In this paper a mathematical model for the soda ash drying process in a pneumatic dryer was presented. The model presents a macroscopic aspect of the drying process, for a two-phase, gas-solid system. The model is based on mass and heat transfer between the gas phase and the particle, movement of air and particles through the system, and geometric characteristics of the drying system (fan, air heater, pneumatic dryer, and cyclone). The effects of the process parameters, such as airflow, inlet air temperature, and relative humidity, temperature at the inlet of the dryer, etc., have been studied by solving the model. Also, the model was tested for different values of the capacity of wet soda and different values of the operating parameters of the heating medium. The model was implemented in MATLAB and solved with a nonlinear equations solver. Data obtained by the model were compared with industrial pneumatic dryer data for drying wet soda ash particles with good agreement.

A simulation of a single-stage evaporator system integrated with a mechanical com- pressor for a case study (concentrating the electrolytic system KNO3 – H2O) was performed. A mathematical model of the subsystem of a single-stage evaporator, a mechanical compressor, and superheated steam seeding is presented. Microsoft Excel with VBA (Visual Basic for Application) was used to solve the mathematical model. The model was solved by an iterative method where the values of the in- let stream temperature and the salt concentration in the concentrated stream at the evaporator outlet were assumed. The process parameters of the system have been determined. Since the goal of any industrial process is to minimize costs and maximize products, the impact of mean temperature difference changes on satu- ration water consumption and molar salt content in the concentrated stream was presented. 106.92 kg/h of freshwater are required to obtain 18% by weight of salt in a concentrated stream, while 432.30 kg/h of fresh water are required to obtain 25% by weight of salt in a concentrated stream. Consumption of heating steam ranged from 1760.31 to 4473.4 kg/h depending on the average temperature dif- ference. By increasing the temperature differences from 10 to 25 ◦C, the amount of transferred upper lines increases from 1025 to 2750 kW, which is an advantage of increasing the mean temperature difference. The disadvantage of the larger tem- perature difference is the increase in the power of the mechanical compressor from 97.02 to 384.12 kW.

The aims of this study were to determine improved kineticparameters in five kinetic models for oxidation of n-butane intomaleic anhydride in an industrial fixed-bed reactor, and tosimulate the reactor performance. On the basis of the measuredprocess parameters, inlet and outlet concentrations of n-butanewere calculated and then used to fit the kinetic models. Theindustrial fixed-bed reactor was approximated by 10 continuousstirred tank reactors (CSTR) connected in series. Based on thecalculated outlet concentration of n-butane from the industrialreactor, the outlet concentration of n-butane from thepenultimate reactor was calculated. Then the concentrations ofn-butane were calculated until the inlet concentration of nbutanein the first reactor was obtained. Kinetic parameterswere determined by comparing the inlet concentrations of nbutanein the first reactor with the inlet concentration of nbutaneobtained on the basis of the measured processparameters in the industrial fixed-bed reactor. Kinetic modelswith improved kinetic parameters showed better simulationresults compared to kinetic models with the existing kineticparameters. The best agreement of simulation results andmeasured values was achieved with application of the kineticmodel 2 (Equations (2a-c)). The smallest deviations ofnumerical simulation in comparison with measured values of theoutlet pressure of reaction mixture were 0.45, 0.75 and 0.75%for application of the kinetic model 3 (Equations (3a-c)). Thepercentage deviations of numerical simulation with improvedkinetic parameters and the existing kinetic parameters incomparison with measured values of inside reactor temperaturewere in the range 0.90-5.36% and in the range 4.17-9.78%(kinetic model 2, Equations (2a-c)), respectively.

The objectives of this study were to develop and validate the mathematical model (kinetic and reactor model) of composting process, as well to used validated model in order investigate the effects of the air flow rate on organic matter conversion, carbon dioxide concentration and mixture temperature. The mathematical model incorporated two microbial populations that metabolized composting material which was split into two different fractions according to its degradability (easily-degradable and hardly-degradable). Comparisons of simulation and experimental results for five dynamic state variables demonstrated that the model has very good predictions of the composting process. Simulations with validated model showed that among three dynamic state variables (organic matter conversion, carbon dioxide concentration, mixture temperature), carbon dioxide concentration is the most sensitive while organic matter conversion is the least sensitive to the change of air flow rate.

The aim of this study was to determine the composting kinetics for mixture of poultry manure and wheat straw based on the volatile solids content. Experimental data was fitted with the first-order and the nth-order kinetic model. The nth-order kinetic model showed better prediction performance than the firstorder kinetic model. For the first-order kinetic model, maximum and mean differences between experimental and simulation results for the content of volatile solids were 5.43% and 3.00%, for the first reactor, and 4.68% and 2.12% for the second reactor, respectively, for the nth-order kinetic model, maximum and mean differences were 4.92% and 1.68%, for the first reactor, and 4.09% and 1.42% for the second reactor, respectively.

Wild onion is a vegetable plant recognizable as food and folk medicine. Its greater application in the food and pharmaceutical industry has found in last decades. In food industry wild onion is mainly used as a spice, while in the pharmaceutical industry it is a common ingredient in dietary supplements. Processing of a fresh wild onion is constantly increasing. Active ingredients of wild onion are: raw vegetable fibers especially cellulose, allium compounds, chlorophyll, flavonoid, quercetin. Wild onion is used in a fresh and processed condition. In most cases it is processed by drying at 40-50 °C for 5 to 10 hours, but also the active ingredients are extracted with various technological processes. Water content in the final product ranges from 6 10% and water activity from 0,17 to 0,21. Total phenolic content was expressed as mg of gallic acid in 100 g of raw material and it was estimated as an average value 561,013. The antioxidant capacity was expressed as EC50 value that represents amount of sample required for the reduction of 50% DPPH free radicals and it was estimated as an average value 6,032. The content of the water was determined by drying. The water activity and color intensity were estimated by using instrumental methods. Antioxidant capacity was estimated by using of DPPH method and phenolic content by application of Folin-Ciocalteu calorimetry. Processing of fresh wild onion in the standardized dried semiproducts may be significant due to the conservation of biological properties, and possibility of applications in the food and pharmaceutical industries. Abbreviations: DPPH-2,2-diphenyl-1-picrylhydrazyl; EC50, concentration of antioxidant needed to reduce the original amount of radical by 50%.