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BackgroundRoutine vascular surgery operations involve stitching of disconnected human arteries with themselves or with artificial grafts (arterial anastomosis). This study aims to extend current knowledge and provide better-substantiated understanding of the mechanics of end-to-end anastomosis through the development of an analytical model governing the dynamic behavior of the anastomotic region of two initially separated arteries.MethodsThe formulation accounts for the arterial axial-circumferential deformation coupling and suture-artery interaction. The proposed model captures the effects of the most important parameters, including the geometric and mechanical properties of artery and sutures, number of sutures, loading characteristics, longitudinal residual stresses, and suture pre-tensioning.ResultsClosed-form expressions are derived for the system response in terms of arterial radial displacement, anastomotic gap, suture tensile force, and embedding stress due to suture-artery contact interaction. Explicit objective functionalities are established to prevent failure at the anastomotic interface.ConclusionsThe mathematical formulation reveals useful interrelations among the problem parameters, thus making the proposed model a valuable tool for the optimal selection of materials and improved functionality of the sutures. By virtue of their generality and directness of application, the findings of this study can ultimately form the basis for the development of vascular anastomosis guidelines pertaining to the prevention of post-surgery implications.

This work presents a soft-sensor approach for estimating critical mechanical properties of sandcrete materials. Feed-forward (FF) artificial neural network (ANN) models are employed for building soft-sensors able to predict the 28-day compressive strength and the modulus of elasticity of sandcrete materials. To this end, a new normalization technique for the pre-processing of data is proposed. The comparison of the derived results with the available experimental data demonstrates the capability of FF ANNs to predict with pinpoint accuracy the mechanical properties of sandcrete materials. Furthermore, the proposed normalization technique has been proven effective and robust compared to other normalization techniques available in the literature.

SUMMARYThis paper presents ÿndings from a comprehensive analytical and experimental study on the upliftrestraining XY-FP sliding isolation system. To investigate the e ectiveness of the XY-FP isolator and provide a rational basis for evaluating the e cacy of the developed mathematical model, an extensive experimental program was conducted on the earthquake simulator at the University at Bu alo. The experimental program involved a slender, ÿve-storey, scale-model frame seismically isolated with four XY-FP isolators subjected to simulations of historical horizontal and vertical ground motions. The experimental response demonstrates the validity of the concept and provides evidence for the e ectiveness of the XY-FP isolator in preventing uplift. A comprehensive analytical model capable of emulating the mechanical behaviour of the XY-FP isolator is developed and implemented in program 3D-BASIS-ME. The newly enhanced program is used to predict the dynamic response of the seismically-isolated model structure. Comparison of analytical predictions with experimental results attests to the e cacy of the analytical model for simulating the response of the XY-FP isolator. With its appealing conceptual simplicity and its proven e ectiveness, the new uplift-restraining isolator has the potential to facilitate the application of seismic isolation even under the most extreme of conditions, including but not limited to near-fault strong ground motions and uplift-prone structural systems.