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Open AccessJournal ArticleDOI

Cost-safety optimization of steel-concrete composite beams using standardized formulation

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TLDR
A comparison study was conducted to investigate the performance of the proposed method against Social Harmony Search, Ant Colony optimization (ACO), and Improved Ant Colony Optimization (IACO) methods and the results confirmed the higher accuracy of the suggested method than SHS, ACO and IACO methods.
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This article is published in Engineering Science and Technology, an International Journal.The article was published on 2019-04-01 and is currently open access. It has received 14 citations till now.

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Effect of porosity on predicting compressive and flexural strength of cement mortar containing micro and nano-silica by multi-objective ANN modeling

TL;DR: In this article, the effect of various porosity values on the compressive and flexural strength of cement mortar hardened specimens containing micro silica and nano silica (Ns) in the two phases of experiment and the prediction modeling is described.
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Electrochemical and statistical analyses of the combined effect of air-entraining admixture and micro-silica on corrosion of reinforced concrete

TL;DR: In this paper, the combined effect of air-entraining admixture (AEA) and micro-silica (MS) on the structure of cement mortar to improve the corrosion behavior of the resulting reinforced concrete was clarified.
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Structural response of ferrocement panels incorporating lightweight expanded clay and perlite aggregates: Experimental, theoretical and statistical analysis

TL;DR: In this paper, structural response of lightweight ferrocement panels (FPs) as low cost, durable, thin engineering elements was evaluated. And the results indicated that the mean values of Fcr and Fu were higher at the FPs incorporating leca and perlite, respectively.
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Hybrid artificial neural network with biogeography-based optimization to assess the role of cement fineness on ecological footprint and mechanical properties of cement mortar expose to freezing/thawing

TL;DR: In this article, a hybrid artificial neural network (ANN) with biogeography-based optimization (BBO) model was developed to predict the mechanical properties of cementitious materials under freezing and thawing conditions.
References
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Sensitivity Analysis as an Ingredient of Modeling

TL;DR: In this article, the authors explore the tasks where sensitivity analysis can be useful and try to assess the relevance of SA within the modeling process, and suggest that SA could considerably assist in the use of models, by providing objective criteria of judgement for different phases of the model-building process: model identification and discrimination; model calibration; model corroboration.
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Multi-material topology optimization using ordered SIMP interpolation

TL;DR: In this article, an ordered multi-material SIMP interpolation method is proposed to solve multilayer topology optimization problems without introducing any new variables, where power functions with scaling and translation coefficients are introduced to interpolate the elastic modulus and cost properties for multiple materials with respect to the normalized density variables.
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Discrete cost optimization of composite floors using a floating-point genetic algorithm

TL;DR: Based on a comparison with example designs presented in the literature it is concluded that a formal cost optimization can result in substantial cost savings.
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ANN prediction of cement mortar compressive strength, influence of cement strength class

TL;DR: In this article, an artificial neural network (ANN) study is presented to predict the compressive strength (Fc) of mortar mixtures containing different cement strength classes of CME 32.5, 42.5 and 52.5 MPa.
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Sensitivity analysis of reinforced concrete beams strengthened with FRP laminates

TL;DR: In this paper, numerical procedures are proposed to predict the failure of reinforced concrete (RC) beams strengthened in flexure with fiber-reinforced polymeric (FRP) laminates.
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