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Modeling deficit irrigation in alfalfa production
No full textA conceptual agronomic model EPIC was extended to consider the effects of salinity in alfalfa production under optimal and water stress irrigation conditions. The extended model was calibrated and validated with observed lysimeter data. The model parameters that affected alfalfa yield and soil salinity the most were wilting point, field capacity, hydraulic conductivity, nitrate concentration, biomass energy ratio, seeding rate, average soil salinity EC e at which crop yield is reduced by 50% ( EC50 ), and initial soil gypsum concentration. The calibrated and validated model was then applied to an alfalfa deficit irrigation study. The four irrigation treatments included optimum check, minimum stress, short stress, and long stress, each of which produced differential alfalfa yields. The purpose of summer deficit irrigation was to ascertain how much agricultural water at what cost could be made available for urban water uses during water shortfalls. The results of model simulation were found to be satisfactory under all irrigation treatments though the model slightly overestimated the yields and underestimated the soil EC e at the end of short and long stress treatments. An economic component is included to determine the appropriate compensation for farmers undergoing a range of deficit irrigations
Electrolysis of MgCl2 with a top Inserted anode and an Mg-Pb cathode
No full textHigh energy consumption in the production of magnesium by molten salt electrolysis is mainly due to the recombination of magnesium and chlorine. The large interelectrode distance used, in conventional techniques, to reduce the extent of ‘back reaction’, results in a significant potential drop. A laboratory cell that enables the operation with smaller interelectrode distance and easy separation of electrode products has been used to study electrolytic magnesium production. The cell features a top inserted graphite anode and a Mg-Pb alloy cathode at the bottom. Current efficiency and power consumption were determined at 690° C using a current density of 0.48 A cm−2. Experiments were performed to study the effects of MgCl2 concentration and anode-cathode distance (a.c.d.) on cell operation. Results indicated that an electrolyte containing 20% MgCl2 (equiweight NaCl:KCl and 1 % NaF) with a 3 cm a.c.d. reduced the cell voltage to 3.72 V. This value corresponds to an energy consumption of 11.3 kWh kg−1 including the refining of Mg-Pb alloy produced at the cathode. This cell performance is more energy efficient compared to conventional magnesium cells
Çarpmaya maruz bırakılmış E cam/polyester kompozitinin kalıcı dayanım analizi
No full textThesis (Master)--Izmir Institute of Technology, Mechanical Engineering, Izmir, 2018Includes bibliographical references (leaves: 73-78)Text in English; Abstract: Turkish and EnglishIn this thesis, residual strength analysis of an E-Glass/polyester laminate was carried out for multiple impact loading. MAT_162 material model in LS-DYNA finite element code was used to model the constitutive behavior of the composite and material model parameters were determined using the results of the mechanical characterization. Experimental and numerical multiple loading were performed for two cases, namely Split Hopkinson Pressure Bar (SHPB) and projectile impact testing device. Numerical models were simulated DYNAIN file method strategy in which a composite laminate was impacted multiple times, which was very close to the actual case. A numerical ballistic test model using conventional strategy (in the same simulation all the loads applied sequentially) was employed to check the accuracy of that using the proposed new methodology. After the first hit the SHPB results revealed that delamination occurred at the interface between the first and second layers. Following the second hit, delamination propagated along the inside layers of the composite and occurred at the interface between the eighth and ninth layer. As far as the bar responses concerned, the reflected pulse increased from zero to a maximum value then gradually decreased at the first impact. However, a sharp rise was seen in the reflected pulse of the second impact due to failure corresponding to catastrophic failure. In projectile impact tests, delamination was also found to be increased with the increasing number of hits at both front and back surfaces. Similar results were obtained for both DYNAIN and conventional strategies. It was concluded that simulations showed well agreement with experimental results.Bu tezde, bir kompozit malzemenin kalıcı dayanım analizi çoklu hasar yüklemeleri için araştırılmıştır. LS-DYNA sonlu elemanlar programındaki MAT_162 malzeme modeli kompozit malzemenin yapısal davranışını modellemekte kullanılmış ve malzeme modeli parametreleri mekanik karakterizasyon sonuçları kullanılarak hesaplanılmıştır. Çoklu yükleme iki durum için gerçekleştirilmiştir. Bunlar Split Hopkinson Basınç Barı (SHBB) ve mermi hasar test düzeneğidir. Numerik modellemede DYNAIN dosya yöntem stratejisi kullanılmıştır. Bu strateji ile kompozit numune deneysel olarak gerçekleştirilen çalışmaya çok yakın bir şekilde çoklu kez hasara maruz kalmıştır. Konvansiyonel stratejinin kullanıldığı nümerik modeller (tüm yüklemelerin sırayla aynı simülasyonda uygulandığı) öne sürülen yeni metodolojinin doğruluğunu kontrol etmekte kullanılmıştır. SHBB testindeki ilk atıştan sonra delaminasyon birinci ve ikinci katmanların arasında ki ara yüzeyde ortaya çıkmıştır. Ancak ikinci atıştan sonra delaminasyon kompozitin katmanları arasında ilerlemiş, ve sekizinci ve dokuzuncu katmanların arasındaki ara yüzeyde meydana gelmiştir. İlk atıştaki bar tarihçeleri incelendiğinde yansıyan dalga sıfırdan maksimum bir değere artmış sonrasında kademeli olarak azalmıştır. Ancak, ikinci atıştaki katastrofik hasardan dolayı yansıyan dalgada keskin bir artış gözlemlenmiştir. Mermi hasar testleri için, delaminasyonun ön ve arka yüzeylerde artan atış sayılarıyla birlikte arttığı bulunmuştur. Benzer sonuçlar hem DYNAIN hem de konvansiyonel metot ile elde edilmiştir. Gerçekleştirilen simülasyon çalışmalardan elde edilen sonuçların deneysel sonuçlarla örtüştüğü sonucuna varılmıştır
Effect of COVID-19 pandemic on ambient air quality and excess risk of particulate matter in Turkey
No full textThe COVID-19 pandemic, which has reached 4 million global cases as of March 10, 2020, has become a worldwide problem. Turkey is one of the most affected (9th in the world) country with 139 771 cases. An intermittent curfew policy that differ for three age groups, and an intercity travel ban varying within the country have been implemented. The effects of changes in social life and industrial activity in terms of environmental pollution are not yet known. The short-term effects on PM2.5, PM10, SO2, NO2, NO, NOx, O3 and CO concentrations measured at 51 air quality measurement stations (AQMS) in 11 cities in March – April period of 2020 were statistically compared with that of the previous year. While PM2.5 (9/14 AQMS) and PM10 (29/35 AQMS) concentrations were not significantly affected, NO (12/24 AQMS), NO2 (20/29 AQMS), NOX (17/25 AQMS) concentrations were decreased, SO2 concentrations at half of the AQMSs (11/25) did not show a significant change. There were stations at which higher pollutant concentrations were measured in the study period in 2020 compared to that of 2019. Excess risks associated with PM2.5 and PM10 were estimated to be variable, albeit with a small difference. In conclusion, the heterogeneous actions taken in response to the COVID-19 pandemic resulted in mixed effects on ambient air quality
Derin öğrenme tabanlı saldırı tespit sistemleri için doğruluk ve verimlilik analizi
No full textAs technology advances and attack techniques show continuous progress, intrusion detection systems also need to develop. Hence, machine learning techniques started to be adopted more and more in the research on intrusion detection systems. In this study, application of Recurrent and Feed-forward Neural Network models is examined for detection and classification of attacks on computer networks. Using the dataset CICIDS2017 that has 14 up-to-date attack types, numerous tests are run with Multilayer Perceptron (MLP), Long-short Term Memory (LSTM), and Gated Recurrent Unit (GRU) neural network models and their success rates for the classification of malicious packets are examined. Additionally, based on the obtained results, a second set of tests are performed to observe the effect of the features in the dataset on success rates and performance. As a result of ablation study, performed by reducing the number of attributes used by one for each feature, the accuracy rates of different network models are obtained and it has been shown that using the most effective features, the duration of the tests can be reduced without affecting the detection rates significantly.İlerleyen teknolojiler ve sürekli gelişen atak teknikleri sebebi ile saldırı tespit sistemlerinin de geliştirilmesine ihtiyaç vardır. Dolayısıyla, makine öğrenmesi teknikleri, saldırı tespit sistemleri üzerine yapılan çalışmalarda git gide daha fazla kullanılmaya başlanmıştır. Bu çalışmada, Tekrarlayan Sinir Ağlarının (RNN) ve İleri Beslemeli Sinir Ağlarının, bilgisayar ağları üzerindeki atakları tespit etme ve sınıflandırma başarımları incelenmiştir. 14 güncel atak tipinin bulunduğu CICIDS2017 veri seti kullanılarak, Çok Katmanlı Algılayıcı (MLP), Uzun/Kısa Süreli Bellek (LSTM), ve Kapılı Tekrarlayan Hücre (GRU) sinir ağı modelleri ile testler koşulmuş ve bunların kötücül paketleri tespitteki başarım oranları elde edilmiştir. Bu testlerin yanı sıra, alınan sonuçlara göre, veri setindeki özniteliklerin başarıya ve performansa etkisi üzerinde ikinci grup testler yapılmıştır. Kullanılan özniteliklerin sayısı teker teker azaltılarak yapılan ablasyon testleri sonucunda, bahsi geçen modellerin doğruluk oranları elde edilmiş ve en etkili öznitelikleri kullanarak, test sürelerinin, tespit oranlarını önemli ölçüde etkilemeden düşürülebileceği gösterilmiştir