An Evaluation Model for Tailings Storage Facilities Using Improved Neural Networks and Fuzzy Mathematics

With the development of mine industry, tailings storage facility (TSF), as the important facility of mining, has attracted increasing attention for its safety problems. However, the problems of low accuracy and slow operation rate often occur in current TSF safety evaluation models. This paper establishes a reasonable TSF safety evaluation index system and puts forward a new TSF safety evaluation model by combining the theories for the analytic hierarchy process (AHP) and improved back-propagation (BP) neural network algorithm. The varying proportions of cross validation were calculated, demonstrating that this method has better evaluation performance with higher learning efficiency and faster convergence speed and avoids the oscillation in the training process in traditional BP neural network method and other primary neural network methods. The entire analysis shows the combination of the two methods increases the accuracy and reliability of the safety evaluation, and it can be well applied in the TSF safety evaluation

Analysis of Computer Network Security Storage System Based on Cloud Computing Environment

A fundamental component of cloud computers from a business perspective is that users are allowed to use any desire and pay with a product that desire. Its cloud services were accessible anytime and anywhere consumers needed them. As a result, consumers are free to purchase whatever IT services they want, and they don't have to worry about how easy things can be managed. The remote server is used in a new information storage computing architecture that is considered an Internet generation. Ensuring security, material at resource providers' sites is a challenge that must be addressed in cloud technology. Thus, rather than reliance on a single provider for knowledge storing, this research implies developing construction for protection of knowledge stockpiling with a variation of operations, in which knowledge is scrambled and divided into numerous cipher frames and distributed across a large number of provider places. This support was applied to provide greater security, scalability, or reliability that was suggested according to the new structure. This paper, presented an encoded model for the cloud environment to improve security. The proposed model comprises the parity metadata for the database management provision to the provider. In the developed encoder chunks parity is not stored within the single resources with the provision of the available information chunks. The constructed security architecture in the RAID layer increases the dependability of the data with the deployment of the RAID 10 deployment. The developed RAID-based encoder chunks exhibit improved efficiency for the higher uptime at a minimal cost

Mining Safety and Sustainability I

Safety and sustainability are becoming ever bigger challenges for the mining industry with the increasing depth of mining. It is of great significance to reduce the disaster risk of mining accidents, enhance the safety of mining operations, and improve the efficiency and sustainability of development of mineral resource. This book provides a platform to present new research and recent advances in the safety and sustainability of mining. More specifically, Mining Safety and Sustainability presents recent theoretical and experimental studies with a focus on safety mining, green mining, intelligent mining and mines, sustainable development, risk management of mines, ecological restoration of mines, mining methods and technologies, and damage monitoring and prediction. It will be further helpful to provide theoretical support and technical support for guiding the normative, green, safe, and sustainable development of the mining industry

Study on MPGA-BP of Gravity Dam Deformation Prediction

Displacement is an important physical quantity of hydraulic structures deformation monitoring, and its prediction accuracy is the premise of ensuring the safe operation. Most existing metaheuristic methods have three problems: (1) falling into local minimum easily, (2) slowing convergence, and (3) the initial value’s sensitivity. Resolving these three problems and improving the prediction accuracy necessitate the application of genetic algorithm-based backpropagation (GA-BP) neural network and multiple population genetic algorithm (MPGA). A hybrid multiple population genetic algorithm backpropagation (MPGA-BP) neural network algorithm is put forward to optimize deformation prediction from periodic monitoring surveys of hydraulic structures. This hybrid model is employed for analyzing the displacement of a gravity dam in China. The results show the proposed model is superior to an ordinary BP neural network and statistical regression model in the aspect of global search, convergence speed, and prediction accuracy

Dynamic simulation of red mud washers used in aluminum industries

Clarifier-Thickener equipment is used in a wide range of continuous sedimentation and sludge thickening processes where solid particles from continuous inflow mixtures are separated from the liquid. In this operation, the concentration of solids increases due to settling, so that the formation of a thicker bed is inevitable with time. Under optimal operating conditions, it is always possible to obtain two discharges from these vessels: a highly concentrated suspension at the bottom (underflow), and a clarified liquid stream at the top of the equipment (overflow or effluent). In the Bayer Process an insoluble sub-product is formed as a result of the digestion of the bauxite ore with caustic soda. This product is called “red mud” and it has to be continuously removed by settlers or thickeners/clarifiers. This project proposes the simulation of a continuous thickener/clarifier in order to predict the concentration profile and the height of the mud level (process controlled variable) as alternative to current measurement system, that contains long delay discrete sampling time(15 minutes each measurement). The simulation also, can provide an option of creating a knowledge base for off-line control. The project essentially involves two methods of simulation, namely mathematical modelling and neural networks. The model based applies a kinematic model to approximate the process behaviour using both, equipment and suspension characteristics. On the other hand, due to the large amount of historical data, neural network is proposed for system identification. The first method is based on the solution of a highly nonlinear model, based on kinematic modelling of sedimentation extended to flocculated suspensions. This approach uses a conservative finite difference scheme of the upwind type for solving an initial boundary value problem (IBVP). The successful simulation of the equipment and further validation of the mathematical model are then achieved once the properties of the suspensions have been determined. These properties are related to flux batch settling and solid stress functions, whose parameters can be obtained experimentally.On-site testing of the characteristics of red mud was conducted at the Rio Tinto Yarwum Alumina Refinery in Queensland. The settling properties of the suspension were determined via batch settling. For measurement of the rheology properties, the vane technique was used employing a Haake VT 550 rheometer. The results of the simulation showed that the concentration profile and height of the heavy mud level can be determined via a steady state model for a given underflow concentration. These results, however, were not in good agreement with measured data. The second method of simulation involved the use of Rio Tinto Yarwun historical data to develop a neural model in order to obtain a relationship between process variables. This approach has the advantage that no mathematical model is needed. With this method, historical data (continuous data) are obtained and analysed, and daily averages of the variables involved in the process are calculated. Different network architectures are tested according to the washer process. Ultimately, two networks were developed to describe washer dynamics.

Engineering handbook

1995 handbook for the faculty of Engineerin

Articles indexats publicats per investigadors del Campus de Terrassa: 2013

Aquest informe recull els 228 treballs publicats per 177 investigadors/es del Campus de Terrassa en revistes indexades al Journal Citation Report durant el 2013Preprin