Searching for superconductivity in high entropy oxide Ruddlesden?Popper cuprate films
Explore the source record for details and available documents.
Mazza, Alessandro R.↗
SEARCH · Engineering Papers
Results for “driving behavior”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Selectively patterned Mg-doped GaN by SiN x -driven hydrogen injection
In this work, we demonstrate a method to achieve selectively patterned Mg-doped GaN layers using hydrogen drive-in through plasma-enhanced chemical vapor deposition (PECVD) silicon nitride (SiN x ) films. Activated Mg-doped GaN layers were selectively deactivated by patterned PECVD SiN x films with low-temperature annealing and showed high-resistive behavior. Spatially resolved photoluminescence measurements were used to optically verify the deactivation of Mg acceptors and showed distinct features corresponding to activated and deactivated Mg in GaN. The method suggested here provides a simple and effective method to achieve patterned Mg-doped GaN regions without thermal and plasma damage, which could cause degradation of device performance. The proposed method could provide a way to achieve future high-performance GaN lateral and vertical devices that rely on laterally patterned doping.
42 ENGINEERING↗
Flight Planning for the International Space Station - Levitation Observation of Dendrite Evolution in Steel Ternary Alloy Rapid Solidification (LODESTARS)
During rapid solidification, a molten sample is cooled below its equilibrium solidification temperature to form a metastable liquid. Once nucleation is initiated, growth of the solid phase proceeds and can be seen as a sudden rise in temperature. The heat of fusion is rejected ahead of the growing dendrites into the undercooled liquid in a process known as recalescence. Fe-Cr-Ni alloys may form several equilibrium phases and the hypoeutectic alloys, with compositions near the commercially important 316 stainless steel alloy, are observed to solidify by way of a two-step process known as double recalescence. During double recalescence, the first temperature rise is associated with formation of the metastable ferritic solid phase with subsequent conversion to the stable austenitic phase during the second temperature rise. Selection of which phase grows into the undercooled melt during primary solidification may be accomplished by choice of the appropriate nucleation trigger material or by control of the processing parameters during rapid solidification. Due to the highly reactive nature of the molten sample material and in order to avoid contamination of the undercooled melt, a containerless electromagnetic levitation (EML) processing technique is used. In ground-based EML, the same forces that support the weight of the sample against gravity also drive convection in the liquid sample. However, in microgravity, the force required to position the sample is greatly reduced, so convection may be controlled over a wide range of internal flows. Space Shuttle experiments have shown that the double recalescence behavior of Fe-Cr-Ni alloys changes between ground and space EML experiments. This program is aimed at understanding how melt convection influences phase selection and the evolution of rapid solidification microstructures.
Flemings, Merton C.↗
LDRD conclusion poster - Synthesizing Heterometallic Uranium Single Crystals to Understand the Influence of the Secondary Metals on Uranyl Axial Bond Strength
Understanding how transition metals influenced the chemistry of lanthanide and actinide (f-element) materials is critical for advancing separation technologies, materials design, and coordination chemistry. This project examined how incorporating first-row transition metals affected the structural and spectroscopic properties of f-element coordination polymers. In uranium(VI)-based systems synthesized with 2,6-pyridinedicarboxylic acid (PDC) ligands, single-crystal X-ray diffraction and Raman spectroscopy revealed that the presence of transition metals shortened the uranyl axial bond and induced a blue shift in its symmetric stretching vibration—evidence of increased bond strength. Electronic structure analysis, including Density of States (DOS) calculations using density functional theory (DFT), revealed altered orbital overlaps and highlighted the role of transition metal d-orbitals in modulating bonding. Raman modes were modeled using truncated structural fragments in collaboration with the University of Notre Dame, and although the predicted frequencies were lower than experimental values, they remained within expected ranges. In parallel, similar experiments with cerium (Ce) in the presence of cobalt (Co) and PDC demonstrated multi-step single-crystal-to-single-crystal transformations—behavior not observed in the uranium systems. Initial products included light yellow, orange, and polycrystalline materials. Single-crystal X-ray diffraction studies, conducted in collaboration with the Colorado School of Mines, identified the yellow phase as monometallic Ce(PDC)2(H2O)2·4H2O and the orange phase as heterometallic Ce2Co(PDC)4(H2O)6. After standing in solution for one week, both phases fully transformed into a dark yellow crystalline phase, [Ce3(PDC)5(H2O)8].6(H2O). Remarkably, this transformation was reversible—disturbing the equilibrium by removing some crystals caused reversion to the initial Ce(PDC)2(H2O)2·4H2O phase, highlighting dynamic behavior. All three structures were previously unreported. Solid-state UV-visible and Raman spectroscopy further distinguished these phases, revealing ligand-to-metal charge transfer involving Ce and characteristic d–d transitions from Co(II). The precise mechanism driving these transformations remained unclear; however, pH-dependent experiments confirmed that the transformation did not occur when the pH decreased. Overall, the project demonstrated that transition metals could be employed to tune bonding interactions, structural dimensionality, and optical properties in f-element materials, establishing new pathways for designing functional heterometallic systems. The work resulted in several novel structural discoveries and fostered productive collaborations with the University of Notre Dame and the Colorado School of Mines.
37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
Densification and oxidation behavior of spark plasma sintered Hafnium Diboride-Hafnium Carbide composite
This study reports on the sintering and oxidation behaviors of Hafnium Diboride (HfB 2 ) and Hafnium Carbide (HfC) based ultra-high temperature ceramic (UHTC) composites. Pure Hafnium Diboride, Hafnium Carbide, and HfB 2 -50 vol% HfC composite were consolidated using spark plasma sintering (SPS) without the use of sintering aids. HfB 2 -HfC composite displayed a high sintered density of 98% as compared to 87% density of pure HfB 2 . The increased density of the HfB 2 -HfC composite is attributed to the bimodal powder distribution, which allowed for the smaller HfC particle to occupy the voids between the larger HfB 2 particles resulting in improved packing efficiency. Moreover, the higher planar surface energy, for the (111) and the (200) planes for HfC, contributed to the smaller HfC particle being a significant driving force in the sintering process. Oxidation studies of each material were carried out by exposing them to a high-speed plasma jet in a temperature exceeding 2700 °C. The results of these studies show an improved oxidation resistance of HfB 2 -HfC composite by 54% and 70% over pure HfC and HfB 2 , respectively. The enhanced oxidation behavior is attributed to B 2 O 3 filling in the porosity between the HfO 2 scale and protecting the underlying material. This study provides a new alternative to improve the sinterability of UHTC diborides by introducing another UHTC (i.e., HfC) to form a fully dense composite without sintering aid and superior oxidation resistance.
36 MATERIALS SCIENCE↗
Effect of Vacuum on Force Response of an Ultrasonic Penetrator
Introduction: The Apollo astronauts encountered higher than expected resistances when interacting with the lunar soil via the Apollo Lunar Surface Drill (ALSD) and the trenching tool. Reducing the force required to move tools or other mechanical components through regolith will impact many steps of the resource extraction process. Force reduction has been achieved in soil materials by imparting vibration to tooling interfaces such as a vibratory farming cultivator, a percussive scoop, and ultrasonically resonant penetrators. Vibration-assisted tools in granular media reduce interaction forces by fluidizing a volume around the tool, allowing the tool to progress through a dynamic (fluid) medium instead of a static (solid) medium. This work seeks to quantify ultrasonic vibration’s effect on the force response of a penetrator in lunar soil simulant in vacuum sufficient to be within the molecular flow regime of any disturbed gases. Methods: A custom vacuum chamber setup, CUBEvac, was designed and built to facilitate penetration testing in a high vacuum environment, for comparison to penetration behavior in ambient terrestrial environment. A two-stage pumping system (Agilent Triscroll 600 roughing pump, Agilent VHS-6 oil diffusion pump) reached chamber pressures of about 5x10-6 Torr with regolith simulant in place. Figure 1 is a schematic of the heart of the assembly (note the penetration drive mechanisms above the chamber feedthrough and the regolith simulant sample in the bottom are not shown). The penetration actuation stack was comprised of a stepper motor driving a lead screw to move the ultra-sonic probe vertically inside the chamber. Motion was coordinated with an Arduino Uno. GRC-3 lunar simulant was used for this set of experiments. Samples were prepared in a four-liter stain-less steel, cylindrical pot with an internal diameter of approximately 15.56 cm (6.125 in) and a depth of 19.37 cm (7 5/8 in) for testing. The soil was baked out prior to compaction preparation as a measure to reduce soil moisture which interfered with pump down capacity. The soil was not baked again if it was removed from the vacuum chamber, prepped, and immediately returned to the vacuum chamber for pump down. The soil was compacted using a 60 Hz vibration table with a surcharge of 34 kg place on top of the soil in the container. Prepared soil samples weighed approximately 6.5 kg (bulk density 1.895-1.934 g/cm3). Two probe end effectors were tested: A cone penetrometer (static only) with a nominal diameter of 12.7 mm (0.5 in) and a nominal height of 28.6 mm (1.125 in); and a vibrating cylindrical probe measuring 12.7 mm in diameter and 50.8 mm in effective length from the tip (Figure 2). The cylindrical probe vibrated resonantly at 20 kHz with an amplitude 23 μm. The cone penetration tests were conducted to assess potential soil behavior differences in vacuum. The cylinder probe tests were conducted as the primary subject of this investigation to assess force response in vacuum. For each test, a regolith simulant sample was load-ed and compacted in the chamber, which was then evacuated for roughly 18 hours to reach the lowest possible pressure (approximately 5x10-6 Torr for most tests). The probe was then moved to about 10 mm above the soil surface before being pushed to a depth of 50 mm for the cylinder probe tests and to a depth of 100 mm for the cone penetrometer tests, both at a speed of 2 mm/s. The simulant samples were prepared the same for all tests. Ideally, they would respond consistently to probe penetration under ambient and vacuum conditions. This was evaluated by measuring the resistance of representative prepared simulant beds with a standard cone penetrometer in both environments. Results and Discussion: The resistance of the simulant samples in the vacuum tests was consistently lower than in the ambient tests as determined by the cone penetration tests. Thus, the ambient and vacuum results cannot be compared directly; work is underway to de-confound and better correlate the data. Still, figures 3-6 show that probe penetration forces are lower overall in the vacuum environment. In both environments, resonant vibration of the probe provides two useful effects: It reduces the probe penetration force and smooths the force-depth curve, significantly reducing local maxima. These effects have implications for various potential applications, such as astronaut hand-tools, where benefits (reducing astronaut effort) outweigh the cost of the additional energy re-quired to generate vibration. These results demonstrate that resonantly vibrating tools can meaningfully reduce the penetration force required for excavation, probing, and drilling tools in simulated lunar regolith deposits under vacuum levels approaching those that will be experience on the Moon’s surface. Lunar-gravity, ambient environment tests are scheduled soon. The effects of realistic temperatures and temperature gradients and deeper vacuum remain to be tested.
E Rezich↗
Topology-enhanced mechanical stability of swelling nanoporous electrodes
Abstract Materials like silicon and germanium offer a 10-fold improvement in charge capacity over conventional graphite anodes in lithium-ion batteries but experience a roughly threefold volume increase during lithiation, which challenges ensuring battery integrity. Nanoporous silicon, created by liquid-metal-dealloying, is a potentially attractive anode design to mitigate this challenge, exhibiting both higher capacity and extended cycle lifetimes. However, how nanoporous structures accommodate the large volume change is unknown. Here, we address this question by using phase-field modeling to produce nanoporous particles and to investigate their elastoplastic swelling behavior and fracture. Our simulations show that enhanced mechanical stability results from the network topology consisting of ligaments connected by bulbous, sphere-like nodes. The ligaments forcefully resist elongation while the nodes, behaving like isolated spherical particles, experience large stresses driving fracture. However, being smaller compared to a sphere of the same volume as the entire nanoporous particle, the nodes are more protected against fracture.
36 MATERIALS SCIENCE↗
Organismic materials for beyond von Neumann machines
The elementary basis of intelligence in organisms with a central nervous system includes neurons and synapses and their complex interconnections forming neural circuits. In non-neural organisms such as slime mold with gel-like media, viscosity modulation enables adaptation to changing environments. At a larger scale, collective intelligence emerges via social interactions and feedback in animal colonies. Learning and memory are therefore multi-scale features that evolve as a result of constant interactions with the environment. There is growing interest in emulating such features of intelligence in computing machines and autonomous systems. Materials that can respond to their environment in a manner similar to organisms (referred to as "organismic materials") therefore may be of interest as hardware components in artificial intelligence machines. In this brief review, we present a class of semiconductors called correlated oxides as candidates for learning machines. The term "correlated" refers to the fact that electrons in such lattices strongly interact and the ground state is not what is predicted by classical band theory. Such materials can undergo insulator-metal transitions at near ambient conditions under external stimuli such as thermal or electrical fields, strain, and chemical doping. Depending on the mechanism driving the transition, intermediate states can be metastable with different volatilities, and the time scales of phase change can be controlled over many orders of magnitude. The change in electronic properties can be sharp or gradual, leading to digital or analog behavior. These properties enable the realization of artificial neurons and synapses and emulate the associative and non-associative learning characteristics found in various organisms. We examine microscopic properties concerning electronic and structural transitions leading to collective behavior and theoretical treatments of the ground state and dynamical response, showcasing VO 2 as a model system. Next, we briefly review algorithms designed from the plasticity demonstrated by phase changing systems. Finally, we conclude the brief review with suggestions for future research toward realizing non-von Neumann machines.
42 ENGINEERING↗
Quasi-1D Coulomb Drag in the Nonlinear Regime
One-dimensional Coulomb drag has been an essential tool to probe the physics of interacting Tomonaga-Luttinger liquids. To date, most experimental work has focused on the linear regime while the predictions for Luttinger liquids beyond the linear response theory remain largely untested. In this Letter, we report measurements of reciprocal momentum transfer induced Coulomb drag between vertically coupled quasi-one-dimensional quantum wires in the nonlinear regime. Measurements were performed at ultralow temperatures between wires only 15 nm apart. Our results reveal a nonlinear dependence of the drag voltage as a function of the drive current superimposed with an oscillatory contribution, in agreement with theoretical predictions for Coulomb drag between Tomonaga-Luttinger liquids. Additionally, the observed current-voltage characteristics exhibit a nonmonotonic temperature dependence, further corroborating the presence of non-Fermi-liquid behavior in our system. In conclusion, these findings are observed both in the single and in the multiple subband regimes and in the presence of disorder, extending the onset of this behavior beyond the clean single channel Tomonaga-Luttinger regime where the predictions were originally formulated.
1-dimensional systems↗
Stabilization of discrete-event processes
Discrete-event processes are modeled by state-machines in the Ramadge-Wonham framework with control by a feedback event disablement mechanism. In this paper, concepts of stabilization of discrete-event processes are defined and investigated. The possibility of driving a process (under control) from arbitrary initial states to a prescribed subset of the state set and then keeping it there indefinitely is examined. This stabilization property is studied also with respect to 'open-loop' processes and their asymptotic behavior is characterized. Polynomial time algorithms are presented for verifying various types of attraction and for the synthesis of attractors.
Brave, Y.↗
2013-2014 Greater Fairbanks, Alaska, Transportation Survey
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
2013-2014 Greater Fairbanks, Alaska, Transportation Survey
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
2013-2014 Greater Fairbanks, Alaska, Transportation Survey
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
2013-2014 Greater Fairbanks, Alaska, Transportation Survey
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
2013-2014 Greater Fairbanks, Alaska, Transportation Survey
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
2013-2014 Greater Fairbanks, Alaska, Transportation Survey
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
2013-2014 Greater Fairbanks, Alaska, Transportation Survey
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
2013-2014 Greater Fairbanks, Alaska, Transportation Survey
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗