---

This paper presents an evaluation on lateral cyclic behaviors of precast concrete columns using a steel box connection through experimental investigation. The test consisted of one monolithic reinforced concrete column as a reference and five precast concrete columns. All specimens had identical dimensions of 0.25 x 0.25 m2 cross sectional area and 1.7 m in height with a longitudinal reinforcement ratio of 0.0152. Materials used for all specimens were also from the same batch. The study was aimed at understanding the design concept of the steel connecting box and detailing of column reinforcement for avoiding the brittle failure of precast concrete frame buildings. The experimental results show that without premature failure in welding or nut slipping, depending largely on the reinforcement details, the precast system with a steel box connection can be effectively used. Flexural failure mode with a ductile mechanism can be achieved to resemble the monolithic one. With a higher relative stiffness and capacities of the designed connecting box, the precast columns show a higher capacity as the failure section was shifted to an upper level. Hence, it can be said that the proper details of precast concrete columns contain acceptable seismic performances e.g. ultimate capacity, stiffness, energy dissipation, and capacity degradation under repeated loading.

---

In recent years, environmental protection is increasingly becoming a major issue in transportation including asphalt production. Despite the fact that Hot Mix Asphalt (HMA) is widely used around the world some recent studies suggest using Warm Mix Asphalt (WMA) technology that reduces the production and placement temperature of asphalt mixes. Currently, a common way of producing WMA is through the utilization of additives. This paper firstly characterizes the effect of WMA additives (organic, chemical, water containing additives) on base bitumen properties. Following the determination of optimum bitumen content of the mixtures with different WMA additives through Marshall Test, Hamburg Wheel Tracking Device is used to measure the permanent deformation characteristics of WMA mixtures. Based on the findings of this study, the utilization of WMA additives help in the reduction of viscosity values which are in return decreases mixing and compaction temperature leading to the reduction of energy costs as well as emissions. Besides, it can be concluded that all WMA mixtures performed better than HMA mixtures in the matter of rut depth.

---

Among important issues in progressive collapse behavior of a building is tracking down the type and location of the damaged elements. This paper deals with identifying the distribution of collapse from the first element to the entire building due to earthquake loads. Here, 3D collapse propagations in symmetric and asymmetric reinforced concrete buildings are compared using nonlinear time history analyses. The variables of such analyses are earthquake load intensity and the level of in plan one directional mass eccentricity. Results show that collapse distribution is dependent on the degree of asymmetry in building. Some patterns to predict progressive collapse scenarios in similar symmetric and asymmetric buildings are also determined. One main pattern shows that the propagation of collapse is horizontal through the stories, but not vertical through the height of the buildings. Spread of the collapse is independent of the earthquake records also according to the results, damage concentration is larger in places with larger mass concentration.

---

Colored self-compacting mortar (C-SCM) is a novel cementitious product that has been recently used in decoration and rehabilitation and has improved aesthetic quality of architectural constructions. C-SCM is susceptible to strength decrease due to excessive pigment presence in the mixture. Optimum pigment content with respect to color intensity and mechanical performance is an important matter that should be determined to prevent mortar failure after construction. In this research, two inorganic pigments in production of colored self-compacting mortar were utilized. The impact of titanium dioxide (TiO2) and iron hydroxide (FeO(OH)) contents on behavior of C-SCMs were investigated in white and gray cement matrixes. Experiments included measurements of compressive strength of mortar cubes and cylinders, flexural strength and colorimetric properties. Analyses on compressive and flexural toughness were applied, as well. It was concluded that pigment content in mix design of colored self-compacting mortar could be optimized with regard to color quality in surface and mechanical strength of the product. Results implied that 5 and 2% of titanium dioxide were the saturation points of color and strength respectively and iron hydroxide at 10% was unsurpassed in C-SCMs containing white cement. Application of both pigments in gray SCMs caused the saturation points of color and strength to occur at 10 and 2%, respectively.

---

Roadway striping is a major operation and maintenance (O&M) task that must be performed to maintain safe vehicular traffic on roadways, which require re-striping or new striping every few seasons depending on the degree of deterioration due to weathering, abrasion, and damage during snow removal. Performance is normally assessed using manually collected data such as working hours, material consumption, and approximate striping distance achieved during a striping season, but the performance analysis methods currently used do not provide a clear holistic picture and are insufficient to permit an in-depth analysis. In order to address this deficiency, this study utilized telematics technology to automatically collect data that could then be used to improve striping performance without the need for additional staff or equipment. This paper presents the telematics data collection and implementation in two areas: 1) providing performance analyses using telematics data and 2) developing performance metrics for future performance measurement. As a result of the study, performance analyses revealed there was sufficient room for improvement and several recommendations were made. Performance metrics were provided using Monte Carlo and triangular distribution.

---

This paper describes both global and local versions of an energetic analytical model to quantify the damage caused to reinforced concrete (RC) structures under monotonic, cyclic or fatigue loading. The proposed model closely represents the damage to structures and yields a damage index (DI) for the RC members. The model is cumulative and is based on the energy absorbed. The energy under the monotonic envelope curve at the failure of the member is taken as a reference capacity. The data required to apply the model in any given situation or member can be obtained either by numerical simulation or from experimental tests. An analytical computer program was developed to simulate numerically the response of RC members taking into account the nonlinear behavior of the materials and structures involved. The proposed model was verified by comparison with practical tests undertaken by other researchers on over 20 RC columns. The comparison demonstrates that the model provides a realistic estimation of the damage of the RC structural members. The comparison between values of the proposed DI calculated based on experimental test data and numerical simulation results for a cyclic loading case shows that to calculate DI, it is not necessary to perform expensive experimental tests and that using a nonlinear structural analytical simulation is sufficient. The results are also compared to a damage model proposed by Meyer (1988).

---

Abstract: Rainfall is an important triggering factor influencing the stability of soil slope. Study on some influences of the rainfall on the instability characteristics of unsaturated soil embankment slope has been conducted in this paper. Firstly, based on the effective stress theory of unsaturated soil for single variable, fluid-solid coupling constitutive equations were established. Then, a segment of red clay embankment slope, along a railway from Dazhou to Chengdu, damaged by rainfall, was theoretical and numerical-simulating researched by considering both the runoff-underground seepage and the fluid-solid coupling. The failure characteristics of the embankment slope and the numerical simulation results were in excellent agreement. In the end, a sensitivity analysis of the key factors influencing the slope stability subjected to rainfall was performed with emphasis on damage depth as well as infiltration rainfall depth. From the analysis in this paper, it was concluded that the intensity of rainfall, rainfall duration and long-term strength of soil have most effect on slope stability when subjected to rainfall. These results suggest that the numerical simulation can be used for practical applications.

---

The present study demonstrates the influence of operating speed on capacity of a midblock section of urban road. Speed – flow data collected at 12 midblock sections of 6-lane and 4-lane divided urban arterials in four metropolitan cities of India are analyzed to determine their capacity. Lane capacity was found to vary from 1482 pcu/hr to 2105 pcu/hr. This variation is explained on the basis of city size and driving behavior, which would influence the free flow speed on the road. Free flow speed was also measured at each section and these speed data were used to determine operating speed (85th percentile of free flow speed of standard car) on the road. Lane capacity was found to be strongly related with operating speed on a road and a second degree polynomial model is developed between the lane capacity and operating speed. This model is further validated by collecting speed flow data at two new sections and their capacity was estimated from field data and from the model developed in the study. The predicted capacity was found to be matching with field capacity and the maximum error was 0.10 percent. Operating speed on a road can vary due to road surface condition, side friction or similar other factors. All these will have influence on capacity of the road. The capacity model suggested in the present study can be a useful tool to determine capacity of an urban road from its operating speed data.

---

The present study aims at the divination of the speed ranges of Level of Service (LOS) categories of urban traffic facilities. Free flow speed (FFS), congested travel speed, geometric and surrounding environmental conditions are considered to define LOS criteria for urban street in Indian context. Cluster analysis is found to be a powerful tool to delineate LOS criteria. Hard Competitive Learning (hardcl) method is used to classify large number of speed data obtained using Global Positioning System (GPS). Six cluster validation parameters are used to classify the urban streets as well as the LOS categories. It can be confirmed from the above research work that the LOS categories for different urban street class are lower than that of the values proposed by HCM 2000 and the average travel speed of LOS categories expressed in percentage of the free flow speed are lower than the values mentioned in HCM 2010.

---

Construction industries are the most dangerous worksites with high risk of occupational accident and bodily injuries, which ranges from mild to very severe cases. The aim of this study was to explore the causal factors of accident severity rate (ASR), in 13 of the biggest Iranian construction industries. In this analytical cross-sectional study, the data of registered accidents from 2009 until 2013 were obtained from an official database. Data of HSE risk management systems and HSE training were also gathered from comprehensive accident investigation reports. Data analysis and regression modeling were done using SPSS statistical software (version 22). The mean and SD of ASR of studied construction worksites was 257.52±1098.95. The results show that the system associated with HSE and HSE risk management established only 41.8 and 18.4%, respectively. The results of multiple linear regression indicated that some individual and organizational factors (IOFs), HSE training factors (HTFs), and Risk Management System factors (RMSFs) were significantly associated with ASR (p<0.05). The study revealed the causal factors of ASR. Hence, these findings can be applied in the design and implementation of a comprehensive HSE risk management system to reduce ASR.

---

Traffic simulation is a powerful tool for analyzing and solving several transportation issues and traffic problems. However, all traffic micro-simulation models require a suitable car-following model to show the real situation in the best way possible. Several car-following models have been proposed. An obvious disadvantage of the former models is the great number of parameters which are difficult to calibrate. Moreover, any change in these parameters creates considerable disturbances. In this paper, a car-following model was proposed using the Epsilon -Support Vector Regression method whose output is the acceleration of the following car. Radial Basis Function was used as the kernel of the ε-SVR method, and the model parameters were tuned using the Grid Search method. The best values for the parameters were obtained. Furthermore, linear scaling in the interval [-1, 1] was used for both the training and testing input data, and the method was proven to more accurate than the case where no scaling was used. Accordingly, a car-following model with the mean squared error equal to 0.005 and the squared correlation coefficient equal to 0.98 was proposed using the function estimation method through the ε-SVR method. Finally, the ε-SVR output was compared with the results of the well-known car-following models, including Helly linear model, the GHR model, and the Gipps model. It was shown that, when using the scaling and parameters tuning techniques, the proposed method was more accurate compared to all three of those models. Moreover, a function fitting Artificial Neural Network was ran for this purpose and the outputs showed that the result of the ε-SVR method is better than that of the function fitting method by the proposed ANN. Implementing a microscopic validation of the proposed model showed that it can be used in the drivers’ assistance devices and other purposes of Intelligent Transportation Systems.

---

The study has been developed a qualitative System Dynamics model to measure sustainability performance of construction project, considering contractors’ tendency to productivity. Construction contractors do not have a clear understanding of sustainability especially in developing countries. However, they welcome higher productivity as a determinant parameter in scheduling and financial success of construction project. Therefore, construction productivity improvement can be employed as an incentive to persuade contractors for implementing sustainability mechanisms in construction project. Sustainability performance has been examined in three aspects of economic, social and environmental by introducing different subsystems and feedback loops. These loops are based on the causal links among the factors affecting construction sustainability and productivity. The findings provide a proper basis for both practitioners and researchers through illustrating the cohesion between productivity and sustainability.

---

Pedestrians are among one of the most vulnerable road users. Speed of vehicles is considered as one of the major causes of danger for pedestrians crossing the street (making cross movements). Therefore, it is of utmost importance to devise suitable solutions for reducing speed of vehicles. One of these solutions is installation of Pedestrian Refuge Islands (PRI) in very wide midblocks. With regard to fluctuations in pedestrian and vehicle traffic volume in traffic hours, there are different variations in collisions between vehicle and pedestrian. In this article the effect of constructed PRI in Tehran on speed of vehicles and consequently their effects on probability fluctuations of fatal accidents are determined. Speed of vehicles in two phases of before and after arriving to the PRI is assessed. Additionally, speed of vehicles in non-observed volumes of vehicle and pedestrian are calculated using Aimsun.v6 simulation software. Paired T-test is applied to compare average speed of vehicles before and after the PRI. The results revealed that except for traffic volumes of 3000-4000 veh/h and 400-600 ped/h in other volumes reduction of average speed of vehicles as a result of PRI is significant. Also, the results show that in all volumes, these equipments reduce the probability of fatal accidents to under 10%. According to the results, it is recommended that PRI should be installed in midblocks where traffic volume of vehicles in each lane is less than 750 veh/h.

---

The gap acceptance behavior of drivers at U-turn median openings is studied by considering the critical gap which cannot be obtained directly by field measurements. A thorough investigation on critical gap estimation is carried out by collecting the data sets from median openings at 4-lane, 6-lane and 8-lane roads of Hyderabad City, India. Wide difference (10% - 42%) among the critical gap values estimated by the application of existing methods shows the limitation to consider for the mixed traffic situations. In order to address this issue, recently developed method Influence Area For Gap Acceptance (INAFOGA) which is based on clearing behavior of drivers at unsignalised intersections is modified and applied considering the merging behavior of U-turn vehicles at median openings and named as ‘Modified INAFOGA’ method. Modified INAFOGA method is compared with probability equilibrium method through paired-sample hypothesis (t-test) and result revealed that difference in mean values 0.009 signifies that both methods are comparable. Difference in critical gap values obtained from the box plots and radar charts indicates that Probability equilibrium method is not suitable to address the behavior of U-turn vehicles at median openings under mixed traffic conditions. These observations coupled with higher critical gap values validate the fact that ‘modified INAFOGA’ method is indeed appropriate under mixed traffic conditions.

---

One of the frequent aspects of lawlessness at signalized intersections is red light violation (RLV). In addition to adverse effects on intersection safety, RLV can cause delay in the startup of the vehicles in the competing phase, defined as the green flow in this study. In this research a video camera was used to collect the required data from intersections in order to investigate the adverse effect of RLV in the city of Esfahan, Iran. Then, by assigning a cellular network to the conflict points of the vehicles path in successive phases the vehicles arrival times to these cells were measured and the imposed delays to the green flow were measured. The results of this study showed that the behavior of drivers in the green flow, the time passed into red interval, and the presence of an all-red interval are the prominent factors affecting the delay caused by RLV. Furthermore, in the absence of an all-red intervals a delay in the range of 1 to 4.5 seconds was inflicted on the subsequent competing green phase. Results of the study also showed that the amount of delay increased substantially when a RL violator was not permitted to precede through the intersection by the green flow vehicles.

---

In recent times, Bus Arrival Time Prediction (BATP) systems are gaining more popularity in the field of Advanced Public transportation systems (APTS), a major functional area under Intelligent Transportation Systems (ITS). BATP systems aim to predict bus arrival times at various bus stops and provide the same to passenger’s pre-trip or while waiting at bus stops. A BATP system, which is accurate, is expected to attract more commuters to public transport, thus helping to reduce congestion. However, such accurate prediction of bus arrival still remains a challenge, especially under heterogeneous and lane-less traffic conditions such as the one existing in India. The uncertainty associated with such traffic is very high and hence the usual approach of prediction based on average speed will not be enough for accurate prediction. In order to make accurate predictions under such conditions, there is a need to identify correct inputs and suitable prediction methodology that can capture the variations in travel time. To accomplish the above goal, a robust framework relying on data analytics is proposed in this study. The spatial and temporal patterns in travel times were identified in real time by performing cluster analysis and the significant inputs thus identified were used for the prediction. The prediction algorithm used the Adaptive Kalman Filter approach, in order to take into account of the high variability in travel time. The proposed schemes were corroborated using real-world GPS data and the results obtained are very promising.