Mekatronik Mühendisliği Bölümü Koleksiyonu

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https://hdl.handle.net/20.500.13055/48

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Artificial intelligence in planetary science and astronomy: Applications and research potential
(Euro Planet, 2025) Kacholia, Devanshi; Verma, Nimisha; D’Amore, Mario; Angrisani, Marianna; Frigeri, Alessandro; Schmidt, Frédéric; Carruba, Valerio; Hatipoğlu, Y. Güray; Roos-Serote, Maarten; Smirnov, Evgeny; Vergara Sassarini, Natalia Amanda; Solmaz, Arif; Oszkiewicz, Dagmara; Ivanovski, Stavro
Artificial Intelligence (AI) is one of the most influential fields of the 21st century (Zhang et al., 2021). Rich, E (2019) candidly described it as “the study of how to make computers do things which, at the moment, people do better”, today AI often surpasses human ability in tasks like large scale data mining and pattern recognition - its true strength. AI’s subfields - Machine Learning (ML) and deep learning (DL), play a critical role in expanding the usage to a vast variety of fields like planetary science, astronomy, earth observations, and remote sensing, just to name a few. There is an expected inclination towards incorporating AI more frequently in the studies of planetary science given the vast and complex nature of planetary data. In fact, AI has already been instrumental in extracting meaningful insights and advancing research in both interplanetary and astronomical studies. In planetary sciences, several AI techniques have been employed in order to bridge gaps in our understanding of the varied patterns and occurrences for studying the natural features observable from the data returned by scientific payloads. For example, PCA and cluster analysis can help in detecting patterns of compositional variation from multi and hyper-spectral imagery (Moussaoui et al., 2008; D’Amore & Padovan, 2022). Furthermore, to study specific features and patterns in their occurrences, correlations with neighbouring features; unsupervised algorithms and more complex -supervised techniques can be helpful depending on the scale of the task. From simple methods of unsupervised learning like clustering used to study the spectral signatures of Jezero crater on Mars (Pletl et al., 2023) to applying large language models to track asteroids affected by gravitational effects which alter the asteroid’s orbit (Carruba et al., 2025), such applications highlight the prospects of AI in the field of planetary science. Henceforth, to develop a deeper understanding of the potential and applications of ML, below is a typical AI workflow.
Planetary research: A new diamond open access journal for planetary science
(Euro Planet, 2025) Attree, Nicholas; Crameri, Fabio; Broquet, Adrien; Seignovert, Benoît; Hatipoğlu, Güray; Solmaz, Arif; Wieczorek, Mark
Planetary Research is a new diamond open-access journal for the planetary sciences and is set to be launched in January 2026. Planetary Research will follow an alternative to the traditional model of commercial publishing: the diamond open access model, whereby the journal is run entirely by volunteers using free and open-source software, and owned by the community, through a non-profit association that has been set up in France (The Planetary Research Cooperative). This means that all articles published in Planetary Research will be available for free for both authors and readers, with no access, subscription, or submission processing charges, whilst the journal scope and principles are determined by the community through participation in the online forum and monthly meetings. Further opportunities for participation include open calls for the positions of editor-in chief, editors, associate editors, and members of the media team and technical team, with deadlines on July the 1st, 2025 (see https://planetary-research.org for details).
Europlanet machine learning working group: A year of progress
(Euro Planet, 2025) Ivanovski, Stavro Lambrov; Verma, Nimisha; Hatipoğlu, Güray; Angrisani, Marianna; Solmaz, Arif; Smirnov, Evgeny; Carruba, Valerio; Kacholia, Devanshi; Oszkiewicz, Dagmara; D'Amore, Mario
The rapid advances in machine learning (ML) present unprecedented opportunities for planetary science. We have established a dedicated working group (WG) focused on the application of ML in this field to harness these technological advancements, address complex scientific questions, and enhance our understanding of planetary systems. The Europlanet Machine Learning Working Group held its kick-off meeting during the EPSC 2024 in Berlin, September 2024. The discussion focused on launching the group for exchanging ideas and opportunities with people within and outside of Europlanet’s membership for the first year of its launch. Some of the main goals established were to create a knowledge-sharing platform for members to share their research and invite collaboration, form sub-groups within the WG to expand on current research focus, and foster new collaborative research opportunities within or outside of Europlanet with new funding.
Testing the performance of cross-correlation techniques to search for molecular features in JWST NIRSpec G395H observations of transiting exoplanets
(Oxford University Press, 2025) Esparza-Borges, Emma; Lopez-Morales, Mercedes; Palle, Enric; Makhnev, Vladimir; Gordon, Iouli; Hargreaves, Robert; Kirk, James; Caceres, Claudio; Solmaz, Arif; Redfield, Seth
Cross-correlations techniques offer an alternative method to search for molecular species in James Webb Space Telescope (JWST) observations of exoplanet atmospheres. In a previous article, we applied cross-correlation functions for the first time to JWST NIRSpec/G395H observations of exoplanet atmospheres, resulting in a detection of CO in the transmission spectrum of WASP-39b and a tentative detection of CO isotopologues. Here, we present an improved version of our cross-correlation technique and an investigation into how efficient the technique is when searching for other molecules in JWST NIRSpec/G395H data. Our search results in the detection of more molecules via cross-correlations in the atmosphere of WASP-39b, including H2O and CO2, and confirms the CO detection. This result proves that cross-correlations are a robust and computationally cheap alternative method to search for molecular species in transmission spectra observed with JWST. We also searched for other molecules (CH4, NH3, SO2, N2O, H2S, PH3, O3, and C2H2) that were not detected, for which we provide the definition of their cross-correlation baselines for future searches of those molecules in other targets. We find that that the cross-correlation search of each molecule is more efficient over limited wavelength regions of the spectrum, where the signal for that molecule dominates over other molecules, than over broad wavelength ranges. In general, we also find that Gaussian normalization is the most efficient normalization mode for the generation of the molecular templates.
Değiştirilebilir platformlu rover araç
(BIDGE Publications, 2025) Aydın, Diyar Can; Aktoz, Halil; Özdalgıç, Berin; Solmaz, Arif
Bu çalışmada, çok amaçlı kullanım senaryolarına uyum sağlayabilen, modüler yapıda bir rover araç tasarımı ve geliştirilmesi ele alınmıştır. Geliştirilen sistem; arazi keşfi, çevresel veri toplama, mahsul analizi ve tarımsal ürünlerin toplanması gibi görevleri yerine getirebilecek şekilde yapılandırılmıştır. Tasarım süreci; robot kolları, görüntü işleme algoritmaları, sensör tabanlı veri analizi ve modüler mekanik-elektronik yapılar üzerine yapılan kapsamlı literatür taramalarıyla temellendirilmiştir. Sistem geliştirme süreci, elde edilen akademik ve deneysel veriler doğrultusunda özgünleştirilmiş; prototip üretimi sonrası gerçekleştirilen saha testleri ile sistem performansı değerlendirilmiştir. Bu doğrultuda, sadece mekanik yapı değil, elektronik devreler, yazılım altyapısı ve görev modülleri de geri bildirimler doğrultusunda sürekli olarak optimize edilmiştir. Kullanılan sensör ve modüller görev bazlı olarak çeşitlendirilmiştir: arazi analizi için gaz sensörleri, kamera, robot kol ve aydınlatma sistemleri; tarımsal uygulamalar için ise nem ve sıcaklık sensörleri ile otonom destekli robotik kollar entegre edilmiştir. Sonuç olarak, bu çalışma farklı operasyonel ihtiyaçlara cevap verebilen, yeniden yapılandırılabilir modüllere sahip, sahada etkin görev icra edebilen otonom bir robotik platform geliştirilmesini hedeflemektedir. Sistem, çok disiplinli bir yaklaşımla tasarlanmış olup, tarım teknolojileri ve keşif robotları gibi çeşitli alanlara katkı sağlayacak potansiyele sahiptir.
Girişimcilik ağı: Çok katmanlı dijital girişimcilik ağı platformu tasarımı ve uygulama modeli
(BIDGE Publications, 2025) Adsan, Murat; Tanrıver, Kürşat; Solmaz, Arif; Aydın, Yenal; Ak, Mine; Akkuş, Nihat; Başargan, Hakan
Bu çalışmada, dijital girişimcilik alanında çoklu kullanıcı tipine uygun olarak geliştirilen ve sürdürülebilir dijital ağ yapısıyla öne çıkan Girisimagi platformu tanıtılmaktadır. Girisimagi, yalnızca üniversite öğrencilerine değil; bireysel girişimcilere, kurumsal firmalara, yatırımcılara ve mentörlere hitap eden bütünleşik bir sistem olarak yapılandırılmıştır. 2024’te Türkiye girişimcilik ekosistemi 331 yatırım anlaşmasıyla 2,6 milyar USD işlem hacmine ulaşırken, internet penetrasyonu %86,5’e yükselmiş. Bu göstergeler, ölçeklenebilir dijital platformlara duyulan ihtiyacı net biçimde ortaya koymaktadır. Proje, kullanıcıların projelerini tanıtabilecekleri, sponsorluk ve mentörlük desteği alabilecekleri, firmaların ihtiyaç duyduğu girişim fikirleri için çağrıda bulunabilecekleri bir dijital ortam sunmaktadır. Girisimagi.org alan adı altında yapılandırılan ana platform, WHM/cPanel altyapısı üzerine kurulu olup; teknik moderasyon, içerik denetimi, kategoriye ayrılmış içerik yönetimi ve proje-firma eşleşme sistemleri gibi gelişmiş özelliklere sahiptir. Literatürdeki benzer platformlardan farklı olarak bu sistemde kullanıcı türlerine göre özelleştirilmiş iş akışları ve açık inovasyon destekli modüller entegre edilmiştir. Sunulan platform, girişimcilik kültürünü yaygınlaştırmak, üniversite-sanayi iş birliğini güçlendirmek ve projeleri somut çıktılarla desteklemek amacıyla geliştirilmiştir. Bildiride sırasıyla (i) modüler platform mimarisi, (ii) LAMP tabanlı teknik altyapı ve ölçeklenebilirlik çözümleri, (iii) pilot uygulamadan elde edilen kullanıcı deneyimi bulguları ve (iv) sürdürülebilirlik ile gelecek çalışma önerileri ele alınarak okuyucuya net bir yol haritası sunulmaktadır.
Enkaz altı mikro kurtarma kolu tasarımı (EMOK)
(BIDGE Publications, 2025) Demirtaş, Elif; Karabacak, Şeyma; Demir, Merve; Ak, Mine; Solmaz, Arif; Tanrıver, Kürşat
Bu çalışmada 3D tasarım, yapısal, parametrik analizleriyle birlikte ele alınan bir robot kol tasarımı sunulmaktadır. Robot kolun tasarım aşamasından sonra ileri çalışmalarda dar alanlara girebilen, çok yönlü sensörlerle donatılmış ve çevresel algılayıcılarla entegre edilerek enkaz altındaki bireylerin yerinin tespit edebilen bir prototip imalatın yapılması hedeflemektedir. Sistemin en önemli özelliklerinden biri işitme ve konuşma engelli bireylerle temel işaret dili aracılığıyla iletişim kurabilme yeteneğine sahip olabilmesidir. Böylece kurtarma ekiplerinden önce bireylerle temas kurarak bilgi aktarımı ve moral desteği sağlaması amaçlanmaktadır. Bunun için prototip öncesi büyük önem taşıyan tasarımda kapsamlı bir yapısal analiz ve parametrik yapılmıştır. Yapılan sonlu eleman analiz sonuçlarına göre maksimum gerilme 65,355 MPa çıkmıştır. Buna göre robot kol iskelet malzemesi 3D yazıcılarla basılabilen PLA malzemesinden değil 2,52 kat daha emniyetli olduğu hesaplanan alüminyum alaşım malzemenin kullanılması gerektiği görülmüştür.
Dinamik raf sistemli servis robotu
(BIDGE Publications, 2025) Çalışkan, Abdurrahim; Çebi, Mehmet Fatih; Çelik, Miraç Mehmet; Güneş, Rabia Yaren; Şahin, Kerem; Uluç, Hatice Ece; Ak, Mine; Solmaz, Arif; Tanrıver, Kürşat
Bu çalışmada, gelecekteki robotik servis sistemlerine katkı sağlaması hedeflenen bir servis modeli tasarlanmıştır. Robot, güvenlik kameralarından aldığı görüntü verilerini kullanarak masaların doluluk durumunu analiz etmekte ve siparişi aldığı masaya yönlenmektedir. Bu sürecin, yapay zekâ algoritmaları ile optimize edilerek en verimli yönlendirmeyi sağlaması hedeflenmektedir. Robotun en önemli yeniliklerinden biri, dinamik raf sistemidir. Servis öncesinde aktifleşen bu sistem, rafları masa hizasına getirerek müşterilerin ayağa kalkmadan tepsiye kolayca ulaşmasını sağlamaktadır. İlk raf boşaldığında, tavan kısmındaki boşluğa doğru yükselmekte; ardından ikinci raf, birinci rafın önceki konumuna yükselerek geçmekte ve servis edilmektedir. Diğer raflar için de aynı işlem sırasıyla gerçekleşmektedir. Servis tamamlandığında ise tüm raflar kendi başlangıç konumlarına dönmektedir. Bu mekanizma sayesinde servis sırasında oluşabilecek kazaların önlenmesi hedeflenmektedir. Ayrıca, robota entegre edilecek POS cihazı ile ödeme işlemlerinin yapılabilmesi mümkündür. Sistem tasarımı tamamlanmış; uygun profiller seçilmiş, yapısal analizler gerçekleştirilmiş ve tekerlek tork hesaplarına göre uygun servo motorlar belirlenmiştir. Sistemin yazılım kısmı geliştirme aşamasındadır.
Integrated use of finite element analysis and gaussian process regression in the structural analysis of AISI 316 stainless steel chimney systems
(Nature Portfolio, 2025) Tanrıver, Kürşat; Etyemez, Ayhan; Ay, Mustafa
This study aimed to conduct a comprehensive structural analysis and machine learning-assisted predictive modelling of a chimney system manufactured from 2 mm thick AISI 316 stainless steel with a diameter of Ø500 mm. The primary motivation of this work was to examine, in detail, the structural behavior of chimney modules under various force and pressure conditions using conventional methods, and to develop a reliable model capable of performing parametric predictions for new scenarios based on the acquired data. The scope of the study encompassed finite element analyses of both the entire chimney system and 3-meter-long intermediate modules, field tests, and the application of the Gaussian Process Regression (GPR) machine learning model. In the analysis of the entire chimney system under an applied force of 22,000 N, a maximum stress of 28 MPa and a safety factor of 8.39 were observed in the chimney clamps. The total deformation was found to be 0.58 mm, which is within acceptable limits. In the structural analysis of the intermediate chimney modules under a force of 1000 N and an internal pressure of 5 MPa, a maximum stress of 11,984 MPa, a safety factor of 1.71, and a total deformation of 0.46 mm were determined, all of which are consistent with the literature. The accuracy of these analyses was validated through pressure and leakage tests conducted in accordance with the EN 1859 standard. The developed GPR machine learning model demonstrated exceptionally high accuracy (R² > 0.999) in predicting Von Mises stress values, providing reliable forecasts with an error rate of less than 3% when compared to ANSYS simulation outputs. However, in predicting total deformation values, error rates exceeded 70%, indicating that the model was less sensitive in low-amplitude deformation cases. These findings suggest that the GPR model can generate reliable predictions for Von Mises stress a more critical parameter than total deformation in chimney design. By integrating conventional structural analysis methods with advanced machine learning techniques, this study demonstrates the potential of predictive modeling as an efficient and reliable tool in engineering design processes, making a significant contribution to the field’s body of knowledge.
Dynamics of the forced thirring instanton with two forcing terms
(Springer Nature Link, 2025) Ak, Mine
We consider the dynamical behavior of fermionic instanton solutions of the Thirring Model with two forcing terms. In particular, the study focuses on the effect of the frequency and amplitude of the forcing terms on the behavior of fermionic instanton solutions. Numerical analysis based on the Smaller Alignment Index (SALI) method, Bifurcation Diagram and Permutation Entropy (PE) are used to show how and which dynamical behaviors occur in the system. Color maps and diagrams of the SALI time (St ) (the time St required for the SALI index to below a threshold value of 10−12) and PE of the system with respect to varying of frequency and amplitude values of the forcing terms are plotted comparatively to determine different dynamical behavior of the system. The study shows that fermionic instanton solutions exhibit a wide variety of dynamical behavior due to two forcing terms. Furthermore, it is emphasized that SALI time (St ) can be easily compared with bifurcation diagram and complexity method as a fast, efficient and precise method to investigate different degrees of chaos. In general, the instanton solutions with two forcing terms have been observed to exhibit different type of dynamical behavior. In this study, identical and symmetric coexisting attractors are demonstrated for these different types of behavior of the forced Thirring instanton.
Electronic circuit design and case studies in autonomous vehicles
(İksad Publishing House, 2025) Taş, Kerem Ali; Karabıyık, Mehmet Can; Tanrıver, Kürşat; Ak, Mine
Autonomous vehicle technologies are advancing rapidly due to the development of sophisticated electronic circuit systems, providing safe and efficient transportation solutions. This study examines electronic circuit designs and case studies used in autonomous vehicles. Fundamental components such as sensor fusion, microcontrollers, motor drivers, and power management are detailed, and their impact on autonomous driving is discussed. The study specifically analyzes environmental perception mechanisms by integrating LIDAR, ultrasonic, and infrared sensors, emphasizing their role in data processing and decision-making. Additionally, energy efficiency and performance optimization are explored through motor driver circuits and battery management systems. A case study involving an autonomous mobile robot demonstrates the design, circuit schematics, and system integration processes step by step. In conclusion, the success of autonomous vehicles largely depends on the precision and reliability of electronic circuits. The design principles and application examples presented in this study aim to contribute to the development of autonomous systems.
Impact of structural and CFD analysis on the cost of biogas-fueled gas engine exhaust pipes
(Ahmet ÇALIK, 2025) Kaymaz, Rabia; Ak, Mine; Tanrıver, Kürşat
In this study, the effects of exhaust pipe design used in biogas-fueled cogeneration systems on engineering performance and cost were investigated. First, the existing system was analyzed by field work, and then structural analysis was applied with CFD (Computational Fluid Dynamics). The exhaust pipe route, pipe diameter, and material thickness of the existing system were evaluated, and design improvements were suggested. It was determined that the shorter pipeline application with the changes made in the pipe route and layout reduced pressure losses. Despite the use of an exhaust pipe with a smaller diameter and made of thinner material in the proposed new design, compliance with the standards was ensured, and it was shown to be safe against wind loads with finite element analysis. Considering the calculated maximum wind load of 5.52 kN and the weight of the system, the maximum stress value was calculated as 108.691 MPa as a result of the Von Mises stress analysis applied to the exhaust pipe system in the finite element analysis. This value showed that the system was 1.56 times safer. In the deformation analysis, the maximum displacement value was measured as 0.13 mm, and this value is ideal. In the cost analysis, it was determined that the proposed new system provides a cost reduction of approximately 53% compared to the existing system. The results obtained emphasize the importance of engineering analysis in exhaust pipe design, and show the applicability of the approach to increase economic and environmental sustainability in industrial facilities.
CFD simulation analysis of a diesel generator exhaust muffler and performance-based optimization
(MDPI Publishing, 2025) Tanrıver, Kürşat
This study addresses a gap in the literature by simultaneously optimizing noise reduction and structural integrity in silencer design. A novel silencer model offering advan tages over conventional designs was developed. In the first phase, the initial optimization model was developed to minimize noise levels while considering environmental con straints. CFD analyses using NEC Acostix and Ex-Tuner calculated noise, temperature, and pressure, followed by validation in SimScale. The results demonstrated improved efficiency in reducing pressure loss and noise. A silencer with Ø 800 mm diameter, 3000 mm length, and Ø 355.6 mm exhaust connection was manufactured and tested, achieving 96 dB(A) at 1 m, with front and side measurements of 85.1 dB(A) and 74.4 dB(A), respectively. In the second phase, fastener durability in silencer support plates was optimized using tensile tests and FEA in Ansys R19.2. Parametric analyses for M4-M20 bolts were conducted, and regression analysis in Minitab (Minitab Statistical Software Version 21.1) showed 97.74% accuracy. An objective function was developed using curve fitting. The second optimization problem, incorporating design constraints, was solved using the interior point and Lagrange multipliers methods. This study provides a foundation for silencer design, ensuring both structural reliability and noise control. Future research will explore performance eco-friendly solutions across varying generator power levels.
Chimney installation and thermal-flow analysis in cogeneration systems
(Liberty Academic Publishers, 2025) Kaymaz, Rabia; Tanrıver, Kürşat; Ak, Mine
Bu çalışmada kojenerasyon sistemlerinde baca tasarımının enerji verimliliğine etkisi, çevresel sürdürülebilirlik, kullanılan malzemelerin performansı ve atık ısı geri kazanımı üzerinde detaylı bir çalışma sunulmuştur. Bu çalışmanın girdilerini oluşturmak için Türkiye’de önemli tesisleri barındıran İZAYDAŞ Biyogaz Entegre Elektrik Tesisinde atık yönetimi ve enerji geri kazanım süreçleri incelenmiş; bu süreçlerin daha sürdürülebilir ve verimli hale getirilmesine yönelik iyileştirme önerileri üzerinde odaklanılmıştır. Bu çalışmanın baca tasarımı aşamasında kesit hesaplarının yapılması ve optimizasyonu için Kesa Aladin programı kullanılmıştır. Statik hesaplarda ise Ansys programı yapısal analiz modülünden faydalanılmıştır. Böylelikle kojenerasyon sistemlerinde baca tasarımının iyileştirilmesiyle performans artışı sağlama potansiyelini ve verimlilik hedeflerine ulaşmadaki önemini vurgulayarak okuyuculara farkındalık kazandırılması amaçlanmıştır.
Modifying the refuse chute design to prevent infection spread: Engineering analysis and optimization
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Tanrıver, Kürşat; Ay, Mustafa
Considering the presence of airborne viruses, there is a need for renovation in refuse chutes, regarded as the first step in recycling household waste in buildings. This study aimed to revise the design of existing refuse chutes in light of the challenging experiences in waste management and public health during the coronavirus pandemic. This research primarily focused on the risks posed by various types of coronaviruses, such as the novel coronavirus (COVID-19) and acute respiratory syndrome (SARS and SARS-CoV), on stainless steel surfaces, with evidence of their survival under certain conditions. Refuse chutes are manufactured from stainless steel to resist the corrosive effects of waste. In examining the existing studies, it was observed that Casanova et al. and Chowdhury et al. found that the survival time of coronaviruses on stainless steel surfaces decreases as the temperature increases. Based on these studies, mechanical revisions have been made to the sanitation system of the refuse chute, thus increasing the washing water temperature. Additionally, through mechanical improvements, an automatic solution spray entry is provided before the intake doors are opened. Furthermore, to understand airflow and clarify flow parameters related to airborne infection transmission on residential floors in buildings equipped with refuse chutes, a computational fluid dynamics (CFD) analysis was conducted using a sample three-story refuse chute system. Based on the simulation results, a fan motor was integrated into the system to prevent pathogens from affecting users on other floors through airflow. Thus, airborne pathogens were periodically expelled into the atmosphere via a fan shortly before the intake doors were opened, supported by a PLC unit. Additionally, the intake doors were electronically interlocked, ensuring that all other intake doors remained locked while any single door was in use, thereby ensuring user safety. In a sample refuse chute, numerical calculations were performed to evaluate parameters such as the static suitability of the chute body thickness, static compliance of the chute support dimensions, chute diameter, chute thickness, fan airflow rate, ventilation duct diameter, minimum rock wool thickness for human contact safety, and the required number of spare containers. Additionally, a MATLAB code was developed to facilitate these numerical calculations, with values optimized using the Fmincon function. This allowed for the easy calculation of outputs for the new refuse chute systems and enabled the conversion of existing systems, evaluating compatibility with the new design for cost-effective upgrades. This refuse chute design aims to serve as a resource for readers in case of infection risks and contribute to the literature. The new refuse chute design supports the global circular economy (CE) model by enabling waste disinfection under pandemic conditions and ensuring cleaner source separation and collection for recycling. Due to its adaptability to different pandemic conditions including pathogens beyond coronavirus and potential new virus strains, the designed system is intended to contribute to the global health framework. In addition to the health measures described, this study calls for future research on how evolving global health conditions might impact refuse chute design.
Comparison of classical and heuristic methods for solving engineering design problems
(2024) Tanrıver, Kürşat; Ay, Mustafa
This paper presents an innovative application of the Ant Colony Optimization (ACO) algorithm to optimize engineering problems, specifically on welded beams and pressure vessels. A simulation study was conducted to evaluate the performance of the new ACO algorithm, comparing it with classical optimization techniques and other heuristic algorithms previously discussed in the literature. The algorithm was executed 20 times to obtain the most efficient results. The best performance outcome in the welded beam simulation was 1.7288, achieved after 540 iterations using 1000 ants, with a computation time of 6.27 seconds. Similarly, the best performance result in the pressure vessel simulation was 5947.1735, obtained after 735 iterations using 1000 ants and completed in 6.97 seconds. Compared to similar results reported in the literature, the new ACO algorithm demonstrated superior performance, offering an outstanding solution. Additionally, users can utilize this new ACO algorithm to quickly acquire information about welded beam design and prefabrication through simulation.
A deep feature driven expert system to estimate the postmortem interval from corneal opacity development
(Wiley, 2025) Cantürk, İsmail; Özyılmaz, Lale
Postmortem interval (PMI) estimation remains an unresolved challenge in forensic science, necessitating practical, reliable andmore accurate tools. This study aimed to develop a quantitative PMI estimation tool that effectively meets these needs. Focusingon the postmortem opacity development of the eye as a key marker for determining time since death, we propose an artificialintelligence-based clinical PMI prediction system utilising computer vision, deep learning and machine learning methods. TheAlexNet algorithm was utilised to extract deep features from the postmortem eye images. Extracted features were then processedby machine learning algorithms. For feature selection, Lasso and Relief techniques were employed, while SVM and KNN wereapplied for classifications. The results were validated using the leave- one-subject-out method. The system was tested across dif-ferent postmortem ranges, providing multi-label predictions. The performance was evaluated using various metrics. The deepfeatures exhibited effective performance in grading postmortem opacity development, achieving state-of-the-art results. Theaccuracy scores were 0.96 and 0.97 for 3-h intervals (i.e., 5-class) and 5-h intervals (i.e., 3-class) experiments, respectively. Theexperimental results indicate that the proposed system represents a promising tool for PMI estimation.
Optimization of properties of iron oxide nanoparticles synthized by solgel method
(ISRES Publishing, 2024) Sadullahoğlu, Gülten
In this study, the effects of pH value and capping agent on the morphology, pore structure and size of iron oxide nanoparticles were investigated systematically to obtain optimum properties. Iron oxide nanoparticles were synthized by sol-gel method. Polyvinyl alcohol (PVA) was used as capping agent by adding to the solution at 70 °C. After the drying process the powders were heat treated at 250 °C for 2 h under air atmosphere. Particle size of each sample was determined by using ZetaSizer instrument. X-ray diffraction (XRD) technique was employed for structural properties of iron oxide nanoparticles, FE-SEM (Field Emmision Scanning Electron Microscopy) was used to analyze the morphology of the powders. Magnetic properties of the nanoparticles were measured by VSM (Vibrating Sample Magnetometer) under air atmosphere at room temperature. Spesific surface area, porosity and pore size distribution of iron oxide nanoparticles were calculated by Brunauer-Emmett-Teller (BET) instrument. The results indicated that formation of the γ-Fe2O3 is sensitive to either the pH value of the solution or the capping agent, for the uncoated samples when pH value of the solution is adjusted to 2.5, α-Fe2O3 phase was detected as a single phase. When the solution was neutralized, γ-Fe2O3 was formed as the major phase in the microstructure, γ-Fe2O3 phase was formed as the major phase in the PVA coated samples leading to highest value of 50.33 emu/g measured in the sample of PVA8.5. For the PVA coated samples, specific surface area is in the range of 15.73 – 20.81 m2/g, the intervals of pore volume and average pore width are increased to 0.099 – 0.121 cm3/g and 23.19 – 23.07 nm respectively.
Comparison of different machining strategies and their effects on CNC vertical machining center
(2024) Öztürk, Ömer Faruk; Tanrıver, Kürşat; Ay, Mustafa
In today's world, interest in the aviation sector and developments within it continue to grow at an accelerated pace. With this increase, the demand for the production of components for unmanned aerial vehicles, passenger airplanes, or jet aircraft has risen correspondingly. However, due to the complex structure of aviation parts, the strategy employed during their processing is of significant importance. The distortion issue encountered in the machining of aviation parts, particularly in thin-walled components, leads to unwanted dimensional changes and significantly complicates the production of these parts. This study aims to investigate the effects of different machining techniques on the widely used Al 7075 T7351 aluminum alloy in the aviation sector and to contribute the experimental results to both readers and the literature. In the experiments, samples of Al 7075 T7351 aluminum alloy with thicknesses of 1.00 mm, 1.20 mm, and 1.50 mm were processed using various machining strategies. According to the experimental results, the effect of tool strategy on thickness was observed to vary between a minimum of 0.67% and a maximum of 7.78%. Taking the average of the minimum and maximum values of the three samples, the average effect of the tool path strategy on surface roughness was found to be 55.46%, and its effect on parallelism varied between 37.50% and 112.50%. Furthermore, it is believed that the methods presented in this study will contribute to solving similar problems in other industries, in addition to the aviation sector, in areas such as material selection, determination of processing parameters, and compliance of three-dimensional coordinate measurements (CMM) with standards.
Efficient path planning for drilling processes: The hybrid approach of a genetic algorithm and ant colony optimisation
(University of Zagreb, 2024) Tanrıver, Kürşat; Ay, Mustafa
Efficiency in machining time during drilling is affected by various factors, with one key element being the machining path. Solving the machining path closely resembles the Travelling Salesman Problem (TSP). In this article, drilling on a sample model is simulated using a hybrid algorithm that is developed based on TSP. This hybrid algorithm (GACO) is created by combining the strengths of the Genetic Algorithm (GA) and Ant Colony Optimisation (ACO). Codes written to verify the stability of the algorithms were executed 10 times, and results were recorded indicating the shortest path and machining sequence. Accordingly, the performance of the hybrid GACO algorithm was observed to be 3.16% better than the ACO algorithm in terms of both total path length and total machining time. In terms of computation time, the ACO algorithm lagged behind the GACO algorithm by 6.46%. Furthermore, the hybrid GACO algorithm demonstrated enhanced performance in both total path length and total machining time when compared with the literature. This study aims to contribute to the industry, professionals, and practitioners in this field by providing cost and time savings.

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