Journal of Civil Engineering and Materials Application
Volume:5 Issue: 3, Summer 2021

Portland cement as the main constituent of conventional concrete is the most widely used cementitious material in the construction industry. But Portland cement production has major environmental disadvantages, including high energy consumption and carbon dioxide (CO2) emissions. So that production of Portland cement is accounted for 7 to 10% of global CO2 emissions. Considering the amount of Portland cement production and CO2 emissions in Iran, it can be concluded that Iran is facing environmental problems caused by cement production. Hence, various CO2 emissions mitigation strategies of Iranian cement industry have been evaluated in this study. This research work applied Analytical Hierarchy Process (AHP) method to evaluate and prioritize mitigation strategies. The obtained results showed that among the 16 strategies studied, clinker substitution (blended cement) and production of low carbon cements such as geopolymer cement were recognized as the most important strategies to reduce CO2 emissions in the Iranian cement industry.

Researchers have focused on the fabrication and implementation of concrete which has optimal characteristics, logical price with minimum harmful impacts on the environment. For this purpose, the current project was conducted. Geopolymer cement due to its high durability, insignificant energy consumption, least CO2 emissions, acceptable investment cost and specific characteristics is accounted as a new class of mineral binders which is different from such binders as Portland cement. In this research the geopolymer concrete was made using metakaolin precursor containing 0.3, 0.5 and 1% polypropylene fibers together with monomer with 2, 2.5 and 3 ratios. Next, a number of engineering properties such as the bending strength, compressive strength, electrical resistivity, water absorption and microstructure were assessed at 90 days age using electron microscopy scanning method. metakaolin, concrete geopolymer, concrete durability, scanning electron microscopy test, polypropylene fibers, monomer ratios.metakaolin, concrete geopolymer, concrete durability, scanning electron microscopy test, polypropylene fibers, monomer ratios.

Today, Metaheuristic Algorithms are considered as one of the most important and appropriate methods to achieve good solutions and optimization. In this research, a Particle swarm optimization (PSO) algorithm with a nonlinear objective function has been used to solve the problem of optimizing the reservoir water allocation of the Eyvashan earth dam based on the reservoir water balance for irrigation periods (2014-2020). The results show that the highest agricultural demand downstream of the dam in June was 8.96 (MCM). The amount of reservoir release calculated by the model to meet the water requirement downstream of the dam (37.80MCM) is much more optimal than the total amount of downstream needs (41.03MCM). Also, the minimum amount of water shortage due to severe drought while controlling floods is easily possible due to the useful volume of the reservoir and the annual flow of the reservoir. According to the PSO model, in each period of operation of Eyvashan earth dam, about 7.9% can be saved in the reservoir release for the needs of downstream agriculture in the months of high water consumption in summer.

The gridshell structure is a kind of freeform structure, which is formed by the deformation of a flat grid and the final shape is a double curvature structure. The structural performance of the gridshell is usually obtained by finite element analysis (FEA), which is a time-consuming procedure. This paper aims to present a framework for structural analysis based on the machine learning (ML) model in order to reduce computational time. To this aim, design parameters including the length, width, height, and grid size of the structure are taken into consideration as inputs. The outputs are the member-stresses and the ratio of displacement to self-weight. Therefore, a combination of two algorithms, least square support vector machine (LSSVM) and particle swarm optimization (PSO), is considered. PSO-LSSVM hybrid model is applied to predict the results of the structural analysis rather than the FEA. The results show that the proposed hybrid approach is an efficient method for obtaining structural performance.

Utilization of the reclaimed asphalt pavement (RAP) material to prepare a durable bituminous concrete (BC) mix, used for surface course of flexible pavement, is a challenging task of this investigation. RAP is one of the latest substitutes of virgin aggregate and virgin binder of bituminous concrete mix. Using RAP on flexible pavements can improve the engineering properties of bituminous mix and is also beneficial for economic and environmental. To execute such study, virgin aggregate (VA) has been replaced by 0, 10, 20, 30, 40, 50, 60, 75, and, 100% RAP material respectively in the cited mix with 2% Ordinary Portland Cement (OPC) as mineral filler. To characterize the RAP aggregate and aged binder several laboratory tests such as specific gravity test, water absorption test, shape test, impact test, Los-Angeles abrasion test and, advanced test as X-RF, X-RD, and GPC test, etc. has been employed. However, to assess the durability and strength of RAP enriched BC mix, Marshall stability test, modified Marshall immersion test, indirect tensile strength (ITS) test and, Cantabro abrasion test has been conducted. Marshall stability test, modified Marshall immersion test, ITS test, and Cantabro abrasion test is explored that 50% RAP modified bituminous mix has the capability to better perform than the conventional mix in terms of durability and strength. Because molecular bonding of carbonyl compound between aged and virgin binder is suspected in the mix improvement factor that leads to the longer span life of the RAP modified flexible pavement.