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While analytical solutions of critical (phase) transitions in physical systems are abundant for simple nonlinear systems, such analysis remains intractable for real-life dynamical systems. A key example of such a physical system is…

Thermoacoustic instability in annular combustors, essential to aero engines and modern gas turbines, can severely impair operational stability and efficiency, accurately recognizing and understanding various combustion modes is the…

Machine Learning · Computer Science 2025-03-19 Tao Yang , Weiming Xu , Liangliang Xu , Peng Zhang

Supersonic combustion plays a vital role in various applications, including scramjets, dual-mode ramjets, and pulse detonation engines. However, the flame characteristics can vary significantly, depending on the application. To model…

Fluid Dynamics · Physics 2023-06-21 Xu Zhu , Jian An , Nana Wang , Jian Zhang , Zhuyin Ren

Combustion instability in gas turbines and rocket engines, as one of the most challenging problems in combustion research, arises from the complex interactions among flames, which are also influenced by chemical reactions, heat and mass…

Machine Learning · Computer Science 2024-11-26 Weiming Xu , Tao Yang , Peng Zhang

Oscillatory combustion in aero engines and modern gas turbines often has significant adverse effects on their operation, and accurately recognizing various oscillation modes is the prerequisite for understanding and controlling combustion…

Machine Learning · Computer Science 2026-02-26 Weiming Xu , Tao Yang , Peng Zhang

Hypersonic flight poses unique propulsion challenges, requiring engines that maintain thrust, efficiency, and stability across a wide range of operating conditions. These engines must transition smoothly between flight regimes and…

Fluid Dynamics · Physics 2025-11-25 Nick Plewacki , Benjamin Kale , Manu Kamin , Luis Bravo

Speech Emotion Recognition (SER) systems often degrade in performance when exposed to the unpredictable acoustic interference found in real-world environments. Additionally, the opacity of deep learning models hinders their adoption in…

Sound · Computer Science 2025-12-23 Sudip Chakrabarty , Pappu Bishwas , Rajdeep Chatterjee

This study has presented a comprehensive computational fluid dynamics (CFD) analysis of combustion flow in a realistic can combustor, evaluating the influence of various turbulence models on flow, thermal, and species fields. The…

Fluid Dynamics · Physics 2026-05-20 Aishvarya Kumar , Ram Prakash Bharti

In many cyber-physical systems, imaging can be an important but expensive or 'difficult to deploy' sensing modality. One such example is detecting combustion instability using flame images, where deep learning frameworks have demonstrated…

Machine Learning · Computer Science 2021-10-07 Tryambak Gangopadhyay , Vikram Ramanan , Satyanarayanan R Chakravarthy , Soumik Sarkar

The 100 MW cryogenic liquid oxygen/hydrogen multi-injector combustor BKD operated by the DLR Institute of Space Propulsion is a research platform that allows the study of thermoacoustic instabilities under realistic conditions,…

The article investigates liquid oxygen (LOx)-methane supercritical combustion dynamics in a multi-element rocket scale combustor using large eddy simulation (LES). A complex framework of real gas thermodynamics and flamelet generated…

Fluid Dynamics · Physics 2023-11-28 Abhishek Sharma , Ashoke De , S. Sunil Kumar

Variational Autoencoders (VAEs), as a form of deep generative model, have been widely used in recent years, and shown great great peformance in a number of different domains, including image generation and anomaly detection, etc.. This…

Machine Learning · Computer Science 2024-08-28 Liang Cheng , Peiyuan Guan , Amir Taherkordi , Lei Liu , Dapeng Lan

The high cost of high-resolution computational fluid/flame dynamics (CFD) has hindered its application in combustion related design, research and optimization. In this study, we propose a new framework for turbulent combustion simulation…

Fluid Dynamics · Physics 2020-03-03 Jian An , Hanyi Wang , Bing Liu , Kai Hong Luo , Fei Qin , Guo Qiang He

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However,…

Data Analysis, Statistics and Probability · Physics 2018-03-14 Xun Huan , Cosmin Safta , Khachik Sargsyan , Gianluca Geraci , Michael S. Eldred , Zachary P. Vane , Guilhem Lacaze , Joseph C. Oefelein , Habib N. Najm

Combustion is the primary process in gas turbine engines, where there is a need for efficient air-fuel mixing to enhance performance. High-shear swirl injectors are commonly used to improve fuel atomization and mixing, which are key factors…

Machine Learning · Computer Science 2024-09-25 PK Archhith , SK Thirumalaikumaran , Balasundaram Mohan , Saptharshi Basu

Vehicle trajectory prediction is crucial for advancing autonomous driving and advanced driver assistance systems (ADAS). Although deep learning-based approaches - especially those utilizing transformer-based and generative models - have…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Junwei You , Rui Gan , Weizhe Tang , Zilin Huang , Jiaxi Liu , Zhuoyu Jiang , Haotian Shi , Keshu Wu , Keke Long , Sicheng Fu , Sikai Chen , Bin Ran

Accurate classification of respiratory sounds requires deep learning models that effectively capture fine-grained acoustic features and long-range temporal dependencies. Convolutional Neural Networks (CNNs) are well-suited for extracting…

Sound · Computer Science 2025-07-29 Nouhaila Fraihi , Ouassim Karrakchou , Mounir Ghogho

Reduced-order models (ROMs) are very popular for surrogate modeling of full-order computational fluid dynamics (CFD) simulations, allowing for real-time approximation of complex flow phenomena. However, their application to CFD models…

Fluid Dynamics · Physics 2025-11-25 Rakesh Halder , Benet Eiximeno , Oriol Lehmkuhl

Acoustic echo cancellation (AEC), noise suppression (NS) and dereverberation (DR) are an integral part of modern full-duplex communication systems. As the demand for teleconferencing systems increases, addressing these tasks is required for…

Detecting anomalies in multivariate time series is essential for monitoring complex industrial systems, where high dimensionality, limited labeled data, and subtle dependencies between sensors cause significant challenges. This paper…

Machine Learning · Computer Science 2025-11-18 Bahareh Golchin , Banafsheh Rekabdar
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