Experimental Measurement Data Research Articles

Material characterization of thin planar structures using full-field harmonic vibration response measured with stroboscopic holography

We propose a novel material characterization method to estimate the Young's modulus of thin 2-D structures using non-modal noisy single frequency harmonic vibration data measured with holography. The method uses finite-difference discretization to apply the plate equation to all measured pixels inside the boundary of the vibrating structure and then treats the problem as a Bayesian optimization process to find the value of the Young's modulus by minimizing the Euclidian distance between the measured displacement field and repeatedly calculated displacement field using the plate equation. In order to assess the accuracy of the method, ground truth harmonic displacement magnitude fields of different plates were obtained using analytical solutions and the finite-element method and were used to estimate the Young's moduli. We applied Gaussian and non-Gaussian noise with different intensities to assess the robustness and accuracy of the proposed material characterization method in the presence of noise. We demonstrated that for multiple benchmarks for signal to noise ratio of down to 0 dB, our proposed method had errors of less than 5%. We also quantified the effects of uncertainties in the geometrical and material parameters as well as boundary conditions on the estimated Young's modulus. Furthermore, we studied the effects of the mesh size on the runtime and applied the method to experimental holography vibration measurement data of a copper plate.

Millimetre wave channel modeling based on grey genetic optimization model

In this paper, grey genetic optimization model (GGOM) is proposed for predicting insufficient channel parameters without increasing the amount of measurement data. Based on the millimetre wave 28 GHz indoor measurement data for both LOS and NLOS scenarios, the GGOM model is compared with traditional back propagation (BP) and grey model (GM) to analyse channel parameters like delay spread, excess delay and azimuth spread. Results show that the fitness of GGOM is better than the grey model in improving the stability of system. It works well with insufficient data (size less than 30) in most cases as it is set regardless of the specific scene and measurement data. This is verified by QuaDRiGa platform by generating uniformly distributed and interpolated data between the experimental measurement data. GGOM fits best with the measurement data compared with other prediction methods in channel characterization. Moreover, the mean absolute percentage error (MAPE) for GGOM is the least compared with GM and BP methods. The proposed GGOM model has good performance in modeling insufficient data of propagation channel, practically.

Incorporating Prior Knowledge in Local Parametric Modeling for Frequency Response Measurements: Applied to Thermal/Mechanical Systems

Frequency response function (FRF) identification is a key step in experimental modeling of many applications, including mechatronic systems. Applying these techniques to systems where measurement time is limited leads to a situation where the accuracy of the identified model is deteriorated by transient dynamics. This article aims to develop an identification procedure that mitigates these transient dynamics by employing local parametric modeling techniques. To improve the modeling accuracy, prior knowledge is suitably incorporated in the procedure while at the same time allowing for rational parameterizations that maintain a closed-form solution. The prior knowledge is exploited in a relevant local frequency range using a specific Möbius transformation. Preexisting methods, including the commonly used local polynomial method, are recovered as a special case. The presented framework leads to accurate identification results in a simulation study as well as on experimental measurement data.

Thermoelectric cooling properties of a quantum Hall Corbino device

We analyze the thermoelectric cooling properties of a Corbino device in the quantum Hall regime on the basis of experimental data of electrical conductance. We focus on the cooling power and the coefficient of performance within and beyond linear response. Thermovoltage measurements in this device reported in {\em Phys. Rev. Applied, {\bf 14} 034019 (2020)} indicated that the transport takes place in the diffusive regime, without signatures of effects due to the electron-phonon interaction in a wide range of temperatures and filling factors. In this regime, the heat and charge currents by electrons can be described by a single transmission function. We infer this function from experimental data of conductance measurements and we calculate the cooling power and the coefficient of performance for a wide range of filling factors and temperatures, as functions of the thermal and electrical biases. We predict an interesting cooling performance in several parameter regimes.

An Investigation on High-Resolution Temperature Measurement in Precision Fly-Cutting.

The loads acting on a workpiece during machining processes determine the modification of the surface of the final workpiece and, thus, its functional properties. In this work, a method that uses thermocouples to measure the temperature in precision fly-cutting machining with high spatial and temporal resolution is presented. Experiments were conducted for various materials and machining parameters. We compare experimental measurement data with results from modern and advanced machining process simulation and find a good match between experimental and simulation results. Therefore, the simulation is validated by experimental data and can be used to calculate realistic internal loads of machining processes.

Transfer Case Clutch Torque Modeling and Validation Under Slip and Overtaken Conditions

Abstract The vehicle transfer case clutch plays an important role for four-wheel drive (4WD) vehicles since the torque transmitted through the clutch determines the amount of traction torque on tires, which is important for vehicle performance. However, the clutch torque measurement is usually unavailable on production vehicles and needs to be estimated accurately to improve vehicle performance. This paper proposes a unified scheme to model clutch output torque under all three conditions: open (no torque output), slipping, and overtaken. Specifically, the clutch torque model under clutch overtaken condition is first investigated using the vehicle longitudinal and tire dynamics. It was found that effective radius of front tires, powered by the transfer case clutch torque, cannot be assumed as constant and should be compensated by vehicle acceleration, while the effective radius of rear tires connected directly to the propulsion system does not need to be compensated. In addition, it was found that torque model under clutch overtaken condition cannot be used under slip condition. As a result, a general clutch torque model is developed for both slip and overtaken conditions with a clutch slip speed compensation, resulting a root-mean-square error percentage (RMSE%) of 6.8% comparing with the experimental measurement data. Note that overtaken torque model is a special case of the general torque model by setting slip speed equal to zero. The general clutch torque model is able to calculate clutch output torque accurately under both slip and overtaken conditions.

Repeater Power Conversion Efficiency in Submarine Optical Communication Systems

In power-limited trans-oceanic submarine systems, the electrical-to-optical (E/O) power conversion efficiency determines the amount of optical signal power generated by repeaters, which governs the cable capacity. In contrast to conventional submarine systems, recent single mode fiber spatial division multiplexing (SDM) systems operate at a lower channel power and support a larger number of optical fibers. Moreover, pump sharing technology is used in SDM systems to enhance cable capacity and system reliability, where a group of pump lasers are combined to feed a group of fiber pairs. The repeater E/O power conversion efficiency is directly related with cable capacity, as well as capacity per power and cost per capacity analysis. Therefore, it is important to understand the characteristics of repeater E/O efficiency. We developed a model to analyze the repeater E/O efficiency in submarine SDM systems. Experimental measurement data of pump lasers and numerical simulation results of Erbium doped fiber amplifiers (EDFAs) were used as input information to the model to analyze repeater E/O efficiency in various system designs. Based on the E/O efficiency model results, we investigated cable capacity using the Gaussian noise (GN) model. Moreover, cable capacity per power was calculated and compared based on three different power metrics: (i) electrical supply power, (ii) pump optical power and (iii) EDFA output power. With the aid of the repeater E/O efficiency model, one can analyze the efficiency of submarine systems using the direct metric of cable capacity per electrical supply power.

A Modified Formula for Calculating Dielectric Properties of Granular Agricultural Products in the Microwave Band

Dielectric properties are important characteristic parameters in the microwave-assisted application of hygroscopic agricultural media. To break through the limitation of traditional general effective medium (GEM) formula and develop the new calculation formula suitable for agricultural products, a modified formula, that is, modified general agricultural products effective medium (abbreviated as MGAPEM) formula, was presented in this study for the dielectric property calculation of granular agricultural products in the microwave band. The correctness, validity, and accuracy of MGAPEM formula were verified by using literature and experimental measurement data. Results show that the maximum errors of the dielectric constant and dielectric loss factor are 0.42% and 0.98%, respectively, in the conditions of microwave frequency (2.0–12.2 Ghz) and moisture content (2.0%-19.7%, wet basis). The accuracy of MGAPEM is higher than some traditional theoretical formulas. The MGAPEM formula provides a theoretical formula for the dielectric property analysis of granular agricultural products in the microwave band at room temperature (24℃).

Alumina Trihydrate Effect on Flashover Voltage of Polyester Insulators by Whale Optimization Algorithm Technique

Ceramic materials are commonly used as outdoor insulators for high-voltage power transmission lines. Presently, these ceramic insulators are replaced by composite polymeric insulators with polyester, especially in rainy areas. Unlike ceramic materials, polymer materials have a shorter life, so fillers are used to improve their physical and chemical properties. This paper aims to improve the flashover voltage performance of polyester loaded with Alumina Trihydrate filler in wet weather condition. Due to the high cost of raw materials (polyester and Alumina Trihydrate filler), the Whale Optimization Algorithm model was used to predict the best concentration of Alumina Trihydrate filler to give the best value of flashover voltage. The model is based on experimental data of flashover voltage measurements. A positive correlation of the calculations from the Whale Optimization Algorithm model with experimental data has been demonstrated. The results showed that the flashover voltage performance of polyester is increased with the increase of Alumina Trihydrate filler concentration. Also, the optimum concentration of Alumina Trihydrate filler and flashover values predicted by the MATLAB Whale Optimization Algorithm are very accurate.

Application of artificial neural network model for forecast energy efficiency of the cryogenic liquefaction system in the meaning of sustainability

Sustainable engineering approaches are a necessity for improving efficiency. For this reason, the artificial neural network (ANN) model is used to forecast different types of energy efficiency problems. In this paper, a comparison is made between a simple model based on ANN which gives meaningful findings in terms of thermodynamics and a model that is based on thermodynamic principles as auditing and predicting tool to forecast exergy efficiency of the system by applying different ANN architecture types with 441 data of experimental measurements obtained from liquefied nitrogen and analysed the Engineering Equation Solver (EES) program to make an exergy analysis.

Engineering networks simulation and assessment of the mathematical model accuracy

The article shows the way to implement a quasilinear mathematical model of flow distribution in pipeline engineering networks that is effective in a wide range of changes in the multidimensional random vector of loads at network nodes and provides reliable determination of the parameters of the probability distribution functions of flows in active and passive network elements. The proposed model consists of determining the matrix of generalized network parameters-the load distribution coefficients along the branches of the circuit, calculated at the point corresponding to the mathematical expectation of the node loads. Based on the obtained model, the convergence of the results obtained with the results of simulation of engineering networks is proved using a numerical experiment on an electronic computer. The effectiveness of the developed model, the corresponding algorithms and a set of programs for an electronic computer is shown - the value of the criterion of reduced costs for parametric optimization of engineering networks can be reduced by 5-7% compared to the methods used in practice. The possibility of obtaining at the design stage the equivalent hydraulic characteristics of engineering networks in the form corresponding to the data of experimental measurements of pressures at the nodes of real complex engineering networks is proved.

Unsteady RANS simulation of OECD-TAMU cold-leg mixing benchmark

Unsteady Reynolds-Average Navier-Stocks (URANS) simulation was conducted, in which the mixing of two immiscible fluids with different densities were measured using the multi-component material model for the OECD-TAMU cold-leg mixing benchmark. The turbulence models (i.e. realizable κ-ε, standard κ-ω and κ-ω SST) were validated against the particle image velocimetry (PIV) data and sensitivity analysis of uncertain input parameters were carried out. Turbulence models for the prediction of mean velocity components and root mean square velocity components, the mixing phenomena in the cold-leg were found in good agreement with the PIV data. However, the turbulence models unable to predict the close agreement with PIV data in the downcomer. Numerical uncertainty of two meshes was conducted for cold-leg and downcomer. It is observed that the numerical uncertainty band is within the range of experimental measurement data. Furthermore, The sensitivity of five uncertain input parameters (i.e. Schmidt number, density difference, heavy fluid viscosity, light fluid viscosity) was analyzed and their influence on the output parameters was noticed. Therefore, the turbulent Schmidt number and density difference, revealing significant effect on the out parameters. As a consequence, the major contribution of turbulent Schmidt number and density difference will be observed in the propagation of input uncertainty.

Application of Bayesian approach and probability theory for calculating territorial risk and zoning on urban area

The article describes a new algorithm for assessing territorial risk. The risk in the algorithm is calculated as the ratio of the prior and posterior probabilities of an unfavorable (risk) event. An event is an excess of the threshold content of toxicants in a certain area of space, taking into account how often this event occurred in all other areas of space. This can be used for zoning an urbanized area. We used a probabilistic safety assessment (PSA) apparatus based on hazard modelling and a scenario-based approach. Such an apparatus does not analyse certain integral characteristics of the process, but all possible states in a given time section at the same time, forming a probabilistic model. The probabilistic approach ensures the accuracy and realism of assessments of the state of the environment of an urbanized area that are unattainable for deterministic methods and, in addition, allows you to take into account the cumulative effect of multiple sources of uncertainty. Using the probabilistic method and assessing the level of risks allows you to broadcast complex scientific information in an accessible format to people making environmental decisions. Risk is not an absolute but a relative category. It is heterogeneous in both time and space. Therefore, it can be used when zoning the environment, especially since the parameters that are used to calculate risk very often form the same data arrays necessary for classifying and zoning spatial non-uniformity of the system in general. After analyzing various approaches, we came to the conclusion that for a given time period the probability of an adverse event will be calculated more accurately if we calculate not using the classical formula (the number of cases per time interval), but in the form of the ratio of the posterior and prior probabilities. This takes into account the risk in a certain area of space and correlates with the frequency of the same event in all other areas. To assess the likelihood of polymetallic pollution of environmental objects in an urbanized area with its subsequent zoning, we considered the variability of the metal content in environmental objects. Based on the probabilities that metal concentrations exceeded their threshold values, the territorial relative risk was calculated and zoning of the urbanized territory was carried out. Testing of the considered approaches was carried out in the territory of Kazan on the basis of an array of data of experimental measurements on the content of metals in environmental objects. For sampling, 170 points were selected across the territory of the city of Kazan, which are under the influence of stationary and mobile sources of the influx of metals into the urbanized territory. The probability distribution of exceeding the threshold level of metal content in environmental objects in the territory of Kazan is shown cartographically.

Modeling to Predict the Cycle Life of a Lithium-Ion Battery

The lithium-ion battery (LIB) is the primary choice for many applications such as mobile electronics, electric vehicles, and stationary energy storage solutions due to its high energy density, high voltage and low self-discharge rate. The service life of LIB for such applications is generally limited by aging, although it depends strongly on the usage conditions. The aging of LIB manifests itself in the variation of electrical and thermal behaviors such as capacity fade, cell voltage drop under load, and peak temperature rise during cycling. It is of intense interest to predict accurately the cycle life of the commercial LIB by including the effect of aging.In this work, a modeling is performed to predict the cycle life of an LIB cell during cycling over a long time. This work adopts a simple modeling approach by considering Ohm’s law and charge conservation on the electrodes based on the simplified polarization characteristics of the electrodes. By not computing the potential distribution of electrolyte phase and the transport phenomena of ionic species, the modeling method in this work cuts down considerable computation time in comparison with rigorous electrochemical models. The validation of the modeling approach is provided through the comparison of the modeling results with the experimental measurement data.

Inhomogeneous interval fields based on scaled inverse distance weighting interpolation

This paper introduces a novel method to model non-deterministic quantities based on experimental measurement data. The focus of this work is on quantities that vary over a continuous domain, e.g., material properties, time-dependent strain rate effects, or stress–strain curves. These quantities are modelled by means of the recently introduced concept of interval fields. An interval field defines intervals that are defined throughout the continuous domain and have dependence in this domain by expanding them over a set of basis functions, describing the spatial nature of the non-determinism of the modelled quantities. One of the more intuitive concepts of defining basis functions in an interval field is through inverse distance weighting interpolation (IDW), which starts from known intervals at specific control points within the domain. For each of these control points, a corresponding basis function is defined, the relative weight of which is decreasing inversely with the distance. Through this definition, all intervals have non-vanishing basis functions throughout the model domain. This makes the application of standard IDW extremely challenging when the interval uncertainty varies inhomogeneously over the domain, i.e., when local effects are present in the model.Therefore, in this paper standard IDW is adapted by changing the distance measure. More specifically, the weight of intervals is increased locally, while diminishing the weight in other regions. For this purpose, a function is introduced that maps the domain to a higher dimension feature space, in which the distances that determine the weight are measured. This mapping function is based on either the size of the intervals at the control points or experimental data, which both yield additional control resulting in increased agreement with experimental data.This paper demonstrates that this method outperforms standard IDW in controllability, while limiting the number of control points. This is illustrated in three case studies: a first case concerning modelling local non-determinism; a second case where a mix of global and local effects is modelled; and the third case, where the interval field is based on experimental stress strain curves. In all these cases, multiple configurations demonstrate the effects of the parameters, and how the new technique is applied. The proposed technique outperforms standard IDW in all three case studies, with an increased coefficient of determination, R2, between 22% and 56%, in comparison to standard IDW.

System Identification of Micro Piezoelectric Actuators via Rate-Dependent Prandtl-Ishlinskii Hysteresis Model Based on a Modified PSO Algorithm

As one of the high-precision actuating mechanisms, the piezoelectric actuators show the advantage of micro/nano stage maneuverability in facilitating the actuating performance of the mechanical systems. To improve the actuating accuracy, it is important to predict the output behavior accurately under the wide operating range, particularly, the change of the driving frequency. The modeling method using the rate-dependent Prandtl-Ishlinskii (RDPI) model is subsequently adopted, which can show the strong nonlinearities relating to the coupling effects between the internal hysteresis and the actuating frequency. Considering the electromechanical characteristics of piezoelectric actuators, a modified particle swarm optimization (MPSO) algorithm is introduced for identifying the RDPI model using the experimental measurement data. The developed MPSO algorithm can overcome the local optimizing limitation of the classical particle swarm optimization (CPSO) algorithm and guarantee the accuracy of predicting the output. The utility and superiority of the MPSO are verified by fitting the identified model to the actual output of the piezoelectric actuators in the micro range at different actuating frequencies. The comparisons with available models using MPSO, CPSO and LS algorithms have examined the validity of the proposed identification method.

AnisEulerSC: A MATLAB program combined with MTEX for modeling the anisotropic seismic properties of a polycrystalline aggregate with microcracks using self-consistent approximation

Seismic anisotropy of polycrystalline materials depends on the characteristics of microcracks as well as the crystallographic orientations of minerals. Here, we present a MATLAB-based software, AnisEulerSC (Anisotropy from Euler angles using Self-Consistent approximation), for modeling the anisotropic seismic properties of a polycrystalline aggregate with microcracks using the self-consistent approximation. In this program, several commands of MTEX (a MATLAB toolbox for texture analysis) are utilized to analyze constituent components of a rock sample based on experimental measurement data (e.g., electron backscatter diffraction) and to calculate and visualize seismic wave velocities and polarizations. We provide several examples of SC modeling to explore the effects of grain shapes on a polycrystalline aggregate and the effects of crack shapes and orientations on the anisotropic seismic properties of a polycrystalline aggregate.

Mitigation of Through-Wall Distortions of Frontal Radar Images Using Denoising Autoencoders

Radar images of humans and other concealed objects are considerably distorted by attenuation, refraction, and multipath clutter in indoor through-wall environments. Although several methods have been proposed for removing target-independent static and dynamic clutter, there still remain considerable challenges in mitigating target-dependent clutter especially when the knowledge of the exact propagation characteristics or analytical framework is unavailable. In this article, we focus on mitigating wall effects using a machine learning-based solution—denoising autoencoders—that does not require prior information of the wall parameters or room geometry. Instead, the method relies on the availability of a large volume of training radar images gathered in through-wall conditions and the corresponding clean images captured in line-of-sight conditions. During the training phase, the autoencoder learns how to denoise the corrupted through-wall images in order to resemble the free space images. We have validated the performance of the proposed solution for both static and dynamic human subjects. The frontal radar images of static targets are obtained by processing wideband planar array measurement data with 2-D array and range processing. The frontal radar images of dynamic targets are simulated using narrowband planar array data processed with 2-D array and Doppler processing. In both simulation and measurement processes, we incorporate considerable diversity in the target and propagation conditions. Our experimental results, from both simulation and measurement data, show that the denoised images are considerably more similar to the free-space images when compared to the original through-wall images.

Global Research Alliance N2 O chamber methodology guidelines: Statistical considerations, emission factor calculation, and data reporting.

Static chambers are often used for measuring nitrous oxide (N2 O) fluxes from soils, but statistical analysis of chamber data is challenged by the inherently heterogeneous nature of N2 O fluxes. Because N2 O chamber measurements are commonly used to assess N2 O mitigation strategies or to determine country-specific emission factors (EFs) for calculating national greenhouse gas inventories, it is important that statistical analysis of the data is sound and that EFs are robustly estimated. This paper is one of a series of articles that provide guidance on different aspects of N2 O chamber methodologies. Here, we discuss the challenges associated with statistical analysis of heterogeneous data, by summarizing statistical approaches used in recent publications and providing guidance on assessing normality and options for transforming data that follow a non-normal distribution. We also recommend minimum requirements for reporting of experimental and metadata of N2 O studies to ensure that the robustness of the results can be reliably evaluated. This includes detailed information on the experimental site, methodology and measurement procedures, gas analysis, data and statistical analyses, and approaches to generate EFs, as well as results of ancillary measurements. The reliability, robustness, and comparability of soil N2 O emissions data will be improved through (a) application, and reporting, of more rigorous methodological standards by researchers and (b) greater vigilance by reviewers and scientific editors to ensure that all necessary information is reported in scientific publications.

Antenna Feed Array Synthesis for Efficient Communication Systems

Accurate synthesis of antenna radiation behavior is a complementary step towards simulation in antenna systems design process. In this paper, a spherical harmonic decomposition (SHD) and coupled structure electromagnetic statistical model (CSESM) methods are hybridized and adapted for the first time, to actively synthesize radiation characteristics using antenna feed array. The problem of finding the feed array aperture size, capable of synthesizing a required field intensity distribution, within a specified region for a reflector system signaling a satellite is also addressed. Relationship that exist between the required number of elements in feed array, frequency of operation, volume of the synthesis region, and the required reflector size is theoretically benchmarked. EM radiation behavior via antenna feed array is optimally synthesized using the proposed SHD-CSESM-based method. With this approach, operation limits on the synthesis of the signal field within a test volume of a given radius is predicted. Efficiency and effectiveness of SHD-CSESM-based EM field synthesis scheme unveiled are investigated for structures in a region where feed antennas are positioned distance away (focal point) from reflector system operating at Ka band. Experimental measurement data of a circularly polarized Ka-band $2\times2$ -antenna feed array is compared with the proposed theoretical method, and results obtained demonstrate the validity of the proposed algorithm. Furthermore, for any wave number ${k}$ or frequency f, the field radiation behaviour within the sphere can be accurately synthesized using an ${N}$ order expansion and ${V} \ge (4{N}+1)/{N}$ array size. Results obtained show that the proposed synthesis method handles constrains related to both aperture domain and radiation domain. Hence, SHD-CSESM-based technique is a good candidate for EM field synthesis, with the notion of automating system design processes in the emerging and future EM field applications.