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The analysis of semirigid steel structure connections based on exact theoretical modeling, which is demanding and time consuming if all the nonlinear parameters of the problem are taken into account, can be avoided provided that enough experimental measurements exist and an appropriate predictor can be constructed from them. A supervised learning backpropagation neural network approach is proposed in this paper for the construction of this model free predictor. A number of experimental momentrotation curves for single-angle and single-plate beamto-column connections are used in this paper to train the neural network. The trained network provides us with an estimator for the mechanical behavior of the steel structure connection element. 0 1995 Microcompufers in Civil Engineering. Published by Blackwell Publishers,

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Upgrading the Syrian refugee shelter design serves humanitarian needs, especially since the currently used T-shelters have a life span of 2–4 years, and there are no clear signs of an imminent return of Syrian refugees to their country, even after the end of the civil war. The use of 3D concrete printing can provide a promising method to construct new durable shelters with a long life span and provide better protection against extreme change in the desert climate, privacy, and cultural constraints. This research aims to use multi-criteria decision methods—in particular, the Analytical Hierarchal Process (AHP) method—to select the best 3D concrete printing to construct these shelters. The proposed model takes the following into consideration: the machine’s technical characteristics, building structure characteristics, and economic and environmental aspects. The three basic developed technologies—contour crafting, D-shape, and concrete printing—were used as alternatives in the model. The results show that contour crafting is the best technology for this application, and the inconsistency test and sensitivity analysis indicate an effective and reasonable technology ranking.