Digital Twin Technologies for Turbomachinery in a Life Cycle Perspective: A Review

Xie, Rong; Chen, Muyan; Liu, Weihuang; Jian, Hongfei; Shi, Yufeng

doi:10.3390/su13052495

Cited by 24 publications

(9 citation statements)

References 87 publications

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“…It would be beneficial if these data could be used to inform future designs, particularly at the conceptual design phase where the resources available to evaluate candidate designs are limited, but where the decisions taken have a significant impact on the final product [92,93]. Exploiting these data are the motivating philosophy behind the digital twin approach to design, in which sustainable practices throughout the lifecycle of a product are encouraged [94]. However, using a large heterogeneous dataset of historic data is a challenging task due to both the size of the datasets involved and the varying levels of epistemic uncertainty associated with the collection of the data.…”

Section: Multi-fidelity Methodsmentioning

confidence: 99%

Machine Learning Methods in CFD for Turbomachinery: A Review

Hammond

Pepper

Montomoli

et al. 2022

IJTPP

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Computational Fluid Dynamics is one of the most relied upon tools in the design and analysis of components in turbomachines. From the propulsion fan at the inlet, through the compressor and combustion sections, to the turbines at the outlet, CFD is used to perform fluid flow and heat transfer analyses to help designers extract the highest performance out of each component. In some cases, such as the design point performance of the axial compressor, current methods are capable of delivering good predictive accuracy. However, many areas require improved methods to give reliable predictions in order for the relevant design spaces to be further explored with confidence. This paper illustrates recent developments in CFD for turbomachinery which make use of machine learning techniques to augment prediction accuracy, speed up prediction times, analyse and manage uncertainty and reconcile simulations with available data. Such techniques facilitate faster and more robust searches of the design space, with or without the help of optimization methods, and enable innovative designs which keep pace with the demand for improved efficiency and sustainability as well as parts and asset operation cost reduction.

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Section: Multi-fidelity Methodsmentioning

confidence: 99%

Machine Learning Methods in CFD for Turbomachinery: A Review

Hammond

Pepper

Montomoli

et al. 2022

IJTPP

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“…The concept of digital twin was first proposed by Michael Grieves at the University of Michigan in 2003. In 2010, the National Aeronautics and Space Administration (NASA) introduced the concept of digital twin in the space technology roadmap, intending to use it to implement comprehensive diagnosis and prediction functions for flight systems to ensure continuous and safe operation during their service life [173]. Digital twins have become the new futuristic obsession of the construction sector [174].…”

Section: Digital Twin Developmentmentioning

confidence: 99%

Three decades of statistical pattern recognition paradigm for SHM of bridges

Figueiredo

2022

Structural Health Monitoring

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Bridges play a crucial role in modern societies, regardless of their culture, geographical location, or economic development. The safest, economical, and most resilient bridges are those that are well managed and maintained. In the last three decades, structural health monitoring (SHM) has been a promising tool in management activities of bridges as potentially it permits one to perform condition assessment to reduce uncertainty in the planning and designing of maintenance activities as well as to increase the service performance and safety of operation. The general idea has been the transformation of massive data obtained from monitoring systems and numerical models into meaningful information. To deal with large amounts of data and perform the damage identification automatically, SHM has been cast in the context of the statistical pattern recognition (SPR) paradigm, where machine learning plays an important role. Meanwhile, recent technologies have unveiled alternative sensing opportunities and new perspectives to manage and observe the response of bridges, but it is widely recognized that bridge SHM is not yet fully capable of producing reliable global information on the presence of damage. While there have been multiple review studies published on SHM and vibration-based structural damage detection for wider scopes, there have not been so many reviews on SHM of bridges in the context of the SPR paradigm. Besides, some of those reviews become obsolete quite fast, and they are usually biased towards applications falling outside of bridge engineering. Therefore, the main goal of this article is to summarize the concept of SHM and point out key developments in research and applications of the SPR paradigm observed in bridges in the last three decades, including developments in sensing technology and data analysis, and to identify current and future trends to promote more coordinated and interdisciplinary research in the SHM of bridges.

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“…Water pumps play a key role in the stable operation of IES as an important fluid component [34]. When a water pump fails, it is usually manifested as a decrease in the pump's head.…”

Section: Modeling Of Ies Failurementioning

confidence: 99%

A Robust Operation Method with Advanced Adiabatic Compressed Air Energy Storage for Integrated Energy System under Failure Conditions

et al. 2022

Self Cite

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Integrated energy system (IES) is an important direction for the future development of the energy industry, and the stable operation of the IES can ensure heat and power supply. This study established an integrated system composed of an IES and advanced adiabatic compressed air energy storage (AA-CAES) to guarantee the robust operation of the IES under failure conditions. Firstly, a robust operation method using the AA-CAES is formulated to ensure the stable operation of the IES. The method splits the energy release process of the AA-CAES into two parts: a heat-ensuring part and a power-ensuring part. The heat-ensuring part uses the high-temp tank to maintain the balance of the heat subnet of the IES, and the power-ensuring part uses the air turbine of the first stage to maintain the balance of the power subnet. Moreover, another operation method using a spare gas boiler is formulated to compare the income of the IES with two different methods under failure conditions. The results showed that the AA-CAES could guarantee the balance of heat subnet and power subnet under steady conditions, and the dynamic operation income of the IES with the AA-CAES method was a bit higher than the income of the IES with the spare gas boiler method.

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Digital Twin Technologies for Turbomachinery in a Life Cycle Perspective: A Review

Cited by 24 publications

References 87 publications

Machine Learning Methods in CFD for Turbomachinery: A Review

Machine Learning Methods in CFD for Turbomachinery: A Review

Three decades of statistical pattern recognition paradigm for SHM of bridges

A Robust Operation Method with Advanced Adiabatic Compressed Air Energy Storage for Integrated Energy System under Failure Conditions

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