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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.

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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Strut Shaping of 34m Beam Waveguide Antenna for Reductions in Near-Field RF and Noise Temeperature

Struts shaping of the NASA's Deep Space Network (DSN) 34m Beam Waveguide (BWG) antenna has been implemented to reduce near-field RF exposure while improving the antenna noise temperature. Strut shaping was achieved by introducing an RF shield that does not compromise the structural integrity of the existing structure. Reduction in the RF near-field exposure will compensate for the planned transmit power increase of the antenna from 20 kW to 80 kW while satisfying safety requirements for RF exposure. Antenna noise temperature was also improved by as much as 1.5 K for the low elevation angles and 0.5 K in other areas. Both reductions of RF near-field exposure and antenna noise temperature were verified through measurements and agree very well with calculated results.

reflector↗
NASA NTRS2015

Self-Repairing Fatigue Damage in Metallic Structures for Aerospace Vehicles Using Shape Memory Alloy Self-healing (SMASH) Technology

This DAA is for the Phase II webinar presentation of the ARMD-funded SMASH technology. A self-repairing aluminum-based composite system has been developed using liquid-assisted healing theory in conjunction with the shape memory effect of wire reinforcements. The metal matrix composite was thermodynamically designed to have a matrix with a relatively even dispersion of low-melting phase, allowing for repair of cracks at a pre-determined temperature. Shape memory alloy wire reinforcements were used within the composite to provide crack closure. Investigators focused the research on fatigue cracks propagating through the matrix in order to optimize and computer model the SMASH technology for aeronautical applications.

fatigue↗
NASA NTRS2015

Shape Memory Alloy Rock Splitters (SMARS) - A Non-Explosive Method for Fracturing Planetary Rocklike Materials and Minerals

A static rock splitter device based on high-force, high-temperature shape memory alloys (HTSMAs) was developed for space related applications requiring controlled geologic excavation in planetary bodies such as the Moon, Mars, and near-Earth asteroids. The device, hereafter referred to as the shape memory alloy rock splitter (SMARS), consisted of active (expanding) elements made of Ni50.3Ti29.7Hf20 (at.%) that generate extremely large forces in response to thermal input. The preshaping (training) of these elements was accomplished using isothermal, isobaric and cyclic training methods, which resulted in active components capable of generating stresses in excess of 1.5 GPa. The corresponding strains (or displacements) were also evaluated and were found to be 2 to 3 percent, essential to rock fracturing and/or splitting when placed in a borehole. SMARS performance was evaluated using a test bed consisting of a temperature controller, custom heaters and heater holders, and an enclosure for rock placement and breakage. The SMARS system was evaluated using various rock types including igneous rocks (e.g., basalt, quartz, granite) and sedimentary rocks (e.g., sandstone, limestone).

NiTiHf↗
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 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

Applications of Displacement Transfer Functions to Deformed Shape Predictions of the G-III Swept-Wing Structure

In support of the Adaptive Compliant Trailing Edge [ACTE] project at the NASA Armstrong Flight Research Center, displacement transfer functions were applied to the swept wing of a Gulfstream G-III airplane (Gulfstream Aerospace Corporation, Savannah, Georgia) to obtain deformed shape predictions. Four strainsensing lines (two on the lower surface, two on the upper surface) were used to calculate the deformed shape of the G III wing under bending and torsion. There being an insufficient number of surface strain sensors, the existing G III wing box finite element model was used to generate simulated surface strains for input to the displacement transfer functions. The resulting predicted deflections have good correlation with the finite-element generated deflections as well as the measured deflections from the ground load calibration test. The convergence study showed that the displacement prediction error at the G III wing tip can be reduced by increasing the number of strain stations (for each strain-sensing line) down to a minimum error of l.6 percent at 17 strain stations; using more than 17 strain stations yielded no benefit because the error slightly increased to 1.9% when 32 strain stations were used.

displacement theory↗
NASA NTRS2017

Additive Manufacturing of NiTiHf High Temperature Shape Memory Alloy

Additive manufacturing of a NiTi-20Hf high temperature shape memory alloy (HTSMA) was investigated. A selective laser melting (SLM) process by Phenix3D Systems was used to develop components from NiTiHf powder (of approximately 25-75 m particle fractions), and the thermomechanical response was compared to the conventionally vacuum induction skull melted counterpart. Transformation temperatures of the SLM material were found to be slightly lower due to the additional oxygen pick up from the gas atomization and melting process. The shape memory response in compression was measured for stresses up to 500 MPa, and transformation strains were found to be very comparable (Up to 1.26 for the as-extruded; up to 1.52 for SLM).

NiTiHf; High Temperature Shape Memory Alloys; Addi↗
NASA NTRS2018

Wing Shaping and Gust Load Controls of Flexible Aircraft: An LPV Approach

In the proposed paper, the optimum wing shape of a highly flexible aircraft under varying flight conditions will be controlled by a linear parameter-varying approach. The optimum shape determined under multiple objectives, including flight performance, ride quality, and control effort, will be determined as well. This work is an extension of work done previously by the authors, and updates the existing optimization and utilizes the results to generate a robust flight controller.

Gust Load Alleviation↗
NASA NTRS2018

Influence of Thin-Film Adhesives in Pullout Tests Between Nickel-Titanium Shape Memory Alloy and Carbon Fiber-Reinforced Polymer Matrix Composites

Strips of nickel-titanium (NiTi) shape memory alloy (SMA) and carbon fiber-reinforced polymer matrix composite (PMC) were bonded together using multiple thin film adhesives and their mechanical strengths were evaluated under pullout test configuration. Tensile and lap shear tests were conducted to confirm the deformation of SMAs at room temperature and to evaluate the adhesive strength between the NiTi strips and the PMC. Optical and scanning electron microscopy techniques were used to examine the interfacial bonding after failure. Simple equations on composite tensile elongation were used to fit the experimental data on tensile properties. ABAQUS models were generated to show the effects of enhanced bond strength and the distribution of stress in SMA and PMC. The results revealed that the addition of thin film adhesives increased the average adhesive strength between SMA and PMC while halting the room temperature shape memory effect within the pullout specimen.

Polymer Matrix Composites↗
NASA NTRS2018

Application of Machine-Learning Algorithms for On-Board Asteroid Shape Model Determination

The Application of Machine-learning Algorithms for On-board Asteroid Shape Model Determination project will develop an innovative system for spacecraft navigation to expand the capability of small spacecraft to meet the critical challenges associated with small-body exploration. Such challenges include accurate navigation in a microgravity environment and precision targeting of particular locations on an asteroid surface for sample collection. This on-board system will cut the computational "umbilical" back to Earth-currently necessary for the generation of a global shape model that requires thousands of images with sufficient resolution and adequate variation of incidence and emission angles, processed manually by a team of experts on Earth for several months. Small satellites have limited bandwidth and are unable to downlink the data volume required for this processing, restricting their ability to perform deep-space asteroid exploration.

Machine learning algorithms↗
NASA NTRS2016

Diffraction Modeling of Finite Subband EFC Probing on Dark Hole Contrast with WFIRST-CGI Shaped Pupil Coronagraph

The current NASA WFIRST (Wide-Field InfraRed Survey Telescope) coronagraph instrument (CGI) design allocates two subband filters per each full science band in order to contain system complexity and cost. We present our detailed investigation results on the adequacy of such a limited number of finite subband filters in achieving broadband dark hole contrast with a shaped pupil coronagraph (SPC). The study is based on diffraction propagation modeling with realistic WFIRST optics, where each subband’s image plane electric field is estimated from pairwise pupil plane deformable mirror (DM) probing and image plane intensity averaging of the resulting fields of multiple (subband) wavelengths. Multiple subband choices and probing and control strategies are explored, including standard subband probing; mixed wavelength and/or weighted Jacobian matrix; subband probing with intensity subtraction; and extended subband probing with intensity subtraction. Overall, the investigation shows that the achievable contrast with a limited number of finite subbands is about 2~2.5x worse than the designed contrast for the current SPC. The result suggests that future shaped pupil designs should be optimized for slightly broader bandwidths than the intended science bandpasses if limited subbands are used for wavefront sensing via probing.

WFIRST↗
NASA NTRSDate not supplied

Composition-property correlations in NiTi-based shape memory alloys from the first principles

Development of shape memory alloys (SMA) has been traditionally accomplished by means of extensive empirical efforts, with a very limited support from phenomenological models and related tools. We present a theoretical framework based on the Hamiltonian formalism, which connects important thermodynamic properties directly to the relative energies (the eigenvalues of the Hamiltonian), computed from the first principles using density functional theory. The estimates based on this formalism allow to establish correlations between composition and physical properties, such as relative energies, phase transition temperatures, hysteresis, thermal expansion, and other thermodynamic information. Importantly, estimates and correlations not only provide a fast answer, but also elucidate underpinning of thermodynamic features in terms of the electronic structure. Using this framework, we consider phase transformations and correlations between the selected properties and composition in the NiTi-based ternary and multicomponent shape memory alloys. Our theoretical guidance facilitates design and development of future alloys.

shape memory alloys↗
NASA NTRSDate not supplied

Controlling properties by chemistry in doped shape memory alloys

Shape memory alloys find increasing use in airspace applications. Using theoretical and computational methods, we investigate correlations between the selected properties and composition in doped NiTi-based shape memory alloys. Among the properties we consider relative energies, phase transition temperature, and hysteresis. We compare predictions to experimental data. Our theoretical guidance facilitates design of future alloys. We acknowledge support from the NASA Transformative Aeronautics Concepts Program, Transformational Tools & Technologies (TTT) Project.

NiTi↗
NASA NTRSDate not supplied

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

Solar sail deformation leads to disturbance torques from solar radiation pressure, driving performance requirements for momentum management systems. For the Solar Cruiser technology demonstrator mission, we have developed a model leveraging neural network-based machine learning to derive sail shape characteristics. The model uses torque and attitude telemetry simulated from a reduced-order tensor model of the deformed sail mesh over a characterization sequence. The machine learning model predicts sail boom deflection with comparable accuracy to that of an onboard context camera. This model can discover sail shape with no additional mass or data downlink requirements, allowing for validation of sail force modeling assumptions using in flight data. The results from the project hold promise for the further implementation of machine learning techniques in solar sail telemetry analysis and control.

solar sail↗
NASA NTRSDate not supplied

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

Solar sail deformation leads to disturbance torques from solar radiation pressure, driving performance requirements for momentum management systems. For the Solar Cruiser technology demonstrator mission, we have developed a model leveraging neural network-based machine learning to derive sail shape characteristics. The model uses torque and attitude telemetry simulated from a reduced-order tensor model of the deformed sail mesh over a characterization sequence. The machine learning model predicts sail boom deflection with comparable accuracy to that of an onboard context camera. This model can discover sail shape with no additional mass or data downlink requirements, allowing for validation of sail force modeling assumptions using in flight data. The results from the project hold promise for the further implementation of machine learning techniques in solar sail telemetry analysis and control.

solar sail↗
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

Experimental Characterization of Additively Manufactured Nickel-Titanium Shape Memory Alloy Heat Pipes

Shape memory alloys (SMA) have been identified for use in spacecraft components as replacement for conventional deployment mechanisms. They may be used in thermal management components such as radiators to create self-deploying radiators. One SMA, NiTi, has also been developed for additive manufacturing processes. Heat pipes are a common way to create highly effective and lightweight spaceflight radiators, and heat pipes can also be made from NiTi and related alloys. The wick is the critical element of a functioning heat pipe, and recent progress over the past years has led to the development of additively manufactured heat pipe wicks in various materials. The combination of these efforts is the focus of this project: creating an additively manufactured, shape memory alloy self-deploying heat pipe radiator. This paper will focus on the experimental characterization of these additively manufactured NiTi heat pipes. The heat pipe coupons were additively manufactured by direct metal laser sintering (DMLS), with an integral liquid cooled condenser. Heat is input to the heat pipe via a thin film heater. Thermocouples were spot welded to the heat pipes to measure temperature at several axial locations. The heat pipes were tested with two working fluids: water and ethanol. Ethanol is not an ideal working fluid for heat pipes but is useful in characterizing them because it wets well to a wide variety of surfaces. Water is in general a superior working fluid for heat pipes, but its contact angle and therefore wicking performance strongly depends on the surface chemistry of the surface it is in contact with. A particular measurement of interest in this test is the evaporator to condenser thermal conductance, which will be compared in the full paper to recently published correlations for additively manufactured heat pipes. Experimental results for two straight geometry and one bellows geometry heat pipe will be presented. The bellows geometry is of interest for condenser of the self-deploying radiator design.

Additive manufacturing↗