Stratum Displacement Law and Intelligent Optimization Control Based on Intelligent Fuzzy Control Theory During Shield Tunneling

The laws of Stratum displacement and optimal control are critical for shield operation. This article’s focus is made on the intelligent fuzzy control theory concentrating on earth pressure, total thrust, driving speed, cutter torque, grouting pressure and grouting volume as the main elements of the study. A model of intelligent fuzzy control theory based on the model of No. 9 Line of Guangzhu Rail transit, on the Tianma river shield section. The paper also analyzes stratum displacement law due to shield tunnelling, executes & analyses intelligent controls for optimization of parameters, combining the five two-dimensional structures of the double structure of fuzzy control system. According to the observations made on the model. The model is upto date and the control of all parameters develops stably. The parameter ranges should be controlled as follows: earth pressure, 0.19 ~ 0.22Mpa; total thrust, 1100 ~ 1350T; driving speed, 38 ~ 50mm / min; cutter torque, 1600 ~ 2300 KN • m; grouting pressure, 0.19 ~ 0.25Mpa and grouting volume, 30 ~ 50L/min. Keywords: Shield tunnel, intelligent fuzzy control, Stratum displacement, optimal control DOI: 10.7176/CER/13-6-01 Publication date:October 31st 202

Assessment of risks of tunneling project in Iran using artificial bee colony algorithm

The soft computing techniques have been widely applied to model and analyze the complex and uncertain problems. This paper aims to develop a novel model for the risk assessment of tunneling projects using artificial bee colony algorithm. To this end, the risk of the second part of the Emamzade Hashem tunnel was assessed and analyzed in seven sections after testing geotechnical characteristics. Five geotechnical and hydrological properties of study zone are considered for the clustering of geological units in front of tunneling project including length of tunnel, uniaxial compressive strength, rock mass rating, tunneling index Q, density and underground water condition. These sections were classified in two low-risk and high-risk groups based on their geotechnical characteristics and using clustering technique. It was resulted that three sections with lithologies Durood Formation, Mobarak Formation, and Ruteh Formation are placed in the high risk group and the other sections with lithologies Baroot Formation, Elika Formation, Dacite tuff of Eocene, and Shear Tuff, and Lava Eocene are placed in the low risk group. In addition, the underground water condition and density with 0.722 and 1 Euclidean distances have the highest and lowest impacts in the high risk group, respectively. Therefore, comparing the obtained results of modelling and actual excavation data demonstrated that this technique can be applied as a powerful tool for modeling risks of tunnel and underground constructions

Advances in Computational Intelligence Applications in the Mining Industry

This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners

Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року

Second International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2021). Kryvyi Rih, Ukraine, May 19-21, 2021.Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року

Tradition and Innovation in Construction Project Management

This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings

Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding

Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors

Volume II: Mining Innovation

Contemporary exploitation of natural raw materials by borehole, opencast, underground, seabed, and anthropogenic deposits is closely related to, among others, geomechanics, automation, computer science, and numerical methods. More and more often, individual fields of science coexist and complement each other, contributing to lowering exploitation costs, increasing production, and reduction of the time needed to prepare and exploit the deposit. The continuous development of national economies is related to the increasing demand for energy, metal, rock, and chemical resources. Very often, exploitation is carried out in complex geological and mining conditions, which are accompanied by natural hazards such as rock bursts, methane, coal dust explosion, spontaneous combustion, water, gas, and temperature. In order to conduct a safe and economically justified operation, modern construction materials are being used more and more often in mining to support excavations, both under static and dynamic loads. The individual production stages are supported by specialized computer programs for cutting the deposit as well as for modeling the behavior of the rock mass after excavation in it. Currently, the automation and monitoring of the mining works play a very important role, which will significantly contribute to the improvement of safety conditions. In this Special Issue of Energies, we focus on innovative laboratory, numerical, and industrial research that has a positive impact on the development of safety and exploitation in mining

Exploring the Drivers of, and Potential Interventions to Reduce, Antimicrobial Resistance in the European Food System Context

Antimicrobial resistance (AMR) is a growing One Health problem that has become one of the leading causes of death worldwide. AMR emerges from a complex system characterized by multiple interacting factors across the human-animal-environment spectrum, all of which have the potential to be impacted by the effects of climate change. This thesis aimed to explore the drivers of AMR and assess potential interventions to reduce AMR in the Swedish food system context under potential climate change conditions. This thesis had four main objectives, to: 1) identify the quantitative and qualitative data needed to create and parameterize a simulation model of AMR emergence and transmission within the Swedish food system; 2) create and use a simulation model to test the potential ability of selected interventions to reduce AMR in the food system; 3) assess the sustainability of these interventions under climate change;, and 4) outline a systematic approach for creating mixed methods models for complex public health issues. The structure of the simulation model was based on an expert-derived causal loop diagram (CLD), created by Swedish and European AMR experts during a previously conducted participatory modelling workshop, that contained 91 nodes and 331 relationships deemed important to the development and spread of AMR within the Swedish food system. To determine if there was adequate information to create and parameterize the simulation model of AMR, a scoping review was conducted. This review identified 140 existing models and data from 414 sources to inform 64 of the major nodes within the CLD. The identified models addressed the main parts of the system (e.g., agriculture and farm transmission, antimicrobial use (AMU) and AMR, supply and demand for food); however, there was limited connection between the different areas of the food system. Nodes on the outer edges of the CLD did not have data, nor were they included within the scope of the models identified in the scoping review. Other data gaps included the environmental sector and wildlife. To further refine and parameterize the simulation model, semi-quantitative statements referring to the state of the nodes and relationships in the CLD were extracted from the transcripts from the prior participatory workshop. Transcript analysis identified 83 nodes, 48 of which were included in the CLD, and 35 were new nodes that emerged during the analysis or were existing nodes that were merged or divided. Based on the data requirements of the models identified via the scoping review, and the data currently available, it was not possible to create a fully quantitative model without including many assumptions. Therefore, the CLD was used as the base structure of a fuzzy cognitive map (FCM) of the Swedish food system, which was refined and parameterized by the data from the scoping review and transcript analysis. The final FCM contained 90 nodes, and 491 relationships. The use of FCM allowed for the evaluation of eight interventions under predicted climate change conditions, however, none of them were able to significantly reduce AMR in the system. Finally, the entire processes was reflected upon, including steps taken, challenges and mitigation strategies, and recommendations for future research in systems approaches for modelling complex systems and public health problems. In conclusion, this thesis identified that it was not feasible to create a purely quantitative model of AMR within the Swedish food system due to data limitations. However, by using data from the literature and experts’ tacit knowledge, an FCM of the system provided an innovative way to analyze the complex system, provided invaluable insight into the behaviour of the system, and aided in scenario analysis from a broader systems lens