This paper presents the findings from a study on gravity-induced slope deformations along the northern slope of Mt. Nuria (Rieti-Italy). The slope extends from the village of Pendenza to the San Vittorino plain and hosts the Peschiera River springs, i.e. the most important springs of the Central Apennines (average discharge: about 18 m3/s).
Detailed geological-geomorphological and geomechanical surveys, supported by a site stress-strain monitoring system and laboratory tests, led us to define the main evolutionary features of the studied phenomena. Based on the collected data, a “geological-evolutionary model” was developed with a view to identifying a spatio-temporal correlation between relief forms, jointing of the rock mass and its stress conditions. The geological-evolutionary model was expected to improve numerical simulations and to test our assumptions.
The numerical model also allowed us to simulate changes in the stress-strain conditions of the rock mass and correlate them with jointing, seepage, as well as with site-detected and site-monitored forms and deformations. In particular, significant relations between seepage, tensile stresses within the rock mass, karst solution and collapse of cavities were identified. 相似文献
The development of numerical methods for stochastic differential equations has intensified over the past decade. The earliest methods were usually heuristic adaptations of deterministic methods, but were found to have limited accuracy regardless of the order of the original scheme. A stochastic counterpart of the Taylor formula now provides a framework for the systematic investigation of numerical methods for stochastic differential equations. It suggests numerical schemes, which involve multiple stochastic integrals, of higher order of convergence. We shall survey the literature on these and on the earlier schemes in this paper. Our discussion will focus on diffusion processes, but we shall also indicate the extensions needed to handle processes with jump components. In particular, we shall classify the schemes according to strong or weak convergence criteria, depending on whether the approximation of the sample paths or of the probability distribution is of main interest. 相似文献
A Lagrangian particle method embedded within a 2-D finite element code, is used to study the transport and ocean–estuary exchange processes in the well-mixed Great Bay Estuarine System in New Hampshire, USA. The 2-D finite element model, driven by residual, semi-diurnal and diurnal tidal constituents, includes the effects of wetting and drying of estuarine mud flats through the use of a porous medium transport module. The particle method includes tidal advection, plus a random walk model in the horizontal that simulates sub-grid scale turbulent transport processes. Our approach involves instantaneous, massive [O(500,000)] particle releases that enable the quantification of ocean–estuary and inter-bay exchanges in a Markovian framework. The effects of the release time, spring–neap cycle, riverine discharge and diffusion strength on the intra-estuary and estuary–ocean exchange are also investigated.The results show a rather dynamic interaction between the ocean and the estuary with a fraction of the exiting particles being caught up in the Gulf of Maine Coastal Current and swept away. Three somewhat different estimates of estuarine residence time are calculated to provide complementary views of estuary flushing. Maps of residence time versus release location uncover a strong spatial dependency of residence time within the estuary that has very important ramifications for local water quality. Simulations with and without the turbulent random walk show that the combined effect of advective shear and turbulent diffusion is very effective at spreading particles throughout the estuary relatively quickly, even at low (1 m2/s) diffusivity. The results presented here show that a first-order Markov Chain approach has applicability and a high potential for improving our understanding of the mixing processes in estuaries. 相似文献