Preferred physical-mathematical model of the cold energy storage system

Menin, Boris

doi:10.1016/j.applthermaleng.2016.10.128

“…The results of the theoretical conclusions of the informational method have been applied to several practical problems, including the measurement of a physical constant [13], the determination of the required simplicity of a physical law [9], and the evaluation of the efficiency of a technological process (thermal energy accumulation and ice maker performance) [18][19][20][21].…”

Section: Beginnings Of the Informational Approachmentioning

confidence: 99%

A new look at the process of modelling physical phenomena: Informational approach

Menin¹

2023

Preprint

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<p> When building a model of a physical phenomenon or process, scientists face an inevitable compromise between the simplicity of the model (qualitative‒quantitative set of variables) and its accuracy. For hundreds of years, the visual simplicity of a law testified to the genius and depth of the physical thinking of the scientist who proposed it. Currently, the desire for a deeper physical understanding of the surrounding world and newly discovered physical phenomena motivates researchers to increase the number of variables considered in a model. This direction leads to an increased probability of choosing an inaccurate or even erroneous model. This study describes a method for estimating the limit of measurement accuracy, taking into account the stage of model building in terms of storage, transmission, processing and use of information by the observer. This limit, due to the finite amount of information stored in the model, allows you to select the optimal number of variables for the best reproduction of the observed object and calculate the exact values of the threshold discrepancy between the model and the phenomenon under study in measurement theory. We consider two examples: measurement of the speed of sound and measurement of physical constants. </p>

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“…The results of the theoretical conclusions of the informational method have been applied to several practical problems, including the measurement of a physical constant [13], the determination of the required simplicity of a physical law [9], and the evaluation of the efficiency of a technological process (thermal energy accumulation and ice maker performance) [18][19][20][21].…”

Section: Beginnings Of the Informational Approachmentioning

confidence: 99%

A new look at the process of modelling physical phenomena: Informational approach

Menin¹

2023

Preprint

0

View full text Add to dashboard Cite

<p> When building a model of a physical phenomenon or process, scientists face an inevitable compromise between the simplicity of the model (qualitative‒quantitative set of variables) and its accuracy. For hundreds of years, the visual simplicity of a law testified to the genius and depth of the physical thinking of the scientist who proposed it. Currently, the desire for a deeper physical understanding of the surrounding world and newly discovered physical phenomena motivates researchers to increase the number of variables considered in a model. This direction leads to an increased probability of choosing an inaccurate or even erroneous model. This study describes a method for estimating the limit of measurement accuracy, taking into account the stage of model building in terms of storage, transmission, processing and use of information by the observer. This limit, due to the finite amount of information stored in the model, allows you to select the optimal number of variables for the best reproduction of the observed object and calculate the exact values of the threshold discrepancy between the model and the phenomenon under study in measurement theory. We consider two examples: measurement of the speed of sound and measurement of physical constants. </p>

show abstract

“…The results of the theoretical conclusions of the informational method have been applied to several practical problems, including the measurement of a physical constant [13], the determination of the required simplicity of a physical law [9], and the evaluation of the efficiency of a technological process (thermal energy accumulation and ice maker performance) [23] [24] [25] [26].…”

Section: B Meninmentioning

confidence: 99%

“…The closeness of the uncertainty ε 1,2,3 obtained in the experiment to the justified uncertainty ε opt1,2,3 indicates the preference of the chosen model [23] compared to the other two models [27] [29]: ε 1 /ε opt1 = 0.53 < ε 2 /ε opt2 = 0.69 < ε 3 /ε opt3 = 0.8. This recommendation is also confirmed by calculating the ratio of the number of FIQs taken into account in the model, γ 1,2,3 and the optimal γ mod1,2,3 : γ 1 = 1, γ mod1 = 19 (Table 1), and γ 1 /γ mod1 = 1/19 = 0.05 [27]; γ 2 = 4, γ mod2 = 19 (Table 1), Journal of Applied Mathematics and Physics and γ 2 /γ mod2 = 4/19 = 0.21 [29]; γ 3 = 18, γ mod3 = 52 (Table 1), γ 3 /γ opt3 = 18/52 = 0.35 [28].…”

Section: B Meninmentioning

confidence: 99%

Unleashing the Power of Information Theory: Enhancing Accuracy in Modeling Physical Phenomena

Menin¹

2023

JAMP

0

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When building a model of a physical phenomenon or process, scientists face an inevitable compromise between the simplicity of the model (qualitativequantitative set of variables) and its accuracy. For hundreds of years, the visual simplicity of a law testified to the genius and depth of the physical thinking of the scientist who proposed it. Currently, the desire for a deeper physical understanding of the surrounding world and newly discovered physical phenomena motivates researchers to increase the number of variables considered in a model. This direction leads to an increased probability of choosing an inaccurate or even erroneous model. This study describes a method for estimating the limit of measurement accuracy, taking into account the stage of model building in terms of storage, transmission, processing and use of information by the observer. This limit, due to the finite amount of information stored in the model, allows you to select the optimal number of variables for the best reproduction of the observed object and calculate the exact values of the threshold discrepancy between the model and the phenomenon under study in measurement theory. We consider two examples: measurement of the speed of sound and measurement of physical constants.

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Preferred physical-mathematical model of the cold energy storage system

Cited by 7 publications

References 9 publications

A new look at the process of modelling physical phenomena: Informational approach

A new look at the process of modelling physical phenomena: Informational approach

A new look at the process of modelling physical phenomena: Informational approach

Unleashing the Power of Information Theory: Enhancing Accuracy in Modeling Physical Phenomena

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