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  <title><![CDATA[PhD Defense by Fernando Vasconcelos da Senhora]]></title>
  <body><![CDATA[<p><strong>School of Civil and Environmental Engineering</strong></p><p><strong>Ph.D. Thesis Defense Announcement</strong></p><p>MULTI-SCALE ARCHITECTED MATERIAL STRUCTURAL OPTIMIZATION FOR LIGHTWEIGHT STRUCTURES AND ELASTO-STATIC CLOAKING: FROM DESIGN TO ADDITIVE MANUFACTURING</p><p><strong>By&nbsp;</strong>Fernando Vasconcelos da Senhora</p><p><strong>Advisor:</strong></p><p>Prof. Glaucio H. Paulino (Princeton University)</p><p><strong>Committee Members:</strong>&nbsp; Dr. Emily D. Sanders (ME), Dr. Graeme J. Kennedy (AE), Dr. Aditya Kumar (CEE), Dr. Vikram Deshpande (University of Cambridge)</p><p><strong>Date and Time:&nbsp;</strong>&nbsp;June, 27th, 2024.&nbsp; 10:00 am - EDT</p><p><strong>Location:</strong>&nbsp;Mason Building, Room 5134 /&nbsp;<a href="https://gatech.zoom.us/j/95365406015">https://gatech.zoom.us/j/95365406015</a></p><p><strong>ABSTRACT</strong><br>The ever-growing demand for high-performance structures and materials has<br>pushed traditional design to its limits. The challenges that humanity will face in the<br>coming centuries in space exploration, biomedicine, and resilient infrastructure<br>necessitate the development of new structures and materials that surpass our<br>current capabilities. We propose a multi-scale, multi-material structural optimization<br>framework featuring locally-varying architected material properties, offering a<br>promising avenue to address the structural challenges of the future. This research<br>brings structural optimization and architected materials closer to real-life engineering applications by addressing theoretical, computational, and<br>manufacturing challenges in the field. We have developed architected material<br>models with versatile and enhanced mechanical properties while studying the effect<br>of disorder on their microstructure. Concurrently, we have expanded structural<br>optimization techniques to accommodate a diverse set of locally-varying<br>architected materials and design requirements during the optimization for<br>applications such as extremely light structures with high strength-to-weight ratios<br>and elasto-static cloaking. To improve computational efficiency, we have<br>incorporated a machine learning-enhanced framework that achieves optimized<br>structures at a fraction of the cost of traditional techniques. Simultaneously, we<br>have advanced manufacturing capabilities to ensure the feasibility of the multi-scale<br>micro-architecture embedded structures by integrating digital light processing<br>additive manufacturing techniques within the architected material setting to<br>fabricate the optimized results. Finally, the manufactured parts undergo mechanical<br>testing with 3D Digital Image Correlation to evaluate the developed designs. The<br>proposed engineering framework takes into account all stages of production, from<br>design to manufacturing. The development of lightweight, high-strength materials<br>and structures with tailored properties can lead to significant improvements in<br>efficiency, performance, and sustainability in various applications, with the potential<br>to impact a wide range of industries, from aerospace to biomedical.</p>]]></body>
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