• Journal of the Korean Society for Precision Engineering
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• v.25 no.5
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• pp.52-59
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• 2008

The accuracy of the machine tools is degraded because of thermal error of structure due to thermal variation. To improve the accuracy of a machine tools, measurement and prediction of thermal error is very important. The main part of thermal source is spindle due to high speed with friction. The thermal error of spindle is very important because it is over 10% in total thermals errors. In this paper, the suitable thermal error prediction technology for machine tools with open architecture controller is developed and implemented to machine tools. Two thermal error prediction technologies, neural network and multi-linear regression, are investigated in several methods. The multi-linear regression method is more effective for implementation to CNC. The developed thermal error prediction technology is implemented on the internal function of CNC.

• Computers and Concrete
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• v.17 no.2
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• pp.173-188
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• 2016

Generally, thermal stress induced by hydration heat causes cracking in mass concrete structures, requiring a thorough control during the construction. The prediction of the thermal stress is currently undertaken by means of numerical analysis despite its lack of reliability due to the properties of concrete varying over time. In this paper, a method for the prediction of thermal stress in concrete structures by adjusting thermal stress measured by a thermal stress device according to the degree of restraint is proposed to improve the prediction accuracy. The ratio of stress in concrete structures to stress under complete restraint is used as the degree of restraint. To consider the history of the degree of restraint, incremental stress is predicted by comparing the degree of restraint and the incremental stress obtained by the thermal stress device. Furthermore, the thermal stresses of wall and foundation predicted by the proposed method are compared to those obtained by numerical analysis. The thermal stresses obtained by the proposed method are similar to those obtained by the analysis for structures with internally as well as externally strong restraint. It is therefore concluded that the prediction of thermal stress for concrete structures with various boundary conditions using the proposed method is suggested to be accurate.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.47-52
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• 2002

There are many factors in machine tool error. These are thermal deformation, geometric error, machine's part assembly error, error caused by tool bending. Among them thermal error is 70% of total error of machine tool . Prediction of thermal error is very difficult. because of nonlinear tendency of machine tool deformation. In this study, we tried thermal error prediction by using multi regression analysis.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.119-127
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• 2022

Most of the construction works are conducted outdoors, so the construction workers are affected by weather conditions such as temperature, humidity, and wind velocity which can be evaluated the thermal comfort as environmental factors. In our previous researches, it was found that construction accidents are usually occurred in the discomfort ranges. The safety management, therefore, should be planned in consideration of the thermal comfort and measured by a specialized simulation tool. However, it is very complex, time-consuming, and difficult to model. To address this issue, this study is aimed to develop a framework of a prediction model for improving the prediction accuracy about outdoor thermal comfort considering environmental factors using machine learning algorithms with hyperparameter tuning. This study is done in four steps: i) Establishment of database, ii) Selection of variables to develop prediction model, iii) Development of prediction model; iv) Conducting of hyperparameter tuning. The tree type algorithm is used to develop the prediction model. The results of this study are as follows. First, considering three variables related to environmental factor, the prediction accuracy was 85.74%. Second, the prediction accuracy was 86.55% when considering four environmental factors. Third, after conducting hyperparameter tuning, the prediction accuracy was increased up to 87.28%. This study has several contributions. First, using this prediction model, the thermal comfort can be calculated easily and quickly. Second, using this prediction model, the safety management can be utilized to manage the construction accident considering weather conditions.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.5 s.311
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• pp.60-67
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• 2006

Thermal analysis and prediction of electronic components is required to predict and optimize the reliability of onboard electronic unit employed in space vehicles. This paper introduces a methodology on thermal prediction that uses isothermal PCB model, thermal force model, thermal resistance matrix and superposition principle to calculate electronic devices temperatures undergoing thermal conduction environment. An example is Presented including a prediction result by this method and simulation results performed by commercial program.

• Journal of Aerospace System Engineering
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• v.10 no.4
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• pp.26-34
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• 2016

In a number of industries, porous insulations have been frequently used, reducing thermal insulation space through excellent performance of the thermal insulation's characteristics. This paper suggests an effective thermal conductivity prediction model. Firstly, we perform a literature review of traditional effective thermal conductivity prediction models and compare each model with experimental heat transfer results. Furthermore, this research defines the effectiveness of thermal conductivity prediction models using experimental heat transfer results and the Zehner-Schlunder model. The newly defined effective thermal conductivity prediction model has been verified to better predict performance than other models. Finally, this research performs a transient heat transfer analysis of a thermal protection system with a porous insulation in a high speed vehicle using the finite element method and confirms the validity of the effective thermal conductivity prediction model.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.48-51
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• 2002

This paper predicted the thermal conductivity of spun carbon/phenolic composites by the thermal resistance method. This method uses the analogy between the diffusion of heat and electrical charge. To verify the theoretical predictions, the thermal conductivity of spun carbon/phenolic composites was examined experimentally. The reported thermal conductivities of graphite/epoxy composite of a eight harness satin laminate was used of the comparison with the prediction values of the model and it was noticed that a good agreement has been found.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.5
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• pp.1192-1202
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• 1994

Fatigue behavior and life prediction were presented for thermal-mechanical and isothermal low cycle fatigue of 12Cr forged steel used for high temperature applications. In-phase and out-of-phase thermal-mechanical fatigue test at 350 to 600.deg. C and isothermal low cycle fatigue test at 600.deg. C were conducted using smooth cylindrical hollow specimen under strain-control with total strain ranges from 0.006 to 0.015. Cyclic softening behavior was observed regardless of thermal-mechanical and isothermal fatigue tests. The phase difference between temperature and strain in thermal-mechanical fatigue resulted in significantly shorter fatigue life for out-of-phase than for in-phase. The difference in fatigue lives was dependent upon the magnitudes of inelastic strain ranges and mean stresses. Increase in inelastic strain range showed a tendency of intergranular cracking and decrease in fatigue life, especially for out-of-phase thermal-mechanical fatigue. Thermal-mechanical fatigue life prediction was made by partitioning the strain ranges of the hysteresis loops and the results of isothermal low cycle fatigue tests which were performed under the combination of slow and fast strain rates. Predicted fatigue lives for out-of-phase using the strain range partitioning method showed an excellent agreement with the actual out-of-phase thermal-mechanical fatigue lives within a factor of 1.5. Conventional strain range partitioning method exhibited a poor accuracy in the prediction of in-phase thermal-mechanical fatigue lives, which was quite improved conservatively by a proposed strain range partitioning method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.5
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• pp.108-114
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• 1999

The thermal environmental chamber has been using in maintaining weather condition keeping thermal capacity under heating and cooling load fluctuation and for the performance testing of cooling system or air-conditioner on artificial envi-ronment. In ordder to make the various environmental conditions in the thermal environmental chamber the proper cooling system is necessary to eliminate the heating load produced inside the chamber and to maintain the designed environmental condition. For this reason the optimal design of cooling system and the prediction of performance is also required. This paper describes the prediction of performance of cooling system in the thermal environmental chamber with the capacity of 37,000kcal/hr which is developed for the test of performance in heating mode of heat pump system, In the results this paper is trying to develop simulation program on the base of mathematical models and which can be applied effectively to the optimal design of cooling system and prediction of performance to the inside and outside change of envi-ronmetal load.

• Journal of Welding and Joining
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• v.21 no.3
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• pp.92-98
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• 2003

This paper describes the numerical prediction of the thermal fatigue life of a $\mu$BGA(Micro Ball Grid Array) solder joint. Finite element analysis(FEA) was employed to simulate thermal cycling loading for solder joint reliability. Strain values, along with the result of mechanical fatigue tests for solder alloys were then used to predict the solder joint fatigue life using the Coffin-Manson equation. The results show that Sn-3.5mass%Ag solder had the longest thermal fatigue life in low cycle fatigue. Also a practical correlation for the prediction of the thermal fatigue life was suggested by using the dimensionless variable ${\gamma}$, which was possible to use several lead free solder alloys for prediction of thermal fatigue life. Furthermore, when the contact angle of the ball and chip has 50 degrees, solder joint has longest fatigue life.