Zhangtao Peng, Qian Fang, Qing Ai, Xiaomo Jiang, Hui Wang, Xingchun Huang and Yong Yuan
A risk-based method is proposed to identify the dominant influencing factors of secondary lining cracking in an operating mountain tunnel with weak surrounding rock.
Abstract
Purpose
A risk-based method is proposed to identify the dominant influencing factors of secondary lining cracking in an operating mountain tunnel with weak surrounding rock.
Design/methodology/approach
Based on the inspection data from a mountain tunnel in Southwest China, a lognormal proportional hazard model is established to describe the statistical distribution of secondary lining cracks. Then, the model parameters are obtained by using the Bayesian regression method, and the importance of influencing factors can be sorted based on the absolute values of the parameters.
Findings
The results show that the order of importance of the influencing factors of secondary lining cracks is as follows: location of the crack on the tunnel profile, rock mass grade of the surrounding rock, time to completion of the secondary lining, and void behind the secondary lining. Accordingly, the location of the crack on the tunnel profile and rock mass grade of the surrounding rock are the two most important influencing factors of secondary lining cracks in the investigated mountain tunnel, and appropriate maintenance measures should be focused on these two aspects.
Originality/value
This study provides a general and effective reference for identifying the dominant influencing factors of secondary lining cracks to guide the targeted maintenance in mountain tunnels.
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Da Teng, Yun-Wen Feng, Jun-Yu Chen and Cheng Lu
The purpose of this paper is to briefly summarize and review the theories and methods of complex structures’ dynamic reliability. Complex structures are usually assembled from…
Abstract
Purpose
The purpose of this paper is to briefly summarize and review the theories and methods of complex structures’ dynamic reliability. Complex structures are usually assembled from multiple components and subjected to time-varying loads of aerodynamic, structural, thermal and other physical fields; its reliability analysis is of great significance to ensure the safe operation of large-scale equipment such as aviation and machinery.
Design/methodology/approach
In this paper for the single-objective dynamic reliability analysis of complex structures, the calculation can be categorized into Monte Carlo (MC), outcrossing rate, envelope functions and extreme value methods. The series-parallel and expansion methods, multi-extremum surrogate models and decomposed-coordinated surrogate models are summarized for the multiobjective dynamic reliability analysis of complex structures.
Findings
The numerical complex compound function and turbine blisk are used as examples to illustrate the performance of single-objective and multiobjective dynamic reliability analysis methods. Then the future development direction of dynamic reliability analysis of complex structures is prospected.
Originality/value
The paper provides a useful reference for further theoretical research and engineering application.
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Leshi Shu, Ping Jiang, Li Wan, Qi Zhou, Xinyu Shao and Yahui Zhang
Metamodels are widely used to replace simulation models in engineering design optimization to reduce the computational cost. The purpose of this paper is to develop a novel…
Abstract
Purpose
Metamodels are widely used to replace simulation models in engineering design optimization to reduce the computational cost. The purpose of this paper is to develop a novel sequential sampling strategy (weighted accumulative error sampling, WAES) to obtain accurate metamodels and apply it to improve the quality of global optimization.
Design/methodology/approach
A sequential single objective formulation is constructed to adaptively select new sample points. In this formulation, the optimization objective is to select a sample point with the maximum weighted accumulative predicted error obtained by analyzing data from previous iterations, and a space-filling criterion is introduced and treated as a constraint to avoid generating clustered sample points. Based on the proposed sequential sampling strategy, a two-step global optimization approach is developed.
Findings
The proposed WAES approach and the global optimization approach are tested in several cases. A comparison has been made between the proposed approach and other existing approaches. Results illustrate that WAES approach performs the best in improving metamodel accuracy and the two-step global optimization approach has a great ability to avoid local optimum.
Originality/value
The proposed WAES approach overcomes the shortcomings of some existing approaches. Besides, the two-step global optimization approach can be used for improving the optimization results.
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Qi Zhou, Xinyu Shao, Ping Jiang, Tingli Xie, Jiexiang Hu, Leshi Shu, Longchao Cao and Zhongmei Gao
Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might significantly…
Abstract
Purpose
Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might significantly degrade the overall performance of engineering systems and change the feasibility of the obtained solutions. This paper aims to propose a multi-objective robust optimization approach based on Kriging metamodel (K-MORO) to obtain the robust Pareto set under the interval uncertainty.
Design/methodology/approach
In K-MORO, the nested optimization structure is reduced into a single loop optimization structure to ease the computational burden. Considering the interpolation uncertainty from the Kriging metamodel may affect the robustness of the Pareto optima, an objective switching and sequential updating strategy is introduced in K-MORO to determine (1) whether the robust analysis or the Kriging metamodel should be used to evaluate the robustness of design alternatives, and (2) which design alternatives are selected to improve the prediction accuracy of the Kriging metamodel during the robust optimization process.
Findings
Five numerical and engineering cases are used to demonstrate the applicability of the proposed approach. The results illustrate that K-MORO is able to obtain robust Pareto frontier, while significantly reducing computational cost.
Practical implications
The proposed approach exhibits great capability for practical engineering design optimization problems that are multi-objective and constrained and have uncertainties.
Originality/value
A K-MORO approach is proposed, which can obtain the robust Pareto set under the interval uncertainty and ease the computational burden of the robust optimization process.
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Diego Quer-Ramón, Enrique Claver-Cortés and Laura Rienda-García
Since the beginning of the 21st century, China’s outward foreign direct investment (OFDI) is growing steadily and Chinese multinationals (MNCs) are playing an increasingly…
Abstract
Purpose
Since the beginning of the 21st century, China’s outward foreign direct investment (OFDI) is growing steadily and Chinese multinationals (MNCs) are playing an increasingly important role in the global economy. Thus, the number of papers focusing on China’s OFDI and Chinese MNCs has been increasing during the last years. The aim of this chapter is to carry out a review of the empirical papers dealing with Chinese MNCs published between 2002 and 2012 in high-impact international business and management journals.
Design/methodology/approach
This chapter reviews 43 empirical papers focusing on Chinese MNCs that were published in nine major scholarly journals between 2002 and 2012.
Findings
We report individual and institutional contributions, the theories and methods used, the research topics, and the main findings. We also discuss implications for future research.
Originality/value
Some previous literature reviews have dealt with research on China’s OFDI and Chinese MNCs. Nevertheless, none of the earlier reviews dealt specifically with empirical papers; neither did they provide an analysis of both individual and institutional contributions.
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Ji Cheng, Ping Jiang, Qi Zhou, Jiexiang Hu, Tao Yu, Leshi Shu and Xinyu Shao
Engineering design optimization involving computational simulations is usually a time-consuming, even computationally prohibitive process. To relieve the computational burden, the…
Abstract
Purpose
Engineering design optimization involving computational simulations is usually a time-consuming, even computationally prohibitive process. To relieve the computational burden, the adaptive metamodel-based design optimization (AMBDO) approaches have been widely used. This paper aims to develop an AMBDO approach, a lower confidence bounding approach based on the coefficient of variation (CV-LCB) approach, to balance the exploration and exploitation objectively for obtaining a global optimum under limited computational budget.
Design/methodology/approach
In the proposed CV-LCB approach, the coefficient of variation (CV) of predicted values is introduced to indicate the degree of dispersion of objective function values, while the CV of predicting errors is introduced to represent the accuracy of the established metamodel. Then, a weighted formula, which takes the degree of dispersion and the prediction accuracy into consideration, is defined based on the already-acquired CV information to adaptively update the metamodel during the optimization process.
Findings
Ten numerical examples with different degrees of complexity and an AIAA aerodynamic design optimization problem are used to demonstrate the effectiveness of the proposed CV-LCB approach. The comparisons between the proposed approach and four existing approaches regarding the computational efficiency and robustness are made. Results illustrate the merits of the proposed CV-LCB approach in computational efficiency and robustness.
Practical implications
The proposed approach exhibits high efficiency and robustness in engineering design optimization involving computational simulations.
Originality/value
CV-LCB approach can balance the exploration and exploitation objectively.
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Wenyi Xia, Kun Wang and Anming Zhang
This chapter reviews three main issues in the interactions between air transport and high-speed rail (HSR) in China, namely the interaction between low-cost carriers (LCCs) and…
Abstract
This chapter reviews three main issues in the interactions between air transport and high-speed rail (HSR) in China, namely the interaction between low-cost carriers (LCCs) and HSR, HSR speed effect on airlines, and airline–HSR integration. Studies on these three aspects of airline–HSR interactions have yet been well reviewed, and our chapter aims to fill in this gap. In this chapter, we comprehensively survey literature on the topics, especially studies on Chinese markets that have recently witnessed major HSR developments (and have planned further large-scale HSR expansion in the coming years). Our review shows that, first, compared to full-service carriers, LCCs face fiercer competition from HSR. However, the expansion of HSR network in China can be better coordinated with LCC development. Second, HSR speed exerts two countervailing effects on airline demand and price (the “travel-time” effect and “safety” effect, respectively). Specifically, an HSR speed reduction can have a positive effect on airlines due to longer HSR travel time, but a negative effect on airlines due to improved perception on HSR safety. Third, airline–HSR integration can be implemented through cooperation between airlines and HSR operators and through co-location of airports and HSR stations and can have important implications for intermodal transport and social welfare.
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Qimin Xu and Rong Jiang
This paper aims to propose a 3D-map aided tightly coupled positioning solution for land vehicles to reduce the errors caused by non-line-of-sight (NLOS) and multipath interference…
Abstract
Purpose
This paper aims to propose a 3D-map aided tightly coupled positioning solution for land vehicles to reduce the errors caused by non-line-of-sight (NLOS) and multipath interference in urban canyons.
Design/methodology/approach
First, a simple but efficient 3D-map is created by adding the building height information to the existing 2D-map. Then, through a designed effective satellite selection method, the distinct NLOS pseudo-range measurements can be excluded. Further, an enhanced extended Kalman particle filter algorithm is proposed to fuse the information from dual-constellation Global Navigation Satellite Systems and reduced inertial sensor system. The dependable degree of each selected satellite is adjusted through fuzzy logic to further mitigate the effect of misjudged LOS and multipath.
Findings
The proposed solution can improve positioning accuracy in urban canyons. The experimental results evaluate the effectiveness of the proposed solution and indicate that the proposed solution outperforms all the compared counterparts.
Originality/value
The effect of NLOS and multipath is addressed from both the observation level and fusion level. To the authors’ knowledge, mitigating the effect of misjudged LOS and multipath in the fusion algorithm of tightly coupled integration is seldom considered in existing literature.
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Yalin Pan, Jun Huang, Feng Li and Chuxiong Yan
The purpose of this paper is to propose a robust optimization strategy to deal with the aerodynamic optimization issue, which does not need a large sum of information on the…
Abstract
Purpose
The purpose of this paper is to propose a robust optimization strategy to deal with the aerodynamic optimization issue, which does not need a large sum of information on the uncertainty of input parameters.
Design/methodology/approach
Interval numbers were adopted to describe the uncertain input, which only requires bounds and does not necessarily need probability distributions. Based on the method, model outputs were also regarded as intervals. To identify a better solution, an order relation was used to rank interval numbers.
Findings
Based on intervals analysis method, the uncertain optimization problem was transformed into nested optimization. The outer optimization was used to optimize the design vector, and inner optimization was used to compute the interval of model outputs. A flying wing aircraft was used as a basis for uncertainty optimization through the suggested optimization strategy, and optimization results demonstrated the validity of the method.
Originality/value
In aircraft conceptual design, the uncertain information of design parameters are often insufficient. Interval number programming method used for uncertainty analysis is effective for aerodynamic robust optimization for aircraft conceptual design.