Showing papers by "Istanbul Technical University published in 2022"

Hybrid power and propulsion systems for ships: Current status and future challenges

Abstract: Increasing environmental concerns are driving the shipping industry to take strict measures to deal with greenhouse gas emissions. International Maritime Organization drives the industry to find more efficient and environmentally friendly power systems. To mitigate harmful emissions, researches on marine alternative fuels, operational improvements like slow steaming or predictive maintenance, and additional emission abatement technologies are not sufficient. The use of electricity as the main energy vector is one of the ways to improve the shipping propulsion system's efficiency. In this study, power generation technologies, energy storage components, energy management systems, and hybrid propulsion topologies are reviewed. Diesel engines, fuel cells, solar and wind power as renewable energy sources are discussed as power generation units. On the energy storage side, batteries, supercapacitors, and flywheels are presented and described. Three common hybrid propulsion configurations, serial, parallel, and serial-parallel architectures are detailed with their pros and cons by highlighting commonly used energy management systems and optimization methods. Lastly, criteria for hybrid system selection are defined according to eight different ship types and assessed by providing a generic methodological approach. It is shown that electrical components and architectural design should be elaborated according to operational and architectural characteristics for ships. In short term, it is concluded that internal combustion engines are still the major hybridization element with different energy storage systems. New regulations on the mitigation of harmful emissions will accelerate the transition to hybrid power which is an important option for the ultimate zero-carbon shipping goal.

Recent advances on the improvement of quercetin bioavailability

Abstract: Natural antioxidants, such as polyphenols, are finding increasing application in functional foods designed to improve human health, wellbeing, and performance. Quercetin is a flavonol-based polyphenol that exhibits a broad range of potentially beneficial health effects, including anti-hypertensive, anti-diabetic, anti-asthmatic, anti-carcinogenic, anti-viral and antioxidant activities. The types and amounts of quercetin found in different plant sources vary considerably. Onions have a particularly high quercetin content, mainly in the form of isoquercetin, whereas black teas and apples mainly contain quercetin in the form of rutin. Quercetin has been incorporated into different kinds of food matrices to improve their nutritional profiles, including baked goods and dairy products. However, the bioavailability of quercetin is often relatively low (<10%) because of its poor water-solubility, chemical stability, and absorption profile. The bioavailability of quercetin depends on its chemical structure, physicochemical properties, and food matrix effects. A number of studies have shown that the bioavailability of quercetin can be improved by encapsulating it in well-designed colloidal delivery systems assembled from food-grade ingredients. This review summarizes the major factors affecting the bioavailability of quercetin, as well as approaches being developed to increase its bioavailability. Enhancing the bioavailability of quercetin may lead to the development of more effective nutraceuticals and functional foods.

Physics and Modeling of Large Flow Disturbances: Discrete Gust Encounters for Modern Air Vehicles

Abstract: Gusts of moderate and large magnitude induce flow separation and other complexities when they interact with the lifting surfaces of air vehicles. The presence of these nonlinear gusts are becoming ...

Demand forecasting model using hotel clustering findings for hospitality industry

Abstract: Tourism has become a growing industry day by day with the developing economic conditions and the increasing communication and social interaction ability of the people. Forecasting tourism demand is not only important for tourism operators to maximize their revenues but also important for the formation of economic plans of the countries on a global scale. Based on the predictions countries are able to regulate the sectors that benefit economically from tourism locally. Therefore, it is crucial to accurately predict the demand in many weeks advance. In this study, we propose a new demand forecasting model for the hospitality industry that forecasts weekly hotel demand four weeks in advance through Attention-Long Short Term Memory (Attention-LSTM). Unlike most of the existing methods, the proposed method utilizes the time series demand data together with additional features obtained from K-Means Clustering findings such as Top 10 Hotel Features or Hotel Embeddings obtained using Neural Networks (NN). While creating our model, the clustering part was influenced by the fact that travelers choose their accommodation according to certain criteria, and the hotels meeting similar criteria may have similar demands. Therefore, before the clustering part, we also applied methods that would enable us to represent the features of the hotels more properly and we observed that 10-D Embedded Hotel Data representation with NN Embeddings came to the fore. In order to observe the performance of the proposed hotel demand forecasting model we used a real-world dataset provided by a tourism agency in Turkey and the results show that the proposed model achieves less mean absolute error and mean absolute percentage error (at worst % 3 and at most % 29 improvements) compared to the currently used machine learning and deep learning models.

Co-occurence of antibiotics and micro(nano)plastics: a systematic review between 2016-2021

Abstract: Pollution by plastics and antibiotics are emerging issues in the areas of the environment and human health. In recent years, several studies have documented the widespread occurrence of plastic particles in various environmental, as well as human, systems, and much research has focused on possible interactions of contaminants with microplastics. Thus, the co-occurrence of plastics and antibiotics has caused another global problem for the environment and human health. Therefore, we focused on the current knowledge in the field of the co-occurrence of plastics and antibiotics to summarize the available studies. In this review, categorization of the topics, contaminants details, such as polymer type, size and source, antibiotic type, and other experimental parameters were summarized and discussed. This study indicated that the sorption of antibiotics on plastics, antibiotic susceptibility in the presence of plastics, and antibiotic resistance gene onto plastics were the most frequently examined categories in this field. Moreover, the variability in the procedures and the processes, and the heterogeneity data of reporting between different studies on similar topic make it difficult to bring all results together and produce a comprehensive picture of the current knowledge. Therefore, it is suggested that further research should be done using this systematic study.

Investigation of Parameters Affecting Rotary Engine by Means of a One Zone Thermodynamic Model

Abstract: The scope of this work was to establish a one zone thermodynamic calculation model to analyze 13B multi side port (MSP) rotary engine on the base of Mazda RX-8. Volume variation was calculated according to the basic geometrical data of the engine and heat transfer was calculated by using the Wilmer's heat transfer coefficient. Combustion process was defined as heat addition according to Vibe function and simultaneously converting fresh charge to combustion products. To account related losses discharge drag, leakage, crevice volumes and mean friction pressure were taken into account. The port fuel injection (homogeneous mixture) was used in the model assumptions. Model calculations were validated with experimental data. Many parameters were investigated in the model such as combustion chamber pressure, mass and engine torque at different speeds and full load conditions. Moreover, the effect of the Vibe parameter, combustion duration and intake port variations on the torque were investigated. The highest torque value was observed in the model with only primary intake port at low rpm (1000 - 3750 rpm), primary and secondary port at mid rpm (3750 - 6250 rpm). Higher torque values were obtained from two secondary and two auxiliaries than primary, secondary and auxiliary in the literature at high rpm (6250 - 8500 rpm). Combustion duration, Vibe parameter and variations of different intake ports has a significant effect on the engine characteristics. The thermodynamic model developed in this study may be used as an effective tool to examine the performance parameters of the Wankel engine.

Multi-criteria decision making for city-scale infrastructure of post-earthquake assembly areas: Case study of Istanbul

Abstract: Assembly areas are first gathering places after earthquakes, and provide temporary sheltering. However if these areas have greater risks after earthquakes, they become more deadly. Current studies commonly look for evacuation shelter and temporary housing location models but most of them are not suited to assembly areas. This study aims to determine safe post-earthquake assembly areas by using the multi-criteria decision-making approach through an analytical hierarchy process using a geographical information system. 15 criteria were defined to evaluate the suitability in terms of spatial, natural structure and accessibility of each potential open space for emergency gathering. Following these criteria, possible areas were mapped, evaluated and scored with thematic hazard maps by using geographic information system in a case study to demonstrate the model. Finally, suitability layers were superimposed to estimate the safe assembly areas index and produce the city-scale infrastructure map. As a result, 107 assembly areas were designated for seven neighborhoods in Istanbul. Study results show that not every open area is safe to be a post-earthquake assembly area. The proposed method can provide useful information that could assist in earthquake disaster mitigation, and help government decisionmakers support further location allocation optimization of safe assembly areas.

Unconstrained face mask and face-hand interaction datasets: building a computer vision system to help prevent the transmission of COVID-19

Abstract: Health organizations advise social distancing, wearing face mask, and avoiding touching face to prevent the spread of coronavirus. Based on these protective measures, we developed a computer vision system to help prevent the transmission of COVID-19. Specifically, the developed system performs face mask detection, face-hand interaction detection, and measures social distance. To train and evaluate the developed system, we collected and annotated images that represent face mask usage and face-hand interaction in the real world. Besides assessing the performance of the developed system on our own datasets, we also tested it on existing datasets in the literature without performing any adaptation on them. In addition, we proposed a module to track social distance between people. Experimental results indicate that our datasets represent the real-world's diversity well. The proposed system achieved very high performance and generalization capacity for face mask usage detection, face-hand interaction detection, and measuring social distance in a real-world scenario on unseen data. The datasets are available at https://github.com/iremeyiokur/COVID-19-Preventions-Control-System.

Fabrication and characterization of zein nanofibers integrated with gold nanospheres

Abstract: The synthesis, characterization, and coating effect of zein nanofibers integrated with gold nanospheres were studied. Zein solution including ethanol/liquid gold nanospheres (80/20 v/v) was prepared to produce complex nanofibers. Dielectric constant (ε′), dielectric loss factor (ε′′), and loss tangent (ε′′/ε′) values of feed solutions were evaluated at 300 and 3000 MHz, and electrical conductivity was measured (808.67 ± 2.082 μs/cm). SEM image showed a bead free structure of the gold-zein complex. Zeta potential and DLS measurements (translational diffusion coefficient, hydrodynamic radii, polydispersity index, major axis) were done by dispersing nanofibers in ethanol or water. The stability of nanofiber dispersed in ethanol was higher (+41.73 mV) compared to that of dispersed in water (+5.1 mV). Molecular characterization by FTIR confirmed the formation of the zein-gold complex through a nitrogen-gold coordination bond and electrostatic interactions. The gold-zein nanofibers coating in sea bream fillets reduced 17.8% of total mesophilic bacteria (TMAB) compared to the uncoated group (p < 0.05) after 8 days of observation. The highest changes in ε′ for uncoated (57.65%) and coated samples (14.84%) during storage showed the positive impact of nanofiber treatment. These results showed that zein nanofibers with gold nanospheres could be potentially used as antimicrobial layer for food products. Preparation, characterization, and surface coating of zein nanofibers integrated with gold nanospheres. • Electrospinnability was affected by electrical conductivity and dielectric values. • Binding between gold ion and zein molecules was confirmed by FTIR. • Zein-gold nanofiber stability was studied by zeta potential measurements. • Aggregation behavior of nanofiber in solutions was determined. • The dielectric stability increased after treatment with zein-gold nanofibers.