Wei Zhang, Beibing Dai, Zhen Liu and Cuiying Zhou
The cracking of a reinforced concrete lining has a significant influence on the safety and leakage of pressure tunnels. This study aims to develop, validate and apply a numerical…
Abstract
Purpose
The cracking of a reinforced concrete lining has a significant influence on the safety and leakage of pressure tunnels. This study aims to develop, validate and apply a numerical algorithm to simulate the lining cracking process during the water-filling period of pressure tunnels.
Design/methodology/approach
Cracks are preset in all lining elements, and the Mohr−Coulomb criterion with a tension cutoff is used in determining whether a preset crack becomes a real crack. The effects of several important factors such as the water pressure on crack surfaces (WPCS) and the heterogeneity of the lining tensile strength are also considered simultaneously.
Findings
The crack number and width increase gradually with the increase in internal water pressure. However, when the pressure reaches a threshold value, the increase in crack width becomes ambiguous. After the lining cracks, the lining displacement distribution is discontinuous and steel bar stress is not uniform. The measured stress of the steel bar is greatly determined by the position of the stress gauge. The WPCS has a significant influence on the lining cracking mechanism and should not be neglected.
Originality/value
A reliable algorithm for simulating the lining cracking process is presented by which the crack number and width can be determined directly. The numerical results provide an insight into the development law of lining cracks and show that the WPCS significantly affects the cracking mechanism.
Details
Keywords
Fang Yan, Yanfang Ma and Cuiying Feng
The purpose of this paper is to study a transportation service procurement bid construction problem from a less than a full truckload perspective. It seeks to establish stochastic…
Abstract
Purpose
The purpose of this paper is to study a transportation service procurement bid construction problem from a less than a full truckload perspective. It seeks to establish stochastic mixed integer programming to allow for the proper bundle of loads to be chosen based on price, which could improve the likelihood that carrier can earn its maximum utility.
Design/methodology/approach
The authors proposes a bi-level programming that integrates the bid selection and winner determination and a discrete particle swarm optimization (PSO) solution algorithm is then developed, and a numerical simulation is used to make model and algorithm analysis.
Findings
The algorithm comparison shows that although GA could find a little more Pareto solutions than PSO, it takes a longer time and the quality of these solutions is not dominant. The model analysis shows that compared with traditional approach, our model could promote the likelihood of winning bids and the decision effectiveness of the whole system because it considers the reaction of the shipper.
Originality/value
The highlights of this paper are considering the likelihood of winning the business and describing the conflicting and cooperative relationship between the carrier and the shipper by using a stochastic mixed integer programming, which has been rarely examined in previous research.
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Miao Tian, Ying Cui, Haixia Long and Junxia Li
In novelty detection, the autoencoder based image reconstruction strategy is one of the mainstream solutions. The basic idea is that once the autoencoder is trained on normal…
Abstract
Purpose
In novelty detection, the autoencoder based image reconstruction strategy is one of the mainstream solutions. The basic idea is that once the autoencoder is trained on normal data, it has a low reconstruction error on normal data. However, when faced with complex natural images, the conventional pixel-level reconstruction becomes poor and does not show the promising results. This paper aims to provide a new method for improving the performance of novelty detection based autoencoder.
Design/methodology/approach
To solve the problem that conventional pixel-level reconstruction cannot effectively extract the global semantic information of the image, a novel model with the combination of attention mechanism and self-supervised learning method is proposed. First, an auxiliary task, reconstruct rotated image, is set to enable the network to learn global semantic feature information. Then, the channel attention mechanism is introduced to perform adaptive feature refinement on the intermediate feature map to optimize the correspondingly passed feature map.
Findings
Experimental results on three public data sets show that the proposed method has potential performance for novelty detection.
Originality/value
This study explores the ability of self-supervised learning methods and attention mechanism to extract features on a single class of images. In this way, the performance of novelty detection can be improved.
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Keywords
The aggregate index and per capita index have different meanings for some countries or regions. CO2 emissions per capita matters for China because of its huge population…
Abstract
Purpose
The aggregate index and per capita index have different meanings for some countries or regions. CO2 emissions per capita matters for China because of its huge population. Therefore, this study aims to deepen the understanding of Kuznets curve from the perspective of CO2 emissions per capita. In this study, mathematical formulas will be derived and verified.
Design/methodology/approach
First, this study verified the existing problems with the environmental Kuznets curve (EKC) through multiple regression. Second, this study developed a theoretical derivation with the Solow model and balanced growth and explained the underlying principles of the EKC’s shape. Finally, this study quantitatively analyzed the influencing factors.
Findings
The CO2 emission per capita is related to the per capita GDP, nonfossil energy and total factor productivity (TFP). Empirical results support the EKC hypothesis. When the proportion of nonfossil and TFP increase by 1%, the per capita CO2 decrease by 0.041 t and 1.79 t, respectively. The growth rate of CO2 emissions per capita is determined by the difference between the growth rate of output per capita and the sum of efficiency and structural growth rates. To achieve the CO2 emission intensity target and economic growth target, the growth rate of per capita CO2 emissions must fall within the range of [−0.92%, 6.1%].
Originality/value
Inspired by the EKC and balanced growth, this study investigated the relationships between China’s environmental variables (empirical analysis) and developed a theoretical background (macro-theoretical derivation) through formula-based derivation, the results of which are universally valuable and provide policymakers with a newly integrated view of emission reduction and balanced development to address the challenges associated with climate change caused by energy.