Engineering topics

Wang, Liu

Publications and source records attributed to Wang, Liu.

3 records

DOE OSTI2015

Insensitive high-energy energetic structural material of tungsten-polytetrafluoroethylene-aluminum composites

Energetic structural material is a kind of materials that are inert under normal conditions but could produce exothermic chemical reaction when subjected to impact. This report shows a kind of energetic structural material of tungsten (W)-polytetrafluoroethylene (PTFE)-aluminum (Al) with density of 4.12 g/cm{sup 3}, excellent ductility and dynamic compressive strength of 96 MPa. Moreover, 50W-35PTFE-15Al (wt%) can exhibit a high reaction energy value of more than 2 times of TNT per unit mass and 5 times of TNT per unit volume, respectively, but with excellent insensitivity compared with traditional explosives. Under thermal conditions, the W-PTFE-Al composite can keep stable at 773 K. Under impact loading, when the strain rate up to ∼4820 s{sup −1} coupled with the absorbed energy per unit volume of 120 J/cm{sup 3}, deflagration occurs and combustion lasts for 500 μs. During impact compressive deformation, the PTFE matrix is elongated into nano-fibers, thus significantly increases the reaction activity of W-PTFE-Al composites. The nano-fiber structure is necessary for the reaction of W-PTFE-Al composites. The formation of PTFE nano-fibers must undergo severe plastic deformation, and therefore the W-PTFE-Al composites exhibit excellent insensitivity and safety. Furthermore, the reaction mechanisms of W-PTFE-Al composites in argon and in air are revealed.

36 MATERIALS SCIENCE↗

NASA NTRS2014

An Architecture to Enable Autonomous Control of Spacecraft

Autonomy is required for manned spacecraft missions distant enough that light-time communication delays make ground-based mission control infeasible. Presently, ground controllers develop a complete schedule of power modes for all spacecraft components based on a large number of factors. The proposed architecture is an early attempt to formalize and automate this process using on-vehicle computation resources. In order to demonstrate this architecture, an autonomous electrical power system controller and vehicle Mission Manager are constructed. These two components are designed to work together in order to plan upcoming load use as well as respond to unanticipated deviations from the plan. The communication protocol was developed using "paper" simulations prior to formally encoding the messages and developing software to implement the required functionality. These software routines exchange data via TCP/IP sockets with the Mission Manager operating at NASA Ames Research Center and the autonomous power controller running at NASA Glenn Research Center. The interconnected systems are tested and shown to be effective at planning the operation of a simulated quasi-steady state spacecraft power system and responding to unexpected disturbances.

space power systems↗

NASA NTRS1988

Robot path planning using a genetic algorithm

Robot path planning can refer either to a mobile vehicle such as a Mars Rover, or to an end effector on an arm moving through a cluttered workspace. In both instances there may exist many solutions, some of which are better than others, either in terms of distance traversed, energy expended, or joint angle or reach capabilities. A path planning program has been developed based upon a genetic algorithm. This program assumes global knowledge of the terrain or workspace, and provides a family of good paths between the initial and final points. Initially, a set of valid random paths are constructed. Successive generations of valid paths are obtained using one of several possible reproduction strategies similar to those found in biological communities. A fitness function is defined to describe the goodness of the path, in this case including length, slope, and obstacle avoidance considerations. It was found that with some reproduction strategies, the average value of the fitness function improved for successive generations, and that by saving the best paths of each generation, one could quite rapidly obtain a collection of good candidate solutions.

Cleghorn, Timothy F.↗