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In this study, the household consumption-related ecological footprint of lifestyles linked to panel housing estates and suburban neighbourhoods were compared in the case of Budapest and its suburbs. Our results show that the biggest parts of the ecological footprint are in both study areas the carbon, the cropland and the forest components, in line with earlier calculations. On the whole, the ecological footprint values are bigger in the suburban study area (2.63 gha/capita) compared to the panel housing estates (2.29 gha/capita), mainly because of the differences between the carbon uptake and the built-up land components. Beyond comparing the ecological footprint values of different residential areas, the study also contributes to the literature by addressing the improvement options of the respective areas through a rough model calculation on the reduction opportunities in both cases, resulting 36 percent in case of panel housing estates, and 47 percent in the suburban areas. Although these values have to be considered cautiously, they show significant opportunities in ecological footprint reduction in both types of residential areas supported by individual motivations, as well as by policy measures.

In this study a 2D visualization technique is presented that is suitable for determining the optimal operational parameters of solid waste gasification depending on the intended use of the product. Steam gasification of different wastes (wheat straw, wood, municipal solid waste (MSW), polyethylene (PE), green waste) was modelled in Aspen Plus simulation software, validated with literature data and a MATLAB – Aspen Plus inter software connection was also created to minimize the possibility of errors when the raw material composition and other parameters are changed. Correlation was found between the simulation and literature data; therefore, the model was also suitable for evaluating the effects of process parameters (T = 650–1100 °C, steam rate = 0–1.5 kg/h) on gas composition, lower heating value and H2/CO ratio. The model was also extended to a wide range of domestic waste types, making it possible to determine the optimal process parameters without performing a high number of time- and energy-intensive gasification experiments. Regarding the process parameters it was established that the temperature has a significant effect on the gasification reactions and shifts the chemical reactions towards hydrogen and carbon monoxide formation, but above 800 °C it has a limited effect on the gas composition, lower heating value and H2/CO ratio. The increasing steam rate also facilitated the hydrogen and carbon monoxide formation, but above a certain ratio its effect was opposite due to the water-gas shift reaction and the shorter residence times. The obtained gases can be used for energy purposes or as raw material for Low-Temperature Fischer-Tropsch synthesis, or production of aldehyde, higher alcohol, acetic acid or even polycarbonate for which the optimal temperatures and steam rates were also determined.

Manufacturers use a large number of components in the production of modern rubber products. The selection of the constituents of the rubber recipe is primarily determined by the purpose of use. The different fields of applications of rubbers require the presence of appropriate mechanical properties. In this respect, it can be useful to know which substances forming the rubber recipe have significant influence on the different mechanical properties. In this study, the statistical analysis of the influence of rubber components on the hardness of natural rubber (NR) is proposed based on literature review. Based on the literature data, various statistical analyses, like linear regression, constrained linear regression, Ridge regression, Ridge sparse regression and binary classification decision trees were performed to determine which rubber components have the most significant effect on the hardness. In the statistical analyses, the effect of a total of 42 constituents of rubber compound on hardness was investigated. Most of the applied statistical methods confirmed that the traditional frequently used rubber components, such as carbon black and sulfur, have a primary effect on the hardness. However, the substances forming the rubber compound that are not widely used in practice or newly developed components appear differently in the lists of significant additives obtained by the different statistical methods.

In this article, the authors focus on the introduction of a hybrid method for risk-based fault detection (FD) using dynamic principal component analysis (DPCA) and failure method and effect analysis (FMEA) based Bayesian networks (BNs). The FD problem has garnered great interest in industrial application, yet methods for integrating process risk into the detection procedure are still scarce. It is, however, critical to assess the risk each possible process fault holds to differentiate between non-safety-critical and safety-critical abnormalities and thus minimize alarm rates. The proposed method utilizes a BN established through FMEA analysis of the supervised process and the results of dynamical principal component analysis to estimate a modified risk priority number (RPN) of different process states. The RPN is used parallel to the FD procedure, incorporating the results of both to differentiate between process abnormalities and highlight critical issues. The method is showcased using an industrial benchmark problem as well as the model of a reactor utilized in the emerging liquid organic hydrogen carrier (LOHC) technology.

In Hungary, post-war housing estates can be categorised according to the time of their construction. Thanks to the development of construction technologies and urban planning, these so-called generations of housing estates demonstrate different features with regard to their physical layout and socio-economic characteristics. Socio-economic transformation that took place after the change of regime (1989) was widely affected by the physical parameters of these neighbourhoods and their dwelling stock. Our results show that different generations of housing estates have followed distinct trajectories in the housing market; thus, in addition to their geographical location within the city, planning, architecture, design, and the dwelling stock play a significant role in the market positions of these generations of housing estates. House prices have risen rapidly in Budapest since 2014 up until the pandemic in 2020, and housing estates became popular segments of the housing market. The main aim of this article is to investigate the role of urban planning, architecture and the built environment in this real estate process. The research is based on empirical real estate investigations, statistical house price analyses, and fieldwork undertaken on housing estates. The case study area is Csepel, a former industrial town which became the administrative district 21 of Budapest in 1950. All types of post-war generations of housing estates co-exist, and the majority of the population lives in such neighbourhoods. This special geographical context makes it possible to explore the influential role of the built environment in the housing market. Empirical results from these low- and mid-rise housing estates can make a major contribution to the more effective and successful development of high-rise neighbourhoods.

In recent years the topic of additive manufacturing has become quite popular in industrial applications and scientific studies. However, the rapid development in this field, especially the slicer and machine software, makes research difficult because these can become obsolete due to software improvements. Another impeding aspect is the lack of knowledge and interest in the field of 3D printing or additive manufacturing process and materials; primarily, 3D printing is seen as a tool to achieve some results by researchers. Due to these facts, most studies do not discuss 3D printing parameters properly, making reproducing results almost impossible. This paper discusses three 3D printing parameters that affect the properties of final products made by different chopped fibre filled- and generic nylon filaments; these parameters are the printing temperature, nozzle diameter, layer height, infill orientation and wall line count (or perimeter count). The family of nylon filaments is mainly used for functional 3D printing, especially in replacing aluminium and steel parts, thanks to their mechanical and thermal properties. Furthermore, a polynomial function was fitted to the measured data points, which made it possible to calculate the tensile strength and ductility of the 3D-printed samples based on their printing parameters.

The properties of 3D-printed bodies are an essential part of both the industrial and research sectors, as the manufacturers try to improve them in order to make this now additive manufacturing method more appealing compared to conventional manufacturing methods, like injection moulding. Great achievements were accomplished in both 3D printing materials and machines that made 3D printing a viable way to produce parts in recent years. However, in terms of printing parameters, there is still much room for advancements. This paper discusses four of the 3D printing parameters that affect the properties of the final products made by chopped glass fibre-filled nylon filaments; these parameters are the printing temperature, nozzle diameter, layer height, and infill orientation. Furthermore, a polynomial function was fitted to the measured data points, which made it possible to calculate the tensile strength, flexural strength, and Young’s modulus of the 3D-printed samples based on their printing parameters. A Pearson correlation analysis was also carried out to determine the impact of each parameter on all three mechanical properties studied. Both the infill orientation and printing temperature had a significant effect on both strengths and Young’s modulus, while the effect of nozzle diameters and layer heights were dependent on the infill orientation used. Also, a model with excellent performance was established to predict the three mechanical properties of the samples based on the four major parameters used. As expected from a fibre-reinforced material, the infill orientation had the most significant effect on the tensile strength, flexural strength, and Young’s modulus. The temperature was also quite significant, while the nozzle diameters and layer height effect were situational. The highest values for the tensile strength, flexural strength, and Young’s modulus were 72 MPa, 78.63 MPa, and 4243 MPa, respectively, which are around the same values the manufacturer states.

One of the most critical components of the chemical industry in terms of crystallisation is the pharmaceutical sector. Most medicine components are expensive and require complex processes for their production, so producing waste is highly inefficient. Another concern is the high-quality standards for most pharmaceutical products. Therefore, optimising the crystallisation process is critical from a quality perspective, with the main concerns being the product's crystal structure and particle diameter distribution. Regardless efficient control in batch processes such as crystallisation is a difficult task due to the inherently nonlinear behaviour of the system. Using a priori model of the system as the basis for nonlinear model predictive control could provide a useful tool for handling the crystallisation process, mitigating the effects of disturbance and noise and ensuring appropriate product quality. In this work, we wish to showcase the possibility of controlling a crystallisation process using model predictive control to enable the production of crystal products with desired particle diameter distribution and crystalline product average size. The method is shown using citric acid as a model substance in a case study of a continuous crystallisation procedure in a stirred tank reactor. The crystalliser model includes an energy balance, so the system's behaviour depends on the cooling rate and residence time. Accordingly, the control problem can be formulated as multiple inputs and multiple outputs (MIMO) system. Moreover, the two controlled (average particle size and crystal size dispersion) variables are not easily detached from each other. So, the traditional controlling strategies, for example, the decoupling controller, is challenging to apply. The MPC (model predictive control) as an advanced control algorithm can be a solution to this.

Coke oven gas is a by-product of coke production. Cleaned coke oven gas can be a valuable energy source, ideal as a substitute for natural gas. However, to meet increasingly stringent environmental regulations and to protect combustion equipment, the high efficiency of the coke oven gas purification process must be ensured continuously, even for existing, less up-to-date plants. Process simulators built to support technologies can be a great help in this task. At the same time, they can be used to assist operations, understand general and specific process behaviour features, and examine development suggestions. The H2S scrubber of an existing coke oven gas purification plant was investigated in this study. Previously, the steady-state model of the purification process was studied, and the impact of operating parameters was investigated. Then the dynamic model of the purification process was created in Aspen Hysys simulator software. Finally, the model was validated against laboratory analyses and daily operational plant data. Subsequently, the control structure of the purification process was studied. It was concluded that the control system used in the coke oven gas purification plant is rather elementary and is primarily designed to ensure the safe operation of the technology. However, a more complex advanced control structure is needed to continuously provide a constant gas composition, in which the dynamic model of the technology is a great support. In this study, two examples for improving the control structure of the process were presented using the dynamic model of the H2S scrubber.

In the post-industrial age, the transformation of urban networks and urban regions was fundamentally influenced by the rapid spread of infocommunication technologies (ICT) and the Internet. People share information in their daily lives with the help of various ICT devices and ultimately generate georeferenced data that could obtain important information about people’s use of space, spatial movement and social connections. The main aim of the study is to explore the urban geographical and spatial impacts of ICT and social media networks in Hungarian cities. We focus on drawing territorial and settlement hierarchical patterns and clusters based on the mobile communication and online social network relationship data of Hungarian cities. The paper highlights the relationship between the intensity of mobile communication and the density and expansion of intercity social relations and the settlements’ level of economic development, respectively. The methodology is based on mobile phone call detail record (CDR) analysis and intercity network analysis of social media activities. Our findings suggest that different communication networks follow divergent spatial patterns in Hungary. The traditional East–West dichotomy of the Hungarian spatial divide is still reflected in mobile communication, but intercity clusters based on social media activities are usually aligned to the borders of administrative structures. In several cases, we were able to identify strong intercity links between settlements with a similar level of economic development of the mesolevel spatial structure that traverses over different counties and regional borders. Results on social and demographic issues suggest that ‘generation Z’ could play a key role in dampening the social and economic tensions created by the digital divide in the long run. Using a multidimensional explanatory model, we could demonstrate the growing interconnectedness between digital networks and economic development.

The application of renewables is one of the key aspects of the design of sustainable processes. Biomass has a high interest as a feedstock, mostly because of the conversion potential to valuable products, e.g. syngas (containing hydrogen and carbon monoxide). Regarding sustainability and global climate change, carbon dioxide reduction, capture and storage are important tasks of waste-derived syngas production. There are many possibilities for the further handling of syngas to reduce the carbon dioxide concentrations, such as absorption, adsorption etc. The main goal of this study is to optimise the parameters and design the key operating units of different scenarios for carbon dioxide reduction (absorption by monoethanolamine (MEA) solution, cryogenic distillation, Ca-looping) from biomass-derived syngas. Pyrolysis-reforming of the biomass has been performed in a multizone horizontal tubular reactor using different process parameters. Gas fraction has been analysed by gas-chromatography, then based on the result, the key process parameters were identified focusing on the techno-economical approach of the different scenarios. The CO2 removal efficiencies obtained by cryogenic distillation and Ca-looping were nearly the same. Meanwhile, the amine solution absorbed 83.5 % of the CO2 content of the feedstock. The capital expenditures of the absorption, cryogenic distillation and Ca-looping were 1,587,000, 2,633,000 and 1,555,000 USD, respectively. The calculated values of the operating expenditures (OPEX) changed between 42,000 and 529,000 USD/year, while according to the expectations, the highest OPEX was observed in cryogenic distillation. Based on the results, it was found that the best available technology for CO2 removal is absorption using MEA solution.

Loess-paleosol bluffs can be unstable, but in the course of urbanization, houses may be built in such locations to take advantage of the view. One factor affecting the stability of such bluffs is water, the role of which in mass movements is well established. In this study, the connection of mass movements to meteorological conditions, such as rainfall and subsequent water level changes, was researched using new statistical methods. The periodicity of the water level of the Danube was analyzed using wavelet spectrum analyses, while changepoint analysis was used to determine variations in the quantity of precipitation. These results were compared to the chronology of six mass movements in Kulcs, Hungary. This study also focused on the changes in geochemical properties of loess in different weather conditions (dry periods, wet periods, and flooding). The results showed that only two mass movements were connected to hydrological conditions, and in the other case human activity and geochemical changes may have been factors. The results of geochemical models created using PHREEQC showed calcite and kaolinite precipitation, and albite and dolomite dissolution as the main mineral changes over the course of a year. Albite was found to dissolve only in wet periods, and kaolinite precipitation was significant during flood periods.

In this simulation study, we compare the dynamics and thermal behavior of different ideal flow crystallizers. The first step in creating mathematical models for the crystallizers was the implementation of the population balance equation. The population balance equation was completed with mass balance equations for the solute and the solvent as well as in the case of non-isothermal crystallizers with an energy balance equation. The solution to the population balance equation, which is a partial differential equation, can only be performed numerically. Using the method of moments, which calculates the moments of the population density function, gives a mathematically simpler model for simulating and analyzing the crystallizers. All crystallizers studied are considered mixed suspension and mixed product crystallizers. In this simulation study, the investigated crystallizers are the batch mixed suspension and mixed product isothermal crystallizer, the batch mixed suspension and mixed product non-isothermal crystallizer, and the continuous mixed suspension and mixed product removal (CMSMPR) non-isothermal crystallizer equipped with a cooling jacket. We consider citric acid as the solid material to be crystallized, and a water–glycol system is used as a cooling medium. Considering the nucleation kinetics, we applied both primary and secondary nucleation. In the case of a crystal growth kinetic, we assumed a size-independent growth rate. The highest expected value and the variance of the crystal product occur in the isotherm batch case, which can be explained by the high crystallization rate caused by the high supersaturation. Contrary to this, in the non-isothermal batch case, the final mean particle size and variance are the lowest. In continuous mode, the variance and mean values are between the values obtained in the two other cases. In this case, the supersaturation is maintained at a constant level in the steady state, and the average residence time of the crystal particles also has an important influence on the crystal size distribution. In the case of non-isothermal crystallization, the simulation studies show that the application of the energy balance provides different dynamics for the crystallizers. The implementation of an energy balances into the mathematical model enables the calculation of the thermal behavior of the crystallizers, enabling the model to be used more widely.

In this article, the authors focus on the introduction of a hybrid method for risk-based fault detection (FD) using dynamic principal component analysis (DPCA) and failure method and effect analysis (FMEA) based Bayesian networks (BNs). The FD problem has garnered great interest in industrial application, yet methods for integrating process risk into the detection procedure are still scarce. It is, however, critical to assess the risk each possible process fault holds to differentiate between non-safety-critical and safety-critical abnormalities and thus minimize alarm rates. The proposed method utilizes a BN established through FMEA analysis of the supervised process and the results of dynamical principal component analysis to estimate a modified risk priority number (RPN) of different process states. The RPN is used parallel to the FD procedure, incorporating the results of both to differentiate between process abnormalities and highlight critical issues. The method is showcased using an industrial benchmark problem as well as the model of a reactor utilized in the emerging liquid organic hydrogen carrier (LOHC) technology. [ABSTRACT FROM AUTHOR]

In recent years, one of the most important challenges worldwide is to meet increasingly stricter environmental regulations while maintaining the profitability of plants. Modelling particular parts of existing technologies can help efficient operation, reduce energy consumption, minimize emissions, and keep operating costs low. Furthermore, adequately validated models provide the opportunity to examine different equipment designs, operating parameters side by side without hindering the technological process. The coke oven gas purification technology of a Hungarian coke oven plant was studied in this research work. As a by-product of coke production, approximately 40,000 - 60,000 m3 crude coke oven gas is generated every hour, which has to be cleaned before being used for energy purposes. First, the cooled crude coke oven gas is fed into the hydrogen sulfide scrubber in a counter-current flow. Then, the hydrogen sulfide is absorbed in an ammonia-rich washing liquid coming from the following two ammonia scrubbers. In this study, two mathematical models, equilibrium-stage and rate-based models, were used to simulate the removal of H2S from coke oven gas in the Aspen Plus process simulator program. The validation of the models was performed by using the operating measurements of the outlet streams. The results closely approximate the measured composition of the outflows. However, the simulation results predicted by the rate-based model show better agreement than the equilibrium model compared with the experimental data. With the use of the rate-based model, a sensitivity analysis was made, taking into account the parameters that have a tremendous impact on the cleaning process and can also be controlled by appropriate intervention. The creation of this model was the first step in building the simulation of the entire gas purification process, which will be used to optimize the operation and create an operator training system.

The 21st century has brought fundamental changes in the development of cities, with the spread of ICT and the rise of digitalization. The new technologies are increasingly making their mark on urban planning and policy as well. The question of how contemporary urban planning is adapting to new challenges is particularly relevant as neighborhoods built in previous centuries and decades by traditional planning methods are now increasingly confronted with new public and environmental demands. Despite the bad reputation of Budapest’s 8th district, Józsefváros, based on the socio-economic and urban problems it has continuously faced in the past, the neighborhood has become one of the most dynamically developing urban areas in the last decade. From a planning point of view, an exciting area of the district is Szigony Street and its wider surroundings due to the strongly fragmented, heterogeneous urban fabric. Nevertheless, the only high-rise mass housing estate built in Budapest’s historic inner city in the 1960s and 1970s is located there. Our research used a complex methodology (document, content and database analysis, fieldwork, surveys with professionals, and interviews) to explore the planning history of the area’s development. Ultimately, the aim was to identify the most important outcomes and consequences of traditional and contemporary planning and design and whether modern digital planning can make a meaningful contribution to the development of the neighborhood. Our results show that urban planning and development in Budapest are still essentially based on traditional top-down approaches. Digitalization has a role to play primarily in visualization and contextualization but digitalizing of planning alone will not solve problems and past planning mistakes that affect the urban fabric of a neighborhood.

Hydrogen is one of the key components in renewable energy systems. Its storage and transport, however, are challenging. The Liquid Organic Hydrogen Carrier (LOHC) technology is a possible solution for this issue. With suitable organic components, hydrogen can be stored in a chemically bound form which is safer and has a higher energy density than other solutions. Furthermore, the storage and transport of the LOHC component with high hydrogen content can be provided under normal environmental conditions. The LOHC process cycle involves a catalytic hydrogenation and dehydrogenation step where the LOHC component can be recovered and recycled. The paper reviews a few relevant studies regarding the possible LOHC compound pairs, the potential catalyst systems, and the necessary equipment. Then, the paper discusses a simulation study of three LOHC systems, determining suitable operating conditions and estimating costs. The toluene-methylcyclohexane system was found to be the most promising for LOHC application. Two energy integration opportunities were also examined. The first case study was based on separate hydrogenation and dehydrogenation sites, while the second was based on one site utilization. The results show a lower energy demand in the case of a toluene system, with a reduction of 70% in heating and 45% in cooling. [ABSTRACT FROM AUTHOR]

In this study, the household consumption-related ecological footprint of lifestyles linked to panel housing estates and suburban neighbourhoods were compared in the case of Budapest and its suburbs. Our results show that the biggest parts of the ecological footprint are in both study areas the carbon, the cropland and the forest components, in line with earlier calculations. On the whole, the ecological footprint values are bigger in the suburban study area (2.63 gha/capita) compared to the panel housing estates (2.29 gha/capita), mainly because of the differences between the carbon uptake and the built-up land components. Beyond comparing the ecological footprint values of different residential areas, the study also contributes to the literature by addressing the improvement options of the respective areas through a rough model calculation on the reduction opportunities in both cases, resulting 36 percent in case of panel housing estates, and 47 percent in the suburban areas. Although these values have to be considered cautiously, they show significant opportunities in ecological footprint reduction in both types of residential areas supported by individual motivations, as well as by policy measures. [ABSTRACT FROM AUTHOR]

Turbulences in energy prices have a major effect on the energy industry. These disturbances should allow more efficient operation and the optimisation of technologies, leading to more versatile operation with model-based methods. In our study, a coke oven gas purification system was examined. The system consists of three columns, which interact and are modelled in Aspen Plus. After identifying the steady-state model, sensitivity analyses were conducted to obtain more information on the effects of the parameters that can and cannot be influenced by operating circumstances. Finally, the model was used to carry out optimisation studies to find the most beneficial operating conditions under the gas composition requirements. Two optimisation strategies were examined. In the case when only the purity was concerned, 0.54 g/Nm3, 0.01 g/Nm3, and 0.03 g/Nm3 concentrations were found for H2S, NH3, and HCN, respectively. However, when the washing water temperature was included, the concentrations of H2S, NH3, and HCN increased to 1 g/Nm3, 0.5 g/Nm3, and 0.04 g/Nm3, still below the environmental regulations. However, the latter case will be more feasible energetically because it can be completed without using refrigeration and facilitates lower washing water streams.

The Hungarian economy has gone through rapid transformation and modernization since the political changes of 1989/90. One of the signs of successful economic restructuring and re-integration to the world economy was the growing role of creative economy. In the present paper we analyse the changing geographical pattern of creative economy in Hungary, based on longitudinal statistical data. Our findings suggest growing core-periphery relations in the spatial pattern of creative economy, especially cince the recent financial crisis. The relative weight of Budapest and its urban region has been continuously growing and even major regional centres are unable to keep pace with the Hungarian capital. We also found that cities in the Hungarian urban system became highly differentiated according to their attractiveness for creative firms and labour, and there is a growing competition among secondary cities for knowledge based and creative activities. The growing geographical concentration of the creative economy (especially the knowledge intensive industries) is partly the result of previous neoliberal regional and urban policies.

The properties of 3D-printed bodies are an essential part of both the industrial and research sectors, as the manufacturers try to improve them in order to make this now additive manufacturing method more appealing compared to conventional manufacturing methods, like injection moulding. Great achievements were accomplished in both 3D printing materials and machines that made 3D printing a viable way to produce parts in recent years. However, in terms of printing parameters, there is still much room for advancements. This paper discusses four of the 3D printing parameters that affect the properties of the final products made by chopped glass fibre-filled nylon filaments; these parameters are the printing temperature, nozzle diameter, layer height, and infill orientation. Furthermore, a polynomial function was fitted to the measured data points, which made it possible to calculate the tensile strength, flexural strength, and Young's modulus of the 3D-printed samples based on their printing parameters. A Pearson correlation analysis was also carried out to determine the impact of each parameter on all three mechanical properties studied. Both the infill orientation and printing temperature had a significant effect on both strengths and Young's modulus, while the effect of nozzle diameters and layer heights were dependent on the infill orientation used. Also, a model with excellent performance was established to predict the three mechanical properties of the samples based on the four major parameters used. As expected from a fibre-reinforced material, the infill orientation had the most significant effect on the tensile strength, flexural strength, and Young's modulus. The temperature was also quite significant, while the nozzle diameters and layer height effect were situational. The highest values for the tensile strength, flexural strength, and Young's modulus were 72 MPa, 78.63 MPa, and 4243 MPa, respectively, which are around the same values the manufacturer states. [ABSTRACT FROM AUTHOR]

Sedimentation is important in many processes for example in cement, chemical and food industries. Investigation of the sedimentation process of solid bodies showed a phenomenon as settling velocity is not the constant value as it is expected from the analytical deduction; rather it has fluctuating behaviour. Seeking an explanation, detailed two phase hydrodynamic models are developed. In the present work, two-dimensional incompressible flow equation in conservative Euler form is solved numerically on PC by an implicit finite difference method, and the fluid-solid interaction is described by the Immersed Boundary Method. For additional model validation, Particle Tracing module of COMSOL is applied as well. The self-developed simulator based on an a priori (white box) model, and the 3D model by the commercial CFD software is used for modelling the two-phase system and the particle motion in the fluid column. Settling velocity is calculated and compared to the velocity of a particle recorded by a high-speed camera measurement system in the laboratory scale sedimentation equipment. The results are promising, and after improvements, the simulator can be a useful tool in supporting energetically optimal industrial design and operation.

The removal of volatile organic compounds (VOC) is an environmentally challenging problem. The organic compounds are widely used in automotive, plastic, and other industries. The systems containing VOC are multiphase by nature, often with solid, liquid, and gas phases. The different devices and processes can be used for the separation task, for example, scrubbing. However, the simplest way to treat a system with VOC is a counter current gas contact, where the flowing gas purifies the product. This operation can be completed in columns, where the solid particles are discharging, and the gas is fed at the bottom of the column to ensure the proper phase contact and residence time. In our previous work, the modelling and optimisation of a laboratory scale silo were performed [1]. After the mesh independence study, the measured residence times were compared to the simulated ones, and a validated model was created. Then we optimized the inner construction of the vessel by placing inserts serves the optimal discharge (mass flow) of the silo. In this study, we extend the capabilities of the model by the inclusion of the counter-current gas stream. Multiscale and multidimensional models are implemented to calculate the interparticle removal and surface reactions. The model with different spatial dimensions was compared to each other by the mean of information transfer, and content as well. The modelling approaches are compared to each other based for further use. In the case of pseudo-2D devices, where the changes in one of the spatial dimensions is neglectable there is no need to implement 3D simulations, it is enough to create a proper 2D model.