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A Parametric Analysis of Streamwise Vortices on a Compression Ramp at Mach 4
Get PDF九州工業大学博士（工学）1 Introduction|2 Mathematical modeling|3 Mesh Sensitivity and Validation Framework|4 Streamwise vortices in superosnic compression ramp flows|5 ConclusionShock-wave/boundary-layer interaction (SWBLI) over a compression ramp has been extensively studied to understand high-speed flow behavior around components such as control surfaces and engine inlets. The shock generated by wall deflection can cause boundary layer separation, with the extent of the separation bubble influenced by the upstream boundary layer state and ramp angle. Near the rear of the bubble, concave streamlines may induce Görtler-type instabilities, characterized by counter-rotating streamwise vortices that can promote transition to turbulence. Such vortices are observed in various applications, including flow over turbine blades, supercritical airfoils, and forebody compression surfaces in hypersonic inlets. In this work, Large-eddy simulations (LES) of supersonic flow over a compression ramp are conducted to investigate the formation of streamwise vortices and their impact on flow dynamics. The simulations are performed at a freestream Mach number of M∞ = 4.0 and unit Reynolds number of 4.56 × 10 6 per meter. Two ramp angles (15° and 18°) and three ramp corner positions(P1–P3) are examined. Initial 2D simulations across six configurations (15P1–3 and 18P1–3) help identify cases prone to Görtler instability. Results show that increasing the ramp angle or moving the ramp corner downstream leads to greater separation length and enhanced streamline curvature, promoting Görtler-type instabilities and the emergence of longitudinal vortices. For the 15° cases, no streaks are observed at P1–P2, but they begin to appear at P3. In contrast, all 18° cases exhibit longitudinal streaks, with the strongest spanwise interactions observed in the 18P3 case. Spanwise fluctuations intensify downstream due to both linear and nonlinear amplification of streamwise vortices. Notably, the vortex wavelength decreases by ~15% as plate length increases by 80% from 18P1 to 18P3. In the most extreme configuration (18P3), unsteady wall pressure data and iso-surfaces of the Qcriterion reveal intermittent high-frequency fluctuations—hallmarks of transitional flow. Further time-resolved analysis highlights the presence of secondary spanwise instabilities that give rise to turbulent spots propagating at about 60% of the freestream velocity. These findings provide clear evidence of the route to transition being driven by centrifugal instabilities in separated curved flows.
Another key result of this study is derived from space-time plots of the Stanton number (St), which visualize wall heat flux behavior across time and span. These plots reveal distinct, streamwisealigned, counter-rotating vortices that enhance local wall heating. In the 18P3 case, the peak St value is approximately 27% higher than its time- and span-averaged value, compared to ~17% for the 15P3 case highlighting stronger downwash and heat flux concentration in the steeper ramp configuration. Additionally, a negative correlation is observed between the flow reattachment location and local St near the reattachment point. Earlier reattachment corresponds to higher localheating rates, while delayed reattachment reduces the St value, resulting in up to 40% variation relative to the mean. These findings underscore the critical influence of ramp geometry and surface length on the formation and amplification of streamwise vortices. They also reveal important implications for wall heat transfer and transition prediction in hypersonic flows—two aspects crucial for thermal protection system (TPS) design and reliability of high-speed flight vehicles. The coupling between geometric parameters, instability growth, and thermal response provides a deeper physical understanding of SWBLI-induced transition mechanisms.九州工業大学博士学位論文 学位記番号:工博甲第607号 学位授与年月日:令和7年9月25日令和7年度doctoral thesi
A Proposal of Data Analyzer Utilizing “Key Words Meeting” Activity Logs to Assess Learner Attitudes and Provide Personalized Encouragement and Inspiration in Individual Classrooms
Get PDFIn the case of online learning systems, researchers and developers of the systems have been interested in automatic analysis and feedback methods of logged web data in the aim of encouragements of learners effectively. Logs of learner activity within online systems implicitly represent not only memory retention levels of learning contents but also their awareness and perceptions as a clue even it is not directly connected to the content itself and yet a hint for improvements in future learning. In the KWM system, which was designed for diverse individuals to agree with each other for becoming one as a team in an epidemiological sense, we focused on the method to analyze logs in the website for the clarification of the interactive process between the lecturer and learners and simultaneously influences of sharing the interactive information. Since a major upgrade of the KWM harms compatibility with the existing version and the involvement of new functions may have a risk for speeding down as the online web system, we have proposed the back-end system to support lecturers as KWM users but also validate its computational effort for considerations of possible KWM upgrades. In the computer experiment, we compared the tabular method with the nested tree data structure and demonstrated the effectiveness in the sense of computational costs.journal articl
ソフトウェア不具合解析作業の効率化に向けたテキストログ異常検知に関する研究
Get PDF九州工業大学博士（工学）1 序論| 2 SPClassifier を使用したログ異常検知手法の改善：複数のアンサンブル手
法| 3 代表的なログ異常検知モデルの汎用性評価| 4 研究用ログデータセットと開発現場におけるログ構造の違いと複雑度の評価指標の作成| 5 ログのパラメータ異常を検出するための研究課題と提案手法の調査| 6 教師なし学習手法を用いたマルチログパラメータ異常検知| 7 教師なしマルチログパラメータ異常検知：提案Token を追加した精度改善| 8 パラメータ異常検知：学習データ内ノイズ割合による精度変化の調査| 9 事前学習済みBERT モデルを使用したパラメータ異常検知精度の評価| 10 総まとめ九州工業大学博士学位論文 学位記番号:工博甲第605号 学位授与年月日:令和7年3月25日令和7年度doctoral thesi
Assertive Communication Practice Using GPT: Development, Practice and Challenges
Get PDFWith the release of ChatGPT by OpenAI, the use of generative AI in education is accelerating. While various AI technologies have already been introduced into educational settings, the adoption of generative AI raises concerns about dependency and ethical issues, and researchers are warning to carefully evaluate its educational effectiveness. Collaborating with a researcher specializing in AI development for service robots, a teacher-researcher in language and culture education, explored the possibility of incorporating GPT into an educational module for intercultural communication. This paper is an empirical study examining chat data, GPT’s evaluation of learners, and learners’ self-evaluation obtained from the module. The study investigates the efficacy and limitations of the module by using the critical discourse analysis method. The findings suggest that the module provides opportunities to train learners in intercultural communication skills, however, it also highlights the need for improvements to maximize the effective use of GPT.departmental bulletin pape
Mitigating opinion polarization in social networks using adversarial attacks
Get PDFIn recent years, the spread of social networking services (SNS) has made it easier to connect with people who have similar opinions. Accordingly, similar opinions are shared within a group, while the frequency of exposure to different opinions tends to decrease. As a result, the polarization of opinion among groups is more likely to occur. Some studies have been conducted to identify the conditions under which opinion polarization occurs by simulating opinion dynamics, but specific methods for mitigating it have been poorly understood. Recently, it was found that even a few artificial perturbations inspired by the adversarial attack reverse the result in voter models, where a minority opinion becomes dominant through these perturbations. In this study, we conducted numerical simulations to determine whether it is possible to mitigate opinion polarization by adding such perturbations to the network in opinion dynamics models. The results show that opinion polarization can be mitigated by strategically generating perturbations to the weights of network links, and the effect increases as the perturbation strength parameter increases. Moreover, our analysis reveals that the effectiveness of this polarization mitigating method is enhanced in larger networks. Our results propose an effective way to prevent polarization of opinion in social networks.journal articl
Generation of Photo Slideshow with Song based on Closeness between Concept of Lyrics and That of Images
Get PDFThis paper proposes a method that allows users to easily convert a large number of still images into movies by displaying photos in sync with memories or favorite songs, which offers a new media viewing method for users to look back at the vast number of photos in their photo folders. We assume here that users select a song and have images stored in local PC. One method of synchronization involves selecting images based on elapsed time of song. However, since lyrics convey meaning, it can be better to display the images that align with both lyrics’ meaning and images’ meaning matched. In order to do this, we need the space which shares the concept of both lyrics and images, and select colors as the concept. Displayed images are determined based on the distance between points that are mapped from words and images to color space. Specifically, the color concepts from words are extracted using the Color Image Scale, and that from images are determined as the most frequent colors by cluster analysis. Experimental results show that it is possible to easily create movies where images with colors that match the mood of the lyrics are displayed.journal articl
土に埋もれる ―マシーセンが読むソローとジュエット
Get PDF『アメリカン・ルネサンス ―エマソンとホイットマンの時代の芸術と表現』（American Renaissance: Art and Expression in the Age of Emerson and Whitman, 1941）で扱った5人の作家の共通項としてF. O. マシーセン（F. O. Matthiessen）が掲げた「民主主義（democracy）」（ix)は、1970年代以降、フェミニスト批評家たちから批判されてきた。彼の民主主義に女性排除の傾向を見たニーナ・ベイム（Nina Baym）やジェイン・トンプキンス（Jane Tompkins）は女性作家の再評価に踏み出し、そこからジェンダー研究と不可分の感傷小説研究の系譜が展開していく。ベイムやトンプキンスが女性作家を再評価する際に打ち出したのは、共感という価値だった。彼女たちは共感によってマシーセンの女性排除に対抗したのだが、実はマシーセンは彼女たちよりも早く、『アメリカン・ルネサンス』で、共感という観点からホーソーン、メルヴィル、ホイットマンを高く評価していだ。ではこの批評家は、女性作家についてはどのように評価していたのか。
マシーセンは『アメリカン・ルネサンス』の出版より12年前の1929年に、批評家としての第一作『セアラ・オーン・ジュエット』（Sarah Orne Jewett）を上梓している。彼がジュエットを重視していたことはジョセフ・シシラ（Joseph Csicsila）、デイヴィッド・バーグマン（David Bergman）、舌津智之らの研究によって明らかになっている。にもかかわらず、マシーセンが女性作家を排除したという前提は、感傷小説研究において脈々と受け継がれてしまっている（大野，「共感するマシーセン」1, 7, n6)。シシラらの研究を踏まえる本稿では、『ジュエット』におけるジュエットの扱いを『アメリカン・ルネサンス』におけるソローのそれと比較し、マシーセンがソローを共感という基準では評価しなかった一方、ジュエットについては共感という側面からホーソーンの系譜に位置付けつつ、鋭敏な身体感覚と士壌に根ざした言語表現という点でソローの系譜とみなしていることを明らかにする。この考察を通じ、女性作家排除の代表格とみなされがちであったマシーセンを、ジュエット研究の開拓者として再評価したい。journal articl
Automatic Classification of Respiratory Sounds Based on Convolutional Recurrent Neural Network and Bagging k-Nearest Neighbor
Get PDFRespiratory diseases or lung diseases such as asthma bronchiectasis cystic fibrosis are a serious disease. Approximately 8 million people died in each year by chronic obstructive pulmonary disease, lower respiratory tract infections, trachea, bronchial and lung tumors. In addition, COVID-19 is prevalent worldwide in recent years. To analyze these symptom, auscultation of respiratory sounds is very important for screening the respiratory disease. However, there is no quantitative evaluation method for the diagnosis of respiratory sounds until now. To overcome this problem, it is necessary to develop a system to support the diagnosis of respiratory sounds. In the development of support system for auscultation, research by a large-scale, open database used in ICBHI (The International Conference on Biomedical and Health Informatics) 2017 Challenge is in progress. It is expected that a general purpose and highly accurate system will be developed using this dataset. We describe an algorithm for the automatic classification of the respiratory sounds as crackles, wheeze, both, and normal. We improve the classification rates compared with other ICBHI 2017 Challenge teams based on three components. First, we generate the spectrogram images by short-time Fourier transformation. We also extract features using a convolutional recurrent neural network. Third, we classify unknown respiratory sounds by bagging k-nearest neighbor algorithm. In the experiment, we applied our proposed method to 920 respiratory sound data which is obtained by the ICBHI Challenge data sets, and achieved Sensitivity with 0.670, Specificity with 0.863, ICBHI Score with 0.766 respectively. Also, area under the curve based on receiver operating characteristic curve of normal class with 0.892, crackle with 0.891, wheeze with 0.874, both with 0.883 were obtained respectively.journal articl
A Computational Approach for Global Trade Analysis in Korea Contributing to the Forecasting of Future Efficacy in Global and Domestic Korean Transportations
Get PDFEconomic forecasting studies are integral for shaping strategic policy decisions by providing data-driven insights that guide resource allocation, logistics and transportation, and long-term planning. This study investigate the trade dynamics of the Republic of Korea through the Global Trade Analysis Project Recursive dynamic GTAP-RD model with the GTAP v11 database to forecast economic scenarios and Shared Socioeconomic Pathways (SSPs) serve as growth trajectories. The analysis centers on the Republic of Korea's key trading partners, as identified by the GTAP database, and top trading sectors from the Korea Transport Database (KTDB) to compare the key influencers on Korea's trade thereby providing deeper strategic economic planning. This study investigates further the involvement of Korea's logistics and transportation by focusing on changes in import/export tonnage to inform infrastructure planning and strategic transport development. The evaluation of Korea's trade in the global context is of the essence to ensure adaptive logistics, backing economic resilience, and aligning with changeable global trade conditions.conference pape
A Data Format Integration of Open-Street-Map and Lanelet2 Toward the Ontology Framework for Safety Automated driving systems
Get PDFThis study proposes a framework that integrates OpenStreetMap (OSM) data with ontology-based systems to enhance automated driving. OSM provides static geographical data, while the Lanelet2 mapping framework incorporates lanelevel road information and topological relationships. This combination enables advanced testing of vehicle behavior in realistic environments. Ontology-based integration offers semantic representations of road elements and traffic rules, supporting the modeling of complex driving scenarios. By structuring spatial and semantic data, this approach ensures accurate simulation and testing, facilitating applications such as traffic analysis, route optimization, and automated driving decision-making. The framework enhances scalability, precision, and safety in autonomous vehicle development, enabling more effective testing and validation. This integration supports comprehensive, context-aware simulations that improve vehicle response to real-world driving conditions.conference pape