Afshar Kasaei

Through the advancement of Data Science methodologies, a new era in output-only identification techniques has been inaugurated, driven by the integration of data-driven methodologies within the realm of Structural Health Monitoring (SHM). This study endeavors to introduce a simplified data-driven approach catering to System Identification (SI) and Response Estimation (RE). This is realized through the utilization of a summation of sine functions, fashioned as a model to harmonize with time domain vibration and acoustic responses. The fidelity of the findings is subsequently authenticated through the application of the Frequency Domain Decomposition (FDD) technique. In addition to the identification process, the proposed approach extends its applicability to predicting time domain responses at novel locations. This augmentation is achieved by harnessing an enhanced methodology founded on the principles of the Dynamic Mode Decomposition (DMD) technique. The veracity of these predicted outcomes is underscored through a comparison with measurements recorded at the same locations, alongside concurrent analysis of DMD-derived results. In order to affirm the efficacy of the proposed methodology, a case study involving a building grappling with enigmatic vibration issues is meticulously selected. The findings underscore that the proposed technique not only adeptly discerns unidentified vibrations without resorting to frequency domain transformation techniques, but also facilitates precise estimation of time domain responses.

As the aviation industry seeks sustainable propulsion solutions, innovative technologies have emerged, among which rim-driven fan (RDF) systems hold notable promise. This comprehensive review paper deeply investigates RDF technology, uncovering its principles, benefits, and transformative potential for aviation propulsion. Amid escalating concerns about greenhouse gas emissions, the aviation sector’s shift towards electric propulsion has gained impetus. RDF technology has emerged as a beacon of optimism, heralding the prospect of energy-efficient and eco-conscious air travel. Navigating the slower development pace of RDF technology for aerospace applications, this paper draws insights from analogous marine technologies and relevant literature. Merging these realms, this paper meticulously examines RDF systems, spotlighting their unique attributes, with particular emphasis on the rim-driven configuration and its fundamental design principles. This review delves into the progressive strides accomplished in RDF’s evolution, encompassing the spectrum from evolving electric motor variants to intricate design considerations, strategic noise and vibration management, innovative control methodologies, advancements in bearing technology, and the strategic integration of finite element analysis (FEA) and computational fluid dynamics (CFD) for comprehensive performance optimization. In the context of aviation’s electrification journey, the exploration of RDF technology marks a pivotal inflection point. This paper concludes by succinctly encapsulating pivotal insights, accentuating RDF technology’s central role in reshaping aviation’s propulsion paradigm. As the aviation sector charts a course towards sustainable progress, the lessons gleaned from RDF technology are poised to chart the trajectory of aviation’s environmental transformation.

This article presents an innovative application of the frequency domain decomposition method based on an acoustic and vibration response. Frequency domain decomposition method has been frequently used for operational modal analysis testing in the last decade to identify modal parameters for in-situ case studies. For these studies, the outputs of the vibration response through accelerometers have been employed in the analysis. In this article, the frequency domain decomposition method is employed, for the first time, to analyze both acoustic and vibration response of the building which is a novel application in building vibration response. As a case study, a cylindrical shaped seven-story building, which appears to be subjected to a vibration problem, was selected. In this research, both acoustic and vibration responses are captured to determine the source of this unknown excitation. The results show that using microphones, as an acoustic response, can be as reliable as accelerometers to identify forced vibration.