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Article
Peer-Review Record

Fourier Series Approximation of Vertical Walking Force-Time History through Frequentist and Bayesian Inference

Vibration 2022, 5(4), 883-913; https://doi.org/10.3390/vibration5040052
by Angus Ewan Peters 1,*, Vitomir Racic 2, Stana Živanović 3 and John Orr 1
Reviewer 2: Anonymous
Vibration 2022, 5(4), 883-913; https://doi.org/10.3390/vibration5040052
Submission received: 11 October 2022 / Revised: 11 November 2022 / Accepted: 30 November 2022 / Published: 9 December 2022
(This article belongs to the Special Issue Feature Papers in Vibration)

Round 1

Reviewer 1 Report

General Comment:

In my view, the general object and purpose of the paper is not properly accomplished:

 

“The proposed models provide consistently lower force amplitudes than any previous model and are shown to be more representative of real walking”. 

 

Why is this model more “representative”? The paper does not  provide evidence in this regard

 

“The proposed model provides a closer approximation of a structural acceleration than any other similar Fourier based model. The proposed model provides further evidence to combine the so called high and low frequency load models. The paper further demonstrates a resonant like response can occur for structure up to 20Hz”.

 

The paper does not  provide evidence in this regard

 

“Therefore, this paper seeks to improve the accuracy and reliability of ver-

tical walking load models by proposing a novel DLF model for the Fourier series approximation that considers the inherent inter-subject variability of pedestrians and considers the surrounding energy of each integer of walking”

 

The paper does not  provide evidence in this regard

 

“Thus, the proposed models produce DLF values consistently lower than any other industry used Fourier series-based model published and closer to the mean response of real footfalls, “

 

Values consistently lower is not an accomplishment in principle if the scarcity and statistical deviation is not considered 

 

Minor comments:

  • Numeration of figures is incorrect

  • Equations are not centered within the paragraph

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

The paper presents two procedures to obtain a DLF model from data, trying to build a regression model and compare its results with other models found in literature.

 

I suggest the authors to review text and figures and, along other cases, these: 1) "Data from paper" description in Fig. 1 seems confusing; 2) Fig. 7 captions are repetitive and its y-axis limits are not uniform; 3) The first plot of Fig. 11 is with small fonts and is not clear if it is part of this Figure; 4) It would be good if the table 2 have the used dataset range.

 

General Coments: 

1) Why the authors decided to not show the NN results? The error is smaller than others models tested. The argument used (page 13, line 2 to 4) is that the NN model is not practical for practical engineers. Nevertheless, today every engineering student should be able to  handle computational computer programming scripts (e.g.: python script), in which a saved trained NN model could be used. I suggest to show the NN results in Fig. 9 against the other frequentist proposed model.

2) The paper doesn't mention at all the biodynamic component of the problem. Although a better representation of the force model it is welcome, the force model is not the only factor in the human-structure interaction. The concurrent models (Varela et al. and Toso et al.), including the fact of closer comparasion with the proposed models, used the force model with the biodynamic model for pedestrian representation. So, it would be good to mention this context properly to address well the whole scientific problem to the reader.

3) The validation done, comparing with the response of other models is partial, because doesn't take in account measured values in real structures. The text should be clear at this point.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

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