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Civil Engineering Journal

cej
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Published by C.E.J Publishing Group

ISSN : 24763055 EISSN : 24763055 DOI : -

Core Subject : Engineering,

Civil Engineering, Building, Construction & Architecture

Civil Engineering Journal is a multidisciplinary, an open-access, internationally double-blind peer -reviewed journal concerned with all aspects of civil engineering, which include but are not necessarily restricted to: Building Materials and Structures, Coastal and Harbor Engineering, Constructions Technology, Constructions Management, Road and Bridge Engineering, Renovation of Buildings, Earthquake Engineering, Environmental Engineering, Geotechnical Engineering, Highway Engineering, Hydraulic and Hydraulic Structures, Structural Engineering, Surveying and Geo-Spatial Engineering, Transportation Engineering, Tunnel Engineering, Urban Engineering and Economy, Water Resources Engineering, Urban Drainage.

Arjuna Subject : -

Articles 1,848 Documents

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Estimation of Origin â€“ Destination Matrix from Traffic Counts Based On Fuzzy Logic Nabizade Gangeraj, Ebrahim; Behzadi, Gholam Ali; Behzad, Reza
Civil Engineering Journal Vol 3, No 11 (2017): November
Publisher : Salehan Institute of Higher Education

Determining trip demand matrix is among the basic data in transportation planning. This matrix is derived by surveys, interviews with citizens or questionnaires that required time, money and manpower. Thus, in recent years, demand estimation methods based on network information is taken into consideration. In these methods with the information including: volume, travel time, capacity of the links and initial demand matrix it is possible to estimate the demand matrix. In this paper, we removed the additional parameters in previous studies and used a simple solution to estimate the matrix. This paper proposes a Fuzzy-PFE estimation method that allows to improve the estimation performances of PFE estimator. The objective function presented based on the reduction of travel time and travel time of routs in networks is uncertain. The method is developed by fuzzy sets theory and fuzzy programming that seems to be convenient theoretical framework to represent uncertainty in the available data. The new model is the removal of iterative process of origin - destination matrix estimation using travel time and increase convergence of the model for the large-scale and congested networks by applying little changes in the basic model. In this paper we used TRANSCAD Software to determine the shortest path in the network and optimization of objective function is performed by CPLEX.

Effects of Hybridization of Carbon and Polypropylene Short Fibers as Reinforcement on Flexural Properties of Fine Aggregate Concretes Halvaei, Mana; Jamshidi, Masoud; Latifi, Masoud
Civil Engineering Journal Vol 2, No 10 (2016): October
Publisher : Salehan Institute of Higher Education

Nowadays, the advantages of short fibers as reinforcement in cement based materials are well known. In this paper, the effect of hybridization of short polypropylene (PP) and carbon fibers on flexural properties of a fine aggregate concrete has been investigated. Samples with dimensions of Â containing 2 vol% of the polypropylene and carbon fibers with 6 and 8mm length were made. The PP to carbon fiber proportion in the samples were selected as 100:0, 75:25, 50:50, 25:75 and 0:100. A four-point bending test was carried out on all the samples to investigate the flexural behaviour. It was found that the addition of carbon fibers significantly increases the flexural load (i.e. 260%). The application of PP fibers leads to a 2590% increase in the toughness compared to the control sample. It was also found that the sample with carbon to PP ratio of 75/25 shows the optimum results and it leads to 190% and 2070% increment in the flexural load and toughness, respectively, in comparison to the control sample.

Rural Tourism Entrepreneurship Survey with Emphasis on Eco-museum Concept Mojgan Ghorbanzadeh
Civil Engineering Journal Vol 4, No 6 (2018): June
Publisher : Salehan Institute of Higher Education

Unemployment and scarcity of job opportunities count as major problems suffered in villages, especially by the youth. To this end, rural entrepreneurship, particularly in tourism and ecotourism sector, may contribute to the growth of rural economy through strategic and forward-looking planning along with other factors. Innovation and creativity are turning into one of the essential ingredients of continued development. Rural museums, such as “Eco-museum”, are one of the measures taken with regard to protecting various material and spiritual phenomena resulting from traditional habitats. “Eco-museums” can be deemed as a project to support sustainability, and a significant factor for development of entrepreneurship and businesses, especially small- and medium-sized businesses. Espidan, a village in North Khorasan province of Iran, can exert such an effect and play such a role as an eco-museum. Through library resources and field studies, the present study attempts to examine the potentials of Espidan for strengthening its rural tourist properties and fulfilment of ecotouristic objectives in line with three main criteria: public contribution, exclusive eco-museum activities, and creating social, cultural and natural conditions (the determining the vital conditions for a place to evolve into an eco-museum). A study and evaluation of the recommended criteria in Espidan indicates that the village demonstrates considerable potentials for evolving into an eco-museum. As effective steps towards achieving continued development, practical solutions have been proposed for fulfilment of eco-museum objectives as such an evolution into an eco-museum can result in rural entrepreneurship.

Experimental and Numerical Study of Nano-Silica Additions on the Local Bond of Ultra-High Performance Concrete and Steel Reinforcing Bar Ahad Amini Pishro; Xiong Feng
Civil Engineering Journal Vol 3, No 12 (2017): December
Publisher : Salehan Institute of Higher Education

Micro-silica is widely used as an additive to cement in producing high performance concrete. This matter is used to enhance the strength and efficiency of concrete. Recently, due to the development of advanced nano-technology, nano-silica has been produced with particle sizes smaller than micro-silica and higher pozzolanic activity. Studies show that addition of nano-silica into cement-based materials improves their mechanical properties. Considering the unique characteristics of nano-silica, it seems that this material can be used in ultra-high performance concrete (UHPC). Therefore, further studies are needed on how the local bond and bond stress of steel reinforcing bar and UHPC containing nano-silica would be effected. In the present study, after preparing the mix designs and proposed specimens, the effects of various parameters on the local bond of steel reinforcing bars and UHPC containing nano-silica were examined by pullout experiments. In this research, we have numerically investigated the bond strength using numerical methods and calibration of the ABAQUS results in addition to its experimental study of ultra-high performance concrete and steel reinforcement. In numerical analysis, the concrete damage plasticity method was used to simulate the nonlinear behavior of concrete and its strain softness. Comparing between numerical and experimental analysis results shows that numerical analysis with high precision can predict the bond stress, bond load, and concrete specimen fracture mode.

Response of Steel Moment and Braced Frames Subjected to Near-Source Pulse-Like Ground Motions by Including Soil-Structure Interaction Effects Pooriya Ayough; Sara Mohamadi; Seyed Ali Haj Seiyed Taghia
Civil Engineering Journal Vol 3, No 1 (2017): January
Publisher : Salehan Institute of Higher Education

Most seismic regulations are usually associated with fixed-base structures, assuming that elimination of this phenomenon leads to conservative results and engineers are not obliged to use near-fault earthquakes. This study investigates the effect of soil–structure interaction on the inelastic response of MDOF steel structures by using well known Cone method. In order to achieve this, three dimensional multi-storey steel structures with moment and braced frame are analysed using non-linear time history method under the action of 40 near-fault records. Seismic response parameters, such as base shear, performance of structures, ductility demand and displacement demand ratios of structures subjected to different frequency-contents of near-fault records including pulse type and high-frequency components are investigated. The results elucidate that the flexibility of soil strongly affects the seismic response of steel frames. Soil–structure interaction can increase seismic demands of structures. Also, soil has approximately increasing and mitigating effects on structural responses subjected to the pulse type and high frequency components. A threshold period exists below which can highly change the ductility demand for short period structures subjected to near-fault records.

Prediction of the Production Rate of Chain Saw Machine using the Multilayer Perceptron (MLP) Neural Network Javad Mohammadi; Mohammad Ataei; Reza Khalo Kakaei; Reza Mikaeil; Sina Shaffiee Haghshenas
Civil Engineering Journal Vol 4, No 7 (2018): July
Publisher : Salehan Institute of Higher Education

The production rate in rock cutting machines is one of the most influential parameters in designing and planning procedures. Complete understanding of the production rate of cutting machines help experts and owners of this industry to predict the production expenses. Therefore, the present study predicts the production rate of the chain saw machine in dimensional stone quarries. In this research, the method of artificial neural networks was used for modeling and predicting the production rate. In addition, in this modeling, 98 data were collected from the results obtained from field studies on 7 carbonate rock samples as the dataset. Four important parameters, including uniaxial compressive strength (UCS), Los Angeles abrasion (LAA) Test, equivalent quartz content (Qs), and Schmidt Hammer (Sch) were considered as input data and the production rate was considered as the output data. The model was evaluated by the performance indices for artificial neural networks, including the value account for (VAF), root mean square error (RMSE), and coefficient of determination (R2). For simulation, 10 models were created and evaluated. Finally, the best model, i.e. model No. 3, was selected with a 4 × 3 × 1 structure, including 4 input neurons, 3 neurons in the hidden layer and 1 output neuron. The results obtained from the model’s performance indices show that a very appropriate prediction has been done for determining the production rate of the chain saw machine by artificial neural networks.

Monthly Forecasting of Water Quality Parameters within Bayesian Networks: A Case Study of Honolulu, Pacific Ocean Ehsan Jafari Nodoushan
Civil Engineering Journal Vol 4, No 1 (2018): January
Publisher : Salehan Institute of Higher Education

This study investigates the efficiency of Bayesian network (BN) and also artificial neural network models for predicting water quality parameters in Honolulu, Pacific Ocean. Monthly forecasting of three important characteristics of water body including water temperature, salinity and dissolved oxygen have been taken under consideration. Two separate strategies were applied in which the first strategy was related to prediction of the water quality parameters based on previous time series of the same variable. In the second strategy, an attempt was made to forecast DO using different affecting parameters such as temperature, salinity, previous time series of DO, and amount of chlorophyll. The efficiency of the models were assessed by using error measures. Results revealed that the BN models are superior over the ANN models in case of temperature and DO forecasting. Also, it was found that the first strategy is more efficient than the second strategy for predicting DO concentration. The best BN models for temperature, salinity and DO were achieved when time series of the same parameter up to 3, 2, and 3 previous months applied as input variables respectively. Overall, it can be concluded that BN and ANN models can be successfully applied for water quality modelling and forecasting in coastal waters. Moreover, the current study demonstrated that the BN models have a great ability dealing with time series including incomplete or missing data.

State of the Art: Mechanical Properties of Ultra-High Performance Concrete Mohamadtaqi Baqersad; Ehsan Amir Sayyafi; Hamid Mortazavi Bak
Civil Engineering Journal Vol 3, No 3 (2017): March
Publisher : Salehan Institute of Higher Education

During the past decades, there has been an extensive attention in using Ultra-High Performance Concrete (UHPC) in the buildings and infrastructures construction. Due to that, defining comprehensive mechanical properties of UHPC required to design structural members is worthwhile. The main difference of UHPC with the conventional concrete is the very high strength of UHPC, resulting designing elements with less weight and smaller sizes. However, there have been no globally accepted UHPC properties to be implemented in the designing process. Therefore, in the current study, the UHPC mechanical properties such as compressive and tensile strength, modulus of elasticity and development length for designing purposes are provided based on the reviewed literature. According to that, the best-recommended properties of UHPC that can be used in designing of UHPC members are summarized. Finally, different topics for future works and researches on UHPC’s mechanical properties are suggested.

Evaluation of Harmony Search Optimization to Predict Local Scour Depth around Complex Bridge Piers Habibeh Ghodsi; Mohammad Javad khanjani; Ali Asghar Beheshti
Civil Engineering Journal Vol 4, No 2 (2018): February
Publisher : Salehan Institute of Higher Education

One of the main causes of bridge collapse may be flood flow scour near piers. Several experimental and local field investigations were carried out to study scour depth. However, existing empirical equations do not commonly provide accurate scour prediction due to the complexity of the scour process. Physical and economic considerations often lead to bridge foundation constructs which included a pier column based on a pile cap supported by an array of piles. Piers with this configuration are referred to as complex piers. A few studies have been done on complex bridge pier scour depth estimation. Such efforts may be classified into theoretical and empirical equations. This paper investigates local scour around complex bridge piers by using harmony search algorithm under clear water conditions. Statistical indices such as the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and bias were used to evaluate the performance of these methods. By designing laboratory tests, 82 experimental data points were measured by authors. Also 615 experimental data sets with the same measured experimental conditions were collected from published literature and used for optimization. The results show that the developed HS model can predict scour depth better than other equations according to statistical indices.

Classification of Precast Concrete Segments Damages during Production and Transportation in Mechanized Shield Tunnels of Iran Mohsen Ali Shayanfar; Payman Mahyar; Ahmad Jafari; Mohammad Mohtadinia
Civil Engineering Journal Vol 3, No 6 (2017): June
Publisher : Salehan Institute of Higher Education

Precast concrete segments used in shield tunnel linings are prone to damage in many situations. These damages can occur at different stages such as fabrication in segment factory, transportation to tunneling site, during tunneling process, and at serviceability stage. The aim of the present article is to study the damages inflicted on concrete segments during production and transportation, and to present a new classification of these damages throughout the two stages. The developed classification is based on field observations and examinations of major subway and water conveyance mechanized shield tunnels of Iran, located in Tehran, Tabriz, Mashhad, Kermanshah (Nosood) and Isfahan (Golab). The quality of tunnel lining suffers from what, as a direct consequence of any damage to concrete segments, during production and transportation, which will be also discussed in this article. For further investigation, more than 250 concrete segments from Tehran subway line 3 and 350 segments of concrete segments from Tehran subway line 7 were selected and studied for a statistical analysis of chipping and crack, consecutively. Absence of preventive measures to limit segment damages in precast segment factories is one of the main reasons for increased number of damaged concrete segments, and as a result, increased costs of tunnel construction at later stages. In this paper, production phase damages and factors contributing to these damages are studied. According to the findings of the study, the human (operator) error was the most important cause for chipping, and, time-dependent behavior of concrete was the essential reason in crack of precast segments. Eventually, final section of the article presents practical solutions for reduction of damages during fabrication and transportation of concrete segments.

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