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The C-Gauge is made of a 3D-printed aluminum body with strain gauges attached to the inner and outer walls of the connecting beam. The legs of the gauge attach firmly to the cord. When the cord is stretched, the tension in the cord goes through the legs and into the beam, causing it to bend. This bending creates a tension and compression stress in the bottom and top surface of the beam, respectively. The strain gauges capture the tension and compression, which are then used to determine the tension in the cord. The use of multiple strain gauges mitigates any torsion loading of the gauge and provides a direct measurement of the axial tension load of the cord. The C-Gauge is a low-profile, non-invasive system that can be installed onto an existing cord in a system (e.g., the suspension, reefing, or riser lines in a parachute) without the need to remove or re-install the cord. It is small and lightweight and does not add stiffness or weight to the cord and thus does not affect the dynamics of the parachute or the structural response of the system. The C-Gauge can be scaled to larger and smaller sizes to measure larger and smaller load capabilities, dependent on the cord. The C-Gauge is at a TRL 4 (component and/or breadboard validation in a laboratory environment) and it is now available for your company to license and develop into a commercial product. Please note that NASA does not manufacture products itself for commercial sale.

The MAchine learning ESTimations for uRban Operations (MAESTRO) system is a novel approach that couples commodity sensors with advanced algorithms to provide real-time onboard local wind and kinematics estimations to a vehicle's guidance and navigation system. Sensors and computations are integrated in a novel way to predict local winds and promote safe operations in dynamic urban regions where Global Positioning System/Global Navigation Satellite System (GPS/GNSS) and other network communications may be unavailable or are difficult to obtain when surrounded by tall buildings due to multi-path reflections and signal diffusion. The system can be implemented onboard an Unmanned Aerial Systems (UAS) and once airborne, the system does not require communication with an external data source or the GPS/GNSS. Estimations of the local winds (speed and direction) are created using inputs from onboard sensors that scan the local building environment. This information can then be used by the onboard guidance and navigation system to determine safe and energy-efficient trajectories for operations in urban and suburban settings. The technology is robust to dynamic environments, input noise, missing data, and other uncertainties, and has been demonstrated successfully in lab experiments and computer simulations.