A harmonic mean theorem for optimal branching exponents in transport networks

Optimal branching in transport networks has been analysed mechanism by mechanism since Murray's law (branching exponent x=3), but no combining rule exists when several dissipation mechanisms coexist. We prove that the optimal exponent is the weighted harmonic mean of the single-mechanism exponents, weighted by each mechanism's share of the dissipation budget. The result holds for any smooth dissipation function and any smooth convex structural cost. A bounding consequence establishes a strict floor x>5/2 for any Poiseuille-plus-pulsatility combination at every finite Womersley number, providing a parameter-free test that distinguishes dissipation-based from impedance-based optimization of biological networks. The predictions are robust to wall compliance and physiological flow variability; the latter preferentially amplifies entrance losses, yielding a testable prediction that vascular beds with high flow variability should exhibit systematically lower branching exponents. Read inversely, the theorem predicts that roughly half of coronary pumping power is dissipated by entrance effects. An order-by-order analysis of the human pulmonary arterial tree predicts the observed transition from x≈2.1 to x≈3, in quantitative agreement with cross-species morphometric data. The same entrance-driven mechanism reproduces the two-regime architecture of allometric scaling theory as asymptotic limits of a single cost function.

Authors

Institutions

Publication Details

Journal
Journal of The Royal Society Interface
Published
2026-11-04
DOI
https://doi.org/10.1098/rsif.2026.0331
Primary Topic
Heat Transfer and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A harmonic mean theorem for optimal branching exponents in transport networks

Himanshu Mishra, Neeta Lohani, Harmesh Kumar
Journal of The Royal Society Interface
Heat Transfer and Optimization
article

A harmonic mean theorem for optimal branching exponents in transport networks

Himanshu Mishra, Neeta Lohani, Harmesh Kumar
article en

Abstract

Optimal branching in transport networks has been analysed mechanism by mechanism since Murray's law (branching exponent x=3), but no combining rule exists when several dissipation mechanisms coexist. We prove that the optimal exponent is the weighted harmonic mean of the single-mechanism exponents, weighted by each mechanism's share of the dissipation budget. The result holds for any smooth dissipation function and any smooth convex structural cost. A bounding consequence establishes a strict floor x>5/2 for any Poiseuille-plus-pulsatility combination at every finite Womersley number, providing a parameter-free test that distinguishes dissipation-based from impedance-based optimization of biological networks. The predictions are robust to wall compliance and physiological flow variability; the latter preferentially amplifies entrance losses, yielding a testable prediction that vascular beds with high flow variability should exhibit systematically lower branching exponents. Read inversely, the theorem predicts that roughly half of coronary pumping power is dissipated by entrance effects. An order-by-order analysis of the human pulmonary arterial tree predicts the observed transition from x≈2.1 to x≈3, in quantitative agreement with cross-species morphometric data. The same entrance-driven mechanism reproduces the two-regime architecture of allometric scaling theory as asymptotic limits of a single cost function.

Journal of The Royal Society InterfaceVol. 23(244)
Thapar Institute of Engineering & Technology (IN)
Openalex Percentile: Top 25%
Heat Transfer and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon