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Synergistic strengthening mechanism of cryogenic treatment for mechanical properties and damping characteristics of Mn–Cu alloy
No full textMn–Cu alloys are widely used as shock absorption and noise reduction materials in engineering fields. However, the strengthening of their mechanical properties often leads to a decrease in damping performance, which limits the further application of these alloys. To overcome this limitation, this paper systematically investigated the effects of different cryogenic treatment times (−196 °C) (0 h, 12 h, 24 h, 36 h) on the microstructure, mechanical properties and damping behavior of the Mn–Cu alloy. The results show that cryogenic treatment can effectively increase the internal dislocation density of the alloy, promote the refinement of the α -Mn phase, increase the proportion of the Mn-rich region, and induce the FCC→FCT martensitic phase transformation to improve the formation of twinning. As the cryogenic time increases, the tensile strength and hardness of the alloy increases, but the elongation decreases slightly. Cryogenic treatment introduces a large number of dislocations in the alloy, which makes the damping performance of the alloy exhibit a synergistic strengthening effect of twinning damping and dislocation damping mechanisms at different temperatures, providing a new method for the development of high-performance of Mn–Cu alloys.The project was supported by the National Natural Science Foundation of China (52175410), the Natural Science Research Program for Higher Educational Institutions in Jiangsu Province (18KJB430009), and Zhenjiang Basic Research Special Project (JC2024010).Journal of Materials Research and Technolog
Securing landscape resilience
No full textHarris, Jim A. - Associate Supervisor
Simms, Daniel M. - Associate SupervisorClimate-induced perturbations are expected to increase in frequency and
intensity and affect wetlands by altering its hydrology. An essential first step in
comprehending the wetland hydrological and ecological resilience to future
amplified climatic disturbances in coastal regions and beyond is this work, which
enhances the approach for measuring wetland hydrologic resilience at a regional
scale.
Land use change, natural disturbance and climate change directly alter
ecosystem productivity and resilience levels. The estimation of ecological
resilience dynamics depends on the quality of land cover change data and the
effectiveness of the ecosystem models that represent the vegetation growth
processes and disturbance effects. We used different mathematical approaches
determining resilience, land cover change data to examine landscape resilience
of the ecological networks in terms of scale, and how resilience exhibits as an
emergent behaviour in different types of ecosystems, with its influencing factors,
suggesting application to other estuarine ecosystems. A set of quantitative
metrics was developed including the variations of landscapes, utilizing spectral
power to determine changes in autocorrelation and variance as measures of
critically slowing down, detecting the early warning signals with the development
of the Dynamic Linear Model (DLM).
The coastal landscape, which includes coastal-herbaceous wetlands, was then
subjected to this method detecting the influence of salinity intrusion on estuarine
systems along geographical and temporal salinity gradients. We discovered that
an excellent indication of resilience is the multiscale autocorrelation fluctuations
of wetlands, affected by the temporal trends in data, under various climatic
circumstances.
Climate interannual variability was the key driving force for the large interannual
changes of ecosystem state level while extreme weather events and drought
were the dominant driving forces for resilience balances in several specific
ecoregions. There is a need for techniques that may be utilised to recognise when
a major transition is about to happen because these events might happen without
warning and are challenging to handle. A number of "early warning signals" can
be used to determine a system's near to a critical transition, according to recent
theory, and successful empirical examples point to the possibility of practical use.
Our study provides a practical toolbox that can be applied in a variety of sectors
to help identify early warning signs of crucial transitions in time series data, in
addition to a methodological guide.Natural Environment Research Council (NERC)PhD in Environment and Agrifoo
Digital twin of aircraft electrical actuator to generate data for health management research
No full textKing, Stephen - Associate SupervisorElectric-powered actuators play an important role in the new generations of commercial aircraft systems. They are used in Flight Control, Propulsion, Landing Gear and even seat actuation. As they are “Power-by-Wire” and connected to the aircraft control system, it is easy to acquire their operations and health data. Electro-Mechanical Actuator (EMA) is increasingly used to replace traditional hydraulic actuators in the future All/More Electric Aircraft.
However, lack of historical operational data makes complicated the risk analysis of EMA into aircraft systems. This research aims to develop an approach of Digital Twin design to support data generation for Aircraft Health Management algorithm development. The Digital Twin is designed to represent flight control EMA. The data generator is developed combining the Digital Twin EMA and a fault injection module, controlled by MATLAB scripts, to simulate operations in multiple scenarios, including nominal operations, degradation, and fault. EMA faults represented include unstable power supply, mechanical backlash, and power cable wear. The combination of simultaneous faults is explored by introducing multiple faults as part of the case analysis. This research indicates data could be generated to enable failure features detection in early or mid-stage failures. The research tackles the challenge to monitor, trigger and locate faults at subsystem/component level of an EMA. The framework could generate datasets to accelerate diagnostic and prognostic research in the early detection of EMA failures and enhance performance, thus facilitating timely maintenance actions that can prevent costly downtimes and extend the operational life of aircraft components.
The framework extends the concept of Digital Twin as a tool to support engineering design and operations to a toll for data generation.PhD in Transport System
Impact of crude oil contamination on green leafy vegetables: nutritional and health risk assessments
No full textFor decades, crude oil spills have been a serious environmental challenge which have led to the establishment of crude oil remediation intervention values (CRIV) by different national agencies to regulate the release of toxic petroleum hydrocarbons via these spills. To ascertain the suitability of these CRIV in crude oil‐polluted agricultural sites, the impact of five CRIV on the nutritional composition of two green leafy vegetables (GLV) and associated human health risk was investigated using standard analytical procedures. Briefly, high‐performance liquid chromatography was used in determining the composition of the sugars while inductively coupled plasma mass spectrometer and atomic absorption spectrometer were utilized in quantifying the levels of minerals in the harvested samples. This was followed by human health risk assessment based on the evaluation of noncarcinogenic and carcinogenic risks. CRIV at 3000 and 5000 mg/kg total petroleum hydrocarbons (TPH) reduced the fructose and glucose contents of Lactuca sativa whereas the sucrose level was enhanced at 10,000 mg/kg TPH. All the tested CRIV had no statistically significant effect (p > 0.05) on the Na/K ratio of Brassica oleracea as well as the F/G and Ca/P ratios of L. sativa. Among the studied nonessential heavy metals, only the samples' Pb contents were below the FAO/WHO Codex maximum level. Multivariate statistical analysis indicated that the 10,000 mg/kg TPH treatment GLV samples' nutrients were the most impacted by the crude oil stress which also primarily had the highest non‐carcinogenic and cancer risk levels. The investigation revealed the potential of some crude oil concentrations in agricultural sites to alter the physiology of GLV and their nutritional composition. Consequently, use of CRIV at TPH concentration of ≤ 3000 mg/kg is recommended to protect the quality of GLV from such sites and to safeguard against possible cancer risk.The authors sincerely thank the Petroleum Technology Development Fund (PTDF), Nigeria [PTDF/E/OSS/PHD/OJO/625/12], for the financial aid given to the first author, Johnson Oluwaseun Odukoya, that made this research possible.Remediation Journa
Carbon footprint of wire arc additively manufactured optimized structural steel element
No full textMetal Additive Manufacturing (AM), and particularly Wire Arc Additive Manufacturing (WAAM), opens new opportunities for steel structures by enabling efficient, reliable, and material‐saving solutions with reduced environmental impact. The AEC sector is starting to adopt WAAM for full‐scale structural elements, benefiting from its design freedom. However, tailored design approaches are needed to fully harness its potential and realize geometries unachievable with conventional methods. This study evaluates the environmental performance of a novel steel structural element featuring a Tubular Sandwich Section (TSS), fabricated using WAAM. The TSS, which defines the section of the structural element, consists of inner and outer cylinders connected by internal spokes, providing improved radial strength and better alignment with structural requirements. Its performance is compared to that of a conventional Circular Hollow Section (CHS), manufactured through cold forming with equivalent diameter and radial capacity. A cradle‐to‐gate analysis shows that WAAM enables a lighter and more sustainable alternative, highlighting its promise in reducing the carbon footprint of the construction sector.SDSS 2025 International Colloquium on Stability and Ductility of Steel Structuresce/paper
Discussion and re-evaluation of recent research on pressure ingress into a room from an opening
No full textWe review Codina and Ambrosini’s articles Full-scale testing of leakage of blast waves inside a partially vented room exposed to external air blast loading (2018), and Numerical and analytical study of overpressures and impulses inside a masonry box subjected to external blast loading (2019) concerning shock ingress into a room from a façade opening. The articles report the results of a full-scale experimental series for shock ingress loading of a room’s interior walls and compare them to predictions from CFD simulations and the widely used UFC 3-340-02 method. They conclude that the UFC overpredicts the impulse on the room interior side walls by up to 685%, while underpredicting the impulse on the back wall by up to 60%. Subsequently, they recommend applying modification factors to the UFC peak pressure and positive phase duration results to better match the experimental results. In this paper, we review the scarce published research on this subject to highlight the significance of the data presented within these two papers. We then critically assess the design, execution, and analysis of the reported experiments and simulations. We present an alternative analysis of their published data which accounts for the use of non-blast gauges and compare it with our own CFD simulations. These CFD simulations closely predict the alternative analysis of the experimental results and offer amendments to the original papers’ conclusions.International Journal of Protective Structure
Investigation of thermal penetration from the fire scene into the deceased fire victim
No full textInvestigating fatal fires is a complex multi-disciplinary undertaking, with victims considered to be a fundamental part of the evidence. This study investigated thermal penetration into human remains with the aim of extending the results to the assessment of the fatal fire victim. Data was collected during the burning of 15 unembalmed bodies in years 2017–2019 with the San Luis Obispo Strike Team (SLOFIST) on their annual Forensic Fire Death Investigation Course (FFDIC). Cadavers were placed within a scene of individually built compartment rooms to simulate accidental and intentional fires. Thermocouples were placed within the compartments at ceiling/mid/floor levels and within the thoracic cavity of the deceased which facilitated analysis of thermal transition through phases of fire development from ignition to suppression. Radiant heat flux data enabled investigation of the relationship of the thermal environment and internal body temperature rise in kW/m2. A statistically significant relationship between ceiling radiant flux and internal body temperature was identified in the thermal penetration of the body at p ≤ 0.041, and a highly statistically significant correlation of p ≤ 0.001 between internal body temperature rise and the fire development phenomenon of flashover. The effect size for this relationship (88%) indicates that a large proportion of internal body temperature rise in fire victims is accounted for by exposure to the fire phenomenon of flashover.Science & Justic
Development of a cooperative multistatic radar network based on the Aveillant holographic radar
No full textStaring radars use a transmitting static wide-beam antenna and a directive digital array to form multiple simultaneous beams on receive. Because beams are static, the radar can employ long integration times that facilitate the detection of slow low-RCS targets, such as drones, which present a challenge to traditional air surveillance radar. Typical low-altitude trajectories employed by drones often result in low-grazing angle multipath effects, which are difficult to mitigate with a monostatic radar alone. Using multiple spatially separated receivers cooperating with the staring transmitters in a multistatic network allows multi-perspective target acquisitions that can help mitigate interference from the environment and improve the detection and localisation of drones. The term drone refers to small unmanned aerial systems (UASs) with a radar cross-section (RCS) of approximately 0.01 m2,such as the DJI Phantom/Inspire series. This thesis presents the development of a cooperative radar network. The radar network consists of a staring transmitter and multiple bistatic passive receivers. The advantage of a staring transmitter is that the network can use long integration times to detect slow and low RCS targets such as drones. The staring transmitter ensures a constant signal at the receiver nodes within the radar’s coverage and, therefore, can be simplified as they do not need to employ pulse-chasing techniques. Target position and velocity estimation algorithms have been developed for the cooperative radar network. The theoretical lower bound on the error of estimation algorithms is used to determine the estimation performance of the radar network and is further used to optimise the network’s geometry by minimising estimation error. As part of the thesis, a passive bistatic dual-channel receiver has been developed and employed in a bistatic configuration with a staring transmitter of opportunity to test the theoretical algorithms and measure a drone in flight. The receivers are designed along passive radar principles and consist of two receive channels: a surveillance channel aligned with the transmitter and a reference channel aligned with the target. The receiver employs horn antennas with a wide 90◦ degree beamwidth and has been used to perform laboratory measurements of a rotating fan, the micro-Doppler signature of a remote-control helicopter, a moving car and a drone in flight
A comprehensive framework for enhancing environmental sustainability in the chemical industry
No full textThe chemical industry, essential to economic growth and innovation, faces critical environmental sustainability challenges, notably pollution, emissions, and intensive resource use. Motivated by the need for practical tools to address these issues, this research develops a structured, comprehensive framework to assess and enhance environmental sustainability within the chemical sector. The framework employs clearly defined Key Performance Indicators (KPIs) related to emissions, resource consumption, and pollutants, providing systematic methods for their identification, measurement, benchmarking, and improvement. It was developed through a structured literature review and sectoral data analysis, followed by the formulation of benchmark construction and a tiered rating approach to assess relative performance. Benchmark values are established using competitive market data, enabling accurate performance comparisons. The framework's effectiveness and practicality are demonstrated through two illustrative case studies, a detailed process-level analysis (steam cracking) and an indicator-level analysis (NOx emissions), which highlight clear opportunities for improvement. This study contributes a scalable, actionable approach that enables chemical companies to achieve measurable sustainability improvements, align with regulatory requirements, and strategically advance their environmental performance.Cleaner Manufacturin
A hybrid finite-volume reconstruction framework for efficient high-order shock-capturing on unstructured meshes
No full textIn this paper, we present a multi-dimensional, arbitrary-order hybrid reconstruction framework for compressible flows on unstructured meshes. The proposed method advances state-of-the-art high-resolution schemes by combining the efficiency of linear reconstruction with the robustness of high-order non-oscillatory formulations, activated only where necessary through a novel a priori detection strategy. This approach minimises the use of costly Compact Weighted Essentially Non-Oscillatory (CWENOZ) or Monotonic Upstream-centered Scheme for Conservation Laws (MUSCL) reconstructions, thereby substantially reducing computational overhead without compromising accuracy or stability. The framework integrates the strengths of CWENOZ formulations and the Multi-dimensional Optimal Order Detection (MOOD) paradigm, while introducing a redesigned Numerical Admissibility Detector (NAD) that classifies the local flow field in a single step into smooth, weakly non-smooth, and discontinuous regions. Each region is then reconstructed using an optimal method: a high-order linear scheme in smooth areas, CWENOZ in weakly non-smooth zones, and a second-order MUSCL scheme near discontinuities. This targeted, a priori allocation preserves high-order accuracy where possible and guarantees non-oscillatory, stable solutions near shocks and strong gradients. The proposed hybrid strategy is implemented within the open-source unstructured finite-volume solver UCNS3D and supports arbitrary-order reconstructions on mixed-element meshes. Comprehensive two- and three-dimensional benchmark tests demonstrate that the method maintains the designed order of accuracy in smooth regions while significantly enhancing robustness in shock-dominated flows. Owing to the reduced frequency of expensive nonlinear reconstructions, the framework achieves up to a 2.5 × speed-up compared to a CWENOZ scheme of the same order in 3D compressible turbulence simulations. Overall, this hybrid framework brings high-order accuracy closer to in industrial-scale CFD simulations through its combination of reduced computational cost, improved robustness, and reliability.The authors acknowledge the computing time on ARCHER2 through UK Turbulence Consortium [EP/X035484/1], and P.T. acknowledges the support provided by the EPSRC grant for “Adaptively Tuned High-Order Unstructured Finite-Volume Methods for Turbulent Flows” [EP/W037092/1].Computers & Fluid