Hirad Assimi

Hirad Assimi
University of Adelaide · School of Computer Science

PhD Candidate

About

18
Publications
24,141
Reads
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170
Citations
Additional affiliations
July 2018 - December 2018
University of Adelaide
Position
  • Research Assistant
Description
  • Evolutionary Computation (4095_4195_7093 Combined): History of evolutionary computation; major areas: genetic algorithms, evolution strategies, evolution programming, genetic programming, classifier systems; constraint handling; multi-objective cases; etc
April 2015 - June 2016
University of Guilan
Position
  • Research Assistant
Description
  • -Numerical methods in engineering -Mechanical Vibrations
Education
July 2018 - July 2021
University of Adelaide
Field of study
  • Computer Science
October 2014 - September 2017
University of Guilan
Field of study
  • Mechanical Engineering
October 2009 - September 2014
University of Guilan
Field of study
  • Mechanical Engineering

Publications

Publications (18)
Preprint
Full-text available
Stockpiles are essential in the mining value chain, assisting in maximising value and production. Quality control of taken minerals from the stockpiles is a major concern for stockpile managers where failure to meet some requirements can lead to losing money. This problem was recently investigated using a single reclaimer, and basic assumptions. Th...
Preprint
Full-text available
Topology optimisation of trusses can be formulated as a combinatorial and multi-modal problem in which locating distinct optimal designs allows practitioners to choose the best design based on their preferences. Bilevel optimisation has been successfully applied to truss optimisation to consider topology and sizing in upper and lower levels, respec...
Article
Full-text available
Optimal design of controllers without considering uncertainty in the plant dynamics can induce feedback instabilities and lead to obtaining infeasible controllers in practice. This paper presents a multi-objective evolutionary algorithm integrated with Monte Carlo simulations (MCS) to perform the optimal stochastic design of robust controllers for...
Preprint
Full-text available
Real-world combinatorial optimization problems are often stochastic and dynamic. Therefore, it is essential to make optimal and reliable decisions with a holistic approach. In this paper, we consider the dynamic chance-constrained knapsack problem where the weight of each item is stochastic, the capacity constraint changes dynamically over time, an...
Chapter
The development of modern engineering systems has introduced increasing levels of complexity and uncertainty over time. Combined with the design philosophy of engineering itself, this has given rise to many studies addressing the simple or multi-objective optimization problems present in these complex systems. Although conventional approaches can b...
Article
Full-text available
Most real-world engineering problems deal with multiple conflicting objectives simultaneously. In order to address this issue in truss optimization, this paper presents a multi-objective genetic programming approach for sizing and topology optimization of trusses. It aims to find the optimal cross-sectional areas and connectivities between the node...
Conference Paper
Full-text available
Evolutionary algorithms have been widely used for a range of stochastic optimization problems. In most studies, the goal is to optimize the expected quality of the solution. Motivated by real-world problems where constraint violations have extremely disruptive effects, we consider a variant of the knapsack problem where the profit is maximized unde...
Preprint
Full-text available
Evolutionary algorithms have been widely used for a range of stochastic optimization problems. In most studies, the goal is to optimize the expected quality of the solution. Motivated by real-world problems where constraint violations have extremely disruptive effects, we consider a variant of the knapsack problem where the profit is maximized unde...
Article
Full-text available
Optimization without considering uncertainty of system parameters can lead to potentially high-risk solutions. In order to take into account the effect of those uncertain parameters of the system, multi-objective reliability-based robust design optimization (RBRDO) using the sensitivity-assisted Monte Carlo Simulation method is developed in this st...
Article
Truss optimization aims to provide the lightest truss to gain the maximum benefit out of available resources. Truss optimization may subject to static and dynamic constraints. Static constraints include structural kinematic stability, maximum allowable stress in truss members, maximum allowable deflection in the truss nodes and critical buckling lo...
Article
This paper presents a genetic programming approach for simultaneous optimization of sizing and topology of truss structures. It aims to find the optimal cross-sectional areas and connectivities of the joints to achieve minimum weight in the search space. The structural optimization problem is subjected to kinematic stability, maximum allowable stre...
Article
Full-text available
Implementing spatial structures is common in real-world structures such as bridges, space structures, and ships. This topic has attracted researchers to propose more efficient and pristine methods to obtain more robust and cheaper solutions for spatial structure optimization problems. This paper presents a hybrid approach for simultaneous optimizat...
Article
Full-text available
Selective laser melting (SLM) is a popular additive manufacturing process that creates 3D metal parts by fusing fine metal powders together. Modeling and optimization of SLM prototypes has been extensively studied deterministically in the literature considering different properties such as bead width, compressive strength, tensile strength etc. How...
Conference Paper
Full-text available
There are much research effort in the literature using genetic programming as an efficient tool for design of controllers for industrial systems. In this paper, multi-objective uniform-diversity genetic programming (MUGP) is used for automated synthesis of both structure and parameter tuning of optimal controllers as a many-objective optimization p...

Questions

Questions (10)
Question
I tried to model a simply supported bridge, but I can't reproduce the results in the literature. The description of the truss is as follows,
"To demonstrate the flexibility of the approach, a simply supported bridge is optimized for its weight minimization with several cases of frequency constraints. Members on the lower chord are represented by beam elements with fixed rectangular cross sections B = 8 cm and H = 5 cm. Others are modeled as bar elements with initial sectional areas A = 1 cm2 . Young’s modulus is E = 2.1 × 1011 Pa, and the material density is ρ = 7800 kg/m3 for all elements. The initial configuration of the structure is shown in Fig. 6. A nonstructural mass m = 10 kg is attached at each of the nodes on the lower chord. The natural frequencies of the truss are about 20, 40 and 60" with some variations in the third or fourth floating point.
The schematic of the truss is depicted is attached.
--
First I modeled all elements as bar elements and it resulted in natural frequencies as "20.35 40.00 60.27". I believe that It came to a correct K matrix but the M matrix somehow was wrong. I surveyed the literature and I found out that the lower chord elements should be beam elements and I modified my model. But it still gives me very wrong Frequencies that are mentioned at the end. I also supposed that Iz in the beam element command of OpenSEES should be (bh/12)*(b^2+h^2) and consistent mass matrix as (rho*cross-section). I will appreciate if you help me to modify the model to repeat the literature results.
My tcl code is as follows and also attached:
model BasicBuilder -ndm 2 -ndf 3
node 1 0.0000 0.0000
node 2 1.0000 0.0000
node 3 1.0000 0.9392
node 4 2.0000 0.0000
node 5 2.0000 1.3270
node 6 3.0000 0.0000
node 7 3.0000 1.5063
node 8 4.0000 0.0000
node 9 4.0000 1.6086
node 10 5.0000 0.0000
node 11 5.0000 1.6679
node 12 6.0000 0.0000
node 13 6.0000 1.6086
node 14 7.0000 0.0000
node 15 7.0000 1.5063
node 16 8.0000 0.0000
node 17 8.0000 1.3270
node 18 9.0000 0.0000
node 19 9.0000 0.9392
node 20 10.0000 0.0000
fix 1 1 1 1
fix 20 1 1 1
uniaxialMaterial Elastic 1 2.1e+11
mass 1 10 10 0
mass 2 10 10 0
mass 4 10 10 0
mass 6 10 10 0
mass 8 10 10 0
mass 10 10 10 0
mass 12 10 10 0
mass 14 10 10 0
mass 16 10 10 0
mass 18 10 10 0
mass 20 10 10 0
geomTransf Linear 1
element elasticBeamColumn 1 1 2 0.0040000000 2.1e+11 2.9666e-6 1 -mass 31.20 -cmass 1
element Truss 2 1 3 0.0002983800 1 -rho 2.33 -cMass 1
element Truss 3 2 3 0.0001109800 1 -rho 0.87 -cMass 1
element elasticBeamColumn 4 2 4 0.0040000000 2.1e+11 2.9666e-6 1 -mass 31.20 -cmass 1
element Truss 5 3 4 0.0001009100 1 -rho 0.79 -cMass 1
element Truss 6 3 5 0.0002595500 1 -rho 2.02 -cMass 1
element Truss 7 4 5 0.0001261000 1 -rho 0.98 -cMass 1
element elasticBeamColumn 8 4 6 0.0040000000 2.1e+11 2.9666e-6 1 -mass 31.20 -cmass 1
element Truss 9 5 6 0.0001197500 1 -rho 0.93 -cMass 1
element Truss 10 5 7 0.0002426400 1 -rho 1.89 -cMass 1
element Truss 11 6 7 0.0001358800 1 -rho 1.06 -cMass 1
element elasticBeamColumn 12 6 8 0.0040000000 2.1e+11 2.9666e-6 1 -mass 31.20 -cmass 1
element Truss 13 7 8 0.0001477100 1 -rho 1.15 -cMass 1
element Truss 14 7 9 0.0002564800 1 -rho 2.00 -cMass 1
element Truss 15 8 9 0.0001129500 1 -rho 0.88 -cMass 1
element elasticBeamColumn 16 8 10 0.0040000000 2.1e+11 2.9666e-6 1 -mass 31.20 -cmass 1
element Truss 17 9 10 0.0001319900 1 -rho 1.03 -cMass 1
element Truss 18 9 11 0.0002921700 1 -rho 2.28 -cMass 1
element Truss 19 10 11 0.0001000400 1 -rho 0.78 -cMass 1
element elasticBeamColumn 20 10 12 0.0040000000 2.1e+11 2.9666e-6 1 -mass 31.20 -cmass 1
element Truss 21 10 13 0.0001319900 1 -rho 1.03 -cMass 1
element Truss 22 11 13 0.0002921700 1 -rho 2.28 -cMass 1
element Truss 23 12 13 0.0001129500 1 -rho 0.88 -cMass 1
element elasticBeamColumn 24 12 14 0.0040000000 2.1e+11 2.9666e-6 1 -mass 31.20 -cmass 1
element Truss 25 12 15 0.0001477100 1 -rho 1.15 -cMass 1
element Truss 26 13 15 0.0002564800 1 -rho 2.00 -cMass 1
element Truss 27 14 15 0.0001358800 1 -rho 1.06 -cMass 1
element elasticBeamColumn 28 14 16 0.0040000000 2.1e+11 2.9666e-6 1 -mass 31.20 -cmass 1
element Truss 29 14 17 0.0001197500 1 -rho 0.93 -cMass 1
element Truss 30 15 17 0.0002426400 1 -rho 1.89 -cMass 1
element Truss 31 16 17 0.0001261000 1 -rho 0.98 -cMass 1
element elasticBeamColumn 32 16 18 0.0040000000 2.1e+11 2.9666e-6 1 -mass 31.20 -cmass 1
element Truss 33 16 19 0.0001009100 1 -rho 0.79 -cMass 1
element Truss 34 17 19 0.0002595500 1 -rho 2.02 -cMass 1
element Truss 35 18 19 0.0001109800 1 -rho 0.87 -cMass 1
element elasticBeamColumn 36 18 20 0.0040000000 2.1e+11 2.9666e-6 1 -mass 31.20 -cmass 1
element Truss 37 19 20 0.0002983800 1 -rho 2.33 -cMass 1
puts "eigen values: [eigen -fullGenLapack 3]"
Result of the code:
FullGenEigenSolver::solve() - the eigenvalue 9 is complex with magnitude 2.41214e+15
FullGenEigenSolver::solve() - the eigenvalue 10 is complex with magnitude 2.41214e+15
FullGenEigenSolver::solve() - the eigenvalue 13 is complex with magnitude 1.90904e+08
FullGenEigenSolver::solve() - the eigenvalue 14 is complex with magnitude 1.90904e+08
FullGenEigenSolver::solve() - the eigenvalue 16 is complex with magnitude 9.83875e+07
FullGenEigenSolver::solve() - the eigenvalue 17 is complex with magnitude 9.83875e+07
FullGenEigenSolver::solve() - the eigenvalue 20 is complex with magnitude 8.9533e+06
FullGenEigenSolver::solve() - the eigenvalue 21 is complex with magnitude 8.9533e+06
FullGenEigenSolver::solve() - the eigenvalue 25 is complex with magnitude 842310
FullGenEigenSolver::solve() - the eigenvalue 26 is complex with magnitude 842310
eigen values: -3.007715e+15 -2.412142e+15 -2.412142e+15
Question
I want to obtain the natural frequencies of a benchmark truss which is famously known as the ten-bar planar truss. It consists of 10 truss members and 6 nodes. Two nodes are its supports and other four nodes are free nodes. The modulus elasticity is 6.89e10 and the added non-structural mass to the free nodes is 454 kg. Fig 1 shows the schematic of the truss and the obtained cross-section areas of this problem is listed in Fig 2. This figure also lists the natural frequencies obtained by different trusses. I tried to simulate the truss obtained by MC-TLBO which is listed in the last column but I faced a problem:
I didn’t reach the natural frequency in the literature and my model resulted in omega^2=1.575894e+04 and f=(omega/(2*pi))=19.98 Hz. It’s notable that I added some negligible massed on the other degree of freedom of the nodes according to OpenSEES official examples to obtain other natural frequencies.
The figures are referred from the [1] and The Tcl model is attached by myself (The units are in SI).
Any comment will be appreciated and thanks in advance for your time.
Refs.
[1] Farshchin, M., C. V. Camp, and M. Maniat. "Multi-class teaching–learning-based optimization for truss design with frequency constraints." Engineering Structures 106 (2016): 355-369.
Question
I'm trying to model a 25 bar truss benchmark with elastic elements but the loading is somehow weird to me. Can you tell me what kind of loading it's ? Those multiple force vectors on nodes 1 and 2 are applied simultaneously or else? Why the resultant forces can not be considered? The schematic of the 25 bar truss and the loading conditions are attached.
Any comment would be appreciated. Thx in advance
sources of attached materials:
Cheng, Min-Yuan, Doddy Prayogo, Yu-Wei Wu, and Martin Marcellinus Lukito. "A Hybrid Harmony Search algorithm for discrete sizing optimization of truss structure." Automation in Construction 69 (2016): 21-33.
Question
I want to model this 25 bar truss benchmark. the schematic of the benchmark, the loading conditions and my partial tcl file are attached.
How can I define this kind of loading in my code? Because there are multiple loading on nodes 1 and 2.
is it possible with multiple pattern plains? if yes how can i link them to analyze simultaneously.
I tried to model it as it's shown in the tcl file, but it doesn't work, since the  maximum deflection in the nodes should be lower than 0.35 inch.
Any help would be appreciated, thanks in advance.
Question
The features which I'm looking for are powerful library of elements and materials like Opensees, having various solvers, handling static/dynamic loading/analysis and capability of running in command-line platform (console) to make it easy to link.

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