powerHull is a web-based resistance prediction software. It started as a personal project to learn Python and now decided to post it here to get your feedback. It is all written in python using the Django web framework. You can access it from here powerhull.azurewebsites.net
Because it is hosted on Microsoft's cloud free tier service, sometimes accessing the website might take a bit. Current features include:
- Bare hull resistance prediction
- Appendage resistance estimation (rudders, shafts, struts, trim-tabs)
- Air drag estimation
- Adding resistance margin
- Setting overall propulsion efficiency and transmission loss for estimating total required power
- User registration for storing/retrieving parameters
- Metric/Imperial units
- Saving results locally in csv format (Excel compatible)
Currently implemented methods:
- Original Savitsky method including whisker spray resistance, lift and drag from trim tabs, porpoising stability assesment
- Modified Savitsky with the Blount & Fox M-Factor for hump-speed region
- Mercier & Savitsky for pre-planing speeds
- VTT Series
- Series 62
I hope you can find this work useful and maybe comment here with some feedback regarding improvements and future additions.
Because it is hosted on Microsoft's cloud free tier service, sometimes accessing the website might take a bit. Current features include:
- Bare hull resistance prediction
- Appendage resistance estimation (rudders, shafts, struts, trim-tabs)
- Air drag estimation
- Adding resistance margin
- Setting overall propulsion efficiency and transmission loss for estimating total required power
- User registration for storing/retrieving parameters
- Metric/Imperial units
- Saving results locally in csv format (Excel compatible)
Currently implemented methods:
- Original Savitsky method including whisker spray resistance, lift and drag from trim tabs, porpoising stability assesment
- Modified Savitsky with the Blount & Fox M-Factor for hump-speed region
- Mercier & Savitsky for pre-planing speeds
- VTT Series
- Series 62
I hope you can find this work useful and maybe comment here with some feedback regarding improvements and future additions.