Detta examensarbete har utförts på och i samarbete med ITN, Institutionen för Teknik och Naturvetenskap, vid Linköpings Universitet. Problemställningen härrör från tidigare projektsamarbete mellan Linköpings Universitet, Telia AB och Ericsson. Uppgiften består i att ta fram en optimeringsalgoritm som använder sig av ett nytt angreppssätt genom att försöka minska osäkerheten på indata.

Search-based placement methods have long been used for placing integrated circuits targeting the field programmable gate array (FPGA) and standard cell design styles. Such methods offer the potential for high-quality solutions but often come at the cost of long run-times compared to alternative methods. This dissertation examines strategies for enhancing local search heuristics---and in particular, simulated annealing---through the application of directed moves. These moves help to guide a search-based optimizer by focusing efforts on states which are most likely to yield productive improvement, effectively pruning the size of the search space. The engineering theory and implementation details of directed moves are discussed in the context of both field programmable gate array and standard cell designs. This work explores the ways in which such moves can be used to improve the quality of FPGA placements, improve the robustness of floorplan repair and legalization methods for mixed-size standard cell designs, and enhance the quality of detailed placement for standard cell circuits. The analysis presented herein confirms the validity and efficacy of directed moves, and supports the use of such heuristics within various optimization frameworks.

There is significant interest in the synthesis of discrete-state random fields, particularly those possessing structure over a wide range of scales. However, given a model on some finest, pixellated scale, it is computationally very difficult to synthesize both large and small-scale structures, motivating research into hierarchical methods. This thesis proposes a frozen-state approach to hierarchical modelling, in which simulated annealing is performed on each scale, constrained by the state estimates at the parent scale. The approach leads significant advantages in both modelling flexibility and computational complexity. In particular, a complex structure can be realized with very simple, local, scale-dependent models, and by constraining the domain to be annealed at finer scales to only the uncertain portions of coarser scales, the approach leads to huge improvements in computational complexity. Results are shown for synthesis problems in porous media.

The objective of this work is to investigate the influence of hot rolling process on the mechanical properties of AA 5052 aluminum alloy. Hot-rolled band fabricated by tandem mill (hot-band A) will be compared with that fabricated by reverse mill hot-band C). Optical microscopic observations revealed that hot-band A has a uniform microstructure throughout the thickness, while hot-band C exhibits non-uniform microstructure, fine grains near the surface and coarser grains in the center. Both hot-bands were subjected to cold-rolling and annealing to O-temper. Two annealing processes were used: (a) annealing in 500oC salt bath, which may simulate the high heating rate of continuous annealing line (CAL), and (b) annealing in 320oC conventional air furnace with heating rate of 30oC/h, which may simulate the slow heating rate of batch-type annealing. In general, both materials annealed in 320oC air furnace exhibit higher yield strength than those annealed in 500oC salt bath do, however, both materials exhibit better tensile ductility after annealed in 500oC salt bath as compared with those annealed in 320oC air furnace.TEM examinations indicated that the cold-rolled sheet after annealing in 320oC air furnace contains larger number of precipitates comparing with its 500oC salt bath annealed counterpart. This observation may account for the higher yield strength of cold-rolled sheet annealed in 320oC air furnace. After cold-rolling and annealing in 320oC air furnace, the material C shows higher yield strength than the material A does. However, after annealing in 500oC salt bath, both materials have similar yield strength. XRD pole-figure analysis indicated that hot-band A exhibited stronger texture than hot-band C did. The texture intensity for both materials decreased considerably after cold-rolling and annealing. Orientation image mapping (OIM) obtained by EBSD (electron backscattered diffraction) analysis indicated that the grain boundaries in both materials after cold-rolling and annealing were mainly high angle boundaries, and the 500oC salt bath annealed specimens have more equiaxed grain shape as compared with the 320oC air furnace annealed specimens.

Optimization methods have been developed and refined throughout many scientific fields of study. This work utilizes one such developed technique of optimization called simulated annealing to produce optimal operation parameters for a 15x15 fuel assembly to be used in an operating nuclear power reactor. The two main cases of optimization are: one that finds the optimal 235U enrichment layout of the fuel pins in the assembly and another that finds both the optimal 235U enrichments where gadolinium burnable absorber pins are also inserted. Both of these optimizations can be performed by coupling Adaptive Simulated Annealing to TransLAT which successfully searches the optimization space for a fuel assembly layout that produces the minimized pin power peaking factor. Within given time constraints this package produces optimal layouts within a given set of assumptions and constraints. Each layout is forced to maintain the fuel assembly average 235U enrichment as a constraint. Reductions in peaking factors that are produced through this method are on the order of 2% to 3% when compared to the baseline results. As with any simulated annealing approach, families of optimal layouts are produced that can be used at the engineer’s discretion.

The Co-Cu nanoparticles is one of the magnetic materials that have considerable potential for a variety of industrial applications, including giant magnetoresistance (GMR) digital storage devices and have therefore attracted a great deal of attention in recent years. For this reason, it will be an important reference to the development of the magnetic digital storage devices if we can go deep into study the material properties of the Co-Cu nanoparticles. This study uses molecular dynamics simulations to investigate the crystalline process of Co-Cu nanoparticles of high and low Co concentrations (5~25 %) during the annealing process. The modified many-body tight binding potential is adopted to accurately model the Cu-Cu, Co-Co, and Co-Cu pair inter-atomic interactions. The structural transformations at the upper and lower melting points are observed by the radial distribution function (RDF), the angle correction function (ACF) and the average bond lengths. finally, we employs molecular dynamics simulations to predict the distribution function of diluted magnetic Co atoms in a Cu host and then uses the the Ruderman-Kittel-Kasuya-Yosida (RKKY) theory and quantum magnetism theory to calculate the magnetic properties of the Co-Cu alloys at different temperature, including their Curie temperature.

The main purpose of this thesis is to estimate the signal arrival time in low rate wireless personal area network systems. In a dense multipath environment, the generalized maximum-likelihood (GML) algorithm can be used for the time-of-arrival (TOA) estimation. Nevertheless, the GML algorithm is very time-consuming and usually takes a long period of time, and sometimes fails to converge. Hence, a simplified scheme that would improve the algorithm is investigated. In the simplified scheme, the search is executed in a sequential form. Two threshold parameters are determined for the stop condition in the algorithm. One threshold is on the arrival time of estimated path, while the other is on the fading amplitude of estimated path. The determination of thresholds can be based on the minimum error probability, which is defined as the sum of the false alarm probability and the missing probability. Root-mean-square error statistics are used to improve the thresholds setting. In this scheme, candidate pairs of thresholds are evaluated in each appropriate range. To solve the problem that the root-mean-square error value for each pair of thresholds is calculated, the simulated annealing is adopted for searching the best threshold pair. The problem that all possible solutions in a large range must be evaluated can be solved by simulated annealing. From the simulation results, it is seen that, while the signal-to-noise ratio is larger or equal to 4dB, the proposed scheme can achieve better performance than the root-mean-square error statistics scheme.

The main purpose of this thesis is to combine modified GML algorithm with 2-D simulated annealing for estimation of signal arrival time in the UWB systems.In a dense multipath environment, the generalized maximum-likelihood (GML) algorithm can be used for the time-of-arrival (TOA) estimation. Nevertheless, the GML algorithm usually takes a long period of time, and sometimes fails to converge. Hence, a modified GML (MGML) algorithm is investigated. Two threshold parameters need to be determined in using the estimation algorithm. One threshold is to decide the arrival time range of estimated path, and the other, an amplitude threshold, is to judge whether the estimated path is true. Generally, the decision rule of thresholds may be based on the minimum error probability, which is defined as the sum of false alarm probability and miss probability. To mitigate the effects from noise and dense multipath interference, and to reduce the computational complexity of the algorithm, a method of threshold settings based on the minimum root mean square error (RMSE) criteria is discussed. In this scheme, the RMSE value for each candidate threshold pair in an appropriate region is computed. Constructing an accurate RMSE table and performing a full-scale grid search of adequate threshold settings can be very time-consuming. A 2-D simulated annealing process is adopted for finding the best pair of thresholds for use in the modified GML algorithm. The simulated annealing, different from the gradient descent, can avoid trapping into a local minimum in finding the best threshold pair. The resulting threshold pair makes the modified GML algorithm become more efficient in estimating the signal arrival time with an automatic search manner. Simulation results show that the proposed scheme can achieve better performance than the grid search approaches in UWB environments.

The manual trial and error has been widely used in the past, but such approach is inefficient. In recent years, many heuristic algorithms used in a wide range of applications have been developed. These algorithms have more efficiency than traditional ones, because they can locate the best solution. Every algorithm has its own niche application in different problems. In this study, the boundary parameters of the hydrodynamic-based tidal model are calibrated by using the Simulated Annealing algorithms (SA). The objective is to minimize the deviation between the estimated results acquired from the simulation model and the real tidal data along Taiwan coast. Based on the real physics distribution of the boundary parameters, we aimed to minimize the sum of each station¡¦s root mean square error (RMSE). Genetic Algorithms (GAs) and Simulated Annealing Algorithms on parameters calibration for tidal model are compared under the same condition. GAs is superior on solving the problems mentioned above while both algorithms showed improved results. By setting the initial solution derived from GAs, the solving efficiency of SA can be improved in this study.

Recently, wet sand blasting on coated cutting tool inserts has drawn interest to the tooling industry due to its positive effects on cutting performance and tool life. This performance boost has partly been attributed to the buildup of compressive residual stresses in the coating during the blasting process. However, the mechanism of forming residual stresses in ceramic coatings during sand blasting is not fully understood. This work utilize x-ray diffraction as the main tool to study the formation and relaxation of residual stresses after wet sand blasting and annealing on 001, 012 and 110 textured α-Al2O3 coatings. To minimize the influence of stress gradients in the samples, all stress measurements were set up with a fixed analysis depth of 2 µm. Sand blasting was made with an alumina based slurry at 2, 3.2 and 4 bar pressure and the anneal was done at temperatures from 400 to 1000 °C for 2 hours or more. The coating hardness was evaluated by nanoindentation. Finally, the activation energy for the relaxation of residual stresses was estimated using the Zener-Wert-Avrami function. The results reveal the highest compressive residual stress with up to -5.3 GPa for the 012 texture while the stresses for the 001 and 110 textures peaked at -3.1 and -2.0 GPa, respectively. Further, a hardness gradient was present after blasting of the 001 and 012 textured samples indicating a higher stress at the surface of the coating. The 110 textured sample is the most brittle resulting in flaking of the coating during sand blasting. The different deformation mechanisms are related to difference in active slip planes between coatings with different textures. Both the stress and hardness decreased after heat treatment and the activation energy for stress relaxation was found to be as 1.1 ± 0.3 eV, 1.9 ± 0.2 eV and 1.2 ± 0.1 eV for the 001, 012 and 110 textures, respectively.