S. Navarro-Martinez

ORCID: 0000-0001-8342-6573
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About
Contact & Profiles
Research Areas
  • Combustion and flame dynamics
  • Advanced Combustion Engine Technologies
  • Particle Dynamics in Fluid Flows
  • Computational Fluid Dynamics and Aerodynamics
  • Fire dynamics and safety research
  • Fluid Dynamics and Heat Transfer
  • Fluid Dynamics and Turbulent Flows
  • Wind and Air Flow Studies
  • Gas Dynamics and Kinetic Theory
  • Radiative Heat Transfer Studies
  • Combustion and Detonation Processes
  • Atmospheric chemistry and aerosols
  • Plasma and Flow Control in Aerodynamics
  • Meteorological Phenomena and Simulations
  • Heat Transfer Mechanisms
  • Coagulation and Flocculation Studies
  • Fluid Dynamics Simulations and Interactions
  • Electrohydrodynamics and Fluid Dynamics
  • Climate variability and models
  • Minerals Flotation and Separation Techniques
  • Energetic Materials and Combustion
  • Thermochemical Biomass Conversion Processes
  • Coal Combustion and Slurry Processing
  • Advanced Thermodynamics and Statistical Mechanics
  • Radiomics and Machine Learning in Medical Imaging

Imperial College London
2016-2025

Imperial Valley College
2017

University of Stuttgart
2009

10.1016/j.proci.2008.06.178 article EN Proceedings of the Combustion Institute 2008-10-11

10.1007/s10494-010-9320-1 article EN Flow Turbulence and Combustion 2011-01-14

10.1016/j.ijmultiphaseflow.2014.02.013 article EN International Journal of Multiphase Flow 2014-03-22

This paper presents a computational study exploring the dependence of oscillation rates and Mach, Reynolds, Strouhal numbers on dynamic stability mechanically deployable aeroshell. Computational fluid dynamics free-oscillation simulations are performed to compute pitch damping coefficient with rate. The is split in its fore- aftbody components. loads shown excite oscillations at low angles attack. High values Mach number tend decrease coefficient, supporting theory that instability stems...

10.2514/1.a36126 article EN Journal of Spacecraft and Rockets 2025-03-19

Abstract Numerical weather prediction is an established forecasting technique in which equations describing wind, temperature, pressure and humidity are solved using the current atmospheric state as input. This study examines deep learning to forecast given historical data from two London-based locations. Two distinct Bi-LSTM recurrent neural network models were developed TensorFlow framework trained make predictions next 24 72 h, past 120 h. The first predicted temperature at Kew Gardens...

10.1007/s10489-023-04824-w article EN cc-by Applied Intelligence 2023-08-01

10.1016/j.proci.2006.07.212 article EN Proceedings of the Combustion Institute 2006-09-26

10.1016/j.proci.2010.07.032 article EN Proceedings of the Combustion Institute 2010-10-04

10.1016/j.ijheatfluidflow.2014.10.028 article EN International Journal of Heat and Fluid Flow 2014-11-23

A joint experimental and computational study of thermoacoustic instabilities in a model swirl-stabilised combustor is presented. This paper aims to deliver better characterisation such through the examination measurements conjunction with numerical results obtained via Large Eddy Simulation (LES). The configuration features cylindrical combustion chamber where lean premixed methane/air flame experiences self-sustained oscillations. nonlinear behaviour acoustically excited experimentally...

10.1016/j.proci.2018.07.090 article EN cc-by Proceedings of the Combustion Institute 2018-08-08

10.1007/s10494-009-9228-9 article EN Flow Turbulence and Combustion 2009-06-05
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