Multiphase flows
Multiphase flows are a ubiquitous feature of our environment whether one considers rain, snow, fog, avalanches, mudslides, sediment transport, and debris flows. Very critical biological and medical flows are also multiphase, from blood flow to semen to the bends to lithotripsy to laser surgery cavitation and so on. These are classified according to the state of the different phases or components and therefore refer to gas/solids flows, or liquid/solids flow, or gas/particle flows or bubbly flows and so on. Some are defined in terms of a specific type of fluid flow and deal with low Reynolds number suspension flows, dusty gas dynamics and so on. Others focus attention on a particular application such as slurry flows, cavitating flows, aerosols, debris flows, fluidized beds and so on.
Fluidized beds: Chemically non-reacting and reacting flows(combustion/gasification)
Fluidized beds are generally used in petroleum, pharmaceutical, chemical, mineral, and fossil fuel plants. Gasification of a feedstock in fluidized bed increases the efficiency of the power plant and reduces the greenhouse gases.
VMK Kotteda, A Stephens, W Spotz, V Kumar, and A Kommu, ‘Uncertainty quantification of fluidized beds using a data-driven framework’, Powder Technology , (2019)
VMK Kotteda, V Kumar and W Spotz, ‘Performance of preconditioned iterative solvers in MFiX-Trilinos for fluidized beds’, Journal of Supercomputing 74, 8:4104-4126 (2018).
VMK Kotteda, A Kommu, V Kumar and W Spotz, Uncertainty quantification of a fluidized bed reactor, AJKFluids ASME - JSME - KSME Joint Fluids Engineering Conference, July 28-August 1, 2019, San Francisco, CA, USA.
A badhan, VMK Kotteda and V Kumar, CFD DEM Analysis of a Dry powder Inhaler, AJKFluids ASME - JSME - KSME Joint Fluids Engineering Conference, July 28-August 1, 2019, San Francisco, CA, USA.
VMK Kotteda, V Kumar and W Spotz, Performance portability of a fluidized bed solver, IEEE High Performance Extreme Computing Conference (HPEC), Sep 25-27, 2018, Waltham, MA USA.
J Contreras-Serna, A Schiaffino, VMK Kotteda, A Garcia-Cuellar and V Kumar, Numerical simulation of the formation of melt jets in melt-coolant interactions, ASME 5th Joint US-European Fluids Engineering Summer Conference, Jul 15 - Jul 20, 2018, Le Centre Sheraton Montreal, Montreal, Quebec, Canada.
Poro-elasticity
Poroelasticity is the study of the transitory interactions between solid deformation and fluid flow within a porous medium. It is characterized by a time dependent, two-way coupling where changes in the state variables of one phase alter those of the other. Applying external load to a saturated porous medium causes changes in the fluid pressures which induces a flow. Likewise, a change in fluid pressures induces stresses that deform the solid skeleton.
P Delgado, VMK Kotteda, and V Kumar, ‘Hybrid Fixed-Point Fixed-Stress Splitting Method for Linear Poroelasticity’, Geosciences 9, 29–43 (2019).
VMK Kotteda, A Schiaffino, A Chattopadhyay, S Sanjay, V Kumar, and A Bronson, ‘Sensitivity of Viscosity on Molten Ti Infusion into a B4C Packed-Bed at the Microscopic Scale’, Metallurgical and Materials Transaction B, (2019).
A Schiaffino, VMK Kotteda, V Kumar, A Bronson and SS Kumar, Uncertainty Quantification of Molten Hafnium Infusion Into A B4c Packed-Bed, AJKFluids ASME - JSME - KSME Joint Fluids Engineering Conference, July 28-August 1, 2019, San Francisco, CA, USA.
ST Hussain, A Chattopadhyay, A Schiaffino, VMK Kotteda and V Kumar, Optimization of Micro-Pillar Wick Structured Cooler by using an Exa-scale Pore Network Simulator, 2018 Rice oil and gas high-performance computing, March 12-13, 2018, Rice University, Houston, TX.
A Rodriguez, A Schiaffino, VMK Kotteda and V Kumar, Neural network approach to predict the flow rate for the immiscible two-phase flow at pore scale for enhancing oil recovery application, ASME 5th Joint US-European Fluids Engineering Summer Conference, Jul 15 - Jul 20, 2018, Le Centre Sheraton Montreal, Montreal, Quebec, Canada.
A Schiaffino, VMK Kotteda, S Shantha, A Bronson and V Kumar, Predicting The Depth Of Penetration Of Molten Metal Into A Pore Network Using Tensorflow, ASME 5th Joint US-European Fluids Engineering Summer Conference, Jul 15 - Jul 20, 2018, Le Centre Sheraton Montreal, Montreal, Quebec, Canada.
Z Nieto, VMK Kotteda, A Rodriguez, V Kumar and A Bronson, Utilization of machine learning to predict the surface tension of molten metals and alloys, ASME 5th Joint US-European Fluids Engineering Summer Conference, Jul 15 - Jul 20, 2018, Le Centre Sheraton Montreal, Montreal, Quebec, Canada.
Water Braking Phenomena for the Holloman High-Speed Test Track
The Holloman High Speed Test Track operated by the Air Force Test Center 846th Test Squadron, is the world’s premier rocket sled test track and has the longest facility of its type in the world, making it one of the most unique test facilities in the DoD capable of replicating operational flight profiles, providing accurate and reliable data to the USAF, Army, Navy and other government agencies for Test and Evaluation (T&E) of critical weapon system and aerospace technology at fraction of the cost to flight testing. Operational flight speeds (can reach >8 Mach) is achieved via rail-mounted rocket-propelled sleds where the test object is attached to a forebody sled driven by one or more pusher sleds to accelerate the object. The sleds need to be recovered on the rail via a combination of aerodynamic drag followed by entry into water braking mechanism, a poorly understood phenomenon due to complex nonlinear multiphase flow dynamics interaction. Accurate prediction of the test profile can result in radical changes to designs of specific sleds and provide greater confidence of braking mechanism and recovery of the critical AF infrastructures. In collaboration with the squadron & supported by rigorous verification and validation, we propose to develop a better predictive capability of the water braking phenomena with high-fidelity Computational Fluid Dynamics (CFD) investigation capable of resolving flow separation, boundary layer, sled and rail/concrete interactions, test vehicles and articles for the test.
J Terrazas, VMK Kotteda, V Kumar, R Edmonds and M Zeisset, The CFD Modeling of the Water Braking Phenomena for the Holloman High-Speed Test Track, AJKFluids ASME - JSME - KSME Joint Fluids Engineering Conference, July 28-August 1, 2019, San Francisco, CA, USA.
Data-driven framework/Uncertainty Quantification/Sensitivity analysis/Optimization
Turbulence is significant in many engineering applications, and modeling of these flows poses unique challenges due to complex nonlinear interactions that can involve, for example, effects of multiple physical processes, density differences between fluids, and broad ranges of spatial and temporal scales. Machine learning has demonstrated to be an effective and promising approach to investigate and solve problems in many areas of physics, including turbulence. Machine learning offers computers to learn from datasets without explicit programming instructions and application of machine learning is ubiquitous in our everyday life. The datasets required for training are widely available these days. In recent years, machine learning has driven advances in many different fields. This is due to the improvement in the machine learning models, availability of large datasets for training and readiness of computational resources for training the models with large datasets.
VMK Kotteda, A Stephens, W Spotz, V Kumar, and A Kommu, ‘Uncertainty quantification of fluidized beds using a data-driven framework’, Powder Technology , (2019)
VMK Kotteda, A Schiaffino, A Chattopadhyay, S Sanjay, V Kumar, and A Bronson, ‘Sensitivity of Viscosity on Molten Ti Infusion into a B4C Packed-Bed at the Microscopic Scale’, Metallurgical and Materials Transaction B, (2019).
D Lozano, VMK Kotteda, VS Rao Gudimetla and V Kumar, ‘Implementing Artificial Intelligence in predicting metrics for characterizing laser propagation in atmospheric Turbulence’, Journal of Fluid Engineering , (2019).
VMK Kotteda, A Kommu, V Kumar and W Spotz, Uncertainty quantification of a fluidized bed reactor, AJKFluids ASME - JSME - KSME Joint Fluids Engineering Conference, July 28-August 1, 2019, San Francisco, CA, USA.
LF Rodriguez, V Kumar, J Espiritu, VMK Kotteda, D Lozano and A Rodriguez, Branch and Bound Analysis To Characterize Phase Variations In Laser Propagation Through Deep Turbulence, AJKFluids ASME - JSME - KSME Joint Fluids Engineering Conference, July 28-August 1, 2019, San Francisco, CA, USA.
J Contreras-Serna, A Schiaffino, VMK Kotteda, A Garcia-Cuellar and V Kumar, Numerical simulation of the formation of melt jets in melt-coolant interactions, ASME 5th Joint US-European Fluids Engineering Summer Conference, Jul 15 - Jul 20, 2018, Le Centre Sheraton Montreal, Montreal, Quebec, Canada.
D Lozano, VMK Kotteda, VSRao Gudimetla and V Kumar, Implementing Artificial Intelligence in predicting metrics for characterizing laser propagation in atmospheric Turbulence, ASME 5th Joint US-European Fluids Engineering Summer Conference, Jul 15 - Jul 20, 2018, Le Centre Sheraton Montreal, Montreal, Quebec, Canada.
A Rodriguez, A Schiaffino, VMK Kotteda and V Kumar, Neural network approach to predict the flow rate for the immiscible two-phase flow at pore scale for enhancing oil recovery application, ASME 5th Joint US-European Fluids Engineering Summer Conference, Jul 15 - Jul 20, 2018, Le Centre Sheraton Montreal, Montreal, Quebec, Canada.
A Schiaffino, VMK Kotteda, S Shantha, A Bronson and V Kumar, Predicting The Depth Of Penetration Of Molten Metal Into A Pore Network Using Tensorflow, ASME 5th Joint US-European Fluids Engineering Summer Conference, Jul 15 - Jul 20, 2018, Le Centre Sheraton Montreal, Montreal, Quebec, Canada.
Z Nieto, VMK Kotteda, A Rodriguez, V Kumar and A Bronson, Utilization of machine learning to predict the surface tension of molten metals and alloys, ASME 5th Joint US-European Fluids Engineering Summer Conference, Jul 15 - Jul 20, 2018, Le Centre Sheraton Montreal, Montreal, Quebec, Canada.
Various widely used open-source or commercial solvers are available to us to simulate complex engineering problems including fluidized beds. However, most of these solvers do not provide meaningful confidence intervals of the simulation results. It could be due to the lack of tools for finding the ranges as well as the expense of the computations. We know that these intervals are beneficial for verification and validation of the numerical results. In general, nonlinearities and transient behavior of the flows increase the computational cost substantially. Further, species and chemical reactions consideration in fluidized bed reactors significantly impact the computational cost. Besides, multiphase flows such as fluidized beds involve numerous uncertain parameters. Techniques such as sensitivity analysis are useful in identifying the few metrics that have the most influence on the quantities of interest. Further, fluidized beds are more complex than single phase flow simulations, and the computational cost increase plays a crucial role in finding a sampling technique and number of samples.
A badhan, VMK Kotteda and V Kumar, CFD DEM Analysis of a Dry powder Inhaler, AJKFluids ASME - JSME - KSME Joint Fluids Engineering Conference, July 28-August 1, 2019, San Francisco, CA, USA.
VMK Kotteda, A Stephens, W Spotz, V Kumar, and A Kommu, ‘Uncertainty quantification of fluidized beds using a data-driven framework’, Powder Technology , (2019)
VMK Kotteda, A Kommu, V Kumar and W Spotz, Uncertainty quantification of a fluidized bed reactor, AJKFluids ASME - JSME - KSME Joint Fluids Engineering Conference, July 28-August 1, 2019, San Francisco, CA, USA.
VMK Kotteda, A Schiaffino, A Chattopadhyay, S Sanjay, V Kumar, and A Bronson, ‘Sensitivity of Viscosity on Molten Ti Infusion into a B4C Packed-Bed at the Microscopic Scale’, Metallurgical and Materials Transaction B, (2019).
A Schiaffino, VMK Kotteda, V Kumar, A Bronson and SS Kumar, Uncertainty Quantification of Molten Hafnium Infusion Into A B4c Packed-Bed, AJKFluids ASME - JSME - KSME Joint Fluids Engineering Conference, July 28-August 1, 2019, San Francisco, CA, USA.
Air-breathing engines
An air-breathing engine uses atmospheric air, brought to the engine face via an inlet to oxidize the liquid fuel. This fuel air mixture is combusted and passed through a nozzle to produce a fast moving jet. Thrust is generated in accordance with Newton’s third law of motion. The various engines used in supersonic aircrafts are turbojet, turbofan and ramjet engine. In these engines, an air intake reduces the speed of the incoming air through various shocks so that the combustion takes place at subsonic speeds. Most modern passenger and military aircrafts are powered by gas turbine engines. The most common and relatively simple among the family of gas turbine engines is the turbojet. In this type of engine, an air intake captures atmospheric air and passes it downstream to the compressor, which further increases the pressure of the incoming air. The compressed air is mixed with the fuel and ignited by flame in combustion chamber. The products of combustion expand through the turbine and generate power. This power is used to drive the compressor. The hot gas stream exiting the turbine expands to the ambient pressure through the propelling nozzle and produce a high speed jet. This high speed jet results in forward thrust on the airframe.
Most modern jet engines are turbofan engines. In these engines, low pressure compressor acts as a fan. The compressed air is provided to the engine core as well as the bypass duct. The flow in the bypass duct either passes through a separate nozzle or mixes with engine core, before expanding through a mixed flow nozzle. For flight Mach number above 2.5, the pressure rise in the inlet diffuser is very high and the associated high ram temperatures make it impossible to place the rotating machinery in the flow path. In these circumstances a ramjet engine is used. A ramjet engine is a mechanically simple jet engine, which is based on ram compression in supersonic flight. It operates on the same principle as the turbojet, except for the presence of rotating machinery. The intake converts most of the kinetic energy of the incoming flow into the pressure energy through oblique shocks followed by reflected shocks and the terminal normal shock. The interaction of these shocks with the boundary layer may change the characteristics of the flow and lead to shutdown of the engine. The flow downstream of the normal shock expands further in the subsonic diffuser. The compressed air is mixed with a fuel and burnt in the combustion chamber. The hot gas stream exiting the combustion chamber expands to the ambient pressure through the nozzle.
Inlets
Air intakes form a very vital component of any aircraft engine. They are expected to provide sufficient amount of air at low speed to the combustor/engine face with relatively low distortion to sustain continuous combustion. A mixed‐compression inlet is often used for flight Mach number greater than 2.5. It is characterized by multiple reflected oblique shocks in the convergent portion and a terminal normal shock immediately downstream of the throat. A typical mixed compression inlet consists of two parts: supersonic diffuser just upstream of the throat and a subsonic diffuser that lies downstream of the throat section. During the critical operation of the inlet, the normal shock sits right at the throat and any further increase in the back‐pressure causes the flow to become unstable. In the sub‐critical regime, the normal shock is pushed in the convergent part of the intake. In such a state, the normal shock can be expelled out and the intake can ‘unstart’. The air intake is also associated with the ‘buzz’ instability during its sub‐critical operation. It is a self‐excited diffuser instability in which the normal shock oscillates back and forth in the convergent portion leading to high unsteadiness in the flow. It involves periodic filling and discharge of the plenum chamber, complex shock–boundary layer interaction, shear layer/slip stream–boundary layer interaction, transient shock movement and flow separation. It adversely affects the mass flow entering the engine and may lead to combustion instability, engine surge and flame out. It can also lead to deterioration of the performance of propulsion system, thus causing catastrophic loss in thrust.
S Mittal, G Chopra, M Furquan, Navrose, VMK Kotteda and V Bhatt, ‘Finite Element Computations of Complex Flows’, Proceedings of the Indian National Science Academy 82, 2:385-394 (2016).
VMK Kotteda and S Mittal, ‘Flow in a Y-intake at supersonic speeds’, Journal of Propulsion and Power 32, 171-187 (2016).
VMK Kotteda and S Mittal,“Finite element computation of buzz instability in supersonic air intakes”, Advances in Computational Fluid-Structure Interaction and Flow Simulation (Birkhäuser, Cham, 2016), Yuri Bazilevs & Kenji Takizawa, eds.
VMK Kotteda and S Mittal, ‘Instabilities in air intakes of supersonic air vehicles’, Directions, IIT Kanpur , (2015).
VMK Kotteda and S Mittal, ‘Computation of turbulent flow in a mixed compression intake’, International Journal of Advances in Engineering Sciences and Applied Mathematics 6, 126-141 (2014).
VMK Kotteda and S Mittal, ‘Stabilized finite element computation of compressible flow with linear and quadratic interpolation functions’, International Journal for Numerical Methods in Fluids 75, 273–294 (2014).
VMK Kotteda and S Mittal, ‘Viscous flow in a mixed compression intake’, International Journal for Numerical Methods in Fluids 67, 1393–1417 (2011).
VMK Kotteda and S Mittal, Numerical simulation of viscous flow in a twin intake, 2nd National Propulsion Conference, Feb 23-24, 2015, IIT Bombay, India.
VMK Kotteda and S Mittal, Flow in a mixed compression intake with linear and quadratic elements, 15th AeSI Annual CFD Symposium, Aug 9-10, 2013, IISc Bangalore, India.
VMK Kotteda and S Mittal, Finite element computations of compressible flows using linear and quadratic interpolation functions, 13th AeSI Annual CFD Symposium, Aug 11-12 2011, IISc Bangalore, India.
VMK Kotteda and S Mittal, Finite element computation of compressible flows using conservative variables, 16th International Conference on Finite Elements in Flow Problems (FEF-2011), Mar 23-25, 2011, Munich, Germany.
VMK Kotteda and S Mittal, Viscous Flow in a Mixed Compression Intake, 8th Asian Computational Fluid Dynamics Conference, Jan 10-14, 2010, Hong Kong, China.
Nozzles
Nozzle is a vital component of the engine. The hot gas stream exiting the combustion chamber expands to ambient pressure through the nozzle, producing a high speed jet in the exhaust plume. The high speed jet results in forward thrust on the airframe.
Nozzles are categorized into three types based on the contour: conical, bell or contoured and annular. Conical nozzle is often used because of its simplicity and ease of construction. In this nozzle, the divergent wall angle is constant. In general, high divergent wall angle minimizes the size and weight of the nozzle. However, high wall angle can cause over-expansion because of high ambient pressure at low altitudes. Bell nozzle is most commonly used because of its low weight and good performance. The divergence wall angle near the throat is relatively large and it decreases with increase in the distance from the throat. The contour of this type of nozzle is designed such that it avoids the oblique shocks and maximizes the performance. Annular nozzle is known as the plug or ‘altitude-compensating’ nozzle. This type of nozzle is least employed because of the complexity of its design. Annulus refers to the ring or annulus along which the combustion takes place. ‘Plug’ refers to the center body that blocks the flow around central portion of the nozzle. Annular nozzles are of two types: plug and expansion deflection nozzle. In the plug nozzle, the plug guides the inner flow. Greater surface cooling requirement for the plug restricts the use. In expansion deflection nozzle, the walls guide the outer flow. The inner flow is allowed to expand freely at various ambient pressures and therefore it has good altitude compensation.
VMK Kotteda and S Mittal, ‘Flow in a planar convergent-divergent nozzle’, Shock waves 27, 441-455 (2017).
S Mittal, G Chopra, M Furquan, Navrose, VMK Kotteda and V Bhatt, ‘Finite Element Computations of Complex Flows’, Proceedings of the Indian National Science Academy 82, 2:385-394 (2016).
Laser propagation in atmospheric turbulence
Within the department of defense, there is an expanding interest to characterize the effects of atmospheric turbulence on the optical system. We essentially want to comprehend laser propagation over a long path and understand the effects of atmospheric turbulence. This is because laser propagation through a turbulent medium can result in refractive index fluctuations that cause random phase perturbations on a laser beam that can lead to beam distortions. Improvement and understanding of optical systems capable of propagating lasers over long distances in atmospheric turbulence conditions can enhance the performance in remote sensing, long-range satellite communications, active imaging, and other related optical systems. However, it can be complicated to characterize these random variations in optical systems associated with the temperature variations that are caused by turbulent eddies.
D Lozano, VMK Kotteda, VS Rao Gudimetla and V Kumar, ‘Implementing Artificial Intelligence in predicting metrics for characterizing laser propagation in atmospheric Turbulence’, Journal of Fluid Engineering , (2019).
LF Rodriguez, V Kumar, J Espiritu, VMK Kotteda, D Lozano and A Rodriguez, Branch and Bound Analysis To Characterize Phase Variations In Laser Propagation Through Deep Turbulence, AJKFluids ASME - JSME - KSME Joint Fluids Engineering Conference, July 28-August 1, 2019, San Francisco, CA, USA.
D Lozano, VMK Kotteda, VSRao Gudimetla and V Kumar, Implementing Artificial Intelligence in predicting metrics for characterizing laser propagation in atmospheric Turbulence, ASME 5th Joint US-European Fluids Engineering Summer Conference, Jul 15 - Jul 20, 2018, Le Centre Sheraton Montreal, Montreal, Quebec, Canada.
Single phase, Bluff body hydrodynamics
The subject of flow-induced oscillations of multiple cylinders has been the focus of several studies owing to its high engineering significance. A group of cylinders, placed in tandem, staggered, or both the configurations, finds applications in tall chimneys, heat exchangers, off-shore oil drilling, cables laid in ocean current, etc. When a cylinder is placed in the wake of another body, the downstream cylinder undergoes oscillations at higher amplitudes as it interacts with the vortices shed by the upstream body. In this case, the downstream cylinder experiences fluid forces exerted by the upstream vortices in addition to the forces caused due to its own vortex shedding. Therefore, the downstream cylinder exhibits galloping response.
S Behara, V Chandra, B Ravikanth, and VMK Kotteda, ‘Oscillation responses and wake modes of three staggered rotating cylinders in two- and three-dimensional flows’, Physics of Fluids 30, 103602 (2018).
I want to thank the institutions that have provided access to their parallel machines:
