An analytic network process model to prioritize supply chain risks in green residential megaprojects

Megaprojects and specifically ‘green’ construction of residential megaprojects can contain significant risks of failure. To design proper risk mitigation strategies, after identifying key risk factors, the next step is to conduct assessments that would facilitate the process of risk element prioritization. Risk assessment comprises the establishment of factor interrelation and discerning the indicators of importance. This research proposes a novel version of an integrated prioritization method and analyzes twelve all-inclusive key supply chain oriented risk factors identified in a previous study. Through a comprehensive literature review three criteria, impact, probability, and manageability are selected. Also, a fourth criterion namely influence rate is included in the model, based on the driving powers that can also be derived from the Interpretive Structural Modeling’s (ISM) assessment. Fundamentally, the calculations hinge on the Analytic Network Process (ANP) method which provides an assessment of the alternatives’ weights based on pairwise comparisons concerning the criteria specified. To enhance the accuracy of the perceptive judgments of the expert panelists, a bell-shaped fuzzy function is used to convert the verbal statements to crisp values. In addition, Row Sensitivity Analysis is administered to check the stability of the results and provide predictive scenarios. To validate the model, a case study, located in Iran, was conducted, where an expert panel consisting of four individuals made the pair-wise comparisons through an ANP questionnaire. Results indicate priority and sensitivity of the alternatives concerning criteria, for the case under study.

Solar still desalination system equipped with paraffin as phase change material: exergoeconomic analysis and multi-objective optimization

The current work is about analysis and multi-objective optimization (MOO) of weir-type solar still systems equipped with phase change material (PCM) regarding the exergetic and economic performance. To do so, the energetic and exergetic modeling of the suggested system is conducted then the substantial economic factors is applied to obtain the total cost rate of the considered SSDS. The total exergetic efficiency and total annual cost (TAC) is considered objective functions. Four parameters include mass of the PCM (m_PCM), inlet brine water flow rate ([Formula: see text]), gap distance (d), and insulation width (x_ins) is chosen as decision variables. Moreover, a genetic algorithm-based MOO was applied to find the optimum states of evaluated solar still unit. The outputs represented that increasing the brine feed water mass flow rate does not affect the TAC while decreasing distilled water production rate. The scattered distribution of optimum states infers that the optimum value of PCM mass is about 1 kg. In addition, applied MOO reveals that with optimization of the studied system, the exergy efficiency increases about 1.47% and the annual distilled water increases 4.35% compared with the non-optimized system. The suggested system is capable to produce fresh water in remote areas without any pollution as well as in a low cost rate.

Multi-objective optimization of a photovoltaic thermal-compound sensible rotary heat exchanger system using exergo-economic and enviro-economic approaches

This paper presents exergo-economic and enviro-economic assessment of a novel building integrated photovoltaic thermal-compound sensible rotary heat exchanger (BIPVT-SRHX) system. The innovative BIPVT-SRHX system preheats/precools the outdoor air in winter/summer and generates electric power. The performance of the system are analyzed from the energy/exergy viewpoints for Kermanshah, Iran climatic conditions. Then, the multi-objective genetic algorithm (MOGA) optimization is used to optimize to determine the optimum values of geometric and operating parameters in order to maximize the annual average exergo-economic and enviro-economic aspects of the system. The considered geometric and operating parameters include the length, width and depth of the air channel located underneath the PV modules, the air mass flow rate, and the diameter, rotational velocity and length of the SRHX. Moreover, the annual performance of the optimized and non-optimized BIPVT-SRHX systems are compared. The results showed that the annual average exergo-economic and enviro-economic aspects of the optimized BIPVT-SRHX system are 0.0076 $/annum and 246.9 kWh/$, respectively. Furthermore, it was found that the annual average enviro-economic aspect, annual average exergo-economic aspect, and yearly sum of CO₂ mitigation of the optimized BIPVT-SRHX system are respectively 36.8%, 23.1% and 37.7% higher than the non-optimized system.