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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
ENABLING EFFICIENT FLEET COMPOSITION SELECTION THROUGH THE DEVELOPMENT OF A RANK HEURISTIC FOR A BRANCH AND BOUND METHOD
In the foreseeable future, autonomous mobile robots (AMRs) will become a key enabler
for increasing productivity and flexibility in material handling in warehousing facilities,
distribution centers and manufacturing systems.
The objective of this research is to develop and validate parametric models of AMRs,
develop ranking heuristic using a physics-based algorithm within the framework of the
Branch and Bound method, integrate the ranking algorithm into a Fleet Composition
Optimization (FCO) tool, and finally conduct simulations under various scenarios to
verify the suitability and robustness of the developed tool in a factory equipped with
AMRs. Kinematic-based equations are used for computing both energy and time
consumption. Multivariate linear regression, a data-driven method, is used for designing
the ranking heuristic. The results indicate that the unique physical structures and
parameters of each robot are the main factors contributing to differences in energy and
time consumption. improvement on reducing computation time was achieved by
comparing heuristic-based search and non-heuristic-based search. This research is
expected to significantly improve the current nested fleet composition optimization tool
by reducing computation time without sacrificing optimality. From a practical
perspective, greater efficiency in reducing energy and time costs can be achieved.Ford Motor CompanyNo embargoAcademic Major: Aerospace Engineerin
Chiral active fluids: Odd viscosity, active turbulence, and directed flows of hydrodynamic microrotors
While the number of publications on rotating active matter has rapidly increased in recent years, studies on purely hydrodynamically interacting rotors on the microscale are still rare, especially from the perspective of particle based hydrodynamic simulations. The work presented here targets to fill this gap. By means of high-performance computer simulations, performed in a highly parallelised fashion on graphics processing units, the dynamics of ensembles of up to 70,000 rotating colloids immersed in an explicit mesoscopic solvent consisting out of up to 30 million fluid particles, are investigated. Some of the results presented in this thesis have been worked out in collaboration with experimentalists, such that the theoretical considerations developed in this thesis are supported by experiments, and vice versa. The studied system, modelled in order to resemble the essential physics of the experimentally realisable system, consists out of rotating magnetic colloidal particles, i.e., (micro-)rotors, rotating in sync to an externally applied magnetic field, where the rotors solely interact via hydrodynamic and steric interactions. Overall, the agreement between simulations and experiments is very good, proving that hydrodynamic interactions play a key role in this and related systems.
While already an isolated rotating colloid is driven out of equilibrium, only collections of two or more rotors have experimentally shown to be able to convert the rotational energy input into translational dynamics in an orbital rotating fashion. The rotating colloids inject circular flows into the fluid, such that detailed balance is broken, and it is not a priori known whether equilibrium properties of colloids can be extended to isolated rotating colloids. A joint theoretical and experimental analysis of isolated, pairs, and small groups of hydrodynamically interacting rotors is given in chapter 2. While the translational dynamics of isolated rotors effectively resemble the dynamics of non-rotating colloids, the orbital rotation of pairs of rotors can be described with leading order hydrodynamics and a two-dimensional analogy of FaxĂ©nâs law is derived.
In chapter 3, a homogeneously distributed ensemble of rotors (bulk) as a realisation of a chiral active fluid is studied and it is explicitly shown computationally and experimentally that it carries odd viscosity. The mutual orbital translation of rotors and an increase of the effective solvent viscosity with rotor density lead to a non-monotonous behaviour of the average translational velocity. Meanwhile, the rotor suspension bears a finite osmotic compressibility resulting from the long-ranged nature of hydrody- namic interactions such that rotational and odd stresses are transmitted through the solvent also at small and intermediate rotor densities. Consequently, density inhomogeneities predicted for chiral active fluids with odd viscosity can be found and allow for an explicit measurement of odd viscosity in simulations and experiments. At intermediate densities, the collective dynamics shows the emergence of multi-scale vortices and chaotic motion which is identified as active turbulence with a self-similar power-law decay in the energy spectrum, showing that the injected energy on the rotor scale is transported to larger scales, similar to the inverse energy cascade of clas- sical two-dimensional turbulence. While either odd viscosity or active turbulence have been reported in chiral active matter previously, the system studied here shows that the emergence of both simultaneously is possible resulting from the osmotic compressibility and hydrodynamic mediation of odd and active stresses. The collective dynamics of colloids rotating out of phase, i.e., where a constant torque instead of a constant angular velocity is applied, is shown to be qualitatively very similar. However, at smaller densities, local density inhomogeneities imply position dependent angular velocities of the rotors resulting from inter-rotor friction.
While the friction of a quasi-2D layer of active colloids with the substrate is often not easily modifiable in experiments, the incorporation of substrate friction into the simulation models typically implies a considerable increase in computational effort. In chapter 4, a very efficient way of incorporating the friction with a substrate into a two-dimensional multiparticle collision dynamics solvent is introduced, allowing for an explicit investigation of the influences of substrate on active dynamics. For the rotor fluid, it is explicitly shown that the influence of the substrate friction results in a cutoff of the hydrodynamic interaction length, such that the maximum size of the formed vortices is controlled by the substrate friction, also resulting in a cutoff in the energy spectrum, because energy is taken out of the system at the respective length. These findings are in agreement with the experiments.
Since active particles in confinement are known to organise in states of collective dynamics, ensembles of rotationally actuated colloids are studied in circular confinement and in the presence of periodic obstacle lattices in chapters 5 and 6, respectively. The results show that the chaotic active turbulent transport of rotors in suspension can be enhanced and guided resulting from edge flows generated at the boundaries, as has recently been reported for a related chiral active system. The consequent collective rotor dynamics can be regarded as a superposition of active turbulent and imposed flows, leading to on average stationary flows. In contrast to the bulk dynamics, the imposed flows inject additional energy into the system on the long length scales, and the same scaling behaviour of the energy spectrum as in bulk is only obtained if the energy injection scales, due to the mutual generation of rotor translational dynamics throughout the system and the edge flows, are well separated. The combination of edge flow and entropic layering at the boundaries leads to oscillating hydrodynamic stresses and consequently to an oscillating vorticity profile. In the presence of odd viscosity, this consequently leads to non-trivial steady-state density modulations at the boundary, resulting from a balance of osmotic pressure and odd stresses.
Relevant for the efficient dispersion and mixing of inert particles on the mesoscale by means of active turbulent mixing powered by rotors, a study of the dynamics of a binary mixture consisting out of rotors and passive particles is presented in chapter 7. Because the rotors are not self-propelled, but the translational dynamics is induced by the surrounding rotors, the passive particles, which do not inject further energy into the system, are transported according to the same mechanism as the rotors. The collective dynamics thus resembles the pure rotor bulk dynamics at the respective density of only rotors. However, since no odd stresses act between the passive particles, only mutual rotor interactions lead to odd stresses leading to the accumulation of rotors in the regions of positive vorticity. This density increase is associated with a pressure increase, which balances the odd stresses acting on the rotors. However, the passive particles are only subject to the accumulation induced pressure increase such that these particles are transported into the areas of low rotor concentration, i.e., the regions of negative vorticity. Under conditions of sustained vortex flow, this results in segregation of both particle types.
Since local symmetry breaking can convert injected rotational into translational energy, microswimmers can be constructed out of rotor materials when a suitable breaking of symmetry is kept in the vicinity of a rotor. One hypothetical realisation, i.e., a coupled rotor pair consisting out of two rotors of opposite angular velocity and of fixed distance, termed a birotor, are studied in chapter 8. The birotor pumps the fluid into one direction and consequently translates into the opposite direction, and creates a flow field reminiscent of a source doublet, or sliplet flow field. Fixed in space the birotor might be an interesting realisation of a microfluidic pump. The trans- lational dynamics of a birotor can be mapped onto the active Brownian particle model for single swimmers. However, due to the hydrodynamic interactions among the rotors, the birotor ensemble dynamics do not show the emergence of stable motility induced clustering. The reason for this is the flow created by birotor in small aggregates which effectively pushes further arriving birotors away from small aggregates, which eventually are all dispersed by thermal fluctuations
Augmented classification for electrical coil winding defects
A green revolution has accelerated over the recent decades with a look to replace existing transportation power solutions through the adoption of greener electrical alternatives. In parallel the digitisation of manufacturing has enabled progress in the tracking and traceability of processes and improvements in fault detection and classification. This paper explores electrical machine manufacture and the challenges faced in identifying failures modes during this life cycle through the demonstration of state-of-the-art machine vision methods for the classification of electrical coil winding defects. We demonstrate how recent generative adversarial networks can be used to augment training of these models to further improve their accuracy for this challenging task. Our approach utilises pre-processing and dimensionality reduction to boost performance of the model from a standard convolutional neural network (CNN) leading to a significant increase in accuracy
Supernatural crossing in Republican Chinese fiction, 1920sâ1940s
This dissertation studies supernatural narratives in Chinese fiction from the mid-1920s to the 1940s. The literary works present phenomena or elements that are or appear to be supernatural, many of which remain marginal or overlooked in Sinophone and Anglophone academia. These sources are situated in the May Fourth/New Culture ideological context, where supernatural narratives had to make way for the progressive intellectualsâ literary realism and their allegorical application of supernatural motifs. In the face of realism, supernatural narratives paled, dismissed as impractical fantasies that distract one from facing and tackling real life.
Nevertheless, I argue that the supernatural narratives do not probe into another mystical dimension that might co-exist alongside the empirical world. Rather, they imagine various cases of the charactersâ crossing to voice their discontent with contemporary society or to reflect on the notion of reality. âCrossingâ relates to charactersâ acts or processes of trespassing the boundary that separates the supernatural from the conventional natural world, thus entailing encounters and interaction between the natural and the supernatural. The dissertation examines how crossing, as a narrative device, disturbs accustomed and mundane situations, releases hidden tensions, and discloses repressed truths in Republican fiction.
There are five types of crossing in the supernatural narratives.
Type 1 is the crossing into âhauntedâ houses. This includes (intangible) human agency crossing into domestic spaces and revealing secrets and truths concealed by the scary, feigned âhauntingâ, thus exposing the hidden evil and the other house occupiersâ silenced, suffocated state.
Type 2 is men crossing into female ghostsâ apparitional residences. The female ghosts allude to heart-breaking, traumatic experiences in socio-historical reality, evoking sympathetic concern for suffering individuals who are caught in social upheavals.
Type 3 is the crossing from reality into the charactersâ delusional/hallucinatory realities. While they physically remain in the empirical world, the charactersâ abnormal perceptions lead them to exclusive, delirious, and quasi-supernatural experiences of reality. Their crossings blur the concrete boundaries between the real and the unreal on the mental level: their abnormal perceptions construct a significant, meaningful reality for them, which may be as real as the commonly regarded objective reality.
Type 4 is the crossing into the netherworld modelled on the real world in the authorsâ observation and bears a spectrum of satirised objects of the Republican society.
The last type is immortal visitors crossing into the human world. This type satirises humanityâs vices and destructive potential.
The primary sources demonstrate their writersâ witty passion to play with super--natural notions and imagery (such as ghosts, demons, and immortals) and stitch them into vivid, engaging scenes using techniques such as the gothic, the grotesque, and the satirical, in order to evoke sentiments such as terror, horror, disgust, dis--orientation, or awe, all in service of their insights into realist issues. The works also creatively tailor traditional Chinese modes and motifs, which exemplifies the revival of Republican interest in traditional cultural heritage. The supernatural narratives may amaze or disturb the reader at first, but what is more shocking, unpleasantly nudging, or thought-provoking is the problematic society and peopleâs lives that the supernatural (misunderstandings) eventually reveals. They present a more compre--hensive treatment of reality than Republican literature with its revolutionary consciousness surrounding class struggle. The critical perspectives of the supernatural narratives include domestic space, unacknowledged history and marginal individuals, abnormal mentality, and pervasive weaknesses in humanity.
The crossing and supernatural narratives function as a means of better understanding the lived reality.
This study gathers diverse primary sources written by Republican writers from various educational and political backgrounds and interprets them from a rare perspective, thus filling a research gap. It promotes a fuller view of supernatural narratives in twentieth-century Chinese literature. In terms of reflecting the social and personal reality of the Republican era, the supernatural narratives supplement the realist fiction of the time
Predictive Maintenance of Critical Equipment for Floating Liquefied Natural Gas Liquefaction Process
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 Rowenâs 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 engineâs 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 turbineâs 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 turbineâs 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
Cost-effective non-destructive testing of biomedical components fabricated using additive manufacturing
Biocompatible titanium-alloys can be used to fabricate patient-specific medical components using additive manufacturing (AM). These novel components have the potential to improve clinical outcomes in various medical scenarios. However, AM introduces stability and repeatability concerns, which are potential roadblocks for its widespread use in the medical sector. Micro-CT imaging for non-destructive testing (NDT) is an effective solution for post-manufacturing quality control of these components. Unfortunately, current micro-CT NDT scanners require expensive infrastructure and hardware, which translates into prohibitively expensive routine NDT. Furthermore, the limited dynamic-range of these scanners can cause severe image artifacts that may compromise the diagnostic value of the non-destructive test. Finally, the cone-beam geometry of these scanners makes them susceptible to the adverse effects of scattered radiation, which is another source of artifacts in micro-CT imaging.
In this work, we describe the design, fabrication, and implementation of a dedicated, cost-effective micro-CT scanner for NDT of AM-fabricated biomedical components. Our scanner reduces the limitations of costly image-based NDT by optimizing the scanner\u27s geometry and the image acquisition hardware (i.e., X-ray source and detector). Additionally, we describe two novel techniques to reduce image artifacts caused by photon-starvation and scatter radiation in cone-beam micro-CT imaging.
Our cost-effective scanner was designed to match the image requirements of medium-size titanium-alloy medical components. We optimized the image acquisition hardware by using an 80 kVp low-cost portable X-ray unit and developing a low-cost lens-coupled X-ray detector. Image artifacts caused by photon-starvation were reduced by implementing dual-exposure high-dynamic-range radiography. For scatter mitigation, we describe the design, manufacturing, and testing of a large-area, highly-focused, two-dimensional, anti-scatter grid.
Our results demonstrate that cost-effective NDT using low-cost equipment is feasible for medium-sized, titanium-alloy, AM-fabricated medical components. Our proposed high-dynamic-range strategy improved by 37% the penetration capabilities of an 80 kVp micro-CT imaging system for a total x-ray path length of 19.8 mm. Finally, our novel anti-scatter grid provided a 65% improvement in CT number accuracy and a 48% improvement in low-contrast visualization. Our proposed cost-effective scanner and artifact reduction strategies have the potential to improve patient care by accelerating the widespread use of patient-specific, bio-compatible, AM-manufactured, medical components
Sensors and Methods for Railway Signalling Equipment Monitoring
Signalling upgrade projects that have been installed in equipment rooms in the recent past have limited capability to monitor performance of certain types of external circuits. To modify the equipment rooms on the commissioned railway would prove very expensive to implement and would be unacceptable in terms of delays caused to passenger services due to re-commissioning circuits after modification, to comply with rail signalling standards. The use of magnetoresistive sensors to provide performance data on point circuit operation and point operation is investigated. The sensors are bench tested on their ability to measure current in a circuit in a non-intrusive manner. The effect of shielding on the sensor performance is tested and found to be significant. The response of the sensors with various levels of amplification produces linear responses across a range of circuit gain. The output of the sensor circuit is demonstrated for various periods of interruption of conductor current. A three-axis accelerometer is mounted on a linear actuator to demonstrate the type of output expected from similar sensors mounted on a set of points. Measurements of current in point detection circuits and acceleration forces resulting from vibration of out of tolerance mechanical assemblies can provide valuable information on performance and possible threats to safe operation of equipment. The sensors seem capable of measuring the current in a conductor with a comparatively high degree of sensitivity. There is development work required on shielding the sensor from magnetic fields other than those being measured. The accelerometer work is at a demonstration level and requires development. The future testing work with accelerometers should be at a facility where multiple point moves can be made; with the capability to introduce faults to the point mechanisms. Methods can then be developed for analysis of the vibration signatures produced by the various faults
Walking with the Earth: Intercultural Perspectives on Ethics of Ecological Caring
It is commonly believed that considering nature different from us, human beings (qua rational, cultural, religious and social actors), is detrimental to our engagement for the preservation of nature. An obvious example is animal rights, a deep concern for all living beings, including non-human living creatures, which is understandable only if we approach nature, without fearing it, as something which should remain outside of our true home. âWalking with the earthâ aims at questioning any similar preconceptions in the wide sense, including allegoric-poetic contributions. We invited 14 authors from 4 continents to express all sorts of ways of saying why caring is so important, why togetherness, being-with each others, as a spiritual but also embodied ethics is important in a divided world
How to Be a God
When it comes to questions concerning the nature of Reality, Philosophers and Theologians have the answers.
Philosophers have the answers that canât be proven right. Theologians have the answers that canât be proven wrong.
Todayâs designers of Massively-Multiplayer Online Role-Playing Games create realities for a living. They canât spend centuries mulling over the issues: they have to face them head-on. Their practical experiences can indicate which theoretical proposals actually work in practice.
Thatâs todayâs designers. Tomorrowâs will have a whole new set of questions to answer.
The designers of virtual worlds are the literal gods of those realities. Suppose Artificial Intelligence comes through and allows us to create non-player characters as smart as us. What are our responsibilities as gods? How should we, as gods, conduct ourselves?
How should we be gods
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