Forced convection around horizontal tubes bundles of a heat exchanger using a two-phase mixture model: Effects of nanofluid and tubes Configuration

In this paper, numerical simulation of laminar flow and heat transfer of nanofluid on a group of heat exchanger tubes is described. For better prediction of the behavior of the nanofluid flow on the tube arrays, two-phase mixture model was used. To achieve this aim, heat transfer and laminar flow of two-phase nanofluid as cooling fluid at volume fraction of 0, 2, 4, and 6% solid nanoparticles of silver and Reynolds numbers of 100 to1800 were investigated for different Configurations of tube arrays. The results indicated when the nanofluid collides with the tube arrays, the growth of heat boundary layer and gradients increase. The increase in the growth of boundary layer in the area behind the tubes was very remarkable, such that at the Reynolds number of 100, due to diffusion of the effect of wall temperature in the cooling fluid close to the wall, it had a considerable growth. Further, from the second row onwards, the slope of pressure drop coefficient diagrams was descending. Among the different Configuration s of tubes and across all the investigated Reynolds numbers, square Configuration had the maximum pressure drop coefficient as well as the highest extent of fluid momentum depreciatio

Constructing a smart framework for supplying the biogas energy in green buildings using an integration of response surface methodology, artificial intelligence and petri net modelling

Nowadays, energy crisis is considered an essential active issue for future urbanization in megacities. While the rate of population growth increases, the volume of municipal solid waste production increases significantly. This highlights the need of Sustainable Development Goals (SDGs) for both developed and developing countries. This paper constructs a novel smart framework for supplying biogas energy. Our study is applicable for fields of waste management and energy supply in green buildings. The proposed framework integrates the Response Surface Methodology (RSM), Artificial Intelligence (AI), and Petri net modeling. In this regard, the AI techniques including the Random Tree (RT), Random Forest (RF), Artificial Neural Network (ANN) and, Adaptive-Networkbased Fuzzy Inference System (ANFIS) are employed. In addition, for creating the optimum condition, a dynamic control system using the Petri Net modeling is applied. Among all machine learning methods, ANFIS with 0.99 correlation coefficient had the best accuracy for Accumulated Biogas Production (ABP) based on effective factors. Finally, the main findings of this paper are to introduce a novel framework for addressing different scientific issues such as supplying the clean energy in green buildings, the development of a smart and sustainable biogas production control system, integration of solid waste management with the SDGs in green buildings

Bio-recovery of municipal plastic waste management based on an integrated decision-making framework

Recent years have seen rapid development in industrialization and urbanization with huge growth in the population throughout the world. In this regard, an efficient and robust framework for the concept of a green city and sustainable development goals to manage municipal plastic wastes is still needed. This study models a bio-recovery of municipal different plastic wastes management based on a new integrated Multi-Criterion Decision-Making (MCDM) approach through a case study in Mashahd, Iran. The proposed integrated MCDM framework includes the Shannon Entropy (SE), Ordered Weighted Aggregation (OWA), Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and, ELimination Et Choice Translating REality (ELECTRE) systems in an intelligent way. Through decision-making computations, all criteria are approved after extraction from the literature review by experts with more than 60% agreement percentage. Different scenarios of economic, energy, and environmental crises are created. One finding of this paper is to create a new entrance in economic competition with plastic biodegradation to present a novel, environmental-friendly product with high-quality and low-cost advantages. Another finding determines that with an application of plastic wastes bio-recovery, citizens' satisfaction from urban management system will be increased from 49% to 64%. Whereas, based on the outcomes of this investigation, the rate of municipal waste industries development, smart city goals’ meeting, and rate of hazardous material emission from municipal solid wastes are increased to 58%, 25%, and 70%, respectively. The declared numerical outcomes illustrate the effectiveness of plastic waste bio-recovery on the smart city approach