Primary Research Areas

 

For the motivation and for details of our work in each of these research areas click on the respective panel to expand

 

Natural Hazard Risk Assessment and Mitigation

 

In recent decades increased urbanization and mass migrations towards cities have contributed to population shifts and infrastructure growth in some of the world’s most hazard-prone areas. The inevitable result is  particularly large life and economic loss potential, something that has unfortunately been confirmed far too often by the thousands of lives lost and communities devastated in recent events like Hurricanes Katrina and Ike and earthquakes in Haiti, Chile, New Zealand and Japan. Undoubtedly, modern design procedures are contributing to improved protective systems against such hazards, though with the unintended consequence of a false sense of security that can lead to risk insensitivity. The public often forgets that protective measures are only designed to withstand certain probabilities of occurrence in connection with natural events whose properties never remain static and as such offer limited protection under larger events, e.g., Hurricane Katrina. Furthermore, the high concentration of people and critical infrastructure systems in confined areas means that even smaller events can have significant losses. Unfortunately, accurate assessments of risk in such complex environments are non-trivial to achieve using traditional approaches.

 

Motivated by this realization, the research of the HIPAD laboratory seeks to expand the available simulation-based, probabilistic tools for natural hazard risk assessment/mitigation and to integrate soft-computing approaches with high-performance computing capabilities, to provide a versatile, powerful framework, that, when coupled with a variety of enabling technologies and knowledge diffusion mechanisms, is capable of penetrating technology-adoption-barriers to address the 21st century challenge of enhancing community resilience to natural disasters. The relevant problems currently investigated extend to life-cycle cost estimation and optimization for civil engineering structures, protection of critical isolated building-contents, selection of ground motion models for efficient description of seismic hazard, protection of base-isolated structures against near-field ground motions, real-time estimation of hurricane surge and wave risk.

 

Sustainable Civil Infrastructures

 

Civil Infrastructure is second only to the health care industry in annual expenditures in the United States. Specifically, more than 150,000 bridges in this country are structurally deficient or functionally obsolete. Sadly, over 1500 bridges in similar conditions have failed already since 1966. Without an economically feasible plan for widespread evaluation and prioritization of maintenance efforts, rectifying the current infrastructure crisis remains a daunting task with serious public safety implications. This is compounded by the fact that most states similarly lack the capability for rapid assessment of their infrastructure in the wake of natural disasters (e.g., tornadoes, floods and earthquakes), accidental impacts, or even terrorist activities. One response is the development of an automated, unattended and effective assessment tool for large networks of Civil Infrastructure Systems (CIS) that can remove humans from time- and labor-intensive inspection into more appropriate venues of decision-making and response. The relevant efforts have focused the last decade on hardware development (wireless and innovative sensing technologies) and damage detection algorithms.

 

The research of the HIPAD lab seeks to integrate the advances established in these fields with a rational and consistent framework, rather than ad-hoc evaluation, that can use the vast assimilated data to guide the decisions about optimal infrastructure maintenance while simultaneously incorporating in the analysis the uncertainties included in the assessment and operation of CIS. Towards this goal our efforts focus on integration of Bayessian identification and model updating techniques and simulation tools for uncertainty propagation informed by monitoring data (posterior setting), to provide a robust automated decision support systems for optimal monitoring and maintenance of infrastructure system.

 

Analysis and Design or High-Performance Engineering Systems

 

The knowledge for engineering systems and their environment (representing operational conditions) is never complete. Uncertainties always exist and for an efficient analysis and design need to be explicitly accounted for. For example, this is true for offshore energy conversion devices, such as floating buoys (wave energy conversion) or wind turbines (wind energy conversion). For such applications there is a significant degree of variability for the environmental excitation conditions. This variability impacts both the performance (amount of energy extracted) as well as the reliability (structural integrity and maintenance costs) of offshore energy conversion device and it is crucial that it is explicitly addressed. Only then can one reach intelligent conclusions regarding the viability and comparative worth of the technology as well as make truly optimal design decisions.

 

This is true for many other categories of high-perormance engineering systems. In this setting, the work of HIPAD focuses on development of a comprehensive, versatile frameworks for analysis and design of such systems in presence of modeling uncertainties. The framework is founded on a probabilistic characterization of the relevant model uncertainties and on stochastic simulation concepts for evaluating and optimizing the probabilistic performance. Our work is motivated by the realization that computational and algorithmic advances in Simulation Based Engineering Science are creating new opportunities for detailed analysis and design of complex engineering systems. Leveraging this potential the tools proposed: (i) put no restrictions in the complexity of the numerical models used; (ii) allow for consideration of complex probability description for describing the modeling uncertainties; (iii) facilitate collaborations with researchers with different expertise as well as development of automated assessment tools that can be adopted by non-expert end-users. The relevant problems currently investigated extend to optimization of grids of wave-energy conversion devices or offshore wind turbines, and to protection of tension leg platform against extreme environmental conditions.

 

Empowerement Models for Sustainable, Residential Reconstruction

in Haiti after the 2010 Earthquake

 

Two years after the January 2010 Haiti earthquake, despite the millions of dollars pledged through foreign aid and well-intended efforts of the international community, the sad reality is that the majority of the families displaced due to the earthquake [over 600,000 Haitians] are still waiting in transitory shelters, without a clear roadmap towards safe permanent housing they will be able to call “home”. While many agree that sustainable redevelopment and self-reliance is essential for Haiti, few appreciate how it can be practically achieved, particularly in the domain of urban residential redevelopment. As the poorest Western nation with the highest import taxes and severe deforestation, construction practices cannot rely on the many engineered materials that are required in traditional code-compliant designs used in other seismically active regions and even other parts of the developing world due to the lack of affordable local inventory. The pre-existing lack of education, codification and oversight to regulate the construction processes adds to such challenges.

 

The HIPAD laboratory is committed to provide an affordable, sustainable, safe housing solution for the bottom of the econimic pyramid Haitian families. Dr Taflanidis is an integral member of Engineering2Empower team at the University of Notre Dame, trying to address the problem of substandard residential housing in the developing world. Visit http://Engineering2Empower.org to learn more

 

 

For current funded projects see the Projects tab.

 

 

Research Specializations

 

Click on a specific panel to expand for our most important publications in that topic

 

Stochastic Optimization Algorithms

  1. Taflanidis, A.A (2012). “Stochastic Subset Optimization incorporating moving least squares response surface methodologies for stochastic sampling”. Advances in Engineering Software, 44: 3-14. [Link]
  2. Taflanidis, A.A. and J.L. Beck (2010). “Reliability-based design using two-stage stochastic optimization with a treatment of model prediction errors”. Journal of Engineering Mechanics ASCE, 136 (12): 1460-1473. [Link]
  3. Taflanidis, A.A. and J.L. Beck (2009). “Stochastic subset optimization for reliability optimization and sensitivity analysis in system design”. Computers and Structures, 31 (5-6): 847-857. [Link]
  4. Taflanidis, A.A. and J.L. Beck (2008). “An efficient framework for optimal robust stochastic system design using stochastic simulation”. Computer Methods in Applied Mechanics and Engineering, 198 (1): 88-101. [Link]
  5. Taflanidis, A.A. and J.L. Beck (2008). “Stochastic Subset Optimization for problems with reliability objectives”. Probabilistic Engineering Mechanics, 23 (2-3): 324-338. [Link]

 

Simulation-Based Science for Addressing Modeling Uncertainties

  1. Vetter, C. and A.A. Taflanidis (2012). “Global probabilistic sensitivity analysis for stochastic ground motion modeling in seismic risk assessment”. Soil Dynamics and Earthquake Engineering, 10.1016/j.soildyn.2012.01.004. [Link]
  2. Taflanidis, A.A (2011). “Optimal probabilistic design of seismic-dampers for protection of isolated bridges against near-fault seismic excitations”. Engineering Structures, 33 (12): 3496–3508. [Link]
  3. Taflanidis, A.A., and G. Jia (2011). “A simulation-based framework for risk assessment and probabilistic sensitivity analysis of base-isolated structures”. Earthquake Engineering and Structural Dynamics, 40: 1629–1651. [Link]
  4. Taflanidis, A.A., Loukogeorgaki, E and D.C. Angelides (2011). “Analysis and design of offshore energy conversion devices under modeling uncertainties”. In Proceedings of the OCEANS’11 Conference. September 19-22. Kona, Hawaii. [Link]
  5. Taflanidis, A.A. and J.L. Beck (2009). “Life-cycle cost optimal design of passive dissipative devices”. Structural Safety, 31 (6): 508-522. [Link]
  6. Taflanidis A.A., Angelides D.C. and J.T. Scruggs (2009). “Simulation-based design of mass dampers for response mitigation of tension leg platforms”. Engineering Structures, 87 (4): 318-331. [Link]
  7. Taflanidis, A.A. and J.L. Beck (2008). “An efficient framework for optimal robust stochastic system design using stochastic simulation”. Computer Methods in Applied Mechanics and Engineering, 198 (1): 88-101. [Link]

 

Stochastic Mechanics

  1. Vetter, C. and A.A. Taflanidis (2012). “Global probabilistic sensitivity analysis for stochastic ground motion modeling in seismic risk assessment”. Soil Dynamics and Earthquake Engineering, 10.1016/j.soildyn.2012.01.004. [Link]
  2. Taflanidis, A.A., and S.-H. Cheung (2012). “Stochastic sampling using moving least squares response surface methodologies”. Probabilistic Engineering Mechanics, 28: 216-224. [Link]
  3. Jia G. and A.A. Taflanidis (2011). “Relative entropy estimation through stochastic sampling and stochastic simulation techniques”. In Proceedings of the 2nd International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering. September 6-9. Crete, Greece. [Link]
  4. Taflanidis, A.A., and J.T Scruggs (2010). “Performance measures and optimal design of linear structural systems under stochastic stationary excitation”. Structural Safety, 32(5): 305-315. [Link]
  5. Taflanidis, A.A. (2010). “Reliability-based optimal design of linear dynamical systems under stochastic stationary excitation and model uncertainty”. Engineering Structures, 32 (5): 1446-1458. [Link]
  6. Taflanidis, A.A., Beck, J.L. and D.C. Angelides (2007). “Robust reliability-based design of liquid column mass dampers under earthquake excitation with use of an analytical reliability approximation”. Engineering Structures, 29 (12): 3525-3537. [Link]
  7. Taflanidis, A.A. and J.L. Beck (2006). “Analytical approximation for stationary reliability of certain and uncertain linear dynamic systems with higher dimensional output”. Earthquake Engineering and Structural Dynamics, 35 (10): 1247-1267. [Link]
  8. Taflanidis, A.A., Angelides, D.C. and G.C. Manos (2005). “Optimal design and performance of liquid column mass dampers for rotational vibration control of structures under white noise excitation”. Engineering Structure, 27 (4): 524-534. [Link]

 

Bayessian Identification and Model Updating

  1. Beck, J.L and A.A. Taflanidis (2012). “Prior and posterior robust stochastic predictions for dynamical systems using probability logic”. Journal of Uncertainty Quantification, in press.  
  2. Taflanidis, A.A. and I. Gidaris (2011). “Bayesian updating of bridge deteriorating infrastructures through monitoring data”. In Proceedings of the ASME 2011 International Mechanical Engineering Congress and Exposition. November 11-17. Denver, Colorado.

 

Soft Computing Applications in Probabilistic Mechanics

  1. Taflanidis, A.A., and S.-H. Cheung (2012). “Stochastic sampling using moving least squares response surface methodologies”. Probabilistic Engineering Mechanics, 28: 216-224. [Link]
  2. Taflanidis, A.A (2012). “Stochastic Subset Optimization incorporating moving least squares response surface methodologies for stochastic sampling”. Advances in Engineering Software, 44: 3-14. [Link]
  3. Taflanidis, A.A. (2011). “Application of response surface methodologies for hurricane risk assessment”. In Proceedings of the 2nd International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering. September 6-9. Crete, Greece. [Link]
  4. Jia G. and A.A. Taflanidis (2011). “Relative entropy estimation through stochastic sampling and stochastic simulation techniques”. In Proceedings of the 2nd International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering. September 6-9. Crete, Greece. [Link]

 

Earthquake Engineering

  1. Vetter, C. and A.A. Taflanidis (2012). “Global probabilistic sensitivity analysis for stochastic ground motion modeling in seismic risk assessment”. Soil Dynamics and Earthquake Engineering, 10.1016/j.soildyn.2012.01.004. [Link]
  2. Vetter, C., Gidaris, I., and A.A Taflanidis (2012). “Seismic Hazard Characterization through Stochastic Ground Motion Modeling”. In Proceedings of theASCE 2012 Structures Congress. May 11-17. Chicago, Illinois.
  3. O’Donnell, A.P.,  Kurama, Y.C, Kalkan, E. and A.A. Taflanidis (2012). “Calibration of a Reusable Nonlinear Beam-Column Connection for Use in an Experimental Ground Motion Scaling Study”. In Proceedings of the ASCE 2012 Structures Congress. May 11-17. Chicago, Illinois.
  4. Taflanidis, A.A (2011). “Optimal probabilistic design of seismic-dampers for protection of isolated bridges against near-fault seismic excitations”. Engineering Structures, 33 (12): 3496–3508. [Link]
  5. Taflanidis, A.A., and G. Jia (2011). “A simulation-based framework for risk assessment and probabilistic sensitivity analysis of base-isolated structures”. Earthquake Engineering and Structural Dynamics, 40: 1629–1651. [Link]
  6. Taflanidis, A.A. (2011). “Life-cycle repair cost assessment and sensitivity analysis”. In Proceedings of the 11th International Conference on Applications of Statistics and Probability in Civil Engineering. August 1-4. Zurich, Switzerland.
  7. O’Donnell, A.P., Beltsar, O.A.,  Kurama, Y.C, Kalkan, E. and A.A. Taflanidis (2011). “Evaluation of ground motion scaling methods for analysis of structural systems”.  In Proceedings of the 2011 ASCE Structures Congress. April 14-16. Las Vegas, Nevada. [Link]
  8. Khandelwal, K., Taflanidis, A.A. and R. Kiran (2011). “Robustness of Steel Buildings under Extreme Seismic Events: Study of Building Systems Collapse through Multi-scale Computational Methods”. In Proceedings of the2011 NSF Engineering Research and Innovation Conference. January 4-7. Atlanta, Georgia.
  9. Taflanidis, A.A. and J.L. Beck (2009). “Life-cycle cost optimal design of passive dissipative devices”. Structural Safety, 31 (6): 508-522. [Link]
  10. Taflanidis, A.A., Scruggs J.T. and J.L. Beck (2008). “Probabilistically robust nonlinear design of control systems for base-isolated structures”. Structural control and Health Monitoring, 15 (5): 697-719. [Link]
  11. Taflanidis, A.A., Beck, J.L. and D.C. Angelides (2007). “Robust reliability-based design of liquid column mass dampers under earthquake excitation with use of an analytical reliability approximation”. Engineering Structures, 29 (12): 3525-3537. [Link]
  12. Scruggs, J.T., Taflanidis, A.A. and J.L. Beck (2006). “Reliability-based control optimization for active base isolation systems”. Journal of Structural Control and Health Monitoring, 13 (2-3): 705-723. [Link]

 

Hurricane Risk Assessment

  1. Taflanidis, A.A., Kennedy, A.B, Westerink, J.J, Hope, M., Tanaka, S., Smith, J.  and K.F. Cheung (2011). “Probabilistic hurricane surge risk estimation through high-fidelity numerical simulation and response surface approximations”. In Proceedings of the International Conference on Vulnerability and Risk Analysis and Management/Fifth International Symposium on Uncertainty Modeling and Analysis. April 11-13. Hyattsville, Maryland. [Link]
  2. Smith, J.M, Westerink, J.J, Kennedy, A.B, Taflanidis, A.A. and T.D. Smith (2011). “SWIMS Hawaii hurricane wave, surge, and runup inundation fast forecasting tool”. In Proceedings of the 2011 Solutions to Coastal Disasters Conference. June 26-29, Anchorage, Alaska. [Link]
  3. Taflanidis, A.A. (2011). “Application of response surface methodologies for hurricane risk assessment”. In Proceedings of the 2nd International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering. September 6-9. Crete, Greece. [Link]

 

Bridge Engineering

  1. Taflanidis, A.A (2011). “Optimal probabilistic design of seismic-dampers for protection of isolated bridges against near-fault seismic excitations”. Engineering Structures, 33 (12): 3496–3508. [Link]
  2. Taflanidis, A.A. and I. Gidaris (2011). “Bayesian updating of bridge deteriorating infrastructures through monitoring data”. In Proceedings of the ASME 2011 International Mechanical Engineering Congress and Exposition. November 11-17. Denver, Colorado.

 

Residential Housing in Developing Countries

  1. Kijewski-Correa, T., Taflanidis, A.A, Mix, D., and R. Kavanagh. “Sustainable reconstruction for Léogâne, Haiti after the January 2010 earthquake”. Journal of Leadership and Management in Engineering, ASCE, in press.
  2. Kijewski-Correa, K. and A.A. Taflanidis (2012). “The Haitian housing dilemma: Can sustainability and hazard-resilience be achieved?”. Bulletin of Earthquake Engineering, 10.1007/s10518-011-9330-y. [Link]
  3. Mix, D., Kijewski-Correa, T. and A.A. Taflanidis (2011). “Assessment of Residential Housing in Léogâne, Haiti after the January 2010 Earthquake and Identification of Needs for Rebuilding”. Earthquake Spectra, 27 (S1): S299–S322. [Link]

 

Automated Tools for Knowledge Dissemination

  1. Taflanidis, A.A., Kennedy, A.B, Westerink, J.J, Hope, M., Tanaka, S., Smith, J.  and K.F. Cheung (2011). “A comprehensive approach for online fast hurricane-risk prediction”. In Proceedings of the 11th International Conference on Applications of Statistics and Probability in Civil Engineering. August 1-4. Zurich, Switzerland.
  2. Taflanidis, A.A., Loukogeorgaki, E and D.C. Angelides (2011). “Analysis and design of offshore energy conversion devices under modeling uncertainties”. In Proceedings of the OCEANS’11 Conference. September 19-22. Kona, Hawaii. [Link]
  3. Smith, J.M, Westerink, J.J, Kennedy, A.B, Taflanidis, A.A. and T.D. Smith (2011). “SWIMS Hawaii hurricane wave, surge, and runup inundation fast forecasting tool”. In Proceedings of the 2011 Solutions to Coastal Disasters Conference. June 26-29, Anchorage, Alaska. [Link]

 

Passive and Semi-active structural control

  1. Taflanidis, A.A (2011). “Optimal probabilistic design of seismic-dampers for protection of isolated bridges against near-fault seismic excitations”. Engineering Structures, 33 (12): 3496–3508. [Link]
  2. Taflanidis, A.A., Scruggs, J.T, and J.L. Beck (2010). “Robust stochastic design of linear controlled systems for performance optimization”. Journal of Dynamic Systems Measurement and Control ASME, 132 (5): 051008. [Link]
  3. Taflanidis, A.A., and J.T Scruggs (2010). “Performance measures and optimal design of linear structural systems under stochastic stationary excitation”. Structural Safety, 32(5): 305-315. [Link]
  4. Taflanidis, A.A. (2010). “Reliability-based optimal design of linear dynamical systems under stochastic stationary excitation and model uncertainty”. Engineering Structures, 32 (5): 1446-1458. [Link]
  5. Taflanidis, A.A. and J.L. Beck (2009). “Life-cycle cost optimal design of passive dissipative devices”. Structural Safety, 31 (6): 508-522. [Link]
  6. Taflanidis A.A., Angelides D.C. and J.T. Scruggs (2009). “Simulation-based design of mass dampers for response mitigation of tension leg platforms”. Engineering Structures, 87 (4): 318-331. [Link]
  7. Taflanidis, A.A., Scruggs J.T. and J.L. Beck (2008). “Probabilistically robust nonlinear design of control systems for base-isolated structures”. Structural control and Health Monitoring, 15 (5): 697-719. [Link]
  8. Taflanidis, A.A., Scruggs, J.T. and J.L. Beck (2008). “Reliability-based performance objectives and probabilistic robustness in structural control applications”. Journal of Engineering Mechanics ASCE, 134 (4): 291-301. [Link]
  9. Taflanidis, A.A., Beck, J.L. and D.C. Angelides (2007). “Robust reliability-based design of liquid column mass dampers under earthquake excitation with use of an analytical reliability approximation”. Engineering Structures, 29 (12): 3525-3537. [Link]
  10. Scruggs, J.T., Taflanidis, A.A. and W.D. Iwan (2007). “Nonlinear stochastic controllers for semiactive and regenerative systems with guaranteed quadratic performance bounds. Part II- Output feedback control”. Journal of Structural Control and Health Monitoring, 14 (8): 1121-1137. [Link]
  11. Scruggs, J.T., Taflanidis, A.A. and W.D. Iwan (2007). “Nonlinear stochastic controllers for semiactive and regenerative systems with guaranteed quadratic performance bounds. Part I- State feedback control”. Journal of Structural Control and Health Monitoring, 14 (8):1101-1120. [Link]
  12. Scruggs, J.T., Taflanidis, A.A. and J.L. Beck (2006). “Reliability-based control optimization for active base isolation systems”. Journal of Structural Control and Health Monitoring, 13 (2-3): 705-723. [Link]
  13. Taflanidis, A.A., Angelides, D.C. and G.C. Manos (2005). “Optimal design and performance of liquid column mass dampers for rotational vibration control of structures under white noise excitation”. Engineering Structure, 27 (4): 524-534. [Link]

 

Offshore Energy Extraction Devices (Wind Turbines,

Wave Energy Extraction Devices)

  1. Taflanidis, A.A., Loukogeorgaki, E and D.C. Angelides (2011). “Analysis and design of offshore energy conversion devices under modeling uncertainties”. In Proceedings of the OCEANS’11 Conference. September 19-22. Kona, Hawaii. [Link]
  2. Taflanidis, A.A., Loukogeorgaki, E. and D.C. Angelides (2011). “Risk assessment and sensitivity analysis for offshore wind turbines”. In Proceedings of the 21st International Offshore (Ocean) and Polar Engineering Conference. June 19-24. Maui, Hawaii. [Link]

 

Offshore Structures

  1. Taflanidis A.A., Angelides D.C. and J.T. Scruggs (2009). “Simulation-based design of mass dampers for response mitigation of tension leg platforms”. Engineering Structures, 87 (4): 318-331. [Link]
  2. Taflanidis, A.A., Beck, J.L. and D.C. Angelides (2008). “Robust-to-modeling-uncertainties nonlinear control design for offshore structures”. International Journal of Offshore and Polar Engineering, 18 (2): 91-98. [Link]

 

 

 

 

  hazards  

Natural Hazard Risk Assessment and Mitigation

 

  infrustructure  

Automated Decision Support Systems for Infrastructure Maintenance

 

 

 

uncertainty

Simulation-Based Science for Addressing Modeling Uncertainties in Engineering System Analysis and Design