Matching Items (40)
Filtering by
- All Subjects: Mechanical Engineering
- Creators: Rykaczewski, Konrad
Description
Microfluidics is the study of fluid flow at very small scales (micro -- one millionth of a meter) and is prevalent in many areas of science and engineering. Typical applications include lab-on-a-chip devices, microfluidic fuel cells, and DNA separation technologies. Many of these microfluidic devices rely on micron-resolution velocimetry measurements to improve microchannel design and characterize existing devices. Methods such as micro particle imaging velocimetry (microPIV) and micro particle tracking velocimetry (microPTV) are mature and established methods for characterization of steady 2D flow fields. Increasingly complex microdevices require techniques that measure unsteady and/or three dimensional velocity fields. This dissertation presents a method for three-dimensional velocimetry of unsteady microflows based on spinning disk confocal microscopy and depth scanning of a microvolume. High-speed 2D unsteady velocity fields are resolved by acquiring images of particle motion using a high-speed CMOS camera and confocal microscope. The confocal microscope spatially filters out of focus light using a rotating disk of pinholes placed in the imaging path, improving the ability of the system to resolve unsteady microPIV measurements by improving the image and correlation signal to noise ratio. For 3D3C measurements, a piezo-actuated objective positioner quickly scans the depth of the microvolume and collects 2D image slices, which are stacked into 3D images. Super resolution microPIV interrogates these 3D images using microPIV as a predictor field for tracking individual particles with microPTV. The 3D3C diagnostic is demonstrated by measuring a pressure driven flow in a three-dimensional expanding microchannel. The experimental velocimetry data acquired at 30 Hz with instantaneous spatial resolution of 4.5 by 4.5 by 4.5 microns agrees well with a computational model of the flow field. The technique allows for isosurface visualization of time resolved 3D3C particle motion and high spatial resolution velocity measurements without requiring a calibration step or reconstruction algorithms. Several applications are investigated, including 3D quantitative fluorescence imaging of isotachophoresis plugs advecting through a microchannel and the dynamics of reaction induced colloidal crystal deposition.
ContributorsKlein, Steven Adam (Author) / Posner, Jonathan D (Thesis advisor) / Adrian, Ronald (Committee member) / Chen, Kangping (Committee member) / Devasenathipathy, Shankar (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2011
Description
Locomotion of microorganisms is commonly observed in nature. Although microorganism locomotion is commonly attributed to mechanical deformation of solid appendages, in 1956 Nobel Laureate Peter Mitchell proposed that an asymmetric ion flux on a bacterium's surface could generate electric fields that drive locomotion via self-electrophoresis. Recent advances in nanofabrication have enabled the engineering of synthetic analogues, bimetallic colloidal particles, that swim due to asymmetric ion flux originally proposed by Mitchell. Bimetallic colloidal particles swim through aqueous solutions by converting chemical fuel to fluid motion through asymmetric electrochemical reactions. This dissertation presents novel bimetallic motor fabrication strategies, motor functionality, and a study of the motor collective behavior in chemical concentration gradients. Brownian dynamics simulations and experiments show that the motors exhibit chemokinesis, a motile response to chemical gradients that results in net migration and concentration of particles. Chemokinesis is typically observed in living organisms and distinct from chemotaxis in that there is no particle directional sensing. The synthetic motor chemokinesis observed in this work is due to variation in the motor's velocity and effective diffusivity as a function of the fuel and salt concentration. Static concentration fields are generated in microfluidic devices fabricated with porous walls. The development of nanoscale particles that swim autonomously and collectively in chemical concentration gradients can be leveraged for a wide range of applications such as directed drug delivery, self-healing materials, and environmental remediation.
ContributorsWheat, Philip Matthew (Author) / Posner, Jonathan D (Thesis advisor) / Phelan, Patrick (Committee member) / Chen, Kangping (Committee member) / Buttry, Daniel (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2011
Description
Locomotion of microorganisms is commonly observed in nature and some aspects of their motion can be replicated by synthetic motors. Synthetic motors rely on a variety of propulsion mechanisms including auto-diffusiophoresis, auto-electrophoresis, and bubble generation. Regardless of the source of the locomotion, the motion of any motor can be characterized by the translational and rotational velocity and effective diffusivity. In a uniform environment the long-time motion of a motor can be fully characterized by the effective diffusivity. In this work it is shown that when motors possess both translational and rotational velocity the motor transitions from a short-time diffusivity to a long-time diffusivity at a time of pi/w. The short-time diffusivities are two to three orders of magnitude larger than the diffusivity of a Brownian sphere of the same size, increase linearly with concentration, and scale as v^2/2w. The measured long-time diffusivities are five times lower than the short-time diffusivities, scale as v^2/{2Dr [1 + (w/Dr )^2]}, and exhibit a maximum as a function of concentration. The variation of a colloid's velocity and effective diffusivity to its local environment (e.g. fuel concentration) suggests that the motors can accumulate in a bounded system, analogous to biological chemokinesis. Chemokinesis of organisms is the non-uniform equilibrium concentration that arises from a bounded random walk of swimming organisms in a chemical concentration gradient. In non-swimming organisms we term this response diffusiokinesis. We show that particles that migrate only by Brownian thermal motion are capable of achieving non-uniform pseudo equilibrium distribution in a diffusivity gradient. The concentration is a result of a bounded random-walk process where at any given time a larger percentage of particles can be found in the regions of low diffusivity than in regions of high diffusivity. Individual particles are not trapped in any given region but at equilibrium the net flux between regions is zero. For Brownian particles the gradient in diffusivity is achieved by creating a viscosity gradient in a microfluidic device. The distribution of the particles is described by the Fokker-Planck equation for variable diffusivity. The strength of the probe concentration gradient is proportional to the strength of the diffusivity gradient and inversely proportional to the mean probe diffusivity in the channel in accordance with the no flux condition at steady state. This suggests that Brownian colloids, natural or synthetic, will concentrate in a bounded system in response to a gradient in diffusivity and that the magnitude of the response is proportional to the magnitude of the gradient in diffusivity divided by the mean diffusivity in the channel.
ContributorsMarine, Nathan Arasmus (Author) / Posner, Jonathan D (Thesis advisor) / Adrian, Ronald J (Committee member) / Frakes, David (Committee member) / Phelan, Patrick E (Committee member) / Santos, Veronica J (Committee member) / Arizona State University (Publisher)
Created2013
Description
Human fingertips contain thousands of specialized mechanoreceptors that enable effortless physical interactions with the environment. Haptic perception capabilities enable grasp and manipulation in the absence of visual feedback, as when reaching into one's pocket or wrapping a belt around oneself. Unfortunately, state-of-the-art artificial tactile sensors and processing algorithms are no match for their biological counterparts. Tactile sensors must not only meet stringent practical specifications for everyday use, but their signals must be processed and interpreted within hundreds of milliseconds. Control of artificial manipulators, ranging from prosthetic hands to bomb defusal robots, requires a constant reliance on visual feedback that is not entirely practical. To address this, we conducted three studies aimed at advancing artificial haptic intelligence. First, we developed a novel, robust, microfluidic tactile sensor skin capable of measuring normal forces on flat or curved surfaces, such as a fingertip. The sensor consists of microchannels in an elastomer filled with a liquid metal alloy. The fluid serves as both electrical interconnects and tunable capacitive sensing units, and enables functionality despite substantial deformation. The second study investigated the use of a commercially-available, multimodal tactile sensor (BioTac sensor, SynTouch) to characterize edge orientation with respect to a body fixed reference frame, such as a fingertip. Trained on data from a robot testbed, a support vector regression model was developed to relate haptic exploration actions to perception of edge orientation. The model performed comparably to humans for estimating edge orientation. Finally, the robot testbed was used to perceive small, finger-sized geometric features. The efficiency and accuracy of different haptic exploratory procedures and supervised learning models were assessed for estimating feature properties such as type (bump, pit), order of curvature (flat, conical, spherical), and size. This study highlights the importance of tactile sensing in situations where other modalities fail, such as when the finger itself blocks line of sight. Insights from this work could be used to advance tactile sensor technology and haptic intelligence for artificial manipulators that improve quality of life, such as prosthetic hands and wheelchair-mounted robotic hands.
ContributorsPonce Wong, Ruben Dario (Author) / Santos, Veronica J (Thesis advisor) / Artemiadis, Panagiotis K (Committee member) / Helms Tillery, Stephen I (Committee member) / Posner, Jonathan D (Committee member) / Runger, George C. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Portable devices rely on battery systems that contribute largely to the overall device form factor and delay portability due to recharging. Membraneless microfluidic fuel cells are considered as the next generation of portable power sources for their compatibility with higher energy density reactants. Microfluidic fuel cells are potentially cost effective and robust because they use low Reynolds number flow to maintain fuel and oxidant separation instead of ion exchange membranes. However, membraneless fuel cells suffer from poor efficiency due to poor mass transport and Ohmic losses. Current microfluidic fuel cell designs suffer from reactant cross-diffusion and thick boundary layers at the electrode surfaces, which result in a compromise between the cell's power output and fuel utilization. This dissertation presents novel flow field architectures aimed at alleviating the mass transport limitations. The first architecture provides a reactant interface where the reactant diffusive concentration gradients are aligned with the bulk flow, mitigating reactant mixing through diffusion and thus crossover. This cell also uses porous electro-catalysts to improve electrode mass transport which results in higher extraction of reactant energy. The second architecture uses porous electrodes and an inert conductive electrolyte stream between the reactants to enhance the interfacial electrical conductivity and maintain complete reactant separation. This design is stacked hydrodynamically and electrically, analogous to membrane based systems, providing increased reactant utilization and power. These fuel cell architectures decouple the fuel cell's power output from its fuel utilization. The fuel cells are tested over a wide range of conditions including variation of the loads, reactant concentrations, background electrolytes, flow rates, and fuel cell geometries. These experiments show that increasing the fuel cell power output is accomplished by increasing reactant flow rates, electrolyte conductivity, and ionic exchange areas, and by decreasing the spacing between the electrodes. The experimental and theoretical observations presented in this dissertation will aid in the future design and commercialization of a new portable power source, which has the desired attributes of high power output per weight and volume and instant rechargeability.
ContributorsSalloum, Kamil S (Author) / Posner, Jonathan D (Thesis advisor) / Adrian, Ronald (Committee member) / Christen, Jennifer (Committee member) / Phelan, Patrick (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2010
Description
In nature, it is commonly observed that animals and birds perform movement-based thermoregulation activities to regulate their body temperatures. For example, flapping of elephant ears or plumage fluffing in birds. Taking inspiration from nature and to explore the possibilities of such heat transfer enhancements, augmentation of heat transfer rates induced by the vibration of solid and well as novel flexible pinned heatsinks were studied in this research project. Enhancement of natural convection has always been very important in improving the performance of the cooling mechanisms. In this research, flexible heatsinks were developed and they were characterized based on natural convection cooling with moderately vibrating conditions. The vibration of heated surfaces such as motor surfaces, condenser surfaces, robotic arms and exoskeletons led to the motivation of the development of heat sinks having flexible fins with an improved heat transfer capacity. The performance of an inflexible, solid copper pin fin heat sink was considered as the baseline, current industry standard for the thermal performance. It is expected to obtain maximum convective heat transfer at the resonance frequency of the flexible pin fins. Current experimental results with fixed input frequency and varying amplitudes indicate that the vibration provides a moderate improvement in convective heat transfer, however, the flexibility of fins had negligible effects.
ContributorsPrabhu, Saurabh (Author) / Rykaczewski, Konrad (Thesis advisor) / Phelan, Patrick (Committee member) / Wang, Robert (Committee member) / Arizona State University (Publisher)
Created2019
Description
In convective heat transfer processes, heat transfer rate increases generally with a large fluid velocity, which leads to complex flow patterns. However, numerically analyzing the complex transport process and conjugated heat transfer requires extensive time and computing resources. Recently, data-driven approach has risen as an alternative method to solve physical problems in a computational efficient manner without necessitating the iterative computations of the governing physical equations. However, the research on data-driven approach for convective heat transfer is still in nascent stage. This study aims to introduce data-driven approaches for modeling heat and mass convection phenomena. As the first step, this research explores a deep learning approach for modeling the internal forced convection heat transfer problems. Conditional generative adversarial networks (cGAN) are trained to predict the solution based on a graphical input describing fluid channel geometries and initial flow conditions. A trained cGAN model rapidly approximates the flow temperature, Nusselt number (Nu) and friction factor (f) of a flow in a heated channel over Reynolds number (Re) ranging from 100 to 27750. The optimized cGAN model exhibited an accuracy up to 97.6% when predicting the local distributions of Nu and f. Next, this research introduces a deep learning based surrogate model for three-dimensional (3D) transient mixed convention in a horizontal channel with a heated bottom surface. Conditional generative adversarial networks (cGAN) are trained to approximate the temperature maps at arbitrary channel locations and time steps. The model is developed for a mixed convection occurring at the Re of 100, Rayleigh number of 3.9E6, and Richardson number of 88.8. The cGAN with the PatchGAN based classifier without the strided convolutions infers the temperature map with the best clarity and accuracy.
Finally, this study investigates how machine learning analyzes the mass transfer in 3D printed fluidic devices. Random forests algorithm is hired to classify the flow images taken from semi-transparent 3D printed tubes. Particularly, this work focuses on laminar-turbulent transition process occurring in a 3D wavy tube and a straight tube visualized by dye injection. The machine learning model automatically classifies experimentally obtained flow images with an accuracy > 0.95.
ContributorsKang, Munku (Author) / Kwon, Beomjin (Thesis advisor) / Phelan, Patrick (Committee member) / Ren, Yi (Committee member) / Rykaczewski, Konrad (Committee member) / Sohn, SungMin (Committee member) / Arizona State University (Publisher)
Created2022
Description
The thermal conductivity of cadmium sulfide (CdS) colloidal nanocrystals (NCs) and magic-sized clusters (MSCs) have been investigated in this work. It is well documented in the literature that the thermal conductivity of colloidal nanocrystal assemblies decreases as diameter decreases. However, the extrapolation of this size dependence does not apply to magic-sized clusters. Magic-sized clusters have an anomalously high thermal conductivity relative to the extrapolated size-dependence trend line for the colloidal nanocrystals. This anomalously high thermal conductivity could probably result from the monodispersity of magic-sized clusters. To support this conjecture, a method of deliberately eliminating the monodispersity of MSCs by mixing them with colloidal nanocrystals was performed. Experiment results showed that mixtures of nanocrystals and MSCs have a lower thermal conductivity that falls approximately on the extrapolated trendline for colloidal nanocrystal thermal conductivity as a function of size.
ContributorsSun, Ming-Hsien (Author) / Wang, Robert (Thesis advisor) / Rykaczewski, Konrad (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2022
Description
Windows are one of the most significant locations of heat transfer through a building envelope. In warm climates, it is important that heat gain through windows is minimized. Heat transfer through a window glazing occurs by all major forms of heat transfer (convection, conduction, and radiation). Convection and conduction effects can be limited by manipulating the thermal properties of a window’s construction. However, radiation heat transfer into a building will always occur if a window glazing is visibly transparent. In an effort to reduce heat gain through the building envelope, a window glazing can be designed with spectrally selective properties. These spectrally selective glazings would possess high reflectivity in the near-infrared (NIR) regime (to prevent solar heat gain) and high emissivity in the atmospheric window, 8-13μm (to take advantage of the radiative sky cooling effect). The objective of this thesis is to provide a comprehensive study of the thermal performance of a visibly transparent, high-emissivity glass window. This research proposes a window constructed by coating soda lime glass in a dual layer consisting of Indium Tin Oxide (ITO) and Polyvinyl Fluoride (PVF) film. The optical properties of this experimental glazing were measured and demonstrated high reflectivity in the NIR regime and high emissivity in the atmospheric window. Outdoor field tests were performed to experimentally evaluate the glazing’s thermal performance. The thermal performance was assessed by utilizing an experimental setup intended to mimic a building with a skylight. The proposed glazing experimentally demonstrated reduced indoor air temperatures compared to bare glass, ITO coated glass, and PVF coated glass. A theoretical heat transfer model was developed to validate the experimental results. The results of the theoretical and experimental models showed good agreement. On average, the theoretical model demonstrated 0.44% percent error during the daytime and 0.52% percent error during the nighttime when compared to the experimentally measured temperature values.
ContributorsTrujillo, Antonio Jose (Author) / Phelan, Patrick (Thesis advisor) / Wang, Liping (Thesis advisor) / Rykaczewski, Konrad (Committee member) / Arizona State University (Publisher)
Created2022
Description
Dehumidifiers are ubiquitous and essential household appliances in many parts of the world. They are used extensively in tropical and sub-tropical environments to lower humidity in living spaces, where high ambient humidity can lead to numerous negative health effects from mild physical discomfort to more serious conditions such as mold build up in structures and dangerous illnesses in humans. Most common dehumidifiers are based on conventional mechanical refrigeration cycles, where the effects of condensation heat transfer play a critical role in their effectiveness. In these devices, humid ambient air flows over a cold evaporator, which lowers the temperature of the humid ambient air below its dew point temperature and therefore decreases its water content by causing liquid water condensation on the evaporator surface. The rate at which humidity can be extracted from the ambient air is governed in part by how quickly the evaporator can shed the condensed droplets. Recent advances in soft, stretchable, thermally enhanced (through the addition of liquid metals) silicone tubing offer the potential to use these stretchable tubes in place of conventional copper pipe for applications such as dehumidification. Copper is a common material choice for dehumidifier evaporator tubing owing to its ubiquity and its high thermal conductivity, but it has several thermal downsides. Specifically, copper tubes remain static and typically rely on gravity alone to remove water droplets when they reach a sufficient mass. Additionally, copper’s naturally hydrophilic surface promotes film-wise condensation, which is substantially less effective than dropwise condensation. In contrast to copper, thermally enhanced soft stretchable tubes have naturally hydrophobic surfaces that promote the more effective dropwise condensation mode and a soft surface that offers higher nucleation density. However, soft surfaces also increase droplet pinning, which inhibits their departure. This work experimentally explores the effects of periodic axial stretching and retraction of soft tubing internally cooled with water on droplet condensation dynamics on its exterior surface. Results are discussed in terms of overall system thermal performance and real-time condensation imaging. An overall null result is discovered, and recommendations for future experiments are made.
Contributorsnordstog, thomas (Author) / Rykaczewski, Konrad (Thesis advisor) / Wang, Robert (Committee member) / Devasenathipathy, Shankar (Committee member) / Arizona State University (Publisher)
Created2022