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142 records · Page 8

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NASA NTRS2015

On the Recovery Stress of a Ni50.3Ti29.7Hf20 High Temperature Shape Memory Alloy

Recovery stress in shape memory alloys (SMAs), also known as blocking stress, is an important property generally obtained during heating under a dimensional constraint as the material undergoes the martensitic phase transformation. This property has been instinctively utilized in most SMA shape-setting procedures, and has been used in numerous applications such as fastening and joining, rock splitting, safety release mechanisms, reinforced composites, medical devices, and many other applications. The stress generation is also relevant to actuator applications where jamming loads (e.g., in case the actuator gets stuck and is impeded from moving) need to be determined for proper hardware sizing. Recovery stresses in many SMA systems have been shown to reach stresses in the order of 800 MPa, achieved via thermo-mechanical training such as pre-straining, heat treatments or other factors. With the advent of high strength, high temperature SMAs, recovery stress data has been rarely probed, and there is no information pertinent to the magnitudes of these stresses. Thus, the purpose of this work is to investigate the recovery stress capability of a precipitation strengthened, Ni50.3Ti29.7Hf20 (at.) high temperature SMA in uniaxial tension and compression. This material has been shown to exhibit outstanding strength and stability during constant-stress, thermal cycling, but no data exists on constant-strain thermal cycling. Several training routines were implemented as part of this work including isothermal pre-straining, isobaric thermal cycling, and isothermal cyclic training routines. Regardless of the training method used, the recovery stress was characterized using constant-strain (strain-controlled condition) thermal cycling between the upper and lower cycle temperatures. Preliminary results indicate recovery stresses in excess of 1.5 GPa were obtained after a specific training routine. This stress magnitude is significantly higher than conventional NiTi stress generation capability.

Recovery Stress↗

NASA NTRS2016

Parallel Grand Canonical Monte Carlo (ParaGrandMC) Simulation Code

This report provides an overview of the Parallel Grand Canonical Monte Carlo (ParaGrandMC) simulation code. This is a highly scalable parallel FORTRAN code for simulating the thermodynamic evolution of metal alloy systems at the atomic level, and predicting the thermodynamic state, phase diagram, chemical composition and mechanical properties. The code is designed to simulate multi-component alloy systems, predict solid-state phase transformations such as austenite-martensite transformations, precipitate formation, recrystallization, capillary effects at interfaces, surface absorption, etc., which can aid the design of novel metallic alloys. While the software is mainly tailored for modeling metal alloys, it can also be used for other types of solid-state systems, and to some degree for liquid or gaseous systems, including multiphase systems forming solid-liquid-gas interfaces.

Vesselin I Yamakov↗

NASA NTRS2016

Cu-Al-Ni Shape Memory Single Crystal Wires with High Transformation Temperature

CN-250X is a new material with higher performance than Nickel-Titanium Shape Memory Alloy (SMA). For space mechanisms, the main disadvantage of Nickel-Titanium Shape Memory Alloy is the limited transformation temperature. The new CN-250X Nimesis alloy is a Cu-Al-Ni single crystal wire available in large quantity because of a new industrial process. The triggering of actuators made with this Cu-Al-Ni single crystal wire can range from ambient temperature to 200 C in cycling and even to 250 C in one-shot mode. Another advantage of CN-250X is a better shape recovery (8 to 10%) than Ni-Ti (6 to 7%). Nimesis is the first company able to produce this type of material with its new special industrial process. A characterization study is presented in this work, including the two main solicitation modes for this material: tensile and torsion. Different tests measure the shape recovery of Cu-Al-Ni single crystals wires during heating from room temperature to a temperature higher than temperature of end of martensitic transformation.

Hautcoeur, Alain↗

NASA NTRS2018

Phase Heritage: Deciphering Evidence of Pre-Existing Phases via Inherited Crystallographic Orientations

The concept of 'phase heritage' (e.g., Timms et al., 2017a) involves microstructural recognition of the former presence of a phase that has since transformed to another via evidence encoded in crystallographic orientations. Phase heritage relies on the phenomenon that newly grown (daughter) phases nucleate with particular crystallographic orientation relationships with the preceding (parent) phase. This phenomenon is common for displacive (i.e., shear or martensitic) transformations, well documented in the metals and ceramics literature, but is relatively uncommon in geosciences. This presentation outlines the concepts behind this approach, showcases results from software for automated analysis of EBSD data, and illustrates examples of polymorphic and dissociation phase transformations in the ZrSiO4-ZrO2-SiO2 system, which has particularly useful applications for 'extreme thermobarometry' in impact environments (Timms et al., 2017a).

Timms, Nicholas E.↗

NASA NTRS2019

Investigating Additively Manufactured 17-4 PH for Structural Applications

17-4 is used regularly to manufacture force transducers particularly for wind tunnel testing. Such applications place demanding structural requirements on the transducers with static safety factors of 1.5 common and the potential for additional dynamic loads. Additive manufacturing (AM) of transducers is very appealing because of significant potential cost and time savings as well as increased design flexibility. This study looks at the processing of 17-4 powder using selective laser melting by two different facilities using their own best practices. Hot isostatic pressing (HIP) is used by both facilities as part of the thermomechanical processing following printing to explore whether it can improve the consistency of mechanical properties. Results revealed that HIP reduced average porosity of 17-4 parts and that the yield strength of parts following solutionization and aging met wrought material property targets. Strain to failure of one of the facilities parts was less than 5% compared to greater than 9% for the other facility. Inspection of failure surfaces revealed this discrepancy could be attributed to pores (2-4% area fraction) on the failure surface of the low ductility parts. Phase content varied between the facilities with one facility producing fully martensitic parts and the other containing some retained austenite. The phase content of the starting powder and a slower than air cooling rate following the final heat treatment above the austenite eutectoid temperature are likely sources of the retained austenite. Taken together these results suggest that the current state of the art in AM 17-4 processing is sufficient for many NASA force measurement applications, but that attention is required at each stage of processing to assure desired mechanical properties.

Burns, Devin E.↗

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↗

NASA NTRS2022

Parallel Grand-Canonical Monte Carlo (ParaGrandMC) User’s Manual Version 2.0

This manual describes the commands and command line options for the Parallel Grand Canonical Monte Carlo version 2.0 (ParaGrandMC.2.0) simulation code. This is a highly scalable parallel FORTRAN 2003 code for simulating the thermodynamic evolution of materials at the atomic level, and predicting their thermodynamic state, phase diagram, chemical composition and mechanical properties. The code is specifically designed to simulate multi-component alloy systems, predict solid-state phase transformations such as austenite-martensite transformations, precipitate formation, recrystallization, capillary effects at interfaces, surface absorption, etc., which can aid the design of novel metallic alloys. While the software is mainly tailored for modeling metal alloys, it can also be used for other types of solid-state systems, and to some degree for liquid or gaseous systems, including multiphase systems forming solid-liquid-gas interfaces. In addition to performing Monte Carlo (MC) simulations, the code can also perform Molecular Dynamics (MD) and Langevin Dynamics (LD) simulations, which can be combined and interchanged with MC for faster and more efficient system evolution. A detailed description of the MC part of the code is provided in the NASA ParaGrandMC report: NASA/CR–2016-219202; http://www.sti.nasa.gov.

High performance computing↗

NASA NTRSDate not supplied

Data-Driven Study of Shape Memory Behavior of Multi-Component Ni-Ti Alloys

Ni-Ti based shape memory alloys (SMAs) have found wide-spread use in aerospace, automotive, biomedical, and commercial applications owing to their favorable properties and ease of operation. Especially important for many NASA applications is the ability to tune the martensitic transformation temperature of Ni-Ti alloys by varying the alloy composition and processing conditions. Recently, researchers at NASA have compiled an extensive database of shape memory properties of materials, including over 8,000 multi-component Ni-Ti alloys containing 37 different alloying elements. Using this dataset, machine learning models are trained to predict transformation temperatures, hysteresis, and transformation strain with extremely low mean absolute errors. These models are used to learn relationships between shape memory behavior and input parameters in the composition and processing space. ML predictions are validated through new experiments. The combination of an extensive experimental dataset and accurate learning models, together, make our approach highly suitable for the rapid discovery and design of novel SMAs with targeted properties. We are not aware of any current approaches capable of predicting SMA transformation behavior over such a wide range of compositions and processing conditions.

Shape memory alloys↗

NASA NTRSDate not supplied

Data-Driven Study of Shape Memory Behavior of Multi-component Ni-Ti Alloys

Ni-Ti based shape memory alloys (SMAs) have found wide-spread use in aerospace, automotive, biomedical, and commercial applications owing to their favorable properties and ease of operation. Especially important for many NASA applications is the ability to tune the martensitic transformation temperature of Ni-Ti alloys by varying the composition and processing conditions. Recently, researchers at NASA have compiled an extensive database of shape memory properties of materials, including over 8,000 multi-component Ni-Ti alloys containing 37 different alloying elements. Using this dataset, machine learning models are trained to predict transformation temperatures, hysteresis, and transformation strain with extremely small errors. These models are used to learn relationships between shape memory behavior and input parameters in the composition and processing space. ML predictions are validated through new experiments. The combination of an extensive dataset and accurate learning models, together, make our approach highly suitable for the rapid discovery of novel SMAs with targeted properties.

Shape Memory Alloys↗

NASA NTRS2023

Ruggedness Evaluation of ASTM International Standard Test Methods for Shape Memory Materials: E3098 Standard Test Method for Mechanical Uniaxial Pre-strain and Thermal Free Recovery of Shape Memory Alloys

This paper evaluates the ruggedness testing of the recently released ASTM International E3098 Standard Test Method for Mechanical Uniaxial Pre-strain and Thermal Free Recovery of Shape Memory Alloys. The ruggedness experiment was designed with eight runs in two replicates, consisting of seven factors: strain rate (ė), heating and cooling rates (Ṫ heat and Ṫ cool , respectively), upper and lower cycle temperatures (UCT and LCT, respectively), hold time (t hold ), and minimum load (F min ) imparted on the samples. The results indicate that the strain rate factor had no effect on any result variable, whereas the minimum load factor had a large effect on several result variables including the austenite start and martensite finish temperatures as well as most of the strain measurements from the thermal cycle. The lower cycle temperature factor had a large effect on the stress at maximum strain during pre-straining (e i ), denoted by S i , at ~7.2 MPa, as well as the A f , at 5.47 °C. Closely following the LCT effect, Ṫ heat was found to have a large effect on the austenite start temperature (A s ), at a value of ~2.72 °C. The testing methodology, analysis techniques, and resulting conclusions on the ruggedness of the test method are presented.

Shape memory alloys↗

NASA NTRS2023

Crystallographic and TEM Features of a TBC/Ti2AlC MAX Phase Interface after 1300°C Burner Rig Oxidation

A FIB/STEM interfacial study was performed on a TBC/Ti 2 AlC MAX phase system, oxidized in an aggressive burner rig test (Mach 0.3 at 1300 °C for 500 h). The 7YSZ TBC, α-Al 2 O 3 TGO, and MAXthal 211 TM Ti 2 AlC base were variously characterized by TEM/STEM, EDS, SADP, and HRTEM. The YSZ was a mix of “clean” featureless and “faulted” high contrast grains. The latter exhibited ferro-elastic domains of high Y content tetragonal t″ variants. No martensite was observed. The TGO was essentially a duplex α-Al 2 O 3 structure of inner columnar plus outer equiaxed grains. It maintained a perfectly intact, clean interface with the Ti 2 AlC substrate. The Ti 2 AlC substrate exhibited no interfacial Al-depletion zone but, rather, numerous faults along the basal plane of the hexagonal structure. These are believed to offer a means of depleting Al by forming crystallographic, low-Al planar defects, proposed as Ti 2.5 AlC 1.5 . These characterizations support and augment prior optical, SEM, and XRD findings that demonstrated remarkable durability for the YSZ/Ti 2 AlC MAX phase system in aggressive burner tests.

TI2AlC↗

NASA NTRSDate not supplied

ICME for NASA Aerospace Applications: Batteries for Electric Aviation

NASA’s approach to computational materials modeling is detailed in the NASA Vision 2040 Roadmap for Multiscale Modeling and Simulation of Materials and Systems. This report is in the spirit of national initiatives such as the Material Genome Initiative (MGI), Integrated Computational Materials Engineering (ICME), and others. We utilize a combination of fundamental modeling, computational high-throughput screening, and data science methods, e.g., machine learning, are used to find innovative solutions to NASA or national technology challenges. Applications of interest are wide ranging from advanced alloys to batteries to coatings, among others. In this talk, we present three examples for recent work related to NASA applications. First, doping advanced sulfur battery cathodes with selenium boosts electrical conductivity important for electric aircraft applications. First principles calculations will be discussed that result in compositional design maps for these materials. Second, development of icephobic coatings is important to mitigate safety hazards associated with icing for aircraft. Molecular dynamics simulations are reported for ice-surface interfaces to understand adhesion mechanisms and help screen optimal ice-phobic coatings. Third, shape memory alloys have numerous applications as actuators, superelastic materials, etc. for aerospace. We report machine learning models that predict martensitic transition temperatures across a broad swath of compositional space.

John Lawson↗

NASA NTRS2024

SMAnalytics Automated Shape Memory Test Analysis Software User's Manual: UCFTC, UPER, and DSC Test Methods, Version 1.0.2

Over the course of 60 years of shape memory alloy research and development, the properties of these alloys have been measured using various testing methods, which are often customized by the organization performing the test. However, commercial adoption of shape memory alloys in aeronautic actuator applications requires reducing property uncertainty through standardizing test methods. Historically, differential scanning calorimetry (DSC) has been used to measure transformation temperatures under stress-free conditions. This testing method is well established, and tests are run under the applicable standard, ASTM F2004-17: Standard Test Method for Transformation Temperature of Nickel-Titanium Alloys by Thermal Analysis. Two other test methods for measuring strains and transformation temperatures under constant load or free recovery after prestraining have only recently been standardized—ASTM E3097: Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of SMAs (UCFTC) and ASTM E3098: Standard Test Method for Mechanical Uniaxial Pre-Strain and Thermal Free Recovery of SMAs (UPFR). These standards represent a critical step forward in producing reliable material property data for the use of these alloys in aeronautics and other commercial areas. However, no standard programs or software packages were previously available for postprocessing UCFTC- and UPFR-type test data to extract property data. Each organization that performed the testing analyzed data using its own custom manual methods, such as using a plot and a straight edge, spreadsheet plotting methods, or custom code routines, to extract the required values for strains, stresses, and transformation temperatures. SMAnalytics represents the first publicly available uniform software package for processing data generated using the DSC, UCFTC, and UPFR test methods, as well as many modifications of these methods, including loading in martensite versus austenite and performing multiple thermal cycles at stress. In doing so, it provides a tool for reducing potential error or variability in the measured values due to the precision of the technique used and person-to-person variability. It is also expected that this automated data-parsing tool can accelerate the data analysis phase of the test campaign, especially for large data files. This User’s Manual describes how the SMAnalytics software works and the method for its use.

Shape Memory Alloy↗

NASA NTRSDate not supplied

Wear-Resistance Investigations on Ceramic Coatings for Lunar Dust Mitigation

Lunar dust has posed a major challenge to exploration efforts due to abrasion and impact. This work focuses on fundamental studies on ceramic coatings as candidates for enhanced resistance to impact and wear. As a first step, standard and modified approaches to the method of abrasion testing were explored for options to incorporate lunar regolith as wear media, the effects of which were presented for AL6061-T6 control samples. Following this, wear results for air plasma-sprayed (APS) alumina coatings were investigated due to their superior strength and surface hardness. In addition, APS 8 wt % yttria-stabilized zirconia (8YSZ) coatings were studied for their strength and martensitic transformation toughness. Measurements were made by assessing the mass loss, with a standard scale at various intervals. In addition, surface roughness was measured with a profilometer and features identified with a high-resolution microscope. The findings demonstrated that wear media has a distinct effect on the abrasion. The alumina coatings demonstrated improved wear over 8YSZ. However, the tailorability of 8YSZ makes it an attractive option to continue to modify as a wear-resistant coating to protect against lunar dust abrasion. The results of these measurements provide insight into the wear behavior of future directions in candidate ceramic coatings for the harsh lunar environment.

ceramic coatings↗

NASA NTRSDate not supplied

Wear-Resistance Investigations on Ceramic Coatings for Lunar Dust Mitigation

ceramic coatings↗

NASA NTRS2017

Precipitation Strengthenable NiTiPd High Temperature Shape Memory Alloys

In binary NiTi alloys, it has long been known that Ni-rich alloys can be heat treated to produce precipitates which both strengthen the matrix against dislocations and improve the behavior of the material under thermal and mechanical cycling. Within recent years, the same effect has been observed in Ni-rich NiTiHf high temperature shape memory alloys and heat treatment regimens have been defined which will reliably produce improved properties. In NiTiPd alloys, precipitation has also been observed, but studies are still underway to define reliable heat treatments and compositions which will provide a balance of strengthening and good thermomechanical properties. For this study, a series of NiTi-32 at.Pd alloys was produced to determine the effect of changing nickeltitanium content on the transformation behavior and heat treatability of the material. Samples were aged at temperatures between 350C and 450C for times up to 100 hours. Actuation type behavior was evaluated using uniaxial constant force thermal cycling (UCFTC) to determine the effect of composition and aging on the material behavior. TEMSEM was used to evaluate the microstructure and determine the types of precipitates formed. The correlation between composition, heat treat, microstructure, and thermomechanical behavior will be addressed and discussed.

Transformation strain↗