Design and characterization of in-plane MEMS yaw rate sensor

In this paper, we present the design and characterization of a vibratory yaw rate MEMS sensor that uses in-plane motion for both actuation and sensing. The design criterion for the rate sensor is based on a high sensitivity and low bandwidth. The required sensitivity of the yawrate sensor is attained by using the inplane motion in which the dominant damping mechanism is the fluid loss due to slide film damping i.e. two-three orders of magnitude less than the squeeze-film damping in other rate sensors with out-of-plane motion. The low bandwidth is achieved by matching the drive and the sense mode frequencies. Based on these factors, the yaw rate sensor is designed and finally realized using surface micromachining. The inplane motion of the sensor is experimentally characterized to determine the sense and the drive mode frequencies, and corresponding damping ratios. It is found that the experimental results match well with the numerical and the analytical models with less than 5% error in frequencies measurements. The measured quality factor of the sensor is approximately 467, which is two orders of magnitude higher than that for a similar rate sensor with out-of-plane sense direction.

A numerical study of projectile impact on thin aluminium plates

This article deals with a simulation-based Study of the impact of projectiles on thin aluminium plates using LS-DYNA by modelling plates with shell elements and projectiles with solid elements. In order to establish the required modelling criterion in terms of element size for aluminium plates, a convergence Study of residual velocity has been carried Out by varying mesh density in the impact zone. Using the preferred material and meshing criteria arrived at here, extremely good prediction of test residual velocities and ballistic limits given by Gupta et al. (2001) for thin aluminium plates has been obtained. The simulation-based pattern of failure with localized bulging and jagged edge of perforation is similar to the perforation with petalling seen in tests. A number Of simulation-based parametric studies have been carried out and results consistent with published test data have been obtained. Despite the robust correlation achieved against published experimental results, it would be prudent to conduct one's own experiments, for a final correlation via the present modelling procedure and analysis with the explicit LS-DYNTA 970 solver. Hence, a sophisticated ballistic impact testing facility and a high-speed camera have been used to conduct additional tests on grade 1100 aluminium plates of 1 mm thickness with projectiles Of four different nose shapes. Finally, using the developed numerical simulation procedure, an excellent correlation of residual velocity and failure modes with the corresponding test results has been obtained.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

Agents Based Algorithms for Design Parameter Estimation in Contaminant Transport Inverse Problems

A considerable amount of work has been dedicated on the development of analytical solutions for flow of chemical contaminants through soils. Most of the analytical solutions for complex transport problems are closed-form series solutions. The convergence of these solutions depends on the eigen values obtained from a corresponding transcendental equation. Thus, the difficulty in obtaining exact solutions from analytical models encourages the use of numerical solutions for the parameter estimation even though, the later models are computationally expensive. In this paper a combination of two swarm intelligence based algorithms are used for accurate estimation of design transport parameters from the closed-form analytical solutions. Estimation of eigen values from a transcendental equation is treated as a multimodal discontinuous function optimization problem. The eigen values are estimated using an algorithm derived based on glowworm swarm strategy. Parameter estimation of the inverse problem is handled using standard PSO algorithm. Integration of these two algorithms enables an accurate estimation of design parameters using closed-form analytical solutions. The present solver is applied to a real world inverse problem in environmental engineering. The inverse model based on swarm intelligence techniques is validated and the accuracy in parameter estimation is shown. The proposed solver quickly estimates the design parameters with a great precision.

Concrete-filled double skin tube columns subjected to lateral impact loading: Experimental and numerical study

This research treats the lateral impact behaviour of composite columns, which find increasing use as bridge piers and building columns. It offers (1) innovative experimental methods for testing structural columns, (2) dynamic computer simulation techniques as a viable tool in analysis and design of such columns and (3) significant new information on their performance which can be used in design. The research outcomes will enable to protect lives and properties against the risk of vehicular impacts caused either accidentally or intentionally.

Studies on design, fabrication and reliability assessment of embedded passives on a high-density interconnect (HDI) organic substrate using a sequential build-up process

One of the foremost design considerations in microelectronics miniaturization is the use of embedded passives which provide practical solution. In a typical circuit, over 80 percent of the electronic components are passives such as resistors, inductors, and capacitors that could take up to almost 50 percent of the entire printed circuit board area. By integrating passive components within the substrate instead of being on the surface, embedded passives reduce the system real estate, eliminate the need for discrete and assembly, enhance electrical performance and reliability, and potentially reduce the overall cost. Moreover, it is lead free. Even with these advantages, embedded passive technology is at a relatively immature stage and more characterization and optimization are needed for practical applications leading to its commercialization.This paper presents an entire process from design and fabrication to electrical characterization and reliability test of embedded passives on multilayered microvia organic substrate. Two test vehicles focusing on resistors and capacitors have been designed and fabricated. Embedded capacitors in this study are made with polymer/ceramic nanocomposite (BaTiO3) material to take advantage of low processing temperature of polymers and relatively high dielectric constant of ceramics and the values of these capacitors range from 50 pF to 1.5 nF with capacitance per area of approximately 1.5 nF/cm(2). Limited high frequency measurement of these capacitors was performed. Furthermore, reliability assessments of thermal shock and temperature humidity tests based on JEDEC standards were carried out. Resistors used in this work have been of three types: 1) carbon ink based polymer thick film (PTF), 2) resistor foils with known sheet resistivities which are laminated to printed wiring board (PWB) during a sequential build-up (SBU) process and 3) thin-film resistor plating by electroless method. Realization of embedded resistors on conventional board-level high-loss epoxy (similar to 0.015 at 1 GHz) and proposed low-loss BCB dielectric (similar to 0.0008 at > 40 GHz) has been explored in this study. Ni-P and Ni-W-P alloys were plated using conventional electroless plating, and NiCr and NiCrAlSi foils were used for the foil transfer process. For the first time, Benzocyclobutene (BCB) has been proposed as a board level dielectric for advanced System-on-Package (SOP) module primarily due to its attractive low-loss (for RF application) and thin film (for high density wiring) properties.Although embedded passives are more reliable by eliminating solder joint interconnects, they also introduce other concerns such as cracks, delamination and component instability. More layers may be needed to accommodate the embedded passives, and various materials within the substrate may cause significant thermo -mechanical stress due to coefficient of thermal expansion (CTE) mismatch. In this work, numerical models of embedded capacitors have been developed to qualitatively examine the effects of process conditions and electrical performance due to thermo-mechanical deformations.Also, a prototype working product with the board level design including features of embedded resistors and capacitors are underway. Preliminary results of these are presented.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Numerical simulation of solidification of liquid aluminum alloy flowing on cooling slope

Preparation of semisolid slurry using a cooling slope is increasingly becoming popular, primarily because of the simplicity in design and ease control of the process. In this process, liquid alloy is poured down an inclined surface which is cooled from underneath. The cooling enables partial solidification and the incline provides the necessary shear for producing semisolid slurry. However, the final microstructure of the ingot depends on several process parameters such as cooling rate, incline angle of the cooling slope, length of the slope and initial melt superheat. In this work, a CFD model using volume of fluid (VOF) method for simulating flow along the cooling slope was presented. Equations for conservation of mass, momentum, energy and species were solved to predict hydrodynamic and thermal behavior, in addition to predicting solid fraction distribution and macrosegregation. Solidification was modeled using an enthalpy approach and a volume averaged technique for the different phases. The mushy region was modeled as a multi-layered porous medium consisting of fixed columnar dendrites and mobile equiaxed/fragmented grains. The alloy chosen for the study was aluminum alloy A356, for which adequate experimental data were available in the literature. The effects of two key process parameters, namely the slope angle and the pouring temperature, on temperature distribution, velocity distribution and macrosegregation were also studied.

An Experimental and Numerical Study of Calliphora Wing Structure

Experiments are performed to determine the mass and stiffness variations along the wing of the blowfly Calliphora. The results are obtained for a pairs of wings of 10 male flies and fresh wings are used. The wing is divided into nine locations along the span and seven locations along the chord based on venation patterns. The length and mass of the sections is measured and the mass per unit length is calculated. The bending stiffness measurements are taken at three locations, basal (near root), medial and distal (near tip) of the fly wing. Torsional stiffness measurements are also made and the elastic axis of the wing is approximately located. The experimental data is then used for structural modeling of the wing as a stepped cantilever beam with nine spanwise sections of varying mass per unit lengths, flexural rigidity (EI) and torsional rigidity (GJ) values. Inertial values of nine sections are found to approximately vary according to an exponentially decreasing law over the nine sections from root to tip and it is used to calculate an approximate value of Young's modulus of the wing biomaterial. Shear modulus is obtained assuming the wing biomaterial to be isotropic. Natural frequencies, both in bending and torsion, are obtained by solving the homogeneous part of the respective governing differential equations using the finite element method. The results provide a complete analysis of Calliphora wing structure and also provide guidelines for the biomimetic structural design of insect-scale flapping wings.

Performance study of high operating temperature HgCdTe mid wave infrared detector through numerical modeling

The design of present generation uncooled Hg1-xCdxTe infrared photon detectors relies on complex heterostructures with a basic unit cell of type (n) under bar (+)/pi/(p) under bar (+). We present an analysis of double barrier (n) under bar (+)/pi/(p) under bar (+) mid wave infrared (x = 0.3) HgCdTe detector for near room temperature operation using numerical computations. The present work proposes an accurate and generalized methodology in terms of the device design, material properties, and operation temperature to study the effects of position dependence of carrier concentration, electrostatic potential, and generation-recombination (g-r) rates on detector performance. Position dependent profiles of electrostatic potential, carrier concentration, and g-r rates were simulated numerically. Performance of detector was studied as function of doping concentration of absorber and contact layers, width of both layers and minority carrier lifetime. Responsivity similar to 0.38 A W-1, noise current similar to 6 x 10(-14) A/Hz(1/2) and D* similar to 3.1 x 10(10)cm Hz(1/2) W-1 at 0.1 V reverse bias have been calculated using optimized values of doping concentration, absorber width and carrier lifetime. The suitability of the method has been illustrated by demonstrating the feasibility of achieving the optimum device performance by carefully selecting the device design and other parameters. (C) 2010 American Institute of Physics. doi:10.1063/1.3463379]

A numerical study of projectile impact on mild steel armour plates

The present article deals with the development of a finite element modelling approach for the prediction of residual velocities of hard core ogival-nose projectiles following normal impact on mild steel target plates causing perforation. The impact velocities for the cases analysed are in the range 818–866.3 m/s. Assessment of finite element modelling and analysis includes a comprehensive mesh convergence study using shell elements for representing target plates and solid elements for jacketed projectiles with a copper sheath and a rigid core. Dynamic analyses were carried out with the explicit contact-impact LS-DYNA 970 solver. It has been shown that proper choice of element size and strain rate-based material modelling of target plate are crucial for obtaining test-based residual velocity.The present modelling procedure also leads to realistic representation of target plate failure and projectile sheath erosion during perforation, and confirms earlier observations that thermal effects are not significant for impact problems within the ordnance range. To the best of our knowledge, any aspect of projectile failure or degradation obtained in simulation has not been reported earlier in the literature. The validated simulation approach was applied to compute the ballistic limits and to study the effects of plate thickness and projectile diameter on residual velocity, and trends consistent with experimental data for similar situations were obtained.

Analytical and simulation studies of a multiprocessor system for high-speed numerical computations

This paper describes the architecture of a multiprocessor system which we call the Broadcast Cube System (BCS) for solving important computation intensive problems such as systems of linear algebraic equations and Partial Differential Equations (PDEs), and highlights its features. Further, this paper presents an analytical performance study of the BCS, and it describes the main details of the design and implementation of the simulator for the BCS.

Numerical and experimental study of the thermal behaviour of coining and upsetting processes

A numerical simulation technique has been employed to study the thermal behavior of hot-forging type forming processes. Experiments on the coining and upsetting of an aluminum billet were conducted to validate the numerical predictions. Typical forming conditions for both the coining and upsetting processes were then studied in detail. an electrical analogy scheme was used to determine the thermal contact resistance. This scheme can conviniently provide the interface characteristics for typical processing conditions, which normally involve high pressures and temperatures. A single forging cycle was first considered, and then a batch of twenty-five forgings was studied. Each forging cycle includes the billet mounting, ascent, loading, dwelling, unloading, descent, and billet removal stages. The temperature distribution in the first forging to be formed is found to be significantly different from that at the end of the batch. In industry, forging is essentially a batch operation. The influence of forming speed and reduction on thermal characteristics was investigated also. The variations that can occur in the process design by considering differences in temperature characteristics are discussed also.