16045

GPU Based Real-Time Welding Simulation with Smoothed-Particle Hydrodynamics

Qing Gu
Concordia University, Montreal, Quebec, Canada
Concordia University, 2016

@phdthesis{qing2016gpu,

   title={GPU Based Real-time Welding Simulation with Smoothed-Particle Hydrodynamics},

   author={Qing, Gu},

   year={2016},

   school={Concordia University}

}

Download Download (PDF)   View View   Source Source   

383

views

Welding training is essential in the development of industrialization. A good welder will build robust workpieces that ensure the safety and stability of the product. However, training a welder requires lots of time and access professional welding equipment. Therefore, it is desirable to have a training system that is economical and easy to use. After decades development of computer graphics, sophisticated methodologies are developed in simulation fields, along the advanced hardware, enables the possibility of simulation welding with software. In this thesis, a novel prototype of welding training system is proposed. We use smoothed-particle hydrodynamics (SPH) method to simulate fluid as well as heat transfer and phase changing. In order to accelerate the processing to reach the level of real-time, we adopt CUDA to implement the SPH solver on GPU. Plus, Leap Motion is utilized as the input device to control the welding gun. As the result, the simulation reaches decent frame rate that allows the user control the simulation system interactively. The input device permits the user to adapt to the system in less than 5 minutes. This prototype shows a new direction in the training system that combines VR, graphics, and physics simulation. The further development of VR output device like Oculus Rift will enable the training system to a more immersive level.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

TwitterAPIExchange Object
(
    [oauth_access_token:TwitterAPIExchange:private] => 301967669-yDz6MrfyJFFsH1DVvrw5Xb9phx2d0DSOFuLehBGh
    [oauth_access_token_secret:TwitterAPIExchange:private] => o29ji3VLVmB6jASMqY8G7QZDCrdFmoTvCDNNUlb7s
    [consumer_key:TwitterAPIExchange:private] => TdQb63pho0ak9VevwMWpEgXAE
    [consumer_secret:TwitterAPIExchange:private] => Uq4rWz7nUnH1y6ab6uQ9xMk0KLcDrmckneEMdlq6G5E0jlQCFx
    [postfields:TwitterAPIExchange:private] => 
    [getfield:TwitterAPIExchange:private] => ?cursor=-1&screen_name=hgpu&skip_status=true&include_user_entities=false
    [oauth:protected] => Array
        (
            [oauth_consumer_key] => TdQb63pho0ak9VevwMWpEgXAE
            [oauth_nonce] => 1481142331
            [oauth_signature_method] => HMAC-SHA1
            [oauth_token] => 301967669-yDz6MrfyJFFsH1DVvrw5Xb9phx2d0DSOFuLehBGh
            [oauth_timestamp] => 1481142331
            [oauth_version] => 1.0
            [cursor] => -1
            [screen_name] => hgpu
            [skip_status] => true
            [include_user_entities] => false
            [oauth_signature] => NLPV9bT3ff2NCWaGDhpcd7OTlgs=
        )

    [url] => https://api.twitter.com/1.1/users/show.json
)
Follow us on Facebook
Follow us on Twitter

HGPU group

2080 peoples are following HGPU @twitter

HGPU group © 2010-2016 hgpu.org

All rights belong to the respective authors

Contact us: