Journal of Civil Engineering
Volume:8 Issue: 1, Winter 2024

Soil improvement involves a variety of approaches. Among them, addition of specific materials has been widely adopted in the literature. Colossal numbers of worn tires are released in the environment every year. It will cause serious environmental issues. Moreover, cement production process causes detrimental consequences for environment, but it still is considered as one of the main options in construction projects. So, the main purpose of this research is to find suitable alternative methods to decrease cement usage. In this paper the effect of adding zeolite and waste rubber powder on unconfined compression strength (UCS) of soil were investigated. Two types of sandy soil were adopted in this study, SP and SW soil. In order to improve these two types of soils, 4% by weight cement, 0, 0.25, 0.5 and 0.75% rubber powder and 0, 10, 30 and 50% zeolite replacement with cement during curing period of 7, 14 and 28 days were considered. According to the compaction test results, by increasing the percentage of rubber powder, the maximum dry density and the optimal moisture content of both type of soils decreases. However, with zeolite addition, the maximum dry density of both type of soils has decreased and value of optimum moisture has increased. The optimum percentage of zeolite and rubber powder in SW soil was 30% and 0.5% respectively, while in SP soil these amounts were 10% and 0.25% respectively.

Analysis of various physical phenomena requires solution of partial differential equations. Numerical methods especially the meshless schemes are used to discretize and solve these equations. Recently, several modifications have been proposed and applied to improve numerical performance of the smoothed particle hydrodynamics (SPH) method as a well-known meshless method. This study aims to show that the least squares methods especially in the context of the mixed formulation can get more accuracy compared with all existing SPH models. To validate this claim, three meshless numerical models are derived from Taylor series expansion on the basis of the mixed formulation. One of the models is based on mixed first order ordinary formulation while two other use the first and second order least squares mixed scheme. For accuracy analysis of the proposed methods, a potential flow and three two dimensional differential equations have been solved and examined with the presented SPH models. The main finding of this study is that the proposed mixed second order least squares method has the ability to achieve significant computational efficiency over several efficient and accurate SPH models. In addition to this, it has been found that the least square scheme can improve accuracy of the ordinary mixed model.

It is a common understanding that higher traffic volume leads to more pollutant air. Therefore, when the air quality deteriorates, policy makers restrict private vehicles to decrease the air population. This study aims to challenge this assumption by using statistical models including multivariate regression and ordered logistic regression models. These models are calibrated by employing datasets on air pollution, traffic quality, and weather conditions, for Tehran the capital of Iran by using R studio. The results show that the coefficient of the Traffic Quality Index (TQI), representing traffic volume, is not statistically significant. This finding suggests that traffic volume does not significantly impact air quality in Tehran. Among the variables, temperature has the most considerable effect on air pollution and has the highest significant coefficient. The coefficients of all variables align with our previous knowledge. In fact, temperature and wind speed showing negative significant coefficients, implying that lower temperatures and slower wind speeds leads to higher levels of air pollution. Conversely, TQI and humidity exhibit positive significant coefficients, showing that increased traffic volume and higher humidity levels are associated with more polluted air. In conclusion, restricting private cars may not be a practical solution for addressing the issue of air pollution in Tehran.

Millions of dollars are spent every year on road pavements, which generally require rehabilitation every one to five years. Roller-compacted concrete (RCC) pavements are a good replacement for asphalt pavements due to their special properties, such as better durability and conformity with sustainable development principles. On the other hand, changes in the ambient temperature, which cause freeze-thaw cycles, can strongly affect the strength and durability of concrete pavements. Hence, a study of the impact of freeze-thaw cycles and additives on the properties of RCC seems necessary for developing suitable measures for controlling damage and durability loss in concrete. To this end, the present study investigated the influence of cement and nanographene content on the durability of pavements and the weight loss, dynamic modulus of elasticity, durability factor, and spalling of RCC. Nanographene with 0.05%, 0.07%, and 0.1% of cement weight was added to specimens prepared with cement grades of 200, 250, and 300. The specimens were subjected to freeze-thaw cycles after preparation and curing. According to the results, the addition of nanographene improved the properties of RCC under freeze-thaw cycles, reduced weight loss and spalling in the specimens with different cement contents, and enhanced their durability factor and modulus of elasticity. Although adding nanographene significantly contributed to better concrete properties, its effect was directly related to the concrete content. Finally, the optimal values of the cement and graphene content after 300 cycles were obtained to be 300 and 0.05% of cement weight, respectively.

Today, due to the complexity of construction projects, Building Information Modeling (BIM) is used to increase accuracy and speed and avoid the cost of rework in a building's construction cycle. One of the most important functions of BIM technology in the design and construction phase is the identification of clashes and their reporting. The purpose of this study is to classify and prioritize the serious clashes between the two disciplines of structures and MEP. To do this, each structure type and MEP element must be assigned the required weight, which is done using the best-worst method (BWM). The corresponding questionnaire is distributed to nine BIM experts. With the help of weights and the outputs of the Navisworks software, the process of prioritizing clashes and the methods of eliminating clashes are carried out. Of the structural elements, 32% are accounted for by each beam and column element, 19% by the foundation, 13% by lateral bracing systems and 4% by the structural floor. Due to the many elements of the MEP, they are divided into six groups. The weighting of MEPs (costs) is 39% for group five, 22% for group two, 15% for group six, 11% for group three, 9% for group four and 4% for group one. Additionally, the MEP weight (time) items are 39% for group five, 20% for group six, 14% for each item from groups two and three, 8% for group four, and 5% for group one.

The minimum cost is a crucial target of almost all types of construction projects, and it is achieved by an efficient scheduling. However, each project is unique and duration of activities involved in a project often cannot accurately be predicted. In this research, fuzzy sets were the solution. One prominent point of this research was considering the level of risk acceptance, based on which, crisp durations for activities were attained. In other words, fuzzy scheduling was turned into crisp scheduling. Then, a method based on genetic algorithm was selected to select the operating mode for the smallest project total costs. The last stage of the proposed method was determination of the fuzzy project cost. Simplifications made in this study make it possible to find optimum solutions in complex problems. Next, an example of a construction project was used which substantiated that genetic algorithm with its selected input data (population and generation number) and criterion of selecting surviving chromosomes for next generation (roulette wheel principle) could deliver reliable outcomes and provides a tool for handling real-world construction projects. Furthermore, the performed sensitivity analysis proved that the proposed model is not much sensitive to large variation in the values of acceptance level of risk. Finally, for the purpose of validation of the effectiveness of the proposed model, the case study was solved by three widely-used approaches. This comparison (at least 17% improvement in solutions) was a reason for the fact that the presented model is a tool helping project managers a lot.