Recent Submissions

  • Adiabatic compressed air energy storage technology

    Barbour, Edward R.; Pottie, Daniel L.F.; Loughborough University (Cell Press, 2021-08-18)
    Adiabatic compressed air energy storage (ACAES) is frequently suggested as a promising alternative for bulk electricity storage, alongside more established technologies such as pumped hydroelectric storage and, more recently, high-capacity batteries, but as yet no viable ACAES plant exists. At first sight, this appears surprising, given that technical literature consistently refers to its potential as a promising energy storage solution and the fact that two diabatic compressed air energy storage (DCAES) plants exist at utility scale (Huntorf, Germany and Macintosh Alabama, USA), with over 80 years of combined operation. In this article, we discuss aspects of the main components that constitute a compressed air energy storage (CAES) system, the fundamental differences between how they operate in diabatic and adiabatic contexts, and the design challenges that need to be overcome for ACAES to become a viable energy storage option in the future. These challenges are grounded in thermodynamics and are consistent
  • Why is adiabatic compressed air energy storage yet to become a viable energy storage option?

    Barbour, Edward R.; Pottie, Daniel L.F.; Eames, Philip; Loughborough University (Cell Press, 2021-05-21)
    Recent theoretical studies have predicted that adiabatic compressed air energy storage (ACAES) can be an effective energy storage option in the future. However, major experimental projects and commercial ventures have so far failed to yield any viable prototypes. Here we explore the underlying reasons behind this failure. By developing an analytical idealized model of a typical ACAES design, we derive a design-dependent efficiency limit for a system with hypothetical, perfect components. This previously overlooked limit, equal to 93.6% under continuous cycling for a typical design, arises from irreversibility associated with the transient pressure in the system. Although the exact value is design dependent, the methodology we present for finding the limit is applicable for a wide range of designs. Turning to real systems, the limit alone does not fully explain the failure of practical ACAES research. However, reviewing the available evidence alongside our analytical model, we reason that underestimation of th
  • An alternative sequence of operation for Pumped-Hydro Compressed Air Energy Storage (PH-CAES) systems

    Pottie, Daniel L.F.; Ferreira, Rafael A.M.; Maia, Thales A.C.; Porto, Matheus P. (Elsevier, 2020-01-09)
    In a previous publication, entitled “Experimental study of a PH-CAES system: Proof of concept”, we presented results of an innovative solution for energy storage that uses only air and water as working fluids, named PH-CAES (Pumped-Hydro Compressed Air Energy Storage). Differently from a conventional CAES that operates with air turbines and air compressors, the PH-CAES uses a pump to compress water against air, and a hydraulic turbine to generate power. In the time of the aforementioned publication, it was possible to see that with a suitable thermodynamic cycle the PH-CAES could reach a high round-trip efficiency. Since then, we have worked on this cycle, and in this article we share the progress we have made. We redefined the sequence of charging and discharging aiming to provide constant power output. We present here simulations based on the balance of energy and entropy for transient regime, also used datasheets to simulate the pump characteristics. The maximum round-trip efficiencies were approximately 42%. We show that this is a relatively high round-trip efficiency, when compared to other CAES systems, which usually depend on multiple heat exchangers, burning fuel or an external heat source, validating thus, the technical relevance of the proposed solution.
  • On the use of micro-perforated panels for sound absorption

    Tayong-Boumda, Rostand; University of Bedfordshire (IntechOpen, 2025-01-28)
    This study deals with the sound absorption for Micro-Perforated Panels (MPP) as an effective solution for sound reduction. Single and multiple MPPs backed by an air cavity are presented, analysed, and both their behaviour and response are modelled and measured. The experimental setup relies on the use of an impedance tube. Three MPP samples were fabricated for this study: two MPP samples are made of Aluminium and one sample is polymer-made to analyse the contribution of the panel vibration to the overall sound absorption. To support the analysis, two models are presented: a model based on the acoustic propagation in short and narrow tubes and a model based on the equivalent fluid. Both models are compared to the experimental data and discussed. The theory considers no interactions between the holes. It is particularly showed that the sound absorption in the low-frequency ranges can be enhanced by using the combined effects of multiple MPPs and their vibrational effects. Relatively good agreement is also obser
  • Filtration characterisation of leather-fiber wastewater

    Tayong-Boumda, Rostand; Mortazavi, Mina (2024-11-07)
    The treatment of industrial sludge has been going on for a while now and there exists various treatment methods and techniques which differ in terms of financial (device, process, etc…) and practical (space and treatment volume) constraints. The discharge of industrial waste often results into harmful agents that negatively affect our environment and lifestyle. Leather treatment finds many applications to our daily life and its manufacturing process makes it one of the most important sources of pollution to the environment. The present work deals with the filtration characterisation and dewatering techniques applied to an industrial sludge made of leather-fibre particles. The raw sample was collected from leather factory and was tested. The study focuses on characterising particles’ physical and geometry properties obtained from the sedimentation rate, centrifuge machine, particle size and spectrophotometry measurements. Particle size analysis of the raw sample showed that it contained large size and nano-par
  • Introduction to thermal energy storage: solar, geothermal and hydrogen energy

    Verma, Vikas; Thangavel, Sivasakthivel; Dutt, Nitesh; Kumar, Ashwani; Weerasinghe, Rohitha (CRC Press, 2024-05-21)
    This chapter explores the critical role of thermal energy storage in the context of solar, geothermal, and hydrogen energy. It emphasizes the imperative of sustainable development and environmental preservation by harnessing renewable resources. Renewable energy sources, including solar, geothermal, and hydrogen energy, are investigated for their potential to reduce greenhouse gas emissions, bolster energy security, and stimulate economic growth. This chapter underscores the substantial growth observed in renewable energy utilization, particularly in 2020, signifying a global shift toward cleaner energy alternatives. Technological advancements in energy capture and storage, together with the increasing global adoption of Net Zero strategies, have significantly expanded renewable and green energy production. These advances span from small-scale solar panel installations to vast offshore wind farms, innovative geothermal applications, and electricity generation through hydrogen.
  • Highly efficient thermal renewable energy systems : design, optimization and applications

    Verma, Vikas; Thangavel, Sivasakthivel; Dutt, Nitesh; Kumar, Ashwani; Weerasinghe, Rohitha (CRC Press, 2024-05-21)
  • Ultrasonic metrics for large-area rapid wrinkle detection and classification in composites

    Smith, Robert A.; Tayong-Boumda, Rostand; Nelson, Luke J.; Mienczakowski, M.J.; Wilcox, Paul D. (Ultrasonics, 2024-01-29)
    Due to their high strength-to-weight ratio, composite materials are now in use in many high-stress applications, particularly where light weight is also a requirement. In these situations, the detrimental knock-down in mechanical strength due to an out-of-plane wrinkle defect can have serious consequences and is the reason for a requirement to rapidly detect any such wrinkles at manufacture. Unfortunately, current ultrasonic inspection techniques used for quality control at manufacture are not sensitive enough to detect these wrinkles above coherent structural noise variations. This paper exploits the ply resonance that is a characteristic of multi-layer structures to generate two new metrics for both detection and classification of out-of-plane wrinkles, due to their perturbations of the ply spacing. These can be measured at every location on a structure using the instantaneous frequency, which is the rate of change of phase in the pulse-echo ultrasonic response. The proposed two new metrics for detection an
  • Deformability, noise and vibrations of polymer gears

    Tayong-Boumda, Rostand; Keen, R. (Elsevier, 2024-11-01)
    Polymer Gears discusses polymer gear design and their efficient mechanical properties, light weight, and low noise during operation. As plastic gears are replacing metallic gears in traditional and new applications, there is still lack of material characterization and complex relations between different geometric and operating parameters. Thus, polymer gear design remains an open challenge. This book serves as a comprehensive and professional guide on the topic, providing readers with current developments carried out in the field of plastic gears production, characterization, and applications.
  • Centrifugal pump fault detection with convolutional neural network transfer learning

    Sunal, Cem Ekin; Velisavljevic, Vladan; Dyo, Vladimir; Newton, Barry; Newton, Jake; University of Bedfordshire; Royal Holloway, University of London; Uptime Systems Ltd. (MDPI, 2024-04-11)
    The centrifugal pump is the workhorse of many industrial and domestic applications, such as water supply, wastewater treatment and heating. While modern pumps are reliable, their unexpected failures may jeopardise safety or lead to significant financial losses. Consequently, there is a strong demand for early fault diagnosis, detection and predictive monitoring systems. Most prior work on machine learning-based centrifugal pump fault detection is based on either synthetic data, simulations or data from test rigs in controlled laboratory conditions. In this research, we attempted to detect centrifugal pump faults using data collected from real operational pumps deployed in various places in collaboration with a specialist pump engineering company. The detection was done by the binary classification of visual features of DQ/Concordia patterns with residual networks. Besides using a real dataset, this study employed transfer learning from the image detection domain to systematically solve a real-life problem in the engineering domain. By feeding DQ image data into a popular and high-performance residual network (e.g., ResNet-34), the proposed approach achieved up to 85.51% classification accuracy.
  • A privacy-preserving approach to effectively utilize distributed data for malaria image detection

    Kareem, Amer; Liu, Haiming; Velisavljevic, Vladan; University of Bedfordshire; University of Southampton (MDPI, 2024-03-18)
    Malaria is one of the life-threatening disease caused by the parasite knows as Plasmodium falciparum affecting the human red blood cells. Therefore, it is an important to have an effective computer aided system in place for early detection and treatment. As the visual heterogeneity of the malaria dataset is highly complex and dynamic, therefore higher number of images are needed to train the machine learning (ML) models effectively. However, hospitals as well as medical institutions do not share the medical image data for collaboration due to general data protection regulation (GDPR) and data protection act (DPA). To overcome this collaborative challenge, our research utilised real-time medical image data using framework of federated learning (FL) framework. We have used the state of the art ML models that include the Resnet50 and densenet in a federated learning framework. We have experimented both models in different settings on malaria dataset constituting 27,560 publicly available images and our preliminary results showed that the densenet model performed better in accuracy (75%) in contrast to resnet50 (72%) while considering 8 clients, while the trend is observed common in 4 clients with the similar accuracy of 94% and 6 client showed that the densenet model performed quite well with the accuracy of 92% while resnet50 achieving only 72%. The federated learning framework enhances the accuracy due to it’s decentralised nature, continuous learning, effective communication among clients as well as the efficient local adaptation. The use of federated learning architecture among the distinct clients for ensuring the data privacy and following the GDPR is the contribution of this research work.
  • From augmentation to inpainting: improving Visual SLAM with signal enhancement techniques and GAN-based image inpainting

    Theodorou, Charalambos; Velisavljevic, Vladan; Dyo, Vladimir; Nonyelu, Fredi; University of Bedfordshire; Briteyellow Ltd; Royal Holloway (IEEE, 2024-03-07)
    This paper undertakes a comprehensive investigation that surpasses the conventional examination of signal enhancement techniques and their effects on visual Simultaneous Localization and Mapping (vSLAM) performance across diverse scenarios. Going beyond the conventional scope, the study extends its focus towards the seamless integration of signal enhancement techniques, aiming to achieve a substantial enhancement in the overall vSLAM performance. The research not only delves into the assessment of existing methods but also actively contributes to the field by proposing innovative denoising techniques that can play a pivotal role in refining the accuracy and reliability of vSLAM systems. This multifaceted approach encompasses a thorough exploration of the intricate relationships between signal enhancement, denoising strategies, their cumulative impact on the performance of vSLAM in real-world applications and the innovative use of Generative Adversarial Networks (GANs) for image inpainting. The GANs effectively fill in missing spaces following object detection and removal, presenting a novel state-of-the-art approach that significantly enhances overall accuracy and execution speed of vSLAM. This paper aims to contribute to the advancement of vSLAM algorithms in real-world scenarios, demonstrating improved accuracy, robustness, and computational efficiency through the amalgamation of signal enhancement and advanced denoising techniques.
  • Fault detection and monitoring for electric pump motors

    Velisavljevic, Vladan; Dyo, Vladimir; Newton, J.; Newton, B.; Sunal, Cem Ekin (2024-02-29)
    Patent file GB2402869.8 Outcome of Innvoate KTP project.
  • 3D study of the vibrational behavior of lithic flint blades

    Tayong-Boumda, Rostand; Fushimi, Tatsuki; Grøn, Ole; Boldreel, Lars Ole; ; University of Bedfordshire; University of Bristol; University of Tsukuba; University of Copenhagen (Elsevier, 2023-11-09)
    Stone Age sites are well known to often contain many lithic flint blades and flakes, which may provide important information about early European Stone Age cultures and their environment. Understanding the mechanical behaviour of lithic flint blades represents an important problem for scientists in general and archaeologists in particular. In this study, the structural behaviour of lithic flint blades is studied. Ten specimens with different geometric shapes (tilted, curved, with bumping surfaces) were studied and tested. Their natural frequencies, damping ratios, and mode shapes (that is how the specimen deforms under any external excitation) are estimated using two models: an analytical model that accounts for the specimen's curvature and a 3D Finite Element (FE) method. Advanced experimental methods, including ultrasound techniques, were used to measure the mechanical properties of the specimens. The experimental set-up was built around a laser vibrometer that measured the specimen's displacement. The model predictions were compared with the experimental data to validate their effectiveness. A good agreement is observed between the models and the real data. It is particularly observed that despite their complicated geometries, the specimens still follow a structured pattern in their dynamic response. The presented study supports the use of acoustic methods as an effective tool to characterize and detect submerged prehistoric materials. This work contributes to the dynamic characterization of submerged Stone Age materials.
  • Ultrasonic metrics for large-area rapid wrinkle detection, classification and quantification in composites

    Smith, Robert A.; Tayong-Boumda, Rostand; Nelson, Luke J.; Wilcox, Paul D.; University of Bristol; University of Bedfordshire (2022-12-31)
    Due to their high strength-to-weight ratio, composite materials are now in use in many high-stress applications, particularly where light weight is also a requirement. In these situations, the detrimental knock-down in mechanical strength due to an out-of-plane wrinkle defect can have serious consequences and is the reason for a requirement to rapidly detect and quantify any such wrinkles at manufacture. Unfortunately, these wrinkles do not perturb the ultrasound currently used for quality control at manufacture in a way that can be readily detected above coherent structural noise variations. This paper exploits the ply resonance that is a characteristic of multi-layer structures to generate two new metrics for both detection and quantification of out-of-plane wrinkles, due to their effect on the ply spacing. These can be measured at every three-dimensional location in a structure using the instantaneous frequency, which is the rate of change of phase in the pulse-echo ultrasonic response. The proposed two new metrics for detection and quantification of wrinkles are: Mean Spacing and Spacing Difference. Use of an analytical model to predict the ultrasonic response of the structure has allowed an understanding of how these metrics will be affected by various wrinkle types and how they can not only detect but also classify and quantify the wrinkle extent and severity. Three main types of wrinkles are considered: classic wrinkles near the mid-plane of a structure, back-surface wrinkles forming from a resin bulge near the back of a structure, and folded wrinkles where several plies can be folded over completely in the bulk of the structure. Both simulations and experimental results demonstrate the effectiveness of these metrics on various types of structure including carbon-fibre and glass-fibre composites with a range of ply thicknesses and wrinkle types.
  • On the design and structural study of a rear swing arm for an electric bike

    Tayong-Boumda, Rostand; Henderson, Dave; Murray, Alex; University of Bedfordshire; Flit Bike Ltd (Elsevier, 2023-10-18)
    As electric bikes continue to grow in popularity, it is important to ensure that they are equipped with well-designed components. One such component is the rear swing arm (RSA). This study deals with the design and structural analysis of an RSA used for electric bikes. This RSA is composed of two swing arms (one on each side of the bikes), a yoke, a suspension block, and bolts or screws. First, an analytical approach was developed to calculate the initial values for the width and shape of the swing arm. Next, experimental data were used to analyze the response of the RSA and determine the final profile for the swing arms and yoke structure. Finally, the finite element approach was implemented to assess the stress, displacement, and fatigue responses of the RSA when subjected to realistic excitations and conditions. The initial results depicted the following characteristics for the RSA: C-channel profile, 43 mm height, and 2 mm wall thickness. These results implied that the maximum shear force would occur in a region representing approximately 15.5% of the total length of the RSA. Further analysis and calculations showed that this region would decrease to approximately 2.85% of the total length of the RSA. For the final design, the mechanical performance of the RSA was observed to remain acceptable despite the relatively high Von Mises stress values around these singularities. This study assumed the use of 7075 T651 aluminum alloy as the primary material for the RSA.
  • Aquaculture 4.0: hybrid neural network multivariate water quality parameters forecasting model

    Eze, Elias Chinedum; Kirby, Sam; Attridge, John; Ajmal, Tahmina; University of East London; University of Bedfordshire; Chelsea Technologies Ltd (Springer Nature, 2023-09-26)
    This study examined the efficiency of hybrid deep neural network and multivariate water quality forecasting model in aquaculture ecosystem. Accurate forecasting of critical water quality parameters can allow for timely identification of possible problem areas and enable decision-makers to take pre-emptive remedial actions that can significantly improve water quality management in aquaculture industry. A novel hybrid deep learning neural network multivariate water quality parameters forecasting model is developed with the aid of ensemble empirical mode decomposition (EEMD) method, deep learning long-short term memory (LSTM) neural network (NN), and multivariate linear regression (MLR) method. The presented water quality forecasting model (shortened as EEMD-MLR-LSTM NN model) is developed using multivariate time-series water quality sensor data collected from Loch Duart company, a Salmon offshore aquaculture farm based around Scourie, northwest Scotland. The performance of the novel hybrid water quality forecasting model is validated by comparing the forecast result with measured water quality parameters data and the real Phytoplankton data count from the aquaculture farm. The forecast accuracy of the results suggests that the novel hybrid water quality forecasting model can be used as a valuable support tool for water quality management in aquaculture industries.
  • Insights into the spray impingement process from a gasoline direct injection fuel system fuelled with gasoline and ethanol

    Li, Xiang; Zhang, Xuewen; Ni, Peiyong; Weerasinghe, Rohitha; Pei, Yiqiang; Peng, Zhijun; Nantong University; Tianjin University; University of Bedfordshire; University of Lincoln (Elsevier, 2023-06-27)
    Particulate Matter (PM) emissions have a negative impact on both climate change and human health. To control PM emissions emitted by vehicles with the Gasoline Direct Injection (GDI) fuel system, increasing fuel injection pressure is being developed as a practical approach. In this paper, an experimental and numerical study was presented to thoroughly explore the entire development process of gasoline and ethanol impingement spray from a GDI injector under injection pressure of 10 MPa and 50 MPa. The results demonstrate that more droplets are predicted to distribute in the splash region with the increase of injection pressure (𝑃𝐼 ) from 10 MPa to 50 MPa, which helps improve air-fuel mixing quality and reduce PM emissions. The splash probability of gasoline droplets is about two percent higher than ethanol. By increasing 𝑃𝐼 from 10 MPa to 50 MPa, droplets with higher absolute normal velocity would promote the growth of impingement spray. The probability curves of droplet diameter are more concentrated in the smaller size range. Besides, the probability of relatively large droplets of gasoline is slightly lower than that of ethanol. Regarding the fuel film distribution, more folds and bulges can be seen at the boundary of fuel film with the 𝑃𝐼 increase to 50 MPa. Meantime, the film distribution becomes more scattered, which would benefit the homogeneity of air-fuel mixture. The film distribution area and boundary irregularity of gasoline are greater than those of ethanol, further promoting a homogeneous air-fuel mixture.
  • Quantitative analysis of water injection mass and timing effects on oxy-fuel combustion characteristics in a GDI engine fuelled with E10

    Chen H, Hao; Wang, Chenxi; Li, Xiang; Li, Yongzhi; Zhang, Miao; Peng, Zhijun; Pei, Yiqiang; Ma, Zhihao; Zhang, Xuewen; Ni, Peiyong; et al. (MDPI, 2023-06-29)
    The climate change issue has become a growing concern due to the increasing greenhouse gas emissions. To achieve carbon neutrality for mitigating the climate problem, the oxy-fuel combustion (OFC) technique on internal combustion engines (ICEs) has attracted much attention. Furthermore, the water injection (WI) strategy was proven effective in improving the combustion process and thermal efficiency in engines under OFC mode. However, WI strategy effects on gasoline direct injection (GDI) engines fuelled with gasoline–alcohol blends have not been reported. This study quantitatively analysed WI mass and timing effects on oxy-fuel combustion performance from a GDI engine fuelled with E10 (10% ethanol and 90% gasoline in mass) by simulation. The results show that equivalent brake-specific fuel consumption (BSFCE) shows a monotonically decreasing trend with the increase in the water–fuel mass ratio (Rwf ) from 0 to 0.2. However, further increasing Rwf would cause a deterioration in BSFCE due to the enhanced cooling effects of water vaporisation. Moreover, an appropriate water injection timing (tWI ) could be explored for improving OFC performance, especially for large Rwf conditions. The difference in BSFCE between tWI = 􀀀100CA and tWI = 􀀀60CA can be up to around 6.3 g/kWh by increasing Rwf to 0.6.
  • 3D numerical analysis of the structural behaviour of a carbon fibre reinforced polymer drive shaft

    Samuel, Mosopefoluwa; Tayong-Boumda, Rostand; University of Bedfordshire (Elsevier, 2023-04-28)
    Due to their high strength and favourable mechanical behaviour, metals are used in a variety of applications within the automotive industry, including drive shafts. However, the use of metallic drive shafts in the automotive sector presents some disadvantages such as high inertial masses. This work investigates the mechanical benefits of using Carbon Fibre Reinforced Polymers (CFRP) for manufacturing drive shafts. A Formula Student car was used as a model for the present work design for the drive shaft. Drive shafts made of Steel AISI 4340, Aluminium, and CFRP are investigated when subjected to mechanical excitations. Simulation includes the use of Comsol Multiphysics software. The CFRP drive shaft was modelled using the layered material feature. Various stacking sequences are tested. Results show that [90°/0°/-45°/+45°] sequence presents the best mechanical behaviour. Analytical and numerical calculations for the natural frequencies are performed and compared. CFRP drive shaft is observed to give the highest fundamental natural frequency when compared to the metallic counterparts. Fatigue analysis are also studied and revealed that the drive shafts can sustain the applied load for its expected fatigue life, with the CFRP drive shaft having the highest fatigue usage factor. Critical buckling analysis showed that the drive shaft made of steel has the highest critical buckling torque. However, drive shafts made of carbon fibre reinforced polymer was found to be 40.7% lighter than the aluminium tube and 79.6% lighter than the steel tube.

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