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Dr. Maria Nogal
TU Delft, The Netherlands

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Research Keywords & Expertise

0 Climate Change
0 Critical Infrastructure
0 Reliability
0 Resilience
0 operational research

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Short Biography

I am an Assistant Professor in the Faculty of Civil Engineering and Geosciences in TU Delft. I study the resilience of the built environment, its assessment and management, paying special attention to the impact of climate change upon the interconnected infrastructure systems. I have made significant contributions to the field by providing tools to assess infrastructure systems resilience, and developing managerial frameworks including aspects such as political decisions and socio-economic uncertainties. My participation in international research projects dealing with the resilience of interconnected systems, such as the FP7 RAIN project and the H2020 RESILENS project, has allowed me to develop methods and strategies that can be applied by managers and practitioners in their daily activities and strategic plans to achieve structures and infrastructure systems that are proved to be more resilient. As a result, I have informed policies and decision-makers as shown by my participation in the Committee on the Effect of climate change under the actions to support European policies and standards led by the European Joint Research Centre (JRC), and my participation in the Resource Guide on Resilience edited by the International Risk Governance Council (IRGC). Also, I have presented my work in a number of international events, such as the International Forum on Engineering Decision Making (IFED) and the Advanced Research Workshop on Resilience organised by the North Atlantic Trea

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Software
Published: 12 July 2021
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Mitigation Controller (MitC): an automated risk-mitigation tool for construction projects.

ACS Style

Omar Kammouh; Maurits Kok; Maria Nogal. mitc. 2021, 1 .

AMA Style

Omar Kammouh, Maurits Kok, Maria Nogal. mitc. . 2021; ():1.

Chicago/Turabian Style

Omar Kammouh; Maurits Kok; Maria Nogal. 2021. "mitc." , no. : 1.

Review
Published: 14 June 2021 in Structure and Infrastructure Engineering
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Performance evaluation and maintenance planning are gaining importance with ageing rail infrastructure and increasing demand on track safety and continuous availability. The discrete/point railway assets (e.g. bridges, level crossings) together with extended track sections constitute the main railway network infrastructure. The former has important implications in train safety, riding comfort and operating expenditures due to local intensified degradation and plays a role in effective network capacity due to their large quantity. The heterogeneity in asset features and operating environment also adds difficulties to efficient maintenance planning of multiple discrete assets. The current review screens the issue to level crossings, as little concern has been engaged to this asset type, and draws together different perspectives related to their maintenance management. The systems thinking approach is integrated and two levels of asset management (i.e. micro- and macro-level) are used to structure the synthesis, which are interdependent and synergistic. Two major approaches, namely, the mechanistic and data-driven modelling are synthesised. Both contribute to the maintenance knowledge and their comparisons are elaborated. Limitations in existing studies are identified and directions for future research are provided, aiming to contribute to a more refined ‘inspection and diagnosis’ process to properly capture the local track issues and move towards system-level maintenance approach for multiple level crossings.

ACS Style

Yue Shang; Maria Nogal; Haoyu Wang; A. R. M. (Rogier) Wolfert. Systems thinking approach for improving maintenance management of discrete rail assets: a review and future perspectives. Structure and Infrastructure Engineering 2021, 1 -19.

AMA Style

Yue Shang, Maria Nogal, Haoyu Wang, A. R. M. (Rogier) Wolfert. Systems thinking approach for improving maintenance management of discrete rail assets: a review and future perspectives. Structure and Infrastructure Engineering. 2021; ():1-19.

Chicago/Turabian Style

Yue Shang; Maria Nogal; Haoyu Wang; A. R. M. (Rogier) Wolfert. 2021. "Systems thinking approach for improving maintenance management of discrete rail assets: a review and future perspectives." Structure and Infrastructure Engineering , no. : 1-19.

Journal article
Published: 23 April 2021 in Automation in Construction
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Structural identification using dynamical parameters (such as the natural vibration frequencies and mode shapes) is an important issue, especially in bridges or high-rise buildings. However, incorrect decisions could happen on the Structural Health Monitoring (SHM) strategy and the Structural System Identification (SSI) analysis that makes the sometimes expensive and time-consuming process useless due to the large uncertainty of the resulting estimations. This paper discusses the role of the SHM strategy and the SSI analysis based on the constrained observability method (COM) and decision trees (DT) in reducing the estimation error. Here, the COM uses subsets of natural frequencies and/or modal-shapes to deal with the nonlinearity of the SSI derived from the operational aspects of the methods, and combines the unknown items including frequencies and mode shapes into an optimization process. Next, a decision-support tool based on decision trees is applied to help engineers to establish the best SHM + SSI strategy yielding the most accurate estimations. The principle and steps of this new method, the combination of constrained observability m,ethod and decision trees, are presented for the first time. After that, a numerical model of a bridge case is used to show how to choose the optimal strategy, when factors such as the structure layout, span length, measurement set, and parameters of the COM are included as decision variables. The importance ranking of these four factors is the layout, measurement set, parameters of the COM, and length through the sensitivity analysis of the COM estimated. Last, a real bridge is used to validate this methodology under the undamaged and damaged scenarios by comparing an Error Index, which shows the optimal SHM + SSI strategy works well no matter the bridge is damaged or not. The presented analysis leads to significant insights that can help the decision-making of the optimal SHM + SSI strategy, avoiding erroneous decisions if this tool is not used beforehand.

ACS Style

Tian Peng; Maria Nogal; Joan R. Casas; Jose Turmo. Planning low-error SHM strategy by constrained observability method. Automation in Construction 2021, 127, 103707 .

AMA Style

Tian Peng, Maria Nogal, Joan R. Casas, Jose Turmo. Planning low-error SHM strategy by constrained observability method. Automation in Construction. 2021; 127 ():103707.

Chicago/Turabian Style

Tian Peng; Maria Nogal; Joan R. Casas; Jose Turmo. 2021. "Planning low-error SHM strategy by constrained observability method." Automation in Construction 127, no. : 103707.

Journal article
Published: 21 April 2021 in Sensors
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The inverse problem of structural system identification is prone to ill-conditioning issues; thus, uniqueness and stability cannot be guaranteed. This issue tends to amplify the error propagation of both the epistemic and aleatory uncertainties, where aleatory uncertainty is related to the accuracy and the quality of sensors. The analysis of uncertainty quantification (UQ) is necessary to assess the effect of uncertainties on the estimated parameters. A literature review is conducted in this paper to check the state of existing approaches for efficient UQ in the parameter identification field. It is identified that the proposed dynamic constrained observability method (COM) can make up for some of the shortcomings of existing methods. After that, the COM is used to analyze a real bridge. The result is compared with the existing method, demonstrating its applicability and correct performance by a reinforced concrete beam. In addition, during the bridge system identification by COM, it is found that the best measurement set in terms of the range will depend on whether the epistemic uncertainty involved or not. It is concluded that, because the epistemic uncertainty will be removed as the knowledge of the structure increases, the optimum sensor placement should be achieved considering not only the accuracy of sensors, but also the unknown structural part.

ACS Style

Tian Peng; Maria Nogal; Joan Casas; Jose Turmo. Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method. Sensors 2021, 21, 2918 .

AMA Style

Tian Peng, Maria Nogal, Joan Casas, Jose Turmo. Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method. Sensors. 2021; 21 (9):2918.

Chicago/Turabian Style

Tian Peng; Maria Nogal; Joan Casas; Jose Turmo. 2021. "Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method." Sensors 21, no. 9: 2918.

Journal article
Published: 16 April 2021 in Automation in Construction
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The wellbeing of modern societies is dependent upon the functioning of their infrastructure networks. This paper introduces the 3C concept, an integrative multi-system and multi-stakeholder optimization approach for managing infrastructure interventions (e.g., maintenance, renovation, etc.). The proposed approach takes advantage of the benefits achieved by grouping (i.e., optimizing) intervention activities. Intervention optimization leads to substantial savings on both direct intervention costs (operator) and indirect unavailability costs (society) by reducing the number of system interruptions. The proposed optimization approach is formalized into a structured mathematical model that can account for the interactions between multiple infrastructure networks and the impact on multiple stakeholders (e.g., society and infrastructure operators), and it can accommodate different types of intervention, such as maintenance, removal, and upgrading. The different types of interdependencies, within and across infrastructures, are modeled using a proposed interaction matrix (IM). The IM allows integrating the interventions of different infrastructure networks whose interventions are normally planned independently. Moreover, the introduced 3C concept accounts for central interventions, which are those that must occur at a pre-established time moment, where neither delay nor advance is permitted. To demonstrate the applicability of the proposed approach, an illustrative example of a multi-system and multi-actor intervention planning is introduced. Results show a substantial reduction in the operator and societal costs. In addition, the optimal intervention program obtained in the analysis shows no predictable patterns, which indicates it is a useful managerial decision support tool.

ACS Style

Omar Kammouh; Maria Nogal; Ruud Binnekamp; A.R.M. Rogier Wolfert. Multi-system intervention optimization for interdependent infrastructure. Automation in Construction 2021, 127, 103698 .

AMA Style

Omar Kammouh, Maria Nogal, Ruud Binnekamp, A.R.M. Rogier Wolfert. Multi-system intervention optimization for interdependent infrastructure. Automation in Construction. 2021; 127 ():103698.

Chicago/Turabian Style

Omar Kammouh; Maria Nogal; Ruud Binnekamp; A.R.M. Rogier Wolfert. 2021. "Multi-system intervention optimization for interdependent infrastructure." Automation in Construction 127, no. : 103698.

Journal article
Published: 21 February 2021 in Energies
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The prevailing need for a more sustainable management of natural resources depends not only on the decisions made by governments and the will of the population, but also on the knowledge of the role of energy in our society and the relevance of preserving natural resources. In this sense, critical work is being done to instill key concepts—such as the circular economy and sustainable energy—in higher education institutions. In this way, it is expected that future professionals and managers will be aware of the importance of energy optimization, and will learn a series of computational methods that can support the decision-making process. In the context of higher education, this paper reviews the main trends and challenges related to the concepts of circular economy and sustainable energy. Besides, we analyze the role of simulation and serious games as a learning tool for the aforementioned concepts. Finally, the paper provides insights and discusses open research opportunities regarding the use of these computational tools to incorporate circular economy concepts in higher education degrees. Our findings show that, while efforts are being made to include these concepts in current programs, there is still much work to be done, especially from the point of view of university management. In addition, the analysis of the teaching methodologies analyzed shows that, although their implementation has been successful in favoring the active learning of students, their use (especially that of serious games) is not yet widespread.

ACS Style

Rocio de la Torre; Bhakti Onggo; Canan Corlu; Maria Nogal; Angel Juan. The Role of Simulation and Serious Games in Teaching Concepts on Circular Economy and Sustainable Energy. Energies 2021, 14, 1138 .

AMA Style

Rocio de la Torre, Bhakti Onggo, Canan Corlu, Maria Nogal, Angel Juan. The Role of Simulation and Serious Games in Teaching Concepts on Circular Economy and Sustainable Energy. Energies. 2021; 14 (4):1138.

Chicago/Turabian Style

Rocio de la Torre; Bhakti Onggo; Canan Corlu; Maria Nogal; Angel Juan. 2021. "The Role of Simulation and Serious Games in Teaching Concepts on Circular Economy and Sustainable Energy." Energies 14, no. 4: 1138.

Journal article
Published: 31 October 2020 in Sustainability
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When analysing the performance of bike-sharing scheme (BSS) stations, it is common to find stations that are located in specific points that capture the interest of users, whereas nearby stations are clearly underused. This uneven behaviour is not totally understood. This paper discusses the potential factors influencing station attractiveness, supported by the related literature on cyclists’ and pedestrians’ preferences and the characteristics of the stations themselves. The existing literature addresses these topics independently, while this work unites them by proposing a non data-extensive methodology that allows the attractiveness of BSS stations to be assessed. Attractiveness in this context is understood as the set of physical, environmental and service-related features of a bike station that make it more appealing for BSS users than nearby stations. Special attention is paid to differentiating objective features, based on facts, from subjective features, those influenced by personal perceptions. This classification becomes important in this context because subjective aspects can change from one geographical location to another, making the findings related to these aspects difficult to apply to other regions. Moreover, the assessment of the stations’ levels of safety and security is included. Thus, the proposed measure of attractiveness of BSS stations provides a balanced overview of several features. The consideration of station attractiveness when designing BSS layouts will help to refine the design of new layouts and will assist in conducting an appropriate diagnostic evaluation of the existing ones. This tool will allow urban and transportation planners to reduce re-balancing costs and to maximise user satisfaction at a low cost, which have a direct impact on improving the urban sustainability. The proposed method is applied to the Dublin bike sharing scheme, Dublinbikes, with good performance results.

ACS Style

Maria Nogal; Pilar Jiménez. Attractiveness of Bike-Sharing Stations from a Multi-Modal Perspective: The Role of Objective and Subjective Features. Sustainability 2020, 12, 9062 .

AMA Style

Maria Nogal, Pilar Jiménez. Attractiveness of Bike-Sharing Stations from a Multi-Modal Perspective: The Role of Objective and Subjective Features. Sustainability. 2020; 12 (21):9062.

Chicago/Turabian Style

Maria Nogal; Pilar Jiménez. 2020. "Attractiveness of Bike-Sharing Stations from a Multi-Modal Perspective: The Role of Objective and Subjective Features." Sustainability 12, no. 21: 9062.

Journal article
Published: 01 September 2020 in Géotechnique
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ACS Style

Shuyin Feng; Paul J. Vardanega; Erdin Ibraim; Iswandaru Widyatmoko; Chibuzor Ojum; Brendan C. O'Kelly; Maria Nogal. Permeability assessment of some granular mixtures. Géotechnique 2020, 70, 845 -847.

AMA Style

Shuyin Feng, Paul J. Vardanega, Erdin Ibraim, Iswandaru Widyatmoko, Chibuzor Ojum, Brendan C. O'Kelly, Maria Nogal. Permeability assessment of some granular mixtures. Géotechnique. 2020; 70 (9):845-847.

Chicago/Turabian Style

Shuyin Feng; Paul J. Vardanega; Erdin Ibraim; Iswandaru Widyatmoko; Chibuzor Ojum; Brendan C. O'Kelly; Maria Nogal. 2020. "Permeability assessment of some granular mixtures." Géotechnique 70, no. 9: 845-847.

Journal article
Published: 16 April 2020 in Journal of Sound and Vibration
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The characteristics of civil structures inevitably suffer a certain level of damage during its lifetime and cheap, non-destructive and reliable methods to assess their correct performance are of high importance. Structural System Identification (SSI) using measured response is the way to fine why performance is not correct and identify where the problems can be found. Different methods of SSI exist, both using static and vibration experimental data. However, using these methods is not always possible to decide if available measurements are sufficient to uniquely obtain the unknown. A (SSI) method that uses constrained observability method (COM) has already been developed based on the information provided by the monitoring of static non-destructive tests - using deflections and rotations under a known loading case. The method assures that all observable variables can be obtained with the available measured data. In the present paper, the problem of determining the actual characteristics of the members of a structure such as axial stiffness, flexural stiffness and mass using vibration data is analyzed. Subsets of natural frequencies and/or modal shapes are used. To give a better understanding of the proposed method and to demonstrate its potential applicability, several examples of growing complexity are analyzed, and the results show how constrained observability techniques might be efficiently used for the dynamic identification of structural systems using dynamic data. These lead to significant conclusions regarding the functioning of an SSI method based on dynamic behavior.

ACS Style

T. Peng; M. Nogal; J.R. Casas; J.A. Lozano-Galant; J. Turmo. Constrained observability techniques for structural system identification using modal analysis. Journal of Sound and Vibration 2020, 479, 115368 .

AMA Style

T. Peng, M. Nogal, J.R. Casas, J.A. Lozano-Galant, J. Turmo. Constrained observability techniques for structural system identification using modal analysis. Journal of Sound and Vibration. 2020; 479 ():115368.

Chicago/Turabian Style

T. Peng; M. Nogal; J.R. Casas; J.A. Lozano-Galant; J. Turmo. 2020. "Constrained observability techniques for structural system identification using modal analysis." Journal of Sound and Vibration 479, no. : 115368.

Journal article
Published: 01 March 2020 in Geotechnical Research
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This paper presents a critical review of the grading entropy approach of saturated permeability-coefficient predictions (k P) for coarse-grained soils. The approach applies grading entropy theory to the particle-size distributions (PSDs), such that the entirety of each gradation curve can be interpreted as a single point on a grading entropy chart, plotting its normalised entropy increment (B) against relative based grading entropy (A) values. Published datasets of measured permeability coefficient (k M) values for saturated compacted silty sand, sand and gravel materials are examined to understand the dependence of A and B on various gradation parameters and void ratio (e). In particular, log k M negatively correlates with log B and positively correlates to log A and e (log e). As such, power functions of the form

ACS Style

Brendan C O’Kelly; María Nogal. Determination of soil permeability coefficient following an updated grading entropy method. Geotechnical Research 2020, 7, 58 -70.

AMA Style

Brendan C O’Kelly, María Nogal. Determination of soil permeability coefficient following an updated grading entropy method. Geotechnical Research. 2020; 7 (1):58-70.

Chicago/Turabian Style

Brendan C O’Kelly; María Nogal. 2020. "Determination of soil permeability coefficient following an updated grading entropy method." Geotechnical Research 7, no. 1: 58-70.

Research article
Published: 29 July 2019 in Wind Energy
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The present paper discusses the application of stress‐cycle (SN) fatigue design procedures for offshore wind turbines, applied to the tower and substructure, and emphasizing the long‐term loading characterization. Three main methodologies are compared to assess SN fatigue long‐term design, direct scale‐up of loads and cycles to the design lifetime, probability fit for the loading distribution, and truncation and fit of the tail region. Different characteristic SN slopes are researched. The comprehensive comparison developed shows that limited interest exists in increasing the complexity of the loading assessment for SN fatigue design. In particular, the notion of representative sample has key influence on the fatigue calculations. Probability analysis techniques are not an adequate substitute of a representative sample. If definition of a representative sample for design is unpractical due to its large cost, direct scale‐up of cycles from a time t to a larger time T can be applied with uncertainty assessment. Bootstrapping of load ranges is implemented to tackle the limitations imposed by approaching a design time much larger than the evaluated time. It takes advantage of the fact that SN fatigue design is a statistical problem of mean value. Bootstrapping proved to be an efficient estimator of uncertainty with relatively constant confidence bounds, of particular interest to perform SN fatigue design with small samples. New insights on its application for fatigue design are presented. Due to its simple application and nonparametric character, it can be applied in combination with other techniques, such as extrapolation of loads and cycles.

ACS Style

Rui Teixeira; Maria Nogal; Alan O'Connor. Analysis of long‐term loading characterization for stress‐cycle fatigue design. Wind Energy 2019, 22, 1563 -1580.

AMA Style

Rui Teixeira, Maria Nogal, Alan O'Connor. Analysis of long‐term loading characterization for stress‐cycle fatigue design. Wind Energy. 2019; 22 (11):1563-1580.

Chicago/Turabian Style

Rui Teixeira; Maria Nogal; Alan O'Connor. 2019. "Analysis of long‐term loading characterization for stress‐cycle fatigue design." Wind Energy 22, no. 11: 1563-1580.

Journal article
Published: 25 July 2019 in Transportation Research Part A: Policy and Practice
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The concept of intrinsic vulnerability of a traffic network is defined for the first time in this paper. Intrinsic vulnerability is the susceptibility to incidents characterised by a probability of occurrence in space and time of difficult estimation, which can result in considerable reduction or loss of the system functionality. Given the nature of this type of vulnerability, its assessment might arise as a major problem. Therefore, this paper investigates the assessment of the intrinsic vulnerability of a traffic network through a set of quantifiable indicators, i.e., accessibility and reliability. Moreover, it is of interest to determine whether the selected indicators are sufficient to assess the intrinsic vulnerability or if there is any significant missing aspect to be considered. A new methodology based on structured elicitation of multivariate uncertainty from experts is presented to address these issues, allowing the estimation of the intrinsic vulnerability and its probabilistic relationship with the indicators accessibility and reliability. Although applied to the case of the metric intrinsic vulnerability, the proposed methodology emerges as an effective tool to understand other traffic descriptors of difficult evaluation such as resilience.

ACS Style

Maria Nogal; Oswaldo Morales Nápoles; Alan O'Connor. Structured expert judgement to understand the intrinsic vulnerability of traffic networks. Transportation Research Part A: Policy and Practice 2019, 127, 136 -152.

AMA Style

Maria Nogal, Oswaldo Morales Nápoles, Alan O'Connor. Structured expert judgement to understand the intrinsic vulnerability of traffic networks. Transportation Research Part A: Policy and Practice. 2019; 127 ():136-152.

Chicago/Turabian Style

Maria Nogal; Oswaldo Morales Nápoles; Alan O'Connor. 2019. "Structured expert judgement to understand the intrinsic vulnerability of traffic networks." Transportation Research Part A: Policy and Practice 127, no. : 136-152.

Journal article
Published: 18 June 2019 in Structural Safety
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Characterizing uncertainty in complex systems is steadily growing as a topic of interest. One of the efficient ways to characterize a complex system is achieved by probabilistic sensitivity analysis. In the context of this type of analysis, there are a limited number of methods that quantify the change of the output to its full probabilistic extent. Moreover, in some engineering applications, such as reliability analysis, some established indicators of sensitivity do not fit the best interest of the analysis procedure. This is the case of Kullback-Leibler divergence. Despite applied for probabilistic sensitivity analysis, it has limited interest in certain circumstances. A transformation of this indicator of entropy between two distributions is proposed in the present work. This transformation is used to establish a complementary indicator that is more perceptive, and more efficient for reliability sensitivity analysis. This new function is applied to research the global sensitivity analysis of an offshore wind turbine on a monopile foundation. Results show that, for engineering problems as the one presented, the usage of this transformed indicator produces intuitive results. It allows the efficient identification of relevant states of operation as well as the most influent variables in the design of experiments, resulting in better comprehension of system’s behaviour and operational risks.

ACS Style

Rui Teixeira; Alan O'Connor; Maria Nogal. Probabilistic sensitivity analysis of offshore wind turbines using a transformed Kullback-Leibler divergence. Structural Safety 2019, 81, 101860 .

AMA Style

Rui Teixeira, Alan O'Connor, Maria Nogal. Probabilistic sensitivity analysis of offshore wind turbines using a transformed Kullback-Leibler divergence. Structural Safety. 2019; 81 ():101860.

Chicago/Turabian Style

Rui Teixeira; Alan O'Connor; Maria Nogal. 2019. "Probabilistic sensitivity analysis of offshore wind turbines using a transformed Kullback-Leibler divergence." Structural Safety 81, no. : 101860.

Journal article
Published: 11 April 2019 in International Journal of Fatigue
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The current paper discusses a new methodology to assess stress-cycle fatigue design using meta-modelling. Research on its application is presented for offshore wind turbine towers. Kriging models are used to surrogate the complex time-domain stress-cycle fatigue assessment that demands multiple evaluations in the design phase. The presented development highlights the importance of having a notion of improvement for the problem of meta-modelling. Literature shows that, when meta-modelling complex engineering problems, the idea of improvement is not always considered. To tackle the problem of assessing fatigue in the design phase, a learning criterion is introduced. It has the particularity of relating to the physical description of the stress-cycle fatigue. Results of the proposed criterion are compared with meta-modelling using a Latin hypercube sampling, and with the standard design approach that bins environmental conditions for fatigue design calculations. A full 1 year validation sample is used to study convergence. As surrogate models for SN fatigue, Kriging models significantly decrease computational efforts of the designing procedure. Results showed that computational efforts can be reduced consistently by a factor of 5-8 without compromising accuracy. This may correspond to a reduction of up to approximately 85% of the effort needed to assess stress-cycle fatigue in the design phase. To conclude, it is important to highlight that the methodology presented has a universal character. It can be implemented to reduce computational time or assess probabilistic behaviour while maintaining only one requirement, definition of a single representative indicator. In the case of fatigue, the short-term stress-cycle damage rate was considered.

ACS Style

Rui Teixeira; Maria Nogal; Alan O’Connor; James Nichols; Antoine Dumas. Stress-cycle fatigue design with Kriging applied to offshore wind turbines. International Journal of Fatigue 2019, 125, 454 -467.

AMA Style

Rui Teixeira, Maria Nogal, Alan O’Connor, James Nichols, Antoine Dumas. Stress-cycle fatigue design with Kriging applied to offshore wind turbines. International Journal of Fatigue. 2019; 125 ():454-467.

Chicago/Turabian Style

Rui Teixeira; Maria Nogal; Alan O’Connor; James Nichols; Antoine Dumas. 2019. "Stress-cycle fatigue design with Kriging applied to offshore wind turbines." International Journal of Fatigue 125, no. : 454-467.

Conference paper
Published: 01 January 2019 in Proceedings of the 29th European Safety and Reliability Conference (ESREL)
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ACS Style

Maria Nogal; Daniel Honf. Resilience Assessment of the Traffic Network Luxembourg-Metz. The Power of Information. Proceedings of the 29th European Safety and Reliability Conference (ESREL) 2019, 1 .

AMA Style

Maria Nogal, Daniel Honf. Resilience Assessment of the Traffic Network Luxembourg-Metz. The Power of Information. Proceedings of the 29th European Safety and Reliability Conference (ESREL). 2019; ():1.

Chicago/Turabian Style

Maria Nogal; Daniel Honf. 2019. "Resilience Assessment of the Traffic Network Luxembourg-Metz. The Power of Information." Proceedings of the 29th European Safety and Reliability Conference (ESREL) , no. : 1.

Journal article
Published: 19 December 2018 in Reliability Engineering & System Safety
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When assessing the resilience of road transport networks, users’ response should be considered as they represent the main capability of the system to adapt to changes when any disruptive event occurs and to recover afterwards. Given the variability in users’ response, it seems deterministic approaches might not be adequate to represent the real system performance, thus, a stochastic perspective is required. This paper presents a new approach to assess the resilience of a traffic network when suffering from a disruptive event, considering the stochastic behaviour of the users, where their decisions will be biased by their perception of the traffic conditions rather than by the actual conditions. This approach provides more realistic patterns than the deterministic approach, mainly in terms of recovery times. The real traffic network Luxembourg-Metz has been used to illustrate the approach.

ACS Style

M. Nogal; D. Honfi. Assessment of road traffic resilience assuming stochastic user behaviour. Reliability Engineering & System Safety 2018, 185, 72 -83.

AMA Style

M. Nogal, D. Honfi. Assessment of road traffic resilience assuming stochastic user behaviour. Reliability Engineering & System Safety. 2018; 185 ():72-83.

Chicago/Turabian Style

M. Nogal; D. Honfi. 2018. "Assessment of road traffic resilience assuming stochastic user behaviour." Reliability Engineering & System Safety 185, no. : 72-83.

Books book
Published: 04 July 2018 in Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges
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Structural system identification (SSI) is a powerful tool for the assessment of the current condition of structures in operation. The basic assumption is that the deterioration of structures is reflected in the change of structural parameters. In SSI, the observability of these parameters depends on the location and the number of sensors. If the available sensors are less than the required ones, some parameters might not be observed. Furthermore, the incapability of identifying all parameters might occur when the sensors are sufficient but placed improperly. An investigation was carried out using SSI by observability method when then number of measurements is the same as the number of sensors. It is seen that a large proportion of the studied measurement sets cannot ensure the observability of all parameters. To improve the observability of structural parameters, a two-stage static SSI method is presented to fully exploit the information in the measurements. In the first stage, the SSI problem is treated in a linear manner and thereby the computation is greatly reduced. In the following stage, the nonlinear relations among the variables in the formulated system are recovered and thus the capability of the method to observe those structural parameters is enhanced.

ACS Style

Jun Lei; Maria Nogal; José Antonio Lozano Galant; Dong Xu; Jose Turmo. A two-stage static structural system identification by observability method. Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges 2018, 2894 -2900.

AMA Style

Jun Lei, Maria Nogal, José Antonio Lozano Galant, Dong Xu, Jose Turmo. A two-stage static structural system identification by observability method. Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges. 2018; ():2894-2900.

Chicago/Turabian Style

Jun Lei; Maria Nogal; José Antonio Lozano Galant; Dong Xu; Jose Turmo. 2018. "A two-stage static structural system identification by observability method." Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges , no. : 2894-2900.

Journal article
Published: 06 March 2018 in Journal of Hydraulic Research
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ACS Style

Rui Teixeira; Maria Nogal; Alan O'Connor. On the suitability of the generalized Pareto to model extreme waves. Journal of Hydraulic Research 2018, 56, 755 -770.

AMA Style

Rui Teixeira, Maria Nogal, Alan O'Connor. On the suitability of the generalized Pareto to model extreme waves. Journal of Hydraulic Research. 2018; 56 (6):755-770.

Chicago/Turabian Style

Rui Teixeira; Maria Nogal; Alan O'Connor. 2018. "On the suitability of the generalized Pareto to model extreme waves." Journal of Hydraulic Research 56, no. 6: 755-770.

Conference paper
Published: 21 October 2017 in Proceedings of EECE 2020
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During the first step in the development of any structural system identification method, the method should be validated by noise-free measurements in the first place. Nevertheless, this assumption is far from reality as the measurements in these tests are always subjected to the errors of measurement devices. To fill this gap, this paper analyzes the effects of measurement errors in a parametric structural system identification method: the observability method. To illustrate the symbolic approach of this method a simply supported beam is first analyzed in detail. This simulation provides the parametric equations of the estimates. Then, the effects of errors in a particular measurement, errors in all measurements, load locations are studied in this structure. Two additional examples of increasing complexity are also analyzed to show the effect of modelling errors on the estimates. A fluctuation of the observed parameters around the real values is proved a characteristic of this method. The results of these structures illustrate how important the effects of modelling errors are especially in areas with low curvatures.

ACS Style

Jun Lei; Jose-Antonio Lozano-Galant; Maria Nogal; Dong Xu; Jose Turmo. Impact of Measurement Errors in Inverse Analysis. Proceedings of EECE 2020 2017, 8, 894 -904.

AMA Style

Jun Lei, Jose-Antonio Lozano-Galant, Maria Nogal, Dong Xu, Jose Turmo. Impact of Measurement Errors in Inverse Analysis. Proceedings of EECE 2020. 2017; 8 ():894-904.

Chicago/Turabian Style

Jun Lei; Jose-Antonio Lozano-Galant; Maria Nogal; Dong Xu; Jose Turmo. 2017. "Impact of Measurement Errors in Inverse Analysis." Proceedings of EECE 2020 8, no. : 894-904.

Conference paper
Published: 06 September 2017 in Footbridge 2017 Berlin - Tell A Story: Conference Proceedings 6-8.9.2017 TU-Berlin
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The condition assessment of pedestrian bridges might be overlooked due to the small scale of these structures. A short list of accidents is provided to justify the necessity of condition assessment on pedestrian bridges. In this paper, the structural system identification by observability method is applied in two traditional arrangements of pedestrian bridges. In the simply supported beam example, the symbolical expressions of the estimation for bending stiffnesses are derived first. The validity of the method is justified by the accurate estimations using error-free measurements. However, as the real-life measurements are inevitably polluted by errors, the effect of measurement errors is thoroughly studied according to measurement errors in a particular measurement, loading cases and errors in all measurements. The simulation errors of the method is also demonstrated by a two-span continuous beam. The results show that the loading case is important regarding the accuracy of the estimations.

ACS Style

Jun Lei; Jose A. Lozano-Galant; Maria Nogal; Dong Xu; José Turmo. Structural System Identification of Pedestrian Bridges by Observability Method. Footbridge 2017 Berlin - Tell A Story: Conference Proceedings 6-8.9.2017 TU-Berlin 2017, 1 .

AMA Style

Jun Lei, Jose A. Lozano-Galant, Maria Nogal, Dong Xu, José Turmo. Structural System Identification of Pedestrian Bridges by Observability Method. Footbridge 2017 Berlin - Tell A Story: Conference Proceedings 6-8.9.2017 TU-Berlin. 2017; ():1.

Chicago/Turabian Style

Jun Lei; Jose A. Lozano-Galant; Maria Nogal; Dong Xu; José Turmo. 2017. "Structural System Identification of Pedestrian Bridges by Observability Method." Footbridge 2017 Berlin - Tell A Story: Conference Proceedings 6-8.9.2017 TU-Berlin , no. : 1.