Air-inflated fabric arch structure, Dynamic deployment behavior, Peak pressure, Control volume method, Artificial neural networks, Technology

Air-inflated fabric arch structure has obvious advantage of being light-weight, able to accommodate large spans, low cost, easy mobilization and reusable. It has been widely applied to military and aerospace structures. However, there are few studies on its dynamic deployment behavior and self-erection feasibility during the construction phase, which restricts the breakthrough of its span and its development in civil buildings. In this study, the effects of considering heat exchange with the environment and the traditional adiabatic assumption of Control Volume method (CV Method)on deployment pressure were analysed and compared. Comparing the simulation with the experimental data, the feasibility of the ABAQUS fluid cavity in simulating the dynamic deployment behavior of Air-inflated fabric arch structure was verified. The traditional Control Volume Method were modified by including a heat exchange, and the feasibility of this method was verified. Next, the modified Control Volume method was employed to evaluate the factors influencing the deployment pressure of air-inflated fabric arch structure. Research was conducted on influence of deployment time, span to height ratio, and arch length to diameter. The reasonable design parameters for span to height ratio and arch length to diameter ratio of air-inflated fabric arch structure are given. A fully connected neural network with two layers was constructed to predict the peak pressure. The accuracy of this method was verified by the results. Thus, this study serves as a reference for deployment behavior in engineering applications.