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SUMMARY:On the length scale\, robustness and manufacturability in topology
  optimization -  Dr Boyan Stefanov Lazarov\, School of Mechanical\, Aerosp
 ace and Civil Engineering\, University of Manchester
DTSTART:20180518T130000Z
DTEND:20180518T140000Z
UID:TALK105199@talks.cam.ac.uk
CONTACT:Hilde Hambro
DESCRIPTION:Topology optimization has gained the status of being the prefe
 rred optimization tool in the mechanical\, automotive\, and aerospace indu
 stries. It has undergone tremendous development since its introduction in 
 1988\, and nowadays it has spread to many other disciplines such as acoust
 ics\, optics\, and material design. The basic idea is to distribute materi
 al in a predefined domain by minimizing a selected objective function and 
 fulfilling a set of constraints. The procedure consists of repeated system
  analyses\, gradient evaluation steps by adjoint sensitivity analysis\, an
 d design updates based on mathematical programming methods. The existence 
 of a solution is ensured by regularization techniques which result in inte
 rmediate density material regions. Manufacturing of the final optimized de
 sign requires post-processing. However\, any amendments can nullify the ef
 fect of the optimization. Therefore\, this talk aims to present recent dev
 elopments in obtaining black and white manufacturable designs with clearly
  defined length scale. The focus is on the mathematical modeling of the ma
 terial density\, its link to micro- and nano- scale production techniques\
 , and on the introduction of uncertainties in the optimization. The model 
 results in manufacturable black and white designs with a robust performanc
 e.\n\nThe result of the topology optimization procedure is a bitmap image 
 of the design. The ability of the method to modify every pixel/voxel resul
 ts in design freedom unavailable with any other alternative approach. Howe
 ver\, this freedom requires the computational power of large parallel mach
 ines. Incorporating an uncertainty model in the optimization and the high 
 contrast between the material phases further increase the computational co
 st. Hence\, methods for reducing the computational complexity and handling
  the high material contrast will be presented and discussed as well. The d
 evelopment will be demonstrated in the design of compliant mechanisms\, he
 at sinks\, material microstructures for additive manufacturing\, photonic 
 devices\, and fluid flow problems.\n
LOCATION:Oatley Seminar Room\, Department of Engineering
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