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