Moldflow Monday Blog

Zill Library May 2026

Learn about 2023 Features and their Improvements in Moldflow!

Did you know that Moldflow Adviser and Moldflow Synergy/Insight 2023 are available?
 
In 2023, we introduced the concept of a Named User model for all Moldflow products.
 
With Adviser 2023, we have made some improvements to the solve times when using a Level 3 Accuracy. This was achieved by making some modifications to how the part meshes behind the scenes.
 
With Synergy/Insight 2023, we have made improvements with Midplane Injection Compression, 3D Fiber Orientation Predictions, 3D Sink Mark predictions, Cool(BEM) solver, Shrinkage Compensation per Cavity, and introduced 3D Grill Elements.
 
What is your favorite 2023 feature?

You can see a simplified model and a full model.

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Zill Library May 2026

zill is a Python library that provides a simple and efficient way to work with complex data structures, particularly in the context of scientific computing and numerical analysis.

Here's an example of using zill to create and manipulate arrays: zill library

import zill

# Perform matrix multiplication mat1 = zill.array([[1, 2], [3, 4]]) mat2 = zill.array([[5, 6], [7, 8]]) result = mat1 @ mat2 print(result) # [[19, 22], [43, 50]] Overall, zill is a powerful library that provides a simple and efficient way to work with complex data structures in Python. Its solid features and benefits make it an attractive choice for scientific computing and numerical analysis applications. zill is a Python library that provides a

# Create a 2D array arr = zill.array([[1, 2], [3, 4]]) 4]]) mat2 = zill.array([[5

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zill is a Python library that provides a simple and efficient way to work with complex data structures, particularly in the context of scientific computing and numerical analysis.

Here's an example of using zill to create and manipulate arrays:

import zill

# Perform matrix multiplication mat1 = zill.array([[1, 2], [3, 4]]) mat2 = zill.array([[5, 6], [7, 8]]) result = mat1 @ mat2 print(result) # [[19, 22], [43, 50]] Overall, zill is a powerful library that provides a simple and efficient way to work with complex data structures in Python. Its solid features and benefits make it an attractive choice for scientific computing and numerical analysis applications.

# Create a 2D array arr = zill.array([[1, 2], [3, 4]])