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Showing 2 results for Bazazzadeh
Volume 13, Issue 2 (Summer 2023)
Abstract
Aims: Today, the energy crisis has become a global problem, and all countries are involved in this crisis, so solutions with small results can lead to significant changes on a macro scale. Passive cooling strategies are a method to reduce energy consumption in buildings and help improve and promote energy management in hot climates.
Methods: The current study analysis ventilation performance related to constructing four-story buildings. Furthermore, there is a heavy investigation into the mechanical aspects of ventilation; hence this research is going to fill the gap in the architectural view of the ventilation system. The modeling uses energy software (Design-Builder).
Findings: Studies have been conducted to investigate the position of the stack, and the earth's rotation, in addition to changes in the materials of the stack in the residential area of Dezful city. The most frequent residential land size in the residential area of Dezful is 10x20 square meters. In addition, changing materials has a direct impact on stack ventilation.
Conclusion: The simulation outcomes demonstrated that material and site rotation changes could alter the stack's performance, meaning that glass can be more effective than aluminum. Still, the position of the stack in the plan does not make a significant difference in the stack's performance. The result is outstanding for architects and all people working in this field, which can be a guideline in designing energy-efficient.
S. Mesgary, M. Bazazzadeh, A.r. Mostofizadeh,
Volume 20, Issue 1 (January 2020)
Abstract
Grain design is the most important part of a solid rocket motor. The aim of this study is finocyl grain design based on predetermined objective function with respect to ballistic curves in order to satisfy various thrust performance requirements through an innovative design approach using a genetic algorithm optimization method. The classical sampling method has been used for design space-filling. The level set method has been used for simulating the evolution of the burning surface in the propellant grain. An algorithm has been developed beside the level set code that prepares the initial grain configuration using Pro/Engineer software to export generated models to level set code. The lumped method has been used to perform internal ballistic analysis. Two meta-models are used to surrogate the level set method in the optimization design loop. The first method is based on adaptive basis function construction and the second method is based on the artificial neural network. In order to validate the proposed algorithm, a grain finosyl sample has been investigated. The results show that both grain design method reduced the design time significantly and this algorithm can be used in designing of any grain configuration. In addition, data have more accuracy in grain design based on the artificial neural network, so this method is the more effective and practical method to grain burn-back training.
