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At least 235 records · Page 13

Microprocessor arrays for large scale computation

An important new direction in computer architecture centers around the achievement of very high computational power (capacity, speed and reliability) through the use of tens of thousands of microprocessors, micromemories, and switch modules, all interconnected into a large homogeneous network using one of certain advanced connection schemes. When surrounded and supported by conventional computers and memories, such a machine holds potential for out-performing both conventional and array-based computers of the mid-1980's by one to two orders of magnitude, at least for particular classes of applications amenable to high parallelism, such as aerodynamic simulation. The homogeneous feature of this machine concept also implies size extendability, fault tolerance, and improved flexibility to handle a variety of algorithms of interest. Current work is addressing the design of technologically efficient interconnection configurations and the development of new computation algorithms that are especially efficient for highly parallel computation.

Kautz, W. H.↗

Rocket Engine Health Management: Early Definition of Critical Flight Measurements

The NASA led Space Launch Initiative (SLI) program has established key requirements related to safety, reliability, launch availability and operations cost to be met by the next generation of reusable launch vehicles. Key to meeting these requirements will be an integrated vehicle health management ( M) system that includes sensors, harnesses, software, memory, and processors. Such a system must be integrated across all the vehicle subsystems and meet component, subsystem, and system requirements relative to fault detection, fault isolation, and false alarm rate. The purpose of this activity is to evolve techniques for defining critical flight engine system measurements-early within the definition of an engine health management system (EHMS). Two approaches, performance-based and failure mode-based, are integrated to provide a proposed set of measurements to be collected. This integrated approach is applied to MSFC s MC-1 engine. Early identification of measurements supports early identification of candidate sensor systems whose design and impacts to the engine components must be considered in engine design.

Christenson, Rick L.↗

Polarity effects on wake–up behavior of Al 0.94 B 0.06 N ferroelectrics

Wurtzite ferroelectric materials are promising candidates for energy-efficient memory technologies, particularly for applications requiring high operating temperatures. Asymmetric wake-up behaviors, in which the polarization reversal depends both on polarity and cycle number for the first few dozen cycles, must be better understood for reliable device operation. Here, the detailed analysis of the asymmetric wake-up behavior of thin film Al 0.94 B 0.06 N was performed combining time-resolved switching measurements with Rayleigh analysis, piezoelectric measurements, and etching experiments of progressively switched samples. Furthermore, the analysis shows that the gradual opening of the polarization hysteresis loops associated with wake-up is driven by a gradual increase in the domain-wall density and/or domain-wall mobility with electric field cycle to the polarity opposite to the growth polarity. The insights of this discovery will help to guide interface and polarity design in the eventual deployment of reliable devices based on these materials.

36 MATERIALS SCIENCE↗

Space-Derived Sewer Monitor

The QuadraScan Longterm Flow Monitoring System is a second generation sewer monitor developed by American Digital Systems, Inc.'s founder Peter Petroff. Petroff, a former spacecraft instrumentation designer at Marshall Space Flight Center, used expertise based on principles acquired in Apollo and other NASA programs. QuadraScan borrows even more heavily from space technology, for example in its data acquisition and memory system derived from NASA satellites. "One-time" measurements are often plagued with substantial errors due to the flow of groundwater absorbed into the system. These system sizing errors stem from a basic informational deficiency: accurate, reliable data on how much water flows through a sewer system over a long period of time is very difficult to obtain. City officials are turning to "permanent," or long-term sewer monitoring systems. QuadraScan offers many advantages to city officials such as the early warning capability to effectively plan for city growth in order to avoid the crippling economic impact of bans on new sewer connections in effect in many cities today.

Source record↗

BioSentinel: Leading the Way for Deep Space CubeSat Missions

Flagship science missions are not alone in Deep Space thanks to BioSentinel, a 6U spacecraft launched on Artemis-1. BioSentinel is one of the longest operating CubeSats beyond cislunar space. The subsystems and COTS components of the BioSentinel bus are a template for future deep space missions, and the lessons learned from over a year of operations will enable improved performance for the next missions. BioSentinel achieved its unprecedented performance for an SLS secondary payload due to preparation, planning, and a robust design. Pre-launch antenna and interface testing with both DSN and ESA confirmed command and data pathways and allowed for operational flexibility in the critical early hours post-deployment. Mission Operations simulations prior to launch identified potential risks and primed operators to respond in flight, preparing the team to react quickly to successfully detumble the spacecraft and enter a power-positive state. The spacecraft would not have survived without the inclusion of the trailblazing 3D-printed composite cold gas propulsion system. The non-standard tank geometry enabled efficient use of the limited space available in the CubeSat, as well as the capability to detumble the spacecraft and manage momentum, while providing sufficient margin to execute potential delta-V maneuvers. The Iris radio has operated for over 18 months with no significant issues. Initial Iris performance estimates have been accurate throughout the mission. BioSentinel continues to collect data on thermal conditions and to validate our performance models with real-world knowledge. We have received exemplary support from our DSN partners. Following the conclusion of the primary science mission, the Linear Energy Transfer (LET) Spectrometer continued to collect solar and galactic radiation data from its location in heliocentric orbit. The free space dataset offered by the BioSentinel LET is a valuable source of data for model validation and future mission planning. As the spacecraft travels farther from Earth it is poised to provide longitudinally distributed measurements of solar particle events during solar maximum. The lessons learned from BioSentinel suggest key areas to enhance performance. The ability to upload modified flight software can increase the stability of memory management. Additional heaters in the propulsion system design have already proven successful on the Starling mission. Streamlining mission operations can reduce costs, increase data return, and better utilize DSN time. Enhancements such as these will facilitate reliable, long-duration deep space exploration using the proven BioSentinel 6U CubeSat bus.

BioSentinel↗

Fast-Response-Time Shape-Memory-Effect Foam Actuators

Bulk shape memory alloys, such as Nitinol or CuAlZn, display strong recovery forces undergoing a phase transformation after being strained in their martensitic state. These recovery forces are used for actuation. As the phase transformation is thermally driven, the response time of the actuation can be slow, as the heat must be passively inserted or removed from the alloy. Shape memory alloy TiNi torque tubes have been investigated for at least 20 years and have demonstrated high actuation forces [3,000 in.-lb (approximately equal to 340 N-m) torques] and are very lightweight. However, they are not easy to attach to existing structures. Adhesives will fail in shear at low-torque loads and the TiNi is not weldable, so that mechanical crimp fits have been generally used. These are not reliable, especially in vibratory environments. The TiNi is also slow to heat up, as it can only be heated indirectly using heater and cooling must be done passively. This has restricted their use to on-off actuators where cycle times of approximately one minute is acceptable. Self-propagating high-temperature synthesis (SHS) has been used in the past to make porous TiNi metal foams. Shape Change Technologies has been able to train SHS derived TiNi to exhibit the shape memory effect. As it is an open-celled material, fast response times were observed when the material was heated using hot and cold fluids. A methodology was developed to make the open-celled porous TiNi foams as a tube with integrated hexagonal ends, which then becomes a torsional actuator with fast response times. Under processing developed independently, researchers were able to verify torques of 84 in.-lb (approximately equal to 9.5 Nm) using an actuator weighing 1.3 oz (approximately equal to 37 g) with very fast (less than 1/16th of a second) initial response times when hot and cold fluids were used to facilitate heat transfer. Integrated structural connections were added as part of the net shape process, eliminating the need for welding, adhesives, or mechanical crimping. Inexpensive net-shape processing was used, which reduces the cost of the actuator by over a factor of 10 over nonporous TiNi made by hot drawing of tube or electrical discharge machining. By forming the alloy as an open-celled foam, the surface area for heat transfer is dramatically increased, allowing for much faster response times. The technology also allows for netshape fabrication of the actuator, which allows for structural connections to be integrated into the actuator material, making these actuators significantly less expensive. Commercial applications include actuators for concepts such as the variable area chevron and nozzle in jet aircraft. Lightweight tube or rod components can be supplied to interested parties.

Jardine, Peter↗

High Performance Parallel Computational Nanotechnology

At a recent press conference, NASA Administrator Dan Goldin encouraged NASA Ames Research Center to take a lead role in promoting research and development of advanced, high-performance computer technology, including nanotechnology. Manufacturers of leading-edge microprocessors currently perform large-scale simulations in the design and verification of semiconductor devices and microprocessors. Recently, the need for this intensive simulation and modeling analysis has greatly increased, due in part to the ever-increasing complexity of these devices, as well as the lessons of experiences such as the Pentium fiasco. Simulation, modeling, testing, and validation will be even more important for designing molecular computers because of the complex specification of millions of atoms, thousands of assembly steps, as well as the simulation and modeling needed to ensure reliable, robust and efficient fabrication of the molecular devices. The software for this capacity does not exist today, but it can be extrapolated from the software currently used in molecular modeling for other applications: semi-empirical methods, ab initio methods, self-consistent field methods, Hartree-Fock methods, molecular mechanics; and simulation methods for diamondoid structures. In as much as it seems clear that the application of such methods in nanotechnology will require powerful, highly powerful systems, this talk will discuss techniques and issues for performing these types of computations on parallel systems. We will describe system design issues (memory, I/O, mass storage, operating system requirements, special user interface issues, interconnects, bandwidths, and programming languages) involved in parallel methods for scalable classical, semiclassical, quantum, molecular mechanics, and continuum models; molecular nanotechnology computer-aided designs (NanoCAD) techniques; visualization using virtual reality techniques of structural models and assembly sequences; software required to control mini robotic manipulators for positional control; scalable numerical algorithms for reliability, verifications and testability. There appears no fundamental obstacle to simulating molecular compilers and molecular computers on high performance parallel computers, just as the Boeing 777 was simulated on a computer before manufacturing it.

Saini, Subhash↗

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↗

Estimating soybean yields from high-temporal-resolution multi-source data using deep learning

Accurate and timely crop yield prediction is crucial for ensuring food security and maintaining stable agricultural markets. In recent years, there has been a surge in interest in leveraging high-temporal-resolution, multi-source data for effective crop growth monitoring and yield estimation. A notable challenge arises from the difficulty in capturing the intricate interactions between variables across different time steps within these high-temporal-resolution time series datasets. This complexity hinders the reliable extraction of yield information from voluminous and often noisy datasets, especially during periods of extreme weather events. Here, in this study, we propose an Attention and Graph Isomorphism Network-enhanced Bi-directional Long Short-Term Memory network (AGB-LSTM) for estimating county-level soybean yield in the United States. This model integrates a diverse set of remote sensing data, including Near-Infrared Reflectance of Vegetation (NIRv), Sun-Induced chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP), along with environmental covariates. The AGB-LSTM effectively leverages information related to crop yield from high-temporal-resolution time series data (5-days), achieving an accuracy of R²= 0.67 and rRMSE = 14.46%. This approach significantly outperforms traditional machine learning methods such as Random Forest (RF) (R²= 0.52, rRMSE = 17.36%) and Bi-LSTM (R²= 0.58, rRMSE = 16.17%). Sensitivity experiments with different time steps and ranges demonstrated that our model could accurately and stably predict yields 1 to 2 months before harvest. Moreover, data with a finer temporal resolution consistently improved prediction performance, resulting in an approximately 20% increase in and an approximately 20% decrease in rRMSE compared to using monthly composites. We also evaluated the robustness of the model under extreme climate events and observed strong performance (R²= 0.50, rRMSE = 21.32%). Finally, yield mapping for major soybean-producing regions in North America in 2023 revealed spatial patterns that closely matched USDA yield reports. Our findings suggest that the AGB-LSTM model is a promising and effective method for estimating yield and has notable potential for global crop yield forecasting.

Deep learning↗

Error latency measurements in symbolic architectures

Error latency, the time that elapses between the occurrence of an error and its detection, has a significant effect on reliability. In computer systems, failure rates can be elevated during a burst of system activity due to increased detection of latent errors. A hybrid monitoring environment is developed to measure the error latency distribution of errors occurring in main memory. The objective of this study is to develop a methodology for gauging the dependability of individual data categories within a real-time application. The hybrid monitoring technique is novel in that it selects and categorizes a specific subset of the available blocks of memory to monitor. The precise times of reads and writes are collected, so no actual faults need be injected. Unlike previous monitoring studies that rely on a periodic sampling approach or on statistical approximation, this new approach permits continuous monitoring of referencing activity and precise measurement of error latency.

Young, L. T.↗

Recent Advances in Commercial Memories and Potential Contribution to GN&C Miniaturation

The last few years have seen a surge in technology, device, and architecture introductions in commercial memories such as SDRAM and NAND driven by the explosion of handheld and portable electronics. Some of the resultant devices provide high density in very small and light packages, which may be possible to leverage for the miniaturization of future GN&C systems in addition to providing considerable memory capacity to enable advanced capabilities such as image-based navigation or adaptive/autonomous operations. We will show that these advanced SDRAM and NAND technologies are worth serious consideration for the next generation of GN&C needs by highlighting reliability and radiation effects results from some of these devices.

Yang-Scharlotta, Jean Y.↗

Data-driven estimation of energy consumption for electric bus under real-world driving conditions

Reliable and accurate estimation of an electric bus’s instantaneous energy consumption is critical in evaluating energy impacts of planning and control of electric bus operations. In this study, we developed machine learning-based long short-term memory (LSTM) and artificial neural network (ANN) models to estimate 1 Hz energy consumption of electric buses based on continuous monitoring data of electric buses in Chattanooga, Tennessee, in 2019 and 2020. We propose a data-partitioning algorithm to separate energy charging and discharging modes before applying data-driven estimation models. Here, a K-fold cross-validation-based model selection process was conducted to identify the optimal model structure and input variables in terms of prediction accuracy. The estimation results show the predicted mean absolute percentage error rates of LSTM and ANN models were 3% and 5%, respectively. We compared the proposed models with existing models in the literature based on the same testing data to demonstrate the predictability of our models.

Artificial neural network↗

Tools Ensure Reliability of Critical Software

In November 2006, after attempting to make a routine maneuver, NASA's Mars Global Surveyor (MGS) reported unexpected errors. The onboard software switched to backup resources, and a 2-day lapse in communication took place between the spacecraft and Earth. When a signal was finally received, it indicated that MGS had entered safe mode, a state of restricted activity in which the computer awaits instructions from Earth. After more than 9 years of successful operation gathering data and snapping pictures of Mars to characterize the planet's land and weather communication between MGS and Earth suddenly stopped. Months later, a report from NASA's internal review board found the spacecraft's battery failed due to an unfortunate sequence of events. Updates to the spacecraft's software, which had taken place months earlier, were written to the wrong memory address in the spacecraft's computer. In short, the mission ended because of a software defect. Over the last decade, spacecraft have become increasingly reliant on software to carry out mission operations. In fact, the next mission to Mars, the Mars Science Laboratory, will rely on more software than all earlier missions to Mars combined. According to Gerard Holzmann, manager at the Laboratory for Reliable Software (LaRS) at NASA's Jet Propulsion Laboratory (JPL), even the fault protection systems on a spacecraft are mostly software-based. For reasons like these, well-functioning software is critical for NASA. In the same year as the failure of MGS, Holzmann presented a new approach to critical software development to help reduce risk and provide consistency. He proposed The Power of 10: Rules for Developing Safety-Critical Code, which is a small set of rules that can easily be remembered, clearly relate to risk, and allow compliance to be verified. The reaction at JPL was positive, and developers in the private sector embraced Holzmann's ideas.

Source record↗

Towards the formal verification of the requirements and design of a processor interface unit: HOL listings

This technical report contains the Higher-Order Logic (HOL) listings of the partial verification of the requirements and design for a commercially developed processor interface unit (PIU). The PIU is an interface chip performing memory interface, bus interface, and additional support services for a commercial microprocessor within a fault tolerant computer system. This system, the Fault Tolerant Embedded Processor (FTEP), is targeted towards applications in avionics and space requiring extremely high levels of mission reliability, extended maintenance-free operation, or both. This report contains the actual HOL listings of the PIU verification as it currently exists. Section two of this report contains general-purpose HOL theories and definitions that support the PIU verification. These include arithmetic theories dealing with inequalities and associativity, and a collection of tactics used in the PIU proofs. Section three contains the HOL listings for the completed PIU design verification. Section 4 contains the HOL listings for the partial requirements verification of the P-Port.

Fura, David A.↗

Lessons Learned from OSIRIS-Rex Autonomous Navigation Using Natural Feature Tracking

The Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer (Osiris-REx) spacecraft is scheduled to launch in September, 2016 to embark on an asteroid sample return mission. It is expected to rendezvous with the asteroid, Bennu, navigate to the surface, collect a sample (July 20), and return the sample to Earth (September 23). The original mission design called for using one of two Flash Lidar units to provide autonomous navigation to the surface. Following Preliminary design and initial development of the Lidars, reliability issues with the hardware and test program prompted the project to begin development of an alternative navigation technique to be used as a backup to the Lidar. At the critical design review, Natural Feature Tracking (NFT) was added to the mission. NFT is an onboard optical navigation system that compares observed images to a set of asteroid terrain models which are rendered in real-time from a catalog stored in memory on the flight computer. Onboard knowledge of the spacecraft state is then updated by a Kalman filter using the measured residuals between the rendered reference images and the actual observed images. The asteroid terrain models used by NFT are built from a shape model generated from observations collected during earlier phases of the mission and include both terrain shape and albedo information about the asteroid surface. As a result, the success of NFT is highly dependent on selecting a set of topographic features that can be both identified during descent as well as reliably rendered using the shape model data available. During development, the OSIRIS-REx team faced significant challenges in developing a process conducive to robust operation. This was especially true for terrain models to be used as the spacecraft gets close to the asteroid and higher fidelity models are required for reliable image correlation. This paper will present some of the challenges and lessons learned from the development of the NFT system which includes not just the flight hardware and software but the development of the terrain models used to generate the onboard rendered images.

Navigation↗

Main memory unit

The development of a main memory unit (MMU) for the space ultrareliable module computer (SUMC) model HTC is discussed. The design, fabrication, and test of basic memory modules (BMM) which were to be used in the design and construction of the MMU are described. The BMM was designed from state-of-the-art technologies which included large scale integration devices mounted and interconnected on a substrate to form a functional module to be utilized in the MMU development. A SUMC memory system design study is discussed which addressed itself to the BMM design and analysis to be conducted to determine the most efficient organization of the BMM in order to establish such modularity features as: word length expandability without redesign, high reliability, and fault tolerance. One MMU was designed, fabricated, tested, and delivered which will be electrical and mechanically compatible with the hybrid technology computer (HTC) model of the SUMC family of computers. The MMU will contain a storage capacity of 8196 36 bit words which includes a parity bit for each 8 bit byte of data.

Source record↗

Computerized monitoring and control of experiments in space

The computer subsystem of the Villanova University GAS (Get Away Special) experiment apparatus is discussed. The function of the computer subsystem is to provide data acquisition and control system support to the experiments. The computer subsystem will provide high availability, low power consumption and highly reliable data retention. The general layout of the subsystem provides for redundant processing units, control modules, and multiple data acquisition modules. Each of the two redundant processing units will be composed of a microprocessor, control logic, PROM, RAM, non-volitile memory, timers, self-check logic and data ports to the data acquisition and control modules. One unit will control the experiment while the other shadows the primary unit operation. The data acquisition module gathers data from the experiment. The data is transfered to the processing unit in digital form. The control module validates the data, decodes it and executes the command.

Janisch, Thomas V.↗

Factor analysis and predictive validity of microcomputer-based tests

11 tests were selected from two microcomputer-based performance test batteries because previously these tests exhibited rapid stability (less than 10 min, of practice) and high retest reliability efficiencies (r greater than 0.707 for each 3 min. of testing). The battery was administered three times to each of 108 college students (48 men and 60 women) and a factor analysis was performed. Two of the three identified factors appear to be related to information processing ("encoding" and "throughput/decoding"), and the third named an "output/speed" factor. The spatial, memory, and verbal tests loaded on the "encoding" factor and included Grammatical Reasoning, Pattern Comparison, Continuous Recall, and Matrix Rotation. The "throughput/decoding" tests included perceptual/numerical tests like Math Processing, Code Substitution, and Pattern Comparison. The output speed factor was identified by Tapping and Reaction Time tests. The Wonderlic Personnel Test was group administered before the first and after the last administration of the performance tests. The multiple Rs in the total sample between combined Wonderlic as a criterion and less than 5 min. of microcomputer testing on Grammatical Reasoning and Math Processing as predictors ranged between 0.41 and 0.52 on the three test administrations. Based on these results, the authors recommend a core battery which, if time permits, would consist of two tests from each factor. Such a battery is now known to permit stable, reliable, and efficient assessment.

Non-NASA Center↗