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Numerical simulations were performed in this work to assess the impact of the ratio of live-to-dead load ( ρ ) and the stiffness variability of the constitutive materials on the accidental torsional response of buildings. Three values of ρ (0.2, 0.5 and 0.8) and two materials (reinforced concrete and steel) were studied. Story drifts and ductility demands were the main structural response parameters analyzed to evaluate the significance of both variables. Six structural models, representative of frame buildings with different lateral vibration periods (0.25 to 1.5 s), were subjected to five earthquake ground motions recorded on firm soils. With the Monte Carlo method, the intensity and location of the live load, as well as the flexural stiffness of the structural members, were randomly varied to simulate building cases with accidental torsion. According to the results, the effect of the live-to-dead load ratio ( ρ ) on the torsional response is more significant than that of the material stiffness variation. For both materials, the maximum torsion response for ρ  = 0.8 resulted 66% greater than that for ρ  = 0.2. For both materials and considering all earthquakes and structural models, the increase in the average peak accidental torsional response for ρ  = 0.8 was approximately 20% greater than that for ρ  = 0.2. These results corroborate that the accidental torsional response of buildings increases in proportion to ρ . Discrimination between concrete and steel buildings was not significant.

“The population of India is the second highest in the world as per the 2022 report” [1]. In order to live well, there is an increasing demand for adequate infrastructure. People are migrating from rural to urban regions. Problems will rise due to the high population in urban areas. Due to a lack of available land for construction in metropolitan areas, high-rise building structures are becoming more necessary to address the population density issue. High-rise structures are in high demand, and their construction must be completed without compromising any of the three criteria of cost, timeliness, and safety. AutoCAD design software enables the production of both 2D and 3D drawings for use in constructing multi-story buildings. This study aims to utilize the software package STAAD-Pro to analyze and design a multi-story building, following the production of 2D and 3D drawings using AutoCAD. STAAD-Pro offers a far quicker method of structural analysis and planning for the likelihood of the fewest faults. The design involves load calculations and analyzing the whole structure by STAAD Pro. “The method used in STAAD Pro analysis is Limit State Design followed by Indian Standard Codes. The loads considered for designing the building are dead loads, live loads, and Wind loads. For analyzing a multi-storied building, one has to consider all the possible loadings and see that the structure is safe against all possible loading conditions” [2]. The aim of this study is to analyze the structural behavior of the building and ensure that it meets the necessary design standards and codes. To remain competitive in the constantly expanding market, it is crucial for structural engineers to optimize their time management. This study highlights the importance of using advanced software tools in the design and analysis of complex structures to ensure their safety and stability.

Autonomous microgrids (ATMG), with green power sources, like solar and wind, require an efficient control scheme to secure frequency stability. The weather and locationally dependent behavior of the green power sources impact the system frequency imperfectly. This paper develops an intelligent, i.e., fuzzy logic-based sliding mode control (F-SMC) utilizing a proportional-integral-derivative (PID) type sliding surface to regulate the frequency of a wind-diesel generator-based ATMG system. A dynamic structure of the wind generator is designed to participate in the frequency support of the considered plant. The mastery of the F-SMC is analyzed over the conventional SMC (C-SMC) under load perturbation. This study used the artificial gorilla troop optimization (GTO) technique to tune the F-SMC parameters. The effectiveness of the GTO-tuned F-SMC frequency regulation (FR) scheme is compared with well-established particle swarm optimization (PSO) and grey wolf optimization (GWO) approaches under various scenarios such as load perturbations, governor dead band (GDB), generation rate constraint (GRC), higher/lower dimensions of ATMG, and wind speed variations. Finally, the proposed GTO-based F-SMC approach has been validated upon a standard IEEE-14 bus system and compared with recent techniques.

The abstract for a study on parametric design and analysis of PEBs, comparing with the portal arrangement, focuses on variations of bay spacing and Roof angle parameters and percentage variation in effective weight (MT) of structure. A pre-engineered steel building will be designed with different parameters using the software Staadprov8i and analyzed with different loads on the building i.e. dead load, live load, collateral load, Earthquake load, wind load, and load combinations on the building by using appropriate codes. Finite Element Analysis (FEA) and other simulation methods will be employed to evaluate the structural integrity of the PEBs under different loading conditions. Determining the structure’s lowest weight and the significant displacements or forces in each direction will contribute to the structure’s stability and safety. Pre-engineered structures and high-quality construction methods are part of the pre-engineered construction idea, which will reduce the duration and cost of construction. This study aims to provide valuable insights that can guide the development of more efficient and adaptable pre-engineered building solutions in the construction industry.

Effective wildfire management and prevention strategies depend on accurate forecasts of fire occurrence and propagation. Fuel load and fuel moisture content are essential variables for forecasting fire occurrence, and whilst existing operational systems incorporate dead fuel moisture content, both live fuel moisture content and fuel load are either approximated or neglected. We propose a mid-complexity model combining data driven and analytical methods to predict fuel characteristics. The model can be integrated into earth system models to provide real-time forecasts and climate records taking advantage of meteorological variables, land surface modelling, and satellite observations. Fuel load and moisture is partitioned into live and dead fuels, including both wood and foliage components. As an example, we have generated a 10-year dataset which is well correlated with independent data and largely explains observed fire activity globally. While dead fuel moisture correlates highest with fire activity, live fuel moisture and load are shown to potentially enhance prediction skill. The use of observation data to inform a dynamical model is a crucial first step toward disentangling the contributing factors of fuel and weather to understand fire evolution globally. This dataset, with high spatiotemporal resolution (∼9 km, daily), is the first of its kind and will be regularly updated.

The study employs finite element method to examine the effects of curve angle variations on the behavior of single and double-cell prestressed concrete box-girder bridges. A total of eighty bridge models were examined, featuring a range of curve angles from 0 to 60°, with increments of 12° between each model (0°, 12°, 24°, 36°, 48°, and 60°). The study revealed that bridges with curve angles of 24° or less exhibit minimal impact on forces, suggesting that they can be effectively treated as straight bridges for analytical purposes. The study revealed a marked change in structural response for bridges with curve angles greater than 24°, highlighting the influence of increased curvature on bridge behavior. A comprehensive evaluation was conducted to investigate the influence of changes in curve angles, span lengths, cell numbers, and span–depth ratios on structural forces and deflections under various load types, including dead, live, and prestressed loads. As the curve angle increases, a corresponding decrease in the flexural moment and vertical deflection is observed under prestressed loading conditions. Based on the analysis, it is reasonable to conclude that prestressed concrete box-girder bridges are best suited for applications involving higher curve angles.

The objective of this paper is to assess the creep law of natural salt in a small deviatoric stress range. In this range, creep is suspected to be much faster than what is predicted by most constitutive laws used in the cavern and mining industries. Five 2-year, multistage creep tests were performed with creep-testing devices set in a gallery of the Altaussee mine in Austria to take advantage of the very stable temperature and humidity conditions in this salt mine. Each stage was 8-month long. Dead loads were applied, and vertical displacements were measured through gages that had a resolution of 12.5 nm. Loading steps were 0.2, 0.4, and 0.6 MPa, which are much smaller than the loads that are usually applied during creep tests (5–20 MPa). Five salt samples were used: two samples were cored from the Avery Island salt mine in Louisiana, United States; two samples were cored from the Gorleben salt mine in Germany; and one sample was cored from a deep borehole at Hauterives in Drôme, France. During these tests, transient creep is relatively long (6–10 months). Measured steady-state strain rates (\\[\\dot {\\varepsilon }\\] = 10−13–10−12 s−1) are much faster (by 7–8 orders of magnitude) than those extrapolated from relatively high-stress tests (σ = 5–20 MPa). When compared to n = 5 within the high-stress domain for Gorleben and Avery Island salts, a power-law stress exponent within the low-stress domain appears to be close to n = 1. These results suggest that the pressure solution may be the dominant deformation mechanism in the steady-state regime reached by the tested samples and will have important consequences for the computation of caverns or mines behavior. This project was funded by the Solution-Mining Research Institute.

The current practice in civil engineering is to provide designs with a certain level of safety, which makes it necessary to forecast how a system will perform with minimal or no prior knowledge. These current design methodologies commonly fall short of expectations in unexpected contexts since they are typically only learned via several iterations of trial and error. This study examined the reliability of a typical Howe-type steel roof truss system used for a recently constructed mega-church in one of Nigeria’s main cities. To help the designer determine the expected performance and suitable safety levels for such steel roof truss construction, the design data were applied to the other 11 major cities from the six geopolitical zones in Nigeria. To produce identical policy guidelines to the designer, the dimensional requirements for the roof truss were also reproduced for a span of 12 m, a truss height of 3 m and 28 m, and a height of 5 m in all the zones. For every truss element, a reliability index was developed to measure the structural performance based on the likelihood of failure. The reliability indices were found to be quite sensitive to the size of the steel sections employed. Therefore, as the number of steel sections employed in the design increases, the safety indices, reduce, suggesting an increase in dead loads. Based on the system-level probability of failure of the truss members, contour maps were developed. Therefore, it is advised that the reliability concept be used in the reevaluation of both new and old civil structures. Highlights A typical Howe roof truss system under practical loading using the same height-to-span ratio in all the selected geographical zones is presented. The effect of wind pressure on the roof system is determined. Statistical models for the relevant design variables for the roof trusses and development of probability of failure for the designed truss systems under uncertainties in loading and material properties were established; and. A guide for the designers on the expected performance and appropriate safety levels for Howe roof trusses in Nigeria is presented.

Fine dead fuel load is one of the most significant components of wildfires without which ignition would fail. Several studies have previously investigated 1-h fuel load using standard fuel parameters or site-specific fuel parameters estimated ad hoc for the landscape. On the one hand, these methods have a large margin of error, while on the other their production times and costs are high. In response to this gap, a set of models was developed combining multi-source remote sensing data, field data and machine learning techniques to quantitatively estimate fine dead fuel load and understand its determining factors. Therefore, the objectives of the study were to: (1) estimate 1-h fuel loads using remote sensing predictors and machine learning techniques; (2) evaluate the performance of each machine learning technique compared to traditional linear regression models; (3) assess the importance of each remote sensing predictor; and (4) map the 1-h fuel load in a pilot area of the Apulia region (southern Italy). In pursuit of the above, fine dead fuel load estimation was performed by the integration of field inventory data (251 plots), Synthetic Aperture Radar (SAR, Sentinel-1), optical (Sentinel-2), and Light Detection and Ranging (LIDAR) data applying three different algorithms: Multiple Linear regression (MLR), Random Forest (RF), and Support Vector Machine (SVM). Model performances were evaluated using Root Mean Squared Error (RMSE), Mean Squared Error (MSE), the coefficient of determination (R2) and Pearson’s correlation coefficient (r). The results showed that RF (RMSE: 0.09; MSE: 0.01; r: 0.71; R2: 0.50) had more predictive power compared to the other models, while SVM (RMSE: 0.10; MSE: 0.01; r: 0.63; R2: 0.39) and MLR (RMSE: 0.11; MSE: 0.01; r: 0.63; R2: 0.40) showed similar performances. LIDAR variables (Canopy Height Model and Canopy cover) were more important in fuel estimation than optical and radar variables. In fact, the results highlighted a positive relationship between 1-h fuel load and the presence of the tree component. Conversely, the geomorphological variables appeared to have lower predictive power. Overall, the 1-h fuel load map developed by the RF model can be a valuable tool to support decision making and can be used in regional wildfire risk management.

The high-altitude assembly and tensioning construction of large-span beam string structures (BSS) offers numerous advantages, including structural simplicity, clear force transmission, minimal deformation, strong stability, structural adaptability, self-balancing capability, and ease of construction. However, it also presents technical challenges such as complex loading behavior, difficult deformation control, and high precision requirements during construction. This paper, based on the practical application in the Lingshui Gymnasium project in Hainan, employs a combination of theoretical analysis, numerical calculation, and in-situ testing to investigate the mechanical response characteristics of large-span BSS roofs. Under self-weight, the displacement of the support scaffolding causes the mid-span deflection on the left side of the beam-string to be greater than that on the right side. After the staged tensioning is completed, the mid-span of the beam-string exhibits an upward arching phenomenon. Under the standard combination of dead load and live load, the maximum deflection occurs at the mid-span of the beam-string, with a deflection-to-span ratio of 1/423, which meets the serviceability requirements. In terms of the improvement and innovation of construction technology, the supporting tire frame, tension cable, gusset, early warning and other aspects have been improved and innovated, and these improvements provide support for the improvement of the construction technology of the large-span tensioned string girder structure as well as the development and scientific and technological progress of the industry.