Xuzhou Institute of Technology

About: Xuzhou Institute of Technology is a education organization based out in Xuzhou, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 1696 authors who have published 1521 publications receiving 13541 citations.

A Hybrid Approach for Dynamic Simulation of Safety Risks in Mega Construction Projects

Abstract: Mega construction projects (MCPs) are inherently high-risk and complex. The challenge of safety management for mega construction projects is that safety risk factors constantly change and interact with each other in the long-term construction period. Few of the prior studies have enabled the prediction of the safety state in a dynamic and connected overview, which is a critical characteristic of safety risks in MCPs. Therefore, a hybrid approach for the dynamic simulation of risk factors is proposed. A three-stage procedure review of explicit documents, including accident investigation reports and construction standards, was carried out to identify safety risk factors and the causal relationships among them. Subsequently, the likelihood exposure and consequence (LEC) assessment method was applied to define the changes in risk factors over time. A system dynamics (SD) model was established to integrate the interacting risks and simulate the developing trend of the overall safety risk state. Moreover, a sensitivity analysis was provided to rank risk factors and simulate optimal risk mitigation strategies. Finally, the model was applied to the urban rail transit Line 9 project in China as a case study. The results indicated that the proposed hybrid approach performed satisfactorily under complex interrelated risk factors. Therefore, this study provides a practical framework to simulate and predict the safety state dynamically in a timely process for MCPs, either ahead of a project theoretically or during a project with real data.

Wavelength-sensitive PIT-like double-layer graphene-based metal–dielectric–metal waveguide

Abstract: A wavelength-sensitive plasmonically induced transparency-like (PIT-like) device consisting of a double-layer graphene-based metal–dielectric–metal (MDM) waveguide is proposed. We initially investigate monolayer graphene sandwiched in the MDM waveguide and utilize the phase-matching equation to explain the reflected resonant wavelength of the transmission spectra. The PIT-like windows in the transmission spectra of double-layer graphene can be achieved by tuning the applied bias voltage on the graphene layer and the distance between the graphene layer and metal substrate. We can obtain the high-performance PIT-like devices with a flexible on–off–on effect. We use a finite element method to do all related simulations.

Image contour detection based on improved level set in complex environment

Abstract: An improved image segmentation model was established to achieve accurate detection of target contours under high noise, low resolution, and uneven illumination environments. The new model is based on the variational level set algorithm, which improves the C–V (Chan and Vese) model and GAC (Geodesic Active Contour) model, fuses the contour and area models to segment the image information, that is, the edge information and region information of the image are fused into the same "energy" functional. According to the geometric characteristics of the curve, GAC model can effectively avoid re parameterization and light insensitivity in the evolution process, and CV model can effectively distinguish the fuzzy boundary of the image by maximizing the gray difference between the target and the background, it has strong anti-noise performance. By solving the steady-state solution of the partial differential equation, the optimal solution of the energy model is solved. New method can improve the calculation accuracy, topological structure adaptability, anti-noise ability, and reduce the light sensitivity effectively. Experiment shows that the new model has good robustness, high real-time performance, and it can effectively improve detection accuracy.