2016 NASA EPSCOR RID PROJECTS
Analysis and Design of A Novel Unmanned Air Vehicle with Possible Conversion to Five Micro Air Vehicles for Planetary Exploration
Principal Investigator: Dr. Abdessattar Abdelkefi
Affiliation/Dept.: New Mexico State University, Mechanical and Aerospace Engineering
NASA Collaborator/NASA Center: Dave Berger, MIRO Project Manager, University Affairs Officer/NASA Armstrong Flight Research Center
Description: The design, optimization, and fabrication of unmanned air vehicles and micro air vehicles for planetary exploration in Mars and other planets is one of the high priority future technologies by NASA which is well-described under Technology Areas TA11T “Modeling, Simulation, Information Technology, and Processing Roadmap” and A04 “Robotics, Tele-Robotics and Autonomous Systems”. These drones can also be used for other NASA applications, such as mapping, air sampling, and biological/chemical sensing. In this effort, we aim to model and design a novel UAV that can be converted to five MAVs in order to efficiently perform its mission for NASA applications including planetary exploration and mapping.
Modeling of Microcracking in 3D Woven Composites during Processing
Principal Investigator: Dr. Borys Drach
Affiliation/Dept.: New Mexico State University, Mechanical & Aerospace Engineering Department
NASA Collaborator/NASA Center: John Vickers, Principal Technologist, Advanced Manufacturing/NASA Space Technology Mission Directorate
Description: Three-dimensional (3D) woven composites is a relatively new class of materials that shows great promise as an alternative to the traditional metallic materials used in the aerospace industry. The composites have exceptional stiffness and strength, and can be designed for a specific application. The widespread adoption of the composites is currently hindered by high manufacturing costs and lack of accurate modeling tools capable of predicting mechanical behavior of the material during manufacturing and under static and dynamic loading.
It has been observed that processing of some polymer matrix 3D woven composites results in development of microcracks. The microcracks have minimal effect on the overall elastic properties; however, they may significantly affect fatigue life of the 3D woven composites. To minimize the microcracking, the effect must be taken into account at the reinforcement design stage. Currently, there are no accurate approaches capable of predicting the effect and no design recommendations to help avoid it.
The goal of the proposed research is to identify the most important geometric parameters of 3D woven reinforcements contributing to microcracking during processing. To achieve the goal, a novel numerical approach is proposed. The approach will be based on novel realistic weave geometries and will incorporate progressive matrix failure.
Successful completion of the project will advance the state of the art in design and modeling of 3D woven composites, contribute to NASA research and educational objectives, and potentially improve NMSU capabilities by initiating a new research direction of interest to federal funding agencies and the aerospace industry.
Multifunctional Structural Composites Capable of Self‐Powered Sensing and Harvesting Energy for Next Generation Aerospace Structures
Principal Investigator: Dr. Donghyeon Ryu
Affiliation/Dept.: New Mexico Institute of Mining and Technology, Mechanical Engineering
NASA Collaborator/NASA Center: Timothy Risch, Deputy Chief, Aerostructures Branch/NASA Armstrong Flight Research Center
Description: Interior delamination in the fiber-reinforced polymer (FRP) composites due to the high-frequency vibrational loads has been daunting threaten to the aerospace structures due to its invisibility and quick propagation. To detect the delamination onset in timely manner, advanced sensor technologies (e.g., fiber Bragg grating and piezoelectric sensor) have been suggested in the structural health monitoring framework. Yet, those sensors are limited due to energy dependency, large form factor, high cost in sensor interrogation and data processing.
In this proposed study, PI will devise multifunctional structural composites capable of self-powered sensing and harvesting energy.
An Intelligent Management System for Large Scale Cloud Data Centers
Principal Investigator: Dr. Hamdy Soliman
Affiliation/Dept.: New Mexico Institute of Mining and Technology, Computer Science & Engineering
NASA Collaborator/NASA Center: Hossin Abdeldayem, Senior Scientist/NASA Goddard Space Flight Center
Description: Large scale cloud data centers (CDCs) have become the computing engine supporting almost all aspects of our life. From companies that operate commercial public CDCs as a core line of business (e.g., Amazon) to research institutions (e.g., NASA) that rely on their private CDCs to conduct cutting edge research, data center owners face complex challenges in managing their data centers. Typically, CDCs may contain hundreds or thousands of servers along with network switches, routers, firewalls, storage devices, and several other types of hardware elements. Software that runs in a data center include management and control software (e.g., virtualization packages), networking protocols, open-source code, customer-developed code, and various applications with known or unknown origins. Current approaches for managing CDCs have three fundamental limitations. First, each approach tends to focus on a few aspects of the management spectrum. Second, most existing approaches do not capture long term effects. Third, most solutions are only reactive in that they observe the data center and take corrective actions after unwanted events do occur. In this project, we propose to develop an intelligent management system (IMS) for large scale CDCs that:
- better captures the effects of the system’s components on each other,
- takes into account the data center’s history, and
- is proactive, i.e., takes corrective measures before unwanted consequences get to materialize.
The benefits of the proposed project are significant to NASA and other operators of large scale data centers. An intelligent management system would translate into considerable improvements in terms of reliability, robustness, and costs.