![Sample our Economics, Finance,Business & Industry journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5931/TOC-Subject-Sample-2021-Economics-Finance-Business-Industry.jpg"})
ABSTRACT
This study investigated the thin-layer drying kinetics of salted silver jewfish in a hybrid solar drying system and under open sun. Ten drying models were compared with experimental data of salted silver jewfish drying. A new model was introduced, which is an offset linear logarithmic (offset modified Page model). The fit quality of the models was evaluated using the coefficient of determination (R2), root mean square error (RMSE), and sum of squared absolute error (SSAE). The result showed that Midilli et al. model and new model were comparable with two or three-term exponential drying models. This study also analyzed energy and exergy during solar drying of salted silver jewfish. Energy analysis throughout the solar drying process was estimated on the basis of the first law of thermodynamics, whereas exergy analysis during solar drying was determined on the basis of the second law of thermodynamics. At an average solar radiation of 540 W/m2 and a mass flow rate of 0.0778 kg/sec, the collector efficiency and drying system efficiency were about 41% and 23%, respectively. Specific energy consumption was 2.92 kWh/kg. Moreover, the exergy efficiency during solar drying process ranged from 17% to 44%, with an average value of 31%. The values of improvement potential varied between 106 and 436 W, with an average of 236 W.
Funding
The authors would like to thank the Universiti Kebangsaan Malaysia (UKM-DLP-2011-034) and UKM-GUP-2011-108, (UKM-HEJIM-KOMUNITI- 13-2010) and the Solar Energy Research Institute (SERI), Universiti Kebangsaan Malaysia for support.
Nomenclature
| Ac | = | collector area (m2) |
| a | = | drying constant |
| C | = | specific heat of air (J/kg/°C) |
| d | = | mass of dry materials |
| Ex | = | exergy |
| exp | = | exponential |
| H | = | relative humidity (%) |
| IP | = | improvement potential (W) |
| k | = | drying constant |
| L | = | latent heat of vaporisation of water at exit air temperature (J/kg) |
| M | = | moisture content |
| Me | = | equilibrium moisture content |
| Mo | = | initial moisture content |
| MBE | = | mean bias error |
| m | = | mass flow rate (kg/sec) |
| N | = | number of observations |
| n | = | drying constant |
| S | = | solar radiation (W/m2) |
| R2 | = | coefficient of determination |
| RMSE | = | root mean square error |
| T | = | temperature (°C) |
| t | = | drying time |
| W | = | weight of water evaporated from the product |
| W | = | mass of wet materials |
| = | density of air (kg/m3) | |
| = | efficiency |
Subscripts
| c | = | chamber |
| f | = | fan |
| I | = | inlet |
| o | = | outlet |
| dci | = | drying chamber inlet |
| dco | = | drying chamber outlet |
| exp | = | experimental |
| pre | = | prediction |
![Supercharge Your Next Research Paper: Research and write your next paper with Jenni AI.]({"type":"image" , "src" : "/sda/112445/Skyscraper-econ.png"})