WeChat Mini Program
Old Version Features

Scaling Effects of Increased Annular Diameter in a Rotating Detonation Rocket Engine

AIAA SCITECH 2023 Forum(2023)

Jacobs Technology Inc

Cited 2|Views5
Abstract
As scaling of rotating detonation rocket engines becomes increasingly important for transition from laboratory-scale experiments to application-based testing and flight demonstrations, scaling methodologies must be studied and tested. In this study, a 76.2~mm RDRE is scaled up to a 101.6~mm annulus, proportionally scaling the injection area such that the ratio of the annulus area to the injection area is constant. This enables similar injector response for both geometries. Additionally, as symmetric injector response has been shown to be important to RDRE operation, a new injector is designed that provides axial net-momentum balance and symmetric plenum pressures around phi=1.2. These three geometries are compared on the basis of their operability limits, system pressures, detonation wave propagation and global performance. It is shown that the scaling methodology used produces an engine that provides similar performance at equivalent total mass flux, and also demonstrates that the momentum-balanced injector with greater injection area provides the same global performance with significantly reduced plenum pressures and increased detonation wave speed.
More
Translated text
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper

要点】:本文研究了旋转爆轰火箭发动机(RDRE)在增加环形直径时的缩放效应,提出了一种新的缩放方法和对称的注射器设计,以保持相似的性能和操作极限。

方法】:通过将76.2毫米的RDRE环形直径放大到101.6毫米,并按比例放大注射面积,保持环形面积与注射面积之比恒定,同时设计了一种新的注射器,实现了轴向净动量平衡和对称的储室压力。

实验】:研究比较了三种几何结构在操作性极限、系统压力、爆轰波传播和全局性能方面的差异,使用的数据集为不同尺寸RDRE的实验数据,结果表明所采用缩放方法能保持相似性能,且新的动量平衡注射器在降低储室压力和提高爆轰波速度方面表现出显著优势。