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Steady increase in overexploitation of stone quarries, generation of construction and demolition waste, and costs of preparing extra landfill space have become environmental and waste management challenges in metropolises. In this paper, aggregate production is studied in two scenarios: scenario 1 representing the production of natural aggregates (NA) and scenario 2 representing the production of recycled aggregates (RA). This study consists of two parts. In the first part, the objective is the environmental assessment (energy consumption and CO 2 emission) and economic (cost) evaluation of these two scenarios, which is pursued by life-cycle assessment (LCA) method. In the second part, the results of the first part are used to estimate the optimal combination of production of NA and RA and thereby find an optimal solution (scenario) for a more eco-friendly aggregate production. The defined formulas and relationship are used to develop a model. The results of model validation show that the optimal ratio, in optimal scenario, is 50%. The results show that, compared to scenario 1, optimal scenario improves the energy consumption, CO 2 emissions, and production cost by, respectively, 30%, 36%, and 31%, which demonstrate the effectiveness of this optimization.

Concrete exposed to hot climatic conditions is prone to plastic shrinkage after casting within the first few hours due to the water evaporation and restraining conditions of concrete. This cracking is more commonly observed in concrete elements with a large surface area exposed to drying. In this research, plastic shrinkage of 13 self-compacting concrete samples with different cement paste volumes and various coarse to total aggregate ratios was studied. Test specimens of fresh concrete were subjected to a wind tunnel, which simulated hot dry environmental condition immediately after casting. It can be observed from the test results that the relationship between free plastic shrinkage and the difference between bleeding and evaporation is direct and linear. Finally, a model for plastic shrinkage estimation was suggested by considering the effect of free plastic shrinkage strain, restraining factor, and tensile strain capacity of self-compacting concrete.

Bridge construction projects are rife with uncertainty because of their unique features, from execution of the work, time estimation, inspection and assessment to fund allocation. Therefore, a critical step is recognise and categorise the uncertainties associated in bridge building in order to meet project objectives in terms of quality, cost, schedule, environmental, safety, and technical indicators. Various models, however, have been created to detect and prioritise the uncertainty. One of the most commonly used approaches for dealing with uncertainty is the spherical fuzzy set. To formulate an issue, this technique uses a mathematical procedure. The analytic hierarchy process (AHP), on the other hand, is a computer technique that solves a complicated problem by breaking it down into numerous basic problems. A hybrid model based on spherical fuzzy sets and AHP (SAHP) can benefit from both approaches. This study proposes a SAHP based on group decision making (GSAHP) to prioritise the sources of uncertainty in bridge construction projects. Likewise, a modified algorithm is proposed for checking the consistency of the spherical fuzzy matrices. To show the model potential, a real case study is illustrated and evaluated. The model demonstrates its capabilities in modelling uncertainty under an environment with a number of unknown components. The findings reveal that the “delays” factor is of the highest, and the “project team conflicts” parameter is of the least importance. The research findings could be used by decision makers and managers to develop preventive measures.