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Pavement Quality Index Rating Strategy Using Fracture Energy Analysis for Implementing Smart Road Infrastructure.

ABSTRACT: Developing a responsive pavement-management infrastructure system is of paramount importance, accentuated by the quest for sustainability through adoption of the Road Traffic Management System. Technological advances have been witnessed in developed countries concerning the development of smart, sustainable transportation infrastructure. However, the same cannot be said of developing countries. In this study, the development of a pavement management system at network level was examined to contribute towards a framework for evaluating a Pavement Quality Index and service life capacity. Environmental surface response models in the form of temperature and moisture variations within the pavement were applied, using sensor devices connected to a data cloud system to carry out mathematical analysis using a distinctive mesh analysis deformation model. The results indicated variation in the Resilient Modulus of the pavement, with increasing moisture content. Increase in moisture propagation increased saturation of the unbound granular base which reduced the elastic modulus of the sub-base and base layer and reduced the strength of the pavement, resulting in bottom-up cracks and cracking failure. The horizontal deformation reduced, indicating that the material was experiencing work hardening and further stress would not result in significant damage. Increasing temperature gradient resulted in reduced stiffness of the asphalt layer. In tropical regions, this can result in rutting failure which, over time, results in top-down cracks and potholes, coupled with increasing moisture content.

SUBMITTER: Abejide S

PROVIDER: S-EPMC8235173 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Complex processes meet and need Industry 4.0 capabilities. Shorter product cycles, flexible production needs, and direct assessment of product quality attributes and raw material attributes call for an increased need of new process analytical technologies (PAT) concepts. While individual PAT tools may be available since decades, we need holistic concepts to fulfill above industrial needs. In this series of two contributions, we want to present a combined view on the future of PAT (process analytical technology), which is projected in smart labs (Part 1) and smart sensors (Part 2). Part 2 of this feature article series describes the future functionality as well as the ingredients of a smart sensor aiming to eventually fuel full PAT functionality. The smart sensor consists of (i) chemical and process information in the physical twin by smart field devices, by measuring multiple components, and is fully connected in the IIoT 4.0 environment. In addition, (ii) it includes process intelligence in the digital twin, as to being able to generate knowledge from multi-sensor and multi-dimensional data. The cyber-physical system (CPS) combines both elements mentioned above and allows the smart sensor to be self-calibrating and self-optimizing. It maintains its operation autonomously. Furthermore, it allows-as central PAT enabler-a flexible but also target-oriented predictive control strategy and efficient process development and can compensate variations of the process and raw material attributes. Future cyber-physical production systems-like smart sensors-consist of the fusion of two main pillars, the physical and the digital twins. We discuss the individual elements of both pillars, such as connectivity, and chemical analytics on the one hand as well as hybrid models and knowledge workflows on the other. Finally, we discuss its integration needs in a CPS in order to allow its versatile deployment in efficient process development and advanced optimum predictive process control.

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Pavement Quality Index Rating Strategy Using Fracture Energy Analysis for Implementing Smart Road Infrastructure.

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