Production and Characterization of Additively Manufactured Radiator Panels With Integral Branching Heat Pipes for High-Temperature Heat Rejection

Emerging concepts for fission surface power and nuclear electric propulsion necessitate lightweight, mechanically robust, and thermally efficient heat rejection radiators. State-of-the-art intermediate-temperature (~400 K) composite radiator assemblies have been developed based on titanium-water heat pipes bonded to metal, graphite, and carbon-fiber-based panels. NASA has identified a need for new radiator concepts that can operate at even higher temperatures (500 – 600 K), minimize thermal resistances and thermal stress failures at bond interfaces, and approach areal densities of 2 – 3 kg m_-2. To meet these needs, our team is developing additively manufactured (AM) radiator panels with integral branching wicking heat pipe networks. Water is selected as the working fluid for this temperature range. Based on simulations and thermal vacuum experiments, these branching embedded heat pipe networks can efficiently distribute heat over panels for finned surface efficiencies of η_f >70% at T_H = 500 K input heat. This paper first presents laser powder-bed fusion AM strategies to produce embedded porous structures for wicking heat pipes in Inconel 718 and titanium alloys (commercially pure and Ti-6Al-4V alloys). Post-build chemical and thermal treatments are described that yield hydrophilic wicking surfaces for operation with water. Transient rate-of-rise experiments with water and acetone are reported that yield estimates for AM wick porosity (ϵ), permeability (K), and effective pore radius (^r_pore). Based on the wick characterization results, small prototype radiator panels (75 × 125 mm) with integrated heat pipe networks were manufactured. Heat rejection performance data are presented from cold thermal vacuum testing, with heat input temperatures up to ~510 K. Future efforts will focus on improving heat pipe performance, optimizing radiator mass, and evaluating larger panels to assess scalability.