Erping Zhou

Sandwich structures fabricated from an aluminium skinned foam enclosed within a carbon fibre reinforced composite structure have the potential application for high-performance on- and off-road automotive vehicles. The deformations and failure of these types of structures are presented, and results indicate that the application of aluminium face sheets with aluminium foam (AF) aids to prevent the delamination of the outer layers of carbon fibre reinforced polymers (CFRP). The load carrying capacity has been increased by utilising a manufacturing method to maintain the adhesion between the core and the skins until the failure stage is reached. The core shear and de-bonded issue associated with this type of sandwich structure can be addressed by this manufacture method. The peak average flexure load capacity of an aluminium foam sandwich structure (AFSS) with a completely wrapped around CFRP skin was 2800 N with a mass of 191 g. This compares favourably with previously used AFSS without the skins, which had a peak average load of 600 N and a mass of 125 g. An initial finite element model for comparison purposes has been developed to represent the structure’s behaviour and predict the associated failure loads. It is proposed that CFRP wrapped around AFSS enhances the structural performance without significant weight gain.

The rapid uptake of energy harvesting triboelectric nanogenerators (TENGs) for self-powered electronics requires the development of high-performance tribo-materials capable of providing large power outputs. This work reports on the synthesis and use of aniline formaldehyde resin (AFR) for energy-harvesting applications. The facile, acidic-medium reaction between aniline and formaldehyde produces the aniline-formaldehyde condensate, which upon an in-vacuo high temperature curing step provides smooth AFR films with abundant nitrogen and oxygen surface functional groups which can acquire a tribo-positive charge and thus endow AFR with a significantly higher positive tribo-polarity than the existing state-of-art polyamide-6 (PA6). A TENG comprising of optimized thin-layered AFR against a polytetrafluomethylene (PTFE) film produced a peak-to-peak voltage of up to similar to 1000 V, a current density of similar to 65 mA m(-2), a transferred charge density of similar to 200 mu C m(-2) and an instantaneous power output (energy pulse) of similar to 11 W m(-2) (28.1 mu J cycle(-1)), respectively. The suitability of AFR was further supported through the Kelvin probe force microscopy (KPFM) measurements, which reveal a significantly higher average surface potential value of 1.147 V for AFR as compared to 0.87 V for PA6 and a step-by-step increase of the surface potential with the increase of energy generation cycles. The work not only proposes a novel and scalable mouldable AFR synthesis process but also expands with excellent prospects, the current portfolio of tribo-positive materials for triboelectric energy harvesting applications.

Electrospinning is a simple, versatile technique for fabricating fibrous nanomaterials with the desirable features of extremely high porosities and large surface areas. Using emulsion electrospinning, polytetrafluoroethylene/polyethene oxide (PTFE/PEO) membranes were fabricated followed by a sintering process to obtain pure PTFE fibrous membranes, which were further utilised against a polyamide 6 (PA6) membrane for vertical contact-mode triboelectric nanogenerators (TENGs). Electrostatic force microscopy (EFM) measurements of the sintered electrospun PTFE membranes revealed the presence of both positive and negative surface charges owing to the transfer of positive charge from PEO which further corroborated by FTIR measurements. To enhance the ensuing triboelectric surface charge, a facile negative charge-injection process was carried out onto the electrospun (ES) PTFE subsequently. The fabricated TENG gave a stabilised peak-to-peak open-circuit-voltage (Voc) of up to ~900 V, a short-circuit current density (Jsc) of ~20 mAm-2 and a corresponding charge density of ~149 μCm-2, which are ~12, 14 and 11 times higher than the corresponding values prior to the ion-injection treatment. This increase in surface charge density is caused by the inversion of positive surface charges with the simultaneous increase in the negative surface charge on the PTFE surface, which was confirmed by using EFM measurements. The negative charge injection led to an enhanced power output density of ~9 Wm-2 with high stability as confirmed from the continuous operation of the ion-injected PTFE/PA6 TENG for 30,000 operation cycles, without any visible reduction in the output. The work thus introduces a relatively simple, cost-effective and environmentally friendly technique for fabricating fibrous fluoropolymer polymer membranes with high thermal/chemical resistance in TENG field and an ion-injection method which is able to dramatically improve the surface charge density of the PTFE fibrous membranes.

Utilising an interfacial piezoelectric ZnO nanosheet layer, a significant enhancement in the power density is reported for the triboelectric nanogenerators (TENG) based on phase inversion membranes of polyvinylidene fluoride (PVDF) and polyamide-6 (PA6). At an applied force of 80 N, the TENG device incorporating electrochemically deposited ZnO nanosheets produces an output voltage of ~ 625 V and a current density of ~ 40 mA m−2 (corresponding a charge density of 100.6 μC m−2), respectively; significantly higher than ~ 310 V and ~ 10 mA m−2 (corresponding a charge density of 77.45 μCm−2) for the pristine TENG device. The enhancement in the surface charge density provided by the interfacial piezoelectric ZnO layer is also reflected in the high piezoelectric coefficient d33 (−74 pm V−1) as compared to the pristine fluoropolymer membranes (−50 pm V−1). For tribo-negative membranes incorporating the interfacial ZnO layer, piezoelectric force microscopy measurements further show enhanced domain size which can be attributed to the interfacial dipoledipole interaction with the ferroelectric polarisation of PVDF, which promotes the alignment with the polar axis of ZnO. Under compressive stress, the piezoelectric potential thus produced in the ZnO nanosheets provides charge injection on to the surface of ZnSnO3-PVDF membrane, improving the charge density, which in-turn significantly enhances the power density from 0.11 to ~ 1.8 W/m2. The TENG devices thus fabricated using a facile electrochemical deposition and phase inversion technique show enhanced output power without the need for high electric field poling or external charge injection process by relying on the coupling of triboelectric and piezoelectric effects.

Vertical contact-separation mode triboelectric generator (TEG) based on lead-free perovskite, zinc stannate (ZnSnO3)-polyvinylidene fluoride (PVDF) composite and polyamide-6 (PA6) membrane is demonstrated. For the 5 wt% PVDF-ZnSnO3 nanocomposites, the facile phase-inversion method provides a simple route to achieve high crystallinity and β-phase with a piezoelectric coefficient d33 of −65 pm V−1, as compared to −44 pm V−1 for pristine PVDF membranes. Consequently, at a cyclic excitation impact of 490 N/3 Hz, the PVDF-ZnSnO3/PA6 based TEGs provide a significantly higher voltage of 520 V and a current density of 2.7 mA m−2 (corresponding charge density of 62.0 µC m−2), as compared to the pristine PVDF-PA6 TEG which provides up to 300 V with a current density of 0.91 mA m−2 (corresponding to a charge density of 55.0 µC m−2). This increase in the electrical output can be attributed to not only the enhanced polarisation of PVDF by ZnSnO3 leading to an increase in the β-phase content, but also to the surface charge density increase by stress induced polarisation of ZnSnO3, leading to the generation of stronger piezoelectric potential. The work thus introduces a novel method of enhancing the surface charge density via the addition of suitable high polarisation piezoelectric materials thus eliminating the need for prior charge injection for fluoropolymer membranes.

The Artificial Immune Recognition System (AIRS), which has been proved to be a successful classification method in the field of Artificial Immune Systems, has been used in many classification problems and gained good classification effect. However, the network inhibition mechanisms used in these methods are based on the threshold inhibition and the cells with low affinity will be deleted directly from the network, which will misrepresent the key features of the data set for not considering the density information within the data. In this paper, we utilize the concept of data potential field and propose a new weight optimizing network inhibition algorithm called variable weight artificial immune recognizer (V-AIR) where we replace the network inhibiting mechanism based on affinity with the inhibiting mechanism based on weight optimizing. The concept of data potential field was also used to describe the data distribution around training samples and the pattern of a training data belongs to the class with the largest potential field. At last, we used this algorithm to rolling bearing analog fault diagnosis and reciprocating compressor valves fault diagnosis, which get a good classification effect.

In this paper we present a new variant of the online real time recurrent learning algorithm proposed by Williams and Zipser (1989). Whilst the original algorithm utilises gradient information to guide the search towards the minimum training error, it is very slow in most applications and often gets stuck in local minima of the search space. It is also sensitive to the choice of learning rate and requires careful tuning. The new variant adjusts weights by moving to the tangent planes to constraint surfaces. It is simple to implement and requires no parameters to be set manually. Experimental results show that this new algorithm gives significantly faster convergence whilst avoiding problems like local minima.

This paper focuses on the development of a magnetic moment method of calculating vector field quantities for a highly permeable ferrite cored eddy current probe. Basis functions are used in this method to replace the scattered field caused by the probe core in accordance with the surface equivalence theorem. These functions are further developed and tested for accuracy and convergence. An efficient material profile equation, independent of probe coil and basis function properties, is also designed and verified. Collocation point selection and optimisation is finally undertaken leading to the accurate determination of probe source coil impedance. The accuracy of calculation is verified using an industry standard finite element solver.

The Eddy current principle has been widely used for measuring coating thickness and the physical properties of materials. Most publications on the Eddy current method are directed towards air-cored coils operated at high frequency on non-ferrous metals. The benefit of ferrite-cored probes has seen little attention. Ferrite-cored probes provide the advantage of enhanced signal-to-noise ratio and increased resolution for electronic detection, which is of importance for measurements taken on unsaturated ferromagnetic substrates. This paper describes the design and development of a novel ferrite-cored probe, which includes the selection of ferrite material, the design of the probe structure and core. Probe core loss and sheared permeability have been investigated and overall probe uncertainties have also been discussed and used to develop a measurement methodology.

It is well known that there are many process parameters which influence the results of laser melting. Some parameters should be kept within certain tolerance limits to ensure the expected quality of the mark; hence, a closed-loop control system is required during the laser melting process for quality control. For this, accurate dynamic models are required. This paper describes two dynamic experimental models relating processing parameters and melt pool temperature during laser melting of clay tiles. The models were determined by process identification. The observable signal considered was melt pool temperature, measured on-line with an infrared pyrometer. The input quantities investigated were laser power and traverse speed. Good agreement between the data measured and the model outputs were achieved by an ARX (2,2,1) auto-regression model. The models were validated with experimental data and proved to be extremely accurate (errors less then 1%).