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In recent years, higher penetrations of renewable energy generations helped persuade sustainable energy and environmental targets, although their intermittent and fluctuated nature raised technical challenges. However, hybrid power system can minimize these technical issues by integrating flexible generation capable renewable energy sources like biomass. This study deals with optimizing gridintegrated and stand-alone biomass-based hybrid power system for the energy demand of a rural region containing poultry farms. Besides solar and wind energy, energy storage integration is evaluated regarding overall technical-environmental-economic performance, considering the actual manure potential using HOMER Pro. In addition, sensitivity analyses are performed, considering the estimated load and inflations using an artificial neural network method. Using biomass and solar hybrid options offers more autonomous, environmentally friendly, and economic advantages. Biomass-based hybrid power system with solar energy reduced net present cost by around 12% and increased renewable fraction by 7%, and grid-connected options can provide 88.9% renewable fraction. In addition, the energy storage integration increased renewable fraction by around 10% and reduced excess energy by 16%. The proposed biomass-based hybrid power system achieves cost-effective sizing of solar or wind-based hybrid systems, empowers the reliability of renewable energy and presents good consistency of decarbonization targets.

The main outdoor factors that reduce the efficiency of the photovoltaic (PV) panel are the reflection and refraction of light, dirt, dust, and organic waste accumulating on the panel surface. In this article, an antireflection, self-cleaning coating was applied on the PV panel cover glass with a new method. With the coating, the surface has been given a hydrophobic feature. As a coating method, a 3-D printer has not been seen in the literature and used as a new method. The electrospinning method has also been tried as an alternative method. Solutions in different combinations were developed using polylactic acid or polymethylmethacrylate polymer, chloroform ($\text{CHCl}_3$) as a solvent, and silicon dioxide ($\text{SiO}_2$) and titanium dioxide ($\text{TiO}_2$) nanoparticles as primary materials in a modified 3-D printer for bioprinting. Five PV panels were obtained by applying different 3-D parameters from three solutions, which have the best results. Coating thicknesses are in the range of 3.12-8.47 mu m. Coated and uncoated PV panels were tested in outdoor conditions for ten-day periods. The power outputs of the PV panels were measured, and their ten-day average efficiency was presented. According to the results, the highest efficiency increase is 8.7%. The highest light transmittance is 88.2% at 550 nm. In addition, hydrophobic properties were observed on all surfaces and the water contact angle was measured as 96.18 degrees.

Injecting hydrogen into the natural gas network to reduce CO2 emissions in the EU residential sector is considered a critical element of the zero CO2 emissions target for 2050. Burning natural gas and hydrogen mixtures has potential risks, the main one being the flame flashback phenomenon that could occur in home appliances using premixed laminar burners. In the present study, two-dimensional transient computations of laminar CH4- + air and CH4 + H-2 + air flames are performed with the open-source CFD code OpenFOAM. A finite rate chemistry based solver is used to compute reaction rates and the laminar reacting flow. Starting from a flame stabilized at the rim of a cylindrical tube burner, the inlet bulk velocity of the premixture is gradually reduced to observe flashback. The results of the present work concern the effects of wall temperature and hydrogen addition on the flashback propensity of laminar premixed methane-hydrogen-air flames. Complete sequences of flame dynamics with gradual increases of premixture velocity are investigated. At the flame flashback velocities, strong oscillations at the flame leading edge emerge, causing broken flame symmetry and finally flame flashback. The numerical results reveal that flashback tendency increase with increasing wall temperature and hydrogen addition rate. (C) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which emerged in 2019, cut the epoch that will make profound fluctuates in the history of the world in social, economic, and scientific fields. Urgent needs in public health have brought with them innovative approaches, including diagnosis, prevention, and treatment. To exceed the coronavirus disease 2019 (COVID-19) pandemic, various scientific authorities in the world have procreated advances in real time polymerase chain reaction (RT-PCR) based diagnostic tests, rapid diagnostic kits, the development of vaccines for immunization, and the purposing pharmaceuticals for treatment. Diagnosis, treatment, and immunization approaches put forward by scientific communities are cross-fed from the accrued knowledge of multidisciplinary sciences in health biotechnology. So much so that the pandemic, urgently prioritized in the world, is not only viral infections but also has been the pulsion in the development of novel approaches in many fields such as diagnosis, treatment, translational medicine, virology, microbiology, immunology, functional nano- and bio-materials, bioinformatics, molecular biology, genetics, tissue engineering, biomedical devices, and artificial intelligence technologies. In this review, the effects of the COVID-19 pandemic on the development of various scientific areas of health biotechnology are discussed.

© 2023 by the authors.The important parts of a transformer, such as the core, windings, and insulation materials, are in the oil-filled tank. It is difficult to detect faults in these materials in a closed area. Dissolved Gas Analysis (DGA)-based fault diagnosis methods predict a fault that may occur in the transformer and take the necessary precautions before the fault grows. Although these fault diagnosis methods have an accuracy of over 95%, their validity is controversial since limited data are used in the studies. The success rates and reliability of fault diagnosis methods in transformers, one of the most important pieces of power systems equipment, should be increased. In this study, a hybrid fault diagnosis system is designed using DGA-based methods and Fuzzy Logic. A mathematical approach and support vector machines (SVMs) were used as decision-making methods in the hybrid fault diagnosis systems. The results of tests performed with 317 real fault data sets relating to transformers showed accuracy of 95.58% using a mathematical approach and 96.23% using SVMs.

Enerji; yaşamımızda en çok duyduğumuz ve kullandığımız kavramlardan biri olmakla beraber, günümüzde sosyal, ekonomik, teknolojik ve çevresel yönleriyle ele alınan ve değerlendirilen çok geniş bir kapsama sahiptir. Kavram olarak günlük yaşamda farklı kullanımları ve birçok disiplinde farklı tanımlamaları vardır. Günlük yaşamda kullandığımız enerji kavramı, kullanıma göre farklı büyüklüklerin oluşmasına neden olur. Bu büyüklükleri bilmek ve yaşamımızın içerisinde bilinçli olarak kullanmak, hem topluma hem de bireylere ekonomik ve çevresel faydalar sağlayacağı bir gerçektir. Bu kapsamda toplumun tüm eğitim seviyelerinde okul öncesinden başlayarak, yaşam boyu öğrenme süreci ile enerji okuryazarlığı kavramı ele alınmalı ve geliştirilmelidir. Böylece bireylerin günlük kullanımlarında farklı bakış açıları ve gelişim süreci elde edebilir.Enerji teknolojileri; enerjinin üretiminden tüketimine kadar birçok alt sistem ve bileşeni kapsamaktadır. Çok büyük etki alanına sahip olan enerjinin üretim-tüketim sürecinde sürdürebilir yaşamı desteklemek, ekonomik ve teknolojik olmak gibi birçok ölçüt öne çıkmaktadır. Bu kapsamda enerji teknolojilerinin yenilenmesi, genel olarak mevcut teknolojileri iyileştirmek veya yenilerini oluşturmak olarak ifade edilmektedir. Uzun vadeli olarak enerji teknolojileri üzerine yapılan araştırmalarda ve istihdamda uluslararası literatürdeki çalışmaların kapsamında en önemli üç başlık; enerji verimliliği, enerji depolanması ve yenilenebilir enerji kaynakları olarak ifade edilmektedir. Bu temel alanlar öğrencilerimizin yönlendirilmesi açısından önemlidir.Sunulan bu çalışmayla öğretmenler, enerji teknolojileri başlığı altında öncelikle öğrencilerin enerji kavramından başlayarak, enerji okuryazarlığı ve sürdürülebilir yaşamı destekleme süreçlerini kavramaları hedeflemelidir. Bu çerçevede çalışmada ilk olarak enerji kavramının tanımı, büyüklük olarak anlamı, dönüşümü, enerji verimliliği konuları yer almaktadır. Sonraki aşamada ise, enerji teknolojilerinin üretim süreçleri ele alınmaktadır. Böylece geleneksel ve yenilenebilir enerji kaynakları üzerine enerji teknolojileri ifade edilmektedir. Özellikle çalışmada rüzgâr ve güneş bazlı yenilenebilir enerji üretim teknolojileri detaylı olarak sunulmaktadır. Son olarak, günümüzde enerji teknolojilerinin en önemli parçası haline gelen enerji depolama sistemleri üzerine bir bölüm çalışma içinde bulunmaktadır. Bu çalışma, öğretmenlere \"Dene ve Yap\" öğrenme süreci içerisinde öğrencilerin konuları ele alması yaklaşımıyla oluşturulmuştur. Özellikle deney sürecinde öğrencinin karşılaşacağı sorunlara vereceği çözümler, değişkenlerin belirlemesi ve nasıl değişeceği gibi fikirler, yaparak ve yaşayarak öğrenme sürecini oluşturması bu çalışmanın istenen aşamalarıdır. Enerji teknolojileri başlığı altında verilen bu çalışma diğer Deneyap başlıklarından farklı olarak, konunun içeriği ve farklılığı nedeniyle öğrencilerin en yüksek düzeyde anlama ve kavrama sağlamak hedefi ile 5E öğretim yöntemi kullanılarak tasarlanmıştır. Bu çalışmanın 5E öğrenme döngüsü modeli ile öğrencilerin araştırma sorgulamaya teşvik etmesi hedeflenmektedir.Böylece \"Enerji Teknolojileri\" başlığı altında mühendisliğin temel konularına odaklanılarak, enerji kavramı üzerine açıklama ve tanımlamalar yapılması sağlanacaktır. Analitik bir çerçevede enerji kavramını açık bir şekilde öğretmek, disiplinler arası sorunlar hakkında düşünmesini sağlamak iyi donanımlı yeni nesil bilim insanları ve mühendisler yetiştirmeye yardımcı olacaktır.

Enerji; yaşamımızda en çok duyduğumuz ve kullandığımız kavramlardan biri olmakla beraber, günümüzde sosyal, ekonomik, teknolojik ve çevresel yönleriyle ele alınan ve değerlendirilen çok geniş bir kapsama sahiptir. Kavram olarak günlük yaşamda farklı kullanımları ve birçok disiplinde farklı tanımlamaları vardır. Günlük yaşamda kullandığımız enerji kavramı, kullanıma göre farklı büyüklüklerin oluşmasına neden olur. Bu büyüklükleri bilmek ve yaşamımızın içerisinde bilinçli olarak kullanmak, hem topluma hem de bireylere ekonomik ve çevresel faydalar sağlayacağı bir gerçektir. Bu kapsamda toplumun tüm eğitim seviyelerinde okul öncesinden başlayarak, yaşam boyu öğrenme süreci ile enerji okuryazarlığı kavramı ele alınmalı ve geliştirilmelidir. Böylece bireylerin günlük kullanımlarında farklı bakış açıları ve gelişim süreci elde edebilir.Enerji teknolojileri; enerjinin üretiminden tüketimine kadar birçok alt sistem ve bileşeni kapsamaktadır. Çok büyük etki alanına sahip olan enerjinin üretim-tüketim sürecinde sürdürebilir yaşamı desteklemek, ekonomik ve teknolojik olmak gibi birçok ölçüt öne çıkmaktadır. Bu kapsamda enerji teknolojilerinin yenilenmesi, genel olarak mevcut teknolojileri iyileştirmek veya yenilerini oluşturmak olarak ifade edilmektedir. Uzun vadeli olarak enerji teknolojileri üzerine yapılan araştırmalarda ve istihdamda uluslararası literatürdeki çalışmaların kapsamında en önemli üç başlık; enerji verimliliği, enerji depolanması ve yenilenebilir enerji kaynakları olarak ifade edilmektedir. Bu temel alanlar öğrencilerimizin yönlendirilmesi açısından önemlidir.Sunulan bu çalışmayla öğretmenler, enerji teknolojileri başlığı altında öncelikle öğrencilerin enerji kavramından başlayarak, enerji okuryazarlığı ve sürdürülebilir yaşamı destekleme süreçlerini kavramaları hedeflemelidir. Bu çerçevede çalışmada ilk olarak enerji kavramının tanımı, büyüklük olarak anlamı, dönüşümü, enerji verimliliği konuları yer almaktadır. Sonraki aşamada ise, enerji teknolojilerinin üretim süreçleri ele alınmaktadır. Böylece geleneksel ve yenilenebilir enerji kaynakları üzerine enerji teknolojileri ifade edilmektedir. Özellikle çalışmada rüzgâr ve güneş bazlı yenilenebilir enerji üretim teknolojileri detaylı olarak sunulmaktadır. Son olarak, günümüzde enerji teknolojilerinin en önemli parçası haline gelen enerji depolama sistemleri üzerine bir bölüm çalışma içinde bulunmaktadır. Bu çalışma, öğretmenlere \"Dene ve Yap\" öğrenme süreci içerisinde öğrencilerin konuları ele alması yaklaşımıyla oluşturulmuştur. Özellikle deney sürecinde öğrencinin karşılaşacağı sorunlara vereceği çözümler, değişkenlerin belirlemesi ve nasıl değişeceği gibi fikirler, yaparak ve yaşayarak öğrenme sürecini oluşturması bu çalışmanın istenen aşamalarıdır. Enerji teknolojileri başlığı altında verilen bu çalışma diğer Deneyap başlıklarından farklı olarak, konunun içeriği ve farklılığı nedeniyle öğrencilerin en yüksek düzeyde anlama ve kavrama sağlamak hedefi ile 5E öğretim yöntemi kullanılarak tasarlanmıştır. Bu çalışmanın 5E öğrenme döngüsü modeli ile öğrencilerin araştırma sorgulamaya teşvik etmesi hedeflenmektedir.Böylece \"Enerji Teknolojileri\" başlığı altında mühendisliğin temel konularına odaklanılarak, enerji kavramı üzerine açıklama ve tanımlamalar yapılması sağlanacaktır. Analitik bir çerçevede enerji kavramını açık bir şekilde öğretmek, disiplinler arası sorunlar hakkında düşünmesini sağlamak iyi donanımlı yeni nesil bilim insanları ve mühendisler yetiştirmeye yardımcı olacaktır.

Gemilerin çoğunda elektrik enerjisi ihtiyacı dizel jeneratör grupları ile karşılanmaktadır. Gemilerin türüne bağlı olarak gemilerde farklı sayılarda ve kapasitelerde jeneratör grupları bulunabilir. Gemilerde elektrik enerjisi ihtiyacının birden fazla jeneratör ile karşılanması durumunda diğer jeneratörün senkronize bir şekilde devreye alınması gerekmektedir. Bu süreç hem otomatik hem de manuel olarak yürütülebilmektedir. Bu çalışmada, bir gemide iki jeneratörün senkronizasyon süreci Matlab&Simulink programında bir benzetim çalışması yapılarak incelenmiştir. Sonrasında, senkronizasyon sürecinde jeneratör baralarındaki elektriksel parametrelerin değişimleri yorumlanmıştır. Bu çalışma ile özellikle gemi personelinin senkronizasyon süreci hakkında teorik bilgi edinmesi ve literatüre gemi elektriği alanında katkı sunulması amaçlanmıştır. The electrical energy needs of ships are generally met by diesel generator sets. Depending on the type of ships, there may be different numbers and capacities of generator sets on the ships. If the electrical energy needs of ships are met by more than one generator, the other generator should be activated in a synchronized manner. This process can be carried out both automatically and manually. In this study, the synchronization process of two generators on a ship was performed by making a simulation study in Matlab&Simulink. Then, the changes in the electrical parameters in the generator busbars during the synchronization process were interpreted. With this study, it is aimed to obtain theoretical knowledge about the synchronization process of ship personnel and to contribute to the literature in the field of ship electricity.

In this research, the advantages of the e-scooter tool used in the mail or package delivery process were discussed by considering the Turkish Post Office (PTT) data in the districts of Istanbul (Kadıköy, Üsküdar, Kartal, and Maltepe) in Turkey. The optimization Poisson regression model was utilized to deliver the maximum number of packages or mails with minimum cost and the shortest time in terms of energy consumption, cost, and environmental contribution. Statistical and optimization results of dependent and independent variables were calculated using numerical and categorical features of 100 e-scooter drivers. The Poisson regression analysis determined that the e-scooter driver’s gender (p|0.05 < 0.199) and age (p|0.05 < 0.679) factors were not effective on the dependent variable. We analysed that the experience in the profession (tenure), the size of the area responsible, and environmental factors is effective in the e-scooter distribution activity. The number of packages delivered was 234 in a day, and the delivery cost per package was calculated as 0.51 TL (Turkish Lira) for the optimum values of the dependent variables. The findings show that the choice of e-scooter vehicle in the mail or package delivery process is beneficial in terms of time, cost, energy, and environmental contribution in districts with higher population density. As the most important result, the operation of e-scooter vehicles with electrical energy shows that it is environmentally friendly and has no CO2 emission. The fact that the distribution of packages or mail should now turn to micro-mobility is emerging with the advantages of e-scooter vehicles in the mail and package delivery. Finally, this analysis aims to provide a model for integrating e-scooters in package or mail delivery to local authorities, especially in densely populated areas.

Solar energy has increased in its share of global electrical energy production. The increasing reliability of solar energy has positively affected the sustainability of photovoltaic (PV) power plants. A failure in any module in the plant can reduce or interrupt the production of electrical energy, causing significant losses in both efficiency and asset value. Therefore, responding to a fault as quickly as possible in a PV power plant is critical. The ability of the PV plant operator to react to potential faults is directly related to the rapid detection of faulty modules. In this paper, different PV monitoring systems in the literature are investigated extensively from the point of view of the devices and the techniques used to measure PV systems\" current, voltage, solar radiation, and module temper-ature. In particular, the communication methods and data acquisition cards used in monitoring were examined. Remote monitoring technologies quickly detect the location of a malfunction in a large-scale power plant. In this context, traditional wire communication methods, today\"s communication technologies, and the low-cost IoT (Internet of Things) technologies used to monitor the performance of large and small-scale PV power plants are compared in detail. With the advancement of Internet of Things technologies such as Zigbee and LoRa, research on remote wireless monitoring of photovoltaic modules has accelerated in recent years. These technologies are projected to be widely deployed in the near future for the maintenance and fault detection of numerous photovoltaic installations.

In this study, a laboratory-scale cooling system, simulating a household refrigerator, was examined experimentally for an average cabinet temperature of 4 degrees C with two different types of phase change materials (PCMs) (water and eutectic solution). The system was tested with various amounts of water and different concentrations of sodium sulfate (Na2SO4) in water. The influence of different amounts and types of the PCMs on the cabinet air temperature and compressor power consumption was analyzed during the running period. The cabinet air temperature change over time was also observed during the power failure period. The examinations suggest using 1.0 wt.% Na2SO4 solution as the PCM in the cooling systems. This solution provides the lowest energy consumption (19.5 kJ), and the running time percentage (21.7%); while maximizing the energy saving (14.2%). In addition, integrating it as PCM could allow preserving products for long periods without significant quality loss during a power failure; because it prevented the rapid increase of the cabinet air temperature in this scenario. Lastly, when the cycle frequency is considered, it has the best time interval and the number of cycles (5.3). Thus, it has a positive effect on reducing the compressor cycling frequency, which eventually increases the compressor lifespan.

In this study, the Aspen Plus simulator was used to develop a circulating fluidized bed (CFB) gasifier/steam turbine/proton-exchange membrane (PEM) fuel cell integrated system. Since integrated systems comprise many thermochemical, biochemical, and physical processes, equipment, chemicals, etc., determining output parame-ters is challenging and important. In this context, twenty torrefied biomass samples were parametrically analyzed for syngas properties and H2 production rates. So, using solid fuel characteristics and gasifier operating parameters, a data set including PEM fuel cell module outputs was created. Thereafter, the created data set was utilized to train the artificial neural network (ANN) model. This paper, as far as we know, examines the impacts of different torrefied biomass samples on PEM fuel cell outputs for a sophisticated integrated system dependent on gasification conditions, and provides a more generalized and rapid prediction model for the integrated system with complicated equations. Additionally, parametric studies assist in determining the proposed new integrated system\"s minimal operating condition, which is highly dependent on the fuel characteristic. High steam/fuel ratio, high carbonization degree, and low pressure lowered PEM efficiency while increasing power and voltage outputs. The ANN model also accurately forecasts PEM fuel cell output parameters (R-2 greater than 0.99 and MAPE less than 1%) based on torrefied biomass proximate analysis data and gasification process operating parameters. As a consequence, a CFB gasifier/steam turbine/PEM fuel cell system, which contains diverse modules and thermochemical processes, can be examined using ANN models trained on a large and high-quality dataset.

The rapid increase in the world population along with the rising trend of global economic growth triggers serious problems related to energy consumption. In this regard, a comprehensive analysis of the current and potential energy situation in the light of demographic trends, main economic indicators, technical conditions, social and environmental concerns has become a significant issue for developing well-planned global and regional energy strategies. In this study, a multi-objective decision-making model is constructed for renewable energy planning to determine the most appropriate resource diversity for Turkey by focusing on five renewable energy sources, namely solar, wind, geothermal, hydroelectric, and biomass. There are four objective functions presented in the proposed multi-objective model including maximization of the technical score of regions, maximization of the job creation, maximization of the environmental score, and minimization of the cost. As a solution methodology, a two-phase fuzzy goal programming approach is performed. The proposed model is solved using LINGO software as a comprehensive solver for model optimization. The appropriateness of the proposed method is analyzed by comparing it with other multi-objective methods. Results reveal that the majority of the energy demand should be met via solar and hydroelectric energies for the satisfaction of the indicated objectives. (c) 2022 Elsevier Ltd. All rights reserved.

The use of energy storage systems (ESS) and distributed generators (DGs) to improve reliability is one of the solutions that has received much attention from researchers today. In this study, we utilize a multi-objective optimization method for optimal planning of distributed generators in electric distribution networks from the perspective of multi-objective optimization. The objective is to improve the reliability of the network while reducing the annual cost and network losses. A modified version of the multi-objective sine–cosine algorithm is used to determine the optimal size, location, and type of DGs and the optimal capacity, location, and operation strategy of the ESS. Three case studies of IEEE 33-bus, 69-bus and 141-bus test systems with Turkish DG and load data were conducted to validate the effectiveness of the proposed approach. The distribution of the Pareto front solutions and the optimal objective functions are compared with the other known algorithms. The simulation results show that the average energy not supplied and annual energy losses for the test systems are reduced by up to 68% and 64%, respectively. Moreover, the Pareto fronts of the proposed method show a better distribution and dominate those obtained by MOGWO, MOSMA, NSGA-II, MOPSO and MOEA-D according to three different Pareto optimization metrics. Finally, the computational effort result shows faster convergence of MOSCA compared to MOGWO, MOSMA, NSGA-II, MOPSO and MOEAD.

Tedious trial-and-error procedures are commonly practiced for surface modification of the perovskite solar cell (PSC) active layers. A guideline to rationally choose the passivating functional groups of the polymeric structure that is eminently effective in passivating the charged defects and elongating the device lifetime is hence in urgent demand. Herein, three prototypical polymers, poly(vinyl acetate) (PVA), polyethylene glycol (PEG), and poly(9-vinylcarbazole) (PVK), are selected to investigate the structural effect of the polymeric modification agents on the PSCs. We found that PVA possesses the Lewis base functional group with the minimized steric hindrance and the strongest electron-donating ability, enabling the most effective defect passivation on the perovskite film surface and the most enhanced carrier diffusion capacity. It demonstrates a power conversion efficiency (PCE) of 23.20% and noticeably enhanced operational stability. Our work provides important insights toward the selection of polymeric modification agents for high-performance and long-term stable PSCs.

Two methods for estimating the near-optimal positions and sizes of capacitors in radial distribution networks are presented. The first model assumes fixed-size capacitors, while the second model assumes controllable variable-size capacitors by changing the tap positions. In the second model, we limit the number of changes in capacitor size. In both approaches, the models consider many load scenarios and aim to obtain better voltage profiles by minimizing voltage deviations and active power losses. We use two recently developed heuristic algorithms called Salp Swarm Optimization algorithm (SSA) and Dragonfly algorithm (DA) to solve the proposed optimization models. We performed numerical simulations using data by modifying an actual distribution network in Almaty, Kazakhstan. To mimic various load scenarios, we start with the baseline load values and produce random variations. For the first model, the optimization algorithms identify the near-optimal positioning and sizes of fixed-size capacitors. Since the second model assumes variable-size capacitors, the algorithms also decide the tap positions for this case. Comparative analysis of the heuristic algorithms shows that the DA and SSA algorithms give similar results in solving the two optimization models: the former gives a slightly better voltage profile and lower active power losses.

The baffle plate is the most important elements affecting not only the thermal efficiency but also the hydraulic performance of shell-tube heat exchangers that can be designed in different types today and can be put into the production phase. Different designs of baffle plates are closely related to thermal performance with pressure drop as well. In this investigation, the design geometry of the shell-tube type was carried out by means of the ANSYS Fluent program.In the analyses, it is purposed to examine the consequences on the heat transfer rate per drop of pressure and not only the pressure’s drop but also the coefficient parameter of heat transfer of the exchangers in which traditional one-piece type baffle plate and perforated type baffle plate are used where the shell side. Here, water is used as the working fluid; it was examined as 1.2, 1.5, 1.8 and 2.1kg/h at four varied mass flow rates (m). As a result, the values compared to the traditional one-piece baffle plate and the perforated type baffle plate. It has been monitored that the heat transfer rates per drop of pressure vary

Gasification provides various environmental and technological advantages, and the efficiency of the gasification system is affected by several factors, including the kind of fuel and gasification agent used, the gasifier\"s length and diameter, the operating pressure and temperature, etc. Experimental optimization approaches are more realistic, but they are time demanding; also, a reactor operating at high temperatures and pressures could be dangerous and expensive. Thus, researchers use a variety of modeling techniques, including the process simulators. Additionally, artificial neural network (ANN) as a machine learning approach, which is one of the process modeling methods, is a remarkable approach, and several papers have been published in which it has been utilized in combination with other modeling techniques. On the other hand, a combined process simulator/ANN model that considers gasifier design/operational parameters for the kinetic modeling of gasification process has not been reported. In this study, after kinetic modeling and validation of seven different circulating fluidized gasifiers using Aspen Plus, parametric studies were performed. Parametric analysis was used to examine the impacts of gasifier diameter, length, gasifier temperature, air/fuel ratio, and fuel type, and a dataset was created for ANN training. The syngas composition and thermal value were predicted using the ANN model. Therefore, a model was developed that takes into consideration both design and operating variables. The investigations revealed that heterogeneous reactions were the most critical factor in defining syngas characteristics. Although design factors have a considerable impact on syngas characteristics, the gasifier temperature is a key factor in the whole process. Furthermore, the ANN model estimates syngas specifications with great accuracy (R2 > 0.99 and MAPE < 3%) based on fuel attributes and gasifier design/operating parameters. Hence, ANN models can be used to analyze the effectiveness of systems including a complex combination of reactions and thermochemical processes.