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Solid State Memory Study Final Report

Existing and future solid state nonvolatile memory technologies are described and evaluated in this report. Solid state memory technologies can offer size, speed, power, weight, and ruggedness advantages over conventional moving media storage technologoies such as disk or tape. This technology list is a broad sampling of past, present, emerging, and future solid state memory technologies.

Solid State Memory↗

Compact holographic memory using E - O beam steering

An innovative holographic memory system has been developed at JPL for high-density and high speed data storage in a space environment. This system ulitlizes a newly developed electro-optic (E-O) beam steering technology for beam steering to enable high-speed random access memory read/write without moving parts. Recently, a compact CD-sized holographic memory broadboard has been developed and demonstrated for holographic data storage adn retrieval. Detail technical progress will be presented in this paper.

electo - optic (E - O ) beam↗

Surface Control of Cold Hibernated Elastic Memory Self-Deployable Structure

A new class of simple, reliable, lightweight, low packaging volume and cost, self-deployable structures has been developed for use in space and commercial applications. This technology called 'cold hibernated elastic memory' (CHEM) utilizes shape memory polymers (SMP)in open cellular (foam) structure or sandwich structures made of shape memory polymer foam cores and polymeric composite skins. Some of many potential CHEM space applications require a high precision deployment and surface accuracy during operation. However, a CHEM structure could be slightly distorted by the thermo-mechanical processing as well as by thermal space environment Therefore, the sensor system is desirable to monitor and correct the potential surface imperfection. During these studies, the surface control of CHEM smart structures was demonstrated using a Macro-Fiber Composite (MFC) actuator developed by the NASA LaRC and US Army ARL. The test results indicate that the MFC actuator performed well before and after processing cycles. It reduced some residue compressive strain that in turn corrected very small shape distortion after each processing cycle. The integrated precision strain gages were detecting only a small flat shape imperfection indicating a good recoverability of original shape of the CHEM test structure.

glass transition temperature Tg↗

Assessment of Shape Memory Alloys - From Atoms To Actuators - Via In Situ Neutron Diffraction

As shape memory alloys (SMAs) become an established actuator technology, it is important to identify the fundamental mechanisms responsible for their performance by understanding microstructure performance relationships from processing to final form. Yet, microstructural examination of SMAs at stress and temperature is often a challenge since structural changes occur with stress and temperature and microstructures cannot be preserved through quenching or after stress removal, as would be the case for conventional materials. One solution to this dilemma is in situ neutron diffraction, which has been applied to the investigation of SMAs and has offered a unique approach to reveal the fundamental micromechanics and microstructural aspects of bulk SMAs in a non-destructive setting. Through this technique, it is possible to directly correlate the micromechanical responses (e.g., internal residual stresses, lattice strains), microstructural evolutions (e.g., texture, defects) and phase transformation properties (e.g., phase fractions, kinetics) to the macroscopic actuator behavior. In this work, in situ neutron diffraction was systematically employed to evaluate the deformation and transformation behavior of SMAs under typical actuator conditions. Austenite and martensite phases, yield behavior, variant selection and transformation temperatures were characterized for a polycrystalline NiTi (49.9 at. Ni). As the alloy transforms under thermomechanical loading, the measured textures and lattice plane-level variations were directly related to the cyclic actuation-strain characteristics and the dimensional instability (strain ratcheting) commonly observed in this alloy. The effect of training on the shape memory characteristics of the alloy and the development of two-way shape memory effect (TWSME) were also assessed. The final conversion from a material to a useful actuator, typically termed shape setting, was also investigated in situ during constrained heatingcooling and subsequent shape recovery experiments. Neutron diffraction techniques are also being applied to the investigation of novel high temperature SMAs with the objective of designing alloys with better stability, higher transition temperatures and ultimately superior durability.

Shape Memory Alloys↗

Comparison of TID Response and SEE Characterization of Single and Multi Level High Density NAND Flash Memories

Heavy ion single-event measurements and TID response for 8Gb commercial NAND flash memories are reported. Radiation results of multi-level flash technology are compared with results from single-level flash technology. In general, these commercial high density memories appear to be much less susceptible to SEE and have better TID response compared to older generations of flash memories. The charge pump survived up to 600 krads.

nonvolatile memory↗

Engineering Design Tools for Shape Memory Alloy Actuators: CASMART Collaborative Best Practices and Case Studies

The primary goal of the Consortium for the Advancement of Shape Memory Alloy Research and Technology (CASMART) is to enable the design of revolutionary applications based on shape memory alloy (SMA) technology. In order to help realize this goal and reduce the development time and required experience for the fabrication of SMA actuation systems, several modeling tools have been developed for common actuator types and are discussed herein along with case studies, which highlight the capabilities and limitations of these tools. Due to their ability to sustain high stresses and recover large deformations, SMAs have many potential applications as reliable, lightweight, solid-state actuators. Their advantage over classical actuators can also be further improved when the actuator geometry is modified to fit the specific application. In this paper, three common actuator designs are studied: wires, which are lightweight, low-profile, and easily implemented; springs, which offer actuation strokes upwards of 200 at reduced mechanical loads; and torque tubes, which can provide large actuation forces in small volumes and develop a repeatable zero-load actuation response (known as the two-way shape memory effect). The modeling frameworks, which have been implemented in the design tools, are developed for each of these frequently used SMA actuator types. In order to demonstrate the versatility and flexibility of the presented design tools, as well as validate their modeling framework, several design challenges were completed. These case studies include the design and development of an active hinge for the deployment of a solar array or foldable space structure, an adaptive solar array deployment and positioning system, a passive air temperature controller for regulation flow temperatures inside of a jet engine, and a redesign of the Corvette active hatch, which allows for pressure equalization of the car interior. For each of the presented case studies, a prototype or proof-of-concept was fabricated and the experimental results and lessons learned are discussed. This analysis presents a collection of CASMART collaborative best practices in order to allow readers to utilize the available design tools and understand their modeling principles. These design tools, which are based on engineering models, can provide first-order optimal designs and are a basic and efficient method for either demonstrating design feasibility or refining design parameters. Although the design and integration of an SMA-based actuation system always requires application- and environment-specific engineering considerations, common modeling tools can significantly reduce the investment required for actuation system development and provide valuable engineering insight.

Design tools↗

NOR Flash Memory Scrubbing Application for Boot File Preservation of NASA’s Descent and Landing Computer (DLC)

Progress on NASA’s Safe and Precise Landing Integrated Capabilities Evolution (SPLICE)project continues, specifically with this development of the Descent and Landing Computer(DLC). One of the DLC’s primary contributions as a SPLICE technology is its implementationof algorithms and operation of sensors to autonomously guide a spacecraft in performing moreprecise and safer landings on celestial bodies such as the Moon and Mars. The second iterationof the DLC is known as the Engineering Test Unit (ETU) and one of its desired functionalitiesis the ability to preserve the fidelity of the system’s boot file through the use of memoryscrubbing. The ETU has two primary boards, one for housing a Multi-Processor System ona Chip (MPSoC) and the other for housing a Xilinx Kintex Ultrascale FPGA3. To emulate amemory scrubbing function implemented on the ETU’s FPGA board, the design and testingof a software application was performed on a Xilinx KCU105 FPGA evaluation board. Thememory scrubbing application had to meet certain key criteria such as (1) properly utilize withthe flash memory’s Serial Peripheral Interface (SPI) to read, write, and erase flash memoryproperly, (2) be able to detect arbitrarily large or small amounts of bit-errors, (3) be able tocorrect all detected errors, and (4) perform memory scrubbing indefinitely and autonomously.A prototype implementation was constructed and tested, demonstrating successful detectionand correction of bit errors in multiple configurations. In the form of burst errors or singularbit flips, and in amounts of errors ranging from one to fifteen (per 256 Bytes), the applicationwas successful in preserving memory fidelity.

Radiation tolerant↗

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↗

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↗

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗

Dual redundant core memory systems

Electronic memory system consisting of series redundant drive switch circuits, triple redundant majority voted memory timing functions, and two data registers to provide functional dual redundancy is described. Signal flow through the circuits is illustrated and equence of events which occur within the memory system is explained.

Hull, F. E.↗

Apollo guidance, navigation and control: Guidance system operations plans for manned LM earth orbital and lunar missions using Program COLOSSUS 3. Section 7: Erasable memory programs

Erasable-memory programs (EMPs) designed for the guidance computers used in the command (CMC) and lunar modules (LGC) are described. CMC programs are designated COLOSSUS 3, and the associated EMPs are identified by a three-digit number beginning with 5. LGC programs are designated LUMINARY 1E, and the associated EMPs are identified, with one exception, by a three-digit number beginning with 1. The exception is EMP 99. The EMPs vary in complexity from a simple flagbit setting to a long and intricate logical structure. They all, however, cause the computer to behave in a way not intended in the original design of the programs; they accomplish this off-nominal behavior by some alteration of erasable memory to interface with existing fixed-memory programs to effect a desired result.

Hamilton, M. H.↗

Sequential behavior and its inherent tolerance to memory faults.

Representation of a memory fault of a sequential machine M by a function mu on the states of M and the result of the fault by an appropriately determined machine M(mu). Given some sequential behavior B, its inherent tolerance to memory faults can then be measured in terms of the minimum memory redundancy required to realize B with a state-assigned machine having fault tolerance type tau and fault tolerance level t. A behavior having maximum inherent tolerance is exhibited, and it is shown that behaviors of the same size can have different inherent tolerance.

Meyer, J. F.↗

Development of a monolithic ferrite memory array

The results of the development and testing of ferrite monolithic memory arrays are presented. This development required the synthesis of ferrite materials having special magnetic and physical characteristics and the development of special processes; (1) for making flexible sheets (laminae) of the ferrite composition, (2) for embedding conductors in ferrite, and (3) bonding ferrite laminae together to form a monolithic structure. Major problems encountered in each of these areas and their solutions are discussed. Twenty-two full-size arrays were fabricated and fired during the development of these processes. The majority of these arrays were tested for their memory characteristics as well as for their physical characteristics and the results are presented. The arrays produced during this program meet the essential goals and demonstrate the feasibility of fabricating monolithic ferrite memory arrays by the processes developed.

Heckler, C. H., Jr.↗

A simulation model for a memory organization for a multiprocessor.

A model for a memory organization for a multiprocessor with look-ahead and interleaved multimodule main memory is presented. The model is used to determine the extent of look-ahead and depth of interleaving that provide the most prolific speed match between processors and main memory.

Eubank, J. B.↗

Plated wire memory subsystem

The design, construction, and test history of a 4096 word by 18 bit random access NDRO Plated Wire Memory for use in conjunction with a spacecraft input/output and central processing unit is reported. A technical and functional description is given along with diagrams illustrating layout and systems operation. Test data is shown on the procedures and results of system level and memory stack testing, and hybrid circuit screening. A comparison of the most significant physical and performance characteristics of the memory unit versus the specified requirements is also included.

Carpenter, K. H.↗

Magnetic bubble domain memories

Some attractive features of Bubble Domain Memory and its relation to existing technologies are discussed. Two promising applications are block access mass memory and tape recorder replacement. The required chip capabilities for these uses are listed, and the specifications for a block access mass memory designed to fit between core and HPT disk are presented. A feasibility model for a tape recorder replacement is introduced.

Ypma, J. E.↗