846 resultados para Input-Output Modelling


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Utilising cameras as a means to survey the surrounding environment is becoming increasingly popular in a number of different research areas and applications. Central to using camera sensors as input to a vision system, is the need to be able to manipulate and process the information captured in these images. One such application, is the use of cameras to monitor the quality of airport landing lighting at aerodromes where a camera is placed inside an aircraft and used to record images of the lighting pattern during the landing phase of a flight. The images are processed to determine a performance metric. This requires the development of custom software for the localisation and identification of luminaires within the image data. However, because of the necessity to keep airport operations functioning as efficiently as possible, it is difficult to collect enough image data to develop, test and validate any developed software. In this paper, we present a technique to model a virtual landing lighting pattern. A mathematical model is postulated which represents the glide path of the aircraft including random deviations from the expected path. A morphological method has been developed to localise and track the luminaires under different operating conditions. © 2011 IEEE.

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The creation of idealised, dimensionally reduced meshes for preliminary design and optimisation remains a time-consuming, manual task. A dimensionally reduced model is ideal for assessing design changes through modification of element properties without the need to create a new geometry or mesh. In this paper, a novel approach for automating the creation of mixed dimensional meshes is presented. The input to the process is a solid model which has been decomposed into a non-manifold assembly of smaller volumes with different meshing significance. Associativity between the original solid model and the dimensionally reduced equivalent is maintained. The approach is validated by means of a free-free modal analysis on an output mesh of a gas turbine engine component of industrial complexity. Extensions and enhancements to this work are also discussed.

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It has been argued that the variation in brain activity that occurs when observing another person reflects a representation of actions that is indivisible, and which plays out in full once the intent of the actor can be discerned. We used transcranial magnetic stimulation to probe the excitability of corticospinal projections to 2 intrinsic hand muscles while motions to reach and grasp an object were observed. A symbolic cue either faithfully indicated the required final orientation of the object and thus the nature of the grasp that was required, or was in conflict with the movement subsequently displayed. When the cue was veridical, modulation of excitability was in accordance with the functional role of the muscles in the action observed. If however the cue had indicated that the alternative grasp would be required, modulation of output to first dorsal interosseus was consistent with the action specified, rather than the action observed-until the terminal phase of the motion sequence during which the object was seen lifted. Modulation of corticospinal output during observation is thus segmented-it progresses initially in accordance with the action anticipated, and if discrepancies are revealed by visual input, coincides thereafter with that of the action seen.

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The environmental fate of selected persistent organic pollutants (POPs) in the North Sea system is modelled with a high resolution Fate and Transport Ocean Model (FANTOM) that uses hydrodynamic model output from the Hamburg Shelf Ocean Model (HAMSOM). Large amounts of POPs enter the North Sea from the surrounding highly populated, industrialised and agricultural countries. Major pathways to the North Sea are atmospheric deposition and river inputs, with additional contributions coming from bottom sediments and adjacent seas. The model domain covers the entire North Sea region, extending northward as far as the Shetland Islands, and includes adjacent basins such as the Skagerrak, Kattegat, and the westernmost part of the Baltic Sea. Model resolution (for both models) is 1.5’ latitude x 2.5’ longitude (approximately 3 km horizontal resolution) with 30 vertical levels. The POP model also has 20 sediment layers. Important model processes controlling the fate of POPs in the North Sea system are discussed. Results focus on Lindane gamma- HCH or gamma-hexachlorocyclohexane) and PCB 153.

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In the production process of polyethylene terephthalate (PET) bottles, the initial temperature of preforms plays a central role on the final thickness, intensity and other structural properties of the bottles. Also, the difference between inside and outside temperature profiles could make a significant impact on the final product quality. The preforms are preheated by infrared heating oven system which is often an open loop system and relies heavily on trial and error approach to adjust the lamp power settings. In this paper, a radial basis function (RBF) neural network model, optimized by a two-stage selection (TSS) algorithm combined with partial swarm optimization (PSO), is developed to model the nonlinear relations between the lamp power settings and the output temperature profile of PET bottles. Then an improved PSO method for lamp setting adjustment using the above model is presented. Simulation results based on experimental data confirm the effectiveness of the modelling and optimization method.

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The injection stretch blow moulding process involves the inflation and stretching of a hot preform into a mould to form bottles. A critical process variable and an essential input for process simulations is the rate of pressure increase within the preform during forming, which is regulated by an air flow restrictor valve. The paper describes a set of experiments for measuring the air flow rate within an industrial ISBM machine and the subsequent modelling of it with the FEA package ABAQUS. Two rigid containers were inserted into a Sidel SBO1 blow moulding machine and subjected to different supply pressures and air flow restrictor settings. The pressure and air temperature were recorded for each experiment enabling the mass flow rate of air to be determined along with an important machine characteristic known as the ‘dead volume’. The experimental setup was simulated within the commercial FEA package ABAQUS/Explicit using a combination of structural, fluid and fluid link elements that idealize the air flowing through an orifice behaving as an ideal gas under isothermal conditions. Results between experiment and simulation are compared and show a good correlation.

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This paper details the theory and implementation of a composite damage model, addressing damage within a ply (intralaminar) and delamination (interlaminar), for the simulation of crushing of laminated composite structures. It includes a more accurate determination of the characteristic length to achieve mesh objectivity in capturing intralaminar damage consisting of matrix cracking and fibre failure, a load-history dependent material response, an isotropic hardening nonlinear matrix response, as well as a more physically-based interactive matrix-dominated damage mechanism. The developed damage model requires a set of material parameters obtained from a combination of standard and non-standard material characterisation tests. The fidelity of the model mitigates the need to manipulate, or "calibrate", the input data to achieve good agreement with experimental results. The intralaminar damage model was implemented as a VUMAT subroutine, and used in conjunction with an existing interlaminar damage model, in Abaqus/Explicit. This approach was validated through the simulation of the crushing of a cross-ply composite tube with a tulip-shaped trigger, loaded in uniaxial compression. Despite the complexity of the chosen geometry, excellent correlation was achieved with experimental results.

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The capability to numerically model the crushing behaviour of composite structures will enable the efficient design of structures with high specific energy absorption capacity. This is particularly relevant to the aerospace and automotive industries where cabin structures need to be shown to be crashworthy. In this paper, a three-dimensional damage model is presented, which accurately represents the behaviour of composite laminates under crush loading. Both intralaminar and interlaminar failure mechanisms are taken into account. The crush damage model was implemented in ABAQUS/Explicit as a VUMAT subroutine. Numerical predictions are shown to agree well with experimental results, accurately capturing the intralaminar and interlaminar damage for a range of stacking sequences, triggers and composite materials. The use of measured material parameters required by the numerical models, without the need to ‘calibrate’ this input data, demonstrates this computational tool's predictive capabilities

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Aims. We investigated the response of the solar atmosphere to non-thermal electron beam heating using the radiative transfer and hydrodynamics modelling code RADYN. The temporal evolution of the parameters that describe the non-thermal electron energy distribution were derived from hard X-ray observations of a particular flare, and we compared the modelled and observed parameters.

Methods. The evolution of the non-thermal electron beam parameters during the X1.5 solar flare on 2011 March 9 were obtained from analysis of RHESSI X-ray spectra. The RADYN flare model was allowed to evolve for 110 s, after which the electron beam heating was ended, and was then allowed to continue evolving for a further 300 s. The modelled flare parameters were compared to the observed parameters determined from extreme-ultraviolet spectroscopy.

Results. The model produced a hotter and denser flare loop than that observed and also cooled more rapidly, suggesting that additional energy input in the decay phase of the flare is required. In the explosive evaporation phase a region of high-density cool material propagated upward through the corona. This material underwent a rapid increase in temperature as it was unable to radiate away all of the energy deposited across it by the non-thermal electron beam and via thermal conduction. A narrow and high-density (ne ≤ 1015 cm-3) region at the base of the flare transition region was the source of optical line emission in the model atmosphere. The collision-stopping depth of electrons was calculated throughout the evolution of the flare, and it was found that the compression of the lower atmosphere may permit electrons to penetrate farther into a flaring atmosphere compared to a quiet Sun atmosphere.

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Extrusion is one of the major methods for processing polymeric materials and the thermal homogeneity of the process output is a major concern for manufacture of high quality extruded products. Therefore, accurate process thermal monitoring and control are important for product quality control. However, most industrial extruders use single point thermocouples for the temperature monitoring/control although their measurements are highly affected by the barrel metal wall temperature. Currently, no industrially established thermal profile measurement technique is available. Furthermore, it has been shown that the melt temperature changes considerably with the die radial position and hence point/bulk measurements are not sufficient for monitoring and control of the temperature across the melt flow. The majority of process thermal control methods are based on linear models which are not capable of dealing with process nonlinearities. In this work, the die melt temperature profile of a single screw extruder was monitored by a thermocouple mesh technique. The data obtained was used to develop a novel approach of modelling the extruder die melt temperature profile under dynamic conditions (i.e. for predicting the die melt temperature profile in real-time). These newly proposed models were in good agreement with the measured unseen data. They were then used to explore the effects of process settings, material and screw geometry on the die melt temperature profile. The results showed that the process thermal homogeneity was affected in a complex manner by changing the process settings, screw geometry and material.

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We present a comprehensive model for predicting the full performance of a second harmonic generation-optical parametric amplification system that aims at enhancing the temporal contrast of laser pulses. The model simultaneously takes into account all the main parameters at play in the system such as the group velocity mismatch, the beam divergence, the spectral content, the pump depletion, and the length of the nonlinear crystals. We monitor the influence of the initial parameters of the input pulse and the interdependence of the two related non-linear processes on the performance of the system and show its optimum configuration. The influence of the initial beam divergence on the spectral and the temporal characteristics of the generated pulse is discussed. In addition, we show that using a crystal slightly longer than the optimum length and introducing small delay between the seed and the pump ensures maximum efficiency and compensates for the spectral shift in the optical parametric amplification stage in case of chirped input pulse. As an example, calculations for bandwidth transform limited and chirped pulses of sub-picosecond duration in beta barium borate crystal are presented.

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The evaporator is an important component in the Organic Rankine Cycle (ORC)-based Waste Heat Recovery (WHR) system since the effective heat transfer of this device reflects on the efficiency of the system. When the WHR system operates under supercritical conditions, the heat transfer mechanism in the evaporator is unpredictable due to the change of thermo-physical properties of the fluid with temperature. Although the conventional finite volume model can successfully capture those changes in the evaporator of the WHR process, the computation time for this method is high. To reduce the computation time, this paper develops a new fuzzy based evaporator model and compares its performance with the finite volume method. The results show that the fuzzy technique can be applied to predict the output of the supercritical evaporator in the waste heat recovery system and can significantly reduce the required computation time. The proposed model, therefore, has the potential to be used in real time control applications.

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Passive intermodulation (PIM) often limits the performance of communication systems with analog and digitally-modulated signals and especially of systems supporting multiple carriers. Since the origins of the apparently multiple physical sources of nonlinearity causing PIM are not fully understood, the behavioral models are frequently used to describe the process of PIM generation. In this paper a polynomial model of memoryless nonlinearity is deduced from PIM measurements of a microstrip line with distributed nonlinearity with two-tone CW signals. The analytical model of nonlinearity is incorporated in Keysight Technology’s ADS simulator to evaluate the metrics of signal fidelity in the receive band for analog and digitally-modulated signals. PIM-induced distortion and cross-band interference with modulated signals are compared to those with two-tone CW signals. It is shown that conventional metrics can be applied to quantify the effect of distributed nonlinearities on signal fidelity. It is found that the two-tone CW test provides a worst-case estimate of cross-band interference for two-carrier modulated signals whereas with a three-carrier signal PIM interference in the receive band is noticeably overestimated. The simulated constellation diagrams for QPSK signals demonstrate that PIM interference exhibits the distinctive signatures of correlated distortion and this indicates that there are opportunities for mitigating PIM interference and that PIM interference cannot be treated as noise. One of the interesting results is that PIM distortion on a transmission line results in asymmetrical regrowth of output PIM interference for modulated signals.

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Large-scale commercial exploitation of wave energy is certain to require the deployment of wave energy converters (WECs) in arrays, creating ‘WEC farms’. An understanding of the hydrodynamic interactions in such arrays is essential for determining optimum layouts of WECs, as well as calculating the area of ocean that the farms will require. It is equally important to consider the potential impact of wave farms on the local and distal wave climates and coastal processes; a poor understanding of the resulting environmental impact may hamper progress, as it would make planning consents more difficult to obtain. It is therefore clear that an understanding the interactions between WECs within a farm is vital for the continued development of the wave energy industry.To support WEC farm design, a range of different numerical models have been developed, with both wave phase-resolving and wave phase-averaging models now available. Phase-resolving methods are primarily based on potential flow models and include semi-analytical techniques, boundary element methods and methods involving the mild-slope equations. Phase-averaging methods are all based around spectral wave models, with supra-grid and sub-grid wave farm models available as alternative implementations.The aims, underlying principles, strengths, weaknesses and obtained results of the main numerical methods currently used for modelling wave energy converter arrays are described in this paper, using a common framework. This allows a qualitative comparative analysis of the different methods to be performed at the end of the paper. This includes consideration of the conditions under which the models may be applied, the output of the models and the relationship between array size and computational effort. Guidance for developers is also presented on the most suitable numerical method to use for given aspects of WEC farm design. For instance, certain models are more suitable for studying near-field effects, whilst others are preferable for investigating far-field effects of the WEC farms. Furthermore, the analysis presented in this paper identifies areas in which the numerical modelling of WEC arrays is relatively weak and thus highlights those in which future developments are required.

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Pollen grains from the genus ragweed (Ambrosia spp.) are important aeroallergens. In Europe, the largest sources of atmospheric ragweed pollen are the Rhône Valley (France), parts of Northern Italy, the Pannonian Plain and Ukraine. Episodes of Long Distance Transport (LDT) of ragweed pollen from these centres can cover large parts of Europe and are predominantly studied using receptor based models (Smith et al., (2013) and references therein). The clinical impact of allergenic ragweed pollen arriving from distant sources remains unclear (Cecchi et al. 2010). Although a recent study has found the major allergens of ragweed in air samples collected in Poznań, Poland, during episodes of long-distance transport from the Pannonian Plain (Grewling et al. 2013). The source orientated models SILAM, DEHM, COSMO-Art, METRAS and ENVIRO-HIRLAM currently report having the capability of modelling atmospheric concentrations of pollen in Europe. The performance of such source-orientated models is strongly dependent on the quality of the emissions data, which is a focus of current research (e.g. Thibaudon et al. (2014)). The output from these models are important for warning allergy sufferers in areas polluted by ragweed, but could also be used to warn the public of ragweed pollen being transported into areas where the plant is not abundant. Areas outside of the main areas of ragweed infection that contain considerable local populations must, however, also include local scale models. These models can be used to predict local concentrations, even when LDT is not present. This concept of combined LDT and local scale calculations has been shown to be work for air pollutants and is considered usable for urban scale calculations of aeroallergens once urban scale maps of aeroallergen sources have been produced.