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Accurately estimating the severity of derailment is a crucial step in quantifying train derailment consequences and, thereby, mitigating its impacts. The purpose of this paper is to propose a simplified approach aimed at addressing this research gap by developing a physics-informed 1-D model. The model is used to simulate train dynamics through a time-stepping algorithm, incorporating derailment data after the point of derailment.

In this study, a simplified approach is adopted that applies a 1-D kinematic analysis with data obtained from various derailments. These include the length and weight of the rail cars behind the point of derailment, the train braking effects, derailment blockage forces, the grade of the track and the train rolling and aerodynamic resistance. Since train braking/blockage effects and derailment blockage forces are not always available for historical or potential train derailment, it is also necessary to fit the historical data and find optimal parameters to estimate these two variables. Using these fitted parameters, a detailed comparison can be performed between the physics-informed 1-D model and previous statistical models to predict the derailment severity.

The results show that the proposed model outperforms the Truncated Geometric model (the latest statistical model used in prior research) in estimating derailment severity. The proposed model contributes to the understanding and prevention of train derailments and hazmat release consequences, offering improved accuracy for certain scenarios and train types

This paper presents a simplified physics-informed 1-D model, which could help understand the derailment mechanism and, thus, is expected to estimate train derailment severity more accurately for certain scenarios and train types compared with the latest statistical model. The performance of the braking response and the 1-D model is verified by comparing known ride-down profiles with estimated ones. This validation process ensures that both the braking response and the 1-D model accurately represent the expected behavior.

The purpose of this paper is to increase understanding of the real situation of Enterprise's Sustainable Innovation (ESI) in China.

First, the paper analyzes the practice of Chinese ESI in the past 30 years, and then reviews research results of the topic in China, by the authors and by other Chinese scholars. Finally, it provides the future prospects for ESI in China.

The practice of Chinese ESI started in 1978 when this country began reform, and two stages of Chinese ESI practice has been summarized. Otherwise, six major characteristics have been highlighted. China is one of the earliest countries that began to research on ESI and has achieved significant results since 1995. The paper summarizes major research findings of ESI in China, which can be divided into two categories. Especially, it stresses that one of the distinguishing achievements is research on mechanisms of ESI in China.

The research on ESI in China is initially implemented based on Chinese practice. So, future research may explore whether the research results could be suitable for abroad, or not.

This original paper analyzes ESI practice and research findings in China, and may have value in helping people to understand ESI's real situation.

Previous research has explored a relatively narrow representation of the lesbian, gay, bisexual, transsexual and queer (LGBTQ) community. Yet modern event attendees are part of a diverse niche group within the broader LGBTQ community. This group comprises a wide range of event attendees in search of more than sex, clubs and feather boas. This paper aims to report on empirical research conducted in Queenstown, New Zealand, during the 2016 Gay Ski Week (GSW) and explores the transformative, inclusive potential of event places, social atmospheres and experiences.

Ethnographic and autoethnographic research methods were used in this study for the exploration of transformative tourism experiences. Qualitative data were collected via in-depth interviews, observations and one of the author’s immersive experiences of the event. This author was able to bridge the divide between research and participant, contributing to a contextualised understanding of various participants’ subjective realities.

The paper reports on and discusses empirical findings, which are organised under the meta-themes of place and social atmosphere, attendee experiences, acceptance and inclusivity.

From these themes emerge a broader understanding of how LGBTQ tourism events can contribute to transformative, inclusive experiences.

This paper explores the need for event managers to revisit and adapt to the demographic, motivational and behavioural characteristics of the modern gay event attendee. In particular, this paper discovers the motivations of Asian gay attendees as a marginalised community within a traditional LGBTQ event in a traditional heterosexual destination.

The surging market demand for green construction materials has brought opportunities for construction materials enterprises' greenwashing behavior (GWB). This study aims to establish the causal relationship among the influencing factors of GWB and reveal the key influencing factors from the perspective of Chinese construction materials enterprises under multi-agent interactions.

This study is based on stakeholder theory, resource-based theory and the green development behavior and performance of industrial enterprises (GDBP-IE). First, with the literature analysis, an index framework of the influencing factors of enterprises' GWB was constructed from five dimensions (including 15 factors): environmental regulation, public scrutiny, market environment, corporate resources and corporate green development (GD) performance. Second, the interactive relationship among influencing factors was obtained by a questionnaire survey. Finally, the data are processed and analyzed with the grey-DEMATEL (Decision-making Trial and Evaluation Laboratory) method.

Among the factors, corporate information transparency has the greatest impact on the other factors, and consumer green preferences are most influenced by others. The most critical and important factor is the corporate social performance factor. In China, corporate social performance, corporate information transparency, corporate size and media supervision are the key factors influencing the GWB of construction materials enterprises.

This study provides a new perspective on the literature related to GWB by considering multi-agent interactions and extends the evidence from the construction materials industry for research on the drivers or influencing factors of enterprises' bad environmental behavior. Furthermore, it adds insights from China for further research on the governance strategies of GWB in other countries.

This paper investigates the effects of different uncertainties on Internet stock trading (IST) adoption intentions of individual investors in China and aims to determine the interaction effects of trust and perceived benefits in the relationship between uncertainty dimensions and IST adoption intentions.

Using a structured questionnaire, a survey of 353 experienced stock traders was conducted in China. The proposed uncertainty-trust-perceived benefits framework was examined through structural equation modelling using Smart PLS 3.0.

The study found significant negative effects of perceived technology uncertainty, perceived regulatory uncertainty and perceived information asymmetry on the IST adoption intentions of individual investors. Perceived service intangibility was found to have only insignificant effects on IST adoption intentions. In terms of interaction results, trust significantly moderates the relationship between IST adoption intentions and, respectively, perceived technology uncertainty and perceived information asymmetry. Similarly, perceived benefits significantly moderate the relationship between intentions to adopt IST and both perceived technology uncertainty and perceived regulatory uncertainty.

The regulators for IST development in China could utilise the results of this study as guidelines for strategies to increase the use of IST among existing and potential investors.

Using social cognitive theory, this research investigates the effects of various uncertainties on IST adoption intentions of individual investors in China; these effects have not been explored by previous literature. Furthermore, few studies other than this one have investigated the interaction effects of factors which counteract the negative effect of other factors.

At the US passenger stations, train operations approaching terminating tracks rely on the engineer’s compliant behavior to safely stop before the end of the tracks. Noncompliance actions from the disengaged or inattentive engineers would result in hazards to train passengers, train crewmembers and bystanders at passenger stations. Over the past decade, a series of end-of-track collisions occurred at passenger stations with substantial property damage and casualties. This study’s developed systemic model and discussions present policymakers, railway practitioners and academic researchers with a flexible approach for qualitatively assessing railroad safety.

To achieve a system-based, micro-level analysis of end-of-track accidents and eventually promote the safety level of passenger stations, the systems-theoretic accident modeling and processes (STAMP), as a practical systematic accident model widely used in the complex systems, is developed in view of environmental factors, human errors, organizational factors and mechanical failures in this complex socio-technical system.

The developed STAMP accident model and analytical results qualitatively provide an explicit understanding of the system hazards, constraints and hierarchical control structure of train operations on terminating tracks in the US passenger stations. Furthermore, the safety recommendations and practical options related to obstructive sleep apnea screening, positive train control-based collision avoidance mechanisms, robust system safety program plans and bumping posts are proposed and evaluated using the STAMP approach.

The findings from STAMP-based analysis can serve as valid references for policymakers, government accident investigators, railway practitioners and academic researchers. Ultimately, they can contribute to establishing effective emergent measures for train operations at passenger stations and promote the level of safety necessary to protect the public. The STAMP approach could be adapted to analyze various other rail safety systems that aim to ultimately improve the safety level of railroad systems.

This paper studies the nonlinear dynamics of membrane structure considering wrinkling effect. The coupling between wrinkles and vibration is investigated elaborately, and new insight on the dynamics of wrinkled membrane is unveiled.

Based on the stability theory of plates and shells, the wrinkling model of the membrane structure is established. Considering the effects of wrinkling and nonlinearity, the dynamic response is calculated with NewMark method.

Wrinkling will impact the dynamics of the membrane structure significantly for asymmetrical tension loading cases, dynamic response of the wrinkled membrane structure can be classified into three categories: when the vibration is small, the dynamics of the wrinkled membrane structure will behave linearly, and the wrinkles will only affect the dynamic properties as initial conditions; when the vibration is relatively large, the wrinkles will interact with the vibration during the dynamic process, and the dynamics of the structure shows very complex features; when the vibration is large enough, the dynamics will be dominated by the geometric nonlinearity of large-amplitude vibration.

In the previous works on dynamics of wrinkled membrane structure, only the vibration modes have been studied, which means all those investigations are confined with linear vibration; little research has been conducted on the nonlinear dynamics of wrinkled membrane structure. In view of this, this paper presents an investigation of dynamic properties of membrane structure considering the wrinkling and geometric nonlinear effects. This research work presents some novel discoveries on the nonlinear dynamics of wrinkled membrane.

This research is aimed to mainly be applicable to expediting engineering projects, uses the method of inverse optimization and the double-layer nested genetic algorithm combined with nonlinear programming algorithm, study how to schedule the number of labor in each process at the minimum cost to achieve an extremely short construction period goal.

The method of inverse optimization is mainly used in this study. In the first phase, establish a positive optimization model, according to the existing labor constraints, aiming at the shortest construction period. In the second phase, under the condition that the expected shortest construction period is known, on the basis of the positive optimization model, the inverse optimization method is used to establish the inverse optimization model aiming at the minimum change of the number of workers, and finally the optimal labor allocation scheme that meets the conditions is obtained. Finally, use algorithm to solve and prove with a case.

The case study shows that this method can effectively achieve the extremely short duration goal of the engineering project at the minimum cost, and provide the basis for the decision-making of the engineering project.

The contribution of this paper to the existing knowledge is to carry out a preliminary study on the relatively blank field of the current engineering project with a very short construction period, and provide a path for the vast number of engineering projects with strict requirements on the construction period to achieve a very short construction period, and apply the inverse optimization method to the engineering field. Furthermore, a double-nested genetic algorithm and nonlinear programming algorithm are designed. It can effectively solve various optimization problems.

This paper aims to try to develop new, environmentally friendly and efficient lubricating additives; study the compatibility of carbon-based additives with different base oils [Polyalphaolefin (PAO)-3, PAO-20 and NPE-2]; and explore the lubrication mechanism.

Oleylamine modified carbon nanoparticles (CNPs-OA) were prepared and the dispersion stability of CNPs-OA in PAO-3, PAO-20 and NPE-2 base oils was investigated by transmission electron microscopy, Fourier transform infrared, thermogravimetric analysis, energy dispersive spectroscopy and X-ray photoelectron spectroscopy. Universal Mechanical Tester (UMT) platform was used to carry out experiments on the effects of different additive concentrations on the lubricating properties of base oil.

The mean friction coefficient of PAO-3, PAO-20 and NPE-2 reduced by 32.8%, 10.1% and 11.4% when the adding concentration of CNPs-OA was 1.5, 2.0 and 0.5 Wt.%, respectively. Generally, The CNPs-OA exhibited the best friction-reducing and anti-wear performance in PAO-3.

The agglomeration phenomenon of carbon nanoparticles as lubricating additive was improved by surface modification, and the lubricating effect of carbon nanoparticles in three synthetic aviation lubricating base oils was compared.

The green innovation behavior of construction enterprises is the key to reducing the construction industry's carbon emissions and realizing the green transformation of the construction industry. The purpose of this study is to reveal the evolutionary mechanism of green innovation behavior in construction enterprises.

This study is based on resource-based theory, Porter's hypothesis and signaling theory. First, a measurement model of the green innovation behavior of construction enterprises was constructed from three aspects: environmental regulation, enterprise resources and public opinion through hierarchical analysis. Then, the state values of the measurement model of green innovation behavior of construction enterprises were calculated through the time series data from 2011–2018. Finally, the Markov chain model was used to predict the evolutionary trend of green innovation behavior of construction enterprises, and the accuracy of the prediction effect of the Markov chain model was verified using the time series data of 2019.

The Markov chain model of green innovation behavior of construction enterprises constructed in this study has high accuracy. This model finds that the transition of the growth state of green innovation behavior in China's construction industry is fluid and predicts the evolution trend of the innovation behavior of construction enterprises. In the future, the green innovation behavior of construction enterprises has a probability of 70.17% to be in a continuous growth state and 40.27% to be in a rapid growth state.

Based on the Markov chain model of green innovation behavior of construction enterprises, this study finds that the transition of the growth state of green innovation behavior of construction enterprises in China has the characteristics of liquidity. In addition, it reveals the development process of the green innovation behavior of construction enterprises from 2011–2018 and predicts the evolution trend of the green innovation behavior of construction enterprises.