Applicability Of Proposed Method Research Articles

Amplitude variation with incident angle inversion for fluid factor in the depth domain

The development of Pre−stack depth migration makes the imaging of the subsurface structure in the depth possible, which set a foun− dation for the study of amplitude variation with incident angle (AVA) inversion. This leads to the increasing demanding of the seismic inversion methods in the depth domain for guiding reservoir characterization. However, the conventional seismic inversion methods in the time domain are not suitable in the depth domain due to the seismic wavelet in the depth domain is depth−variant and depending on medium velocity. To address this issue, we proposed a pragmatic seismic inversion method for fluid factor in the depth domain with amplitude variation with incident angle gathers by using a true−depth wavelet on the process of seismic inversion. This wavelet is es− timated by converting the time wavelet to the depth wavelet with seismic velocity. To guide the fluid discrimination, the proposed method directly estimates the fluid factor from the pre−stack seismic data and all the process of the method is implemented in the depth domain. To deal with the weak nonlinearity induced by the velocity, the Bayesian inference, the prior information and model constraint are in− troduced in this seismic inversion method. Tests on synthetic data show that the fluid factor can be well estimated reasonably even with moderate noise. The field data example illustrates the feasibility and efficiency of the proposed method in application and the estimated fluid factor and shear modulus are in good agreement with the drilling results.

Centrifuge-less deep eutectic solvent based magnetic nanofluid-linked air-agitated liquid–liquid microextraction coupled with electrothermal atomic absorption spectrometry for simultaneous determination of cadmium, lead, copper, and arsenic in food samples and non-alcoholic beverages

In this research, the novel environmentally-friendly analytical method, Centrifuge-less deep eutectic solvent based magnetic nanofluid-linked air-agitated liquid–liquid microextraction (CL-DES-MNF-AALLME) coupled with ETAAS was proposed for simultaneous preconcentration of heavy metals of lead, arsenic, cadmium, and copper. In CL-DES-MNF-AALLME, the extraction solvent is novel magnetic nanofluid consists of DES based magnetic multiwall carbon nanotubes which can easily be separated from the media with no need to centrifugation. The detection limits of 4.2, 3, 3.5 and 3.6 ng L−1 were acquired for cadmium, lead, copper, and arsenic respectively. The proper closeness of enrichment factors in the range of 635–644.5 to preconcentration factor (640), confirm the quantitatively of the proposed extraction method with relative standard deviation of 2.5–3.1(%) (n = 7). The potential of the CL-DES-MNF-AALLME was considered in walnut, rice, tomato paste, spinach, orange juice, black tea, and water samples which showed high capability of the proposed method for application in the complex matrixes.

Stability Analysis of Axisymmetric Concave Slopes Based on Two‐Dimensional Limit Equilibrium Approach considering Additional Shear Resistance

Axisymmetric concave slopes, one special type of three‐dimensional (3D) slopes, may be encountered in mining and civil engineering practice. Analysis of 3D slopes is generally complex and mostly relies on complicated numerical simulations. This paper proposes an elastoplastic solution for determining the additional shear resistances due to spatial effects of axisymmetric concave slopes. By incorporating the extra antislide forces, this paper proposes a simplified two‐dimensional (2D) limit equilibrium procedure for the stability analysis of axisymmetric concave slopes. Combined with an iteration algorithm, the procedure can obtain the factors of safety for axisymmetric concave slopes in a simple and efficient way. Comparisons of the results from the proposed method and the numerical software FLAC3D are performed to demonstrate the validity of the proposed method for practical applications. Finally, the effects of several key parameters on the stability of axisymmetric concave slopes are investigated through a parametric study.

Reconstruction method for fluorescence molecular tomography based on L1-norm primal accelerated proximal gradient.

Fluorescence molecular tomography (FMT) has been widely used in preclinical tumor imaging, which enables three-dimensional imaging of the distribution of fluorescent probes in small animal bodies via image reconstruction method. However, the reconstruction results are usually unsatisfactory in the term of robustness and efficiency because of the ill-posed and ill-conditioned of FMT problem. In this study, an FMT reconstruction method based on primal accelerated proximal gradient (PAPG) descent and L1-norm regularized projection (L1RP) is proposed. The proposed method utilizes the current and previous iterations to obtain a search point at each iteration. To achieve fast convergence, the PAPG method is applied to efficiently solve the search point, and then L1RP is performed to obtain the robust and accurate reconstruction. To verify the performance of the proposed method, simulation experiments are conducted. The comparative results revealed that it held advantages of robustness, accuracy, and efficiency in FMT reconstructions. Furthermore, a phantom experiment and an in vivo mouse experiment were also performed, which proved the potential and feasibility of the proposed method for practical applications.

Regularized Gaussian Mixture Model for High-Dimensional Clustering.

Finding low-dimensional representation of high-dimensional data sets is an important task in various applications. The fact that data sets often contain clusters embedded in different subspaces poses barrier to this task. Driven by the need in methods that enable clustering and finding each cluster's intrinsic subspace simultaneously, in this paper, we propose a regularized Gaussian mixture model (GMM) for clustering. Despite the advantages of GMM, such as its probabilistic interpretation and robustness against observation noise, traditional maximum-likelihood estimation for GMMs shows disappointing performance in high-dimensional setting. The proposed regularization method finds low-dimensional representations of the component covariance matrices, resulting in better estimation of local feature correlations. The regularization problem can be incorporated in the expectation maximization algorithm for maximizing the likelihood function of a GMM, with the M -step modified to incorporate the regularization. The M -step involves a determinant maximization problem, which can be solved efficiently. The performance of the proposed method is demonstrated using several simulated data sets. We also illustrate the potential value of the proposed method in applications using four real data sets.

Health Degradation Monitoring and Early Fault Diagnosis of a Rolling Bearing Based on CEEMDAN and Improved MMSE.

Rolling bearings play a crucial role in rotary machinery systems, and their operating state affects the entire mechanical system. In most cases, the fault of a rolling bearing can only be identified when it has developed to a certain degree. At that moment, there is already not much time for maintenance, and could cause serious damage to the entire mechanical system. This paper proposes a novel approach to health degradation monitoring and early fault diagnosis of rolling bearings based on a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and improved multivariate multiscale sample entropy (MMSE). The smoothed coarse graining process was proposed to improve the conventional MMSE. Numerical simulation results indicate that CEEMDAN can alleviate the mode mixing problem and enable accurate intrinsic mode functions (IMFs), and improved MMSE can reflect intrinsic dynamic characteristics of the rolling bearing more accurately. During application studies, rolling bearing signals are decomposed by CEEMDAN to obtain IMFs. Then improved MMSE values of effective IMFs are computed to accomplish health degradation monitoring of rolling bearings, aiming at identifying the early weak fault phase. Afterwards, CEEMDAN is performed to extract the fault characteristic frequency during the early weak fault phase. The experimental results indicate the proposed method can obtain a better performance than other techniques in objective analysis, which demonstrates the effectiveness of the proposed method in practical application. The theoretical derivations, numerical simulations, and application studies all confirmed that the proposed health degradation monitoring and early fault diagnosis approach is promising in the field of prognostic and fault diagnosis of rolling bearings.

The performance of cathodically pretreated boron-doped diamond electrode in cationic surfactant media for enhancing the adsorptive stripping voltammetric determination of catechol-containing flavonoid quercetin in apple juice

In the present paper, an electroanalytical methodology was developed for the determination of an important catechol-containing flavonoid derivative, quercetin using adsorptive stripping voltammetry at a cathodically pretreated boron-doped diamond electrode. In cyclic voltammetry, the compound showed a couple of oxidation/reduction peak at low positive potentials, and additional two oxidation peaks at more positive potentials. The sensitivity of the stripping voltammetric measurements was significantly improved when the cationic surfactant, cetyltrimethylammonium bromide (CTAB) was present in the electrolyte solution. Using square-wave stripping mode, a highly linear analytical curve was obtained for quercetin determination in 0.1 M acetate buffer solution (pH 4.7) containing 3 × 10−4 M CTAB at + 0.37 V (vs. Ag/AgCl) (after 30 s accumulation at open-circuit condition) in the range of 0.5–200 ng mL−1 (1.7 × 10−9–3.3 × 10−7 M), with a detection limit of 0.132 ng mL−1 (4.4 × 10−10 M). As an example, the practical applicability of proposed method was successfully tested with the measurement of quercetin concentration in commercial apple juice samples.

Dielectric permittivity diagnostics as a tool for cultural heritage preservation: Application on degradable globigerina limestone

Most monuments and historical buildings in the Maltese Islands are made of the local Globigerina Limestone (GL). This type of stone, however, is very delicate and prone to degradation caused by the environmental conditions of the islands. Hence, for the preservation of the Cultural Heritage monuments, it is necessary to promptly assess the health status of these structures and, in particular, their water content (which represents one of the major causes of degradation).Starting from these considerations, in this work, a time domain reflectometry (TDR)-based method for estimating water content of GL is presented. More specifically, the proposed method relies on estimating the water content value of the GL structure from TDR-based dielectric permittivity measurements. To verify the suitability of this system, experimental tests were carried out on a GL sample. In addition to this, also the dielectric characterization of GL was carried out. The results anticipate the strong potential of the proposed method for practical applications in the Cultural Heritage diagnostics.

Laser heterodyne interference signal processing method based on phase shift of reference signal.

A novel signal processing method based on phase shift of reference signal is proposed for heterodyne interferometer. The integer fringe counting method based on overflow judgment and compensation can realize longtime and correct integer number measurement. In order to eliminate the influence of jitter in measurement signals on combination of integer and fraction fringe counting, the reference signal with phase shift of 180° is used to obtain integer compensating number to compensate the unstable integer number in unstable phase zone, which guarantees the correct combination of integer and fraction fringe counting. The principle of the proposed signal processing was described in detail. The static and dynamic resolution of the proposed method were discussed. A signal processing board based on FPGA was developed, and three tests were performed to verify the feasibility of the proposed method. A displacement measurement experimental setup was constructed, and two experiments verified the effectiveness of proposed method in application of an interferometer to realize precision displacement and testing of a stage.

Assessment of downburst wind loading on tall structures

Wind features for purposes of structural analysis and design, implicit in wind codes worldwide until the end of last century, were based on the behavior of synoptic winds in the vicinity of the ground surface. Afterwards it was finally recognized that synoptic storms are not the only cause of wind damage to buildings and structures, not even its main cause. In spite of this evidence, non-synoptic winds are still far from being considered as standard loading in structural design. A simplified approach recently proposed by one of the authors to describe the wind velocity field in this type of meteorological phenomenon, more specifically, in downbursts within instability lines, is herein examined, including an assessment of dynamic and size effects not previously addressed. The predictions of the proposed method in applications to tall and slender structures are determined in the paper, assuming that available aerodynamic coefficients, obtained assuming synoptic wind, may be still applied with negligible error.

Sintering process of inkjet-printed silver patterns using a heated inert gas

In this study, we introduce a thermal sintering process using a heated inert gas as a new sintering method. The heated gas flow is formed by passing nitrogen (N2) gas through a heating head of 300 to 700°C, and the desired substrates are then exposed to the heated gas flow through a 400mm long and 5mm wide slit-nozzle. Sintering performance of Ag films was characterized by analyzing the electrical resistivity and metallographic structures according to the temperature change of the heating head. The temperature distribution of the heating region is analyzed by infrared (IR) thermal imaging and surface temperature measured by thermo-label tape. To test the feasibility of the proposed method for application to printed circuit board (PCB) manufacturing, we performed a reliability evaluation using the printed Ag patterns under the standard of the Institute for Interconnecting and Packaging Electronic Circuit (IPC), TM650. Various reliability test patterns were created by Ag inkjet-printing on both a rigid flame retardant 4 (FR4) substrate and a flexible polyimide (PI) film substrate. The reliability evaluation includes withstanding voltage, adhesive strength, thermal shock, pressure cooker, and bending tests. The surface wettability of the substrates was controlled to obtain high quality fine and uniform patterns by UV/O3 treatment after coating a fluoropolymer thin film.

Evaluation of linear autoregressive models for estimation of energy spectra in gappy turbulent velocity data

AbstractThis paper deals with the problem of data interpolation in velocity time series measured by acoustic Doppler velocimeters and acoustic Doppler current profilers; the gap‐filled data are often used to determine turbulent kinetic energy (TKE) dissipation using Kolmogorov's inertial subrange scaling. For the latter to estimate dissipation accurately, it is important that the interpolation scheme preserves the attributes, both spectral slope and component magnitudes, of the true energy spectrum. We show that this goal can be achieved using the simple zeroth‐order sample and hold interpolation in situations where isolated data gaps, having durations shorter than the integral time scale of flow, occur. Its success is explained using the framework of stochastic autoregressive (AR) processes, which we also compare to the Langevin equation for the Lagrangian velocity of a turbulent flow field. We also demonstrate that linear interpolation is not appropriate because it can be interpreted as a nonstationary second order AR process, leading to erroneous conclusions for spectral slope and magnitude. When data dropouts occur in clusters, i.e., of durations longer than the integral time scale, we propose to use the first order AR process, of which sample and hold is its limiting case, for interpolation. The effectiveness of our proposal is tested and demonstrated with synthetic time series having a range of spectral slopes, from −7/6 to −8/3, and with experimental data measured in a turbulent channel flow. A comparison is also made with the more sophisticated proper orthogonal decomposition‐based interpolation. The paper ends with a step‐by‐step procedure on using the proposed method in applications.

Stiffness-based Approach for Preliminary Design of Framed Tube Structures

A parametric formulation for preliminary design of tubed-system tall buildings is presented in which some optimality criteria and practical constraints are considered. Here, a minimum compliance optimization formulation, developed by other researchers, is applied to a framed-tube structure. The tube behavior is modeled as a cantilevered box beam. Independent variable in this problem is thickness of the box, and a formulation for its optimal value is proposed. The challenge in this research was treatment of the lower bound constraint on thickness in an analytical manner. To deal with this constraint, a critical height parameter is introduced, and the design domain is divided into two zones of constant thickness and constant curvature. This definition allows for computation of optimal thickness distribution along the structure through an analytic dimensionless equation. Most of the previously published papers in the field of tall structures are suitable for abstract analyses but not for design. In addition, most of them are computer-based. Considering these limitations, the current research presents a hand-calculation method for preliminary design, suitable for sensitivity analyses and parametric studies. As the presented formulations are dimensionless, they are applicable in any dimensional system. Different static loading patterns are considered; including the concentrated, uniform, triangular and quadratic forms. A numerical example is presented to demonstrate the ease of the proposed method in application, and the analysis results are presented by charts to validate the efficiency of it.

Real‐time harmonic estimation using a novel hybrid technique for embedded system implementation

Summary In this paper, an analytical technique for efficient estimation of harmonics generated by power systems is presented. A robust linear estimator known as H∞ filter is applied to extract the amplitudes of harmonics. As well, phases are estimated using a nonlinear algorithm, namely, cubature Kalman filter. Both methods are based upon space modeling of the studied signals leading to improved numerical stability. The proposed H∞-cubature Kalman filter algorithm has the capability of estimating power system time varying waveforms even in highly noisy measurements. Synthetic and real signals are used for testing the proposed algorithm, and accuracy of the estimation is reported by statistical indices. Simulations in MATLAB are compared with unscented Kalman filter to represent the quality of estimation. Real-time implementation of the proposed algorithm is conducted using C++ programming code in hardware-in-the-loop laboratory. The setup consists of an embedded computer set and dedicated hardware. Results show satisfactory performance of the proposed method for practical application in power quality and protection cases.

Entropy Ensemble Filter: A Modified Bootstrap Aggregating (Bagging) Procedure to Improve Efficiency in Ensemble Model Simulation

Over the past two decades, the Bootstrap AGGregatING (bagging) method has been widely used for improving simulation. The computational cost of this method scales with the size of the ensemble, but excessively reducing the ensemble size comes at the cost of reduced predictive performance. The novel procedure proposed in this study is the Entropy Ensemble Filter (EEF), which uses the most informative training data sets in the ensemble rather than all ensemble members created by the bagging method. The results of this study indicate efficiency of the proposed method in application to synthetic data simulation on a sinusoidal signal, a sawtooth signal, and a composite signal. The EEF method can reduce the computational time of simulation by around 50% on average while maintaining predictive performance at the same level of the conventional method, where all of the ensemble models are used for simulation. The analysis of the error gradient (root mean square error of ensemble averages) shows that using the 40% most informative ensemble members of the set initially defined by the user appears to be most effective.

A simplified co‐rotational method for quadrilateral shell elements in geometrically nonlinear analysis

SummaryThis paper presents a simplified co‐rotational formulation for quadrilateral shell elements inheriting the merit of element‐independence from the traditional co‐rotational approach in literature. With the objective of application to nonlinear analysis of civil engineering structures, the authors further simplify the formulation of the geometrical stiffness using the small strain assumption, which is valid in the co‐rotational approach, with the warping effects considered as eccentricities. Compared with the traditional element‐independent co‐rotational method, the projector is neglected both in the tangent stiffness matrix and in the internal force vector for simplicity in formulation. Meanwhile, a quadrilateral flat shell element allowing for drilling rotations is adopted and incorporated into this simplified co‐rotational algorithm for geometrically nonlinear analysis involved with large displacements and large rotations. Several benchmark problems are presented to confirm the efficiency and accuracy of the proposed method for practical applications.

A general probabilistic approach for the quantitative assessment of LES combustion models

The Wasserstein metric is introduced as a probabilistic method to enable quantitative evaluations of LES combustion models. The Wasserstein metric can directly be evaluated from scatter data or statistical results through probabilistic reconstruction. The method is derived and generalized for turbulent reacting flows, and applied to validation tests involving a piloted turbulent jet flame with inhomogeneous inlets. It is shown that the Wasserstein metric is an effective validation tool that extends to multiple scalar quantities, providing an objective and quantitative evaluation of model deficiencies and boundary conditions on the simulation accuracy. Several test cases are considered, beginning with a comparison of mixture-fraction results, and the subsequent extension to reactive scalars, including temperature and species mass fractions of CO and CO2. To demonstrate the versatility of the proposed method in application to multiple datasets, the Wasserstein metric is applied to a series of different simulations that were contributed to the TNF-workshop. Analysis of the results allows to identify competing contributions to model deviations, arising from uncertainties in the boundary conditions and model deficiencies. These applications demonstrate that the Wasserstein metric constitutes an easily applicable mathematical tool that reduce multiscalar combustion data and large datasets into a scalar-valued quantitative measure.

Analysis of KUCA measurements by the reactivity monitoring MAρTA method

A recently developed method for the continuous reactivity monitoring in nuclear reactors and in subcritical source-driven systems is applied for the interpretation of flux measurements carried out in the KUCA facility. The scope of the work is to validate the method using real experimental data. The method is based on general mathematical properties of the differential equations constituting the point kinetic model. Several pulsed experiments performed in different system configurations and using different source target materials are analysed. The results are compared with the classic area ratio method. A good agreement is obtained when the space-energy transient following the source shut-down dies out and when the system sets on a point-like evolution. The results prove the suitability of the proposed method for application to the reactivity monitoring of source-driven systems.

A polynomial equation-based interpolation method of NURBS tool path with minimal feed fluctuation for high-quality machining

Due to the approximation errors of interpolation methods in non-uniform rational b-spline (NURBS) interpolation, feed fluctuation is inevitable, which has great effects on the machining quality and should be minimized. Based on the idea of zero feed fluctuation, a polynomial equation-based interpolation method of NURBS tool path is proposed in this paper. Firstly, a polynomial equation with respect to the curve parameter increment is formulized according to the sampling step size, which is determined by the scheduled feedrate, acceleration, and jerk. Then, Newton’s method is utilized to solve the high-degree polynomial equation with taking both convergence rate and computational load. In order to improve the computing efficiency in real-time interpolation, a fast-evaluation and derivation algorithm is proposed, which uses the Taylor series expansion to accelerate the calculation of any order derivatives of NURBS. Simulations are conducted among the proposed method and the chord-tracking algorithm (CTA) method, and the results of each method are compared on the basis of computing time and feed fluctuation, which shows that the proposed method is better than the CTA method. Experiment is also conducted to verify the feasibility and applicability of the proposed method in practical application.

Application of engineering ductile tearing simulation method to CRIEPI pipe test

A method to simulate ductile tearing in large-scale pipes using finite element analysis is proposed, based on the stress-modified fracture strain model. An element-size-dependent critical damage model is also introduced in damage simulations. The damage model and associate parameters are determined from tensile and fracture toughness test data. The method is applied to simulate five bending tests of circumferential cracked carbon steel pipes. Simulated results agree overall well with two through-wall cracked pipe test data, but consistently over-predict the maximum loads for three surface cracked pipe tests. Advantages of the proposed method in practical application is briefly discussed.