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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.

The On-line Project Information System (OPIS) is a LAMP-based (Linux, Apache, MySQL, PHP) system being developed at NASA Ames Research Center to improve Agency information transfer and data availability, largely for improvement of system analysis and engineering. The tool will enable users to investigate NASA technology development efforts, connect with experts, and access technology development data. OPIS is currently being developed for NASA's Exploration Life Support (ELS) Project. Within OPIS, NASA ELS Managers assign projects to Principal Investigators (PI), track responsible individuals and institutions, and designate reporting assignments. Each PI populates a “Project Page” with a project overview, team member information, files, citations, and images. PI's may also delegate on-line report viewing and editing privileges to specific team members. Users can browse or search for project and member information.

Noise generation in axial piston machines can be attributed to two main sources; fluid borne and structure borne. Any attempt towards noise reduction in axial piston machines should focus on simultaneous reduction of these two sources. A multi-parameter multi-objective optimization approach to design valve plates to reduce both sources of noise for pumps which operate in a wide range of operating conditions has been detailed in a previous work (Seeniraj and Ivantysynova, 2008). The focus of this paper is to explain the background and to demonstrate the functionality and usefulness of the methodology for pump design.

Dynamics of machine tool components play a critical role in the outcome of machining processes. This paper addresses several important issues on machine tool and machining dynamics. It illustrates the dynamic behavior of structural components under operating conditions and presents an improved technique for modeling structural non-linearity. It also describes spindle modeling capability that has been developed to predict dynamic and thermal characteristics of spindle systems. Finally, the paper discusses the impact of non-linear dynamics on machining stability.

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.

Wheat is a candidate crop for the Advanced Life Support (ALS) system, and cereal grains and their products will be included on long-term space missions beyond low earth orbit. While the exact supply scenario has yet to be determined, some type of post-processing of these grains must occur if they are shipped as bulk ingredients or grown on site for use in foods. Understanding the requirements for processing grains in space is essential for incorporating the process into the ALS food system. The ESM metric developed by NASA describes and compares individual system impact on a closed system in terms of a single parameter, mass. The objective of this study was to compare the impact of grain mill type on the ESM of producing yeast and flat breads. Hard red spring wheat berries were ground using a Brabender Quadrumat Jr. or the Kitchen-Aid grain mill attachment (both are proposed post-harvest technologies for the ALS system) to produce white and whole wheat flour, respectively.

One of the challenges NASA faces today is developing an Advanced Life Support (ALS) system that will enable long duration space missions beyond low earth orbit (LEO). This ALS system must include a food processing subsystem capable of producing a variety of nutritious, acceptable, and safe edible ingredients and food products from pre-packaged and re-supply foods as well as salad crops grown on the transit vehicle or other crops grown on planetary surfaces. However, designing, building, developing, and maintaining such a subsystem is bound to many constraints and restrictions. The limited power supply, storage locations, variety of crops, crew time, need to minimize waste, and other ESM parameters influence the selection of processing equipment and techniques.

In the past decades, automotive structure design has sought to minimize its mass while maintaining or improving structural performance. As such, topology optimization (TO) has become an increasingly popular tool during the conceptual design stage. While the designs produced by TO methods provide significant performance-to-mass ratio improvements, they require considerable computational resources when solving large-scale problems. An alternative for large-scale problems is to decompose the design domain into multiple scales that are coupled with homogenization. The problem can then be solved with hierarchical multiscale topology optimization (MSTO). The resulting optimal, homogenized macroscales are de-homogenized to obtain a high-fidelity, physically-realizable design. Even so MSTO methods are still computationally expensive due to the combined costs of solving nested optimization problems and performing de-homogenization.

In long-duration, closed human habitats in space that include crop growth, one challenge that is faced while designing a candidate waste processor is the composition of solid-waste loads, which include human waste, packaging and food-processing materials, crop spoilage, and plant residues. In this work, a new modeling tool is developed to characterize crop residues and food wastes based on diet in order to support the design of solid-waste technologies for closed systems. The model predicts amounts of crop residues and food wastes due to food processing, crop harvests, and edible spoilage. To support the design of solid-waste technologies, the generation of crop residues and food wastes was characterized for a 600-day mission to Mars using integrated menu, crop, and waste models. The three sources of plant residues and food waste are identified to be food processors, crop harvests, and edible spoilage.

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.

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.