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In this paper, a deep learning based time-domain inversion method is proposed to reconstruct high-contrast scatterers from the measured electromagnetic fields. The scatterers investigated in this study include four kinds of geometry shapes, which cover the arbitrary geometrical shapes, handwritings and lossy medium. After being well trained, the performance of the proposed method is evaluated from the perspective of accuracy, noise interference, and computational acceleration. It can be proven that the proposed framework can realize high-precision inversion in several milliseconds. Compared with typical reconstruction methods, it avoids the iterative calculation by utilizing the parallel computing ability of GPU and thus significantly reduce the computing time. Besides, the proposed method has shown the potential to be applied in practical scenarios with experimental results. Herein, it is confident that the proposed method has the potential to serve as a new path for real-time quantitative microwave imaging for various practical scenarios. In the end, the limitation of the method is also discussed. [ABSTRACT FROM AUTHOR]

Ventilation, cooling, heating, and air conditioning (HVAC) systems represent a substantial portion, approximately 40%, of energy consumption in buildings. Among the key components of HVAC/R systems, the compressor, fans, and electrical resistances are major consumers of electricity. In this context, the compressor stands out due to its significant dynamic behaviour, serving as the pivotal element in heat pump operations. However, many manufacturers solely provide empirical data regarding compressor performance, lacking comprehensive models for assessing performance across various operational conditions. This paper addresses the methodology for evaluating mathematical models utilizing experimental compressor data. Through this approach, we aim to bridge the gap between empirical observations and predictive modelling, enabling a more nuanced understanding and optimization of HVAC/R system performance. The proposed model uses interpolation and it takes as input the evaporation and condensation temperatures. It shows an R -- square and adjusted R -- square value of 0.99. By using the experimental data and an open -- source library for interpolation this paper paves the way for a flexible and practical compressor modelling. [ABSTRACT FROM AUTHOR]

In this paper, we further develop a novel, efficient approach to the problem of signal detection against background noise based on a nonlinear residual functional called the neuron-like criterion function (NCF). A detailed comparison of the NCF-based technique and the conventional correlation criterion function (CCF)-based matched-signal detection is performed. For this purpose, we calculated the detection performance curves for both techniques and found the range of the problem parameters in which the NCF-based detector shows a certain advantage. The latter consists of achieving a fixed value of detection probability at a lower threshold value of the input signal-to-noise ratio (SNR) compared to the CCF-based detector. Special attention is given to the practically important scenario of receiving a weak signal against the background of non-stationary noise with a certain trend (positive or negative) of its intensity. For these two specific cases, modified NCFs are given, which are then used for computer simulation. For both broadband and narrow-band signals, the quantitative bounds of the most effective use of the derived NCFs are established and interpreted. The real sea noise data obtained from two underwater acoustic arrays, one stationary on the sea bottom and the other towed near the sea surface, are used for experimental validation. The experimental data processing results confirm the simulation results and make it possible to demonstrate the advantage of the NCF if the noise intensity shows a significant trend over the signal observation interval. The latter case obviously corresponds to the use of the towed array in the coastal area. [ABSTRACT FROM AUTHOR]

This work outlines an efficient deep learning approach for analyzing vascular wall fractures using experimental data with openly accessible source codes (https://doi.org/10.25835/weuhha72) for reproduction. Vascular disease remains the primary cause of death globally to this day. Tissue damage in these vascular disorders is closely tied to how the diseases develop, which requires careful study. Therefore, the scientific community has dedicated significant efforts to capture the properties of vessel wall fractures. The symmetry-constrained compact tension (symconCT) test combined with digital image correlation (DIC) enabled the study of tissue fracture in various aorta specimens under different conditions. Main purpose of the experiments was to investigate the displacement and strain field ahead of the crack tip. These experimental data were to support the development and verification of computational models. The FEM model used the DIC information for the material parameters identification. Traditionally, the analysis of fracture processes in biological tissues involves extensive computational and experimental efforts due to the complex nature of tissue behavior under stress. These high costs have posed significant challenges, demanding efficient solutions to accelerate research progress and reduce embedded costs. Deep learning techniques have shown promise in overcoming these challenges by learning to indicate patterns and relationships between the input and label data. In this study, we integrate deep learning methodologies with the attention residual U-Net architecture to predict fracture responses in porcine aorta specimens, enhanced with a Monte Carlo dropout technique. By training the network on a sufficient amount of data, the model learns to capture the features influencing fracture progression. These parameterized datasets consist of pictures describing the evolution of tissue fracture path along with the DIC measurements. The integration of deep learning should not only enhance the predictive accuracy, but also significantly reduce the computational and experimental burden, thereby enabling a more efficient analysis of fracture response. [ABSTRACT FROM AUTHOR]

In this article, the performances of the SPH method to solve Shallow Water Equations SWEs with three investigation parameters were studied, such as the type of kernel functions, namely: cubic spline, Gaussian and quintic spline kernels, the number of particles used and the stabilization terms injected, specifically: Lax Friedrichs flux, artificial viscosity and two shocks Riemann solver. Three benchmarking tests make the subject of unsteady free surface flow in this study. It is 1D typical dam-break on wet and dry bottom; 2D partial dam-break on a dry floodplain and 2D partial dam-break on channel with 90° bend. The analysis of the different errors between the numerical and analytical solutions and/or the experimental data shows that the SPH method gives reliable values with the selected optimal parameters which are the cubic kernel function and the artificial viscosity term. The increase in the number of particles increases the precision but also the calculation time. [ABSTRACT FROM AUTHOR]

This paper presents a detailed study on the main parameters and performance evaluation of microjet engines, at take-off regime and at various engine working regimes, based on thermodynamic analysis of a particular engine data library, from different engine manufacturers such as JetCat and AMT Netherlands. The studied engines have the same spool design but different thrust classes ranging from 97 to 1569 N. The particular data library includes engine specifications from catalogs or data sheets as well as our own experimental data from the JetCat P80 microjet engine, obtained using the ET 796 Jet Turbine Module, a complete testing facility for gas turbine education purposes. Various ratios and differences between certain engine main parameters and performances are studied in order to calculate values through which the analyses can be performed. Even if the engines have different thrust classes, the study examines if there are close values of the ratios and differences of parameters, that can be defined as reference parameters through which the engine performance can be compared and evaluated. [ABSTRACT FROM AUTHOR]

An equibiaxial tension test could be necessary to set up hyperelastic material constants for elastomers exactly. Unfortunately, very often, only uniaxial tension experimental data are available. It is possible to use only uniaxial data to compute hyperelastic constants for a hyperelastic model, but the prediction of behavior in different deformation modes (as is equibiaxial or pure shear) will not work correctly with this model. It is quite obvious that there is some relation between uniaxial and equibiaxial behavior for the elastomers. Thus, we could use uniaxial data to predict equibiaxial behavior. If we were able to predict (at least approximately) equibiaxial data, then we could create a hyperelastic model usable for the general prediction of any deformation mode of elastomer. The method of the appropriate processing of experimental data for such prediction is described in the article and is verified by the comparison with the experiment. The presented results include uniaxial and equibiaxial experimental data, the created average curve of both the deformation modes, and the predicted equibiaxial data. Using Student's t-test, a close coincidence of the real and predicted equibiaxial data was confirmed. [ABSTRACT FROM AUTHOR]

Behind a retaining wall, the mean effective stress mainly decreases during an excavation phase following an unloading stress path. The volumetric strains generated by purely elastic soils are systematically dilative which induces aberrant ground uplifts. The introduction of plasticity along with a nonlinear elastic domain turns out to be essential for a realistic prediction of ground movements. In this paper, a numerical analysis is carried out using a finite element code considering an advanced soil constitutive model called "Generalized Hardening Soil" which has been recently developed. This model contains the exact same set of features as the Hardening Soil Small Strain model but with the possibility to activate each of its plastic and nonlinear elastic mechanisms independently. The role of these mechanisms are investigated to assess their impact on the shape and the amplitude of the ground movements. Numerical results demonstrated that plasticity triggers the main contractive volumetric strains leading to settlements. Nevertheless it cannot fully compensate the elastic uplifts due to unloading. The insertion of strain dependent stiffness is essential as well as the stress dependency. A back analysis of the historical excavation of the Taipei National Enterprise Center permitted to validate these findings. [ABSTRACT FROM AUTHOR]

The larval development of a fish parasite, Acanthocephalus tenuirostris, has been studied under experimental conditions. This species is common in the eastern regions of Russia, from Primorye to the upper reaches of the Kolyma River. The material for the experiments has been collected from different areas of Magadan oblast, which is located mainly in the subarctic climate zone. In several series of experiments, intermediate hosts (Asellus hilgendorfii) are infected and maintained at a constant temperature of 15°C. In all cases, no more than 45 days are required for the formation of the final cystacanth stage. Along with cystacanths, a large number of other larvae at earlier developmental stages are simultaneously recorded in the hemocoel of the isopods. An additional experiment, carried out at 15°C for the first 45 days and 4–6°C for the next 207 days, has shown the possibility of the further development of larvae at low temperatures. A comparison with the available literature data on the timing of development of European Acanthocephalus species living in temperate climate has suggested that A. tenuirostris has adapted to cold climate conditions, which provides a twofold acceleration of the rate of its development compared to larval A. lucii in Europe. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Topological data analysis (TDA) is a powerful and promising tool for data analysis, but yet not exploited enough. It is a multidimensional method which can extract the topological features contained in a given dataset. An original TDA-based method allowing to monitor the health of structures when equipped with piezoelectric transducers (PZTs) is introduced here. Using a Lamb wave based Structural Health Monitoring (SHM) approach, it is shown that with specific pre-processing of the measured time-series data, the TDA (persistent homology) for damage detection and classification can be greatly improved. The TDA tool is first applied directly in a traditional manner in order to use homology classes to assess damage. After that, another method based on slicing the temporal data is developed to improve the persistence homology perception and to leverage topological descriptors to discriminate different damages. The dataset used to apply both methods comes from experimental campaigns performed on aeronautical composite plates with embedded PZTs where different damage types have been investigated such as delamination, impacts and stiffness reduction. The proposed approach enables to consider a priori physical information and provides a better way to classify damages than the traditional TDA approach. In summary, this article demonstrates that manipulating the topological the features of PZTs time-series signals using TDA provides an efficient mean to separate and classify the damage natures and opens the way for further developments on the use of TDA in SHM. [ABSTRACT FROM AUTHOR]

In this work, a mathematical model of the transfer process in a layer under the condition of given experimental data on a part of the layer boundary is presented and investigated. Such research is important for the mathematical description of the objects and systems for which, based on physical considerations, it is impossible to correctly impose boundary or initial conditions, even in a sufficiently general form, but there are experimental data on the desired function or its derivative at the boundary of the body or at the initial time. The values of the desired function at the boundary are known at certain moments in time. The boundary condition is constructed by the experimental data and the initial-boundary value problem, with such a boundary condition, is formulated and solved. The influence of the statistical characteristics of the sample of experimental data on the solution to the initial-boundary value problem is analyzed, and a two-sided statistical estimation of the solution is determined. The confidence intervals for the coefficients of the regression equation and the corresponding confidence intervals for the sought function are established. The influence of the statistical characteristics of the sample on the sought function at the lower boundary of the layer is investigated. Numerical analysis of the solution to the initial-boundary value problem is carried out depending on the statistical characteristics of the sample. Various cases of samples by size and variance are considered. Numerical solutions are studied under the conditions of large and small time intervals of the considered process. [ABSTRACT FROM AUTHOR]

It is found that without any additional assumptions, Nernst's equation can be re-deduced from the experimental data obtained from the thermodynamic systems at ultra-low temperatures, which is different from the derivation processes in textbooks and literature, and consequently, the physical content included by Nernst's equation should not be referred to as Nernst's postulate or Nernst's theorem. It should be renamed as the Nernst statement. This discovery will play an important role in improving the theoretical framework of thermodynamics. It can effectively prevent some artificial assumptions into the third law of thermodynamics, making it a true reflection of the objective world. It solves the awkward problem caused by using a thermodynamic theorem as the core contents of a thermodynamic law for over one hundred years. [ABSTRACT FROM AUTHOR]

In the present review, the merits and demerits of machine learning (ML) in materials science are discussed, compared with first principles calculations (PDE (partial differential equations) model) and physical or phenomenological ODE (ordinary differential equations) model calculations. ML is basically a fitting procedure of pre-existing (experimental) data as a function of various factors called descriptors. If excellent descriptors can be selected and the training data contain negligible error, the predictive power of a ML model is relatively high. However, it is currently very difficult for a ML model to predict experimental results beyond the parameter space of the training experimental data. For example, it is pointed out that all-dislocation-ceramics, which could be a new type of solid electrolyte filled with appropriate dislocations for high ionic conductivity without dendrite formation, could not be predicted by ML. The merits and demerits of first principles calculations and physical or phenomenological ODE model calculations are also discussed with some examples of the flexoelectric effect, dielectric constant, and ionic conductivity in solid electrolytes. [ABSTRACT FROM AUTHOR]

Motorcycle motion is largely influenced by the road geometry, which alters the allowable accelerations in longitudinal and lateral directions and influences the vertical wheel loads. Recently, a method for three-dimensional road reconstruction and its incorporation into transient and quasi-steady-state (QSS) minimum lap time simulations (MLTSs) has been proposed. The main purpose of this work is to demonstrate how significantly different results from a minimum lap time optimal control problem can be obtained when using inappropriate elevation data sources in the track reconstruction problem, and how the road model reconstructed using poor input data can lead to misleading conclusions when analyzing real vehicle and driver performances. Two road models derived from high- and low-resolution digital elevation models (DEMs) are compared and their impact on the optimal maneuver of a racing motorcycle is examined. The essentials of track identification are presented, as well as vehicle positioning on the 3D road and the generalized QSS motorcycle model. Obtained 3D and 2D road models are analyzed in detail, on a case example of the Road Atlanta racetrack, and used in minimum lap time simulations, which are validated by the experimental data recorded on the Supersport motorcycle. The comparative analysis showed that great care should be taken when selecting the elevation dataset in the track reconstruction process, and that the 1 m resolution local DEMs seem to be sufficient to obtain MLTS results close to the measured ones. The example of using the 3D free-trajectory QSS minimum lap time problem to localize the track segments where real driver actions can be improved is also presented. The differences between simulation results on different road models of the same racetrack can be large and influence the interpretation of optimal maneuver. [ABSTRACT FROM AUTHOR]

Copyright of Revista Mexicana de Ingeniería Biomédica is the property of Sociedad Mexicana de Ingenieria Biomedica, A.C. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The results of measurements of the thermal conductivity carried out in a gas phase for six binary mixed refrigerants, consisting of hydrofluorocarbons R-125, R-134a, and R32, are analyzed. For each mixture, an equation is given for calculating its thermal conductivity depending on temperature and pressure. The previously proposed model for predicting the thermal conductivity of vapors of mixed refrigerants in a wide range of state parameters has been refined in application to the R-125/R-134a and R32/R-125 systems. [ABSTRACT FROM AUTHOR]

Model updating procedures based on experimental data are commonly used in case of historic buildings to identify numerical models that are subsequently employed to assess their structural behaviour. The reliability of these models is closely related to their ability to account for all the uncertainties that are involved in the knowledge process. In this regard, to handle these uncertainties and quantify their propagation, Bayesian inference is frequently employed being able to deal with the effects of parameter uncertainty, observation errors and model inadequacy. The computation of the posterior distribution through Bayesian inference needs–however–the evaluation of the likelihood function, which requires solving complex multi-dimensional integration problems. To bridge this shortcoming, the paper compares two Bayesian inference approaches to show how different approximations affect the results of simulated inference: a discrete approach for the likelihood computation in the Bayesian Model Updating (BMU) and a Monte Carlo likelihood-free method known as Approximate Bayesian Computation (ABC) are reported. As reference, the typology of historic masonry towers was considered by using their natural frequencies as experimental data for model updating. The two procedures provide very similar results supporting the validity of both methods despite ABC turns out to be a more flexible approach. [ABSTRACT FROM AUTHOR]

Since the beginning of the 20th century, many studies have focused on the possibility of considering the sky as a body characterized by an apparent temperature, and several correlations to quantify the apparent sky temperature have been proposed. However, the different models were obtained for specific meteorological conditions and through measurements at specific sites. The available models do not cover all locations in the world, although the evaluation of the sky temperature is fundamental for estimating the net radiative heat transfer between surfaces and the sky. Here, experimental data logged from a regional micrometeorological network (in Italy, within the Lazio region) were processed and used to identify an empirical model for the estimation of the sky temperature in the Mediterranean area. Data relating to atmospheric infrared radiation were used to compute the sky temperature, aiming at identifying a direct correlation with the ambient temperature. Climatic data acquired during 2022 were processed. The proposed correlations were compared with other models available in the literature, including the standard ISO 13790. This study proposes an annual-based direct correlation in its initial phase, demonstrating a superior fit to the measured data compared to well-known direct empirical models from the literature. Subsequently, quarterly-based correlations are introduced further in a secondary phase of the work to improve the model's adaptation to experimental observations. The results reveal that quarterly-based correlations improve goodness-of-fit indexes compared to annual-based and well-known direct empirical correlations. Finally, a detached building was modeled via a dynamic code to highlight the influence of different correlations on annual energy needs. [ABSTRACT FROM AUTHOR]

Measurements of the viscosity of pure hydrogen and a binary (hydrogen + methane) mixture with a nominal composition 90 mol % hydrogen are presented. The measurements were conducted with a two-capillary viscometer relative to helium along three isotherms of (298.15, 323.15, and 348.15) K and at pressures of up to 18 MPa. Expanded relative combined uncertainties in viscosity range from (0.65 to 2.7) % (k = 2) for the hydrogen data, and from (0.91 to 3.2) % (k = 2) for the (hydrogen + methane) data. The viscosity data are compared to experimental literature data and viscosity correlations implemented in the NIST REFPROP v10.0 database. Good agreement between this work's data, literature data, and the viscosity correlation was achieved for pure hydrogen. The (hydrogen + methane) mixture was compared to the Extended Corresponding States (ECS) model implemented in REFPROP v10.0. Relative deviations between the experimental data and the ECS model exceed the experimental uncertainty and were found to exhibit a positive trend with increasing density and a weakly pronounced negative trend with increasing temperature. No experimental literature data are available at overlapping state regions. Nonetheless, deviations to the ECS model imply reasonable consistency of this work's data and literature data. In addition to experimental viscosities, experimental zero-density viscosity ratios of the fluids under investigation and helium are reported. Fairly good agreement within the experimental uncertainty of this work with a highly accurate literature value and a value obtained from accurate ab initio calculated data was achieved for hydrogen. [ABSTRACT FROM AUTHOR]

This paper reports a novel investigation in applying commercial Ultra High-Frequency RFID tags (UHF-RFID tags), which are widely used in logistics as sensing elements in civil engineering structures, particularly for monitoring out-of-plane displacements of brick masonry walls. Both laboratory tests and in situ experimental tests assessed the feasibility of the proposed application. Laboratory tests showed a very satisfactory response while the in situ experiments showed a weaker response. Nevertheless, the potential reliability of the proposed technique can be stated. The authors traced back the causes of the performance decrease to environmental interference, mainly due to the extensive presence of a rigid steel frame surrounding the out-of-plane loaded panels. Measurements of displacements, in fact, are obtained indirectly from the phase of UHF-RFID signals that strongly suffer from multipath generated by metallic surfaces. Despite some limitations, the proposed measurement technique permits a reliable and sustainable approach to the monitoring of structures. The use of commercial UHF-RFID wireless tags, in fact, assures easy and fast installation operations and assures the possibility of placing a large number of sensors over the structure with very low maintenance costs with respect to the more traditional monitoring techniques. Moreover, using very thin and small commercial UHR-RFID tags on cultural heritage structures can represent an opportunity for sustainable long-time monitoring with reduced costs. Overall, the results of this study are sufficiently satisfactory to be considered as the opening of new possible scenarios in wireless structural monitoring in the civil engineering field. The authors propose as future work to use UHF-RFID tags for the real-time monitoring of an existing masonry facade that, not being characterized by the presence of a steel frame, can potentially assure an adequate response and properly transmit the electromagnetic signal. [ABSTRACT FROM AUTHOR]

Numerical methods are very useful for predicting water levels, velocities and flow rates in hydraulic systems. The Saint-Venant system of equations, which is a hyperbolic partial differential system, is widely used in the modelling of a flood wave due to a dam failure. In this study, two explicit finite difference Lax-Friedrichs and modified Lax-Friedrichs numerical schemes are used to simulate the failure wave of a dam. The calibration of the obtained results is done in relation to experimental measurements and numerical results existing in the literature specialized in this field of research. The experimental set-up consists of a water reservoir that simulates the reservoir of a dam, followed downstream by a horizontal dry bottom section, a triangular bottom sill with steep slopes and a small tide of water at rest after the triangular obstacle which ends with a vertical diaphragm. The simulation obtained results with the new formulation of the Lax-Friedrichs numerical scheme showed good agreement with the simulated, experimental and numerical results of other researchers. [ABSTRACT FROM AUTHOR]

Green roofs are considered sustainable practice s in the urban environment as they provide several benefits to the city and to the building such as mitigating the urban heat island effect and optimizing the energy performance of buildings. The impact of green roofs on the energy balance of urban building surfaces in warmer climates, such as the Mediterranean, is still under investigation. In this study, 5 years of experimental data recorded between 2015 and 2020 were analyzed in comparison between a non-insulated flat roof and a green roof. The aim of this study is to investigate the thermal regulation capacity of green roofs on the energy balance of buildings and their efficiency as potential UHI mitigation strategies to make cities more resilient. Results of the study demonstrated that despite the limited depth of the substrate and plant diversity, the green roof provided thermal regulation to the building by reducing temperature fluctuations and moderating temperatures for both the building and its surrounding environment. Practical application: This study provides evidence that the implementation of a green roof could effectively moderate roof temperatures and reduce fluctuations, especially during the summer season. Furthermore, the study demonstrated that even a simple and shallow extensive green roof could provide thermal benefits in a Mediterranean climate. Therefore, due to its structural lower weight, this type of green roofs could be installed on existing buildings and could provide thermal benefits to the building and the city. [ABSTRACT FROM AUTHOR]

Cellular Automata have successfully been successfully applied to the modeling and simulation of pedestrian and crowd dynamics. In particular, the investigated scenarios have often been focused on the evaluation of medium–high population density situations, in which the motivation of pedestrians to reach a certain location overcomes their tendency to naturally respect proxemic distances. The global COVID-19 outbreak, though, has shown that sometimes it is crucial to contemplate how proxemic tendencies are emphasized and amplified by the affective state of the individuals involved in the scenario, representing an important factor to take into consideration when investigating the behaviour of a crowd. In this paper we present a research effort aimed at integrating results of quantitative analyses regarding the effects of affective states on the perception of distances maintained by different types of pedestrians with the modeling of pedestrian movement choices in a cellular automata framework. [ABSTRACT FROM AUTHOR]

Reinforced concrete slab-column connections are vulnerable to punching shear failure when subjected to combined gravity and lateral loadings during earthquakes. Over the years, many experimental campaigns have been conducted and assessed the seismic performance of flat slabs. The experimental findings were used to derive empirical equations for the design provisions. The paper aims to provide a detailed description of the code development for seismic punching shear. Two current code provisions (ACI 318-19, EC 2 & EC 8-2004) for seismic punching shear are presented and discussed. Relevant and updated experimental data of interior slab-column connections without and with shear reinforcement are selected and assessed against the current design provisions with a focus on key response parameters such as the drift ratio and the gravity shear ratio. The ACI 318-19 limit drift line is considered to assess the lateral deformation demand for the connections with respect to the updated database. The gravity shear ratio is shown to have a considerable impact on the limit drift ratio of slab-column connections without shear reinforcement. The majority of the test specimens with no shear reinforcement experienced punching shear failure, followed by the specimens which showed a combined flexure–punching failure. Punching shear failures occurred for a range of gravity shear ratios of 0.2 to 0.9, while all combined flexure–punching shear failures occurred for gravity shear ratio values below 0.5. The shear-reinforced concrete slab-column connections can achieve much higher drift ratios. Most of the slabs were reinforced with shear studs, particularly in the range of gravity shear ratios of 0.4 to 0.6. Most test specimens failed by flexure for gravity shear ratio values of 0.1 to 0.7, followed by the specimens which failed in combined flexure–punching for gravity shear ratio values that ranged from 0.3 to 0.9. Finally, the available numerical and analytical models for seismic punching shear are presented with the objective of observing their potential strengths and limitations. [ABSTRACT FROM AUTHOR]

Copyright of WISTA Wirtschaft und Statistik is the property of Statistisches Bundesamt and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article examines the pollution dynamics in urban wet-weather runoff, addressing the statistical characterization and systematic classification of water quality characteristics as key aspects of sustainable and effective urban stormwater quality control and treatment measures. A reliable first flush methodology is applied to discrete water quality data of different pollution parameters from an Italian database for the identification of the Bivio Vela catchment's representative evolution of mean concentrations and the assessment of the required runoff volume to reduce stormwater pollutant concentrations to background levels. A comparison is carried out between results from two catchments with different land use types (industrial versus residential) and the complexity of the sewerage system, highlighting challenges in tracking pollution trends and delineating peculiar dynamics of different quality parameters in a specific geographic context. Despite appreciably different pollutant dynamics, both catchments achieve background levels for all the examined parameters after 6 mm runoff. The outcome of the analysis has clear implications for the design approach of sustainable stormwater management practices. [ABSTRACT FROM AUTHOR]

This paper considers a linear continuous- or discrete-time dynamic object in the absence of its mathematical model. As is demonstrated below, a control law that suboptimally damps initial and (or) exogenous disturbances of such objects can be implemented based on experimental and a priori data. The approach involves the methods of robust control design and duality theory as well as the technique of linear matrix inequalities. [ABSTRACT FROM AUTHOR]

To describe the degradation of proton exchange membrane fuel cells (PEMFCs), empirical degradation models of different indexes of PEMFCs are established. Firstly, the simulation process and assumptions of PEMFC degradation are proposed. Secondly, the degradation simulation results including the performance and distribution indexes under the different degradation levels are conducted by AVL FIRE M. Finally, the empirical degradation models of performance and distribution indexes are established based on the above simulation results and experimental data. The results show that the relationship between the experimental and simulation results is established by the index of current density. The empirical degradation models of current density, average equilibrium potential on the cathode catalyst layer (CL), average membrane water content, average oxygen molar concentration on the cathode CL, and average hydrogen crossover flux are the linear function. The empirical degradation models of average exchange current density on the anode CL, average hydrogen molar concentration on the anode CL, and average oxygen crossover flux are the quadratic function. The empirical degradation model of average activation overpotential on the cathode CL is the quintic function. [ABSTRACT FROM AUTHOR]

In this study, a parallel hybrid electric vehicle produced within the scope of our project titled "Development of Fuel Efficiency Enhancing and Innovative Technologies for Internal Combustion Engine Vehicles" has been modeled. Firstly, a new rule-based control method is proposed to minimize fuel consumption and carbon emission values in driving cycles in the experimental model of the parallel hybrid electric vehicle produced within the scope of this project. The proposed control method ensures that the internal combustion engine (ICE) operates at the optimum point. In addition, the electric motor (EM) is activated more frequently at low speeds, and the electric motor can also work as a generator. Then, a new dataset was also created on a traffic-free racetrack with the proposed control method for fuel consumption estimation of a parallel hybrid electric vehicle using ECE-15 (Urban Driving Cycle), EUDC (Extra Urban Driving Cycle), and NEDC (New European Driving Cycle) driving cycles. The data set is dependent on 11 different input variables, which complicates the system. Afterward, the fuel estimation process is made with seven different machine learning methods (ML), and these methods are compared using the obtained data set. To avoid overfitting machine learning, two different test data sets were created. The Random Forest algorithm is the most suitable technique in terms of training and testing the fuel consumption model using correlation coefficient ( R 2 ), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) simulation appropriateness for both test datasets. Moreover, the random forest algorithm achieved an impressive accuracy of 97% and 90% for both test datasets, outperforming the other algorithms. Furthermore, the proposed method consumes 4.72 L of fuel per 100 km, while the gasoline-powered vehicle consumes 7 L of fuel per 100 km. The results show that the proposed method emits 4.69 kg less C O 2 emissions. The effectiveness of the Random Forest Algorithm has been verified by both simulation results and real-world data. [ABSTRACT FROM AUTHOR]

Presented are the materials for the certification of the MCU-HTR software package, which implements the Monte Carlo method, as applied to the calculation of the neutronic characteristics of high-temperature gas-cooled reactors and critical assemblies with fuel based on microparticles with a multilayer coating. A verification matrix for certification of the MCU-HTR software package has been developed. All calculations were carried out using a special methodology that enables taking into account the double heterogeneity of fuel arrangement in the core and a detailed full-scale description of the geometry of the calculated objects. The volume of results obtained is unique in terms of completeness and content for the practice of calculating such systems. The calculated reaction rate distributions, efficiency of control rods, and neutronic functionals for start-up experiments of the HTTR reactor with prismatic fuel blocks, the pebble bed HTR-10 reactor, and the experimental configurations implemented on the VHTRC critical assembly are presented. Disagreement between the calculated values and experimental data for the listed characteristics is estimated. [ABSTRACT FROM AUTHOR]

In this article, we present the results of the creation of an information-analytical system (IAS) developed as a tool for research and prediction of the behavior of the corium simulating a core melt of a nuclear reactor in the experiments. This was carried out to justify the safety of the use of nuclear energy according to specific requirements of a customer. The data loaded into the IAS were obtained on the basis of the National Nuclear Center of the Republic of Kazakhstan (NNC) as a result of modeling the processes occurring during severe accidents at nuclear installations. The experimental data obtained at the benches of NNC and characterizing the processes occurring during the interaction of the core melt of the nuclear reactor with coolants, structural materials and structural elements of nuclear reactors were classified and structured for the convenience of analyzing and processing the data obtained. The structure of the created IAS is shown and the analytical block is described in detail. [ABSTRACT FROM AUTHOR]

A formula for Maxwellian-Averaged Cross-Sections (MACS) at 30 keV is derived. Based on the presented formula, a linear relationship was found between the log ( MACS A 1. 4 ) and (N − Z) 2 A 2 of the target nucleus. From this relationship, a good agreement between the calculated MACS and the experimental data can be observed. It seems therefore possible to use this systematic law in order to analyze the experimental data. It would be useful in estimating the MACS of neighboring isotopes for which no experimental data are available. [ABSTRACT FROM AUTHOR]

The application of Building Information Modeling (BIM) on historic constructions is investigated in this paper by discussing, as a representative case study, the Galleria dell'Accademia di Firenze (Italy), thus showing as this tool can be used effectively for the management and maintenance activities of a historic museum. In fact, while BIM is already well-known as a powerful tool for the design and management of new buildings, its development in the field of historical construction is currently growing and attracting increasing interest in the scientific community. This paper proposes, in particular, an Information Model (IM) aimed to collect the structural information to be subsequently employed for numerical modeling of the building, thus representing the link between the real world and the computational models. The possibility to handle different types of information to be used for the management, maintenance, and modeling of existing constructions, as shown in this paper, encourages the popularization of this approach as an effective method to support cultural heritage (CH) conservation. [ABSTRACT FROM AUTHOR]

This paper considers a new meta-heuristic method called Grey Wolf optimizer (GWO). It is inspired by the behavior of grey wolves (Canis lupus) in nature, especially the leadership hierarchy and the hunting mechanism of a pack. This recent optimization method presents an interesting case of study given its promising performance in a variety of engineering fields. We are mainly focusing on the parameter identification problem given its crucial role in systems modeling and control. For this reason, the GWO is investigated to solve this kind of problem for an activated sludge process model used in wastewater treatment. The considered model is a nonlinear hybrid one. It has four unknown parameters to be identified. Simulation results are carried out and compared to other techniques: classical (Nelder–Mead method) and intelligent ones (Genetic Algorithm, Particle Swarm Optimization, Fireflies Algorithm, Cuckoo Search, and Teaching–Learning Based Optimization). The outcome of this comparison shows the satisfactory effectiveness and simplicity of the proposed method versus the others approaches. [ABSTRACT FROM AUTHOR]

We propose a reparameterized regression for the median of an extended Maxwell distribution that can be used when the response variable has a positive support. We obtain some structural properties of the distribution. The parameter estimates are obtained by maximum likelihood and Bayesian methods. Some influence measures and quantile residuals are defined. Several Monte Carlo simulations are reported for inference purposes. The new regression is applied to an experimental data set. [ABSTRACT FROM AUTHOR]

The paper presents a practical and relevant analytical calculation model for free turbine turboshaft working regimes and engine performance. The analytical calculation model is based on a post-processing method that analyzes a series of experimental data, specifically focusing on the percentage variations of the engine's main parameters from the minimum to the takeoff working regime. The experimental data were acquired from three different types of engines: TV2-117A turboshaft, AI-20K turboprop, and Viper 632-41 turbojet. The analysis method aimed to identify, through calculations, certain similarity parameters that exhibit nearly constant variations or variations within tight limits. These parameters can then be used as approximate constants in the calculation model. By utilizing these constants related to similarity parameters, a mathematical connection between different engine regimes is established; more exactly, for the engine data from a known to unknown regime. In the current case, only the engine data from the takeoff regime are requested to be known, and in this way, the other working regimes of several engines can be calculated. [ABSTRACT FROM AUTHOR]

This article considers a series of three experiments on the elastoplastic deformation of the V95 alloy, which is sensitive to the type of stress state. Experimental studies were carried out on a CL-EVM (complex loading) test machine on thin-walled tubular specimens during their deformation along two-link strain trajectories with 90 degree break angles. Experimental studies were carried out in the deviatoric plane with simultaneous combined action of axial force and torque on tubular specimens ( experiments). The scalar and vector properties of the V95 aluminum alloy are studied. It is found that, for the implemented complex strain trajectories in the form of two-link polygonal chains for the V95 material, the isotropy postulate is not fulfilled accurately enough in terms of scalar and vector properties. [ABSTRACT FROM AUTHOR]

The reconstruction of physical properties of a medium from boundary measurements, known as inverse scattering problems, presents significant challenges. The present study aims to validate a newly developed convexification method for a 3D coefficient inverse problem in the case of buried unknown objects in a sandbox, using experimental data collected by a microwave scattering facility at The University of North Carolina at Charlotte. Our study considers the formulation of a coupled quasilinear elliptic system based on multiple frequencies. The system can be solved by minimizing a weighted Tikhonov-like functional, which forms our convexification method. Theoretical results related to the convexification are also revisited in this work. [ABSTRACT FROM AUTHOR]

Deep eutectic solvents may develop a pivotal role in future technologies considering sustainability and safety as pivotal aspects for chemistry developments. The possible application of these fluids for heat transfer operations is of great relevance for which the knowledge of thermal properties such as thermal conductivity is required as well as inferring structure–property relationships which allow reverse design of the fluids according to the technological requirements. Considering the technological relevance of this property, the available literature on the thermal conductivity for deep eutectic solvents is critically discussed showing strengths and weaknesses. The analysis of the state-of-the-art shows the future needs in this research field considering the application of these solvents for thermal-related technologies. The review indicates the scarcity of reliable experimental data and the need of predictive methods, which could be used for process design and solvent screening purposes. Likewise, considering the relevance of developing predictive methods for in silico design of these fluids according to industrial needs, the available predictive theoretical approaches are analysed showing their reliability as well as future needs. Finally, considering the need of developing suitable and reliable structure–property relationship, the molecular level basis of thermal conductivity in deep eutectic solvents is discussed, showing the role of hydrogen bonding and the effects rising from the involved hydrogen bond donors and acceptors as well as the eutectic compositions. This work reports the first literature review and analysis on thermal conductivity for deep eutectic solvents considering an experimental and theoretical approach as well as providing support for the molecular basis of this technologically relevant property, thus contributing to the development of environmentally friendly materials for thermal-related technologies. [ABSTRACT FROM AUTHOR]

Copyright of WISTA Wirtschaft und Statistik is the property of Statistisches Bundesamt and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Soil shear strength is the most fundamental property when designing structures in the ground and should be carefully assessed and understood. Several empirical models were introduced to predict the shear strength of unsaturated soils. However, there is uncertainty regarding the applicability and sensitivity of these prediction models. This paper presents a comprehensive verification study to assess the reliability and validity of the existing theoretical models. The results obtained from the prediction models are compared to measured data using thirty experimental data sets. A performance classification program is also conducted to assess the suitability of the analytical models for different soil types as well as over a wide range of matric suctions, saturation degrees, soil densities, soil plasticity, and clay activity. The impact of each single parameter is clarified by the microstructure studies, which also provides insight into the mechanics of unsaturated soils. The results indicated that the applicability of models is more appropriate for sandy soils rather than for clayey ones. The performance of shear strength models tends to decrease with an increase in matric suction, initial density, plasticity index, and clay activity. It is, therefore, recommended that the shear strength estimation models should be carefully selected depending on the soil type and properties. Besides, the analysed results pointed out that the choice to assume the factor χ in the equation of Bishop equals the saturation degree is only suitable for medium-dense soils with low matric suction. This assumption is particularly not effective for clayey soils, or dense soils with high matric suction. [ABSTRACT FROM AUTHOR]

This paper develops a novel unified approach to designing suboptimal robust control laws for uncertain objects with different criteria based on a priori information and experimental data. The guaranteed estimates of the γ0, generalized H2, and H∞ norms of a closed loop system and the corresponding suboptimal robust control laws are expressed in terms of solutions of linear matrix inequalities considering a priori knowledge and object modeling data. A numerical example demonstrates the improved quality of control systems when a priori and experimental data are used together. [ABSTRACT FROM AUTHOR]

This paper presents a special analysis study about the gas turbine operating line, and an overall description of a gas turbines project, based on experimental data from two particular applications, in order to convert two different types of aero engines into the same engine configuration. The experimental works were carried out with the aim of converting an Ivchenko AI-20K turboprop and a Rolls-Royce Viper 632-41 turbojet into free turbine turboshaft engines, to be used in marine propulsion, and also to obtain an experimental database to be used in other gas turbine applications. In order to carry out the experimental work, the engines were tested in turbojet configuration, to simulate the free turbine load by using jet nozzles with different geometries of the outlet cross-section. Following the engines' tests, a series of measured data were obtained, through which it was possible to experimentally determine the operating line of some engine components such as the compressor, turbine, and exhaust jet nozzle. This paper is comprehensive and useful through its scientific and technical guidelines, the operation curves coming in handy in the thermodynamic analysis and testing methodology for researchers dealing with similar applications. [ABSTRACT FROM AUTHOR]

The study of the rheological properties of a lubricant allows for the assessment of the structure's durability in which they are used. Computer engineering enables the prediction of the structure performance using refined mathematical models of its materials. This paper presents an experimental investigation of the rheological behavior of a lubricant that is actively used in bridge structures. The paper proposed a methodology for determining the rheological characteristics of the lubricant using a rotational viscometer. Additionally, the article performed the task of identifying the mathematical model of the lubricant behavior based on the Maxwell body, using two approaches: the Anand model and the Prony series. The proposed models allow for numerical modeling of the structure's performance throughout their lifecycle within the scope of computer engineering. [ABSTRACT FROM AUTHOR]

Culverts are ubiquitous hydraulic structures used in cross-drainage and agricultural water systems, especially at farm outlets in irrigation systems. Gate control adds hydraulic complexity to culvert water flow, yet it has hardly been studied. This study has two objectives: (1) to classify the operational conditions of gated culverts, and (2) to establish an experimental data set for analyzing discharge relationships based on that classification. A theoretical inlet–outlet control–based classification resulted in 22 inlet control and 19 outlet control cases, organized in 4 inlet and 5 outlet control groups. A total of 230 laboratory tests were conducted. The laboratory setup reproduced the conditions of inlet submerged with outlet in free surface (one of four inlet control groups) and all conditions except inlet in free surface with outlet submerged (four of five outlet control groups) of the inlet and outlet control groups, respectively. Comparison with existing classification schemes for gated culverts confirmed the suitability of the proposed scheme and provided further insight into flow classification. The discharge grouped by narrow ranges of gate openings was found to follow a power-law relationship of head with an exponent between 0 and 1. Flow transition regions between groups of conditions were examined, suggesting parabolic transition curves. The gate opening was found to be the dominant variable, resulting in a direct proportional effect on discharge, i.e., data corresponding to greater gate openings enveloped those with smaller openings. The slope's influence could not be discerned within the slope range tested. Discharge estimation based on a dimensionless, empirical model produced reasonable results, although its case-dependent nature requires further research to develop operational hydraulic models for determining discharge through gated culverts. Application of the proposed classification scheme could help develop these hydraulic tools with sufficient accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Épidémiologie et Santé Animale is the property of Association pour l'Etude de l'Epidemiologie des Maladies Animales (AEEMA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Currently, electric mobility and autonomous vehicles are of top priority from safety, environmental and economic points of view. In the automotive industry, monitoring and processing accurate and plausible sensor signals is a crucial safety-critical task. The vehicle's yaw rate is one of the most important state descriptors of vehicle dynamics, and its prediction can significantly contribute to choosing the correct intervention strategy. In this article, a Long Short-Term Memory network-based neural network model is proposed for predicting the future values of the yaw rate. The training, validating and testing of the neural network was conducted based on experimental data gathered from three different driving scenarios. The proposed model can predict the yaw rate value in 0.2 s in the future with high accuracy, using sensor signals of the vehicle from the last 0.3 s in the past. The R 2 values of the proposed network range between 0.8938 and 0.9719 in the different scenarios, and in a mixed driving scenario, it is 0.9624. [ABSTRACT FROM AUTHOR]

Despite the increasing prevalence of nonalcoholic fatty liver disease (NAFLD) worldwide, its complex pathogenesis remains incompletely understood. The currently stated hypotheses cannot fully clarify the interrelationships between individual pathogenetic mechanisms of the disease. No appropriate health strategies have been developed for treating NAFLD. NAFLD is characterized by an accumulation of triglycerides in hepatic cells (steatosis), with the advanced form known as nonalcoholic steatohepatitis. In the latter, superimposed inflammation can lead to fibrosis. There are scientific data on NAFLD's association with components of metabolic syndrome. Hormonal factors are thought to play a role in the development of metabolic syndrome. Endogenous melatonin, an indoleamine hormone synthesized by the pineal gland mainly at night, is a powerful chronobiotic that probably regulates metabolic processes and has antioxidant, anti-inflammatory, and genomic effects. Extrapineal melatonin has been found in various tissues and organs, including the liver, pancreas, and gastrointestinal tract, where it likely maintains cellular homeostasis. Melatonin exerts its effects on NAFLD at the cellular, subcellular, and molecular levels, affecting numerous signaling pathways. In this review article, we discuss the experimental scientific data accumulated on the involvement of melatonin in the intimate processes of the pathogenesis of NAFLD. [ABSTRACT FROM AUTHOR]