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Unlocking the potential of teff for sustainable, gluten-free diets and unravelling its production challenges to address global food and nutrition security: a review
Get PDFSustainable diets, as defined by the Food and Agriculture Organisation, aim to be nutritionally adequate, safe, and healthy, while optimising natural and human resources. Teff (Eragrostis tef), a gluten-free grain primarily grown in Ethiopia, has emerged as a key contender in this context. Widely regarded as a “supergrain”, teff offers an outstanding nutrition profile, making it an excellent choice for people with gluten-related disorders. Rich with protein, essential amino acids, polyunsaturated fats, and fibre, and abundant in minerals like calcium and iron, teff rivals other popular grains like quinoa and durum wheat in promoting human health. Beyond its nutritional benefits, teff is a hardy crop that thrives in diverse climates, tolerating both drought and waterlogged conditions. Due to its resilience and rich nutrient content, teff holds the potential to address nine of the 17 United Nations’ Sustainable Development Goals (SDGs), including SDG 1 (no poverty), SDG 2 (zero hunger), and SDG 3 (good health and wellbeing), which are tied to improving food and nutrition security. However, teff production in Ethiopia faces significant issues. Traditional farming practices, insufficient storage infrastructure, and food safety challenges, including adulteration, hinder teff’s full potential. This review explores teff’s dual role as a nutritious, sustainable food source and outlines the key challenges in its production to conclude on what needs to be done for its adoption as a golden crop to address global food and nutrition security.This work was funded by NutriNuts (Innovate UK—Agritech 8, 2019–2023) and EWA-BELT (Horizon 2020, 862848).Food
Dynamic UAV flight simulator utilizing a Stewart platform
Get PDFThis paper focuses on replicating the motion profile of a UAV flying in different conditions on a Stewart platform testbed. The resulting system provides a safe platform to operate indoors reproducing the same signals to those of a UAV flying outdoors. This approach results in more frequent use of all flying abilities while retaining high safety standards. To illustrate the effectiveness of the testbed, experimental results are presented. Six linear actuators are used in the testbed to achieve the desired orientation and position. The desired length of each actuator is calculated via an inverse kinematics algorithm. To validate the algorithm, Inertial Measurement Unit (IMU) data from three aerial platforms of different configurations/size are used. The IMU data captured from flying/hovering the aerial platforms indoors, with and without disturbance, is pre-processed using Fast Fourier Transform (FFT) and used as an input to the Stewart platform.UK Research and Innovation2024 7th Iberian Robotics Conference (ROBOT
Integrating an incident dataset with a question and answering language model to assist hazard identification: comparison of an extractive and generative model
Get PDFRobust hazard identification (HAZID) relies upon extensive knowledge of the system being analysed, the technical aspects, and how it will be used operationally. Typically, this knowledge is held by human participants who can draw out answers in natural language to hazard related questions based upon their own experience. However, several threats exist to this, such as high staff turnover, a poor learning from incidents capability or even insufficient Information Technology resources. Alternatively, incident databases hold vast amounts of hazard information that can be transformed into a source of knowledge. As mitigation to the aforementioned issues, this paper presents a Question and Answering (Q&A) Bidirectional Encoder Representations from Transformers (BERT) language model trained upon aviation incidents and a unique Q&A dataset. The model can extract answers to typical HAZID questions, based upon factual incident reports. Alongside this extractive approach, the paper also explores the use of a generative Large Language Model combined with an incident dataset. Both models proved a useful addition to HAZID activities based upon the Structured What If Technique (SWIFT), answering safety-themed questions based upon a retrieved context of incident reports that semantically matched the query. For the purposes of HAZID, it was suggested that the generative option is preferable based upon its ease of implementation, lower resource requirements and quality of responses. Additionally, it is shown that it is possible for organisations to train and create their own custom models for HAZID purposes. Future work may wish to consider the application of models that can hypothesize scenarios based upon incident reports, building further understanding to the relationships between causes, hazards and consequences.Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliabilit
Cooperative tracking strategies for optical space-to-space surveillance constellations
Get PDFMost space surveillance and tracking systems are constituted by networks of ground stations of observing radars and
optical telescopes. These systems are usually reliable, easily serviceable, and effective under ideal conditions, but suffer
from strong bounds on scalability and coverage due to the heavy constraints on their geographic locations, potential cloud
coverage and the perturbing effect of the atmosphere. A large constellation of small satellites carrying optical telescopes
could complement these limitations, thanks to the lack of such constraints and the possibility of observing target objects
at close range. As a result, it would be theoretically possible to track objects more accurately and for longer times,
improving the accuracy of collision risk analysis and manoeuvre detection amid other tasks. However, due to the small
fields of view of suitable onboard optical sensors, a random static arrangement of their lines of sight would be largely
inefficient in reaching good performance levels, as the target would unpredictably enter and exit the observable portion
of the sky. To solve this problem, we propose a cooperative intelligent tracking strategy for the constellation. Assuming
known initial states for some targets, we use predictions on the future states to dynamically control the attitudes of
the constellation satellites to maximise the length of the tracking window while minimising energy expenditures. We
evaluate the performance of the strategy using quality figures such as the number of effectively trackable targets and the
mean square error of the estimation error during tracking. We repeat the analysis for various constellation geometries and
multiple target orbits to investigate the general applicability of such a strategy. In conclusion, we check for robustness by
analysing performance drops under the loss of operating nodes. The results thus obtained will inform on the usefulness
of space-to-space SST constellations and the general design of strategies for the dynamic scheduling of operations of
distributed systems observing multiple targets.75th International Astronautical Congress (IAC
The use of ammonia recovered from wastewater as a zero-carbon energy vector to decarbonise heat, power and transport – a review
Get PDFAmmonia (NH3) is an energy vector with an emerging role in decarbonising heat, power and transport through its direct use as a fuel, or indirectly as a hydrogen carrier. Global ammonia production is having to grow to enable the exploitation of NH3 for energy decarbonisation, which it is projected will consume >50 % of manufacturing capacity by 2050. Ammonia recovered from wastewater can be directly exploited as a sustainable source of ammonia, to reduce the demand for ammonia produced through the energy intensive Haber-Bosch process, while fostering a triple carbon benefit to the water sector, by: (i) avoiding the energy required for aeration of biological processes; (ii) reducing nitrous oxide emissions associated with ammonia oxidation, which is a potent greenhouse gas; and (iii) producing a zero-carbon energy source that can decarbonise energy use. While previous reviews have described technologies relevant for ammonia recovery, to produce ammonia as a zero-carbon fuel or hydrogen carrier, wastewater ammonia must be transformed into the relevant concentration, phase and achieve the product quality demanded for zero carbon heat, power and transport applications, which are distinct from those demanded for more conventional exploitation routes (e.g. agricultural). This review therefore presents a synthesis of established and emerging technologies for the extraction and concentration of ammonia from wastewater, with specific emphasis on enabling the production of ammonia in a form that can be directly exploited for zero carbon energy generation. A précis of technologies for the valorisation of ammonia as a clean energy or hydrogen resource is also introduced, together with discussion of their relevancy and applicability to the water sector including implications to energy, carbon emissions and financial return. The exploitation of ammonia recovered from wastewater as a zero carbon energy source is shown to offer a critical contemporary response for the water sector that seeks to rapidly decarbonise existing infrastructure, while responding to ever stricter nitrogen discharge limits.Engineering and Physical Sciences Research CouncilWe are grateful for the financial and technical support offered by Anglian Water, Northumbrian Water and Severn Trent Water. We also acknowledge the funding and training resources provided by the Engineering and Physical Sciences Research Council through the WIRe Centre for Doctoral Training (EP/S023666/1) and STREAM Industrial Doctorate Centre (EP/L015412/1).Water Researc
Implementation of a federated laboratories network for testing formation flying technologies
Get PDFFormations of microsatellites are a highly attractive solution for achieving responsive space missions focused on Earth observation and communication support, due to their low cost and mass. However, operating these formations is challenging and requires extensive testing, which can be difficult to carry out due to the need for multiple platforms and large testing spaces. This paper presents the first concept and the first steps of a research program funded by NATO in the framework of the Science for Peace and Security program, with the specific purpose to develop and evaluate the necessary infrastructure for establishing a virtual, multi-platform distributed laboratory network comprised of laboratories from Sapienza, Lulea and Cranfield Universties. The value of this network will be increased by sharing resources, equipment, and expertise among the participating laboratories.This research was funded by the NATO Science for Peace and Security Programme under Grant No. MYP.G614175th International Astronautical Congress (IAC 2024
A prognostic approach to improve system reliability for aircraft system
Get PDFThe primary aims of prognostics encompass the timely detection of potential failures, mitigation or elimination of unscheduled maintenance, prediction of the most suitable timing for preventive maintenance replacement, optimization of maintenance cycles and operational readiness, and enhancement of system reliability by improving design and logistical support for existing systems. In order to facilitate the progress of these approaches, currently available datasets provide a unique and reliable compilation of flight-to-failure trajectories linked to small aircraft engines that have been observed in actual flight conditions. Furthermore, the paper offered an improved neural network that utilized the TanH hyperbolic tangent function. This neural network was enhanced later by integrating it with the TanH, linear, and Gaussian functions. Additionally, a random holdback validation approach was employed in the paper. The results suggest that the NN TanH technique, when implemented, has the potential to significantly enhance the reliability of an aircraft component. This is achieved through accurate estimates of the remaining useful life (RUL) and a proactive understanding of the failure system.European Commission: Grant Number 9556817th International Conference on System Reliability and Safety (ICSRS
Autonomous detect and avoid algorithm respecting airborne right of way rules
Get PDFRobust conflict resolution systems are crucial for BVLOS (beyond visual line of sight) operations of UAVs (Unmanned Aerial Vehicles) in the unsegregated airspace. The present conflict resolution research focus is skewed towards optimal path planning, often ignoring the airborne Right-of-way rules prescribed by the FAA and CAA. Although this approach might result in the most optimal path to resolve the conflict, it can cause confusion among other airspace users if the rules of the air are not obeyed when operating in the vicinity of other aircraft. In the present work, a real-time model predictive control approach is proposed that heavily prioritizes adherence to the prescribed right-of-way rules of the air. The maneuvering limitations of the involved aircraft are also taken into account. Several conflict scenarios were simulated, and the results show that the developed algorithm could resolve all conflicts.AIAA SCITECH 2024 Foru
Enhancing aircraft safety through advanced engine health monitoring with long short-term memory
Get PDFPredictive maintenance holds a crucial role in various industries such as the automotive, aviation and factory automation industries when it comes to expensive engine upkeep. Predicting engine maintenance intervals is vital for devising effective business management strategies, enhancing occupational safety and optimising efficiency. To achieve predictive maintenance, engine sensor data are harnessed to assess the wear and tear of engines. In this research, a Long Short-Term Memory (LSTM) architecture was employed to forecast the remaining lifespan of aircraft engines. The LSTM model was evaluated using the NASA Turbofan Engine Corruption Simulation dataset and its performance was benchmarked against alternative methodologies. The results of these applications demonstrated exceptional outcomes, with the LSTM model achieving the highest classification accuracy at 98.916% and the lowest mean average absolute error at 1.284%.Sensor
Qualitative investigation of wake composition in offshore wind turbines: a combined computational and statistical analysis of inner and outer blade sections
Get PDFHigh-fidelity numerical simulations are used to thoroughly analyze the evolution of the wake behind a megawatt-scale offshore wind turbine. The wake features are classified in terms of wake dynamics composition and the associated turbulence characteristics originating from the inner and outer sections of the blades. Understanding the wake is essential for developing compact layouts for future wind farms. We employed a transient Sliding Mesh Interface (SMI) technique to analyze the fully dynamic wake evolution of the offshore NREL 5MW full turbine. Our high-fidelity results have been validated against previously published results in the literature. We thoroughly investigated the dominant structures of the wake using Proper Orthogonal Decomposition (POD) techniques, which we applied to transient simulations of fully developed flows after five wind turbine revolutions over the snapshot data. Our findings show that the inner section of the blades, which is composed of airfoils with larger cross-sections, is responsible for the dominant components of the wake, while the contribution of the wake from the outer section of the blade is significantly lower. Therefore, designing more aerodynamic sections for the blade’s inner section can help reduce the dominant wake components and thus decrease the inter-turbine distance in future wind farms.2023 7th International Conference on Renewable Energy and Environmen