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  Partner: UNT Libraries
 Department: Department of Mechanical and Energy Engineering
 Decade: 2010-2019
 Collection: UNT Theses and Dissertations
Analysis of Sources Affecting Ambient Particulate Matter in Brownsville, Texas
Texas is the second largest state in U.S.A. based on geographical area, population and the economy. It is home to several large coastal urban areas with major industries and infrastructure supporting the fossil-fuel based energy sector. Most of the major cities on the state have been impacted by significant air pollution events over the past decade. Studies conducted in the southern coastal region of TX have identified long range transport as a major contributor of particulate matter (PM) pollution along with local emissions. Biomass burns, secondary sulfates and diesel emissions sources are comprise as the dominant mass of PM2.5 have been noted to be formed by the long range transport biomass from Central America. Thus, the primary objective of this study was to identify and quantify local as well as regional sources contributing to the PM pollution in the coastal area of Brownsville located along the Gulf of Mexico. Source apportionment techniques such as principal component analysis (PCA) and positive matrix factorization (PMF) were employed on the air quality monitoring data to identify and quantify local and regional sources affecting this coastal region. As a supplement to the PMF and PCA, conditional probability function (CPF) analysis and potential source contribution function (PSCF) analysis were employed to characterize the meteorological influences for PM events. PCA identified an optimal solution of 6 sources affecting the coastal area of Brownsville, while PMF resolved 8 sources for the same area. Biomass comingled with sea salt was identified to be the dominant contributor from the PCA analysis with 30.2% of the apportioned PM mass in Brownsville, meanwhile PMF account secondary sulfates I & II with 27.6%. the other common sources identified included, biomass burning, crustal dust, secondary sulfate, oil combustion, mobile sources and miscellaneous traffic sources.
Characterization of Viscoelastic Properties of a Material Used for an Additive Manufacturing Method
Recent development of additive manufacturing technologies has led to lack of information on the base materials being used. A need arises to know the mechanical behaviors of these base materials so that it can be linked with macroscopic mechanical behaviors of 3D network structures manufactured from the 3D printer. The main objectives of my research are to characterize properties of a material for an additive manufacturing method (commonly referred to as 3D printing). Also, to model viscoelastic properties of Procast material that is obtained from 3D printer. For this purpose, a 3D CAD model is made using ProE and 3D printed using Projet HD3500. Series of uniaxial tensile tests, creep tests, and dynamic mechanical analysis are carried out to obtained viscoelastic behavior of Procast. Test data is fitted using various linear and nonlinear viscoelastic models. Validation of model is also carried out using tensile test data and frequency sweep data. Various other mechanical characterization have also been carried out in order to find density, melting temperature, glass transition temperature, and strain rate dependent elastic modulus of Procast material. It can be concluded that melting temperature of Procast material is around 337°C, the elastic modulus is around 0.7-0.8 GPa, and yield stress is around 16-19 MPa.
Energy Usage While Maintaining Thermal Comfort : A Case Study of a UNT Dormitory
Campus dormitories for the University of North Texas house over 5500 students per year; each one of them requires certain comfortable living conditions while they live there. There is an inherit amount of money required in order to achieve minimal comfort levels; the cost is mostly natural gas for water and room heating and electricity for cooling, lighting and peripherals. The US Department of Energy has developed several programs to aid in performing energy simulations to help those interested design more cost effective building designs. Energy-10 is such a program that allows users to conduct whole house evaluations by reviewing and altering a few parameters such as building materials, solar heating, energy efficient windows etc. The idea of this project was to recreate a campus dormitory and try to emulate existent energy consumption then try to find ways of lowering that usage while maintaining a high level of personal comfort.
Estimation of Aircraft Emissions for the Corpus Christi International Airport, Corpus Christi, Texas
Commercial aviation is a vital part of the United States economy. It generates over $1 trillion annually, which is more than 5% of the U.S. GDP, and produces approximately 10 million jobs. Every year there is an increase in commercial air traffic. This is attributed to expanding trade between states and other countries, which requires larger amounts of cargo aircraft in operation, and also catering to the growing number of middle and upper class passengers who travel for business and pleasure purposes. A rise in commercial aviation leads to the use of more aviation fuel on a monthly and annual basis. This in turn leads to escalated levels of combustion by-products from jet and turbofan engines into the atmosphere. The negative effects of these by-products range from producing poor air quality and consequent health hazards to contributing to global warming. This study is aimed at assessing the impacts of aircraft emissions on the local air quality in Corpus Christi using the Emissions and Dispersion Modeling System. Flight data for the study was obtained from the Department of Transportation's Research and Innovative Technology Administration. Analyses of the emissions were compared on monthly, annual, engine type and airline provider bases. Climatic, economic and anthropogenic factors were identified in the analyses.
Experimental Study on Fluidization of Biomass, Inert Particles, and Biomass/Sand Mixtures
Fluidization of biomass particles is an important process in the gasification, pyrolysis and combustion in order to extract energy from biomass. Studies on the fluidization of biomass particles (corn cob and walnut shell), inert particles (sand, glass bead, and alumina), which are added to facilitate fluidization of biomass, and biomass/sand mixture were performed. Experiments were carried out in a 14.5 cm internal diameter cold flow fluidization bed to determine minimum fluidization velocities with air as fluidizing medium. On the of basis of experimental data from both present work and those found in the literature, new correlations were developed to predict minimum fluidization velocity for inert particles as well as biomass particles. It was found that the proposed correlations satisfactorily predict minimum fluidization velocities and was in well agreement with experimental data. Furthermore, effect of weight percentage of biomass in the biomass/sand mixtures was studied. The weight fraction of biomass particles in the mixture was chosen in the range of 0 ~ 100 wt. %. The results show that minimum fluidization velocity of the mixtures increases with an increase in biomass content. Using the present experimental data, a new correlation was developed in terms of mass ratio for predicting values of minimum fluidization velocity of these mixtures. However, the validity of the proposed correlation should be further studied by conducting more experiments using the biomass/sand mixtures of different particle size, shape, and density.
High-Precision Micropipette Thermal Sensor for Measurement of Thermal Conductivity of Carbon Nanotubes Thin Film
The thesis describes novel glass micropipette thermal sensor fabricated in cost-effective manner and thermal conductivity measurement of carbon nanotubes (CNT) thin film using the developed sensor. Various micrometer-sized sensors, which range from 2 µm to 30 µm, were produced and tested. The capability of the sensor in measuring thermal fluctuation at micro level with an estimated resolution of ±0.002oC is demonstrated. The sensitivity of sensors was recorded from 3.34 to 8.86 µV/oC, which is independent of tip size and dependent on the coating of Nickel. The detailed experimental setup for thermal conductivity measurement of CNT film is discussed and 73.418 W/moC was determined as the thermal conductivity of the CNT film at room temperature.
Investigation of an Investment Casting Method Combined with Additive Manufacturing Methods for Manufacturing Lattice Structures
Cellular metals exhibit combinations of mechanical, thermal and acoustic properties that provide opportunities for various implementations and applications; light weight aerospace and automobile structures, impact and noise absorption, heat dissipation, and heat exchange. Engineered cell topologies enable one to control mechanical, thermal, and acoustic properties of the gross cell structures. A possible way to manufacture complex 3D metallic cellular solids for mass production with a relatively low cost, the investment casting (IC) method may be used by combining the rapid prototyping (RP) of wax or injection molding. In spite of its potential to produce mass products of various 3D cellular metals, the method is known to have significant casting porosity as a consequence of the complex cellular topology which makes continuous fluid's access to the solidification interface difficult. The effects of temperature on the viscosity of the fluids were studied. A comparative cost analysis between AM-IC and additive manufacturing methods is carried out. In order to manufacture 3D cellular metals with various topologies for multi-functional applications, the casting porosity should be resolved. In this study, the relations between casting porosity and processing conditions of molten metals while interconnecting with complex cellular geometries are investigated. Temperature, and pressure conditions on the rapid prototyping – investment casting (RP-IC) method are reported, thermal stresses induced are also studied. The manufactured samples are compared with those made by additive manufacturing methods.
Laminar Natural Convection From Isothermal Vertical Cylinders
Laminar natural convection heat transfer from the vertical surface of a cylinder is a classical subject, which has been studied extensively. Furthermore, this subject has generated some recent interest in the literature. In the present investigation, numerical experiments were performed to determine average Nusselt numbers for isothermal vertical cylinders (103 < RaL < 109, 0.5 < L/D <10, and Pr = 0.7) with and without an adiabatic top in a quiescent ambient environment which will allow for plume growth. Results were compared with commonly used correlations and new average Nusselt number correlations are presented. Furthermore, the limit for which the heat transfer results for a vertical flat plate may be used as an approximation for the heat transfer from a vertical cylinder was investigated.
Multi-year Operation Effect of Geothermal Heat Exchanger on Soil Temperature for Unt Zero Energy Lab
Ground source heat pump (GSHP) uses earth’s heat to heat or cool space. Absorbing heat from earth or rejecting heat to the earth, changes soil’s constant temperature over the multiple years. In this report we have studied about Soil temperature change over multiple years due to Ground loop heat exchanger (GLHE) for Zero Energy Research Laboratory (ZØE) which is located in Discovery Park, University of North Texas, Denton, TX. We did 2D thermal analysis GLHP at particular Depth. For simulation we have used ANSYS workbench for pre-processing and FLUENT ANYS as solver. TAC Vista is software that monitors and controls various systems in ZØE. It also monitors temperature of water inlet/outlet of GLHE. For Monitoring Ground temperatures at various depths we have thermocouples installed till 8ft from earth surface, these temperatures are measured using LabVIEW. From TAC Vista and LabVIEW Reading’s we have studied five parameters in this report using FLUENT ANSYS, they are; (1) Effect of Time on soil Temperature change over Multi-years, (2) Effect of Load on soil temperature change over Multi-years, (3) Effect of Depth on soil temperature change over Multi-years, (4) Effect of Doubling ΔT of inlet and outlet of GLHE on soil temperature change over multi-years and (5) Effect on soil temperature change for same ZØE Laboratory, if it’s in Miami, Florida. For studying effect of time on soil temperature change for multi-years, we have varied heating and cooling seasons. We have four cases they are Case A: GSHP always “ON” (1) 7 months cooling and 5 month cooling and (2) 257 days are cooling and 108 days heating. Case B: GSHP “OFF” for 2 months (1) 7 months cooling and 3 months heating and (2) 6 months cooling and 4 month heating. For Studying Effect of Load on soil temperature change over multi-years, we have considered maximum temperature difference between inlet and outlet for heating and cooling season for simulation. For studying effect of doubling ΔT of inlet and outlet of GLHE, we have doubled the temperature difference between inlet and outlet of GLHP. There will be soil temperature change over year at various depths. For studying Effect of Depth on soil temperature change for multi-years, we have consider 5 depths, they are 4ft, 6ft, 8ft, 110ft and 220ft. The Densities of soil are known from site survey report of ZØE GSHP manufacturers till depth of 13ft. For studying effect of soil temperature over multi-years for same ZØE in Miami, Florida, we have considered equivalent cooling and heating season from weather data for past one year and assuming same number of days of cooling and heating for next 20 years we have simulated for soil temperature change.
Quantification of Anthropogenic and Natural Sources of Fine Particles in Houston, Texas Using Positive Matrix Factorization
Texas, due to its geographical area, population, and economy is home to a variety of industrialized areas that have significant air quality problems. These urban areas are affected by elevated levels of fine particulate matter (PM2.5). The primary objective of this study was to identify and quantify local and regional sources of air pollution affecting the city of Houston, Texas. Positive Matrix Factorization (PMF) techniques were applied to observational datasets from two urban air quality monitoring sites in Houston from 2003 through 2008 in order to apportion sources of pollutants affecting the study region. Data from 68 species for Aldine and 91 for Deer Park were collected, evaluated, and revised to create concentration and uncertainty input files for the PMF2 and EPA PMF (PMF3) source apportionment models. A 11-sources solution for Aldine and 10-sources for Deer Park were identified as the optimal solutions with both models. The dominant contributors of fine particulate matter in these sites were found to be biomass burnings (2%-8.9%), secondary sulfates I (21.3%-7.6%) and II (38.8%-22.2%), crustal dust (8.9%-10.9%), industrial activities (10.9%-4.2%), traffic (23.1%-15.6%), secondary nitrates (4.4%-5.5%), fresh (1%-1.6%) and aged(5.1%-4.6%) sea salt and refineries (1.3%-0.6%), representing a strong case to confirm the high influence of local activities from the industrial area and the ship channel around the Houston channel. Additionally, potential source contribution function (PSCF) and conditional probability function (CPF) analyses were performed to identify local and regional source-rich areas affecting this urban airshed during the study period. Similarly, seasonal variations and patterns of the apportioned sources were also studied in detail.
Simulation Study of Tremor Suppression and Experiment of Energy Harvesting with Piezoelectric Materials
The objective of this research is to develop a wearable device that could harvest waste mechanical energy of the human hand movement and utilize this energy to suppress wrist tremors. Piezoelectric material is used to measure the hand movement signals, and the signal of wrist tremor is filtered to be utilized to suppress the tremor. In order to conduct the experiment of energy harvesting and tremor suppression, an experimental rig was fabricated. Two types of piezoelectric materials, PVDF (polyvinylidene fluoride) films and MFC (macro fiber composite) films, are used to harvest mechanical energy and used as actuators to suppress hand tremors. However, due to some shortages of the materials, these two types of materials are not used as actuators to suppress the wrist tremors. Thus, we use Matlab Simulink to simulate the tremor suppression with AVC (active vibration control) algorithm.
Thermal Characterization of Austenite Stainless Steel (304) and Cnt Films of Varying Thickness Using Micropipette Thermal Sensors
Thermal transport behavior of austenite stainless steel stripe (304) and the carbon nano-tubes (CNTs) films of varying thickness are studied using a micropipette thermal sensor. Micropipette sensors of various tip sizes were fabricated and tested for the sensitivity and reliability. The sensitivity deviated by 0.11 for a batch of pipette coated under same physical vapor deposition (PVD) setting without being affected by a tip size. Annealing, rubber coating and the vertical landing test of the pipette sensor proved to be promising in increasing the reliability and durability of the pipette sensors. A micro stripe (80µm × 6µm × 0.6µm) of stainless steel, fabricated using focused ion beam (FIB) machining, was characterized whose thermal conductivity was determined to be 14.9 W/m-K at room temperature. Similarly, the thermal characterization of CNT films showed the decreasing tendency in the thermal transport behavior with the increase in the film thickness.
Ultrafast Laser Sampling of a Plant Tissue and ion Conductivity Measurement for Investigation of Light Stress Generation Mechanisms
In this study we applied ultra-short laser pulses on a biological sample (Arabidopsis), in order to cut it precisely in a square pattern and subsequently use it for studying stress generation mechanisms. For this purpose, we utilized femtosecond laser pulses at 100 fs pulse width and 80 MHz repetition rate. We took two processing parameters into consideration such as laser power, laser exposure time which is related to the stage speed. Therefore, we were able to find the laser optimum conditions for ablation of biological tissues. The mutant and wildtype (control) obtained from laser cutting with a size of 500 µm × 500 µm were directly transferred (in-situ with laser cutting) into a microfabricated chamber containing ~500 nanoliters deionized water for measuring ion conductivity. The ion conductivity is a signature of cell-death mechanisms caused by various stresses. A light with intensity of 100 µmol was exposed to the samples for 2 hours and 20 minutes as a source of stress. A quantitative electrical analysis with high accuracy was assured by utilizing a microchamber, which enables a measurement in nanoliter volume. We measured the impedance which is reciprocal of conductivity using a lock-in amplifier and a precise current source at frequency of 130 Hz. Initially high impedance of mutant sample tended to drop within 2 hours and finally approached the constant value which signified that the cell death mechanism was complete. However, the wildtype sample demonstrated approximately constant impedance (conductivity) during the experiment.
Using a Multimodal Sensing Approach to Characterize Human Responses to Affective and Deceptive States
Different ways to measure human affective and deceptive reactions to stimulus have been developed. One method is a multimodal approach using web camera, thermal imaging camera and physiological sensors data to extract different features in the human face (verbal and non-verbal behavior) such as breathing rate, heart rate, face temperature, skin conductance, eye tracking, language analysis and facial expressions among others. Human subjects from different ages and ethnicity were exposed to two different experiments were they watched videos (affection recognition) and others answered an interview session (deception recognition). With the data collected from videos (thermal and visual), different regions of interest (ROI) of the face were selected as well as the whole picture. The ROI were determined based on the most sensitive parts of the face where larger changes of temperature or other physiological features are recorded. It was also analyzed the language (written and spoken) in order to obtain the verbal modalities. The data has been compared among the subjects to determine whether the deceptive and affective reactions of a person can be predicted using multimodal approach. From the multiple data obtained, a characterization of reactions is proposed when subjects are exposed to different stimulus, positive or negative, as well as deceptive behavior and later on recognize if the person is happy, sad, nervous, anxious, telling the truth, lying etc. Using the multimodal approach we were able to predict automatically, with higher accuracy than the baseline, affective and deceptive states of a person. In the affective state recognition, the classifier software differentiated affective state versus neutral state with 92.85% accuracy. Then it differentiated Positive State, Negative State and Neutral State with 57.14% accuracy. Additionally, it differentiated Positive State versus Negative State with 73.21% accuracy. Finally, the classifier was able to predict Deceptive State (people lying) and Non Deceptive State (people telling the truth) with 72.72% accuracy.
Using a Multimodal Sensing Approach to Characterize Human Thermal Comfort Level
A method to distinguish human level of comfort has been developed by using a thermal camera, physiological sensors, and a surroundings sensor. The method has successfully collected data from hominal facial features, breathing rate, skin temperature, room temperature, blood volume pressure, relative humidity, and air velocity. Participants from all genders and races were involved in two sessions of a human comfort experiment including a psychology survey session. The variables, such as room temperature and clothing are controlled to maintain steady test conditions. The region of interest was determined by body temperature and facial temperature as registered by the thermal imaging camera. To experience different levels of discomfort, participants were required to perform two different activities. The first session included an activity on the air resistance elliptical and the second session required the subjects to remain steady in front of a fan. The data was subsequently compared on all subjects to determine whether human discomfort and comfort can be predicted by using various approaches. The parameters of discomfort and comfort were simulated to characterize human levels of comfort. According to arrangement of correlation among thermal comfort responses, blood volume pressure, skin temperature, respiration, and skin conduction, we are be able to predict discomfort and comfort affective states.