Overview

In this case study, we explore how Paul Keutelian, a systems and thermal fluids engineer with extensive experience in Coreform Cubit and MOOSE, leverages these tools to tackle complex simulation workflows in aerospace and nuclear industries. Through strategic use of these advanced software tools, Paul has streamlined his processes to achieve high-quality meshes and reliable simulations in a fraction of the time typically required. We provide insights into how Paul’s workflow enhances both the speed and accuracy of simulation efforts, ultimately enabling his teams to make informed design decisions rapidly.

Problem

Engineers working with complex simulations often face a range of challenges in preparing models for analysis. One common hurdle is managing large assemblies with numerous parts and intricate geometries. Without efficient tools and workflows, the preparation process can be time-consuming, involving repetitive tasks to clean up, decompose, and mesh geometry. Furthermore, achieving accurate simulations depends on the quality and consistency of the mesh, especially for assemblies with both simple and complex geometries.

Paul’s challenge was to develop a streamlined workflow for meshing and refining assemblies that minimizes the time and effort needed to achieve accurate results. He needed to isolate specific components quickly, set up automation to handle repetitive processes, and implement an effective strategy to mesh high-complexity parts. Additionally, the workflow had to enable reliable integration with simulation software like MOOSE, allowing for comprehensive analysis across a range of design scenarios.

Solution

To address these challenges, Paul developed a systematic approach for preparing and meshing assemblies using Coreform Cubit, with further automation and analysis in MOOSE. His workflow integrates several of Coreform Cubit’s powerful features, including CAD data import, geometry manipulation, similarity selection, compositing, and automation through Python scripting. This strategic approach allows Paul to handle complex assemblies with ease and adaptability, ensuring both speed and accuracy in simulation workflows. 

1. Streamlined Assembly Decomposition and Selection

Paul starts by importing assemblies into Coreform Cubit and quickly isolating components of interest using the similarity selection tool. For example, when given a large vacuum chamber assembly containing specific heaters to be analyzed, he uses Coreform Cubit’s selection and filtering features to “clear out the materials that [he doesn’t] need,” reducing the entire assembly down to the key parts in under a minute.

This new workflow promises to streamline simulations in industry applications, from initial design phases to benchmarking and validation for criticality safety and operational performance analysis. The results offer an accessible path for engineers and scientists to conduct high-fidelity multiphysics simulations without the constraints of traditional, complex data setups.

2. Automated Mesh Preparation Workflow

Using a customized toolbar, Paul created a step-by-step process that simplifies each stage of mesh preparation. He organizes the workflow into specific stages: decomposing parts, compositing, imprinting, merging, and then meshing. Paul notes that keeping this workflow in mind and maintaining a specific order prevents backtracking or inconsistent mesh results. This structured approach ensures consistency and quality in mesh preparation, even for intricate parts.

3. Advanced Automation with Python Scripting

Paul enhances his workflow by incorporating Python scripts that automate various processes, from reading input tables to adjusting mesh parameters. He manages these parameters in a single source of truth, a csv file, keeping test cases, configurations, and outputs together. This input file and a python script he explains, allows him to perform parameter sweeps and variable adjustments without manual input for each simulation, leveraging the Coreform Cubit Python API and the MOOSE command line and parameter sweeps. With this automated system, he can generate consistent meshing schemes for different parts of an assembly, especially when components share similar geometry.

4. Seamless Integration with MOOSE for Comprehensive Analysis

After completing mesh preparation in Coreform Cubit, Paul exports the mesh and test parameters as input data to MOOSE, where he uses the software’s parameter study capabilities to run simulations across various design conditions. This integration allows him to adjust simulation parameters dynamically via command-line inputs, supporting iterative testing without the need for constant file modifications. This flexibility has proven essential for running complex simulations efficiently, making it possible to test a range of scenarios and optimize designs accordingly.

Through these strategies, Paul has created an efficient, repeatable workflow for preparing and analyzing complex assemblies. His process leverages the full potential of Coreform Cubit and MOOSE, providing significant gains in speed and accuracy for high-stakes simulations in engineering fields.