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At least 649 records · Page 36

Nonlinear Shear Rheology of Entangled Polymer Rings

Steady-state shear viscosity η($\bar{γ}$) of unconcatenated ring polymer melts as a function of the shear rate $\bar{γ}$ is studied by a combination of experiments, simulations, and theory. Experiments using polystyrenes with Z ≈ 5 and Z ≈ 11 entanglements indicate weaker shear thinning for rings compared to linear polymers exhibiting power law scaling of shear viscosity η ~ $\bar{γ}$ –0.56 ± 0.02 , independent of chain length, for Weissenberg numbers up to about 10 2 . Nonequilibrium molecular dynamics simulations using the bead-spring model reveal a similar behavior with η ~ $\bar{γ}$ -0.57 ± 0.08 for 4 ≤ Z ≤ 57. Viscosity decreases with chain length for high $\bar{γ}$. In our experiments, we see the onset of this regime, and in simulations, which we extended to Wi ~ 10 4 , the nonuniversality is fully developed. In addition to a naive scaling theory yielding for the universal regime η ~ $\bar{γ}$ –0.57 , we developed a novel shear slit model explaining many details of observed conformations and dynamics as well as the chain length-dependent behavior of viscosity at large $\bar{γ}$. The signature feature of the model is the presence of two distinct length scales: the size of tension blobs and much larger thickness of a shear slit in which rings are self-consistently confined in the velocity gradient direction and which is dictated by the size of a chain section with relaxation time 1/$\bar{γ}$. These two length scales control the two normal stress differences. In this model, the chain length-dependent onset of nonuniversal behavior is set by tension blobs becoming as small as about one Kuhn segment. This model explains the approximate applicability of the Cox–Merz rule for ring polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Preferential adsorption of noble gases in zeolitic tuff with variable saturation: A modeling study of counter-intuitive diffusive-adsorptive behavior

Noble gas transport through geologic media has important applications in the prediction and characterization of measured gas signatures related to underground nuclear explosions (UNEs). Retarding processes such as adsorption can cause significant species fractionation of radionuclide gases, which has implications for measured and predicted signatures used to distinguish radioxenon originating from civilian nuclear facilities or from UNEs. Accounting for the effects of variable water saturation in geologic media on tracer transport is one of the most challenging aspects of modeling gas transport because there is no unifying relationship for the associated tortuosity changes between different rock types, and reactive transport processes such as adsorption that are affected by the presence of water likewise behave differently between gas species. In this study, we perform numerical diffusive-adsorptive transport simulations to estimate gas transport parameters associated with bench-scale laboratory diffusion cell experiments measuring breakthrough in zeolitic and non-zeolitic rocks for a gaseous mixture of xenon, krypton, and SF 6 at varying degrees of water saturation (S w ). Counter-intuitive transport behavior was observed in the zeolitic rock experiments whereby breakthrough concentrations were significantly higher when the core was partially saturated (S w = 17 %) than under dry (S w = 0 %) conditions. Breakthrough of xenon was especially retarded in the dry core – likely due to comparatively high affinity of xenon for zeolitic adsorption sites – and estimated effective diffusion coefficients for all gases were approximately an order of magnitude lower than what is predicted by porosity-tortuosity models. We propose the counter-intuitive behavior observed is because water infiltration of zeolite nanopores reduces both the adsorptive capacity of the rock and the tortuosity of connected flow paths. We developed a two-site competitive kinetic Langmuir adsorption reaction for the porous media transport simulator in order to constrain transport parameters within zeolitic tuff, where differential adsorption to zeolite and non-zeolite pores was observed. We determined that liquid saturation-dependent diffusive-adsorptive transport is affected by subtle and at times competing processes that are specific to different gases, which have a significant overall influence on effective transport parameters.

58 GEOSCIENCES↗

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advancing Chemical Separations: Unraveling the Structure and Dynamics of Phase Splitting in Liquid–Liquid Extraction

Liquid-liquid extraction (LLE), the go-to process for a variety of chemical separations, is limited by spontaneous organic phase splitting upon sufficient solute loading, called third phase formation. In this study we explore the applicability of critical phenomena theory to gain insight into this deleterious phase behavior with the goal of improving separations efficiency and minimizing waste. Here, a series of samples representative of rare earth purification were constructed to include each of one light and one heavy lanthanide (cerium and lutetium) paired with one of two common malonamide extractants (DMDOHEMA and DMDBTDMA). The resulting postextraction organic phases are chemically complex and often form rich hierarchical structures whose statics and dynamics near the critical point were probed herein with small-angle X-ray scattering and high-speed X-ray photon correlation spectroscopy. Despite their different extraction behaviors, all samples show remarkably similar critical behavior with exponents well described by classical critical point theory consistent with the 3D Ising model, where the critical behavior is characterized by fluctuations with a single diverging length scale. This unexpected result indicates a significant reduction in relevant chemical parameters at the critical point, indicating that the underlying behavior of phase transitions in LLE rely on far fewer variables than are generally assumed. The obtained scalar order parameter is attributed to the extractant fraction of the extractant/diluent mixture, revealing that other solution components and their respective concentrations simply shift the critical temperature but do not affect the nature of the critical fluctuations. These findings point to an opportunity to drastically simplify studies of liquid-liquid phase separation and phase diagram development in general while providing insights into LLE process improvement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Viscoelastic Material Characterization and Modeling of Photovoltaic Module Packaging Materials for Direct Finite-Element Method Input

Numerical tools, such as the finite-element method, are increasingly used to design and evaluate the photovoltaic (PV) modules, providing for the reduction of development time and improved performance and reliability. However, high-fidelity material models are necessary to accurately model the complex structural behavior of the involved packaging materials. A common simplification used in recent years is to model the polymer materials (i.e., encapsulant and backsheet) as linear elastic, which will lead to inaccurate results. Therefore, in this work, we present a thorough characterization of the time- and temperature-dependent mechanical response of predominant PV module encapsulant and backsheet materials. Based on this material characterization, we developed and experimentally validated generalized Maxwell models to describe each material's viscoelastic response. In addition, we included measurements of the coefficient of thermal expansion and presented all material models in such a fashion for direct input into commercial finite-element method modeling software.

FEM↗

Verification Testing For Solid-Element Material Models 11-19 in DYNA3D/ParaDyn

This technical report documents the creation and implementation of verification tests for solid-element material models 11 through 19 available in DYNA3D/ParaDyn. The verification tests covered all aspects of each material model, except for the Weibull distribution functionality in material models 15 and 19. General test cases were created to verify the elastic and plastic behavior of the material models. Other additional tests were developed to examine the intricacies of each material model. Each test involved the use a kinematic load case and specification of material parameters necessary to activate corresponding features of the material model. The load cases prescribed the full time history of the kinematic motion for the solid elements, and these loads are independent of the material model or element formulation. When possible, closed form solutions were then derived for each verification test in a continuum setting. The DYNA3D simulations for each test were carried out over a unit time interval, t ϵ [0, 1], and the as implemented DYNA3D response was compared to the closed form solutions evaluated at discrete points in time. A relative error measure was determined for each test to justify the proper implementation of the material model. The relative errors comparing the DYNA3D solution to the analytical solution were, in general, on the order of machine precision except where noted. This signifies the proper implementation of solid-element material models 11-19. In the development of these verification tests, six bugs were found and fixed in the source code. Additionally, this work generated eighteen DYNA3D input decks and answer extraction scripts in the DYNA3D/ParaDyn Software Quality Assurance test suite, which are comprised of a total of 285 solid-element tests. Testing for each material model utilizes two input decks and answer extraction scripts, where one focuses on the linear elastic response and the other examines the inelastic and remaining functionalities of the material model. In total, this work added 285 individual verification test problems in the DYNA3D/ParaDyn test suite.

42 ENGINEERING↗

Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures

The use of active wake mixing (AWM) to mitigate downstream turbine wakes has created new opportunities for reducing power losses in wind farms. However, many current analytical or semi-empirical wake models do not capture the flow instabilities that are excited through the blade pitch actuation. In this work, we develop a framework, which accounts for the impacts of the large-scale coherent structures and turbulence on the mean flow, for modeling AWM. The framework uses a triple-decomposition approach for the unsteady flow field and models the mean flow and fine-scale turbulence with a parabolized Reynolds-averaged Navier–Stokes (RANS) system. The wave components are modeled using a simplified spatial linear stability formulation that captures the growth and evolution of the coherent structures. Comparisons with high-fidelity large eddy simulations (LESs) of the turbine wakes showed that this framework was able to capture the additional wake mixing and faster wake recovery in the far-wake regions for both the pulse and helix AWM strategies with minimal computational expense. In the near-wake region, some differences are observed in both the RANS velocity profiles and initial growth of the large-scale structures, which may be due to some simplifying assumptions used in the model.

17 WIND ENERGY↗

Application of the Continuum Damage Mechanics Wilshire-Cano-Stewart (WCS) Model

In this study, the applications of the continuum damage mechanics-based Wilshire-Cano-Stewart (WCS) model are explored to predict rupture time, minimum-creep-strain-rate (MCSR), damage, damage evolution, and creep deformation. Increase knowledge in manufacturing methods has pushed the limit of material science and the development of new materials. Conventional testing is required to qualify materials against creep which according to the ASME B&PV III code, 10,000+ hours of experiments are necessary for each heat before materials are put into service. This process is costly and not feasible for new materials. As an alternative, models have been employed to predict creep behaviors and reduce the amount of time necessary for material qualification. Many models have been developed to predict distinct creep behaviors and the question of which model is best remains. Amongst current models, the WCS model has emerge with the ability to predict multiple behaviors using an explicit analytical approach with the ability to predict long-term creep. In this study the novel continuum damage mechanics WCS is employed in multiple applications. The goals of the study are (a) to discuss and determine the framework of the WCS model and validated it mathematically and using parametric simulations, (b) applied the model to accelerated creep data to show the capabilities of the model with non-conventional data, and (c) applied a novel numerical method, the datum temperature method (DTM) to show the model extrapolations and interpolations capabilities with limited and reduce data sets. To accomplish these goals, data is gathered for alloy P91 and Inconel 718 to develop and post-audit validate the model. The benefits of using the WCS model is that it provides an explicit stress and temperature dependency ideal for extrapolations, the coupled equations are suitable for finite element analysis (FEA) implementation, and it follows an explicit calibration approach. The model also proves that it can be applied to accelerated testing data and using the DTM.

Cano, Jaime A↗

Is the Adoption of Electric Vehicles (EVs) and Solar Photovoltaics (PVs) Interdependent or Independent? An Integrated EVs-PVs Modeling Framework

Transportation and residential energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics or PVs) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market share for both EVs and PVs continue to grow, both these emerging technologies are deployed rather disjoint without considering the existence of potential similarities among users who own (or aspire to own) EVs and PVs. This might be due to lack of understanding of the behavioral interdependence in consumer preferences towards these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores EV and PV adoption behaviors. A structural equations model (SEM) is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive 'bundled' adoption of EVs and PVs could accelerate the adoption of both these sustainable technologies. The results highlights the need to consider transport and building energy efficient technology adoption behavior in a single integrated structure.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

A Generalization of Threshold-Based and Probability-Based Models of Information Diffusion

Diffusion of information through complex networks is of interest in studies such as propagation prediction and influence maximization, both of which have applications in viral marketing and rumor controlling. There are a variety of information diffusion models, all of which simulate the adoption and spread of information over time. However, there is a lack of understanding of whether, despite their conceptual differences, these models represent the same underlying generative structures. For instance, if two different models utilize different conceptual mechanisms, but generate the same results, does the choice of model matter? A classification of diffusion of information models is developed based on the neighbor knowledge of the model infection requirement and the stochasticity of the model. This classification allows for the identification of models that fall into each respective category. The study involves the analysis of the following agent-based models on directed scale-free networks: (1) a linear absolute threshold model (LATM), (2) a linear fractional threshold model (LTFM), (3) the independent cascade model (ICM), (4) Bass-Rand-Rust model (BRRM) (5) a stochastic linear absolute threshold model (SLATM) (6) a stochastic fractional threshold model (SLFTM), and (7) Dodds–Watts model (DWM). Through the execution of simulations and analysis of the experimental results, the distinctive properties of each model are identified. Our analysis reveals that similarity in conceptual design does not imply similarity in behavior concerning speed, final state of nodes and edges, and sensitivity to parameters. Therefore, we highlight the importance of considering the unique behavioral characteristics of each model when selecting a suitable information diffusion model for a particular application.

97 MATHEMATICS AND COMPUTING↗

SMART Deliverable 6.1.2a: Application of the ORION tool to the IBDP Carbon Storage Site

Forecasting and managing potential induced seismic activity is one of the challenges facing commercialscale geologic carbon sequestration (GCS), as well as other geologic energy extraction and byproduct disposal technologies. Historically, the process to develop robust, science-based forecasts of induced seismicity has required an integrated effort from experts in seismology, geomechanics, and reservoir engineering to manage data, develop and evaluate models of subsurface processes, and to calibrate and interpret the results from a range of models to understand site behavior relative to prescribed standards and in the context of uncertainty in geologic characterization data, forecasting models, and operational scenario uncertainty. The Operational Forecasting of Induced Seismicity (ORION) toolkit is an open-source, observation-based forecasting toolkit that is being co-developed by two U.S. DOE-funded initiatives: the National Risk Assessment Partnership (NRAP) and the Scienceinformed Machine Learning for Accelerating Real Time Decisions in Subsurface Applications (SMART) Initiative. ORION is designed to provide functionality to support decision making about seismic hazard analysis and risk management for GCS stakeholders ranging from the public to site operators to expert seismologists. The tool, which is written as open-source code in the Python programming language, is composed of a desktop graphical user interface (GUI) and an underlying forecasting engine. The forecasting engine uses available reservoir properties, well and fluid injection scenario details, and observed seismic catalog data as inputs to produce a set of temporal and spatio-temporal seismic forecasts.

58 GEOSCIENCES↗

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↗

On the Low Risk of Subsynchronous Resonance (SSR) in Type III Wind Turbines Operating in Grid-Forming Control

We have shown in a previous work that the risk of sub-synchronous resonance (SSR) between a wind power plant with Type III wind turbines and series-compensated transmission lines is low when the wind turbines in the plant are operated in grid-forming mode, instead of the standard grid-following mode. The fundamental mechanism behind the improved damping characteristics is explained in this paper by modeling the positive and negative sequence impedances of Type III wind turbines for GFM operation mode. It is discovered that the GFM control naturally acts against the negative resistance of Type III wind turbines that results from an interaction between the proportional gain of the rotor-side converter current controller and negative slip. The developed sequence impedance models and improved damping behavior are verified using PSCAD simulations of a 2.5-MW Type III GFM wind turbine. The modeling predictions are also supported by experimentally measuring the sequence impedance response of a 2.5-MW Type III wind turbine during operation in GFL and GFM modes.

grid-following turbine↗

Particle Swarm Optimization of Dynamic Load Model Parameters in Large Systems

This paper considers two dynamic load models that are widely used in industry to account for induction motor behavior: CMLD and CLOD. These models must be parametrized for the specific utility system in a general way so that they can be used in planning studies and provide a conservative but realistic representation of load behavior. This study considers a measurement-based approach to tuning both models. The load modeling study compares the response of the tuned models to generic candidate models using historical events. This study considers one area-based subsystem to simplify the modeling approach and reduce the number of models required for simulations. Additionally, because dynamic load models often produce similar results for different sets of parameters, a sensitivity study was conducted to assess the parameter impacts on the voltage response. The sensitivity study covers the parameters that are tuned using event measurements. The process to estimate the parameters uses the particle-swarm optimization algorithm. Overall, the performance of the tuned model more accurately captures recovery voltage, delayed recovery, and settling voltage than its predecessor models while not being overly tuned so that it remains general for peak summer conditions.

dynamic load modeling↗

Modelica-based system modeling for studying control-related faults in chiller plants and boiler plants serving large office buildings

System modeling is critical when studying operation faults in chiller plants and boiler plants. However, current fault models have difficulties faithfully representing the operation of chiller plants and boiler plants under the effects of those faults, especially the control-related ones. In this study, we present a systematic method to develop high-fidelity models for approximating the behaviors of chiller plants and boiler plants under faulty conditions. Compared to existing ones, the resulting fault models have two advantages: first, they better characterize the dynamic patterns in the system operation. In those models, control architecture and control logic are faithfully implemented. Thus, they can be used to study control-related faults, such as incorrect staging control due to sensor bias and mistuned feedback control. Second, they are readily extensible and can support large-scale investigations to explore different faulty conditions/scenarios. Those models are established in a hierarchical structure while modules in each layer can be redeclared and parameterized at upper layers. In such a case, modifications to the models can be realized through model modifiers and the process can be easily streamlined with scripts. We applied the proposed models in a comprehensive fault impact evaluation of the 13 control-related faults of chiller and boiler plants. In this evaluation, the proposed plant model is coupled with the EnergyPlus thermal load model to study the impact of various faulty scenarios. Based on the evaluation results, we identified the faults that have the most significant impacts on the operation of the chiller and boiler plants, respectively. We also found that the relationship between the impacts of the studied faults and the severity level of the faults are highly non-linear

Huang, Sen↗