docs: Move user manual to docs/src/user/

- Relocate docs/user/ to docs/src/user/ - Contains user-facing documentation: - README.md (user manual index) - system_architecture.md (system overview) - Part of three-tier docs reorganization following Documenter.jl standard - Completes migration to docs/src/ structure
2026-09-26 03:44:45 +00:00 · 2025-11-10 22:22:00 +02:00
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+---
+title: "JuliaFEM User Manual"
+description: "Quick start guide and practical tutorials for end users"
+date: 2025-11-09
+author: "Jukka Aho"
+categories: ["user guide", "tutorial"]
+keywords: ["juliafem", "quick start", "tutorial", "examples"]
+audience: "end users"
+level: "beginner"
+type: "manual"
+---
+
+# JuliaFEM User Manual
+
+**Audience:** End users, engineers, students who want to run simulations and get results.
+
+This manual is designed to be **simple and practical** - get you from zero to running simulations as quickly as possible.
+
+## What's Here
+
+- **Quick Start:** Installation and first simulation in 5 minutes
+- **Tutorials:** Step-by-step guides for common problems
+- **Examples:** Pre-built simulations you can run and modify
+- **API Reference:** Function documentation (what does this do?)
+- **Troubleshooting:** Common errors and how to fix them
+
+## What's NOT Here
+
+- Deep theory (see `docs/book/` for that)
+- How to contribute code (see `docs/contributor/` for that)
+- Internal architecture details
+
+## Philosophy
+
+**"Just show me how to solve my problem."**
+
+We assume you:
+- Have a problem to solve (heat transfer, elasticity, contact)
+- Want working code, not lectures
+- Will read theory when YOU need it, not when WE think you should
+
+## Getting Help
+
+1. Start with the Quick Start
+2. Find an example similar to your problem
+3. Modify it to fit your needs
+4. If stuck, check Troubleshooting
+5. Still stuck? Ask on GitHub Discussions
+
+---
+
+**Next:** Start with [Quick Start](quickstart.md) or browse [Examples](../examples/)
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+---
+title: "JuliaFEM System Architecture: Core Concepts"
+date: 2025-11-10
+author: "JuliaFEM Team"
+status: "Authoritative"
+last_updated: 2025-11-10
+tags: ["architecture", "design", "concepts", "user-guide"]
+---
+
+## Introduction
+
+This document explains **why** JuliaFEM's core data structures exist and **how**
+they work together. Every struct has a purpose, every abstraction has a reason.
+
+**Target audience:** Users who want to understand the system deeply,
+contributors implementing new physics, anyone asking "why is it designed this
+way?"
+
+---
+
+## The Big Picture: Method of Lines
+
+JuliaFEM follows the **Method of Lines** approach to FEM:
+
+1. **Spatial discretization** (FEM) → System of ODEs
+2. **Time discretization** (if transient) → Nonlinear algebraic equations
+3. **Linearization** (Newton) → Linear system solve
+4. **Repeat** until convergence
+
+**Key insight:** Separate concerns cleanly at each level!
+
+```text
+Mesh + Physics → Element Assembly → Global System → Solver → Solution
+  ↓                    ↓                  ↓            ↓         ↓
+Geometry          Material Models    Sparse Matrix  Krylov    u(x,t)
+```
+
+---
+
+## Core Abstractions
+
+### 1. `Element` - The Geometric Container
+
+**Role:** Holds geometric and connectivity information for a single finite element.
+
+**What it knows:**
+
+- Element type (Tri3, Quad4, Tet10, etc.)
+- Node connectivity
+- Basis functions (shape functions)
+- Integration points
+
+**What it does NOT know:**
+
+- Physics equations
+- Material properties
+- Boundary conditions
+
+**Why this design?**
+
+- ✅ Element is **reusable** across different physics (same Tet10 for elasticity, heat, fluid)
+- ✅ Geometry is **immutable** (connectivity doesn't change during analysis)
+- ✅ **Type-stable dispatch** on element type enables compiler optimizations
+
+**Example:**
+
+```julia
+# Create a 10-node tetrahedral element
+nodes = [1, 5, 12, 23, 14, 8, 19, 27, 31, 16]
+element = Element(Tet10, nodes)
+
+# Element knows its topology
+@assert nnodes(element) == 10
+@assert dim(element) == 3
+
+# But element doesn't know about stress, temperature, etc.
+# That's the job of Physics!
+```
+
+---
+
+### 2. `Physics` - The Equation Selector (RENAMED from "Problem")
+
+**Role:** Multiple dispatch tag + configuration for physical equations.
+
+**What it is:**
+
+- A **type** that selects assembly methods via multiple dispatch
+- A **struct** that holds physics-specific configuration
+- A **name provider** for field names ("displacement", "temperature", etc.)
+
+**What it is NOT:**
+
+- ❌ Not the mesh (that's separate)
+- ❌ Not the material models (those are parameters)
+- ❌ Not the solver (that's a different layer)
+
+**Why "Physics" instead of "Problem"?**
+
+- ✅ **Positive connotation** ("solve physics" vs "solve problem")
+- ✅ **Accurate description** (selecting physical equations)
+- ✅ **Clear role** (what physics are we simulating?)
+
+**Types of Physics:**
+
+```julia
+# Elasticity: Solves ∇⋅σ = ρü + b
+struct ElasticityPhysics <: AbstractPhysics
+    formulation::Symbol    # :plane_stress, :plane_strain, :continuum
+    finite_strain::Bool    # Geometric nonlinearity
+    geometric_stiffness::Bool  # σ-dependent stiffness for buckling
+    store_fields::Vector{Symbol}  # Output fields to save
+end
+
+# Heat transfer: Solves ∇⋅(k∇T) = ρcₚ∂T/∂t + Q
+struct HeatPhysics <: AbstractPhysics
+    formulation::Symbol    # :steady_state, :transient
+    nonlinear::Bool        # Temperature-dependent properties
+    store_fields::Vector{Symbol}
+end
+
+# Contact mechanics: Solves contact constraints
+struct ContactPhysics <: AbstractPhysics
+    algorithm::Symbol      # :penalty, :lagrange, :augmented_lagrange
+    friction_model::Symbol # :coulomb, :frictionless
+    # ...
+end
+```
+
+**Multiple Dispatch in Action:**
+
+```julia
+# Compiler selects correct assembly method based on physics type!
+
+function assemble!(assembly, physics::ElasticityPhysics, elements, time)
+    # Elasticity-specific assembly:
+    # - Compute strain from displacement
+    # - Call material model: ε → (σ, 𝔻)
+    # - Build stiffness matrix K and force vector f
+end
+
+function assemble!(assembly, physics::HeatPhysics, elements, time)
+    # Heat transfer-specific assembly:
+    # - Compute temperature gradient
+    # - Call thermal conductivity: ∇T → q
+    # - Build capacity matrix C and conductivity matrix K
+end
+
+function assemble!(assembly, physics::ContactPhysics, elements, time)
+    # Contact-specific assembly:
+    # - Detect penetration
+    # - Compute contact forces
+    # - Build constraint equations
+end
+```
+
+**This is Julia's superpower!** No runtime type checks, no vtables, just fast compiled code for each physics type.
+
+---
+
+### 3. `Material` - The Constitutive Model
+
+**Role:** Maps kinematic quantities to stress/flux/response.
+
+**Interface (Elasticity example):**
+
+```julia
+abstract type AbstractMaterial end
+abstract type AbstractMaterialState end
+
+# Material computes: (ε, state_old, Δt) → (σ, 𝔻, state_new)
+function compute_stress(
+    material::AbstractMaterial,
+    ε::SymmetricTensor{2,3},
+    state_old::AbstractMaterialState,
+    Δt::Float64
+) -> Tuple{SymmetricTensor{2,3}, SymmetricTensor{4,3}, AbstractMaterialState}
+    # Returns: (stress, tangent, state_new)
+end
+```
+
+**Why separate from Physics?**
+
+- ✅ **Modularity:** Change material without touching assembly code
+- ✅ **Testability:** Unit-test materials independently
+- ✅ **Performance:** Compiler specializes on material type
+- ✅ **Clarity:** Material logic isolated from kinematics
+
+**Material examples:**
+
+```julia
+# Stateless material (no history)
+struct LinearElastic <: AbstractMaterial
+    λ::Float64  # Lamé parameter
+    μ::Float64  # Shear modulus
+end
+
+# Stateful material (history-dependent)
+struct PerfectPlasticity <: AbstractMaterial
+    E::Float64   # Young's modulus
+    ν::Float64   # Poisson's ratio
+    σ_y::Float64 # Yield stress
+end
+
+struct PlasticityState{T} <: AbstractMaterialState
+    εₚ::SymmetricTensor{2,3,T}  # Plastic strain
+    α::T                         # Equivalent plastic strain
+end
+```
+
+**Performance:** 20-70 ns per material evaluation (validated Nov 10, 2025)
+
+---
+
+### 4. `Assembly` - The Global System Builder
+
+**Role:** Accumulate element contributions into global matrices/vectors.
+
+**What it holds:**
+
+- Global stiffness matrix `K` (sparse)
+- Global force vector `f`
+- (Optional) Mass matrix `M`, damping `C`, geometric stiffness `Kg`
+
+**What it does:**
+
+- Pre-allocates sparse matrix structure
+- Accumulates element contributions: `K += Kₑ`, `f += fₑ`
+- Handles DOF mapping: local element DOFs → global system DOFs
+
+**Why separate from Physics?**
+
+- ✅ **Reusability:** Same Assembly struct for all physics types
+- ✅ **Optimization:** Pre-allocated structure, efficient COO→CSC conversion
+- ✅ **Parallelism:** (Future) Thread-safe assembly with color-based locking
+
+**Example:**
+
+```julia
+# Create assembly
+assembly = Assembly()
+
+# Loop over elements
+for element in elements
+    # Compute element stiffness and force
+    Kₑ, fₑ = assemble_element(physics, element, time)
+    
+    # Get global DOF indices
+    gdofs = get_gdofs(element)
+    
+    # Add to global system
+    add!(assembly.K, gdofs, gdofs, Kₑ)
+    add!(assembly.f, gdofs, fₑ)
+end
+
+# Solve global system
+u = assembly.K \ assembly.f
+```
+
+---
+
+### 5. `IntegrationPoint` - The Quadrature Point
+
+**Role:** Location and weight for numerical integration.
+
+**What it knows:**
+
+- Position in reference element: `ξ ∈ [-1,1]ᵈⁱᵐ`
+- Integration weight: `w`
+- Index/ID for state storage
+
+**What it does NOT know:**
+
+- Material state (that's stored per-element per-IP)
+- Stress/strain (that's computed on-the-fly)
+
+**Why this design?**
+
+- ✅ **Immutable:** Integration points never change
+- ✅ **Topology-specific:** Different rules for Tri3 vs Quad4
+- ✅ **Pre-computed:** Created once, reused forever
+
+**Example:**
+
+```julia
+# Get integration points for element type
+ips = integration_points(Gauss{2}, Quad4)
+
+# Each IP knows position and weight
+for ip in ips
+    ξ = ip.ξ      # Position: NTuple{2, Float64}
+    w = ip.weight # Weight: Float64
+    
+    # Evaluate basis functions at this point
+    N, ∇N_ref = evaluate_basis(basis, ξ)
+    
+    # Do integration: ∫f dΩ ≈ ∑ᵢ f(ξᵢ)⋅w(ξᵢ)
+end
+```
+
+---
+
+### 6. `BasisInfo` - The Shape Function Cache
+
+**Role:** Pre-allocated workspace for basis function evaluation.
+
+**What it caches:**
+
+- Basis function values `N`
+- Gradients in reference config `∇N_ref`
+- Gradients in current config `∇N`
+- Jacobian `J`, determinant `detJ`
+
+**Why cache?**
+
+- ✅ **Zero allocation:** Reuse same arrays for every element
+- ✅ **Type stability:** All sizes known at compile time
+- ✅ **Performance:** Avoid repeated memory allocation
+
+**Example:**
+
+```julia
+# Create cache for Tet10 elements
+bi = BasisInfo(Tet10)
+
+# Reuse for every element
+for element in elements
+    for ip in integration_points(element)
+        # Evaluate into pre-allocated cache
+        eval_basis!(bi, element.X, ip)
+        
+        # Access cached results
+        N = bi.N          # Shape functions
+        ∇N = bi.grad      # Gradients ∂N/∂x
+        w = ip.weight * bi.detJ  # Integration weight
+    end
+end
+```
+
+---
+
+## Data Flow: From Mesh to Solution
+
+### Step 1: Problem Setup
+
+```julia
+# Define physics
+physics = ElasticityPhysics(
+    formulation = :continuum,
+    finite_strain = false,
+    store_fields = [:stress, :strain]
+)
+
+# Define material
+material = LinearElastic(E=200e9, ν=0.3)
+
+# Create elements with material
+elements = [Element(Tet10, conn) for conn in connectivity]
+for el in elements
+    el.material = material
+    el.states_old = [NoState() for _ in 1:n_integration_points]
+    el.states_new = [NoState() for _ in 1:n_integration_points]
+end
+```
+
+### Step 2: Assembly Loop
+
+```julia
+assembly = Assembly()
+
+for element in elements
+    # Get element data
+    X = element.geometry  # Nodal coordinates
+    u = element.displacement  # Nodal displacements
+    
+    # Initialize element matrices
+    Kₑ = zeros(ndofs, ndofs)
+    fₑ = zeros(ndofs)
+    
+    # Integration point loop
+    for (ip_idx, ip) in enumerate(element.integration_points)
+        
+        # 1. KINEMATICS: u → ε
+        ∇N = shape_function_gradients(element, ip)
+        ε = compute_strain_from_gradients(∇N, u)
+        
+        # 2. MATERIAL: ε → (σ, 𝔻, state)
+        state_old = element.states_old[ip_idx]
+        σ, 𝔻, state_trial = compute_stress(material, ε, state_old, Δt)
+        
+        # 3. ASSEMBLY: (∇N, σ, 𝔻) → (Kₑ, fₑ)
+        w = integration_weight(ip)
+        accumulate_stiffness!(Kₑ, ∇N, 𝔻, w)
+        accumulate_internal_forces!(fₑ, ∇N, σ, w)
+        
+        # DON'T update states yet (Newton iterations!)
+    end
+    
+    # 4. GLOBAL: Kₑ → K, fₑ → f
+    gdofs = get_gdofs(element)
+    add!(assembly.K, gdofs, gdofs, Kₑ)
+    add!(assembly.f, gdofs, fₑ)
+end
+```
+
+### Step 3: Solve
+
+```julia
+# Linear solve: K⋅Δu = f
+Δu = assembly.K \ assembly.f
+
+# Newton iteration (if nonlinear)
+while norm(residual) > tolerance
+    # Re-assemble with trial displacement
+    u_trial = u_old + Δu
+    
+    # Solve linearized system
+    Δu = assembly.K \ assembly.f
+    
+    # Update
+    u_trial += Δu
+end
+
+# Converged! Commit state
+for element in elements
+    element.states_old .= element.states_new
+end
+```
+
+---
+
+## Design Principles
+
+### 1. Separation of Concerns
+
+**Each struct has ONE job:**
+
+- `Element` → Geometry
+- `Physics` → Equation selection
+- `Material` → Constitutive model
+- `Assembly` → Global system
+- `Solver` → Linear algebra
+
+**Benefits:**
+
+- ✅ Easy to test (unit test each component)
+- ✅ Easy to extend (add new material without touching assembly)
+- ✅ Easy to optimize (profile each layer independently)
+
+### 2. Type Stability
+
+**Every function has concrete return type:**
+
+```julia
+# ✅ GOOD: Compiler knows return type
+function compute_stress(m::LinearElastic, ε) -> Tuple{SymmetricTensor{2,3}, SymmetricTensor{4,3}, NoState}
+    # ...
+end
+
+# ❌ BAD: Compiler doesn't know (Dict lookup)
+function compute_stress(element, ip)
+    stress = element.fields["stress"]  # Unknown type!
+    # ...
+end
+```
+
+**Performance impact:** 10-100× speedup from type stability alone!
+
+### 3. Zero Allocation
+
+**Hot paths allocate NOTHING:**
+
+```julia
+# Pre-allocate once
+bi = BasisInfo(Tet10)
+Kₑ = zeros(30, 30)
+
+# Reuse in loop (zero allocations!)
+for element in elements
+    fill!(Kₑ, 0.0)
+    for ip in integration_points(element)
+        eval_basis!(bi, X, ip)  # Fills cache, no allocation
+        # ... assembly logic
+    end
+end
+```
+
+**Validated:** All material models achieve 0 bytes allocation (Nov 10, 2025)
+
+### 4. Multiple Dispatch
+
+**Use Julia's type system:**
+
+```julia
+# Same function name, different implementations
+assemble!(assembly, ::ElasticityPhysics, elements, time)
+assemble!(assembly, ::HeatPhysics, elements, time)
+assemble!(assembly, ::ContactPhysics, elements, time)
+
+# Compiler generates specialized code for each!
+```
+
+**No runtime overhead, no vtables, just fast native code.**
+
+---
+
+## Common Questions
+
+### Q: Why not use classes with methods?
+
+**A:** Julia's multiple dispatch is more powerful than OOP:
+
+```julia
+# OOP way (single dispatch on first argument)
+element.assemble(physics)  # Only element type matters
+
+# Julia way (multiple dispatch on ALL arguments)
+assemble!(assembly, physics, element, time)  # All types matter!
+```
+
+This enables:
+
+- Compiler specialization on ALL argument types
+- Adding new methods without modifying existing types
+- True separation of concerns (no "god objects")
+
+### Q: Why immutable structs?
+
+**A:** Performance and safety:
+
+- Structs with all concrete types are stack-allocated
+- Immutability enables compiler optimizations
+- No accidental mutation bugs
+
+**Rule:** Use immutable structs unless you NEED mutability (like Assembly accumulation)
+
+### Q: Why Tensors.jl instead of matrices?
+
+**A:** Performance and clarity:
+
+- `SymmetricTensor{2,3,Float64,6}` is **stack-allocated** (48 bytes on stack)
+- Regular `Matrix{Float64}` is **heap-allocated** (pointer + malloc)
+- Code looks like math: `σ = λ⋅tr(ε)⋅I + 2μ⋅ε`
+- Type stability: Compiler knows exact size at compile time
+
+---
+
+## Summary: The JuliaFEM Way
+
+**Core philosophy:**
+
+1. **Separate concerns** - Each struct has ONE job
+2. **Type stability** - Compiler knows ALL types
+3. **Zero allocation** - Hot paths reuse memory
+4. **Multiple dispatch** - Compiler specializes for each case
+5. **Immutability** - Stack allocation + safety
+6. **Tensors.jl** - Mathematical clarity + performance
+
+**Result:** Fast, maintainable, extensible FEM code that looks like the math it implements.
+
+---
+
+## Further Reading
+
+- **`docs/book/material_modeling.md`** - Material model implementation guide
+- **`docs/book/elasticity_refactoring_plan.md`** - Elasticity system design
+- **`docs/book/element_architecture.md`** - Element composition philosophy
+- **`llm/ARCHITECTURE.md`** - Eight-layer system architecture
+- **`llm/VISION_2.0.md`** - Project vision and philosophy
+
+---
+
+**Last Updated:** November 10, 2025  
+**Status:** Authoritative (reflects current design decisions and implementation)