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An efficient selection operator for use in genetic search of pipe networks optimal design is introduced in this paper. The proposed selection scheme is the superior member of a family of improved selection operators developed in an attempt to more closely simulate the main features of the natural mating process which is not reflected in existing selection schemes. The mating process occurring in the nature exhibits two distinct features. First, there is a competition between phenotypes looking for the fittest possible mate which usually ends up with choosing a mate with more or less the same fitness. Second, and more importantly, the search for a mate is often confined to a community of phenotypes rather than the whole population. Four different selection operators simulating these features in a random and pre-determined manner are developed and tested. All the selection schemes exhibit good convergence characteristics, in particular the one in which both the size of the sub-community and the pair of the mates in the sub-community are determined randomly. The efficiency of the proposed selection operator is shown by applying the method for the optimal design of three well-known benchmark networks, namely two-loop, Hanoi and New-York networks. The proposed scheme produces results comparable to the best results presented in the literature with much less computational effort

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Water conveyance systems (WCSs) are costly infrastructures in terms of materials, construction, maintenance and energy requirements. Much attention has been given to the application of optimization methods to minimize the costs associated with such infrastructures. Historically, traditional optimization techniques have been used, such as linear and non-linear programming. In this paper, application of ant colony optimization (ACO) algorithm in the design of a water supply pipeline system is presented. Ant colony optimization algorithms, which are based on foraging behavior of ants, is successfully applied to optimize this problem. A computer model is developed that can receive pumping stations at any possible or predefined locations and optimize their specifications. As any direct search method, the mothel is highly sensitive to setup parameters, hence fine tuning of the parameters is recommended.

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This paper presents a relatively new management model for the optimal design and operation of irrigation water pumping systems. The model makes use of the newly introduced particle swarm optimization algorithm. A two step optimization model is developed and solved with the particle swarm optimization method. The model first carries out an exhaustive enumeration search for all feasible sets of pump combinations able to cope with a given demand curve over the required period. The particle swarm optimization algorithm is then called in to search for optimal operation of each set. Having solved the operation problem of all feasible sets, one can calculate the total cost of operation and depreciation of initial investment for all the sets and the optimal set and the corresponding operating policy is determined. The proposed model is applied to the design and operation of a real-world irrigation pumping system and the results are presented and compared with those of a genetic algorithm. The results indicate that the proposed mode in conjunction with the particle swarm optimization algorithm is a versatile management model for the design and operation of real-world irrigation pumping systems.

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A novel approach to determine optimal sampling locations under parameter uncertainty in a water distribution system (WDS) for the purpose of its hydraulic model calibration is presented. The problem is formulated as a multi-objective optimisation problem under calibration parameter uncertainty. The objectives are to maximise the calibrated model accuracy and to minimise the number of sampling devices as a surrogate of sampling design cost. Model accuracy is defined as the average of normalised traces of model prediction covariance matrices, each of which is constructed from a randomly generated sample of calibration parameter values. To resolve the computational time issue, the optimisation problem is solved using a multi-objective genetic algorithm and adaptive neural networks (MOGA-ANN). The verification of results is done by comparison of the optimal sampling locations obtained using the MOGA-ANN model to the ones obtained using the Monte Carlo Simulation (MCS) method. In the MCS method, an equivalent deterministic sampling design optimisation problem is solved for a number of randomly generated calibration model parameter samples.The results show that significant computational savings can be achieved by using MOGA-ANN compared to the MCS model or the GA model based on all full fitness evaluations without significant decrease in the final solution accuracy.

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By application of design spectra in seismic analyses, determination of design spectra for different site conditions, magnitudes, safety levels and damping ratios will improve the accuracy of seismic analysis results. The result of this research provides different design acceleration spectra based on Iran earthquakes database for different conditions. For this purpose first a set of 146 records was selected according to causative earthquake specifications, device error modification and site conditions. Then the design acceleration spectra are determined for 4 different site conditions presented in Iranian code of practice for seismic resistant design of buildings (Standard No. 2800), different magnitudes (MsO5.5 & Ms>5.5), different damping ratios (0, 2, 5, 10, 20 percent) and also various safety levels (50% & 84%). Also this research compares the determined design spectra with those in Standard No. 2800.

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This paper presents the application of an iterative penalty method for the design of water distribution pipe networks. The optimal design of pipe networks is first recasted into an unconstrained minimization problem via the use of the penalty method, which is then solved by a global mathematical optimization tool. The difficulty of using a trial and error procedure to select the proper value of the penalty parameter is overcome by an iterative use of the penalty parameter. The proposed method reduces the original problem with a priori unknown penalty parameter to a series of similar optimization problems with known and increasing value of the penalty parameters. An iterative use of the penalty parameter is then implemented and its effect on the final solution is investigated. Two different methods of fitting, namely least squares and cubic splines, are used to continuously approximate the discrete pipe cost function and are tested by numerical examples. The method is applied to some benchmark examples and the results are compared with other global optimization approaches. The proposed method is shown to be comparable to existing global optimization methods.

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Current practices in railway track analysis and design are reviewed and discussed in this paper. The

mechanical behavior of railway track structure comprising of various components has not been fully understood due

to the railway track structural complexity. Although there have been some improvements in the accuracy of current

track design methods in recent decades, there are still considerable uncertainties concerning the accuracy and

reliability of the current methods. This indicates a need for a thorough review and discussion on the current practices

in the analysis and design of railway track systems. In this paper, railway design approaches proposed by various

standards along with the results of a wide range of technical researches are studied and necessary suggestions are

made for the improvement of current practices in the analysis and design of railway track

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Railway service terminals are the places of a railway network usually equipped with costly technology based

on highly complicated technological procedures demanding a high degree of coordination and control skills. Design

of these systems and the organization of their operation should facilitate reaching to the required capacity together

with high quality of service processes as well as minimal costs of resources. Due to the complexity of such systems, a

simulation model seems to be the only suitable tool for performing investigations under realistic conditions. The paper

focuses on the possible utilization of simulation methods to support the design and optimisation of infrastructure,

operation, and process control algorithms in railway terminals. The paper also deals with the most important

properties and possibilities offered by the simulation tool Villon and comments on the experience gained during its

utilization. The tool supports tactical (mid-term) and strategic (long-term) planning usually related to infrastructural

or operational proposals which are supposed to guarantee the optimal (or at least effective) behaviour of the modelled

terminal.

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Considering normal concrete (NC) the type of concrete need to be vibrated after placing in the formwork, Lightweight

concretes have been successfully applied in the building constructions for decades because of their low specific weight in

connection with a high strength, a high capacity of thermal insulation and a high durability. The development leading to a self

compacting light weight concrete (SCLWC) represents an important innovative step in the recent years. This concrete combines

the favorable properties of a lightweight concrete with those of a self compacting concrete (i.e., the type of concrete need no

vibration after placing in the formwork). Research work is aimed on development of (SCLWC) with the use of light weight

aggregates " Light expand clay aggregate (Leca)". In this investigation, by trial and error procedure, different mix design of

SCLWC were caste and tested to reach a so called standard self compacting concrete in fresh matrix phase such as values of

slump flow, L-box, V-funnel and in hardened phase, the 28 day compressive strength. Based on the results obtained, for two best

so-called standard mix design of SCLWC the stress-strain diagrams are drawn and discussed. Also by three different methods,

the modulus of elasticity of SCLWC are obtained and discussed here. It was found that a brittle mode of failure is governed in

SCLWC.

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Self Compacting Concrete (SCC) specimens with limestone (L) and quartz (Q) powders were formulated. The influence of the type

of the powder on the properties of fresh and hardened concrete was evaluated. Dense packing theories were used for mix design

of samples. The equation of Fuller and Thompson for particle size distribution (PSD) of aggregates was modified with considering

fine particles and a proper PSD curve was obtained for SCC. Experimental results showed that this method needs use of less

powder content and results in higher strength/cement ratio compared to traditional mixing methods. No significant difference was

observed between the compressive strengths of specimens containing limestone (L-specimens) and quartz (Q-specimens) powders,

with similar proportions of materials. The residual compressive strength of specimens was examined at 500°C and contradictory

behaviors were observed. One Q-specimen suffered from explosive spalling, while no spalling was occurred for L-specimens. On

the other hand, the residual strength of remained Q-specimens showed considerable increase compared to L-specimens. The results

show the necessity for more detailed investigations considering different effective parameters.

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An evolutionary structural optimization (ESO) method is used for plastic design of frames. Based on safe theorems some criteria are derived and made an effort to satisfy them during the optimization process. In this regard, equilibrium is checked and yield condition is gradually satisfied during the optimization process. In this method, the amount of used material and the stiffness for each element are improved, simultaneously, to impose upper bound of moment in the element. Frame analysis and optimization algorithm are implemented as PLADOF (PLAstic Design of Frames) computer code. Four examples are presented to illustrate the performance of the algorithm

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Present study is an extension of earlier work carried out on two-lane two way roads in the two provinces of Pakistan i.e. N-25,

N-55 and N-5 regarding the measure of operating speed and development of operating speed prediction models. Curved sections

of two-lane rural highways are the main location of run-off road accidents. In addition to that the road alignment having

combination of geometric elements may be more harmful to the drivers than the successive features with adequate separation.

This study is carried out on two-lane two- way road along N-65 (from Sibi to Quetta). Three sections are selected for study with

thirty three horizontal curves. Continuous speed profile data was recorded with the help of VBox (GPS based device) which was

attached with a vehicle to detect vehicle position through satellite signals. VBox is new equipment with modern technology in this

field and it helps in recording continuous speed profile and saving of this information on the computer as a permanent record.

Through the regression analysis, models were developed for estimation of operating speed on horizontal curves and on tangent,

and estimation of maximum speed reduction from tangent to curve. The validation of developed model shows compatibility with

the experimental data.

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It has been realized that the raft (mat) foundations are capable of bearing very large loads when they are assisted with a pile
group. The contribution of both raft and piles to carry the surcharge loads is taken into account, considering the stiffness and
strength of involved elements in the system, i.e. piles, raft and surrounding soil. The piles are usually required not to ensure the
overall stability of the foundation but to act as settlement reducers. There is an alternative design in which, the piles are nonconnected
from the raft to reduce the settlement, which are then known to be "settlement reducer non-connected piles" to increase
the system stiffness. In this paper, two and three dimensional finite element analysis of connected and non-connected pile-raft
systems are performed on three case studies including a 12-storey residential building in Iran, a 39-storey twin towers in
Indonesia, and the Messeturm tower, 256m high, in Frankfurt, Germany. The analyses include the investigation of the effect of
different parameters, e.g. piles spacing, embedment length, piling configuration and raft thickness to optimize the design. The role
of each parameter is also investigated. The parametric study results and comparison to a few field measurements indicate that
by concentrating the piles in the central area of the raft foundation the optimum design with the minimum total length of piles is
achieved, which is considered as control parameter for optimum design. This can be considered as a criterion for project cost
efficiency. On the other hand, non-connected piled-raft systems can significantly reduce the settlements and raft internal bending
moments by increasing the subsoil stratum stiffness. Finally, the comparison indicates that simple and faster 2D analysis has
almost similar results to the time consuming and complicated 3D analysis.

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Learning rapidly and competently has become a pre-eminent strategy for improving organizational performance in the

new knowledge era. Improving dynamic learning capability is an exclusive strategy for corporate success in construction

industry. Thus engineering design firms should implement OL to accomplish a state of readiness for change and develop a

competence to respond and identify future business potentials. This study aims to analyze the relationship between

organizational learning (OL) and performance improvement (PI) in civil engineering design firms of Turkish construction

industry. OL structure in engineering design firms incorporates five constructs: organizational environment, strategy

development and implementation, supportive leadership, leveraging knowledge, and learning capability. The empirical data

was collected through a questionnaire survey conducted to engineering design firms registered to the Turkish Chamber of Civil

Engineers. The hypothesized model relationships were tested using Structural Equation Modeling (SEM). The results show that

each of the variables has a different role and significant positive impact on the OL process and organizational PI. The variables

“Supportive leadership” and “Learning capability” proved to be strongly significant and positively related to organizational

performance in engineering design firms. In engineering design firms, supportive leadership is needed in order to establish a

participative cultural environment that helps design a new form of organization which emphasizes learning, flexibility, and

rapid response. Learning capability is the potential to explore and exploit knowledge through learning flows that make possible

the development, evolution and use of knowledge stocks enacting engineering design firms and their members to add value to

the design business.

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Barrel vaults are attractive space structures that cover large area without intermediate supports. In this paper, the charged

search system (CSS) optimization algorithm is employed for optimal design of barrel vaults. This method utilizes the governing

laws of Coulomb and Gauss from electrostatics and the Newtonian law of mechanics. The results demonstrate the efficiency of

the discrete CSS algorithm compared to other meta-heuristic algorithms.

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In this paper, a new approach was presented for bus network design which took the effects of three out of four stages of the bus planning process into account. The presented model consisted of three majors steps 1- Network Design Procedure (NDP), 2- Frequency Determination and Assignment Procedure (FDAP), and 3- Network Evaluation Procedure (NEP). Genetic Algorithm (GA) was utilized to solve this problem since it was capable of solving large and complex problems. Optimization of bus assignment at depots is another important issue in bus system planning process which was considered in the presented model. In fact, the present model was tested on Mandl’s bus network which was a benchmark in Swiss network and was initially employed by Mandl and later by Baaj, Mahmassani, Kidwai, Chakroborty and Zhao. Several comparisons indicated that the model presented in this paper was superior to the previous models. Meanwhile, none of the previous approaches optimized depots assignment. Afterwards, sensitivity analysis on GA parameters was done and calculation times were presented. Subsequently the proposed model was evaluated thus, Mashhad bus network was designed using the methodology of the presented model.

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Since the 1990’s, network reliability has been considered as a new index for evaluating transportation networks under uncertainty. A large number of studies have been revealed in the literature in this field, which are mostly dedicated to developing relevant measures that can be utilized for the evaluation of vulnerable networks under different sources of uncertainty, such as daily traffic flow fluctuations, natural disasters, weather conditions, and so fourth. This paper addresses the resource allocation problem in vulnerable transportation networks, in which multiple performance reliability measures should be met at their desired levels, while the overall cost of upgrading links’ performances should be minimized simultaneously. For this purpose, a new approach has been considered to formulate the two well-known performance measures, connectivity and capacity reliability, along with their application in a bi-objective nonlinear mixed integer goal programming model. In order to take into account the uncertain conditions of supply, links’ capacities have been assumed to be random variables and follow normal distribution functions. A computationally efficient method has been developed that allows calculating the network-wise performance indices simply by means of a set of functions of links’ performance reliabilities. Using this approach, as the performance reliability of links are themselves functions of the random links’ capacities, they can be simply calculated through numerical integration. To achieve desirable levels for both connectivity reliability and capacity reliability (as network-wise performance reliability measures) two distinct objectives have been considered. One of the objectives seeks to maximize each of the measures regardless of what is happening to the other objective function which minimizes the budget. Since optimization models with two conflicting objectives cannot be solved directly, the well-known goal attainment multi-objective decision-making (MODM) approach has been adapted to formulate the model as a single objective model. Then the resultant single objective model has been solved through the generalized gradient method, which is a straightforward solution algorithm coded in existing commercial software such as MATLAB programming software. To show the applicability of the proposed model, numerical results are provided for a simple network. Also, to show the sensitiveness of the model to decision maker’s direction weights, the results of sensitivity analysis are presented..

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Construction industry consists of several phases in which a variety of stakeholders are involved. As construction projects are becoming larger, more complex and more diverse, the design phase has been more important factor for the success of projects than ever before. However, it is considered that most of design work occurred in actual design process is intangible. Such recognition makes the design phase more unsystematic and arbitrary, which finally weakens the competitiveness of whole project. In order to solve these problems, this study developed a web-based system for integrated design management (IDMS) which consists of 8 modules including design document, schedule, quality, and building permit management. This section is intended to validate the system implementation and its effectiveness. Two characteristics have made this research significantly different from previous studies. First of all, users of the system including architects and other design professionals were continuously involved starting from the development phase to the validation phase. The other unique characteristic is that the actual design project was applied as a test bed in the final verification stage. The research team applied the actual data which had been generated while each business process, and verified the effectiveness of system implementation. The authors expect that such a user-centered approach enable the system more robust and effective.

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Because thin plate reinforced concrete members such as walls and slabs are greatly influenced by the drying shrinkage, cracks can occur in these members due to the restraint of the volume change caused by drying shrinkage. Therefore, the control of cracking due to drying shrinkage is very important in building construction that the thin plate members are frequently used. However, few researches of estimating shrinkage cracking in RC walls have been executed, and the cracking control design of RC walls has been conducted based on the experience rather than the quantitative design method. In this study, the practical cracking prediction method using equivalent bond-loss length Lb was proposed for the quantitative drying shrinkage crack control of RC wall. The calculated values using proposed method were compared with the experimental results from uniaxial restrained shrinkage cracking specimens and the investigative values from the field study. In general, the results of this method were close to those of the experiment and the field study.

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The main cause of structural damage in buildings subjected to seismic actions is lateral drift. In almost all reinforced concrete (RC) structures, whether designed with walls or frames, it is likely to be the code drift limits that control the design drift. The design drift limits and their contribution to damage may be represented indirectly through the material strain limits. The aim of this study is to investigate the seismic design indicators of RC columns using finite element analyses (FEA). The results of FEA have been compared with the results of experimental studies selected from literature. It is observed that the lateral load-deflection curves of analyzed columns are in agreement with the experimental results. Based on these lateral load-deflection curves, the drift limits and the material strain limits, given by the codes as performance indicator, are compared. It is observed that the material strain limits are non-conservative as performance indicator of RC columns, compared to the drift limits.