• Journal of the Korean Society for Railway
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• v.13 no.3
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• pp.290-297
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• 2010

At present, the design live load of railway is divided into common railway and high speed railway separately in Korea. L22 which is based on American railway standards is used for common railway and HL25 which is based on Eurocode is used for high speed railway. Although, the design load is the starting point for design of railway, any research for developing design load does not exist at all. However, Europe and Japan develops the design load model consistently for advanced design. Recently, deterministic, probabilistic and cost performance approaches are investigated for developing new design load in Europe which is called LM2000. In the present paper, as a step for developing new design live load model for Korean railway, deterministic processes will be introduced. The safety margins are analyzed based on serviced real trains versus proposed new design load model and a necessity for new design live load will be presented quantitatively.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.511-525
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• 2021

Aluminium outfitting is widely used in offshore platforms owing to its anti-corrosion ability and its light weight. However, various standards exist (ISO, NORSOK and EN) for the design of handrails used in offshore platforms, and different suppliers have different criteria. This causes great confusion for designers. Moreover, the design load required by the standards is not clearly defined or is uncertain. Thus, many offshore projects reference previous project details or are conservatively designed without additional clarification. In this study, all of the codes and standards were reviewed and analysed through prior studies, and data on variable factors that directly and indirectly affect the handrails applied to offshore platforms were analysed. A total of 50 handrail design load scenarios were proposed through deterministic and probabilistic approaches. To verify the proposed new handrail design load selection scenario, structural analysis was performed using SACS (offshore structural analysis software). This new proposal through deterministic and probabilistic approaches is expected to improve safety by clarifying the purpose of the handrails. Furthermore, the acceptance criteria for probabilistic scenarios for handrails suggest considering the frequency of handrail use and the design life of offshore platforms to prevent excessive design. This study is expected to prevent trial and error in handrail design while maintaining overall worker safety by applying a loading scenario suitable for the project environment to enable optimal handrail design.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.7
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• pp.1234-1242
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• 2003

In this paper we present a simple and efficient robust optimal design formulation for MEMS structures and its application to a resonant-type micro probe. The basic idea is to use the gradient index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-effective and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation. This method, although shown for MEMS structures, may as well be easily applied to conventional mechanical structures where information on uncertainties is lacking but robustness is highly important.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1254-1261
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• 2003

In this paper we present a simple and efficient robust optimal design formulation and its application to a resonant-type micro probe. The basic idea is to use the Gradient Index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-efficient and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation.

• International Journal of Automotive Technology
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• v.6 no.3
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• pp.235-242
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• 2005

This study introduces the Reliability-Based Design Optimization (RBDO) to enhance the kinematic and compliance (K & C) characteristics of automotive suspension system. In previous studies, the deterministic optimization has been performed to enhance the K & C characteristics. Unfortunately, uncertainties in the real world have not been considered in the deterministic optimization. In the design of suspension system, design variables with the uncertainties, such as the bushing stiffness, have a great influence on the variation of the suspension performances. There is a need to quantify these uncertainties and to apply the RBDO to obtain the design, satisfying the target reliability level. In this research, design variables including uncertainties are dealt as random variables and reliability of the suspension performances, which are related the K & C characteristics, are quantified and the RBDO is performed. The RBD-optimum is compared with the deterministic optimum to verify the enhancement in reliability. Thus, the reliability of the suspension performances is estimated and the RBD-optimum, satisfying the target reliability level, is determined.

• Advances in aircraft and spacecraft science
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• v.4 no.3
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• pp.297-316
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

• Advances in aircraft and spacecraft science
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• v.4 no.3
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• pp.317-334
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

• Journal of Mechanical Science and Technology
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• v.18 no.10
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• pp.1722-1729
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• 2004

This paper presents a design methodology for determining configurations of slider air bearings considering the randomness of the air-bearing surface (ABS) geometry by using the iSIGHT. A reliability-based design optimization (RBDO) problem is formulated to minimize the variations in the mean values of the flying heights from a target value while satisfying the desired probabilistic constraints keeping the pitch and roll angles within a suitable range. The reliability analysis is employed to estimate how the fabrication tolerances of individual slider parameters affect the final flying attitude tolerances. The proposed approach first solves the deterministic optimization problem. Then, beginning with this solution, the RBDO is continued with the reliability constraints affected by the random variables. Reliability constraints overriding the constraints of the deterministic optimization attempt to drive the design to a reliability solution with minimum increase in the objective. The simulation results of the RBDO are listed in comparison with the values of the initial design and the results of the deterministic optimization, respectively. To show the effectiveness of the proposed approach, the reliability analyses are simply carried out by using the mean value first-order second-moment (MVFO) method. The Monte Carlo simulation of the RBDO's results is also performed to estimate the efficiency of the proposed approach. Those results are demonstrated to satisfy all the desired probabilistic constraints, where the target reliability level for constraints is defined as 0.8.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.129-136
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• 2005

The deterministic analysis method has generally used to evaluate the slope stability and it evaluates the slope stability with decision value that is a representative value of design variables. However, one of disadvantages in the deterministic approach is there is not able to consider the uncertainty of soil strength properties, even though it is the biggest influential parameter of the slope stability. On the other hand, the limit state design(LSD) can take a consideration of uncertainties and computes both the reliability index and the probability of failure. LSD method is capable of overcoming the disadvantages of deterministic method and evaluating the slope stability more reliably. In this study, both the mean value and standard deviation of the internal land's representative soil strength properties applied to process the LSD method. The major purpose of this study is to gauge the general applicability of the limit state design in soil slope and to weigh the comparative validity of the proposed partial safety factor. In order to reach the aim of this study, the partial safety factor and resistance factor which totally satisfied the slope's overall safety factor were calculated by the load and resistance safety factor design (LRFD).

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.13-28
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• 2002

Higher efficiency and effectiveness of Research & Development phases can be attained using advanced statistical methodologies. In this work statistical methodologies are combined with a deterministic approach to engineering design. In order to show the potentiality of such integration, a simple but effective example is presented. It concerns the problem of optimising the performances of a paper helicopter. The design of this simple device is not new in quality engineering literature and has been mainly used for educational purposes. Taking full advantage of fundamental engineering knowledge, an aerodynamic model is originally formulated in order to describe the flight of the helicopter. Screening experiments were necessary to get first estimates of model parameters. Subsequently, deterministic evaluations based on this model were necessary to set up further experimental phases needed to search (or a better design. Thanks to this integration of statistical and deterministic phases, a significant performance improvement is obtained. Moreover, the engineering knowledge かms out to be developed since an explanation of the “why” of better performances, although approximate, is achieved. The final design solution is robust in a broader sense, being both validated by experimental evidence and closely examined by engineering knowledge.