Because current full‐core neutronic‐calculations use two‐group neutron diffusion and rely on homogenizing fuel assemblies, reconstructing pin powers from such a calculation is an elaborate and not very accurate process; one which becomes more difficult with increased core heterogeneity. A three‐dimensional Heterogeneous Finite Element Method (HFEM) is developed to address the limitations of current methods by offering fine‐group energy representation and fuel‐pin‐level spatial detail at modest computational cost. The calculational cost of the method is roughly equal to the calculational cost of the Finite Differences Method (FDM) using one mesh box per fuel assembly and a comparable number of energy groups. Pin‐level fluxes are directly obtained from the method’s results without the need for reconstruction schemes. / UOIT

discrete parts manufacturing industries. We are motivated by the production environment of Roketsan Missiles Industries Incorporation, operating at Turkish defense industry. Our objective is to minimize the total weighted completion times of the jobs in the system. We formulate the problem as a mixed integer linear program and find that our model could find optimal solutions only to small sized problem instances. For medium and large sized problem instances, we develop heuristic algorithms with high quality approximate solutions in reasonable solution time. Our proposed heuristic algorithm has hierarchical approach and benefits from optimization models and priority rules. We improve the heuristic method via best move with non-blocking strategy and design several experiments to test the performances. Our computational results have revealed that proposed heuristic algorithm can find high quality solutions to large sized instances very quickly.

We consider a (generally, non-coercive) mixed boundary value problem in a bounded domain for a second order elliptic differential operator A. The differential operator is assumed to be of divergent form and the boundary operator B is of Robin type. The boundary is assumed to be a Lipschitz surface. Besides, we distinguish a closed subset of the boundary and control the growth of solutions near this set. We prove that the pair (A,B) induces a Fredholm operator L in suitable weighted spaces of Sobolev type, the weight function being a power of the distance to the singular set. Moreover, we prove the completeness of root functions related to L.

The use of relays is seen as a promising way to extend cell coverage and increase rates in LTE Advanced networks. Instead of increasing the number of base stations (BS), relays with lower cost could provide similar gains. A relay will have a wireless link to the closest BS as only connection to the core network and will cover areas close to the cell edge or other areas with limited rates. Performing transmissions in several hops (BS-relay & relay-user) requires more radio resources than using direct transmission. This thesis studies how the available radio resources should be allocated between relays and users in order to maximize throughput and/or fairness. Time and frequency multiplexed backhaul is investigated under a full buffer traffic assumption. It is shown that the system will be backhaul limited and that the two ways of multiplexing will perform equally when maximising throughput and/or fairness. The analysis results in a set of throughput/fairness suboptimal solutions, dependant on how many relays are used per cell. The results are verified by simulations, which also show the limiting effects on throughput caused by interference between relays. It is also analysed how the resource allocation should be done given non-fullbuffer traffic. A resource allocation that minimises packet delay given a certain number of relays per cell is presented. The analysis is based on queuing theory. Finally some different schedulers and their suitability for relay networks are discussed. Simulation results are shown, comparing the throughput and fairness of Round Robin, Weighted Round Robin, Proportional Fairness and Weighted Proportional Fairness schemes. It is shown that allocating the resource among the relays according to the number of users served by the relays improves the fairness.

The increasing usage of information technology in military affairs raises the need for robust high capacity radio networks. The network will be used to provide several different types of services, for example group calls and situation awareness services. All services have specific demands on packet delays and packet losses in order to be fully functional, and therefore there is a need for a Quality of Service (QoS) mechanism in the network. In this master thesis we examine the possibility to provide a QoS mechanism in Ad Hoc networks by using priority queues. The study includes two different queuing schemes, namely fixed priority queuing and weighted fair queuing. The performance of the two queuing schemes are evaluated and compared with respect to the ability to provide differentiation in network delay, i.e., provide high priority traffic with lower delays than low priority traffic. The study is mainly done by simulations, but for fixed priority queuing we also derive a analytical approximation of the network delay. Our simulations show that fixed priority queuing provides a sharp delay differentiation between service classes, while weighted fair queuing gives the ability to control the delay differentiation. One of those queuing schemes alone might not be the best solution for providing QoS, instead we suggest that a combination of them is used.

When we want to solve electromagnetic problems, the Finite Difference Time Domain (FDTD) method is a very useful numerical simulation technique to solve these problems. However, the traditional FDTD method is an explicit finite-difference scheme, so the method is limited by the Courant-Friedrich-Levy (CFL) stability condition. In other words, the minimum cell size will limit the maximum time-step size in a computational domain. Therefore, while simulating structures of fine scale dimensions, it will relatively result in a prohibitively high computation time generated by the maximum time-step size. The WLP-FDTD is based on the Weighted Laguerre Polynomials technique and the traditional FDTD algorithm. It is an implicit finite-difference equations. Therefore, it can completely avoid the stability constraint, and then improve calculation time by choosing relatively large time-step. In this thesis, we incorporate non-uniform grid method into the WLP-FDTD. By using them to simulate the structures of fine scale dimensions can reduce the computation time and memory usage. Further, we extend this method from two-dimensional to three-dimensional and add loss media into original formulations that will make the application of this method more widely.

In this thesis, we propose a model which applies the genetic programming (GP) to train the profitable and stable trading strategy in the training period, and then the strategy is applied to trade stocks in the testing period. The variables for GP in our models include 6 basic information and 25 technical indicators. We perform our models on Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) from 2000/9/14 to 2010/5/21, approximately ten years. We conduct five experiments. In these experiments, we find that the trading strategies generated by GP with two arithmetic trees have more stable returns. In addition, if we obtain the trading strategies in three historical periods which are the most similar to the current training period, we earn higher return in the testing periods. In each experiment, 24 cases are considered, with training periods of 90, 180, 270, 365, 455, 545, 635 and 730 days, and testing periods of 90, 180 and 365 days, respectively. The testing period is rolling updated until the end of the experiment period. The best cumulative return 165.30\% occurs when 730-day training period pairs with 365-day testing period, which is much higher than the return of the buy-and-hold strategy 1.19\%.

In this dissertation, the generalized score tests based on weighted estimating equations are proposed for missing covariate data. Their properties, including the effects of nuisance functions on the forms of the test statistics and efficiency of the tests, are investigated. Different versions of the test statistic are properly defined for various parametric and semiparametric settings. Their asymptotic distributions are also derived. It is shown that when models for the nuisance functions are correct, appropriate test statistics can be obtained via plugging the estimates of the nuisance functions into the appropriate test statistic for the case that the nuisance functions are known. Furthermore, the optimal test is obtained using the relative efficiency measure. As an application of the proposed tests, a formal model validation procedure is developed for generalized linear models in the presence of missing covariates. The asymptotic distribution of the data driven methods is provided. A simulation study in both linear and logistic regressions illustrates the applicability and the finite sample performance of the methodology. Our methods are also employed to analyze a coronary artery disease diagnostic dataset.

In the present study, a fifth-order weighted essentially non-oscillatory (WENO) scheme was built for solving the surface-capturing level-set equation. Combined with the level-set equation, the three-dimensional Reynolds averaged Navier-Stokes (RANS) equations were employed for the prediction of nonlinear wave-interaction and wave-breaking phenomena over sloping beaches. In the level-set finite-analytic Navier-Stokes (FANS) method, the free surface is represented by the zero level-set function, and the flows are modeled as immiscible air-water two phase flows. The Navier-Stokes equations for air-water two phase flows are formulated in a moving curvilinear coordinate system and discretized by a 12-point finite-analytical scheme using the finite-analytic method on a multi-block over-set grid system. The Pressure Implicit with Splitting of Operators / Semi-Implicit Method for Pressure-Linked Equation Revised (PISO/SIMPLER) algorithm was used to determine the coupled velocity and pressure fields. The evolution of the level-set method was solved using the third-order total variation diminishing (TVD) Runge-Kutta method and fifth-order WENO scheme. The accuracy was confirmed by solving the Zalesak's problem. Two major subjects are discussed in the present study. First, to identify the WENO scheme as a more accurate scheme than the essentially non-oscillatory scheme (ENO), the characteristics of a nonlinear monochromatic wave were studied systematically and comparisons of wave profiles using the two schemes were conducted. To eliminate other factors that might produce wave profile fluctuation, different damping functions and grid densities were studied. To damp the reflection waves efficiently, we compared five damping functions. The free-surface elevation data collected from gauges distributed evenly in a numerical wave tank are analyzed to demonstrate the damping effect of the beach. Second, as a surface-tracking numerical method built on curvilinear coordinates, the level-set RANS model was tested for nonlinear bichromatic wave trains and breaking waves on a sloping beach with a complex free surface. As the wave breaks, the velocity of the fluid flow surface became more complex. Numerical modeling was performed to simulate the two-phase flow velocity and its corresponding surface and evolution when the wave passed over different sloping beaches. The breaking wave test showed that it is an efficient technique for accurately capturing the breaking wave free surface. To predict the breaking points, different wave heights and beach slopes are simulated. The results show that the dependency of wave shape and breaking characteristics to wave height and beach slope match the results provided by experiments.

We propose an algebraic construction of $(d+1)$-point $D$-optimal designs for $d$th degree polynomial regression with weight function $omega(x)ge 0$ on the interval $[a,b]$. Suppose that $omega'(x)/omega(x)$ is a rational function and the information of whether the optimal support contains the boundary points $a$ and $b$ is available. Then the problem of constructing $(d+1)$-point $D$-optimal designs can be transformed into a differential equation problem leading us to a certain matrix including a finite number of auxiliary unknown constants, which can be solved from a system of polynomial equations in those constants. Moreover, the $(d+1)$-point $D$-optimal interior support points are the zeros of a certain polynomial which the coefficients can be computed from a linear system. In most cases the $(d+1)$-point $D$-optimal designs are also the approximate $D$-optimal designs.