Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Method of manufactured solutions”

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.

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

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Methods for making bifunctional porous non-noble metal phosphide catalyst for overall water splitting, electrodes for overall water splitting, and methods for electrocatalytic water splitting

A method of manufacturing a bifunctional electrocatalyst for overall water splitting comprising oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) by growing electrocatalyst comprising primarily metallic phosphides on a three-dimensional substrate by: immersing the substrate in an iron nitrate solution to form a once disposed substrate; subjecting the once disposed substrate to thermal phosphidation with phosphorus powder under inert gas to grow metal phosphides thereupon and form a once subjected substrate; cooling the once subjected substrate to form a cooled, once subjected substrate; immersing the cooled, once subjected substrate in an iron nitrate solution to form a twice disposed substrate; and subjecting the twice disposed substrate to thermal phosphidation with phosphorus powder under inert gas to provide an electrode comprising the bifunctional electrocatalyst on the three-dimensional substrate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2014

3D Printing in Zero-G ISS Technology Demonstration

The National Aeronautics and Space Administration (NASA) has a long term strategy to fabricate components and equipment on-demand for manned missions to the Moon, Mars, and beyond. To support this strategy, NASA and Made in Space, Inc. are developing the 3D Printing In Zero-G payload as a Technology Demonstration for the International Space Station. The 3D Printing In Zero-G experiment will be the first machine to perform 3D printing in space. The greater the distance from Earth and the longer the mission duration, the more difficult resupply becomes; this requires a change from the current spares, maintenance, repair, and hardware design model that has been used on the International Space Station up until now. Given the extension of the ISS Program, which will inevitably result in replacement parts being required, the ISS is an ideal platform to begin changing the current model for resupply and repair to one that is more suitable for all exploration missions. 3D Printing, more formally known as Additive Manufacturing, is the method of building parts/ objects/tools layer-by-layer. The 3D Print experiment will use extrusion-based additive manufacturing, which involves building an object out of plastic deposited by a wire-feed via an extruder head. Parts can be printed from data files loaded on the device at launch, as well as additional files uplinked to the device while on-orbit. The plastic extrusion additive manufacturing process is a low-energy, low-mass solution to many common needs on board the ISS. The 3D Print payload will serve as the ideal first step to proving that process in space. It is unreasonable to expect NASA to launch large blocks of material from which parts or tools can be traditionally machined, and even more unreasonable to fly up specialized manufacturing hardware to perform the entire range of function traditionally machining requires. The technology to produce parts on demand, in space, offers unique design options that are not possible through traditional manufacturing methods while offering cost-effective, high-precision, low-unit on-demand manufacturing. Thus, Additive Manufacturing capabilities are the foundation of an advanced manufacturing in space roadmap.

Johnston, Mallory M.↗
DOE OSTI2026

Towards a Unified Low-Cost Flow Plate, Flow-Field, PTL Solution for Proton Exchange Membrane Electrolyzers

Proton exchange membrane (PEM) water electrolysis is a highly efficient method for hydrogen production. Research cells typically consist of one proton exchange membrane, two catalyst layers, two porous transport layers, two flow-field plates, and two endplates. In commercial systems, the machined flow-field plates that are employed in research cells are typically replaced by stamped parts or open mesh material solutions to reduce manufacturing cost at scale. Nonetheless, the cell contains about 8 total interfaces: bipolar plate / flow plate material / porous transport medium / electrode / membrane / electrode / porous transport medium / flow plate material / bipolar plate. All these materials and interfaces need to be optimized for maximum performance and efficiency. Reducing the amount of interfaces by combining individual cell components directly benefits the fabrication cost (by reducing the parts count and the needs for surface coatings) and the electrochemical performance (by reducing ohmic losses). We have designed a novel PEM electrolysis cell with a piece of channeled titanium felt functioning as both the anode flow-field and the PTL, referred to as the channeled diffusion layer (CDL). The pores of the felt facilitate both in-plane and through-plane diffusion, ensuring maximum catalyst utilization while also minimizing mass transport loss. The titanium felt can be mass manufactured with existing stamping and forming methods and is therefore a promising candidate to reduce the capital cost of PEM electrolyzers whilst improving hydrogen production efficiency. Experiments conducted with 3mg IrOx/cm2 loading MEAs have shown a approximately 40% boost in peak current by implementing the CDL design. Low catalyst-loading MEAs are being tested in ongoing experiments and their results will be discussed and compared.

08 HYDROGEN↗
DOE OSTI2024

Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)

RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Reference solutions for linear radiation transport: the Hohlraum and Lattice Benchmarks

Radiation transport describes the propagation of energetic particles through space as they interact with a surrounding material medium. In a kinetic description, radiation transport is modeled by a radiation transport equation (RTE) that prescribes the density of the radiation in position-momentum phase space. The purpose of this dataset is to provide highly resolved solutions to two benchmark problems. These two benchmarks do not possess exact solutions; moreover, the construction of a manufactured solution may require a non-physical source that is not desirable, especially if it spoils the physical nature of the solution. Thus the goal of this computational study is to provide a highly resolved reference solution for testing newer, more cost efficient methods that are currently being developed in the research community.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Quantifying Uncertainty of Landing and Takeoff Noise for Commercial Supersonic Aircraft

Of the many challenges faced by manufacturers attempting to offer supersonic travel to the public, the uncertainty in predicting the noise of these aircraft in airport operations has an immediate impact. No noise regulation exists in FAA or ICAO for certifying such aircraft, as these organization require solid data, usually from existing aircraft. Manufacturers are taking large risks to design a vehicle not knowing whether it will be allowed to fly. A partial solution to this conundrum is to use physics-based simulations to provide the “data” used to calibrate system-level prediction methods, carefully documenting the uncertainty of the method for application to supersonic aircraft. A close look at the accuracy of empirical prediction methods points to areas where improvements need to be made if noise studies of supersonic aircraft are to be useful. As NASA embarks on a focused research program to improve predictions of noise from the noise-dominant propulsion noise of commercial supersonic aircraft, this paper documents the work done to baseline the uncertainties found in today’s noise prediction methods. A relatively simplistic method was developed, summarizing the error of the empirical methods on a component basis and following their impact on the total aircraft during landing and takeoff operations using Monte Carlo analysis. By this method it is found that current empirical noise prediction methods have an uncertainty of 1.5 EPNdB cumulative for propulsion noise of a representative conventional subsonic passenger aircraft. When applied to likely near-term supersonic commercial aircraft, the uncertainty is 7.6 EPNdB cumulative, a difference that must be reduced if the prediction methods are to guide decision makers.

Airport noise↗
DOE OSTI2020

Quantum computing based hybrid solution strategies for large-scale discrete-continuous optimization problems

Quantum computing (QC) has gained popularity due to its unique capabilities that are quite different from that of classical computers in terms of speed and methods of operations. This paper proposes hybrid models and methods that effectively leverage the complementary strengths of deterministic algorithms and QC techniques to overcome combinatorial complexity for solving large-scale mixed-integer programming problems. Four applications, namely the molecular conformation problem, job-shop scheduling problem, manufacturing cell formation problem, and the vehicle routing problem, are specifically addressed. Large-scale instances of these application problems across multiple scales ranging from molecular design to logistics optimization are computationally challenging for deterministic optimization algorithms on classical computers. To address the computational challenges, hybrid QC-based algorithms are proposed and extensive computational experimental results are presented to demonstrate their applicability and efficiency. The proposed QC-based solution strategies enjoy high computational efficiency in terms of solution quality and computation time, by utilizing the unique features of both classical and quantum computers.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2000

Validated Feasibility Study of Integrally Stiffened Metallic Fuselage Panels for Reducing Manufacturing Costs

The continual need to reduce airframe cost and the emergence of high speed machining and other manufacturing technologies has brought about a renewed interest in large-scale integral structures for aircraft applications. Applications have been inhibited, however, because of the need to demonstrate damage tolerance, and by cost and manufacturing risks associated with the size and complexity of the parts. The Integral Airframe Structures (IAS) Program identified a feasible integrally stiffened fuselage concept and evaluated performance and manufacturing cost compared to conventional designs. An integral skin/stiffener concept was produced both by plate hog-out and near-net extrusion. Alloys evaluated included 7050-T7451 plate, 7050-T74511 extrusion, 6013-T6511 extrusion, and 7475-T7351 plate. Mechanical properties, structural details, and joint performance were evaluated as well as repair, static compression, and two-bay crack residual strength panels. Crack turning behavior was characterized through panel tests and improved methods for predicting crack turning were developed. Manufacturing cost was evaluated using COSTRAN. A hybrid design, made from high-speed machined extruded frames that are mechanically fastened to high-speed machined plate skin/stringer panels, was identified as the most cost-effective manufacturing solution. Recurring labor and material costs of the hybrid design are up to 61 percent less than the current technology baseline.

Pettit, R. G.↗
DOE OSTI2021

Collaboration on SBIR/TTO Phase II Project for Optical QC Device and Collaboration on SBIR/TTO Phase II-b Project for Advanced Quality Inspection Device Development: Cooperative Research and Development CRADA Number CRD-16-00652 (Final Report)

The overall goal of this program is to develop and commercialize a turnkey quality control solution for the entire PEM fuel cell manufacturing process including membrane, gas diffusion layers, catalyst, and assembled systems. This quality control solution is unique to each customer’s specific needs but includes a suite of in-line quality control systems for roll-to-roll manufacturing that can target thin, transparent membrane as well as opaque membrane, catalyst, and GDLs. The Phase II developed the CPNUVV system for thin, transparent membrane that operates using polarized filters to enhance defect resolution and determine thickness. However, PEM material manufacturers want a complete, turnkey solution for all components of the PEM fuel cell. In the Phase IIB, Mainstream will partner with NREL, and transition reflectance technology NREL developed (US Patent 9,234,843) to operate in real-time on a web-line to develop a total solution to PEM quality control. The device will identify and mark defects as well as monitor materials thickness in real-time to improve line efficiency and to reduce waste. The research performed at NREL under this CRADA increases the basis of knowledge about optical inspection methods, how they perform with regards to fuel cell component materials, and how they can be implemented in in-line, real-time configurations to provide quality inspection for roll-to-roll (R2R) manufacturing. Methods explored were found to be sensitive to catalyst loading in electrodes on both membrane and gas diffusion media substrates and to membrane thickness, across a broad range of thickness. The latter capability is novel and now patented and provides a previously unstudied and undemonstrated capability for R2R manufacturing of membranes.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Fabrication of ceramic to metal graded structure for high temperature CSP receiver application using solid state additive manufacturing

The overarching goal of this project is to come up with an innovative joining solution for integration of SiC ceramic to structural materials such as stainless steels (SS)/Ni-base alloys, where intimate metallurgical bonding between SiC ceramic and the structural metallic alloy is demonstrated at the interface. Implementation of a simple, yet robust joining method would help in increasing the application space of SiC in a high-temperature CSP (concentrated solar power) plant, especially in the receiver section. This research goal has been achieved by creating a functionally graded material (FGM) interface between SiC and the selected structural material with the help of powder metallurgy (PM) approach and demonstrate intimate metallurgical bonding between monolithic RB-SiC and 316L stainless steel alloy blanks.

36 MATERIALS SCIENCE↗
NASA NTRS2022

Test methods for image-based information in next-generation manufacturing

Typical control designs in the process systems engineering literature have assumed that the primary sensing methodologies are traditional instruments such as thermocouples. Digitalization is changing the landscape for manufacturing, and data-based sensing modalities (e.g., image-based sensing) are becoming of greater interest for plant control. These considerations require novel test/evaluation solutions. For example, process systems engineering researchers may wish to test image-based sensors in simulation. In this work, we provide preliminary thoughts on how image-based technologies might be evaluated via simulation for process systems.

Henrique Oyama↗
NASA NTRS2011

Design of a Robotic Ankle Joint for a Microspine-Based Robot

Successful robotic exploration of near-Earth asteroids necessitates a method of securely anchoring to the surface of these bodies without gravitational assistance. Microspine grip- per arrays that can grasp rock faces are a potential solution to this problem. A key component of a future microspine-based rover will be the ankle used to attach each microspine gripper to the robot. The ankle's purpose is twofold: 1) to allow the gripper to conform to the rock so a higher percentage of microspines attach to the surface, and 2) to neutralize torques that may dislodge the grippers from the wall. Parts were developed using computer aided design and manufactured using a variety of methods including selective laser sintering, CNC milling, and traditional manual machining techniques. Upon completion of the final prototype, the gripper and ankle system was tested to demonstrate robotic engagement and disengagement of the gripper and to determine load bearing ability. The immediate application of this project is to out t the Lemur IIb robot so it can climb and hang from rock walls.

Near-Earth objects↗
DOE OSTI2022

Enriched immersed boundary method (EIBM) for interface-coupled multi-physics and applications to convective conjugate heat transfer

It is challenging to develop numerical methods that simultaneously maintain accuracy of resolving boundary conditions and mesh flexibility to handle the interface in interface-coupled multi-physics problems involving large property discontinuity. On the one hand, boundary-fitted methods possess high accuracy in capturing the interfacial phenomenon but involve complicated volumetric mesh generation, mesh-motion, and even re-meshing procedures. On the other hand, immersed boundary methods (IBM) provide mesh flexibility but sometimes suffer from inferior interface representations, leading to poor enforcement of boundary conditions. This paper presents an enriched immersed boundary method (EIBM) to overcome this challenge and demonstrates its efficacy in conjugate heat transfer, a representative example in interface-coupled multi-physics systems that have implications for many industrial processes. Further, the core technique of the method is to enhance IBM’s accuracy of the fluid–solid interface by enriching the degrees of freedom of the cut elements to enforce temperature and flux compatibilities and resolve all the physical unknowns on the background mesh to simplify the volumetric mesh generation. We implement the EIBM under the framework of a variational multiscale formulation for coupled Navier–Stokes and thermodynamics equations. The enriched DoFs enable better enforcement of temperature and flux compatibilities with large conductivity ratios across the fluid–solid interface. At the same time, the immersed nature of the proposed method still attains mesh flexibility. The EIBM’s accuracy is thoroughly evaluated through a set of examples, ranging from benchmark problems with analytical solutions to real-world cooling processes of a moving metallic structure with complex geometry.

42 ENGINEERING↗
DOE OSTI2022

Effect of coaxial nozzle wear on catchment efficiency in direct energy deposition built components

Laser based Direct Energy Deposition (DED) systems using metallic powder feedstock are recognized as a promising manufacturing method for their ability to shorten production cycles and create complex part geometries. Components are built by generating a melt pool with a high-power laser beam while material is coaxially injected and left to solidify. An impediment to large scale use of DED lies in poor powder catchment efficiency, the condition in which a portion of injected powder escapes the melt pool resulting in a ratio of decreased printed material mass to mass of supplied feedstock. The wear state of a coaxial nozzle on a DED system within a hybrid manufacturing machine tool has been observed to decrease catchment efficiency over time. Herein this study investigates this effect by adapting flow visualization techniques to an in-situ process monitoring format, the implementation of a Computational Fluid Dynamics (CFD) simulation, and deposition testing. Nozzle geometric defects due to wear are identified and categorized, and the impact of nozzle tip wear, resulting in axial tip reduction, on powder catchment efficiency is proven by multiple calculation methods. A linear correlation between catchment efficiency and powder stream diameter is identified, causing a 15–20% loss in efficiency sustained over incremental nozzle tip reduction up to − 1 mm. These results provide a foundation for further study of wear effects and Zero defect manufacturing solutions for powder fed DED systems.

42 ENGINEERING↗
DOE OSTI2024

Photonic curing for innovative fabrication of flexible metal oxide optoelectronics

Abstract Flexible optoelectronics, based on non-planar substrates, hold promise for diverse applications such as wearables, health monitors, and displays due to their cost-effective manufacturing methods. Despite the superior properties of metal oxides, the challenge of processing them at high temperatures incompatible with plastic substrates necessitates innovative annealing approaches. Photonic curing, which delivers microsecond to millisecond broadband (200–1500 nm) light pulses on a sample, emerges as a viable solution. Depending on the optical properties, the targeted film absorbs the radiant energy resulting in rapid heating while the transparent substrate absorbs a minimal amount of light and remains at ambient temperature. The light intensity can be high, but since the light pulse is short, the total energy absorbed by the sample remains low and will not damage the plastic substrate. This perspective explores the innovative application of photonic curing to fabricate flexible metal oxide optoelectronics, including thin-film transistors, metal–insulator–metal devices, solar cells, transparent conductors, and Li batteries, emphasizing the conversion of sol–gel precursors to metal oxides. However, this technique was initially developed for sintering metal nanoparticles to conductive patterns and poses intriguing challenges in explaining its mechanism for metal oxide conversion, especially considering the limited absorption of visible light by most sol–gel precursors. The review delves into UV-induced photochemistry, common flexible metal-oxide optoelectronic components, and non-intuitive distinctions between photonic curing and thermal annealing. By elucidating the distinctive role of photonic curing in overcoming temperature-related challenges and advancing the fabrication of flexible metal oxide optoelectronics, this perspective offers valuable insights that could shape the future of flexible optoelectronics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Implementation of Sacrificial Support Structures for Hybrid Manufacturing of Thin Walls

Thin-walled features can be difficult to produce with traditional machining methods which often rely on excess stock material for stiffness. This challenge is increased in hybrid manufacturing where the feature is already near net shape before machining. Significant workpiece deflection can result in poor geometric and surface finish tolerances on the finished part. A potential solution to this problem is to implement sacrificial support structures to the as-printed geometry. The supports are then machined away during the finishing portion of the hybrid process. In the present work, several different design parameters for these sacrificial supports were evaluated to determine their impact on the quality of representative thin wall geometry samples. The angle, height, and spacing of triangular support structures were varied for each sample and then machined and examined. The addition of these supports relative to an unsupported configuration provided a deflection reduction of around 0.2 mm. Surface roughness was improved by approximately 1.5 µm. Increasing values of support height were found to correspond to reduced wall deflection. Similarly, decreasing values of support angle and support spacing improved geometric accuracy. Efficiency comparisons showed that increases in print time corresponded to rapidly diminishing gains in geometric accuracy but continued to improve surface roughness. Implications for hybrid finishing of additively manufactured thin-walled structures is briefly discussed.

36 MATERIALS SCIENCE↗
NASA NTRS2013

SpiderFab(TradeMark):Process for On-Orbit Construction of Kilometer-Scale Apertures

The SpiderFab effort investigated the value proposition and technical feasibility of radically changing the way we build and deploy spacecraft by enabling space systems to fabricate and integrate key components on-orbit. Weeveloped an architecture for a SpiderFab system, identifying the key capabilities, and detailed two concept implementations of this architecture, one specialized for fabricating support trusses for large solar arrays, and the second a robotic system capable of fabricating spacecraft components such as antenna reflectors. We then performed analyses to evaluate the value proposition for on-­orbit fabrication, and in each case found that the dramatic improvements in structural performance and packing efficiency enabled by on-orbit fabrication can provide order-of-magnitude improvements in key system metrics. For phased-­‐array radars, SpiderFab enables order-­of-­magnitude increases in gain-per-stowed-volume. For the New Worlds Observer mission, SpiderFab construction of a starshade can provide a ten-fold increase in the number of Earth-like planets discovered per dollar. For communications systems, SpiderFab can change the cost equation for large antenna reflectors, enabling affordable deployment of much larger apertures than feasible with current deployable technologies. To establish the technical feasibility, we identified methods for combining several additive manufacturing technologies with robotic assembly technologies, metrology sensors, and thermal control techniques to provide the capabilities required to implement a SpiderFab system. We performed proof-­of-concept level testing of these approaches, in each case demonstrating that the proposed solutions are feasible, and establishing the SpiderFab architecture at TRL-3. Further maturation of SpiderFab to mission-readiness is well-suited to an incremental development program. Affordable smallsat demonstrations will prepare the technology for full-scale demonstration that will unlock the full potential of the SpiderFab architecture by flight qualifying and validating an on-orbit fabrication and integration process that can be re-used to reduce the life-cycle cost and increase power, bandwidth, resolution, and sensitivity for a wide range of NASA Science and Exploration missions.

Hoyt, Robert↗
NASA NTRS2018

Nickel Titanium Alloys, Methods of Manufacture Thereof and Article Comprising the Same

Disclosed herein is a shape memory alloy comprising 48 to 50 atomic percent nickel, 15 to 30 atomic percent hathium, 1 to 5 atomic percent aluminum; with the remainder being titanium. Disclosed herein too is a method of manufacturing a shape memory alloy comprising mixing together to form an alloy nickel, hafnium, aluminum and titanium in amounts of 48 to 50 atomic percent nickel, 15 to 30 atomic percent hafnium, 1 to 5 atomic percent aluminum; with the remainder being titanium; solution treating the alloy at a temperature of 700 to 1300.degree. C. for 50 to 200 hours; and aging the alloy at a temperature of 400 to 800.degree. C. for a time period of 50 to 200 hours to form a shape memory alloy.

Manuel, Michele Viola↗