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1 – 7 of 7Ainslie French, Luigi Cutrone, Antonio Schettino, Marco Marini, Francesco Battista and Pasquale Natale
This paper aims to detail the reactive flow simulations of a LOX/CH4 multi-element rocket engine. The work has been conducted within the framework of the HYPROB-BREAD project…
Abstract
Purpose
This paper aims to detail the reactive flow simulations of a LOX/CH4 multi-element rocket engine. The work has been conducted within the framework of the HYPROB-BREAD project whose main objective is the design, manufacture and testing of a LOX/LCH4 regeneratively cooled ground demonstrator.
Design/methodology/approach
Numerical simulations have been carried out with both commercial software and CIRA software developed in house. Two sets of boundary conditions, nominal and experimental, have been applied from which a code-to-code validation has been effected with the former and a code-to-experiment validation with the latter.
Findings
The results presented include both flow data and heat fluxes as well as parameters associated with engine performance, and indicate an excellent agreement with experimental data of a LOX/CH4 multi-element rocket engine.
Originality/value
The research is unique as the CIRA code Numerical Experimental Tool (NExT) has been validated with the commercial software FLUENT as well as with experimental values from the firing of the LOX/CH4 rocket engine demonstrator.
Details
Keywords
This chapter examines the tactics that travel influencers pursued to circulate popular content on YouTube. They gathered practical expertise on algorithms which has been widely…
Abstract
This chapter examines the tactics that travel influencers pursued to circulate popular content on YouTube. They gathered practical expertise on algorithms which has been widely shared on digital platforms by algorithmic experts. The abstract knowledge about algorithmic mediation has become a global form as it circulates on YouTube and Instagram. The chapter traces how YouTube videos portraying the tourism destination Chiang Mai are connected to further YouTube videos through the platform’s ‘related videos’ curation. Drawing on computational data about the recommender network, the case provides insights into how YouTube’s video recommendation algorithm suggests videos to its viewers. The algorithm predominately organised video content connected to vlogs on Chiang Mai into groups based on semantic similarities of video titles and keywords. The case study finds that the recommendation algorithm acts as a classification technology establishing hierarchical orders of travel video content and video subgenres.