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CATEGORIES:Engineering Department Bio- and Micromechanics Sem
inars
SUMMARY:On the length scale\, robustness and manufacturabi
lity in topology optimization - Dr Boyan Stefanov
Lazarov\, School of Mechanical\, Aerospace and Ci
vil Engineering\, University of Manchester
DTSTART;TZID=Europe/London:20180518T140000
DTEND;TZID=Europe/London:20180518T150000
UID:TALK105199AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/105199
DESCRIPTION:Topology optimization has gained the status of bei
ng the preferred optimization tool in the mechanic
al\, automotive\, and aerospace industries. It has
undergone tremendous development since its introd
uction in 1988\, and nowadays it has spread to man
y other disciplines such as acoustics\, optics\, a
nd material design. The basic idea is to distribut
e material in a predefined domain by minimizing a
selected objective function and fulfilling a set o
f constraints. The procedure consists of repeated
system analyses\, gradient evaluation steps by adj
oint sensitivity analysis\, and design updates bas
ed on mathematical programming methods. The existe
nce of a solution is ensured by regularization tec
hniques which result in intermediate density mater
ial regions. Manufacturing of the final optimized
design requires post-processing. However\, any ame
ndments can nullify the effect of the optimization
. Therefore\, this talk aims to present recent dev
elopments in obtaining black and white manufactura
ble designs with clearly defined length scale. The
focus is on the mathematical modeling of the mate
rial density\, its link to micro- and nano- scale
production techniques\, and on the introduction of
uncertainties in the optimization. The model resu
lts in manufacturable black and white designs with
a robust performance.\n\nThe result of the topolo
gy optimization procedure is a bitmap image of the
design. The ability of the method to modify every
pixel/voxel results in design freedom unavailable
with any other alternative approach. However\, th
is freedom requires the computational power of lar
ge parallel machines. Incorporating an uncertainty
model in the optimization and the high contrast b
etween the material phases further increase the co
mputational cost. Hence\, methods for reducing the
computational complexity and handling the high ma
terial contrast will be presented and discussed as
well. The development will be demonstrated in the
design of compliant mechanisms\, heat sinks\, mat
erial microstructures for additive manufacturing\,
photonic devices\, and fluid flow problems.\n
LOCATION:Oatley Seminar Room\, Department of Engineering
CONTACT:Hilde Hambro
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