Aminuddin Ab. Ghani

Genetic Programming to Predict Bridge Pier Scour

Bridge-pier scour is a significant problem for the safety of bridges. Extensive laboratory and field studies have been conducted examining the effect of relevant variables. This note presents an alternative to the conventional regression-based equations (HEC-18 and regression equation developed by the writers), in the form of artificial neural networks (ANNs) and genetic programming (GP). There had been 398 data sets of field measurements that were collected from published literature and were used to train the network or evolve the program. The developed network and evolved programs were validated by using the observations that were not involved in the training. The performance of GP was found more effective when compared to regression equations and ANNs in predicting the scour depth at bridge piers.

Gene-Expression Programming for Sediment Transport in Sewer Pipe Systems

Old sewerage systems were designed based on empirical rules to minimize sediment problems and a list of codes for self-cleansing sewers. These codes were applicable to noncohesive sediments (typically storm sewers). This study presents gene-expression programming (GEP), which is an extension of genetic programming (GP), as an alternative approach for modeling the functional relationships of sediment transport in sewer pipe systems. A functional relation has been developed using GEP. The proposed relationship can be applied to different boundaries with partial flow. The proposed GEP approach gives satisfactory results (r2=0.97 and MSE=0.0054) compared to the existing predictor.

Flood risk mapping for Pari River incorporating sediment transport

Geographic Information Systems (GIS) are an efficient and interactive spatial decision support tool for flood risk analysis. This paper describes the development of ArcView GIS extension — namely AVHEC-6.avx — to integrate the HEC-6 hydraulic model within GIS environment. The extension was written in an Avenue Script language and Dialog Designer with a series of ‘point and click’ options. It has the capability of analyzing the computed water surface profiles generated from HEC-6 model and producing a related flood map for the Pari River in the ArcView GIS. The user-friendly menu interface guides the user to understand, visualize, build query, conduct repetitious and multiple analytical tasks with HEC-6 outputs. The flood risk model was tested using the hydraulic and hydrological data from the Pari River catchment area. The required sediment input parameters were obtained from field sampling. The results of this study clearly show that GIS provides an effective environment for flood risk analysis and mapping. The present study only concentrates on the flood risk within the boundary of the bunds.  2002 Elsevier Science Ltd. All rights reserved.

Gene expression programming for total bed material load estimation—a case study

This paper presents Gene-Expression Programming (GEP), which is an extension to the genetic programming (GP) approach to predict the total bed material load for three Malaysian rivers. The GEP is employed without any restriction to an extensive database compiled from measurements in the Muda, Langat, and Kurau rivers. The GEP approach demonstrated a superior performance compared to other traditional sediment load methods. The coefficient of determination, R(2) (=0.97) and the mean square error, MSE (=0.057) of the GEP method are higher than those of the traditional method. The performance of the GEP method demonstrates its predictive capability and the possibility of the generalization of the model to nonlinear problems for river engineering applications.

Genetic programming to predict ski-jump bucket spill-way scour

Researchers in the past had noticed that application of Artificial Neural Networks (ANN) in place of conventional statistics on the basis of data mining techniques predicts more accurate results in hydraulic predictions. Mostly these works pertained to applications of ANN. Recently, another tool of soft computing, namely, Genetic Programming (GP) has caught the attention of researchers in civil engineering computing. This article examines the usefulness of the GP based approach to predict the relative scour depth downstream of a common type of ski-jump bucket spillway. Actual field measurements were used to develop the GP model. The GP based estimations were found to be equally and more accurate than the ANN based ones, especially, when the underlying cause-effect relationship became more uncertain to model.

ANFIS-Based Approach for Predicting the Scour Depth at Culvert Outlets

The processes involved in the local scour at culverts are so complex and that makes it difficult to establish a general empirical model to provide accurate estimation for scour. This paper describes the use of adaptive neurofuzzy inference system (ANFIS) to estimate the scour depth at culvert outlets. The data sets of laboratory measurements were compiled from published literature and used to train the ANFIS network. The developed network was validated by using the observations that were not involved in training. The performance of ANFIS was found to be more effective ( R2 =0.94 ) when compared with the results of regression equations and artificial neural networks modeling in predicting the scour depth at culvert outlets ( R2 =0.78 ) . Further work is required to collect field data of scour at culvert outlets to train the genetic programming approach and validate its usefulness.

Genetic Programming to Predict River Pipeline Scour

The process involved in the local scour below pipelines is so complex that makes it difficult to establish a general empirical model to provide an accurate estimation for scour. This technical note describes the use of genetic programming (GP) to estimate the pipeline scour depth. The data sets of laboratory measurements were collected from published literature and used to train the network or evolve the program. The developed network and evolved programs were validated by using the observations that were not involved in the training. The performance of GP was found to be more effective when compared with the results of regression equations and artificial neural networks modeling in predicting the scour depth around pipelines.

Bio-ecological drainage system (BIOECODS) for water quantity and quality control

Abstract Land use change in urbanizing watersheds can have a significant impact on hydrologic and hydraulic process as well a degradation of water quality on receiving waters. The Bio‐Ecological Drainage System (BIOECODS) consists of elements of storage, flow retarding and infiltration engineering. Swales, dry ponds, detention ponds and wetland are the main components of BIOECODS that function as flow attenuation and water quality treatment devices. The BIOECODS is a pilot project that meets the requirements of the Stormwater Management Manual for Malaysia and has been constructed at the Engineering Campus of the University Science Malaysia, Nibong Tebal, Penang. BIOECODS represents an alternative to the traditional hard engineering‐based drainage system to manage stormwater quantity and quality for urban areas. This article discusses how the BIOECODS could be implemented to control stormwater quantity from an urbanized area and reduce the water quality impact on the receiving water.

3D simulation of flow around a single spur dike with free-surface flow

In the present study, flow patterns around a single spur dike (also termed a groyne) with free-surface flow was simulated using a numerical model known as Fluent. The model solved the fully three-dimensional, Reynolds-averaged Navier–Stokes equation to predict flow near the structure where three-dimensional flow is dominant. To treat the complex free-surface flow, the volume of fluid method with geometric reconstruction scheme was applied and turbulence was simulated using standard equations. In this research work, both a structured and an unstructured mesh were used and the density of the mesh spacing was selected the highest near the walls and also free surface to obtain more accurate results. Comparison of free surface and velocities of 3D model showed good agreement with three experimental flume data obtained by other researchers. The reattachment length for various conditions was computed using the numerical results and flow pattern was presented for repelling, attracting and vertical spur dikes together. Also, bed-shear stress distribution was presented and the effects of flow discharge and the length and angle of the spur dike upon the bed shear-stress distribution were evaluated.

Sediment size characteristics of urban drains in Malaysian cities

Abstract The existing conventional drainage systems in cities throughout Malaysia have been built mainly to cater for the increase in surface runoff due to rapid development that occurs in the city borders. The drainage system is normally made up of open rigid concrete drain channels susceptible to maintenance problems such as sediment deposition, litter and utility pipes crossing. This paper highlights the results of surveys carried out to determine the sediment size characteristics in urban drains of five cities in Malaysia. A preliminary result from a sediment profile observation at Sungai Raja drainage system, Alor Setar is also described to establish the effect of drain size and slope on deposition trend.