Predictive modeling and optimization of tubular distiller operation using response surface methodology under silver nanomaterial infused PCM thickness variations
This study introduces a novel mathematical model to predict freshwater production and temperature profiles within a tubular solar still (TSS) under varying conditions. Employing RSM (response surface methodology) with a four-factor, five-level central composite design, we evaluated the performance o...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
|
| Series: | Case Studies in Thermal Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X24017209 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832573202195283968 |
|---|---|
| author | W.M. Farouk Ayman Hoballah Z.M. Omara Fadl A. Essa |
| author_facet | W.M. Farouk Ayman Hoballah Z.M. Omara Fadl A. Essa |
| author_sort | W.M. Farouk |
| collection | DOAJ |
| description | This study introduces a novel mathematical model to predict freshwater production and temperature profiles within a tubular solar still (TSS) under varying conditions. Employing RSM (response surface methodology) with a four-factor, five-level central composite design, we evaluated the performance of an Ag-nanomaterial's-improved phase changing material (PCM)-enhanced TSS. RSM effectively modeled the system, enabling optimization of yield (P) and water (Tw) and glass (Tg) temperatures across different PCM thicknesses. Regression models were developed using RSM to predict performance parameters, leading to the identification of optimal process conditions. PCM thickness was varied from 0 to 4 cm. Optimal conditions included a 1.34 cm PCM thickness, 40 °C ambient temperature, 0.73 m/s air speed, and 720 W/m2 radiation. In this case the expected optimum responses of productivity, 5931.15 mL/m2.d. The RSM models demonstrated high accuracy and consistency with experimental data, validating the approach. These findings highlight the potential of RSM for enhancing solar distillation system performance. |
| format | Article |
| id | doaj-art-30b5339262244002982e2239daa6de98 |
| institution | Kabale University |
| issn | 2214-157X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Thermal Engineering |
| spelling | doaj-art-30b5339262244002982e2239daa6de982025-02-02T05:27:10ZengElsevierCase Studies in Thermal Engineering2214-157X2025-02-0166105689Predictive modeling and optimization of tubular distiller operation using response surface methodology under silver nanomaterial infused PCM thickness variationsW.M. Farouk0Ayman Hoballah1Z.M. Omara2Fadl A. Essa3Mechanical engineering departament, Faculty of engineering (Benha), Benha university, Benha, 13511, EgyptElectrical Power and Machines Engineering Department, Faculty of Engineering, Tanta University, Tanta 31521, EgyptMechanical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh, 33516, Egypt; Pharos University in Alexandria, Canal El Mahmoudia Street, Beside Green Plaza Complex 21648, Alexandria, Egypt; Corresponding author. Mechanical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh, 33516, Egypt.Mechanical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh, 33516, Egypt; Corresponding author.This study introduces a novel mathematical model to predict freshwater production and temperature profiles within a tubular solar still (TSS) under varying conditions. Employing RSM (response surface methodology) with a four-factor, five-level central composite design, we evaluated the performance of an Ag-nanomaterial's-improved phase changing material (PCM)-enhanced TSS. RSM effectively modeled the system, enabling optimization of yield (P) and water (Tw) and glass (Tg) temperatures across different PCM thicknesses. Regression models were developed using RSM to predict performance parameters, leading to the identification of optimal process conditions. PCM thickness was varied from 0 to 4 cm. Optimal conditions included a 1.34 cm PCM thickness, 40 °C ambient temperature, 0.73 m/s air speed, and 720 W/m2 radiation. In this case the expected optimum responses of productivity, 5931.15 mL/m2.d. The RSM models demonstrated high accuracy and consistency with experimental data, validating the approach. These findings highlight the potential of RSM for enhancing solar distillation system performance.http://www.sciencedirect.com/science/article/pii/S2214157X24017209Tubular stillDistillationResponse surface methodologyPCM thicknessParaffin wax |
| spellingShingle | W.M. Farouk Ayman Hoballah Z.M. Omara Fadl A. Essa Predictive modeling and optimization of tubular distiller operation using response surface methodology under silver nanomaterial infused PCM thickness variations Case Studies in Thermal Engineering Tubular still Distillation Response surface methodology PCM thickness Paraffin wax |
| title | Predictive modeling and optimization of tubular distiller operation using response surface methodology under silver nanomaterial infused PCM thickness variations |
| title_full | Predictive modeling and optimization of tubular distiller operation using response surface methodology under silver nanomaterial infused PCM thickness variations |
| title_fullStr | Predictive modeling and optimization of tubular distiller operation using response surface methodology under silver nanomaterial infused PCM thickness variations |
| title_full_unstemmed | Predictive modeling and optimization of tubular distiller operation using response surface methodology under silver nanomaterial infused PCM thickness variations |
| title_short | Predictive modeling and optimization of tubular distiller operation using response surface methodology under silver nanomaterial infused PCM thickness variations |
| title_sort | predictive modeling and optimization of tubular distiller operation using response surface methodology under silver nanomaterial infused pcm thickness variations |
| topic | Tubular still Distillation Response surface methodology PCM thickness Paraffin wax |
| url | http://www.sciencedirect.com/science/article/pii/S2214157X24017209 |
| work_keys_str_mv | AT wmfarouk predictivemodelingandoptimizationoftubulardistilleroperationusingresponsesurfacemethodologyundersilvernanomaterialinfusedpcmthicknessvariations AT aymanhoballah predictivemodelingandoptimizationoftubulardistilleroperationusingresponsesurfacemethodologyundersilvernanomaterialinfusedpcmthicknessvariations AT zmomara predictivemodelingandoptimizationoftubulardistilleroperationusingresponsesurfacemethodologyundersilvernanomaterialinfusedpcmthicknessvariations AT fadlaessa predictivemodelingandoptimizationoftubulardistilleroperationusingresponsesurfacemethodologyundersilvernanomaterialinfusedpcmthicknessvariations |