7,258 research outputs found

    Numerical modelling of ground-tunnel support interaction using bedded-beam-spring model with fuzzy parameters

    Get PDF
    The study of the ground-tunnel interaction by introducing a predetermined degree of variation (fuzziness) in some parameters of the chosen model is presented and discussed. This research comes from the consideration that tunnel model parameters and geometry are usually affected by a degree of uncertainty, mainly due to construction imprecision and the great variability of rock mass properties. The research has been developed by using the fuzzy set theory assuming that three model parameters are affected by a certain amount of uncertainty (defined by the so-called membership functions). The response of the numerical model is calculated by solving the fuzzy equations for different shapes of the membership functions. In order to investigate the effects of some model parameters, and to provide a simple procedure and tool for the designers, a study on the effect of tunnel boundary conditions, based on a fuzzy model, has been carried out using a simple but well known and widely used design method such as the bedded-beam-spring mode

    Influence of the Tunnel Shape on Shotcrete Lining Stresses

    Get PDF
    Tunnel excavation is frequently carried out in rock masses by the drill and blast method and the final shape of the tunnel boundary can be irregular due to overbreaks. In order to investigate the effects of overbreaks a study of the effect of tunnel boundary irregularity has been carried out. This is done developing a computational tool able to take into account fuzzy variables (i.e., thickness of the beams of the bedded spring approach used for the model). The obtained results show that irregularity effects should be considered when a shotcrete lining is used as the final tunnel lining (for the case where the tunneling procedure does not permit a smooth surface to be obtained). This is crucial to obtain a durable linin

    Fuzzy modelling of powder snow avalanches

    Get PDF
    This paper examines powder snow avalanches by introducing a predetermined degree of variation, or fuzziness, in model parameters. Given a value of vagueness in the parameters, fuzzy set theory makes it possible to evaluate the vagueness in the results. The use of a more complex stochastic analysis can be avoided. Six parameters of the model are taken to be affected by a certain amount of uncertainty; the response of the numerical model is calculated by solving the fuzzy equations. In this way, it is possible to evaluate how the results are affected by a given change in the model parameters. The paper first presents a well-known avalanche model and its solution considering the influence of friction. A brief introduction of the fuzzy set is given with regard to the avalanche model mentioned. Later, the fuzzy solution of the model in terms of velocity and average pressure is calculated for three different levels of imprecision in the data. At the end, the results are presented and commented

    The safety case and the lessons learned for the reliability and maintainability case

    Get PDF
    This paper examine the safety case and the lessons learned for the reliability and maintainability case

    Input variable selection in time-critical knowledge integration applications: A review, analysis, and recommendation paper

    Get PDF
    This is the post-print version of the final paper published in Advanced Engineering Informatics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.The purpose of this research is twofold: first, to undertake a thorough appraisal of existing Input Variable Selection (IVS) methods within the context of time-critical and computation resource-limited dimensionality reduction problems; second, to demonstrate improvements to, and the application of, a recently proposed time-critical sensitivity analysis method called EventTracker to an environment science industrial use-case, i.e., sub-surface drilling. Producing time-critical accurate knowledge about the state of a system (effect) under computational and data acquisition (cause) constraints is a major challenge, especially if the knowledge required is critical to the system operation where the safety of operators or integrity of costly equipment is at stake. Understanding and interpreting, a chain of interrelated events, predicted or unpredicted, that may or may not result in a specific state of the system, is the core challenge of this research. The main objective is then to identify which set of input data signals has a significant impact on the set of system state information (i.e. output). Through a cause-effect analysis technique, the proposed technique supports the filtering of unsolicited data that can otherwise clog up the communication and computational capabilities of a standard supervisory control and data acquisition system. The paper analyzes the performance of input variable selection techniques from a series of perspectives. It then expands the categorization and assessment of sensitivity analysis methods in a structured framework that takes into account the relationship between inputs and outputs, the nature of their time series, and the computational effort required. The outcome of this analysis is that established methods have a limited suitability for use by time-critical variable selection applications. By way of a geological drilling monitoring scenario, the suitability of the proposed EventTracker Sensitivity Analysis method for use in high volume and time critical input variable selection problems is demonstrated.E

    Are we at the dawn of quantum-gravity phenomenology?

    Get PDF
    A handful of recent papers has been devoted to proposals of experiments capable of testing some candidate quantum-gravity phenomena. These lecture notes emphasize those aspects that are most relevant to the questions that come to mind when one is exposed for the first time to these research developments: How come theory and experiments are finally meeting in spite of all the gloomy forecasts that pervade traditional reviews? Is this a case of theorists having put forward more and more speculative ideas until a point was reached at which conventional experiments could rule out the proposed phenomena? Or has there been such a remarkable improvement in experimental techniques and ideas that we are now capable of testing plausible candidate quantum-gravity phenomena? These questions are analysed rather carefully for the recent proposals of interferometry-based tests and tests using observations of gamma rays of astrophysical origin. I also briefly discuss other proposed experiments (including tests of quantum-gravity-induced decoherence using the neutral-kaon system and accelerator tests of models with large extra dimensions). The emerging picture suggests that we are finally starting the exploration of a large class of plausible quantum-gravity effects. However, our chances to obtain positive (discovery) experimental results depend crucially on the magnitude of these effects. In most cases the level of sensitivity that the relevant experiments should achieve within a few years corresponds to effects suppressed only linearly by the Planck length.Comment: 47 pages, Latex. Based on lectures given at the XXXV Karpacz Winter School of Theoretical Physics "From Cosmology to Quantum Gravity", Polanica, Poland, 2-12 February, 1999. To appear in the proceeding

    A comparative study of multiple-criteria decision-making methods under stochastic inputs

    Get PDF
    This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative
    • 

    corecore