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At least 505 records · Page 28

Scalable line and plane relaxation in a parallel structured multigrid solver

The efficient solution of sparse, linear systems that arise through the discretization of partial differential equations remains a key challenge for a range of high performance scientific simulations. One approach for reducing data movement and improving performance is by exposing and exploiting structure in a problem through the use of robust structured multilevel solvers. By choosing coarsening that preserves the structure of the problem, these methods maintain efficient structured computation and communication throughout the multigrid hierarchy. However, when coarsening is not permitted to be dependent on the operator, anisotropy must be addressed by the smoother — producing error compatible for coarse-grid correction with structured coarsening. Here, the components required in a scalable parallel structured solver are described with a focus on memory and communication efficiency of robust smoothers. While the implementation of communication and memory reduction techniques in smoothers integrated in a complete 3D solver present a significant engineering challenge, a novel approach is proposed that addresses these challenges systematically through a change to the solver’s execution model. Enabled by user-level threading paired with a set of data and communication abstractions, this approach permits seamless aggregation of communication in plane smoothers — directly reusing code for a 2D distributed multilevel cycle. Results show an effective reduction in communication costs for coarse-grid problems, and result in a speedup of 8.7x in smoothing routines shown in Fig. 12 using this approach. This produces a significant improvement to strong scalability while maintaining favorable weak scaling behavior. Finally, a parallel scaling study using a series of refined meshes is included that demonstrates the effectiveness of this approach in an application of interest.

97 MATHEMATICS AND COMPUTING↗

Towards a Consolidated Approach for the Assessment of Evaluation Models of Nuclear Power Reactors

The STARS project at the Paul Scherrer Institut (PSI) has adopted the TRACE thermal-hydraulic (T-H) code for best-estimate system transient simulations of the Swiss Light Water Reactors (LWRs). For analyses involving interactions between system and core, a coupling of TRACE with the SIMULATE-3K (S3K) LWR core simulator has also been developed. In this configuration, the TRACE code and associated nuclear power reactor simulation models play a central role to achieve a comprehensive safety analysis capability. Thus, efforts have now been undertaken to consolidate the validation strategy by implementing a more rigorous and structured assessment approach for TRACE applications involving either only system T-H evaluations or requiring interfaces to e.g. detailed core or fuel behavior models. The first part of this paper presents the preliminary concepts of this validation strategy. The principle is to systematically track the evolution of a given set of predicted physical Quantities of Interest (QoIs) over a multidimensional parametric space where each of the dimensions represent the evolution of specific analysis aspects, including e.g. code version, transient specific simulation methodology and model "nodalisation". If properly set up, such environment should provide code developers and code users with persistent (less affected by user effect) and quantified information (sensitivity of QoIs) on the applicability of a simulation scheme (codes, input models, methodology) for steady state and transient analysis of full LWR systems. Through this, for each given transient/accident, critical paths of the validation process can be identified that could then translate into defining reference schemes to be applied for downstream predictive simulations. In order to illustrate this approach, the second part of this paper presents a first application of this validation strategy to an inadvertent blowdown event that occurred in a Swiss BWR/6. The transient was initiated by the spurious actuation of the Automatic Depressurization System (ADS). The validation approach progresses through a number of dimensions here: First, the same BWR system simulation model is assessed for different versions of the TRACE code, up to the most recent one. The second dimension is the "nodalisation" dimension, where changes to the input model are assessed. The third dimension is the "methodology" dimension. In this case imposed power and an updated TRACE core model are investigated. For each step in each validation dimension, a common set of QoIs are investigated. For the steady-state results, these include fuel temperatures distributions. For the transient part of the present study, the evaluated QoIs include the system pressure evolution and water carry-over into the steam line.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Turbo-Turtle v0.12.1

A collection of solid body modeling tools for 2D sketched, 2D axisymmetric, and 3D revolved models. It also contains general purpose meshing and image generation utilities appropriate for any model, not just those created with this package. Implemented for Abaqus and Cubit as backend modeling and meshing software. Orginal implementation targeted Abaqus so most options and descriptions use Abaqus modeling concepts and language. Turbo-Turtle makes a best effort to maintain common behaviors and features across each third-party software’s modeling concepts. As much as possible, the work for each subcommand is performed in Python 3 to minimize solution approach duplication in third-party tools. The third-party scripting interface is only accessed when creating the final tool specific objects and output. The tools contained in this project can be expanded to drive other meshing utilities in the future, as needed by the user community. This project derives its name from the origins as a sphere partitioning utility following the turtle shell (or soccer ball) pattern.s.

Brindley, Kyle↗

Analysis of the Space Propulsion System Problem Using RAVEN

This paper presents the solution of the space propulsion problem using a PRA code currently under development at Idaho National Laboratory (INL). RAVEN (Reactor Analysis and Virtual control ENviroment) is a multi-purpose Probabilistic Risk Assessment (PRA) software framework that allows dispatching different functionalities. It is designed to derive and actuate the control logic required to simulate the plant control system and operator actions (guided procedures) and to perform both Monte- Carlo sampling of random distributed events and Event Tree based analysis. In order to facilitate the input/output handling, a Graphical User Interface (GUI) and a post-processing data-mining module are available. RAVEN allows also to interface with several numerical codes such as RELAP5 and RELAP-7 and ad-hoc system simulators. For the space propulsion system problem, an ad-hoc simulator has been developed and written in python language and then interfaced to RAVEN. Such simulator fully models both deterministic (e.g., system dynamics and interactions between system components) and stochastic behaviors (i.e., failures of components/systems such as distribution lines and thrusters). Stochastic analysis is performed using random sampling based methodologies (i.e., Monte-Carlo). Such analysis is accomplished to determine both the reliability of the space propulsion system and to propagate the uncertainties associated to a specific set of parameters. As also indicated in the scope of the benchmark problem, the results generated by the stochastic analysis are used to generate risk-informed insights such as conditions under witch different strategy can be followed.

97 MATHEMATICS AND COMPUTING↗

Cloud Atlas: An Interactive Apparatus for Air Quality Awareness

This paper introduces a research project of a kinetic apparatus that translates collected air quality data to users. The kinetic mechanical skeleton is embedded with processors and electronics, and constantly changes its form according to air quality data collected online via a web crawler. By translating invisible environmental conditions, such as air quality data into morphological, colorful, and acoustic changes for the device, the participants can be aware of the phenomenon of air pollution in real time. The interac- tions between participants' movements and the changes of the device imply how human behaviors can affect the state of the atmosphere. As a result, the device evokes public awareness and participation in environmental issues through tangible experiences. This research aims to explore a new kind of responsive architecture that acts as a medium between invisible environments and inhabitants.

Zhao, Xiaoxiao↗

A behavioral choice model of the use of car-sharing and ride-sourcing services

There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing and car-sharing services, this paper presents a bivariate ordered probit model estimated on a survey data set derived from the 2014-2015 Puget Sound Regional Travel Study. Model estimation results show that users of these services tend to be young, well-educated, higher-income, working individuals residing in higher-density areas. There are significant interaction effects reflecting the influence of children and the built environment on disruptive mobility service usage. The model developed in this paper provides key insights into factors affecting market penetration of these services, and can be integrated in larger travel forecasting model systems to better predict the adoption and use of mobility-on-demand services.

30 DIRECT ENERGY CONVERSION↗

Advanced Laboratory and Field Arrays: Technical Report for Performance Enhancement for Marine Energy Converter (MEC) Arrays (Task 5)

Task 5 consisted of two parts, wave energy converter (WEC) arrays and current energy converter (CEC) arrays. The two parts of the project were executed independently, and this report covers only the work on WECs. In this part of the task, the team characterized the behavior of and developed control schemes for wave energy converter (WEC) arrays that improved performance (i.e., maximized aggregate power generation and reduced the levelized cost of energy) over baseline, non-coordinated control approaches. Specifically, for WEC arrays: the team developed optimal layouts of arrays that considered the effect of WEC placement within an array on coordinated array control with real-time estimation schemes. The numerical codes developed through this task were made available to users for array design. These tools utilized existing commercial software as well as software developed within the project team.

13 HYDRO ENERGY↗

Improved Weld Residual Stress Modeling System in BlackBear

This report presents enhancements to the MOOSE-based BlackBear application aimed at improving its capability to simulate welding and other thermo-mechanical manufacturing processes. Two primary avenues of improvement are pursued. First, to enhance user accessibility, we introduce a centralized default block restriction mechanism that ensures coverage checks are performed within user-specified default blocks. This default setting is applied consistently to all block-describable objects, such as variables, kernels, and more. In addition, we develop a modular action for moving heat source simulations, which integrates path file parsing, subdomain modification, and heat source kernel enforcement into a single, streamlined configuration. Second, to improve solver robustness, we implement an alternative method for assigning initial conditions to the updated active domain during the simulation, thereby enhancing convergence behavior. To validate the framework, we design and conduct several benchmark simulations, including heat conduction with progressive material addition, linear elasticity with time-dependent material deposition, and viscoplasticity model with isotropic hardening under similar conditions. Finally, we demonstrate the effectiveness of the proposed framework through large-scale thermo-mechanical welding simulations in both two and three dimensions.

42 ENGINEERING↗

PERCEPTIVE: an R shiny $\underline{p}$ipelin$\underline{e}$ for the p$\underline{r}$edi$\underline{c}$tion of $\underline{ep}$igenetic modula$\underline{t}$ors $\underline{i}$n no$\underline{v}$el sp$\underline{e}$cies

Epigenetic processes are central to regulating gene expression, genome stability, and metabolic function across the tree of life; yet, their roles remain underexplored in microalgae, especially as new species continue to be identified and characterized. This is likely due to the cumbersome nature and species-dependent attributes of epigenetic wet-lab methodologies, which preclude the rapid identification of epigenetic modifications and modulators. However, there is high conservation of epigenetic processes from budding yeast to humans; in many cases, one may infer how behavior and function are epigenetically regulated in novel species by identifying epigenetic modulators, or the proteins responsible for conferring epigenetic modifications. Here, to this end, we have developed a graphical software package, titled PERCEPTIVE (pipeline for the prediction of epigenetic modulators in novel species). This platform solely uses the genomic sequence of an algal species, and preexisting information from other model organisms, to predict the epigenetic modulators and associated modifications in algae. Predictions are presented to the user in a graphical interface, which provides literature-based interpretation of results, enabling users to quickly understand potential epigenetic processes in their algal species of interest and plan follow-up experiments. To test PERCEPTIVE, we predicted epigenetic modulators in several feedstock candidate algae species. To validate these predictions, wet-lab studies were performed, including mass spectrometry; these results underscore the high accuracy of PERCEPTIVE predictions. Overall, PERCEPTIVE represents a powerful in silico tool for the research and manipulation of algal species, which does not require a priori knowledge of epigenetics and is accessible to a broad set of investigators.

59 BASIC BIOLOGICAL SCIENCES↗

Aggregated Modeling of Thermostatic Loads in Demand Response: A Systems and Control Perspective

Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated models for a homogeneous population of thermostatically controlled loads. The different types of loads considered in this paper include, but are not limited to, water heaters and HVAC units. The effects of demand response and user over-ride on the load population dynamics are investigated. The controllability of the developed lumped models is validated which forms the basis for designing different control strategies.

Kalsi, Karanjit↗

A User Guide to PARET/ANL (V.7.6) (Rev.1)

PARET was originally created in 1969 at what is now Idaho National Laboratory (INL), to analyze reactivity insertion events in research and test reactor cores cooled by light or heavy water, with fuel composed of either plates or pins. The use of PARET is also appropriate for fuel assemblies with curved fuel plates when their radii of curvatures are large with respect to the fuel plate thickness. The PARET/ANL version of the code has been developed at Argonne National Laboratory (ANL) under the sponsorship of the U.S. Department of Energy/NNSA, and has been used by the Reactor Conversion Program to determine the expected transient behavior of a large number of reactors. PARET/ANL models the various fueled regions of a reactor core as channels. Each of these channels consists of a single flat fuel plate/pin (including cladding and, optionally, a gap) with water coolant on each side. In slab geometry the coolant channels for a given fuel plate are of identical dimensions (mirror symmetry), but they can be of different thickness in each channel. There can be many channels, but each channel is independent and coupled only through reactivity feedback effects to the whole core. The time-dependent differential equations that represent the system are replaced by an equivalent set of finite-difference equations in space and time, which are integrated numerically. PARET/ANL uses fundamentally the same numerical scheme as RELAP5 for the time-integration of the point-kinetics equations. The one-dimensional thermal-hydraulic model includes temperature-dependent thermal properties of the solid materials, such as heat capacity and thermal conductivity, as well as the transient heat production and heat transfer from the fuel meat to the coolant. Temperature- and pressure-dependent thermal properties of the coolant such as enthalpy, density, thermal conductivity, and viscosity are also used in determining parameters such as friction factors and heat transfer coefficients. The code first determines the steady-state solution for the initial state. Then the solution of the transient is obtained by integration in time and space. Multiple heat transfer, DNB and flow instability correlations are available. The code was originally developed to model reactors cooled by an open loop, which was adequate for rapid transients in pool-type cores. An external loop model appropriate for Miniature Neutron Source Reactors (MNSR’s) was also added to PARET/ANL to model natural circulation within the vessel, heat transfer from the vessel to pool and heat loss by evaporation from the pool. PARET/ANL also contains models for decay heat after shutdown, control rod reactivity versus time or position, time-dependent pump flow, and loss-of-flow event with flow reversal as well as logic for trips on period, power, and flow. Feedback reactivity effects from coolant density changes and temperature changes are represented by tables. Feedback reactivity from fuel heat-up (Doppler Effect) is represented by a four-term polynomial in powers of fuel temperature. Photo-neutrons produced in beryllium or in heavy water may be included in the point-kinetics equations by using additional delayed neutron groups.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Tactical Analysis for Calculating Contextual Risk at Boundaries: Summary of Laboratory Directed Research & Development Effort

The Tactical Analysis for Calculating Contextual Risk at Boundaries (TACCRAB) tool is an innovative digital twin (DT) platform and automated risk algorithm designed to transform operational decision-making in structured screening environments, with an initial focus on Southern Border Land Ports of Entry (POEs). The invention provides integration points for advanced artificial intelligence, predictive modeling, and real-time data analysis to produce a comprehensive risk management tool that enables proactive, data-informed security strategies. The core inventive features of TACCRAB center on its unique risk algorithm, which dynamically calculates contextual risk by synthesizing historical data, near real-time streaming data from the checkpoints themselves, and AI-generated predictions. Unlike traditional risk assessment methods, TACCRAB utilizes a DT to provide comprehensive operational insights, allowing stakeholders to visualize, simulate, and optimize checkpoint configurations with unprecedented speed and contextual awareness. TACCRAB's key innovation lies in its ability to combine multiple complex inputs - including technology detection probabilities, resource availability, screening pathway characteristics, and threat actor behavioral patterns - into a unified risk calculation and update these inputs based on changing operational and environmental conditions. By leveraging a DT that continuously updates and learns from linked data, TACCRAB can suggest adaptive mitigation strategies that minimize risk while maintaining operational efficiency. Particularly novel is the platform's approach to decision support, which goes beyond static risk assessment. The DT provides dynamic metrics such as wait times, resource allocation effectiveness, and potential emerging threat scenarios, enabling users to view sophisticated, relevant what-if simulations and optimize checkpoint operations in near real-time. The system's architecture allows for generalized application across different screening environments, such as secure facilities, ports of entry, and soft targets, making it a versatile tool for security and operational management. The invention distinguishes itself through its comprehensive integration of predictive modeling, AI-driven pattern discovery, and user-friendly interface design. By combining these elements, TACCRAB transforms complex risk data into actionable insights, supporting decision-makers at various organizational levels - from booth agents making split-second screening decisions to checkpoint managers optimizing the day's resource allocation to strategic planners managing long-term investments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Science Requirements and Conceptual Design for a Polarized Medium Energy Electron-Ion Collider at Jlab

Researchers have envisioned an electron-ion collider with ion species up to heavy ions, high polarization of electrons and light ions, and a well-matched center-of-mass energy range as an ideal gluon microscope to explore new frontiers of nuclear science. In its most recent Long Range Plan, the Nuclear Science Advisory Committee (NSAC) of the US Department of Energy and the National Science Foundation endorsed such a collider in the form of a 'half-recommendation.' As a response to this science need, Jefferson Lab and its user community have been engaged in feasibility studies of a medium energy polarized electron-ion collider (MEIC), cost-effectively utilizing Jefferson Lab's already existing Continuous Electron Beam Accelerator Facility (CEBAF). In close collaboration, this community of nuclear physicists and accelerator scientists has rigorously explored the science case and design concept for this envisioned grand instrument of science. An electron-ion collider embodies the vision of reaching the next frontier in Quantum Chromodynamics - understanding the behavior of hadrons as complex bound states of quarks and gluons. Whereas the 12 GeV Upgrade of CEBAF will map the valence-quark components of the nucleon and nuclear wave functions in detail, an electron-ion collider will determine the largely unknown role sea quarks play and for the first time study the glue that binds all atomic nuclei. The MEIC will allow nuclear scientists to map the spin and spatial structure of quarks and gluons in nucleons, to discover the collective effects of gluons in nuclei, and to understand the emergence of hadrons from quarks and gluons. The proposed electron-ion collider at Jefferson Lab will collide a highly polarized electron beam originating from the CEBAF recirculating superconducting radiofrequency (SRF) linear accelerator (linac) with highly polarized light-ion beams or unpolarized light- to heavy-ion beams from a new ion accelerator and storage complex. Since the very beginning, the design studies at Jefferson Lab have focused on achieving high collider performance, particularly ultrahigh luminosities up to 10{sup 34} cm{sup -2}s{sup -1} per detector with large acceptance, while maintaining high polarization for both the electron and light-ion beams. These are the two key performance requirements of a future electron-ion collider facility as articulated by the NSAC Long Range Plan. In MEIC, a new ion complex is designed specifically to deliver ion beams that match the high bunch repetition and highly polarized electron beam from CEBAF. During the last two years, both development of the science case and optimization of the machine design point toward a medium-energy electron-ion collider as the topmost goal for Jefferson Lab. The MEIC, with relatively compact collider rings, can deliver a luminosity above 10{sup 34} cm{sup -2}s{sup -1} at a center-of-mass energy up to 65 GeV. It offers an electron energy up to 11 GeV, a proton energy up to 100 GeV, and corresponding energies per nucleon for heavy ions with the same magnetic rigidity. This design choice balances the scope of the science program, collider capabilities, accelerator technology innovation, and total project cost. An energy upgrade could be implemented in the future by adding two large collider rings housed in another large tunnel to push the center-of-mass energy up to or exceeding 140 GeV. After careful consideration of an alternative electron energy recovery linac on ion storage ring approach, a ring-ring collider scenario at high bunch repetition frequency was found to offer fully competitive performance while eliminating the uncertainties of challenging R&D on ampere-class polarized electron sources and many-pass energy-recovery linacs (ERLs). The essential new elements of an MEIC facility at Jefferson Lab are an electron storage ring and an entirely new, modern ion acceleration and storage complex. For the high-current electron collider ring, the upgraded 12 GeV CEBAF SRF linac will serve as a full-energy injector, and, if needed, provide top-off refilling. The CEBAF fixed-target nuclear physics program can be simultaneously operated since the filling time of the electron ring is very short. The ion complex for MEIC consists of sources for polarized light ions and unpolarized light to heavy ions, an SRF ion linac with proton energy up to 280 MeV, a 3 GeV prebooster synchrotron, a large booster synchrotron for proton energy up to 20 GeV, and a medium-energy collider ring with energy up to 100 GeV. The ion complex can accelerate other species of ions with corresponding energies at each accelerating stage. There are three collision points planned for MEIC. Two of them are for collisions with medium-energy ions; the third is for low energy ion beams stored in a dedicated low-energy compact storage ring, as a possible follow-on project.

43 PARTICLE ACCELERATORS↗

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Accurate and efficient interatomic potentials are essential for molecular dynamics (MD) simulations of radiation damage, gas diffusion, and phase stability in complex ceramics such as LiAlO 2 , especially under extreme conditions relevant to tritium production. Here, we evaluate the performance of six machine-learned interatomic potentials (MLIPs), moment tensor potential (MTP), Gaussian approximation potential, deep potential (DeePMD), atomic cluster expansion (ACE), message-passing ACE (multilayer atomic cluster expansion (MACE) pretrained) and MACE (trained from-scratch), all trained on the same density functional theory dataset with inclusion of tritium. The MLIPs are benchmarked against traditional Buckingham and ReaxFF potentials in terms of energy accuracy, density predictions, thermal equilibration behavior, threshold displacement energy (E d ), tritium diffusivity, and computational cost. Among the models, MTP shows the best overall balance between efficiency and accuracy, with low force and energy errors and realistic E d values for Li and Al. The ACE and MACE (pretrained and trained from scratch) models exhibit high E d (>200 eV) and unphysical pair interactions. DeePMD underestimates Ed due to overly repulsive behavior even at equilibrium distances. All models over-estimate tritium diffusion but the pretrained MACE model behaves well during tritium-diffusion simulations up to 500 K, maintaining diffusivities in the physically consistent 10 −11 m 2 /s range. Finally, we quantify the computational cost of each potential in large-scale atomic/molecular massively parallel simulator, finding that only MTP is more efficient than traditional empirical potentials, while others are significantly more expensive. These findings explain the trade-offs between accuracy and computational cost in MLIP development and provide essential guidance for use in high-throughput radiation damage and gas diffusion simulations in nuclear ceramics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Modeling the Impact of Grain Size on Corrosion Behavior of Ni-Based Alloys in Molten Chloride Salt via Cellular Automata

Molten chloride salts hold significant promise as both thermal transfer and storage media for next-generation concentrated solar power (CSP) systems. However, molten chlorides pose a considerable corrosion risk to structural materials, particularly Ni-based alloys. One approach to enhancing corrosion resistance is through the optimization of grain structure; however, it remains uncertain whether increasing or decreasing grain size enhances corrosion resistance. A cellular automata (CA) program was developed to evaluate the interplay between grain size and corrosion in Ni-based alloy. Our CA program tracks alloy composition, surface roughness, and thickness loss via a graphical user interface, displaying corrosion and diffusion status, and multiple user input cards for tuning the simulation. CA simulations of Inconel 625 indicate enhanced corrosion resistance with increased grain size, with passivating oxides offering limited protection. Additionally, the temporal evolution of alloy surface roughness demonstrates notable fluctuations, with abrupt increases attributed to corrosion along vertical grain boundaries and sudden decreases to grain detachment from the protective film.

Materials Science↗

Ex-Vessel Core Melt Modeling Comparison between MELTSPREAD-CORQUENCH and MELCOR 2.1

System-level code analyses by both United States and international researchers predict major core melting, bottom head failure, and corium-concrete interaction for Fukushima Daiichi Unit 1 (1F1). Although system codes such as MELCOR and MAAP are capable of capturing a wide range of accident phenomena, they currently do not contain detailed models for evaluating some ex-vessel core melt behavior. However, specialized codes containing more detailed modeling are available for melt spreading such as MELTSPREAD as well as long-term molten corium-concrete interaction (MCCI) and debris coolability such as CORQUENCH. In a preceding study, Enhanced Ex-Vessel Analysis for Fukushima Daiichi Unit 1: Melt Spreading and Core-Concrete Interaction Analyses with MELTSPREAD and CORQUENCH, the MELTSPREAD-CORQUENCH codes predicted the 1F1 core melt readily cooled in contrast to predictions by MELCOR. The user community has taken notice and is in the process of updating their systems codes; specifically MAAP and MELCOR, to improve and reduce conservatism in their ex-vessel core melt models. This report investigates why the MELCOR v2.1 code, compared to the MELTSPREAD and CORQUENCH 3.03 codes, yield differing predictions of ex-vessel melt progression. To accomplish this, the differences in the treatment of the ex-vessel melt with respect to melt spreading and long-term coolability are examined. The differences in modeling approaches are summarized, and a comparison of example code predictions is provided.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

ReachNow EV Driving Data From Seattle, WA, Portland, OR, and New York, NY

ReachNow provided Idaho National Laboratory (INL) with a dataset describing approximately 49,000 trips taken by customers and employees in approximately 100 BMW i3 EVs operating in ReachNow's free-floating car-sharing fleets in Seattle, WA, Portland, OR, and New York, NY between May 2016 and February 2017. Data fields include vehicle rental period start and end timestamps, the location where vehicles were parked at the start and end of rental periods, and distance driven during rental periods. A field categorizing the user during each rental period is also included. This field makes it possible to identify when vehicles were rented by customers and when vehicles were driven by fleet management team employees to reposition, charge, or service the vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

How Many Trip Requests Could We Support? An Activity-Travel Based Vehicle Scheduling Approach

In a world of ever-changing travel behavior and ever-increasing modal options, is vital to have integrated models that could capture the interactions between supply and demand layers of travel. Addressing this need, we propose three different versions of network representation and mathematical models for the activity-based vehicle routing problem to connect activity-travel graphs of passengers (demand layer) to spatio-temporal networks of vehicles (supply layer). Versions I and II are arc-based, while version III is path-based. In version I, we introduce the concept of activity-travel graphs for passengers. For vehicles, we construct space–time networks and add a new dimension, called “under-service state”, to track the execution status of trip requests at any location and time. In version II, we reduce the complexity of the network structure by eliminating the state dimension and some other modifications in the structure of the passengers’ and vehicles’ network. Although both versions can capture various behavioral constraints of the activity-based vehicle routing problem (e.g., mandatory and optimal activities, duration of activities, chain of activities, preferred starting and ending times of activities), due to the high level of complexity of the network structure, both versions can only solve small-sized problems. To tackle the computational complexity, we propose a path-based network representation in version III, and to make a balance between the disutility of passengers and vehicles, we present a tolled user equilibrium problem. Mathematical models are coded in C and GAMS and implemented on real-world Phoenix regional transportation network with more than 39 million trip requests, which demonstrate the effectiveness of the proposed solution for the original and restricted master problems.

33 ADVANCED PROPULSION SYSTEMS↗