Publication:
Designing experiments for estimating an appropriate outlet size for a silo type problem

Consultable a partir de

Date

2023

Authors

López Fidalgo, Jesús
May, Caterina

Director

Publisher

Institute of Mathematical Statistics
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión publicada / Argitaratu den bertsioa

Project identifier

AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113443RB-C21/ES/
AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116873GB-I00/ES/
AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114031RB-I00/ES/

Abstract

Jam formation is a problem that may occur when granular material is discharged by gravity from a silo. The estimation of the minimum outlet size, which guarantees that the time to the next jamming event is long enough, can be crucial in the industry. The time is modeled by an exponential distribution with two unknown parameters, and this goal translates to precise estimation of a nonlinear transformation of the parameters. We obtain c-optimum experimental designs with that purpose, applying the graphic Elfving method. Because the optimal experimental designs depend on the nominal values of the parameters, we conduct a sensitivity analysis on our dataset. Finally, a simulation study checks the performance of the approximations, first with the Fisher Information matrix, then with the linearization of the function to be estimated. The results are useful for experimenting in a laboratory and then translating the results to a real scenario. From the application we develop a general methodology for estimating a one-dimensional transformation of the parameters of a nonlinear model.

Keywords

Bulk solid storage, Jam formation, Nonlinear heteroscedastic model, Optimal design of experiments

Department

Estadística, Informática y Matemáticas / Estatistika, Informatika eta Matematika

Faculty/School

Degree

Doctorate program

Editor version

Funding entities

The first author was sponsored by Ministerio de Ciencia e Innovación PID2020-113443RB-C21 and the third one by Ministerio de Ciencia e Innovación PID2020-116873GB-I00 and PID2020-114031RB-I00.

© Institute of Mathematical Statistics, 2023

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