8,204 research outputs found

    A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms

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    Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data. A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability. To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity. A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case. The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change. The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ā€˜problem of implementationā€™ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sectorā€™s emergence

    The determinants of value addition: a crtitical analysis of global software engineering industry in Sri Lanka

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    It was evident through the literature that the perceived value delivery of the global software engineering industry is low due to various facts. Therefore, this research concerns global software product companies in Sri Lanka to explore the software engineering methods and practices in increasing the value addition. The overall aim of the study is to identify the key determinants for value addition in the global software engineering industry and critically evaluate the impact of them for the software product companies to help maximise the value addition to ultimately assure the sustainability of the industry. An exploratory research approach was used initially since findings would emerge while the study unfolds. Mixed method was employed as the literature itself was inadequate to investigate the problem effectively to formulate the research framework. Twenty-three face-to-face online interviews were conducted with the subject matter experts covering all the disciplines from the targeted organisations which was combined with the literature findings as well as the outcomes of the market research outcomes conducted by both government and nongovernment institutes. Data from the interviews were analysed using NVivo 12. The findings of the existing literature were verified through the exploratory study and the outcomes were used to formulate the questionnaire for the public survey. 371 responses were considered after cleansing the total responses received for the data analysis through SPSS 21 with alpha level 0.05. Internal consistency test was done before the descriptive analysis. After assuring the reliability of the dataset, the correlation test, multiple regression test and analysis of variance (ANOVA) test were carried out to fulfil the requirements of meeting the research objectives. Five determinants for value addition were identified along with the key themes for each area. They are staffing, delivery process, use of tools, governance, and technology infrastructure. The cross-functional and self-organised teams built around the value streams, employing a properly interconnected software delivery process with the right governance in the delivery pipelines, selection of tools and providing the right infrastructure increases the value delivery. Moreover, the constraints for value addition are poor interconnection in the internal processes, rigid functional hierarchies, inaccurate selections and uses of tools, inflexible team arrangements and inadequate focus for the technology infrastructure. The findings add to the existing body of knowledge on increasing the value addition by employing effective processes, practices and tools and the impacts of inaccurate applications the same in the global software engineering industry

    Effectiveness of Lateral Auditory Collision Warnings: Should Warnings Be Toward Danger or Toward Safety?

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    Objective. The present study investigated the design of spatially oriented auditory collision warning signals to facilitate driversā€™ responses to potential collisions. Background. Prior studies on collision warnings have mostly focused on manual driving. It is necessary to examine the design of collision warnings for safe take-over actions in semi-autonomous driving. Method. In a video-based semi-autonomous driving scenario, participants responded to pedestrians walking across the road, with a warning tone presented in either the avoidance direction or the collision direction. The time interval between the warning tone and the potential collision was also manipulated. In Experiment 1, pedestrians always started walking from one side of the road to the other side. In Experiment 2, pedestrians appeared in the middle of the road and walked toward either side of the road. Results. In Experiment 1, drivers reacted to the pedestrian faster with collision-direction warnings than with avoidance-direction warnings. In Experiment 2, the difference between the two warning directions became non-significant. In both experiments, shorter time intervals to potential collisions resulted in faster reactions but did not influence the effect of warning direction. Conclusion. The collision-direction warnings were advantageous over the avoidance-direction warnings only when they occurred at the same lateral location as the pedestrian, indicating that this advantage was due to the capture of attention by the auditory warning signals. Application. The present results indicate that drivers would benefit most when warnings occur at the side of potential collision objects rather than the direction of a desirable action during semi-autonomous driving

    Predictive Maintenance of Critical Equipment for Floating Liquefied Natural Gas Liquefaction Process

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    Predictive Maintenance of Critical Equipment for Liquefied Natural Gas Liquefaction Process Meeting global energy demand is a massive challenge, especially with the quest of more affinity towards sustainable and cleaner energy. Natural gas is viewed as a bridge fuel to a renewable energy. LNG as a processed form of natural gas is the fastest growing and cleanest form of fossil fuel. Recently, the unprecedented increased in LNG demand, pushes its exploration and processing into offshore as Floating LNG (FLNG). The offshore topsides gas processes and liquefaction has been identified as one of the great challenges of FLNG. Maintaining topside liquefaction process asset such as gas turbine is critical to profitability and reliability, availability of the process facilities. With the setbacks of widely used reactive and preventive time-based maintenances approaches, to meet the optimal reliability and availability requirements of oil and gas operators, this thesis presents a framework driven by AI-based learning approaches for predictive maintenance. The framework is aimed at leveraging the value of condition-based maintenance to minimises the failures and downtimes of critical FLNG equipment (Aeroderivative gas turbine). In this study, gas turbine thermodynamics were introduced, as well as some factors affecting gas turbine modelling. Some important considerations whilst modelling gas turbine system such as modelling objectives, modelling methods, as well as approaches in modelling gas turbines were investigated. These give basis and mathematical background to develop a gas turbine simulated model. The behaviour of simple cycle HDGT was simulated using thermodynamic laws and operational data based on Rowen model. Simulink model is created using experimental data based on Rowenā€™s model, which is aimed at exploring transient behaviour of an industrial gas turbine. The results show the capability of Simulink model in capture nonlinear dynamics of the gas turbine system, although constraint to be applied for further condition monitoring studies, due to lack of some suitable relevant correlated features required by the model. AI-based models were found to perform well in predicting gas turbines failures. These capabilities were investigated by this thesis and validated using an experimental data obtained from gas turbine engine facility. The dynamic behaviours gas turbines changes when exposed to different varieties of fuel. A diagnostics-based AI models were developed to diagnose different gas turbine engineā€™s failures associated with exposure to various types of fuels. The capabilities of Principal Component Analysis (PCA) technique have been harnessed to reduce the dimensionality of the dataset and extract good features for the diagnostics model development. Signal processing-based (time-domain, frequency domain, time-frequency domain) techniques have also been used as feature extraction tools, and significantly added more correlations to the dataset and influences the prediction results obtained. Signal processing played a vital role in extracting good features for the diagnostic models when compared PCA. The overall results obtained from both PCA, and signal processing-based models demonstrated the capabilities of neural network-based models in predicting gas turbineā€™s failures. Further, deep learning-based LSTM model have been developed, which extract features from the time series dataset directly, and hence does not require any feature extraction tool. The LSTM model achieved the highest performance and prediction accuracy, compared to both PCA-based and signal processing-based the models. In summary, it is concluded from this thesis that despite some challenges related to gas turbines Simulink Model for not being integrated fully for gas turbine condition monitoring studies, yet data-driven models have proven strong potentials and excellent performances on gas turbineā€™s CBM diagnostics. The models developed in this thesis can be used for design and manufacturing purposes on gas turbines applied to FLNG, especially on condition monitoring and fault detection of gas turbines. The result obtained would provide valuable understanding and helpful guidance for researchers and practitioners to implement robust predictive maintenance models that will enhance the reliability and availability of FLNG critical equipment.Petroleum Technology Development Funds (PTDF) Nigeri

    Quantifying the Indirect Effect of Wolves on Aspen in Northern Yellowstone National Park: Evidence for a Trophic Cascade?

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    Yellowstone National Park is renowned for its incredible wildlife, and perhaps the most famous of these species is the gray wolf, which was reintroduced to the Park in the mid-1990s. After reintroduction, it was highly publicized by scientists, journalists, and environmentalists that the wolf both decreased elk density and changed elk behavior in a way that reduced elk effects on plants, a process known as a ā€œtrophic cascade.ā€ Aspen, which is eaten by elk in winter, is one species at the forefront of Yellowstone trophic cascade research because it has been in decline across the Park for over a century. However, due to the challenges of measuring trophic cascades, there is continued uncertainty regarding the effects of wolves on aspen in northern Yellowstone. Thus, the purpose of my dissertation was to provide a comprehensive test of a trophic cascade in this system. Specifically, I used 20 years of data on aspen, elk, and wolves in Yellowstone to: 1) clarify annual trends in browsing and height of young aspen (a proxy for regeneration) after wolf reintroduction, 2) assess the influence of wolves scaring elk on aspen (ā€œtrait-mediated indirect effectsā€), and 3) evaluate the effect of wolves killing elk on aspen (ā€œdensity-mediated indirect effectsā€). My research suggests that wolves indirectly contributed to increased aspen over story recruitment following their reintroduction by helping to reduce the elk population size, but elk response to the risk of wolf predation did not reduce elk foraging in a way that measurably increased aspen recruitment. Additionally, hunter harvest of elk north of the park was twice as important as wolf predation in causing increased aspen recruitment. However, despite wolves and hunters limiting elk abundance, it is still uncommon for young aspen to grow past peak browsing height (120-cm), indicating that many stands remain vulnerable to elk herbivory nearly 30 years after wolf reintroduction. These results highlight that the strength and mechanism of predator effects on plant communities are context-specific. Thus, using predator reintroduction as a tool for ecosystem restoration without considering the many factors that shape trophic cascades may result in different management and conservation outcomes than intended

    Physical phenomena controlling quiescent flame spread in porous wildland fuel beds

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    Despite well-developed solid surface flame spread theories, we still lack a coherent theory to describe flame spread through porous wildland fuel beds. This porosity results in additional complexity, reducing the thermal conductivity of the fuel bed, but allowing in-bed radiative and convective heat transfer to occur. While previous studies have explored the effect of fuel bed structure on the overall fire behaviour, there remains a need for further investigation of the effect of fuel structure on the underlying physical phenomena controlling flame spread. Through an extensive series of laboratory-based experiments, this thesis provides detailed, physics-based insights for quiescent flame spread through natural porous beds, across a range of structural conditions. Measurements are presented for fuel beds representative of natural field conditions within an area of the fire-prone New Jersey Pinelands National Reserve, which compliment a related series of field experiments conducted as part of a wider research project. Additional systematic investigation across a wider range of fuel conditions identified independent effects of fuel loading and bulk density on the spread rate, flame height and heat release rate. However, neither fuel loading nor bulk density alone provided adequate prediction of the resulting fire behaviour. Drawing on existing structural descriptors (for both natural and engineered fuel beds) an alternative parameter Ī±ĻƒĪ“ was proposed. This parameter (incorporating the fuel bed porosity (Ī±), fuel element surface-to-volume ratio (Ļƒ), and the fuel bed height (Ī“)) was strongly correlated with the spread rate. One effect of the fuel bed structure is to influence the heat transfer mechanisms both above and within the porous fuel bed. Existing descriptions of radiation transport through porous fuel beds are often predicated on the assumption of an isotropic fuel bed. However, given their preferential angle of inclination, the pine needle beds in this study may not exhibit isotropic behaviour. Regardless, for the structural conditions investigated, horizontal heat transfer through the fuel bed was identified as the dominant heating mechanism within this quiescent flame spread scenario. However, the significance of heat transfer contributions from the above-bed flame generally increased with increasing Ī±ĻƒĪ“ value of the fuel bed. Using direct measurements of the heat flux magnitude and effective heating distance, close agreement was observed between experimentally observed spread rates and a simple thermal model considering only radiative heat transfer through the fuel bed, particularly at lower values of Ī±ĻƒĪ“. Over-predictions occurred at higher Ī±ĻƒĪ“ values, or where other heat transfer terms were incorporated, which may highlight the need to include additional heat loss terms. A significant effect of fuel structure on the primary flow regimes, both within and above these porous fuel beds, was also observed, with important implications for the heat transfer and oxygen supply within the fuel bed. Independent effects of fuel loading and bulk density on both the buoyant and buoyancy-driven entrainment flow were observed, with a complex feedback cycle occurring between Heat Release Rate (HRR) and combustion behaviour. Generally, increases in fuel loading resulted in increased HRR, and therefore increased buoyant flow velocity, along with an increase in the velocity of flow entrained towards the combustion region. The complex effects of fuel structure in both the flaming and smouldering combustion phases may necessitate modifications to other common modelling approaches. The widely used Rothermel model under-predicted spread rate for higher bulk density and lower Ī±ĻƒĪ“ fuel beds. As previously suggested, an over-sensitivity to fuel bed height was observed, with experimental comparison indicating an under-prediction of reaction intensity at lower fuel heights. These findings have important implications particularly given the continuing widespread use of the Rothermel model, which continues to underpin elements of the BehavePlus fire modelling system and the US National Fire Danger Rating System. The physical insights, and modelling approaches, developed for this low-intensity, quiescent flame spread scenario, are applicable to common prescribed fire activities. It is hoped that this work (alongside complimentary laboratory and field experiments conducted by various authors as part of a wider multi-agency project (SERDP-RC2641)) will contribute to the emerging field of prescribed fire science, and help to address the pressing need for further development of fire prediction and modelling tools

    Balancing the urban stomach: public health, food selling and consumption in London, c. 1558-1640

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    Until recently, public health histories have been predominantly shaped by medical and scientific perspectives, to the neglect of their wider social, economic and political contexts. These medically-minded studies have tended to present broad, sweeping narratives of health policy's explicit successes or failures, often focusing on extraordinary periods of epidemic disease viewed from a national context. This approach is problematic, particularly in studies of public health practice prior to 1800. Before the rise of modern scientific medicine, public health policies were more often influenced by shared social, cultural, economic and religious values which favoured maintaining hierarchy, stability and concern for 'the common good'. These values have frequently been overlooked by modern researchers. This has yielded pessimistic assessments of contemporary sanitation, implying that local authorities did not care about or prioritise the health of populations. Overly medicalised perspectives have further restricted historians' investigation and use of source material, their interpretation of multifaceted and sometimes contested cultural practices such as fasting, and their examination of habitual - and not just extraordinary - health actions. These perspectives have encouraged a focus on reactive - rather than preventative - measures. This thesis contributes to a growing body of research that expands our restrictive understandings of pre-modern public health. It focuses on how public health practices were regulated, monitored and expanded in later Tudor and early Stuart London, with a particular focus on consumption and food-selling. Acknowledging the fundamental public health value of maintaining urban foodways, it investigates how contemporaries sought to manage consumption, food production waste, and vending practices in the early modern City's wards and parishes. It delineates the practical and political distinctions between food and medicine, broadly investigates the activities, reputations of and correlations between London's guild and itinerant food vendors and licensed and irregular medical practitioners, traces the directions in which different kinds of public health policy filtered up or down, and explores how policies were enacted at a national and local level. Finally, it compares and contrasts habitual and extraordinary public health regulations, with a particular focus on how perceptions of and actual food shortages, paired with the omnipresent threat of disease, impacted broader aspects of civic life

    THE DREAM OF A ZERO WASTE SOCIETY: EXPLORING THE PRACTICES AND BEHAVIOURS OF WASTE GENERATION IN GREATER MEXICO CITY

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    This research aims to re-conceptualise consumption and waste generation through a broader set of theoretical questions and analytical methodologies to establish a more holistic theoretical framework for comprehending the global South's "waste crisis." This thesis is primarily based on the following question: "why do we dispose of things?". By focusing on practices and behaviours of consumption and disposal by citizens of GMC, this thesis seeks to unpack the networks, symbols, skills, and meanings of these practices. This moves the conceptualisation of waste generation away from being conceived as an irremediable consequence of population growth or as primary responsibility on the consumers' shoulders. Therefore, this thesis proposes that consumers are embedded in a "throwaway environment" that pushes them toward unsustainable practices. However, this does not mean that the consumers have a "throwaway culture"; consumers might be "carriers" of practices, but they are still active participants. By unravelling the multiple layers of framing that aggregate into the consumption and disposal of citizens in GMC, we shall see how GMC society's historical, social, and political framework serves as dispositions that guide an individual to act. This study focuses on modifying the narrative of considering consumers as careless, lazy, or consumption-driven. It also sheds light on how ignoring these behaviours and practices will only bring temporary and reactionary solutions when dealing with waste. This dissertation also offers an analytical framework that explores how consumers' elements interrelate and are synergetic. By re-conceptualising consumption and waste generation, I propose not focusing on the insidious moral narrative of whether consumption and disposal are acceptable and to what degree. Instead, we should concentrate on a policy strategy that will help reduce the flow of materials. As a result, we might be able to curve a waste crisis by accepting shared responsibility (mostly borne by governments and businesses
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