Optimization of strength and toughness on the effect of the weldable high strength steels (hss) used in offshore structures

Optimization of high strength and toughness combination on the effect of weldability is very vital to be considered in offshore oil and gas industries. Having a balanced and improved high strength and toughness is very much recommended in offshore structures for an effective production and viable exploration of hydrocarbons. This thesis aims to investigate the possibilities to improve the toughness of high strength steel. High carbon contents induce hardness and needs to be reduced for increasing toughness. The rare combination of high strength with high toughness possibilities was examined by determining the following toughening mechanism of: Heat treatment and optimal microstructure, Thermomechanical processing, Effect of welding parameters on toughness and weldability of steel. The implementation of weldability of steels to attain high toughness for high strength in offshore structures is mostly in shipbuilding, offshore platforms, and pipelines for high operating pressures. As a result, the toughening mechanisms suggested have benefits to the aims of the effect of high strength to high toughness of steel for efficiency, production and cost reduction.

Optimization of parameters for fiber laser-MAG hybrid welding in shipbuilding applications

The Arctic region becoming very active area of the industrial developments since it may contain approximately 15-25% of the hydrocarbon and other valuable natural resources which are in great demand nowadays. Harsh operation conditions make the Arctic region difficult to access due to low temperatures which can drop below -50 °C in winter and various additional loads. As a result, newer and modified metallic materials are implemented which can cause certain problems in welding them properly. Steel is still the most widely used material in the Arctic regions due to high mechanical properties, cheapness and manufacturability. Moreover, with recent steel manufacturing development it is possible to make up to 1100 MPa yield strength microalloyed high strength steel which can be operated at temperatures -60 °C possessing reasonable weldability, ductility and suitable impact toughness which is the most crucial property for the Arctic usability. For many years, the arc welding was the most dominant joining method of the metallic materials. Recently, other joining methods are successfully implemented into welding manufacturing due to growing industrial demands and one of them is the laser-arc hybrid welding. The laser-arc hybrid welding successfully combines the advantages and eliminates the disadvantages of the both joining methods therefore produce less distortions, reduce the need of edge preparation, generates narrower heat-affected zone, and increase welding speed or productivity significantly. Moreover, due to easy implementation of the filler wire, accordingly the mechanical properties of the joints can be manipulated in order to produce suitable quality. Moreover, with laser-arc hybrid welding it is possible to achieve matching weld metal compared to the base material even with the low alloying welding wires without excessive softening of the HAZ in the high strength steels. As a result, the laser-arc welding methods can be the most desired and dominating welding technology nowadays, and which is already operating in automotive and shipbuilding industries with a great success. However, in the future it can be extended to offshore, pipe-laying, and heavy equipment industries for arctic environment. CO2 and Nd:YAG laser sources in combination with gas metal arc source have been used widely in the past two decades. Recently, the fiber laser sources offered high power outputs with excellent beam quality, very high electrical efficiency, low maintenance expenses, and higher mobility due to fiber optics. As a result, fiber laser-arc hybrid process offers even more extended advantages and applications. However, the information about fiber or disk laser-arc hybrid welding is very limited. The objectives of the Master’s thesis are concentrated on the study of fiber laser-MAG hybrid welding parameters in order to understand resulting mechanical properties and quality of the welds. In this work only ferrous materials are reviewed. The qualitative methodological approach has been used to achieve the objectives. This study demonstrates that laser-arc hybrid welding is suitable for welding of many types, thicknesses and strength of steels with acceptable mechanical properties along very high productivity. New developments of the fiber laser-arc hybrid process offers extended capabilities over CO2 laser combined with the arc. This work can be used as guideline in hybrid welding technology with comprehensive study the effect of welding parameter on joint quality.

Towards sustainable Iron- and steelmaking with economic optimization

The iron and steelmaking industry is among the major contributors to the anthropogenic emissions of carbon dioxide in the world. The rising levels of CO2 in the atmosphere and the global concern about the greenhouse effect and climate change have brought about considerable investigations on how to reduce the energy intensity and CO2 emissions of this industrial sector. In this thesis the problem is tackled by mathematical modeling and optimization using three different approaches. The possibility to use biomass in the integrated steel plant, particularly as an auxiliary reductant in the blast furnace, is investigated. By pre-processing the biomass its heating value and carbon content can be increased at the same time as the oxygen content is decreased. As the compression strength of the preprocessed biomass is lower than that of coke, it is not suitable for replacing a major part of the coke in the blast furnace burden. Therefore the biomass is assumed to be injected at the tuyere level of the blast furnace. Carbon capture and storage is, nowadays, mostly associated with power plants but it can also be used to reduce the CO2 emissions of an integrated steel plant. In the case of a blast furnace, the effect of CCS can be further increased by recycling the carbon dioxide stripped top gas back into the process. However, this affects the economy of the integrated steel plant, as the amount of top gases available, e.g., for power and heat production is decreased. High quality raw materials are a prerequisite for smooth blast furnace operation. High quality coal is especially needed to produce coke with sufficient properties to ensure proper gas permeability and smooth burden descent. Lower quality coals as well as natural gas, which some countries have in great volumes, can be utilized with various direct and smelting reduction processes. The DRI produced with a direct reduction process can be utilized as a feed material for blast furnace, basic oxygen furnace or electric arc furnace. The liquid hot metal from a smelting reduction process can in turn be used in basic oxygen furnace or electric arc furnace. The unit sizes and investment costs of an alternative ironmaking process are also lower than those of a blast furnace. In this study, the economy of an integrated steel plant is investigated by simulation and optimization. The studied system consists of linearly described unit processes from coke plant to steel making units, with a more detailed thermodynamical model of the blast furnace. The results from the blast furnace operation with biomass injection revealed the importance of proper pre-processing of the raw biomass as the composition of the biomass as well as the heating value and the yield are all affected by the pyrolysis temperature. As for recycling of CO2 stripped blast furnace top gas, substantial reductions in the emission rates are achieved if the stripped CO2 can be stored. However, the optimal recycling degree together with other operation conditions is heavily dependent on the cost structure of CO2 emissions and stripping/storage. The economical feasibility related to the use of DRI in the blast furnace depends on the price ratio between the DRI pellets and the BF pellets. The high amount of energy needed in the rotary hearth furnace to reduce the iron ore leads to increased CO2 emissions.

On the use of convex underestimators in global optimization

Många kvantitativa problem från vitt skilda områden kan beskrivas som optimeringsproblem. Ett mått på lösningens kvalitet bör optimeras samtidigt som vissa villkor på lösningen uppfylls. Kvalitetsmåttet kallas vanligen objektfunktion och kan beskriva kostnader (exempelvis produktion, logistik), potentialenergi (molekylmodellering, proteinveckning), risk (finans, försäkring) eller något annat relevant mått. I min doktorsavhandling diskuteras speciellt icke-linjär programmering, NLP, i ändliga dimensioner. Problem med enkel struktur, till exempel någon form av konvexitet, kan lösas effektivt. Tyvärr kan inte alla kvantitativa samband modelleras på ett konvext vis. Icke-konvexa problem kan angripas med heuristiska metoder, algoritmer som söker lösningar med hjälp av deterministiska eller stokastiska tumregler. Ibland fungerar det här väl, men heuristikerna kan sällan garantera kvaliteten på lösningen eller ens att en lösning påträffas. För vissa tillämpningar är det här oacceptabelt. Istället kan man tillämpa så kallad global optimering. Genom att successivt dela variabeldomänen i mindre delar och beräkna starkare gränser på det optimala värdet hittas en lösning inom feltoleransen. Den här metoden kallas branch-and-bound, ungefär dela-och-begränsa. För att ge undre gränser (vid minimering) approximeras problemet med enklare problem, till exempel konvexa, som kan lösas effektivt. I avhandlingen studeras tillvägagångssätt för att approximera differentierbara funktioner med konvexa underskattningar, speciellt den så kallade alphaBB-metoden. Denna metod adderar störningar av en viss form och garanterar konvexitet genom att sätta villkor på den perturberade Hessematrisen. Min forskning har lyft fram en naturlig utvidgning av de perturbationer som används i alphaBB. Nya metoder för att bestämma underskattningsparametrar har beskrivits och jämförts. I sammanfattningsdelen diskuteras global optimering ur bredare perspektiv på optimering och beräkningsalgoritmer.

Currency Carry Trades – Excess Returns and Performance Optimization of G10 Currency Carry Trade Strategies during the Euro Era

This study examines the excess returns provided by G10 currency carry trading during the Euro era. The currency carry trade has been a popular trade throughout the past decades offering excess returns to investors. The thesis aims to contribute to existing research on the topic by utilizing a new set of data for the Euro era as well as using the Euro as a basis for the study. The focus of the thesis is specifically on different carry trade strategies’ performance, risk and diversification benefits. The study finds proof of the failure of the uncovered interest rate parity theory through multiple regression analyses. Furthermore, the research finds evidence of significant diversification benefits in terms of Sharpe ratio and improved return distributions. The results suggest that currency carry trades have offered excess returns during 1999-2014 and that volatility plays an important role in carry trade returns. The risk, however, is diversifiable and therefore our results support previous quantitative research findings on the topic.

Intelligent mapping of stresses in a hydraulic crane

Continuous loading and unloading can cause breakdown of cranes. In seeking solution to this problem, the use of an intelligent control system for improving the fatigue life of cranes in the control of mechatronics has been under study since 1994. This research focuses on the use of neural networks as possibilities of developing algorithm to map stresses on a crane. The intelligent algorithm was designed to be a part of the system of a crane, the design process started with solid works, ANSYS and co-simulation using MSc Adams software which was incorporated in MATLAB-Simulink and finally MATLAB neural network (NN) for the optimization process. The flexibility of the boom accounted for the accuracy of the maximum stress results in the ADAMS model. The flexibility created in ANSYS produced more accurate results compared to the flexibility model in ADAMS/View using discrete link. The compatibility between.ADAMS and ANSYS softwares was paramount in the efficiency and the accuracy of the results. Von Mises stresses analysis was more suitable for this thesis work because the hydraulic boom was made from construction steel FE-510 of steel grade S355 with yield strength of 355MPa. Von Mises theory was good for further analysis due to ductility of the material and the repeated tensile and shear loading. Neural network predictions for the maximum stresses were then compared with the co-simulation results for accuracy, and the comparison showed that the results obtained from neural network model were sufficiently accurate in predicting the maximum stresses on the boom than co-simulation.

Context-specific independence in graphical models

The theme of this thesis is context-speci c independence in graphical models. Considering a system of stochastic variables it is often the case that the variables are dependent of each other. This can, for instance, be seen by measuring the covariance between a pair of variables. Using graphical models, it is possible to visualize the dependence structure found in a set of stochastic variables. Using ordinary graphical models, such as Markov networks, Bayesian networks, and Gaussian graphical models, the type of dependencies that can be modeled is limited to marginal and conditional (in)dependencies. The models introduced in this thesis enable the graphical representation of context-speci c independencies, i.e. conditional independencies that hold only in a subset of the outcome space of the conditioning variables. In the articles included in this thesis, we introduce several types of graphical models that can represent context-speci c independencies. Models for both discrete variables and continuous variables are considered. A wide range of properties are examined for the introduced models, including identi ability, robustness, scoring, and optimization. In one article, a predictive classi er which utilizes context-speci c independence models is introduced. This classi er clearly demonstrates the potential bene ts of the introduced models. The purpose of the material included in the thesis prior to the articles is to provide the basic theory needed to understand the articles.

Production planning and optimization of a pulp mill: introduction of the optimisation based scheduling software for pulp industry

The objective of this project was to introduce a new software product to pulp industry, a new market for case company. An optimization based scheduling tool has been developed to allow pulp operations to better control their production processes and improve both production efficiency and stability. Both the work here and earlier research indicates that there is a potential for savings around 1-5%. All the supporting data is available today coming from distributed control systems, data historians and other existing sources. The pulp mill model together with the scheduler, allows what-if analyses of the impacts and timely feasibility of various external actions such as planned maintenance of any particular mill operation. The visibility gained from the model proves also to be a real benefit. The aim is to satisfy demand and gain extra profit, while achieving the required customer service level. Research effort has been put both in understanding the minimum features needed to satisfy the scheduling requirements in the industry and the overall existence of the market. A qualitative study was constructed to both identify competitive situation and the requirements vs. gaps on the market. It becomes clear that there is no such system on the marketplace today and also that there is room to improve target market overall process efficiency through such planning tool. This thesis also provides better overall understanding of the different processes in this particular industry for the case company.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Distribution network design and optimization

The objective of this thesis is to examine distribution network designs and modeling practices and create a framework to identify best possible distribution network structure for the case company. The main research question therefore is: How to optimize case company’s distribution network in terms of customer needs and costs? Theory chapters introduce the basic building blocks of the distribution network design and needed calculation methods and models. Framework for the distribution network projects was created based on the theory and the case study was carried out by following the defined framework. Distribution network calculations were based on the company’s sales plan for the years 2014 - 2020. Main conclusions and recommendations were that the new Asian business strategy requires high investments in logistics and the first step is to open new satellite DC in China as soon as possible to support sales and second possible step is to open regional DC in Asia within 2 - 4 years.

Optimization and Measuring Techniques for Collect-and-Place Machines in Printed Circuit Board Industry

This thesis considers optimization problems arising in printed circuit board assembly. Especially, the case in which the electronic components of a single circuit board are placed using a single placement machine is studied. Although there is a large number of different placement machines, the use of collect-and-place -type gantry machines is discussed because of their flexibility and increasing popularity in the industry. Instead of solving the entire control optimization problem of a collect-andplace machine with a single application, the problem is divided into multiple subproblems because of its hard combinatorial nature. This dividing technique is called hierarchical decomposition. All the subproblems of the one PCB - one machine -context are described, classified and reviewed. The derived subproblems are then either solved with exact methods or new heuristic algorithms are developed and applied. The exact methods include, for example, a greedy algorithm and a solution based on dynamic programming. Some of the proposed heuristics contain constructive parts while others utilize local search or are based on frequency calculations. For the heuristics, it is made sure with comprehensive experimental tests that they are applicable and feasible. A number of quality functions will be proposed for evaluation and applied to the subproblems. In the experimental tests, artificially generated data from Markov-models and data from real-world PCB production are used. The thesis consists of an introduction and of five publications where the developed and used solution methods are described in their full detail. For all the problems stated in this thesis, the methods proposed are efficient enough to be used in the PCB assembly production in practice and are readily applicable in the PCB manufacturing industry.

Optimization of a dynamic district heating power plant

The purpose of this Thesis is to find the most optimal heat recovery solution for Wärtsilä’s dynamic district heating power plant considering Germany energy markets as in Germany government pays subsidies for CHP plants in order to increase its share of domestic power production to 25 % by 2020. Different heat recovery connections have been simulated dozens to be able to determine the most efficient heat recovery connections. The purpose is also to study feasibility of different heat recovery connections in the dynamic district heating power plant in the Germany markets thus taking into consideration the day ahead electricity prices, district heating network temperatures and CHP subsidies accordingly. The auxiliary cooling, dynamical operation and cost efficiency of the power plant is also investigated.

Improving Cost-Efficiency and Reducing Environmental Impacts of Intermodal Transportation with Dry Port Concept – Major Rail Transport Corridor in Baltic Sea Region

Transportation plays a major role in the gross domestic product of various nations. There are, however, many obstacles hindering the transportation sector. Cost-efficiency along with proper delivery times, high frequency and reliability are not a straightforward task. Furthermore, environmental friendliness has increased the importance of the whole transportation sector. This development will change roles inside the transportation sector. Even now, but especially in the future, decisions regarding the transportation sector will be partly based on emission levels and other externalities originating from transportation in addition to pure transportation costs. There are different factors, which could have an impact on the transportation sector. IMO’s sulphur regulation is estimated to increase the costs of short sea shipping in the Baltic Sea. Price development of energy could change the roles of different transport modes. Higher awareness of the environmental impacts originating from transportation could also have an impact on the price level of more polluting transport modes. According to earlier research, increased inland transportation, modal shift and slowsteaming can be possible results of these changes in the transportation sector. Possible changes in the transportation sector and ways to settle potential obstacles are studied in this dissertation. Furthermore, means to improve cost-efficiency and to decrease environmental impacts originating from transportation are researched. Hypothetical Finnish dry port network and Rail Baltica transport corridor are studied in this dissertation. Benefits and disadvantages are studied with different methodologies. These include gravitational models, which were optimized with linear integer programming, discrete-event and system dynamics simulation, an interview study and a case study. Geographical focus is on the Baltic Sea Region, but the results can be adapted to other geographical locations with discretion. Results indicate that the dry port concept has benefits, but optimization regarding the location and the amount of dry ports plays an important role. In addition, the utilization of dry ports for freight transportation should be carefully operated, since only a certain amount of total freight volume can be cost-efficiently transported through dry ports. If dry ports are created and located without proper planning, they could actually increase transportation costs and delivery times of the whole transportation system. With an optimized dry port network, transportation costs can be lowered in Finland with three to five dry ports. Environmental impacts can be lowered with up to nine dry ports. If more dry ports are added to the system, the benefits become very minor, i.e. payback time of investments becomes extremely long. Furthermore, dry port network could support major transport corridors such as Rail Baltica. Based on an analysis of statistics and interview study, there could be enough freight volume available for Rail Baltica, especially, if North-West Russia is part of the Northern end of the corridor. Transit traffic to and from Russia (especially through the Baltic States) plays a large role. It could be possible to increase transit traffic through Finland by connecting the potential Finnish dry port network and the studied transport corridor. Additionally, sulphur emission regulation is assumed to increase the attractiveness of Rail Baltica in the year 2015. Part of the transit traffic could be rerouted along Rail Baltica instead of the Baltic Sea, since the price level of sea transport could increase due to the sulphur regulation. Both, the hypothetical Finnish dry port network and Rail Baltica transport corridor could benefit each other. The dry port network could gain more market share from Russia, but also from Central Europe, which is the other end of Rail Baltica. In addition, further Eastern countries could also be connected to achieve higher potential freight volume by rail.