• Title/Summary/Keyword: Design optimization

Search Result 8,499, Processing Time 0.038 seconds

Optimization of Dual Layer Phoswich Detector for Small Animal PET using Monte Carlo Simulation

  • Y.H. Chung;Park, Y.;G. Cho;Y.S. Choe;Lee, K.H.;Kim, S.E.;Kim, B.T.
    • Proceedings of the Korean Society of Medical Physics Conference
    • /
    • 2003.09a
    • /
    • pp.44-44
    • /
    • 2003
  • As a basic measurement tool in the areas of animal models of human disease, gene expression and therapy, and drug discovery and development, small animal PET imaging is being used increasingly. An ideal small animal PET should have high sensitivity and high and uniform resolution across the field of view to achieve high image quality. However, the combination of long narrow pixellated crystal array and small ring diameter of small animal PET leads to the degradation of spatial resolution for the source located at off center. This degradation of resolution can be improved by determining the depth of interaction (DOI) in the crystal and by taking into account the information in sorting the coincident events. Among a number of 001 identification schemes, dual layer phsowich detector has been widely investigated by many research groups due to its practicability and effectiveness on extracting DOI information. However, the effects of each crystal length composing dual layer phoswich detector on DOI measurements and image qualities were not fully characterized. In order to minimize the DOI effect, the length of each layer of phoswich detector should be optimized. The aim of this study was to perform simulations using a simulation tool, GATE to design the optimum lengths of crystals composing a dual layer phoswich detector. The simulated small PET system employed LSO front layer LuYAP back layer phoswich detector modules and the module consisted of 8${\times}$8 arrays of dual layer crystals with 2 mm ${\times}$ 2 mm sensitive area coupled to a Hamamatsu R7600 00 M64 PSPMT. Sensitivities and variation of radial resolutions were simulated by varying the length of LSO front layer from 0 to 10 mm while the total length (LSO + LuYAP) was fixed to 20 mm for 10 cm diameter ring scanner. The radial resolution uniformity was markedly improved by using DOI information. There existed the optimal lengths of crystal layers to minimize the variation of radial resolutions. In 10 cm ring scanner configuration, the radial resolution was kept below 3.4 mm over 8 cm FOV while the sensitivity was higher than 7.4% for LSO 5 mm : LuYAP 15 mm phoswich detector. In this study, the optimal length of dual layer phoswich detector was derived to achieve high and uniform radial resolution.

  • PDF

The Optimization of Hyperbolic Settlement Prediction Method with the Field Data for Preloading on the Soft Ground (쌍곡선법을 이용한 계측 기반 연약지반 침하 거동 예측의 최적화 방안)

  • Choo, Yoon-Sik;Kim, June-Hyoun;Hwang, Se-Hwan;Chung, Choong-Ki
    • Journal of the Korean Geotechnical Society
    • /
    • v.26 no.7
    • /
    • pp.147-159
    • /
    • 2010
  • The settlement prediction is very important in preloading method for a construction site on the soft ground. At the design stage, however, it is hard to predict the settlement exactly due to limitations of the site survey. Most of the settlement prediction is performed by a regression settlement curve based on the field data during construction. In Korea, hyperbolic method has been most commonly used to align the settlement curve with the field data, because of its simplicity and many application cases. The results from hyperbolic method, however, may differ by data selections or data fitting methods. In this study, the analyses using hyperbolic method were performed about the field data of $\bigcirc\bigcirc$ site in Pusan. Two data fitting methods, using an axis transformation or an alternative method which is a direct regression method, were applied with various data groups. If data was used only after the ground water level being stabilized, fitting results using both methods were in good agreement with the measured data. Regardless of the information about the ground water level, the alternative method gives better results with the field data than the method using an axis transformation.

Prediction of the remaining time and time interval of pebbles in pebble bed HTGRs aided by CNN via DEM datasets

  • Mengqi Wu;Xu Liu;Nan Gui;Xingtuan Yang;Jiyuan Tu;Shengyao Jiang;Qian Zhao
    • Nuclear Engineering and Technology
    • /
    • v.55 no.1
    • /
    • pp.339-352
    • /
    • 2023
  • Prediction of the time-related traits of pebble flow inside pebble-bed HTGRs is of great significance for reactor operation and design. In this work, an image-driven approach with the aid of a convolutional neural network (CNN) is proposed to predict the remaining time of initially loaded pebbles and the time interval of paired flow images of the pebble bed. Two types of strategies are put forward: one is adding FC layers to the classic classification CNN models and using regression training, and the other is CNN-based deep expectation (DEX) by regarding the time prediction as a deep classification task followed by softmax expected value refinements. The current dataset is obtained from the discrete element method (DEM) simulations. Results show that the CNN-aided models generally make satisfactory predictions on the remaining time with the determination coefficient larger than 0.99. Among these models, the VGG19+DEX performs the best and its CumScore (proportion of test set with prediction error within 0.5s) can reach 0.939. Besides, the remaining time of additional test sets and new cases can also be well predicted, indicating good generalization ability of the model. In the task of predicting the time interval of image pairs, the VGG19+DEX model has also generated satisfactory results. Particularly, the trained model, with promising generalization ability, has demonstrated great potential in accurately and instantaneously predicting the traits of interest, without the need for additional computational intensive DEM simulations. Nevertheless, the issues of data diversity and model optimization need to be improved to achieve the full potential of the CNN-aided prediction tool.

Empirical and Numerical Analyses of a Small Planing Ship Resistance using Longitudinal Center of Gravity Variations (경험식과 수치해석을 이용한 종방향 무게중심 변화에 따른 소형선박의 저항성능 변화에 관한 연구)

  • Michael;Jun-Taek Lim;Nam-Kyun Im;Kwang-Cheol Seo
    • Journal of the Korean Society of Marine Environment & Safety
    • /
    • v.29 no.7
    • /
    • pp.971-979
    • /
    • 2023
  • Small ships (<499 GT) constitute 46% of the existing ships, therefore, it can be concluded that they produce relatively high CO2 gas emissions. Operating in optimal trim conditions can reduce the resistance of the ship, which results in fewer greenhouse gases. An affordable way for trim optimization is to adjust the weight distribution to obtain an optimum longitudinal center of gravity (LCG). Therefore, in this study, the effect of LCG changes on the resistance of a small planing ship is studied using empirical and numerical analyses. The Savitsky method employing Maxsurf resistance and the STAR-CCM+ commercial computational fluid dynamics (CFD) software is used for the empirical and numerical analyses, respectively. Finally, the total resistance from the ship design process is compared to obtain the optimum LCG. To summarize, using numerical analysis, optimum LCG is achieved at the 46.2% length overall (LoA) at Froude Number 0.56, and 43.4% LoA at Froude Number 0.63, which provides a significant resistance reduction of 41.12 - 45.16% compared to the reference point at 29.2% LoA.

Explainable Artificial Intelligence (XAI) Surrogate Models for Chemical Process Design and Analysis (화학 공정 설계 및 분석을 위한 설명 가능한 인공지능 대안 모델)

  • Yuna Ko;Jonggeol Na
    • Korean Chemical Engineering Research
    • /
    • v.61 no.4
    • /
    • pp.542-549
    • /
    • 2023
  • Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.

Research and improvement of image analysis and bar code and QR recognition technology for the development of visually impaired applications (시각장애인 애플리케이션 개발을 위한 이미지 분석과 바코드, QR 인식 기술의 연구 및 개선)

  • MinSeok Cho;MinKi Yoon;MinSu Seo;YoungHoon Hwang;Hyun Woo;WonWhoi Huh
    • The Journal of the Convergence on Culture Technology
    • /
    • v.9 no.6
    • /
    • pp.861-866
    • /
    • 2023
  • Individuals with visual impairments face difficulties in accessing accurate information about medical services and medications, making it challenging for them to ensure proper medication intake. While there are healthcare laws addressing this issue, there is a lack of standardized solutions, and not all over-the-counter medications are covered. Therefore, we have undertaken the design of a mobile application that utilizes image recognition technology, barcode scanning, and QR code recognition to provide guidance on how to take over-the-counter medications, filling the existing gaps in the knowledge of visually impaired individuals. Currently available applications for individuals with visual impairments allow them to access information about medications. However, they still require the user to remember which specific medication they are taking, posing a significant challenge. In this research, we are optimizing the camera capture environment, user interface (UI), and user experience (UX) screens for image recognition, ensuring greater accessibility and convenience for visually impaired individuals. By implementing the findings from our research into the application, we aim to assist visually impaired individuals in acquiring the correct methods for taking over-the-counter medications.

Design and Performance Evaluation of Digital Twin Prototype Based on Biomass Plant (바이오매스 플랜트기반 디지털트윈 프로토타입 설계 및 성능 평가)

  • Chae-Young Lim;Chae-Eun Yeo;Seong-Yool Ahn;Myung-Ok Lee;Ho-Jin Sung
    • The Journal of the Convergence on Culture Technology
    • /
    • v.9 no.5
    • /
    • pp.935-940
    • /
    • 2023
  • Digital-twin technology is emerging as an innovative solution for all industries, including manufacturing and production lines. Therefore, this paper optimizes all the energy used in a biomass plant based on unused resources. We will then implement a digital-twin prototype for biomass plants and evaluate its performance in order to improve the efficiency of plant operations. The proposed digital-twin prototype applies a standard communication platform between the framework and the gateway and is implemented to enable real-time collaboration. and, define the message sequence between the client server and the gateway. Therefore, an interface is implemented to enable communication with the host server. In order to verify the performance of the proposed prototype, we set up a virtual environment to collect data from the server and perform a data collection evaluation. As a result, it was confirmed that the proposed framework can contribute to energy optimization and improvement of operational efficiency when applied to biomass plants.

A Simulation Study of the Inset-fed 2-patch Microstrip Array Antenna for X-band Applications (X-band 대역용 2-패치 마이크로스트립 인셋 급전 어레이 안테나 시뮬레이션 연구)

  • Nkundwanayo Seth;Gyoo-Soo Chae
    • Advanced Industrial SCIence
    • /
    • v.3 no.2
    • /
    • pp.31-37
    • /
    • 2024
  • This paper presents a single and 2-patch microstrip array antenna operated on a frequency of 10.3GHz(x-band). It outlines the process of designing a microstrip patch array antenna using CST MWS. Initially, a single microstrip antenna was designed, followed by optimization using CST MWS to attain optimal return losses and gain. Subsequently, the design was expanded to create a 2×1 microstrip inset-fed array antenna for the X-band applications. The construction material is Roger RO4350B, with specific dimensions (h=0.79mm, 𝜖r = 3.54). The achieved results include an S11 of -18dB at the resonant frequency (10.3GHz), a gain of 9.82dBi, a bandwidth of 0.165GHz, and a 3-dB beamwidth of 30°, 121° in Az(𝜑=0) and El(𝜑=90) plane, respectively. The future plan involves the fabrication of this array antenna and further expansion to a 4×4 array of microstrip antennas. It is then incorporated on the X-band applications for practical uses.

State-Space Equation Model for Motion Analysis of Floating Structures Using System-Identification Methods (부유식 구조체 운동 해석을 위한 시스템 식별 방법을 이용한 상태공간방정식 모델)

  • Jun-Sik Seong;Wonsuk Park
    • Journal of the Computational Structural Engineering Institute of Korea
    • /
    • v.37 no.2
    • /
    • pp.85-93
    • /
    • 2024
  • In this paper, we propose a method for establishing a state-space equation model for the motion analysis of floating structures subjected to wave loads, by applying system-identification techniques. Traditionally, the motion of floating structures has been analyzed in the time domain by integrating the Cummins equation over time, which utilizes a convolution integral term to account for the effects of the retardation function. State-space equation models have been studied as a way to efficiently solve floating-motion equations in the time domain. The proposed approach outlines a procedure to derive the target transfer function for the load-displacement input/output relationship in the frequency domain and subsequently determine the state-space equation that closely approximates it. To obtain the state-space equation, the method employs the N4SID system-identification method and an optimization approach that treats the coefficients of the numerator and denominator polynomials as design variables. To illustrate the effectiveness of the proposed method, we applied it to the analysis of a single-degree-of-freedom model and the motion of a six-degree-of-freedom barge. Our findings demonstrate that the presented state-space equation model aligns well with the existing analysis results in both the frequency and time domains. Notably, the method ensures computational accuracy in the time-domain analysis while significantly reducing the calculation time.

Preparation of Cosmeceuticals Containing Scutellaria baicalensis Extracts: Optimization of Emulsion Stability and Antibacterial Property (황금추출물이 함유된 Cosmeceuticals의 제조: 유화안정성 및 항균특성 최적화)

  • Seheum Hong;Young Woo Choi;Wenjia Xu;Seung Bum Lee
    • Applied Chemistry for Engineering
    • /
    • v.35 no.4
    • /
    • pp.316-320
    • /
    • 2024
  • To optimize the emulsion stability and antibacterial activity against Escherichia coli (E. coli) of cosmeceuticals using Scutellaria baicalensis extracts and olive wax as natural emulsifiers, we conducted a study. The independent variables were the amounts of Scutellaria baicalensis extracts and olive wax added. The response variables included the emulsion stability index (ESI) of the cosmeceuticals product and the inhibition diameter against E. coli. Through central composite design-response surface methodology (CCD-RSM), we obtained a statistically significant and reliable regression equation within a 95% confidence interval. By optimizing multiple responses, we determined that the optimal emulsification conditions that satisfied both ESI and E. coli inhibition diameter were 3.7 wt% of Scutellaria baicalensis extracts and 2.7 wt% of olive wax. The predicted ESI and E. coli inhibition diameter were 97.9% and 9.7 mm, respectively. When actual experiments were conducted under the optimal conditions, the measured ESI and E. coli inhibition diameter were 95.0% and 9.4 mm, respectively, with an average error rate of 3.2 ± 0.4%.