Movement of deposited water on turbomachinery rotor blade surfaces

A theoretical approach for calculating the movement of liquid water following deposition onto a turbomachine rotor blade is described. Such a situation can occur during operation of an aero-engine in rain. The equation of motion of the deposited water is developed on an arbitrarily oriented plane triangular surface facet. By dividing the blade surface into a large number of facets and calculating the water trajectory over each one crossed in turn, the overall trajectory can be constructed. Apart from the centrifugal and Coriolis inertia effects, the forces acting on the water arise from the blade surface friction, and the aerodynamic shear and pressure gradient. Non- dimensionalisation of the equations of motion provides considerable insight and a detailed study of water flow on a flat rotating plate set at different stagger angles demonstrates the paramount importance of blade surface friction. The extreme cases of low and high blade friction are examined and it is concluded that the latter (which allows considerable mathematical generalisation) is the most likely in practice. It is also shown that the aerodynamic shear force, but not the pressure force, may influence the water motion. Calculations of water movement on a low-speed compressor blade and the fan blade of a high bypass ratio aero-engine suggest that in low rotational speed situations most of the deposited water is centrifuged rapidly to the blade tip region. Copyright © 2006 by ASME.

TOPS (Task optimization in the presence of signal-dependent noise) model

This paper proposes a movement trajectory planning model, which is a maximum task achievement model in which signal-dependent noise is added to the movement command. In the proposed model, two optimization criteria are combined, maximum task achievement and minimum energy consumption. The proposed model has the feature that the end-point boundary conditions for position, velocity, and acceleration need not be prespecified. Consequently, the method can be applied not only to the simple point-to-point movement, but to any task. In the method in this paper, the hand trajectory is derived by a psychophysical experiment and a numerical experiment for the case in which the target is not stationary, but is a moving region. It is shown that the trajectory predicted from the minimum jerk model or the minimum torque change model differs considerably from the results of the psychophysical experiment. But the trajectory predicted from the maximum task achievement model shows good qualitative agreement with the hand trajectory obtained from the psychophysical experiment. © 2004 Wiley Periodicals, Inc.

An experimental model of relay deployment planning tool for a wireless sensor network system to monitor civil engineering structures

It is essential to monitor deteriorated civil engineering structures cautiously to detect symptoms of their serious disruptions. A wireless sensor network can be an effective system for monitoring civil engineering structures. It is fast to deploy sensors especially in difficult-to-access areas, and it is extendable without any cable extensions. Since our target is to monitor deteriorations of civil engineering structures such as cracks at tunnel linings, most of the locations of sensors are known, and sensors are not required to move dynamically. Therefore, we focus on developing a deployment plan of a static network in order to reduce the value of a cost function such as initial installation cost and summation of communication distances of the network. The key issue of the deployment is the location of relays that forward sensing data from sensors to a data collection device called a gateway. In this paper, we propose a relay deployment-planning tool that can be used to design a wireless sensor network for monitoring civil engineering structures. For the planning tool, we formalize the model and implement a local search based algorithm to find a quasi-optimal solution. Our solution guarantees two routings from a sensor to a gateway, which can provide higher reliability of the network. We also show the application of our experimental tool to the actual environment in the London Underground.

Geotechnical observations of construction OF A large shallow SCL tunnel in soft ground

The Fort Canning Tunnel is the first road tunnel in Singapore to be built using the sprayed concrete lining (SCL) method. The major technical challenge of this was to construct a 15m wide tunnel by mining in soft ground under a shallow overburden of 3m to 9m. This paper describes the geotechnical investigations and monitoring controls for the safe and progressive execution of the works, such as soil investigations, trial forepoling works, surface settlement monitoring, tunnel settlement monitoring, face movement monitoring, and the observational approach to construction. The monitored field data showed the volume loss to range from 0.4% to 2.1%, and the observed surface settlement trough was found to agree well with the theoretical Gaussian trough. Other observations made include substantial surface settlements induced by the stress relief at and ahead of the tunnel face in spite of the forepoling umbrella, and the higher volume losses associated with higher overburden. Tunnel face movements were observed during installation of forepoling. These observations are of interest to engineers planning future SCL tunnels in similar conditions.

Impedance control is tuned to multiple directions of movement

Humans are able to learn tool-handling tasks, such as carving, demonstrating their competency to make and vary the direction of movements in unstable environments. It has been shown that when a single reaching movement is repeated in unstable dynamics, the central nervous system (CNS) learns an impedance internal model to compensate for the environment instability. However, there is still no explanation for how humans can learn to move in various directions in such environments. In this study, we investigated whether and how humans compensate for instability while learning two different reaching movements simultaneously. Results show that when performing movements in two different directions, separated by a 35° angle, the CNS was able to compensate for the unstable dynamics. After adaptation, the force was found to be similar to the free movement condition, but stiffness increased in the direction of instability, specifically for each direction of movement. Our findings suggest that the CNS either learned an internal model generalizing over different movements, or alternatively that it was able to switch between specific models acquired simultaneously. © 2008 IEEE.