Farshid Rashidiyan, Seyed Rasoul Mirghaderi, Saeed Mohebbi and Sina Kavei
This research study focuses on investigating the seismic performance of non-straight beams in steel structures and exploring the mechanism by which plastic hinges are formed…
Abstract
Purpose
This research study focuses on investigating the seismic performance of non-straight beams in steel structures and exploring the mechanism by which plastic hinges are formed within these beams. The findings contribute to the understanding of their behaviour under seismic loads and offer insights into their potential for enhancing the lateral resistance of the structure. The abstract of the study highlights the significance of corners in structural plans, where non-coaxial columns, diagonal elements or beams deviating from a straight path are commonly observed. Typically, these non-straight beams are connected to the columns using pinned connections, despite their unknown seismic behaviour. Recognizing the importance of generating plastic hinges in special moment resisting frames and the lack of previous research on the involvement of these non-straight beams, this study aims to address this knowledge gap.
Design/methodology/approach
This study examines the seismic behaviour and plastic hinge formation of non-straight beams in steel structures. Non-straight beams are beams that connect non-coaxial columns and diagonal elements, or deviate from a linear path. They are usually pinned to the columns, and their seismic contribution is unknown. A critical case with a 12-m non-straight beam is analysed using Abaqus software. Different models are created with varying cross-section shapes and connection types between the non-straight beams. The models are subjected to lateral monotonic and cyclic loads in one direction. The results show that non-straight beams increase the lateral stiffness, strength and energy dissipation of the models compared to disconnected beams that act as two cantilevers.
Findings
The analysis results reveal several key findings. The inclusion of non-straight beams in the models leads to increased lateral stiffness, strength and energy dissipation compared to the scenario where the beams are disconnected and act as two cantilever beams. Plastic hinges are formed at both ends of the non-straight beam when a 3% drift is reached, contributing to energy damping and introducing plasticity into the structure. These results strongly suggest that non-straight beams play a significant role in enhancing the lateral resistance of the system. Based on the seismic analysis results, this study recommends the utilization of non-straight beams in special moment frames due to the formation of plastic hinges within these beams and their effective participation in resisting lateral seismic loads. This research fills a critical gap in understanding the behaviour of non-straight beams and provides valuable insights for structural engineers involved in the design and analysis of steel structures.
Originality/value
The authors believe that this research will greatly contribute to the knowledge and understanding of the seismic performance of non-straight beams in steel structures.
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Keywords
A. Kaveh, H. Rahami, S.R. Mirghaderi and M. Ardalan Asl
In the analysis of some near‐regular structures one can solve the regular part independently and then superimpose the effect of the additional part. For such models, the matrices…
Abstract
Purpose
In the analysis of some near‐regular structures one can solve the regular part independently and then superimpose the effect of the additional part. For such models, the matrices corresponding to regular part have canonical forms and their eigensolution or inversion can easily be performed. The effect of member changing the regular to a near‐regular structure can then be added. The purpose of this paper is to analyze near‐regular structures using the force method.
Design/methodology/approach
The paper uses the force method, and instead of selecting a statically determinate basic structure (standard method), the paper employs the regular part of the structure as the basic structure.
Findings
A new algebraic method is introduced for the force method of analysis for efficient analysis of large near‐regular structures.
Originality/value
In this paper, the force method is used, however, instead of selecting a statically determinate basic structure, the regular part of the structure is employed as the basic structure. Those additional elements are considered as redundant elements. This method is applied to truss and frame structures. In the present approach it is possible to have missing elements instead of additional elements.
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Nabi Moradpour, Ahmad Pourahmad, Hossein Hataminejad, Keramatollah Ziari and Ayyoob Sharifi
In Iran, the frequent occurrence of disasters has always been a major problem. In recent decades, disasters have created considerable challenges, especially in cities. Hence…
Abstract
Purpose
In Iran, the frequent occurrence of disasters has always been a major problem. In recent decades, disasters have created considerable challenges, especially in cities. Hence, understanding the levels of urban resilience (UR) and planning for addressing vulnerabilities plays a key role in the era of increasing risks and uncertainties. The present study aims to provide a comprehensive overview of the state of resilience of Iranian cities.
Design/methodology/approach
A systematic literature review method was used to determine how resilient Iranian cities are. To find relevant studies, the authors searched Iranian and international databases such as Scopus, ScienceDirect, SID and Magiran. There was no restriction on the inclusion date, meaning that all papers published up until September 16, 2021 were considered for inclusion. The PRISMA framework was used for literature search and selection and, finally, 153 studies focused on 52 cities of Iran were selected for the systematic review.
Findings
In general, the results showed that the level of resilience was low in Iranian cities. Also, informal settlements, worn-out urban fabrics and the central parts of cities showed lower resilience than other parts.
Originality/value
The results of the study can be used to inform municipal authorities, urban planners and non-governmental organizations of the actions that need to be taken to enhance the resilience of Iranian cities.
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This paper aims to develop a simple model for estimating sustainable development goals index using the capabilities of artificial neural networks.
Abstract
Purpose
This paper aims to develop a simple model for estimating sustainable development goals index using the capabilities of artificial neural networks.
Design/methodology/approach
Sustainable development has three pillars, including social, economic and environmental pillars. Three clusters corresponding to the three pillars were created by extracting sub-indices of three 2018 global reports and performing cluster analysis on the correlation matrix of sub-indices. By setting the sustainable development goals index as the target variable and selecting one indicator from each cluster as input variables, 20 artificial neural networks were run 30 times.
Findings
Artificial neural networks with seven nodes in one hidden layer can estimate sustainable development goals index by using just three inputs, including ecosystem vitality, human capital and gross national income per capita. There is an excellent similarity (>95%) between the results of the artificial neural network and the sustainable development goals index.
Practical implications
Instead of calculating 232 indicators for determining the value of sustainable development goals index, it is possible to use only three sub-indices, but missing 5% of precision, by using the proposed artificial neural network model.
Originality/value
The study provides additional information on the estimating of sustainable development and proposes a new simple method for estimating the sustainable development goals index. It just uses three sub-indices, which can be retrieved from three global reports.
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A. Kaveh, H. Rahami and Iman Shojaei
The purpose of this paper is to present an efficient method for dynamic analysis of structures utilizing a modal analysis with the main purpose of decreasing the computational…
Abstract
Purpose
The purpose of this paper is to present an efficient method for dynamic analysis of structures utilizing a modal analysis with the main purpose of decreasing the computational complexity of the problem. In traditional methods, the solution of initial-value problems (IVPs) using numerical methods like finite difference method leads to step by step and time-consuming recursive solutions.
Design/methodology/approach
The present method is based on converting the IVP into boundary-value problems (BVPs) and utilizing the features of the latter problems in efficient solution of the former ones. Finite difference formulation of BVPs leads to matrices with repetitive tri-diagonal and block tri-diagonal patterns wherein the eigensolution and matrix inversion are obtained using graph products rules. To get advantage of these efficient solutions for IVPs like the dynamic analysis of single DOF systems, IVPs are converted to boundary-value ones using mathematical manipulations. The obtained formulation is then generalized to the multi DOF systems by utilizing modal analysis.
Findings
Applying the method to the modal analysis leads to a simple and efficient formulation. The laborious matrix inversion and eigensolution operations, of computational complexities of O(n2.373) and O(n3), respectively, are converted to a closed-form formulation with summation operations.
Research limitations/implications
No limitation.
Practical implications
Swift analysis has become possible.
Originality/value
Suitability of solving IVPs and modal analysis using conversion and graph product rules is presented and applied to efficient seismic optimal analysis and preliminary design.
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Keywords
Raunaque Mujeeb Quaiser and Praveen Ranjan Srivastava
This research aims to identify the key factors affecting Outbound Open Innovation between Startups and Big organizations using the multiple criteria decision-making analysis…
Abstract
Purpose
This research aims to identify the key factors affecting Outbound Open Innovation between Startups and Big organizations using the multiple criteria decision-making analysis (MCDM) approach. The MCDM technique ranks the four key factors identified from the literature study that can help to improve collaboration opportunities with Startups.
Design/methodology/approach
Identification of key factors affecting Outbound Open Innovation between Startups and big organizations based on extant literature. A questionnaire is prepared based on these four identified key factors to gather views of the startup's employees, from the designer level to the startup's founder. MCDM techniques are used to evaluate the questionnaire. The ensemble technique is used to rank the key factors coming from three different MCDM methods.
Findings
The findings from the MCDM approach and Ensemble techniques give insight to the big organizations to facilitate outbound Open Innovation effectively. It also provides insight into the requirements of the startups and the kind of support they seek from the big organizations. The ranking can help the big organization close the gaps and make an informed decision to increase the effectiveness of the collaborations and boost innovation.
Originality/value
This is a unique research work where the MCDM approach is used to identify the ranking of key factors affecting outbound open innovation between startups and big organizations. The MCDM technique is followed by the ensemble method to rationalize the findings. Technology Relevance ranks highest, followed by Innovation Ecosystem, Organization commitment and Knowledge Sharing.
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Samia Chebira, Noureddine Bourmada, Abdelali Boughaba and Mebarek Djebabra
The increasing complexity of industrial systems is at the heart of the development of many fault diagnosis methods. The artificial neural networks (ANNs), which are part of these…
Abstract
Purpose
The increasing complexity of industrial systems is at the heart of the development of many fault diagnosis methods. The artificial neural networks (ANNs), which are part of these methods, are widely used in fault diagnosis due to their flexibility and diversification which makes them one of the most appropriate fault diagnosis methods. The purpose of this paper is to detect and locate in real time any parameter deviations that can affect the operation of the blowout preventer (BOP) system using ANNs.
Design/methodology/approach
The starting data are extracted from the tables of the HAZOP (HAZard and OPerability) method where the deviations of the parameters of normal BOP operating (pressure, flow, level and temperature) are associated with an initial rule base for establishing cause and effect of relationships between the causes of deviations and their consequences; these data are used as a database for the neural network. Three ANNs were used, the multi-layer perceptron network (MLPN), radial basis functions network (RBFN) and generalized regression neural networks (GRNN). These models were trained and tested, then, their comparative performances were presented. The respective performances of these models are highlighted following their application to the BOP system.
Findings
The performances of the models are evaluated using determination coefficient (R2), root mean square error (RMSE) and mean absolute error (MAE) statistics and time execution. The results of this study show that the RMSE, MAE and R2 values of the GRNN model are better than those corresponding to the RBFN and MLPN models. The GRNN model can be applied with better performance, to establish a diagnostic model that can detect and to identify the different causes of deviations in the parameters of the BOP system.
Originality/value
The performance of the trained network is found to be satisfactory for the real-time fault diagnosis. Therefore, future studies on modeling the BOP system with soft computing techniques can be concentrated on the ANNs. Consequently, with the use of these techniques, the performance of the BOP system can be ensured performing only a limited number of monitoring operations, thus saving engineering effort, time and funds.
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Ghazzali N. Nadanveettil, Ibnu Noufal Kambitta Valappil, Hadungshar Swargiary and R. Sevukan
This study aims to present scientometric mapping and altmetric analysis of publications related to “Hockey” in the past three decades. By using the advanced analytical techniques…
Abstract
Purpose
This study aims to present scientometric mapping and altmetric analysis of publications related to “Hockey” in the past three decades. By using the advanced analytical techniques of mapping coupled with altmetric analysis, this paper aims to reveal the complex network of collaborations, the dispersion of expertise worldwide and prevailing thematic trends in the field of hockey.
Design/methodology/approach
The data was extracted from the Web of Science (WoS) database and Altmetric Explorer for articles related to hockey over the past three decades. VOSviewer was used to conduct network analysis whereas MS-Excel was used for altmetric data analysis. The study focused on the articles retrieved using the key term “Hockey” in English language publications. The altmetric attention scores (AAS) were used to measure the level of online attention on different platforms, complementing traditional bibliometric analysis.
Findings
The study reveals a notable increase in the productivity of hockey research over the past 30 years, with a specific focus on major surges in publication output and altmetric attention in recent times. Coauthorship and country-wise mapping analysis highlight global research collaboration trends, while keyword analysis underscores thematic concentrations. Key journals such as British Journal of Sports Medicine and American Journal of Sports Medicine emerge as crucial dissemination platforms. The importance of X posts (Formerly Twitter) and Mendeley in the diffusion of hockey literature is highlighted by altmetric research.
Originality/value
The study provides a concise overview of research conducted on the game of hockey. This research will be advantageous for researchers and individuals involved in the hockey community, as it offers bibliographic insights and aids in identifying suitable media for disseminating their findings.
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Hichem Aouag, Mohyiddine Soltani and Mohamed Djamel Mouss
This paper aims to investigate an integrated approach that aims at enhancing the application process of value stream mapping (VSM) method. It also proposes an extended VSM called…
Abstract
Purpose
This paper aims to investigate an integrated approach that aims at enhancing the application process of value stream mapping (VSM) method. It also proposes an extended VSM called Economic and Environmental VSM(E-EVSM). The proposed approach highlights the improvement of economic and environmental performances.
Design/methodology/approach
The proposed approach has studied the integration of VSM, fuzzy decision-making trial and evaluation laboratory (DEMATEL) and fuzzy quality function deployment (QFD) to improve the economic and environmental performances of manufacturing processes. The VSM method is used for data collection and manufacturing process assessment, whereas fuzzy DEMATEL is used to analyse the current state map. Finally, fuzzy QFD is used to organize the improvement phase of VSM method.
Findings
The clear findings of this research prove the effectiveness of VSM method on the environmental and economic performances of manufacturing processes. In addition, the proposed approach will show the advantages of fuzzy DEMATEL and fuzzy QFD approaches in improving the application of the VSM method.
Research limitations/implications
The limitation of this study includes the lack of consideration of other dimensions such as social, technological and managerial. In addition, the proposed approach studied an average set of environmental and economic indicators.
Originality/value
The novelty of the proposed approach is proved by the development of an extended VSM method (E-EVSM). Also, the proposed approach contributes by a new methodology for analysing and improving the current state map of manufacturing processes.