methodNumerical methods

Numerical integration

Approximate accumulated quantity over an interval with a stated quadrature rule and convergence check.

Working definition

Numerical integration approximates a definite integral from sampled function values. Accuracy depends on smoothness, interval partition, singularities, oscillation, and the chosen quadrature rule; adaptive methods allocate evaluations according to estimated local error.

Notation

I = ∫ₐᵇ f(x) dxI ≈ Σ wᵢf(xᵢ)

Assumptions

  • The integral exists under the chosen definition.
  • The integrand can be evaluated accurately.
  • Discontinuities and singularities are isolated.

Invariants

  • Additivity holds across exact subinterval partitions.
  • Units equal integrand units times integration-variable units.
  • Convergence should stabilize under refinement.

Reproducible procedure

  • Partition at known discontinuities.
  • Apply an appropriate fixed or adaptive rule.
  • Repeat with tighter tolerance or an independent rule.

Error and boundary controls

  • Quadrature estimates can fail on unresolved spikes.
  • Cancellation can hide large local errors.
  • Model and measurement uncertainty remain separate.

What this does not establish

An accurately accumulated exposure or signal does not by itself identify causation or predictive usefulness.

Explicit applications

1 cross-domain bridges

Semiconductor manufacturingphysical model

Accumulated thermal exposure

Integrate a time-varying temperature or power profile to compare qualified process exposure.

Inputs

  • temperature time series
  • time intervals
  • response model

Outputs

  • integrated exposure
  • numerical error estimate
  • coverage gaps

Transformation: Apply declared quadrature over valid segments and propagate sensor uncertainty.

Limit: Equal integrated exposure need not imply equal material response when kinetics are nonlinear.

Open connected system →

Authoritative references

  1. [1]DLMF Chapter 3: Numerical Methods · National Institute of Standards and Technology

    Establishes: Reference definitions, algorithms, convergence conditions, and error terms for interpolation, quadrature, differentiation, and nonlinear equation solving.

    Boundary: A numerical method is reliable only under its stated regularity, conditioning, precision, and convergence assumptions; the reference does not validate any domain interpretation.

  2. [2]NIST Technical Note 1297: Guidelines for Evaluating and Expressing Measurement Uncertainty · National Institute of Standards and Technology

    Establishes: A measurement framework for identifying uncertainty components, combining standard uncertainties, and reporting expanded uncertainty with declared coverage.

    Boundary: Reported uncertainty describes the measurement model and included components. It is not a guarantee that all systematic errors or model inadequacies were found.

Related mathematical concepts