951 resultados para finite-difference time-domain (FDTD) method
Resumo:
This is an investigation on the development of a numerical assessment method for the hydrodynamic performance of an oscillating water column (OWC) wave energy converter. In the research work, a systematic study has been carried out on how the hydrodynamic problem can be solved and represented reliably, focusing on the phenomena of the interactions of the wave-structure and the wave-internal water surface. These phenomena are extensively examined numerically to show how the hydrodynamic parameters can be reliably obtained and used for the OWC performance assessment. In studying the dynamic system, a two-body system is used for the OWC wave energy converter. The first body is the device itself, and the second body is an imaginary “piston,” which replaces part of the water at the internal water surface in the water column. One advantage of the two-body system for an OWC wave energy converter is its physical representations, and therefore, the relevant mathematical expressions and the numerical simulation can be straightforward. That is, the main hydrodynamic parameters can be assessed using the boundary element method of the potential flow in frequency domain, and the relevant parameters are transformed directly from frequency domain to time domain for the two-body system. However, as it is shown in the research, an appropriate representation of the “imaginary” piston is very important, especially when the relevant parameters have to be transformed from frequency-domain to time domain for a further analysis. The examples given in the research have shown that the correct parameters transformed from frequency domain to time domain can be a vital factor for a successful numerical simulation.
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This paper presents a study on the numerical simulation of the primary wave energy conversion in the oscillating water column (OWC) wave energy converters (WECs). The new proposed numerical approach consists of three major components: potential flow analysis for the conventional hydrodynamic parameters, such as added mass, damping coefficients, restoring force coefficients and wave excitations; the thermodynamic analysis of the air in the air chamber, which is under the assumptions of the given power take-off characteristics and an isentropic process of air flow. In the formulation, the air compressibility and its effects have been included; and a time-domain analysis by combining the linear potential flow and the thermodynamics of the air flow in the chamber, in which the hydrodynamics and thermodynamics/aerodynamics have been coupled together by the force generated by the pressurised and de-pressurised air in the air chamber, which in turn has effects on the motions of the structure and the internal water surface. As an example, the new developed approach has been applied to a fixed OWC device. The comparisons of the measured data and the simulation results show the new method is very capable of predicting the performance of the OWC devices.
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In combination of the advantages of both parallel mechanisms and compliant mechanisms, a compliant parallel mechanism with two rotational DOFs (degrees of freedom) is designed to meet the requirement of a lightweight and compact pan-tilt platform. Firstly, two commonly-used design methods i.e. direct substitution and FACT (Freedom and Constraint Topology) are applied to design the configuration of the pan-tilt system, and similarities and differences of the two design alternatives are compared. Then inverse kinematic analysis of the candidate mechanism is implemented by using the pseudo-rigid-body model (PRBM), and the Jacobian related to its differential kinematics is further derived to help designer realize dynamic analysis of the 8R compliant mechanism. In addition, the mechanism’s maximum stress existing within its workspace is tested by finite element analysis. Finally, a method to determine joint damping of the flexure hinge is presented, which aims at exploring the effect of joint damping on actuator selection and real-time control. To the authors’ knowledge, almost no existing literature concerns with this issue.
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In mixed sediment beds, erosion resistance can change relative to that of beds composed of a uniform sediment because of varying textural and/or other grain-size parameters, with effects on pore water flow that are difficult to quantify by means of analogue techniques. To overcome this difficulty, a three-dimensional numerical model was developed using a finite difference method (FDM) flow model coupled with a distinct element method (DEM) particle model. The main aim was to investigate, at a high spatial resolution, the physical processes occurring during the initiation of motion of single grains at the sediment-water interface and in the shallow subsurface of simplified sediment beds under different flow velocities. Increasing proportions of very fine sand (D50=0.08 mm) were mixed into a coarse sand matrix (D50=0.6 mm) to simulate mixed sediment beds, starting with a pure coarse sand bed in experiment 1 (0 wt% fines), and proceeding through experiment 2 (6.5 wt% fines), experiment 3 (10.5 wt% fines), and experiment 4 (28.7 wt% fines). All mixed beds were tested for their erosion behavior at predefined flow velocities varying in the range of U 1-5=10-30 cm/s. The experiments show that, with increasing fine content, the smaller particles increasingly fill the spaces between the larger particles. As a consequence, pore water inflow into the sediment is increasingly blocked, i.e., there is a decrease in pore water flow velocity and, hence, in the flow momentum available to entrain particles. These findings are portrayed in a new conceptual model of enhanced sediment bed stabilization.
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Far-field stresses are those present in a volume of rock prior to excavations being created. Estimates of the orientation and magnitude of far-field stresses, often used in mine design, are generally obtained by single-point measurements of stress, or large-scale, regional trends. Point measurements can be a poor representation of far-field stresses as a result of excavation-induced stresses and geological structures. For these reasons, far-field stress estimates can be associated with high levels of uncertainty. The purpose of this thesis is to investigate the practical feasibility, applications, and limitations of calibrating far-field stress estimates through tunnel deformation measurements captured using LiDAR imaging. A method that estimates the orientation and magnitude of excavation-induced principal stress changes through back-analysis of deformation measurements from LiDAR imaged tunnels was developed and tested using synthetic data. If excavation-induced stress change orientations and magnitudes can be accurately estimated, they can be used in the calibration of far-field stress input to numerical models. LiDAR point clouds have been proven to have a number of underground applications, thus it is desired to explore their use in numerical model calibration. The back-analysis method is founded on the superposition of stresses and requires a two-dimensional numerical model of the deforming tunnel. Principal stress changes of known orientation and magnitude are applied to the model to create calibration curves. Estimation can then be performed by minimizing squared differences between the measured tunnel and sets of calibration curve deformations. In addition to the back-analysis estimation method, a procedure consisting of previously existing techniques to measure tunnel deformation using LiDAR imaging was documented. Under ideal conditions, the back-analysis method estimated principal stress change orientations within ±5° and magnitudes within ±2 MPa. Results were comparable for four different tunnel profile shapes. Preliminary testing using plastic deformation, a rough tunnel profile, and profile occlusions suggests that the method can work under more realistic conditions. The results from this thesis set the groundwork for the continued development of a new, inexpensive, and efficient far-field stress estimate calibration method.
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The goal of this work is to present an efficient CAD-based adjoint process chain for calculating parametric sensitivities (derivatives of the objective function with respect to the CAD parameters) in timescales acceptable for industrial design processes. The idea is based on linking parametric design velocities (geometric sensitivities computed from the CAD model) with adjoint surface sensitivities. A CAD-based design velocity computation method has been implemented based on distances between discrete representations of perturbed geometries. This approach differs from other methods due to the fact that it works with existing commercial CAD packages (unlike most analytical approaches) and it can cope with the changes in CAD model topology and face labeling. Use of the proposed method allows computation of parametric sensitivities using adjoint data at a computational cost which scales with the number of objective functions being considered, while it is essentially independent of the number of design variables. The gradient computation is demonstrated on test cases for a Nozzle Guide Vane (NGV) model and a Turbine Rotor Blade model. The results are validated against finite difference values and good agreement is shown. This gradient information can be passed to an optimization algorithm, which will use it to update the CAD model parameters.
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The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the in influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.
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A potentially powerful drive-by bridge inspection approach was proposed to inspect bridge conditions utilizing the vibrations of a test vehicle while it passes over the target bridge. This approach suffers from the effect of roadway surface roughness and two solutions were proposed in previous studies: one is to subtract the responses of two vehicles (time-domain method) before spectral analysis and the other one is to subtract the spectrum of one vehicle from that of the other (frequency-domain method). Although the two methods were verified theoretically and numerically, their practical effectiveness is still an open question.Furthermore, whether the outcome spectra processed by those methods could be used to detect potential bridge damage is of our interests. In this study, a laboratory experiment was carried out with a test tractor-trailer system and a scaled bridge. It was observed that, first, for practical applications, it would be preferable to apply the frequency-domain method, avoiding the need to meet a strict requirement in synchronizing the responses of the two trailers in time domain; second, the statistical pattern of the processed spectra in a specific frequency band could be an effective anomaly indicator incorporated in drive-by inspection methods.
Resumo:
The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.
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Thesis (Ph.D.)--University of Washington, 2016-08
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A high-frequency time domain finite element scattering code using a combination of edge and piecewise constant elements on unstructured tetrahedral meshes is described. A comparison of computation with theory is given for scattering from a sphere. A parallel implementation making use of the bulk synchronous parallel (BSP) programming model is described in detail; a BSP performance model of the parallelized field calculation is derived and compared to timing measurements on up to 128 processors on a Cray T3D.
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This research is based on a numerical model for forecasting the three-dimensional behavior of (sea) water motion due to the effect of a variable wind velocity. The results obtained are then analyzed and compared with observation. This model is based on the equations that overcome the current and distribution of temperature by applying the method of finite difference with assuming Δx, Δy as constant and Δz, variable. The model is based on the momentum equation, continuity equation and thermodynamic energy equation and tension at the surface and middle layers and bottom stress. The horizontal and vertical eddy viscosity and thermal diffusivity coefficients we used in accordance with that of the Bennet on Outario Lake (1977). Considering the Caspian Sea dimension in numerical model the Coriolis parameter used with β effects and the approximation Boussines have been used. For the program controlling some simple experiment with boundary condition similar to that of the Caspian Sea have been done. For modeling the Caspian Sea the grid of the field was done as follows: At horizontal surface grid size is 10×10km extension and at vertical in 10 layers with varying thickness from surface to bed respectively as: 5, 10, 20, 3, 50, 100, 150, 200, 25, 500 and higher. The data of wind as velocity، direction and temperature of water related to 15th September 1995 at 6،12 and 18 o’clock were obtained from synoptic station at the Caspian Sea shore and the research marine of Haji Alief. The information concerning shore wind was measured and by the method of SPM (shore protection manual) was transferred to far shore winds through interpolation and by use of inverse square distance of position distribution of the wind velocity at the Caspian surface field was obtained. The model has been evaluated according to the reports and observations. Through studying the position of the current in different layers، the velocity in the cross section in the northern، southern and the middle layers، will be discussed. The results reveal the presence of the circulation cells in the three above mentioned areas. The circulation with depth is reduced too. The results obtained through the numerical solution of the temperature equation have been compared with the observation. The temperature change in different layers in cross section illustrates the relative accordance of the model mentioned.
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Thermal characterizations of high power light emitting diodes (LEDs) and laser diodes (LDs) are one of the most critical issues to achieve optimal performance such as center wavelength, spectrum, power efficiency, and reliability. Unique electrical/optical/thermal characterizations are proposed to analyze the complex thermal issues of high power LEDs and LDs. First, an advanced inverse approach, based on the transient junction temperature behavior, is proposed and implemented to quantify the resistance of the die-attach thermal interface (DTI) in high power LEDs. A hybrid analytical/numerical model is utilized to determine an approximate transient junction temperature behavior, which is governed predominantly by the resistance of the DTI. Then, an accurate value of the resistance of the DTI is determined inversely from the experimental data over the predetermined transient time domain using numerical modeling. Secondly, the effect of junction temperature on heat dissipation of high power LEDs is investigated. The theoretical aspect of junction temperature dependency of two major parameters – the forward voltage and the radiant flux – on heat dissipation is reviewed. Actual measurements of the heat dissipation over a wide range of junction temperatures are followed to quantify the effect of the parameters using commercially available LEDs. An empirical model of heat dissipation is proposed for applications in practice. Finally, a hybrid experimental/numerical method is proposed to predict the junction temperature distribution of a high power LD bar. A commercial water-cooled LD bar is used to present the proposed method. A unique experimental setup is developed and implemented to measure the average junction temperatures of the LD bar. After measuring the heat dissipation of the LD bar, the effective heat transfer coefficient of the cooling system is determined inversely. The characterized properties are used to predict the junction temperature distribution over the LD bar under high operating currents. The results are presented in conjunction with the wall-plug efficiency and the center wavelength shift.
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Spasticity is a common disorder in people who have upper motor neuron injury. The involvement may occur at different levels. The Modified Ashworth Scale (MAS) is the most used method to measure involvement levels. But it corresponds to a subjective evaluation. Mechanomyography (MMG) is an objective technique that quantifies the muscle vibration during the contraction and stretching events. So, it may assess the level of spasticity accurately. This study aimed to investigate the correlation between spasticity levels determined by MAS with MMG signal in spastic and not spastic muscles. In the experimental protocol, we evaluated 34 members of 22 volunteers, of both genders, with a mean age of 39.91 ± 13.77 years. We evaluated the levels of spasticity by MAS in flexor and extensor muscle groups of the knee and/or elbow, where one muscle group was the agonist and one antagonist. Simultaneously the assessment by the MAS, caught up the MMG signals. We used a custom MMG equipment to register and record the signals, configured in LabView platform. Using the MatLab computer program, it was processed the MMG signals in the time domain (median energy) and spectral domain (median frequency) for the three motion axes: X (transversal), Y (longitudinal) and Z (perpendicular). For bandwidth delimitation, we used a 3rd order Butterworth filter, acting in the range of 5-50 Hz. Statistical tests as Spearman's correlation coefficient, Kruskal-Wallis test and linear correlation test were applied. As results in the time domain, the Kruskal-Wallis test showed differences in median energy (MMGME) between MAS groups. The linear correlation test showed high linear correlation between MAS and MMGME for the agonist muscle as well as for the antagonist group. The largest linear correlation occurred between the MAS and MMG ME for the Z axis of the agonist muscle group (R2 = 0.9557) and the lowest correlation occurred in the X axis, for the antagonist muscle group (R2 = 0.8862). The Spearman correlation test also confirmed high correlation for all axes in the time domain analysis. In the spectral domain, the analysis showed an increase in the median frequency (MMGMF) in MAS’ greater levels. The highest correlation coefficient between MAS and MMGMF signal occurred in the Z axis for the agonist muscle group (R2 = 0.4883), and the lowest value occurred on the Y axis for the antagonist group (R2 = 0.1657). By means of the Spearman correlation test, the highest correlation occurred between the Y axis of the agonist group (0.6951; p <0.001) and the lowest value on the X axis of the antagonist group (0.3592; p <0.001). We conclude that there was a significantly high correlation between the MMGME and MAS in both muscle groups. Also between MMG and MAS occurred a significant correlation, however moderate for the agonist group, and low for the antagonist group. So, the MMGME proved to be more an appropriate descriptor to correlate with the degree of spasticity defined by the MAS.