Sep 2026· SAE technical papers on CD-ROM/SAE technical paper series· Vol 1· 19 references
Abstract
A numerical study on the influence of annular gap variation in correctly expanded sonic coaxial jets, focusing on its effect on mixing characteristics and jet symmetry, is presented in this paper. The computational simulations were conducted using a three-dimensional steady-state compressible Reynolds-Averaged Navier–Stokes (RANS) framework with the Spalart–Allmaras (SA) turbulence model. Both symmetric (uniform gap) and asymmetric (nonuniform gap) configurations were simulated. Eccentricity was introduced by offsetting the secondary nozzle by 2 mm downward from the center of the primary nozzle. In symmetric configurations with uniform annular gaps, the jet exhibited balanced shear-layer development, uniform entrainment, and symmetric Mach decay characteristics. However, the asymmetric annular gap configuration exhibited approximately 25–30% earlier potential core breakdown, 30–35% greater radial jet spreading, and nearly 6–10% faster centerline velocity decay compared with the symmetric configuration. The streamline analysis revealed enhanced entrainment, localized recirculation regions, asymmetric vortex generation, and accelerated momentum diffusion caused by unequal shear-layer interaction. These results demonstrate that annular gap asymmetry can serve as an effective passive flow control strategy for enhancing jet mixing and directional momentum redistribution. Such configurations may be useful in practical applications including exhaust gas dilution, fuel–air mixing enhancement in combustors, thrust vectoring, and jet-noise suppression systems.
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
The application of agile software methods and more recently the integration of Lean practices contribute to the trend of continuous improvement in the software industry. One such area warranting proper empirical evidence is a project’s operational efficiency when using the Kanban method. This short paper takes a new an...
Marko Ikonen, Petri Kettunen, Nilay V. Oza et al.· EUROMICRO Conference on Soft...· 67 citations· ⚡9
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.