Using Numerical Optimization and Parametric Modeling Techniques For Design Optimization

Today, optimization methods feed critical information in the decision making process of the most challenging engineering and planning projects. Design Optimization uses optimization methods to solve design problems by incorporating a number of disciplines.

Design optimization allows designers to incorporate all relevant disciplines simultaneously. Instead of optimizing each discipline sequentially, proper design optimization exploits the interactions between the disciplines by optimizing them simultaneously. This method aims at reducing the time required to engineer a new product, when successively passing through research, virtual prototyping and production.

At every stage, specific design optimization aspects help you gain deeper insight into the model behavior. A good understanding makes it a lot easier to improve the performance of your product. This is where numerical optimization and parametric modeling comes in. Numerical optimization is finding the best solution in the design space that yields a multitude of global and local ‘best case results’. Obviously, although superior to sequential evaluation and execution of disciplines, proper design optimization adds a layer of complexity to a project’s scope. For this reason, numerical optimization software, like Optimus, from Noesis Solutions allow this process to be more user-friendly, targeted and precise. No more trial and error.

Historically, design engineers start from a set of input variables. When spending time manually improving the design, they try to judge the impact of partially conflicting attributes, such as weight, cost and product performance characteristics. With the Optimus software, this entire process is reversed.

The engineer or design team is first tasked with setting the desired output targets. Then Optimus works backwards to identify the input values that match your design criteria, using advanced iteration and numerical optimization methods. The algorithms incorporated in the numerical optimization software ensure that the optimal product attributes are secured.

By minimizing, maximizing or zero-mizing the design manually or automatically, numerical optimization techniques help you improve the performance of the original configuration. The information picked up supports smart design decisions early on in the process.

This allows design teams to build a better-performing design faster and more affordably, reach a design’s ultimate performance, meet the optimum and fit the constraints and balance conflicting objectives. Teams are about to obtain a trade-off between multiple simulation disciplines, troubleshoot an attribute-driven discipline and use simulation models to correlate measurements.

Overall numerical optimization software like that of Optimus provides the platform to create better products more effectively and efficiently.