A response‐based decoupling criterion for multiply‐supported secondary systems

It is often infeasible to carry out coupled analyses of multiply‐supported secondary systems for earthquake excitations. ‘Approximate’ decoupled analyses are then resorted to, unless the response errors due to those are significantly high. This study proposes a decoupling criterion to identify such cases where these errors are likely to be larger than an acceptable level. The proposed criterion is based on the errors in the primary system response due to decoupling and has been obtained by assuming (i) the input excitation to be an ideal white noise process, (ii) cross‐modal correlation to be negligible, and (iii) the combined system to be classically damped. It uses the modal properties of the undamped combined system, and therefore, a perturbation approach has been formulated to determine the combined system properties in case of light to moderately heavy secondary systems. A numerical study has been carried out to illustrate the accuracy achieved with the proposed perturbation formulation. The proposed decoupling criterion has been validated with the help of two example primary‐secondary systems and four example excitation processes. Copyright © 2002 John Wiley & Sons, Ltd.     

Modelling evaporation using an artificial neural network algorithm

This paper investigates the prediction of Class A pan evaporation using the artificial neural network (ANN) technique. The ANN back propagation algorithm has been evaluated for its applicability for predicting evaporation from minimum climatic data. Four combinations of input data were considered and the resulting values of evaporation were analysed and compared with those of existing models. The results from this study suggest that the neural computing technique could be employed successfully in modelling the evaporation process from the available climatic data set. However, an analysis of the residuals from the ANN models developed revealed that the models showed significant error in predictions during the validation, implying loss of generalization properties of ANN models unless trained carefully. The study indicated that evaporation values could be reasonably estimated using temperature data only through the ANN technique. This would be of much use in instances where data availability is limited. Copyright © 2002 John Wiley & Sons, Ltd.     

Facies architecture of a submarine fan channel–levee complex: the Juniper Ridge Conglomerate, Coalinga, California

The Upper Cretaceous Juniper Ridge Conglomerate (JRC) near Coalinga, California, provides a rare, high-quality exposure of a submarine channel to overbank transition. The facies architecture of the JRC comprises a thick, predominantly mudstone sequence overlain by a channellized conglomerate package. Conglomeratic bounding surfaces truncate successions of interbedded turbiditic sandstones and mudstones both vertically and laterally. Thick-bedded, massive sandstones are interbedded with conglomerates. Facies architecture, palaeocurrent indicators, slump features, sandstone percentages and sandstone bed thickness trends lead to the interpretation that these elements comprise channel and overbank facies. A vertical sequence with conglomerate at the base, followed by thick-bedded sandstone, and capped by interbedded turbiditic sandstone and mudstone form a fining-upward lithofacies association that is interpreted as a single channel-fill/overbank system. Three similar lithofacies associations can be related to autocyclic processes of thalweg migration and submarine fan aggradation or to allocyclically driven changes in sediment calibre.     

Hydrogeochemistry of the Simav geothermal field, western Anatolia, Turkey

Thermal waters hosted by Menderes metamorphic rocks emerge along fault lineaments in the Simav geothermal area. Thermal springs and drilled wells are located in the Eynal, Çitgöl and Na a locations, which are part of the Simav geothermal field. Studies were carried out to obtain the main chemical and physical characteristics of thermal waters. These waters are used for heating of residences and greenhouses and for balneological purposes. Bottom temperatures of the drilled wells reach 163°C with total dissolved solids around 2225 mg/kg. Surface temperatures of thermal springs vary between 51°C and 90°C. All the thermal waters belong to Na–HCO₃–SO₄ facies. The cold groundwaters are Ca–Mg–HCO₃ type. Dissolution of host rock and ion-exchange reactions in the reservoir of the geothermal system shift the Ca–Mg–HCO₃ type cold groundwaters to the Na–HCO₃–SO₄ type thermal waters. Thermal waters are oversaturated at discharge temperatures for aragonite, calcite, quartz, chalcedony, magnesite and dolomite minerals giving rise to a carbonate-rich scale. Gypsum and anhydrite minerals are undersaturated with all of the thermal waters. Boiling during ascent of the thermal fluids produces steam and liquid waters resulting in an increase of the concentrations of the constituents in discharge waters. Steam fraction, y, of the thermal waters of which temperatures are above 100°C is between 0.075 and 0.119. Reservoir pH is much lower than pH measured in the liquid phase separated at atmospheric conditions, since the latter experienced heavy loss of acid gases, mainly CO₂. Assessment of the various empirical chemical geothermometers and geochemical modelling suggest that reservoir temperatures vary between 175°C and 200°C.     

The 3D simulation and optimized management model of groundwater systems based on eco-environmental water demand

Through the study of mutual process between groundwater systems and eco-environmental water demand, the eco-environmental water demand is brought into groundwater systems model as the important water consumption item and unification of groundwater’s economic, environmental and ecological functions were taken into account. Based on eco-environmental water demand at Da’an in Jilin province, a three-dimensional simulation and optimized management model of groundwater systems was established. All water balance components of groundwater systems in 1998 and 1999 were simulated with this model and the best optimal exploitation scheme of groundwater systems in 2000 was determined, so that groundwater resource was efficiently utilized and good economic, ecologic and social benefits were obtained.     

On the spatial relationship between landslides and causative factors on Lantau Island, Hong Kong

This paper presents a statistical approach to study the spatial relationship between landslides and their causative factors at the regional level. The approach is based on digital databases, and incorporates such methods as statistics, spatial pattern analysis, and interactive mapping. Firstly, the authors propose an object-oriented conceptual model for describing a landslide event, and a combined database of landslides and environmental factors is constructed by integrating the various databases within such a conceptual framework. The statistical histogram, spatial overlay, and dynamic mapping methods are linked together to interactively evaluate the spatial pattern of the relationship between landslides and their causative factors. A case study of an extreme event in 1993 on Lantau Island indicates that rainfall intensity and the migration of the center of the rainstorm greatly influence the occurrence of landslides on Lantau Island. A regional difference in the relationship between landslides and topography is identified. Most of the landslides in the middle and western parts of the island occurred on slopes with slope angles of 25–35°, while in the eastern part, the corresponding range is 30–35°. Overlaying landslide data with land cover reveals that a large number of landslides occurred in the bareland and shrub-covered area, and in the transition zones between different vegetation types. The proposed approach can be used not only to analyze the general characteristics of such a relationship, but also to depict its spatial distribution and variation, thereby providing a sound basis for regional landslide prediction.     

Issues of Globalization and Reflexivity in the Japanese Tourism Production System: The Case of Whistler,British Columbia

This article examines contemporary Japanese overseas tourism from a supplier‐side perspective using the concept of production systems. We first outline characteristics of the evolving structure of Japanese overseas tourism, with an emphasis on the global spread of Japanese travel companies. This provides a frame for presenting an empirical account of the transactional relationships in the Japanese package tour production system in Whistler, British Columbia, where Japanese tour operators play a pivotal role. We conclude that the recent expansion of Japanese travel companies is fostering the functional integration of the global tourism production system and exhibits increasing reflexivity.     

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.