{"title":"On the infodynamics of ramifications in constructal design.","authors":"Miguel R O Panão","doi":"10.1016/j.biosystems.2024.105388","DOIUrl":null,"url":null,"abstract":"<p><p>Infodynamics is the study of how information behaves and changes within a system during its development. This study investigates the insights that informational analysis can provide regarding the ramifications predicted by constructal design. First, infodynamic neologisms informature, defined as a measure of the amount of information in indeterminate physical systems, and infotropy - contextualized informature representing the degree of transformation of indeterminate physical systems - are introduced. Flow architectures can be designed using either symmetric or asymmetric branching. The infodynamic analysis of symmetric branching revealed diminishing returns in information content, demonstrating that informature serves as a measure of diversity. These findings align with the principle of \"few large and many small, but not too many,\" which is consistent with higher thermofluid performance. The Performance Scaled Svelteness Ψ expresses the ability of the flow architecture to promote thermofluid performance. By contextualizing the informature with Ψ, a performance infotropy that quantifies the degree of transformation associated with the link between thermofluid performance and diversity in the ramified flow structure is obtained. A predicted growth and decay effect with increasing branching levels leads to a local maximum, highlighting that the evolutionary direction of the ramifications is inversely proportional to the scale of the environment in which the flow structure develops. Assuming an evolutionary trend toward maximum infodynamic complexity, a pattern of asymmetric ramifications emerges, similar to the sap distribution in leaves or branching of trees.</p>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":" ","pages":"105388"},"PeriodicalIF":2.0000,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosystems","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.biosystems.2024.105388","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Infodynamics is the study of how information behaves and changes within a system during its development. This study investigates the insights that informational analysis can provide regarding the ramifications predicted by constructal design. First, infodynamic neologisms informature, defined as a measure of the amount of information in indeterminate physical systems, and infotropy - contextualized informature representing the degree of transformation of indeterminate physical systems - are introduced. Flow architectures can be designed using either symmetric or asymmetric branching. The infodynamic analysis of symmetric branching revealed diminishing returns in information content, demonstrating that informature serves as a measure of diversity. These findings align with the principle of "few large and many small, but not too many," which is consistent with higher thermofluid performance. The Performance Scaled Svelteness Ψ expresses the ability of the flow architecture to promote thermofluid performance. By contextualizing the informature with Ψ, a performance infotropy that quantifies the degree of transformation associated with the link between thermofluid performance and diversity in the ramified flow structure is obtained. A predicted growth and decay effect with increasing branching levels leads to a local maximum, highlighting that the evolutionary direction of the ramifications is inversely proportional to the scale of the environment in which the flow structure develops. Assuming an evolutionary trend toward maximum infodynamic complexity, a pattern of asymmetric ramifications emerges, similar to the sap distribution in leaves or branching of trees.
期刊介绍:
BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.