Desert RATS 2011: Human and robotic exploration of near-Earth asteroids

The Desert Research and Technology Studies (D-RATS) 2011 field test involved the planning and execution of a series of exploration scenarios under operational conditions similar to those expected during a human exploration mission to a near-Earth asteroid (NEA). The focus was on understanding the operations tempo during simulated NEA exploration and the implications of communications latency and limited data bandwidth. Anchoring technologies and sampling techniques were not evaluated due to the immaturity of those technologies and the inability to meaningfully test them at D-RATS. Reduced gravity analogs and simulations are being used to fully evaluate Space Exploration Vehicle (SEV) and extravehicular (EVA) operations and interactions in near-weightlessness at a NEA as part of NASA's integrated analogs program. Hypotheses were tested by planning and performing a series of 1-day simulated exploration excursions comparing test conditions all of which involved a single Deep Space Habitat (DSH) and either 0, 1, or 2 SEVs; 3 or 4 crewmembers; 1 of 2 different communications bandwidths; and a 50-second each-way communications latency between the field site and Houston. Excursions were executed at the Black Point Lava Flow test site with a remote Mission Control Center and Science Support Room at Johnson Space Center (JSC) being operated with 50-second each-way communication latency to the field. Crews were composed of astronauts and professional field geologists. Teams of Mission Operations and Science experts also supported the mission simulations each day. Data were collected separately from the Crew, Mission Operations, and Science teams to assess the test conditions from multiple perspectives. For the operations tested, data indicates practically significant benefits may be realized by including at least one SEV and by including 4 versus 3 crewmembers in the NEA exploration architecture as measured by increased scientific data quality, EVA exploration time, capability assessment ratings, and consensus acceptability ratings provided by Crew, Mission Operations, and Science teams. A combination of text and voice was used to effectively communicate over the communications latency, and increased communication bandwidth yielded a small but practically significant improvement in overall acceptability as rated by the Science team, although the impact of bandwidth on scientific strategic planning and public outreach was not assessed. No effect of increased bandwidth was observed with respect to Crew or Mission Operations team ratings of overall acceptability.     

Modeling satellite battery aging for an operational satellite simulator

During the satellite’s operations, simulation tools perform an important role in ensuring the space mission success. In this sense, the models implemented in the context of an operational satellite simulator that enables analysis of health status and maintenance during operations shall reflect the current satellite behavior with high fidelity. Moreover, it is complicated to obtain all analytical models of a satellite’s disciplines, considering its aging. This paper proposes an Artificial Neural Network (ANN) to reproduce the battery voltage behavior of a large sun-synchronous remote sensing satellite, the CBERS-4, currently in operation. Using the genetic algorithm to find the best network architecture of ANN, the neural model for this application presented an error of less than 1%, demonstrating its feasibility to obtain a high fidelity model for an operational simulator enabling extend analyses. The paper addresses advanced techniques aligned with the space industry’s future, increasing the ability to analyze a large amount of data and improve the space system’s operation.     

Configurationmodelofpartial repairablesparesunder batch ordering policy based on inventory state

Rational planning of spares configuration project is an effective approach to improve equipment availability as well as reduce life cycle cost （LCC）. With an analysis of various impacts on support system, the spares demand rate forecast model is constructed. According to systemic analysis method, spares support effectiveness evaluation indicators system is built, and then, initial spares configuration and optimization method is researched. To the issue of discarding and con-sumption for incomplete repairable items, its expected backorders function is approximated by Laplace demand distribution. Combining the （s-1, s） and （R, Q） inventory policy, the spares resup-ply model is established under the batch ordering policy based on inventory state, and the optimi-zation analysis flow for spares configuration is proposed. Through application on shipborne equipment spares configuration, the given scenarios are analyzed under two constraint targets：one is the support effectiveness, and the other is the spares cost. Analysis reveals that the result is consistent with practical regulation;therefore, the model＇s correctness, method＇s validity as well as optimization project＇s rationality are proved to a certain extent.