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Testing a hypothesis of technology transfer in the 1100’s between Italy and Denmark
Get PDFA one-hundred-year-old hypothesis regarding the transfer of the brick building technology from Lombardy to Denmark by the mid-1100’s has been tested. Two churches in Denmark and two in Italy have been re-examined by their architectural traits. 305 brick samples have been analysed by TL-dating, magnetic susceptibility, TL-sensitivity, XRD, FTIR, XRF, LA-ICP-MS, and spectrophotometric colour measurements. Mortar samples have been analysed by Py-GC-MS and thin section examination allowed a comparison of the manufacturing technologies. The scarce historical references on the transfer theory have been re-examined in perspective of the archaeometric evidence. Although not decisive by themselves one by one, collectively our results point to a rejection of the direct transfer hypothesis. Considering the results of the present investigation it seems more likely that the diffusion of knowledge about brick building technology followed a more convoluted path from the Cistercian communities in Lombardy towards Denmark with stops underway, likely in Germany.The AP Møller Foundation (grant number 211170) and the Augustinus Foundation (grant number 20-0761) are sincerely thanked for supporting this project.npj Heritage Scienc
Integrated sensing and communication for UAV beamforming: antenna sesign for tracking applications
Get PDFUnmanned Aerial Vehicles (UAVs) are promising nodes for Integrated Sensing and Communication (ISAC), but accurate Direction-of-Arrival (DoA) estimation on a small airframe is challenged by platform loading, motion, attitude, and multipath. Traditionally, DoA algorithms have been developed and evaluated for stationary, ground-based (or otherwise mechanically stable) antenna arrays. Extending them to UAVs violates these assumptions. This work designs a six-element Uniform Circular Array (UCA) at 2.4 GHz (radius ≈0.5λ) for a quadrotor and introduces a Pose-Aware MUSIC (MUltiple SIgnal Classification) estimator for DoA. The novelty is a MUSIC formulation that (i) applies pose correction using the drone’s instantaneous roll–pitch–yaw (pose correction) and (ii) applies a Doppler correction that accounts for platform velocity. Performance is assessed using data synthesized from embedded-element patterns obtained by electromagnetic characterization of the installed array, with additional channel/hardware effects modeled in post-processing (Rician LOS/NLOS mixing, mutual coupling, per-element gain/phase errors, and element–position jitter). Results with the six-element UCA show that pose and Doppler compensation preserve high-resolution DoA estimates and reduce bias under realistic flight and platform conditions while also revealing how coupling and jitter set practical error floors. The contribution is a practical PA-MUSIC approach for UAV ISAC, combining UCA design with motion-aware signal processing, and an evaluation that quantifies accuracy and offers clear guidance for calibration and field deployment in GNSS-denied scenarios. The results show that, across 0–25 dB SNR, the proposed hybrid DoA estimator achieves <0.5∘ RMSE in azimuth and elevation for ideal conditions and ≈5∘–6∘ RMSE when full platform coupling is considered, demonstrating robust performance for UAV ISAC tracking.Vehicle
Influence of thermal contrast and limitations of a deep-learning based estimation of early-stage tumour parameters in different breast shapes using simulated passive and dynamic thermography
Get PDFTo enhance diagnostic sensitivity compared to passive thermography, thermal stress can be applied to the breast surface with the temperatures being measured in the thermal recovery phase, a process called dynamic thermography. This study aims to evaluate the limitations of both passive and dynamic thermography in estimating early-stage tumour parameters across different breast shapes and how to improve the results. Three breast models with thermoregulation were solved numerically using COMSOL Multiphysics®. A neural network developed in PyTorch was used to estimate breast tumour location and size. The estimates obtained using each approach were compared, and the effects of thermal contrast, noise, and tumour depth range were analysed. Dynamic thermography provided the most accurate estimates compared to passive thermography, with mean error reductions that reached up to 33.25%. Additionally, the number of estimates with errors higher than 10% was up to 48.42% lower. Tumour radius showed the lowest noise threshold, providing the highest estimations errors. Adding deeper tumours to the datasets caused mean error increases of up to 51.27%. Thus, this work contributes by comparing both types of thermography, analysing thermal aspects of the temperature data that influences the neural network's estimation process, and suggesting alternatives to improve its accuracy.This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) - Finance Code 001. H.F. is grateful for the support provided by the Conselho Nacional de Desenvolvimento Científico e Tecnológico - Brazil (CNPq) - Finance Code 312530/2023-4.Thermal Science and Engineering Progres
Enhancing quadrotor resilience in outdoor operations with real-time wind gust measurement by using LiDAR
Get PDFUnmanned Aerial Vehicles (UAVs) encounter wind gusts during outdoor operations, impacting their position holding, particularly for quadrotors. This vulnerability is amplified during the autonomous docking to outdoor charging stations. The integration of real-time wind preview information for UAV gust rejection control has become more feasible with advances in remote wind sensor technologies like LiDAR. In this study, a ground-based LiDAR system is proposed to predict wind gusts at the landing site of quadrotors. The acquired wind preview data are subsequently utilized by the Model Predictive Control (MPC) to effectively mitigate disturbances. To validate the proposed methodology, a nonlinear simulation environment has been established using LiDAR data collected from comprehensive field tests. The results demonstrate a notable improvement in the system performance compared to benchmark results. This research underscores the practical utility of real-time wind preview information, facilitated by LiDAR technology, in enhancing the overall operational resilience of UAVs, especially quadrotors, during challenging environmental conditions.Unmanned System
Resilience to climate change by biocontrol yeasts against Ochratoxin A production in Robusta coffee
Get PDFAspergillus carbonarius is the main producer of Ochratoxin A (OTA) in coffee. In the last few years, there has been an increasing interest in using yeast isolates as Biocontrol Agents to prevent OTA production in coffee cherries during the primary postharvest processing. Little is known about how climate change abiotic conditions of increased temperature (+2–4 °C), elevated CO2 (existing levels of 400 vs. 1000 ppm), and increased drought stress will impact biocontrol resilience. This study examined the effect of a three-way interaction between temperature (27, 30, and 33 °C) x water activity (aw) (0.90 and 0.95 aw) x CO2 level (400 vs. 1000 ppm) on the growth and OTA production of A. carbonarius and the resilience of three yeast strains’ biocontrol capacity on fresh coffee cherries. High aw (0.95), CO2, and temperature levels increased the production of OTA by A. carbonarius. All the yeast biocontrol strains significantly reduced A. carbonarius growth by at least 20% and OTA production by up to 85%. From the three strains used, the Meyerozyma caribbica strain (Y4) showed the best resilience to climate change, since it reduced both growth (50%) and OTA production (70%) under future scenarios of CO2 and aw at all temperatures tested, and should be the one selected for pilot scale experiments in Ivory Coast.Centre de Coopération Internationale en Recherche Agronomique pour le DéveloppementThe research was supported by a grant from Agropolis Fondation (ref 1800-0022) and the financial support of Cranfield University.Toxin
Putting numbers to a metaphor: a Bayesian Belief Network with which to infer soil quality and health
Get PDFSoil Quality or Soil Health are terms adopted by the scientific community as metaphors for the effects of differing land management practices on the properties and functions of soil. Because they are metaphors, consistent quantitative definitions are lacking. We present here an approach based on expert elicitation in the field of soil function and management that offers a universal way of putting numbers to the metaphor. Like humans, soils differ and so do the ways in which they are understood to become unhealthy. Long-term experiments such as the Broadbalk Wheat experiment at Rothamsted provide unparalled sources of data with which to investigate the state and changes of soil quality and health that have developed from known management over timescales of one hundred years or more. Similarly, large-scale datasets such as the National Soils Inventory and Countryside Survey provide rich resources to explore the geographical variability of soil quality and health in different places against a background of different observed management practices. We structure experts’ views of the extent to which soil delivers the functions expected of it within Bayesian Belief Networks anchored by measurable properties of soil. With these networks, we infer the likely state of soil (i) on Broadbalk, (ii) at locations throughout England & Wales as well as inferring (iii) the most straightforward ways of improving soil quality and health at the locations in (ii). Our methodology has general applicability and could be deployed elsewhere or in other disciplines.This research was funded from the Soil Security Programme grant no NE/P014313/1. APW, LCT, RC and JAH were also part supported by BBSRC responsive mode grant and BB/J000671/1.European Journal of Agronom
Aerodynamics of high-bypass-ratio aeroengine nacelles: numerical and experimental investigation
Get PDFThis work presents a numerical and experimental investigation of the nacelle aerodynamics for high-bypass- ratio aeroengines. A conventional nacelle that is representative of a current standard, and a compact design that is envisaged for future aeroengines, were optimized with an existing computational method. Both nacelles were tested in a large-scale transonic wind tunnel. For the first time, the aerodynamic benefits of compact nacelles are demonstrated through an experimental test campaign. Measurements and computational fluid dynamics (CFD) simulations confirmed the drag reduction of compact configurations across a wide range of operating points with different flight Mach numbers, mass-flow capture ratios, and angles of attack. For midcruise conditions with a Mach number of 0.85, this was a drag reduction of 8.5% and 8.8% for the measurements and CFD, respectively. These benefits are similar to an isolated optimization, that is, not installed in the wind tunnel, which confirmed the capabilities of the method to identify the drag benefit of compact designs. Relative to the measurements, the main aerodynamic characteristics on the nacelles were captured by CFD in terms of isentropic Mach number distributions and shock location. This work provides a quantitative evaluation for the use of CFD within an industrial setting for nacelle design and analysis.This project has received funding from the Clean Sky 2 Joint Undertaking (JU) under Grant Agreement Number 101007598. The JU receives support from the European Union’s Horizon 2020 research and innovation program and the Clean Sky 2 JU members other than the Union.Journal of Aircraf
A complete reinforcement learning based framework for reconfigurable manufacturing system scheduling
Get PDFEmmanouilidis, Christos - Associate SupervisorSince the last decade of the 20th century, a new kind of manufacturing system
paradigm known as the reconfigurable manufacturing system (RMS) has been
emerging. The purpose of an RMS is to offer a balanced solution that can
swiftly respond to volatile global markets with fluctuating product demand. It
achieves this by combining the high throughput of conventional dedicated
manufacturing lines (DMLs) with the flexibility of flexible manufacturing systems
(FMSs). To instigate the market uncertainty, RMS possesses six core
characteristics, namely modularity, integrability, convertibility, scalability,
diagnosability, and customisation. These core characteristics are becoming
more available with the development of Industry 4.0 technologies. Simulation on
digital twins is one of the compelling approach that help RMSs check their
status in real time. However, the extended data flow challenges the traditional
rule-based scheduling policies and urges a flexible approach to replace ill-suited
approaches, then further reveals the potential of an RMS.
Reinforcement learning (RL) is a promising decision-making approach which
had already led to breakthroughs in a lot of research aspects including game
playing, robotics, finance, and autonomous driving. With a monolithic parametric
reward function, RL agents addressed a wide range of complex tasks by
integrating information from real manufacturing processes. Simulating complex
and changeable production systems, like RMS, is an area where RL principles
may be applied.
An end-to-end deep reinforcement learning framework was developed in this
research. The resulting policy is trained to generate a sequence of consecutive
actions that can be used as an RMS schedule to manage a fluctuating market
simulator in real-time.PhD in Manufacturin
Value-based planning for capability evolution
Get PDFRiaz, Atif - Associate SupervisorSystems such as military equipment can be viewed as capability components
constituting capability systems alongside others (e.g., interoperating systems,
personnel, etc.). Capability systems are developed to perform the tasks of their
acquirer organisation and realise the capabilities identified in the organisation’s
capability planning. Also, they are continuously engineered for the capabilities’
evolution.
In this time-dependent context, individual systems need to sustain their value to
the acquirer. Their design ought to be better aligned with the overarching
capability development. Two challenges were identified regarding this goal:
1. Evaluation of design alternatives based on their contribution to the
organisational capability, corresponding to the top-level organisational
task. It should account for the organisation’s priorities concerning different
capability areas.
2. Exploration of design evolution alternatives considering the long planning
horizons, expecting future changes and uncertainties regarding the
capability needs and the system’s context (e.g., adversaries, environment,
etc.).
To address them, a novel framework was developed. It incorporates:
• Value-based evaluation of design alternatives.
It is founded on a value metric formally defined to represent the contribution to
the organisational capability. Two methods were developed to estimate the
“value”: The first method determines task importance reflecting the acquirer’s
needs. The second method estimates the achieved capability levels by identifying
the trade-off relationships of factors regarding the system design and context.
• Scenario planning method.
It allows to model different futures using codified change trajectories of needs
and contextual factors. By calculating value trajectories of the evolving system
alternatives for the scenarios, what-if analysis to aid decisions is made possible.
• A consistent domain ontology underpinning the framework.
It defines and relates concepts from relevant industrial domains.
The proposed framework and methods were tested and evaluated with
representative test cases. Evaluation by industrial practitioners was also
performed. The results showed the framework’s usefulness and relevance to
real-world practices.PhD in Aerospac
Role of solute chemistry on membrane crystallisation of inorganic salts
No full textMembrane distillation crystallisation (MDCr) is a process developed to recover
valuable salts from salt-rich solutions like sea water, brackish water, waste and others
for the promotion of zero liquid discharge (ZLD). The chemistry of the crystallised salts
is characterised by their different crystal-liquid interfacial energy derived from their
solubility. Various studies have evidenced the importance of the interfacial energy in
the nucleation process through Gibbs energy but it has never previously used to
determine the scaling, nucleation and crystal growth kinetics of membrane distillation
crystallisation. Using a combination of a backscatter technique and digital microscopy
to detect bulk and scaling induction, this work provides a precise determination of
scaling and bulk induction and metastable zone width (MSZW), resulting into a critical
differentiation of heterogeneous adhesive growth for low interfacial energy salt and
homogeneous bulk deposition for high interfacial energy growth. After understanding
that the membrane is not playing as much role as previously thought in MDCr for high
interfacial energy salts, another crucial component of the chemistry of the salt and its
solubility, is the solubility–temperature dependence. It was found that even in low
interfacial energy salts, the dominant factor of scaling is temperature polarisation and
not heterogeneous nucleation as previously assumed. To confirm the less critical role
of the membrane in MDCr, three membranes comprised of distinctive properties were
compare through the use of a neutral solubility–temperature dependent salt. The
results demonstrate how both scaling and crystal growth are kinetically controlled
rather than thermodynamically dependent upon the material properties to initiate
nucleation. To enhance the dependency of the membrane for nucleation within a
kinetically controlled environment, K₂SO₄ was studied which exhibits a sharp positive
solubility–temperature dependency. The modification of the solubility limit due to
temperature polarisation, modifies the thermodynamic barrier of the MSZW which
increase scaling, the extent of which is evidenced to directly inform the nucleation
kinetics within the bulk solution. This thesis collectively describes and relates solute
chemistry to both scaling and nucleation, enabling enhanced crystallisation strategies
to be developed for MDC.PhD in Water, including Desig