Reliability assessment of serviceability performance of braced retaining walls using a neural network approach

In urban environments, one major concern with deep excavations in soft clay is the potentially large ground deformations in and around the excavation. Excessive movements can damage adjacent buildings and utilities. There are many uncertainties associated with the calculation of the ultimate or serviceability performance of a braced excavation system. These include the variabilities of the loadings, geotechnical soil properties, and engineering and geometrical properties of the wall. A risk‐based approach to serviceability performance failure is necessary to incorporate systematically the uncertainties associated with the various design parameters. This paper demonstrates the use of an integrated neural network–reliability method to assess the risk of serviceability failure through the calculation of the reliability index. By first performing a series of parametric studies using the finite element method and then approximating the non‐linear limit state surface (the boundary separating the safe and ‘failure’ domains) through a neural network model, the reliability index can be determined with the aid of a spreadsheet. Two illustrative examples are presented to show how the serviceability performance for braced excavation problems can be assessed using the reliability index. Copyright © 2005 John Wiley & Sons, Ltd.     

The wadic project: A comprehensive field evaluation of directional wave instrumentation

The results of a comprehensive field trial of nearly all commercially available directional wave measurement systems at the Edda field in the North Sea during winter 1985-86 are presented. The results summarize the accuracy of the principal engineering wave parameters from each system and the dependence on sea state. Limiting factors on system performance and operational problems are also included in the assessment. Overall experience has been good with systems utilizing widely different measurement principles returning consistent results.     

Heat flow near obstacles in the solar convection zone

Disturbances in the heat flow in the solar convection zone are calculated with a turbulent thermal diffusion coefficient based on a mixing length approximation. As a consequence of the radiative boundary condition at the surface and the strong increase of the diffusion coefficient with depth, the convection zone resembles a thermally superconducting shell enclosed between a thin surface layer and an interior core of low thermal conductivity. Thermal disturbances originating in the convection zone do not penetrate into the interior, and penetrate only weakly through the solar surface. A thermally isolating obstacle buried entirely in the convection zone casts a shadow of reduced temperature at the solar surface; the brightening surrounding this shadow is undetectable. The shadow is weak unless the object is located close to the surface (less than 2000 km). Assuming a sunspot to be an area of reduced thermal conductivity which extends a finite depth into the convection zone, the heat flow around this obstacle is calculated. The heat flux blocked below the spot (missing flux) spreads over a very extended area surrounding the spot. The brightening corresponding to this missing flux is undetectable if the reduction of the thermal conductivity extends to a depth greater than 1000 km. It is concluded that no effect other than a decrease of the convective efficiency is needed to explain the temperature change observed at the solar surface in and around a sunspot. The energy balance is calculated between magnetic flux tubes, oriented vertically in the solar surface, (magnetic elements in active regions and the quiet network) and their surroundings. Near the visible surface radiation enters the tube laterally from the surrounding convection zone. The heating effect of this influx is important for small tubes (less than a few arcseconds). Due to this influx tubes less than about 1 in diameter can appear as bright structures irrespective of the amount of heat conveyed along the tube itself. Through the lateral influx, small tubes such as are found in the quiet network act as little leaks in the solar surface through which an excess heat flux escapes from the convection zone.     

Inferring erosional resistance of bedrock units in the east Tennessee mountains from digital elevation data

Measures of local relief, regional relief, and slope were calculated from digital elevation models (DEMs) for 50 bedrock units in the Ridge and Valley and Blue Ridge provinces of Tennessee. Each of these measures was normalized and the three were then averaged to produce the erosional resistance index (ERI). Bedrock units with higher ERI values include coarse clastics, intermediate clastics, and metaplutonics. Units with lower values include shales, limestones, limestones plus dolostones, and carbonates plus fine clastics. Dolostones tend to have intermediate values. The calculated ERI values were compared with subjective ratings by a geologist with decades of field experience in east Tennessee. Generally, the agreement between the two ratings was good, the most glaring exception being several shales with improbably high ERI values. These turned out to be thin units cropping out beneath very hard sandstones, allowing them to stand higher and steeper than would otherwise be possible. A systematic method for detecting such erroneously high ERI values is suggested. Inspection of a drainage map superimposed on the geology map shows that in a given area, streams tend to flow on rock units with the lowest ERI values. In addition, statistical analysis shows that bedrock units with the lowest ERI values are, on average, almost three times closer to the nearest stream and six times as likely to have streams flowing on them than are units with highest values. Further, the effect of ERI on stream location is strongest for streams with drainage areas between 1 and 30 km². Thus, small streams appear to be subject to greater lithologic control than are larger streams.