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Combined intensity and coherent change detection with four classes for laboratory multistatic polarimetric synthetic aperture radar
Get PDFSatellites and drone swarms can be used to collect multistatic Synthetic Aperture Radar (SAR) images. Synthetic Aperture Radar images can be used for Intelligence Surveillance and Reconnaissance. One method is to use Coherent Change Detection (CCD) to identify changes such as objects or tracks in the scene. This paper investigates a two-stage change detector, formed using intensity change and CCD images, extended to laboratory measured multistatic SAR data. A variety of performance metrics are used to quantitatively assess the results. Bistatic results are compared to a variety of multistatic and fully polarimetric results. The improvement in performance of multistatic and fully polarimetric images over bistatic images is shown. Additionally challenges and limitations of using multistatic datasets are highlighted.This research was produced as a part of a PhD funded by Defence Science and Technology Laboratory.IET Radar, Sonar & Navigatio
Enhancing situational awareness of helicopter pilots in unmanned aerial vehicle-congested environments using an airborne visual artificial intelligence approach
Get PDFThe use of drones or Unmanned Aerial Vehicles (UAVs) and other flying vehicles has increased exponentially in the last decade. These devices pose a serious threat to helicopter pilots who constantly seek to maintain situational awareness while flying to avoid objects that might lead to a collision. In this paper, an Airborne Visual Artificial Intelligence System is proposed that seeks to improve helicopter pilots’ situational awareness (SA) under UAV-congested environments. Specifically, the system is capable of detecting UAVs, estimating their distance, predicting the probability of collision, and sending an alert to the pilot accordingly. To this end, we aim to combine the strengths of both spatial and temporal deep learning models and classic computer stereo vision to (1) estimate the depth of UAVs, (2) predict potential collisions with other UAVs in the sky, and (3) provide alerts for the pilot with regards to the drone that is likely to collide. The feasibility of integrating artificial intelligence into a comprehensive SA system is herein illustrated and can potentially contribute to the future of autonomous aircraft applications.Sensor
Towards 6G UAV networks: experimental performance analysis
Get PDFUnmanned Aerial Vehicles (UAVs) are becoming increasingly prevalent across industries, from surveillance to delivery services, necessitating seamless handover between base stations for continuous operation and safety. Challenges arise due to the need to maintain connectivity and control as the UAV transitions between different access technologies, for Fifth Generation (5G) and beyond such as Sixth Generation (6G). Factors like altitude, mobility, and dynamic operation patterns pose hurdles to achieving smooth handovers critical for mission success. Traditional strategies often lack adaptability and efficiency, prompting the exploration of innovative approaches. To address these challenges, an experimental flight trial evaluates UAV handover performance in a heterogeneous network environment compared to simulation-level analysis. The trial involves UAV flight in an urban area with non-standalone (NSA) 6G connectivity, monitoring key performance indicators (KPIs) such as reference signal received power (RSRP), signal-to-noise interference ratio (SINR), throughput, and number of handovers. The system architecture encompasses an airborne measurement platform (DJI F450 UAV with XCAL mobile measurement tool and Pixhawk 4 Autopilot) and a ground-based counterpart interfacing through the core network. The analysis focuses on three key metrics: RSRP, RSRQ, and SINR, revealing temporary interruptions attributed to the UAV's exclusive connection to the wireless network. Insights from experimental trials highlight complexities and challenges associated with UAV handover performance, informing the design of improved protocols and communication systems. By addressing these challenges, the aim is to enhance operational reliability and mission success, unlocking the full potential of UAV technology across applications like surveillance, reconnaissance, delivery services, and more.Engineering and Physical Sciences Research CouncilThis work is funded by the UKRI- EPSRC CHEDDAR Project - Communications Hub for Empowering Distributed Cloud Computing Applications and Research) under grant numbers EP/X040518/1 and EP/Y037421/1.2024 AIAA DATC/IEEE 43rd Digital Avionics Systems Conference (DASC
Assessing diurnal land surface temperature variations across landcover and local climate zones: implications for urban planning and mitigation strategies on socio-economic factors
Get PDFRising temperatures and rapid urbanization globally reinforce the need to understand urban climates. We investigated the influence of land cover and local climate zones (LCZs) on diurnal land surface temperature (LST) in various seasons in greater Delhi region, India, and their implications on socio-economic factors. Day LST was the highest in the summer and night LST in the monsoon, which also had the lowest diurnal differences in LST. Higher height and density of built-up features contributed to greater heat at night. During the day, open built-up and vegetated areas experienced relatively less heat than their compact equivalents. The lowest diurnal difference was in medium height compact urban zones and tall vegetation. Social inequity in access to urban cooling was indicated by large low-income and heat-vulnerable populations inhabiting the hottest LCZs. This research highlighted that even in semi-arid and subtropical climates, spatial planning policy should consider both the seasonality and diurnal differences in temperature as much as appropriate morphologies for design of thermally comfortable and climate resilient urban spaces. These policies should address the evidenced social inequities in heat exposure to reduce the adverse health impacts on vulnerable groups and therefore contribute to wider societal and economic benefits of healthier populations.Commonwealth Scholarship CommissionSustainable Cities and Societ
Air rage from the sharp end: cabin crew perspectives on disruptive passenger behaviour in Europe and its impact on occupational safety and well-being
Get PDFDisruptive passenger behaviour (DPB) incidents spiked during the COVID-19 pandemic period, compromising the safety of commercial flights on a daily basis. This qualitative semi-structured interview study examined the perceived triggering factors and motivations for DPB and the subsequent impact of DPB upon cabin crew well-being and safety. Twenty-four European cabin crew disclosed experiences, subjective observations of perpetrator traits, assessment of DPB development and information regarding their well-being and perceived safety. Thematic analysis revealed that the perceived frequency of DPB had increased, driven by an accumulation of pandemic-related factors–such as enforcing mask wearing amongst intoxicated passengers. DPB was found to decrease resilience and spur maladaptive coping strategies in crew. Suggested enhancements to current DPB mitigation consisted of stricter punishment for DPB as a deterrent, alcohol bans and higher quality training. These findings can inform decision-makers’ efforts to support cabin crew well-being and create safer cabin workplaces in the future.International Journal of Occupational Safety and Ergonomic
Blue hydrogen production through partial oxidation: a techno‐economic and life cycle assessment
Get PDFPartial oxidation (POx) as a hydrogen production method has not received comprehensive exploration as the resulting syngas has a relatively low H2/CO ratio compared to established techniques like steam methane reforming (SMR). As a result, this study aims to comprehensively investigate the feasibility of a low‐carbon hydrogen production process using POx from both technical‐economic and environmental standpoints. To achieve this, the Aspen Plus® software is employed to model a hydrogen production plant with carbon capture integration, referred to as POx‐CCS (carbon capture and storage). The research reveals that the overall energy efficiency of the POx‐CCS process is around 73%. Moreover, the economic evaluation indicates that the levelised cost of hydrogen (LCOH) is €1.8/ kgH2, given a fuel price of €5.7 per GJ. This cost competitiveness positions POx‐CCS in line with conventional hydrogen production methods. From an environmental perspective, the impact of climate change on hydrogen production through the POx‐CCS process is assessed to be 1.1 kg CO2 eq./kgH2. This impact is reduced by 69% compared to SMR with CCS.International Journal of Energy Researc
Vom Draht zum Bauteil: Entwicklung einer Aluminium-Lithium-Legierung für die additive Fertigung mit Draht und Lichtbogen
Get PDFThe Innovative Aluminium filler Wires for Aircraft Structures (IAWAS) project aimed to demonstrate the potential of Wire Arc Additive Manufacture (WAAM) for the production of aluminium lithium components. Preliminary testing demonstrated the possibility of depositing an 2395 aluminium lithium filler wire using a plasma arc heat source and a local shielding device. The deposit had a low porosity level but also low ductility caused by long, vertical, segregated grain boundaries. Both chemical composition and deposition conditions are known to impact the deposit microstructure. In-situ alloying, an efficient technique to develop new material, was implemented using plasma arc as a heat source on aluminium lithium alloys. The results aligned with the literature review on the impact of copper on crack sensitivity and led to the design of a new alloy. Unfortunately, the composition selected yielded challenges during the drawing process, and the filler material quality was poor, leading to a low WAAM deposit quality. Machine hammer peening was implemented on the AA2395 alloy, resulting in a drastic increase in ductility and yield strength of 480 MPa after solution treatment and ageing. This alloy was used to manufacture an aluminium lithium demonstrator to showcase the potential of WAAM to produce real-life components.The authors would like to acknowledge the European funding allocated to the IAWAS project partners (Grant agreement ID: 821371). This research work was also supported by the Engineering and Physical Sciences Research Council (EPSRC) through the NEwWire Additive.BHM Berg-und Hüttenmännische Monatsheft
Simultaneous removal of organic micropollutants and metals from water by a multifunctional β-cyclodextrin polymer-supported-polyaniline composite
Get PDFThe occurrence of diverse pollutants in water resources across the globe, including organic micropollutants and heavy metals, has challenged the efficacy of many existing water treatment processes. Various materials and media have been developed for removal of these compounds, but few have the capacity to remove multiple contaminants which are typically present in real water sources. Here we report on a novel sorbent (PANI@PCDP) for the simultaneous removal of organic micropollutants and heavy metals during a single process. Cr(VI) and bisphenol A (BPA) were selected as target pollutants due to their frequent occurrence in aquatic environments and the significant health risks they pose. PANI@PCDP exhibited a high level of performance for removal of BPA and total Cr at pH 6 for initial concentrations of 0.5–100 mg/L for Cr(VI) and 0.228–22.8 mg/L for BPA. Up to 98 % Cr was removed at pH 6 through the adsorption and reduction of Cr(VI), followed by the sequestration of the generated Cr(III). In addition, BPA could be captured by PANI@PCDP at an adsorption rate of 1.4 × 10-1 g mg−1 min−1 as a result of the fast formation of complexes with the media. When the PANI@PCDP media was tested on a wider variety of emerging organic micropollutants (including chlorinated aromatic compounds, simple aromatics, and pharmaceuticals) good removal was observed. Such performance benefits arise from the integration of porous β-cyclodextrin polymers with polyaniline, which provides the PANI@PCDP with multiple binding sites for contaminant removal. In addition, the PANI@PCDP can be regenerated at least five times without loss in performance using a facile procedure, providing evidence for its practical application in water treatment.Chemical Engineering Journa
The road not taken yet: a review of cyber security risks in mobility-as-a-service (MaaS) ecosystems and a research agenda
Get PDFThis paper identifies the state-of-the-art key aspects for the development of mobility-as-a-service (MaaS) ecosystems and provides evidence on the importance of cyber security which has been broadly overlooked in the literature. The analysis is carried out in three stages: (i) a literature review, (ii) a presentation of expert workshop findings, and (iii) a synthesis of both findings to develop a research agenda on cyber security aspects of MaaS ecosystems. The review identifies and bridges the gap between two strands of MaaS literature: the studies that focus on the factors that drive the development of MaaS, and those that create narratives of future MaaS scenarios. The analysis employs the Business Model Canvas to synthesise important factors that underline the development of MaaS in a 7-dimension matrix. This matrix is then used to assess to what extent the available MaaS scenarios cover such dimensions, showing that the literature has overlooked the incentives for users, incentives for MaaS providers, public governance and cyber security elements of the MaaS development. Finally, this paper synthesises the findings from the review of the literature and an expert workshop to develop a research agenda to characterise and analyse the role of incentives to influence the individuals' and organisations' data sharing preferences and emerging cyber security risks in MaaS ecosystems, which will be of interest to both scholars and policymakers. Only through explicit consideration of data-sharing behaviours and risks across individuals and organisations that MaaS ecosystems can support the transition to a net-zero economy.Engineering and Physical Sciences Research Council (EPSRC)Research in Transportation Business and Managemen
An enhanced deep autoencoder for flight delay prediction
Get PDFAccurate and timely flight delay prediction cannot be overemphasized because of the ever-increasing
demand for air travel and its importance in deploying intelligent transportation systems. Nonetheless,
there has not been a universal solution to the problem, as more intelligent flight decision systems are
required for the aviation industry’s future growth. Existing flight delay classification and prediction
approaches are mainly shallow traffic models and do not satisfy many applications in the real world.
Our motivation to rethink the deep architecture model for predicting flight delays emanates from the
problem. In this research, we proposed a technique that modified stacked autoencoder architecture
parameters for training the network and understanding the link between space, time and information
gained from the flight on-time data. We developed three different types of autoencoders based on the
architecture of the modified stacked autoencoder. The models learn the generic flight delay features,
and it’s trained greedily in a layer-wise fashion. To the best of our knowledge, this is the first time
these performances of vanilla autoencoder, logistic regression autoencoder and Multilayer perceptron
for classification were evaluated based on the developed modified stacked autoencoder architecture.
Moreover, our experiment demonstrates that the models achieved varying levels of accuracy in
the flight delay classifications task. The deep vanilla autoencoder shows superior accuracy, recall
and precision performance compared to logistic regression autoencoder and Multilayer perceptron
autoencoders at different parameter settings.The Petroleum Trust Development Fund (PTDF) Nigeria partially funded this work through grant number PTDF/ED/OSS/PHD/DBB/1558/19 for one of the first author’s Ph.D. studies.We also thank the UKRI for the COVID-19 recovery grant under the budget code SA077NThis research was heavily affected by the COVID-19 pan- demic during the first authors’ Ph.D. studies. This led to an extension to registration for 3 months, which was funded by the UKRI doctoral extension recovery grant.Journal of Aviation/Aerospace Education and Researc