Non-equilibrium solidification of undercooled droplets during atomization process

Thermal history of droplets associated with gas atomization of melt has been investigated. A mathematical model, based on classical theory of heterogeneous nucleation and volume separation of nucleants among droplets size distribution, is described to predict undercooling of droplets. Newtonian heat flow condition coupled with velocity dependent heat transfer coefficient is used to obtain cooling rate before and after nucleation of droplets. The results indicate that temperature profile of droplets in the spray during recalescence, segregated and eutectic solidification regimes is dependent on their size and related undercooling. The interface temperature during solidification of undercooled droplets rapidly approaches the liquidus temperature of the alloy with a subsequent decrease in solid-liquid interface velocity. A comparison in cooling rates of atomized powder particles estimated from secondary dendrite arm spacing measurements are observed to be closer to those predicted from the model during segregated solidification regime of large size droplets.     

Survey of denoising,segmentation and classification of magnetic resonance imaging for prostate cancer

Multimedia Tools and Applications - Prostate cancer (PCa) has become the second most dreadful cancer in men after lung cancer. Traditional approaches used for treatment of PCa were manual, time...     

Control of systems with actuator saturation non-linearities: An LMI approach

In this paper, we develop a static, full-state feedback and a dynamic, output feedback control design framework for continuous-time, multivariable, linear, time-invariant systems subject to time-invariant, sector-bounded, input non-linearities. The proposed framework directly accounts for robust stability and robust performance over the class of input non-linearities. Specifically, the problem of feedback control design in the presence of time-invariant, sector-bounded, input non-linearities is embedded within a Lure-Postnikov Lyapunov function framework by constructing a set of linear-matrix-inequality conditions whose solution guarantees closed-loop asymptotic stability with guaranteed domains of attraction in the face of time-invariant, sector-bounded, actuator non-linearities. A detailed numerical algorithm is provided for solving the linear-matrix-inequality conditions arising in actuator saturation control. Three illustrative numerical examples are presented to demonstrate the effectiveness of the proposed approach.     

A framework for rapid computational prototyping of manufacturing entities

A framework for enhancement of conceptual tools for rapid computational prototyping of manufacturing entities is presented. A typical manufacturing entity (i.e. manufacturing system and/or individual part) is hierarchically represented in a computer and coupled with applications by dividing its information content into three computational elements: data, drawing and user interface. The information content is divided in this way because each of the above elements has a sufficiently distinct requirement for an efficient computer implementation. Although independent advances have taken place in computer data representation by highly efficient and focused data structures, in drawing representation by sophisticated computer graphics, as well as in user interface by a variety of interface media, these advances cannot be directly utilized in the design of a manufacturing entity unless they are efficiently integrated by relatively small programming effort as is deseribed in this rapid prototyping framework. The framework is implemented in object-oriented programming. A breadth of application areas for the framework is illustrated, and specific details are illustrated with reference to depth in one application area.     

Error compensation in machine tools: a neural network approach

For a non-idealized machine tool, each point in the workspace is associated with a tool point positioning error vector. If this error map can be determined, then it is possible to substantially improve the positioning performance of the machine by introducing suitable compensation into the control loop. This paper explores the possibility of using an artifical neural network (ANN) to compute this mapping. The training set for the ANN is obtained by mounting a physical artifact whose dimensions are precisely known in the machine's workspace. The machine, equipped with a touch trigger probe, measures the positions of features on the artifact. The difference between the machine reading and the known dimension is the machine error at that point in the workspace. Using standard modeling techniques, the kinematic error model for a CNC turning center was developed. This model was parameterized by measurement of the parametric error functions using a laser interferometer, electronic levels and a precision square. The kinematic model was then used to simulate the artifact-measuring process and develop the ANN training set. The effect of changing artifact geometry was explored and a machining operation was simulated using the ANN output to provide compensation. The results show that the ANN is capable of learning the error map of a real machine, and that ANN-based compensation can significantly reduce part-dimensional errors.     

Control of a robotic orthosis for gait rehabilitation

Robot assisted gait training may help in producing rapid improvements in functional gait parameters. This paper presents new experimental results with an intrinsically compliant robotic gait training orthosis. The newly developed robotic orthosis has 6 degrees of freedom (DOFs). A trajectory tracking controller based on the boundary layer augmented sliding control (BASMC) law was implemented to guide the subject’s limbs on physiological gait trajectories. The compliance of the robotic orthosis sagittal plane hip and knee joints was also controlled, independently of the trajectory tracking control. The robotic orthosis and the control scheme were evaluated on three neurologically intact subjects walking on a treadmill. A maximum trajectory tracking error of 10° was recorded at the hip and knee sagittal plane joints. The results showed that subjects can walk in the robotic orthosis with comfort and the BASMC law was able to guide the subject’s limbs on reference physiological trajectories.     

Architectural considerations for next-generation file systems

Integration – supporting multiple application classes with heterogeneous performance requirements – is an emerging trend in networks, file systems, and operating systems. We evaluate two architectural alternatives – partitioned and integrated – for designing next-generation file systems. Whereas a partitioned server employs a separate file system for each application class, an integrated file server multiplexes its resources among all application classes; we evaluate the performance of the two architectures with respect to sharing of disk bandwidth among the application classes. We show that although the problem of sharing disk bandwidth in integrated file systems is conceptually similar to that of sharing network link bandwidth in integrated services networks, the arguments that demonstrate the superiority of integrated services networks over separate networks are not applicable to file systems. Furthermore, we show that: an integrated server outperforms the partitioned server in a large operating region and has slightly worse performance in the remaining region; the capacity of an integrated server is larger than that of the partitioned server; and an integrated server outperforms the partitioned server by a factor of up to 6 in the presence of bursty workloads.     

Robust H∞ stabilization via parametrized Lyapunovbounds

The parametrized Lyapunov bounding technique of Haddad and Bernstein (1991, 1993, 1995) is extended to include an H_∞ -disturbance attenuation constraint. The results presented in this paper provide a framework for designing fixed-order (i.e., full- and reduced-order) controllers that guarantee robust H₂ and H_∞ performance in the presence of structured constant real parameter variations in the state space model