Optimal design of pad footing based on MINLP optimization

Jelušič, Primož; Žlender, Bojan

doi:10.1016/j.sandf.2018.02.002

Cited by 19 publications

(8 citation statements)

References 17 publications

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“…The majority of previous studies focused on the optimization of individual RC structural elements, such as slabs [ 13 , 23 , 24 ], beams [ 12 , 18 , 22 ], columns [ 15 , 16 , 25 ], footings [ 21 , 26 , 27 ], and retaining walls [ 19 , 28 , 29 ]. The design procedures in these studies were subjected to specific code restrictions, such as the American concrete institute (ACI 318-19, ACI 318-14, ACI 318-05), Indian standards (IS: 456), Eurocode 2 (EN 1992-1-1:2004/A1:2014), and Brazilian standards (ABNT NBR 6118:2014, ABNT NBR 6118:2007).…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Reinforced Concrete Materials in Construction

2022

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The structural design process is iterative and involves many design parameters. Thus, this paper presents a controlled framework for selecting the adequate structural floor system for reinforced concrete buildings and efficiently utilizing the corresponding construction materials. Optimization was performed using an evolutionary algorithm to minimize the total construction cost, considering the costs of concrete, steel reinforcement, formwork, and labor. In the problem formulation, the characteristic compressive strength of concrete was treated as a design variable because it affects the mechanical performance of concrete. The design variables included the column spacings, concrete dimensions, and steel reinforcement of different structural components. The constraints reflected the Egyptian code of practice provisions. Because the choice of the structural floor system affects the design details, three systems were considered: solid slabs, flat slabs with drop panels, and flat slabs without drop panels. Two benchmark examples were presented, and the optimal design results of the structural floor systems were compared. The solid slab system had the lowest construction cost among the three structural floor systems. Comparative diagrams were developed to investigate the distribution of construction costs of each floor system. The results revealed that an adequate choice of design variables could save up to 17% of the building’s total construction cost.

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Section: Introductionmentioning

confidence: 99%

Optimal Design of Reinforced Concrete Materials in Construction

2022

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“…However, the genetic algorithm (GA) is utilized in order to increase the convergence rate and to avoid getting trapped in local minima. In the recent past, several methods [12], [13] and algorithms have been applied to the optimization of engineering problems [14]- [19]. However in this paper the genetic algorithm is used to obtain the best prediction model for NOx emissions.…”

Section: Optimization Methodsmentioning

confidence: 99%

Anfis Prediction and Modelling of Harmful Effects on the Environment Produced by Vehicles Crossing Road Bumps

Toplak

Sever

2018

WIT Transactions on the Built Environment

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Modelling and predictions of road traffic emissions and ground-borne vibrations caused by vehicles driving over different types of road bumps has become a rapidly developing research area. However, due to the lack of effective methods and indicators that would define traffic behavior, the accuracy of emissions and vibrations with such an approach is often not at the appropriate level. This paper presents the attempt to model and predict harmful road traffic emissions and vibrations using microsimulation traffic tools and emission models on one side and hybrid optimized models based on artificial neural networks and neuro-fuzzy techniques on the other. The optimized ANFIS-based model was developed to predict harmful road traffic emissions. Basic data were obtained with two programs: VISSIM for micro simulation of traffic flow and ENVIVER to calculate the corresponding emissions at vehicle level. The predicted NOx values indicate a significant increase of emissions by vehicles driving over road bumps, which is almost 100% higher than normal driving. The evaluation and prediction of ground-borne vibrations focused on heavy-duty vehicles, which usually cause perceptible levels of ground-borne vibrations. The prognosis of ground-borne vibration was made with local measurements and empirical vibration predictors. The predicted vibration levels caused by heavy-duty vehicles driving over road bumps are up to 24 times higher than normal vehicle driving (sinusoidal bump). Research shows that setting up speed bumps in different locations in urban areas has to be carefully examined because the level of harmful emissions and ground-borne vibrations increase.

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“…In the recent past, various Figure 1: ANFIS architecture for two-rule two-input sugeno model. methods [6], [7] and algorithms have been applied to the optimization of structures [8]- [13]. However in this paper the optimization algorithms are used to obtain the best prediction model for traffic induced vibration.…”

Section: Genetic Algorithm and Particle Swarm Optimizationmentioning

confidence: 99%

A New Approach for the Prediction of Traffic-Induced Ground Vibration Using a Hybrid Optimized Anfis-Based Model

Lubej

Ivanič

2018

WIT Transactions on the Built Environment

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An attempt has been made to evaluate and predict the traffic-induced ground vibration using a hybrid optimized ANFIS-based model. Towards this aim, ground vibrations caused by traffic were monitored on a building located near the road. To investigate the appropriateness of this approach, the prediction by ANFIS was also compared with the most widely used vibration predictors. In this research, a hybrid of adaptive neuro-fuzzy inference system (ANFIS) optimized by particle swarm optimization (PSO) and genetic algorithm (GA) was proposed to predict traffic-produced ground vibration. The performance criterion selected for the comparison between the actual and the predicted data were the sum of squares due to error (SSE), the root mean square error (RMSE), and goodness of fit (R-square, adjusted R-square). It turns out that the hybrid GA-ANFIS prediction model outperforms the commonly used predictors and conventional ANFIS.

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Optimal design of pad footing based on MINLP optimization

Cited by 19 publications

References 17 publications

Optimal Design of Reinforced Concrete Materials in Construction

Optimal Design of Reinforced Concrete Materials in Construction

Anfis Prediction and Modelling of Harmful Effects on the Environment Produced by Vehicles Crossing Road Bumps

A New Approach for the Prediction of Traffic-Induced Ground Vibration Using a Hybrid Optimized Anfis-Based Model

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