- Engineering Workflow Automation
- Design Space Exploration
Probably you’re using best-in-class software to support your engineering processes, but once too often you’re facing problems meeting key requirements within deadlines and budget constraints? You may ask yourself what’s actually missing to realize greater engineering achievements. Is it the ability to have all engineering tools work together toward the final development objectives, across multiple engineering disciplines? Or is it something different altogether?
Rightfully, development teams in all sorts of manufacturing businesses find it important to use engineering tools with a proven track record. That’s why you have invested time and effort to select engineering software tools that really help you resolve your specific engineering challenges.
And over the years, you have gradually built up the expertise and confidence with these tools to successfully address increasingly complex challenges for various disciplines, such as acoustics, structural mechanics,computational fluid dynamics or numerical optimization.
So a simulation based design approach has made it possible for your team to successfully resolve monodisciplinary engineering problems. But what you’re still struggling with is to connect various engineering tools into a multidisciplinary approach. In particular, you find it rather troublesome to have all these tools communicate and to share information that is critical to reach global engineering objectives. That still requires a lot of manual tasks, and therefore eats up valuable engineering resources that could be better spent on other tasks.
What you’re still struggling with today is to connect various engineering tools into a multidisciplinary approach
Then it’s worthwhile taking a look at Engineering Workflow Automation, which is available as part of Optimus. To start with, you can graphically define straightforward as well as complex engineering workflows.
More importantly, the concept allows you to integrate any engineering software into such a workflow, thanks to Optimus’ open communication infrastructure. This means that you can connect to most widespread engineering tools through a number of standard interfaces. In addition, you can literally integrate any engineering software in just a few steps.
This 360 degrees openness is really an aspect that makes Optimus stand out from the crowd. Its seamless integration with engineering simulation tools (including any in-house tools developed by your colleagues) paves the way to multidisciplinary engineering & optimization.
Your gain at the end of the day is an approach that valorizes corporate simulation practices and know-how
So, your gain at the end of the day is an approach that valorizes corporate simulation practices and know-how by formalizing them in a series of well-documented engineering workflows. And thanks to these workflows, simulation processes can be run fully automatically – with Optimus executing hundreds or even thousands of manual model changes, and performing all related data processing and performance evaluation tasks. And – most importantly – doing all of this using the engineering tools you have built up experience with.
But what if you want to work with optimization algorithms developed by your colleagues? Or third-party optimization libraries such as the Dakota Toolkit from Sandia National Laboratories? With Optimus being a multidisciplinary optimization environment, you probably think you need to give up on in-house and third-party optimization algorithms when switching to Optimus?
Well, nothing could be further from the truth than that. Optimus’ 360 degrees openness is not limited to physics simulation software. Any design exploration or engineering optimization method that you are using today can easily be deployed from within Optimus as well. Let’s take the example of the Dakota Toolkit that was mentioned. Just recently, Noesis Solutions made it easy for you to use Dakota’s rich library of optimization and uncertainty quantification methods. With this new Dakota plugin, you can access all of Dakota’s gradient and non-gradient based optimization methods directly from within the Optimus environment. And you can also perform uncertainty quantiﬁcation with any of Dakota’s sampling, reliability, and stochastic expansion methods.
Connectors to the most widely used Dakota algorithms are provided off the shelf and can be selected like any Optimus built-in algorithms, with Dakota running next to Optimus. In case you also want to use any other algorithm from the Dakota toolkit, you can easily do that using straightforward templates.
Interested to find out more about how to use the Dakota toolkit as part of your engineering work with Optimus ? Get in touch.
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