Mechanical Engineering Theses and Dissertations

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Application of Diagnostics and Prognostics Techniques to Qualification Against Wear-Out Failure
(2022) Ram, Abhishek; Das, Diganta; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
QUALIFICATION IS A PROCESS THAT DEMONSTRATES WHETHER A PRODUCT MEETS OR EXCEEDS SPECIFIED REQUIREMENTS. TESTING AND DATA ANALYSIS PERFORMED WITHIN A QUALIFICATION PROCEDURE SHOULD VERIFY IF PRODUCTS SATISFY THOSE REQUIREMENTS, INCLUDING RELIABILITY REQUIREMENTS. MOST OF THE ELECTRONICS INDUSTRY QUALIFIES PRODUCTS USING PROCEDURES DICTATED WITHIN QUALIFICATION STANDARDS. A REVIEW OF COMMON QUALIFICATION STANDARDS REVEALS THAT THOSE STANDARDS DO NOT CONSIDER CUSTOMER REQUIREMENTS OR THE PRODUCT PHYSICS-OF-FAILURE IN THAT INTENDED APPLICATION. AS A RESULT, QUALIFICATION, AS REPRESENTED IN THE REVIEWED QUALIFICATION STANDARDS, WOULD NOT MEET OUR DEFINITION OF QUALIFICATION FOR RELIABILITY ASSESSMENT. THIS THESIS PROVIDES AN APPLICATION-SPECIFIC APPROACH FOR DEVELOPING A QUALIFICATION PROCEDURE THAT ACCOUNTS FOR CUSTOMER REQUIREMENTS, PRODUCT PHYSICS-OF-FAILURE, AND KNOWLEDGE OF PRODUCT BEHAVIOR UNDER LOADING. THIS THESIS PROVIDES A REVAMPED APPROACH FOR DEVELOPING A LIFE CYCLE PROFILE THAT ACCOUNTS FOR LOADING THROUGHOUT MANUFACTURING/ASSEMBLY, STORAGE AND TRANSPORTATION, AND OPERATION. THE THESIS ALSO DISCUSSES IDENTIFYING VARIATIONS IN THE LIFE CYCLE PROFILE THAT MAY ARISE THROUGHOUT THE PRODUCT LIFETIME AND METHODS FOR ESTIMATING LOADS. THIS UPDATED APPROACH FOR DEVELOPING A LIFE CYCLE PROFILE SUPPORTS BETTER FAILURE PRIORITIZATION, TEST SELECTION, AND TEST CONDITION AND DURATION REQUIREMENT ESTIMATION. ADDITIONALLY, THIS THESIS INTRODUCES THE APPLICATION OF DIAGNOSTICS AND PROGNOSTICS TECHNIQUES TO ANALYZE REAL-TIME DATA TRENDS WHILE CONDUCTING QUALIFICATION TESTS. DIAGNOSTICS TECHNIQUES IDENTIFY ANOMALOUS BEHAVIOR EXHIBITED BY THE PRODUCT, AND PROGNOSTICS TECHNIQUES FORECAST HOW THE PRODUCT WILL BEHAVE DURING THE REMAINDER OF THE QUALIFICATION TEST AND HOW THE PRODUCT WOULD HAVE BEHAVED IF THE TEST CONTINUED. AS A RESULT, COMBINING DIAGNOSTICS AND PROGNOSTICS TECHNIQUES CAN ENABLE THE PREDICTION OF THE REMAINING TIME-TO-FAILURE FOR THE PRODUCT UNDERGOING QUALIFICATION. SEVERAL ANCILLARY BENEFITS RELATED TO AN IMPROVED TESTING STRATEGY, PARTS SELECTION AND MANAGEMENT, AND SUPPORT OF A PROGNOSTICS AND HEALTH MANAGEMENT SYSTEM IN OPERATION ALSO ARISE FROM APPLYING PROGNOSTICS AND DIAGNOSTICS TECHNIQUES TO QUALIFICATION.
Developments in Carbon Fiber Rod Analysis for Sporting Goods Applications
(2022) Quigley, Connor Robert; Chung, Peter; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
In sporting goods manufacturing, such as in fishing rod design, new products are created using an Edisonian process. By changing the geometry of the carbon fiber prepreg layup, a rod can be constructed that lends itself to a specific application. This thesis will present an integrated computational materials engineering (ICME) approach for carbon fiber fishing rods using simulation theory and experiments. The computations are based on the finite element method (FEM), including the use of integrated Euler-Bernoulli beam theory in MATLAB. The experimental methodology uses three-point bending (3PB) flexure test analysis to determine values for Young’s Modulus which are then incorporated into numerical solutions and modelling. Discretized values for Young’s Modulus are used in thin-walled tapered cylindrical Euler-Bernoulli beam models through variable second area moment of inertia (I_y) and constant I_y approaches. The 3PB flexural experiments performed on a test rod section agree to FEM solutions, along with convergence with respect to mesh size between variable I_y and constant I_y beam models. A modal analysis on the beam provides insight to the free-vibrational effects of a fishing rod under differing boundary conditions. Through this ICME approach, rod manufacturers can understand properties in rod prototypes and better develop future rod models.
ENABLING CO2 ISOTHERMAL COMPRESSION USING LIQUID PISTON AND INTEGRATED GAS COOLER
(2022) Kim, Timothy; Hwang, Yunho; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
New avenues of decreasing environmental impacts and increasing the efficiency of HVAC systems are constantly being explored in the race to reduce carbon emissions and global warming. These new avenues have led to the exploration of the use of carbon dioxide as a refrigerant in refrigeration applications. Many researchers have also investigated ways to reduce the power consumption of compressors, which is typically the main source of power draw for HVAC systems. One theoretical process to achieve this is through isothermal compression. This thesis explores the idea of isothermally compressing CO2 by using a liquid piston and integrated gas cooler to achieve higher efficiencies with this transcritical cycle. A test facility was designed, sized, constructed, and calibrated to emulate the suction and discharge conditions of a typical CO2 system for air conditioning applications. A prototype of the liquid piston and integrated gas cooler chamber was designed and constructed as well. A simulation model was built in Engineering Equation Solver in order to properly design the gas cooler chamber. Other critical components have been carefully chosen to ensure smooth operation of the system. Results show isothermal efficiencies of up to 82.7% during steady-state operation and an isothermal efficiency of 91.2% during steady-state operation with the additional help of evaporative cooling. Comparing this to other conventional compressors give up to 34.2% absolute improvement in the isothermal compressor efficiency. These results show sufficient performance to warrant the design of a fully working prototype despite efficiency/capacity tradeoffs in the system. Challenges had been encountered such as the loss of refrigerant through the liquid piston, which will be accounted for in the next prototype. Discussion of the next prototype includes the use of a double-acting piston and a smaller tubed fractal heat exchanger design.
Modeling of HVAC Configurations for De-Carbonization in a Mid-Size Hospital
(2022) Grant, Zachary; Hwang, Yunho; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
As the threat of climate change becomes more imminent, there has been increasing emphasis on technologies that reduce carbon emissions in the HVAC sector. The clear path forward given existing technologies is electrification since electricity production has future potential to become cleaner. In terms of building type, high ventilation requirements and near continuous occupancy make healthcare facilities some of the highest energy users. HVAC equipment runs all day and night in these facilities with little change. Conventional HVAC equipment such as a boiler is proven to consume more energy than heat pump systems. More specifically, the Variable Refrigerant Flow (VRF) heat pump and the Ground Source Heat Pump (GSHP) are areas of ongoing research. This analysis included creating whole-building energy models using EnergyPlus and OpenStudio to compare the energy consumption for these heat pump configurations and some cheaper electrification alternatives. The results suggested that the GSHP system possessed the greatest potential for energy savings and thus decarbonization given its higher efficiency during times of extreme ambient temperatures compared to other options.
Investigation of Swirl Distributed Combustion with Experimental Diagnostics and Artificial Intelligence Approach
(2022) Roy, Rishi; Gupta, Ashwani K; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Swirl Distributed Combustion was fundamentally investigated with experimental diagnostics and predictive analysis using machine learning and computer vision techniques. Ultra-low pollutants emission, stable operation, improved pattern factor, and fuel flexibility make distributed combustion an attractive technology for potential applications in high-intensity stationary gas turbines. Proper mixing of inlet fresh air and hot products for creating a hot and low-oxygen environment is critical to foster distributed combustion, followed by rapid mixing with the fuel. Such conditions result in a distributed thick reaction zone without hotspots found in (thin reaction front) of conventional diffusion flames leading to reduced NOx and CO emissions. The focus of this dissertation is to develop a detailed fundamental understanding of distributed combustion in a lab-based swirl combustor (to mimic gas turbine can combustor) at moderate heat release intensities in the range 5.72- 9.53 MW/m3-atm using various low-carbon gaseous fuels such as methane, propane, hydrogen-enriched fuels. The study of distributed combustion at moderate thermal intensity helped to understand the fundamental aspects such as reduction of flame fluctuation, mitigation of thermo-acoustic instability, flame shape evolution, flow field behavior, turbulence characteristics, variation of Damkӧhler number, vortex propagation, flame blowoff, and pollutant and CO2 emission reduction with gradual mixture preparation. Initial efforts were made to obtain the volumetric distribution ratio, evolution of flame shape in terms of OH* radical imaging, variation of flame standoff, thermal field uniformity, and NO and CO emissions when the flame transitions to distributed reaction zone. Further investigation was performed to study the mitigation of flame thermo-acoustics and precession vortex core (PVC) instabilities in swirl distributed combustion compared to swirl air combustion using the acoustic pressure and qualitative heat release fluctuation data at different dilution CO2 dilution levels with and without air preheats. Proper orthogonal decomposition (POD) technique was utilized to visualize the appearance of dynamic coherent structures in reactive flow fields and reduction of fluctuation energy. Vortex shedding was found responsible for the fluctuation in swirl air combustion while no significant flame fluctuation was observed in distributed combustion. Distributed combustion showed significantly reduced acoustic noise and much higher stability quantified by local and global Rayleigh index. This study was extended with hydrogen-enriched methane (vol. = 0, 10, 20, 40% H2) to compare the stability of the flow field in conventional air combustion and distributed combustion. Results were consistent and distributed reaction zones showed higher flame stability compared to conventional swirl air combustion. The study of lean blowoff in distributed combustion showed a higher lean blowoff equivalence ratio with gradual increase in heat release intensity, which was attributed to higher flow field instability due to enhanced inlet turbulence. Extension of lean blowoff (ϕLBO) was observed with gradual %H2 which showed decrease of lean blowoff equivalence ratio in distributed reaction zones. Additionally, the reduction in ϕLBO was achieved by adding preheats to the inlet airstream for different H2 enrichment cases due to enhanced flame stability gained from preheating. Examination of non-reactive flow field with particle image velocimetry (PIV) was performed to understand the fundamental differences between swirl flow and distributed reaction flow at constant heat release intensities. Higher rms fluctuation leading to healthy turbulence and higher Reynolds stress were found in distributed reaction flow cases signifying enhanced mixing characteristics in distributed combustion. Reduction of pollutant emission was an important focus of this research. Measurement of NO and CO emission at different mixture preparation levels exhibited significant reduction in NO emission (single digit) compared to swirl air combustion due to mitigation of spatial hotspots and temperature peaks. Additionally, better mixing and uniform stoichiometry supported reduced CO emissions in distributed combustion for every fuel. With increased H2 in the fuel, NO gradually increased for air combustion while reduction of NO was found in distributed combustion due to decrease in thermal and prompt NO generation. Finally, the use of machine learning and computer vision techniques was investigated for software-based prediction of combustion parameters (pollutants and flame temperature) and feature-based recognition of distributed combustion regimes. The primary goal of using artificial intelligence is to reduce the time of experimentation and frequent manual interference during experiments in order to enhance the overall accuracy by reducing human errors. Such predictions will help in developing data-driven smart-sensing of combustion parameters and reduce the dependence on experimental trials.

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