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The purpose of this paper is to introduce structured light image processing technology into pipeline welding automation projects, and develop a vision‐based pipeline girth‐welding robot. The welding torch can accurately track the weld and complete the omni‐orientation welding automatically.

Weld image processing adopts the base theory including Laplacian of Gaussian filter, neighbourhood mean filter, largest variance threshold segmentation and morphologic, etc. obtains good effect of weld recognition.

The paper uses a vision sensor to achieve the weld character's recognition and extraction, directly control the robot tracking weld to complete automation welding. Compared with the existing pipeline welding devices, it does not need the lay orbit or plot tracking mark, which can shorten the assistant time to improve the productivity.

The research findings can satisfy the need of whole‐directional automation welding for large diameter transportation pipe's circular abutting weld. It fits for the automation welding for the long‐distance transportation pipe of petroleum, natural gas, and water.

Aiming at the character recognition and extract of V‐type weld, the method combining the neighbourhood mean filter algorithm with the largest variance threshold segmentation is proposed to obtain the quick weld image processing speed.

Ignition process is a critical issue in combustion systems. It is particularly important for reliability and safety prospects of aero-engine. This paper aims to numerically investigate the burner-to-burner propagation during ignition process in a full annular multiple-injector combustor and then validate it by comparing with experimental results.

The annular multiple-injector experimental setup features 16 swirling injectors and two quartz tubes providing optical accesses to high-speed imaging of flames. A Reynolds averaged Navier–Stokes model, adaptive mesh refinement (AMR) and complete San Diego chemistry are used to predict the ignition process.

The ignition process shows an overall agreement with experiment. The integrated heat release rate of simulation and the integrated light intensity of experiment is also within reasonable agreement. The flow structure and flame propagation dynamics are carefully analyzed. It is found that the flame fronts propagate symmetrically at an early stage and asymmetrically near merging stage. The flame speed slows down before flame merging. Overall, the numerical results show that the present numerical model can reliably predict the flame propagation during the ignition process.

The dedicated AMR method together with detailed chemistry is used for predicting the unsteady ignition procedure in a laboratory-scale annular combustor for the first time. The validation shows satisfying agreements with the experimental investigations. Some details of flow structures are revealed to explain the characteristics of unsteady flame propagations.

This paper aims to extract the universal results or conclusions with high value from the existing research conclusions, further compares the research results of knowledge search and its various dimensions on the impact of enterprise innovation performance in the existing research and supports the decision of which knowledge search to give priority to in the context of limited resources.

Based on the resource-based theory and resource dependence theory, this paper uses meta meta-analysis method to quantitatively synthesize multiple representative literature on the relationship between knowledge search and enterprise innovation performance, build a theoretical model of knowledge search and its dimensions and enterprise innovation performance and explore the internal mechanism of enterprises to improve innovation performance through knowledge search.

The results show the following: knowledge search behavior promotes the innovation performance of Chinese enterprises; expanding the width of knowledge search and deepening the depth of knowledge search have a positive impact on improving the innovation performance of Chinese enterprises; enterprise scale, industry field, development stage and other factors regulate the contribution of knowledge search width and depth to improving the innovation performance of Chinese enterprises.

This paper effectively clarifies the regulatory role of each dimension of knowledge search, makes reasonable explanations for different conclusions that are ambiguous or conflicting and answers questions like how knowledge search is related to enterprise innovation performance and what kind of knowledge search is more effective so as to provide some useful practical guidance and inspiration for enterprises to carry out innovation activities.

The purpose of this study is to explore the impact of online reviews on answer adoption in virtual Q&A communities, with an eye toward extending knowledge exchange and community management.

Online reviews contain rich cognitive and emotional information about community members regarding the provided answers. As feedback information on answers, it is crucial to explore how online reviews affect answer adoption. Based on signaling theory, a research model reflecting the influence of online reviews on answer adoption is established and empirically examined by using secondary data with 69,597 Q&A data and user data collected from Zhihu. Meanwhile, the moderating effects of the informational and emotional consistency of reviews and answers are examined.

The negative binomial regression results show that both answer-related signals (informational support and emotional support) and answerers-related signals (answerers’ reputations and expertise) positively impact answer adoption. The informational consistency of reviews and answers negatively moderates the relationships among information support, emotional support and answer adoption but positively moderates the effect of answerers’ expertise on answer adoption. Furthermore, the emotional consistency of reviews and answers positively moderates the effect of information support and answerers’ reputations on answer adoption.

Although previous studies have investigated the impacts of answer content, answer source credibility and personal characteristics of knowledge seekers on answer adoption in virtual Q&A communities, few have examined the impact of online reviews on answer adoption. This study explores the impacts of informational and emotional feedback in online reviews on answer adoption from a signaling theory perspective. The results not only provide unique ideas for community managers to optimize community design and operation but also inspire community users to provide or utilize knowledge, thereby reducing knowledge search costs and improving knowledge exchange efficiency.

Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.

The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.

The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.

This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.

Recent studies suggested that owner dynamic capabilities (ODCs) enabling public owners of megaprojects to activate, orchestrate and reorganize resources to uncertainties were beneficial to improving the project resilience of megaprojects. However, most of them pay insufficient attention to the specific context of long cycles and deep uncertainty in megaprojects, neglecting the causal complexity that different dimensions of ODCs and learning mechanisms interact with each other in terms of enhancing project resilience. Therefore, this study aims to systematically unveil the complex causality among ODCs, learning mechanisms and project resilience of megaprojects.

This study introduces a configurational perspective to explore how multi-dimensional ODCs combine to improve project resilience in megaprojects along with different organizational learning mechanisms and learning orientations. Based on 330 ODC events in 19 construction megaprojects, a multi-temporal crisp-set qualitative comparative analysis method is adopted to extract configurations of ODCs for project resilience improvement and unveil their evolution features over the whole megaproject lifecycle.

Six configurations are identified for improving project resilience in megaprojects, including cognition-dominant, cognition-deficient, transformation-dominant, innovation-driven, value-co-creation and exploitative-transformation configurations. The results also indicate that distinct megaproject stages appeal to corresponding ODC configurations for project resilience improvement under unique uncertain contexts.

This study not only makes theoretical contributions to the literature on dynamic capability and project resilience in the megaproject management field but also provides useful practical guidance for public owners of megaprojects to better utilize ODCs for project resilience improvement.