Search Results

The NASA-wide CEV Smart Buyer Team (SBT) was assembled in January 2006 and was tasked with the development of a NASA in-house design for the CEV Crew Module (CM), Service Module (SM), and Launch Abort System (LAS). This effort drew upon over 250 engineers from all of the 10 NASA Centers. In 6 weeks, this in-house design was developed. The Thermal Systems Team was responsible for the definition of the active and passive design architecture. The SBT effort for Thermal Systems can be best characterized as a design architecting activity. Proof-of-concepts were assessed through system-level trade studies and analyses using simplified modeling. This nimble design approach permitted definition of a point design and assessing its design robustness in a timely fashion. This paper will describe the architecting process and present trade studies and proposed thermal designs

This paper presents a review of our current experimental and theoretical understanding of icing feathers and the role that they play in the formation of ice accretions. It covers the following areas: a short review of past research work related to icing feathers; a discussion of the physical characteristics and terminology used in describing icing feathers; the presence of feathers on ice accretions formed in unswept airfoils, especially at SLD conditions; the role that icing feathers play in the formation of ice accretion shapes on swept wings; the formation of icing feathers from roughness elements; theoretical considerations regarding feather formation, feather interaction to form complex icing structures, the role of film dynamics in the formation of roughness elements and the formation of feathers. Hypotheses related to feather formation and feather growth are discussed.

NASA and the FAA are funding the development of ground-based remote sensing systems specifically designed to detect and quantify the icing environment aloft. The goal of the NASA activity is to develop a relatively low cost stand-alone system that can provide practical icing information to the flight community. The goal of the FAA activity is to develop more advanced systems that can identify supercooled large drop (SLD) as well as general icing conditions and be integrated into the existing weather information infrastructure. Both activities utilize combinations of sensing technologies including radar, radiometry, and lidar, along with Internet-available external information such as numerical weather model output where it is found to be useful. In all cases the measured data of environment parameters will need to be converted into a measure of icing hazard before it will be of value to the flying community.

To support NASA's goal to improve aviation safety, the Aircraft Icing Project of the Aviation Safety Program has developed a number of education and training aids for pilots and operators on the hazards of atmospheric icing. A review of aircraft incident and accident investigations has revealed that flight crews have not always understood the effects of ice contamination on their aircraft. To increase this awareness, NASA has partnered with regulatory agencies and pilot trade organizations to assure relevant and practical materials that are focused toward the intended pilot audience. A number of new instructional design approaches and media delivery methods have been introduced to increase the effectiveness of the training materials by enhancing the learning experience, expanding user interactivity and participation, and, hopefully, increasing learner retention rates.

This paper discusses technologies and software tools that are being implemented in a software toolkit currently under development at NASA Glenn Research Center. Its purpose is to help study the effects of icing on airfoil performance and assist with the aerodynamic simulation process which consists of characterization and modeling of ice geometry, application of block topology and grid generation, and flow simulation. Tools and technologies for each task have been carefully chosen based on their contribution to the overall process. For the geometry characterization and modeling, we have chosen an interactive rather than automatic process in order to handle numerous ice shapes. An Appendix presents features of a software toolkit developed to support the interactive process. Approaches taken for the generation of block topology and grids, and flow simulation, though not yet implemented in the software, are discussed with reasons for why particular methods are chosen.

Ice accretions that have formed inside gas turbine engines as a result of flight in clouds of high concentrations of ice crystals in the atmosphere have recently been identified as an aviation safety hazard. NASA's Aviation Safety Program (AvSP) has made plans to conduct research in this area to address the hazard. This paper gives an overview of NASA's engine ice-crystal icing research project plans. Included are the rationale, approach, and details of various aspects of NASA's research.

The history and current status of spacecraft smoke detection is discussed including a review of the state of understanding of the effect of gravity on the resultant smoke particle size. The results from a spacecraft experiment (Comparative Soot Diagnostics (CSD)) which measured microgravity smoke particle sizes are presented. Five different materials were tested producing smokes with different properties including solid aerosol smokes and liquid droplets aerosol smokes. The particulate size distribution for the solid particulate smokes increased substantially in microgravity and the results suggested a corresponding increase for the smokes consisting of a liquid aerosol. A planned follow on experiment that will resolve the issues raised by CSD is presented. Early results from this effort have provided the first measurements of the ambient aerosol environment on the ISS (International Space Station) and suggest that the ISS has very low ambient particle levels.

The International Space Station Carbon Dioxide Removal Assembly (CDRA) uses regenerable adsorption technology to remove carbon dioxide (CO2) from cabin air. CO2 product water vapor measurements from a CDRA test bed unit at the NASA Marshall Space Flight Center were made using a tunable infrared diode laser differential absorption spectrometer (TILDAS) provided by NASA Glenn Research Center. The TILDAS instrument exceeded all the test specifications, including sensitivity, dynamic range, time response, and unattended operation. During the CO2 desorption phase, water vapor concentrations as low as 5 ppmv were observed near the peak of CO2 evolution, rising to levels of ∼40 ppmv at the end of a cycle. Periods of high water concentration (>100 ppmv) were detected and shown to be caused by an experimental artifact.

The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries using the input from a user-supplied computational fluid dynamics (CFD) solution for the geometry of interest. The most significant developments in the advancement of GlennICE have been investigating the convergence of the collection efficiency, efficiently finding trajectories, and improving the refinement methodology. Such developments have increased the efficiency of GlennICE for practical engineering application. With the increasing demand for applying GlennICE for more memory-intensive problems, the scalability of GlennICE has yet to be investigated. This paper is aimed at presenting a method to benchmark the scalability of GlennICE utilizing a relevant engineering problem within a parallel environment.

Modifications have been implemented in the GlennICE software to accommodate a non-inertial reference frame. GlennICE accepts a flow solution from an external flow solver. It then introduces particles and tracks them through the flow field in a Lagrangian manner. Centrifugal and Coriolis terms were added to the GlennICE software to account for relative frame simulations. The objective of the present paper is twofold. First, to check that the new terms are implemented correctly and that the code still behaves as expected with respect to convergence. And second, to provide some initial insight into an upcoming propeller experiment in the NASA Icing Research Tunnel. The paper presents a description of the code modifications. In addition, results are presented for two operating conditions, and three particle sizes. Each case was simulated with four different grid densities to assess grid dependence.

Many studies have been performed to quantify the formation and evolution of roughness on ice shapes created in Appendix C icing conditions, which exhibits supercooled liquid droplets ranging from 1-50 µm. For example Anderson and Shin (1997), Anderson et al. (1998), and Shin (1994) represent early studies of ice roughness during short-duration icing events measured in the Icing Research Tunnel at the NASA Glenn Research Center. In the historical literature, image analysis techniques were employed to characterize the roughness. Using multiple images of the roughness elements, these studies of roughness focused on extracting parametric representations of ice roughness elements. While the image analysis approach enabled many insights into icing physics, recent improvements in laser scanning approaches have revolutionized the process of ice accretion shape characterization.

The influence of freestream static temperature on roughness temporal evolution and spatial variation was investigated in the Icing Research Tunnel (IRT) at NASA Glenn Research Center. A 53.34 cm (21-in.) NACA 0012 airfoil model and a 152.4 cm (60-in.) HAARP-II business jet airfoil model were exposed to Appendix C clouds for fixed exposure times and thus fixed ice accumulation parameter. For the base conditions, the static temperature was varied to produce different stagnation point freezing fractions. The resulting ice shapes were then scanned using a ROMER Absolute Arm system and analyzed using the self-organizing map approach of McClain and Kreeger. The ice accretion prediction program LEWICE was further used to aid in interrogations of the ice accretion point clouds by using the predicted surface variations of local collection efficiency.