20505 research outputs found
Sort by
Cradle-to-gate sustainability assessment of centralised versus decentralised additive manufacturing for wind turbine blade mould production
No full textAdditive Manufacturing (AM) has emerged as a transformative technology in the production of wind turbine blade moulds, enabling greater design flexibility, mass customisation, and on-demand responsiveness. This study presents a comparative environmental sustainability assessment of centralised and decentralised AM supply chains for wind turbine blade mould manufacturing across four European regions centred on Luxembourg. A cradle-to-gate Life Cycle Assessment (LCA) framework is employed to quantify carbon footprint (CFP) and water footprint (WFP) across the stages of raw material acquisition, manufacturing, and transportation. The turbine blade moulds are produced using two composite materials: ABS+20%CF and ABS+20%CF, both selected for their mechanical performance and printability in AM applications. Geospatial routing data obtained from third-party mapping and navigation platforms are utilised to estimate regional transport distances and routes, thereby enabling a spatially explicit evaluation of environmental trade-offs between centralised and decentralised supply chain configurations.13th CIRP Global Web ConferenceProcedia CIR
Dataset: Evaluating efficacy of organo-mineral fertiliser to meet nutrient demands of cereal crops in England
No full textThis research compares the effect of novel organo-mineral fertiliser and conventional mineral fertiliser on arable crop production and soil health in England.Innovate U
Rush dominance in wet pastures - spatial analysis, trajectories and drivers
No full textDorset Wildlife TrustLowland wet pastures are biodiversity-rich ecosystems but are increasingly threatened by the expansion of rush (Juncus spp.), which can dominate and displace species of conservation value. This study quantified the spatial extent, temporal dynamics, and key drivers of rush distribution in Kingcombe Meadows Reserve, Dorset, using high-resolution aerial imagery (2005, 2020) and deep learning methods. A pretrained U-Net convolutional neural network (CNN) was trained on randomly selected annotated image samples to produce reserve-wide rush maps, achieving overall accuracies above 91%. Bias-corrected area estimations showed that rush cover increased substantially over the study period, rising from 7.6% in 2005 to 20% in 2020, indicating both localised spread and establishment in previously unoccupied areas. Topographic analysis revealed that rush occurred predominantly at lower elevations (114-158 m) and on gentle slopes (less than 8 degrees), where hydrological conditions favour persistence. Current grazing pressures showed no significant relationship with rush distribution, suggesting that grazing alone could not explain recent expansion patterns in the reserve. This study demonstrates that CNN-based segmentation provides a powerful framework for fine-scale vegetation mapping and ecological assessment. The results highlight the need for integrated management strategies that combine grazing, hydrological, and topographic considerations to control rush encroachment effectively. More broadly, the approach offers a transferable tool for conservation practitioners and policymakers to monitor invasive or encroaching species in wet grasslands and other sensitive habitats, supporting evidence-based management and enhancing biodiversity conservation at a landscape scale.MK Soil Science Ltd (sponsorship)Dorset Wildlife Trust (operational support)MSc in Advanced GIS and Remote Sensin
Spine motion segment analogues: 3D printing, multiscale modelling and testing to produce more biofidelic examples
No full textThis article belongs to the Special Issue Recent Advances in 3D Printing Technologies in Bioengineering with Selected Papers from the 29th Congress of the European Society of Biomechanics (ESB 2024)Computed tomography and magnetic resonance imaging are two powerful modalities which can be used in the clinical setting to produce data for the creation of patient-specific finite element analysis (FEA) models and physical analogues—for instance, by using additive manufacturing (AM)—that mimic the properties of soft and hard tissues, both morphologically and mechanically. However, there remains a gap between creating a perfect biofidelic physical analogue and its computational counterpart. This gap exists because, firstly, in silico models are often too complex to realise, and secondly, real-life conditions are challenging to emulate both computationally and mechanically, as they involve multiscale situations that are inherently heterogeneous and patient specific. In this study, we applied a multi-scale approach to design and model porcine vertebral specimens. Our results identified critical design factors that affect the quality and accuracy of the models, specifically highlighting that scanning resolution/fidelity and the thresholding technique have a directly proportional impact on model accuracy. A small shift up and down the greyscale level by 20 units can affect the behaviour of the AM sample by as much as [−15% +47%]. Working up the levels for manufacturing, testing and modelling (i) cylindrical cores to (ii) whole vertebrae and then (iii) a whole spine motion segment, we observed that the fidelity of predictions reduces, and errors increase as the structure becomes more complicated and intricate (3.6%, 7.5% and 15%, respectively). We are confident that further material-level developments will provide solutions for the more intricate parts of spinal motion segments, such as the intervertebral discs and facets, which in their natural form are highly sophisticated structures. To the best of our knowledge, this is the first time a holistic multiscale approach has been implemented to produce AM biofidelic analogues of skeletal parts. Our data showed good agreement between the physical and in silico models, confirming that it is possible to model real-time objects and situations both physically and in silico. This ultimately will enable the development of accurate, patient-specific physical models for use in biomechanical testing and medicolegal applications.The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article from a CDS Cranfield University internal funding to C.F. and T.S. and funding to P.Z. from RCDM (Royal College for Defence Medicine), Birmingham (grant no.DMSRSG20130905).29th Congress of the European Society of Biomechanics (ESB 2024)Journal of Manufacturing and Materials Processin
Conceptual Design of Martian Aerial Robots
No full textThis thesis addresses the design and optimisation of rotary Vertical Take-Off and
Landing (VTOL) aerobots for Mars exploration. Current surface exploration
robots, such as rovers and landers, are constrained by their limited mobility in
accessing Mars’ diverse and rugged terrain. To overcome these challenges, this
research investigates the feasibility and performance of aerobots as a
complementary solution, building on NASA's Ingenuity Helicopter technology
demonstrator.
The research focuses on overcoming the engineering challenges posed by Mars'
thin atmosphere, low gravity, and extreme environmental conditions. A structured
framework is developed to systematically integrate environmental constraints and
mission-specific requirements into the aerobot design process. Central to the
study is the adaptation of helicopter momentum theory for Martian conditions,
providing a theoretical basis for estimating power consumption and rotorcraft
performance during key flight phases, including hover, vertical climb, and forward
flight. Following the theoretical groundwork, a parametric analysis evaluates
several rotorcraft configurations such as single-rotor, dual, quadcopter, and
hexacopter, focusing on power efficiency, lift capacity, and operational feasibility.
Among the configurations analysed, hexacopters demonstrate superior stability,
redundancy, and power efficiency, making them the most promising design for
Martian missions.
The research also develops practical design variants for the proposed aerobots,
addressing deployment challenges such as packaging within spacecraft
aeroshells through the implementation of foldable rotor systems. These
innovations ensure that the aerobots meet the spatial constraints of Mars
exploration missions while maximising performance. The findings from this
research provide a foundation for future Mars aerobot development, with
recommendations for further computational modelling and experimental
validation to enhance reliability in mission-critical applications.PhD in Aerospac
Sources, characterisation and exposure risk of airborne microplastic emissions from municipal solid waste dumping site in Nigeria
No full textWalton, Christopher - Associate SupervisorAirborne microplastics (AMPs) represent an emerging environmental and public health
challenge, with their sources, transport mechanisms, and impacts still poorly
understood, particularly in developing regions with inadequate waste management
systems. This research addresses three key gaps: the need for cost-effective and
efficient AMP sampling tools, the AMP flux estimations under different environmental
conditions, and the modelling of AMP dispersion to understand their transport and
potential exposure risks downwind.
This research tackles these challenges by developing a low-cost sampler for AMP
collection. The low-cost sampler was validated against the commercial sampler (SKC
Deployable Sampler equipped with a Total Suspended Particulate (TSP) head), with
a focus on fibres, fragments, and films across diverse environmental conditions. The
emission of AMPs was quantified using a modified Fick’s law, which incorporates sitespecific
parameters such as wind speed, temperature, and particle properties.
Seasonal variation in AMP emissions was analysed by collecting and processing 226
environmental samples (42 soil and 184 air) from the municipal solid waste disposal
site and its environment during dry and wet seasons. Dispersion modelling was
conducted using SCREEN3 to simulate the downwind transport of AMPs.
A low-cost sampler (LCS) was developed and evaluated against a commercial
sampler, demonstrating a strong correlation (ρ = 0.976) and high accuracy (94.12%)
compared to a reference sampler. The LCS effectively captured seasonal variations
in AMP abundance. Polymer analysis identified five predominant polymers, with nylon
(fibres), PVC (fragments), and PE (films) accounting for the majority of microplastics.
The cost analysis revealed that the LCS offers 61% savings over second-hand and
98% over new commercial samplers, making it a reliable and affordable tool for AMP
research in resource-limited settings.
The airborne microplastics measured on-site reveal seasonal variations in
concentrations. Notably, the dry season reveals higher concentrations (mean: 14.37 ±
3.87 MP/m³) comparable to the wet season (mean: 11.31 ± 3.00 MP/m³). Upwind
concentrations were considerably lower, averaging 4.25 ± 1.17 MP/m³ during the dry
season and 2.75 ± 1.43 MP/m³ during the wet season, reflecting contributions from
distant fibre-rich sources, likely indoor emissions. On-site, films exhibited the lowest
emissions but retained moderate mobility during the wet season. Fibres showed the
highest diffusion coefficients, indicating potential for long-range transport. Fragments
were the most abundant microplastic type (55% dry, 53% wet), with high emission
factors (188 µg/day dry, 170 µg/day wet). Rising velocities were higher during the dry
season due to favourable wind conditions, with values of 0.1056 m/s for nylon fibres,
0.0835 m/s for PVC fragments, and 0.0742 m/s for PE films. The rising velocities and
flux measurements highlighted the influence of soil porosity and wind speed on
resuspension and transport of microplastics.
The SCREEN3 dispersion model reveals distinct seasonal variations in the transport
of AMP from MSW sites. Peak AMP concentrations occurred at 100–107 m downwind,
with wet season levels (fibres: 2.28 × 10⁻² μg/m³, fragments: 6.81 × 10⁻² μg/m³, films:
2.41 × 10⁻³ μg/m³) exceeding dry season concentrations by 2.1–2.2 times. Fragments
posed the highest health risks (Level III), particularly during short-term exposures,
while fibres and films showed lower risks. SCREEN3 agreed well with ground
measurements (R2 = 0.98 to 0.96) and identified key drivers such as stability classes
and precipitation, affirming its utility for AMP transport modelling and risk assessment.
This study highlights the significant environmental and health implications of airborne
microplastic (AMP) emissions from municipal solid waste (MSW) sites. Fragments
pose the greatest risks, particularly during the wet season. The development of a lowcost
sampler and advanced dispersion modelling provides essential tools for AMP
monitoring. To mitigate AMP impacts, improved waste management practices, such
as minimising open burning, are necessary. Integrating AMP data into air quality
monitoring frameworks and prioritising seasonal mitigation measures are also
recommended. Future studies should investigate long-range transport mechanisms,
refine emission factor models, and chronic exposure risks to develop comprehensive
strategies for mitigating AMP impacts globally.PhD in Energy and Powe
Optimised Multi-Arm Robot Motion to Reduce Satellite Disturbances During In-Orbit Assembly
No full textThe increasing demand for large-scale space structures, such as modular telescopes and solar power stations, requires efficient and reliable In-Orbit Assembly (ISA) operations. Robotic systems play a central role in this process, but their locomotion can induce significant disturbances to the hosting spacecraft because of momentum conservation. These need to be actively compensated, at the expense of scarce and valuable fuel resources. This thesis investigates passive disturbance minimisation through optimised path planning for Cranfield’s Multi-Arm Robot for In-Orbit Operations (MARIO). A literature review identified key approaches to reaction-minimising motion planning, including real-time control, trajectory optimisation, and sampling-based planners. Based on this analysis, the Stochastic Trajectory Optimization for Motion Planning (STOMP) algorithm was implemented within ROS2 and MoveIt2, with a custom cost function penalising joint torques as an indicator of disturbance. The methodology was tested through high-fidelity Gazebo simulations of MARIO performing crawling locomotion on modular structures designed for laboratory experiments at Cranfield University’s ASTRA-Lab. Results demonstrated that mass distribution strongly influences disturbance magnitude, and that optimised trajectories can reduce disturbances by nearly 50% compared to linear baselines. However, issues such as inverse kinematics solver variability, limited repeatability, and collision risks limited practical applicability. The most promising results were obtained when combining Cartesian initial trajectories with STOMP optimisation, although the custom disturbance cost function proved less effective than anticipated. The findings highlight both the potential and challenges of trajectory optimisation for space robotics, offering insights into the coupling between manipulator motion and spacecraft dynamics. Future work should refine disturbance modelling cost functions, integrate hybrid planning approaches such as RRT* with STOMP, and extend validation to physical experiments with MARIO in the ASTRA-Lab. Overall, this research contributes to safer and more fuel-efficient in-orbit assembly operations, supporting the development of sustainable space infrastructure.MSc in Robotic
CFD Investigation on Tailplane Ice Protection System
No full textIn this study, the effectiveness of engine exhaust in shielding aircraft tailplanes from ice accretion a known aviation safety hazard is examined. Three sample aircraft which are Gulfstream G280, Airbus A320 and Airbus A380 were used to run Computational Fluid Dynamics (CFD) simulations, considering important parameters such exhaust temperature, plume dispersion, and flying phase. The A320 was evaluated in four operational conditions: take-off, cruise, runway roll, and taxiing. EASA Type Certificate Data Sheets were used to collect engine exhaust data in order to guarantee realistic boundary conditions. The results clearly show the differences between aircraft types. Since the engines of the A320 and A380 are situated beneath the wings, the exhaust plumes swiftly disperse beneath the tailplane, creating hardly any heating effect. Due to the absence of a tailplane ice prevention system (IPS), these aircraft would have been subject to weight and fuel penalties. The G280, on the other hand, which has engines situated on the rear fuselage, displayed some tailplane heating and plume impingement. An IPS is still necessary since this natural impact was insufficiently powerful at altitude. The distinction reflects aircraft philosophy: business jets place a higher priority on flexibility and safety margins, whereas high-volume airline aircraft are optimized for efficiency. Overall, the study confirms that exhaust heat alone cannot provide reliable ice protection. Instead, the findings point towards hybrid approaches where limited natural heating could be combined with technologies like electrothermal or bleed-air systems as a more practical way forward for future aircraft.MSc in Aerospace Vehicle Desig
USV pursuit–evasion using a complementary scientific machine learning with control barrier functions approach
No full textThe maritime pursuit–evasion problem is increasingly relevant to autonomous robotics and naval operations, particularly for security, surveillance, search and rescue, and environmental monitoring. Effective pursuit requires accurate evader behavior prediction combined with robust obstacle avoidance in cluttered maritime environments. Traditional methods, including differential game theory and heuristic planning, often neglect realistic complexities and provide limited safety guarantees. Recent reinforcement learning approaches improve flexibility but struggle with generalization and formal safety assurance in complex scenarios. To bridge this gap, we propose a novel integration of scientific machine learning with control barrier functions, enabling provably safe pursuit and navigation under realistic vessel dynamics, partial observability, and nonconvex obstacle constraints. Simulations validate ability of the proposed methods to achieve safe and effective pursuit in challenging maritime environments.This work was supported by the Engineering and Physical Sciences Research Council under Grant 220124IEEE Journal of Oceanic Engineerin
From complexity responses to enacted practice: mindfulness as a multi-level metacognitive capability in project leadership
No full textProject complexity research has established that structural, socio-political, and emergent complexities require different response capabilities, yet little is known about how project leaders enact these responses in practice. Drawing on practice theory and strategy-as-practice, this study examines how project leaders mobilise mindfulness as a multi-level metacognitive practice to address project complexity. We analyse qualitative data from a flagship UK government Project Leadership Programme, including open-ended survey responses (n = 58) and semi-structured interviews (n = 10) with senior project leaders. Our findings show that mindfulness is enacted at individual, team, and organisational levels to operationalise planning and control, relationship-building, and flexibility responses. Mindfulness functions both as relief, enabling leaders to regulate stress and reactivity, and as engagement, supporting sustained attention, psychologically safe dialogue, and adaptive sensemaking. We contribute to theory by extending project complexity research from identifying effective responses to explaining how response capabilities are enacted across organisational levels through socially embedded metacognitive practice. We contribute to practice by offering a scalable and context-sensitive repertoire of mindfulness practices that project leaders can embed in leadership development, governance routines, and team interactions to build sustained capability for navigating structural, socio-political, and emergent project complexity.International Journal of Project Managemen