Search Results (28)

Welding and cutting behaviour may affect the mechanical properties of titanium alloy welded structures, which may have some impact on the safety assessment of the structure. This study analyses changes in residual stress in Ti80 butt-welded thick plates before and after wire-cut electric discharge machining, using numerical simulations based on thermo-elastoplastic theory and the element birth and death method, validated by X-ray non-destructive testing. The transverse residual tensile stress near the weld exhibits an asymmetric bimodal distribution, while the longitudinal stress is significantly higher than the transverse stress. Wire-cut electric discharge machining had minimal influence on the transverse residual stress distribution but led to partial relief of the longitudinal residual tensile stress. The maximum reductions in transverse and longitudinal welding residual tensile stresses are approximately 60% and 36%, respectively. The findings indicate that wire-cut electric discharge machining can alter surface residual stresses in Ti alloy butt-welded thick plates. This study also establishes a numerical simulation methodology for analysing welding residual stresses and their evolution due to wire-cut electric discharge machining. The results provide a theoretical basis for analysing the structural strength and safety of Ti-alloy-based deep-sea submersibles. Full article

This paper introduces a flexible distribution called the asymmetric double normal distribution, specifically designed to model univariate data exhibiting asymmetry and either unimodal or bimodal characteristics. This distribution is highly flexible, capable of capturing a wide range of data behaviors, from smooth densities to those with thinner tails. It generalizes the skew-normal distribution as a special case and provides a simpler alternative to mixture models by avoiding issues related to parameter identifiability. This study explores the structural and theoretical properties of the asymmetric double normal distribution, and parameter estimation is carried out using the maximum likelihood method. Simulation experiments assess the performance of the estimators, while applications in regression and real-life data fitting illustrate the practical relevance of this model. This proposed distribution proves to be a powerful tool for modeling asymmetric and bimodal data, offering significant advantages for statistical analysis in diverse applications. Full article

To improve the guidance for the wind tunnel test, this study initially conducted thorough research on the wind environment at a coastal bridge site to ascertain the characteristics of the wind parameters varying along the bridge span. Subsequently, the measured results were utilized to steer wind tunnel test research, focusing on analyzing the influence of the spoiler and maintenance track on the second-order heaving vortex-induced vibration of the flat steel box girder. This investigation uncovered two distinct distributions in the angle of attack along the span: bimodal distribution and asymmetric unimodal distribution. The angle of attack of the incoming flow was primarily concentrated within ±5°. Both the two-side and the windward spoiler were found to exert similar effects on the second-order heaving vortex-induced vibration, primarily impacting the second lock-in region. Furthermore, the outer maintenance track could effectively suppress the vortex-induced vibration, while the spacing of the inner maintenance track significantly affected the vortex-induced vibration at high wind speeds. Full article

A nonlinear log-Birnbaum–Saunders regression model with additive errors is introduced. It is assumed that the error term follows a flexible sinh-normal distribution, and therefore it can be used to describe a variety of asymmetric, unimodal, and bimodal situations. This is a novelty since there are few papers dealing with nonlinear models with asymmetric errors and, even more, there are few able to fit a bimodal behavior. Influence diagnostics and martingale-type residuals are proposed to assess the effect of minor perturbations on the parameter estimates, check the fitted model, and detect possible outliers. A simulation study for the Michaelis–Menten model is carried out, covering a wide range of situations for the parameters. Two real applications are included, where the use of influence diagnostics and residual analysis is illustrated. Full article

This paper explores bimodal skew-symmetric distributions, a versatile family of distributions characterized by parameters that control asymmetry and kurtosis. These distributions encapsulate both symmetrical and well-known asymmetrical behaviors. A simulation study evaluates the model’s estimation accuracy, detailing the score function and the robustness of the observed information matrix, which is proven to be non-singular under specific conditions. We apply the bimodal skew-normal model to protein data from cancer cells, comparing its performance against four established distributions supported on the entire real line. Results indicate superior performance by the proposed model, underscoring its potential for enhancing analytical precision in biological research. Full article

A synthetic strategy to access asymmetric dinuclear bis(ansa-metallocene) pre-catalysts is described. As a key step, the Pd-catalyzed Suzuki cross-coupling of 9,9-bis(trimethylsilyl)-fluoren-2-yl-boronic acid with a substituted 2-bromo-9H-fluorene generates an asymmetric 2,2′-bifluorene platform, which can be individually functionalized at the two differentiated 9-positions. Herein, as a first demonstration of this strategy, we report the asymmetric dinuclear bis(ansa-zirconocene) complex 2,2′-[{Me₂C(Flu)(Cp)}ZrCl₂][{Me₂C(^7-tBuFlu)(Cp)}ZrCl₂], which has been characterized with NMR spectroscopy and high-resolution mass spectrometry. The performance of this bimetallic pre-catalyst when combined with MAO has been evaluated in ethylene, propylene, and ethylene/1-hexene (co-)polymerization. This pre-catalyst is revealed to be less productive than the mononuclear reference pre-catalyst {Me₂C(^2,7-tBuFlu)(Cp)}ZrCl₂, likely because of higher steric hindrance induced by the linkage at the difluorenyl platform. The resulting (co-)polymers featured only slight differences in terms of molecular weights, tacticity, and comonomer incorporation. No bimodal molecular weight distribution was achieved at any produced polymer; this might have originated from the close similarity of the connected Cp/Flu moieties or a rapid chain-transfer phenomenon between the different active sites which were quite close to each other. Full article

In this paper, we present a two-component Weibull mixture model. An important property is that this new model accommodates bimodality, which can appear in data representing phenomena in some heterogeneous populations. We provide statistical properties, such as the quantile function and moments. Additionally, the expectation-maximization (EM) algorithm is used to find maximum-likelihood estimates of the model parameters. Further, a Monte Carlo study is carried out to evaluate the performance of the estimators on finite samples. The new model’s relevance is shown with an application referring to the vote proportion for the Brazilian presidential elections runoff in 2018. The proportion of votes is an important measure in analyzing electoral data. Since it is a variable limited to the unitary interval, unit distributions should be considered to analyze its probabilistic behavior. Thus, the introduced model is suitable for describing the characteristics detected in these data, such as the asymmetric behavior, bimodality, and the unit interval as support. In the application, the superiority of the proposed model is verified when comparing the fit with the two-component beta mixture models. Full article

It is common in many fields of knowledge to assume that the data under study have a normal distribution, which often generates mistakes in the results, since this assumption does not always coincide with the characteristics of the observations under analysis. In some cases, the data may have degrees of skewness and/or kurtosis greater than what the normal model can capture, and in others, they may present two or more modes. In this work, two new families of skewed distributions are presented that fit bimodal data with positive support. The new families were obtained from the extension of the bimodal normal distribution to the alpha-power family class. The proposed distributions were studied for their main properties, such as their probability density function, cumulative distribution function, survival function, and hazard function. The parameter estimation process was performed from a classical perspective using the maximum likelihood method. The non-singularity of Fisher’s information was demonstrated, which made it possible to find the stochastic convergence of the vector of the maximum likelihood estimators and, based on the latter, perform statistical inference via the likelihood ratio. The applicability of the proposed distributions was exemplified using real data sets. Full article

Image segmentation is an important task in image processing and analysis but due to the same ground object having different spectra and different ground objects having similar spectra, segmentation, particularly on high-resolution remote sensing images, can be significantly challenging. Since the spectral distribution of high-resolution remote sensing images can have complex characteristics (e.g., asymmetric or heavy-tailed), an innovative image segmentation algorithm is proposed based on the hierarchical Student’s-t mixture model (HSMM) and spatial constraints with adaptive smoothing. Considering the complex distribution of spectral intensities, the proposed algorithm constructs the HSMM to accurately build the statistical model of the image, making more reasonable use of the spectral information and improving segmentation accuracy. The component weight is defined by the attribute probability of neighborhood pixels to overcome the influence of image noise and make a simple and easy-to-implement structure. To avoid the effects of artificially setting the smoothing coefficient, the gradient optimization method is used to solve the model parameters, and the smoothing coefficient is optimized through iterations. The experimental results suggest that the proposed HSMM can accurately model asymmetric, heavy-tailed, and bimodal distributions. Compared with traditional segmentation algorithms, the proposed algorithm can effectively overcome noise and generate more accurate segmentation results for high-resolution remote sensing images. Full article

Aiming at the problem where the current engineering wake model does not describe the wind speed distribution of the wake in the complex terrain wind farm completely, based on the three-dimensional full wake model (3DJGF wake model), this paper proposed a wake model that can predict the three-dimensional wind speed distribution of the entire wake region in the complex wind farm, taking into account the Coanda effect, wind shear effect, and wake subsidence under the Gaussian terrain. Two types of Doppler lidar were used to conduct wind field experiments, and the inflow wind profile and three-dimensional expansion of the wake downstream of the wind turbine on the Gaussian terrain were measured. The experimental results showed that the wake centerline and terrain curve showed similar variation characteristics, and the near wake profile was similar to a super-Gaussian shape (asymmetric super-Gaussian shape) under low-wind-speed conditions, while the near wake profile presented a bimodal shape (asymmetric bimodal shape) under high-wind-speed conditions. The predicted profiles of the Gaussian terrain wake model were compared with the experimental data and the three typical wake models. The comparison results showed that the newly proposed Gaussian terrain wake model fit well with the experimental data in both near wake and far wake regions, and it had better performance in predicting the wake speed of the Gaussian terrain wind farm than the other three wake models. It can effectively predict the three-dimensional velocity distribution in the whole wake region of complex terrain. Full article

Motivated by the recent popularization of the beta prime distribution, a more flexible generalization is presented to fit symmetrical or asymmetrical and bimodal data, and a non-monotonic failure rate. Thus, the Weibull-beta prime distribution is defined, and some of its structural properties are obtained. The parameters are estimated by maximum likelihood, and a new regression model is proposed. Some simulations reveal that the estimators are consistent, and applications to censored COVID-19 data show the adequacy of the models. Full article

In this paper, we introduce bimodal extensions, one symmetric and one asymmetric, of the logistic distribution. We define this new density and study some basic properties. We draw inferences from the moment estimator and maximum likelihood approaches. We present a simulation study to assess the behaviour of the moment and maximum likelihood estimators. We also study the singularity of the Fisher information matrix for particular cases. We offer applications in real data and compare them with a mixture of logistics distributions. Full article

In this study, a technique that uses a capacitance sensor with an asymmetric electrode to measure the void fraction of a refrigerant was developed. It is known that the void fraction and flow pattern affect the measured capacitance. Therefore, the relationship between the void fraction and capacitance is not linear; hence, a calibration method for obtaining accurate measurements is necessary. A calibration method was designed in this study based on repeated capacitance measurements and the bimodal temporal distribution to calibrate the atypical and repetitive flow patterns of slug flow and its transition to the intermittent flow regime. The calibration method also considers the weighted-average relation for the gradual transition of the intermittent to annular flow pattern according to the change from low to high quality. The proposed method was experimentally analyzed under the conditions of R32 refrigerant, a tube inner diameter of 7.1 mm, saturation temperature of 25 °C, mass flux of 100–400 kg m⁻² s⁻¹, and vapor quality of 0.025–0.900, and it was validated using a quick-closing valve (QCV) system under identical conditions. A relative error of 2.99% was obtained for the entire system, indicating good agreement between the proposed and QCV-based methods. Full article

In this work, we propose a new bimodal distribution with support in the real line. We obtain some properties of the model, such as moments, quantiles, and mode, among others. The computational implementation of the model is presented in the tpn package of the software R. We perform a simulation study in order to assess the properties of the maximum likelihood estimators in finite samples. Finally, we present an application to a bimodal data set, where our proposal is compared with other models in the literature. Full article

In this article, we introduce a new family of symmetric-asymmetric distributions based on skew distributions and on the family of order statistics with proportional hazards. This new family of distributions is able to fit both unimodal and bimodal asymmetric data. Furthermore, it contains, as special cases, the symmetric distribution and the “skew-symmetric” family, and therefore the skew-normal distribution. Another interesting feature of the family is that the parameter controlling the distributional shape in bimodal cases takes values in the interval (0, 1); this is an advantage for computing maximum likelihood estimates of model parameters, which is performed by numerical methods. The practical utility of the proposed distribution is illustrated in two real data applications. Full article