Non-Linear Journal Bearing Model for Analysis of Superharmonic Vibrations of Rotor Systems

A rotating machine usually consists of a rotor and bearings that supports it. The nonidealities in these components may excite vibration of the rotating system. The uncontrolled vibrations may lead to excessive wearing of the components of the rotating machine or reduce the process quality. Vibrations may be harmful even when amplitudes are seemingly low, as is usually the case in superharmonic vibration that takes place below the first critical speed of the rotating machine. Superharmonic vibration is excited when the rotational velocity of the machine is a fraction of the natural frequency of the system. In such a situation, a part of the machine’s rotational energy is transformed into vibration energy. The amount of vibration energy should be minimised in the design of rotating machines. The superharmonic vibration phenomena can be studied by analysing the coupled rotor-bearing system employing a multibody simulation approach. This research is focused on the modelling of hydrodynamic journal bearings and rotorbearing systems supported by journal bearings. In particular, the non-idealities affecting the rotor-bearing system and their effect on the superharmonic vibration of the rotating system are analysed. A comparison of computationally efficient journal bearing models is carried out in order to validate one model for further development. The selected bearing model is improved in order to take the waviness of the shaft journal into account. The improved model is implemented and analyzed in a multibody simulation code. A rotor-bearing system that consists of a flexible tube roll, two journal bearings and a supporting structure is analysed employing the multibody simulation technique. The modelled non-idealities are the shell thickness variation in the tube roll and the waviness of the shaft journal in the bearing assembly. Both modelled non-idealities may cause subharmonic resonance in the system. In multibody simulation, the coupled effect of the non-idealities can be captured in the analysis. Additionally one non-ideality is presented that does not excite the vibrations itself but affects the response of the rotorbearing system, namely the waviness of the bearing bushing which is the non-rotating part of the bearing system. The modelled system is verified with measurements performed on a test rig. In the measurements the waviness of bearing bushing was not measured and therefore it’s affect on the response was not verified. In conclusion, the selected modelling approach is an appropriate method when analysing the response of the rotor-bearing system. When comparing the simulated results to the measured ones, the overall agreement between the results is concluded to be good.

Scale-up model obtained from the rheological analysis of highly concentrated emulsions prepared at three scales

We examine the scale invariants in the preparation of highly concentrated w/o emulsions at different scales and in varying conditions. The emulsions are characterized using rheological parameters, owing to their highly elastic behavior. We first construct and validate empirical models to describe the rheological properties. These models yield a reasonable prediction of experimental data. We then build an empirical scale-up model, to predict the preparation and composition conditions that have to be kept constant at each scale to prepare the same emulsion. For this purpose, three preparation scales with geometric similarity are used. The parameter N¿D^α, as a function of the stirring rate N, the scale (D, impeller diameter) and the exponent α (calculated empirically from the regression of all the experiments in the three scales), is defined as the scale invariant that needs to be optimized, once the dispersed phase of the emulsion, the surfactant concentration, and the dispersed phase addition time are set. As far as we know, no other study has obtained a scale invariant factor N¿Dα for the preparation of highly concentrated emulsions prepared at three different scales, which covers all three scales, different addition times and surfactant concentrations. The power law exponent obtained seems to indicate that the scale-up criterion for this system is the power input per unit volume (P/V).

Control of permanent magnet linear synchronous motor in motion control applications

The aim of the thesis is to study the principles of the permanent magnet linear synchronous motor (PMLSM) and to develop a simulator model of direct force controlled PMLSM. The basic motor model is described by the traditional two-axis equations. The end effects, cogging force and friction model are also included into the final motor model. Direct thrust force control of PMLSM is described and modelled. The full system model is proven by comparison with the data provided by the motor manufacturer.

Flow analysis by using solenoid valves for As(III) determination in natural waters by an on-line separation and pre-concentration system coupled to a tungsten coil atomizer

A flow system coupled to a tungsten coil atomizer in an atomic absorption spectrometer (TCA-AAS) was developed for As(III) determination in waters, by extraction with sodium diethyldithiocarbamate (NaDDTC) as complexing agent, and by sorption of the As(III)-DDTC complex in a micro-column filled with 5 mg C18 reversed phase (10 µL dry sorbent), followed by elution with ethanol. A complete pre-concentration/elution cycle took 208 s, with 30 s sample load time (1.7 mL) and 4 s elution time (71 µL). The interface and software for the synchronous control of two peristaltic pumps (RUN/ STOP), an autosampler arm, seven solenoid valves, one injection valve, the electrothermal atomizer and the spectrometer Read function were constructed. The system was characterized and validated by analytical recovery studies performed both in synthetic solutions and in natural waters. Using a 30 s pre-concentration period, the working curve was linear between 0.25 and 6.0 µg L-1 (r = 0.9976), the retention efficiency was 94±1% (6.0 µg L-1), and the pre-concentration coefficient was 28.9. The characteristic mass was 58 pg, the mean repeatability (expressed as the variation coefficient) was 3.4% (n=5), the detection limit was 0.058 µg L-1 (4.1 pg in 71 µL of eluate injected into the coil), and the mean analytical recovery in natural waters was 92.6 ± 9.5 % (n=15). The procedure is simple, economic, less prone to sample loss and contamination and the useful lifetime of the micro-column was between 200-300 pre-concentration cycles.

Readout electronics for low dark count pixel detectors based on geiger mode avalanche photodiodes fabricated in conventional CMOS technologies for future linear colliders

The high sensitivity and excellent timing accuracy of Geiger mode avalanche photodiodes makes them ideal sensors as pixel detectors for particle tracking in high energy physics experiments to be performed in future linear colliders. Nevertheless, it is well known that these sensors suffer from dark counts and afterpulsing noise, which induce false hits (indistinguishable from event detection) as well as an increase of the necessary area of the readout system. In this work, we present a comparison between APDs fabricated in a high voltage 0.35 µm and a high integration 0.13 µm commercially available CMOS technologies that has been performed to determine which of them best fits the particle collider requirements. In addition, a readout circuit that allows low noise operation is introduced. Experimental characterization of the proposed pixel is also presented in this work.

Applications and Markets of Linear Motors

A steady increase in practical industrial applications has secured a place for linear motors. They provide high dynamics and high positioning accuracy of the motor, high reliability and durability of all components of the system. Machines with linear motors have very big perspectives in modern industry. This thesis enables to understand what a linear motor is, where they are used and what situation there is on their market nowadays. It can help to understand reasonability of applying linear motors on manufacture and benefits of its application.

Spectrophotometric flow injection system for determination of Zn2+ in ophthalmic formulations using Alizarin red S

A spectrophotometric flow injection method for the determination of Zn(II) in ophthalmic formulations was developed. In this work, Zn(II) ion was complexed with Alizarin red S in borate buffer solution (pH 9.0) and the chromophore produced was monitored at 520 nm. The analytical curve was linear in the Zn(II) concentration range from 6.05 x 10-6 to 1.50 x 10-4 mol L-1 with a detection limit of 3.60 x 10-6 mol L-1. Recoveries ranged from 96.3 to 105 % and a relative standard deviation of 1.2 % (n = 10) for 5.5x10-5 mol L-1 Zn(II) reference solution were obtained. The sampling rate was 60 h-1 and the results obtained of Zn(II) in ophthalmic products using this procedure are in close agreement with those obtained using a comparative spectrophotometric procedure at 95 % confidence level.

A pH optode based on thymol blue: application to determination of CO2 using flow injection analysis system

An optode based on thymol blue (TB), an acid-based indicator, has been constructed and evaluated as a detector in FIA system for CO2 determination. The dye was chemically immobilised on the surface of a bifurcated glass optical fibre bundle, using silanisation in organic media. In FIA system, hydrogen carbonate or carbonate samples are injected in a buffer carrier solution, and then are mixed with phosphoric acid solution to generate CO2, which diffuses through a PTFE membrane, in order to be collected in an acceptor carrier fluid, pumped towards to detection cell, in which the optode was adapted. The proposed system presents two linear response ranges, from 1.0 x 10-3 to 1.0 x 10-2 mol l-1, and from 2.0 x 10-2 to 0.10 mol l-1. The sampling frequency was 11 sample h-1, with good repeatability (R.S.D < 4 %, n = 10). In flow conditions the optode lifetime was 170 h. The system was applied in the analysis of commercial mineral water and the results obtained in the hydrogen carbonate determination did not differ significantly from those obtained by potentiometry, at a confidence level of 95 %.

Bimodal pore distribution on soils under conservation management system for coffee crop

This study aims at detailing bimodal pore distribution by means of water retention curve in an oxidic-gibbsitic Latosol and in a kaolinitic cambisol Latossol under conservation management system of coffee crop. Samples were collected at depths of 20; 40; 80; 120 and 160 cm on coffee trees rows and between rows under oxidic-gibbsitic Latosol (LVd) and kaolinitic cambisol Latossol (LVAd). Water retention curve was determined at matrix potentials (Ψm) -1; -2; -4; -6; -10 kPa obtained from the suction unit; the Ψm of -33; -100; -500; -1,500 kPa were obtained by the Richards extractor, and WP4-T psychrometer was used to determine Ψm -1,500 to -300,000 kPa. The water retention data were adjusted to the double van Genuchten model by nonlinear model procedures of the R 2.12.1 software. Was estimated the model parameter and inflection point slope. The system promoted changes in soil structure and water retention for the conditions evaluated, and both showed bimodal pores distribution, which were stronger in LVd. There was a strong influence of mineralogy gibbsitic in the water retention more negative than Ψm -1500 kPa, reflected in the values of the residual water content.

Dispersal and metacommunity dynamics in a soft-sediment benthic system : how well is the seafloor connected?

Connectivity depends on rates of dispersal between communities. For marine soft-sediment communities continued small-scale dispersal as post-larvae and as adults can be equally important in maintaining community composition, as initial recruitment of substrate by pelagic larvae. In this thesis post-larval dispersal strategies of benthic invertebrates, as well as mechanisms by which communities are connected were investigated. Such knowledge on dispersal is scarce, due to the difficulties in actually measuring dispersal directly in nature, and dispersal has not previously been quantified in the Baltic Sea. Different trap-types were used underwater to capture dispersing invertebrates at different sites, while in parallel measuring waves and currents. Local community composition was found to change predictably under varying rates of dispersal and physical connectivity (waves and currents). This response was, however, dependent on dispersal-related traits of taxa. Actively dispersing taxa will be relatively better at maintaining their position, as they are not as dependent on hydrodynamic conditions for dispersal and will be less prone to be passively transported by currents. Taxa also dispersed in relative proportions that were distinctly different from resident community composition and a significant proportion (40 %) of taxa were found to lack a planktonic larval life-stage. Community assembly was re-started in a large-scale manipulative field experiment over one year across several sites, which revealed how patterns of community composition (α-, β- and λ-diversity) change depending on rates of dispersal. Results also demonstrated that in response to small-scale disturbance, initial recruitment was by nearby-dominant species after which other species arrived from successively further away. At later assembly time, the number of coexisting species increased beyond what was expected purely by local niche requirements (species sorting), transferring regional differences in community composition (β-diversity) to the local scale (α-diversity, mass effect). Findings of this thesis complement more theoretical studies in metacommunity ecology by demonstrating that understanding how and when individuals disperse relative to underlying environmental heterogeneity is key to interpreting how patterns of diversity change across different spatial scales. Such information from nature is critical when predicting responses to, for example, different types of disturbances or management actions in conservation.

Novel Methods for Error Modeling and Parameter Identification of a Redundant Serial-Parallel Hybrid Robot

To obtain the desirable accuracy of a robot, there are two techniques available. The first option would be to make the robot match the nominal mathematic model. In other words, the manufacturing and assembling tolerances of every part would be extremely tight so that all of the various parameters would match the “design” or “nominal” values as closely as possible. This method can satisfy most of the accuracy requirements， but the cost would increase dramatically as the accuracy requirement increases. Alternatively, a more cost-effective solution is to build a manipulator with relaxed manufacturing and assembling tolerances. By modifying the mathematical model in the controller, the actual errors of the robot can be compensated. This is the essence of robot calibration. Simply put, robot calibration is the process of defining an appropriate error model and then identifying the various parameter errors that make the error model match the robot as closely as possible. This work focuses on kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial-parallel hybrid robot. The robot consists of a 4-DOF serial mechanism and a 6-DOF hexapod parallel manipulator. The redundant 4-DOF serial structure is used to enlarge workspace and the 6-DOF hexapod manipulator is used to provide high load capabilities and stiffness for the whole structure. The main objective of the study is to develop a suitable calibration method to improve the accuracy of the redundant serial-parallel hybrid robot. To this end, a Denavit–Hartenberg (DH) hybrid error model and a Product-of-Exponential (POE) error model are developed for error modeling of the proposed robot. Furthermore, two kinds of global optimization methods, i.e. the differential-evolution (DE) algorithm and the Markov Chain Monte Carlo (MCMC) algorithm, are employed to identify the parameter errors of the derived error model. A measurement method based on a 3-2-1 wire-based pose estimation system is proposed and implemented in a Solidworks environment to simulate the real experimental validations. Numerical simulations and Solidworks prototype-model validations are carried out on the hybrid robot to verify the effectiveness, accuracy and robustness of the calibration algorithms.

Parameter estimation and use of gamma interferon assay for the diagnosis of bovine tuberculosis in Brazil

This study aimed to evaluate the interference of tuberculin test on the gamma-interferon (INFg) assay, to estimate the sensitivity and specificity of the INFg assay in Brazilian conditions, and to simulate multiple testing using the comparative tuberculin test and the INFg assay. Three hundred-fifty cattle from two TB-free and two TB-infected herds were submitted to the comparative tuberculin test and the INFg assay. The comparative tuberculin test was performed using avian and bovine PPD. The INFg assay was performed by the BovigamTM kit (CSL Veterinary, Australia), according to the manufacturer's specifications. Sensitivity and specificity of the INFg assay were assessed by a Bayesian latent class model. These diagnostic parameters were also estimate for multiple testing. The results of INFg assay on D0 and D3 after the comparative tuberculin test were compared by the McNemar's test and kappa statistics. Results of mean optical density from INFg assay on both days were similar. Sensitivity and specificity of the INFg assay showed results varying (95% confidence intervals) from 72 to 100% and 74 to 100% respectively. Sensitivity of parallel testing was over 97.5%, while specificity of serial testing was over 99.7%. The INFg assay proved to be a very useful diagnostic method.

Application of a Pid+fuzzy controller on the motion control system in machine tools

This work deals with an hybrid PID+fuzzy logic controller applied to control the machine tool biaxial table motions. The non-linear model includes backlash and the axis elasticity. Two PID controllers do the primary table control. A third PID+fuzzy controller has a cross coupled structure whose function is to minimise the trajectory contour errors. Once with the three PID controllers tuned, the system is simulated with and without the third controller. The responses results are plotted and compared to analyse the effectiveness of this hybrid controller over the system. They show that the proposed methodology reduces the contour error in a proportion of 70:1.

Linear-quadratic optimal control of descriptor systems

In recent years the analysis and synthesis of (mechanical) control systems in descriptor form has been established. This general description of dynamical systems is important for many applications in mechanics and mechatronics, in electrical and electronic engineering, and in chemical engineering as well. This contribution deals with linear mechanical descriptor systems and its control design with respect to a quadratic performance criterion. Here, the notion of properness plays an important role whether the standard Riccati approach can be applied as usual or not. Properness and non-properness distinguish between the cases if the descriptor system is exclusively governed by the control input or by its higher-order time-derivatives additionally. In the unusual case of non-proper systems a quite different problem of optimal control design has to be considered. Both cases will be solved completely.

Non-Linear Unsteady Aerodynamic Response Approximation Using Multi-Layer Functionals

Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.