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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Travel Patterns And Characteristics Of Transit Users In New York State

This research is a detailed examination of the travel behaviors and patterns of transit users within New York State (NYS), primarily based on travel data provided by the National Household Travel Survey (NHTS) in 2009 and the associated Add-on sample households purchased by the New York State Department of Transportation (NYSDOT). Other data sources analyzed in this study include: NYS General Transit Feed Specification (GTFS) to assist in analyzing spatial relationships for access to transit and the creation of Transit Shed geographic areas of 1, 2.5, and 5 miles from transit stop locations, LandScan population database to understand transit coverage, and Census Bureau s American Community Survey (ACS) data to examine general transit patterns and trends in NYS over time. The majority of analyses performed in this research aimed at identifying transit trip locations, understanding differences in transit usage by traveler demographics, as well as producing trip/mode-specific summary statistics including travel distance, trip duration, time of trip, and travel purpose of transit trips made by NYS residents, while also analyzing regional differences and unique travel characteristics and patterns. The analysis was divided into two aggregated geographic regions: New York Metropolitan Transportation Council (NYMTC) and NYS minus NYMTC (Rest of NYS). The inclusion of NYMTC in all analysis would likely produce misleading conclusions for other regions in NYS. TRANSIT COVERAGE The NYS transit network has significant coverage in terms of transit stop locations across the state s population. Out of the 19.3 million NYS population in 2011, about 15.3 million (or 79%) resided within the 1-mile transit shed. This NYS population transit coverage increased to 16.9 million (or 88%) when a 2.5-mile transit shed was considered; and raised to 17.7 million (or 92%) when the 5-mile transit shed was applied. KEY FINDINGS Based on 2009 NHTS data, about 40% of NYMTC households used transit as their means of transportation on any typical day; while only 4% of households located elsewhere in NYS did the same. Regardless of geographic regions, 45% of the transit users came from households with income under $40,000, while 20% of transit users were from the top income group of $100,000 plus households. Travel made by NYMTC transit users were nearly twice as likely to be for work trips as compared to their counterpart non-transit users. Transit users in NYS generally made more trips but with shorter distances; they also drove less, which resulted in fewer miles. Furthermore, NYS transit users spent more time on each trip than their counterpart non-transit users. Because of the intensity of transit network services within NYMTC, 88% of the households reside within the 1-mile transit shed. Outside the NYMTC, however, only 54% of the region s households are located within the same distance. Impact to vehicle ownership was clearly evidenced. Nearly all people from zero-vehicle households in NYMTC lived within a 1-mile radius of transit stops. Elsewhere in NYS, 74% of residents from zero-vehicle households resided within the 1-mile transit shed. Close proximity to transit has a significant impact on increasing transit uses. Transit mode share, as a main mode, was higher for NYS residents that lived within the 1-mile transit shed than others. Based on ACS data, over the period from 2005 to 2013, the total number of NYMTC workers increased more than 9%, while transit commuting grew at a higher rate of more than 15% during the same period. REMARKS Note that transit use in areas outside the NYMTC region generally is not common, resulting in a smaller sample size of transit users in the Rest of NYS region. Caution should be exercised for statistics produced based on small sample sizes that tend to be less precise (i.e., with a larger margin of error). Furthermore, standardized transit network data were not available prior to 2005; comparable analyses using 2001 NHTS therefore was not feasible. As a result, this study focused on examining travel behaviors of transit users using 2009 NHTS data only.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Equilibrium-gated pattern formation: How molecular dissociation thermodynamics drive emergent behavior in dissipative polymeric systems

Emergent patterns in biological systems arise through dissipative processes that balance reaction and transport phenomena, producing highly functional properties from self-regulating mechanisms. Synthetic fabrication, by contrast, often relies on user-controlled, multistep methods that lack the self-organizing capabilities of natural systems. Inspired by nature, we sought chemical systems that integrate strongly coupled reaction and transport phenomena, identifying frontal ring-opening metathesis polymerization (FROMP) as a method capable of creating diverse forms and functions through reactive processing. By employing discrete molecular initiators, FROMP allows precise control of key reaction steps—inhibition, initiation, and propagation. Using an integrated computational and experimental framework, we uncover how near-equilibrium inhibition dynamics, coupled with far-from-equilibrium reaction kinetics, drive pattern formation in frontally polymerized synthetic materials. We propose the concept of equilibrium-gated pattern formation, demonstrating how initiator chemistry can be tuned to achieve programmable macroscale properties. Our study reveals a surprising insight: Emergent behavior in FROMP systems arises from the inhibition-dominated regime of resin composition, expanding prior observations that such behavior is confined to a narrow compositional space near the boundary between front quenching and uniform front propagation. We identify a broader compositional window, far from the quenching regime, where emergent behavior reliably manifests. This expanded design space significantly enhances the operational flexibility of reactive systems and their capacity for self-organization. Furthermore, these insights provide a roadmap for designing bioinspired materials with self-organizing capabilities, unlocking possibilities in synthetic manufacturing.

Architected Polymers↗
DOE OSTI2021

Defect Spirograph: Dynamical Behavior of Defects in Spatially Patterned Active Nematics

We report that topological defects in active liquid crystals can be confined by introducing gradients of activity. Here, we examine the dynamical behavior of two defects confined by a sharp gradient of activity that separates an active circular region and a surrounding passive nematic material. Continuum simulations are used to explain how the interplay among energy injection into the system, hydrodynamic interactions, and frictional forces governs the dynamics of topologically required self-propelling + 1/2 defects. Our findings are rationalized in terms of a phase diagram for the dynamical response of defects in terms of activity and frictional damping strength. Different regions of the underlying phase diagram correspond to distinct dynamical modes, namely immobile defects, steady rotation of defects, bouncing defects, bouncing-cruising defects, dancing defects, and multiple defects with irregular dynamics. These dynamic states raise the prospect of generating synchronized defect arrays for microfluidic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ABC -Auxetics: An Implicit Design Approach for Negative Poisson's Ratio Materials

A novel methodology is introduced for designing auxetic (negative Poisson's ratio) structures based on topological principles and is demonstrated by investigating a new class of auxetics based on two-dimensional (2D) textile weave patterns. Conventional methodology for designing auxetic materials typically involves determining a single deformable block (a unit cell) of material whose shape results in auxetic behavior. Consequently, patterning such a unit cell in a 2D (or 3D) domain results in a larger structure that exhibits overall auxetic behavior. Such an approach naturally relies on some prior intuition and experience regarding which unit cells may be auxetic. Second, tuning the properties of the resulting structures is typically limited to parametric variations of the geometry of a specific type of unit cell. Thus, most of the currently known auxetic structures belong to a selected few classes of unit cell geometries that are explicitly defined in accordance with a specified topological (i.e., grid structure). Herein, a new class of auxetic structures is demonstrated that, while periodic, can be generated implicitly, i.e., without reference to a specific unit cell design. The approach leverages weave-based parameters (A–B–C), resulting in a rich design space for auxetics that is previously unexplored.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Impact of thermodynamic fluctuations and pattern size on the nucleation behavior during area selective deposition

In this work, the authors explore the impact that thermodynamic fluctuations have on the spontaneous appearance of defects during area selective deposition on patterned surfaces that are fully covered by adsorbates under local thermodynamic equilibrium, such as self-assembled monolayers. By using a simple lattice gas model for the adsorbed monolayer, the authors were able to track the spontaneous formation of defects in the monolayer as a function of the pattern width. The results indicate that, for pattern widths of the order of tens of nanometers, roughening effects at the pattern edge can be the leading source for the spontaneous appearance of nucleation defects. This leads to an enhancement of the density of defects that can be up to three orders of magnitude higher than those expected in uniform (not patterned) surfaces. The model also predicts a density of defects that is inversely proportional to the pattern width. Finally, if the dynamic nucleation of defects during area selective deposition is driven by thermodynamic fluctuations, the model predicts that the nucleation rate should be proportional to the total precursor fluency and independent of purge times. Moreover, a tight confinement of the monolayer through a high quality smooth interface in the patterned substrate and strong cohesive interactions between adsorbates should each contribute to a reduction of the overall defect density.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Three-Tone Chemical Patterns for Block Copolymer Directed Self-Assembly

Chemical patterns for directed self-assembly (DSA) of lamellaeforming block copolymers (BCP) with density multiplication can be fabricated by patterning resist on a cross-linked polystyrene layer, etching to create guide stripes, and depositing end-grafted brushes in between the stripes as background. To date, two-tone chemical patterns have been targeted with the guide stripes preferentially wet by one block of the copolymer and the background chemistry weakly preferentially wet by the other block. In the course of fabricating chemical patterns in an all-track process using 300 mm wafers, it was discovered that the etching process followed by brush grafting could produce a three-tone pattern. We characterized the three regions of the chemical patterns with a combination of SEM, grazing-incidence small-angle X-ray scattering (GISAXS), and assessment of BCP-wetting behavior, and evaluated the DSA behavior on patterns over a range of guide stripe widths. In its best form, the three-tone pattern consists of guide stripes preferentially wet by one block of the copolymer, each flanked by two additional stripes that wet the other block of the copolymer, with a third chemistry as the background. Three-tone patterns guide three times as many BCP domains as two-tone patterns and thus have the potential to provide a larger driving force for the system to assemble into the desired architecture with fewer defects in shorter time and over a larger process window.

block copolymer↗
DOE OSTI2020

Activity Time-Use Patterns and Experienced Satisfaction: Travel Behavioral Dynamics from the 2010–2013 American Time-Use Survey Data

Central to the theory of activity-based approaches is the role of time-use and its impacts on various decision processes related to individual activity-travel patterns, thereby determining ones’ daily well-being. This research aims at quantifying and investigating the underlying correlation of time-use and happiness using the repeated cross-section data from the 2010-2013 American Time Use Survey Well-Being module. The survey specifically records reported levels of activity satisfaction as measured through – happiness, meaningfulness, tiredness, sadness and stress experienced from activity participation. Using these scores, we first construct a composite degree of activity satisfaction that a person experiences using latent class cluster analysis. A series of regression models are then estimated to jointly analyze episodic duration and satisfaction separately for each of years from 2010-2013, by controlling for socioeconomics, household lifecycle stages (29-groups based on age, gender, marital status and presence of children), activity characteristics and global life and health assessment measures. Overall, model estimation results reveal a strong negative correlation between episodic duration and happiness from individual activity engagement patterns. This correlation pattern is temporally stable for the years 2010-2013, with minor variations. Results also suggest that household lifecycle stage has a major impact on activity time-use and satisfaction behavior. Further, single parent and younger couples (25 years to 45 years) with children are more likely to engage in longer and less happy episodes due to family commitments. The model findings also show a strong correlation between health conditions and activity happiness.

Ravulaparthy, Srinath↗
DOE OSTI2017

Geometric prepatterning-based tuning of the period doubling onset strain during thin-film wrinkling

Wrinkling of thin films is an easy-to-implement and low-cost technique to fabricate stretch-tunable periodic micro and nanoscale structures. However, the tunability of such structures is often limited by the emergence of an undesirable period-doubled mode at high strains. Predictively tuning the onset strain for period doubling via existing techniques requires one to have extensive knowledge about the nonlinear pattern formation behavior. Herein, a geometric prepatterning-based technique is introduced that can be implemented even with limited system knowledge to predictively delay period doubling. The technique comprises prepatterning the film/base bilayer with a sinusoidal pattern that has the same period as the natural period of the system. This technique has been verified via physical and computational experiments on the polydimethylsiloxane (PDMS)/glass bilayer system. It is observed that the onset strain can be increased from the typical value of 20% for flat films to greater than 30% with a modest prepattern aspect ratio (2·amplitude/period) of 0.15. In addition, finite element simulations reveal that (i) the onset strain increases with increasing prepattern amplitude and (ii) the delaying effect can be captured entirely by the prepattern geometry. Therefore, one can implement this technique even with limited system knowledge, such as material properties or film thickness, by simply replicating pre-existing wrinkled patterns to generate prepatterned bilayers. Furthermore, geometric prepatterning is a practical scheme to increase the operating range of stretch-tunable wrinkle-based devices by at least 50%.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predicting Compliance in an Epidemiological Model: Constructs from Psychological Theory and Research

Vaccination and the alternative behavior, vaccine refusal, are a classic example of manifesting behaviors driven by social norms and norm violations. Establishing how norms emerge, and under what circumstances people choose to violate them are key issues to understand in modeling epidemics. Interactions between individuals can lead to large-scale patterning of behavior (emergent phenomena). As norm violations are revealed through human behavior, drawing on psychological theory and principles to predict those violations is a viable approach for more human-constrained epidemiological models. As an example of the implications at scale, vaccine refusal is correlated with the spread of mis/disinformation about vaccine side-effects. Considering the complexities of network dynamics, the downstream effects means that if even a small group within a population are persuaded against vaccination, there is a reservoir from which disease and disease outbreaks can propagate. This work will attempt to identify those psychological indicators, to define circumstances that predict health behaviors, and identify potentially modifiable antecedents of health behavior, and factors that influence changes toward health protective behaviors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Occupancy schedules learning process through a data mining framework

Building occupancy is a paramount factor in building energy simulations. Specifically, lighting, plug loads, HVAC equipment utilization, fresh air requirements and internal heat gain or loss greatly depends on the level of occupancy within a building. Developing the appropriate methodologies to describe and reproduce the intricate network responsible for human-building interactions are needed. Extrapolation of patterns from big data streams is a powerful analysis technique which will allow for a better understanding of energy usage in buildings. A three-step data mining framework is applied to discover occupancy patterns in office spaces. First, a data set of 16 offices with 10 minute interval occupancy data, over a two year period is mined through a decision tree model which predicts the occupancy presence. Then a rule induction algorithm is used to learn a pruned set of rules on the results from the decision tree model. Finally, a cluster analysis is employed in order to obtain consistent patterns of occupancy schedules. Furthermore, the identified occupancy rules and schedules are representative as four archetypal working profiles that can be used as input to current building energy modeling programs, such as EnergyPlus or IDA-ICE, to investigate impact of occupant presence on design, operation and energy use in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Kensor: Coordinated Intelligence from Co-Located Sensors

Internet of Things (IoT) is becoming more pervasive in many installations, including homes, manufacturing plants, and industrial facilities of all kinds. The data that IoT produces is a reflection of usual behavior such as daily routines and scheduled tasks, but also from unexpected behavior due to unintentional or undesirable abnormalities. Here, we focus on achieving coordinated intelligence about normal and abnormal phenomena from multiple sensors that are geographically colocated in close proximity, monitoring and controlling a set of co-located devices. Given a set of co-located sensors, we seek an intelligent approach that would automatically determine the “normal” patterns of behaviors among the correlated sensors. After normal behavior is extracted, later monitoring should detect any deviant variations over time. An example application is an entry monitoring and alert system for facilities such as nuclear reactors, where badge readers, door locks, lights, weight trackers and other co-located sensors at the entry point are collectively tracked. To address this problem, we identify the possible solution approach that can be used to solve its different variants. The implemented model is developed as a combination of rules and Markov Chain methods.

Kotevska, Olivera↗
DOE OSTI2017

Superconductor to weak-insulator transitions in disordered tantalum nitride films

Here, we study the two-dimensional superconductor-insulator transition (SIT) in thin films of tantalum nitride. At zero magnetic field, films can be disorder-tuned across the SIT by adjusting thickness and film stoichiometry; insulating films exhibit classical hopping transport. Superconducting films exhibit a magnetic-field-tuned SIT, whose insulating ground state at high field appears to be a quantum-corrected metal. Scaling behavior at the field-tuned SIT shows classical percolation critical exponents zν ≈ 1.3, with a corresponding critical field H c << H c2 , the upper critical field. The Hall effect exhibits a crossing point near H c , but with a nonuniversal critical value ρ c xy comparable to the normal-state Hall resistivity. We propose that high-carrier-density metals will always exhibit this pattern of behavior at the boundary between superconducting and (trivially) insulating ground states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Anticipating Technical Expertise and Capability Evolution in Research Communities Using Dynamic Graph Transformers

The ability to anticipate global technical expertise and capability evolution trends is essential for national and global security, especially in safety-critical domains such as nuclear nonproliferation (NN) and rapidly emerging fields like artificial intelligence (AI). Here, in this work, we extend traditional statistical relational learning approaches (e.g., link prediction in collaboration networks) and formulate a problem of anticipating technical expertise and capability evolution using dynamic heterogeneous graph representations. We develop novel capabilities to forecast collaboration patterns, authorship behavior, and technical capability evolution at different granularities (e.g., scientist and institution levels) in two distinct research fields. We implement a dynamic graph transformer (DGT) neural architecture, which pushes the state-of-the-art graph neural network models by: 1) forecasting heterogeneous (rather than homogeneous) nodes and edges; and 2) relying on both discrete- and continuous-time inputs. We demonstrate that our DGT models predict collaboration, partnership, and expertise patterns with 0.26, 0.73, and 0.53 mean reciprocal rank values for AI and 0.48, 0.93, and 0.22 for NN domains. DGT model performance exceeds the best-performing static graph baseline models by 30%–80% across AI and NN domains. Our findings demonstrate that DGT models boost inductive task performance when previously unseen nodes appear in the test data for the domains with emerging collaboration patterns (e.g., AI). Specifically, models accurately predict which established scientists will collaborate with early career scientists and vice versa in the AI domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Space telescope and optical reverberation mapping project. IV. Anomalous behavior of the broad ultraviolet emission lines in NGC 5548

During an intensive Hubble Space Telescope (HST) Cosmic Origins Spectrograph (COS) UV monitoring campaign of the Seyfert 1 galaxy NGC 5548 performed from 2014 February to July, the normally highly correlated far UV continuum and broad emission line variations decorrelated for ∼60–70 days, starting ∼75 days after the first HST/COS observation. Following this anomalous state, the flux and variability of the broad emission lines returned to a more normal state. This transient behavior, characterized by significant deficits in flux and equivalent width of the strong broad UV emission lines, is the first of its kind to be unambiguously identified in an active galactic nucleus reverberation mapping campaign. The largest corresponding emission line flux deficits occurred for the high ionization, collisionally excited lines C iv and Si iv(+O iv]), and also He ii(+O iii]), while the anomaly in Lyα was substantially smaller. This pattern of behavior indicates a depletion in the flux of photons with E{sub ph}>54 eV relative to those near 13.6 eV. We suggest two plausible mechanisms for the observed behavior: (i) temporary obscuration of the ionizing continuum incident upon broad line region (BLR) clouds by a moving veil of material lying between the inner accretion disk and inner (BLR), perhaps resulting from an episodic ejection of material from the disk, or (ii) a temporary change in the intrinsic ionizing continuum spectral energy distribution resulting in a deficit of ionizing photons with energies >54 eV, possibly due to a transient restructuring of the Comptonizing atmosphere above the disk. Current evidence appears to favor the latter explanation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Full-flow-regime storage-streamflow correlation patterns provide insights into hydrologic functioning over the continental US

Interannual changes in low, median, and high regimes of streamflow have important implications for flood control, irrigation, and ecologic and human health. The Gravity Recovery and Climate Experiment (GRACE) satellites record global terrestrial water storage anomalies (TWSA), providing an opportunity to observe, interpret, and potentially utilize the complex relationships between storage and full-flow-regime streamflow. Here we show that utilizable storage-streamflow correlations exist throughout vastly different climates in the continental US (CONUS) across low- to high-flow regimes. A panoramic framework, the storage-streamflow correlation spectrum (SSCS), is proposed to examine macroscopic gradients in these relationships. SSCS helps form, corroborate or reject hypotheses about basin hydrologic behaviors. SSCS patterns vary greatly over CONUS with climate, land surface, and geologic conditions. Data mining analysis suggests that for catchments with hydrologic settings that favor storage over runoff, e.g., a large fraction of precipitation as snow, thick and highly-permeable permeable soil, SSCS values tend to be high. Based on our results, we form the hypotheses that groundwater flow dominates streamflows in South-eastern CONUS and Great Plains, while thin soils in a belt along the Appalachian Plateau impose a limit on water storage. SSCS also suggests shallow water table caused by high-bulk density soil and flat terrain induces rapid runoff in several regions. Our results highlight the importance of subsurface properties and groundwater flow in capturing flood and drought. Finally, we propose that SSCS can be used as a fundamental hydrologic signature to constrain models and to provide insights that lead us to better understand hydrologic functioning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Computational investigation on the structures and electronic properties of the nanosized rhenium clusters

Here, the stable equilibrium geometries, relative stabilities, and electronic and magnetic characteristics of Re n (n = 2–16) clusters were investigated by density functional theory method. The calculated fragmentation energies and second-order differences of energies exhibited interestingly that the stabilities of Re n (n = 2–16) clusters show a dramatic odd-even alternative behavior of the cluster size n: with the even-numbered Ren clusters being obviously more stable than their neighboring odd-numbered Re n clusters (beside n = 11). Simultaneously, the calculated HOMO-LUMO gaps of Re n (n = 6–16) display an oscillatory feature at large-sized Ren clusters. From the calculated magnetic moments and growth behaviors of Rhenium clusters, the magnetic Re 6 unit can be seen as the building block for the novel magnetic cluster-assembled nanomaterial. Such calculated results are in good agreement with the available experimental measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2026

2022 Bull E-Bike Pilot Program Study

In 2022, the City of Durham conducted an e-bike pilot program study to learn more about how electric bikes (e-bikes) could improve the transportation experience in the "Bull City" (a.k.a., Durham, North Carolina). The study used pedal-assist e-bikes, which feature an electric motor and battery to help power the bike. The motor amplifies the power behind each pedal stroke, augmenting the energy you put into the bike. #### Data Collection Agency The City of Durham's Transportation Department conducted the study. #### Survey Methodology Program participants used electric-assist e-bikes for at least 4 weeks between August and November 2022 in exchange for sharing information about their experiences, including tracking their travel via a smartphone app. In addition to the e-bike, participants received maintenance support along with a helmet, bike lock, and other accessories. Data collection was enabled by the [NLR OpenPATH platform](https://www.nlr.gov/transportation/openpath.html). #### Survey Records and Data Survey records include a total of 76 participants. The dataset contains 3 months of partially automated travel diaries, combining sensed and surveyed travel behavior data—patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from participants. The number of total trips was 6,488, the number of e-bike trips was 2,183, and the number of e-bike miles traveled was 5,450.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

2021–2022 Can Do Colorado E-Bike Full-Scale Pilot Program Study

In 2021–2022, the Colorado Energy Office conducted a full-scale pilot program study on e-bike usage as part of the Can Do Colorado initiative, providing e-bikes to low-income participants across the state. A [2020 mini pilot program study](https://www.nlr.gov/transportation/secure-transportation-data/tsdc-2020-can-do-colorado-e-bike-pilot-program.html) informed the full-scale study. Both studies used pedal-assist e-bikes, which feature an electric motor and battery to help power the bike. The motor amplifies the power behind each pedal stroke, augmenting the energy you put into the bike. #### Data Collection Agency The Colorado Energy Office conducted the study in partnership with local organizations in Adams and Broomfield counties (Smart Commute Metro North), Boulder (Community Cycles), Durango (Four Corners Office for Resource Efficiency), Fort Collins (City of Fort Collins), Pueblo (Pueblo County), and Vail (Town of Vail). #### Survey Methodology Program participants received an e-bike and accessories at no cost and manually submitted travel data and feedback via the CanBikeCO smartphone app. Developed in partnership with NLR, the app used a customized version of the open-source [NLR OpenPATH platform](https://www.nlr.gov/transportation/openpath.html). #### Survey Records and Data Survey records include 170 participants. The six datasets contain up to 18 months of partially automated travel diaries, combining sensed and surveyed travel behavior data—patterns of multimodal, end-to-end, individual human mobility—as well as demographic information from participants. The number of e-bike trips and e-bike miles traveled per location are 1,560 and 4,179 for Adams and Broomfield counties; 8,481 and 27,000 for Boulder; 2,815 and 6,307 for Durango; 3,483 and 7,080 for Fort Collins; 4,022 and 14,887 for Pueblo, and 1,206 and 3,3361 for Vail.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗