Determination of the deformation properties of bedrock under turbine foundations     

Rudolf Hiltscher  Anders Carlsson  Tommy Olsson 《Rock Mechanics and Rock Engineering》1984,17(1):37-49

Summary This paper presents an improved investigation technique for in-situ determination of the deformation properties of rock masses, which are important parameters in the desing of foundations. This technique permits testing on a circular, one square metre area of the rock. In order to obtain reproducible loading conditions when testing, an equipment was introduced that gave almost uniformly distributed loading of the rock surface. This device is described in this paper. Displacement measurements are made in a central measuring hole, since a point of zero displacement, located equidistant between the loaded surface and the upward-pointing anchoring forces, offered a suitable reference point. In this way, the measuring device is also well protected against disturbing variations in temperature. During cyclic loading and unloading, charateristic load/deflection graphs are recorded, which directly demonstrate the deformation properties of the rock, such as the modulus of deformation at different loads, linearity deviation from linearity, as well as hysteresis effects and creep. It is clear that the results of the investigation apply only to the measuring point—the place at which the investigation was carried out. The properties of the rock nearby may vary considerably. The procedure for using this method of investigation for testing improvement measures for turbine foundations is shown in some examples.  相似文献   

Book Review: Spatial Statistics: Methodological Aspects and Applications. By Marc Moore (ed.). Lecture Notes in Statistics 159. Springer, New York, 2001, 282 p., $69.95 (U.S.), paperback, ISBN 0-387-95240-3     

Donald E. Myers 《Mathematical Geology》2003,35(5):647-648

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On Modelling Discrete Geological Structures as Markov Random Fields   总被引：1，自引：0，他引：1  

Tommy Norberg  Lars Rosén  Ágnes Baran  Sándor Baran 《Mathematical Geology》2002,34(1):63-77

The purpose of this paper is to extend the locally based prediction methodology of BayMar to a global one by modelling discrete spatial structures as Markov random fields. BayMar uses one-dimensional Markov-properties for estimating spatial correlation and Bayesian updating for locally integrating prior and additional information. The methodology of this paper introduces a new estimator of the field parameters based on the maximum likelihood technique for one-dimensional Markov chains. This makes the estimator straightforward to calculate also when there is a large amount of missing observations, which often is the case in geological applications. We make simulations (both unconditional and conditional on the observed data) and maximum a posteriori predictions (restorations) of the non-observed data using Markov chain Monte Carlo methods, in the restoration case by employing simulated annealing. The described method gives satisfactory predictions, while more work is needed in order to simulate, since it appears to have a tendency to overestimate strong spatial dependence. It provides an important development compared to the BayMar-methodology by facilitating global predictions and improved use of sparse data.  相似文献   

Book Review: Practical Geostatistics 2000. By Isobel Clark and William V. Harper. Ecosse North America, Columbus, Ohio, 2000, 416 p., $60.00 (U.S.), ISBN 0-9703317-0-3 paperback     

Donald E. Myers 《Mathematical Geology》2002,34(6):779-781

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Book Review: Spatial Statistics: Methodological Aspects and Applications. By Marc Moore (ed.). Lecture Notes in Statistics 159. Springer,New York, 2001, 282 p., $69.95 (U.S.), paperback,ISBN 0-387-95240-3     

Myers  Donald E. 《Mathematical Geosciences》2003,35(5):647-648

Mathematical Geosciences -  相似文献   

Theoretical assessment of changes in design flood peak of an overland plane for two opposing urbanization sequences     

Tommy S. W. Wong  Yunjie Li 《水文研究》1999,13(11):1629-1647

By considering urbanization on an overland plane as a process whereby a relatively rough, permeable surface is gradually replaced by a relatively smooth, less permeable surface, the effect of urbanization sequence on the flood peak is theoretically assessed by the kinematic wave method. In the assessment, two opposing urbanization sequences are considered: one from downstream to upstream, and the other from upstream to downstream. The assessment is carried out in terms of the individual effect as well as the combined effect of the Manning resistance coefficient and the runoff coefficient. For both urbanization sequences and for all degrees of urbanization, the assessment shows that surface conversion from rough to smooth, or from permeable to less permeable causes the flood peak to increase. A comparison of the individual effects shows that for equal reductions in surface roughness and permeability, the reduction in permeability causes greater increases in the flood peak compared with the reduction in surface roughness. For a partially urbanized plane and for the same degree of urbanization, due to the partial area effect, urbanization at the downstream end generally causes greater increases in the flood peak. In terms of urbanization sequence, the downstream to upstream urbanization sequence generally causes greater increases in the flood peak. The effect of urbanization sequence on the flood peak, however, is only significant for the larger reductions in surface roughness and permeability. Finally, a comparison of the results of this study with those obtained from drainage basins shows that for most of the results from the basins, they correspond to those for the small reductions in surface roughness and permeability on an overland plane. For these cases, the effect of urbanization sequence on the flood peak is small. Copyright © 1999 John Wiley & Sons, Ltd.  相似文献   

Analysis of nonlinear associations between prenatal methylmercury exposure from fish consumption and neurodevelopmental outcomes in the Seychelles Main Cohort at 17 years     

Li-Shan?HuangEmail authorView author&#;s OrcID profile  Deborah?A.?Cory-Slechta  Christopher?Cox  Sally?W.?Thurston  Conrad?F.?Shamlaye  Gene?E.?Watson  Edwin?van Wijngaarden  Grazyna?Zareba  J.?J.?Strain  Gary?J.?Myers  Philip?W.?Davidson 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(4):893-904

The Seychelles Child Development Study has been examining the relationship between prenatal methylmercury (MeHg) exposure from consuming fish during pregnancy and child development. This study re-analyzes seven outcomes in the 17 year Main Cohort data to determine if there are nonlinear or non-homogeneous (subgroup) associations that were not identified in the linear analysis. We adopted two statistical approaches. First, we carried out an additive nonlinear analysis assuming homogeneous prenatal MeHg-outcome relationships to explore overall associations. Second, we applied the regression tree to the Woodcock–Johnson Calculation subtest (it was significantly associated in earlier analyses) and identified 4 clusters based on covariates. Then we used additive models to assess the prenatal MeHg association in each of the four clusters for all seven outcomes. This approach assumes nonlinear associations in each cluster and non-homogeneous associations between clusters. The additive nonlinear analysis yielded prenatal MeHg curves similar to the linear analysis. For the regression tree analysis, the curves relating prenatal MeHg to outcomes between the 4 clusters differed and some crossed at higher prenatal MeHg levels, suggesting non-homogeneity in the upper range of exposure. Additionally, some of the curves suggested a possible non-linear relationship within the range of exposure we studied. This non-linear analysis supports the findings from the linear analysis. It shows little evidence to support an adverse association of prenatal MeHg exposure through maternal consumption of fish contaminated with natural background levels. However, the tree analysis suggests that the prenatal exposure/outcome relationship may not be homogeneous across all individuals and that some subpopulations may have an adverse association in the upper range of the exposures studied. More robust data in the higher levels of exposure in this cohort are needed to confirm this finding.  相似文献   

Influence of combined changes in salinity and copper modulation on growth and copper uptake in the tropical green macroalga Ulva reticulata     

Florence Mamboya  Thomas J. Lyimo  Tommy Landberg  Mats Bjrk 《Estuarine, Coastal and Shelf Science》2009,84(3):326-330

The influence of salinity on growth and Cu uptake in the green macroalga Ulva reticulata collected from the intertidal area in the Western Indian Ocean was studied under controlled laboratory conditions. Exposure concentrations ranged from 5 to 500 μg Cu l⁻¹ at five salinities (ranging 20–40). The accumulation of Cu increased with decreasing salinity, so that the uptake at 500 μg Cu l⁻¹ was approximately 2.7, 2.4 and 2.0 times higher at salinities of 20, 25, and 30 respectively, than uptake at salinity of 35, and with uptake being lowest at salinity of 40. Ulva maintained a positive growth rate over the whole salinity range (20–40), with highest rates at salinity of 35. When exposing to Cu at low salinities (20 and 25), the growth rate of Ulva was strongly inhibited suggesting an increase in toxicity of Cu with decreasing salinity. EC50 and NOEC increased with increase in salinity, implying a reduced Cu toxicity at high salinities. It was concluded that salinity needs to be considered when using macroalgae, such as U. reticulata, as a bioindicator of heavy metals in areas with heavy rainfall, underground fresh water intrusion or in estuaries, as they might accumulate more metals and be more negatively affected.  相似文献   

Experimental analysis of the flow field around horizontal axis tidal turbines by use of scale mesh disk rotor simulators     

L.E. Myers  A.S. Bahaj 《Ocean Engineering》2010,37(2-3):218-227

Understanding the flow field around horizontal axis marine current turbines is important if this new energy generation technology is to advance. The aim of this work is to identify and provide an understanding of the principal parameters that govern the downstream wake structure and its recovery to the free-stream velocity profile. This will allow large farms or arrays of devices to be installed whilst maximising device and array efficiency. Wake characteristics of small-scale mesh disk rotor simulators have been measured in a 21 m tilting flume at the University of Southampton. The results indicate that wake velocities are reduced in the near wake region (close behind the rotor disk) for increasing levels of disk thrust. Further downstream all normalised wake velocity values converge, enforcing that, as for wind turbines, far wake recovery is a function of the ambient flow turbulence. Varying the disk proximity to the water surface/bed introduces differential mass flow rates above and below the rotor disk that can cause the wake to persist much further downstream. Finally, the introduction of increased sea bed roughness whilst increasing the depth-averaged ambient turbulence actually decreases downstream wake velocities. Results presented demonstrate that there are a number of interdependent variables that affect the rate of wake recovery and will have a significant impact on the spacing of marine current turbines within an array.  相似文献   

Intelligent modelling of clay compressibility using hybrid meta-heuristic and machine learning algorithms     

Pin Zhang  Zhen-Yu Yin  Yin-Fu Jin  Tommy HTChan  Fu-Ping Gao 《地学前缘(英文版)》2021,12(1):441-452

Compression index Ccis an essential parameter in geotechnical design for which the effectiveness of correlation is still a challenge.This paper suggests a novel modelling approach using machine learning(ML)technique.The performance of five commonly used machine learning(ML)algorithms,i.e.back-propagation neural network(BPNN),extreme learning machine(ELM),support vector machine(SVM),random forest(RF)and evolutionary polynomial regression(EPR)in predicting Cc is comprehensively investigated.A database with a total number of 311 datasets including three input variables,i.e.initial void ratio e0,liquid limit water content wL,plasticity index Ip,and one output variable Cc is first established.Genetic algorithm(GA)is used to optimize the hyper-parameters in five ML algorithms,and the average prediction error for the 10-fold cross-validation(CV)sets is set as thefitness function in the GA for enhancing the robustness of ML models.The results indicate that ML models outperform empirical prediction formulations with lower prediction error.RF yields the lowest error followed by BPNN,ELM,EPR and SVM.If the ranges of input variables in the database are large enough,BPNN and RF models are recommended to predict Cc.Furthermore,if the distribution of input variables is continuous,RF model is the best one.Otherwise,EPR model is recommended if the ranges of input variables are small.The predicted correlations between input and output variables using five ML models show great agreement with the physical explanation.  相似文献