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- All Subjects: Mechanical Engineering
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- Creators: Rykaczewski, Konrad
Description
This thesis evaluates the viability of an original design for a cost-effective wheel-mounted dynamometer for road vehicles. The goal is to show whether or not a device that generates torque and horsepower curves by processing accelerometer data collected at the edge of a wheel can yield results that are comparable to results obtained using a conventional chassis dynamometer. Torque curves were generated via the experimental method under a variety of circumstances and also obtained professionally by a precision engine testing company. Metrics were created to measure the precision of the experimental device's ability to consistently generate torque curves and also to compare the similarity of these curves to the professionally obtained torque curves. The results revealed that although the test device does not quite provide the same level of precision as the professional chassis dynamometer, it does create torque curves that closely resemble the chassis dynamometer torque curves and exhibit a consistency between trials comparable to the professional results, even on rough road surfaces. The results suggest that the test device provides enough accuracy and precision to satisfy the needs of most consumers interested in measuring their vehicle's engine performance but probably lacks the level of accuracy and precision needed to appeal to professionals.
ContributorsKing, Michael (Author) / Ren, Yi (Thesis director) / Spanias, Andreas (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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
With the substantial development of intelligent robots, human-robot interaction (HRI) has become ubiquitous in applications such as collaborative manufacturing, surgical robotic operations, and autonomous driving. In all these applications, a human behavior model, which can provide predictions of human actions, is a helpful reference that helps robots to achieve intelligent interaction with humans. The requirement elicits an essential problem of how to properly model human behavior, especially when individuals are interacting or cooperating with each other. The major objective of this thesis is to utilize the human intention decoding method to help robots enhance their performance while interacting with humans. Preliminary work on integrating human intention estimation with an HRI scenario is shown to demonstrate the benefit. In order to achieve this goal, the research topic is divided into three phases. First, a novel method of an online measure of the human's reliance on the robot, which can be estimated through the intention decoding process from human actions，is described. An experiment that requires human participants to complete an object-moving task with a robot manipulator was conducted under different conditions of distractions. A relationship is discovered between human intention and trust while participants performed a familiar task with no distraction. This finding suggests a relationship between the psychological construct of trust and joint physical coordination, which bridges the human's action to its mental states. Then, a novel human collaborative dynamic model is introduced based on game theory and bounded rationality, which is a novel method to describe human dyadic behavior with the aforementioned theories. The mutual intention decoding process was also considered to inform this model. Through this model, the connection between the mental states of the individuals to their cooperative actions is indicated. A haptic interface is developed with a virtual environment and the experiments are conducted with 30 human subjects. The result suggests the existence of mutual intention decoding during the human dyadic cooperative behaviors. Last, the empirical results show that allowing agents to have empathy in inference, which lets the agents understand that others might have a false understanding of their intentions, can help to achieve correct intention inference. It has been verified that knowledge about vehicle dynamics was also important to correctly infer intentions. A new courteous policy is proposed that bounded the courteous motion using its inferred set of equilibrium motions. A simulation, which is set to reproduce an intersection passing case between an autonomous car and a human driving car, is conducted to demonstrate the benefit of the novel courteous control policy.
ContributorsWang, Yiwei (Author) / Zhang, Wenlong (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Ren, Yi (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2021
Description
In the development of autonomous ground vehicles (AGVs), how to guarantee vehicle lateral stability is one of the most critical aspects. Based on nonlinear vehicle lateral and tire dynamics, new driving requirements of AGVs demand further studies and analyses of vehicle lateral stability control strategies. To achieve comprehensive analyses and stability-guaranteed vehicle lateral driving control, this dissertation presents three main contributions.First, a new method is proposed to estimate and analyze vehicle lateral driving stability regions, which provide a direct and intuitive demonstration for stability control of AGVs. Based on a four-wheel vehicle model and a nonlinear 2D analytical LuGre tire model, a local linearization method is applied to estimate vehicle lateral driving stability regions by analyzing vehicle local stability at each operation point on a phase plane. The obtained stability regions are conservative because both vehicle and tire stability are simultaneously considered. Such a conservative feature is specifically important for characterizing the stability properties of AGVs.
Second, to analyze vehicle stability, two novel features of the estimated vehicle lateral driving stability regions are studied. First, a shifting vector is formulated to explicitly describe the shifting feature of the lateral stability regions with respect to the vehicle steering angles. Second, dynamic margins of the stability regions are formulated and applied to avoid the penetration of vehicle state trajectory with respect to the region boundaries. With these two features, the shiftable stability regions are feasible for real-time stability analysis.
Third, to keep the vehicle states (lateral velocity and yaw rate) always stay in the shiftable stability regions, different control methods are developed and evaluated. Based on different vehicle control configurations, two dynamic sliding mode controllers (SMC) are designed. To better control vehicle stability without suffering chattering issues in SMC, a non-overshooting model predictive control is proposed and applied. To further save computational burden for real-time implementation, time-varying control-dependent invariant sets and time-varying control-dependent barrier functions are proposed and adopted in a stability-guaranteed vehicle control problem.
Finally, to validate the correctness and effectiveness of the proposed theories, definitions, and control methods, illustrative simulations and experimental results are presented and discussed.
ContributorsHuang, Yiwen (Author) / Chen, Yan (Thesis advisor) / Lee, Hyunglae (Committee member) / Ren, Yi (Committee member) / Yong, Sze Zheng (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2021
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
Autonomous systems inevitably must interact with other surrounding systems; thus, algorithms for intention/behavior estimation are of great interest. This thesis dissertation focuses on developing passive and active model discrimination algorithms (PMD and AMD) with applications to set-valued intention identification and fault detection for uncertain/bounded-error dynamical systems. PMD uses the obtained input-output data to invalidate the models, while AMD designs an auxiliary input to assist the discrimination process. First, PMD algorithms are proposed for noisy switched nonlinear systems constrained by metric/signal temporal logic specifications, including systems with lossy data modeled by (m,k)-firm constraints. Specifically, optimization-based algorithms are introduced for analyzing the detectability/distinguishability of models and for ruling out models that are inconsistent with observations at run time. On the other hand, two AMD approaches are designed for noisy switched nonlinear models and piecewise affine inclusion models, which involve bilevel optimization with integer variables/constraints in the inner/lower level. The first approach solves the inner problem using mixed-integer parametric optimization, whose solution is included when solving the outer problem/higher level, while the second approach moves the integer variables/constraints to the outer problem in a manner that retains feasibility and recasts the problem as a tractable mixed-integer linear programming (MILP). Furthermore, AMD algorithms are proposed for noisy discrete-time affine time-invariant systems constrained by disjunctive and coupled safety constraints. To overcome the issues associated with generalized semi-infinite constraints due to state-dependent input constraints and disjunctive safety constraints, several constraint reformulations are proposed to recast the AMD problems as tractable MILPs. Finally, partition-based AMD approaches are proposed for noisy discrete-time affine time-invariant models with model-independent parameters and output measurement that are revealed at run time. Specifically, algorithms with fixed and adaptive partitions are proposed, where the latter improves on the performance of the former by allowing the partitions to be optimized. By partitioning the operation region, the problem is solved offline, and partition trees are constructed which can be used as a `look-up table' to determine the optimal input depending on revealed information at run time.
ContributorsNiu, Ruochen (Author) / Yong, Sze Zheng S.Z. (Thesis advisor) / Berman, Spring (Committee member) / Ren, Yi (Committee member) / Zhang, Wenlong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2022
Description
Recent advancements in the field of light wavefront engineering rely on complex 3D metasurfaces composed of sub-wavelength structures which, for the near infrared range, are challenging to manufacture using contemporary scalable micro- and nanomachining solutions. To address this demand, a novel parallel micromachining method, called metal-assisted electrochemical nanoimprinting (Mac-Imprint) was developed. Mac-Imprint relies on the catalysis of silicon wet etching by a gold-coated stamp enabled by mass-transport of the reactants to achieve high pattern transfer fidelity. This was realized by (i) using nanoporous catalysts to promote etching solution diffusion and (ii) semiconductor substrate pre-patterning with millimeter-scale pillars to provide etching solution storage. However, both of these approaches obstruct scaling of the process in terms of (i) surface roughness and resolution, and (ii) areal footprint of the fabricated structures. To address the first limitation, this dissertation explores fundamental mechanisms underlying the resolution limit of Mac-Imprint and correlates it to the Debye length (~0.9 nm). By synthesizing nanoporous catalytic stamps with pore size less than 10 nm, the sidewall roughness of Mac-Imprinted patterns is reduced to levels comparable to plasma-based micromachining. This improvement allows for the implementation of Mac-Imprint to fabricate Si rib waveguides with limited levels of light scattering on its sidewall. To address the second limitation, this dissertation focuses on the management of the etching solution storage by developing engineered stamps composed of highly porous polymers coated in gold. In a plate-to-plate configuration, such stamps allow for the uniform patterning of chip-scale Si substrates with hierarchical 3D antireflective and antifouling patterns. The development of a Mac-Imprint system capable of conformal patterning onto non-flat substrates becomes possible due to the flexible and stretchable nature of gold-coated porous polymer stamps. Understanding of their mechanical behavior during conformal contact allows for the first implementation of Mac-Imprint to directly micromachine 3D hierarchical patterns onto plano-convex Si lenses, paving the way towards scalable fabrication of multifunctional 3D metasurfaces for applications in advanced optics.
ContributorsSharstniou, Aliaksandr (Author) / Azeredo, Bruno (Thesis advisor) / Chan, Candace (Committee member) / Rykaczewski, Konrad (Committee member) / Petuskey, William (Committee member) / Chen, Xiangfan (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