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Register a new userUsing Genetic Algorithm in Optimum Design of C Section of Cold Formed Thin Walled Column subjected to Axial Force
استخدام الخوارزمية الجينية في التصميم الأمثل لعمود معدني رقيق الجدران خاضع لقوة محورية
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Added by
Tishreen University ورقة بحثية
Publication date
2017
fields
Structural Engineering
and research's language is
العربية
Authors
بادية حيدر( باحث )
Created by
Shamra Editor
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تستخدم منتجات الفولاذ الرقيق على نطاق واسع في صناعة البناء حيث يتم تشكيلها على البارد من صفائح فولاذية ذات سماكات موحدة. تهدف هذه الدراسة إلى تحديد المقطع الأمثل لعمود معدني مصنوع من فولاذ رقيق الجدران و مسحوب على البارد مقطعه C مع شفة معرض لعدة مستويات من القوى المحورية باستخدام الخوارزمية الجينية. توصل البحث إلى أن الخوارزمية الجينية قادرة على حل مسألة التصميم الأمثل للعمود المدروس بكفاءة عالية و دقة. كما توصل إلى أن القيد المتعلق بالتحنيب الفتلي الانعطافي بالإضافة إلى التحنيب الكلي باتجاه x هما القيدان المسيطران في حالة الارتفاعات الكبيرة. توصي الدراسة بإعادة دراسة المسألة بحيث تصبح متعددة الأهداف و ذلك بإضافة تابع هدف جديد إليها وهو التحنيب الكلي بالاتجاهين x,y.
Thin walled Steel products are very much used in the construction industry, where it is cold formed from uniform thickness steel plates. This study aims at determining the optimal section of cold formed thin walled lipped C compressed member under the effect of several levels of axial force using Genetic Algorithm. The research found that the genetic algorithm is able to resolve the issue of the optimal design of studied column with high efficiency, accuracy. Also it found that the torsional flexural buckling constraint and the overall buckling constraint in x-direction are the effective constraints in case of long height. The study recommends restudying the same issue as a multi objective optimization problem by adding additional objective functions which are the overall buckling in x&y directions.
References used
DUBINĂ, D. SI VAYAS,I. ; Cold-formed steel design, Ed. Kleidarithmos, Atena Grecia.2004
(PAUL M. PERNES et.al; Optimized sections for cold formed steel channel profiles under compression and bending according to EN1993-1-3, Acta Technica Napocensis: Civil Engineering & Architecture Vol. 55, No. 3 (2012
LEE, ,J. ; KIM, S. and et.al, Optimum design of cold-formed steel channel beams using micro Genetic Algorithm, Engineering Structures, 27, 2005, 17-24
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Cold formed steel (CFS) has many advantages over other construction materials.
CFS members are lightweight. They weigh up to 30-35% less than their wood
counterparts.. This makes CFS members economical and the same time very easy to erect
and inst
all. They may be shaped (cold-bent) to nearly any open cross section. This allows
for the use of optimization technique’s to find optimal shapes for the members’ cross
sections.
The research aims to show the genetic algorithm's ability in determining the optimum
dimensions cold formed C section. To do so, the optimum design mathematical
formulation was formulated by adding the manufacturing constraints that reflect the
section folding operations in addition the geometrical and structural constraints.
The research found that the genetic algorithm is effective tool in finding the best
solution to this issue, as it showed its ability to deal with asymmetric section through
reaching solutions conform to the basic principles of mechanics of material.
The algorithm is adjustable, so that it can implement the design restrictions which are
compatible with any codes or any manufacturing requirements imposed by modulation
techniques.
The principal objective of this research is an adoption of the Genetic
Algorithm (GA) for studying it firstly, and to stop over the operations which
are introduced from the genetic algorithm.The candidate field for applying
the operations of the g
enetic algorithm is the sound data compression field.
This research uses the operations of the genetic algorithm for the
enhancement of the performance of one of the popular compression method.
Vector Quantization (VQ) method is selected in this work. After studying
this method, new proposed algorithm for mixing the (GA) with this method
was constructed and then the required programs for testing this algorithm
was written. A good enhancement was recorded for the performance of the
(VQ) method when mixed with the (GA). The proposed algorithm was
tested by applying it on some sound data files. Some fidelity measures are
calculated to evaluate the performance of the new proposed algorithm.
In this study, basic methodologies of the GA and the scaling
procedures are summarized, the scaling criteria of real time history
records to satisfy the Syrian design code are discussed. The
traditional time domain scaling procedures and the scali
ng
procedures using GA are utilized to scale a number of the available
real records to match the Syrian design spectra. The resulting time histories of the procedures are investigated and compared in terms of meeting criteria.
Route discovery in infrastructure based network is an important problem. Normally, route selection or route discovery is done based on the shortest path principle. In infrastructure based networks، a number of issues for route discovery need to be ad
dressed as the packet flow are prone to errors making the routing operation failure. Reliability, for example، is an important issue for route discovery. Ensuring Quality of Service (QoS) is important and is to be taken care while forwarding a packet flow. In this paper، a model for route discovery in infrastructure based networks using GA is being proposed. Out of many paths available from the gateway of the network to the final destination, the one is selected which satisfies the desired QoS. Two important QoS parameters، path loss and processing time at the router (Base Station), have been considered. The experimental results for both the QoS parameters reveal the efficacy of the model.
This paper aims to reduce the power losses and to enhance the
voltage profile of the power system while maintaining the loading of the
transmission lines within the allowable limits, through the optimal
placement of the Unified Power Flow Controller (UPFC).
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