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The article discusses the problems associated with the tourism industry and the hotel business during the pandemic. A study was carried out and relevant conclusions were presented on how the pandemic affected the hotel business in Europe and Russia. The authors examined and analyzed in detail the indicators of forecasts in the sphere of the Russian hotel business, particularly in the regions. The authors paid special attention to the study of open public spaces and conducted a detailed analysis, which made it possible to identify the opportunities for the development of the hotel business. In the article the main trends of a pandemic and post-pandemic are studied – the need to reinforce sanitary measures. The research focuses on identifying the features of the economic state of the regions during the pandemic. The authors developed and substantiated the areas that are relevant, useful and applicable for the hotel business; revealed the features of the process of restoration of the hotel business. Special attention is paid to the study of state support measures; the features of their further actualization for the development of the tourism industry are presented. The authors have proposed the ways to overcome the crisis, contributing to a slow, but accurate and safe recovery of the hotel business and an increase in demand.

The process of combusting Tuva coals before and after their carbonization was studied using the methods of thermogravimetric analysis and electron microscopy. Coal samples were subjected to thermomechanical and elemental analysis, which revealed a higher content of volatile substances in Kaa-Khem coal (47.5 %) compared to Chadan coal (10 %). Following carbonization, a decrease in volatile substances to 11.5 % and 9.3 %, respectively, was observed. The conducted thermogravimetric analysis showed the ignition temperature of the coke residue of the Kaa-Khem and Chadan coal samples to increase by 76 °C and 90 °C, respectively, after carbonization. The burnup temperature of the coke residue after carbonizing (723 °C) Kaa-Khem coal samples remained effectively the same, while the Chadan coal showed an increase from 704 °C to 727 °C. The carbonization of coals was established to decrease the maximum reaction rate from 19 % per min to 10% per min for Kaa-Khem coal and from 26 % per min to 11 % per min for Chadan coal. The process of combusting the coke residue after coal carbonization was found to shift into the region of higher temperatures: from 448–723°C to 524–724°C for Kaa-Khem coal and from 436–704 °C to 526–727 °C for Chadan coal. A morphological analysis of the surface of coal particles after carbonization showed the appearance of larger-size pores and cracks on the surface of carbonates compared to coal before carbonization. The conclusion is made that the content of volatile substances, rather than the developed pore structure, comprises the main factor in improving the combustion characteristics of Tuva coals under the conditions of non-isothermal heating before and after their carbonization.

Abstract Two systems of hydraulic mixing in a vertical cylindrical anaerobic digester: standard and modernised are discussed in the paper. Numerical investigations that were carried out are focused on a study of hydrodynamic processes in an aerobic digester using two various systems of hydraulic mixing as well as on analysis of the efficiency of methane fermentation process accomplished under different geometric parameters of an anaerobic digester and systems of hydraulic mixing.

AbstractA common control strategy for the production of recombinant proteins in Pichia pastoris using the alcohol oxidase 1 (AOX1) promotor is to separate the bioprocess into two main phases: biomass generation on glycerol and protein production via methanol induction. This study reports the establishment of a soft sensor for the prediction of biomass concentration that adapts automatically to these distinct phases. A hybrid approach combining mechanistic (carbon balance) and data‐driven modeling (multiple linear regression) is used for this purpose. The model parameters are dynamically adapted according to the current process phase using a multilevel phase detection algorithm. This algorithm is based on the online data of CO2 in the off‐gas (absolute value and first derivative) and cumulative base feed. The evaluation of the model resulted in a mean relative prediction error of 5.52% and R² of .96 for the entire process. The resulting model was implemented as a soft sensor for the online monitoring of the P. pastoris bioprocess. The soft sensor can be used for quality control and as input to process control systems, for example, for methanol control.

AbstractSmart Grids are electrical grids that require a decentralised way of controlling electric power conditioning and thereby control the production and distribution of energy. Yet, the integration of Distributed Renewable Energy Sources (DRESs) in the Smart Grid introduces new challenges with regards to electrical grid balancing and storing of electrical energy, as well as additional monetary costs. Furthermore, the future smart grid also has to take over the provision of Ancillary Services (ASs). In this paper, a distributed ICT infrastructure to solve such challenges, specifically related to ASs in future Smart Grids, is described. The proposed infrastructure is developed on the basis of the Smart Grid Architecture Model (SGAM) framework, which is defined by the European Commission in Smart Grid Mandate M/490. A testbed that provides a flexible, secure, and low-cost version of this architecture, illustrating the separation of systems and responsibilities, and supporting both emulated DRESs and real hardware has been developed. The resulting system supports the integration of a variety of DRESs with a secure two-way communication channel between the monitoring and controlling components. It assists in the analysis of various inter-operabilities and in the verification of eventual system designs. To validate the system design, the mapping of the proposed architecture to the testbed is presented. Further work will help improve the architecture in two directions; first, by investigating specific-purpose use cases, instantiated using this more generic framework; and second, by investigating the effects a realistic number and variety of connected devices within different grid configurations has on the testbed infrastructure.

Computational fluid dynamics (CFD) studies are carried out on a two-bladed vertical axis wind turbine operating at a wind speed of 8 m/s for tip speed ratios (λ) of 0.50–3.0. The blade is the NACA0021 airfoil with chord length 0.265 m and rotor radius 1 m. Basic sensitivity studies for various time step sizes are carried out. The results are validated against available measurement data from the literature. Excellent agreement is obtained for small λ up to optimum condition. For the higher tip speed ratios, the two-dimensional CFD computations predict higher results than the wind tunnel experiment, but they are very similar to the field measurement data. Wake characteristics are presented, showing that the wake becomes Gaussian at 5 times radius downstream of the rotor. It is shown that complex flow phenomena occur owing to dynamic stall onset, especially for the smaller tip speed ratio.

Alkali activated concretes have emerged as a prospective alternative to conventional concrete wherein diverse waste materials have been converted as valuable spin-offs. This paper presents a wide experimental study on the sustainability of employing waste sawdust as a fine/coarse aggregate replacement incorporating fly ash (FA) and granulated blast furnace slag (GBFS) to make high-performance cement-free lightweight concretes. Waste sawdust was replaced with aggregate at 0, 25, 50, 75, and 100 vol% incorporating alkali binder, including 70% FA and 30% GBFS. The blend was activated using a low sodium hydroxide concentration (2 M). The acoustic, thermal, and predicted engineering properties of concretes were evaluated, and the life cycle of various mixtures were calculated to investigate the sustainability of concrete. Besides this, by using the available experimental test database, an optimized Artificial Neural Network (ANN) was developed to estimate the mechanical properties of the designed alkali-activated mortar mixes depending on each sawdust volume percentage. Based on the findings, it was found that the sound absorption and reduction in thermal conductivity were enhanced with increasing sawdust contents. The compressive strengths of the specimens were found to be influenced by the sawdust content and the strength dropped from 65 to 48 MPa with the corresponding increase in the sawdust levels from 0% up to 100%. The results also showed that the emissions of carbon dioxide, energy utilization, and outlay tended to drop with an increase in the amount of sawdust and show more the lightweight concrete to be more sustainable for construction applications.