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Mass distributions on R3: total mass, first moment and inertia matrix

Definition

Let B(R3) be the Borel sigma-algebra of R3 (The Borel sigma-algebra of a topological space) and let ν be a measure on the measurable space (R3,B(R3)) (Measures on sigma-algebras, Measure spaces) that is finite, ν(R3)<+∞, and bounded, meaning that there is a real R>0 with ν(R3∖B‾R(0))=0, the closed ball being that of Open ball, closed ball and sphere in a metric space. Throughout, integrals are Lebesgue integrals against ν in the sense of Integral over a measurable subset and Integrable real and complex functions, and their integrals, and for a measurable vector- or matrix-valued function the integral is defined componentwise: ∫F dν:=(∫F1 dν,∫F2 dν,∫F3 dν) and (∫M dν)jk:=∫Mjk dν, whenever every displayed scalar integral is finite.

A mass distribution on R3 is a bounded finite Borel measure ν with m:=ν(R3)∈(0,+∞); the number m is its total mass. Writing points of R3 as ρ and using the Euclidean inner product ⟨⋅,⋅⟩ and norm ∥ρ∥2=⟨ρ,ρ⟩ of The Euclidean inner product ⟨x,y⟩=∑k<nxkyk on Rn, define:

  1. the first moment μ(ν):=∫ρ dν∈R3, read componentwise as μ(ν)j=∫ρj dν;
  2. the inertia matrix I(ν)∈M3(R) (The vector space Mm×n(F):=F m×n of m by n matrices over a field, with entrywise operations) by its entries I(ν)jk:=∫(∥ρ∥22 δjk−ρjρk) dν, where δjk=1 if j=k and δjk=0 otherwise; equivalently I(ν)=∫(∥ρ∥22I3−ρρT) dν with I3 the identity matrix and ρρT the matrix product of Rectangular matrix multiplication and the identity matrix In, including zero-sized shapes.

The mass distribution is centred when μ(ν)=0. Under the Axiom of Countable Choice ACω (The Axiom of Countable Choice (ACω)), each of the integrals above is a finite real number: on B‾R(0) one has ∣ρj∣≤R and ∣ρjρk∣≤R2, and ν(R3)<+∞; the precise statement and proof are Finiteness of the moments of a bounded finite Borel measure on R3 ↗, which depends on this definition only for its notation. The assumption is used there exactly once, to obtain the Borel measurability of the polynomial integrands from the published continuity criterion; every later item that invokes this finiteness carries the assumption explicitly.

Remarks

  • Nothing physical is asserted. "Mass distribution", "total mass" and "inertia matrix" are names for the mathematical objects just defined. No postulate that a physical body is described by such a measure, no identification of ν with a measured mass, and no mechanical law is part of this definition; the physical reading is supplied by the classical-mechanics items that consume it, with their own hypotheses.

  • Generality. The measure need not be absolutely continuous with respect to Lebesgue measure and need not be atomless: finitely many point masses, a surface density, and a volume density are all special cases. The bounded-support hypothesis makes every polynomial moment of degree at most two finite; without it the second moment could diverge.

  • Why the first moment matters. Being centred is a condition on the coordinates in which the measure is expressed: it says that the origin of the body coordinate system has been placed at the centre of mass of the distribution. A physical consumer that uses this definition must state that its body coordinates are so placed; the general translation behaviour of μ and I is not asserted here.

Depends on

Dependency tree · 2 levels

Sources