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Results for “State Machine”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Platoon management with cooperative adaptive cruise control enabled by VANET

Previous studies have shown the ability of vehicle platooning to improve highway safety and throughput. With Vehicular Ad-hoc Network (VANET) and Cooperative Adaptive Cruise Control (CACC) system, vehicle platooning with small headway becomes feasible. In this paper, we developed a platoon management protocol for CACC vehicles based on wireless communication through VANET. This protocol includes three basic platooning maneuvers and a set of micro-commands to accomplish these maneuvers. Various platooning operations such as vehicle entry and vehicle (including platoon leader) leaving can be captured by these basic platoon maneuvers. The protocol operation is described in detail using various Finite State Machines (FSM), and can be applied in collaborative driving and intelligent highway systems. This protocol is determined in an integrated simulation platform, VENTOS, which is developed based on SUMO and OMNET++. The validity and effectiveness of our approach is shown by means of simulations, and different platooning setting are calibrated.

42 ENGINEERING↗
DOE OSTI2023

A nanocryotron memory and logic family

The development of superconducting electronics based on nanocryotrons has been limited so far to few device circuits, in part due to the lack of standard and robust logic cells. Here, we introduce and experimentally demonstrate designs for a set of nanocryotron-based building blocks that can be configured and combined to implement memory and logic functions. The devices were fabricated by patterning a single superconducting layer of niobium nitride and measured in liquid helium on a wide range of operating points. The tests show 10 - 4 bit error rates with above ± 20 % margins up to 50 MHz and the possibility of operating under the effect of an out-of-plane 36 mT magnetic field, with ± 30 % margins at 10 MHz. Additionally, we designed and measured an equivalent delay-flip-flop made of two memory cells to show the possibility of combining multiple building blocks to make larger circuits. These blocks may constitute a solid foundation for the development of nanocryotron logic circuits and finite-state machines with potential applications in the integrated processing and control of superconducting nanowire single-photon detectors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems

Though robustness and resilience are commonly quoted as features of neuromorphic computing systems, the expected performance of neuromorphic systems in the face of hardware failures is not clear. In this work, we study the effect of failures on the performance of four different training algo-rithms for spiking neural networks on neuromorphic systems: two back-propagation-based training approaches (Whetstone and SLAYER), a liquid state machine or reservoir computing approach, and an evolutionary optimization-based approach (EONS). We show that these four different approaches have very different resilience characteristics with respect to simulated hardware failures. We then analyze an approach for training more resilient spiking neural networks using the evolutionary optimization approach. We show how this approach produces more resilient networks and discuss how it can be extended to other spiking neural network training approaches as well.

Schuman, Catherine↗
DOE OSTI2020

Microgrid Power Flow Control with Integrated Battery Management Functions

This paper presents a microgrid power flow control for islanded microgrids consisting of photovoltaic (PV) system, battery energy storage system (BESS) and diesel generator. The proposed control ensures automatic coordination among the microgrid units. To achieve the coordination, the local control of PV system and BESS are configured to regulate power flow without relying on communications. The generator is controlled as the back-up source and its connection depends on battery state of charge (SOC). A state machine with hysteresis settings is used to trigger smooth transition among operation modes. Not only does the proposed controller consider battery SOC and power limits, but also integrates three-stage charging control as battery charging mechanism, which is not considered in the existing literature. The proposed control is validated for an islanded hybrid microgrid using an OPAL-RT real-time simulator.

Long, Qian↗
DOE OSTI2021

Conceptual Design of High Field Central Solenoid for Fusion Nuclear Science Facility

Fusion Nuclear Science Facility (FNSF) is a critical fusion nuclear step in the US beyond ITER before proceeding to a larger and electricity producing fusion power plant. Although FNSF is a steady state machine to be operated at high duty cycle, a high field and high current density central solenoid magnet is needed for plasma startups. Due to space constraints in the FNSF in-board radial build, the magnetic field and coil current density required exceed conventional low temperature superconductor (LTS) performance limits and the design can only be achieved by high temperature superconductors (HTS). The design for the central solenoid, also called the ohmic heating (OH) magnet for FNSF shall meet the 100 Weber double flux swing requirement for plasma startups. Finally, the stresses at such a high field and high current density coil may require a bucked and wedged TF-OH design to accommodate space for coil winding support structures in in-board system radial build for high field FNSF operations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

High energy density picoliter-scale zinc-air microbatteries for colloidal robotics

The recent interest in microscopic autonomous systems, including microrobots, colloidal state machines, and smart dust, has created a need for microscale energy storage and harvesting. However, macroscopic materials for energy storage have noted incompatibilities with microfabrication techniques, creating substantial challenges to realizing microscale energy systems. Here, we photolithographically patterned a microscale zinc/platinum/SU-8 system to generate the highest energy density microbattery at the picoliter (10 −12 liter) scale. The device scavenges ambient or solution-dissolved oxygen for a zinc oxidation reaction, achieving an energy density ranging from 760 to 1070 watt-hours per liter at scales below 100 micrometers lateral and 2 micrometers thickness in size. The parallel nature of photolithography processes allows 10,000 devices per wafer to be released into solution as colloids with energy stored on board. Within a volume of only 2 picoliters each, these primary microbatteries can deliver open circuit voltages of 1.05 ± 0.12 volts, with total energies ranging from 5.5 ± 0.3 to 7.7 ± 1.0 microjoules and a maximum power near 2.7 nanowatts. We demonstrated that such systems can reliably power a micrometer-sized memristor circuit, providing access to nonvolatile memory. We also cycled power to drive the reversible bending of microscale bimorph actuators at 0.05 hertz for mechanical functions of colloidal robots. Additional capabilities, such as powering two distinct nanosensor types and a clock circuit, were also demonstrated. The high energy density, low volume, and simple configuration promise the mass fabrication and adoption of such picoliter zinc-air batteries for micrometer-scale, colloidal robotics with autonomous functions.

Robotics↗
DOE OSTI2020

Evolutionary Optimization for Neuromorphic Systems

Designing and training an appropriate spiking neural network for neuromorphic deployment remains an open challenge in neuromorphic computing. In 2016, we introduced an approach for utilizing evolutionary optimization to address this challenge called Evolutionary Optimization for Neuromorphic Systems (EONS). In this work, we present an improvement to this approach that enables rapid prototyping of new applications of spiking neural networks in neuromorphic systems. We discuss the overall EONS framework and its improvements over the previous implementation. We present several case studies of how EONS can be used, including to train spiking neural networks for classification and control tasks, to train under hardware constraints, to evolve a reservoir for a liquid state machine, and to evolve smaller networks using multi-objective optimization.

Schuman, Catherine↗
DOE OSTI2018

DBSchema_DMS

PRISM Data Management System database schema. This is a collection of DDL files that define the database schema used by the Data Management System (DMS) component of the Pan-Omics Research Information Storage and Management system (PRISM) at the Pacific Northwest National Laboratory (PNNL). PRISM incorporates a diverse set of analysis tools and allows a wide range of operations to be incorporated, leveraing a state machine that is accessible to independent, distributed computational nodes. The system has scaled well as data volume has increased since 2002, while allowing adaptability for incorporating new and improved data analysis tools for more effective proteomics research.

Monroe, Matthew↗
DOE OSTI2021

Q Framework

The Q Formal Analysis Framework is a set of software tools used to formally prove that implementations of high-consequence digital systems meet mathematical specifications. The tools are designed to work together as a set. Specifications are derived directly from high-level requirements and expressed in the QSpec hierarchical state machine format. The toolkit includes QSpec, QRefact, and QReqs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-0504 O

Hulette, GeoffreyC.↗
DOE OSTI2021

Sequential Training ToolKit - STTK

Sequential Training ToolKit, or STTK, is a software toolkit plugin for the Unity development platform that enables software developers to easily develop structured Sequential Training applications for gaming and extended reality (XR) environments. STTK is architected to easily import the toolkit as a plugin for the Unity platform and then interact with the graphical user interface (GUI) for drag-and-drop functionality. STTK also includes easy add-on plugins for Prefabs and auto-builds a State Machine. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3059 O

Klein, BrandonThorin↗
DOE OSTI2022

GABLE contract source code

Garbled Autonomous Bots Leveraging Ethereum (GABLE) uses simple but effective algorithms to permit secure private execution of garbled state machines and garbled circuits on public computing resources. This release consists of two Solidity smart contracts illustrating the GABLE approach. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2022-7215 O

Pattengale, Nicholas↗
DOE OSTI2024

spot_bt_ros v.0.1.0

SAND2024-08478O The spot_bt_ros tool allows users to easily construct complex autonomous behaviors for Boston Dynamic's Spot robot without having to overly rely on the Spot software development kit (SDK). This package specifically allows a user to run the Robot Operating System 2 alongside the SDK. Using a form-of-state machine called a "behavior tree,” the software develops different "leaves" or actions that the robot undergoes. Attaching multiple actions in sequence creates a "branch" and several of these make up the "tree." Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Kakish, Zahi↗
DOE OSTI2024

spot_bt v.0.1.1

SAND2024-08430O spot_bt allows users to easily construct complex, autonomous behaviors without having to overly rely on Boston Dynamic’s Spot robot software development kit. Using a form-of-state machine called a "behavior tree," the software develops and applies different "leaves" or actions to the robot. Attaching multiple actions in sequence creates a "branch," and a series of these make up the "tree." The software works on any x86 or aarch64 hardware but must run on a Linux OS. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525

Kakish, Zahi↗
DOE OSTI2011

Keeping checkpoint/restart viable for exascale systems.

Next-generation exascale systems, those capable of performing a quintillion (10{sup 18}) operations per second, are expected to be delivered in the next 8-10 years. These systems, which will be 1,000 times faster than current systems, will be of unprecedented scale. As these systems continue to grow in size, faults will become increasingly common, even over the course of small calculations. Therefore, issues such as fault tolerance and reliability will limit application scalability. Current techniques to ensure progress across faults like checkpoint/restart, the dominant fault tolerance mechanism for the last 25 years, are increasingly problematic at the scales of future systems due to their excessive overheads. In this work, we evaluate a number of techniques to decrease the overhead of checkpoint/restart and keep this method viable for future exascale systems. More specifically, this work evaluates state-machine replication to dramatically increase the checkpoint interval (the time between successive checkpoint) and hash-based, probabilistic incremental checkpointing using graphics processing units to decrease the checkpoint commit time (the time to save one checkpoint). Using a combination of empirical analysis, modeling, and simulation, we study the costs and benefits of these approaches on a wide range of parameters. These results, which cover of number of high-performance computing capability workloads, different failure distributions, hardware mean time to failures, and I/O bandwidths, show the potential benefits of these techniques for meeting the reliability demands of future exascale platforms.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Using Discrete Event Simulation for Programming Model Exploration at Extreme-Scale: Macroscale Components for the Structural Simulation Toolkit (SST).

Discrete event simulation provides a powerful mechanism for designing and testing new extreme- scale programming models for high-performance computing. Rather than debug, run, and wait for results on an actual system, design can first iterate through a simulator. This is particularly useful when test beds cannot be used, i.e. to explore hardware or scales that do not yet exist or are inaccessible. Here we detail the macroscale components of the structural simulation toolkit (SST). Instead of depending on trace replay or state machines, the simulator is architected to execute real code on real software stacks. Our particular user-space threading framework allows massive scales to be simulated even on small clusters. The link between the discrete event core and the threading framework allows interesting performance metrics like call graphs to be collected from a simulated run. Performance analysis via simulation can thus become an important phase in extreme-scale programming model and runtime system design via the SST macroscale components.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Dependency graph for code analysis on emerging architectures

Direct acyclic dependency (DAG) graph is becoming the standard for modern multi-physics codes.The ideal DAG is the true block-scheme of a multi-physics code. Therefore, it is the convenient object for insitu analysis of the cost of computations and algorithmic bottlenecks related to statistical frequent data motion and dymanical machine state.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

FY17 ISCR Scholar End-of-Assignment Report - Robbie Sadre

Throughout this internship assignment, I did various tasks that contributed towards the starting of the SASEDS (Safe Active Scanning for Energy Delivery Systems) and CES-21 (California Energy Systems for the 21st Century) projects in the SKYFALL laboratory. The goal of the SKYFALL laboratory is to perform modeling and simulation verification of transmission power system devices, while integrating with high-performance computing. The first thing I needed to do was acquire official Online LabVIEW training from National Instruments. Through these online tutorial modules, I learned the basics of LabVIEW, gaining experience in connecting to NI devices through the DAQmx API as well as LabVIEW basic programming techniques (structures, loops, state machines, front panel GUI design etc).

24 POWER TRANSMISSION AND DISTRIBUTION↗