Interscale Content Hub – It’s always interesting to see how the debate between simulation vs digital twin technology plays out each year.
There’s a fine line between the two. So, these two important technologies will undoubtedly keep us busy for a while yet.
But we all know how useful these technologies are for streamlining processes.
So, why are we still here? Let’s look at the many specific aspects below.
Understanding Simulation Technology
Simulation tech is all about creating a virtual model that mimics how a real-world system works.
This model predicts how the system will behave in different situations, so you can test it out and make improvements without the risks of real-world testing.
Simulations are usually static and scenario-based, which gives you a good understanding of how a system will perform in a specific situation.
This technology has many uses in the AEC industry, such as checking buildings’ structural integrity, environmental impact, and energy efficiency.
For instance, finite element analysis (FEA) is a pretty common simulation technique used by engineers to assess stress distribution in building structures.
By running different load scenarios, engineers can ensure the safety of a building design before it’s actually built.
You can also use simulation in project planning to make sure you’re using your resources in the best way, predict how long things will take, and manage risks. This helps you to be more efficient and cost-effective overall.
As Ana Wooley and colleagues highlight in their paper, “When is a Simulation a Digital Twin? A Systematic Literature Review,” the simulation models are often grouped based on their capabilities.
These range from basic modelling to advanced prescriptions of optimal solutions.
This shows how flexible simulation technology is and how it can help with lots of different issues in the AEC industry.
Exploring Digital Twin Technology
While simulations focus on predicting future outcomes based on existing models, digital twins take it a step further by creating a live virtual copy of a physical asset, process or system.
What sets digital twins apart from static simulations is how they’re continuously updated with data from their real-world counterparts, thanks to sensors and IoT devices.
This means you can monitor, diagnose and do predictive maintenance in real-time.
In their paper, “Enabling Elements of Simulations Digital Twins and its Applicability for Information Superiority in Defence Domain,” Kapish Aggarwal et al., point out that digital twins are not just virtual copies.
From Aggarwal and colleagues’ perspective, digital twins are “living, breathing replicas” that change in accordance with the real thing.
This is what makes digital twins different from traditional simulation models, and it opens up a whole new world of possibilities for real-time monitoring, predictive maintenance, performance optimization, and data-driven decision-making.
Take the aerospace industry, for example. Digital twins monitor and predict the performance of aircraft engines, which helps cut maintenance costs and improve reliability.
Key Differences Between Simulation and Digital Twin
Static vs. Dynamic Nature
Simulations are usually set up to test specific scenarios in a static way. The simulations give you great insights based on what you’ve set up in advance, but they don’t adapt to changes in real time.
Digital twins are different. They’re dynamic models that interact with their physical counterparts in real time, updating as new data comes in.
This means digital twins can offer more accurate and timely insights, which helps with making decisions and adjusting plans in real time.
As a point of reference, you might want to check “List of 7 Digital Twins Software as Your Cheat Code for Efficient Projects.”
Data Integration and Real-Time Updates
Simulations often use historical or hypothetical data to predict outcomes, which makes them less effective for real-time applications.
Digital twins bring together real-time data from sensors and IoT devices, giving us a current and evolving picture of the physical system.
This constant flow of data helps us make more accurate predictions and allows us to take proactive steps to maintain and optimise.
Scope and Complexity
Simulations are usually focused on specific parts of a system, which makes them great for testing individual scenarios.
But digital twins cover the whole ecosystem of the physical asset, from design to decommissioning.
They bring together lots of different data and models, giving you a complete picture of how the system is performing and where there might be problems at any stage of its life.
Lifecycle Representation
Simulations are mainly used during the design and testing stages of a project. They help us make sure our designs are right and predict how they’ll perform in different situations.
Digital twins are used throughout the entire lifecycle of an asset, unlike simulations which are only used at certain stages.
They help you keep an eye on things, plan for maintenance, and make improvements, so the asset works well from start to finish.
Comparative Analysis: Simulation vs. Digital Twin
Capabilities and Features
Simulation technology is well-known for its ability to test specific conditions and optimise design parameters effectively.
It’s used a lot in fields like design optimisation, safety testing and performance analysis.
For example, engineers often use simulations to check the structural integrity of buildings before construction.
On the other hand, digital twin technology lets you keep an eye on things and predict when maintenance is needed.
A digital twin is always up to date with the latest data from the real thing, so you can make changes and improvements as you go along.
This feature is great for making assets last longer and improving how efficiently they’re used.
Take the aerospace industry, for instance. Digital twins monitor aircraft engines in real time, predicting when maintenance is needed and preventing failures.
Applications and Use Cases
Simulations are mainly used to test and improve specific scenarios. They provide a way to test different scenarios in a controlled environment, where you can tweak different variables to see what happens.
This is a huge help in fields like manufacturing, where simulations can make production processes more efficient and cut costs.
Digital twins are used in more complex and integrated environments, though.
They’re a key part of smart buildings, infrastructure management and system integration, giving you a complete view of how everything’s working.
Take digital twins in smart cities, for example. They monitor and manage urban infrastructure, making sure resources are used efficiently and that maintenance is done before it’s needed.
While we’re on the topic, have a look at “Construction with Digital Twin Information Systems: Your Basic Guideline,” for an idea of how digital twins are used in construction projects.
Implementation and Integration
In most cases, it’s easier and cheaper to use simulations rather than digital twins. Yup, the simulations don’t need a lot of infrastructure and are designed to tackle specific tasks, so they’re a great fit for many projects.
The thing is, they’re not really fit for purpose when it comes to ongoing operations because they don’t provide real-time updates.
You’ll need to invest a lot in IoT and data infrastructure if you want to use digital twins.
If you want to get real-time data from physical assets, you need to make sure you have good sensors and a solid connectivity solution.
Even though it costs more upfront, the benefits of real-time monitoring, predictive maintenance, and getting a complete picture of the system make it worth the investment for many industries.
Take the oil and gas industry, for instance. Digital twins have led to big improvements in efficiency and safety.
Benefits and Limitations
Simulations let you test things out in a way that’s safer than doing it in the real world.
The thing is, simulations are static and don’t adapt to real-time changes, so they’re not so useful in dynamic environments.
It’s also worth noting that simulations are cost-effective and focused, making them ideal for specific, predefined scenarios.
On the other hand, digital twins are dynamic and comprehensive, which makes them expensive.
Digital twins are ideal for getting real-time data integration and continuous updates, which gives you a detailed and up-to-date representation of physical systems.
This capability helps us make better decisions and work more efficiently, but it does require a lot of resources to set up and keep running.
The complex nature of digital twins means they’re best suited for large-scale applications where real-time monitoring and predictive capabilities are critical.
Integrating Simulation and Digital Twin with Interscale’s BIM Management
It can be tricky to get to grips with simulation vs. digital twin technologies, mainly because they’re pretty complex and you need a solid data integration system in place.
That’s why we at Interscale offer customized solutions to make your process easier and ensure everything is integrated and managed smoothly.
Our team of experts has a lot of experience in BIM management and digital twin technologies.
For instance, we worked with Ewert Leafs Tech on a case study where we helped them optimize their digital twin strategy.
The result was better operational efficiency and lower maintenance costs.
We take a comprehensive approach to BIM management, so we can cover all aspects of the simulation and digital twin lifecycle, from initial setup to ongoing updates and analysis.
We know we’ve got a lot on our plate, so we’d like you to do some background checks. It would be great if you could visit and read our Interscale BIM management service page.
Or, if you need to make a few more tweaks, we’d be happy to run them by you. When’s good for you? We’d love to have discussion sessions. We’re here whenever you need us.
In Closing
Simulation and digital twin technologies are both really useful in a lot of industries these days.
If you use both simulation and digital twin technologies, along with BIM management solutions from Interscale, you’ll see a big boost in efficiency and innovation on your projects.
And at the end of the day, knowing the different benefits of simulation vs. digital twin can help you get better results.
