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In order to solve the problems faced by First Order Reliability Method (FORM) and First Order Saddlepoint Approximation (FOSA) in structural reliability optimization, this paper aims to propose a new Reliability-based Design Optimization (RBDO) strategy for offshore engineering structures based on Original Probabilistic Model (OPM) decoupling strategy. The application of this innovative technique to other maritime structures has the potential to substantially improve their design process by optimizing cost and enhancing structural reliability.

In the strategy proposed by this paper, sequential optimization and reliability assessment method and surrogate model are used to improve the efficiency for solving RBDO. The strategy is applied to the analysis of two marine engineering structure cases of ship cargo hold structure and frame ring of underwater skirt pile gripper. The effectiveness of the method is proved by comparing the original design and the optimized results.

In this paper, the proposed new RBDO strategy is used to optimize the design of the ship cargo hold structure and the frame ring of the underwater skirt pile gripper. According to the results obtained, compared with the original design, the structure of optimization design has better reliability and stability, and reduces the risk of failure. This optimization can also better balance the relationship between performance and cost. Therefore, it is recommended for related RBDO problems in the field of marine engineering.

In view of the limitations of FORM and FOSA that may produce multiple MPPs for a single performance function, the new RBDO strategy proposed in this study provides valuable insights and robust methods for the optimization design of offshore engineering structures. It emphasizes the importance of combining advanced MPP search technology and integrating SORA and surrogate models to achieve more economical and reliable design.

As a clean and renewable energy source, wind energy will become one of the main sources of new energy supply in the future. Relying on the stable and strong wind resources at sea, wind energy has great potential to become the primary energy. As a critical part of the wind turbine, the gearbox of a wind turbine often bears a large external load. Especially at sea, due to the effects of ocean corrosion, waves and wind, the burden of the wind turbine gearbox is greater, which brings great challenges to its reliability analysis. This study aims to systematically review the reliability research in wind turbine gearboxes and guide future research directions and challenges.

This study systematically reviews some design requirements and reliability analysis methods for wind turbine gearboxes. Then, it summarizes previous studies on wind load uncertainty modeling methods, including the processing of wind measurement data and the summary of three different classifications of random wind speed prediction models. Finally, existing reliability analysis studies on two major parts of the gearbox are described and summarized.

First, the basic knowledge of wind turbine gearboxes and their reliability analysis is introduced. The requirements and reliability analysis methods of wind turbine gearboxes are explained. Then, the processing methods of wind measurement data and three different random wind speed prediction models are described in detail. Furthermore, existing reliability analysis studies on two common parts of wind turbine gearboxes, gears and bearings, are summarized and classified, including a summary of bearing failure modes. Finally, three possible future research directions for wind turbine gearbox reliability analysis are discussed, namely, reliability research under the influence of multiple factors on gears, damage indicators of bearing failure modes and quantitative evaluation criteria for the overall dynamic characteristics of offshore wind turbine gearboxes and a summary is also given.

This paper aims to systematically introduce the relevant contents of wind turbine gearboxes and their reliability analysis. The contents of wind speed data processing, predictive modeling and reliability analysis of major components are also comprehensively reviewed, including the classification and principle introduction of these contents.

Transporting hydrogen through natural gas pipelines in blended compositions has been proven to be a highly feasible solution in the short term. However, under hydrogen-rich environments, steel structures are prone to hydrogen-induced damage (HID). Additionally, uncertainties in various parameters can significantly impact the performance evaluation of hydrogen pipelines. Efficient reliability and sensitivity analyses of medium- to high-strength steel pipelines considering HID have become a challenge. Therefore, the primary aim of this study is to address this issue.

This study first establishes reliability analysis models for medium- to high-strength steels, represented by X65 and X80. In these models, the effect of HID is expressed by reduced stress, and its statistical parameters are calculated. Then, a highly efficient enhanced first order reliability method (FORM) is proposed for pipeline reliability analysis. This method overcomes the oscillation and convergence issues of traditional FORM when dealing with certain problems and can compute negative reliability indices. The proposed reliability analysis method is applied to solve the constructed reliability models. Finally, a reliability sensitivity analysis is conducted on the models to identify the key variables affecting the reliability of medium- to high-strength steel pipelines under HID.

First, two reliability analysis examples are used to validate the effectiveness of the proposed enhanced FORM. Then, using this method to solve the constructed reliability models for X65 and X80 steel pipelines under HID reveals that, for both types of steel, the reliability indices decrease significantly when considering HID compared to cases without HID. The decline is more pronounced for X80 steel than for X65 steel. As internal pressure increases, the reliability of both steels drops sharply, showing a concave parabolic trend. Moreover, the reliability sensitivity analysis shows that at a pressure of 10 MPa, for both X80 and X65, internal pressure, pipeline wall thickness and model error are the top three factors influencing reliability. As internal pressure increases, its influence becomes stronger, while the impact of other variables diminishes. Notably, for X80 steel, the presence of hydrogen amplifies the effect of internal pressure on pipeline reliability compared to when HID is not considered, but for X65, this trend is reversed.

Given the urgent need for safety evaluation studies on hydrogen transport through natural gas pipelines, this research provides new insights by constructing reliability models for X65 and X80 pipeline steels under HID and introducing an enhanced FORM method. The results of the reliability and sensitivity analyses of the models offer valuable insights and serve as a reference for engineering design.

Firms are driven to ride on the digital wave in today’s open innovation ecosystem. This study aims to explore the effect of digital transformation (DT) on knowledge-intensive business services (KIBS) firms’ innovation ambidexterity, namely, radical versus incremental innovation, respectively. Meanwhile, the authors evaluated the moderating role of the complexity of R&D collaboration portfolio (i.e. organizational diversity and geographic diversity) in the above relationships.

Using a panel data set of 171 Chinese listed firms in the information and communications technology services industry from 2010 to 2018, the proposed hypotheses were empirically attested.

It is found that DT has a positive relationship with radical innovation and an inverted U-shaped relationship with incremental innovation. In terms of the R&D collaboration portfolio, organizational diversity positively moderates the relationships between DT and innovation ambidexterity, respectively. The geographic diversity weakens the inverted U-shaped effect of DT on incremental innovation; however, its moderating role in the link between DT and radical innovation is not empirically verified.

Extant scholars mainly addressed the interplay between KIBS firms and their manufacturing clients, while this study reveals the different consequences of DT on KIBS firms’ innovation ambidexterity to highlight the role of KIBS firms is an independent and essential innovator in a knowledge-driven economy. Notably, the findings contribute to knowledge management (KM) and R&D literature by confirming the diversity of the R&D collaboration portfolio is a critical KM strategy for KIBS firms to develop and promote external knowledge resources.

In the context of severe environmental pollution and resource shortage, this study aims to examine how knowledge flows affect the green activities of firms. Specifically, this paper explored whether the firms’ knowledge flows, namely, knowledge inflow (KIF) and knowledge outflow (KOF), play a moderating role in relationship between corporate environmental responsibility (CER) and green innovation in Chinese high-polluting firms.

The analysis was carried out based on a panel data set of 305 heavy-polluting Chinese listed firms from 2010 to 2020. Meanwhile, this paper adopted the fixed model to empirically attest the proposed hypotheses regarding the relationships among CER, knowledge flows and green innovation.

The results indicate that there is a U-shaped relationship between CER and green innovation, while the two dimensions of knowledge flows exert opposing effects on the nonlinear link between CER and green innovation. Specifically, KIF positively moderates the effect of CER on green innovation, whereas KOF negatively moderates the effect of CER on green innovation.

This study demonstrates how green innovation can be influenced by CER and, moreover, provides a more nuanced understanding of the value of knowledge management (KM) in firms’ green activities. In this way, this paper answers the call for understanding the importance of green transformation in the context of KM.

This paper provides a day-to-day analysis of the reliability of commuting time and trip scheduling under the Advanced Traveler Information System (ATIS). A simple network with parallel routes and bottleneck congestion is used to simulate the departure time and route choice decisions of commuters to minimize total travel time and scheduling delay cost. There are two major factors influencing the decisions of drivers in their departure time and route choices: their accumulated travel experience and information provided by ATIS. A simple experiment is carried for investigating trip-scheduling reliability of this network system.

The purpose of this paper is to investigate the flow and heat transfer of power-law fluids over a non-linearly stretching sheet with non-Newtonian power-law stretching features.

The governing non-linear partial differential equations are reduced to a series of ordinary differential equations by suitable similarity transformations and the numerical solutions are obtained by the shooting method.

As the temperature power-law index or the power-law number of the fluids increases, the dimensionless stream function, dimensionless velocity and dimensionless temperature decrease, while the velocity boundary layer and temperature boundary layer become thinner for other fixed physical parameters. The thermal diffusivity varying as a function of the temperature gradient can be used to present the characteristics of flow and heat transfer of non-Newtonian power-law fluids.

Unlike classical works, the effect of power-law viscosity on the temperature field is considered by assuming that the temperature field is similar to the velocity field with modified Fourier’s law heat conduction for power-law fluid media.