Damped vibration & damping ratio
API · /vibration-api
Vibration & Natural Frequency API
Single-degree-of-freedom vibration (spring-mass-damper) maths as an API, computed locally and deterministically. The natural endpoint gives the undamped natural frequency of a spring-mass system, ωn = √(k/m), fn = ωn/2π and the period T = 1/fn, and solves for whichever of the stiffness, mass or natural frequency you leave out. The damped endpoint analyses a damped system from the stiffness, mass and either a damping coefficient or a damping ratio: it returns the critical damping coefficient cc = 2√(km), the damping ratio ζ = c/cc, the classification (underdamped, critically damped or overdamped), and — for an underdamped system — the damped natural frequency ωd = ωn·√(1−ζ²), its period, and the logarithmic decrement δ = 2πζ/√(1−ζ²). The pendulum endpoint gives the period and frequency of a simple pendulum, T = 2π·√(L/g), and solves the length from a target period, with gravity adjustable. Everything is computed locally and deterministically, so it is instant and private. Ideal for mechanical, structural and earthquake-engineering tools, machine-condition-monitoring and isolation-design apps, instrument and clock design, and physics education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is discrete spring-mass-damper vibration; for standing waves on strings and in air columns use a standing-wave API.
API health
healthy- Uptime
- 100.00%
- Server probes · 24h
- Avg latency
- 92 ms
- Server probes · 24h
- Subscribers
- 3,990
- active
- Total calls
- 36
- last 7 days
Pricing
Pick a tier — billed monthly, cancel anytime.
Free
Free
- 2,000 calls / month
- 2 requests / second
- Hard cap (429 above quota, no overage)
- Undamped natural frequency (omega_n, f_n) endpoint
- Deterministic SI-unit results, no upstream latency
- 2,000 calls/month for prototyping
Starter
€9.00 /month
- 25,000 calls / month
- 5 requests / second
- Hard cap (429 above quota, no overage)
- Damped natural frequency + damping ratio outputs
- Logarithmic decrement & critical damping coefficient
- 25,000 calls/month for small design tools
- Email support
Pro
€24.00 /month
- 150,000 calls / month
- 15 requests / second
- Hard cap (429 above quota, no overage)
- Full forced-response: transmissibility & magnification factor
- Resonance & half-power bandwidth Q-factor
- 150,000 calls/month for production CAE workflows
- Priority support
Mega
€75.00 /month
- 751,000 calls / month
- 40 requests / second
- Hard cap (429 above quota, no overage)
- Batch SDOF sweeps across stiffness/mass/damping grids
- Highest throughput for simulation pipelines
- 750,000 calls/month
- 99.9% uptime SLA & dedicated support
Built by
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O-ring seal-design maths as an API, computed locally and deterministically — the squeeze, gland and stretch numbers an engineer or maker designs a seal to. The squeeze endpoint gives the compression that makes the seal: squeeze = (cross-section − gland depth) ÷ cross-section, so a 0.139-inch cord in a 0.113-inch deep groove is squeezed 18.7 %, and it grades the result — roughly 10–16 % suits dynamic (reciprocating) seals and 15–30 % static ones — and, given the groove width, the gland fill percentage, which should stay under about 85 % so the rubber has room to expand from heat or fluid swell. The gland endpoint works the other way: from the cross-section and whether the seal is static or dynamic (or a target squeeze) it returns the groove depth and a width sized for about 70 % fill — typically 1.3 to 1.5 times the cross-section — plus a corner radius. The stretch endpoint checks installation: stretch = (mating diameter − o-ring ID) ÷ ID, which should stay under about 5 % on a rod because stretching thins the cross-section and steals squeeze. Everything is computed locally and deterministically, so it is instant and private. Ideal for mechanical-engineering, hydraulics, pneumatics, vacuum and product-design app developers, seal-selection and gland-design tools, and CAD plugins. Pure local computation — no key, no third-party service, instant. Inches or millimetres. Live, nothing stored. 3 compute endpoints.
api.oanor.com/oring-api
Gear Ratio API
Gear-train ratio, speed and torque maths as an API, computed locally and deterministically. The ratio endpoint computes the gear ratio of a single pair from the driver and driven tooth counts (or pitch diameters), ratio = N_driven/N_driver, classifies it as a reduction (more torque, less speed) or an overdrive, and — given an input speed and torque — returns the output speed (input/ratio) and the output torque (input·ratio·efficiency). The train endpoint computes a compound gear train: the overall ratio is the product of the individual stage ratios, and it returns each stage ratio, the output speed and torque, noting that idler gears change only the direction of rotation, not the ratio. The solve endpoint finds the missing one of the input speed, the output speed and the ratio from the other two — for example, the ratio needed to drop a 1500 rpm motor to a 500 rpm output. Everything is computed locally and deterministically, so it is instant and private. Ideal for drivetrain, robotics and machine-design tools, gearbox and transmission selection, bicycle and vehicle gearing, and mechanical-engineering education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is gear-train ratio and torque; for spur-gear tooth geometry use a spur-gear API.
api.oanor.com/gearratio-api
Belt Conveyor API
Belt-conveyor design maths as an API, computed locally and deterministically. The capacity endpoint computes the throughput of a belt conveyor — the volumetric capacity Q = A·v·3600 (m³/h) from the belt cross-section and speed, and the mass capacity Q·ρ/1000 (t/h) from the bulk density — and, when only the belt width is given, estimates the cross-section as A ≈ load_factor·width². The power endpoint computes the drive power as the sum of the horizontal friction power, μ·g·(material + 2·belt + idler mass per metre)·length·speed, and the vertical lift power, ṁ·g·height, then divides by the drive efficiency to give the motor power. The tension endpoint computes the belt tensions from the effective tension Te = P/v: the tight-side tension T1 = Te·e^(μθ)/(e^(μθ)−1) and the slack-side tension T2 = T1 − Te, using the Euler-Eytelwein grip of the belt on the drive pulley. Everything is computed locally and deterministically, so it is instant and private. Ideal for bulk-materials-handling, mining and plant-design tools, conveyor selection and motor sizing, and mechanical-engineering education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is a simplified belt-conveyor model; for rope/belt capstan friction use a capstan API and for belt-drive geometry use a belt-drive API.
api.oanor.com/conveyor-api
Pulley System API
Pulley and block-and-tackle mechanics as an API, computed locally and deterministically. The advantage endpoint computes the mechanical advantage of a pulley system — the ideal MA equals the number of rope parts supporting the load, which is also the velocity ratio — and returns the effort needed to hold or raise a load, effort = load/(n·efficiency), the length of rope that must be pulled (n times the lift height) and the work in and out. The friction endpoint models a real block and tackle where every sheave loses a little tension: the mechanical advantage becomes MA = e·(1−eⁿ)/(1−e) for a per-sheave efficiency e (≈0.96 for a plain bearing, ≈0.98 for a ball bearing), so it returns the true MA, the overall efficiency and the extra effort friction costs you. The solve endpoint takes any two of the load, the effort and the number of rope parts and returns the third — for example, how many parts you need so a given person can raise a given load, or the heaviest load a winch can lift. Everything is computed locally and deterministically, so it is instant and private. Ideal for rigging, lifting and hoist-design tools, sailing, climbing and theatre-rigging apps, crane and winch sizing, and physics education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is pulley and block-and-tackle mechanics; for lever and moment balance use a lever API and for rope-around-a-drum capstan friction use a capstan API.
api.oanor.com/pulley-api
Frequently asked questions
Quick answers about pricing, quotas, and integration.
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Code snippets
Sign up to get an API key, then call any path under your slug.
curl https://api.oanor.com/vibration-api/SOME_PATH \
-H "x-oanor-key: oanor_test_..."
const res = await fetch("https://api.oanor.com/vibration-api/SOME_PATH", {
headers: { "x-oanor-key": "oanor_test_..." }
});
const data = await res.json();
$ch = curl_init("https://api.oanor.com/vibration-api/SOME_PATH");
curl_setopt($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/vibration-api/SOME_PATH",
headers={"x-oanor-key": "oanor_test_..."},
)
print(r.json())
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