Iranian Journal of science and Technology (B: Engineering)
Volume:35 Issue: 1, feb 2011

Strut and Tie Model (STM) has been widely applied for the design of non flexural and deep members in reinforced concrete structures in the last few decades. Experimental research on STM is underway to further rationalize the method for the analysis and design of disturbed regions in reinforced concrete structures. In this research six deep beams with a shear span to depth ratio (a/d) of 0.64, 0.76 and 0.94 have been designed against the external assumed loads. The beams were later tested under monotonic two point loads and the actual shear strength of the deep beams was determined at the failure loads of the beams. The load carrying capacity of the deep beams was also calculated on the basis of the actual strengths of the compression struts and nodes with the help of guidelines given by ACI-318-06, for the use of STM. The observed failure loads were compared with the load carrying capacity of beams worked out from the strengths of the struts. The failure loads were also compared with the provisions of EC-02. It has been observed that both STM based on ACI 318-06 and EC-02 have given a reasonable prediction of the shear strength of deep beams.

The bearing capacity and deformation behavior of geostructures are highly dependent on the mechanical response of a thin layer of soil in contact with a structure that is technically called an interface. This paper presents a constitutive model for the mechanical behavior of sand-structure interfaces. To this goal, the critical state compatible bounding surface framework of Manzari & Dafalias is modified to capture the fundamental state dependent aspects of sand-structure interface behavior. The model has relatively few parameters which have clear physical meanings. The model predictions are compared with experimental results for various interface types, normal stress levels, and stiffness boundary conditions. Using a unique set of model parameters, it is shown that the model is capable of providing reasonable predictions for stress-displacements and normal displacement-tangential displacement behaviors of sand-structure interfaces.

This paper reports on the capability of nonlinear quasi-static finite element modeling in simulating the hysteretic behavior of FRP-retrofitted reinforced concrete (RC) exterior beam-column joints under cyclic loads. For the purposes of our investigation, three concrete beam-to- column joint specimens (un-strengthened and FRP-strengthened) were selected. The ANSYS finite element software was used for modeling RC exterior joints. The specimens were loaded using a step-by- step load increment procedure to simulate the cyclic loading regime employed in testing. Additionally, an automatically reforming stiffness matrix strategy was used to simulate the actual seismic performance of the RC members after cracking, steel yielding, and concrete crushing during the push and pull loading cycles. The results show that the hysteretic simulation is satisfactory for both un-strengthened and FRP-strengthened specimens. Furthermore, when FRP strengthening is employed, strengthened beam-column joints exhibit a better structural performance than the un-strengthened specimens.

In recent times, earthquake-induced structural pounding has been intensively studied through the use of different impact force models. The numerical results obtained from the previous studies indicate that the linear viscoelastic model is relatively simple and accurate in modeling pounding-involved behavior of structures during earthquakes. The only shortcoming of the model is a negative value of the pounding force occurring just before separation, which has no physical explanation. The aim of the present paper is to verify the effectiveness of the modified linear viscoelastic model, in which the damping term is activated only during the approach period of collision, therefore overcoming this disadvantage. First, the analytical formula between the impact damping ratio and the coefficient of restitution is reassessed in order to satisfy the relation between the post-impact and the prior-impact relative velocities. Then, the performance of the model is checked in a number of comparative analyses, including numerical simulation of pounding-involved response, as well as comparison with the results of the impact experiment and shaking table experiments concerning pounding between two steel towers excited by harmonic waves. The final outcome of this study demonstrates that the results obtained through the modified linear viscoelastic model without the tension force are comparably similar to those found by using the linear viscoelastic model.

A sound assessment of the in-plane shear and out-of-plane bending capacities of the load-bearing walls is imperative when conducting seismic assessment or seismic design of masonry buildings. The bulk of work on the subject so far has assumed uniform construction with the brick units connected to each other by mortar bed joints as well as head joints. However, in many construction practices, either for architectural purposes or for speeding up the construction process, the head joints are omitted. This omission may have a profound effect on the response and the strength capacities of the wall. In this paper, the results of a number of tests carried out on half-scale brick wall panels, having different material properties, with head joints and without head joints, are presented. The walls are subjected to in-plane shear, as well as out-of-plane bending pushover loads to failure and their load-displacement curves are established. Representing numerical models for the in-plane shear case are also analyzed and results are compared with those of the experiments. It is found that, depending on the material properties and the modes of failure of the wall, the head joints contribute 35% to 50% to the in-plane shear capacity of the wall. The contribution of the head joints to the out-of-plane flexural strength of the wall is also found to be substantial.

Permanent deformation of asphaltic materials has a major contribution to rutting. Under static loading, the steady-state deformation of asphaltic materials is the key component of the permanent deformation. The steady-state deformation behaviour of a standard 70/100 penetration grade pure bitumen and two types of asphaltic mixtures used in the UK pavements, namely a 10mm Dense Bitumen Macadam (DBM), which is a dense graded mixture, and a 30/10 Hot Rolled Asphalt (HRA), which is a gap graded mixture have been studied. Using Dynamic Shear Rheometer (DSR) Constant stress creep tests were conducted on the bitumen at 10°C and 20°C over a range of stress levels. Uniaxial creep and constant strain rate tests have been conducted over a range of stress levels, strain rates and temperatures, and triaxial creep tests have been conducted over a range of stress levels and confining pressures on the mixtures. The steady-state deformation behaviour of the bitumen is found to be linear at stress levels less than 100 kPa and non-linear power law creep with a power exponent of 2.6 at stress levels higher than 500 kPa. The steady-state deformation behaviour of both mixtures is found to be well captured by the Modified Cross Model which predicts linear viscous behaviour at low stress levels and non-linear viscous behaviour at high stress levels. The steady-state deformation behaviour of the DBM mixture is found to be more sensitive to the stress level. The temperature dependency of the steady-state deformation behaviour is found to be well captured by the Williams-Landel-Ferry (WLF) equation. It is found that confinement has a stiffening effect on the steady-state deformation behaviour of the mixtures. The stiffening effect of the confining stress is found to be higher for the DBM mixture.

Bidding is a strategic decision that helps contractor firms to survive. Traditionally, bidding behaviors are highly unstructured in construction companies. This paper discusses the issues involved in evaluating a tender to assist the managers of a firm in making reliable and sound decisions. The emphasis of the work is on developing a logical decision making framework that covers organizational, environmental, risky and financial considerations.The model takes advantage of well-known decision making methods such as the analytical hierarchy process and the simple additive weighting. The model’s input would be the linguistic description of each project’s value with respect to the decision criteria, and the output would be the value of each project proposed to decision makers considering its correlation with existing projects. By means of a case study, the model has been implemented. The proposed decision making model is found to yield substantially improved solutions when large size contractors are concerned.

Water Distribution Networks (WDNs) are an essential infrastructure of every civilization. In the past decades, there has been a lot of work on the optimization of WDNs. This paper presents a hybrid NSGA-II for multi-objective optimization of combinatorial WDN design, utilizing the SOM network as a tool to find the genotypic or phenotypic similarities. SOM is a versatile unsupervised Artificial Neural Network (ANN) that can be used to extract the similarities and find the related vectors with the use of a proper similarity measure. The proposed method, SOM-NSGA-II, derives subpopulations or virtual islands for inbreeding similar individuals to speed up the convergence process of the optimization. The cross-over operation between similar individuals of the subpopulations at the constraint dominated region of the solution space showed a faster convergence and a wider Pareto front for the test problems considered. An added advantage of the method is the application of genotypic sorting of the population by SOM for visual representation of the structure of the Pareto front. The resulted maps showed the extent of variation of the decision variables and their relative importance. This method may be utilized to speed up optimization of large scale WDNs and as an important visual aid for decision makers and designers of WDNs.

A concern that researchers usually face in different applications of Artificial Neural Network (ANN) is determination of the size of effective domain in time series. In this paper, fractal analysis was used on groundwater depth time series to determine the size of effective domain in the series in an observation well in Union County, New Jersey, U.S. The variation method was applied to the sets considering different domains of 20, 40, 60, 80, 100, and 120 preceding days and the fractal dimension was determined. The fractal dimension remained constant (1.52) when the length of the domain decreased below 80 days. Data sets in different domains were fed to a Feed Forward Back Propagation ANN with one hidden layer and the the groundwater depths were forecasted. Root Mean Square Error (RMSE) and the correlation factor (R2) of estimated and observed groundwater depths for all domains were determined. In general, groundwater depth forecast improved, as evidenced by lower RMSEs and higher R2s, when the domain length increased from 20 to 120. However, 80 days was selected as the effective domain because the improvement was less than 1% beyond that. Forecasted groundwater depths utilizing measured daily data (set #1) and data averaged over the effective domain (set #2) were compared. It was postulated that the more accurate nature of the measured daily data was the reason for a better forecast with lower RMSE (0.1027 m compared to 0.255 m) in set #1. However, a major drawback was the size of the input data in this set which was 80 times the size of the input data in set #2; a factor that may increase the computational effort unpredictably. Hence, it was concluded that fractal analysis may be successfully utilized to lower the size of input data sets considerably, while maintaining the effective information in the data set.

Fuzzy logic provides an effective tool for classifying water quality in a river system based on limited observations. In this study, a fuzzy index (range of 0-100) is proposed for evaluation of water quality for industrial uses. Fuzzy inference system makes it possible to combine the certainty levels for the acceptability of water based on a prescribed limit of various regulatory bodie's quality classes and expert opinions. Application of the proposed fuzzy index is demonstrated with a case study for the Zayandehrud River, located in Isfahan province, Iran. A data set on nine sampling stations along this river was used. Water quality was evaluated for industrial purposes by means of six parameters (pH, TH, TA, SO42-, Cl- and TDS). The results showed that during the study period, the water quality of the river was suitable for some industrial purposes except in Varzaneh. In this station, Zayandehrud receives wastewater of some small industries and agricultural lands. The water quality degraded from Pole Kalleh (index value of 90) to Varzaneh (index value of 15) in the winter months. In the summer months, the index was variable for these two stations. The proposed approach exhibits a convenient tool for continuous monitoring of river water for industrial purposes.