承德公路隧道围岩分级与塌方机理分析

During tunnel constriction the classification of rock mass is widely used in tunnel design and construction. Moreover it offers the base information about tunnel investment and security. The quick classification of rock mass is very important for not delaying tunnel construction. Nowadays the tunnel engineers usually use initial survey files which are obtained by probe drilling to design a tunnel. It brings the problem that initial surrounding rock classification is usually much different from the real condition during the tunnel construction. Because initial surrounding rock lack credibility, it need us to make real time surrounding rock classification during the tunnel construction, and feed back the result to designers and constructors. Therefore, to find a quick wall rock classification method is very important not only for the time limit for a project but also for not delaying tunnel construction. Not all but many tunnels and underground constructions do suffer form collapse during the period of construction. Although accidental collapse in a large project in civil and geotechnical engineering sometimes appears to be a local event, if it occurred, it can bring about casualties, disrupted，production, construction delay, environmental damage, capital cost etc，therefore, it has been a difficult problem ,both in theory and in practice, establishing how to prevent underground structures form collapse and how to handle such an event in case in occurs. It is important to develop effective solutions and technical measures to prevent and control the collapse. According to the tunnel collapse occurred in Cheng De this paper analyze the main collapse mechanism leading to tunnel collapse and summon up the disposal method when collapse happened. It may be useful for tunnel construction in Cheng De in future. This paper is base on tunnel surrounding rock classification and tunnel support tasks during the tunnel construction in Cheng De area. It aims at solving 4 important problems in tunnel design and construction. 1) The relationship between rock rebound strength and rock single axle compression strength. First we go to the face wall and do rebound test on the tunnel face, then we chose some pieces of rock and do point loading test. Form the tests record we try to find the relationship between rock rebound strength and rock single axle compression strength. 2) The relationship between the value [BQ] and the value Q. First in order to obtain the information of rock character, rock strength, degree of weathering, the structure of rock mass, the joint condition, underground water condition and so on, we go to the tunnel face to do field investigation. And then we use two kinds of rock classification method to make surrounding rock classification. Base on the works above, finally we analyze the relationship between the value [BQ] and the value Q. 3) Sum up the mechanism leading to tunnel collapse and it disposal method in Cheng De area According to the tunnel collapse occurred in Cheng De this paper analyze the main reasons leading to the tunnel collapse and sum up the disposal method when collapse happened. 4) Obtain the properties of steel frame grid by numerical simulation. First we establish the 3D numeral model of steel frame grid by ADINA, and then find the mechanics properties by numerical simulation in ADINA. Second Based on the rock mass geological structure model, we established steel frame grid numeral model which is installed in the tunnel by FLAC3D and simulated the progress of tunnel construction. We hope that the support effect in tunnel can be evaluated from the numerical simulation.

Permutation Tests for Classification

We introduce and explore an approach to estimating statistical significance of classification accuracy, which is particularly useful in scientific applications of machine learning where high dimensionality of the data and the small number of training examples render most standard convergence bounds too loose to yield a meaningful guarantee of the generalization ability of the classifier. Instead, we estimate statistical significance of the observed classification accuracy, or the likelihood of observing such accuracy by chance due to spurious correlations of the high-dimensional data patterns with the class labels in the given training set. We adopt permutation testing, a non-parametric technique previously developed in classical statistics for hypothesis testing in the generative setting (i.e., comparing two probability distributions). We demonstrate the method on real examples from neuroimaging studies and DNA microarray analysis and suggest a theoretical analysis of the procedure that relates the asymptotic behavior of the test to the existing convergence bounds.

Generating Circuit Tests by Exploiting Designed Behavior

This thesis describes two programs for generating tests for digital circuits that exploit several kinds of expert knowledge not used by previous approaches. First, many test generation problems can be solved efficiently using operation relations, a novel representation of circuit behavior that connects internal component operations with directly executable circuit operations. Operation relations can be computed efficiently by searching traces of simulated circuit behavior. Second, experts write test programs rather than test vectors because programs are more readable and compact. Test programs can be constructed automatically by merging program fragments using expert-supplied goal-refinement rules and domain-independent planning techniques.

Time-dependent Hyperstar algorithm for robust vehicle navigation in time-dependent stochastic road networks.

The vehicle navigation problem studied in Bell (2009) is revisited and a time-dependent reverse Hyperstar algorithm is presented. This minimises the expected time of arrival at the destination, and all intermediate nodes, where expectation is based on a pessimistic (or risk-averse) view of unknown link delays. This may also be regarded as a hyperpath version of the Chabini and Lan (2002) algorithm, which itself is a time-dependent A* algorithm. Links are assigned undelayed travel times and maximum delays, both of which are potentially functions of the time of arrival at the respective link. The driver seeks probabilities for link use that minimise his/her maximum exposure to delay on the approach to each node, leading to the determination of the pessimistic expected time of arrival. Since the context considered is vehicle navigation where the driver is not making repeated trips, the probability of link use may be interpreted as a measure of link attractiveness, so a link with a zero probability of use is unattractive while a link with a probability of use equal to one will have no attractive alternatives. A solution algorithm is presented and proven to solve the problem provided the node potentials are feasible and a FIFO condition applies for undelayed link travel times. The paper concludes with a numerical example.

Winkler springs (p-y curves) for liquefied soil from element tests.

In practice, piles are most often modelled as "Beams on Non-Linear Winkler Foundation" (also known as “p-y spring” approach) where the soil is idealised as p-y springs. These p-y springs are obtained through semi-empirical approach using element test results of the soil. For liquefied soil, a reduction factor (often termed as p-multiplier approach) is applied on a standard p-y curve for the non-liquefied condition to obtain the p-y curve liquefied soil condition. This paper presents a methodology to obtain p-y curves for liquefied soil based on element testing of liquefied soil considering physically plausible mechanisms. Validation of the proposed p-y curves is carried out through the back analysis of physical model tests.

Learning to drive: from hazard detection to hazard handling

Hazard perception has been found to correlate with crash involvement, and has thus been suggested as the most likely source of any skill gap between novice and experienced drivers. The most commonly used method for measuring hazard perception is to evaluate the perception-reaction time to filmed traffic events. It can be argued that this method lacks ecological validity and may be of limited value in predicting the actions drivers’ will take to hazards encountered. The first two studies of this thesis compare novice and experienced drivers’ performance on a hazard detection test, requiring discrete button press responses, with their behaviour in a more dynamic driving environment, requiring hazard handling ability. Results indicate that the hazard handling test is more successful at identifying experience-related differences in response time to hazards. Hazard detection test scores were strongly related to performance on a driver theory test, implying that traditional hazard perception tests may be focusing more on declarative knowledge of driving than on the procedural knowledge required to successfully avoid hazards while driving. One in five Irish drivers crash within a year of passing their driving test. This suggests that the current driver training system does not fully prepare drivers for the dangers they will encounter. Thus, the third and fourth studies in this thesis focus on the development of two simulator-based training regimes. In the third study participants receive intensive training on the molar elements of driving i.e. speed and distance evaluation. The fourth study focuses on training higher order situation awareness skills, including perception, comprehension and projection. Results indicate significant improvement in aspects of speed, distance and situation awareness across training days. However, neither training programme leads to significant improvements in hazard handling performance, highlighting the difficulties of applying learning to situations not previously encountered.