| Title |
Optimisation of Material Flows in the Concept Urban Mining Based on the Use of Long-Term Storage Depot |
| ID_Doc |
16713 |
| Authors |
Globa, SB; Ashkerov, M; Arnold, V; Berezovaya, VV |
| Title |
Optimisation of Material Flows in the Concept Urban Mining Based on the Use of Long-Term Storage Depot |
| Year |
2021 |
| Published |
|
| DOI |
10.1007/978-3-030-56433-9_51 |
| Abstract |
Purpose: The purpose of the chapter is to improve material flows in urban areas with the help of long-term storage depots for mineral construction waste remaining after the demolition of buildings and structures for their further use as recycling materials. Design/methodology/approach: Urbanized territories are depots of material resources that are most efficiently used within the framework of circular economy and replace with them fully or partially natural resources. This concept is called urban mining. The authors identify a way to optimize the flow of mineral resources using long-term storage depots and calculate its efficiency using a specific example. Findings: It is shown that the studied method significantly optimizes the flow of mineral resources during the transition to circular economy and the introduction of the concept of urban mining. At the same time, with the given parameters, the current and maximum volumes of long-term storage depots are calculated, as well as the time when the system reaches a reduction in the generated waste in comparison with the volume of their recycling. Outlook-further research assignments: The project is at the initial stage of development and implies the use of optimization algorithms and machine learning for multivariate analysis and decision-making in real time with its further implementation. |
| Author Keywords |
Urban mining; Circular economy; Long-term storage depot; Recycling materials |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Book Citation Index – Social Sciences & Humanities (BKCI-SSH); Book Citation Index – Science (BKCI-S) |
| EID |
WOS:000836061400050 |
| WoS Category |
Development Studies; Computer Science, Artificial Intelligence; Social Sciences, Interdisciplinary |
| Research Area |
Development Studies; Computer Science; Social Sciences - Other Topics |
| PDF |
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