In this paper we propose distributed storage algorithms for large-scale wireless sensor networks. Assume a wireless sensor network with n nodes that have limited power, memory, and bandwidth. Each node is capable of both sensing and storing data. Such sensor nodes might disappear from the network due to failures or battery depletion. Hence it is desired to design efficient schemes to collect data from these n nodes. We propose two distributed storage algorithms (DSA's) that utilize network flooding to solve this problem. In the first algorithm, DSA-I, we assume that the total number of sensors is known to each sensor in the network. We show that this algorithm is efficient in terms of the encoding and decoding operations. Furthermore, every node utilizes network flooding to disseminate its data throughout the network using a mixing time of approximately O(n). In the second algorithm, DSA-II, we assume that the total number of nodes is not known to every sensor; hence dissemination of the data does not depend on n. The encoding operations in this case take O(Cµ 2 ), where µ is the mean degree of the network graph and C is a system parameter. We evaluate the performance of the proposed algorithms through analysis and simulation. We show that the performance of the proposed algorithms matches the derived theoretical results.

The aging of civil infrastructure and aerospace structures has led to an increased need to monitor the overall structural health. If growing damage not identified on time, it may has serious consequences, both safety related and economic. However, the complexity of large structures and the difficulty in accessing them makes the use of commonly existing conventional Non Destructive Evaluation (NDE) methods such as visual inspection and instrumental evaluation methods, impractical. An effective alternative in Structural Health Monitoring (SHM) is the use of methods that depend on Vibration-Based Damage Identification (VBDI) techniques. These methods use limited instrumentation to detect the changes in the measured modal characteristics of the structure, that is, its frequencies and mode shapes. These characteristics change with the physical properties of the structure (stiffness, mass and damping matrices) and can be used to help find the location and extent of damage. Optimal matrix update method is one of the VBDI algorithms that depends on finite element modelling (FEM) of the structure and is therefore referred to as model-based damage identification algorithm. The FRF differences method is also one of the VBDI techniques that depends on the directly measured frequency response functions data and is therefore referred to as non model-based or modal-based damage identification algorithm. However, VBDI algorithms still faces a number of challenges that have not been fully resolved. Some of these challenges are highlighted through modal tests designed to provide estimates of damage in a 3D eight-bay free-free frame. Details of tests on a healthy structure as well as on a structure in which predetermined damage has been introduced are presented. A proposed algorithm combining the aforementioned model-based and non-model based methods is introduced to improve the reliability of damage detection. The algorithm is first tested through numerical simulation to predicting damage on the basis of modal test data and the predictions are compared with the known damage.

A numerical study for damage of RC columns under demolition blasting has been carried out and the results were compared with available experimental work. Basic considerations for the finite element method of the LS-DYNA Program are introduced. Equations of state models as well as three constitutive material models (the concrete mass, the reinforcing steel, and the high energy explosive material) are described in detail. In the present work, three Finite Element modeling of steel bars as beam, solid elements or by converting reinforcement quantity into concrete solid elements have been examined through comparison with available experimental work. The influence of different parameters on the blasting damage pattern of RC columns has been investigated. These parameters include steel rebar arrangement, explosive factors and the concrete strength of columns. The results have been presented and discussed.

The advances in using composite materials in different structural application lead to the need of continuous, robust, and structural health monitoring (SHM) systems. One of the most promising techniques for SHM is electromechanical impedance (EMI) technique which depends mainly on the coupling nature of piezoelectric ceramics. Piezoelectric wafer active sensors (PWAS) can be employed as both a well-controlled actuator and sensor at the same time for diagnostic algorithms based on EMI technique. The study presented in this paper interested in EMI technique application to detect damage in composite laminated plates by applying synchronized system of PWAS array operated remotely by exerting harmonic analysis in desired frequency ranges. Frequency ranges are selected upon modal analysis of the healthy tested structure. Harmonic analysis is carried out for different damage scenarios. Extracted electrical charge spectrum data from each PWAS for the previous scenarios can be processed to plot electrical impedance for each case. The modeling process was carried out using a finite element commercial package, ANSYS v.15.0 in which multiphysics-based modeling can be used for such structure made of laminated composite material. The extracted resultant spectrum, for healthy structure, is used as a datum in which it is related to its damaged counterparts through damage identification indices such as root mean square deviation (RMSD), and damage detection index (DDI). These indices were used as indicators for the changes in the modal parameters and hence, yielded reasonable results for both damage quantification and localization purposes.