Faculty of Science and Engineering
Based at Thornton Science Park, the new Faculty of Science and Engineering is located in a major research and innovation hub for the North West which is only a 20minute bus trip from the main Chester Campus. The Faculty offers degrees in engineering and science disciplines using a strongly interdisciplinary teaching philosophy.
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Velocity distribution of liquid phase at gasliquid twophase stratified flow based on particle image velocimetryHorizontal gasliquid flows are commonly encountered in the production section of the oil and gas industry. To further understand all parameters of the pipe crosssection, this paper use particle image velocimetry to study the circular pipe crosssection liquid velocity distribution rule. Firstly the focus is on the software and hardware combination of image correction system, to solve the influence of different refractive indexes of medium and pipeline curvature caused by image distortion. Secondly, the velocity distribution law of the corrected stratified flow (the range of liquid flow of 0.09–0.18 m3/h, and gas flow range of 0.3–0.7 m3/h) crosssection at different flow points of the pipeline crosssection at x = 0 and in the Y direction at the maximum liquid velocity is studied. It is found that these distribution laws are caused by the influence of the interphase force of the gasliquid interface and the resistance of the pipe wall. The current measurements also produce a valuable data set that can be used to further improve the stratified flow model for gasliquid flow.

(Ba0.6Sr0.4)TiO3/PEEK composites modified by Polyethersulfone with low dielectric constant and high dielectric tunability under DC biasCeramic/polyetheretherketone (PEEK) composites show a wide range of applications and have attracted extensive interest in the scientific community due to their outstanding dielectric and mechanical characteristics. However, the interface connection between the ceramic and PEEK is a vital issue that must be addressed to improve their physical and electrical properties. In this work, the polyethersulfone resin (PES) was selected as interface modifier between barium strontium titanate (Ba0.6Sr0.4TiO3, BST) and PEEK. Coldpressing sintering was used to create BST/PEEK materials with superior dielectric frequency stability and dielectric tunability. The effects of PES content on the morphology and dielectric characteristics of PES modified BST/PEEK materials were investigated. The results showed PES could improve the dispersion of BST particles in polymer. The dielectric constant, dielectric tunability, and breakdown strength increased first, then reduced as PES content increased. The composite had the most homogeneous microstructure and the best dielectric properties when the PES content was 7.5vol%. The frequency dispersion factor F(x) was much smaller than that of other ceramic/polymer composites reported. In addition, the dielectric tunability of the composites could reach a relatively high level (34.18%) while the dielectric constant was as low as 14. The dielectric tunable efficiency (TuE) was proposed to evaluate the property of low dielectric constant and high dielectric tunability under DC bias. The TuE of PES modified BST/PEEK composites show the highest value comparing with reported dielectric tunable composites. This research laid the path for the development of a novel ceramic/polymer composite with good interface bonding and high dielectric tunability.

THz probing ferroelectric domain wall dynamicsThis work uses THz time domain spectroscopy (THzTDS) to detect the dynamics of domain walls in a Aurivillius phase ferroelectric ceramic, Ca 0.96 Rb 0.02 Ce 0.02 Bi 2 Nb 2 O 9 . Results show that ferroelectric domain walls are active at the THz band, with lower dielectric permittivity compared with that of the domain. This work has verified that it is feasible to use domain wall engineering method to optimize properties of ferroelectrics at the THz band, which help create new applications for ferroelectric materials at THz frequency.

L1 scheme for solving an inverse problem subject to a fractional diffusion equationThis paper considers the temporal discretization of an inverse problem subject to a time fractional diffusion equation. Firstly, the convergence of the L1 scheme is established with an arbitrary sectorial operator of spectral angle < π / 2 , that is the resolvent set of this operator contains { z ∈ C ∖ { 0 } :  Arg z  < θ } for some π / 2 < θ < π . The relationship between the time fractional order α ∈ ( 0 , 1 ) and the constants in the error estimates is precisely characterized, revealing that the L1 scheme is robust as α approaches 1. Then an inverse problem of a fractional diffusion equation is analyzed, and the convergence analysis of a temporal discretization of this inverse problem is given. Finally, numerical results are provided to confirm the theoretical results.

Higher moments for the Stochastic Cahn  Hilliard Equation with multiplicative Fourier noiseWe consider in dimensions $d=1,2,3$ the $\eps$dependent stochastic CahnHilliard equation with a multiplicative and sufficiently regular in space infinite dimensional Fourier noise with strength of order $\mathcal{O}(\eps^\gamma)$, $\gamma>0$. The initial condition is nonlayered and independent from $\eps$. Under general assumptions on the noise diffusion $\sigma$, we prove moment estimates in $H^1$ (and in $L^\infty$ when $d=1$). Higher $H^2$ regularity $p$moment estimates are derived when $\sigma$ is bounded, yielding as well space H\"older and $L^\infty$ bounds for $d=2,3$, and path a.s. continuity in space. All appearing constants are expressed in terms of the small positive parameter $\eps$. As in the deterministic case, in $H^1$, $H^2$, the bounds admit a negative polynomial order in $\eps$. Finally, assuming layered initial data of initial energy uniformly bounded in $\eps$, as proposed by X.F. Chen in \cite{chenjdg}, we use our $H^1$ $2$dmoment estimate and prove the stochastic solution's convergence to $\pm 1$ as $\eps\rightarrow 0$ a.s., when the noise diffusion has a linear growth.

New methodology to reduce power by using smart street lighting systemOne of most important things now is to create smart street and smart lighting system to save enormous electrical energy. Especially Iraq is suffering shortage of electrical energy generation up to 45%. Because of this, Iraq needs to save a lot of electrical energy in the entire country so as to meet the electrical demand and reduce the large amount of CO2 emission. However, this work presents a very unique and economic control lighting system (CLS) for main streets and sidewalks, which can control the lighting system to give sufficient illumination to the drivers and the pedestrians simultaneously. And at the same time, the CLS system can reduce a lot of electrical energy consumption and the CO2 emissions together. However, by using these smart systems with the exciting illumination source in the streets, the CLS can minimize the electrical energy consumed for the lighting at the main roads and the footpath by about 60% and can use the surplus energies to fill the shortage of electricity in the country. Also, this system will increase the lifetime of the lighting system which means further decrease in cost. Finally, this work presents new type of illumination source, highintensity discharge (HID), which can reduce the electrical consumption much more by up to 90%, when using the CLS with HID.

Lossless Compression of Neuromorphic Vision Sensor Data Based on Point Cloud RepresentationVisual information varying over time is typically captured by cameras that acquire data via images (frames) equally spaced in time. Using a different approach, Neuromorphic Vision Sensors (NVSs) are emerging visual capturing devices that only acquire information when changes occur in the scene. This results in major advantages in terms of low power consumption, wide dynamic range, high temporal resolution, and lower data rates than conventional video. Although the acquisition strategy already results in much lower data rates than conventional video, such data can be further compressed. To this end, in this paper we propose a lossless compression strategy based on point cloud compression, inspired by the observation that, by appropriately reporting NVS data in a $(x,y,t)$ tridimensional space, we have a point cloud representation of NVS data. The proposed strategy outperforms the benchmark strategies resulting in a compression ratio up to 30% higher for the considered.

Design and Simulation of Reversible TimeSynchronized QuantumDot Cellular Automata Combinational Logic Circuits with Ultralow Energy DissipationThe quantumdot cellular automata (QCA) represent emerging nanotechnology that is poised to supersede the current complementary metaloxidesemiconductor digital integrated circuit technology. QCA constitutes an extremely promising transistorless paradigm that can be downscaled to the molecular level, thereby facilitating terascale device integration and extremely low energy dissipation. Reversible QCA circuits, which have reversibility sustained down from the logical level to the physical level, can execute computing operations dissipating less energy than the Landauer energy limit (kBTln2). Time synchronization of logic gates is an essential additional requirement, especially in cases involving complex circuits, for ensuring accurate computational results. This paper reports the design and simulation of eight new both logically and physically reversible timesynchronized QCA combinational logic circuits. The new circuit design presented here mitigates the clock delay problems, which are caused by the nonsynchronization of logic gate information, via the use of an inherently more symmetric circuit configuration. The simulation results confirm the behaviour of the proposed reversible timesynchronized QCA combinational logic circuits which exhibit ultralow energy dissipation and simultaneously provide accurate computational results.

Rare earth iondoped Y2.95R0.05MgAl3SiO12 (R = Yb, Y, Dy, Eu, Sm) garnettype microwave ceramics for 5G applicationIn this work, Y2.95R0.05MgAl3SiO12 (R=Yb, Y, Dy, Eu, Sm) microwave singlephase dielectric ceramics were successfully prepared via conventional ceramic technology by doping a series of rare earth elements with different ionic radius (Yb, Y, Dy, Eu, Sm) for the first time. The effects of A site occupied by rare earth elements on the microwave dielectric properties of Y2.95R0.05MgAl3SiO12 were studied by crystal structure refinement, scanning electron microscope (SEM), bond valence theory, PVL theory and infrared reflection spectroscopy. It was found that the ionicity of YO bond, the lattice energy, the bond energy and bond valance of Al(Tet)O bond had important effects on microwave dielectric properties. Particularly, the optimum microwave dielectric properties were obtained for Y2.95Dy0.05MgAl3SiO12 sintered at 1575 °C for 6 h, with εr = 9.68, Q×f = 68,866 GHz, and τf = 35.8 ppm/°C, displaying its potential prospect in the 5G communication.

Terahertz Faraday rotation of SrFe12O19 hexaferrites enhanced by NbdopingThe magnetooptical and dielectric behaviour of Mtype hexaferrites as permanent magnets in the THz band are essential for potential applications like microwave absorbers and antennas, while are rarely reported recent years. In this work, singlephase SrFe12xNbxO19 hexaferrite ceramics were prepared by conventional solid state sintering method. Temperaturedependent of dielectric parameters were investigated here to search the relationship between dielectric response and magnetic phase transition. The saturated magnetization increases by nearly 12% while the coercive field decreases by 30% in the x = 0.03 composition compared to that of the x = 0.00 sample. Besides, Nb substitution improves the magnetooptical behaviour in the THz band by comparing the Faraday rotation parameter from 0.75 (x = 0.00) to 1.30 (x = 0.03). The changes in the magnetic properties are explained by a compositiondriven increase of the net magnetic moment and enhanced ferromagnetic exchange coupling. The substitution of donor dopant Nb on the Fe site is a feasible way to obtain multifunctional Mtype hexaferrites, as preferred candidates for permanent magnets, sensors and other electronic devices.

FinFETbased nonlinear analog signal processing modulesFinFETs exhibit far superior transistor characteristics (better gate control and a lower subthreshold slope) as compared to the standard MOSFETs, this paper first employs the FinFETs in the design of an operational transconductance amplifier (OTA). The FinFETbased OTA offers a linearity range and  3 dB bandwidth of 300 mV and 631.81 GHz, respectively. Further, the nonlinear applications of the proposed OTA, viz. voltage divider, memristor emulator, and a memristive neuron, are presented. The proposed analog voltage divider circuit contains one OTA and two external NFinFETs. The maximum bandwidth obtained for the voltage divider is 217.54 GHz. The memristor emulator contains one OTA, two external NFinFETs, and one grounded capacitor. The proposed emulator circuit follows the signature characteristics of the actual memristor device. The frequency response characteristics of the proposed emulator circuit depict a bandwidth of 22.7 GHz. The proposed emulator shows nonvolatile as well as electronically tunable features. Next, MonteCarlo simulation analysis has been performed on the proposed circuits in order to observe the effects of statistical variation in different operating conditions. Furthermore, we propose a FinFETbased passive memristive neuron model using a memristor emulator circuit. The proposed neuron circuit follows a tangent hyperbolic activation function. All the proposed circuits are suitable for monolithic implementation. The proposed circuits are verified using 20 nm FinFET technology. The simulation results obtained using HSPICE agree well with the theoretical analysis.

Finite difference method for timefractional KleinGordon equation on an unbounded domain using artificial boundary conditionsA finite difference method for timefractional KleinGordon equation with the fractional order $\alpha \in (1, 2]$ on an unbounded domain is studied. The artificial boundary conditions involving the generalized Caputo derivative are derived using the Laplace transform technique. Stability and error estimates of the proposed finite difference scheme are proved in detail by using the discrete energy method. Numerical examples show that the artificial boundary method is a robust and efficient method for solving the timefractional KleinGordon equation on an unbounded domain.

Correction of HighOrder Lk Approximation for SubdiffusionThe subdiffusion equations with a Caputo fractional derivative of order $\alpha \in (0, 1)$ arise in a wide variety of practical problems, which describe the transport processes, in the forcefree limit, slower than Brownian diffusion. In this work, we derive the correction schemes of the Lagrange interpolation with degree $k ( \leq 6)$ convolution quadrature, called $L_{k}$ approximation, for the subdiffusion. The key step of designing correction algorithm is to calculate the explicit form of the coefficients of $L_{k}$ approximation by the polylogarithm function or BoseEinstein integral. To construct a $\tau_{8}$ approximation of BoseEinstein integral, the desired $(k+1\alpha)$thorder convergence rate can be proved for the correction $L_{k}$ scheme with nonsmooth data, which is higher than kthorder BDFk method in [Jin, Li, and Zhou, SIAM J. Sci. Comput., 39 (2017), A3129–A3152; Shi and Chen, J. Sci. Comput., (2020) 85:28]. The numerical experiments with spectral method are given to illustrate theoretical results.

Detailed Error Analysis for a Fractional Adams Method on CaputoHadamard Fractional Differential EquationsWe consider a predictorcorrector numerical method for solving CaputoHadamard fractional differential equation over the uniform mesh $\log t_{j} = \log a + \big ( \log \frac{t_{N}}{a} \big ) \big ( \frac{j}{N} \big ), \, j=0, 1, 2, \dots, N$~with $a \geq 1$, where $\log a = \log t_{0} < \log t_{1} < \dots < \log t_{N}= \log T$ is a partition of $[\log a, \log T]$. The error estimates under the different smoothness properties of the solution $y$ and the nonlinear function $f$ are studied. Numerical examples are given to verify that the numerical results are consistent with the theoretical results.

Opportunities for improved space heating energy efficiency from fluid property modificationsUnsteady behaviour of hydronic heating systems causes higher mean room temperatures than are required for comfort. Peak room temperatures depend on interactions between thermostats, heat emitters and the room. The importance of fluid properties on such unsteady heating is often misunderstood meaning potential energy savings are overlooked. This paper demonstrates the influence of fluid modifications and indicates a plausible magnitude of the energy saving opportunity. The results showed that fluid side heat transfer coefficient in isolation had negligible effect. Specific heat capacity of the fluid and flow rates were important, as they altered the amount of embedded energy in the heat emitter when thermostat was met. Reductions in mean heating power for steady demand conditions were between 0 and 7% for plausible changes to fluid properties, depending on heat emitter size, room insulation and external temperature. Reductions in individual cycle energy were between 5 and 25%. When considered in the context of intermittent finite duration heating events, those that contained a small number of thermostat cycles demonstrated energy savings that tended towards the reductions in individual cycle energy. Heating events with larger numbers of cycles showed energy savings tending towards the reduction in mean heating power.

A stable platinum porphyrinbased photocatalyst for hydrogen production under visible light in waterA stable system containing a Pt metallated porphyrin as a molecular solid photocatalyst in acidic aqueous solution is able to produce hydrogen efficiently, under visible light irradiation. The system shows an average H2 evolution of 467.3 μmol g1 h1.

Dietary restriction and ageing: Recent evolutionary perspectivesDietary restriction (DR) represents one of the most robust interventions for extending lifespan. It is not known how DR increases lifespan. The prevailing evolutionary hypothesis suggests the DR response redirects metabolic resources towards somatic maintenance at the expense of investment in reproduction. Consequently, DR acts as a proximate mechanism which promotes a prolongevity phenotype. This idea is known as resource reallocation. However, growing findings suggest this paradigm could be incomplete. It has been argued that during DR it is not always possible to identify a tradeoff between reproduction and lifespan. It is also suggested the relationship between reproduction and somatic maintenance can be uncoupled by the removal or inclusion of specific nutrients. These findings have created an imperative to reexplore the nexus between DR and evolutionary theory. In this review I will address this evolutionary conundrum. My overarching objectives are fourfold: (1) to outline some of the evidence for and against resource reallocation; (2) to examine recent findings which have necessitated a theoretical reevaluation of the link between life history theory and DR; (3) to present alternatives to the resource reallocation model; (4) to present emerging variables which potentially influence how DR effects evolutionary tradeoffs.

Deep Learning based Human Detection in PrivacyPreserved Surveillance VideosVisual surveillance systems have been improving rapidly over the recent past, becoming more capable and pervasive with incorporation of artificial intelligence. At the same time such surveillance systems are exposing the public to new privacy and security threats. There have been an increasing number of reports of blatant abuse of surveillance technologies. To counteract this, data privacy regulations (e.g. GDPR in Europe) have provided guidelines for data collection and data processing. However, there is still a need for a private and secure method of model training for advanced machine learning and deep learning algorithms. To this end, in this paper we propose a privacypreserved method for visual surveillance. We first develop a dataset of privacy preserved videos. The data in these videos is masked using Gaussian Mixture Model (GMM) and selective encryption. We then train highperformance object detection models on the generated dataset. The proposed method utilizes stateofart object detection deep learning models (viz. YOLOv4 and YOLOv5) to perform human/object detection in masked videos. The results are encouraging, and are pointers to the viability of the use of modern day deep learning models for object detection in privacypreserved videos.