Ústav procesního inženýrství
Browse
Recent Submissions
Now showing 1 - 5 of 54
- ItemComprehensive review on waste generation modeling(MDPI, 2023-02-10) Šomplák, Radovan; Smejkalová, Veronika; Rosecký, Martin; Szásziová, Lenka; Nevrlý, Vlastimír; Hrabec, Dušan; Pavlas, MartinStrategic plans for waste management require information on the current and future waste generation as a primary data source. Over the years, various approaches and methods for waste generation modeling have been presented and applied. This review provides a summary of the tasks that require information on waste generation that are most frequently handled in waste management. It is hypothesized that there is not currently a modeling approach universally suitable for forecasting any fraction of waste. It is also hypothesized that most models do not allow for modeling different scenarios of future development. Almost 360 publications were examined in detail, and all of the tracked attributes are included in the supplementary. A general step-by-step guide to waste generation forecasting, comprising data preparation, pre-processing, processing, and post-processing, was proposed. The problems that occurred in the individual steps were specified, and the authors’ recommendations for their solution were provided. A forecasting approach based on a short time series is presented, due to insufficient options of approaches for this problem. An approach is presented for creating projections of waste generation depending on the expected system changes. Researchers and stakeholders can use this document as a supporting material when deciding on a suitable approach to waste generation modeling or waste management plans.
- ItemNetwork Flow Problem Heuristic Reduction Using Machine Learning(Springer Nature, 2023-09-23) Rosecký, Martin; Pluskal, Jaroslav; Šomplák, RadovanMost of the supporting tools developed for logistic optimization and processing infrastructure planning are based on the network flow problem. The real-world application of these instruments can provide great insight and help to ensure long-term sustainability. The main limitation of these tools lies in great computing demand when there is the necessity of solving large-scale tasks in great detail. It means that the ability to find the optimal solution for real-world problems is limited. Thus, the detail of infrastructure is often reduced by data aggregation or heuristic approaches are used to find a suboptimal solution. This paper proposes a machine learning classification model to reduce the number of variables for an exact solution algorithm. First, the design of experiments is used to create a set of smaller problems that are possible to solve exactly. Artificial data are used at this stage, while domain knowledge is used to set appropriate distribution and parameters. Second, the classification model estimates the probability of the presence of each arc in the optimal solution. Features, which are related to costs and capacity, of each arc are utilized in the classification model. Models created on a subset of generated problems are then tested on the other problems. Finally, the proposed framework is applied to the waste management problem in the Czech Republic. The results of the verification show, that it is possible to remove 95 % of arcs without impact on strategic decisions and without significant change of an objective function. The computing time of the reduced problem takes only 7 % of the original task.
- ItemTechnology for Hot Spring Cooling and Geothermal Heat Utilization: A Case Study for Balneology Facility(MDPI, 2023-03-23) Vondra, Marek; Buzík, Jiří; Horňák, David; Procházková, Michaela; Miklas, Václav; Touš, Michal; Jegla, Zdeněk; Máša, VítězslavReducing energy costs in Europe is more challenging than before due to extreme price increases. The use of local renewable energy sources is one way to contribute to this effort. In the case of spa resorts, the use of heat from hot springs for therapeutic baths is an option. It is necessary to cool down this thermal mineral water to a temperature acceptable to the human body. However, due to the high mineral content of this water, heavy fouling can be a problem for conventional heat exchangers. The purpose of this study is to identify the suitable cooling technology in terms of required cooling capacity and waste heat recovery capability. The cooling technology was selected on the basis of a literature search. A pilot cooling unit consisting of vacuum cooler and plate heat exchanger was designed and tested in a real spa resort for six months. Both selected technologies have demonstrated the ability to cool thermal mineral water in long-term operation, as well as the possibility to utilize waste heat for domestic hot water heating. However, fouling problems occur in the plate heat exchanger. The vacuum cooler demonstrated greater operational robustness and resistance to encrustation.
- ItemCooking oils and fat waste collection infrastructure planning: a regional-level outline(SPRINGER, 2022-01-01) Matušinec, Josef; Hrabec, Dušan; Šomplák, Radovan; Nevrlý, Vlastimír; Redutskiy, YuryAmong the current trends in waste management and circular economy is the involvement of new fractions of waste for sorting and collection. One of them is fats and cooking oils, especially those coming from households. Now, the nascent fat waste recycling becomes promoted as regulations and waste recovery targets have been set in the European Union. The traditional manner of discarding household fat waste usually causes sewage problems. However, utilisation of this waste brings the potential for contributing to the energy supply and material recovery. This research presents a mathematical model for the optimal location of fat waste bins and containers in the given municipalities. The container network should comprise as few containers as possible, while the walking distance for the citizens towards the container is as short as possible. The objective of the proposed optimisation model is to minimise the total number of collection points (infrastructure cost). The collection points represent the citizens' addresses in a municipality. The average walking distance towards a container is a novel feature in the model, which is pertinent to waste fractions with low production per person. Cluster analysis describes the variability between municipalities, and further, it is possible to use regression analysis to model the number of containers for any municipality or region. The proposed general decision support tool estimates the total cost and number of bins needed for any region or a country. The region from the Czech Republic, which was used as a study area, revealed the requirement for 609 containers, with only EUR 30,000 of investment cost. There are around 950 inhabitants assigned to a single collection point on average. [GRAPHICS] .
- ItemUsing numerical dissipation rate and viscosity to assess turbulence-related data accuracy - Part 1: Experimental setup(Wiley-VCH GmbH, 2023-08-22) Turek, Vojtěch; Jegla, Zdeněk; Dohnal, Miloslav; Reppich, MarcusThis is the first part of a two-part paper focusing on the assessment of accuracy of turbulence-related data from computational fluid dynamics (CFD) simulations using effective numerical dissipation rate and effective numerical viscosity. Setup of the CFD cases replicating a swirling pipe flow experiment from literature, for which turbulence-related data measured via laser Doppler anemometry (LDA) had been reported, is presented. The way effective numerical dissipation rate and effective numerical viscosity were obtained for each mesh cell is also discussed. The results of the study are presented in the second part of this series.