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Discussion: Embracing microfluidics to advance environmental science and technology
Get PDFMicrofluidics, also called lab-on-a-chip, represents an emerging research platform that permits more precise and manipulation of samples at the microscale or even down to the nanoscale (nanofluidic) including picoliter droplets, microparticles, and microbes within miniaturized and highly integrated devices. This groundbreaking technology has made significant strides across multiple disciplines by providing an unprecedented view of physical, chemical, and biological events, fostering a holistic and an in-depth understanding of complex systems. The application of microfluidics to address the challenges in environmental science is likely to contribute to our better understanding, however, it's not yet fully developed. To raise researchers' interest, this discussion first delineates the valuable and underutilized environmental applications of microfluidic technology, ranging from environmental surveillance to acting as microreactors for investigating interfacial dynamic processes, and facilitating high-throughput bioassays. We highlight, with examples, how rationally designed microfluidic devices lead to new insights into the advancement of environmental science and technology. We then critically review the key challenges that hinder the practical adoption of microfluidic technologies. Specifically, we discuss the extent to which microfluidics accurately reflect realistic environmental scenarios, outline the areas to be improved, and propose strategies to overcome bottlenecks that impede the broad application of microfluidics. We also envision new opportunities and future research directions, aiming to provide guidelines for the broader utilization of microfluidics in environmental studies.Science of The Total Environmen
Developing a human-centric de-icing system to increase airport capacity and operational safety
Get PDFhttps://ergonomics.org.uk/events-calendar/ehf2024.htmlThis research paper presents an innovative automated de-icing system designed to enhance operational efficiency, safety, and environmental sustainability at airports during cold weather conditions. Traditional manual de-icing methods, which are labour intensive and pose significant safety risks and environmental concerns, are inefficient and costly. The proposed system incorporates human-centric design principles and advanced automation technologies, including predictive modelling and real-time data analytics, to facilitate safer and more efficient de-icing operations with reduced physical labour and improved aircraft turnaround times. Drawing upon interviews with Bucharest International Airport subject matter experts, the research identified key operational, safety, and environmental challenges in current de-icing processes in order to provide relevant human-centric design requirements. Subsequent system development focused on minimizing human error and physical strain, streamlining equipment preparation, and reducing environmental impact through sustainable practices. The research underscores the need for further empirical testing to validate the system's effectiveness in real-world settings, offering a significant step forward in achieving safer, more efficient, and environmentally responsible airport de-icing operations.Ergonomics & Human Factors 202
Convex–concave optimization for a launch vehicle ascent trajectory with chance constraints
Get PDFThe objective of this paper is to present a convex–concave optimization approach for solving the problem of a multistage launch vehicle ascent trajectory. The proposed method combines convex–concave decomposition and successive linearization techniques to generate a new sequence of convex subproblems to replace the original non-convex problem. Bernstein approximation is used to transform the chance constraints into convex ones. A hp-adaptive pseudospectral scheme is employed to discretize the optimal control problem into a nonlinear programming problem with less computation cost. The performance of the proposed strategy is compared against other typical techniques in a selection of test case scenarios. Numerical results demonstrate the viability of the method and show pros and cons of the proposed technique.Journal of the Franklin Institut
Techno-economic viability of bio-based methyl ethyl ketone production from sugarcane using integrated fermentative and chemo-catalytic approach: process integration using pinch technology
Get PDFButanediols are versatile platform chemicals that can be transformed into a spectrum of valuable products. This study examines the techno-commercial feasibility of an integrated biorefinery for fermentative production of 2,3-butanediol (BDO) from sucrose of sugarcane (SC), followed by chemo-catalytic upgrading of BDO to a carbon-conservative derivative, methyl ethyl ketone (MEK), with established commercial demand. The techno-economics of three process configurations are compared for downstream MEK separation from water and co-product, isobutyraldehyde (IBA): (I) heterogeneous azeotropic distillation of MEK-water and extractive separation of (II) MEK and (III) MEK-IBA from water using p-xylene as a solvent. The thermal efficiency of these manufacturing processes is further improved using pinch technology. The implementation of pinch technology reduces 8% of BDO and 9–10% of MEK production costs. Despite these improvements, raw material and utility costs remain substantial. The capital expenditure is notably higher for MEK production from SC than BDO alone due to additional processing steps. The extraction based MEK separation is the simplest process configuration despite marginally higher capital requirements and utility consumption with slightly higher production costs than MEK-water azeotropic distillation. Economic analysis suggests that bio-based BDO is cost-competitive with its petrochemical counterpart, with a minimum gross unitary selling price of US$ 1.54, assuming a 15% internal rate of return over five-year payback periods. However, renewable MEK is approximately 16–24% costlier than the petrochemical route. Future strategies must focus on reducing feedstock costs, improving BDO fermentation efficacy, and developing a low-cost downstream separation process to make renewable MEK commercially viable.Chemical Engineering Journa
An enabling architecture for computational cost efficiency in predictive maintenance digital twins
Get PDFAs digital twins emerge to provide a replication of physical assets in the digital space, the application of predictive maintenance of industrial asset becomes more effective. Developing digital twins for the predictive maintenance case study leverages Internet of Things, cloud computing and machine learning. While these technologies extend the necessary tools for deploying predictive maintenance digital twins, an enabling architecture facilitated by fog computing positions predictive maintenance digital twins for improved computational cost and latency than centralizing in the cloud or running locally at the edge. This work presents the application of a distributed digital framework, showing the benefits of better compute utilization and latency by adopting a distributed digital twin framework for predictive maintenance of wind turbine components in a wind farm.This work acknowledges support from the Petroleum Technology Development Fund (PTDF), Nigeria, and Cranfield University’s Digital Aviation Research & Technology Center (DARTEC), UK.2024 International Conference on Cyber-Physical Social Intelligence (ICCSI
Uncovering reward goals in distributed drone swarms using physics-informed multiagent inverse reinforcement learning
Get PDFThe cooperative nature of drone swarms poses risks in the smooth operation of services and the security of national facilities. The control objective of the swarm is, in most cases, occluded due to the complex behaviors observed in each drone. It is paramount to understand which is the control objective of the swarm, whilst understanding better how they communicate with each other to achieve the desired task. To solve these issues, this article proposes a physics-informed multiagent inverse reinforcement learning (PI-MAIRL) that: 1) infers the control objective function or reward function from observational data and 2) uncover the network topology by exploiting a physics-informed model of the dynamics of each drone. The combined contribution enables to understand better the behavior of the swarm, whilst enabling the inference of its objective for experience inference and imitation learning. A physically uncoupled swarm scenario is considered in this study. The incorporation of the physics-informed element allows to obtain an algorithm that is computationally more efficient than model-free IRL algorithms. Convergence of the proposed approach is verified using Lyapunov recursions on a global Riccati equation. Simulation studies are carried out to show the benefits and challenges of the approach.IEEE Transactions on Cybernetic
Advanced mobility flight dynamics restriction to support high availability communication systems
Get PDFElectric Vertical Take-Off and Landing (eVTOL) platforms play a crucial role in Advanced Air Mobility (AAM) initiatives, particularly in urban environments. Ensuring the safety and reliability of communication networks during air traffic operations is paramount, with communication performance heavily reliant on antenna radiation characteristics. Maintaining consistent communication throughout the entire flight is essential for flight success. However, dynamic maneuvers such as banking turns can result in airframe shadowing, where the vehicle's structure obstructs antenna signals, posing a challenge to communication reliability. This paper proposes a model integrated into eVTOL avionics to mitigate airframe shadowing issues and maintain optimal communication availability during normal flight operations. A new algorithm is proposed, and simulation studies analysis are conducted to assess the impact of airframe shadowing on eVTOL communication performance. Additionally, insights are provided to air traffic management (ATM) and pilots regarding optimal look angles to minimize or avoid airframe shadowing effects.Engineering and Physical Sciences Research CouncilThis work partially supported by 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
An empirical method for modelling the secondary shock from high explosives in the far-field
Get PDFAs the detonation product cloud from a high explosive detonation expands, an arresting flow is generated at the interface between these products and the surrounding air. Eventually this flow forms an inward-travelling shock wave which coalesces at the origin and reflects outwards as a secondary shock. Whilst this feature is well known and often reported, there remains no established method for predicting the form and magnitude of the secondary shock. This paper details an empirical superposition method for modelling the secondary shock, based on the physical analogy of the secondary loading pulse resembling the blast load from a smaller explosive relative to the original. This so-called dummy charge mass is determined from 58 experimental tests using PE4, PE8, and PE10, utilising Monte Carlo sampling to account for experimental uncertainty, and is found to range between 3.2–4.9% of the original charge mass. A further 18 “unseen” datapoints are used to rigorously assess the performance of the new model, and it is found that reductions in mean absolute error of up to 40%, and typically 20%, are achieved compared to the standard model which neglects the secondary shock. Accuracy of the model is demonstrated across a comprehensive range of far-field scaled distances, giving a high degree of confidence in the new empirical method for modelling the secondary shock from high explosives.Shock Wave
Unmanned air vehicle operational framework for public safety communications
Get PDFThe aviation and air mobility sector are experiencing a profound evolution, fuelled by swift technological progress and escalating requirements for effective, secure, and dependable airborne communication frameworks. The integration of Unmanned Aerial Systems (UAS), such as drones, into commercial and logistical activities is revolutionizing traditional concepts of air mobility. Integrating the Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) protocol into UAS communication networks enhances safety and reliability by preventing collisions. CSMA/CA allows UAS to sense the communication medium's availability before transmitting data, minimizing the risk of collisions and ensuring efficient data transmission, cru-cial for scenarios where safety is paramount. Sixth-Generation (6G) technology coupled with CSMA/CA protocol integration strengthens reliability and effectiveness in ensuring safe and efficient UAS operations. Simulation analysis using MATLAB helps understand signal quality and latency variations with distance from the UAV to the receiver, essential for safety communications analysis. Analyzing handover procedures is crucial for public safety, especially in scenarios where UAS encounter situations requiring a change from one base transceiver station (BTS) to another. Vertical handovers, particularly relevant in the context of evolving Unmanned Traffic Management (UTM) and Air Traffic Management (ATM) architectures, may become more prevalent due to the significant altitude variations inherent in UAS operations.Engineering and Physical Sciences Research CouncilThis research partially funded by the UKRI DSIT/EPSRC project CHEDDAR - Communications Hub for Empowering Distributed Cloud Computing Applications and Research under grants EP/X040518/1 and EP/Y037421/1.2024 AIAA DATC/IEEE 43rd Digital Avionics Systems Conference (DASC
An overview on oxidation of metallic interconnects in solid oxide fuel cells under various atmospheres
Get PDFThis study explores the emergence of oxidation-resistant alloys as potential replacements for traditional ceramics in Solid Oxide Fuel Cells (SOFCs), specifically Ferritic Stainless Steel (FFS). Despite its promise, FFS encounters challenges such as oxidation and corrosion. Most research on FFS interconnect damage has primarily focused on high-temperature oxidation in single atmospheres. However, in practice, the interconnect is exposed to both oxidizing and reducing atmospheres concurrently, leading to enhanced oxidation known as the dual atmosphere effect. The significance of this phenomenon is increasingly recognized by researchers and industry experts, yet understanding its implications for FFS degradation and protective measures remains a young discipline. This article provides an overview of the oxidation mechanisms of FSS under various conditions, proposed mechanisms, and potential protective strategies to address the effects of the dual atmosphere.China Scholarship CouncilThis research was supported by the Centre for Energy Engineering at Cranfield University (UK). Thanks to the China Scholarship Council (CSC, China) for the financial support.International Journal of Hydrogen Energ