154 resultados para Compact Upwind Scheme


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The Surface Urban Energy and Water Balance Scheme (SUEWS) is developed to include snow. The processes addressed include accumulation of snow on the different urban surface types: snow albedo and density aging, snow melting and re-freezing of meltwater. Individual model parameters are assessed and independently evaluated using long-term observations in the two cold climate cities of Helsinki and Montreal. Eddy covariance sensible and latent heat fluxes and snow depth observations are available for two sites in Montreal and one in Helsinki. Surface runoff from two catchments (24 and 45 ha) in Helsinki and snow properties (albedo and density) from two sites in Montreal are also analysed. As multiple observation sites with different land-cover characteristics are available in both cities, model development is conducted independent of evaluation. The developed model simulates snowmelt related runoff well (within 19% and 3% for the two catchments in Helsinki when there is snow on the ground), with the springtime peak estimated correctly. However, the observed runoff peaks tend to be smoother than the simulated ones, likely due to the water holding capacity of the catchments and the missing time lag between the catchment and the observation point in the model. For all three sites the model simulates the timing of the snow accumulation and melt events well, but underestimates the total snow depth by 18–20% in Helsinki and 29–33% in Montreal. The model is able to reproduce the diurnal pattern of net radiation and turbulent fluxes of sensible and latent heat during cold snow, melting snow and snow-free periods. The largest model uncertainties are related to the timing of the melting period and the parameterization of the snowmelt. The results show that the enhanced model can simulate correctly the exchange of energy and water in cold climate cities at sites with varying surface cover.

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Site-specific meteorological forcing appropriate for applications such as urban outdoor thermal comfort simulations can be obtained using a newly coupled scheme that combines a simple slab convective boundary layer (CBL) model and urban land surface model (ULSM) (here two ULSMs are considered). The former simulates daytime CBL height, air temperature and humidity, and the latter estimates urban surface energy and water balance fluxes accounting for changes in land surface cover. The coupled models are tested at a suburban site and two rural sites, one irrigated and one unirrigated grass, in Sacramento, U.S.A. All the variables modelled compare well to measurements (e.g. coefficient of determination = 0.97 and root mean square error = 1.5 °C for air temperature). The current version is applicable to daytime conditions and needs initial state conditions for the CBL model in the appropriate range to obtain the required performance. The coupled model allows routine observations from distant sites (e.g. rural, airport) to be used to predict air temperature and relative humidity in an urban area of interest. This simple model, which can be rapidly applied, could provide urban data for applications such as air quality forecasting and building energy modelling, in addition to outdoor thermal comfort.

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In recent years, ZigBee has been proven to be an excellent solution to create scalable and flexible home automation networks. In a home automation network, consumer devices typically collect data from a home monitoring environment and then transmit the data to an end user through multi-hop communication without the need for any human intervention. However, due to the presence of typical obstacles in a home environment, error-free reception may not be possible, particularly for power constrained devices. A mobile sink based data transmission scheme can be one solution but obstacles create significant complexities for the sink movement path determination process. Therefore, an obstacle avoidance data routing scheme is of vital importance to the design of an efficient home automation system. This paper presents a mobile sink based obstacle avoidance routing scheme for a home monitoring system. The mobile sink collects data by traversing through the obstacle avoidance path. Through ZigBee based hardware implementation and verification, the proposed scheme successfully transmits data through the obstacle avoidance path to improve network performance in terms of life span, energy consumption and reliability. The application of this work can be applied to a wide range of intelligent pervasive consumer products and services including robotic vacuum cleaners and personal security robots1.

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We investigated the plume structure of a piezo-electric sprayer system, set up to release ethanol in a wind tunnel, using a fast response mini-photoionizaton detector. We recorded the plume structure of four different piezo-sprayer configurations: the sprayer alone; with a 1.6-mm steel mesh shield; with a 3.2-mm steel mesh shield; and with a 5 cm circular upwind baffle. We measured a 12 × 12-mm core at the center of the plume, and both a horizontal and vertical cross-section of the plume, all at 100-, 200-, and 400-mm downwind of the odor source. Significant differences in plume structure were found among all configurations in terms of conditional relative mean concentration, intermittency, ratio of peak concentration to conditional mean concentration, and cross-sectional area of the plume. We then measured the flight responses of the almond moth, Cadra cautella, to odor plumes generated with the sprayer alone, and with the upwind baffle piezo-sprayer configuration, releasing a 13:1 ratio of (9Z,12E)-tetradecadienyl acetate and (Z)-9-tetradecenyl acetate diluted in ethanol at release rates of 1, 10, 100, and 1,000 pg/min. For each configuration, differences in pheromone release rate resulted in significant differences in the proportions of moths performing oriented flight and landing behaviors. Additionally, there were apparent differences in the moths’ behaviors between the two sprayer configurations, although this requires confirmation with further experiments. This study provides evidence that both pheromone concentration and plume structure affect moth orientation behavior and demonstrates that care is needed when setting up experiments that use a piezo-electric release system to ensure the optimal conditions for behavioral observations.

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Changes in the depth of Lake Viljandi between 1940 and 1990 were simulated using a lake water and energy-balance model driven by standard monthly weather data. Catchment runoff was simulated using a one-dimensional hydrological model, with a two-layer soil, a single-layer snowpack, a simple representation of vegetation cover and similarly modest input requirements. Outflow was modelled as a function of lake level. The simulated record of lake level and outflow matched observations of lake-level variations (r = 0.78) and streamflow (r = 0.87) well. The ability of the model to capture both intra- and inter-annual variations in the behaviour of a specific lake, despite the relatively simple input requirements, makes it extremely suitable for investigations of the impacts of climate change on lake water balance.

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A low cost, compact embedded design approach for actuating soft robots is presented. The complete fabrication procedure and mode of operation was demonstrated, and the performance of the complete system was also demonstrated by building a microcontroller based hardware system which was used to actuate a soft robot for bending motion. The actuation system including the electronic circuit board and actuation components was embedded in a 3D-printed casing to ensure a compact approach for actuating soft robots. Results show the viability of the system in actuating and controlling siliconebased soft robots to achieve bending motions. Qualitative measurements of uniaxial tensile test, bending distance and pressure were obtained. This electronic design is easy to reproduce and integrate into any specified soft robotic device requiring pneumatic actuation.

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Background We investigated interacting effects of matric potential and soil strength on root elongation of maize and lupin, and relations between root elongation rates and the length of bare (hairless) root apex. Methods Root elongation rates and the length of bare root apexwere determined formaize and lupin seedlings in sandy loam soil of various matric potentials (−0.01 to −1.6 MPa) and bulk densities (0.9 to 1.5 Mg m−3). Results Root elongation rates slowed with both decreasing matric potential and increasing penetrometer resistance. Root elongation of maize slowed to 10 % of the unimpeded rate when penetrometer resistance increased to 2 MPa, whereas lupin elongated at about 40 % of the unimpeded rate. Maize root elongation rate was more sensitive to changes in matric potential in loosely packed soil (penetrometer resistances <1 MPa) than lupin. Despite these differing responses, root elongation rate of both species was linearly correlated with length of the bare root apex (r2 0.69 to 0.97). Conclusion Maize root elongation was more sensitive to changes in matric potential and mechanical impedance than lupin. Robust linear relationships between elongation rate and length of bare apex suggest good potential for estimating root elongation rates for excavated roots.

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Weeds tend to aggregate in patches within fields and there is evidence that this is partly owing to variation in soil properties. Because the processes driving soil heterogeneity operate at different scales, the strength of the relationships between soil properties and weed density would also be expected to be scale-dependent. Quantifying these effects of scale on weed patch dynamics is essential to guide the design of discrete sampling protocols for mapping weed distribution. We have developed a general method that uses novel within-field nested sampling and residual maximum likelihood (REML) estimation to explore scale-dependent relationships between weeds and soil properties. We have validated the method using a case study of Alopecurus myosuroides in winter wheat. Using REML, we partitioned the variance and covariance into scale-specific components and estimated the correlations between the weed counts and soil properties at each scale. We used variograms to quantify the spatial structure in the data and to map variables by kriging. Our methodology successfully captured the effect of scale on a number of edaphic drivers of weed patchiness. The overall Pearson correlations between A. myosuroides and soil organic matter and clay content were weak and masked the stronger correlations at >50 m. Knowing how the variance was partitioned across the spatial scales we optimized the sampling design to focus sampling effort at those scales that contributed most to the total variance. The methods have the potential to guide patch spraying of weeds by identifying areas of the field that are vulnerable to weed establishment.

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This thesis is an empirical-based study of the European Union’s Emissions Trading Scheme (EU ETS) and its implications in terms of corporate environmental and financial performance. The novelty of this study includes the extended scope of the data coverage, as most previous studies have examined only the power sector. The use of verified emissions data of ETS-regulated firms as the environmental compliance measure and as the potential differentiating criteria that concern the valuation of EU ETS-exposed firms in the stock market is also an original aspect of this study. The study begins in Chapter 2 by introducing the background information on the emission trading system (ETS), which focuses on (i) the adoption of ETS as an environmental management instrument and (ii) the adoption of ETS by the European Union as one of its central climate policies. Chapter 3 surveys four databases that provide carbon emissions data in order to determine the most suitable source of the data to be used in the later empirical chapters. The first empirical chapter, which is also Chapter 4 of this thesis, investigates the determinants of the emissions compliance performance of the EU ETS-exposed firms through constructing the best possible performance ratio from verified emissions data and self-configuring models for a panel regression analysis. Chapter 5 examines the impacts on the EU ETS-exposed firms in terms of their equity valuation with customised portfolios and multi-factor market models. The research design takes into account the emissions allowance (EUA) price as an additional factor, as it has the most direct association with the EU ETS to control for the exposure. The final empirical Chapter 6 takes the investigation one step further, by specifically testing the degree of ETS exposure facing different sectors with sector-based portfolios and an extended multi-factor market model. The findings from the emissions performance ratio analysis show that the business model of firms significantly influences emissions compliance, as the capital intensity has a positive association with the increasing emissions-to-emissions cap ratio. Furthermore, different sectors show different degrees of sensitivity towards the determining factors. The production factor influences the performance ratio of the Utilities sector, but not the Energy or Materials sectors. The results show that the capital intensity has a more profound influence on the utilities sector than on the materials sector. With regard to the financial performance impact, ETS-exposed firms as aggregate portfolios experienced a substantial underperformance during the 2001–2004 period, but not in the operating period of 2005–2011. The results of the sector-based portfolios show again the differentiating effect of the EU ETS on sectors, as one sector is priced indifferently against its benchmark, three sectors see a constant underperformance, and three sectors have altered outcomes.

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This paper discusses an important issue related to the implementation and interpretation of the analysis scheme in the ensemble Kalman filter . I t i s shown that the obser vations must be treated as random variables at the analysis steps. That is, one should add random perturbations with the correct statistics to the obser vations and generate an ensemble of obser vations that then is used in updating the ensemble of model states. T raditionally , this has not been done in previous applications of the ensemble Kalman filter and, as will be shown, this has resulted in an updated ensemble with a variance that is too low . This simple modification of the analysis scheme results in a completely consistent approach if the covariance of the ensemble of model states is interpreted as the prediction error covariance, and there are no further requirements on the ensemble Kalman filter method, except for the use of an ensemble of sufficient size. Thus, there is a unique correspondence between the error statistics from the ensemble Kalman filter and the standard Kalman filter approach

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We present a novel algorithm for concurrent model state and parameter estimation in nonlinear dynamical systems. The new scheme uses ideas from three dimensional variational data assimilation (3D-Var) and the extended Kalman filter (EKF) together with the technique of state augmentation to estimate uncertain model parameters alongside the model state variables in a sequential filtering system. The method is relatively simple to implement and computationally inexpensive to run for large systems with relatively few parameters. We demonstrate the efficacy of the method via a series of identical twin experiments with three simple dynamical system models. The scheme is able to recover the parameter values to a good level of accuracy, even when observational data are noisy. We expect this new technique to be easily transferable to much larger models.

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Terrain following coordinates are widely used in operational models but the cut cell method has been proposed as an alternative that can more accurately represent atmospheric dynamics over steep orography. Because the type of grid is usually chosen during model implementation, it becomes necessary to use different models to compare the accuracy of different grids. In contrast, here a C-grid finite volume model enables a like-for-like comparison of terrain following and cut cell grids. A series of standard two-dimensional tests using idealised terrain are performed: tracer advection in a prescribed horizontal velocity field, a test starting from resting initial conditions, and orographically induced gravity waves described by nonhydrostatic dynamics. In addition, three new tests are formulated: a more challenging resting atmosphere case, and two new advection tests having a velocity field that is everywhere tangential to the terrain following coordinate surfaces. These new tests present a challenge on cut cell grids. The results of the advection tests demonstrate that accuracy depends primarily upon alignment of the flow with the grid rather than grid orthogonality. A resting atmosphere is well-maintained on all grids. In the gravity waves test, results on all grids are in good agreement with existing results from the literature, although terrain following velocity fields lead to errors on cut cell grids. Due to semi-implicit timestepping and an upwind-biased, explicit advection scheme, there are no timestep restrictions associated with small cut cells. We do not find the significant advantages of cut cells or smoothed coordinates that other authors find.