Column Length Research Articles

Potentiality of alginate-yeast biosorbent for biogas purification

The paper discussed the current research on the applicability of biosorbents for the purification of biogas, particularly the decrease of H2S by using encapsulated or embedded biological biomass. This study investigated the potential of alginate-yeast biosorbent (AlgY) for biogas purification, focusing on hydrogen sulfide (H2S) removal. A biogas column test was conducted to compare the biosorption efficiency of AlgY and pure alginate beads. Using Response Surface Methodology (RSM), the effects of column length, acquisition time, and biosorbent type were evaluated for CH4, CO2, and H2S removal. Results depicted significant H2S reduction, with AlgY achieving a p-value of < 0.0001 and a high correlation coefficient (R2 = 0.9518). The relatively high correlation coefficient (R2) of the tested quadratic model of all the responses were recorded (R2; 0.5560, 0.5048, and 0.9518 for CH4, CO2, and H2S respectively). According to the studies’ preliminary findings, the type of biosorbent has a significant role in determining the biosorption effectiveness. The ANOVA of model terms depicted a significant p-value (p < 0.05) indicated a potential alginate-yeast (AlgY) biosorbent for H2S purification or reduction.

Periodic Burst Freezing in a Water-Filled Capillary Tube.

Water-filled porous structures are ubiquitous components in life sciences and engineering. At sufficiently low temperatures, the water inside the porous structures can freeze, triggering the frost heave effect and causing problems such as permafrost, frost damage, and frostbite. In this study, we report a unique pattern of frost heat release through periodic bulging and bursting at the end of a water column inside a capillary tube. When water freezes, it expands in volume and attempts to drain out. However, surface tension can hinder the flow of water, resulting in the formation of a bulge that periodically bursts when the spherical molecule reaches a critical threshold. We determined that the critical contact angle of the bulge is approximately 135°, which is balanced by the surface tension at the three-phase line of contact. The size of the bulge increases nonlinearly with the diameter of the capillary tube, while the number of periodic repetitions is inversely proportional to the tube diameter and directly proportional to the length of the water column. These findings provide insights into the interaction between surface tension and frost heave, which has important implications for the design and optimization of microfluidic devices with improved resistance to freezing.

Hydrogen recovery from steam methane reforming using the ITQ-12 zeolite

The aim of this work is to investigate the potential use of the ITQ-12 zeolite in a PSA process to obtain purified hydrogen from the SMR product stream using molecular simulation. Since the main components of the product stream are hydrogen and carbon dioxide, we put the focus on the separation of these two gases. The separation of hydrogen from the other components (methane, carbon monoxide and nitrogen) will be briefly touched upon as well. From inspection of the adsorption isotherms of carbon dioxide and hydrogen in ITQ-12 we found that the former gas dominates at industrially relevant conditions (311 K and 16 ⋅105 Pa). Breakthrough curves reveal that the ITQ-12 zeolite is likely to perform well in a PSA process for the separation of hydrogen from carbon dioxide. We found that in general higher column lengths and lower gas feed velocities are favourable for a good separation while higher gas feed velocities are favourable for the cleansing of carbon dioxide from the column. For the full mixture it is necessary to employ longer column lengths in order to separate hydrogen from the other components. This is because nitrogen and carbon monoxide exhibit retention times similar to hydrogen, though the latter still travels through the column the fastest. Alternatively the use of ITQ-12 could be combined with other separation techniques, where ITQ-12 is used to mainly remove CO2 and CH4 from the SMR product stream. These findings suggest that SMR could become an economically viable way to produce hydrogen by using ITQ-12 in the separation process.

A Comparative Study of Sound Resonance Using Arduino-Based Ultrasonic Sensors and Visualization Analysis with Python

<p>In the modern era, the study of sound resonance in physics laboratories has increasingly incorporated technological tools to improve the experimental process. While conventional approaches to resonance experiments remain common, they often face challenges related to equipment setup and limited real-time data analysis. This research compares conventional methods with Arduino-based techniques, combined with Python for data visualization and analysis, in sound resonance experiments. The integration of Arduino microcontrollers and ultrasonic sensors offers a more accessible and streamlined alternative to conventional resonance measurement techniques, facilitating improved data collection and interpretation. Data is gathered using PLX DAQ software connected to the Arduino system, with the results visualized and analyzed using Python tools. The experiments show that the average air column length when the water in the reservoir was lowered is 16.10 cm, with an error of 3.04%, and when the water was raised, the average length is 15.60 cm, with an error of 5.98%. A 512 Hz sound source was used to determine the fundamental frequency, revealing slight variations due to changes in the measurement distance. Specifically, the fundamental frequency was recorded as (528 ± 5) Hz when the water level was lowered and (545 ± 8) Hz when it was raised. This study highlights the positive role of technology in enhancing physics education and research, particularly in sound resonance studies.</p>

Geotechnical response of Strip footing resting on oil-contaminated sand improved with stone columns: numerical study

Ground improvement techniques are frequently employed in construction sites characterized by weak soil conditions that may result in suboptimal performance. The use of ordinary and encased stone columns aims to enhance endurance, shear strength, and soil hardness, thereby mitigating settlement issues and expediting the consolidation of contaminated sand soils. In this research, a comprehensive investigation involving 74 cases was conducted to assess the behavior of both ordinary stone columns and encased stone columns under strip footing in contaminated sand subgrade. The objective was to discern the impact and characteristics of encapsulation in comparison to encapsulated stone columns, employing a Finite Element Model (FEM) within the PLAXIS 3D software package. The study focused on stone columns with two different diameters (D = 0.5 m and 0.6 m), while the column length was 12 m across all cases. As the contamination level increases—at the variable contaminated sand levels of (2%, 5%, and 10%)—the viscosity of the soil rises, leading to a reduction in cohesion between soil granules. Consequently, the internal friction angle decreases, with values diminishing from 31° to 27° and then to 24°, respectively. The clean sand was placed to achieve relative density, a medium dense sand state (Dr = 50%). The two categories of stone columns examined were ordinary stone columns (OSC) without encapsulation and encased stone columns (ESC) encapsulated with varying degrees of hardening. Results obtained at variable internal friction angles (35, 40, and 45 degrees) revealed a notable increase in the endurance of ordinary stone columns on untreated soil conditions, reaching 100%, 125%, and 148% for column diameters (D = 0.5 m) and 130%, 145%, and 180% for column diameters (D = 0.6 m), respectively. The corresponding increase in the endurance of encased stone columns under untreated soil conditions was found to be 275%, 33%, and 345% for column diameters (D = 0.5 m) and reached 313%, 350%, and 375% for column diameters (D = 0.6 m), respectively. All preceding results were obtained under the condition of a contaminated sand content of 5%. The investigation aimed to provide valuable insights into the performance and efficacy of ordinary stone columns (OSC) and encased stone columns (ESC) as a geotechnical solution for improving soil conditions in construction projects.

Seismic Performance of Concrete Columns Reinforced with Hot-Rolled Thermo-mechanically Treated Steel Bars

ABSTRACT The details of experimental testing of full-scale reinforced concrete columns are presented in this paper. The columns were reinforced with hot-rolled thermo-mechanically treated bars with uncertain yield strength which influences (particularly) the splice length demand and column response to seismic loads. The testing was carried out using quasi-static cyclic or monotonic loading under a constant axial load to study the seismic behaviour of the columns. The parameters of the study included lap splices, cold joints and lateral load scenarios. The damage concentration was higher close to the end of the dowel bar (as opposed to the column base) for the lap-spliced columns subjected to cyclic loading due to larger slippage in the dowel bars. Conversely, the damage was the least in a similar column subjected to monotonic loading which also exhibited the largest lateral load capacity and highest ductility. The influence of shear distortion was insignificant on the column free-end deflection. The pre-peak stiffness and lateral load capacity were less for the lap spliced columns tested under cyclic loading as a result of deficient development length due to unintended increase in the rebar yield strength. The lateral load capacity of the column was uninfluenced by the cold joint at the column base although it reduced the column ductility by nearly 25% compared to a similar column without a cold joint.

Prediction of crippling load of I-shaped steel columns by using soft computing techniques

This study is primarily aimed at creating three machine learning models: artificial neural network (ANN), random forest (RF), and k-nearest neighbour (KNN), so as to predict the crippling load (CL) of I-shaped steel columns. Five input parameters, namely length of column (L), width of flange (bf), flange thickness (tf), web thickness (tw) and height of column (H), are used to compute the crippling load (CL). A range of performance indicators, including the coefficient of determination (R2), variance account factor (VAF), a-10 index, root mean square error (RMSE), mean absolute error (MAE) and mean absolute deviation (MAD), are used to assess the effectiveness of the established machine learning models. The results show that all of the three ML (machine learning) models can accurately predict the crippling load, but the performance of ANN is superior: it delivers the highest value of R2 = 0.998 and the lowest value of RMSE = 0.008 in the training phase, as well as the highest value of R2 = 0.996 and the smaller value of RMSE = 0.012 in the testing phase. Additional methods, including rank analysis, reliability analysis, regression plot, Taylor diagram and error matrix plot, are employed to assess the models’ performance. The reliability index (β) of the models is calculated by using the first-order second moment (FOSM) technique, and the result is compared with the actual value. Additionally, sensitivity analysis is performed to check the impact of the input variables on the output (CL), finding that bf has the greatest impact on the crippling load, followed by tf, tw, H and L, in that order. This study demonstrates that ML techniques are useful for developing a reliable numerical tool for measuring the crippling load of I-shaped steel columns. It is found that the proposed techniques can also be used to predict other kinds of failures as well as different kinds of perforated columns.

Understanding the fundamentals of the on-off retention mechanism of oligonucleotides and their application to high throughput analysis

Ion-pair reversed-phase liquid chromatography (IP-RPLC) is clearly recognized as the gold standard for analyzing therapeutic oligonucleotides (ONs). Recent studies have shown that ONs exhibit an on-off retention behavior in IP-RPLC, meaning that minor changes in acetonitrile (ACN) proportion can significantly impact retention. However, this behavior was initially demonstrated with only a single mobile phase condition. The aim of this study is to gain a deeper understanding of ON elution behavior by measuring the S values (slope of the retention model, log k vs.%ACN) across a broad range of mobile phase conditions. We systematically calculated the S values for both a 20-mer and 100-mer model ON under various conditions, including different IP reagents, IP concentrations, mobile phase pH, column temperatures, and two different buffering acids. We demonstrated that these mobile phase conditions impact the S values in the following order: IP hydrophobicity > IP concentration > column temperature > buffering acid > mobile phase pH. The main explanation for this trend is that mobile phase conditions that reduce the ion-pair retention mechanism (such as low IP hydrophobicity or concentration) will enhance the impact of% ACN on retention, leading to higher S values.In the second part of the study, this knowledge was used to develop ultra-fast separations for two therapeutic oligonucleotides: a 20-mer antisense oligonucleotide (ASO) without phosphorothioate (PS) modifications and a large single guide RNA (sgRNA) that includes certain PS modifications. The mobile phase conditions were optimized to maximize S values, while preventing the separation of diastereomers. It is important to notice that an S-value of at least 30 is required to benefit from the use of ultra-short columns. This approach allows the successful separation of the main species (ASO and sgRNA) and related impurities in less than one minute using a 5 mm length column.

Multilinear regression model for predicting the ultimate load of slender circular CFDST columns subjected to concentric and eccentric loading

AbstractThis paper presents a novel approach to predict the ultimate load of slender circular concrete‐filled double skin tubular (CFDST) columns subjected to concentric and eccentric loading. The proposed approach was developed using a multilinear regression model through analyzing a database containing 165 CFDST column configurations. The data set was obtained by varying the magnitude of the parameters to determine its effect on the ultimate load using FE analysis. The variables considered in the model formulation are concrete strength, steel tube strengths, tube diameters, tube thicknesses, load eccentricity, column curvature, and column length. The accuracy and efficiency of the proposed models were validated with previous experimental investigations. The results demonstrate that the proposed models provide a practical, simple, and efficient approach to predict the ultimate load of slender circular CFDST columns subjected to concentric and eccentric loading. When compared to existing experimental work on slender circular CFDST columns subjected to concentric and eccentric loading, the proposed model over predicts the ultimate load by a maximum of 6%.

Design Methods of Aluminium Pin-Ended Columns with Topology-Optimised Cross-Sections

This paper presents a numerical study of topology-optimised pin-end aluminium alloy columns using finite element analysis (FEA). The FEA models integrate geometric imperfections and material nonlinearity, and are validated against experimental findings from the existing literature. ABAQUS v.6.15 (release 2020) is used in preparing the FEA models and obtaining the analysis results. Furthermore, modern design methodologies including Eurocode 9, the direct strength method (DSM), and the continuous strength method (CSM) are employed to assess the maximum load capacity of such columns. Parametric investigations encompass diverse parameters such as varied cross-sections, column lengths, and global and local imperfections. By analysing a total of 288 FE models, incorporating 16 column cross-sections across two lengths with nine distinct imperfections, this study compares results with those derived from modern design methodologies. Thus, this research elucidates the behaviour of novel cross-sections and the application of contemporary design techniques in their analysis.

Numerical analysis of soil reinforced by sand columns using different installation methods

This study involves a finite element numerical simulation of laboratory tests conducted on small-scale models. The tests involved the installation of columns using different techniques: without soil displacement and without column compaction (WR-NC), and without soil displacement but with column compaction (WR-WC). The reinforced soil masses were then subjected to a uniform 150 kPa load. A comparison between the numerical and experimental results showed excellent agreement, validating the simulation. Following this validation, a parametric analysis was carried out to examine the effects of the various parameters on the behavior of the reinforced soil masses. In the first method, three different column diameters were analyzed, focusing on the effects of diameter (area replacement ratio), column length, and geogrid containment benefits. In the second method, three levels of compaction pressure were applied during the column installation. The study evaluated the impact of column installation techniques on the behavior of the reinforced masses. The findings indicate that settlement reduction is proportional to the increase in area replacement ratio and column length. Additionally, confining the columns with geogrid was shown to be effective in further reducing settlements. The results also revealed that increasing compaction stress leads to greater radial expansion of the columns, which densifies and stiffens the surrounding soil, thereby reducing settlement. Overall, the study concludes that column installation techniques significantly influence the behavior of reinforced soil masses.

Optimization of protein identifications through the use of different chromatographic approaches and bioinformatic pipelines.

Selection of proteomic workflows for a given project can be a daunting task. This research provides a guide outlining the impact on protein identification of different steps such as chromatographic separation, data acquisition strategies, and bioinformatic pipelines. The data presented here will help experts and nonexpert proteomic users to increase proteome coverage and peptide identification. HeLa protein digests were analyzed through different C18 chromatographic columns (15 and 50 cm in length), using top 12 data-dependent acquisition (DDA), top 20 DDA, and data-independent acquisition (DIA) with a nanospray source in positive mode in a Thermo Q Exactive instrument. The raw data were analyzed using different search engines, rescoring approaches, and multi-engine searches. The results were analyzed in the context of peptide and protein identifications, precursor properties, and computation requirements to understand the differences between methods. Our results showed that higher column lengths and top N DDA approaches were able to significantly increase protein identifications. The use of multiple search engines yielded limited gains, whereas the use of rescoring methods clearly outperformed other strategies. Finally, DIA approaches, although successful at generating new identifications, had a limited performance influenced by the previous collection of DDA data, which could prohibitively increase instrument time. Nonetheless, the use of library-free methods showed promising results. Our results highlight the impact of different experimental approaches on proteome coverage. Changes in chromatographic columns, data acquisition, or bioinformatic analysis can significantly increase the number of protein identifications (>400%). Thus, this research provides a reference upon which to build a successful proteomic workflow with different considerations at every step.

An experimental and numerical study on the behavior of finite-length column vortex

This paper explores experimental and numerical investigation of the spatiotemporal dynamics of a finite-length vortex column in three dimensions using particle image velocimetry and large eddy simulation. The research examines the combined impact of bending, buckling, and core-splitting on a finite-length vortex column. More precisely, the work centers on the fundamental motions, evolutions in flow along the axis, how the shape of the vortex core changes over time, the instability caused by the long waves on the vortex column, and the division of the vortex core. A novel prototype is developed that utilizes piston-driven inflow and produces a vortex column through the principles of flow separation and Biot–Savart induction, which is studied for predicting an ex situ cyclonic line vortex. The present study discusses the complete three-dimensional overview of the same columnar vortex. The meridional swirl and the axial transport of vorticity deform the shape of the core cross sections in different lengths of the column. The jump in the axial velocity at the core boundary allows for the occurrence of bending instabilities with a left-handed helical structure. These instabilities have a long wavelength, similar to the length of the vortex column, and belong to the m = +1 mode. The vortex column experiences a non-uniform curvature and torsion caused by the intricate shape of the laboratory model and varying flow speeds at different heights of the vortex column. The results offer valuable insights into the role of inertia, Coriolis, and viscous forces on the dynamics of the vortex column.

Prediction and reliability analysis of ultimate axial strength for outer circular CFRP-strengthened CFST columns with CTGAN and hybrid MFO-ET model

This study develops a novel hybrid machine learning model to estimate the ultimate axial strength and conduct a reliability analysis for outer circular carbon fiber-reinforced polymer (CFRP)-strengthened concrete-filled steel tube (CFST) columns. The experimental datasets are collected and enriched using the conditional tabular generative adversarial network (CTGAN). The column length, the steel properties (cross-section diameter, thickness, and yield strength), the CFRP properties (thickness, tensile strength, and elastic modulus), and concrete strength are selected as input variables to develop the Extra Trees (ET) model hybridized with Moth-Flame Optimization (MFO) algorithm for the ultimate axial strength estimation. The results reveal that the CTGAN can efficiently capture the actual data distribution of CFRP-strengthened CFST columns and the developed hybrid MFO-ET model can accurately predict the ultimate axial strength with a high accuracy (R2 of 0.985, A10 of 0.867, RMSE of 182.810 kN, and MAE of 124.534 kN) based on the synthetic database. In addition, compared with the best empirical model, the MFO-ET model increases the R2 by (6.78% and 13.48%) and A10 by (108.19% and 122.88%) and reduces the RMSE by (68.19% and 66.24%) and MAE by (71.33% and 68.48%) based on real and synthetic databases, respectively. Notably, a reliability analysis is performed to evaluate the safety of the developed MFO-ET model using Monte Carlo Simulation (MCS). Finally, a web application tool is created to make the developed MFO-ET model easier for users to design practical applications.

Stability capacity design of longitudinal asymmetrical shuttle-shaped columns subjected to compression-bending loads

Combining graceful architectural lines and superior mechanical properties, longitudinal asymmetrical shuttle-shaped columns (LA-SSCs) have provided a number of reliable solutions for carrying horizontal and vertical payloads on various types of supporting columns in large-span space structures. This paper investigates the global stability behavior and ultimate load-bearing capacity of LA-SSCs under the combination of axial compression and horizontal point load, and a corresponding strength design procedure is proposed for practical engineering applications. Firstly, the sectional strength prediction formula of LA-SSC under the compression-bending combination loads is derived on the basis of the cross-section strength theory with an explicit expression, and the validity and appropriateness of the formula is verified by using finite element (FE) numerical investigation of examples. Subsequently, the weak section of LA-SSC is analyzed and the formula for its location is proposed, and the results show that the weak section is not always the minimum section of LA-SSC as the load or tapering ratio varies. Afterwards, focusing on the global stability capacity behaviors and design, the implications of major parameters of LA-SSCs, such as the column length and vertical-horizontal loading ratios, are investigated and discussed in detail. Finally, the global stability design formula of LA-SSCs under axial compression and horizontal point loads is established by using FE numerical examples, and the corresponding design methodology and calibration procedure are supplied. With the relevant formulas of definite physical significance and favorable mathematical precision, the design methodology of LA-SSCs under the load combination is proposed and is complete and efficient in predicting the global stability capacity.

Mathematical model for heat transfer during underground coal gasification process

Purpose. To develop a mathematical model of the “coal-gas” medium heat transfer during underground coal gasification to predict the combustion face advance velocity and the duration of gasification column mining. Methodology. To detect the temperature fields in the coal seam and gas, depending on the displacement length of the phase transition boundary, a boundary-value problem of mathematical physics has been developed. To solve this boundary-value problem, Boltzmann transformations, as well as methods for solving ordinary differential equations, are used. Newton-Raphson method, which has quadratic convergence, is used to find the roots of the transcendental equation. Findings. Tendencies in the formation of mathematical models when studying temperature fields around an underground gasifier have been analyzed, with highlighting their disadvantages. A mathematical model of heat transfer during underground gasification has been developed, taking into account the phase transition boundaries of the “coal-gas” medium. A computational experiment was conducted to determine the temperature of the phase transition boundary based on the length of the gasification column and the duration of the process. Originality. A mathematical model for heat transfer during coal gasification in the form of a boundary-value problem of mathematical physics, which consists of parabolic heat-transfer equations, the Stefan condition at the phase transition boundary, and the Dirichlet boundary conditions, has been constructed. As a result of solving the boundary-value problem, a self-similar solution has been obtained for the distribution of the coal seam and gas temperature fields, as well as the position of the phase transition boundary depending on the gasification duration and on the medium density, thermal conductivity coefficients, specific heat capacity of gas and coal, specific calorific value and temperature of coal combustion, initial coal temperature and constant temperature of the gasification process. The conducted analysis of numerical calculations provides a deeper understanding of the dynamics of underground coal gasification process and makes necessary corrections to achieve the maximum process efficiency. Practical value. A methodology for determining the displacement length of the phase transition boundary of the “coal-gas” medium has been developed, taking into account the change in the combustion face temperature along the gasification zone length depending on the duration of this process. Application of the methodology makes it possible to predict the time of mining the gasified coal column for drawing up a calendar plan for mining operations.

Development of microflow ultra high performance liquid chromatography-mass spectrometry metabolomic assays for analysis of mammalian biofluids

Introduction and objectivesThe application of untargeted metabolomics assays using ultra high performance liquid chromatography-mass spectrometry (UHPLC-MS) to study metabolism in biological systems including humans is rapidly increasing. In some of these studies there is a requirement to collect and analyse low sample volumes of biofluids (e.g. tear fluid) or low cell and tissue mass samples (e.g. tissue needle biopsies). The application of microflow, capillary or nano liquid chromatography (≤ 1.0 mm column internal diameter (i.d.)) theoretically should accomplish a higher assay sensitivity compared to analytical liquid chromatography (2.1–5.0 mm column internal diameter). To date, there has been limited research into microflow UHPLC-MS assays that can be applied to study samples of low volume or mass.MethodsThis paper presents three complementary UHPLC-MS assays (aqueous C18 reversed-phase, lipidomics C18 reversed-phase and Hydrophilic Interaction Liquid Chromatography (HILIC)) applying 1.0 mm internal diameter columns for untargeted metabolomics. Human plasma and urine samples were applied for the method development, with porcine plasma, urine and tear fluid used for method assessment. Data were collected and compared for columns of the same length, stationary phase and stationary phase particle size but with two different column internal diameters (2.1 mm and 1.0 mm).Results and conclusionsAll three assays showed an increase in peak areas and peak widths when applying the 1.0 mm i.d. assays. HILIC assays provide an advantage at lower sample dilutions whereas for reversed phase (RP) assays there was no benefit added. This can be seen in the validation study where a much higher number of compounds were detected in the HILIC assay. RP assays were still appropriate for small volume samples with hundreds of compounds being detected. In summary, the 1.0 mm i.d. column assays are applicable for small volume samples where dilution is required during sample preparation.

Study on the influence of heave plate on energy capture performance of central pipe oscillating water column wave energy converter

This paper proposes a novel central pipe oscillating water column (OWC) wave energy converter (WEC) with a heave plate and investigates the influence of heave plate on energy capture performance of the OWC WEC through numerical methods. First, dynamic equations are established for floater and water column. Then, energy capture performance of the WEC is computed by solving relative motion equations using numerical methods. Wave tank experiments are conducted to validate the proposed numerical models. Finally, the influences of heave plate opening diameter and connecting column length on energy capture performance are investigated based on the proposed numerical models. The results indicate that increasing heave plate opening diameter decreases both the maximum capture width ratio (CWR) and response period. And increasing connecting column length widens the response bandwidth. When the heave plate opening diameter decreases from 350 mm to 0, the maximum CWR increases from 30.05 % to 41.68 % and the response period increases from 1.28 s to 1.72 s. When the connecting column length increases from 225 mm to 600 mm, the response band extends by 0.1 s. The proposed device and the obtained analysis results are of great significance for broadband and efficient wave energy generation.

Determination of cyclic behavior of various cross-section composite column-beam connections reinforced with FRP composite using FEM analysis and ML models

ABSTRACT This study examined the cyclic behavior of glass-fiber-reinforced polymer composite column-beam connectors in various diameters. Mean learning (XGBoost and the random forest algorithm) and numerical methods were used to identify the data collected experimentally due to the rotation behavior. The initial sample had a column length of 1200 mm and a cross-section of 80 × 80 mm, with a beam section measuring 80 × 160 mm. The second sample had a 100 × 100 mm column and a beam section measuring 100 × 200 and 1200 mm, respectively. For the third sample, the column’s dimensions were 130 × 130 mm in cross-section and 1200 mm in length, and the beam was 130 × 260 mm. Spruce wood is used to make glulam components for columns and beams. Following the creation of the column-beam connections, glass-based fiber-reinforces polymer (FRP) fabric was used to wrap the column-beam connections that needed strengthening. The cyclic behavior of the reinforced reference samples and the samples with reinforced column-beam joint areas was examined. The column-beam connection with code C13B13-R has the most load-carrying capacity (13.9 kN), while the beam with code C08B08-UR has the lowest load-carrying capacity (03.4 kN). Examining the table reveals that the findings of the numerical analysis and the experiment provide comparable conclusions. When comparing experimental and numerical results, similar values are found for stiffness values (R 2 of 0.99), load-bearing capacity (R 2 of 0.99), and energy consumption capacity (R 2 of 0.99). With R 2 of 0.9978, RMSE of 0.01017, and MAE of 0.01043, the random forest approach identified the stiffness values in the model with the best accuracy. It has been shown that the seismic behavior of column-beam couplings built with these materials may be studied with mean learning models and numerical analysis, instead of demanding and time-consuming experimental studies.

Numerical investigation on plastic hinge behavior of hybrid steel-FRP reinforced concrete columns

This paper presents a numerical study on the plastic hinge behavior and rotation capacity of concrete columns reinforced with a combination of steel bars and fiber-reinforced polymer (FRP) bars. A meso-scale numerical model, which considers the internal heterogeneity of concrete and bond behavior between concrete and longitudinal reinforcements, was developed and validated. The failure modes, lateral load-displacement responses, and the physical plastic hinge lengths of hybrid steel-FRP reinforced concrete (SFRC) columns were investigated and compared with those of conventional steel-reinforced concrete columns. The results indicated that the steel yielding zone and curvature localization zone of SFRC columns with FRP longitudinal bars were enlarged, due to the relatively low modulus of FRP bars. After that, a parametric analysis was performed to study the plastic hinge length of SFRC columns with respect to the nominal area ratio of FRP longitudinal bars, shear span-to-depth ratio, axial load ratio, and longitudinal reinforcement ratio. A new empirical model was proposed to predict the equivalent plastic hinge length, which was subsequently integrated into an analytical method for predicting the ultimate rotation. The comparison of predictions with simulation and test results demonstrated the accuracy of both the proposed empirical model and analytical method.