Cavitation erosion through water hammer and column separation is a major concern in hydraulic applications such as percussive rock drilling. Cavitation aspects must be considered both in early and late design stages, which require deep knowledge and tools for prediction. In this study, an oil-hydraulic test equipment for water hammer assessment was designed using state-of-the-art simulation tools. Several tests were performed, with and without column separation, showing good repeatability on measured pressures. At higher flow rates, column separation was the dominating feature and several high-pressure peaks with subsequent time delay reduction could be observed. These patterns were affected by the oil temperature, with most substantial changes at lower temperature ranges (<32 °C). Standard transmission line simulations managed to predict the water hammer, but as expected not the column separation, which is the theme of future work using this setup.

Dizziness is commonly associated with anxiety, and is often caused by a dysfunction of the balance system. While a link between dizziness and both anxiety disorders and depression has been established, less is known about information processing in dizziness. In the first experiment we tested whether 15 patients with dizziness would display an emotional Stroop effect for panic-related words. Also included was a control group of 15 persons. The Stroop task was preceded by ratings of personal relevance of the Stroop words and followed by a surprise free recall of the words. Results showed a Stroop effect for panic-related words in the dizziness group, but the interaction did not reach significance (p = 0.08). Separate analysis of dizziness-related panic words however resulted in a significant group x condition interaction. In the free recall of Stroop words a main effect of word category was found, with more panic-related words being recalled. The second experiment investigated autobiographical memories in 14 patients with dizziness and 14 matched controls. Results showed a group x condition interaction with less specific memories being recalled following positive cue-words in the dizziness group. The overall pattern of results suggests that dizziness is related to deficits in information processing, which could be targeted in treatment.

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Cavitation erosion is one of the main concerns in hydraulic rock drills and can reduce both performance as well as life span. Current simulation tools can detect a potential risk of cavitation, however, the equations do not include cavitation physics and therefore cannot estimate the severity nor erosion locations. In order to evaluate the cavitation damage, long term tests are performed which are both costly and time consuming. With better computational capacity and more accurate numerical flow models, the possibilities to simulate the course of cavitation have increased. So far, most numerical studies on cavitation focus on steady-state problems while studies on hydraulic transients and water hammer effects have received less attention. This paper is a step towards simulation of water hammer induced cavitation and cavitation erosion in pipe flow using Computational Fluid Dynamics (CFD). In order to validate the results, experimental measurements are performed with a test equipment that creates hydraulic transients in a pipe and records these using piezoelectric pressure sensors. The results from CFD are compared to both the experimental data and to numerical results from a software called Hopsan, a one-dimensional multi-domain system simulation tool that uses wave characteristics to calculate pressures and flows. For smaller transients where no cavitation occur, all results show good agreement. For larger transients with cavitation, the results from Hopsan do not longer agree with the measurements, while the CFD model still performs well and is able to predict both formation and collapse of cavitation.

Marine propeller design can be carried out with the aid of automated optimization, but experience shows that a such an approach has still been inferior to manual design in industrial scenarios. In this study, the automated propeller design optimization is evolved by integrating human-computer interaction as an intermediate step. An interactive optimization methodology, based on interactive genetic algorithms (IGAs), has been developed, where the blade designers systematically guide a genetic algorithm towards the objectives. The designers visualize and assess the shape of the blade cavitation and this evaluation is integrated in the optimization method. The IGA is further integrated with a support-vector machine model, in order to avoid user fatigue, IGA's main disadvantage. The results of the present study show that the IGA optimization searches solutions in a more targeted manner and eventually finds more non-dominated feasible designs that also show a good cavitation behaviour in agreement with designer preference.

A pipe water hammer with column separation was studied in a range of flow rates (Re=465 to 2239) in a test rig with an acrylic glass observation section. Pressure transients were measured with piezoresistive pressure sensors, while the gas evaporation and condensation were captured by high-speed recording with a Photron SA-Z at a frame rate of 75,000 fps. Separation lengths were estimated by a threshold value in the images. The results did not show a sharp gas–oil interface but consisted of small, dispersed bubbles mixed with larger vapor structures, where the bubbles seemed to become smaller after each collapse. These findings differ from the transient cavitating characteristics commonly reported in nonhydraulic piping systems governed by different fluid properties and time scales. Good repeatability, both in terms of pressure transients and bubble distribution, was observed. The column separation was quantified as a metric of separation length, which was consistent between the tests. Combined with pressure measurements, these results may assist in obtaining a better understanding of the transient cavitation dynamics within oil–hydraulic systems as well as be used to improve modelling strategies towards more accurate cavitation erosion predictions.

Driver's face is a rich source of information for understanding driver behaviour. From the driver's face, one could get an idea of the driver's emotional state and where s/he looks at. In recent years, naturalistic driving studies and field operational tests have been conducted to collect driver behavioural data, which often includes video of the driver, from many drivers driving for an extended period of time. Due to the Data Privacy Act, it is desirable to make the driver video anonymous, while preserving the original facial expressions. This paper describes our attempt to make a system that could do so. The system is a combination of an automatic Facial Action Coding System (FACS) coder based on Active Appearance Models (AAMs), a classifier that analyses local deformations in the AAM shape mesh and a 3D visualisation. The image acquisition hardware is based on a SmartEye eye tracker installed in a vehicle. The eye tracker we used provides a constant image quality independent of external illumination, which is a precondition for deploying the system in a vehicle environment. While the system uses Action Unit (AU) activations internally, the evaluation was done using the six basic emotions.

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