Time of Flight Diffraction (TOFD) is one of the most accurate ultrasonic methods for crack detection and sizing in pipeline girth welds. Its performance, however, is limited by the temporal resolution of the signal. In this thesis, we develop a signal processing method based on autoregressive spectral extrapolation to improve the temporal resolution of ultrasonic signals. The original method cannot be used in industrial applications since its performance is highly dependent on selection of a number of free parameters. This method is modified by optimizing its various steps and limiting the number of free parameters, and an automated algorithm for selection of values for the remaining free parameters is proposed based on the analysis of a large set of synthetic signals. The performance of the final algorithm is evaluated using experimental data; it is shown that the uncertainty in crack sizing accuracy can be reduced by as much as 80%. Furthermore, the proposed method is shown to be capable of resolving overlapping echoes; therefore, smaller cracks that have echoes that are not clearly resolved in the raw signal, can be detected and sized in the enhanced signal.

Time of Flight Diffraction (TOFD) is one of the most accurate ultrasonic methods for crack detection and sizing in pipeline girth welds. Its performance, however, is limited by the temporal resolution of the signal. In this thesis, we develop a signal processing method based on autoregressive spectral extrapolation to improve the temporal resolution of ultrasonic signals. The original method cannot be used in industrial applications since its performance is highly dependent on selection of a number of free parameters. This method is modified by optimizing its various steps and limiting the number of free parameters, and an automated algorithm for selection of values for the remaining free parameters is proposed based on the analysis of a large set of synthetic signals. The performance of the final algorithm is evaluated using experimental data; it is shown that the uncertainty in crack sizing accuracy can be reduced by as much as 80%. Furthermore, the proposed method is shown to be capable of resolving overlapping echoes; therefore, smaller cracks that have echoes that are not clearly resolved in the raw signal, can be detected and sized in the enhanced signal.

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Based on the recent successes in stochastic linear programming and mixed integer programming, in this thesis we combine these two important areas of mathematical programming; specifically we study stochastic integer programming. We first study a simple and important stochastic integer programming problem, called stochastic uncapacitated lot-sizing (SLS), which is motivated by production planning under uncertainty. We describe a multi-stage stochastic integer programming formulation of the problem and develop a family of valid inequalities, called the (Q, S) inequalities. We establish facet-defining conditions and show that these inequalities are sufficient to describe the convex hull of integral solutions for two-period instances. A separation heuristic for (Q, S) inequalities is developed and incorporated into a branch-and-cut algorithm. A computational study verifies the usefulness of the inequalities as cuts. Then, motivated by the polyhedral study of (Q, S) inequalities for SLS, we analyze the underlying integer programming scheme for general stochastic integer programming problems. We present a scheme for generating new valid inequalities for mixed integer programs by taking pair-wise combinations of existing valid inequalities. The scheme is in general sequence-dependent and therefore leads to an exponential number of inequalities. For some special cases, we identify combination sequences that lead to a manageable set of all non-dominated inequalities. For the general scenario tree case, we identify combination sequences that lead to non-dominated inequalities. We also analyze the conditions such that the inequalities generated by our approach are facet-defining and describe the convex hull of integral solutions. We illustrate the framework for some deterministic and stochastic integer programs and we present computational results which show the efficiency of adding the new generated inequalities as cuts.

Advances in computational power have produced great strides in the later design and production portions of an aircraft s life cycle, and these advances have included the internal layout component of the design and manufacturing process. However, conceptual and preliminary design tools for internal layout remain primarily based on historical regressions and estimations a situation that becomes untenable when considering revolutionary designs or component technologies. Bringing internal layout information forward in the design process can encourage the same level of benefits enjoyed by other disciplines as advances in aerodynamics, structures and other fields propagate forward in the design of complex systems. Accurate prediction of the volume required to contain all of an aircraft s internal components results in a more accurate prediction of aircraft specifications, mission effectiveness, and costs, helping determine if an aircraft is the best choice for continued development. This is not a computationally simple problem, however, and great care must be taken to ensure the efficiency of any proposed solution. Any solution must also address the uncertainty inherent in describing internal components early in the design process. Implementing a methodology that applies notions of an intelligent search for a solution, as well as deals robustly with component sizing, produces a high chance of success. Development of a robust, rapid method for assessing the volumetric characteristics of an aircraft in the context of the conceptual and preliminary design processes can offer many of the benefits of a complete internal layout without the immense assignment of resources typical in the detail phase of the design process. A simplified methodology for volumetrically sizing an aircraft is presented here as well as an assessment of the state-of-the-art techniques for volumetric considerations used in current aircraft design literature. A prototype tool using a combination of original code and publicly available libraries is developed and explored. A sample aircraft design is undertaken with the prototype tool to demonstrate the effectiveness of the methodology.

Thesis (Ph. D.)--Institute of Paper Chemistry, 1942. / Includes bibliographical references (p. 83-86).

Ultra-deep submicron circuits require accurate modeling of gate delay in order to meetaggressive timing constraints. With the lack of statistical data, variability due to the mechanical manufacturing process and its chemical properties poses a challenging problem. Discrete gate sizing requires (i) accurate models that take into account random parametric variation and (ii) a fair allocation of resources to optimize the solution. The proposed GTFUZZ gate sizing algorithm handles both tasks. Gate sizing is modeled as a resource allocation problem using fuzzy game theory. Delay is modeled as a constraint and power is optimized in this algorithm. In GTFUZZ, delay is modeled as a fuzzy goal with fuzzy parameters to capture the imprecision of gate delay early in the design phase when extensive empirical data is absent. Dynamic power is modeled as a fuzzy goal without varying coefficients. The fuzzy goals provide a flexible platform for multimetric optimization. The robust GTFUZZ algorithm is compared against fuzzy linear programming (FLP) and deterministic worst-case FLP (DWCFLP) algorithms. The benchmark circuits are first synthesized, placed, routed, and optimized for performance using the Synopsys University 32/28nm standard cell library and technology files. Operating at the optimized clock frequency, results show an average power reduction of about 20% versus DWCFLP and 9% against variation-aware gate sizing with FLP. Timing and timing yield are verified by both Synopsys PrimeTime and Monte Carlo simulations of the critical paths using HSPICE.

This thesis work was done in order to improve the capabilities in a preliminary aircraft analysis program, DIBA, at Saab Aerosystems. The areas that this was done are in the sizing and balance. One sizing tool was developed in order to make a performance analysis with the DIBA generated geometry and customer and/or regulation based criteria. A balance diagram, a neutral point estimation function, a landing gear plot and a trim program was created in order to extend the weight and balance analysis. Results show that various aircraft both military and civil can be analyzed with good comparison to other analysis and reality. For example EXCEL implemented analysis and graphs over real aircrafts shown in the report.

Edge wicking, i.e. in-plane wetting, is an important parameter for liquid packaging board products. Before filling of the products at the dairy the web is being sterilised with hydrogen peroxide (H2O2). A tube is shaped and cut into packages which mean that new surfaces are created. If a short stop occurs in the sterilising bath the raw edges exposed to H2O2 could absorb the liquid and when the package later is being filled this absorption could lead to tube burst. For the end products it is also important to prevent the liquid from penetrating the raw edges of the board in order to maintain the functionality and fresh look of the package. To control edge wicking different kinds of internal hydrophobic sizing agents are used. Alkyl ketene dimer (AKD) is the most common size in neutral sizing and rosin in conjunction with alum is the traditional acidic sizing agent. AKD and rosin size are often used in combination (dual sizing) to make the board hydrophobic. The objective of this work was to examine the effects of the sizing agents on different pulps in different dosages. The pulps used in the sheet preparation were unbleached kraft pulp as well as bleached and unbleached CTMP refined to different levels. Apart from varying the size dosages, the wet sheets were also pressed at different levels to vary the density. The major part of the study included dual sizing but a minor part also concerned mono sized sheets. The parameters investigated on the laboratory sheets were STFI-Density, hydrogen peroxide edge wicking, pressurised edge wicking, lactic acid edge wicking (LA) and AKD and rosin size content. In hydrogen peroxide edge wicking the amount of size was the central source of improved wick index. The retention was therefore of great significance for the results. The dual sized sheets were found to give least edge wicking, due to the synergy effect between AKD and alum rosin size. The kraft pulps gave sheets with satisfactory edge wicking even at the lowest size dosage (1 kg/t) while CTMP required a dosage of 4 kg/t to reach the same wick index. To achieve acceptable pressurised edge wicking values the most important parameter was found to be the density of the sheets. The kraft pulp sheets gave the lowest edge penetration while the high freeness CTMP sheets did not give satisfactory penetration resistant even at the highest size dosage. The edge wicking of lactic acid could be prevented by sizing with AKD only. Sheets made from mono sized sheets containing rosin size did not manage to avoid a large in-plane wetting of the board structure. Hence, dual sizing to improve the edge wicking of lactic acid is not necessary. The density was found not to be an important parameter in lactic acid edge wicking, all the pulps got equal edge wicking regardless of density. Retention above 1 kg/t AKD in sheets was enough to prevent penetration. Retention above 1.5 kg/t AKD in sheet did not improve the edge wicking any further. No significant difference in sizeability between unbleached and bleached CTMP was observed.

Emerging financial and environmental challenges associated with conventional power sources have increased global interest in consuming unpolluted, renewable energy sources for irrigation sector. Solar energy may be an attractive choice in this regard due to its strong influence on crop water use and related energy requirement. However, a comprehensive approach for a reliable and economically viable photovoltaic (PV) system design to produce energy from solar source is required to accurately explore its potential. This thesis describes the development and application of a reliability assessment model, identifies a suitable solar irrigation management scheme, and provides guidelines for evaluating economic viability of a solar-powered center pivot irrigation system. The reliability model, written in MATLAB, was developed based on the loss of power supply probability (LPSP) technique in which various sub-models for estimating energy production, energy requirement and energy storage were combined. The model was validated with actual data acquired from the study site located at Outlook, Saskatchewan, Canada and an excellent agreement was found. For example, normalized root mean square error (NRMSE) for the battery current was found to be 0.027. Irrigation management strategies (irrigation depth, frequency and timing) were investigated by comparing the PV system sizing requirement for a conventional (25-35 mm per application) and for a frequent light irrigation management strategy (5-8 mm per application). The results suggest that the PV sizing can be reduced significantly by adopting frequent light irrigations which utilize the power as it is produced during daylight hours, rather than relying on stored energy. The potential of a solar-powered center pivot irrigation system was revealed for three different crops (canola, soybean and table potato) at the site by conducting a detailed economic analysis for the designed PV system. High value crops with moderate water requirements such as table potatoes appeared to be the most feasible choice for the study site. However, the potential may greatly vary for different crops in altered locations due to management, agronomic, climate, social, and economic variations. It can be concluded that a holistic approach described here can be used as a tool for designing an appropriate PV powered center pivot irrigation system under variable operating and meteorological conditions. Furthermore, its potential can be accurately explored by conducting a detailed economic analysis for a given location, considering different available crop choices.