<p> The TNO model, a trailing edge noise prediction method, is validated, modified, and analyzed for various input formats. Two different methods are used to calculate the flow field for this model: Reynolds averaged Navier-Stokes (RANS) and a viscous panel method, XFOIL. It is found that the RANS-based TNO model show good agreement with the experiments but the XFOIL-based TNO was found to overpredict the turbulence kinetic energy and, consequently, the sound pressure level. A modification is made in the XFOIL-based TNO model by substituting Prandtl's mixing length hypothesis from the original model with a new blended model consisting of the mixing length hypothesis and the Cebeci-Smith eddy viscosity model. Twenty-six different test cases are tested with airfoils: NACA 0012, NACA 0015, NACA 64-618, NACA 64₃-418, and DU 96-w-180. RANS input to the TNO model is able to predict the sound pressure spectrum to within 3 dB for the frequency range of 800Hz to 2000Hz in 16 of the 26 cases. The new blended model is found to show clear improvements to the prediction for 14 out of the 26 cases when compared to the original XFOIL input. Moreover, the new XFOIL input was able to predict sound pressure level to within 3 dB for 14 of the 26 cases. Overall, the new proposed model improves the prediction for the XFOIL-based TNO model.</p><p>

<p> Due to millions of years of evolution, sharks have evolved to become quick and efficient ocean apex predators. Shark skin is made up of millions of microscopic scales, or denticles, that are approximately 0.2 mm in size. Scales located on the shark&rsquo;s body where separation control is paramount (such as behind the gills or the trailing edge of the pectoral fin) are capable of bristling. These scales are hypothesized to act as a flow control mechanism capable of being passively actuated by reversed flow. It is believed that shark scales are strategically sized to interact with the lower 5% of a boundary layer, where reversed flow occurs at the onset of boundary layer separation. Previous research has shown shark skin to be capable of controlling separation in water. This thesis aims to investigate the same passive flow control techniques in air. </p><p> To investigate this phenomenon, several sets of microflaps were designed and manufactured with a 3D printer. The microflaps were designed in both 2D (rectangular) and 3D (mirroring shark scale geometry) variants. These microflaps were placed in a low-speed wind tunnel in the lower 5% of the boundary layer. Solid fences and a flat plate diffuser with suction were placed in the tunnel to create different separated flow regions. A hot film probe was used to measure velocity magnitude in the streamwise plane of the separated regions. The results showed that low-speed airflow is capable of bristling objects in the boundary layer. When placed in a region of reverse flow, the microflaps were passively actuated. Microflaps fluctuated between bristled and flat states in reverse flow regions located close to the reattachment zone.</p><p>

<p> As aircraft are designed to a greater extent on computers, the need for accurate and fast CFD algorithms has never been greater. The development of CFD algorithms requires experimental data against which CFD output can be validated and from which insight about flow physics can be acquired. Skin friction, in particular, is an important quantity to predict with CFD, and experimental skin friction data sets aid not only with the validation of the CFD predictions, but also in tuning the CFD models to predict specific flow fields. However, a practical experimental technique for collecting spatially and temporally resolved skin friction data on complex models does not yet exist. This dissertation develops and demonstrates a new luminescent oil film skin friction meter which can produce spatially-resolved quantitative steady and unsteady skin friction data on models with complex curvature. </p><p> The skin friction acting on the surface of a thin film of oil can be approximated by the expression &tau;<i>_w</i> =&mu;<i>_o</i><i>u_h/h</i>, where &mu;<i>_o</i> is the dynamic viscosity of the oil, <i>u_h</i> is the velocity of the surface of the oil film, and <i>h</i> is the thickness of the oil film. The new skin friction meter determines skin friction by measuring <i>h</i> and <i>u_h</i>. The oil film thickness <i>h</i> is determined by ratioing the intensity of the fluorescent emissions from the oil film with the intensity of the incident light which is scattered from the surface of the model. When properly calibrated, that ratio provides an absolute oil film thickness value. This oil film thickness meter is therefore referred as the Ratioed-Image Film-Thickness (RIFT) Meter. The oil film velocity <i>u_h</i> is determined by monitoring the evolution of tagged molecules within the oil film: Photochromic molecules are dissolved into the fluorescent oil and a pattern is written into the oil film using an ultraviolet laser. The evolution of the pattern is recorded, and standard cross-correlation techniques are applied to the resulting sequence of images. This newly developed skin friction meter is therefore called the Luminescent Oil Film Flow-Tagging skin friction meter, or the LOFFT skin friction meter. The LOFFT skin friction meter is demonstrated by collecting time-averaged skin friction measurements on NASA's FAITH model and by collecting unsteady skin friction measurements with a frequency response of 600Hz. Higher frequency response is possible and is dependent on the experimental setup. </p><p> This dissertation also contributes to the work done on the Global Luminescent Oil Film Skin Friction Meter (GLOFSFM) by noting that the technique could be influenced by ripples at the oil-air interface. An experiment studying the evolution of ripples at the oil-air interface was conducted to determine under what oil film conditions the GLOFSFM can be appropriately applied. The RIFT meter was crucial for this experiment, as it facilitated quantitative distributed oil film thickness measurements during the wind-tunnel run. The resulting data set is rich in content, permitting the computation of mean wavelengths, peak-to-trough ripple heights, wave speeds, and mean thicknesses. In addition to determining under what oil film conditions the GLOFSFM may be applied, this experiment directly determined the oil film conditions under which the velocity of the ripples may be used to proxy the velocity of the oil film surface. The RIFT meter and the ability to determine oil film surface velocity by monitoring ripple velocities admit yet another time-averaged skin friction meter, the Fluorescent-Oil Ripple-Velocity (FORV) skin friction meter. The FORV skin friction meter recovers skin friction as &tau;<i>_w</i> = &mu;<i>_ov_rip/H</i>, where <i> v_rip</i> is the velocity of the ripples, and <i>H</i> is the oil film thickness averaged over the thickness fluctuations due to the ripples. The FORV skin friction meter is demonstrated on NASA's FAITH model.</p><p>

<p> With the growing threat of orbital debris impacts to space structures, the development of space shielding concepts has been a critical research topic. In this study, numerical simulations of the hypervelocity impact response of stacked aluminum 6061-T6 sheets were performed to assess the effects of layering on penetration resistance. This work was initially motivated by set of experimental tests where a stack of four aluminum sheets of equal thickness was observed to have a higher hypervelocity ballistic resistance than a monolithic aluminum sheet with the same total thickness. A set of smoothed particle hydrodynamic simulations predicted a 40% increase in the ballistic limit for a 6-layer target compared to a monolithic sheet. In addition, the effect of variable sheet thickness and sheet ordering on the impact resistance was investigated, while still maintaining a constant overall thickness. A set of thin layers in front of a thick layer generally lead to a higher predicted ballistic limit than the inverse configuration. This work demonstrates an increase in the performance of advanced space shielding structures associated with multi-layering. This suggests that it may be possible to dramatically improve the performance of such structures by tailoring the material properties, interfaces, and layering concepts.</p><p>

The goal of this dissertation is to introduce a method of fault diagnosis that is designed to cope with fault signature variability, the main source of difficulty for the existing diagnostic systems. This method is a non-parametric pattern classifier that uses a multi-valued influence matrix (MVIM) as its diagnostic model. In this method, process abnormalities are detected through processing the sensory data and flagging, and diagnostic reasoning is performed by matching the flagged measurements against the columns of the influence matrix. Fault signature improvement is achieved by a Flagging Unit, which is tuned based on a training set. This unit is shown to have the ability to improve detection, reduce false alarms, and enhance diagnostics. The improved fault signatures by the Flagging Unit are also shown to be beneficial to other classifiers such as the Bayes classifier and artificial neural nets. The applicability of the MVIM method is investigated in fault diagnosis of a helicopter gearbox. A total of five tests were performed, during which eight failures occurred. In order to enhance the effect of the failures on the vibration data, the vibration signals obtained from the gearbox were digitized and processed by a vibration signal analyzer. The parameters obtained from this signal analyzer were then utilized to train the MVIM method and test its performance for both detection and diagnosis. The averaged values of the parameters obtained from individual accelerometers were used to reduce the processing time. Training sets were formed based on parameters from various combinations of the five tests, and the MVIM method was tested based on the parameters from all of the five tests. Detection results indicate that the MVIM method provided excellent results when the full range of faults' effects on the vibration measurements were included in the training set. The MVIM method was also utilized to rank the parameters for their significance in detection. It is shown that through this ranking the optimal subset of parameters for detection can be selected, which is particularly important in reducing processing time for on-line detection. For diagnosis, the MVIM method was used in a hierarchical manner. The parameters from individual accelerometers were first processed through detection MVIMs, to trigger the presence of a fault, and then examined by diagnostic MVIMs to identify the fault. Diagnostic results show that the MVIM method had a correct diagnostic rate of 95% for the faults included in training. (Abstract shortened by UMI.)

The problem of detection of a constant signal in additive noise is addressed. In centralized detectors all observations are obtained and processed at the same place, whereas in distributed detectors observations on the same phenomenon is obtained at several geographically dispersed local sensors. The local sensors transmit a condensed signal to a global decision maker. In this dissertation we address some problems under both categories. We present centralized truncated sequential nonparametric detectors that can be implemented with a hard-limiter and a dead-zone limiter. These detectors are based on approximations of the sequential sign and the sequential conditional sign detectors. The sequential tests are modelled as Markov chains for design and performance evaluations. By using truncation the possibility of excessively long tests is removed. The approximations allow mathematically tractable design for constant false alarm rate (CFAR) performance. In comparison to the sequential sign and conditional sign detectors, the proposed detectors have slightly higher average sample numbers (ASN) under no signal and nominal signal conditions, but considerably lower ASN for intermediate signal strengths. A number of distributed detection schemes are considered. Firstly, the optimum decision policy for a sequential fusion center with fixed local sensors is studied. The sequential fusion rule is numerically studied using Markov chain modelling. We then focus on deriving optimum M level quantizers at the local sensors where $M > 2$. The solutions are obtained assuming a fixed fusion rule using the Bayesian and the locally optimum detection criteria. The receiver operating characteristics for different values of M and a number of different fusion rules are compared. The performance improves with increasing values of M; however the communication cost also increases. Finally, the concept of multilevel quantization is extended to distributed nonparametric detection. Two schemes are presented which employ Wilcoxon statistics and generate M-level signals from the local sensors. Design issues and numerical performance evaluations of the proposed detectors are presented.

Thesis (M.App.Sc.) - Carleton University, 2009. / Includes bibliographical references (p.153-159). Also available in electronic format on the Internet.

<p> The effects of vapor-grown carbon nanofiber (VGCNF) weight fraction, applied stress, and temperature on the viscoelastic responses (creep strain, creep rate, and creep compliance) of VGCNF/vinyl ester (VE) nanocomposites were studied using a central composite design (CCD). The nanocomposite test articles were fabricated by high shear mixing, casting, curing, and post-curing in an open face mold under a nitrogen environment. Short-term creep/creep recovery experiments were conducted at prescribed combinations of temperatures (23.8 - 69.2 C), applied stresses (30.2 - 49.8 MPa), and VGCNF weight fractions (0.00 - 1.00 parts of VGCNF per hundred parts of resin, phr) determined from the CCD. The response surface models (RSMs) for predicting these viscoelastic responses were developed using the least squares method and an analysis of variance procedure. The response surface estimates indicate that increasing the VGCNF weight fraction marginally increases the creep resistance of the VGCNF/VE nanocomposite at low temperatures (i.e., 23.8 - 46.5 C). However, increasing the VGCNF weight fraction for temperatures greater than 50 C decreased the creep resistance of these nanocomposites. The latter response may be due to a decrease in the nanofiber-to-matrix adhesion as the temperature is increased. The RSMs for creep strain, creep rate, and creep compliance revealed the interactions between the VGCNF weight fraction, stress, and temperature on the creep behavior of thermoset polymer</p>

<p> NASA has had a decades-long problem with cost growth during the development of space science missions. Numerous agency-sponsored studies have produced average mission level development cost growths ranging from 23 to 77%. </p><p> A new study of 26 historical NASA science instrument set developments using expert judgment to re-allocate key development resources has an average cost growth of 73.77%. Twice in history, during the Cassini and EOS-Terra science instrument developments, a barter-based mechanism has been used to re-allocate key development resources. The mean instrument set development cost growth was -1.55%. Performing a bivariate inference on the means of these two distributions, there is statistical evidence to support the claim that using a barter-based mechanism to re-allocate key instrument development resources will result in a lower expected cost growth than using the expert judgment approach. </p><p> Agent-based discrete event simulation is the natural way to model a trade environment. A NetLogo agent-based barter-based simulation of science instrument development was created. The agent-based model was validated against the Cassini historical example, as the starting and ending instrument development conditions are available. The resulting validated agent-based barter-based science instrument resource re-allocation simulation was used to perform 300 instrument development simulations, using barter to re-allocate development resources. The mean cost growth was -3.365%. A bivariate inference on the means was performed to determine that additional significant statistical evidence exists to support a claim that using barter-based resource re-allocation will result in lower expected cost growth, with respect to the historical expert judgment approach. </p><p> Barter-based key development resource re-allocation should work on science spacecraft development as well as it has worked on science instrument development. A new study of 28 historical NASA science spacecraft developments has an average cost growth of 46.04%. As barter-based key development resource re-allocation has never been tried in a spacecraft development, no historical results exist, and an inference on the means test is not possible. </p><p> A simulation of using barter-based resource re-allocation should be developed. The NetLogo instrument development simulation should be modified to account for spacecraft development market participant differences. The resulting agent-based barter-based spacecraft resource re-allocation simulation would then be used to determine if significant statistical evidence exists to prove a claim that using barter-based resource re-allocation will result in lower expected cost growth.</p>

<p> Nanofluids, stable colloidal suspensions of nanoparticles in a base fluid, have potential applications in the heat transfer, combustion and propulsion, manufacturing, and medical fields. Experiments were conducted to determine the evaporation rate of room temperature, millimeter-sized pendant drops of ethanol laden with varying amounts (0-3% by weight) of 40-60 nm aluminum nanoparticles (nAl). Time-resolved high-resolution drop images were collected for the determination of early-time evaporation rate (D²/D₀² > 0.75), shown to exhibit D-square law behavior, and surface tension. Results show an asymptotic decrease in pendant drop evaporation rate with increasing nAl loading. The evaporation rate decreases by approximately 15% at around 1% to 3% nAl loading relative to the evaporation rate of pure ethanol. Surface tension was observed to be unaffected by nAl loading up to 3% by weight. </p><p> A model was developed to describe the evaporation of the nanofluid pendant drops based on D-square law analysis for the gas domain and a description of the reduction in liquid fraction available for evaporation due to nanoparticle agglomerate packing near the evaporating drop surface. Model predictions are in relatively good agreement with experiment, within a few percent of measured nanofluid pendant drop evaporation rate. </p><p> The evaporation of pinned nanofluid sessile drops was also considered via modeling. It was found that the same mechanism for nanofluid evaporation rate reduction used to explain pendant drops could be used for sessile drops. That mechanism is a reduction in evaporation rate due to a reduction in available ethanol for evaporation at the drop surface caused by the packing of nanoparticle agglomerates near the drop surface. Comparisons of the present modeling predictions with sessile drop evaporation rate measurements reported for nAl/ethanol nanofluids by Sefiane and Bennacer [11] are in fairly good agreement. Portions of this abstract previously appeared as: W. J. Gerken, A. V. Thomas, N. Koratkar and M. A. Oehlschlaeger, Int. J. Heat Mass Transfer, vol. 74, no. 1, pp. 263-268, July 2014. W. J. Gerken, M. A. Oehlschlaeger, "Nanofluid Pendant Droplet Evaporation", in Proceedings of the ASME 2013 Summer Heat Transfer Conference, Minneapolis, MN, 2013, pp. V001T03A018.</p>