Linear Superposition Model Research Articles

Corrosion fatigue crack growth model for aluminum alloys in jet fuel

AbstractAluminum alloys are primary structural materials in aircraft fuel systems, where jet fuel can influence the fatigue crack growth (FCG) behavior of materials. This paper presents a model for calculating the FCG rate of aluminum alloys in jet fuel environment. The model is based on elastoplastic fracture mechanics and revises the interaction terms in the linear superposition model by accounting for the corrosive environment and the crack closure effect. The derivation process of the model is discussed in detail. To validate the efficacy of the model, FCG tests were conducted on three types of aviation aluminum alloys, namely, 2524‐T3, 7050‐T7451, and 7075‐T62 in the jet fuel. The experimental results were compared with FCG rates in the laboratory air environment. Findings indicate that the proposed model effectively captures the primary trends observed in the experimental data. In addition, the failure surfaces of the specimens were observed using a super‐depth‐of‐field optical microscopy system.

Finite element analysis of fretting fatigue properties of GH4169 superalloy considering the surface treatments

In the present work, the fretting fatigue properties of GH4169 superalloy at 650℃ were investigated through numerical simulation considering the influences of the surface treatments. As a detrimental phenomenon, fretting fatigue involves fatigue and wear simultaneously, where the coefficient of friction and residual stress fields induced by the surface coating or modification techniques may affect the fretting fatigue lifetimes by changing the complex stress state between the two contacting surfaces. The numerical solutions were implemented to compare the crack initiation angles and paths under different surface conditions. The simulation results indicated that fretting fatigue cracks in residual stress fields were tendentiously parallel to the surface resulting in crack retardation and debris peeling, as verified by experimental observations. Additionally, three propagation models were compared to study the effect of compressive loading on the driving force of crack propagation rates, especially where compressive residual stresses was present. The combination of the linear superposition model with the Harter-T method was proven to be more accurate in the fretting fatigue life prediction, which may provide a modeling basis for service life prediction of engineering components in many practical applications.

CVT on-line error measurement hybrid-driven by domain knowledge and Stacking Model

The performance of Capacitive Voltage Transformer (CVT) degrades over time, making measurement error monitoring a research hotspot in the field of smart grid. At present, these are several challenges such as complex data features, a lack of criteria for selecting optimal measurement models, and low precision. CVT measurement errors can be classified into ideal error and additional one. The former is typically evaluated via mutual information and redundancy within the topology-level transformer group. Considering that a single model cannot process the time series, strong randomness and nonlinearity of the additional error, the Stacking model is selected. Based on the principle of heterogeneity and high-quality, correlation coefficient and feature contribution degree, Random Forest, eXtreme Gradient Boosting, Ridge Regression, K Nearest Neighbors, Support Vector Regression, and Long Short-Term Memory are chosen as base learners through correlation and feature contribution analysis; while extra-trees with strong generalization and robustness is chosen as the meta learner. To improve the measurement precision, the attention-like mechanism is used to scale time and accuracy weights. Finally, according to the power domain knowledge, a linear superposition model is developed to fuse the ideal and additional errors, and thus realize online error measurement for CVTs. The experimental results indicate that the improved Stacking model outperforms mainstream measurement models by an average reduction of 59.47%, and 52.58% in the root mean squared error and the mean absolute error with the best R2 closest to 1. It not only effectively improves the accuracy but also meets speed requirement for online error measurement.

Lactoferrin as a carrier of iron: Development and physicochemical characterization

Iron deficiency is the main cause of anemia, one of the most common nutritional deficiencies affecting millions of people worldwide. In addition, iron instability, sensitivity, and intense flavor limit its use in food fortification. In this work, lactoferrin (LF) particles were developed by Nano Spray Dryer (NSD) and its capacity to be used as an iron carrier was evaluated. The effect of NSD temperature (60 °C, 80 °C, and 100 °C) and LF concentrations (10 mg mL−1, 50 mg mL−1, and 100 mg mL−1) was evaluated on the LF structure and on the production and stability of a LF-iron carrier. Results showed that the NSD is suitable for producing LF particles with diameters ranged from 38.8 nm to 4533.6 nm. Although different surface morphologies were obtained, higher protein concentrations (100 mg mL−1) produced round shape and smooth surface particles, but for lower protein concentrations (10 mg mL−1 and 50 mg mL−1) wrinkled particles and doughnut shape particles were obtained. SDS-page electrophoresis and circular dichroism (CD) for secondary structure (185–260 nm) show that the characteristics of the structures were maintained, meaning that NSD does not cause protein degradation. CD for tertiary structure (250 nm–350 nm) and fluorescence tests confirmed the interaction between LF and iron, observed by an intensity decrease and a wavelength shift in fluorescence spectra. The CD tertiary structure analysis showed higher ellipticity for the Trp peak, meaning conformational changes in the neighbor amino acids due to protein-iron interaction. Iron release experiments were performed at different pH values (2.0 and 7.4) at 37 °C aiming to understand the release mechanism in different media. Results showed that at pH 2 the iron release could be described by the linear superposition model (Radj2 = 0.9879) (explained by Fick and relaxation phenomenon) and that at pH 7.4 there is no iron release, showing that particles are stable at neutral pH. NSD is a suitable technology for producing iron-loaded protein-based carriers that could be used in food applications.

Experimental study on a light–heavy interface evolution induced by two successive shock waves

Richtmyer–Meshkov instability induced by two successive shock waves is experimentally studied in a specific shock tube. To create two successive shock waves synchronously, a driver section is added between the driver and driven sections of the standard shock tube, and an electronically controlled membrane rupture equipment is adopted. The shock-tube flow after the membranes rupture is well described by combining the shock relations, isentropic wave relations with compatibility relations across the contact surface (region). The new shock tube is capable of generating two successive shock waves with controllable strengths and time interval, and provides a relatively ‘clean’ wave system. Then the developments of single-mode light–heavy interfaces with different initial conditions induced by two successive shock waves are investigated. The initial amplitudes are all small enough such that the first-shocked interface is within the linear growth regime at the arrival of the second shock. The results show that if the pre-second-shock perturbation amplitude is small, the linear, nonlinear and modal evolutions of the double-shocked interface can be reasonably predicted by the existing models proposed for predicting the perturbation growth induced by a single shock. For the double-shocked interface, the second shock provides an additional perturbation velocity field to the original one introduced by the first shock impact. The validity of the linear superposition model indicates that the linear superposition of these two perturbation velocity fields is satisfied. Therefore, a double-shocked interface evolves similarly to a single-shocked interface provided that their postshock amplitudes and linear growth rates are the same.

Study on Doppler Spectra of Electromagnetic Scattering of Time-Varying Kelvin Wake on Sea Surface.

In general, it is more practical to detect ship wake under the background of a complicated sea state than the ship directly. Thus, in this paper, the Doppler spectra of time-varying Kelvin wake on a time-varying sea surface are numerically investigated by considering the change of ship wake with time in ocean environments. For this purpose, the linear superposition model of a time-varying sea surface and a time-varying Kelvin wake is established. Combined with the facet scattering field model of sea surface and Kirchhoff approximation (KA), the Doppler of the radar scattering echo signal of the time-varying wake on the sea surface is simulated and analyzed under different polarizations, incident angles, ship speeds, and wind speeds, as well as wind directions. It can be observed that the Doppler spectrum changes as the conditions change. This study provides a reference for extracting motion features of ship wakes in a sea clutter environment.

A Linear Superposition Model of Envelope and Frequency Following Responses May Help Identify Generators Based on Latency.

Envelope and frequency-following responses (FFRENV and FFRTFS) are scalp-recorded electrophysiological potentials that closely follow the periodicity of complex sounds such as speech. These signals have been established as important biomarkers in speech and learning disorders. However, despite important advances, it has remained challenging to map altered FFRENV and FFRTFS to altered processing in specific brain regions. Here we explore the utility of a deconvolution approach based on the assumption that FFRENV and FFRTFS reflect the linear superposition of responses that are triggered by the glottal pulse in each cycle of the fundamental frequency (F0 responses). We tested the deconvolution method by applying it to FFRENV and FFRTFS of rhesus monkeys to human speech and click trains with time-varying pitch patterns. Our analyses show that F0ENV responses could be measured with high signal-to-noise ratio and featured several spectro-temporally and topographically distinct components that likely reflect the activation of brainstem (<5 ms; 200-1000 Hz), midbrain (5-15 ms; 100-250 Hz), and cortex (15-35 ms; ~90 Hz). In contrast, F0TFS responses contained only one spectro-temporal component that likely reflected activity in the midbrain. In summary, our results support the notion that the latency of F0 components map meaningfully onto successive processing stages. This opens the possibility that pathologically altered FFRENV or FFRTFS may be linked to altered F0ENV or F0TFS and from there to specific processing stages and ultimately spatially targeted interventions.

Exploring the performance of amaranth grain starch and protein microcapsules as β-carotene carrier systems for food applications

Underexploited sources of bio-based wall materials for bioactive compounds (such as β-carotene) encapsulation have gained increasing interest within the scientific community. In this study, the potential of amaranth (Amaranthus cruentus) grain starch and protein rich fractions as microcapsules’ wall materials to carrier β-carotene was evaluated. Microcapsules were produced by spray-drying and their morphological and physicochemical characterisation was carried out. The microcapsules presented a spherical shape (particle size distribution: 0.3–30 µm) and encapsulation efficiencies ranging from 64 % to 69 %. Results showed that protein-based microcapsules had better β-carotene storage stability as compared to starch-based microcapsules (at 8 and 25 °C). β-carotene release kinetics at 37 °C and pH 7.4 could be mainly described by structural-relaxation phenomenon using the linear superposition model. Moreover, encapsulated β-carotene exhibited higher bioaccessibility than its free form after simulated in vitro digestion tests. Microcapsules did not affect cell viability at 0.0625 mg L−1 of β-carotene. Thus, amaranth grain biopolymers-based microcapsules were successfully developed as promising β-carotene delivery systems to be added to food products and consequently, to improve their functionality.

Numerical and experimental investigations on fretting fatigue properties of GH4169 superalloy at the elevated temperature

Fretting fatigue is a detrimental phenomenon in aeronautic industry, where the appropriate methods for crack location prediction and total life prediction are vital. In the present paper, both experimental and numerical approaches were developed for GH4169 superalloy with different interference magnitudes at 650 °C. Three fretting crack initiation models were compared for crack location prediction, among which the SWT model was extended to describe the initiation face in the three-dimensional model considering the subsurface stresses. Moreover, three propagation models were conducted for crack growth rate calculation. One of the methods was the combination of the linear superposition model with the Harter-T method, which emphasized the compression load effect on the driving force of crack propagation rates and the negative stress ratio variation impact. Finally, the life prediction approach was proposed using the averaged SWT parameters combined with the composite propagation model. The obtained total life estimations were found to agree well with the experimental results.

Rain Detection and Removal via Shrinkage-based Sparse Coding and Learned Rain Dictionary

Abstract Rain removal is essential for achieving autonomous driving because it preserves the details of objects that are useful for feature extraction and removes the rain structures that hinder feature extraction. Based on a linear superposition model in which the observed rain image is decomposed into two layers, a rain layer and a non-rain layer, conventional rain removal methods estimate these two layers alternatively from an observed single image based on prior modeling. However, the prior knowledge used for the rain structures is not always correct because various types of rain structures can be observed in the rain images, which results in inaccurate rain removal. Therefore, in this article, a novel rain removal method based on the use of a scribbled rain image set and a new shrinkage-based sparse coding model is proposed. The scribbled rain images have information about which pixels have rain structures. Thus, various types of rain structures can be modeled, owing to the abundance of rain structures in the rain image set. To detect the rain regions, two types of approaches, one based on reconstruction error comparison (REC) via a learned rain dictionary and the other based on a deep convolutional neural network (DCNN), are presented. With the rain regions, the proposed shrinkage-based sparse coding model determines how much to reduce the sparse codes of the rain dictionary and maintain the sparse codes of the non-rain dictionary for accurate rain removal. Experimental results verified that the proposed shrinkage-based sparse coding model could remove rain structures and preserve objects’ details due to the REC- or DCNN-based rain detection using the scribbled rain image set. Moreover, it was confirmed that the proposed method is more effective at removing rain structures from similar objects’ structures than conventional methods.

Combined scalar tracking, computational fluid dynamics, and multi-objective genetic algorithm method to accelerate optimization of film cooling systems

This paper presents a method to significantly accelerate optimization of film cooling systems. The method combines high-fidelity computational fluid dynamics with scalar tracking implemented, a proxy model (linear superposition model) initialized with the computational fluid dynamics solution, and a multi-objective evolutionary algorithm approach. The proposed method is structured as follows: the computational fluid dynamics solution is used to predict the (generally complex) flow domain for the film cooling system; the scalar tracking method identifies the contributions of individual holes to an overall cooling effectiveness distribution by associating a unique passive scalar variable to the flow associated with each hole, and solving an additional advection–diffusion (scalar transport) equation; the proxy model is a (generally linear) superposition model implemented – for example – in Matlab, which inherits the scalar values from the computational fluid dynamics solution, and allows extrapolation of solutions to new design points as part of an optimization process; the optimization process is handled with a multi-objective evolutionary algorithm approach which iterates the proxy model to optimize for a defined objective function. The process works with inner and outer convergence loops. The inner convergence loop is the multi-objective evolutionary algorithm interfacing with the proxy model, which achieves convergence against a design target. At the end of each inner loop cycle, a high-fidelity computational fluid dynamics simulation is run, and this is used to recalibrate the proxy model. Convergence for a given objective function is typically achieved with six outer-loop iterations (high-fidelity computational fluid dynamics runs) and 10,000 inner-loop iterations per outer-loop iteration. The significant advantage of the proposed method is that for certain optimization problems, the computational cost can be reduced by several orders of magnitude, replacing thousands of high-fidelity computational fluid dynamics runs with approximately six computational fluid dynamics runs. The process is demonstrated by applying the optimization method to the film cooling of a flat plate. In our example we have an objective function which maximizes the component life (related to the difference from an arbitrary target temperature distribution) and minimizes the mixing loss introduced by the films. The flow environment was moderately compressible. The optimization converged after six computational fluid dynamics runs. A 30% reduction in mixing loss, a 11% increase in component life, and a 30% reduction in cooling mass flow rate were achieved. The advantages and limitations of the proposed method are also discussed in detail.

Development and Characterization of Lipid-Based Nanosystems: Effect of Interfacial Composition on Nanoemulsion Behavior

Nanoemulsions were successfully developed through high-pressure homogenization. The layer-by-layer electrostatic technique was used for the subsequent deposition of a chitosan and alginate polyelectrolyte layers, thus leading to the development of a multilayer nanoemulsion. The effect of polyelectrolytes concentration in the development of multilayer nanoemulsions was evaluated in terms of hydrodynamic diameter (Hd), polydispersity index (PdI), zeta potential (Zp), and curcumin encapsulation efficiency. The interactions between polyelectrolytes and nanoemulsion were further analyzed using Fourier transform infrared (FTIR) spectroscopy and quartz crystal microbalance (QCM), while curcumin degradation was determined through the evaluation of the antioxidant capacity of the nanosystems. Results showed an encapsulation efficiency of 99.8 ± 0.8% and a loading capacity of 0.53 ± 0.03% (w/w). The presence of the multilayers leads to an increase of the Hd of the nanosystems, from 80.0 ± 0.9 nm (nanoemulsion) to 130.1 ± 1.5 nm (multilayer nanoemulsion). Release profiles were evaluated at different conditions, fitting a linear superposition model to experimental data suggests an anomalous behavior, being the relaxation of the surfactant and polyelectrolytes the rate-determining phenomena in curcumin release. The developed nanosystems showed great potential for the incorporation of lipophilic bioactive compounds, in view of their application in food and pharmaceutical products.

The Influence of Al Content and Thickness on the Microstructure and Tensile Properties in High-Pressure Die Cast Magnesium Alloys

The influence of Al content and section thickness on the microstructural features and tensile properties of high-pressure die cast AM series magnesium alloys is quantified in order to better understand the relationship between microstructure and tensile properties. It is found that with increasing aluminum content, the yield strength increases and the ductility decreases. Increasing the plate thickness results in a decrease in both the yield strength and ductility. The grain size, β-Mg17Al12 phase volume fraction, and solute content are all quantified through the thickness of the plates. It is found that the plates have a skin with increased hardness, due to a fine grain structure. The primary factors affecting strengthening in these alloys, including microstructural variations through the thickness, are accounted for using a linear superposition model. We conclude that yield strength is dominated by grain boundary strengthening and solid solution strengthening effects. The through-thickness grain size and solute concentration were quantified and these variations were found to play an important role in controlling the yield strength of these alloys.

Lactoferrin-based nanoparticles as a vehicle for iron in food applications – Development and release profile

This study aims at developing and characterizing bovine lactoferrin (bLf) nanoparticles as an iron carrier. bLf nanoparticles were characterized in terms of size, polydispersity index (PdI), electric charge (ζ-potential), morphology, structure and stability over time. Subsequently, iron release experiments were performed at different pH values (2.0 and 7.0) at 37°C, in order to understand the release mechanism. bLf (0.2%, w/v) nanoparticles were successfully produced by thermal gelation (75°C for 20min). bLf nanoparticles with 35mM FeCl3 showed an iron binding efficiency value of approximately 20%. The nanoparticles were stable (i.e. no significant variation of size and PdI of the nanoparticles) for 76days at 4°C and showed to be stable between 4 and 60°C and pH2 and 11. Release experiments at pH2 showed that iron release could be described by the linear superposition model (explained by Fick and relaxation phenomenon). On the contrary, the release mechanism at pH7 cannot be described by either Fick or polymer relaxation behaviour. In general, results suggested that bLf nanoparticles could be used as an iron delivery system for future food applications.

Influence of chitosan coating on protein-based nanohydrogels properties and in vitro gastric digestibility

Chitosan coating was applied in Lactoferrin (Lf)-Glycomacropeptide (GMP) nanohydrogels by layer-by-layer coating process. A volume ratio of 10 of Lf-GMP nanohydrogels (0.2 mg mL−1, at pH 5.0) to chitosan (1 mg mL−1, at pH 3) demonstrated to be the optimal condition to obtain stable nanohydrogels with size of 230 ± 12 nm, a PdI of 0.22 ± 0.02 and a ζ-potential of 30.0 ± 0.15 mV. Transmission electron microscopy (TEM) images showed that the application of chitosan coating in Lf-GMP did not affect the spherical shape of nanohydrogels and confirmed the low aggregation of nanohydrogels in solution. The analysis of chemical interactions between chitosan and Lf-GMP nanohydrogels were performed by Fourier transform infrared spectroscopy (FTIR) and by circular dichroism (CD) that revealed that a specific chemical interaction occurring between functional groups of protein-based nanohydrogels and active groups of the chitosan was established. The effect of chitosan coating on release mechanisms of Lf-GMP nanohydrogels at acid conditions (pH 2, 37 °C) was evaluated by the encapsulation of a model compound (caffeine) in these systems. Linear Superposition Model was used to fit the experimental data and revealed that Fick and relaxation mechanisms are involved in caffeine release. It was also observed that the Fick contribution increase with the application of chitosan coating. In vitro gastric digestion was performed with Lf-GMP nanohydrogels and Lf-GMP nanohydrogels with chitosan coating and it was observed that the presence of chitosan improve the stability of Lf and GMP (proteins were hydrolysed at a slower rate and were present in solution by longer time). Native electrophoreses revealed that the nanohydrogels without coating remained intact in solution until 15 min and with chitosan coating remained intact until 60 min, during gastric digestion.

Force field analysis suggests a lowering of diffusion barriers in atomic manipulation due to presence of STM tip.

We study the physics of atomic manipulation of CO on a Cu(111) surface by combined scanning tunneling microscopy and atomic force microscopy at liquid helium temperatures. In atomic manipulation, an adsorbed atom or molecule is arranged on the surface using the interaction of the adsorbate with substrate and tip. While previous experiments are consistent with a linear superposition model of tip and substrate forces, we find that the force threshold depends on the force field of the tip. Here, we use carbon monoxide front atom identification (COFI) to characterize the tip's force field. Tips that show COFI profiles with an attractive center can manipulate CO in any direction while tips with a repulsive center can only manipulate in certain directions. The force thresholds are independent of bias voltage in a range from 1 to 10mV and independent of temperature in a range of 4.5 to 7.5K.

Issues involved in the quantitative 3D imaging of proton doses using optical CT and chemical dosimeters

Dosimetry of proton beams using 3D imaging of chemical dosimeters is complicated by a variation with proton linear energy transfer (LET) of the dose–response (the so-called ‘quenching effect’). Simple theoretical arguments lead to the conclusion that the total absorbed dose from multiple irradiations with different LETs cannot be uniquely determined from post-irradiation imaging measurements on the dosimeter. Thus, a direct inversion of the imaging data is not possible and the proposition is made to use a forward model based on appropriate output from a planning system to predict the 3D response of the dosimeter.In addition to the quenching effect, it is well known that chemical dosimeters have a non-linear response at high doses. To the best of our knowledge it has not yet been determined how this phenomenon is affected by LET. The implications for dosimetry of a number of potential scenarios are examined.Dosimeter response as a function of depth (and hence LET) was measured for four samples of the radiochromic plastic PRESAGE®, using an optical computed tomography readout and entrance doses of 2.0 Gy, 4.0 Gy, 7.8 Gy and 14.7 Gy, respectively. The dosimeter response was separated into two components, a single-exponential low-LET response and a LET-dependent quenching. For the particular formulation of PRESAGE® used, deviations from linearity of the dosimeter response became significant for doses above approximately 16 Gy.In a second experiment, three samples were each irradiated with two separate beams of 4 Gy in various different configurations. On the basis of the previous characterizations, two different models were tested for the calculation of the combined quenching effect from two contributions with different LETs. It was concluded that a linear superposition model with separate calculation of the quenching for each irradiation did not match the measured result where two beams overlapped. A second model, which used the concept of an ‘effective dose’ matched the experimental results more closely. An attempt was made to measure directly the quench function for two proton beams as a function of all four variables of interest (two physical doses and two LET values). However, this approach was not successful because of limitations in the response of the scanner.

Implementation of a multisource model for gold nanoparticle‐mediated plasmonic heating with near‐infrared laser by the finite element method

The use of optically tunable gold nanoparticles (GNPs) in conjunction with near-infrared (NIR) laser has emerged as an attractive option for laser-induced thermal therapy (LITT), as it capitalizes on plasmonic heating of GNPs tuned to absorb light strongly in the NIR region. Previously, the authors developed a multisource model to predict the temperature change in a GNP-laden tissue-like medium illuminated by NIR laser and implemented it by a linear superposition (LS) method combining analytic and finite element method (FEM) solutions. While it is intuitive and straightforward, the LS approach might be somewhat cumbersome to implement for realistic LITT cases because it requires separate calculations of the temperature change due to individual GNP heat sources and the laser heat source. Therefore, the current investigation aimed to develop a simpler yet mathematically more elegant and computationally more efficient method solely based on FEM to implement the authors' multisource model. A multisource FEM model was developed to calculate the full spatiotemporal temperature distribution due to all heat sources (i.e., individual GNPs and the laser heat source) by solving the heat diffusion equation with multiple heat sources using FEM. This model was tested for its validity using two computational phantoms, a two-layer GNP-laden cylindrical phantom and a breast phantom with a GNP-laden microcavity. For comparison, the results for the two phantom cases were also obtained from the LS method. For the two-layer phantom case, the FEM approach resulted in a maximum temperature increase of 16.4 °C at a depth of 1.35 cm, 2.5 mm below the interface between the two layers, while the LS method produced a maximum temperature increase of 16.7 °C at a depth of 1.3 cm, 2 mm below the interface between the two layers. A comparison of the depth versus temperature changes obtained from the two approaches showed reasonably good agreement within 6%. In the breast phantom case, the LS results show a maximum temperature increase of 16.35 °C at a depth of 2.17 cm, 0.3 mm away from the center of the cavity in the direction closer to the laser. The FEM results show the same characteristics as those obtained via the LS method with a maximum temperature increase of 16.2 °C at a depth of 2.16 cm, 0.4 mm away from the center of the cavity in the direction closer to the laser. The two methods produced good agreement within 2% for the depth versus temperature distributions. The current multisource FEM model not only reproduced the results from the previous LS model, but also dramatically reduced computation time by 2 orders of magnitude, despite a generally more stringent requirement for computer memory. With further experimental validation, the FEM model can be used to predict the distinct plasmonic heating characteristics expected from NIR laser illumination of tissue-like media filled with GNPs, while offering the capability of handling heterogeneous spatial distribution of GNPs for realistic clinical cases.

A value-consistent dimensionality reduction model for electronic tongue data

High-dimensional data are always a great challenge for post-processing. This paper proposed a new computational model for dimensionality reduction toward the huge data sampled from the multi-sensor array in voltammetric electronic tongue. It employs a linear superposition model of noise for a set of basis functions to describe the serial current responses of cross-sensitive multi-sensor array. And the coefficients of the basis function set, with a much lower dimensionality, are used as the reduced feature data for a sample. More importantly, the values of those coefficients show high consistency with the responses of electrodes, namely, larger currents measured may result in greater coefficient values, and vice versa.According to the theoretical analysis and practical results of the experiments, besides the value-consistency which is never supported by existing approaches, the proposed model also performs very well in the three key factors for evaluating an approach to dimensionality reduction (i.e. reduction rate, reconstruction error, and complexity): (1) strong ability in dimensionality reduction and feature preservation—the reduction rate reaches as high as circa 280–420, and the average reconstruction error is circa 1–5%; (2) linear time complexity—it is applicable to most huge datasets.

Near-Neutral pH Stress Corrosion Cracking Susceptibility of Plastically Prestrained X70 Steel Weldment

The application of strain-based design for pipelines requires comprehensive understanding of the postyield mechanical behavior of materials. In this article, the impact of plastic prestrain on near-neutral pH stress corrosion cracking (SCC) susceptibility of welded X70 steel was investigated with a slow strain rate tensile (SSRT) test. Generally, plastic prestrain reduces the SCC resistance in various welded zones. The SCC susceptibility of the test materials can be put in the following order: heat-affected zone (HAZ) > weld metal (WM) > base metal (BM). Fractographic analysis indicates that there are two cracking modes, mode I and mode II, during SSRT tests. Mode I cracks propagate along the direction perpendicular to the maximum tensile stress, and mode II cracks lie in planes roughly parallel to the plane where the maximum shear exists. The SCC of the BM is governed by mode I cracking and fracture of the HAZ, and the WM is dominated by mode II cracking. Damage analysis shows that the detrimental impact of plastic prestrain on the residual SCC resistance cannot be evaluated with the linear superposition model. A plastic prestrain sensitivity, a material constant independent of plastic prestrain, is proposed to characterize the susceptibility of SCC resistance to plastic prestrain, and it increases with the SCC susceptibility of the steels. The enhanced SCC susceptibility caused by plastic prestrain may be related to an increase in yield strength. The correlation of the ratio of the reduction in area in NS4 solution to that in air (RASCC/RAair) with the yield strength is microstructure dependent.