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reactor-core-sim

reactor neutronics, depletion and safety thermal-hydraulics for core design and licensing

CASMO/SIMULATE, Serpent, OpenMC, VERA/MPACT, RELAP5

SystemTechniques · 16Primitives · 35 reactor-core-sim Batch checkpoint restartdistributed · medium: Large batch jobs (end-of-day, settlement, payroll runs) that checkpoint and restart idempotentlyHalo exchangedistributed · medium: Each rank stores its block plus a border copy of its neighbours' edge cells, refreshed by small messages every step; communication scales with block surface, not volume.›Pipe network hydraulicsembedded · medium: Solve pipe-network flows and heads (Hazen-Williams, gradient method) for water systemsFmi co simulationnumerics · medium: Couple simulation units (FMUs) with a master algorithm: step negotiation, rollback, algebraic loopsGmresnumerics · medium: GMRES with restarts: Arnoldi, Givens rotations, for nonsymmetric sparse systemsSparse direct solvernumerics · medium: Solve sparse Ax = b exactly by reordering, symbolic analysis, numeric LLᵀ/LU and triangular solves; fill-in, not flops per entry, decides the cost.›Multigroup cross section processingphysics · medium: Collapse continuous-energy nuclear data to multigroup constants with temperature broadeningNewton root findingnumerics · low: Linearize at the guess and jump to the tangent root; quadratic convergence near a simple root, made robust by brackets (1D) or line search.›Sparse matrices (CSR)numerics · low: Compressed sparse row stores only nonzeros as row pointers, column indices and values; SpMV streams them once, so it is memory-bandwidth bound.›Stiff solvers (implicit, BDF)numerics · low: Implicit steps solve a small nonlinear system so fast decaying modes stay stable at any step size; BDF methods are the stiff-ODE workhorse.›Conjugate gradientnumerics · low: Krylov iteration for symmetric positive definite Ax = b using one matrix-vector product and two dot products per step; converges in about √κ iterations.›Matrix exponential ode solvernumerics · low: Linear decay-chain ODE systems solved with matrix exponentials (CRAM), optionally coupled to a changing sourceMonte Carlo integrationnumerics · low: Estimate an expectation by averaging random samples; error falls as σ/√N in any dimension, and variance reduction (antithetic, control variates, importance sampling) shrinks σ.›Multigridnumerics · low: Smooths high-frequency error on the fine grid and solves the smooth remainder on coarser grids; O(n) elliptic solves at any resolution.›Power iteration eigenvaluenumerics · low: Source-iteration or Arnoldi solve for the dominant eigenvalue and eigenvector of a critical systemIdempotency keysfinance · low: Client-chosen unique key per logical operation, stored with a request fingerprint and the final response, so retries replay the first result instead of acting twice.›Write-ahead logstorage · low: Append each change to a checksummed sequential log and fsync it before touching data pages; the basis of crash durability in nearly every database.›Cron schedulingsystems · low: Cron expression parsing and next-fire-time computation, with catch-up and time-zone rulesEager rendezvous protocoldistributed · low: MPI point-to-point: eager sends for small messages, rendezvous handshake for large onesRdmanetworking · low: RDMA verbs over InfiniBand/RoCE: queue pairs, memory registration, one-sided opsZero-copy I/Onetworking · low: Move bytes between files, sockets and NICs by passing page references instead of copying through user space: sendfile, splice, MSG_ZEROCOPY, kTLS.›Calling conventions abicompilers · low: System V, Windows x64 and AAPCS64 ABIs: argument registers, stack frames, struct passing, FFIAdaptive Runge-Kutta (Dormand-Princ…numerics · low: An embedded 5(4) Runge-Kutta pair estimates each step's error for free and resizes the step to meet a tolerance; the default non-stiff solver.›+ 9 more techniques+ 19 more primitives

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