34 resultados para modern dynamics simulation


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This paper reviews the development of computational fluid dynamics (CFD) specifically for turbomachinery simulations and with a particular focus on application to problems with complex geometry. The review is structured by considering this development as a series of paradigm shifts, followed by asymptotes. The original S1-S2 blade-blade-throughflow model is briefly described, followed by the development of two-dimensional then three-dimensional blade-blade analysis. This in turn evolved from inviscid to viscous analysis and then from steady to unsteady flow simulations. This development trajectory led over a surprisingly small number of years to an accepted approach-a 'CFD orthodoxy'. A very important current area of intense interest and activity in turbomachinery simulation is in accounting for real geometry effects, not just in the secondary air and turbine cooling systems but also associated with the primary path. The requirements here are threefold: capturing and representing these geometries in a computer model; making rapid design changes to these complex geometries; and managing the very large associated computational models on PC clusters. Accordingly, the challenges in the application of the current CFD orthodoxy to complex geometries are described in some detail. The main aim of this paper is to argue that the current CFD orthodoxy is on a new asymptote and is not in fact suited for application to complex geometries and that a paradigm shift must be sought. In particular, the new paradigm must be geometry centric and inherently parallel without serial bottlenecks. The main contribution of this paper is to describe such a potential paradigm shift, inspired by the animation industry, based on a fundamental shift in perspective from explicit to implicit geometry and then illustrate this with a number of applications to turbomachinery.

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Inflatable aerodynamic decelerators have potential advantages for planetary re-entry in robotic and human exploration missions. It is theorized that volume-mass characteristics of these decelerators are superior to those of common supersonic/subsonic parachutes and after deployment they may suffer no instabilities at high Mach numbers. A high fidelity computational fluid-structure interaction model is employed to investigate the behavior of tension cone inflatable aeroshells at supersonic speeds up to Mach 2.0. The computational framework targets the large displacements regime encountered during the inflation of the decelerator using fast level set techniques to incorporate boundary conditions of the moving structure. The preliminary results indicate large but steady aeroshell displacement with rich dynamics, including buckling of the inflatable torus that maintains the decelerator open under normal operational conditions, owing to interactions with the turbulent wake. Copyright © 2009 by the American Institute of Aeronautics and Astronautics, Inc.

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Inflatable aerodynamic decelerators have potential advantages for planetary re-entry in robotic and human exploration missions. In this paper, we focus on an inflatable tension cone design that has potential advantages over other geometries. A computational fluid-structure interaction model of a tension cone is employed to investigate the behavior of the inflatable aeroshell at supersonic speeds for conditions matching recent experimental results. A parametric study is carried out to investigate the deflections of the tension cone as a function of inflation pressure of the torus at a Mach of 2.5. Comparison of the behavior of the structure, amplitude of deformations, and determined loads are reported. © 2010 by the American Institute of Aeronautics and Astronautics, Inc.

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Climate change is becoming a serious issue for the construction industry, since the time scales at which climate change takes place can be expected to show a true impact on the thermal performance of buildings and HVAC systems. In predicting this future building performance by means of building simulation, the underlying assumptions regarding thermal comfort conditions and the related heating, ventilating and air conditioning (HVAC) control set points become important. This article studies the thermal performance of a reference office building with mixedmode ventilation in the UK, using static and adaptive thermal approaches, for a series of time horizons (2020, 2050 and 2080). Results demonstrate the importance of the implementation of adaptive thermal comfort models, and underpin the case for its use in climate change impact studies. Adaptive thermal comfort can also be used by building designers to make buildings more resilient towards change. © 2010 International Building Performance Simulation Association (IBPSA).

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Product-Service Systems (PSS) are new business strategies moving and extending the product value towards its functional usage and related required services. From a theoretical point of view the PSS concept is known since a decade and many Authors reported reasonable possible success factors: higher profits over the entire life-cycle, diminished environmental burden, and localization of required services. Nevertheless the PSS promises remain quantitatively unproven relaying on a simple theory that involves a few constructs with some empirical grounding, but that is limited by weak conceptualization, few propositions, and/or rough underlying theoretical logic. A plausible interpretation to analyze the possible evolution of a PSS strategy could be considering it as a new business proposition competing on a traditional Product-Oriented (PO) market, assumed at its own equilibrium state at a given time. The analysis of the dynamics associated to a possible transition from a traditional PO to a PSS strategy allows investigating the main parameters and variables influencing an eventual successful adoption. This research is worthwhile because organizations undergoing fundamental PSS strategy are concerned about change and inertia key processes which, despite equilibrium theory and because of negative feedback loops, could undermine, economically, the return of their PSS proposition. In this paper Authors propose a qualitative System Dynamics (SD) approach by considering the PSS as a perturbation of an existing PO market featured by a set of known parameters. The proposed model incorporates several PSS factors able to influence the success of a PSS proposition under a set of given and justified assumptions, attempting to place this business strategy in a dynamic framework.

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Elderly and disabled people can be hugely benefited through the advancement of modern electronic devices, as those can help them to engage more fully with the world. However, existing design practices often isolate elderly or disabled users by considering them as users with special needs. This article presents a simulator that can reflect problems faced by elderly and disabled users while they use computer, television, and similar electronic devices. The simulator embodies both the internal state of an application and the perceptual, cognitive, and motor processes of its user. It can help interface designers to understand, visualize, and measure the effect of impairment on interaction with an interface. Initially a brief survey of different user modeling techniques is presented, and then the existing models are classified into different categories. In the context of existing modeling approaches the work on user modeling is presented for people with a wide range of abilities. A few applications of the simulator, which shows the predictions are accurate enough to make design choices and point out the implication and limitations of the work, are also discussed. © 2012 Copyright Taylor and Francis Group, LLC.

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A workshop on the computational fluid dynamics (CFD) prediction of shock boundary-layer interactions (SBLIs) was held at the 48th AIAA Aerospace Sciences Meeting. As part of the workshop, numerous CFD analysts submitted solutions to four experimentally measured SBLIs. This paper describes the assessment of the CFD predictions. The assessment includes an uncertainty analysis of the experimental data, the definition of an error metric, and the application of that metric to the CFD solutions. The CFD solutions provided very similar levels of error and, in general, it was difficult to discern clear trends in the data. For the Reynolds-averaged Navier-Stokes (RANS) methods, the choice of turbulence model appeared to be the largest factor in solution accuracy. Scale-resolving methods, such as large-eddy simulation (LES), hybrid RANS/LES, and direct numerical simulation, produced error levels similar to RANS methods but provided superior predictions of normal stresses. Copyright © 2012 by Daniella E. Raveh and Michael Iovnovich.

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Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization. © 2012 Kadiallah et al.

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We show how machine learning techniques based on Bayesian inference can be used to reach new levels of realism in the computer simulation of molecular materials, focusing here on water. We train our machine-learning algorithm using accurate, correlated quantum chemistry, and predict energies and forces in molecular aggregates ranging from clusters to solid and liquid phases. The widely used electronic-structure methods based on density-functional theory (DFT) give poor accuracy for molecular materials like water, and we show how our techniques can be used to generate systematically improvable corrections to DFT. The resulting corrected DFT scheme gives remarkably accurate predictions for the relative energies of small water clusters and of different ice structures, and greatly improves the description of the structure and dynamics of liquid water.

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A recent trend in spoken dialogue research is the use of reinforcement learning to train dialogue systems in a simulated environment. Past researchers have shown that the types of errors that are simulated can have a significant effect on simulated dialogue performance. Since modern systems typically receive an N-best list of possible user utterances, it is important to be able to simulate a full N-best list of hypotheses. This paper presents a new method for simulating such errors based on logistic regression, as well as a new method for simulating the structure of N-best lists of semantics and their probabilities, based on the Dirichlet distribution. Off-line evaluations show that the new Dirichlet model results in a much closer match to the receiver operating characteristics (ROC) of the live data. Experiments also show that the logistic model gives confusions that are closer to the type of confusions observed in live situations. The hope is that these new error models will be able to improve the resulting performance of trained dialogue systems. © 2012 IEEE.

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The information provided by the in-cylinder pressure signal is of great importance for modern engine management systems. The obtained information is implemented to improve the control and diagnostics of the combustion process in order to meet the stringent emission regulations and to improve vehicle reliability and drivability. The work presented in this paper covers the experimental study and proposes a comprehensive and practical solution for the estimation of the in-cylinder pressure from the crankshaft speed fluctuation. Also, the paper emphasizes the feasibility and practicality aspects of the estimation techniques, for the real-time online application. In this study an engine dynamics model based estimation method is proposed. A discrete-time transformed form of a rigid-body crankshaft dynamics model is constructed based on the kinetic energy theorem, as the basis expression for total torque estimation. The major difficulties, including load torque estimation and separation of pressure profile from adjacent-firing cylinders, are addressed in this work and solutions to each problem are given respectively. The experimental results conducted on a multi-cylinder diesel engine have shown that the proposed method successfully estimate a more accurate cylinder pressure over a wider range of crankshaft angles. Copyright © 2012 SAE International.

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Superhydrophobic surfaces are shown to be effective for surface drag reduction under laminar regime by both experiments and simulations (see for example, Ou and Rothstein, Phys. Fluids 17:103606, 2005). However, such drag reduction for fully developed turbulent flow maintaining the Cassie-Baxter state remains an open problem due to high shear rates and flow unsteadiness of turbulent boundary layer. Our work aims to develop an understanding of mechanisms leading to interface breaking and loss of gas pockets due to interactions with turbulent boundary layers. We take advantage of direct numerical simulation of turbulence with slip and no-slip patterned boundary conditions mimicking the superhydrophobic surface. In addition, we capture the dynamics of gas-water interface, by deriving a proper linearized boundary condition taking into account the surface tension of the interface and kinematic matching of interface deformation and normal velocity conditions on the wall. We will show results from our simulations predicting the dynamical behavior of gas pocket interfaces over a wide range of dimensionless surface tensions.

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An increasin g interest in biofuel applications in modern engines requires a better understanding of biodiesel combustion behaviour. Many numerical studies have been carried out on unsteady combustion of biodiesel in situations similar to diesel engines, but very few studies have been done on the steady combustion of biodiesel in situations similar to a gas turbine combustor environment. The study of biodiesel spray combustion in gas turbine applications is of special interest due to the possible use of biodiesel in the power generation and aviation industries. In modelling spray combustion, an accurate representation of the physical properties of the fuel is a first important step, since spray formation is largely influenced by fuel properties such as viscosity, density, surface tension and vapour pressure. In the present work, a calculated biodiesel properties database based on the measured composition of Fatty Acid Methyl Esters (FAME) has been implemented in a multi-dimensional Computational Fluid Dynamics (CFD) spray simulation code. Simulations of non-reacting and reacting atmospheric-pressure sprays of both diesel and biodiesel have been carried out using a spray burner configuration for which experimental data is available. A pre-defined droplet size probability density function (pdf) has been implemented together with droplet dynamics based on phase Doppler anemometry (PDA) measurements in the near-nozzle region. The gas phase boundary condition for the reacting spray cases is similar to that of the experiment which employs a plain air-blast atomiser and a straight-vane axial swirler for flame stabilisation. A reaction mechanism for heptane has been used to represent the chemistry for both diesel and biodiesel. Simulated flame heights, spray characteristics and gas phase velocities have been found to compare well with the experimental results. In the reacting spray cases, biodiesel shows a smaller mean droplet size compared to that of diesel at a constant fuel mass flow rate. A lack of sensitivity towards different fuel properties has been observed based on the non-reacting spray simulations, which indicates a need for improved models of secondary breakup. By comparing the results of the non-reacting and reacting spray simulations, an improvement in the complexity of the physical modelling is achieved which is necessary in the understanding of the complex physical processes involved in spray combustion simulation. Copyright © 2012 SAE International.