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The purpose of this paper is to provide a comprehensive review of a non-contact full-field optical measurement technique known as digital image correlation (DIC).

The approach of this review paper is to introduce the research pertaining to DIC. It comprehensively covers crucial facets including its principles, historical development, core challenges, current research status and practical applications. Additionally, it delves into unresolved issues and outlines future research objectives.

The findings of this review encompass essential aspects of DIC, including core issues like the subpixel registration algorithm, camera calibration, measurement of surface deformation in 3D complex structures and applications in ultra-high-temperature settings. Additionally, the review presents the prevailing strategies for addressing these challenges, the most recent advancements in DIC applications across quasi-static, dynamic, ultra-high-temperature, large-scale and micro-scale engineering domains, along with key directions for future research endeavors.

This review holds a substantial value as it furnishes a comprehensive and in-depth introduction to DIC, while also spotlighting its prospective applications.

This paper aims to investigate the influence of droplet infiltration and sliding on the deposition size and make a uniform deposition by controlling the interaction between droplets, using the three-dimensional lattice Boltzmann method (LBM) based on the actual working condition.

D3Q19 Shan-Chen LB approach is developed and optimized based on the metal droplet deposition. The Carnahan-Starling equation of state and transition layers are introduced to maintain the greater stability and low pseudo velocities. In addition, an additional collision term is adopted to implement immersed moving boundary scheme to deal with no-slip boundaries on the front of the phase change.

The numerical results show that the new¬ incoming droplet wet and slide off the solidified surface and the rejection between droplets are the reasons for the deviation of the actual deposition length. The total length of the longitudinal section negatively correlates with the deposition distance. To improve the dimensional accuracy, the deposition distance and repulsion rate need to be guaranteed. The optimal deposition distance is found to have a negative linear correlation with wettability.

The numerical model developed in this paper will help predict the continuous metal droplet deposition and provide guidance for the selection of deposition distance.

The vehicle´s body front pillar should absorb most of the striker kinetic energy, while only a fraction of that is absorbed by the door structure. This study aims to discuss the aforementioned issue. In this test the striker is a virtual entity. Six uniaxial strain gauges are installed throughout the door. Additionally, contactless 3D digital image correlation (DIC) allows to assess the major door panel’s continuous deformation and strain fields.

A coach is a large and heavy long-distance passenger transport vehicle. Their structural certification, classifies coaches as M3 Class III vehicles. New coach structures’ designs need analyses of each sub-system for critical pre-validation of the entire structure, aiming driver and passenger carrier safety. Also, a thorough examination due to increased travel speed is needed.

Experimental pseudo-dynamic (PSD) results were compared and validated using finite element method (FEM) with two pieces of distinct FEM software (Abaqus® and PamCrash®). The time dependent solution was carried out by explicit techniques. Results by FEM and PSD test showed good agreement, evidencing the reliability of the tools selected. Results by PamCrash® were closer to the experimental data.

R-29 is truck-only regulation, however can be adapted to coaches in case of a frontal collision. The present work focuses on the impact behavior of the passenger front door subsystem.

As a first validation the entire structure, the behavior of a vehicle door, under in-plane impacts was studied. The corresponding deformation energy absorbed by the frontal passenger coach door under virtual impacts of a swinging striker was assessed using a PSD approach.

The low-temperature sintering of silica glass combined with additive manufacturing (AM) technology has brought a revolutionary change in glass manufacturing. This study aims to carry out in an attempt to achieve precious manufacturing of silicate glassy matrix through the method of slurry extrusion.

A low-cost slurry extrusion modelling technology is used to extrude silicate glassy matrix inks, composed of silicate glass powder with different amounts of additives. Extrudability of the inks, their printability window and the featuring curves of silicate glassy matrix are investigated. In addition, the properties of the low-temperature sintering green part as a functional part are explored and evaluated from morphology, hardness and colour.

The results showed that the particle size was mainly distributed from 1.4 µm to 5.3 µm, showing better slurry stability and print continuity. The parameters were set to 8 mm/s, 80% and 0.4 mm, respectively, to achieve better forming of three-dimensional (3D) samples. Besides, the organic binder removal step was concentrated on 200°C–300°C and 590°C–650°C was the fusion bonding temperature of the powder. The hardness values of 10 test samples ranged from 588 HL to 613 HL, which met the requirements of hard stones with super-strong mechanical strength. In addition, the mutual penetration of elements caused by temperature changes may lead to a colourful appearance.

The custom continuous AM technology enables the fabrication of a glass matrix with 3D structural features. The precise positioning technology of the glass matrix is expected to be applied more widely in functional parts.

Prior studies have argued that multinational firms with dynamic capabilities can reconfigure and upgrade their internal and external resources and adapt to an ever-changing competitive global environment. The impact of home country networks exerting on multinational corporations’ (MNCs) dynamic capabilities has been rarely discussed in extant research. This paper aims to explore how two types of home country networks’ relational embeddedness (from domestic firms and foreign firms) affect Chinese MNCs’ dynamic capabilities.

Several hypotheses were tested by analyzing the survey data from 204 multinational companies in china.

The results reveal the impact mechanism of the home country network on dynamic capabilities. Embeddedness in domestic networks positively affects embeddedness in the foreign network; embeddedness in foreign firms exerts positive effects on the three dimensions of MNC’s dynamic capabilities. Additionally, the effect of domestic firms’ relational embeddedness on resource reconfiguring capability is mediated by foreign firms’ embeddedness. Consequently, this study provides a theoretical introduction for MNCs from emerging economies.

This study has several managerial implications for emerging MNCs’ international operations. For MNCs from emerging economies, close cooperation with domestic firms helps firms to develop a close relationship with foreign firms; meanwhile, developing a close relationship with foreign firms can obtain spillover about technology and management experience better, improving dynamic capability. Specifically, domestic embeddedness, through foreign embeddedness, can extend the impact to focal firms in developing resource reconfiguring capability.

This study provides an alternate view of how home country networks influence the dynamic capabilities of Chinese MNCs and outlines its impact mechanism. Therefore, the study contributes both to the international business literature and social network literature.

The purpose of this paper is to explore whether the out-of-sample model bias plays an important role in predicting volatility.

Under the heterogeneous autoregressive realized volatility (HAR-RV) framework, we analyze the predictive power of out-of-sample model bias for the realized volatility (RV) of the Dow Jones Industrial Average (DJI) and the S&P 500 (SPX) indices from in-sample and out-of-sample perspectives respectively.

The in-sample results reveal that the prediction model including the model bias can obtain bigger R², and the out-of-sample empirical results based on several evaluation methods suggest that the prediction model incorporating model bias can improve forecast accuracy for the RV of the DJI and the SPX indices. That is, model bias can enhance the predictability of original HAR family models.

The author introduce out-of-sample model bias into HAR family models to enhance model capability in predicting realized volatility.

With the rapid development of the digital economy, an increasing number of digitalized two-sided platforms have deployed the tying strategy to leverage their market power from the core two-sided product to other two-sided products in the competitive market, which transforms the competition among single platforms into that among platform ecological networks. To clarify the mechanism of the formation of the digital platform ecological networks, this paper aims to analyze the expansion and stability of platform ecology by exploring the impacts of network externalities and sellers’ heterogeneity on the tying strategy of two-sided platforms.

This paper develops a game model of two-sided platforms based on Choi and Jeon (2021), which highlights the decisive influence of non-negative price constraints (NPC) on platforms’ tying motivation. Taking the operating systems market as an example, we expand from the perspective of platform service differences to relax the NPC and explore the internal logic of platform ecosystem expansion.

Platforms have an incentive to charge lower prices or even subsidize buyers when the network externalities on the sellers’ side are relatively strong. When the product is highly differentiated and heterogenous, platforms are motivated to tie to capture more buyers with a lower price and grab excess profits from sellers. Eventually, tying is able to consolidate the two-sided platform ecological networks by excluding competitors, capturing user value and deterring entry.

In order to describe the characteristics of platform ecological network more generally, this paper extends the research based on the analyses of Choi and Jeon (2021) by (1) allowing horizontal differences between tied products and (2) relaxing the NPC. Unlike Choi and Jeon (2021), this paper allows platforms to charge users of two-sided platforms at negative prices (or to subsidize them). (3) Setting simultaneous pricing in two-sided platforms. Classical two-sided market theory stresses that the presence of cross-network externalities can give rise to a “chicken and egg” problem.

With many years’ economic transformation from “Made in China” to “Created in China,” the State Council has set May 10th as annual “China’s Brand Day” from 2017. This action indicates the implementation of brand strategy and the new national policy of promoting China’s brands. The purpose of this paper is to examine the influence of marketing background of top management team (TMT) on trademark and brand output.

Using the trademark application data of Chinese-listed companies, this paper constructs a multiple linear regression model and uses the OLS method. This research also uses two-stage regression to examine the effect of endogeneity on the results.

Our results show that the higher the proportion of executives with marketing background in TMT, the more the number of trademark applications. Furthermore, we document that the positive impact of TMT marketing background on the number of trademark applications is more pronounced in non-state-owned enterprises, companies with more patent output and companies whose CEO has marketing background, indicating that when TMT can play a bigger role, companies have better innovation ability and team collaboration is more efficient, the promoting role of TMT marketing background on the number of corporate trademark applications will be stronger.

This research focuses on the world’s largest emerging economy – China, which is different from the existing literature that is mainly based on western developed countries. With China’s economy stepping into a new normal and consumption upgrading, it is important and worthy of a deep discussion about which factors affect the company’s trademark and brand management.

The demand to reduce carbon emissions has become an increasingly important social factor due to the unprecedented impacts of climate change. However, most existing publications have focused on minimizing emissions during the operational phase of buildings. At the same time, there is a lack of comprehensive research conducted on carbon emissions, specifically during the construction phase. The purpose of this paper is to identify, review and classify current practices related to carbon emissions management in construction operations to gain greater insight into how to reduce and mitigate emissions and achieve more sustainable solutions.

This study reviewed the published literature on carbon emissions from construction. A total of 198 bibliographic records were extracted from the Scopus collection database and analyzed using Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA). PRISMA is used as a basis for reporting possible trends, research methods and strategies used in published literatures. A total of 99 papers related to carbon emissions in the construction operations were further reviewed and analyzed. This review paper draws on existing research and identifies current carbon management patterns in construction projects.

Data indicated an upward trend in the number of publications in carbon emissions research during the last few years, particularly in 2015, 2017 and 2019. The most significant contributions to the domain were reported from China, Europe and the USA. This paper found that most studies conduct the Life Cycle Assessment (LCA) method to estimate carbon emissions. This paper found that the primary studies have focused on construction machinery and equipment emissions. The strategies such as establishing uniform standards for carbon emissions policies and regulations, equipment and logistic planning and low carbon design material will potentially impact carbon emissions reductions.

This paper provides information that will be beneficial for the construction industry to design and manage construction operations. It will also be of interest to those looking to reduce or manage construction emissions.

Although there is a diversity of current thinking related to the practical estimation and management of carbon emissions in construction projects, there is no consolidated set of keys of standardized carbon emissions management in practice. By assessing the existing paradigms of carbon assessment methods and tactics in the construction industry, this study contributed to the existing knowledge base by providing insights into current techniques in the construction sector for monitoring and mitigating emissions.

The air‐breathing hypersonic vehicle (AHV) includes intricate inherent coupling between the propulsion system and the airframe dynamics, which results in an intractable nonlinear system for the controller design. The purpose of this paper is to propose an H∞ control method for AHV based on the online simultaneous policy update algorithm (SPUA).

Initially, the H∞ state feedback control problem of the AHV is converted to the problem of solving the Hamilton‐Jacobi‐Isaacs (HJI) equation, which is notoriously difficult to solve both numerically and analytically. To overcome this difficulty, the online SPUA is introduced to solve the HJI equation without requiring the accurate knowledge of the internal system dynamics. Subsequently, the online SPUA is implemented on the basis of an actor‐critic structure, in which neural network (NN) is employed for approximating the cost function and a least‐square method is used to calculate the NN weight parameters.

Simulation study on the AHV demonstrates the effectiveness of the proposed H∞ control method.

The paper presents an interesting method for the H∞ state feedback control design problem of the AHV based on online SPUA.