1,721,266 research outputs found
Cuomo (S.), Pappus of Alexandria and the mathematics of Late Antiquity. (Cambridge Classical Studies), 2000
No full textFederspiel Michel. Cuomo (S.), Pappus of Alexandria and the mathematics of Late Antiquity. (Cambridge Classical Studies), 2000. In: Revue des Études Anciennes. Tome 103, 2001, n°3-4. pp. 557-559
Modelling of rainfall-induced runoff and superficial erosion in unsaturated air-fall soil deposits
No full textModelling of flowslides and debris avalanches in natural and engineered slopes: a review
No full textBackground: The landslides of the flow-type are dangerous and also challenging to study. A wide literature has been investigating the principal mechanisms governing each stage in which these phenomena can be ideally subdivided: failure, post-failure and propagation. However, holistic contributions and general overviews are very rare. In addition, a number of numerical methods have been issued and validated so that new chances exist to efficiently model those threats. The paper focuses on two classes of rainfall-induced landslides of the flow-type, namely debris flows and debris avalanches. The principal numerical methods are reviewed for modelling the landslide initiation and propagation and are later used for analyzing a series of benchmark slopes and real case histories which are successfully simulated. Results: The rainfall from ground surface and water spring from the bedrock are key factors for slope instability. Pore water pressure plays a relevant role also during the propagation stage. The entrainment of further material makes the propagation patterns complex due to lateral spreading and slow-down of the front of flows. It is shown that the used models are capable to provide useful indications even for combined channelized and unchannelized flows. Conclusions: Notwithstanding the complexity of flow-like landslides and the related challenges in modelling, the understanding and forecasting of such natural hazards is achievable with a satisfactory confidence. Among the key factors, rainfall, pore water pressure and bed entrainment deserves a special attention. Further improvements are expectable as the numerical models are becoming more efficient. Thus, more accurate descriptions of local effects will be possible and also additional mechanisms will be eventually analysed
Material Point Method modelling of cascading effects of flow-like lanslides
No full textThe Material Point Method (MPM) is here used to reproduce the hydro-mechanical coupling between solid particle and pore water pressure inside the soil involved in flow-like landslides. Examples are considered for the case of shallow soil deposits mobilized along steep slopes and impacting buildings and artificial barriers. Multiple mechanisms and cascading effects are investigated. Of special interest is the case of debris avalanches, which are characterized by impact loading, lateral thrust of stable soil and entrainment of material during the landslide propagation path. MPM is one of the most suitable method to deal with static equilibrium of elasto-plastic materials in the pre-failure stage, large deformations upon failure, extremely large displacements during the propagation stage while tracking the stress-strain history of the materials involved
On a Class of Integrals Useful to Solve Well-Type Flows in Heterogeneous Porous Formations
No full textWe provide analytical (closed form) expression for a class of integrals that frequently arise into modeling well-type flows through heterogeneous porous formations. In particular, these integrals are encountered when ensemble (second-order) moments of the flow variables are computed by means of a perturbation approach that regards the variance σY2 of the random field Y ≡ In K (being K the hydraulic conductivity) as a small paramete
An efficient localized meshless method based on the space–time gaussian rbf for high-dimensional space fractional wave and damped equations
No full textIn this paper, an efficient localized meshless method based on the space–time Gaussian radial basis functions is discussed. We aim to deal with the left Riemann–Liouville space fractional derivative wave and damped wave equation in high-dimensional space. These significant problems as anomalous models could arise in several research fields of science, engineering, and technology. Since an explicit solution to such equations often does not exist, the numerical approach to solve this problem is fascinating. We propose a novel scheme using the space–time radial basis function with advantages in time discretization. Moreover this approach produces the (n + 1)-dimensional spatial-temporal computational domain for n-dimensional problems. Therefore the local feature, as a remarkable and efficient property, leads to a sparse coefficient matrix, which could reduce the computational costs in high-dimensional problems. Some benchmark problems for wave models, both wave and damped, have been considered, highlighting the proposed method performances in terms of accuracy, efficiency, and speed-up. The obtained experimental results show the computational capabilities and advantages of the presented algorithm
A Sojourn-Based Approach to Semi-Markov Reinforcement Learning
No full textIn this paper we introduce a new approach to discrete-time semi-Markov decision processes based on the sojourn time process. Different characterizations of discrete-time semi-Markov processes are exploited and decision processes are constructed by their means. With this new approach, the agent is allowed to consider different actions depending also on the sojourn time of the process in the current state. A numerical method based on Q-learning algorithms for finite horizon reinforcement learning and stochastic recursive relations is investigated. Finally, we consider two toy examples: one in which the reward depends on the sojourn-time, according to the gambler’s fallacy; the other in which the environment is semi-Markov even if the reward function does not depend on the sojourn time. These are used to carry on some numerical evaluations on the previously presented Q-learning algorithm and on a different naive method based on deep reinforcement learning
Wetting test and X-ray computed tomography of volcanic unsaturated sands
No full textWetting can induce the so-called 'capillary collapse' in loose unsaturated soils. Collapse mechanisms have been studied at macro-scale for many years, while few observations at micro-scale are available. In this work, wetting tests were conducted by combining X-ray computed tomography (CT) and image treatment to investigate the soil collapse of volcanic sands of southern Italy at both macro- and micro-scale. The specimens were tested under self-weight and the matric suction was gradually reduced until collapse. Standard techniques and image analysis were used to measure the porosity and degree of saturation for the whole specimen, while image analysis of sub-volumes was done at micro-scale. The X-ray CT-aided wetting tests allowed: (a) the analysis of soil microstructure and its variations, (b) the accurate measurements of porosity and degree of saturation for differently sized representative element volumes (REVs). The local modifications of soil internal structure were measured and compared with the overall behaviour of the whole specimen. The porosity changed both in REV-averaged values and spatial distribution. The degree of saturation increased while keeping similar spatial distribution until collapse. The insights at both micro- and macro-scale provided a rational overview of the complex mechanisms regulating the pre- and post-collapse configuration of soil
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