Digital Twin vs. Simulation: What’s the Difference and Why It Matters?

The two technologies are doing wonders in the AECO industry, but with a little confusion, everything can go wrong.

Digital Twin vs Simulation is one of those comparisons where both of these have a different approach.

Even the output that comes out has different purposes in the construction industry.

So, Digital Twins serve as an exact replica of a structure or facility. It holds and displays live data, offering a digital transformation of the facility.

On the contrary, simulations are excellent to explore “what if” scenarios of a facility design. For example, professionals simulate various environmental conditions to see how the building design adapts.

Digital twins offer real-time awareness of the conditions of a building, whether it is operational or under construction.

Let’s cut through the market confusion and gain clarity over these two technologies. We will further look over their technical requirements and find out which delivers the most value.

But before that, let’s go through the basics to understand where we can use these technologies effectively.

What are Digital Twins?

These are the exact physical counterparts of a building with a detailed digital representation of every system and facility.

Digital Twins provide a bi-directional connection between physical building assets and their digital forms. It is like a real-world counterpart that reflects the current state of the system twins, processes, or environments.

You might not be that much surprised if this were all a Digital twin could do, right? But here the things about it get interesting.

These replicas hold deeper insights about a building and its systems. It also provides the historical data of that system and its predictable future for optimized operations. However, before reaching this, it all starts when designers build digital twin prototype of this digital technology.

Unlike the technical people, clients and owners often misinterpret Digital Twins as static 3D models. And it is not on them, because they are 3D models, however far more advanced than static data BIM models.

So, here are the key traits of a true Digital Twin, so you always have a clue.

• Persistent and evolving: This is the biggest differentiator of digital twins. They are not like BIM models, but are definitely a product of them. So, these replicas continuously evolve as the real-life building progresses, providing real-time monitoring.
• Bi-directionally connected: We mentioned this earlier, but now you will know what’s with it. So, digital twins have a two-way communication with the building, given that the model is advanced enough. This helps professionals to send and receive real-world data, keeping track of every activity.
• Continuously updated: A digital twin continuously gets updated when there are design changes and construction progress. This is one of the greatest benefits of digital twins that modern infrastructure projects are adopting.

What are Simulations?

Simulations are also models like Digital Twins; however, they represent particular sections of features of a building.

The core philosophy of simulation models is to enable outcomes of certain situations in a virtual environment. And not just have it, but also evaluate the potential threats that may lead to occupant risk or compromise building security.

Unlike Digital Twins, professionals build these models for specific conditions and constraints to analyze the energy output of a building.

The fun part is that the traditional simulation conditions can be manipulated to check the system behavior under every condition. For example, professionals can simulate and measure the impact of wind turbines around a structure.

Now that we have understood the basics, we are ready to conduct a comparison of the Digital Twin vs. the Simulation model.

Defining characteristics of simulation models:

Scenario-based: A true simulation model will always be based on a particular scenario. Designers use these to test hypothetical situations without any real-world consequences. Whether it is for analyzing the structural stress or the architectural design, resilience simulation models are a great help.

Time-bounded: Unlike digital twins, simulations do not capture the ongoing status of building systems. Professionals run these models with defined timeframes to flag any potential issues within them. They test multiple scenarios in a time-bounded manner to find out the best-suited design option.

Hypothesis-driven: Simulation workflows always start with assumptions. These are like, to what extent can a design withstand seismic loads, or what type of architecture will make the best use of daylight? Professionals put models in such simulations to understand the design behavior and make sound decisions.

Now, we will be going a level deeper to understand how these systems are formed and used. For that, we have to look into their technical key differences in terms of data structure, processing models, and system architectures.

Key Technical Differences: Digital Twin vs. Simulation

Why the Difference Matters in AECO

The AECO industry treats these two technologies as superior capabilities in modern digital construction.

The differentiation is not just with the output, but also what information is available, how it is used, and what kind of data-driven decision-making it supports.

For example, simulations are more focused on showing you outcomes. In contrast, a Digital Twin helps to track, manage, and control the operations of a running facility.

Those are connected to the physical asset/key features and work on a bi-directional information exchange.

Hence, Digital Twins support advanced analysis and detailed information about physical assets for the predictive maintenance of assets.

Digital Twin vs Simulation: “What could happen” vs “ What is happening”

Let’s understand from the perspective of a commercial building that is currently consuming more energy than expected.

When designers use a simulation model, it will show them various mishaps because of the current design.

They can manipulate the variables for every building system, such as, what happens if the HVAC setpoints change, or what if there is an occupancy surge.

This way, simulations tell us “what could happen”, in a particular scenario. However, the story gets more interesting with Digital Twins.

These are live replicas of a structure, with a lot of data in them, unlike static simulations. It brings together live and legacy information about a building in one single control point.

Everything, from operational data, equipment status, maintenance histories, to failure history and environmental effects; Digital Twin technology takes you on a whole different level with unit twins.

Here is a summary of the distinction:

• Simulations: They show you what could happen if there is a particular type of operational scenario or environmental conditions.
• Digital Twins: These show you the live status of the building. It is like seeing the building getting alive and providing information about what is happening, the cause behind it, and potential future impacts if not fixed.

Digital Twin vs Simulation: Not Competing Technologies

The industry always prefers to treat the same type of evolving technologies as competitors.

And there is a simple reason behind it. It is the capability of both to understand how a building or infrastructure behaves and how different assets behave.

By now, we have seen that both the techs serve differently; however, their outputs complement each other for the data generated. In short, simulations provide designers with the framework to test designs under controlled environments.

The Digital Twins provide a solid connection between physical assets, systems, and the point controlling them. See, for large-scale infrastructures, such as modern airports and metro stations, they are huge throughout the entire manufacturing process.

So, overseeing every bit of this larger system and controlling it without a centralized spot could be a nightmare.

Here, digital twins bring the complete picture of the actual system in a shell. Facility managers operate this shell, expand it to get detailed asset information, status, and even run simulations in real time.

However, creating digital twins with simulation capabilities is significantly more advanced and not widely adopted yet.

Digital Twin captures, “ What is happening”

Since digital twins bring information directly from the physical objects, it allows a proper virtual representation of the current state.

It processes a good amount of data from BIM-embedded sensors data, Building Management Systems, IoT devices, and maintenance records. Facility managers gain insight into the current building state and ensure everything is up and running.

Simulation tells you “ What if”

Simulations are simple when you see it from the designers’ perspective. For them, a design only passes after the evaluation through the general outputs.

Here, the advantage is that teams execute different models in multiple scenarios to get the right fit. Hence, simulations remove a lot of rework which are the result of wrong assumptions in the design phase.

Here, designers no longer need to create designs on assumptions. They can just visualize and measure the impact of the concerned conditions on that design. This gives them instant room for modifications and improvements, where the design provides greater operational value.

Simulations and Digital Twin: Working Together

So we discussed that these two technologies are not competing. Rather, they have different purposes across the entire lifecycle and also in the advanced manufacturing industry.

Firms that can efficiently make both of these work together and can provide real value to their customers with predictive capabilities.

Let’s understand how the real optimization processes emerge through this example.

So, there is an office building where energy usage is higher than expected because of maybe two or more components.

Here, a digital process twin can show the current energy flow in the building through real-time performance data. In a digital thread, it shows the HVAC status (the load on them), indoor conditions, and other vital operational information.

At this point, when facility managers have this information-rich data and access to the live digital Twin, they can implement simulations.

They can now test different scenarios and building design changes to initiate the performance optimization.

So, both the technologies answer different questions:

• Simulations provide information about what could happen in a particular scenario.
• Digital Twins or asset twins provide live information about the building business operations for predictive analytics.
• Digital twins + Simulations provide the asset’s state, based on which we can run simulations and observe any change in the asset’s status.

Choosing the Right Approach: Simulation, Digital Twin, or Both?

So far, we have known what these two technologies are capable of, what exactly differentiates them, and what brings them together.

Now, it’s time for a simple framework that you can use to be on the right track while choosing an approach.

Everything boils down to project requirements and the scope of work. There might be clients who really do not know the practical use of digital twins; however, they fantasize about it.

Hence, as the project executor, your job is to understand the needs and act accordingly for operational efficiency.

If you are testing a design before construction, go for virtual model-based simulations. Similarly, if the goal is to monitor an operational asset, digital twins are the way forward.

Now, if a building requires continuous optimization, you need to use digital twins there.

One key misconception is that digital twins are not simulations, though they look very similar to one another. And on the other hand, you cannot create a physical twin from a simulation.

Final Thoughts

The comparison of Digital Twin vs Simulations offers a different perspective on building designs. Simulations help in exploring particular external and internal conditions that may affect a building. And this happens before even a single brick is laid out, so designers get the room to experiment. A virtual twin here connects an already operational building with a centralized live digital model. Modern experts are also integrating machine learning in digital twins that will give rise to enhanced intelligence. The model has evolved along with the building, and it connects real-time data with advanced analysis to support better decisions and predictions throughout the building lifecycle.

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