Flow Over a Flat Plate


Samples of My Presentations

  1. Ph.D. Defence
  2. SciTech Conference 2018

Refereed Journal Papers

Analysis and Optimization Study of Ducted Wind Turbines

Tariq Khamlaj & Markus Rumpfkeil

Abstract: Wind-lens turbines offer the potential for better energy efficiency and better suitability for urban and suburban environments compared to unshrouded or bare wind turbines. Wind-lenses, which are typically comprised of a diffuser shroud equipped with a flange, can enhance the wind velocity at the rotor plane due to the generation of a lower back pressure. In this article, the wind-lens efficiency is increased by designing the shroud and turbine shape as well as flange height through an optimization process that seeks to maximize the power while minimizing drag and thrust forces. The employed optimizer is a multi-objective genetic algorithm (MOGA). Bezier curves are used to define the chord and twist distribution of the turbine blades and a piecewise quadratic polynomial is utilized to define the shroud shape. The power, thrust, and drag coefficients are calculated by solving the Reynolds-averaged-Navier-Stokes (RANS) equations with the k-ε turbulence model for the flow within and around the diffuser augmented wind turbine using the open source code software OpenFOAM. To reduce the computational cost, the turbine rotor itself is modeled by incorporating blade element momentum model body forces into the RANS equations. Realistic rotor data for the sectional lift and drag coefficients for all angles of attacks are utilized via look-up tables. Grid convergence studies for verification and comparisons with experiments for validation are carried out to demonstrate that the adopted methodology is able to accurately predict the performance of a wind-lens prior to performing shape optimizations. It will be demonstrated that the resulting optimal designs yield significant improvements in the output power coefficient.

Energy, Volume 162, pp. 1234-1252, 2018.

Theoretical Analysis of Shrouded Horizontal Axis Wind Turbines

Tariq Khamlaj & Markus Rumpfkeil

Abstract: Numerous analytical studies for power augmentation systems can be found in the literature with the goal to improve the performance of wind turbines by increasing the energy density of the air at the rotor. All methods to date are only concerned with the effects of a diffuser as the power augmentation, and this work extends the semi-empirical shrouded wind turbine model introduced first by Foreman to incorporate a converging-diverging nozzle into the system. The analysis is based on assumptions and approximations of the conservation laws to calculate optimal power coefficients and power extraction, as well as augmentation ratios. It is revealed that the power enhancement is proportional to the mass stream rise produced by the nozzle diffuser-augmented wind turbine (NDAWT). Such mass flow rise can only be accomplished through two essential principles: the increase in the area ratios and/or by reducing the negative back pressure at the exit. The thrust coefficient for optimal power production of a conventional bare wind turbine is known to be 8/9, whereas the theoretical analysis of the NDAWT predicts an ideal thrust coefficient either lower or higher than 8/9 depending on the back pressure coefficient at which the shrouded turbine operates. Computed performance expectations demonstrate a good agreement with numerical and experimental results, and it is demonstrated that much larger power coefficients than for traditional wind turbines are achievable. Lastly, the developed model is very well suited for the preliminary design of a shrouded wind turbine where typically many trade-off studies need to be conducted inexpensively.

Energies 10(1), 38, 2017

Refereed Conference Papers

Optimization Study of Shrouded Horizontal Axis Wind Turbine

Tariq Khamlaj & Markus Rumpfkeil

Abstract: There is a large interest in wind turbines which are suitable for urban and suburban environments in order to bring power production closer to the consumer to minimize transportation power losses. A prime candidate for these kinds of applications is a wind-lens. Wind-lenses, which consist of a diffuser shroud equipped with a brim, have the potential to increase the wind speed at the rotor due to the generation of a low back pressure region through vortex formation. The objective of this study is to improve the wind-lens efficiency by designing the duct and brim shape through an optimization process that maximizes the power while minimizing drag for a given turbine rotor shape. The optimization process is carried out by the DAKOTA software package developed by Sandia National Labs. The power and drag coefficients are calculated by employing the Reynolds-averaged-Navier-Stokes (RANS) equations to simulate the flow within and around a diffuser augmented wind turbine with a brim. The open source code OpenFOAM is used and in order to reduce the computational cost, the turbine rotor is represented via an axisymmetric CFD-integrated blade element momentum model (also known as actuator disk model). Realistic rotor data, such as local chord lengths and twist angles as well as the sectional airfoils’ lift and drag coefficients for all angles of attacks, are utilized in the blade element model. Grid convergence studies for verification and comparisons with experiments for validation are carried out to demonstrate that the adopted methodology is able to predict the performance of a wind-lens accurately prior to performing shape optimizations. It will be demonstrated that the optimum designs yield significant improvements in the output power coefficient.

2018 Wind Energy Symposium, AIAA SciTech Forum, (AIAA 2018-09)

PDF Version 6.2018-0996

ICON Technology & Process Consulting

As a consultant CFD engineer, my duties are as following;

  1. Planning and Delivery Numerical Simulations
  • Planning and set-up of simulations including geometry preparation and mesh generation as defined by customer requirements.
  • Analysis, assessment and troubleshooting of simulation results.                  
  • Comparison of simulation and experimental results.
  • Documentation of simulation results in presentations and reports                                                          
  • Development, recording and reporting of best practices as required                                                       
  • Development and application of CFD methods and models according to customer needs                  
  • Delivering consultancy projects.
  • Data archiving                                                                                                                                                      

2. Delivery of Support & Training

  • Customization of software in accordance with customer needs                                                                
  • Proactive delivery of user support to customers both remotely and/or on-site                                     
  • Delivery of training to customers both remotely and/or on-site                                                                
  • Proactive interaction with customers to ensure client satisfaction                     
  • Software installations and systems support                                    
  • Coordination and support to development team in resolving software bugs                                         
  • Flag and communicate to management any matters of concern                                                             

Customer Communication & Collaboration

  • Work closely with customers and related parties to identify and communicate simulation requirements and results
  • Communicate regularly with customers to ensure objectives are fully identified and understood  and any variations to project definition are communicated
  • Serve as a key point-of-contact for customers
  • Assess & resolve customer issues and technical problems with support of delivery team colleagues where required
  • Resolve issues related to the process, usability, and application of tools.


Welcome to my website!

My name is Tariq Khamlaj, and I have recently joined ICON Technology & Process Consulting company team as a Consulting CFD Engineer here in Michigan. Before joining ICON Technology, I worked as an adjunct assistant professor in the Department of Mechanical and Aerospace Engineering at the University of Dayton. On August 24, 2018, I successfully defended my dissertation (see the video) under the guidance of Dr. Markus Rumpfkeil, and I graduated on December 15, 2018. My Ph.D. research focuses on the analysis and optimization of wind-lens turbines or shrouded horizontal axis wind turbines. I apply shape optimization techniques to a small-scale shrouded horizontal-axis wind turbine or wind-lens using computational fluid dynamics (CFD) for the analysis and a genetic algorithm for the optimization to increase the power production of these turbines. In my spare time, I am working on employing the active subspace method (ASM) to the optimization of shrouded wind turbines to discover and exploit low-dimensional trends in the design space. This will allow finding an optimal design with reduced computational cost. As an adjunct assistant professor, I was the head of the Material Science Lab where I was responsible for overseeing ten sections, coordinating with the TA’s, creating the lab experiments,  as well as grading lab reports associated with a material science class. On this website, you will find a list of my publications (if you want to hear more about what I am doing and how I spend my day), OpenFOAM test cases, optimization details, some lecture notes that I developed, and source codes used to generate results for my dissertation.

In my spare time, I enjoy playing sand volleyball and bodybuilding etc.

This slideshow requires JavaScript.

Verification and Validation

Developing most numerical solvers involves making certain assumptions which may neglect certain physics but with an acceptable loss of accuracy. Once the numerical solver is created, its quality is measured with

Verification: A process to determine that the model equations are solved correctly. This frequently includes comparisons to known solutions for particular cases or to results from previous work. Also, conducting grid convergence studies is essential in any numerical study to verify that the solution is insensitive to the grid resolution.

Validation: A process to determine that the model equations replicate the true behavior of the physical system. This often involves comparisons to experimental data.


Why CFD?

Fluid dynamics is the science of fluid motion. Fluid flows are commonly studied in one of the 3 ways:

       ❶ Theoretical fluid dynamics,
       ❷ Experimental fluid dynamics,
       ❸ Numerically: Computational Fluid Dynamics.

What is CFD?

Computational fluid dynamics, commonly shortened as CFD, is a subdivision of fluid mechanics that utilizes numerical methods and algorithms to solve and analyze problems that involve fluid flows. CFD is the science of predicting fluid flow, heat transfer, mass transfer, chemical reactions, and associated phenomena by solving mathematical equations, governing these processes using numerical approaches. CFD permits scientists and engineers to perform numerical experiments (i.e. computer simulations) in a virtual flow laboratory.

What is a fluid flow?

Fluid flows encountered in everyday life include:

       ❶ Interaction of various objects with the surrounding air/water (aerospace automotive and marine applications).
       ❷ Complex flows in heat exchangers, chemical reactors, and furnaces.
       ❸ Combustion in automobile engines and other propulsion systems.
       ❹ Heating, ventilation and air conditioning of buildings and vehicles.
       ❺ Environmental hazards (air pollution, transport of contaminants).
       ❻ Film coating, thermoforming in material processing applications.
        ❼ Processes in the human body (blood flow, breathing).

CFD does not substitute the measurements entirely, but the amount of experimentation and the overall cost can be reduced significantly. Equipment and personnel are expensive and difficult to transport. CFD simulations are relatively inexpensive, and costs are likely to decrease as computers become more prevailing. CFD provides an insight into flow patterns that are difficult, expensive or impossible to study using traditional (experimental) methods. CFD simulations can be performed in a short period of time. This quick turnaround means that engineering data can be presented early in the design process. CFD permits better control over the physical process and offers the capability to isolate specific phenomena for study. Experiments only allow data to be extracted at a limited number of locations in the system (pressure and temperature probes, heat flux gauges). CFD allows the specialist to inspect a large number of locations in the region of interest and yields a comprehensive set of flow parameters for examination. CFD solutions depend upon physical representations of real-world processes (turbulence, compressibility, chemistry, multiphase flow). The CFD solutions can only be as accurate as the physical models on which they are based. The accuracy of the CFD solution is only as good as the initial/boundary conditions provided to the numerical model.


University of Dayton


Ph.D. Researcher

❶As a researcher in the Department of Mechanical and Aerospace Engineering, I am currently working on employing the active subspace method (ASM) on Ducted wind turbines to discover and exploit low-dimensional, monotonic trends in the quantity of interest as a function of the design. This will allow finding an optimal design with reduced computational cost.

Roadmap of the current research.

❷Vertical axis wind turbines such as Darrieus turbines are a very interesting type of wind turbines, but this type for turbines has a low performance compared to horizontal axis wind turbines. Therefore, further research work is needed to increase its performance to match the higher demand of the power generation in small-scale applications. The main target of the current work is to increase the output power coefficient Cp of a straight-bladed Darrieus wind turbine (H-rotor) using OpenFOAM and the Genetic Algorithm.

Lab Instructor

My experience here will be provided at the end of April 2019