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Article
Publication date: 23 May 2022

Yangsheng Ye, Degou Cai, Lin Geng, Hongye Yan, Junkai Yao and Feng Chen

This study aims to propose a semiempirical and semitheoretical cyclic compaction constitutive model of coarse-grained soil filler for the high-speed railway (HSR) subgrade under…

1012

Abstract

Purpose

This study aims to propose a semiempirical and semitheoretical cyclic compaction constitutive model of coarse-grained soil filler for the high-speed railway (HSR) subgrade under cyclic load.

Design/methodology/approach

According to the basic framework of critical state soil mechanics and in view of the characteristics of the coarse-grained soil filler for the HSR subgrade to bear the train vibration load repeatedly for a long time, the hyperbolic empirical relationship between particle breakage and plastic work was derived. Considering the influence of cyclic vibration time and stress ratio, the particle breakage correction function of coarse-grained soil filler for the HSR subgrade under cyclic load was proposed. According to the classical theory of plastic mechanics, the shearing dilatation equation of the coarse-grained soil filler for the HSR subgrade considering particle breakage was modified and obtained. A semiempirical and semitheoretical cyclic compaction constitutive model of coarse-grained soil filler for the HSR subgrade under cyclic load was further established. The backward Euler method was used to discretize the constitutive equation, build a numerical algorithm of “elastic prediction and plastic modification” and make a secondary development of the program to solve the cyclic compaction model.

Findings

Through the comparison with the result of laboratory triaxial test under the cyclic loading of coarse-grained soil filler for the HSR subgrade, the accuracy and applicability of the cyclic compaction model were verified. Results show that the model can accurately predict the cumulative deformation characteristics of coarse-grained soil filler for the HSR subgrade under the train vibration loading repeatedly for a long time. It considers the effects of particle breakage and stress ratio, which can be used to calculate and analyze the stress and deformation evolution law of the subgrade structure for HSR.

Originality/value

The research can provide a simple and practical method for calculating deformation of railway under cyclic loading.

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Article
Publication date: 14 April 2020

Yu Yan, Wei Jiang, Dehua Zou, Wusheng Quan, Hong Jun Li, YunFei Lei and Zhan fan Zhou

In the long-term network operation, the power distribution network will be subjected to the effects of ultra-high voltage, strong electromagnetic interference and harsh natural…

313

Abstract

Purpose

In the long-term network operation, the power distribution network will be subjected to the effects of ultra-high voltage, strong electromagnetic interference and harsh natural environment on the power system, which will lead to the occurrence of different faults in the distribution network and directly affect the normal operation of the power grid.

Design/methodology/approach

The purpose of this study is to solve the problems of labor intensity, high risk and low efficiency of distribution network manual maintenance operation, this paper proposed a new configuration of the live working robot for distribution network maintenance, the robot is equipped with dual working arms through the mobile platform, which can realize the coordination movement, the autonomous reorganization and replacement of the end tools, respectively, so as the robot power distribution maintenance function such as stripping, trimming, wiring and the operation control problem of the distribution network-robot with small arms and in small operation space can be realized.

Findings

To effective elimination or reduce the adverse effects of the internal forces in the closed chain between the working object and manipulator under the typical task of the 10 kV distribution network, this paper has established the robot coordinated control dynamics model in the closed-chain between the dual-working object and proposed the dynamic distribution method of closed-chain internal force and the effectiveness has been proved by simulation experiments and 10 kV field operation.

Originality/value

The force-position hybrid control can realize the mutual compensation of force and position so as to effectively reduce the internal force in the closed chain. Finally, the engineering practicality of the method is verified by field operation experiment, the effective implementation of this control method greatly improves the robot working efficiency and the operation reliability, the promotion and application of the control method have great theoretical and practical value and maintenance management system, so as to achieve automation of electric.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

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Book part
Publication date: 22 November 2024

Ayat-Allah Bouramdane

In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving…

Abstract

In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving energy landscape requires understanding regional intricacies and identifying areas for improvement. This chapter examines hydrogen transport from production to utilization, evaluating technologies’ pros, cons, and process equations and using Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) tool to assess these technologies based on multiple criteria. It also explores barriers and opportunities in hydrogen transport within the 21st-century energy transition, providing insights for overcoming challenges. Evaluation criteria for hydrogen transport technologies were ranked by relative importance, with energy efficiency topping the list, followed by energy density, infrastructure requirements, cost, range, and flexibility. Safety, technological maturity, scalability, and compatibility with existing infrastructure received lower weights. Hydrogen transport technologies were categorized into three performance levels: low, medium, and high. Hydrogen tube trailers ranked lowest, while chemical hydrides, hydrail, liquid organic hydrogen carriers, hydrogen pipelines, and hydrogen blending exhibited moderate performance. Compressed hydrogen gas, liquid hydrogen, ammonia carriers, and hydrogen fueling stations demonstrated the highest performance. The proposed framework is crucial for next-gen smart cities, cutting emissions, boosting growth, and speeding up development with a strong hydrogen infrastructure. This makes the region a sustainable tech leader, improving air quality and well-being. Aligned with Gulf Region goals, it is key for smart cities. Policymakers, industries, and researchers can use these insights to overcome barriers and seize hydrogen transport tech opportunities.

Details

The Emerald Handbook of Smart Cities in the Gulf Region: Innovation, Development, Transformation, and Prosperity for Vision 2040
Type: Book
ISBN: 978-1-83608-292-7

Keywords

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Book part
Publication date: 29 December 2016

Mariya Gubareva and Maria Rosa Borges

This chapter reassesses the economics of interest rate risk management in light of the global financial crisis by developing a derivative-based integrated treatment of interest…

Abstract

This chapter reassesses the economics of interest rate risk management in light of the global financial crisis by developing a derivative-based integrated treatment of interest rate and credit risk interrelation. The decade-long historical data on credit default swap spreads and interest rate swap rates are used as proxy measures for credit risk and interest rate risk, respectively. An elasticity of interest rate risk and credit risk, considered a function of the business cycle phases, maturity of instruments, economic sector, creditworthiness, and other macroeconomic parameters, is investigated for optimizing economic capital. This chapter sheds light on how financial institutions may address hedge strategies against downside risks implementing the proposed derivative-based integrated treatment of interest rate and credit risk assessment allowing for optimization of interest rate swap contracts. The developed framework of integrated interest rate and credit risk management is of special importance for emerging markets heavily dependent on foreign capital as it potentially allows emerging market banks to improve risk management practices in terms of capital adequacy and Basel III rules. Analyzing diversification versus compounding effects, it allows enhancing financial stability through jointly optimizing Pillar 1 and Pillar 2 economic capital.

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Article
Publication date: 24 July 2019

Fangyong Niu, Dongjiang Wu, Yunfei Huang, Shuai Yan, Guangyi Ma, Chaojiang Li and Jun Ding

Direct additive manufacturing of ceramics (DAMC) is a highly promising ceramics preparation technology because of its simple process and rapid response capability, but the…

493

Abstract

Purpose

Direct additive manufacturing of ceramics (DAMC) is a highly promising ceramics preparation technology because of its simple process and rapid response capability, but the cracking issue prevents its industrial application. The purpose of this paper is to propose aluminum titanate (Al2TiO5) with low coefficient of thermal expansion (CTE) to suppress cracks during the DAMC.

Design/methodology/approach

Al2O3/Al2TiO5 (A/AT) composite ceramic samples with different compositions were in-situ synthesized from Al2O3/TiO2 (A/T) powder in a directed laser deposition (DLD) process. The relationship between the content of TiO2 and cracking characteristics of fabricated sample was discussed. Phase composition, microstructure and properties of the fabricated samples were also investigated.

Findings

The results of this paper show that the doping of TiO2 can obtain Al2TiO5 synthesized in situ by reaction with Al2O3 and effectively suppress cracks during DAMC. When the content of TiO2 reaches 30 wt.per cent, cracks hardly occur even under conditions of slow deposition. Crack-free structures such as vane, cone and pyramid were successfully prepared, with a maximum cross-sectional dimension of 30 mm and maximum length of 150 mm. A continuous matrix phase formed of the low CTE of Al2TiO5 is the major cause of crack suppression. The dispersed distribution of a-Al2O3 columnar dendrites has the effect of increasing the strength of the matrix. Under current process conditions, the prepared sample with 10 wt.per cent TiO2 has micro-hardness of 21.05 GPa and flexural strength of 170 MPa.

Originality/value

This paper provides a new method and inspiration for direct additive manufacturing of large-sized crack-free ceramics, which has the potential to promote practical application of the technology.

Details

Rapid Prototyping Journal, vol. 25 no. 8
Type: Research Article
ISSN: 1355-2546

Keywords

Available. Open Access. Open Access
Article
Publication date: 30 June 2020

Sung-Woo Lee, Sung-Ho Shin and Hee-Sung Bae

This study aims to analyze information on vessel traffic between the two Koreas with a probability distribution for each route/vessel type. The study will then conduct an estimate…

486

Abstract

This study aims to analyze information on vessel traffic between the two Koreas with a probability distribution for each route/vessel type. The study will then conduct an estimate for maritime transport patterns of inter-Korean trade in the future. To analyze the flow of inter-Korean coastal shipping, this study conducted visualization analysis of shipping status between North and South Korea by year, ship type, and port using navigation data of three years from Port Logistics Information System (Port-MIS) sources during 2006 to 2008, which saw the most active exchanges between the two governments. Also, this study analyzes shipping status between the two governments as a probability distribution for each port and provides the prospects for future maritime transport for inter-Korean trade by means of Bayesian Networks and simulation. The results of the analysis are as follows: i) when North-South routes are reopened, the import volume for sand from North Korea will be increased; ii) investment in the modernization of ports in North Korea is required so that shipping companies can generate profit through economies of scale; iii) the number of the operating vessels including container ships between the two governments is expected to increase like when the tensions and conflict on the Korean Peninsula was release, especially between Busan port in South Korea and Nampo port in North Korea; and iv) among container ships, transshipment containers imported and exported through Busan Port will be shipped to North Korea by feeder transportation.

Details

Journal of International Logistics and Trade, vol. 18 no. 2
Type: Research Article
ISSN: 1738-2122

Keywords

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Article
Publication date: 2 July 2020

Laura Almeida, Vivian W.Y. Tam, Khoa N. Le and Yujuan She

Occupants are one of the most impacting factors in the overall energy performance of buildings, according to literature. Occupants’ behaviours and actions may impact the overall…

686

Abstract

Purpose

Occupants are one of the most impacting factors in the overall energy performance of buildings, according to literature. Occupants’ behaviours and actions may impact the overall use of energy in more than 50%. In order to quantify the impact that occupant behaviour has in the use of energy, this study simulated interactions between occupants and the systems present in two actual buildings. The main aim was to compare the deviations due to occupant behaviour with the actual conditions and energy use of the two buildings.

Design/methodology/approach

The buildings used as a case study in this research were green buildings, rated according to the Australian Green Star certification system as a 6-star and a non-rated building. The two buildings are university buildings with similar characteristics, from Western Sydney University, in Sydney, Australia. A comparison was performed by means of building simulations among the use of energy in both buildings, aiming to understand if the green rating had any impact on the energy related to occupant behaviour. Therefore, to represent the actual buildings' conditions, the actual data related with climate, geometry, systems, internal loads, etc. were used as input variables in the simulation models of the green and the non-rated buildings. Both models were calibrated and validated, having as target the actual monitored use of electricity.

Findings

Occupants were categorized according to their levels of energy use as follows: saving, real and intensive energy users. Building simulations were performed to each building, with varying parameters related with lighting, plug loads, windows/doors opening, shading and air conditioning set points. Results show that occupant behaviour may impact the buildings' energy performance in a range of 72% between the two extremes. There is no significant relationship between the green rating and the way occupants behave in terms of the energy use.

Originality/value

This study intends to show the impact of different categories of occupant behaviour in the overall energy performance of two university buildings, a non-rated and a green-rated building, having as reference an actual representation of the buildings. Additionally, the study aims to understand the main differences between a green-rated and a non-rated building when accounting with the previous categories.

Details

Engineering, Construction and Architectural Management, vol. 27 no. 8
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 31 May 2024

Fahad Khalid, Chih-Yi Su, Kong Weiwei, Cosmina L. Voinea and Mohit Srivastava

This study empirically evaluates the effect of China’s 2016 Green Financial System (GFS) framework on corporate green development, focusing on the role of green investment in…

191

Abstract

Purpose

This study empirically evaluates the effect of China’s 2016 Green Financial System (GFS) framework on corporate green development, focusing on the role of green investment in achieving sustainability.

Design/methodology/approach

This study uses a quasinatural experiment design to combine difference-in-difference and propensity score matching methods for analysis. It examines 799 polluting and 1,130 nonpolluting firms from 2013 to 2020, enabling a comprehensive assessment of the GFS framework’s influence.

Findings

This study affirms a statistically significant positive influence of the GFS framework on escalating green investment levels in polluting firms. Robust sensitivity analyses, encompassing parallel trend assessment, entropy balancing test, and alternative proxies, corroborate these findings. A mediation analysis identifies the implementation of an environmental management system as the potential underlying mechanism. A cross-sectional analysis identifies high financial slack, high profitability, mandatory CSR regulations, and marketization level as the influencing factors.

Research limitations/implications

The study’s findings have critical implications for policymakers, regulators, and companies. Demonstrating the effectiveness of the GFS framework in driving green investment underscores the importance of aligning financial systems with sustainability goals.

Originality/value

This study contributes novel empirical evidence on the positive effect of China’s GFS framework on corporate green development. The quasinatural experiment design, coupled with comprehensive sensitivity analyses, strengthens the robustness of the findings.

Details

China Finance Review International, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-1398

Keywords

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Article
Publication date: 23 September 2020

Z.F. Zhang, Wei Liu, Egon Ostrosi, Yongjie Tian and Jianping Yi

During the production process of steel strip, some defects may appear on the surface, that is, traditional manual inspection could not meet the requirements of low-cost and…

230

Abstract

Purpose

During the production process of steel strip, some defects may appear on the surface, that is, traditional manual inspection could not meet the requirements of low-cost and high-efficiency production. The purpose of this paper is to propose a method of feature selection based on filter methods combined with hidden Bayesian classifier for improving the efficiency of defect recognition and reduce the complexity of calculation. The method can select the optimal hybrid model for realizing the accurate classification of steel strip surface defects.

Design/methodology/approach

A large image feature set was initially obtained based on the discrete wavelet transform feature extraction method. Three feature selection methods (including correlation-based feature selection, consistency subset evaluator [CSE] and information gain) were then used to optimize the feature space. Parameters for the feature selection methods were based on the classification accuracy results of hidden Naive Bayes (HNB) algorithm. The selected feature subset was then applied to the traditional NB classifier and leading extended NB classifiers.

Findings

The experimental results demonstrated that the HNB model combined with feature selection approaches has better classification performance than other models of defect recognition. Among the results of this study, the proposed hybrid model of CSE + HNB is the most robust and effective and of highest classification accuracy in identifying the optimal subset of the surface defect database.

Originality/value

The main contribution of this paper is the development of a hybrid model combining feature selection and multi-class classification algorithms for steel strip surface inspection. The proposed hybrid model is primarily robust and effective for steel strip surface inspection.

Details

Engineering Computations, vol. 38 no. 4
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 10 August 2021

Elham Amirizadeh and Reza Boostani

The aim of this study is to propose a deep neural network (DNN) method that uses side information to improve clustering results for big datasets; also, the authors show that…

124

Abstract

Purpose

The aim of this study is to propose a deep neural network (DNN) method that uses side information to improve clustering results for big datasets; also, the authors show that applying this information improves the performance of clustering and also increase the speed of the network training convergence.

Design/methodology/approach

In data mining, semisupervised learning is an interesting approach because good performance can be achieved with a small subset of labeled data; one reason is that the data labeling is expensive, and semisupervised learning does not need all labels. One type of semisupervised learning is constrained clustering; this type of learning does not use class labels for clustering. Instead, it uses information of some pairs of instances (side information), and these instances maybe are in the same cluster (must-link [ML]) or in different clusters (cannot-link [CL]). Constrained clustering was studied extensively; however, little works have focused on constrained clustering for big datasets. In this paper, the authors have presented a constrained clustering for big datasets, and the method uses a DNN. The authors inject the constraints (ML and CL) to this DNN to promote the clustering performance and call it constrained deep embedded clustering (CDEC). In this manner, an autoencoder was implemented to elicit informative low dimensional features in the latent space and then retrain the encoder network using a proposed Kullback–Leibler divergence objective function, which captures the constraints in order to cluster the projected samples. The proposed CDEC has been compared with the adversarial autoencoder, constrained 1-spectral clustering and autoencoder + k-means was applied to the known MNIST, Reuters-10k and USPS datasets, and their performance were assessed in terms of clustering accuracy. Empirical results confirmed the statistical superiority of CDEC in terms of clustering accuracy to the counterparts.

Findings

First of all, this is the first DNN-constrained clustering that uses side information to improve the performance of clustering without using labels in big datasets with high dimension. Second, the author defined a formula to inject side information to the DNN. Third, the proposed method improves clustering performance and network convergence speed.

Originality/value

Little works have focused on constrained clustering for big datasets; also, the studies in DNNs for clustering, with specific loss function that simultaneously extract features and clustering the data, are rare. The method improves the performance of big data clustering without using labels, and it is important because the data labeling is expensive and time-consuming, especially for big datasets.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 14 no. 4
Type: Research Article
ISSN: 1756-378X

Keywords

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