• Nuclear Engineering and Technology
• /
• 제53권10호
• /
• pp.3275-3285
• /
• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

• Membrane and Water Treatment
• /
• 제9권5호
• /
• pp.363-371
• /
• 2018

In this work, it was investigated the usability of artificial bee colony (ABC) and genetic algorithm (GA) in modeling adsorption of Co(II) onto drinking water treatment sludge (DWTS). DWTS, obtained as inevitable byproduct at the end of drinking water treatment stages, was used as an adsorbent without any physical or chemical pre-treatment in the adsorption experiments. Firstly, DWTS was characterized employing various analytical procedures such as elemental, FT-IR, SEM-EDS, XRD, XRF and TGA/DTA analysis. Then, adsorption experiments were carried out in a batch system and DWTS's Co(II) removal potential was modelled via ABC and GA methods considering the effects of certain experimental parameters (initial pH, contact time, initial Co(II) concentration, DWTS dosage) called as the input parameters. The accuracy of ABC and GA method was determined and these methods were applied to four different functions: quadratic, exponential, linear and power. Some statistical indices (sum square error, root mean square error, mean absolute error, average relative error, and determination coefficient) were used to evaluate the performance of these models. The ABC and GA method with quadratic forms obtained better prediction. As a result, it was shown ABC and GA can be used optimization of the regression function coefficients in modeling adsorption experiments.

• 한국정보전자통신기술학회논문지
• /
• 제16권6호
• /
• pp.378-384
• /
• 2023

본 연구에서는 신경망포텐셜(Neural Network Potential)의 효율성과 정확도를 동시에 달성할 수 있는 기술자 벡터 조건을 도출하고자 한다. 소재 시스템은 단원소 소재인 실리콘으로 선정하였으며, 인공신경망 학습을 위한 원자 구조별 에너지 데이터는 밀도범함수이론 계산을 통하여 생성하였다. Behler-Parrinello 타입의 원자중심대칭함수를 기술자 벡터로 사용하였고, 다양한 벡터 길이에 대한 신경망포텐셜 생성 후 분자동역학 시뮬레이션에 적용하여 실리콘 소재의 구조 및 기계적 물성 재현성을 평가하였다. 실험 결과, 물성 재현 정확도를 유지하면서 학습 및 계산 효율성을 동시에 달성할 수 있는 기술자벡터의 최소 길이는 약 50이고, 소재의 기계적 물성이 이 길이에 더 큰 영향을 받으며, 같은 길이의 조건에서는 방사 대비 각도 방향 대칭함수를 더 반영하면 신경망포텐셜의 정확도가 올라감을 발견하였다. 이를 토대로 신경망포텐셜의 효율성과 정확도 동시 달성을 위한 최적의 기술자벡터 설정 가이드라인 제공이 가능할 것으로 기대된다.

• 한국항공우주학회지
• /
• 제32권7호
• /
• pp.69-75
• /
• 2004

비행중인 다른 항공기를 회피하며 항공기를 목표점까지 유도하는 문제를 2차원 평면에서 고려하였다. 항공기는 속도의 크기가 일정한 질점이며, 제어입력으로 측가속도를 사용하는 것으로 가정하였다. 이동장애물에는 척력 포텐셜함수를 목적점에는 인력 포텐셜함수를 인공적으로 부여하여 항공기에 척력과 인력이 작용하도록 하였다. 유도/회피명령은 이들 포텐셜력과 상대속도를 사용하여 실시간으로 구현 가능한 유도/회피법칙을 구현하였다. Log 형태의 포텐셜함수를 사용하면 구현된 유도법칙은 잘 알려진 비례항법유도법칙이 되며, 회피법칙은 장애물까지 도달시간에 반비례하고 시선각 변화의 반대 방향으로 항공기를 회전시킨다. 제안된 유도/회피법칙은 시뮬레이션을 통하여 타당성을 검증하였다.

• Smart Structures and Systems
• /
• 제4권5호
• /
• pp.583-603
• /
• 2008

In this study, a real-time damage detection method using output-only acceleration signals and artificial neural networks (ANN) is developed to monitor the occurrence of damage and the location of damage in structures. A theoretical approach of an ANN algorithm that uses acceleration signals to detect changes in structural parameters in real-time is newly designed. Cross-covariance functions of two acceleration responses measured before and after damage at two different sensor locations are selected as the features representing the structural conditions. By means of the acceleration features, multiple neural networks are trained for a series of potential loading patterns and damage scenarios of the target structure for which its actual loading history and structural conditions are unknown. The feasibility of the proposed method is evaluated using a numerical beam model under the effect of model uncertainty due to the variability of impulse excitation patterns used for training neural networks. The practicality of the method is also evaluated from laboratory-model tests on free-free beams for which acceleration responses were measured for several damage cases.

• 대한의용생체공학회:의공학회지
• /
• 제26권4호
• /
• pp.243-249
• /
• 2005

The number of people who have lost limbs due to amputation has increased due to various accidents and diseases. Numerous attempts have been made to provide these people with prosthetic devices. These devices are often controlled using myoelectric signals. Although the success of fitting myoelectric signals (EMG) for single device control is apparent, extension of this control to more than one device has been difficult. The lack of success can be attributed to inadequate multifunctional control strategies. Therefore, the objective of this study was to develop multifunctional myoelectric control strategies that can generate a number of output control signals. We demonstrated the feasibility of a neural network classification control method that could generate 12 functions using three EMG channels. The results of evaluating this control strategy suggested that the neural network pattern classification method could be a potential control method to support reliability and convenience in operation. In order to make this artificial neural network control technique a successful control scheme for each amputee who may have different conditions, more investigation of a careful selection of the number of EMG channels, pre-determined contractile motions, and feature values that are estimated from the EMG signals is needed.

• 수산경영론집
• /
• 제38권3호
• /
• pp.25-51
• /
• 2007

Recently those who visit a fishing village is increasing. So the government's policymaker is interested in a tourism of fishing village. There are a lot of local governments that they turn it to good account to activate the fishing community. So they plan for the tourism facility in the fishing village and invest in it. The fishery facility can playa role in it. Nonetheless it is not playing a role in tourism facility. Though the breakwaters projecting far into the sea are good waterfront, most of them are not reflecting the function of it. And fishery facility producing seed is a good resource of eco-tourism, but it is yet a tourist potential. Although the artificial reef is going far toward promoting a fishery resource, it is seldom used as a tourism resource. The multiple functions of fishery facilities have to be improved to raise the investment effect of them. Especially the tourism function has to be added on their basic function. The multiple functions of fishery facilities is necessary to satisfy tourist's needs. In results, not only their value but also value of fishing village will be raised.

• Asian Pacific Journal of Cancer Prevention
• /
• 제13권6호
• /
• pp.2813-2818
• /
• 2012

Background: Considerable evidence suggests that metadherin (MTDH) is a potentially crucial mediator of tumor malignancy and an important therapeutic target for simultaneously enhancing chemotherapy efficacy and reducing metastasis risk. Inhibition of MTDH expression by RNA interference has been shown in several previous research, but silencing MTDH expression by microRNA (miRNA) interference in breast cancer has not been established. In the present study, we investigated the role of MTDH-miRNA in down-regulation of proliferation, motility and migration of breast carcinoma cells. Methods: Expression vectors of recombinant plasmids expressing artificial MTDH miRNA were constructed and transfected to knockdown MTDH expression in MDA-MB-231 breast cancer cells. Expression of MTDH mRNA and protein was detected by RT-PCR and Western blot, respectively. MTT assays were conducted to determine proliferation, and wound healing assays and transwell migration experiments for cell motility and migration. Results: Transfection of recombinant a plasmid of pcDNA-MTDH-miR-4 significantly suppressed the MTDH mRNA and protein levels more than 69% in MDA-MB-231 breast cancer cells. This knockdown significantly inhibited proliferation, motility and migration as compared with controls. Conclusions: MTDH-miRNA may play an important role in down-regulating proliferation, motility and migration in breast cancer cells, and should be considered as a potential small molecule inhibitor therapeutic targeting strategy for the future.

• 한국산림과학회지
• /
• 제59권1호
• /
• pp.121-142
• /
• 1983

Recently mycorrhizal research has been one of the most fast-growing research areas in modern plant science and microbiology. The application potential of mycorrhizal techniques to agriculture and forestry is enormous in view of the ubiquitous nature of mycorrhizae and known benefits of mycorrhizae to host plants. Unfortunately, very few scientists in Korea are currently involved in mycorrhizal research. When a team of American plant pathologists visited Korea in September 1982 to participate in the Korea-U.S.A. Joint Seminar on Forest Diseases and Insect Pests, they were surprised by the principal author's statement that there was no single research project on mycorrhizae sponsored by Korean government or any scientific institutions. The author initiated a few years ago a research project on the ecology of tree mycorrhizae with a foreign financial support. Major areas of interest were survey of ectomycorrhizae in relation to soil fertility, taxonomic distribution of mycorrhizae among woody plants, identification of ectomycorrhizal fungi, and growth response of woody plants to artificial inoculation. In spite of the enormous application potential of mycorrhizae to agronomic plants, the subject of mycorrhizae has not been recognized by Korean agronomists, foresters or pathologists. The purpose of this review rather written in Korean is to introduce the techniques of mycorrhizal research to Korean scientists and to urge them to participate in challenging new scientific field which might bring us a remarkable increase in crop productivity and tree growth through manipulation of this unique symbiosis. In this review, following topics were discussed in the same order: introduction; brief history of mycorrhizal research; morphology and classification of mycorrhizae; distribution of mycorrhizae in plant kingdom and in soil profile; physiology of mycorrhizae (functions, mineral nutrition, mycorrhizal formation); interaction of mycorrhizae with soil-born plant pathogens. mycorrhizae in nitrogen-fixing plants; application of mycorrhizal techniques to nursery practices (isolation, culture, inoculation, and response); prospect in the future.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2008년도 제39회 하계학술대회
• /
• pp.1883-1884
• /
• 2008

This paper presents a framework for decentralized control of self-organizing swarm agents based on the artificial potential functions (APFs). The framework explores the benefits by associating agents based on position information to realize complex swarming behaviors. A key development is the introduction of a set of association rules by APFs that effectively deal with a host of swarming issues such as flexible and agile formation. In particular, this paper presents an association rule for swarming that requires less movements for each agent and compact formation among agents. Extensive simulations are presented to illustrate the viability of the proposed framework.