【Hackathon 5th No.56】A Physics-Informed Neural Network to solve 2D steady-state heat equation#692
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科学计算的官方活动群，可以加一下 |
liaoxin2
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Oct 18, 2023
| \frac{\partial^2T}{\partial x^2} + \frac{\partial^2T}{\partial y^2}=0 | ||
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| 其中，$T$ 表示温度分布，传统的求解方法涉及使用数值方法如有限元法或有限差分法，这些方法通常需要离散化领域并求解大规模矩阵系统。近年来，基于物理信息的神经网络（Physics-informed neural networks, PINN）逐渐成为求解偏微分方程的新方法。PINN 结合了神经网络的灵活性和对物理约束的建模能力，能够直接在连续领域中解决偏微分方程问题。 |
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“其中，$T$ 表示温度分布”中$前后请检查一下是否都有英文空格，无法显示出来
| 热传导是自然界中的常见现象，广泛应用于工程、科学和技术领域。了解和模拟传热过程对于设计和优化热传导设备、材料和系统至关重要。2D 定常传热方程描述了稳态热传导过程，其数学表达形式为： | ||
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| $$ | ||
| \frac{\partial^2T}{\partial x^2} + \frac{\partial^2T}{\partial y^2}=0 |
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请全文检查一下，公式中也需要有标点符号
没有理解“公式中也需要有标点符号”是啥意思
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就是在每一行数学公式后面加上英文逗号或者句号
好的，已添加
liaoxin2
suggested changes
Oct 18, 2023
| 热传导是自然界中的常见现象，广泛应用于工程、科学和技术领域。了解和模拟传热过程对于设计和优化热传导设备、材料和系统至关重要。2D 定常传热方程描述了稳态热传导过程，其数学表达形式为： | ||
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| $$ | ||
| \frac{\partial^2T}{\partial x^2} + \frac{\partial^2T}{\partial y^2}=0 |
liaoxin2
approved these changes
Oct 18, 2023
luotao1
approved these changes
Oct 18, 2023
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Add Hackathon 5th Science 56 RFC
关联：PaddlePaddle/PaddleScience#560