Independent Input Parameters Research Articles

Intelligent parameter optimization of Savonius rotor using Artificial Neural Network and Genetic Algorithm

Power coefficient, the most significant criterion for evaluating the performance of Savonius rotor is a multi-dimensional function of numerous parameters like overlap ratio, number of stages, blade rotation, etc. All these parameters have been examined separately and an approximate span in which optimum performance can be attained is proposed for each one. Furthermore, neither any attempt on scrutinizing this range accurately nor any investigations on probing the probability of existence of any interacting relation among these parameters have been reported so far. Using computational intelligence, an accurate study toward this span and a probable relation among these parameters has been conducted. Power coefficient is considered as a function of six independent input parameters, according to experimental data extracted from a related paper. An Artificial Neural Network has been assigned to investigate a logical interaction among dependent and independent variables and define a cost function based on same empirical data. This function is then optimized by Genetic Algorithm and best amount for each parameter has been determined. Suggested geometry and flow field conditions have then been simulated by Computational Fluid Dynamics and acceptable agreement is detected.

A case study on global sensitivity analysis with dependent inputs: The natural gas transmission model

This paper addresses the identification of the most important input parameters in a natural gas transmission model, in particular regarding their possible effects on pressure and temperature drops. This model has the peculiarity that a significant number of its uncertain input parameters are dependent on each other. Combinations of input parameters considered a priori as valid deliver impossible physical results (i.e.: negative pressures). This advises the application of a sampling method that rejects samples that lead to non-physical results. In a Bayesian framework, selective sample rejection modifies the a priori probability density function (pdf) of independent input parameters producing an a posteriori pdf with dependent inputs. Borgonovo's δ has been the Global Sensitivity Analysis measure selected for performing the sensitivity analysis. The results obtained are completely in line with what physical intuition indicates.

Electro Chemical Machining of Aluminum-Boron Carbide-Nanographite Composites

Non-traditional machining process had made possible the machining of hard to cut materials. Among several non-traditional processes electrochemical machining has been given attention since there occurs no burrs or tool wear. Composites with nano reinforcements had outclassed their counterparts in terms of the properties shown by the nano composites. In the present work aluminium matrix has been reinforced with boron carbide and nano graphite which is added as a solid lubricant to improve tribological properties. The composite is subjected to electrochemical machining with a view of optimizing the process parameters. The process involves introducing abrasive particles while machining which aids in machining. Optimization of process parameters was based on the response surface methodology techniques with four independent input parameters such as voltage, current, electrolytic concentration and feed rate and ECM process performance in terms of material removal rate and overcut.

Probabilistic fire spread forecast as a management tool in an operational setting.

BackgroundAn approach to predict fire growth in an operational setting, with the potential to be used as a decision-support tool for fire management, is described and evaluated. The operational use of fire behaviour models has mostly followed a deterministic approach, however, the uncertainty associated with model predictions needs to be quantified and included in wildfire planning and decision-making process during fire suppression activities. We use FARSITE to simulate the growth of a large wildfire. Probabilistic simulations of fire spread are performed, accounting for the uncertainty of some model inputs and parameters. Deterministic simulations were performed for comparison. We also assess the degree to which fire spread modelling and satellite active fire data can be combined, to forecast fire spread during large wildfires events.ResultsUncertainty was propagated through the FARSITE fire spread modelling system by randomly defining 100 different combinations of the independent input variables and parameters, and running the correspondent fire spread simulations in order to produce fire spread probability maps. Simulations were initialized with the reported ignition location and with satellite active fires. The probabilistic fire spread predictions show great potential to be used as a fire management tool in an operational setting, providing valuable information regarding the spatial–temporal distribution of burn probabilities. The advantage of probabilistic over deterministic simulations is clear when both are compared. Re-initializing simulations with satellite active fires did not improve simulations as expected.ConclusionThis information can be useful to anticipate the growth of wildfires through the landscape with an associated probability of occurrence. The additional information regarding when, where and with what probability the fire might be in the next few hours can ultimately help minimize the negative environmental, social and economic impacts of these fires.Electronic supplementary materialThe online version of this article (doi:10.1186/s40064-016-2842-9) contains supplementary material, which is available to authorized users.

Status and prospects of the two-Higgs-doubletSU(6)/Sp(6)little-Higgs model and the alignment limit

We study in detail the little-Higgs model proposed by Low, Skiba and Smith with an SU(6)/Sp(6) group structure. The effective theory at the TeV scale is a two-Higgs doublet model (2HDM) with additional heavy vector-like fermions and vector-bosons. We identify a set of independent input parameters and develop expressions for masses and couplings in terms of these. We perform a random scan of the parameter space and find points that satisfy constraints, including the recent 8 TeV LHC Higgs measurements, namely, the Higgs mass, Higgs couplings to the top, bottom, $\tau$, $W^\pm$ and $Z$, top-quark mass, and collider bounds on colored vector-like fermions ($t'$ and $b'$), and also precision electroweak constraints. The LHC constraints on the $hWW$ and $hZZ$ couplings are satisfied by being close to the "alignment limit". We find how fine-tuned the model is after including these constraints. For the points that satisfy the constraints, we present the 1-loop effective couplings of the CP-even and CP-odd neutral scalars to two gluons including contributions of standard model and heavy vector-like quarks. We also present the branching ratios of the heavy neutral scalars into the $\gamma\gamma,\, \tau\bar\tau,\, b\bar b,\, t\bar t, WW, ZZ, Zh, hh$ modes, and the heavy charged scalar into $tb,\, \tau\nu, cs, W h$ modes. These will aid searches of the heavy scalars at the LHC and other future colliders.

Support vector regression model for predicting the sorption capacity of lead (II)

Summary Biosorption is supposed to be an economical process for the treatment of wastewater containing heavy metals like lead (II). In this research paper, the support vector regression (SVR) has been used to predict the sorption capacity of lead (II) ions with the independent input parameters being: initial lead ion concentration, pH, temperature and contact time. Tree fern, an agricultural by-product, has been employed as a low cost biosorbent. Comparison between multiple linear regression (MLR) and SVR-based models has been made using statistical parameters. It has been found that the SVR model is more accurate and generalized for prediction of the sorption capacity of lead (II) ions.

Empirical modeling of flexural and splitting tensile strengths of concrete containing fly ash by GEP

In this paper, the flexural strength (ffs) and splitting tensile strength (fsts) of concrete containing different proportions of fly ash have been modeled by using gene expression programming (GEP). Two GEP models called GEP-I and GEP-II are constituted to predict the ffs and fsts values, respectively. In these models, the age of specimen, cement, water, sand, aggregate, superplasticizer and fly ash are used as independent input parameters. GEP-I model is constructed by 292 experimental data and trisected into 170, 86 and 36 data for training, testing and validating sets, respectively. Similarly, GEP-II model is constructed by 278 experimental data and trisected into 142, 70 and 66 data for training, testing and validating sets, respectively. The experimental data used in the validating set of these models are independent from the training and testing sets. The results of the statistical parameters obtained from the models indicate that the proposed empirical models have good prediction and generalization capability.

Dynamic bulk and shear moduli due to grain-scale local fluid flow in fluid-saturated cracked poroelastic rocks: Theoretical model

Grain-scale local fluid flow is an important loss mechanism for attenuating waves in cracked fluid-saturated poroelastic rocks. In this study, a dynamic elastic modulus model is developed to quantify local flow effect on wave attenuation and velocity dispersion in porous isotropic rocks. The Eshelby transform technique, inclusion-based effective medium model (the Mori–Tanaka scheme), fluid dynamics and mass conservation principle are combined to analyze pore-fluid pressure relaxation and its influences on overall elastic properties. The derivation gives fully analytic, frequency-dependent effective bulk and shear moduli of a fluid-saturated porous rock. It is shown that the derived bulk and shear moduli rigorously satisfy the Biot-Gassmann relationship of poroelasticity in the low-frequency limit, while they are consistent with isolated-pore effective medium theory in the high-frequency limit. In particular, a simplified model is proposed to quantify the squirt-flow dispersion for frequencies lower than stiff-pore relaxation frequency. The main advantage of the proposed model over previous models is its ability to predict the dispersion due to squirt flow between pores and cracks with distributed aspect ratio instead of flow in a simply conceptual double-porosity structure. Independent input parameters include pore aspect ratio distribution, fluid bulk modulus and viscosity, and bulk and shear moduli of the solid grain. Physical assumptions made in this model include (1) pores are inter-connected and (2) crack thickness is smaller than the viscous skin depth. This study is restricted to linear elastic, well-consolidated granular rocks.

Effect of cooling methods on hole quality in drilling of aluminium 6061-6T

The influence of cooling method and drilling parameters on hole production has been investigated experimentally and analytically by measuring the hole quality. A three-level, three-parameter experiment was conducted using design-of-experiment methodology. The three levels of independent input parameters were: for cooling method—flood drilling, minimum quantity lubrication (MQL) drilling and cryogenic drilling; for feed rate—0.2, 0.3 and 0.4 mm/rev; and for cutting speed—60, 75 and 100 m/min. The selected work and tool materials were aluminium 6061-6T and high speed steel (HSS), respectively. The measured output parameters were the three most widely used quality characteristics of drilled holes - diameter error, circularity and surface roughness. The results were analysed applying three methods: Pareto ANOVA, Taguchi method and traditional analysis. The findings revealed that the cooling method has a significant effect on diameter error (contribution ratio 88.27%), moderate effect on surface roughness (contribution ratio 41.74%) and relatively small effect on circularity (contribution ratio 23.64%). The best results for the dimensional accuracy and surface roughness were achieved by MQL drilling. Cryogenic drilling produced the best circularity results; however, in terms of dimensional accuracy and surface roughness it was the worst.

Thermal-hydraulic performance optimization of inline and staggered fin-tube compact heat exchangers applying longitudinal vortex generators

Optimization is now recognized as essential in the design of modern compact heat exchanger since the augmentation of heat transfer applying longitudinal vortex generator depends on different interacting parameters, such as its streamwise and spanwise locations, and attack and roll angles and shape. For this work, an optimization procedure based on the SIMPLEX method was conducted through a fluid–solid conjugated heat transfer modeling considering a fin-tube compact heat exchanger with two rows of tubes in staggered and inline arrangements, in order to find an optimum configuration of the vortex generators for two objective functions related to Colburn factor (j) and Friction factor (f). Two Reynolds numbers (250 and 650), performing as a function of fin-pitch, were evaluated. Moreover, a simple approach based on trigonometric decomposition to treat the constraints is presented, which allows great flexibility to vortex generators to cover the design space solution. Seven independent input parameters for each vortex generator in optimization procedure were considered, totaling fourteen independent variables. The results indicate that this work-optimized configuration for the vortex generators achieved higher heat transfer augmentation than those in previous works in the open literature, for both objective functions, Reynolds number and tube arrangements, and it is more pronounced for staggered tube arrangement than for inline tube arrangement. Moreover, suitable vortex generator shapes to maximize the objective functions are more similar to rectangular-winglet type than delta-winglet type, and the optimum ratio between the vortex generator height and fin-pitch is 0.6. Although several trends could be defined for the optimum points, optimized configurations of the vortex generators were found to be different for each Reynolds number, tube arrangement and objective functions, indicating strong asymmetry between the vortex generators to achieve higher heat transfer augmentation.

Investigations on effect of process parameters of electrodeposited Ni-Al2O3 composite coating using orthogonal array approach and mathematical modeling

This research article aims at preparation of nickel-aluminum oxide (Ni-Al2O3) metal matrix composite coatings that were prepared from conventional electro-deposition process. Micron sized alumina particles were deposited in nickel matrix by electro-co-deposition technique. The primary electroplating parameters of current density, pH value of electrolyte, temperature of bath, amount of ceramic particles (Al2O3) in bath, and agitation speed were considered for experimental studies. Experimental design and run orders were framed by orthogonal array of Taguchi's approach. L27 orthogonal array was chosen for experimental design based on five plating parameters and three levels. The experiments were conducted by adjusting the plating parameters and the samples were prepared from electrolytic bath. Volume fraction of Al2O3 and micro-hardness of deposits were recorded for each coated sample systematically. The mean effect studies of electroplating parameters were investigated using Taguchi's approach. The S/N ratio values for the response of micro-hardness were calculated and analyzed for significances of independent input parameters. It was found that current density, pH, temperature and agitation speed were the most significant factors. A second order quadratic equation was developed as prediction model for micro-hardness. The predicted micro-hardness values were found to be in good agreement with the experimental results.

Abrasive Assisted Electrochemical Machining of Al-B<sub>4</sub>C Nanocomposite

Aluminium reinforced with SiC, Al2O3 and B4C etc. possesses an attractive combination of properties such as high wear resistance, high strength to weight ratio and high specific stiffness. Among the various reinforced materials used for aluminium, B4C has outperformed all others in terms of hardening effect. Particle size reduction of B4C is found to have positive impact on the material hardness. In the view of physical properties, B4C has less density than that of SiC and Al2O3, which makes it an attractive reinforcement for aluminium and its alloys for light weight applications. In this work, Al nano B4C composite prepared by ultrasonic cavitation method was machined by Abrasive assisted electrochemical machining using cylindrical copper tool electrodes with SiC abrasive medium. In this paper, attempts have been made to model and optimize process parameters in Abrasive assisted Electro-Chemical Machining of Aluminium-Boron carbide nano composite. Optimization of process parameters is based on the statistical techniques using Response Surface Methodology with four independent input parameters such as voltage, current, abrasive concentration and feed rate were used to assess the process performance in terms of material removal rate and surface finish. The obtained results were compared with abrasive assisted electro chemical machining of Aluminium-Boron carbide micro composite and the effect of particle size on the process parameters was analyzed.

Effects of Insert Geometry and Feed Rate on Quality Characteristics of Turned Parts

This paper investigates experimentally and analytically the influence of insert geometry and feed rate on the quality characteristics of turned parts under the dry cutting condition. A three-level, three-parameter experiment was planned using the design of experiment methodology. The three levels of independent input parameters were: insert shape–rhombus, triangle, and square; nose radius 0.4, 0.8, and 1.2 mm; and feed rate–0.11, 0.22 and 0.33 mm/rev. The measured output parameters were the three most widely used quality characteristics of turned parts–diameter error, circularity and surface finish (arithmetic average). The results were analyzed using three methods: traditional analysis, Pareto analysis of variation and Taguchi method. The results reveal that two of the selected tool geometry parameters, insert shape and nose radius, influence diameter error considerably (total contribution 66.97%) and have minor effects on circularity (total contribution 3.67%) and surface finish (total contribution 11.60%). Feed rate is the major contributor to surface finish (76.42% contribution), whereas circularity is dominated by interaction effects such as insert shape–feed rate interaction (31.44% contribution).

Optimization of winglet-type vortex generator positions and angles in plate-fin compact heat exchanger: Response Surface Methodology and Direct Optimization

Augmentation of heat transfer has been an important research topic for many years. Although many heat transfer enhancement techniques have been proposed over the years, few researches deal with thermal optimization considering vortex generators (VG). This work is related to optimization of VG position and angles in a fin-tube compact heat exchanger using the Genetic Algorithm (GA). Two approaches were evaluated: Response Surface Methodology (RSM) applying Neural Networking method, and Direct Optimization (DO). Numerical analyses based on the finite-volume methodology was performed to analyze heat transfer and pressure drop of a fin-tube heat exchanger with two row of tubes in staggered tube arrangement applying two delta winglet type longitudinal vortex generators with aspect ratio 2. Turbulent flow simulation was performed for Reynolds number 1400 (based on fin pitch). Four vortex generator parameters which impact heat exchanger performance were analyzed: longitudinal vortex generator position in x–y directions, attack angle (θ) and roll angle (φ). The present work is the first to study the influence of VG roll angle on heat transfer enhancement. Therefore, eight independent input parameters were considered, four VG parameters for each tube. Four performance evaluation criteria (PEC) based on Colburn factor (j) and Friction factor (f) were chosen as objective function. The optimized VG configurations led to heat transfer enhancement rates higher than reported in the literature. Direct Optimization reported better results than Response Surface Methodology for all objective functions. Important flow interactions were found between vortices generated by VG1 and VG2, which influenced the results of Colburn factor (j) and Friction factor (f). The best results for each objective functions were achieved when VG1 was not symmetrical to VG2. Regarding global pressure drop, VG1 does not contribute to its mitigation, whereas VG2 is very important to flow separation delay in tube 2. The main contribution of VG1 is to increase the heat transfer rate, whereas VG2 increases the heat transfer rate and decreases the pressure drop. Roll angle has a strong influence on friction factor (f), especially for VG1.

Some emprical equations for predicting standard penetration test blow counts in clayey soils: a case study in Mersin, Turkey

The standard penetration test (SPT) is a widespread test used in situ. Soil mechanical properties such as grain-size content, moisture content, atterberg limits, activity of clay, and consistency of clay determine the SPT blow count. In addition, the SPT blow count reflects the soil mechanical and compressibility parameters. The purpose of this study is to determine the clayey soil states that determine the SPT blow count number; 220 data points derived from a foundation investigation of a sewerage project in Mersin City were used in the study. The Mersin sewerage project includes the sewerage station, central pumping station, and west pumping station in Mersin city, Turkey. The corrected SPT blow counts (N60) and corresponding parameters (fine-grain size percent, liquid limit, plastic limit, plasticity index, moisture content, activity, and consistency) of the clayey soil from these locations were used in a series of simple and nonlinear multiple regression analyses. Based on the analyses, the acceptable results have been determined by a simple regression analyses between the corrected SPT blow counts and the following input parameters: activity, moisture content (in percent), fine-grained percent (in percent). The simple regression analyses for N60-LL (in percent), N60-PL (in percent), and N60-PI (in percent) are considered unacceptable so these parameters are not evaluated as input parameters in the multiple regression analyses. Multiple regression analyses with two independent input parameters produces acceptable results. The optimal equation is determined with multiple regression analyses using activity and moisture content as the input parameters; this equation has a coefficient of determination of R2 = 0.78. The prediction capability of the developed equations is also acceptable. However, the prediction equations proposed in this study are developed with a limited number of data points. For this reason, a cross-check should be performed before using these empirical equations for design purposes.

Near-polytropic stellar simulations with a radiative surface

Studies of solar and stellar convection often employ simple polytropic setups using the diffusion approximation instead of solving the proper radiative transfer equation. This allows one to control separately the polytropic index of the hydrostatic reference solution, the temperature contrast between top and bottom, and the Rayleigh and Peclet numbers. We extend such studies by including radiative transfer in the gray approximation using a Kramers-like opacity with freely adjustable coefficients. We study the properties of such models and compare them with results from the diffusion approximation. We use the Pencil Code, which is a high-order finite difference code where radiation is treated using the method of long characteristics. The source function is given by the Planck function. The opacity is written as kappa=kappa_0 rho^a T^b, where b is varied from -3.5 to +5, and kappa_0 is varied by four orders of magnitude. We consider sets of one dimensional models and perform a comparison with the diffusion approximation. Except for the case where b=5, we find one-dimensional hydrostatic equilibria with a nearly polytropic stratification and a polytropic index close to n=(3-b)/(1+a), covering both convectively stable (n>3/2) and unstable (n<3/2) cases. For b=3 and a=-1, the value of n is undefined a priori and the actual value of $n$ depends then on the depth of the domain. For large values of $\kappa_0$, the thermal adjustment time becomes long, the Peclet and Rayleigh numbers become large, and the temperature contrast increases and is thus no longer an independent input parameter, unless the Stefan Boltzmann constant is considered adjustable. Proper radiative transfer with Kramers-like opacities provides a useful tool for studying stratified layers with a radiative surface in ways that are more physical than what is possible with polytropic models using the diffusion approximation.

Cloud droplet activity changes of soot aerosol upon smog chamber ageing

Abstract. Particles containing soot, or black carbon, are generally considered to contribute to global warming. However, large uncertainties remain in the net climate forcing resulting from anthropogenic emissions of black carbon (BC), to a large extent due to the fact that BC is co-emitted with gases and primary particles, both organic and inorganic, and subject to atmospheric ageing processes. In this study, diesel exhaust particles and particles from a flame soot generator spiked with light aromatic secondary organic aerosol (SOA) precursors were processed by UV radiation in a 6 m3 Teflon chamber in the presence of NOx. The time-dependent changes of the soot nanoparticle properties were characterised using a Cloud Condensation Nuclei Counter, an Aerosol Particle Mass Analyzer and a Soot Particle Aerosol Mass Spectrometer. The results show that freshly emitted soot particles do not activate into cloud droplets at supersaturations ≤2%, i.e. the BC core coated with primary organic aerosol (POA) from the exhaust is limited in hygroscopicity. Before the onset of UV radiation it is unlikely that any substantial SOA formation is taking place. An immediate change in cloud-activation properties occurs at the onset of UV exposure. This change in hygroscopicity is likely attributed to SOA formed from intermediate volatility organic compounds (IVOCs) in the diesel engine exhaust. The change of cloud condensation nuclei (CCN) properties at the onset of UV radiation implies that the lifetime of soot particles in the atmosphere is affected by the access to sunlight, which differs between latitudes. The ageing of soot particles progressively enhances their ability to act as cloud condensation nuclei, due to changes in: (I) organic fraction of the particle, (II) chemical properties of this fraction (e.g. primary or secondary organic aerosol), (III) particle size, and (IV) particle morphology. Applying κ-Köhler theory, using a κSOA value of 0.13 (derived from independent input parameters describing the organic material), showed good agreement with cloud droplet activation measurements for particles with a SOA mass fraction ≥0.12 (slightly aged particles). The activation properties are enhanced with only a slight increase in organic material coating the soot particles (SOA mass fraction &lt; 0.12), however not as much as predicted by Köhler theory. The discrepancy between theory and experiments during the early stages of ageing might be due to solubility limitations, unevenly distributed organic material or hindering particle morphology. The change in properties of soot nanoparticles upon photochemical processing clearly increases their hygroscopicity, which affects their behaviour both in the atmosphere and in the human respiratory system.

Abrasive Assisted Electro Chemical Machining of Aluminum-Boron Carbide-Graphite Hybrid Composite

In this paper, attempts have been made to model and optimize process parameters in Abrasive assisted Electro-Chemical Machining (AECM) of Aluminium-Boron carbide-Graphite composite using cylindrical copper tool electrodes with SiC abrasive medium. Optimization of process parameters is based on the statistical techniques with four independent input parameters such as voltage, current, reinforcement and feed rate were used to assess the AECM process performance in terms of material removal rate. The obtained results are compared with without abrasive assisted electro chemical machining of Aluminium-Boron carbide-Graphite composite. Abrasive assisted ECM process exhibited higher material removal rate from composite material when compared with without abrasive assisted ECM.

Multi Response Optimization of material removal rate and Overcut in EDM using RSM

In this experimental study, attempts have been made to model and optimize EDM process parameters of die steel using different electrode shape namely, cylindrical, rectangular, and hexagonal shape based on Response Surface Methodology (RSM) by using statistical software, Design Expert (DX-6). Four independent input parameters, viz., pulse on time, pulse off time, peak current and tool shape were performed to explore the influence on material removal rate and overcut. The regression equation, and ANOVA was developed using the experimental data and graphs were plotted to investigate the effect of process variables on response characteristics. Multi response optimization was carried out using desirability function in conjunction with RSM to overcome the problem of contradictory responses of single response optimization. From the experimental data of RSM, empirical model were developed and the confirmation experiments were performed, which were found within 95% confidence interval. Optimal setting for multi response characteristics means for both MRR and Overcut are 33.84Amp IP, 10µs Ton, 5.10µs Toff, for the hexagonal shape of electrode.

Effect of Graphite Addition on Surface Roughness during Turning of AA 7075-ZrB2 In-situ Metal Matrix Composites

This project work involves the study of surface roughness during turning of AA 7075-ZrB2 in-situ metal matrix composites. The composites of AA 7075 alloy, AA 7075-3% ZrB2 and AA 7075-3%ZrB2-1% Gr were manufactured using in-situ liquid metallurgy route. This in-situ method involves formation of reinforcements within the matrix by the chemical reaction of two or more chemical compounds that produces some changes in the matrix material within the vicinity. The samples were turned in CNC high speed turning machine with three independent input parameters of cutting speed, feed rate and depth of cut. The TiN coated carbide tipped tool inserts were used to carry out the turning process. The microstructures of the fabricated samples were taken using optical microscope. The mechanical properties in terms of hardness and flexural strength were also examined. The response of the surface roughness was measured after turning of every independent input parameter. It was observed that good surface finish was obtained for AA 7075-3%ZrB2-1% Gr hybrid in-situ composites when compared to other AA 7075-3%ZrB2 and AA 7075 alloy. This was due to self-lubricating properties of Gr which helps to improve the machinability.