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The new devices and missions to achieve the aims of NASA's Science Mission Directorate (SMD) are creating increasingly demanding thermal environments and applications. In particular, the low conductance of metal-to-metal interfaces used in the thermal switches lengthen the cool-down phase and resource usage for spacecraft instruments. During this work, we developed and tested a vacuum-compatible, durable, heat-conduction interface that employs carbon nanotube (CNT) arrays directly anchored on the mating metal surfaces via microwave plasma-enhanced, chemical vapor deposition (PECVD). We demonstrated that CNT-based thermal interface materials have the potential to exceed the performance of currently available options for thermal switches and other applications.

This paper presents the continuation of the modeling work described in a companion paper “Modeling of Nonlinear Elastomeric Mounts. Part 1: Dynamic Testing and Parameter Identification” by the same authors. That paper discussed a dynamic test procedure and an optimization methodology to identify and model an elastomeric mount as a non-linear lumped parameter structure. This paper discusses a numerical modeling methodology to confirm or improve the agreement between the dynamic test results and the input-output relationship of the analytical model generated in the companion paper. In this paper, the model developed in the companion paper and the model parameters are input into a dynamic simulation model using a commercial simulation package. The model is then run to produce the numerical force-versus-displacement (F-x) curves of the mount. The numerical F-x curves are compared with the F-x curves obtained from the experiments.

The formation of ice on aircraft is a highly dynamic process during which ice will expand and contract upon freezing and undergoing changes in temperature. Finite element analysis (FEA) simulations were performed investigating the stress/strain response of an idealized ice sample bonded to an acrylic substrate subjected to a uniform temperature change. The FEA predictions were used to guide the placement of strain gages on custom-built acrylic and aluminum specimens. Tee rosettes were placed in two configurations adjacent to thermocouple sensors. The specimens were then placed in icing conditions such that ice was grown on top of the specimen. It was hypothesized that the ice would expand on freezing and contract as the temperature of the interface returned to the equilibrium conditions.

This paper presents in-process monitoring and control based on a novel ultrasonic sensing technique. The developed ultrasonic system provides non-contact measurement of surface roughness, which is applicable to wet machining environments. The utility and robustness of the technique are demonstrated through applications to different processes and materials. In-process surface roughness monitoring capability of the system is also shown along with its potential to monitor flank wear conditions. The result of in-process surface roughness control implementation based on the developed technique shows the control scheme is able to maintain consistent surface roughness values regardless of the tool wear state.

Throughout the industry, organizations struggle with the task of implementing effective human factors programs aimed at reducing maintenance errors. Almost universally, many barriers have frustrated these efforts. In 1998 and 1999, the National Transportation Safety Board sponsored two workshops designed at identifying barriers to the implementation of human factors programs and to explore what was working and what was not working among the many industry efforts. This paper explores the findings of these workshops. In addition, it will report findings of Purdue University studies that reveal a rapid deterioration of even the most successful human factors programs. The research findings disclose several “disconnects” within most organizations which rapidly negate the positive effects of successful human factors and error management training and nullify many proactive human factors programs.

Fatigue damage prediction approaches in both time and frequency domains have been developed to simulate the operational life of mechanical structures under random loads. Fatigue assessment of mechanical structures and components subjected to those random loads is increasingly being addressed by frequency domain approaches because of time and cost savings. Current frequency-based fatigue prediction methods focus on stationary random loadings (stationary Power Spectral Density), but many machine components, such as jet engines, rotating machines, and tracked vehicles are subjected to non-stationary PSD conditions under real service loadings. This paper describes a new fatigue damage modeling approach capable of predicting fatigue damage for structures exposed to non-stationary (evolutionary) PSD loading conditions where the PSD frequency content is time-varying.

This paper describes research to analyze widespread fatigue damage in lap joints. The particular objective is to determine when large numbers of small cracks could degrade the joint strength to an unacceptable level. A deterministic model is described to compute fatigue crack growth and residual strength of riveted panels that contain multiple cracks. Fatigue crack growth tests conducted to evaluate the predictive model are summarized, and indicate good agreement between experimental and numerical results. Monte Carlo simulations are then performed to determine the influence of statistical variability on various analysis parameters.

Bioregenerative systems for removal of gaseous contaminants are desired for long-term space missions to reduce the equivalent system mass of the air cleaning system. This paper describes an innovative design of a new biofiltration test lab for investigating the capability of biofiltration process for removal of ersatz multi-component gaseous streams representative of spacecraft contaminants released during long-term space travel. The lab setup allows a total of 24 bioreactors to receive identical inlet waste streams at stable contaminant concentrations via use of permeations ovens, needle valves, precision orifices, etc. A unique set of hardware including a Fourier Transform Infrared (FTIR) spectrometer, and a data acquisition and control system using LabVIEW™ software allows automatic, continuous, and real-time gas monitoring and data collection for the 24 bioreactors. This lab setup allows powerful factorial experimental design.

Driveline and suspension notched components of off-road ground vehicles often experience multiaxial fatigue failures along notch locations. Large nominal load histories may induce local elasto-plastic stress and strain responses at the critical notch locations. Fatigue life prediction of such notched components requires detailed knowledge of local stresses and strains at notch regions. The notched components that are often subject to multiaxial loadings in services, experience complex stress and strain responses. Fatigue life assessment of the components utilizing non-linear Finite Element Analysis (FEA) require unfeasibly inefficient computation times and large data. The lack of more efficient and effective methods of elasto-plastic stress-strain calculation may lead to the overdesign or earlier failures of the components or costly experiments and inefficient non-linear FEA.