Dear TeamCAD website visitors,
We continue to cover interesting topics related to the BIM project process and digital twins. As I announced in my previous article, “The Big Savings BEP Brings To The Investor “, I am going to cover the topic “Data Is The New Gold, Does The Same Apply To Data In Digital Twins?” in this article.
Have you heard that the data is the new gold or new black gold?
If you take a good look at the image above, you are going to admit that these claims come from very competent portals and from very competent companies and institutions. The claim that data is new gold raises many questions, as information and data in themselves have no material or market value, such as gold or oil. Therefore, we must keep in mind that when claiming that data is “new gold”, we do not mean comparing the market value of information and data on the one hand and gold on the other, but something completely different.
Namely, during the development of the human civilization, gold imposed itself as the most reliable form of preserving the value of property and capital, because, until the seventies of the last century, gold was the basis for the entire money supply on the planet. Practically, every banknote on the planet had a base in the gold bars of central banks around the world, and that is what still gives gold great value today and makes it a very reliable form of preserving the capital value.
But how to compare the value of information and data with the gold value? In which way to compare them? I think we can easily compare the value of information or data and the gold value if we compare the potential they carry with themselves. If we know that gold has a limited price, where the factor that limits the value of a gram or ounce of gold is its current price on the international market, the information or data has no such limitations and its value is measured by the potential benefit that the information or data provides to its owner. If we add that information and data as an integral part of data science, along with digital twin technology, are one of the main hopes of the fourth industrial revolution, the high value of information and data becomes more than obvious to us.
You have probably heard the saying of the Chinese philosopher Confucius: “Give a man a fish, and you feed him for a day. Teach a man to fish, and you feed him for a lifetime.” Therefore, data and information have a supreme value and their value is much greater than anything material, even gold itself. I am of the opinion that, precisely because of the views expressed in the previous part of the article, there are today’s comparisons of the value of information, data, and thus skills on the one hand and the value of gold on the other.
If we now return to the world of BIM technologies and digital twins and look at the value of information, data, and skills from that perspective, we come to the true meaning of today’s popular claim that “data is the new gold”. Although this claim stems from Data Science, it is absolutely applicable to today’s BIM technologies (Building Information Modelling) and digital twin technologies, which are based not only on 3D geometry but on something much larger and more valuable – on their majesty information and data.
Below, I m going to try to support the above thoughts and attitudes related to the potential and value of information and data in digital twin technology and answer some of the questions that, I am sure, arise for every reader of this article:
- Why is data so valuable in digital twin technology?
- How to generate data in the digital twin model in the most efficient way?
- How to efficiently process data in a digital twin model?
- How to visualize data most efficiently?
- How to turn the data in the digital twin model into concrete savings?
Why Is Data So Valuable In Digital Twin Technology?
As you could read in one of my previous articles “What Are The Digital Twins?”, we defined digital twins as a digital replica of physical data, processes, systems, and a digital simulation of reality that can be used for a variety of purposes. This practically means that we can test a digital replica of a real-world object for various dynamic influences without any damage to the physical object itself and make perfectly objective decisions based on comparing different results obtained from simulations in digital twin models.
If we take into account that simulations on a digital replica of real-world objects can be done an unlimited number of times and in different variants, the information and data generated from the various options and solutions considered allow us great savings. Also, the data allow us to make decisions based on data obtained from simulations, ie. Data-Driven Decisions.
It is also important to note that currently the cheapest option obtained based on data from various digital simulation tools, using digital twin technologies, does not always mean the cheapest option during a certain period of a facility operating in the real world. For example, if the designer’s criterion is to choose the cheapest chiller for the investor, without considering energy consumption during his work as a very important criterion in choosing building equipment, the investor would achieve certain savings in the first years of operation due to lower costs of purchase and chillers installation, but in the following years, the chiller operation would lose significant funds due to higher consumption of electricity for heating and cooling, and thus higher expenditures to pay the bills for consumed electricity.
I hope that with the help of a few previous examples I gave you an idea of why the data are generated by different simulations and processed in order to optimize operating costs, very valuable in digital twin technology, and have great potential to bring significant savings to the investor. Of course, one of the important parameters in digital twin technology is the way in which information and data are generated, processed, and visualized, which you are going to find out more about below.
How To Generate Data In The Digital Twin Model In The Most Efficient Way In Order To Achieve Savings?
When we talk about the most efficient way to generate data in a digital twin model, we must consider that there are two typical scenarios:
- data generated during the BIM project process,
- data generated during the operational use of the facility and the equipment installed in it.
In the first case, when we generate data during the BIM project process, the most efficient way of collecting data is good communication in project teams of different disciplines on the project, timely data exchange between disciplines in the BIM project process, BIM project process automation and BIM data exchange, and then implementation of different digital simulation tools within digital twin models generated based on BIM models in different phases of the project process.
When we talk about the data generated during the facility operational use, things are a bit more complicated. It is often the case that we do not have access to any data from the BIM discipline models, it is a very common case that the investor himself does not have a BIM as-built model, and we are often forced to invest great effort in data collection. The fastest way is to create BIM as-built models of the different disciplines, and then it is necessary to install different sensors in the constructed buildings, which would collect data over a longer period of time. The data collected in this way, using the “Internet of Things”, are transferred to the digital twin model for further processing and analysis, and based on them, we get the opportunity to optimize the data obtained in the digital twin model.
How To Efficiently Process Data In A Digital Twin Model?
Depending on the purpose for which the digital twin model was created, different tools can be used to process the data in the digital twin model in the most efficient way. However, the data processing methodology in the digital twin model can be roughly divided into:
- CFD (Computational fluid dynamics) is a calculation of fluid dynamics and is part of fluid mechanics which takes numerical analysis and structured data as a basis for analysis to solve problems related to fluid behavior in liquid and gaseous state. CFD analysis has a very wide application including forces and moments on various digital models, pressure in pipes caused by substances in liquid and gaseous state that are in the pipes, explosion analysis, simulation of motion and flow of different types of particles, temperature action, weather simulation, the behavior of digital models in the air tunnel, etc.
- Dynamo and Python are digital tools that are explained in detail in the article “BIM Workflow Automation”. Here I would like to avoid a more detailed description of Dynamo and Python as digital tools which, in addition to automating the BIM project process, have great application in data processing in digital twin models. If you want more information about Dynamo and Python, please select this link.
- Machine learning is a digital tool that is defined as a sub-area of artificial intelligence. Machine learning is based on learning a machine based on experience and imitation of human actions in certain repetitive circumstances. Simply put, machine learning is based on observing the actions that a person performs when he encounters a certain typical problem. After a certain number of repetitions, the program that “monitors a person” learns and adopts the algorithm of human behavior and takes over the execution of the same operation that he learned by “monitoring a person”.
Given that artificial intelligence is still not able to make very complex decisions and see the problems that arise with data generated by different simulations, I think we still can not talk about the massive and implied use of artificial intelligence as a digital tool for process simulation in digital twins.
How To Visualize Data Most Efficiently?
After we have collected relevant data, then processed them and obtained parameters from various calculations and results that can help us optimize the digital twin model, there is a need to visualize the obtained data in a clear and acceptable and understandable way. It should be borne in mind that, when we act from the perspective of the service provider to the client, we must take into account that the information we provide to the client at meetings, where to decide on certain changes in the project or built facility, is easy to understand. It often happened to me to present data at the meeting which, although relevant and that would bring savings to the client, would not be accepted because I did not format them in a way that is easily understood by the client, who does not necessarily have to be of engineering or technical profession. That is why, in my opinion, data visualization is just as important as the accuracy of data generated by different methodologies, because the data must be as simple to understand as possible.
I will give you a couple of examples:
- During the preparation for the meeting with the client, it was necessary to prepare and present data on the physical characteristics of steel beams in the platform model. It was necessary to give the profile of the steel beam, the upper elevation of the steel beams, and show the client all steel beams longer than 6.0 m due to the specific transport requirements and the limited space for the construction of the steel platform. The required data would traditionally be presented using multiple drawings. It would be necessary to mark the upper elevation of each steel beam, to tag each steel beam and dimension the drawing of steel beams to present the required data in an appropriate traditional way. But why not do something like this – directly from the Revit model without any drawings, doesn’t the construction model look simpler and easier to understand?
- Using sensors in an already constructed building, temperature measurements were performed in each room during a one month period. After data transfer via the “Internet of Things” and processing of the obtained data, the average temperature in each room was obtained during a predefined time interval. The obtained data indicated that the average temperature in some rooms deviated from the expected values predicted by the project. In this case, the lower temperature than predicted in the project was an obstacle for the tenant of the business space to achieve full comfort. To more easily present the measured data, the data obtained from the sensors were visualized in a digital twin model using the Power BI data visualization program.
- Using sensors on the bridge, vibration data was collected during regular traffic. According to the project documentation made following the norms from 1975, the bridge needed to be reconstructed. The client turned to us to check whether it is possible to postpone the reconstruction of the bridge for some time if the current norms are respected. Instead of the classical approach, where we would do static calculations according to existing norms, sensor data and measured vibrations showed that, with minimal interventions where only one sensor showed higher vibrations than the prescribed norms, it is possible to postpone bridge reconstruction for at least seven years. If we take into account that the bridge is located near the port, which has very intensive ship traffic, the client is provided with great savings, because it was not necessary to close the port during the two-month minimum works on the reconstruction of the bridge.
I hope that based on the previous examples you saw the need to visualize the data in the digital twin model in the simplest possible way and that the whole point in the story about the data in the digital twin model is that each participant in the project process easily and simply understands data through a maximally simplified representation using the various visualization software solutions available to us today.
How To Turn The Data In The Digital Twin Model Into Concrete Savings?
We have come a long way in being able to turn the data in the digital twin model into concrete savings for the client. First, it was necessary to generate relevant data, then process them in a valid way and finally visualize them in a way that is easily understood by the client.
In the case of buildings that are now the subject of the project and that are done according to current standards, the best advice is to do periodic simulations in digital twin models during the project process. Today, the biggest problem are buildings that were already built in the middle and end of the last century. What should be especially kept in mind is the fact that the price of energy has jumped enormously in the last couple of decades, which makes older buildings very energy inefficient. Most often, energy efficiency is the main reason for investing in constructed buildings.
The technology of digital twins and the application of digital simulation tools provides us with great opportunities to achieve significant savings for the client by improving the energy efficiency of constructed facilities. Estimates based on previous experience are that without any investment in the purchase of new equipment in the building, i.e. only by optimizing the turning the heating on and off, cooling, water heating, lighting, etc., the minimum savings that an investor or tenant can achieve is 5% of the energy price which the investor or tenant pays without optimizing the energy efficiency of the building.
So, only in that segment of the building life cycle, enormous money could be saved on an annual basis. If we add to that the predictability of the expenditure on the maintenance of the building and the equipment built into it through data collection using sensors, “Internet of Things” and other tools provided by digital twin technology, I think it is more than clear to any reader what the savings is possible to achieve with the help of digital twin technology and on objective Data-Driven Decisions.
This concludes the article “Data Is The New Gold, Does The Same Apply To Data In Digital Twins?” and my view of whether information and data in digital twins are the new gold, as is the case with information and data within the data science. At the same time, I would like to take this opportunity to announce my next article “Sensors and IoT in The Digital Twin Technology”.
If you have any questions, comments, or want to know more details about the topic I covered in the article “Data Is The New Gold, Does The Same Apply To Data In Digital Twins?”, please contact TeamCAD, who will be pleased to give you additional information.
Also, if you need advice on how to best apply digital twin technology or you want to apply digital twin technology to your project or constructed facility, please contact TeamCAD, who will be happy to help you.
Until the next time,