Range Of Parameter Variations Research Articles

A Survey-cum-Tutorial on Approximations to Gaussian ${Q}$ Function for Symbol Error Probability Analysis Over Nakagami-${m}$ Fading Channels

This paper is a survey-cum-tutorial on the Gaussian Q function and its approximations; and their significance in computing the error probabilities over Nakagami-m fading. The goal is to focus on benefits of approximate computing over perfect solutions. Undoubtedly their exist closed-form solutions to some integrals involved in the error probabilities, but these either involve complex mathematical computations or are undefined for complete range of parameter variations, i.e., are valid only for certain specific parameter values. On the other hand approximations result in general solutions which reduce the computation complexity and are also valid for the entire range of parameter variations; though this comes at a cost, as approximations tend to introduce slight errors in computations. Through this paper, we analyze approximations for their simplicity, analytical tractability, and accuracy to understand how it can benefit research in domains where perfect solutions are either lacking or complex. We focus on Nakagami-m as it spans wide range of fading and covers other Nakagami distributions as special cases. For various digital modulation schemes the error probabilities are first expressed in closed-form using approximations, which are then compared for their accuracy over wide range of signal-to-noise ratio (SNR) [-10, 60] dB, along with variations in the fading parameter m.

Protection of Power System during Cyber-Attack using Artificial Neural Network

Impacts of frequency and voltage disturbance on an isolated power system caused by cyber-attack have been discussed, and a neural network-based protective approach has been proposed in this research work. Adaptive PID controllers for both load frequency control and automatic voltage regulator have been implemented using an artificial neural network-oriented by genetic algorithm. The parameters of the PID controller have been tuned offline by using a genetic algorithm over a wide range of system parameter variations. These data have been used to train the neural network. Three input switch has been implemented to control governor speed regulation and amplifier gain. For load frequency control neural network tuned PID controller mitigate frequency disturbance 48% faster than manually tuned PID and for the automatic voltage regulator, neural network tuned PID controller mitigate voltage disturbance 70% faster than manually tuned PID during cyber-attack.

An Accurate Tool for Detecting Stator Inter-Turn Fault in LSPMSM

This paper proposes an accurate diagnosing tool that can predict the stator inter-turn size in line start permanent magnetic synchronous motor (LSPMSM). The proposed diagnosing approach is developed based on an experimentally validated mathematical model of the motor under inter-turn fault. The developed model has been tested using MATLAB® under different loading and fault size conditions. Since the stator currents and voltages are easily accessible, it is decided to use them as the key signatures for developing the diagnostic tool. Several time and frequency-based features have been extracted using motor current and voltage waveforms under different loading and fault size conditions. The developed tool has been designed to correlate the extracted features with its corresponding size of stator inter-turn fault. Finally, testing of the developed diagnosis tool shows a high accuracy of 96% in detecting the size. Moreover, the proposed diagnostic tool is examined against motor parameter variations. The results confirm the robustness of the proposed approach where the accuracy is slightly affected under a wide range of motor parameter variations.

The effects of in-plane and out-of-plane constraints on J-R curves for X80 steel: A study using clamped SENT specimens

In the present paper, an experimental program was carried out to develop J-R curves using clamped single edge notched tension (SENT) specimens. A wide range of geometrical parameter variations is considered including different crack depth to plate width ratios (a/W) and plate thickness to width ratios (B/W). The material studied is the oil and gas pipeline steel API X80. Power law curve fitting parameters and tearing modulus are obtained for the J-R curves using the unloading compliance (UC) method for the clamped SENT specimens. Moreover, in-plane and out-of-plane constraint effects on J-R curves using clamped SENT specimens are studied, the second terms in the Williams’ series expansion are used to quantify the constraint effects. Specifically, it is demonstrated that the normalized T11 and the independent portion of T33, which equals T33-νT11, can be used to quantify the in-plane and out-of-plane constraint effects, respectively. Comparisons show that the constraint dependent J-R curves can reproduce well with all experimental data for clamped SENT specimens. Finally, the present approach is applied to predict the J-R curves of ductile crack extension for other specimens or real engineering structures with varying in-plane and out-of-plane low constraint conditions.

Nonsteady Shock Wave Attenuation Due to Leakage

Leakage flow between the rotor and the stator can cause serious performance degradation of wave rotors which utilize nonsteady shock waves to directly transfer energy from burned gases to precompressed air. To solve this problem, primary flow features relevant to leakage are extracted and it was found that the leakage-attributed performance degradation could be abstracted to a special initial-boundary value problem of one-dimensional Euler equations. Then, a general loss assessment method is proposed to solve the problem of nonsteady flow loss prediction. Using the above method, a reasonable physical hypothesis of the initial-boundary value problem depicting the nonsteady leakage flow process is proposed and further, a closed-form leakage loss analytical model combined with an empirical correction method for the discharge coefficient is established. Finally, with the experimentally verified CFD method, comprehensive numerical verification is conducted for the loss prediction model; it is proved that the physical hypothesis of the proposed model in this paper is reasonable and the model is capable of predicting nonsteady shock wave attenuation due to leakage exactly within the range of parameter variations of wave rotors.

Heat and mass transfer induced by the ignition of single gel propellant droplets

This experimental research studies the gas-phase ignition of single droplets of several gel propellant compositions based on ethyl alcohol with a gellant, liquid and fine solid combustible components. Droplets 2 mm in diameter were located on a holder and heated in a muffle furnace at a temperature ranging from 873 to 1073 K. A software and hardware system of high-speed video recording (4200 frames per second at full resolution) allowed the analysis of consistent patterns in the physical and chemical processes occurring during the induction period. For the compositions under study, we determined the threshold conditions (minimum ambient temperature of 873–943 K) required for the gel propellant ignition as well as the dependences of the ignition delay times versus air temperature. The ignition delay times range from 0.1 to 3.3 s. If the ignition does not start within this period, it will not occur after a longer heating time, since the propellant droplets evaporate completely. For the first time, using the shadow methods, we analyze the characteristics of vapor jetting during the induction period as a result of microexplosions caused by the differences in the boiling points of fuel components. The average vapor jetting speed is about 3 m/s. The size of the zones, in which the vapors slow down to zero, ranges from 6 to 8 mm. We determine the consistent patterns of changes in the diameter of the sphere-shaped gas-vapor envelope around the propellant droplet at the moment of ignition at different ambient temperatures. The higher the temperature, the higher the intensity of physical and chemical processes. This shortens the ignition delay times. At relatively high air temperatures (over 1050 K), the diameter of the flammable gas-vapor envelope around the propellant droplet at the moment of ignition is three times smaller than this value at the near-threshold ignition conditions, when the diameter of the fuel vapor envelope is about 9 mm (more than four typical initial droplet diameters). The results obtained helped us formulate a physical model of the process, which may serve as the basis for the development of a mathematical model simulating the ignition of gel propellant droplets under rapid heating. Such a mathematical model will make it possible to reliably forecast the characteristics of the process in a wide variation range of propellant properties, droplet configurations and parameters of the heating source.

The Influence of Incoherent Nanoparticles on Thermal Stability of Aluminum Alloys

In this paper, the mathematical simulation is used to study the effect from the size of incoherent nanoparticles on thermal strength of heterophase aluminum alloy in materials with the similar volume fraction of the strengthening phase. It is shown that during the deformation process, the particle size affects the evolution of shear dislocations, prismatic dislocation loops and dislocation dipoles. It is found that if the volume fraction of incoherent particles is low, the behavior of the flow stress curves depends on the particle size. The paper identifies the variation range of scale parameters for thermal stability of dispersion-hardened materials.

PHYSIOLOGICAL FUNCTIONAL STATES OF MITOCHONDRIA IN THE THERMODYNAMIC AND ELECTROCHEMICAL CYCLE

PHYSIOLOGICAL FUNCTIONAL STATES OF MITOCHONDRIA IN THE THERMODYNAMIC AND ELECTROCHEMICAL CYCLE

Global sensitivity analysis of the APSIM-Oryza rice growth model under different environmental conditions

This study conducted the global sensitivity analysis of the APSIM-Oryza rice growth model under eight climate conditions and two CO2 levels using the extended Fourier Amplitude Sensitivity Test method. Two output variables (i.e. total aboveground dry matter WAGT and dry weight of storage organs WSO) and twenty parameters were analyzed. The ±30% and ±50% perturbations of base values were used as the ranges of parameter variation, and local fertilization and irrigation managements were considered. Results showed that the influential parameters were the same under different environmental conditions, but their orders were often different. Climate conditions had obvious influence on the sensitivity index of several parameters (e.g. RGRLMX, WGRMX and SPGF). In particular, the sensitivity index of RGRLMX was larger under cold climate than under warm climate. Differences also exist for parameter sensitivity of early and late rice in the same site. The CO2 concentration did not have much influence on the results of sensitivity analysis. The range of parameter variation affected the stability of sensitivity analysis results, but the main conclusions were consistent between the results obtained from the ±30% perturbation and those obtained the ±50% perturbation in this study. Compared with existing studies, our study performed the sensitivity analysis of APSIM-Oryza under more environmental conditions, thereby providing more comprehensive insights into the model and its parameters.

Stress intensity factor and T-stress solutions for three-dimensional clamped single edge notched tension (SENT) specimens

In the present paper, a crack compliance analysis approach and extensive three-dimensional finite element analysis were conducted for clamped SENT specimens, which is one of the most widely used low-constraint specimens for less-conservative fracture toughness testing. A wide range of geometrical parameters variations are considered including in-plane crack depth to plate width ratio (a/W), out-of-plane plate thickness to width ratio (B/W), and daylight to width ratio (H/W). Complete solutions of stress intensity factor (K), in-plane T-stress (T11) and out-of-plane T-stress (T33) are obtained. The results obtained from above two methods are in good agreement. Furthermore, the combination of the effects of crack depths (a/W), plate thickness (B/W), and daylight to width ratio (H/W) on the stress intensity factor, T11 and T33 stress are thus illustrated. To better understand the difference between the derived stress intensity factor solutions and 2D plane strain results, fracture experiments were conducted for clamped SENT specimens with different crack depths. Solutions obtained will be very useful for analyzing fracture toughness test data and determining fatigue crack growth rate for clamped SENT specimens with different crack depths (a/W), plate thickness (B/W), and daylight to width ratio (H/W).

Effects of specularity and particle-particle restitution coefficients on the recirculation characteristics of dispersed gas-particle flows through a sudden expansion

We numerically investigate the effects of restitution and specularity coefficients on the characteristics of dispersed gas-particle flows through a sudden expansion. The studies are carried out using an indigenous finite volume flow solver in a collocated framework with two-fluid model. Parametric studies are performed to gain insights into the differences in recirculation patterns that arise due to variations in restitution and specularity coefficients. The simulations show that particle-particle interactions, quantified by restitution coefficient (e) have a greater impact on recirculation characteristics than particle-wall interactions, which are quantified by specularity coefficient (ϕ). Studies reveal that the recirculation lengths tend to decrease as particle collisions become more elastic (as e tends to unity) while they increase, as the value of ϕ increases. However, the changes in recirculation length are very gradual and less pronounced when only particle-wall interactions are considered as compared to particle-particle interactions. From the range of parametric variations studied in this work, the maximum recirculation length has been found when the value of ϕ is maximum and that of e is minimum.

An improved analytical model for static pull-in voltage of a flexured MEMS switch

This paper presents the design of low-k meander based MEMS shunt capacitive switch with beam perforations. A closed form model to accurately calculate the pull-in voltage of the designed switch for two cases have been presented viz. a non-uniform meander based MEMS shunt switch and an uniform serpentine meander based MEMS shunt switch with perforated structure. The modified Mejis and Fokkema’s capacitance model have been used to propose a generalized closed form expression for the pull-in voltage which takes care of the nonlinear electrostatic force on the switch as well. The proposed model also takes into account the fringing field effect due to beam thickness and etched holes on the beam. The model is validated by calculating the pull-in voltage for both the meander designs under variation of various design parameters. The results obtained under most design specification variation has been found out to be in the range of 1.5–2.3 V for uniform meander based MEMS shunt switch and 3.2–5.2 V for the non-uniform counterpart. The model based results have been further verified by comparison with simulated results of full 3D FEM solver CoventorWare in a wide range of structural parameter variations. It has been observed that the performance of the proposed model is reasonably satisfactory with an average deviation of 4.73% for uniform serpentine flexure and 3.65% for non-uniform flexure based switch.

Reduced order surrogate modeling technique for linear dynamic systems

The availability of reduced order models can greatly decrease the computational costs needed for modeling, identification and design of real-world structural systems. However, since these systems are usually employed with some uncertain parameters, the approximant must provide a good accuracy for a range of stochastic parameters variations. The derivation of such reduced order models are addressed in this paper. The proposed method consists of a polynomial chaos expansion (PCE)-based state-space model together with a PCE-based modal dominancy analysis to reduce the model order. To solve the issue of spatial aliasing during mode tracking step, a new correlation metric is utilized. The performance of the presented method is validated through four illustrative benchmarks: a simple mass-spring system with four Degrees Of Freedom (DOF), a 2-DOF system exhibiting a mode veering phenomenon, a 6-DOF system with large parameter space and a cantilever Timoshenko beam resembling large-scale systems.

ANFIS Based Control Design for AGC of a Hydro-hydro Power System with UPFC and Hydrogen Electrolyzer Units

This paper presents the design of artificial neuro fuzzy inference system (ANFIS) based automatic generation control (AGC) scheme for a two-area hydro-hydro dominating power system. The proposed control scheme is flexible with simple structure and may prove to be a promising tool for considered system in the presence of system non-linearity and for wide range of parametric variations. The ANFIS based control are implemented and the system dynamic responses are obtained considering 1% load disturbance in area-1 and compared with fuzzy and conventional proportional integral (PI) based AGC to show the simplicity and effectiveness of the proposed control. The further improvements in the system dynamic responses with the proposed control are observed by considering the unified power flow control (UPFC) in series with the tie-line and hydrogen aqua electrolyzer units installed at one of the terminal of the control areas. The dynamic performance of the designed control is also evaluated considering the governor dead-band and generation rate constraint (GRC) non-linearity and for wide range of system parametric variations.

Direct Shear Behavior of Fiber Reinforced Concrete Elements

Improving the accuracy of load-deformation behavior, failure mode, and ultimate load capacity for reinforced concrete members subjected to in-plane loadings such as corbels, wall to foundation connections and panels need shear strength behavior to be included. Shear design in reinforced concrete structures depends on crack width, crack slippage and roughness of the surface of cracks.
 This paper illustrates results of an experimental investigation conducted to investigate the direct shear strength of fiber normal strength concrete (NSC) and reactive powder concrete (RPC). The tests were performed along a pre-selected shear plane in concrete members named push-off specimens. The effectiveness of concrete compressive strength, volume fraction of steel fiber, and shear reinforcement ratio on shear transfer capacity were considered in this study. Furthermore, failure modes, shear stress-slip behavior, and shear stress-crack width behavior were also presented in this study.
 Tests’ results showed that volume fraction of steel fiber and compressive strength of concrete in NSC and RPC play a major role in improving the shear strength of concrete. As expectedly, due to dowel action, the shear reinforcement is the predominant factor in resisting the shear stress. The shear failure of NSC and RPC has the sudden mode of failure (brittle failure) with the approximately linear behavior of shear stress-slip relationship till failure. Using RPC instead of NSC with the same amount of steel fibers in constructing the push-off specimen result in high shear strength. In NSC, shear strength influenced by the three major factors; crack surface friction, aggregate interlock and steel fiber content if present. Whereas, RPC has only steel fiber and cracks surface friction influencing the shear strength. Due to cementitious nature of RPC in comparisons with NSC, the RPC specimen shows greater cracks width.
 It is observed that the Mattock model gives very satisfactory predictions when applied to the present test results with a range of parametric variations; ranging from 0 % to 0.5 % in steel fibers content; from 0 % to 0.53 % in transverse reinforcement ratio; from 15 to 105 MPa in compressive strength of concrete. While it gives a poor prediction for a specimen with 1% steel fiber.

Application of function of quality losses G. Taguchi for study of roller burnishing parameters

The results of roller burnishing parameters analysis with selfacting feed are presented in this paper. Method of parameter process design based on the quality losses G. Taguchi function was applied. The following controlled parameters were assumed: Ra - roughness parameter before roller burnishing process, w - interference between a roller and a burnished sample. k - multiplication factor of each sample point deformation, V - burnishing velocity. The following factors were assumed as process disturbances: treated material hardness and lubrication of burnished surface. Basing on experimental results it was found that strongest influence (in tested range of parameters variations) on roller burnished surface roughness has initial surface roughness and burnishing velocity. These factors also showed have the smallest resistance to process disturbances.

Landscape of gene networks for random parameter perturbation.

Landscape approaches have been exploited to study the stochastic dynamics of gene networks. However, how to calculate the landscape with a wide range of parameter variations and how to investigate the influence of the network topology on the global properties of gene networks remain to be elucidated. Here, I developed an approach for the landscape of random parameter perturbation (LRPP) to address this issue. Based on a self-consistent approximation approach, by making perturbations to parameters in a given range, I obtained the landscape for gene network systems. I applied this approach to two biological models, one for the mutual repression model and the other for the embryonic stem (ES) cell differentiation network. For the mutual repression model, my results confirm quantitatively that positive feedback promotes the robustness of multistability. For the ES cell differentiation model, I identify three cell states, representing the ES cell, the differentiation cell, and the intermediate state cell, respectively. I propose that the intermediate states and the wide range of parameter values coming from inhomogeneous cellular environments provide possible explanations for the heterogeneity observed in single cell experiments. I also offer a counterintuitive result that noise could reduce heterogeneity and promote the stability of cell states. These results support that the network topology determines the operating principles of the genetic networks, reflected by the representative landscapes from LRPP. This work provides a new route to obtain the potential landscape for a gene network system given a wide range of parameter values and study the influences of the network topology on the global properties of the system.

Intergranular corrosion testing of 6000 aluminum alloys

The ISO 11846 Method B is one of the most frequently used corrosion tests to investigate the intergranular corrosion susceptibility of Al‐Mg‐Si(‐Cu) alloys and involves the sample immersion in an aqueous solution containing 30 g/L NaCl and 10 ml/L concentrated HCl for 24 h. Unfortunately, the standard allows for a broad range of parameter variation, for instance the temperature of the test solution and the volume‐to‐surface‐ratio of the solution related to the sample surface area, which causes insufficient reproducibility and reliability of this test method. In the present study, the influence of testing parameter variations within the scope of ISO 11846 Method B on the test results of an almost Cu‐free and a Cu‐containing variant of the 6016 aluminum alloy, both tested in the T4 condition and after a bake‐hardening treatment, was studied in detail. The results show that particularly the volume‐to‐surface‐ratio as well as the surface preparation and the solution temperature significantly influence the test results.

Novel analytical model for optimizing the pull-in voltage in a flexured MEMS switch incorporating beam perforation effect

This paper presents a new method for the design, modelling and optimization of a uniform serpentine meander based MEMS shunt capacitive switch with perforation on upper beam. The new approach is proposed to improve the Pull-in Voltage performance in a MEMS switch. First a new analytical model of the Pull-in Voltage is proposed using the modified Mejis-Fokkema capacitance model taking care of the nonlinear electrostatic force, the fringing field effect due to beam thickness and etched holes on the beam simultaneously followed by the validation of same with the simulated results of benchmark full 3D FEM solver CoventorWare in a wide range of structural parameter variations. It shows a good agreement with the simulated results. Secondly, an optimization method is presented to determine the optimum configuration of switch for achieving minimum Pull-in voltage considering the proposed analytical mode as objective function. Some high performance Evolutionary Optimization Algorithms have been utilized to obtain the optimum dimensions with less computational cost and complexity. Upon comparing the applied algorithms between each other, the Dragonfly Algorithm is found to be most suitable in terms of minimum Pull-in voltage and higher convergence speed. Optimized values are validated against the simulated results of CoventorWare which shows a very satisfactory results with a small deviation of 0.223V. In addition to these, the paper proposes, for the first time, a novel algorithmic approach for uniform arrangement of square holes in a given beam area of RF MEMS switch for perforation. The algorithm dynamically accommodates all the square holes within a given beam area such that the maximum space is utilized. This automated arrangement of perforation holes will further improve the computational complexity and design accuracy of the complex design of perforated MEMS switch.

Design a Ship Autopilot using Neural Network

Ship autopilots play an important role in insurance of safe navigation and efficient transportation as else. For their successful design and development, many control techniques were and are being developed. In this paper, the application of artificial neural network (ANN) is investigated to design an autopilot for a surface ship. Feed forward multilayered architecture of ANN is used for approximation of the inverse model of the ship. The designed autopilot acts like an optimal one because of using a cost function for generation of ANN training data. The performance of designed autopilot is evaluated in still water and different wave frequencies. The stability and robustness of the designed system is proved through simulation, carried out in Matlab. The results show that the proposed autopilot can efficiently be used to control the course of a ship in a range of parameter variation. 1. Introduction The main duty of an autopilot is to keep the course of ship in a predefined direction using mostly the rudder. The safety and efficiency of transportation are directly dependent on the performance of ship autopilots. For this, a lot of techniques like proportional-integral-derivative controller, optimal control theory, adaptive control, and nonlinear control are used to improve the autopilot performance. The major feature of these approaches is that they require the exact knowledge of dynamics of controlled objects, which is difficult to obtain in practice due to complexity of ship hydrodynamics. For adaptive and nonlinear control there are some demerits like difficult design and stability analysis. The mentioned above disadvantages can be overcome by using artificial neural network (ANN) because of ANN approximation ability of arbitrary smooth function with required accuracy (Haykin 1999; Terekhov 2002). The first way of application of ANN to ship steering is to use a conventional controller for training the neural network (NN) controller (Endo et al. 1989; Burns & Richter 1996; Unar 1999; Khizer et al. 2013; Pathan et al. 2012a, 2012b; Velagic 2006; Zirilli et al. 2000; Alarcin 2007; Alarcin et al. 2010). Another way to develop NN controller is to integrate NN with other control techniques in sense of adaptive control (Cao et al. 2000; Tzung-hang et al. 2001; Ming-chung & Zi-yi 2013; Li et al. 2004; Jun & Liu 2013; Xu et al. 2014; Xiao et al. 2011; Wang et al. 2013; Yang & Zhao 2006; Leonessa & VanZwieten 2004; Hu & Pan 2012).