Handle effort & mechanical advantage
API · /screwjack-api
Screw Jack API
Power-screw (lead-screw and screw-jack) mechanics as an API, computed locally and deterministically. The torque endpoint computes the torque to raise and to lower a load on a power screw from the load, the mean thread diameter, the lead (given directly or as pitch × starts) and the coefficient of friction: T_raise = (W·dm/2)·(L + π·μ′·dm)/(π·dm − μ′·L), with the matching lower torque, the lead angle, the efficiency (W·L ÷ 2π·T_raise) and whether the screw is self-locking (it is when the effective friction is at least the tangent of the lead angle). Square threads are the default; pass a thread angle (for example 29° for an ACME thread) and it applies the effective friction μ/cos(half-angle). The effort endpoint turns that torque into the hand force on a lever or handle and the resulting mechanical advantage. The travel endpoint relates turns, lift distance and — with an rpm — the linear speed and time. Lengths are in millimetres, load in newtons and torque in newton-metres. Everything is computed locally and deterministically, so it is instant and private. Thread friction only — add collar/thrust friction separately. Ideal for machine-design and mechanism tools, jack, press, vice and clamp design, maker and robotics projects, and engineering calculators. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is power-screw mechanics; for the geometry of a screw thread use a thread API and for bolt tightening torque use a torque API.
API salute
salutare- Tempo di attività
- 100.00%
- Sondaggi del server · 24 ore su 24
- Latenza media
- 76 ms
- Sondaggi del server · 24 ore su 24
- Abbonati
- 4,613
- attiva
- Chiamate totali
- 76
- ultimi 7 giorni
Prezzi
Scegli un livello: fatturazione mensile, annullamento in qualsiasi momento.
Free
Gratis
- 1,500 chiamate/mese
- 2 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 15,035 calls/month
- 2 req/sec
- Torque + effort + travel
- No credit card
Starter
€9.00 /mese
- 18,000 chiamate/mese
- 6 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 25.45k llamadas/mes
- 8 req/seg
- Eficiencia, autobloqueo, ACME
- Soporte por correo electrónico
Pro
€24.00 /mese
- 120,000 chiamate/mese
- 15 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 297.5k calls/month
- 20 req/sec
- Machine-design pipelines
- Priority support
Mega
€74.00 /mese
- 600,000 chiamate/mese
- 40 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 1.53M llamadas/mes
- 50 req/seg
- Escala de plataforma
- SLA dedicado
Costruito da
Correlato APIs
Altro APIs con tag sovrapposti.
Slider-Crank Mechanism API
Slider-crank (piston-crank) mechanism kinematics as an API, computed locally and deterministically. The position endpoint takes the crank radius, the connecting-rod length and the crank angle from top dead centre and returns the exact piston displacement from TDC, x = r(1−cosθ) + l(1 − √(1−λ²sin²θ)) with λ = r/l, the piston-pin distance from the crank axis, the connecting-rod swing angle φ = asin(λ·sinθ), the stroke (2r), the rod ratio n = l/r and the fraction of stroke travelled. The velocity endpoint adds the crank speed (as rpm or angular velocity) and returns the exact piston velocity, v = ω·[r·sinθ + r·λ·sinθcosθ/√(1−λ²sin²θ)], and the piston acceleration from the standard two-term approximation a ≈ r·ω²·(cosθ + λ·cos2θ) — the inertia term engine designers use for balancing. The geometry endpoint summarises the whole mechanism: the stroke, the rod ratio, the top- and bottom-dead-centre positions, the maximum connecting-rod angle asin(λ), and — with a speed — the mean piston speed 2·stroke·(rev/s). Everything is computed locally and deterministically, so it is instant and private. Ideal for engine, compressor and pump-mechanism design tools, robotics and linkage simulation, CNC and animation, and mechanical-engineering education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is slider-crank linkage kinematics; for rotational energy use a flywheel API and for shaft torsion use a torsion API.
api.oanor.com/crankslider-api
Railway Tractive Effort API
Railway train-performance maths as an API, computed locally and deterministically — the tractive-effort, resistance and adhesion numbers a railway engineer, train planner or rail-sim developer rates motive power with. The tractive-effort endpoint gives the pulling force a locomotive develops = 375 × horsepower × efficiency ÷ speed (mph), the classic hyperbolic curve where a constant-power loco pulls hardest at low speed and tapers as it accelerates — 4,000 hp at 25 mph and 82 % efficiency is about 49,200 lbf at the rail. The resistance endpoint gives the forces a train fights: grade resistance ≈ 20 lb per ton per 1 % of grade (the weight component along the slope, the dominant force on a hill — a 5,000-ton train on a 1 % grade fights 100,000 lbf) plus curve resistance ≈ 0.8 lb per ton per degree of curve from flange friction. The adhesion endpoint gives the hard ceiling: however much power a loco has, it can only pull as hard as the wheels grip — maximum starting tractive effort = the adhesion coefficient (≈ 0.25 dry, more with sand) × the weight on the driving wheels, so 200 tons on the drivers is about 100,000 lbf before slip. Everything is computed locally and deterministically, so it is instant and private. Ideal for rail-operations and motive-power planning tools, train-simulator and railfan apps, and transport-engineering utilities. Pure local computation — no key, no third-party service, instant. Excludes the speed-dependent Davis rolling/air resistance. 3 compute endpoints. For highway curve geometry use a horizontal-curve API.
api.oanor.com/railway-api
Worm Gear API
Worm-gear engineering maths as an API, computed locally and deterministically — the ratio, lead-angle and efficiency numbers a machine designer or millwright sizes a worm drive with. The ratio endpoint gives the reduction = wheel teeth ÷ worm starts, so a single-start worm on a 40-tooth wheel is a big 40:1 reduction in one compact stage — the high ratio in a small package is the whole appeal of a worm drive. The geometry endpoint gives the lead (= starts × axial pitch, with axial pitch = π × module) and the lead angle = atan(lead ÷ (π × worm pitch diameter)), and tests for self-locking: a small lead angle (roughly under 5–6° for typical steel-on-bronze) means the wheel cannot back-drive the worm — invaluable for hoists and holding loads, at the cost of efficiency. The efficiency endpoint gives the mesh efficiency when the worm drives = tan(lead angle) ÷ tan(lead angle + friction angle), which is low for the small lead angles that give big ratios — often 50–70 %, which is why worm gears run warm and need good lubrication — while high-lead multi-start worms reach 90 %+; when the lead angle drops to the friction angle the drive becomes self-locking. Everything is computed locally and deterministically, so it is instant and private. Ideal for mechanical-design and gearbox tools, machine-building and CAD utilities, and engineering calculators. Pure local computation — no key, no third-party service, instant. Confirm self-locking dynamically — vibration can unlock a marginal pair. 3 compute endpoints. For spur gears use a spur-gear API; for a general ratio a gear-ratio API.
api.oanor.com/wormgear-api
Hydraulic Cylinder API
Hydraulic-cylinder engineering maths as an API, computed locally and deterministically — the force, speed and oil-volume numbers a fluid-power designer, machine builder or hydraulics technician sizes a cylinder with. The force endpoint gives the push and pull from the bore, rod diameter and working pressure: extending, the oil acts on the full bore area, so the cylinder is strongest pushing out; retracting, it acts only on the annulus left by the rod, giving less force — a 100 mm bore with a 56 mm rod at 160 bar pushes about 125.7 kN out but pulls only 86.3 kN back, which is why a press or an excavator does its hard work on the extend stroke. The speed endpoint gives the piston speed from the pump flow (speed = flow ÷ area), so extending is the slower stroke and retracting the faster, the trade-off every circuit designer balances against force. The volume endpoint gives the swept oil volume per stroke for extend and retract, the rod displacement and the bore-to-annulus area ratio — the differential (regeneration) ratio used to speed the extend stroke in a regen circuit — so the pump, tank and lines can be sized for the larger volume. Everything is computed locally and deterministically, so it is instant and private. Ideal for fluid-power and machine-design tools, hydraulics-sizing calculators, mobile- and industrial-equipment utilities, and engineering apps. Pure local computation — no key, no third-party service, instant. Ideal-area estimates — allow for friction, back-pressure and efficiency. 3 compute endpoints. For Pascal force-multiplication use a hydraulics API; for valve sizing a valve-flow (Cv/Kv) API.
api.oanor.com/hydrauliccylinder-api
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Frammenti di codice
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curl https://api.oanor.com/screwjack-api/SOME_PATH \
-H "x-oanor-key: oanor_test_..."
const res = await fetch("https://api.oanor.com/screwjack-api/SOME_PATH", {
headers: { "x-oanor-key": "oanor_test_..." }
});
const data = await res.json();
$ch = curl_init("https://api.oanor.com/screwjack-api/SOME_PATH");
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_HTTPHEADER, ["x-oanor-key: oanor_test_..."]);
$response = curl_exec($ch);
import requests
r = requests.get(
"https://api.oanor.com/screwjack-api/SOME_PATH",
headers={"x-oanor-key": "oanor_test_..."},
)
print(r.json())
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