فهرست مطالب

Scientia Iranica - Volume:26 Issue:5, 2019
  • Volume:26 Issue:5, 2019
  • Transactions on Civil Engineering (A)
  • تاریخ انتشار: 1398/07/09
  • تعداد عناوین: 11
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  • Yusuf Erzin *, Yesim Tuskan Pages 2615-2623
    In this study, the performance of the artificial neural network (ANN) and multiple regression (MR) models to predict the factor of safety, Fs, values of soil against liquefaction was investigated and compared. To achieve this, two earthquake parameters, namely, earthquake magnitude (Mw) and horizontal peak ground acceleration (amax ), and  six soil properties, namely, standard penetration test number (SPT-N), saturated unit weight (γsat), natural unit weight (γn),  fines content (FC), the depth of ground water level from the ground surface (GWL), and the depth of the soil from ground surface (d) varied in the liquefaction analysis and then the Fs value  was calculated for each case by using the Excell program developed and used in the development of the ANN and MR models. The results obtained from the simplified method were compared with those obtained from both the ANN and MR models.It was found that the predicted values from the ANN model matched the calculated values much better than those obtained from the MR model. Moreover, the performance indices such asthedetermination coefficient, variance account for, mean absolute error, root mean square error, and the scaled percent error were computed to evaluate the prediction capacity of the models developed. The study demonstrates that the ANN model is able to predict the Fs value of the soil against liquefaction, quite efficiently, and is superior to the MR model.
    Keywords: Artificial Neural Networks, factor of safety, liquefaction potential, multiple regression
  • C.Lakshmi Priyanka, B. Vijayalakshmi, M. Nagavalli, G. Dhinakaran * Pages 2624-2632
    Steel industries produces ground granulated blast furnace slag (GGBFS) as a waste material and has enormous scope to be made use of in concrete as partial substitute to cement. The average particle size of GGBFS used was 17.5 µm. It fills voids and modifies the microstructure in turn enhancing the strength and durability of concrete. In the present work commercially available ultra fine slag (readymade ultrafine slag - RUFS) with an average size of 5 µm was used as mineral admixture in three different percentages of 30, 40 and 50 as substitute to cement. Results of present work were compared to precursor slag of author’s earlier works. From the experimental results it was understood that RUFS with 40% substitution to cement gave better performance among three different percentages used. Comparing with author’s earlier works, RUFS performed better than precursor slag and had slightly higher results than that of concrete with 5 to 15% of RUFS. Hence it is suggested that cement could be replaced with readymade ultrafine in high volume as much of 40% without compromising its performance.
    Keywords: Ground Granulated Blast Furnace Slag, Readymade Ultra Fine Slag, compressive strength, Sorptivity, porosity, high volume
  • Amirreza Mahpour *, Amin Alvanchi, Mohammad Mehdi Mortaheb Pages 2633-2652
    Purpose of this research is twofold. Study’s first part focuses on developing quantitative wastage models for rebar, concrete, brick and cement, as major bulk traditional building materials, used in Tehran residential buildings. Primary results indicate that multiple linear regression is an apt tool to model studied variables’ effects on materials wastage. In every developed wastage model, subtractive or accumulative effect of each studied variable is recognized by its coefficient value and sign. Developed models resulted in adjusted R2 values of 0.907, 0.875, 0.920 and 0.790 respectively for rebar, cement, brick and concrete waste. Cement, with average wastage of 8.57% by weight, is identified as the most wasted material verified by the case study. In study’s second part, previously developed models as well as project management experts’ opinions were combined to structure a cement waste reduction guideline for traditional building construction which is common in Tehran, Iran. With this purpose in mind, for projects’ initiating phase, choosing lump-sum contract instead of cost-plus contract is suggested. Moreover a financial incentive reward scheme, with its economic viability and environment friendliness, has been tested with positive results and hence is proposed for construction phase. Applicability of proposed scheme is verified through a case study.
    Keywords: Building Materials Waste, Quantification, Construction Waste Reduction, Cement, Tehran Residential Buildings, Iran
  • Hamed Alikhani, Amin Alvanchi * Pages 2653-2664

    Bridge maintenance activities are often budgeted, scheduled and conducted for networks of bridges with different ages, types and conditions, which can make bridge network maintenance management challenging. In this study, we propose an improved maintenance planning model based on genetic algorithm for a network of bridges to bring a long-term perspective to the lifespan of bridges. To test the applicability and efficiency of the model, it is applied to a network of 100 bridges in one of the south-western provinces of Iran. The results of the model implementation show considerable potential for improvement over the currently adopted model for bridge maintenance planning.

    Keywords: Bridge maintenenance, maintenenace planning, asset management, budgeting, Genetic Algorithm
  • Mohammad Mehdi Mohebbi, Ghassem Habibagahi *, Ali Niazi, Arsalan Ghahramani Pages 2665-2677

    Dust events are among the serious environmental challenges in some countries. Sustainable solutions can be applied to tackle this problem by considering soil as a living ecosystem. Biocementation based on production of carbonates by heterotrophic bacteria is one of the favored methods to suppress the dust from wind erosion because this type of bacteria produces calcium carbonate (main product) as well as water and carbon dioxide (by-products). In present research, bacterial species of Bacillus amyloliquefaciens was used. First, bacteria were cultivated to reach toa pre-determined concentration. Next, bacterial cells and nutrients in the form of solution were sprayed on the soil surface. Then, samples were tested in a closed circuit wind tunnel. Three main groups of samples were tested: without sand bombardment and undisturbed soil surface, with sand bombardment and undisturbed soil surface, and without sand bombardment and with disturbed soil surface. The results show that the implemented method for stabilization of soil was efficient. Moreover, based on the results of second group of tests, curing duration, amount of water, temperature-water interaction and water -bacterial cells interaction were found to be of considerable significance.

    Keywords: wind erosion, dust control, wind tunnel, biocementation, calcium carbonate, Bacillus amyloliquefaciens
  • Mohammad Hossein Ilkhani, Hosein Naderpour *, Ali Kheyroddin Pages 2678-2688
    Shear failure of the RC beam-column joints is a brittle failure which has no priorwarning and can induce tremendous damages because of collapse of column and joint before theconnected beam. This paper is focused on one particular method of strengthening the RC joints,that is, the use of FRP composites as confining element. The results of previous studies have shownthat strengthening the RC beam-column joints with FRP composites can improve their shearcapacity. In this study, the data collected from the existing standards and studies regarding the FRPstrengthened RC joints were used to develop an artificial neural network model for predicting theshear strength contribution of FRP jacket. The developed model was then used to evaluate the roleof different parameters on this contribution, and finally derive a formula for contribution of FRPjacket to the shear strength of the RC beam-column joints.
    Keywords: RC Joint, FRP, Capacity, ANN
  • H. Khaksar, A. Sheikholeslami * Pages 2689-2702
    Flight planning, as one of the challenging issue in the industrial world, is faced with many uncertain conditions. One such condition is delay occurrence, which stems from various factors and imposes considerable costs on airlines, operators, and travelers. With these considerations in mind, we implemented flight delay prediction through proposed approaches that are based on machine learning algorithms. Parameters that enable the effective estimation of delay are identified, after which Bayesian modeling, decision tree, cluster classification, random forest, and hybrid method are applied to estimate the occurrences and magnitude of delay in a network. These methods were tested on a U.S. flight dataset and then refined for a large Iranian airline network. Results showed that the parameters affecting delay in US networks are visibility, wind, and departure time, whereas those affecting delay in Iranian airline flights are fleet age and aircraft type. The proposed approaches exhibited an accuracy of more than 70% in calculating delay occurance and magnitude in both the whole-network US and Iranian. It is hoped that the techniques put forward in this work will enable airline companies to accurately predict delays, improve flight planning, and prevent delay propagation.
    Keywords: flight delay predictor, airline delay, Data mining, machine learning algorithms, visibility distance
  • M. Zanjanchi, M. Mofid * Pages 2703-2711

    Determination of nonlinear dynamic behavior of structures has always been one of the main goals for both structural and earthquake engineers. One of the newest methods for analyzing seismic behavior of structures is Modal Incremental Dynamic Analysis (MIDA). In fact, this method is an alternative to the Incremental Dynamic Analysis (IDA) which is a difficult and time-consuming method. Despite the MIDA's approximate results, advantages such as adequate accuracy, high speed, and low cost has made this method an efficient and appropriate approach. In all previous studies, the proposed models have had a regularized plan, hence, all the analyses have been carried out on a frame. In this study, the MIDA analysis is developed in an unsymmetric-plan type building by considering three structures with 4, 7, and 10 stories having irregularity in plan and thereafter, the accuracy of work has been examined. In this study, by a simplification, instead of considering an unconventional plan, we used a rectangular plan with an eccentricity of 15% between the center of mass and the center of rigidity. Comparing the results of this study with the IDA method proves the high level of accuracy of this method in assessing seismic demands.

    Keywords: Modal Incremental Dynamic, Incremental Dynamic Analysis, Unsymmetric-plan building, unconventional plan, Seismic demands
  • Kamal Rahmani, Mohsen Ghaemian *, Abbas Hosseini Pages 2712-2722
    In the present paper, the effect of Nano silica on mechanical properties and durability of concrete containing polypropylene fibers has been investigated. Here, the length and length to diameter ratio of used polypropylene fibers were considered to be fixed and equal to 18 mm and 600 respectively and the cement content was 479 kg/m3. The effect of fibers and Nano silica in four different percentages at 0.1, 0.2, 0.3 and 0.4 percent by volume for fibers and 3 percent for Nano silica in concrete with water to cement ratio of 0.33, 0.36, 0.4, 0.44 and 0.5 have been compared and evaluated. In total, more than 425 cubic and cylindrical specimens were made according to ASTM standards. Finally, samples of polypropylene fiber containing Nano-silica were tested under compressive loads, flexural strength, indirect tensile strength (Brazilian test), abrasion resistance, permeability and porosity and their mechanical properties were evaluated. The test results showed a significant increase in mechanical properties improvement and durability of concrete. Compressive strength, tensile strength, flexural strength and abrasion resistance (of concrete) increased up to 55%, 25%, 49%, and 45% respectively. Also, considerable reduction of hydraulic conductivity coefficient to 50% indicates high durability of these types of concrete.
    Keywords: concrete, Nano-silica, Polypropylene fiber, Mechanical properties of concrete
  • Muhammad Auchar Zardari *, Nawab Ali Lakho Pages 2723-2730
    Reinforced Baked Clay (RBC) might serve as low cost material of building construction to substitute Reinforced Cement concrete (RCC). Deflection of a beam under a sustained load is considered an important parameter. It is not yet reported in literature what is the effect of reinforcement on long-term deflection response of RBC beams and relative comparison to that of RCC beams. For this purpose, RBC beams were manufactured, baked, and post-reinforced in tension zone only with three ratios of reinforcement (i.e., 0.003, 0.006, and 0.009). All the beams were subjected to a sustained load of 50 kN for one year. The results indicate that long-term deflection of RBC beams was reduced to 20%, and 50% when the reinforcement ratio was increased to 2 and 3 times of the initial reinforcement ratio of 0.003, respectively. The ultimate load carrying capacity of the RBC beams was similar to that of RCC beams. The deflection of RBC beams was thrice of the deflection of RCC beams. This paper shows that RBC beams could be utilized instead of RCC ones with no sacrifice on strength.
    Keywords: Reinforced baked clay, Beams, Deflection, ACI, Sustained load, Low-cost material
  • Ali Kaveh *, Mohsen Kooshkebaghi Pages 2731-2747
    A new swarm intelligence optimization technique is proposed, called Artificial Coronary Circulation System (ACCS). This optimization method simulates the coronary arteries (veins) growth on human heart. In this algorithm, each capillary is considered as a candidate solution. This algorithm starts with a random initial population of candidate solutions, and by using Coronary Growth Factor (CGF) evaluates the solutions. In each run the best candidate solution is selected as the main coronary vessel (artery or vein) and the other capillaries are considered as searchers of the search space. Then the heart decides other candidates to move toward/away from the main coronary vessels and searches for the optimal solution by using the heart memory. Finally, application of the proposed algorithm is demonstrated using some benchmark functions and some mechanical problems, confirming the potential and capability of the new algorithm.
    Keywords: Metaheuristic algorithm, optimization, artificial coronary circulation system, coronary arteries growth, human heart arterial tree