A coupled approach of optimization, uncertainty analysis and configurational mechanics for a fail‐safe design of structures

Serafinska, Aleksandra; Özenç, Kaan; Kaliske, Michael

doi:10.1002/nme.5282

Cited by 8 publications

(5 citation statements)

References 52 publications

(79 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, according to the theory of each method (Equations (1) and 3), meta analysis would be affected by ecological factors and some other related environmental characteristics including wetland area, the GDP per capita, the population density, latitude, the distance from the wetland to the city centre and the evaluation year, while the wavelet transform would be mainly affected by two parameters including scale factors and distance factors. In order to precisely analyze the influence of each factor for two methods, sensitivity analysis method was used to test each possible parameter that affected the simulated result [53][54][55]. The sensitivity of parameter variables is the variation with the corresponding parameters, which increased by 10% [56][57][58].…”

Section: Discussionmentioning

confidence: 99%

Addressing the Modelling Precision in Evaluating the Ecosystem Services of Coastal Wetlands

et al. 2018

View full text Add to dashboard Cite

Wetlands are one of the world's most productive ecosystems, and therefore it is crucial that management decisions regarding wetlands incorporate awareness of accurate assessments of the value of their respective ecosystem services. In this paper, we seek to improve the modelling precision in the scale transform process of ecosystem service evaluation. Firstly, we selected eight services as the criteria to calculate wetland ecosystem values: substance production, flood control, carbon sequestration, gas regulation, climate regulation, wave reduction, adding new lands, recreation and education. Then, six coastal wetlands of Liaoning province were chosen as the case study areas, and their ecosystem values were calculated by empirical method. Next, we simulated ecosystem values of the six cases by two spatial-scales transform methods named meta-analysis and wavelet transform. Finally, we compared the two groups of simulated values with the empirical measured values to examine their evaluation precisions. The results indicated that the total precision of the wavelet transform model (0.968) was higher than that of meta-analysis (0.712). In addition, the simulated values of single services such as substance production, flood control, carbon sequestration, gas regulation, and climate regulation were closer to the measured values using wavelet transform model. This research contributes to identifying an evaluation model with higher precision for evaluating wetland ecosystem services in the process of scale transform.

show abstract

Section: Discussionmentioning

confidence: 99%

Addressing the Modelling Precision in Evaluating the Ecosystem Services of Coastal Wetlands

et al. 2018

View full text Add to dashboard Cite

show abstract

“…In the present work, this technology is applied for the first time with OF cables, combining in a single product the protection of the embankment against erosion, the continuous monitoring of most of its structural health [15], and the ongoing interactions between the levee system and the environment, allowing a one-step advancement in Technology Readiness Level (TRL): from a level 4 (technology validated in the laboratory by Officine Maccaferri Spa) to a level 5 (Technology validated in an industrially relevant environment in the case of key enabling technologies) [16]. The advantage of this type of wire mesh, compared to the classic simple hexagonal mesh (and this explains its diffusion and success), lies in the fact that it can be seen as a "failsafe" [17]: the effects of the local failure of a single steel wire remain confined to its surroundings, without spreading to large areas of the system structure.…”

Section: Methodsmentioning

confidence: 99%

“…Water 2020, 12, x FOR PEER REVIEW 4 of 16 wire mesh, compared to the classic simple hexagonal mesh (and this explains its diffusion and success), lies in the fact that it can be seen as a "failsafe" [17]: the effects of the local failure of a single steel wire remain confined to its surroundings, without spreading to large areas of the system structure.…”

Section: Methodsmentioning

confidence: 99%

Conceptualization and Prototype of an Anti-Erosion Sensing Revetment for Levee Monitoring: Experimental Tests and Numerical Modeling

Bertulessi

Bignami

Boschini

et al. 2020

Water

View full text Add to dashboard Cite

The problem of levee embankment control during high flows is crucial for flood risk management in floodplains. Levee defense lines are often hundreds of kilometers long and surveys during emergencies are not easy tasks. For these reasons, levees monitored with in situ sensors and a suitable Information Technology (IT) real-time data communication and integration infrastructure, so-called “smart levees”, are gaining increasing interest as a crucial protection technology in floodplains. The paper presents the conceptualization of a prototype of a levee smart revetment, based on the integration of an optical fiber (OF) cable into a steel double-twisted wire mesh. In this paper the feasibility of this kind of revetment is firstly assessed. The flow pattern of overtopping water on the embankment is discussed, thus producing a raw estimation of the shear stress acting on the revetment in the field. A sample case is then analyzed in both numerical and laboratory tests. For this purpose, a numerical Finite Element Model (FEM) to describe the mechanical behavior of a double-twisted wire mesh when loaded along its own plane is presented. Numerical results indicate that the related strain, relatively low as compared to the steel wire yield stress, can be fully detected by the optical fiber continuous Brillouin sensor. This has been validated by the experimental activity performed and a digital twin of the prototype of the smart revetment, suitable for virtually testing the product under any load and constraint conditions and tailoring the production process, has been created.

show abstract

“…Initially, the dispatch reliability was the statistical result of the cancel and delay events. As for the control of the aircraft performance, relevant research has always focused on the monitoring and calculating of reliability, using the method of multi-layer self-attention [1], kriging combined with decomposed-coordinated [2,3] or extremum response [4], neural network model [5][6][7], discrete-time Bayesian network [8,9], stochastic process theory [10], finite element simulation response with optimization algorithm [11][12][13] or FORM/SORM [14] and so on. It can predict the trends in the performance of a device or structure over time.…”

Section: Introductionmentioning

confidence: 99%

Mechanical Dispatch Reliability Prediction for Civil Aircraft Considering Operational Parameters

Feng¹,

Song²,

Lu³

2023

Computer Modeling in Engineering &Amp; Sciences

View full text Add to dashboard Cite

To effectively predict the mechanical dispatch reliability (MDR), the artificial neural networks method combined with aircraft operation health status parameters is proposed, which introduces the real civil aircraft operation data for verification, to improve the modeling precision and computing efficiency. Grey relational analysis can identify the degree of correlation between aircraft system health status (such as the unscheduled maintenance event, unit report event, and services number) and dispatch release and screen out the most closely related systems to determine the set of input parameters required for the prediction model. The artificial neural network using radial basis function (RBF) as a kernel function, has the best applicability in the prediction of multidimensional, small sample problems. Health status parameters of related systems are used as the input to predict the changing trend of MDR, under the artificial neural network modeling framework. The case study collects real operation data for a certain civil aircraft over the past five years to validate the performance of the model which meets the requirements of the application. The results show that the prediction quadratic error E p of the model reaches 6.9 × 10 −8 . That is to say, in the existing operating environment, the prediction of the number of delay & cancel events per month can be less than once. The accuracy of RBF ANN, BP ANN and GA-BP ANN are compared further, and the results show that RBF ANN has better adaptability to such multidimensional small sample problems. The efforts of this paper provide a highly efficient method for the MDR prediction through aircraft system health state parameters, which is a promising model to enhance the prediction and controllability of the dispatch release, providing support for the construction of the civil aircraft operation system.

show abstract

A coupled approach of optimization, uncertainty analysis and configurational mechanics for a fail‐safe design of structures

Cited by 8 publications

References 52 publications

Addressing the Modelling Precision in Evaluating the Ecosystem Services of Coastal Wetlands

Addressing the Modelling Precision in Evaluating the Ecosystem Services of Coastal Wetlands

Conceptualization and Prototype of an Anti-Erosion Sensing Revetment for Levee Monitoring: Experimental Tests and Numerical Modeling

Mechanical Dispatch Reliability Prediction for Civil Aircraft Considering Operational Parameters

Contact Info

Product

Resources

About