Vitus Mwinteribo Tabie, Chong Li, Wang Saifu, Jianwei Li and Xiaojing Xu
This paper aims to present a broad review of near-a titanium alloys for high-temperature applications.
Abstract
Purpose
This paper aims to present a broad review of near-a titanium alloys for high-temperature applications.
Design/methodology/approach
Following a brief introduction of titanium (Ti) alloys, this paper considers the near-α group of Ti alloys, which are the most popular high-temperature Ti alloys developed for a high-temperature application, particularly in compressor disc and blades in aero-engines. The paper is relied on literature within the past decade to discuss phase stability and microstructural effect of alloying elements, plastic deformation and reinforcements used in the development of these alloys.
Findings
The near-a Ti alloys show high potential for high-temperature applications, and many researchers have explored the incorporation of TiC, TiB SiC, Y2O3, La2O3 and Al2O3 reinforcements for improved mechanical properties. Rolling, extrusion, forging and some severe plastic deformation (SPD) techniques, as well as heat treatment methods, have also been explored extensively. There is, however, a paucity of information on SiC, Y2O3 and carbon nanotube reinforcements and their combinations for improved mechanical properties. Information on some SPD techniques such as cyclic extrusion compression, multiaxial compression/forging and repeated corrugation and straightening for this class of alloys is also limited.
Originality/value
This paper provides a topical, technical insight into developments in near-a Ti alloys using literature from within the past decade. It also outlines the future developments of this class of Ti alloys.
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Chensen Ding, Xiangyang Cui, Chong Li, Guangyao Li and Guoping Wang
Traditional adaptive analysis based on a coarse mesh, using finite element method (FEM) analysis, produces the original solution. Then post-processing the result and figuring out…
Abstract
Purpose
Traditional adaptive analysis based on a coarse mesh, using finite element method (FEM) analysis, produces the original solution. Then post-processing the result and figuring out the regions should be refined and these regions refined once. Finally, this new mesh is used to get the solution of first refinement. After several iterations of above procedures, we can achieve the last result that is closer to the true solution, which takes time, making adaptive scheme inpractical to engineering application. The paper aims to discuss these issues.
Design/methodology/approach
This paper based on FEM proposes a multi-level refinement strategy with a refinement strategy and an indicator. The proposed indicator uses value of the maximum difference of strain energy density among the elements that associated with one node, and divides all nodes into several categories based on the value. A multi-level refinement strategy is proposed according to which category the node belongs to refine different elements to different times rather than whether refine or not.
Findings
Multi-level refinement strategy takes full use of the numerical calculation, resulting in the whole adaptive analysis that only need to iterate twice while other schemes must iterate more times. Using much less times of numerical calculation and approaches, more accurate solution, making adaptive analysis more practical to engineering.
Originality/value
Multi-level refinement strategy takes full use of the numerical calculation, resulting in the whole adaptive analysis only need iterate twice while other schemes must iterate more times. using much less times of numerical calculation and approaches more accurate solution, making adaptive analysis more practical to engineering.
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Liqin Zhou, Changbin Wang, Lin Li, Chengxi Zhang, Dalei Song and Chong Li
A novel fault-tolerant control (FTC) method is proposed to assure the stability of the remote-operated vehicle (ROV) by considering the thruster failure-induced model…
Abstract
Purpose
A novel fault-tolerant control (FTC) method is proposed to assure the stability of the remote-operated vehicle (ROV) by considering the thruster failure-induced model perturbations. The stability of the ROV with failures is guaranteed and optimized with the determined model perturbation set. The effectiveness of the double-boundary interval fault-tolerant control (DBIFTC) is verified through the experiments and proves that the stability is well maintained, which demonstrates a decent performance.
Design/methodology/approach
This paper studies a control problem for a multi-vector propulsion ROV by using the DBIFTC method in the presence of thruster failure and external disturbances. The ROV kinematics and dynamical models with multi-vector-arranged thruster failure are investigated and formulated for control system design.
Findings
In this paper, the authors address the FTC problem of ROV with multi-vector thrusters and propose a DBIFTC scheme. The advantage is that as the kinematic system model of ROV is preanalyzed and identified, the DBIFTC becomes more effective. The mathematical stability of the system under the proposed control scheme can be guaranteed.
Research limitations/implications
The ROV model used in this paper is based on the system identification of experimental data. Although this model has real experimental value and physical significance, the accuracy can be further improved.
Practical implications
Cable-controlled underwater ROVs are widely used in military missions and scientific research because of their flexibility, sufficient load capacity and real-time information transmission characteristics. The DBIFTC method proposed in this paper can effectively reduce the problem of underwater vehicle under propeller failure or external disturbance and save unnecessary cost.
Social implications
The DBIFTC method proposed in this paper can ensure the attitude stability of ROV or other underwater equipment operating in the event of propeller failure or external disturbance. In this way, the robot can better perform undersea work and tasks.
Originality/value
The kinematics and failure mechanisms of the ROV with multi-vector propulsion system are investigated and established. An optimized DBIFTC scheme is investigated to stabilize ROV yaw attitude under the thruster failure condition. The feasibility and effectiveness of the DBIFTC is experimentally validated.
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Chong Li, Yuling Qu and Xinping Zhu
A novel asynchronous network-based model is proposed in this paper for the sentiment analysis of online public opinions. This new model provides a new approach to analyze the…
Abstract
Purpose
A novel asynchronous network-based model is proposed in this paper for the sentiment analysis of online public opinions. This new model provides a new approach to analyze the evolution characteristics of online public opinion sentiments in complex environment.
Design/methodology/approach
Firstly, a new sentiment analysis model is proposed based on the asynchronous network theory. Then the graphical evaluation and review technique is employed and extended to design the model-based sentiment analysis algorithms. Finally, simulations and real-world case studies are given to show the effectiveness of the proposed model.
Findings
The dynamics of online public opinion sentiments are determined by both personal preferences to certain topics and the complex interactive influences of environmental factors. The application of appropriate quantitative models can improve the prediction of public opinion sentiment.
Practical implications
The proposed model-based algorithms provide simple but effective ways to explore the complex dynamics of online public opinions. Case studies highlight the role of government agencies in shaping sentiments of public opinions on social topics.
Originality/value
This paper proposes a new asynchronous network model for the dynamic sentiment analysis of online public opinions. It extends the previous static models and provides a new way to extract opinion evolution patterns in complex environment. Applications of the proposed model provide some new insights into the online public opinion management.
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Rong Wang, Jin Wu, Chong Li, Shengbo Qi, Xiangrui Meng, Xinning Wang and Chengxi Zhang
The purpose of this paper is to propose a high-precision attitude solution to solve the attitude drift problem caused by the dispersion of low-cost micro-electro-mechanical system…
Abstract
Purpose
The purpose of this paper is to propose a high-precision attitude solution to solve the attitude drift problem caused by the dispersion of low-cost micro-electro-mechanical system devices in strap-down inertial navigation attitude solution of micro-quadrotor.
Design/methodology/approach
In this study, a three-stage attitude estimation scheme that combines data preprocessing, gyro drifts prediction and enhanced unscented Kalman filtering (UKF) is proposed. By introducing a preprocessing model, the quaternion orientation is calculated as the composition of two algebraic quaternions, and the decoupling feature of the two quaternions makes the roll and pitch components independent of magnetic interference. A novel real-time based on differential value (DV) estimation algorithm is proposed for gyro drift. This novel solution prevents the impact of quartic characteristics and uses the iterative method to meet the requirement of real-time applications. A novel attitude determination algorithm, the pre-process DV-UKF algorithm, is proposed in combination with UKF based on the above solution and its characteristics.
Findings
Compared to UKF, both simulation and experimental results demonstrate that the pre-process DV-UKF algorithm has higher reliability in attitude determination. The dynamic errors in the three directions of the attitude are below 2.0°, the static errors are all less than 0.2° and the absolute attitude errors tailored by average are about 47.98% compared to the UKF.
Originality/value
This paper fulfils an identified need to achieve high-precision attitude estimation when using low-cost inertial devices in micro-quadrotor. The accuracy of the pre-process DV-UKF algorithm is superior to other products in the market.
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Chengxin Lin, Jieyi Chen, Chao Feng and Xiaojuan Li
Prefabricated building has emerged as a hallmark of modern construction industrialization and a pivotal driver of industrial upgrading. In this new building type, the supply of…
Abstract
Purpose
Prefabricated building has emerged as a hallmark of modern construction industrialization and a pivotal driver of industrial upgrading. In this new building type, the supply of high-quality prefabricated components plays a crucial role in ensuring project quality, cost-effectiveness and on-time completion. Consequently, selecting the optimum suppliers for these components is vital. This study provides valuable insights for construction enterprises, guiding them in the optimal selection of prefabricated component suppliers and thereby contributing to the sustainable development of the construction industry.
Design/methodology/approach
The entropy weight method is used to integrate and rank 19 commonly used evaluation indices, forming a supplier evaluation system from the enterprises perspective. Subsequently, the VIKOR multi-attribute decision model, combined with a comprehensive evaluation method based on cloud modeling, is applied to identify the most suitable suppliers through case study.
Findings
The findings emphasized that product quality, particularly the component compliance rate, is paramount in supplier selection. Additionally, companies should prioritize cost management and fundamental supplier capabilities, such as transportation efficiency and operational flexibility, while fostering strong partnerships with high-quality suppliers. Furthermore, all stakeholders need to enhance the supply chain’s responsiveness and adaptability, ensuring these improvements are achieved without strict cost controls.
Originality/value
This study minimizes the influence of subjective biases from decision-makers’ by integrating quantitative and qualitative analysis methods, thereby enhancing the comprehensiveness and accuracy of evaluations. By effectively addressing the fuzziness and uncertainty inherent in evaluation data, it establishes a robust system for selecting prefabricated building suppliers. This approach offers reliable and practical decision support, providing theoretical backing for enterprises in choosing prefabricated component suppliers and promoting the sustainable development of the prefabricated construction industry.
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The US-China trade war has brought forth the problem of balance of trade not only for them, but also for many other economies in the world. However, all the commodity segments are…
Abstract
The US-China trade war has brought forth the problem of balance of trade not only for them, but also for many other economies in the world. However, all the commodity segments are not equally affected and thus, the segment-wise trade analysis of commodities can bring up many valuable insights, vital for policy formulation process. Despite this, existing literature barely covered this aspect as a focal research. Therefore, this chapter has carried out segment-wise analysis of commodity classes popular in international trade discussions for the United States and China since the trade dispute intensified between them. In this chapter, we have built an argument around three commodity-segments which are popular in international trade studies namely, the raw material segment, semi-finished goods segment, and finished goods segments. While doing this analysis, we majorly focused on monopolistic power of economies in different commodity segments. We found that while in the segment of raw material, mostly cost is driving the trade, in the finished goods segment, variety and innovations are the key drivers that can boost trade by discovering new consumption spaces.
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Fangfang Hou, Boying Li, Zhengzhi Guan, Alain Yee Loong Chong and Chee Wei Phang
Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social…
Abstract
Purpose
Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social relationship (PSR), this study aims to capture viewers’ lively social feelings toward the streamer as the key factor leading to the purchase behavior of virtual gifts. It also aims to establish a theoretical link between PSR and viewers’ holistic experience in live streaming as captured by cognitive absorption and aims to investigates the role of technological features (i.e. viewer–streamer and viewer–viewer interactivity, streamer-level and viewer-level deep profiling and design aesthetics) in shaping viewers’ experience.
Design/methodology/approach
Based on 433 survey responses, this study employs a combination of structural equation modeling and neural networks to offer valuable insights into the relationships between the technological environment, viewer experience and viewer behavior.
Findings
Our results highlight the salience of PSR in promoting the purchase of virtual gifts through cognitive absorption and the importance of the technological environment in eliciting the viewer experience. This study sheds light on the development of PSR in a technological environment and its relationship with cognitive absorption.
Originality/value
By applying PSR to conceptualize viewers’ perceived connection with the streamer, this study extends the research on purchase behavior in the non-shopping context by providing an enlightened understanding of virtual gift purchase behavior in live streaming. Moreover, by theoretically linking PSR with cognitive absorption, virtual gift purchase and technological features of live streaming, it enriches the theory of PSR and bridges the gap between the design practice of supporting the IT infrastructure of live streaming and research.
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Praveen Ranjan Srivastava, Dheeraj Sharma and Inderjeet Kaur
Businesses need to make quick decisions and adjustments to fulfill the growing online demand. Previous studies examined various factors affecting the online sales performance of…
Abstract
Purpose
Businesses need to make quick decisions and adjustments to fulfill the growing online demand. Previous studies examined various factors affecting the online sales performance of products such as books, electronics and movies; however, they paid limited attention toward the local brand clothing products. The current study investigates the importance of different kinds of seller-generated and consumer-generated signals such as price, discount, product ratings, review volume, review sentiment, number of questions and interaction between some of these factors for predicting the sales performance of clothing products.
Design/methodology/approach
The multiple linear regressions has been employed to investigate the influence of various predictor variables on sales performance. The study also examines the importance of these predictor variables by using different machine learning models, including random forest (RF), neural networks and support vector regression (SVR).
Findings
The findings of the study emphasize the importance of price and discount rates offered on the product. The quantitative characteristics of reviews, such as review volume and average rating, have been found to be more important predictors than sentiment strengths. However, the sentiment strength of reviews with higher helpfulness scores plays a significant role in predicting sales performance.
Originality/value
The study highlights the varying importance of seller-based and consumer-based signals in predicting sales performance. It also investigates the interaction effect of these two kinds of signals. The consumer-generated signals have been further divided into two components based on social influence theory, and the interaction effects of these components have also been examined.
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Moses Nzuki Nyangu, Freshia Wangari Waweru and Nyankomo Marwa
This paper examines the sluggish adjustment of deposit interest rate categories with response to policy rate changes in a developing economy.
Abstract
Purpose
This paper examines the sluggish adjustment of deposit interest rate categories with response to policy rate changes in a developing economy.
Design/methodology/approach
Symmetric and asymmetric error correction models (ECMs) are employed to test the pass-through effect and adjustment speed of deposit rates when above or below their equilibrium levels.
Findings
The findings reveal an incomplete pass-through effect in both the short run and long run while mixed results of symmetric and asymmetric adjustment speed across the different deposit rate categories are observed. Collusive pricing arrangement behavior is supported by deposit rate categories that adjust more rigidly upwards than downwards, while negative customer reaction behavior is supported by deposit rate categories that adjust more rigidly downwards than upwards.
Practical implications
Even though the findings indicate an aspect of increased responsiveness over the period, the sluggish adjustment of deposit rates imply that monetary policy is still ineffective and not uniform across the different deposit rate categories.
Originality/value
To the best of the authors' knowledge, this is the first study to empirically examine both symmetric and asymmetric adjustment behavior of deposit interest rate categories in Kenya. The findings are key to policy makers as they provide insights on how long it takes to adjust different deposit rate categories to monetary policy decisions. In addition, the behavior of deposit rates partly explains why interest rates capping was imposed in Kenya in 2016.