PUBLICATIONS

JOURNAL PAPERS

[J23] X.Q. Tang, U. Alibrandi, C.G. Koh 2025. Numerical simulation of sediment erosion and transport using Consistent Particle Method, Advances in Water Resources, 205

The Consistent Particle Method (CPM) is extended to simulate sediment erosion and transport
consistency order is ensured and accuracy improved over kernel-based particle methods.
Four numerical examples are presented to validate CPM results

[J22] Jędrzejczyk, K. Firek, J. Rusek & U. Alibrandi 2024. Prediction of damage intensity to masonry residential buildings with convolutional neural network and support vector machine, Scientific Reports, 14, 2024

Damage assessment in mining terrains
Masonry residential buildings
Convolutional Neural Networks
Support Vector Machines (SVM)

[J21] Y. Gao, U. Alibrandi and K.M. Mosalam 2024. Sustainable Resilient Engineering and Multi-Attribute Utility Theory for Optimal Facade Design Under Uncertainty in the Tropics. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

Sustainable Resilient Engineering (SRE) for energy-efficiency building façade design
SRE is used jointly with Multi-Attribute Utility Theory (MAUT)
Risk-averse utility functions are used in MAUT
It is shown that the current facade design from the practictioners is unconservative
Real-world examples show the good performances of the proposed approach

[J20] Rusek, J, Alibrandi, U., Slowik, L. And Chomacki, L. 2023. BNSL GOBNILP algorithm in application to damage intensity prognostic system to RC multistorey residential buildings subjected to negative impacts of the industrial environment of mines, Journal of Building Engineering, 80,

Bayesian Networks (BN) are used to estimate the damage intensity of multifamily prefabricated RC buildings
The buildings are located in the range of impacts of the industrial environment of mines.
The database included structural and material features, quality of maintenance and durability
GOBNILP was used to obtain the optimal topology of the BN network
It is discussed that the BN may be used for diagnosis damage cause and their prediction

[J19] U. Alibrandi, L.V. Andersen & E. Zio 2022. Informational probabilistic sensitivity analysis and active learning surrogate modelling, with applications to structural reliability, Probabilistic Engineering Mechanics

The informational coefficient of correlation is able to overcome the limitations of the linear coefficient of correlation
It is introduced a novel framework of probabilistic sensitivity analysis based on the informational coefficient of correlation
it is shown the correlation with the Value of Information and classical sensitivity analysis
It is introduced a new learning function for active learning based surrogate modelling
The procedure of active learning can be applied to any surrogate, not only Kriging
The methods are applied to benchmark examples, and to case study

[J18] U. Alibrandi 2022. Risk-Informed Digital Twin of Buildings and Infrastructures for Sustainable and Resilient urban communities, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

It is introduced a new concept of societal risk informed digital-twin for the built environment
The improved performances of developed data-driven physics-based surrogate models are shown
The integrated multi-criteria decision making under uncertainty is capable to describe risk aversion and perception of the involved stakeholders
A novel framework of Sustainable and Resilient Based Engineering is proposed
Applications of socio-technical optimal design, smart heath monitoring and management under uncertainty are shown

[J17] B.K. Mallikarjuna, S. Chockalingam, U. Alibrandi, A.S. Asmone, S. Manthapuri 2022. Towards Responsible Design of Low-carbon Buildings: From Concept to Engineering, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

Smart, healthy, green and net-zero energy buildings are discussed and conceptualized inside a unified view
Responsible design-thinking from concept to application in the building industry is proposed
A formulation of Responsible Based Engineering is presented here modelled through cartograms and Bayesian Networks
The framework is shown through a multi-hazard analysis including fire safety and cyber attack

[J16] K.M. Mosalam, U. Alibrandi, H. Lee & J. Armengou 2018. Performance Based Engineering and Multi Criteria Decision Analysis for Sustainable and Resilient Building Design, Structural Safety, 74: 1-13

A novel framework of multi-criteria decision making under uncertainty for sustainable and resilient building design is proposed
The generalized expected utility, using superquantiles for risk-aversion toward extreme events, is introduced
The framework is incorporated inside the PEER performance based approach, here modelled through Bayesian Networks (BN)
The role of FORM and the design point is discussed
The case study shows that a building needs to be resilient, in order to be really sustainable

[J15] U. Alibrandi & K.M. Mosalam 2018. Code-Conforming PEER Performance Based Earthquake Engineering using Stochastic Dynamic Analysis and Information Theory, KSCE Journal of Civil Engineering, 22(3): 1002-1015

A novel framework of response-spectrum code-conforming stochastic seismic analysis is discussed
The performance-based design is applied considering the seismic excitation coherent with the codes, and no ground motions need to be selected
Stochastic dynamic analysis is solved through the information theory, and it requires a very limited number of analyses
The model uncertainty is taken into account
The procedure can be used for optimal design in current engineering practice

[J14] U. Alibrandi & K.M. Mosalam 2017. Kernel Density Maximum Entropy with generalized moments for evaluating probability distributions, including tails, from a small sample of data, International Journal for Numerical Methods in Engineering, 113(13): 1904-28

A novel kernel density approach based on the information theory is proposed
Generalized moments (including power and fractional as specific cases) are included
Uniqueness of the solution, with low computational cost is addressed
Extreme events from samples of small size can be well estimated
Examples of stochastic dynamic analysis and earthquake engineering show the excellent performances of the proposed approach

[J13] U. Alibrandi & K.M Mosalam. 2017. Equivalent Linearization Methods for nonlinear stochastic dynamic analysis using linear response surfaces, Journal of Engineering Mechanics.

Three methods of stochastic equivalent linearizations are presented and discussed
It is introduced for the first time the Gaussian Equivalent Linearization Method (GELM) in the framework of structural reliability
It is shown that the Tail Equivalent Linearization Method (TELM) is a method of critical excitation
It is introduced the Tail Probability Equivalent Linearization Method (TPELM), based on SVM
Selected examples of stochastic dynamic analysis (SDOF and MDOF) show advantages and limitations of the three linearization methods

[J12] U. Alibrandi & C.G. Koh. 2017. Stochastic Dynamic Analysis of Floating Production Systems using the First Order Reliability Method and the Secant Hyperplane Method, Ocean Engineering

Stochastic dynamic analysis of Floating Production System (FPS) is discussed
Fully coupled time-domain analysis between vessel and riser is taken into account
The Tail Equivalent Linearization Method (TELM) is applied for the first time to this problem
The Tail Probability Equivalent Linearization Method (TPELM) is also implemented
A simple numerical application shows advantages and limitations of TELM and TPELM

[J11] U. Alibrandi, Ma C.Y. & C.G. Koh, 2016. The Secant Hyperplane Method (SHM) for structural reliability analysis, Journal of Engineering Mechanics. doi: 10.1061/(ASCE)EM.1943-7889.0001024.

The reliability problem is treated as a classification problem
It is proposed the Secant Hyperplane Method (SHM) as an improvement of the FORM solution, and obtained through linear Support Vector Machine (SVM) with soft margin
SHM provides also information about the achieved accuracy
Low- and very high-dimensional examples, including stochastic dynamic analysis, show the performances of the proposed method
It is shown that SHM solves the main drawbacks of the FORM solution, but keeping the simplicity conceptual and computational

[J10] U. Alibrandi & C.G. Koh, 2015. First Order Reliability Method in presence of random and interval variables, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 1(4). doi:10.1115/1.4030911

A method based on FORM is discussed to solve the problem of reliability with random and interval variables
MCS in presence of random and interval variables is discussed
The proposed approach reduces the hybrid problem to a standard reliability problem with random variables only
The proposed approach requires only three FORM solutions and one interval analysis, reducing the computational cost of several orders of magnitude
Examples of stochastic dynamic analysis and performance based engineering are shown

[J9] U. Alibrandi, A. Alani & C.G. Koh, 2015. Implications of high dimensional spaces for structural reliability analysis and a novel linear response surface based on SVM, International Journal of Computational Methods, 12(4). DOI: 10.1142/S0219876215400162.

The geometry of very high-dimensional spaces is discussed in detail
For the first time in literature, the full implications of high-dimensional geometry for structural reliability analysis are discussed
It is underlined because FORM can give good approximations in very high-dimensional spaces
It is introduced a novel linear response surface based on Support Vector Machine (SVM)
Low- and high-dimensional reliability problems, including stochastic dynamic analysis, are shown

[J8] U. Alibrandi & G. Falsone, 2015. Optimal design of dampers in seismic excited structures by the expected stochastic dissipated power, Probabilistic Engineering Mechanics, 41: 129-138

A method for optimal design of dampers in seismic excited structures is presented
It is based on the Expected value of the stochastic Power Dissipated (EPD)
The optimal damper placement is obtained through a simple optimization problem
A parametric study is applied to SDOF and 2DOF problems
The performances of the method are shown through its implementation to a 10-story building, and considering different soil profiles

[J7] U. Alibrandi, A.M. Alani & G. Ricciardi, 2015. A new second-order SVM-based Response Surface for Structural Reliability Analysis, Probabilistic Engineering Mechanics, 41: 1-12.

A method for structural reliability analysis based on Support Vector Machine (SVM) is presented
A second-order polynomial kernel is adopted, to avoid the evaluation of the hyperparameters
An effective sampling strategy is proposed to be used jointly with SVM
Several examples show the accuracy and effectiveness of the proposed procedure which outperforms the other methods of low-dimensional reliability analysis

[J6] G. Finocchio, O. Casablanca, G. Ricciardi, U. Alibrandi, F. Garesci, M. Chiappini & B. Azzerboni, 2014. Seismic metamaterials based on isochronous mechanical oscillators, Applied Physics Letters, 104, 191903.

It is introduced a Seismic Metamaterial (SM) composed by a chain of mass-in-mass system able to filter the S-waves of an earthquake
The effect of the SM is modelled into soil response analysis
It is shown that the soil amplification function is reduced also in a region near the resonance frequency
It is discussed how SM can be practically realized to an industrial level
A numerical example show the attractive performances of the proposed SM

[J5] U. Alibrandi, 2014. A Response Surface Method for stochastic dynamic analysis, Reliability Engineering and System Safety, 26: 44-53.

A novel response surface methodology for stochastic dynamic analysis is presented
It is based on High-Dimensional Model Representation (HDMR) which can be applied for weakly non-gaussian systems
For strongly non-gaussian systems a procedure based on FORM improves the approximation given by HDMR
The design point in very high-dimensional spaces is determined through a response surface based on the improved Model Correction Factor Method (iMCFM)
Applications to hysteretic SDOF and MDOF are presented

[J4] U. Alibrandi & A. Der Kiureghian, 2012. A Gradient-Free Method for Determining the Design Point in Nonlinear Stochastic Dynamic Analysis, Probabilistic Engineering Mechanics, 28: 2-10.

A gradient-free method is developed for finding the design point in nonlinear stochastic dynamic analysis
The proposed approach is based on the Model Correction Factor Method (MCFM)
The approximation is improved through improved formulation of MCFM
Applications to hysteretic SDOF and MDOF are presented
The computational cost is several order of magnitude lower than the existing literature

[J3] U. Alibrandi, N. Impollonia & G. Ricciardi, 2010. Probabilistic Eigenvalue Buckling Analysis solved through the Ratio of Polynomial Response Surface, Computer Methods in Applied Mechanics and Engineering , 199(9-12): 450-464, 2010

A physics-based response surface approach for reliability buckling analysis is introduced
Geometry of buckling eigenvalue analysis is discussed in detail
It is noted that for very small probabilities perturbation method and FORM may provide poor approximations
Several examples show the performances of the proposed physics-based surrogate models
The accuracy of the response surface is shown for different values of degree of correlations and number of random variables, including random field modelling

[J2] U. Alibrandi & G. Ricciardi, 2008. Efficient evaluation of the pdf of a random variable through the Kernel-Density Maximum Entropy approach, International Journal for Numerical Methods in Engineering, 75(13): 1511-1548, 2008.

A moment-based kernel density approach based on the information theory is proposed
The continuous moment problem is reduced to a discrete moment problem
Convergence analysis and field of validity of the proposed kernel density representation is addressed
The method is benchmarked through analytical examples whose solution is known in closed form
Real-world data examples show the main potentials of the proposed procedure

[J1] U. Alibrandi & G. Ricciardi, 2008. The use of stochastic stresses in the static approach of probabilistic limit analysis , International Journal for Numerical Methods in Engineering, 73(6): 747-782

A novel framework of probabilistic limit analysis is introduced
It is underlined that the probabilistic kinematic approach of limit analysis may provide unsafe bounds
The proposed approach provides tight safe and unsafe bounds to the conditional probability of collapse
Moreover, the proposed static approach is able to determine the exact conditional probability of collapse, which is addressed for the first time in literature
Numerical examples show the accuracy and effectiveness of the proposed approach

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INTERNATIONAL CONFERENCES

[C50] F Genovese, U. Alibrandi and A. Sofi 2024. Sustainable and resilient building design under imprecise ground motion, Landscapes Across the Mediterranean (CrossMED), December 11-13 2024

Sustainable and resilient design under imprecise probability
Seismic ground motion under imprecise information
Sustainable and Resilient Engineering
Recurrent Neural Network for prediction of Energy consumption
Multi-Attribute Utility Theory under imprecise information

[C49] U Alibrandi, C. Perez and K.M. Mosalam 2024. Quantum Physics Stochastic Neural Networks (QPNN), The 8th International Conference on System Reliability and Safety, Sicily, Italy - November 20-22, 2024

Quantum Probability (QP) is introduced
QP is a probability theory under unstructured, uncontrollable uncertain environment
A framework grounded on Dirac-Feynmann rules is introduced
Quantum Physics Stochastic Neural Networks are introduced
Connections with statistical mechanics and Ising machines are underlined

[C48] G. Du, R. Brincker, S.D.R. Amador and U. Alibrandi 2024. OMA-driven structural assessment to prevent fatigue-induced failure in steel bridges, 12th IABMAS International Conference on Bridge Maintenance, Safety and Management, Copenaghen, Denmark – June 24-28, 2024

[C47] U Alibrandi, K.M. Mosalam and E. Zio. Quantum imprecise Bayesian Networks (QIBN) for modelling of socio-ecological-technical systems under uncertainty, The 7th International Conference on System Reliability and Safety, Bologna, Italy - November 22-24, 2023

Quantum Imprecise Bayesian Networks (QI-BN) are introduced
QI-BN may model statistical and model uncertainties
QI-BN is applied to a problem of structural reliability
QI-BN is applied for human decision making
QI-BN is used jointly with digital twin technologies for prognostic health monitoring

[C46] U. Alibrandi, L. He, A. Contento, I K-T Pang, K.M. Mosalam and B. Briseghella, Risk-informed Digital Twin of a butterfly-arch stress-ribbon pedestrian bridge, ARCH23, 10th International Conference on arch bridges Fuzhou, China, October 25-27 2023

The Risk-informed Digital Twin (RDT) provides physics-informed data-driven probabilistic predictions
RDT is grounded on the framework of Sustainable and Resilient Engineering (SRE)
A demonstrator of bridge RDT is discussed
The case study is the butterfly-arch stress-ribbon pedestrian bridge in Fuzhou, Fujian, China
Finite Element Models of the bridge are evaluated through Operational Modal Analyis

[C45] U Alibrandi,A. Ruggieri, S.DR. Amador, R. Brincker and E. Zio. Quantum-inspired Bayesian Networks (QBN) for lifecycle integrity of offshore platforms in the North Sea, Radical Innovation Sprint, RIS 2022, 12 January 2023

It is introduced a novel framework of Quantum-inspired Bayesian Networks (QBN)
The probabilities attached to the QBN are derived through the framework Sustainable and Resilient Based Engineering (SRBE)
QBN are capable to describe human decision making under uncertainty
QBN are are capable to process deep uncertainty
QBN are implemented with Operational Modal Analysis (OMA) for prognostic health monitoring

[C44] U. Alibrandi, E. Zio, K.M. Mosalam. Quantum-like Uncertainty Quantification (QUQ) for urban sustainability and resilience, International Symposium on Reliability Engineering and Risk Management, ISRERM 2022, 4-7 September 2022

It is introduced a novel framework of Quantum-inspired Structural Reliability and Uncertainty Quantification
It is based on quantum probabilities, differing from kolmogovorian probabilities, including interferences in addition to correlation
It is able to outperform the expected utility theory for human decision making under uncertainty
It provides good predictions of socio-ecological-technical systems under deep uncertainty
Some examples show the good performances of the proposed approach

[C43] U. Alibrandi, G. Du, S.D.R Amador, R. Brincker. Utility of Information (UoI) for probabilistic fatigue monitoring, International Symposium on Reliability Engineering and Risk Management, ISRERM 2022, 4-7 September 2022

Probabilistic fatigue monitoring of offshore platform is considered
The parameters of the Paris Law are calibrated through SN curve
Predictions of the crack growth are developed through Operational Modal Analysis
Role of the monitoring is underlined through the Value of Information

[C42] U. Alibrandi, G. Muscolino & A. Sofi. Sustainable and Resilient Building Design under imprecise stochastic ground motion. ICOSSAR 2021-2022,13th International Conference on Structural Safety & Reliability, 20-24 June 2022, Tongji, Shanghai

It is implemented the framework of Sustainable and Resilient Based Engineering (SRBE)
SRBE is an extension of the PEER Performance Based Engineering (PBE)
The ground motion is modelled through imprecise stochastic process
The response is obtained in closed form through novel procedure based on interval analysis

[C41] U. Alibrandi & K.M. Mosalam. OpenAIUQ: a platform for risk-informed digital twins of cities, ICOSSAR 2021-2022,13th International Conference on Structural Safety & Reliability, 20-24 June 2022, Tongji, Shanghai

The first software of uncertainty quantification for risk-informed digital twin is presented
The module of UQ is shown, the algorithms adopt a novel framework of machine learning and information theory
The module of structural FEM (OpenSees) is implemented and coupled with UQ
OpenAIUQ is applied to the Risk-informed Digital Twin of the SinBerBEST building office in Singapore

[C40] G. Pignatta & U. Alibrandi (2021). Risk-informed Digital Twin (RDT) for the decarbonization of the built environment: the Australian residential context, Environ. Sci. Proc. 2021, 3

It is discussed the Risk-informed Digital Twin (RDT)
It is planned the deployment of the RDT to a Building, giving rise to the Risk-informed Digital Building Twin (RDBT)
The RDBT will be deployed to an instrumented building in Sidney
The RDBT will be implemented for decarbonization of the built environment

[C39] U. Alibrandi & E. Zio (2021). Mutual information for global sensitivity analysis and adaptive-learning surrogate modelling, REC2021, International Workshop on Reliable Engineering Computing, 16-20 May, 2021, Taormina, Italy

A new framework of uncertainty quantification based on the information theory and mutual information is discussed
It is discussed the adoption of the informational coefficient of correlation as a measure of dependence
The method is applied for probabilistic sensitivity analysis
Active Kriging Mutual Information (AK-MI) is proposed as an alternative tool of active learning-based surrogate modelling

[C38] U. Alibrandi (2020) Risk-informed Digital Twin of Smart Buildings and Infrastructures, Comes, T. et al., (Eds). Proceedings of the Joint International Resilience Conference 2020, Interconnected: Resilience innovations for Sustainable Development Goals, 4TU Centre for Resilience Engineering / Future Resilience Systems – SEC., 12 May 2020 (online)

The risk-informed digital twin deployed into an office in Singapore is discussed
The potential of the risk-informed digital twin is discussed
Lifecycle sustainability analysis of the office building is presented

[C37] U. Alibrandi & K.M. Mosalam (2020). Information Theory for data-driven Risk Analysis: The informational coefﬁcient of correlation as a measure of dependency, 29th European Safety and Reliability Conference, September 22-26, 2019, Hannover

It is discussed the reinterpretation of structural reliability analysis in view of the information theory
It is questioned the applicability of the classical coefficient of correlation
It is introduced the “Informational coefficient of correlation” based on the information theory
Relationships with copula are discussed
Applications with respect to structural reliability and global sensitivity analysis are also analysed

[C36] C. Luo, X. Li, Y. Zhou, A. Caunhye, U. Alibrandi, N. Aydin, C. Ratti, D. Eckhoff, I. Bojic (2019). Data-driven disruption response planning for a Mass Rapid Transit system, KES International Symposium on Smart Transportation Systems, June 17-19, 2019, Malta

The paper studies the disruption management of a Mass Rapid Transit (MRT) network in Singapore
The data are obtained from the transportation smart cards
Optimization approach minimizes the effects of MRT disruptions
A case study analyses the MRT disruption in the central business district of Singapore
The case study shows that the approach allows to reduce the travel delay of commuters

[C35] U. Alibrandi & K.M. Mosalam. Distribution with Independent Components for Uncertainty Quantification and Structural Reliability Analysis, 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP13, May 26-30, 2019, Seoul, South Korea

The paper shows a reinterpretation of Structural Reliability Analysis in view of information theory and machine learning
It is shown that the optimal probabilistic model may be determined through minimum relative entropy
A novel multivariate probabilistic model, called Distributions with Independent Components (DIC), is proposed
DIC is applied to evaluate the joint distribution of height and period of wave data
The case study shows that DIC outperforms Nataf in accuracy and computational cost.

[C34] U. Alibrandi & K.M. Mosalam. Holistic Design Platform for Sustainable and Resilient Building Design, 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP13, May 26-30, 2019, Seoul, South Korea

The paper introduces the Societal Holistic Design Platform (HDP) under uncertainty for sustainable and resilient building design
The HDP integrates tools of classical Risk Analysis, Stochastic Dynamics, Structural Health Monitoring, multicriteria decision making, AI and IoT
The HDP is deployed in an office building in Singapore
The HDP is a first example worldwide of Cyber-Physical System (CPS) under uncertainty centered around the humans
It represents a first example worldwide of Risk-informed Digital Twin

[C33] U. Alibrandi & K.M. Mosalam. Kernel Density Maximum Entropy for stochastic dynamic analysis of floating production systems, 6th International Symposium on Reliability Engineering and Risk Management, May 31 – Jun 01, 2018. NUS, Singapore.

The paper shows the application of Kernel Density Maximum Entropy (KDMEM) for floating production systems (vessel and risers)
Extreme events are well approximated from only samples
Interval confidences can be also detected through bootstrap
The method is applied to a floating production system modelled through Orcaflex
The case study shows that KDMEM is a valid alternative to the Generalized Extreme Value Distribution

[C32] U. Alibrandi & K.M. Mosalam. The Tail Probability Equivalent Linearization Method for stochastic dynamic analysis of marine structures, 6th International Symposium on Reliability Engineering and Risk Management, May 31 – Jun 01, 2018. NUS, Singapore.

Stochastic dynamic analysis of Floating Production System (FPS) is discussed
Fully coupled time-domain analysis between vessel and riser is taken into account
The Tail Probability Equivalent Linearization Method (TPELM) is discussed
The case study shows the good performances of TPELM to this category of problems

[C31] U. Alibrandi & K.M. Mosalam. Multi criteria lifecycle analyses for sustainable and resilient building design, 6th International Symposium on Reliability Engineering and Risk Management, May 31 – Jun 01, 2018. NUS, Singapore.

[C30] I Konstantakopoulos, U. Alibrandi, K.M. Mosalam & C. Spanos. Hierarchical Decision Making by leveraging utility theory and game theoretic analysis towards sustainability in building design – operation, 6th International Symposium on Reliability Engineering and Risk Management, May 31 – Jun 01, 2018. NUS, Singapore.

The paper shows how to pursue building energy efficiency driven by behavior and preferences of the occupants
It is proposed a framework of “social game under uncertainty”, where game theory is integrated with uncertainty quantification
The utility functions of the users are determined through Machine Learning, using the data of energy consumption of the users
The case study shows that it is possible to address 20% energy savings driven by behavior and preferences of the occupants
The framework allows to design the incentives in order to address the chosen sustainability targets

[C29] U. Alibrandi & K.M. Mosalam. The Tail Probability Equivalent Linearization Method , International Symposium on Sustainability and Resilience of Infrastructure (ISSRI 2016), Taiwan, November 10-13, 2016

The paper introduces the Tail Probability Equivalent Linearization Method (TPELM)
TPELM is compared with Gaussian Equivalent Linearization Method (GELM) and Tail Equivalent Linearization Method (TELM)
A simple non-linear SDOF shows that TPELM outperforms the other existing linearization methods
The application to a RC frame subjected to stochastic excitation shows that TPELM is the only viable solution to approximate extreme events in real-world systems

[C28] U. Alibrandi & K.M. Mosalam. Life cycle optimal design using Performance Based Engineering, Second International Conference on Performance-based and Life-cycle Structural Engineering (PLSE 2015), Brisbane, December 9-11, 2015

Lifecycle optimal building design is presented
The framework implements a multi-criteria decision making under uncertainty, and the Generalized Expected Utility
The evaluation of the lifecycle performances is addressed through the PEER performance based approach, here modelled through Bayesian Networks (BN)

[C27] U. Alibrandi & K.M. Mosalam. Bayesian Networks for Sustainable Building Design, Advanced Building Skins Conference, Berna, Switzerland, November 3-4, 2015

Lifecycle optimal facade design is presented
The framework implements a multi-criteria decision making under uncertainty
The evaluation of the lifecycle performances is addressed through the PEER performance based approach, here modelled through Bayesian Networks (BN)

[C26] U. Alibrandi & K.M. Mosalam. FORM for probabilistic Sustainable Building Design, Symposium on Reliability of Engineering System (SRES 2015), Hangzhou, China, October 15-17, 2015

A novel framework of multi-criteria decision making under uncertainty for sustainable and resilient building design is proposed
The framework is incorporated inside the theory of structural reliability analysis
The role of FORM and the design point is discussed

[C25] U. Alibrandi & K.M. Mosalam. Tail equivalent Linearization Method for Performance Based Earthquake Engineering, Symposium on Reliability of Engineering System (SRES 2015), Hangzhou, China, October 15-17, 2015

The Tail Equivalent Linearization Method (TELM) is applied for PEER Performance Based Earthquake Engineering (PBEE)
Seismic fragility analysis is developed through TELM
The method is applied to a shear-type frame

[C24] U. Alibrandi & K.M. Mosalam. A Decision Support Tool (DST) for sustainable building design, Risk and Reliability Symposium in honor of Prof Armen Der Kiureghian, University of Illinois at Urbana-Champaign, October 4-5, 2015

[C23] U. Alibrandi, S. Muin & K.M. Mosalam. The method of the independent components for sustainable building design, The First IEEE International Conference on Building Energy Efficiency and Sustainable Technologies, SinBerBEST, Singapore, August 31-September 1, 2015

A novel framework of multi-criteria decision making under uncertainty for sustainable building design is proposed
Multi Attribute Utility Theory (MAUT) is adopted
The marginal distributions are evaluated through Kernel Density Maximum Entropy Method (KDMEM)
The joint distribution is evaluated through Independent Component Analysis (ICA)

[C22] U. Alibrandi. Tail Equivalent Linearization Methods for seismic response spectrum analysis, 1st ECCOMAS Thematic Conference on International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2015), 25-27 May 2015, Crete, Greece

Stochastic dynamic analysis is used for seismic analysis
The ground motion is modelled through a PSD compatible with response spectrum given by the codes
The stochastic response is determined through the Tail Equivalent Linearization Method (TELM)

[C21] U. Alibrandi, C.Y. Ma, Y.M. Low & C.G. Koh. Prediction of the response of a SCR using the Multi-Gaussian Maximum Entropy Method, OMAE2015, Proceedings of the ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering, 31 May - 5 June 2015, St. John’s, Newfoundland, Canada

Stochastic dynamic analysis of a Steel Catenary Riser (SCR) is presented
Stochastic response is determined through the Kernel Density Maximum Entropy Method (KDMEM)
Extreme responses are evaluated from a small number of dynamic computations

[C20] U. Alibrandi & C.G. Koh. Stochastic Dynamic Analysis of a marine riser using the First Order Reliability Method, 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12, Vancouver, Canada, July 12-15, 2015

Stochastic dynamic analysis of a marine riser is developed
Wave elevation is modelled through a stochastic Gaussian process
The dynamic response of the riser is evaluated through the First Order Reliability Method (FORM)

[C19] U. Alibrandi & C.G. Koh. The Tail Equivalent Linearization Method for Stochastic Dynamic Analysis of a Marine Riser, 27th KKHTCNN Symposium on Civil Engineering, 10-12 November, 2014, Shanghai, China

Stochastic dynamic analysis of a marine riser is developed
Wave elevation is modelled through a stochastic Gaussian process
The first passage probability of the riser is evaluated through the Tail Equivalent Linearization Method (TELM)

[C18] U. Alibrandi & C.G. Koh. Reliability Seismic Analysis of MDOF systems with hysteretic dampers using the Tail Equivalent Linearization Method, 27th KKHTCNN Symposium on Civil Engineering,10-12 November, 2014, Shanghai, China

Stochastic dynamic analysis of a MDOF system with hysteretic dampers is developed
Earthquake ground motion is modelled through a stochastic Gaussian process
The first passage probability of the responses of the system is evaluated through the Tail Equivalent Linearization Method (TELM)

[C17] U. Alibrandi, C.Y. Ma & C.G. Koh. Prediction of responses of Floating Production Systems using the Multi Gaussian Maximum Entropy Method, Proceeding on the 11th International Conference on Hydrodynamics (ICHD 2014), 19-24 October 2014, Nanyang Technological University, Singapore

Stochastic dynamic analysis of a Floating Production System (FPS) is presented
Stochastic response is determined through the Kernel Density Maximum Entropy Method (KDMEM)
Extreme responses and fatigue analysis are evaluated from a small number of dynamic computations

[C16] U. Alibrandi, C.Y. Ma & C.G. Koh, The improved FORM for Stochastic Dynamic Analysis, Second International Conference on Vulnerability and Risk Analysis and Management (ICVRAM2014) , 13 - 16 July 2014, University of Liverpool, UK

Nonlinear stochastic dynamic analysis is developed
Geometry of very high-dimensional spaces is discussed
It is proposed a linear response surface based on linear SVM, as an improvement of the First Order Reliability Method

[C15] C.Y. Ma, U. Alibrandi & C.G. Koh, Uncertainties in Effective Tension and Bending Moment of a Steel Catenary Riser under Random Wave, Second International Conference on Vulnerability and Risk Analysis and Management (ICVRAM2014) , 13 - 16 July 2014, University of Liverpool, UK

Stochastic dynamic analysis of a Steel Catenary Riser (SCR) is presented
Stochastic response is determined through the Kernel Density Maximum Entropy Method (KDMEM)
Extreme responses of effective tension and bending moment are evaluated from a small number of dynamic computations

[C14] U. Alibrandi & C.G. Koh, FORM and improved FORM for Stochastic Dynamic Analysis, 17th Working Conference of the IFIP working group 7.5 on Reliability and Optimization of Structural Systems (IFIP 2014), 3 - 7 July 2014, Huangshan, China

Nonlinear stochastic dynamic analysis is developed
Geometry of very high-dimensional spaces is discussed
It is proposed a linear response surface based on linear SVM, as an improvement of the First Order Reliability Method

[C13] U. Alibrandi & C.G. Koh, A new method for the analysis of systems with uncertain parameters, 17th Working Conference of the IFIP working group 7.5 on Reliability and Optimization of Structural Systems (IFIP 2014), 3 - 7 July 2014, Huangshan, China

An alternative method of reliability analysis is presented
It is based on the Kernel Density Maximum Entropy Method (KDMEM)
Failure probability is evaluated from a small number of analyses

[C12] C.Y. Ma, U. Alibrandi & C.G. Koh, Reliability Analysis of a Steel Catenary Riser with environmental, geometry and operational uncertainties, OMAE2014, Proceedings of the ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering, 8 - 13 June 2014, San Francisco, California

Stochastic dynamic analysis of a Steel Catenary Riser (SCR) is presented
Environmental, geometry and operational uncertainties are considered
The stochastic response is evaluated through statistical distributions

[C11] U. Alibrandi, C.Y. Ma & C.G. Koh, A Linear Response Surface based on SVM for Structural Reliability Analysis, APCOM & ISCM 2013: 5th Asia Pacific Congress on Computational Mechanics & 4th International Symposium on Computational Mechanics, 11-14th December, 2013, Singapore

A linear response surface based on SVM is presented
Probabilistic and interval uncertain parameters are considered

[C10] U. Alibrandi, C.Y. Ma & C.G. Koh, Stochastic Dynamic Analysis of a Steel Catenary Riser connected to a floating vessel, 26TH KKHTCNN Symposium on Civil Engineering,18-20th November, 2013, Singapore

Nonlinear stochastic dynamic analysis of a Steel Catenary Riser connected to a floating vessel is developed
Wave elevation is modelled through a Gaussian stochastic process
The stochastic response is evaluated through the First Order Reliability Method

[C9] U. Alibrandi, An alternative linear response surface improving FORM solution for stochastic dynamic analysis, 16th Working Conference of the IFIP working group 7.5 on Reliability and Optimization of Structural Systems (IFIP 2012),24-27 June 2012, Yerevan, Armenia

[C8] U. Alibrandi & G. Ricciardi. Structural Reliability Analysis solved through a SVM-based Response Surface, ICASP 2011, The 11th International Conference on applications of Statistics and Probability in Civil Engineering, 1-4 August 2011, Zurich, Switzerland

[C7] U. Alibrandi. A Response Surface Method for nonlinear stochastic dynamic analysis, ICASP 2011, The 11th International Conference on applications of Statistics and Probability in Civil Engineering, 1-4 August 2011, Zurich, Switzerland

[C6] U. Alibrandi & A. Der Kiureghian. The Model Correction Factor Method in NonLinear Stochastic Dynamic Analysis, 6th Computational Stochastic Mechanics Conference, June 13-16, 2010, Rhodos, Greece.

[C5] U. Alibrandi, N. Impollonia & G. Ricciardi. Post-Buckling analysis of frames with uncertain parameters, International Mechanical Engineering Congress and expositions, ASME 2009 , Lake Buena Vista, Florida, November 13-19, 2009

[C4] U. Alibrandi, M. Di Paola, G. Ricciardi. Path Integral Solution solved by the kernel density maximum entropy approach, International Symposium on Recent Advances in Mechanics, Dynamical Systems and Probability Theory, MDP – 2007, Palermo, June 3-6, 2007

[C3] U. Alibrandi, N. Impollonia & G. Ricciardi, A non linear performance function for probabilistic buckling analysis, ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, Rethymno, Crete, Greece, 13–16 June 2007

[C2] U. Alibrandi & G. Ricciardi, Bounds of the probability of collapse of rigid-plastic structures by means of Stochastic Limit Analysis, Proceedings of the 9th International Conference on Structural Safety and Reliability, ICOSSAR'05, Rome, Italy, June 19-23, 2005

[C1] U. Alibrandi , S. Lacquaniti, G. Ricciardi , Non-Gaussian Stochastic Linearization for MDOF systems by a Modified Hermite Series Approach, ASEM ’04, Advances in Structural Engineering and Mechanics, Seoul, Korea, 2-4 September 2004

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