Application of Inverse Neural Networks for Optimal Pretension of Absorbable Mini Plate and Screw System

Autor: Luis Jesús Villarreal-Gómez, Manuel Javier Rosel-Solis, Alex Bernardo Pimentel-Mendoza, Lázaro Rico-Pérez, José Omar Dávalos-Ramírez, Yuridia Vega
Rok vydání: 2021
Předmět:
musculoskeletal diseases
Shaft length
020209 energy
finite element method
absorbable
Inverse
02 engineering and technology
lcsh:Technology
lcsh:Chemistry
03 medical and health sciences
0302 clinical medicine
stomatognathic system
Fracture fixation
mini plate and screw
0202 electrical engineering
electronic engineering
information engineering
von Mises yield criterion
General Materials Science
lcsh:QH301-705.5
Instrumentation
Mathematics
Fluid Flow and Transfer Processes
Artificial neural network
lcsh:T
business.industry
Process Chemistry and Technology
Design of experiments
General Engineering
030206 dentistry
Structural engineering
musculoskeletal system
equipment and supplies
lcsh:QC1-999
Finite element method
Computer Science Applications
stomatognathic diseases
lcsh:Biology (General)
lcsh:QD1-999
lcsh:TA1-2040
inverse artificial neural network
lcsh:Engineering (General). Civil engineering (General)
business
optimization
Screw system
lcsh:Physics
Zdroj: Applied Sciences, Vol 11, Iss 1350, p 1350 (2021)
Applied Sciences
Volume 11
Issue 3
ISSN: 2076-3417
DOI: 10.3390/app11031350
Popis: Mandibular fractures are common facial lesions typically treated with titanium plate and screw systems
nevertheless, this material is associated with secondary effects. Absorbable material for implants is an alternative to titanium, but there are also problems such as incomplete screw insertion and screw breakage due to high pretension in the screw caused by the insertion torque. The purpose of this paper is to find the optimal screw pretension (SP) in absorbable plate and screw systems by means of artificial neural network (ANN) and its inverse (ANNi). This optimal SP must satisfy a desired maximum von Mises strain (MVMS). For training the ANN, a database was generated by means of a design of experiments (DOE). Each DOE configuration was solved by means of finite element method (FEM) calculations. To obtain the optimal value for (SP) in the mini absorbable screw for fracture fixation, a strategy to invert the ANN is developed. Using the ANN coefficients, a sensitive study was performed to identify the influence of the design parameters in the MVMS. The optimal SP obtained was 14.9742 N. The MVMS condition was satisfied with an error less than 1.1% in comparison with FEM and ANN results. The screw shaft length is the most influencing MVMS parameter.
Databáze: OpenAIRE
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