Quantitative Numerical Simulations Research Articles

A Comparative Study of Vehicle Velocity Prediction for Hybrid Electric Vehicles Based on a Neural Network

Vehicle velocity prediction (VVP) plays a pivotal role in determining the power demand of hybrid electric vehicles, which is crucial for establishing effective energy management strategies and, subsequently, improving the fuel economy. Neural networks (NNs) have emerged as a powerful tool for VVP, due to their robustness and non-linear mapping capabilities. This paper describes a comprehensive exploration of NN-based VVP methods employing both qualitative theory analysis and quantitative numerical simulations. The used methodology involved the extraction of key feature parameters for model inputs through the utilization of Pearson correlation coefficients and the random forest (RF) method. Subsequently, three distinct NN-based VVP models were constructed comprising the following: a backpropagation neural network (BPNN) model, a long short-term memory (LSTM) model, and a generative pre-training (GPT) model. Simulation experiments were conducted to investigate various factors, such as the feature parameters, sliding window length, and prediction horizon, and the prediction accuracy and computation time were identified as key performance metrics for VVP. Finally, the relationship between the model inputs and velocity prediction performance was revealed through various comparative analyses. This study not only facilitated the identification of an optimal NN model configuration to balance prediction accuracy and computation time, but also serves as a foundational step toward enhancing the energy efficiency of hybrid electric vehicles.

A stochastic-statistical residential burglary model with independent Poisson clocks

Residential burglary is a social problem in every major urban area. As such, progress has been to develop quantitative, informative and applicable models for this type of crime: (1) the Deterministic-time-step (DTS) model [Short, D’Orsogna, Pasour, Tita, Brantingham, Bertozzi & Chayes (2008) Math. Models Methods Appl. Sci.18, 1249–1267], a pioneering agent-based statistical model of residential burglary criminal behaviour, with deterministic time steps assumed for arrivals of events in which the residential burglary aggregate pattern formation is quantitatively studied for the first time; (2) the SSRB model (agent-based stochastic-statistical model of residential burglary crime) [Wang, Zhang, Bertozzi & Short (2019) Active Particles, Vol. 2, Springer Nature Switzerland AG, in press], in which the stochastic component of the model is theoretically analysed by introduction of a Poisson clock with time steps turned into exponentially distributed random variables. To incorporate independence of agents, in this work, five types of Poisson clocks are taken into consideration. Poisson clocks (I), (II) and (III) govern independent agent actions of burglary behaviour, and Poisson clocks (IV) and (V) govern interactions of agents with the environment. All the Poisson clocks are independent. The time increments are independently exponentially distributed, which are more suitable to model individual actions of agents. Applying the method of merging and splitting of Poisson processes, the independent Poisson clocks can be treated as one, making the analysis and simulation similar to the SSRB model. A Martingale formula is derived, which consists of a deterministic and a stochastic component. A scaling property of the Martingale formulation with varying burglar population is found, which provides a theory to the finite size effects. The theory is supported by quantitative numerical simulations using the pattern-formation quantifying statistics. Results presented here will be transformative for both elements of application and analysis of agent-based models for residential burglary or in other domains.

The orientation order of liquid‐crystalline polymer, measured by ESR and optical dichroism techniques

ABSTRACTMolecular orientation order and rotation mobility of comb‐shaped liquid crystalline polymer forming nematic and smectic mesophases are characterized by spin probe and dichroism technique in the temperature range 100–420 K. The models describing the mechanism of molecular rotations in different temperature ranges were determined by quantitative numerical simulations of ESR spectra. In the vicinity of the glass transition point of the polymer, where the fast amplitude‐restricted molecular reorientations take place, the quasi‐libration model was found to be adequate for the description of ESR spectra, while the often used Brownian rotational diffusion is appropriate at higher temperatures only. Orientation distribution function of probe molecules was characterized quantitatively by order parameters up to sixth rank for a wide temperature range. The orientation order parameters measured via the spin probe technique are shown to correlate with orientation order parameters measured by optical techniques. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019, 57, 819–825

Qualitative Identification of the Static Pull-In and Fundamental Frequency of One-Electrode MEMS Resonators.

This paper attempts to qualitatively identify the static pull-in position, pull-in voltage, and fundamental frequency of one-electrode microresonators from a physical perspective. During theoretical derivation, a generalized one-degree-of-freedom (1-DOF) model in nondimensional form derived using the differential quadrature method (DQM) is first introduced and then transformed for frequency normalization. Based on the deduced formulas, the upper and lower bounds of the static pull-in position and pull-in voltage are both deduced through mathematical proof. To distinguish the monotonic and nonmonotonic behavior of the fundamental frequency versus direct current (DC) voltage, a critical condition decided only by cubic stiffness is then determined. For the first time, two extreme static positions, as well as the corresponding fundamental frequencies and DC voltages to identify different frequency behaviors are derived, and their variations versus cubic stiffness are then discussed and verified. During the simulation process, a high-order DQM and COMSOL 2D model are both applied for numerical analyses. Guided by nondimensional results, typical behaviors with specific physical parameters are examined in detail. Results demonstrate that the curve tendencies between all the qualitative results and quantitative numerical simulations in dimensional form agree well with each other, implying the possibility of using 1-DOF model to qualitatively discuss physical parameters effects on the system statics and dynamics.

Multi-GPU hybrid programming accelerated three-dimensional phase-field model in binary alloy

In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.

Improved Fluorescent Protein Contrast and Discrimination by Optically Controlling Dark State Lifetimes.

Modulation and optical control of photoswitchable fluorescent protein (PS-FP) dark state lifetimes drastically improves sensitivity and selectivity in fluorescence imaging. The dark state population of PS-FPs generates an out-of-phase fluorescence component relative to the sinusoidally modulated 488 nm laser excitation. Because this apparent phase advanced emission results from slow recovery to the fluorescent manifold, we hasten recovery and, therefore, modulation frequency by varying coillumination intensity at 405 nm. As 405 nm illumination regenerates the fluorescent ground state more rapidly than via thermal recovery, we experimentally demonstrate that secondary illumination can control PS-FPs dark state lifetime to act as an additional dimension for discriminating spatially and spectrally overlapping emitters. This experimental combination of out of phase imaging after optical modulation (OPIOM) and synchronously amplified fluorescence image recovery (SAFIRe) optically controls the fluorescent protein dark state lifetimes for improved time resolution, with the resulting modulation-based selective signal recovery being quantitatively modeled. The combined experimental results and quantitative numerical simulations further demonstrate the potential of SAFIRe-OPIOM for wide-field biological imaging with improved speed, sensitivity, and optical resolution over other modulation-based fluorescence microscopies.

Phase equilibria, thermodynamics and microstructure simulation of metastable spinodal decomposition in c–Ti1−xAlxN coatings

Based on the experimental equilibrium data on spinodal decomposition in the literature together with the newly measured data in the present work, a complete metastable phase diagram for the pseudo-binary c–TiN/c-AlN system was constructed for the first time, from which a self-consistent thermodynamic description was then established by means of CALculation of PHAse Diagram (CALPHAD) method with the aid of first-principles computed free energies. By coupling with the CALPHAD thermodynamic database, two- and three-dimensional quantitative numerical simulations of microstructure evolution in metastable c–Ti1−xAlxN coatings during spinodal decomposition were performed using Cahn-Hilliard model. Three sets of diffusivity data available in the literature were carefully screened by comparing the simulated microstructures with the experimental ones, and one of them was chosen for the final simulations. The simulated composition wavelengths during spinodal decomposition at different temperatures agree with the experimental data. Moreover, the effect of the composition fluctuation on the microstructure evolution during spinodal decomposition was also comprehensively investigated.

A key process controlling the wet removal of aerosols: new observational evidence.

The lifetime and spatial distributions of accumulation-mode aerosols in a size range of approximately 0.05–1 μm, and thus their global and regional climate impacts, are primarily constrained by their removal via cloud and precipitation (wet removal). However, the microphysical process that predominantly controls the removal efficiency remains unidentified because of observational difficulties. Here, we demonstrate that the activation of aerosols to cloud droplets (nucleation scavenging) predominantly controls the wet removal efficiency of accumulation-mode aerosols, using water-insoluble black carbon as an observable particle tracer during the removal process. From simultaneous ground-based observations of black carbon in air (prior to removal) and in rainwater (after removal) in Tokyo, Japan, we found that the wet removal efficiency depends strongly on particle size, and the size dependence can be explained quantitatively by the observed size-dependent cloud-nucleating ability. Furthermore, our observational method provides an estimate of the effective supersaturation of water vapour in precipitating cloud clusters, a key parameter controlling nucleation scavenging. These novel data firmly indicate the importance of quantitative numerical simulations of the nucleation scavenging process to improve the model’s ability to predict the atmospheric aerosol burden and the resultant climate forcings, and enable a new validation of such simulations.

Thermo-mechanical behaviour during encapsulation of glass in a steel vessel

Quantitative numerical simulations and qualitative evaluations are conducted to elucidate thermo-mechanical behaviour during pouring and solidification of molten glass into a stainless-steel cylindrical container. Residual stress and structural integrity in this casting/vitrification process is important because it can be used for long-term storage of high-level nuclear wastes. The predicted temperature and stress distributions in the glass and container agree well with previous measurements of the temperature histories and residual stresses. Three different thermal-stress models are developed using the finite-element method and compared. Two simple slice models were developed based on the generalized plane strain assumption as well as a detailed two-dimensional axi-symmetric model that adds elements according to the stages of pouring glass into the stainless steel container. The results reveal that mechanical interaction between the glass and the wall of the stainless steel container generates residual tensile stresses that approach the yield strength of the steel. Together, these results reveal important insights into the mechanism of stress generation in the process, the structural integrity of the product, and accuracy of the modelling-tool predictions.

HiSPoD: a program for high-speed polychromatic X-ray diffraction experiments and data analysis on polycrystalline samples

A high-speed X-ray diffraction technique was recently developed at the 32-ID-B beamline of the Advanced Photon Source for studying highly dynamic, yet non-repeatable and irreversible, materials processes. In experiments, the microstructure evolution in a single material event is probed by recording a series of diffraction patterns with extremely short exposure time and high frame rate. Owing to the limited flux in a short pulse and the polychromatic nature of the incident X-rays, analysis of the diffraction data is challenging. Here, HiSPoD, a stand-alone Matlab-based software for analyzing the polychromatic X-ray diffraction data from polycrystalline samples, is described. With HiSPoD, researchers are able to perform diffraction peak indexing, extraction of one-dimensional intensity profiles by integrating a two-dimensional diffraction pattern, and, more importantly, quantitative numerical simulations to obtain precise sample structure information.

The effect of quenched bond disorder on first-order phase transitions

We investigate the effect of quenched bond disorder on the two-dimensional three-color Ashkin–Teller model, which undergoes a first-order phase transition in the absence of impurities. This is one of the simplest and striking models in which quantitative numerical simulations can be carried out to investigate emergent criticality due to disorder rounding of first-order transition. Utilizing extensive cluster Monte Carlo simulations on large lattice sizes of up to 128×128 spins, each of which is represented by three colors taking values ±1, we show that the rounding of the first-order phase transition is an emergent criticality. We further calculate the correlation length critical exponent, ν, and the magnetization critical exponent, β, from finite size scaling analysis. We find that the critical exponents, ν and β, change as the strength of disorder or the four-spin coupling varies, and we show that the critical exponents appear not to be in the Ising universality class. We know of no analytical approaches that can explain our non-perturbative results. However our results should inspire further work on this important problem, either numerical or analytical.

Experiments and numerical simulations of thermal shock crack patterns in thin circular ceramic specimens

An attempt was made to explore the formation mechanism of thermal shock crack patterns in ceramics and to develop quantitative numerical simulations. A set of experiments on thin circular ceramic specimens yielded two-dimensional readings of thermal shock crack patterns with periodical and hierarchical characteristics. The numerical simulations of the thermal shock crack patterns are based on the minimum potential energy principle, where the convective heat transfer coefficient at high temperatures, which is difficult to measure, was inversely estimated by the crack spacing, which is easy to measure. Numerical simulation results were in good agreement with the experimental data. Several interesting thermal shock crack evolution phenomena were found. Two stability criteria of crack propagation, i.e. the minimum potential energy principle and the fracture mechanics bifurcation theory, were compared. It was found that the two criteria verify and complement each other. The present study leads to an improved understanding of the formation and evolution of thermal shock crack patterns in ceramics and can help engineers to assess the thermal shock failure of practical ceramic components.

Control of DNA Capture by Nanofluidic Transistors

We report the use of an array of electrically gated ~200 nm solid-state pores as nanofluidic transistors to manipulate the capture and passage of DNA. The devices are capable of reversibly altering the rate of DNA capture by over 3 orders of magnitude using sub-1 V biasing of a gate electrode. This efficient gating originates from the counter-balance of electrophoresis and electroosmosis, as revealed by quantitative numerical simulations. Such a reversible electronically tunable biomolecular switch may be used to manipulate nucleic acid delivery in a fluidic circuit, and its development is an important first step toward active control of DNA motion through solid-state nanopores for sensing applications.

Electromagnetically-induced Deformation of Functionalized Fabric

This work investigates the deformation of charged fabric via external electromagnetic fields. A reduced-order model is constructed by combining a yarn-segment network representation with dynamic discrete/lumped charged-masses. The deformation of the fabric is dictated by solving a coupled system of differential equations for the motion of the lumped charged-masses, which are coupled through the yarn-segments. Initially, the effects of the electric and magnetic fields are analytically studied for the components (yarn-segment network and charged-masses) that comprise the model. Quantitative numerical simulations are then provided for the entire, assembled, larger-scale, coupled system, based on a computationally-efficient time-stepping algorithm. The model is relatively easy to implement and provides analysts with a straightforward tool to study electromagnetic fabric systems.

The Effect of Load (Pressure) for Quantitative EHL Film Thickness

New quantitative numerical simulations of the elastohydrodynamic lubrication (EHL) film thickness using realistic pressure and shear-dependent rheology and realistic compressibility have indicated that the dependence of central film thickness upon Hertz pressure (or load) for the classic Newtonian, slightly compressible solution is merely a lower limit with magnitudes three times as great being possible. Experimental measurements of central film thickness employing Hertz pressures from 1.0 to 2.6 GPa confirm that for a neat mineral oil, the classical pressure dependence is accurate, while for two gear oils the experimental pressure dependence is much larger. Shear-dependent viscosity is a major factor and compressibility plays a lesser role, while there is evidence that mechanical degradation is also important. New experimental evidence of the enhanced scale sensitivity resulting from shear-thinning has also been obtained. These results for the pressure and scale dependence have dire implications for the usual practice of extrapolation of film thickness from experimental measurements at large scale and low pressure using effective pressure–viscosity coefficients. For machines of small scale and high pressure, the extrapolation will sometimes result in substantially overestimated film thicknesses.

Rheology and high-pressure models for quantitative elastohydrodynamics

With the recent appearance of quantitative numerical simulations of the elastohydrodynamic lubrication of concentrated contacts, accurate models that can reproduce the behaviour that has been observed in viscometers for more than 50 years are now needed. This article summarizes the most recent work regarding modelling the temperature and pressure dependence of density, the temperature, pressure, and shear dependence of viscosity, and the pressure and shear dependence of the stress at localization. Thermal conductivity is addressed as well.

An Experimental Validation of the Recently Discovered Scale Effect in Generalized Newtonian EHL

New quantitative numerical simulations of the elastohydrodynamic lubrication (EHL) film forming ability of generalized Newtonian liquids have elucidated a previously unrecognized property of EHL films. The dependency of the film thickness on the scale of the contact is greater when the viscosity is shear dependent within the inlet. Measurements of film thickness were performed in a ball on disc experiment using balls ranging from 5.5 to 35 mm in diameter. Three liquids were investigated with varying shear dependence in the range of stress important to film forming. The experimental results confirm the previous analytical findings. Numerical simulations using the measured viscosities show that the increased scale sensitivity is substantially the result of shear-thinning. However, the smallest scales produced films thinner than even the shear-dependent prediction, possibly indicating molecular degradation. It is quite likely that some machine components, which were designed using the effective viscous properties derived from a larger scale film thickness measurement, are operating with substantially lower film thickness than the designer had intended.

Hydrodynamic Response of Northeastern Gulf of Mexico to Hurricanes

The northeastern Gulf of Mexico in the USA is extremely susceptible to the impacts of tropical cyclones because of its unique geometric and topographic features. Focusing on Hurricanes Ivan (2004) and Katrina (2005), this paper has addressed four scientific questions on this area’s response to hurricanes: (1) How does the shallow, abandoned Mississippi delta contribute to the storm surge? (2) What was the controlling factor that caused the record-high storm surge of Hurricane Katrina? (3) Why are the responses of an estuary to Hurricanes Ivan and Katrina so different from the corresponding surges on the open coast? (4) How would the storm surge differ if Hurricane Katrina had taken a different course? Guided by field observations of winds, waves, water levels, and currents, two state-of-the-art numerical models for storm surges and wind waves have been coupled to hindcast the relevant hydrodynamic conditions, including storm surges, surface waves, and depth-averaged currents. Fairly good agreement between the modeled and measured surge hydrographs was found. The quantitative numerical simulations and simple qualitative analysis have revealed that the record-high storm surge of Hurricane Katrina was caused by the interaction of the surge with the extremely shallow, ancient deltaic lobe of Mississippi River. A hypothetical scenario formed by shifting the path of Hurricane Katrina to the observed path of Hurricane Frederic (1979) resulted in a much smaller surge than that observed in coastal Mississippi and Louisiana. However, this scenario did still result in a high surge near the head of Mobile Bay. One of the important lessons learned from Hurricane Katrina is that the Saffir–Simpson scale should be systematically revised to reflect the topographic and geometric features of a complex, heterogeneous coast, including the possible surge amplification in an estuary or a submerged river delta.

Pillars of Heaven

Sometimes the most beautiful things are the hardest to understand. Pillars like those of the Eagle Nebula form at the boundary between some of the hottest (10000 K) and coldest (10 K) gas in the Galaxy. Many physical processes come into play in the birth and growth of such gaseous pillars: hydrodynamic instability, photoionization, ablation, recombination, molecular heating and cooling, and probably magnetic fields. High-quality astronomical observations, quantitative numerical simulations, and scaled laser experiments provide a powerful combination for understanding their formation and evolution.

Numerical Analysis of Ca 2+ Depletion in the Transverse Tubular System of Mammalian Muscle

Calcium currents were recorded in contracting and actively shortening mammalian muscle fibers. In order to characterize the influence of extracellular calcium concentration changes in the small unstirred lumina of the transverse tubular system (TTS) on the time course of the slow L-type calcium current ( I Ca), we have combined experimental measurements of I Ca with quantitative numerical simulations of Ca 2+ depletion. I Ca was recorded both in calcium-buffered and unbuffered external solutions using the two-microelectrode voltage clamp technique (2-MVC) on short murine toe muscle fibers. A simulation program based on a distributed TTS model was used to calculate the effect of ion depletion in the TTS. The experimental data obtained in a solution where ion depletion is suppressed by a high amount of a calcium buffering agent were used as input data for the simulation. The simulation output was then compared with experimental data from the same fiber obtained in unbuffered solution. Taking this approach, we could quantitatively show that the calculated Ca 2+ depletion in the transverse tubular system of contracting mammalian muscle fibers significantly affects the time-dependent decline of Ca 2+ currents. From our findings, we conclude that ion depletion in the tubular system may be one of the major effects for the I Ca decline measured in isotonic physiological solution under voltage clamp conditions.