OVERVIEW OF THE BEST 2020 AXIAL-FLOW FAN DATA AND INCLUSION IN SIMILARITY CHARTS FOR THE SEARCH OF THE BEST DESIGN

The paper deals with the aerodynamic performance of ducted axial-flow fans available in the 2020 market and aims to create a general picture of the best designs and design trends, as a tool for fan designers. To this end, the paper first presents the general formulation of the similarity approach to the fan performance analysis, including the effects of rotational speed (which affects the validity of the Reynolds similarity) and turbomachine size (which can hinder the perfect geometrical similarity of some shape details). The second part reports a statistical survey of the axial-flow fan performance based on data from catalogues of major manufacturers, and compares the resulting Cordier-lines with optimum fan designs from empirical or CFD-based models available in the literature. In addition to the global performance at maximum aeraulic and total-to-static efficiencies, this survey uses the form of dimensionless Balje-Cordier charts to identify the trends and values of other design parameters, such as hub-to-tip ratio, blade count, and blade positioning angle. As a result, a summary of the aerodynamic performance of year 2020 best designs, the improvements achieved during the last forty years, and the present design trends in contra-rotating, vane-axial, and tube-axial fan types are made available to fan designers.

Computational Investigation of a Novel Box-Wing Aircraft Concept

With regard to the current needs for greener aviation, this study focuses on a novel concept of Box-Wing Aircraft (BWA). Labelled SmartLiner (BWA/SL), this conceptual aircraft comes as a triplane comprising backward and forward swept wings. The aerodynamic performance and structural characteristics of this BWA/SL aircraft are here explored through numerical simulation, using Computational Fluid Dynamics (CFD) and Fluid-Structure Interaction (FSI). The computational approach is first validated using NASA’s Common Research Model (CRM) aircraft, which is then taken as a reference solution against which to compare the aero-structural merits of the BWA/SL concept. Results show that, although its design is still preliminary and lacks optimization, the BWA/SL aircraft exhibits very decent aerodynamic performance, with higher lifting capacities and a reasonable lift-to-drag ratio. Moreover, thanks to the closed frame of its peculiar planform, it demonstrates superior structural characteristics, including under extreme loading scenarios. Based on this preliminary analysis and considering the room left for its further optimization, this conceptual aircraft thus appears as a potentially promising alternative for the development of more environmentally friendly airliners.

LETR: An End-to-End Detector of Reconstruction Area in Blade’s Adaptive Machining with Transformer

In the leading/trailing edge’s adaptive machining of the near-net-shaped blade, a small portion of the theoretical part is retained for securing aerodynamic performance by manual work. However, this procedure is time-consuming and depends on the human experience. In this paper, we defined retained theoretical leading/trailing edge as the reconstruction area. To accelerate the reconstruction process, an anchor-free neural network model based on Transformer was proposed, named LETR (Leading/trailing Edge Transformer). LETR extracts image features from an aspect of mixed frequency and channel domain. We also integrated LETR with the newest meta-Acon activation function. We tested our model on the self-made dataset LDEG2021 on a single GPU and got an mAP of 91.9\%, which surpassed our baseline model, Deformable DETR by 1.1\%. Furthermore, we modified LETR’s convolution layer and named the new model after GLETR (Ghost Leading/trailing Edge Transformer) as a lightweight model for real-time detection. It is proved that GLETR has fewer weight parameters and converges faster than LETR with an acceptable decrease in mAP (0.1\%) by test results.