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DOE OSTI2021

Updates to the Regional Seismic Travel Time (RSTT) Model: 2. Path-dependent Travel-time Uncertainty

Abstract The regional seismic travel time (RSTT) model and software were developed to improve travel-time prediction accuracy by accounting for three-dimensional crust and upper mantle structure. Travel-time uncertainty estimates are used in the process of associating seismic phases to events and to accurately calculate location uncertainty bounds (i.e. event location error ellipses). We improve on the current distance-dependent uncertainty parameterization for RSTT using a random effects model to estimate slowness (inverse velocity) uncertainty as a mean squared error for each model parameter. The random effects model separates the error between observed slowness and model predicted slowness into bias and random components. The path-specific travel-time uncertainty is calculated by integrating these mean squared errors along a seismic-phase ray path. We demonstrate that event location error ellipses computed for a 90% coverage ellipse metric (used by the Comprehensive Nuclear-Test-Ban Treaty Organization International Data Centre (IDC)), and using the path-specific travel-time uncertainty approach, are more representative (median 82.5% ellipse percentage) of true location error than error ellipses computed using distance-dependent travel-time uncertainties (median 70.1%). We also demonstrate measurable improvement in location uncertainties using the RSTT method compared to the current station correction approach used at the IDC (median 74.3% coverage ellipse).

58 GEOSCIENCES↗

DOE OSTI2021

Do automated vehicle (AV) enthusiasts value travel time differently from cautious travelers? an exploration of travelers’ attitudes towards AV

The anticipation of automated vehicles (AV) has resulted in diverse research topics, including understanding the adoption and usage of this emerging mode. Using attitudinal indicators, this paper identifies prevalent types of attitudes towards AV. It then explores the variation of those attitudes across different demographic groups and quantifies the influence of these attitudes on the preference for AV. The paper uses stated preference survey data collected among respondents of Chicago in 2019. The exploratory factor analysis of the attitudinal indicators identifies four factors, namely 'Cautious Travelers', 'Hedonists', 'Utilitarians', and 'Safety-First'. Next, the paper develops an integrated choice and latent variable model to test the influence of these four types of attitudes on the preference for AV. Finally, the results indicate that the cautious travelers associate higher Value of Travel Time (VOTT) to AV and enthusiasts associate lower VOTT to AV than a base model without such attitudes.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1985

Ocean acoustic tomography - Travel time biases

The travel times of acoustic rays traced through a climatological sound-speed profile are compared with travel times computed through the same profile containing an eddy field. The accuracy of linearizing the relations between the travel time difference and the sound-speed deviation at long ranges is assessed using calculations made for two different eddy fields measured in the eastern Atlantic. Significant nonlinearities are found in some cases, and the relationships of the values of these nonlinearities to the range between source and receiver, to the anomaly size associated with the eddies, and to the positions of the eddies are studied. An analytical model of the nonlinearities is discussed.

Spiesberger, J. L.↗

DOE OSTI2023

Do people spend travel time the way they think they would? a comparative study of generic and trip-specific travel time allocation using hybrid multiple discrete continuous (MDC) framework

Unlike driving alone, public transportation allows one to engage in extraneous activities while traveling – often referred to as travel-based multitasking. Research involving travel-based multitasking often relies on either generic (i.e. not related to an actual trip) or revealed (i.e. related to an executed trip) data. The data collected for this study provided a unique opportunity to compare the generic and trip-specific preferences while traveling on public transportation. To this end, the study develops two integrated choice and latent variable models with multiple discrete-continuous (MDC) kernels to simultaneously model the activity selection and the time allocation for generic and trip-specific data, respectively. According to the results the trip-specific data could identify more nuances in the travel-based multitasking behavior than the generic data. Finally, the heterogeneity identified by the developed models will be helpful for the transit operators in providing appropriate facilities (e.g. internet access, reading lights) along various transit corridors.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Machine Learning Travel Time emulator

This notebook makes seismic phase travel time predictions using machine learning. There are 3 different machine learning models corresponding to the three regimes: local, regional, and teleseismic. After reading in the test data and splitting into the 3 regimes, we use precomputed scalers to scale the input features used to make the travel time predictions. We then load the machine learning models and use them to predict travel times for test data.

Anderson, Gemma↗

DOE OSTI2022

Developing a Consistent Travel-Time Framework for Comparing Three-Dimensional Velocity Models for Seismic Location Accuracy

Abstract Location algorithms have historically relied on simple, one-dimensional (1D) velocity models for fast seismic event locations. 1D models are generally used as travel-time lookup tables, one for each seismic phase, with travel-times pre-calculated for event distance and depth. These travel-time lookup tables are extremely fast to use and this fast computational speed makes them the preferred type of velocity model for operational needs. Higher-dimensional (i.e., three-dimensional—3D) seismic velocity models are becoming readily available and provide more accurate event locations over 1D models. The computational requirements of these 3D models tend to make their operational use prohibitive. Additionally, comparing location accuracy for 3D seismic velocity models tends to be problematic, as each model is determined using different ray-tracing algorithms. Attempting to use a different algorithm than the one used to develop a model usually results in poor travel-time prediction. We demonstrate and test a framework to create first-P and first-S 3D travel-time correction surfaces using an open-source framework ( PCalc + GeoTess , https://www.sandia.gov/salsa3d/software/geotess ) that easily stores 3D travel-time and uncertainty data. This framework produces fast travel-time and uncertainty predictions and overcomes the ray-tracing algorithm hurdle because the lookup tables can be generated using the exact ray-tracing algorithm that is preferred for a model.

3D velocity models↗

DOE OSTI2020

Post-Calibration Uncertainty Analysis for Travel Times at a Naval Weapons Industrial Reserve Plant

The Naval Weapons Industrial Reserve Plant (NWIRP) in McGregor, Texas began manufacturing explosives in 1980 and several hazardous chemicals were discovered in lakes and streams surrounding the site in 1998. Contaminants traveled to local lakes and streams much faster than initially predicted. This research estimated contaminant travel times and identified locations where monitoring wells should be installed to yield the greatest reductions in uncertainties in travel-time predictions. To this end, groundwater and particle-tracking models for NWIRP site were built to predict hydraulic heads and contaminant travel times. Next, parameter (hydraulic conductivities) uncertainties, parameter identifiabilities, observation (hydraulic heads) worth, and predictive (contaminant travel times) uncertainties were quantified. Parameter uncertainties were reduced by up to 92%; a total of 19 of 158 parameters were at least moderately identifiable; travel-time uncertainties were reduced up to 92%. Additionally, travel-time predictions and post-calibration parameter distributions were generated using the null-space Monte Carlo (NSMC) technique. NSMC predicted that conservative tracers exited the flow system within a year, which matches with field data. Finally, an observations-worth analysis found that additional 11 more measurements would reduce travel-time uncertainties by factors from 1.04 to 4.3 over existing data if monitoring wells were installed at the suggested locations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

NASA NTRS2009

Implementation and Comparison of Acoustic Travel-Time Measurement Procedures for the Helioseismic and Magnetic Imager Time-Distance Helioseismology Pipeline

The Helioseismic and Magnetic Imager (HMI) instrument on board the Solar Dynamics Observatory (SDO) satellite is designed to produce high-resolution Doppler velocity maps of oscillations at the solar surface with high temporal cadence. To take advantage of these high-quality oscillation data, a time-distance helioseismology pipeline has been implemented at the Joint Science Operations Center (JSOC) at Stanford University. The aim of this pipeline is to generate maps of acoustic travel times from oscillations on the solar surface, and to infer subsurface 3D flow velocities and sound-speed perturbations. The wave travel times are measured from cross covariances of the observed solar oscillation signals. For implementation into the pipeline we have investigated three different travel-time definitions developed in time-distance helioseismology: a Gabor wavelet fitting (Kosovichev and Duvall, 1997), a minimization relative to a reference cross-covariance function (Gizon and Birch, 2002), and a linearized version of the minimization method (Gizon and Birch, 2004). Using Doppler velocity data from the Michelson Doppler Imager (MDI) instrument on board SOHO, we tested and compared these definitions for the mean and difference travel-time perturbations measured from reciprocal signals. Although all three procedures return similar travel times in a quiet Sun region, the method of Gizon and Birch (2004) gives travel times that are significantly different from the others in a magnetic (active) region. Thus, for the pipeline implementation we chose the procedures of Kosovichev and Duvall (1997) and Gizon and Birch (2002). We investigated the relationships among these three travel-time definitions, their sensitivities to fitting parameters, and estimated the random errors they produce

Couvidat, S.↗

NASA NTRS2012

Systematic Center-To-Limb Variation in Measured Helioseismic Travel Times and Its Effect on Inferences of Solar Interior Meridional Flows

We report on a systematic center-to-limb variation in measured helioseismic travel times, which must be taken into account for an accurate determination of solar interior meridional flows. The systematic variation, found in time-distance helioseismology analysis using SDO/HMI and SDO/AIA observations, is different in both travel-time magnitude and variation trend for different observables. It is not clear what causes this systematic effect. Subtracting the longitude-dependent east-west travel times, obtained along the equatorial area, from the latitude-dependent north-south travel times, obtained along the central meridian area, gives remarkably similar results for different observables. We suggest this as an effective procedure for removing the systematic center-to-limb variation. The subsurface meridional flows obtained from inversion of the corrected travel times are approximately 10 m s−1 slower than those obtained without removing the systematic effect. The detected center-to-limb variation may have important implications in the derivation of meridional flows in the deep interior and needs to be better understood.

Sun: oscillations↗

DOE OSTI2020

Updates to the Regional Seismic Travel Time (RSTT) Model: 1. Tomography

Abstract A function of global monitoring of nuclear explosions is the development of Earth models for predicting seismic travel times for more accurate calculation of event locations. Most monitoring agencies rely on fast, distance-dependent one-dimensional (1D) Earth models to calculate seismic event locations quickly and in near real-time. RSTT (Regional Seismic Travel Time) is a seismic velocity model and computer software package that captures the major effects of three-dimensional crust and upper mantle structure on regional seismic travel times, while still allowing for fast prediction speed (milliseconds). We describe updates to the RSTT model using a refined data set of regional phases (i.e., Pn, Pg, Sn, Lg) using the Bayesloc relative relocation algorithm. The tomographic inversion shown here acts to refine the previous RSTT public model ( rstt201404um ) and displays significant features related to areas of global tectonic complexity as well as further reduction in arrival residual values. Validation of the updated RSTT model demonstrates significant reduction in median epicenter mislocation (15.3 km) using all regional phases compared to the iasp91 1D model (22.1 km) as well as to the current station correction approach used at the Comprehensive Nuclear-Test-Ban Treaty Organization International Data Centre (18.9 km).

58 GEOSCIENCES↗

NASA NTRS2010

Implementation and Comparison of Acoustic Travel-Time Measurement Procedures for the Solar Dynamics Observatory-Helioseismic and Magnetic Imager Time-Distance Helioseismology Pipeline

The Helioseismic and Magnetic Imager (HMI) instrument onboard the Solar Dynamics Observatory (SDO) satellite is designed to produce high-resolution Doppler-velocity maps of oscillations at the solar surface with high temporal cadence. To take advantage of these high-quality oscillation data, a time - distance helioseismology pipeline (Zhao et al., Solar Phys. submitted, 2010) has been implemented at the Joint Science Operations Center (JSOC) at Stanford University. The aim of this pipeline is to generate maps of acoustic travel times from oscillations on the solar surface, and to infer subsurface 3D flow velocities and sound-speed perturbations. The wave travel times are measured from cross-covariances of the observed solar oscillation signals. For implementation into the pipeline we have investigated three different travel-time definitions developed in time - distance helioseismology: a Gabor-wavelet fitting (Kosovichev and Duvall, SCORE'96: Solar Convection and Oscillations and Their Relationship, ASSL, Dordrecht, 241, 1997), a minimization relative to a reference cross-covariance function (Gizon and Birch, Astrophys. J. 571, 966, 2002), and a linearized version of the minimization method (Gizon and Birch, Astrophys. J. 614, 472, 2004). Using Doppler-velocity data from the Michelson Doppler Imager (MDI) instrument onboard SOHO, we tested and compared these definitions for the mean and difference traveltime perturbations measured from reciprocal signals. Although all three procedures return similar travel times in a quiet-Sun region, the method of Gizon and Birch (Astrophys. J. 614, 472, 2004) gives travel times that are significantly different from the others in a magnetic (active) region. Thus, for the pipeline implementation we chose the procedures of Kosovichev and Duvall (SCORE'96: Solar Convection and Oscillations and Their Relationship, ASSL, Dordrecht, 241, 1997) and Gizon and Birch (Astrophys. J. 571, 966, 2002). We investigated the relationships among these three travel-time definitions, their sensitivities to fitting parameters, and estimated the random errors that they produce.

HMI↗

NASA NTRS1975

Extremal inversion of lunar travel time data

The tau method, developed by Bessonova et al. (1974), of inversion of travel times is applied to lunar P-wave travel time data to find limits on the velocity structure of the moon. Tau is the singular solution to the Clairaut equation. Models with low-velocity zones, with low-velocity zones at differing depths, and without low-velocity zones, were found to be consistent with data and within the determined limits. Models with and without a discontinuity at about 25-km depth have been found which agree with all travel time data to within two standard deviations. In other words, the existence of the discontinuity and its size and location have not been uniquely resolved. Models with low-velocity channels are also possible.

Burkhard, N.↗

DOE OSTI2023

Crustal Scale Travel Time Prediction with the SALSA3D Framework and Machine Learning

The SALSA3D project aims to improve our models used in travel time prediction. The current version uses tomographic modeling for propagation through the Earth’s mantle because of the large number (order of millions) of observations of seismic phases which primarily traverse the Earth’s mantle and the ability to pose the travel time problem as a set of linear equations. However, all seismic rays traverse the crust to reach receivers at the surface and therefore models of propagation through the crust are required. Therefore, the primary motivation for this study is to explore how to increase the scope of the SALSA3D project to phases which travel primarily through the crust. In this report, we evaluate new, machine learning based and physics-based methods to model these travel times for integration into the SALSA3D framework. Our results suggest that using our existing physics-based travel time tomography method is a viable approach for the regional to global scale, but better predictive capabilities can be achieved through a neural network trained on the region of interest for near-regional offsets. We suggest future iterations of SALSA3D should incorporate machine learning tools such as Physics-Informed Neural Networks or Bayesian Neural Networks.

58 GEOSCIENCES↗

DOE OSTI2023

Estimating Arctic Ocean Acoustic Travel Times Using an Earth System Model

Abstract The hydroacoustic environment of a rapidly warming Arctic Ocean will be impacted by interconnected changes in the physical environment and increased human activity. Previous acoustic calculations will need to be updated to reflect current and future conditions. Earth System Models are important tools for making projections of changes in a wide range of physical processes under future climates. We present a comparison of Arctic acoustic travel times based on output from the Department of Energy's Energy Exascale Earth System Model with measured travel times from the 2016–2017 Canada Basin Acoustic Propagation Experiment and with travel times predicted by empirical temperature and salinity observations. This comparison allows us to test the impact of changes in Arctic sound speed profiles on acoustic travel times and connects Arctic hydroacoustics with the changing Arctic environment as described by a climate model.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Travel Time to Radiation Oncology Facilities in the United States and the Influence of Certificate of Need Policies

Radiation therapy often requires weeks of daily treatment making travel distance a known barrier to care. However, the full extent and variability of travel burden, defined by travel time, across the nation is poorly understood. Additionally, some states restrict radiation oncology (RO) services through Certificate of Need (CON) policies, but it is unknown how this affects travel times to care. Therefore, we aim to evaluate travel times to US RO facilities and assess the association with CON policies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

A Spatial-Temporal Analysis of Travel Time Gap and Inequality between Public Transportation and Personal Vehicles

The increased use of personal vehicles presents environmental challenges, prompting the exploration of public transportation as an affordable, eco-friendly alternative. However, obstacles like fixed schedules, limited routes, and extended travel times impede widespread adoption. This study investigates the temporal evolution of spatial inequality in the travel time gap between public transportation and personal vehicles, reflecting disparities across states and time periods. Analyzing Census Transportation Planning Program data for six northeastern states in 2010 and 2016 reveals no significant increase in the travel time gap, but notable growth in inequality in a few urban and disadvantaged communities. Comprehending these trends is vital for fostering equitable advancements in transportation infrastructure and enhancing public transportation competitiveness.

Pan, Melrose↗

NASA NTRS1991

Joint inversion of shear wave travel time residuals and geoid and depth anomalies for long-wavelength variations in upper mantle temperature and composition along the Mid-Atlantic Ridge

Measurements were carried out for SS-S differential travel time residuals for nearly 500 paths crossing the northern Mid-Atlantic Ridge, assuming that the residuals are dominated by contributions from the upper mantle near the surface bounce point of the reflected phase SS. Results indicate that the SS-S travel time residuals decrease linearly with square root of age, to an age of 80-100 Ma, in general agreement with the plate cooling model. A joint inversion was formulated of travel time residuals and geoid and bathymetric anomalies for lateral variation in the upper mantle temperature and composition. The preferred inversion solutions were found to have variations in upper mantle temperature along the Mid-Atlantic Ridge of about 100 K. It was calculated that, for a constant bulk composition, such a temperature variation would produce about a 7-km variation in crustal thickness, larger than is generally observed.

Sheehan, Anne F.↗

NASA NTRS1972

Backus-Gilbert inversion of travel time data

Application of the Backus-Gilbert theory for geophysical inverse problems to the seismic body wave travel-time problem is described. In particular, it is shown how to generate earth models that fit travel-time data to within one standard error and having generated such models how to describe their degree of uniqueness. An example is given to illustrate the process.

Johnson, L. E.↗