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At least 1,765 records · Page 98

Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing

While the complementary metal-oxide semiconductor (CMOS) technology is the mainstream for the hardware implementation of neural networks, an alternative route is explored based on a new class of spiking oscillators called “thermal neuristors”, which operate and interact solely via thermal processes. Utilizing the insulator-to-metal transition (IMT) in vanadium dioxide, a wide variety of reconfigurable electrical dynamics mirroring biological neurons is demonstrated. Notably, inhibitory functionality is achieved just in a single oxide device, and cascaded information flow is realized exclusively through thermal interactions. To elucidate the underlying mechanisms of the neuristors, a detailed theoretical model is developed, which accurately reflects the experimental results. In conclusion, this study establishes the foundation for scalable and energy-efficient thermal neural networks, fostering progress in brain-inspired computing.

36 MATERIALS SCIENCE↗

Classical Benchmarks for Variational Quantum Eigensolver Simulations of the Hubbard Model

Simulating the Hubbard model is of great interest to a wide range of applications within condensed matter physics, however its solution on classical computers remains challenging in dimensions larger than one. The relative simplicity of this model, embodied by the sparseness of the Hamiltonian matrix, allows for its efficient implementation on quantum computers, and for its approximate solution using variational algorithms such as the variational quantum eigensolver. While these algorithms have been shown to reproduce the qualitative features of the Hubbard model, their quantitative accuracy in terms of producing true ground state energies and other properties, and the dependence of this accuracy on the system size and interaction strength, the choice of variational ansatz, and the degree of spatial inhomogeneity in the model, remains unknown. Here we present a rigorous classical benchmarking study, demonstrating the potential impact of these factors on the accuracy of the variational solution of the Hubbard model on quantum hardware, for systems with up to 32 qubits. We find that even when using the most accurate wavefunction ansätze for the Hubbard model, the error in its ground state energy and wavefunction plateaus for larger lattices, while stronger electronic correlations magnify this issue. Concurrently, spatially inhomogeneous parameters and the presence of off-site Coulomb interactions only have a small effect on the accuracy of the computed ground state energies. Our study highlights the capabilities and limitations of current approaches for solving the Hubbard model on quantum hardware, and we discuss potential future avenues of research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Flight demonstration of flight termination system and solid rocket motor ignition using semiconductor laser initiated ordnance

Solid State Laser Initiated Ordnance (LIO) offers new technology having potential for enhanced safety, reduced costs, and improved operational efficiency. Concerns over the absence of programmatic applications of the technology, which has prevented acceptance by flight programs, should be abated since LIO has now been operationally implemented by the Laser Initiated Ordnance Sounding Rocket Demonstration (LOSRD) Program. The first launch of solid state laser diode LIO at the NASA Wallops Flight Facility (WFF) occurred on March 15, 1995 with all mission objectives accomplished. This project, Phase 3 of a series of three NASA Headquarters LIO demonstration initiatives, accomplished its objective by the flight of a dedicated, all-LIO sounding rocket mission using a two-stage Nike-Orion launch vehicle. LIO flight hardware, made by The Ensign-Bickford Company under NASA's first Cooperative Agreement with Profit Making Organizations, safely initiated three demanding pyrotechnic sequence events, namely, solid rocket motor ignition from the ground and in flight, and flight termination, i.e., as a Flight Termination System (FTS). A flight LIO system was designed, built, tested, and flown to support the objectives of quickly and inexpensively putting LIO through ground and flight operational paces. The hardware was fully qualified for this mission, including component testing as well as a full-scale system test. The launch accomplished all mission objectives in less than 11 months from proposal receipt. This paper concentrates on accomplishments of the ordnance aspects of the program and on the program's implementation and results. While this program does not generically qualify LIO for all applications, it demonstrated the safety, technical, and operational feasibility of those two most demanding applications, using an all solid state safe and arm system in critical flight applications.

Schulze, Norman R.↗

The role of radiation hard solar cells in minimizing the costs of global satellite communications systems

An analysis embodied in a PC computer program is presented which quantitatively demonstrates how the availability of radiation hard solar cells can minimize the cost of a global satellite communication system. The chief distinction between the currently proposed systems, such as Iridium Odyssey and Ellipsat, is the number of satellites employed and their operating altitudes. Analysis of the major costs associated with implementing these systems shows that operation within the earth's radiation belts can reduce the total system cost by as much as a factor of two, so long as radiation hard components including solar cells, can be used. A detailed evaluation of several types of planar solar cells is given, including commercially available Si and GaAs/Ge cells, and InP/Si cells which are under development. The computer program calculates the end of life (EOL) power density of solar arrays taking into account the cell geometry, coverglass thickness, support frame, electrical interconnects, etc. The EOL power density can be determined for any altitude from low earth orbit (LEO) to geosynchronous (GEO) and for equatorial to polar planes of inclination. The mission duration can be varied over the entire range planned for the proposed satellite systems. An algorithm is included in the program for determining the degradation of cell efficiency for different cell technologies due to proton and electron irradiation. The program can be used to determine the optimum configuration for any cell technology for a particular orbit and for a specified mission life. Several examples of applying the program are presented, in which it is shown that the EOL power density of different technologies can vary by an order of magnitude for certain missions. Therefore, although a relatively radiation soft technology can be made to provide the required EOL power by simply increasing the size of the array, the impact on the total system budget could be unacceptable, due to increased launch and hardware costs. In aggregate these factors can account for more than a 10% increase in the total system cost. Since the estimated total costs of proposed global coverage systems range from $1 Billion to $9 Billion, the availability of radiation hard solar cells could make a decisive difference in the selection of a particular constellation architecture.

Summers, Geoffrey P.↗

Tuning of MEMS Devices using Evolutionary Computation and Open-loop Frequency Response

We propose a tuning method for MEMS gyroscopes based on evolutionary computation that has the capacity to efficiently increase the sensitivity of MEMS gyroscopes through tuning and, furthermore, to find the optimally tuned configuration for this state of increased sensitivity. The tuning method was tested for the second generation JPL/Boeing Post-resonator MEMS gyroscope using the measurement of the frequency response of the MEMS device in open-loop operation.

evolvable hardware↗

Evolutionary Computation Applied to the Tuning of MEMS Gyroscopes

We propose a tuning method for MEMS gyroscopes based on evolutionary computation to efficiently increase the sensitivity of MEMS gyroscopes through tuning and, furthermore, to find the optimally tuned configuration for this state of increased sensitivity. The tuning method was tested for the second generation JPL/Boeing Post-resonator MEMS gyroscope using the measurement of the frequency response of the MEMS device in open-loop operation.

evolvable hardware↗

System for controller area network payload decoding

A system for decoding an unknown automotive controller area network (“CAN”) message definitions. CAN data vehicle signal mappings are typically held in secret and varied by automotive model and year. Without knowledge of the mappings, the wealth of real-time vehicle data hidden in the automotive CAN packets is uninterpretable—impeding research, after-market tuning, efficiency and performance monitoring, fault diagnosis, and privacy-related technologies. This system can ascertain the CAN signals' boundaries (start bit and length), endianness (byte ordering), signedness (binary-to-integer encoding) from raw CAN data. This allows conversion of CAN data to time series. Interpreting the translated CAN data's physical meaning and finding a linear mapping to standard units (e.g., knowing the signal is speed and scaling values to represent units of miles per hour) can be achieved for many signals by leveraging diagnostic standards to obtain real-time measurements of in-vehicle systems. The system can be integrated into lightweight hardware enabling an OBD-II plugin for real-time in-vehicle CAN decoding or run on standard computers. The system can output a standard DBC file with the signal definition information.

Verma, Kiren E.↗

Testbed Demonstration of a Microgrid Building Block Prototype

With the adoption of ambitious climate action goals, the penetration level of distributed energy resources (DERs) is rapidly increasing. Microgrids are an efficient way to integrate these DERs, facilitating their operation and control. Additionally, microgrids enhance the overall resilience of the distribution system by serving critical loads both within and outside their boundaries. However, the need for substantial customized engineering leads to a high cost of development, installation and maintenance of microgrids. To address this challenge, Microgrid Building Blocks (MBB) are proposed to reduce the deployment cost of microgrids through modular, standardized design and implementation. This work presents a testbed demonstrating the integrated power conversion, control, and communication functionalities of an MBB. The testbed is formed by a real-time electromagnetic transient (EMT) simulation combined with a hardware and software prototype of MBB. The use cases supported by the MBB testbed are enumerated. The islanded operation, voltage regulation, and optimal dispatch capabilities of an MBB-based microgrid controller are validated through a case study.

Somda, Baza [Virginia Tech]↗

Design of Hopfield Networks Based on Superconducting Coupled Oscillators

The global energy shortage has driven the development of many energy-efficient computational platforms beyond Moore's law, among which brain-inspired neuromorphic computing is one of the promising solutions. Associative memory and pattern recognition are important computations solved by brain-inspired Hopfield networks. Classical Hopfield networks store memories via fixed point attractors of their dynamics. In oscillatory Hopfield networks, these attractors are replaced by periodic orbits. Here, we design an oscillatory Hopfield network based on coupled superconducting oscillators. We first employ a mathematical phase reduction approach to map networks of coupled superconducting rapid single flux quantum (RSFQ) ring oscillators to coupled Kuramoto phase-oscillator networks. We use this theory to numerically optimize the hardware's mutual inductances in order to directly match the phase-reduced superconducting oscillators to a model of phase-oscillator-based Hopfield networks. The resulting network can store multiple oscillatory phase-locked memory patterns and recover the patterns based on the initial phase conditions. As different pattern recognition tasks, or learning, require tunable connectivity strengths between the oscillatory nodes, we further employ a coupler circuit that enables tuning the coupling strength between two oscillators by applying an external flux. We demonstrate the functionality of our design through numerical simulations of a small example network with oscillators operating at 86 GHz and recognizing patterns within 10 ns. Our approach enables the learning and retrieval of dynamical memory patterns with a wide range of applications where rhythmic dynamic output is beneficial.

Cheng, Ran↗

Using CLIPS to represent knowledge in a VR simulation

Virtual reality (VR) is an exciting use of advanced hardware and software technologies to achieve an immersive simulation. Until recently, the majority of virtual environments were merely 'fly-throughs' in which a user could freely explore a 3-dimensional world or a visualized dataset. Now that the underlying technologies are reaching a level of maturity, programmers are seeking ways to increase the complexity and interactivity of immersive simulations. In most cases, interactivity in a virtual environment can be specified in the form 'whenever such-and-such happens to object X, it reacts in the following manner.' CLIPS and COOL provide a simple and elegant framework for representing this knowledge-base in an efficient manner that can be extended incrementally. The complexity of a detailed simulation becomes more manageable when the control flow is governed by CLIPS' rule-based inference engine as opposed to by traditional procedural mechanisms. Examples in this paper will illustrate an effective way to represent VR information in CLIPS, and to tie this knowledge base to the input and output C routines of a typical virtual environment.

Engelberg, Mark L.↗

Microgravity Research Results and Experiences from the NASA Mir Space Station Program

The Microgravity Research Program Office (MRPO) participated aggressively in Phase I of the International Space Station Program using the Russian Mir Space Station. The Mir Station offered an otherwise unavailable opportunity to explore the advantages and challenges to long duration microgravity space research. Payloads with both NASA and commercial backing were included as well as cooperative research with the Canadian Space Agency (CSA). From this experience, much was learned about dealing with long duration on orbit science utilization and developing new working relationships with our Russian partner to promote efficient planning, operations, and integration to solve complexities associated with a multiple partner program. Microgravity participation in the NASA Mir Program began with the first joint NASA Mir flight to the Mir Space Station. The earliest participation setup acceleration measurement capabilities that were used throughout the Program. Research, conducted by all Microgravity science disciplines, continued on each subsequent increment for the entire three-year duration of the Program. The Phase I Program included the Microgravity participation of over 30 Fluids, Combustion, Materials, and Biotechnology Sciences and numerous commercially sponsored research payloads. In addition to the research gained from Microgravity investigations, long duration operation of facility hardware was tested. Microgravity facilities operated on Mir included the Space Acceleration Measurement System (SAMS), the Microgravity Glovebox (MGBX), the Biotechnology System (BTS) and the Canadian Space Agency sponsored Microgravity Isolation Mount (MIM). The Russian OPTIZONE Furnace was also incorporated into our material science research. All of these efforts yielded significant and useful scientific research data. This paper focuses on the microgravity research conducted onboard the Mir space station. It includes the Program preparation and planning necessary to support this type of cross increment research experience; the payloads which were flown; and summaries of significant microgravity science findings. Most importantly this paper highlights the various disciplines of microgravity research conducted during the International Space Station, Phase 1 Program onboard the Mir Station. A capsulation of significant research and the applicability of our findings are provided. In addition, a brief discussion of how future microgravity science gathering capabilities, hardware development and payload operations techniques have enhanced our ability to conduct long duration microgravity research.

Schagheck, R. A.↗

Flexible Composite-Material Pressure Vessel

A proposed lightweight pressure vessel would be made of a composite of high-tenacity continuous fibers and a flexible matrix material. The flexibility of this pressure vessel would render it (1) compactly stowable for transport and (2) more able to withstand impacts, relative to lightweight pressure vessels made of rigid composite materials. The vessel would be designed as a structural shell wherein the fibers would be predominantly bias-oriented, the orientations being optimized to make the fibers bear the tensile loads in the structure. Such efficient use of tension-bearing fibers would minimize or eliminate the need for stitching and fill (weft) fibers for strength. The vessel could be fabricated by techniques adapted from filament winding of prior composite-material vessels, perhaps in conjunction with the use of dry film adhesives. In addition to the high-bias main-body substructure described above, the vessel would include a low-bias end substructure to complete coverage and react peak loads. Axial elements would be overlaid to contain damage and to control fiber orientation around side openings. Fiber ring structures would be used as interfaces for connection to ancillary hardware.

Brown, Glen↗

Runtime Thread-Block Optimization for Custom Multistream CUDA Kernels for the Glenn Research Center Communication Analysis Suite

In preparation of the return of humans to the Moon with the coming Artemis missions, NASA scientists must evaluate proposed landing site locations for terrain and communications viability. The Glenn Research Center Communication Analysis Suite (GCAS) combines sophisticated communication network models with accurate lunar terrain to access sites across the Moon’s south pole. Given the importance of proper site selection to crew safety and mission success, many locations need to be analyzed resulting in a large computational load needing to be performed. To meet the growing project demands, development has begun to improve the runtime efficiency of GCAS with GPU parallelization by way of multi-stream CUDA kernels. One of the most prominent factors in kernel optimization is the proper selection of thread-block dimensions in order to maximize the concurrent operation on the device. Typically, thread-block dimensions are optimized by hand requiring many stages of benchmarking and iteration. Additionally, given the main conditions to optimization are the physical GPU architecture and problem size, these optimal dimensions are non-portable and fragile in their scope. As such, a novel optimization routine was developed to generate the optimal thread-block dimensions during runtime with considerations to hardware specifications and problem size resolving the issues of portability and enabling the function of more dynamic routines.

Aden Bergstresser↗

Improving Stratocumulus Cloud Amounts in a 200‐m Resolution Multi‐Scale Modeling Framework Through Tuning of Its Interior Physics

Abstract High‐Resolution Multi‐scale Modeling Frameworks (HR)—global climate models that embed separate, convection‐resolving models with high enough resolution to resolve boundary layer eddies—have exciting potential for investigating low cloud feedback dynamics due to reduced parameterization and ability for multidecadal throughput on modern computing hardware. However low clouds in past HR have suffered a stubborn problem of over‐entrainment due to an uncontrolled source of mixing across the marine subtropical inversion manifesting as stratocumulus dim biases in present‐day climate, limiting their scientific utility. We report new results showing that this over‐entrainment can be partly offset by using hyperviscosity and cloud droplet sedimentation. Hyperviscosity damps small‐scale momentum fluctuations associated with the formulation of the momentum solver of the embedded large eddy simulation. By considering the sedimentation process adjacent to default one‐moment microphysics in HR, condensed phase particles can be removed from the entrainment zone, which further reduces entrainment efficiency. The result is an HR that can produce more low clouds with a higher liquid water path and a reduced stratocumulus dim bias. Associated improvements in the explicitly simulated sub‐cloud eddy spectrum are observed. We report these sensitivities in multi‐week tests and then explore their operational potential alongside microphysical retuning in decadal simulations at operational 1.5° exterior resolution. The result is a new HR having desired improvements in the baseline present‐day low cloud climatology, and a reduced global mean bias and root mean squared error of absorbed shortwave radiation. We suggest it should be promising for examining low cloud feedbacks with minimal approximation.

54 ENVIRONMENTAL SCIENCES↗

Issues concerning centralized versus decentralized power deployment

The results of a study of proposed lunar base architectures to identify issues concerning centralized and decentralized power system deployment options are presented. The power system consists of the energy producing system (power plant), the power conditioning components used to convert the generated power into the form desired for transmission, the transmission lines that conduct this power from the power sources to the loads, and the primary power conditioning hardware located at the user end. Three power system architectures, centralized, hybrid, and decentralized, were evaluated during the course of this study. Candidate power sources were characterized with respect to mass and radiator area. Two electrical models were created for each architecture to identify the preferred method of power transmission, dc or ac. Each model allowed the transmission voltage level to be varied at assess the impact on power system mass. The ac power system models also permitted the transmission line configurations and placements to determine the best conductor construction and installation location. Key parameters used to evaluate each configuration were power source and power conditioning component efficiencies, masses, and radiator areas; transmission line masses and operating temperatures; and total system mass.

Metcalf, Kenneth J.↗

Controller area network decoder (CAN-D)

A system and method for decoding an unknown automotive controller area network (“CAN”) message definitions. CAN data vehicle signal mappings are typically held in secret and varied by automotive model and year. Without knowledge of the mappings, the wealth of real-time vehicle data hidden in the automotive CAN packets is uninterpretable—impeding research, after-market tuning, efficiency and performance monitoring, fault diagnosis, and privacy-related technologies. This technology can ascertain the CAN signals' boundaries (start bit and length), endianness (byte ordering), signedness (binary-to-integer encoding) from raw CAN data. This allows conversion of CAN data to time series. Interpreting the translated CAN data's physical meaning and finding a linear mapping to standard units (e.g., knowing the signal is speed and scaling values to represent units of miles per hour) can be achieved for many signals by leveraging diagnostic standards to obtain real-time measurements of in-vehicle systems. The system and method can be integrated into lightweight hardware enabling an OBD-II plugin for real-time in-vehicle CAN decoding or run on standard computers. The system can output a standard DBC file with the signal definition information.

Verma, Kiren E.↗

Multiphysics Modeling of Hydrokinetic Turbine Energy Conversion System

Hydrokinetic turbines (HKTs) hold great promise as a renewable energy source, but high maintenance costs and limited energy output hinder their widespread adoption. The lack of comprehensive research on HKT drivetrain designs creates a knowledge gap in enhancing generation efficiency and cost reduction. A model of the HKT system with a focus on electric drivetrains and power converters is required to address this knowledge gap. This paper first introduces a MATLAB-averaged model integrating electrical-mechanical-thermal domains and aging behaviors within multi-time frames. Then a PLECS model, which incorporates maximum power point tracking and dq reference framed control for AC-DC-AC power converters, is enriched by a dynamic thermal model to predict fast transients accurately. These models optimize the design at the component level, resulting in improved integrated system performance. Furthermore, the validation of the models is carried out through hardware experiments for the averaged model and hardware-in-the-loop testing for the dynamic model.

ADVANCED PROPULSION SYSTEMS,HYDRO ENERGY↗

Attention to quantum complexity

The imminent era of error-corrected quantum computing demands robust methods to characterize quantum state complexity from limited, noisy measurements. We introduce the Quantum Attention Network (QuAN), a classical artificial intelligence (AI) framework leveraging attention mechanisms tailored for learning quantum complexity. Inspired by large language models, QuAN treats measurement snapshots as tokens while respecting permutation invariance. Combined with our parameter-efficient miniset self-attention block, this enables QuAN to access high-order moments of bit-string distributions and preferentially attend to less noisy snapshots. We test QuAN across three quantum simulation settings: driven hard-core Bose-Hubbard model, random quantum circuits, and toric code under coherent and incoherent noise. QuAN directly learns entanglement and state complexity growth from experimental computational basis measurements, including complexity growth in random circuits from noisy data. In regimes inaccessible to existing theory, QuAN unveils the complete phase diagram for noisy toric code data as a function of both noise types, highlighting AI’s transformative potential for assisting quantum hardware.

Kim, Hyejin [Cornell Univ., Ithaca, NY (United Sta↗