• Journal of the Korean Geotechnical Society
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• v.24 no.1
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• pp.119-130
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• 2008

Uncertainties in physical and engineering parameters for the design of shallow foundations arise from various aspects such as inherent variability and measurement error. This paper aims at investigating and reducing uncertainty from deterministic method by using the reliability-based design of shallow foundations accounting for the variation of various design parameters. A probability distribution type and statistics of random variables such as unit weight, cohesion, infernal friction angle and Young's modulus in geotechnical engineering are suggested to calculate the ultimate bearing capacities and immediate settlements of foundations. Reliability index and probability of failure are estimated based on the distribution types of random variables. Widths of foundation are calculated at target reliability index and probability of failure. It is found that application and analysis of the best-fit distribution type for each random variables are more effective than adoption of the normal distribution type in optimizing the reliability-based design of shallow foundations.

• Journal of the Korean Geotechnical Society
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• v.40 no.5
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• pp.7-20
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• 2024

Ground improvement techniques through soil densification are widely used to enhance the cyclic resistance and seismic performance of liquefiable soils. However, most studies have primarily focused on the increase in soil strength before and after ground improvement, with limited investigation into changes in spatial statistical characteristics. This study aims to identify the changes in soil strength and spatial variability due to ground improvement by analyzing data from 19 cases where ground improvement was conducted using timber piles, aggregate piers, and dynamic compaction, with a cone penetration test (CPT) performed pre- and post-improvement. The changes in cone tip resistance were evaluated by comparing cone tip resistance profiles before and after ground improvement, while changes in spatial variability were assessed by examining variations in three parameters of the random field: mean (or trend function), variance, and scale of fluctuation. The results indicate that cone tip resistance generally increased, while inherent variability tended to decrease. The scale of fluctuation, representing spatial autocorrelation, generally increased following ground improvement, with higher initial fluctuation parameters correlating with a greater rate of increase. Furthermore, the probabilistic analysis of liquefaction-induced settlement revealed that changes in the scale of fluctuation due to ground improvement significantly influenced the variability of settlement, underscoring the importance of considering this factor.

• Structural Engineering and Mechanics
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• v.50 no.3
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• pp.305-322
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• 2014

Reliability-based design limit states and associated partial load factors provide a consistent level of design safety across bridge types and members. However, limit states in the current AASHTO LRFD have not been developed explicitly for the situation encountered by integral abutment bridges (IABs) that have unique boundary conditions and loads with inherent uncertainties. Therefore, new reliability-based limit states for IABs considering the variability of the abutment support conditions and thermal loading must be developed to achieve IAB designs that achieve the same safety level as other bridge designs. Prestressed concrete girder bridges are considered in this study and are subjected to concrete time-dependent effects (creep and shrinkage), backfill pressure, temperature fluctuation and temperature gradient. Based on the previously established database for bridge loads and resistances, reliability analyses are performed. The IAB limit states proposed herein are intended to supplement current AASHTO LRFD limit states as specified in AASHTO LRFD Table 3.4.1-1.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.5
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• pp.206-214
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• 1996

Because of the wide variety of the composite materials, inherent variability in properties, and complex temperature and strain rate dependence, large strain behavior of these materials has not been well characterized. Large strain behavior under uniaxial tension is characterized over a range of temperatures and strain rates, and a modified simple linear viscoelastic model is fit to the observed data. Of particular importance is the strain rate and temperature dependence of these composites, and it is the primary focus of this study. The strain rate and temperature dependence is then used to predict limiting tensile strains, based on Marciniak imperfection theory. Excellent correlation was obtained between model and experiment and the results are summarized in maps of forming limit as a function of strain rate and temperature.

• Journal of Korean Society for Quality Management
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• v.31 no.4
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• pp.239-246
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• 2003

Dynamic robust design has been regarded as the most powerful design methodology for improving product quality, Dynamic SN ratio adopted in dynamic robust design combines two major quality attributes, the variability around the linear function and the slope of the linear function, into a single design metric. The principal shortcoming associated with the dynamic SN ratio is that the metric is independent of designer's preferences for the quality attributes due to priori sets of attribute tradeoff values inherent in it. Therefore, a more rigorous preference­based design metric to accurately capture designer's intent and preference is needed. A new design metric that can be used in dynamic robust design is proposed. The effectiveness of the proposed design metric is examined with the aid of a demonstrative case study and the results are discussed.

• Proceedings of the Korea Concrete Institute Conference
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• 1989.10a
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• pp.69-72
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• 1989

It is widely recognized that the strength of reinforced concrete members has characteristics of random variations due to the variability of the mechanical properties of concrete and steel, the dimensional error as well as incorrect placement of reinforcing bars. In those sources of randomness, variations in concrete strength may be the one affecting the strength of R.C. members most. The concrete strength is usually assumed to have large uncertainty due to the variations in many factors, such as material properties, proportions of the concrete mix, methods of mixing, transporting, placing and curing, etc. In this study, the random characteristics inherent in the strength of field-cast concrete have been examined based on the data collected by testing standard cylinders made of field-cast concrete and cured under in-situ condition.

• Structural Engineering and Mechanics
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• v.37 no.6
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• pp.685-691
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• 2011

Developing accurate prediction models for deterioration behavior represents a challenging but essential task in comprehensive Infrastructure Management Systems. The challenge may be a result of the lack of historical data, impact of unforeseen parameters, and/or the past repair/maintenance practices. These realities contribute heavily to the noticeable variability in deterioration behavior even among similar components. This paper introduces a novel approach to predict the deterioration of any infrastructure component. The approach is general as it fits any component, however the prediction is custom for a specific item to consider the inherent impacts of expected and unexpected parameters that affect its unique deterioration behavior.

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.1
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• pp.65-75
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• 1993

Fuzzy data is a phenomenon often occurring in real life. There is the inherent vagueness of classification terms referring to a continuous scale, the uncertainty of linguistic terms such as "I almost agree" or the vagueness of terms and concepts due to the statistical variability in communication [20] and many more. Previously, such fuzzy data was approximated by non-fuzzy (crisp) data, which obviously did not lead to a correct and precise representation of the real world. Fuzzy set theory has been developed to represent and manipulate fuzzy data [18]. Explicitly managing the degree of fuzziness in databases allows the system to distinguish between what is known, what is not known and what is partially known. Systems in the literature whose specific objective is to handle imprecision in databases present various approaches. This paper is concerned with the different ways uncertainty and imprecision are handled in database design. It outlines the major areas of fuzzification in (relational) database systems.

• Structural Engineering and Mechanics
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• v.33 no.4
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• pp.529-537
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• 2009

A key parameter in the design of a laterally loaded pile is the determination of its performance level. Performance level of a pile is usually expressed as the maximum head deflection and bending moment. In general, uncertainties in the performance of a pile originates from many factors such as inherent variability of soil properties, inadequate soil exploration programs, errors taking place in the determination of soil parameters, limited calculation models as well as uncertainties in loads. This makes it difficult for practicing engineers to decide for the reliability of laterally loaded piles both in cohesive and cohesionless soils. In this paper, limit state functions and consequent performance functions are obtained for single concrete piles to predict the maximum bending moment, a widely accepted design criterion along with the permissible pile head displacement. Analyses were made utilizing three dimensional finite element method and soil-structure-interaction (SSI) effects were accounted for.

• Journal of Mechanical Science and Technology
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• v.20 no.10
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• pp.1662-1669
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• 2006

Since randomness and uncertainties of design parameters are inherent, the robust design has gained an ever increasing importance in mechanical engineering. The robustness is assessed by the measure of performance variability around mean value, which is called as standard deviation. Hence, constraints in robust optimization problem can be approached as probability constraints in reliability based optimization. Then, the FOSM (first order second moment) method or the AFOSM (advanced first order second moment) method can be used to calculate the mean values and the standard deviations of functions describing constraints and object. Among two methods, AFOSM method has some advantage over FOSM method in evaluation of probability. Nevertheless, it is difficult to obtain the mean value and the standard deviation of objective function using AFOSM method, because it requires that the mean value of function is always positive. This paper presented a special technique to overcome this weakness of AFOSM method. The mean value and the standard deviation of objective function by the proposed method are reliable as shown in examples compared with results by FOSM method.