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Palmer, Benjamin CliveSensitization Effects on Environmentally Enhanced Cracking of 5XXX Series Alloys: Macro and Mesoscale Observations
Master of Sciences (Engineering), Case Western Reserve University, 2017, Materials Science and Engineering
The focus of this study was on the tensile behavior and damage development in 5083- H131 Al-Mg alloy sensitized to different levels. Samples were tested in the as-received state, after sensitization at 175°C for 100hrs, or 80°C for >500hrs. Tensile testing was conducted under moderate (50%RH) or low (<1%RH) humidity environments to determine the environmental effects on the mechanical behavior of the material. Three different deformation/fracture modes were present depending on the sensitization level and testing environment. Interrupted tensile tests and microscopy revealed that strain was more heterogeneously distributed in the highly sensitized specimens compared to the as-received ones. Differential scanning calorimetry was also performed as a means of determining the degree of sensitization of specimens thermally exposed at temperatures from 60-175°C. This technique was able to detect the presence of Mg-rich phase(s) at thermal exposures as low as 60°C, though it has quantitative limits due to the resolution limit.

Committee:

John Lewandowski, Dr. (Advisor); David Schwam, Dr. (Committee Member); Clare Rimnac, Dr. (Committee Member)

Subjects:

Materials Science; Mechanical Engineering

Keywords:

Environment-enhanced-cracking; Stress corrosion cracking; 3-D tomography; Aluminum-magnesium alloys; Differential scanning calorimetry

Letcher, RyanSmartHub: A Low Cost Manual Wheelchair Fitness Metrics Tool for Clinicians, Researchers, and Wheelchair Users
Master of Science, The Ohio State University, 2017, Mechanical Engineering
Approximately 73% of manual wheelchair (MWC) users report upper extremity (UE) injuries and pain in their lifetime due to the repetitive trauma that occurs during the stroke cycle, which reduces their quality of life. Optimizing stroke frequency and force requirements for propelling the wheelchair are primary approaches used by clinicians to reduce the risk of UE injuries. Currently, clinicians use a standard measurement tool called the SmartWheel, which is both expensive and limited in its use and range of application, for testing of the stroke cycle of a MWC user. The purpose of this research is to create a low cost device that monitors MWC fitness metrics, including stroke frequency and push force, to allow clinicians to assist the user in the prevention of force related injuries, to assist researchers in the modeling of the joint torques in the user’s UEs, and to allow wheelchair users to personally track their own fitness level on a daily basis. The device, called the SmartHub, attaches to the wheel of a MWC and continuously collects angular velocity data during a clinical trial. This data is then post-processed using MATLAB, which outputs the following metrics: distance, velocity, total time, number of strokes, stroke frequency, stroke length, and tangential stroke force. These metrics are utilized by a clinician to assist them in adjusting the settings of a user’s wheelchair, adjusting the user’s seated position, or in training a user on how to optimize their stroke cycle. A head-to-head comparison of the SmartHub and the SmartWheel was performed to validate the metrics calculated by the SmartHub. Certain outputs of the SmartHub were found to have error on the order of less than 1.5% when compared to the SmartWheel. A planned application for the SmartHub technology is the generation of real-world data that will be utilized in a recently developed OpenSim biomechanical model of a MWC user in order to calculate the shoulder joint torques through application of inverse dynamics.

Committee:

Sandra Metzler (Advisor); Carmen DiGiovine (Committee Member)

Subjects:

Biomechanics; Mechanical Engineering

Keywords:

Smarthub manual wheelchair fitness metrics tool; SmartWheel standard measurement tool; Manual wheelchair users;

Guo, QiA Framework for Optimal Decision Making of a Photovoltaic Recycling Infrastructure Planning
Doctor of Philosophy (Ph.D.), University of Dayton, 2017, Mechanical Engineering
Solar energy, as an emerging renewable clean energy, has been rapidly growing for 15 years all over the world and is expected to grow 15% annually until 2020. In 2015, at least 40 GW of Photovoltaic (PV) systems were installed, achieving 178GW current solar power installation worldwide. In the next five years, 540 GW cumulative capacities are expected to be installed worldwide and US contributed 6.5 GW PV installations in 2015. US electricity demand is expected to be dominated by solar power by 2050 or even earlier. The widespread deployment of PV will not only contribute to a reduction in greenhouse gas emission, but can also mitigate the worldwide fossil fuel depletion. As the number of PV systems increases, the mass of PV waste will increase as well, adding a new source to the existing waste stream. The amount of End-of-Life (EoL) PV will approach 13.4 million ton worldwide, including approximately 5.5 million ton located in the US by 2025. PV contains high value, toxic, and energy-intensive materials. In addition, the market price of some materials utilized in the thin-film and crystalline PV technologies has drastically increased in the recent years. There is a strong need of coordinating the information to optimize the reverse logistics planning in a photovoltaic (PV) recycling network in the U.S. Two major tasks are included: 1) locating PV Recycling Centers (PVRC); 2) allocating Transportation Companies (TC) shipping PV installation sites (PVIS) to PVRC. One contribution of this dissertation is to decide the optimal number, as well as the location of PVRC by minimizing the overall cost. Another contribution is to determine the optimal distribution scheme to minimize the transportation cost among TC, PVIS, and PVRC. In order to accomplish the two tasks, a mathematical modeling framework was developed to facilitate PV recycling in an economically and environmentally feasible manner. The framework included two mathematical models: 1) Multi-Facility Optimization Model; 2) Optimal Distribution Model. The multi-facility optimization model included the transportation module, the economic module, and the environmental module. The model identifies the geographical location of the prospective PVRCs by minimizing the total costs in different scenarios. While in the Optimal Distribution Model, a static and a dynamic optimization algorithm was applied for conducting the optimal solution accurately and efficiently. To show the efficacy of the proposed framework, case studies for recycling EoL PV in California were performed. Historical PV installation data in the region was utilized to gather information about the amount of the prospective end-of-life (EoL) PV waste generation in CA. In order to integrate the temporal and the spatial dispersion of PVISs in CA, a three-phase recycling plan was proposed. For well displaying the geographical results, Geographic Information System (GIS) was utilized to visualize the installation data, optimized location of the PVRCs, and the optimal distribution scheme. The proposed generic framework provided a great insight for decision makers about the trade-offs among various scenarios by considering cost, environmental impact, and investment risk on PV recycling planning.

Committee:

Jun-Ki Choi (Advisor); Chuck Ebeling (Committee Member); Ron Deep (Committee Member); Shuang-ye Wu (Committee Member)

Subjects:

Energy; Mechanical Engineering

Keywords:

PV recycling, Optimization, End-of-Life recycling framework

Hutten, Victoria ElizabethProcess Modeling of Thermoplastics and Thermosetting Polymer Matrix Composites (PMCs) Manufactured Using Fused Deposition Modeling (FDM)
Master of Science (M.S.), University of Dayton, 2017, Mechanical Engineering
In this work, a model framework for the simulation of Fused Deposition Modeling (FDM) of thermoplastic and thermosetting polymers and Polymer Matrix Composites (PMCs) was developed. A Python script was constructed to automatically generate a 3D finite element heat transfer and stress model of individual roads within a 3D printed part. The script creates the road activation sequence based on the print path specified in the part G-code and associated boundary conditions which are continuously updated throughout the analysis with minimal input from the user. Thermosetting polymers and polymer matrix composites (PMCs) are modeled by implementing a material sub-model from Convergent Manufacturing Technologies called COMPRO that captures the curing kinetics of the material during the printing and post-cure cycle. The modeling approach is formulated for both material systems through tailorable conditions such as build plate temperature, ambient conditions, print temperature, etc. To the author’s knowledge, no 3D finite element model of the FDM process exists for the thermal history and residual stress prediction of thermosetting polymers and PMCs. Although the objective of this work is to create a model for the prediction of thermosetting polymers and PMCs, the characterization and subsequent printing of these materials is still in the development stages. Therefore, in order to validate that the proposed model is capturing the correct physics for the FDM process, model predictions for Acrylonitrile Butadiene Styrene (ABS) coupons were compared with experimentally printed specimens. A series of sensitivity studies were then performed for this model to investigate significant effects as well as trends in the predictions from assumptions in the boundary conditions. The model is then extended to thermosetting PMCs to demonstrate the linkage between COMPRO and the modeling framework.

Committee:

Robert Brockman, PhD (Committee Chair); Brent Volk, PhD (Committee Member); Thomas Whitney, PhD (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

finite element analysis; process modeling; fused deposition modeling; polymer matrix composites; thermosetting polymers

Bafakeeh, Omar TMicro/Nano Surface Finish Single Side Electrolytic In-Process Dressing (ELID) Grinding with Lapping Kinematics of Sapphire
Doctor of Philosophy, University of Toledo, 2017, Industrial Engineering
The demand for Sapphire ( a-AL2 O3 ) has increased significantly, due to its excellent reliable properties. Sapphire, known for its high hardness and brittleness, has excellent optic, mechanical, and physical properties. Sapphire is used in many different applications such as aerospace, optics, electronics, and in other industries. Machining of sapphire is challenging due to its high hardness and brittleness. The manufacturing of such material is very expensive because the tool wear is very high and longtime machining. Single side grinding is sometimes preferable over conventional grinding because of the ability to provide flat surfaces for ceramic materials. The use of electrolytic in-process dressing (ELID) helps reduce machining time. The use of the kinematics of lapping with the ELID will help reduce machining time in addition to eliminating the use of lapping and polishing. This current study examines five parameters with three levels each. A full factorial design, for both roughness (Ra) and material removal rate (MRR) are be conducted to present mathematical models which predict future results. Three grinding wheels with different mesh sizes are be used. The influence of the grain size on the result will be investigated. The kinematics of the process will be investigated based on the effect of different eccentricities. The parameters used in this study are; different wheel mesh sizes, different pressures, different eccentricities, different spindle speed, and different wheel speed ratios; each of these parameters are in three levels.

Committee:

Ioan Marinescu (Committee Chair); Abdollah Afjeh (Committee Member); Mansoor Alam (Committee Member); Sarit Bhaduri (Committee Member); Matthew Franchetti (Committee Member)

Subjects:

Industrial Engineering; Mechanical Engineering

Keywords:

ELID, Single Side Grinding, Fine Grinding, Sapphire

Riyad, M Faisal Simultaneous analysis of Lattice Expansion and Thermal Conductivity in Defected Oxide Ceramics
Master of Science, The Ohio State University, 2017, Mechanical Engineering
Objective of this thesis is to investigate the impact of point defects on thermal conductivity and lattice expansion in uranium dioxide ceramic. Specific emphasize is on light ion irradiation induced point defects which causes the degradation of thermal conductivity of oxide ceramics. Radiation induced defects include vacancies and interstitials hosted by the anion and cation sub lattice of the structure. A crystallographic structure is assumed for each defect and is used to model defect impact on lattice parameter. In ceramic materials, thermal conductivity is governed by phonon modes determined by crystalline structure. The irradiation induced point defects limit thermal transport by acting as phonon scattering centers. The point defects scattering originates from both the mass and ionic radius mismatch between the impurity atom and the host lattice. We present a model to estimate the phonon scattering parameter for different types of point defects and implement it in classical phonon mediated thermal transport model to estimate the thermal conductivity reduction in light ion irradiated UO2. The results are compared to results of experimental measurements. Laser based modulated thermoreflectance (MTR) technique was used to measure the thermal conductivity model in ion irradiated UO2 samples. Unlike laser flash analysis, traditionally used for measuring thermal conductivity in nuclear materials, MTR method has a sensitivity to a few micron thick thin damage resulting from ion beam irradiation. In this technique, the irradiated sample, coated by a thin metallic film, is heated by a harmonically modulated laser pump and a probe beam measures the temperature induced changes in reflectivity. In this work, experimentally measured thermal wave phase profiles obtained from UO2 samples irradiated with 2.6 MeV H+ ions were analyzed using different multilayer approximations of the damaged region. An infinite damage layer approximation model that neglects undamaged layer and peak damage region characteristic to light ion irradiations is discussed. The limitation of the approach and demonstration of its applicability range was analyzed. Finally, measured conductivities of the ion irradiated samples using a thermal conductivity model for point defects was examined. Previously reported XRD measurements on same proton irradiated UO2 samples show the lattice expands linearly as a function of atomic displacements (dpa). The defect concentration can be defined as a function of dpa and the defect production rate. The estimation of defect concentration is validated by accounting their overall contribution to the change in lattice parameters and comparing them with the measured values by XRD. Finally, their overall contribution to the reduction in thermal conductivity is compared with the experimentally measured values to determine the concentration of defects in the lattice structure of UO2.

Committee:

Marat Khafizov, Dr. (Advisor); Sandip Mazumder, Dr. (Committee Member)

Subjects:

Materials Science; Mechanical Engineering; Nuclear Engineering; Nuclear Physics

Keywords:

Lattice Expansion; Thermal Conductivity; Defected Oxide Ceramics

Nasrin, SadiaFailure mechanism and lifetime prediction of monolithic restorations
Doctor of Philosophy, The Ohio State University, 2017, Mechanical Engineering
In this work, first, a 3D failure prognosis methodology was developed for interface initiated failures of monolithic ceramic crowns, combining experimentally determined fast fracture parameters and finite element multi-axial stress analysis on the basis of fracture mechanics based failure probability model. The complete 3D restoration model was developed using commercially available hardware and software. The proposed method was verified by prior 2D axisymmetric restoration model and experimental data of failure probability of flat onlay specimen with borosilicate glass. A detailed analysis of the stress state (flexural stress, interfacial shear stress and interfacial normal tensile stress) at the ceramic/cement interface was conducted and the impact of reduced cement modulus on these stress states was also analyzed to simulate bond degradation. Second, by introducing ceramic fatigue in this method, we develop interface-initiated fatigue failure model of monolithic ceramic crowns under simulated masticatory loading. For this purpose, four representative ceramic materials, fluromica (FM), leucite (LR), yttrium-stabilized zirconia (YZ) and lithium disilicate (LD) where material parameters (fast fracture parameters and fatigue parameters) were available in the existing literature were chosen. Fast fracture parameters were converted to multi-axial stress state parameters and fatigue parameters were converted to power-law-based parameters based on existing conversion methods. Crown survival probabilities as a function of loading cycles were obtained from simulations performed on the four ceramic materials utilizing identical crown geometries and loading conditions. Additionally, for two of the model crown systems (FM and LD), region dependent failure probabilities were determined and compared against fractographic analyses of failed crowns available in dental literature. Third, an approximate but simple relative fatigue life estimation method was established. Careful examination of experimentally measured/converted fatigue parameters of materials (FM, LR, LD and YZ) in the existing literature lead to the finding that, ceramic fatigue relating the maximum cyclic stress and stress corresponding to initial crack size prior to N number of cycled fatigue were somewhat similar. This finding was valid for clinically relevant loading range and mastication frequency. Based on this, an approximate fatigue equation universally applicable to all dental ceramic materials was developed. Utilizing the developed universal fatigue equation, an approximate relative fatigue life estimation method was established considering failures from only high stress region in ceramic/cement interface.

Committee:

noriko katsube (Advisor); robert seghi (Committee Member); stainslav rokhlin (Committee Member); carlos castro (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

3D failure prognosis methodology; monolithic ceramic crowns; prediction of monolithic restorations

Sangle, Sagar DilipDesign and Testing of Scalable 3D-Printed Cellular Structures Optimized for Energy Absorption
Master of Science in Mechanical Engineering (MSME), Wright State University, 2017, Mechanical Engineering
Sandwich panel structures are widely used due to their high compressive and flexural stiffness and strength-to-weight ratios, good vibration damping, and low through-thickness thermal conductivity. These structures consist of solid face sheets and low-density cellular core structures that are often based upon honeycomb topologies. Interest in additive manufacturing (AM), popularly known as 3D printing (3DP), has rapidly grown in past few years. The 3DP method is a layer-by-layer approach for the fabrication of 3D objects. Hence, it is very easy to fabricate complex structures with complex internal features that cannot be manufactured by any other fabrication processes. Due to the recent advancement of 3DP processes, the core lattice configurations can be redesigned to improve certain properties such as specific energy absorption capabilities. This thesis investigates the load-displacement behavior of 3D printable lattice core structures of five different configurations and rank them according to their specific energy absorption under quasi-static loads. The five different configurations are body centered cubic (bcc) diamonds without vertical struts; bcc diamonds with vertical alternate struts, tetras, tetrahedrons, and pyramids. First, both elastic and elastic-plastic finite element analysis (FEA) approach was used to find optimum cell dimension for each configuration. Cell size and strut diameter were varied for each configuration, the energy absorption during compression were calculated, and the optimum dimension was identified for each configuration. Next, the optimized designs were printed using acrylonitrile butadiene styrene (ABS) polymer to evaluate their compression behavior. Fused deposition modeling based Stratasys uPrint printer was used for printing the samples. After printing the samples, all five designs of lattice structures were subjected to compression load and their load-displacement behavior were analyzed and compared. From both FEA calculations and experimental results, the five configurations can be placed as tetrahedrons, pyramids, tetras, BCC diamonds with struts, and diamonds without struts, the first one having the highest and the last one having the lowest energy absorption capabilities. A detailed discussion on the FEA modeling, sample fabrication, and testing of different configurations is presented in the thesis report.

Committee:

Raghavan Srinivasan, Ph.D. (Committee Co-Chair); Ahsan Mian, Ph.D. (Committee Co-Chair); Joy Gockel, Ph.D. (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

Lattice structures; energy absorption; 3D printing; additive manufacturing; compression testing; finite element analysis

Lee, Kuan-LinDevelopment of a Compact Thermal Management System Utilizing an Integral Variable Conductance Planar Heat Pipe Radiator for Space Applications
Doctor of Philosophy, Case Western Reserve University, 2017, EMC - Mechanical Engineering
In the present research an innovative space thermal management system is developed utilizing an integral planar variable conductance heat pipe (VCPHP) radiator, which can function reliably over a wide range of environmental conditions. The condenser (or radiator) of this planar shaped heat pipe is self-adjustable, and the evaporator temperature can be stabilized within a tolerable range even when the sink temperature changes significantly. This research includes the design, fabrication and test of four prototype planar heat pipe radiators, which are made with a metallic material and a thermally conductive polymer. The corresponding thermal performance of prototype VCPHPs were measured and analyzed through a benchtop heat pipe-based heat rejection system. To further support the concept, a multi-scale, steady-state heat pipe operation model (SSHPOM), which is able to capture both the thermal and hydrodynamic characteristics of the developed VCPHP radiator was developed. The mathematical model combines a theoretical thin-film evaporation model, a NCG expansion model and 2D steady-state heat transfer analysis. After validation, a feasibility of a large scale VCPHP designed for the Altair Lunar lander mission is predicted via numerical simulations with radiation cooling boundary conditions. Using the mathematical model, the influence of several design parameters can be identified and a maximum heat rejection turn-down ratio of 11.0 is achievable. Furthermore, the vapor-NCG topology within the integral planar heat pipe with a non-uniform heat load is simulated through a volume of fluid (VOF)-based approach.

Committee:

Yasuhiro Kamotani (Advisor); Jaikrishnan Kadambi (Advisor); James T'ien (Committee Member); Chung-Chiun Liu (Committee Member)

Subjects:

Aerospace Engineering; Mechanical Engineering

Keywords:

heat pipes; radiator; two-phase heat transfer; space thermal control system

Papageorge, MichaelA study of scalar mixing in gas phase turbulent jets using high repetition rate imaging
Doctor of Philosophy, The Ohio State University, 2017, Mechanical Engineering
In this dissertation, high-speed mixture fraction (a conserved flow scalar) and velocity measurements were performed to understand the linked spatio-temporal dynamics of scalar mixing processes in gas-phase turbulent jets. The current research focused on four over-arching topics: (i) design and construction of the high energy pulse burst laser system (HEPBLS), (ii) experimental verification of statistical convergence theory for time-series measurements in turbulent flows and the development of a new "multi-burst" data processing methodology for "short duration" time-series measurements, (iii) development and application of high-speed (10 kHz) two-dimensional mixture fraction imaging for spatio-temporal statistical analysis of scalar mixing, and (iv) development and application of simultaneous high-speed velocity and mixture fraction measurements to understand the space-time coupling between velocity and scalar fluctuations. The high-speed measurements presented in this dissertation were facilitated through the design and construction of a new high-energy pulse burst laser system (HEPBLS). The design target of the HEPBLS was ultra-high pulse energy output at high repetition rates for turbulence and combustion imaging diagnostics. Several modifications were made to the original pulse burst concept leading to ultra-high laser pulse energies (> 1 Joule/pulse at 532 nm and 10 kHz) over long burst durations (> 20 ms). The high laser pulse energies enable high-fidelity two-dimensional mixture fraction measurements at 10's of kHz using planar Rayleigh scattering and two-line mixture fraction imaging using spontaneous Raman scattering. While the primary imaging diagnostics used the second-harmonic (532 nm) output from the HEPBLS, it is noted that high-energy ultra-violet (266, 355 nm) output was demonstrated as well. The result is a flexible system capable of facilitating a wide range of laser diagnostic techniques at 10's of kHz that have not been available previously. Convergence of turbulent flow statistics from finite-record length time-series measurements was examined via theory and experiment. Analytical solutions of the convergence of statistical moments and correlation functions were developed and experimentally verified for the first time, providing a practitioner a method for accurately estimating the uncertainty of a measurement for a given record length. In addition, a new "multi-burst" data processing method was proposed (and experimentally validated) based on combined ensemble and time-series statistics specifically targeted for shorter-duration time-series measurements characteristic of data acquired using the HEPBLS. A subtle, but important, result was that the primary factor governing statistical convergence was the total amount of data and not the exact manner (i.e., record length or number of individual time series) in which it was collected. In this manner, a large number of short-duration time-series measurements can be acquired and achieve high statistical convergence. Scalar mixing dynamics was first examined using high-speed (10 kHz) planar Rayleigh scattering imaging in a series of turbulent propane jets. In this manner, quantitative two-dimensional measurements of the mixture fraction field were collected for jets with Reynolds numbers of Red=10000, 20000, and 30000 with high signal-to-noise ratios (60 < SNR < 200). The integral length and time scales were calculated via correlation functions across the full range of Reynolds numbers and as function of axial and radial position. The radial dependence of the integral scales was shown to be strongly affected by the increasing intermittency of the turbulence with increasing radial location. Without accounting for local intermittency effects, the integral time scales were overestimated by as much as a factor of three. The results also showed that Taylor's hypothesis, a common Galilean transformation between space and time, properly predicts the functional relationship between the integral length and time scales, but does not allow for a quantitative transformation. A recently proposed "elliptical" model for transformation of correlation functions between space and time was found to be more accurate. The current work demonstrates the accuracy of the elliptical model in turbulent free shear flows for the first time. Subsequently, the model was used to help understand the relationship between the scalar fluctuations and turbulent velocity field. Results showed that the decorrelation of scalar fluctuations is governed by both convection and turbulent velocity fluctuations. Simultaneous 10 kHz mixture fraction and velocity measurements were performed using two-line spontaneous Raman scattering and particle imaging velocimetry (PIV). Of particular note from a diagnostic standpoint, is that the presence of the PIV seed particles was found to have a negligible influence on the accuracy of the scalar measurements. A qualitative analysis of observed scalar and velocity features show that the majority of the time the axial velocity component and the mixture fraction are highly correlated, but there are distinct periods in which the two fields appear to be relatively uncorrelated or even anti-correlated. Quantitative analysis of statistical metrics including autocorrelation functions, two-point temporal correlation functions, and temporal scalar-velocity cross correlation were performed. The results show that scalar fluctuations and axial velocity fluctuations are highly correlated with a peak correlation coefficient of 0.6 that occurred at zero time lag indicating that the velocity and scalar fluctuations are in phase. Overall, it is concluded that scalar mixing within gas-phase jets is predominantly a passive process and largely controlled by the local axial velocity fluctuations.

Committee:

Jeffrey Sutton (Advisor); Mohammad Samimy (Committee Member); Datta Gaitonde (Committee Member); Gregory James (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

Turbulence; Turbulent Jet; Round Jet;

Ranade, VishakhduttDynamic Modeling of Rankine Cycle using Arbitrary Lagrangian Eulerian Method
MS, University of Cincinnati, 2017, Engineering and Applied Science: Mechanical Engineering
Thermoelectric power plants are often based on Rankine cycle where the steam is cooled using water from a lake or a river. This water is recirculated in a cooling tower where a portion of the cooling water is lost to evaporation. To reduce water consumption in thermoelectric power plants, there is an urgent need to develop efficient air-cooled condensers for Rankine cycles. To this end, understanding how the Rankine cycle performance changes with diurnal temperature variation is essential. In the present study, a computational model was developed to simulate the transient behavior of a Rankine cycle and its response to changing ambient air temperature. The computation model is based on the Arbitrary Lagrangian Eulerian method incorporating the merits of Lagrangian and Eulerian techniques aiming towards a higher computational efficiency while accurately tracking the H2O mass moving through the boiler, turbine, condenser, and the pump. The model was developed using MATLAB and validated using available data. The model was first applied to simulate transient dynamics of a vapor compression cycle for which data were readily available in the literature. The validated model was then used to simulate a Rankine cycle. Parameters of interest for the computation included the delivery conditions for boiler, turbine, condenser and the resulting power output. Simulations were run with varying ambient temperature throughout the day. The maximum ambient temperature was varied to represent four locations in different regions of the United States. These results were compared to cycle operation under air pre-cooling which maintains a fixed maximum air temperature reaching the condenser. When the ambient air temperature increases, the condenser temperature and consequently its pressure increases. This results in a decrease in the turbine power output. This reduction in power output can be mitigated by maintaining the temperature of the air going to the condenser at the design condition. The increase in cycle efficiency obtained with air pre-cooling is plotted for four different locations. The developed computational model based on the Arbitrary-Lagrangian-Eulerian method is able to accurately capture the transient variation in Rankine cycle performance with varying ambient conditions.

Committee:

Milind Jog, Ph.D. (Committee Chair); Michael Kazmierczak, Ph.D. (Committee Member); David Thompson, Ph.D. (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

Rankine Cycle;Arbitrary Lagrangian Eulerian;ALE;Lagrangian

Kharraz, Adel OmarStability of Swirling Flow in Passive Cyclonic Separator in Microgravity
Doctor of Philosophy, Case Western Reserve University, EMC - Mechanical Engineering
The use of passive cyclonic separators in microgravity environment to perform phase separation requires taking into account the effect of capillary forces. The study utilizes control-volume approximation and VOF-based CFD simulation to investigate their effects on separator performance in microgravity. The configuration of liquid film and gas core rotating inside the separator involves the presence of a free surface (interface). In this situation the liquid film thickness becomes very critical because the increase of this film causes an increase in the capillary force at the interface, which may eventually cause a collapse of the liquid film. Therefore an investigation is performed by conducting a parametric study with respect to the dimensionless parameters that represent the separator geometry and the swirling flow hydrodynamics to determine the effects of all of these parameters on the liquid film thickness. The control-volume approximation in this study is developed using the conservation of mass and angular momentum as well as applying a pressure balance for the separator, taking into account the capillary force effect at the interface. The flow field is assumed to behave as a solid body rotation. The developed equations are solved to obtain the critical (minimum) Weber number at the interface before collapsing. The CFD approach utilizes 2-D axisymmetric meshing to discretize the governing equations. OpenFOAM, which is an open source software package, is used to generate the meshing and perform the simulation. The approach is used to develop a skin friction coefficient formula at a low volume flow rate injection which is needed in the control-volume approximation. The flow field is studied with decreasing Weber numbers until the liquid film collapses, which determines the critical Weber number. Also, the effect of contact angle on the liquid film stability is qualitatively investigated using this approach. Two-phase flow injection is also investigated using only the control-volume approximation. The investigation is carried out at several injection volumetric qualities with the assumption that the void fraction and injection volumetric quality are equal (homogeneous injection).

Committee:

Yasuhiro Kamotani, Professor (Advisor)

Subjects:

Mechanical Engineering

Kakumani, AkulDesign of a Tensile Tester to Test an Ant Neck Joint
Master of Science, The Ohio State University, 2017, Mechanical Engineering
Insect body and limb segments are connected using internal, soft membranous and external hard materials of varying geometries to allow for motion whereas vertebrates employ internal stiff and soft components with physical constraints. Insect joints are therefore mechanically distinct from vertebrate joints. Ants, in particular, have a highly integrated system that is comprised of composite materials, internal muscle mechanisms, and material microstructure. As a result of their unique structure and material properties they are able to carry loads in excess of 1000 times their own weight, the load path of which passes through the neck joint. To study this joint, multiple experiments were conducted prior to this research project using a custom-built, open centrifuge following a method also used to investigate the attachment forces of arboreal ants. The current project builds on the results obtained from the previous project, including the development of a device for a neck joint tensile test. This improved design involves a load cell and a displacement sensor that record the load and displacement values when the neck is being loaded to the point of failure. These values are then used to determine the stress and strain values and compared to the values obtained in the previous research. The design of the tensile tester also includes the design of a fixture for holding the ant without compromising its internal structure and geometry.

Committee:

Sandra Metzler (Advisor)

Subjects:

Mechanical Engineering

Keywords:

Tensile Tester; Ant Neck Joint; Mechanical Engineering

Kattoura, MichealEffects of Advanced Surface Treatments on the Fatigue Behavior of ATI 718Plus at Room and Elevated Temperatures
PhD, University of Cincinnati, 2017, Engineering and Applied Science: Mechanical Engineering
Fatigue failure is a major reason behind the failure of mechanical components and machine parts. In turbine engines and related applications, the components are subjected to cyclic loading at elevated temperatures. Superalloys have high strength and environmental resistance to perform under extreme high temperatures and stress conditions. Improvement in the strength, fatigue life, and/or temperature capabilities of these superalloys will yield huge economic benefits. To address these challenges, surface treatment techniques are implemented to improve the fatigue behavior of currently used superalloys at elevated temperatures. This study investigates Ultrasonic Nano-crystal Surface Modification (UNSM) and Laser Shock Peening (LSP) as techniques to improve strength and fatigue behavior of ATI 718 Plus (718Plus) at room and elevated temperatures. The effect of temperature and strain rate on the strength, ductility, and failure behavior of 718Plus was investigated. The results showed that with the increase of temperature at slow strain rate, there is a small reduction in the yield strength, a large drop in ductility, and a change in fracture mode from ductile transgranular to brittle intergranular cracking. Analysis of the microstructure showed that the driving mechanism at higher temperatures and slower strain rates is oxygen-induced intergranular cracking, a dynamic embrittlement mechanism and that the d precipitates on the grain boundaries are facilitators. Increase of strain rate at 704 °C caused a small increase in the yield strength, a huge increase in the ductility, and a change in fracture mode from brittle to ductile failure. This showed that the driving mechanism at higher strain rates was Portevin–Le Chatelier effect. Finally, 718Plus has superior fatigue behavior at its operation temperature (650 °C) compared to room temperature due to the strengthening of the ?' precipitates which increased its endurance limit by ~20% (~145 MPa). The repetitive strikes from UNSM induced plastic deformation that led to nano-sized crystallites, high density of twins, and high dislocations density in the near surface, coupled with extremely high magnitude surface compressive stresses (-1200 MPa) and increase in the surface hardness by ~2.3 GPa. This led to increase in the room temperature yield strength by ~ 13% (~ 145 MPa) and endurance limit by ~ 13% (~ 100 MPa). At 650 °C, UNSM retained 56% of its residual stresses after 140 hours. In addition, the microstructure created by UNSM remained stable at 650 °C. The high retained residual stress and stable microstructure led to an increase in the yield strength by ~ 11% (~105 MPa) and endurance limit by ~ 8% (~ 67 MPa) of 718Plus at its operation temperature. The shockwave by LSP induced plastic deformation that greatly increased the dislocation density in the form of dislocation entanglements and slip bands. LSP created high residual stresses (-750 MPa) and increased the surface hardness by ~ 1.62 GPa. This led to increase in the room temperature yield strength by ~ 16% (~ 175 MPa) and endurance limit by ~ 15% (~ 110 MPa). At 650 °C, LSP retained 68% of its residual stresses after 140 hours. In addition, the microstructure created by LSP remained stable at 650 °C. The high retained residual stress and stable microstructure led to an increase of in the yield strength by ~14% (~ 140 MPa) and endurance limit by ~10% (~ 90 MPa) of 718Plus at its operation temperature. The improvement in fatigue behavior 718Plus was due to the shielding provided by UNSM & LSP. The compressive stress shielding hindered the crack initiation and lowered the crack propagation rates. In addition, the near surface microstructure created a barrier that restricted the movement of dislocations to the surface. Thus, the required cycles to create extrusions and intrusions, which lead to crack initiation, was much higher and the crack propagation rates especially near the surface were much lower.

Committee:

Vijay Vasudevan, Ph.D. (Committee Chair); Woo Kyun Kim, Ph.D. (Committee Member); Yijun Liu, Ph.D. (Committee Member); Dong Qian, Ph.D. (Committee Member); Jing Shi, Ph.D. (Committee Member)

Subjects:

Mechanical Engineering; Mechanics

Keywords:

Advanced Surface treatments;Nickel-based superalloys;Fatigue behavior;Residual stresses;Electron microscopy;Elevated temperature testing

Zhu, Yonry RApplications and Modeling of Non-Thermal Plasmas
Bachelor of Science (BS), Ohio University, 2018, Engineering Physics
This thesis focuses on validation of a 0D plasma kinetic model and its subsequent use as an explanatory tool to support the results of hot-fire tests of a plasma assisted rotating detonation combustor. The plasma model predictions showed good agreement with experimentally measured values of various ground state species number densities, vibrationally excited N2 number densities, plasma temperatures, and ignition delay times. Once validated, the plasma model was combined with a ZND detonation model and semi-empirical correlation to determine the effects of a non-thermal plasma on the reduction of the detonation cell size for an H2 - air mixture. The modeling results showed that non-thermal plasma significantly reduces the detonation cell size. This effect is most pronounced at lean conditions, where the model predicted a reduction in cell size by a factor of more than 100. For stoichiometric and rich conditions, the cell size reduction was around a factor of 5. An investigation was conducted to determine the viability of using a non-thermal plasma to expand the operating regime of a rotating detonation combustor. The plasma was produced with a nanosecond pulse generator connected to a ceramic and metal centerbody electrode. Hot-fire testing results showed that the plasma causes detonation onset in conditions that would otherwise not support detonation. This effect was most prominent at near-stoichiometric conditions, with a reduced effect for richer or leaner mixtures.

Committee:

David Burnette (Advisor)

Subjects:

Aerospace Engineering; Mechanical Engineering; Plasma Physics

Keywords:

non-thermal plasma; plasma assisted combustion; nanosecond pulsed plasma; plasma modeling; detonation combustion; rotating detonation combustor; detonation;

Hall, Brenton TaylorUsing the Non-Uniform Dynamic Mode Decomposition to Reduce the Storage Required for PDE Simulations
Master of Mathematical Sciences, The Ohio State University, 2017, Mathematical Sciences
Partial Differential Equation simulations can produce large amounts of data that are very slow to transfer. There have been many model reduction techniques that have been proposed and utilized over the past three decades. Two popular techniques Proper Orthogonal Decomposition and Dynamic Mode Decomposition have some hindrances. Non-Uniform Dynamic Mode Decomposition (NU-DMD), which was introduced in 2015 by Gueniat et al., that overcomes some of these hindrances. In this thesis, the NU-DMD's mathematics are explained in detail, and three versions of the NU-DMD's algorithm are outlined. Furthermore, different numerical experiments were performed on the NU-DMD to ascertain its behavior with repect to errors, memory usage, and computational efficiency. It was shown that the NU-DMD could reduce an advection-diffusion simulation to 6.0075% of its original memory storage size. The NU-DMD was also applied to a computational fluid dynamics simulation of a NASA single-stage compressor rotor, which resulted in a reduced model of the simulation (using only three of the five simulation variables) that used only about 4.67% of the full simulation's storage with an overall average percent error of 8.90%. It was concluded that the NU-DMD, if used appropriately, could be used to possibly reduce a model that uses 400GB of memory to a model that uses as little as 18.67GB with less than 9% error. Further conclusions were made about how to best implement the NU-DMD.

Committee:

Ching-Shan Chou (Advisor); Jen-Ping Chen (Committee Member)

Subjects:

Aerospace Engineering; Applied Mathematics; Computer Science; Mathematics; Mechanical Engineering

Keywords:

Fluid Dynamics; Fluid Flow; Model Reduction; Partial Differential Equations; reducing memory; Dynamic Mode Decomposition; Decomposition; memory; Non-Uniform Dynamic Mode Decomposition

Wagner, ChristopherRegression Model to Project and Mitigate Vehicular Emissions in Cochabamba, Bolivia
Master of Science (M.S.), University of Dayton, 2017, Renewable and Clean Energy
The purpose of this study is to generate a regression model tying the vehicular emissions in Cochabamba, Bolivia to input factors including the current state of the public fleet, city population, weather, and GDP. The finished model and the process to generate it can act as a tool to project future emissions in the city, accounting for the aforementioned input factors. It can also be used to estimate the drop in city pollution levels in a scenario where the public transportation fleet is partially replaced by non-emitting, electric vehicles. The main pollutant focused on in this study is particulate matter (PM10), but data also exists for ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2). The model generation process explained in the study could be applied to these pollutants as well. The regression model is generated using the open source software, R. Its final form utilizes a random forest regression model, but neural net, gradient boosting, and support vector machine models were also explored.

Committee:

Robert Brecha, Ph.D. (Committee Chair); Andrew Chiasson, Ph.D. (Committee Member); Malcolm Daniels, Ph.D. (Committee Member)

Subjects:

Engineering; Environmental Engineering; Mechanical Engineering

Keywords:

Random Forest Model; Vehicular Fleet; Cochabamba, Bolivia; Vehicle Emissions; Predictive Ensemble Model

Hou, GuangfengMultiphysics Gas Phase Pyrolysis Synthesis of Carbon Nanotube Yarn and Sheet
PhD, University of Cincinnati, 2017, Engineering and Applied Science: Mechanical Engineering
Carbon nanotubes (CNTs) have superior properties as a nano-scale object. For real engineering applications, there is a challenge for effectively assembling this nano object into macroscopic entities. Moreover, in the form of macroscale materials, CNT yarn and sheet (CNTYS) have much lower properties than individual nanotubes. CNTYS are composed of billions of micrometer to millimeter length CNT bundles in their cross-sections. Reasons for the underperformance of CNTYS lie mainly in the CNT to CNT junctions in the assemblages, and also the quality, purity, alignment, density and length of the CNTs in the assemblages. CNTYS can be produced continuously using the gas phase pyrolysis (floating catalyst) method, which is a practical method for high rate manufacturing of CNT. This goal of this research is to investigate the process mechanism and develop multiphysics control techniques for the gas phase pyrolysis method to improve the properties of CNTYS. A horizontal reactor has been developed, and CNTYS have been successfully synthesized. The synthesis process integrates multiple physical processes including positive displacement fuel injection, induction pre-heating of the fuel, high temperature synthesis, and electromagnetic and electrostatic excitation to manipulate the nanotubes and plasma in the reactor. These processes are multiscale in time and length. This research investigates both numerically and experimentally some of the complex interrelated factors affecting the multiphysics synthesis process to improve CNTYS properties. A voltage signal was measured inside the reactor, possibly for the first time. The voltage signal was induced by the heater coil and the electromagnetic coil current and creates a cold plasma. Simulation results predicted, for the first time, the existence of a convection vortex in the horizontal gas phase pyrolysis reactor. Based on experimental observations and numerical simulation, a convection vortex model was proposed to describe CNT sock (aerogel or smoke) formation. A web-shell structure was used to study the sock dynamics. Overall, several novel techniques, including induction heating, pressured fuel injection, and electromagnetic and electrostatic manipulation were investigated to improve CNTYS quality and production rate. Ultra-high quality CNT sheet with a Raman G/D ratio of 100 was synthesized. The process yield was improved by controlling the process parameters in the reactor. Discussion of various up and coming technical applications of CNTYS were also included.

Committee:

Mark Schulz, Ph.D. (Committee Member); Yijun Liu, Ph.D. (Committee Member); David Mast, Ph.D. (Committee Member); Vesselin Shanov, Ph.D. (Committee Member); Jing Shi, Ph.D. (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

carbon nanotube;CNT sock;gas phase pyrolysis;multiphysics

Kamble, MithilDevelopment of a Polygonal Finite Element Solver and Its Application to Fracture Problems
MS, University of Cincinnati, 2017, Engineering and Applied Science: Mechanical Engineering
This study develops a polygonal finite element solver for 2-D crack propagation simulation along with a meshing algorithm which creates necessary polygonal mesh. The work starts with a brief literature review of historical development of computational fracture mechanics. After reviewing multiple methods employed for modeling fracture problems, Wachspress formulation is selected for constructing the polygonal finite element solver. Polygonal interpolants are developed using Wachspress’ framework and validated using published results. A polygonal meshing algorithm is also developed since conventional finite element meshers do not support domain meshing using higher order polygons. The meshing algorithm is then used to create the mesh and input files for the polygonal finite element solver. The polygonal solver is validated using conventional patch tests. The accuracy and convergence of the method is assessed using classical solid mechanics problems with known analytical solutions. Next, ability to include cracks geometrically is added to the meshing algorithm. The polygonal solver is updated with crack tracking and remeshing capability. A fracture problem is solved using the developed subroutines.

Committee:

Yijun Liu, Ph.D. (Committee Chair); Woo Kyun Kim, Ph.D. (Committee Member); Kumar Vemaganti, Ph.D. (Committee Member)

Subjects:

Mechanical Engineering; Mechanics

Keywords:

Polygonal finite element method;Polygonal interpolants;Finite element methods;Fracture mechanics;Computational fracture mechanics;Crack propagation

Jia, WenboA Numerical Study of Catalytic Light-Off Response
Master of Science, The Ohio State University, 2016, Mechanical Engineering
The performance of a three-way catalytic converter is studied numerically using commercial computational fluid dynamics (CFD) software FluentTM 15.0 and MATLAB/Simulink programs. At first a cold flow simulation is performed to study the effects of converter geometric parameters on flow distributions at the monolith inlet. The effectiveness of the heat transfer from exhaust gases to the monolith through convective heat transfer is then investigated without consideration of the chemical reactions. The kinetics model proposed by Holder et al. is implemented into the 1D channel model and a 2D axisymmetric model is developed combining 2D axisymmetric heat conduction with the 1D channel model. The effects of cell density, catalyst loading, flow and temperature distributions at the monolith inlet on conversion efficiencies are examined. The results show that the flow and temperature distribution and the pressure drop across the monolith are strongly affected by converter geometric parameters such as the pipe/diffuser angle, the substrate length to diameter ratio L/D, and the inlet gas temperature and mass flow rate. The flow at the monolith inlet becomes more non-uniform with increasing of the angle ¿, the mass flow rate, and the inlet gas temperature and decreasing of the ratio L/D. The temperature at the monolith inlet becomes more uniform with increasing of the mass flow rate and decreasing of the inlet gas temperature. The pressure drop across the monolith increases with increasing of the mass flow rate, the inlet gas temperature, the angle, and the ratio L/D. The results also suggest that a substrate with a larger cell density and heavier loaded catalyst in the front gives better conversion efficiencies. The conversion efficiencies are not affected much by a change of thermal conductivity of the converter insulation mat up to 10%. Furthermore uniform flow and temperature distributions at the monolith inlet give rise to the best conversion efficiencies for a converter with a given flow condition. For a given temperature distribution at the monolith inlet, the effects of the flow distribution at the inlet on the conversions are negligible. The conversion efficiencies decrease as the temperature distribution at the monolith inlet becomes more non-uniform.

Committee:

Mei Zhuang, Dr. (Advisor); Xiaodong Sun, Dr. (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

catalytic converter, CFD, chemical kinetics, light-off response

Fais, Collier R.Simulation, Design, and Hardware Implementation of a 4-axis Cable Suspended Robot
Master of Science (MS), Ohio University, 2017, Mechanical Engineering (Engineering and Technology)
A classroom-scale 4-axis cable-suspended robot (CSR) is developed with MATLAB software for versatile graphical user interface (GUI) computer simulations, SolidWorks software for computer aided design (CAD), construction and machining of basic stock materials, and Parker Automation Control (PAC) software for 2-axis straight line trajectories. The MATLAB simulation program provides results of active cable lengths and velocities and accelerations, active cable tensions, active motor positions and velocities and accelerations, active cable-winch positions and velocities and accelerations, end-effector kinematics (position, velocity, acceleration, jerk and snap), global Cartesian end-effector position, robot Cartesian stiffness, and robot singularity evaluation over a variety of 3-D and 2-D trajectories and static poses. Results gained from the MATLAB simulation are used to verify that a CAD model of the prototype system can withstand the predicted operational forces based on several failure criterion yielding a minimum factor of safety of 4.34. The prototype hardware system is assembled and used to complete a straight-line point-to-point trajectory excecuted via the PAC software demonstrating a maximum, minimum and average position error of 10.3”, 4.8” and 8.7”, repectively, given a desired position within a 10 by 4 foot planar workspace.

Committee:

Robert Williams (Advisor)

Subjects:

Mechanical Engineering

Keywords:

Cable-suspended Robot; MATLAB, Algae

Elmushyakhi, AbrahamIn-Plane Fatigue Characterization of Core Joints in Sandwich Composite Structures
Doctor of Philosophy (Ph.D.), University of Dayton, 2017, Materials Engineering
In practice, adjacent preform sandwich cores are joined with a simple butt joint without special precautions. When molded, this gap is filled with resin and creates a resin rich area. Stress risers will be amplified under cyclic load, and consequently, the serviceability of the structure will be affected. Designers and researchers are aware of this problem; however, quantifying this effect and its intensity and consequence on the service life of the structures has not yet been developed. Despite pervious findings, limited experimental data backed by a comprehensive root cause failure analysis is available for sandwich under axial static, fatigue and post-fatigue. If such a comprehensive experimental characterization is conducted, specifically understanding the nature of the damage, intensity, and residual strength, then a valid multi-scale damage model could be generated to predict the material state and fatigue life of similar composite structures with/without core joints under in-plane static and fatigue load. This research study characterized the effect of scarf and butt core joints in foam core sandwich structures under in-plane static and fatigue loads (R=0.1 and R= -1). Post-Fatigue tensile tests were also performed to predict the residual strength of such structures. Nondestructive Evaluation Techniques were used to locate the stress concentrations and damage creation. A logical blend of experimental and analytical prediction of the service life of composite sandwich structures is carried out. The testing protocol and the S-N curves provided in this work could be reproducible and extrapolated to any kind of core material. This research study will benefit composite engineers and joint designers in both academia and industry to better apprehend the influence of core joints and its consequence on the functionality of sandwich structures.

Committee:

Elias Toubia (Advisor); Paul Murray (Committee Member); Thomas Whitney (Committee Member); Youssef Raffoul (Committee Member)

Subjects:

Aerospace Engineering; Aerospace Materials; Civil Engineering; Composition; Design; Engineering; Materials Science; Mechanical Engineering; Polymers

Keywords:

Sandwich Composite Structures; Design; Fatigue; Damage; Joints; Lightweight Materials; E-glass-vinyl ester; GFRP Laminate; Modeling; Prediction; Nondestructive Testing

Alrobaian, Abdulrahman AbdullahMulti-Spectral Remote Thermal Imaging for Surface Emissivity and Estimation of Roof R-Values Using Physics-Based and Data Mining Models
Doctor of Philosophy (Ph.D.), University of Dayton, 2017, Mechanical Engineering
Remote thermal imaging of buildings is notable for providing interesting but generally qualitative images of buildings. A recent study showed that if accurate measurements of exterior surface temperatures could be obtained from single-point-in-time-imaging, then it would be possible to infer envelope R-values and thermal capacitances with reasonable accuracy. This research seeks to answer the question, “How can we make possible reasonably accurate measurements of the external temperatures from at-scale remote imaging?” Without knowledge of the emissivity of the exterior surfaces, accurate thermal assessment is seemingly impossible. Here, we exploit the unique spectral characteristics of the most common exterior building surfaces using multi-spectral imaging. Four to five images of exterior surfaces in the 1-5-micron range, where the spectral emissivity of different building materials changes most, is posed. The pattern of the emission can be correlated to various envelope component surface spectral emissivities. A neural network pattern matching algorithm is used to `find’ the surface type. Then, with known emissivity, the surface temperature can be inferred from the magnitude of the emission. Theoretical results indicate that temperature error in measuring the surface temperature in using this approach can be less than ±1oC. This error is sufficient for identifying envelope R-values based upon the research posed by Salahaldin and Hallinan [1]. Most exciting is the prospect of this technique for effectively measuring building R-values at scale via fly-over or drive by imaging. Conventional residential building energy auditing needed to identify opportunities for energy savings is expensive and time consuming. On-site energy audits require quantification of envelope R-values, air and duct leakage, and heating and cooling system efficiencies. There is a need to advance lower cost automated approaches, which could include aerial and drive-by thermal imaging at-scale in an effort to measure the building R-value. However, single-point in time thermal images are generally qualitative, subject to errors stemming from building dynamics, background radiation, wind speed variation, night sky thermal radiation, and error in extracting temperature estimates from thermal images from surfaces with generally unknown emissivity. This work proposes two alternative approaches for estimating roof R-values from thermal imaging, one a physics based approach and the other a data-mining based approach. Both approaches employ aerial visual imagery to estimate the roof emissivity based on the color and type of roofing material, from which the temperature of the envelope can be estimated. The physics-based approach employs a dynamic energy model of the envelope with unknown R-value and thermal capacitance. These are tuned in order to predict the measured surface temperature at the time of the imaging, given the transient weather conditions prior to the imaging. The data-mining approach integrates the inferred temperature measurement, historical utility data, and easily accessible or potentially easily accessible housing data. A data mining regression model, trained from this data using residences with known R-values, is used to predict the roof R-value in the unknown houses. The data mining approach was shown to be a far superior approach, demonstrating an ability to estimate attic/roof R-value with an r-squared value of greater than 0.88 using as few as nine training houses. The implication of this research is significant, offering the possibility of auditing residences remotely at-scale via aerial and drive-by thermal imaging coupled with utility analysis.

Committee:

Kevin Hallinan (Advisor); Andrew Chiasson (Committee Member); Jun- Ki Choi (Committee Member); Robert Brecha (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

Thermal Imaging, Multispectral, R-value,Data mining

Worsham, MatthewCarbon Lock-in and Decarbonization Pathways at the University of Dayton
Master of Science (M.S.), University of Dayton, 2017, Renewable and Clean Energy
Despite the availability of cost-effective alternatives to highly carbon-intensive practices, the world continues to invest in fossil fuel energy systems. For universities that have pledged to become carbon neutral, this concept of carbon lock-in raises the stakes of their carbon commitments, presenting challenges to traditional practices in facilities planning and operations. Building upon past research on carbon lock-in effects on college campuses, this thesis seeks to identify the University of Dayton’s over-committed emissions under a business-as-usual scenario and chart out a course for decarbonization pathways that would unlock those emissions that are hardest to avoid. I find the business-as-usual scenario results in high carbon liability at the neutrality date, which represents high costs to offset carbon emissions or purchase other “end-of-pipe” solutions. I also discuss decarbonization pathways that could unlock these over-committed emissions. Future work should explore some of the carbon unlocking strategies discussed here so the university can begin to integrate them into its climate action plan and construction policies. Additionally, this perspective on carbon lock-in will be useful to administrators and facilities managers at other institutions concerned about carbon neutrality and high carbon liabilities associated with existing and future carbon-emitting infrastructure.

Committee:

Robert Brecha, PhD (Advisor); Kevin Hallinan, PhD (Committee Member); Jun-Ki Choi, PhD (Committee Member)

Subjects:

Climate Change; Engineering; Mechanical Engineering; Sustainability

Keywords:

carbon lock-in; climate commitment; social cost of carbon; higher education; over-committed emissions; carbon accounting; emissions scenarios; facilities management; american college and university presidents climate commitment; decarbonization pathways

Zeng, XiangruiOptimally-Personalized Hybrid Electric Vehicle Powertrain Control
Doctor of Philosophy, The Ohio State University, 2016, Mechanical Engineering
One of the main goals of hybrid electric vehicle technology is to improve the energy efficiency. In industry and most of academic research, the powertrain control is designed and evaluated under standard driving cycles. However, the situations that a vehicle may encounter in the real world could be quite different from the standard cycles. Studies show that the human drivers have a great influence on the vehicle energy consumptions and emissions. The actual operating conditions that a vehicle faces are not only dependent on the roads and traffic, but also dependent on the drivers. A standard driving cycle can only represent the typical and averaged driving style under the typical driving scenarios, therefore the control strategies designed based on a standard driving cycle may not perform well for all different driving styles. This motivates the idea to design optimally-personalized hybrid electric vehicle control methods that can be adaptive to individual human driving styles and their driving routes. Human-subject experiments are conducted on a driving simulator to study the driving behaviors. A stochastic driver pedal model that can learn individual driver’s driving style is developed first. Then a theoretic investigation on worst-case relative cost optimal control problems, which is closely related to vehicle powertrain optimal control under real-world uncertain driving scenarios, is presented. A two-level control structure for plug-in hybrid electric vehicles is proposed, where the parameters in the lower-level controller can be on-line adjusted via optimization using historical driving data. The methods to optimize these parameters are designed for fixed-route driving first, and then extended to multi-routes driving using the idea similar to the worst-case relative cost optimal control. The performances of the two proposed methods are shown through simulations using human driving data and stochastic driver model data respectively. The energy consumption results in both situations are close to the posteriori optimal result and outperform other existing methods, which show the effectiveness of applying optimally-personalized energy management strategy on hybrid electric vehicles. Finally, a route-based global energy-optimal speed planning method is also proposed. This off-line method provides a useful tool to evaluate the potential of other speed planning methods, for either eco-driving guidance applications or future automated vehicle controls. The contributions of this dissertation include 1) a novel stochastic driver pedal behavior model which can learn independent drivers’ driving styles is created, 2) a new worst-case relative cost optimal control method is proposed, 3) a real-time implementable stochastic optimal energy management strategy for hybrid electric vehicles running on fixed routes is designed using the statistics of history driving data, 4) the fix-route strategy is extended to the multi-route situation, and 5) an off-line global energy-optimal speed planning solution for road vehicles on a given route is presented.

Committee:

Junmin Wang (Advisor); Ryan Harne (Committee Member); Chia-Hsiang Menq (Committee Member); Haijun Su (Committee Member)

Subjects:

Automotive Engineering; Mechanical Engineering

Keywords:

Hybrid electric vehicle; energy management strategy; optimal control; speed planning; driver model

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