Different Sets Of Experimental Data Research Articles

Identification of damaged member in a truss structure using acoustic emission technique aided by SVM

Structures are prone to damage, and detecting them at their very initiation is extremely important for taking corrective measures. Truss is a very important civil engineering structure having a complex geometry: width and thickness being very small compared to the length of a member and the presence of discontinuities in the form of joints. Most of the existing techniques identify damages after they have grown to a substantial degree. For early detection of damages, the acoustic emission (AE) technique may be used effectively as the initiation of damage itself results in the emission of AE wave, analysis of which may lead to detection of the damage. Additionally, signature behavior of the virgin structure is not necessary, unlike many other nondestructive testing methods. Existing studies largely use the time of arrival (TOA) of AE wave at the sensor location(s) in the formulation for damage localization. However, TOA is significantly affected by reflected waves from the edges of truss members and attenuation of signal strength during its passage through joints. In addition, TOA suffers from a lack of objectivity in prescribing the relevant threshold value. Accordingly, damage localization may be affected. In this context, a machine learning approach is very promising if appropriate signal features are used for training. Accordingly, in the present study, an effort is made to develop a support vector machine model for the localization of a truss member, where damage has been initiated. The model is trained and then tested using different sets of experimental data, collected from a laboratory-scale truss. The results of the localization, as predicted by the model, are found to be encouraging when compared with the physical observation.

Analysis of charged hadrons’ transverse momentum distributions in p + Pb and Xe + Xe collisions at LHC energies

This paper is focused on comparative analysis of transverse momentum ( pT ) distributions across two different sets of experimental data from ALICE at the LHC, juxtaposing with the Monte-Carlo models EPOS-LHC and EPOS 1.99 simulations. The chosen collision sets have approximately same per nucleon energy. We analyze the transverse momentum spectra of hadrons ( π++π−, K++K− and p+p¯ ) in p+Pb collisions at sNN= 5.02 TeV, and Xe + Xe collisions at sNN= 5.44 TeV spanning a rapidity range of 0 < yCM < 0.5, centrality of 0 to 5% (the most central or head-on collisions). Analysis of the Hadrons yield is crucial for understanding the mechanism of underlying hadronization in the hot and dense quark matter produced in relativistic heavy ion collisions. The experimental results are compared with the predictions of hydrodynamic models EPOS-LHC and EPOS-1.99. It is notably found that the maximum yields of various particles occur at low pT. Furthermore, the comparison showed a slightly better agreement between experimental results and the predictions of the EPOS-LHC as opposed to that of EPOS-1.99. The EPOS-LHC model significantly shows an enhanced agreement with experimental results in the case of Xe+Xe collisions as compared to p+Pb collisions.

On the theory of mechanically induced chemiluminescence in multiple network elastomers

Mechanophores, force-sensitive molecules, can be covalently linked into polymer networks to reveal the damage properties of polymeric materials under deformation. Recent works have introduced bis-adamantyl dioxetane (Ad) into multiple network elastomers. These mechanoluminescent cross-linking molecules can emit luminescence as they break. The experimental results can directly visualize the damage behaviors of multiple network elastomers and reveal the damage mechanism of these materials during deformation. In this work, we develop a constitutive model to describe the complex mechanical behaviors of multiple network elastomers based on observations from mechano-chemiluminescent experiments. The free energy density consists of the contributions from the filler network, the matrix network, and the entangled network. A new type of single-chain model is developed for the filler network, while the classic eight-chain mapping is adopted for the micro–macro transition. The chains in the filler network are progressively damaged under deformation to explain the stress-softening behaviors observed in the small and median strain regions of multiple network elastomers. The entangled network is rooted in individual fragments of the damaged filler network, which can be further damaged in the large deformation regime. The model can comprehensively capture the complex mechanical responses of multiple network elastomers with different values of the prestretching ratio of the filler network, including linear response, necking instability, and re-hardening phenomena in quadruple networks. By assuming that the luminescence intensity of the materials is proportional to the total percentage of damage from both filler and entangled networks, we quantify the relationship between damage and the luminescence intensity from mechanophores, which is further validated in quantifying luminescence intensity against different sets of experimental data on the uniaxial tension of multiple network elastomers. The model is further implemented for finite element analysis, demonstrating the ability to visualize and characterize the damage behaviors around a crack.

A dispersive estimate of the a0(980) contribution to hadronic light-by-light scattering in (𝑔 − 2)µ

A dispersive implementation of the a0(980) resonance to (𝑔 − 2)µ requires the knowledge of the double-virtual S-wave γ * γ * → πη / KK¯I = 1 am plitudes. To obtain these amplitudes we used a modified coupled-channel Muskhelishvili-Omnès formalism, with the input from the left-hand cuts and the hadronic Omnès function. The latter were obtained using a data-driven N/D method in which the fits were performed to the different sets of experimental data on two-photon fusion processes with πη and KK¯ final states. This yields the preliminary dispersive estimate aμHLbL[a0(980)]resc. = -0.46(2) × 10-11.

Model Identification of E. coli Cultivation Process Applying Hybrid Crow Search Algorithm

Cultivation process (CP) modeling and optimization are ambitious tasks due to the nonlinear nature of the models and interdependent parameters. The identification procedures for such models are challenging. Metaheuristic algorithms exhibit promising performance for such complex problems since a near-optimal solution can be found in an acceptable time. The present research explores a new hybrid metaheuristic algorithm built upon the good exploration of the genetic algorithm (GA) and the exploitation of the crow search algorithm (CSA). The efficiency of the proposed GA-CSA hybrid is studied with the model parameter identification procedure of the E. coli BL21(DE3)pPhyt109 fed-batch cultivation process. The results are compared with those of the pure GA and pure CSA applied to the same problem. A comparison with two deterministic algorithms, i.e., sequential quadratic programming (SQP) and the Quasi-Newton (Q-N) method, is also provided. A more accurate model is obtained by the GA-CSA hybrid with fewer computational resources. Although SQP and Q-N find a solution for a smaller number of function evaluations, the resulting models are not as accurate as the models generated by the three metaheuristic algorithms. The InterCriteria analysis, a mathematical approach to revealing certain relations between given criteria, and a series of statistical tests are employed to prove that there is a statistically significant difference between the results of the three stochastic algorithms. The obtained mathematical models are then successfully verified with a different set of experimental data, in which, again, the closest one is the GA-CSA model. The GA-CSA hybrid proposed in this paper is proven to be successful in the collaborative hybridization of GA and CSA with outstanding performance.

CFD modelling of the non-isobaric evaporation of cryogenic liquids in storage tanks

A new CFD model relevant to non-isobaric cryogen evaporation has been developed. It considers the heat influx, from the surroundings to the liquid and vapour phases, and the heat transfer between the phases. The phase change is modelled considering two contributions: an interfacial energy balance far from the tank wall, and by direct wall-to-liquid conduction near the wall. The model provides well resolved liquid and vapour temperature and velocity profiles, as well as pressure build-up and evaporation rates. It shows that below the vapour-liquid interface, liquid natural convection is dampened by thermal stratification, which is driven by the increase of the interfacial temperature due to increase in pressure. The pressure build-up is mainly governed by the heating of the vapour, particularly at the beginning of the evaporation. The model was used to analyse liquid velocity profiles for two different sets of experimental data for evaporation of liquid nitrogen by optimizing empirical parameters, namely the wall heat partitioning fraction and the overall heat transfer coefficients. The results show that a large fraction of the vapour heat ingress is not transferred to the vapour phase bulk. Instead, it is transported through the walls and transferred to the liquid at the liquid-vapour-wall contact point, driving phase change. Heat conduction from the walls to the interface has a significant effect, even for low heat fluxes, and cannot be neglected.

Introducing "MEW2" Software: A Tool to Analyze MQ-NMR Experiments for Elastomers.

Low-field time-domain proton Nuclear Magnetic Resonance (NMR) spectroscopy is an attractive and powerful tool for studying the structure and dynamics of elastomers. The existence of crosslinks and other topological constraints in rubber matrices (entanglements and filler-rubber interactions, among others) renders the fast segmental fluctuations of the polymeric chains non-isotropic, obtaining nonzero residual dipolar couplings, which is the main observable of MQ-NMR experiments. A new software, Multiple quantum nuclear magnetic resonance analyzer for Elastomeric Networks v2 (MEW2), provides a new tool to facilitate the study of the molecular structure of elastomeric materials. This program quantitatively analyzes two different sets of experimental data obtained in the same experiment, which are dominated by multiple-quantum coherence and polymer dynamics. The proper quantification of non-coupled network defects (dangling chain ends, loops, etc.) allows the analyzer to normalize the multiple quantum intensity, obtaining a build-up curve that contains the structural information without any influence from the rubber dynamics. Finally, it provides the spatial distribution of crosslinks using a fast Tikhonov regularization process based on a statistical criterion. As a general trend, this study provides an automatic solution to a tedious procedure of analysis, demonstrating a new tool that accelerates the calculations of network structure using 1H MQ-NMR low-field time-domain experiments for elastomeric compounds.

A Thermal Conductivity Model for Deformable and Unsaturated Soils to Assess the Thermal Behaviour of Energy Piles

This paper presents an empirical model that predicts the thermal conductivity of soils by accounting for the effect of both the degree of saturation and void ratio on the heat exchange capacity of shallow geothermal reservoirs. The model is generated by the product of two terms: the former accounts for the effect of void ratio on the dry thermal conductivity, whereas the latter describes the influence of the degree of saturation on the moisture-dependent thermal conductivity. The model is a function of three parameters, which are easy to calibrate based on their physical meaning. Model predictions are validated against five different sets of experimental data from literature by means of two alternative approaches: blind prediction of thermal conductivity measurements not employed during calibration and numerical simulations of thermal tests performed on energy piles. Results show that the proposed model is capable of accurately predicting both the thermal conductivity of deformable unsaturated soils as well as reproducing the thermal behaviour of energy piles.

A Lode-Dependent Failure and Yield Criterion for Cohesive and Noncohesive Materials

Experimental studies on different materials demonstrate a wide variety of strength behavior. Although the classical failure/yield criteria might be suitable for special cases, they cannot accurately cover the whole range. Thus, the need to employ a unifying model, capable of comprising various criteria seems inevitable. This paper develops a flexible Lode-dependent failure and yield criterion that allows the generation of various shapes in both deviatoric and meridian planes. The model, thus, can cover all the classical criteria including von Mises, Drucker–Prager, Tresca, Mohr–Coulomb, Matsuoka–Nakai, Lade–Duncan, and other recently developed failure/yield criteria. Moreover, the model can consider tensile strength that makes it appropriate for cohesive materials as well. After defining the model, the condition for its convexity and differentiability is discussed. Then, the results derived from the developed model are compared with some of the well-known criteria and different sets of experimental data to attest to its accuracy and applicability in predicting the strength and yield of different materials.

The underlying mechanisms behind the hydration-induced and mechanical response of spider silk

Spider silk is a unique protein material that exhibits counterintuitive behaviors such as a significant reduction in stiffness of up to three orders of magnitude and a decrease in length of up to ∼60%, commonly termed supercontraction, upon exposure to high relative humidity (RH). In this work a robust free energy-based model is derived for the humidity-induced and mechanical response of spider silk. As opposed to the classical treatment of gels, the penetration of water molecules into a silk network results in an anisotropic response. First, the kinematics that describe the hydration-induced behavior are discussed and the balance laws and equilibrium requirements are reviewed. Next, the balance of free energy is used to derive constitutive relations that relate the free energy-density to the stress, the chemical potential, and the supercontraction stretch that develop in a spider silk fiber. Following experimental observations, a free energy-density that comprises four contributions is proposed: the first two contributions account for the entropic gain and the loss of chain orientation due to water uptake and the consequent dissociation of intermolecular hydrogen bonds, respectively, the third contribution describes the mixing process between the water and the polymer molecules in the silk, and the fourth contribution arises from the supercontraction phenomenon. Explicit forms are proposed for the four free energy-density contributions. The model is validated through a comparison to five different sets of experimental data under different boundary conditions. With an eye to future applications, the response of a spider silk fiber that is radially constrained and subjected to increasing humidity is also explored. The findings from this work pave the way to the design of silk-based composites and biomimetic materials with fascinating non-trivial properties and behaviors.

Prediction of airflow rate passing through compressible wet fiber web in vacuum dewatering for energy conversion improvement

Vacuum dewatering is a highly energy-intensive process that is widely adopted in industrial production such as papermaking and chemical manufacture. A significant portion of the energy consumed by vacuum system is converted into energy that drives airflow passing through the wet fiber web. During the energy conversion process, a part of the energy is wasted due to the redundant capacity of the vacuum pump, which is caused by the deviation of the airflow rate estimation during the design of the vacuum system. To improve the energy conversion rate, a variable porosity model (VPM) is proposed in this study to better simulate the process of airflow passing through a porous medium–wet fiber web. Compared with the existing constant porosity model (CPM), the VPM model takes the effect of wet fiber web compressibility into account to improve the accuracy of airflow rate calculation. Different sets of experimental data demonstrate that the accuracy of airflow calculation of the VPM is about 22 times that of the CPM. In addition, the characteristic parameterization of different fiber structures in this study expands the applicability of the model and can be widely adopted in multitudinous industrial fields, which is of great significance for improving the energy conversion rate of vacuum dewatering process and saving energy.

Radioactive source localization using a data driven MVA method

We present a small form factor (0.5 cm3) static CdZnTe (CZT) sensor network consisted of a number of Non Directional Detectors (NDD) capable to localize a stationary radiation source in 3D. The localization is performed with fusion algorithms based on AI techniques. The algorithms are based on Multilayer Perseptron Neural Network (MLP) and Gradient Boosted Decision Trees (BDTG). A data driven method based on experimental data was used to produce the events for both training and testing of the algorithms. The localization efficiency of the algorithms was verified with a different set of experimental data taken in our laboratory using a 137Cs source of 180 μCi. A localization resolution of a bare radioactive source of the order of 10 cm to 20 cm has been archived in 3D after at least of 40 sec exposure time within a monitored volume of 5 m × 2.8 m × 2 m. The localization of slightly shielded sources in 3D can be also achieved but with a hardly worse resolution.

Nanofiltration of complex mixtures: The effect of the adsorption of divalent ions on membrane retention

In nanofiltration (NF), solution and membrane chemistry determine the membrane charge density. In multi-component electrolytes solutions, it is important to consider the interaction between ions and NF membranes. For instance, in the presence of divalent ions, charge reversal can take place due to the interaction of counterions with the charged functional groups of the membrane. This paper presents a model based on state-of-the-art mean-field theory that includes the effect of divalent counterions on the membrane charge density. By using a Langmuir equation with two model parameters, we consider the adsorption of divalent ions (e.g., Ca2+ and Mg2+) in the polyamide active layer of the membrane and calculate the effective membrane charge density. Two different sets of experimental data from literature are used to evaluate the model. Contrary to the statement of a recent study on NF, we show that mean-field theory can predict the rejection of all types of ions in a multi-component electrolyte solution when the effect of divalent counterions on the membrane charge density is included. Moreover, the results in this study reinforce the idea that adsorption of counterions plays a fundamental role in the performance of nanofiltration.

Steady state crack growth in viscoelastic solids: A comparative study

We compare the predictions of different theories on the steady state growth of a Mode I crack in linear viscoelastic solids. The theories studied in this work include those by Knauss, Schapery, Persson and Brener. The comparisons focus on the fractional dissipation rate and the relationship between crack growth velocity and fracture energy. Analytical solutions are carried out using realistic constitutive models such as the Generalized Maxwell Solid (GMS) and the Power Law Solid (PLS). These theories are tested against two different sets of experimental data reported in the literature. We also present new results such as the strain field directly ahead of the crack tip, the residual strain on the crack surfaces and the crack opening displacement (COD). We use the expressions for COD to study the shape and size of the “viscoelastic trumpet” proposed by de Gennes. Using a new approach, we study the shape and size of the viscoelastic dissipation zone around the crack tip and discuss its dependence on the crack growth velocity.

Multi-region modeling of conversion of a thick biomass particle and the surrounding gas phase reactions

In this paper, a novel multi-region Eulerian model is presented to study the conversion of thermally thick biomass particles. In the present model, the particle and the surrounding fluid are treated as two separate regions that are coupled through an interface. There are some benefits for using a multi-region approach, including a more realistic radiation modeling, flexibility to define the flow boundary conditions at the surface of the particle, and also the possibility to use different governing equations for each region. Furthermore, the multi-region approach provides a solution to the stiff problem of coupling the particle to the surrounding fluid which can be used to significantly reduce the computational cost. In the current model, sub-models for drying, pyrolysis, gasification, combustion, and shrinkage are included. The local effect of shrinkage is considered through porosity change and the global effect of shrinkage is modeled using a dynamic mesh approach. The particle surface and center temperature and particle mass loss during pyrolysis and combustion are compared to different sets of experimental data. The model is used to study the shrinkage and anisotropic heat transfer on particle conversion, and also the pyrolysis in cases with and without the gas phase reactions.

Stimulated luminescence; Analysis of complex signals and fitting of dose response curves using analytical expressions based on the Lambert W function implemented in a commercial spreadsheet

Thermoluminescence (TL) and optically stimulated luminescence (CW-OSL, LM-OSL) are widely used by the scientific community in different applications. In order for the information of a glow or decay curve to be used correctly, the deconvolution of the corresponding curve is essential. Nowadays, there are plethora of deconvolution methods with none of them being dominant and universal. Recently, researchers created some new analytical equations for the TL, CW-OSL and the LM-OSL phenomena, based on the Lambert W function, with the use of a single master equation, as well as some new dose response curves based on a) the simple One Trap One Recombination (OTOR) model and b) the more complex Two Traps One Recombination (TTOR) model. The main aim of the study is to recreate these five expressions in different Excel spreadsheets, for a more practical use. The first step is the creation of a computational code of the Lambert W function in VBA at Excel. After that aim is achieved, five spreadsheets were created, namely the TL deconvolution, the CW-OSL deconvolution, the LM-OSL deconvolution, the OTOR model Dose response and the TTOR Dose response. In order to run some tests using these spreadsheets, four different sets of experimental data originated from different sources were used each time, with the calculated values being compared to the literature. In the end, the present study provides some notes and discussion about the applications of the newly created deconvolution spreadsheets.

Comprehensive Mathematical Model for Freezing Time Prediction of Finite Object

Frozen food sees a continuous increase in consumption thanks to the capability to preserve the organoleptic properties and, at the same time, to increase the shelf-life of the food itself. Therefore, a proper design of the freezing process is crucial and is strictly related to an accurate evaluation of freezing time because this establishes the minimum residence time of the product in a continuous freezer. For this reason, several mathematical models have been proposed and investigated for predicting the freezing time, starting from empirical models (lower accuracy and computational time) up to computational fluid dynamics simulation (higher accuracy and computational time). An excellent compromise between accuracy and computational effort seems to be a model that combines empirical laws for property evaluation and heat diffusion equation solved in one dimension. This model can numerically be solved using the method of lines in which spatial derivatives are discretized by the finite difference method and the resulting system of ordinary differential equations is integrated using an appropriate solver. This work aimed to fill some gaps to develop a comprehensive and more accurate model for freezing time prediction. Indeed, the key idea is to validate a model that could be used to optimize the refrigeration process for energy-saving and be the base for a design of experiment in case of lack of experimental data. The newly developed model includes the evaluation of freezing time for finite food shapes because, in some cases, it is not possible to assume a characteristic direction for heat flux. The property of unfrozen and frozen food (e.g. density, thermal conductivity, apparent specific heat, etc.) are evaluated basing on the principal constituent of food (e.g. water, fiber, protein, etc.), while heat transfer coefficient is evaluated using empirical equations, depending on adimensional numbers. In this way, it is possible to be flexible and not strictly related to the evaluation of the properties of food for each different case. The proposed model was validated with different sets of experimental data related to beef and strawberry pulp freezing. For these cases, the R2 index is equal to 0.982 and 0.996 respectively, showing a good agreement between experimental and predicted data. Finally, a case study of spinach cubes freezing was provided to show the potentiality of the novel model.

A detailed reaction mechanism for elemental sulphur combustion in the furnace of sulphuric acid plants

AbstractElemental sulphur combustion is traditionally used to generate SO2 to produce sulphuric acid that is consumed in chemical industries, but is now also being considered as an energy vector for power generation. Despite the fact that sulphur combustion has been practiced for decades, there are limited reaction mechanisms for its combustion chemistry, which is critical for the optimization of the sulphuric acid production process to maximize efficiency and reduce cost. In this paper, a detailed reaction mechanism is developed and validated with different sets of experimental data from lab‐scale and industrial plant studies. The reaction mechanism is used to conduct sulphur furnace simulations, where the effects of feed air/sulphur ratio and oxygen enrichment of air stream on furnace temperature and the concentrations of SO2, SO3, and O2 are investigated. The dominant reaction pathways in sulphur combustion, particularly for the production of SO2 and SO3, are identified. It was found that the feed air/sulphur ratio monitors the furnace temperature and can be used to obtain the desired O2/SO2 ratio at the furnace exit for the optimal operation of catalytic converter (for SO2 oxidation to SO3) that follows the furnace in the sulphuric acid plant. Moreover, high oxygen enrichment above 35% (while maintaining the desired O2/SO2 ratio at the furnace exit) significantly increased the furnace capacity through reduced total gas flow (thus decreasing blower energy requirement and equipment size). The developed reaction mechanism provides a method to obtain optimized furnace parameters to achieve high efficiency and reduced costs in sulphuric acid plants.

Experimental study of a linear Fresnel concentrator: A new procedure for optical and heat losses characterization

This paper describes a set of iterative procedures developed in Matlab and Engineering Equation Solver, used to experimentally obtain the optical and heat loss characterization of a small-scale linear Fresnel concentrator. These procedures were created for a prototype designed and built for direct steam generation by the LEPTEN laboratory, at the Federal University of Santa Catarina. Two different sets of experimental data were considered. First, the heat transfer fluid was at the lowest temperature achievable using the experimental setup available and was used to obtain the optical peak efficiency and the incidence angle modifier. The second set, with wider range of fluid temperatures, was used to find the heat losses. Applying the procedures developed, convergence was obtained. The optical peak efficiency ranged from 47 to 52%. Monte Carlo Ray-Tracing software was used to obtain the incidence angle modifier, and these curves were compared with experimental ones. The heat loss curve was constructed for fluid temperatures up to 130 °C. These iterative procedures can be adapted to determine the heat loss and optical efficiency in any linear Fresnel solar concentrator if adequate experimental data is available. Each software used had its role, and the use of both allowed creating a fast easy-to-converge methodology.

Heat Capacities and Enthalpies of Normal Alkanes in an Ideal Gas State

The reference literature contains data on the ideal gas-phase heat capacities and enthalpies of substances obtained experimentally. In this brief report, the highly accurate and simple unified analytical dependences of the heat capacity and enthalpy of normal alkanes larger than propane in the ideal gas state on temperature and the number of carbon atoms in a molecule are derived based on the analysis of the structure of chemical groups in the molecules and on the reference values of heat capacity and enthalpy for any two selected normal alkanes at one temperature. The dependences include a single set of coefficients for all normal alkanes and can be applied even to normal alkanes with the number of carbon atoms larger than 20, for which there is no data available. The dependences are thoroughly checked against two different sets of experimental data and two different sets of computational data obtained by low- and high-level theoretical methods: PM6 and G4. The error in calculating the heat capacity and enthalpy in the temperature range 300–1500 K is about 0.1% or less, which is comparable with the error of reference experimental data. Due to the generality of these dependences, one can treat the arising deviations as the indication of possible errors in the sets of reference data used for analysis. Such dependences are useful for estimating the heat capacities and enthalpies of vapors of large n-alkanes with scarce or lacking data. In addition, they can be readily used in computational fluid dynamics applications and provide the accurate interpolation/extrapolation of the tabulated experimental data without using semi-empirical methods of chemical thermodynamics and high-order polynomials.