270 resultados para turbine inlet temperature
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Previous studies have demonstrated the importance of weather variables in influencing the incidence of influenza. However, the role of air pollution is often ignored in identifying the environmental drivers of influenza. This research aims to examine the impacts of air pollutants and temperature on the incidence of pediatric influenza in Brisbane, Australia. Lab-confirmed daily data on influenza counts among children aged 0-14years in Brisbane from 2001 January 1st to 2008 December 31st were retrieved from Queensland Health. Daily data on maximum and minimum temperatures for the same period were supplied by the Australian Bureau of Meteorology. Winter was chosen as the main study season due to it having the highest pediatric influenza incidence. Four Poisson log-linear regression models, with daily pediatric seasonal influenza counts as the outcome, were used to examine the impacts of air pollutants (i.e., ozone (O3), particulate matter≤10μm (PM10) and nitrogen dioxide (NO2)) and temperature (using a moving average of ten days for these variables) on pediatric influenza. The results show that mean temperature (Relative risk (RR): 0.86; 95% Confidence Interval (CI): 0.82-0.89) was negatively associated with pediatric seasonal influenza in Brisbane, and high concentrations of O3 (RR: 1.28; 95% CI: 1.25-1.31) and PM10 (RR: 1.11; 95% CI: 1.10-1.13) were associated with more pediatric influenza cases. There was a significant interaction effect (RR: 0.94; 95% CI: 0.93-0.95) between PM10 and mean temperature on pediatric influenza. Adding the interaction term between mean temperature and PM10 substantially improved the model fit. This study provides evidence that PM10 needs to be taken into account when evaluating the temperature-influenza relationship. O3 was also an important predictor, independent of temperature.
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Using our porcine model of deep dermal partial thickness burn injury, various cooling techniques (15 degrees C running water, 2 degrees C running water, ice) of first aid were applied for 20 minutes compared with a control (ambient temperature). The subdermal temperatures were monitored during the treatment and wounds observed and photographed weekly for 6 weeks, observing reepithelialization, wound surface area and cosmetic appearance. Tissue histology and scar tensile strength were examined 6 weeks after burn. The 2 degrees C and ice treatments decreased the subdermal temperature the fastest and lowest, however, generally the 15 and 2 degrees C treated wounds had better outcomes in terms of reepithelialization, scar histology, and scar appearance. These findings provide evidence to support the current first aid guidelines of cold tap water (approximately 15 degrees C) for 20 minutes as being beneficial in helping to heal the burn wound. Colder water at 2 degrees C is also beneficial. Ice should not be used.
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The relationship between temperature and mortality is generally found to be bathtub shaped (rising at both extremes). However, there are limited data on the potential health effects of temperature variability and on temperature itself...
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An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.
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A pilot experiment was performed using the WOMBAT powder diffraction instrument at ANSTO in which the first neutron diffraction peak (Q0) was measured for D2O flowing in a 2 mm internal diameter aluminium tube. Measurements of Q0 were made at -9, 4.3, 6.9, 12, 18.2 and 21.5 °C. The D2O was circulated using a siphon with water in the lower reservoir returned to the upper reservoir using a small pump. This enabled stable flow to be maintained for several hours. For example, if the pump flow increased slightly, the upper reservoir level rose, increasing the siphon flow until it matched the return flow. A neutron wavelength of 2.4 Å was used and data integrated over 60 minutes for each temperature. A jet of nitrogen from a liquid N2 Dewar was directed over the aluminium tube to vary water temperature. After collection of the data, the d spacing of the aluminium peaks was used to calculate the temperature of the aluminium within the neutron beam and therefore was considered to be an accurate measure of water temperature within the beam. Sigmaplot version 12.3 was used to fit a Weibull five parameter peak fit to the first neutron diffraction peak. The values of Q0 obtained in this experiment showed an increase with temperature consistent with data in the literature [1] but were consistently higher than published values for bulk D20. For example at 21.5 °C we obtained a value of 2.008 Å-1 for Q0 compared to a literature value of 1.988 Å-1 for bulk D2O at 20 °C, a difference of 1%. Further experiments are required to see if this difference is real or artifactual.
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X-ray diffraction structure functions for water flowing in a 1.5 mm diameter siphon in the temperature range 4 – 63 °C were obtained using a 20 keV beam at the Australian Synchrotron. These functions were compared with structure functions obtained at the Advanced Light Source for a 0.5 mm thick sample of water in the temperature range 1 – 77 °C irradiated with an 11 keV beam. The two sets of structure functions are similar, but there are subtle differences in the shape and relative position of the two functions suggesting a possible differences between the structure of bulk and siphon water. In addition, the first structural peak (Q0) for water in a siphon, showed evidence of a step-wise increase in Q0 with increasing temperature rather than a smoothly varying increase. More experiments are required to investigate this apparent difference.
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It has become more and more demanding to investigate the impacts of wind farms on power system operation as ever-increasing penetration levels of wind power have the potential to bring about a series of dynamic stability problems for power systems. This paper undertakes such an investigation through investigating the small signal and transient stabilities of power systems that are separately integrated with three types of wind turbine generators (WTGs), namely the squirrel cage induction generator (SCIG), the doubly fed induction generator (DFIG), and the permanent magnet generator (PMG). To examine the effects of these WTGs on a power system with regard to its stability under different operating conditions, a selected synchronous generator (SG) of the well-known Western Electricity Coordinating Council (WECC three-unit nine-bus system and an eight-unit 24-bus system is replaced in turn by each type of WTG with the same capacity. The performances of the power system in response to the disturbances are then systematically compared. Specifically, the following comparisons are undertaken: (1) performances of the power system before and after the integration of the WTGs; and (2) performances of the power system and the associated consequences when the SCIG, DFIG, or PMG are separately connected to the system. These stability case studies utilize both eigenvalue analysis and dynamic time-domain simulation methods.
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Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE) technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.
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Composites with carbon nanotubes are becoming increasingly used in energy storage and electronic devices, due to incorporated excellent properties from carbon nanotubes and polymers. Although their properties make them more attractive than conventional smart materials, their electrical properties are found to be temperature-dependent which is important to consider for the design of devices. To study the effects of temperature in electrically conductive multi-wall carbon nanotube/epoxy composites, thin films were prepared and the effect of temperature on the resistivity, thermal properties and Raman spectral characteristics of the composite films was evaluated. Resistivity-temperature profiles showed three distinct regions in as-cured samples and only two regions in samples whose thermal histories had been erased. In the vicinity of the glass transition temperature, the as-cured composites exhibited pronounced resistivity and enthalpic relaxation peaks, which both disappeared after erasing the composites’ thermal histories by temperature cycling. Combined DSC, Raman spectroscopy, and resistivity-temperature analyses indicated that this phenomenon can be attributed to the physical aging of the epoxy matrix and that, in the region of the observed thermal history-dependent resistivity peaks, structural rearrangement of the conductive carbon nanotube network occurs through a volume expansion/relaxation process. These results have led to an overall greater understanding of the temperature-dependent behaviour of conductive carbon nanotube/epoxy composites, including the positive temperature coefficient effect.
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Children are vulnerable to temperature extremes. This paper aimed to review the literature regarding the relationship between ambient temperature and children’s health and to propose future research directions. A literature search was conducted in February 2012 using the databases including PubMed, ProQuest, ScienceDirect, Scopus and Web of Science. Empirical studies regarding the impact of ambient temperature on children’s mortality and morbidity were included. The existing literature indicates that very young children, especially children under one year of age, are particularly vulnerable to heat-related deaths. Hot and cold temperatures mainly affect cases of infectious diseases among children, including gastrointestinal diseases, malaria, hand, foot and mouse disease, and respiratory diseases. Paediatric allergic diseases, like eczema, are also sensitive to temperature extremes. During heat waves, the incidences of renal disease, fever and electrolyte imbalance among children increase significantly. Future research is needed to examine the balance between hot- and cold-temperature related mortality and morbidity among children; evaluate the impacts of cold spells on cause-specific mortality in children; identify the most sensitive temperature exposure and health outcomes to quantify the impact of temperature extremes on children; elucidate the possible modifiers of the temperature and children’s health relationship; and project children’s disease burden under different climate change scenarios.
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The phenylperoxyl radical has long been accepted as a critical intermediate in the oxidation of benzene and an archetype for arylperoxyl radicals in combustion and atmospheric chemistry. Despite being central to many contemporary mechanisms underpinning these chemistries, reports of the direct detection or isolation of phenylperoxyl radicals are rare and there is little experimental evidence connecting this intermediate with expected product channels. We have prepared and isolated two charge-tagged phenyl radical models in the gas phase [i.e., 4-(N,N,N-trimethylammonium) phenyl radical cation and 4-carboxylatophenyl radical anion] and observed their reactions with dioxygen by ion-trap mass spectrometry. Measured reaction rates show good agreement with prior reports for the neutral system (k(2)[(Me3N+)C6H4 center dot + O-2] = 2.8 x 10(-11) cm(3) molecule(-1) s(-1), Phi = 4.9%; k(2)[(-O2C)C6H4 center dot + O-2] = 5.4 x 10(-1)1 cm(3) molecule(-1) s(-1), Phi = 9.2%) and the resulting mass spectra provide unequivocal evidence for the formation of phenylperoxyl radicals. Collisional activation of isolated phenylperoxyl radicals reveals unimolecular decomposition by three pathways: (i) loss of dioxygen to reform the initial phenyl radical; (ii) loss of atomic oxygen yielding a phenoxyl radical; and (iii) ejection of the formyl radical to give cyclopentadienone. Stable isotope labeling confirms these assignments. Quantum chemical calculations for both charge-tagged and neutral phenylperoxyl radicals confirm that loss of formyl radical is accessible both thermodynamically and entropically and competitive with direct loss of both hydrogen atom and carbon dioxide.
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This paper reports on an investigation of the flow/chemistry coupling inside a nominally two-dimensional inlet-fuelled scramjet configuration. The experiments were conducted at a freestream Mach number of 7.3 and a total flow enthalpy of 4.3MJ/kg corresponding to a Mach 9.7 flight condition. The phenomenon of radical-farming has been studied in detail using two-dimensional OH* chemiluminescence imaging and emission spectroscopy. High signal levels of excited OH (OH*) were detected behind the first shock reflections inside the combustion chamber upstream of any measurable pressure rise from combustion, which occurred towards the rear of the combustor. The production of OH in the first hot pocket initiates the ignition process and then accelerates the combustion process in the next downstream hot pocket. This was confirmed by numerical simulations of premixed hydrogen/air flow through the scramjet. Chemical kinetics analyses reveal that the ignition process is governed by the interaction between various reaction groups leading to a chainbranching explosion for low mean temperature and pressure combustion flowfields.
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In this study, a machine learning technique called anomaly detection is employed for wind turbine bearing fault detection. Basically, the anomaly detection algorithm is used to recognize the presence of unusual and potentially faulty data in a dataset, which contains two phases: a training phase and a testing phase. Two bearing datasets were used to validate the proposed technique, fault-seeded bearing from a test rig located at Case Western Reserve University to validate the accuracy of the anomaly detection method, and a test to failure data of bearings from the NSF I/UCR Center for Intelligent Maintenance Systems (IMS). The latter data set was used to compare anomaly detection with SVM, a previously well-known applied method, in rapidly finding the incipient faults.
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High quality, micron-sized interpenetrating grains of MgB2 with high density are produced at low temperatures (~420oC < T < ~500oC) under autogenous pressure by pre-mixing Mg powder and NaBH4 and heating in an Inconel 601 alloy reactor for 5−15 hours. Optimum production of MgB2 with yields greater than 75% occurs for autogenous pressure in the range 1.0 MPa to 2.0 MPa with the reactor at ~500oC. Autogenous pressure is induced by the decomposition of NaBH4 in the presence of Mg and/or other Mg-based compounds. The morphology, transition temperature and magnetic properties of MgB2 are dependent on the heating regime. Significant improvement in physical properties accrues when the reactor temperature is held at 250oC for >20minutes prior to a hold at 500oC.
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Fruit softening in apple (Malus 3 domestica) is associated with an increase in the ripening hormone ethylene. Here, we show that in cv Royal Gala apples that have the ethylene biosynthetic gene ACC OXIDASE1 suppressed, a cold treatment preconditions the apples to soften independently of added ethylene. When a cold treatment is followed by an ethylene treatment, a more rapid softening occurs than in apples that have not had a cold treatment. Apple fruit softening has been associated with the increase in the expression of cell wall hydrolase genes. One such gene, POLYGALACTURONASE1 (PG1), increases in expression both with ethylene and following a cold treatment. Transcriptional regulation of PG1 through the ethylene pathway is likely to be through an ETHYLENE-INSENSITIVE3-like transcription factor, which increases in expression during apple fruit development and transactivates the PG1 promoter in transient assays in the presence of ethylene. A coldrelated gene that resembles a COLD BINDING FACTOR (CBF) class of gene also transactivates the PG1 promoter. The transactivation by the CBF-like gene is greatly enhanced by the addition of exogenous ethylene. These observations give a possible molecular mechanism for the coldand ethylene-regulated control of fruit softening and suggest that either these two pathways act independently and synergistically with each other or cold enhances the ethylene response such that background levels of ethylene in the ethylene-suppressed apples is sufficient to induce fruit softening in apples.