GA-ASI & Conflux Technology to produce AM heat exchanger for RPAS
April 29, 2020
![](http://www.metal-am.com/wp-content/uploads/sites/4/2020/05/2017_SkyGuardian1200x600-web.jpg)
General Atomics Aeronautical Systems, Inc. (GA-ASI), a designer and manufacturer of Remotely Piloted Aircraft (RPA) systems, radars, and electro-optic and related mission systems, and affiliate of General Atomics, has partnered with Additive Manufacturing company Conflux Technology, Geelong, Victoria, Australia, to additively manufacture a heat exchanger for integration with GA-ASI’s line of Remotely Piloted Aircraft Systems (RPAS).
Conflux Technology is an Additive Manufacturing applications company that specialises in thermal and fluid engineering. The company is providing design expertise in the optimisation of additively manufactured heat exchangers to increase the performance of RPA.
According to GA-ASI, the Australian Government recently selected GA-ASI’s MQ-9B SkyGuardian® variant to provide the Armed RPAS for the Australian Defence Force (ADF) under Project Air 7003. The MQ-9 is said to have a proven ability in multi-role combat performance and capability to support ad-hoc communications networks and interoperability with Allies.
“GA-ASI and Conflux are developing novel and state-of-the-art thermal solutions for application to our existing and next-generation RPAS,” stated Linden Blue, GA-ASI CEO. “This will allow enhanced endurance and lower manufacturing cost, as well as more flexibility in our product design and integration.”
Michael Fuller, Conflux Technology CEO, commented, “Fundamental efficiency gains require heat transfer innovations. In Conflux we have a highly innovative engineering team that blends first principles thermo-fluid dynamics with design creativity and Additive Manufacturing process expertise.”
“Conflux heat exchangers derive their performance from highly complex geometries enabled by Additive Manufacturing. Our scientists and engineers, alongside their GA-ASI counterparts, will now develop heat exchange applications to improve fundamental efficiencies for GA-ASI’s RPA systems,” he concluded.