SEARCH · Search NASA

Results for “SMA”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

NASA NTRS2010

Kinetic Temperatures of the Dense Gas Clumps in the Orion KL Molecular Core

High angular-resolution images of the J = 18(sub K)-17(sub K) emission of CH3CN in the Orion KL molecular core were observed with the Submillimeter Array (SMA). Our high-resolution observations clearly reveal that CH3CN emission originates mainly from the Orion Hot Core and the Compact Ridge, both within approximately 15 inches of the warm and dense part of Orion KL. The clumpy nature of the molecular gas in Orion KL can also be readily seen from our high-resolution SMA images. In addition, a semi-open cavity-like kinematic structure is evident at the location between the Hot Core and the Compact Ridge. We performed excitation analysis with the "population diagram" method toward the Hot Core, IRc7, and the northern part of the Compact Ridge. Our results disclose a non-uniform temperature structure on small scales in Orion KL, with a range of temperatures from 190-620 K in the Hot Core. Near the Compact Ridge, the temperatures are found to be 170-280 K. Comparable CH3CN fractional abundances of 10(exp -8) to 10(exp -7) are found around both in the Hot Core and the Compact Ridge. Such high abundances require that a hot gas phase chemistry, probably involving ammonia released from grain mantles, plays an important role in forming these CH3CN molecules.

Wang, Kuo-Song↗

NASA NTRS2013

Thermo-Mechanical Methodology for Stabilizing Shape Memory Alloy Response

This innovation is capable of significantly reducing the amount of time required to stabilize the strain-temperature response of a shape memory alloy (SMA). Unlike traditional stabilization processes that take days to weeks to achieve stabilized response, this innovation accomplishes stabilization in a matter of minutes, thus making it highly useful for the successful and practical implementation of SMA-based technologies in real-world applications. The innovation can also be applied to complex geometry components, not just simple geometries like wires or rods.

Padula, Santo↗

NASA NTRS2013

Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

spectral mixing analysis↗

NASA NTRS2014

Three-Dimensional Cellular Structures Enhanced By Shape Memory Alloys

This research effort explored lightweight structural concepts married with advanced smart materials to achieve a wide variety of benefits in airframe and engine components. Lattice block structures were cast from an aerospace structural titanium alloy Ti-6Al-4V and a NiTi shape memory alloy (SMA), and preliminary properties have been measured. A finite element-based modeling approach that can rapidly and accurately capture the deformation response of lattice architectures was developed. The Ti-6-4 and SMA material behavior was calibrated via experimental tests of ligaments machined from the lattice. Benchmark testing of complete lattice structures verified the main aspects of the model as well as demonstrated the advantages of the lattice structure. Shape memory behavior of a sample machined from a lattice block was also demonstrated.

nitinol alloys↗

NASA NTRS2015

A Morphing Radiator for High-Turndown Thermal Control of Crewed Space Exploration Vehicles

Spacecraft designed for missions beyond low earth orbit (LEO) face a difficult thermal control challenge, particularly in the case of crewed vehicles where the thermal control system (TCS) must maintain a relatively constant internal environment temperature despite a vastly varying external thermal environment and despite heat rejection needs that are contrary to the potential of the environment. A thermal control system is in other words required to reject a higher heat load to warm environments and a lower heat load to cold environments, necessitating a quite high turndown ratio. A modern thermal control system is capable of a turndown ratio of on the order of 12:1, but for crew safety and environment compatibility these are massive multi-loop fluid systems. This paper discusses the analysis of a unique radiator design which employs the behavior of shape memory alloys (SMA) to vary the turndown of, and thus enable, a single-loop vehicle thermal control system for space exploration vehicles. This design, a morphing radiator, varies its shape in response to facesheet temperature to control view of space and primary surface emissivity. Because temperature dependence is inherent to SMA behavior, the design requires no accommodation for control, instrumentation, nor power supply in order to operate. Thermal and radiation modeling of the morphing radiator predict a turndown ranging from 11.9:1 to 35:1 independent of TCS configuration. Stress and deformation analyses predict the desired morphing behavior of the concept. A system level mass analysis shows that by enabling a single loop architecture this design could reduce the TCS mass by between 139 kg and 225 kg. The concept is demonstrated in proof-of-concept benchtop tests.

Cognata, Thomas J.↗

NASA NTRS2015

Shape Memory Alloy Research and Development at NASA Glenn - Current and Future Progress

Shape memory alloys (SMAs) are a unique class of multifunctional materials that have the ability to recover large deformations or generate high stresses in response to thermal, mechanical and or electromagnetic stimuli. These abilities have made them a viable option for actuation systems in aerospace, medical, and automotive applications, amongst others. However, despite many advantages and the fact that SMA actuators have been developed and used for many years, so far they have only found service in a limited range of applications. In order to expand their applications, further developments are needed to increase their reliability and stability and to address processing, testing and qualification needed for large-scale commercial application of SMA actuators.

Challenges↗

NASA NTRS2015

Apparatus and Method for Low-Temperature Training of Shape Memory Alloys

An apparatus and method for the low-temperature thermo-mechanical training of shape memory alloys (SMA) has been developed. The experimental SMA materials are being evaluated as prototypes for applicability in novel thermal management systems for future cryogenic applications. Alloys providing two-way actuation at cryogenic temperatures are the chief target. The mechanical training regimen was focused on the controlled movement of rectangular strips, with S-bend configurations, at temperatures as low as 30 K. The custom holding fixture included temperature sensors and a low heat-leak linear actuator with a magnetic coupling. The fixture was mounted to a Gifford-McMahon cryocooler providing up to 25 W of cooling power at 20 K and housed within a custom vacuum chamber. Operations included both training cycles and verification of shape memory movement. The system design and operation are discussed. Results of the training for select prototype alloys are presented.

Training↗

NASA NTRS2016

The NASA Commercial Crew Program (CCP) Mission Assurance Process

In 2010, NASA established the Commercial Crew Program in order to provide human access to the International Space Station and low earth orbit via the commercial (non-governmental) sector. A particular challenge to NASA has been how to determine the commercial providers transportation system complies with Programmatic safety requirements. The process used in this determination is the Safety Technical Review Board which reviews and approves provider submitted Hazard Reports. One significant product of the review is a set of hazard control verifications. In past NASA programs, 100 percent of these safety critical verifications were typically confirmed by NASA. The traditional Safety and Mission Assurance (SMA) model does not support the nature of the Commercial Crew Program. To that end, NASA SMA is implementing a Risk Based Assurance (RBA) process to determine which hazard control verifications require NASA authentication. Additionally, a Shared Assurance Model is also being developed to efficiently use the available resources to execute the verifications. This paper will describe the evolution of the CCP Mission Assurance process from the beginning of the Program to its current incarnation. Topics to be covered include a short history of the CCP; the development of the Programmatic mission assurance requirements; the current safety review process; a description of the RBA process and its products and ending with a description of the Shared Assurance Model.

Commercial Crew Program↗

NASA NTRS2016

A Computationally-Efficient, Multi-Mechanism Based Framework for the Comprehensive Modeling of the Evolutionary Behavior of Shape Memory Alloys

The report summarizes the accomplishments made during the 4-year duration of the project. Here, the major emphasis is placed on the different tasks performed by the two research teams; i.e., the modeling activities by the University of Akron (UA) team and the experimental and neutron diffraction studies conducted by the University of Central Florida (UCF) team, during this 4-year period. Further technical details are given in the upcoming sections by UA and UCF for each of the milestones/years (together with the corresponding figures and captions).The project majorly involved the development, validation, and application of a general theoretical model that is capable of capturing the nonlinear hysteretic responses, including pseudoelasticity, shape memory effect, rate-dependency, multi-axiality, asymmetry in tension versus compression response of shape memory alloys. Among the targeted goals for the SMA model was its ability to account for the evolutionary character response (including transient and long term behavior under sustained cycles) for both conventional and high temperature (HT) SMAs, as well as being able to simulate some of the devices which exploit these unique material systems. This required extensive (uniaxial and multi-axial) experiments needed to guide us in calibrating and characterizing the model. Moreover, since the model is formulated on the theoretical notion of internal state variables (ISVs), neutron diffraction experiments were needed to establish the linkage between the micromechanical changes and these ISVs. In addition, the design of the model should allow easy implementation in large scale finite element application to study the behavior of devices making use of these SMA materials under different loading controls. Summary of the activities, progress/achievements made during this period is given below in details for the University of Akron and the University (Section 2.0) of Central Florida (Section 3.0).

Alloys↗

NASA NTRS2017

Computational and Experimental Fluid-Structure Interaction Analysis of a High-Lift Wing with a Slat-Cove Filler for Noise Reduction

Airframe noise is a significant component of overall noise produced by transport aircraft during landing and approach (low speed maneuvers). A significant source for this noise is the cove of the leading-edge slat. The slat-cove filler (SCF) has been shown to be effective at mitigating slat noise. The objective of this work is to understand the fluid-structure interaction (FSI) behavior of a superelastic shape memory alloy (SMA) SCF in flow using both computational and physical models of a high-lift wing. Initial understanding of flow around the SCF and wing is obtained using computational fluid dynamics (CFD) analysis at various angles of attack. A framework compatible with an SMA constitutive model (implemented as a user material subroutine) is used to perform FSI analysis for multiple flow and configuration cases. A scaled physical model of the high-lift wing is constructed and tested in the Texas A&M 3 ft-by-4-foot wind tunnel. Initial validation of both CFD and FSI analysis is conducted by comparing lift, drag and pressure distributions with experimental results.

Scholten, William D.↗

NASA NTRS2018

Supplier Research & Analysis Approach

"The implementation of NASA GSFC's portfolio of mission projects relies upon inter-connected, multi-tiered supply chains of organizations operating under direct and indirect contracts and other agreements throughout the U.S. and around the world. These supply chains are subject to an inter-related array of technical/production, business, market and security risks that are amplified by the ongoing globalization of industry and technology and which can disrupt or threaten the production and delivery of products and services when needed and in conformance with requirements. In recognition of such risks and associated challenges, GSFC's SMA directorate launched an innovative Supplier Research and Analysis (SRA) capability three years ago to gain greater insight into the operating environment, performance, capabilities and viability of current and prospective suppliers for GSFC projects and proposals. The capability uses business intelligence techniques and primarily open source information resources as part of a cost-effective, non-intrusive methodology to produce several types of research and analysis reports. The reports are based on a holistic analytical framework encompassing key technical/production, business enterprise management, market and security factors, and feature in-depth information, summary information profiles, SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis, and candidate risk concerns in order to pro-actively support SMA and project management needs. The SRA capability, which is designed to complement and support ongoing SMA/project management activities and practices, has produced over 95 reports since its start-up in early 2015. This presentation addresses the approach, methodology and performance of the Supplier Research and Analysis (SRA) capability and its value in assuring the success of NASA mission projects. In doing so, the presentation provides lessons-learned, best practices, case examples and address how it fits into the development of an enterprise-level Supply Chain Risk Management capability."

supplier research and analysis↗

NASA NTRS2018

Passive Thermal Management Systems Employing Shape Memory Alloys

A thermal management system includes a first substrate having a first conductive inner surface. A second substrate has a second conductive inner surface. A connecting structure is attached to the first and second substrates to space apart the first and second inner surfaces defining an insulating space for a single architecture. One or more passively-acting elements are attached to the inner surface of at least one substrate and including a shape memory material such as a shape memory alloy (SMA). The SMA passively reacts to the temperature of the first substrate by thermally contacting or separating from the second inner surface of the second substrate for the control of the conduction of heat energy in either direction.

Trigwell, Steven↗

NASA NTRS2018

NC Space Grant Report

During the summer of 2018 I supported the Safety & Mission Assurance Directorate (SMA) and Operations Support Division (QA-20) at Stennis Space Center. The mission of the SMA team is to prove safety, risk, reliability, independent assessments, configuration management and quality assurance guidance, and services for all NASA Stennis Space Center (SSC) programs, facilities, and supporting infrastructure. The office actively participates and contributes to the Agency-level Safety & Mission Assurance (S&MA) effort. Over the course of the Summer I participated in three projects. Two of them were focused around Fault Tree Analysis (FTA) and the third focused on relief valves for their E-1 engine test stand.

Torres, David↗

NASA NTRS2018

Supply Chain Research and Analysis for Space Systems

The implementation of NASA GSFC's portfolio of mission projects relies upon inter-connected, multi-tiered supply chains of organizations operating under direct and indirect contracts and other agreements throughout the U.S. and around the world. These supply chains are subject to an inter-related array of technical/production, business, market and security risks that are amplified by the ongoing globalization of industry and technology and which can disrupt or threaten the production and delivery of products and services when needed and in conformance with requirements. In recognition of such risks and associated challenges, GSFC's SMA directorate launched an innovative Supply Chain Research and Analysis capability three years ago to gain greater insight into the operating environment, performance, capabilities and viability of current and prospective suppliers for GSFC projects and proposals. The capability uses business intelligence techniques and primarily open source information resources as part of a cost-effective, non-intrusive methodology to produce several types of research and analysis reports. The reports are based on a holistic analytical framework encompassing key technical/production, business enterprise management, market and security factors, and feature in-depth information, summary information profiles, SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis, and candidate risk concerns in order to pro-actively support SMA and project management needs. The SRA capability, which is designed to complement and support ongoing SMA/project management activities and practices, has produced over 105 reports since its start-up in early 2015.This presentation addresses the approach, methodology and performance of the Supply Chain Research and Analysiscapability and its value in assuring the success of NASA mission projects. In doing so, the presentation provides lessons-learned, best practices, case examples and address how it fits into the development of an enterprise-level Supply Chain Risk Management capability.

supply chain risk management↗

NASA NTRS2018

The Effects of Fiber Orientation and Adhesives on Tensile Properties of Carbon Fiber Reinforced Polymer Matrix Composite with Embedded Nickel-Titanium Shape Memory Alloys

Tensile tests of Nickel-titanium (NiTi) shape memory alloys (SMA) embedded within carbon fiber reinforced polymer matrix composite (CFRP/PMC) laminates were evaluated with simultaneous monitoring of modal acoustic emissions (MAE). Three different layup configurations utilizing two different thin film adhesives were applied to bond the materials. Ultimate tensile strengths, strains, and moduli were obtained along with cumulative AE energy of events and specimen failure location. Scanning electron microscopy was used to examine the break areas of the specimens post-test. Microscopy was used to validate failure locations revealed from MAE analysis. A unique finding within this research showed that 90° plies in the outer ply gave the strongest acoustic signals as well as the cleanest fracture of the specimens tested. Overlapping 0° ply layers surrounding the SMA was found to be the best scenario to prevent failure of the specimen itself.

Derek Quade↗

NASA NTRSDate not supplied

A Machine Learning Approach to Predict Martensitic Transition Temperatures for Shape Memory Alloys

Shape memory alloys (SMAs) are a unique class of materials with several remarkable properties including shape recovery, superelasticity, etc. Especially important for many NASA applications is the ability to tune the martensitic phase transition temperature by varying the alloy composition. Nickel-titanium (NiTi) based alloys are the most widely studied of this class, with compositions involving ternary, quaternary, or higher additions being considered. Over the past several years, a significant database of SMA properties has been assembled by NASA researchers. Such a database is ideal for data science-based approaches including machine learning. We present results from a developed machine learning model capable of accurately predicting the transition temperature of SMAs across a wide range of compositions. Our model has the added benefit of interpretability and even provides confidence intervals for our predictions. This model will make rapid screening and design of new SMA materials possible. Predictions from the machine learning model can be validated by empirical and/or atomistic scale modeling.

Shreyas Honrao↗

NASA NTRSDate not supplied

Advanced eLectrical Bus (ALBus) CubeSat: From Build to Flight

Advanced eLectrical Bus (ALBus) CubeSat is a technology demonstration mission of a 3-U CubeSat with an advanced digitally controlled electrical power system and novel use of Shape Memory Alloy (SMA) technology for reliable deployable solar array mechanisms. The primary objective was to advance the power management and distribution (PMAD) capabilities to enable future missions requiring more flexible and reliable power systems with higher output power capabilities. Goals included demonstration of 100W distribution to a target electrical load, response to continuous and fast transient power requirements, and exhibition of reliable deployment of solar arrays and antennas utilizing re-settable SMA mechanisms. The power distribution function of the ALBus PMAD system is unique in the total power to target load capability, as power is distributed from batteries to provide 100W of power directly to a resistive load. The deployable solar arrays utilize NASA’s Nickel-Titanium-Palladium-Platinum (NiTiPdPt) high-temperature SMAs for the retention and release mechanism, and a superelastic binary NiTi alloy for the hinge component. The project launched as part of the CubeSat Launch Initiative (CLI) Educational Launch of Nanosatellites (ELaNa) XIX mission on Rocket Lab’s Electron in December 2018. This paper summarizes the final launched design and the lessons learned from build to flight.

Deboshri Sadhukhan↗

NASA NTRSDate not supplied

A Machine Learning Approach to Design Shape Memory Alloys for NASA Applications

Shape memory alloys (SMAs) are a unique class of materials with several remarkable properties including shape recovery, superelasticity, etc. Nickel-titanium (NiTi) based alloys are the most widely studied of this class, with compositions including ternary, quaternary, or higher additions being considered. Especially important for many NASA applications is the ability to tune the martensitic phase transition temperature of NiTi alloys by varying the alloy composition and processing conditions. In addition, low hysteresis and an acceptable recoverable transformation strain are required. Over the past several years, a significant database of SMA properties has been assembled by NASA researchers. Such a database is ideal for data science-based approaches. We present results from our machine learning approach for designing new SMAs with target properties within our range of interest. Our developed models are capable of accurately predicting the transition temperature, hysteresis, and transformation strain of SMAs across a wide range of compositions. This approach has the potential to significantly accelerate the discovery and design of new SMA materials.

Shreyas Jaikumar Honrao↗