Evaluation of flood determination with various methods: Case study of Ayamama Creek

Gelişmekte olan birçok ülkede hızlı kentleşme, afet riskleri ve etkilenebilirlikler büyük sorun teşkil etmektedir. Kontrolsüz gelişmeler, yoğun yerleşim yerleri ve yetersiz altyapı ile ilgili mevcut riskleri ortaya çıkarmaktadır. Tehlikeli alanların haritalanmasındaki gelişmeler, toplum etkilenebilirliklerinin değerlendirilmesi ve yıkıcı güçlere karşı dayanıklı tasarımların yapılması, kayıpların azaltılması için yeni fırsatlar yaratmıştır. Bu çalışmanın amacı, taşkın analizinde en çok kullanılan; i) Çok Kriterli Karar Verme, ii) Hidrolik Modelleme, iii) Bilgi Difüzyon Teorisi ve iv) Eğri Numarası (SCS-CN) yöntemlerinin değerlendirmesi ve karşılaştırmasıdır. Elde edilen sonuçlar ışığında; oluşturulan etkilenebilirlik haritasına göre toplamda 1995 binanın etkilenebilir alanlar içerisinde bulunduğu ve bunların 420’sinin çok yüksek etkilenebilir alanlarda olduğu belirlenmiştir. Ayamama Deresi için yapılan modelleme sonucuna göre 185 m3 /s’lik kararlı akımın yaklaşık olarak 73 ha’lık bir alanı etkileyeceği sonucuna varılmış ve etkilenecek alanlar CBS ortamında belirlenmiştir. Yapılan obje-tabanlı en yakın komşuluk sınıflandırma sonucu temel alındığında olası taşkında etkilenebilir alanda; toplamda 1859 binanın etkileneceği belirlenmiştir. Havzaya ait eğri numaraları SCS-CN yöntemi ile belirlenerek Bilgi Difüzyon yönteminde kullanılmıştır. Bilgi Difüzyonu analiz sonuçlarına göre; Ayamama Deresi 180 m3 /s’lik akıma ulaştığında taşkın olma olasılığının yaklaşık olarak % 97.2 olacağı ve taşkın sularının yaklaşık 50 ha gibi bir alanda etkili olacağı belirlenmiştir.In many developing countries, rapid urbanization, disaster risks and affectability pose a great problem. Uncontrolled developments will bring out the inherent risks related with high-density environments and inadequate infrastructure. Advances in mapping hazardous areas have created new opportunities for assessing population vulnerabilities, doing designs to withstand against destructive forces and reducing losses. The aim of this study is to evaluate and compare the most used methods including i) Multi Criteria Decision Analysis, ii) Hydraulic Modeling, iii) Information Diffusion Theory and iv) SCS-CN (Soil Conservation Service Curve Number) in flood analysis. In the light of the results; 1995 buildings were found to be in vulnerable zones in total and 420 of them were found to be in a very high vulnerable zones according to the prepared affectability map. Hydrologic modeling results based on the defined discharge rate showed that 73 hectares of the urbanized area will be affected in the event of 185m3 /s of steady flow in Ayamama Creek and these areas were determined in GIS. Based upon the nearest neighbour object-based classification, total of 1859 buildings were defined to be affected by a potential flood. Curve numbers of the catchment were determined by using SCS-CN method and used in Information Diffusion method. According to the results of this method, when the Ayamama Creek reaches 180m3 /s of flow rate, the probability of flood occurrence is estimated to be %97.2 and it was determined that the flood waters will be effective in about 50 hectares of the area

Geophysical and UAV surveys on Konya Karahöyük (central Anatolia, Turkey)

Geophysical prospection and unmanned aerial vehicles (UAV) were applied systematically to improve excavation strategies. Magnetic results were verified using GPR in the suitable areas

Multi-temporal UAV based repeat monitoring of rivers sensitive to flood

Multi-temporal repeat monitoring of flood-vulnerable rivers is crucial due to rapid alteration of morphological properties of in-channel landforms. Besides, the characteristics of the river crossing bridges may deteriorate due to flood induced scouring around bridge piles or due to flood loads. Thus, in this study high-resolution topography of the study region was acquired during two consecutive years by unmanned aerial vehicle (UAV) based surveys using Structure-from-Motion (SfM) processing. Following the extraction of digital elevation models (DEM), repeat data that were obtained at each UAV survey were compared using Geomorphic Change Detection (GCD) to calculate volumes of deposition and erosion via DEM of difference (DoD) algorithm. Thus, detailed high-resolution maps of the river channels can be rapidly and efficiently generated by low cost UAV based measurement methods in order for continuous tracking of stream channel morphology for the rivers sensitive to floods

Multi-Hazard Assessment of RC Bridges using Unmanned Aerial Vehicle-Based Measurements

The structural performance of reinforced concrete bridges is crucial regarding the bridge safety. Monitoring the bridge performance under multihazard effects such as scour, and earthquake becomes even more important. Thus, the scour depth along the piers and piles of bridge substructures has to be measured and tracked consistently in order for reliable multi-hazard bridge behaviour predictions. A practical Unmanned Aerial Vehicle based scour measurement method was proposed to increase the measurement accuracy and reduce the implementation costs. This method has been used in shallow and clear-water riverbeds. The Boğaçayı Bridge was selected as the case study located at the Boğaçayı River in Antalya, Turkey, since it was exposed to stream and flood, induced scour in the previous years. In the study region, the amount of scour was determined with considerable accuracy, and the scour measurements were used for generating the Three-Dimensional Finite Element model of the bridge. The multi-hazard performance of the bridge was acquired by implementing nonlinear static analysis using pushover curves corresponding to various scour depths concentrated at some of the bridge piers. Therefore, a continuously updateable multi-hazard bridge assessment system was proposed, which was implemented in bridges under scour and earthquake effects, regarding Unmanned Aerial Vehicle based measurements

Bir uçuş simulasyonu ortamında çalışma belleği kapasitesi, dikkat ve deneyimin durumsal farkındalık üzerindeki etkilerinin araştırılması.

Experienced and novice simulator pilots are subject to some of the constraints of a real flight (or a full flight simulator) situation in a PC based flight simulation. In this thesis, the effects of expertise, working memory capacity, inhibition and divided attention on situation awareness (SA) in simulated flight task environments are investigated. The cognitive aspects underlying the process of situation awareness are explored by analyzing the compound effects of above listed factors. Online and Offline SA measurements obtained from a simulated flight task are used with flight hours standing for expertise and scores of Automated Operation Span Task, Stroop and Coşkunöz visual attention tasks as measurements for working memory capacity, inhibition and divided attention respectively. Regression analyses reveal that expected relationships of simulator pilots’ SA with expertise and inhibition capacity are supported. On the other hand, expected relationships of SA with working memory and divided attention capacities are not revealed. This situation probably results from unsystematic differences in simulator pilots’ practices. In addition to the main experiment, simulator pilots’ levels of neural activity at their dorsolateral prefrontal cortex are also measured during their behavioral performance. The relationships among neural correlates of mental workload induced by the simulated flight are investigated by the functional near-infrared (fNIR) spectroscopy optical brain imaging technology. Theorized mental workload distinction in the scenario of the simulated flight task is successfully observed in both perceived workload declarations and oxygenation measurements by fNIR.M.S. - Master of Scienc

Caractérisation des connexions cellules de Purkinje-cellule des noyaux profonds dans le cervelet de souris

The cerebellum integrates motor commands with somatosensory, vestibular, visual and auditory information for motor learning and coordination functions. The deep cerebellar nuclei (DCN) generates the final output by processing inputs from Purkinje cells (PC), mossy and climbing fibers. We investigated the properties of PC connections to DCN cells using optogenetic stimulation in L7-ChR2 mice with in vivo multi electrode extracellular recordings in lobule IV/V of the cerebellar cortex and in the medial nuclei. DCN cells discharged phase locked to local field potentials in the beta, gamma and high frequency bands. We identified two groups of DCN cells with significant differences in action potential waveforms and firing rates, matching previously discriminated in vitro properties of GABAergic and non-GABAergic cells. PCs inhibited the two group of cells gradually (rate coding), however spike times were controlled for only non-GABAergic cells. Our results suggest that PC inputs temporally control the output of cerebellum and the internal DCN circuitry supports this phenomenon since GABAergic cells do not induce a temporal effect through local inhibition.Le cervelet permet l’apprentissage moteur et la coordination des mouvements fins. Pour ce faire, il intègre les informations sensorielles provenant de l’ensemble du corps ainsi que les commandes motrices émises par d’autres structures du système nerveux central. Les noyaux cérébelleux profonds (DCN) constituent la sortie du cervelet et intègre les informations provenant des cellules de Purkinje (PC), des fibres moussues et des fibres grimpantes. Nous avons étudié les connexions fonctionnelles entres les PC et les DNC in vivo, grâce à une stimulation optogénétique des lobules IV/V du cortex cérébelleux et à l’enregistrement multi unitaire du noyau médian. Nous avons ainsi identifié deux groupes de cellules au sein des DCN, présentant des caractéristiques propres au niveau de leur fréquence de décharge et de la forme des potentiels d’action, en accord avec la dichotomie établie par une précédente étude in vitro permettant de séparer les neurones GABAergiques des autres neurones. Nos résultats suggèrent que les PC contrôlent la sotie du cervelet d’un point de vue temporel. De plus, la ciruiterie interne des DCN conforte ce résultat de part le fait que les cellules GABAergiques ne produisent pas d’effet temporel au travers de l’inhibition locale

Exploring the Effects of Working Memory Capacity, Attention, and Expertise on Situation Awareness in a Flight Simulation Environment

Simulator pilots are subject to some of the constraints of a real flight situation in a PC based flight simulation. Situation awareness (SA) for simulator pilots was explored in terms of underlying cognitive aspects by analyzing the compound effects of expertise, working memory, inhibition and divided attention. Online and Offline SA measurements were analyzed with expertise and scores of Automated Operation Span Task, Stroop and Coşkunöz visual attention tasks. Regression analyses revealed the expected relationships of simulator pilots’ SA with expertise and inhibition capacity but not with working memory and divided attention capacity. Obtained results were also compared to those of professional pilots. Despite similar cognitive capacities and expertise, simulator pilots had incompatible results with professional pilots in offline SA queries and they exhibited different SA performance related to expertise and cognitive capacity tests. This situation probably resulted from unsystematic differences in simulator pilots’ practices

Modeling Morphodynamic Processes in Meandering Rivers with UAV-Basedmeasurements

Akay, Semih Sami (Arel Author)Accurate surface models are a crucial component of studies of morphodynamic modeling of rivers and river channel evolution. The high flows that rivers have are caused by changes in flood bed or low canal flow, also it changes river channel morphology. Floods that occur during the spring months cause significant geomorphological changes. In addition to this, low flows during the summer also trigger erosion and superficial accumulation in the ongoing process. Using an accurate, high-resolution, seamless surface models of the river channel and floodplain allows to detect morphological changes of the whole river channel more accurately than using traditional methods. This enables a more comprehensive view of the riverbed evolution. Therefore, high-quality topographical data at different scales are required to study fluvial processes and river dynamics. Nowadays, a combination of photogrammetry and Unmanned Aerial Vehicle (UAV) systems is widely used for various applications, especially for 3D surface modelling and large scale mapping. UAV systems offer many advantages in terms of cost and image resolution when compared to terrestrial photogrammetry and satellite remote sensing systems. In the study, aerial imaging was carried out via UAV to produce very high resolution surface models based on Structure from Motion (SfM) technique. Multi-temporal topographic data were produced and morphodynamic processes in the Buyuk Menderes River were modeled. Thus, UAV-based a fast and practical way to derive volumetric quantity of lost/gained soil was developed

Efficiency analysis of solar farms by UAV-based thermal monitoring

Solar energy is a rapidly growing industry, and the performance analysis and maintenance of solar farms are crucial for ensuring their photovoltaics efficiency and longevity. In this context, many solar farms are established and it is crucial for energy producers to operate these farms efficiently. However, control of solar degradation panels locally takes time and control procedures are a challenge for the producers particularly for large farms. In recent years, the use of unmanned aerial vehicles equipped with thermal imaging sensors has emerged as a promising technique for monitoring solar farms. Herein, degradation inspection and efficiency analyses of the solar panels can be effectively conducted by mapping thermal orthomosaic data. In this study, thermal images were obtained for orthomosaic data production by conducting photogrammetric flights with a real time kinematic enabled unmanned aerial vehicles on a solar farm. The solar panels were divided into segments by the segmentation process and photovoltaics efficiency was calculated for each panel based on solar energy. The photovoltaics efficiency was monitored to vary at most 1.22 % throughout the day with the maximum efficiency reaching 18.25 % in the afternoon, and the minimum efficiency dipping to 17.03 % midday. Close efficiency values were acquired in the morning and afternoon with a difference not exceeding 0.12 %. As such, the damage conditions of panels can be identified by designating the ones with the lowest efficiency. Thus it can be deduced that rapid, cost effective and feasible assessment of solar farms may be possible by unmanned aerial vehicle-based thermal monitoring while bringing forth more sensitive future predictions