College of Engineering

Theses and dissertations submitted to the College of Engineering

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Coal, the primary energy fuel in the Philippines, is comprised of 32.2% of the
country’s installed capacity and can grow up to as much as 42% by 2040 base on DOE’s
projection. Coal combustion in power plants produces emissions including carbon dioxide
(CO2), particulate matter (<2.5μm in diameter) (PM2.5), oxides of nitrogen (NOx) and
oxides of sulfur (SOx). These emissions have been established to negatively affect human
health by contributing to the increase in number of cases of cardiovascular and respiratory
disease. This study aims to estimate the life cycle health impacts of air emissions from
coal-based power plants in Luzon. The analysis covers mining, transportation, and energy
conversion stages of the life cycle. Past emission estimates from countries like Japan,
China and Netherlands vary due to factors such as differences in estimation methods,
working conditions and quality of coal used. The estimates for the health impacts also vary
due to factors such as differences in estimation methods, concentration of initial pollutants,
populations’ response to the change in pollution concentration, and the number of deaths
per incidence case of a health effect. Estimated health impacts from this study can used for
future researches and decision making analysis on the best generation technology towards
sustainable development in the Philippines. Performing life cycle analysis allows the
decision makers to identify which part of the life cycle has the highest impact on health.
Identifying the stage that has the most impact will allow the decision makers to efficiently
target the areas for improvement. The method used in this research can also be used as
a model for other research considering the health impacts of other generation technologies.
Pulverized subcritical coal (PC) and Circulating Fluidized Bed (CFB) technologies were
analyzed using 1 kWh functional unit. The emissions considered were CO2, PM2.5, NOx
and SOx. The emissions were categorized as global warming potential, particulate matter
formation potential and photochemical oxidation formation potential. To measure the
health impact of coal fired power plants the values obtained from each impact categories
were multiplied by a corresponding characterization factor to get Disability-adjusted life
years (DALY) per kWh of generated electricity. Most data used in the analysis were
obtained from the Energy Regulatory Commission, National Energy Technology
Laboratory’s life cycle inventory database and the Department of Energy. Average
emissions for Pulverized subcritical coal power plants were estimated at 1.82 g of
PM2.5/kWh, 7.73 g SOx/kWh, 2.49 g NOx/kWh and 957.92 g CO2/kWh while average
emissions for CFB were estimated at 2.76 g of PM2.5/kWh, 7.35 g SOx/kWh, 1.14 g
NOx/kWh and 1292.38 g CO2/kWh. The average health impacts of PC and CFB are 1.82 x
10-6 DALY/kWh and 2.45 x 10-6 DALY/kWh, respectively. Sensitivity analyses indicate
that to reduce the health impacts of coal fired power plants the emission from energy
conversion stage must be minimized and the emission that has the highest health impact is
particulate matter. This can be achieved by using Pulverized coal power plants with
tangential burners, and the following emission control technologies low NOx burners, Wet-
FGD and Fabric Filter.

This paper aims to develop a Graphical Footprint Model (GFM) that will validate radio frequency (RF) energy harvesting capabilities of radio frequency (RF) energy sources, such as frequency modulation (FM), television (TV), and cellular technology (Cell) for validation of RF at different classified multiple urban settings. The GFM is composed of scoring scheme for energy capabilities, which is based on a -20dBm and up of Power Received Levels (PRL) at different classified multiple urban settings, which includes Line of Sight (LOS), Rural (R), Suburban (S), Urban High (UH), Urban Very High (UVH), and Non-Line of Sight (NLOS) settings. The Communications Engineering Formula Budget link was used to get the PRL for RF potentials in dBm, to determine the classified multi-settings together with the RF sources for RF harvesting capabilities.

In establishing a benchmark for the GFM, a review of twenty one research studies was undertaken for data analytics. The result of the exercise showed a percentage acceptability range of 84.00 % with a Mean Square Error (MSE) of 14 along a mean average distance accuracy range of 1451 meters. To determine whether the GFM can predict heuristically with the use of a weighted mean, the analysis covered spread-out data points over a large range of values, considering a standard deviation of 3091. The grand mean obtained was an intensity score of 3, with the initial voltage range from 70mV to 125 mV. This is a very good level for GFM to predict heuristically the RF potential.

In a classified Line of sight multiple setting area, the farthest average distance radius of RF energy potentials from television (TV), frequency modulation (FM), and cell sources are 2768, 2175, and 127 meters respectively, with an intensity score of 1 (Fair level with an initial voltage of 22mV to 40mV for RF potential). On the other hand, in a classified Urban Very High (UVH) multiple setting, the farthest distance for RF potential from a TV source is 1110 meters, from FM source at 950 meters and from a cell source at 76 meters, all with an intensity score of 1. Through the GMF, farthest point as well as the nearest point for RF potential, its corresponding scores, initial voltages and powers can be determined.

The GFM will benefit future design engineers and installers of RF harvesters. GFM can provide them the necessary information to determine the locations and distances for RF potential emitted from FM, TV, and Cell energy sources in different classified multiple settings. GFM serves as a smart and useful tool for design considerations of RF harvester modules that have application in Internet of Things (IoT) and other devices that need only a minimal amount of power.

Recent studies have focused on the detrimental effects of earthquakes on the bearing capacity of shallow foundations. According to Terzaghi’s classical theory, the bearing capacity of a shallow strip foundation is the superposition of three contributing factors, namely, the cohesion of the soil (Nc), the unit weight of the soil (Nγ), and the soil surcharge (Nq). The kinematic element method (KEM) based on the upper-bound limit analysis theory has shown potential in solving soil stability problems through simple kinematics, statics, and optimization. This research aims to assess the static and seismic bearing capacity of shallow strip foundations using the kinematic element method – particle swarm optimization (KEM-PSO) along with the traditional pseudo-static approach, comparing the results with the Analysis of Bearing Capacity (ABC) program, and existing literature solutions. Additionally, the study investigates the validity of the superposition of effects principle by comparing separate soil and superstructure inertia with the combination of the two. The results reveal an overestimation of the static bearing capacity factor Nγ but a negligible difference for Nq and Nc compared to the ABC program. The discrepancy is attributed to the limitations of the KEM in considering the distribution of stresses within the soil mass surrounding the foundation and in discretizing the failure mechanism. Similarly, the seismic bearing capacity factors Nγ and Nq are overestimated. The study proposes quadratic and bi-quadratic correction factors for the static and seismic cases using the Levenberg-Marquardt non-linear least squares methods. The corrected values align well with the available literature solutions. Thus, KEM-PSO and the correction factor functions can serve as a design tool for shallow strip foundations' static and seismic bearing capacity. The study validates the superposition of the inertia effects principle, enabling different seismic loads assigned to the soil and superstructure.

Desorption and back diffusion of a chlorinated solvent such as trichloroethylene (TCE) from the low permeability zone (LPZ) to the transmissive zone in the subsurface exhibits a challenge in remediation. The study was to investigate the in situ chemical oxidation (ISCO) using a sodium persulfate sustained-release rod (SPS SR-rod) for potential remediation application of TCE contamination in the LPZ within a two-dimensional sand tank. The objective was to determine the SPS concentration distribution contour when placing the SPS SR-rod atop and within the LPZ. A laboratory scale, 2D tank system (100 cm L x 5 cm W x 50 cm H) represents a distinct type of LPZ in the geologic settings, exhibiting a saturated dual permeability porous media. The SPS SR-rod placed within the LPZ released an average ~625 mg L-1 concentration contour from at least 10 to 15 cm lateral distance from the rod. When the rod placement was atop LPZ, continuous determination of persulfate concentrations at an average value of ~57 mg L-1 within the LPZ was observed comparably at low and high hydraulic gradients of 0.01 and 0.05, respectively. A separate evaluation of both SPS SR-rod placements in the 2D sand tank injected with pure TCE is conducted to test if the oxidant perfusion can address the difficulties in destroying soil-sorbed TCE. It took five days for sorption-desorption from the injection point to occur. On the 10th and 15th days, the concentrations of TCE exceed the groundwater limit of 0.05 mg L-1 set by Taiwan. Comparably lower concentrations are observed in the HPZ following back diffusion and concentration gradient principles where lower mass flux results in lower resultant aqueous concentration. In the presence of an SPS SR-rod, TCE concentration measures up to 0.6 mg L-1 versus 1.4 mg L-1 when no SPS rod is present. The persistence of persulfate in the LPZ and its slow release in the subsurface supports that the SPS SR-rod may be an efficiently controlled release material in extending the ISCO remediation of TCE in low-concentration scenarios in LPZ and its surrounding environment. This approach allows for efficient and effective remediation and limited loss of oxidant mass during delivery while minimizing the risk of adverse effects or excessive chemical usage.

Titanium dioxide (TiO2) is an n-type semiconductor that is commonly used as an optoelectronic material due to its high stability. These applications include as photocatalysts and as photovoltaic devices. However, TiO2 has poor absorption in the
visible-light region. Hence, to improve its visible light sensitivity, TiO2 can be doped with nitrogen (N). Doping TiO2 with N also exhibits p-type conductivity.
Tin oxide (SnO2) is an n-type semiconductor that is also used as an optoelectronic material. Coupled together, the two can form a heterojunction. In this study, 120-nm thick SnO2 films are deposited on 250-nm thick N-doped TiO2 films grown on silicon dioxide substrates. N-doped TiO2 is produced by reactive sputter deposition of titanium nitride (TiN) films with post-deposition annealing.
Grazing incidence X-ray diffraction, X-ray photoelectron spectroscopy, and energy dispersive X-ray spectroscopy confirmed the formation of N-doped TiO2 when TiN is annealed at 450◦C. Interstitial doping was considered to be the major doping mechanism. UV-vis spectral analysis showed an increase in absorbance in the visible light region with a shift in the optical band gap from 3.33 eV for TiN to 2.51 eV for N-doped TiO2. Hall effect measurements revealed TiN and N-doped TiO2 film resistivities on the order of 10−4 Ω-cm. Carrier densities are on the order of 1021 cm−3. Carrier mobilities up to around 45 cm2 V−1 s−1. Sheet resistances below 6 Ω sq−1. For annealed SnO2 film, resistivity was around 0.091 Ω-cm, electron carrier density of around 1019 cm−3, carrier mobility around 2 cm2 V−1 s−1, and sheet resistance around 8000 Ω sq−1. The current-voltage characteristic of the SnO2-N-doped TiO2 heterojunction thin films exhibited a rectifying behavior under dark and light illumination.