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At least 37 records · Page 2

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗

Changes in Climate and Its Effect on Timing of Snowmelt and Intensity-Duration-Frequency Curves

Snow is a critical water resource for much of the U.S. and failure to account for changes in climate could deleteriously impact military assets. In this study, we produced historical and future snow trends through modeling at three military sites (in Washington, Colorado, and North Dakota) and the Western U.S. For selected rivers, we performed seasonal trend analysis of discharge extremes. We calculated flood frequency curves and estimated the probability of occurrence of future annual maximum daily rainfall depths. Additionally, we generated intensity-duration-frequency curves (IDF) to find rainfall intensities at several return levels. Generally, our results showed a decreasing trend in historical and future snow duration, rain-on-snow events, and snowmelt runoff. This decreasing trend in snowpack could reduce water resources. A statistically significant increase in maximum streamflow for most rivers at the Washington and North Dakota sites occurred for several months of the year. In Colorado, only a few months indicated such an increase. Future IDF curves for Colorado and North Dakota indicated a slight increase in rainfall intensity whereas the Washington site had about a twofold increase. This increase in rainfall intensity could result in major flood events, demonstrating the importance of accounting for climate changes in infrastructure planning.

58 GEOSCIENCES↗

Persistent global greening over the last four decades using novel long-term vegetation index data with enhanced temporal consistency

Advanced Very High-Resolution Radiometer (AVHRR) satellite observations have provided the longest global daily records from 1980s, but the remaining temporal inconsistency in vegetation index datasets has hindered reliable assessment of vegetation greenness trends. To tackle this, we generated novel global long-term Normalized Difference Vegetation Index (NDVI) and Near-Infrared Reflectance of vegetation (NIRv) datasets derived from AVHRR and Moderate Resolution Imaging Spectroradiometer (MODIS). We addressed residual temporal inconsistency through three-step post processing including cross-sensor calibration among AVHRR sensors, orbital drifting correction for AVHRR sensors, and machine learning-based harmonization between AVHRR and MODIS. After applying each processing step, we confirmed the enhanced temporal consistency in terms of detrended anomaly, trend and interannual variability of NDVI and NIRv at calibration sites. Our refined NDVI and NIRv datasets showed a persistent global greening trend over the last four decades (NDVI: 0.0008 yr -1 ; NIRv: 0.0003 yr -1 ), contrasting with those without the three processing steps that showed rapid greening trends before 2000 (NDVI: 0.0017 yr -1 ; NIRv: 0.0008 yr -1 ) and weakened greening trends after 2000 (NDVI: 0.0004 yr -1 ; NIRv: 0.0001 yr -1 ). These findings highlight the importance of minimizing temporal inconsistency in long-term vegetation index datasets, which can support more reliable trend analysis in global vegetation response to climate changes.

54 ENVIRONMENTAL SCIENCES↗

Multi-Scale Temporal Patterns in Stream Biogeochemistry Indicate Linked Permafrost and Ecological Dynamics of Boreal Catchments

Temporal patterns in stream chemistry provide integrated signals describing the hydrological and ecological state of whole catchments. However, stream chemistry integrates multi-scale signals of processes occurring in both the catchment and stream. Deconvoluting these signals could identify mechanisms of solute transport and transformation and provide a basis for monitoring ecosystem change. Here, we applied trend analysis, wavelet decomposition, multivariate autoregressive state-space modeling, and analysis of concentration-discharge relationships to assess temporal patterns in high-frequency (15 min) stream chemistry from permafrost-influenced boreal catchments in Interior Alaska at diel, storm, and seasonal time scales. We compared catchments that varied in spatial extent of permafrost to identify characteristic biogeochemical signals. Catchments with higher spatial extents of permafrost were characterized by increasing nitrate concentration through the thaw season, an abrupt increase in nitrate and fluorescent dissolved organic matter (fDOM) and declining conductivity in late summer, and flushing of nitrate and fDOM during summer rainstorms. In contrast, these patterns were absent, of lower magnitude, or reversed in catchments with lower permafrost extent. Solute dynamics revealed a positive influence of permafrost on fDOM export and the role of shallow, seasonally dynamic flowpaths in delivering solutes from high-permafrost catchments to streams. Lower spatial extent of permafrost resulted in static delivery of nitrate and limited transport of fDOM to streams. Shifts in concentration-discharge relationships and seasonal trends in stream chemistry toward less temporally dynamic patterns might therefore indicate reorganized catchment hydrology and biogeochemistry due to permafrost thaw.

54 ENVIRONMENTAL SCIENCES↗

Advancing Solar Innovation for Low and Moderate-Income Households (Final Technical Report)

The overarching goal of this project was to deepen the understanding of the social and economic aspects of solar adoption, with a specific eye towards any pathways or barriers that could be identified that directly impact low and moderate-income households. Specific objectives included (1) identifying and assessing significant non-economic barriers that complicate the ability of LMI households to adopt and benefit from solar, even under scenarios with low economic barriers; (2) assessing the differential ability of groups to benefit from solar adoption based on their ability to invest in different solar innovations; (3) explaining why some LMI communities nonetheless experience significantly higher rates of solar adoption and benefit than others; (4) developing a methodological model for generating data addressing key issues to the project; and (5) designing and developing an interactive web portal that aggregates existing datasets, provides researchers trend analysis capabilities, standardizes project protocols for other states and communities; provides the opportunities for researchers using the same protocol in other communities to upload their results; and engages with the general public by providing them the ability to upload their own perspectives and stories of solar technology adoption. Through a common framework for conducting semi-structured field interviews. In partnership with cooperative extension services, in conjunction with survey research and the aggregation of existing solar adoption datasets, this study has identified that currently ,there is a strong values alignment and knowledge access challenge that continues to affect solar adoption. Participants in this study – many of whom are either low or moderate-income and/or live in underserved rural communities do not believe solar is an option where they live or believe solar is appropriate for their lifestyle. This perception challenge is further exacerbated by the absolute dearth of adopters in most communities and a total lack of local marketing for solar energy. What marketing that does exist is geared towards audiences other than those in the participant's community, reinforcing a perception that 22% of survey respondents (n = 1,551) have: that solar energy is not meant for them and their community. Overcoming these serious human challenges pertaining to knowledge and marketing are critical to reducing the customer acquisition costs incurred amongst LMI communities and especially those in rural America where the opportunities solar provides to increase local energy resilience, security, all while engaging in personal stewardship of the planet could align with local values. Community-Based Social Marketing, built in partnership with community leaders and geared towards meeting local visions of ideal life, is a near term opportunity to bridge the gap between local priorities and national market and policy imperatives for solar while moving towards the administration's goals for renewable energy as part of a just and equitable decarbonization program. The tools and methods developed for this study can serve as a template for identifying other specific local challenges for solar adoption in other state, and provide the opportunity for a common data framework for understanding system-wide trends and barriers to achieving uptake of residential solar in communities that may, ultimately, benefit the most from the technology.

14 SOLAR ENERGY↗

Consistent thermodynamic properties for alicyclic components of jet fuels: Experimental data, estimation methods, and homologous series trends

Alkylcycloalkanes represent a significant fraction of jet fuel components. An evaluation of their thermodynamic properties, enthalpies of formation in liquid and gas phases and enthalpies of vaporization, was conducted. A combination of available experimental data, up-to-date group-contribution methods, high-level quantum-chemical calculations, and homologous series trends was used to identify outliers and to recommend the most reliable values. The group-contribution approach was found to work well for the enthalpies of vaporization. Its performance for the enthalpies of formation in the liquid and gas phases was found to be substantially less effective, especially considering notable differences in this property among stereoisomers. Computationally affordable high-level ab initio results and homologous series trend analysis appeared more reliable. In conclusion, the recommended property values for 212 individual compounds and their isomeric mixtures were provided.

09 BIOMASS FUELS↗

Examination of Global Midlatitude Atmospheric River Lifecycles Using an Object-Oriented Methodology

Tracking atmospheric rivers (ARs) across their lifecycles is a field of recent interest with a multitude of emerging methodologies. The CONNected-objECT (CONNECT) algorithm is adapted for the tracking of global midlatitude AR lifecycles and associated precipitation by implementing a seeded region growing segmentation algorithm, creating the AR-CONNECT algorithm. To facilitate the permissiveness of the methodology, AR-CONNECT is without hard-coded geometric criteria yet is still shown to extract synoptic-scale elongated objects >99.99% of the time. One of the consequences of the methodology is the ability to occasionally track atmospheric water vapor anomalies before evolving into AR geometries, effectively tracking AR genesis further back than other studies. With the aid of subdaily satellite-derived rain data, we investigate the climatology, trends, and patterns of AR lifecycles from 1983–2016 and compare with other AR tracking studies. We find that AR frequency, genesis, and terminus locations are in generally good agreement with other AR tracking methodologies, though with key differences, and that AR frequencies in each hemisphere are determined by the number of AR hotspots. Furthermore, we uncover evidence that certain AR characteristics, such as frequency, areal extent, and duration, show evidence of increasing trends. Midlatitude precipitation uncovered by AR-CONNECT shows contributions up to 50% over land and 65% over the ocean. Trend analysis of AR precipitation shows an increase in precipitation associated with ARs propagated by the Southern Jet Stream and ARs that traverse over the Sahara Desert, among others, but is determined not to be a driver of changes in global precipitation.

54 ENVIRONMENTAL SCIENCES↗

Two decades of fumigation data from the Soybean Free Air Concentration Enrichment facility

Abstract The Soybean Free Air Concentration Enrichment (SoyFACE) facility is the longest running open-air carbon dioxide and ozone enrichment facility in the world. For over two decades, soybean, maize, and other crops have been exposed to the elevated carbon dioxide and ozone concentrations anticipated for late this century. The facility, located in East Central Illinois, USA, exposes crops to different atmospheric concentrations in replicated octagonal ~280 m 2 Free Air Concentration Enrichment (FACE) treatment plots. Each FACE plot is paired with an untreated control (ambient) plot. The experiment provides important ground truth data for predicting future crop productivity. Fumigation data from SoyFACE were collected every four seconds throughout each growing season for over two decades. Here, we organize, quality control, and collate 20 years of data to facilitate trend analysis and crop modeling efforts. This paper provides the rationale for and a description of the SoyFACE experiments, along with a summary of the fumigation data and collation process, weather and ambient data collection procedures, and explanations of air pollution metrics and calculations.

60 APPLIED LIFE SCIENCES↗

The crucial role of diagnostics in achieving ignition on the National Ignition Facility (NIF)

Well over 100 diagnostics can operate on the National Ignition Facility (NIF) as a result of several decades of development on NIF, and before that on Nova, OMEGA, and earlier LLNL lasers. A subset of these have guided the approach to achieving ignition on the NIF in 2022 [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129(7), 075001 (2022)]. Achieving ignition on NIF has required many types of experiments with this core set of diagnostics, some constraining known unknowns and some revealing surprises—arguably unknown unknowns. Early design work realized that the extreme precision required for ignition on NIF would require fine-tuning by experiment, that is, measuring and adjusting known unknowns. Many examples are given where the use of the core set of ignition diagnostics in experimental arrangements called platforms demonstrated control of the key theoretical parameters defined as shape, adiabat, velocity, and mix. The direction of the adjustments to input conditions is found either by trend analysis or, in many cases, by observing from the diagnostic data the direction to make an adjustment. In addition, diagnostics have revealed some unexpected or neglected known issues, which degrade performance, or unexpected issues, unknown unknowns. Some of these factors had been previously considered, but underestimated or difficult to calculate at the time. The overall methodology can be described as a variant of Popper's falsifiability philosophy [K. Popper, The Logic of Scientific Discovery (Hutchinson, 1974)]. This paper summarizes the role of ignition diagnostics in terms of falsification or validation of theory or experimental setup as well as uncovering unexpected issues. The journey to ignition started in the seventies with a 1-µm wavelength laser producing disastrous results. Diagnostics have guided us to the recent multi-decadal goal of demonstrating ignition and burn in the laboratory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Deployment of Traditional and Hybrid Machine Learning for Critical Heat Flux Prediction in the CTF Thermal-Hydraulics Code

Critical heat flux (CHF) marks the transition from nucleate to film boiling, where heat transfer to the working fluid can rapidly deteriorate. Accurate CHF prediction is essential for efficiency, safety, and preventing equipment damage, particularly in nuclear reactors. Although widely used, empirical correlations frequently exhibit discrepancies when compared to experimental data, limiting their reliability in diverse operational conditions. Traditional machine learning (ML) approaches have demonstrated potential for CHF prediction but often suffer from limited interpretability, data scarcity, and insufficient knowledge of physical principles. Hybrid model approaches, which combine data-driven ML with base models, mitigate these concerns by incorporating prior knowledge of the domain. This study integrates an externally trained purely data-driven ML model and two hybrid models (using the Biasi and Bowring CHF correlations) within the CTF subchannel code via a custom Fortran framework. Performance was evaluated using two validation cases: a subset of the Nuclear Regulatory Commission (NRC) CHF database and the Bennett dryout experiments. In both cases, the hybrid models demonstrated significantly lower error metrics compared to conventional empirical correlations, with the best models often reducing relative error by about 5 percentage points. The pure ML model achieved comparable accuracy, outperforming the hybrid Biasi model in the NRC test case (3.3% versus 5.5% relative error) but exhibiting slightly higher error against the hybrid Bowring model in the Bennett test case (7.7% versus 6.1%). Trend analysis of error parity indicated that ML-based models reduced the tendency for CHF overprediction, improving overall accuracy. These results demonstrate that ML-based CHF models can be effectively integrated into subchannel codes and could potentially increase performance compared to conventional methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

2017 Puget Sound Regional Travel Study

# 2017 Puget Sound Regional Travel Study The 2017 Puget Sound Regional Travel Study collected household- and person-level activity and travel pattern information from residents throughout the Puget Sound Regional Council's four-county region in Washington State. It followed the [2014-2015 Puget Sound Regional Travel Study](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-puget-sound-travel-study), starting a planned six-year data collection that includes 2019 and 2021. The multiyear program's goal is to maintain an updated source of household travel behavior data that: - Supports modeling and planning needs - Facilitates trend analysis over time - Allows for regular study design updates to integrate evolving data collection methods and emerging travel behaviors and transportation issues. ## Data Collection Agency The Puget Sound Regional Council conducted the study. ## Methodology The 2017 study featured both the design and administration of a one-day household travel diary (approximately 80% of households before data cleaning) and a seven-day smartphone global positioning system (GPS) diary (approximately 20% of households before data cleaning). It combined data collection methods, including smartphone, online, and telephone. The survey design included several stages to recruit and collect data about households, their members, and their travel behaviors during the assigned travel period. ## Survey Records Survey records include a total of 6,254 participants. ## More Information For more information, see the [survey documentation](https://www.nrel.gov/media/docs/libraries/tsdc/zip/tsdc-2017-puget-sound-travel-study-documentation.zip?sfvrsn=45991f2f_1). ## Transportation Data The data set contains a demographic and socioeconomic composition of 6,254 people from 3,285 households in the Puget Sound regional area, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged over 508 thousand vehicle miles of travel by participants during 52,492 trips. Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2017 Puget Sound Regional Travel Study

# 2017 Puget Sound Regional Travel Study The 2017 Puget Sound Regional Travel Study collected household- and person-level activity and travel pattern information from residents throughout the Puget Sound Regional Council's four-county region in Washington State. It followed the [2014-2015 Puget Sound Regional Travel Study](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-puget-sound-travel-study), starting a planned six-year data collection that includes 2019 and 2021. The multiyear program's goal is to maintain an updated source of household travel behavior data that: - Supports modeling and planning needs - Facilitates trend analysis over time - Allows for regular study design updates to integrate evolving data collection methods and emerging travel behaviors and transportation issues. ## Data Collection Agency The Puget Sound Regional Council conducted the study. ## Methodology The 2017 study featured both the design and administration of a one-day household travel diary (approximately 80% of households before data cleaning) and a seven-day smartphone global positioning system (GPS) diary (approximately 20% of households before data cleaning). It combined data collection methods, including smartphone, online, and telephone. The survey design included several stages to recruit and collect data about households, their members, and their travel behaviors during the assigned travel period. ## Survey Records Survey records include a total of 6,254 participants. ## More Information For more information, see the [survey documentation](https://www.nrel.gov/media/docs/libraries/tsdc/zip/tsdc-2017-puget-sound-travel-study-documentation.zip?sfvrsn=45991f2f_1). ## Transportation Data The data set contains a demographic and socioeconomic composition of 6,254 people from 3,285 households in the Puget Sound regional area, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged over 508 thousand vehicle miles of travel by participants during 52,492 trips. Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2017 Puget Sound Regional Travel Study

# 2017 Puget Sound Regional Travel Study The 2017 Puget Sound Regional Travel Study collected household- and person-level activity and travel pattern information from residents throughout the Puget Sound Regional Council's four-county region in Washington State. It followed the [2014-2015 Puget Sound Regional Travel Study](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-puget-sound-travel-study), starting a planned six-year data collection that includes 2019 and 2021. The multiyear program's goal is to maintain an updated source of household travel behavior data that: - Supports modeling and planning needs - Facilitates trend analysis over time - Allows for regular study design updates to integrate evolving data collection methods and emerging travel behaviors and transportation issues. ## Data Collection Agency The Puget Sound Regional Council conducted the study. ## Methodology The 2017 study featured both the design and administration of a one-day household travel diary (approximately 80% of households before data cleaning) and a seven-day smartphone global positioning system (GPS) diary (approximately 20% of households before data cleaning). It combined data collection methods, including smartphone, online, and telephone. The survey design included several stages to recruit and collect data about households, their members, and their travel behaviors during the assigned travel period. ## Survey Records Survey records include a total of 6,254 participants. ## More Information For more information, see the [survey documentation](https://www.nrel.gov/media/docs/libraries/tsdc/zip/tsdc-2017-puget-sound-travel-study-documentation.zip?sfvrsn=45991f2f_1). ## Transportation Data The data set contains a demographic and socioeconomic composition of 6,254 people from 3,285 households in the Puget Sound regional area, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged over 508 thousand vehicle miles of travel by participants during 52,492 trips. Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2017 Puget Sound Regional Travel Study

# 2017 Puget Sound Regional Travel Study The 2017 Puget Sound Regional Travel Study collected household- and person-level activity and travel pattern information from residents throughout the Puget Sound Regional Council's four-county region in Washington State. It followed the [2014-2015 Puget Sound Regional Travel Study](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-puget-sound-travel-study), starting a planned six-year data collection that includes 2019 and 2021. The multiyear program's goal is to maintain an updated source of household travel behavior data that: - Supports modeling and planning needs - Facilitates trend analysis over time - Allows for regular study design updates to integrate evolving data collection methods and emerging travel behaviors and transportation issues. ## Data Collection Agency The Puget Sound Regional Council conducted the study. ## Methodology The 2017 study featured both the design and administration of a one-day household travel diary (approximately 80% of households before data cleaning) and a seven-day smartphone global positioning system (GPS) diary (approximately 20% of households before data cleaning). It combined data collection methods, including smartphone, online, and telephone. The survey design included several stages to recruit and collect data about households, their members, and their travel behaviors during the assigned travel period. ## Survey Records Survey records include a total of 6,254 participants. ## More Information For more information, see the [survey documentation](https://www.nrel.gov/media/docs/libraries/tsdc/zip/tsdc-2017-puget-sound-travel-study-documentation.zip?sfvrsn=45991f2f_1). ## Transportation Data The data set contains a demographic and socioeconomic composition of 6,254 people from 3,285 households in the Puget Sound regional area, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged over 508 thousand vehicle miles of travel by participants during 52,492 trips. Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2017 Puget Sound Regional Travel Study

# 2017 Puget Sound Regional Travel Study The 2017 Puget Sound Regional Travel Study collected household- and person-level activity and travel pattern information from residents throughout the Puget Sound Regional Council's four-county region in Washington State. It followed the [2014-2015 Puget Sound Regional Travel Study](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-puget-sound-travel-study), starting a planned six-year data collection that includes 2019 and 2021. The multiyear program's goal is to maintain an updated source of household travel behavior data that: - Supports modeling and planning needs - Facilitates trend analysis over time - Allows for regular study design updates to integrate evolving data collection methods and emerging travel behaviors and transportation issues. ## Data Collection Agency The Puget Sound Regional Council conducted the study. ## Methodology The 2017 study featured both the design and administration of a one-day household travel diary (approximately 80% of households before data cleaning) and a seven-day smartphone global positioning system (GPS) diary (approximately 20% of households before data cleaning). It combined data collection methods, including smartphone, online, and telephone. The survey design included several stages to recruit and collect data about households, their members, and their travel behaviors during the assigned travel period. ## Survey Records Survey records include a total of 6,254 participants. ## More Information For more information, see the [survey documentation](https://www.nrel.gov/media/docs/libraries/tsdc/zip/tsdc-2017-puget-sound-travel-study-documentation.zip?sfvrsn=45991f2f_1). ## Transportation Data The data set contains a demographic and socioeconomic composition of 6,254 people from 3,285 households in the Puget Sound regional area, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged over 508 thousand vehicle miles of travel by participants during 52,492 trips. Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2017 Puget Sound Regional Travel Study

# 2017 Puget Sound Regional Travel Study The 2017 Puget Sound Regional Travel Study collected household- and person-level activity and travel pattern information from residents throughout the Puget Sound Regional Council's four-county region in Washington State. It followed the [2014-2015 Puget Sound Regional Travel Study](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-puget-sound-travel-study), starting a planned six-year data collection that includes 2019 and 2021. The multiyear program's goal is to maintain an updated source of household travel behavior data that: - Supports modeling and planning needs - Facilitates trend analysis over time - Allows for regular study design updates to integrate evolving data collection methods and emerging travel behaviors and transportation issues. ## Data Collection Agency The Puget Sound Regional Council conducted the study. ## Methodology The 2017 study featured both the design and administration of a one-day household travel diary (approximately 80% of households before data cleaning) and a seven-day smartphone global positioning system (GPS) diary (approximately 20% of households before data cleaning). It combined data collection methods, including smartphone, online, and telephone. The survey design included several stages to recruit and collect data about households, their members, and their travel behaviors during the assigned travel period. ## Survey Records Survey records include a total of 6,254 participants. ## More Information For more information, see the [survey documentation](https://www.nrel.gov/media/docs/libraries/tsdc/zip/tsdc-2017-puget-sound-travel-study-documentation.zip?sfvrsn=45991f2f_1). ## Transportation Data The data set contains a demographic and socioeconomic composition of 6,254 people from 3,285 households in the Puget Sound regional area, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged over 508 thousand vehicle miles of travel by participants during 52,492 trips. Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗