RESEARCH INFRASTRUCTURE DEVELOPMENT (RID) PROJECTS
Principal Investigator: Dr. Meeko Oishi, Associate Professor and Regents’ Lecturer, Department of Electrical and Computer Engineering, University of New Mexico
NASA Collaborator: Michael Feary, NASA Ames Research Center
Period of Performance: May 1, 2013 – April 30, 2014
Project: Assuring information availability in user-interfaces: hybrid system observability for aerospace systems
Description: Develop mathematical and computational techniques to identify problematic human-automation interaction at the design stage. Problems in human-automation interaction have contributed to major failures in expensive, high-risk, and safety-critical systems (including aircraft and aerospace systems).
Principal Investigator: Dr. Svetlana Poroseva, Associate Professor, Mechanical Engineering Department, University of New Mexico
NASA Collaborator: Dr. Ruben Del Rosario, NASA Fundamental Aeronautic Program, NASA Ames
Project: Prediction of Separated Turbulent Flow Characteristics with Reynolds Stress Transport Models
Description: The current engineering practice in simulating turbulent flows is to utilize one- or two-equation turbulence models that solve a simplified set of the Reynolds-Averaged Navier-Stokes (RANS) equations. Such models allow computations of three-dimensional high-Reynolds-number flows to be conducted in a timely manner. However, these models lack the explicit description of many flow details and as a result, perform purely in predicting the behavior of turbulent separated flows in particular. As demonstrated during NASA- and world-wide-organized workshops, computationally expensive approaches to simulate turbulent flows such as Large Eddy Simulations and Detached Eddy Simulations also do not show much better predictive capability in high-Reynolds-number separated flows. In this research, the predictive capability of Reynolds Stress Transport (RST) models in such flows is investigated. Similar to one- and two-equation models, RST models solve a set of RANS equations, but the set also includes the equations for the Reynolds stresses. Thus, RST models explicitly take into consideration the interaction of velocity and pressure fields. As a flow separation is driven by the interaction of these two fields, RST models are expected to describe better the behavior of separated flows. Various models for physical processes that occur within a flow will be considered and their effect on the overall RST model predictive capability will be evaluated.
Principal Investigator: Dr. Horton Newsom, Senior Research Scientist III, Dr. Shawn Wright, Senior Research Scientist, Institute of Meteoritics, University of New Mexico, and Roberta Beal
NASA Collaborator: Dr. Barbara Cohen, NASA Marshall Space Flight Center
Project: The Formation of Accretionary Lapilli at Lonar Crater India, and Meteor Crater Arizona
Description: This research is designed to determine the nature of the processes leading to the formation of accretionary lapilli, millimeter size impact melt or shocked rock fragments coated with accreted shell of ash size mineral grains, recently discovered by our group at Lonar Crater, India. The research provides an exciting opportunity to determine the formation mechanism of these materials in an impact crater plume. Accretionary lapilli are well known in volcanic settings and their formation involves the presence of water in the plumes created by the volcanic activity. However, preliminary examination of the numerous samples of lapilli from Lonar suggest that the fine grain mantling materials may be sintered on to the cores of the lapilli, suggesting extreme heat may be an important component of the lapilli formation in the impact setting. High-resolution element mapping of the contacts between the fine grain particles in the lapilli mantles of impact and volcanic lapilli will determine the nature of the process, cementation or sintering, causing the materials to adhere to each other in these different settings. Possible samples of similar lapilli from Meteor Crater in Arizona and volcanic lapilli will also be analyzed for comparison.
Principal Investigator: Dr. Horton Newsom, Senior Research Scientist III, Institute of Meteoritics, University of New Mexico
NASA Collaborator: Dr. Diana Blaney, Mars Exploration Rovers, Deputy Project Scientist, Jet Propulsion Laboratory; David Cremers, Principal Scientist, Applied Research Associates
Project: Mars Astrobiology: Pushing The Limits of Organic Detection Using Data Fusion of Multiple Spectroscopy Techniques
Description: The goal of this work is to determine the ability for data fusion to enhance the organic, mineralogical, and chemical analyses of environments likely to be encountered in future Mars rover missions. Data fusion is the deconvolution and recombination of complementary datasets to enhance discrimination and detection capabilities; here, this work applues Laser-Induced Breakdown Spectroscopy (LIBS), Raman spectroscopy, and reflectance infrared (IR) spectroscopy to Mars analog materials and extends the scope of previous studies in which only simple comparisons of results between instruments were made. These three techniques are among the most productive instruments for rover missions due to their relatively low energy requirements and ability to analyze surfaces remotely; LIBS and Raman instruments are already selected for the instrument suites of the 2011 MSL and 2018 ExoMars rover missions, respectively. The primary objectives of the project are 1) to determine experimentally the capability of LIBS, specifically the ChemCam LIBS instrument onboard the Mars Science Laboratory mission, to detect trace organics in mineral matrices, and 2) to assess the degree to which data fusion of LIBS, Raman and IR spectroscopies enhances discrimination of organic and mineral species in Mars analog samples.
Principal Investigator: Rafiqul Tarefder, Assistant Professor, Civil Engineering Department, University of New Mexico
NASA Collaborators: John Dorsey of NASA Langley Research Center and Preston B. McGill of NASA Marshal Space Flight Center
Project: Predicting Failure Behavior of Polymeric Composites in Space Vehicles Using a Unified Constitutive Model
Description: Understanding and prediction of the failure (i.e. damage and cracks) behavior of polymeric composites play vital roles in the design and safety of space vehicles such as aircrafts, spacecrafts, missiles, satellites, and launch-system. The traditional finite element fracture models require defining crack location or crack zone in the model geometry and parameters. This research is a unified modeling approach, which allows researchers to model elastic, plastic, and creep strains, micro-cracking, and fracture leading to damage in a single framework without requiring researchers to define a crack location or zone. Thus the unified modeling approach has advantages over the traditional fracture mechanics approach. In this study, principles of mechanics and physics will be invoked to derive a simple unified constitutive model, which will be implemented in a numerical scheme (i.e. finite element) to predict failure behavior of composites. In particular, the research involves numerical modeling of damage and crack growth in simple panels made of IM-7/977-2 composite, which is space qualified. The proposed model will be validated using laboratory tests and data from literature. It is hoped that the validated model will be used to study design life of space vehicles and complex aerospace components such as turbine vanes, blades, disks, rocket nozzle liners, etc. subjected to complex service loadings. The proposed research may lead to the development of tools for designing durable aircrafts and spacecrafts for safe satellite missions, which is the current focus of NASA’s Aeronautic Research Mission Directorate.
Principal Investigator: Zayd Chad Leseman, Assistant Professor, and Jonathan Phillips, Professor, Mechanical Engineering Department, University of New Mexico
NASA Collaborator: Dr. Meyya Meyyappan, Chief Scientist, NASA Ames Research Center
Project: Growth of Carbonaceous Materials for Enhanced Material Properties
Description: This research encompasses a technology that leads to the growth of carbonaceous materials that have the potential of having enhanced materials properties and the ability to enhance other materials through creation of composites. Thus far, the PI has been able to grow graphite and carbon filaments at significantly lower temperatures, < 750K, than any other existing technique for growth of carbonaceous materials. Moreover, the carbonaceous materials only grow on a catalytic template, which allows for targeted growth of said carbonaceous materials. These materials are of high interest to many missions of NASA. Specifically, these materials can be used to make molecular electronics, increase thermal management, and create materials with higher stiffnesses and strengths. Thin sheets of graphite (graphene) are believed to the ideal candidate for molecular electronics. Though this advancement itself will not contribute significantly to decreasing of payload, it will enable lower energy consumption, which will impact battery size and the overall size of the payload. Interwoven carbon filaments and/or graphite used in its bulk form can be used to create materials with higher thermal conductivities, stiffnesses, and strengths. This can be accomplished by using the bulk materials or adding them to a matrix material and forming a composite. Improvement of these thermal and mechanical properties will allow for decreasing of the payload size.
Principal Investigator: Dr. Penelope King, Research Professor, Department of Earth & Planetary Sciences, University of New Mexico
NASA Collaborator: Joy Crisp, Mars Science Laboratory Deputy Project Scientist, NASA Jet Propulsion Laboratory; Ralf Gellert, Assistant Professor, Department of Physics, University of Guelph
Project: Enhancing Mars Exploration by Characterizing Coatings on Rocks
Description: Future exploration of Mars, the search for life, and understanding of the processes and history of the climate and surface of Mars depends on understanding how to interpret the analytical data collected in current and future missions. This research provides critical information to more effectively assess the chemistry and mineralogy of rocks on Mars’ surface. The research provides data needed to estimate the extent of rock alteration (e.g., thickness of a salt, clay or silica deposit on a surface). Such information is critical for determining alteration processes and environmental conditions like pH, water-rock ratio, and gas partial pressures. This study contributes to understanding the viability of the surface for life, and potential hazards or resources for human exploration. Results may be applied to findings from the MER mission and will provide vital information for the MSL mission.
Principal Investigator: Dr. Mark Stone, Associate Professor, Department of Civil Engineering, University of New Mexico
NASA Collaborator: John Haynes, Program Manager, Public Health Applications, NASA Science Mission Directorate/Applied Sciences Program
Project: Enhanced Dust Production Forecasts Using Soil Moisture Models
Description: Windblown dust can result in wide range of negative consequences including dust related human illnesses, local environmental degradation, and even a loss of water resources through reduced snowpack albedo. Severe dust storms commonly occur in arid regions including western China, Saharan Africa, and the Southwest United States. In some regions, such events are increasing in magnitude, duration, and frequency due to desertification and severe droughts. It is thus important to improve predictive models of dust production and transport. In collaboration with researchers at the University of Arizona and George Mason University, the research team has improved descriptions of storm generated dust clouds by incorporating remote sensing data into simulations using a dust model. The objective of the research is to demonstrate the use of spatially explicit hydrologic models to improve descriptions of dust emissions. Hydrologic models are capable of simulating the boundary conditions necessary for describing dust emissions – namely soil moisture content and land cover. These tools can be used to improve our ability to forecast dust emissions from a landscape. Such tools can also digest remote sensing data to parameterize or calibrate vegetation characteristics, snow cover, and precipitation patterns. Thus, this approach will combine the best available information from simulations and remote sensing to better describe spatial distributions of the conditions that control dust emissions.