Multi-Objective Optimization of Passive Solar Chimney Ventilation in Eastern Algeria: A Case Study Combining Surrogate Modeling and Metaheuristic Search.
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| Title: | Multi-Objective Optimization of Passive Solar Chimney Ventilation in Eastern Algeria: A Case Study Combining Surrogate Modeling and Metaheuristic Search. |
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| Authors: | Belfegas, Billal1 (AUTHOR), Laouissi, Aissa1,2 (AUTHOR), Swaminathan, Vasanth2,3 (AUTHOR), Karmi, Yacine1,3 (AUTHOR), Elhadj, Raouache1,2 (AUTHOR), Nouioua, Mourad2,3 (AUTHOR) |
| Source: | Energies (19961073). Jun2026, Vol. 19 Issue 12, p2776. 20p. |
| Subject Terms: | *Solar chimneys, *Multi-objective optimization, *Machine learning, *Thermal comfort, *Ventilation, *Energy consumption, *Fluid dynamics |
| Geographic Terms: | Algeria |
| Abstract: | Solar chimneys represent an effective passive ventilation technology capable of improving indoor thermal comfort while reducing building energy consumption. In this study, the thermal and fluid dynamic performance of a solar chimney integrated into a residential building located in Bordj Bou Arréridj (Eastern Algeria) was investigated through a comprehensive numerical, predictive, and optimization framework. A transient mathematical model was developed to evaluate the influence of key geometric parameters, including chimney width and inlet opening width, as well as environmental factors such as solar radiation intensity and wind speed, on the system performance. The generated simulation database was subsequently employed to develop and compare four machine learning models, namely, Artificial Neural Networks with Bayesian Regularization (ANN-BR), Deep Neural Networks optimized by Improved Grey Wolf Optimization (DNN-IGWO), k-Nearest Neighbors (KNN), and Extreme Gradient Boosting (XGBoost), for predicting eight output parameters including glazing temperature, fluid temperature, absorber temperature, outlet temperature, thermal efficiency, air change rate (ACH), mass flow rate, and outlet velocity. The results demonstrated that increasing chimney and inlet widths significantly enhances ventilation performance by increasing airflow rate and ACH. Weather conditions and wind speed were also found to strongly affect thermal efficiency and buoyancy-driven airflow. Among the predictive models, XGBoost and DNN-IGWO exhibited the highest predictive accuracy, achieving coefficients of determination ( R 2 ) close to unity and very low prediction errors for all output variables, confirming their robustness and generalization capability. The proposed methodology provides a reliable tool for rapid performance prediction and design optimization of solar chimney systems under different climatic and operating conditions, thereby supporting the development of energy-efficient passive ventilation strategies for residential buildings. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 194909225 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Multi-Objective Optimization of Passive Solar Chimney Ventilation in Eastern Algeria: A Case Study Combining Surrogate Modeling and Metaheuristic Search. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Belfegas%2C+Billal%22">Belfegas, Billal</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Laouissi%2C+Aissa%22">Laouissi, Aissa</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Swaminathan%2C+Vasanth%22">Swaminathan, Vasanth</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Karmi%2C+Yacine%22">Karmi, Yacine</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Elhadj%2C+Raouache%22">Elhadj, Raouache</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Nouioua%2C+Mourad%22">Nouioua, Mourad</searchLink><relatesTo>2,3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Jun2026, Vol. 19 Issue 12, p2776. 20p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Solar+chimneys%22">Solar chimneys</searchLink><br />*<searchLink fieldCode="DE" term="%22Multi-objective+optimization%22">Multi-objective optimization</searchLink><br />*<searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Thermal+comfort%22">Thermal comfort</searchLink><br />*<searchLink fieldCode="DE" term="%22Ventilation%22">Ventilation</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br />*<searchLink fieldCode="DE" term="%22Fluid+dynamics%22">Fluid dynamics</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Algeria%22">Algeria</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Solar chimneys represent an effective passive ventilation technology capable of improving indoor thermal comfort while reducing building energy consumption. In this study, the thermal and fluid dynamic performance of a solar chimney integrated into a residential building located in Bordj Bou Arréridj (Eastern Algeria) was investigated through a comprehensive numerical, predictive, and optimization framework. A transient mathematical model was developed to evaluate the influence of key geometric parameters, including chimney width and inlet opening width, as well as environmental factors such as solar radiation intensity and wind speed, on the system performance. The generated simulation database was subsequently employed to develop and compare four machine learning models, namely, Artificial Neural Networks with Bayesian Regularization (ANN-BR), Deep Neural Networks optimized by Improved Grey Wolf Optimization (DNN-IGWO), k-Nearest Neighbors (KNN), and Extreme Gradient Boosting (XGBoost), for predicting eight output parameters including glazing temperature, fluid temperature, absorber temperature, outlet temperature, thermal efficiency, air change rate (ACH), mass flow rate, and outlet velocity. The results demonstrated that increasing chimney and inlet widths significantly enhances ventilation performance by increasing airflow rate and ACH. Weather conditions and wind speed were also found to strongly affect thermal efficiency and buoyancy-driven airflow. Among the predictive models, XGBoost and DNN-IGWO exhibited the highest predictive accuracy, achieving coefficients of determination ( R 2 ) close to unity and very low prediction errors for all output variables, confirming their robustness and generalization capability. The proposed methodology provides a reliable tool for rapid performance prediction and design optimization of solar chimney systems under different climatic and operating conditions, thereby supporting the development of energy-efficient passive ventilation strategies for residential buildings. [ABSTRACT FROM AUTHOR] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=194909225 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/en19122776 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 20 StartPage: 2776 Subjects: – SubjectFull: Solar chimneys Type: general – SubjectFull: Multi-objective optimization Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Thermal comfort Type: general – SubjectFull: Ventilation Type: general – SubjectFull: Energy consumption Type: general – SubjectFull: Fluid dynamics Type: general – SubjectFull: Algeria Type: general Titles: – TitleFull: Multi-Objective Optimization of Passive Solar Chimney Ventilation in Eastern Algeria: A Case Study Combining Surrogate Modeling and Metaheuristic Search. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Belfegas, Billal – PersonEntity: Name: NameFull: Laouissi, Aissa – PersonEntity: Name: NameFull: Swaminathan, Vasanth – PersonEntity: Name: NameFull: Karmi, Yacine – PersonEntity: Name: NameFull: Elhadj, Raouache – PersonEntity: Name: NameFull: Nouioua, Mourad IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19961073 Numbering: – Type: volume Value: 19 – Type: issue Value: 12 Titles: – TitleFull: Energies (19961073) Type: main |
| ResultId | 1 |
