RSS 1.0Mechanical Engineering
The Department of Mechanical Engineering is located on Thornton Science Park, a modern expressly-designed site that profits from a recently-completed multi-million pound renovation that has created a state-of-the-art teaching and research facility. The site was home to Shell UK’s exploration and research centre since the 1940s, and its takeover by the University heralded the opportunity to apply its legacy to the continuation of world-class innovation and research in the North West.
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Dynamic modelling of interactions between building heating eventsWith high energy prices, more households in fuel poverty and space heating accounting for significant amounts of global CO2 emissions, every effort is required to improve the efficacy and efficiency of building heating systems. There is an opportunity to reduce global CO2 emissions and energy demand within domestic and commercial applications by better utilising heating events. During periods of inactivity, setpoints are often reduced to conserve energy. This decreases building fabric temperature, which must be restored during working hours. This paper quantifies how heating events interact, specifically considering their contribution to subsequent heating events to inform decisions on heating schedules. Using a validated dynamic room model representing a typical UK domestic property, the relationship between room temperature, room temperature history, building fabric and surrounding conditions on the coupling of adjacent heating events was explored. The amount of energy that is usefully retained for the subsequent heating event depends significantly on the duration of the previous heating and cooling periods. For example, a day-long heating event with four heating periods of 1.5 hours (duty cycle of 0.25), consumes 9.4% more energy than a single 6.0 hour heating period. A small energy pulse was used in the model to track the interactions between specific heating events. It showed that the useful contribution of a heating event to future heating events depended on the time temperature history of the room, due to the dynamic thermal behaviour of the building fabric.
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Importance of demand side unsteadiness on opportunity for space heating energy savingMuch effort is focused on improving space heating system efficiency through improving technologies such as boilers and heat pumps, improving building energy losses through, for example, improved insulation and reducing wasted heating through improved building controls. The importance of the hydronic circuit in affecting the amount of wasted energy is often overlooked, in part due to the conscious and unconscious application of quasi-steady assumptions to energy analyses of buildings. Occupant behaviour, equipment use and solar irradiance are three examples which cause the demand on the heating system to be significantly unsteady despite stable room temperature requirements and relatively high building fabric thermal masses. This paper presents results from a single room validated unsteady space heating energy model used to explore the effects of demand side unsteadiness on energy consumption for heating system with on-off and more complex proportional-integral type controls. Demand side unsteadiness is shown to have a significant influence on the heating energy consumed, typically increasing it compared to a steady equivalent. With on-off thermostat control, the behaviour is highly non-linear, depending significantly on the timing of demand perturbances relative to 'on' events. The heating energy used exceeded the minimum required to maintain 20°C in cold and mild heating conditions by 1-14% and 14-75% respectively. With more complex proportional-integral based controllers, the excessive energy used exceeded the minimum required by 4-12% and 9-44% in cold and mild conditions respectively. High frequency demand side perturbations are effectively filtered out by the space's thermal mass. Lower frequency perturbations such as those arising from solar cycles are filtered out by the heating system control response. However, there remains frequencies of perturbance which are similar to the hydronic system response timescales which are not well managed, leading to the excess energy provision.
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Computational and Experimental Study on the Resistance Welding Process of a Glass Fibre-Reinforced Epoxy-Based Composite with Thermoplastic Interlayer AdherentIn this work, resistance welding of a glass fibre-reinforced epoxy composite (GFRC) was studied with numerical optimisation and experimental validation. A steel mesh and polymethyl methacrylate (PMMA) films were used as the heating element and adherent interlayers, respectively. A transient heat transfer module was implemented to conduct the parametric optimisation study, with variables of electricity power, clamping distance and weld time. The optimal welding condition was then confirmed as 20 W, 0.4 mm and 30 s, with the melting degree of 95.2 %. A thermal meter and a thermal camera validated the simulated temperature results. Welding quality was experimentally characterized by single lap shear tests and scanning electron microscopy (SEM). The highest lap shear strength of 3.8 ± 0.3 MPa was captured on the specimen welded with the optimised condition. This was 76 % that of the benchmark made with adhesive bonding method but it was over 200 times faster.
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Student perceptions of remote learning transitions in engineering disciplines during the COVID-19 pandemic: a cross-national studyThis study captures student perceptions of the effectiveness of remote learning and assessment in two associated engineering disciplines, mechanical and industrial, during the COVID-19 pandemic in a cross-national study. A structured questionnaire with 24 items on a 5-point Likert scale was used. Parallel and exploratory factor analyses identified three primary subscales. The links between student perceptions and assessment outcomes were also studied. There was a clear preference for face-to-face teaching, with the highest for laboratories. Remote live lectures were preferred over recorded. Although students found the switch to remote learning helpful, group work and communication were highlighted as concern areas. Mean scores on subscales indicate a low preference for remote learning (2.23), modest delivery effectiveness (3.05) and effective digital delivery tools (3.61). Gender effects were found significant on all subscales, along with significant interactions with university and year-group. Preference for remote delivery of design-based modules was significantly higher than others.
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Fabrication of superamphiphobic surface with re-entrant structures via self-assembly colloidal template-assisted electrochemical depositionSuperamphiphobic surfaces with re-entrant structures have attracted widespread attention due to their superior water and oil resistance. However, current methods for fabricating superamphiphobic surfaces mostly rely on expensive equipment and cumbersome processes. This paper represents a facile and controlled preparation method for superamphiphobic surfaces with zinc oxide (ZnO) re-entrant structures using self-assembled polystyrene (PS) monolayer colloidal crystals (MCCs) as templates to assist electrochemical deposition of ZnO film. The prepared surface shows contact angles (CAs) larger than 150° and sliding angles smaller than 10° for water, glycerol, ethylene glycol (EG), and olive oil. The morphology and size of the re-entrant structures were modulated by the deposition potential and time, and the mechanism of the influence of the structures on the wetting properties was investigated. This superamphiphobic surface with re-entrant structures can be used as a surface-enhanced Raman spectroscopy (SERS) substrate for molecular detection with a detection limit of 10−10 M for rhodamine (R6G), benefiting from the enrichment effect of the superamphiphobic surface and the Schottky barrier at the Ag/ZnO contact interface. We hope that this preparation method for superamphiphobic surface has broad application prospects in the fields of self-cleaning, anti-icing, anti-fog, corrosion resistance, microfluidics, photocatalysis and fluid drag reduction.
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Energy harvesting using a magnetostrictive transducer based on switching controlIn this works we propose a switching control energy harvesting method using magnetostrictive materials. By combining a magnetostrictive material, an electric circuit, and an electronic switch, large-scale kinetic to electrical energy conversion can be achieved. The magnetostrictive material, magnet bias, and coils constitute an energy transducer, called a magnetostrictive transducer. The electronic switch strategically controls the switching of the circuit state according to an input switching signal. Using numerical simulations, we optimised the parameters and validated the harvesting performance with experimental measurements using a 3.75 m vibrated cantilever truss structure. In 20.0 s, the proposed method achieved an electrical energy of approximately 45 μJ, which is seven times more than that of the conventional passive method.
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A Miniature and Intelligent Low-Power in situ Wireless Monitoring System for Automotive Wheel AlignmentAutomotive wheel misalignment is the most significant cause of excessive wear on tires, which will severely affect the stability and safety of vehicle handling, and cause serious consequences for human health and the environment. In this study, an energy-efficient onboard wheel alignment wireless monitoring system (WAWMS) is developed to detect wheel misalignment in real time. To minimise power consumption, a dual wake-up strategy is proposed to wake the microcontroller by a real-time clock (RTC) and an accelerometer. Furthermore, an online self-calibration method of inertial measurement unit (IMU) sampling frequency is investigated to improve measurement accuracy. Eventually, real-world wheel misalignment tests were performed with the WAWMS. The error-correcting output codes based support vector machines (ECOC-SVM) method successfully classifies different wheel alignment conditions with an average accuracy of 93.2% using nine principal components (PCs) of 3-axis acceleration spectrum matrixes. It validates the effectiveness of the designed WAWMS on automotive wheel alignment monitoring.
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Automated retrieval and comparison of sheet metal partsWith the number of 3D CAD models increasing rapidly, retrieving models of similar parts has become an important activity as existing designs may contain vital information regarding design and manufacturing. This paper is targeted at retrieving and comparing sheet metal parts. In the method proposed herein, the general shape of a sheet metal part is represented by a simplified hierarchical tree wherein the nodes represent the planar walls of the part and feature-related information is attached to these nodes as textual attributes. A shape index is derived from this simplified tree and subsequently used to retrieve similar parts from the database. The retrieved parts are assessed for their similarity with the enquiry part using five criteria: the general shape of the part, bends and their direction, feature types, feature location and feature size. In addition to determining the degree of similarity, the main advantage of the proposed method is that the assessment provides useful feedback to design and manufacturing engineers based on these five criteria. A prototype system developed in C++ has been tested on a database containing a few hundred parts and the effectiveness of the proposed method in retrieving and comparing the parts is discussed.
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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.
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Multifunctional cellular sandwich structures with optimised core topologies for improved mechanical properties and energy harvesting performanceThis paper developed a multifunctional composite sandwich structure with optimised design on topological cores. As the main concern, full composite sandwich structures were manufactured with carbon fibre reinforced polymer (CFRP) facesheets and designed cores. Three-point bending tests have been performed to assess the mechanical performance of designed cellular sandwich structures. To evaluate the energy harvesting performance, the piezoelectric transducer was integrated at the interface between the upper facesheet and core, with both sinusoidal base excitation input and acceleration measured from real cruising aircraft and vehicle. It has been found that the sandwich with conventional honeycomb core has demonstrated the best mechanical performance, assessed under the bending tests. In terms of energy harvesting performance, sandwich with re-entrant honeycomb manifested approximately 20% higher RMS voltage output than sandwiches with conventional honeycomb and chiral structure core, evaluated both numerically and experimentally. The resistance sweep tests further suggested that the power output from sandwich with re-entrant honeycomb core was twice as large as that from sandwiches with conventional honeycomb and chiral structure cores, under optimal external resistance and sinusoidal base excitation.
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Thermal Induced Interface Mechanical Response Analysis of SMT Lead-Free Solder Joint and Its Adaptive OptimizationSurface mount technology (SMT) plays an important role in integrated circuits, but due to thermal stress alternation caused by temperature cycling, it tends to have thermo-mechanical reliability problems. At the same time, considering the environmental and health problems of lead (Pb)-based solders, the electronics industry has turned to lead-free solders, such as ternary alloy Sn-3Ag-0.5Cu (SAC305). As lead-free solders exhibit visco-plastic mechanical properties significantly affected by temperature, their thermo-mechanical reliability has received considerable attention. In this study, the interface delamination of an SMT solder joint using a SAC305 alloy under temperature cycling has been analyzed by the nonlinear finite element method. The results indicate that the highest contact pressure at the four corners of the termination/solder horizontal interface means that delamination is most likely to occur, followed by the y-direction side region of the solder/land interface and the top arc region of the termination/solder vertical interface. It should be noted that in order to keep the shape of the solder joint in the finite element model consistent with the actual situation after the reflow process, a minimum energy-based morphology evolution method has been incorporated into the established finite element model. Eventually, an Improved Efficient Global Optimization (IEGO) method was used to optimize the geometry of the SMT solder joint in order to reduce the contact pressure at critical points and critical regions. The optimization result shows that the contact pressure at the critical points and at the critical regions decreases significantly, which also means that the probability of thermal-induced delamination decreases.
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Electromechanical characterization and kinetic energy harvesting of piezoelectric nanocomposites reinforced with glass fibersPiezoelectric composites are a significant research field because of their excellent mechanical flexibility and sufficient stress-induced voltage. Furthermore, due to the widespread use of the Internet of Things (IoT) in recent years, small-sized piezoelectric composites have attracted a lot of attention. Also, there is an urgent need to develop evaluation methods for these composites. This paper evaluates the piezoelectric and mechanical properties of potassium sodium niobate (KNN)-epoxy and KNN-glass fiber-reinforced polymer (GFRP) composites using a modified small punch (MSP) and nanoindentation tests in addition to d33 measurements. An analytical solution for the piezoelectric composite thin plate under bending was obtained for the determination of the bending properties. Due to the glass fiber inclusion, the bending strength increased by about four times, and Young's modulus in the length direction increased by approximately two times (more than that of the KNN-epoxy); however, in the thickness direction, Young's modulus decreased by less than half. An impact energy harvesting test was then performed on the KNN-epoxy and KNN-GFRP composites. As a result, the output voltage of KNN-GFRP was larger than that of KNN-epoxy. Also, the output voltage was about 2.4 V with a compressive stress of 0.2 MPa, although the presence of the glass fibers decreased the piezoelectric constants. Finally, damped flexural vibration energy harvesting test was carried out on the KNN-epoxy and KNN-GFRP composites. The KNN-epoxy was broken during the test, however KNN-GFRP composite with a load resistance of 10 generated 35 nJ of energy. Overall, through this work, we succeeded in developing piezoelectric energy harvesting composite materials that can withstand impact and bending vibration using glass fibers and also established a method for evaluating the electromechanical properties with small test specimen.
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Numerical prediction of the chip formation and damage response in CFRP cutting with a novel strain rate based material modelCarbon fibre reinforced plastics (CFRPs) are susceptible to various cutting damages. An accurate model that could efficiently predict the material removal and chip formation mechanisms will thus help to reduce the damages during cutting and further improved machining quality can be pursued. In previous studies, macro numerical models have been proposed to predict the orthogonal cutting of the CFRP laminates with subsurface damages under quasi-static loading conditions. However, the strain rate effect on the material behaviours has rarely been considered in the material modelling process, which would lead to the inaccurate prediction of the cutting process and damage extent, especially at high cutting speed. To address this issue, a novel material failure model is developed in this work by incorporating the strain rate effect across the damage initiation (combined Hashin and Puck laws) and evolution criteria. The variation in material properties with the strain rate is considered for the characterization of the stress-strain relationships under different loading speeds. With this material model, a three-dimensional macro numerical model is established to simulate the orthogonal cutting of CFRPs under four typical fibre cutting angles. The machining process and cutting force simulated by the proposed model are well agreed with the results of the CFRP orthogonal cutting experiments, and the prediction accuracy has been improved compared with the model without considering the strain rate effect. In addition, the effects of processing conditions on the subsurface damage in machining CFRPs under 135° are assessed. The subsurface damage is found to decrease with the cutting speed increases to 100 mm/s, afterwards, it tends to be stable when the cutting speed is over 100 mm/s. The increased severity of the subsurface damage is predicted with the higher cutting depths.
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Multi-metric Evaluation of the Effectiveness of Remote Learning in Mechanical and Industrial Engineering During the COVID-19 Pandemic: Indicators and Guidance for Future Preparedness, 2021This data set is a follow on study from a study on remote learning conducted in 2020 during the first year of the COVID-19 pandemic. It contains data collected from 5 universities in 5 countries about the effectiveness of e-learning during the COVID-19 pandemic in 2021, specifically tailored to mechanical and industrial engineering students. A survey was administered in August 2021 at these universities simultaneously, using Google Forms. The survey had 41 questions, including 24 questions on a 5-point Likert scale. The survey questions gathered data on their program of study, year of study, university of enrolment and mode of accessing their online learning content. The Likert scale questions on the survey gathered data on the effectiveness of digital delivery tools, student preferences for remote learning and the success of the digital delivery tools during the pandemic. All students enrolled in modules taught by the authors of this study were encouraged to fill the survey up. Additionally, remaining students in the departments associated with the authors were also encouraged to fill up the form through emails sent on mailing lists. The survey was also advertised on external websites such as survey circle and facebook. Crucial insights have been obtained after analysing this data set that link the student demographic profile (gender, program of study, year of study, university) to their preferences for remote learning and effectiveness of digital delivery tools. This data set can be used for further comparative studies and was useful to get a snapshot of the evolution of the student preferences and e-learning effectiveness during the COVID-19 pandemic from 2020 to 2021 by comparing with the dataset from 2020.
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Multi-metric Evaluation of the Effectiveness of Remote Learning in Mechanical and Industrial Engineering During the COVID-19 Pandemic: Indicators and Guidance for Future Preparedness, 2020This data set contains data collected from 5 universities in 5 countries about the effectiveness of e-learning during the COVID-19 pandemic, specifically tailored to mechanical and industrial engineering students. A survey was administered in May, 2020 at these universities simultaneously, using Google Forms. The survey had 41 questions, including 24 questions on a 5-point Likert scale. The survey questions gathered data on their program of study, year of study, university of enrolment and mode of accessing their online learning content. The Likert scale questions on the survey gathered data on the effectiveness of digital delivery tools, student preferences for remote learning and the success of the digital delivery tools during the pandemic. All students enrolled in modules taught by the authors of this study were encouraged to fill the survey up. Additionally, remaining students in the departments associated with the authors were also encouraged to fill up the form through emails sent on mailing lists. The survey was also advertised on external websites such as survey circle and facebook. Crucial insights have been obtained after analysing this data set that link the student demographic profile (gender, program of study, year of study, university) to their preferences for remote learning and effectiveness of digital delivery tools. This data set can be used for further comparative studies and was useful to get a snapshot of student preferences and e-learning effectiveness during the COVID-19 pandemic, which required the use of e-learning tools on a wider scale than previously and using new modes such as video conferencing that were set up within a short timeframe of a few days or weeks.
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Non-Exhaust Vehicle Emissions of Particulate Matter and VOC from Road Traffic: A ReviewAs exhaust emissions of particles and volatile organic compounds (VOC) from road vehicles have progressively come under greater control, non-exhaust emissions have become an increasing proportion of the total emissions, and in many countries now exceed exhaust emissions. Non-exhaust particle emissions arise from abrasion of the brakes and tyres and wear of the road surface, as well as from resuspension of road dusts. The national emissions, particle size distributions and chemical composition of each of these sources is reviewed. Most estimates of airborne concentrations derive from the use of chemical tracers of specific emissions; the tracers and airborne concentrations estimated from their use are considered. Particle size distributions have been measured both in the laboratory and in field studies, and generally show particles to be in both the coarse (PM2.5-10) and fine (PM2.5) fractions, with a larger proportion in the former. The introduction of battery electric vehicles is concluded to have only a small effect on overall road traffic particle emissions. Approaches to numerical modelling of non-exhaust particles in the atmosphere are reviewed. Abatement measures include engineering controls, especially for brake wear, improved materials (e.g. for tyre wear) and road surface cleaning and dust suppressants for resuspension. Emissions from solvents in screen wash and de-icers now dominate VOC emissions from traffic in the UK, and exhibit a very different composition to exhaust VOC emissions. Likely future trends in non-exhaust particle emissions are described.
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The Potential of Incremental Forming Techniques for Aerospace ApplicationsIncremental sheet metal forming (ISF) processes are part of a set of non-classical techniques that allow producing low-batches, customized and/or specific geometries for advanced engineering applications, such as aerospace, automotive and biomedical parts. Combined or not with other joining processes and additive manufacturing techniques, ISF processes permit rapid prototyping frameworks, and can be included in the class of smart manufacturing processes. This chapter discusses the fundamentals of ISF technology, key attributes, future challenges and presents few examples related to the use of incremental forming for the development of complex parts as specifically found in aerospace applications such as aerofoils. The use of incremental forming to produce customized designs and to perform quick try-outs of ready-to-use parts contributes to decrease the time to market, decrease tooling cost and increase part design freedom.
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Design and finite element simulation of metal-core piezoelectric fiber/epoxy matrix composites for virus detectionUndoubtedly, the coronavirus disease 2019 (COVID-19) has received the greatest concern with a global impact, and this situation will continue for a long period of time. Looking back in history, airborne transimission diseases have caused huge casualties several times. COVID-19 as a typical airborne disease caught our attention and reminded us of the importance of preventing such diseases. Therefore, this study focuses on finding a new way to guard against the spread of these diseases such as COVID-19. This paper studies the dynamic electromechanical response of metal-core piezoelectric fiber/epoxy matrix composites, designed as mass load sensors for virus detection, by numerical modelling. The dynamic electromechanical response is simulated by applying an alternating current (AC) electric field to make the composite vibrate. Furthermore, both concentrated and distributed loads are considered to assess the sensitivity of the biosensor during modelling of the combination of both biomarker and viruses. The design parameters of this sensor, such as the resonant frequency, the position and size of the biomarker, will be studied and optimized as the key values to determine the sensitivity of detection. The novelty of this work is to propose functional composites that can detect the viruses from changes of the output voltage instead of the resonant frequency change using piezoelectric sensor and piezoelectric actuator. The contribution of this detection method will significantly shorten the detection time as it avoids fast Fourier transform (FFT) or discrete Fourier transform (DFT). The outcome of this research offers a reliable numerical model to optimize the design of the proposed biosensor for virus detection, which will contribute to the production of high-performance piezoelectric biosensors in the future.
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Panel adjustment and error analysis for a large active main reflector antenna by using the panel adjustment matrixActive panels are generally applied in large aperture and high frequency reflector antennas, and the precise calculation of the actuator adjustment value is of great importance. First, the approximation relationship between the adjustment value and panel elastic deformation is established. Subsequently, a panel adjustment matrix for the whole reflector is derived to calculate the reflector deformation caused by the actuator adjustment. Next, the root mean square (rms) error of the deformed reflector is expressed as a quadratic form in the matrix form, and the adjustment value can be derived easily and promptly from the corresponding extreme value. The solution is expected to be unique and optimal since the aforementioned quadratic form is a convex function. Finally, a 35 m reflector antenna is adopted to perform the panel adjustments, and the effect of the adjustment errors is discussed. The results show that compared to the traditional model, where the panel elastic deformation is not considered, the proposed method exhibits a higher accuracy and is more suitable for use in large reflectors with a high operation frequency. The adjustment errors in different rings exert different influences on the gain and sidelobe level, which can help determine the actuator distribution with different precisions.
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Computational simulation of the damage response for machining long fibre reinforced plastic (LFRP) composite parts: A reviewLong fibre reinforced plastics (LFRPs) possess excellent mechanical properties and are widely used in the aerospace, transportation and energy sectors. However, their anisotropic and inhomogeneous characteristics as well as their low thermal conductivity and specific heat capacity make them prone to subsurface damage, delamination and thermal damage during the machining process, which seriously reduces the bearing capacity and shortens the service life of the components. To improve the processing quality of composites, finite element (FE) models were developed to investigate the material removal mechanism and to analyse the influence of the processing parameters on the damage. A review of current studies on composite processing modelling could significantly help researchers to understand failure initiation and development during machining and thus inspire scholars to develop new models with high prediction accuracy and computational efficiency as well as a wide range of applications. To this aim, this review paper summarises the development of LFRP machining simulations reported in the literature and the factors that can be considered in model improvement. Specifically, the existing numerical models that simulate the mechanical and thermal behaviours of LFRPs and LFRP-metal stacks in orthogonal cutting, drilling and milling are analysed. The material models used to characterise the constituent phases of the LFRP parts are reviewed. The mechanism of material removal and the damage responses during the machining of LFRP laminates under different tool geometries and processing parameters are discussed. In addition, novel and objective evaluations that concern the current simulation studies are conducted to summarise their advantages. Aspects that could be improved are further detailed, to provide suggestions for future research relating to the simulation of LFRP machining.
