The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles
Open accessAbstract
Future generations of NASA and U.S. Air Force vehicles will require lighter mass while being subjected to higher loads and more extreme service conditions over longer time periods than the present generation. Current approaches for certification, fleet management and sustainment are largely based on statistical distributions of material properties, heuristic design philosophies, physical testing and assumed similitude between testing and operational conditions and will likely be unable to address these extreme requirements. To address the shortcomings of conventional approaches, a fundamental paradigm shift is needed. This paradigm shift, the Digital Twin, integrates ultra-high fidelity simulation with the vehicle s on-board integrated vehicle health management system, maintenance history and all available historical and fleet data to mirror the life of its flying twin and enable unprecedented levels of safety and reliability.
AI snapshot
Written from the paper’s full text.
TL;DR
The paper proposes the Digital Twin paradigm—an integrated multiphysics, multiscale, probabilistic simulation of an as-built vehicle using best physical models, sensor updates, fleet history, and IVHM data—to mirror the life of its flying twin and improve certification, fleet management, and sustainment. It argues conventional factor-of-safety, similitude, and inspection approaches are inadequate for future NASA and U.S. Air Force vehicles with lighter mass, higher loads, and longer extreme service.
Key findings
- Conventional certification and sustainment rely on factors-of-safety, similitude, worst-case scenarios, and fleet leaders; factors can be as large as 2.0 depending on material and configuration, a service life factor of 4.0 is applied to well-characterized spaceflight structures, and known flaws must show a safety factor of 1.5 against fracture.
- The Digital Twin integrates ultra-high fidelity physical models, on-board IVHM sensor data, maintenance history, and historical/fleet data via data mining and text mining; it continuously forecasts vehicle health, remaining useful life, and probability of mission success, and can recommend mission profile changes or activate self-healing mechanisms.
- Near-term opportunities include the AFRL Digital Twin: Spiral 1 using the F-15 as a testbed, and a NASA approach focused on a small highly critical non-redundant component such as a MEMS.
- Expected advantages include decreased system weight by reducing reliance on statistical distributions, heuristic design philosophies, physical testing, and assumed similitude, plus increased reliability through continuous monitoring and mitigation of degradation and anomalous events.
Methods
- Conceptual/vision paper, not an experimental study; it presents the Digital Twin paradigm and requirements, with examples drawn from NASA standards and handbooks including NASA-STD-5001A, NASA-STD-5019, and NASA-HDBK-5010.
- No sample, dataset, or statistical analysis is reported; the paper discusses conventional approaches, Digital Twin attributes, near-term opportunities, advantages, and influence on national goals.
- Illustrative figures and tables are used to motivate the paradigm, such as an STS payload launch/landing spectrum and upper-bound fatigue crack growth rate curves estimated as three standard deviations above mean values.
Limitations
- The paper states the Digital Twin is an ambitious concept “unlikely to attain maturity for many decades,” so a series of intermediate steps is required.
- The paper states future vehicles may encounter conditions that cannot be foreseen, and long-duration space missions may make conventional inspection and maintenance impossible.
- Evident from the text: no quantitative validation, implementation results, or performance metrics for a Digital Twin are reported; the work is a concept and roadmap paper.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 21 cited sources checked · 0 supported · 0 flagged
- Interpretationreasoning
When similitude is violated, probabilistic methods break down as readily as those based on factors-of-safety.
“When similitude is violated, probabilistic methods break down as readily as those based on factors-of-safety.”
Quote in the paperSubstantial claim - Premisenone given
Current approaches for certification, fleet management and sustainment of NASA and U.S. Air Force vehicles are largely based on statistical distributions of material properties, heuristic design philosophies, physical testing and assumed similitude between testing and operational conditions.
“Current approaches for certification, fleet management and sustainment are largely based on statistical distributions of material properties, heuristic design philosophies, physical testing and assumed similitude between testing and operational conditions and will likely be unable to address these extreme requirements.”
- Also stated in: § Introduction · plain
“Existing methodologies for vehicle certification, fleet management and sustainment are largely based on similitude and a heuristic understanding of the effects of operational and anomalous conditions on the structural health, safety and performance of a vehicle.”
Quote in the paperNot a substantial claim - Also stated in: § Introduction · plain
- Interpretationreasoning
Computer codes used to predict failures are of limited predictive capability because they only produce responses that have previously been observed experimentally and then programmed for future assessment.
“Such codes are of limited”
Quote in the paperSubstantial claim - Interpretationreasoning
Current approaches for certification, fleet management and sustainment will likely be unable to address future extreme requirements.
“Current approaches for certification, fleet management and sustainment are largely based on statistical distributions of material properties, heuristic design philosophies, physical testing and assumed similitude between testing and operational conditions and will likely be unable to address these extreme requirements.”
Quote in the paperNot a substantial claim - Interpretationreasoning
Current probabilistic or reliability methodologies are inadequate because they are based on assumed similitude between the circumstances in which the underlying statistics were obtained and the environment in which the vehicle operates.
“Even current probabilistic or reliability methodologies are inadequate because they are based on assumed similitude between the circumstances in which the underlying statistics were obtained and the environment in which the vehicle operates.”
Quote in the paperSubstantial claim
- Premisecitation
The accepted practice for verification of launch vehicles is the prototype approach in which a separate, dedicated test structure, identical to the flight structure, is tested to demonstrate that the design meets the factor-of-safety requirements.
“As discussed in the standard, the accepted practice for”
Quote in the paperSubstantial claim0 of 1 sources checked- cites NASA-STD-5001A
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationreasoning
Codified practices may not be sufficient to address the future extreme requirements of some future NASA and U.S. Air Force vehicles.
“Moreover, they may not be sufficient to address the future extreme requirements of some future NASA and U.S. Air Force vehicles.”
Quote in the paperNot a substantial claim
- May combine two claims. 15
- Classified as probably not a substantial claim. 39
May combine two claims.
Interpretationnone givenCompounding of factors-of-safety is pervasive and may lead to unnecessarily heavy structures and reduced performance without necessarily improving the actual safety of the vehicle or the probability of mission success.
“Additionally, compounding of factors-of-safety is pervasive and may lead to unnecessarily heavy structures and reduced performance without necessarily improving the actual safety of the vehicle or the probability of mission success.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Premisenone givenInspection schedules for fleet management and sustainment are typically determined from experience with similar vehicles that have performed similar missions.
“Inspection schedules are typically determined from experience with similar vehicles that have performed similar missions.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Premisenone givenInspection is often performed based on experience with the fleet leader, the vehicle in the fleet that experienced the most flights or the worst degradation.
“Often, inspection is performed based on experience with the fleet leader, the vehicle in the fleet that experienced the most flights or the worst degradation.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningThe ability to fully understand degradation and anomalous events and foresee previously unknown unknowns may represent the difference between mission success and mission failure.
“Thus, the ability to fully understand degradation and anomalous events and foresee previously unknown unknowns may represent the difference between mission success and mission failure.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisereasoningIf unacceptable degradation of a component is found during inspection of the fleet leader, it may be decided that all vehicles of that class be inspected immediately regardless of the specific history of each vehicle.
“If, for example, unacceptable degradation of a component was found during an inspection of the fleet leader, it may be decided that all vehicles of that class be inspected immediately regardless of the specific history of each vehicle.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationNASA-HDBK-5010 discusses separate conservatisms for crack size, applied loads, material properties, and analysis for known cracks in fracture critical hardware.
“An extreme case of codified conservatism is discussed in NASA-HDBK-5010 10 , where separate conservatisms for crack size, applied loads, material properties, and analysis are discussed for”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-HDBK-5010
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThe Digital Twin will decrease system weight by reducing reliance on statistical distributions of material properties, heuristic design philosophies, physical testing and assumed similitude between testing and operational conditions.
“It will also decrease system weight by reducing reliance on statistical distributions of material properties, heuristic design philosophies, physical testing and assumed similitude between testing and operational conditions.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationAccording to NASA-STD-5001A, a service life factor of 4.0 is applied to spaceflight structures made of well-characterized materials with sufficient load cycle data, while structures made of not well-characterized materials or complex failure modes may require an additional factor and testing.
“According to NASA-STD-5001A 1 , a service life factor of 4.0 is applied to”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-STD-5001A
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationKnown cracks in fracture critical hardware require special treatment wherein upper bounds for crack size estimate accounting for any possible nondetected adjacent cracks and/or crack tip extensions are required.
“Known cracks in fracture critical hardware require special treatment wherein upper bounds for crack size estimate accounting for”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-HDBK-5010
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationAnalyses of known flaws must show that the component has a service life factor of four and a safety factor of 1.5 against fracture.
“Finally, analyses of known flaws must show that the component has a service life factor of four and a safety factor of 1.5 against fracture.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-HDBK-5010
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAFRL Digital Twin: Spiral 1 is a plan to integrate existing state-of-the-art technologies, benchmark current capabilities and identify gaps using components from an existing U.S. Air Force vehicle, specifically the F-15, as a testbed.
“Among these steps is the Air Force Research Laboratory (AFRL) Digital Twin: Spiral 1 17 , a plan to integrate existing state-of-the-art technologies, benchmark current capabilities and identify gaps using components from an existing U.S. Air Force vehicle, specifically, the F-15, as a testbed.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [17]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenComplex missions, particularly those where external support is difficult or impossible, will necessitate complete real-time management of complex materials, structures and systems that will ultimately lead to self-aware vehicles.
“Complex missions, particularly those where external support is difficult or impossible, will necessitate complete real-time management of complex materials, structures and systems that will ultimately lead to”
Quote in the paperNot a substantial claim- Rests on an assumption: The consequences of failure during a long-duration space mission, where the vehicle is far from home, will almost certainly be catastrophic.
Probably not a substantial claim: may not pass S4 (based). May combine two claims.
InterpretationreasoningThe Digital Twin continuously forecasts the health of the vehicle or system, the remaining useful life and the probability of mission success.
“By combining all of this information, the Digital Twin continuously forecasts the health of the vehicle or system, the remaining useful life and the probability of mission success.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenThe vision for the Digital Twin integrates the broad range of technologies with a singular focus.
“Unlike those individual visions, the vision for the Digital Twin integrates the broad range of technologies with a singular focus.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationVerification depends on the ability to perform laboratory tests on a dedicated test structure identical to the flight structure, and loading, boundary conditions, and environment must be representative of flight conditions.
“In all of these cases,”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-STD-5001A
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenIf various best-physics models can be integrated with one another and with on-board sensor suites, they will form a basis for certification of vehicles by simulation and for real-time, continuous, health management of those vehicles during their missions.
“If various best-physics (i.e., the most accurate, physically realistic and robust) models can be integrated with one another and with on-board sensor suites, they will form a basis for certification of vehicles by simulation and for real-time, continuous, health management of those vehicles during their missions.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
InterpretationreasoningAs a result of future vehicle requirements, demands on structural materials will be greatly increased and structural margins will necessarily be decreased.
“As a result, demands on structural materials will be greatly increased and structural margins will necessarily be decreased.”
Quote in the paperSubstantial claim- Rests on an assumption: Future generations of NASA and U.S. Air Force vehicles will require lighter mass while being subjected to higher loads and more extreme service conditions over longer time periods than the present generation.
Probably not a substantial claim: may not pass S4 (based).
Interpretationnone givenAs a virtual instantiation of a flying vehicle, the Digital Twin is expected to be able to experience every event that its flying twin experiences.
“As a virtual instantiation of a flying vehicle, the Digital Twin is expected to be able to experience every event that its flying twin experiences.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.
InterpretationcitationBecause the vehicles needed for future extreme missions are unlikely to be developed using existing material forms, the design and development of new enabling materials is required and is well aligned with the NRC's ICME roadmap.
“Because the vehicles needed for future extreme missions are unlikely to be developed using existing material forms, the design and development of new enabling (e.g., multifunctional, nanostructured, ultra-durable) materials is required and is well aligned with the NRC's ICME roadmap.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [20]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationApplication of continuum fracture mechanics analyses, including NASGRO fatigue crack growth analysis, is the foundation of much of the codified fracture control methodology.
“The application of continuum fracture mechanics analyses, including NASGRO fatigue crack growth analysis (see JSC 22267B 6 ), is the foundation of much of the codified fracture control methodology.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites JSC 22267B
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
InterpretationcitationThe ability to assess the evolution of defects is a critical element within the Digital Twin's on-board IVHM system and is well aligned with the NRC's advocacy for developments in Materials State Awareness.
“The ability to assess the evolution of defects is a critical element within the Digital Twin's on-board IVHM system and is well aligned with the NRC's advocacy for developments in Materials State Awareness.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [21]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe protoflight approach requires a factor-of-safety for yield that is higher than the factor-of-safety used for prototype testing.
“The latter approach requires a factor-of-safety for yield that is higher than the factor-of-safety used for prototype testing.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-STD-5001A
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S4 (based). May combine two claims.
Interpretationnone givenThe Digital Twin can predict system response to safety critical events and uncover previously unknown issues before they become critical by comparing predicted and actual responses.
“The Digital Twin can also predict system response to safety critical events and uncover previously unknown issues before they become critical by comparing predicted and actual responses.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
InterpretationreasoningBecause of its ability to mirror the life of a specific vehicle in an as-built state, the Digital Twin will necessarily revolutionize certification, fleet management and sustainment.
“Because of its ability to mirror the life of a specific vehicle in an as-built state, the Digital Twin will necessarily revolutionize certification, fleet management and sustainment.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationFracture critical hardware requires the additional imposition of damage tolerance requirements.
“Fracture critical hardware requires the additional imposition of damage tolerance requirements (see, for example, NASA-STD-5019 2 ).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-STD-5019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
Interpretationnone givenThe Digital Twin concept is unlikely to attain maturity for many decades, so a series of intermediate steps is required.
“However, such an ambitious concept is unlikely to attain maturity for many decades, so a series of intermediate steps is required.”
Quote in the paperNot a substantial claim- Rests on an assumption: The Digital Twin concept is unlikely to attain maturity for many decades.
May combine two claims.
InterpretationreasoningThe extensive legacy of historical flight information incorporated in standards and handbooks will likely be insufficient to either certify future extreme vehicles or to guarantee mission success.
“Thus, the extensive legacy of historical flight information incorporated in the various standards and handbooks that were based on decades of aircraft and spacecraft design experience, will likely be insufficient to either certify future extreme vehicles or to guarantee mission success.”
Quote in the paperNot a substantial claim- Rests on an assumption: Future generations of vehicles will rely on increasingly complex, heterogeneous and multifunctional material forms with increasingly complex failure modes.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationMinimum design and test factors-of-safety for metallic and composite structures in NASA-STD-5001A vary widely depending on circumstance and can be as large as 2.0 depending on material and local structural configuration.
“These factors vary widely depending on circumstance and can be as large as 2.0 depending on the material and local structural configuration.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-STD-5001A
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationWorst-case limit loads for the mission must be used to compute the far field stress state at the location of the detected crack.
“Additionally, worst-case limit loads for the mission must be used to compute the far field stress state at the location of the detected crack.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-HDBK-5010
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenAn understanding of the exact state of the structure of the vehicle or its systems, including existence of defects at the microstructural and possibly atomistic scale, is required as a baseline for ultra-high fidelity simulations.
“Additionally, an understanding of the exact state of the structure of the vehicle or its systems, including the existence of defects at the microstructural and, possibly, the atomistic scale, is required as a baseline for ultra-high fidelity simulations.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThe Digital Twin will enable mission managers to make knowledgeable decisions regarding the consequences of possible in-flight changes to a vehicle's mission.
“Additionally, it will enable mission managers to make knowledgeable decisions regarding the consequences of possible in-flight changes to a vehicle's mission.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
InterpretationreasoningOnce the vehicle is launched, the Digital Twin will increase the reliability of the flying vehicle because of its ability to continuously monitor and mitigate degradation and anomalous events.
“Once the vehicle is launched, the Digital Twin will increase the reliability of the flying vehicle because of its ability to continuously monitor and mitigate degradation and anomalous events.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationBecause of apparent scatter in material response under cyclic and creep loading, corresponding factors-of-safety are even larger.
“Because of the apparent scatter in material response under cyclic and creep loading, the corresponding factors are even larger.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-STD-5001A
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenMany of the technologies critical for the Digital Twin are currently being developed under related visions for multi-scale and multi-physics modeling, structural health management, high-performance computing and others.
“Many of the technologies critical for the Digital Twin are currently being developed under related visions for multi-scale and multi-physics modeling, structural health management, highperformance computing and others.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
Interpretationnone givenThe systems on board the Digital Twin are capable of mitigating damage or degradation by activating self-healing mechanisms or by recommending changes in mission profile to decrease loadings, thereby increasing both the life span and the probability of mission success.
“Finally, the systems on board the Digital Twin are capable of mitigating damage or degradation by activating self-healing mechanisms or by recommending changes in mission profile to decrease loadings thereby increasing both the life span and the probability of mission success.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenCodified practices tend to be reactive rather than proactive and are often based on heuristic experience, worst-case scenarios and fleet leaders rather than on the specific material, structural configuration and usage of an individual vehicle.
“However, they tend to be reactive rather than proactive and are often based on heuristic experience, worst-case scenarios and fleet leaders rather than on the specific material, structural configuration and usage of an individual vehicle.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe handbook requires analysts to use material properties corresponding to the lower bound of fracture toughness and the upper bound of fatigue crack growth rate.
“The handbook requires analysts to use material properties corresponding to the lower bound of fracture toughness and the upper bound of fatigue crack growth rate (da/dN vs. ΔK) as shown in Figure 2.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-HDBK-5010
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationUpper bounds of fatigue crack growth rate curves are either visually estimated or statistically estimated as being three standard deviations above the mean values.
“Upper bounds of fatigue crack growth rate curves are either visually estimated or statistically estimated as being three standard deviations above the mean values.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-HDBK-5010
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenBy replacing conventional engineering practices with an understanding of the degradation of an individual vehicle or vehicle system, the paradigm of the Digital Twin will impact the way that physical items ranging from micro-devices to civil infrastructure are developed, certified and maintained.
“By replacing conventional engineering practices with an understanding of the degradation of an individual vehicle or vehicle system, the paradigm of the Digital Twin will impact the way that physical items ranging from micro-devices to civil infrastructure are developed, certified and maintained.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationcitationThe Digital Twin paradigm can provide focus to the recent advocacy of the National Science Foundation and the National Research Council in the areas of Simulation Based Engineering Science, Integrated Computational Materials Engineering and Materials State Awareness.
“In addition to its prominence in the recently-published roadmaps of NASA's Office of Chief Technologist (OCT) [15][16] and plans of the Air Force Research Laboratory [17][18] , the Digital Twin paradigm can provide focus to the recent advocacy of the National Science Foundation (NSF) and the National Research Council (NRC) in the areas of Simulation Based Engineering Science (SBES) 19 , Integrated”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [19]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [20]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [21]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S4 (based).
Interpretationnone givenBy exercising ultra-high fidelity approaches on flight hardware, the shortcomings of the existing state-of-the-art in multiscale modeling, in-situ experimentation and material state awareness will be highlighted.
“By exercising such ultra-high fidelity approaches on flight hardware, the shortcomings of the existing state-of-the-art in multiscale modeling, in-situ experimentation and material state awareness will be highlighted.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe crack size assumed for analysis is a combination of NDE-detected crack dimensions and an adjustment based on NDE detection capability.
“Here, the crack size assumed for analysis (2c A ) is a combination of the NDE-detected crack dimensions (2c D ) and an adjustment based on the NDE detection capability (2c N ).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites NASA-HDBK-5010
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenPotential spin-offs from the development of the Digital Twin span the breadth of the Nation's industrial and manufacturing sectors, infrastructure and development of nanotechnology.
“Potential spin-offs from the development of the Digital Twin span the breadth of the Nation's industrial and manufacturing sectors, infrastructure and development of nanotechnology.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
Future generations of NASA and U.S. Air Force vehicles will require lighter mass while being subjected to higher loads and more extreme service conditions over longer time periods than the present generation.
“Future generations of NASA and U.S. Air Force vehicles will require lighter mass while being subjected to higher loads and more extreme service conditions over longer time periods than the present generation.”
The paper relies on this without support.
Future vehicles will have little direct precedent to follow, and in some cases (e.g., long duration space missions) the vehicle may be impossible to inspect and maintain in the conventional sense.
“Unlike the methods used to insure safety and reliability of existing vehicles that have a clear and wellunderstood legacy, many future vehicles will have little direct precedent to follow, and in some cases (e.g., long duration space missions) the vehicle may be impossible to inspect and maintain in the conventional sense.”
The paper relies on this without support.
Future generations of vehicles will rely on increasingly complex, heterogeneous and multifunctional material forms with increasingly complex failure modes.
“Future generations of vehicles will rely on increasingly complex, heterogeneous and multifunctional material forms with increasingly complex failure modes.”
The paper relies on this without support.
The extensive physical testing that provided the confidence needed to assure the success of previous missions has become increasingly expensive to perform.
“Additionally, the extensive physical testing that provided the confidence needed to assure the success of previous missions has become increasingly expensive to perform.”
The paper relies on this without support.
The consequences of failure during a long-duration space mission, where the vehicle is far from home, will almost certainly be catastrophic.
“Moreover, the consequences of failure during a long-duration space mission, where the vehicle is far from home, will almost certainly be catastrophic.”
The paper relies on this without support.
The Digital Twin concept is unlikely to attain maturity for many decades.
“However, such an ambitious concept is unlikely to attain maturity for many decades, so a series of intermediate steps is required.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
DT consists of three parts: the physical product, the virtual product, and the communication platform between them.
“Consequently, DT consists of three parts, which include the physical product, virtual product, and the communication platform between them (Glaessgen & Stargel 2012).”
From A review of digital twin applications in construction (2022) · cites this paper as Glaessgen & Stargel 2012
The Concept section describes a digital simulation that mirrors an as-built vehicle and incorporates sensor data from it, supporting the physical–virtual relationship. It does not describe the Digital Twin as three parts or identify a communication platform as a distinct part (page not available in our copy). (LLM, conf=0.84)
Experimental — accuracy not yet measuredConventional maintenance methods are more reactive than proactive.
“This makes these methods more reactive than proactive [31].”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [31]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Handbook 5010 is identified as both HDBK and STD
MinorThe text cites document 5010 as NASA-HDBK-5010, but reference 10 identifies it as NASA-STD-5010.
“An extreme case of codified conservatism is discussed in NASA-HDBK-5010 10”
“10. Anon., "Fracture Control Implementation Handbook for Payloads, Experiments, and Similar Hardware," NASA-STD-5010, May 2005.”
Cites
Reengineering aircraft structural life prediction using a digital twin
Tuegel, E. J., Ingraffea, A. R., Eason, T. G., & Spottswood, S. M. (2011) · International Journal of Aerospace Engineering · doi:10.1155/2011/154798 · Cited by 1,119 · see citing works
Flagged first, then by citations
Research works printed but not linked: 9
- Anon, 2008, NASA-STD-5019
- Anon, 2008, NASA-STD-6016
- Anon, 2001, Version 3, 0, 22267B
- Anon, Fracture Control Implementation Handbook for Payloads, Experiments, and Similar Hardware,"NASA-STD-5010,May2005
- Anon, 2004, Rules for Construction of Pressure Vessels
- Kobryn P.A., 2011, USAF Air Force Research Laboratory, 88ABW-, 01428
- Anon, 2006, Simulation-Based Engineering Science: Revolutionizing Engineering Science through Simulation
- Anon, 2008, National Research Council, ISBN, 0, 12000
- Anon, 2008, National Research Council,ISBN, 0, 12166
Cited by
Sorted by citations
Digital Twin in Industry: State-of-the-Art
Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2873186 · Cited by 4,391 · see citing works
“, increase of reliability, and timely assessment of mission parameters) [7].”
BackgroundInfluentialDigital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems
Grieves, M., & Vickers, J. (2017) · Transdisciplinary Perspectives on Complex Systems · doi:10.1007/978-3-319-38756-7_4 · Cited by 3,727 · see citing works
Digital Twin in manufacturing: A categorical literature review and classification
Kritzinger, W., Karner, M., Traar, G., Henjes, J., & Sihn, W. (2018) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2018.08.474 · Cited by 3,612 · see citing works
Digital twin: Enabling technologies, challenges and open research
Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020) · IEEE Access · doi:10.1109/access.2020.2998358 · Cited by 2,965 · see citing works
“’’ [10] Definition a) is an ambiguous definition specific for NASA’s interplanetary vehicle development [5] and is one of the early papers that defines Digital Twins.”
BackgroundCharacterising the Digital Twin: A systematic literature review
Jones, D., Snider, C., Nassehi, A., Yon, J., & Hicks, B. (2020) · CIRP Journal of Manufacturing Science and Technology · doi:10.1016/j.cirpj.2020.02.002 · Cited by 2,422 · see citing works
Review of digital twin about concepts, technologies, and industrial applications
Liu, M., Fang, S., Dong, H., & Xu, C. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.06.017 · Cited by 1,965 · see citing works
A Review of the Roles of Digital Twin in CPS-based Production Systems
Negri, E., Fumagalli, L., & Macchi, M. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.07.198 · Cited by 1,669 · see citing works
Enabling technologies and tools for digital twin
Qi, Q., Tao, F., Hu, T., Anwer, N., Liu, A., Wei, Y., Wang, L., & Nee, A. Y. C. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2019.10.001 · Cited by 1,579 · see citing works
Satellite Communications in the New Space Era: A Survey and Future Challenges
Kodheli, O., Lagunas, E., Maturo, N., Sharma, S. K., R., B. S. M., Montoya, J. F. M., Duncán, J. C. M., Spano, D., Chatzinotas, S., Kisseleff, S., et al. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3028247 · Cited by 1,596 · see citing works
“In addition to the aforementioned operations, the digital twin is expected to play a crucial role in integrating historical and fleet data, maintenance history and sensor data from the satellite on-board integrated health management system to enhance the safety and reliability of satellites/space vehicles [342].”
BackgroundA survey on digital twin: definitions, characteristics, applications, and design implications
Barricelli, B. R., Casiraghi, E., & Fogli, D. (2019) · IEEE Access · doi:10.1109/access.2019.2953499 · Cited by 1,480 · see citing works
“Precisely, ten years after Grieves’ definition, NASA researchers, in their roadmap [22], which is now considered by aerospace researchers [23], [24] as the seminal work about DTs, suggested that DT would improve performance in the field of aviation.”
BackgroundTowards a semantic Construction Digital Twin: Directions for future research
Boje, C., Guerriero, A., Kubicki, S., & Rezgui, Y. (2020) · Automation in Construction · doi:10.1016/j.autcon.2020.103179 · Cited by 1,477 · see citing works
Shaping the digital twin for design and production engineering
Schleich, B., Anwer, N., Mathieu, L., & Wartzack, S. (2017) · CIRP Annals · doi:10.1016/j.cirp.2017.04.040 · Cited by 1,305 · see citing works
“in their integrated technology roadmap (Technology Area 11: Modeling, Simulation, Information Technology & Processing Roadmap; 2010), which has been slightly adapted in [10]: “A Digital Twin is an integrated multiphysics, multiscale, probabilistic simulation of an as-built vehicle or system that uses the best availabl…”
MethodLeveraging Digital Twin Technology in Model-Based Systems Engineering
Madni, A. M., Madni, C. C., & Lucero, S. D. (2019) · Systems · doi:10.3390/systems7010007 · Cited by 1,050 · see citing works
“Finally, the systems on board the digital twin are capable of mitigating damage or degradation by activating self-healing mechanisms, or by recommending changes in mission profile to decrease loads, thereby increasing both the life span and the probability of mission success [9].”
BackgroundInfluentialDigital twin: origin to future
Singh, M., Fuenmayor, E., Hinchy, E., Qiao, Y., Murray, N., & Devine, D. (2021) · Applied System Innovation · doi:10.3390/asi4020036 · Cited by 1,038 · see citing works
“…literature have referred to DT as a virtual or digital model [21,23,27–35], layout [36], counterpart [7,9,35,37], doppelganger [38], clone [39], footprint [40], software analogue [41], representation [42–46], information constructs [2,47], or simulation [20,26,48–51] of its physical counterpart.”
BackgroundInfluentialDigital twin paradigm: A systematic literature review
Semeraro, C., Lezoche, M., Panetto, H., & Dassisti, M. (2021) · Computers in industry (Print) · doi:10.1016/j.compind.2021.103469 · Cited by 852 · see citing works
“The cluster C1 involves the definitions provided by: (Grieves, 2014), (Glaessgen and Stargel, 2012), (Ríos et al., 2015), (G.”
BackgroundInfluentialDigital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models
Minerva, R., Lee, G. M., & Crespi, N. (2020) · Proceedings of the IEEE · doi:10.1109/jproc.2020.2998530 · Cited by 812 · see citing works
“There are ongoing technological trends for creating DTs in several fields: smart cities [138], [196] or specific issues of the cities, like traffic [197], aerospace [187], aircraft fleet management [198], innovative factory [2], [199]–[201], environmental management [202], logistics [203], [204], the future of work or…”
BackgroundMethodA Novel Cloud-Based Framework for the Elderly Healthcare Services Using Digital Twin
Liu, Y., Zhang, L., Yang, Y., Zhou, L., Ren, L., Wang, F., Liu, R., Pang, Z., & Deen, M. J. (2019) · IEEE Access · doi:10.1109/access.2019.2909828 · Cited by 763 · see citing works
“At present, one commonly used definition from NASA [28] is, ‘‘A Digital Twin is an integrated multiphysics, multiscale, probabilistic simulation of an as-built vehicle or system that uses the best available physical models, sensor updates, fleet history, etc., to mirror the life of its corresponding…”
BackgroundMethodDigital twins for health: a scoping review
Katsoulakis, E., Wang, Q., Wu, H., Shahriyari, L., Fletcher, R., Liu, J., Achenie, L. E. K., Liu, H., Jackson, P., Xiao, Y., et al. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01073-0 · Cited by 848 · see citing works
“Around 2010,NASA and John Vickers utilizedthe DT as a virtual model of a physical system 5,6 .”
MethodDigital Twin for maintenance: A literature review
Errandonea, I., Beltrán, S., & Arrizabalaga, S. (2020) · Computers in Industry · doi:10.1016/j.compind.2020.103316 · Cited by 819 · see citing works
Digital twins in smart farming
Verdouw, C., Tekinerdoğan, B., Beulens, A., & Wolfert, S. (2021) · Agricultural Systems · doi:10.1016/j.agsy.2020.103046 · Cited by 634 · see citing works
“Moreover, Digital Twins may consider multiple interdependent objects as well as sub systems at different levels of granularity (Glaessgen and Stargel, 2012; Verdouw et al., 2016b; Grieves and Vickers, 2017).”
BackgroundRathore, M. M., Shah, S. A., Shukla, D., Bentafat, E., & Bakiras, S. (2021) · IEEE Access · doi:10.1109/access.2021.3060863 · Cited by 616 · see citing works
“For instance, Glaessgen and Stargel [18] defined it from the perspective of vehicles as ‘‘A digital twin is an integrated multiphysics, multiscale, probabilistic simulation of an as-built vehicle or system that uses the best available physical models, sensor updates, fleet history, etc., to mirror the life of its corres…”
BackgroundAn application framework of digital twin and its case study
Zheng, Y., Yang, S., & Cheng, H. (2018) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0911-3 · Cited by 534 · see citing works
“…phase, NASA and US Air Force apply the DT technology in vehicles development, so they can predict the future performance and status of vehicles by constructing ultra-high fidelity simulation models with the parameters of material properties and Manufacturing defects (Glaessgen and Stargel 2012).”
BackgroundMethodDigital Twins: State of the art theory and practice, challenges, and open research questions
Sharma, A., Kosasih, E., Zhang, J., Brintrup, A., & Calinescu, A. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2022.100383 · Cited by 587 · see citing works
“[26] discusses application of DT for NASA and U.S. Air Force vehicles.”
MethodSmart Manufacturing and Intelligent Manufacturing: A Comparative Review
Wang, B., Tao, F., Fang, X., Liu, C., Liu, Y., & Freiheit, T. I. (2020) · Engineering · doi:10.1016/j.eng.2020.07.017 · Cited by 571 · see citing works
Developing a Digital Twin at Building and City Levels: Case Study of West Cambridge Campus
Lu, Q., Parlikad, A. K., Woodall, P., Ranasinghe, G. D., Xie, X., Liang, Z., Konstantinou, E., Heaton, J., & Schooling, J. M. (2020) · Journal of Management in Engineering · doi:10.1061/(asce)me.1943-5479.0000763 · Cited by 532 · see citing works
Mechanistic models for additive manufacturing of metallic components
Wei, H., Mukherjee, T., Zhang, W., Zuback, J. S., Knapp, G., De, A., & DebRoy, T. (2020) · Progress in Materials Science · doi:10.1016/j.pmatsci.2020.100703 · Cited by 533 · see citing works
A systematic review of a digital twin city: A new pattern of urban governance toward smart cities
Deng, T., Zhang, K., & Shen, Z. M. (2021) · Journal of Management Science and Engineering · doi:10.1016/j.jmse.2021.03.003 · Cited by 560 · see citing works
Towards the future of smart electric vehicles: Digital twin technology
Bhatti, G., Mohan, H., & Singh, R. R. (2021) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2021.110801 · Cited by 547 · see citing works
Digital Twins: From Personalised Medicine to Precision Public Health
Kamel Boulos, M. N., & Zhang, P. (2021) · Journal of Personalized Medicine · doi:10.3390/jpm11080745 · Cited by 530 · see citing works
“However, the first practical application that gave rise to the present name of this concept came later in 2010, during NASA’s (United States National Aeronautics and Space Administration) attempt to create digital simulations of spacecraft for testing [6].”
BackgroundA hybrid predictive maintenance approach for CNC machine tool driven by Digital Twin
Luo, W., Hu, T., Ye, Y., Zhang, C., & Wei, Y. (2020) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2020.101974 · Cited by 525 · see citing works
A BIM-data mining integrated digital twin framework for advanced project management
Pan, Y., & Zhang, L. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103564 · Cited by 553 · see citing works
A Digital-Twin-Assisted Fault Diagnosis Using Deep Transfer Learning
Xu, Y., Sun, Y., Liu, X., & Zheng, Y. (2019) · IEEE Access · doi:10.1109/access.2018.2890566 · Cited by 517 · see citing works
Digital twin and its implementations in the civil engineering sector
Jiang, F., Ma, L., Broyd, T., & Chen, K. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103838 · Cited by 531 · see citing works
Digital Twin Service towards Smart Manufacturing
Qi, Q., Tao, F., Zuo, Y. N., & Zhao, D. (2018) · Procedia CIRP · doi:10.1016/j.procir.2018.03.103 · Cited by 504 · see citing works
A Digital Twin Approach for Fault Diagnosis in Distributed Photovoltaic Systems
Jain, P., Poon, J., Singh, J. P., Spanos, C. J., Sanders, S. R., & Panda, S. K. (2019) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2019.2911594 · Cited by 464 · see citing works
“of a physical system that analytically computes the measurable characteristic outputs in real time [26].”
BackgroundDing, K., Chan, F. T. S., Zhang, X., Zhou, G., & Zhang, F. (2019) · International Journal of Production Research · doi:10.1080/00207543.2019.1566661 · Cited by 456 · see citing works
“…integrated technology roadmap defined the Digital Twin as ‘an integrated multi-physics, multi-scale simulation of a vehicle or system that uses the best available physical models, sensor updates, fleet history, etc., to mirror the life of its corresponding flying twin’ (Glaessgen and Stargel 2012).”
A comprehensive review of digital twin — part 1: modeling and twinning enabling technologies
Thelen, A., Zhang, X., Fink, O., Lu, Y., Ghosh, S., Youn, B. D., Todd, M. D., Mahadevan, S., Hu, C. K., & Hu, Z. Y. (2022) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-022-03425-4 · Cited by 471 · see citing works
“Amongst the many definitions of digital twin, the one specified in Glaessgen and Stargel (2012) is considered one of the most broadly accepted definitions, even though the definition may vary from application to application.”
BackgroundMethodInfluentialLee, D., Lee, S. H., Masoud, N., Krishnan, M. S., & Li, V. C. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103688 · Cited by 454 · see citing works
“The digital twin was first proposed in the product lifecycle management field [12] and studied in the aircraft and aerospace fields as a mirroring model for simulating an as-built vehicle, system, or process [13,14].”
BackgroundModel‐based systems engineering: Motivation, current status, and research opportunities
Madni, A. M., & Sievers, M. (2018) · Systems Engineering · doi:10.1002/sys.21438 · Cited by 424 · see citing works
Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing
Zhou, G., Zhang, C., Li, Z., Ding, K., & Wang, C. (2019) · International Journal of Production Research · doi:10.1080/00207543.2019.1607978 · Cited by 433 · see citing works
“The general acceptable definition of digital twin was developed by NASA (Glaessgen and Stargel 2012): an integrated multi-physics, multiscale, probabilistic simulation of an as-built product, system or process which can mirror the life of its corresponding twin using available physical models,…”
MethodDevelopment of metaverse for intelligent healthcare
Wang, G., Badal, A., Jia, X., Maltz, J. S., Mueller, K. D., Myers, K. J., Niu, C., Vannier, M. W., Yan, P., Yu, Z., et al. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00549-6 · Cited by 430 · see citing works
A survey on AI-driven digital twins in Industry 4.0: smart manufacturing and advanced robotics
Huang, Z., Shen, Y., Li, J., Fey, M., & Brecher, C. (2021) · Sensors · doi:10.3390/s21196340 · Cited by 418 · see citing works
She, C., Sun, C., Gu, Z., Li, Y., Yang, C., Poor, H. V., & Vucetic, B. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2021.3053601 · Cited by 405 · see citing works
“According to the definition in [278], “a digital twin is an integrated multiphysics, multiscale, probabilistic simulation of an as-built vehicle or system that uses the best available physical models, sensor updates, fleet history, and so on to mirror the life of its corresponding real system.””
BackgroundDigital twin in healthcare: Recent updates and challenges
Sun, T., He, X., & Li, Z. (2023) · Digital Health · doi:10.1177/20552076221149651 · Cited by 421 · see citing works
Industrial applications of digital twins
Jiang, Y., Yin, S., Li, K., Luo, H., & Kaynak, O. (2021) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2020.0360 · Cited by 414 · see citing works
“, to mirror the life of its corresponding twin [19].”
BackgroundHolistic Network Virtualization and Pervasive Network Intelligence for 6G
Shen, X., Gao, J., Wu, W. R., Li, M., Zhou, C., & Zhuang, W. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2021.3135829 · Cited by 395 · see citing works
“Air Force Vehicles developed a digital twin paradigm for vehicles to forecast their remaining usable life and the mission success probability [76].”
BackgroundDeep learning in drug discovery: an integrative review and future challenges
Askr, H., Elgeldawi, E., Aboul-Ella, H., Elshaier, Y., Gomaa, M. M., & Hassanien, A. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10306-1 · Cited by 328 · see citing works
“The synthesis of big molecule-based entities in various combinations that has applications in the treatment of inflammatory, microbial, and cancer issues, is the focus of biopharmaceutical manufacturing (Glaessgen and Stargel 2012; Narayanan et al.”
BackgroundDigital Twin for the Oil and Gas Industry: Overview, Research Trends, Opportunities, and Challenges
Wanasinghe, T. R., Wroblewski, L., Petersen, B. K., Gosine, R. G., James, L. A., Silva, O. D., Mann, G. K. I., & Warrian, P. J. (2020) · IEEE Access · doi:10.1109/access.2020.2998723 · Cited by 411 · see citing works
“There is a range of industries, such as manufacturing [9]–[12], automotive [13], [14], healthcare [15]–[20], aviation [21]–[25] and terrestrial exploration [21], [26], where the DT concept has been successfully deployed.”
BackgroundDynamic Bayesian Network for Aircraft Wing Health Monitoring Digital Twin
Li, C., Mahadevan, S., Ling, Y., Choze, S., & Wang, L. (2017) · AIAA Journal · doi:10.2514/1.j055201 · Cited by 382 · see citing works
Gomes, C. Â. G., Thule, C., Broman, D., Larsen, P. G., & Vangheluwe, H. L. (2018) · ACM Computing Surveys · doi:10.1145/3179993 · Cited by 532 · see citing works
Sepasgozar, S. M. E. (2021) · Buildings · doi:10.3390/buildings11040151 · Cited by 381 · see citing works
Applications of Digital Twin across Industries: A Review
Singh, M., Srivastava, R., Fuenmayor, E. A., Kuts, V., Qiao, Y., Murray, N., & Devine, D. M. (2022) · Applied Sciences · doi:10.3390/app12115727 · Cited by 376 · see citing works
“Any damage detected by DT could be resolved by activating in situ repairs or recommending appropriate changes to the mission, resulting in a longer lifespan and a higher success rate of the mission [45].”
On the Integration of Agents and Digital Twins in Healthcare
Croatti, A., Gabellini, M., Montagna, S., & Ricci, A. (2020) · Journal of Medical Systems · doi:10.1007/s10916-020-01623-5 · Cited by 356 · see citing works
“There is not a common agreement on the definition of DTs, especially because the concept has been evolved over the years, since its initial formulation in the aerospace field by the National Aeronautics and Space Administration (NASA) [8, 10].”
BackgroundLiu, X., Jiang, D., Tao, B., Xiang, F., Jiang, G., Sun, Y., Kong, J., & Li, G. (2023) · Advanced Engineering Informatics · doi:10.1016/j.aei.2023.101876 · Cited by 369 · see citing works
The role of data fusion in predictive maintenance using digital twin
Liu, Z., Meyendorf, N., & Mrad, N. (2018) · AIP conference proceedings · doi:10.1063/1.5031520 · Cited by 364 · see citing works
Digital twin for CNC machine tool: modeling and using strategy
Luo, W., Hu, T., Zhang, C., & Wei, Y. (2019) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0946-5 · Cited by 350 · see citing works
“In recent years, with the requirement of smart manufacturing mode, developed from CPS concept, the appearance of digital twin (DT) (Grieves and Vickers 2017; Glaessgen and Stargel 2012) technology provides an effective resolution to integrate the physical world and the information world.”
BackgroundA probabilistic graphical model foundation for enabling predictive digital twins at scale
Kapteyn, M. G., Pretorius, J. V. R., & Willcox, K. E. (2021) · Nature Computational Science · doi:10.1038/s43588-021-00069-0 · Cited by 363 · see citing works
Laaki, H., Miché, Y., & Tammi, K. (2019) · IEEE Access · doi:10.1109/access.2019.2897018 · Cited by 273 · see citing works
“It includes physical products, digital products and the connectivity in between, as de(cid:28)ned in e.g. [4].”
BackgroundWagg, D. J., Worden, K., Barthorpe, R., & Gardner, P. (2020) · ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg · doi:10.1115/1.4046739 · Cited by 321 · see citing works
Digital Twin: A Comprehensive Survey of Security Threats
Alcaraz, C., & López, J. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3171465 · Cited by 364 · see citing works
“…or system that uses the best available physical models, sensor updates, fleet history, etc., to mirror the life of its corresponding flying twin ” [7], “ a computerized model of a physical device or system that represents all functional features and links with the working elements ” [3], and “ a…”
BackgroundDesign, Modeling and Implementation of Digital Twins
Segovia, M., & García-Alfaro, J. (2022) · Sensors · doi:10.3390/s22145396 · Cited by 355 · see citing works
“This can be based on, e.g., historical data of the physical model [14,15].”
Shahzad, M., Shafiq, M. T., Douglas, D., & Kassem, M. (2022) · Buildings · doi:10.3390/buildings12020120 · Cited by 356 · see citing works
Mobility Digital Twin: Concept, Architecture, Case Study, and Future Challenges
Wang, Z.-R., Gupta, R., Han, K., Wang, H., Ganlath, A., Ammar, N., & Tiwari, P. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3156028 · Cited by 285 · see citing works
“Along with its rapid development in different domains during the past decade, including aeronautics and space [4], [7], robotics [8], [9], manufacturing [10], [11], and informatics [12], the Digital Twin also has a huge potential in the transportation domain.”
BackgroundZafar, M. H., Langås, E. F., & Sanfilippo, F. (2024) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2024.102769 · Cited by 338 · see citing works
Shim, C.-S., Dang, N.-S., Lon, S., & Jeon, C.-H. (2019) · Structure and Infrastructure Engineering · doi:10.1080/15732479.2019.1620789 · Cited by 312 · see citing works
Recent advances on industrial data-driven energy savings: Digital twins and infrastructures
Teng, S. Y., Touš, M., Leong, W. D., How, B. S., Lam, H. L., & Máša, V. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.110208 · Cited by 315 · see citing works
Perno, M., Hvam, L., & Haug, A. (2021) · Computers in Industry · doi:10.1016/j.compind.2021.103558 · Cited by 328 · see citing works
“The structure of the search strings was derived directly from the RQs to ensure they Glaessgen and Stargel (2012) “An integrated multiphysics, multiscale, probabilistic simulation of an as-built vehicle or system that uses the best available physical models, sensor updates, fleet history, etc., to…”
MethodDigital Twin in Aerospace Industry: A Gentle Introduction
Li, L., Aslam, S., Wileman, A., & Perinpanayagam, S. (2021) · IEEE Access · doi:10.1109/access.2021.3136458 · Cited by 316 · see citing works
Deep Reinforcement Learning for Stochastic Computation Offloading in Digital Twin Networks
Dai, Y., Zhang, K., Maharjan, S., & Zhang, Y. (2020) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.3016320 · Cited by 298 · see citing works
“The concept of digital twin is first proposed in [2] and applied by NASA to comprehensive diagnosis and maintenance of flight systems.”
MethodA Survey on Digital Twin for Industrial Internet of Things: Applications, Technologies and Tools
Xu, H., Wu, J., Pan, Q., Guan, X., & Guizani, M. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3297395 · Cited by 304 · see citing works
From Corrective to Predictive Maintenance—A Review of Maintenance Approaches for the Power Industry
Moleda, M., Małysiak-Mrozek, B., Ding, W.-P., Sunderam, V., & Mrozek, D. (2023) · Italian National Conference on Sensors · doi:10.3390/s23135970 · Cited by 317 · see citing works
A Simulation-Based Architecture for Smart Cyber-Physical Systems
Gabor, T., Belzner, L., Kiermeier, M., Beck, M. T., & Neitz, A. (2016) · 2016 IEEE International Conference on Autonomic Computing (ICAC) · doi:10.1109/icac.2016.29 · Cited by 298 · see citing works
“These ultra-high fidelity simulations are commonly called a digital twin with respect to the system they model [4], [5], [6].”
BackgroundDigital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review
Chen, Y., Yang, O., Sampat, C., Bhalode, P., Ramachnadran, R., & Ierapetritou, M. (2020) · Processes · doi:10.3390/pr8091088 · Cited by 295 · see citing works
“Since the first definition of DT, interpretations from different perspectives have been proposed, with the most popular one given by Glaessegen and Stargel, noting that a DT is an integrated multiphysics, multiscale, probabilistic simulation of a complex product and uses the best available data, sensors, and models to…”
BackgroundMethodInfluentialCombustion machine learning: Principles, progress and prospects
Ihme, M., Chung, W. T., & Mishra, A. (2022) · Progress in Energy and Combustion Science · doi:10.1016/j.pecs.2022.101010 · Cited by 278 · see citing works
Visualisation of the Digital Twin data in manufacturing by using Augmented Reality
Zhu, Z.-X., Liu, C., & Xu, X. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.03.223 · Cited by 241 · see citing works
Trusting artificial intelligence in cybersecurity is a double-edged sword
Taddeo, M., McCutcheon, T., & Floridi, L. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0109-1 · Cited by 260 · see citing works
“be considered a ‘digital twin’ [30] of the deployed system.”
BackgroundDelgado, J. M. D., & Oyedele, L. O. (2021) · Advanced Engineering Informatics · doi:10.1016/j.aei.2021.101332 · Cited by 272 · see citing works
Blockchain for digital twins: recent advances and future research challenges
Yaqoob, I., Salah, K., Uddin, M., Jayaraman, R., Omar, M., & Imran, M. (2020) · IEEE Network · doi:10.1109/mnet.001.1900661 · Cited by 256 · see citing works
“DTs are expected to United States Air Force vehicles because of their striking features [1].”
BackgroundThe Convergence of Digital Twin, IoT, and Machine Learning: Transforming Data into Action
Kaur, M., Mishra, V., & Maheshwari, P. (2019) · Internet of Things · doi:10.1007/978-3-030-18732-3_1 · Cited by 209 · see citing works
Jia, W., Wang, W., & Zhang, Z. (2022) · Advanced Engineering Informatics · doi:10.1016/j.aei.2022.101706 · Cited by 256 · see citing works
“NASA proposed the concept of the digital twin in 2012 [2].”
BackgroundDigital Twin-enabled Collaborative Data Management for Metal Additive Manufacturing Systems
Liu, C., Le Roux, L., Körner, C., Tabaste, O., Lacan, F., & Bigot, S. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.05.010 · Cited by 252 · see citing works
“, to mirror the life of its corresponding twin [50].”
BackgroundAivaliotis, P., Georgoulias, K., Arkouli, Z., & Makris, S. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.03.072 · Cited by 204 · see citing works
Improving process safety: What roles for Digitalization and Industry 4.0?
Lee, J., Cameron, I., & Hassall, M. E. (2019) · Process Safety and Environmental Protection · doi:10.1016/j.psep.2019.10.021 · Cited by 241 · see citing works
Intelligent Maintenance Systems and Predictive Manufacturing
Lee, J., Ni, J., Singh, J., Jiang, B., Azamfar, M., & Feng, J. (2020) · Journal of Manufacturing Science and Engineering · doi:10.1115/1.4047856 · Cited by 263 · see citing works
Data‐driven physics‐based digital twins via a library of component‐based reduced‐order models
Kapteyn, M. G., Knezevic, D. J., Huynh, D. B. P., Tran, M., & Willcox, K. E. (2020) · International Journal for Numerical Methods in Engineering · doi:10.1002/nme.6423 · Cited by 237 · see citing works
“The digital twin paradigm has garnered attention in a range of engineering applications, such as structural health monitoring and aircraft sustainment procedures [1, 2], simulation-based vehicle certification [1, 3], and fleet management [1, 4, 5].”
BackgroundData-driven ship digital twin for estimating the speed loss caused by the marine fouling
Coraddu, A., Oneto, L., Baldi, F., Cipollini, F., Atlar, M., & Savio, S. (2019) · Ocean Engineering · doi:10.1016/j.oceaneng.2019.05.045 · Cited by 239 · see citing works
“In this work a data driven Digital Twin of the ship is built, leveraging on the large amount of information collected from the on-board sensors, and is used for estimating the speed loss due to marine fouling.”
MethodInfluentialA Cyber-Physical Machine Tools Platform using OPC UA and MTConnect
Liu, C., Vengayil, H., Lu, Y.-Q., & Xu, X. (2019) · Journal of manufacturing systems · doi:10.1016/j.jmsy.2019.04.006 · Cited by 209 · see citing works
Scaling digital twins from the artisanal to the industrial
Niederer, S., Sacks, M. S., Girolami, M., & Willcox, K. E. (2021) · Nature Computational Science · doi:10.1038/s43588-021-00072-5 · Cited by 231 · see citing works
“A great deal of attention has focused on digital twins to support structural health monitoring, sustainment and predictive maintenance 14,15 .”
BackgroundA Requirements Driven Digital Twin Framework: Specification and Opportunities
Moyne, J. R., Qamsane, Y., Balta, E. C., Kovalenko, I., Faris, J., Barton, K. L., & Tilbury, D. M. (2020) · IEEE Access · doi:10.1109/access.2020.3000437 · Cited by 230 · see citing works
“These include contributions from NASA and the US Air Force Research Laboratory [20], General Electric (GE) [8], the Industrial Internet Consortium [21], and a number of academic sources [22]–[25].”
BackgroundIs Human Digital Twin possible?
Shengli, W. (2021) · Computer Methods and Programs in Biomedicine Update · doi:10.1016/j.cmpbup.2021.100014 · Cited by 233 · see citing works
Digital twins: An analysis framework and open issues
Boyes, H. A., & Watson, T. (2022) · Computers in Industry · doi:10.1016/j.compind.2022.103763 · Cited by 241 · see citing works
“The concept of simulation as a core element of a digital twin was established by Glaessgen and Stargel (2012).”
Systematic review of digital twin technology and applications
Yao, J.-F., Yang, Y., Wang, X.-C., & Zhang, X.-P. (2023) · Visual Computing for Industry, Biomedicine, and Art · doi:10.1186/s42492-023-00137-4 · Cited by 201 · see citing works
“Reference Year DT definition 1 [9] 2012 DT is a multi‑scale integrated simulation of a physical equipment or system that makes full use of virtual models, real‑time sen‑ sor data, and historical data on the equipment or system to map the entire life cycle of the process 2 [8] 2012 DT models need to…”
BackgroundMethodDigital twin and cloud-side-end collaboration for intelligent battery management system
Wang, Y., Xu, R., Zhou, C., Kang, X., & Chen, Z. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2021.11.006 · Cited by 222 · see citing works
Web-based digital twin modeling and remote control of cyber-physical production systems
Liu, C., Jiang, P., & Jiang, W. (2020) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2020.101956 · Cited by 223 · see citing works
Sleiti, A. K., Kapat, J. S., & Veselý, L. (2022) · Energy Reports · doi:10.1016/j.egyr.2022.02.305 · Cited by 233 · see citing works
Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review
Peladarinos, N., Piromalis, D. D., Cheimaras, V., Tserepas, E., Munteanu, R. A., & Papageorgas, P. G. (2023) · Sensors · doi:10.3390/s23167128 · Cited by 227 · see citing works
“[9], the concept of DTs emerged from NASA’s pioneering work in integrating physical models and simulations [10,11] to analyze intricate systems.”
BackgroundDigital Twin for Supply Chain Coordination in Modular Construction
Lee, D., & Lee, S. H. (2021) · Applied Sciences · doi:10.3390/app11135909 · Cited by 234 · see citing works
“A digital twin consists of three main components: the physical object, the virtual object, and the linkage between them [27].”
BackgroundArmeni, P., Polat, I., Rossi, L. M. D., Diaferia, L., Meregalli, S., & Gatti, A. M. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12081255 · Cited by 219 · see citing works
Real-time machining data application and service based on IMT digital twin
Tong, X., Liu, Q., Pi, S., & Xiao, Y. (2019) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01500-0 · Cited by 192 · see citing works
“A general definition of the digital twin was given by Glaessgen and Stargel (2012): digital twin is an integrated multi-physics, multi-scale, and probabilistic simulation of a complex product and use the best available physical models and sensor updates to mirror the life of its corresponding twin.”
MethodThe concept of digital twin and digital shadow in manufacturing
Bergs, T., Gierlings, S., Auerbach, T., Klink, A., Schraknepper, D., & Augspurger, T. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.02.010 · Cited by 212 · see citing works
- Authors
- Glaessgen, E., & Stargel, D.
- Affiliations
- Langley Research Center (US)
- United States Air Force Office of Scientific Research (US)
- Venue
- 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA
- Published
- 2012-04-23
- OpenAlex
- W2046074714
- Semantic Scholar
- 733d40c04be482d38dbd21f82b81e0fc890b6669
- Cited by
- 2,404
- References
- 1
- Citations by year
- 2026: 214 · 2025: 332 · 2024: 451 · 2023: 381 · 2022: 342 · 2021: 278 · 2020: 211 · 2019: 108 · 2018: 48 · 2017: 13 · 2016: 11 · 2015: 4 · 2014: 6 · 2013: 4
- FWCI
- 11.20
- Type
- conference paper
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- NASA STI Repository (National Aeronautics and Space Administration) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Control and Systems Engineering › Engineering and Test Systems
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Reliability and Maintenance Optimization
- Keywords
- digital twin, integrated vehicle health management, aircraft certification, fleet management, program sustainability, material property variation, maintenance history, safety and reliability
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