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Results for “hybrid architectures”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

A neurocomputer based on an analog-digital hybrid architecture

A novel analog-digital hybrid architecture based on the utilization of high density digital random access memories for the storage of the synaptic weights of a neural network, and high speed analog hardware to perform neural computation is described. An electronic neurocomputer based on such an architecture is ideally suited for investigating the dynamics, associative recall properties, and computational capabilities of neural networks and provides significant speed improvement in comparison to conventional software based neural network simulations. As a demonstration of the feasibility of the hybrid architectural concept, a prototype breadboard hybrid neurocomputer system with 32 neurons has been designed and fabricated with off-the-shelf hardware components. The performance of the breadboard system has been tested for variety of applications including associative memory and combinatorial problem solving such as Graph Coloring, and is discussed in this paper.

Moopenn, A.↗
NASA NTRS2015

Mars Conjunction Crewed Missions With a Reusable Hybrid Architecture

A new crew Mars architecture has been developed that provides many potential benefits for NASA-led human Mars moons and surface missions beginning in the 2030s or 2040s. By using both chemical and electric propulsion systems where they are most beneficial and maintaining as much orbital energy as possible, the Hybrid spaceship that carries crew round trip to Mars is pre-integrated before launch and can be delivered to orbit by a single launch. After check-out on the way to cis-lunar space, it is refueled and can travel round trip to Mars in less than 1100 days, with a minimum of 300 days in Mars vicinity (opportunity dependent). The entire spaceship is recaptured into cis-lunar space and can be reused. The spaceship consists of a habitat for 4 crew attached to the Hybrid propulsion stage which uses long duration electric and chemical in-space propulsion technologies that are in use today. The hybrid architecture's con-ops has no in-space assembly of the crew transfer vehicle and requires only rendezvous of crew in a highly elliptical Earth orbit for arrival at and departure from the spaceship. The crew transfer vehicle does not travel to Mars so it only needs be able to last in space for weeks and re-enter at lunar velocities. The spaceship can be refueled and resupplied for multiple trips to Mars (every other opportunity). The hybrid propulsion stage for crewed transits can also be utilized for cargo delivery to Mars every other opportunity in a reusable manner to pre-deploy infrastructure required for Mars vicinity operations. Finally, the Hybrid architecture provides evolution options for mitigating key long-duration space exploration risks, including crew microgravity and radiation exposure.

Merrill, Raymond G.↗
NASA NTRS2014

CSP: A Multifaceted Hybrid Architecture for Space Computing

Research on the CHREC Space Processor (CSP) takes a multifaceted hybrid approach to embedded space computing. Working closely with the NASA Goddard SpaceCube team, researchers at the National Science Foundation (NSF) Center for High-Performance Reconfigurable Computing (CHREC) at the University of Florida and Brigham Young University are developing hybrid space computers that feature an innovative combination of three technologies: commercial-off-the-shelf (COTS) devices, radiation-hardened (RadHard) devices, and fault-tolerant computing. Modern COTS processors provide the utmost in performance and energy-efficiency but are susceptible to ionizing radiation in space, whereas RadHard processors are virtually immune to this radiation but are more expensive, larger, less energy-efficient, and generations behind in speed and functionality. By featuring COTS devices to perform the critical data processing, supported by simpler RadHard devices that monitor and manage the COTS devices, and augmented with novel uses of fault-tolerant hardware, software, information, and networking within and between COTS devices, the resulting system can maximize performance and reliability while minimizing energy consumption and cost. NASA Goddard has adopted the CSP concept and technology with plans underway to feature flight-ready CSP boards on two upcoming space missions.

Reconfigurable↗
DOE OSTI2024

PaRSEC: Scalability, flexibility, and hybrid architecture support for task-based applications in ECP

This paper highlights the most significant enhancements made to PaRSEC, a scalable task-based runtime system designed for hybrid machines, during the Exascale Computing Project (ECP). The enhancements focus on expanding the capabilities of PaRSEC to address the evolving landscape of parallel computing. Notable achievements include the integration of support for three major types of accelerators (NVIDIA, AMD, and Intel GPUs), the refinement and increased flexibility of the communication subsystem, and the introduction of new programming interfaces tailored for irregular applications. Additionally, the project resulted in the development of powerful debugging and performance analysis tools aimed at assisting users in understanding and optimizing their applications. We present a comprehensive demonstration of these advancements through a series of benchmarks and applications within ECP and beyond, thereby showcasing the enhanced capabilities of PaRSEC across the diverse architectures within the ECP, providing valuable insights into the runtime system’s adaptability and performance across varied computing environments.

Bouteiller, Aurelien↗
NASA NTRS2011

Hybrid architecture active wavefront sensing and control system, and method

According to various embodiments, provided herein is an optical system and method that can be configured to perform image analysis. The optical system can comprise a telescope assembly and one or more hybrid instruments. The one or more hybrid instruments can be configured to receive image data from the telescope assembly and perform a fine guidance operation and a wavefront sensing operation, simultaneously, on the image data received from the telescope assembly.

Feinberg, Lee D.↗
NASA NTRS1989

A hybrid architecture for the implementation of the Athena neural net model

The implementation of an earlier introduced neural net model for pattern classification is considered. Data flow principles are employed in the development of a machine that efficiently implements the model and can be useful for real time classification tasks. Further enhancement with optical computing structures is also considered.

Koutsougeras, C.↗
NASA NTRS1996

Hybrid Architectures and Their Impact on Intelligent Design

In this presentation we investigate a novel framework for the design of autonomous fuzzy intelligent systems. The system integrates the following modules into a single autonomous entity: (1) a fuzzy expert system; (2) artificial neural network; (3) genetic algorithm; and (4) case-base reasoning. We describe the integration of these units into one intelligent structure and discuss potential applications.

Kandel, Abe↗
NASA NTRS2010

Hybrid Architecture Active Wavefront Sensing and Control

A method was developed for performing relatively high-speed wavefront sensing and control to overcome thermal instabilities in a segmented primary mirror telescope [e.g., James Webb Space Telescope (JWST) at L2], by using the onboard fine guidance sensor (FGS) to minimize expense and complexity. This FGS performs centroiding on a bright star to feed the information to the pointing and control system. The proposed concept is to beam split the image of the guide star (or use a single defocused guide star image) to perform wavefront sensing using phase retrieval techniques. Using the fine guidance sensor star image for guiding and fine phasing eliminates the need for other, more complex ways of achieving very accurate sensing and control that is needed for UV-optical applications. The phase retrieval occurs nearly constantly, so passive thermal stability over fourteen days is not required. Using the FGS as the sensor, one can feed segment update information to actuators on the primary mirror that can update the primary mirror segment fine phasing with this frequency. Because the thermal time constants of the primary mirror are very slow compared to this duration, the mirror will appear extremely stable during observations (to the level of accuracy of the sensing and control). The sensing can use the same phase retrieval techniques as the JWST by employing an additional beam splitter, and having each channel go through a weak lens (one positive and one negative). The channels can use common or separate detectors. Phase retrieval can be performed onboard. The actuation scheme would include a coarse stage able to achieve initial alignment of several millimeters of range (similar to JWST and can use a JWST heritage sensing approach in the science camera) and a fine stage capable of continual updates.

Feinberg, Lee↗
NASA NTRS2011

Hybrid Power Management-Based Vehicle Architecture

Hybrid Power Management (HPM) is the integration of diverse, state-of-the-art power devices in an optimal configuration for space and terrestrial applications (s ee figure). The appropriate application and control of the various power devices significantly improves overall system performance and efficiency. The basic vehicle architecture consists of a primary power source, and possibly other power sources, that provides all power to a common energy storage system that is used to power the drive motors and vehicle accessory systems. This architecture also provides power as an emergency power system. Each component is independent, permitting it to be optimized for its intended purpose. The key element of HPM is the energy storage system. All generated power is sent to the energy storage system, and all loads derive their power from that system. This can significantly reduce the power requirement of the primary power source, while increasing the vehicle reliability. Ultracapacitors are ideal for an HPM-based energy storage system due to their exceptionally long cycle life, high reliability, high efficiency, high power density, and excellent low-temperature performance. Multiple power sources and multiple loads are easily incorporated into an HPM-based vehicle. A gas turbine is a good primary power source because of its high efficiency, high power density, long life, high reliability, and ability to operate on a wide range of fuels. An HPM controller maintains optimal control over each vehicle component. This flexible operating system can be applied to all vehicles to considerably improve vehicle efficiency, reliability, safety, security, and performance. The HPM-based vehicle architecture has many advantages over conventional vehicle architectures. Ultracapacitors have a much longer cycle life than batteries, which greatly improves system reliability, reduces life-of-system costs, and reduces environmental impact as ultracapacitors will probably never need to be replaced and disposed of. The environmentally safe ultracapacitor components reduce disposal concerns, and their recyclable nature reduces the environmental impact. High ultracapacitor power density provides high power during surges, and the ability to absorb high power during recharging. Ultracapacitors are extremely efficient in capturing recharging energy, are rugged, reliable, maintenance-free, have excellent lowtemperature characteristic, provide consistent performance over time, and promote safety as they can be left indefinitely in a safe, discharged state whereas batteries cannot.

Eichenberg, Dennis J.↗
NASA NTRS2015

An Integrated Hybrid Transportation Architecture for Human Mars Expeditions

NASA's Human Spaceflight Architecture Team is developing a reusable hybrid transportation architecture that uses both chemical and electric propulsion systems on the same vehicle to send crew and cargo to Mars destinations such as Phobos, Deimos, the surface of Mars, and other orbits around Mars. By applying chemical and electrical propulsion where each is most effective, the hybrid architecture enables a series of Mars trajectories that are more fuel-efficient than an all chemical architecture without significant increases in flight times. This paper presents an integrated Hybrid in-space transportation architecture for piloted missions and delivery of cargo. A concept for a Mars campaign including orbital and Mars surface missions is described in detail including a system concept of operations and conceptual design. Specific constraints, margin, and pinch points are identified for the architecture and opportunities for critical path commercial and international collaboration are discussed.

Merrill, Raymond G.↗
NASA NTRS2019

End to End Optimization of a Mars Hybrid Transportation Architecture

NASA’s Mars Study Capability Team (MSCT) is developing a reusable Mars hybrid transportation architecture in which both chemical and solar electric propulsion systems are used in a single vehicle design to send crew and cargo to Mars. This paper presents a new integrated framework that combines Earth departure/arrival, heliocentric trajectory, Mars orbit reorientation, and vehicle sizing into a single environment and solves the entire mission from beginning to end in an effort to find a globally optimized solution for the hybrid architecture.

Qu, Min↗
DOE OSTI2025

A hybrid neural architecture: Online attosecond x-ray characterization

The emergence of high-repetition-rate x-ray free-electron lasers (XFELs), such as SLAC’s LCLS-II, serves as our canonical example for autonomous controls that necessitate high-throughput diagnostics paired with streaming computational pipelines capable of single-shot analysis with extremely low latency. We present the deterministic characterization with an integrated parallelizable hybrid resolver architecture, a hybrid machine learning framework designed for fast, accurate analysis of XFEL diagnostics using angular streaking-based sinogram images. This architecture integrates convolutional neural networks and bidirectional long short-term memory models to denoise input, identify x-ray sub-spike features, and extract sub-spike relative delays with sub-30 attosecond temporal resolution. Deployed on low-latency hardware, it achieves over 10 kHz throughput with 168.3 μs inference latency, indicating scalability to 14 kHz with field-programmable gate array integration. By transforming regression tasks into classification problems and leveraging optimized error encoding, we achieve high precision with low-latency performance that is critical for real-time streaming event selection and experimental control feedback signals. This represents a key development in real-time control pipelines for next-generation autonomous science, generally, and high repetition-rate x-ray experiments in particular.

Accelerator Physics (physics.acc-ph)↗
NASA NTRSDate not supplied

Parallel Hybrid Turboprop Performance Modeling and Optimization

NASA’s Electrified Powertrain Flight Demonstration (EPFD) project conducts ground and flight tests of integrated Megawatt (MW) class hybrid-electric powertrain systems on regional turboprop aircraft demonstrators. To meet the increased demand for assessment of potential capabilities and benefits from these novel vehicle configurations, NASA is developing tooling and models to estimate the performance of hybridized regional turboprops. This paper covers the development of a parametrically driven performance model for a De Havilland Canada Dash 8-400 (Q400) regional turboprop integrated with a novel parallel hybrid architecture using the Gascon framework. Gascon is a modern reimplementation of the General Aviation Synthesis Program (GASP) built using the Condor mathematical modeling framework in Python. Within Gascon, a parametric representation of the parallel hybrid architecture was synthesized, which features the electric motor coupled to the power turbine. This capability allows for in-the-loop optimization of the parametric parallel hybrid architecture to characterize the mission capabilities and fuel savings of the design and determine optimal power scheduling strategies for efficient electric power management for a given mission. The study shows that a fuel savings of up to 20% can be achieved, but that increased fuel savings comes at the expense of payload capacity.

Gascon↗
NASA NTRSDate not supplied

Parallel Hybrid Turboprop Performance Modeling and Optimization

NASA’s Electrified Powertrain Flight Demonstration (EPFD) project conducts ground and flight tests of integrated Megawatt (MW) class hybrid-electric powertrain systems on regional turboprop aircraft demonstrators. To meet the increased demand for assessment of potential capabilities and benefits from these novel vehicle configurations, NASA is developing tooling and models to estimate the performance of hybridized regional turboprops. This paper covers the development of a parametrically driven performance model for a De Havilland Canada Dash 8-400 (Q400) regional turboprop integrated with a novel parallel hybrid architecture using the Gascon framework. Gascon is a modern reimplementation of the General Aviation Synthesis Program (GASP) built using the Condor mathematical modeling framework in Python. Within Gascon, a parametric representation of the parallel hybrid architecture was synthesized, which features the electric motor coupled to the power turbine. This capability allows for in-the-loop optimization of the parametric parallel hybrid architecture to characterize the mission capabilities and fuel savings of the design and determine optimal power scheduling strategies for efficient electric power management for a given mission. The study shows that a fuel savings of up to 20% can be achieved, but that increased fuel savings comes at the expense of payload capacity.

Gascon↗
NASA NTRS2012

Feasibility Study of Two Candidate Reaction Wheel/thruster Hybrid Control Architecture Designs for the Cassini Spacecraft

As the first spacecraft to achieve orbit at Saturn in 2004, Cassini has collected science data throughout its four-year prime mission (2004-08), and has since been approved for a first and second extended mission through 2017. Cassini carries a set of three "fixed" reaction wheels and a backup reaction wheel (reaction wheel #4) is mounted on top of an articulable platform. If necessary, this platform could be articulated to orient the backup reaction wheel with the degraded wheel. The reaction wheels are used primarily for attitude control when precise and stable pointing of a science instrument such as the narrow angle camera is required. In 2001-02, reaction wheel #3 exhibited signs of bearing cage instability. As a result, reaction wheel #4 was articulated to align with reaction wheel #3. Beginning in July 2003, Cassini was controlled using wheel #1, #2, and #4. From their first use in the spring of 2000 until today, reaction wheels #1 and #2 have accumulated more than3.5 billions revolutions each. As such, in spite of very carefully management of the wheel spin rates by the mission operation team, there are some observed increases in the drag torque of the wheels' bearings. Hence, the mission operations team must prepare for the contingency scenario in which the reaction wheel #1 (in addition to wheel #3) had degraded. In this hypothetical fault scenario, the two remaining reaction wheels (#2 and #4) will not be able to provide precise and stable three-axis control of the spacecraft. In this study, we evaluate the feasibility of controlling Cassini using the two remaining reaction wheels and four thrusters to meet the science pointing requirements for two key science operational modes: the Optical Remote Sensing and Downlink, Fields, Particles, & Waves operation modes. The performance (e.g., pointing control error, pointing stability, hydrazine consumption rate, etc.) of the hybrid controllers in both operations scenarios will be compared with those achieved using an all-thruster controller design. Strength and weaknesses of the hybrid control architecture are assessed quantitatively.

Cassini↗
DOE OSTI2024

Comparison of Real-Time Pressure Rail Selection Algorithms for the Hybrid Hydraulic Electric Architecture: Case Study on a Track Loader

Abstract The hybrid hydraulic electric architecture (HHEA) seeks to combine the high power/torque/force density of hydraulics with the efficiency of electric machines. A set of common pressure rails is used to provide a majority of the power and this power is modulated by small electric machines to provide precise control for the operator. The HHEA has been studied in previous work using off-line dynamic programming optimization to determine energy efficient pressure rail selections, but this approach requires drive cycle information apriori. A Lagrange multiplier method has also been investigated where a set of gains (Lagrange multipliers) are optimized off-line with the idea the these gains, once determined, could be used for real-time operation. In this work, three new real-time pressure rail selection algorithms that do not require future drive cycle information are investigated; greedy, torque minimizing, and thresholding. The greedy control is found to only use 1% more energy than the globally optimal dynamic programming solution; but a model of energy loss is required.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Interpretable Models for Workflow Differentiation in High-Performance Scientific Networks

Scientific workflows in high-performance networks spawn hundreds of interdependent flows that must be managed collectively—yet existing network classifiers treat each flow in isolation, leading to fragmented QoS decisions and missed interflow patterns. We present a novel traffic classification solution that operates at the workflow level, distinguishing entire filetransfer operations from streaming analytics by capturing how concurrent flows interact and burst together. We introduce a workflow identification window (WIW) that ingests raw packet headers from parallel flows into unified tensors, preserving the spatial-temporal patterns that differentiate scientific workflows. This approach achieves 98.7% accuracy using CNN, LSTM, and hybrid architectures, while maintaining 84% accuracy on production traffic collected a week later—demonstrating robustness to temporal drift. By integrating SHAP and GradCAM explainability, we reveal that early-packet timing patterns and cross-flow correlations drive classification decisions, providing operators with interpretable insights. Our system enables coherent workflow-level QoS enforcement and dynamic bandwidth allocation in scientific networks, eliminating manual per-flow configuration while maintaining classification latency at millisecond level.

Giannakou, Anna [LBL, Berkeley]↗