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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↗

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↗

Design of Multi-Stage Solvent Extraction Process for Separation of Rare Earth Elements

Flowsheet design and stage determination for the separation of rare earth elements (REEs) using solvent extraction (SX) is a challenging task because of the chemical similarity of the REEs. Low separation factors between the elements and complex equilibrium chemistry provide unique challenges to designing an efficient flowsheet for the separation of elements. The multi-stage nature of the SX process adds further complexity, making the assessment of products for a proposed design and stage combination difficult. Therefore, to develop a SX flowsheet, it is essential to quantify the performance for various design and separation conditions. This paper attempts to address the challenge by utilizing an equilibrium and process modeling approach. Results from a bench-scale study performed on a 10 g/L rare earth salt mixture were used in studying the extraction/stripping behavior and developing equilibrium models. DEHPA with TBP as a phase modifier was used as an extractant, while hydrochloric acid was utilized as a stripping agent. The results obtained were used in developing extraction/stripping models, which were integrated into a process framework of a SX train in a Matlab/Simulink environment. The models were programmed as a function block routine and used for developing a flowsheet, which was simulated for differing separation and design conditions. To identify optimum stage combinations, a particle swarm optimization (PSO) routine was developed and implemented for each SX train. Recovery and purity of elements of interest were used as objective function criteria. The stage combination leading to the minimization of the objective function was used to identify the optimum stage combination for a series of SX trains to attempt a balance of purity and recovery. The models and optimization method were implemented to separate a feed mixture containing REEs, which indicated that 99.52 and 85.41 percent purity is achievable for Yttrium and Lanthanum separation using 8-12-3 and 10-3-5 stage combination for loading, scrubbing, and striping. The model also indicated difficult separability between neodymium, praseodymium, and cerium.

Srivastava, Vaibhav (ORCID:0000000212645987)↗

Chain Flexibility and Structure of a Polyimide Copolymer: Revisiting the Freely Rotating Chain Model

Poly(4–4′-oxydiphenylene-pyromellitimide)-based polyimides─trade name Kapton─have wide-ranging engineering applications owing to their thermal and mechanical stability, but little is known about underlying chain-level characteristics. While theoretical models have conceptualized Kapton as inflexible polycyclic rods separated by freely rotating diphenyl ether hinge groups, the model’s core predictions remain untested and subtleties of the relaxation behavior are missed, which atomistic modeling can resolve. To these ends, we examine all-atom Kapton structures in crystalline and glassy amorphous configurations using a DFT-validated class II force field. Constructing amorphous configurations is challenging, as the fused-ring-containing backbone has slow relaxation dynamics and scaling suggestive of entanglements even in oligomers. In conclusion, we find larger backbone rearrangements of the linear polycyclic segments about ether groups that are consistent with the rod-hinge picture on the monomer scale, whereas a ring rotation analysis suggests partially flexible rod-like segments and involves multiple facile rotational relaxation modes.

Liesen, Nicholas T. [Lawrence Livermore National L↗

$\mathcal{g}$ modes of neutron stars with hadron-to-quark crossover transitions

Here we perform the first study of the principal core g-mode oscillation in hybrid stars containing quark matter, utilizing a crossover model for the hadron-to-quark transition inspired by lattice QCD. The ensuing results are compared with our recent findings of g-mode frequencies in hybrid stars with a first-order phase transition using Gibbs constructions. We find that models using Gibbs construction yield g-mode amplitudes and the associated gravitational energy radiated that dominate over those of the chosen crossover model owing to the distinct behaviors of the equilibrium and adiabatic sound speeds in the various models. Based on our results, we conclude that were g modes to be detected in upgraded LIGO and Virgo detectors it would indicate a first-order phase transition akin to a Gibbs construction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Model Driven Deception for Defense of Operational Technology Environments

Due to the strong integration of real-world physics, OT deception platforms must operate differently than traditional IT deceptions. For instance, turning off a valve will be detected downstream by other sensors because the flow will reduce and stop. Additionally, controllers and applications leverage data from sensors to send control commands to each other. A believable deception must be integrated with the system to project the effects of events. An attack will likely attempt to control the physical process in a negative manner. To make the attacker believe they are achieving their objective, it must predict the effects of these actions, to a reasonable degree. Our approach to simulating a model to generate realistic decoy behavior is explored including description of two approaches: a physics model-based approach and a data driven approach. The performance of two machine learning techniques are investigated in their ability to learn a good enough model of the physics of the system.

97 MATHEMATICS AND COMPUTING↗

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗

A CALPHAD-informed approach to modeling constituent redistribution in Zr-based metallic fuels using BISON

Here, a CALPHAD-informed (Computer Coupling of Phase Diagrams and Thermochemistry) constituent redistribution model was developed for Zr-based metallic fuels and incorporated into the BISON fuel performance code. Three uncertain model parameters associated with β and γ phase kinetics were calibrated using integral test data from U-Zr fuel elements irradiated in Experimental Breeder Reactor II. The calibrated constituent redistribution model was shown to predict the behavior of U-Zr fuels with excellent accuracy. Model predictions for U-Pu-Zr fuels were physically reasonable but less accurate. Reduction of uncertainties in the ternary phase transition temperatures and collection of kinetic data for the ζ phase are expected to improve the model’s ternary predictions. Finally, the new model was coupled to existing thermomechanics models in BISON to simulate irradiation of an entire U-Zr fuel element, demonstrating its ability to accurately predict the behavior of U-Zr fuels with realistic geometries and mesh resolutions at the engineering scale.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Scattering neutrinos, spin models, and permutations

We consider a class of Heisenberg all-to-all coupled spin models inspired by neutrino interactions in a supernova with N degrees of freedom. These models are characterized by a coupling matrix that is relatively simple in the sense that there are only a few, relative to N , nontrivial eigenvalues, in distinction to the classic Heisenberg spin-glass models, leading to distinct behavior in both the high-temperature and low-temperature regimes. When the momenta of the neutrinos are uniform and random in directions, we can calculate the large- N partition function for the quantum Heisenberg model. In particular, the high-temperature partition function predicts a non-Gaussian density of states, providing interesting counterexamples showing the limits of general theorems on the density of states for quantum spin models. We can repeat the same argument for classical Heisenberg models, also known as rotor models, and we find the high-temperature expansion is completely controlled by the eigenvalues of the coupling matrix, and again predicts non-Gaussian behavior for the density of states as long as the number of eigenvalues does not scale linearly with N . Indeed, we derive the amusing fact that these partition functions are essentially the generating function for counting permutations in the high-temperature regime. Finally, for the case relevant to neutrinos in a supernova, we identify the low-temperature phase as a unique state with the direction of the momenta of the neutrino dictating its coherent state in flavor-space, a state we dub the “flavor-momentum-locked” state. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Impact analysis of DERs on bulk power system stability through the parameterization of aggregated DER_a model for real feeders

With an ever increasing percentage of distributed energy resources (DERs) connected behind the meter in the distribution system, it is becoming increasingly important to equip transmission planners with the visibility of DER dynamic performance in distribution system. Not having visibility of the disconnection of DERs with the occurrence of transmission events, could result in an erroneous view of the stability of bulk power system. Here, in this paper, a parameterized aggregated model (DER_a) serves as a representation of the distribution-level dynamics of real residential feeders, which is used for analysis of bulk power system stability. The parameters are obtained by executing dynamic Monte Carlo simulations. Faults are then induced at the substation level causing the DERs to trip which subsequently enables the parameterization of the low and high voltage breakpoints (v l0 , v l1 , v h0 , and v h1 ) of the DER_a model’s partial voltage trip block. These parameters are then utilized to study the effectiveness of the DER_a model to represent the behavior of the aggregated DERs’ response and their impact on the bulk power system. The case study shows the ability of the positive-sequence DER_a model to provide an accurate estimation of DERs that are susceptible to trip due to 3-$\phi$ and 1-$\phi$ faults of transmission.

14 SOLAR ENERGY↗

Comparative determinant quantum Monte Carlo study of the acoustic and optical variants of the Su-Schrieffer-Heeger model

We compare the acoustic Su–Schrieffer–Heeger (SSH) model with two of its optical variants where the phonons are defined on either on the sites or bonds of the system. First, we discuss how to make fair comparisons between these models in any dimension by ensuring their dimensionless coupling λ and relevant phonon energies are the same. We then use determinant quantum Monte Carlo to perform nonperturbative and sign-problem-free simulations of all three models on one-dimensional chains at and away from half-filling. By comparing the results obtained from each model, we demonstrate that the optical and acoustic models produce near identical results within error bars for suitably chosen phonon energies and λ at half-filling. In contrast, the bond model has quantitatively different behavior due to its coupling to the q = 0 phonon mode. These differences also manifest in the total length of the chain, which shrinks for the bond model but not for the acoustic and optical models when λ ≠ 0. Furthermore, our results have important implications for quantum Monte Carlo modeling of SSH-like interactions, where these models are sometimes regarded as being interchangeable.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Discrete element model for powder grain interactions under high compressive stress

A reduced order, nonlocal model is proposed for the contact force between initially spherical particles under compression. The model in effect provides the normal component of the interaction force between elements in the discrete element method (DEM). It is applicable to high relative density and large stress in powder compaction. It takes into account the mutual interaction between multiple points of contact, in contrast to the usual assumption in DEM of pair interactions. The mathematical form of the model is derived from a variational formulation that leads to the momentum balance for the forces on each grain. The model is calibrated mainly using detailed three dimensional peridynamic simulations of single grains under compressive loading by rigid plates that move radially with prescribed velocity. This calibration takes into account the large deformation and fracture of the grains. The interaction model also includes terms for the unloading behavior and adhesion. Finally, as validation, the model is applied to test data on the compaction of microcrystalline cellulose bulk powder.

36 MATERIALS SCIENCE↗