10 resultados para INVERSE

em University of Queensland eSpace - Australia


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The focus of the present work is the well-known feature of the probability density function (PDF) transport equations in turbulent flows-the inverse parabolicity of the equations. While it is quite common in fluid mechanics to interpret equations with direct (forward-time) parabolicity as diffusive (or as a combination of diffusion, convection and reaction), the possibility of a similar interpretation for equations with inverse parabolicity is not clear. According to Einstein's point of view, a diffusion process is associated with the random walk of some physical or imaginary particles, which can be modelled by a Markov diffusion process. In the present paper it is shown that the Markov diffusion process directly associated with the PDF equation represents a reasonable model for dealing with the PDFs of scalars but it significantly underestimates the diffusion rate required to simulate turbulent dispersion when the velocity components are considered.

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An inverse methodology for the design of biologically loaded radio-frequency (RF) coils for magnetic resonance imaging applications is described. Free space time-harmonic electromagnetic Green's functions and de-emphasized B-1 target fields are used to calculate the current density on the coil cylinder. In theory, with the B-1 field de-emphasized in the middle of the RF transverse plane, the calculated current distribution can generate an internal magnetic field that can reduce the central overemphasis effect caused by field/tissue interactions at high frequencies. The current distribution of a head coil operating at 4 T (170 MHz) is calculated using an inverse methodology with de-emphasized B-1. target fields. An in-house finite-difference time-domain routine is employed to evaluate B-1 field and signal intensity inside a homogenous cylindrical phantom and then a complete human head model. A comparison with a conventional RF birdcage coil is carried out and demonstrates that this method can help in decreasing the normal bright region caused by field/tissue interactions in head images at 170 MHz and higher field strengths.

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Radio-frequency ( RF) coils are designed such that they induce homogeneous magnetic fields within some region of interest within a magnetic resonance imaging ( MRI) scanner. Loading the scanner with a patient disrupts the homogeneity of these fields and can lead to a considerable degradation of the quality of the acquired image. In this paper, an inverse method is presented for designing RF coils, in which the presence of a load ( patient) within the MRI scanner is accounted for in the model. To approximate the finite length of the coil, a Fourier series expansion is considered for the coil current density and for the induced fields. Regularization is used to solve this ill-conditioned inverse problem for the unknown Fourier coefficients. That is, the error between the induced and homogeneous target fields is minimized along with an additional constraint, chosen in this paper to represent the curvature of the coil windings. Smooth winding patterns are obtained for both unloaded and loaded coils. RF fields with a high level of homogeneity are obtained in the unloaded case and a limit to the level of homogeneity attainable is observed in the loaded case.

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Kalman inverse filtering is used to develop a methodology for real-time estimation of forces acting at the interface between tyre and road on large off-highway mining trucks. The system model formulated is capable of estimating the three components of tyre-force at each wheel of the truck using a practical set of measurements and inputs. Good tracking is obtained by the estimated tyre-forces when compared with those simulated by an ADAMS virtual-truck model. A sensitivity analysis determines the susceptibility of the tyre-force estimates to uncertainties in the truck's parameters.

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An inverse methodology to assist in the design of radio-frequency (RF) head coils for high field MRI application is described in this work. Free space time-harmonic electromagnetic Green's functions and preemphasized B1 field are used to calculate the current density on the coil cylinder. With B1 field preemphasized and lowered in the middle of the RF transverse plane, the calculated current distribution can generate an internal magnetic field that can reduce the EM field/tissue interactions at high frequencies. The current distribution of a head coil operating at 4 T is calculated using inverse methodology with preemphasized B1 fields. FDTD is employed to calculate B1 field and signal intensity inside a homogenous cylindrical phantom and human head. A comparison with conventional RF birdcage coil is reported here and demonstrated that inverse-method designed coil with preemphasized B1 field can help in decreasing the notorious bright region caused by EM field/tissue interactions in the human head images at 4 T.

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Calculating the potentials on the heart’s epicardial surface from the body surface potentials constitutes one form of inverse problems in electrocardiography (ECG). Since these problems are ill-posed, one approach is to use zero-order Tikhonov regularization, where the squared norms of both the residual and the solution are minimized, with a relative weight determined by the regularization parameter. In this paper, we used three different methods to choose the regularization parameter in the inverse solutions of ECG. The three methods include the L-curve, the generalized cross validation (GCV) and the discrepancy principle (DP). Among them, the GCV method has received less attention in solutions to ECG inverse problems than the other methods. Since the DP approach needs knowledge of norm of noises, we used a model function to estimate the noise. The performance of various methods was compared using a concentric sphere model and a real geometry heart-torso model with a distribution of current dipoles placed inside the heart model as the source. Gaussian measurement noises were added to the body surface potentials. The results show that the three methods all produce good inverse solutions with little noise; but, as the noise increases, the DP approach produces better results than the L-curve and GCV methods, particularly in the real geometry model. Both the GCV and L-curve methods perform well in low to medium noise situations.