Novel Aspects of Interference Alignment in Wireless Communications

Interference alignment (IA) is a promising joint-transmission technology that essentially enables the maximum achievable degrees-of-freedom (DoF) in K-user interference channels. Fundamentally, wireless networks are interference-limited since the spectral efficiency of each user in the network is degraded with the increase of users. IA breaks through this barrier, that is caused by the traditional interference management techniques, and promises large gains in spectral efficiency and DoF, notably in interference limited environments. This dissertation concentrates on overcoming the challenges as well as exploiting the opportunities of IA in K-user multiple-input multiple-output (MIMO) interference channels. In particular, we consider IA in K-user MIMO interference channels in three novel aspects. In the first aspect, we develop a new IA solution by designing transmit precoding and interference suppression matrices through a novel iterative algorithm based on Min-Maxing strategy. Min-Maxing IA optimization problem is formulated such that each receiver maximizes the power of the desired signal, whereas it preserves the minimum leakage interference as a constraint. This optimization problem is solved by relaxing it into a standard semidefinite programming form, and additionally its convergence is proved. Furthermore, we propose a simplified Min-Maxing IA algorithm for rank-deficient interference channels to achieve the targeted performance with less complexity. Our numerical results show that Min-Maxing IA algorithm proffers significant sum-rate improvement in K-user MIMO interference channels compared to the existing algorithms in the literature at high signal-to-noise ratio (SNR) regime. Moreover, the simplified algorithm matches the optimal performance in the systems of rank-deficient channels. In the second aspect, we deal with the practical challenges of IA under realistic channels, where IA is highly affected by the spatial correlation. Data sum-rate and symbol error-rate of IA are dramatically degraded in real-world scenarios since the correlation between channels decreases the SNR of the received signal after alignment. For this reason, an acceptable sum-rate of IA in MIMO orthogonal frequency-division-multiplexing (MIMO-OFDM) interference channels was obtained in the literature by modifying the locations of network nodes and the separation between the antennas within each node in order to minimize the correlation between channels. In this regard, we apply transmit antenna selection to MIMO-OFDM IA systems either through bulk or per-subcarrier selection aiming at improving the sum-rate and/or error-rate performance under real-world channel circumstances while keeping the minimum spatial antenna separation of half-wavelengths. A constrained per-subcarrier antenna selection is performed to avoid subcarrier imbalance across the antennas of each user that is caused by per-subcarrier selection. Furthermore, we propose a sub-optimal antenna selection algorithm to reduce the computational complexity of the exhaustive search. An experimental testbed of MIMO-OFDM IA with antenna selection in indoor wireless network scenarios is implemented to collect measured channels. The performance of antenna selection in MIMO IA systems is evaluated using measured and deterministic channels, where antenna selection achieves considerable improvements in sum-rate and error-rate under real-world channels. Third aspect of this work is exploiting the opportunity of IA in resource management problem in OFDM based MIMO cognitive radio systems that coexist with primary systems. We propose to perform IA based resource allocation to improve the spectral efficiency of cognitive systems without affecting the quality of service (QoS) of the primary system. IA plays a vital role in the proposed algorithm enabling the secondary users (SUs) to cooperate and share the available spectrum aiming at increasing the DoF of the cognitive system. Nevertheless, the number of SUs that can share a given subcarrier is restricted to the IA feasibility conditions, where this limitation is considered in problem formulation. As the optimal solution for resource allocation problem is mixed-integer, we propose a two-phases efficient sub-optimal algorithm to handle this problem. In the first phase, frequency-clustering with throughput fairness consideration among SUs is performed to tackle the IA feasibility conditions, where each subcarrier is assigned to a feasible number of SUs. In the second phase, the power is allocated among subcarriers and SUs without violating the interference constraint to the primary system. Simulation results show that IA with frequency-clustering achieves a significant sum-rate increase compared to cognitive radio systems with orthogonal multiple access transmission techniques. The considered aspects with the corresponding achievements bring IA to have a powerful role in the future wireless communication systems. The contributions lead to significant improvements in the spectral efficiency of IA based wireless systems and the reliability of IA under real-world channels.Interference Alignment (IA) ist eine vielversprechende kooperative Übertragungstechnik, die die meisten Freiheitsgrade (engl. degrees-of-freedom, DoF) in Bezug auf Zeit, Frequenz und Ort in einem Mehrnutzer Überlagerungskanal bietet. Im Grunde sind Funksysteme Interferenz begrenzt, da die Spektraleffizienz jedes einzelnen Nutzers mit zunehmender Nutzerzahl sinkt. IA durchbricht die Schranke, die herkömmliches Interferenzmanagement errichtet und verspricht große Steigerungen der Spektraleffizienz und der Freiheitsgrade, besonders in Interferenzbegrenzter Umgebung. Die vorliegende Dissertation betrachtet bisher noch unerforschte Möglichkeiten von IA in Mehrnutzerszenarien für Mehrantennen- (MIMO) Kanäle sowie deren Anwendung in einem kognitiven Kommunikationssystem. Als erstes werden mit Hilfe eines effizienten iterativen Algorithmus, basierend auf der Min-Maxing Strategie, senderseitige Vorkodierungs- und Interferenzunterdrückungs Matrizen entwickelt. Das Min-Maxing Optimierungsproblem ist dadurch beschreiben, dass jeder Empfänger seine gewünschte Signalleistung maximiert, während das Minimum der Leck-Interferenz als Randbedingung beibehalten wird. Zur Lösung des Problems wird es in eine semidefinite Form überführt, zusätzlich wird deren Konvergenz nachgewiesen. Des Weiteren wird ein vereinfachter Algorithmus für nicht vollrangige Kanalmatrizen vorgeschlagen, um die Rechenkomplexität zu verringern. Wie numerische Ergebnisse belegen, bedeutet die Min-Maxing Strategie eine wesentliche Verbesserung des Systemdurchsatzes gegenüber den bisher in der Literatur beschriebenen Algorithmen für Mehrnutzer MIMO Szenarien im hohen Signal-Rausch-Verhältnis (engl. signal-to-noise ratio, SNR). Mehr noch, der vereinfachte Algorithmus zeigt das optimale Verhalten in einem System mit nicht vollrangigen Kanalmatrizen. Als zweites werden die IA Herausforderungen an Hand von realistischen/realen Kanälen in der Praxis untersucht. Hierbei wird das System stark durch räumliche Korrelation beeinträchtigt. Der Datendurchsatz sinkt und die Symbolfehlerrate steigt dramatisch unter diesen Bedingungen, da korrelierte Kanäle den SNR des empfangenen Signals nach dem Alignment verschlechtern. Aus diesem Grund wurde in der Literatur für IA in MIMO-OFDM Überlagerungskanälen sowohl die Position der einzelnen Netzwerkknoten als auch die Trennung zwischen den Antennen eines Knotens variiert, um so die Korrelierung der verschiedenen Kanäle zu minimieren. Das vorgeschlagene MIMO-OFDM IA System wählt unter mehreren Sendeantennen, entweder pro Unterträger oder für das komplette Signal, um so die Symbolfehlerrate und/oder die gesamt Datenrate zu verbessern, während die räumliche Trennung der Antennen auf die halbe Wellenlänge beschränkt bleiben soll. Bei der Auswahl pro Unterträger ist darauf zu achten, dass die Antennen gleichmäßig ausgelastet werden. Um die Rechenkomplexität für die vollständige Durchsuchung gering zu halten, wird ein suboptimaler Auswahlalgorithmus verwendet. Mit Hilfe einer Innenraummessanordnung werden reale Kanaldaten für die Simulationen gewonnen. Die Evaluierung des MIMO IA Systems mit Antennenauswahl für deterministische und gemessene Kanäle hat eine Verbesserung bei der Daten- und Fehlerrate unter realen Bedingungen ergeben. Als drittes beschäftigt sich die vorliegende Arbeit mit den Möglichkeiten, die sich durch MIMO IA Systeme für das Ressourcenmanagementproblem bei kognitiven Funksystemen ergeben. In kognitiven Funksystemen müssen MIMO IA Systeme mit primären koexistieren. Es wird eine IA basierte Ressourcenzuteilung vorgeschlagen, um so die spektrale Effizienz des kognitiven Systems zu erhöhen ohne die Qualität (QoS) des primären Systems zu beeinträchtigen. Der vorgeschlagenen IA Algorithmus sorgt dafür, dass die Zweitnutzer (engl. secondary user, SU) untereinander kooperieren und sich das zur Verfügung stehende Spektrum teilen, um so die DoF des kognitiven Systems zu erhöhen. Die Anzahl der SUs, die sich eine Unterträgerfrequenz teilen, ist durch die IA Randbedingungen begrenzt. Die Suche nach der optimalen Ressourcenverteilung stellt ein gemischt-ganzzahliges Problem dar, zu dessen Lösung ein effizienter zweistufiger suboptimaler Algorithmus vorgeschlagen wird. Im ersten Schritt wird durch Frequenzzusammenlegung (Clusterbildung), unter Berücksichtigung einer fairen Durchsatzverteilung unter den SUs, die IA Anforderung erfüllt. Dazu wird jede Unterträgerfrequenz einer praktikablen Anzahl an SUs zugeteilt. Im zweiten Schritt wird die Sendeleistung für die einzelnen Unterträgerfrequenzen und SUs so festgelegt, dass die Interferenzbedingungen des Primärsystems nicht verletzt werden. Die Simulationsergebnisse für IA mit Frequenzzusammenlegung zeigen eine wesentliche Verbesserung der Datenrate verglichen mit kognitiven Systemen, die auf orthogonalen Mehrfachzugriffsverfahren beruhen. Die in dieser Arbeit betrachteten Punkte und erzielten Lösungen führen zu einer wesentlichen Steigerung der spektralen Effizienz von IA Systemen und zeigen deren Zuverlässigkeit unter realen Bedingungen

Blind CSI acquisition for multi-antenna interference mitigation in 5G networks

Future wireless communication networks are required to satisfy the increasing demands of traffic and capacity. The upcoming fifth generation (5G) of the cellular technology is expected to meet 1000 times the capacity that of the current fourth generation (4G). These tight specifications introduce a new set of research challenges. However, interference has always been the bottleneck in cellular communications. Thus, towards the vision of the 5G, massive multi-input multi-output (mMIMO) and interference alignment (IA) are key transmission technologies to fulfil the future requirements, by controlling the residual interference. By equipping the base-station (BS) with a large number of transmit antennas, e.g, tens of hundreds of antennas, a mMIMO system can theoretically achieve significant capacity with limited interference, where many user equipment (UEs) can be served simultaneously at the same time and frequency resources. A mMIMO offers great spatial degrees of freedom (DoFs), which boost the total network capacity without increasing transmission power or bandwidth. However, the majority of the recent mMIMO investigations are based on theoretical channels with independent and identically distributed (i.i.d) Gaussian distribution, which facilitates the computation of closed-form rate expressions. Nonetheless, practical channels are not spatially uncorrelated, where the BS receives different power ratios across different spatial directions between the same transmitting and receiving antennas. Thus, it is important to understand the behavior of such new technology with practical channel modeling. Alternatively, IA is known to break the bottleneck between the capacity of the network and the overall spectral efficiency (SE), where a performance degradation is observed at a certain level of connected user capacity, due to the overwhelming inter-user interference. Theoretically, IA guarantees a linear relationship between half of the overall network SE and the online capacity by aligning interference from all transmitters inside one spatial signal subspace, leaving the other subspace for desired transmission. However, IA has tight feasibility conditions in practice including high precision channel state information at transmitter (CSIT), which leads to severe feedback overhead. In this thesis, high-precision blind CSIT algorithms are developed under different transmission technologies. We first consider the CSIT acquisition problem in MIMO IA systems. Proposed spatial channel estimation for MIMO-IA systems (SCEIA) shows great offered spatial degrees of freedom which contributes to approaching the performance of the perfect-CSIT case, without the requirements of channel quantization or user feedback overhead. In massive MIMO setups, proposed CSIT strategy offered scalable performance with the number of the transmit antennas. The effect of the non-stationary channel characteristics, which appears with very large antenna arrays, is minimized due to the effective scanning precision of the proposed strategy. Finally, we extend the system model to the full dimensional space, where users are distributed across the two dimensions of the cell space (azimuthal/elevation). Proposed directional spatial channel estimation (D-SCE) scans the 3D cell space and effectively attains additional CSIT and beamforming gains. In all cases, a list of comparisons with state-of-the-art schemes from academia and industry is performed to show the performance improvement of the proposed CSIT strategies

Light-driven directional mass transport in azobenzene containing materials for complex textures on surfaces

Azobenzene-containing materials are one of the most investigated photo-responsive material classes over the last decades. The main reason of such huge interest is their ability to develop superficial reliefs in response to the irradiation with spatially structured optical fields in the UV/visible optical range. This phenomenon has been understood as generated by a light-driven macroscopic mass transport of the host material (typically an amorphous polymer) driven in non-trivial way by the microscopic photo-isomerization dynamics of the azobenzene molecules embedded into it. Even if the exact physical link between the light-induced molecular dynamics and the macroscopic mass displacement is still debated, some of the fingerprints of the phenomenon are fully established. The mass migration, indeed, happens only in illuminated areas of the material and it is highly directional, with a very peculiar sensitivity to the intensity and polarization distributions of the irradiating light field. Since its discovery in 1995, the possibilities offered by this effect for superficial pattering have been largely exploited and recent advances in this field are now oriented toward the realization of complex superficial textures. In the present thesis are proposed two main ideas to accomplish this complex light-driven structuration onto the azopolymer surfaces. The first idea is based on the use of complex structured intensity patterns to irradiate a plane azopolymer film. Such approach can have a two-fold relevance in the azobenzene related research fields. If, on one hand, the use of complex illumination patterns has already been demonstrated to be a fundamental tool in order to highlight new aspects of the mass migration phenomenon, on the other hand the possibility to achieve a precise control on the complex illumination patterns allows the actual employment of the azomaterials as versatile platform in photo-lithographic applications. In particular, the holographic illumination technique described in this thesis opens unprecedented possibilities in both the mentioned research areas. The second idea is instead based on the light-driven reconfiguration of azopolymer surfaces presenting a pre-patterned micro texture. In this situation the illumination pattern can be maintained as simple as conceivable, being constituted even only by a single polarized light beam. However, a great variety of three-dimensional micro-architectures can be obtained using this approach. In particular, azopolymer surfaces having a directional and reversible geometrical asymmetry are achieved by tuning few illumination parameters. These asymmetric microstructures, furthermore, have the ability to tailor several physical macroscopic features of the surfaces, as for example the wettability properties of the azomaterial films. In this thesis is reported a detailed study of such light-controlled wettability tuning, highlighting once more the possibilities offered by this unique photo-responsive material framework for applications in many fields of science

Targeting the Nt17 of the huntingtin protein via natural and chemical modifications: impact on aggregation and membrane interactions

Huntington Disease (HD) is a fatal neurodegenerative disorder caused by an expanded polyglutamine domain (polyQ) in the first exon of the huntingtin protein (htt-exon1). The major hallmark of HD is the accumulation of aggregates into proteinaceous inclusion bodies. PolyQ expansion in huntingtin promotes self-assembly into a variety of toxic aggregates such as oligomers, fibrils, and amorphous aggregates. The resulting heterogeneous mixture of distinct species makes it difficult to assign a toxic function to specific aggregate structures. In addition, htt interacts with a variety of membranous surfaces. The first 17 amino acids (Nt17) of htt directly flanking the polyQ domain functions in binding lipids and in promoting aggregation based on its ability to form an amphipathic a-helix. Nt17 undergoes several posttranslational modifications that modulate aggregation, subcellular localization, and toxicity of mutant htt. To gain in-depth mechanistic insights into huntingtin aggregation at lipid interfaces, both natural and chemical Nt17 modification strategies were employed. Specifically, the direct impact of SUMOylation was characterized. SUMOylation promoted the formation of large, SDS-soluble amorphous aggregates of htt and significantly inhibited the ability of htt to bind lipid membranes. In addition, the interaction of various htt aggregates species with lipid membrane was determined, and oligomers displayed the largest membrane activity. To further investigate these htt oligomers, a crosslinking strategy was employed that targeted lysine residues within Nt17. Crosslinking htt oligomers compromises their conformational flexibility, inhibiting their membrane activity. Cellular toxicity of crosslinked oligomers was also reduced, suggesting membrane activity may underlie mechanisms associated with htt oligomers

COMPETITIVE AND METABOLIC STRATEGIES OF MARINE BACTERIA AND THEIR INFLUENCE ON OCEAN ECOLOGY AND BIOGEOCHEMISTRY

Marine bacterial communities play a crucial role in biogeochemical cycling of carbon and other elements in the global ocean. Cyanobacteria photosynthesize, fixing carbon that forms the basis of the marine food web. Heterotrophic bacteria in turn metabolize fixed carbon compounds for energy and secondary production (generation of new heterotrophic bacterial biomass), remineralizing it to carbon dioxide that will eventually be released back into the atmosphere. The interplay between these autotrophic and heterotrophic processes determines whether atmospheric carbon is exported to the deep ocean. Thus, understanding this interplay with model organisms and complex natural marine bacterial communities is important for carbon cycle modeling as climate change alters marine ecosystems. This dissertation combines culturing, traditional genetics, and bioinformatics techniques to better understand the roles of bacterial species, genera, and families in carbon cycling. I used co-culture and traditional genetics to describe an interbacterial killing phenotype in the coastal generalist Ruegeria pomeroyi DSS-3, which allows other researchers using this model organism for carbon metabolism studies to design their experiments with this phenotype factored into the design. I used quantitative metagenomics to assemble two new Synechococcus genomes from the iron-limited Northeast Pacific. My analysis of these genomes revealed the apparent gene loss of a major nitrogen assimilation pathway that not only could restrict this genus’ ability to contribute to new primary production in this region, but also is likely relevant in several other iron-limited regions of the global ocean. Finally, I employed quantitative metagenomics and metatranscriptomics in a Northeastern Atlantic dissolved organic carbon incubation experiment to calculate bacterial community growth rates on DOC at the family, genus, and species level. These growth rates were used to identify key taxa n DOC remineralization, and metatranscriptome read mapping to these key players provided clues as to what compounds could have been fueling their growth. Overall, this dissertation uses a variety of genetic and genomic techniques to improve our understanding of multiple aspects of marine microbial community dynamics, from inter-species competition to autotrophic primary productivity to heterotrophic secondary productivity.Doctor of Philosoph

Magnetic attraction in microgravity. FELDs Experiment from simulations to data analysis

Elaborato scritto sulla progettazione dell'esperimento FELDs. Descrizione delle fasi di progettazione e della fase di analisi finale dei dati raccolti. Analisi del procedimento per la specifica dei parametri dominanti e descrizione delle simulazioni utilizzat

siRNA Targeting of Thymidylate Synthase, Thymidine Kinase 1 and Thymidine Kinase 2 as an Anticancer Therapy: A Combinatorial RNAi Approach

Thymidylate synthase (TS) is the only de novo source of thymidylate (dTMP) for DNA synthesis and repair. Drugs targeting TS protein are a mainstay in cancer treatment but off-target effects and toxicity limit their use. Cytosolic thymidine kinase (TK1) and mitochondrial thymidine kinase (TK2) contribute to an alternative dTMP-producing pathway, by salvaging thymidine from the tumour milieu, and may modulate resistance to TS-targeting drugs. We have previously shown that TS antisense molecules (oligodeoxynucleotides, ODNs, and small interfering siRNA, siRNA) sensitize tumour cells, both in vitro and in vivo, to TS targeting drugs. As both TS and TKs contribute to cellular dTMP, we hypothesized that TKs mediate resistance to the capacity of TS siRNA to sensitize tumour cells to TS-targeting drugs. Downregulation of TKs with siRNA enhanced the capacity of TS siRNA to sensitize tumour cells to traditional TS protein-targeting drugs (5FUdR and pemetrexed). Combined downregulation of these enzymes is an attractive strategy to enhance TS-targeted anticancer therapy. TK2 can phosphorylate both thymidine and deoxycytidine to generate dTMP and dCMP, precursors for dTTP and dCTP, respectively. dCTP negatively regulates deoxycytidine kinase (dCK), another enzyme that phosphorylates deoxycytidine as well as the anticancer drug gemcitabine. Antisense knockdown of TK2 could reduce TK2-produced dCMP, thus decreasing dCTP levels and inhibition of dCK, and lead to increased dCK activity, gemcitabine activation, and anticancer effectiveness. Given the substrate promiscuity of TK2, we hypothesized that: (1) TK2 can mediate human tumour cell resistance to gemcitabine, (2) antisense downregulation of TK2 can overcome that resistance, and (3) TK2 siRNA-induced drug sensitization results in mitochondrial damage. siRNA downregulation of TK2 expression sensitized MCF7 and HeLa cells to gemcitabine, but did not sensitize A549 cells (low TK2 expresser). Treatment with TK2 siRNA and gemcitabine: 1) decreased mitochondrial redox status, 2) decreased mitochondrial DNA (mtDNA:nDNA ratio), and 3) decreased mitochondrial activity. This is the first demonstration of a direct role for TK2 in gemcitabine resistance, or any independent role in cancer drug resistance, and further distinguishes TK2 from other dTMP-producing enzymes

Scalable designs and methods for heterogeneous electronic-photonic integrated circuitry

A set of semiconductor designs shown to be capable of facilitating scalable and reconfigurable layouts for electronic-photonic integrated circuitry is presented. Three emphases are established to outline and discuss the methods and advantages of merging stand-alone optical components into integrated heterogeneous systems, specifically for implementing optical sensing, efficient laser wavelength tuning, and III-V-on-Si semiconductor fabrication techniques together on a single platform. Considerations regarding the optical geometries and power efficiency of each design are reiterated to assure that each design is compatible with the goals of system-level integration in either biochemical point-of-use or telecommunications applications. These three approaches to scalable photonic designs are then investigated in their ability to offer dynamic controls of optical signals and their novel usage of heterogeneous material patterning. The optical sensing platform directly integrates multiple linear variable filters (LVFs) atop a CMOS image sensor for electronic controls of detecting a biochemical fluorescent or absorptive optical signal signature, enabling good wavelength resolution (3.77−6.08 nm) over a wide-band detection spectrum. Detection limits of 0.28 nM for Quantum Dot emitters and 32 ng/mL for near-infrared fluorescent dyes are found in this integrated design, providing comparable results in the compact optical platform to conventional laboratory spectrometers. The instrument is then extended in its usage by testing on point-of-use detection tests via discerning the concentration of free-chlorine in water colorimetrically. The tunable laser cavity design integrates together a GaN waveguide into a standard InGaAsP telecom (1550 nm) edge-emitting laser atop silicon, allowing for wide-band tuning via the strong anisotropic effects solved for in wurtzite GaN. A tuning parameter based off a refractive index variation, Δ, is found to be at |1.75∙10E−4|, based off the electro-optic effects in conjunction with an etched grating geometry designed directly into the coupled GaN waveguide, with the structure further extended into a Y-branch laser cavity to enable the Vernier effect for wideband tuning via mode-hopping. A separate GaN-based design, consisting of an RF signal modulator that launches a surface acoustic wave (SAW) into a cavity to produce a highly controllable refractive index variation, Δ, via the photo-elastic and photo-elastic effects, is found to produce a large tuning parameter of |1.84∙10E−3|. These effects are then described in their application to dynamically controllable effects for dense wavelength division multiplexing (DWDM) and how the underlying electronic platform enables this, providing advantages over larger footprint or less efficient designs. The fabrication techniques designed provide a method to enable bonding of III-V epitaxial wafers onto a silicon carrier wafer for large-scale processing before final bonding onto CMOS. A processing recipe takes bulk GaAs epitaxial structures and constructs a method for reversibly bonding and processing them on a silicon carrier wafer as III-V islands, ready for final large scale flip-chip bonding onto aligning CMOS features. Additional findings discuss the merits of various etch processes and techniques such that they are compatible to the heterogeneous III-V-on-Si patterning as laid out. The methods optimized allow for simultaneous, heterogeneous development of system-level device integration such that further processing can place various III-V devices side-by-side and process geometries in unison. Processing steps and their results are presented. The extension of this method to different III-V alloys beyond GaAs entirely is therefore considered for even larger-scale system design across photonic elements. Each set of findings presents both the relevant photonic device characteristics and also a method on how to intersect these devices with a paired CMOS electronic system on silicon, so that a single unified electronic-photonic schematic can be made. Accompanying these conclusions is a range of experimental work ranging from simulation studies, to full-scale integrable sensing designs and their testing, to detailed cleanroom-based fabrication processes for designing the system of III-V-on-Si patterns. A final set of conclusions relates the three tracks of research as being part of a common path forward in scalable photonics designs. Forecasts are then made on how the field of electronic-photonic integration and its applications utilized herein may yet evolve and potentially encompass findings or methodologies from this work

Experimental and Computational Study of Fluid Dynamics in Solar Reactor

The experimental simulation and a computational validation of a methane-cracking solar reactor powered by solar energy is the focus of this article. A solar cyclone reactor operates at over 1000 °C where the methane decomposition reaction takes place. Carbon particles are formed when methane molecules dissociate into carbon and hydrogen. During the course of this two-phase flow transport, part of the carbon particles tend to deposit on the inner surfaces such as the inner wall, window, and exit of the reactor. The deposition of carbon particles on the inner surfaces of the reactor blocks energy input and decreases converting efficiency. Particularly when they accumulate near the reactor exit, agglomeration of these particles tends to block the exit. In response to the unwanted deposition, a cyclone main flow provided a shield flow concept was predicted to prevent carbon deposition from the methane decomposition process via computational fluid dynamics (CFD). Based on the geometry of previous CFD studies an experimental validation to the effectiveness of the shield flows was performed via particle image velocimetry (PIV) and pressure sensitive paint (PSP) techniques. Three flow cases using air at atmospheric pressure, air at partial vacuum and mixture of different gas species at atmospheric pressure were used to simulate the flow interaction in the high temperature environment where methane cracking process occurs. The vortex structure in the reactor prolonged the resident time of the main flow in favor of higher energy conversion. The optimal resident time took place when the main flow decreased by 20 % compared to a reference CFD prediction. The resident time decreased when wall streams increase. According to the experimental data obtained from the three flow cases, a CFD simulation was performed to validate the computational model. A high temperature case simulation was compared to the room temperature cases via CFD. The CFD results showed same flow pattern between high temperature case and room temperature cases. By experimental and computational approaches, this article provides a thorough analysis to the future design and study of the solar cyclone reactors

Robotic 3D Reconstruction Utilising Structure from Motion

Sensing the real-world is a well-established and continual problem in the field of robotics. Investigations into autonomous aerial and underwater vehicles have extended this challenge into sensing, mapping and localising in three dimensions. This thesis seeks to understand and tackle the challenges of recovering 3D information from an environment using vision alone. There is a well-established literature on the principles of doing this, and some impressive demonstrations; but this thesis explores the practicality of doing vision-based 3D reconstruction using multiple, mobile robotic platforms, the emphasis being on producing accurate 3D models. Typically, robotic platforms such as UAVs have a single on-board camera, restricting which method of visual 3D recovery can be employed. This thesis specifically explores Structure from Motion, a monocular 3D reconstruction technique which produces detailed and accurate, although slow to calculate, 3D reconstructions. It examines how well proof-of-concept demonstrations translate onto the kinds of robotic systems that are commonly deployed in the real world, where local processing is limited and network links have restricted capacity. In order to produce accurate 3D models, it is necessary to use high-resolution imagery, and the difficulties of working with this on remote robotic platforms is explored in some detail