Simplified Empirical Model Research Articles

Improving Shear Strength Prediction in Steel Fiber Reinforced Concrete Beams: Stacked Ensemble Machine Learning Modeling and Practical Applications

Existing machine learning (ML) models often encounter challenges in accurately predicting the shear strength of steel fiber reinforced concrete (SFRC) beams, mainly due to a lack of generalization. This study introduces an advanced stacked ensemble ML architecture to overcome this limitation by utilizing a comprehensive data set of 394 experimental observations and a 20-feature matrix. The model exhibits exceptional performance with a mean absolute error of 0.391 and a correlation coefficient (R2) of 93.7%, and surpasses traditional ML algorithms. Furthermore, a sensitivity analysis of the developed model yields that shear strength is highly responsive to the shear span-to-effective depth ratio, with an increase from 1 to 4 resulting in a significant reduction (about 50%) in strength. Increasing the percentage of longitudinal steel from 1 to 2% leads to a 14.6% gain, whereas doubling its yield strength has a more modest 3.7% effect. Increasing the compressive strength of concrete from 25 to 50 MPa, notably increases the shear strength by 19.6%. Fiber length, diameter, and aspect ratio exhibit varying impacts, with shear strength most influenced by the fiber volume fraction, which leads to a peak enhancement of 30.7% at 2% fibrous volume; however, the tensile strength of fibers minimally affects the shear strength. Additionally, this research presents a simplified empirical model to predict the shear strength of SFRC beams based on the key determinants. This model employs the iterative Gauss–Newton algorithm, demonstrates reasonable predictive capability, and boasts an R2 of 83.3% and mean prediction-tested strengths of around 1.039. The practical implications of these findings are substantial for the construction industry as they enable a more accurate and reliable design of SFRC beams, optimize material usage, and potentially reduce construction costs as well as enhance structural safety.

Empirical modelling of a semihermetic reciprocating compressor for different CO2-based mixtures

Mixing CO2 with other refrigerants gives carbon dioxide new thermophysical properties, such as higher critical temperature or lower working pressures.However, most of these new mixtures havenotyetbeenevaluatedexperimentally, introducing a lack of knowledge about how the main components of a refrigerating plant will operate with these blends.One clear example is the compressor, whose operationdirectly affects the performance and energy consumption of theplant. Accordingly, this work evaluates experimentally the behaviour of a CO2 semi-hermetic reciprocating compressor working with four different CO2-based mixtures of CO2/R32, CO2/R290, CO2/R1270 and CO2/R1234yf. The analysis covers the parameters of volumetric and global efficiency, discharge temperature, mass flow rate, and electrical power consumption, where noticeable differences are shown in terms of efficiencies, affecting the mass flow rate and the electrical power consumption significantly, and, to a lesser extent, the discharge temperature. The experimental results are compared with the standardized models from UNE-12900 and AHRI-540, proposing a simplified empirical model with a prediction error below 4% for all analysed mixtures and an extensive model for other CO2-based mixtures.

Stability of Ficus virens-Reinforced Slopes Considering Mechanical and/or Hydrological Effects

Vegetation reinforcement for slopes has been recognized as an environment-friendly measure and has been widely adopted in engineering practice. However, the stability analysis of vegetation reinforcement for slopes has mainly been discussed for an infinite slope and common grass and scrub plant species. This study proposes a procedure for analyzing the stability of a finite slope reinforced with Ficus virens under transpiration and rainfall conditions. A simplified empirical model for characterizing root cohesion and triaxial testing is utilized to quantify the mechanical effect of roots on rooted soil shear strength. A numerical modeling technique with COMSOL Multiphysics is used to investigate the hydrological effect of roots. The combination of these two effects forms an expression for the unsaturated shear strength of rooted soils. The stability of a vegetated soil slope is then investigated in terms of safety factors and failure mechanisms, with/without considering rainfall. The results show that the stability solutions without consideration of the roots’ mechanical and/or hydrological effects are overly conservative. The hydrological contribution to slope stability could also be partially preserved under short-term rainfall, and as rainfall continues, the hydrological effect is weakened, while the mechanical reinforcement is assumed to be unchanged. In the meantime, the hydrological contribution to slope stability is susceptible to atmospheric conditions, which indicates a favorable effect on water uptake and an adverse consequence for water infiltration.

A simplified machine learning empirical model for biomimetic crack healing of bio-inspired concrete

Bio-inspired self-healing is an effective technique to extend the durability and longevity of concrete infrastructures. However, factors influencing biomimetic crack healing need to be understood for effective strategies. This study aims to develop an interpretable empirical prediction model for self-healing concrete using Multivariate linear regression (MVLR). Other machine learning (ML) techniques like deep neural networks (DNN), extreme gradient boosting (XGBoost), and convolutional neural network (CNN) were also employed for comparison. Although the XGBoost model performed best with R2 of 0.95 and the least statistical errors, however, MVLR offered a more interpretable approach. The developed empirical formulation revealed that immobilizer and bacterial strain had the strongest impact on biomimetic crack healing, followed by initial crack width and healing duration. The formulated mathematical expression was moreover experimentally validated, yielding minimal Mean Squared Error and Root Mean Squared Error values of 0.0057 and 0.0588, respectively. Thus, these findings can be utilized for the effective implementation of bio-inspired concrete in the field of construction.

Potential energy savings of air lubrication technology on merchant ships

As the reduction of greenhouse gas emissions has become an important issue, measures and devices to reduce energy consumption are in increasing demand. In this study, the potential energy saving due to the application of air lubrication technology in merchant ships is analyzed. We propose a simplified empirical model, covering three different air lubrication technologies, based on the experimental results and assumptions taken in the existing studies. The bottom surface area covered with air is important for the efficiency of the air lubrication system, according to the sensitivity analysis. From the global fleet analysis, net-percentage power saving varies according to the operational profile as well as the technology. Net-percentage power savings of 2–5% from air bubble, 8–14% from air layer, and 16–22% from air cavity technology were obtained assuming calm-water conditions. The methodology can be adopted in early design stage and fleet-wide analyses of various energy-saving measures.

Experimental study of a sustainable cooling process hybridizing indirect evaporative cooling and mechanical vapor compression

The hybrid indirect evaporative cooling-mechanical vapor compression (IEC-MVC) process is an emerging cooling technology that combines the advantages of IEC and MVC, i.e., effective temperature and humidity control, high energy efficiency, and low water consumption. This paper presents an experimental study of the hybrid IEC-MVC process. A 1-Rton pilot is fabricated by connecting IEC and MVC in series, and its performance is evaluated under different operating conditions (outdoor air temperature and humidity, air flowrate, compressor frequency). Results revealed that the outdoor air temperature and humidity could be lowered to 5–15 °C and 5–10 g/kg, respectively. The IEC handles 35%–50% of the total cooling load, and the energy consumption can be reduced by 15%–35% as compared to standalone MVC. Moreover, the condensate collected from the evaporator can compensate for >70% of water consumption in IEC, making the system applicable in arid regions. Based on the derived results, a simplified empirical model is developed for rapid evaluation of the IEC-MVC process, and the energy-saving potential in major cities of Saudi Arabia is estimated.

Numerical and Empirical Models for Service Life Assessment of RC Structures in Marine Environment

The service life prediction of reinforced concrete (RC) structures in marine environment is essential in structural repair and health monitoring. In this paper, a numerical model for predicting the service life of reinforced concrete is first developed which considering the time-varying boundary of chloride concentration, critical chloride concentration and density of corrosion current. Based on the model, the effects of water–cement ratio, reinforcement diameter, concrete cover thickness and critical chloride ion concentration on the service life and deterioration duration of RC structures are investigated. The key factors affecting the service life of reinforced concrete structures are determined. More importantly, based on regression analysis, a new simplified empirical model for predicting the service life of RC structures is also developed. It provides a fast assessment tool for practical engineers. Both the numerical model and empirical model validated are suitable for practical engineering applications. The results show that with the increase of water–cement ratio, the service life of reinforced concrete structure decreases exponentially. And with the increase of the thickness of the concrete cover, the service life, deterioration duration, and safety reserve increase linearly. However, the influence of the diameter of the reinforcing bar on the service life can be ignored.

A simplified empirical model to estimate oxygen relaxivity at different magnetic fields.

The change in longitudinal relaxation rate (R1 ) produced by oxygen has been used as a means of inferring oxygenation levels in magnetic resonance imaging in numerous applications. The relationship between oxygen partial pressure (pO2 ) and R1 is linear and reproducible, and the slope represents the relaxivity of oxygen (r1Ox ) in that material. However, there is considerable variability in the values of r1Ox reported, and they have been shown to vary by field strength and temperature. Therefore, we have compiled 28 reported empirical values of the relaxivity of oxygen as a resource for researchers. Furthermore, we provide an empirical model for estimating the relaxivity of oxygen in water, saline, plasma, and vitreous fluids, accounting for magnetic field strength and temperature. The model agrees well (R2 = 0.93) with the data gathered from the literature for fields ranging from 0.011 to 8.45 T and temperatures of 21-40 °C. This provides a useful resource for researchers seeking to quantify pO2 in simple fluids in their studies, such as water and saline phantoms, or bodily fluids such as vitreous fluids, cerebrospinal fluids, and amniotic fluids.

Relationship between 25 Hydroxyvitamin D, Overweight/Obesity Status, Pro-Inflammatory and Oxidative Stress Markers in Patients with Type 2 Diabetes: A Simplified Empirical Path Model.

Vitamin D deficiency is highly prevalent in patients with overweight/obesity and type 2 diabetes (T2DM). Herein, we investigated the relationship between vitamin D status and overweight/obesity status, insulin resistance (IR), systemic inflammation as well as oxidative stress (OS). Anthropometric and laboratory assessments of 25-hydroxyvitamin D (25(OH)D) and glycemic, pro-inflammatory and OS biomarkers were performed in a sample of 47 patients with T2DM who were divided into categories based on overweight and degree of obesity. The main findings were: the overweight/obesity status correlated negatively with the degree of serum 25(OH)D deficiency (ρ = −0.27) with a trend towards statistical significance (p = 0.069); the homeostasis model assessment of insulin resistance (HOMA-IR) was significantly different (p = 0.024) in patients with 25(OH)D deficiency, as was total oxidant status (TOS) and oxidative stress index (OSI) in patients with severe serum 25(OH)D deficiency as compared to those with 25(OH)D over 20 ng/mL (TOS: p = 0.007, OSI: p = 0.008); and 25(OH)D had a negative indirect effect on TOS by body mass index (BMI), but BMI was not a significant mediator of the studied relationship. In a setting of overweight and increasing degree of obesity, patients with T2DM did not display decreasing values of 25(OH)D. Subjects with the lowest values of 25(OH)D presented the highest values of BMI. Patients with 25(OH)D deficiency were more insulin resistant and showed increased OS but no elevated systemic inflammation. The negative effect of 25(OH)D on TOS did not seem to involve BMI as a mediator.

Development of a compact and robust kinetic mechanism for furan group biofuels combustion in internal combustion engines

A compact kinetic reaction mechanism for simulating the oxidation of the unsaturated furanic fuels including furan, 2-methylfuran (MF2) and 2,5-dimethylfuran (DMF) is proposed in this work. The mechanism is developed by integrating the major reaction pathways for the three furanic fuel components into a toluene reference fuel reaction mechanism. The sub-mechanism describing the formation and growth of polycyclic aromatic hydrocarbons up to pyrene is also incorporated so that the prediction of soot formation is enabled. The major reaction pathways for these furanic fuels are derived from the detailed furanic fuel reaction mechanism in the literature via a systematic selection and extraction procedure. An advanced genetic algorithm is applied to automatically optimize the rate parameters for the major furanic fuel reaction pathways. In addition, a simplified empirical soot model is embedded in the mechanism for simulating the soot formation process in the oxidation of the furanic fuels. The resulting mechanism, consisting of 145 species and 643 reactions, has been evaluated against the ignition delays, speciation profiles, laminar flame speeds as well as the soot mass measured from the combustion of the furanic fuels in the literature. The simulation results in general match satisfactorily well with the experimental data, suggesting the high performance of the proposed mechanism. The performance of the reaction mechanism for engine combustion simulation is also tested. A four-cylinder compression ignition engine is simulated using a coupled KIVA4-CHEMKIN code package. The influences of DMF on the engine combustion characteristics and soot emissions are investigated.

Differences in carbon isotope discrimination between angiosperm and gymnosperm woody plants, and their geological significance

For most of the Phanerozoic Eon, Earth’s woody vegetation has been dominated by C3 plants - predominantly gymnosperms - with angiosperms only emerging as the dominant plant group as CO2 declined during the Cenozoic (66 Ma onward). At present, differences in carbon isotope discrimination (Δ13C) between angiosperm and gymnosperm plants are relatively small (2–3 ‰), but an increasing body of evidence points to larger differences across geological times (up to 6–7 ‰), potentially associated with varying environmental conditions and atmospheres (i.e. concentrations of atmospheric carbon dioxide, [CO2], and oxygen, [O2] could have ranged from ∼180 to 1100 ppm, and ∼15 to 25%, respectively, across the past 250 Ma). Yet, differences in Δ13C between the two plant groups, and their potential link to climatic and environmental changes, have not yet been fully explored and understood. Here, we combine a comprehensive ab initio model of discrimination, with a recent model of plant eco-physiology based on least-cost optimality theory, to show how differences in Δ13C between angiosperms and gymnosperms arise. We train the comprehensive model using a very large (n>7000) database of leaf and tree ring data spanning the past 110 years. We find that averaged differences in Δ13C between angiosperm and gymnosperms decrease modestly with atmospheric [O2]:[CO2] ratios, and increase strongly with vapor pressure deficit (D). These relationships can be explained by three key physiological differences: (1) the ratio of cost factors for transpiration to carboxylation (higher in angiosperms); (2) the ratio of mesophyll to stomatal conductances of CO2 (lower in gymnosperms); and (3) differences in photorespiration. In particular, the amount of CO2 released from photorespiration per oxygenation reaction, λ, is generally lower in gymnosperms than in angiosperms. As a result of these factors, Δ13C is more sensitive to [CO2] in angiosperms, and to D in gymnosperms. We propose a simplified empirical model to account for this behaviour, and test it against isotopic data from leaves, tree rings and previously-published plant chamber experiments, along with geological data from the Cenozoic. Overall, these data agree with our model over a range of [O2]:[CO2] ratios from 100 to 650 mol mol−1 (equivalent to a CO2 range around 323–2100 ppm at 21% O2), and D levels between 0.45 and 1.1 kPa (R2 = 0.51, RMSE = 1.49 ‰). Our simplified empirical model offers a new explanation for secular trends in the geological record, and suggests a way forward to improve paleo-[CO2] proxies based on terrestrial discrimination models by incorporating the effects of [O2], phylogeny, and photorespiration. Lastly, the framework predicts that the average difference in Δ13C between woody C3 plant groups will increase in the future if both [CO2] and global D continue to rise as suggested by projections.

Simplified empirical model to predict biomass thermal conversion products

The objective of this study was to develop empirical models for predicting the obtained products from lignocellulosic biomass through alternative technologies. The model can be applied for further studies to provide the insight information for bio-refinery optimization and planning where suitable biomass characteristics are necessary for the conversion pathways to achieve the target products. To build the regression model, 330 case studies including the use of 66 lignocellulosic biomasses in 5 technologies were simulated using Aspen plus 11.0 software. Five correlations between biomass characteristics and five product yields were then successfully developed with R2 equals to 0.99. The results indicated that almond shell with high VM, C, H contents and low FC, O, N contents produced the highest syngas, hydrogen, power and liquid fuels product yields (7121 kJ/kgbiomass, 0.051 kg/kgbiomass, 6474 kJ/kgbiomass and 0.12 L/kgbiomass, respectively). Among the local biomass candidates, palm empty fruit bunch (PEFB) was the preferable choice.

New interlocking inter-module connection for modular steel buildings: Simplified structural behaviours

Inter-module connections (IMCs) are the key component which transforms individual building modules into complete modular buildings. Structural design of these connections is, however, reported to be a major challenge, due to a lack of knowledge of the structural performance. Therefore, in this study, the structural behaviours of the newly proposed interlocking (IL) IMC, which incorporates interlocking components to improve the constructability and shear force–displacement (V-x) behaviour, are investigated. The simplified model previously proposed for the shear behaviour of the experimental IL connection specimens is reviewed, and numerical simulations are undertaken using ABAQUS to investigate the effect of the loading and boundary conditions on the V-x behaviour. Then, extended numerical models are developed based on a more realistic geometry which has two bolts per column to improve the resistance to in-plane rotation. A simplified empirical model is established, in which the V-x behaviour of the more realistic connections is represented by exponential functions, allowing for the effect of the axial load. Next, the numerical model is extended, and the axial force–displacement and bending moment-rotation behaviours are evaluated, after which semi-empirical models are derived. In this way, simplified models are developed which can predict the structural behaviours of the interlocking IMC.

An Underwater Acoustic Channel Modeling for Internet of Things Networks

Interest in wideband and medium distance underwater acoustic communication systems is increasing due to the practical application of underwater Internet of Things (IoT) networks. In this paper, we propose a simplified empirical channel model for the medium distance underwater acoustic channels based on real measurement results. The simple and tractable channel model is critical for the development of advanced underwater communications technology. The underwater channel measurements were performed at 20 m sea water depth, the transmitters (TXs) were located at 5 m and 15 m from the bottom, the receivers (RXs) were located at 4 m, 8 m, 12 m, and 16 m from the bottom, and the TX–RX distances were 21 m, 71 m, 127 m, and 273 m. We derived the path loss from the measured dataset, and modified the log-distance model to create a model suitable for an underwater IoT channel. Numerical results show that the proposed model is accurate and reliable enough to use in the development of advanced underwater communication technologies.

Simplified structural behaviours of post-tensioned inter-module connection for modular buildings

When designing modular buildings, the structural behaviour of the inter-module connections (IMCs) must be simplified so they can be incorporated in the structural model. However, the existing models for the shear, axial and moment-rotation behaviour are limited, and further study is required to develop improved models. In this study, the shear, axial and moment-rotation behaviours of a post-tensioned IMC are investigated. A numerical model is developed and calibrated based on the shear behaviour obtained from experiments. Following the experiments, a simplified empirical model is proposed for the shear behaviour. The numerical model is then extended to determine the axial and moment-rotation behaviour. Simplified analytical models are derived and compared with the numerical results. Further, the numerical results are compared with the behaviour of other existing IMCs, for which experimental data are available in the literature. In this way, simplified models which can predict the shear, axial and moment-rotation behaviour of the post-tensioned IMC are developed. The developed simplified models can be used to predict the behaviour of modular structures with the newly proposed post-tensioned IMC.

A New Approach for Probabilistic Risk Assessment of Ship Collision with Riverside Bridges

The configuration of riverside bridges, such as the spatial distribution, wading status, and ship accessibility of piers, is generally different from river‐crossing bridges. Thus, the ship collision risk of riverside bridges cannot be assessed using conventional assessment methods applicable to river‐crossing bridges. The aim of this paper is, therefore, to develop a new probabilistic method for assessing the risk of ship collision with riverside bridges. First, a fully probabilistic framework for assessing the ship‐bridge collision risk is presented. Second, a new probabilistic hazard analysis model of ship collision with riverside bridges is proposed, based on a combined study of riverside bridge characterization and an improved yaw ship collision model. A simplified empirical model for evaluating ship‐bridge collision force is then adopted, and the probabilistic distribution of the collision force is obtained based on Monte Carlo simulation. Furthermore, finite element simulation is conducted to estimate the collapse probability of piers. Finally, the method developed is applied to the probabilistic assessment of ship collision risk with riverside bridges located at Shabin Road, Chongqing, China. The results show that the risk of ship‐bridge collision at Shabin Road is low to moderate. The example demonstrated indicates that the methodology introduced in this paper is capable of assessing the ship‐bridge collision risk in a concise and rapid way.

Damage Assessment of Reinforced Concrete Buildings Considering Irregularities (RESEARCH NOTE)

Structural damage can be controlled in performance based seismic design (PBSD) according to the requirement under a certain hazard level. During strong ground motion (GM) such buildings suffer minor to major damages depending on the shaking level of GM. The available damage assessment methods are complex, tedious and time-consuming procedure. In the present study, a simplified empirical model has been proposed that computes the GDI in a single step using the engineering demand parameters (EDPs) namely joint rotation, Inter storey drift (IDR), peak roof displacement. It has been found that the proposed method gives results of GDI near to Park-Ang model. It has been observed that the ground storey suffers maximum damage for all cases. Further, a relationship has been established between ground story DI and global DI. The proposed model effectively berlongferestimates reliable DI and could be used as a powerful tool for estimating seismic damage in buildings, especially for massive structures.

Simplified Regional Prediction Model of Long-Term Trend for Critical Frequency of Ionospheric F2 Region over East Asia

To improve the accuracy of predictions and simplify the difficulty with the algorithm, a simplified empirical model is proposed in developing a long-term predictive approach in determining the ionosphere’s F2-layer critical frequency (foF2). The main distinctive features introduced in this model are: (1) Its vertical incidence sounding data, which were obtained from 18 ionosonde stations in east Asia between 1949 and 2017, used in reconstructing the model and verification; (2) the use of second-order polynomial and triangle harmonic functions, instead of linear ones, to obtain the relationship between the seasonal vs. solar-cycle variations of foF2 and solar activity parameters; (3) the flux of solar radio waves at 10.7 cm and sunspot number are together introduced in reconstructing the temporal characteristics of foF2; and (4) the use of the geomagnetic dip coordinates rather than geographic coordinates in reconstructing the spatial characteristics of foF2. The statistical results reveal that foF2 values calculated from the proposed model agree well with the trend in the monthly median statistical characteristics obtained from measurements. The results are better than those obtained from the International Reference Ionosphere model using both the CCIR and URSI coefficients. Furthermore, the proposed model has enabled some useful guidelines to be established for a more complete and accurate Asia regional or global model in the future.

Comparative study of extracellular recording methods for analysis of afferent sensory information: Empirical modeling, data analysis and interpretation

BackgroundPhysiological studies of sensorial systems often require the acquisition and processing of data extracted from their multiple components to evaluate how the neural information changes in relation to the environment changes. In this work, a comparative study about methodological aspects of two electrophysiological approaches is described. New methodExtracellular recordings from deep vibrissal nerves were obtained by using a customized microelectrode Utah array during passive mechanical stimulation of rat´s whiskers. These recordings were compared with those obtained with bipolar electrodes. We also propose here a simplified empirical model of the electrophysiological activity obtained from a bundle of myelinated nerve fibers. ResultsThe peripheral activity of the vibrissal system was characterized through the temporal and spectral features obtained with both recording methods. The empirical model not only allows the correlation between anatomical structures and functional features, but also allows to predict changes in the CAPs morphology when the arrangement and the geometry of the electrodes changes. Comparison with existing method(s)This study compares two extracellular recording methods based on analysis techniques, empirical modeling and data processing of vibrissal sensory information. ConclusionsThis comparative study reveals a close relationship between the electrophysiological techniques and the processing methods necessary to extract sensory information. This relationship is the result of maximizing the extraction of information from recordings of sensory activity.

Simplified 1D Empirical Model for Volumetric Behavior of High-Carbonate Clay

Simplified 1D Empirical Model for Volumetric Behavior of High-Carbonate Clay