Soft Computing in Civil EngineeringSoft Computing in Civil Engineering
http://iranjournals.nlai.ir/2124/
Thu, 20 Feb 2020 01:33:16 +0100FeedCreatorSoft Computing in Civil Engineering
http://iranjournals.nlai.ir/2124/
Feed provided by Soft Computing in Civil Engineering. Click to visit.Adaptive Neuro-Fuzzy and Simple Adaptive Control Methods for Alleviating the Seismic Responses ...
http://iranjournals.nlai.ir/2124/article_649999_70497.html
This paper describes two adaptive control methods for mitigating the seismic responses of two connected buildings with MR dampers at different levels. First method developed in this study is the adaptive neuro-fuzzy controller which consists of a fuzzy logic controller provided with learning algorithm based on adaptive neural networks. The learning algorithm is implemented to modify the parameters of the fuzzy logic controller such that its outputs track the behavior of predetermined training data. Second method is the simple adaptive controller which falls into the category of model-following adaptive strategies. In this method, a plant is commanded to follow a well-designed reference-model with desirable trajectories through a closed loop action. The coupled system consists of two adjacent buildings having different heights in order to separate the model shapes of the individual buildings. Different types of feedbacks such as displacement, velocity, and acceleration are employed to identify their impacts on the performance of the developed adaptive controllers. Numerical analyses are carried out for the complex system assuming no change in the nominal design parameters and then for the system where a change in these parameters is introduced. The results reveal that using the adaptive controllers developed in this study to regulate the MR dampers connecting the two adjacent buildings can successfully alleviate the seismic responses under various types and intensities of earthquakes.Sun, 30 Jun 2019 19:30:00 +0100Hydrologic Input-output model of Mt. Isarog watershed: Estimating the channel cross section ...
http://iranjournals.nlai.ir/2124/article_650000_70497.html
This study estimated the daily extreme runoff water on the watershed based from the gathered twenty four hour peak precipitation per month of year 2018 using modified soil conservation system (SCS-CN) method. This established fuzzy rule based system which is used to estimate the runoff that could pass the channel without overflow, and this described the event of overflow in the river channel. Rain gauge was used to collect the daily rainfall data. Pattern recognition method was used to compute watershed area through satellite images and in confirming areas with evidences of runoff overflow. The process was centered on the size of the cross sectional area of the river and the amount of river water discharge. The highest precipitation event that happened on the month of December has found the river channel cross section to be insufficient to transport the extreme daily watershed runoff. Traces of runoff overflow are visible on satellite images.Sun, 30 Jun 2019 19:30:00 +0100Forecasting of Wind- Wave Height by using Adaptive Neuro-Fuzzy Inference System and Decision Tree
http://iranjournals.nlai.ir/2124/article_650001_70497.html
Wind- induced waves are considered to be the most important waves in the sea due to their high energy and frequency. Among the characteristics of the waves, height is one of the most important parameters that are used in most equations related to marine engineering designs. Since the application of soft computing methods in marine engineering has been developed in recent years, in this study, an adaptive neuro-fuzzy inference system and a decision tree have been used to predict the wind-induced wave height in Bushehr port. In order to identify the effective parameters, implementing different models from different inputs. By considering the accuracy of the models, the effective parameters in wave height were identified using statistical measures correlation coefficient (r), Mean Square Error (mse). The results of this study indicated that in the prediction of wind-induced wave height, compared to the decision tree, the accuracy of the model of the neural-fuzzy system for 3, 6 and 9 hours was higher. Also, the results showed that the use of wind shear velocity instead of wind speed at 10 meters above the water level had a higher accuracy in forecasting of the significant wave height. The results also indicated that among the presented models, the combined model of the significant wave height, shear velocity, and the difference between the direction and wind speed as well as the length of the fetch has the highest accuracy.Sun, 30 Jun 2019 19:30:00 +0100Structural Optimization of Concrete Volume for Machine Foundation using Genetic Algorithms
http://iranjournals.nlai.ir/2124/article_650002_70497.html
This research work aims to optimize a concrete foundation designed to support a high-capacity motor-driven compressor. The structure has plane dimensions of approximately 15 m × 11 m and a height of 1.5 m. The concrete block is to be supported by 20 concrete piles approximately 8.5 m in length and 0.5 m in diameter. The investigated structural system is subjected to deterministic dynamic loadings due to the nature of the equipment supported by the concrete foundation. The main objective of the optimization is to reduce the structural volume through the analysis of its dynamic response, in order to minimize the cost of the concrete volume. In this research work, Genetic Algorithms (GAs) are used through an appropriate interface between ANSYS and MATLAB software. The results of this study show that through the GAs it is possible to achieve a considerable volume reduction with respect to the original volume of concrete used in the design of the foundations structural system.Sun, 30 Jun 2019 19:30:00 +0100