No description available.

Time-resolved velocity information of carotid blood flow can be used to estimate haemodynamic conditions associated with carotid artery disease leading to stroke. MRI provides high-resolution measurement of such information but long scan time limits its clinical application in this area. In order to reduce scan time the MRI signal is often undersampled by skipping part of the signal during data acquisition. The aim of this work is to implement and evaluate different undersampling techniques for carotid velocity measurement on a 1.5 T clinical scanner. Most recent undersampling techniques assume spatial and temporal redundancies of real time-resolved MRI signal. In these techniques different undersampling strategies were proposed. Prior information or different assumptions of the nature of true signal were used in signal reconstruction. A brief review of these techniques and details of a representative technique, known as k-t BLAST, are presented. Another undersampling scheme, termed ktVD, is proposed to use predesigned undersampling patterns with variable sampling densities in both temporal and spatial dimensions. It aims to collect enough signal content at the signal acquisition stage and simplify signal reconstruction. Fidelity of the results from undersampled data is affected by many factors, such as signal dynamic content, degree of signal redundancy, noise level, degree of undersampling, undersampling patterns, and parameters of post-processing algorithms. Simulations and in vivo scans were conducted to investigate the effects of these factors in time-resolved 2D scans and time-resolved 3D scans. The results suggested velocity measurement became less reliable when they were obtained from less than 25% of the full signal. In time-resolved 3D scans the signal can be undersampled in either one or two spatial dimensions in addition to the temporal dimension. This allows more options in the design of undersampling patterns, which were tested in vivo. In order to test undersampling in three dimensions in high resolution 3D scans and measure velocity in three dimensions, a flow phantom was also scanned at high degrees of undersampling to test the proposed method.

Doctor of Philosophy / Department of Biological and Agricultural Engineering / Naiqian Zhang / An optical sensor for determining water velocity in natural open channels like creeks and rivers has been designed and tested. The sensor consists of a plastic body which is shaped so that water flows through a U-shaped channel into which are mounted LEDs and matching phototransistors at various angles. A small amount of dye is injected into the water just upstream of two sets of LEDs and phototransistors which are spaced 4 cm apart. The time delay between the dye’s effects on these signals depends on water velocity and is determined using a biased cross correlation calculation. In addition to providing velocity, the LEDs and phototransistors can also be used to estimate soil sediment concentration. A previous version of the sensor was tested in enclosed flow to confirm that the general design of the sensor, including LEDs, phototransistors, dye and electronics, would indeed work to detect the velocity of water flowing through the sensor. Although the conditions for the test were unlike those experienced in natural open channels, the ability to catch all the fluid flowing through the sensor provided a simple confirmation of the velocity estimate that was not available in field settings. Further testing in the field then confirmed that the sensor worked in the field but also identified several areas needing improvement. Computational fluid dynamics was used to improve the sensor body. The electronics and program running the sensor were also redesigned. After making these improvements, a new version of the sensor was produced. The testing of the new version of the sensor confirmed its ability to accurately detect velocity in natural open channels. The velocity measurements from this sensor were compared to the commercially available Flowtracker velocity sensor. A regression analysis on the measurements from the two sensors found that the velocity measurements from each sensor were nearly identical across a range of velocities. Other tests established that the electronics and programming running the sensor performed as designed. The development and testing of this sensor has resulted in a system which works in natural open channels like creeks and rivers.

Doctor of Philosophy / Department of Biological & Agricultural Engineering / Naiqian Zhang / Suspended sediment concentration (SSC) in water is one of the most important parameters to evaluate water quality. Monitoring SSC provides important information on determining sediment transport for soil erosion research and soil/water conservation practices. Sediment mass transported at a given time can be assessed by simultaneous SSC and water flow velocity measurements. Fouling, including bio-fouling, has damaging impact on optical SSC measurements over the long term. In this study, an inexpensive, real-time, self-cleaning, optical sediment and flow velocity sensor was developed. Laboratory experiments were conducted on a previously designed SSC sensor. A light modulation algorithm was designed to reduce the influence of ambient light, especially sunlight, on measurement accuracy. Statistical models to predict SSC based on measured light intensities were established and compared with neural network models. The statistical analysis showed that soil texture played an important role in SSC measurement accuracy while the designed sensor was capable of reducing the effect of water color on sensor performance. Neural-network models can further remove the influence of soil texture type on SSC measurement. The sensor design was simplified based on a stepwise selection analysis. Long-term field experiments were conducted in Kansas and Georgia to evaluate the sensor performance, the effect of fouling, including bio-fouling, on sensor lenses, and the effect of temperature on the measurement. Methods of removing the fouling effect through data correction were developed. Results indicated that the designed optical SSC sensor was capable of providing rapid response to SSC fluctuations in water flow. Temperature of the water body has an insignificant impact on SSC measurement. In order to reduce fouling, an air-blast cleaning mechanism was integrated into the optical sediment sensor. Laboratory experiments in a manually created fouling environment were conducted to observe the fouling process on sensor cases made of different materials, and to verify the effectiveness of air-blast cleaning in reducing fouling. Results indicated that air-blast cleaning mechanism was capable of reducing clay/silt fouling on sensor signals. The duration and frequency of air-blast cleaning can be determined and adjusted depending on actual field conditions. An air pressure drop test was conducted on the hose carrying pressurized air. Results showed negligible pressure drop.A flow velocity measurement function based on the cross-correlation principle was integrated into the optical sediment sensor. An experiment was conducted in laboratory to examine the sensor performance on velocity measurement using a closed circulation system. A solution of blue colorant, Brilliant Blue FCF, was used as an artificial source to absorb light emitted by LEDs in the sensor and the signal variation patterns were measured. The results indicated that the cross-correlation-based velocity sensor was capable of measuring water flow velocity within in a certain velocity range using the dye injection method.

Flow rate measurements are a common topic for process monitoring in chemical engineering and food industry. To achieve the requested low uncertainties of 0:1% for flow rate measurements, a precise measurement of the shear layers of such flows is necessary. The Laser Doppler Velocimeter (LDV) is an established method for measuring local flow velocities. For exact estimation of the flow rate, the flow profile in the shear layer is of importance. For standard LDV the axial resolution and therefore the number of measurement points in the shear layer is defined by the length of the measurement volume. A decrease of this length is accompanied by a larger fringe distance variation along the measurement axis which results in a rise of the measurement uncertainty for the flow velocity (uncertainty relation between spatial resolution and velocity uncertainty). As a unique advantage, the laser Doppler profile sensor (LDV-PS) overcomes this problem by using two fan-like fringe systems to obtain the position of the measured particles along the measurement axis and therefore achieve a high spatial resolution while it still offers a low velocity uncertainty. With this technique, the flow rate can be estimated with one order of magnitude lower uncertainty, down to 0:05% statistical uncertainty.1 And flow profiles especially in film flows can be measured more accurately. The problem for this technique is, in contrast to laboratory setups where the system is quite stable, that for industrial applications the sensor needs a reliable and robust traceability to the SI units, meter and second. Small deviations in the calibration can, because of the highly position depending calibration function, cause large systematic errors in the measurement result. Therefore, a simple, stable and accurate tool is needed, that can easily be used in industrial surroundings to check or recalibrate the sensor. In this work, different calibration methods are presented and their in uences to the measurement uncertainty budget of the sensor is discussed. Finally, generated measurement results for the film flow of an impinging jet cleaning experiment are presented.