Cross-corpus inventory of units, quantities, and domain-specific numeric parameters

Cross-corpus inventory of notable units, quantities, and parameters.

Terrain/erosion: Large-scale uplift/erosion experiments use 50×50 km terrain, uplift 5×10^-4 m/y, erosion coefficient 5.61×10^-7 y^-1, target summit ≈2000 m, and Δt=2.5×10^5 y #ZHQFZP stream-power applicability is 10^5–10^7 y and tens–hundreds km #MSXUGH commonly m=0.5,n=1 #EKXATA with empirical h_max[km]=2.244u/k #MNZNZU Thermal erosion often uses 30° talus #9VNYCT or varied 6°–54° limits #6N825C mountains form around 50 iterations and stabilize in 100–300 #W7JZEK Analytical erosion examples use 512² cells, 50 m spacing, t=4.6 My, 460 simulation steps of 10,000 y versus 43 fixed-point steps #E6X4P6 shrinking cells 50→25→12 m raises simulation iterations 230→460→980 #EQTM8J Examples span 200 ky–1.6 My #LBNKBW 100/200/300 ky at 30 m spacing #Z3MXM7 and a 4.6 My mountain at 5/15/25 km scales #N9TEH4 FastFlow compares Δt=1,000 y explicit to 20,000 y implicit; a 10 My landscape takes 7.2 s vs 0.5 s #M53PTE while 10 iterations/0.1 s represent 700 ky on 512² and 100 iterations take 0.7 s #YVMH2N Routing runs under 55 ms to 4096² #BDZQP4 with 5× flow and 34–52× depression-routing speedups at 1024² #8QGM6W Real 1 m DEM examples contain 383,918 and 8,445,644 basins #NEL8YN

Hydrology/rivers: A recurring empirical relation is discharge φ[m³/s]=0.42A^0.69 for drainage area A[m²] #VG86AP #HS22AT Procedural Riverscapes spans a 3×3 km terrain, ≈4 km river, >40,000 primitives, 100 m input DEM pixels, and 10 cm output detail #ACDG5B primitives sampled every 50 cm and construction trees generated in ≈15 ms #YCESD5 rendering >70 fps at 1920×1080 #GZJUCV Storage ranges from 22 kB for 50 m to 2.7 MB for ≈4 km; primitives cost 50–90 bytes #9DU2N2 Compared offline production used 3 cm precision, 4.5M particles, 200M voxels, 20 s output, and 165 total work/simulation hours #2KNSHV Priority-Flood tests include 3 m DEMs of 152M and 318M cells #8ERHN4 a larger benchmark covered 72,500 km² and ≈8×10^9 cells, averaging 16.8% and maxing 37.2% speedup #XR7Z7G with up to 37% improvement and one CPU matching six processors #ED94U3

Water/waves/rendering: Surface Wavelets simulates 4×4 km at 60 fps #WKY9MT using 4096 cells per spatial axis (≈1 m spacing; #UG8PZG 16 directions and usually 1–4 wavenumber samples #WV3FXP Despite the coarse grid it resolves 2 cm wavelengths; an equivalent direct heightfield would bottom out at 0.5 m under Nyquist #BEDUYL Precomputation gives ≈4.7×, 60→280 fps #23W9S2 a profile-buffer optimization raised evaluation 1.8→275 fps, reported as 233× #82HGFN Four wavenumber groups roughly quadruple cost and reduce 70→20 fps #9AHGRG Water viscosity is given as 10^-6 m/s in the dissipation model #NHQBFC unit as printed should be checked dimensionally). Breaking-wave tests use 160k–200k grid points at 40–75 fps; simulation consumes 80% of runtime #RTYCL9 Layered particle water uses 20k–64k particles at 1280×720 and 112 bits/pixel of intermediate buffers #LUVPJR with runtime split ≈23.12/24.4/27.43/25.05% across depth, thickness, smoothing, and composition over 6k frames #754PPX Advected river textures report 60–120 fps, average 85 #8KBMFE illustrate 1.3 m/s flow #JS4LBU use a 15° flow-hint cutoff #BMKDJR and set particle lifetime 1.5 s plus travel limit 5% of river length #K7SCA8 Scalable river animation tests 25×25 km at 800×600 with 20 px particle/sprite radius #EUX776 Halftone foam adds <3% load over five-minute tests #V5XDSY surveyed historical ocean methods report ≈20–30 fps on GeForce 2 #2RHVZB and ≈100 fps on GeForce 3 #KAFWZ7

Roads/racing: Procedural road routing discretizes position×orientation as n²×m #43XVF5 tunnel/bridge masks use 50–300 m lengths on a 300² grid at 10 m spacing, comparing 2728 visited points to 50 stochastic samples #WJSTC2 and produces paths in <1 s on 100² grids #JLGV3R Racing optimization covers a 4.5 km circuit, converges in 4–5 iterations, about 30 s each #BPF8Q6 experimental laps are 138.6 s versus 139.2 s and a professional 137.7 s, with μ=0.90 and peak 0.9g #8AQDAB Each full iteration is 26 s across 1843 timesteps versus hours for nonlinear optimization #CK2TWF controller rate is 200 Hz #3LSFWC

Trails/movement: Mountain-walker footprints use a 10 cm square footprint #J2KKMV Simulations use Gmax=200 m^-1, visibility 10 m, 50 footfalls (versus real-world several hundred), weathering 1000 s (versus days), walker speeds 0.5–1.5 m/s, a 25×10 m slope, and 25,000 walkers #WUZ6YE Zigzags appear with forbidden angles 25° uphill/10° downhill, weathering 1500 s, and α≳0.45 #AJSDD6 Stability tests use Δt 0.5/0.25 s and Δx=Δy 5/2.5 cm #HWVUS7 Biomechanics: a 10° incline may require 60° hip flexibility vs 30° flat; observed ankle max ≈24° #54E5UT Field slopes cited around 1:8 and 1:2 #GNDKEV Trail design suggests 8–10% for family/senior users where 12–16% may be structurally sustainable #D33DUB hillslope:trail grade ratios around 2:1–3:1 #SFWHTE and a worked example adds 500 ft to reduce 200 ft rise over 2000 ft from 10% to 8% #76SGWC Sudden changes include 5→10% and 7→20% #247BPE paired clinometer readings should agree within 1 percentage point #8CNUPW

Domain-specific abstract quantities: Wholeness case studies use 1,800 Manhattan axial lines and 166,479 Swedish streets, finding power-law exponents around 2+ #LUZ5UR Living Images reports recursively defined substructures ≈3% of pixels, ≤2% decomposable, and >3–4 recursive levels #D2C54Y #XZBXLL Head/tail breaks continues while the head is ≤40% #MKYDT2 Platformer physics uses Castlevania ≈3.7 tiles/s, Mario 10 tiles/s, others ≈5.5, and suggests 4–10 tiles/s as playable #A6TZBP