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At least 91 records · Page 5

Calibration of Car-Following Models Using a Dual Genetic Algorithm with Central Composite Design

We report the calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. Finally, this method can be extended to other optimization tasks using GA in transportation studies.

42 ENGINEERING↗

HPC4Mfg with Sepion

We employed ab-initio simulations and quantum chemical calculations to develop a computational framework for simulating the microscopic structure and mechanical properties of novel polymer membranes used in lithium sulfur batteries. To meet industry targets, next generation batteries with high specific energy (Wh/kg) are essential. Efforts to commercialize light-weight, energy-dense lithium-sulfur secondary batteries (2510 Wh/kg) have been stalled by ongoing problems with the battery’s separator membrane, which should prevent cross-over of active material from cathode to anode that, if unchecked, limits cycle-life. However, Sepion Technologies’ polymer membranes yield long-lasting lithium-sulfur cells. Advancing to 10 Ah battery prototypes, Sepion faces challenges in membrane manufacturing related to polymer processing and the molecular basis for membrane performance and durability. High performance computing offers critical new insight into these phenomena, which in turn will accelerate product entry into the market.

25 ENERGY STORAGE↗

Pedestrian-Involved Traffic Signal Optimization Using Decentralized Graph-based Multi-Agent Reinforcement Learning

Incorporating pedestrian movements in traffic signal timing optimization is essential for ensuring smooth and safe urban transportation systems. To develop an effective signal timing plan, it is crucial to comprehend how various pedestrian accommodation strategies impact both vehicle and pedestrian flow. This study explores the application of the Decentralized Graph-based Multi-Agent Reinforcement Learning (DGMARL) method for signal timing optimization. It considers both pedestrian and vehicle traffic state and assesses the effects of fixed and adaptive pedestrian request response on traffic and signal timing. The evaluation of DGMARL encompasses vehicles Eco_PI which is fuel consumption impact related to vehicle stops and stop delay, and pedestrian waiting time to ensure overall system efficiency. The proposed approach was evaluated using a Digital Twin microscopic traffic simulation model of MLK Smart Corridor in Chattanooga, Tennessee. The evaluation outcomes of vehicles Eco_PI, pedestrian waiting time and serving time are compared with the actuated and DGMARL signal timing with fixed pedestrian recall and minimum recall to determine the most suitable approaches for various traffic conditions. The results indicated that, on average, the strategy of Signal timing optimization with adaptive pedestrian request response improved the Eco_PI by 32.43%, and Signal timing optimization with both automated pedestrian traffic demand and adaptive pedestrian request response improved the Eco_PI by 31.62% compared to the actuated and DGMARL signal timing with fixed pedestrian recall and minimum recall.

K Kumarasamy, Vijayalakshmi↗

Battery Electric Vehicle Eco-Cooperative Adaptive Cruise Control in the Vicinity of Signalized Intersections

This study develops a connected eco-driving controller for battery electric vehicles (BEVs), the BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The developed controller can assist BEVs while traversing signalized intersections with minimal energy consumption. The calculation of the optimal vehicle trajectory is formulated as an optimization problem under the constraints of (1) vehicle acceleration/deceleration behavior, defined by a vehicle dynamics model; (2) vehicle energy consumption behavior, defined by a BEV energy consumption model; and (3) the relationship between vehicle speed, location, and signal timing, defined by vehicle characteristics and signal phase and timing (SPaT) data shared under a connected vehicle environment. The optimal speed trajectory is computed in real-time by the proposed BEV eco-CACC-I controller, so that a BEV can follow the optimal speed while negotiating a signalized intersection. The proposed BEV controller was tested in a case study to investigate its performance under various speed limits, roadway grades, and signal timings. In addition, a comparison of the optimal speed trajectories for BEVs and internal combustion engine vehicles (ICEVs) was conducted to investigate the impact of vehicle engine types on eco-driving solutions. Lastly, the proposed controller was implemented in microscopic traffic simulation software to test its networkwide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed controller can effectively reduce stop-and-go traffic in the vicinity of signalized intersections and that the BEV Eco-CACC-I controller produces average savings of 9.3% in energy consumption and 3.9% in vehicle delays.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Developing a Hybrid Electric Vehicle Eco-Cooperative Adaptive Cruise Control System at Signalized Intersections.

This study develops an eco-driving strategy for hybrid electric vehicles (HEVs) in the vicinity of signalized intersections, entitled HEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The proposed system computes real-time, energy-optimized vehicle trajectories using HEV vehicle dynamics and energy consumption models. In the proposed system, a simple HEV energy model is used to compute the instantaneous fuel consumption. This HEV energy model is selected since it is general, transferable, and can be easily used to compute instantaneous energy consumption levels for HEVs without the additional input of vehicle engine data or complicated power control strategies. In addition, a vehicle dynamics model is used to capture the relationship between speed, acceleration level, and tractive/resistance forces on vehicles. The energy-optimum problem is formulated as an optimization problem with constraints, which is solved using a moving-horizon dynamic programming approach. The proposed HEV Eco-CACC-I system was tested to evaluate its performance for various speed limits, roadway grades, and signal timings. Lastly, the proposed HEV controller was implemented in a microscopic traffic simulation software to test its network-wide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed system can effectively reduce stop-and-go traffic in the vicinity of signalized intersections producing savings of 7.4% in energy consumption, 5.8% in traffic delay and 23% vehicle stops, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

On the Impact of Bus Dwelling on Macroscopic Fundamental Diagrams

Network macroscopic fundamental diagrams (MFDs) have recently been shown to exist in real-world urban traffic networks. When present, MFDs can be used to model traffic dynamics within an urban network by dividing the network into a set of spatially compact homogeneous regions and tracking the average level of congestion in each region. Existing analytical methods to estimate MFD mostly focus on the behavior of a single type of vehicle and do not capture the patterns of mixed traffic (e.g., cars and buses). The existence of buses matters since a bus will block the movements of other vehicles when it dwells at the bus stop. This paper proposes an analytical method to estimate the impact of bus dwelling on a network’s MFD based on the network’s geometric features, traffic control strategies, and bus operation parameters, and validates the performance of the proposed method using simulations based on microscopic traffic models. Comparisons of the analytical and simulation results show that the proposed analytical method can generally provide a good estimate of the lower bound and upper bound of the network’s MFD.

Xu, Guanhao↗

Design and Development of Modules to Support Live Microscopic Imaging on Ground-Based Microgravity Simulators

In space, astronauts are exposed to environmental stressors that often result in physiological changes. One prominent stressor in spaceflight is microgravity, and research has shown that long term microgravity exposure causes muscle atrophy, bone loss, cardiovascular concerns, and vision impairment. It is critical to understand how altered gravity affects physiology on the cellular, molecular, and gene level in order to accurately assess health risks and to develop effective countermeasures. Ground-based microgravity simulators such as random positioning machines (RPMs) are used to produce some of the biological effects of altered gravity on different cell types and organisms. Real-time imaging during simulations are of particular interest as we can study how basic cell functions such as cell division, cell migration, and proliferation progress under microgravity conditions. However, design limitations of present microgravity simulators such as susceptibility to parasitic vibration and displacement of the sample from the center of rotation challenge the accuracy of experiment results and live images. We have developed a cell culture sample holder module suitable for live microscopic imaging on an RPM. CAD modeling and 3D printing technology were used to implement modifications to the sample holder and to install a digital microscope to perform live bright-field and fluorescent imaging. Vibration damping materials were also investigated to allow for stable imaging while the microgravity simulator was within a cell culture incubator. Novel methods and hardware modifications for improving live cell imaging on ground-based microgravity simulators were proposed and discussed.

3D printing↗

Modeling a Miniaturized Scanning Electron Microscope Focusing Column - Lessons Learned in Electron Optics Simulation

This presentation discusses work done to assess the design of a focusing column in a miniaturized Scanning Electron Microscope (SEM) developed at the NASA Marshall Space Flight Center (MSFC) for use in-situ on the Moon-in particular for mineralogical analysis. The MSFC beam column design uses purely electrostatic fields for focusing, because of the severe constraints on mass and electrical power consumption imposed by the goals of lunar exploration and of spaceflight in general. The resolution of an SEM ultimately depends on the size of the focused spot of the scanning beam probe, for which the stated goal here is a diameter of 10 nanometers. Optical aberrations are the main challenge to this performance goal, because they blur the ideal geometrical optical image of the electron source, effectively widening the ideal spot size of the beam probe. In the present work the optical aberrations of the mini SEM focusing column were assessed using direct tracing of non-paraxial rays, as opposed to mathematical estimates of aberrations based on paraxial ray-traces. The geometrical ray-tracing employed here is completely analogous to ray-tracing as conventionally understood in the realm of photon optics, with the major difference being that in electron optics the lens is simply a smoothly varying electric field in vacuum, formed by precisely machined electrodes. Ray-tracing in this context, therefore, relies upon a model of the electrostatic field inside the focusing column to provide the mathematical description of the "lens" being traced. This work relied fundamentally on the boundary element method (BEM) for this electric field model. In carrying out this research the authors discovered that higher accuracy in the field model was essential if aberrations were to be reliably assessed using direct ray-tracing. This led to some work in testing alternative techniques for modeling the electrostatic field. Ultimately, the necessary accuracy was attained using a BEM/Fourier series hybrid approach. The presentation will give background remarks about the MSFC mini Lunar SEM concept and electron optics modeling, followed by a description of the alternate field modeling techniques that were tried, along with their incorporation into a ray-trace simulation. Next, the validation of this simulation against commercially available software will be discussed using an example lens as a test case. Then, the efficacy of aberration assessment using direct ray-tracing will be demonstrated, using this same validation case. The discussion will include practical error checks of the field solution. Finally, the ray-trace assessment of the MSFC mini Lunar SEM concept will be shown and discussed. The authors believe this presentation will be of general interest to practitioners of modeling and simulation, as well as those with a general optics background. Because electron optics and photon optics share many basic concepts (e.g., lenses, images, aberrations, etc.), the appeal of this presentation need not be restricted to just those interested in charged particle optics.

Modeling Miniaturizing Scanning↗

Simulating Space Weathering in the Transmission Electron Microscope via Dynamic in Situ Heating and Helium Irradiation of Olivine

The chemical composition, microstructure, and optical properties of grains on the surfaces of airless bodies are predominantly altered by micrometeorite impacts and solar wind irradiation. These processes drive space weathering and result in the formation of features including chemically-altered, amorphous grain rims, Fe nanoparticles (npFe), and vesiculated grain textures. These characteristics have been identified in returned samples from the surfaces of the Moon and asteroid Itokawa. In order to advance our understanding of the formation of these microstructural and chemical features in returned samples, we have simulated space weathering processes for a variety of materials via laboratory experiments. These experiments include ion irradiation to simulate solar wind exposure and laser irradiation and in situ heating to simulate micrometeorite impacts. While these experiments have provided considerable insight into the formation mechanisms of many space weathering features, they are predominantly static and typically performed separately. Here we present results from the simulated space weathering of olivine grains via He irradiation and dynamic heating, both performed in situ inside the transmission electron microscope (TEM). These experiments allow for the real-time observation of chemical and microstructural changes resulting from the superposed effects of ion irradiation and pulsed heating.

Thompson, M. S.↗

Unified understanding of the impact of semiflexibility, concentration, and molecular weight on macromolecular-scale ring diffusion

Conformationally fluctuating, globally compact macromolecules such as polymeric rings, single-chain nanoparticles, microgels, and many-arm stars display complex dynamic behaviors due to their rich topological structure and intermolecular organization. Synthetic rings are hybrid objects with conformations that display both ideal random walk and compact globular features, which can serve as models of genomic DNA. To date, emphasis has been placed on the effect of ring molecular weight on their unusual behaviors. Here, we combine simulations and a microscopic force-level theory to build a unified understanding for how key aspects of ring dynamics depend on different tunable molecular properties including backbone rigidity, monomer concentration, degree of traditional entanglement, and molecular weight. Our large-scale molecular dynamics simulations of ring melts with very different backbone stiffnesses reveal unanticipated behaviors which agree well with our generalized theory. This includes a universal master curve for center-of-mass diffusion constants as a function of molecular weight scaled by a chemistry and thermodynamic state-dependent critical molecular weight that generalizes the concept of an entanglement cross-over for linear chains. The key physics is how backbone rigidity and monomer concentration induced changes of the entanglement length, interring packing, degree of interpenetration, and liquid compressibility slow down space-time dynamic-force correlations on macromolecular scales. A power law decay of the center-of-mass diffusion constant with inverse molecular weight squared is the first consequence, followed by an ultraslow activated hopping transport regime. Our results set the stage to address slow dynamics and kinetic arrest in different families of compact synthetic and biological polymeric systems.

Science & Technology - Other Topics↗

Predicting Complex Relaxation Processes in Metallic Glass

Relaxation processes significantly influence the properties of glass materials. However, understanding their specific origins is difficult; even more challenging is to forecast them theoretically. In this study, using microseconds molecular dynamics simulations together with an accurate many-body interaction potential, we predict that an Al 90 Sm 10 metallic glass would have complex relaxation behaviors: In addition to the main (α) relaxation, the glass (i) shows a pronounced secondary (β) relaxation at cryogenic temperatures and (ii) exhibits an anomalous relaxation process (α 2 ) accompanying α relaxation. Both of the predictions are verified by experiments. Computational simulations reveal the microscopic origins of relaxation processes: while the pronounced β relaxation is attributed to the abundance of stringlike cooperative atomic rearrangements, the anomalous α 2 process is found to correlate with the decoupling of the faster motions of Al with slower Sm atoms. The combination of simulations and experiments represents a first glimpse of what may become a predictive routine and integral step for glass physics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Magnetic monopoles and toroidal moments in LuFeO 3 and related compounds

Magnetic monopoles and toroidal order are compelling features that have long been theorized but remain elusive in real materials. Multiferroic hexagonal ferrites and manganites are an interesting realization of frustrated triangular lattice of spins, where magnetic order is interacting with ferroelectricity and trimerization. In this paper, we discuss a microscopic mechanism by which trimerization leads to a modulation of magnetic exchanges, and therefore magnetic monopolar and toroidal orders emerge from the combination of 120° antiferromagnetism and trimerization. The experimentally observable signatures of magnetic monopolar and toroidal orders are identified in the inelastic neutron scattering cross section, simulated from a microscopic model of LuFeO 3 . The nonreciprocal magnon propagation is demonstrated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Microscopic and Macroscopic Characterization of Grain Boundary Energy and Strength in Silicon Carbide via Machine-Learning Techniques

Predicting the properties of grain boundaries poses a challenge because of the complex relationships between structural and chemical attributes both at the atomic and continuum scales. Grain boundary systems are typically characterized by parameters used to classify local atomic arrangements in order to extract features such as grain boundary energy or grain boundary strength. The present work utilizes a combination of high-throughput atomistic simulations, macroscopic and microscopic descriptors, and machine-learning techniques to characterize the energy and strength of silicon carbide grain boundaries. Additionally, a diverse data set of symmetric tilt and twist grain boundaries are described using macroscopic metrics such as misorientation, the alignment of critical low-index planes, and the Schmid factor, but also in terms of microscopic metrics, by quantifying the local atomic structure and chemistry at the interface. These descriptors are used to create random-forest regression models, allowing for their relative importance to the grain boundary energy and decohesion stress to be better understood. Results show that while the energetics of the grain boundary were best described using the microscopic descriptors, the ability of the macroscopic descriptors to reasonably predict grain boundaries with low energy suggests a link between the crystallographic orientation and the resultant atomic structure that forms at the grain boundary within this regime. For grain boundary strength, neither microscopic nor macroscopic descriptors were able to fully capture the response individually. However, when both descriptor sets were utilized, the decohesion stress of the grain boundary could be accurately predicted. These results highlight the importance of considering both macroscopic and microscopic factors when constructing constitutive models for grain boundary systems, which has significant implications for both understanding the fundamental mechanisms at work and the ability to bridge length scales.

36 MATERIALS SCIENCE↗

Hysteresis curves reveal the microscopic origin of cooperative CO 2 adsorption in diamine-appended metal–organic frameworks

Diamine-appended metal-organic frameworks (MOFs) of the form Mg 2 (dobpdc)(diamine) 2 adsorb CO 2 in a cooperative fashion, exhibiting an abrupt change in CO 2 occupancy with pressure or temperature. This change is accompanied by hysteresis. While hysteresis is suggestive of a first-order phase transition, we show that hysteretic temperature-occupancy curves associated with this material are qualitatively unlike the curves seen in the presence of a phase transition; they are instead consistent with CO 2 chain polymerization, within one-dimensional channels in the MOF, in the absence of a phase transition. Here, our simulations of a microscopic model reproduce this dynamics, providing a physical understanding of cooperative adsorption in this industrially important class of materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward a Reversible Calcium-Sulfur Battery with a Lithium-Ion Mediation Approach

Calcium represents a promising anode for the development of high-energy-density, low-cost batteries. Yet, a lack of suitable electrolytes has restricted the development of rechargeable batteries with a Ca anode. Furthermore, to achieve a high energy density system, sulfur would be an ideal cathode to couple with the Ca anode. Unfortunately, a reversible calcium-sulfur (Ca-S) battery has not yet been reported. Herein, a basic study of a reversible nonaqueous room-temperature Ca-S battery is presented. The reversibility of the Ca-S chemistry and high utilization of the sulfur cathode are enabled by employing a Li + -ion-mediated calcium-based electrolyte. Mechanistic insights pursued by spectroscopic, electrochemical, microscopic, and theoretical simulation (density functional theory) investigations imply that the Li + -ions in the Ca-electrolyte stimulate the reactivation of polysulfide/sulfide species. The coordination of lithium to sulfur reduces the formation of sturdy Ca-S ionic bonds, thus boosting the reversibility of the Ca-S chemistry. Furthermore, the presence of Li + -ions facilitates the ionic charge transfer both in the electrolyte and across the solid electrolyte interphase layer, consequently reducing the interfacial and bulk impedance of Ca-S batteries. As a result, both the utilization of active sulfur in the cathode and the discharge voltage of Ca-S batteries are significantly improved.

25 ENERGY STORAGE↗

Phase field modeling of shearing processes of a dual-lobed γ"|γ'|γ" coprecipitate

The Ni-based superalloy IN718 is one of the most widely used commercial alloy in the aerospace industry since its development in 1960s. The excellent mechanical properties have been attributed in a great deal to strengthening by coherent γ' and γ" precipitates. The deformation mechanisms of these two phases have been well studied individually. Recent experimental characterization has shown coprecipitates of these two phases in a variety of morphologies and it was argued that these coprecipitates may lead to improved strengthening as compared to their monolithic counterparts. However, the deformation mechanisms of these coprecipitates are still not well understood. In this study, we performed microscopic phase field simulations, with generalized-stacking-fault (GSF) energy surfaces from ab initio calculations as inputs, to systematically study the shearing processes of a periodical array of dual-lobed coprecipitates as well as monolithic precipitates. We found that the coupling between the γ' and γ" phases in the coprecipitates forces dislocations to take high energy shearing pathways in both phases that would not occur if they were in monolithic forms. The coupling also creates stacking fault configurations in the coprecipitates that require high stress to form. Thus, the presence of coprecipitates in general should increase the resistance to dislocation shearing and lead to higher strength levels. Various fault configurations observed during the shearing process are documented as a reference for future comparison with experimental observations. The link between stacking fault shearing and microtwinning is also discussed. Here, the mechanisms analyzed in this study deepens our understanding of coprecipitation effects on alloy strength and may form a cornerstone for multi-precipitate strengthened alloy design strategies.

36 MATERIALS SCIENCE↗