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

Date
2023Version
Acceso abierto / Sarbide irekia
Type
Artículo / Artikulua
Version
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/
Impact
|
10.1214/22-AOAS1644
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 transf ...
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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. [--]
Subject
Bulk solid storage,
Jam formation,
Nonlinear heteroscedastic model,
Optimal design of experiments
Publisher
Institute of Mathematical Statistics
Published in
Annals of Applied Statistics 2023, 17(1)
Departament
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila
Publisher version
Sponsorship
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.