Public Resources
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Digital Twin Toolkit
By Sarah Hayes
The purpose of this toolkit is to help you on your digital twin journey. It is intended to help you and your team think about why you need a digital twin and what it can be used for.
DT Hub members asked for support in making the business case for digital twins so through the Gemini programme, we put together a team of volunteers who are working in the area of digital twins and who offered their contribution on a pro bono basis to the development of a DT Toolkit.
The result is a DT toolkit report which takes you through:
· What is a digital twin?
· What can digital twins be used for?
· A case study register on the DT Hub
· A business case template for a digital twin
· A roadmap to implementing your digital twin
This is the first version of the DT toolkit and we’re looking for your involvement in testing this toolkit and developing it further. Please comment here.
The toolkit includes a business case template (available below or upon clicking "download this file"), which is intended to help you put together the business case for a digital twin.
To watch the Sarah Hayes' presentation and the DT Toolkit Launch click here.
DT toolkit business case template.docx
3,271 downloads
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Analysis of the U.K.’s Top 100 Construction Companies Shows Which Firms Performed Best Over the Past Decade
By Catherine Condie
Article by Bentley Systems
6 downloads
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Leadership in a Data-driven Age: Why the Best Managers Will Always Welcome Greater Transparency and Why Fundamental Leadership Components Haven’t Changed
By Catherine Condie
Article by Bentley Systems
3 downloads
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Grand Paris Express: What We Learn from City Centre Transport Megaprojects in Paris and London
By Catherine Condie
Article by Bentley Systems
3 downloads
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For Electric Vehicle Charging, “Going Dutch” Means Being Open, Transparent, and Interoperable
By Catherine Condie
Article from Bentley Systems
4 downloads
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How the World’s First Digital Twin of a Nation Can Help Create Better Cities
By Catherine Condie
Article by Bentley Systems
9 downloads
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The Wind of Change Is Blowing on Renewables, Making Them Cheaper and More Efficient
By Catherine Condie
Article by Bentley Systems
4 downloads
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Could a National Framework for Data Help Overcome the Shortcomings of the COVID-19 Census?
By Catherine Condie
Article by Bentley Systems
4 downloads
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A Smarter Way to Future-proof Our Water Supply
By Catherine Condie
Article by Bentley Systems
3 downloads
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Transforming and Decarbonising Infrastructure Delivery
By Catherine Condie
Article by Bentley Systems
5 downloads
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Vertical Buildings: What Asset Owners and Contractors Need to Know about Britain’s New Building Safety Regulator
By Catherine Condie
Article by Bentley Systems
5 downloads
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Cyber-Physical Infrastructure Consultation
By Catherine Condie
From the Department for Science, Innovation and Technology
Executive Summary
From collaborative swarms of drones packing our food, to interactive virtual representations of operational hospitals, cyber-physical systems and their increasing interconnection are transforming our world at an increasing rate1.
Our consultation last year explored the opportunities and challenges of a national Cyber-Physical Infrastructure, in which connected networks of such systems could provide a step change in the economic and social value of the individual applications.
A significant number of written responses from industry (including both developers and users), academia, the wider public sector and wider society, supplemented by extensive online and in-person dialogue has informed this response.
The strategic value and opportunities of Cyber-Physical Infrastructure were strongly endorsed by respondents, particularly highlighting: Innovation and productivity; Resilience; Climate change response; and Levelling up.
Responses highlighted opportunities across a range of sectors, recognising the breadth and cross-sectoral potential of Cyber-Physical Infrastructure. However, the opportunities within the following sectors were identified most prominently: Energy Systems and utilities; Infrastructure and Built Environment; Manufacturing; Natural Environment; Transport and Supply Chains; and Wellbeing, Health and Social Care. Two cross cutting areas of Research, Development and Innovation, and Net Zero were also strongly identified (see Section 5 for more detail).
There was also a strong call for government to help tackle a number of systemic challenges, through the supporting key enablers, namely: Security & resilience; Interoperability; Recognised value propositions; Frameworks, guidance and standardisation; and Skills (see Section 6 for more detail).
This consultation response sets our vision to enable greater innovation in the UK through a Cyber Physical Infrastructure (see Section 4) and the key next steps that we and wider public sectors partners will continue to take in collaboration with industry, academia and wider society to realise this, including:
• Launching a grant competition to fund one or more organisations working together to develop and host a Cyber-Physical Infrastructure ecosystem accelerating capability
• Continued UKRI funding of a breadth of cyber-physical research, development and innovation including: o £3m to develop a multi-disciplinary UK digital twinning research community
o Additional funding for digital twinning research to support and improve the operation and resilience of the UK energy grid
o A suite of Catapult-led Cyber-Physical Infrastructure projects
o Up to £20m for a research hub in digital twinning for decarbonisation and improved integration of the UK’s transport systemo £7.5 million in cyber security research with partners including the National Cyber Security Centre
o A Turing Research and Innovation Cluster (TRIC) in Digital Twins
• Department for Transport investing in digital twins for transport
• Department for Business and Trade continuing to lead delivery of the National Digital Twin Programme
1 https://www.gov.uk/government/publications/cyber-physical-infrastructure
16 downloads
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Public resources on DAFNI
By Daniel Block
The Data and Analytics Facility for National Infrastructure (DAFNI) provided storage and computing capabilities via their public portal, and a secure private development environment to enable collaboration on sensitive data across the distributed team. The version of the CReDo model hosted on DAFNI is designed to be used with data stored on the platform and provides users the opportunity to run the visualisations with their own data, or to integrate with an alternative analysis pipeline.
A document detailing public resources on DAFNI is available to download here
23 downloads
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How to access CReDo on DAFNI platform
By Daniel Block
The Data and Analytics Facility for National Infrastructure (DAFNI) provided storage and computing capabilities via their public portal, and a secure private development environment to enable collaboration on sensitive data across the distributed team. The version of the CReDo model hosted on DAFNI is designed to be used with data stored on the platform and provides users the opportunity to run the visualisations with their own data, or to integrate with an alternative analysis pipeline.
For information about how to access and use the CReDo model on DAFNI, please download this document.
31 downloads
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CReDo Technical Report 4: Modelling System Impact
By Daniel Block
Summary
Infrastructure assets in different sectors require connectivity in order to operate and provide essential services to end users. For example, water requires power and telecoms, power requires telecoms, among other connections. Understanding the connectivity of different infrastructure assets at the systems level, as well as which connections and assets are critical, is essential to ensure that investment planning is targeted at the most critical assets for normal and unusual operation. CReDo’s ambition is to address the connections between different infrastructure assets owned and operated by different asset owners in order to understand where the critical connections at the systems level may be, how critical assets may fail during extreme flooding scenarios and what is the level of vulnerability and impact on service provision.
In this use case, asset data from three service providers delivering power, water and telecommunication services have been integrated and interrogated within a single platform to provide insights into sectoral interdependencies and better understand how the system responds to and is impacted by a range of potential future flood events, driven by a changing climate. This first phase of CReDo involves a modelling approach that assesses how the different assets are connected in the wider system and how cascading failures are propagating across the system following asset failures in parts of the network.
The approach taken to analyse the flood impacts first used a flood-depth criteria for high-level identification of assets that would directly fail from high flood levels across the site. Building on this, the core of the work was to propagate failures from those directly impacted nodes. Failures are triggered from the direct connections between assets (a power asset providing external power supply to water assets) when a single asset fails as a result of flooding. The model developed is deterministic. The propagation of failure is implemented first within each sectoral network independently (water, power and telecommunication) before being extended across networks. This was achieved by integrating the data into component networks models and connecting these with an overarching coordinating algorithm.
Building on the work undertaken in this first phase of CReDo, it is recommended that the next phases consider the following to address the current limitations. These include:
Modelling of more complex interdependencies in the system (including for links and dependencies on the transport sector); Modelling of existing redundancy in individual assets, for example a flood defence wall or backup power supplies; Modelling of criticality of individual assets and how system vulnerability may be expressed; Running of a series of simulations at the system level to better understand how the system responds under a range of possible climate impact and individual asset failure scenarios; Development of dynamic models that simulate system impacts over time; recognising that the system is not static, and failures will unfold as the event progresses and recovery methods are put in place.
Testing the system under various scenarios with these criticalities identified would provide useful insights to asset owners/operators for making investment decisions that maximise system resilience in the face of extreme flood and other climate hazards driven by a changing climate.
Finally, where the current work focussed on developing and testing failure and propagation models at a local scale, future work should allow for an implementation at a larger scale where the Information Management Framework associated tools can be scaled up and adapted to wider geographies and portfolio of assets.
133 downloads
- CReDo
- Climate Resilience
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CReDo Technical Report 3: Assessing Asset Failure
By Catherine Condie
Summary
Planning for resilience against climate hazards in our economic infrastructure requires a systems approach. The development of connected digital twins that enable the sharing of information between infrastructure sectors and organisations will improve our understanding of how assets fail, where they fail and how any cascading failures can better inform resilience planning at the systems-level. To understand the connections between different assets in a system — and how a cascading failure could impact service provision — the vulnerability and probability of failure of individual assets and failure modes against different climatic hazards need to be understood.
In this use case, the vulnerability of individual assets within an infrastructure system has been considered as the susceptibility of an asset to failure, its condition, capacity and ability to cope in the presence of the hazard, and it is expressed in probabilistic terms. Thus, asset failure following exposure to coastal flooding has been assessed using probabilistic modelling. This allows for the consistent interrogation of how individual assets in the system could fail under various incidents induced by coastal flooding. Singular characteristics of some assets and asset networks require distinct probability distributions that consider specific causal pathways that would lead the asset to fail. Bayesian Network Modelling uses probabilities to represent all uncertainties that are quantified for the modelling, and was adopted as the common language to model probability of failure and express vulnerability caused by coastal flooding at the asset-level.
This report outlines the general approach undertaken in the connected digital twin to assess the probability of failure of assets within the network and how it has been applied specifically to investigate the probability of failure of an individual wastewater pumping station against coastal flooding.
The model for the probability of failure requires input in the form of flood information (extent, depth), supported by expert judgement. This is to understand the causal pathways leading to the failure of an asset in the example of a wastewater pumping station. The development of a probabilistic model that is sufficiently realistic to deliver the intended goal is paramount for understanding vulnerability at the asset level and how this can affect the wider infrastructure system. This requires elicitation from experts in asset owner/manager organisations. Engaging with experts who operate individual assets not only provides a detailed understanding of the functioning /non-functioning of an asset, it also allows investigation of probabilities of failure for individual asset components under various operating conditions and past incidents in collaboration with asset owners. Through this engagement, a calibration of the probabilistic models can be undertaken for various sites and asset classes.
The work conducted focusses on how Bayesian Network Modelling can be implemented across the asset network, by understanding and integrating a range of failure modes into a working interface. Key to the failure of an asset is the direct exposure of its main parts to coastal flooding. Elements such as the submergibility of parts, their location above the standard level of protection of the asset or how the asset operates during increasing flows in the wastewater network as a result of the coastal flooding conditions would have an impact on any direct failure assessment. Other indirect failure modes highlighted in the findings originate from externalities to individual assets, including its accessibility and thus its reliance on transport infrastructures to implement pre-incident and post-incident recovery efforts. Similarly, the dependence of an asset on external power supply and telecommunication provision for its functioning could lead to its failure if such external connections were cut prior or during a flood incident.
The modelling work conducted in this phase of work considers maximum flooding conditions occurring at the same time across the entire network and leading to the worst disruption. It is recommended that future asset vulnerability modelling should focus on both the asset-specific and external factors that influence the probability of failure, allowing for the sequencing of failures as the flood event unfolds and alongside other associated climatic hazards. Investigations of how quickly an asset can recover after failing is another aspect that should be taken into account in the evaluation of its vulnerability. This would further support the system-wide vulnerability and cascading failure assessments.
Overall, the deployment of Bayesian Network Modelling across the network demonstrates the benefits of having an overarching framework for assessing vulnerability of individual assets. Such assessments could be improved by investigating different combinations of failure modes across assets, and testing probability of failures across multiple climate scenarios, within the same interface. Whilst such an approach allows for a level of fine-tuning to calibrate site-specific probability distributions, the greatest benefits to resilience and investment planning decisions would be to implement the approach at the systems level. This would involve a multi-sectoral network of hundreds to thousands of assets.
124 downloads
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CReDo technical report 2: Generating Flood Data
By Daniel Block
Summary
Climate change will modify the frequency and magnitude of many extreme weather events. In the UK, flooding is expected to increase due to wetter winters and more intensive summer convective storms. In addition, sea level rise will threaten low-lying areas, overall posing a risk to communities, infrastructure and the delivery of services to society.
For the development of the CReDo connected digital twin, the processing, integration and interrogation of appropriate flood hazard information was required alongside asset data to test the ability of the system-of-systems to cope under a range of future flood scenarios. This report includes a list of open-source flood data to enable a rapid screening of the risk of a portfolio of assets. It also presents standard industry approaches to evaluate the extent and magnitude of flooding in the UK by a combination of hydrological and hydraulic models. Guidance and process for incorporating the impact of climate change into these evaluations is explained too.
Flooding can occur from a variety of sources, and two of them, the sea and direct rainfall, were investigated in detail given their relevance for the CReDo study area. Environment Agency coastal flood mapping was obtained and applied in the analysis. It considered the risk of flooding due to storm surge and waver overtopping exacerbated with sea level rise. The Environment Agency also provided fluvial (river) flood maps and models, which confirmed that river floods would be contained within flood defences even for climate change scenarios in the area under study. Information of this sort is held by the regulator nationwide and can be accessed upon request, constituting a desirable starting point of any detailed flood investigation. However, the risk of pluvial (surface water) flooding associated with intense direct rainfall onto the study area was missing, and modelling with HiPIMS (a hydrodynamic flood model) undertaken for a range of climate change projections for its characterisation. The model was able to combine the topography and land cover of the area with a set of pluvial, fluvial and tidal boundary conditions to represent overland flow in two dimensions.
Understanding the impact of climate change on flood hazard requires an estimation of changes in weather extremes, which can be derived using a range of climate models developed at a global, regional or local scale for a suite of scenarios representing various levels of global warming. UKCP18 is the most up to date set of climate projections available in the UK, which can be applied to flood models to establish changes in the likelihood and intensity (i.e. flood depth) of flooding at an asset level. In CReDo this was achieved by adding a climate change allowance to uplift the selected pluvial and fluvial extreme events. The standard industry approach is to adopt the allowances prescribed by the regulator for a certain time horizon and location. However, in CReDo, UKCP18 local projections for the high emission scenario were consulted to establish changes in the intensity of convective storms, and the probabilistic projections of extremes were used to examine the full range of uncertainty in emissions and climate models.
Although in this first phase of development the impact of climate change on a single extreme flood event has been used to demonstrate the future risk to assets, the long-term objective of CReDo is to expand the hazard information to include a greater number of events and additional risks (e.g. heat waves), so that the resilience of the system can be tested in a dynamic way. This will enable future work to quantify the impact on the level or service and to identify the critical assets contributing to it. Having a single platform for the processing, running and interrogation of climate, flood and asset data conjunctively is key for a realistic representation of the system operation, and this has been achieved in CReDo. This will help to prioritise adaptation actions to reduce risks to an acceptable level.
149 downloads
- CReDo
- Climate Resilience
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CReDo technical report 1: Building a Cross-Sector Digital Twin
By Daniel Block
Summary
A digital twin was developed to resolve the effect of floods on individual infrastructure assets and the resulting cascade of effects across the combined network of:
Anglian Water’s water and sewerage assets. BT’s communication assets. UK Power Networks’ power network assets.
The digital twin uses simple hierarchical domain ontologies to represent the data describing the assets as a knowledge graph. This data structure is exploited to describe the connectivity and operational states of the assets.
The digital twin demonstrates how to use the hierarchical structure of the ontologies underlying the knowledge graph to achieve interoperability between the data from the different asset owners. It combines the asset data with the output of flood simulations, and models the response both of individual assets and of the combined network to the flood. The digital twin is designed to be extensible. It should be straightforward to extend the breadth of coverage to include assets from other sectors and other regions of the country, and the depth of coverage to include a more granular description of assets and their operational state. Such extensions will be necessary to enable the digital twin to properly address extreme weather scenarios, and to extend the digital twin to other use cases.
A browser-based geospatial visualisation of data from the digital twin allows the assets, logical connectivity of the network and operational state of the assets to be explored. The visualisation is overlaid by data from flood simulations. The data are presented in selectable layers to provide the ability to focus on different aspects of the network. Assets can be selected to view metadata about the asset and the time history of the operational state of the asset throughout the flood. Additional controls facilitate the exploration of the connections to and from individual assets.
A public demonstrator of the current digital twin and visualisation is to be made available on DAFNI, the Data & Analytics Facility for National Infrastructure. The corresponding software and a synthetic data set are published under permissive licences so that asset owners and third parties can test the ideas on their own data and contribute to future developments. The sharing of data and the ability to visualise the connectivity of assets was valuable and led to the correction of anomalies that could not be seen when looking at any single network.
An inconsistency that was present in one ontology was able to be overcome with a conversation and a few lines of extra code, and did not inhibit the functionality of the digital twin. The ontologies could be improved at a later date to address the issue more robustly. In the future, the ontologies could also be aligned with hierarchical ontologies arising from the Information Management Framework. This would aid consistency and interoperability. Although the data were accessed as a knowledge graph, some of it was able to be hosted using relational databases, allowing the use of established technology for each type of data. It was shown that other knowledge graphs could be incorporated into the digital twin. This was demonstrated for data about buildings and live streams of data from river level sensors. Such data could later be included in the evaluation of scenarios by the digital twin.
Future work should consider how to represent scenario-specific information, and how to simulate events efficiently whilst still providing wide-scale data coverage. The level of detail represented in a digital twin should be driven by the needs of use cases. In the case of the current digital twin, it should be extended to include whatever is necessary to describe the resilience of the combined network. This may include extending the digital twin to other domains and sectors. It should also extend work started in this first phase of the project to quantify the value of the increase in resilience that could be achieved as a result of being able to assess the combined network using shared data.
376 downloads
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CReDo: an overview
By Daniel Block
CReDo is the culmination of a concerted effort across multiple organisations. The project sought to include data from a wide range of sources, comprising differing formats and digital availability. Building on the principles of the National Digital Twin programme’s Information Management Framework, asset data from multiple organisations has been integrated within one system model and equipped with a visual interface. This has allowed for a clear representation of the connectivity between assets and an analysis of the resulting interdependencies between sectors.
Additional flood hazard information was processed, integrated and interrogated within the system model to represent the extent and depth of flooding across the studied area under various future flooding scenarios. This climatic data was used alongside asset information to investigate direct failures resulting from local flooding conditions, and to test the ability of the system to cope under a range of future flood scenarios. In order to build a picture of the wider system impacts, two processes were run in parallel;
First, information about assets was gathered along with information concerning the likelihood of failure in various flooding scenarios. This was conducted using expert elicitation techniques and Bayesian modelling, assessing the probability of failure of a given asset as a result of local flooding conditions. Second, operational research techniques have been employed to better understand the infrastructure interdependencies and to propagate failures resulting from flood conditions across single networks, and further across the entire infrastructure system.
"There is huge potential for connected digital twins to benefit industry and society in terms of damage prevention, cost savings and service reliability, not just for the immediate services like telecoms, energy, water and utilities – but these also cascade down to any industry – or person – that relies heavily on or would be affected by disruption to those services."
Tom Collingwood
STFC Hartree Centre
594 downloads
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Identifying the expected impacts of CReDo report
By Daniel Block
The Benefits report includes an illustrative quantification of the potential benefits of CReDo based on a simulation using synthetic data. The Frontier Economics team found that the benefits from CReDo looking at the impact of future surface water flooding scenarios could range from £6m to £13m across East Anglia and from £81m to £186m across the UK over the period to 2050 (in constant prices from 2022-2050). The analysis used synthetic data and does not cover the benefits of other use cases such as extreme heat. Limitations from using synthetic data rather than real data mean that at this stage, it has not been possible to provide robust estimates of the potential benefits that CReDo can generate.
The methodology underpinning the results can be adapted and refined to form the basis of a more detailed evaluation of a future version of CReDo. A refined version of this cost-benefit analysis methodology could be integrated in CReDo and would help the users of CReDo to understand the costs and benefits of different strategies to increase resilience of the infrastructure networks. An indicative public return on investment of 23:1 implies that connected digital twins like CReDo help to address a coordination problem. While the benefits accrue across multiple parties, individual actors may lack the incentive to invest alone in systems-based solutions such as CReDo. Therefore, work is required to demonstrate the benefits and to kickstart the coordination of effort to achieve those benefits
The quotes on this page, from CReDo’s Asset Owners, point more directly toward the wider scope and larger scale of potential benefits from connected digital twins across infrastructure sectors.
“We have been successful in demonstrating what a digital twin is truly about, and what it can do. Being able to demonstrate that collaborative approach has been a learning curve on every single front, but to end up with an output that brings that to life and can demonstrate in a tangible way the sustained benefit that can be achieved, is very powerful.”
Matt Webb
UK Power Networks
“We require tools to help us make better choices, and one thing that CReDo has shown us is how complicated the modelling is, how much information is required and how it’s not necessarily easily discoverable. You need to have climate models, topographical data, highways models, and the complexity of the analysis itself, identifying the elements, the failure probabilities and these are all reasons to build it once and allow all the asset owners to access the system. … That to me seems to be one of the benefits that I did not see at the start.”
Louise Krug
BT
93 downloads
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Connected Digital Twins Summit 2023
By Catherine Condie
22 June 2023, 09:00-17:30 – Hybrid Event Venue: Urban Innovation Centre, 1 Sekforde Street, London EC1R 0BE
UK and international Digital Twin Hub community members will convene to explore the latest cross-industry, business applications of digital twins that are creating impact and ROI. Join 350+ senior-level policymakers, corporate asset owners, solution providers, academics, and investors to experience live demonstrations and interactive showcases, and gain access to new tools to enable business decisions.
169 downloads
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An Information Management Framework for Environmental Digital Twins (IMFe)
By Catherine Condie
An Information Management Framework for Environmental Digital Twins (IMFe)
Executive summary
Environmental science is primarily concerned with assessing the impacts of changing environmental conditions on the state of the natural world, whether affected by natural variability or by the impact of human activity. The Natural Environment Research Council (NERC) has recently published its digital strategy, the first of its kind for NERC, which sets out a vision for digitally enabled environmental science for the next decade. This is echoed in the Met Office’s Research and Innovation Strategy that includes the vision of transforming the weather and climate research and services through deploying transformative technologies such as Digital Twins. This strategy places data and digital technologies at the heart of UK environmental science. One such set of technologies are digital twins.
A digital twin is a virtual representation of an object or system (for example the natural environment) updated as the system changes using observations. Observations may come from a range of sources, some traditionally used in the environmental science community such as satellite remote sensing or sensors on ships or weather stations, or through the emergence of sensors on everything from fridges to cars to large-scale built infrastructure. A digital twin then uses simulations or data-based methods such as machine learning to generate a replica (‘twin’) of the system that can be used to understand the system itself. Environmental digital twins therefore have the potential to significantly improve our understanding of the natural environment.
The emergence of increasingly large, diverse, observed data sources and the development of digital twin technologies combined provides an opportunity for the environmental science community to make a step-change in our understanding of the environment. But to realise the value of environmental digital twins they need to be developed following agreed standards to make sure the information can be trusted by the user, and so that data from twins can be shared, both between environmental digital twins and with other types of digital infrastructure.
To enable this, an information management framework (IMF) is needed that establishes the components for effective information management within and across the digital twin ecosystem. It must enable secure, resilient interoperability of data, and is a reference point to facilitate data use in line with security, legal, commercial, privacy and other relevant concerns. Previous work has highlighted the importance of developing an IMF, including the Centre for Digital Built Britain (CDBB) roadmap to an IMF (CDBB, 2020).
This roadmap follows the CDBB approaches and develops it further to outline the steps needed to develop an IMF that meets the demanding requirements of the environmental domain (an IMFe) whilst also ensuring interoperability with other digital twins.
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Launching the Digital Twin Toolkit presentation
By Tammy Au
To download the slides, please click the 'Download this file' on the right.
The DT Toolkit can be found here.
101 downloads
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Digital Twin Hub - Overview brochure
By Catherine Condie
Overview brochure. 33 pages.
Everything you need to know about the DT Hub and its community in an easy download.
New for the DT Hub in 2023 is our overview brochure, highlighting our work as a community to date, our priorities and objectives, key projects and initiatives, and the impact we make collaboratively.
We hope you will use the brochure to share our vision with colleagues and industry contacts.
“Digital twins and connected digital twins will equip us against global systemic challenges including pandemics, climate change and resilience. They make investment sense for societies, industries and governments as we move towards the vision of a cyber physical future, and their impact on our economies will be huge. The need for connected digital twins to meet the challenges of this changing world has never been greater and the Digital Twin Hub is leading the way."
Dr Alison Vincent, Chair, Digital Twin Hub
319 downloads
- Media
- Collaboration
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