Models of Machines and Models of Phenomena

Sterrett, Susan G.

doi:10.1080/02698590600641024

Cited by 53 publications

(13 citation statements)

References 5 publications

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“…[41] in which the author shows how new areas of application and investigative research have been found. The topic is further developed in other articles [42][43][44].…”

Section: Short Historical Reviewmentioning

confidence: 99%

A Review of Similitude Methods for Structural Engineering

Casaburo

Petrone

Franco

et al. 2019

Applied Mechanics Reviews

126

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Similitude theory allows engineers, through a set of tools known as similitude methods, to establish the necessary conditions to design a scaled (up or down) model of a full-scale prototype structure. In recent years, to overcome the obstacles associated with full-scale testing, such as cost and setup, research on similitude methods has grown and their application has expanded into many branches of engineering. The aim of this paper is to provide as comprehensive a review as possible about similitude methods applied to structural engineering and their limitations due to size effects, rate sensitivity phenomena, etc. After a brief historical introduction and a more in-depth analysis of the main methods, the paper focuses on similitude applications classified, first, by test article, then by engineering fields.

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“…[41] in which the author shows how new areas of application and investigative research have been found. The topic is further developed in other articles [42][43][44].…”

Section: Short Historical Reviewmentioning

confidence: 99%

A Review of Similitude Methods for Structural Engineering

Casaburo

Petrone

Franco

et al. 2019

Applied Mechanics Reviews

126

View full text Add to dashboard Cite

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“…Rather than trying to get hold on similarity between phenomena (Sterrett 2006), I thus focus on the similarity between derivations of phenomena. This brings me back to Kuhn's problem, that is, how do we know on which exemplar a new phenomenon can be modelled (Kuhn 1970, 190)?…”

Section: Derivational Redundancy and Derivational Similaritymentioning

confidence: 99%

Towards a General Model of Applying Science

Bod¹

2006

International Studies in the Philosophy of Science

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How is scientific knowledge used, adapted, and extended in deriving phenomena and realworld systems? This paper aims at developing a general account of 'applying science' within the exemplar-based framework of Data-Oriented Processing (DOP), which is also known as Exemplar-Based Explanation (EBE). According to the exemplar-based paradigm, phenomena are explained not by deriving them all the way down from theoretical laws and boundary conditions but by modelling them on previously derived phenomena that function as exemplars. To accomplish this, DOP proposes to maintain a corpus of derivation trees of previous phenomena together with a matching algorithm that combines subtrees from the corpus to derive new phenomena. By using a notion of derivational similarity, a new phenomenon can be modelled as closely as possible on previously explained phenomena. I will propose an instantiation of DOP which integrates theoretical and phenomenological modelling and which generalises over various disciplines, from fluid mechanics to language technology. I argue that DOP provides a solution for what I call Kuhn's problem and that it redresses Kitcher's account of explanation.

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“…Usually, this validation process is fragmented by the point of view of the researcher, the available techniques/materials, the knowledge accumulated etc. . Although it is widely accepted that a theory is usually criticized by falsification, mathematical models are often tested by validation; thus, a set of validations checks for all the main results should be undeniably performed …”

Section: Introductionmentioning

confidence: 99%

“…etc.. 1,2 Although it is widely accepted that a theory is usually criticized by falsification, mathematical models are often tested by validation; thus, a set of validations checks for all the main results should be undeniably performed. 3 The study of physical phenomena is mainly based on the concept of physical similarity.…”

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confidence: 99%

Validation method for the systematization of results based on a similarity concept

Gavriil

Vafeas

Kanavouras

et al. 2018

Math Methods in App Sciences

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The development of a functional methodological approach is presented here, to clarify a globally valid way of evaluating the precision of mathematical modeling of physical and/or chemical processes. Starting from the description of the system, a phenomenon accompanied by a disclaiming hypothesis is investigated, against which the knowledge is accumulated with time. Moreover, the possibility of the evolution of any phenomenon being interrupted when a parameter overpasses a critical threshold, after which the hypothesis is not any more valid, is introduced. This possibility should be obtained through the dependence of a selected macroscopic quantity (marker) on a specific parameter. To apply this methodology, the problem of Stokes flow through a granular medium of spheroidal grains has been selected as an indicative case study. The prolate spheroidal configuration is considered, since the results for the oblate spheroid can be recovered via a simple transformation. Therein, the three‐dimensional flow fields are initially constructed analytically via the Papkovich‐Neuber differential representation, which provides the velocity and pressure fields in terms of harmonic spheroidal eigenfunctions. Next, under the Kuwabara‐type spheroidal 2D unit cell concept, the above expressions degenerate to the axisymmetric case, and the full solution is then obtained, keeping the leading terms of the series, which are adequate for most engineering applications for specific aspect ratio of the spheroids. In the sequel, the aforementioned problem is solved numerically for a 3D extension of the same model, where this numerical solution has been achieved by using the finite volumes method, while the resulting linear systems were approximated by applying the well‐known successful over‐relaxation concept. Finally, outcomes by both models have been compared via the above methodology, resulting to objective and reliable accuracy criteria.

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Models of Machines and Models of Phenomena

Cited by 53 publications

References 5 publications

A Review of Similitude Methods for Structural Engineering

A Review of Similitude Methods for Structural Engineering

Towards a General Model of Applying Science

Validation method for the systematization of results based on a similarity concept

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