Numerical modeling of air-fiber flows

The dynamics of fiber suspensions are of great importance in applications such as the dry-forming process of pulp mats for use in hygiene products. In this forming process, fibers are transported in flowing air. The fibers interact with the fluid, and may interact with each other and interlock in flocs. The characteristics of the suspension structure are essential for the design and optimization of the forming process, and for improving the quality of the final products. Particularly, it is desired to achieve a uniform fiber distribution in the pulp mats. Thus, it is of high interest to develop tools, which can be used to perform comprehensive studies of the complex phenomenon of fiber suspension flows. This work is concerned with numerical analysis of fiber suspensions, related to the mat-forming process. For that purpose, a particle-level fiber model has been implemented into an open source computational fluid dynamics (CFD) code. A fiber is modeled as a chain of rigid cylindrical segments. The segments interact with the flow through hydrodynamic drag forces, and may interact with each other through short-range attractive forces. The segments are tracked individually using Lagrangian particle tracking (LPT). The implemented model comprises two alternatives, the flexible and the rigid fiber model, respectively. The equations of motion of a flexible fiber represent the application of Euler's second laws for rigid body motion for the fiber segments. The flexible fiber model takes into account all the degrees of freedom necessary to realistically reproduce the fiber dynamics. Connectivity forces act between the adjacent fiber segments to ensure the fiber integrity. The rigid fiber model keeps the relative orientation between the segments fixed. The equations of motion are formulated for the fiber as a whole, while the hydrodynamic contributions are taken into account from the individual segments. The fiber inertia is taken into account in both alternatives of the model. The fiber model has been coupled with imposed flow fields, or with flow fields computed by the CFD solvers. The behavior of the implemented model is compared with analytical and experimental results available in the literature. The simulation results show that the model correctly predicts the dynamics of isolated rigid and flexible fibers in creeping shear flow. The model is used to study the dynamics of flexible and rigid fibers in high Reynolds number flows and in geometries that are representative for the mat-forming process. The effects of fiber properties, such as fiber inertia and fiber length are analyzed. Simulations are carried out to investigate the rheology of suspensions of flexible and curved fibers in creeping shear flow of a Newtonian fluid. The effects of fiber flexibility and fiber curvature on the specific viscosity and the normal stress differences are examined. Finally, aggregation of rod-like fibers is investigated in a turbulent flow of an asymmetric planar diffuser. The influences of the average flow gradient, the fiber inertia and the turbulence dispersion on the aggregation rate are analyzed. The study identifies a darting fiber motion as a mechanism that significantly enhances fiber collisions and aggregation

Shape evolution of long flexible fibers in viscous flows

The present work studies numerically the dynamics and shape evolution of long flexible fibers suspended in a Newtonian viscous cellular flow using a particle-level fiber simulation technique. The fiber is modeled as a chain of massless rigid cylindrical segments connected by ball and socket joints; one-way coupling between the fibers and the flow is considered while Brownian motion is neglected. The effect of stiffness, equilibrium shape, and aspect ratio of the fibers on the shape evolution of the fibers are analyzed. Moreover, the influence of fiber stiffness and their initial positions and orientations on fiber transport is investigated. For the conditions considered, the results show that the fiber curvature field resembles that of the flow streamline. It is found that the stiffer fibers experience not only a quicker relaxation phase, in which they transient from their initial shape to their "steady-state shape," but they also regain their equilibrium shape to a larger extent. The findings also demonstrate that even a small deviation of fiber shape from perfectly straight impacts significantly the early-stage evolution of the fiber shape and their bending behavior. Increasing the fiber aspect ratio, when other parameters are kept fixed, leads the fiber to behave more flexible, and it consequently deforms to a larger extent to adjust to the shape of the flow streamlines. In agreement with the available experimental results, the fiber transport studies show that either the fiber becomes trapped within the vortices of the cellular array or it moves across the vortical arrays while exhibiting various complex shapes

System-level modeling and thermal simulations of large battery packs for electric trucks

Electromobility has gained significance over recent years and the requirements on the performance and efficiency of electric vehicles are growing. Lithium-ion batteries are the primary source of energy in electric vehicles and their performance is highly dependent on the operating temperature. There is a compelling need to create a robust modeling framework to drive the design of vehicle batteries in the ever-competitive market. This paper presents a system-level modeling methodology for thermal simulations of large battery packs for electric trucks under real-world operating conditions. The battery pack was developed in GT-SUITE, where module-to-module discretization was performed to study the thermal behavior and temperature distribution within the pack. The heat generated from each module was estimated using Bernardi’s expression and the pack model was calibrated for thermal interface material properties under a heat-up test. The model evaluation was performed for four charging/discharging and cooling scenarios typical for truck operations. The results show that the model accurately predicts the average pack temperature, the outlet coolant temperature and the state of charge of the battery pack. The methodology developed can be integrated with the powertrain and passenger cabin cooling systems to study complete vehicle thermal management and/or analyze different battery design choices

Multiphysics simulation optimization framework for lithium-ion battery pack design for electric vehicle applications

Large-scale commercialization of electric vehicles (EVs) seeks to develop battery systems with higher energy efficiency and improved thermal performance. Integrating simulation-based design optimization in battery development process expands the possibilities for novel design exploration. This study presents a dual-stage multiphysics simulation optimization methodology for comprehensive concept design of Lithium-ion (Li-ion) battery packs for EV applications. At the first stage, multi-objective optimization of electrochemical thermally coupled cells is performed using genetic algorithm considering the specific energy and the maximum temperature of the cells as design objectives. At the second stage, the energy efficiency and the thermal performances of each optimally designed cell are evaluated under pack operation to account for cell-to-pack interactions under realistic working scenarios. When operating at 1.5 C discharge current, the battery pack comprising optimally designed cells for which the specific energy and the maximum temperature are equally weighted delivers the highest specific energy with enhanced thermal performance. The most favorable pack design shows 8% reduction in maximum pack temperature and 16.1% reduction in module-to-module temperature variations compared to commercially available pack. The methodology for design optimization presented in this work is generic, providing valuable knowledge for future cell and pack designs that employ different chemistries and configurations

Lithium-ion Battery Pack Design for Electric Vehicles Using GT-AutoLion: Multi-Physics Simulation and Multi-Criteria Optimization Approach

High specific energy battery systems with improved thermal performance are required for large-scale introduction of electric vehicles (EVs) into the market. This study presents a comprehensive multi-physics simulation and multi-criteria optimization framework for Lithium-ion (Li-ion) battery pack design for EV applications. The battery cells are modeled by electrochemical thermally coupled approach using GT-AutoLion. Multi-objective optimization using genetic algorithm is employed to explore energy and thermally efficient cell design alternatives. The performances of the optimally designed cells are then evaluated under pack environment to account for inhomogeneities in large traction battery packs under realistic working scenarios. It is observed that considering the thermal efficiency of battery cells is crucial for obtaining improved battery pack performance. The integrated framework developed in this work provides systematic pack-aware guidelines for manufacturers already at the initial cell design stage. Moreover, the proposed design optimization methodology is generic, handing over valuable knowledge for future cell and pack designs for various applications

Revealing driver psychophysiological response to emergency braking in distracted driving based on field experiments

Purpose: The purpose of this paper is to characterize distracted driving by quantifying the response time and response intensity to an emergency stop using the driver’s physiological states. Design/methodology/approach: Field tests with 17 participants were conducted in the connected and automated vehicle test field. All participants were required to prioritize their primary driving tasks while a secondary nondriving task was asked to be executed. Demographic data, vehicle trajectory data and various physiological data were recorded through a biosignalsplux signal data acquisition toolkit, such as electrocardiograph for heart rate, electromyography for muscle strength, electrodermal activity for skin conductance and force-sensing resistor for braking pressure. Findings: This study quantified the psychophysiological responses of the driver who returns to the primary driving task from the secondary nondriving task when an emergency occurs. The results provided a prototype analysis of the time required for making a decision in the context of advanced driver assistance systems or for rebuilding the situational awareness in future automated vehicles when a driver’s take-over maneuver is needed. Originality/value: The hypothesis is that the secondary task will result in a higher mental workload and a prolonged reaction time. Therefore, the driver states in distracted driving are significantly different than in regular driving, the physiological signal improves measuring the brake response time and distraction levels and brake intensity can be expressed as functions of driver demographics. To the best of the authors’ knowledge, this is the first study using psychophysiological measures to quantify a driver’s response to an emergency stop during distracted driving

A study of a flexible fiber model and its behavior in DNS of turbulent channel flow

The dynamics of individual flexible fibers in a turbulent flow field have been analyzed, varying their initial position, density and length. A particlelevel fiber model has been integrated into a general-purpose, open source Computational Fluid Dynamics (CFD) code. The fibers are modeled as chains of cylindrical segments connected by ball and socket joints. The equations of motion of the fibers contain the inertia of the segments, the contributions from hydrodynamic forces and torques, and the connectivity forces at the joints. Direct Numerical Simulation (DNS) of the incompressible Navier–Stokes equations is used to describe the fluid flow in a plane channel and a one-way coupling is considered between the fibers and the fluid phase. We investigate the translational motion of fibers by considering the mean square displacement of their trajectories. We find that the fiber motion is primarily governed by velocity correlations of the flow fluctuations. In addition, we show that there is a clear tendency of the thread-like fibers to evolve into complex geometrical configurations in a turbulent flow field, in fashion similar to random conformations of polymer strands subjected to thermal fluctuations in a suspension. Finally, we show that fiber inertia has a significant impact on reorientation time-scales of fibers suspended in a turbulent flow field

Revealing driver psychophysiological response to emergency braking in distracted driving based on field experiments

Purpose – The purpose of this paper is to characterize distracted driving by quantifying the response time and response intensity to an emergency stop using the driver’s physiological states. Design/methodology/approach – Field tests with 17 participants were conducted in the connected and automated vehicle test field. All participants were required to prioritize their primary driving tasks while a secondary nondriving task was asked to be executed. Demographic data, vehicle trajectory data and various physiological data were recorded through a biosignalsplux signal data acquisition toolkit, such as electrocardiograph for heart rate, electromyography for muscle strength, electrodermal activity for skin conductance and force-sensing resistor for braking pressure. Findings – This study quantified the psychophysiological responses of the driver who returns to the primary driving task from the secondary nondriving task when an emergency occurs. The results provided a prototype analysis of the time required for making a decision in the context of advanced driver assistance systems or for rebuilding the situational awareness in future automated vehicles when a driver’s take-over maneuver is needed. Originality/value – The hypothesis is that the secondary task will result in a higher mental workload and a prolonged reaction time. Therefore, the driver states in distracted driving are significantly different than in regular driving, the physiological signal improves measuring the brake response time and distraction levels and brake intensity can be expressed as functions of driver demographics. To the best of the authors’ knowledge, this is the first study using psychophysiological measures to quantify a driver’s response to an emergency stop during distracted driving

Particle-level simulations of flocculation in a fiber suspension flowing through a diffuser

We investigate flocculation in dilute suspensions of rigid, straight fibers in a decelerating flow field of a diffuser. We carry out numerical studies using a particle-level simulation technique that takes into account the fiber inertia and the non-creeping fiber-flow interactions. The fluid flow is governed by the Reynolds-averaged Navier-Stokes equations with the standard k-omega eddy-viscosity turbulence model. A one-way coupling between the fibers and the flow is considered with a stochastic model for the fiber dispersion due to turbulence. The fibers interact through short-range attractive forces that cause them to aggregate into flocs when fiber-fiber collisions occur. We show that ballistic deflection of fibers greatly increases the flocculation in the diffuser. The inlet fiber kinematics and the fiber inertia are the main parameters that affect fiber flocculation in the pre-diffuser region

An investigation into Macro BIM Maturity and Its impacts: A comparison of Qatar and the United Kingdom

Emerging frameworks of BIM implementation have proposed several attributes as measures of macro-scale BIM maturity within countries. Such macro-scale BIM maturity indicators determine the policy and institutional imperatives for BIM diffusion at the national and market levels. Although macro-scale initiatives are enacted to ultimately drive micro-scale (organisational) BIM adoption, it remains unclear whether they have been effective in practice. To ascertain this, the macro-scale BIM maturity of two countries (Qatar and the United Kingdom) are examined in order to identify the influence of the key macro-scale maturity factors on implementation at the micro-scale. Based on expert BIM maturity evaluation and interviews (n=16), the maturity of both countries was ascertained and compared. Subsequently, a survey (n=73) of construction businesses was used to solicit opinions about the relevance of macro-BIM maturity factors to implement at the micro-level. The study further identifies peculiarities with respect to the maturity levels of both countries. The findings indicate that both Qatar and UK have generally comparable levels of macro-BIM maturity, although, in some areas, both countries failed to meet the expectations of organisations in terms of facilitating their BIM adoption at the micro-level. Qatari organisations were of the opinion that further maturity is required in relation to champions and drivers, as well as regulatory frameworks. Similarly, in the UK, organisations were of the view that there was a need for more in terms of champions and drivers as well as noteworthy publications in order to facilitate micro-scale adoption