This thesis presents a research effort aimed at developing using construction methods and techniques in army tactical shelter. The beginning step focuses on developing and identifying different activities and work breakdown structure applicable in shelter prototype. The next step focuses on identifying resource allocation. This include allocate resources based on the delivered project as per alternative one and for the second alternative as optimization, resource allocation modified and tried to level and minimize resource peak. In addition, the cost calculated for the whole project as well as for each WBS and activities which consider as alternative one and in the second alternative, cost mitigation applied according to available resources and adjusting predecessors and successors of each activity. In conclusion, two alternatives compared, available outcome presents, and future work suggested for the project team to continue this effort.

The main objective of this work is to give contribution in both additive manufacturing (AM) and tribometry derived from the application and study of materials available with the use of biomimetic designs. Additional contributions are determining what effects treatments for flooring surfaces may have on the dynamic coefficient of friction and the effects of these products on common surfaces. The validity of the proposed methodology for a proof of concept was demonstrated by comparing measured dynamic coefficient of friction for designs using standardized equipment and comparing these values to plantar skin tested using an accepted and standardized testing method that has been extensively researched and validated. Initial biomimetic designs and characteristics unique to each design were researched and compared. Eleven designs were selected to be fabricated, tested, and compared to select the most desirable applications for further investigation. Research into potential treatments commercially available for use was done to determine the efficacy of these products. Prototype sensor designs were selected and fabricated using direct light processing (DLP) technology. Examination of the measured values was done through an analysis of the variances in the response variable and comparisons using Fisher and Tukey pairwise comparison method. Future work recommendations are provided for …

The objective of this research is developing a new method of design for cold-formed steel framed shear wall sheathed by ¾" thick USG structural panel concrete subfloor using a predictive analytical model and comparing the results obtained from the model with those achieved from real testing to verify the analytical model and predicted lateral load-carrying capacity resulted from that. Moreover, investigating the impact of various screw spacings on shear wall design parameter such as ultimate strength, yield strength, elastic stiffness, ductility ratio and amount of energy dissipation is another purpose of this research.

Optical microlasers have been used in different engineering fields and for sensing various applications. They have been used in biomedical fields in applications such as for detecting protein biomarkers for cancer and for measuring biomechanical properties. The goal of this work is to propose a microfluidic-based fabrication method for fabricating optical polymer based microlasers, which has advantages, over current methods, such us the fabrication time, the contained cost, and the reproducibility of the microlaser's size. The microfluidic setup consisted of microfluidic pumps and a flow focusing droplet generator chip made of polydimethylsiloxane (PDMS). Parameters such as the flow rate (Q) and the pressure (P) of both continuous and dispersed phases are taken into account for determining the microlaser's size and a MATLAB imaging tool is used to reduce the microlaser's diameter estimation. In addition, two applications are discussed: i) electric field measurements via resonator doped with Di-Anepps-4 voltage sensitive dye, and ii) strain measurements in a 3D printed bone-like structure to mimic biomedical implantable sensors.