Although fully automated modal analysis, a Structural Health Monitoring (SHM) technique, has recently been used to monitor the current condition of various civil structures, its application to transmission towers remains limited. Most modal analysis and dynamic characterization studies related to these towers, which are essential for first-level damage detection, still require manual selection of input parameter values. This research aims to contribute to the existing discussion by applying a machine learning algorithm to Stochastic Subspace Identification (SSI) to derive the modal parameters of a transmission tower, thereby improving similar studies. In addition to utilizing Random Forest as the core intelligence of the method, the research explores three other machine learning algorithms—XGBoost, Decision Trees, and k-Nearest Neighbors (KNN)—as alternative modal prediction models within the framework.

This paper presents the results of both analytical (PV stage) and operational (FI stage) modal analyses on a 230-kV transmission tower in Orion, Bataan, Philippines. Despite the limited sensor locations, ten frequency values extracted from the actual tower closely approximated those from analytical studies and predictions from related research. Significant differences were noted for damping ratios, which typically exhibit higher estimation uncertainty. However, the values obtained from the field test, which ranged from 0.68% to 3.02%, fell within the recommendations of international structural codes, such as the 4% suggested by ASCE 74. This study also demonstrates techniques for analyzing how environmental factors such as wind speed and temperature affect the modal parameters. Random Forest stands out among the machine learning models tested, showing the fastest runtime, highest performance accuracy, and smallest Coefficient of Variation values given random datasets, closely followed by XGBoost.

The results of this study can be used in model updating and structural design of transmission towers in the Philippines. They also serve as a baseline for future recordings, facilitating enhanced and data-driven post-disaster decision-making.

Regarding pressure-volume-temperature (PVT) thermodynamic property modelling, the Soave-Redlich-Kwong (SRK) and Peng-Robinson (PR) equations are known as the most successful equations of state to date, largely because of their simplicity and engineering flexibility. In an endeavor to improve volumetric and caloric predictions by the two foremost equations of state, attempts such as reworking the temperature dependencies of the attractive term, addition of volume translation terms, and derivation of mixing rules for mixture phase equilibria have been implemented. While such modifications have improved the predictive power of the two equations, the inherent weakness of a two-parameter cubic equation convinced researchers to develop more powerful equations which involve the modification of the volume dependency of the attractive term, recasting of the repulsion term to model rigid noninteracting spheres, and addition of equation of state parameters. In addition, attempts to generalize such equations in line with the corresponding states principle with moderate success. However, all these modifications come with the cost of thermodynamic inconsistency, mathematical complexity, and computational firepower required to execute the PVT equation. Herein, we aim to discuss the development of equations of state that can describe volumetric and caloric properties of classical fluids at enhanced ranges, keeping in mind thermodynamic consistency restrictions and mathematical rigor involved. As the development of the attractive term is largely empirical, numerical optimization will be employed to develop the optimal form of the volume dependency of the attractive term. Moreover, the determination of thermodynamically-consistent temperature dependencies for the attraction term will be considered. Once the optimal equations of state that can model pure-fluid behavior has been derived, the equations will then be generalized and extended to mixtures, in line with the corresponding states principle. Traditional one-fluid/binary interaction parameter methods and modern equation of state/activity coefficient techniques will be used along with the developed equations. Current mixing rules involving group contribution models may also be reworked to increase the utility of the derived equations of state. The performance of the proposed equations will then be compared to models known in literature for both pure classical fluids and mixtures. Should the proposed equations be proven to model fluids at a larger range than the contemporary equations of state available in literature, this can potentially lead to economic and environmental advantages due to less overdesign involved in process simulations and design.

This dissertation presents the development, validation, and application of a suite of computational tools primarily designed to model and characterize the responses of radiation detection materials to ionizing photons, with extensions to material dose distribution and shielding analysis that broaden their applicability to a wide range of scientific and industrial fields. The suite includes Detector Materials Simulations (DETMATS), Photon Transport and Response Characterization Kit (P-TReCK), and GaussSpectraSwift. DETMATS, an Excel-based VBA application using the EPICS2023 library, is benchmarked for calculating the efficiency of high-energy photon detection materials against PHITS 3.31, showing minimal relative differences across a range of photon energies for NaI(Tl) and LaBr3(Ce) detectors. The P-TReCK tool, developed in C# for Windows, simulates real-time spectrum analysis, material dose distributions, and shielding performance. It includes a specialized version for simulating true coincidence summing (TCS) effects, significantly improving accuracy in close source-detector geometries and material-specific responses. For example, when radioactive material TCS effects are modeled, P-TReCK and PHITS both show a 33% overestimation in 60Co detection efficiency if TCS is not considered in close source-detector configurations, highlighting the significant accuracy improvement achieved by incorporating TCS. This tool also calculates TCS correction factors for common radionuclides, with results showing a relative difference of less than 1% compared to recent literature values, demonstrating excellent agreement. In terms of speed, P-TReCK outperformed MCNP5 (basic physics) by 3.1x, MCNP5 (detailed physics) by 3.5x, PHITS 3.33 (basic physics) by 3.8x, PHITS 3.33 (detailed physics) by 4.2x, and DETMATS by 13x. Case studies demonstrate the versatility of P-TReCK in simulating gamma-ray detectors and material dose distributions. Simulations of irradiated material phantoms, with customizable material composition and density, were benchmarked using water, yielding an average relative difference of less than 0.5% compared to PHITS 3.341 and MCNP5. Additionally, simulations of various shielding materials for attenuating ionizing photons from an adjacent soft tissue model yielded a 1% average relative difference against PHITS 3.341 for incident photon energies between 300 keV and 2,000 keV. GaussSpectraSwift, a Windows application developed in C#, streamlines the modeling of realistic detector response spectra by performing energy-resolution curve fitting and Gaussian energy broadening (GEB) for Monte Carlo detector simulation applications. It shows high equivalence with SciPy and improved accuracy in broadening detector response spectra, as indicated by reduced RMSE of its output broadened spectra compared to ideal spectrum benchmarks. This capability enhances the modeling of energy resolution for radiation detection materials by using fitted models that capture the material's intrinsic properties along with the effects of electronics noise, which influence the detector's energy response. Overall, this research presents a suite of validated software tools that enhance the analysis and characterization of radiation detection materials, dose distributions, and shielding simulations, with applications across various scientific and industrial fields.

Materials degradation is inevitable and can lead to product failure, incurring loss of product integrity, costs, and even loss of life. While the degradation of monolithic materials has been extensively researched, the failure mechanisms of composite materials remain relatively unexplored. This study investigates the influence of storage aging and defect size on the fracture behavior of rubber composites, specifically for tire sidewall applications. By establishing baseline failure characteristics of fresh composites, this research identifies changes in fracture mechanisms and features as degradation progresses.
Carbon black (CB)-reinforced natural rubber/ butadiene rubber (NR/BR) composites were fractured via tensile load according to ASTM D 412. Fractographic analysis revealed consistent fracture initiation at the edge of dog-bone specimens, followed by the formation of distinct fractures, namely smooth zone, hackle marks, and rupture zone. The “cup-and-cone” fracture origin is indicative of localized shear that resulted to yielding and permanent plastic deformation before initiation of crack. Continued application of tensile load increased the concentrated stress at the origin equivalent to the ultimate tensile strength, initiating crack formation. The crack then propagated slowly through the material, creating a smooth region with faint tear lines. As the load increased, the crack propagation accelerated, forming hackle lines. This reduced the cross-sectional area of the material that could still carry the load, causing the bulk stress to approach its ultimate tensile strength and forming the rupture zone to complete the fracture. The measured ultimate tensile strength and fracture energy of the composites were 15.77 ± 0.58 MPa and 61.08 ± 6.47 J/mm3, respectively.
Exposure to ambient conditions (20-28°C, 55-90% RH) for up to three years significantly degraded the fracture strength of the composites by 37%. While fractographic features remained similar, the fracture origin shifted away from the edge or surface. This suggests that environmental aging, likely due to oxidation brought about by oxygen diffusion from surrounding environment, induced chain scission and crosslink rupture which are typical consequences of oxidation of polymers. Consequently, structural defects formed, acting as nucleation sites for crack initiation. Reduced crosslink density further compromised the material's resistance to crack propagation, leading to premature failure compared to unaged samples.
Considering that defects formed during aging, the influence of defect size on failure mechanisms of notched rubber composites subjected to Mode-I tearing. Compared to unnotched samples, tear lines at the previously identified smooth zone became more pronounced, and secondary crack planes developed parallel to the load direction. The E-strain plot, representing the rate of stress change with respect to strain (dσ/dε), was analyzed to assess crack growth resistance. Distinct regions in the plot were identified, namely strain softening (Payne effect), minimum modulus (Emin), stress upturn, modulus plateau (Eplateau), and fracture. The introduction of a 1mm-notch resulted in the reduction of strain of the Eplateau leading to faster occurrence of fracture as compared to unnotched specimens. At 3mm-notch, fracture occurred after stress upturn whereas immediate fracture occurred at Emin with 5mm-notch. With increasing defect size, the stress concentration at the crack tip also increases such that the strain stiffening contributed by the crosslinks and rubber chains could no longer resist the crack propagation and eventual fracture. Consequently, tearing energy decreased with increasing notch size, from a critical value of 0.239 ± 0.058 J/mm2 for a 3mm notch. Moreover, aging reduced tearing energy up to 73% after two years, highlighting the material's decreased resistance to fracture under both tensile and tearing loads.
This research concludes that environmental aging significantly deteriorates the mechanical properties and fracture resistance of rubber composites. While the overall fracture features remain unchanged, internal defects become more potent in initiating cracks. Future studies should investigate the effects of aging on fracture behavior under dynamic loading conditions and with various filler types and formulations to better understand how aging impacts rubber material performance. This knowledge is crucial for developing more durable rubber components.

The current trend of Horizontal Axis Wind Turbines (HAWT) with respect to energy extraction is towards higher diameter which needs to operate at a wind speed of 15m/s to maximize efficiency. On the other hand, while the Philippines Wind Settings predominantly exhibit 4 m/s, maximum wind speeds is only around 10m/s. Current studies have also showed that extracting energy from these low-level wind speeds is a challenge without utilization of Wind Turbine Augmentation Devices. Relatedly, one of the known wind turbine augmentation techniques is the “shrouding” of HAWT, sometimes called Ducted HAWT. In this regard, a numerical investigation was conducted on the performance of Ducted HAWT using blade design in the study of Alkhabbaz, et al., (2022). The calculations yield average accuracy of 10.83% using Steady-state formulations as opposed to the previous study’s 12.43% that used Transient formulations, a reduction of 1.60%. The CFD calculations were then performed for a Ducted HAWT configuration with the low-reynolds Selig-family Airfoil S7055 as the duct cross-section. It was found out that maximum C_p is 0.4325 at 955 RPM on its design wind speed of 7m/s, an increase of 30.22% from Open Rotor experimental results. Finally, a comparison of Open Rotor HAWT and Inlet-scaled Open Rotor HAWT with the Ducted HAWT was performed. The comparison yielded that Ducted HAWT has an overall superior performance even at low wind speeds with an increase of as high as 44.14% at 4 m/s in TSR = 5 (optimal operational speed). However, thrust levels have been seen to also increase as a high as 30.74% in TSR = 2 at 10 m/s. Generally, the increase in thrust levels is offset by the increase in power generation thereby exhibiting superior performance of Ducted HAWT with minimal aerodynamic tradeoffs.