919 resultados para Drop on Demand


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The continued outward growth from a central business district has been the dominant characteristic of most cities in Australia. However, this feature is seen as unsustainable and alternative scenarios to contain the outward growth are being proposed. Melbourne is currently grappling with this issue while simultaneously trying to reduce per capita greenhouse gas emissions. Housing size, style and its location are the three principal factors which determine the emissions from the residential sector. This paper describes a methodology to assess the combined impact of these factors on past and possible future forms of residential development in Melbourne. The analysis found that the location of the housing and its size are the dominant factors determining energy use and greenhouse gas emissions.

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An experiment is described in which a mica surface is driven towards a mercury drop immersed in aqueous electrolyte. Under appropriate conditions, hydrodynamic pressure in the aqueous film creates a classical dimple in the mercury drop. The use of optical interferometry and video recording to monitor the shape of the drop and the thickness of the aqueous film with sub-nanometre resolution yields a high density of precise data showing the formation and evolution of the dimple as the film drains. Variation of electrical potential applied to the mercury phase allows control of the surface forces acting between the drop and the mica surface, so that the effect of surface forces on the film drainage process is highlighted. It is found that the film thickness at the centre of the dimple and the lateral extent of the dimple are not significantly affected by surface forces. On the other hand, the minimum film thickness at the edge of the dimple is sensitive even to weak surface forces. Since this minimum film thickness is a major determinant of the film drainage rate, it is shown that surface forces have an important effect on the overall drainage process.

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This paper describes an experiment designed to measure surface and hydrodynamic forces between a mercury drop and a flat mica surface immersed in an aqueous medium. An optical interference technique allows measurement of the shape of the mercury drop as well as its distance from the mica, for various conditions of applied potential, applied pressure, and solution conditions. This enables a detailed exploration of the surface forces, particularly double-layer forces, between mercury and mica. A theoretical analysis of drop shape under the influence of surface forces shows that deformation of the drop is a sensitive indicator of the forces, as well as being a very important factor in establishing the overall interaction between the solid and the fluid.

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This paper proposes a method of improving level of service in congested urban railways by means of a triple-track line operation for a highly dense urban area with special travel demand characteristics. Where the future travel demand forecasts show sluggish growth or no growth at all, there is little to no incentives for heavy railway investments like quadruple-track extension and construction of new railway routes to alleviate current railway congestion problems. In such a situation, triple-track line operation can be the best alternative due to its moderate investment cost and ease in land acquisition for just an additional single track along the existing tracks. Our simulation investigation in one of the congested railway lines in Tokyo showed that triple track line operation increases railway capacity by 26% and shortens travel time by 38% in peak direction during morning peak hours. These results are encouraging and are useful for removing current railways problems in Tokyo and in similar urban situations elsewhere.

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In this paper, we empirically analyze the effects of trade reforms on import demand and derive their implications on economic development in Turkey, a country that underwent sudden and substantial trade liberalization in the mid-1980s. The tool for this analysis is the estimation of disaggregated import demand elasticities. The adoption of a more liberal trade regime as well as radical attempts to foster economic development makes the Turkish experience particularly interesting for analysis. Almost all of our elasticities are estimated to be significant, unlike those of most previous studies in the literature on other countries. We test for different elasticities over “closed” and “open” economy periods, and find that the effects of the trade reforms of the 1980s were significant for a number of industries that form the backbone of the Turkish economy. We also compare our results with elasticity estimates from past studies for developed countries.

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An accurate measurement of the impacts of external shocks on construction demand will enable construction industry policymakers and developers to make allowances for future occurrences and advance the construction industry in a sustainable manner. This paper aims to measurethe dynamic effects of the late 2000s global financial crisis on the level of demand in the Australian construction industry. The vector error correction (VEC) model with intervention indicators is employed to estimate the external impact from the crisis on a macro-level construction economic indicator, namely construction demand. The methodology comprises six main stages to produce appropriate VEC models that describe the characteristics of the underlying process. Research findings suggestthat overall residential and non-residential construction demand were affected significantly by the recent crisis and seasonality. Non-residentialconstruction demand was disrupted more than residential construction demand at the crisis onset. The residential constructionindustry is more reactive and is able to recover faster following the crisis in comparison with the non-residential industry. The VEC model with intervention indicators developed in this study can be used as an experiment for an advanced econometric method. This can be used to analyse the effects of special eventsand factors not only on construction but also on other industries.

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Developing sustainable e-learning requires a better understanding of the perceptions and preferences of e-learning providers and e-learners on the four crucial dimensions for elearning success including pedagogies, technologies, learning resources and management of learning resources. There is, however, little research on evaluating whether these critical dimensions are perceived as critical by e-learning providers and e-learners. To address this issue, this study investigates the gap between e-learners’ and e-learning providers’ perceptions and preferences on these critical dimensions for e-learning effectiveness. Such an investigation paves the way for developing appropriate measures to reduce the gap between the supply and the demand for sustainable e-learning.

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Electrical load forecasting plays a vital role in order to achieve the concept of next generation power system such as smart grid, efficient energy management and better power system planning. As a result, high forecast accuracy is required for multiple time horizons that are associated with regulation, dispatching, scheduling and unit commitment of power grid. Artificial Intelligence (AI) based techniques are being developed and deployed worldwide in on Varity of applications, because of its superior capability to handle the complex input and output relationship. This paper provides the comprehensive and systematic literature review of Artificial Intelligence based short term load forecasting techniques. The major objective of this study is to review, identify, evaluate and analyze the performance of Artificial Intelligence (AI) based load forecast models and research gaps. The accuracy of ANN based forecast model is found to be dependent on number of parameters such as forecast model architecture, input combination, activation functions and training algorithm of the network and other exogenous variables affecting on forecast model inputs. Published literature presented in this paper show the potential of AI techniques for effective load forecasting in order to achieve the concept of smart grid and buildings.

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An accurate estimation of pressure drop due to vehicles inside an urban tunnel plays a pivotal role in tunnel ventilation issue. The main aim of the present study is to utilize computational intelligence technique for predicting pressure drop due to cars in traffic congestion in urban tunnels. A supervised feed forward back propagation neural network is utilized to estimate this pressure drop. The performance of the proposed network structure is examined on the dataset achieved from Computational Fluid Dynamic (CFD) simulation. The input data includes 2 variables, tunnel velocity and tunnel length, which are to be imported to the corresponding algorithm in order to predict presure drop. 10-fold Cross validation technique is utilized for three data mining methods, namely: multi-layer perceptron algorithm, support vector machine regression, and linear regression. A comparison is to be made to show the most accurate results. Simulation results illustrate that the Multi-layer perceptron algorithm is able to accurately estimate the pressure drop.

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For strictly quasi concave differentiable utility functions, demand is shown to be differentiable almost everywhere if marginal utilities are pointwise Lipschitzian. For concave utility functions, demand is differentiable almost everywhere in the case of differentiable additively separable utility or in the case of quasi-linear utility.

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This paper investigates which properties money-demand functions have to satisfy to be consistent with multidimensional extensions of Lucasí(2000) versions of the Sidrauski (1967) and the shopping-time models. We also investigate how such classes of models relate to each other regarding the rationalization of money demands. We conclude that money demand functions rationalizable by the shoppingtime model are always rationalizable by the Sidrauski model, but that the converse is not true. The log-log money demand with an interest-rate elasticity greater than or equal to one and the semi-log money demand are counterexamples.

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This paper evaluates the long-run effects of economic instability. In particular, we study the impact of idiosyncratic shocks to father’s income on children’s human capital accumulation variables such as school drop-outs, repetition rates and domestic and non-domestic labor. Although, the problem of child labor in Brazil has declined greatly during the last decade, the number of children working is still substantial. The low levels of educational attainment in Brazil are also a main cause for concern. The large rotating panel data set used allows for the estimation of the impacts of changes in occupational and income status of fathers on changes in his child’s time allocation circumstances. The empirical analysis is restricted to families with fathers, mothers and at least one child between 10 and 15 years of age in the main Brazilian metropolitan areas during the 1982-1999 period. We perform logistic regressions controlling for child characteristics (gender, age, if he/she is behind in school for age), parents characteristics (grade attainment and income) and time and location variables. The main variables analyzed are dynamic proxies of impulses and responses, namely: shocks to household head’s income and unemployment status, on the one hand and child’s probability of dropping out of school, of repeating a grade and of start working, on the other. The findings suggest that father’s income has a significant positive correlation with child’s dropping out of school and of repeating a grade. The findings do not suggest a significant relationship between a father’s becoming unemployed and a child entering the non-domestic labor market. However, the results demonstrate a significant positive relationship between a father becoming unemployed and a child beginning to work in domestic labor. There was also a positive correlation between father becoming unemployed and a child dropping out and repeating a grade. Both gender and age were highly significant with boys and older children being more likely to work, drop-out and repeat grades.