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

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

Statistischer Maßstabseffekt im Stahlbau und korrespondierender Einfluss auf die Zuverlässigkeit

This thesis aims to investigate the statistical size effect in the elasto-plastic material and the corresponding reliability of steel structures. The core idea is that the stochastic material properties are directly embedded in mechanical calculations to develop a more accurate and economical design method for steel structure. Moreover, the results of the experimental investigation with different specimen sizes, whose diameter is limit up to 32 mm, show that the statistical size effect exists in steel structures. This thesis demonstrates finally that the structural reliability is affected by the statistical size effect and the structural safety can be optimized by considering this effect. Because of the uncertainty and non-uniformity of the microscopic imperfection distribution, the material strength in macroscale presents complex randomness. This study described the randomness of material properties through two different ways: developing a stochastic material model for elasto-plastic material and establishing a discrete random field with a general mathematical program. The proposed stochastic material model is extended to analyze the steel structure with multiaxial stress and is integrated into the commercial FEM software for analysis of the complex structures with stress gradient. The stochastic finite element method is implemented to analyze the response of the 3D structures by a general-purpose FEM program when the random field file is imported into the finite element model. The uniaxial tensile tests with different specimen sizes and different material are carried out to demonstrate the statistical size effect in steel structures. The results show that the variations of the yield and tensile strength increase with the decreasing specimen volume. Moreover, according to the bending tests, it is obvious that the structural component strength is not only related to the specimen volume, but also the stress distribution. These two proposed simulation methods, which are an extension and supplement to traditional simulation methods, can effectively simulate the statistical size effect for the tensile and flexural components in steel structures. Finally, it is found by studying the influence of statistical size effect on structural reliability that the strength, which is obtained by small specimens through statistical analysis in the laboratory, is no more accurately applicable to large construction. The reliability theory for the structural safety which exists over the decades can be compared and validated or improved through the embedding the stochastic material properties in the numerical simulation.Das Ziel dieser Arbeit besteht darin, den Einfluss des statistischen Maßstabseffekts auf die elasto-plastischen Werkstoffeigenschaften und die entsprechende Zuverlässigkeit im Stahlbau zu quantifizieren. Die stochastischen Materialeigenschaften werden direkt in die numerischen Berechnungen implementiert, um eine präzisere und wirtschaftlichere Methodik für die Bemessung von Stahlkonstruktionen zu entwickeln. Darüber hinaus zeigen die Ergebnisse experimenteller Untersuchungen mit verschiedenen Probengrößen (max. Durchmesser bis zu 32 mm), dass der statistische Maßstabseffekt in Stählen existiert. Mittels numerischer Simulationen wird gezeigt, dass die Zuverlässigkeit der Bauteile durch den statistischen Maßstabseffekt beeinflusst wird und dass die strukturelle Sicherheit unter Berücksichtigung dieses Effekts optimiert werden kann. Aufgrund der vorhandenen mikroskopischen Imperfektionen und der Unsicherheiten über deren Verteilung zeigen die mechanischen Eigenschaften des Werkstoffs Zufälligkeiten. Diese Arbeit beschreibt die Zufälligkeit des Werkstoffs auf zwei verschiedene Wege: die Erste ist die Entwicklung eines stochastischen Materialmodells mit elasto-plastischen Materialeigenschaften. Die zweite Möglichkeit ist der Aufbau eines diskreten Zufallsfeldes mit einem allgemeinen mathematischen Programm. Das vorgeschlagene stochastische Materialmodell wird erweitert, um die Stahlkonstruktion unter multiaxialer Beanspruchung zu analysieren. Es wird in die kommerzielle FEM-Software integriert, um komplexe Bauwerke mit Spannungsgradienten zu analysieren. Die stochastische Finite-Elemente-Methode wird implementiert, um die Antworten der 3D-Konstruktion durch ein allgemeines FEM-Programm zu analysieren, nachdem die Zufallsfelddatei in das Finite-Elemente-Modell importiert wurde. Um den statistischen Maßstabseffekt im Stahlbau zu demonstrieren, werden die uniaxialen Zugversuche mit unterschiedlichen Probengrößen und verschiedenen Werkstoffen durchgeführt. Die Ergebnisse zeigen, dass die Streuungen der Streckgrenze und die Zugfestigkeit mit zunehmendem Probenvolumen abnehmen. Darüber hinaus hängt die Festigkeit des Bauteils nicht nur vom Probenvolumen gemäß den Biegetests, sondern auch von der Spannungsverteilung ab. Sowohl die analytische Methode als auch die vorgeschlagene Simulationsmethode, die eine Erweiterung und Ergänzung zu traditionellen Simulationsverfahren sind, können den statistischen Maßstabseffekt für die Zug- und Biegekomponenten in Stahlkonstruktionen erfassen. Die Untersuchungen des Einflusses des statistischen Maßstabseffektes auf die strukturelle Zuverlässigkeit ergaben, dass die Festigkeiten, die an kleinen Proben durch statistische Analysen im Labor ermittelt werden, für größere Bauteile nicht mehr exakt zutreffen. Daher kann die Zuverlässigkeitstheorie für die strukturelle Sicherheit mit der Simulation verglichen und validiert oder verbessert werden, indem die stochastischen Materialeigenschaften in das Simulationsmodell eingebettet werden

Benelux meeting on systems and control, 23rd, March 17-19, 2004, Helvoirt, The Netherlands

Book of abstract

ISGSR 2011 - Proceedings of the 3rd International Symposium on Geotechnical Safety and Risk

Scientific standards applicable to publication of BAWProceedings: http://izw.baw.de/publikationen/vzb_dokumente_oeffentlich/0/2020_07_BAW_Scientific_standards_conference_proceedings.pd

Computer Vision Approaches to Liquid-Phase Transmission Electron Microscopy

Electron microscopy (EM) is a technique that exploits the interaction between electron and matter to produce high resolution images down to atomic level. In order to avoid undesired scattering in the electron path, EM samples are conventionally imaged in solid state under vacuum conditions. Recently, this limit has been overcome by the realization of liquid-phase electron microscopy (LP EM), a technique that enables the analysis of samples in their liquid native state. LP EM paired with a high frame rate acquisition direct detection camera allows tracking the motion of particles in liquids, as well as their temporal dynamic processes. In this research work, LP EM is adopted to image the dynamics of particles undergoing Brownian motion, exploiting their natural rotation to access all the particle views, in order to reconstruct their 3D structure via tomographic techniques. However, specific computer vision-based tools were designed around the limitations of LP EM in order to elaborate the results of the imaging process. Consequently, different deblurring and denoising approaches were adopted to improve the quality of the images. Therefore, the processed LP EM images were adopted to reconstruct the 3D model of the imaged samples. This task was performed by developing two different methods: Brownian tomography (BT) and Brownian particle analysis (BPA). The former tracks in time a single particle, capturing its dynamics evolution over time. The latter is an extension in time of the single particle analysis (SPA) technique. Conventionally it is paired to cryo-EM to reconstruct 3D density maps starting from thousands of EM images by capturing hundreds of particles of the same species frozen on a grid. On the contrary, BPA has the ability to process image sequences that may not contain thousands of particles, but instead monitors individual particle views across consecutive frames, rather than across a single frame

An integrated approach to span design in open stope mining

In order to develop an appropriate mine design, a thorough understanding of the rock mass conditions and its potential response to mining is required. Rock mass characterisation is a key component in developing models of the rock mass and its engineering behaviour, and relies on disparate data collected by exploration geologists, mine geologists, rock mechanics engineers and technicians, in a variety of formats. Optimal rock mass model development requires the effective integration of all data sources, which currently requires considerable effort in collecting, managing, collating, validating and analysing this data.The importance of understanding the spatial variability of rock mass conditions has been highlighted as a major issue. The traditional approach of using simplistic models of “average” rock mass conditions can lead to sub-optimal designs, which may result in unplanned additional costs or economic implications of dilution and ore loss. The design of stope and pillars should be optimised for the prevailing rock mass conditions in the various regions of the mine.Some of the existing design tools used for open stope design have shown poor reliability in their performance predictions. Though some may have been originally developed to assist in initial stope size selection (i.e. pre-feasibility and feasibility levels), they are potentially being inappropriately relied upon for detailed design. Consideration of large scale structures on stability and their influence on local rock mass conditions are also important aspects of open stope design that are commonly over-looked. There is a need to select design methodologies that are optimised for the stage of project development. It is also important to emphasise the iterative, evolutionary and interdisciplinary nature of open stope design.This thesis proposes a framework that attempts to integrate different rock mass characterisation models, numerical modelling and stope performance data to assist in improving the overall excavation design process. The key philosophy behind design optimisation is the continual reduction in uncertainty in collected data, analysis and design methods used with a view to improving the overall reliability of the design. A stope span design optimisation approach is proposed which attempts to ensure that the appropriate methodologies in data collection, data analysis, rock mass model formulation and stope design are utilised at relevant project stages in order to minimise uncertainty and maximise design reliability. The design optimisation approach recognises that the appropriateness of a particular design methodology is highly dependant on the availability of an appropriate rock mass model, which is in turn dependant on the availability of quality rock mass data. With respect to the design of spans in open stope mining, the key aims of the proposed integrated approach are to; • Assess the suitability of data for analysis • If data is unsuitable, assess the most appropriate data collection strategy • Assess the most appropriate approach to rock mass modelling • Assess the most appropriate design methodologies • Assess the reliability of the design criteria and quantify the potential economic impact of the design on the projectOptimisation of the design process also requires integration of state-of-the-art techniques in data collection, analysis, modelling and engineering analysis and design at the appropriate stage of project development. During development of this thesis a number of improvements have been proposed in key areas in the rock engineering design process which can be incorporated into the integrated approach, including; • A rock mass data model has been developed that assists in facilitating the ongoing rock mass characterisation process. The data model is capable of integrating rock mass data from various sources, which promotes sharing of data and avoids duplication of data collection efforts. The data model is able to query rock mass data, define relationships between data types, apply bias corrections, and perform basic analysis for use in subsequent detailed analysis and rock mass modelling. • An implicit based approach to spatial rock mass and deterministic discontinuity modelling can be employed to improve understanding of the spatial variability of rock mass parameters, inter-relationships between rock mass characteristics on their role in design. For example, understanding the influence of large-scale structures on rock mass characteristics and excavation performance. • Improved scale independent geometrical assessments of stope performance have been proposed that maximise the use of stope performance data. • An integrated back analysis framework has been presented that is able to account for structural complexity, scale and features that cannot be directly incorporated into linear elastic numerical modelling codes. • With regard to linear elastic back analyses, an number of improvements have been proposed, as well as a suggested method to assess appropriateness of continuum models based on discontinuity intensity and critical span