Structural Loads Research Articles

Comparative life cycle assessment of sprayed-UHPC sandwich panels over brick & block cavity construction

This paper presents a novel developed Sprayed Ultra-High-Performance Cementitious Sandwich Panel (SUHPC-SP) for structural applications. The SUHPC-SP features sprayed UHPC outer layers making it suited for structural load bearing applications, and a foamed concrete core layer offering high thermal properties. With the development of enhanced material properties and novel production methods, the established SUHPC-SP can achieve optimal mechanical performance while minimising the volumes of material required. As such, this study assesses SUHPC-SP potential to increase sustainable outputs over reference Brick and Block (B&B) construction; by quantifying and comparing the whole life cycle environmental and economic impacts of the two methods. A comparative life cycle assessment (LCA) of these types of construction products is presented for the first time in this paper. The study found that integrating SUHPC-SP over typical B&B construction can reduce environmental impacts by as much as 500% and costs by up to 180%. This informs sustainable construction decisions, offering an effective alternative to conventional inefficient building methods and materials.

IPC‐based robust disturbance accommodating control for load mitigation and speed regulation of wind turbines

SummaryOver the past few decades, global demand for renewable energy has been rising steadily. To meet this demand, there has been an exponential growth in size of wind turbines (WTs) to capture more energy from wind. Consequent increase in weight and flexibility of WT components has led to increased structural loading, affecting reliability of these wind energy conversion systems. Spatio‐temporal variation of rotor effective wind field acts as a disturbance to a WT system, hence, necessitating controllers that can cancel this disturbance. Additionally, assumptions made in extracting linear models for controller design lead to modeling errors resulting from changing operating conditions. Previous attempts have proposed robust controllers incorporating wind disturbance models. However, these controllers have been evaluated on smaller WTs, which experience lower structural loading than larger ones. Additionally, a majority these controllers are based on collective pitch control (CPC), hence do not address loading in the blades. To address these challenges, this contribution proposes an independent pitch‐based robust disturbance accommodating controller (IPC‐RDAC) for reducing structural loads and regulating generator speed in utility‐scale WTs. The proposed controller is designed using ‐synthesis approach and is evaluated on the 5 MW National Renewable Energy Laboratory (NREL) reference WT. Its performance is evaluated against a gain‐scheduled proportional integral (GSPI)‐based reference open‐source controller (ROSCO) and a CPC‐based RDAC (CPC‐RDAC) controller, developed previously by the authors. Simulation results for various wind conditions show that the proposed controller offers improved performance in blade and tower load mitigation, as well a generator speed regulation.

Stepwise Identification Method of Thermal Load for Box Structure Based on Deep Learning.

Accurate and rapid thermal load identification based on limited measurement points is crucial for spacecraft on-orbit monitoring. This study proposes a stepwise identification method based on deep learning for identifying structural thermal loads that efficiently map the local responses and overall thermal load of a box structure. To determine the location and magnitude of the thermal load accurately, the proposed method segments a structure into several subregions and applies a cascade of deep learning models to gradually reduce the solution domain. The generalization ability of the model is significantly enhanced by the inclusion of boundary conditions in the deep learning models. In this study, a large simulated dataset was generated by varying the load application position and intensity for each sample. The input variables encompass a small set of structural displacements, while the outputs include parameters related to the thermal load, such as the position and magnitude of the load. Ablation experiments are conducted to validate the effectiveness of this approach. The results show that this method reduces the identification error of the thermal load parameters by more than 45% compared with a single deep learning network. The proposed method holds promise for optimizing the design and analysis of spacecraft structures, contributing to improved performance and reliability in future space missions.

LIDAR‐assisted feedforward individual pitch control of a 15 MW floating offshore wind turbine

AbstractNacelle‐mounted, forward‐facing light detection and ranging (LIDAR) technology can deliver benefits to rotor speed regulation and loading reductions of floating offshore wind turbines (FOWTs) when assisting with blade pitch control in above‐rated wind speed conditions. Large‐scale wind turbines may be subject to significant variations in structural loads due to differences in the wind profile across the rotor‐swept area. These loading fluctuations can be mitigated by individual pitch control (IPC). This paper presents a novel LIDAR‐assisted feedforward IPC approach that uses each blade's rotor azimuth position to allocate an individual pitch command from a multi‐beam LIDAR. In this study, the source code of OpenFAST wind turbine modelling software was modified to enable LIDAR simulation and LIDAR‐assisted control. The LIDAR simulation modifications were accepted by the National Renewable Energy Laboratory (NREL) and are now present within OpenFAST releases from v3.5 onwards. Simulations of a 15 MW FOWT were performed across the above‐rated wind spectrum. Under a turbulent wind field with an average wind speed of 17 ms−1, the LIDAR‐assisted feedforward IPC delivered up to 54% reductions in the root mean squared errors and standard deviations of key FOWT parameters. Feedforward IPC delivered enhancements of up to 12% over feedforward collective pitch control, relative to the baseline feedback controller. The reductions to the standard deviation and range of the rotor speed may enable structural optimization of the tower, while the reductions in the variations of the loadings present an opportunity for reduced fatigue damage on turbine components and, consequently, a reduction in maintenance expenditure.

Influence of turbulent coherent structures on the performance and wake of a wind turbine

Wind energy in the atmospheric boundary layer serves as the primary source for energy absorption and structural load on wind turbines. However, the impact of turbulent coherent structures on the aerodynamic performance and wake characteristics of wind turbines has not been comprehensively evaluated. In this study, the proper orthogonal decomposition (POD) method is employed to assess the influence of turbulent coherent structures of varying scales on the aerodynamic performance and wake characteristics of wind turbines in the neutral atmospheric boundary layer. The results show that turbulent coherent structures are the main factor that determines the wind velocity fluctuation, aerodynamic performance and wake characteristics of wind turbine in the atmospheric boundary layer. When considering the 13th or lower order POD mode, the wind velocity fluctuation increases with the increase of energy content (more POD modes) of the turbulent coherent structures. When considering the first 19 POD modes, the dynamic loads and power of wind turbine fluctuate with high frequencies, the thrust fluctuates in an amplitude range between 2.4 % and 13.9 % around the mean value, and the power fluctuates from 4.5 % to 28.6 % of the mean value. When considering the first 40 POD modes, the average power generation of the wind turbine increases by 26 % compared to the case with no turbulent structures considered. The study of turbine wake shows that turbulent coherent structures can expand the wind turbine wake approximately to a width of 2.5D and a height of 3D (D is the diameter of the wind turbine), offset the wake approximately to 2D, and move forward the position of the wake vortex beginning to dissipation approximately to 7D behind the wind turbine. In addition, turbulent coherent structures can accelerate the wake velocity recovery by increasing the momentum exchange between the atmospheric boundary layer and wind turbine wake.

Computationally-efficient high-fidelity nonlinear FEA of seismically isolated post-tensioned RC bridges

This study presents a novel computationally efficient high-fidelity nonlinear FEA (NLFEA) methodology for prestressed RC bridges constructed in the UAE and seismically isolated with elastomeric bearings. Specifically, the presented NLFEA methodology, using 3D solid brick elements, is shown to overcome traditional prohibitive numerical burdens. This is demonstrated without compromising accuracy or upscaling applicability and appropriateness. The proposed NLFEA approach is highlighted through detailed modeling of RC bridges’ non-traditional structural components and loading aspects (elastomeric bearings and post-tension prestressing cables). The mechanical behavior of elastomeric isolators and the RC continua, including cracking and other nonlinear phenomena, are captured via 3D solid brick elements. Moreover, the modeling procedure accurately represents the post-tension tendons’ prestressing forces and the associated effects on the RC elements. The prestressing forces are incorporated within the tendon elements via insightful manipulations of stepwise initial conditions and internal force adjustments. Additionally, load-carrying capacity determination for the elastomeric bearings was achieved by conducting a parametric investigation to capture their mechanical behavior adequately. Eventually, the analysis of a full-scale bridge is presented in this paper. The post-tensioned RC bridge understudy spans 100 m over eight elastomeric (natural rubber) seismic isolator bearings. Twelve post-tension prestressing cables are utilized to provide the bridge with continuous internal tension-balancing forces. A high-fidelity detailed FEA model of the complete bridge is developed and validated against a SAP2000 FEA model. It is shown that reasonable computational efforts can be expected without compromising the accuracy of the results.

Machine learning-aided generative design methodology for a Martian regolith habitation shell

This study presents a novel design methodology to automate the development process of a regolith habitation shell for a crewed mission on Mars. The integration of generative design, simulation tools, and data science methodologies allows for a systematic and comprehensive iterative design process, which facilitates the development of dual-habitation shells that can resist harsh conditions on Mars.The study establishes a methodology consisting of four fundamental sections. Initially, the environmental conditions on the surface of Mars are assessed and quantified as structural loads, so that the generative design tools effectively transform these stresses into design parameters that might be used in finite element modeling (FEM). Next, this study employs human factors derived from existing literature as input for Social Network Analysis (SNA) and the Label Propagation Algorithm (LPA) to address important design inquiries concerning functional zoning, layout configuration, geometry generation, and habitability variables. These inquiries aim to inform the decision-making process regarding autonomous typology design. Furthermore, the use of space syntax, physics simulations, and Voronoi algorithms improves the accuracy of the habitation planning process by generating floor designs and habitable volumes that align with the distinctive requirements and preferences of individuals. Lastly, the regolith habitation shell is constructed using structural simulation techniques that incorporate Mars' environmental pressures as design considerations. By employing Karamba3D and numerical finite element modeling (FEM) techniques, the structural performance of the regolith habitation shell under the environmental conditions on Mars is simulated.Consequently, this study introduces three distinct habitation shell designs that were developed and exposed to structural simulations to evaluate the effects of environmental stresses on Mars. The study explores the conjunction between generative design, data science, and structural simulations by employing a systematic and comprehensive design process. Its objective is to provide insights into the impact of environmental pressures on habitation shells and improve our understanding of design outcomes for future exploration on Mars.

The immunity protection of intestine induced by pseudorabies virus del gI/gE/TK in piglets.

Compared to the classical strain of Pseudorabies virus (PRV), the PRV variant exhibits stronger transmissibility and pathogenicity, causing immense disasters for the global pig industry. Based on this variant, our laboratory has preliminarily constructed a modified pseudorabies virus with deletions in the gE/gI/TK genes. In this study, the protective efficacy of PRV XJ del gI/gE/TK against piglet intestinal damage was evaluated. The results demonstrated that piglets immunized with PRV XJ del gI/gE/TK exhibited alleviated intestinal damage caused by the PRV XJ variant strain. This included reduced viral load, suppressed inflammation, and maintenance of intestinal structure and function. Additionally, PRV XJ del gI/gE/TK also strongly activated the innate immune response in the intestines, increasing the expression of antiviral factor mRNA and the secretion of SIgA to counteract the attack of the PRV XJ variant strain. Our study indicates that PRV XJ del gI/gE/TK can inhibit intestinal damage caused by PRV XJ variant strain and activate the innate immune response in the intestines.

Numerical analysis on the factors affecting post-peak characteristics of coal under uniaxial compression

The post-peak characteristics of coal serve as a direct reflection of its failure process and are essential parameters for evaluating brittleness and bursting liability. Understanding the significant factors that influence post-peak characteristics can offer valuable insights for the prevention of coal bursts. In this study, the Synthetic Rock Mass method is employed to establish a numerical model, and the factors affecting coal post-peak characteristics are analyzed from four perspectives: coal matrix mechanical parameters, structural weak surface properties, height-to-width ratio, and loading rate. The research identifies four significant influencing factors: deformation modulus, density of discrete fracture networks, height-to-width ratio, and loading rate. The response and sensitivity of post-peak characteristics to single-factor and multi-factor interactions are assessed. The result suggested that feasible prevention and control measures for coal bursts can be formulated through four approaches: weakening the mechanical properties of coal pillars, increasing the number of structural weak surfaces in coal pillars, reducing the width of coal pillars, and optimizing mining and excavation speed. The efficacy of measures aimed at weakening the mechanical properties of coal is successfully demonstrated through a case study on coal burst prevention using large-diameter borehole drilling.

Enhanced dung beetle optimizer for Kriging-assisted time-varying reliability analysis

<p>During the engineering structure's operation, the mechanical structure's performance and loading will change with time, so the parameter uncertainty and structural reliability will also have dynamic characteristics. The time-varying reliability analysis method can more accurately evaluate structural reliability by fully using this dynamic uncertainty. However, the time-varying reliability analysis was mainly based on the spanning rate method, which was complex and difficult to obtain the final result. Therefore, this study proposed an enhanced dung beetle optimization (EDBO) assisted time-varying reliability analysis method based on the adaptive Kriging model. With the help of the adaptive Kriging model and the EDBO optimization algorithm, the efficiency of the time-varying reliability analysis method was improved. At the same time, to prevent prematurely falling into the local search trap, the method improved the uniformity of the sample by initializing the sample through improved tent chaotic mapping (ITCM). Next, the Gaussian random walk strategy was used to search the updated position, which further improved the accuracy of the reliability analysis results. Finally, the accuracy and effectiveness of the proposed time-varying reliability analysis method were verified by four mechanical structure model examples. From the calculation results, it can be seen that with the help of the new DBO optimization algorithm, the relative error of the proposed reliability analysis results was about 20%~30% lower than that of the traditional reliability analysis method. What's more, the calculation efficiency was higher than that of other reliability analysis methods.</p>

Widely Employed Constitutive Material Models in Abaqus FEA Software Suite for Simulations of Structures and Their Materials: A Brief Review

The structural response of masonry/concrete structures depends upon the load-carrying mechanism and subsequently deformations produced by loads carried. In masonry/concrete structures, identification of the stress/strain imposing stress conditions and strain hardening/softening makes the structural response more complicated. Elastic damage models or elastic-plastic constitutive laws are inadequate to simulate masonry/concrete response under high strain-rate loadings. Further, irreversible or plastic strain cannot be realized using the elastic damage model. Several constitutive damage models are available in the literature. In this article, a concise explanation of the functioning of different material models in the Abaqus software package has been provided. These models include concrete damage plasticity for concrete and masonry, traction separation constitutive laws for brick-mortar interface, Hashin's criteria for CFRP, Johnson-Cook plasticity for steel, and crushable foam plasticity hardening for metallic foams. Researchers frequently utilize these models for numerical simulations and modeling of infrastructural elements and their respective materials when subjected to various structural loads. Besides, this paper presents a discourse on problem-solving methods and a comparison between explicit and implicit analysis. The research provides valuable input to researchers and practitioners in the field of structural engineering for an in-depth understanding of the functioning of Abaqus' pre-existing material models.

Evaluation of Wind Flow and Structural Loads by the Dynamic Terrain Approach

Evaluation of Wind Flow and Structural Loads by the Dynamic Terrain Approach

Supported H8PV5Mo7O40 on activated carbon: Synthesis and Investigation of influencing factors for catalytic performance.

Polyoxometalates (POMs), in particular the Keggin-type HPA-5 (H8PV5Mo7O40) are widely established as effective catalysts for acid- and redox-catalyzed reactions. Yet, they are mainly used as homogeneous catalysts, which poses challenges regarding catalyst separation. This study explores the synthesis of supported HPA-5, and its application as a heterogeneous catalyst for biomass conversion, focusing on activated carbons with diverse chemical and physical properties as support materials. Characterization of these carbons gives insights into the influence of surface area, oxygen content, and acidity on HPA adsorption and stability. Activated carbon CW20, was found to be the best support due to its high vanadium loading and effective preservation of the HPA-5 structure. It underwent various pre- and post-treatments, and the obtained supported catalysts were evaluated for their catalytic performance in converting glucose under both oxidative (OxFA process) and inert (Retro-Aldol condensation) conditions. Notably, HPA-5 supported on CW20 emerged as an exceptional catalyst for the retro-aldol condensation of glucose to lactic acid, achieving a selectivity of 15% and a conversion rate of 71%, with only minimal vanadium leaching.

Calibration and verification of creep parameters for concrete

Concrete is a material which undergoes slow increasing deformation while subjected to persistent mechanical stress. This phenomenon is known as creep. In concrete material, creep occurs at all stress levels. Additional deformation of concrete structures at the end of their design working life caused by creep is usually two to three times of the immediate elastic deformation value, but might be even more in some cases. The value is dependent on many parameters, e.g. concrete grade, cement class, ambient environment relative humidity, geometry of the structure (drying surface of concrete in contact with air) and also the age of concrete at the time of loading. According to corresponding European standard, the effects of creep are evaluated using creep coefficient, and should be considered for verification of serviceability limit states, and if significant, also at ultimate limit states. In order to evaluate the creep effects in geometrically more complex structures, numerical finite element (FEM) analyses might be conducted. In commercially available software ANSYS, there is a library of several implicit creep equations, with several input parameters. These parameters need to be calibrated in order to match the assumptions of the creep effects over time in accordance with the corresponding European standard. In this study, calibration process of European standard concrete C35/45 parameters for selected implicit creep equation from ANSYS library is presented. The parameters are calibrated for two different ambient relative humidity (RH) levels, 78.8% and 90%, each for concrete loaded in 28 days (also 90 days for RH 78.8% and 50 days for RH 90%) after its casting, and suitable for finite element analysis of creep effects within the first year after loading of the concrete structure. The calibration process is split into two parts, analytical one conducted in table processor, where approximate estimations of suitable parameter values are determined. The second part consist of the subsequent optimization process in OptiSLang software, where the optimal parameter values are determined in order to achieve the best match between the time dependent Eurocode standard creep coefficient and the creep coefficient based on the results of one solid element uniaxial compression test in ANSYS finite element software. The obtained parameters are then verified on an analysis of a simply-supported concrete beam modelled of solid 3D finite elements. The values of selected creep equation parameters are summarized in the table, and might be used in the subsequent ongoing research.

The role of key workplace elements in determining individual and organizational success in Jordan Tourism Board

The aim of this research was to investigate the impact of various work-related factors, such as task load, workers’ compensation, and organizational structure community on job success and the overall performance of the Jordan tourism board. The researchers conducted an analysis of 269 randomly selected samples from their study and discussed their findings to validate their hypotheses. The study revealed that factors like compensation levels, organizational structure, community, and task load significantly influence individual and organizational success. The first aspect examined was the task load, which was assessed by considering factors such as job completion rates, daily challenges faced, and the time required for tasks. Work-related compensation, encompassing factors like experience, skill, incentives, and rewards, emerged as the second most crucial factor after working hours. The third and most vital component to consider was the organization structure community, which includes communities of practice, collaborative efforts, and physical infrastructure. According to the research findings, improving employee performance can be achieved by reducing their task load, increasing work income, and developing the organization community that fosters teamwork and the formation of workgroups. These elements collectively impact overall productivity. The study provides valuable insights into an underexplored area, shedding light on how task load, compensation, and organizational structure community interplay. The research's focus on the Jordan tourism board is particularly significant, as it has the potential to help tourism companies enhance their operations and provide superior service to their customers.

Expanding the cross-cultural validity of the Enright Forgiveness Inventory short form.

This research assessed the cross-cultural validity and internal consistency of the Enright Forgiveness Inventory short form (EFI-30). A total of 1677 people across four countries (United States, the Philippines, China and Saudi Arabia) participated in the study. Data analysis relied on multigroup confirmatory factor analysis and assessments of internal consistency. The results indicated that the EFI-30 has the same structure and factor loadings in the four countries and that internal consistency for the EFI-30 factors was >0.80 in the four countries. The discrimination values suggest that the instrument can differentiate people with different levels of forgiveness. The analyses in this study indicate that the EFI-30 is a valid and reliable assessment of cognition, behaviour and affect related to forgiveness in the United States, the Philippines, China and Saudi Arabia. Clinicians working in these countries can confidently use this shorter version of the EFI to measure forgiveness.

Psychometrické vlastnosti Dotazníka agresivity Bussa a Perryho (BPAQ)

The primary objective of this research is to assess the psychometric properties of the Buss and Perry Aggression Questionnaire (BPAQ). Comprising twenty-nine items, the questionnaire was administered to a sample of 922 students aged between 14 and 22 years (74,0% of the respondents were female). Confirmatory factor analysis was employed to scrutinize the questionnaire, utilizing fit indices for assessment. Results indicate that the data sufficiently support the proposed model. Upon exclusion of item BPAQ4, the four-factor structure of the Slovak version of the questionnaire was corroborated: ?2 (343) = 922,118; p < 0,001; RMSEA = 0,043 (90% CI 0,039–0,046); CFI = 0,970 and TLI = 0,967. Further examination through measurement invariance analyses revealed equivalence in factor structure and factor loadings between male and female participants. Reliability assessment of the tool, as measured by coefficients ? and ?, demonstrated satisfactory to high levels, with individual subscales ranging from ? = 0,676 to ? = 0,800, and from ? = 0,671 to ? = 0,780, respectively.

Application of AI for modelling and structural analysis of a parametric 2D frame with voice assistant

Structural calculations are essential for civil engineering, but specialized software for their analysis is limited. The lack of availability of efficient tools has generated the need to explore new ways to optimize these calculations. This work addresses the aforementioned problem, proposing the use of Python and automation technologies to offer an innovative and accessible solution to improve efficiency in the field of structural analysis of 2D frames. This proposal seeks to reduce work times by relying on AI, as well as to promote accessibility in this field. To achieve this purpose, the Python library AnaStruct, specifically designed for structural analysis using matrix methods, is used. This tool enables the detailed definition of structural elements, constraints and loads, as well as the visualization of the analysis results. In addition, the Speech Recognition library is implemented for interaction through voice reception, which speeds up the data entry process and structural analysis commands. Through surveys conducted, it is observed that the program achieved an average reduction of the analysis time between 73.33% and 94.29%, compared to traditional methods. Where 100% of the respondents unanimously confirmed that it improves efficiency, and 78.6% expressed their willingness to recommend it for future projects.

Development and characterization of thin iron-based shape memory alloy prestressing wire

Iron-based shape memory alloys (Fe-SMA) have been used successfully in the previous years as prestressing reinforcement in the form of rebars, rods and flat strips, for various types of structural elements and loading scenarios. This paper introduces a new application of this material in the form of thin wire. An experimental characterization study is presented herein for Fe-SMA wire that was drawn to a diameter of 0.5 mm, regarding its tensile stress-strain response and recovery stress development upon heating, for different activation temperatures and prestraining levels. Furthermore, an investigation is presented regarding the effects of heat treatment conditions on the mechanical response and prestressing performance of the wire. For the optimum heat treatment conditions and activation temperature range considered in this study, the measured tensile strength and recovery stress of the Fe-SMA wire was 1117 MPa and up to 390 MPa, respectively. The results indicate a strong potential of Fe-SMA as a candidate prestressing material where flexible wire cross-sections of small diameter are desired instead of larger, solid cross-section tendons (e.g., multi-strand wire ropes or concrete confinement spirals), or as novel short fiber reinforcement for concrete with prestressing capabilities.

Cross-cultural adaptation and psychometric properties of the Iowa-Netherlands Comparison Orientation Measure for the Brazilian context.

The Iowa-Netherlands Comparison Orientation Measure (INCOM) was developed to measure individual differences in social comparison orientation and has been widely used in research and various different settings. The aim of this study was to adapt the online version of the INCOM and to evaluate its psychometric parameters when applied to a Brazilian population of university students. The procedures were divided into two steps: step 1 - cross-cultural adaptation and analysis of content validity, and step 2 - assessment of psychometric characteristics. Step 1 comprised the processes of translation, evaluation by an expert committee, evaluation by the target population, and back-translation. For step 2, 1,065 university students were recruited and then factor analysis, analysis of reliability, and analysis of validity based on external measures were performed. The adaptation process yielded satisfactory results, including good indicators of content validity. Exploratory factor analysis revealed a two-dimensional structure and adequate factor loadings, except for item 11, which was excluded from the final version. Additionally, the final version of the scale had adequate fit indices (χ2 = 148.45, degrees of freedom [df] = 26; p < 0.001; root mean square error of approximation [RMSEA] = 0.06; comparative fit index [CFI] = 0.99; and Tucker-Lewis index [TLI] = 0.98). Evidence of reliability (Cronbach's alpha = 0.83) was observed and there were positive correlations with negative affect (r = 0.36) and negative correlations with positive affect and self-esteem (r = -0.15; r = -0.41, respectively). The Brazilian version of the INCOM presents satisfactory psychometric parameters and can thus be used to measure social comparison orientation.