本論文應用策略性貿易理論的觀點，分別探討三個獨立的研究主題：各國關稅結構中普遍存在的「關稅調升」現象、外銷比例政策與外籍廠商技術選擇的關係、及關稅與配額政策對於外籍廠商技術授權決策的影響。 壹、 關稅調升與連續性壟斷 「關稅調升」為世界上大部分國家關稅結構中普遍存在的現象，惟這種現象的理論探討卻十分匱乏。因此，本章的目的即在補充「關稅調升」成因的理論探討。藉由連續性壟斷產業模型的建立，我們的研究顯示：政府若對下游進口產品課徵關稅，此一關稅除了具備新貿易政策理論所稱之「利潤萃取」效果之外，尚具備萃取外國生產上游產品廠商部份獨佔利潤的功能，我們稱此為下游產品關稅的「垂直」效果。在連續性壟斷產業的架構之下，隨著生產階段的遞增，下游產品關稅能夠萃取這些上游獨佔利潤的外國廠商家數亦將增加，「關稅調升」現象因而產生。因此，本章發現關稅之「利潤萃取」效果與「垂直」效果的聯合作用是造成關稅調升現象的重要因素。 貳、 外銷比例政策與技術選擇 在實務上，外銷比例政策常為開發中國家對於多國籍廠商在其國內設廠營運時的一項管制措施。在台灣的發展經驗中，外銷比例政策亦常被政府的財經官員認為具有移轉外國優越技術的有效政策工具，其理由乃在於藉由對多國籍廠商內銷比例的管制，誘使其提升在台的生產技術以面對高度競爭性的國際市場，並同時讓本國廠商透過技術擴散或技術移轉的方式獲得多國籍廠商的技術水準。 本章的目的在於探討外銷比例政策是否真能達到提升外籍廠商技術水準的效果。本章的研究結果發現：在外籍廠商獨占本國市場的情況下，除非政府允諾給於外籍廠商高度比例的內銷市場，否則外銷比例政策非但不會促使外籍廠商選擇較為優良的技術，反而會導致其採取較劣等的技術。另一方面，當本國市場有本國廠商參與競爭時，外銷比例對於外籍廠商技術水準的選擇除了受到前述比例值高低之影響外，也受到市場策略性競爭效果的影響。當本國市場的需求函數為線形時，市場競爭的策略性效果會使得外籍廠商在面對外銷比例的管制增加時會選擇較差之技術。因此，一般而言，外銷比例政策並無法確保外籍廠商會使用較為先進之技術水準。 參、 外籍廠商技術授權：關稅與配額政策的比較 貿易保護政策的實施有可能改變廠商海外市場的營運選擇，譬如改採以技術授權的方式間接進入海外市場，因此地主國的貿易保護政策可以促使該國廠商獲取外籍廠商先進技術的授權。 本章的研究乃在於提供貿易保護政策與國際間授權技術選擇關係的理論分析。藉由比較不同的貿易政策對於對於多國籍廠商市場進入方式與授權技術選擇的影響，本章發現對應於一特定之關稅稅率，等量配額政策在市場需求曲線為凹性（凸性）的情況下，將比關稅政策更易於（更不易於）誘使外國廠商授權先進的技術給本國廠商；而當市場需求曲線為線性的情況下，關稅政策與等量配額政策對於外籍廠商授權技術水準的影響是完全相同的。然而，若本國採取的是等率配額政策，則不論其對應之關稅稅率為何，外籍廠商在等率配額限制之下一定會授權給本國廠商最先進之技術。 第一章 緒論 1 第二章 關稅調升與連續性壟斷 6 第一節 本章前言 6 第二節 基本模型 11 （1） 最終財貨關稅 13 （2） 原物料關稅 20 第三節 關稅調升現象 23 第四節 n層次加工產業下的關稅結構 32 第五節 本章結語 35 附錄 37 第三章 外銷比例政策與技術選擇 39 第一節 本章前言 39 第二節 外籍廠商獨佔下的技術選擇 42 第三節 寡占下的外籍廠商技術選擇 48 第四節 本章結語 54 附 錄 56 第四章 外籍廠商技術授權：關稅與配額政策的比較 58 第一節 本章前言 58 第二節 基本模型 61 第三節 外籍廠商在關稅政策下的授權技術選擇 62 第四節 外籍廠商在等量配額政策下的授權技術選擇 70 第五節 外籍廠商在等率配額政策下的授權技術選擇 78 第六節 範例說明 82 第七節 本章結語 86 第五章 結論 87 參考文獻 89

Multiple-input, multiple-output (MIMO) techniques have been proposed to meet the needs for higher data rates and lower delays in future wireless communication systems. The downlink capacity of multiuser MIMO systems is achieved when the system transmits to several users simultaneously. Frequently, many more users request service than the transmitter can simultaneously support. Thus, the transmitter requires a scheduling algorithm for the users, which must balance the goals of increasing throughput, reducing multiuser interference, lowering delays, ensuring fairness and quality of service (QoS), etc. In this thesis, we investigate the application of genetic algorithms (GAs) to perform scheduling in multiuser MIMO systems. GAs are a fast, suboptimal, low-complexity method of solving optimization problems, such as the maximization of a scheduling metric, and can handle arbitrary functions and QoS constraints. We first examine a system that transmits using capacity-achieving dirty paper coding (DPC). Our proposed GA structure both selects users and determines their encoding order for DPC, which affects the rates they receive. Our GA can also schedule users independently on different carriers of a multi-carrier system. We demonstrate that the GA performance is close to that of an optimal exhaustive search, but at a greatly reduced complexity. We further show that the GA convergence time can be significantly reduced by tuning the values of its parameters. While DPC is capacity-achieving, it is also very complex. Thus, we also investigate GA scheduling with two linear precoding schemes, block diagonalization and successive zero-forcing. We compare the complexity and performance of the GA with "greedy" scheduling algorithms, and find the GA is more complex, but performs better at higher signal-to-noise ratios (SNRs) and smaller user pool sizes. Both algorithms are near-optimal, yet much less complex than an exhaustive search. We also propose hybrid greedy-genetic algorithms to gain benefits from both types of algorithms. Lastly, we propose an improved method of optimizing the transmit covariance matrices for successive zero-forcing. Our algorithm significantly improves upon the performance of the existing method at medium to high SNRs, and, unlike the existing method, can maximize a weighted sum rate, which is important for fairness and QoS considerations. / Communications

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The search for the closest lattice point arises in many communication problems, and is known to be NP-hard. The Maximum Likelihood (ML) Detector is the optimal detector which yields an optimal solution to this problem, but at the expense of high computational complexity. Existing near-optimal methods used to solve the problem are based on the Sphere Decoder (SD), which searches for lattice points confined in a hyper-sphere around the received point. The SD has emerged as a powerful means of finding the solution to the ML detection problem for MIMO systems. However the bottleneck lies in the determination of the initial radius. This thesis is concerned with the detection of transmitted wireless signals in Multiple-Input Multiple-Output (MIMO) digital communication systems as efficiently and effectively as possible. The main objective of this thesis is to design efficient ML detection algorithms for MIMO systems based on the depth-first search (DFS) algorithms whilst taking into account complexity and bit error rate performance requirements for advanced digital communication systems. The increased capacity and improved link reliability of MIMO systems without sacrificing bandwidth efficiency and transmit power will serve as the key motivation behind the study of MIMO detection schemes. The fundamental principles behind MIMO systems are explored in Chapter 2. A generic framework for linear and non-linear tree search based detection schemes is then presented Chapter 3. This paves way for different methods of improving the achievable performance-complexity trade-off for all SD-based detection algorithms. The suboptimal detection schemes, in particular the Minimum Mean Squared Error-Successive Interference Cancellation (MMSE-SIC), will also serve as pre-processing as well as comparison techniques whilst channel capacity approaching Low Density Parity Check (LDPC) codes will be employed to evaluate the performance of the proposed SD. Numerical and simulation results show that non-linear detection schemes yield better performance compared to linear detection schemes, however, at the expense of a slight increase in complexity. The first contribution in this thesis is the design of a near ML-achieving SD algorithm for MIMO digital communication systems that reduces the number of search operations within the sphere-constrained search space at reduced detection complexity in Chapter 4. In this design, the distance between the ML estimate and the received signal is used to control the lower and upper bound radii of the proposed SD to prevent NP-complete problems. The detection method is based on the DFS algorithm and the Successive Interference Cancellation (SIC). The SIC ensures that the effects of dominant signals are effectively removed. Simulation results presented in this thesis show that by employing pre-processing detection schemes, the complexity of the proposed SD can be significantly reduced, though at marginal performance penalty. The second contribution is the determination of the initial sphere radius in Chapter 5. The new initial radius proposed in this thesis is based on the variable parameter α which is commonly based on experience and is chosen to ensure that at least a lattice point exists inside the sphere with high probability. Using the variable parameter α, a new noise covariance matrix which incorporates the number of transmit antennas, the energy of the transmitted symbols and the channel matrix is defined. The new covariance matrix is then incorporated into the EMMSE model to generate an improved EMMSE estimate. The EMMSE radius is finally found by computing the distance between the sphere centre and the improved EMMSE estimate. This distance can be fine-tuned by varying the variable parameter α. The beauty of the proposed method is that it reduces the complexity of the preprocessing step of the EMMSE to that of the Zero-Forcing (ZF) detector without significant performance degradation of the SD, particularly at low Signal-to-Noise Ratios (SNR). More specifically, it will be shown through simulation results that using the EMMSE preprocessing step will substantially improve performance whenever the complexity of the tree search is fixed or upper bounded. The final contribution is the design of the LRAD-MMSE-SIC based SD detection scheme which introduces a trade-off between performance and increased computational complexity in Chapter 6. The Lenstra-Lenstra-Lovasz (LLL) algorithm will be utilised to orthogonalise the channel matrix H to a new near orthogonal channel matrix H ̅.The increased computational complexity introduced by the LLL algorithm will be significantly decreased by employing sorted QR decomposition of the transformed channel H ̅ into a unitary matrix and an upper triangular matrix which retains the property of the channel matrix. The SIC algorithm will ensure that the interference due to dominant signals will be minimised while the LDPC will effectively stop the propagation of errors within the entire system. Through simulations, it will be demonstrated that the proposed detector still approaches the ML performance while requiring much lower complexity compared to the conventional SD.

Chronic recording of neural signals is indispensable in designing efficient brain machine interfaces and to elucidate human neurophysiology. The advent of multi-channel micro-electrode arrays has driven the need for electronic store cord neural signals from many neurons. The continuous increase in demand of data from more number of neurons is challenging for the design of an efficient neural recording frontend(NRFE). Power consumption per channel and data rate minimization are two key problems which need to be addressed by next generation of neural recording systems. Area consumption per channel must be low for small implant size. Dynamic range in NRFE can vary with time due to change in electrode-neuron distance or background noise which demands adaptability. In this thesis, techniques to reduce power-per-channel and area-per-channel in a NRFE, via new circuits and architectures, are proposed. An area efficient low power neural LNA is presented in UMC 0.13 μm 1P8M CMOS technology. The amplifier can be biased adaptively from 200 nA to 2 μA , modulating input referred noise from 9.92 μV to 3.9μV . We also describe a low noise design technique which minimizes the noise contribution of the load circuitry. Optimum sizing of the input transistors minimizes the accentuation of the input referred noise of the amplifier. It obviates the need of large input coupling capacitance in the amplifier which saves considerable amount of chip area. In vitro experiments were performed to validate the applicability of the neural LNA in neural recording systems. ADC is another important block in a NRFE. An 8-bit SAR ADC along with the input and reference buffer is implemented in 0.13 μm CMOS technology. The use of ping-pong input sampling is emphasized for multichannel input to alleviate the bandwidth requirement of the input buffer. To reduce the output data rate, the A/D process is only enabled through a proposed activity dependent A/D scheme which ensures that the background noise is not processed. Based on the dynamic range requirement, the ADC resolution is adjusted from 8 to 1 bit at 1 bit step to reduce power consumption linearly. The ADC consumes 8.8 μW from1Vsupply at1MS/s and achieves ENOB of 7.7 bit. The ADC achieves FoM of 42.3 fJ/conversion in 0.13 μm CMOS technology. Power consumption in SARADCs is greatly benefited by CMOS scaling due to its highly digital nature. However the power consumption in the capacitive DAC does not scale as well as the digital logic. In this thesis, two energy-efficient DAC switching techniques, Flip DAC and Quaternary capacitor switching, are proposed to reduce their energy consumption. Using these techniques, the energy consumption in the DAC can be reduced by 37 % and 42.5 % compared to the present state-of-the-art. A novel concept of code-independent energy consumption is introduced and emphasized. It mitigates energy consumption degradation with small input signal dynamic range.

Abstract This thesis focuses on the timely problem of energy-efficient transmission for wireless multiantenna cellular systems. The emphasis is on transmit beamforming (BF) and active antenna set optimization to maximize the network-wide energy efficiency (EE) metric, i.e., the number of transmitted bits per energy unit. The fundamental novelty of EE optimization is that it incorporates the transceivers' processing power in addition to the actual transmit power in the BF design. The key features of the thesis are that it focuses on sophisticated power consumption models (PCMs), giving useful insights into the EE of current cellular systems in particular, and provides mathematical tools for EE optimization in future wireless networks generally. The BF problem is first studied in a multiuser multiple-input single-output system by using a PCM scaling with transmit power and the number of active radio frequency (RF) chains. To find the best performance, a globally optimal solution based on a branch-reduce-and-bound (BRB) method is proposed, and two efficient designs based on zero-forcing and successive convex approximation (SCA) are derived for practical applications. Next, joint BF and antenna selection (JBAS) is studied, which can switch off some RF chains for further EE improvements. An optimal BRB method and efficient SCA-based algorithms exploiting continuous relaxation (CR) or sparse BF are proposed to solve the resulting mixed-Boolean nonconvex problem (MBNP). In a multi-cell system, energy-efficient coordinated BF is explored under two optimization targets: 1) the network EE maximization and 2) the weighted sum EEmax (WsumEEmax). A more sophisticated PCM scaling also with the data rate and the associated computational complexity is assumed. The SCA-based methods are derived to solve these problems in a centralized manner, and distributed algorithms relying only on the local channel state information and limited backhaul signaling are then proposed. The WsumEEmax problem is solved using SCA combined with an alternating direction method of multipliers, and iterative closed-form algorithms having easily derivable computational complexity are developed to solve both problems. The work is subsequently extended to a multi-cell multigroup multicasting system, where user groups request multicasting data. For the MBNP, a modeling method to improve the performance of the SCA for solving the CR is proposed, aiming at encouraging the relaxed Boolean variables to converge at the binary values. A second approach based on sparse BF, which introduces no Boolean variables, is also derived. The methods are then modified to solve the EE and sum rate trade-off problem. Finally, the BF design with multiantenna receivers is considered, where the users can receive both unicasting and multicasting data simultaneously. The performances of the developed algorithms are assessed via thorough computer simulations. The results show that the proposed algorithms provide 30-300% EE improvements over various conventional methods in the BF optimization, and that JBAS techniques can offer further gains of more than 100%. / Tiivistelmä Tämä väitöskirja keskittyy ajankohtaiseen energiatehokkaaseen lähetinsuunnitteluun langattomissa solukkoverkoissa, joissa suorituskykymittarina käytetään energiatehokkuuden (energy efficiency (EE)) maksimointia, eli kuinka monta bittiä pystytään lähettämään yhtä energiayksikköä kohti. Työn painopiste on lähettimien keilanmuodostuksen (beamforming (BF)) ja aktiivisten lähetinantennien optimoinnissa. EE-optimoinnin uutuusarvo on ottaa lähettimien prosessoinnin tehonkulutus huomioon keilanmuodostuksen suunnittelussa, varsinaisen lähetystehon lisäksi. Työ antaa hyvän käsityksen erityisesti tämänhetkisten solukkoverkkojen energiatehokkuudesta, ja luo työkaluja EE-optimointiin tulevaisuuden järjestelmissä. Ensin suunnitellaan keilanmuodostus yksisolumallissa, jossa tehonkulutus kasvaa lähetystehon ja aktiivisten radiotaajuusketjujen lukumäärän mukana. Ongelmaan johdetaan optimaalinen ratkaisu, ja kaksi käytännöllistä menetelmää perustuen nollaanpakotukseen tai peräkkäinen konveksi approksimaatio (successive convex approximation (SCA)) -ideaan. Seuraavaksi keskitytään keilanmuodostuksen ja antenninvalinnan yhteisoptimointiin (joint beamforming and antenna selection (JBAS)), jossa radiotaajuusketjuja voidaan sulkea EE:n parantamiseksi. Tähän ehdotetaan optimaalinen menetelmä ja kaksi käytännöllistä SCA-menetelmää perustuen binääristen ja jatkuvien muuttujien yhteisoptimointiongelman relaksaatioon, tai harvan vektorin optimointiin. Monisoluverkon EE-optimoinnissa käytetään yksityiskohtaisempaa tehonkulutusmallia, joka skaalautuu myös datanopeuden ja prosessoinnin monimutkaisuuden mukaan. Työssä käytetään kahta suorituskyvyn mittaria: 1) koko verkon energiatehokkuuden, ja 2) painotettujen energiatehokkuuksien summien maksimointia (weighted sum EEmax (WsumEEmax)). Ensin johdetaan keskitetyt ratkaisut SCA-ideaa käyttäen. Tämän jälkeen keskitytään hajautettuun optimointiin, joka pystytään toteuttamaan paikallisen kanavatiedon avulla, kun matalanopeuksinen skalaariarvojen jako on käytettävissä tukiasemien välillä. Ensin WsumEEmax-ongelma ratkaistaan yhdistämällä SCA ja kerrointen vaihtelevan suunnan menetelmä, ja lisäksi ehdotetaan iteratiivinen suljetun muodon ratkaisu molempiin ongelmiin, joka mahdollistaa tarkan laskennallisen monimutkaisuuden määrityksen. Lopussa työ laajennetaan monisoluverkkoon, jossa tukiasemat palvelevat käyttäjäryhmiä ryhmälähetyksenä. Keskittymällä JBAS-ongelmaan, ensin ehdotetaan lähestymistapa parantaa SCA-menetelmän suorituskykyä yhteisoptimointiongelman relaksaation ratkaisemisessa. Toinen yksinkertaisempi lähestymistapa perustuu harvan vektorin optimointiin, joka ei vaadi binäärisiä muuttujia. Lisäksi menetelmiä muunnellaan myös energiatehokkuuden ja summadatanopeuden kompromissin optimointiin. Lopussa työ ottaa huomioon vielä moniantennivastaanottimet, joka mahdollistaa sekä täsmälähetyksen että ryhmälähetyksen samanaikaisesti. Menetelmien suorituskykyä arvioidaan laajamittaisilla tietokonesimulaatioilla. Tulokset näyttävät väitöskirjan menetelmien lisäävän energiatehokkuutta 30-300% verrattuna lukuisiin perinteisiin menetelmiin BF-optimoinnissa, ja JBAS-menetelmät antavat vielä yli 100% lisää suorituskykyä.

This thesis treats two essentially different subjects: V-cycle schemes are considered in Chapters 2-4, whereas the aggregation-based coarsening is analysed in Chapters 5-6. As a matter of paradox, these two multigrid ingredients, when combined together, can hardly lead to an optimal algorithm. Indeed, a V-cycle needs more accurate prolongations than the simple piecewise-constant one, associated to aggregation-based coarsening. On the other hand, aggregation-based approaches use almost exclusively piecewise constant prolongations, and therefore need more involved cycling strategies, K-cycle <a href=http://www3.interscience.wiley.com/journal/114286660/abstract?CRETRY=1&SRETRY=0>[Num.Lin.Alg.Appl. vol.15(2008), pp.473-487]</a> being an attractive alternative in this respect.<p><br><p><br><p>Chapter 2 considers more precisely the well-known V-cycle convergence theories: the approximation property based analyses by Hackbusch (see [Multi-Grid Methods and Applications, 1985, pp.164-167]) and by McCormick [SIAM J.Numer.Anal. vol.22(1985), pp.634-643] and the successive subspace correction theory, as presented in [SIAM Review, vol.34(1992), pp.581-613] by Xu and in [Acta Numerica, vol.2(1993), pp.285-326.] by Yserentant. Under the constraint that the resulting upper bound on the convergence rate must be expressed with respect to parameters involving two successive levels at a time, these theories are compared. Unlike [Acta Numerica, vol.2(1993), pp.285-326.], where the comparison is performed on the basis of underlying assumptions in a particular PDE context, we compare directly the upper bounds. We show that these analyses are equivalent from the qualitative point of view. From the quantitative point of view,<p>we show that the bound due to McCormick is always the best one.<p><br><p><br><p>When the upper bound on the V-cycle convergence factor involves only two successive levels at a time, it can further be compared with the two-level convergence factor. Such comparison is performed in Chapter 3, showing that a nice two-grid convergence (at every level) leads to an optimal McCormick's bound (the best bound from the previous chapter) if and only if a norm of a given projector is bounded on every level.<p><br><p><br><p>In Chapter 4 we consider the Fourier analysis setting for scalar PDEs and extend the comparison between two-grid and V-cycle multigrid methods to the smoothing factor. In particular, a two-sided bound involving the smoothing factor is obtained that defines an interval containing both the two-grid and V-cycle convergence rates. This interval is narrow when an additional parameter α is small enough, this latter being a simple function of Fourier components.<p><br><p><br><p>Chapter 5 provides a theoretical framework for coarsening by aggregation. An upper bound is presented that relates the two-grid convergence factor with local quantities, each being related to a particular aggregate. The bound is shown to be asymptotically sharp for a large class of elliptic boundary value problems, including problems with anisotropic and discontinuous coefficients.<p><br><p><br><p>In Chapter 6 we consider problems resulting from the discretization with edge finite elements of 3D curl-curl equation. The variables in such discretization are associated with edges. We investigate the performance of the Reitzinger and Schöberl algorithm [Num.Lin.Alg.Appl. vol.9(2002), pp.223-238], which uses aggregation techniques to construct the edge prolongation matrix. More precisely, we perform a Fourier analysis of the method in two-grid setting, showing its optimality. The analysis is supplemented with some numerical investigations. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

Cette thèse porte sur la fonctionnalisation de surface par microstructuration laser. L’étude expérimentale a consisté à texturer des surfaces d’acier inoxydable avec une source laser impulsionnelle à fibre dopée Yb (1030 nm, 300 fs), dans le but de contrôler leur mouillabilité et de les rendre superhydrophobes. Par une optimisation des conditions d’irradiation, il est possible de conférer à la surface une structuration à double échelle de rugosité. Des structures d’une dizaine de micromètres sont réalisées par ablations successives selon un motif de lignes croisées, sur lesquelles se forment des nanostructures auto-organisées. La simulation du couplage de l’énergie dans la cible a permis de déterminer les paramètres opératoires pour limiter l’accumulation thermique en surface. L’étude fait clairement apparaître le rôle de la texturation dans l’apparition du caractère superhydrophobe de la surface, tout en soulignant l’influence des propriétés physico-chimiques du matériau. / This PhD thesis is about surface functionalization by laser microstructuring. The experimental study consists in texturing stainless steel surfaces with a pulsed Yb fibre laser source (1030 nm, 300 fs), in order to control their wettability and confer to them superhydrophobic properties. With an optimization of the irradiating conditions on the target, it is possible to confer to the surface a dual-scale roughness. By successive ablations according to a pattern of crossed lines, microstructures in the range of tens of micrometres are realized, on which self-organized nanostructures are superimposed. Simulation of the energy coupling in the material allows to determine the process parameters to be used, in order to limit the thermal accumulation and avoid the melting of the surface. This study reveals the role of the laser texturing in the apparition of the superhydrophobic character and emphasizes the influence of the physicochemical properties of the material.

Silicon carbide (SiC) integrated circuits (ICs) can enable the emergence of robust and reliable systems, including data acquisition and on-site control for extreme environments with high temperature and high radiation such as deep earth drilling, space and aviation, electric and hybrid vehicles, and combustion engines. In particular, SiC ICs provide significant benefit by reducing power dissipation and leakage current at temperatures above 300 °C compared to the Si counterpart. In fact, Si-based ICs have a limited maximum operating temperature which is around 300 °C for silicon on insulator (SOI). Owing to its superior material properties such as wide bandgap, three times larger than Silicon, and low intrinsic carrier concentration, SiC is an excellent candidate for high-temperature applications. In this thesis, analog and mixed-signal circuits have been implemented using SiC bipolar technology, including bandgap references, amplifiers, a master-slave comparator, an 8-bit R-2R ladder-based digital-to-analog converter (DAC), a 4-bit flash analog-to-digital converter (ADC), and a 10-bit successive-approximation-register (SAR) ADC. Spice models were developed at binned temperature points from room temperature to 500 °C, to simulate and predict the circuits’ behavior with temperature variation. The high-temperature performance of the fabricated chips has been investigated and verified over a wide temperature range from 25 °C to 500 °C. A stable gain of 39 dB was measured in the temperature range from 25 °C up to 500 °C for the inverting operational amplifier with ideal closed-loop gain of 40 dB. Although the circuit design in an immature SiC bipolar technology is challenging due to the low current gain of the transistors and lack of complete AC models, various circuit techniques have been applied to mitigate these problems. This thesis details the challenges faced and methods employed for device modeling, integrated circuit design, layout implementation and finally performance verification using on-wafer characterization of the fabricated SiC ICs over a wide temperature range. / <p>QC 20170905</p>

The developments of new types of conductors and increase of voltage level have driven the need to carry out research on evaluating overhead line acoustic noise. The surface potential gradient of a conductor is a critical design parameter for planning overhead lines, as it determines the level of corona loss (CL), radio interference (RI), and audible noise (AN). The majority of existing models for surface gradient calculation are based on analytical methods which restrict their application in simulating complex surface geometries. This thesis proposes a novel method which utilizes both analytical and numerical procedures to predict the surface gradient. Stranding shape, proximity of tower, protrusions and bundle arrangements are considered within this model. One of UK National Grid's transmission line configurations has been selected as an example to compare the results for different methods. The different stranding shapes are a key variable in determining dry surface fields. The dynamic behaviour of water droplets subject to AC electric fields is investigated by experiment and finite element modelling. The motion of a water droplet is considered on the surface of a metallic sphere. To understand the consequences of vibration, the FEA model is introduced to study the dynamics of a single droplet in terms of phase shift between vibration and exciting voltage. Moreover, the evolution of electric field within the whole cycle of vibration is investigated. The profile of the electric field and the characteristics of mechanical vibration are evaluated. Surprisingly the phase shift between these characteristics results in the maximum field occurring when the droplet is in a flattened profile rather than when it is ‘pointed’.Research work on audible noise emitted from overhead line conductors is reviewed, and a unique experimental set up employing a semi-anechoic chamber and corona cage is described. Acoustically, this facility isolates undesirable background noise and provides a free-field test space inside the anechoic chamber. Electrically, the corona cage simulates a 3 m section of 400 kV overhead line conductors by achieving the equivalent surface gradient. UV imaging, acoustic measurements and a partial discharge detection system are employed as instrumentation. The acoustic and electrical performance is demonstrated through a series of experiments. Results are discussed, and the mechanisms for acoustic noise are considered. A strategy for evaluating the noise emission level for overhead line conductors is developed. Comments are made on predicting acoustic noise from overhead lines. The technical achievements of this thesis are summarized in three aspects. First of all, an FEA model is developed to calculate the surface electric field for overhead line conductors and this has been demonstrated as an efficient tool for power utilities in computing surface electric field especially for dry condition. The second achievement is the droplet vibration study which describes the droplets' behaviour under rain conditions, such as the phase shift between the voltage and the vibration magnitude, the ejection phenomena and the electric field enhancement due to the shape change of droplets. The third contribution is the development of a standardized procedure in assessing noise emission level and the characteristics of noise emissions for various types of existing conductors in National Grid.