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Evidence of collaborative opportunities to ensure long-term sustainability in African farming
Get PDFFarmers face the challenge of increasing production to feed a growing population and support livelihoods, whilst also improving the sustainability and resilience of cropping systems. Understanding the key factors that influence farming management practices is crucial for determining farmers' adaptive capacity and willingness to engage in cooperative strategies. To that end, we investigated management practices that farmers adopt and the factors underlying farmers' decision-making. We also aimed to identify the constraints that impede the adoption of strategies perceived to increase farming resilience and to explore how the acceleration of technology adoption through cooperation could ensure the long-term sustainability of farming. Surveys were distributed to farming stakeholders and professionals who worked across the contrasting environments of Morocco. We used descriptive statistics and analysis by log-linear modelling to predict the importance of factors influencing farmers’ decision-making. The results show that influencing factors tended to cluster around environmental pressures, crop characteristics and water availability with social drivers playing a lesser role. Subsidies were also found to be an important factor in decision-making. Farming stakeholders generally believed that collaborative networks are likely to facilitate the adoption of sustainable agricultural practices. We conclude that farmers need both economic incentives and technical support to enhance their adaptive capacity as this can lessen the socioeconomic vulnerability inherent in arid and semi-arid regions.Journal of Cleaner Productio
A review of predictive techniques used to support decision making for maintenance operations of wind turbines
Get PDFThe analysis of reliable studies helps to identify the credibility, scope, and limitations of various techniques for condition monitoring of a wind turbine (WT) system’s design and development to reduce the operation and maintenance (O&M) costs of the WT. In this study, recent advancements in data-driven models for condition monitoring and predictive maintenance of wind turbines’ critical components (e.g., bearing, gearbox, generator, blade pitch) are reviewed. We categorize these models according to data-driven procedures, such as data descriptions, data pre-processing, feature extraction and selection, model selection (classification, regression), validation, and decision making. Our findings after reviewing extensive relevant articles suggest that (a) SCADA (supervisory control and data acquisition) data are widely used as they are available at low cost and are extremely practical (due to the 10 min averaging time), but their use is in some sense nonspecific. (b) Unstructured data and pre-processing remain a significant challenge and consume a significant time of whole machine learning model development. (c) The trade-off between the complexity of the vibration analysis and the applicability of the results deserves further development, especially with regards to drivetrain faults. (d) Most of the proposed techniques focus on gearbox and bearings, and there is a need to apply these models to other wind turbine components. We explain these findings in detail and conclude with a discussion of the main areas for future work in this domain.Energie
Reward inference of discrete-time expert's controllers: A complementary learning approach
No full textUncovering the reward function of optimal controllers is crucial to determine the desired performance that an expert wants to inject to a certain dynamical system. In this paper, a reward inference algorithm of discrete-time expert's controllers is proposed. The approach is inspired by the complementary mechanisms of the striatum, neocortex, and hippocampus for decision making and experience transference. These systems work together to infer the reward function associated to expert's controller using the complementary merits of data-driven and online learning methods. The proposed approach models the neocortex system as two independent learning algorithms given by a Q-learning algorithm and a gradient identification rule. The hippocampus is modelled by a least-squares update rule that extracts the relation from the states and control inputs of the expert's data. The striatum is modelled by an inverse optimal control algorithm which iteratively finds the hidden reward function. Lyapunov stability theory is used to show the stability and convergence of the proposed approach. Simulation studies are given to demonstrate the effectiveness of the proposed complementary learning algorithm.Information Science
Multi-impact response of CR4 mild steel: Characterising the transition from absorption to failure
Get PDFSingle impact perforation shots are well understood for various target materials and different shaped projectiles. Although considered a rare case, localised multi-impacts are not well understood as they involve both perforating and non-perforating impacts on the target. The lack of understanding of non-perforating impact on metallic materials makes it tough to predict the change in the material’s mechanical performance. Given the widespread use of metallic materials for protective applications, it is important to understand the material response when subject to multiple impacts. To determine the effect of a non-perforating shot on CR4 mild steel and establish a minimum energy impact that will define the transition point whereby the metal can no longer absorb energy a series of impact experiments were conducted. Results show a subsequent perforation event occurs at a lower than the experimentally determined perforation velocity. Results suggest that there could be a direct correlation between the material thickness and the critical crater depth (the depth of crater required to affect the materials ability to absorb energy, the measure of materials performance). As the crater depth increased from 3mm to 8.5mm for the first shot, the energy absorption of the steel plate reduced by 25%. This allowed the residual performance for CR4 mild steel to be quantified for a known impact crater, giving a 7% performance loss for every millimetre the critical crater depth grows beyond 3mm until the point of failure.Engineering Research Expres
Optimal skin simulant for ballistic testing
Get PDFAn extensive literature review, combined with practical experience of forensic testing, has identified several concerns regarding existing studies into skin simulants. These can be summarized as arising due to human skin being a highly complex, multi-layered and anisotropic material whose mechanical properties depend on many factors such as age and gender of the host. In many studies (and papers) essential information is missing. Although there is some parallelism between the studies, the reported energy density at perforation is very inconsistent (a function of the natural variation of skin properties alluded to above) and differs from 0,113 J/mm2 [1] to 0,239 J/mm2 [2]. Which is, in fact, a more than 100% variation. Such a variation is arguably insufficient to enable accurate replication with a single simulant material. Combined with the missing common agreement about the energy density threshold between countries, laboratories and researchers, this analysis clearly identifies the need for an adjustable and / or customizable skin simulant. To-date, the most often used simulation material for human skin in ballistic testing is ‘Chrome crusted cow hide’ [3]. However, this is a natural material and, consequently therefore, inevitably physically variable in nature – both inter and intra hide. Ballistic tests on 10 chrome crusted cow hides using 4,5 mm BB’s gave v50% ranging from 113 m/s to 200 m/s, an uncontrolled variability for forensic experiments. Hence, the authors examined a skin analogue that could be produced in-house, enabling tailoring to match the desired properties, and with improved consistency. To this end, a thin, 4 mm thick, layer of gelatine (30 – 45 weight %, increasing per 1 weight %) was studied. The ballistic resistance of the gelatine skin analogue was compared to the v50%’s published values in literature, with good agreement found as the gelatine concentration was varied. In comparison to the chrome crusted cow hides this suggests that this relatively simple and accessible approach has potential to provide a more consistent standard.Forensic Science Internationa
Contributions of CH4-amine interactions by primary, secondary, and tertiary amines on CO2/CH4 separation efficiency
Get PDFIn designing amine-incorporated adsorbents for CO2/CH4 separation, it is essential to understand the individual effects amine moieties have on the separation of CO2/CH4 mixtures. In this work, primary, secondary, and tertiary amines are moderately grafted on SBA-15 to examine factors affecting adsorption of CO2 and CH4. Materials were characterised by thermogravimetric and elemental analysis, and their performance was measured by volumetric and gravimetric gas adsorption. An amine density of 1.6–1.7 mmol/g in secondary and tertiary amines showed an equivalent CH4 uptake of <0.04 mmol/g at 25 °C, while primary amines adsorbed 0.05 mmol/g, indicating stronger interaction forces with CH4. In terms of selectivity, primary and secondary amines grafted at 1.3–1.4 mmol/g had similar values, unaffected by amine type. Adsorption results cross analysed with DFT simulations indicate similar binding energies for CH4 by both amine moieties, concluding the facilitated access of gas molecules to primary amine moieties is the primary factor dictating degree of adsorption. At an amine density of ∼ 1.7 mmol/g for both primary and secondary amines, an increase in temperature from 25 to 40 °C at a CO2 partial pressure of 40 kPa showed a decrease in CO2/CH4 selectivity of only primary amines. Secondary amines are thus more selective amine moieties at these conditions. Furthermore, in isothermal adsorption–desorption conditions, moderately grafted secondary amines have an equal working capacity to primary amines. Both these qualities support secondary amines at moderate densities as candidates for adsorbent development in CO2/CH4 separations.Chemical Engineering Journa
New insights into method development and characterization of amorphous silica from wheat straw
Get PDFAmorphous silica, a specialised silicate adsorbent is extensively extracted from agricultural residues for application in various environmental domains. Wheat straws are a rich source of silica that have earlier been overlooked however demand for value addition. The study presents an innovative approach to extracting silica from wheat straw and standardising the extraction process to produce clean product. The sodium silicate solution and the amorphous silica synthesis were obtained by modifying the template mediated sol–gel method. Optimum temperature, concentration and pH were identified for the cleaner production of silica with maximum yield and favourable adsorbent characteristics. The crystallographic properties analysed by the X-Ray Diffraction revealed the amorphous nature of silica extracted from ash at 650 °C for 4 h. The structure of phytolith present in the wheat straw was observed in the form of articulated elongate undulate epidermal phytolith under scanning electron microscopy. The Energy Dispersive X-ray spectrum exhibited higher amount of silica (Si %) of 70.10% with a minimal percentage of potassium (9.96%). The sharp bend at 1025 cm−1 is attributed to the siloxane (Si–O-Si) vibrations in Fourier transform infrared spectroscopic graph of amorphous silica. The specific surface area measurements of amorphous silica showed type II isotherm curve with a hysteresis of H3 type. The optimum conditions derived to produce amorphous silica were 3 M NaOH and 3 M H2SO4 at pH 9.Silico
Accuracy assessment of surveying strategies for the characterization of microtopographic features that influence surface water flooding
Get PDFWith the increase in rainfall intensity, population, and urbanised areas, surface water flooding (SWF) is an increasing concern impacting properties, businesses, and human lives. Previous studies have shown that microtopography significantly influences flow paths, flow direction, and velocity, impacting flood extent and depth, particularly for the shallow flow associated with urban SWF. This study compares two survey strategies commonly used by flood practitioners, S1 (using Unmanned Aerial Systems-based RGB data) and S2 (using manned aircraft with LiDAR scanners), to develop guidelines on where to use each strategy to better characterise microtopography for a range of flood features. The difference between S1 and S2 in elevation and their accuracies were assessed using both traditional and robust statistical measures. The results showed that the difference in elevation between S1 and S2 varies between 11 cm and 37 cm on different land use and microtopographic flood features. Similarly, the accuracy of S1 ranges between 3 cm and 70 cm, and the accuracy of S2 ranges between 3.8 cm and 30.3 cm on different microtopographic flood features. Thus, this study suggests that the flood features of interest in any given flood study would be key to select the most suitable survey strategy. A decision framework was developed to inform data collection and integration of the two surveying strategies to better characterise microtopographic features. The findings from this study will help improve the microtopographic representation of flood features in flood models and, thus, increase the ability to identify high flood-risk prompt areas accurately. It would also help manage and maintain drainage assets, spatial planning of sustainable drainage systems, and property level flood resilience and insurance to better adapt to the effects of climate change. This study is another step towards standardising flood extent and impact surveying strategies.Engineering and Physical Sciences Research Council (EPSRC): EP/N010329/1.
Atkins GlobalRemote Sensin
Cooling of concentrated photovoltaic cells - a review and the perspective of pulsating flow cooling
Get PDFThis article presents a review to provide up-to-date research findings on concentrated photovoltaic (CPV) cooling, explore the key challenges and opportunities, and discuss the limitations. In addition, it provides a vision of a possible future trend and a glimpse of a promising novel approach to CPV cooling based on pulsating flow, in contrast to existing cooling methods. Non-concentrated photovoltaics (PV) have modest efficiency of up to around 20% because they utilise only a narrow spectrum of solar irradiation for electricity conversion. Therefore, recent advances employed multi-junction PV or CPV to widen the irradiation spectrum for conversion. CPV systems concentrate solar irradiation on the cell’s surface, producing high solar flux and temperature. The efficient cooling of CPV cells is critical to avoid thermal degradation and ensure optimal performance. Studies have shown that pulsating flow can enhance heat transfer in various engineering applications. The advantage of pulsating flow over steady flow is that it can create additional turbulence and mixing in the fluid, resulting in a higher heat transfer coefficient. Simulation results with experimental validation demonstrate the enhancement of this new cooling approach for future CPV systems. The use of pulsating flow in CPV cooling has shown promising results in improving heat transfer and reducing temperature gradients.Engineering and Physical Sciences Research Council (EPSRC): EP/T006315/1.
Petroleum Technology Development Fund, Nigeria.Energie
Aluminium foam-filled honeycomb crash absorbers
Get PDFHoneycomb structures are frequently used as energy absorption devices in the automotive and aerospace industry. Many studies have been conducted to optimise these structures and improve crashworthiness behaviour. This paper attempts to improve the crashworthiness behaviour of a honeycomb crash box by filling the cells with open-cell aluminium foams. Experimental tests were conducted to develop the honeycomb and aluminium foam material model and, also, to validate the finite element model by experimental data. Foam-filling the crash box allows the control of the densification zone for different impact energies using open-cell aluminium foam, which shows the main novelty of this research. In the end, the optimised structure is presented concerning the optimum number of foam-filled cells and, also, to the aluminium foam’s density that best fits this application.Materials Science Foru