Can Ertekin

MATHEMATICAL MODELING OF THIN LAYER SOLAR DRYING OF SULTANA GRAPES

Thin layer solar drying experiments were conducted for Sultana grapes (cv. Thompson seedless) grown in Antalya, Turkey. An indirect forced convection solar dryer consisting of a solar air heater and a drying cabinet was used in the experiments. Air heated by the solar air heater was forced through the product by an electric fan. In order to examine the effect of drying air temperature and velocity on a thin layer drying of Sultana grapes, twenty-two experiments were performed. Eight different thin layer mathematical drying models were compared according to their coefficient of determination to estimate solar drying curves. The effects of drying air temperature and velocity on the model constants and coefficients were predicted by the regression models. According to the results, a two-term drying model could satisfactorily describe the solar drying curve of Sultana grapes with a correlation coefficient (r) of 0.979. The constants and coefficients of this model could be explained by the effect of drying air temperature and velocity.

Assessing the potential of renewable energy sources in Turkey

To meet Turkey’s growing energy demand, the installed electric power capacity of 27.8 GW in 2001 has to be doubled by 2010 and increased fourfold by 2020. The difference between Turkey’s total primary energy supply (TPES) of from its own sources and total final consumption (TFC) is projected grow from 1 quad (1.06–2.06) in 1999 to 5.71 quads (2.79–8.5) in 2020 (1 quad=293.071 TWh). Turkey’s limited amount of fossil fuels has a present average ratio of proved reserves of 97.38 quads to production rate of 3.2 quads yr−1 of about 30 years. Turkey’s reliance on fossil fuel-based energy systems to meet the growing demand is most likely to exacerbate the issues of energy insecurity, national environmental degradation, and global climate change in increasing proportions. Economically-feasible renewable energy potential in Turkey is estimated at a total of ca. 1.69 quads yr−1 (495.4 TWh yr−1) with the potential for 0.67 quads yr−1 (196.7 TWh yr−1) of biomass energy, 0.42 quads yr−1 (124 TWh yr−1) of hydropower, 0.35 quads yr−1 (102.3 TWh yr−1) of solar energy, 0.17 quads yr−1 (50 TWh yr−1) of wind energy, and 0.08 quads yr−1 (22.4 TWh yr−1) of geothermal energy. Pursuit and implementation of sustainability-based energy policy could provide about 90 and 35% of Turkey’s total energy supply and consumption projected in 2010, respectively. Utilization of renewable energy technologies for electricity generation would necessitate about 23.2 Mha (29.8%) of Turkey’s land resources.

Comparison of some existing models for estimating global solar radiation for Antalya (Turkey)

Abstract Solar radiation data for Antalya (36°53′ N, 30°42′ E) in Turkey were used to test the applicability of twenty six models available for computing the monthly average daily global radiation on a horizontal surface. The models were compared on the basis of statistical error tests using the mean percentage error (MPE), root mean square error (RMSE) and the mean bias error (MBE). According to our results, the Samuel model below (Samuel T.D.M.A. Estimation of global radiation for Srilanka. Solar Energy 1991;47(5):333) showed the best estimation of global solar radiation on a horizontal surface for Antalya by means of the MPE (1.5%), RMSE (0.27 MJ/m 2 ) and MBE (−0.02 MJ/m 2 ) statistical tests: H H 0 =−2.4275+11.946 S S 0 −16.745 S S 0 2 +7.9575 S S 0 3

Estimation of monthly average daily global radiation on horizontal surface for Antalya (Turkey)

In this study, multiple linear regression models were used to estimate the monthly average daily global radiation using nine different variables for Antalya, Turkey; the extraterrestrial radiation, solar declination, mean relative humidity, ratio of sunshine duration, mean temperature, mean soil temperature, mean cloudiness, mean precipitation and mean evaporation. The results showed that the models can estimate global radiation within relative error (|e|) of −5.7 and 3.9%, a mean error (MPE) of 2.0% and root-mean square error (RMSE) of 2.5% for Antalya.

Modeling Spatio-Temporal Dynamics of Optimum Tilt Angles for Solar Collectors in Turkey

Quantifying spatial and temporal variations in optimal tilt angle of a solar collector relative to a horizontal position assists in maximizing its performance for energy collection depending on changes in time and space. In this study, optimal tilt angles were quantified for solar collectors based on the monthly global and diffuse solar radiation on a horizontal surface across Turkey. The dataset of monthly average daily global solar radiation was obtained from 158 places, and monthly diffuse radiation data were estimated using an empirical model in the related literature. Our results showed that high tilt angles during the autumn (September to November) and winter (December to February) and low tilt angles during the summer (March to August) enabled the solar collector surface to absorb the maximum amount of solar radiation. Monthly optimum tilt angles were estimated devising a sinusoidal function of latitude and day of the year, and their validation resulted in a high R2 value of 98.8%, with root mean square error (RMSE) of 2.06°.

Modeling Potential Distribution and Carbon Dynamics of Natural Terrestrial Ecosystems: A Case Study of Turkey

We derived a simple model that relates the classification of biogeoclimate zones, (co)existence and fractional coverage of plant functional types (PFTs), and patterns of ecosystem carbon (C) stocks to long-term average values of biogeoclimatic indices in a time- and space-varying fashion from climate–vegetation equilibrium models. Proposed Dynamic Ecosystem Classification and Productivity (DECP) model is based on the spatial interpolation of annual biogeoclimatic variables through multiple linear regression (MLR) models and inverse distance weighting (IDW) and was applied to the entire Turkey of 780,595 km2 on a 500 m × 500 m grid resolution. Estimated total net primary production (TNPP) values of mutually exclusive PFTs ranged from 108 ± 26 to 891 ± 207 Tg C yr-1 under the optimal conditions and from 16 ± 7 to 58 ± 23 Tg C yr-1 under the growth-limiting conditions for all the natural ecosystems in Turkey. Total NPP values of coexisting PFTs ranged from 178 ± 36 to 1231 ± 253 Tg C yr-1 under the optimal conditions and from 23 ± 8 to 92 ± 31 Tg C yr-1 under the growth-limiting conditions. The national steady state soil organic carbon (SOC) storage in the surface one meter of soil was estimated to range from 7.5 ± 1.8 to 36.7 ± 7.8 Pg C yr-1 under the optimal conditions and from 1.3 ± 0.7 to 5.8 ± 2.6 Pg C yr-1 under the limiting conditions, with the national range of 1.3 to 36.7 Pg C elucidating 0.1% and 2.8% of the global SOC value (1272.4 Pg C), respectively. Our comparisons with literature compilations indicate that estimated patterns of biogeoclimate zones, PFTs, TNPP and SOC storage by the DECP model agree reasonably well with measurements from field and remotely sensed data.

Infrared drying of strawberry

The effects of different drying conditions, such as infrared power, drying air temperature and velocity, on quality of strawberry were evaluated. Drying time decreased with increased infrared power, air temperature and velocity. An increase in power from 100W to 300W, temperature from 60 to 80°C and velocity from 1.0m.s-1 to 2.0m.s-1 decreased fruit color quality index. For total phenol and anthocyanin content, 300W, 60°C, and 1.0m.s-1 were superior to the other experimental conditions. The drying processes increased N, P and K and decreased Ca, Mg, Fe, Mn, Zn and Cu contents. The optimal conditions to preserve nutrients in infrared drying of strawberry were 200W, 100°C and 1.5m.s-1.

Statistical Modeling of Spatio-Temporal Variability in Monthly Average Daily Solar Radiation over Turkey

Though one of the most significant driving forces behind ecological processes such as biogeochemical cycles and energy flows, solar radiation data are limited or non-existent by conventional ground-based measurements, and thus, often estimated from other meteorological data through (geo)statistical models. In this study, spatial and temporal patterns of monthly average daily solar radiation on a horizontal surface at the ground level were quantified using 130 climate stations for the entire Turkey and its conventionally-accepted seven geographical regions through multiple linear regression (MLR) models as a function of latitude, longitude, altitude, aspect, distance to sea; minimum, maximum and mean air temperature and relative humidity, soil temperature, cloudiness, precipitation, pan evapotranspiration, day length, maximum possible sunshine duration, monthly average daily extraterrestrial solar radiation, and time (month), and universal kriging method. The resulting 20 regional best-fit MLR models (three MLR models for each region) based on parameterization datasets had R2adj values of 91.5% for the Central Anatolia region to 98.0% for the Southeast Anatolia region. Validation of the best-fit MLR models for each region led to R2 values of 87.7% for the Mediterranean region to 98.5% for the Southeast Anatolia region. The best-fit anisotropic semi-variogram models for universal kriging as a result of one-leave-out cross-validation gave rise to R2 values of 10.9% in July to 52.4% in November. Surface maps of monthly average daily solar radiation were generated over Turkey, with a grid resolution of 500 m × 500 m.

A comprehensive review of thin-layer drying models used in agricultural products

ABSTRACT Drying is one of the widely used methods of grain, fruit, and vegetable preservation. The important aim of drying is to reduce the moisture content and thereby increase the lifetime of products by limiting enzymatic and oxidative degradation. In addition, by reducing the amount of water, drying reduces the crop losses, improves the quality of dried products, and facilitates its transportation, handling, and storage requirements. Drying is a process comprising simultaneous heat and mass transfer within the material, and between the surface of the material and the surrounding media. Many models have been used to describe the drying process for different agricultural products. These models are used to estimate drying time of several products under different drying conditions, and how to increase the drying process efficiency and also to generalize drying curves, for the design and operation of dryers. Several investigators have proposed numerous mathematical models for thin-layer drying of many agricultural products. This study gives a comprehensive review of more than 100 different semitheoretical and empirical thin-layer drying models used in agricultural products and evaluates the statistical criteria for the determination of appropriate model.

Assessing monthly average solar radiation models: a comparative case study in Turkey

Solar radiation data are required by solar engineers, architects, agriculturists, and hydrologists for many applications such as solar heating, cooking, drying, and interior illumination of buildings. In order to achieve this, numerous empirical models have been developed all over the world to predict solar radiation. The main objective of this study is to examine and compare 147 solar radiation models available in the literature for the prediction of monthly solar radiation at Ankara (Turkey) based on selected statistical measures such as percentage error, mean percentage error, root mean square error, mean bias error, and correlation coefficient. Our results showed that Ball et al. (Agron J 96:391–397, 2004) model and Chen et al. (Energy Convers Manag 47:2859–2866, 2006) model performed best in the estimation of solar radiation on a horizontal surface for Ankara.