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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

I/O Router Placement and Fine-Grained Routing on Titan to Support Spider II

The Oak Ridge Leadership Computing Facility (OLCF) introduced the concept of Fine-Grained Routing in 2008 to improve I/O performance between the Jaguar supercomputer and Spider, OLCF s center-wide Lustre file system. Fine-grained routing organizes I/O paths to minimize congestion. Jaguar has since been upgraded to Titan, providing more than a ten-fold improvement in peak performance. To support the center s increased computational capacity and I/O demand, the Spider file system has been replaced with Spider II. Building on the lessons learned from Spider, an improved method for placing LNET routers was developed and implemented for Spider II. The fine-grained routing scripts and configuration have been updated to provide additional optimizations and better match the system setup. This paper presents a brief history of fine-grained routing at OLCF, an introduction to the architectures of Titan and Spider II, methods for placing routers in Titan, and details about the fine-grained routing configuration.

Ezell, Matthew A↗
DOE OSTI2015

The criticality incident detection system omission cases for the fuel routes at EDF energy power stations - 14280

Criticality safety cases have been produced to justify the omission of criticality alarms from the fuel routes of EDF Energy's UK power stations. This work has addressed the UK regulator's expectations that adequate criticality warning systems should be provided wherever fissile material is present, unless a safety case shows that no criticality excursion could give any individual a whole body dose exceeding the annual whole body dose limit of 20 mSv, or that the predicted frequency of such excursions is acceptably low. In the UK, EDF Energy operates eight nuclear power stations; one Pressurized Water Reactor (PWR) and seven Advanced Gas-cooled Reactor stations (AGRs). At these stations, the term 'fuel route' is used to encompass all of the ex-reactor arrangements for the handling and storage of both new fuel and discharged irradiated fuel. These fuel routes were all designed in the 1980's (or earlier), using sound deterministic criticality safety principles, from which it was concluded that criticality alarms were not required in any of these areas. Subsequent changes to UK regulations have resulted in the need for the stations' criticality safety cases to be updated to include formal justifications for the omission of criticality alarms from these fuel routes. The EDF Energy Criticality Incident Detection System (CIDS) omission cases have been produced using the principles originally developed for UKAEA in the early 1960's by Aspinall and Daniels. These principles continue to be regarded as a best-practice approach by UK industry. Modern UK regulations also incorporate the ALARP principle, which requires operators to minimize and balance all of the safety risks from power station operations, so that the risks to both the public and to workers are As Low As is Reasonably Practicable. This paper describes how the work undertaken used the so-called Aspinall and Daniels criteria in conjunction with the requirements of the ALARP principle. The fuel storage pond at the Sizewell B PWR was addressed by dose calculations to show that, from the shielding effects of the concrete structure and the pond water, the potential consequences of a criticality accident could not result in a radiation dose in excess of 20 mSv. All of the other fuel route areas were addressed on the basis that, even if all of the active engineered and administrative criticality controls were to fail, a criticality accident would still not be reasonably expected, i.e. the predicted frequencies of all such excursions are acceptably low. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Robust vehicle routing under uncertainty via branch-price-and-cut

Here, this paper contemplates how branch-price-and-cut solvers can be employed along with the robust optimization paradigm to address parametric uncertainty in the context of vehicle routing problems. In this setting, given postulated uncertainty sets for customer demands and vehicle travel times, one aims to identify a set of cost-effective routes for vehicles to traverse, such that the vehicle capacities and customer time window constraints are respected under any anticipated demand and travel time realization, respectively. To tackle such problems, we propose a novel approach that combines cutting-plane techniques with an advanced branch-price-and-cut algorithm. Specifically, we use deterministic pricing procedures to generate "partially robust" vehicle routes and then utilize robust versions of rounded capacity inequalities and infeasible path elimination constraints to guarantee complete robust feasibility of routing designs against demand and travel time uncertainty. In contrast to recent approaches that modify the pricing algorithm, our approach is both modular and versatile. It permits the use of advanced branch-price-and-cut technologies without significant modification, while it can admit a variety of uncertainty sets that are commonly used in robust optimization but could not be previously employed in a branch-price-and-cut setting.

42 ENGINEERING↗
DOE OSTI2016

Using geographic information science to evaluate legal restrictions on freight transportation routing in disruptive scenarios

Disasters have consequences and freight transportation is not immune from the effects of such disruptions. In the aftermath of disasters, planners and policymakers have to utilize scarce resources and work within legal frameworks to provide recovery for affected citizens and business. As seen with Hurricane Sandy, various observers noted the challenge with freight rerouting due to inoperable infrastructure and legal barriers involved with intermodal freight transportation. This paper focuses on how Geographic Information Systems (GIS); specifically WebTRAGIS (Transportation Routing Analysis GIS), a transportation routing platform developed at Oak Ridge National Laboratory, can be used to evaluate different routing options for freight transportation. In the case of freight transportation, the Merchant Marine Act of 1920 (also known as the Jones Act) restricts Short Sea Shipping (SSS) between coastwise points within U.S. territorial waters. This restriction leads to reliance on land-side modes for handling increased freight resulting from cargo diversion. Using Hurricane Sandy and the closure of the Port of New York/New Jersey as a case study, different modal studies were conducted; ultimately highlighting the various routes and provides insight into potential review of modal restrictions such as the Jones Act.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Trip Energy Estimation Methodology and Model Based on Real-World Driving Data for Green-Routing Applications

A data-informed model to predict energy use for a proposed vehicle trip has been developed in this paper. The methodology leverages roughly one million miles of real-world driving data to generate the estimation model. Driving is categorized at the sub-trip level by average speed, road gradient, and road network geometry, then aggregated by category. An average energy consumption rate is determined for each category, creating an energy rate look-up table. Proposed vehicle trips are then categorized in the same manner, and estimated energy rates are appended from the look-up table. The methodology is robust and applicable to a wide range of driving data. The model has been trained on vehicle travel profiles from the Transportation Secure Data Center at the National Renewable Energy Laboratory and validated against on-road fuel consumption data from testing in Phoenix, Arizona. When compared against the detailed on-road conventional vehicle fuel consumption test data, the energy estimation model accurately predicted which route would consume less fuel over a dozen different tests. When compared against a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology should accurately select the route that consumes the least fuel 90% of the time. The model results can be used to inform control strategies in routing tools, such as change in departure time, alternate routing, and alternate destinations to reduce energy consumption. This work provides a highly extensible framework that allows the model to be tuned to a specific driver or vehicle type.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Development of The PaR Tool: Modernization of the Planning and Routing Scripts

The placement of an efficient route for power lines is a poorly understood. Owners of the land are often divided about whether to allow their land to have a pole placed. A planning and routing toolkit allows for the people to allow and deny access to land then instantly see the route recalculate. The original planning and routing scripts were the original proof of concept, there was a series of problems that greatly hindered the functionality of the system. The PaR Tool a fully featured application replaced the proof of concept scripts and the speed of the system was increased by 254%. It is readily extensible and far easier to use.

17 WIND ENERGY↗
DOE OSTI2025

Route Energy Prediction (RouteE) Powertrain Validation Report

The National Renewable Energy Laboratory's flagship package in the RouteE suite, RouteE-Powertrain, is a mesoscopic energy model that predicts vehicle energy consumption given discrete attributes that describe each segment or link in a vehicle's path on a road network. High-frequency, physics-based, powertrain simulators, such as NREL's FASTSim, are well-suited to model vehicle energy consumption when real driving data and a detailed understanding of the vehicle powertrain specifications are available. However, there are a variety of situations in the past, present (real-time), and future where high-frequency driving data and/or vehicle information may not be available, but reliable energy consumption is still desired, such as energy-aware vehicle routing. These are the ideal applications for RouteE-Powertrain. The suite of RouteE tools also includes RouteE-Compass, which is an eco-routing software that incorporates energy consumption into network routing algorithms, and RouteE-Mobile, which is a prototype smartphone navigation app to demonstrate the integrated capabilities of the RouteE suite for real-world eco-routing. The focus of this validation report is to share key metrics about the data sets and models behind RouteE-Powertrain. The set of RouteE-Powertrain models discussed in this report are made available through the RouteE web API through the NREL Developer Network.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2016

Risk-Hedged Approach for Re-Routing Air Traffic Under Weather Uncertainty

This presentation corresponds to: our paper explores a new risk-hedged approach for re-routing air traffic around forecast convective weather. In this work, flying through a more likely weather instantiation is considered to pose a higher level of risk. Current operational practice strategically plans re-routes to avoid only the most likely (highest risk) weather instantiation, and then tactically makes any necessary adjustments as the weather evolves. The risk-hedged approach strategically plans re-routes by minimizing the risk-adjusted path length, incorporating multiple possible weather instantiations with associated likelihoods (risks). The resulting model is transparent and is readily analyzed for realism and treated with well-understood shortest-path algorithms. Risk-hedged re-routes are computed for some example weather instantiations. The main result is that in some scenarios, relative to an operational-practice proxy solution, the risk-hedged solution provides the benefits of lower risk as well as shorter path length. In other scenarios, the benefits of the risk-hedged solution are ambiguous, because the solution is characterized by a tradeoff between risk and path length. The risk-hedged solution can be executed in those scenarios where it provides a clear benefit over current operational practice.

air traffic routing↗
NASA NTRSDate not supplied

Deep Reinforcement Learning based Routing in an Air-to-Air Ad-hoc Network

This paper studies the Multiple Sources and Multiple Destinations (MSMD) routing problem in a dynamic Air-to-Air Ad-hoc Network (AAAN). We consider a spectrum limited scenario where multiple links have to share the same frequency channel so that co-channel interference becomes inevitable. As a result, routing decisions and spectrum access are coupled and must be jointly considered. This paper proposes a deep Q-learning based algorithm to find an optimal routing and channel selection strategy that minimizes the end-to-end communication delay. Specifically, under the assumption that only local information is available to every node, the Deep Q-Network (DQN) is trained offline to learn the optimal routing and channel selection strategy. After the trained DQN is implemented in every node, multiple relay nodes can simultaneously determine their next-hop relay and channel selections in real-time. Simulation results demonstrate the efficacy of our proposed algorithm.

AAAN↗
NASA NTRSDate not supplied

Deep Reinforcement Learning based Routing in an Air-to-Air Ad-hoc Network

This paper studies the Multiple Sources and Multiple Destinations (MSMD) routing problem in a dynamic Air-to-Air Ad-hoc Network (AAAN). We consider a spectrum limited scenario where multiple links have to share the same frequency channel so that co-channel interference becomes inevitable. As a result, routing decisions and spectrum access are coupled and must be jointly considered. This paper proposes a deep Q-learning based algorithm to find an optimal routing and channel selection strategy that minimizes the end-to-end communication delay. Specifically, under the assumption that only local information is available to every node, the Deep Q-Network (DQN) is trained offline to learn the optimal routing and channel selection strategy. After the trained DQN is implemented in every node, multiple relay nodes can simultaneously determine their next-hop relay and channel selections in real-time. Simulation results demonstrate the efficacy of our proposed algorithm.

AAAN↗
DOE OSTI2025

Energy-Aware Route Planning with RouteE Compass

This poster introduces RouteE Compass, a new tool that advances sustainable transportation by enabling energy-aware route planning across diverse vehicle types and large-scale road networks. By addressing practical trade-offs between energy consumption, travel time, and economic cost, RouteE Compass fills critical gaps in traditional routing methods, which often lack the flexibility to prioritize energy directly. The tool's scalability and high-performance computing capabilities allow for national-scale analyses, offering actionable insights for fleet operators, transit agencies, and researchers. As an open-source, extensible platform, RouteE Compass empowers ongoing research and innovation in energy-aware routing, supporting the broader goals of reducing emissions and enhancing transportation sustainability.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗
DOE OSTI2016

Transport spatial model for the definition of green routes for city logistics centers

This paper presents a transport spatial decision support model (TSDSM) for carrying out the optimization of green routes for city logistics centers. The TSDSM model is based on the integration of the multi-criteria method of Weighted Linear Combination (WLC) and the modified Dijkstra algorithm within a geographic information system (GIS). The GIS is used for processing spatial data. The proposed model makes it possible to plan routes for green vehicles and maximize the positive effects on the environment, which can be seen in the reduction of harmful gas emissions and an increase in the air quality in highly populated areas. The scheduling of delivery vehicles is given as a problem of optimization in terms of the parameters of: the environment, health, use of space and logistics operating costs. Each of these input parameters was thoroughly examined and broken down in the GIS into criteria which further describe them. The model presented here takes into account the fact that logistics operators have a limited number of environmentally friendly (green) vehicles available. The TSDSM was tested on a network of roads with 127 links for the delivery of goods from the city logistics center to the user. The model supports any number of available environmentally friendly or environmentally unfriendly vehicles consistent with the size of the network and the transportation requirements. - Highlights: • Model for routing light delivery vehicles in urban areas. • Optimization of green routes for city logistics centers. • The proposed model maximizes the positive effects on the environment. • The model was tested on a real network.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A real-time energy and cost efficient vehicle route assignment neural recommender system

Here, this paper presents a neural network recommender system algorithm for assigning vehicles to routes based on energy and cost criteria. In this work, we applied this new approach to efficiently identify the most cost-effective medium and heavy duty truck (MDHDT) powertrain technology, from a total cost of ownership (TCO) perspective, for given trips. We employ a machine learning based approach to efficiently estimate the energy consumption of various candidate vehicles over given routes, defined as sequences of links (road segments), with little information known about internal dynamics, i.e. using high level macroscopic route information. A complete recommendation logic is then developed to allow for real-time optimum assignment for each route, subject to the operational constraints of the fleet. We show how this framework can be used to (1) efficiently provide a single trip recommendation with a top-k vehicles star ranking system, and (2) engage in more general assignment problems where n vehicles need to be deployed over m (m ≤ n) trips. This new assignment system has been deployed and integrated into the POLARIS. Transportation System Simulation Tool for use in research conducted by the Department of Energy's Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium (SMART, 2024).

Energy consumption↗
DOE OSTI2012

A new continuous two-step molecular precursor route to rare-earth oxysulfides Ln{sub 2}O{sub 2}S

A continuous two-step molecular precursor pathway is designed for the preparation of rare-earth oxysulfides Ln{sub 2}O{sub 2}S (Ln=Y, La, Pr, Nd, Sm-Lu). This new route involves a first oxidation step leading to the rare-earth oxysulfate Ln{sub 2}O{sub 2}SO{sub 4} which is subsequently reduced to the rare-earth oxysulfide Ln{sub 2}O{sub 2}S by switching to a H{sub 2}-Ar atmosphere. The whole process occurs at a temperature significantly lower than usual solid state synthesis (T{<=}650 Degree-Sign C) and avoids the use of dangerous sulfur-based gases, providing a convenient route to the synthesis of the entire series of Ln{sub 2}O{sub 2}S. The molecular precursors consist in heteroleptic dithiocarbamate complexes [Ln(Et{sub 2}dtc){sub 3}(phen)] and [Ln(Et{sub 2}dtc){sub 3}(bipy)] (Et{sub 2}dtc=N,N-diethyldithiocarbamate; phen=1,10-phenanthroline; bipy=2,2 Prime -bipyridine) and were synthesized by a new high yield and high purity synthesis route. The nature of the molecular precursor determines the minimum synthesis temperature and influences therefore the purity of the final Ln{sub 2}O{sub 2}S crystalline phase. - Graphical abstract: A continuous two-step molecular precursor pathway was designed for the preparation of rare-earth oxysulfides Ln{sub 2}O{sub 2}S (Ln=Y, La, Pr, Nd, Sm-Lu), starting from heteroleptic dithiocarbamate complexes. The influence of the nature of the molecular precursor on the minimum synthesis temperature and on the purity of the final Ln{sub 2}O{sub 2}S crystalline phase is discussed. Highlights: Black-Right-Pointing-Pointer A new high yield and high purity synthesis route of rare earth dithiocarbamates is described. Black-Right-Pointing-Pointer These compounds are used as precursors in a continuous process leading to rare-earth oxysulfides. Black-Right-Pointing-Pointer The oxysulfides are obtained under much more moderate conditions than previously described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

A one-pot, solid-state route for realizing highly visible light active Na-doped gC{sub 3}N{sub 4} photocatalysts

The visible light photocatalytic activity of graphitic carbon nitride (gC{sub 3}N{sub 4}), a promising metal-free photocatalytic material, is rather low, and is not as good as expected. Herein, to realize improved photocatalytic activity, sodium-doped gC{sub 3}N{sub 4} (Na-gC{sub 3}N{sub 4}) is prepared through a novel solid-state process based on the thermal polycondensation of urea in the presence of sodium chloride and ammonium chloride. The proposed solid-state process is simple, requires no solvent, and provides a general route for rapid and large-scale synthesis of metal-doped gC{sub 3}N{sub 4}. The Na species exist in + 1 oxidation state and bind N atoms in the nitride ring of gC{sub 3}N{sub 4}. The photocatalytic activity improvement of gC{sub 3}N{sub 4} for the mineralization of 17α-ethynylestradiol (EE2) under visible light is seen after the Na doping. The improved photocatalytic activity is due to increased absorption of light, increased separation of charge carriers, stronger oxidation ability of valance band holes, and increased specific surface area. The typical photocatalytic activity of 0.6 wt% Na-gC{sub 3}N{sub 4} for the EE2 mineralization with an initial EE2 concentration of 1 mg/L and a catalyst concentration of 1 g/L is 95.7% within 2 h of visible light irradiation. Under identical experimental conditions, the EE2 mineralization by pristine gC{sub 3}N{sub 4} is only 23.5%. - Graphical abstract: Highly visible light active Na-gC{sub 3}N{sub 4} photocatalysts were simply synthesized through a novel one-pot route based on the thermal polycondensation of urea. The doped Na species plays a critical role in improving the photocatalytic activity. Display Omitted - Highlights: • A new solid-state route is introduced to obtain visible light active Na-doped gC{sub 3}N{sub 4}. • The proposed synthesis route is fast, simple, and highly scalable. • Na doping leads to improved light absorption capability. • Na doping leads to improved separation of charge carriers. • Na doping leads to improved photocatalytic activity under visible light.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Evolution of microstructure, texture and inhibitor along the processing route for grain-oriented electrical steels using strip casting

In the present work, a regular grade GO sheet was produced successively by strip casting, hot rolling, normalizing annealing, two-stage cold rolling with intermediate annealing, primary recrystallization annealing, secondary recrystallization annealing and purification. The aim of this paper was to characterize the evolution of microstructure, texture and inhibitor along the new processing route by comprehensive utilization of optical microscopy, X-ray diffraction and transmission electron microscopy. It was found that a fine microstructure with the ferrite grain size range of 7–12 μm could be obtained in the primary recrystallization annealed sheet though a very coarse microstructure was produced in the initial as-cast strip. The main finding was that the “texture memory” effect on Goss texture started on the through-thickness intermediate annealed strip after first cold rolling, which was not similar to the “texture memory” effect on Goss texture starting on the surface layers of the hot rolled strip in the conventional production route. As a result, the origin of Goss nuclei capable of secondary recrystallization lied in the grains already presented in Goss orientation in the intermediate annealed strip after first cold rolling. Another finding was that fine and dispersive inhibitors (mainly AlN) were easy to be produced in the primary recrystallization microstructure due to the initial rapid solidification during strip casting and the subsequent rapid cooling, and the very high temperature reheating usually used before hot rolling in the conventional production route could be avoided. - Highlights: • A regular grade grain-oriented electrical steel was produced. • Evolution of microstructure, texture and inhibitor was characterized. • Origin of Goss nuclei lied in the intermediate annealed strip. • A fine primary recrystallization microstructure could be produced. • Effective inhibitors were easy to be obtained in the new processing route.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Quantum chemistry-assisted synthesis route development

We have been investigating “quantum chemistry-assisted synthesis route development” using in silico screenings and applied the method to several targets. Another example was conducted to develop synthesis routes for a urea derivative, namely 1-(4-(trifluoromethyl)-2-oxo-2H-chromen-7-yl)urea. While five synthesis routes were examined, only three routes passed the second in silico screening. Among them, the reaction of 7-amino-4-(trifluoromethyl)-2H-chromen-2-one and O-methyl carbamate with BF{sub 3} as an additive was ranked as the first choice for synthetic work. We were able to experimentally obtain the target compound even though its yield was as low as 21 %. The theoretical result was thus consistent with that observed. The summary of transition state data base (TSDB) is also provided. TSDB is the key to reducing time of in silico screenings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

New route of phase transition for enhanced TCO property of ZnO: A first-principles study

The ZnO is one of the best transparent conducting oxide (TCO) materials for optoelectronic properties. Primarilly three phases of ZnO namely wurtzite, rocksalt and zincblend along with other prominent phases under different pressure and with different phase transformation routes are reported. The route of phase transformation may differ and depends on the external parameters such as pressure. The conventional route for the phase transformation of wurtzite (B4) phase into CsCl type (B2) phase via rocksalt phase (B1) is estimated at the relatively high pressure value of the 256 GPa. In present paper, we propose a new route of transformation of B4 to B2 phase of ZnO via β-BeO type phase at relatively low pressure value of 43 GPa. In present study, the phase transformation analysis and the electronic structure analysis for different phases are carried out by using density functional theory (DFT). It is also observed that B2 phase have high dispersive nature of bottom of conduction band and consequently high mobility of charge carriers. It indicates the possibility of B2 phase may have better TCO properties among other phases of ZnO.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗