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Two Nash-equilibrium-based steering control models for representing a driver’s interaction with vehicle automated steering
No full textAutomated steering technology offers significant benefits to the safety of vehicles, but desire to keep the human driver in the loop requires a better understanding of the interaction between driver and vehicle. An existing noncooperative–game–theoretic framework for modelling such interaction is revisited, leading to the development of two driver steering control models. Both bear Nash–equilibrium properties, but involve different assumptions about driver steering behaviour. A simulation study is performed to demonstrate the difference between the two driver models. An experiment using a fixed–base driving simulator is conducted to measure six test subjects' steering angles in response to the lane–change manoeuvres generated by an automated steering controller. The two driver models' capabilities for representing driver steering behaviour are investigated through fitting them to measured driver steering angles. Key model parameters are identified using a system identification procedure. It is found that the two driver models have equivalent capability in capturing the trend of the six test subjects' measured steering angles, but less good at reproducing the overshoot and oscillation involved in two subjects' steering angles. It is found that the inclusion of an arm neuromuscular system model can improve the performance of the proposed driver models
Neuronal oscillator robustness to multiple global perturbations
No full textNeuronal activity depends on ion channels and biophysical processes that are strongly and differentially sensitive to physical variables such as temperature and pH. Nonetheless, neuronal oscillators can be surprisingly resilient to perturbations in these variables. We study a three-neuron pacemaker ensemble that drives the pyloric rhythm of the crab, Cancer borealis. These crabs routinely experience a number of global perturbations, including changes in temperature and pH. Although pyloric oscillations are robust to such changes, for sufficiently large deviations the rhythm reversibly breaks down. As temperature increases beyond a tipping point, oscillators transition to silence. Acidic pH deviations also show tipping points, with a reliable transition first to tonic spiking, then to silence. Surprisingly, robustness to perturbations in pH only moderately affects temperature robustness. Consistent with high animal-to-animal variability in biophysical circuit parameters, tipping points in temperature and pH vary across animals. However, the ordering and discrete classes of transitions at critical points are conserved. This implies that qualitative oscillator dynamics are preserved across animals despite high quantitative parameter variability. A universal model of bursting dynamics predicts the existence of these transition types and the order in which they occur
Chemo-mechanical model of a cell as a stochastic active gel
No full textWhile it is commonly observed that the shape dynamics of mammalian cells can undergo large random fluctuations, theoretical models aiming at capturing cell mechanics often focus on the deterministic part of the motion. In this paper, we present a framework that couples an active gel model of the cell mechanical scaffold with the complex cell metabolic system stochastically delivering the chemical energy needed to sustain an active stress in the scaffold. Our closure assumption setting the magnitude of the fluctuations is that the chemo-mechanical free energy of the cell is controlled at a target homeostatic value. Our model rationalizes the experimental observation that the cell shape fluctuations depend on the mechanical environment that constraints the cell. We apply our framework to the simple case of a cell migrating on a one dimensional track to successfully capture the different regimes of the cell mean square displacement along the track as well as the magnitude of the long time scale effective diffusive motion of the cell
Erratum: A generalization of the Lagrange-Hamilton formalism with application to non-conservative systems and the quantum to classical transition (Journal of Mathematical Physics (2021) 62 (033503) DOI: 10.1063/5.0039248)
No full textThis article was originally published online on March 3, 2021 with a typographical error in the title. “Lagrange” was misspelled as “Langrange.” All online versions of the article were corrected on March 4, 2021. The title appears correctly above
Multiscale numerical modeling of solid particle penetration and hydrocarbons removal in a catalytic stripper
No full textThe catalytic stripper has emerged as a technology for removal of semivolatile material from aerosol streams for automotive and aerospace emissions measurements, including portable solid particle emissions measurements governed by the Real Driving Emissions regulations. This study employs coupled energy and mass transfer models to predict solid particle penetration and hydrocarbon removal for various configurations of a catalytic stripper. The continuum-scale macromodel applies mass, momentum and energy conservation for the inlet heating region of a catalytic stripper whereby the catalyst monolith is represented by a porous medium. The particle and species dynamics inside the catalytic monolith were computed by coupled microsimulations of the monolith channel using boundary conditions from the macromodel. The results from the numerical simulations were validated with corresponding experimental data and employed using a parametric study of flow rate and catalyst length with a view to optimizing the operating condition. Results of the simulation and experiment show that solid particle penetration through the catalytic stripper can exceed approximately 60% for particles at 10 nm mobility diameter and hydrocarbons removal of >95% for an optimized catalytic stripper device. Copyright © 2021 American Association for Aerosol Research
The instantaneous dynamic resistance voltage of DC-carrying REBCO tapes to AC magnetic field
No full textWhen a REBCO tape carrying DC transport current is exposed to a perpendicular AC magnetic field with amplitude above certain value, flux could be triggered to traversing the superconducting tape. During the process, a biased DC response voltage, called the dynamic resistance voltage will be induced. In the paper, the calculation on the time-dependent dynamic resistance voltage was carried out by the H-formulation model implemented in the finite-element method (FEM) software package COMSOL Multiphysics. Fourier analysis on the waveform of dynamic resistance voltage was utilized to figure out the main components of the response voltage. The DC component, second harmonic component and ratio of the two components can reflect how the instantaneous dynamic resistance responds to the applied AC magnetic field and the DC transport current. The findings in the paper can be used to monitor the state of DC-carrying REBCO tapes subject to an AC magnetic field
Pruning Pareto optimal solutions for multi-objective portfolio asset management
No full textBudget allocation problems in portfolio management are inherently multi-objective as they entail different types of assets of which performance metrics are not directly comparable. Existing asset management methods that either consolidate multiple goals to form a single objective (a priori) or populate a Pareto optimal set (a posteriori) may not be sufficient because a decision maker (DM) may not possess comprehensive knowledge of the problem domain. Moreover, current techniques often present a Pareto optimal set with too many options, making it counter-productive. In order to provide the DM with a diverse yet compact solution set, this paper proposes a three-step approach. In the first step, we employ different approximation functions to capture investment-performance relationships at the asset-type level. These simplified relationships are then used as inputs for the multi-objective optimisation model in the second step. In the final step, Pareto optimal solutions generated by a selected evolutionary algorithm are pruned by a clustering method. To measure the spread of representative solutions over the Pareto front, we present two novel indicators based on average Euclidean distance and cosine similarity between original Pareto solutions and representative solutions. Through numerical examples, we demonstrate that this approach can provide a set of representative solutions that maintain high integrity of the original Pareto front. We also put forward suggestions on choosing appropriate approximation functions, pruning methods, and indicators
Smart transport: A comparative analysis using the most used indicators in the literature juxtaposed with interventions in English metropolitan areas
No full textThe development of smart transport technologies, methods, strategies and infrastructures has drawn much attention in recent years, owing to the rise of smart cities paradigms and the rapid technological advancements in the transport sector. New transport technologies create opportunities and challenges for English cities to move towards a more sustainable and integrated future. Smart governance and interventions in the English metropolitan areas are reviewed to provide a background of the smart city and transport development in the UK. Despite the increasing commercial and political attention, there is still a lack of understanding and proposals for a robust framework to evaluate the smart transport system. It is challenging to build a toolbox that suits both academics and practitioners when developing transport interventions and investments. This paper proposes a comprehensive and up-to-date framework to assess smart transport development in cities. A systematic literature review is conducted to identify the most used indicators and important indices. New indicators that illustrate trending themes are added to the existing toolbox. In total, 49 indicators are listed in this study, including five new ones. We also show several aspects and the overall performance in the new evaluation framework by aggregating indicators into indices in the following groups: 1) private, public and emergency transport indices; 2) accessibility, sustainability and innovation indices; and 3) a composite index. The new evaluation framework is applied in eleven English metropolitan areas. The empirical results show that Greater London has the best development in smart transport, followed by West Midlands and West of England. The findings can provide useful insights for metropolitan authorities and their transport authorities when key devolution strategies are in place and substantial investment packages are considered
Distributed abstraction and verification of an installed optical fibre network
No full textThe management of wavelength routed optical mesh networks is complex with many potential light path routes and numerous physical layer impairments to transmission performance. This complexity can be reduced by applying the ideas of abstraction from computer science where different equipment is described in the same basic terms. The noise-to-signal ratio can be used as a metric to describe the quality of transmission performance of a signal propagated through a network element and accumulates additively through a sequence of such elements allowing the estimation of end-to-end performance. This study aims to explore the robustness of the noise-to-signal ratio metric in an installed fibre infrastructure. We show that the abstracted noise-to-signal ratio is independent of the observers and their location. We confirm that the abstracted noise-to-signal ratio can reasonably predict the performance of light-paths subsequently set in our network. Having a robust network element abstraction that can be incorporated into routeing engines allows the network management controller to make decisions on the most effective way to use the network resources in terms of the routeing and data coding format
Online handwritten Gurmukhi word recognition using fine-tuned Deep Convolutional Neural Network on offline features
No full textThe recognition of online handwriting is a vital application of pattern recognition, which involves the extraction of spatial and temporal information of handwritten patterns, and understanding the handwritten text while writing on the digital surface. Although, online handwriting recognition is a mature but exciting and fast developing field of pattern recognition, the same is not true for many of the Indic scripts. Gurmukhi is one of such popular scripts of India, and online handwriting recognition issues for larger units as words or sentences largely remained unexplored for this script till date. The existing study and first ever attempt for online handwritten Gurmukhi word recognition has relied upon the widely used hidden Markov model. This existing study evaluated against and performed very well in their chosen metrics. But, the available online handwritten Gurmukhi word recognition system could not obtain more than 90% recognition accuracy in data dependent environment too. The present study provided benchmark results for online handwritten Gurmukhi word recognition using deep learning architecture convolutional neural network, and obtained above 97% recognition accuracy in data dependent mode of handwriting. The previous Gurmukhi word recognition system followed the stroke based class labeling approach, whereas the present study has followed the word based class labeling approach. Present Online handwritten Gurmukhi word recognition results are quite satisfactory. Moreover, the proposed architecture can be used to improve the benchmark results of online handwriting recognition of several major Indian scripts. Experimental results demonstrated that the deep learning system achieved great results in Gurmukhi script and outperforms existing results in the literature