974 resultados para transverse stochastic cooling


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Green roof plants alter the microclimate of building roofs and may improve roof insulation. They act by providing cooling by shading, but also through transpiration of water through their stomata. However, leaf surfaces can become warmer when plants close the stomata and decrease water loss in response to drying substrate (typically associated with green roofs during summers), also reducing transpirational cooling. By using a range of contrasting plant types (Sedum mix – an industry green roof ‘standard’, Stachys byzantina, Bergenia cordifolia and Hedera hibernica) we tested the hypothesis that plants differ in their ‘cooling potential’. We firstly examined how leaf morphology influenced leaf temperature and how drying substrate altered that response. Secondly, we investigated the relationship between leaf surface temperatures and the air temperatures immediately above the canopies (i.e. potential to provide aerial cooling). Finally we measured how the plant type influenced the substrate temperature below the canopy (i.e. potential for building cooling). In our experiments Stachys outperformed the other species in terms of leaf surface cooling (even in drying substrate, e.g. 5 oC cooler compared with Sedum), substrate cooling beneath its canopy (up to 12 oC) and even - during short intervals over hottest still periods - the air above the canopy (up to 1 oC, when soil moisture was not limited). We suggest that the choice of plant species on green roofs should not be entirely dictated by what survives on the shallow substrates of extensive systems, but consideration should be given to supporting those species providing the greatest eco-system service potential.

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We discuss the time evolution of the wave function which is the solution of a stochastic Schrödinger equation describing the dynamics of a free quantum particle subject to spontaneous localizations in space. We prove global existence and uniqueness of solutions. We observe that there exist three time regimes: the collapse regime, the classical regime and the diffusive regime. Concerning the latter, we assert that the general solution converges almost surely to a diffusing Gaussian wave function having a finite spread both in position as well as in momentum. This paper corrects and completes earlier works on this issue.

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We consider the relation between so called continuous localization models—i.e. non-linear stochastic Schrödinger evolutions—and the discrete GRW-model of wave function collapse. The former can be understood as scaling limit of the GRW process. The proof relies on a stochastic Trotter formula, which is of interest in its own right. Our Trotter formula also allows to complement results on existence theory of stochastic Schrödinger evolutions by Holevo and Mora/Rebolledo.

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Direct outdoor air cooling contributes a lot not only to the improvement of the indoor air quality but also to the energy saving. Its full use will reduce the water chiller’s running time especially in some stores where cooling load keeps much higher and longer than that in other buildings. A novel air-conditioning system named Combined Variable Air Volume system (CVAV), combining a normal AHU with a separate outdoor air supply system, was proposed firstly by the authors. The most attractive feature of the system is its full utilization of cooling capacity and freshness of outdoor air in the transition period of the year round. On the basis of the obtain of the dynamic cooling loads of the typical shopping malls in different four cities located in cold climates in China with the aid of DOE-2, the possibility of increasing the amount of outdoor air volume of CVAV system in the transition period instead of operating the water chillers was confirmed. Moreover, a new concept, Direct Outdoor Air Cooling Efficiency (DOACE), was defined as the ratio of cooling capacity of outdoor air to the water chiller, indicating the degree of outdoor air’s utilization. And the DOACE of the CVAV was calculated and compared with that of conventional all-air constant volume air-conditioning systems, the results showed that CVAV bear much more energy saving potential with the 10%~19% higher DOACE and it is a kind of energy efficient systems and can improve the indoor air quality as well.

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In this paper, numerical analyses of the thermal performance of an indirect evaporative air cooler incorporating a M-cycle cross-flow heat exchanger has been carried out. The numerical model was established from solving the coupled governing equations for heat and mass transfer between the product and working air, using the finite-element method. The model was developed using the EES (Engineering Equation Solver) environment and validated by published experimental data. Correlation between the cooling (wet-bulb) effectiveness, system COP and a number of air flow/exchanger parameters was developed. It is found that lower channel air velocity, lower inlet air relative humidity, and higher working-to-product air ratio yielded higher cooling effectiveness. The recommended average air velocities in dry and wet channels should not be greater than 1.77 m/s and 0.7 m/s, respectively. The optimum flow ratio of working-to-product air for this cooler is 50%. The channel geometric sizes, i.e. channel length and height, also impose significant impact to system performance. Longer channel length and smaller channel height contribute to increase of the system cooling effectiveness but lead to reduced system COP. The recommend channel height is 4 mm and the dimensionless channel length, i.e., ratio of the channel length to height, should be in the range 100 to 300. Numerical study results indicated that this new type of M-cycle heat and mass exchanger can achieve 16.7% higher cooling effectiveness compared with the conventional cross-flow heat and mass exchanger for the indirect evaporative cooler. The model of this kind is new and not yet reported in literatures. The results of the study help with design and performance analyses of such a new type of indirect evaporative air cooler, and in further, help increasing market rating of the technology within building air conditioning sector, which is currently dominated by the conventional compression refrigeration technology.

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This paper provides a comparative study of the performance of cross-flow and counter-flow M-cycle heat exchangers for dew point cooling. It is recognised that evaporative cooling systems offer a low energy alternative to conventional air conditioning units. Recently emerged dew point cooling, as the renovated evaporative cooling configuration, is claimed to have much higher cooling output over the conventional evaporative modes owing to use of the M-cycle heat exchangers. Cross-flow and counter-flow heat exchangers, as the available structures for M-cycle dew point cooling processing, were theoretically and experimentally investigated to identify the difference in cooling effectiveness of both under the parallel structural/operational conditions, optimise the geometrical sizes of the exchangers and suggest their favourite operational conditions. Through development of a dedicated computer model and case-by-case experimental testing and validation, a parametric study of the cooling performance of the counter-flow and cross-flow heat exchangers was carried out. The results showed the counter-flow exchanger offered greater (around 20% higher) cooling capacity, as well as greater (15%–23% higher) dew-point and wet-bulb effectiveness when equal in physical size and under the same operating conditions. The cross-flow system, however, had a greater (10% higher) Energy Efficiency (COP). As the increased cooling effectiveness will lead to reduced air volume flow rate, smaller system size and lower cost, whilst the size and cost are the inherent barriers for use of dew point cooling as the alternation of the conventional cooling systems, the counter-flow system is considered to offer practical advantages over the cross-flow system that would aid the uptake of this low energy cooling alternative. In line with increased global demand for energy in cooling of building, largely by economic booming of emerging developing nations and recognised global warming, the research results will be of significant importance in terms of promoting deployment of the low energy dew point cooling system, helping reduction of energy use in cooling of buildings and cut of the associated carbon emission.

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The probabilistic projections of climate change for the United Kingdom (UK Climate Impacts Programme) show a trend towards hotter and drier summers. This suggests an expected increase in cooling demand for buildings – a conflicting requirement to reducing building energy needs and related CO2 emissions. Though passive design is used to reduce thermal loads of a building, a supplementary cooling system is often necessary. For such mixed-mode strategies, indirect evaporative cooling is investigated as a low energy option in the context of a warmer and drier UK climate. Analysis of the climate projections shows an increase in wet-bulb depression; providing a good indication of the cooling potential of an evaporative cooler. Modelling a mixed-mode building at two different locations, showed such a building was capable of maintaining adequate thermal comfort in future probable climates. Comparing the control climate to the scenario climate, an increase in the median of evaporative cooling load is evident. The shift is greater for London than for Glasgow with a respective 71.6% and 3.3% increase in the median annual cooling load. The study shows evaporative cooling should continue to function as an effective low-energy cooling technique in future, warming climates.

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Recent activity in the development of future weather data for building performance simulation follows recognition of the limitations of traditional methods, which have been based on a stationary (observed) climate. In the UK, such developments have followed on from the availability of regional climate models as delivered in UKCIP02 and recently the probabilistic projections released under UKCP09. One major area of concern is the future performance and adaptability of buildings which employ exclusively passive or low-energy cooling systems. One such method which can be employed in an integral or retrofit situation is direct or indirect evaporative cooling. The effectiveness of evaporative cooling is most strongly influenced by the wet-bulb depression of the ambient air, hence is generally regarded as most suited to hot, dry climates. However, this technology has been shown to be effective in the UK, primarily in mixed-mode buildings or as a retrofit to industrial/commercial applications. Climate projections for the UK generally indicate an increase in the summer wet-bulb depression, suggesting an enhanced potential for the application of evaporative cooling. The paper illustrates this potential by an analysis of the probabilistic scenarios released under UKCP09, together with a detailed building/plant simulation of case study building located in the South-East of England. The results indicate a high probability that evaporative cooling will still be a viable low-energy technique in the 2050s.

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The Chartered Institute of Building Service Engineers (CIBSE) produced a technical memorandum (TM36) presenting research on future climate impacting building energy use and thermal comfort. One climate projection for each of four CO2 emissions scenario were used in TM36, so providing a deterministic outlook. As part of the UK Climate Impacts Programme (UKCIP) probabilistic climate projections are being studied in relation to building energy simulation techniques. Including uncertainty in climate projections is considered an important advance to climate impacts modelling and is included in the latest UKCIP data (UKCP09). Incorporating the stochastic nature of these new climate projections in building energy modelling requires a significant increase in data handling and careful statistical interpretation of the results to provide meaningful conclusions. This paper compares the results from building energy simulations when applying deterministic and probabilistic climate data. This is based on two case study buildings: (i) a mixed-mode office building with exposed thermal mass and (ii) a mechanically ventilated, light-weight office building. Building (i) represents an energy efficient building design that provides passive and active measures to maintain thermal comfort. Building (ii) relies entirely on mechanical means for heating and cooling, with its light-weight construction raising concern over increased cooling loads in a warmer climate. Devising an effective probabilistic approach highlighted greater uncertainty in predicting building performance, depending on the type of building modelled and the performance factors under consideration. Results indicate that the range of calculated quantities depends not only on the building type but is strongly dependent on the performance parameters that are of interest. Uncertainty is likely to be particularly marked with regard to thermal comfort in naturally ventilated buildings.

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The relationship between price volatility and competition is examined. Atheoretic, vector auto regressions on farm prices of wheat and retail prices of derivatives (flour, bread, pasta, bulgur and cookies) are compared to results from a dynamic, simultaneous-equations model with theory-based farm-to-retail linkages. Analytical results yield insights about numbers of firms and their impacts on demand- and supply-side multipliers, but the applications to Turkish time series (1988:1-1996:12) yield mixed results.

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We develop and analyze a class of efficient Galerkin approximation methods for uncertainty quantification of nonlinear operator equations. The algorithms are based on sparse Galerkin discretizations of tensorized linearizations at nominal parameters. Specifically, we consider abstract, nonlinear, parametric operator equations J(\alpha ,u)=0 for random input \alpha (\omega ) with almost sure realizations in a neighborhood of a nominal input parameter \alpha _0. Under some structural assumptions on the parameter dependence, we prove existence and uniqueness of a random solution, u(\omega ) = S(\alpha (\omega )). We derive a multilinear, tensorized operator equation for the deterministic computation of k-th order statistical moments of the random solution's fluctuations u(\omega ) - S(\alpha _0). We introduce and analyse sparse tensor Galerkin discretization schemes for the efficient, deterministic computation of the k-th statistical moment equation. We prove a shift theorem for the k-point correlation equation in anisotropic smoothness scales and deduce that sparse tensor Galerkin discretizations of this equation converge in accuracy vs. complexity which equals, up to logarithmic terms, that of the Galerkin discretization of a single instance of the mean field problem. We illustrate the abstract theory for nonstationary diffusion problems in random domains.

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The recent roll-out of smart metering technologies in several developed countries has intensified research on the impacts of Time-of-Use (TOU) pricing on consumption. This paper analyses a TOU dataset from the Province of Trento in Northern Italy using a stochastic adjustment model. Findings highlight the non-steadiness of the relationship between consumption and TOU price. Weather and active occupancy can partly explain future consumption in relation to price.

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Nocturnal cooling of air within a forest canopy and the resulting temperature profile may drive local thermally driven motions, such as drainage flows, which are believed to impact measurements of ecosystem–atmosphere exchange. To model such flows, it is necessary to accurately predict the rate of cooling. Cooling occurs primarily due to radiative heat loss. However, much of the radiative loss occurs at the surface of canopy elements (leaves, branches, and boles of trees), while radiative divergence in the canopy air space is small due to high transmissivity of air. Furthermore, sensible heat exchange between the canopy elements and the air space is slow relative to radiative fluxes. Therefore, canopy elements initially cool much more quickly than the canopy air space after the switch from radiative gain during the day to radiative loss during the night. Thus in modeling air cooling within a canopy, it is not appropriate to neglect the storage change of heat in the canopy elements or even to assume equal rates of cooling of the canopy air and canopy elements. Here a simple parameterization of radiatively driven cooling of air within the canopy is presented, which accounts implicitly for radiative cooling of the canopy volume, heat storage in the canopy elements, and heat transfer between the canopy elements and the air. Simulations using this parameterization are compared to temperature data from the Morgan–Monroe State Forest (IN, USA) FLUXNET site. While the model does not perfectly reproduce the measured rates of cooling, particularly near the top of the canopy, the simulated cooling rates are of the correct order of magnitude.

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In this article, we illustrate experimentally an important consequence of the stochastic component in choice behaviour which has not been acknowledged so far. Namely, its potential to produce ‘regression to the mean’ (RTM) effects. We employ a novel approach to individual choice under risk, based on repeated multiple-lottery choices (i.e. choices among many lotteries), to show how the high degree of stochastic variability present in individual decisions can distort crucially certain results through RTM effects. We demonstrate the point in the context of a social comparison experiment.