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High costs and extreme risks prevent the life testing of NASA hardware. These unavoidable limitations prevent the determination of sound reliability bounds for NASA hardware; thus the true risk assumed in future missions is unclear. A simulation infrastructure for determining these risks is developed in a configurable format here. Positive preliminary results in preparation for validation testing are reported. A stochastic filter simulates non-deterministic output from the various unit processes. A maintenance and repair module has been implemented with several levels of complexity. Two life testing approaches have been proposed for use in future model validation.

A reliable nutrient delivery system is essential for long-term cultivation of plants in space. At the Kennedy Space Center, a series of ground-based tests are being conducted to compare candidate plant nutrient delivery systems for space. To date, our major focus has concentrated on the Porous Tube Plant Nutrient Delivery System, the ASTROCULTURE™ System, and a zeoponic plant growth substrate. The merits of each system are based upon the performance of wheat supported over complete growth cycles. To varying degrees, each system supported wheat biomass production and showed distinct patterns for plant nutrient uptake and water use.

Over the last couple decades, there has been a growing interest in incorporating commercial off-the-shelf (COTS) technologies and open standards in the design of human-rated spacecraft. This approach is intended to reduce development and upgrade costs, lower the need for new design work, eliminate reliance on individual suppliers, and minimize schedule risk. However, it has not traditionally been possible for COTS solutions to meet the high reliability and fault tolerance requirements of systems implementing critical spacecraft functions. Byzantine faults are considered particularly dangerous to such systems because of their ability to escape traditional means of fault containment and disrupt consensus between system components. In this paper, we discuss the design of a voting protocol using Time-Triggered Ethernet capable of achieving data integrity in the presence of a single Byzantine fault.

Conceptual designs for a space suit Personal Life Support Subsystem (PLSS) were developed and assessed to determine if upgrading the system using new, emerging, or projected technologies to fulfill basic functions would result in mass, volume, or performance improvements. Technologies were identified to satisfy each of the functions of the PLSS in three environments (zero-g, Lunar, and Martian) and in three time frames (2006, 2010, and 2020). The viability of candidate technologies was evaluated using evaluation criteria such as safety, technology readiness, and reliability. System concepts (schematics) were developed for combinations of time frame and environment by assigning specific technologies to each of four key functions of the PLSS -- oxygen supply, waste removal, thermal control, and power. The PLSS concepts were evaluated using the ExtraVehicular Activity System Sizing Analysis Tool, software created by NASA to analyze integrated system mass, volume, power and thermal loads.

A small team of NASA engineers has been assembled at the Johnson Space Center, with the goal of developing an inexpensive space-capable vehicle. In order to minimize cost and development time of the experimental vehicle, it was desirable to build upon a previously-developed vehicle shape. The basic shape of the X-24A experimental lifting body was chosen for several reasons, and in the case of the Environmental Control and Life Support (ECLS), the de-orbit cross-range capability of this shape provides for a minimal on-orbit time while waiting for landing opportunities, which in turn simplifies the ECLS. Figure 1 shows the X-38 vehicle body shape. In keeping with the goal of rapidly developing an inexpensive and reliable vehicle, the ECLS was developed using simple, passive systems where practical. This paper provides an overview of the ECLS mission requirements and design, with emphasis on the philosophy used in its development.

Techniques developed for structural reliability analysis are applied to mechanical reliability problems, including those with non-normal random variables, complicated design equations, chain and ductile system structures, and screening or testing of components.

In planning for Exploration missions and developing the required suite of environmental monitors, the difficulty lies in down-selecting a multitude of technology options to a few candidates with exceptional potential. Technology selection criteria include conventional analytical parameters (e.g., range, sensitivity, selectivity), operational factors (degree of automation, portability, required level of crew training, maintenance), logistical factors (size, mass, power, consumables, waste generation) and engineering factors such as complexity and reliability. Other more subtle considerations include crew interfaces, data readout and degree of autonomy from the ground control center. We anticipate that technology demonstrations designed toward these goals will be carried out on the International Space Station, the end result of which is a suite of techniques well positioned for deployment during Exploration missions.

Automotive software complexity has been growing rapidly with time. The demand for automation in automotive segment including autonomous automobiles and software based products has caught the attention of researchers. Hence, it is necessary to check the complexity of automotive software and their reliability growth. Testing in the field of software artifact is resource intensive exercise. If project managers are able to put forward testing activities well then the testing resource consumptions may be much more resource/cost efficient. Reliability can be estimated during testing phase of software using software reliability growth models (SRGMs). A software package Computer Aided Software Reliability Estimation (CASRE) has many important SRGMs. These SRGMs are based on Non-Homogeneous Poisson Process (NHPP), Markov process or Bayesian models.