RESKIT RSU72-0156 is a precisely replicated 230-gallon centerline fuel tank, specially designed for OV-10 Bronco model aircraft in A, B, and C variants at 1/72 scale. Manufactured using advanced 3D printing technology, it ensures the highest level of detail and accuracy to the original. This product is intended as an accessory for models of the United States Air Force (USAF) and other air forces operating this aircraft.

History and use: The OV-10 Bronco is a versatile aircraft renowned for its service during the Vietnam War and subsequent conflicts throughout the Cold War era. It was widely used by the USAF, USMC, and other air forces around the world, mainly performing reconnaissance missions, close air support, and artillery spotting. The 230-gallon centerline fuel tank enabled a significant increase in the operational range of the OV-10, especially during extended patrols and operations over vast areas, which was crucial during missions over Vietnam or the desert regions of the Middle East.

• Scale: 1/72
• Material: 3D printed (resin) for sharp details and easy processing
• Intended for: OV-10 Bronco (A, B, C) models – USAF and other air forces
• Quantity in set: 1 piece centerline tank
• Category: model accessories, 3D printed aircraft detail
• Historical period: Cold War (1960s, 70s, 80s) and later times

The RSU72-0156 tank model from RES/KIT is an excellent choice for modelers seeking faithful recreations of historical machines and for military aviation enthusiasts. The workmanship quality and the potential to enhance model realism make this product recommended both for advanced modelers and intermediate ones wishing to develop their skills.

Assembly difficulty level: 2/5 – The product requires basic modeling skills, resin processing, and painting.

The RESKIT RSU72-0156 tank allows for a professional upgrade of the OV-10 model, making it a perfect addition to both diorama setups and single aircraft builds. I highly recommend this accessory to all military aviation enthusiasts and those who value historical accuracy in their models.