Soft Computing in Civil EngineeringSoft Computing in Civil Engineering
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Sat, 26 May 2018 22:08:07 +0100FeedCreatorSoft Computing in Civil Engineering
http://www.jsoftcivil.com/
Feed provided by Soft Computing in Civil Engineering. Click to visit.An Interior-Constraint BEM for Regularization of Problems with Improper Boundary Conditions
http://www.jsoftcivil.com/article_55277_5935.html
A well-posed problem in analysis of elastic bodies requires the definition of appropriate constrains of the boundary to prevent rigid body motion. However, one is sometimes presented with the problem of non-self-equilibrated tractions on an elastic body that will cause rigid body motion, while the boundary should remain unconstrained. One such case is the analysis of multi-particle dynamics where the solution is obtained in a quasi-static approach. In such cases, the motion of the particles is governed by the dynamic equilibrium while the contact forces between particles may be computed from elastostatic solutions. This paper presents two regularization methods of Interior-Constraint Boundary Element techniques for elastostatic analysis with improper boundary supports. In the proposed method rigid body modes are eliminated by imposing constrains on the interior of an elastic body. This is accomplished through simultaneously solving the governing Boundary Integral Equation and Somigliana’s Identity. The proposed method is examined through assessment and verification studies where it is demonstrated, that for all considered problems rigid body motion is successfully constrained with minimal effects on body deformations.Sat, 31 Mar 2018 19:30:00 +0100Refined Simplified Neutrosophic Similarity Measures Based on Trigonometric Function and Their ...
http://www.jsoftcivil.com/article_61655_0.html
Refined simplified neutrosophic sets (RSNSs) are appropriately used in decision-making problems with sub-attributes considering their truth components, indeterminacy components and falsity components independently. This paper presents the similarity measures of RSNSs based on tangent and cotangent functions. When the weights of each element/attribute and each sub-element/sub-attribute in RSNSs are considered according to their importance, we propose the weighted similarity measures of RSNSs and their multiple attribute decision-making (MADM) method with RSNS information. In the MADM process, the developed method gives the ranking order and the best selection of alternatives by getting the weighted similarity measure values between alternatives and the ideal solution according to the given attribute weights and sub-attribute weights. Then, an illustrative MADM example in a construction project with RSNS information is presented to show the effectiveness and feasibility of the proposed MADM method under RSNS environments. This study extends existing methods and provides a new way for the refined simplified neutrosophic MADM problems containing both the attribute weight and the sub-attribute weights.Sun, 06 May 2018 19:30:00 +0100Comparative Analysis of Rigid Pavement using Westergaard Method and Computer Program
http://www.jsoftcivil.com/article_56038_5935.html
Country’s economic, social and cultural development is mainly dependent on performance of its highway structure. Selection of appropriate pavement type and related design method are vital for the improvement of pavement performance and its service life, and reduction in the initial and maintenance cost. The rigid pavement exposed to many distresses during its service life resulted due to variation of traffic loading, material properties and climatic conditions. The main objective of this project is to make comparison between manual and computer design for rigid pavement structure under different loading, material properties and temperature regimes. For manual design and computer design, “Westergaard Method” and “KENPAVE software” were used respectively. The stress analysis results revealed that edge stresses are higher as compared with interior and corner location, and stresses estimated at all locations with Westergaard method are significantly lower than stresses estimated with KENPAVE software. Results of sensitivity analysis showed that change in pavement thickness, material properties and wheel load has significant impact on developed stresses at different slab locations.Sat, 31 Mar 2018 19:30:00 +0100Connectivity and Flowrate Estimation of Discrete Fracture Network Using Artificial Neural Network
http://www.jsoftcivil.com/article_59741_0.html
Hydraulic parameters of rock mass are the most effective factors that affect rock mass behavioral and mechanical analysis. Aforementioned parameters include intensity and density of fracture intersections, percolation frequency, conductance parameter and mean outflow flowrate which flowing perpendicular to the hydraulic gradient direction. In order to obtain hydraulic parameters, three-dimensional discrete fracture network generator, 3DFAM, was developed. But unfortunately, hydraulic parameters obtaining process using conventional discrete fracture network calculation is either time consuming and tedious. For this reason, in this paper using Artificial Neural Network, a tool is designed which precisely and accurately estimate hydraulic parameters of discrete fracture network. Performance of designed optimum artificial neural network is evaluated from mean Squared error, errors histogram, and correlation between artificial neural network predicted value and with discrete fracture network conventionally calculated value. Results indicate that there is acceptable value of mean squared error and also major part of estimated values deviation from actual value placed in acceptable error interval of (-1.17, 0.85). In the other hand, excellent correlation of 0.98 exist between predicted and actual value that prove reliability of designed artificial neural network.Sat, 17 Mar 2018 20:30:00 +0100Profiled Composite Slab Strength Determination Method
http://www.jsoftcivil.com/article_57404_5935.html
Abstract: The purpose of this article is to develop a new numerical approach for determining the strength capacity of a profiled composite slab (PCS) devoid of the current challenges of expensive and complex laboratory procedure required for establishing its longitudinal shear capacity. The new Failure Test Load (FTL) methodology is from a reliability-based evaluation of PCS load capacity design with longitudinal shear estimation under slope-intercept (m-k) method. The limit-state capacity development is through consideration of the experimental FTL value as the maximum material strength, and design load equivalent estimation using the shear capacity computation. This facilitates the complex strength verification of PDCS in a more simplified form that is capable of predicting FTL value, which will aid in determining the longitudinal shear of profiled deck composite slab with ease. The developed strength determination effectively performs well in mimicking the probabilistic deck performance and composite slab strength determination. The strength test performance between the developed scheme and the experiment-based test results indicates high similarity, demonstrating the viability of the proposed strength determination methodology.Sat, 31 Mar 2018 19:30:00 +0100Prediction of Concrete Properties Using Multiple Linear Regression and Artificial Neural Network
http://www.jsoftcivil.com/article_59743_0.html
The selection of appropriate type and grade of concrete for a particular application is the critical step in any construction project. Workability & compressive strength are the two significant parameters that need special attention. The aim of this study is to predict the slump along with 7-days & 28-days compressive strength based on the data collected from various RMC plants. There are many studies reported in general to address this issue time to time over a long period. However, considering the worldwide use of a huge quantity of concrete for various infrastructure projects, there is a scope for the study that leads to most accurate estimate. Here, data from various concrete mixing plants and ongoing construction sites was collected for M20, M25, M30, M35, M40, M45, M50, M55, M60 and M70 grade of concrete. Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were built to predict slump as well as 7-days and 28-days compressive strength. A variety of experiments was carried out that suggests ANN performs better and yields more accurate prediction compared to MLR model for both slump & compressive strength.Sat, 17 Mar 2018 20:30:00 +0100Stream Flow Forecasting using Least Square Support Vector Regression
http://www.jsoftcivil.com/article_54124_5935.html
Effective stream flow forecast for different lead-times is useful in almost all water resources related issues. The Support Vector Machines (SVMs) are learning systems that use a hypothetical space of linear functions in a kernel induced higher dimensional feature space, and are trained with a learning algorithm from optimization theory. The support vector regression attempts to fit a curve with respect to the kernel used in SVM on data points such that the points lie between two marginal hyper planes which helps in minimizing the regression error. The current paper presents least square support vector regression (LS-SVR) to predict one day ahead stream flow using past values of the rainfall and stream flow at three stations in India, namely Nighoje and Budhwad in Krishna river basin and Mandaleshwar in Narmada river basin. The relevant inputs are fixed on the basis of autocorrelation, Cross-correlation and trial and error. The model results are reasonable as can be seen from low value of Root Mean Square Error (RMSE), Coefficient of Efficiency (CE) and Mean Absolute Relative Error (MARE) accompanied by scatter plots and hydrographs.Sat, 31 Mar 2018 19:30:00 +0100Application of ANN in Estimating Discharge Coefficient of Circular Piano Key Spillways
http://www.jsoftcivil.com/article_60611_0.html
Among all solutions for disrupted vortex formation in shaft spillways, an innovative one called Circular Piano Key Spillway, based upon piano key weir principles, has been experimented less. In this study, the potential of Artificial Neural Networks (ANN) in estimating the amounts of discharge coefficient of Circular Piano Key Spillway has been evaluated. In order to pursue this purpose, the results of some physical experiments were used. These experiments have been conducted in the hydraulic laboratory using different physical models of Circular Piano Key Spillway including three models with different angles of 45, 60 and 90 degrees. Data from those experiments were used in training and test steps of ANN models. Multilayer Perceptron (MLP) network with Levenberg-Marquardt backpropagation algorithm was used. The performance of artificial neural network was measured by these statistical indicators: coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) and optimum quantities of statistical indicators for test step were assessed 0.9999, 0.4988, 0.5963 and 0.9999 respectively, for Circular Piano Key Spillway with an angle of 90 degree and for training step were assessed 0.9999, 0.5479, 0.6305 and 0.9999 respectively, for Circular Piano Key Spillway with an angle of 90 degree. In other words, Circular Piano Key Spillway with an angle of 90 degrees has the optimum performance, both in training and test steps. Artificial Neural Network model can successfully estimate the amounts of discharge coefficient of Circular Piano Key Spillway.Wed, 18 Apr 2018 19:30:00 +0100Reliability Analysis of Structures Using Modified FA_PSO Algorithm
http://www.jsoftcivil.com/article_56144_5935.html
Designing buildings with a very high safety factor is one of the main purposes of a civil engineer. Since in the structural design process, there are several no-confidence; we cannot achieve a perfect safe design. In these cases, we face amount of the probability of failure. So the theory of reliability used to assess the uncertainty. This theoretical for expression the safety of a system uses the reliability index, so it can be said that the calculation of reliability index is an important part of the theory. By the theory of structural reliability, uncertainties arising from the nature of the statistical parameters can be written mathematical equations and considerations of safety and performance of the structure into the design process. Since classical methods are not capable of solving complex functions, metaheuristic algorithms used. In fact, a metaheuristic algorithm is a set of concepts, which significantly able to solve many complex issues, which they can reach an optimal solution in a short time. In this paper, the particle swarm algorithm combined with Firefly and to assess the reliability theory has been used. Reliability index is calculated by searching the shortest distance between the origin and the closed point of Limit State Surface in the Standard normalized space.Mathematical and engineering studies on the issues indicated; Hybrid Firefly and particle swarm algorithm are with great accuracy and speed.Sat, 31 Mar 2018 19:30:00 +0100Optimum Design of Structures Against earthquake by Simulated Annealing Using Wavelet Transform
http://www.jsoftcivil.com/article_62820_0.html
Optimization of earthquake-affected structures is one of the most widely used methods in structural engineering. In this paper optimum design of structures is achieved by simulated annealing method. The evolutionary algorithm is employed for optimum design of structures. To reduce the computational work, a discrete wavelet transform is used by means of which the number of points in the earthquake record is decreased. The loads are considered as earthquake loads. A time history analysis is carried out for the dynamic analysis. By discrete wavelet transform (DWT) the earthquake record is decomposed into a number of points. Then in the optimization process, the structures are analyzed for these points. To reconstruct the actual responses from these points, a reverse wavelet transform (RWT) was used. A number of space structures are designed for minimum weight and the results are compared with exact dynamic analysis. The result show, DWT and RWT were an effective approach for reducing the computational cost of optimization.Tue, 22 May 2018 19:30:00 +0100Modeling of Compressive Strength Characteristics of Structural-sized Afara (Terminalia superba) ...
http://www.jsoftcivil.com/article_57405_5935.html
This paper investigated the reliability of the Structural-sized Afara and Babo timber species as column materials. The work centers on the compressive strength characteristics of Nigerian Afara (Terminalia superba) and Babo (Isoberlinia doka) timber column of nominal lengths 200, 400, 600 and 800 mm and a nominal width and thickness of 50 mm by 50 mm. The steps involved collection and conditioning of Afara and Babo timber species, preparation of test specimens, determination of physical properties such as moisture content and density, determination of compressive strengths using varying heights of 200, 400, 600 and 800 mm and derivation of continuous column design equations. Forty test samples were used in all the tests carried out. Afara and Babo have an average density of 509.80 and 849.67 kg/m3 respectively. Moisture content of both species less than the maximum recommended value of 20 % and the average strength at yield of Afara and Babo are 19.99 and 30.96 N/mm2. The derived continuous equations for design of Afara column and Babo column are σ=ć16.992eć^(0.0039λ) and σ=ć32.031eć^(-0.001λ) respectively. The results of the reliability analysis show that Afara and Babo timber species have reliability index of 0.63 and 0.64 respectively for a service life of 50 years, assuming other serviceability conditions are met. This design procedure is distinct and more effective than the usual procedure of classification of compression members as short, intermediate and long. The paper therefore recommends the adoption of these equations for the design of compression members from these timber species in Nigeria.Sat, 31 Mar 2018 19:30:00 +0100Artificial neural networks prediction of compaction characteristics of black cotton soil ...
http://www.jsoftcivil.com/article_63018_0.html
Artificial neural networks (ANNs) that has been successfully applied to structural and most other disciplines of civil engineering is yet to be extended to soil stabilization aspect of geotechnical engineering. As such, this study aimed at applying the ANNs as a soft computing approach that were trained with the feed forward back-propagation algorithm, for the simulation of optimum moisture content (OMC) and maximum dry density (MDD) of cement kiln dust-stabilized black cotton soil. Ten input and two output data set were used for the ANN model development. The mean squared error (MSE) and R-value were used as yardstick and criterions for acceptability of performance. In the neural network development, NN 10-5-1 and NN 10-7-1 respectively for OMC and MDD that gave the lowest MSE value and the highest R-value were used in the hidden layer of the networks architecture and performed satisfactorily. For the normalized data used in training, testing and validating the neural network, the performance of the simulated network was satisfactory having R values of 0.983 and 0.9884 for the OMC and MDD, respectively. These values met the minimum criteria of 0.8 conventionally recommended for strong correlation condition. All the obtained simulation results are satisfactory and a strong correlation was observed between the experimental OMC and MDD values as obtained by laboratory tests and the predicted values using ANN.Wed, 23 May 2018 19:30:00 +0100An Analysis of Sight Distances Considering Both the Vertical and Horizontal Curves of a Tourist ...
http://www.jsoftcivil.com/article_57946_5935.html
This analyzed sight distances contemplating both vertical and horizontal curves of a tourist bound destination highway in Camarines Sur particularly the Lagonoy to Presentacion section. The Quantum Geographic Information System (QGIS) was used. The data were validated through site observation. The radius, tangent and sight distances for horizontal curves were obtained through graphical measurement while the elevations, length, slopes of both forward and back tangents, and sight distances of vertical curves were computed using mathematics formula. The decision sight distance and the equivalent maximum speed values were deduced through the policies imposed by the American Association of State Highway and Transportation Officials (AASHTO [1]). The highway has numerous horizontal and vertical curves with radius, tangent distances, intersecting angles, curve lengths; elevations of point of curvature (PC), point of tangencies (PT), and point of intersections (PI); and slope of forward and back tangent accorded to short sight distances which delimit car speeds to avoid accident. Through the obtained sight distance data, the maximum speed limit map was completed.Sat, 31 Mar 2018 19:30:00 +0100