Improving the Knowledge-Based Expert System Lifecycle

Knowledge-based expert systems are used to enhance and automate manual processes through the use of a knowledge base and modern computing power. The traditional methodology for creating knowledge-based expert systems has many commonly encountered issues that can prevent successful implementations. Complications during the knowledge acquisition phase can prevent a knowledge-based expert system from functioning properly. Furthermore, the time and resources required to maintain a knowledge-based expert system once implemented can become problematic. There are several concepts that can be integrated into a proposed methodology to improve the knowledge-based expert system lifecycle to create a more efficient process. These methods are commonly used in other disciplines but have not traditionally been incorporated into the knowledge-based expert system lifecycle. A container-loading knowledge-based expert system was created to test the concepts in the proposed methodology. The results from the container-loading knowledge-based expert system test were compared against the historical records of thirteen container ships loaded between 2008 and 2011

Impulse-based discrete element modelling of rock impact and fragmentation, with applications to block cave mining

Impulse-based methods efficiently and accurately model high-frequency collisions of complex shapes based on the enforcement of non-penetrating constraints. It does not rely on penalty parameters nor requires the computation of penetration between bodies. This work presents a novel necessary condition for energy conservation in impulse-based methods. In previous versions of the impulse methods, such as sequential and simultaneous impulse methods, the relative velocity at the contact points after collision is directly derived from the relative velocity before collision, in a purely simultaneous or sequential manner. This work presents a novel energy tracking method (ETM), in which the relative velocities are iteratively but gradually adjusted, simultaneously modelling their interaction at each iteration. ETM ensures the energy conservation while capturing the propagation of forces during collision. The ETM is applied to model the dynamics of fragment collision in the context of fragmentation. Two approaches of fragmentation are proposed: a finite-discrete element approach, and a low cost, fragmentation pattern-based approach. The first approach models the growth of fractures using the finite element method (FEM) and advanced re-meshing technology. This finite-discrete element approach suffers from the drawback of massive computational cost. The low-cost, fragmentation pattern-based approach separate colliding bodies directly. The fragmentation pattern is generated using Weibull distribution equations, the patterns and size distributions computed using full finite/discrete element simulations and experimental results. This work investigates the influence of fragmentation on the frequency of hang-up events and on the gravity flow of rock fragments within a block caving system. Numerical results indicate that models that do not consider fragmentation tend to overestimate the frequency of hang-up accidents.Open Acces

Container Loading Problems: A State-of-the-Art Review

Container loading is a pivotal function for operating supply chains efficiently. Underperformance results in unnecessary costs (e.g. cost of additional containers to be shipped) and in an unsatisfactory customer service (e.g. violation of deadlines agreed to or set by clients). Thus, it is not surprising that container loading problems have been dealt with frequently in the operations research literature. It has been claimed though that the proposed approaches are of limited practical value since they do not pay enough attention to constraints encountered in practice.In this paper, a review of the state-of-the-art in the field of container loading will be given. We will identify factors which - from a practical point of view - need to be considered when dealing with container loading problems and we will analyze whether and how these factors are represented in methods for the solution of such problems. Modeling approaches, as well as exact and heuristic algorithms will be reviewed. This will allow for assessing the practical relevance of the research which has been carried out in the field. We will also mention several issues which have not been dealt with satisfactorily so far and give an outlook on future research opportunities

Automating the packing heuristic design process with genetic programming

The literature shows that one-, two-, and three-dimensional bin packing and knapsack packing are difficult problems in operational research. Many techniques, including exact, heuristic, and metaheuristic approaches, have been investigated to solve these problems and it is often not clear which method to use when presented with a new instance. This paper presents an approach which is motivated by the goal of building computer systems which can design heuristic methods. The overall aim is to explore the possibilities for automating the heuristic design process. We present a genetic programming system to automatically generate a good quality heuristic for each instance. It is not necessary to change the methodology depending on the problem type (one-, two-, or three-dimensional knapsack and bin packing problems), and it therefore has a level of generality unmatched by other systems in the literature. We carry out an extensive suite of experiments and compare with the best human designed heuristics in the literature. Note that our heuristic design methodology uses the same parameters for all the experiments. The contribution of this paper is to present a more general packing methodology than those currently available, and to show that, by using this methodology, it is possible for a computer system to design heuristics which are competitive with the human designed heuristics from the literature. This represents the first packing algorithm in the literature able to claim human competitive results in such a wide variety of packing domains

Experimental and numerical modelling investigations into coal mine rockbursts and gas outbursts

Rockbursts and gas outbursts are a longstanding hazard in underground coal mining due to their sudden occurrences and high consequences. These hazards are becoming prominent due to the increase in mining depth, difficult mining conditions, and adverse gas pressure conditions. Several researchers have proposed different theories, mechanisms, and indices to determine the rockbursts and gas outbursts liability but most of them focus on only some aspects of the complex engineering system for the ease to represent them using partial differential equations. They have often ignored the dynamics of changing mining environment, coal seam heterogeneity and stochastic variations in the rock properties. Most of the indices proposed were empirical and their suitability to different mining conditions is largely debated. To overcome the limitations of previous theories, mechanisms and indices, a probabilistic risk assessment framework was developed in this research to mathematically represent the complex engineering phenomena of rockbursts and gas outbursts for a heterogeneous coal seam. An innovative object-based non-conditional simulation approach was used to distribute lithological heterogeneity occurring in the coal seam to respect their geological origin. The dynamically changing mining conditions during a longwall top coal caving mining (LTCC) was extracted from a coupled numerical model to provide statistically sufficient data for probabilistic analysis. The complex interdependencies among several parameters, their stochastic variations and uncertainty were realistically implemented in the GoldSim software, and 100,000 equally likely scenarios were simulated using the Monte Carlo method to determine the probability of rockbursts and gas outbursts. The results obtained from the probabilistic risk assessment analysis incorporate the variations occurring due to lithological heterogeneity and give a probability for the occurrence of rockbursts, coal and gas outbursts, and safe mining conditions. The framework realistically represents the complex mining environment, is resilient and results are reliable. The framework is generic and can be suitably modified to be used in different underground mining scenarios, overcoming the limitations of earlier empirical indices used.Open Acces

Influence of pozzolans and plasticizer on the performance of paste backfill in underground mines

Gideon Yowa investigated the possibility of using pozzolans to partially replace cement in mine filling to reduce the filling cost and make backfilling more environmentally friendly. He found that when pozzolans replace cement partially, the strength attained was comparable to the strength that pure cement attained. The results are useful for underground mines that use cemented paste fill

Constraint programming methods in three-dimensional container packing

Cutting and packing problems are present in many, at first glance unconnected, areas, therefore it's beneficial to have a good understanding of their underlying structure, to select proper techniques for finding solutions. Cutting and packing problems are a class of combinatorial problems in which there are specified two classes of objects: big and small items and the task is to place the small items within big items. Even in the 1-dimensional case, bin-packing is strongly NP-hard (Garey 1978), which suggests, that exact solutions may not be found in a reasonable time for bigger instances. In the literature, there are presented many various approaches to packing problems, e.g. mixed-integer programming, approximation algorithms, heuristic solutions, and local search algorithms, including metaheuristic approaches like Tabu Search or Simulated Annealing. The main goal of this work is to review existing solutions, survey the variants arising from the industry applications, present a solution based on constraint programming and compare its performance with the results in the literature. Optimization with constraint programming is a method searching for the global optima, hence it may require a higher workload compared to the heuristic and local search approaches, which may finish in a local optimum. The performance of the presented model will be measured on test data used in the literature, which were used in many articles presenting a variety of approaches to three-dimensional container packing, which will allow us to compare the efficiency of the constraint programming model with other methods used in the operational research

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