Immersive artificial intelligence system for dangerous heat transfer experiments

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About This Project

Experimental Heat transfer enhancement studies involve high-risk experiments in high temperature and high pressure laboratory environments. These experiments are conducted by experimenter physically present in the lab. We propose to study if smart-artificial intelligent sensor systems could make heat transfer labs safer and mitigate personnel danger and save time. We aim to make the Heat Transfer Systems smart, safe and cost-effective for universities and other laboratories.

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What is the context of this research?

The world is replete with technology, and every bit of it has a common enemy:heat. If too much heat builds up in a power turbine blade, radar array or smartphone chips, materials can fail, often irreversibly. Hence, heat transfer enhancement studies are vital in allowing engineers to design cooler [computer] chips that will run at a higher heat flux for better performance without failure. In MTHSS project, an amalgamation of Artificial Intelligence and smart systems to the safer spray cooling heat transfer enhancement system is proposed. This would enable a faster, safer laboratory environment for the experimenter. A spray-cooling system indigenously developed at USC will be studied for fail-proof safety, time-dependent data analysis and make futuristic leak projections using AI system.

What is the significance of this project?

Researchers working in heat transfer enhancement studies perform experiments under high temperature and pressure conditions. Classic examples include nuclear-fuel-rod, naval powerplant experiments, etc. Products such as superheated steam from the experiment are invisible and hazardous can can cause skin burns or cut the flesh of the experimenter within seconds. Due to the inherent dangers, minimal experiments are conducted simulating real-life conditions. Using video monitoring, alarm systems and AI in conjugation, we can notify researchers when experimental chambers have reached steady-state conditions and ensure system safety. We could neutralize the possibilities of any injury or burns to the experimenter due to unknown leaks or malfunctions by use of appropriate sensor system.

What are the goals of the project?

The goals of the project are three-fold: 1) create a stand-alone heat transfer enhancement system using sensors, AI and smart devices, 2) compare AI system effectiveness compared with the traditional-manual experimentation for data acquisition and remote access, and 3) create a mobile application to control the set-up remotely and access the data in real-time that can alert when leaks occur and enable the system to turn-on and shut down. The experimental equipment in the spray cooling system such as pump, chiller etc. would be connected to the smart systems and the sensors will be installed around the experimental setup and the entire set-up will be video monitored and programmed to shut-off in the event of a malfunction.

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Sowmya Raghu is a Research Associate and Azzam Salman is a Graduate Student in the Enhanced Heat Transfer Laboratory at the University of South Carolina with experience in simulation and experimental work in heat transfer studies in gas turbine engines and microchannels. They are currently venturing into the incorporation of Artificial Intelligent Systems in such studies. In Phase-1 of the project, with the advice of Dr. Jamil Khan, they are planning to work on this project for 5 hours per week to learn coding for AI and Machine learning by taking an edX course by Microsoft. AI equipment cost would go towards purchase of sensors,smart plugs, Amazon Echo Show and Google Home for virtual assistant integration and to set up a local WiFi network with 5 GHz frequency at school and monthly WiFi costs. Preliminary usage of Dialog-Flow free edition and upgrade to enterprise edition are AI software leaning tool costs.

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It is very interesting project. Using a smart artificial intelligent system in heat transfer enhancement we’ll be very helpful for researchers. It will reduce the risks of hazardous environment by remotely controlled equipment. Moreover, for experimental work that takes long time, it will be very helpful and time saving to have remote smart AI that controlling the experiment instead of having the researcher physically in the lab.
This is an interesting project which touches upon a critical issue with heat transfer experiments/systems whereby the safety of the experimenter is of paramount interest by integrating artificial intelligence to monitor the whole system while it is in operation and for sensing possible leaks and potential dangers. A system like this could be used to monitor experiments in various fields. I am highly looking forward to the outcome of this project.

Project Timeline

The Phase-1 of the project will be completed within 4 month time frame. The project will be initiated in December and will be completed by the March. During this period, the AI system would be set up to operate multiple components in heat transfer system from data acquisition to operating a pump. One conference publication, one journal publication and an invention disclosure is expected by the end of this project .

Dec 01, 2018

MHTSS Project Launch

Dec 05, 2018

Procurement of materials

Dec 14, 2018

WiFi and Smart plug set up with working checks

Jan 15, 2019

Progress Report 1 for backers and supports

Jan 31, 2019

Completion of course -  Microsoft Professional AI program

Meet the Team

Sowmya Raghu
Sowmya Raghu
Ph.D. Student

Affiliates

University of South Carolina
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Azzam S. Salman
Azzam S. Salman
Graduate Research Assistant

Affiliates

University of South Carolina
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Jamil Khan
Jamil Khan
Head of Department - Mechanical Engineering

Affiliates

University of South Carolina
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Sowmya Raghu

I am currently a first-year Ph.D. Student in the Department of Mechanical Engineering at the University of South Carolina. I have been awarded Grace Jordan McFadden Professor Program Fellowship by the Graduate School at UofSC. Before joining Ph.D., I worked as an adjunct faculty and research associate in the Department of Mechanical Engineering at the University of South Carolina. I completed my Master's in Aerospace Engineering from The Pennsylvania State University with minor in Computational Engineering. I have completed my Bachelor's in Aeronautical Engineering from Anna University, India. I have previously worked in Hindustan Aeronautical Limited in Bangalore as a Graduate Trainee in the Engine division. I have always been fascinated by gas turbine engines and been working in the field of heat transfer and turbo-machinery for the last four years. I have ventured into micro-channel and simulated nuclear fuel rod studies since February 2018 at the University of South Carolina. I have received several awards and accolades for my outstanding research and community outreach during my B.E and MS.

I am venturing into the upcoming and promising arena of incorporation of Artificial Intelligent systems in Heat transfer Enhancement studies with a motive of providing a safer environment for experimenters working in a hazardous environment and save valuable experimenter's time by using monitoring systems for the experiment.

I aspire to be a Professor moving forward in the field of Aerospace and Mechanical Engineering. I would like to create STEM outreach for young girl students and provide job opportunities for Women in Engineering.

Azzam S. Salman

I received my BSc and MSc in Mechanical Engineering from Mosul University, Iraq in 2006 and 2009 respectively. I joined Enhanced Heat transfer Lab as a Ph.D. student at the University of South Carolina in the summer of 2014, after getting a scholarship from the Iraqi government. My main research focuses on spray cooling heat transfer enhancement experimentally. Also, working on spray cooling modeling and simulation by using STAR CCM+ to study the heat transfer process on the surfaces in detail. My future work will be using artificial intelligence to run and control heat transfer experiments with high heat flux. These experiments require a long time to reach the steady-state conditions, and sitting beside the experimental set up for a long time has a potential risk. I think using artificial intelligence will be a promising technique for saving time, and reducing the potential risk of heat transfer experiments.

Jamil Khan

Professor Dr. Jamil Khan is the Head of the Department of Mechanical Engineering. He has been working in the field of heat transfer and fluid flow with phase change systems since the 1990's. He has been involved in enhanced heat transfer research for heat dissipation from electronic devices using both passive and active micro-channel cooling at single phase and with boiling.
Dr. Khan has established the Enhanced Heat Transfer Lab in the University of South Carolina's Department of Mechanical Engineering. Computational and experimental analysis of coupled electro-thermal processes related to high temperature fuel cells; experimental, modeling and computational studies of natural convection heat transfer and fluid-flow, and related to thermal hydraulics for nuclear reactor rod bundles are the main research arenas of the Lab group comprising of graduate and undergraduate students. Dr. Khan has published more than 145 papers and has won numerous awards for Research and Teaching.

Lab Notes

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Additional Information

Learning AI module from the edX course - https://www.edx.org/microsoft-... would be an essential part in progressing towards AI system implementation. In the Phase-2 of the project, an inexpensive, immersive virtual automated lab set-up will be developed for micro-channel studies


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