Physical Modeling and Computational Techniques for Thermal and Fluid-dynamics

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.

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.

ABSTRACTThe hydrodynamic performance of a gas-stirred ladle is analyzed experimentally, through a factorial experimental design, through physical modeling and particle image velocimetry techniques, to find the effects of the nozzle position, and its number, the gas flow rate and the presence or not of an oil layer on the flow velocity field, the turbulent kinetic energy distribution, and the open eye area, A. Flow patterns changed drastically in the presence of one or two plugs and as a result of the nozzle’s positions. The turbulent flow fields showed significant differences under the presence or absence of an oil layer and the open eye area strongly depends on the gas flow rate, the position and the number of nozzles. Responses , , and A were statistically processed to identify the relevant effects of each variable on , , and A. These responses were used to calculate the optimum process conditions that minimize A and maximize both and , and then improve mixing efficiency in ladles using multi-objective optimization through the genetic algorithm (GAmultiobj). A Pareto characterization and its analysis were performed to reveal the embedded operation rules allowing optimum performances of the ladle for specific production goals.

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.

In the past 20 years, the US Navy has used the physical scale modeling (PSM) technique to design effective cathodic protection (CP) systems for the ships underwater hull, nickel-aluminum-bronze props and other hull components.In more recent years, a number of computational techniques have been devised in an attempt to fulfill this purpose.Physical models have proven highly adept at ICCP design, since modeled information provides a direct relationship to the actual hull and can be scaled up directly because of confidence in the physically measured data.Boundary element (BE) models have been correspondingly devised that mimic actual hull design and even the PSM layout, but because the BE method is a computational methodology, the calculated data requires systematic validation with a physical analog to insure confidence in the control response.BE literature has discussed design issues regarding mesh layout, intrinsic geometric complexities, accuracy of material response input, the predictive engineering design capability for zonal response, and assessment of electric field response.It does not significantly discuss the accuracy of the BE model calculated work predictive design capability, without the need for "tweaking," and ultimately a rigorous validation of both the mesh and resultant system design technique.This paper presents validation requirements, for any BE model, that is inherently robust enough to be used for CP design and control, and a proposed four-point methodology that will allow for the comprehensive validation of the BE model to predict the ICCP control responses and system performance behavior.

Landslide-generated tsunamis represent a serious source of hazard for many coastal and lacustrine communities. The understanding of the complex physical phenomena that govern the tsunami generation, propagation and interaction with the coast is essential to reduce and mitigate the tsunamis risk. Experimental, analytical, and numerical models have been extensively used (both as separated tools and in conjunction) to shed light on these complicated natural events. In this work, a non-exhaustive update of the state of the art related to the physical and numerical modeling techniques of landslide-generated tsunamis, with a special focus on those studies published in the last ten years, is provided. As far as numerical models are concerned, a special attention is paid to the most recently developed Computational Fluid Dynamics (CFD) techniques, whose development and application have experienced a boost up the last decade.

Tests were conducted in a 5m × 55 m wind wave tank to determine the response of a compliant tower to the combined action of random seas and a turbulent shear flow. The model, the sea state and the turbulence were modeled at a linear scale of 1:200 with other scales being determined by equality of Froude Number and fluid density. The test program included three sea states and four wind speeds including zero). The results presented include a detailed description of the model and the wind and wave conditions together with measured response spectra for all combinations of the wind and wave conditions. INTRODUCTION Compliant structures with natural frequencies well below the energy containing region of the design wave spectrum are an attractive form for deep-water production. The long fundamental natural period of this class of structure, usually greater than 30 seconds, alleviates the effect of the first order wave action. However, the structural response is sensitive to low frequency turbulent wind and non-linear (second-order) wave forces which can cause a resonant response of the lowest vibration modes. Despite the considerable advances in computational techniques and analytical models simulating the behavior of offshore structures, experimental investigation remains an alternative route to an understanding of the structural effects of environmental loads. The compliant structure studied in the model tests can be classified as a flexible tower. A hydroe1astic model of the compliant tower was constructed to study the effects of wind and wave loads on structural response at model scale and all experimental simulations were performed at the Wind Wave Testing Facility of the Boundary Layer Wind Tunnel Laboratory at the University of Western Ontario, London, Ontario. Unless otherwise stated, all response data are presented in prototype scale. The hydroe1astic model tests were designed to examine the dynamic response of the tower under controlled conditions. Laboratory scale response to prescribed loading conditions can with some restrictions, be scaled to predict the full scale structural performance. The physical modeling techniques and similitude requirements have been documented in the literature [1,2] and it is not intended to elaborate here. It is well known that both Froude number and Reynolds number similarity conditions cannot be fulfilled simultaneously in a laboratory model scale if the fluid media (air and water) used are the same as prototype. For most offshore structures, the system is dominated by gravity waves and inertia forces and Froude number similarity becomes important. Consequently, the Reynolds number similarity has to be relaxed. In Froude number scaling, the velocity, the time and the bending rigidity scale can be related to the geometric length scale as follows: (Equation available in full paper) The inability to obtain equality of Reynolds numbers detracts from the value of model results particularly if the results are to be scaled directly to prototype scale for a particular design rather than, as is the present case, used to explore interactions between wind and wave loads in a more general sense.

We present Senspectra, a computationally augmented physical modeling toolkit designed for sensing and visualization of structural strain. Senspectra seeks to explore a new direction in computational materiality, incorporating the material quality of malleable elements of an interface into its digital control structure. The system functions as a decentralized sensor network consisting of nodes, embedded with computational capabilities and a full spectrum LED, and flexible joints. Each joint functions as an omnidirectional bend sensing mechanism to sense and communicate mechanical strain between neighboring nodes. Using Senspectra, a user incrementally assembles and refines a physical 3D model of discrete elements with a real-time visualization of structural strain. While the Senspectra infrastructure provides a flexible modular sensor network platform, its primary application derives from the need to couple physical modeling techniques utilized in architecture and design disciplines with systems for structural engineering analysis. This offers direct manipulation augmented with visual feedback for an intuitive approach to physical real-time finite element analysis, particularly for organic forms.

Grey-box modelling and identification using physical knowledge and bayesian techniques

The scientific study of complex systems has transformed a wide range of disciplines in recent years, enabling researchers in both the natural and social sciences to model and predict phenomena as diverse as earthquakes, global warming, demographic patterns, financial crises, and the failure of materials. In this book, Didier Sornette boldly applies his varied experience in these areas to propose a simple, powerful, and general theory of how, why, and when stock markets crash. Most attempts to explain market failures seek to pinpoint triggering mechanisms that occur hours, days, or weeks before the collapse. Sornette proposes a radically different view: the underlying cause can be sought months and even years before the abrupt, catastrophic event in the build-up of cooperative speculation, which often translates into an accelerating rise of the market price, otherwise known as a "bubble." Anchoring his sophisticated, step-by-step analysis in leading-edge physical and statistical modeling techniques, he unearths remarkable insights and some predictions--among them, that the "end of the growth era" will occur around 2050. Sornette probes major historical precedents, from the decades-long "tulip mania" in the Netherlands that wilted suddenly in 1637 to the South Sea Bubble that ended with the first huge market crash in England in 1720, to the Great Crash of October 1929 and Black Monday in 1987, to cite just a few. He concludes that most explanations other than cooperative self-organization fail to account for the subtle bubbles by which the markets lay the groundwork for catastrophe. Any investor or investment professional who seeks a genuine understanding of looming financial disasters should read this book. Physicists, geologists, biologists, economists, and others will welcome Why Stock Markets Crash as a highly original "scientific tale," as Sornette aptly puts it, of the exciting and sometimes fearsome--but no longer quite so unfathomable--world of stock markets.Some images inside the book are unavailable due to digital copyright restrictions.

An investigation of the behaviour and energy budget of sturzstroms has been carried out using physical, analytical and numerical modelling techniques. Sturzstroms are rock slides of very large volume and extreme run out, which display intensive fragmentation of blocks of rock due to inter-particle collisions within a collisional flow. Results from centrifugal model experiments provide strong arguments to allow the micro-mechanics and energy budget of sturzstroms to be described quantitatively by a fractal comminution model. A numerical experiment using a distinct element method (DEM) indicates rock mass and boundary conditions, which allow an alternating fragmenting and dilating dispersive regime to evolve and to sustain for long enough to replicate the spreading and run out of sturzstroms without needing to resort to peculiar mechanism. The fragmenting spreading model supported here is able to explain the run out of a fluid-absent granular flow beyond the travel distance predicted by a Coulomb frictional sliding model. This, and its strong relation to internal fragmentation, suggests that a sturzstrom constitutes a landslide category of its own. This study provides a novel framework for the understanding the physics of such sturzstroms.

The quality of nutrition, physiologically balanced, environmentally friendly and healthy food contributes to the extension of human life. Global digitalization and intelligent technologies are rapidly developing around the world. At the same time, current laws protecting consumer rights and interests are rapidly becoming obsolete and failing to meet growing needs and new challenges in the booming digital world of smart technology. Existing consumer protection systems are too inertial and ignore individual consumer demands, local opportunities and regional features. Particular attention should therefore be paid to finding new opportunities to protect consumer rights by monitoring product quality at all stages of production and consumption. The new cyber-physical platform-based approach represents different physical and virtual modelling techniques and original smart tools for consumer protection using the Internet of Things, original smart sensors and mobile applications.

In this work, the spatial electro-thermal modeling and simulation of power electronic modules is discussed. It is shown how physical and mathematical modeling techniques can be combined to obtain a compact time-efficient electro-thermal simulation framework for power electronic modules. The accuracy of the modeling framework is demonstrated based on experiments. It can be used for the fast calculation of the temperature distribution of a power module in an electric vehicle over driving cycles. The spatial temperature information allows to effectively estimate the lifetime of the power module.

Rapid development in computers has led to significant advancement in simulation technology. The analysis tools such as CFD and FEA are now household tools used for improving plant operations, building reliable equipment with enhanced safety features with an eye on improving and optimizing performance. In this paper a few case studies are selectively presented to demonstrate the value of these tools to the customer — improved efficiency, reduced schedule times and cost. These examples are chosen to show how these technologies are used to identify and mitigate any safety and operational risks associated with plant design and improve the design over the projects life cycle. The first example considers a design and operation improvement in a Heat recovery Steam generator (HRSG). To reduce material and equipment costs, it is very easy to design the HRSG with sharp corners and steep angles from one module to another and keep them closer to each other. This essentially reduces the overall efficiency of the plant due to gas turbine exhaust flow non-uniformity and re-circulation zones. The existing flow correction device consisting of 32 large tubes running across the sides produces a very large pressure drop. Using CFD, a flow distribution grid is designed, providing at least a 20% improvement in velocity distribution. The second example considers a coal burning boiler performance optimization. In this boiler upgrade project, CFD is used to confirm the feasibility of increasing the capacity and reducing the particulate emissions of the coal fired furnace and steam boiler units. Some of these factors were difficult to evaluate reliably using physical scale modeling techniques that were performed mainly only for cold flow pressure drop analysis. However the experimental results were used for benchmarking the CFD results. A third example shows how fluid dynamic analysis combined with thermal and structural analysis may be used to obtain the thermal fatigue life of various components of a molecular sieve dehydrator unit, where the design life is governed by the thermal loads generated during the regeneration cycle. Based on the fatigue analysis a more effective support is designed to withstand a higher flow capacity thus increasing production.