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Effect of prolonged natural ageing on microstructure and tensile properties of a high strength die-cast Al-Mg-Si-Zn alloy
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Data will be made available on request.A two-year prolonged natural ageing effect of a high strength and heat treatment-free Al5.5Mg2Si3Zn die-cast alloy was investigated, and the microstructure was characterized to understand the underlying mechanisms of high strength in the as-cast state and the strong natural ageing strengthening. The die-cast alloy exhibited the high yield strength (YS) of 211 ± 2.3 MPa, ultimate tensile strength (UTS) of 334.7 ± 14.4 MPa and the good elongation (EL) of 5.8 ± 1.28 % in the initial as-cast state. After natural ageing for 24 months, the die-cast alloy delivered the high YS of 290.9 ± 2.7 MPa, UTS of 375.3 ± 6.8 MPa and the industrially acceptable EL of 2.58 ± 0.24 %, which shows 38 % improvement in YS over the die-cast alloy under as-cast condition. The intrinsic connection between the YS and the natural ageing time of 24 months can be expressed as an exponential model, i.e., YS (MPa)= 291.83–71.93 × 0.99t (day). The YS reached a stable state after natural ageing for 8.3 months. The as-cast alloy comprised the intermetallic phases of Mg2Si, α-Fe and Mg32(Al, Zn)49. The diameter of the fibrous Mg2Si phase ranged from 0.08 to 0.25 μm, while the size of the fine blocky α-Fe was measured as ∼0.8 μm. Strengthening by refined primary and secondary phases and solid solution are responsible for the high as-cast YS over 200 MPa. The precipitation strengthening of nanoscale η'-MgZn2 precipitates with the number density of 23.6 × 1023, 36.5 × 1023 and 44.8 × 1023/m^2 contributed to the strong enhancement of 34.2, 68.0 and 79.8 MPa over the as-cast YS after natural ageing for 1, 7.2 and 24 months, respectively.This work has been supported by the National Outstanding Youth Science Fund Project of National Natural Science Foundation of China, the Jiangsu Specially-Appointed Professor project and Innovate UK (No. 113151, 10113213, 103962)
Privacy-preserving distributed optimization for economic dispatch in smart grids
No full textThe material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Daniele Casagrande under the direction of Editor Florian Dorfler.This paper discusses a distributed economic dispatch problem (EDP) of smart grids while preventing sensitive information from being leaked during the communication process. In response to the problem, a novel privacy-preserving distributed economic dispatch strategy is developed via adding an exponentially decaying random noise to minimize the total cost of the grid while ensuring the privacy of sensitive state information. The quantitative relationship between the privacy and the estimation accuracy of eavesdroppers is profoundly disclosed in the framework of (ς, σ)-data-privacy. Furthermore, a sufficient condition on the iteration step size is achieved to ensure that the well-designed algorithm can converge to the optimal value of the addressed EDP exactly by resorting to the classical Lyapunov stability theory. Finally, simulation results verify the effectiveness of the carefully constructed privacy-preserving scheme.This work was supported in part by the National Natural Science Foundation of China under Grants 62373251, U21A2019, 62222312 and 62473285; in part by the National Key Research and Development Program of China under Grant 2022YFB4501704; in part by the Shanghai Science and Technology Innovation Action Plan Project of China under Grant 22511100700; and in part by Fundamental Research Funds for the Central Universities
High-performance hybrid AI systems with quantum-secure protocols for cyber-physical remote healthcare applications
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonDigital Twin (DT) technology is increasingly important for real-time healthcare monitoring and
predictive analytics. However, existing healthcare systems face critical challenges, including
excessive computational load, high network latency, vulnerability to quantum cyberattacks,
and inefficient strategies for distributing tasks across cloud and edge environments. Existing
solutions often fail to scale efficiently, protect sensitive health data against future cyberattacks,
or deliver reliable performance under dynamic conditions. To address these challenges, this
work proposes an integrated healthcare framework that advances the state-of-the-art across
multiple dimensions.
First, to tackle the computational bottleneck in wearable healthcare devices, a lightweight
one-dimensional convolutional neural network (CNN) accelerator was designed and implemented
on field-programmable gate arrays (FPGAs), leveraging shift-based computation and
pipelined architecture. This achieved a classification throughput of 1145 GOPS (Giga operations
per second), enabling ultra-low-latency and energy-efficient biosignal analysis. Second, to
enhance system responsiveness and scalability, a cloud-edge Digital Twin healthcare system was
developed, leveraging secure Internet of Things (IoT) communication, dynamic telemetry optimization
using Pyomo mathematical programming, and real-time predictive analytics. Third, to
address emerging data security threats, a novel quantum-secure healthcare Digital Twin model
was introduced, leveraging Quantum Key Distribution (QKD) protocols and hybrid artificial
intelligence (AI) models combining multilayer perceptrons (MLP), extreme gradient boosting
(XGBoost), and generative adversarial networks (GANs) for data augmentation. Finally, to optimize
system resilience under dynamic healthcare conditions, a dynamic task offloading strategy
was proposed, leveraging multi-agent reinforcement learning (MAPPO), adaptive cybersecurity
protection (ACTO), and quantum-enhanced task preprocessing (AQDT-IoT).
Experimental results demonstrate that the FPGA accelerator achieves 1145 GOPS throughput
for real-time biosignal classification, while the proposed cloud-edge healthcare system
reduces network latency by 40% and improves throughput by 30%. The hybrid AI model
achieves an average prediction accuracy of 97.48% across health indicators under 10-fold crossvalidation.
Moreover, the adaptive task offloading framework increases task success rates by
32% and reduces error rates by 80%, significantly improving operational efficiency and system
robustness. Compared to previous approaches, the proposed framework delivers a highly
scalable, secure, and intelligent Digital Twin Healthcare system, significantly strengthening
patient monitoring, predictive decision-making, and preparedness against future quantum-era
cybersecurity threats.Ministry of Higher Education and Scientific Research, the Cultural Attach´e, and the University of Diyala in Ira
Enhancing Operational Efficiency in Mumbai's Airport Departure Terminal: A Hybrid Simulation Modeling Approach
Get PDFAirports function as complex systems comprising interrelated entities, resources, and processes. Inefficiencies within these systems, particularly long waiting times, contribute to passenger dissatisfaction. This study examines operational improvements at Mumbai International Airport, one of India's busiest hubs, focusing on identifying bottlenecks and reducing congestion for departing passengers. Discrete event simulation served as the core methodological framework. Through hybrid simulation, AS-IS models were developed to analyze operational processes and evaluate bottlenecks. BPMN was used for conceptual modeling, followed by Simul8 for dynamic modeling. TO-BE system configurations for check-in, security screening and boarding were then remodeled. Simulation experiments were conducted to determine the optimal setup that minimizes queuing time while maximizing passenger throughput. The findings highlight an ideal system configuration that significantly reduces waiting times and overall passenger processing time, resulting in improved operational efficiency. These insights provide data-driven recommendations for optimizing airport processes, ultimately enhancing passenger experience and improving airport performance
Investigation on the integrated approach to design and ultraprecision machining of freeform surfaced optics and its implementation perspectives
Get PDFOver the last two decades or so, high precision freeform surfaced components and devices have been drawing the increasing attention by the industry due to their potentials in fulfilling demands for various engineering and consumers applications, such as consumer electronics, biomedical engineering, ophthalmic optics, automotive, electro-optics, aerospace engineering and mobile communications. Meanwhile, ultraprecision manufacturing technology is becoming one of the most effective methods for manufacturing high precision freeform surfaced components with functional features. Therefore, scientific understanding of ultraprecision manufacturing for freeform surfaces is essential and much needed, particularly for robustly fulfilling the gaps between fundamentals, technological innovations and their industrial scale applications. This doctoral thesis is focused on investigating a NURBS (Non-Uniform Rational B-Splines) based integrated approach to design, manufacturing and assessment of freeform surfaced optics and its implementation and application perspectives. Therefore, this doctoral research objectively covers NURBS based modeling and analysis of freeform lenses combining with e-portal development for customization, virtual lens conception and ray tracing simulation assessment, NURBS based toolpath generation and analysis considering design for manufacturing, micro cutting mechanics and the ultraprecision process, dynamic cutting forces modelling, and freeform surface topography generation and characterization, further supported by simulations and experimental trials.
The research reveals the integral process of design and manufacturing of freeform surfaced optics involves meticulous steps, including optic surface modeling and analysis, optic surface design, ultraprecision machining toolpath generation, simulation in both optical performance and machining cutting force on design for high precision manufacturing aspect, optic surface assessment in the digital mode, ultraprecision manufacturing physically, and quality assessment. Throughout the process, NURBS based modelling and analysis are the kernel, on which high precision is pursued and assured by the modelling/algorithms and the associated ultraprecision technology protocol. An integrated approach is developed and implemented through the web-based e-portal, for customized precision design and manufacturing of freeform surfaced varifocal lenses. The e-portal is specifically designed to meet the stringent demands of personalized mass customization, and to technically render a highly interactive and transparent experience of the lens design and manufacture for the lens users. By using Shiny and R-script programming for the e-portal development and combining COMSOL Multiphysics for the ray tracing simulation, the e-portal leverages open-source programming to provide the design responsiveness, manufacturing agility and accessibility. Furthermore, the integration of R-script and Shiny programming allows for advanced interactive information processing online, which also enables the e-portal driven ultraprecision manufacturing system for personalized freeform surface lenses.
Cutting force is a pivotal parameter in the ultraprecision machining process. However, scant emphasis is placed on elucidating the nuances of cutting forces and the associated cutting dynamics in ultraprecision diamond turning of freeform surfaces particularly using fast and/or slow tool servo modes. Theoretical analysis on the cutting force and its modelling are carried out in the ultraprecision diamond turning of freeform surfaces, particularly considering constant variations of cutting forces along the freeform surface curvature and the increasingly stringent requirement on high precision optical surface finishing. The cutting forces modelling is based on further developing the improved Aktins model while taking account of the influence of shear angles varying constantly along the freeform surface machining. Based on the toolpath data of the cutting process at the freeform surface, the depth-of-cut of the surface, curvature variations, and shear angle variations throughout the process are meticulously analyzed. Subsequently, the cutting force modelling is developed to discern the nuances of the cutting motion by analyzing the cutting toolpath, and thus enabling the prediction of cutting forces variation during the cutting motions with a diamond cutting tool. Finally, an approach for examining the correlations between cutting forces and the surface texture, and surface texture aspect ratio is developed and further investigated, particularly against the functional performance of a freeform surface and its generation in ultraprecision machining. The investigation is also evaluated and validated by industrial application data.
The analysis and characterization of the freeform surface is essentially mandatory for the ultraprecision manufacturing process due to its high-precision ‘deterministic manufacturing’ nature and the ability to producing the manufacturing outcome without any additional process. The machine tool trajectory is remained on the surface and can be observed with high-accuracy metrology equipment, which makes the surface topography characteristics containing more valuable information as required for optics surface performance. The above-mentioned surface assessment protocol is developed as a part of the integrated approach, in which the surface texture aspect ratio is investigated particularly the relationships between the surface texture height variation and lateral feature, the underlying micro cutting mechanics affecting their formation and generation in the process, and the resultant optical performance of the freeform surface. Nanometric surface measurement techniques and 3D surface parameters are further explored to quantify the surface texture aspect ratio and assess its correlation with the surface optical performance. Experimental results demonstrate there is a significant correlation between the higher surface texture aspect ratios and increased aberrations, leading to decreased optical quality. Controlling the surface texture aspect ratio during the machining process is crucial for achieving the optimal surface functional performance. The research results above contribute well to the understanding of how the surface texture aspect ratio affecting the performance of freeform surfaced optic components, and provide insights for design and manufacturing of high-performance optical components, although optimization work is further needed in optics surface functionality and optical system design
Adapting the engineering design process to develop a business model for service-oriented living labs: a case study of PISCES
Get PDFThis paper focuses on the development of a viable business model for the PISCES Living Lab, which seeks to address plastic pollution in Indonesia. The overarching aim is to transition it from a project-based initiative to a self-sustaining service enterprise. The paper introduces a new modified engineering design process as a workshop template to guide an interdisciplinary team in creating a business model for a service-oriented living lab. A four-day workshop was conducted in Banyuwangi, Indonesia, involving a diverse group of stakeholders from the project, and the final outcome was the creation of a Business Model Canvas outlining the core components of the PISCES Living Lab’s business model. The findings demonstrate the effectiveness of integrating the engineering design process with business model innovation, offering a structured yet flexible approach to developing self-sustaining Living Labs.This work is supported by the project “A Systems Analysis Approach to Reduce Plastic Waste in Indonesian Societies (PISCES)”, funded by UK Research and Innovation (UKRI) and UK Global Challenges Research Fund (GCRF) (Grant Ref: NE/V006428/1)
Flow boiling in micro-pin fin heat exchangers and comparison with correlations
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Data will be made available on request.The thermo-fluid performance of micro-pin fin heat exchangers has recently received extensive attention from the research community engaged in developing thermal management systems for high heat flux devices. Two-phase flow in these geometries could provide better thermal performance compared to other designs. However, more studies are still required to understand the effect of the control parameters on the fundamental flow boiling characteristics. Therefore, the present study aimed to examine experimentally the performance of micro-pin fin heat exchangers at different operating conditions. Staggered diamond micro-pin fins having a pin height of 1 mm and pin width of 0.6 mm were manufactured on a total base area of 20 mm × 25 mm. HFE-7100 was tested at a system pressure (inlet pressure) of 1, 1.5 and 2 bar, mass flux from 100 to 250 kg/m² s and 5 K inlet sub-cooling, while the wall heat flux was varied up to 324 kW/m². The heat flux was increased gradually until the maximum thermal limit was achieved. Flow pattern features and bubble nucleation around the pins were visualised using a high-speed, high-resolution camera. A base heat flux up to 0.63 MW/m² was recorded without reaching the dryout region or the critical heat flux. Low substrate surface temperature, i.e. less than 85 °C, and stable flow without flow reversal and hysteresis were achieved in this geometry, making flow boiling in micro-pin fin heat sinks suitable for cooling electronics. Nucleate boiling was found to be present for the entire range studied. The effect of heat flux and pressure on the heat transfer rates was significant, while the mass flux effect was marginal for the range studied. Ten existing heat transfer and pressure drop correlations were evaluated, and a good prediction was found by some of them. The prediction of the pressure drop by existing correlations improved when the pin dimensions and the space between them was introduced in the two-phase friction multiplier.The work was conducted with the support of the Engineering and Physical Sciences Research Council of the UK, under Grant: EP/T033045/1
Integrated Underfrequency Load Shedding Strategy for Islanded Microgrids Integrating Multiclass Load-Related Factors
Get PDFReducing the decision response time of load shedding while considering the comprehensive value of load shedding is one of the main challenges faced in emergency control of islanded microgrids. However, the existing underfrequency load shedding strategies do not fully consider the multiple factors associated with the load, and load assessment and load shedding decision-making are separated; this results in a long response time for underfrequency load shedding decisions for islanded microgrids. Therefore, in this paper, an integrated underfrequency load shedding strategy for islanded microgrids is proposed, which integrates multiclass load-related factors. This strategy first constructs an integrated underfrequency load shedding model for islanded microgrids on the basis of multiclass load-related factors such as the load frequency regulation effect, load shedding cost, and three-phase system power unbalance degree. Then, the load shedding model is described as a Markov decision process (MDP), and the environment, action space, and reward function are defined considering the load shedding objectives and constraints of islanded microgrids. Finally, a novel twin delay deep deterministic policy gradient method with softmax and dual buffer replay (DBR-SD3) is developed to determine the optimal integrated underfrequency load shedding strategy. This approach integrates softmax and the dual buffer replay mechanism into twin delay deep deterministic policy gradient (TD3), which greatly improves the ability of the agent to learn the optimal load shedding strategy in a complex microgrid operating environment. The simulation results based on the improved IEEE 37-bus microgrid and IEEE 118-bus microgrid verify that the proposed integrated load shedding strategy can greatly reduce the decision response time, correct the three-phase power unbalance of the system while minimizing the load shedding cost, and restore the system frequency to a normal level more quickly. Moreover, even under strong noise interference, the proposed strategy can produce stable load shedding decisions and has strong robustness and adaptability.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62233006)
Prioritising research on endocrine disruption in the marine environment: a global perspective
No full textSupporting Information is available online at: https://onlinelibrary.wiley.com/doi/10.1111/brv.70106#support-information-section .A healthy ocean is a crucial life support system that regulates the global climate, is a source of oxygen and supports major economic activities. A vast and understudied biodiversity from micro- to macro-organisms is integral to ocean health. However, the impact of pollutants that reach the ocean daily is understudied for marine taxa, which are also absent or poorly represented in regulatory test guidelines for chemical hazard assessment. Inspired by the United Nations Decade of Ocean Science, which aims to reverse the decline in ocean health, this communication calls for global coordination in building resources for studying the effects of marine pollution. The bibliographic analysis, a collective product of scientists from diverse backgrounds, focused on endocrine-disrupting chemicals (EDCs). In this review, we (i) critically analyse the literature on endocrine signalling pathways and high-level physiological impacts of EDCs across 20 representative marine taxa; (ii) identify knowledge and regulatory gaps; (iii) apply bioinformatics approaches to marine species genomic resources, with relevance for predictions of susceptibility; and (iv) provide recommendations of priority actions for different stakeholders. We reveal that the scientific literature on EDCs is biased towards terrestrial and/or freshwater organisms, is limited to a handful of animal taxa, and marine organisms are dramatically underrepresented. Our bibliographic analysis also confirmed that only a small number of (neuro) endocrine pathways are covered for all animals, whilst basic knowledge on endocrine systems/endocrine disruption for most marine invertebrate phyla is minimal. Despite significant gaps in genomic resources for marine animals, endocrine-related protein conservation was evident across more than 500 species from diverse marine taxa, highlighting that they are at risk from EDCs. Despite recent technological advances, translation of existing knowledge into international regulatory test guidelines for chemical hazard assessment and monitoring programs is limited. Furthermore, the current understanding is confounded in part by transposing vertebrate endocrinology onto non-vertebrate taxa. In this context, specific recommendations are provided for all stakeholders, including academia (e.g. to expand knowledge across metazoan taxa and endocrine targets and translate it to New Approach Methodologies and Adverse Outcome Pathways; to increase and improve tools for comparative species-sensitivity distributions and cross-species extrapolations), regulators (e.g. increase awareness of specific risks for the marine environment, prioritise international standardisation of testing methods for marine species and request evidence for absence of endocrine disruption in marine phyla), policy makers (e.g. implement sustained, long-term international marine monitoring programs and increase global co-operation) and the public or non-governmental organisations (e.g. foster public engagement and behaviours that prevent marine chemical pollution; promote citizen science activities; and drive political actions towards protective and restorative marine policies). We hope that this and past reviews can contribute towards meeting ambitious international plans for marine water quality assurance, mitigation of marine pollution impacts and protection of marine biodiversity. The importance of marine biodiversity for climate change mitigation, food security and sustainable ecosystem services calls for urgent, cooperative action.Ministerio de Ciencia, Innovación y Universidades. Grant Numbers: IT1743-22, PID2023-146085NB-I00;
Department for Environment, Food and Rural Affairs, UK Government. Grant Number: C8378;
Fundação para a Ciência e a Tecnologia. Grant Numbers: DL57/2016/CP1361/CT0015, LA/P/0094/2020, LA/P/0101/2020, UID/PRR/04326/2025, UIDB/04326/2020, UIDB/50017/2020;
Euromarine. Grant Number: EM/PFB/2019.048.
Article funding:
Open access publication funding provided by FCT (b-on)
Nature at Risk, Finance at Stake: A Systematic Literature Review of Biodiversity Risk in Finance Research
Get PDFFor the purpose of open access, the author has applied a ‘Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising (https://creativecommons.org/licenses/by/4.0/).Biodiversity-related financial risk is increasingly recognized not only as a market concern but as an ethical and systemic imperative for businesses and financial institutions. This systematic literature review synthesizes 103 peer-reviewed studies to examine how biodiversity risk is conceptualized, measured, and integrated within financial research. While awareness of biodiversity as a systemic financial risk is expanding, the field remains theoretically fragmented and methodologically uneven. Four dominant themes emerge: financial materiality, visibility and recognition, governance and accountability, and levels of analysis. Building on these findings, the review introduces an eco-financial transmission framework that connects biodiversity loss to financial exposure through valuation, governance, and disclosure channels. It further underscores the moral responsibility of financial actors to embed biodiversity into investment practices, ESG strategies, and regulatory design. By integrating ecological economics with ethical finance, this review advances a conceptual foundation for a financial system that not only mitigates biodiversity risk but also supports long-term ecological resilience.The authors received no specific funding for this work
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