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At least 1,225 records · Page 68

Science data systems

Video film converter for data processing, linear feedback shift registers, and woven plated wire memory storage units for science missions

MEMORY STORAGE UNIT↗

Investigation of fluctuations in angular velocity in magnetic memory devices

The fluctuations in the angular velocity of individual assemblies of a precision mechanical system were analyzed. The system was composed of an electric motor and a magnetic drum which were connected by a flexible coupling. A dynamic model was constructed which took into account the absence of torsion in the rigid shafts of the electric motor drive rotor and the magnetic drum. The motion was described by Lagrange differential equations of the second kind. Curves are developed to show the nature of amplitude fluctuation of the magnetic drum angular velocity at a specific excitation frequency. Additional curves show the amplitudes of fluctuation of the magnetic drum angular velocity compared to the quantity of damping at specific frequencies.

Meshkis, Y. A.↗

Visions of tomorrow: A focus on national space transportation issues; Proceedings of the Twenty-fifth Goddard Memorial Symposium, Greenbelt, MD, Mar. 18-20, 1987

The present conference on U.S. space transportation systems development discusses opportunities for aerospace students in prospective military, civil, industrial, and scientific programs, current strategic conceptualization and program planning for future U.S. space transportation, the DOD space transportation plan, NASA space transportation plans, medium launch vehicle and commercial space launch services, the capabilities and availability of foreign launch vehicles, and the role of commercial space launch systems. Also discussed are available upper stage systems, future space transportation needs for space science and applications, the trajectory analysis of a low lift/drag-aeroassisted orbit transfer vehicle, possible replacements for the Space Shuttle, LEO to GEO with combined electric/beamed-microwave power from earth, the National Aerospace Plane, laser propulsion to earth orbit, and a performance analysis for a laser-powered SSTO vehicle.

Soffen, Gerald A.↗

G-133: A soft x ray solar telescope

The GOLDHELOX Project, NASA payload number G-133, is a robotic soft x ray solar telescope designed and built by an organization of undergraduate students. The telescope is designed to observe the sun at a wavelength of 171 to 181 A. Since we require observations free from atmospheric interference, the telescope will be launched in a NASA Get-Away-Special (GAS) canister with a Motorized Door Assembly (MDA). In this paper we primarily discuss the most important elements of the telescope itself. We also elaborate on some of the technical difficulties associated with doing good science in space on a small budget (about $100,000) and mention ways in which controlling the instrument environment has reduced the complexity of the system and thus saved us money.

Williams, Memorie K.↗

Performance of multi level error correction in binary holographic memory

At the Optical Computing Lab in the Jet Propulsion Laboratory (JPL) a binary holographic data storage system was designed and tested with methods of recording and retrieving the binary information. Levels of error correction were introduced to the system including pixel averaging, thresholding, and parity checks. Errors were artificially introduced into the binary holographic data storage system and were monitored as a function of the defect area fraction, which showed a strong influence on data integrity. Average area fractions exceeding one quarter of the bit area caused unrecoverable errors. Efficient use of the available data density was discussed. .

data storage↗

Content-addressable read/write memories for image analysis

The commonly encountered image analysis problems of region labeling and clustering are found to be cases of search-and-rename problem which can be solved in parallel by a system architecture that is inherently suitable for VLSI implementation. This architecture is a novel form of content-addressable memory (CAM) which provides parallel search and update functions, allowing speed reductions down to constant time per operation. It has been proposed in related investigations by Hall (1981) that, with VLSI, CAM-based structures with enhanced instruction sets for general purpose processing will be feasible.

Snyder, W. E.↗

Parallel Gaussian elimination of a block tridiagonal matrix using multiple microcomputers

The solution of a block tridiagonal matrix using parallel processing is demonstrated. The multiprocessor system on which results were obtained and the software environment used to program that system are described. Theoretical partitioning and resource allocation for the Gaussian elimination method used to solve the matrix are discussed. The results obtained from running 1, 2 and 3 processor versions of the block tridiagonal solver are presented. The PASCAL source code for these solvers is given in the appendix, and may be transportable to other shared memory parallel processors provided that the synchronization outlines are reproduced on the target system.

Blech, Richard A.↗

Resistive Switching Memory Performance of Two-Dimensional Polyimide Covalent Organic Framework Films

Two-dimensional polyimide covalent organic framework (2D PI-NT COF) films were constructed on indium tin oxide-coated glass substrates to fabricate two-terminal sandwiched resistive memory devices. The 2D PI-NT COF films condensated from the reaction between 4,4',4"-triaminotriphenylamine and naphthalene-1,4,5,8-tetracarboxylic dianhydride under solvothermal conditions demonstrated high crystallinity, good orientation preference, tunable thickness, and low surface roughness. The well-aligned electron-donor (triphenylamine unit) and -acceptor (naphthalene diimide unit) arrays rendered the 2D PI-NT COF films a promising candidate for electronic applications. The memory devices based on 2D PI-NT COF films exhibited a typical write-once-read-many-time resistive switching behavior under an operating voltage of +2.30 V on the positive scan and -2.64 V on the negative scan. A high ON/OFF current ratio (>10 6 for the positive scan and 10 4 -10 6 for the negative scan) and long-term retention time indicated the high fidelity, low error, and high stability of the resistive memory devices. The memory behavior was attributed to an electric field-induced intramolecular charge transfer in an ordered donor-acceptor system, which provided the effective charge-transfer channels for injected charge carriers. Furthermore, this work represents the first example that explores the resistive memory properties of 2D PI-COF films, shedding light on the potential application of 2D COFs as information storage media.

2D covalent organic framework film↗

Understanding GPU Memory Corruption at Extreme Scale: The Summit Case Study

GPU memory corruption and in particular double-bit errors (DBEs) remain one of the least understood aspects of HPC system reliability. Albeit rare, their occurrences always lead to job termination and can potentially cost thousands of node-hours, either from wasted computations or as the overhead from regular checkpointing needed to minimize the losses. As supercomputers and their components simultaneously grow in scale, density, failure rates, and environmental footprint, the efficiency of HPC operations becomes both an imperative and a challenge. We examine DBEs using system telemetry data and logs collected from the Summit supercomputer, equipped with 27,648 Tesla V100 GPUs with 2nd-generation high-bandwidth memory (HBM2). Using exploratory data analysis and statistical learning, we extract several insights about memory reliability in such GPUs. We find that GPUs with prior DBE occurrences are prone to experience them again due to otherwise harmless factors, correlate this phenomenon with GPU placement, and suggest manufacturing variability as a factor. On the general population of GPUs, we link DBEs to short- and long-term high power consumption modes while finding no significant correlation with higher temperatures. We also show that the workload type can be a factor in memory’s propensity to corruption.

Oles, Vlad↗

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↗

The changing nature of spacecraft operations: From the Vikings of the 1970's to the great observatories of the 1990's and beyond

Four trends in spacecraft flight operations are discussed which will reduce overall program costs. These trends are the use of high-speed, highly reliable data communications systems for distributing operations functions to more convenient and cost-effective sites; the improved capability for remote operation of sensors; a continued rapid increase in memory and processing speed of flight qualified computer chips; and increasingly capable ground-based hardware and software systems, notably those augmented by artificial intelligence functions. Changes reflected by these trends are reviewed starting from the NASA Viking missions of the early 70s, when mission control was conducted at one location using expensive and cumbersome mainframe computers and communications equipment. In the 1980s, powerful desktop computers and modems enabled the Magellan project team to operate the spacecraft remotely. In the 1990s, the Hubble Space Telescope project uses multiple color screens and automated sequencing software on small computers. Given a projection of current capabilities, future control centers will be even more cost-effective.

Ledbetter, Kenneth W.↗

Progress and Challenges for Memtransistors in Neuromorphic Circuits and Systems

Due to the increasing importance of artificial intelligence (AI), significant recent effort has been devoted to the development of neuromorphic circuits that seek to emulate the energy-efficient information processing of the brain. While non-volatile memory (NVM) based on resistive switches, phase-change memory, and magnetic tunnel junctions has shown potential for implementing neural networks, additional multi-terminal device concepts are required for more sophisticated bio-realistic functions. Of particular interest are memtransistors based on low-dimensional nanomaterials, which are capable of electrostatically tuning memory and learning behavior at the device level. Herein, a conceptual overview of the memtransistor is provided in the context of neuromorphic circuits. Recent progress is surveyed for memtransistors and related multi-terminal NVM devices including dual-gated floating-gate memories, dual-gated ferroelectric transistors, and dual-gated van der Waals heterojunctions. Further, the different materials systems and device architectures are classified based on the degree of control and relative tunability of synaptic behavior, with an emphasis on device concepts that harness the reduced dimensionality, weak electrostatic screening, and phase-changes properties of nanomaterials. Finally, strategies for achieving wafer-scale integration of memtransistors and multi-terminal NVM devices are delineated, with specific attention given to the materials challenges for practical neuromorphic circuits.

36 MATERIALS SCIENCE↗

SMC 2021 : Analyzing Resource Utilization and User Behavior on Titan Supercomputer

Resource utilization statistics of submitted jobs on a supercomputer can help us understand how users from various scientific domains use HPC platforms and better design a job scheduler. We explore to generate insight regarding workload distribution and usage pattern domains from job scheduler trace, GPU failure information, and project-specific information collected from Titan supercomputer. Furthermore, we want to know how the scheduler performance varies over time and how the users' scheduling behavior changes following a system failure. These observations have the potential to provide valuable insight, which is helpful to prepare for system failures. These practices will help us develop and apply novel machine learning algorithms in understanding system behavior, requirement, and better scheduling of HPC systems. There are two datasets, RUR and GPU. RUR: This dataset is the job scheduler traces collected from the Titan supercomputerfrom 01/01/2015 to 07/31/2019 (2015.csv - 2019.csv). These were collected usingResource Utilization Report (RUR), a Cray-developed resource-usage data collectionand reporting system. It contains the usage information of its critical resources (CPU,Memory, GPU, and I/O) of each running job on Titan during that period [2]. ProjectAreas: Every job is associated with a project ID. TheProjectAreas.csvdatasetprovides a mapping of the project ID to its domain science. GPU: There have been some hardware-related issues in the GPUs in Titan that caused some GPUs to fail, sometimes irrecoverably during some job runs. This dataset provides information regarding these failures during the execution of the submitted jobs. GPUs on Titan are uniquely identified by a serial number (SN), and they are installed in a location. A GPU can be installed in a location, then removed from that location following a failure, and then re-installed in a different location after fixing the problem. If the failure can't be recovered, the GPU might be removed entirely from Titan. There are two prominent types of failures that resulted in the removal of GPUs from Titan: Double Bit Error (DBE) and Out of the Bus (OTB). The dataset (gc_full.csv) has the following fields: 1. SN : Serial number of a GPU 2. location : The location where it is installed 3. insert : The time when it was inserted into that location 4. remove : The time when it was removed from that location 5. duration : Amount of time the GPU spent in this location 6. out : If the device was taken out entirely w/o a re-installment into a new location. 7. event : If the GPU was taken out entirely, the reason for its removal. To learn more about this dataset, please refer to the git repositoryhttps://github.com/olcf/TitanGPULifeand the related publication [1]. References [1] George Ostrouchov, Don Maxwell, Rizwan A Ashraf, Christian Engelmann, MallikarjunShankar, and James H Rogers. Gpu lifetimes on titan supercomputer: Survival analysisand reliability. InSC20: International Conference for High Performance Computing,Networking, Storage and Analysis, pages 1-14. IEEE, 2020. [2] Feiyi Wang, Sarp Oral, Satyabrata Sen, and Neena Imam. Learning from five-yearresource-utilization data of titan system. In2019 IEEE International Conference onCluster Computing (CLUSTER), pages 1-6. IEEE, 2019.

42 ENGINEERING↗

Surrogate Modeling of Nonlinear Dynamic Systems: A Comparative Study

Surrogate models play a vital role in overcoming the computational challenge in designing and analyzing nonlinear dynamic systems, especially in the presence of uncertainty. This paper presents a comparative study of different surrogate modeling techniques for nonlinear dynamic systems. Four surrogate modeling methods, namely, Gaussian process (GP) regression, a long short-term memory (LSTM) network, a convolutional neural network (CNN) with LSTM (CNN-LSTM), and a CNN with bidirectional LSTM (CNN-BLSTM), are studied and compared. All these model types can predict the future behavior of dynamic systems over long periods based on training data from relatively short periods. The multi-dimensional inputs of surrogate models are organized in a nonlinear autoregressive exogenous model (NARX) scheme to enable recursive prediction over long periods, where current predictions replace inputs from the previous time window. Three numerical examples, including one mathematical example and two nonlinear engineering analysis models, are used to compare the performance of the four surrogate modeling techniques. The results show that the GP-NARX surrogate model tends to have more stable performance than the other three deep learning (DL)-based methods for the three particular examples studied. The tuning effort of GP-NARX is also much lower than its deep learning-based counterparts.

42 ENGINEERING↗

Technique for Solving Electrically Small to Large Structures for Broadband Applications

Fast iterative algorithms are often used for solving Method of Moments (MoM) systems, having a large number of unknowns, to determine current distribution and other parameters. The most commonly used fast methods include the fast multipole method (FMM), the precorrected fast Fourier transform (PFFT), and low-rank QR compression methods. These methods reduce the O(N) memory and time requirements to O(N log N) by compressing the dense MoM system so as to exploit the physics of Green s Function interactions. FFT-based techniques for solving such problems are efficient for spacefilling and uniform structures, but their performance substantially degrades for non-uniformly distributed structures due to the inherent need to employ a uniform global grid. FMM or QR techniques are better suited than FFT techniques; however, neither the FMM nor the QR technique can be used at all frequencies. This method has been developed to efficiently solve for a desired parameter of a system or device that can include both electrically large FMM elements, and electrically small QR elements. The system or device is set up as an oct-tree structure that can include regions of both the FMM type and the QR type. The system is enclosed with a cube at a 0- th level, splitting the cube at the 0-th level into eight child cubes. This forms cubes at a 1st level, recursively repeating the splitting process for cubes at successive levels until a desired number of levels is created. For each cube that is thus formed, neighbor lists and interaction lists are maintained. An iterative solver is then used to determine a first matrix vector product for any electrically large elements as well as a second matrix vector product for any electrically small elements that are included in the structure. These matrix vector products for the electrically large and small elements are combined, and a net delta for a combination of the matrix vector products is determined. The iteration continues until a net delta is obtained that is within the predefined limits. The matrix vector products that were last obtained are used to solve for the desired parameter. The solution for the desired parameter is then presented to a user in a tangible form; for example, on a display.

Jandhyala, Vikram↗

Acquisition and improvement of human motor skills: Learning through observation and practice

Skilled movement is an integral part of the human existence. A better understanding of motor skills and their development is a prerequisite to the construction of truly flexible intelligent agents. We present MAEANDER, a computational model of human motor behavior, that uniformly addresses both the acquisition of skills through observation and the improvement of skills through practice. MAEANDER consists of a sensory-effector interface, a memory of movements, and a set of performance and learning mechanisms that let it recognize and generate motor skills. The system initially acquires such skills by observing movements performed by another agent and constructing a concept hierarchy. Given a stored motor skill in memory, MAEANDER will cause an effector to behave appropriately. All learning involves changing the hierarchical memory of skill concepts to more closely correspond to either observed experience or to desired behaviors. We evaluated MAEANDER empirically with respect to how well it acquires and improves both artificial movement types and handwritten script letters from the alphabet. We also evaluate MAEANDER as a psychological model by comparing its behavior to robust phenomena in humans and by considering the richness of the predictions it makes.

Iba, Wayne↗

El Agente: An autonomous agent for quantum chemistry

Computational chemistry tools are widely used to study the behavior of chemical phenomena. Yet, the complexity of these tools can make them inaccessible to non-specialists and challenging even for experts. In this work, we introduce El Agente Q, an LLM-based multi-agent system that dynamically generates and executes quantum chemistry workflows from natural language user prompts. The system is built on a novel cognitive architecture featuring a hierarchical memory framework that enables flexible task decomposition, adaptive tool selection, post-analysis, and autonomous file handling and submission. El Agente Q is benchmarked on six university-level course exercises and two case studies, demonstrating robust problem-solving performance (averaging >87% task success) and adaptive error handling through in situ debugging. It also supports longer-term, multi-step task execution for more complex workflows, while maintaining transparency through detailed action trace logs. Together, these capabilities lay the foundation for increasingly autonomous and accessible quantum chemistry.

agentic systems↗

Active control of buckling of flexible beams

The feasibility of using the rapidly growing technology of the shape memory alloys actuators in actively controlling the buckling of large flexible structures is investigated. The need for such buckling control systems is becoming inevitable as the design trends of large space structures have resulted in the use of structural members that are long, slender, and very flexible. In addition, as these truss members are subjected mainly to longitudinal loading they become susceptible to structural instabilities due to buckling. Proper control of such instabilities is essential to the effective performance of the structures as stable platforms for communication and observation. Mathematical models are presented that simulate the dynamic characteristics of the shape memory actuator, the compressive structural members, and the associated active control system. A closed-loop computer-controlled system is designed, based on the developed mathematical models, and implemented to control the buckling of simple beams. The performance of the computer-controlled system is evaluated experimentally and compared with the theoretical predictions to validate the developed models. The obtained results emphasize the importance of buckling control and suggest the potential of the shape memory actuators as attractive means for controlling structural deformation in a simple and reliable way.

Baz, A.↗