Fracture modelling of DP780 sheets using a hybrid experimental-numerical method and two-dimensional digital image correlation

This paper is concerned with the construction of fracture envelopes of DP780 sheets using two methods: a hybrid experimental-numerical method; two-dimensional digital image correlation (2D-DIC). For the hybrid method, four types of ductile fracture tests were carried out covering a wide range of stress states on specimens: with a central hole; two symmetric circular notches; flat grooved; and diagonally double-notched. Based on the fracture strain and loading paths identified with finite element simulation, a fracture envelope was obtained by employing the three-parameter modified Mohr-Coulomb fracture model. In addition, the fracture surface strain was directly measured using 2D-DIC. Loading histories of each test were extracted from a surface element of a three dimensional finite element model. The comparison of fracture envelopes constructed by the two methods reveals that there is little difference. Thus, it can be concluded that 2D-DIC is applicable to fracture modelling of DP780 sheets despite the assumption of the plane stress condition even after necking

Ridge regression for two dimensional locality preserving projection

Two Dimensional Locality Preserving Projection (2D-LPP) is a recent extension of LPP, a popular face recognition algorithm. It has been shown that 2D-LPP performs better than PCA, 2D-PCA and LPP. However, the computational cost of 2D-LPP is high. This paper proposes a novel algorithm called Ridge Regression for Two Dimensional Locality Preserving Projection (RR- 2DLPP), which is an extension of 2D-LPP with the use of ridge regression. RR-2DLPP is comparable to 2DLPP in performance whilst having a lower computational cost. The experimental results on three benchmark face data sets - the ORL, Yale and FERET databases - demonstrate the effectiveness and efficiency of RR-2DLPP compared with other face recognition algorithms such as PCA, LPP, SR, 2D-PCA and 2D-LPP.

Random Subspace Two-Dimensional PCA for face recognition

The two-dimensional Principal Component Analysis (2DPCA) is a robust method in face recognition. Much recent research shows that the 2DPCA is more reliable than the well-known PCA method in recognising human face. However, in many cases, this method tends to be overfitted to sample data. In this paper, we proposed a novel method named random subspace two-dimensional PCA (RS-2DPCA), which combines the 2DPCA method with the random subspace (RS) technique. The RS-2DPCA inherits the advantages of both the 2DPCA and RS technique, thus it can avoid the overfitting problem and achieve high recognition accuracy. Experimental results in three benchmark face data sets -the ORL database, the Yale face database and the extended Yale face database B - confirm our hypothesis that the RS-2DPCA is superior to the 2DPCA itself.

DryLab® optimised two-dimensional high performance liquid chromatography for differentiation of ephedrine and pseudoephedrine based methamphetamine samples

In-silico optimised two-dimensional high performance liquid chromatographic (2D-HPLC) separations of a model methamphetamine seizure sample are described, where an excellent match between simulated and real separations was observed. Targeted separation of model compounds was completed with significantly reduced method development time. This separation was completed in the heart-cutting mode of 2D-HPLC where C18 columns were used in both dimensions taking advantage of the selectivity difference of methanol and acetonitrile as the mobile phases. This method development protocol is most significant when optimising the separation of chemically similar chemical compounds as it eliminates potentially hours of trial and error injections to identify the optimised experimental conditions. After only four screening injections the gradient profile for both 2D-HPLC dimensions could be optimised via simulations, ensuring the baseline resolution of diastereomers (ephedrine and pseudoephedrine) in 9.7 min. Depending on which diastereomer is present the potential synthetic pathway can be categorized.

Protocols for finding the most orthogonal dimensions for two-dimensional high performance liquid chromatography

The selection of two high performance liquid chromatography (HPLC) columns with vastly different retention mechanisms is vital for performing effective two-dimensional (2D-) HPLC. This paper reports on a systematic method to select a pair of HPLC columns that provide the most different separations for a given sample. This was completed with the aid of a HPLC simulator that predicted retention profiles on the basis of real experimental data, which is difficult when the contents of sample matrices are largely-or completely-unknown. Peaks from the same compounds must first be matched between chromatograms to compare the retention profiles and optimised 2D-HPLC column selection. In this work, two methods of matching peaks between chromatograms were explored and an optimal pair of chromatography columns was selected for 2D-HPLC. First, a series of 17 antioxidants were selected as an analogue for a coffee extract. The predicted orthogonality of the standards was 39%, according to the fractional surface coverage 'bins' method, which was close to the actual space utilisation of the standard mixture, 44%. Moreover, the orthogonality for the 2D-HPLC of coffee matched the predicted value of 38%. The second method employed a complex sample matrix of urine to optimise the column selections. Seven peaks were confidently matched between chromatograms by comparing relative peak areas of two detection strategies: UV absorbance and potassium permanganate chemiluminescence. It was found that the optimal combinations had an orthogonality of 35% while the actual value was closer to 30%.

Stationary phase characterisation and method development for fast two-dimensional HPLC

Fundamental improvements to the experimental protocol of two-dimensional high performance liquid chromatography were developed to accomplish truly quantitative analyses of complex natural products. This included developing novel measurement techniques to elucidate the retention behaviour of monolithic columns. Approaches to streamline chromatographic method development were also explored.

In-silico optimisation of two-dimensional high performance liquid chromatography for the determination of Australian methamphetamine seizure samples

In-silico optimisation of a two-dimensional high performance liquid chromatography (2D-HPLC) separation protocol has been developed for the interogation of methamphetamine samples including model, real world seizure, and laboratory synthesised samples. The protocol used Drylab® software to rapidly identify the optimum separation conditions from a library of chromatography columns. The optimum separation space was provided by the Phenomonex Kinetex PFP column (first dimension) and an Agilent Poroshell 120 EC-C18 column (second dimension). To facilitate a rapid 2D-HPLC analysis the particle packed C18 column was replaced with a Phenomenex Onyx Monolithic C18 withought sacrificing separation performance. The Drylab® optimised and experimental separations matched very closely, highlighting the robust nature of HPLC simulations. The chemical information gained from an intermediate methamphetamine sample was significant and complimented that generated from a pure seizure sample. The influence of the two-dimensional separation on the analytical figures of merit was also investigated. The limits of detection for key analytes in the second dimension determined for methamphetamine (4.59 × 10-⁴ M), pseudoephedrine (4.03 × 10-4 M), caffeine (5.16 × 10-⁴ M), aspirin (9.32 × 10-4 M), paracetamol (5.93 × 10-4 M) and procaine (2.02 × 10-3 M).

Objective classification of fabric pilling based on the two-dimensional discrete wavelet transform

A number of methods for automated objective ratings of fabric pilling based on image analysis are described in the literature. The periodic structure of fabrics makes them suitable candidates for frequency domain analysis. We propose a new method of frequency domain analysis based on the two-dimensional discrete wavelet transform to objectively measure pilling intensity in sample images. We present a preliminary evaluation of the proposed method based on analysis of two series of standard pilling evaluation test images. The initial results suggest that the proposed method is feasible, and that the ability of the method to discriminate between levels of pilling intensity depends on the wavelet analysis scale being closely matched to the fabric interyarn pitch. We also present a heuristic method for optimal selection of an analysis wavelet and associated analysis scale.

Evaluating the robustness of objective pilling classification with the two-dimensional discrete wavelet transform

Previously, we proposed a new method of frequency domain analysis based on the two-dimensional discrete wavelet transform to objectively measure pilling intensity in sample fabric images. We have further evaluated this method, and our results indicate that it is robust to small horizontal and/or vertical translations and to significant variations in the brightness of the image under analysis, and is sensitive to rotation and to dilation of the image. These results suggest that as long as precautions are taken to ensure fabric test samples are imaged under consistent conditions of weave/knit pattern alignment (rotation) and apparent interyarn pitch (dilation), the method will yield repeatable results.

Objective assessment of pilling of nonwoven fabrics using the two dimensional discrete wavelet transform

Fabric pilling is a serious problem for the apparel industry, causing an unsightly appearance and premature wear. Woolen products are particularly prone to pilling. Recently, a process for production of woolen nonwoven apparel fabrics has been commercialized in Australia, and may lead to new markets for Australian wool. However, the success of such nonwoven fabrics will partly rely on their propensity to pill. A key element in the control of fabric pilling is the evaluation of resistance to pilling by testing. Resistance to pilling is normally tested in the laboratory by processes that simulate accelerated wear, followed by a manual assessment of the degree of pilling by an expert based on a visual comparison of the sample to a set of test images. To bring more objectivity into the pilling rating process, a number of automated systems based on image analysis have been developed. The authors previously proposed a new method of image analysis based on the two-dimensional discrete wavelet transform to objectively measure the pilling intensity for woven fabrics. This paper presents preliminary work in extending this method to nonwoven fabrics.

Compositional dynamics of a commercial wine fermentation using two-dimensional FTIR correlation analysis

We have demonstrated that compositional changes occurring during a commercial red wine fermentation can be effectively monitored using FTIR spectroscopy and modelled with the aid of two-dimensional correlation techniques. This study represents a novel application of two-dimensional spectroscopy and showed that the reaction rates for the conversion of fructose and glucose to alcohol were different, with the latter being more rapid. The use of a simple three-component model serves to aid interpretation of the data and the results obtained confirm the value of two-dimensional FTIR correlation spectroscopy as a chemometric tool which has considerable potential for process monitoring.

The assessment of тт-тт selective stationary phases for two-dimensional HPLC analysis of foods : application to the analysis of coffee

Differences between alkyl, dipole–dipole, hydrogen bonding, and π-π selective surfaces represented by non-resonance and resonance π-stationary phases have been assessed for the separation of ‘Ristretto’ café espresso by employing 2DHPLC techniques with C18 phase selectivity detection. Geometric approach to factor analysis (GAFA) was used to measure the detected peaks (N), spreading angle (β), correlation, practical peak capacity (n_p) and percentage usage of the separations space, as an assessment of selectivity differences between regional quadrants of the two-dimensional separation plane. Although all tested systems were correlated to some degree to the C18 dimension, regional measurement of separation divergence revealed that performance of specific systems was better for certain sample components. The results illustrate that because of the complexity of the ‘real’ sample obtaining a truly orthogonal two-dimensional system for complex samples of natural origin may be practically impossible.

The analysis of café espresso using two-dimensional reversed phase–reversed phase high performance liquid chromatography with UV-absorbance and chemiluminescence detection

In this study, an activity based screening technique combining two-dimensional liquid chromatography (2DHPLC) with UV-absorbance and chemiluminescence detection was applied to study “Ristretto”, "Decaffeinatto” and “Volluto” espresso coffees. This technique, which coupled the separation power of 2DHPLC with the sensitivity and selectivity of the chemiluminescence detection, offers great potential for screening complex samples for antioxidant compounds. Detailed information regarding the complexity of the sample, and the variation between these three coffees could be obtained using this multidimensional-hyphenated method of analysis.

Peak modeling approach to accurate assignment of first-dimension retention times in comprehensive two-dimensional chromatography

Modeling of first-dimension retention of peaks based on modulation phase and period allows reliable prediction of the modulated peak distributions generated in the comprehensive two-dimensional chromatography experiment. By application of the inverse process, it is also possible to use the profile of the modulated peaks (their heights or areas) to predict the shape and parameters of the original input chromatographic band (retention time, standard deviation, area) for the primary column dimension. This allows an accurate derivation of the firstdimension retention time (RSD 0.02%) which is equal to that for the non-modulated experiment, rather than relying upon the retention time of the major modulated peak generated by the modulation process (RSD 0.16%). The latter metric can produce a retention time that differs by at least the modulation period employed in the experiment, which displays a discontinuity in the retention time vs modulation phase plot at the point of the 180° out-ofphase modulation. In contrast, the new procedure proposed here gives a result that is essentially independent of modulation phase and period. This permits an accurate value to be assigned to the first-dimension retention. The proposed metric accounts for the time on the seconddimension, the phase of the distribution, and the holdup time that the sampled solute is retained in the modulating interface. The approach may also be based on the largest three modulated peaks, rather than all modulated peaks. This simplifies the task of assigning the retention time with little loss of precision in band standard deviation or retention time, provided that these peaks are not all overloaded in the first or second dimension.