#cooling

Heatsink and thermal-resistance maths for electronics as an API, computed locally and deterministically. The junction endpoint computes the junction temperature of a component from its power dissipation, the ambient temperature and the thermal-resistance chain, Tj = Ta + P·(Rθjc + Rθcs + Rθsa) — junction-to-case, case-to-sink (the interface material) and sink-to-ambient — and also reports the case and sink temperatures and, given a maximum junction temperature, the headroom. The required endpoint solves the largest heatsink thermal resistance you may use to stay under a junction limit, Rθsa = (Tj_max − Ta)/P − Rθjc − Rθcs, and flags when no heatsink can do it. The power endpoint gives the maximum power a device can dissipate for a given thermal path, P = (Tj_max − Ta)/Rθtotal. Everything is computed locally and deterministically, so it is instant and private. Ideal for electronics, power-supply and PCB-design app developers, heatsink selection and thermal-budget tools, and engineering education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is conduction thermal-resistance; for convective Newton cooling use a cooling API.

api.oanor.com/heatsink-api

Heating and cooling degree-day maths as an API, computed locally and deterministically. The daily endpoint computes the heating degree days, HDD = max(0, base − mean), and the cooling degree days, CDD = max(0, mean − base), for a single day from a base temperature and the daily mean — or the minimum and maximum, since the mean is taken as their average. The period endpoint sums the degree days over a list of daily temperatures (means or min/max pairs), returning the total HDD and CDD, the count of heating and cooling days and the average temperature — the standard way to characterise a heating or cooling season. The energy endpoint turns degree days into an energy estimate: the heat delivered is UA·DD·24/1000 kWh from the building heat-loss coefficient, the fuel or electricity input is that divided by the boiler efficiency (or a heat-pump COP), and — with an energy price — the cost. Everything is computed locally and deterministically, so it is instant and private. Ideal for building-energy, HVAC and facilities tools, heating-bill and fuel-budget estimation, weather-normalisation and energy-benchmarking apps, and engineering education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is degree-day demand estimation; for U-value and heat-loss fabric calculations use a U-value API.

api.oanor.com/degreeday-api

HVAC sizing maths as an API, computed locally and deterministically from standard rule-of-thumb factors. The cooling endpoint estimates the air-conditioner load for a room — in BTU per hour, tons of cooling and kilowatts — from the floor area (in square feet or metres, or length × width) using a baseline of about 20 BTU/h per square foot, with adjustments for the number of occupants, a kitchen, sun exposure and ceiling height. The heating endpoint estimates the heating load from the area and a climate zone (mild through very cold) or a custom BTU per square foot. The convert endpoint converts between BTU per hour, tons of cooling, kilowatts and watts (one ton = 12,000 BTU/h ≈ 3.517 kW). Everything is computed locally and deterministically, so it is instant and private. These are rule-of-thumb estimates in the EnergyStar style — a proper Manual J load calculation accounting for insulation, windows and local climate is recommended for a real installation. Ideal for HVAC and home-improvement tools, air-conditioner and heater sizing guides, smart-home and energy apps, and contractor quoting. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is HVAC sizing; for appliance running cost use an energy-cost API.

api.oanor.com/hvac-api