1000 resultados para blower door testing


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A one-man performance for young audiences developed with the support of the Australia Council in 2004. Next Door portrays the same half-hour in the lives of two cowboy neighbours, experienced from both sides of the wall that divides them. It’s a humorous examination of how humanity’s greatest strength – imagination, can be used to distort perception and alienate the ‘other’.

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This paper presents a study into the behaviour of extruded polystyrene foam at low strain rates. The foam is being studied in order assess its potential for use as part of a new innovative design of portable road safety barrier the aim to consume less water and reduce rates of serious injury. The foam was tested at a range of low strain rates, with the stress and strain behaviour of the foam specimens being recorded. The energy absorption capabilities of the foam were assessed as well as the response of the foam to multiple loadings. The experimental data was then used to create a material model of the foam for use in the explicit finite element solver LS-DYNA. Simulations were carried out using the material model which showed excellent correlation between the numerical material model and the experimental data.

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The OECD (2006 Starting Strong II: Early Childhood Education and Care. OECD Publishing: Paris) envisions early childhood education and care settings as meeting places for diverse social groups; places that build social capital. This vision was assessed in a comparison of three preschools types: full-fee paying, subsidised-fee and publicly funded. The social composition within each was examined and the connectedness of the children (n = 472) who attended compared. Publicly funded preschools had more socially diverse populations. The quantity of social connectedness did not differ but children in publicly funded preschools described higher quality social relationships. Not all preschool settings are socially diverse but, where they are, the quality of relationships is highest.

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The topic of fault detection and diagnostics (FDD) is studied from the perspective of proactive testing. Unlike most research focus in the diagnosis area in which system outputs are analyzed for diagnosis purposes, in this paper the focus is on the other side of the problem: manipulating system inputs for better diagnosis reasoning. In other words, the question of how diagnostic mechanisms can direct system inputs for better diagnosis analysis is addressed here. It is shown how the problem can be formulated as decision making problem coupled with a Bayesian Network based diagnostic mechanism. The developed mechanism is applied to the problem of supervised testing in HVAC systems.

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