Frequency Analysis Approach Research Articles

Key Aroma Compounds of Dark Chocolates Differing in Organoleptic Properties: A GC-O Comparative Study.

Dark chocolate samples were previously classified into four sensory categories. The classification was modelled based on volatile compounds analyzed by direct introduction mass spectrometry of the chocolates’ headspace. The purpose of the study was to identify the most discriminant odor-active compounds that should characterize the four sensory categories. To address the problem, a gas chromatography-olfactometry (GC-O) study was conducted by 12 assessors using a comparative detection frequency analysis (cDFA) approach on 12 exemplary samples. A nasal impact frequency (NIF) difference threshold combined with a statistical approach (Khi² test on k proportions) revealed 38 discriminative key odorants able to differentiate the samples and to characterize the sensory categories. A heatmap emphasized the 19 most discriminant key odorants, among which heterocyclic molecules (furanones, pyranones, lactones, one pyrrole, and one pyrazine) played a prominent role with secondary alcohols, acids, and esters. The initial sensory classes were retrieved using the discriminant key volatiles in a correspondence analysis (CA) and a hierarchical cluster analysis (HCA). Among the 38 discriminant key odorants, although previously identified in cocoa products, 21 were formally described for the first time as key aroma compounds of dark chocolate. Moreover, 13 key odorants were described for the first time in a cocoa product.

A new method to restore the impact of land‐use change on flood frequency based on the Hydrologic Engineering Center‐Hydrologic Modelling System model

AbstractTo reveal the impacts of land‐use change on flood frequency distribution, a method to contradiction restore the largest‐gauged annual flood series to current land‐use conditions was proposed, based on the Hydrologic Engineering Center‐Hydrologic Modelling System (HEC‐HMS), with a newly developed iterative asymptotic method to calibrate the model parameters. Using the Xixi Basin on the southeastern coast of China as a case‐study, the HEC‐HMS model was applied to forward restore the largest annual floods between 1956 and 2011 by using the land‐use conditions of 2010. The flood peak flow series derived from forward restoration were used for flood frequency analysis. The results showed that (a) the iterative asymptotic method could calibrate the initial loss ratio and wave velocity relatively well. The physical meaning of the parameter values obtained was clear. The overall model simulation result was satisfactory, with Nash–Sutcliffe efficiency coefficients of 0.827 and 0.843 in the calibration and verification periods, respectively. (b) The calibration method effectively addressed the difficulty in determining the model parameters needed for resolving the restoration of the impacts of land‐use changes on the largest‐gauged annual flood peak flows and provided a newer HEC‐HMS‐based restoration approach for nonstationary flood frequency analysis. (c) Urbanization in the Xixi Basin caused a degradation in forested and arable lands, as well as in grasslands. Its main impact on the flood frequency distribution was that the average flood peak flow increased from 2,633.32 to 2,889.48 m3s−1and the changes in the coefficient of variation and coefficient of skewness were very small.

Biphasic exocytosis of herpesvirus from hippocampal neurons and mechanistic implication to membrane fusion

Exocytosis is a crucial cellular process involved in the release of neural transmitters or signaling hormones, and disposal of waste or toxic materials. The relationship between structural transition and temporal progression of this process is poorly understood, partly due to lack of adequate tools to resolve such dynamic structures at sufficient resolution in 3D. Exocytosis can be hijacked by some viruses, exemplified by the widely used model α-herpesvirus pseudorabies virus (PRV), which relies on exocytosis for trans-synaptic spread across neurons. Here, we have used cryo electron tomography (cryoET) to capture 199 events of PRV exocytosis from cultured hippocampal neurons. We established cumulative frequency analysis to estimate the relative duration of an exocytosis stage based on the frequency of observed viral particles at that stage. This analysis revealed that PRV exocytosis is biphasic, including a fast, “release phase” driven by fusion proteins and fused membranes, and a slow, “recovery phase” driven by flattening of curved membranes. The biphasic property of exocytosis discovered here appears to be conserved for membrane fusion during viral entry, and our approach of cumulative frequency analysis should have general utility for characterizing other membrane fusion events.

Updating urban design floods for changes in central tendency and variability using regression

Ordinary least squares (OLS) regression offers a decision-oriented approach for modeling trends in annual peak flows. We introduce a two-stage OLS approach for nonstationary flood frequency analysis that (i) models changes in their central tendency (median) in response to environmental perturbations with one regression and then (ii) examines changes in the coefficient of variation (Cv) by running a second regression on Anscombe-transformed residuals from the first regression. Monte Carlo simulations show that this approach yields 100-year flood estimates with mean squared errors comparable to estimates made with an advanced generalized linear model-based method. Also, this second-stage regression often produces approximately normal residuals, which permits statistical inferences on Cv trends. Case studies illustrate the dramatic impact that decreasing and increasing Cv trends can have on 100-year floods. Findings motivate the incorporation of trends in variability in infrastructure design along with further research examining asymmetric changes in urban flood variability.

Stator fault diagnosis of a BLDC motor based on discrete wavelet analysis using ADAMS simulation

In this paper, a method is considered to observe the stator inter-turn fault (SITF) in brushless DC motors (BLDCM). This is a crucial subject to deal with, since the fault may cause expensive replacement of parts in case of late diagnosis. The approach used here is the discrete wavelet transform, which is one of the many kinds of time–frequency analysis approaches. Taking advantage of a model closely related to a real BLDCM, the stator current is simulated and the aforesaid signal-based method is applied to it. The feature used as a parameter to determine whether SITF has occurred or not is the average change or deviation in the energy amount of four signals named high frequency (detail) signals. In other words, first, the difference percentage of the energy parameters between those four signals in healthy and faulty operation mode would be measured. Then, the average percentage of the energy variation amounts are to be compared with a threshold to determine the fault occurrence. Having a precise Simulink/Matlab plus ADAMS model of the motor, the designed algorithm will be validated.

Maximum entropy method for flood frequency analysis: A case study of the Grand River in Ontario, Canada

Flood frequency analysis provides the fundamental information for the design of hydraulic and civil infrastructure facilities as well as water resources management. The available procedures to determine flood distributions and their parameters from historical data suffer from restriction on the family of presumed standard classical distributions, such as gamma distribution and extreme value distributions. This paper presents a distribution-free approach for flood frequency analysis by using the combination of maximum entropy method and Akaike’s information criterion. The determination procedure is given in a flowchart. It is distribution-free because no classical distributions were presumed in advance and the inference result gives a universal form of probability curves. Comparative studies from historical flood data show that the proposed method can, accurately and reasonably, characterize the probabilistic information of observed or transformed flood data.

An effective approach for stochastic natural frequency analysis of circular beams with radially varying material inhomogeneities

The natural frequency of functionally graded material beams is closely related to the spatially varying material model. Specially when the model is stochastic due to the variability of observational data. In this regard, this paper presents an effective approach for stochastic natural frequency analysis of circular composite beams with radially varied material properties. The higher-order shear deformation based spectral element model is first setup for structural natural frequency analysis. The random field theory is introduced to represent the radially varied stochastic material properties. To improve numerical efficiency of the brute-force simulation method, a multivariate Gegenbauer polynomial based sparse regression model is proposed to mimic the structural uncertain natural frequency function. Several numerical examples are presented to examine the performance of this proposed approach. Results have illustrated the high efficiency and numerical accuracy of utilizing the sparse regression method for uncertain natural frequency analysis of composite beams with radially varied stochastic material properties.

Weighted contribution rate of nonlinear output frequency response functions and its application to rotor system fault diagnosis

Rotor cracking is a common fault in rotating machinery, that can often be detected based on the vibrations of such machinery. Therefore, many vibration signal based techniques have been developed for rotor fault detection. However, signal based fault diagnosis is often affected by noise and cannot be used to fully quantify the operating conditions of rotors, which are often more relevant to rotor structural characteristics compared to vibration behaviours. Nonlinear output frequency response functions (NOFRFs) represent a nonlinear system frequency analysis approach that was proposed to address challenges associated with applying signal based fault detection. NOFRFs have a wide range of applications in industry, including rotor fault diagnosis. In this study, a novel NOFRFs based criterion called the weighted contribution rate of NOFRFs is proposed to enhance the capability of the NOFRFs based rotor crack detection and quantification. The proposed criterion can amplify the impact of rotor characteristics that are sensitive to rotor cracks, which considerably improves the crack diagnosis performance. The effectiveness and advantages of the proposed rotor damage detection method are verified both experimentally and through simulations, demonstrating its potential applications in the early stages of rotor crack diagnosis.

Estimates of gridded relative changes in 24-h extreme rainfall intensities based on pooled frequency analysis

The potential effect of climate change needs to be considered in urban infrastructure design and risk assessment to improve reliability. The present study proposes a methodology for obtaining grid-scale relative changes for updating 24-h extreme rainfall intensity, through the estimation of rainfall intensity quantiles from baseline and future simulations using a pooled frequency analysis approach. Coherence of relative changes over return periods and time horizons is analysed, and adjustments are proposed to facilitate the application of relative changes in practice. The approach is applied to Canada, using gridded daily precipitation series from model combinations belonging to the North American Coordinated Regional Climate Downscaling Experiment. Multi-model 10th, 50th and 90th percentile relative changes are provided for six return periods, considering two future scenarios (RCP 4.5 and RCP 8.5), and two horizons (2050 and 2080). Overall, estimated relative changes varied smoothly and formed a number of clusters of similar values across the country. Relative changes for RCP 8.5 are recommended for 2050, whereas either those for RCP 4.5 or RCP 8.5 could be used for 2080. As an example, median multi-model 50th percentile relative change over Canada is found to be 14%, 16% and 27% for RCP 4.5 – 2080, RCP 8.5 – 2050, and RCP 8.5 – 2080, respectively.

Research on Index System of Industrial Design and Development in Manufacturing Enterprises

In recent years, the central leaders and relevant ministries and commissions have issued guidelines for the development of China’s industrial design, and the development of industrial design in manufacturing enterprises has attracted more attention. At present, the development level of industrial design in various regions and industries in China is uneven. No institution or organization can accurately provide nationwide survey data, and the existing regional or industry-related survey data lack uniformity and continuity, which cannot provide sufficient reference for the country to formulate relevant policies. This paper mainly describes the building of index system of industrial design and development in manufacturing enterprise. The paper builds the framework based on literature at home and abroad, two rounds of questionnaire, expert interview and field research, selects indexes through Delphi method, analytic method and frequency analysis approach and then revises index system according to the expert evaluation of regional pilot. It attempts to connect with national statistical framework, so as to grasp the problems and trends of the development of industrial design. The establishment of index system of industrial design and development in manufacturing enterprise plays an important role in the future development of China’s industrial design and the formulation of economic transformation policies.

Nonstationary warm spell frequency analysis integrating climate variability and change with application to the Middle East

The Middle East can experience extended wintertime spells of exceptionally hot weather, which can result in prolonged droughts and have major impacts on the already scarce water resources of the region. Recent observational studies point at increasing trends in mean and extreme temperatures in the Middle East, while climate projections seem to indicate that, in a warming weather scenario, the frequency, intensity and duration of warm spells will increase. The nonstationary warm spell frequency analysis approach proposed herein allows considering both climate variability through global climatic oscillations and climate change signals. In this study, statistical distributions with parameters conditional on covariates representing time, to account for temporal trend, and climate indices are used to predict the frequency, duration and intensity of wintertime warm spells in the Middle East. Such models could find a large applicability in various fields of climate research, and in particular in the seasonal prediction of warm spell severity. Based on previous studies linking atmospheric circulation patterns in the Atlantic to extreme temperatures in the Middle East, we use as covariates two classic modes of ‘fast’ and ‘slow’ climatic variability in the Atlantic Ocean (i.e., the Northern Atlantic Oscillation and the Atlantic Multidecadal Oscillation respectively). Results indicate that the use of covariates improves the goodness-of-fit of models for all warm spell characteristics.

On the choice of the optimal frequency analysis of annual extreme rainfall by multifractal approach

Intensity Duration Frequency (IDF) curves are important tools for hydraulic and hydrologic design. Considering that there are different approaches to obtain the rainfall quantiles on which the IDF curves are based, the availability of a method to evaluate their reliability is of great importance. With this aim, in this work the multifractal properties of hourly rainfall data recorded at 23 rain gauges in the Umbria Region (Italy) have been used to select the most appropriate frequency analysis method of extreme annual rainfall at each location. Three methods have been tested: Local Frequency Analysis (by fitting at each station extreme annual rainfall data of different durations by a probability distribution function), Regional Frequency Analysis approach based on L-Moments and flood index method (considering the extreme annual rainfall data from all the stations), and a variant of the latter method known as In-site Regional Frequency Analysis (based on the consideration of the station as a region). Therefore, quantiles of rainfall for different durations and return periods have been obtained. These quantiles have been fitted to the Montana Intensity-Duration-Frequency (IDF) curve. The scaling properties of rainfall have been obtained through out the empirical moments scaling function K(q). Their comparison with some scaling behavior properties of the IDF curves has let the selection of the most adequate quantile estimation method at each site, being the Regional Frequency Analysis the most appropriate one for 14 out of the 23 sites included in the study.

Using hybrid weighting‐clustering approach for regional frequency analysis of maximum 24‐hr rainfall based on climatic, geographical, and statistical attributes

Estimation of extreme rainfall amounts has great importance, especially in some fields such as the design of water structures, water resources engineering, extreme flood management, and soil erosion conservation. One of the problems, which hydrologists faced, is an acceptable estimation of extreme events in areas with insufficient data. In this case, separation of the study area into homogenous regions and performing regional frequency analysis (RFA) result in greater precision and fewer errors in frequency analysis models, enabling estimation of quantiles for each return period in the region of interest. In this study, the maximum 24‐hr rainfall data related to Lake Urmia Basin (LUB) for 63 selected stations during the period of 1979–2008 are used. Moreover, determining an appropriate weight for each group of attributes is attempted according to the degree of importance and contribution share of each climatic, geographical, and statistical attribute. Then, for regionalization using a clustering approach, the attributes are defined in seven different groups. Subsequently, the performance of different groups associated with weighted attributes of maximum 24‐hr rainfall is evaluated for RFA in the study area. The results showed that the combination of climatic, geographical, and statistical attributes present better results and more reliable estimates of extreme values. The results indicated better performance of weighted models to the attributes compared to non‐weighted frequency analysis models in the estimation of maximum 24‐hr rainfall. The results also showed that by evaluating three to four groups and applying average weights of 0.3–0.85 for the attributes through the use of hybrid weighting‐clustering approach, more accurate estimates of extreme values for different return periods can be obtained.

Copula-based trivariate drought frequency analysis approach in seven climatic sub-regions of mainland China over 1961–2013

In drought analysis, many types of research have applied bivariate analysis. However, a more effective appraisal is achievable by employing three mutually correlated drought variables (i.e., duration, severity, peak) concurrently. This study adopted trivariate copulas for multivariate drought frequency estimation in seven climatic sub-regions and mainland China between 1961 and 2013. The joint distribution is modeled using nine trivariate copula functions, namely Clayton, Ali–Mikhail–Haq (AMH), Gumbel–Hougaard, Frank, M3, M4, M5, M6, and M12. The performance of the different copulas was evaluated using the root mean square error (RMSE), Akaike information criterion (AIC), bias, and graphical test. The results showed that trivariate Clayton copula performed better in modeling joint dependence structure of drought variables in contrast to other class of copulas in sub-regions I–VII and mainland China. Therefore, the Clayton copula–based drought joint distributions were used for the multivariate drought frequency analysis, regarding probabilities and return periods. The joint probabilities in the “OR” cases were greater than that of the “AND” cases in all the seven sub-regions and mainland China. There is every possibility that drought event occurrence will be given for “OR” cases. Accordingly, counter measures of drought hazards need to be set for proactive responses especially in sub-regions III, V, and VI. The trivariate return periods were compared with the univariate and bivariate return periods and discussed the need of multivariate drought frequency analysis. In conclusion, the Clayton trivariate copula is an excellent choice for efficient drought risk evaluation, and results are very handy in the design of water resource hydrologic systems under severe and extreme drought conditions.

Haar wavelet discretization approach for frequency analysis of the functionally graded generally doubly-curved shells of revolution

• Free vibration of the FG generally doubly-curved shells of revolution is studied. • A numerical approach based on the Haar wavelet discretization method is presented. • Boundary conditions are imitated by adding artificial springs to constraints. • Proposed method show high accuracy, high reliability and rapid convergence rate. This paper aims to investigate the free vibrational analysis of the generally doubly-curved shells of revolution made of functionally graded (FG) materials and constrained with different boundary conditions by means of an efficient, convenient and explicit method based on the Haar wavelet discretization approach. The FG materials of the shell consist of a combination of ceramic and metal, which four parameter power-law distribution functions have chosen for modeling of the smoothly and gradually variation of the material properties in the thickness direction. The theoretical model of the shell is formulated by employing of the first-order shear deformation theory. The rotation and displacement components of each point of the shell are expanded in the form of product of the Haar wavelet series in meridional direction as well as trigonometric series in the circumferential direction. By adding the boundary condition equations to the main system of equations, the constants appeared from the integrating of the Haar wavelet series are satisfied. In addition, with solving the characteristic equation, the vibrational results including the natural frequencies and the corresponding mode shapes are achieved. Then, the present results have been compared with those available in the literature. The results indicate that this method has high accuracy, high reliability and also a higher convergence rate in attaining the frequencies of the FG doubly-curved shells of revolution. Also, the effects of the main parameters such as power-law exponent, geometrical parameters, material distribution profiles and different types of boundary conditions, on the vibrational behavior of the FG doubly-curved shells of revolution, are investigated. Finally, taking into account the effects of geometrical parameters and material distribution profiles, for FG doubly-curved shells of revolution with different boundary conditions such as classic, elastic restraints and their combination, a variety of new frequency studies are provided which can be considered as proof results for further researches in this field.

Spectroscopic Optical Coherence Tomography by Using Multiple Multipole Expansion

This paper presents a pre-processing method to remove multiple scattering artifacts in spectroscopic optical coherence tomography (SOCT) using time–frequency analysis approaches. The method uses a multiple multipole expansion approach to model the light fields in SOCT. It is shown that the multiple scattered fields can be characterized by higher order terms of the multiple multipole expansion. Hence, the multiple scattering artifact can thus be eliminated by applying the time–frequency transform on the SOCT measurements characterized by the lower order terms. Simulation and experimental results are presented to show the effectiveness of the proposed pre-processing method.

Natural frequency analysis of functionally graded material beams with axially varying stochastic properties

• Functionally graded material properties of beams are modelled as random fields. • A generalized eigenvalue equation is derived for stochastic free vibration analysis. • Effective surrogate models are developed based on the polynomial chaos expansion. • Several examples are presented to demonstrate the engineering applications. The functionally graded material (FGM) has a potential to replace ordinary ones in engineering reality due to its superior thermal and dynamical characteristics. In this regard, the paper presents an effective approach for uncertain natural frequency analysis of composite beams with axially varying material properties. Rather than simply assuming the material model as a deterministic function, we further extend the FGM property as a random field, which is able to account for spatial variability in laboratory observations and in-field data. Due to the axially varying input uncertainty, natural frequencies of the stochastically FGM (S-FGM) beam become random variables . To this end, the Karhunen–Loève expansion is first introduced to represent the composite material random field as the summation of a finite number of random variables. Then, a generalized eigenvalue function is derived for stochastic natural frequency analysis of the composite beam. Once the mechanistic model is available, the brutal Monte-Carlo simulation (MCS) similar to the design of experiment can be used to estimate statistical characteristics of the uncertain natural frequency response. To alleviate the computational cost of the MCS method, a generalized polynomial chaos expansion model developed based on a rather small number of training samples is used to mimic the true natural frequency function. Case studies have demonstrated the effectiveness of the proposed approach for uncertain natural frequency analysis of functionally graded material beams with axially varying stochastic properties .

A regional frequency analysis of UK sub‐daily extreme precipitation and assessment of their seasonality

Floods related to extreme precipitation events, especially intense, short‐duration precipitation, may cause significant damage in urbanized areas, including transport infrastructure, electricity networks, and property. These events are expected to increase in frequency with climate change but their characteristics, at either hourly or multi‐hourly timescales, have been little studied due to short and poor quality data records. We examine annual maximum (AMAX) hourly and multi‐hourly (3, 6, 12, and 24 hr) precipitation accumulations in the United Kingdom using a quality‐controlled hourly precipitation data set for the period 1992–2014. We describe their seasonality and diurnal cycle and use a regional frequency analysis (RFA) approach with L‐moments to produce at‐site return level estimates, and then use existing extreme precipitation regions to provide regional‐scale return levels. The analysis shows a clear seasonality and the dominant occurrence of short‐duration AMAX in summer with similar seasonality for 1 and 3 hr accumulation periods in some regions, while longer‐duration AMAX (12 and 24 hr) behave similarly to each other in all regions but are distributed over a longer period including late autumn and winter. The diurnal cycle of 1 hr AMAX indicates that most extremes occur during the afternoon, with a peak typically between 1400 and 1700, especially in southern and eastern regions. However, we also demonstrate that existing regions for UK daily extremes are not able to adequately reflect differences at shorter durations and that new regions should be created. These results provide new insights to help in designing urban drainage systems and infrastructure, including the need for new scaling relationships between sub‐daily and design accumulation periods.

A closed-form approach for the resonant frequency analysis of clamped rectangular microplates under distributed electrostatic force

This paper proposes a fast-converged reduced-order model for small vibrations of electrostatically actuated rectangular microplates around their deformed states. On this foundation, one-mode analysis method and thus closed-form analytical expressions are developed for the fundamental resonant frequency analysis. Numerical multi-mode analysis is conducted to investigate the convergence. It is concluded that the one-mode analysis method can give a converged solution, which demonstrates that the proposed model has a faster convergence than previous models where multi modes are needed. The directly calculated resonant frequencies by the closed-form expressions are in good agreement with the numerical results by FEM simulations with less than 5% variation before pull-in. Parametric study shows the closed-form expressions are applicable to the cases in which the thickness is less than 1/20 of the length and width under a nominal length to width ratio of 1∼2.5, and the gap distance is less than or equal to the thickness of the microplate. Additionally, a kind of electrostatic configurations based on multilayer microplates, capacitive micromachined ultrasonic transducers (CMUTs), were used to experimentally validate the closed-form expressions and good agreement was observed.

Assessing the performance of regional flood frequency analysis methods in South Africa

In engineering and flood hydrology, the estimation of a design flood associates the magnitude of a flood with a level of exceedance, or return period, for a given site. The use of a regional flood frequency analysis (RFFA) approach improves the accuracy and reliability of estimates of design floods. However, no RFFA method is currently widely used in South Africa, despite a number of RFFA studies having been undertaken in Africa and which include South Africa in their study areas. Hence, the performance of the current RFFA approaches needs to be assessed in order to determine the best approaches to use and to determine if a new RFFA approach needs to be developed for use in South Africa. Through a review of the relevant literature it was found that the Meigh et al. (1997) method, the Mkhandi et al. (2000) method, the Görgens (2007) Joint Peak-Volume (JPV) method and the Haile (2011) method are available for application in a nationwide study. The results of the study show that the Haile method generally performs better than the other RFFA methods; however, it also consistently underestimates design floods. Due to the poor overall performance of the RFFA methods assessed, it is recommended that a new RFFA method be developed for application in design flood practice in South Africa.