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The rapid drawdown of reservoir may have a significant impact on the stability of adjacent slopes. In order to avoid potential risks, it is important to calculate the change of slope safety factor prior to the reservoir operation. The finite element method is used to analyze the transient seepage during drawdown, and then the pore water pressures are introduced into the stability computation based on limit equilibrium to obtain the transient safety factor. Computations show that for slopes with a specific geometry, the safety factor ratio depends on the parameters K/(Syv) (where K is the permeability coefficient, v is the drawdown speed, and Sy is the specific yield) and c′/(γHtan ϕ′) (where c′ and ϕ′ are the effective cohesion and friction angle, γ is the soil unit weight, and H is the slope height). By considering a wide range of K/(Syv) and c′/(γHtan ϕ′) values and different slope geometries, the percent reduction in critical safety factor of slope during drawdown relative to that during steady-state seepage is obtained. The drawdown condition that causes a large percent reduction in safety factor is judged as a rapid drawdown, and the opposite is a slow drawdown, which does not affect the slope design. This paper presents a series of charts for engineers and designers to judge rapid and slow drawdown conditions. Before the reservoir operation, the appropriate drawdown speed is selected according to the charts to ensure a slow drawdown for adjacent slope, while in the slope stabilization design, only the rapid drawdown stability analysis needs to be performed. [ABSTRACT FROM AUTHOR]

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Developing robust and reliable control code for autonomous mobile robots is difficult, because the interaction between a physical robot and the environment is highly complex, it is subject to noise and variation, and therefore partly unpredictable. This means that to date it is not possible to predict robot behaviour, based on theoretical models. Instead, current methods to develop robot control code still require a substantial trial-and-error component to the software design process. Such iterative refinement could be reduced, we argue, if a more profound theoretical understanding of robot-environment interaction existed. In this paper, we therefore presented a modelling method that generates a faithful model of a robot's behaviour. Because this modelling method--nonlinear modelling using polynomials--is commonly used in the engineering discipline of system identification, we refer to it here as "robot identification". We show in this paper that using identification to obtain a computer model of robot-environment interaction offers several distinct advantages: 1. Very compact representations (one-line programs) of the robot control program are generated 2. The model can be analysed, for example through sensitivity analysis, leading to a better understanding of the essential parameters underlying the robot's behavior, and 3. The generated, compact robot code can be used for cross-platform robot programming, allowing fast transfer of robot code from one type to another. We demonstrate these points through experiments with a Magellan Pro and a Nomad 200 mobile robot. [ABSTRACT FROM AUTHOR]