Section Dimensions Research Articles

Machine learning approach for predicting fire resistance of FRP‐strengthened concrete beams

AbstractThis paper presents a data‐driven machine learning (ML)‐based approach for predicting the fire resistance of fiber‐reinforced polymer (FRP)‐strengthened reinforced concrete beams. To this end, a comprehensive database of fire tests on FRP‐strengthened concrete beams reported in literature was compiled. The database comprised of varying geometric and material properties, sectional dimensions, steel reinforcement, FRP layers, and thermal insulation, as well as the load level. The compiled database was analyzed using three different ML algorithms including, support vector regression, random forest regressor, and deep neural network. The outcome of the analysis is a computational‐based ML approach for predicting fire resistance of FRP‐strengthened concrete beams. The results predicted from the ML approach were compared with those measured in fire tests to show reliability of the proposed approach. The results infer that the proposed ML approach can effectively predict the fire resistance of FRP‐strengthened concrete beams with varying cross sections, properties of constituent materials, and applied loading.

A methodology for computing the thermal balance and energy consumption of autoclaves during steaming of wood

ABSTRACT A methodology for computing the thermal balance and energy consumption of autoclaves during steaming of wood has been presented. With the help of own non-stationary model, the durations of all stages of steaming regimes of beech prisms intended for veneer production with cross- section dimensions of 0.3 × 0.3 m, initial temperature 0 °C, and moisture content 0.4, 0.6, and 0.8 kg·kg−1 were determined at maximum operating temperature in the autoclave equal to 130 °C. With the determined prism steaming durations, using a proposed steady-state model, the total energy required to carry out the entire steaming process in an autoclave with an internal diameter of 2.4 m, a cylinder length of 9.0 m and a degree of filling with prisms 30%, 40% and 50% and also the required for each of the individual components of the thermal balance are calculated. It was found that the total energy consumption of the autoclave increases from 82 to 113 kWh·m−3 when the moisture content of the prisms increases from 0.4 to 0.8 kg·kg−1 at autoclave filling degree of 40%. The methodology can be applied to compute thermal balances of different autoclaves during steaming of wood to any desired final temperature required for their mechanical processing.

Global Sensitivity Analysis of the Fundamental Frequency of Jacket-Supported Offshore Wind Turbines Using Artificial Neural Networks

Determining the fundamental frequency of Offshore Wind Turbines (OWTs) is crucial to ensure the reliability and longevity of the structure. This study presents a global sensitivity analysis of the fundamental frequency of OWTs on jacket foundations. Monte Carlo sampling was employed to generate a diverse set of wind turbines, emplacements, and jacket designs, ensuring that the generated samples are realistic and yield relevant conclusions. The fundamental frequency and its partial derivatives were obtained via a previously developed ANN model. The relative sensitivities were computed to facilitate the comparison of their influence. The results demonstrate that wind turbine properties are the most relevant variables affecting the fundamental frequency, with a decrement in frequency caused by tower height and rotor-nacelle assembly mass, as well as an increment due to the section dimensions of the tower, particularly at its base. Soil properties have a significant effect on foundation stiffness for soft and light soils but can be neglected for hard and heavy soils. The diameter and thickness of the braces also show different relevance depending on their dimensions, producing rigid links between legs for greater sections. This study provides a measure of the variables influencing the fundamental frequency, facilitating a deeper comprehension of this phenomenon.

Female Directorship And Corporate Social Responsibility Disclosure In Nigeria: The Moderating Role Of Firm Size

Companies have witnessed more stringent pressure for corporate social responsibility reporting and the pressure has become critical for their long-term viability and success. Many studies have been conducted to determine the effect of corporate governance mechanism on corporate social responsibility disclosure both locally and internationally, but the studies have yielded inconsistent results. The moderating role of company size on the effect of corporate governance mechanism on corporate social responsibility disclosure has not been significantly studied in the Nigerian context. This study is to examine the effect of corporate governance mechanism on corporate social responsibility disclosure, and the moderating role of firm size. Ex-post facto research design was employed with cross sectional and time series dimensions. Secondary data was obtained from annual reports and accounts of listed manufacturing companies in Nigeria from 2012 to 2023 using disclosure checklist adopted from previous studies. The data was analysed using ordinary least square regressions to determine the effect of female directors on corporate social responsibility disclosure and the moderating role of firm size in listed manufacturing companies in Nigeria. The findings of the study revealed that: female directors have a positive and significant effect on corporate social responsibility disclosure in Nigeria; Firm size has a significant and positive moderating effect on the effect of female directors on corporate social responsibility disclosure of listed manufacturing companies in Nigeria. The study recommends that government and policy makers should set minimum benchmark for female directorship on corporate governance in Nigeria in order to encourage more corporate information disclosures

Carbon-mechanic dual-control design decision model of prefabricated structural components

Prefabricated enclosure structures (PES) have become the key technology for low-carbon construction in the engineering field due to their low labor demand, fast construction speed, and low environmental pollution. In the context of low-carbon development, efficiently designing PES that not only possess high-strength but also demonstrate significant greenhouse gas (GHG) reduction benefits has become a critical challenge. The objective of this study is to address the challenges of automated design and scientific decision-making methods for PES components. First, the Carbon-mechanic dual-control assessment model (CDAM) is proposed, providing a novel evaluation dimension for the design of prefabricated components. Subsequently, based on the CDAM, an automated design decision-making process, and model for components are established using an improved genetic algorithm and parameterized method. Finally, under the constraints of actual engineering conditions, adaptive solutions were automatically generated for specific cases. These solutions were comprehensively evaluated and optimized using CDAM, resulting in design guidelines and optimal solutions for PES that balance environmental performance and load-bearing capacity. The case analysis results show that the optimal scheme based on the carbon-mechanic dual-control (CM) index is: the sectional dimension is 830 mm, the reinforcement ratio is 0.9 % and the cavity ratio is 45 %, which shows the ideal characteristics of low-carbon and high-strength. Compared with the single index decision scheme, this scheme achieve a maximum of 42 % GHG emissions reduction. The high comprehensive performance scheme is characterized by small sectional dimension, high reinforcement ratio, and high cavity ratio. Cavity ratio is a key parameter to achieve high performance design. The research findings provide an important theoretical basis and technical support for the low-carbon transformation in the engineering field.

Flexural performance of the integrated steel truss reinforced 3D printed concrete beams: Experimental and numerical analysis

This study explored the feasibility of the integrated steel truss (IST) reinforced 3D printed concrete beams (3DPC truss beams for abbreviation) as a load-bearing element. Forty-five 3DPC truss blocks were firstly tested under axial compression to obtain an appropriate sectional dimension range and reinforcement ratio for the design of 3DPC truss beams. Subsequently, six reinforced and one non-reinforced 3DPC truss beams were designed and tested under flexural loading. The results demonstrated no debonding or local anchorage failure, indicating a strong integration between the printed layers and IST. More notably, the 3DPC truss beams exhibited a ductile failure mode comparable to that of balanced-reinforced RC beams, an outcome rarely observed in contemporary reinforced 3DPC structures. Finally, a time cost-efficient design flow with great accuracy based on finite element analysis for the flexural performance of 3DPC truss beams was proposed and validated. The results from this study show substantial promise for 3DPC truss beams in future applications, particularly in constructing lateral structures that require significant load-bearing capacity and enhanced ductility.

Mesoscopic structure of the stock market and portfolio optimization

AbstractThe idiosyncratic and systemic components of market structure have been shown to be responsible for the departure of the optimal mean-variance allocation from the heuristic ‘equally weighted’ portfolio. In this paper, we exploit clustering techniques derived from Random Matrix Theory to study a third, intermediate (mesoscopic) market structure that turns out to be the most stable over time and provides important practical insights from a portfolio management perspective. First, we illustrate the benefits, in terms of predicted and realized risk profiles, of constructing portfolios by filtering out both random and systemic co-movements from the correlation matrix. Second, we redefine the portfolio optimization problem in terms of stock clusters that emerge after filtering. Finally, we propose a new wealth allocation scheme that attaches equal importance to stocks belonging to the same community and show that it further increases the reliability of the constructed portfolios. Results are robust across different time spans, cross sectional dimensions and set of constraints defining the optimization problem.

Wind tunnel investigation of hemispherical forebody interaction on the drag coefficient of a D-shaped model

PurposeAn experimental investigation of hemispherical forebody interaction effects on the drag coefficient of a D-shaped model is carried out for three-dimensional flow in the subcritical range of Reynolds number 1 × 105 ≤ Re ≤ 1.8 × 105. To study the interaction effect, hemispherical shapes of various sizes are attached to the upriver of the D-shaped bluff body model. The diameter of the hemisphere (b1) varied from 0.25 to 0.75 times the diameter of the D-shaped model (b2) and its gap from the D-shaped model (g/b2) ranged from 0.25 to 1.75 b2.Design/methodology/approachThe experiments were carried out in a low-speed open-circuit closed jet wind tunnel with test section dimensions of 1.2 × 0.9 × 1.8 m (W × H × L) capable of generating maximum velocity up to 45 m/s. The wind tunnel is equipped with a driving unit which has a 175-hp motor with three propellers controlled by a 160-kW inverter drive. Drag force is measured with an internal six-component balance with the help of the Spider 3013 E-pro data acquisition system.FindingsThe wind tunnel results show that the hemispherical forebody has a diameter ratio of 0.75 with a gap ratio of 0.25, resulting in a maximum drag reduction of 67%.Research limitations/implicationsThe turbulence intensity of the wind tunnel is about 5.6% at a velocity of 18 m/s. The uncertainty in the velocity and the drag coefficient measurement are about ±1.5 and ±2.83 %, respectively. The maximum error in the geometric model is about ±1.33 %.ractical implicationsThe results from the research work are helpful in choosing the optimum spacing of road vehicles, especially truck–trailer and launch vehicle applications.Social implicationsDrag reduction of road vehicle resulting less fuel consumption as well as less pollution to the environment. For instance, tractor trailer experiencing approximately 45% of aerodynamics drag is due to front part of the vehicle. The other contributors are 30% due to trailer base and 25% is due to under body flow. Nearly 65% of energy was spent to overcome the aerodynamic drag, when the vehicle is traveling at the average of 70 kmph (Seifert 2008 and Doyle 2008).Originality/valueThe benefits of placing the forebody in front of the main body will have a strong influence on reducing fuel consumption.

Strut‐and‐tie model for column‐to‐drilled shaft connections in reinforced concrete bridge columns subjected to lateral loads

AbstractDrilled shafts with a larger diameter than columns are frequently adopted as the foundation of highway bridge columns due to their superior economic efficiency and lower impact on existing facilities in the urban built‐up area. Different section dimensions lead to a socket connection between the column and the oversized shaft and a noncontact lap splice of their longitudinal bars. The force‐transfer mechanism and failure process of column‐to‐drilled shaft connections were deeply revealed in this study. Detailed FE models were developed at theDianaplatform and validated against previous experimental results. Subsequently, a parametric study investigated the effect of the shear span‐to‐depth ratio, diameter ratio of shaft‐to‐column, column embedment depth, and shaft stirrup ratio. Finally, a modified strut‐and‐tie model (STM) was proposed to design stirrups of the transition region efficiently considering the experimental failure mechanism. Results indicate that the numerical models built in theDianaplatform can precisely simulate the mechanical behavior of column‐to‐drilled shaft connections. The failure mechanism of column‐to‐drilled shaft connections is shaft stirrups yield at the compressive side induced by extrusion between the embedded column and shaft. The lateral loading capacity of column‐to‐drilled shaft connections increases with the increase of shear span‐to‐depth ratio, diameter ratio of shaft‐to‐column, column embedment depth, and shaft stirrup ratio. The modified STM is able to reveal the variation tendency of shaft transverse reinforcement demand with the various design parameters and give an average stirrup stress ratio of 1.20 and a coefficient of variation of only 8.31%.

Exploring anisotropic mechanical properties of lobster claw exoskeleton through fractal models

The outstanding mechanical properties of lobster claw exoskeletons are intricately tied to their internal microstructure. Investigating this relationship can offer vital insights for designing high-performance additive manufacturing structures. Fractal theory, with its fractional dimensional perspective, suits the complexity of real-world phenomena. Our study examines fully hydrated lobster claw exoskeletons using a multifaceted approach: four-point bending tests, scanning electron microscopy observations, and fractal models. Test results reveal superior mechanical properties in longitudinal specimens. Scanning electron microscopy shows non-uniform fiber helical structures and porous elements in the exoskeleton. Fracture mechanisms involve both breaking fiber fragments perpendicular to the cross-section and tearing between these fragments. The observed crack propagation paths exhibit statistical self-similarity. Consequently, we develop fractal models for the crack propagation paths in longitudinal and transverse specimens, calculating crack extension forces. Using the box-counting method and its improved variant, we determine the fractal dimensions of specimen sections. The fractal dimension of longitudinal models exceeds that of transverse models, and calculated crack extension forces are higher in longitudinal models. These findings align well with experimental data, demonstrating fractal theory's efficacy in analyzing the lobster claw exoskeleton's anisotropic mechanical properties.

HSC-RSW with laterally installed XADAS dampers: Seismic performance

This study investigates the seismic behavior of high-strength concrete (HSC) rocking shear walls (RSW) equipped with X-shape Adding Damping and Stiffness (XADAS) dampers installed perpendicular to the wall via brackets. Unlike previous studies where dampers are integrated along the wall length, this research leverages the advantages of HSC to minimize sectional dimensions while employing laterally installed XADAS dampers to enhance the cyclic response, yielding flag-shaped hysteresis curves. The alignment angle of the XADAS dampers is also considered a crucial variable in assessing the overall seismic performance of the proposed HSC-RSW system. A novel constructional approach using brackets to install lateral XADAS dampers is implemented. Post-tensioning (PT) forces are applied as consistent axial strains in cables, achieved through predefined cable support displacements. A macro-FEM model is developed to validate the chosen experimental reference test and is subsequently used for further parametric studies. The parametric studies indicate that increasing concrete compressive strength (CCS) enhances the self-centering capability by reducing RSW strains and facilitating rocking. Additionally, incorporating XADAS dampers into the system improves energy dissipation, with a zero-degree alignment angle identified as optimal. Notably, the modeled HSC-RSW systems exhibit limited drift capacity (less than 2 %) compared to normal strength concrete (NSC)-RSW systems, where wall toes are conventionally prone to crushing.

Application of laced built-up columns with cold-formed lipped angle sections in wind turbine towers

Increasing the height of wind turbine towers effectively enhances their power output. Consequently, there is a growing demand for constructing wind turbine towers with higher hubs, especially in heavily populated and energy-intensive areas. Traditional approaches involve enlarging angled steel, posing production challenges and economic feasibility concerns. This study proposes replacing traditional angled steel with cold-formed lipped angles for improved structural performance. In this paper, a finite element model of the built-up column with cold-formed lipped angles is developed through ANSYS software. Finite element calculations are applied to various cross-sectional dimensions of cold-formed lipped angle sections to analyze column curves. Incorporating calculation methods from international standards, the paper presents a fitting formula and calculation method for the load-carrying capacity of the built-up column with cold-formed steel lipped angle sections. Finally, utilizing a wind turbine tower with a 120 m hub height as a case study, the paper conducts structural modeling and design analyses for both the built-up column with cold-formed lipped angles and the one with conventional angled steel. The research indicates that after adopting the built-up column with cold-formed lipped angle sections, the stress ratio of the tower columns is significantly reduced, with an approximate 16 % decrease in the stress ratio of the most critical section. The adoption of cold-formed lipped angle section effectively enhances the overall load-carrying capacity of the wind tower, providing a greater safety margin for the design. The calculation method provides valuable insights for future engineering applications.

Performance of ANN, Random Forest and XGBoost methods in predicting the flexural properties of wood beams reinforced with carbon-FRP

ABSTRACT Wooden material can be used in different areas due to its various positive properties. Glued Laminated wooden elements (glulam) are wood composite materials widely used especially in the construction industry. Carbon fiber-reinforced polymers (FRP) are widely used to increase the bearing capacity values of glulam beams and improve their overall load-displacement behavior. This study was carried out in two stages. In the first stage, the bending properties of glulam timbers of different sizes with wide spans reinforced with carbon fiber-reinforced polymers were experimentally examined. In the next stage, the obtained data were predicted with three different machine learning techniques (ANN, Random Forest and XGBoost). As a result of the study, it was determined that as the section dimensions increased, the bending properties increased, and the reinforcement was effective by approximately 22%. All three different prediction techniques used could make predictions with high accuracy. However, it was determined that the best prediction was made with Random Forest (R2: 0.9892). Therefore, the bending properties of reinforced beams of different sizes can be predicted with machine learning (ML) techniques.

On the effect of background seismicity in physics-based earthquake simulations

Physics-based simulations have been extensively employed to generate synthetic earthquake catalogs over the past decade. In this kind of simulation, primary known faults are typically modeled, while smaller and intermediate faults are often neglected. As a result, the location of earthquakes in the simulation is confined to the modeled faults. Furthermore, due to the elimination of off-fault seismicity, a complete match of the frequency-magnitude distribution of the synthetic catalog with observed data is not achieved. This paper presents an approach to include off-fault seismicity (or background seismicity) within the simulation. First, background earthquakes are separated from the primary faults’ earthquakes, and a fault section is assigned to each event. By employing a scaling relationship, the dimensions of these fault sections are determined according to the magnitude of the corresponding event. The fault section’s slip rates are estimated based on the observed frequency-magnitude distribution. Combining the background fault model with the primary fault model results in a comprehensive model that accounts for all stress interactions between fault elements within the simulator in actual locations. As a result, a broader range of frequency-magnitude distribution in the synthetic catalog can be matched to the observations. A case study using one of the available simulators, Virtual Quake, on a sample area is presented. The results demonstrate that eliminating off-fault seismicity could lead to an underestimated assessment of the earthquake probabilities for the whole region and a biased estimation of earthquake rates in individual faults.

Energy efficient and sustainable design of a multi-story building based on embodied energy and cost

Sustainable multi-story building designs are gaining increasing attention in light of the green development of the building industry. Recently, many studies have been conducted to determine the optimized embodied energy considering size of structural members and materials strength using a single objective function. In this context, the current study adopted a multi-objective function based on cost and Embodied Energy (EE) for the sustainable design of the entire multi-story building. A BuildingEnergy computer program is used to assess the energy consumption performance of a multi-story reinforcement cement concrete building. Based on the proposed method, an analysis is carried out to compare the optimal solutions for multi-story building. Furthermore, a detailed parametric study was conducted to explore the main factors for energy-efficient column and beam design. The results revealed that with a comparison of the most “carbon-friendly” and “cost-friendly” solutions, an added cost of 6–7% can contribute up to a 13% emission reduction. The sectional dimensions, steel rebar, concrete strengths, cost ratio, building height, and eccentricity remarkably influence sustainable design, cost optimization, and minimum carbon emission. Overall, this study could help to define cost-effective and energy-efficient structural members. Eventually, the EE is confirmed to be a feasible parameter for designing more sustainable multi-story RCC buildings.

Transfer learning applications for corrosion prediction for electrodissoluted specimens

Corrosion monitoring is a critical aspect of Structural Health Monitoring (SHM), as it presents inherent challenges in tracking its progression and requires strategically placed sensors for effective surveillance. Moreover, the intricate interplay between environmental factors and the material composition of corroding components further complicates this phenomenon. In this study, a novel neural network framework is designed to predict corrosion evolution based on environmental data, focusing on three distinct aluminium alloys: Al7475, Al2024, and F357. A dedicated neural network model is developed for Al7475, trained on electrodissolution data, including process parameters and profilometry measurements. This model predicts corrosion progression in terms of volume loss, corroded depth, and area based on charge measurements. To address the challenge of material-environment coupling, transfer learning is employed to adapt the neural network to Al2024 and F357. The oxidation charge passed during the electrodissolution mimics in an artificial way the corrosion process due to environmental conditions in the attack site. Consequently, the implemented neural network establishes a robust connection between corrosion process measurements and profilometry data, enabling accurate corrosion progression prediction based on oxidation charge. This framework allows the prediction of a component's residual useful life based on the assessment of the corrosion state, with the knowledge of volume loss further supporting mechanical assessment by evaluating resistant section or pit dimensions, ultimately aiding in the pit-crack transition analysis.

Experimental investigation of cold-formed stainless steel tubular T-joints with loaded chord

This study focuses on the cold-formed stainless steel square hollow section (SHS) tubular T-joints prone to failure by chord sidewall yielding, crushing or instability under axial compression in brace member. An experimental investigation was conducted to understand the joint behaviour subjected to chord axial loading during the brace compression. The dimensions of the tubular sections were 80x80x2mm and 40x40x2mm, corresponding to 2γ values of 20 and 40, respectively. Based on the obtained experimental results, it was observed that the T-joint resistances decrease when subjected to chord compressive load, especially in the cases with elevated values for the chord sidewall slenderness (2γ). On the other hand, if a chord tension force is considered, an increase in the T-joint resistance is observed. With the results obtained from the tests, the design standards EN 1993-1-8 in association with EN 1993-1-4, NBR 16239, CIDECT, ISO 14346 and AISC 360-22 were assessed, as well as the predictions proposed by other authors from the literature. Finally, it was found that design codes are very conservative, except for AISC 360-22 [26], which provided unsafe predictions. On the other hand, equations proposed by other authors from the literature presented better results.

Progressive Collapse Behavior of a Precast Reinforced Concrete Frame System with Layered Beams

A possible way to improve the structural safety and robustness of precast building structures is to develop effective precast frame systems with layered beams, which combine prefabricated parts with cast-in situ ordinary concrete, high-performance concrete, fiber concrete, or FRP. The paper provides a new type of precast reinforced concrete frame system with layered beams for rapidly erected multi-story buildings resistant to accidental actions. Using a combination of the variational method and two-level design schemes, a simplified analytical model has been developed for structural analysis of the precast reinforced concrete frame system, both for serviceable and ultimate limit states as well as for accidental actions. The proposed model allows for determining shear deformations and the formation and opening of longitudinal cracks in the intermediate contact zone between precast and monolithic parts of reinforced concrete structural elements of the frame, as well as the formation and opening of normal cracks because of the action of axial tensile force or bending moment in these elements. The design model was validated by comparing the calculated and experimental data obtained from testing scaled models of the precast reinforced concrete frame system with layered beams. The paper investigates and thoroughly analyzes the factors affecting the stiffness and bearing capacity of the intermediate contact zone, discusses the criteria for the formation of shear cracks along the contact zone of precast and monolithic concrete, and examines the change in the stiffness and dissipative properties of layered elements at different stages of their static–dynamic loading. The robustness of the experimental models of the structural system was not ensured under the specified load, section dimensions, and reinforcement scheme. Following an accidental action, longitudinal cracks were observed in the contact joint between the monolithic and prefabricated parts in the layered beams. This occurred almost simultaneously with the opening of normal cracks in adjacent sections. A comprehensive analysis of the results indicated a satisfactory degree of agreement between the proposed semi-analytical model and the test data.

OPTIMIZATION OF PURLINS CROSS-SECTION EXPOSED TO FIRE

<p>In practice, consideration of fire protection for structural elements mainly occurs after the adopted dimensions of sections. However, this procedure leads to not the most cost-effective solution in general. To find the optimal solution, it is necessary to apply one of the optimization methods. The presented optimization of purlins RHS cross-section is performed with nonlinear programming available in widely used program Excel. The objective function is defined as producing the purlin at a minimal price, considering the price of steel, work, and fire-resistant paint. Limits are introduced to ensure the cross-section satisfies the ultimate limit state for permanent and transient load situations, as well as in case of fire. Besides the ultimate limit states, the limits are defined for serviceability limit states and for cross-sectional geometry. Optimization analysis for different ISO 834 fire durations is followed by a result comparison. It provides an overview of cross-sectional parameters that most influence the bearing capacity in case of fire. It is concluded that by increasing the exposure time to fire, the optimal solution becomes a section with a smaller perimeter, larger surface area, and a thicker layer of fire-resistant coating.</p>

Experimental investigation of the effect of longitudinal tensile reinforcement ratio on ductility behaviour in GPC beams

This research first determined the strength of the cylindrical geopolymer concrete materi- als under compressive stresses. Secondly, conventional and geopolymer-reinforced concrete beams were manufactured in different reinforcement ratios, and their mechanical properties were compared under bending. The main aim of this study is to experimentally compare the effect of reinforcement ratio on the ductility behavior of an alkali-activated geopolymer con- crete (GPC) beam with that of an ordinary Portland cement (OPC) beam. First, balanced reinforcement calculations were made considering the mechanical properties obtained from the material tests. The load-displacement, moment-curvature, and crack development results obtained from beam tests are interpreted with this information. OPC and GPC beams exhibit- ed similar strength and crack development behavior. However, the behavior of GPC and OPC concretes differs regarding the ductility index. Therefore, to achieve similar ductility in the conduct of GPC and OPC beams, the balanced reinforcement ratio and section dimensions of GPC beams should be chosen to be larger than OPC.