstrates a remarkable enhancement in accuracy, precision, recall, and the F1-Score. It achieves an average improvement of 20% in accuracy, 19.66% in precision, 24.33% in recall, and 22.33% in the F1-Score across these metrics. The motivation behind the research is to leverage deep learning technologies to enhance the precision and reliability of lung cancer diagnostics, thus addressing the gap in early detection and treatment. This pursuit is driven by the potential of deep learning models, like DenseNet, to provide significant improvements in analyzing complex medical images for better clinical outcomes.
{"title":"Attention-Based DenseNet for Lung Cancer Classification Using CT Scan and Histopathological Images","authors":"Jia Uddin","doi":"10.3390/designs8020027","DOIUrl":"https://doi.org/10.3390/designs8020027","url":null,"abstract":"Lung cancer is identified by the uncontrolled proliferation of cells in lung tissues. The timely detection of malignant cells in the lungs, crucial for processes such as oxygen provision and carbon dioxide elimination in the human body, is imperative. The application of deep learning for discerning lymph node involvement in CT scans and histopathological images has garnered widespread attention due to its potential impact on patient diagnosis and treatment. This paper suggests employing DenseNet for lung cancer detection, leveraging its ability to transmit learned features backward through each layer continuously. This characteristic not only reduces model parameters but also enhances the learning of local features, facilitating a better comprehension of the structural complexity and uneven distribution in CT scans and histopathological cancer images. Furthermore, DenseNet accompanied by an attention mechanism (ATT-DenseNet) allows the model to focus on specific parts of an image, giving more weight to relevant regions. Compared to existing algorithms, the ATT-DenseNet demonstrates a remarkable enhancement in accuracy, precision, recall, and the F1-Score. It achieves an average improvement of 20% in accuracy, 19.66% in precision, 24.33% in recall, and 22.33% in the F1-Score across these metrics. The motivation behind the research is to leverage deep learning technologies to enhance the precision and reliability of lung cancer diagnostics, thus addressing the gap in early detection and treatment. This pursuit is driven by the potential of deep learning models, like DenseNet, to provide significant improvements in analyzing complex medical images for better clinical outcomes.","PeriodicalId":53150,"journal":{"name":"Designs","volume":"25 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140234660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cyber-physical systems, cloud computing, the Internet of Things, and big data play significant roles in shaping digital and automated landscape manufacturing. However, to fully realize the potential of these technologies and achieve tangible benefits, such as reduced manufacturing lead times, improved product quality, and enhanced organizational performance, new decision support models need development. Game theory offers a promising approach to address multi-objective problems and streamline decision-making processes, thereby reducing computational time. This paper aims to provide a comprehensive and up-to-date systematic review of the literature on the application of game theory models in various areas of digital manufacturing, including production and capacity planning, scheduling, sustainable production systems, and cloud manufacturing. This review identifies key research themes that have been explored and examines the main research gaps that exist within these domains. Furthermore, this paper outlines potential future research directions to inspire both researchers and practitioners to further explore and develop game theory models that can effectively support the digital transformation of manufacturing systems.
{"title":"A Review of Game Theory Models to Support Production Planning, Scheduling, Cloud Manufacturing and Sustainable Production Systems","authors":"P. Renna","doi":"10.3390/designs8020026","DOIUrl":"https://doi.org/10.3390/designs8020026","url":null,"abstract":"Cyber-physical systems, cloud computing, the Internet of Things, and big data play significant roles in shaping digital and automated landscape manufacturing. However, to fully realize the potential of these technologies and achieve tangible benefits, such as reduced manufacturing lead times, improved product quality, and enhanced organizational performance, new decision support models need development. Game theory offers a promising approach to address multi-objective problems and streamline decision-making processes, thereby reducing computational time. This paper aims to provide a comprehensive and up-to-date systematic review of the literature on the application of game theory models in various areas of digital manufacturing, including production and capacity planning, scheduling, sustainable production systems, and cloud manufacturing. This review identifies key research themes that have been explored and examines the main research gaps that exist within these domains. Furthermore, this paper outlines potential future research directions to inspire both researchers and practitioners to further explore and develop game theory models that can effectively support the digital transformation of manufacturing systems.","PeriodicalId":53150,"journal":{"name":"Designs","volume":"3 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140239115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sidorela Caushaj, Giovanni Imberti, Henrique de Carvalho Pinheiro, M. Carello
This article focuses on modelling and validating a groundbreaking magnetorheological braking system. Addressing shortcomings in traditional automotive friction brake systems, including response delays, wear, and added mass from auxiliary components, the study employs a novel brake design combining mechanical and electrical elements for enhanced efficiency. Utilizing magnetorheological (MR) technology within a motor–brake system, the investigation explores the influence of external magnetic flux from the nearby motor on MR fluid movement, particularly under high-flux conditions. The evaluation of a high-magnetic-field mitigator is guided by simulated findings with the objective of resolving potential issues. An alternative method of resolving an interaction between an electric motor and a magnetorheological brake is presented. In addition, to test four configurations, multiple absorber materials are reviewed.
{"title":"Electromagnetic Interaction Model between an Electric Motor and a Magnetorheological Brake","authors":"Sidorela Caushaj, Giovanni Imberti, Henrique de Carvalho Pinheiro, M. Carello","doi":"10.3390/designs8020025","DOIUrl":"https://doi.org/10.3390/designs8020025","url":null,"abstract":"This article focuses on modelling and validating a groundbreaking magnetorheological braking system. Addressing shortcomings in traditional automotive friction brake systems, including response delays, wear, and added mass from auxiliary components, the study employs a novel brake design combining mechanical and electrical elements for enhanced efficiency. Utilizing magnetorheological (MR) technology within a motor–brake system, the investigation explores the influence of external magnetic flux from the nearby motor on MR fluid movement, particularly under high-flux conditions. The evaluation of a high-magnetic-field mitigator is guided by simulated findings with the objective of resolving potential issues. An alternative method of resolving an interaction between an electric motor and a magnetorheological brake is presented. In addition, to test four configurations, multiple absorber materials are reviewed.","PeriodicalId":53150,"journal":{"name":"Designs","volume":"8 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140244034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cities are complex systems requiring urban design models that balance order and disorder. Collective creativity initiatives engage citizens in these processes, empowering bottom-up approaches that prioritize people and social well-being within urban development. This paper investigates an ‘Urban Laboratory’ as a case study, examining the potential of collective creativity to address urban complexity. The successful and ongoing project ‘El Campo de Cebada’ in Madrid, Spain, demonstrates how a community transformed a vacant lot into a vibrant social hub. The phases of this study include case selection, data collection, data analysis, and presentation of the results. This study identifies key enabling factors, including agents, management, social dynamics, infrastructure, and actions. These insights offer a methodological framework for designing future collaborative, resilient, and inclusive urban spaces, addressing the complex needs of communities within our cities.
城市是一个复杂的系统，需要平衡有序与无序的城市设计模式。集体创造力倡议让市民参与到这些过程中，授权自下而上的方法，在城市发展中优先考虑人和社会福祉。本文以一个 "城市实验室 "为案例，研究集体创造力在解决城市复杂性方面的潜力。西班牙马德里正在进行的成功项目 "El Campo de Cebada "展示了一个社区如何将一块空地改造成一个充满活力的社会中心。本研究的各个阶段包括案例选择、数据收集、数据分析和结果展示。本研究确定了关键的有利因素，包括代理人、管理、社会动态、基础设施和行动。这些见解为设计未来的协作性、弹性和包容性城市空间提供了方法论框架，可满足城市中各社区的复杂需求。
{"title":"Collective Creativity and Complexity in Urban Laboratories: El Campo de Cebada","authors":"Amanda Martín-Mariscal, Luz Fernández-Valderrama","doi":"10.3390/designs8020023","DOIUrl":"https://doi.org/10.3390/designs8020023","url":null,"abstract":"Cities are complex systems requiring urban design models that balance order and disorder. Collective creativity initiatives engage citizens in these processes, empowering bottom-up approaches that prioritize people and social well-being within urban development. This paper investigates an ‘Urban Laboratory’ as a case study, examining the potential of collective creativity to address urban complexity. The successful and ongoing project ‘El Campo de Cebada’ in Madrid, Spain, demonstrates how a community transformed a vacant lot into a vibrant social hub. The phases of this study include case selection, data collection, data analysis, and presentation of the results. This study identifies key enabling factors, including agents, management, social dynamics, infrastructure, and actions. These insights offer a methodological framework for designing future collaborative, resilient, and inclusive urban spaces, addressing the complex needs of communities within our cities.","PeriodicalId":53150,"journal":{"name":"Designs","volume":"26 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140264735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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