The Discussion Article cited is extraordinary from several perspectives. It

This comment repudiates these bold claims made by Hazelrigg and Klutke. It is divided into four topics; interpretation of probability, uncertainty of probability, model validation, and advanced UQ frameworks.

Hazelrigg and Klutke assert a consensus around the interpretation of probability where none has ever existed. The dogmatic subjectivism they espouse is a position with an established literature, but that's all it is. For the past 40 years, mutual tolerance has been the order of the day. Pragmatic Bayesians and frequentists alike have recognized that each camp brings unique tools and perspectives that often prove useful in practice.

One of the reasons the Bayesian/frequentist debate has settled into its long stalemate is that it cannot be resolved through mathematics alone. The whole debate turns on how mathematics relate to reality in the context of UQ....

References

References
1.
Hazelrigg
,
G. A.
, and
Klutke
,
G.-A.
,
2016
, “
Models, Uncertainty, and the Sandia V&V Challenge Problem
,”
ASME J. Verif., Valid. Uncertainty Quantif.
,
5
(
1
), p.
015501
.10.1115/1.4046471
2.
Hu
,
K. T.
, and
Orient
,
G. E.
,
2016
, “
The 2014 Sandia Verification and Validation Challenge: Problem Statement
,”
ASME J. Verif., Valid. Uncertainty Quantif.
,
1
(
1
), p.
011001
.10.1115/1.4032498
3.
ASME,
2009
, Standard for Verification and Validation in Computational Fluid Dynamics and Heat Transfer,
American Society of Mechanical Engineers
,
New York
,
ASME
Standard No. V&V 20-2009.https://www.asme.org/codes-standards/find-codes-standards/v-v-20-standard-verification-validation-computational-fluid-dynamics-heat-transfer
4.
ASME,
2012
, An Illustration of the Concepts of Verification and Validation in Computational Solid Mechanics,
American Institute of Mechanical Engineers
,
New York
,
ASME
Standard No. V&V 10.1-2012.https://www.asme.org/codes-standards/find-codes-standards/v-v-10-1-illustration-concepts-verification-validation-computational-solid-mechanics
5.
ASME
,
2018
,
Assessing Credibility of Computational Modeling Through Verification and Validation: Application to Medical Devices
,
American Society of Mechanical Engineers
,
New York
.https://www.asme.org/codes-standards/find-codes-standards/v-v-40-assessing-credibility-computational-modeling-verification-validation-application-medical-devices
6.
ASME,
2019
,
Standard for Verification and Validation in Computational Solid Mechanics
,
American Society of Mechanical Engineers
,
New York
, ASME Standard No. V&V 10–2020.https://www.asme.org/codes-standards/find-codes-standards/v-v-10-standard-verification-validation-computational-solid-mechanics
7.
Shafer
,
G.
,
1976
,
A Mathematical Theory of Evidence
,
Princeton University Press
,
Princeton, NJ
.
8.
Walley
,
P.
,
1991
,
Statistical Reasoning With Imprecise Probabilities
,
Chapman & Hall
,
London, UK
.
9.
Almond
,
R. G.
,
1995
,
Graphical Belief Modeling
,
Chapman & Hall
,
London, UK
.
10.
Kohlas
,
J.
, and
Monney
,
P.-A.
,
1995
,
A Mathematical Theory of Hints—An Approach to the Dempster-Shafer Theory of Evidence
,
Springer
,
Berlin
.
11.
Kramosil
,
I.
,
2001
,
Probabilistic Analysis of Belief Functions
,
Kluwer
,
New York
.
12.
Bae
,
H.-R.
,
Grandhi
,
R. V.
, and
Canfield
,
R. A.
,
2005
,
Structural Uncertainty Quantification and Optimization Using Evidence Theory
,
Tech Science Press
,
Forsyth, GA
.
13.
Bernardini
,
A.
, and
Tonon
,
F.
,
2010
,
Bounding Uncertainty in Civil Engineering
,
Springer-Verlag
,
Berlin
.
14.
Augustin
,
T.
,
Coolen
,
F. P. A.
,
de Cooman
,
G.
, and
Troffaes
,
M. C. M.
, eds.,
2014
, Introduction to Imprecise Probabilities,
Wiley & Sons
,
Chichester, UK
.
15.
Klir
,
G. J.
, and
Smith
,
R. M.
,
2001
, “
On Measuring Uncertainty and Uncertainty-Based Information: Recent Developments
,”
Ann. Math. Artif. Intell.
,
32
(
1/4
), pp.
5
33
.10.1023/A:1016784627561
16.
Martin
,
R.
, and
Liu
,
C.
,
2016
,
Inferential Models
,
CRC Press
,
Boca Raton, FL
.
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