74 resultados para Adaptive Modelling, Entropy Evolution, Sustainable Design
em University of Queensland eSpace - Australia
Resumo:
Sustainable design education is vital for engineering students. This is to allow them to meet the challenges both engineering and the wider community will face in the future. This need has not only been mandated by Engineers Australia’s graduate attributes from an Australian perspective, but more widely the issue of sustainability is one of the greatest challenges humanity has ever faced. Engineers need to be at the forefront of this challenge, because we can not only do the greatest good, but have the potential to cause the greatest harm. The biggest question with respect to the education of engineers about sustainable design is what do engineers need to know, and how best to enable this learning. This paper argues that since the entire phenomenon of sustainable design is constantly growing and changing, it is only by looking at practitioners currently trying design sustainably, and their ways of experiencing sustainable design, can we hope to articulate what it is, and therefore what and how we need to teach engineering students. It also argues that to accommodate sustainable design within engineering, we need to go further and transform the engineering profession to enable it to meet the challenges that sustainability presents. © 2005, Australasian Association for Engineering Education
Resumo:
A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.
Resumo:
This study examined the role of team identification in the dissimilarity and conflict relationship. We tested competing predictions that team identification would either mediate or moderate the positive associations between visible (age, gender and ethnic background), professional (background) and value dissimilarity and task and relationship conflict. Data was collected from 27 MBA student teams twice during a semester. Multilevel modelling and a longitudinal design were used. Results showed that value dissimilarity was positively associated with task and relationship conflict at Time 2. Its effects on relationship conflict at Time 1 were moderated by team identification. Team identification also moderated the effects of gender, age and ethnic dissimilarity on task conflict at Time 2, and the effects of gender and professional dissimilarity on relationship conflict at Time 2. No support was obtained for the mediating role of team identification on the associations between dissimilarity and conflict, or for changes in the effects of dissimilarity over time.
Resumo:
In this paper, we propose a fast adaptive importance sampling method for the efficient simulation of buffer overflow probabilities in queueing networks. The method comprises three stages. First, we estimate the minimum cross-entropy tilting parameter for a small buffer level; next, we use this as a starting value for the estimation of the optimal tilting parameter for the actual (large) buffer level. Finally, the tilting parameter just found is used to estimate the overflow probability of interest. We study various properties of the method in more detail for the M/M/1 queue and conjecture that similar properties also hold for quite general queueing networks. Numerical results support this conjecture and demonstrate the high efficiency of the proposed algorithm.
Resumo:
Abstract: The Murray-Darling Basin comprises over 1 million km2; it lies within four states and one territory; and over 12, 800 GL of irrigation water is used to produce over 40% of the nation's gross value of agricultural production. This production is used by a diverse collection of some-times mutually exclusive commodities (e.g. pasture; stone fruit; grapes; cotton and field crops). The supply of water for irrigation is subject to climatic and policy uncertainty. Variable inflows mean that water property rights do not provide a guaranteed supply. With increasing public scrutiny and environmental issues facing irrigators, greater pressure is being placed on this finite resource. The uncertainty of the water supply, water quality (salinity), combined with where water is utilised, while attempting to maximising return for investment makes for an interesting research field. The utilisation and comparison of a GAMS and Excel based modelling approach has been used to ask: where should we allocate water?; amongst what commodities?; and how does this affect both the quantity of water and the quality of water along the Murray-Darling river system?