Finite element modeling of straightening of thin-walled seamless tubes of austenitic stainless steel

During this thesis work a coupled thermo-mechanical finite element model (FEM) was builtto simulate hot rolling in the blooming mill at Sandvik Materials Technology (SMT) inSandviken. The blooming mill is the first in a long line of processes that continuously or ingotcast ingots are subjected to before becoming finished products. The aim of this thesis work was twofold. The first was to create a parameterized finiteelement (FE) model of the blooming mill. The commercial FE software package MSCMarc/Mentat was used to create this model and the programing language Python was used toparameterize it. Second, two different pass schedules (A and B) were studied and comparedusing the model. The two pass series were evaluated with focus on their ability to healcentreline porosity, i.e. to close voids in the centre of the ingot. This evaluation was made by studying the hydrostatic stress (σm), the von Mises stress (σeq)and the plastic strain (εp) in the centre of the ingot. From these parameters the stress triaxiality(Tx) and the hydrostatic integration parameter (Gm) were calculated for each pass in bothseries using two different transportation times (30 and 150 s) from the furnace. The relationbetween Gm and an analytical parameter (Δ) was also studied. This parameter is the ratiobetween the mean height of the ingot and the contact length between the rolls and the ingot,which is useful as a rule of thumb to determine the homogeneity or penetration of strain for aspecific pass. The pass series designed with fewer passes (B), many with greater reduction, was shown toachieve better void closure theoretically. It was also shown that a temperature gradient, whichis the result of a longer holding time between the furnace and the blooming mill leads toimproved void closure.

Finite element analysis of hot rolling in the blooming mill

During this thesis work a coupled thermo-mechanical finite element model (FEM) was builtto simulate hot rolling in the blooming mill at Sandvik Materials Technology (SMT) inSandviken. The blooming mill is the first in a long line of processes that continuously or ingotcast ingots are subjected to before becoming finished products. The aim of this thesis work was twofold. The first was to create a parameterized finiteelement (FE) model of the blooming mill. The commercial FE software package MSCMarc/Mentat was used to create this model and the programing language Python was used toparameterize it. Second, two different pass schedules (A and B) were studied and comparedusing the model. The two pass series were evaluated with focus on their ability to healcentreline porosity, i.e. to close voids in the centre of the ingot. This evaluation was made by studying the hydrostatic stress (σm), the von Mises stress (σeq)and the plastic strain (εp) in the centre of the ingot. From these parameters the stress triaxiality(Tx) and the hydrostatic integration parameter (Gm) were calculated for each pass in bothseries using two different transportation times (30 and 150 s) from the furnace. The relationbetween Gm and an analytical parameter (Δ) was also studied. This parameter is the ratiobetween the mean height of the ingot and the contact length between the rolls and the ingot,which is useful as a rule of thumb to determine the homogeneity or penetration of strain for aspecific pass. The pass series designed with fewer passes (B), many with greater reduction, was shown toachieve better void closure theoretically. It was also shown that a temperature gradient, whichis the result of a longer holding time between the furnace and the blooming mill leads toimproved void closure.

Finite element modeling of tube deformation during cold pilgering

A three-dimensional finite element model of cold pilgering of stainless steel tubes is developed in this paper. The objective is to use the model to increase the understanding of forces and deformations in the process. The focus is on the influence of vertical displacements of the roll stand and axial displacements of the mandrel and tube. Therefore, the rigid tools and the tube are supported with elastic springs. Additionally, the influences of friction coefficients in the tube/mandrel and tube/roll interfaces are examined. A sensitivity study is performed to investigate the influences of these parameters on the strain path and the roll separation force. The results show the importance of accounting for the displacements of the tube and rigid tools on the roll separation force and the accumulative plastic strain.

Experimental and computational investigation of the roll forming process

One of the first questions to consider when designing a new roll forming line is the number of forming steps required to produce a profile. The number depends on material properties, the cross-section geometry and tolerance requirements, but the tool designer also wants to minimize the number of forming steps in order to reduce the investment costs for the customer. There are several computer aided engineering systems on the market that can assist the tool designing process. These include more or less simple formulas to predict deformation during forming as well as the number of forming steps. In recent years it has also become possible to use finite element analysis for the design of roll forming processes. The objective of the work presented in this thesis was to answer the following question: How should the roll forming process be designed for complex geometries and/or high strength steels? The work approach included both literature studies as well as experimental and modelling work. The experimental part gave direct insight into the process and was also used to develop and validate models of the process. Starting with simple geometries and standard steels the work progressed to more complex profiles of variable depth and width, made of high strength steels. The results obtained are published in seven papers appended to this thesis. In the first study (see paper 1) a finite element model for investigating the roll forming of a U-profile was built. It was used to investigate the effect on longitudinal peak membrane strain and deformation length when yield strength increases, see paper 2 and 3. The simulations showed that the peak strain decreases whereas the deformation length increases when the yield strength increases. The studies described in paper 4 and 5 measured roll load, roll torque, springback and strain history during the U-profile forming process. The measurement results were used to validate the finite element model in paper 1. The results presented in paper 6 shows that the formability of stainless steel (e.g. AISI 301), that in the cold rolled condition has a large martensite fraction, can be substantially increased by heating the bending zone. The heated area will then become austenitic and ductile before the roll forming. Thanks to the phenomenon of strain induced martensite formation, the steel will regain the martensite content and its strength during the subsequent plastic straining. Finally, a new tooling concept for profiles with variable cross-sections is presented in paper 7. The overall conclusions of the present work are that today, it is possible to successfully develop profiles of complex geometries (3D roll forming) in high strength steels and that finite element simulation can be a useful tool in the design of the roll forming process.

The effects of attitudes and personality traits on mode choice

We hypothesise that differences in people's attitudes and personality traits lead them to attribute varying importance to environmental considerations, safety, comfort, convenience and flexibility. Differences in personality traits call be revealed not only in the individuals' choice of transport, but also in other actions of their everyday lives-such as how much they recycle, whether they take precautions or avoid dangerous pursuits. Conditioning on a set of exogenous individual characteristics, we use indicators of attitudes and personality traits to form latent variables for inclusion in an, otherwise standard, discrete mode choice model. With a sample of Swedish commuters, we find that both attitudes towards flexibility and comfort, as well as being pro-environmentally inclined, influence the individual's choice of mode. Although modal time and cost still are important, it follows that there are other ways, apart from economic incentives, to attract individuals to the, from society's perspective, desirable public modes of transport. Our results should provide useful information to policy-makers and transportation planners developing sustainable transportation systems.

Classification of Parkinson’s Disease using MultiPass Lvq,Logistic Model Tree,K-Star for Audio Data set : Classification of Parkinson Disease using Audio Dataset

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

Simulation model using meta heuristic algorithms for achieving optimal arrangement of storage bins in a sawmill yard

Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.