Engineering Design Optimization

Unlock the potential of your engineering designs with SimuTech Group’s FEA optimization services. We specialize in parametric, shape, and topology optimization using advanced simulation tools from Ansys to deliver reliable, efficient solutions tailored to your needs.

What is Engineering Design Optimization?

Engineering design optimization is the systematic process of improving engineering designs to meet specific performance objectives while satisfying constraints. It involves using mathematical models, algorithms, and computational tools to explore and evaluate different design alternatives to find the optimal or near-optimal solution.

Through design optimization, SimuTech Group can help you transform complex challenges into innovative, high-performing designs.

engineering design optimization example using an additive manufacturing simulation

Typical Engineering Design Optimization Process

Defining Objectives: Identifying the goals and criteria that the design must achieve, such as maximizing strength, minimizing weight, or minimizing cost
Identifying Constraints: Considering limitations and requirements that must be adhered to, such as material properties, manufacturing capabilities, regulatory standards, or operational conditions
Formulating Mathematical Models: Developing mathematical representations of the design problem, including objective functions to be optimized and constraints to be satisfied
Exploring Design Space: Using algorithms to systematically search through the space of design variables to understand how varying the parameters affects the design’s performance
Evaluating Solutions: Assessing the performance of candidate designs against the specified objectives and constraints
Iterating and Refining: Iteratively refining the design based on the evaluation results, potentially revisiting and adjusting objectives, constraints, or design variables

Engineering design optimization can be applied to various stages of the design process, from conceptual to detailed design, and across different engineering disciplines, including mechanical, electrical, civil, aerospace, and others. It helps engineers make informed decisions, improve product performance, reduce development time and costs, and ultimately deliver better-engineered products or systems.

Benefits of Optimization

Improved Performance: Optimization enables engineers to enhance the performance of their designs by maximizing desired metrics such as efficiency, strength, or durability while minimizing undesirable factors like weight, cost, or energy consumption
Cost Reduction: Optimizing designs can lead to cost savings by reducing material use, minimizing manufacturing complexity, and streamlining production processes. This can result in lower manufacturing costs and overall project expenses.
Increased Reliability and Safety: Optimization can improve the reliability and safety of engineering systems by identifying and mitigating potential failure points and ensuring that designs meet or exceed relevant safety standards.
Faster Time to Market: By systematically exploring design alternatives and identifying optimal solutions, optimization can help accelerate the product development cycle bringing new products to market more quickly.
Informed Decision-Making: Optimization provides engineers with valuable insights into the design space, allowing them to understand trade-offs and make informed decisions based on quantitative data.
Customization and Tailoring: Optimization enables engineers to tailor designs to specific requirements or constraints, such as customer preferences or environmental conditions, resulting in more customized and tailored solutions.

Optimization Tools for Mechanical Simulation

Ansys has tools for parametric optimization, shape optimization, and topology optimization.
Parametric optimization is completed in Ansys optiSLang.
Shape optimization and topology optimization are handled by the Structural Optimization tool in Ansys Mechanical.

Parametric Optimization: Known structural connectivity and known cross-sectional shape, unknown shape dimensions (left) and optimal cross-section radius (right)

Shape Optimization: Known structural connectivity but unknown cross-sectional shape (left) and optimal cross-section shape (right)

Topology Optimization: Unknown structural connectivity, shape, and dimension (left) and optimal topology (right)

Parametric Optimization in optiSLang

Ansys optiSLang is a tool specifically designed for multidisciplinary optimization and robustness evaluation. Ansys optiSLang integrates with simulation tools to automate the optimization process and enable engineers to efficiently explore design alternatives, identify optimal solutions, and evaluate design robustness under uncertainty.

A typical parametric optimization workflow in optiSLang includes:

Integration with Simulation Tools
Parameterization of Simulation Models
Definition of Objectives and Constraints
Sensitivity Study
Optimization
Robustness Evaluation
Optimization Results Visualization and Interpretation

By leveraging Ansys optiSLang, engineers can streamline the design optimization process, accelerate product development cycles, and ultimately deliver more robust and efficient engineering solutions.

Parametric, Shape, and Topology Optimization Examples and Case Studies

Direct Optimization Analysis of Field Emission Heat Engine Geometry

A thermal stress analysis was performed using Ansys Mechanical and DesignXplorer where 5 geometric parameters were tuned and optimized.
Optimization objectives were to maximize the structural safety factor with constraints specified on the component maximum temperatures and the spacing between the cathode and anode.

Polynomial Response Surface Optimization of the Deformation of a Glass Disk

Optimization objective was to tune the material properties so that the glass had a specified shape when supported on its outer edge under gravity loading.

Robust Design Optimization to Improve Vehicle Window Regulator Product Quality Using Ansys optiSLang and Ansys Mechanical

Window regulators are part of the system that open and closes automobile windows. These regulators must work for a range of curved window sheet radii, serve the three different positions to adjust the windows to the chassis of the car, account for stiffness variations of several components, and adapt to variations in the torque used to assemble the regulator. On rare occasions, these variables have interacted to generate excessive stresses, strong enough to crack the window glass.

This large design space was explored and mapped using optiSLang’s Metamodel of Optimal Prognosis (MOP). A new design was evaluated to be sure that every combination of the input parameters generated less than the maximum allowable stress on the glass.

Probabilistic Analyses of Geometric Variations and Their Influence on Fatigue Behavior of a Gas Turbine Housing

Power generation gas turbines are efficient, reliable, available, flexible, and cost-effective. The competition with renewable energies imposes strong goals onto power plants to improve the cost effectiveness of their turbines. Ansys optiSLang and Ansys Mechanical were used in a probabilistic analysis of geometric variations and their influence on the fatigue behavior.

The task was to quantify the influence of the geometric scatter onto stresses. A statistical analysis was conducted for the result quantities. The resulting stresses can be compared with critical limits for different safety levels. Further, the location of possible critical stresses can be easily identified.

engineering-design-optimization-siemens-generator

Optimize Designs with Ansys Simulation Tools

The Ansys suite of simulation tools offers a wide range of methods to optimize both designs and processes. Optimization is frequently the difference between a design that performs inconsistently within its intended envelope and one that delivers robust, reliable performance across all conditions. At SimuTech, our engineers leverage these tools to help customers explore their product or process design space, providing valuable insights into performance across multiple design variables, constraints, and goals.

Partner with SimuTech for Rapid Product Optimization

Simulation-based optimization saves significant time and costs compared to physical testing, offering a faster path to understanding design performance. Companies that skip optimization to speed up time to market often face costly warranty issues due to poor performance. Don’t let this be your story. Contact us today to ensure your products and processes are optimized for success.