To be competitive in the market, it is very important to design cost effective and reliable products. For this purpose, it is necessary to consider reliability as an integral part of the design procedure. Therefore, reliability which is a design parameter that affects cost and safety of a system should be taken into consideration in early phases since it is very difficult to change design at the later phases. Reliability of a rocket motor can be evaluated by reliability testing but these tests are very expensive and difficult since the tests are destructive and test sample size is determined by the binomial law. Because of the difficulties in reliability testing, in early design phases reliability can be evaluated by using reliability prediction results. This thesis report includes application of probabilistic approach for a solid rocket motor design to evaluate its reliability in preliminary design phase. In this study, it is aimed to assess the solid rocket motor ballistic performance reliability and casing structural reliability, determine important parameters affective on the solid rocket motor reliability and find a new design point to improve the reliability. Variations in dimensions and material properties are considered as the sources of failures and the limit states for acceleration, total impulse and maximum stress in the casing are approximated with response surface method by considering these variations. With the response surface functions, Monte Carlo simulation is used to assess failure probability and distributions of the rocket motor performance. Besides the assessment of the reliability, capability of the response surface functions to estimate the rocket motor performance and effects of the input parameters on the rocket motor performance and performance variation are also examined. By considering the effect of the input parameters, a new design point is proposed to decrease the total probability of failure.

The thesis gives overview of complex aerodynamic optimization approach applied to business-jet aircraft wing design. Response surface method (RSM) potential was explored particularly. The efficiency of RSM approach for CFD based aerodynamic optimization was demonstrated. Basic structural requirements were successfully integrated to optimization – real multidisciplinary problem was solved. Some methods for evaluation of forces distribution along wingspan were explored. Thesis was solving within the frame of 6th EU FP integrated project CESAR.

This thesis deals with different optimization problems encountered in organic synthesis. The use of response surface, sequential simplex and PLS techniques, for simultanious optimization of yield and suppression of side reactions is investigated. This is illustrated by an example of enamine synthesis, were a side reaction was a serious problem. The problem of efficient screening to find suitable catalysts and solvents in new reactions is also investigated. Here, the use of principal properties as selection criterion, is demonstrated with a new process for the silylation of a,ß-unsaturated ketones. The extension of the new method to bis silylation of 1,2- and 1,3-diketones is demonstrated. The total synthesis of (±)-geosmin is investigated by an approach aimed to reduce the number of necessary steps involved. The suggested strategy, is to find compatible solvents through several transformations in the sequence to accomplish one-pot multistep reactions. In this context an improved method for the preparation of 1,10-dimethyl-l(9)-octalone-2 was established. Comparison with previously reported total syntheses of (±)-geosmin was done. / digitalisering@umu

A novel concept of multiple deterministic analyses is proposed to design safer and more damage-tolerant structures, particularly when excited by dynamic including seismic loading in time domain. Since the presence of numerous sources of uncertainty cannot be avoided or overlooked, the underlying risk is estimated to compare design alternatives. To generate the implicit performance functions explicitly, the basic response surface method is significantly improved. Then, several surrogate models are proposed. The advanced factorial design and Kriging method are used as the major building blocks. Using these basic schemes, seven alternatives are proposed. Accuracies of these schemes are verified using basic Monte Carlo simulations. After verifying all seven alternatives, the capabilities of the three most desirable schemes are compared using a case study. They correctly identified and correlated damaged states of structural elements in terms of probability of failure using only few hundreds of deterministic analyses. The modified Kriging method appears to be the best technique considering both efficiency and accuracy. Estimating the probability of failure, the post-Northridge seismic design criteria are found to be appropriate. After verifying the proposed method, a Site-Specific seismic safety assessment method for nonlinear structural systems is proposed to generate a suite of ground excitation time histories. The information of risk is used to design a structure more damage-tolerant. The proposed procedure is verified and showcased by estimating risks associated with three buildings designed by professional experts in the Los Angeles area satisfying the post-Northridge design criteria for the overall lateral deflection and inter-story drift. The accuracy of the estimated risk is again verified using the Monte Carlo simulation technique. In all cases, the probabilities of collapse are found to be less than 10% when excited by the risk-targeted maximum considered earthquake ground motion satisfying the intent of the code. The spread in the reliability indexes for each building for both limit states cannot be overlooked, indicating the significance of the frequency contents. The inter story drift is found to be more critical than the overall lateral displacement. The reliability indexes for both limit states are similar only for few cases. The author believes that the proposed methodology is an alternative to the classical random vibration and simulation approaches. The proposed site-specific seismic safety assessment procedure can be used by practicing engineers for routine applications. The proposed reliability methodology is not problem-specific. It is capable of handling systems with different levels of complexity and scalability, and it is robust enough for multi-disciplinary routine applications. In order to show the multi-disciplinary application of the proposed methodology, the probability of failure of lead-free solders in Ball Grid Array 225 surface-mount packaging for a given loading cycle is estimated. The accuracy of the proposed methodology is verified with the help of Monte Carlo simulation. After the verification, probability of failure versus loading cycles profile is calculated. Such a comprehensive study of its lifetime behavior and the corresponding reliability analyses can be useful for sensitive applications.

In industrial processes decreasing variation is very important while achieving the targets. For manufacturers, finding out optimal settings of product and process parameters that are capable of producing desired results under great conditions is crucial. In most cases, the quality response is measured on a continuous scale. However, in some cases, the desired quality response may be qualitative (categorical). There are many effective methods to design robust products/process through industrial experimentation when the response variable is continuous. But methods proposed so far in the literature for robust design with categorical response variables have various limitations. This study offers a simple and effective method for the analysis of categorical response data for robust product or process design. This method handles both location and dispersion effects to explore robust settings in an effective way. The method is illustrated on two cases: A foam molding process design and an iron-casting process design.

Structural Reliability treats uncertainties in structural design systematically, evaluating the levels of safety and serviceability of structures. During the past decades, it has been established as a valuable design tool for the description of the performance of structures, and lately stands as a basis in the background of the most of the modern design standards, aiming to achieve a uniform behaviour within a class of structures. Several methods have been proposed for the estimation of structural reliability, both deterministic (FORM and SORM) and stochastic (Monte Carlo Simulation etc) in nature. Offshore structures should resist complicated and, in most cases, combined environmental phenomena of greatly uncertain magnitude (eg. wind, wave, current, operational loads etc). Failure mechanisms of structural systems and components are expressed through limit state functions, which distinguish a failure and a safe region of operation. For a jacket offshore structure, which comprises of multiple tubular members interconnected in a three dimensional truss configuration, the limit state function should link the actual load or load combination acting on it locally, to the response of each structural member. Cont/d.

Artificial Neural Network (ANN) ensemble and Response Surface Method (RSM) surrogate models were generated from Finite Element (FE) simulations to predict the overpressure load and vehicle impact response of a novel rapidly deployable protective structure. A Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was used in conjunction with the surrogate models to determine structure topology input variable configurations which were suited to produce the optimal balance of minimum mass, minimum rotation angle, minimum displacement, and maximum total length of the deployable structure. The structure was designed to retract into a container, be lightweight to facilitate transportation, and be able to adapt to varying terrain slopes. This research demonstrates that, in comparison to the RSM, ANN ensembles can more accurately and efficiently be used for identifying optimal design solutions for multi-objective design problems when two surrogate models from the same method corresponding to separate FE models are used simultaneously in a NSGA-II.

Structural Reliability treats uncertainties in structural design systematically, evaluating the levels of safety and serviceability of structures. During the past decades, it has been established as a valuable design tool for the description of the performance of structures, and lately stands as a basis in the background of the most of the modern design standards, aiming to achieve a uniform behaviour within a class of structures. Several methods have been proposed for the estimation of structural reliability, both deterministic (FORM and SORM) and stochastic (Monte Carlo Simulation etc) in nature. Offshore structures should resist complicated and, in most cases, combined environmental phenomena of greatly uncertain magnitude (eg. wind, wave, current, operational loads etc). Failure mechanisms of structural systems and components are expressed through limit state functions, which distinguish a failure and a safe region of operation. For a jacket offshore structure, which comprises of multiple tubular members interconnected in a three dimensional truss configuration, the limit state function should link the actual load or load combination acting on it locally, to the response of each structural member. Cont/d.

This thesis is focused on shape optimization of Venturi´s nozzle with optimization method called response surface method. The first part of this work is concerned with the description of this method as well as explaining the basic principle. Furthermore, there is an explanation of the application of this method in synchronicity with CFD and its operating algorithm. The second part of this thesis is then focused on simple example with plane wing and simplified optimization of Venturi´s nozzle in which this method was tested. In the third part there is described full multiparameter shape optimalization of the nozzle for two geometries.

The focus of this dissertation is on improving decision-maker trade-offs and the development of a new constrained methodology for multiple response surface optimization. There are three key components of the research: development of the necessary conditions and assumptions associated with constrained multiple response surface optimization methodologies; development of a new constrained multiple response surface methodology; and demonstration of the new method. The necessary conditions for and assumptions associated with constrained multiple response surface optimization methods were identified and found to be less restrictive than requirements previously described in the literature. The conditions and assumptions required for a constrained method to find the most preferred non-dominated solution are to generate non-dominated solutions and to generate solutions consistent with decision-maker preferences among the response objectives. Additionally, if a Lagrangian constrained method is used, the preservation of convexity is required in order to be able to generate all non-dominated solutions. The conditions required for constrained methods are significantly fewer than those required for combined methods. Most of the existing constrained methodologies do not incorporate any provision for a decision-maker to explicitly determine the relative importance of the multiple objectives. Research into the larger area of multi-criteria decision-making identified the interactive surrogate worth trade-off algorithm as a potential methodology that would provide that capability in multiple response surface optimization problems. The ISWT algorithm uses an ε-constraint formulation to guarantee a non-dominated solution, and then interacts with the decision-maker after each iteration to determine the preference of the decision-maker in trading-off the value of the primary response for an increase in value of a secondary response. The current research modified the ISWT algorithm to develop a new constrained multiple response surface methodology that explicitly accounts for decision-maker preferences. The new Modified ISWT (MISWT) method maintains the essence of the original method while taking advantage of the specific properties of multiple response surface problems to simplify the application of the method. The MISWT is an accessible computer-based implementation of the ISWT. Five test problems from the multiple response surface optimization literature were used to demonstrate the new methodology. It was shown that this methodology can handle a variety of types and numbers of responses and independent variables. Furthermore, it was demonstrated that the methodology can be successful using a priori information from the decision-maker about bounds or targets or can use the extreme values obtained from the region of operability. In all cases, the methodology explicitly considered decision-maker preferences and provided non-dominated solutions. The contribution of this method is the removal of implicit assumptions and includes the decision-maker in explicit trade-offs among multiple objectives or responses.