Foundational Research Gaps and Future Directions for Digital Twins (2024) / Chapter Skim
Currently Skimming:
6 Feedback Flow from Virtual to Physical: Foundational Research Needs and Opportunities
6 Feedback Flow from Virtual to Physical: Foundational Research Needs and Opportunities
Pages 85-98
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 85... ...
This chapter also discusses the roles of digital twins for providing decision support to a human decision-maker and for decision tasks that are shared jointly within a human–agent team. The chapter concludes with a discussion of the ethical and social implications of the use of digital twins in decision-making. PREDICTION, CONTROL, STEERING, AND DECISION UNDER UNCERTAINTY Just as there is a broad range of model types and data that may compose a digital twin depending on the particular domain and use case, there is an equally broad range of prediction and decision tasks that a digital twin may be called on to execute and/or support.
|
From page 86... ...
Using a digital twin for thermal management allows equipment operators to achieve higher uptimes, as compared to other methods that rely on large safety factors.b Locomotive Trip Optimization Within the locomotive industry, smart cruise control systems consider terrain, train composition, speed restrictions, and operating conditions to compute an optimal speed profile. Trip optimizers utilize digital twins of trains to autonomously
|
From page 87... ...
Research gaps to address these challenges span many technical areas including operations research, reinforcement learning, optimal and stochastic control, dynamical systems, partial differential equation (PDE) constrained optimization, scalable algorithms, and statistics. Rare Events and Risk Assessment in Support of Decision-Making In many applications, digital twins will be called on to execute or support decisions that involve the characterization of low-probability events (e.g., failure in an engineering system, adverse outcomes in a medical intervention)
|
From page 88... ...
On the other hand, Monte Carlo sampling becomes extremely inefficient, especially when dealing with low-probability events. Finding 6-1: There is a need for digital twins to support complex trade-offs of risk, performance, cost, and computation time in decision-making. Sensor Steering, Optimal Experimental Design, and Active Learning Within the realm of decision-making supported and executed by digital twins is the important class of problems that impact the data -- specifically, the sensing and observing systems -- of the physical counterpart. These problems may take the form of sensor placement, sensor steering, and sensor dynamic scheduling, which can be broadly characterized mathematically as optimal experimental design (OED)
|
From page 89... ...
Additionally, in the context of evolving environments and systems, digital twins play a pivotal role in adaptive data collection strategies, identifying areas that need more data and refining collection parameters dynamically. Ultimately, these capabilities, when harnessed correctly, can lead to more informed and timely decision-making, reducing risks and enhancing efficiency.
|
From page 90... ...
In addition, since the coupled data assimilation and optimal control problems are solved repeatedly over a moving time window, there is an opportunity to exploit dynamically adaptive optimization and control algorithms that can exploit sensitivity information to warm-start new solutions. Scalable methods to achieve dynamic adaptation in digital twin decision-making are necessary for exploiting the potential of digital twins.
|
From page 91... ...
placing strong assumptions on the model and relying on extensive calibration efforts to estimate model parameters a priori. Neither of these two approaches is well suited to incorporating physical models or simulators, and filling this gap is essential to decision-making with digital twins.
|
From page 92... ...
The complex and dynamic nature of a digital twin introduces increased challenges around building trust and conveying evolving uncertainty, while also enabling understanding across all individuals who will interact with the digital twin. The contextual details required for digital twins can also introduce challenges in ethics, privacy, ownership, and governance of data around human contributions to and interactions with digital twins. Use- and User-Centered Design There is a range of respective roles that humans can play in interactions with digital twins, and the particular role and interaction of the human with a digital twin will influence the design of the digital twin.
|
From page 93... ...
To support human–digital twin interactions effectively, focused efforts must be made toward developing implementation science around digital twins, structuring user-centered design of digital twins, and enabling adaptations of human behavior. Looking to the future, as emerging advances in the field of artificial intelligence (AI) allow for verbal and visual communication of concepts and processes, AI-mediated communications may be incorporated into digital twins to accelerate their creation, maintain their tight alignment with physical twins, and expand their capabilities.
|
From page 94... ...
Techniques like visualization, confidence intervals, or interactive dashboards can be deployed to make the communication of uncertainty more effective and user-friendly. Conclusion 6-2: Communicating uncertainty to end users is important for digital twin decision support. Establishing Trust in Digital Twins There are many aspects that add to the complexity of establishing trust for digital twins.
|
From page 95... ...
With growing utilization of augmented reality and virtual reality, the collection of human interactions in the digital space will continue to increase and serve as a source of data for human–digital twin interactions. The data gathered within these interactions can also inform what and how future data capture is integrated into the digital twin (e.g., timing of assessments or measurements, introduction of new biosensors for humans interacting with digital twins)
|
From page 96... ...
Conclusion 6-3: While the capture of enough contextual detail in the meta data is critical for ensuring appropriate inference and interoperability, the inclusion of increasing details may pose emerging privacy and security risks. This aggregation of potentially sensitive and personalized data and models is particularly challenging for digital twins.
|
From page 97... ...
TABLE 6-1 Key Gaps, Needs, and Opportunities for Enabling the Feedback Flow from the Virtual Representation to the Physical Counterpart of a Digital Twin Maturity Priority Early and Preliminary Stages Scalable methods are needed for goal-oriented sensor steering and optimal 1 experimental design that encompass the full sense–assimilate–predict–control–steer cycle while accounting for uncertainty. Trusted machine learning and surrogate models that meet the computational and 1 temporal requirements for digital twin real-time decision-making are needed. Scalable methods to achieve dynamic adaptation in digital twin decision-making 2 are needed. Theory and methods to achieve trusted decisions and quantified uncertainty for 1 data-centric digital twins employing empirical and hybrid models are needed. Methods and tools to make sensitivity information more readily available for 1 model-centric digital twins, including automatic differentiation capabilities that will be successful for multiphysics, multiscale, multi-code digital twin virtual representations, are needed. Research on and development of implementation science around digital twins, 1 user-centered design of digital twins, and adaptations of human behavior that enable effective human–digital twin teaming are needed. Certain domains and sectors have had more success, such as in the Department of Defense. Uncertainty visualization is key to ensuring that uncertainties are appropriately 2 considered in the human–digital twin interaction and resulting decisions, but development of effective approaches for presenting uncertainty remains a gap.
|
From page 98... ...
2023. "Building Robust Digital Twins." Presentation to the Committee on Foundational Research Gaps and Future Directions for Digital Twins.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.