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Sensitivity and Optimization Analysis of Torsional Behavior in Multicellular Thin-Walled Tubes
Get PDFMulticellular thin-walled tubes are widely used due to their lightweight, economical design, and superior shear and torsional performance. Their design is sometimes governed by the available materials and the required dimensions. The current study uses advanced sensitivity analysis with meta-modeling tools to understand how different geometric and mechanical factors affect the torsional performance of multicellular thin-walled tubes. The geometric factors include the length, thickness, and width of the beams, while the mechanical properties involve the shear modulus. Variance-based sensitivity analysis is used to assess how variations in these factors impact the rate of twist, torsional stiffness, and shear stress. The interconnected relations between input parameters are exploited for optimal design and superior performance. The results revealed that for a three-celled tube, thick horizontal interior elements with thin deep vertical elements and thin exterior elements provide an optimal design when the cross-sectional area is constrained. This finding, combined with varying the geometrical and material properties, results in an optimal design using CFRP composites when constrained by minimizing the total weight and superior torsional performance. The analysis can be extended to include other constraint(s), but changing the design constraints might change the optimal design. Doi: 10.28991/CEJ-2024-010-09-09 Full Text: PD
Rainfall-Runoff Modeling in a Regional Watershed Using the MIKE 11-NAM Model
Get PDFThis study used the MIKE 11 NAM model to model stormwater runoff in a northern Iraqi regional watershed of the Greater Zab River. During model calibration (2003-2017), observed data on streamflow, evaporation, and rainfall were used to optimize the nine model parameters. In order to validate the model, independent data covering the years 2018 through 2022 was used. The model's efficacy was evaluated using statistical performance metrics, including the coefficient of determination (R2), Nash Sutcliffe efficiency coefficient (NSE), and Root Mean Square Error (RMSE). During calibration (NSE = 0.81, RMSE = 2.2, and R² = 0.82) and validation (NSE = 0.90, RMSE = 6.9, and R² = 0.93), the model's performance demonstrated good agreement between simulated runoff and observed. The good agreement was for the low stream flow values compared to the high ones, due to the low number of parameters, which makes it easier to calibrate. Often, hydrological models do not capture peak flow phenomena, but there is a tendency for a good estimate of the low and medium stream flow values. Approximately 69% of the nutrient flow into the basin originated from the catchment area, which lies inside Iraq, while the remaining 31% came from the Turkey watershed. Future hydrological modeling in the area at the watershed level can utilize this model. Doi: 10.28991/CEJ-2024-010-12-08 Full Text: PD
Sensor Layout Design for Structural Health Monitoring
Get PDFThis study investigates the enhancement of optimal sensor placement (OSP) algorithms by incorporating modal reduction constraints and developing combined techniques. The primary goal is to optimize sensor placement for structural health monitoring (SHM), thereby improving the efficiency of information acquisition within practical constraints. The proposed methodology utilizes iterative elimination and combined criteria to evaluate various sensor configurations. Numerical experiments demonstrate distinct sensor layouts derived from diverse algorithmic approaches. The study's novel contributions include the integration of modal strain energy, effective independence (EI), and modal assurance criterion (MAC) techniques into a unified framework, enhancing adaptability to a wide range of SHM scenarios. Doi: 10.28991/CEJ-2024-010-12-011 Full Text: PD
A Comprehensive Approach to Assess Occupant's Satisfaction and Performances of Residential Building
Get PDFThis paper aims to endeavor to develop a holistic Post Occupancy Evaluation (POE) framework, amalgamating the utilization of building facilities and Building Performance Attributes (BPA) for appraising the performance of Construction and Design Firms (CDFs) alongside building performance indicators such as occupant satisfaction within residential apartment complexes. The study adopts a tripartite research methodology encompassing theoretical exploration, on-site investigations, and analytical examinations. The theoretical component entails an extensive literature survey to integrate 15 identified BPAs seamlessly. Field inquiries involve rating building performance and gauging occupant contentment. The subsequent analytical phase establishes correlations between building performance metrics and occupant satisfaction levels. This systematic approach synergizes user insights with building services, promising a rigorous and systematic building analysis. The outcomes underscore a robust correlation linking building performance attributes to occupant satisfaction, thus affirming the pivotal role of POE as an indispensable tool for appraising building performance. The analysis reveals ten highly correlated parameters, indicating a substantial 67% connection between the Building Performance Rating (BPR) and the Occupant Satisfaction Score (OSS). These influential parameters guide improvements and updates through Post-Occupancy Evaluations (POE). This process is a valuable learning tool for enhancing future organizational projects and improving building performance. The findings emphasize the pertinence of the criteria employed in evaluating building performance, which is relevant for assessing occupant contentment and CDF's effectiveness. Comparing the previous research, this research posits the potential for widespread adoption of POE in augmenting CDFs' performance and lays the groundwork for expanding its utilization. The scholarly exploration introduces novel perspectives and paves the way for a comprehensive integration of POE to enhance CDFs' operational proficiency. Doi: 10.28991/CEJ-2024-010-02-07 Full Text: PD
Artificial Intelligence Models for Predicting the Compressive Strength of Geopolymer Cements
Get PDFThe utilization of nanosilica and cellulose nanocrystals (CNCs) in cement geopolymers remains challenged by intricacies and uncertainties regarding their concentration, posing difficulties in the formulation of systematic geopolymer mix designs. This study aims to formulate models based on Artificial Neural Networks (ANN) capable of forecasting the compressive strength of geopolymers through the utilization of experimentally acquired data. Nanosilica was applied at concentrations of 2%–4% and CNCs at 1%–3%. ANN was modeled using MATLAB to predict the compressive strength of the geopolymer. The results indicated an effect of nanosilica and CNCs on the compressive strength of geopolymer at 2%–4% concentration and 1%–3% CNCs. The best ANN was the GDX training function, purelin activation function, LGD and LGDM learning functions, Lr 0.1 and 0.01 at the number of epochs 3812 out of 25000 and 1774 out of 25000, resulting in the best correlation values of 0.994 and 0.959; the lowest RMSE values are 0.022 and 0.110. The results of the ANN model built based on actual data prove that the model is helpful for accurate simulation to predict the compressive strength of geopolymer cement. This study contributes novelty by optimizing the design model for Geopolymer Cements incorporating nanosilica and CNCs. Doi: 10.28991/CEJ-SP2024-010-03 Full Text: PD
Application of the Arrhenius Equation in Predicting the Temperature Susceptibility of Unmodified and Modified Bituminous Binder
Get PDFBitumen is a temperature-susceptible material. The performance of the bitumen largely depends on the sensitivity of its characteristic properties to the variation in temperature. This paper uses the Arrhenius equation to predict the temperature-sensitive properties of various bitumens. Three modified and unmodified binders of various grades were tested under study shear, frequency mode (oscillatory shearing), and time mode (multiple stress creep and recovery) at different temperatures from 10 to 70ºC. This paper focuses on the activation energy to understand the temperature-susceptible behavior of the bitumen and the influence of aging on the bitumen. To analyze the temperature susceptibility of the bitumen, Steady shear, MSCR, and LAOS tests were performed. From these tests, parameters such as viscosity, dynamic modulus, energy dissipation, and creep compliance at different temperatures were observed to follow the Arrhenius equation. The activation energy constant of the Arrhenius equation is found to vary with the characteristic function used. It is also statistically proven that the activation energy depends on the shear rate or shear stress, indicating that the temperature-susceptible properties of the bitumen are shear rate-dependent. Also, as the bitumen ages, its temperature-susceptible properties improve. Doi: 10.28991/CEJ-2024-010-03-015 Full Text: PD
Influence of Filler Materials on Bituminous Mastic Rheology at High Temperatures
Get PDFThe mixing and compaction temperatures of the bituminous mixture are determined by the viscosity of the binder. It was always a concern to understand the influence of the type of filler on the workability of the bituminous mixture. The interaction of the filler with the bitumen plays a key role in this. The inert filler has a physical interaction with the binder, and the active filler will have both a physical and chemical interaction. Based on the type of interaction, the viscosity and shear thinning characteristics of the mastic (binder + filler) change, which will hence influence the workability of the bituminous mixture. An experimental investigation is conducted to measure the viscosity of the mastic with two types of filler, one chosen from the active filler category (hydrated lime) and another from the inert filler category (quarry dust). A shear rate sweep experiment was carried out within the temperature range of 100 to 160 °C to analyze the Newtonian and shear thinning responses of the mastic. Results indicate that, for an equivalent weight proportion of the filler, mastic containing quarry dust exhibited elevated Newtonian viscosity and zero-shear viscosity (as predicted using the Carreau Yasuda Model). Additionally, quarry dust mastic demonstrated a higher rate of shear thinning. Consequently, the beneficial effect of shear thinning during the compaction of bituminous mixtures has the potential to enhance workability and streamline the compaction process. Doi: 10.28991/CEJ-2024-010-02-013 Full Text: PD
Turbidity Removal Performance of Selected Natural Coagulants for Water Treatment in Colombian Rural Areas
Get PDFDespite the recognized efficiency of natural coagulants, their widespread adoption in the water treatment industry remains low. Our study evaluates the effectiveness of three natural coagulants”Moringa Oleifera, Yausa (Abutilon Insigne Planch), and Breadfruit (Artocarpus Altilis)”in reducing water turbidity levels of 40–50 NTU. Among these, two are native plant species potentially applicable in rural Colombian areas, where there are evident disparities in water infrastructure. This research contributes to the development of these coagulants, exploring their integration with existing water treatment methods, determining their optimal concentrations, and efficiencies in turbidity removal. Our findings reveal significant turbidity removal efficiencies: 88.9% for Moringa Oleifera, 83.3% for Yausa, and 67.2% for Breadfruit. These results indicate the feasibility of these agents as sustainable replacements for traditional chemical coagulants, exhibiting a level of effectiveness alike to that observed in Moringa Oleifera. However, challenges in practical implementation and sustainability, covering technical, environmental, economic, and social aspects, are notable obstacles. The aim of this study is to not only demonstrate the effectiveness of these natural coagulants but also to encourage their broader acceptance and integration into sustainable water treatment practices incorporating two unstudied plant species, such as Yausa and Breadfruit, furthering research to overcome existing challenges. Doi: 10.28991/CEJ-2024-010-02-020 Full Text: PD
Applicability of Numerical Simulation by Particle Method to Unconfined Compression Tests on Geomaterials
Get PDFThis study emphasizes the importance of accurate input parameters for ensuring the precision and reliability of simulations by conducting a sensitivity analysis to determine the calculation and material parameters. The aim is to determine the exact material parameters, for two different soil samples in a rigid state, by comparing the results of a sensitivity analysis with the unconfined compression test benchmark data for each sample. The moving particle semi-implicit (MPS) method, one of the particle methods, was chosen to reproduce the unconfined compression test simulation. The soil particles were assumed to be in the rigid state of the Bingham fluid bi-viscosity model. The first part of the study focuses on a sensitivity analysis of the basic simulation parameter values inputted during the simulation setup for the calculation procedure and the selection of the criteria for the calculation method, and then recommends the optimum values for a higher degree of accuracy based on the results. The second part of the study uses the results to analyze the sensitivity of each influencing parameter of the bi-viscosity Bingham fluid. In the final section, this study will provide a general guideline for selecting the optimum values for the MPS parameters and will recommend approximate values for other soil samples in future research with properties similar to those used in this study. Doi: 10.28991/CEJ-2024-010-01-01 Full Text: PD
Eco-friendly 3D Printing Mortar with Low Cement Content: Investigation on Printability and Mechanical Properties
Get PDFThe conventional approach to achieving optimal printability and buildability in 3D printing mortar relies heavily on cement, which is both costly and environmentally detrimental due to substantial carbon emissions from its production. This study aims to mitigate these issues by investigating the viability of slag as a partial substitute for cement, with the goal of developing an eco-friendly alternative. The newly formulated mortar, featuring a 30% reduction in cement content (from 830 to 581 kg/m3) and the inclusion of 0.10% micro-fibers, exhibits properties comparable to conventional 3D printing mortar. The research is structured into two parts: Part 1 focuses on determining the optimal fiber content, while Part 2 delves into the investigation of fiber-reinforced mortar with reduced cement content for 3D printing. Criteria were established to ensure mortar flow at 115%, initial printable time below 60 minutes, and 7-day compressive strength exceeding 28 MPa. Part 1 results indicate that a fiber content of 0.1% by volume meets the specified requirements. In Part 2, it was observed that increasing the slag replacement percentage extended the initial printable time and time gap. However, even at a 30% replacement rate, the initial printable time remained within the acceptable range, partially attributed to the presence of fibers in the mix. Additionally, higher slag content led to increased flow and reduced filament height in the mixes. Notably, all formulations surpassed the 7-day compressive strength threshold. These findings underscore the potential of slag as a sustainable alternative to cement in 3D printing fiber-reinforced mortar, offering promising prospects for environmentally friendly construction practices. Doi: 10.28991/CEJ-2024-010-03-010 Full Text: PD