Model building with neural networks
I would assume that the physical input parameters occur in some sort of sequence &amp; the Neural Network can easily identify patterns from it. 

I would suggest you do some scaling on the output parameters. Or use non-linear activation functions so that your output ranges from upper bound &amp; lower bound of that function.

Also i would like to suggest that you use LSTM. Recent time-series application using LSTM have promising outputs. Their application ranges from text generation to pixel filling in images &amp; videos. They can be used to get bounded outputs &amp; using torch neural networks allow you to implement them as per your requirements.

You can find implementation guide for Neural Network using torch library here