Tezler

Bu topluluk için Kalıcı Uri

http://hdl.handle.net/11527/3

Gözat

1,5kW IE4 verim sınıfı asenkron motor ve şebeke kalkışlı daimi mıknatıslı senkron motor tasarımları ve performans karşılaştırması

(Lisansüstü Eğitim Enstitüsü, 2022-02-11) Gedik, Hakan ; Ergene, Lale ; 504071007 ; Elektrik Mühendisliği

Dünyada enerji kaynakları hızla tükenirken ve sera gazı salınımları hızla artarken karar vericiler ve politika uygulayıcılar enerji verimliliği ile ilgili ciddi çalışmalar yapmaya başlamıştır. İklim sözleşmeleri ve bunun uygulama adımları olan regülasyonlar sayesinde enerji tüketen ürün ve cihazların verim değerleri ile ilgili zorunluluklar yürürlüğü girmiştir. Elektrik motorları, enerji tüketimindeki ciddi payı sayesinde regülasyonların radarına giren ilk ürünlerden biri olmuştur. 1990'lı yılların sonunda CEMEP tarafından verimli elektrik motorları için bir gruplama yapılmış, motorlar devir sayısı ve güçlerine göre belli verim değerleri ile artan verim sınıfına göre sırasıyla EFF3, EFF2 ve EFF1 olarak gruplanmıştır. Verimlilik konusunda yapılan çalışmalar neticesinde öncelikle 2008 yılında IEC 60034-30 standardı yayımlanarak verimli motor kapsamı, tanımı ve değerleri uluslararası geçerliliği olan bir şekle dönmüştür. En düşük verim sınıfı IE1 olmak üzere IE2, IE3 ve IE4 şeklinde tariflenen motorlar, 2009 yılında Avrupa Birliği'nde yayınlanan 640/2009 regülasyonu ile zorunlu bir üretim ve kullanıma tabi olmuştur. Öncelikle IE2 ve IE3 motor kullanımını zorunlu hale getiren regülasyon Temmuz 2021 itibari ile çıtayı yükselterek 0,75kW altı motorlar haricinde IE2 motorları yasaklamış, ilave olarak 2023 yılında IE4 verim sınıfını büyük güçlü motorlarda zorunlu hale getirmiştir. Regülasyonlar ile verim çıtasının daimi yükseltildiği motor sektöründe pazara ciddi oranda hakim olan asenkron motorlarda verimi arttırıcı faaliyetler hız kazanmış, bununla beraber bu motorlara alternatif olabilecek diğer motor türlerinin endüstride yer bulabilmesi adına çalışmalar başlamıştır. Elektrik motorlarının kullanım alanları arasında ciddi orana sahip olan pompa, fan, kompresör gibi uygulamalar değişken devirli uygulamalar olmalarına rağmen inverter kullanımı çok düşük olduğu için asenkron motorlara alternatif olabilecek dikkat çekici motorlardan biri şebeke kalkışlı daimi mıknatıslı motorlar olmuştur. Bu tez çalışmasında IE3 verim sınıfı 1,5kW 4p 90 gövde bir asenkron motor referans alınarak öncelikle klasik yöntemler ile IE4 verim sınıfı seviyesine çıkarılmıştır. Bu çalışmanın yanında IE3 asenkron motorun statoru sabit tutularak yeni bir rotor tasarımı sayesinde IE4 verim sınıflı şebeke kalkışlı daimi mıknatıslı senkron motor tasarlanmış ve doğrulanmıştır. Motor gövdesi, kapaklar ve diğer mekanik parçalar IE3 verim sınıfı motora ait olup tez çalışması kapsamında tasarlanan parçalar değildir. Elektrik ve elektromanyetik tasarımlar Flux 2D ve SPEED manyetik analiz programları ile gerçekleştirilmiştir. Öncelikle var olan IE3 verim sınıfı asenkron motor modellenerek diğer çalışmalar için referans oluşturması sağlanmıştır. Klasik yöntemlerden paket boyunun arttırılması, verimli sac kullanımı, verimli rulman kullanımı gibi yöntemlerle IE4 asenkron motor tasarımı yapılmıştır. İlave olarak yeni bir rotor tasarımı ile hem mıknatıs hem de alüminyum çubuklardan oluşan hibrit bir yapı ile şebeke kalkışlı senkron motorun tasarımı tamamlanmıştır. Yapılan tasarımlar prototiplenerek IEC 60034-2-1 standardına göre sırasıyla ısınma testi, performans testi ve boşta test adımlarına tabi tutularak test edilmiştir. Yapılan testler neticesinde her iki motorun da IE4 verim değerini yakaladığı tespit edilmiştir. Başarılı tasarım ve doğrulama çalışmalarından sonra her iki motor tipinin performans değerleri karşılaştırılarak uygulama alanına göre kullanıcılar tarafından değerlendirilebilmeye sunulmuştur.
19. yüzyıl tarihi demiryolu binalarında yapısal malzeme ve yapım teknolojilerinin deprem performansına etkisi

(Lisansüstü Eğitim Enstitüsü, 2024-06-25) Küçükayan, Sena Merve ; Çelik, Oğuz Cem ; 502211513 ; Çevre Kontrolü ve Yapı Teknolojisi

Bu tez çalışması, Osmanlı Devleti döneminde inşa edilen tarihi demiryolu hatları ve demiryolu yapılarını, yapısal ve mimari özellikleri ile birlikte deprem performanslarını içermektedir. İlk olarak, Osmanlı'da önemli demiryolu ağları olan İzmir-Aydın, Rumeli, Anadolu, Bağdat ve Hicaz demiryolu hatları ve güzergâhları detaylıca araştırılmış ve bu güzergâhların oluşmasında göz önünde bulundurulan durumlar incelenmiştir. Demiryolu duraklarının konumu belirlenirken, stratejik önemleri, doğal kaynaklar ile ilişkisi, ekonomik katkısı, ticaretin gelişebilmesi ve şehir merkezlerine olan yakınlığı gibi durumlar etkili olmuştur. İncelenen tarihi demiryolu projeleri, devletin modernleşme ve kalkınma sürecinin bir parçası olarak başlasa da zamanla ekomomik durumlardan ötürü yabancı yatırım ve alanında uzman mimar ve mühendislerin katksısı ile gelişmiştir. İnşa edilen demiryolu hatları ile birlikte Osmanlı Devleti'nin iç ve dış ticareti gelişmiş, zamanla hatların genişlemesi ile birlikte farklı bölgeler birbirlerine bağlanmıştır. Yabancı şirketlerin katkısı ve kullanılan yapım teknikleri de demiryolu hatlarının gelişmesi sürecinde önemli bir rol oynamıştır. Demiryolu yapılarında sıkça görülen, ancak günümüzde yaygın olmayan perçin teknolojisi ile birlikte çelik yapılar strüktürel açıdan incelenmiştir. Yığma, ahşap ve çelik yapı malzemeleri ile taşıyıcı ve çatı sistemleri hakında da detaylı bir şekilde inceleme yapılmıştır. Son olarak, tarihi demiryolu garlarının ve istasyonlarının zaman içerisinde yaşanan depremler sonrasında performansları analiz edilmiş ve meydana gelen hasar boyutları ele alınmıştır. Bu kapsamda, demiryolu yapılarının ciddi oranda etkilendiği iki deprem olan 10 Temmuz 1894 İstanbul depremi (~M 7.0) ve 6 Şubat 2023 Kahramanmaraş depremleri (Mw 7.9 ve 7.8) ele alınarak farklı bölgelerde yer alan istasyon yapılarının nasıl etkilendiği detaylandırılmıştır. Yapılan analizler ile birlikte, tarihi demiryolu yapılarının gelecek kuşaklara güvenle aktarılabilmesi için kapsamlı olarak yapısal bakımdan incelenmesi gereği ortaya çıkmıştır. Demiryolu yapılarının incelenmesi, bir yandan ait olduğu dönemin teknolojisini ve mühendislik başarısı ile birlikte yapıların nasıl inşa edildiğini, kullanılan malzemeleri, uygulanan tekniklerini ve dönemin koşullarını göstermektedir. Sonuç olarak bu çalışma, demiryolu yapılarınının detaylı bir şekilde incelenerek yapısal sistemlerinin anlaşılmasını ve tarihi demiryolu yapılarının korunması ve güçlendirilmesi için önemli kararların alınmasına yönelik öneriler sunmaya yöneliktir. Tarihi demiryolu yapılarının yapısal özelliklerini ve depremlere dayanıklılığını anlamak, tarihi mirasın gelecek nesillere aktarılabilmesi için önemli bir süreçtir. Çalışmanın, tarihi demiryolu yapılarının yapısal ve mimari değerini anlamak ve korunmasını isteyen uzmanlar, tarihçiler, mimarlar ve mühendisler için yol gösteren bir kaynak olması hedeflenmektedir.
3D modeling in archaeology Reşitköy Dam excavations

(Graduate School, 2025-01-31) Tok, Kalin ; Özcan, Orkan ; 603211009 ; Geoanthropology

3D (3 Dimensional) modeling has profoundly transformed archaeology by introducing innovative methods for documenting, analyzing, and presenting data. This technology surpasses traditional techniques that rely on sketches, photographs, and physical records by offering dynamic, precise, and interactive means of preserving archaeological sites and artifacts. The integration of 3D technologies addresses the limitations of conventional practices, enriching the scope and depth of archaeological studies and fundamentally enhancing the discipline's ability to safeguard cultural heritage. The primary advantage of 3D modeling is its ability to create detailed digital replicas of archaeological sites. These models capture intricate features with remarkable precision, ensuring that valuable information is preserved and accessible without damaging fragile originals. Furthermore, digital reconstructions enable archaeologists to visualize and analyze historical structures in their original context. This capacity for digital preservation is particularly critical in the face of environmental degradation, conflicts, or other threats to physical resources heritage such as, illegal excavations, environmental factors, or urbanization. 3D modeling provides numerous benefits that make it essential in modern archaeology. It greatly improves the capability to preserve and share archaeological data worldwide, encouraging collaboration among researchers and enhancing public engagement. Techniques like photogrammetry and laser scanning capture fine details often missed by traditional methods, allowing for more accurate measurements and analyses. In educational settings, 3D models offer immersive experiences, including virtual tours of ancient sites, which enrich learning and create a deeper connection to history. These models also play an essential role in restoration efforts, serving as templates for accurately reconstructing damaged or incomplete artifacts and structures. Moreover, employing 3D modeling can shorten the time and reduce costs related to fieldwork and analysis, boosting efficiency without sacrificing accuracy. In comparison to traditional methods, 3D modeling represents a significant advancement. Conventional documentation often lacks the spatial and textural detail provided by digital technologies and is prone to inaccuracies and deterioration over time. Physical replicas, while valuable, are expensive and frequently fail to replicate fine details necessary for comprehensive analysis. By contrast, 3D models ensure exhaustive documentation, integrating spatial, material, and geospatial data into cohesive digital formats that are easily analyzed, stored, and shared. Overall, 3D modeling represents a technological advancement in archaeology, addressing the limitations of traditional documentation while enhancing preservation, research, and public access. Its integration into archaeological practice ensures that cultural heritage is meticulously documented and widely accessible, providing an invaluable resource for future generations and the global community.
3D-printed actuator-based beam-steering approach for improved physical layer security in visible light communication

(Graduate School, 2022-09-05) Erdem, Mehmet Can ; Ferhanoğlu, Onur ; 504201223 ; Electronics Engineering

In this thesis, the design, manufacturing and implementation of a 3D-printed lens scanner-based beam-steering are presented for use in visible light communication (VLC) applications. The scanner, measuring 5 x 5 cm, is designed for low-cost 3D printing with fused deposition modeling using polylactic acid (PLA). The scanning is facilitated through electromagnetic actuation of the lens frame, carrying a conventional 25 mm lens in two nearly orthogonal directions. The serpentine spring that connects the lens frame to the external frame is tailored to offer similar spring constants in the directions of actuation, and minimal (< 1.5 mm) sag due to the mass of the lens. The manufactured actuator was integrated on a miniaturized VLC test-bed (70 cm x 40 cm x 40 cm). Using the test-bed, the applied voltage vs. beam displacement behavior of the actuator was characterized in the lateral plane, and beam-steering on a moving target was demonstrated with face-recognition feedback. The proposed scheme was targeted to offer an improved security measure in VLC through tracking the legitimate receiver (i.e. via face recognition) and using the feedback to steer the focused light onto the targeted device. The joint use of focusing and steering features allows for the legitimate receiver to roam within the room while enjoying the improved secrecy due to focused light. The secrecy capacity for the demonstrated approach was also calculated, which compares favorably to a number of jamming, spatial modulation and beam-forming counterparts. The presented actuator can be used with larger room dimensions, yet up-scaling to larger illumination units will require the use of a lens having a smaller focus to achieve a larger total steering angle. This thesis is composed of five different chapters. The concepts of visible light communication and light fidelity (Li-Fi) are introduced with a thorough literature review in the first chapter, while the techniques used in the thesis are also defined and presented. In the second chapter, the design of the actuator is described through definite computer-aided design (CAD) models and finite element analysis (FEA) simulations, while the experimental setup is also presented. Meanwhile, the demonstrations and the measurement results from the beam-steering operation of the actuator are presented in the third chapter. Then, the discussion section, based on the secrecy improvement through the use of the actuator and the up-scaling of the actuator to real-world dimensions, is presented in the fourth chapter. Finally, the fifth chapter presents the conclusions and further future work based on the actuator. Also, the details regarding the experiments conducted in Chapter 3, some of the designs of the actuator that were changed in order to obtain the final prototype and some discussion based on the mechanical stress on the actuator caused by the weight of the lens are presented in the Appendix section.
72 oluklu, 2 kutuplu asenkron motorlarda farklı sayıda rotor oluklarının uzay harmonikleri üzerine olan etkilerinin tespti

(Lisansüstü Eğitim Enstitüsü, 2023) Onur, Güven ; Kocabaş, Derya Ahmet ; 810625 ; Elektrik Mühendisliği Bilim Dalı

Günümüz dünyasında artan nüfusun en önemli getirisi enerjiye olan ihtiyacın giderek artmasıdır. Fosil yakıtların gerek doğaya zararlı etkileri gerekse dünya üzerinde sınırlı miktarda bulunması, yenilenebilir enerji sistemlerinin giderek daha popüler olmasına sebep olurken, enerji dönüşümü yapılmasını sağlayan araçların da verim ve performans artışını zorunlu hale getirmiştir. Elektrik enerjisi ve mekanik enerji arasındaki dönüşümde şüphesiz en önemli rolü üstlenen elektrik makineleri arasında; üretim kolaylığı, bakım gerektirmemesi, düşük maliyeti sebebiyle asenkron makineleri yaygın olarak kullanılan bir elektrik makinesi haline getirmiştir. Asenkron makineler durağan kısmı stator ve hareketli kısmı rotor olmak üzere iki temel bileşenden oluşur. Statorda oluşturulan manyetik alan, stator ve rotor arasındaki hava aralığından rotora geçerek, rotor manyetik devresi üzerinden tekrar statora geri dönerek devreyi tamamlar. İdealde, hava aralığında bulunan manyetik akı yoğunluğunun saf sinüs biçimli olması istenir ancak motor sargıları saf sinüs biçimli bir kaynak ile beslense dahi oluşan manyetik alan saf sinüs biçimli olamaz. Bunun sebebi makine içerisindeki oluk yapısı ve yerleştirilen sargıların sinüs biçimli olmamasıdır. Hava aralığında oluşan manyeto motor kuvvet sinüs biçimini andıran basamaklı periyodik bir dalga olarak şekillenir. Oluşan bu basamaklı dalga şekli Fourier Dönüşümü ile açıldığında harmonik bileşenleri elde edilecektir. Elde edilen bu harmonik bileşenler kaynak geriliminden bağımsız olarak motor geometrisi sebebiyle ortaya çıktığından uzay harmonikleri olarak isimlendirilirler. Uzay harmoniklerinin varlığı makinede birçok istenmeyen etkilere sahiptir. Bu etkiler istenmeyen titreşim ve akustik gürültüler olarak özetlenebilir. Titreşim ve akustik gürültülerin varlığı ile hem makinenin çıkış performansını hem de verimini azaltacaktır. Sadece kararlı çalışma durumunda değil aynı zamanda kalkış ve frenleme durumlarında da meydana gelebilecek bu zararlı etkileri azaltmak adına birçok yöntem mevcuttur. Bu yöntemlerden en yaygın olarak kullanılanlar, sadece çift tabakalı sargılara uygulanabilecek olan kirişleme yöntemi, rotor iletkenlerine uygulanan kaykı örnek verilebilir. Bu yöntemlerden bir tanesi de motorun tasarım başlangıcında belirlenen uygun stator/rotor oluk kombinasyonu seçimidir. Bu çalışmada 72 stator oluklu, 2 kutuplu, 3 fazlı asenkron motor farklı oluk sayılarına sahip rotorlar ile analitik ve sonlu elemanlar yöntemi ile analiz edilmiştir. Sonlu elemanlar yöntemi kullanılarak elde edilen hava aralığı manyetik akı yoğunluğu dalga şekilleri Fourier Dönüşümü ile harmoniklerine açılmış rotor oluk sayılarının harmonik bileşenlere olan etkileri karşılaştırma yapılarak tespit edilmiştir. Buna ek olarak, tasarlanan her motorun verimi, moment dalgalılığı gibi performans kriterleri karşılaştırılarak bahsedilen stator yapısına ve seçilen motor kriterlerine göre en uygun rotor oluk sayıları tespit edilerek, literatürde stator/rotor oluk sayısı kombinasyonu seçiminde belirlenen kurallar ile ne kadar uygun olduğu karşılaştırılmıştır. Yapılan karşılaştırma sonucunda 3 fazlı, 2 kutuplu ve 72 stator oluğuna sahip bir asenkron motor için 58, 60, 78, 86, 94, 96, 98 rotor oluklu tasarımların diğer tasarımlara göre moment dalgalılıkları ve geçici hal çalışma durumlarında üretilen elektromanyetik momentin tepe değerleri daha düşüktür. Seçilen bu 5 farklı rotor oluk tasarımları arasında 94 rotor oluğu en düşük moment dalgılılığına sahiptir ve en uygun rotor oluk sayısı olarak belirlenmiştir.
8 Gbps LVDS transmitter design in 22 nm FD-SOI for high speed chip-to-chip communication interfaces

(Graduate School, 2024-06-04) Kurt, Alper ; Tekin, Ahmet ; 504211235 ; Electronics Engineering

In recent years, tremendous advancements in the processing speed of microprocessors, motherboards, optical transmission links, and routers have expanded the off-chip data rates. The increasing demand for data bandwidth across electronic systems has led to significant innovations in wireline input/output (I/O) drivers. Various standards have been created by many institutions to manage the difficulties of high-speed wireline data transmission. The aggressive technology scaling not only increased the interest in I/O speed but also it additionally contributed noticeably to the enhancement in data rate and power efficiency of the wireline links. Even though the I/O data rates and data processing power have been improved by the technology scaling, the bandwidth of the copper links has not been scaled in the same manner. Therefore, the requirement for advanced equalization techniques has emerged in recent years to eliminate the corrosive effect of the channel such as inter-symbol interference (ISI) emerging at high frequencies. LVDS standard have been very popular among other communication standards due to its low power consumption, high noise immunity, high speed point-to-point data transmission, and good electromagnetic interference performance. LVDS is configured as a switched-polarity current generator. Optimum line impedance matching is achieved due to differential termination resistor at the receiver end of the system. Since LVDS transmits differential data, crosstalk and robustness of the link to common mode noise is extremely enhanced. The received digital data is represented with analog voltage swing at the output of the LVDS, which improves the data rate and also reduces power consumption. The channel is the physical medium that signal passes through from transmitter side to receiver side. Transmitted signal travels through various traces before reaching its destination. With the increase in frequency, line attenuation of this channel increases due to dielectric loss and skin effect. The channel behaves like a low pass filter which deteriorates the signal quality. first pre-cursor and post-cursor samples become very large due to Pulse dispersion from low-pass filtering, which makes detecting the bits that are transmitted in a sequence. This effects also generates intersymbol interference (ISI), which is interference of the transmitted symbol with the subsequent symbol due to distortion at high data rate. As a result, to overcome the corrosive effects of the channel equalization is needed. In general, pre-emphasis technique is used in transmitter side for channel equalization. In this thesis, 8 Gbps Low-Voltage Differential Signaling (LVDS) transmitter having controllable pre-emphasis and inductive peaking is designed for high speed chip-to-chip communication links. The transmitter system contains of pre-driver, core LVDS driver with Common Mode Feedback (CMFB) Amplifier, delay lines, auxiliary pre-driver and Pre-emphasis blocks. It has 1.225 V output common mode voltage which is adjustable between 0.98 V and 1.330. The output swing amplitude is between 230 mV and 350 mV. It consumes 20.248 mW power at 8 Gbps data rate which yields 2.531 pJ/bit energy efficiency. LVDS transmitter is implemented in 22 nm Fully Depleted Silicon on Insulator (FD-SOI) technology and the layout occupies 0.036 mm2 area including layout.
A control-theoretic approach for vision based quality aware autonomous navigation and mapping toward drone landing

(Graduate School, 2023-12-15) Sözer, Onuralp ; Kumbasar, Tufan ; 518172009 ; Mechatronics Engineering

This thesis presents a novel autonomous navigation approach that is capable of increasing map exploration and accuracy while minimizing the distance traveled for autonomous drone landings. For terrain mapping, a probabilistic sparse elevation map is proposed to represent measurement accuracy and enable the increasing of map quality by continuously applying new measurements with Bayes inference. For exploration, the Quality-Aware Best View (QABV) planner is proposed for autonomous navigation with a dual focus: map exploration and quality. Generated paths allow for visiting viewpoints that provide new measurements for exploring the proposed map and increasing its quality. To reduce the distance traveled, we handle the path-cost information in the framework of control theory to dynamically adjust the path cost of visiting a viewpoint. The proposed methods handle the QABV planner as a system to be controlled and regulate the information contribution of the generated paths. As a result, the path cost is increased to reduce the distance traveled or decreased to escape from a low-information area and avoid getting stuck. The usefulness of the proposed mapping and exploration approach is evaluated in detailed simulation studies including a real-world scenario for a packet delivery drone.
A data fusion application with linear kalman filter

(Graduate School, 2023-07-20) Geniş, Emre ; Kara Bayram, Duygu ; 504201022 ; Electrical Engineering

Bu tez, süreç ve ölçüm gürültüsü kovaryans matrisleri üzerinden lineer Kalman filtresinin kalibrasyonuna odaklanmaktadır. Dolayısıyla, sabit gözlem matrisi değeri 𝑯 = [𝟏; 𝟏] için yalnızca 𝑲, 𝑷, 𝑸, 𝑹 matrisleri ve kalibrasyon hedefi izlenmiştir. Bu tezin bir iyileştirmesi olarak, doğrusal Kalman filtresinin değişkenleri arasındaki etkileşimi daha ayrıntılı olarak ortaya çıkarmak için farklı 𝑯 değerlerinin etkisi incelenebilir. ✓ Ölçüm füzyonu ve durum vektörü füzyon yöntemleri arasındaki hesaplama maliyetini karşılaştırmak için, aynı tür yapay sinyaller her iki yöntemle birleştirilebilir. Örnekleme sıklığını artırmak, uygun 𝑸 ve 𝑹 değerlerini bulmak için otomatik kalibrasyon adımlarının sayısını azaltabilir. Bu sayede daha anlamlı hesaplamalı maliyet analizi yapılabilir. Ek olarak, MATLAB gibi programlar çok çekirdekli işlemcileri destekler. Artan çekirdek sayıları ile hesaplama gereksinimi ölçeklendirme tahminleri, veri birleştirme uygulamaları için kullanılan iş istasyonları ve süper bilgisayarlar için faydalı olabilir.
A dataset quality enhancement method for fine-grained just-in-time software defect prediction models

(Graduate School, 2024-07-01) Fidandan, İrem ; Buzluca, Feza ; 504211520 ; Computer Engineering

Recently developed fine-grained JIT-SDP models offer individual defect-inducingness predictions for each changed file in commits, unlike conventional JIT-SDP models that only predict defect-inducingness for commits. These models also cost-effectively reduce the risk of missing defect-inducing changes in the effort-aware JIT-SDP models by allowing developers to review only defect-inducing files in a commit. Building machine learning models is a data-dependent process, so the quality of the data is crucial. Low data quality negatively affects the predictive performance, interpretability, and scalability of machine learning models. The novelty in the thesis is a two-phased method to improve the quality characteristics of the dataset, including uniqueness, validity, accuracy and relevance, based on the experience and observations in software development for fine-grained JIT-SDP models. In the first phase, miscalculated features are sometimes deleted and sometimes corrected under the right conditions to ensure uniqueness, validity and accuracy. In the second phase, file changes in the commits that have little or no impact on future defects are excluded from the dataset to provide relevance. The proposed data quality improvement method is applied on Trautsch et al.'s dataset. In the data set, there are two different automatically assigned labels by the SZZ algorithm, which includes two basic steps: identifying the bug-fix purpose in full changes or some blocks in changes, and backtracking for each deleted line bug-fix purpose locations to find the changes that previously added them. The reason for the label differences lies in the methods used to identify bug-fix purpose changes. Predictive performance improvements in fine grained JIT-SDP models are then demonstrated when the proposed data quality improvement method is used for within-project and cross-project settings. In within-project setting, time-sensitive validation approach is used. Time-sensitive validation approach first creates three-month training instance groups and one-month test instance groups based on ascending time order, then trains separate models for each instance group and measures their prediction performances, and finally takes arithmetic average of the predictive performance results to get an overall result. For both within-project and cross-project settings, two types of datasets are used: datasets with and without proposed data quality improvements. Model training and evaluation steps are performed for each combination of the features including JIT metrics, static code metrics, PMD static analyzer metrics, and all of them, as well as Adhoc and ITS labels. In addition, CFS is also applied to the dataset with data quality improvements to investigate whether better or same prediction performance can be achieved with cleaner and more explainable models. Random Forest is used for training with SMOTE to balance dataset. Predictive performances are assessed by F1 score. In both within-project and cross-project settings, proposed data quality improvements yielded higher F1 scores than the baseline. Additionally, in cross-project setting, CFS always increased F1 scores. So, the proposed data quality improvement method may help build better fine-grained JIT-SDP models.
A multiscale approach to understand the effects of design parameters on the elastic behavior of 3D orthogonally woven composites

(Graduate School, 2024-11-04) Erkoç, Hilal ; Cebeci, Hülya ; 511201167 ; Aeronautical and Astronautical Engineering

This study aims to investigate the effect of various parameters on the elastic constants of three-dimensional (3D) orthogonally woven composites. Two-dimensional (2D) laminated composites exhibit high in-plane stiffness and strength; however, they are inadequate in applications subjected to out-of-plane loads, particularly in engine fan blades, aircraft fuselage structures, and wind turbine blades. With an innovative approach, 3D orthogonally woven composites effectively overcome the limitations of traditional 2D laminates. The usage of 3D orthogonally woven composites in these structures can be beneficial because 3D orthogonally woven composites are more resistant to out-of-plane loading than 2D laminates, due to their improved mechanical properties through the thickness. In addition to this, improved impact damage tolerance, higher delamination resistance, and reduced assembly and production costs through single-piece fabric production are advantages of 3D orthogonally woven composites. 3D orthogonally woven composites, in spite of their advantages, present certain challenges in application. One of the significant challenges is the complex nature of their manufacturing process, which demands specialized equipment and skilled personnel, leading to high production costs. Their complex structure can also complicate design, analysis, and simulation, requiring advanced computational models. Additionally, the complex architecture of these composites can present challenges in repair and maintenance procedures. 3D orthogonally woven structures consist of three interwoven sets of yarns arranged in orthogonal directions, where the warp and weft yarns remain straight while the binder yarns interlace them to create a multidimensional architecture. This complex architecture of 3D orthogonally woven composites plays an important role in determining the mechanical properties of the structure. Since differences in cross-section configurations, yarn arrangements, and fiber interactions significantly influence the load-carrying capacity, stiffness, and overall performance of the composite, an in-depth examination of the structural architecture is critical to optimizing the mechanical properties of the material. Several analytical studies have examined the effects of binder-to-weft and binder-to-warp ratios on the elastic properties of 3D orthogonally woven composites. These analyses employ representative volume elements (RVEs) to model the material behaviors. The binder-to-weft ratio characterizes the number of wefts of yarn a binder yarn encircles before reversing direction within the weft layer. Similarly, the binder-to-warp ratio represents the proportion of warp yarns per layer relative to the total number of warps encompassed by the RVE. However, a key limitation of these existing studies is based on the absence of a comparative analysis between analytical solutions and numerical simulations. Furthermore, the impact of RVE thickness on its elastic coefficients has not been thoroughly investigated. Here, the effects of changing thickness on the tensile response of the structure, as obtained through analytical solutions and numerical simulations, are presented. Elastic constants of 3D fiber-reinforced composites were estimated using a multi-scale homogenization technique based on meso-macro homogenization with good correlation. Numerical simulations were performed using ABAQUS software to analyze the behavior of the models. Through the optimization of the geometrical parameters of RVE, 3D orthogonally woven composites can be effectively implemented across a diverse range of engineering applications, especially in the aviation field.
A novel application of smart human centric lighting within the scope of energy efficiency and comfort assessment criteria

(Graduate School, 2024-07-30) Aliparast, Sevda ; Onaygil, Sermin ; 301172001 ; Energy Science and Technology

his study investigates the impact of human centric lighting (HCL) in an open plan office environment at Istanbul Technical University. The research involved sixty participants in the first phase and twenty-four in the second phase. The primary objective was to evaluate individualized lighting solutions that comply with Circadian Stimulus (CS) and Equivalent Melanopic Lux (EML) metrics. During the first phase, single Correlated Color Temperature (CCT) Light Emitting Diode (LED) sources were used, while the second phase explored the effects of different CCTs. Preliminary findings indicated potential for energy-efficient lighting modifications, with phase two concentrating on optimizing lighting quality and ensuring comfort criteria were met. In the design development phase, the lighting design process was thoroughly outlined, including summaries of circadian lighting metrics, simulation tools, energy considerations, and the research plan for the circadian lighting open plan office. The study ensured that the design aligned with recommended thresholds for EML and CS, maintaining horizontal and vertical illuminance levels consistent with recommendations from the Illuminating Engineering Society (IES) for visual tasks. Based on the simulation study, two different light distribution curve luminaires, Direct Suspended Linear (L1) and Direct and Indirect Suspended Linear (L2), were chosen for the study. Additionally, threshold suspended mounting heights of 1.5m (L1) and 2.3m (H3), and one Optimum Luminaire Height (OLH) of 1.8m (L2) above the finished floor were defined for the lighting luminaires. The experimental aspect involved assessing changes in lighting levels, psychological comfort, and performance at three main target heights (H1, H2, H3) for both lighting scenarios (L1 and L2). Participants were asked to complete visual cognitive performance tests, proofreading tasks, and the Karolinska Sleepiness Scale (KSS) test across six different lighting scenarios during the first phase to assess the impact of lighting level changes on psychological comfort, and four different lighting scenarios during the second study phase. The experiment aimed to explore human-centered lighting conditions alongside physiological comfort conditions, using questionnaires (Q1 and Q2) to gather data on error quantities (E) and time periods (t) as measurement scales, alongside participants' preferences based on their comfort criteria. Key results indicated that participants' performance and visual perception varied significantly across different lighting conditions and heights. The performance evaluation compared participants' results between heights H1, H2, and H3 for both L1 and L2 scenarios. Significant p-values indicated differences in performance and psychological comfort based on lighting levels, luminaire positions, and light distribution beams. Notably, the performance of participants was significantly influenced by age, with distinct differences observed between age groups 20-30, 30-40, and above 40. Phase one of the study evaluates the lighting mounting height for human-centered lighting. A single CCT of 3800K was investigated to determine its influence on visual comfort and visual test responses. The scenarios of L1H3 and L2H2 were identified as the most successful. The most favorable scenario was observed in L1H3, both in terms of performance and participant preferences. Conversely, the results for L2H2 indicate that while participant performance was successful, their preference was lower compared to L2H3. Although L2H3 was preferable, L2H2 was selected for evaluation in phase two with CCTs of 2700K, 3800K, and 6000K. Phase two of the study focused on varying CCTs to investigate their influence on visual comfort and circadian response. L1 was assessed with a constant CCT of 3800K, while L2 examined CCTs of 2700K, 3800K, and 6000K, set at operation rates of 75%, 60%, and 40% of the total luminaire output, respectively. These configurations aimed to meet the minimum CS requirement of 0.3. Regarding EML values, L1 had an EML set at 358, while L2 exhibited varied results: 275.5 for 2700K, 293 for 3800K, and 319 for 6000K. The findings from phase two indicated dissatisfaction with the lighting set at 6000K, while warmer CCTs of 2700K likely had a positive impact due to the lower dimming rate meeting CS and EML requirements, resulting in higher illuminance levels on the desk compared to 3800K and 6000K scenarios. Participants clearly preferred higher heights (H3) for appealing lighting conditions, confirming the strong correlation among subjective evaluations of lighting scenarios such as color pleasantness, lighting satisfaction, and lighting heights. Overall, the study suggests that individualized lighting systems tailored to open plan office environments can enhance worker satisfaction and meet HCL requirements. Using consistent survey questions across different lighting concepts can help identify specific factors influencing CCT preferences. In conclusion, integrating individualized lighting systems in open plan offices aligns with HCL requirements, ensuring worker satisfaction and potentially improving performance. The findings provide insights for enhancing office lighting environments, emphasizing the importance of considering both energy efficiency and occupant comfort.
A novel artificial intelligence based energy management system for microgrids

(Graduate School, 2023-06-19) Aksoy, Necati ; Genç, V. M. İstemihan ; 504182007 ; Electrical Engineering

In many countries, including our own, large amounts of electrical power are generated where the energy source is located, while it is consumed in areas with large industries and populations. This distance between energy generation and consumption leads to the transmission of energy, which results in the waste of energy as heat and increases energy costs. Microgrids have emerged as a solution to energy use by applying the principle of energy generation and consumption at the same place. Microgrids are small-scale electrical grids that can use distributed energy resources in conjunction with conventional grids. They can combine solar panels or plants, wind turbines, energy storage systems, generators, and the utility grid. This reduces energy loss during transmission, improves energy efficiency, and allows energy to be used efficiently. In addition, microgrids that operate in small settlements such as university campuses, military facilities, towns, or neighborhoods can work in "island mode" without a connection to the utility grid when needed. Many microgrids are currently operated using classical control methods and operate in certain size that has only been determined using optimization methods. This limits the efficiency that can be achieved during the operation of the microgrid and makes it difficult to follow new trends in energy storage technologies. The crux and significance of this thesis revolves around the notion that contemporary energy storage technologies can be utilized efficiently within the system, and that the existing artificial intelligence technology can serve as the foundation of the microgrid energy management system. The energy management system designed in this structure reduces energy waste, lowers costs, improves efficiency, and improves grid stability, while also producing effective solutions for energy demand by controlling the use of various sources together. Moreover, this energy management system contributes to reducing carbon emissions while allowing for the easy adaptation of new technologies. In light of all these advantages, this thesis presents an artificial intelligence-based energy management system design for microgrids. To further explain the concept of artificial intelligence, it encompasses machine learning algorithms as a subset, while machine learning includes deep learning algorithms and concepts. In this thesis, microgrid applications of various sizes and properties are examined, and a microgrid simulation model was created at commonly used sizes. This simulation model assumed a microgrid applied to a university campus, with a solar power plant and wind turbines serving as renewable energy sources. The energy management system being designed predicts the power that these sources will generate, using the up-to-date prediction algorithms within artificial intelligence. When designing, the focus is initially on predicting the power that solar and wind turbines will generate, using five years of meteorological data collected at five-minute intervals. The meteorological dataset, consisting of nine different data types, has undergone a series of data pre-processing. Missing data is filled in accordance with the characteristics of the dataset, and outliers are removed. The characteristics of this dataset were analyzed with different graphs and their suitability for training was examined. The labeled data consisting of the generation values at the same region and at the same time/minute intervals were added to the meteorological data set that was deemed suitable for training. Seven prediction models were developed using four prevalent machine learning methods and three novel algorithms based on the gradient boosting machine to predict the power generated by the solar power plant. These prediction models were trained separately using the training dataset made suitable for training. The results obtained from these seven prediction models were presented in both graphical and tabular formats. In addition to comparing which algorithm gave how successful results for this study, the computation costs were also compared. The designed energy management system must also predict the power generated from wind turbines. In this regard, prediction models were created using three different machine learning algorithms, and the results were obtained. These prediction models were compared using various performance metrics. This study conducted within this thesis, which achieved successful results, offers new approaches and unique results to the literature on the prediction of the power generation of renewable energy sources. An artificial intelligence-based energy management system should provide not only energy efficiency but also low energy costs and profitability for the user. The widespread use of dynamic electricity pricing should also be considered, which is determined based on the relationship between countrywide generation and consumption level. In this thesis, it is assumed that the microgrid simulation model developed is located in a country where dynamic pricing is applied. A five-year dataset was created from actual dynamic pricing data obtained from open-source platforms and analyzed. The dataset was examined, preprocessed, and made ready for the training of prediction models. Four deep learning algorithms with memory cell structures were selected for this study. Using these algorithms and the training dataset, price prediction models were developed, and the results were obtained. The learning performances, error values, and accuracies of the models were presented comparatively. These innovative prediction models were integrated into the designed energy management system. Knowing the power demand from a microgrid makes operational decisions more appropriate and robust. The load demand at which time of the day is an important parameter. Knowing the load demand in advance affects decisions regarding resource utilization. Considering this fact, the energy management system designed should also be able to predict load demand. To this end, load demand prediction models were developed using four deep learning methods with memory cell structures similar to price prediction. Actual load values obtained from open sources were scaled according to the simulation model of the microgrid created. Deep learning models were trained using the five-year load dataset, and the results were obtained. The results were presented comparatively using many performance metrics. As a result of this study, successful prediction models were developed and integrated into the designed energy management system. An artificial intelligence-based energy management system uses many prediction models described above. The theoretical and mathematical foundations of all machine learning and deep learning methods used are provided in the second chapter of this thesis. The energy management system described requires an additional controller to manage the microgrid in addition to human management. In this context, this thesis proposes another artificial intelligence-based controller. Data-driven control methods that have replaced classical control methods are popular topics nowadays. This thesis focuses on machine learning-based control methods of this type. In this context, reinforcement learning, which is one of the three main branches of machine learning, is investigated and its foundations are given. Reinforcement learning is the general name for methods based on the principle of controlling the system without the need for a mathematical model of the system. It is possible to separate this concept into methods based on table creation and methods using deep neural networks. In this thesis, controller agents using both types of methods are created. The agent, which will learn to control the system in reinforcement learning, needs to optimize itself. This optimization process is done through trial and error. For the agent to be able to take the best version through these trials, the system it will control, which is a microgrid environment model in this thesis, must have specific characteristics. Five different control agents were designed specifically for the energy management system, three of which were temporal-difference-based and two were deep reinforcement learning-based. Three environment models designed specifically for the microgrid are proposed in this thesis to enable these agents to train themselves. These environment models with unique reward strategies present a new approach to the literature. These environment models that use renewable energy sources, load demand, and dynamic prices for the training of agents have shown quite successful results in terms of energy management. The trained reinforcement learning agents have learned to manage the microgrid and offer considerable profitability to the user. The energy management system whose design steps are explained in this thesis uses many different artificial intelligence algorithms. These artificial intelligence models created, trained, and successful results achieved have been consolidated under a single graphical interface in this thesis. A unique graphical interface has been designed, and all prediction models and control agents have been integrated into this design. This interface design, which consists of seven pages in total, offers many variables and control actions related to the microgrid to the user. The user can see the powers that will be generated for the future, load demand, and the price. In addition, the user can apply many control actions to the microgrid through this interface. The user, who can also see many real-time parameters, can analyze the performance of prediction models and control agents through relevant pages. In conclusion, this thesis proposes an artificial intelligence-based energy management system that contains many current and innovative algorithms for microgrids and uses them uniquely. Artificial intelligence-based prediction models determine the decisions that an artificial intelligence-based control agent will make. This agent, which learns to select the correct control actions for the microgrid, presents the determined control action to the user through the designed interface. Additionally, the originally designed energy management system interface allows the user to see many parameters related to the microgrid in advance. This thesis proposes an energy management system that contributes to the literature with its original approach and can be used in real-world applications.
A prescriptive analytics approach towards critical ship machinery operations

(Graduate School, 2024-07-09) Yiğin, Barış ; Çelik, Metin ; 512182001 ; Maritime Transportation Engineering

Shipping handles more than 70% of global trade, is a pillar of the supply chain. To ensure safe, reliable, and environmentally responsible operatins, shipowners and operators must maintain their vessels' operational status at all times. Maintenance standards are essential for keeping both main and auxiliary machinery in optimal condition, thereby ensuring reliable and safe operations. These programs aim to maintain high performance with minimal impact on service, recognizing that the cost savings from effective maintenance program can prevent drawbacks due to machinery faults. The main objective of machine maintenance is to maximize availability by extending the service life of ship machineries and eliminating potential failures by early detection. This involves finding the finding the optimum maintenance strategy, as even minor failure can cause irreversible damage to the entire system if not promptly addressed. Given the complexity and interdependencies within marine systems, a proactive maintenance approach is crucial. Due to scarcity of labeled data and anomalous data, the research question of anomaly detection always attracted interest from academia and industry. Implementing anomaly detection technologies is a challenging task in marine systems due to their complexities and external factors. To address these challenges, this study proposes a prescriptive analytics framework that combines predictive analytics and decision support systems. This framework leverages data collected from various sensors installed on ship machinery to monitor performance and detect anomalies. One of the key innovations of this research it employes data augmentation techniques to generate realistic synthetic failure data, further enhancing the robustness of predictive models. The implementation of this prescriptive maintenance framework involves several steps. First, a comprehensive Failure Mode and Effect Analysis (FMEA) is conducted to identify potential failure modes, cause of failures and effects of failures. This analysis helps prioritization of the maintenance activities based on the criticality of different failure modes. Next, with the use of data augmentation technique called Generative Adversarial Network, synthetic data generation carried out to create faulty data information. This faulty data generation step enhance the training pool before the next step of anomaly detection process. In order to perform anomaly detection, six different classifiers namely, logistic regression, decision trees, random forest, K nearest neighbor, AdaBoost and XGBoost algorithms trained and validated using historical data and the generated synthetic data. Data set used in this study includes real time data collected from field on a diesel generator installed on a 310,000 DWT oil tanker. The field data collection took place over a six month period and it includes 33 features and 259,200 row data. Findings from the study yield promising results achieving 83.13% accuracy with use XGBoost algorithm and other ranging between 67% to 81%. Finally, a decision support system is integrated to provide actionable recommendations to ship operators, optimizing maintenance schedules and resource allocation. The results of the field study conducted as part of this research demonstrate the effectiveness of the proposed framework. Ships equipped with the prescriptive maintenance system has a significant potential for reduction in unexpected machinery failures, maintenance cost and autonomy of decision in case of anomalies. The system also offers improvement of overall operational efficiency and reliability of the ships. In conclusion, prescriptive maintenance the pinnacle of modern maintenance strategies, offering returns in terms of equipment reliability, safety and operational efficiency. Although installation of data acquisition systems may require initial investment, the benefits include reduced operational distruption and optimized maintenance budgets, making it a valuable approach for the maritime industry.
A psychological assessment model on the commercial maritime transport sector

(Graduate School, 2024-02-07) Ay, Cenk ; Beşikçi Bal, Elif ; 512202005 ; Maritime Transportation Engineering

The intricate tapestry of maritime psychology unfolds within the vast expanse of the seas, where over a million seafarers navigate under unique and demanding circumstances. This comprehensive exploration traverses the currents of evolving methodologies, challenges, and trends within the maritime psychology landscape. Anchored in a profound literature review, the study illuminates the tangible challenges faced by seafarers, from isolation and hierarchical structures to harsh conditions and prolonged separation. The maritime industry's sheer scale, combined with the distinct challenges of maritime life, underscores the profound implications for seafarers' mental well-being. In tandem with advancing technology, the study delves into the integration of machine learning and artificial intelligence in psychological assessments, sparking debates on diagnostic criteria, expert opinions, and ethical considerations. This application becomes particularly critical in an industry where traditional support systems are not only physically distant but also lack adequate medical facilities. The study unfolds through a bibliometric analysis, revealing a surge in research activity post-2010, with the highest publication rates in 2021 and 2022. The disruptive impact of the COVID-19 pandemic on seafarers' lives and mental health emerges as a significant catalyst for this increase. Moving beyond theoretical frameworks, the investigation encompasses four thematic clusters: "Research Design," "Spatial Design," "Data Collection Tools," and "Assessment Approaches." Observational studies take precedence, emphasizing the importance of understanding naturally occurring events and relationships in maritime contexts. Spatial design assumes critical importance, distinguishing studies in simulated environments from those in real-life maritime settings. The diverse array of data collection tools, from surveys and questionnaires to interviews and simulator data, reflects the multifaceted nature of maritime psychology. A paradigm shift is evident in assessment approaches, with "Statistical Analysis," "Machine Learning," and "Statement Analysis" taking center stage. The practical application centers around depression, a prominent psychiatric condition affecting seafarers. Leveraging the Beck Depression Inventory-II (BDI-II), a dataset of 746 records is obtained. Fuzzy logic and the Adaptive Neuro-Fuzzy Inference System (ANFIS) methodology, integrated with MATLAB Fuzzy Logic Toolbox, provide a seamless fusion for assessing depression severity. The clustering phase adopts both psychiatric and mathematical approaches, resulting in four distinct clustering groups. The pivotal outcome underscores the high accuracy achievable in predicting depression severity through a machine learning-based approach. The ANFIS model tailored for 2-factor clustering consistently outperforms its 5-factor clustering counterpart. The mathematical approach, specifically the 3-factor clustering, emerges as the more effective choice, highlighting the need for nuanced comprehension of psychiatric factors. The ANFIS model's performance details reveal minimal training RMSE, checking RMSE, and high R 2 scores, emphasizing its efficacy in providing nuanced insights into seafarers' mental well-being. The study navigates ethical considerations associated with data collection, advocating for the necessity of developing culturally sensitive measurement tools. Fuzzy logic, specifically ANFIS, emerges as a vital tool in deciphering complex datasets, promising to revolutionize mental health assessments in the maritime industry. While the study acknowledges limitations and the need for future research with more extensive samples, it contributes significantly to maritime psychology methodologies. In conclusion, this research voyage extends beyond theoretical frameworks, offering a practical tool for assessing and addressing the psychological challenges faced by seafarers. The success of the ANFIS model underscores its potential in fostering a healthier and safer maritime working environment. The study advocates for investments in machine learning-based systems, supported by self-sustaining servers, to enhance mental health services in the maritime sector, charting a course towards a more resilient and supportive maritime industry.
Adaptive backstepping control based emegency scheme for improving transient stability of power systems with renewable energy sources

(Graduate School, 2022) Motallebzadeh, Mohammad ; Genç, Veysel Murat İstemihan ; 738021 ; Electrical Engineering Programme

Due to the high demand for electrical energy, operation of modern power systems under stressed loading conditions have become more common. Renewable energy sources are incorporated into modern power systems (RES) that include solar photovoltaics (PV), wind turbines, etc., and complex loads that can considerably alter the electrical system's dynamics. The power system comprises synchronous generators and other energy sources linked together to generate electrical power. When a severe disturbance on the electrical grid occurs, the supply of electrical power may be endangered, and this must be ensured by selecting the corrective action. Transient instabilities occur after extreme contingencies, which are a significant threat to the dynamic security of systems. In this condition, the generator's rotor speeds and rotor angles change suddenly, which causes quick altering of electrical power, and therefore, maintaining system security in tricky conditions is one of the crucial tasks in electrical engineering. The corrective control is applied after disturbance. Emergency control schemes, such as transient stability excitation control (TSEC), can improve the system's stability. TSEC enhances transient stability by controlling excitation system of generators. This control is one of the conventional excitation control techniques that is compared with other methods in this thesis. Besides the emergency control schemes, Power System Stabilizer (PSS) can be a proper solution to decrease the oscillations in a power system in the transient period. A multi-machine power system consists of generators, turbines, transformers, transmission lines, and loads. To design the dynamics of a power system, the set of differential-algebraic equations (DAEs) should be solved with numerical methods. Differential equations include synchronous generator and turbine inter-area equations, and algebraic equations include stator algebraic equations and network equations. In this study, a tandem-compound single-reheat steam turbine controlled by a speed governor is considered, and it produces the related mechanical power for inputting to synchronous generators. Synchronous generators can be designed with different degrees of accuracy to make the related electrical power. In this study, the 3th order (flux-decay) model synchronous generator with the first-order excitation system (static exciter) is regarded. The network side consists of transmission lines, loads, and other components. This study replaces RES with the related synchronous generator with equal injected real and reactive power. In this thesis, Adaptive backstepping control (ABC) is proposed to improve the transient stability of power systems during emergency conditions. The thesis problem and the modeling studies are aligned with the studies of collaboration in the TUBITAK project no. 118E184 and in our published paper, whereas the development of ABC-based controller is the main contribution of this thesis.
Advanced scenario planning: New approaches for developing, evaluating, and selecting scenarios with applications

(Graduate School, 2024-10-24) Yanmaz, Özgür ; Asan, Umut ; 507162125 ; Industrial Engineering

Scenario planning is regarded as a useful tool for strategic planning, particularly in managing uncertainty through the examination of various future scenarios. Since present decisions influence a system's future performance, foreseeing new advancements and problems is critical to the success of future plans. Rather than attempting to accurately predict the future, scenario planning assists in negotiating unexpected and complex developments. Strategic planners can use scenarios to create a more sustainable system by considering how future events can unfold, addressing uncertainties, providing insights into the long-term consequences of decisions, and identifying potential opportunities and threats. A scenario represents a combination of potential developments, which are factors that influence systems in the future. These potential developments are characterized by specific factors and their corresponding levels, all of which have a qualitative nature. In practical scenario planning, the number of possible scenarios can reach into the millions. To formulate effective and actionable plans for the future, it is essential to focus on a manageable subset of scenarios. Therefore, the qualitative nature of the scenarios should first be quantified, and a selection process should be employed to identify a subset of scenarios for further analysis and strategic planning. The studies presented propose a comprehensive methodology for the evaluation and selection of scenarios. Multiple criteria were utilized to assess the scenarios through factor levels from different perspectives. To quantify the factor levels, they were first evaluated with respect to multiple criteria as well as the criteria interactions. Interactions between the criteria are crucial for real-world problems, as decision-making processes often involve these interactions. The Choquet integral was employed to aggregate the evaluations considering criteria interactions, providing numerical values for the factor levels. Since the Choquet integral is defined on measures, a mathematical model was developed to revise the expert assessments thereby obtaining criteria weights that satisfy measure rules. The factor levels were then weighted using a specific criterion (i.e., consistency) to calculate scenario values. After obtaining numerical values for the scenarios, a second mathematical model was developed to select a limited number of high-quality scenarios that best represent potential futures. A total of five criteria were used in the evaluation and selection process. Additionally, a practical application has been conducted to demonstrate the real-world usage of the selected scenarios. Following the selection of scenarios, projects or objectives to be prepared for alternative futures were identified. An actor analysis was performed to determine which stakeholders should collaborate in achieving these objectives within the relevant sectors. This approach ensures that both the evaluation and selection processes are comprehensive, incorporating realistic decision-making dynamics such as criteria interactions and that the selected scenarios can be practically applied in strategic planning.
Aerial link orchestration

(Graduate School, 2024-08-23) Bayram, Büşra ; Seçinti, Gökhan ; 504211548 ; Computer Engineering

Unmanned Aerial Vehicles (UAVs) have become indispensable tools due to their superior maneuverability and flexibility in a variety of activities such as mapping, infrastructure monitoring, and object tracking. Their applications are many, ranging from industrial and military surveillance to commercial delivery and other operations. Because of their hardware architectures, atmospheric factors such as wind and turbulence restrict the movement of UAVs, particularly drones. These conditions not only interfere with their responsiveness but also limit the operation of integrated systems and communication between the drone and the ground control station (GCS). It is critical in drone operations to maintain communication systems with the GCS and ensure the correct functioning of integrated systems, including managing the drone's movement parameters. These different uses, as well as the associated environmental circumstances, highlight the crucial requirement for UAVs to function dependably, as well as the importance of suitable regulations and adaptations. Drones and UAVs utilize a variety of communication methods in order to create a data link between the vehicle and GCS and sometimes between multiple aircraft (swarm technology). UAV communication systems can be utilized for data and image transmission from sensors and payloads to the control station, broadcasting telemetry systems, and command and control. Additionally, they provide bidirectional communication from air to ground and ground to air by allowing data and commands to be received at the ground station. The most common ways of drone communication employ radio-frequency (RF) signals in bands such as HF (high frequency) , satellites, cellulars, and other wireless infrastructures. However, radio technologies are the most widely used. RF datalinks can be analog or digital and have a longer range than Wi-Fi, although they are still limited to line-of-sight (LOS). The range of the UAV communications system is determined by the direction and size of the antenna, the strength of the transmitter, and the frequency, with lower frequencies allowing longer ranges but lower data rates. By addressing these technical difficulties, we develop new techniques to improve UAV communication quality and identify drone flight parameters that influence communication quality. Our goal is to create communication systems that are less impacted by these elements. Our research aims to overcome constraints in high-frequency transmission imposed by drone instability and antenna limitations. Our primary goal is to provide safe, continuous communication while greatly increasing the packet delivery ratio (PDR). We create resilient and adaptive UAV systems that can function well in a variety of dynamic operational scenarios by taking advantage of the inherent flexibility of Software Defined Radio (SDR) technology. This holistic approach encompasses proactive measures against signal interference, noise mitigation, and the management of flight-induced vibrations, harnessing SDR's configurability to meet the evolving demands of modern UAV operations effectively. Our approach involves: * Addressing Drone Flight Patterns and Aerial Conditions: We classify different aerial conditions affecting UAVs. *Enhancing the Modulation and Coding Scheme (MCS): We improve the MCS table to be aware of aerial and flight conditions. *Exhaustive Real-World Experimentation: Utilizing a "train on day, test on the next day" methodology on a real test bed. To increase drone PDR, we use Digital Twin architecture to detect influential parameters. Using the "train one day, test another day" method, we include real-world test flight log data from drones and SDR communication attributes into our digital twin model. This allows us to discover the best parameter values for getting a high PDR, which we then feed back into our system. Based on these results, we update the existing static MCS table to reflect the effect of the identified drone flying factors on communication performance. Our results validated methodologies have demonstrated significant improvements in PDR, achieving an average increase of 27\% across multiple drone platforms and environmental scenarios. These findings underscore the effectiveness of our approach in optimizing communication performance under real-world conditions. Furthermore, our research provides valuable insights into the intricate interactions between UAV flight dynamics and communication efficacy, guiding future advancements in UAV technology. In summary, our research underscores the critical importance of maintaining robust communication networks in dynamic UAV environments. By proposing and validating innovative methodologies, we lay the groundwork for enhanced UAV communication resilience and efficiency. Future endeavors will build upon these foundations, expanding system capabilities across broader operational scenarios and pushing the boundaries of UAV communication technology to new heights.
Aerial package delivery via smart parachute-payload system

(Graduate School, 2024-07-12) Alnıpak, Sinan ; Altuğ, Erdinç ; 503201610 ; System Dynamics and Control

Aerial robots are being used in many areas, they are employed by civilian and military industries. One of the growing sectors is aerial package delivery. Commonly cargos are brought to customers with trucks or cars. Compared to aerial delivery this method is inefficient. The time customers get their cargos can be shortened by making use of drones and this process also requires less manpower due to automatization of these devices. This is also better for nature because unlike most land vehicles, drones do not use fossil fuel as an energy source. Currently, some large companies in the e-commerce business are producing their own unmanned aerial vehicles and developing methods for this type of delivery. A company is already delivering healthcare supply via drone delivery. However, most of them carry one parcel with a single drone at a time. In addition, drones, especially quadcopters, consume vast amounts of energy when travelling through the air. This process can further be improved by delivering multiple cargos at a time, and energy consumption can be reduced. In this thesis, a package delivery system which can distribute multiple parcels at a time is discussed. The system was designed on computer aided design software, and mechanical parts were manufactured via 3D printer. After manufacturing physical system constants were determined and system was mathematically modelled. Because of nonlinearities in the model, it was linearized using Taylor Series expansion. After the modeling process three different controller structures were developed for the system. Firstly, a PID controller was designed and by running simulations, its performance analyzed. Secondly, another controller structure which is widely used in unmanned aerial vehicles, cascade PID controller was designed. Moreover, a cascade LQR controller was designed to see whether performance of the system can be enhanced. Finally, the performance of these controllers is compared based on their time response characteristics. A real-life scenario is discussed how these structures would perform based on Türkiye's wind data.
Afet bölgelerinde kurulan yerleşim birimlerinin enerji ihtiyacının şebekeden bağımsız hibrit sistemlerle karşılanmasının tekno-ekonomik analizi

(Lisansüstü Eğitim Enstitüsü, 2024-07-22) Yılmaz, Ender ; Çakan, Murat ; 30101014 ; Enerji Bilimi ve Teknoloji

Afet bölgelerinde enerji ihtiyacı afetin gerçekleştiği ilk andan itibaren başlamaktadır. Deprem, sel gibi doğal afetlerden sonra özellikle gece yapılan arama-kurtarma çalışmaları sırasında kullanılacak aydınlatma sistemlerinin ve afetten etkilenen kişiler ve afetin yaşandığı bölge ile iletişimi sağlayacak haberleşme cihazlarının sürekli kullanımda olması gerekmektedir. Ayrıca bölgede kullanılacak sağlık cihazlarının çalıştırılması ve su ihtiyacının karşılanması gibi acil konular da enerji ihtiyacını arttırmaktadır. Doğal afetlerden sonra bölgeye verilen elektrik, doğalgaz gibi yakıtları taşıyan hatlardan sızıntı ihtimaline karşı güvenlik nedeniyle kesilebilir. Afetin verdiği zarardan kaynaklı olarak ise elektrik kesintileri, elektrik hatlarında kablolardaki arızalardan kaynaklanacağı gibi, şehir içi şehirlerarası trafolarda hatta enerji üretim tesislerinde problem oluşabilecek problemlerden de kaynaklanabilir. Bununla beraber doğalgaz, petrol gibi nakil hatlarında problem oluşma ihtimali, ulaşım yollarındaki aksaklıklar, afet sonrası bölgelerde enerjinin yerinde üretilme ihtiyacını gündeme getirecektir. Ayrıca bu uygulama kurulacak bölgede kaçak bağlantıların oluşmasını ve bölgenin şebekeye yük getirmemesinin önüne geçeceği gibi ilerleyen zamanlarda bölgede kurulacak kalıcı konutlarda enerji üretim alt yapısını da sağlayacaktır. Deprem, sel gibi doğal afetler, savaş, zorunlu göç gibi insan ve kıtlık gibi iklim kaynaklı afetlerden sonra insanlar bulundukları bölgeden ayrılmak zorunda kalarak afet bölgelerine yerleşmektedir. Bu bölgelere yerleşen insanların başta barınma, yiyecek ve su gibi önemli ihtiyaçları olmaktadır. Bunun yanında günlük hayatın devamı için önemli olan telefon, tablet ve dizüstü bilgisayarı gibi iletişim araçlarının da elektrik ihtiyacının karşılanması gerekmektedir. Bu ihtiyaçların ilk zamanlarda karşılanmasında portatif ve mobil güneş enerjisi sistemleri kullanılabilmektedir. İlerleyen zamanlarda artan güç ihtiyacı ile beraber daha büyük enerji sistemlerine ihtiyaç vardır. Afet bölgesindeki hanelerde, okul ve sağlık ocağı gibi tesislerde, suyun pompalanması gibi uygulamalarda PV-Bataryalardan oluşan bağımsız güneş enerjisi sistemleri enerji ihtiyacını karşılayabilir. Ayrıca PV-Batarya sistemleri ile bazı afet bölgelerinde insani yardım amaçlı yapılan uygulamalarda bölgenin çok büyük oranda enerjisini üretebilecek kapasitelere ulaşılmaktadır. PV panellerin yanında yoğunlaştırılmış güneş enerjisi özellikle suyun dezenfeksiyonu ve yemek pişirilmesi gibi uygulamalarda kullanılabilmektedir. Rüzgar enerjisi son senelerde gelişen teknolojiyle beraber afet bölgelerinde acil enerji ihtiyacını karşılamakta görev alabilmektedir. Biyogaz bir yenilenebilir enerji kaynağı olarak afet bölgelerinde sanitasyon gibi atık yönetimi uygulamalarından elde edilebilmektedir. Elde edilen biyogaz yemek pişirme için ocaklarda, yüksek miktarda elde edilen biyogaz ise jeneratörlerde enerji kaynağı olarak faydalanılabilmektedir. Afet bölgelerinde bir diğer önemli konuda yemeğin pişirilmesidir, geleneksel yöntemler bırakılarak odun ve odun kömürünü daha verimli kullanan ocaklar, LPG ve etanol ocakları, biyogaz ve solar gibi yenilebilir ocaklar ve son zamanlarda enerji-etkin elektrikli ocaklar bu bölgelerde kullanılabilmektedir. Yenilenebilir enerji kaynaklarının afet bölgelerinde yaygın olarak kullanımını sağlayan en önemli unsur bataryalardır. Özellikle son senelerde düşük güçlerden yüksek güçlere kullanımı yaygınlaşan lityum-iyon bataryalar son dönemlerde öne çıkmaktadır. Dizel jeneratörler afet bölgelerinde enerji ihtiyacını karşılanmasında hala ilk akla gelen yöntemdir. Ancak yakıt masraflarındaki artış ve sürekli yakıt ihtiyacı, emisyon sorunu gibi nedenlerden dolayı afet sonrası alanlarda kullanılması azaltılmaya çalışılmaktadır. Hibrit sistemler yenilenebilir ve dizel jeneratörlerin avantajlarını bir araya getirerek daha güvenilir, sürdürülebilir, emre amadeliği yüksek, uygun maliyetli sistemler olmaktadır. 26 Şubat 2023 günü Kahramanmaraş merkezli iki büyük depremde en büyük yıkımın yaşandığı yerlerin başında Hatay'ın Antakya ilçesi gelmektedir. Depremin özellikle ilk günlerinde başta arama kurtarma çalışmaları olmak üzere bölgede enerji sıkıntısı yaşanmıştır. Bu çalışmada, Antakya ilçesinde afet bölgesinde 72 hanelik bir komşuluk biriminin elektrik ihtiyacı HOMER programı kullanılarak depremin ilk günlerinden başlayarak kademeli olarak yenilenebilir ve hibrit sistemler ile karşılanması planlanmaktadır. Bu plan doğrultusunda enerji ihtiyacının karşılanması için gerçekleştirilecek bu kademeli olarak artış dünya bankası enerji sektörü destek programının hazırladığı SE4ALL (Sustainable energy for all- herkes için sürdürülebilir enerji) çoklu-kademe sistemi bölgeye uyarlanarak yapılacaktır. Afet bölgesinin ilk gününden başlayarak bir haftalık, on beş günlük, üç aylık, altı aylık sürelerde 5 kademe tanımlanmıştır.
Afet bölgesinde yer alan kentlerde PM10 ve SO2 düzeylerindeki değişimlerin incelenmesi

(Lisansüstü Eğitim Enstitüsü, 2024-06-06) Kurut, Ali Ozan ; Kahya, Ceyhan ; 511191001 ; Atmosfer Bilimleri

Hava, yaşamın sürdürülebilmesi için gereken temel parametrelerden biridir. Sağlıklı bir yaşam için ise, hava kalitesinin de sağlıklı bir aralıkta bulunması oldukça önemlidir. Hava kirliliği; doğa veya insan kaynaklı salınımlar sonucu, atmosferde bulunan kirleticilerin belirli seviyeleri aşması ve uygun meteorolojik koşullar altında canlı ve cansız varlıklar üzerinde olumsuz etkilere neden olması olarak tanımlanmaktadır. Kirletici seviyelerinin atmosferde belirli eşik değerleri aşması sonucu yaşam alanları ile toplumsal alanların hava kalitesi düşmektedir. İngiltere'de temelleri atılan endüstriyel devrim, sonrasında Avrupa kıtasında, Amerika ve Japonya'da etkilerini göstermiş ve buharlı makineler kullanılarak sürdürülen endüstriyel üretimler sonraki süreçte birçok ülke tarafından kullanılmaya başlamıştır. Hava kalitesi ve hava kirliliği üzerinde bir dönüm noktası olan sanayileşme, beraberinde istihdam olanaklarını ve dolayısıyla ekonomik kalkınmayı getirmiştir. İnsanların istihdam olanakların daha yüksek olduğu sanayi kentlerine göç etmesi, hızlı nüfus artışlarının önünü açmış, nüfus artışlarıyla beraber hanelerde evsel ısınma ihtiyacı sonucu kullanılan fosil yakıt ürünleri miktarı artış göstermiş ve bireysel motorlu taşıt kullanım oranı artmıştır. Sanayi devrimi ve sonrasında gelişen süreç, hava kirliliğine etki eden antropojenik sebepler arasında yer alırken, orman yangınları, volkanik faaliyetler, çöl tozları, depremler ve benzeri birtakım doğal döngüler de atmosfere birtakım kirleticilerin salınmasına yol açarak hava kirliliği üzerine etki edebilen doğal süreçlerin başında gelmektedir. Ayrıca, kirleticilerin bir bölgeden başka bir bölgeye taşınmasında, bir yerleşim bölgesi üzerinde askıda kalmasında rüzgar, basınç ve enverziyon sahaları gibi birtakım meteorolojik parametrelerin de etkisi olduğu bilinmektedir. Dolayısıyla tüm bu süreçlerin neticesinde, atmosfere salınan kirletici parametrelerin emisyon kaynakları birçok farklı alanda çeşitlilik arz etmiş, zaman içerisinde hava kirliliği üzerine tartışmalar ve yapılan çalışmalar hız kazanmıştır. Hükümetler ve birçok sivil toplum kuruluşu tarafından hava kalitesinin iyileştirilmesine yönelik adımlar atılmaya başlanmış, yapılan uluslararası antlaşmalar, mutabakat ve protokoller ile birçok ülke kirletici emisyonlarının azaltılmasına yönelik metinlerin altına imza atmıştır. Ayrıca, hava kalitesinin sağlıklı olduğu aralıktan tehlikeli seviyelere ulaştığı aralığa kadar farklı renk tonlarıyla ifade edildiği ve renk tonlarının karşılık geldiği hassas grupları ifade eden Hava Kalitesi İndeksi (HKİ) oluşturulmuştur. Partikül madde (PM10) ve kükürt dioksit (SO2) de antropojenik ve doğal süreçlerin sonunda atmosfere salınan birincil hava kirleticilerinin başında yer almaktadır. Bu çalışmada da, çapı 10 μm'den küçük olan partikül madde (PM10) ve kükürt dioksit (SO2) parametrelerinin 06.02.2023 tarihli Kahramanmaraş merkezli 7.7 ve 7.6 büyüklüğündeki depremlerden sonra "Genel Hayata Etkili Afet Bölgesi" olarak ilan edilen kentlerdeki dağılımları incelenmiştir. Kirletici verileri 01.12.2018 ile 29.02.2024 tarih aralıkları için elde edilerek, deprem dönemindeki dağılımlarının yanı sıra her iki kirleticinin de Covid-19 pandemisi öncesinde dağılımları ile pandemi dönemindeki dağılımları da ortaya konmaya çalışılmıştır. Kirletici verileri Çevre ve Şehircilik Bakanlığı Ulusal Hava Kalitesi İzleme Ağı veritabanından belirtilen tarihler için elde edilmiş ve sonrasında 01.12.2018 ile 29.02.2020 tarihleri arası pandemiden önceki dönemi, 01.03.2020 ile 30.11.2022 tarihleri arası kentlerde pandemi dönemini, 01.12.2022 29.02.2024 tarihleri arası ise Kahramanmaraş merkezli depremler ve sonrasındaki süreci temsil etmek üzere üç farklı alt periyoda ayrılmıştır. Elde edilen veriler incelenmiş, belirlenen eksik veriler ise SPSS İstatistik programında uygun kayıp veri atama yöntemleri kullanılarak giderilmiştir. Ardından kirleticilerin çalışma alanı içerisindeki tüm istasyonlarda belirlenen üç farklı dönem için mevsimsel olarak zaman serisi çıktıları elde edilmiştir. Çalışma alanı içerisindeki 10 kentte yer alan 14 hava kirliliği ölçüm istasyonunda elde edilen zaman serileri ile kirletici parametrelerin belirlenen üç farklı dönem içerisindeki dağılımları incelenmiş ve yorumlanmıştır. Kirletici parametrelerin istasyon çevresindeki dağılımlarının belirlenmesinin yanı sıra, bu dönemlerde PM10 bağımsız değişken, SO2 ise bağımlı değişken olarak seçilerek %95 güven aralığı için basit doğrusal regresyon modeli kurulmuş, hesaplamalar sonucunda elde edilen korelasyon katsayıları, determinasyon katsayıları ve kurulan modelin anlamlılığını ifade eden p değerleri yorumlanarak aralarındaki ilişki tespit edilmiştir. Son aşamada ise, istasyonlarda ölçümleri yapılan kirletici parametrelerin çalışma periyodundaki üç farklı ana dönem için hesaplamalar neticesinde elde edilen mevsimsel ortalama konsantrasyon değerleri ile limit değer aşım sayıları birbirleri ile karşılaştırılmış ve yorumlanmıştır. Çalışmada yapılan mevsimsel analizler sonrasında elde edilen sonuçlara göre, partikül madde seviyelerinin özellikle Elbistan, Osmaniye, Malatya, Meteoroloji istasyonlarında yüksek seviyelerde seyrettiği belirlenmiştir. Belirtilen istasyonlar kış, ilkbahar, yaz ve sonbahar mevsimlerine yönelik incelemelerde yaz mevsimlerine doğru kirletici konsantrasyonları kademeli olarak düşüşe geçmiş olsa da, çalışma alanı içerisindeki istasyonlar arasında en yüksek partikül madde seviyelerinin gözlemlendiği ve limit değer aşımlarının en çok yaşandığı istasyonlar olarak öne çıkmıştır. Farklı dönemlerde yapılan ölçümlerde ise Çatalan, Diyarbakır, Doğankent, Adıyaman ve Elazığ istasyonları partikül madde seviyelerinin en düşük seyrettiği ve bu anlamda hava kalitesinin daha iyi olduğu istasyonlar olarak belirlenmiştir. Kükürt dioksit ölçümleri ile yapılan mevsimsel analizler sonucunda ise, kirletici seviyelerinin en yüksek seyrettiği istasyonlar Şanlıurfa ve Onikişubat istasyonları başta olmak üzere Elbistan, Osmaniye ve Malatya olarak belirlenmiştir. Küküt dioksit seviyelerinde limit değer aşımı partikül maddeye kıyasla oldukça az sayıda gerçekleşmiş ve partikül madde incelemelerinde karşılaşıldığı gibi, yaz mevsimlerinde en düşük konsantrasyonların ölçüldüğü, kış mevsiminin ise en yüksek kirletici seviyelerinin kaydedildiği belirlenmiştir. Kükürt dioksit seviyelerinin en düşük seyrettiği istasyonların ise Çatalan, Elazığ, Adıyaman, Diyarbakır olduğu belirlenmiştir. Belirtilen istasyonlar bu yönüyle her iki kirleticide de en düşük konsantrasyonlara sahip istasyonlar olarak dikkat çekmiştir. Kirleticiler arasında mevsimsel olarak her bir dönem için kurulan basit doğrusal regresyon modeline göre, kış ve sonbahar aylarında kirleticiler arasındaki doğrusal ilişkinin daha güçlü olduğu, dolayısıyla bu dönemlerde kirletici ölçüm değerlerinin birbiriyle paralellik gösterdiği belirlenirken, ilkbahar ve yaz aylarında kirleticiler arasındaki korelasyon katsayıları ile determinasyon katsayılarının daha düşük seviyelerde seyrettiği görülmüştür. Zaman serilerine göre, pandemi sürecinin ilk aylarında ve depremlerden sonra yaşanan ilk haftalarda bazı istasyonlarda kirletici konsantrasyonlarında ciddi dalgalanmalar tespit edilmiştir. Çalışmada alanı olarak ele alınan bölgede yoğun nüfusu ile dikkat çeken kentlerin varlığı, çevresinde büyük ölçekli sanayi kuruluşları olan istasyonların bulunması, bazı istasyonların, çevresindeki trafik kaynaklı kirletici emisyonlarına açık bir alan üzerinde kurulu olması ve benzer şekilde yoğun nüfuslu ilçe çevrelerinde bulunan istasyonların evsel ısınmada kullanılan fosil yakıtlar sonucu atmosfere salınan kirletici emisyonlarına yoğun şekilde maruz kalması, termik santral gibi çevre ve insan için birçok olumsuz etkisi bulunan güç santrallerinin varlığı, pandemi dönemi başlangıcı ile gelen süreçten sonra dönem dönem tam kapanma ve kademeli olarak normale dönme adımlarının bir yansıması olarak evsel ısınmaya olan talebin, trafik kaynaklı emisyonların iniş çıkışlar göstermesi, ardından yaşanan büyük depremlerle yine bölgedeki kirletici emisyonlarının artışa geçmesi, ele alınan çalışma alanının, Türkiye'de toz taşınımının sık görüldüğü bir coğrafi bölgede yer alması gibi kirletici seviyelerini etkilemesi beklenen faktörler, çalışma sonuçlarına büyük ölçüde yansımıştır.

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Sustainable Development Goal "Goal 7: Affordable and Clean Energy" ile Tezler'a göz atma

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