Journal of Experimental and Theoretical Analyses

Aluminum light poles are essential components of modern infrastructure, providing illumination for highways, urban areas, and pedestrian pathways. Despite their importance, structural vulnerabilities in handholes—necessary for electrical access—can reduce fatigue life due to the structure’s response to wind. This study addresses a critical gap in translating laboratory-derived S–N data into field-applicable methods for assessing cumulative damage in these structures. A probabilistic cumulative damage analysis framework was developed to quantify the structural degradation of handholes due to variable wind velocities. Using a series of controlled cyclic fatigue tests and Miner’s Rule, the study establishes a methodology to convert stress ranges into equivalent wind velocities and correlate laboratory cycle counts with real-world loading conditions. The findings reveal a logarithmic progression of damage accumulation and highlight the utility of integrating standardized factors from ASCE-7 for scalable and geographically adaptable assessments. A proof-of-concept application demonstrates the model’s potential to predict failure risks during extreme wind events, such as hurricanes and tornadoes. This research provides a practical and predictive tool for engineers and contractors to evaluate the structural integrity of aluminum light poles, enabling proactive maintenance and reducing unplanned failures.

This study addresses the critical challenge of variable image quality in deep learning-based automated pest identification. We propose a holistic pipeline that integrates systematic Image Quality Assessment (IQA) with tailored preprocessing to enhance the performance of a YOLOv5 object detection model. The methodology begins with a No-Reference IQA using BRISQUE, PIQE, and NIQE metrics to quantitatively diagnose image clarity, noise, and distortion. Based on this assessment, a tailored preprocessing stage employing six different filters (Wiener, Lucy–Richardson, etc.) is applied to rectify degradations. Enhanced images are then used to train a YOLOv5 model for detecting four common pest species. Experimental results demonstrate that our IQA-anchored pipeline significantly improves image quality, with average BRISQUE and PIQE scores reducing from 40.78 to 25.42 and 34.94 to 30.38, respectively. Consequently, the detection confidence for challenging pests increased, for instance, from 0.27 to 0.44 for Peach Borer after dataset enhancement. This work concludes that a methodical approach to image quality management is not an optional step but a critical prerequisite that directly dictates the performance ceiling of automated deep learning systems in agriculture, offering a reusable blueprint for robust visual recognition tasks.

Roll-to-roll production of thin organic and large-area electronic (TOLAE) devices often involves a two-step process per functional layer: a continuous, un-pattered deposition of the film and subsequent structuring process, such as laser ablation. Thin-film organic devices should be protected using ultra-barrier films. To perform laser ablation of functional layers on top of such barrier films, in particular that of transparent electrodes, highly selective laser ablation is required to completely remove the layers without damaging the thin-film barrier layers underneath. When targeting highly selective laser ablation of indium tin oxide (ITO) on top of silicon nitride (SiN) barrier layers with a 1064 nm picosecond or 1030 nm femtosecond laser, we observed the emergence of visible large-scale patterns due to local variations in ablation quality. Our investigations using a very sensitive Raman spectroscopy setup show that the observed ablation variations stem from subtle differences in optical path length within the heat-stabilized plastic substrates. These variations are likely caused by minute, localized changes in the refractive index, introduced during the bi-axial stretching process used in film fabrication. Depending on the optical path length, these variations lead to either constructive or destructive interference between the incoming laser beam and the light reflected from the back surface of the substrate. By performing laser ablation under an angle such that the reflected and incoming laser beam do not spatially overlap, highly selective uniform laser ablation can be performed, even for two stacked optically transparent layers.