New generation superabrasive tool with monolayer configuration

In recent years, chemically bonded single-layer diamond abrasive tools are getting preference over their galvanically bonded counterparts for many applications because of their outstanding performance. The chemical bonding is achieved by direct brazing of the diamond grit to a steel substrate with an active braze alloy. The present study has shown that the principle of chemical bonding can be extended to fabricate monolayer CBN-coated tools. It is further indicated that understanding of the influence of various construction parameters on the formation of the topography of the tool is required to prepare a good brazed tool. Various case studies are presented to show the influence of the topography of the working surface of such a tool, work material characteristics and grinding parameters on the behaviour of the tool in terms of cutting capability, force and power requirement, loading, grit wear and grit pull out.     

Microstructural development in microsecond pulsed laser melted polycrystalline nickel

The microsecond Nd glass pulsed laser interaction with polycrystalline nickel was studied with particular emphasis on melting and the nature of the microstructural development following irradiation. The change in the melt pool shape and the melting efficiency as a function of the total laser power has been determined. Evidence is presented to show that for low energy pulse, the microstructural development accompanies fresh nucleation of grains and leads to a finer grain size than that of the substrate. At a higher energy level, growth competition leads to a coarser grain size. We also report a banded feature roughly parallel to the melt substrate interface that develops in the resolidified region during high energy interaction. These results are discussed in the light of our present understanding of rapid solidification processes.     

Application of optimization methods to helicopter rotor blade design

The minimum weight design of helicopter rotor blades with constraints on multiple coupled flap-lag natural frequencies is studied in this paper. A constraint is also imposed on the minimum value of the autorotational inertia of the blade to ensure sufficient autorotational inertia to autorotate in case of an engine failure. A stress constraint is used to guard against structural failure due to blade centrifugal forces. Design variables include blade taper ratio, dimensions of the box beam located inside the airfoil and magnitudes of the nonstructural weights. The program CAMRAD is used for the blade modal analysis and the program CONMIN for the optimization. In addition, a linear approximation involving Taylor series expansion is used to reduce the analysis effort. The procedure contains a sensitivity analysis which consists of analytical derivatives of the objective function, the autorotational inertia constraint and the stress constraints. A central finite difference scheme is used for the derivatives of the frequency constraints. Optimum designs are obtained for both rectangular and tapered blades. The paper also discusses the effect of adding constraints on higher frequencies and stresses on the optimum designs. b box beam width - c chord - f ₁,f ₃,f ₄ first three lead-lag dominated frequencies (elastic modes) - f ₂,f ₅ first two flapping dominated frequencies (elastic modes) - g constraint function - h box beam height - h(z) box beam height variation along blade span - n number of blades - r _j distance from the root to the center of thej-th segment - t ₁,t ₂,t ₃ box beam wall thicknesses - x, y, z reference axes - A box beam cross-sectional area - AI autorotational inertia - E Young's modulus - F objective function - FS factor of safety - GJ torsional stiffness - I _x ,I _y total principal area moments of inertia about reference axes - L _j length ofj-th segment - M _j total mass ofj-th segment - N total number of blade segments - NDV number of design variables - R blade radius - W total blade weight - W() blade weight as a function of design variable - W _b box beam weight - W _o nonstructural blade weight (weight of skin, honeycomb, etc. along with tuning/lumped weights) - prescribed autorotational inertia - design variable increment - _h taper ratio inz direction - _i i-th design variable - _j mass density of thej-th segment - _j stress inj-th segment - _max maximum allowable stress - blade RPM - r root value - t tip value - L lower bound - U upper bound - ^ approximate value This paper is declared a work of the U.S. Government and is not subject to copyright protection in the United States     

Design of particle-reinforced polyurethane mould materials for soft tooling process using evolutionary multi-objective optimization algorithms

Polyurethane is used for making mould in soft tooling (ST) process for producing wax/plastic components. These wax components are later used as pattern in investment casting process. Due to low thermal conductivity of polyurethane, cooling time in ST process is long. To reduce the cooling time, thermal conductive fillers are incorporated into polyurethane to make composite mould material. However, addition of fillers affects various properties of the ST process, such as stiffness of the mould box, rendering flow-ability of melt mould material, etc. In the present work, multi-objective optimization of various conflicting objectives (namely maximization of equivalent thermal conductivity, minimization of effective modulus of elasticity, and minimization of equivalent viscosity) of composite material are conducted using evolutionary algorithms (EAs) in order to design particle-reinforced polyurethane composites by finding the optimal values of design parameters. The design parameters include volume fraction of filler content, size and shape factor of filler particle, etc. The Pareto-optimal front is targeted by solving the corresponding multi-objective problem using the NSGA-II procedure. Then, suitable multi-criterion decision-making techniques are employed to select one or a small set of the optimal solution(s) of design parameter(s) based on the higher level information of the ST process for industrial applications. Finally, the experimental study with a typical real industrial application demonstrates that the obtained optimal design parameters significantly reduce the cooling time in soft tooling process keeping other processing advantages.     

On the sizing of a solar thermal electricity plant for multiple objectives using evolutionary optimization

Design, implementation and operation of solar thermal electricity plants are no more an academic task, rather they have become a necessity. In this paper, we work with power industries to formulate a multi-objective optimization model and attempt to solve the resulting problem using classical as well as evolutionary optimization techniques. On a set of four objectives having complex trade-offs, our proposed procedure first finds a set of trade-off solutions showing the entire range of optimal solutions. Thereafter, the evolutionary optimization procedure is combined with a multiple criterion decision making (MCDM) approach to focus on preferred regions of the trade-off frontier. Obtained solutions are compared with a classical generating method. Eventually, a decision-maker is involved in the process and a single preferred solution is obtained in a systematic manner. Starting with generating a wide spectrum of trade-off solutions to have a global understanding of feasible solutions, then concentrating on specific preferred regions for having a more detailed understanding of preferred solutions, and then zeroing on a single preferred solution with the help of a decision-maker demonstrates the use of multi-objective optimization and decision making methodologies in practice. As a by-product, useful properties among decision variables that are common to the obtained solutions are gathered as vital knowledge for the problem. The procedures used in this paper are ready to be used to other similar real-world problem solving tasks.     

Dual-Metal Double-Gate with Low-k/High-k Oxide Stack Junctionless MOSFET for a Wide Range of Protein Detection: a Fully Electrostatic Based Numerical Approach

Silicon - We investigate the performance of a dielectric modulated dual-metal double-gate with low-k/high-k oxide stack junctionless MOSFET (DM-DG-LK/HK-S JL-MOSFET) based sensor device for...     

Evaluation of wear of turning carbide inserts using neural networks

Recent trends, being towards mostly unmanned automated machining systems and consistent system operations, need reliable on-line monitoring processes. A proper on-line cutting tool condition monitoring system is essential for deciding when to change the tool. Many methods have been attempted in this connection.Recently, artificial neural networks have been tried for this purpose because of its inherent simplicity and reasonably quick data-processing capability. The present work uses the back propagation algorithm for training the neural network of 5-3-1 structure. The technique shows close matching of estimation of average flank wear and directly measured wear value. Thus the system developed demonstrates the possibility of successful tool wear monitoring on-line.