Vol 53, No 2 (2019)

The possibility of high-precision determination of mass transfer characteristics of stainless steel packings in the separation of hydrogen and oxygen isotopes by vacuum distillation of water in columns with a diameter of 60–250 mm was shown. An algorithm for calculating the parameters of separation and the concentration profile of deuterium and oxygen-18 during their simultaneous separation in a closed type unit with product selection by vacuum distillation of water was presented.

Biorefineries have been widely studied during the last years and proposed as the best option to transform biomass systems into value-added products. Different methodologies have been proposed for the design of biorefineries: knowledge-based approach, early-stage approach, and superstructures, among others, which have been coupled to process improvement schemes as pinch analysis and process intensification. Regarding process design, it is necessary to ensure that the most advanced concepts are applied on the design to ensure efficient processes that direct to more sustainable processes. The processes that are currently being designed as biorefineries in many cases cannot be considered as completely efficient, because they are generally biased to designs based only in typical methods of process engineering. It is still necessary to implement further design strategies focused on increasing the efficiency and decreasing energy consumption. Multiple methods have been used for the design and improvement of chemical/biotechnological processes. Among these, shortcut methods, especially thermodynamic-topological analysis, are highlighted as a useful tool in the process engineering stage of a given process and might be useful to decrease energy consumption and to increase the efficiency since the design stage. This work proposes a design strategy for biorefineries using a shortcut method as the thermodynamic-topological analysis. For this, a biorefinery based on cocoyam, which is a rural raw material with a high potential for the obtainment of added-value products, was used as a case study. The chosen products were ethanol, lactic acid, starch, and feed additive. The biorefinery was simulated in Aspen Plus. Thermodynamic-topological analysis was implemented in the proposed biorefinery and both biorefineries (with and without the application of thermodynamic-topological analysis) were assessed in economic, environmental, efficiency, and energy-consumption terms. It was determined that the application of thermodynamic-topological analysis generated a more efficient process. After the validation of the results, it was possible to establish a design strategy for biorefineries complementing the knowledge-based approach and based on thermodynamic-topological analysis.

The results of our study of the filling of a cascade of gas centrifuges with different numbers of stages for separation of nickel isotopes used in nuclear physical research and production of radioactive isotopes are presented. During the filling of the cascade, the natural mixture of nickel isotopes is separated, and the isotopes are concentrated in different cascade stages. The concentrations of nickel isotopes in the stages and flows of light and heavy fractions after the filling of the cascade were shown to depend on the number of stages in the cascade.

Based on experimental studies, the effect of gas content in the liquid behind the ridges of artificial helical roughness on film thickness and the value of the heat transfer coefficient is shown. The numerical results for the reverse currents velocity distribution and pressure difference along the ridge height and the cavity length, as well as experimental values of gas content in the liquid separation zone, arising from the flow over a regular roughness, are presented. The scale of reverse currents, their location behind the roughness ridge, and gas content depend on the height and shape of the ridge, the irrigation density, and the physical properties of the liquid. It was concluded that the gas bubbles in the liquid form in reverse current zones in the cavities of the artificial roughness due to reduced pressure compared to gas pressure at the interface and, therefore, gas suction from the interface zone. The dependence for calculating gas content via the thickness of the liquid layer in the roughness cavity is proposed.

A controlled segregated process flows principle was used to design a process of continuous mixing of granular materials with intermittent dosing of a microcomponent. Technology opportunities of mixing under reverse-pulse action on a segregated flow of a component in a drum mixer were analyzed. It was determined by experimental and analytical investigation of the mixing dynamics that the selective action of a sequence of reverse pulses on the segregated flow of the microcomponent ensures the production of a mixture the variation of the composition of which is many times smaller than a mixture in a mixer of a flow pattern that corresponds to perfect mixing.

This work presents a numerical simulation of the aerodynamics of a swirling turbulent flow in a vortex chamber of a combined pneumatic centrifugal machine with a rotor located in its upper part and consisting of a system of rotating blades. Numerical analysis of the swirling turbulent flow made it possible to determine the main patterns in the behavior of the carrier agent in the machine. As a result, a modification of the rotor blade shape is proposed, which allows the distribution change of the radial velocity field as necessary. Numerical studies have shown the promise of this approach for controlling the radial velocity component in the rotor, which is a necessary condition for the separator to operate efficiently. The conducted numerical calculations are validated using test studies and a comparison with experimental data.

The aim of the current study is to optimize the treatment of wastewater rich in starch glue issued from the card board industry by coupling coagulation and electroflotation processes. The treatment consists of maximizing the removal rate of suspended solids contained in wastewater. This study includes both batch and continuous modes. In batch mode, a model water solution was used in order to evaluate the influence of pH, current density, and coagulant concentration, which were selected as operating parameters to be optimized. The methodology of experimental research, with an orthogonal central composite plan, was approved. In order to approach the process to the industrial scale and to improve the suspended solids removal rate, a continuous mode was also studied. The purification efficiency consisting in the elimination of suspended solids exceeded 95%. Physicochemical characterization of the effluent was performed before and after the treatment in batch and continuous modes to improve the efficiency of this process. This characterization included pH, conductivity, salinity, chemical oxygen demand, biochemical oxygen demand, and suspended solids.

Based on the theory of Markov processes, a deaeration model of bulk materials in parallel and sequential operations that include mixing with a degree of mixture heterogeneity and with a compaction method is proposed. Based on one-dimensional or multidimensional Poisson laws, distribution functions over the microscopic states of a system of particles are constructed for the random relative change of a selected deaerated volume. The model is illustrated by combining these processes in the working chamber of a centrifugal device. The random porosity of the mixture is constructed using a one-dimensional Poisson equation, which is discrete in system states and continuous over time parameters, and the relevant moments were estimated using moment generating functions.

In this study, a general model for estimating the nanofluids (NFs) thermal conductivity by using a hybrid group method of data handling polynomial neural network (GMDH–PNN) has been investigated. NFs thermal conductivity was modeled as a function of nanoparticle size and volume fraction, nanoparticle and base fluid thermal conductivity, and base fluid temperature. For this purpose, a network that contains 6 hidden layers with 2 inputs in each layer and with training algorithm of least squares regression has been applied. The results showed a good accuracy for estimating the thermal conductivity of NFs with a root mean squared error (RMSE) of 0.03027 for 118 systems containing 1929 training data sets. Furthermore, the RMSE for 27 systems containing 244 data as the validation sets was 0.02843 and also mean absolute percentage errors (MAPE) for training and validation data sets were 4.47 and 4.59%, respectively. Moreover, the proposed hybrid GMDH–PNN model was compared with different models from literature for different groups of NFs. The results indicated an improvement in prediction of thermal conductivity with lower errors compared to the previous models.