Thermetrics Thermal Manikin Evaluates Climate Control Systems in Green Building Research

    SEATTLE, WA, June 02, 2015 /24-7PressRelease/ -- University Centre for Energy Efficient Buildings (UCEEB) plans to use as a human simulator for measuring and evaluating the performance of heating and air conditioning systems used in buildings.

Thermetrics won the contract to build a custom Newton 32-zone Newton thermal manikin with humidified external breathing capability.

UCEEB is an independent institute of the Czech Technical University in Prague. UCEEB's goal is to research and design buildings which are green, smart, reasonably-priced, and with a healthy interior climate.

As stated by the institute's founder, Professor Zden Bittnar, "Buildings represent an area with significant potential for energy savings and reduction of human impact on the environment, but it is also estimated that people spend up to 90% of their lives inside buildings - which means our health can be greatly influenced by the quality of the interior climate."

What makes the Newton thermal manikin ideal for environmental comfort research?

The UCEEB 32-zone Newton includes a temperature controlled and humidified breathing system that consists of two pneumatic cylinders which are cycled in and out by a servo linear actuator to replicate the cycle, frequency, and volume of human breathing. The breathing system connects to the manikin with hoses for inhaling and exhaling. Inside the manikin, a special manifold behind the face allows for breathing through the nose or mouth in any combination.

Thermetrics, LLC is a wholly owned subsidiary of Measurement Technology NW, dedicated to the design and manufacture of a wide range of precision instruments to measure and evaluate the thermal comfort of textiles, garments, and protective apparel. Our innovative Thermal and Automotive Manikins, Dry and Sweating Guarded Hotplates, and Radiant/Flame Test systems support all current industry test standards for thermal insulation, moisture permeability, and burn injury prediction.

# # #