Fast Measurement Technique Research Articles

Propagation behavior of wetting front and its fluctuation characteristics during subcooled jet impingement quenching

Jet impingement quenching as one of the most effective cooling methods is widely applied in many industrial fields. When a subcooled jet strikes the hot surface, the wetting front propagates outside after the wetting delay accompanied by high-frequency fluctuations. To elucidate the propagation behavior of the wetting front and its fluctuation characteristics, the quenching experiments that an upward water jet with different velocities and subcoolings impacted onto a hot nickel block with an initial temperature of 280°C were conducted. The transient transition boiling associated with the intermittent wet and dry situations around the wetting front was quantitatively analyzed based on the visual observation and fast response surface temperature measurement technique. The liquid-solid contact period near the wetting front, under the late transition boiling regime, spans the range of 494–590 µs. This time interval is comparable to the period of disturbance waves induced by the Plateau-Rayleigh instability of the jet. Furthermore, fluctuation amplitude of the wetting front diminishes from 0.8 to 0.2 mm as it propagates. The order of magnitude and the trend of variation in the fluctuation amplitude with respect to the wetting front radius align with theoretical calculations without considering boiling heat transfer effects.

Measuring the polarized complex forward-scattering amplitudes of single particles in unbounded fluid flow: CAS-v2 protocol.

A detailed protocol for measuring the complex forward-scattering amplitude S(0°) of single particles, the Complex Amplitude Sensing version 1 (CAS-v1), has recently been developed and used for characterizing environmental particles. However, interpretations of the S(0°) data need a priori assumptions on the particle's shape, and applications of the method have mostly been limited to the particles suspended in liquids. Here, we thoroughly upgrade the CAS technique to perform quality-controlled S(0°) measurements at two independent polarizations for particles suspended in gases and liquids. The polarization-resolved S(0°) sensing constrains the particle's shape and improves the physical interpretability of data. An optical coherence backscattering detection technique enables non-invasive yet precise constraints of the particle's location in the sensing region, realizing precise S(0°) measurements even for aerosol particles introduced via a gas jet without using a flow microchannel. The CAS-v2 protocol proposed here will be useful as a fast yet detailed particle measurement technique for laboratory and field studies.

Identification of graphite with perfect rhombohedral stacking by electronic Raman scattering

Rhombohedral graphite (RG) shows strong correlations in its topological flat band and is pivotal for exploring emergent, correlated electronic phenomena. One key advantage is the enhancement of electronic interactions with the increase in the number of rhombohedrally stacked graphene layers. Increasing thickness also leads to an exponential increase in the number of stacking configurations, necessitating a precise method to identify flawless rhombohedral stackings. Overcoming this challenge is difficult because the established technique for stacking sequence identification, based on phonon originated Raman processes (e.g. the 2D peak), fails in thick RG samples. We demonstrate that the strong layer dependence of the band structure can be harnessed to identify RG without stacking faults. For thicknesses ranging from 3 to 12 layers, we show that each perfect RG structure presents distinctive peak positions in electronic Raman scattering (ERS), directly fingerprinting the flawless stacking. This measurement can be carried out using a conventional confocal Raman spectrometer at room temperature, using visible excitation wavelengths. Consequently, this overcomes the identification challenge by providing a simple and fast optical measurement technique, thereby helping to establish RG as a platform for studying strong correlations in one of the simplest crystals possible.

Model-based iterative reconstruction for direct imaging with point spread function encoded echo planar MRI

BackgroundEcho planar imaging (EPI) is a fast measurement technique commonly used in magnetic resonance imaging (MRI), but is highly sensitive to measurement non-idealities in reconstruction. Point spread function (PSF)-encoded EPI is a multi-shot strategy which alleviates distortion, but acquisition of encodings suitable for direct distortion-free imaging prolongs scan time. In this work, a model-based iterative reconstruction (MBIR) framework is introduced for direct imaging with PSF-EPI to improve image quality and acceleration potential. MethodsAn MBIR platform was developed for accelerated PSF-EPI. The reconstruction utilizes a subspace representation, is regularized to promote local low-rankedness (LLR), and uses variable splitting for efficient iteration. Comparisons were made against standard reconstructions from prospectively accelerated PSF-EPI data and with retrospective subsampling. Exploring aggressive partial Fourier acceleration of the PSF-encoding dimension, additional comparisons were made against an extension of Homodyne to direct PSF-EPI in numerical experiments. A neuroradiologists' assessment was completed comparing images reconstructed with MBIR from retrospectively truncated data directly against images obtained with standard reconstructions from non-truncated datasets. ResultsImage quality results were consistently superior for MBIR relative to standard and Homodyne reconstructions. As the MBIR signal model and reconstruction allow for arbitrary sampling of the PSF space, random sampling of the PSF-encoding dimension was also demonstrated, with quantitative assessments indicating best performance achieved through nonuniform PSF sampling combined with partial Fourier. With retrospective subsampling, MBIR reconstructs high-quality images from sub-minute scan datasets. MBIR was shown to be superior in a neuroradiologists' assessment with respect to three of five performance criteria, with equivalence for the remaining two. ConclusionsA novel image reconstruction framework is introduced for direct imaging with PSF-EPI, enabling arbitrary PSF space sampling and reconstruction of diagnostic-quality images from highly accelerated PSF-encoded EPI data.

A non-invasive, low-cost and easy-to-operate underwater terrain monitoring method

A fast, reliable, through water and non-intrusive bed-profile measurement technique that is economical and easy to use in a wide range of laboratory experiments involving sediment transport is proposed. A consumer-grade 3-D range sensing technology which by its low cost, easy operation and relatively good accuracy is becoming an attractive alternative to expensive 3-D laser scanners. The Microsoft XBOX 360 kinect sensor 2.0 is a low-cost and highly popular depth camera, which can be used to scan 3D surface terrain of dynamic objects and has the potential to scan terrain below and above water. Through the software matching of kinect 2.0, a data storage and analysis system are formed, which makes it has the ability to obtain underwater terrain data. In addition, the correction model of water refraction error is established, which can eliminate the measurement error caused by water refraction. Up to four different water conditions, kinect 2.0 is tested. Finally, the influences of water depth, suspend load volume concentration and moving flow velocity on the measurement accuracy of kinect 2.0 are explored, and the compensation methods of measurement error caused by the above factors are given. The results of this paper can provide reference for underwater topographic survey.

A fluorescence approach for an online measurement technique of atmospheric microplastics.

Microplastic particles in the atmosphere are regularly detected in urban areas as well as in very remote locations. Yet the sources, chemical transformation, transport, and abundance of airborne microplastics still remain largely unexplained. Therefore, their impact on health, weather and climate related processes lacks comprehensive understanding. Single particle detection presents a substantial challenge due to its time-consuming process and is conducted solely offline. To get more information about the distribution, fluxes and sources of microplastics in the atmosphere, a reliable and fast online measurement technique is of utmost importance. Here we demonstrate the use of the autofluorescence of microplastic particles for their online detection with a high sensitivity towards different widely used polymers. We deploy online, single particle fluorescence spectroscopy with a Wideband Integrated Bioaerosol Sensor WIBS 5/NEO (Droplet Measurement Technologies, USA), which enables single particle fluorescence measurements at two excitation wavelengths (280 nm and 370 nm) and in two emission windows (310-400 nm and 420-650 nm). We investigated shredded (<100 μm) everyday plastic products (drinking bottles and yogurt cups) and pure powders of polyethylene terephthalate (PET), polyethylene and polypropylene. For the broad range of typical plastic products analyzed, we detected fluorescence on a single particle level using the WIBS. The online detection can identify particles smaller than 2 μm. In the case of microplastic particles from a PET bottle, 1.2 μm sized particles can be detected with 95% efficiency. Comparison with biological aerosols reveals that microplastics can be distinguished from two abundant pollen species and investigation of the complete fluorescence excitation emission maps of all samples shows that online identification of microplastics might be possible with fluorescence techniques if multiple channels are available.

Mid-infrared dual-comb spectroscopy for rapid temperature distribution characterization.

Due to the influence of chemical reactions, phase change, and other phenomena, the combustion system is a complicated high-temperature environment. Therefore, the spatio-temporally resolved monitoring of the temperature field is crucial for gaining a comprehensive understanding of the intricate combustion environment. In this study, we proposed a fast and high-precision temperature measurement technique based on mid-infrared (MIR) dual-comb spectroscopy with a high spectral resolution and fast refresh rate. Based on this technique, the spatio-temporally resolved measurement of a non-uniform temperature field was achieved along the laser path. To verify the capability of DCS for temperature measurement, the bandhead ro-vibrational lines of the CO2 molecule were acquired, and the 1-σ uncertainty of the retrieved temperature was 3.2°C at 800°C within 100 ms. The results demonstrate the potential of our fast and high-precision laser diagnostic technique which can be further applied to combustion kinetics.

Neural network enhanced aging time measurements of diary product remaining with infrared spectroscopy

The determination of the drying degree of food residues on surfaces is an important step before efficient cleaning can be achieved. To accomplish this goal, a rapid evaluation based on a neural network and non-invasive measurement technique is introduced. Two common starch-based products and various yogurts from different manufacturers are used as example contaminants to determine the aging time of dried food residue. Near-infrared spectroscopy serves as a modern and fast measurement technique for investigating food compositions. Two analysis methods were compared for processing the measured near-infrared spectral data. The raw data were analyzed using partial least squares regression in conjunction with necessary preprocessing steps. As an alternative method, three different types of neural networks are employed. The aim of this approach is to compensate for the filtering steps before regression, which are typically necessary for multivariate regression. The challenge is to measure three different types of food and obtain a reliable prediction of moisture content in order to draw conclusions about the drying time. The experiments have shown that simple flat neural networks have similar accuracy compared to conventional regression. The use of a convolutional layer in advance demonstrates a significant improvement in prediction compared to other neural networks and even manages to surpass the accuracy of PLS regression. A network with a convolutional layer can also compensate for the sometimes strong variations between food types.

Progressive Expansion Sampling of Quasi-Static Magnetic Fields in Unconfined Regions

We present a fast and accurate measurement technique for quasi-static magnetic fields by employing a progressive sampling method in an unconfined input space. The proposed machine learning algorithm is tested against uniform sampling on printed circuit board test structures and a buck converter. We prove allocation of multiple, separated regions with predefined lateral field limits at MHz frequencies. The feasibility of equivalent magnetic dipole source modeling based on a small number of samples is demonstrated. Compared to uniform testing, progressive expansion sampling identifies contours of given field limits in less than 3% of the reference measurement time.

Study of fast in-line measurement techniques for water ice characterization

Study of fast in-line measurement techniques for water ice characterization

High-speed and dynamic measurement of the diffraction efficiency of a grating in a wide wavelength range

Approximate 5 min are needed to obtain diffraction efficiency of a grating in a wavelength range with 151 sampling points by the currently widely used measurement technique. The time-consuming nature restricts its usage in many dynamic measurements. To this end, we developed a fast measurement technique, and the corresponding measurement is completed in a high speed within 1 s. Meanwhile, dynamic measurement of the efficiency of a grating from 600 nm to 900 nm during a heating procedure is successfully carried out. Our technique could find applications in other circumstances where high-speed measurement is needed.

Color as a tool for quantitative analysis of heterogeneous polymer degradation

Despite the fact that polymers are widely used in both our homes and industrial applications, critical insights into their degradation mechanisms when exposed to harsh environmental conditions, such as elevated temperature or radiation, are lacking quantifiable metrics. In oxygenated environments, polymer degradation is dominated by thermal-oxidation or photo-oxidation and in many cases occurs in a heterogeneous fashion throughout the thickness. While the heterogeneous oxidation of polymers is a common phenomenon, the effect on the functional lifetime of polymers is not well understood. Methods to evaluate such oxidation phenomena are time consuming and a challenge to implement. Here we show a novel approach for a quantitative evaluation of heterogeneous oxidation in polymers, using a fast and accurate color measurement technique. The proposed color analysis approach was observed to improve the efficiency of obtaining heterogenous oxidation profiles in half the time of common approaches, such as indention or Fourier transform infrared spectroscopy. Furthermore, the method was verified by mapping oxygen concentration through sample thickness using energy dispersive X-ray spectroscopy. The utility of the proposed method is demonstrated through the generation of an oxidation framework, aimed at an intelligent design of experiments for polymer lifetime prediction. We anticipate this work to be a starting point for further evaluation of heterogeneous oxidation in polymers using optical properties.

A Novel Technique for Fast Ohmic Resistance Measurement to Evaluate the Aging of Lithium-Ion xEVs Batteries

Lithium-ion batteries are gaining more attention due to the rapid growth of electrical vehicles (EVs). Additionally, the industry is putting a lot of effort into reusing EV batteries in energy storage systems (ESS). The optimal performance of the repurposed battery system is highly dependent on the individual batteries used in it. These batteries need to be similar in terms of battery capacity, state of health (SOH), and remaining useful life (RUL). Therefore, battery grading techniques are expected to play a vital role in this newly emerging industry. There are various methods suggested to evaluate the aging of a battery in terms of capacity, SOH, and RUL. The use of ohmic resistance is one approach, as it varies with the aging of the battery. In order to measure the ohmic resistance, electrochemical impedance spectroscopy (EIS) is used, followed by the curve fitting procedures. In this research a novel method is suggested to measure the ohmic resistance without performing the broadband conventional EIS test and the curve fitting. Since the battery is perturbed for a specified frequency band (1 kHz to 100 Hz) using the linearly distributed phased multi-sine signal, only 1 sec perturbation is required, and the ohmic resistance can be directly calculated by using two impedance values. Thus, the measurement speed is several times faster than that of the conventional EIS methods. Hence, it is a suitable and convenient technique for the mass testing of the batteries. The accuracy and validity of the proposed technique are verified by testing three types of batteries. The percentage difference in the measured ohmic resistance value between the conventional and the proposed technique is less than 0.15% for all the batteries tested.

High Expressed Emotion (HEE), Assessed Using the Five-Minute Speech Sample (FMSS), as a Predictor of Psychiatric Relapse in Patients with Schizophrenia and Major Depressive Disorder: A Meta-Analysis and Meta-Regression.

Expressed Emotion (EE) describes the tone of a caregiver's response to a patient with a mental disorder, and it is used to predict relapse. The Five-Minute Speech Sample (FMSS) is a 5-min interview with a caregiver that evaluates only two EE dimensions. The present study aimed at evaluating HEE (High Expressed Emotion) as a predictor of relapse in patients with schizophrenia and major depressive disorder. Six studies were selected for the meta-analysis. In total, the studies included 297 subjects. The analyses included a random effects model; a meta-analysis excluding the study with the smallest sample; a cumulative meta-analysis; a meta-regression with random effects, using patient age and duration of illness as moderators; a leave-one-out meta-analysis; and a funnel plot to estimate publication bias. The FMSS emerged as a valid and reliable tool for measuring EE as a predictor of relapse in patients with schizophrenia and major depressive disorder. Patient age and duration of illness had no significant effect on the results. Future meta-analyses should include more studies to reduce publication bias. EE may be a good predictor of relapse when examined through a fast measurement technique such as the FMSS, which may also be useful to analyze the psychopathological structure of caregivers.

Fast band power measurement technique in Wi-Fi systems using spectrum analyzer

Fast band power measurement technique used for measuring band power in wireless fidelity (Wi-Fi) devices. The difficulty during testing the band power is burst mode transmission takes longer time to measure. A test jig or specialized tool required is costly, which allows continuous mode of transmission for power measurement. The delivered average power by a Wi-Fi device depends upon the data rate which can also vary during time. The procedure proposed hereby developed using a spectrum analyzer to measure band power in the burst mode, in order to ensure repeatable results and optimized to enable fast measurements at low cost, less time and above 90% accurate.

Off-axis digital holographic decarrier phase recovery algorithm combined with linear regression

Benefitting from the high measurement efficiency, off-axis digital holography (DH) has become a most powerful DH technique for fast and high-accuracy measurement. Owing to the carrier frequency, the real image can be isolated easily in the Fourier spectrum of one off-axis hologram, so that the Fourier transform algorithm (FTA) is the most widely used algorithm for off-axis DH to realize the phase retrieval. In the FTA, one of the most important tasks is to figure out the accurate peak position of the real image and then shift the real image to the center of spectrum to remove the carrier. However, owing to the digitalization of the hologram, the peak position of the real spectrum is always not located at an integral pixel position in the practical applications, resulting in carrier residuals, thereby lowering the retrieval quality. Much work on accurately determining the peak position has been conducted to suppress the carrier residuals, such as by using the spectrum centroid method and zero padding. However, those estimation algorithms can achieve only satisfied accuracy in some situations. Then, spatial carrier phase shift (SCPS) is utilized to expand the utilization of space-bandwidth and avoid the spectrum leakage caused by band-pass filtering. The SCPS decomposes one off-axis hologram into several sub-holograms, in which the carrier induces the phase shifts between sub-holograms. Many on-axis phase retrieval algorithms are combined with SCPS to retrieve the phase from one off-axis hologram. However, the retrieved phase is usually composed of the sample phase and the carrier, so the accurate carrier information is also required to remove the carrier and obtain the correct reconstructed phase. In this paper, an accurate phase retrieval with carrier removal from single off-axis hologram by using the linear regression is proposed to achieve the simultaneous phase retrieval and carrier removal. In this method, four phase-shifted sub-holograms are extracted first from one off-axis hologram by SCPS. Since the phase shift between sub-holograms is linearly proportional to the carrier, the linear regression can be combined with least-square method to retrieve the phase and carrier simultaneously. Both the simulation and experimental results show that the proposed method can determine the carrier accurately and obtain correct phase without carrier. We believe that this proposed method can be applied to practical measurement.

Material Permittivity Estimation Using Analytic Peak Ratio of Air-Coupled GPR Signatures

Ground penetrating radar (GPR) is widely applied for civil engineering, such as for building health assessments or pavement inspections. In these applications, information on the material permittivity is important for internal structure inspection and characterization. However, in the case of a large building area, a lightweight, fast and effective permittivity measurement technique is required. In addition, the estimation method for different GPR types and range configurations must be generalized for adaptability and wide applicability. This paper proposes a material permittivity estimation technique for air-coupled GPR that effectively works for mobile and large observation missions. The method employs the peak ratio of analytic representation signals between the antenna direct coupling and the material surface reflection. An interpolation algorithm is applied to the reference characteristic curves generated by the finite-difference time-domain technique to adapt the change in radar range configuration. The proposed method has been tested to estimate the permittivity in three different construction materials and measure two metal rebar depths inside reinforced concrete. The experimental results show that the method works with acceptable accuracy. Therefore, the method is sufficiently promising to be utilized in real applications, especially those that require adaptability and mobility, such as ground and aerial vehicle-based radar systems.

Study of hanging valley in loess-paleosoil sediments with soil erosion assessment using nuclear and erosion potential methods

This paper is dealing with soil erosion assessment using two different approaches: nuclear model and erosion potential method, also known as Gavrilovic's method. Complex valley systems on Titel Loess Plateau were selected for investigation. Radiocaesium is favored in many studies as an optimal erosion tracer due to its relatively long half-life, negligible renewal in the environment and strongly binding ability onto soil particles. The use of gamma-spectrometry in environmental testing laboratories acts as a precise and fast measurement technique for determination of 137Cs activity concentrations, without the need for complicate preparation of samples. Annual erosion and deposition rates were estimated according to three conversion models for uncultivated land: the profile distribution model with two years of dominant fallout of 137Cs (1963 and 1986) and the diffusion and migration model using WALLING software. The applied nuclear models were validated by comparison with erosion potential model which is the most relevant empirical model for erosion processes in torrent valleys. The obtained results indicate a good agreement with overall low values of average annual soil erosion rates on all soil profiles in the investigated area. Correlation analysis has determined the different influence of slope, terrain curvature, and vegetation index on the erosion models.

Response analysis of subgrade soils using signal phase shift obtained from laboratory lightweight deflectometer (LWD) tests

Over the past decades, the use of fast and reliable measurement techniques of soil mechanical properties has gained popularity. The lightweight deflectometer (LWD) is among the tools developed that can allow one to determine the elastic modulus of soil. Viscosity response components in pavement or soil typically induce phase shifts between stress and strain peaks, which can be translated to phase angle. Subgrade soil may exhibit varying response types depending on its nature and characteristics. Using large laboratory subgrade samples, an experiment was designed to measure the elastic modulus and phase angle with an LWD in different stress and humidity conditions. A model associating the elastic modulus inferred from LWD tests with parameters describing stress, water content, and soil properties was proposed. This model is fundamentally inferred from the relationship between elastic modulus and phase shift, and was used to assess the relative contribution of varying conditions on soil stiffness.

A contribution to flotation technique as a reliable wettability alteration measurement method for carbonate minerals in separation processes involving hydrocarbons, low salinity water and nanofluids

A reliable flotation method was developed and experimentally evaluated as a fast and repeatable quantitative wettability measurement technique for Enhanced Oil Recovery (EOR) purposes by comparing its performance with the well-known and reliable method of contact angle measurement. In both methods, oil-wet carbonate specimens were contacted with brines of different salinities and nanoparticle concentrations, and the trend of test results were compared. In the salinity tests, it was observed that flotation results are in full consistency with contact angle measurements. In both methods, salinity reduction from seawater (SW) to 10 times diluted seawater (TDSW) resulted in reaching the maximum hydrophilicity while further dilution to 40 TDSW hindered the wettability alteration process. Nanofluid tests in both methods were also in great consistency at nanoparticle concentrations below 0.1%wt due to particle stability limitations. Finally, two flotation mechanisms for the oil/water/rock system were introduced and one of them was empirically confirmed.