18,057 research outputs found

    Large transverse field tunnel splittings in the Fe_8 spin Hamiltonian

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    The spin Hamiltonian that describes the molecular magnet Fe8_8 has biaxial symmetry with mutually perpendicular easy, medium, and hard magnetic axes. Previous calculations of the ground state tunnel splittings in the presence of a magnetic field along the hard axis are extended, and the meaning of the previously discovered oscillation of this splitting is further clarified

    Comparisons of soil suction induced by evapotranspiration and transpiration of S. <i>heptaphylla</i>

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    For a given evapotranspiration (ETr), both soil evaporation and plant transpiration (Tr) would induce soil suction. However, the relative contribution of these two processes to the amount of suction induced is not clear. The objective of this study is to quantify ETr- and Tr-induced suction by a selected tree species, Scheffllera heptaphylla, in silty sand. The relative contribution of transpiration and evaporation to the responses of suction is then explored based on observed differences in Tr- and ETr-induced suction. In total, 12 test boxes were used for testing: 10 for vegetated soil with different values of leaf area index (LAI) and root area index (RAI), while two were for bare soil as references. Each box was exposed to identical atmospheric conditions controlled in a plant room for monitoring suction responses over a week. Due to the additional effects of soil evaporation, ETr-induced suction could be 3%–47% higher than Tr-induced suction, depending on LAI. The significance of evaporation reduced substantially when LAI was higher, as relatively less radiant energy fell on the soil surface for evaporation. For a given LAI, the effects of evaporation were less significant at deeper depths within the root zone. The effects of RAI associated with root-water uptake upon transpiration were the dominant process of ETr affecting the suction responses.</jats:p

    Neural network application to aircraft control system design

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    The feasibility of using artificial neural networks as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research are identified to enhance the practical applicability of neural networks to flight control design
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