Numerical Simulation of Heat Transfer in Primary Surface with Corrugations Recuperators

Study fluid flow and heat transfer characteristics of microchannel in a primary Cross-corrugated(CC) surface recuperators with corrugations and without corrugations, using CFD method. The pitch-over-height ratios P/H of Cross-corrugated (CC) surface is from 1.5 to 4.0, included angles β=75º. The study was performed using CFD software FLUENT to create unit model and simulate fluid temperature, velocity, heat transfer coefficient and other parameters. The results from these simulations were compared to experimental data. It is concluded that, when the Reynolds number is constant, if increase P/H, j/f will decrease, also the decreasing trend will become weak. Under the condition of P/H=2.2, if increase the inlet velocity j/f will decrease; in addition, the heat transfer performance in surface with corrugation will increase 10% compared to that without corrugation. The study results can provide the basis to optimize the design, select the type of heat transfer surface, the scale structure, and heat-transfer surface arrangement for recuperators.

Accuracy of Divergence Measures for Detection of Abrupt Changes

Numerous divergence measures (spectral distance, cepstral distance, difference of the cepstral coefficients, Kullback-Leibler divergence, distance given by the General Likelihood Ratio, distance defined by the Recursive Bayesian Changepoint Detector and the Mahalanobis measure) are compared in this study. The measures are used for detection of abrupt spectral changes in synthetic AR signals via the sliding window algorithm. Two experiments are performed; the first is focused on detection of single boundary while the second concentrates on detection of a couple of boundaries. Accuracy of detection is judged for each method; the measures are compared according to results of both experiments.

Distributional Effects of Tax and Benefit Reforms in the Czech Republic

The Czech Republic has over the past decade carried out two waves of tax and benefit reforms. The first one took place in 2005–2006 during the left-wing government and the second one has been carried out in 2008 by the right-wing government. Using EUSILC data for selected types of households, the paper assesses changes in the distribution of gross incomes and effects of the changes in taxes and benefits on the distribution of incomes after taxes and a provision of social benefits. The analysis is carried out on four types of households with and without children. The analysis is performed using Lorenz curves and Gini coefficients. The results show that the tax system changes the distribution of incomes less significantly than benefits. The 2006 reform reduced the differential between the Gini coefficient for the gross income and the Gini coefficient after taxes and benefits for households with active parents and one child. Reform in 2008 supported families with children and an reduced the differential between the gross income and income after taxes and benefits for different types of families.

Using Mean-Shift Tracking Algorithms for Real-Time Tracking of Moving Images on an Autonomous Vehicle Testbed Platform

This paper describes new computer vision algorithms that have been developed to track moving objects as part of a long-term study into the design of (semi-)autonomous vehicles. We present the results of a study to exploit variable kernels for tracking in video sequences. The basis of our work is the mean shift object-tracking algorithm; for a moving target, it is usual to define a rectangular target window in an initial frame, and then process the data within that window to separate the tracked object from the background by the mean shift segmentation algorithm. Rather than use the standard, Epanechnikov kernel, we have used a kernel weighted by the Chamfer distance transform to improve the accuracy of target representation and localization, minimising the distance between the two distributions in RGB color space using the Bhattacharyya coefficient. Experimental results show the improved tracking capability and versatility of the algorithm in comparison with results using the standard kernel. These algorithms are incorporated as part of a robot test-bed architecture which has been used to demonstrate their effectiveness.

Isobaric Vapor-Liquid Equilibrium of Binary Mixture of Methyl Acetate with Isopropylbenzene at 97.3 kPa

Isobaric vapor-liquid equilibrium measurements are reported for the binary mixture of Methyl acetate and Isopropylbenzene at 97.3 kPa. The measurements have been performed using a vapor recirculating type (modified Othmer's) equilibrium still. The mixture shows positive deviation from ideality and does not form an azeotrope. The activity coefficients have been calculated taking into consideration the vapor phase nonideality. The data satisfy the thermodynamic consistency tests of Herington and Black. The activity coefficients have been satisfactorily correlated by means of the Margules, NRTL, and Black equations. A comparison of the values of activity coefficients obtained by experimental data with the UNIFAC model has been made.

PAPR Reduction Method for OFDM Signalby Using Dummy Sub-carriers

One of the disadvantages of using OFDM is the larger peak to averaged power ratio (PAPR) in its time domain signal. The larger PAPR signal would course the fatal degradation of bit error rate performance (BER) due to the inter-modulation noise in the nonlinear channel. This paper proposes an improved DSI (Dummy Sequence Insertion) method, which can achieve the better PAPR and BER performances. The feature of proposed method is to optimize the phase of each dummy sub-carrier so as to reduce the PAPR performance by changing all predetermined phase coefficients in the time domain signal, which is calculated for data sub-carriers and dummy sub-carriers separately. To achieve the better PAPR performance, this paper also proposes to employ the time-frequency domain swapping algorithm for fine adjustment of phase coefficient of the dummy subcarriers, which can achieve the less complexity of processing and achieves the better PAPR and BER performances than those for the conventional DSI method. This paper presents various computer simulation results to verify the effectiveness of proposed method as comparing with the conventional methods in the non-linear channel.

The Effectiveness of Mineral Fertilization of Winter Wheat by Nitrogen in the Soil and Climatic Conditions in the Cr

The basis of examines is survey of 500 in the years 2002-2010, which was selected according to homogeneity of land cover and where 1090 revenues were evaluated. For achieved yields of winter wheat is obtained multicriterial regression function depending on the major factors influencing the consumption of nitrogen. The coefficient of discrimination of the established model is 0.722. The increase in efficiency of fertilization is involved in supply of organic nutrients, tillage, soil pH, past weather, the humus content in the subsoil and grain content to 0.001 mm. The decrease in efficiency was mainly influenced by the total dose of mineral nitrogen, although it was divided into multiple doses, the proportion loamy particles up to 0.01 mm, rainy, or conversely dry weather during the vegetation. The efficiency of nitrogen was found to be the smallest on undeveloped soils and the highest on chernozem and alluvial soils.

Comparing Autoregressive Moving Average (ARMA) Coefficients Determination using Artificial Neural Networks with Other Techniques

Autoregressive Moving average (ARMA) is a parametric based method of signal representation. It is suitable for problems in which the signal can be modeled by explicit known source functions with a few adjustable parameters. Various methods have been suggested for the coefficients determination among which are Prony, Pade, Autocorrelation, Covariance and most recently, the use of Artificial Neural Network technique. In this paper, the method of using Artificial Neural network (ANN) technique is compared with some known and widely acceptable techniques. The comparisons is entirely based on the value of the coefficients obtained. Result obtained shows that the use of ANN also gives accurate in computing the coefficients of an ARMA system.

Validation on 3D Surface Roughness Algorithm for Measuring Roughness of Psoriasis Lesion

Psoriasis is a widespread skin disease affecting up to 2% population with plaque psoriasis accounting to about 80%. It can be identified as a red lesion and for the higher severity the lesion is usually covered with rough scale. Psoriasis Area Severity Index (PASI) scoring is the gold standard method for measuring psoriasis severity. Scaliness is one of PASI parameter that needs to be quantified in PASI scoring. Surface roughness of lesion can be used as a scaliness feature, since existing scale on lesion surface makes the lesion rougher. The dermatologist usually assesses the severity through their tactile sense, therefore direct contact between doctor and patient is required. The problem is the doctor may not assess the lesion objectively. In this paper, a digital image analysis technique is developed to objectively determine the scaliness of the psoriasis lesion and provide the PASI scaliness score. Psoriasis lesion is modelled by a rough surface. The rough surface is created by superimposing a smooth average (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate average surface followed by a subtraction between rough and average surface to give elevation surface (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 444 lesion models. From roughness validation result, only 6 models can not be accepted (percentage error is greater than 10%). These errors occur due the scanned image quality. Roughness algorithm is validated for roughness measurement on abrasive papers at flat surface. The Pearson-s correlation coefficient of grade value (G) of abrasive paper and Ra is -0.9488, its shows there is a strong relation between G and Ra. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data.

FEA for Transient Responses of an S-Shaped Force Transducer with a Viscoelastic Absorber Using a Nonlinear Complex Spring

To compute dynamic characteristics of nonlinear viscoelastic springs with elastic structures having huge degree-of-freedom, Yamaguchi proposed a new fast numerical method using finite element method [1]-[2]. In this method, restoring forces of the springs are expressed using power series of their elongation. In the expression, nonlinear hysteresis damping is introduced. In this expression, nonlinear complex spring constants are introduced. Finite element for the nonlinear spring having complex coefficients is expressed and is connected to the elastic structures modeled by linear solid finite element. Further, to save computational time, the discrete equations in physical coordinate are transformed into the nonlinear ordinary coupled equations using normal coordinate corresponding to linear natural modes. In this report, the proposed method is applied to simulation for impact responses of a viscoelastic shock absorber with an elastic structure (an S-shaped structure) by colliding with a concentrated mass. The concentrated mass has initial velocities and collides with the shock absorber. Accelerations of the elastic structure and the concentrated mass are measured using Levitation Mass Method proposed by Fujii [3]. The calculated accelerations from the proposed FEM, corresponds to the experimental ones. Moreover, using this method, we also investigate dynamic errors of the S-shaped force transducer due to elastic mode in the S-shaped structure.

Effect of Particle Size in Aviation Turbine Fuel-Al2O3 Nanofluids for Heat Transfer Applications

The effect of Alumina nanoparticle size on thermophysical properties, heat transfer performance and pressure loss characteristics of Aviation Turbine Fuel (ATF)-Al2O3 nanofluids is studied experimentally for the proposed application of regenerative cooling of semi-cryogenic rocket engine thrust chambers. Al2O3 particles with mean diameters of 50 nm or 150 nm are dispersed in ATF. At 500C and 0.3% particle volume concentration, the bigger particles show increases of 17% in thermal conductivity and 55% in viscosity, whereas the smaller particles show corresponding increases of 21% and 22% for thermal conductivity and viscosity respectively. Contrary to these results, experiments to study the heat transfer performance and pressure loss characteristics show that at the same pumping power, the maximum enhancement in heat transfer coefficient at 500C and 0.3% concentration is approximately 47% using bigger particles, whereas it is only 36% using smaller particles.

Texture Feature-Based Language Identification Using Wavelet-Domain BDIP and BVLC Features and FFT Feature

In this paper, we propose a texture feature-based language identification using wavelet-domain BDIP (block difference of inverse probabilities) and BVLC (block variance of local correlation coefficients) features and FFT (fast Fourier transform) feature. In the proposed method, wavelet subbands are first obtained by wavelet transform from a test image and denoised by Donoho-s soft-thresholding. BDIP and BVLC operators are next applied to the wavelet subbands. FFT blocks are also obtained by 2D (twodimensional) FFT from the blocks into which the test image is partitioned. Some significant FFT coefficients in each block are selected and magnitude operator is applied to them. Moments for each subband of BDIP and BVLC and for each magnitude of significant FFT coefficients are then computed and fused into a feature vector. In classification, a stabilized Bayesian classifier, which adopts variance thresholding, searches the training feature vector most similar to the test feature vector. Experimental results show that the proposed method with the three operations yields excellent language identification even with rather low feature dimension.

The Effects of Rain and Overland Flow Powers on Agricultural Soil Erodibility

The purpose of this investigation is to relate the rain power and the overland flow power to soil erodibility to assess the effects of both parameters on soil erosion using variable rainfall intensity on remoulded agricultural soil. Six rainfall intensities were used to simulate the natural rainfall and are as follows: 12.4mm/h, 20.3mm/h, 28.6mm/h, 52mm/h, 73.5mm/h and 103mm/h. The results have shown that the relationship between overland flow power and rain power is best represented by a linear function (R2=0.99). As regards the relationships between soil erodibility factor and rain and overland flow powers, the evolution of both parameters with the erodibility factor follow a polynomial function with high coefficient of determination. From their coefficients of determination (R2=0.95) for rain power and (R2=0.96) for overland flow power, we can conclude that the flow has more power to detach particles than rain. This could be explained by the fact that the presence of particles, already detached by rain and transported by the flow, give the flow more weight and then contribute to the detachment of particles by collision.

Retrospective Synthetic Focusing with Correlation Weighting for Very High Frame Rate Ultrasound

The need of high frame-rate imaging has been triggered by the new applications of ultrasound imaging to transient elastography and real-time 3D ultrasound. Using plane wave excitation (PWE) is one of the methods to achieve very high frame-rate imaging since an image can be formed with a single insonification. However, due to the lack of transmit focusing, the image quality with PWE is lower compared with those using conventional focused transmission. To solve this problem, we propose a filter-retrieved transmit focusing (FRF) technique combined with cross-correlation weighting (FRF+CC weighting) for high frame-rate imaging with PWE. A restrospective focusing filter is designed to simultaneously minimize the predefined sidelobe energy associated with single PWE and the filter energy related to the signal-to-noise-ratio (SNR). This filter attempts to maintain the mainlobe signals and to reduce the sidelobe ones, which gives similar mainlobe signals and different sidelobes between the original PWE and the FRF baseband data. Normalized cross-correlation coefficient at zero lag is calculated to quantify the degree of similarity at each imaging point and used as a weighting matrix to the FRF baseband data to further suppress sidelobes, thus improving the filter-retrieved focusing quality.

CFD Simulation of Condensing Vapor Bubble using VOF Model

In this study, direct numerical simulation for the bubble condensation in the subcooled boiling flow was performed. The main goal was to develop the CFD modeling for the bubble condensation and to evaluate the accuracy of the VOF model with the developed CFD modeling. CFD modeling for the bubble condensation was developed by modeling the source terms in the governing equations of VOF model using UDF. In the modeling, the amount of condensation was determined using the interfacial heat transfer coefficient obtained from the bubble velocity, liquid temperature and bubble diameter every time step. To evaluate the VOF model using the CFD modeling for the bubble condensation, CFD simulation results were compared with SNU experimental results such as bubble volume and shape, interfacial area, bubble diameter and bubble velocity. Simulation results predicted well the behavior of the actual condensing bubble. Therefore, it can be concluded that the VOF model using the CFD modeling for the bubble condensation will be a useful computational fluid dynamics tool for analyzing the behavior of the condensing bubble in a wide range of the subcooled boiling flow.

Analysis of Target Location Estimation in High Performance Radar System

In this paper, an analysis of a target location estimation system using the best linear unbiased estimator (BLUE) for high performance radar systems is presented. In synthetic environments, we are here concerned with three key elements of radar system modeling, which makes radar systems operates accurately in strategic situation in virtual ground. Radar Cross Section (RCS) modeling is used to determine the actual amount of electromagnetic waves that are reflected from a tactical object. Pattern Propagation Factor (PPF) is an attenuation coefficient of the radar equation that contains the reflection from the surface of the earth, the diffraction, the refraction and scattering by the atmospheric environment. Clutter is the unwanted echoes of electronic systems. For the data fusion of output results from radar detection in synthetic environment, BLUE is used and compared with the mean values of each simulation results. Simulation results demonstrate the performance of the radar system.

Screening of Process Variables for the Production of Extracellular Lipase from Palm Oil by Trichoderma Viride using Plackett-Burman Design

Plackett-Burman statistical screening of media constituents and operational conditions for extracellular lipase production from isolate Trichoderma viride has been carried out in submerged fermentation. This statistical design is used in the early stages of experimentation to screen out unimportant factors from a large number of possible factors. This design involves screening of up to 'n-1' variables in just 'n' number of experiments. Regression coefficients and t-values were calculated by subjecting the experimental data to statistical analysis using Minitab version 15. The effects of nine process variables were studied in twelve experimental trials. Maximum lipase activity of 7.83 μmol /ml /min was obtained in the 6th trail. Pareto chart illustrates the order of significance of the variables affecting the lipase production. The present study concludes that the most significant variables affecting lipase production were found to be palm oil, yeast extract, K2HPO4, MgSO4 and CaCl2.

System Reliability by Prediction of Generator Output and Losses in a Competitive Energy Market

In a competitive energy market, system reliability should be maintained at all times. Power system operation being of online in nature, the energy balance requirements must be satisfied to ensure reliable operation the system. To achieve this, information regarding the expected status of the system, the scheduled transactions and the relevant inputs necessary to make either a transaction contract or a transmission contract operational, have to be made available in real time. The real time procedure proposed, facilitates this. This paper proposes a quadratic curve learning procedure, which enables a generator-s contribution to the retailer demand, power loss of transaction in a line at the retail end and its associated losses for an oncoming operating scenario to be predicted. Matlab program was used to test in on a 24-bus IEE Reliability Test System, and the results are found to be acceptable.

Development and Initial Validation of the Social Competency Inventory for Tertiary Level Faculty Members

This study aimed to develop and initially validate an instrument that measures social competency among tertiary level faculty members. A review of extant literature on social competence was done. The review of extant literature led to the writing of the items in the initial instrument which was evaluated by 11 Subject Matter Experts (SMEs). The SMEs were either educators or psychologists. The results of the evaluations done by the SMEs served as bases for the creation of the pre-try-out instrument used in the first trial-run. Insights from the first trial-run participants led to the development of the main try-out instrument used in the final test administration. One Hundred Forty-one participants from five private Higher Education Institutions (HEIs) in the National Capital Region (NCR) and five private HEIs in Central Luzon in the Philippines participated in the final test administration. The reliability of the instrument was evaluated using Cronbach-s Coefficient Alpha formula and had a Cronbach-s Alpha of 0.92. On the other hand, Factor Analysis was used to evaluate the validity of the instrument and six factors were identified. The development of the final instrument was based on the results of the evaluation of the instrument-s reliability and validity. For purposes of recognition, the instrument was named “Social Competency Inventory for Tertiary Level Faculty Members (SCI-TLFM)."

A High Order Theory for Functionally Graded Shell

New theory for functionally graded (FG) shell based on expansion of the equations of elasticity for functionally graded materials (GFMs) into Legendre polynomials series has been developed. Stress and strain tensors, vectors of displacements, traction and body forces have been expanded into Legendre polynomials series in a thickness coordinate. In the same way functions that describe functionally graded relations has been also expanded. Thereby all equations of elasticity including Hook-s law have been transformed to corresponding equations for Fourier coefficients. Then system of differential equations in term of displacements and boundary conditions for Fourier coefficients has been obtained. Cases of the first and second approximations have been considered in more details. For obtained boundary-value problems solution finite element (FE) has been used of Numerical calculations have been done with Comsol Multiphysics and Matlab.