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Prediction of displacement in the equine third metacarpal bone using a neural network prediction algorithm

Mouloodi Saeed, Rahmanpanah Hadi, Burvill Colin, Davies Helen M. S.

Biocybernetics and Biomedical Engineering

2020

Vol. 40, no. 2

849--863

Bone is a nonlinear, inhomogeneous and anisotropic material. To predict the behavior of bones expert systems are employed to reduce the computational cost and to enhance the accuracy of simulations. In this study, an artificial neural network (ANN) was used for the prediction of displacement in long bones followed by ex-vivo experiments. Three hydrated third metacarpal bones (MC3) from 3 thoroughbred horses were used in the experiments. A set of strain gauges were distributed around the midshaft of the bones. These bones were then loaded in compression in an MTS machine. The recordings of strains, load, load exposure time, and displacement were used as ANN input parameters. The ANN which was trained using 3,250 experimental data points from two bones predicted the displace-ment of the third bone (R2 ≥ 0.98). It was suggested that the ANN should be trained using noisy data points. The proposed modification in the training algorithm makes the ANN very robust against noisy inputs measurements. The performance of the ANN was evaluated in response to changes in the number of input data points and then by assuming a lack of strain data. A finite element analysis (FEA) was conducted to replicate one cycle of force-displace-ment experimental data (to gain the same accuracy produced by the ANN). The comparison of FEA and ANN displacement predictions indicates that the ANN produced a satisfactory outcome within a couple of seconds, while FEA required more than 160 times as long to solve the same model (CPU time: 5 h and 30 min).

Evaluate the usefulness of the edf model in the safety assessment on example of the Solina dam

Bąk A.

Logistyka

2015

nr 4

8642--8651, CD3

The EDF model shows dependency between the variation of measurements in the level of the reservoir, medium temperature and influence of time to the displacements observed on the crest of the Solina dam. Previous analysis showed that the model accurately reflects the movement of the crest of the dam, therefore further action was taken towards the prediction of the behavior of the object. The analysis was based on 22 measuring points located on the crest of the dam. Forecast movements of points located on the crest of the Solina dam was made on the basis of 4 different forecasting periods. Only modeling database corresponding to 15 years of exploitation of the dam allows to create a reliable predictions. Implementation of the model which was proposed in the article will allow the interpretation of measurement data. These measures makes it possible to improve the safety of local residents, allows for early detection of anomalies and discontinuities in the behavior of the dam.

Model ÉDF uzależnia zachowania elementów zapór od zmienności poziomu zwierciadła wody górnej, cykliczności temperatur oraz wpływ czasu. Użycie modelu w obrazowaniu przemieszczeń korony zapory Solina dało zadowalające rezultaty, dlatego też podjęto się dalszych działań w kierunku predykcji zachowań budowli. W ramach analizy wykonano prognozę przemieszczeń dla 22 punktów pomiarowych zlokalizowanych na koronie zapory Solina. Predykcja w oparciu o 4 różne okresy prognozowania pozwoliła na wywnioskowanie, iż dla uzyskania wiarygodnych prognoz niezbędna jest sekwencja danych na podstawie 15 lat eksploatacji obiektu. Zastosowanie tak obszernej bazy danych umożliwiło uzyskanie pełnej zgodności pomiędzy wartościami modelowanymi i obserwowanymi przemieszczeniami w obrębie określonych przedziałów ufności. Wdrożenie modelowania zaproponowanego w artykule pozwoli na interpretację danych pomiarowych oraz wnioskowanie o zmianach zachodzących w zaporach. Działania te pozwolą na bieżącą ocenę stanu technicznego zapór, usprawnienie procesu decyzyjnego oraz wskażą konieczne działania naprawcze i renowacyjne.