Hamid Ghasemi
Phone: (+49)3643-584509
Address: Institute of Structural Mechanics-
Bauhaus Universität Weimar
Marienstraße 15,
99423-Weimar –Germany
Address: Institute of Structural Mechanics-
Bauhaus Universität Weimar
Marienstraße 15,
99423-Weimar –Germany
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Papers by Hamid Ghasemi
density mapping techniques for topology optimization of piezoelectric/flexoelectric materials. The fourth order partial differential
equations (PDEs) of flexoelectricity, which require at least C 1 continuous approximations, are discretized using Non-Uniform
Rational B-spline (NURBS). The point wise density mapping technique with consistent derivatives is directly used in the weak form
of the governing equations. The boundary of the design domain is implicitly represented by a level set function. The accuracy of the
IGA model is confirmed through numerical examples including a cantilever beam under a point load and a truncated pyramid under
compression with different electrical boundary conditions. Finally, we provide numerical examples demonstrating the significant
enhancement in electromechanical coupling coefficient that can be obtained using topology optimization.
in Ceramic Matrix Composite (CMC) under thermal and mechanical loadings. The algorithm
finds the optimal cooling capacity of all channels (which directly minimizes the amount of
coolant needed). In the first step, available uncertainties in the constituent material properties, the
applied mechanical load, the heat flux and the heat convection coefficient are considered. Using
the Reliability Based Design Optimization (RBDO) approach, the probabilistic constraints
ensure the failure due to excessive temperature and deflection will not happen. The deterministic
constraints restrict the capacity of any arbitrary cooling channel between two extreme limits. A
“series system” reliability concept is adopted as a union of mechanical and thermal failure
subsets. Having the results of the first step for CMC with uniformly distributed carbon (C-)
fibers, the algorithm presents the optimal layout for distribution of the C-fibers inside the
ceramic matrix in order to enhance the target reliability of the component. A sequential approach
and B-spline finite elements have overcome the cumbersome computational burden. Numerical
results demonstrate that if the mechanical loading dominates the thermal loading, C-fibers
distribution can play a considerable role towards increasing the reliability of the design.
Fiber Reinforced Composite (FRC) by adopting an efficient gradient based optimization approach. Motivated
by lack of non-heuristic and mesh independent optimization algorithms to obtain the optimum distribution
of short fibers through a design domain, Non-Uniform Rational B-spline (NURBS) basis functions
have been implemented to define continuous and smooth mesh independent fiber distribution function
as well as domain discretization. Thanks to higher order (here quadratic) NURBS basis functions along
with their compact support, a drastic reduction in computational time has been obtained by increasing
mesh size while the accuracy of the model is maintained. Moreover combination of NURBS with sensitivity
based optimization method allows a fast convergence to optimum fiber distribution layout. Minimization
of elastic strain energy and maximization of fundamental frequency have been considered as
objective functions for static and free vibration problems, respectively; to get the maximum fiber exploitation
in the structural element. Nodal volume fraction of fiber was defined as the optimization design
variable while a homogenization approach based on the random orientation of short fibers in the matrix
has been adopted. Some numerical examples related to the structural response under static loading as
well as the free vibration behavior are finally conducted to demonstrate the capability and reliability
of the model.
(PNC) continuum structures, in the framework of the combined geometry and material optimization.
Presented model considers material, structural and modeling uncertainties. The material model
covers uncertainties at different length scales (from nano-, micro-, meso- to macro-scale) via a stochastic
approach. It considers the length, waviness, agglomeration, orientation and dispersion (all as random
variables) of Carbon Nano Tubes (CNTs) within the polymer matrix. To increase the computational efficiency,
the expensive-to-evaluate stochastic multi-scale material model has been surrogated by a kriging
metamodel. This metamodel-based probabilistic optimization has been adopted in order to find the optimum
value of the CNT content as well as the optimum geometry of the component as the objective function
while the implicit finite element based design constraint is approximated by the first order reliability
method. Uncertain input parameters in our model are the CNT waviness, agglomeration, applied load and
FE discretization. Illustrative examples are provided to demonstrate the effectiveness and applicability of
the present approach.
for finding the optimal fiber content and its distribution
in solid composites, considering uncertain design parameters,
is presented. In the first stage, the optimal amount of
fiber in a Fiber Reinforced Composite (FRC) structure with
uniformly distributed fibers is conducted in the framework
of a Reliability Based Design Optimization (RBDO) problem.
In the second stage, the fiber distribution optimization
having the aim to more increase in structural reliability is
performed by defining a fiber distribution function through
a Non-Uniform Rational B-Spline (NURBS) surface. The
output of stage 1(optimal fiber content for homogeneously
mainly the result of excessive shear stresses in the core. Generally, the core made of homogeneous Fiber
Reinforced Polymer (FRP) shows better shear resistance in comparison with that made of pure polymer.
Usually, this enhancement is however somewhat limited. This paper proposes a methodology to decrease
interfacial stresses by presenting the optimal distribution of reinforcing ingredients in the polymeric
matrix. For this purpose, a Non-Uniform Rational B-spline (NURBS) based reinforcement distribution
optimizer is developed. This technique aims at the local stress minimization within any arbitrary zone
of the design domain. In our methodology, optimization and model analysis (calculation of the objective
function and the design constraints) have common data sets. The quadratic NURBS basis functions
smoothly define the reinforcement distribution function as a NURBS surface. The core and face sheets
are modeled as multi-patches and compatibility in the displacement field is enforced by the penalty
method. An adjoint sensitivity method is devised to minimize the objective function within areas of interest
defined over arbitrary regions in the design domain. It is also used for efficient updating of design
variables through optimization iterations. The method is verified by several examples.