Fatigue crack growth behavior of X2095 Al–Li alloy

Microstructures and micro-textures of X2095 Al–Li alloy in as-received/superplastic state were characterized by means of SEM/BDS, X-ray diffraction and orientation imaging microscopy (OIM). It was observed that the microstructure of the alloy was typical of a particulate-reinforced composite material, consisting of aluminum matrix and homogeneously distributed T_B(Al₇Cu₄Li) particles with a volume fraction of about 10%. Brass-type texture was the dominant texture component. Both constant amplitude and near-threshold fatigue crack growth rates of the alloy in the L–T and T–L orientations were determined at different stress ratios. Particular attention was paid to the role of the T_B phase in the fatigue crack growth. When a fatigue crack approached a T_B particle, the crack basically meandered to avoid the particle. The T_B particles thus provided a strong resistance to the propagation of fatigue crack by promoting crack deflection and the related crack closure effects. The fatigue crack propagation behavior has been explained by the microstructural features, micro-textures, cracking characteristics and crack closure effects.     

Stabilization of a 3D axially symmetric pendulum

Stabilizing controllers are developed for a 3D pendulum assuming that the pendulum has a single axis of symmetry and that the center of mass lies on the axis of symmetry. This assumption allows development of a reduced model that forms the basis for controller design and global closed-loop analysis; this reduced model is parameterized by the constant angular velocity component of the 3D pendulum about its axis of symmetry. Several different controllers are proposed. Controllers based on angular velocity feedback only, asymptotically stabilize the hanging equilibrium. Then controllers are introduced, based on angular velocity and reduced attitude feedback, that asymptotically stabilize either the hanging equilibrium or the inverted equilibrium. These problems can be viewed as stabilization of a Lagrange top. Finally, if the angular velocity about the axis of symmetry is assumed to be zero, controllers are introduced, based on angular velocity and reduced attitude feedback, that asymptotically stabilize either the hanging equilibrium or the inverted equilibrium. This problem can be viewed as stabilization of a spherical pendulum.     

Modified neo-fuzzy neuron-based approach for economic and environmental optimal power dispatch

At the central energy management center in a power system, the real time controls continuously track the load changes and endeavor to match the total power demand with total generation in such a manner that the operating cost is minimized while all the operating constraints are satisfied. However, due to the strict government regulations on environmental protection, operation at minimum cost is no longer the only criterion for dispatching electrical power. The idea behind the environmentally constrained economic dispatch formulation is to estimate the optimal generation schedule of generating units in such a manner that fuel cost and harmful emission levels are both simultaneously minimized for a given load demand. Conventional optimization techniques become very time consuming and computationally extensive for such complex optimization tasks. These methods are hence not suitable for on-line use. Neural networks and fuzzy systems can be trained to generate accurate relations among variables in complex non-linear dynamical environment, as both are model-free estimators. The existing synergy between these two fields has been exploited in this paper for solving the economic and environmental dispatch problem on-line. A multi-output modified neo-fuzzy neuron (NFN), capable of real time training is proposed for economic and environmental power generation allocation.This model is found to achieve accurate results and the training is observed to be faster than other popular neural networks. The proposed method has been tested on medium-sized sample power systems with three and six generating units and found to be suitable for on-line combined environmental economic dispatch (CEED).     

Flow simulations in arbitrarily complex cardiovascular anatomies – An unstructured Cartesian grid approach

Image guided computational fluid dynamics is attracting increasing attention as a tool for refining in vivo flow measurements or predicting the outcome of different surgical scenarios. Sharp interface Cartesian/Immersed-Boundary methods constitute an attractive option for handling complex in vivo geometries but their capability to carry out fine-mesh simulations in the branching, multi-vessel configurations typically encountered in cardiovascular anatomies or pulmonary airways has yet to be demonstrated. A major computational challenge stems from the fact that when such a complex geometry is immersed in a rectangular Cartesian box the excessively large number of grid nodes in the exterior of the flow domain imposes an unnecessary burden on both memory and computational overhead of the Cartesian solver without enhancing the numerical resolution in the region of interest. For many anatomies, this added burden could be large enough to render comprehensive mesh refinement studies impossible. To remedy this situation, we recast the original structured Cartesian formulation of Gilmanov and Sotiropoulos [Gilmanov A, Sotiropoulos F. A hybrid Cartesian/immersed boundary method for simulating flows with 3D, geometrically complex, moving bodies. J Comput Phys 2005;207(2):457–92] into an unstructured Cartesian grid layout. This simple yet powerful approach retains the simplicity and computational efficiency of a Cartesian grid solver, while drastically reducing its memory footprint. The method is applied to carry out systematic mesh refinement studies for several internal flow problems ranging in complexity from flow in a 90° pipe bend to flow in an actual, patient-specific anatomy reconstructed from magnetic resonance images. Finally, we tackle the challenging clinical scenario of a single-ventricle patient with severe arterio-venous malformations, seeking to provide a fluid dynamics prospective on a clinical problem and suggestions for procedure improvements. Results from these simulations demonstrate very complex cardiovascular flow dynamics and underscore the need for high-resolution simulations prior to drawing any clinical recommendations.     

UASB Treatment of Tapioca Starch Wastewater

Feasibility of the upflow anaerobic sludge blanket (UASB) process was investigated for the treatment of tapioca starch industry wastewater. After removal of suspended solids by simple gravity settling, starch wastewater was used as a feed. Start-up of a 21.5-L reactor with diluted feed of approximately 3,000 mg∕L chemical oxygen demand (COD) was accomplished in about 6 weeks using seed sludge from an anaerobic pond treating tapioca starch wastewater. By the end of the start-up period, gas productivity of 4–5 m3/m3r?day was obtained. Undiluted supernatant wastewater with a COD concentration of 12,000–24,000 mg∕L was fed during steady-state reactor operation at an organic loading rate of 10–16 kg COD/m3r?day. The upflow velocity was maintained at 0.5 m∕h with a recirculation ratio of 4:1. COD conversion efficiencies >95% and gas productivity of 5–8 m3/m3r?day were obtained. These results indicated that removal of starch solids from wastewater by simple gravity settling was sufficient to obtain satisfactory performance of the UASB process.     

Generalized neuron-based PSS and adaptive PSS

Artificial neural networks can be used as intelligent controllers to control non-linear, dynamic systems through learning, which can easily accommodate the non-linearities and time dependencies. However, they require large training time and large number of neurons to deal with complex problems. Taking benefit of the characteristics of a Generalized Neuron that requires much smaller training data and shorter training time, a Generalized Neuron-Based Power System Stabilizer (GNPSS) and an adaptive version of the same have been developed. The objective of this paper is to compare the performance of the GNPSS with that of an adaptive version, the weights of which are updated on-line.     

Thermal treatment of toxic metals of industrial hazardous wastes with fly ash and clay

Waste generated from galvanizing and metal finishing processes is considered to be a hazardous due to the presence of toxic metals like Pb, Cu, Cr, Zn, etc. Thermal treatment of such types of wastes in the presence of clay and fly ash can immobilizes their toxic metals to a maximum level. After treatment solidified mass can be utilized in construction or disposed off through land fillings without susceptibility of re-mobilization of toxic metals. In the present investigation locally available clay and fly ash of particular thermal power plant were used as additives for thermal treatment of both of the wastes in their different proportions at 850, 900 and 950 degrees C. Observed results indicated that heating temperature to be a key factor in the immobilization of toxic metals of the waste. It was noticed that the leachability of metals of the waste reduces to a negligible level after heating at 950 degrees C. Thermally treated solidified specimen of 10% waste and remaining clay have shown comparatively a higher compressive strength than clay fired bricks used in building construction. Though, thermally heated specimens made of galvanizing waste have shown much better strength than specimen made of metal finishing waste. The lechability of toxic metals like Cr, Cu, Pb and Zn became far below from their regulatory threshold after heating at 950 degrees C. Addition of fly ash did not show any improvement either in engineering property or in leachability of metals from the solidified mass. X-ray diffraction (XRD) analysis of the solidified product confirmed the presence of mixed phases of oxides of metals.