Robust combination of the Morris and Sobol methods in complex multidimensional models

García, Dorleta; Aróstegui, Inmaculada; Prellezo, Raúl

doi:10.1016/j.envsoft.2019.104517

Cited by 22 publications

(9 citation statements)

References 39 publications

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“…Thus, this new combination of 20 trajectories was used to estimate the overall importance of each model parameter, and the corresponding plots can be seen in the next subsection. Note also that recently Garcia et al 37 suggested the use of the convergence criteria for the Morris method but for the selection of a group of the most important input factors and NOT for the selection of optimized Morris trajectories.…”

Section: Screening Results: the Maximal Dispersion Of Trajectories Is...mentioning

confidence: 99%

Trajectory-based sensitivity analysis in spectroscopic ellipsometry modeling

Likhachev

2023

Modeling Aspects in Optical Metrology IX

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All indirect optical metrology techniques, such as spectroscopic ellipsometry, reflectometry or scatterometry, for characterization of surfaces, thin films and complex 2D/3D multilayer structures require an appropriate modeling. Parametric sensitivity analysis (SA) is as an essential prerequisite step in optical metrology data modeling to quantify the relative importance of optical model parameters and to identify those with little influence in order to simplify a model. In our previous studies, 1-3 we have detailed the use of the Morris or Elementary Effect (EE) method, a screening type SA procedure, applied it to the spectroscopic ellipsometry data processing and investigated different types of its convergence. The present study is a continuation of these investigations, extending the application of the EE method for ellipsometric modeling. The method is a global SA technique and uses a stepping of m parameters along certain so-called "trajectories", or sequences of points in parameter space, randomly constructed in order to maximally fill the volume of the m-dimensional parameter space. However, it is reputed that the EE method relies heavily on a sampling strategy, or a way of selecting "optimized trajectories" in parameter space, i.e., the selection of a necessary number of trajectories chosen to be well spread over the space to properly cover the entire realistic ranges of all input factors. Here, we test some sampling methods for selecting trajectories with possibly different distributions and investigate their effects on the estimation of various sensitivity measures in spectroscopic ellipsometry data modeling. The results indicate that the performance of the sampling strategy should not be judged only by maximization of the trajectory spread but also by certain convergence criteria for the sensitivity index µ * .

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Section: Screening Results: the Maximal Dispersion Of Trajectories Is...mentioning

confidence: 99%

Trajectory-based sensitivity analysis in spectroscopic ellipsometry modeling

Likhachev

2023

Modeling Aspects in Optical Metrology IX

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“…The Morris screening method can identify and rank important variables through model evaluation. Principle of the method: Variables change by the same relative change amount, and the input variable that causes the largest output deviation is the most important [8].…”

Section: Morris Screening Methodsmentioning

confidence: 99%

Equivalent impedance modeling and control parameters effect analysis of DFIG

Guo,

Li,

Tan

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

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The doubly-fed induction generator(DFIG) is connected to a series compensation line, and the converter controllers interact with the series compensation line to produce sub-synchronous control interaction(SSCI). In this paper, a method of solving the equivalent resistance modeling of DFIG through a small-signal path is proposed to get the effect of converter control parameters on the damping of DFIG. Firstly, The small signal model is solved by the dynamic equation of DFIG, and the equivalent impedance of the small signal path is obtained. Secondly, the Morris screening method takes the equivalent impedance as the evaluation quantity to screen out the control parameters that have a great impact on damping and the control parameters with coupling effect. Finally, The control parameters have a coupling effect and have different degrees of influence on SSCI through the simulation analysis, so the optimized design of controller parameters can attenuate SSCI of DFIG and reduce the risk.

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“…Being a law-driven model relying on the influence of the energy balance equations, a tailored calibration process was employed to obtain sufficient model prediction accuracy. A hybrid of the Morris Method [42], detailed model calibration techniques [33] and iterative calibration processes [43] was used to manually tune the model parameters. The Morris method has been demonstrated as an effective technique to identify the most influential input variables to a model with the lowest computational cost and has been suggested by previous researchers as an appropriate technique for HVAC-Building model calibration [42].…”

Section: Description Of the Case Study Buildingmentioning

confidence: 99%

“…A hybrid of the Morris Method [42], detailed model calibration techniques [33] and iterative calibration processes [43] was used to manually tune the model parameters. The Morris method has been demonstrated as an effective technique to identify the most influential input variables to a model with the lowest computational cost and has been suggested by previous researchers as an appropriate technique for HVAC-Building model calibration [42]. Once the main influencing parameters have been identified, the iterative process of varying their input values to improve the accuracy and train the model is considerably more efficient and effective.…”

Section: Description Of the Case Study Buildingmentioning

confidence: 99%

Assessing the Risk to Indoor Thermal Environments on Industrial Sites Offering AHU Capacity for Demand Response

2021

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Increasing participation in demand response within the industrial sector may be crucial to growing the levels of available flexible capacity required to reliably control national electricity grids as renewable generation increases to satisfy emission targets. This research aims to assist the uptake of demand response in the industrial sector by investigating risk to indoor thermal environments on industrial sites offering air handling unit capacity for demand response. This evaluation uses a systematic model-based approach, calibrated and validated with empirical data from a relevant case study industrial building to assess risk through a number of scenarios. The conditions investigated cover several relevant grid response times and durations, and national and international extreme external ambient temperatures in the past, present and future under a variety of temperature limits. The study demonstrated that there is very low risk to the case study site participating in demand response, with only 15 of 264 initial and 284 of 936 total scenarios triggering any risk. The major factors affecting risk levels identified were more stringent temperature limits and the influence of more extreme climates. The development and implementation of this concept has considerable potential to benefit industrial participants and the wider national electricity grids.

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Robust combination of the Morris and Sobol methods in complex multidimensional models

Cited by 22 publications

References 39 publications

Trajectory-based sensitivity analysis in spectroscopic ellipsometry modeling

Trajectory-based sensitivity analysis in spectroscopic ellipsometry modeling

Equivalent impedance modeling and control parameters effect analysis of DFIG

Assessing the Risk to Indoor Thermal Environments on Industrial Sites Offering AHU Capacity for Demand Response

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