Pressure contours on forming dies: Part 1. Simulation using physical modelling technique

The use of the model technique in the prediction of the pressure distribution over the tool surfaces in cold forging

Influence of major inherited faults zones on gravitational slope deformation: A two-dimensional physical modelling of the La Clapière area (Southern French Alps)

Effect of pulp cleaning zone on gangue control in column flotation

VR simulated training for less invasive vascular intervention

Individualizing therapy, customizing clinical science

ABSTRACTCathodic protection is commonly used for corrosion protection of the underwater hull structures of naval platforms. Cathodic protection works by establishing an electrostatic field that provides the desired potential and current distributions in the seawater surrounding the structures to be protected. Interference to a ship’s cathodic protection system may occur when the ship is alongside a jetty or another naval ship due to the influence of the electrostatic field associated with the cathodic protection system employed on the jetty or another naval ship. The interference may alter the electrostatic field surrounding the ship and, therefore, the level of corrosion protection to the ship hull. In the current study, a physical scale modelling technique is used to evaluate how, and to what extent, the level of cathodic protection on a ship hull could be affected by an external current source. A 1/100 scale ship model with two-zone four-anode impressed current cathodic protection (ICCP) system is used in the study. The modelling results indicate that the presence of stray current may affect the potential distribution along the ship hull. The extent of stray current effect depends on a number of factors including the relative position and layout of stray current source, the magnitude and direction of the stray current flow and the operating mode of the shipboard ICCP system.

Due to a simpler calculation process and better precision, the rotating-angle softened-truss model is often used to predict behaviours of reinforced concrete shell or panel structures. In the current algorithm of the rotating-angle softened-truss model, the calculation process is from strains to stresses, which needs a trial and error procedure. A new algorithm of the rotating-angle softened-truss model is proposed in this paper. The Poisson effect is included in the new algorithm. Its calculation process is from stresses to strains. The trial and error procedure is avoided, which simplifies the calculation process significantly. The reliability of the new algorithm is verified by test data of six panels.

Application of a rigid—plastic finite-element method to some metalforming operations

A primary requirement for the realization of FSA systems is the availability of a mathematical model for the actual process, and the ways to obtain this model may be broadly categorized into 2 methodologies: physical modelling techniques or process identification methods. The physical modelling approach seeks to derive the process model using fundamental laws governing the operations of the process, such as continuity and energy equations. Therefore, the parameters in the model have physical interpretations and they may sometimes be obtained from direct measurements on the process. Clearly, this modelling method requires a good and thorough understanding of the functioning of the entire process. However, even when the requirement can be satisfied, rarely can all parameters of the model be obtainable through direct measurements. Therefore, often physical modelling methods cannot be used alone and they are complemented with other modelling techniques.

The influx of computer-based design and presentation platforms, particularly in conjunction with computer aided physical modelling and manufacturing techniques, has stimulated a renewed focus on imaginative, innovative architectural product design. Essentially, the ambition of the DigiTile exercise was to stimulate the development of individual proposals for new kinds of surface articulations on the basis of a tile-like unit, or set of units. Inspirations varied widely: from precedents ranging from history to nature, as well as from contemporary design practice and graphic imagery. The prevailing freshness and technical inquisitiveness amongst the participants contributed to the generation and concretisation of distinctive tiling concepts, many of which have arguably not been seen before. The findings and conclusions are based upon the array of outcomes from the programme so far, as well from a very recent session. Furthermore, the paper highlights the kinds of opportunities for hands-on education-based compositional studies that we foresee in the near future.

Tangible virtuality—perceptions of computer-aided and physical modelling

Gimbals are mechatronic systems well known for their use in the stabilization of cameras which are under the effect of sudden movements. Gimbals help keeping cameras at previously defined fixed orientations, so that the captured images have the highest quality. This paper focuses on the design of a Linear Quadratic Gaussian, LQG, controller, based on the physical modeling of a commercial Gimbal with two degrees of freedom (2DOF), which is used for first-person applications in unmanned aerial vehicle (UAV). This approach is proposed to make a more realistic representation of the system under study, since it guarantees high accuracy in the simulation of the dynamic response, as compared to the prediction of the mathematical model of the same system. The development of the model starts by sectioning the Gimbal into a series of interconnected links. Subsequently, a fixed reference system is assigned to each link body and the corresponding homogeneous transformation matrices are established, which will allow the calculation of the orientation of each link and the displacement of their centers of mass. Once the total kinetic and potential energy of the mechanical components are obtained, Lagrange’s method is utilized to establish the mathematical model of the mechanical structure of the Gimbal. The equations of motion of the system are then expressed in state space form, with two inputs, two outputs and four states, where the inputs are the torques produced by each one of the motors, the outputs are the orientation of the first two links, and the states are the aforementioned orientations along with their time derivatives. The state space model was implemented in MATLAB’s Simulink environment to compare its prediction of the transient response with the prediction obtained with the representation of the same system using MATLAB’s SimMechanics physical modelling interface. The mathematical model of each one of the three-phase Brushless DC motors is also expressed in state space form, where the three inputs of each motor model are the voltages of the corresponding motor phases, its two outputs are the angular position and angular velocity, and its four states are the currents in two of the phases, the orientation of the motor shaft and its rate of change. This model is experimentally validated by performing a switching sequence in both the simulation model and the physical system and observing that the transient response of the angular position of the motor shaft is in accordance with the theoretical model. The control system design process starts with the interconnection of the models of the mechanical components and the models of the Brushless DC Motor, using their corresponding state space representations. The resulting model features six inputs, two outputs and eight states. The inputs are the voltages in each phase of the two motors in the Gimbal, the outputs are the angular positions of the first two links, and the states are the currents in two of the phases for each motor and the orientations of the first two links, along with their corresponding time derivatives. An optimal LQG control system is designed using MATLAB’s dlqr and Kalman functions, which calculate the gains for the control system and the gains for the states estimated by the observer. The external excitation in each of the phases is carried out by pulse width modulation. Finally, the transient response of the overall system is evaluated for different reference points. The simulation results show very good agreement with the experimental measurements.

The work presented in this dissertation was conducted in an effort to achieve improvement in conventional and digital control methods applied to chemical processes. Emphasis was placed on simplicity and effectiveness in an attempt to provide control improvements which are easily implemented and yet efficient in their tasks. In these studies digital simulation was used exclusively utilizing the IBM 7040 and 360 and the XDS Sigma V computers. Initially the inaccuracies involved in obtaining a firstorder plus dead time model graphically from an open loop response curve are discussed. It is pointed out that fine tuning of two and three mode controllers based on these inaccurate models is necessary and presently must be done by trial and error. Modifications of existing controller tuning relations are presented which guide fine tuning attempts and eliminate much of the trial and error procedure. Second, the subject of linear discrete models applied to sampled-data systems is considered. A multiple linear least squares technique is applied to sampled system input/output records to identify parameters of a linear discrete model. The method is demonstrated to give good results when applied xii to linear and non-linear systems with and without dead time. The simplicity and flexibility of implementing this modeling technique are discussed. Application of this method to systems with measurement noise are shown to be improved when the data are filtered. Third, the implementation of linear discrete models in Deadbeat, Dahlin and Kalman controller synthesis methods are presented. It is demonstrated that the form of the models fits well into each of these controller design philosophies. The Dahlin algorithms which incorporate a tuning parameter give the most consistent performance for model orders and sampling times considered. In general, the performance of controllers based on low order models is seen to compare well with that of higher order controllers. Fourth, utilizing the speed of the multiple linear regression identification, the application of this technique in an adaptive control scheme is presented. Applying a recursive solution of the regression equation enables the updating of the linear discrete model at each sample instant and subsequently the adaptation of the control strategy. This scheme is demonstrated to provide closer control of a non linear, time-variant system than is possible with a stationary model. xiii CHAPTER I The form of the transfer function, HG(z), comprised of the digital hold device and the process itself, is such that multiple linear regression techniques can be applied to identify the model constants (parameters). Model identification is then based only on a linear regression of the sampled-data records of the system input and output. A modeling technique based on multiple linear regression only requires the solution of a set of normal equa tions and therefore is rapid enough to be applied on-line. Model order can also be changed with relative ease requiring only an other pass through the system input/output response data already collected. The effectiveness of this identification method is demonstrated on linear systems as well as on a simulated non linear plug flow reactor system. The effect of measurement noise on modeling accuracy is also considered, and comparison of identification using both filtered and unfiltered data are presented. The advantage of filtering data under these operating conditions is illustrated. Linear discrete models obtained for the simulated reactor were demdnstrated in their capacities as both one step ahead predictor models and as free running models. In these studies the higher order models provided significantly better results. Digital controller synthesis methods are the subject of Chapter IV. The discrete form of the model fits well into these design methods. Flexibility in varying model order is carried over to allow: for flexibility in controller order. The advantages of this flexibility are illustrated with the Deadbeat, Dahlin and Kalman controller design algorithms. Controllers based on each of these design methods are implemented in the plug flow reactor system and compared as to overall control performance and manipulate variable action. Comparisons are made also for both fast and slow sampling rates. Finally, Chapter V incorprates the multiple linear regres sion modeling technique with a direct controller synthesis method in an attempt to achieve an adaptive control scheme. The intent here is to update the process model with each new sample taken, and therefore adapt the controller, which is di rectly based on this model to any variation in the operating levels of the system. Adaptive control in this fashion is demonstrated in application to the non-linear plug flow reactor system with a slowly changing feed rate. The result is a demonstration of an adaptive control strategy which has the capability to function in many possible process applications.

The control of slag foaming is important for optimising basic oxygen furnace (BOF) performance. Acoustics systems monitoring wide frequency bandwidths have been applied to BOF monitoring for the purpose of understanding slag foam height and density but there is limited information about their accuracy and repeatability. Improved understanding of the fundamental behaviour of sound in slag foam could help resolve these issues. In this cold physical model study using, aqueous foams generated in a cylindrical vessel were used to study the attenuation of sound in large samples of foam. Sound pulses over the range of 201 to 1801 Hz were transmitted through varying aqueous foam heights of 100 to 250 mm and acoustic signals detected via a measurement microphone were analysed. The results indicated aqueous foams consisting of smaller bubbles in the range of 0.4 to 0.75 mm with visibly thicker outer films displayed a stronger correlation between the attenuated sound and the stationary foam heights. It was also observed that frequencies above 1009 Hz were more sensitive in terms of their attenuation in varying foam heights and the time-dependant drainage of bubbles compared to lower frequencies. These frequencies were generally higher than those used for industrial slag foam monitoring systems.

The current industrial practice in design of the injected pultrusion (IP) process involves costly trial and error procedures, hitherto unavoidable in the absence of established process models. Even for well understood processes, economic design has traditionally used steady-state physical models, separately followed by control system synthesis using simpler dynamic models. This work describes the development of a rigorous model-based design algorithm for the IP process by integration of economics, operability, and environmental considerations. In our previous work, a 3D dynamic physical model of the IP process was experimentally validated on a bench-scale setup. Using this validated model, we can now reduce the time and expenses associated with a purely experimental approach. An understanding of processing economics leads to throughput rate maximization as the desired economic objective. We develop a multiobjective optimization algorithm that maximizes this objective function, using a response surface methodology with iterative meshing to determine optimal equipment specifications (die dimensions, puller ratings) and processing condition parameters (heating zone temperatures, resin injection pressure). Retrofit design of the bench-scale setup promised a tenfold increase in throughput rate. Calculation of theoretical limit on throughput rates from intrinsic resin cure kinetics supported this finding. Various metrics were proposed to evaluate quality of design in a distributed-parameter sense. Sensitivity studies verified that the economic optimum is also robust to a wide range of expected process disturbances. An analysis of process instrumentation revealed the need for additional measurements. We propose resin flow-rate and cutting force measurements for void and cure sensing respectively. This research is a first step to the integration of design and control for a complex multiphase process using a single dynamic physical model. The integration offers several benefits over current design practices, and highlights the potential for increased productivity in polymer composites manufacturing.