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Elements: An Engineering Simulation Blog

Serving the engineering simulation community and ANSYS and Rocky DEM users by sharing news, workshops, seminars, training, webinars, tips & tricks, and more.

Test vs analysis? Better yet, both!

Rolf Orsagh, Testing Services Manager - Strain Gage InstallationRolf Orsagh
Testing Services Manager
Strain Gage Installation
Most of you know us as your ANSYS software and service provider. While ANSYS certainly represents the focus of our business, it’s not all that we do. Another way we serve our clients is through our physical testing team.

Our physical test team has worked not only across North America, but throughout Europe and Asia and with many industry sectors. For example, our testing experts were key in developing and deploying a digital twin model employed on a turbine for a Middle Eastern power plant.

Given that most of you work mainly with simulation, why are we bringing testing to your attention?

A goal of simulation is to reduce physical prototype testing, but physical testing still has a role in product development and failure investigations. In fact, physical models can work hand-in-hand with simulation in many cases.

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Digital Twin Technology: Reduced Order Modeling In the Field

Alan McKim, SimuTech Group’s Vice President of Test Engineering and QAIn a recent blog post, SimuTech Group’s President, Rick James, wrote a high-level overview of Digital Twin, and explained its significant economic impact. Today, SimuTech Group’s Vice President of Test Engineering and QA, Alan McKim, takes a practical view, discussing how--with help from Reduced Order Modeling (ROM)--Digital Twin works in equipment testing. He also illustrates how SimuTech Group used Digital Twin technology to help a customer gain insight and resolve performance concerns.

Though there’s a lot of discussion about Digital Twin technology, some engineers and designers find it difficult to understand how it can economically impact them. Here’s an analogy that might help illustrate the digital twin concept: equipment used in the field could be compared to staff working in a remote location. You need to communicate regularly with these staff members to solve issues. Imagine a staff member dealing with an issue, but not communicating information back to you. This would cause delays, reduced performance, or potentially even ultimate failure of the offsite effort.

your employee on a deserted islandYou wouldn’t place your employee on a deserted island with no means of communication so why do it to your equipment?In a similar way, equipment has generally been left on its own in the field. However, technology has simplified the ability to gain information about equipment during its operation. Sensors can easily be installed to gather data about temperature, vibration, or load indication--all valuable in determining how the system is performing in its environment. Going back to the analogy: the communication with offsite humans is relatively direct; their communication is understood directly. However, when equipment sends sensor data, this must be interpreted.

This is where mathematical Reduced Order Models (ROMs) come in. With an ROM, you can take the critical aspects of a detailed model and reduce them down to simpler equations or algorithms that can be used in real time. Most engineers are familiar with detailed computer simulations that take hours or days to run. However, with field information, you do not want to wait hours or days to understand the implications. An ROM is the simplification of the input to output of a complex model. You still need the detailed model to generate this relationship, but once it is known, the ROM can be used.

While a Digital Twin is often perceived as a massive undertaking, it doesn’t have to be. Referring back to the analogy of staff working in the field: you may need to deploy a single person, or a group of 100. The same is true for Digital Twin technology, which can be large and broad with lots of details, or narrowly tailored.

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