Dear friend Dr Janardhan Narambhatla

The error message you are seeing suggests that there might be some inconsistency between the element types used in your heat transfer analysis. Specifically, the error message is indicating that you have stress-displacement elements or other elements without temperature degree of freedom, which are not allowed in a heat transfer analysis.

In ANSYS, there are different element types available for different types of analyses, such as mechanical, thermal, and coupled analyses. It is important to select the appropriate element type for your specific analysis to ensure accurate results.

Based on the error message you are seeing; it is possible that you have not fully updated all of the elements in your model to the appropriate element type for a heat transfer analysis. Even if you have updated most of the elements, if there are still a few elements that are not updated, this could cause the error message to appear.

To resolve this issue, you will need to ensure that all elements in your model are compatible with the type of analysis you are running. This may involve changing the element type for some or all of the elements in your model.

If you have already changed the element type for all elements in your model and the error message still persists, it is possible that there are other issues with your model that need to be addressed. In this case, it may be helpful to consult ANSYS documentation or support resources for further guidance.

Additionally, it is worth noting that the appropriate minimum number of samples for running a PMF model will depend on the specific application and the complexity of the model. Generally, it is recommended to have a sufficiently large sample size to ensure statistical significance and accuracy of results. However, the exact minimum number of samples will depend on the specific requirements of your analysis.

Here are some references related to your previous question about block size in the base model bootstrap:

- Efron, B. (1979). Bootstrap methods: another look at the jackknife. Annals of Statistics, 7(1), 1-26. https://doi.org/10.1214/aos/1176344552

- Davison, A. C., & Hinkley, D. V. (1997). Bootstrap methods and their application. Cambridge University Press. https://doi.org/10.1017/CBO9780511802843

- Hall, P. (1988). Theoretical comparison of bootstrap confidence intervals. Annals of Statistics, 16(3), 927-953. https://doi.org/10.1214/aos/1176350949

And here are some references related to your question about the impact of electricity reduction/loadshedding on the small business sector:

- Steyn, L., & Brent, A. C. (2016). A framework for assessing the impact of power outages on SMMEs in South Africa. Energy Policy, 92, 602-611. https://doi.org/10.1016/j.enpol.2016.02.024

- Barnes, D. F., Samad, T., & Dijk, M. P. (2016). The impact of power outages on small and medium enterprises in Jamaica. Energy Policy, 96, 674-682. https://doi.org/10.1016/j.enpol.2016.06.019

- Shekhar, S., & Bazilian, M. (2016). Impact of electricity access on rural income generation: Evidence from Guatemala. Energy for Sustainable Development, 32, 43-50. https://doi.org/10.1016/j.esd.2016.02.006