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At least 1,387 records · Page 77

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Phase control of coherent acoustic phonons in gold bipyramids for optical memory and manipulating plasmon–exciton coupling

Recent efforts have targeted manipulation of nanomaterial vibrational modes in applications such as chemical/mass sensing, optical switching, and phonon-driven photochemistry. While impulsive photoexcitation can generate coherent phonons, multiple excitation pulses offer the prospect of control and manipulation of coherent phonon modes for functions of optical memory and logic. In this work, we use such an approach to inject an arbitrary coherent phonon phase into a colloidal ensemble of highly monodisperse gold bipyramids. We then demonstrate that this technique can be applied to a system that exhibits plasmon-exciton coupling to further manipulate the hybridization of the system. This ability to manipulate acoustic phonons and hybridization can enable optical logic applications of acoustic phonons in addition to optical memory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1985

Pultrusion Process for Fabrication of Tethers (preliminary Concepts)

Three composite materials were manufactured by the pultrusion process, coiled on 24 inch diameter spools for a period of two months, uncoiled and evaluated for memory recall. These materials were pultruded to lengths of approximately 150 feet and cross section profiles were maintained at 0.143 inch in thickness by 0.566 inch in width. Mechanical properties were studied and results compared. The reinforcement material volume percent of each was identical. Of the three systems, the Kevlar reinforced composite had the highest specific strength, the lowest flexural modulus, and the lowest memory recall. Further evaluations of materials and fabrication technology of pultrusion should be conducted to address some problem areas encountered in this preliminary concept. Areas for further study are suggested.

Macconochie, I. O.↗

DOE OSTI2025

Advances in relaxation and memory effects of magnetic nanoparticles for biomedical applications

Functionalized magnetic nanoparticles are pivotal in magnetic resonance imaging, computed tomography, controlled drug delivery, and hyperthermia treatments due to their exceptional magnetic relaxation and functional properties. The magnetic core composition and structure significantly affects the complex magnetic properties of these nanoparticles necessitating a thorough examination of magnetism fundamentals related to these systems. One important aspect is the ability of magnetic nanoparticles to retain previous magnetic state configurations known as memory effect, primarily governed by domain structure and magnetic anisotropy. Despite its relevance to advanced applications, comprehensive studies on magnetic relaxation and memory effects remain limited. Here, the present review aims to bridge this gap by investigating relaxation mechanisms, synthesis strategies, and applications, fostering further innovation. It investigates the memory effects and their dependence on particle composition and morphology along with key synthesis techniques for large-scale production in industrial adoption. Structured into focused sections on magnetic properties and their influence on biomedical and technological applications, this review provides essential insights into memory effects, magneto-relaxation mechanisms, influencing factors, and both experimental and theoretical methodologies. It also delves into computational modelling and AI-driven design, which are revolutionizing the prediction, discovery, and optimization of materials with tailored properties.

36 MATERIALS SCIENCE↗

NASA NTRS1989

Optical Firmware

Data-processing system exploits high speeds inherent in optical elements. Instruction sets for different computer operations reside on different external memory chips. Laser diodes activated for each operation generate light, reflected by holographic optical element to designated receptors in arithmetic and logic unit. Pattern of light beams embodies instruction set at given instant. With potential ability to reprogram in real time, conceptual system applicable to task-driven programming or artificial intelligence.

Bergman, Larry A.↗

NASA NTRS2012

Shape memory-based actuators and release mechanisms therefrom

SM-based actuators (110) and release mechanisms (100) therefrom and systems (500) including one or more release mechanisms (100). The actuators (110) comprise a SM member (118) and a deformable member (140) mechanically coupled to the SM member (118) which deforms upon a shape change of the SM member triggered by a phase transition of the SM member. A retaining element (160) is mechanically coupled to the deformable member (140), wherein the retaining element (160) moves upon the shape change. Release mechanism (100) include an actuator, a rotatable mechanism (120) including at least one restraining feature (178) for restraining rotational movement of the retaining element (160) before the shape change, and at least one spring (315) that provides at least one locked spring-loaded position when the retaining element is in the restraining feature and at least one released position that is reached when the retaining element is in a position beyond the restraining feature (178). The rotatable mechanism (120) includes at least one load-bearing protrusion (310). A hitch (400) is for mechanically coupling to the load, wherein the hitch is supported on the load bearing protrusion (310) when the rotatable mechanism is in the locked spring-loaded position.

Vaidyanathan, Rajan↗

DOE OSTI2022

Methods, systems, and apparatuses for in-line variably porous surfaces

Variably porous panels and panel assemblies incorporating shape memory alloy components along with methods for actuating the shape memory alloys are disclosed to predictably alter the porosity of a substrate surface, with the shape memory alloy maintained in an orientation relative to the panel that is in-plane with a mold-line of the panel outer surface.

36 MATERIALS SCIENCE↗

NASA NTRS1995

The scheme machine: A case study in progress in design derivation at system levels

The Scheme Machine is one of several design projects of the Digital Design Derivation group at Indiana University. It differs from the other projects in its focus on issues of system design and its connection to surrounding research in programming language semantics, compiler construction, and programming methodology underway at Indiana and elsewhere. The genesis of the project dates to the early 1980's, when digital design derivation research branched from the surrounding research effort in programming languages. Both branches have continued to develop in parallel, with this particular project serving as a bridge. However, by 1990 there remained little real interaction between the branches and recently we have undertaken to reintegrate them. On the software side, researchers have refined a mathematically rigorous (but not mechanized) treatment starting with the fully abstract semantic definition of Scheme and resulting in an efficient implementation consisting of a compiler and virtual machine model, the latter typically realized with a general purpose microprocessor. The derivation includes a number of sophisticated factorizations and representations and is also deep example of the underlying engineering methodology. The hardware research has created a mechanized algebra supporting the tedious and massive transformations often seen at lower levels of design. This work has progressed to the point that large scale devices, such as processors, can be derived from first-order finite state machine specifications. This is roughly where the language oriented research stops; thus, together, the two efforts establish a thread from the highest levels of abstract specification to detailed digital implementation. The Scheme Machine project challenges hardware derivation research in several ways, although the individual components of the system are of a similar scale to those we have worked with before. The machine has a custom dual-ported memory to support garbage collection. It consists of four tightly coupled processes--processor, collector, allocator, memory--with a very non-trivial synchronization relationship. Finally, there are deep issues of representation for the run-time objects of a symbolic processing language. The research centers on verification through integrated formal reasoning systems, but is also involved with modeling and prototyping environments. Since the derivation algebra is basd on an executable modeling language, there is opportunity to incorporate design animation in the design process. We are looking for ways to move smoothly and incrementally from executable specifications into hardware realization. For example, we can run the garbage collector specification, a Scheme program, directly against the physical memory prototype, and similarly, the instruction processor model against the heap implementation.

Johnson, Steven D.↗

NASA NTRS1972

Coordination and establishment of centralized facilities and services for the University of Alaska ERTS survey of the Alaskan environment

The author has identified the following significant results. Specifications have been prepared for the engineering design and construction of a digital color display unit which will be used for automatic processing of ERTS data. The color display unit is a disk refresh memory with computer interfaced input and a color cathode ray tube output display. The system features both analog and digital post disk data manipulation and a versatile color coding device suitable for displaying not only images, but also computer generated graphics such as diagrams, maps, and overlays. Input is from IBM compatible 9 track, 800 BPI tapes, as generated by an IBM 360 computer. ERTS digital tapes are read into the 360, where various analyses such as maximum likelihood classification are performed and the results are written on a magnetic tape which is the input to the color display unit. The greatest versatility in the data manipulation area is provided by the minicomputer built into the color display unit, which is off-line from the main 360 computer. The minicomputer is able to read any line from the refresh disk and place it in its 4K-16 bit memory. Considerable flexibility is available for post-processing enhancement of images by the investigator.

Belon, A. E.↗

NASA NTRS2015

Pi-Sat: A Low Cost Small Satellite and Distributed Spacecraft Mission System Test Platform

Current technology and budget trends indicate a shift in satellite architectures from large, expensive single satellite missions, to small, low cost distributed spacecraft missions. At the center of this shift is the SmallSatCubesat architecture. The primary goal of the Pi-Sat project is to create a low cost, and easy to use Distributed Spacecraft Mission (DSM) test bed to facilitate the research and development of next-generation DSM technologies and concepts. This test bed also serves as a realistic software development platform for Small Satellite and Cubesat architectures. The Pi-Sat is based on the popular $35 Raspberry Pi single board computer featuring a 700Mhz ARM processor, 512MB of RAM, a flash memory card, and a wealth of IO options. The Raspberry Pi runs the Linux operating system and can easily run Code 582s Core Flight System flight software architecture. The low cost and high availability of the Raspberry Pi make it an ideal platform for a Distributed Spacecraft Mission and Cubesat software development. The Pi-Sat models currently include a Pi-Sat 1U Cube, a Pi-Sat Wireless Node, and a Pi-Sat Cubesat processor card.The Pi-Sat project takes advantage of many popular trends in the Maker community including low cost electronics, 3d printing, and rapid prototyping in order to provide a realistic platform for flight software testing, training, and technology development. The Pi-Sat has also provided fantastic hands on training opportunities for NASA summer interns and Pathways students.

Software↗

DOE OSTI2024

Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications

Introduction Reconstructing low-level particle tracks in neutrino physics can address some of the most fundamental questions about the universe. However, processing petabytes of raw data using deep learning techniques poses a challenging problem in the field of High Energy Physics (HEP). In the Exa.TrkX Project, an illustrative HEP application, preprocessed simulation data is fed into a state-of-art Graph Neural Network (GNN) model, accelerated by GPUs. However, limited GPU memory often leads to Out-of-Memory (OOM) exceptions during training, due to the large size of models and datasets. This problem is exacerbated when deploying models on High-Performance Computing (HPC) systems designed for large-scale applications. Methods We observe a high workload imbalance issue during GNN model training caused by the irregular sizes of input graph samples in HEP datasets, contributing to OOM exceptions. We aim to scale GNNs on HPC systems, by prioritizing workload balance in graph inputs while maintaining model accuracy. Our paper introduces diverse balancing strategies aimed at decreasing the maximum GPU memory footprint and avoiding the OOM exception, across various datasets. Results Our experiments showcase memory reduction of up to 32.14% compared to the baseline. We also demonstrate the proposed strategies can avoid OOM in application. Additionally, we create a distributed multi-GPU implementation using these samplers to demonstrate the scalability of these techniques on the HEP dataset. Discussion By assessing the performance of these strategies as data loading samplers across multiple datasets, we can gauge their effectiveness in both single-GPU and distributed environments. Our experiments, conducted on datasets of varying sizes and across multiple GPUs, broaden the applicability of our work to various GNN applications that handle input datasets with irregular graph sizes.

Lee, Claire Songhyun↗

NASA NTRS1996

Evolving Requirements for Magnetic Tape Data Storage Systems

Magnetic tape data storage systems have evolved in an environment where the major applications have been back-up/restore, disaster recovery, and long term archive. Coincident with the rapidly improving price-performance of disk storage systems, the prime requirements for tape storage systems have remained: (1) low cost per MB, (2) a data rate balanced to the remaining system components. Little emphasis was given to configuring the technology components to optimize retrieval of the stored data. Emerging new applications such as network attached high speed memory (HSM), and digital libraries, place additional emphasis and requirements on the retrieval of the stored data. It is therefore desirable to consider the system to be defined both by STorage And Retrieval System (STARS) requirements. It is possible to provide comparative performance analysis of different STARS by incorporating parameters related to (1) device characteristics, and (2) application characteristics in combination with queuing theory analysis. Results of these analyses are presented here in the form of response time as a function of system configuration for two different types of devices and for a variety of applications.

Gniewek, John J.↗

NASA NTRS2004

NASA Tech Briefs, June 2004

Topics covered include: COTS MEMS Flow-Measurement Probes; Measurement of an Evaporating Drop on a Reflective Substrate; Airplane Ice Detector Based on a Microwave Transmission Line; Microwave/Sonic Apparatus Measures Flow and Density in Pipe; Reducing Errors by Use of Redundancy in Gravity Measurements; Membrane-Based Water Evaporator for a Space Suit; Compact Microscope Imaging System with Intelligent Controls; Chirped-Superlattice, Blocked-Intersubband QWIP; Charge-Dissipative Electrical Cables; Deep-Sea Video Cameras Without Pressure Housings; RFID and Memory Devices Fabricated Integrally on Substrates; Analyzing Dynamics of Cooperating Spacecraft; Spacecraft Attitude Maneuver Planning Using Genetic Algorithms; Forensic Analysis of Compromised Computers; Document Concurrence System; Managing an Archive of Images; MPT Prediction of Aircraft-Engine Fan Noise; Improving Control of Two Motor Controllers; Electro-deionization Using Micro-separated Bipolar Membranes; Safer Electrolytes for Lithium-Ion Cells; Rotating Reverse-Osmosis for Water Purification; Making Precise Resonators for Mesoscale Vibratory Gyroscopes; Robotic End Effectors for Hard-Rock Climbing; Improved Nutation Damper for a Spin-Stabilized Spacecraft; Exhaust Nozzle for a Multitube Detonative Combustion Engine; Arc-Second Pointer for Balloon-Borne Astronomical Instrument; Compact, Automated Centrifugal Slide-Staining System; Two-Armed, Mobile, Sensate Research Robot; Compensating for Effects of Humidity on Electronic Noses; Brush/Fin Thermal Interfaces; Multispectral Scanner for Monitoring Plants; Coding for Communication Channels with Dead-Time Constraints; System for Better Spacing of Airplanes En Route; Algorithm for Training a Recurrent Multilayer Perceptron; Orbiter Interface Unit and Early Communication System; White-Light Nulling Interferometers for Detecting Planets; and Development of Methodology for Programming Autonomous Agents.

Source record↗

NASA NTRS1992

Dynamic object management for distributed data structures

In distributed-memory multiprocessors, remote memory accesses incur larger delays than local accesses. Hence, insightful allocation and access of distributed data can yield substantial performance gains. The authors argue for the use of dynamic data management policies encapsulated within individual distributed data structures. Distributed data structures offer performance, flexibility, abstraction, and system independence. This approach is supported by data from a trace-driven simulation study of parallel scientific benchmarks. Experimental data on memory locality, message count, message volume, and communication delay suggest that data-structure-specific data management is superior to a single, system-imposed policy.

Totty, Brian K.↗

NASA NTRS1994

An intelligent control system for failure detection and controller reconfiguration

We present an architecture of an intelligent restructurable control system to automatically detect failure of system components, assess its impact on system performance and safety, and reconfigure the controller for performance recovery. Fault detection is based on neural network associative memories and pattern classifiers, and is implemented using a multilayer feedforward network. Details of the fault detection network along with simulation results on health monitoring of a dc motor have been presented. Conceptual developments for fault assessment using an expert system and controller reconfiguration using a neural network are outlined.

Biswas, Saroj K.↗

NASA NTRS2018

Crew Resource Management for Automated Teammates (CRM-A)

Crew Resource Management (CRM) is the application of human factors knowledge and skills to ensure that teams make effective use of all resources. This includes ensuring that pilots bring in opinions of other teammates and utilize their unique capabilities. CRM was originally developed 40 years ago in response to a number of airline accidents in which the crew was found to be at fault. The goal was to improve teamwork among airline cockpit crews. The notion of "team" was later expanded to include cabin crew and ground resources. CRM has also been adopted by other industries, most notably medicine. Automation research now finds itself faced with similar issues to those faced by aviation 40 years ago: how to create a more robust system by making full use of both the automation and its human operators. With advances in machine intelligence, processing speed and cheap and plentiful memory, automation has advanced to the point that it can and should be treated as a teammate to fully take advantage of its capabilities and contributions to the system. This area of research is known as Human-Autonomy Teaming (HAT). Research on HAT has identified reusable patterns that can be applied in a wide range of applications. These patterns include features such as bi-directional communication and working agreements. This paper will explore the synergies between CRM and HAT. We believe that HAT research has much to learn from CRM and that there are benefits to expanding CRM to cover automation.

Crew Resource Management↗

DOE OSTI2021

A phononic interface between a superconducting quantum processor and quantum networked spin memories

We introduce a method for high-fidelity quantum state transduction between a superconducting microwave qubit and the ground state spin system of a solid-state artificial atom, mediated via an acoustic bus connected by piezoelectric transducers. Applied to present-day experimental parameters for superconducting circuit qubits and diamond silicon-vacancy centers in an optimized phononic cavity, we estimate quantum state transduction with fidelity exceeding 99% at a MHz-scale bandwidth. By combining the complementary strengths of superconducting circuit quantum computing and artificial atoms, the hybrid architecture provides high-fidelity qubit gates with long-lived quantum memory, high-fidelity measurement, large qubit number, reconfigurable qubit connectivity, and high-fidelity state and gate teleportation through optical quantum networks.

47 OTHER INSTRUMENTATION↗

NASA NTRS1991

Using process groups to implement failure detection in asynchronous environments

Agreement on the membership of a group of processes in a distributed system is a basic problem that arises in a wide range of applications. Such groups occur when a set of processes cooperate to perform some task, share memory, monitor one another, subdivide a computation, and so forth. The group membership problems is discussed as it relates to failure detection in asynchronous, distributed systems. A rigorous, formal specification for group membership is presented under this interpretation. A solution is then presented for this problem.

Ricciardi, Aleta M.↗

DOE OSTI2024

Colossal Strain Tuning of Ferroelectric Transitions in KNbO 3 Thin Films

Strong coupling between polarization ( P ) and strain (ɛ) in ferroelectric complex oxides offers unique opportunities to dramatically tune their properties. Here colossal strain tuning of ferroelectricity in epitaxial KNbO 3 thin films grown by sub‐oxide molecular beam epitaxy is demonstrated. While bulk KNbO 3 exhibits three ferroelectric transitions and a Curie temperature ( T c ) of ≈676 K, phase‐field modeling predicts that a biaxial strain of as little as −0.6% pushes its T c > 975 K, its decomposition temperature in air, and for −1.4% strain, to T c > 1325 K, its melting point. Furthermore, a strain of −1.5% can stabilize a single phase throughout the entire temperature range of its stability. A combination of temperature‐dependent second harmonic generation measurements, synchrotron‐based X‐ray reciprocal space mapping, ferroelectric measurements, and transmission electron microscopy reveal a single tetragonal phase from 10 K to 975 K, an enhancement of ≈46% in the tetragonal phase remanent polarization ( P r ), and a ≈200% enhancement in its optical second harmonic generation coefficients over bulk values. These properties in a lead‐free system, but with properties comparable or superior to lead‐based systems, make it an attractive candidate for applications ranging from high‐temperature ferroelectric memory to cryogenic temperature quantum computing.

36 MATERIALS SCIENCE↗