Risk-Informed Digital Twin of Buildings and Infrastructures for Sustainable and Resilient Urban Communities
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8, Issue 3
Abstract
The digital twin (DT) is a virtual replica of real-world buildings, processes, structures, people, and systems created and maintained to answer questions about its physical part, the physical twin (PT). In the case of the built environment, the PT is represented by smart buildings and infrastructures. Full synchronization between the DT and the PT will allow for a perpetual learning process and updating between the two twins. In this work, we introduce a novel concept of DT called risk-informed digital twin (RDT). In the DT the model predictions are developed through data-driven tools and algorithms. However, multiple sources of uncertainty during the lifecycle challenge our understanding and ability to effectively model the performance of the modeled systems. The RDT’s importance lies in its integration of the methods and tools of statistics and risk analysis with machine learning. To this aim, the platform incorporates a novel framework of data-driven uncertainty quantification and risk analysis rooted in information theory. At the core of the RDT is a framework of sustainable and resilient based engineering (SRBE), introduced in this work and considered the first step toward the extension of performance-based engineering (PBE) approaches to socioecological-technical systems under uncertainty. A risk-informed multicriteria decision support tool able to incorporate social aspects is also included, and it can be used for sustainable and resilient design in the early stage, or management under uncertainty of smart buildings and infrastructure systems.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The author thanks the following for the interesting and fruitful conversations aimed at the development of shared knowledge: Khalid M. Mosalam (University of California at Berkeley) and all the members of Singapore Berkeley Building Energy Efficiency and Sustainability in the Tropics (SinBerBEST) and Tsinghua-Berkeley Shenzhen Institute (TBSI); Hans Heinimann (ETH-Singapore); Poul Henning Kirkegaard, Lars V. Andersen, and Søren Wandahl (Aarhus University); and Enrico Zio (Politecnico Milano). The author also thanks the anonymous reviewers who provided constructive comments and contributed to significntly improve the quality of the paper.
References
Abdellaoui, M., and J. D. Hey. 2008. Advances in decision making under risk and uncertainty. New York: Springer.
Achillopoulou, D., S. Mitoulis, S. Argyroudis, and Y. Wang. 2020. “Monitoring of transport infrastructure exposed to multiple hazards: A roadmap for building resilience.” Sci. Total Environ. 746 (Dec): 141001. https://doi.org/10.1016/j.scitotenv.2020.141001.
Akbarieh, A., L. B. Jayasinghe, D. Waldmann, and F. N. Teferle. 2020. “Bim-based end-of- lifecycle decision making and digital deconstruction: Literature review.” Sustainability 12 (7): 2670. https://doi.org/10.3390/su12072670.
Alibrandi, U. 2020. Risk and reliability in engineering, lecture notes. Aarhus, Denmark: Aarhus Univ.
Alibrandi, U., L. V. Andersen, and E. Zio. 2021. “Mutual information for global sensitivity analysis and adaptive-learning surrogate modelling.” In Proc., REC2021, Int. Workshop on Reliable Engineering Computing. Reston, VA: ASCE.
Alibrandi, U., and C. G. Koh. 2015. “First order reliability method in presence of random and interval variables.” ASCE-ASME J. Risk Uncertainty Eng. Syst., Part B: Mech. Eng. 1 (4): 041006.
Alibrandi, U., C. Y. Ma, and C. G. Koh. 2016. “The secant hyperplane method (SHM) for structural reliability analysis.” J. Eng. Mech. 142 (3): 04015098. https://doi.org/10.1061/(ASCE)EM.1943-7889.0001024.
Alibrandi, U., and K. M. Mosalam. 2017a. “Equivalent linearization methods for nonlinear stochastic dynamic analysis using linear response surfaces.” J. Eng. Mech. 143 (8): 04017055. https://doi.org/10.1061/(ASCE)EM.1943-7889.0001264.
Alibrandi, U., and K. M. Mosalam. 2017b. “Kernel density maximum entropy with generalized moments for evaluating probability distributions, including tails, from a small sample of data.” Int. J. Numer. Methods Eng. 113 (13): 1904–1928. https://doi.org/10.1002/nme.5725.
Alibrandi, U., and K. M. Mosalam. 2018. “Code-conforming peer performance based earthquake engineering using stochastic dynamic analysis and information theory.” KSCE J. Civ. Eng. 22 (3): 1002–1015. https://doi.org/10.1007/s12205-018-0013-y.
Alibrandi, U., and K. M. Mosalam. 2019a. “Distributions with independent components for uncertainty quantification and structural reliability analysis.” In Proc., 13th Int. Conf. on Applications of Statistics and Probability in Civil Engineering, ICASP13. Seoul: Seoul National Univ.
Alibrandi, U., and K. M. Mosalam. 2019b. “Holistic design platform for sustainable and resilient building design.” In Proc., Int. Conf. on Applications of Statistics and Probability in Civil Engineering, ICASP13. Seoul: Seoul National Univ.
Alibrandi, U., and K. M. Mosalam. 2019c. “Information theory for data-driven risk analysis: The informational coefficient of correlation as a measure of dependence.” In Proc., 29th European Safety and Reliability Conf. ESREL 2019. Hannover, Germany: Institute for Risk and Reliability.
Alibrandi, U., and K. M. Mosalam. 2019d. “Lifecycle multi criteria decision analysis using generalized expected utility.” In Vol. 1 of Handbook on sustainable and resilient infrastructure, 770–788. London: Routledge.
Alibrandi, U., and G. Ricciardi. 2008. “Efficient evaluation of the pdf of a random variable through the kernel-density maximum entropy approach.” Int. J. Numer. Methods Eng. 75 (13): 1511–1548. https://doi.org/10.1002/nme.2300.
Argyroudis, S., et al. 2022. “Digital technologies can enhance climate resilience of critical infrastructure.” Clim. Risk Manage. 35: 100387. https://doi.org/10.1016/j.crm.2021.100387.
Argyroudis, S., S. A. Mitoulis, L. Hofer, M. Zanini, E. Tubaldi, and D. M. Frangopol. 2020. “Resilience assessment framework for critical infrastructure in a multi-hazard environment: Case study on transport assets.” Sci. Total Environ. 714 (Apr): 136854. https://doi.org/10.1016/j.scitotenv.2020.136854.
Artzner, P., F. Delbaen, J. M. Eber, and D. Heath. 1999. “Coherent measures of risk.” Math. Financ. 9 (3): 203–228. https://doi.org/10.1111/1467-9965.00068.
ATC (Applied Technology Council). 2012a. Seismic performance assessment of buildings, volume 1—Methodology. FEMA P-58-1. Washington, DC: FEMA.
ATC (Applied Technology Council). 2012b. Seismic performance assessment of buildings, volume 2—Implementation guide. FEMA P-58-1. Washington, DC: FEMA.
ATC (Applied Technology Council). 2012c. Seismic performance assessment of buildings, volume 4—Methodology for assessing environmental impacts. FEMA P-58-1. Washington, DC: FEMA.
Ayyub, B. 2014. “Systems resilience for multihazard environments: Definition, metrics, and valuation for decision making.” Risk Anal. 34 (2): 340–355. https://doi.org/10.1111/risa.12093.
Baker, J., M. Schubert, and M. Faber. 2008. “On the assessment of robustness.” J. Struct. Saf. 30 (3): 253–267. https://doi.org/10.1016/j.strusafe.2006.11.004.
Bakhaty, A. A., S. Govindjee, and K. M. Mosalam. 2014. Theoretical development of hybrid simulation applied to plate structures. Berkeley, CA: Pacific Earthquake Engineering Research Center, Univ. California, Berkeley.
Boakye, J., C. Murphy, and P. Gardoni. 2018. “Resilience and sustainability goals for communities and quantification metrics.” In Handbook on sustainable and resilient infrastructure, 50–69. London: Routledge.
Bocchini, P., D. M. Frangopol, T. Ummenhofer, and T. Zinke. 2014. “Resilience and sustainability of civil infrastructure: Toward a unified approach.” J. Infrastruct. Syst. 20 (2): 04014004. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000177.
Boje, C., A. Guerriero, S. Kubicki, and Y. Rezgui. 2020. “Towards a semantic construction digital twin: Directions for future research.” Autom. Constr. 114 (Jun): 103179. https://doi.org/10.1016/j.autcon.2020.103179.
Brincker, R., and C. Ventura. 2015. Introduction to operational modal analysis. Chichester, UK: Wiley.
Bügler, M., A. Borrmann, G. Ogunmakin, P. A. Vela, and J. Teizer. 2017. “Fusion of photogrammetry and video analysis for productivity assessment of earthwork processes.” Comput.-Aided Civ. Inf. Eng. 32 (2): 107–123. https://doi.org/10.1111/mice.12235.
Chakraborty, S. 2020a. “Simulation free reliability analysis: A physics-informed deep learning based approach.” Preprint, submitted May 4, 2020. http://arxiv.org/abs/2005.01302v1.
Chakraborty, S. 2020b. “Transfer learning based multi-fidelity physics informed deep neural network.” Preprint, submitted May 19, 2020. http://arxiv.org/abs/2005.01302v1.
Chakraborty, S., and S. Adhikari. 2020. “Machine learning based digital twin for dynamical systems with multiple time-scales.” Preprint, submitted May 12, 2020. http://arxiv.org/abs/2005.05862.
Chakraborty, S., S. Adhikari, and R. Ganguli. 2020. “The role of surrogate models in the development of digital twins of dynamic systems.” Appl. Math. Modell. 90: 662–681.
Charef, R., H. Alaka, and S. Emmitt. 2018. “Beyond the third dimension of BIM: A systematic review of literature and assessment of professional views.” J. Build. Eng. 19 (Sep): 242–257. https://doi.org/10.1016/j.jobe.2018.04.028.
Cheng, T., and J. Teizer. 2013. “Real-time resource location data collection and visualization technology for construction safety and activity monitoring applications.” Autom. Constr. 34 (Sep): 3–15. https://doi.org/10.1016/j.autcon.2012.10.017.
Cornell, C. A., and H. Krawinkler. 2000. Progress and challenges in seismic performance assessment. Berkeley, CA: Pacific Earthquake Engineering Research Center, Univ. California, Berkeley.
Der Kiureghian, A. 2022. Structural and system reliability. Cambridge, UK: Cambridge University Press.
Der Kiureghian, A., and P. L. Liu. 1986. “Structural reliability under incomplete probability information.” J. Eng. Mech. 111 (1): 85–104. https://doi.org/10.1061/(ASCE)0733-9399(1986)112:1(85).
DHS (Department of Homeland Security). 2012. “Multi-hazard loss estimation methodology, hazus mh-2.1. Washington, DC: FEMA.
Ditlevsen, O., and H. O. Madsen. 1966. Structural reliability methods. Hoboken, NJ: Wiley.
Drazin, P. L., and S. Govindjee. 2016. Hybrid simulation theory for a classical nonlinear dynamical system. Berkeley, CA: Pacific Earthquake Engineering Research Center, Univ. California, Berkeley.
Drazin, P. L., S. Govindjee, and K. M. Mosalam. 2015. “Hybrid simulation theory for continuous beams.” J. Eng. Mech. 141 (7): 04015005. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000909.
Ellingwood, B. R., H. Cutler, P. Gardoni, W. G. Peacock, J. W. van de Lindt, and N. Wang. 2016. “The Centerville virtual community: A fully integrated decision model of interacting physical and social infrastructure system.” Sustainable Resilient Infrastruct. 1 (3–4): 95–107. https://doi.org/10.1080/23789689.2016.1255000.
Elmqvist, T., E. Andersson, N. Frantzeskaki, T. McPhearson, P. Olsson, O. Gaffney, K. Takeuchi, and C. Folke. 2019. “Sustainability and resilience for transformation in the urban century.” Nat. Sustainability 2 (4): 267–273. https://doi.org/10.1038/s41893-019-0250-1.
Enzer, M., et al. 2019. Roadmap for delivering the information management framework for the built environment. Cambridge, UK: Univ. of Cambridge.
Field, E., T. Jordan, and C. Cornell. 2003. “Pensha: a developing community-modelling environment for seismic hazard analysis.” Seismol. Res. Lett. 74 (4): 406–419. https://doi.org/10.1785/gssrl.74.4.406.
Frangopol, D., and P. Bocchini. 2011. “Resilience as optimization criterion for the bridge rehabilitation of a transportation network subject to earthquake.” In Proc., ASCE Structures Congress 2011, edited by D. Ames, T. Droessler, and M. M. Hoit, 2044–2055. Hannover, Germany: ASCE.
Frantzeskaki, N., et al. 2016. “Elucidating the changing roles of civil society in urban sustainability transitions.” Curr. Opinion Environ. Sustainability 22 (41–50): 63–76.
Fujimura, K., and A. Der Kiureghian. 2007. “Tail-equivalent linearization method for nonlinear random vibration.” Probab. Eng. Mech. 22 (1): 63–76. https://doi.org/10.1016/j.probengmech.2006.08.001.
Fuller, A., Z. Fan, C. Day, and C. Varlow. 2020. “Digital twin: Enabling technologies, challenges and open research.” IEEE Access 8: 108952–108971. https://doi.org/10.1109/ACCESS.2020.2998358.
Gardoni, P., and C. Murphy. 2020. “Society-based design: Promoting societal well-being by designing sustainable and resilient infrastructure.” Sustainable Resilient Infrastruct. 5 (1–2): 4–19. https://doi.org/10.1080/23789689.2018.1448667.
Garre, L., and A. Der Kiureghian. 2010. “Tail-equivalent linearization method in frequency domain and application to marine structures.” Mar. Struct. 23 (3): 322–338.
Grieves, M. 2006. Product lifecycle management: Driving the next generation of lean thinking. New York: McGraw-Hill.
Grieves, M. 2011. Virtually perfect: Driving innovative and lean products through product lifecycle management. Cocoa Beach, FL: Space Coast Press.
Grieves, M., and J. Vickers. 2017. “Digital twin: Mitigating unpredictable undesirable emergent behavior in complex systems.” In Transdisciplinary perspectives on complex systems, edited by F.-J. Kahlen, S. Flumerfelt, and A. Alves, 85–113. New York: Springer.
Guidotti, R., H. Chmielewski, V. Unnikrishnan, P. Gardoni, T. McAlliser, and J. van de Lindt. 2016a. “Modelling the resilience of critical infrastructure: The role of network dependencies.” Sustainable Resilient Infrastruct. 1 (3–4): 153–168. https://doi.org/10.1080/23789689.2016.1254999.
Guidotti, R., P. Gardoni, and Y. Chen. 2016b. “Network reliability analysis with link and nodal weights.” Sustainable Resilient Infrastruct. 1 (3–4): 153–168. https://doi.org/10.1080/23789689.2016.1254999.
Gunay, M. S., and K. M. Mosalam. 2013. “Peer performance-based earthquake engineering methodology, revisited.” J. Earthquake Eng. 17 (6): 829–858.
Horman, M., and R. Kenley. 2005. “Quantifying levels of wasted time in construction with metaanalysis.” J. Constr. Eng. Manage. 131 (1): 52–61. https://doi.org/10.1061/(ASCE)0733-9364(2005)131:1(52).
Jensen, F. V., and T. D. Nielsen. 2007. Bayesian networks and decision graphs. 2nd ed. New York: Springer.
Kaewunruen, S., S. Peng, and O. Phil-Ebosie. 2020. “Digital twin aided sustainability and vulnerability audit for subway stations.” Sustainability 12 (19): 7873. https://doi.org/10.3390/su12197873.
Kahneman, D., and A. Tversky. 1979. “Prospect theory: an analysis of decision under risk.” Econometrica 47 (2): 263–292. https://doi.org/10.2307/1914185.
Kan, C., and C. Anumba. 2019. “Digital twins as the next phase of cyber-physical systems in construction.” In Proc., ASCE Int. Conf. on Computing in Civil Engineering. Reston, VA: ASCE.
Keeney, R., and H. Raiffa. 1993. Decisions with multiple objectives—Preferences and value tradeoffs. Cambridge, UK: Cambridge University Press.
Koduru, S., and T. Haukaas. 2010. “Feasibility of form in finite element reliability analysis.” Struct. Saf. 32 (2): 145–153. https://doi.org/10.1016/j.strusafe.2009.10.001.
Konstantakopoulos, I. C., U. Alibrandi, K. M. Mosalam, and C. J. Spanos. 2018a. “Hierarchical decision making by leveraging utility theory and game theoretic analysis towards sustainability in building design operation.” In Proc., 6th Int. Symp. on Reliability Engineering and Risk Management (ISRERM18), Singapore.
Konstantakopoulos, I. C., L. J. Ratliff, M. Jin, S. S. Sastry, and C. J. Spanos. 2018b. “A Robust utility learning framework via inverse optimization.” IEEE Trans. Control Syst. Technol. 26 (3): 954–970. https://doi.org/10.1109/TCST.2017.2699163.
Li, C., S. Mahadevan, Y. Ling, S. Choze, and L. Wang. 2017. “Dynamic Bayesian network for aircraft wing health monitoring digital twin.” AIAA 55 (3): 930–941. https://doi.org/10.2514/1.J055201.
Lin, K., Y.-L. Xu, X. Lu, Z. Guan, and J. Li. 2021. “Digital twin-based collapse fragility assessment of a long-span cable-stayed bridge under strong earthquakes.” Autom. Constr. 123 (Mar): 103547. https://doi.org/10.1016/j.autcon.2020.103547.
Liu, P. L., and A. Der Kiureghian. 1986. “Multivariate distribution models with prescribed marginal and covariances.” Probab. Eng. Mech. 1 (2): 105–112. https://doi.org/10.1016/0266-8920(86)90033-0.
Lu, R., and I. Brilakis. 2019. “Digital twinning of existing reinforced concrete bridges from labelled point clusters.” Autom. Constr. 105 (2): 105–112.
Madsen, H. O., S. Krenk, and N. C. Lind. 1986. Methods of structural safety. Englewood Cliffs, NJ: Prentice-Hall.
Mallikarjuna, B., S. Chokalingam, U. Alibrandi, A. Asmone, and S. Manthapuri. 2022. “Towards responsible design of low-carbon buildings: From concept to engineering.” ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng. 8 (2): 02522001. https://doi.org/10.1061/AJRUA6.0001216.
McKenna, F., and G. Fenves. 2001. The openSees command language manual: version 1.2. Berkeley, CA: Univ. of California.
Mosalam, K. M., U. Alibrandi, H. Lee, and J. Armengou. 2018. “Performance based engineering and multi criteria decision analysis for sustainable and resilient building design.” Struct. Saf. 74 (74): 1–13. https://doi.org/10.1016/j.strusafe.2018.03.005.
Muscolino, G., F. Genovese, and A. Sofi. 2022. “Reliability bounds for structural systems subjected to a set of recorded accelerograms leading to imprecise seismic power spectrum.” ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng. 8 (2): 04022009. https://doi.org/10.1061/AJRUA6.0001215.
Nationalbimstandard.org. n.d. “Frequently asked questions about the national bim standard-united states.” Accessed August 6, 2022. https://www.nationalbimstandard.org/.
NIST. 2016. Community resilience planning guide for buildings and infrastructure systems, volume i & ii. Gaithersburg, MD: NIST.
OSISOFT. 2021. “The data management platform.” Accessed August 6, 2022. https://www.osisoft.com/.
PEER. 2011. “Peer nga ground motion database.” Accessed May 1, 2022. https://ngawest2.berkeley.edu/.
Pereira, L. M., E. Bennet, R. Biggs, G. Pterson, T. McPhearson, A. Norstrom, P. Olsson, R. Presier, C. Raudsepp-Hearne, and J. Vervoort. 2018. “Seeds of the future in the present. Exploring pathways for navigating towards ’good’ anthropocenes.” In Urban Planet: Knowledge Towards Sustainable Cities, edited by T. E. A. Elmqvist, 327–350. Cambridge, UK: Cambridge University Press.
Perrow, C. 1984. Normal accidents: Living with high-risk technologies. New York: Basic Books.
Raissi, M., P. Perdikaris, and G. E. Karniadakis. 2019. “Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.” J. Comput. Phys. 378 (Feb): 686–707. https://doi.org/10.1016/j.jcp.2018.10.045.
Rasmussen, C. E., and C. K. I. Williams. 2006. Gaussian processes for machine learning. London: MIT Press.
Rickles, D., P. Hawe, and A. Shiell. 2007. “A simple guide to chaos and complexity.” J. Epidemiol. Commun. Health 61 (11): 933–937. https://doi.org/10.1136/jech.2006.054254.
Rizzuto, E. 2011. “Glossary.” In Theoretical framework on structural robustness: COSTActionTU0601, robustness of structures, edited by J. Sørensen. Brussels, Belgium: European Cooperation in Science and Technology.
Roberts, J., and P. D. Spanos. 1990. Random vibration and statistical linearization. Chichester, UK: Wiley.
Rockafellar, R. 2007. “Coherent approaches to risk in optimization under uncertainty.” INFORMS Tutorials Oper. Res. 38–61.
Rosen, R., G. Wichert, G. Lo, and D. Bettenhausen. 2015. “About the importance of autonomy and digital twins for the future of manufacturing.” IFAC-PapersOnLine 48 (3): 567–572. https://doi.org/10.1016/j.ifacol.2015.06.141.
Sacks, R., I. Brilakis, E. Pikas, H. Xie, and M. Girolami. 2020. “Construction with digital twin information systems.” Data-Centric Eng. 1.
Sacks, R., C. Eastman, G. Lee, and P. Teicholz. 2018. BIM Handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors. 3rd ed. Hoboken, NJ: Wiley.
Shafto, M., M. Conroy, R. Doyle, E. Glaessgen, C. Kemp, J. LeMoigne, and L. Wang. 2010. Modelling, simulation, information technology and processing roadmap. Technologyarea 11. Washington, DC: National Aeronautics and Space Administration.
Sharma, N., A. Tabandeh, and P. Gardoni. 2017. “Resilience analysis: A mathematical formulation to model resilience of engineering systems.” Sustainable Resilient Infrastruct. 3 (2): 1–19. https://doi.org/10.1080/23789689.2017.1345257.
Sofi, A., G. Muscolino, and F. Giunta. 2020. “A sensitivity-based approach for reliability analysis of randomly excited structures with interval axial stiffness.” ASCE-ASME J. Risk Uncertainty Eng. Syst., Part B: Mech. Eng. 6 (4): 1–10.
Sørensen, J. 2011. “Implementation of structural robustness.” In Theoretical framework on structural robustness: COSTActionTU0601, robustness of structures, edited by J. Sørensen. Brussels, Belgium: European Cooperation in Science and Technology.
Takanahashi, K., and M. Nakashima. 1987. “Japanese activities on on-line testing.” J. Eng. Mech. 113 (7): 1014–1032. https://doi.org/10.1061/%28ASCE%290733-9399%281987%29113%3A7%281014%29.
Takewaki, I. 2007. Critical excitation methods in earthquake engineering. Oxford, UK: Butterworth-Heinemann.
Teizer, J., H. Neve, H. Li, S. Wandahl, J. König, B. Ochner, M. König, and J. Lerche. 2020. “Construction resource efficiency improvement by long range wide area network tracking and monitoring.” Autom. Constr. 116 (Aug): 103245. https://doi.org/10.1016/j.autcon.2020.103245.
Tversky, A., and D. Kahneman. 1992. “Advances in prospect theory: Cumulative representation of uncertainty.” J. Risk Uncertainty 5 (4): 297–323. https://doi.org/10.1007/BF00122574.
UNDRR (United Nations Office for Disaster Risk Reduction). 2021. “United nations office for disaster risk reduction.” Accessed December 6, 2021. https://www.undrr.org/.
UN (United Nations). 2021. “Make the sustainable development goals a reality.” Accessed December 6, 2021. https://sdgs.un.org/.
Von Neumann, J., and O. Morgenstern. 1944. Theory of games and economic behavior. Princeton, NJ: Princeton University Press.
Wagg, D. J., K. Worden, R. J. Barthorpe, and P. Gardner. 2020. “Digital twins: State-of-the-art and future directions for modeling and simulation in engineering dynamics applications.” ASCE- ASME J. Risk Uncertainty Eng. Syst., Part B: Mech. Eng. 6 (3): 1–17.
Wang, J., Y. Jing, C. Zhang, and J. Zhao. 2009. “Review on multi-criteria decision analysis aid in sustainable energy decision-making.” Renewable Sustainable Energy Rev. 13 (9): 2263–2278. https://doi.org/10.1016/j.rser.2009.06.021.
Wei, H., I. Shohet, M. Skibniewski, S. Shapira, and X. Yao. 2016. “Assessing the lifecycle sustainability costs and benefits of seismic mitigations designs for buildings.” J. Archit. Eng. 22 (1): 04015011. https://doi.org/10.1061/(ASCE)AE.1943-5568.0000188.
Worden, K., E. Cross, R. J. Barthorpe, D. J. Wagg, and P. Gardner. 2020. “On digital twins, mirrors, and virtualizations: Frameworks for model verification and validation.” ASCE-ASME J. Risk Uncertainty Eng. Syst., Part B: Mech. Eng. 6 (3): 1–9.
Xu, H., and P. Gardoni. 2020. “Multi-level, multi-variate, non-stationary, random field modeling and fragility analysis of engineering systems.” Struct. Saf. 87 (Nov): 101999. https://doi.org/10.1016/j.strusafe.2020.101999.
Yang, D. Y., and D. M. Frangopol. 2018. “Bridging the gap between sustainability and resilience of civil infrastructure using lifetime resilience.” In Vol. 23 of Routledge handbook of sustainable and resilient infrastructure, 419–442. London: Routledge.
Ye, C., L. Butler, B. Calka, M. Iangurazov, Q. Lu, A. Gregory, M. Girolami, and C. Middleton. 2019. “A digital twin of bridges for structural health monitoring.” In Proc., 12th Int. Workshop on Structural Health Monitoring 2019. Stanford, CA: Stanford Univ.
Yu, Q., C. Wang, B. Cetiner, S. Yu, F. McKenna, E. Taciroglu, and K. Law. 2019. “Building information modeling and classification by visual learning at a city scale.” In Proc., 33rd Conf. on Neural Information Processing Systems (NeurIPS 2019). Vancouver, BC, Canada.
Zhang, H., R. Wang, and C. Wang. 2019. “Monitoring and warning for digital twin-driven mountain geological disaster.” In Proc., 2019 IEEE Int. Conf. on Mechatronics and Automation (ICMA), 502–507. New York: IEEE.
Zhang, M. Q., M. Beer, S. T. Quek, and Y. S. Choo. 2010. “Comparison of uncertainty models in reliability analysis of offshore structures under marine corrosion.” Struct. Saf. 32 (6): 425–432. https://doi.org/10.1016/j.strusafe.2010.04.003.
Zhu, M., F. McKenna, and M. Scott. 2018. “Openseespy: Python library for the opensees finite element framework.” SoftwareX 7 (Jan–Jun): 6–11. https://doi.org/10.1016/j.softx.2017.10.009.
Zhu, Y., N. Zabaras, P. S. Koutsorelakis, and P. Perdikaris. 2019. “Physics-constrained deep learning for high-dimensional surrogate modelling and uncertainty quantification without labeled data.” J. Comput. Phys. 394 (Oct): 56–81. https://doi.org/10.1016/j.jcp.2019.05.024.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8 • Issue 3 • September 2022
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© 2022 American Society of Civil Engineers.
History
Received: Jan 29, 2021
Accepted: Feb 8, 2022
Published online: Jun 27, 2022
Published in print: Sep 1, 2022
Discussion open until: Nov 27, 2022
ASCE Technical Topics:
- Buildings
- Business management
- Continuum mechanics
- Decision making
- Decision support systems
- Disaster risk management
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Infrastructure
- Infrastructure resilience
- Motion (dynamics)
- Practice and Profession
- Risk management
- Smart buildings
- Solid mechanics
- Structural engineering
- Structures (by type)
- Sustainable development
- Systems engineering
- Uncertainty principles
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- Yidan Gao, Umberto Alibrandi, Khalid M. Mosalam, Sustainable and Resilient Engineering for Facade Design under Uncertainty in the Tropics, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10.1061/AJRUA6.RUENG-1132, 10, 2, (2024).
- Wuyan Long, Zhikang Bao, Ke Chen, S. Thomas Ng, Ibrahim Yahaya Wuni, Developing an integrative framework for digital twin applications in the building construction industry: A systematic literature review, Advanced Engineering Informatics, 10.1016/j.aei.2023.102346, 59, (102346), (2024).
- Alexander Koutamanis, From Building Information Modelling to Digital Twins: Digital Representation for a Circular Economy, A Circular Built Environment in the Digital Age, 10.1007/978-3-031-39675-5_1, (3-20), (2024).
- Hossein Omrany, Karam M. Al-Obaidi, Amreen Husain, Amirhosein Ghaffarianhoseini, Digital Twins in the Construction Industry: A Comprehensive Review of Current Implementations, Enabling Technologies, and Future Directions, Sustainability, 10.3390/su151410908, 15, 14, (10908), (2023).
- Umberto Alibrandi, Enrico Zio, Khalid M. Mosalam, Quantum Imprecise Bayesian Networks (QIBN) for Modelling Socio-Ecological-Technical Systems under Uncertainty, 2023 7th International Conference on System Reliability and Safety (ICSRS), 10.1109/ICSRS59833.2023.10381339, (43-52), (2023).
- Frank Ato Ghansah, Weisheng Lu, Major opportunities of digital twins for smart buildings: a scientometric and content analysis, Smart and Sustainable Built Environment, 10.1108/SASBE-09-2022-0192, 13, 1, (63-84), (2023).
- Ahmed Farouk Kineber, Atul Kumar Singh, Abdulwahed Fazeli, Saeed Reza Mohandes, Clara Cheung, Mehrdad Arashpour, Obuks Ejohwomu, Tarek Zayed, Modelling the relationship between digital twins implementation barriers and sustainability pillars: Insights from building and construction sector, Sustainable Cities and Society, 10.1016/j.scs.2023.104930, 99, (104930), (2023).
- Tapas Tripura, Aarya Sheetal Desai, Sondipon Adhikari, Souvik Chakraborty, Probabilistic machine learning based predictive and interpretable digital twin for dynamical systems, Computers & Structures, 10.1016/j.compstruc.2023.107008, 281, (107008), (2023).
- Wei Hu, Kendrik Yan Hong Lim, Yiyu Cai, Digital Twin and Industry 4.0 Enablers in Building and Construction: A Survey, Buildings, 10.3390/buildings12112004, 12, 11, (2004), (2022).
- Kaiyang Wang, Fangyu Guo, Towards Sustainable Development through the Perspective of Construction 4.0: Systematic Literature Review and Bibliometric Analysis, Buildings, 10.3390/buildings12101708, 12, 10, (1708), (2022).