Finite Element Analysis of Skid (Base Frame) for Screw Compressor

Abstract

A base frame, commonly referred to as a skid frame, is a rigid structural platform designed to support machinery and its associated components by providing a uniform mounting surface. These frames are typically composed of structural members with varying cross-sections and are essential in applications where stability, alignment, and structural integrity are critical. In the context of screw compressors especially those enclosed within a canopy for noise reduction, safety, and transportation base frames play a crucial role in maintaining operational efficiency and equipment longevity. This paper presents the design and validation of a base frame tailored for a screw compressor operating under known power and load conditions. A three-dimensional CAD model was created using Autodesk Inventor 2023, followed by finite element analysis (FEA) in ANSYS to ensure structural safety. Additionally, an optimization study was carried out using a nature-inspired Artificial Intelligence (AI) algorithm implemented in MATLAB to minimize the weight of the frame without compromising performance. The core objective of this work is to design a base frame with structurally efficient members optimized according to the load distribution on each component.

Introduction

The study focuses on the design and optimization of the base frame used in a 315 kW oil-injected electric screw compressor, which has a total weight of approximately 6.5 tons. The base frame is a critical structural component that supports key subsystems such as the drive assembly, cooling and separation systems, canopy, and electrical enclosures. It must withstand static and dynamic loads, ensure vibration damping, and maintain proper alignment of components to ensure system performance and longevity.

Key Points:

1. Functional Requirements

Functional needs of the base frame are classified into:

• Primary Functions: Provide rigid support, ensure safety, absorb vibrations.

• Secondary Functions: Allow easy assembly, maintenance, mobility, and safe transport.

• Tertiary Functions: Provide a level base, protect from corrosion, and support auxiliary components.

2. Material and Design Approach

• Traditional designs use C- or I-channels (IS 808), which are strong but heavy.

• The new design uses Cold Rolled (CRCS) and Hot Rolled Carbon Steel (HRCS) sheet metal formed into custom C-channel structures, reducing weight and allowing design flexibility.

• Manufacturing is constrained by sheet sizes (max 6m x 2m, up to 6mm thickness) and laser cutting limits.

3. Optimization Using AI

• To avoid overdesign and reduce weight, the study uses AI-based optimization.

• Cohort Intelligence (CI) algorithm, a nature-inspired method, is employed in MATLAB to optimize structural dimensions while maintaining strength and function.

• This approach enables weight and cost reduction without compromising safety.

4. Literature Review Highlights

Several relevant studies support the approach:

• FEA and experimental validation have shown accurate prediction of structural performance.

• Studies confirm structural safety under static/dynamic loads, resonance avoidance, and vibration behavior prediction.

• Use of optimization (e.g., switching from H- to C-channels) has shown material and cost savings.

• One study highlights torsional vibrations in mobile compressors, stressing the impact of rotor inertia on drivetrain behavior.

Conclusion

Finite Element Analysis (FEA) was performed on two distinct base frame models—one fully enclosed with sheet metal and the other featuring a skeletal configuration. The design modification aimed to reduce the overall weight and manufacturing cost of the base frame while maintaining structural performance. The simulation results effectively identified critical stress regions, typically located at joints or areas with reduced cross-sectional geometry. To address these high-stress zones, especially in skeletal frames, reinforcements such as stiffeners introduced between the legs of C-shaped members to distribute the loads more evenly and minimize local deformations. It is also observed that the majority of stress concentrations behave as localized stresses, affecting only a limited number of nodes and not contributing to major structural failures or fractures. Therefore, these localized stresses are not critical under the current loading conditions. Both base frame designs are deemed suitable for their intended application, with the skeleton-type frame showing promising results, particularly under lifting and static loading conditions. However, it is recommended that the skeletal frame be structurally enhanced through localized stiffening to improve rigidity across its entire surface. Based on the outcomes, the skeleton-type base frame can be considered viable for prototype development and experimental validation. Regarding the optimization aspect, the Cohort Intelligence (CI) algorithm demonstrated partial success. Due to the indeterminate nature of the frame structure, the optimization process encountered errors in the later stages of the code. While the algorithm itself is valid for optimization tasks, the structural constraints of the base frame do not fully align with the assumptions of the optimization model. Thus, further customization or algorithmic refinement is needed to effectively apply such techniques to indeterminate structures like base frames.

References

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Copyright

Copyright © 2025 Tejashri Karanjkar, Dr. P. H. Jain, Mr. Noor Khan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.