30793 research outputs found
Sort by
Optimizing the Number of Electric Vehicle Charging Stations at Forecourts to Meet Demand
Get PDFDue to the rapid increase in electric vehicle (EV) adoption, there is a pressing need for expanded charging infrastructure to accommodate this growth. The core challenge lies in balancing the number of EVs with the availability of charging stations to minimize wait times and enhance user satisfaction. This study employs a data-driven approach, utilizing hypothetical surveys of 100 EV users to gather insights into their experiences and expectations. Due to constraints on survey approval, assumptions were made regarding user responses. MATLAB-based artificial neural network (ANN) simulations were conducted to optimize the allocation of charging stations against the number of EV users. This method helps in predicting the required number of charging stations to effectively reduce charging wait times and improve overall user experience
Multifactorial impacts on early breast carcinogenesis-assessing the combined effects of mixtures of endocrine disrupting chemicals and fatty acids
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe percentage of breast cancer attributed to genetic factors is estimated to be between 5-10%, suggesting that a large proportion of breast cancer cases can be attributed to external factors. There has been extensive research on external factors such as obesity, alcohol, smoking, physical activity, diet and environmental chemicals and their role in breast cancer development. However, the evidence of environmental chemicals such as Endocrine Disrupting Chemicals (EDCS) on breast cancer initiation has been inconclusive because they have been studied as single compounds at concentrations not reflective of tissue concentrations. This phenomenon is also applicable to other risk factors, such as diet, suggesting that several multiple risk factors interact to initiate breast carcinogenesis. Using a non-tumorigenic cell line, MCF-12A, in// a 3D model that recapitulates human mammary structure, mixtures of thirteen EDCs and four fatty acids were tested at tissue concentrations for their effect on breast carcinogenesis. The results showed that the mixtures disrupted acini formation and affected genes and pathways involved in carcinogenesis, such as cell proliferation, migration and apoptosis. There were increases in the sizes of acini and decreases in circularity, which are markers of neoplastic transformation. Changes to gene expression and pathways involved in breast cancer were also found when BRCA1-silenced MCF-12A cells were exposed to mixtures of EDCs and fatty acids, suggesting a possible increase in absolute risk for people with a familial mutation in the BRCA1 gene. The ability of 3D models to appropriately model processes involved in normal cellular functions such as proliferation and glycolysis was also demonstrated through a meta-analysis of published data. Overall, we show that exposure to mixtures of EDC and fatty acids can increase induce genes and pathways that can lead to breast carcinogenesis. We also demonstrated the ability of EDCs to induce the expression of carcinogenic genes in BRCA1 silenced cells, suggesting a possible increase in breast cancer risk.Breast Cancer U
3D Concrete Printing in Kuwait: Stakeholder Insights for Sustainable Waste Management Solutions
Get PDFData Availability Statement:
Data are contained within the article.Robotic construction using three-dimensional (3D) concrete printing (3DCP) offers significant potential to transform Kuwait’s construction industry, particularly in reducing waste. This study explores the feasibility of integrating 3DCP into Kuwait’s construction waste management practices by examining the perspectives of key stakeholders. Through a mixed method approach of a comprehensive literature review, a survey of 87 industry professionals, and 33 in-depth interviews with representatives from the Public Authority for Housing Welfare (PAHW), Municipality, private sector, and the general public, the study identifies both the benefits and challenges of 3DCP adoption. The findings highlight key advantages of 3DCP, including increased construction efficiency, cost savings, enhanced design flexibility, and reduced material waste. However, several barriers, such as regulatory limitations, technical challenges in adapting 3DCP to local project scales, and cultural resistance, must be addressed. Results also indicate varying levels of stakeholder familiarity with 3DCP and existing waste management practices, underscoring the need for awareness and educational initiatives. This study makes two significant contributions: first, by providing a detailed analysis of the technical and regulatory challenges specific to Kuwait’s construction sector, and second, by offering a strategic roadmap for 3DCP integration, including regulatory reform, research into sustainable materials, and cross-sector collaboration. These recommendations aim to enhance waste management practices by promoting more sustainable and efficient construction methods by achieving SDGs 9, 11, 12, and 13. The study concludes that government support and policy development will be essential in driving the adoption of 3DCP and achieving long-term environmental benefits in Kuwait’s construction industry.This research received no external funding
Personalized Path-Tracking Approach Based on Reference Vector Field for Four-Wheel Driving and Steering Wire-Controlled Chassis
Get PDFData Availability Statement:
The data presented in this study are available on request from the corresponding author due to privacy.It is essential and forward-thinking to investigate the personalized use of four-wheel driving and steering wire-controlled unmanned chassis. This paper introduces a personalized path-tracking approach designed to adapt the vehicle’s control system to human-like characteristics, enhancing the fit and maximizing the potential of the chassis’ multi-directional driving and steering capabilities. By modifying the classic vehicle motion controller design, this approach aligns with individual driving habits, significantly improving upon traditional path-tracking control methods that rely solely on reference vector fields. First, the classic reference vector field’s logic was expanded upon, and it is shown that a personalized upgrade is feasible. Then, driving behavior data from multiple drivers were collected using a driving simulator. The fuzzy c-means clustering method was used to categorize drivers based on typical states that match vehicle path-tracking performance. Additionally, the random forest algorithm was used as the method for recognizing driving style. Subsequently, a personalized path-tracking control strategy based on the reference vector field was developed and a distributed execution architecture for four-wheel driving and steering wire-controlled unmanned chassis was established. Finally, the proposed personalized path-tracking approach was validated using a driving simulator. The results of the experimental tests demonstrated that the personalized path-tracking control approach not only fits well with various driving styles but also delivers high accuracy in driving style identification, making it highly suitable for application in four-wheel driving and steering wire-controlled chassis.This research was funded by Open Foundation of State Key Laboratory of Automotive Simulation and Control (Grant Number: 20201111); Major Scientific and Technological Innovation Project of Xianyang (Grant Number: L2023-ZDKJ-JSGG-GY-018)
Support structures optimisation for selective laser melting
No full textThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonAdditive Manufacturing (AM), particularly Powder Bed Fusion-Laser Beam for Metals (PBF-LB/M) or Selective Laser Melting (SLM), has revolutionised various industries, including aerospace, automotive, and medical, by enabling the production of complex, thin, lightweight, and customized metal parts. Despite its advantages, key challenges remain in optimizing and designing support structures, which are critical for ensuring part quality, reducing defects caused by thermal stresses, and minimizing post-processing efforts and overall costs. This thesis systematically investigates block-type support structures, evaluating their performance through a Multi-Response Optimization (MRO) approach, experimental studies, and numerical simulations, while comparing them with alternative support geometries, including line, contour, and cone-type supports. It aims to address key challenges in SLM, such as support generation, support removal effort, material consumption, and relevant defects. The research is organized around three key objectives. First, it introduces a framework using multi-response optimization approach to evaluate block-type support structures, aiming to propose optimized geometries that minimize support volume, prevent warping deformation, and enhance support removal efficiency. For layers aligned parallel to the build plate (e.g., 0° overhangs), the findings revealed that block-type supports with a tooth height of 2.7 mm, a tooth top length of 0.2 mm, and a hatch distance of 0.7 mm provide an optimal balance between mechanical stability, minimal warping deformation, material consumption, and ease of removal. Conversely, for layers inclined relative to the build plate (e.g., 25°- 45° overhangs), the optimal balance was observed with a tooth height of 4 mm, a tooth top length of 0.05 mm, and a hatch distance of 2.5 mm. Second, thermo-mechanical simulations examine the thermal behaviour of alternative support geometries, including block, line, contour, and cone-type supports, with the goal of mitigating defects caused by thermal stresses and identifying configurations that offer optimal thermal performance. The outcome, consisting of plots and tables, provide valuable guidelines for achieving effective printing and ensuring the production of defect-free parts. Additionally, the numerically optimized results of this study were validated through experimental testing. It was found that block-type support structures, despite their larger volume and the challenges associated with their removal, demonstrate slightly improved thermal behaviour compared to the other support types analysed. Finally, the study presents an innovative design framework for optimising the SLM workflow, introducing a web-based platform for automated support generation, optimization, and thermal performance assessment. This platform serves as a valuable research tool for managing and visualizing experimental data, allowing researchers and professionals to improve AM production and produce defect-free, high-quality prints while reducing printing time and costs. By integrating and visualizing experimental data and simulation results, the platform allows users to import 3D models, adjust orientation, generate and visualize optimized support structures, and export ready-to-print designs. Moreover, this tool is designed to be accessible to non-expert users, simplifying complex support design decisions while effectively reducing trial-and-error approaches and streamlining the SLM process. Validation on a small L-shaped mounting bracket demonstrates that the platform effectively generates and visualises block-type support structures for imported parts while facilitating successful SLM printing. The printed outcome exhibited excellent dimensional accuracy, minimal warping deformation, and easy support removal (achieved within 2-4 minutes of manual effort) along with satisfactory surface roughness. By leveraging experimental, optimization, and computational tools, such as SLM 3D printing machines, Design-Expert, and COMSOL Multiphysics, this thesis presents a structured methodology for optimizing metal support structures, reducing defects, and enhancing the efficiency of the SLM process. These contributions not only address current challenges but also create opportunities for future advancements in the field, such as improved quality control during pre-printing preparations, ultimately establishing SLM as a viable production method.Lloyd's register foundatio
Unsteady Surface Pressure Characterization of the Base Pressure Region of a Heavy Goods Vehicle
Get PDFThis paper presents an experimental investigation into the time-dependent aerodynamics within the base region of a representative heavy goods vehicle. The work conduced is surface-based, and involved using multiple, customized dynamic pressure sensors for both aligned and mis-aligned flow configurations. Uniquely, the methodology adopted allowed high resolution, detailed interrogation of this region and the presentation of several new insights. Among the most significant are the detailed characterization and quantification of the degree of flow-misalignment necessary to prompt development of a complex vortex/wake structure reported previously. Once developed, this structure dominated the upper-windward quadrant of the base region with measured unsteady surface loads up to 2-3 times greater than that observed under nominal flow conditions. Presented spectral information also showed evidence of both Strouhal-based vortex shedding within the wider base-pressure region as well as more localized regions containing higher spectral contributions centered broadly at several multiples of the primary shedding frequency.The author acknowledges the invaluable assistance and support provided academic and technical staff of Cambridge University
Investor Sentiment, Anchoring, and Momentum Returns.
Get PDFJEL classification: G11, G12, G30, G40, G41, O16.This is a working paper. It is not certified by peer review.We hypothesize that anchoring enhances the disposition effect, while investor sentiment likely strengthens (or weakens) this effect when news contradict (or align with) the prevailing investor sentiment. This study examines the profitability of momentum strategies based on past return performance and/or proximity to the 52-week high across different sentiment states. We find that momentum returns are consistently higher following periods of optimism compared to pessimism, and are greater for stocks sorted by closeness to the 52-week high rather than by past performance. The double-sort strategy shows that a near minus far strategy within past winners or losers generates positive and significant returns following an optimistic sentiment period. Nearness to (farness from) the 52-week high enhances the disposition effect of past winners (losers), while the positive market sentiment attenuates (strengthens) it, giving rise to strong return continuations. Following an optimistic (pessimistic) market sentiment, a momentum strategy produces positive and significant returns for the far (near) portfolio due to strong return continuations of loser (winner) stocks. Past performance strengthens the cognitive dissonance effect of stocks trading near (or far from) the 52-week high during pessimistic (or optimistic) periods
Nonfragile Impulsive State Estimation for Complex Networks With Markovian Switching Topologies Subject to Limited Bit Rate Constraints
Get PDFIn this article, we consider the impulsive estimation problem for a specific category of discrete-time complex networks (CNs) characterized by Markovian switching topologies. The measurement outputs of the underlying CNs, transmitted to the observer over wireless networks, are subject to bit rate constraints. To effectively reduce the estimation error and enhance estimation performance, a mode-dependent impulsive observer is proposed that employs the impulse mechanism. The application of stochastic analysis techniques leads to the derivation of a sufficient condition for ensuring the mean-square boundedness of the estimation error dynamics. The upper bound of the error is then analyzed by iteratively exploring the Lyapunov relation at both impulsive and non-impulsive instants. Moreover, an optimization algorithm is presented for handling the bit rate allocation, which is coupled with the design of desired observer gains using the linear matrix inequality (LMI) approach. Within this theoretical framework, the relationship between the mean-square estimation performance and the bit rate allocation protocol is further elucidated. Finally, a simulation example is provided to demonstrate the validity and effectiveness of the proposed impulsive estimation approach.Natural Science Foundation of Guangdong Province of China (Grant Number: 2021B0101410005, 2021A1515011634 and 2021B1515420008);
10.13039/501100001809-National Natural Science Foundation of China (Grant Number: U22A2044 and 62206063);
Key Area Research and Development Program of Guangdong Province of China (Grant Number: 2021B0101410005);
Local Innovative and Research Teams Project of Guangdong Special Support Program of China (Grant Number: 2019BT02X353);
10.13039/501100004543-China Scholarship Council (Grant Number: 202208440312)
A Computer Vision Model to Support Individuals with Disabilities Within University Campuses
Get PDFThis study introduces MCOF, a multi-camera, computer vision-based system designed to assist visually impaired individuals with mobility on university campuses. The system operates locally and achieves the following performance metrics: (i) detecting body points within 1.2. 10–2seconds, (ii) identifying people, objects, and animals in 2.4. 10–2seconds, and (iii) detecting movements in 5.1. 10−2 seconds. These results were obtained using a GTX 1,660 GPU with up to 6 cameras (or a 6,112MB stream) running concurrently. According to the MCOF architecture, events trigger tickets that are sent to an external information system, which can then implement its own safety and personnel protocols. Additionally, MCOF includes modules to handle electrical and network failures and features an obstruction detection routine for the cameras.10.13039/501100002322-Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance
Multistatic 3-D microwave imaging with dynamic metasurface antennas: a Fourier-based approach
Get PDFArticle and poster presented at SPIE Sensors + Imaging 2024 Conference, Edinburgh, UK, 16-20 September 2024.This paper proposes a novel approach to 3-D microwave imaging using dynamic metasurface antennas in a multistatic configuration. By introducing a panel-to-panel model and a preprocessing technique, raw measurements are converted into the space-frequency domain for efficient data acquisition and reconstruction. Adapting the range migration algorithm in this work enables fast Fourier-based image reconstruction. Simulation results showcase the effectiveness of the proposed method, highlighting its potential for real-world applications.This work was funded by the Leverhulme Trust under the Research Leadership Award RL-2019-019
Data sources:
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇