The Experts below are selected from a list of 273 Experts worldwide ranked by ideXlab platform

Julien Berger - One of the best experts on this subject based on the ideXlab platform.

  • An efficient sensitivity analysis for energy performance of building envelope: A Continuous Derivative based approach
    Building Simulation, 2020
    Co-Authors: Ainagul Jumabekova, Julien Berger, Aurélie Foucquier
    Abstract:

    Within the framework of building energy assessment, this article proposes to use a Derivative based sensitivity analysis of heat transfer models in a building envelope. Two, global and local, estimators are obtained at low computational cost, to evaluate the influence of the parameters on the model outputs. Ranking of these estimators values allows to reduce the number of model unknown parameters by excluding non-significant parameters. A comparison with variance and regression-based methods is carried out and the results highlight the satisfactory accuracy of the Continuous-based approach. Moreover, for the carried investigations the approach is 100 times faster compared to the variance-based methods. A case study applies the method to a real-world building wall. The sensitivity of the thermal loads to local or global variations of the wall thermal properties is investigated. Additionally, a case study of wall with window is analyzed.

  • parameter estimation and model selection for water sorption in a wood fibre material
    Wood Science and Technology, 2020
    Co-Authors: Julien Berger, Thibaut Colinart, Bruna R Loiola, Helcio R B Orlande
    Abstract:

    The sorption curve is an essential feature for the modelling of heat and mass transfer in porous building materials. Several models have been proposed in the literature to represent the amount of moisture content in the material according to the water activity (or capillary pressure) level. These models are based on analytical expressions and few parameters that need to be estimated by inverse analysis. This article investigates the reliability of eight models through the accuracy of the estimated parameters. For this, experimental data for a wood fibre material are generated with special attention to the stop criterion to capture long time kinetic constants. Among five sets of measurements, the best estimate is computed. The reliability of the models is then discussed. After proving the theoretical identifiability of the unknown parameters for each model, the primary identifiability is analysed. It evaluates whether the parameters influence on the model output is sufficient to proceed the parameter estimation with accuracy. For this, a Continuous Derivative-based approach is adopted. Seven models have a low primary identifiability for at least one parameter. Indeed, when estimating the unknown parameters using the experimental observations, the parameters with low primary identifiability exhibit large uncertainties. Finally, an Approximation Bayesian Computation algorithm is used to simultaneously select the best model and estimate the parameters that best represent the experimental data. The GAB and Fredlund-Xing models, together with a proposed model in this work, were the best ones selected by this algorithm.

Sanjaya Kumar Parhi - One of the best experts on this subject based on the ideXlab platform.

  • Extending the applicability of a third-order scheme with Lipschitz and Hölder Continuous Derivative in Banach spaces
    Journal of the Egyptian Mathematical Society, 2020
    Co-Authors: Debasis Sharma, Sanjaya Kumar Parhi
    Abstract:

    We extend the applicability of a cubically convergent nonlinear system solver using Lipschitz Continuous first-order Fréchet Derivative in Banach spaces. This analysis avoids the usual application of Taylor expansion in convergence analysis and extends the applicability of the scheme by applying the technique based on the first-order Derivative only. Also, our study provides the radius of convergence ball and computable error bounds along with the uniqueness of the solution. Furthermore, the generalization of this analysis using Hölder condition is provided. Various numerical tests confirm that our analysis produces better results and it is useful in solving such problems where previous methods can not be implemented.

  • Extending the applicability of a third-order scheme with Lipschitz and Hölder Continuous Derivative in Banach spaces
    Journal of the Egyptian Mathematical Society, 2020
    Co-Authors: Debasis Sharma, Sanjaya Kumar Parhi
    Abstract:

    We extend the applicability of a cubically convergent nonlinear system solver using Lipschitz Continuous first-order Frechet Derivative in Banach spaces. This analysis avoids the usual application of Taylor expansion in convergence analysis and extends the applicability of the scheme by applying the technique based on the first-order Derivative only. Also, our study provides the radius of convergence ball and computable error bounds along with the uniqueness of the solution. Furthermore, the generalization of this analysis using Holder condition is provided. Various numerical tests confirm that our analysis produces better results and it is useful in solving such problems where previous methods can not be implemented.

  • Local Convergence and Complex Dynamics of a Uni-parametric Family of Iterative Schemes
    International Journal of Applied and Computational Mathematics, 2020
    Co-Authors: Debasis Sharma, Sanjaya Kumar Parhi
    Abstract:

    Using the Lipschitz Continuous Derivative, we study the local convergence analysis of a third and fourth-order convergent uni-parametric class of iterative schemes. This technique avoids the usual practice of Taylor expansion in convergence analysis and extends the applicability of the family by using the assumption based on the first-order Derivative only. Our study provides the radii of balls of convergence and computable error bounds along with the uniqueness of the solution. Also, complex dynamical properties of the family are discussed to select good schemes in the view of numerical stability. Numerical illustrations show that our analysis is useful in solving such problems where previous studies fail to solve.

Dharmendra Kumar Gupta - One of the best experts on this subject based on the ideXlab platform.

  • Local convergence of a parameter based iteration with Hölder Continuous Derivative in Banach spaces
    Calcolo, 2016
    Co-Authors: Sukhjit Singh, Dharmendra Kumar Gupta, Rakesh P. Badoni, Eulalia Martínez, Jose L Hueso
    Abstract:

    The local convergence analysis of a parameter based iteration with Holder Continuous first Derivative is studied for finding solutions of nonlinear equations in Banach spaces. It generalizes the local convergence analysis under Lipschitz Continuous first Derivative. The main contribution is to show the applicability to those problems for which Lipschitz condition fails without using higher order Derivatives. An existence-uniqueness theorem along with the derivation of error bounds for the solution is established. Different numerical examples including nonlinear Hammerstein equation are solved. The radii of balls of convergence for them are obtained. Substantial improvements of these radii are found in comparison to some other existing methods under similar conditions for all examples considered.

  • Convergence of a continuation method under Lipschitz Continuous Derivative in Banach spaces
    Journal of Applied Mathematics and Computing, 2011
    Co-Authors: M. Prashanth, Dharmendra Kumar Gupta
    Abstract:

    The aim of this paper is to use recurrence relations instead of majorizing sequences to establish the semilocal convergence of a continuation method combining Chebyshev method and Convex acceleration of Newton’s method for solving nonlinear equations in Banach spaces under the assumption that the first Frechet Derivative satisfies the Lipschitz continuity condition. An existence-uniqueness theorem is given. Also, a closed form of error bounds is derived in terms of a real parameter α∈[0,1]. Two numerical examples are worked out to demonstrate the efficacy of our convergence analysis. On comparing the existence and uniqueness regions for the solution obtained by our analysis with those obtained by using majorizing sequences, it is found that our analysis gives better results in both the examples. Further, we observed that for particular values of α, our analysis reduces to those for Chebyshev method (α=0) and Convex acceleration of Newton’s method (α=1) respectively with improved results.

Helcio R B Orlande - One of the best experts on this subject based on the ideXlab platform.

  • parameter estimation and model selection for water sorption in a wood fibre material
    Wood Science and Technology, 2020
    Co-Authors: Julien Berger, Thibaut Colinart, Bruna R Loiola, Helcio R B Orlande
    Abstract:

    The sorption curve is an essential feature for the modelling of heat and mass transfer in porous building materials. Several models have been proposed in the literature to represent the amount of moisture content in the material according to the water activity (or capillary pressure) level. These models are based on analytical expressions and few parameters that need to be estimated by inverse analysis. This article investigates the reliability of eight models through the accuracy of the estimated parameters. For this, experimental data for a wood fibre material are generated with special attention to the stop criterion to capture long time kinetic constants. Among five sets of measurements, the best estimate is computed. The reliability of the models is then discussed. After proving the theoretical identifiability of the unknown parameters for each model, the primary identifiability is analysed. It evaluates whether the parameters influence on the model output is sufficient to proceed the parameter estimation with accuracy. For this, a Continuous Derivative-based approach is adopted. Seven models have a low primary identifiability for at least one parameter. Indeed, when estimating the unknown parameters using the experimental observations, the parameters with low primary identifiability exhibit large uncertainties. Finally, an Approximation Bayesian Computation algorithm is used to simultaneously select the best model and estimate the parameters that best represent the experimental data. The GAB and Fredlund-Xing models, together with a proposed model in this work, were the best ones selected by this algorithm.

Stéphane Girard - One of the best experts on this subject based on the ideXlab platform.

  • l1 optimal linear programming estimator for periodic frontier functions with holder Continuous Derivative
    Automation and Remote Control, 2014
    Co-Authors: Alexander Nazin, Stéphane Girard
    Abstract:

    We propose a new estimator based on a linear programming method for smooth frontiers of sample points on a plane. The Derivative of the frontier function is supposed to be Holder Continuous. The estimator is defined as a linear combination of kernel functions being sufficiently regular, covering all the points and whose associated support is of smallest surface. The coefficients of the linear combination are computed by solving a linear programming problem. The L 1 error between the estimated and the true frontier function is shown to be almost surely converging to zero, and the rate of convergence is proved to be optimal.

  • L1-optimal linear programming estimator for periodic frontier functions with Hölder Continuous Derivative
    Automation and Remote Control Avtomatika i Telemekhanika, 2014
    Co-Authors: Alexander Nazin, Stéphane Girard
    Abstract:

    We propose a new estimator based on a linear programming method for smooth frontiers of sample points. The Derivative of the frontier function is supposed to be Hölder Continuous.The estimator is defined as a linear combination of kernel functions being sufficiently regular, covering all the points and whose associated support is of smallest surface. The coefficients of the linear combination are computed by solving a linear programming problem. The L1- error between the estimated and the true frontier functions is shown to be almost surely converging to zero, and the rate of convergence is proved to be optimal.

  • L1-optimal linear programming estimatorfor periodic frontier functions with Holder Continuous Derivative
    arXiv: Statistics Theory, 2014
    Co-Authors: Alexander Nazin, Stéphane Girard
    Abstract:

    We propose a new estimator based on a linear programming method for smooth frontiers of sample points. The Derivative of the frontier function is supposed to be Holder Continuous.The estimator is defined as a linear combination of kernel functions being sufficiently regular, covering all the points and whose associated support is of smallest surface. The coefficients of the linear combination are computed by solving a linear programming problem. The L1- error between the estimated and the true frontier functionsis shown to be almost surely converging to zero, and the rate of convergence is proved to be optimal.