• Smart Structures and Systems
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• 제24권1호
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• pp.111-125
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• 2019

Metallic shape memory alloys present fascinating physical properties such as their super-elastic behavior in austenite phase, which can be exploited for providing a structure with both a self-centering capability and an increased ductility. More or less accurate numerical models have been introduced to model their behavior along the last 25 years. This is the reason for which the literature is rich of suggestions/proposals on how to implement this material in devices for passive and semi-active control. Nevertheless, the thermo-mechanical coupling characterizing the first-order martensite phase transformation process results in several macroscopic features affecting the alloy performance. In particular, the effects of day-night and winter-summer temperature excursions require special attention. This aspect might imply that the deployment of some devices should be restricted to indoor solutions. A further aspect is the dependence of the behavior from the geometry one adopts. Two fundamental lacks of symmetry should also be carefully considered when implementing a SMA-based application: the behavior in tension is different from that in compression, and the heating is easy and fast whereas the cooling is not. This manuscript focuses on the passive devices recently proposed in the literature for civil engineering applications. Based on the challenges above identified, their actual feasibility is investigated in detail and their long term performance is discussed with reference to their fatigue life. A few available semi-active solutions are also considered.

• Nuclear Engineering and Technology
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• 제51권5호
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• pp.1218-1230
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• 2019

A sub-channel solver, named ${\underline{S}}teady$ and ${\underline{T}}ransient$ ${\underline{A}}nalyzer$ for ${\underline{R}}eactor$ ${\underline{T}}hermal$ hydraulics (START), has been developed using the homogenous model for two-phase conditions of light water reactors. The code is developed as a fast and accurate TH-solver for coupled and multi-physics calculations. START has been validated against the NUPEC PWR Sub-channel and Bundle Test (PSBT) database. Tests like single-channel quality and void-fraction for steady state, outlet fluid temperature for steady state, rod-bundle quality and void-fraction for both steady state and transient conditions have been analyzed and compared with experimental values. Results reveal a good accuracy of solution for both steady state and transient scenarios. Axially different values for turbulent mixing coefficient are used based on different grid-spacer types. This provides better results as compared to using a single value of turbulent mixing coefficient. Code-to-code evaluation of PSBT results by the START code compares well with other industrial codes. The START code has been parallelized with the OpenMP algorithm and its numerical performance is evaluated with a large whole PWR core. Scaling study of START shows a good parallel performance.

• 대한금속재료학회지
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• 제49권7호
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• pp.515-521
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• 2011

Small punch creep testing has received attention due to the convenience of using smaller specimens than those of conventional uniaxial creep tests, which enables creep testing on developing or currently operational components. However, precedent studies have shown that it is necessary to consider friction between the punch and specimen when computing uniaxial equivalent stress from a finite element model. In this study, small punch creep behaviors of AISI 316L stainless steel, which is widely used in high temperature-high pressure machineries, have been compared for the two different ceramic balls such as $Si_3N_4$ and $Al_2O_3$. The optimal range of the friction coefficient is 0.4~0.5 at $650^{\circ}C$ for the best fit between experimental and simulation data of AISI 316 L stainless steel. The higher the friction coefficient, the longer the creep rupture time is. Therefore, the type of ceramic ball used must be specified for standardization of small punch creep testing.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제25권2호
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• pp.54-65
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• 2021

In this study, a two-dimensional thermoelastic problem under hyperbolic heat conduction theory with an internal heat source is considered. The general solution for the temperature field, stress components and displacement field are obtained using the reduced differential transform method. The stress and displacement components are obtained using the thermal stress function in the reduced differential transform domain. All the solutions are obtained in the form of power series. The special case with a time-dependent laser heat source has been considered. The problem is considered for homogeneous material with finite rectangular cross-section heated with a non-Gaussian temporal profile. The effect of the heat source on all the characteristics of a material is discussed numerically and graphically for magnesium material taking a pulse duration of 0.2 ps. This study provides a powerful tool for finding the solution to the thermoelastic problem with less computational work as compared to other methods. The result obtained in the study may be useful for the investigation of thermal characteristics in engineering and industrial applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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• pp.1193-1215
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• 2021

The measurement of the key product quality index plays an important role in improving the production efficiency and ensuring the safety of the enterprise. Since the actual working conditions and parameters will inevitably change to some extent with time, such as drift of working point, wear of equipment and temperature change, etc., these will lead to the degradation of the quality variable prediction model. To deal with this problem, the selective integrated moving windows based principal component regression (SIMV-PCR) is proposed in this study. In the algorithm of traditional moving window, only the latest local process information is used, and the global process information will not be enough. In order to make full use of the process information contained in the past windows, a set of local models with differences are selected through hypothesis testing theory. The significance levels of both T - test and χ² - test are used to judge whether there is identity between two local models. Then the models are integrated by Bayesian quality estimation to improve the accuracy of quality variable prediction. The effectiveness of the proposed adaptive soft measurement method is verified by a numerical example and a practical industrial process.

• Advances in aircraft and spacecraft science
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• 제8권4호
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• pp.289-302
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• 2021

Ensuring flight safety for passengers as well as crew is the most important aspect of modern aviation, and in order to achieve this, it is necessary to be able to forecast the durability of individual components. The present contribution illustrates the results of a computational analysis to determine the possibility of analysing the prediction of bearing durability in on-board rotating equipment from the point of view of thermal fatigue.In this study, a method developed at the Air Force Institute of Technology was used for analysis, which allowed to determine the bearing durability from the flight altitude profile. Two aircraft have been chosen for analysis - a military M-28 and a civilian Embraer. As a result of the analysis were obtained: the bearing durability in on-board rotating devices, average operation time between failures, as well as failure rate. In conclusion, the practical applicability of this approach is demonstrated by the fact that even with a limited number of flight parameters, it is possible to estimate bearing durability and increase flight safety by regular inspections.

• Advances in nano research
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• 제12권4호
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• pp.375-386
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• 2022

Synthesis of acrylate-based dispersion resins involves many parameters including temperature, ingredients concentrations, and rate of adding ingredients. Proper controlling of these parameters results in a uniform nano-size chain of polymer on one side and elimination of hazardous residual monomer on the other side. In this study, we aim to screen the process parameters via Internet of Things (IoT) to ensure that, first, the nano-size polymeric chains are in an acceptable range to acquire high adhesion property and second, the remaining hazardous substance concentration is under the minimum value for safety of public and personnel health. In this regard, a set of experiments is conducted to observe the influences of the process parameters on the size and dispersity of polymer chain and residual monomer concentration. The obtained dataset is further used to train an Adaptive Neural network Fuzzy Inference System (ANFIS) to achieve a model that predicts these two output parameters based on the input parameters. Finally, the ANFIS will return values to the automation system for further decisions on parameter adjustment or halting the process to preserve the health of the personnel and final product consumers as well.

• 한국공간구조학회논문집
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• 제23권4호
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• pp.81-88
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• 2023

Numerous factors contribute to the deterioration of reinforced concrete structures. Elevated temperatures significantly alter the composition of the concrete ingredients, consequently diminishing the concrete's strength properties. With the escalation of global CO2 levels, the carbonation of concrete structures has emerged as a critical challenge, substantially affecting concrete durability research. Assessing and predicting concrete degradation due to thermal effects and carbonation are crucial yet intricate tasks. To address this, multiple prediction models for concrete carbonation and compressive strength under thermal impact have been developed. This study employs seven machine learning algorithms-specifically, multiple linear regression, decision trees, random forest, support vector machines, k-nearest neighbors, artificial neural networks, and extreme gradient boosting algorithms-to formulate predictive models for concrete carbonation and thermal impact. Two distinct datasets, derived from reported experimental studies, were utilized for training these predictive models. Performance evaluation relied on metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analytical outcomes demonstrate that neural networks and extreme gradient boosting algorithms outshine the remaining five machine learning approaches, showcasing outstanding predictive performance for concrete carbonation and thermal effect modeling.

• Journal of Plant Biotechnology
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• 제50권
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• pp.225-231
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• 2023

Cold stress is one of the most vulnerable environmental stresses that affect plant growth and crop yields. With the recent advancements in genetic approaches using Arabidopsis and other model systems, genes involved in cold-stress response have been identified and the key cold signaling factors have been characterized. Exposure to low-temperature stress triggers the activation of a set of genes known as cold regulatory (COR) genes. This activation process plays a crucial role in enhancing the resistance of plants to cold and freezing stress. The inducer of the C-repeatbinding factor (CBF) expression 1-CBF module (ICE1-CBF module) is a key cold signaling pathway regulator that enhances the expression of downstream COR genes; however, this signaling module in Panax ginseng remains elusive. Here, we identified cold-signaling-related genes, PgCBF1, PgCBF3, and PgICE1 and conducted functional genomic analysis with a heterologous system. We confirmed that the overexpression of cold- PgCBF3 in the cbf1/2/3 triple Arabidopsis mutant compensated for the cold stress-induced deficiency of COR15A and salt-stress tolerance. In addition, nuclearlocalized PgICE1 has evolutionarily conserved phosphorylation sites that are modulated by brassinsteroid insensitive 2 (PgBIN2) and sucrose non-fermenting 1 (SNF1)-related protein kinase 3 (PgSnRK3), with which it physically interacted in a yeast two-hybrid assay. Overall, our data reveal that the regulators identified in our study, PgICE1 and PgCBFs, are evolutionarily conserved in the P. ginseng genome and are functionally involved in cold and abiotic stress responses.

• 한국농림기상학회지
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• 제17권4호
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• pp.384-398
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• 2015

본 연구에서는 청미천 농경지를 중심으로 고해상도 지형 및 토지피복 자료 기반의 WRF/Noah-MP 결합시스템을 구축하고 수치모의 한 결과를 2014년 8월 21일부터 9월 10일까지의 청미천 하계 특별관측 자료와 비교하여, 농경지에서의 지면 및 대기모의 성능을 평가하였다. 지면 및 대기 변수의 단기 및 중기모의에 있어서 Noah-MP의 동적 식생 가동이 얼마나 유용한지를 살펴보기 위하여, 동적 식생을 포함하지 않은 실험(CTL)과 포함한 실험(DVG)을 관측기간에 대해 양방향 6중 둥지격자 시스템으로 수행하였다. 본 연구의 결과는 크게 세 가지로서 다음과 같다. 1) CTL 실험은 낮 동안의 순단파 복사 에너지를 과대 모의 함에 따라 현열 및 잠열 플럭스와 보웬비도 관측에 비해 과대 모의하는 경향을 보였다. CTL 실험의 기온은 관측을 대체로 잘 따라갔으나 일출 후 기온의 상승 속도가 관측에 비해 빠른 모습을 보였다. 최저 기온 및 최고 기온의 시점은 잘 모의하였는데, 특히 일 최저기온의 모의는 관측과 $0.3^{\circ}C$ 오차 이내의 성능을 보여, 동해 및 병해충과 연관된 엽면수분 지속시간 예측에 고무적인 결과로 평가되었다. CTL 실험의 10m 바람은 동서 및 남북 풍속 모두 대체로 과대 모의하는 경향을 보였고, 강수 또한 과대 모의하는 경향을 보였으나 강수의 시작 종료시점은 대체로 잘 포착하였다. 2) Noah-MP의 동적 식생을 구동시킨 DVG 실험은 CTL 실험에 비해 엽면적지수, 단파 복사, 지표면 플럭스, 보웬비, 기온, 바람, 강수의 모의를 전반적으로 관측에 더 가깝게 생산하는 것으로 나타났다. 강수, 온도, 복사, 가용 영양소 등의 변동에 대응하여 엽면적지수를 예단하는 DVG 실험은 CTL 실험보다 더 큰 엽면적지수를 생산했으며, 이는 실측에 더 가까운 결과였다. DVG 실험에서도 일출 후 기온 상승률은 관측에 비해 높았는데, 이는 CTL와 DVG 실험 모두에서 공통으로 사용한 YSU 경계층 방안이 갖는 혼합층의 조기 성장 특성과 관련이 있는 것으로 분석되었다. CTL 실험이 보인 바람과 강수의 과대모의 경향도 DVG 실험에서는 어느 정도 완화되는 개선점을 보였다. 3) 수평 해상도의 증가에 따른 청미천 농경지의 수치모의 성능 향상은 지표면 플럭스, 기온, 바람 강수 모두에서 미비하거나 거의 없는 것으로 나타났으며, 보다 정확한 평가를 위해서는 농경지 상의 여러 지점에서 입체적인 관측이 이뤄져야 하고, 모형에 사용되는 지형 및 토지피복 자료의 도메인 간 일관성이 확보되어야 할 것이다.