https://github.com/leo27945875/python_stable_3d_truss_analysis
slientruss3d : Python for stable truss analysis and optimization tool
https://github.com/leo27945875/python_stable_3d_truss_analysis
architecture civil-engineering deep-learning generate-truss-data genetic-algorithm graph-deep-learning optimization python python3 pytorch pytorch-geometric slientruss3d structural-analysis structural-engineering structure-optimization truss truss-analysis truss-optimization truss-solver
Last synced: 6 months ago
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slientruss3d : Python for stable truss analysis and optimization tool
- Host: GitHub
- URL: https://github.com/leo27945875/python_stable_3d_truss_analysis
- Owner: leo27945875
- License: mit
- Created: 2021-12-05T00:55:35.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2023-02-14T04:01:55.000Z (over 2 years ago)
- Last Synced: 2024-10-13T15:44:17.983Z (7 months ago)
- Topics: architecture, civil-engineering, deep-learning, generate-truss-data, genetic-algorithm, graph-deep-learning, optimization, python, python3, pytorch, pytorch-geometric, slientruss3d, structural-analysis, structural-engineering, structure-optimization, truss, truss-analysis, truss-optimization, truss-solver
- Language: Python
- Homepage:
- Size: 5.44 MB
- Stars: 23
- Watchers: 2
- Forks: 7
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# **slientruss3d** : Python for stable truss analysis and deep learning research
[](https://pypi.org/project/slientruss3d/)
[](https://pypi.org/project/slientruss3d/)
[](https://github.com/leo27945875/Python_Stable_3D_Truss_Analysis/releases)
[](https://pypi.org/project/slientruss3d/)
[](https://pypi.org/project/slientruss3d/)
[](https://github.com/leo27945875/Python_Stable_3D_Truss_Analysis/blob/master/LICENSE.txt)
---
## Description
**`slientruss3d`** is a python package which can solve the resistances, internal forces and joint dispalcements in a stable 2D or 3D truss by `direct stiffness method`. And also can do truss optimization by `Genetic Algorithm (GA)`, `generate truss data` and `work with pytorch-geometric` conveniencely.
This repo is writen by :
```text
Taiwan (臺灣)
Department of Civil Engineering (土木工程學系)
National Yang Ming Chiao Tung University (NYCU) (國立陽明交通大學)
Shih-Chi Cheng (鄭適其)
```
## Content
1. **Installaltion**
- [Install](#Install)
- [Time consuming](#Time-consuming)
- [Update log](#Update-log)
2. **Quick start**
- [Basic example](./detail/how_to_use.md#Basic-example) >( Just read this if you aren't familiar with coding 😎 )
- [Truss](./detail/how_to_use.md#Truss)
- [Member](./detail/how_to_use.md#Member)
- [MemberType](./detail/how_to_use.md#Define-a-new-member)
- [SupportType](./detail/how_to_use.md#Define-a-new-joint)
3. **Combine with JSON**
- [Example code](./detail/combine_with_JSON.md#Example)
- [Embed in Web APP](./detail/combine_with_JSON.md#Embed-in-Web-APP)
- [Format of JSON](./detail/combine_with_JSON.md#Format-of-JSON)
4. **Plot your truss**
- [Example code](./detail/plot_your_truss.md#Example-code)
- [Example figures](./detail/plot_your_truss.md#Example-figures)
5. **Truss optimization**
- [Introduction](./detail/truss_optimization.md#Introduction)
- [Gene](./detail/truss_optimization.md#Gene-data-structure)
- [Fitness function](./detail/truss_optimization.md#Fitness-function)
- [Crossover](./detail/truss_optimization.md#Crossover)
- [Evolution policy](./detail/truss_optimization.md#Evolution-policy)
- [Example code](./detail/truss_optimization.md#Example)
- [Geneic algorithm](./detail/truss_optimization.md#Geneic-algorithm)
- [Customization](./detail/truss_optimization.md#Customization)
6. **Generate truss data automatically**
- [Introduction](./detail/gen_truss.md#Introduction)
- [Generate cube-like truss](./detail/gen_truss.md#Generate-cube-like-truss)
- [Data Augmentation](./detail/gen_truss.md#data-augmentation)
7. **Convert Truss to Pytorch-Geometric HeteroData**
- [Introduction](./detail/to_PyG.md#introduction)
- [Installation](./detail/to_PyG.md#installation)
- [How to use it ?](./detail/to_PyG.md#how-to-use-it)
- [Fields in HeteroData](./detail/to_PyG.md#fields-in-heterodata)
- [Example code](./detail/to_PyG.md#example-code)
---
## Install
First, check your python version:
```text
Python must >= 3.9.7
```
Second, download the **`slientruss3d`** package:
```text
pip install slientruss3d
```
---
## Time consuming
The following are time consuming tests for doing structural analysis for each truss (Each testing runs for 30 times and takes average !).
- **`6-bar truss`** : 0.00037(s)
- **`10-bar truss`** : 0.00050(s)
- **`25-bar truss`** : 0.00126(s)
- **`47-bar truss`** : 0.00253(s)
- **`72-bar truss`** : 0.00323(s)
- **`120-bar truss`** : 0.00557(s)
- **`942-bar truss`** : 0.05253(s)
Testing on :
```text
CPU: Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz
RAM: 8GB DDR4 * 2
```
---
## Update log
### New feature in v2.0.0 update !
- _**Important API adjustment**_ : We `simplified the JSON format` in slientruss3d, see the details in [Format of JSON](./detail/combine_with_JSON.md#Format-of-JSON). You can use the `v1_to_v2.py` module in the root folder to convert the old JSON format to the new one rapidly.
- _**Data Augmentation**_ : You can use some new method in **`slientruss3d.generate`** module to do data augmentation to generated cube-like trusses ! See more details in [Data Augmentation](./detail/gen_truss.md#data-augmentation). For example:
- _**Graph Deep Learning**_ : With the increasing importance of deep learning in the field of truss design, we also provide a solution to let our users convert the `Truss` object to the data structure of [`Pytorch-Geometric`](https://github.com/pyg-team/pytorch_geometric) conveniently. See the details in [Convert Truss to Pytorch-Geometric HeteroData](./detail/to_PyG.md#convert-truss-to-pytorch-geometric-heterodata).
### An important API adjustment after v1.3.25 !
After slientruss3d v1.3.25, the method [`Truss.Solve()`](./detail/how_to_use.md#Do-structural-analysis) will return `None` instead of the result of structural analysis. If you want to get the result of structural analysis, please use other getters defined in Truss object such as:
```python
# Get result of structural analysis:
displace, stress, resistance = truss.GetDisplacements(), truss.GetInternalStresses(), truss.GetResistances()
return displace, stress, resistance
```
### New feature in v1.3.0 update !
After slientruss3d v1.3.0, you can use **`slientruss3d.generate`** module to generate truss data automatically. For now, only simple `cube-like` truss can be generated by slientruss3d, but I think this is still a helpful way for anyone who suffers from lake of truss data.
> More details are in [Generate truss data automatically](./detail/gen_truss.md)
### New feature in v1.2.0 update !
After slientruss3d v1.2.0, you could use **`slientruss3d.ga`** module to do `member type selection optimization` conveniencely with `Genetic Algorithm (GA)`! Just simply define the topology of the truss and what member types you want to use, and then you could start the optimization.
> More details are in [Truss optimization](./detail/truss_optimization.md)
Besides GA, there are some new useful methods in the `Truss` object:
```python
class Truss:
...
# Check whether all internal forces are in allowable range or not:
def IsInternalStressAllowed(self, limit, isGetSumViolation=False) -> tuple[bool, dict | float]:
...
# Check whether all internal displacements are in allowable range or not:
def IsDisplacementAllowed(self, limit, isGetSumViolation=False) -> tuple[bool, dict | float]:
...
```
---
## Enjoy 😎 !