This study assesses the capability of ChatGPT to generate finite element code for geotechnical engineering applications from a set of prompts. We tested three different initial boundary value problems using a hydro-mechanically coupled formulation for unsaturated soils, including the dissipation of excess pore water pressure through fluid mass diffusion in one-dimensional space, time-dependent differential settlement of a strip footing, and gravity-driven seepage. For each case, initial prompting involved providing ChatGPT with necessary information for finite element implementation, such as balance and constitutive equations, problem geometry, initial and boundary conditions, material properties, and spatiotemporal discretization and solution strategies. Any errors and unexpected results were further addressed through prompt augmentation processes until the ChatGPT-generated finite element code passed the verification/validation test. Our results demonstrate that ChatGPT required minimal code revisions when using the FEniCS finite element library, owing to its high-level interfaces that enable efficient programming. In contrast, the MATLAB code generated by ChatGPT necessitated extensive prompt augmentations and/or direct human intervention, as it involves a significant amount of low-level programming required for finite element analysis, such as constructing shape functions or assembling global matrices. Given that prompt engineering for this task requires an understanding of the mathematical formulation and numerical techniques, this study suggests that while a large language model may not yet replace human programmers, it can greatly assist in the implementation of numerical models.
장대레일이 부설된 철도 교량은 궤도-교량 상호작용으로 인하여 경간장 연장에 제약이 있다. 이러한 한계를 극복하기 위하여 궤도와 교량 사이에 저마찰 슬라이드층을 두어 교량과 궤도의 종방향 거동을 분리시켜 상호작용을 원천적으로 저감시키는 슬라이딩 궤도가 개발되고 있다. 본 연구에서는 슬라이드층을 포함하는 궤도 시스템을 실규모로 제작하여 종방향으로 반복하중을 재하하는 시험을 통하여 슬라이딩 궤도의 저마찰 거동을 종합적으로 평가하고자 하였다. 하중 재하 속도를 0.2, 1.0, 5.0, 10mm/min.으로 변화를 주었으며, 5,000, 10,000kg의 부가질량이 재하된 경우에 대한 마찰거동를 비교 검토하였다. 실험 결과 제안된 슬라이드층의 마찰계수는 0.22~0.33인 것으로 확인되었다. 더불어, 30년에 해당하는 10,000회의 반복하중을 재하하여 마찰계수 변화를 관찰한 결과, 마찰계수 증가는 7%에 머물러 반복하중에 대한 장기적인 내구성을 확보한 것으로 확인되었다. 슬라이드층의 마찰계수의 변화에 따른 영향을 상호작용 해석을 통하여 추가로 검토하였다. Railway bridges with continuously welded rail have a limitation of span length due to track-bridge interaction. In order to overcome this, a sliding slab track system has been developed that comprises with a low-frictional sliding layer between the bridge deck and the track slab to isolate the longitudinal behavior between the bridge and the track. In this study, a real scale track system is prepared to experimentally evaluate the longitudinal frictional behavior. Applied loading rates were 0.2, 1.0, 5.0 and 10mm/min; vertical mass on the track are track slab only, 5,000 and 10,000kg added mass, respectively. Test results showed that the resulting frictional coefficients varied from 0.22 to 0.33. In addition, 10,000 cycle loadings were applied to simulate repetitive sliding to represent 30 years of service life. The frictional coefficient increase was measured and found to be 7% of that of the initial loading stage, which means that the sliding layer is adequate to provide low-frictional behavior for the sliding slab track system. Effects of changes of the frictional coefficient of the sliding layer were analyzed by rail-structure interaction analysis.
In this research, we consider a smart grid network of electricity with multiple consumers connected to a monopolistic provider. Each consumer can be informed the real time price changes through the smart meter and updates his consumption schedule to minimize the energy consumption expenditures by which the required power demand should be satisfied under the given real time pricing scheme. This real-time decision making problem has been recently studied through game-theoretic approach. The present paper contributes to the existing literature by incorporating storage appliance into the set of available household appliances which has somewhat distinctive functions compared to other types of appliances and would be regarded to play a significant role in energy consumption scheduling for the future smart grid. We propose a game-theoretic algorithm which could draw the optimal energy consumption scheduling for each household appliances including storage. Results on simulation data showed that the storage contributed to increase the efficiency of energy consumption pattern in the viewpoint of not only individual consumer but also whole system.
An algorithm for measurement of the cutting blade of the ultrasonic vibration cutting machine used in an automation machine is proposed in this paper. The proposed algorithm, which is based upon a multi-step detection method, is developed for the accurate measurement of the cutting blade by exactly determining its rotation angle, length, and thickness. Instead of the commonly used Otsu method, we propose a new curvature-based adaptive binarization method, which provides more accurate details about the dimensions of the cutting blade. A region of interest containing the cutting blade from the acquired image is first extracted in the multi-step detection method, which is further processed to remove the noise, which increases the measurement reliability. An important feature of the proposed process is the restoration of the cutting blade’s tip data, which used to be lost during the fine noise-filtering process. The rotation angle and length are measured using the minimum rotated rectangle while the line fitting based upon the least square method is applied to increase the reliability of the thickness measurement. Experimental results validate the superiority of the proposed method over the conventional Otsu method.
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