Acoustics

The operational phase of offshore wind farms, lasting up to 20–25 years, exceeds the construction phase in duration. The ecological effects of underwater noise demand serious consideration, necessitating urgent research into its acoustic characteristics. This review conducts a systematic analysis of measurements of underwater noise from operational offshore wind farms, considering the correlations between turbine noise and distance, wind speed, turbine power, and foundation type. Propagation distance is the most critical factor influencing the underwater sound pressure level (SPL) of wind turbines, exhibiting a negative correlation with the SPL, with an attenuation of approximately 20.4 dB/decade. In contrast, wind speed and turbine power show a positive correlation with the SPL, with increase rates of 18.5 dB/decade and 12.4 dB/decade, respectively. Further analysis shows that foundation type and drive technology also have a significant impact on underwater SPL. With technological innovation, specifically the upgrade from conventional geared drive to direct-drive technology, the level of underwater noise can be reduced by approximately 9 dB, with the primary peak frequency being shifted to a lower range. Moreover, significant variations in SPLs were noted with the utilization of various types of foundation structures, with monopile foundations exhibiting the highest SPLs of underwater noise. These conclusions have important reference value for the scientific assessment of the health of aquatic organisms and ecosystems.

The accurate diagnosis of acoustic defects and the precise assessment of the performance of building components are highly dependent on massive amounts of sampling data. In this study, we try to combine the compressed sensing theory with the nearfield acoustic holographic sound insulation measurement method and introduce a noise reduction algorithm so as to realize the sound pressure distribution accuracy similar to that of the conventional sampling under low-density data conditions. Numerical simulation results show that the reconstruction error of the method proposed in this paper is only 8.21% higher than that of the complete sampling under the condition of 20% sampling rate, and the reconstruction error is only 2.50% higher than that of the complete sampling under the condition of 40% sampling rate. The reconstruction error under 50% sampling rate and 6.65 dB SNR is only 4.81% higher than the complete sampling, which is basically consistent with the numerical simulation; the sound insulation is only 1 dB lower than that measured by the sound pressure method, and the acoustic defects of the components can basically be identified. The results of this study have a positive significance in simplifying the process of sound insulation measurement in most scenarios.

Urban soundscapes are complex due to the interaction of different sound sources and the influence of structures on sound propagation. Moreover, the dynamic nature of sounds over time and space adds to this complexity. Virtual reality (VR) has emerged as a powerful tool to simulate acoustic and visual environments, offering users an immersive sense of presence in controlled settings. This technology facilitates more accurate and predictive assessment of urban environments. It serves as a flexible tool for exploring, analyzing, and interpreting them under repeatable conditions. This study presents a systematic literature review focusing on research that integrates VR technology for the audiovisual reconstruction of urban environments. This topic remains relatively underrepresented in the existing literature. A total of 69 peer-reviewed studies were analyzed in this systematic review. The studies were classified according to research goals, selected urban environments, VR technologies used, technical equipment, and experimental setups. In this study, the relationship between the tools used in urban VR representations is examined, and experimental setups are discussed from both technical and perceptual perspectives. This paper highlights existing challenges and opportunities in using VR to assess soundscapes and offers practical insights for future applications of VR in urban environments.