Research

Research Interests

• Computational modeling to advance clean combustion and renewable energy & energy conversion technologies, powering a sustainable energy future

• Multi-scale, multiphase & multi-physics simulations of reacting thermo-fluid systems and energetic propulsion systems

• Reactive characteristics of renewable & alternative fuels (hydrogen, ammonia, alcohols, and biofuels)

• High-efficiency and low-carbon-emissions high-energy systems such as gas-turbine engines, rotating detonation engines (RDE), advanced HCCI-type engines, dual fuels engines

• Computational engineering (high-performance computing (HPC), massive parallelism, hybrid computing, in-situ visualization, big data analysis, and machine learning)

• Nano-based materials for energy storage systems, including hydrogen production via electrolysis, advanced batteries, and high-performance supercapacitors.

Keywords: Energy, Combustion, Computational Modeling, Computational Fluid Dynamics (CFD), Scientific Computing, Big Data

Super-knock in Combustion Devices
Advanced combustion devices such as downsized and boosted engines provide higher power density per volume, higher thermal efficiency, and lower emissions. However, these engines operating at elevated pressure and temperature conditions have higher propensity of abnormal combustion phenomena such as super-knock. Super-knock is characterized by excessive pressure oscillations and extremely high-pressure spikes that may lead to mechanical failure. The highly localized detonation events occur at sub-nanosecond timescales and extremely fine spatial resolutions coupling with the complex interplay between turbulence, thermochemical reactions over a wide spectrum of length and time scales, and thus prohibiting experimental discovery. First-principle direct numerical simulations with the capability of fully resolving all temporal and spatial scales and the complex interaction of thermochemistry and turbulence will help address the knocking issues. With the aid of multi-dimensional high-fidelity direct numerical simulations, the objective of this study is to provide fundamental understanding of the super-knock mechanism, and to theoretically develop a reliable predictive model to prevent a priori the destructive operation of the combustion devices.

Ref: M.B. Luong* , H.G. Im, “Prediction of the developing detonation regime in a NTC-fuel/air mixture with temperature inhomogeneities under engine conditions”, Proc. Combust. Inst., 39 (2023) 4979-4988  https://doi.org/10.1016/j.proci.2022.10.015 

Pre-Ignition in Experimental Combustion Facilities
The accurate measurement of the ignition delay time in shock tubes and rapid compression machines is of paramount importance in building a reliable chemical kinetic model for designing industrial combustion applications. However, preignition, an undesired phenomenon in these experimental combustion facilities, leads to non-homogeneous combustion processes, drifting the performance of these facilities away from ideal operation, and thereby affecting the accuracy of the measurements. In line with the predictive ignition criterion that we successfully developed recently, the objective of this study is to extend the ignition criterion for the shock tubes and rapid compression applications to facilitate the predictive accuracy of kinetic model developments.  

Ref:  1. M. Figueroa-Labastida, M.B. Luong, J. Badra, A. Farooq, H.G. Im, “Experimental and computational studies of methanol and ethanol preignition behind reflected shock waves”, Combust. Flame, 234 (2021) 111621 https://doi.org/10.1016/j.combustflame.2021.111621
2. M.B. Luong*, H.G. Im, “Prediction of ignition modes in shock tubes relevant to engine conditions”, in: G. Kalghatgi, A.K. Agarwal, F. Leach, K. Senecal (Eds.), Engines and Fuels for Future Transport. Energy, Environment, and Sustainability, Springer, 2022: pp. 369–393, 10.1007/978-981-16-8717-4_15  

HCCI-Type Combustion Prototypes
Investigated the ignition and chemical characteristics of various fuels (n-heptane and iso-octane, biodiesel), and turbulence–chemistry interactions in advanced low-temperature combustion prototypes, i.e., Homogeneous Charge Compression Ignition (HCCI), Stratified Charge Compression Ignition (SCCI), and Reactivity Controlled Compression Ignition (RCCI), direct dual fuel stratification (DDFS)

Ref: M.B. Luong*, F.E. Hernandez Perez, H.G. Im, “Prediction of ignition modes of NTC-fuel/air mixtures with temperature and concentration fluctuations”, Combust. Flame, 213 (2020) 382–393  https://doi.org/10.1016/j.combustflame.2019.12.002 

Machine Learning and in-situ Visualization 
The massive dataset generated from multi-dimensional direct numerical simulations (DNS) poses significant challenges for data analysis to extract hidden features. To address these challenges, we couple deep neural networks, ParaView in-situ Catalyst, and a high-order shock capturing scheme to our KAUST Adaptive Reacting Flows Solver (KARFS).  Such an integrated framework has been set up and is being deployed, which allows us to visualize, analyze, and capture on the fly the abnormal combustion process occurring at even sub-nanosecond timescales. Apply machine learning to rich-hidden information from big DNS datasets to unravel the abnormal combustion events such that the trained model can be used to prevent undesired abnormal combustion processes in real-world industrial combustion devices.
Ref: 10. M.B. Luong, A. Mahmood, F.E. Hernandez Perez, R. Khurram, Im, H.G. Im, “Predicting Super-knock in IC Engines Using Machine Learning”, 32nd International Conference on Parallel Computational Fluid Dynamics, Nice, France, May 17–19, 2021 

Rotating Detonation Engines (RDE)
Rotating Detonation Engines (RDE) are a promising propulsion technology that utilizes the continuous detonation of a fuel-oxidizer mixture to generate thrust. Unlike conventional deflagration-based engines, RDEs operate with a rotating detonation wave traveling around the combustion chamber. This leads to more efficient energy conversion, resulting in higher pressure and temperature outputs, and potentially enhanced fuel efficiency and reduced emissions. The simplicity of RDEs in terms of fewer moving parts and their ability to operate at high frequencies makes them attractive for aerospace propulsion, gas turbines, and other high-performance applications.
Using direct numerical simulations to investigate the stability of the rotating detonation wave propagation under various fuel mixtures and operating conditions  can provide deep insights into the fundamental physics governing RDE operation, ultimately leading to optimized designs and control strategies.  

Carbon-Free Iron Power Technology in the Energy Transition
Metal fuels as renewable energy carriers represent a revolutionary pathway to a low-carbon economy by enabling clean energy to be stored, transported, and traded with zero carbon emissions. These recyclable fuels, reduced using renewable energy sources like solar and wind, boast the highest energy density among chemical fuels and are stable solids, making them easy to handle and distribute.

Metal fuels can react with water to generate hydrogen, heat, and electricity or burn with air to produce heat for motive or electrical power. Their combustion involves unique processes, such as the ignition and burning of metal particles as sparks, which act as micro-diffusion reactors, leading to a novel combustion regime called discrete flames. This phenomenon, characterized by rapid energy release at discrete points, offers exciting new possibilities for energy generation and efficient combustion.

Metal fuels offer a promising solution for long-term energy storage and transport, highlighting their scalability, safety, and cost-effectiveness. At the forefront of clean energy innovation, metal combustion research addresses scientific and engineering challenges to harness these fuels’ full potential for a sustainable, carbon-free future. 
Ref: Combustion Webinar  by Prof. Jeff Bergthorson https://youtu.be/ImJqyxcOeI8?si=_yVQ19BExqsxfD0i
Combustion Webinar  by  Prof.  XiaoCheng Mi  https://youtu.be/nBBgoW6kQqE?si=stUyUXEPK-ssbqMz 

Computational Singular Perturbation Toolkit (CSPTK)
The Computational Singular Perturbation Toolkit (CSPTK) is a powerful computational framework designed to simplify and analyze complex chemical kinetics. CSP is a method that identifies and separates fast and slow timescales in chemical reaction systems, making it easier to understand and model complex dynamical behavior. CSPTK facilitates this analysis by providing tools to extract reduced models, isolate important chemical pathways, and identify the dominant reaction mechanisms in multi-scale chemical systems. The Tangential Stretching Rate (TSR) and TSR-API are key metrics in CSP analysis that quantify the rate at which chemical trajectories are stretched in the fast subspace. TSR helps distinguish active and dormant modes within the chemical system, revealing which chemical processes are most influential at a given time.

CSPTK and TSR can be used to identify critical combustion features, i.e., by analyzing the fast and slow processes in combustion, CSPTK helps pinpoint the dominant reactions, simplifies the model for more efficient simulations, and improves understanding of combustion dynamics, especially in turbulent and reactive flow conditions. This insight is crucial for optimizing combustion processes and designing high-efficiency, low-emission combustion systems.
Ref: Iliana D. Dimitrova, Minh-Bau Luong, Sangeeth Sanal, Efstathios-Al. Tingas & Hong G. Im (2024) Asymptotic analysis of detonation development at SI engine conditions using computational singular perturbation, Combustion Theory and Modelling, 28:3, 282-316, DOI: 10.1080/13647830.2023.2281379