@@ -52,7 +52,7 @@ PaddleScience 是一个基于深度学习框架 PaddlePaddle 开发的科学计
5252| 飞行器设计 | [ MeshGraphNets] ( https://aistudio.baidu.com/projectdetail/5322713 ) | 数据驱动 | GNN | 监督学习 | [ Data] ( https://aistudio.baidu.com/datasetdetail/184320 ) | [ Paper] ( https://arxiv.org/abs/2010.03409 ) |
5353| 飞行器设计 | [ 火箭发动机真空羽流] ( https://aistudio.baidu.com/projectdetail/4486133 ) | 数据驱动 | CNN | 监督学习 | [ Data] ( https://aistudio.baidu.com/datasetdetail/167250 ) | - |
5454| 飞行器设计 | [ Deep-Flow-Prediction] ( https://aistudio.baidu.com/projectdetail/5671596 ) | 数据驱动 | TurbNetG | 监督学习 | [ Data] ( https://aistudio.baidu.com/datasetdetail/197778 ) | [ Paper] ( https://arxiv.org/abs/1810.08217 ) |
55- | 通用流场模拟 | [ 气动外形设计] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/amgnet/ ) | 数据驱动 | AMGNet | 监督学习 | [ Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/AMGNet/data.zip ) | [ Paper] ( https://arxiv.org/abs/1810.08217 ) |
55+ | 通用流场模拟 | [ 气动外形设计] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/amgnet ) | 数据驱动 | AMGNet | 监督学习 | [ Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/AMGNet/data.zip ) | [ Paper] ( https://arxiv.org/abs/1810.08217 ) |
5656| 流固耦合 | [ 涡激振动] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/viv ) | 机理驱动 | MLP | 半监督学习 | [ Data] ( https://github.com/PaddlePaddle/PaddleScience/blob/develop/examples/fsi/VIV_Training_Neta100.mat ) | [ Paper] ( https://arxiv.org/abs/2206.03864 ) |
5757| 多相流 | [ 气液两相流] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/bubble ) | 机理驱动 | BubbleNet | 半监督学习 | [ Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/BubbleNet/bubble.mat ) | [ Paper] ( https://pubs.aip.org/aip/adv/article/12/3/035153/2819394/Predicting-micro-bubble-dynamics-with-semi-physics ) |
5858| 多相流 | [ twophasePINN] ( https://aistudio.baidu.com/projectdetail/5379212 ) | 机理驱动 | MLP | 无监督学习 | - | [ Paper] ( https://doi.org/10.1016/j.mlwa.2021.100029 ) |
@@ -62,22 +62,22 @@ PaddleScience 是一个基于深度学习框架 PaddlePaddle 开发的科学计
6262| 流场高分辨率重构 | [ 基于Voronoi嵌入辅助深度学习的稀疏传感器全局场重建] ( https://aistudio.baidu.com/projectdetail/5807904 ) | 数据驱动 | CNN | 监督学习 | [ Data1] ( https://drive.google.com/drive/folders/1K7upSyHAIVtsyNAqe6P8TY1nS5WpxJ2c ) <br >[ Data2] ( https://drive.google.com/drive/folders/1pVW4epkeHkT2WHZB7Dym5IURcfOP4cXu ) <br >[ Data3] ( https://drive.google.com/drive/folders/1xIY_jIu-hNcRY-TTf4oYX1Xg4_fx8ZvD ) | [ Paper] ( https://arxiv.org/pdf/2202.11214.pdf ) |
6363| 流场高分辨率重构 | 基于扩散的流体超分重构<sup >coming soon</sup > | 数理融合 | DDPM | 监督学习 | - | [ Paper] ( https://www.sciencedirect.com/science/article/pii/S0021999123000670 ) |
6464| 求解器耦合 | [ CFD-GCN] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/cfdgcn ) | 数据驱动 | GCN | 监督学习 | [ Data] ( https://aistudio.baidu.com/aistudio/datasetdetail/184778 ) <br >[ Mesh] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/CFDGCN/meshes.tar ) | [ Paper] ( https://arxiv.org/abs/2007.04439 ) |
65- | 受力分析 | [ 1D 欧拉梁变形] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/euler_beam/ ) | 机理驱动 | MLP | 无监督学习 | - | - |
65+ | 受力分析 | [ 1D 欧拉梁变形] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/euler_beam ) | 机理驱动 | MLP | 无监督学习 | - | - |
6666| 受力分析 | [ 2D 平板变形] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/biharmonic2d ) | 机理驱动 | MLP | 无监督学习 | - | [ Paper] ( https://arxiv.org/abs/2108.07243 ) |
6767| 受力分析 | [ 3D 连接件变形] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/bracket ) | 机理驱动 | MLP | 无监督学习 | [ Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/bracket/bracket_dataset.tar ) | [ Tutorial] ( https://docs.nvidia.com/deeplearning/modulus/modulus-v2209/user_guide/foundational/linear_elasticity.html ) |
6868| 受力分析 | [ 结构震动模拟] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/phylstm ) | 机理驱动 | PhyLSTM | 监督学习 | [ Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/PhyLSTM/data_boucwen.mat ) | [ Paper] ( https://arxiv.org/abs/2002.10253 ) |
69- | 受力分析 | [ 2D 弹塑性结构] ( https://paddlescience-docs.readthedocs.io/zh/examples/epnn.md ) | 机理驱动 | EPNN | 无监督学习 | [ Train Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/epnn/dstate-16-plas.dat ) <br >[ Eval Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/epnn/dstress-16-plas.dat ) | [ Paper] ( https://arxiv.org/abs/2204.12088 ) |
70- | 受力分析和逆问题 | [ 3D 汽车控制臂变形] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/control_arm.md ) | 机理驱动 | MLP | 无监督学习 | - | - |
71- | 拓扑优化 | [ 2D 拓扑优化] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/topopt.md ) | 数据驱动 | TopOptNN | 监督学习 | [ Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/topopt/top_dataset.h5 ) | [ Paper] ( https://arxiv.org/pdf/1709.09578 ) |
72- | 热仿真 | [ 1D 换热器热仿真] ( https://paddlescience-docs.readthedocs.io/zh/examples/heat_exchanger.md ) | 机理驱动 | PI-DeepONet | 无监督学习 | - | - |
73- | 热仿真 | [ 2D 热仿真] ( https://paddlescience-docs.readthedocs.io/zh/examples/heat_pinn.md ) | 机理驱动 | PINN | 无监督学习 | - | [ Paper] ( https://arxiv.org/abs/1711.10561 ) |
69+ | 受力分析 | [ 2D 弹塑性结构] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/ examples/epnn ) | 机理驱动 | EPNN | 无监督学习 | [ Train Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/epnn/dstate-16-plas.dat ) <br >[ Eval Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/epnn/dstress-16-plas.dat ) | [ Paper] ( https://arxiv.org/abs/2204.12088 ) |
70+ | 受力分析和逆问题 | [ 3D 汽车控制臂变形] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/control_arm ) | 机理驱动 | MLP | 无监督学习 | - | - |
71+ | 拓扑优化 | [ 2D 拓扑优化] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/topopt ) | 数据驱动 | TopOptNN | 监督学习 | [ Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/topopt/top_dataset.h5 ) | [ Paper] ( https://arxiv.org/pdf/1709.09578 ) |
72+ | 热仿真 | [ 1D 换热器热仿真] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/ examples/heat_exchanger ) | 机理驱动 | PI-DeepONet | 无监督学习 | - | - |
73+ | 热仿真 | [ 2D 热仿真] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/ examples/heat_pinn ) | 机理驱动 | PINN | 无监督学习 | - | [ Paper] ( https://arxiv.org/abs/1711.10561 ) |
7474
7575<br >
7676<p align =" center " ><b >材料科学(AI for Material)</b ></p >
7777
7878| 问题类型 | 案例名称 | 优化算法 | 模型类型 | 训练方式 | 数据集 | 参考资料 |
7979| -----| ---------| -----| ---------| ----| ---------| ---------|
80- | 材料设计 | [ 散射板设计(反问题)] ( . /zh/examples/hpinns.md ) | 数理融合 | 数据驱动 | 监督学习 | [ Train Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/hPINNs/hpinns_holo_train.mat ) <br >[ Eval Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/hPINNs/hpinns_holo_valid.mat ) | [ Paper] ( https://arxiv.org/pdf/2102.04626.pdf ) |
80+ | 材料设计 | [ 散射板设计(反问题)] ( https://paddlescience-docs.readthedocs.io /zh/latest/zh/ examples/hpinns) | 数理融合 | 数据驱动 | 监督学习 | [ Train Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/hPINNs/hpinns_holo_train.mat ) <br >[ Eval Data] ( https://paddle-org.bj.bcebos.com/paddlescience/datasets/hPINNs/hpinns_holo_valid.mat ) | [ Paper] ( https://arxiv.org/pdf/2102.04626.pdf ) |
8181| 材料生成 | 面向对称感知的周期性材料生成<sup >coming soon</sup > | 数据驱动 | SyMat | 监督学习 | - | - |
8282
8383<br >
@@ -86,15 +86,16 @@ PaddleScience 是一个基于深度学习框架 PaddlePaddle 开发的科学计
8686| 问题类型 | 案例名称 | 优化算法 | 模型类型 | 训练方式 | 数据集 | 参考资料 |
8787| -----| ---------| -----| ---------| ----| ---------| ---------|
8888| 天气预报 | [ FourCastNet 气象预报] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/fourcastnet ) | 数据驱动 | FourCastNet | 监督学习 | [ ERA5] ( https://app.globus.org/file-manager?origin_id=945b3c9e-0f8c-11ed-8daf-9f359c660fbd&origin_path=%2F~%2Fdata%2F ) | [ Paper] ( https://arxiv.org/pdf/2202.11214.pdf ) |
89+ | 天气预报 | [ NowCastNet 气象预报] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/nowcastnet ) | 数据驱动 | NowCastNet | 监督学习 | [ MRMS] ( https://app.globus.org/file-manager?origin_id=945b3c9e-0f8c-11ed-8daf-9f359c660fbd&origin_path=%2F~%2Fdata%2F ) | [ Paper] ( https://www.nature.com/articles/s41586-023-06184-4 ) |
8990| 天气预报 | GraphCast 气象预报<sup >coming soon</sup > | 数据驱动 | GraphCastNet* | 监督学习 | - | [ Paper] ( https://arxiv.org/pdf/2202.11214.pdf ) |
9091| 大气污染物 | [ UNet 污染物扩散] ( https://aistudio.baidu.com/projectdetail/5663515?channel=0&channelType=0&sUid=438690&shared=1&ts=1698221963752 ) | 数据驱动 | UNet | 监督学习 | [ Data] ( https://aistudio.baidu.com/datasetdetail/198102 ) | - |
9192
9293<!-- --8<-- [start:update] -->
9394## 🕘最近更新
9495
9596- 添加多目标优化算法 [ Relobralo] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/api/loss/mtl/#ppsci.loss.mtl.Relobralo ) 。
96- - 添加气泡流求解案例([ Bubble] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/bubble/ ) )、机翼优化案例([ DeepCFD] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/deepcfd/ ) )、热传导仿真案例([ HeatPINN] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/heat_pinn/ ) )、非线性短临预报模型([ Nowcasting(仅推理)] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/nowcastnet ) )、拓扑优化案例([ TopOpt] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/topopt ) )、矩形平板线弹性方程求解案例([ Biharmonic2D] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/biharmonic2d ) )。
97- - 添加二维血管案例([ LabelFree-DNN-Surrogate] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/labelfree_DNN_surrogate/#4 ) )、空气激波案例([ ShockWave] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/shock_wave/ ) )、去噪网络模型([ DUCNN] ( https://github.com/PaddlePaddle/PaddleScience/tree/develop/jointContribution/DU_CNN ) )、风电预测模型([ Deep Spatial Temporal] ( https://github.com/PaddlePaddle/PaddleScience/tree/develop/jointContribution/Deep-Spatio-Temporal ) )、域分解模型([ XPINNs] ( https://github.com/PaddlePaddle/PaddleScience/tree/develop/jointContribution/XPINNs ) )、积分方程求解案例([ Volterra Equation] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/volterra_ide/ ) )、分数阶方程求解案例([ Fractional Poisson 2D] ( https://github.com/PaddlePaddle/PaddleScience/blob/develop/examples/fpde/fractional_poisson_2d.py ) )。
97+ - 添加气泡流求解案例([ Bubble] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/bubble ) )、机翼优化案例([ DeepCFD] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/deepcfd/ ) )、热传导仿真案例([ HeatPINN] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/heat_pinn ) )、非线性短临预报模型([ Nowcasting(仅推理)] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/nowcastnet ) )、拓扑优化案例([ TopOpt] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/topopt ) )、矩形平板线弹性方程求解案例([ Biharmonic2D] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/biharmonic2d ) )。
98+ - 添加二维血管案例([ LabelFree-DNN-Surrogate] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/labelfree_DNN_surrogate/#4 ) )、空气激波案例([ ShockWave] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/shock_wave/ ) )、去噪网络模型([ DUCNN] ( https://github.com/PaddlePaddle/PaddleScience/tree/develop/jointContribution/DU_CNN ) )、风电预测模型([ Deep Spatial Temporal] ( https://github.com/PaddlePaddle/PaddleScience/tree/develop/jointContribution/Deep-Spatio-Temporal ) )、域分解模型([ XPINNs] ( https://github.com/PaddlePaddle/PaddleScience/tree/develop/jointContribution/XPINNs ) )、积分方程求解案例([ Volterra Equation] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/volterra_ide ) )、分数阶方程求解案例([ Fractional Poisson 2D] ( https://github.com/PaddlePaddle/PaddleScience/blob/develop/examples/fpde/fractional_poisson_2d.py ) )。
9899- 针对串联方程和复杂方程场景,` Equation ` 模块支持基于 [ sympy] ( https://docs.sympy.org/dev/tutorials/intro-tutorial/intro.html ) 的符号计算,并支持和 python 函数混合使用([ #507 ] ( https://github.com/PaddlePaddle/PaddleScience/pull/507 ) 、[ #505 ] ( https://github.com/PaddlePaddle/PaddleScience/pull/505 ) )。
99100- ` Geometry ` 模块和 ` InteriorConstraint ` 、` InitialConstraint ` 支持计算 SDF 微分功能([ #539 ] ( https://github.com/PaddlePaddle/PaddleScience/pull/539 ) )。
100101- 添加 ** M** ulti** T** ask** L** earning(` ppsci.loss.mtl ` ) 多任务学习模块,针对多任务优化(如 PINN 方法)进一步提升性能,使用方式:[ 多任务学习指南] ( https://paddlescience-docs.readthedocs.io/zh/latest/zh/user_guide/#24 ) ([ #493 ] ( https://github.com/PaddlePaddle/PaddleScience/pull/505 ) 、[ #492 ] ( https://github.com/PaddlePaddle/PaddleScience/pull/505 ) )。
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