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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Co-Disposal Waste Package Loading Options for DOE SNF and HLW - 20331

The U.S. Department of Energy (DOE) is responsible for managing spent nuclear fuel (SNF) that is currently in, or will in the future come into, its possession. DOE must continue to safely store that SNF, transport it to an interim storage site or a repository, and dispose of it. These fuels come from a wide range of reactor types with various cladding materials and enrichments. Many of these reactors, now decommissioned, had unique design features, such as core configuration, fuel element and assembly geometry, moderator and coolant materials, operational characteristics, and neutron spatial and spectral properties, resulting in a large diversity of reactor and fuel designs. Because of the wide variety and conditions of SNF, a robust DOE Standard Canister was proposed that would confine radionuclides and preclude moderator. The DOE Standard Canister had four variations: 3.05-meter (10-foot) or 4.57-meter (15-foot) length, and 45.7-cm (18-inch) or 61.0-cm (24-inch) diameter. For ultimate disposal in the Yucca Mountain Repository, these canisters were to be grouped with 61.0-cm (24-inch) diameter high level waste (HLW) canisters in a 2.13-meter (84-inch) diameter co-disposal waste package. The smaller 45.7-cm (18-inch) diameter DOE Standard Canister could be placed in the middle of five HLW canisters. The larger 61.0-cm (24-inch) diameter DOE Standard Canister would take the place of one of the five HLW canisters on the outer ring in the co-disposal waste package. No DOE Standard Canisters have been loaded. A preliminary evaluation has estimated the number of elements of a fuel type that can fit into the different sizes of the DOE Standard Canister, but no definitive loading configuration has been selected. Changing the loading configuration could impact the number of loadable DOE Standard Canisters and the number of co-disposal waste packages needed for eventual disposition. This paper conveys the ranges of DOE Standard Canisters and HLW canisters that may be produced under certain conditions. It also examines the differences in the estimated number of co-disposal waste packages produced for eventual disposal when using different loading strategies in the DOE Standard Canister for Advanced Test Reactor (ATR), Peach Bottom, and High Flux Isotope Reactor (HFIR) SNF. Changing the loading configurations of ATR, Peach Bottom, and HFIR SNF slightly impacted the number of co-disposal waste packages that may be needed for ultimate disposal. The change in loading configuration was more impactful when a different canister was used, as opposed to varying the number of elements that could fit inside the same size canister. In one case, a reduction of co-disposal waste packages could be achieved by allowing mixing of short HLW canisters with long DOE Standard Canisters. The main conclusion from this analysis is that the ratio between HLW canisters and DOE Standard Canisters will drive the total number of co-disposal waste packages. If too many HLW canisters (i.e., more than five times the number of 18-inch DOE standard canisters) or DOE Standard Canisters are produced, some co-disposal waste packages may not have all positions filled. A co-disposal waste package may be filled with all HLW with no DOE Standard Canister, or a co-disposal waste package could be filled with a single DOE Standard Canister. A ratio that does not closely align to optimum could allow for the design of waste packages that hold just HLW canisters or just DOE SNF canisters. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Productivity and bioproduct formation in phototropic knock/out mutants in micro algae

Phototropin is a blue light receptor, which mediates a variety of blue-light elicited physiological processes in plants and algae. In higher plants these processes include phototropism, chloroplast movement and stomatal opening. In the green alga Chlamydomonas reinhardtii, phototropin plays a vital role in progression of the sexual life cycle and in the control of the eye spot size and light sensitivity. Phototropin is also involved in blue-light mediated changes in the synthesis of chlorophylls, carotenoids, chlorophyll binding proteins. We compared the transcriptome of phototropin knock out (PHOT KO) mutant and wild-type parent to analyze differences in gene expression in high light grown cultures (500 μmol photons m⁻²s⁻¹). Our results indicate the up-regulation of genes involved in photosynthetic electron transport chain, carbon fixation pathway, starch, lipid, and cell cycle control genes. With respect to photosynthetic electron transport genes, genes encoding proteins of the cytochrome b6f and ATP synthase complex were up regulated potentially facilitating proton-coupled electron transfer. In addition genes involved in limiting steps in the Calvin cycle Ribulose-1,5-biphosphate carboxylase/oxygenase (RuBisCO), Sidoheptulose 1,7 biophosphatase (SBPase), Glyceraldehyde-3-phosphate dehydrogenase (3PGDH) and that mediate cell-cycle control (CDK) were also up regulated along with starch synthase and fatty acid biosynthesis genes involved in starch and lipid synthesis. In addition, transmission electron micrographs show increased accumulation of starch granules in PHOT mutant compared to wild type, which is consistent with the higher expression of starch synthase genes. Collectively, the altered patterns of gene expression in the PHOT mutants were associated with a two-fold increase in growth and biomass accumulation compared to wild type when grown in environmental photobioreactors (Phenometrics) that simulate a pond environment. In conclusion, our studies suggest that phototropin may be a master gene regulator that suppresses rapid cell growth and promotes gametogenesis and sexual recombination in wild type strains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Nematic Fluctuations in the Non-Superconducting Iron Pnictide BaFe 1.9-x Ni 0.1 Cr x As 2

The main driven force of the electronic nematic phase in iron-based superconductors is still under debate. Here, we report a comprehensive study on the nematic fluctuations in a non-superconducting iron pnictide system BaFe 1.9-x Ni 0.1 Cr x As 2 by electronic transport, angle-resolved photoemission spectroscopy (ARPES), and inelastic neutron scattering (INS) measurements. Previous neutron diffraction and transport measurements suggested that the collinear antiferromagnetism persists to x = 0.8, with similar Néel temperature TN and structural transition temperature Ts around 32 K, but the charge carriers change from electron type to hole type around x = 0.5. In this study, we have found that the in-plane resistivity anisotropy also highly depends on the Cr dopings and the type of charge carriers. While ARPES measurements suggest possibly weak orbital anisotropy onset near Ts for both x = 0.05 and x = 0.5 compounds, INS experiments reveal clearly different onset temperatures of low-energy spin excitation anisotropy, which is likely related to the energy scale of spin nematicity. These results suggest that the interplay between the local spins on Fe atoms and the itinerant electrons on Fermi surfaces is crucial to the nematic fluctuations of iron pnictides, where the orbital degree of freedom may behave differently from the spin degree of freedom, and the transport properties are intimately related to the spin dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Bandgap Engineering of Ga 2 O 3 by MOCVD Through Alloying with Indium

Ga 2 O 3 and In 2 O 3 are vital semiconductors with current and future electronic device applications. Here, we study the alloying of In 2 O 3 and Ga 2 O 3 (IGO) and the associated changes in structure, morphology, band gap, and electrical transport properties. Undoped films of IGO were deposited on sapphire substrates with varying indium (In) percentage from zero to 100% by metal-organic chemical vapor deposition (MOCVD). Some films were annealed in H 2 to induce electrical conductivity. The measurements showed the optical band gap decreased by adding In; this was confirmed by density functional (DFT) calculations, which revealed that the nature of the valence band maximum and conduction band minimum strongly relate to the chemistry and that the band gap drops by adding In. The as-grown films were highly resistive except for pure In 2 O 3 , which possesses p-type conductivity, likely arising from In vacancy-related acceptor states. N-type conductivity was induced in all films after H-anneal. DFT calculations revealed that the presence of In decreases the electron effective mass, which is consistent with the electrical transport measurements that showed higher electron mobility for higher In percentage. The work revealed the successful band gap engineering of IGO and the modification of its band structure while maintaining high-quality films by MOCVD.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Metallic d-wave altermagnetism in WFeB: a platform for electrically switchable perpendicular spin-splitter response

We report the synthesis and magnetic characterization of WFeB and identify it as a metallic d-wave altermagnet representative of a broader TiNiSi-type family. Neutron diffraction, Mössbauer spectroscopy, and magnetometry establish a collinear altermagnetic ordering confirmed by first-principles calculations. The electronic structure shows a nonrelativistic spin splitting of approximately 100 meV, but it also supports a strong spin-splitter transport response. This demonstrates that efficient spin-current generation can occur even with such modest band splitting. Symmetry analysis shows that selected film orientations permit deterministic switching of the Néel vector by current-induced staggered torques, enabling electrical control of a perpendicular spin-splitter response. These results establish WFeB and related TiNiSi-type antiferromagnets as a platform for electrically switchable charge-to-spin conversion driven by altermagnetic symmetry.

FOS: Physical sciences↗
DOE OSTI2022

CO 2 Pipeline risk assessment and comparison for the midcontinent United States

For this work, a comprehensive quantitative risk assessment for the construction and operation of CO 2 transportation networks considered for the Midcontinent United States was conducted. The results showed risks associated with CO 2 pipelines were significantly less than those of other pipeline types. The assessment used four conceptual pipelines of different lengths to discuss risks operators may see. The assessment evaluated the risk associated with construction and operation using data from the US Occupational Safety Health Administration to determine the risk of injury or death for pipeline workers and data from the US Pipeline and Hazardous Materials Safety Administration for CO 2 , natural gas distribution, natural gas transmission/gathering, and non-CO 2 hazardous liquid pipelines to develop quantitative likelihood and severity values leading to risk values. The data for the assessment covered incidents from 2010 to 2017 for CO 2 pipelines. The average risk for construction and 30 years of operation for four CO 2 pipeline configurations ranging between 79 and 1,546 miles in length was found. The construction and operational risk averaged between $\$1,400,521$ (approximately $\$0.02$/tonne of CO 2 ) for the shorter pipeline (79 miles) and $\$27,481,939$ (approximately $\$0.10$/tonne of CO 2 ) for a longer pipeline (1,546 miles). The largest risks of fatality for CO 2 pipelines comes from vehicle transport. The largest operational risk to the pipeline was due to leakage. Public pipeline opposition is also a significant risk; it was not quantified but is addressed.

03 NATURAL GAS↗
DOE OSTI2021

Wood-to-Fuel for California's Transportation Sector using Autothermal Pyrolysis: Kickoff Questionnaire for Benefits Analysis of CEC Projects

This is the first of three questionnaires that you will be asked to complete over the course of the agreement. Please type your responses directly into this document in the spaces below each question. Use as much space as you need; the form automatically creates more space within each response field. In addition, you may submit additional documents, spreadsheets, or other files. Acceptable filetypes are MS Word, MS Excel, and PDF. Additional files do not need to follow any particular format, unless specified by the particular questionnaire designed for your project.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Coexistence of Merons with Skyrmions in the Centrosymmetric Van Der Waals Ferromagnet Fe 5– x GeTe 2

Fe 5-x GeTe 2 is a centrosymmetric, layered van der Waals (vdW) ferromagnet that displays Curie temperatures T c (270–330 K) that are within the useful range for spintronic applications. However, little is known about the interplay between its topological spin textures (e.g., merons, skyrmions) with technologically relevant transport properties such as the topological Hall effect (THE) or topological thermal transport. Here, via high-resolution Lorentz transmission electron microscopy, it is shown that merons and anti-meron pairs coexist with Néel skyrmions in Fe 5-x GeTe 2 over a wide range of temperatures and probe their effects on thermal and electrical transport. A THE is detected, even at room T, that senses merons at higher T's, as well as their coexistence with skyrmions as T is lowered, indicating an on-demand thermally driven formation of either type of spin texture. Remarkably, an unconventional THE is also observed in absence of Lorentz force, and it is attributed to the interaction between charge carriers and magnetic field-induced chiral spin textures. Here these results expose Fe 5-x GeTe 2 as a promising candidate for the development of applications in skyrmionics/meronics due to the interplay between distinct but coexisting topological magnetic textures and unconventional transport of charge/heat carriers.

two-dimensional magnets↗
DOE OSTI2022

Photoactivated p-Doping of Organic Interlayer Enables Efficient Perovskite/Silicon Tandem Solar Cells

Solution-processed organic semiconductor layers on rough surfaces tend to vary widely in thickness, significantly hindering charge extraction in relevant optoelectronic devices. Herein, we report the photoactivated p-doping of hole-transporting material (HTM) to enhance hole extraction for (textured) perovskite/silicon tandem solar cells, making the device performance less sensitive to the variation of hole transport layer thickness. We used the ionic compound 4-isopropyl-4'-methyldiphenyliodonium tetrakis(penta-fluorophenyl-borate) (DPI-TPFB) as a p-type dopant in poly(triaryl amine) (PTAA), which we used as the HTM. We observed that light soaking DPI-TPFB-doped PTAA shows approximately 22 times higher conductivity compared with an undoped PTAA film, which translated into an improved fill factor (FF) for tandem solar cells. Our tandem solar cells achieved an ~80% FF and 27.8% efficiency and operated at their maximum power point for 200 h without loss of performance, in addition to retaining ~83% of initial performance over a month of operation in an outdoor environment.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,S↗
DOE OSTI2024

Three Decades of Wetland Methane Surface Flux Modeling by Earth System Models–Advances, Applications, and Challenges

Earth System Models (ESMs) simulate the exchange of mass and energy between the land surface and the atmosphere, with a key focus on modeling natural greenhouse gas feedbacks. Methane is the second most important greenhouse gas after carbon dioxide. There are growing concerns over the rapidly increasing methane concentration in the atmosphere, underscoring the need for accurate global modeling of its emissions using ESMs. Of the multitude of sources of methane globally, wetlands are the largest natural emitters for methane, leading to significant efforts targeting their representation in ESMs with a special focus on their methane emissions. In this review, we first provide a historical overview of including wetland–methane components in ESMs and how methane modeling approaches have evolved over time. Second, we discuss recent modeling advancements that show promise for improvements in methane emissions predictions, namely the coupling of surface and atmospheric modules of ESMs, the representation of microtopography and transport mechanisms, the resolution of microbial processes at different spatial–temporal scales, and the improved mapping of wetland area extent across the different wetland types. Third, we shed light on the different challenges hindering accurate estimations of wetland–methane emissions, as shown by the consistent discrepancy between bottom–up and top–down models' predictions. Finally, we emphasize that more detailed representation of biogeochemistry and dynamic hydrology while resolving the within–wetland vegetation heterogeneity should improve model predictions, especially when coupled with expanding ground–based measurement networks and high–resolution remote sensing mapping of methane–relevant variables, such as water elevation, water table depth, and methane concentration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A constraint-based framework for exploring the impact of multireaction dependencies on metabolic functions

Abstract Metabolism operates under physico-chemical constraints that result in multireaction dependencies. Understanding how multireaction dependencies affect metabolic phenotypes remains challenging, hindering their biotechnological applications. Here, we propose the concept of a forcedly balanced complex that allows to efficiently determine the effects of specific multireaction dependencies on metabolic network functions in constrained-based models. Using this concept, we found that the fraction of multireaction dependencies induced by forcedly balanced complexes in genome-scale metabolic networks followed power law with exponential cut-off. We identified forcedly balanced complexes that are lethal in cancer but have little effect on growth in healthy tissue models. In addition, these forcedly balanced complexes are largely specific to models of particular cancer types. Therefore, multireaction dependencies resulting from forced balancing of complexes represent an innovative means to control cancers that, we argue, can be implemented via transporter engineering. The presented constraint-based approaches pave the way for using multireaction dependencies in metabolic engineering for diverse biotechnological applications.

Küken, Anika↗
DOE OSTI2020

Near-canopy horizontal concentration heterogeneity of semivolatile oxygenated organic compounds and implications for 2-methyltetrols primary emissions

Semivolatile oxygenated organic compounds (SV-OVOCs) are important atmospheric species, in particular for the production and chemistry of atmospheric particulate matter and related impacts on air quality and climate. In this study, SV-OVOCs were collected in the horizontal plane of the roughness layer over the tropical forest in the central Amazon during the wet season of 2018. A sampler mounted to a copter-type, hovering unmanned aerial vehicle was used. Underlying the collection region, a plateau forest transitioned into a slope forest across several hundred meters. The concentrations of pinonic and pinic acids, which are monoterpene oxidation products, had no statistical difference over the two forests. By comparison, across the study period, differences in the concentration of 2-methyltetrols, which are products of isoprene oxidation, ranged from -70% to +480% over the two forests. The chemical lifetime of 2-methyltetrols in the atmosphere is sufficiently long that heterogeneity in the isoprene emission rate from the two forests followed by atmospheric oxidation does not explain the concentration heterogeneity of 2-methyltetrols. Standing waves and local meteorology also cannot account for the heterogeneity. Of the possibilities considered, the most plausible explanation is the direct emission from the forest of 2-methyltetrols produced through biological processes within the plants. Under this explanation, the rate of direct SV-OVOC emissions should be modulated by forest type and related environmental stressors. Direct emissions of SV-OVOCs should be more broadly considered for constraining and improving models of atmospheric composition, transport, and chemistry over tropical forests.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Ferromagnetism and structural phase transition in rhombohedral PrI r 3

The synthesis, structural, magnetic, thermal, and transport properties are reported for polycrystalline PrI⁢r 3 . At room temperature PrI⁢r 3 displays the rhombohedral space group R–3m and a PuNi 3 -type structure. At around 70 K a phase transition to a monoclinic C⁢2/m structure is observed and continued cooling reveals temperature independent behavior of the unit cell volume. Further, PrI⁢r 3 undergoes a paramagnetic to ferromagnetic transition with T c =7.5K. The temperature dependent magnetic susceptibility follows the Curie-Weiss law with a positive Curie-Weiss temperature, and an effective moment that is close to the theoretical effective moment for a free P⁢r +3 ion. Finally, the structural transition introduces further complexity into the behavior of PuNi 3 -type materials and highlights the importance of temperature-dependent structural studies to complement physical property measurements in intermetallic compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Optimal, centralized dynamic curbside parking space zoning

In this paper we formulate a dynamic mixed integer program for optimally zoning curbside parking spaces subject to transportation policy-inspired constraints and regularization terms. First, we illustrate how given some objective of curb zoning valuation as a function of zone type (paid parking, bus stop, etc.), dynamically rezoning involves unrolling this optimization program over a fixed time horizon. Second, we implement two different solution methods given an example curb zoning valuation. In the first method, we solve long horizon dynamic zoning problems via approximate dynamic programming. In the second method, we employ Dantzig-Wolfe decomposition to break-up the mixed-integer program into a master problem and several sub-problems that can be solved in parallel. This speeds up the computational solve-time of the MIP considerably. We present simulation results and comparisons of the different employed techniques on vehicle arrival-rate data obtained for a neighborhood in downtown Seattle, Washington, USA.

Nazir, Mohammad Nawaf↗
DOE OSTI2021

OpenMC

OpenMC is an open source, community-developed framework for performing Monte Carlo particle transport calculations.It is capable of simulating neutron and photon transport below ~50 MeV and also includes a model for bremsstrahlung production of photons by electrons/positrons. Fixed source, k-eigenvalue, and subcritical multiplication problems can be solved. Problem geometries can be modeled either using constructive solid geometry or a CAD representation. A flexible and efficient tally system enables a wide variety of physical quantities to be tallied and analyzed. OpenMC can run in parallel using a hybrid MPI and OpenMP programming model and has been extensively tested on leadership class supercomputers. A built-in Bateman equation solver enables the modeling of material composition changes due to irradiation. One of the unique features of OpenMC is its rich, extensible Python and C/C++ programming interfaces that enable programming pre- and post-processing, multigroup cross section generation, workflow automation, multiphysics coupling, and the visualization of geometry and tally results. In addition to the core Monte Carlo transport solver and associated APIs, OpenMC includes a Python-based nuclear data interface that enables power users to inspect, modify,and perform various types of nuclear data processing on ENDF, ACE, and OpenMC¿s native HDF5 files

ROMANO, PaulK.↗
DOE OSTI2024

Self-Supervised Cloud Classification

Abstract Low-level marine clouds play a pivotal role in Earth’s weather and climate through their interactions with radiation, heat and moisture transport, and the hydrological cycle. These interactions depend on a range of dynamical and microphysical processes that result in a broad diversity of cloud types and spatial structures, and a comprehensive understanding of cloud morphology is critical for continued improvement of our atmospheric modeling and prediction capabilities moving forward. Deep learning has recently accelerated our ability to study clouds using satellite remote sensing, and machine learning classifiers have enabled detailed studies of cloud morphology. A major limitation of deep learning approaches to this problem, however, is the large number of hand-labeled samples that are required for training. This work applies a recently developed self-supervised learning scheme to train a deep convolutional neural network (CNN) to map marine cloud imagery to vector embeddings that capture information about mesoscale cloud morphology and can be used for satellite image classification. The model is evaluated against existing cloud classification datasets and several use cases are demonstrated, including training cloud classifiers with very few labeled samples, interrogation of the CNN’s learned internal feature representations, cross-instrument application, and resilience against sensor calibration drift and changing scene brightness. The self-supervised approach learns meaningful internal representations of cloud structures and achieves comparable classification accuracy to supervised deep learning methods without the expense of creating large hand-annotated training datasets. Significance Statement Marine clouds heavily influence Earth’s weather and climate, and improved understanding of marine clouds is required to improve our atmospheric modeling capabilities and physical understanding of the atmosphere. Recently, deep learning has emerged as a powerful research tool that can be used to identify and study specific marine cloud types in the vast number of images collected by Earth-observing satellites. While powerful, these approaches require hand-labeling of training data, which is prohibitively time intensive. This study evaluates a recently developed self-supervised deep learning method that does not require human-labeled training data for processing images of clouds. We show that the trained algorithm performs competitively with algorithms trained on hand-labeled data for image classification tasks. We also discuss potential downstream uses and demonstrate some exciting features of the approach including application to multiple satellite instruments, resilience against changing image brightness, and its learned internal representations of cloud types. The self-supervised technique removes one of the major hurdles for applying deep learning to very large atmospheric datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Observational Understanding of Connected Lighting Systems

As part of the Internet of Things (IoT), connected lighting systems provide additional control capabilities and nonlighting-related services (such as communications and data infrastructure) to reduce energy use while increasing both application efficiency and system value. But the positive or negative energy impact of implementing these systems is still largely unknown due to the variety of human factors associated with installation, maintenance, and use. These complications interfere with adoption and acceptance rates of products that will play a significant role in achieving energy savings long-term. Next Generation Lighting Systems, or NGLS, developed and implemented an observational research methodology for connected lighting systems. The methodology was implemented at an indoor (classroom/office) Living Lab at Parsons School of Design in New York City, and an outdoor (parking lot) Living Lab at Virginia Tech Transportation Institute in Blacksburg, Virginia. Although this report focuses on the approach to indoor installations, observational research in both settings provides insight to the type, scale, and frequency of issues across available products as experienced by installing contractors, end users, and other stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL's Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

47 OTHER INSTRUMENTATION↗