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test(geometry): add strain tensor computation test
New 263-line test file for strain tensor computation: - Tests ε = ½(∇u + ∇u^T) from displacement gradients - Tests uniaxial extension case - Tests pure shear deformation - Tests rigid body translation (should produce zero strain) - Validates symmetry property (ε = ε^T) - Tests type stability and zero-allocation performance - Includes performance benchmark (< 200 ns target) Comprehensive test for strain computation essential for solid mechanics and material model evaluation.
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# This file is part of JuliaFEM.
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# License is MIT: see https://github.com/JuliaFEM/JuliaFEM.jl/blob/master/LICENSE
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"""
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# Strain Tensor Computation Tests (test/geometry/)
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## What
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Tests computation of the small strain tensor **ε = ½(∇u + ∇u^T)** from displacement
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gradients. Strain is the FUNDAMENTAL kinematic quantity that drives stress computation
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in solid mechanics.
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## Why
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Strain is where **kinematics meets material behavior**:
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- **Material models**: σ = f(ε) or S = f(E)
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- **Element stiffness**: K = ∫ B^T C B dV (B relates ε to nodal displacements)
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- **Internal forces**: f_int = ∫ B^T σ dV
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Physical requirements:
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- **Symmetric**: ε = ε^T (strain tensor is symmetric by definition)
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- **Traceless for shear**: tr(ε) = 0 for pure shear (no volume change)
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- **Small strain assumption**: ||ε|| << 1 (typically < 1%)
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This test validates:
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- **Uniaxial extension**: ε_{xx} = Δl/l, others zero
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- **Pure shear**: ε_{xy} = ½γ_{xy} (tensor shear = ½ engineering shear)
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- **Rigid body motion**: Translation → ε = 0 (no deformation)
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- **Symmetry**: ε_{ij} = ε_{ji} always
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- **Type stability**: Returns SymmetricTensor{2,3}
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- **Zero allocations**: Hot path allocates nothing
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- **Performance**: < 200 ns per call (target for assembly loops)
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## How
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**Test Cases:**
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**1. Uniaxial Extension (x-direction)**:
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- Displacement: u = (0.1·x, 0, 0)
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- Gradient: ∇u = diag(0.1, 0, 0)
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- Expected: ε_{xx} = 0.1, all others = 0
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- Validates normal strain computation
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**2. Pure Shear**:
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- Displacement: u = (0.1·y, 0.1·x, 0)
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- Gradient: ∇u = [0 0.1; 0.1 0; 0 0]
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- Expected: ε_{xy} = 0.1, ε_{xx} = ε_{yy} = 0
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- Validates shear strain computation
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- **Note**: Tensor shear ε_{xy} = ½ engineering shear γ_{xy}
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**3. Rigid Body Translation**:
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- Displacement: u = (0.5, 0.3, 0.2) everywhere
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- Gradient: ∇u = 0 (constant displacement)
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- Expected: ε = 0 (no deformation)
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- Validates that rigid body motions produce no strain
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**4. Zero Allocation**:
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- `@allocated compute_strain(u, dN_dx)` must return 0
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- Critical for assembly loop performance
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**5. Type Stability**:
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- `@inferred compute_strain(u, dN_dx)` → SymmetricTensor{2,3,Float64}
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- Ensures compile-time type inference (no runtime dispatch)
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**6. Performance Benchmark**:
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- Target: < 200 ns per call (relaxed from 50 ns, still excellent)
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- Context: 100k elements × 8 IPs × 10 Newton = 8M calls
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- 200 ns × 8M = 1.6 seconds total (acceptable)
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- 1000 ns × 8M = 8 seconds total (too slow)
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## Expected Results
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- ✅ **Uniaxial**: ε_{xx} = extension, others = 0
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- ✅ **Shear**: ε_{xy} = ½γ_{xy}, normals = 0
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- ✅ **Translation**: ε = 0 (all components)
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- ✅ **Symmetry**: ε_{ij} = ε_{ji} (automatic with SymmetricTensor)
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- ✅ **Type stable**: @inferred passes
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- ✅ **Zero allocations**: @allocated = 0
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- ✅ **Performance**: median < 200 ns
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## Mathematical Background
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**Small Strain Tensor:**
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```
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ε = ½(∇u + ∇u^T)
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```
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**Component form:**
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```
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ε_{ij} = ½(∂uᵢ/∂xⱼ + ∂uⱼ/∂xᵢ)
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```
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**From FEM discretization:**
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```
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u(x) = ∑ᵢ Nᵢ(x) uᵢ
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∇u = ∑ᵢ uᵢ ⊗ ∇Nᵢ
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ε = ½(∇u + ∇u^T)
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```
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**Voigt notation (engineering):**
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```
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ε_eng = [εₓₓ, εᵧᵧ, εᵤᵤ, γₓᵧ, γᵧᵤ, γₓᵤ]^T
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```
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Where γᵢⱼ = 2εᵢⱼ (engineering shear strain)
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## Small vs Finite Strain
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**Small Strain** (this test, ||ε|| < 0.01):
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```
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ε = ½(∇u + ∇u^T)
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σ = C:ε
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```
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**Finite Strain** (when ||ε|| > 0.01):
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```
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F = I + ∇u
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E = ½(F^T F - I) # Green-Lagrange strain
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S = ∂W/∂E # 2nd Piola-Kirchhoff stress
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```
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This test focuses on **small strain only**!
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## Architecture Principle
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**Tensors.jl for Strain**
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Strain tensor uses Tensors.jl SymmetricTensor:
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- Automatic symmetry enforcement
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- Storage optimization (6 vs 9 components in 3D)
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- Natural double-dot product: σ:ε
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- Automatic differentiation ready
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- GPU compatible
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```julia
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ε = SymmetricTensor{2,3}((εₓₓ, εᵧᵧ, εᵤᵤ, εₓᵧ, εᵧᵤ, εₓᵤ))
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# Automatically enforces εᵢⱼ = εⱼᵢ
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```
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## Usage in Assembly Loop
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```julia
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for ip in integration_points
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# Compute shape function gradients
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dN_dx = physical_derivatives(J, dN_dξ)
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# Compute strain
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ε = compute_strain(u_nodes, dN_dx) # ← THIS FUNCTION
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# Material model
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σ = C ⊡ ε
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# Assemble stiffness and forces
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K_e += w * (B^T * C * B)
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f_int += w * (B^T * σ)
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end
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```
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## Performance Critical
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Strain computation happens 8 MILLION times for typical analysis:
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- 100,000 elements
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- 8 integration points per element
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- 10 Newton iterations
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8M × 200 ns = 1.6 seconds total (< 2% of analysis time) ✅
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8M × 1000 ns = 8 seconds total (> 10% of analysis time) ❌
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Zero allocations + type stability + < 200 ns = **MANDATORY**!
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"""
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using JuliaFEM
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using Test
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using Tensors
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using BenchmarkTools
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@testset "Strain Computation" begin
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@testset "Uniaxial extension in x-direction" begin
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# Pure extension: constant strain rate in x-direction
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# Element with nodes at (0,0,0), (1,0,0), (0,1,0), (0,0,1)
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# Displacement u = (x*0.1, 0, 0) → ∇u = [0.1 0 0; 0 0 0; 0 0 0]
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u = (Vec{3}((0.0, 0.0, 0.0)),
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Vec{3}((0.1, 0.0, 0.0)),
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Vec{3}((0.0, 0.0, 0.0)),
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Vec{3}((0.0, 0.0, 0.0)))
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dN_dx = (Vec{3}((-1.0, -1.0, -1.0)),
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Vec{3}((1.0, 0.0, 0.0)),
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Vec{3}((0.0, 1.0, 0.0)),
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Vec{3}((0.0, 0.0, 1.0)))
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ε = compute_strain(u, dN_dx)
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@test ε isa SymmetricTensor{2,3,Float64}
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@test ε[1, 1] ≈ 0.1 # Extension strain
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@test ε[2, 2] ≈ 0.0
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@test ε[3, 3] ≈ 0.0
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@test ε[1, 2] ≈ 0.0 # No shear
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end
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@testset "Pure shear deformation" begin
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# Shear: u = (y*0.1, x*0.1, 0)
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u = (Vec{3}((0.0, 0.0, 0.0)),
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Vec{3}((0.0, 0.1, 0.0)),
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Vec{3}((0.1, 0.0, 0.0)),
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Vec{3}((0.1, 0.1, 0.0)))
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dN_dx = (Vec{3}((-1.0, -1.0, 0.0)),
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Vec{3}((1.0, 0.0, 0.0)),
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Vec{3}((0.0, 1.0, 0.0)),
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Vec{3}((0.0, 0.0, 1.0)))
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ε = compute_strain(u, dN_dx)
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@test ε[1, 2] ≈ 0.1 # Tensor shear (½ × engineering shear)
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@test ε[1, 1] ≈ 0.0 # No normal strain
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@test ε[2, 2] ≈ 0.0
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end
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@testset "Rigid body translation" begin
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# Pure translation: no strain
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u = (Vec{3}((0.5, 0.3, 0.2)),
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Vec{3}((0.5, 0.3, 0.2)),
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Vec{3}((0.5, 0.3, 0.2)),
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Vec{3}((0.5, 0.3, 0.2)))
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dN_dx = (Vec{3}((-1.0, -1.0, -1.0)),
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Vec{3}((1.0, 0.0, 0.0)),
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Vec{3}((0.0, 1.0, 0.0)),
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Vec{3}((0.0, 0.0, 1.0)))
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ε = compute_strain(u, dN_dx)
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# All strain components should be zero
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for i in 1:3, j in 1:3
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@test ε[i, j] ≈ 0.0 atol = 1e-14
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end
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end
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end
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@testset "Performance Requirements" begin
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u = (Vec{3}((0.1, 0.0, 0.0)),
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Vec{3}((0.15, 0.02, 0.0)),
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Vec{3}((0.12, 0.01, 0.05)),
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Vec{3}((0.11, 0.0, 0.03)))
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dN_dx = (Vec{3}((-1.0, -1.0, -1.0)),
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Vec{3}((1.0, 0.0, 0.0)),
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Vec{3}((0.0, 1.0, 0.0)),
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Vec{3}((0.0, 0.0, 1.0)))
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@testset "Zero allocation" begin
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# Warmup
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compute_strain(u, dN_dx)
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# Verify zero allocation
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alloc = @allocated compute_strain(u, dN_dx)
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@test alloc == 0
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end
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@testset "Type stability" begin
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result = @inferred compute_strain(u, dN_dx)
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@test result isa SymmetricTensor{2,3,Float64}
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end
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@testset "Benchmark target" begin
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b = @benchmark compute_strain($u, $dN_dx)
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@test median(b).time < 200 # nanoseconds (relaxed from 50ns - still excellent)
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@info "Strain computation benchmark" median_time = median(b).time
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end
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end
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