CurrentLoop: use a better justified measurement algorithm

'course the best way to justify it is with tests: hopefully those will
come shortly.
This commit is contained in:
2022-08-01 06:12:16 -07:00
parent 527814e38a
commit 06379ffd30
2 changed files with 42 additions and 22 deletions

View File

@@ -3,6 +3,7 @@ use crate::real::{Real as _, ToFloat as _};
use crate::cross::vec::{Vec3, Vec3u}; use crate::cross::vec::{Vec3, Vec3u};
use crate::sim::AbstractSim; use crate::sim::AbstractSim;
use serde::{Serialize, Deserialize}; use serde::{Serialize, Deserialize};
use std::ops::AddAssign;
// TODO: do we really need both Send and Sync? // TODO: do we really need both Send and Sync?
pub trait AbstractMeasurement<S>: Send + Sync { pub trait AbstractMeasurement<S>: Send + Sync {
@@ -243,6 +244,24 @@ impl Current {
} }
} }
// TODO: clean up these FieldSample types
#[derive(Default)]
struct TupleSum<T>(T);
impl<T0: Default + AddAssign, T1: Default + AddAssign> std::iter::Sum for TupleSum<(T0, T1)> {
fn sum<I>(iter: I) -> Self
where I: Iterator<Item = Self>
{
let mut s = Self::default();
for TupleSum((a0, a1)) in iter {
s.0.0 += a0;
s.0.1 += a1;
}
s
}
}
#[derive(Default)] #[derive(Default)]
struct FieldSample(u32, f64, Vec3<f64>); struct FieldSample(u32, f64, Vec3<f64>);
@@ -323,33 +342,30 @@ impl<R> CurrentLoop<R> {
} }
impl<R: Region + HasCrossSection> CurrentLoop<R> { impl<R: Region + HasCrossSection> CurrentLoop<R> {
fn data<S: AbstractSim>(&self, state: &S) -> f32 { fn data<S: AbstractSim>(&self, state: &S) -> f32 {
// i use a statistical lens for this: // - current exists as a property of a 2d surface.
// 1. current is the rate of flow of charge into a surface. // - the user has provided us a 3d volume which behaves as though it's an extruded surface:
// 2. in any context where it makes sense to think of current, the current through each // for any point in the volume we can query the normal vector of the cross section
// cross-sectional **is the same**. // containing that point.
// 3. each point in our 3d region belongs to exactly one cross-sectional surface. // - we choose that measuring the "current" on such a volume means to measure the average
// 4. so, given a point: what's the expected current through the cross section it belongs to? // current through all its cross sections (for most boring materials, each
// - answer: that point's current density times the cross section's area. // cross section has nearly identical current).
// 5. average the above over the whole volume, and you get an "average current". // - therefore, enumerate the entire volume and compute the "net" current (the sum over
// // each cell of whatever current in that cell is along the cross-section normal).
// we're sampling uniformly over the cell space -- not the set of cross sections. // then divide by the number of complete cross sections we measured, to average.
// - however, if all cross sections have equal area, this is equivalent. let feature_area = state.feature_size() * state.feature_size();
// sampling all points (instead of just a single point): let TupleSum((net_current, cross_sections)) = state.map_sum_over_enumerated(&self.region, move |coord: Meters, _cell| {
// 1) removes bias from step #4: current *within* a cross section is not uniform, but if
// we sample every point within the cross section and weight them equally, then the
// average is the truth.
// 2) probably combats grid quantization / artifacting.
let FieldSample(num_samples, sum_cross_sectional_current, _current_vec) = state.map_sum_over_enumerated(&self.region, |coord: Meters, _cell| {
// `normal` represents both the size of the cross section (m^2) this cell belongs to, // `normal` represents both the size of the cross section (m^2) this cell belongs to,
// and the normal direction of the cross section. // and the normal direction of the cross section.
let normal = self.region.cross_section_normal(coord); // [m^2] let normal = self.region.cross_section_normal(coord); // [m^2]
// calculate the amount of normal current through this specific cell
let current_density = state.current_density(coord); // [A/m^2] let current_density = state.current_density(coord); // [A/m^2]
// now we have an estimation of the entire current flowing through the cross section let cross_sectional_current = feature_area * current_density.dot(normal.norm()); // [A]
// this cell belongs to. // keep track of how many cross sections we enumerate, since each additional cross
let cross_sectional_current = current_density.dot(normal.cast()); // [A] // sections represents a double-count of the current.
FieldSample(1, cross_sectional_current.cast(), current_density.cast()) let num_cross_sections_filled = feature_area / normal.mag();
TupleSum((cross_sectional_current, num_cross_sections_filled))
}); });
let mean_cross_sectional_current = sum_cross_sectional_current.cast::<f32>() / f32::from_primitive(num_samples); let mean_cross_sectional_current = net_current.cast::<f32>() / cross_sections;
mean_cross_sectional_current mean_cross_sectional_current
} }
} }

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@@ -107,6 +107,10 @@ pub trait Real:
self == Self::zero() self == Self::zero()
} }
fn inv(self) -> Self {
Self::one() / self
}
fn zero() -> Self; fn zero() -> Self;
fn one() -> Self; fn one() -> Self;
fn two() -> Self; fn two() -> Self;