Non-intrusive pressure measurement in microchannels

A non-intrusive interferometric measurement technique has been successfully developed to measure fluid compressibility in both gas and liquid phases via refractive index (RI) changes. The technique, consisting of an unfocused laser beam impinging a glass channel, can be used to separate and quantify cell deflection, fluid flow rates, and pressure variations in microchannels. Currently in fields such as microfluidics, pressure and flow rate measurement devices are orders of magnitude larger than the channel cross-sections making direct pressure and fluid flow rate measurements impossible. Due to the non-intrusive nature of this technique, such measurements are now possible, opening the door for a myriad of new scientific research and experimentation. This technique, adapted from the concept of Micro Interferometric Backscatter Detection (MIBD), boasts the ability to provide comparable sensitivities in a variety of channel types and provides quantification capability not previously demonstrated in backscatter detection techniques. Measurement sensitivity depends heavily on experimental parameters such as beam impingement angle, fluid volume, photodetector sensitivity, and a channel’s dimensional tolerances. The current apparatus readily quantifies fluid RI changes of 10-5 refractive index units (RIU) corresponding to pressures of approximately 14 psi and 1 psi in water and air, respectively. MIBD reports detection capability as low as 10-9 RIU and the newly adapted technique has the potential to meet and exceed this limit providing quantification in the place of detection. Specific device sensitivities are discussed and suggestions are provided on how the technique may be refined to provide optimal quantification capabilities based on experimental conditions.

Comparison of magnetic properties and petrography between dykes and lava flows from La Cienega, New Mexico and Thunder Bay area, Canada

Data on the evolution of geomagnetic paleointensity are crucial for understanding the geodynamo and Earth’s thermal history. Although basaltic flows are preferred for paleointensity experiments, quickly cooled mafic dykes have also been used. However, the paleointensity values obtained from the dykes are systematically lower than those from lava flows. This bias may originate from the difference in cooling histories and resultant magnetic mineralogies of extrusive and intrusive rocks. To explore this hypothesis, the magnetic mineralogy of two feeder dyke-lave flow systems, from Thunder Bay (Canada) and La Cienega (New-Mexico), has been studied using magnetic and microscopy methods. Within each system, the flow and dyke show different stages of deuteric oxidation of titanomagnetite, but the oxidation stages also differ between the two systems. It is concluded that the tested hypothesis is viable, but the relationships between the magnetic and mineralogical properties of flows and dykes are complex and need a further investigation.

Comprehensive review and application of particle image velocimetry

For a fluid dynamics experimental flow measurement technique, particle image velocimetry (PIV) provides significant advantages over other measurement techniques in its field. In contrast to temperature and pressure based probe measurements or other laser diagnostic techniques including laser Doppler velocimetry (LDV) and phase Doppler particle analysis (PDPA), PIV is unique due to its whole field measurement capability, non-intrusive nature, and ability to collect a vast amount of experimental data in a short time frame providing both quantitative and qualitative insight. These properties make PIV a desirable measurement technique for studies encompassing a broad range of fluid dynamics applications. However, as an optical measurement technique, PIV also requires a substantial technical understanding and application experience to acquire consistent, reliable results. Both a technical understanding of particle image velocimetry and practical application experience are gained by applying a planar PIV system at Michigan Technological University’s Combustion Science Exploration Laboratory (CSEL) and Alternative Fuels Combustion Laboratory (AFCL). Here a PIV system was applied to non-reacting and reacting gaseous environments to make two component planar PIV as well as three component stereographic PIV flow field velocity measurements in conjunction with chemiluminescence imaging in the case of reacting flows. This thesis outlines near surface flow field characteristics in a tumble strip lined channel, three component velocity profiles of non-reacting and reacting swirled flow in a swirl stabilized lean condition premixed/prevaporized-fuel model gas turbine combustor operating on methane at 5-7 kW, and two component planar PIV measurements characterizing the AFCL’s 1.1 liter closed combustion chamber under dual fan driven turbulent mixing flow.

A study of acoustic emission technique for concrete damage detection

The Acoustic emission (AE) technique, as one of non-intrusive and nondestructive evaluation techniques, acquires and analyzes the signals emitting from deformation or fracture of materials/structures under service loading. The AE technique has been successfully applied in damage detection in various materials such as metal, alloy, concrete, polymers and other composite materials. In this study, the AE technique was used for detecting crack behavior within concrete specimens under mechanical and environmental frost loadings. The instrumentations of the AE system used in this study include a low-frequency AE sensor, a computer-based data acquisition device and a preamplifier linking the AE sensor and the data acquisition device. The AE system purchased from Mistras Group was used in this study. The AE technique was applied to detect damage with the following laboratory tests: the pencil lead test, the mechanical three-point single-edge notched beam bending (SEB) test, and the freeze-thaw damage test. Firstly, the pencil lead test was conducted to verify the attenuation phenomenon of AE signals through concrete materials. The value of attenuation was also quantified. Also, the obtained signals indicated that this AE system was properly setup to detect damage in concrete. Secondly, the SEB test with lab-prepared concrete beam was conducted by employing Mechanical Testing System (MTS) and AE system. The cumulative AE events and the measured loading curves, which both used the crack-tip open displacement (CTOD) as the horizontal coordinate, were plotted. It was found that the detected AE events were qualitatively correlated with the global force-displacement behavior of the specimen. The Weibull distribution was vii proposed to quantitatively describe the rupture probability density function. The linear regression analysis was conducted to calibrate the Weibull distribution parameters with detected AE signals and to predict the rupture probability as a function of CTOD for the specimen. Finally, the controlled concrete freeze-thaw cyclic tests were designed and the AE technique was planned to investigate the internal frost damage process of concrete specimens.

MODELING OF TRANSFER PATH FOR DETERMINATION OF COMBUSTION AND NOISE METRICS ON DIESEL ENGINES

Determination of combustion metrics for a diesel engine has the potential of providing feedback for closed-loop combustion phasing control to meet current and upcoming emission and fuel consumption regulations. This thesis focused on the estimation of combustion metrics including start of combustion (SOC), crank angle location of 50% cumulative heat release (CA50), peak pressure crank angle location (PPCL), and peak pressure amplitude (PPA), peak apparent heat release rate crank angle location (PACL), mean absolute pressure error (MAPE), and peak apparent heat release rate amplitude (PAA). In-cylinder pressure has been used in the laboratory as the primary mechanism for characterization of combustion rates and more recently in-cylinder pressure has been used in series production vehicles for feedback control. However, the intrusive measurement with the in-cylinder pressure sensor is expensive and requires special mounting process and engine structure modification. As an alternative method, this work investigated block mounted accelerometers to estimate combustion metrics in a 9L I6 diesel engine. So the transfer path between the accelerometer signal and the in-cylinder pressure signal needs to be modeled. Depending on the transfer path, the in-cylinder pressure signal and the combustion metrics can be accurately estimated - recovered from accelerometer signals. The method and applicability for determining the transfer path is critical in utilizing an accelerometer(s) for feedback. Single-input single-output (SISO) frequency response function (FRF) is the most common transfer path model; however, it is shown here to have low robustness for varying engine operating conditions. This thesis examines mechanisms to improve the robustness of FRF for combustion metrics estimation. First, an adaptation process based on the particle swarm optimization algorithm was developed and added to the single-input single-output model. Second, a multiple-input single-output (MISO) FRF model coupled with principal component analysis and an offset compensation process was investigated and applied. Improvement of the FRF robustness was achieved based on these two approaches. Furthermore a neural network as a nonlinear model of the transfer path between the accelerometer signal and the apparent heat release rate was also investigated. Transfer path between the acoustical emissions and the in-cylinder pressure signal was also investigated in this dissertation on a high pressure common rail (HPCR) 1.9L TDI diesel engine. The acoustical emissions are an important factor in the powertrain development process. In this part of the research a transfer path was developed between the two and then used to predict the engine noise level with the measured in-cylinder pressure as the input. Three methods for transfer path modeling were applied and the method based on the cepstral smoothing technique led to the most accurate results with averaged estimation errors of 2 dBA and a root mean square error of 1.5dBA. Finally, a linear model for engine noise level estimation was proposed with the in-cylinder pressure signal and the engine speed as components.