Noise Measurement of a Wind Turbine using Thick Blades with Blunt Trailing Edge

The noise generated by wind turbines can potentially cause significant harm to the ecological environment and the living conditions of residents. Therefore, a proper assessment of wind turbine noise is crucial. The IEC 61400-11 standard provides standardized guidelines for measuring turbine noise, facilitating the comparison of noise characteristics among different wind turbine models. This work aims to conduct a comprehensive noise measurement of a 100kW wind turbine using thick blades with blunt trailing edge, which differs from the typical turbines studied previously. The work takes into account the unique design and dynamic characteristics of small-scale wind turbines and adjusts the measurement accordingly, with deviations from the IEC standards will be explicitly addressed

Experimental Investigation of Airfoil Trailing Edge Noise Reduction by using TE Serrations

The growing prominence of aerodynamic noise from wind turbine blades at high wind speeds has made it the primary source of noise for wind turbines, with adverse effects on nearby residents' living conditions. This study focuses on experimental research conducted in an anechoic wind tunnel to investigate the noise reduction mechanism of wind turbine blade airfoils using serrated trailing edges, aiming to contribute to the development of low-noise wind turbine blades. Three models, including two types of NACA series airfoils and one reference plate with attachable serrated trailing edges, were tested. The findings reveal that airfoils with serrated trailing edges exhibit a 3 to 6 dB reduction in the mid-high frequency wideband noise, with the width of the frequency band of noise reduction slightly increasing as the Reynolds number rises. The presence of serrations also eliminates multiple tones of high amplitude exceeding 10 dB. The study highlights serration height as the most influential factor for noise reduction, surpassing the significance of serration width and the ratio of width to height. Moreover, investigations into the noise reduction mechanism indicate varying degrees of reduction in streamwise fluctuating velocity spectra near the serrated trailing edge, even aligning with changes in the sound power spectra. Serrations were found to alter the turbulence length scale in the downstream flow field, potentially impacting noise generation. This study suggests that the reduction in streamwise fluctuating velocity near the serrated trailing edge plays a crucial role in noise reduction, highlighting the importance of detailed flow field measurements and analysis for a comprehensive understanding of the mechanistic relationship between flow changes and serration-induced noise reduction

CPU-GPU Heterogeneous Code Acceleration of a Finite Volume Computational Fluid Dynamics Solver

This work deals with the CPU-GPU heterogeneous code acceleration of a finite-volume CFD solver utilizing multiple CPUs and GPUs at the same time. First, a high-level description of the CFD solver called SENSEI, the discretization of SENSEI, and the CPU-GPU heterogeneous computing workflow in SENSEI leveraging MPI and OpenACC are given. Then, a performance model for CPU-GPU heterogeneous computing requiring ghost cell exchange is proposed to help estimate the performance of the heterogeneous implementation. The scaling performance of the CPU-GPU heterogeneous computing and its comparison with the pure multi-CPU/GPU performance for a supersonic inlet test case is presented to display the advantages of leveraging the computational power of both the CPU and the GPU. Using CPUs and GPUs as workers together, the performance can be improved further compared to using pure CPUs or GPUs, and the advantages can be fairly estimated by the performance model proposed in this work. Finally, conclusions are drawn to provide 1) suggestions for application users who have an interest to leverage the computational power of the CPU and GPU to accelerate their own scientific computing simulations and 2) feedback for hardware architects who have an interest to design a better CPU-GPU heterogeneous system for heterogeneous computing

PaLI: A Jointly-Scaled Multilingual Language-Image Model

Effective scaling and a flexible task interface enable large language models to excel at many tasks. PaLI (Pathways Language and Image model) extends this approach to the joint modeling of language and vision. PaLI generates text based on visual and textual inputs, and with this interface performs many vision, language, and multimodal tasks, in many languages. To train PaLI, we make use of large pretrained encoder-decoder language models and Vision Transformers (ViTs). This allows us to capitalize on their existing capabilities and leverage the substantial cost of training them. We find that joint scaling of the vision and language components is important. Since existing Transformers for language are much larger than their vision counterparts, we train the largest ViT to date (ViT-e) to quantify the benefits from even larger-capacity vision models. To train PaLI, we create a large multilingual mix of pretraining tasks, based on a new image-text training set containing 10B images and texts in over 100 languages. PaLI achieves state-of-the-art in multiple vision and language tasks (such as captioning, visual question-answering, scene-text understanding), while retaining a simple, modular, and scalable design

Molecular cytogenetic, epigenetic and tissue dynamic study of gestational trophoblastic disease

published_or_final_versionPathologyDoctoralDoctor of Philosoph

Aeroacoustic Source Localization

The deconvolutional DAMAS algorithm can effectively eliminate the misconceptions in the usually-used beamforming localization algorithm, allowing for more accurate calculation of the source location as well as the intensity. When solving a linear system of equations, the DAMAS algorithm takes into account the mutual influence of different locations, reducing or even eliminating sidelobes and producing more accurate results. This work first introduces the principles of the DAMAS algorithm. Then it applies both the beamforming algorithm and the DAMAS algorithm to simulate the localization of a single-frequency source from a 1.5 MW wind turbine, a complex line source with the text "UCAS" and a line source downstream of an airfoil trailing edge. Finally, the work presents experimental localization results of the source of a 1.5 MW wind turbine using both the beamforming algorithm and the DAMAS algorithm