محاضرة عامة عن رسالة ماجستير
للمهندس/ الاء محمد رمضان مجاهد
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| 11 - صباحا | الساعة | 13 - يوليو - 2025 | تاريخ المحاضرة |
| قاعة محاضرات ماجستير التصميمات المتكاملة | مكان المحاضرة |
| الماجيستيرات البينية | قسم |
| Department |
| ماجستيــر العلوم في هندسة التصميمات المتكاملة في مشروعات التشييد | التخصص |
| ماجستيــر العلوم في هندسة التصميمات المتكاملة في مشروعات التشييد | Specialization |
| Modeling of Public Assembly Buildings Performance using System Dynamics and Multi-Criteria Decision Making---
نمذجة أداء المباني العامة باستخدام نمذجة ديناميكية النظم وأساليب دعم اتخاذ القرار متعددة المعايير
| عنوان البحث |
| Modeling of Public Assembly Buildings Performance using System Dynamics and Multi-Criteria Decision Making------------------------------------------------------------------------------
نمذجة أداء المباني العامة باستخدام نمذجة ديناميكية النظم وأساليب دعم اتخاذ القرار متعددة المعايير
| Research Title |
| Historical buildings serve as important links to a country’s cultural and architectural heritage. Many of these structures were built in eras when considerations like energy efficiency, occupant comfort, and indoor air quality were not priorities, leaving them inadequately equipped to meet present-day demands. In this study, a holistic framework is developed to evaluate the performance of naturally-ventilated public buildings over a year using System Dynamics (SD) modeling. The framework is applied to buildings that are classified as places of public assembly with specific occupancy characteristics. The proposed framework consists of three modules: 1) Data Acquisition and Processing, 2) Modeling Building Behavior, 3) Decision-Making and Recommendation. In Data Acquisition and Processing module, hourly performance data of eight variables is extracted from the Building Information Model (BIM) using IES Virtual Environment (IESVE) based on essential inputs such as building geometry, material properties, and occupancy schedules. These variables include energy consumption, energy cost, CO2 emissions, temperature, humidity, indoor CO2 concentration, predicted mean vote (PMV), and percentage of people dissatisfied (PPD). Then, the module constructs a unified scoring system using Multi-Attribute Utility Theory (MAUT). It utilizes advanced utility functions that are applied based on the properties of each studied variable, thresholds from international standards, and project-specific characteristics. Modeling Building Behavior module categorizes and models the variables into an SD model using STELLA Architect software. The created SD model consists of three interconnected sub-models: energy efficiency, indoor air quality (IAQ), and occupant comfort. These sub-models interact dynamically through feedback loops, enabling hourly performance trends assessment by calculating individual indices that are aggregated into a comprehensive Building Performance Index (BPI). System Dynamics also supports the simulation of cumulative effects and helps visualize cause-and-effect relationships, allowing the exploration of how interdependent variables evolve over time and under different scenarios. Additionally, the model’s sensitivity to feedback loops allows the detection of environmental and operational fluctuations. In Decision-Making and Recommendation module, a hybrid weighing approach that combines the Analytic Hierarchy Process (AHP) and the entropy method is applied to each category and sub-category. This balances subjective expert judgement with objective data-driven variability to estimate the weights assigned to each performance variable and its corresponding category. Further, the final module tests the model’s robustness by applying several static and dynamic weight adjustment sensitivity scenarios. The framework is applied to a case study of Al-Hussein Mosque, a historically significant building in Cairo. Results reveal that the occupant comfort module is consistently the weakest performance module. Moreover, dynamic scenarios that incorporate seasonal and occupancy-based adjustments provide more realistic approaches to the worst performance periods than static approaches. The proposed framework provides a reliable, exploratory, feedback-driven tool helping stakeholders with realistic, policy-oriented performance assessment. | نبذة عن البحث |
| Historical buildings serve as important links to a country’s cultural and architectural heritage. Many of these structures were built in eras when considerations like energy efficiency, occupant comfort, and indoor air quality were not priorities, leaving them inadequately equipped to meet present-day demands. In this study, a holistic framework is developed to evaluate the performance of naturally-ventilated public buildings over a year using System Dynamics (SD) modeling. The framework is applied to buildings that are classified as places of public assembly with specific occupancy characteristics. The proposed framework consists of three modules: 1) Data Acquisition and Processing, 2) Modeling Building Behavior, 3) Decision-Making and Recommendation. In Data Acquisition and Processing module, hourly performance data of eight variables is extracted from the Building Information Model (BIM) using IES Virtual Environment (IESVE) based on essential inputs such as building geometry, material properties, and occupancy schedules. These variables include energy consumption, energy cost, CO2 emissions, temperature, humidity, indoor CO2 concentration, predicted mean vote (PMV), and percentage of people dissatisfied (PPD). Then, the module constructs a unified scoring system using Multi-Attribute Utility Theory (MAUT). It utilizes advanced utility functions that are applied based on the properties of each studied variable, thresholds from international standards, and project-specific characteristics. Modeling Building Behavior module categorizes and models the variables into an SD model using STELLA Architect software. The created SD model consists of three interconnected sub-models: energy efficiency, indoor air quality (IAQ), and occupant comfort. These sub-models interact dynamically through feedback loops, enabling hourly performance trends assessment by calculating individual indices that are aggregated into a comprehensive Building Performance Index (BPI). System Dynamics also supports the simulation of cumulative effects and helps visualize cause-and-effect relationships, allowing the exploration of how interdependent variables evolve over time and under different scenarios. Additionally, the model’s sensitivity to feedback loops allows the detection of environmental and operational fluctuations. In Decision-Making and Recommendation module, a hybrid weighing approach that combines the Analytic Hierarchy Process (AHP) and the entropy method is applied to each category and sub-category. This balances subjective expert judgement with objective data-driven variability to estimate the weights assigned to each performance variable and its corresponding category. Further, the final module tests the model’s robustness by applying several static and dynamic weight adjustment sensitivity scenarios. The framework is applied to a case study of Al-Hussein Mosque, a historically significant building in Cairo. Results reveal that the occupant comfort module is consistently the weakest performance module. Moreover, dynamic scenarios that incorporate seasonal and occupancy-based adjustments provide more realistic approaches to the worst performance periods than static approaches. The proposed framework provides a reliable, exploratory, feedback-driven tool helping stakeholders with realistic, policy-oriented performance assessment. | Abstract |
المشرفون:
| 1 - أ.د./ محمد محمود مهدي مرزوق |
الوظيفة
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أستاذ / بالكلية
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