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Structural sizing and mass estimation of transport aircraft wings with distributed, hydrogen, and electric propulsions
Get PDFCurrent literature offers limited mass estimation methodologies and their application in the conceptual or preliminary design stages of moderate to high aspect ratio wings with electric, hydrogen or distributed propulsions. This study presents the development and application of a quasi-analytical wing mass estimation method to address this limitation. The proposed method is distinguished from the existing mass estimation methods by its expanded realistic load cases, sensitivity to several design parameters, improved accuracy with short computational time and capabilities for future applications. To achieve these features, new geometric models are introduced; 483 load cases including symmetric manoeuvre, rolling, and combined cases are covered following airworthiness requirements; the structural elements are idealised and sized with strength and buckling criteria; existing methods are evaluated and integrated cautiously for secondary structures and non-optimum masses. A computation time of 0.1s is accomplished for one load case. The developed method achieved the highest accuracy with an average error of -2.2% and a standard error of 1.8% for wing mass estimates compared with six existing methods, benchmarked against thirteen wings of different aircraft categories. The effects of engine numbers with dual- to 16-engine setups and the dry wing concepts on the wing mass are investigated. The optimised number of engines and their locations decreased the wing mass of the high aspect ratio wing significantly. In contrast, the dry wing design increased the wing masses of all baseline aircraft. The future applications and improvements of the presented method in novel configurations and multidisciplinary designed optimisation studies are explained.The Aeronautical Journa
Take-off performance of a single engine battery-electric aeroplane
Get PDFThis paper investigates the take-off performance of a single engine battery-electric aeroplane, using the example of the 300kg Sherwood eKub. It shows analysis of take-off performance of such an aeroplane must include as a minimum two new parameters not normally considered: time at full throttle and state of charge. It was shown in both ground and flight test that the state of available power reduces both as the throttle is fully open, and as battery charge is consumed, although recovers partially when power is reduced for a period. It is possible to schedule take-off performance as a function of the usual parameters plus state of charge. Because of the reducing climb performance with use of state of charge, and the requirement in airworthiness standards for minimum climb performance being available, it becomes necessary to introduce the concept of minimum-indicated state of charge for take-off, SoCiMTO; means to calculate that are shown for compliance with both microlight aeroplane standards and larger aeroplane standards, and the calculations are demonstrated for the eKub. Conclusions are also drawn about the use of commercial products SkyDemon and Google Earth for recording and analysing aeroplane performance data.The Aeronautical Journa
On a journey to citywide inclusive sanitation (CWIS)? A political economy analysis of container-based sanitation (CBS) in the fragmented (in)formal city
Get PDFRapidly growing cities face the chronic challenge of access to safe, dignified and accessible sanitation, in contexts of inequality and informality. Technological and operational innovations, such as container-based sanitation (CBS), are promoted as relatively low-cost market-based circular economy off-grid solutions to deliver citywide inclusive sanitation (CWIS). However, in the absence of evidence that CBS is delivering on these promises, this paper asks: under what conditions can CBS services contribute to achieving CWIS goals? It applies a combined political economy and socio-technical regime analysis to examine multi-level governance in the sanitation sector and CBS service regimes in Cape Town, Lima, Nairobi and Cap-Haitien. Only Cape Town, a municipality-controlled system, demonstrates the necessary public authority that enables CBS to operate at scale. Yet, it is regarded by many residents in informal settlements as poor sanitation for poor people. This suggests that scaling CBS requires sustained public investment and strong coordinating authority.The Francis Crick Institute, UK Research and InnovationThe research work is supported by UK Research and Innovation’s Global Challenges Research Fund (GCRF), grant number (ES/T007877/1).Globalization
A causal learning approach to in-orbit inertial parameter estimation for multi-payload deployers
Get PDFThis paper discusses an approach to inertial parameter estimation for the case of cargo carrying spacecraft that is based on causal learning, i.e. learning from the responses of the spacecraft, under actuation. Different spacecraft configurations
(inertial parameter sets) are simulated under different actuation profiles, in order to produce an optimised
time-series clustering classifier that can be used to distinguish between them. The actuation is comprised of finite sequences of constant inputs that are applied in order, based on typical actuators available. By learning from the system’s responses across multiple input sequences, and then applying measures of time-series similarity and F1-score, an optimal actuation sequence can be chosen either for one specific system configuration or for the overall set of possible
configurations. This allows for both estimation of the inertial parameter set without any prior knowledge of state, as well as validation of transitions between different configurations after a deployment event. The optimisation of the actuation sequence is handled by a reinforcement learning model that uses the proximal policy optimisation (PPO) algorithm, by
repeatedly trying different sequences and evaluating the impact on classifier performance according to a multi-objective metric.75th International Astronautical Congress (IAC 2024
A COLREGs compliance reinforcement learning approach for USV manoeuvring in track-following and collision avoidance problems
Get PDFThe development of new technologies for autonomous platforms has allowed their integration into sea mine countermeasures. This has allowed to remove the personnel from the potential danger by having the mine search task performed by an unmanned surface vessel (USV). Traditional intelligent systems are built by agglomerating hand-coded behaviours that determine how a good manoeuvre looks like. This induces cognitive bias into the pre-defined behaviours that can violate safety and regulatory rules imposed by the COLREGs. To alleviate this issue, this paper proposes a COLREGs compliant reinforcement learning (RL) approach that gives a solution for the autonomous navigation of USVs. A custom simulation environment is developed. The RL agents are trained to deal with path-following problem with obstacle avoidance capabilities. A custom reward function is defined to consider the turning disks for the agent's decision process. A smoothing decision feature is used to smooth the transitions between consecutive actions. The results demonstrate good convergence and high performance under different scenarios. The collision avoidance with COLREGs compliances shows the effectiveness of the proposed approach under several scenarios with static and moving obstacles.Ocean Engineerin
Editorial: Fundamental and practical advances in bioremediation of emerging pollutants as add-on treatments for polluted waters
Get PDFEditorial on the Research Topic:
Fundamental and practical advances in bioremediation of emerging pollutants as add-on treatments for polluted watersFrontiers in Microbiolog
Position uncertainty reduction in visualInertial navigation systems using multi-ML error compensation
Get PDFIn the absence of signals from global navigation satellite systems (GNSS), visual-inertial navigation systems (VINS) are usually utilized in urban air mobility (UAM) applications which require reliable navigation in complex urban areas. This paper focuses on improving vision-based alternatives to GNSS navigation solutions with position uncertainty correction for safe and uninterrupted flights. The novel contribution introduces multiple machine-learning aided hybrid visual-inertial odometry (multi-ML hybrid VIO) that utilizes gated recurrent unit (GRU) based error compensators to enhance positioning within complex environments by reducing the impacts of various sources of uncertainty. Unlike state-of-the-art systems that lack evidence of demonstrating performance enhancement with position uncertainty correction within VIO architectures, the proposed framework simultaneously reduces position uncertainty and improves accuracy. Furthermore, training and testing datasets are generated using MATLAB incorporating unreal engine simulation environment for UAVs to replicate complex scenarios including environmental conditions, illumination variations, weather effects and flight dynamics where traditional VIO systems tend to fail. The proposed hybrid VIO architecture has been validated under combinations of complex scenarios including various sources of uncertainty such as sensor noise, feature tracking error, environmental dynamics, weather effects and lighting conditions for extended flights. The comparison results have demonstrated reduction in horizontal positioning RMSE errors: 1.7m for VIO with VO error compensation 2.18m for VIO with KF error compensation, 1.4m for multi-ML hybrid VIO. Furthermore, it demonstrates generalization ability over seen and unseen fault scenarios that indicates performance improvement of 89% in 3D position compared to VIO with VO error compensation, VIO with KF error compensation, and ESKF-based VIO. Additionally, experimental results demonstrate overall horizontal position uncertainty reduction by 79% for test 1 and 22% for test 2. Finally, this work represents a step forward in improving the safety and effectiveness of UAV navigation by providing vision-based alternative to GNSS solution for uninterrupted flights.37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024
Significant effect of salinity on zinc adsorption on tropical coastal and floodplain soils
Get PDFRising sea levels due to climate change are causing increased salinisation of low‐lying coastal and floodplain soils, and the impact of this process on the bioavailability of plant nutrients needs to be understood as mitigation strategies are adapted. Zinc (Zn) is an element of particular importance due to its function as a micronutrient for plants including rice and other staple foods. In the current study, our aim was to investigate the effects of salinisation on zinc adsorption onto soils representing at‐risk coastal and floodplain environments, addressing in particular our knowledge gap concerning the roles that solution chemistry and soil composition play. To this end, we conducted batch adsorption experiments in the laboratory and ran geochemical models in saline solutions up to 0.7 mol L−1 ion strength incorporating both (i) a multi surface model (MSM) for surface reactions containing three phases, that is iron hydroxides, organic matter and phyllosilicate clays, and (ii) aqueous‐phase complexation to dissolved organic and inorganic ligands. Surface reactions were modelled using the diffuse double layer model, the NICA–Donnan model and an ion exchange model using the Gaines–Thomas convention. We combined the experimentally determined mass composition of surface phases with generic modelling parameters taken from the literature. We first show that increasing salinity enhances the formation of aqueous Zn‐chloride complexes in the presence of dissolved organic matter and bicarbonate, thereby decreasing the availability of free Zn2+ and supressing the partitioning of zinc to the adsorbed phase. We demonstrate using batch adsorption experiments with a calcareous hydraquent and a tropaquept, that salinity decreases zinc adsorption strongly in the pH range between 3 and 6. Satisfactory agreement between experiments and model calculations was achieved with root‐mean‐square errors ranging for different salinities between 2.88% and 2.92% for the hydraquent and between 4.59% and 2.74% for the tropaquept soil. Model predictions of adsorption were slightly inferior at low salinity for the hydraquent soil and at high salinity for the tropaquept soil, pointing possibly to an incomplete geochemical model or to a need to parametrise surface adsorption models at higher ionic strengths. Present surface models have been largely parametrised at lower ionic strength. We lastly apply the MSM to examine zinc adsorption in five endoaquepts soils, representing soil series from Bangladesh. We show that increasing salinity decreases zinc adsorption to the soil organic matter and the clay fractions. We conclude from our findings that increased soil salinity due to rising sea levels and climate change will have a significant impact on zinc cycling and possibly other micronutrients in areas where coastal soils and floodplain soils overlap, such as deltas and estuaries. In particular, we predict a decrease in zinc adsorption in acidic to neutral soils. The availability of zinc for biouptake through the roots of crop plants including rice will be significantly disturbed following salinisation, most likely affecting crop production. Our study demonstrates the potential that geochemical modelling combined with experimental data has to improve our capability to assess the effects of salinity due to rising seawater levels in vulnerable regions of the world.Islamic Development BankWe thank the Islamic Development Bank for financial support for Md Hanif.European Journal of Soil Scienc
In situ nanoconfinement catalysis for highly efficient redox transformation
Get PDFThe rapid reduction of Cr(VI) across a wide pH range, from acidic to alkaline pH conditions to stable Cr(III) species for efficient remediation of Cr(VI) pollution, has long been a challenge. Herein, we propose a new concept of in situ nanoconfinement catalysis (iNCC) for highly efficient remediation of Cr(VI) by growing nanosheets of in situ layered double hydroxide (iLDH) on the surface of Al-Mg-Fe alloy achieving chemical reduction rates of >99% in 1 min from pH 3 to 11 for 100 mg L-1 Cr(VI) with a rate constant of 201 h-1. In stark contrast, the reduction rate is less than 6% in 12 h with a rate constant of 0.77 h-1 for the pristine Al-Mg-Fe alloy. The ultrafast reduction of Cr(VI) is most likely attributed to the synergistic catalysis of Al12Mg17 and Al13Fe4 and nanoconfinement of MgAlFe-iLDH and superstable mineralization of Cr(III) by MgAlCrIII- and MgFeCrIII-iLDHs. This study demonstrates the potential of in situ nanoconfinement catalysis on redox transformation for environmental remediation.ACS Applied Materials and Interface
A numerical approach to overcome the very-low Reynolds number limitation of the artificial compressibility for incompressible flows
Get PDFWe propose a numerical approach to solve a long-standing challenge which is the applicability of the artificial compressibility (AC) formulation for solving the incompressible Navier—Stokes equations at very-low Reynolds numbers. A wide range of engineering applications involves very-low Reynolds number flows in Micro-ElectroMechanical Systems (MEMS) and in the fields of chemical-, agricultural- and biomedical engineering. It is known that the already existing numerical methods using the AC approach fail to provide physically correct results at very-low Reynolds numbers (Re ≤ 1). To overcome the limitation of the AC method for these engineering applications, we propose a higher-order Neumann-type pressure outflow boundary condition treatment along with their up to fourth-order numerical approximations. We found that the numerical treatment of the pressure at the outlet boundary plays the main role in overcoming the limitation of the AC method at very-low Reynolds numbers (Re << 1). Therefore, we provide numerical evidence on the accuracy of the AC method beyond its previously reported limitations, e.g., the low Reynolds number Oseen flow (Re << 1) is first presented in this work. A third-order explicit total-variation diminishing (TVD) Runge–Kutta scheme has been employed with standard finite difference spatial discretisation schemes for improving the accuracy of the numerical solution. For modelling strongly viscous flows, the Reynolds number ranges from 10-1 to 10-4. Overall, we found that the accuracy limitation of the AC method below Re < 1 can be overcome with an accurate numerical treatment of the outlet pressure boundary condition instead of using high-order schemes in the governing equations. For the investigated Reynolds number range (10-1 ≤ Re ≤ 10-4 ), the obtained results show that the relative errors were smaller than 1% for the numerical simulations performed on the configurations of both the two- and three-dimensional, straight microfluidic channels. The imposition of high-order derivative Neumann-type pressure outflow boundary conditions reduced the maximum relative errors of the numerical solutions from 85% and 95% to below than 1% at the outlet section of the two- and three-dimensional, straight microfluidic channel flows, respectively. Taking the advantage of the numerical approach proposed here, two- and three-dimensional benchmark problems employed in the current investigation in comparison with analytical solutions available in the literature, clearly demonstrate that the artificial compressibility can be used beyond its previously known constraints for very-low Reynolds number incompressible flows.The present research work was financially supported by the Centre for Propulsion and Thermal Power Engineering and the Cranfield Air and Space Propulsion Institute (CASPI) at Cranfield University, UK under the project code EDA3126Z, in collaboration with Pangea Aerospace, Spain.Heliyo