Results for “Routing algorithm” — Page 15

DOE OSTI2022

Creating ground truth for nanocrystal morphology: a fully automated pipeline for unbiased transmission electron microscopy analysis

Control over colloidal nanocrystal morphology (size, size distribution, and shape) is important for tailoring the functionality of individual nanocrystals and their ensemble behavior. Despite this, traditional methods to quantify nanocrystal morphology are laborious. New developments in automated morphology classification will accelerate these analyses but the assessment of machine learning models is limited by human accuracy for ground truth, causing even unsupervised machine learning models to have inherent bias. Herein, we introduce synthetic image rendering to solve the ground truth problem of nanocrystal morphology classification. By simulating 2D images of nanocrystal shapes via a function of high-dimensional parameter space, we trained a convolutional neural network to link unique morphologies to their simulated parameters, defining nanocrystal morphology quantitatively rather than qualitatively. An automated pipeline then processes, quantitatively defines, and classifies nanocrystal morphology from experimental transmission electron microscopy (TEM) images. Using improved computer vision techniques, 42,650 nanocrystals were identified, assessed, and labeled with quantitative parameters, offering a 600-fold improvement in efficiency over best-practice manual measurements. Further, a classification algorithm was trained with a prediction accuracy of 99.5%, which can successfully analyze a range of concave, convex, and irregular nanocrystal shapes. The resulting pipeline was applied to differentiating two syntheses of nominally cuboidal CsPbBr 3 nanocrystals and uniquely classifying binary nickel sulfide nanocrystal phase based on morphology. This pipeline provides a simple, efficient, and unbiased method to quantify nanocrystal morphology and represents a practical route to construct large datasets with an absolute ground truth for training unbiased morphology-based machine learning algorithms.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2020

A Minimum Principle-Based Algorithm for Energy-Efficient Eco-Driving of Electric Vehicles in Various Traffic and Road Conditions

Our report presents an optimization algorithm for energy-efficient driving of electric vehicles. The algorithm is based on Pontryagin’s Minimum Principle by considering the driving mission as an optimal control problem. On a planned route, diverse application cases may occur due to various physical traits such as powertrain (e.g., switching between motor and generator operation), environmental variations (e.g., terrain grade change), traffic laws (e.g., speed limits), and safety concerns (e.g., headway to the leading vehicle). The proposed algorithm handles these real-world challenges by considering the perturbation to the system dynamics and the constraints to the control and state variables.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2015

First results of the silicon telescope using an 'artificial retina' for fast track finding

We present the first results of the prototype of a silicon tracker with trigger capabilities based on a novel approach for fast track finding. The working principle of the 'artificial retina' is inspired by the processing of visual images by the brain and it is based on extensive parallelization of data distribution and pattern recognition. The algorithm has been implemented in commercial FPGAs in three main logic modules: a switch for the routing of the detector hits, a pool of engines for the digital processing of the hits, and a block for the calculation of the track parameters. The architecture is fully pipelined and allows the reconstruction of real-time tracks with a latency less then 100 clock cycles, corresponding to 0.25 microsecond at 400 MHz clock. The silicon telescope consists of 8 layers of single-sided silicon strip detectors with 512 strips each. The detector size is about 10 cm x 10 cm and the strip pitch is 183 μm. The detectors are read out by the Beetle chip, a custom ASICs developed for LHCb, which provides the measurement of the hit position and pulse height of 128 channels. The 'artificial retina' algorithm has been implemented on custom data acquisition boards based on FPGAs Xilinx Kintex 7 lx160. The parameters of the tracks detected are finally transferred to host PC via USB 3.0. The boards manage the read-out ASICs and the sampling of the analog channels. The read-out is performed at 40 MHz on 4 channels for each ASIC that corresponds to a decoding of the telescope information at 1.1 MHz. We report on the first results of the fast tracking device and compare with simulations. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Fuel Efficient Speed Optimization for Real-World Highway Cruising

This paper introduces an eco-driving highway cruising algorithm based on optimal control theory that is applied to a conventionally-powered connected and automated vehicle. Thanks to connectivity to the cloud and/or to infrastructure, speed limit and slope along the future route can be known with accuracy. This can in turn be used to compute the control variable trajectory that will minimize energy consumption without significantly impacting travel time. Automated driving is necessary to the implementation of this concept, because the chosen control variables (e.g., torque and gear) impact vehicle speed. An optimal control problem is built up where quadratic models are used for the powertrain. The optimization is solved by applying Pontryagin’s minimum principle, which reduces the problem to the minimization of a cost function with parameters called co-states. The proposed algorithm assumes piecewise constant slopes and speed limits, and it solves the transition vehicle speeds for each junction of such segments. In addition, a method to extract route information from digital maps is presented, which complies with the proposed optimization algorithm. The algorithms are evaluated in simulation, using Autonomie, a simulation tool for vehicle energy consumption modeling. The optimal control trajectory (e.g., torque, gear) is first computed offline. It is then applied in an open-loop fashion in online simulation, using a forward-looking model of the vehicle in Autonomie. Simulation results show over 8% fuel saving for two selected real-world routes.

Simulation and modeling, Optimization, Vehicle net↗

DOE OSTI2020

Joint optimal scheduling for electric vehicle battery swapping-charging system based on wind farms

Insufficiencies in charging facilities limit the broad application of electric vehicles (EVs). In addition, EV can hardly represent a green option if its electricity primarily depends on fossil energy. Considering these two problems, this paper studies a battery swapping-charging system based on wind farms (hereinafter referred to as W-BSCS). In a W-BSCS, the wind farms not only supply electricity to the power grid but also cooperate with a centralized charge station (CCS), which can centrally charge EV batteries and then distribute them to multiple battery swapping stations (BSSs). The operational framework of the W-BSCS is analyzed, and some preprocessing technologies are developed to reduce complexity in modeling. Then, a joint optimal scheduling model involving a wind power generation plan, battery swapping demand, battery charging and discharging, and a vehicle routing problem (VRP) is established. Then a heuristic method based on the exhaustive search and the Genetic Algorithm is employed to solve the formulated NP-hard problem. Numerical results verify the effectiveness of the joint optimal scheduling model, and they also show that the W-BSCS has great potential to promote EVs and wind power.

17 WIND ENERGY↗

DOE OSTI2018

Transmission Route Engineering Analysis And Design

INL’s Transmission Route Engineering Analysis and Design [tool] (TREAD) is a tool meant for the design and routing of new transmission lines. TREAD is capable of taking an arbitrarily large amount of surface layers represented as geographical files and then using a modified version of Dijkstra’s Algorithm for finding the best path. TREAD is also capable of interacting with different weather models in order to gather weather data about the locations that are being routed to. This weather data is then used in conjunction with INL’s General Line Ampacity State Solver.

Lehmer, JacobP.↗

NASA NTRS2021

Separation at Crossing Waypoints Under Wind Uncertainty in Urban Air Mobility

To enable high-density operations in major metropolitan areas, urban air mobility networks are anticipated to have air traffic management with higher levels of autonomy. To ensure that this type of autonomy is feasible, one of the critical steps from a safety and efficiency perspective is understanding various factors that affect the spatial separation between airborne flights and ensure that these factors can be managed. In terms of separation assurance and scheduling, an important real-world concern is that future states of aircraft cannot be perfectly predicted. The focus of this research paper is to understand how these prediction errors affect separation and scheduling services and to explore mitigation strategies to handle these errors. In this research, we have simulated these types of uncertainty by adding wind-prediction errors to trajectory predictions for separation. With these wind-prediction errors, we decompose the problem into two separate questions. First, using both simulation and analytical methods, we look at conflict-detection-only scenarios to understand how the wind errors affect required minimum temporal separation between crossing flights to ensure a specific spatial separation. Next, we study how trajectory errors effect conflict resolution, and we explore different combinations of scheduling and separation assurance to mitigate the effects of uncertainty between crossing flights. The conflict resolution algorithm aims to minimize necessary temporal separation between crossing flights under uncertainty, still ensuring safety-critical spatial separation. In summary, this research suggests that the required minimum temporal separation at a crossing waypoint is dependent on factors such as inbound crossing angle, the relative angle between wind direction and bearing of each route, wind magnitude, wind magnitude uncertainty, nominal cruise airspeed of aircraft, and look-ahead time of the conflict detection algorithm. This research also suggests that different combinations of scheduling and separation have different qualitative results. Using a combination of strategic, flow-based scheduling, tactical scheduling at crossings, speed control near crossing points, and separation management leads to a system that is insensitive to trajectory prediction errors with high throughput and flexibility for aircraft away from shared resources.

urban air mobility↗

NASA NTRS2021

Separation at Crossing Waypoints Under Wind Uncertainty in Urban Air Mobility

To enable high-density operations in major metropolitan areas, urban air mobility networks are anticipated to have air traffic management with higher levels of autonomy. To ensure that this type of autonomy is feasible, one of the critical steps from a safety and efficiency perspective is understanding various factors that affect the spatial separation between airborne flights and ensure that these factors can be managed. In terms of separation assurance and scheduling, an important real-world concern is that future states of aircraft cannot be perfectly predicted. The focus of this research paper is to understand how these prediction errors affect separation and scheduling services and to explore mitigation strategies to handle these errors. In this research, we have simulated these types of uncertainty by adding wind-prediction errors to trajectory predictions for separation. With these wind-prediction errors, we decompose the problem into two separate questions. First, using both simulation and analytical methods, we look at conflict-detection-only scenarios to understand how the wind errors affect required minimum temporal separation between crossing flights to ensure a specific spatial separation. Next, we study how trajectory errors effect conflict resolution, and we explore different combinations of scheduling and separation assurance to mitigate the effects of uncertainty between crossing flights. The conflict resolution algorithm aims to minimize necessary temporal separation between crossing flights under uncertainty, still ensuring safety-critical spatial separation. In summary, this research suggests that the required minimum temporal separation at a crossing waypoint is dependent on factors such as inbound crossing angle, the relative angle between wind direction and bearing of each route, wind magnitude, wind magnitude uncertainty, nominal cruise airspeed of aircraft, and look-ahead time of the conflict detection algorithm. This research also suggests that different combinations of scheduling and separation have different qualitative results. Using a combination of strategic, flow-based scheduling, tactical scheduling at crossings, speed control near crossing points, and separation management leads to a system that is insensitive to trajectory prediction errors with high throughput and flexibility for aircraft away from shared resources.

urban air mobility↗

NASA NTRS2013

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Fourth Revision

This paper presents an overview of the fourth major revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This airborne self-spacing concept is trajectory-based, allowing for spacing operations prior to the aircraft being on a common path. Because this algorithm is trajectory-based, it also has the inherent ability to support required-time-of-arrival (RTA) operations. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. Revisions to this algorithm were based on a change to the expected operational environment.

Abbott, Terence S.↗

NASA NTRS2013

Enhanced Contact Graph Routing (ECGR) MACHETE Simulation Model

Contact Graph Routing (CGR) for Delay/Disruption Tolerant Networking (DTN) space-based networks makes use of the predictable nature of node contacts to make real-time routing decisions given unpredictable traffic patterns. The contact graph will have been disseminated to all nodes before the start of route computation. CGR was designed for space-based networking environments where future contact plans are known or are independently computable (e.g., using known orbital dynamics). For each data item (known as a bundle in DTN), a node independently performs route selection by examining possible paths to the destination. Route computation could conceivably run thousands of times a second, so computational load is important. This work refers to the simulation software model of Enhanced Contact Graph Routing (ECGR) for DTN Bundle Protocol in JPL's MACHETE simulation tool. The simulation model was used for performance analysis of CGR and led to several performance enhancements. The simulation model was used to demonstrate the improvements of ECGR over CGR as well as other routing methods in space network scenarios. ECGR moved to using earliest arrival time because it is a global monotonically increasing metric that guarantees the safety properties needed for the solution's correctness since route re-computation occurs at each node to accommodate unpredicted changes (e.g., traffic pattern, link quality). Furthermore, using earliest arrival time enabled the use of the standard Dijkstra algorithm for path selection. The Dijkstra algorithm for path selection has a well-known inexpensive computational cost. These enhancements have been integrated into the open source CGR implementation. The ECGR model is also useful for route metric experimentation and comparisons with other DTN routing protocols particularly when combined with MACHETE's space networking models and Delay Tolerant Link State Routing (DTLSR) model.

Segui, John S.↗

NASA NTRS2013

Contact Graph Routing Enhancements Developed in ION for DTN

The Interplanetary Overlay Network (ION) software suite is an open-source, flight-ready implementation of networking protocols including the Delay/Disruption Tolerant Networking (DTN) Bundle Protocol (BP), the CCSDS (Consultative Committee for Space Data Systems) File Delivery Protocol (CFDP), and many others including the Contact Graph Routing (CGR) DTN routing system. While DTN offers the capability to tolerate disruption and long signal propagation delays in transmission, without an appropriate routing protocol, no data can be delivered. CGR was built for space exploration networks with scheduled communication opportunities (typically based on trajectories and orbits), represented as a contact graph. Since CGR uses knowledge of future connectivity, the contact graph can grow rather large, and so efficient processing is desired. These enhancements allow CGR to scale to predicted NASA space network complexities and beyond. This software improves upon CGR by adopting an earliest-arrival-time cost metric and using the Dijkstra path selection algorithm. Moving to Dijkstra path selection also enables construction of an earliest- arrival-time tree for multicast routing. The enhancements have been rolled into ION 3.0 available on sourceforge.net.

Segui, John S.↗

DOE OSTI2012

A New Global River Network Database for Macroscale Hydrologic modeling

Coarse resolution (upscaled) river networks are critical inputs for runoff routing in macroscale hydrologic models. Recently, Wu et al. (2011) developed a hierarchical Dominant River Tracing (DRT) algorithm for automated extraction and spatial upscaling of basin flow directions and river networks using fine-scale hydrography inputs (e.g., flow direction, river networks, and flow accumulation). The DRT was initially applied using HYDRO1K baseline fine-scale hydrography inputs and the resulting upscaled global hydrography maps were produced at several spatial scales, and verified against other available regional and global datasets. New baseline fine-scale hydrography data from HydroSHEDS are now available for many regions and provide superior scale and quality relative to HYDRO1K. However, HydroSHEDS does not cover regions above 60°N. In this study, we applied the DRT algorithms using combined HydroSHEDS and HYDRO1K global fine-scale hydrography inputs, and produced a new series of upscaled global river network data at multiple (1/16° to 2°) spatial resolutions in a consistent (WGS84) projection. The new upscaled river networks are internally consistent and congruent with the baseline fine-scale inputs. The DRT results preserve baseline fine-scale river networks independent of spatial scales, with consistency in river network, basin shape, basin area, river length, and basin internal drainage structure between upscaled and baseline fine-scale hydrography. These digital data are available online for public access (ftp://ftp.ntsg.umt.edu/pub/data/DRT/) and should facilitate improved regional to global scale hydrological simulations, including runoff routing and river discharge calculations.

macroscale hydrological modeling↗

DOE OSTI2015

On Modeling and Analysis of MIMO Wireless Mesh Networks with Triangular Overlay Topology

Multiple input multiple output (MIMO) wireless mesh networks (WMNs) aim to provide the last-mile broadband wireless access to the Internet. Along with the algorithmic development for WMNs, some fundamental mathematical problems also emerge in various aspects such as routing, scheduling, and channel assignment, all of which require an effective mathematical model and rigorous analysis of network properties. In this paper, we propose to employ Cartesian product of graphs (CPG) as a multichannel modeling approach and explore a set of unique properties of triangular WMNs. In each layer of CPG with a single channel, we design a node coordinate scheme that retains the symmetric property of triangular meshes and develop a function for the assignment of node identity numbers based on their coordinates. We also derive a necessary-sufficient condition for interference-free links and combinatorial formulas to determine the number of the shortest paths for channel realization in triangular WMNs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Framework for Network Co-Simulation

The Framework for Network Co-Simulation (FNCS) uses a federated approach to integrate simulations which may have differing time scales. Special consideration is given to integration with a communication network simulation such that inter-simulation messages may be optionally routed through and delayed by such a simulation. In addition, FNCS uses novel time synchronization algorithms to accelerate co-simulation including the application of speculative multithreading. FNCS accomplishes all of these improvements with minimal end user intervention. Simulations can be integrated using FNCS while maintaining their original model input files simply by linking with the FNCS library and making appropriate calls into the FNCS API.

Daily, Jeff↗

DOE OSTI2017

The Trip Itinerary Optimization Platform: A Framework for Personalized Travel Information

The New Concepts Incubator team at the National Renewable Energy Laboratory (NREL) developed a three-stage online platform for travel diary collection, personal travel plan optimization and travel itinerary visualization. In the first stage, users provide a travel diary for the previous day through an interactive map and calendar interface and survey for travel attitudes and behaviors. One or more days later, users are invited via email to engage in a second stage where they view a personal mobility dashboard displaying recommended travel itineraries generated from a novel framework that optimizes travel outcomes over a sequence of interrelated trips. A week or more after viewing these recommended travel itineraries on the dashboard, users are emailed again to engage in a third stage where they complete a final survey about travel attitudes and behaviors. A usability study of the platform conducted online showed that, in general, users found the system valuable for informing their travel decisions. A total of 274 individuals were recruited through Amazon Mechanical Turk, an online survey platform, to participate in a transportation study using this platform. On average, the platform distilled 65 feasible travel plans per individual into two recommended itineraries, each optimal according to one or more outcomes and dependent on the fixed times and locations from the travel diary. For 45 percent of users, the trip recommendation algorithm returned only a single, typically automobile-centric, itinerary because there were no other viable alternative transportation modes available. Platform users generally agreed that the dashboard was enjoyable and easy to use, and that it would be a helpful tool in adopting new travel behaviors. Users generally agreed most that the time, cost and user preferred recommendations 'made sense' to them, and were most willing to implement these itineraries. Platform users typically expressed low willingness to try the carbon and calories optimized itineraries. Of the platform users who viewed the dashboard, 13 percent reported changing their travel behavior, most adopting the time, calories or carbon optimized itineraries. While the algorithm incorporates a wealth of travel data obtained from online APIs pertaining to a travelers route such as historic traffic condition data, public transit time-tables, and bike path routes, open-ended responses from users expressed an interest in the integration of even more fine-grained traffic data and the ability to dynamically model the effect of changes in travel times. Users also commonly expressed concerns over the safety of walking and biking recommendations. Responses indicate that more information about the amenities available to cyclists and pedestrians (sidewalks, shade from trees, access to food) and routes that avoid areas of perceived elevated danger would reduce barriers to implementing these recommendations. More accurate representations of personal vehicle trips (based on vehicle make and model, implications of parking) and the identification of routes that optimize caloric intensity (seeking out elevation changes or longer walks to public transit) are promising avenues for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1983

Communications network design and costing model programmers manual

Otpimization algorithms and techniques used in the communications network design and costing model for least cost route and least cost network problems are examined from the programmer's point of view. All system program modules, the data structures within the model, and the files which make up the data base are described.

Logan, K. P.↗

NASA NTRS2012

Advisory Systems Save Time, Fuel for Airlines

Heinz Erzberger never thought the sky was falling, but he knew it could benefit from enhanced traffic control. Throughout the 1990s, Erzberger led a team at Ames Research Center to develop a suite of automated tools to reduce restrictions and improve the efficiency of air traffic control operations. Called CTAS, or Center-TRACON (Terminal Radar Approach Control) Automation System, the software won NASA s Software of the Year award in 1998, and one of the tools in the suite - the traffic management advisor - was adopted by the Federal Aviation Administration and implemented at traffic control centers across the United States. Another one of the tools, Direct-To, has followed a different path. The idea behind Direct-To, explains Erzberger, a senior scientist at Ames, was that airlines could save fuel and money by shortening the routes they flew between take-off and landing. Aircraft are often limited to following established airways comprised of inefficient route segments. The routes are not easily adjusted because neither the pilot nor the aircraft controller can anticipate the constantly changing air traffic situation. To make the routes more direct while in flight, Erzberger came up with an idea for a software algorithm that could automatically examine air traffic in real-time, check to see if a shortcut was available, and then check for conflicts. If there were no conflicts and the shortcut saved more than 1 minute of flight time, the controller could be notified. "I was trying to figure out what goes on in the pilot and controller s minds when they decide to guide the aircraft in a certain way. That resulted in a different kind analysis," Erzberger says. As the engineer s idea went from theory to practice, in 2001, NASA demonstrated Direct-To in the airspace of Dallas-Ft. Worth. Estimations based on the demonstration found the technology was capable of saving 900 flying minutes per day for the aircraft in the test area.

Source record↗

DOE OSTI2014

Framework for Network Co-Simulation

The Framework for Network Co-Simulation (FNCS) uses a federated approach to integrate simulations which may have differing time scales. Special consideration is given to integration with a communication network simulation such that inter-simulation messages may be optionally routed through and delayed by such a simulation. In addition, FNCS uses novel time synchronization algorithms to accelerate co-simulation including the application of speculative multithreading. FNCS accomplishes all of these improvements with minimal end user intervention. Simulations can be integrated using FNCS while maintaining their original model input files simply by linking with the FNCS library and making appropriate calls into the FNCS API.

Daily, Jeff↗