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This paper aims to present new analytical model for the filling times prediction in flip-chip underfill encapsulation process that is based on the surface energetic for post-bump flow.

The current model was formulated based on the modified regional segregation approach that consists of bump and post-bump regions. Both the expansion flow and the subsequent bumpless flow as integrated in the post-bump region were modelled considering the surface energy–work balance.

Upon validated with the past underfill experiment, the current model has the lowest root mean square deviation of 4.94 s and maximum individual deviation of 26.07%, upon compared to the six other past analytical models. Additionally, the current analytically predicted flow isolines at post-bump region are in line with the experimental observation. Furthermore, the current analytical filling times in post-bump region are in better consensus with the experimental times as compared to the previous model. Therefore, this model is regarded as an improvised version of the past filling time models.

The proposed analytical model enables the filling time determination for flip-chip underfill process at higher accuracy, while providing more precise and realistic post-bump flow visualization. This model could benefit the future underfill process enhancement and package design optimization works, to resolve the productivity issue of prolonged filling process.

The analytical underfill studies are scarce, with only seven independent analytical filling time models being developed to date. In particular, the expansion flow of detachment jump was being considered in only two previous works. Nonetheless, to the best of the authors’ knowledge, there is no analytical model that considered the surface energies during the underfill flow or based on its energy–work balance. Instead, the previous modelling on post-bump flow was based on either kinematic or geometrical that is coupled with major assumptions.

Recent U.S. Treasury yields have been constrained to some extent by the zero lower bound (ZLB) on nominal interest rates. Therefore, we compare the performance of a standard affine Gaussian dynamic term structure model (DTSM), which ignores the ZLB, to a shadow-rate DTSM, which respects the ZLB. Near the ZLB, we find notable declines in the forecast accuracy of the standard model, while the shadow-rate model forecasts well. However, 10-year yield term premiums are broadly similar across the two models. Finally, in applying the shadow-rate model, we find no gain from estimating a slightly positive lower bound on U.S. yields.

The aim of this work is to evaluate the electrochemical noise (EN) method as a way of evaluating quickly the aggressiveness of natural atmospheres.

Wire‐on‐bolt tests were used, which implies an exposure of at least three months of bimetallic specimens such as aluminium wire/steel bolt and aluminium wire/copper bolt (CLIMAT units). Electrochemical noise measurements (ENM) also were used.

EN is a powerful tool in the assessing of aggressiveness of atmospheres in short time exposure. Statistical analyses of EN were carried out and provided clear differences between atmospheres depending on pollutants. Results of noise resistance (R_n), root mean square of current (I_rms) and localization index are discussed.

The possible application of ENM to atmospheric corrosion is interesting from a practical point of view. However, more experiments are necessary in order to test a wide range of atmospheres.

EN has proved to be a useful tool when localised corrosion is detected and the presence of chlorides in atmospheres, due to sea fog, results in pitting on the metallic samples.

Illustrates that electrochemical noise can be a powerful tool for assessing the aggressiveness of natural atmospheres.

The purpose of the paper is to study natural convection within porous square and triangular geometries (design 1: regular isosceles triangle, design 2: inverted isosceles triangle) subjected to discrete heating with various locations of double heaters along the vertical (square) or inclined (triangular) arms.

Galerkin finite element method is used to solve the governing equations for a wide range of modified Darcy number, Da_m = 10⁻⁵–10⁻² with various fluid saturated porous media, Pr_m = 0.015 and 7.2 at a modified Rayleigh number, Ra_m = 10⁶ involving the strategic placement of double heaters along the vertical or inclined arms (types 1-3). Adaptive mesh refinement is implemented based on the lengths of discrete heaters. Finite element based heat flow visualization via heatlines has been adopted to study heat distribution at various portions.

The strategic positioning of the double heaters (types 1-3) and the convective heatline vortices depict significant overall temperature elevation at both Da_m = 10⁻⁴ and 10⁻² compared to type 0 (single heater at each vertical or inclined arm). Types 2 and 3 are found to promote higher temperature uniformity and greater overall temperature elevation at Da_m = 10⁻². Overall, the triangular design 2 geometry is also found to be optimal in achieving greater temperature elevation for the porous media saturated with various fluids (Pr_m).

Multiple heaters (at each side [left or right] wall) result in enhanced temperature elevation compared to the single heater (at each side [left or right] wall). The results of the current work may be useful for the material processing, thermal storage and solar heating applications.

The heatline approach is used to visualize the heat flow involving double heaters along the side (left or right) arms (square and triangular geometries) during natural convection involving porous media. The heatlines depict the trajectories of heat flow that are essential for thermal management involving larger thermal elevation. The mixing cup or bulk average temperature values are obtained for all types of heating (types 0-3) involving all geometries, and overall temperature elevation is examined based on higher mixing cup temperature values.

Alzheimer’s disease (AD), the most common cause of dementia, is a neurodegenerative disorder caused by the aggregation of amyloid-beta (Aβ) at outside of neuron cells and also due to tau aggregation inside the cell. Corosolic acid is aimed to be selected as a main active constituent of Lagerstroemia speciosa for the study.

In the present study, molecular docking of corosolic acid and tau protein was examined using PyRx-v.0.8 software. Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties were described and a molecular dynamics study of the bound complex was performed using Desmond.

The docking score and interactions suggested that the corosolic acid (CID:6918774) could bind to tau protein to prevent the fibrillar network, to prevent AD. During simulation corosolic acid-bound protein root mean square deviation (RMSD) values showed more stability when compared to the Apo form of protein. Molecular dynamics study of tau protein and corosolic acid complex gave the insights to develop a drug-like candidate against AD.

The use of corosolic acid of Lagerstroemia speciosa to prevent AD is supported by preliminary analysis on a computational basis. This compound should explore in terms of experimental strategies for the further drug development process. However, in vitro and in vivo evaluation studies are required to suggest the use of corosolic acid against AD.

The purpose of this paper is to present simple correlation for calculating nitrated hydroxyl-terminated polybutadiene (NHTPB) enthalpy of formation.

It uses multiple linear regression methods.

The proposed correlation has determination coefficient 0.96. The correlation has root mean square deviation and the average absolute deviations values 53.4 and 46.1 respectively.

The predictive power of correlation is checked by cross-validation method (R²=0.96, Q L O O 2 = 0.96 ).

This study aims to examine the role of an overall model fit assessment in the context of partial least squares path modeling (PLS-PM). In doing so, it will explain when it is important to assess the overall model fit and provides ways of assessing the fit of composite models. Moreover, it will resolve major concerns about model fit assessment that have been raised in the literature on PLS-PM.

This paper explains when and how to assess the fit of PLS path models. Furthermore, it discusses the concerns raised in the PLS-PM literature about the overall model fit assessment and provides concise guidelines on assessing the overall fit of composite models.

This study explains that the model fit assessment is as important for composite models as it is for common factor models. To assess the overall fit of composite models, researchers can use a statistical test and several fit indices known through structural equation modeling (SEM) with latent variables.

Researchers who use PLS-PM to assess composite models that aim to understand the mechanism of an underlying population and draw statistical inferences should take the concept of the overall model fit seriously.

To facilitate the overall fit assessment of composite models, this study presents a two-step procedure adopted from the literature on SEM with latent variables.

This paper clarifies that the necessity to assess model fit is not a question of which estimator will be used (PLS-PM, maximum likelihood, etc). but of the purpose of statistical modeling. Whereas, the model fit assessment is paramount in explanatory modeling, it is not imperative in predictive modeling.

The purpose of this paper is to improve the hydraulic efficiency without changing the overall dimension. The blade profile optimization design of the aero-centrifugal pump based on the biharmonic equation surrogate model has been studied.

First of all, Bezier curves and linear function are used to control the annular angle distribution and the stacking angle of blade profile under the MATLAB platform. Grid independence analysis has been studied to find the finest mesh scheme. After the precision comparison of test data and computation fluid dynamics 15 sets of design parameters are carried out as the boundary condition of the biharmonic equation. The efficiency surrogate model of the biharmonic equation is constructed via iteratively solving of a discrete difference equation. The other two surrogate models of response surface model (RSM) and radial basis function neural network surrogate model (RBFNNSM) are compared with the biharmonic equation surrogate model by the standard of modified complex correlation coefficient R² and root mean square deviation (RSME). Finally, the artificial fish swarm algorithm has been used to find the global optimal design parameters with the objective function of highest efficiency.

The results show that the design parameters code conversion method can reduce the number of optimization parameters from five to three, makes the design space become a cube, and compared with RSM and RBFNNSM, the biharmonic equation surrogate model has higher precision with R² is 0.8958, RSME is 0.1382. The final optimum result of AFSA is at the point of [1 −1 −1]. The internal flow field analysis shows that after optimization the outlet relative velocity becomes more uniform and the wake effect has been significantly decreased. The hydraulic efficiency of the optimized pump is about 59.45 per cent increasing 5.4 per cent compared with a prototype pump.

This study developed a new method to optimize the design parameters of aero-centrifugal pump impeller based on biharmonic equation surrogate model, which had a good agreement with experimental values within just 15 sets of the original design. The optimization results shows that the method can improve the hydraulic efficiency significantly.

At present, piezoelectric impedance technology has been used in the study of wood damage monitoring. However, little effort has been made in the research on the application of piezoelectric impedance system to monitor the change of wood moisture content (MC). The monitoring method of wood MC is used by piezoelectric impedance technique in this study.

One piezoceramic transducer is bonded to the surface of wood specimens. The MC of the wood specimens increases gradually from 0% to 60% with 10% increments; the mechanical impedance of the wood specimen will change, and the change in the mechanical impedance of the structure is reflected by monitoring the change in the electrical impedance of lead zirconate titanate. Therefore, this paper investigates the relationship between wood MC change and piezoelectric impedance change to verify the feasibility of the piezoelectric impedance method for monitoring wood MC change.

The experiment verified that the real part of impedance of the wood increased with the increase of wood MC. Besides, the damage index root mean square deviation is introduced to quantify the damage degree of wood under different MC. At the same time, the feasibility and validity of this experiment were verified from the side by finite element simulation. Finally, MC monitoring by piezoelectric impedance technique is feasible.

To the best of the authors’ knowledge, this work is the first to apply piezoelectric ceramics to the monitoring of wood MC, which provides a theoretical basis for the follow-up study of a wide range of wood components and even wood structure MC changes.

This study aims to use frequency response analysis, a powerful tool to detect the location and types of transformer winding faults. Proposing an effective intelligent approach for interpreting the frequency responses is the most crucial problem of this method and has created many challenges.

Heat maps based on appropriate statistical indices have been supplied to depict the variations in the frequency responses associated with each fault type, fault location and fault extent along the windings. Also, after analyzing the results of artificial neural network (ANN) techniques, the generalized regression neural network method is introduced as the most effective solution for the classification of transformer winding faults.

Using a comparative approach, the performance of the used indices and ANN techniques are evaluated. The results showed the proper performance of Lin’s concordance coefficient (LCC) index and the amplitude (Amp) part of the frequency response. The proposed fitting percentage (FP) index can assist the intelligent classifiers in diagnosing the radial deformation (RD) fault with the highest accuracy considering all frequency response components in the classification procedure of winding faults.

Various ANN techniques are used to detect and determine the type of four important faults of transformer winding, i.e. axial displacement, RD, disc space variation and short circuit. Various statistical indices, such as cross-correlation factor, LCC, standard difference area, sum of errors, normalized root-mean-square deviation and FP, are used to extract the features of the frequency responses to consider as the ANN inputs. In addition, different components of the frequency response, such as Amp, argument, real and imaginary parts are examined in this paper. To implement the proposed procedure, step by step, various types of winding faults with different locations and extents are applied on the 20 kV winding of a 1.6 MVA distribution transformer.

Contributions have been made in identifying and diagnosing transformer winding defects through the use of appropriate algorithms for future research.