Elastic Maps Research Articles

Measurement of gas and liquid flow rates in two-phase pipe flows by the application of machine learning techniques to differential pressure signals

A new method for the determination of gas and liquid flow rates in vertical upward gas–liquid pipe flows has been proposed. This method consists of an application of machine learning techniques on the probability density function (PDF) and the power spectral density (PSD) of the normalized output of a differential pressure transducer connected to two axially separated wall pressure taps in the pipe. The two-phase flow regime was first identified by the application of the elastic maps method on the differential pressure PDF. The transducer signal was then pre-processed using Principal Component Analysis, and independent features were extracted using Independent Component Analysis. The extracted features were used as inputs to multi-layer back-propagation neural networks, which gave the phase flow rates as output. The present method was used to calibrate a differential pressure sensor to estimate the flow rates of both phases in air–water flow in a vertical pipe of diameter 32.5mm and in the pressure range from 100 to 140kPa. Predictions of the present method were in good agreement with direct flow rate measurements. Compared to previously used methods of feature extraction from differential pressure signals, the present method was the only one to have a good, consistent performance over all flow regimes and for all flow conditions encountered in this study.

Ultrasound to Assess Bone Quality

Bone quality is determined by a variety of compositional, micro- and ultrastructural properties of the mineralized tissue matrix. In contrast to X-ray-based methods, the interaction of acoustic waves with bone tissue carries information about elastic and structural properties of the tissue. Quantitative ultrasound (QUS) methods represent powerful alternatives to ionizing x-ray based assessment of fracture risk. New in vivo applicable methods permit measurements of fracture-relevant properties, [eg, cortical thickness and stiffness at fragile anatomic regions (eg, the distal radius and the proximal femur)]. Experimentally, resonance ultrasound spectroscopy and acoustic microscopy can be used to assess the mesoscale stiffness tensor and elastic maps of the tissue matrix at microscale resolution, respectively. QUS methods, thus, currently represent the most promising approach for noninvasive assessment of components of fragility beyond bone mass and bone microstructure providing prospects for improved assessment of fracture risk.

Is it possible to predict long-term success with k-NN? Case study of four market indices (FTSE100, DAX, HANGSENG, NASDAQ)

This case study tests the possibility of prediction for 'success' (or 'winner') components of four stock & shares market indices in a time period of three years from 02-Jul-2009 to 29-Jun-2012.We compare their performance ain two time frames: initial frame three months at the beginning (02/06/2009-30/09/2009) and the final three month frame (02/04/2012-29/06/2012).To label the components, average price ratio between two time frames in descending order is computed. The average price ratio is defined as the ratio between the mean prices of the beginning and final time period. The 'winner' components are referred to the top one third of total components in the same order as average price ratio it means the mean price of final time period is relatively higher than the beginning time period. The 'loser' components are referred to the last one third of total components in the same order as they have higher mean prices of beginning time period. We analyse, is there any information about the winner-looser separation in the initial fragments of the daily closing prices log-returns time series.The Leave-One-Out Cross-Validation with k-NN algorithm is applied on the daily log-return of components using a distance and proximity in the experiment. By looking at the error analysis, it shows that for HANGSENG and DAX index, there are clear signs of possibility to evaluate the probability of long-term success. The correlation distance matrix histograms and 2-D/3-D elastic maps generated from ViDaExpert show that the 'winner' components are closer to each other and 'winner'/'loser' components are separable on elastic maps for HANGSENG and DAX index while for the negative possibility indices, there is no sign of separation.

Identification of flow regime in vertical upward air–water pipe flow using differential pressure signals and elastic maps

A new method for the identification of flow regime in vertical upward gas–liquid flows has been proposed. It consists of an application of the elastic maps algorithm, which is a machine learning method, to the probability density function of differential pressure measurements in pipes. The proposed method was found to be insensitive to axial location of the measurements, pipe diameter within the range 13.9–49.2mm and absolute pressure within the range 100–240kPa; it is therefore amenable to relatively simple calibration in a calibration rig. Compared to three previously suggested machine learning algorithms, the present one had a superior performance in identifying the gas–liquid flow regime.

Ultrafine Structure of Human Aortic Valve Calcific Deposits

Objective: To elucidate the mechanism of formation of calcific deposits inside the human natural heart valve based on their ultra-fine structure on nanometer scale observed by atomic force microscope. Methods: Cross-sections of an aortic valve calcification were observed by scanning electron microscope. Thin slices several micrometeres thick from the same deposit were observed by atomic force microscopy in the Peak Force Imagining mode providing topographic, adhesion and quantitative nanoscale elastic modulus maps of the surface. Results: Most of the aortic valve calcification was composed of large blocks of mostly compact matter, porous on the microscopic scale. The mineral blocks consisted mainly of closely arranged elongated needle- and plate-like crystals, 30 to 70 nm in diameter, and irregularly disseminated areas of soft organic material. Conclusions: Crystals forming mineral blocks of mostly compact matter are nucleated on organic substrates, with their growth controlled by the diffusion of building units through the virtually stagnant layer of interstitial fluid wetting the deposit surface. Preferentially formed precursors of hydroxyapatite, dicalcium, octacalcium and/or amorphous calcium phosphate, are in later stages of deposit development transformed into biological hydroxyapatite.

Monitoring of Cornea Elastic Properties Changes during UV-A/Riboflavin-Induced Corneal Collagen Cross-Linking using Supersonic Shear Wave Imaging: A Pilot Study

Keratoconus disease or post-LASIK corneal ectasia are increasingly treated using UV-A/riboflavin-induced corneal collagen cross-linking (CXL). However, this treatment suffers from a lack of techniques to provide an assessment in real-time of the CXL effects. Here, we investigated the potential interest of corneal elasticity as a biomarker of the efficacy of this treatment. For this purpose, supersonic shear wave imaging (SSI) was performed both ex vivo and in vivo on porcine eyes before and after CXL. Based on ultrasonic scanners providing ultrafast frame rates (~30 kHz), the SSI technique generates and tracks the propagation of shear waves in tissues. It provides two- and three-dimensional (2-D and 3-D) quantitative maps of the corneal elasticity. After CXL, quantitative maps of corneal stiffness clearly depicted the cross-linked area with a typical 200-μm lateral resolution. The CXL resulted in a 56% ± 15% increase of the shear wave speed for corneas treated in vivo (n = 4). The in vivo CXL experiments performed on pigs demonstrated that the quantitative estimation of local stiffness and the 2-D elastic maps of the corneal surface provide an efficient way to monitor the local efficacy of corneal cross-linking.

Nanoscale Strain-Hardening of Keratin Fibres

Mammalian appendages such as hair, quill and wool have a unique structure composed of a cuticle, a cortex and a medulla. The cortex, responsible for the mechanical properties of the fibers, is an assemblage of spindle-shaped keratinized cells bound together by a lipid/protein sandwich called the cell membrane complex. Each cell is itself an assembly of macrofibrils around 300 nm in diameter that are paracrystalline arrays of keratin intermediate filaments embedded in a sulfur-rich protein matrix. Each macrofibril is also attached to its neighbors by a cell membrane complex. In this study, we combined atomic force microscopy based nano-indentation with peak-force imaging to study the nanomechanical properties of macrofibrils perpendicular to their axis. For indentation depths in the 200 to 500 nm range we observed a decrease of the dynamic elastic modulus at 1 Hz with increasing depth. This yielded an estimate of 1.6GPa for the lateral modulus at 1 Hz of porcupine quill’s macrofibrils. Using the same data we also estimated the dynamic elastic modulus at 1 Hz of the cell membrane complex surrounding each macrofibril, i.e., 13GPa. A similar estimate was obtained independently through elastic maps of the macrofibrils surface obtained in peak-force mode at 1 kHz. Furthermore, the macrofibrillar texture of the cortical cells was clearly identified on the elasticity maps, with the boundaries between macrofibrils being 40–50% stiffer than the macrofibrils themselves. Elasticity maps after indentation also revealed a local increase in dynamic elastic modulus over time indicative of a relaxation induced strain hardening that could be explained in term of a α-helix to β-sheet transition within the macrofibrils.

Ultrafine Structure of the Hydroxyapatite Amorphous Phase in Noninfectious Phosphate Renal Calculi

We aimed to establish detailed morphology of the structureless amorphous hydroxyapatite (HAP) phase to improve our understanding of the formation mechanism of these concretions. Noninfectious phosphate renal calculi composed mainly of HAP consist of inorganic material in the form of spherules, in a seemingly structureless and amorphous phase and organic matter. Several cross-sections of a fraction of phosphate renal stone composed solely of the amorphous HAP phase were examined with atomic force microscope. Both 2- and 3-dimensional images of their structure and nanoscale elastic modulus maps were obtained. The amorphous hap phase consists of 2 distinctly different morphologic forms of hydroxyapatite: separate and/or intergrown columnar crystals, and spherical agglomerates with diameters in the range 150-300 nm consisting of spherulites approximately 10 nm in diameter. The columnar crystals are irregularly disseminated in the stone interior, which is porous because of cavities with depths in excess of 100 nm. Organic matter is almost evenly distributed throughout the stone interior. Based on the observed calculus structure, the following mechanism of formation of the noninfectious phosphate calculi is suggested: Spherulites formed via the perikinetic aggregation of Posner's clusters present in urine supersaturated with respect to hydroxyapatite aggregate into spherical agglomerates that, after reaching a certain size, are retained in cavities with poor urodynamics, gradually settle, and become incorporated into developing concretion. The columnar crystals are probably nucleated on the detritus of organic origin embedded in the hydroxyapatite structureless phase.

Global strength and elastic thickness of the lithosphere

The strength and effective elastic thickness (Te) of the lithosphere control its response to tectonic and surface processes. Here, we present the first global strength and effective elastic thickness maps, which are determined using physical properties from recent crustal and lithospheric models. Pronounced strength contrasts exist between old cratons and areas affected by Tertiary volcanism, which mostly coincide with the boundaries of seimogenic zones. Lithospheric strength is primarily controlled by the crust in young (Phanerozoic) geological provinces characterized by low Te (~25km), high topography (>1000m) and active seismicity. In contrast, the old (Achaean and Proterozoic) cratons of the continental plates show strength primarily in the lithospheric mantle, high Te (over 100km), low topography (<1000m) and very low seismicity.

Direct monitoring of opto-mechanical switching of self-assembled monolayer films containing the azobenzene group

The potential for manipulation and control inherent in molecule-based motors holds great scientific and technological promise. Molecules containing the azobenzene group have been heavily studied in this context. While the effects of the cis–trans isomerization of the azo group in such molecules have been examined macroscopically by a number of techniques, modulations of the elastic modulus upon isomerization in self-assembled films were not yet measured directly. Here, we examine the mechanical response upon optical switching of bis[(1,1'-biphenyl)-4-yl]diazene organized in a self-assembled film on Au islands, using atomic force microscopy. Analysis of higher harmonics by means of a torsional harmonic cantilever allowed real-time extraction of mechanical data. Quantitative analysis of elastic modulus maps obtained simultaneously with topographic images show that the modulus of the cis-form is approximately twice that of the trans-isomer. Quantum mechanical and molecular dynamics studies show good agreement with this experimental result, and indicate that the stiffer response in the cis-form comprises contributions both from the individual molecular bonds and from intermolecular interactions in the film. These results demonstrate the power and insights gained from cutting-edge AFM technologies, and advanced computational methods.

Magnetic Head Protrusion Profiles and Wear Pattern of Thermal Flying-Height Control Sliders With Different Heater Designs

Hard drives featuring sliders with thermal flying-height control (TFC) using thermal expansion of a heating element have been widely used in products for achieving lower magnetic spacing. This approach allows to actively compensate for static FH variations and achieves sub-1-nm clearance during read/write operation. However, the soft-error rate (SER) may not be minimized with an arbitrary heating element due to the nonuniform protrusion profile and the several micrometers of physical separation between reader and writer. Most published work mainly focused on actuation efficiency or reader spacing without detailed study of the relationship between balance of read/write spacing and the location of heating element. This paper uses an established numerical approach with head structure and pole-tip recession profile measured by scanning electron microscope and atomic force microscope to calculate the 3-D protrusion profiles, and to predict the head wear pattern created in TFC stress test, in which an excessive heating power is applied to the heating element so that part of the head is in contact with the spinning disk for a period of time. We also present novel experimental method for measuring wear pattern with angstrom-level resolution by Elastic Peak Maps. TFC sliders with three different heater elements are investigated numerically and experimentally. The numerical results compare well with the measurements in relative wear depths among various layers, and both show that the location and design of heating element have significant effect on the resulting FH profile as well as read and write magnetic spacings. As a result, one can reduce the SER by tailoring the heater design with the considerations of the magnetic requirement and reliability concerns.

Pattern recognition methods for thermal drift correction in Atomic Force Microscopy imaging

Atomic Force Microscopy (AFM) is a fundamental tool for the investigation of a wide range of mechanical properties on nanoscale due to the contact interaction between the AFM tip and the sample surface. The information recorded with AFM is stored and synthesized by imaging the sample properties to be studied. Distortions and unwanted effects in AFM images can be produced both due to instrumental sources or sample unknown bad responses. The focus of this paper is on an algorithm for distortion corrections for AFM recorded images due to the convolution of thermal drift and unknown polymer compliance. When a sequence of AFM images correspondent to the same polymeric area is acquired, it is common to observe the convolution of thermal drift with surface modifications due to the AFM tip stresses. The surface modifications are material properties and add knowledge to the response of the materials on nanoscale. As a consequence, a suitable de-convolution of the thermal drifts on the recorded images needs to be developed. Because soft polymeric samples can present unwanted height alteration due to the stressing AFM tip contact, we present a method that combines a thermal drifts correcting tool (where the original images are modified using a suitable mapping function) with a height rescaling method. In turn, an image matching method based on a Tikhonov functional is developed between topography data and the surface elastic maps, respectively. The precision achieved and the fast computation time required make our methods particularly useful for image analysis on soft polymeric samples as well as in a wide range of other scanning probe microscopy applications.

Quantitative mapping of surface elastic moduli in silica-reinforced rubbers and rubber blends across the length scales by AFM

The surface elastic moduli of silica-reinforced rubbers and rubber blends were investigated by atomic force microscopy (AFM)-based HarmoniX material mapping. Styrene–butadiene rubbers (SBR) and ethylene–propylene–diene rubbers (EPDM) and SBR/EPDM rubber blends with varying concentrations of silica nanoparticles (0, 5, 10, 20, 50 parts per hundred rubber, phr) were prepared to investigate the effect of different composition on the resulting morphology, filler distribution and elastic moduli of a specific rubber or rubber blend sample. For SBR, the elastic modulus values varied from 0.5 MPa for unfilled SBR to 5 MPa for 50 phr reinforced SBR with the increase in the concentration of filler. For EPDM, the corresponding values increased from 1.4 MPa for unfilled EPDM to 4.5 MPa for 50 phr reinforced EPDM. Local stiff and soft domains in silica-reinforced SBR and EPDM rubbers and rubber blends were identified by HarmoniX AFM imaging. While the stiff silica particles show modulus values as high as 2 GPa, the rubber matrix reveals modulus values in the range of ca. 30 MPa for the rubber blends to ca. 300 MPa for the unfilled rubbers. The lower value of elastic modulus of the EPDM phase in the blend, compared to the blank EPDM compound can be attributed to the presence of Sunpar oil in the compound which has a very good affinity with EPDM and decreases the rubber modulus. The elastic moduli maps revealed an increase of the areal fraction of silica particles showing an intrinsic surface modulus value with rising silica content in the compound preparation mixture. HarmoniX AFM measurements revealed the formation of larger silica aggregates in EPDM in contrast to SBR where isolated silica particles were observed. For silica-reinforced rubber blends a phase separation into a soft (ca. 40 MPa) and a significantly harder phase could be observed (ca. 500 MPa–1.5 GPa) indicating the incorporation of silica particles in the SBR phase. Using HarmoniX AFM imaging significantly higher surface elastic moduli were observed compared to those obtained by bulk tensile testing. Possible reasons for the observed differences between bulk modulus values and those measured by AFM are discussed in detail, including the aspect of different averaging procedures like inherent to surface probing by AFM versus bulk tensile testing, different filler distributions in SBR and EPDM and the AFM modulus calibration procedures.

Elastic property maps of austenitic stainless steels.

The most recent advances in theory and methodology are directed towards obtaining a quantitative description of the electronic structure and physical properties of alloy steels. Specifically, we employ ab initio alloy theories to map the elastic properties of austenitic stainless steels as a function of chemical composition. The so generated data can be used in the search for new steel grades, and, as an example, we predict two basic compositions with outstanding properties among the austenitic stainless steels.