467 resultados para South Australian fault model
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In this work, a fault-tolerant control scheme is applied to a air handling unit of a heating, ventilation and air-conditioning system. Using the multiple-model approach it is possible to identify faults and to control the system under faulty and normal conditions in an effective way. Using well known techniques to model and control the process, this work focuses on the importance of the cost function in the fault detection and its influence on the reconfigurable controller. Experimental results show how the control of the terminal unit is affected in the presence a fault, and how the recuperation and reconfiguration of the control action is able to deal with the effects of faults.
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We present an analysis of the oceanic heat advection and its variability in the upper 500 m in the southeastern tropical Pacific (100W–75W, 25S–10S) as simulated by the global coupled model HiGEM, which has one of the highest resolutions currently used in long-term integrations. The simulated climatology represents a temperature advection field arising from transient small-scale (<450 km) features, with structures and transport that appear consistent with estimates based on available observational data for the mooring at 20S, 85W. The transient structures are very persistent (>4 months), and in specific locations they generate an important contribution to the local upper-ocean heat budget, characterised by scales of a few hundred kilometres, and periods of over a year. The contribution from such structures to the local, long-term oceanic heat budget however can be of either sign, or vanishing, depending on the location; and, although there appears some organisation in preferential areas of activity, the average over the entire region is small. While several different mechanisms may be responsible for the temperature advection by transients, we find that a significant, and possibly dominant, component is associated with vortices embedded in the large-scale, climatological salinity gradient associated with the fresh intrusion of mid-latitude intermediate water which penetrates north-westward beneath the tropical thermocline
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Atmospheric pollution over South Asia attracts special attention due to its effects on regional climate, water cycle and human health. These effects are potentially growing owing to rising trends of anthropogenic aerosol emissions. In this study, the spatio-temporal aerosol distributions over South Asia from seven global aerosol models are evaluated against aerosol retrievals from NASA satellite sensors and ground-based measurements for the period of 2000–2007. Overall, substantial underestimations of aerosol loading over South Asia are found systematically in most model simulations. Averaged over the entire South Asia, the annual mean aerosol optical depth (AOD) is underestimated by a range 15 to 44% across models compared to MISR (Multi-angle Imaging SpectroRadiometer), which is the lowest bound among various satellite AOD retrievals (from MISR, SeaWiFS (Sea-Viewing Wide Field-of-View Sensor), MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua and Terra). In particular during the post-monsoon and wintertime periods (i.e., October–January), when agricultural waste burning and anthropogenic emissions dominate, models fail to capture AOD and aerosol absorption optical depth (AAOD) over the Indo–Gangetic Plain (IGP) compared to ground-based Aerosol Robotic Network (AERONET) sunphotometer measurements. The underestimations of aerosol loading in models generally occur in the lower troposphere (below 2 km) based on the comparisons of aerosol extinction profiles calculated by the models with those from Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) data. Furthermore, surface concentrations of all aerosol components (sulfate, nitrate, organic aerosol (OA) and black carbon (BC)) from the models are found much lower than in situ measurements in winter. Several possible causes for these common problems of underestimating aerosols in models during the post-monsoon and wintertime periods are identified: the aerosol hygroscopic growth and formation of secondary inorganic aerosol are suppressed in the models because relative humidity (RH) is biased far too low in the boundary layer and thus foggy conditions are poorly represented in current models, the nitrate aerosol is either missing or inadequately accounted for, and emissions from agricultural waste burning and biofuel usage are too low in the emission inventories. These common problems and possible causes found in multiple models point out directions for future model improvements in this important region.
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The regional climate modelling system PRECIS, was run at 25 km horizontal resolution for 150 years (1949-2099) using global driving data from a five member perturbed physics ensemble (based on the coupled global climate model HadCM3). Output from these simulations was used to investigate projected changes in tropical cyclones (TCs) over Vietnam and the South China Sea due to global warming (under SRES scenario A1B). Thirty year climatological mean periods were used to look at projected changes in future (2069-2098) TCs compared to a 1961-1990 baseline. Present day results were compared qualitatively with IBTrACS observations and found to be reasonably realistic. Future projections show a 20-44 % decrease in TC frequency, although the spatial patterns of change differ between the ensemble members, and an increase of 27-53 % in the amount of TC associated precipitation. No statistically significant changes in TC intensity were found, however, the occurrence of more intense TCs (defined as those with a maximum 10 m wind speed > 35 m/s) was found to increase by 3-9 %. Projected increases in TC associated precipitation are likely caused by increased evaporation and availability of atmospheric water vapour, due to increased sea surface and atmospheric temperature. The mechanisms behind the projected changes in TC frequency are difficult to link explicitly; changes are most likely due to the combination of increased static stability, increased vertical wind shear and decreased upward motion, which suggest a decrease in the tropical overturning circulation.
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A detailed climatology of the cyclogenesis over the Southern Atlantic Ocean (SAO) from 1990 to 1999 and how it is simulated by the RegCM3 (Regional Climate Model) is presented here. The simulation used as initial and boundary conditions the National Centers for Environmental Prediction-Department of Energy (NCEP/DOE) reanalysis. The cyclones were identified with an automatic scheme that searches for cyclonic relative vorticity (zeta(10)) obtained from a 10-m height wind field. All the systems with zeta(10) a parts per thousand currency sign -1.5 x 10(-5) s(-1) and lifetime equal or larger than 24 h were considered in the climatology. Over SAO, in 10 years were detected 2,760 and 2,787 cyclogeneses in the simulation and NCEP, respectively, with an annual mean of 276.0 +/- A 11.2 and 278.7 +/- A 11.1. This result suggests that the RegCM3 has a good skill to simulate the cyclogenesis climatology. However, the larger model underestimations (-9.8%) are found for the initially stronger systems (zeta(10) a parts per thousand currency sign -2.5 x 10(-5) s(-1)). It was noted that over the SAO the annual cycle of the cyclogenesis depends of its initial intensity. Considering the systems initiate with zeta(10) a parts per thousand currency sign -1.5 x 10(-5) s(-1), the annual cycle is not well defined and the higher frequency occurs in the autumn (summer) in the NCEP (RegCM3). The stronger systems (zeta(10) a parts per thousand currency sign -2.5 x 10(-5) s(-1)) have a well-characterized high frequency of cyclogenesis during the winter in both NCEP and RegCM3. This work confirms the existence of three cyclogenetic regions in the west sector of the SAO, near the South America east coast and shows that RegCM3 is able to reproduce the main features of these cyclogenetic areas.
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This study examines the variability of the South America monsoon system (SAMS) over tropical South America (SA). The onset, end, and total rainfall during the summer monsoon are investigated using precipitation pentad estimates from the global precipitation climatology project (GPCP) 1979-2006. Likewise, the variability of SAMS characteristics is examined in ten Intergovernmental Panel on Climate Change (IPCC) global coupled climate models in the twentieth century (1981-2000) and in a future scenario of global change (A1B) (2081-2100). It is shown that most IPCC models misrepresent the intertropical convergence zone and therefore do not capture the actual annual cycle of precipitation over the Amazon and northwest SA. Most models can correctly represent the spatiotemporal variability of the annual cycle of precipitation in central and eastern Brazil such as the correct phase of dry and wet seasons, onset dates, duration of rainy season and total accumulated precipitation during the summer monsoon for the twentieth century runs. Nevertheless, poor representation of the total monsoonal precipitation over the Amazon and northeast Brazil is observed in a large majority of the models. Overall, MI-ROC3.2-hires, MIROC3.2-medres and MRI-CGCM3.2.3 show the most realistic representation of SAMS`s characteristics such as onset, duration, total monsoonal precipitation, and its interannual variability. On the other hand, ECHAM5, GFDL-CM2.0 and GFDL-CM2.1 have the least realistic representation of the same characteristics. For the A1B scenario the most coherent feature observed in the IPCC models is a reduction in precipitation over central-eastern Brazil during the summer monsoon, comparatively with the present climate. The IPCC models do not indicate statistically significant changes in SAMS onset and demise dates for the same scenario.
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The landfall of Cyclone Catarina on the Brazilian coast in March 2004 became known as the first documented hurricane in the South Atlantic Ocean, promoting a new view oil how large-scale features can contribute to tropical transition. The aim of this paper is to put the large-scale circulation associated with Catarina`s transition in climate perspective. This is discussed in the light of a robust pattern of spatial correlations between thermodynamic and dynamic variables of importance for hurricane formation. A discussion on how transition mechanisms respond to the present-day circulation is presented. These associations help in understanding why Catarina was formed in a region previously thought to be hurricane-free. Catarina developed over a large-scale area of thermodynamically favourable air/sea temperature contrast. This aspect explains the paradox that such a rare system developed when the sea surface temperature was slightly below average. But, although thermodynamics played an important role, it is apparent that Catarina would not have formed without the key dynamic interplay triggered by a high latitude blocking. The blocking was associated with an extreme positive phase of the Southern Annular Mode (SAM) both hemispherically and locally, and the nearby area where Catarina developed is found to be more cyclonic during the positive phase of the SAM. A conceptual model is developed and a `South Atlantic index` is introduced as a useful diagnostic of potential conditions leading to tropical transition in the area, where large-scale indices indicate trends towards more favourable atmospheric conditions for tropical cyclone formation. Copyright (c) 2008 Royal Meteorological Society
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Regional Climate Model version 3 (RegCM3) simulations of 17 summers (1988-2004) over part of South America south of 5 degrees S were evaluated to identify model systematic errors. Model results were compared to different rainfall data sets (Climate Research Unit (CRU), Climate Prediction Center (CPC), Global Precipitation Climatology Project (GPCP), and National Centers for Environmental Prediction (NCEP) reanalysis), including the five summers mean (1998-2002) precipitation diurnal cycle observed by the Tropical Rainfall Measuring Mission (TRMM)-Precipitation Radar (PR). In spite of regional differences, the RegCM3 simulates the main observed aspects of summer climatology associated with the precipitation (northwest-southeast band of South Atlantic Convergence Zone (SACZ)) and air temperature (warmer air in the central part of the continent and colder in eastern Brazil and the Andes Mountains). At a regional scale, the main RegCM3 failures are the underestimation of the precipitation in the northern branch of the SACZ and some unrealistic intense precipitation around the Andes Mountains. However, the RegCM3 seasonal precipitation is closer to the fine-scale analyses (CPC, CRU, and TRMM-PR) than is the NCEP reanalysis, which presents an incorrect north-south orientation of SACZ and an overestimation of its intensity. The precipitation diurnal cycle observed by TRMM-PR shows pronounced contrasts between Tropics and Extratropics and land and ocean, where most of these features are simulated by RegCM3. The major similarities between the simulation and observation, especially the diurnal cycle phase, are found over the continental tropical and subtropical SACZ regions, which present afternoon maximum (1500-1800 UTC) and morning minimum (0900-1200 UTC). More specifically, over the core of SACZ, the phase and amplitude of the simulated precipitation diurnal cycle are very close to the TRMM-PR observations. Although there are amplitude differences, the RegCM3 simulates the observed nighttime rainfall in the eastern Andes Mountains, over the Atlantic Ocean, and also over northern Argentina. The main simulation deficiencies are found in the Atlantic Ocean and near the Andes Mountains. Over the Atlantic Ocean the convective scheme is not triggered; thus the rainfall arises from the grid-scale scheme and therefore differs from the TRMM-PR. Near the Andes, intense (nighttime and daytime) simulated precipitation could be a response of an incorrect circulation and topographic uplift. Finally, it is important to note that unlike most reported bias of global models, RegCM3 does not trigger the moist convection just after sunrise over the southern part of the Amazon.
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Renewable energy production is a basic supplement to stabilize rapidly increasing global energy demand and skyrocketing energy price as well as to balance the fluctuation of supply from non-renewable energy sources at electrical grid hubs. The European energy traders, government and private company energy providers and other stakeholders have been, since recently, a major beneficiary, customer and clients of Hydropower simulation solutions. The relationship between rainfall-runoff model outputs and energy productions of hydropower plants has not been clearly studied. In this research, association of rainfall, catchment characteristics, river network and runoff with energy production of a particular hydropower station is examined. The essence of this study is to justify the correspondence between runoff extracted from calibrated catchment and energy production of hydropower plant located at a catchment outlet; to employ a unique technique to convert runoff to energy based on statistical and graphical trend analysis of the two, and to provide environment for energy forecast. For rainfall-runoff model setup and calibration, MIKE 11 NAM model is applied, meanwhile MIKE 11 SO model is used to track, adopt and set a control strategy at hydropower location for runoff-energy correlation. The model is tested at two selected micro run-of-river hydropower plants located in South Germany. Two consecutive calibration is compromised to test the model; one for rainfall-runoff model and other for energy simulation. Calibration results and supporting verification plots of two case studies indicated that simulated discharge and energy production is comparable with the measured discharge and energy production respectively.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this article, an implementation of structural health monitoring process automation based on vibration measurements is proposed. The work presents an alternative approach which intent is to exploit the capability of model updating techniques associated to neural networks to be used in a process of automation of fault detection. The updating procedure supplies a reliable model which permits to simulate any damage condition in order to establish direct correlation between faults and deviation in the response of the model. The ability of the neural networks to recognize, at known signature, changes in the actual data of a model in real time are explored to investigate changes of the actual operation conditions of the system. The learning of the network is performed using a compressed spectrum signal created for each specific type of fault. Different fault conditions for a frame structure are evaluated using simulated data as well as measured experimental data.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)