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1 – 10 of over 1000Si Chen, Haoran Lv, Yinming Zhao and Minning Wang
This paper aims to provide a new method to study and improve the dynamic characteristics of the four-column resistance strain force sensor through the elastomer structure design…
Abstract
Purpose
This paper aims to provide a new method to study and improve the dynamic characteristics of the four-column resistance strain force sensor through the elastomer structure design and optimization.
Design/methodology/approach
Based on the mechanism analysis method, the authors first present a dynamic characteristic model of the four-column resistance strain force sensors’ elastomer. Then, the authors verified and modified the model according to the Solidworks finite element simulation results. Finally, the authors designed and optimized two types of four-column elastomers based on the dynamic characteristic model and verified the improvement of sensor dynamic performance through a hammer knock dynamic experiment.
Findings
The Solidworks finite element simulation and hammer knock dynamic experiment results show that the relative error of the model is less than 10%, which confirms the accuracy of the model. The dynamic performance of the sensors based on the model can be improved by more than 30%, which is a great improvement in sensor dynamic performance.
Originality/value
The authors first present a dynamic characteristic model of the four-column elastomer and optimize the four-column sensors successfully based on the mechanism analysis method. And a new method to study and improve the dynamic characteristics of the resistance is provided.
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Marcin Figat and Agnieszka Kwiek
Tandem wing aircrafts belong to an unconventional configurations group, and this type of design is characterised by a strong aerodynamic coupling, which results in lower induced…
Abstract
Purpose
Tandem wing aircrafts belong to an unconventional configurations group, and this type of design is characterised by a strong aerodynamic coupling, which results in lower induced drag. The purpose of this paper is to determine whether a certain trend in the wingspan impact on aircraft dynamic stability can be identified. The secondary goal was to compare the response to control of flaps placed on a front and rear wing.
Design/methodology/approach
The aerodynamic data and control derivatives were obtained from the computational fluid dynamics computations performed by the MGAERO software. The equations of aircraft longitudinal motion in a state space form were used. The equations were built based on the aerodynamic coefficients, stability and control derivatives. The analysis of the dynamic stability was done in the MATLAB by solving the eigenvalue problem. The response to control was computed by the step response method using MATLAB.
Findings
The results of this study showed that because of a strong aerodynamic coupling, a nonlinear relation between the wing size and aircraft dynamic stability proprieties was observed. In the case of the flap deflection, stronger oscillation was observed for the front flap.
Originality/value
Results of dynamic stability of aircraft in the tandem wing configuration can be found in the literature, but those studies show outcomes of a single configuration, while this paper presents a comprehensive investigation into the impact of wingspan on aircraft dynamic stability. The results reveal that because of a strong aerodynamic coupling, the relation between the span factor and dynamic stability is nonlinear. Also, it has been demonstrated that the configuration of two wings with the same span is not the optimal one from the aerodynamic point of view.
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Xinghua Shan, Xiaoyan Lv, Jinfei Wu, Shuo Zhao and Junfeng Zhang
Revenue management (RM) is a significant technique to improve revenue with limited resources. With the macro environment of dramatically increasing transit capacity and rapid…
Abstract
Purpose
Revenue management (RM) is a significant technique to improve revenue with limited resources. With the macro environment of dramatically increasing transit capacity and rapid railway transport development in China, it is necessary to involve the theory of RM into the operation and decision of railway passenger transport.
Design/methodology/approach
This paper proposes the theory and framework of generalized RM of railway passenger transport (RMRPT), and the thoughts and methods of the main techniques in RMRPT, involving demand forecasting, line planning, inventory control, pricing strategies and information systems, are all studied and elaborated. The involved methods and techniques provide a sequential process to help with the decision-making for each stage of RMRPT. The corresponding techniques are integrated into the information system to support practical businesses in railway passenger transport.
Findings
The combination of the whole techniques devotes to railway benefit improvement and transit resource utilization and has been applied into the practical operation and organization of railway passenger transport.
Originality/value
The development of RMRPT would provide theoretical and technical support for the improvement of service quality as well as railway benefits and efficiency.
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Binh Tran-Nam, Cuong Le-Van, Van Pham-Hoang and Thai-Ha Le
The purpose of this paper is to develop an original model and a solution procedure for solving jointly three main strategic fleet management problems (fleet composition…
Abstract
Purpose
The purpose of this paper is to develop an original model and a solution procedure for solving jointly three main strategic fleet management problems (fleet composition, replacement and make-or-buy), taking into account interdependencies between them.
Design/methodology/approach
The three main strategic fleet management problems were analyzed in detail to identify interdependencies between them, mathematically modeled in terms of integer nonlinear programing (INLP) and solved using evolutionary based method of a solver compatible with a spreadsheet.
Findings
There are no optimization methods combining the analyzed problems, but it is possible to mathematically model them jointly and solve together using a solver compatible with a spreadsheet obtaining a solution/fleet management strategy answering the questions: Keep currently exploited vehicles in a fleet or remove them? If keep, how often to replace them? If remove then when? How many perspective/new vehicles, of what types, brand new or used ones and when should be put into a fleet? The relatively large scale instance of problem (50 vehicles) was solved based on a real-life data. The obtained results occurred to be better/cheaper by 10% than the two reference solutions – random and do-nothing ones.
Originality/value
The methodology of developing optimal fleet management strategy by solving jointly three main strategic fleet management problems is proposed allowing for the reduction of the fleet exploitation costs by adjusting fleet size, types of exploited vehicles and their exploitation periods.
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Rongsheng Wang, Tao Zhang, Zhiming Yuan, Shuxin Ding and Qi Zhang
This paper aims to propose a train timetable rescheduling (TTR) approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information…
Abstract
Purpose
This paper aims to propose a train timetable rescheduling (TTR) approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.
Design/methodology/approach
Firstly, a single-train trajectory optimization (STTO) model is constructed based on train dynamics and operating conditions. The train kinematics parameters, including acceleration, speed and time at each position, are calculated to predict the arrival times in the train timetable. A STTO algorithm is developed to optimize a single-train time-efficient driving strategy. Then, a TTR approach based on multi-train tracking optimization (TTR-MTTO) is proposed with mutual information. The constraints of temporary speed restriction (TSR) and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train. The multi-train trajectories at each position are optimized to generate a time-efficient train timetable.
Findings
The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF. The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay (TTD). As for the TSR scenario, the proposed TTR-MTTO can reduce TTD by 60.60% compared with the traditional TTR approach with dispatchers’ experience. Moreover, TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.
Originality/value
With the cooperative relationship and mutual information between train rescheduling and control, the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.
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It is crucial to find a better portfolio optimization strategy, considering the cryptocurrencies' asymmetric volatilities. Hence, this research aimed to present dynamic…
Abstract
Purpose
It is crucial to find a better portfolio optimization strategy, considering the cryptocurrencies' asymmetric volatilities. Hence, this research aimed to present dynamic optimization on minimum variance (MVP), equal risk contribution (ERC) and most diversified portfolio (MDP).
Design/methodology/approach
This study applied dynamic covariances from multivariate GARCH(1,1) with Student’s-t-distribution. This research also constructed static optimization from the conventional MVP, ERC and MDP as comparison. Moreover, the optimization involved transaction cost and out-of-sample analysis from the rolling windows method. The sample consisted of ten significant cryptocurrencies.
Findings
Dynamic optimization enhanced risk-adjusted return. Moreover, dynamic MDP and ERC could win the naïve strategy (1/N) under various estimation windows, and forecast lengths when the transaction cost ranging from 10 bps to 50 bps. The researcher also used another researcher's sample as a robustness test. Findings showed that dynamic optimization (MDP and ERC) outperformed the benchmark.
Practical implications
Sophisticated investors may use the dynamic ERC and MDP to optimize cryptocurrencies portfolio.
Originality/value
To the best of the author’s knowledge, this is the first paper that studies the dynamic optimization on MVP, ERC and MDP using DCC and ADCC-GARCH with multivariate-t-distribution and rolling windows method.
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Kailun Feng, Shiwei Chen, Weizhuo Lu, Shuo Wang, Bin Yang, Chengshuang Sun and Yaowu Wang
Simulation-based optimisation (SO) is a popular optimisation approach for building and civil engineering construction planning. However, in the framework of SO, the simulation is…
Abstract
Purpose
Simulation-based optimisation (SO) is a popular optimisation approach for building and civil engineering construction planning. However, in the framework of SO, the simulation is continuously invoked during the optimisation trajectory, which increases the computational loads to levels unrealistic for timely construction decisions. Modification on the optimisation settings such as reducing searching ability is a popular method to address this challenge, but the quality measurement of the obtained optimal decisions, also termed as optimisation quality, is also reduced by this setting. Therefore, this study aims to develop an optimisation approach for construction planning that reduces the high computational loads of SO and provides reliable optimisation quality simultaneously.
Design/methodology/approach
This study proposes the optimisation approach by modifying the SO framework through establishing an embedded connection between simulation and optimisation technologies. This approach reduces the computational loads and ensures the optimisation quality associated with the conventional SO approach by accurately learning the knowledge from construction simulations using embedded ensemble learning algorithms, which automatically provides efficient and reliable fitness evaluations for optimisation iterations.
Findings
A large-scale project application shows that the proposed approach was able to reduce computational loads of SO by approximately 90%. Meanwhile, the proposed approach outperformed SO in terms of optimisation quality when the optimisation has limited searching ability.
Originality/value
The core contribution of this research is to provide an innovative method that improves efficiency and ensures effectiveness, simultaneously, of the well-known SO approach in construction applications. The proposed method is an alternative approach to SO that can run on standard computing platforms and support nearly real-time construction on-site decision-making.
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Mergen Kor, Ibrahim Yitmen and Sepehr Alizadehsalehi
The purpose of this paper is to investigate the potential integration of deep learning (DL) and digital twins (DT), referred to as (DDT), to facilitate Construction 4.0 through an…
Abstract
Purpose
The purpose of this paper is to investigate the potential integration of deep learning (DL) and digital twins (DT), referred to as (DDT), to facilitate Construction 4.0 through an exploratory analysis.
Design/methodology/approach
A mixed approach involving qualitative and quantitative analysis was applied to collect data from global industry experts via interviews, focus groups and a questionnaire survey, with an emphasis on the practicality and interoperability of DDT with decision-support capabilities for process optimization.
Findings
Based on the analysis of results, a conceptual model of the framework has been developed. The research findings validate that DL integrated DT model facilitating Construction 4.0 will incorporate cognitive abilities to detect complex and unpredictable actions and reasoning about dynamic process optimization strategies to support decision-making.
Practical implications
The DL integrated DT model will establish an interoperable functionality and develop typologies of models described for autonomous real-time interpretation and decision-making support of complex building systems development based on cognitive capabilities of DT.
Originality/value
The research explores how the technologies work collaboratively to integrate data from different environments in real-time through the interplay of the optimization and simulation during planning and construction. The framework model is a step for the next level of DT involving process automation and control towards Construction 4.0 to be implemented for different phases of the project lifecycle (design–planning–construction).
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Mehmet Kursat Oksuz and Sule Itir Satoglu
Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response…
Abstract
Purpose
Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.
Design/methodology/approach
This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.
Findings
Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.
Originality/value
This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.
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