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Past, present, and future of battlefield forensics: improving the recovery and identification of fallen servicemen and women in a multinational environment - Presentation
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Autonomy is the answer; what was the question?
Get PDFThis paper was also presented at: The International Naval Engineering Conference (INEC), 5-7 November 2024, Liverpool, England
The full paper is available at: https://dspace.lib.cranfield.ac.uk/handle/1826/23196Royal NavyDefence and Security Doctoral Symposia 2024 (DSDS24
Numerical investigation of dynamic flow and melting behavior of high-concentration ice slurry for sustainable pipeline cleaning
No full textHigh-concentration ice slurry is a promising and environmentally friendly solution for energy-efficient pipeline cleaning due to its high latent heat and effective scouring ability. A novel mixture model based on the kinetic theory of granular flow incorporating a phase-change melting model and a dynamic wall temperature function has been developed to simulate the dynamic flow and melting behavior of thick ice slurry in a horizontal pipe. Numerical simulations are compared to experimental data, and results primarily focus on the ice slurry flowing distance before complete melting, effective flowing distance, melting characteristics, formation and evolution of the slurry-water interface, as well as the temperature distribution across different regions of the pipe. Results confirm that injection length, concentration, and velocity of the slurry have a significant effect on its flowing distance, and that the ice slurry melting rate gradually decreases. In addition, the ice slurry exhibits a distinct edge-to-center melting pattern, with the outer layers melting first and surrounding the central region. The ice volume fraction decreases from the center toward both ends from the axial direction, and the ice volume fraction is lowest at the bottom and gradually increases with height. The front and rear interfaces between the ice slurry and water appear finger-shaped, however behaving differently due to the viscosity difference. Numerical results are shown to match well the experimental data, providing a useful numerical tool and guidance for the design and operation of ice slurry-based pipeline cleaning systems.Applied Thermal Engineerin
The status of plasma induced acidification and its valorising potential on slurries and digestate: a review
No full textThis review examines the current status and future potential of plasma-induced acidification (PIA) as a sustainable method for managing nitrogen-rich organic waste streams such as livestock slurry and digestate. Conventional acidification using sulfuric or nitric acid reduces ammonia (NH3) emissions but raises concerns related to safety, cost, and environmental impacts. Plasma-assisted systems offer an alternative by generating reactive nitrogen and oxygen species (RNS/ROS) in situ, lowering pH and stabilizing ammonia (NH3), as ammonium (NH4+), thereby enhancing fertiliser value and reducing emissions of NH3, methane (CH4), and odours. Key technologies such as dielectric barrier discharge (DBD), corona discharge, and gliding arc reactors show promise in laboratory-scale studies, but barriers like energy consumption, scalability, and N2O trade-offs limit commercial adoption. The paper reviews the mechanisms behind PIA, compares it to conventional approaches, and assesses its agronomic and environmental benefits. Valorisation opportunities, including the recovery of nitrate-rich fractions and integration with biogas systems, align plasma treatment with circular economy goals. However, challenges remain, including reactor design, energy efficiency, and lack of recognition as a Best Available Technique (BAT). A roadmap is proposed for transitioning from lab to farm-scale application, involving cross-sector collaboration, lifecycle assessments, and policy support to accelerate adoption and realise environmental and economic gains.This research was funded by Engineering and Physical Sciences Research Council (ESPRC) Doctoral Training Program and N2 Applied.Nitroge
Predicting wear damage in moving mechanical contacts: comparative analysis of regression algorithms and feature selection techniques
No full textAccurate wear prediction is essential for industries such as manufacturing, transportation, and power generation, as it helps reduce operational risks, minimise downtime, and extend the lifespan of critical components. This study presents a machine learning-based predictive model for estimating wear volume in pin-on-disc systems. The methodology comprises four key stages: feature selection, sample size determination, regression model selection, and model evaluation. The experimental data include parameters such as friction coefficient, tangential force, penetration depth, sliding distance, sound pressure, and load. Feature selection is employed to identify the most relevant parameters for wear prediction, utilising two methods —wrapping and embedding —to refine the feature subset and enhance accuracy. To optimise model performance, the sample size is determined to balance underfitting and overfitting. Initially, linear regression is applied, followed by adjustments to the sample size. Where necessary, more complex algorithms, such as support vector machines (SVMs) and random forests (RFs), are explored to enhance accuracy. Model evaluation employs metrics including mean absolute error (MAE), mean bias error (MBE), root mean square error (RMSE), and the coefficient of determination (R²) to assess predictive performance. This research offers a systematic approach to wear volume estimation and presents a comparative analysis of regression algorithms, providing valuable insights for researchers and practitioners in wear prediction applications.ISA Transaction
The life cycle assessment of trees outside woodlands: a systematic review of methodological approaches
No full textPurpose:
The purpose of this study is to understand how Life Cycle Assessment (LCA) methodology has been applied to evaluate the impacts of trees outside woodlands and where improvements are needed. This review aims to discuss the primary limitations when using LCAs to assess trees outside woodlands, particularly in comparison to existing literature on their environmental, social, and economic implications.
Methods:
Following the established STARR-LCA systematic review protocol, a total of 102 studies across 30 countries were identified. The selected studies used LCA frameworks to assess the impacts of five different trees outside woodland systems. Qualitative data relating to the tree system and LCA methodology were manually extracted from each study and summarised for analysis based on the four phases of an LCA: goal and scope, life cycle inventory, impact assessment, and interpretation.
Results and discussion:
This review showed the selected studies were primarily located in Southern Europe, South America, and Asia. Orchards were the focus of 68% of the papers, followed by 13% assessing silvopastoral systems. No papers were found on hedgerows or Miyawaki forests, which were within the scope of this review. The most common functional units were based on mass, area, and economic measures, and 29% of studies used more than one functional unit to interpret their LCA results. Environmental impacts were considered in 98% of the selected studies, whereas 13% of studies integrated an economic impact assessment, and only 5% accounted for the social implications of trees outside woodlands. Similarly, even though trees outside woodlands can increase carbon sequestration and biodiversity levels, these measures were only incorporated into 25% and 10% of the LCA studies, respectively.
Conclusions:
The environmental, economic, and social impacts of trees outside woodlands are dependent on the type of system and its intended purpose, climatic zone, and landscape. Process-based LCAs can be used to effectively assess the impacts of trees outside woodlands. However, the ability to holistically assess trees outside woodlands is limited by current LCA methodology, particularly when accounting for system multifunctionality or ecosystem services such as carbon sequestration and biodiversity. To address these limitations, four research recommendations have been made to improve future LCA studies. This could enhance the usefulness of LCAs in understanding sustainability trade-offs and facilitating decision-making across different tree system scenarios.This research has been funded by the UK Government’s Shared Outcomes Fund as part of the Trees Outside Woodland programme.The International Journal of Life Cycle Assessmen
Implementation of FTA Elute card for viral RNA storage and cost‐effective wastewater surveillance
No full textWastewater‐based epidemiology (WBE) has emerged as a significant tool for early infection detection during the COVID‐19 pandemic, enabling timely diagnosis and effective control. However, conventional methods for sample transport and storage rely on cold chain logistics, which increase costs and limit accessibility. This study presented a portable and user‐friendly strategy for room‐temperature storage of RNA in wastewater using FTA Elute cards. Quantitative reverse transcription polymerase chain reaction (RT‐qPCR) analysis demonstrated a 15.4% recovery of the original RNA with cards, compared to only 0.5% recovery without cards. Stability assessments under room temperature, ‐4 °C, and ‐20 °C confirmed that RNA retained detectability for over one month, with enhanced preservation at lower temperatures. Furthermore, FTA Elute cards exhibited good recovery for SARS‐CoV‐2, influenza A, and influenza B in spiked wastewater. This work provides a promising solution for RNA preservation and transport in environmental matrices without cold chain dependency.Natural Environment Research Council, Department of Health and Social Care, Leverhulme TrustThe research was funded by the UK NERC Fellowship grant (NE/R013349/2) and UKHSA, UKRI NERC N-WESP (NE/V010441/1), and UK Health Security’s Environmental Monitoring for Health Protection. Z.Y. thanks to The Leverhulme Trust Research Leadership Awards (RL-2022-041)Advanced Sensor Researc
A stakeholder-centric fuzzy AHP-TOPSIS framework for prioritizing challenges and solutions in the sustainable circular supply chain of electric vehicle batteries
No full textThe worldwide shift to electric mobility has rendered the establishment of sustainable and circular electric vehicle (EV) battery supply chains an immediate imperative. This study proposes a stakeholder-centric, hybrid multi-criteria decision-making framework that incorporates Fuzzy Analytical Hierarchy Process and Fuzzy Technique of Order of Preference by Similarity to Ideal Solution to prioritize challenges and solutions in the EV battery supply chain. Drawing on stakeholder and sustainability theories, the framework evaluates 10 primary challenge domains, 35 sub-challenges, and 14 solution strategies based on insights from six key stakeholder groups: mining and resource extraction, raw material procurement, manufacturing and product development, supply chain and logistics, product management and strategy, and research and development. FAHP results identify environmental resource and lifecycle concerns and supply network robustness and economic stability as the most significant challenge areas. At the sub-criteria level, stakeholders prioritized scarcity and sustainability of vital resources and vulnerabilities in supply chain architecture. FTOPSIS analysis ranks policy framework and compliance and collaborative and stakeholder engagement as the most influential and widely endorsed solution strategies. A foresight-based sensitivity analysis for the year 2040 compares two contrasting future scenarios: a fully developed circular battery ecosystem and another marked by global supply chain volatility and heavy import dependence. Innovation-driven solutions dominate the former, while policy preparedness and economic incentives dominate in the latter. This study offers a novel, transferable framework that aligns stakeholder priorities with circular economy objectives, providing strategic guidance for fostering resilient and sustainable EV battery supply chains across global regions.Cleaner Logistics and Supply Chai
Leveraging resource management and duality theories to strengthen circular economy practices in the waste‐to‐energy industry
Get PDFWith the immediate actions required to address environmental issues posed by waste generation and the growing interest in the circular economy, anaerobic digestion (AD) offers a promising solution. As a major component of waste‐to‐energy, AD plays a dual role by processing waste and generating renewable energy at the same time, thus contributing to the success of closed‐loop systems. However, the success of AD as a business remains uncertain due to the high costs of material handling. Through a systematic literature review (SLR), this study reveals AD‐specific key barriers in feedstock exchanges and typical strategies applied to address them. The dual role of AD and the involvement of different stakeholders in the upstream processes further complicate these challenges, thus necessitating a more holistic approach to strategy formulation—an aspect not fully covered in the current literature. These gaps present opportunities to theorise the unique operations of AD businesses and the dynamics of multi‐stakeholders in complex feedstock supply processes. This study integrates resource management theories and duality theory, proposing a theoretical framework to enhance the sustainability and circularity of AD ventures. The proposed framework views AD from a resource‐oriented perspective and thus reinforces its pivotal role in fostering a truly closed‐loop system within the circular economy.This work was supported by DTA Future SocietiesBusiness Strategy and the Environmen
Numerical predictions of Low-Reynolds-Number propeller aeroacoustics: comparison of methods at different fidelity levels
Get PDFThis article belongs to the Special Issue New Developments in Aeroacoustics Research: From Fundamentals to ApplicationsLow-Reynolds-number propeller systems have been widely used in aeronautical applications, such as unmanned aerial vehicles (UAV) and electric propulsion systems. However, the aerodynamic sound of the propeller systems is often significant and can lead to aircraft noise problems. Therefore, effective predictions of propeller noise are important for designing aircraft, and the different phases in aircraft design require specific prediction approaches. This paper aimed to perform a comparison study on numerical methods at different fidelity levels for predicting the aerodynamic noise of low-Reynolds-number propellers. The Ffowcs-Williams and Hawkings (FWH), Hanson, and Gutin methods were assessed as, respectively, high-, medium-, and low-fidelity noise models. And a coarse-grid large eddy simulation was performed to model the propeller aerodynamics and to inform the three noise models. A popular propeller configuration, which has been used in previous experimental and numerical studies on propeller noise, was employed. This configuration consisted of a two-bladed propeller mounted on a cylindrical nacelle. The propeller had a diameter of D=9″ and a pitch-to-diameter ratio of P/D=1, and was operated in a forward-flight condition with a chord-based Reynolds number of Re=4.8×104, a tip Mach number of M=0.231, and an advance ratio of J=0.485. The results were validated against existing experimental measurements. The propeller flow was characterized by significant tip vortices, weak separation over the leading edges of the blade suction sides, and small-scale vortical structures from the blade trailing edges. The far-field noise was characterized by tonal noise, as well as broadband noise. The mechanism of the noise generation and propagation were clarified. The capacities of the three noise modeling methods for predicting such propeller noise were evaluated and compared.This research was funded by Innovate UK, Aerospace Technology Institute (ATI), UK grant number 10003388Aerospac