Journal of Garmsar Science and Engineering

Abstract The increase in the production of pollutants has caused serious problems for the environment. It can be said that heavy metals are one of the most harmful pollutants because they cause irreparable risks due to their accumulation and non-biodegradability. They accumulate in plants and animals by contaminating water and soil, and through this, they enter the food chain and have irreparable effects on human health. Their nature is toxic, so even trace amounts of them cause serious problems. Improper disposal of waste, sewage, agricultural fertilizers, pesticides, coal mines, and thermal power plants can be considered as their release factors. Unfortunately, it can be said that most of the methods of their removal are time-consuming and expensive, so the management of the sources that are responsible for their release is of great importance. In this study, heavy metal contamination in water, soil, and dust, as well as phytoremediation method for their removal, have been investigated.

Abstract With the growing demand for designing lightweight, durable, and efficient structures in advanced industries such as aerospace, renewable energy, and automotive engineering, precise analysis of the dynamic behavior of structures like thin-walled beams with variable cross-sections has become increasingly important. This study investigates the vibration and dynamic stress analysis of thin-walled beams with varying cross-sections using the Rayleigh–Ritz method. To accurately model the beam geometry, polynomial functions are employed to define the variation of thickness and diameter along the beam’s length. Utilizing the Rayleigh–Ritz approach, the mass and stiffness matrices are semi-analytically derived, and the governing vibration equations are formulated. Subsequently, the dynamic response of the beam under distributed sinusoidal loading is computed, and the bending stress distribution along the beam is evaluated. For geometry optimization aimed at simultaneously reducing the maximum stress and structural weight, the NSGA-II genetic algorithm is applied, yielding a set of optimal designs on the Pareto front. The results demonstrate that an appropriate design of thickness and diameter functions, assisted by the optimization algorithm, can effectively reduce both dynamic stresses and overall weight. Moreover, comparison of the numerical responses with results obtained from the finite element software ABAQUS shows strong agreement, validating the proposed method. This approach can serve as an effective tool for designing lightweight and robust structures in applications such as aerospace, renewable energy systems, and the automotive industry.

Abstract In this study, the effect of experience and learning in building construction projects was investigated using the log-linear model (straight line). For this purpose, a reputable construction company in Tehran was selected as the case study. The construction details of five building projects of this company, including two five-story buildings, one four-story building, and two fourteen-story buildings, were examined. In addition, project execution data in terms of schedule and cost were collected for all projects in four sections, including: 1) site preparation and foundation, 2) structural work, 3) finishing and completion, and 4) the entire project. Using the power model based on the cumulative learning of the projects under study, the learning rate values for the entire projects ranged from 82.75% to 92.69%, and a value of 89.10% was calculated for the final project. The results indicate that experience had a significant effect on the execution process of these five projects and led to a reduction in construction time per square meter-floor of the building, such that the average reduction in construction time for four projects was approximately 30%. Furthermore, regarding construction cost, the learning rate was calculated to be between 98.80% and 99.53%, indicating that changes in construction costs were influenced less by execution experience and were more likely affected by external factors such as fluctuations in material prices, labor wages, and economic conditions.

Abstract The increasing need of society in various industries, including food and pharmaceutical industries, to receive products with the highest quality and highest efficiency is a strong factor for rapid progress in the field of food-pharmaceutical coating. Considering the ease of using fluid bed technology on an industrial scale compared to other coating methods, its use is one of the most suitable and efficient methods. In this study, a conical fluid bed device with top spraying was used to coat sodium bicarbonate particles as the central core. The base solution for coating was a combination of maltodextrin and hydroxyethyl cellulose with the ability to suspend and stabilize nanoparticles. The surface tension of the coating solution in the presence of different concentrations of nanoparticles (0.15-0.5% by mass) was measured using the Pendant drop method. The results showed an increase in surface tension with increasing nanoparticle concentration due to the more spontaneous wetting process of solid particles. Also, an increase in the average grain size and a more uniform particle size distribution, a more uniform coating layer, and a decrease in its permeability were observed with an increase in the surface tension of the binding liquid

Abstract This study analyzes the co-authorship network structure of nuclear physics researchers in 20 top universities in Iran. The co-authorship graph was constructed with 1,470 nodes and 1,618 edges, and structural properties including diameter, radius, center, girth, average path length, clustering coefficient, independence number, and size of the largest connected component were calculated. Findings showed that 94% of researchers belong to a single connected component. Graph diameter is 11, radius is 6, the center consists of 4 nodes, average path length is 4.91, and average clustering coefficient is 0.0538. Average degree is 2.20, and the independence number of the graph is 852. Five main clusters were identified in the graph. The co-authorship network of Iranian nuclear physics has a sparse structure with small and local collaborations and has greater diameter and average path length compared to international networks. These results indicate the dominance of individual research culture and the necessity of adopting incentive policies for larger collaborative groups in Iran.