Journal of Aerospace Engineering

The objective of this research is to develop a microelectromechanical system (MEMS)-based intelligent hybrid Biaxial Strain Transducer (BiAST) sensor for predicting railroad fatigue life based on strain history. The developed BiAST prototype was deployed to collect real-time strain data from the full-scale test track at the Transportation Technology Center (TTCI), near Pueblo, Colorado. The collected strain data were analyzed using the “Binner” fatigue analysis program for counting the load cycles and estimating the fatigue life of a rail structure. Field-testing results of the BiAST were used to evaluate the BiAST prototype with respect to its repeatability, accuracy, and hybridization. BiAST was effective in detecting the dynamic response of a particular wheel and spurious overload events. BiAST can be used to detect passing wheels, train speed, and track condition.

The use of advanced embedded system technologies such as microelectromechanical system (MEMS) sensors and wireless communications hold great promise for measuring the response of civil structures to ambient and external disturbances. In this paper, the design of a high-performance, planar piezoresistive MEMS accelerometer is discussed in detail. The piezoresistive accelerometer possesses superior performance characteristics including low noise densities when measuring local structural responses characterized by high-frequency content. A low-cost wireless sensing unit, designed for automated structural monitoring, is utilized to record and wirelessly transmit measurements obtained by the piezoresistive accelerometer. To validate the performance of the wireless monitoring system including the interfaced piezoresistive accelerometer, a five degrees-of-freedom laboratory test structure is utilized.

We study here a model hybrid system consisting of a flexible rectangular space structure such as a solar cell array, hoisted at one end by a movable rigid hub, set to vibration from certain initial conditions, but subject to uncertain disturbing forces distributed along its length. Assuming that the control of vibrations is sought by a damper at the hub end proportional to a general nonlinear function of the velocity of the point, we obtain an $H_2$ energy estimate of vibrations over a time interval $\left[0\text{,}T\right]$ in terms of initial energy of the system and the time integral of the $L_2$ norm of the disturbance over the length of the panel. From this, estimates of tolerance level of the disturbances are obtained. Both torsional and flexural modes of vibration are considered.

The intriguing possibility that conditions exist that could support the evolution of life, as we understand it, in the ice-covered oceans of Europa makes the exploration of that Jovian moon a significant priority in NASA’s solar system explorations. There is a need, therefore, to develop and demonstrate technologies and scientific methodologies that could be used to explore these extreme subice realms with the goal of establishing whether or not some form of life has evolved. A NASA search-for-life mission to Europa would involve site reconnaissance, site selection, landing, deep drilling through ice, small autonomous submersibles traversing the purported sea under the ice, and in-situ life detection. Many advanced technologies not currently available would be required. Identification and rank ordering of enabling technologies in a portfolio that can be developed for a certain specified research and development budget is crucial for mission success. This paper describes the results of utilizing a decision tree methodology and an appropriate optimization process to formalize the technology investment strategy.

Space-borne imaging sensors onboard remote sensing satellites capture images of specific interest to the mission. These images contain tremendous volumes of data. Storage capacity onboard the satellite is limited and downlink channels have limited bandwidth capacity. Moreover, most remote sensing satellites are visible to their ground stations for only short periods of time during the day. Therefore, there is significant delay between image capture and terrestrial analysis. Hence, onboard image compression is essential to deliver captured data to the ground in a timely fashion. Smart and efficient onboard image compression using reconfigurable computing technology such as field programmable gate arrays (FPGAs) represents a unique solution that significantly increases the mission effectiveness. The High Performance Computing (HPC-I) payload on the Australian scientific mission satellite FedSat is a demonstration of reconfigurable computing technology in space for a variety of applications including image compression. In this paper, we present the design and implementation on HPC-I of the Satellite Adaptive Image Compression System (SAICS) for space missions. The system concept is based on an FPGA implementation of the adaptive JPEG-LS algorithm. The SAICS is a low complexity, high speed adaptive compression system that uses lossless and near lossless techniques depending on local image statistics. Performance evaluation indicates that satisfactory compression results can only be achieved through a careful trade-off between design complexity and efficiency.