988 resultados para Dynamic Meniscus Profile
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Bridge structures are continuously subject to degradation due to the environment, ageing and excess loading. Periodic monitoring of bridges is therefore a key part of any maintenance strategy as it can give early warning if a bridge becomes unsafe. This article investigates an alternative method for the monitoring of bridge dynamic behaviour: a truck-trailer vehicle system, with accelerometers fitted to the axles of the trailer. The method aims to detect changes in the damping of a bridge, which may indicate the existence of damage. A simplified vehicle-bridge interaction model is used in theoretical simulations to assess the effectiveness of the method in detecting those changes. The influence of road profile roughness on the vehicle vibration is overcome by recording accelerations from both axles of a trailer and then analysing the spectra of the difference in the accelerations between the two axles. The effectiveness of the approach in detecting damage simulated as a loss in stiffness is also investigated. In addition, the sensitivity of the approach to the vehicle speed, road roughness class, bridge span length, changes in the equal axle properties and noise is investigated.
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Pavement surface profiles induce dynamic ride responses in vehicles which can potentially be used to classify road surface roughness. A novel method is proposed for the characterisation of pavement roughness through an analysis of vehicle accelerations. A combinatorial optimisation technique is applied to the determination of pavement profile heights based on measured accelerations at and above the vehicle axle. Such an approach, using low-cost inertial sensors, would provide an inexpensive alternative to the costly laser-based profile measurement vehicles. The concept is numerically validated using a half-car roll dynamic model to infer measurements of road profiles in both the left and right wheel paths.
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Pavements and bridges are subject to a continuous degradation due to traffic aggressiveness, ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure in order to provide adequate maintenance and guarantee the required levels of transport service and safety. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamics of bridges. A simplified quarter carbridge interaction model is used in theoretical simulations and the natural frequency of the bridge is extracted from the spectra of the vehicle accelerations. The accuracy is better at lower speeds and for smooth road profiles. The structural damping of the bridge was also monitored for smooth and rough road profiles. The magnitude of peaks in the power spectral density of the vehicle accelerations decreased with increasing bridge damping and this decrease was easier to detect the smoother the road profile.
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Highway structures such as bridges are subject to continuous degradation primarily due to ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure to provide adequate maintenance and guarantee the required levels of transport service and safety. In Europe, this is now a legal requirement - a European Directive requires all member states of the European Union to implement a Bridge Management System. However, the process is expensive, requiring the installation of sensing equipment and data acquisition electronics on the bridge. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamic behaviour of bridges as an indicator of its structural condition. This approach eliminates the need for any on-site installation of measurement equipment. A simplified half-car vehicle-bridge interaction model is used in theoretical simulations to test the possibility of extracting the dynamic parameters of the bridge from the spectra of the vehicle accelerations. The effect of vehicle speed, vehicle mass and bridge span length on the detection of the bridge dynamic parameters are investigated. The algorithm is highly sensitive to the condition of the road profile and simulations are carried out for both smooth and rough profiles
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This paper investigates the feasibility of using an instrumented vehicle to detect bridge dynamic parameters, such as natural frequency and structural damping, in a scaled laboratory experiment. In the experiment, a scaled vehicle model crosses a steel girder which has been adopted as the bridge model. The bridge model also includes a scaled road surface profile. The effects of varying vehicle model mass and speed are investigated. The damping of the girder is also varied. The bridge frequency and changes in damping are detected in the vehicle acceleration response in the presence of a rough road surface profile.
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Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.
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Three procedures for the isolation of volatiles from grilled goat meat were compared: dynamic headspace entrainment on Tenax TA, simultaneous steam distillation-extraction, and solid-phase microextraction. Headspace entrainment on Tenax TA extracted the highest number of Maillard-derived volatile compounds. Two hundred and three volatile components were identified: 159 are reported for the first time in goat meat. Most of the volatiles detected (155) were lipid oxidation products, such as hydrocarbons, aldehydes, alcohols, ketones, carboxylic acids and esters. Forty-eight Maillard-derived compounds were identified. comprising pyrazines, pyrroles, thiophenes, furanthiol derivatives, alkyl and alicyclic sulphides, pyridines, and thiazoles. Some reported character impact compounds of cooked meat, e.g., 12-methyltridecanal, (EE)-2,4-decadienal, methional, and dimethyl trisulphide were identified in the volatile profile of goat meat, together with a series of C-2 to C-5 alkylformylcyclopentenes, which have been reported in cooked chicken, pork, beef and lamb, as being important for the characteristic flavour impression of different animal species. (C) 2009 Published by Elsevier Ltd.
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A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses dynamic integrated system optimisation and parameter estimation (DISOPE) which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimisation procedure. A new method for approximating some Jacobian trajectories required by the algorithm is introduced. It is shown that the iterative procedure associated with the algorithm naturally suits applications to batch chemical processes.
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There are varieties of physical and behavioral factors to determine energy demand load profile. The attainment of the optimum mix of measures and renewable energy system deployment requires a simple method suitable for using at the early design stage. A simple method of formulating load profile (SMLP) for UK domestic buildings has been presented in this paper. Domestic space heating load profile for different types of houses have been produced using thermal dynamic model which has been developed using thermal resistant network method. The daily breakdown energy demand load profile of appliance, domestic hot water and space heating can be predicted using this method. The method can produce daily load profile from individual house to urban community. It is suitable to be used at Renewable energy system strategic design stage.
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Novel acidic varieties of muskmelon (Cucumis melo L.) are emerging onto the UK market. These melons contain almost twice the amount of citric acid compared to standard melons and are described as ‘zesty and fresh’. This study compared the flavour components of three acidic varieties with a standard Galia-type melon. The volatile and semivolatile compounds were extracted using dynamic headspace extraction (DHE) or solid-phase microextraction (SPME) and solid phase extraction (SPE) respectively, followed by gas chromatography – mass spectrometry (GC-MS) and gas chromatography – olfactometry (GC-O). More than 50 volatile and 50 semivolatile compounds were identified in the headspace and the SPE extracts respectively. GC-O revealed 15 odour-active components in the headspace, with esters being consistently higher in acidic variety. This study showed quantitative and qualitative differences between all four varieties and key differences between acidic varieties and standard melons.
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This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM) datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR). Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.
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A dynamic headspace solid-phase microextraction (HS-SPME) and gas chromatography coupled to ion trap mass spectrometry (GC–ITMS) method was developed and applied for the qualitative determination of the volatile compounds present in commercial whisky samples which alcoholic content was previously adjusted to 13% (v/v). Headspace SPME experimental conditions, such as fibre coating, extraction temperature and extraction time, were optimized in order to improve the extraction process. Five different SPME fibres were used in this study, namely, poly(dimethylsiloxane)(PDMS),poly(acrylate)(PA),Carboxen-poly(dimethylsiloxane)(CAR/PDMS),Carbowax-divinylbenzene(CW/DVB)and Carboxen-poly(dimethylsiloxane)-divinylbenzene (CAR/PDMS/DVB). The best results were obtained using a 75 m CAR/PDMS fibre during headspace extraction at 40◦C with stirring at 750rpm for 60min, after saturating the samples with salt. The optimised methodology was then appliedtoinvestigatethevolatilecompositionprofileofthreeScotchwhiskysamples—BlackLabel,BallantinesandHighlandClan.Approximately seventy volatile compounds were identified in the these samples, pertaining at several chemical groups, mainly fatty acids ethyl esters, higher alcohols, fatty acids, carbonyl compounds, monoterpenols, C13 norisoprenoids and some volatile phenols. The ethyl esters form an essential group of aroma components in whisky, to which they confer a pleasant aroma, with “fruity” odours. Qualitatively, the isoamyl acetate, with “banana” aroma,wasthemostinteresting.Quantitatively,significantcomponentsareethylestersofcaprilic,capricandlauricacids.Thehighestconcentration of fatty acids, were observed for caprilic and capric acids. From the higher alcohols the fusel oils (3-methylbutan-1-ol and 2.phenyletanol) are the most important ones.
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During the construction of five residential buildings in the city of Taubate, State of São Paulo, it was possible to carry out one comprehensive investigation of the behavior of precast concrete piles in clay shales. This paper describes the results of Dynamic Load Tests (DLT's) executed in three piles with different diameters and with the same embedded length. The tests were monitored using the PDA(R) (Pile Driving Analyzer) and the pile top displacement was measured by pencil and paper procedure. From the curves of RMX versus DMX resulted from CASE(R) method, CAPWAPC(R) analyses were made for signals where the maximum mobilized soil resistance was verified. The results were compared with the predicted bearing capacity using the semi-empirical method of Decourt & Quaresma (1978) and Decourt (1982) based on SPT values and the description of the soil profile. Some comments related to the values of quake and damping used for clay shales in the analyses are also presented.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Changes in lipid profile are considered a risk factor for cardiovascular disease (CVD), especially in postmenopausal woman who have been associated with age-related loss of muscle mass. The beneficial role of aerobic exercise in the prevention of CVD has been well documented. However, the effect of strength training has not been established. The purpose of this study was to determine the changes of lipoprotein levels after 12 weeks of different volumes of strength training and its correlation with strength and muscle volume in postmenopausal women. The participants were randomized into three groups: low volume (LVST; n = 12, 1 set) and high volume of strength training (HVST; n = 11, 3 sets), or control group (n = 12). Training groups performed 12 weeks of supervised strength exercises, 15 maximum repetitions, five times a week, 20 minutes for LVST and 40 minutes for HVST for each training session. Measurements included body composition, strength and muscle volume, as well as blood analysis (glucose, total cholesterol, triglycerides, low-density lipoprotein, and high-density lipoprotein) pre- and post-training. The HVST and LVST improved the one-repetition maximum knee extension strength (p < 0.001), maximal dynamic strength (p < 0.001), and muscle volume (p = 0.048). Post-training triglyceride was lower in HVST when compared to LVST and the control group (p = 0.047). Even though they present the same neuromuscular and morphological adaptations in postmenopausal women, the HVST is more effective than LVST in improving the lipid profile of postmenopausal woman, and can be considered as an ideal program of intervention to reverse changes in lipid metabolism commonly found in this group. Copyright (C) 2014, The Society of Chinese Scholars on Exercise Physiology and Fitness. Published by Elsevier (Singapore) Pte Ltd. All rights reserved.