Design and optimization of roof trusses using morphological indicators

Pyl, Lincy; Sitters, Cox; Wilde, W. P. De

doi:10.1016/j.advengsoft.2013.04.021

Cited by 10 publications

(10 citation statements)

References 21 publications

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“…The numerical simulation methods are considered to be the most convenient and important means used in modern computational mechanics. These methods become more efficient when creating and employing an original calculation algorithm for a specific structure to be designed [5][6][7][8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Investigation of mechanical state of spatial roof from steel trusses on asymmetric building

Samofalov

Žiūkas

2015

mech

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Section: Introductionmentioning

confidence: 99%

Investigation of mechanical state of spatial roof from steel trusses on asymmetric building

Samofalov

Žiūkas

2015

mech

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“…where K is buckling constant (K = 4) and E is the modulus of elasticity (E = 10, 000ksi) and L i is the length of the element. Following the figure, a downward load of F = 20 kips is applied on nodes (1), (2), (4), (6), and (8). The members are divided into four groups, indicated by a bar, as following: with the minimum cross-section area of 0.1 in 2 for each member.…”

Section: -Bar Trussmentioning

confidence: 99%

Constrained mean‐variance mapping optimization for truss optimization problems

Aslani

Ghasemi

Gandomi

2017

Structural Design Tall Build

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Summary Truss optimization is a complex structural problem that involves geometric and mechanical constraints. In the present study, constrained mean‐variance mapping optimization (MVMO) algorithms have been introduced for solving truss optimization problems. Single‐solution and population‐based variants of MVMO are coupled with an adaptive exterior penalty scheme to handle geometric and mechanical constraints. These tools are explained and tuned for weight minimization of trusses with 10 to 200 members and up to 1,200 nonlinear constraints. The results are compared with those obtained from the literature and classical genetic algorithm. The results show that a MVMO algorithm has a rapid rate of convergence and its final solution can obviously outperform those of other algorithms described in the literature. The observed results suggest that a constrained MVMO is an attractive tool for engineering‐based optimization, particularly for computationally expensive problems in which the rate of convergence and global convergence are important.

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“…[20][21][22][23][24][25][26] A collection of tools has been developed within these unified systems or as stand-alone pieces of software that generate and swiftly analyze designs during conceptual design phase. The capabilities of these tools have included algorithms that make design decisions based upon previous experiences, 27,28 automatic mesh generation for the design of concepts, 29 graphs that quickly present pertinent information based upon user generated concepts, 30 and structural analysis of generated concepts. 31 This has included quickly analyzing designs for characteristics such as lifetime, 32,33 reliability, 34 complexity, 35 and cost.…”

Section: B Engineering Design Workflowsmentioning

confidence: 99%

Developing an Integrated Computational Environment for the Detailed Design of a Mixing Impeller

Sloan

Suram

Bryden

2014

52nd Aerospace Sciences Meeting

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Digital manufacturing significantly reduces the expense and time required to produce custom products. Utilizing this technology, a customized product can be quickly manufactured. But the timescale and expense of the engineering design workflows used to develop these customized products have not been adapted from the workflows used in mass production due to the development of high fidelity models. But with digital manufacturing the economies of scale are eliminated such that producing many unique designs or many of the same designs result in the same manufacturing cost. Developing a design workflow that utilizes the developed and validated high fidelity models of the already produced design can reduce the amount of time and expense developing a slightly varied customized design. Reduced order modeling enables this reuse and magnification of existing high fidelity models by creating a computationally inexpensive representation of a model from high fidelity data. This thesis explores the integration of reduced order modeling and detailed analysis into the engineering design workflow developing a customized design using digital manufacturing. Specifically detailed analysis is coupled with proper orthogonal decomposition to enable the exploration of the design space while simultaneously shaping the model representing the design. This revised workflow is examined using the design of a laboratory scale overhead mixing impeller. The case study presented here is compared with the design of the Kar Dynamic Mixer developed by the Dow Chemical Company. The result of which is a customized design for a refined set of operating conditions with improved performance. Digital manufacturing significantly reduces the expense and time required to produce custom products. Utilizing this technology, a customized product can be quickly manufactured. But the timescale and expense of the engineering design workflows used to develop these customized products have not been adapted from the workflows used in mass production due to the development of high fidelity models. But with digital manufacturing the economies of scale are eliminated such that producing many unique designs or many of the same designs result in the same manufacturing cost. Developing a design workflow that utilizes the developed and validated high fidelity models of the already produced design can reduce the amount of time and expense developing a slightly varied customized design. Reduced order modeling enables this reuse and magnification of existing high fidelity models by creating a computationally inexpensive representation of a model from high fidelity data. This thesis explores the integration of reduced order modeling and detailed analysis into the engineering design workflow developing a customized design using digital manufacturing. Specifically detailed analysis is coupled with proper orthogonal decomposition to enable the exploration of the design space while simultaneously shaping the model representing the design. This revised workflow is examined ...

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Design and optimization of roof trusses using morphological indicators

Cited by 10 publications

References 21 publications

Investigation of mechanical state of spatial roof from steel trusses on asymmetric building

Investigation of mechanical state of spatial roof from steel trusses on asymmetric building

Constrained mean‐variance mapping optimization for truss optimization problems

Developing an Integrated Computational Environment for the Detailed Design of a Mixing Impeller

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