Power Density Function Research Articles

Topology optimization of photonics devices: fluctuation-trend analysis concept; random initial conditions with Gaussian and Durden–Vesecky power density bandlimited spectra

We present a topology optimization method for a 1D dielectric metasurface, based on a new concept: fluctuation and trend analysis for initial random conditions. The key point of the proposed optimization method is that the procedure initially generates a couple of device distributions termed fluctuation/mother and trend/father, with specific spectra that efficiently sample not the local minimum of the objective function but basins of optimal solutions in the design space. Studying a 1D dielectric metagrating deflecting a normal polarized incident wave onto a range of angles, we show that a suitable choice of a specific power density spectrum for this initial couple highly increases the probability of reaching a basin of high-performance devices. We guess initial geometries holding the physical properties of the desired final device, allowing accurate targeting of these high-performance device basins in the design space. To include desired physical properties in the initial geometry model, we introduce a formalism allowing generation of a random process with a particular power density or correlation function. By means of a suitable definition of the trend function, we identify an ultimate power density bandlimited spectrum for the fluctuation functions allowing a very high probability and leading to a rapid descent to favorable basins of optimal solutions, consequently reaching high-performance final structure in the design space.

Performance evaluation of a wind farm using different power density distributions

ABSTRACT Several wind resource assessment studies showed that the various power density functions (PDFs) were not always able to reproduce the wind regime available in different regions. Moreover, the impact of the PDFs on the assessment of wind farm performance was not widely investigated. Thereby, in the present study, the generalized extreme value (GEV), Weibull and Normal distributions are considered to investigate whether the expected performances of an actual wind farm are well predicted. This study is applied to Kaberten wind park located at Adrar, in south of Algeria. First, the selected PDFs are applied to analyze wind data collected at the meteorological station of Adrar. Then, the expected annual energy production (AEP), capacity factor and number of operating and non-operating hours of the wind park are computed using the PDFs. Thereafter, these predicted performances are compared to actual data of Kaberten wind park, and errors are assessed for every PDF. The results show that the errors on the mean wind speed are less than 0.5% for the three PDFs, whereas the available wind power density relative error varies from about 2.5% for Weibull to 20.9% for GEV, while it is about 5.9% for Normal distribution. Nevertheless, the AEP errors vary from about 8% for the GEV distribution to more than 24% for the two other distributions. Thus, these results indicate that for the studied case, the three PDFs are comparable for estimating the average wind speed, while the GEV distribution is more suitable for estimating the AEP.

Computation of the Spectrum of dc2-Balanced Codes

We apply the central limit theorem for deriving approximations to the auto-correlation function and power density function (spectrum) of second-order spectral null (dc2-balanced) codes. We show that the auto-correlation function of dc2-balanced codes can be accurately approximated by a cubic function. We show that the difference between the approximated and exact spectrum is less than 0.03 dB for codeword length $n=256$ .

Estimation of Two-Dimensional Non-Symmetric Incoherently Distributed Source with L-Shape Arrays.

In the field of array signal processing, distributed sources can be regarded as an assembly of point sources within a spatial distribution. In this study, a two-dimensional (2D) non-symmetric incoherently distributed (ID) source model is proposed; we explore the estimation of a 2D non-symmetric ID source using L-shape arrays. The 2D non-symmetric ID source is established by modeling the angular power density function (APDF) as a Gaussian mixture model. Estimation of the non-symmetric distributed source is proposed based on the expectation maximization (EM) framework. The proposed EM iterative framework contains three steps in the process of each circle. Firstly, the nominal azimuth and nominal elevation of each Gaussian component are obtained from the phase parts of elements in sample covariance matrices. Then the angular spreads can be solved through a one-dimensional (1D) search by the original generalized Capon estimator. Finally, weights of each Gaussian component are obtained by solving the least-squares estimator. Simulations are conducted to verify the effectiveness of the estimation technique.

Radio Sources in the Nearby Universe

Abstract We identified 15,658 NRAO VLA Sky Survey (NVSS) radio sources among the 55,288 2 Micron All-Sky Survey eXtended (2MASX) galaxies brighter than k 20fe = 12.25 at λ = 2.16 μm and covering the Ω = 7.016 sr of sky defined by J2000 δ > −40° and . The complete sample of 15,043 galaxies with 1.4 GHz flux densities S ≥ 2.45 mJy contains a 99.9% spectroscopically complete subsample of 9517 galaxies with k 20fe ≤ 11.75. We used only radio and infrared data to quantitatively distinguish radio sources powered primarily by recent star formation from those powered by active galactic nuclei. The radio sources with that we used to derive the local spectral luminosity and power-density functions account for >99% of the total 1.4 GHz spectral power densities and in the universe today, and the spectroscopic subsample is large enough that the quoted errors are dominated by cosmic variance. The recent comoving star formation rate density indicated by U SF is .

Generation of stochastic signals for dynamic structural analysis

This paper aims to obtain a method capable of generating a random signal that has a specific Power Density Function and a predefined Power Density Function. Modeling these signals is essential for civil engineering purposes. Indeed, it is indispensable when we consider, for example, the reliability and the ergonomics of bridges and offshore platforms that are subjected to wind.

Estimated Spectra of Higher Order Spectral Null Codes

We present an estimate of the power density function (spectrum) of binary $K$ th-order spectral null codes. We work out the auto-correlation model in detail for second-and third-order spectral null codes. We compare the auto-correlation functions and spectra predicted by the model with those generated by full-set $K$ th-order spectral null block codes.

Compander Design for OFDM PAPR Reduction Using Optimal Perturbation of Piecewise Linear Segments

In this paper, we develop an optimal perturbation approach to design companders to mitigate the peak-to-average power ratio problem experienced by orthogonal frequency division multiplexing (OFDM) signals. Specifically, we generalize single-linear component design approaches, which modify the Rayleigh-distributed OFDM signal amplitude tail, to use of multiple contiguous piecewise linear components. The new compander design approach defines and solves a constrained optimization problem to optimally perturb a given proposed multicomponent piecewise linear segment set to meet the power and probability density function constraints. The use of multiple piecewise linear components provides greater design flexibility to meet the constraints, thus providing solutions for pairs of inflection points and cutoff values where more rigidly designed companders fail to exist. We present examples of compander design, and demonstrate compander performance through numerical simulation. The new compander design approach can generate companders that offer performance improvements over current companders.

Surface processing of amorphous optical materials by argon cluster ion beam

The production of a high-quality surface of fused silica is an important task for advanced optical technologies. In this work, the surface of fused silica has been processed by argon cluster ion beam having mean cluster size Nmean ranged from 180 to 1000 atoms/cluster and energy E ranged from 5 to 23.5 keV. The analysis of surface morphology using atomic force microscopy and the spectral power density (PSD) function shows a noticeable smoothing of roughness in different spatial frequency ranges, depending on the cluster ion parameters. To evaluate the processing efficiency, the dependence of the etching rate of SiO2 on the parameters of cluster ions has been investigated. It is shown that the etching rate vetch is determined by the energy per atom in the cluster E/Nmean and it varies from 0.2 to 20 nm/min with an energy change from 5 to 130 eV/atom.

Two-Dimensional DOA Estimation for Incoherently Distributed Sources with Uniform Rectangular Arrays.

Aiming at the two-dimensional (2D) incoherently distributed (ID) sources, we explore a direction-of-arrival (DOA) estimation algorithm based on uniform rectangular arrays (URA). By means of Taylor series expansion of steering vector, rotational invariance relations with regard to nominal azimuth and nominal elevation between subarrays are deduced under the assumption of small angular spreads and small sensors distance firstly; then received signal vectors can be described by generalized steering matrices and generalized signal vectors; thus, an estimation of signal parameters via rotational invariance techniques (ESPRIT) like algorithm is proposed to estimate nominal elevation and nominal azimuth respectively using covariance matrices of constructed subarrays. Angle matching method is proposed by virtue of Capon principle lastly. The proposed method can estimate multiple 2D ID sources without spectral searching and without information of angular power distribution function of sources. Investigating different SNR, sources with different angular power density functions, sources in boundary region, distance between sensors and number of sources, simulations are conducted to investigate the effectiveness of the proposed method.

A Constrained Optimization Approach to Compander Design for OFDM PAPR Reduction

In this paper, we derive new multi-component companders for reducing peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing signals, using a constrained optimization approach. The new companders provide out-of-band power rejection performance improvements over current state-of-the art companders, while maintaining comparable demodulation performance. The newly designed companders are derived by minimally perturbing the Rayleigh signal amplitude distribution, while enforcing the constant power and probability density function constraints. The use of a multi-component approach to compander construction provides design flexibility, and expands the space of tradeoffs between demodulation performance, PAPR reduction, and out-of-band power rejection. Furthermore, the new companders provide solutions in operating regions where certain current companders fail to exist due to violation of one or more constraints; for example, solutions may be derived for cutoff amplitude values that are unobtainable using other companders. We formulate the constrained optimization problem for compander design and derive the compander and decompander forms. Through numerical simulation, we generate performance results demonstrating the capability of the new companders.

Application of surface frequency functions to assess the state of the kinematic pair elements

In this paper the possibility of using frequency functions of the kinematic pair surface layer elements was analyzed for evaluation of the surface layer condition. The function of spectral power density and autocorrelation which were accepted for analysis was characterized. Evaluation of the elements condition was made on the quantify way as changes in degree of isotropy and in the qualitative way based on the graphs of the analyzed frequency functions. After tribological tests the surface structures were adopted to assess the changes. Spectral graphs for structures without cooperation (directly after-machining) and for the different friction distance, were analyzed. Conditions during tribological tests were taken as permanent. The determined degree of isotropy basis on the frequency functions and received graphs of spectra power density function and autocorrelation become useful in evaluation of the surface layer changes during its transformation.

Development of videogrammetry as a tool for gas-particle fluidization research

Many industries use fluidization of solid particles for energy efficiency or environmental friendly process development, and this paper introduces research techniques developed for investigating gas-particle systems At present there is plenty of room for refining gas-particle fluidization process. With the rapidly rising application of mathematical modelling, real time visualization of processes will be widely used for validation of those models in the near future. In presented research, photogrammetry, as a part of close range vision metrology, has been expanded to allow dynamic space and time analysis of the phase concentration distribution inside fluidization devices. A novel videogrammetry method was created with additional stochastic process analysis for detailed frequency and amplitude characteristics. Videogrammetry was used for the assessment of flow regimes, which were held in various types of fluidization apparatuses. Classic bubbling, jet-spouted and fast circulating fluidization processes were explored under the investigation. Videogrammetry is non-invasive flow regime recognition method, which enables detailed research of gas-particle fluidization phenomena. Until now, there were no comparative studies for three different types of fluidization processes with the use of one complex approach. Developed videogrammetric method consists of the flow structure visualization and dynamic image analysis. The analysed feature is the grey level of the image in time domain, and grey level signals were analysed with the use of autocorrelation function and power density function. The results are presented as images, plots and a flow map. Efficiency of the method was tested by comparison of real observed flow structures to the reconstructed flow structures and the recognition accuracy reached 92%.

Methodological Approach to Testing of the Arms and Military Equipment in the Conditions of Limited Resources

The present conditions of economic crisis essentially limit the opportunities for the military industry, and the country's industrial potential. The resources allocated for production of the military equipment have been cut. The test specimens of the military equipment are provided in single units. There are no agreed-upon methods for testing of the military equipment by single units. In our case the accuracy rating may be expressed as a percentage of the indication or as a percentage of the full-scale value. The accuracy rating is given as the limit, which the errors will not exceed. The theory is based on the facts, the reliability of which was verified more than once. The given conditions are characterized by a limited number of the experimental test specimens, amount of the power-generating fuel, lubricants, oil, energy, accumulated energy, wear and depreciation charges, and so on. All this to a great extent limits the number and volume of tests of every specimen of military equipment. Evaluation of the engineering and fighting efficiency, maintenance and service properties, statistical acceptance quality control are put into practice by every test-specimen. Processing and treatment of the evaluation results demand application of special instruments. Let us choose such an instrument as the method of a small sample. The use of this method makes it possible to obtain evaluations of the power density function. Experimental data are represented by the following distributions: distribution of the fighting efficiency, distribution of maintenance and service properties. Evaluation of the distribution used under these conditions receive a numerical value (quantity) of the fighting efficiency and operating quality of the test-specimen of the military equipment.

Wind speed generation for dynamic analysis

AbstractA simple model to generate large band wind speed time sequences, especially easy to implement with a very reduced number of parameters, is presented. It is based on the calculation of a low‐frequency and a high‐frequency components. Low‐frequency component with 1 h sample time is obtained from a random process based on a conditional probability density function. Using real data from two different wind farms in two different months of the year, it has been found that Weibull distribution centered in the current hourly mean value seems to represent well the 1 h conditional PDF in all cases, and the standard deviation of this conditional Weibull is more or less in the range 1–1.3 m s−1 independently of the season of the year or the location. Regarding to high‐frequency component, low‐frequency samples are used as initial and final values and, between them, the turbulence component values are inserted. For that, it has been used a stochastic process based on a Beta probability function and a simple rescaling procedure with two non‐linear parameters, calculated in a recursive way. Unlike the usual modelling procedures presented in the literature, spectral power density functions are not used. This simplifies the implementation significantly. Ten second sample‐time real speed wind data from two different wind farms have been used to validate the proposed high‐frequency model, obtaining excellent results. A thorough revision of the main models found in the literature to produce wind speed time sequences for dynamic analysis is performed in the paper. Copyright © 2017 John Wiley & Sons, Ltd.

Optimal mechanisms with simple menus

We consider revenue-optimal mechanism design for the case with one buyer and two items, when the buyer’s valuations are independent and additive. We obtain two sets of structural results of the optimal mechanisms, which can be summarized in one conclusion: under certain distributional conditions, the optimal mechanisms have simple menus.The first set of results states that, under a condition that requires that the types are concentrated on lower values, the optimal menu can be sorted in ascending order. Applying the theorem, we derive a revenue-monotonicity theorem which states that stochastically dominated distributions yield less revenue.The second set of results states that, under certain conditions which require that types are distributed more evenly or are concentrated on higher values, the optimal mechanisms have a few menu items. Our first result states that, for certain such distributions, the optimal menu contains at most 4 menu items. The condition admits power density functions. Our second result works for a weaker condition, under which the optimal menu contains at most 6 menu items. Our last result in this set works for the unit-demand setting, it states for uniform distributions, the optimal menu contains at most 5 items.

Intrinsic Noise Monitoring of Complex Systems

The power-density function of the noise spectrum of open and complex systems changes by the power of frequency. We show that the fluctuation origin and the noise-powered description are equivalent to describe the colored noise power density. Based on this, we introduce a scale-independent invariant for monitoring the dynamics of the complex system. The monitoring of the noise spectrum of the system specifies the forecast of failure, the timing of desired regular corrections and/or the assessed operation life of the system, indicating the possible faults before it happens, predicting deterioration like wear/tear, fatigue in the still properly working system. These considerations are highly applicable to living systems and their preventive care.

An Integrated Wind Resource Assessment Tool for Wind Farm Planning: System's Upgrades and Applications

An integrated wind resource assessment tool (WRAT) was previously developed and tested to support wind energy studies during the pre-feasibility stage. This WRAT was applied across a 4-year period to assess the wind potential of the Tuscany region (Italy) according to a 2-km spatial resolution based on 120x107 (12840) gridded points. This application provided the input to a GIS-based interactive web decision support system aimed at wind farm planning in Tuscany. In the present work all significant upgrades implemented to the WRAT are described, as well as their main on-site applications performed within wind energy studies in the recent literature. Main WRAT upgrades include: (i) integration of further wind turbine models into system’s database; (ii) wind power density function; (iii) wind speed vertical extrapolation based on logarithmic law and power law; (iv) annual energy yield uncertainty assessment; (v) wind data import and processing at 10-min time bin; (vi) computation of wind turbulence parameters such as turbulence intensity and gust factor; (vii) turbulence intensity vs. wind speed plot and compliance assessment to the IEC standards. In the end, a number of system’s limitations are also pointed out, as well as further upgrades to be possibly implemented in the near future to overcome some of those limitations.

COMPARISON OF EFFICIENCY OF A SOLAR DRIVEN CARNOT ENGINE UNDER MAXIMUM POWER AND POWER DENSITY CONDITIONS

A comparative analysis on thermodynamic efficiency based on maximum power & power density conditions have been performed for a solar-driven Carnot heat engine with internal irreversibility. In this analysis, the heat transfer from the hot reservoir is to be in the radiation mode and the heat transfer to the cold reservoir is to be in the convection mode. The thermodynamic efficiency function, power & power density functions have been derived and maximization of the power functions have been performed for various design parameters. From the optimum conditions, the thermal efficiencies at maximum power and power densities have been obtained. The effects of internal irreversibility, extreme temperature ratios & specific engine size in area ratio between the hot & cold reservoirs as various design parameters on thermodynamic efficiencies have been investigated for both the conditions. The efficiencies have been compared with Curzon- Ahlborn & Carnot efficiencies respectively. The analysis showed that the efficiency at maximum power output is greater than the efficiency at maximum power density. And the efficiencies can be greater than the Curzon- Ahlborn`s efficiency only for low values of design parameters.

COMPARISON OF EFFICIENCY OF A SOLAR DRIVEN CARNOT ENGINE UNDER MAXIMUM POWER AND POWER DENSITY CONDITIONS

A comparative analysis on thermodynamic efficiency based on maximum power & power density conditions have been performed for a solar-driven Carnot heat engine with internal irreversibility. In this analysis, the heat transfer from the hot reservoir is to be in the radiation mode and the heat transfer to the cold reservoir is to be in the convection mode. The thermodynamic efficiency function, power & power density functions have been derived and maximization of the power functions have been performed for various design parameters. From the optimum conditions, the thermal efficiencies at maximum power and power densities have been obtained. The effects of internal irreversibility, extreme temperature ratios & specific engine size in area ratio between the hot & cold reservoirs as various design parameters on thermodynamic efficiencies have been investigated for both the conditions. The efficiencies have been compared with Curzon- Ahlborn & Carnot efficiencies respectively. The analysis showed that the efficiency at maximum power output is greater than the efficiency at maximum power density. And the efficiencies can be greater than the Curzon- Ahlborn`s efficiency only for low values of design parameters.