• Advances in Computational Design
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• v.8 no.4
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• pp.295-307
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• 2023

This paper presents an optimization of the reinforced concrete ribbed slab in terms of minimum CO₂ emissions and an economic justification of the final optimal design. The design variables are six geometry variables including the slab thickness, the ribs spacing, the rib width at the lower and toper end, the depth of the rib and the bar diameter of the reinforcement, and the seventh variable defines the concrete strength. The objective function is considered to be the minimum amount of carbon dioxide gas (CO₂) emission and at the same time, the optimal design is economical. Seven significant design constraints of American Concrete Institute's Standard were considered. A robust metaheuristic optimization method called improved dolphin echolocation and ant colony optimization (IDEACO) has been used to obtain the best possible answer. At optimal design, the three most important sources of CO₂ emissions include concrete, steel reinforcement, and formwork that the contribution of them are 63.72, 32.17, and 4.11 percent respectively. Formwork, concrete, steel reinforcement, and CO₂ are the four most important sources of cost with contributions of 67.56, 19.49, 12.44, and 0.51 percent respectively. Results obtained by IDEACO show that cost and CO₂ emissions are closely related, so the presented method is a practical solution that was able to reduce the cost and CO₂ emissions simultaneously.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.11
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• pp.1603-1611
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• 2010

The comparative study of regression-model-based approximate optimization techniques used in the strength design of an automotive knuckle component that will be under bump and brake loading conditions is carried out. The design problem is formulated such that the cross-sectional sizing variables are determined by minimizing the weight of the knuckle component that is subjected to stresses, deformations, and vibration frequency constraints. The techniques used in the comparative study are sequential approximate optimization (SAO), sequential two-point diagonal quadratic approximate optimization (STDQAO), and approximate optimization based on enhanced moving least squares method (MLSM), such as CF (constraint feasible)-MLSM and Post-MLSM. Commercial process integration and design optimization (PIDO) tools are utilized for the application of SAO and STDQAO. The enhanced MLSM-based approximate optimization techniques are newly developed to ensure constraint feasibility. The results of the approximate optimization techniques are compared with those of actual non-approximate optimization to evaluate their numerical performances.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.68-71
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• 2005

In the case of wind turbine design, Optimization of tower structure is very important because tower generally takes about $20\%$ of overall turbine cost. In this paper, we calculated wind loads considering vortex shedding, and optimized tower flange using the calculation results. For optimization, we used FEM to analyze structural strength of the flange and blade momentum theory to calculate wind loads.

• KCI Concrete Journal
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• v.12 no.1
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• pp.79-89
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• 2000

This research developed an accelerated curing processe for cellulose fiber reinforced cement composites using vigorous reaction between carbon dioxide and cement paste. A wet-processed cellulose fiber reinforced cement system was considered. Carbonation curing was used to complement conventional accelerated curing. The parametric study followed by optimization investigation indicated that the carbonation curing can enhance the productivity and energy efficiency of manufacturing cellulose fiber reinforced cement composites. This also adds environmental benefits to the technical and economical advantages of the technology.

• Journal of the Korean Geotechnical Society
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• v.17 no.6
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• pp.123-133
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• 2001

Since most of soil slopes are in an unsaturated state, it is necessary to consider the unsaturated characteristics of soil slopes, in order to obtain more reasonable results. Therefore in this study we supplemented a slope stability analysis program to consider them, based on the concept of limit equilibrium. We also applied an optimization technique to search for a failure surface. Besides, we carried out experiments to obtain the unsaturated soil properties required in the analysis with weathered granite soils. We formulated a nonlinear apparent cohesion relationship with the matrix suction to be able to apply the unsaturated shear strength characteristics to the stability analysis. In addition, we intended to obtain more accurate soil water characteristic curves(SWCC) by measuring the change in volume of the specimen in the SWCC tests. As a result, we could appropriately assess the change of the safety factor according to the rainfall intensity and duration, by considering the variation of suction, permeability, and shear strength caused by the infiltration of rainfall into slopes.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.10a
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• pp.132-136
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• 2009

The importance and interests for saving of energy and cost in industry has been steadily grown up. Therefore, process optimization to reduce the processing step and energy is one of the most important things. The micro-alloyed steel of which post-heat-treatment is not necessary, has attractive points for high strength materials. However, for the application of non-heat-treated steel to structural parts, it is necessary to confirm the reliability of mechanical properties. In order to estimate mechanical properties. The microstructure, hardness, tensile strength, compressive strength and tensile fatigue strength of micro-alloyed steel having 900MPa tensile strength has been investigated.

• Journal of Ocean Engineering and Technology
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• v.15 no.2
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• pp.124-129
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• 2001

The research on anticorrosive of valve for ship, waterworks, and drainage system is very important. The purpose of this paper is to develop the metal/polyurethan adhesive technique at insider of the value to prevent corrosion in the value. It is performed to the bending strength test by using metal /polyurethan in the metals (SB41, Al6061). It is investigated to the effects of bending strength on curing temperature, preheating time and curing time, and to the fracture mechanism of metal/polyurethan adhensived specimen. As a results, we find that the bending strength is the highest at curing temperature of 11$0^{\circ}C$ and the curing time is 60 minutes in metal/polyurethan adhesive specimen.

• Geomechanics and Engineering
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• v.20 no.3
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• pp.191-205
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• 2020

Soil shear strength parameters play a remarkable role in designing geotechnical structures such as retaining wall and dam. This study puts an effort to propose two accurate and practical predictive models of soil shear strength parameters via hybrid artificial neural network (ANN)-based models namely genetic algorithm (GA)-ANN and particle swarm optimization (PSO)-ANN. To reach the aim of this study, a series of consolidated undrained Triaxial tests were conducted to survey inherent strength increase due to addition of polypropylene fibers to sandy soil. Fiber material with different lengths and percentages were considered to be mixed with sandy soil to evaluate cohesion (as one of shear strength parameter) values. The obtained results from laboratory tests showed that fiber percentage, fiber length, deviator stress and pore water pressure have a significant impact on cohesion values and due to that, these parameters were selected as model inputs. Many GA-ANN and PSO-ANN models were constructed based on the most effective parameters of these models. Based on the simulation results and the computed indices' values, it is observed that the developed GA-ANN model with training and testing coefficient of determination values of 0.957 and 0.950, respectively, performs better than the proposed PSO-ANN model giving coefficient of determination values of 0.938 and 0.943 for training and testing sets, respectively. Therefore, GA-ANN can provide a new applicable model to effectively predict cohesion of fiber-reinforced sandy soil.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.287-292
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• 2022

In this paper, the stochastic distribution of the springback amount is investigated for the stamping process of a U-channel shaped-product with ultra-high strength steel. Using the reliability-based design optimization technique (RBDO), stochastic distribution of process parameters is considered in the analysis including material properties and process variation. Quantification of the springback scatters is carried out with the statistical analysis method according to the material strength. It is found that the scattering amount of springback decreases while the amount of springback increases as the tensile strength of the blank material increases, which is investigated by analyzing the strain and stress distribution of the punch and die shoulder. It is noted that the proposed scheme is capable of predicting and responding to the unavoidable scattering of springback in the sheet metal forming process.

• Steel and Composite Structures
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• v.52 no.2
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• pp.145-163
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• 2024

This paper presents six novel hybrid machine learning (ML) models that combine support vector machines (SVM), Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), extreme gradient boosting (XGB), and categorical gradient boosting (CGB) with the Harris Hawks Optimization (HHO) algorithm. These models, namely HHO-SVM, HHO-DT, HHO-RF, HHO-GB, HHO-XGB, and HHO-CGB, are designed to predict the ultimate strength of both rectangular and circular reinforced concrete (RC) columns. The prediction models are established using a comprehensive database consisting of 325 experimental data for rectangular columns and 172 experimental data for circular columns. The ML model hyperparameters are optimized through a combination of cross-validation technique and the HHO. The performance of the hybrid ML models is evaluated and compared using various metrics, ultimately identifying the HHO-CGB model as the top-performing model for predicting the ultimate shear strength of both rectangular and circular RC columns. The mean R-value and mean a20-index are relatively high, reaching 0.991 and 0.959, respectively, while the mean absolute error and root mean square error are low (10.302 kN and 27.954 kN, respectively). Another comparison is conducted with four existing formulas to further validate the efficiency of the proposed HHO-CGB model. The Shapely Additive Explanations method is applied to analyze the contribution of each variable to the output within the HHO-CGB model, providing insights into the local and global influence of variables. The analysis reveals that the depth of the column, length of the column, and axial loading exert the most significant influence on the ultimate shear strength of RC columns. A user-friendly graphical interface tool is then developed based on the HHO-CGB to facilitate practical and cost-effective usage.