The proposed efforts will focus on two aspects: 1. Studying the self-sensing mechanisms among smart materials, SMAs in particular. The advantages and drawbacks of using SME or PE for performing sensing in comparison with traditional strain gages will be discussed.

The Structural Mechanics and Concepts Branch at NASA Langley Research Center is currently developing a concept for in-space assembly of persistent platforms consisting of repeating truss modules. In-space assembly has been recognized as being critically important for reducing the cost of major lunar and deep space missions. Multiple smaller payloads can be launched by a variety of vehicles which can then be assembled in orbit by robotic/autonomous means. One of the objectives of the research is to use shape memory alloys (SMAs) to monitor structural health through integrated sensors while minimizing parasitic mass, power consumption, wiring complexity, costs, and volume occupied by the sensor systems. As a preliminary design, a cubic truss assembly concept has been developed. Tests will be performed by setting up and understanding circuits found in the literature to test the shape memory effect by deforming an SMA wire and then safely Joule heating the wire to regain its original shape, as well as measuring the resistance across an SMA. Despite distinct advantages due to shape memory effects in SMAs, SMAs are known to be dependent on ambient parameters such as temperature and humidity. Issues of repeatability can also emerge due to aging of the materials. Therefore, a closed-loop control is required. The use of external sensors can limit the applicability of the SMA actuators. One solution could be to combine SMA������������������s own ability to sense the displacement with their actuation property simultaneously, thus creating a so-called self-sensing SMA actuator. In this task, a review of the literature will be conducted first for examining the possible SMA materials which can have proper dual functionality. A circuit design will be proposed and tested for calibrating/quantifying the sensitivity of the self-sensing SMA actuator. An alternative design of SMA configuration such as siprial coli form will be critically considered.

In order to apply technologies to the field applications for inspecting the aerospace composite structures efficiently, the optical-based laser systems should be portable and noise-insensitive. Additionally, the software will be further developed to image smaller flaws (or damages) for instance from automated manufacturing process and/or operation. The objective of the proposal is to continue to develop a rapid laser ultrasonic composite inspection system for quantifying the damage. The proposal is to develop, demonstrate, and mature two innovation technologies in field applications including new hardware and software tools to be encompassed in the system. The two new innovations will overcome current major bottlenecks for rapid large area detection and characterization of either manufacturing or in-service damage in composite structures in terms of sensitivity, resolution, and accuracy. The robust system will also identify and classify the flaw types including porosity and delamination. The resolution limit of each flaw type and quality of the flaw characterization will be determined. The system with much rapid signal and imaging processing tool with high component throughput can be an order of magnitude faster than those of current either contact or non-contact NDI system. The proposal will also develop a practical inspection for data acquisition and analysis methods for processing data that enable in the field to increase automation and reduce the subjective nature of many aspects of the current inspection methodology. The system will enable operating in the field instead of being confined to the vibration-free and isolated laboratory testing. The laser generation and reception generated or received from a fiber optical cable will allow greater flexibility in interrogating hard-to-access areas. In the last year, all the Ne-He laser system and parts have been acquired and they are being assembled for testing in the controlled environments. A computer vision-based SHM system using a high-speed camera has shown initial promise of imaging the sizable damage using 14 KHz piezo excitation. The project is on-going to optimize and fine tune the system by using a piezoshaker for excitation. Several imaging algorithms used in vision-based SHM system are being proposed to image the damage. The image will compare with those by LDV-based system.

Recently, composite structures have seen greatly increased use in aerospace applications as part of both aircraft and spacecraft. The use of composites can significantly reduce vehicle weight and manufacturing time. One large setback of composites, however, is that damage inspection is difficult. Unlike other materials such as aluminum, damage to composites is typically subsurface and cannot be seen by the naked eye. This poses an issue with inspection, as more complicated and time-consuming methods are needed to ensure the safety of a component. If the time required for these inspection methods can be reduced, or even if the structure can be inspected in-situ, the structure could be inspected more frequently to reduce the amount of time damage has to propagate before detection, or inspection of the structure may require less downtime, reducing opportunity costs (for example in commercial aircraft). Ultrasonic guided-wave based techniques have shown great potential for practical applications in nondestructive inspection (NDI) and structural health monitoring (SHM) for reducing the risks of catastrophic failures in critical structures like aircraft [1-5]. By investigating the scattered ultrasonic guided waves in a structure using appropriate signal/image processing algorithms, a wealth of information about the hidden details of the structure can be unearthed, including information about the location and characteristics of any damage present. Proper algorithms can then be implemented to create a ����������������map��������������� of the structure, highlighting any damage that is present. This means that not only the presence of damage is known, but also its size and location. If this technology can be implemented on critical structural components of aircraft and spacecraft, damage could be detected near-real-time so that proper steps can be taken quickly to ensure safety.

The National Institute of Aerospace (NIA) proposes this collaborative research effort with the Information Management Branch at NASA Langley. The Principal Investigator (PI) will first demonstrate limited proof-of-concept to inform a strategy for the broader implementation within NASA Information Technology (IT) security protocols. Then, the PI may assess algorithms and methods to show that they support a robust machine learning module in a deployed system, This study evolves incremental versions of machine learning models to eventually be able to be used in on-line applications to facilitate in-time updates to parameters within the model, allowing users to benefit from classifications or predictions for ����������������known��������������� events or allowing the model to benefit from expert labels in order to update and improve the model for ����������������unknown��������������� events.

Boron nitride nanotubes (BNNT) have been synthesized using a high temperature-pressure (HTP) method. Without a catalyst, the HTP process produces high-quality BNNTs that have small diameters (~ 5 nm), high aspect ratios (��������������� 1:1000), high flexibility, high crystallinity, and piezoelectricity. Their promising material properties include high Young������������������s modulus (up to 1.3 TPa), excellent thermal stability (up to 900 oC in air), high thermal conductivity (300������������������3000 W/mK), excellent electrical insulation (with a wide band of ~ 6.0 eV), and high neutron absorption (10B ~3800 barn). With such unique material properties, BNNT materials can open up opportunities for multifunctional applications in extreme environments. The main objective of this research is to study the structure and the material properties of BNNTs and their nanocomposite materials for extreme environment applications and technologies. The BNNT growth will be optimized for high quality and high yield production using in-situ monitoring system. The BNNTs and their nanocomposites are fabricated in multiscale to demonstrate their material properties. Ex-situ material characterization is systematically conducted to confirm the structure and the material properties (thermal, mechanical, electrical, and radiation) of BNNTs and their nanocomposites including PVDF/BNNTs. In the case of the nanocomposites, various matrices are investigated according to BNNT������������������s affinity and thermal stability, including high performance polymers and metals. Multifunctional BNNT materials and applications will be demonstrated in multi-scale to target a game-changing system design and innovation for aerospace and future NASA missions. Especially the piezoelectric sensing properties through a couple of stretching techniques to induce ������������-phase for enhancing the sensing performance will be studied.

In order to apply this technology to the field applications for inspecting the entire aerospace structures, the laser systems should be portable and noise-insensitive. Additionally, the software will be further developed to image smaller flaws for instance from automated manufacturing. The objective of the proposal is to continue to develop a rapid laser ultrasonic composite inspection system for quantifying the damage. The proposal will develop, demonstrate, and mature two innovation technologies in field applications including new hardware and software tools to be encompassed in the system. The two new innovations will overcome current major obstacles for rapid large area detection and characterization of either manufacturing or in-service damage in composite structures in terms of sensitivity, resolution, and accuracy. The robust system will also identify and classify the flaw types including porosity and delamination. The resolution limit of each flaw type and quality of the flaw characterization will be determined. The system with much rapid signal and imaging processing tool with high component throughput can be an order of magnitude faster than those of current ether contact or non-contact NDI system. The proposal will develop a practical inspection for data acquisition and analysis methods for processing data that enable in the field to increase automation and reduce the subjective nature of many aspects of the current inspection methodology. The system will enable operating in the field instead of being confined to the vibration-free and isolated laboratory testing. The laser generation and reception generated or received from a fiber optical cable will allow greater flexibility in interrogating hard-to-access areas. A computer vision-based SHM system is starting in parallel with the LDV-based system. Several imaging algorithms used in vision-based SHM system are being proposed to image the damage. The image will compare with those by LDV-based system.

The overall objective of this research is to study the structure and the material properties of BNNTs and their nanocomposite materials for extreme environment applications and technologies. The BNNT growth will be optimized for high quality and high yield production using in-situ monitoring system. The BNNTs and their nanocomposites are fabricated in multiscale to demonstrate their material properties. Ex-situ material characterization is systematically conducted to confirm the structure and the material properties (thermal, mechanical, electrical, and radiation) of BNNTs and their nanocomposites including PVDF/BNNTs. In the case of the nanocomposites, various matrices are investigated according to BNNT������������������s affinity and thermal stability, including high performance polymers and metals. Multifunctional BNNT materials and applications will be demonstrated in multi-scale to target a game-changing system design and innovation for aerospace and future NASA missions. Especially the piezoelectric sensing properties through a couple of stretching techniques and 3-D printing fabrication method to induce electric polarization of BNNTs in matrix materials for enhancing the sensing performance will be studied.

The Structural Mechanics and Concepts Branch at NASA Langley Research Center is currently developing a concept for in-space assembly of persistent assets consisting of repeating truss modules. In-space assembly has been recognized as a critically important approach for reducing the cost of major lunar and deep space missions. Multiple smaller payloads can be launched by a variety of vehicles, then assembled in orbit, by robotic/autonomous means. One of the objectives of the research is to develop a method of monitoring structural health through integrated sensors while also minimizing parasitic mass, power consumption, wiring complexity, costs, and volume occupied by the sensor systems. To achieve this goal, Rounak will research methods of determining global health states of the platform and specifying local module detriments such as stress fractures or MMOD impacts. One of the most promising methods is a short pulse based vibration feedback model to determine structural health across the fully assembled structure. By inputting the short pulse with known waveform and magnitude, integrated piezoelectric sensors can sense and analyze the resultant vibrations through their respective portions of the platform to characterize any damage in the struts and/or nodes. Another alternative of using vision-based monitoring techniques will be possibly considered. The usage monitoring using accelerometers for example will be explored. By maximizing the section of the assetthat is being monitored by each sensor system, the number of integrated sensors can be minimized.

Additive manufacturing (AM), also referred to as 3-D printing has been developing steadily since the 1980s. According to some reports, 3-D printing is expected to be a $5.2 billion industry by 2020. AM allows for the manufacture of highly complex geometries which are difficult to handle using traditional manufacturing techniques. However, AM still has several hurdles that it needs to overcome before its widespread adoption, especially in the manufacture of safety critical components e.g., current aerospace practice requires 100% visual inspection of the manufactured component. Often times, manual inspection of the component is much more time consuming than the lay-up process itself. Most of the conventional additive manufacturing systems fail to notice minor defects during material lay-up that may get compounded layer by layer thereby rendering the final product unsuitable for use. These defects could potentially be automatically corrected if detected before the next layer is deployed. The goal of this work is to process the data collected using high-resolution cameras and then to use computer vision technology to detect defects such as porosity, cracks, warping, delamination etc. during the lay-up process itself thereby reducing or eliminating the need for post manufacture inspection of printed objects. This could also facilitate the AM system to take corrective measures during the lay-up process itself thereby achieving a Real-time control of the manufacturing process.