• Computers and Concrete
• /
• 제14권4호
• /
• pp.387-403
• /
• 2014

The aim of this study is to assess the structural performance of deteriorated reinforced concrete bridge piers, and to provide method for developing improved evaluation method. For a deteriorated bridge piers, once the cover spalls off and bond between the reinforcement and concrete has been lost, compressed reinforcements are likely to buckle. By using a sophisticated nonlinear finite element analysis program, the accuracy and objectivity of the assessment process can be enhanced. A computer program, RCAHEST (Reinforced Concrete Analysis in Higher Evaluation System Technology), is used to analyze reinforced concrete structures. Material nonlinearity is taken into account by comprising tensile, compressive and shear models of cracked concrete and a model of reinforcing steel. Advanced deteriorated material models are developed to predict behaviors of deteriorated reinforced concrete. The proposed numerical method for the structural performance assessment of deteriorated reinforced concrete bridge piers is verified by comparing it with reliable experimental results. Additionally, the studies and discussions presented in this investigation provide an insight into the key behavioral aspects of deteriorated reinforced concrete bridge piers.

• Computers and Concrete
• /
• 제14권4호
• /
• pp.405-417
• /
• 2014

The poor seismic performance of reinforced concrete buildings during the latest earthquakes has become a serious issue in the building industry in Turkey. This case, designing new buildings without structural irregularities against earthquake loads reveals to be quite significant. This study mainly is focused on the effects of different torsional irregularities on construction costs and earthquakes performance of reinforced concrete buildings. In that respect, structural torsional irregularities are investigated based on the Turkish Earthquake Code. The study consists of major eight main parametric models. In this models consist of totally 49 models together with the variations in the number of storey. With this purpose, the earthquake performances and construction costs (especially steel quantities) of reinforced concrete buildings which having different structural torsional irregularities were obtained with the help of Sta4-CAD program. Each model has been analyzed by both the methods of equivalent earthquake loading and dynamic analysis. The obtained results reveal that the model-1 which has lower torsional irregularity coefficient shows the best earthquake performance owing to its regular plan geometry. Also, economical comparisons on costs of the torsional irregularity are performed, and results-recommendations are given.

• Journal of Biosystems Engineering
• /
• 제24권5호
• /
• pp.445-452
• /
• 1999

This study was conducted to develop a searching algorithm for optimal daily temperature setpoint greenhouse. An algorithm using crop growth and energy models was developed to determine optimum crop growth environment. The results of this study were as follows: 1. Mathematical models for crop growth and energy consumption were derived to define optimal daily temperature setpoint. 2. Optimum temperature setpoint, which could maximize performance criterion, was determined by using Pontryagin maximum principle. 3. Dynamic control of daily temperature using the developed algorithm showed higher performance criterion than static control with fixed temperature setpoint. Performance criteria for dynamic control models were with simulated periodic weather data and with real weather data, increased by 48% and 60%, respectively.

• 한국유체기계학회 논문집
• /
• 제2권4호
• /
• pp.57-64
• /
• 1999

The prediction method of the performance and aerodynamic noise from a sirocco fan was developed and compared with measured data. To predict the performance of the sirocco fan, the well-known slip coefficients and various loss models were tested and applied to forward curved sirocco impellers. Using loss models proposed for both impeller and casing, the predicted performance characteristics were in good agreement with measured ones by an ANSI test plenum. Various scaling models for aerodynamic noise from the sirocco fan were evaluated and tested against measured power levels in terms of flow coefficient. It was shown that the turbulent broadband sound power from the sirocco fan can be modeled successfully by trailing edge noise.

• 한국가스학회지
• /
• 제10권2호
• /
• pp.55-60
• /
• 2006

Detailed modeling of PEMFCs has been getting considerable interest for predicting the fuel cell performance and also for use in various systems engineering activities. While CFD-based equipment models provide detailed analyses of the performance, they are very time-consuming to develop and run. The computations become quite complex when such models have to be embedded into the flowsheet-level optimization of fuel cell systems. In this paper, we present results about building and using NN-based reduced order models for quickly and repetitively predicting the flow of reactants in a PEMFC manifold.

• 대한기계학회논문집B
• /
• 제21권6호
• /
• pp.804-812
• /
• 1997

The present study has tested most of loss models previously published in the open literature and found an optimum set of empirical loss models for a reliable performance prediction of centrifugal compressors. In order to improve the prediction of efficiency curves, this paper recommends a modified parasitic loss model. Predicted performance curves by the proposed optimum set agree fairly well with experimental data for a variety of centrifugal compressors. The prediction method developed through this study can serve as a tool for preliminary design and assist the understanding of the operational characteristics of general purpose centrifugal compressors.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제4권4호
• /
• pp.452-474
• /
• 2010

Formidable growth of Internet technologies has revealed challenging issues about its scale and performance evaluation. Modeling and simulation play a central role in the evaluation of the behavior and performance of the large-scale network systems. Large numbers of nodes affect simulation performance, simulation execution time and scalability in a weighty manner. Most of the existing simulators have numerous problems such as size, lack of system theoretic approach and complexity of modeled network. In this work, a scalable discrete-event modeling approach is described for studying networks' scalability and performance traits. Key fundamental attributes of Internet and its protocols are incorporated into a set of simulation models developed using the Discrete Event System Specification (DEVS) approach. Large-scale network models are simulated and evaluated to show the benefits of the developed network models and approaches.

• Journal of electromagnetic engineering and science
• /
• 제12권3호
• /
• pp.203-209
• /
• 2012

In order to improve sensing performance when the noise variance is not known, this paper considers a so-called blind spectrum sensing technique that is based on eigenvalue models. In this paper, we employed the spiked population models in order to identify the miss detection probability. At first, we try to estimate the unknown noise variance based on the blind measurements at a secondary location. We then investigate the performance of detection, in terms of both theoretical and empirical aspects, after applying this estimated noise variance result. In addition, we study the effects of the number of SUs and the number of samples on the spectrum sensing performance.

• 산업경영시스템학회지
• /
• 제46권1호
• /
• pp.55-67
• /
• 2023

Lightweight face recognition models, as one of the most popular and long-standing topics in the field of computer vision, has achieved vigorous development and has been widely used in many real-world applications due to fewer number of parameters, lower floating-point operations, and smaller model size. However, few surveys reviewed lightweight models and reimplemented these lightweight models by using the same calculating resource and training dataset. In this survey article, we present a comprehensive review about the recent research advances on the end-to-end efficient lightweight face recognition models and reimplement several of the most popular models. To start with, we introduce the overview of face recognition with lightweight models. Then, based on the construction of models, we categorize the lightweight models into: (1) artificially designing lightweight FR models, (2) pruned models to face recognition, (3) efficient automatic neural network architecture design based on neural architecture searching, (4) Knowledge distillation and (5) low-rank decomposition. As an example, we also introduce the SqueezeFaceNet and EfficientFaceNet by pruning SqueezeNet and EfficientNet. Additionally, we reimplement and present a detailed performance comparison of different lightweight models on the nine different test benchmarks. At last, the challenges and future works are provided. There are three main contributions in our survey: firstly, the categorized lightweight models can be conveniently identified so that we can explore new lightweight models for face recognition; secondly, the comprehensive performance comparisons are carried out so that ones can choose models when a state-of-the-art end-to-end face recognition system is deployed on mobile devices; thirdly, the challenges and future trends are stated to inspire our future works.

• 대한원격탐사학회지
• /
• 제39권5_4호
• /
• pp.1111-1123
• /
• 2023

원격탐사 영상을 이용한 지표 속성의 변화를 모니터링 하기 위해서 딥러닝(deep learning) 모델을 이용한 의미론적 영상 분할 방법이 최근에 널리 사용되고 있다. 대표적인 의미론적 영상 분할 딥러닝 모델인 UNet 모델을 비롯하여 다양한 종류의 UNet 기반의 딥러닝 모델들의 성능 향상을 위해서는 학습 데이터셋의 크기가 충분해야 한다. 학습 데이터셋의 크기가 커지면 이를 처리하는 하드웨어 요구 사항도 커지고 학습에 소요되는 시간도 크게 증가되는 문제점이 발생한다. 이런 문제를 해결할 수 있는 방법인 전이학습은 대규모의 학습 데이터 셋이 없어도 모델 성능을 향상시킬 수 있는 효과적인 방법이다. 본 논문에서는 UNet 기반의 딥러닝 모델들을 대표적인 사전 학습 모델(pretrained model)인 VGG19 모델 및 ResNet50 모델과 결합한 세 종류의 전이학습 모델인 UNet-ResNet50 모델, UNet-VGG19 모델, CBAM-DRUNet-VGG19 모델을 제시하고 이를 건물 추출에 적용하여 전이학습 적용에 따른 정확도 향상을 분석하였다. 딥러닝 모델의 성능이 학습률의 영향을 많이 받는 점을 고려하여 학습률 설정에 따른 각 모델별 성능 변화도 함께 분석하였다. 건물 추출 결과의 성능 평가를 위해서 Kompsat-3A 데이터셋, WHU 데이터셋, INRIA 데이터셋을 사용하였으며 세 종류의 데이터셋에 대한 정확도 향상의 평균은 UNet 모델 대비 UNet-ResNet50 모델이 5.1%, UNet-VGG19 모델과 CBAM-DRUNet-VGG19 모델은 동일하게 7.2%의 결과를 얻었다.