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Recently, the demand for residence and usage of urban infrastructure has been increased, thereby resulting in the elevation of risk levels of human lives over natural calamities. The occupancy demand has rapidly increased the construction rate, whereas the inadequate design of structures prone to more vulnerability. Buildings constructed before the development of seismic codes have an additional susceptibility to earthquake vibrations. The structural collapse causes an economic loss as well as setbacks for human lives. An application of different theoretical methods to analyze the structural behavior is expensive and time-consuming. Therefore, introducing a rapid vulnerability assessment method to check structural performances is necessary for future developments. The process, as mentioned earlier, is known as Rapid Visual Screening (RVS). This technique has been generated to identify, inventory, and screen structures that are potentially hazardous. Sometimes, poor construction quality does not provide some of the required parameters; in this case, the RVS process turns into a tedious scenario. Hence, to tackle such a situation, multiple-criteria decision-making (MCDM) methods for the seismic vulnerability assessment opens a new gateway. The different parameters required by RVS can be taken in MCDM. MCDM evaluates multiple conflicting criteria in decision making in several fields. This paper has aimed to bridge the gap between RVS and MCDM. Furthermore, to define the correlation between these techniques, implementation of the methodologies from Indian, Turkish, and Federal Emergency Management Agency (FEMA) codes has been done. The effects of seismic vulnerability of structures have been observed and compared.

Determining the risk priorities for the building stock in highly seismic-prone regions and making the final decisions about the buildings is one of the essential precautionary measures that needs to be taken before the earthquake. This study aims to develop an Artificial Neural Network (ANN)-based model to predict risk priorities for reinforced-concrete (RC) buildings that constitute a large part of the existing building stock. For this purpose, the network parameters in the network structure have been optimized by establishing a hybrid structure with the Genetic Algorithm (GA). As a result, the ANN model can make accurate predictions with maximum efficiency. The suggested ANN model is a feedforward back-propagation network model. It aims to predict the risk priorities for 329 RC buildings in the most successful way, for which the performance score was calculated using the Turkey Rapid Evaluation Method (2013). In this paper, a GA-ANN hybrid model was implemented in which the ANN, using the most successful gene revealed by the model, produced successful results in calculating the performance score. In addition, the required input parameters for obtaining more efficient results in solving such a problem and the parameters that need to be used in establishing such an ANN network structure have been optimized. With the help of such a model, the operation process will be eliminated. The created hybrid model was 98% successful in determining the risk priority in RC buildings.

The hazardous effects of pollutants from conventional fuel vehicles have caused the scientific world to move towards environmentally friendly energy sources. Though we have various renewable energy sources, the perfect one to use as an energy source for vehicles is hydrogen. Like electricity, hydrogen is an energy carrier that has the ability to deliver incredible amounts of energy. Onboard hydrogen storage in vehicles is an important factor that should be considered when designing fuel cell vehicles. In this study, a recent development in hydrogen fuel cell engines is reviewed to scrutinize the feasibility of using hydrogen as a major fuel in transportation systems. A fuel cell is an electrochemical device that can produce electricity by allowing chemical gases and oxidants as reactants. With anodes and electrolytes, the fuel cell splits the cation and the anion in the reactant to produce electricity. Fuel cells use reactants, which are not harmful to the environment and produce water as a product of the chemical reaction. As hydrogen is one of the most efficient energy carriers, the fuel cell can produce direct current (DC) power to run the electric car. By integrating a hydrogen fuel cell with batteries and the control system with strategies, one can produce a sustainable hybrid car.

Inducer is an important device which is mounted upstream of the inlet to the main impeller of the centrifugal pump and rotates at the same rotational speed as the impeller. The main purpose of the inducer is to improve the suction performance of the pump, but this improvement is dependent on the geometrical parameters of the inducer. Therefore, it is essential to optimize these parameters. In the present study, the performance of an inducer is optimized by considering the inlet tip blade angle, the outlet tip blade angle, and the ratio of the outlet hub radius to inlet hub radius as design variables and the head coefficient, the hydraulic efficiency, and the required net positive suction head (NPSHR) as objective functions. The inducer performance is simulated using 3-D computational fluid dynamics (CFD) and compared with experimental data, which shows the validity of the used method and assumptions. Then the group method of data handling (GMDH) algorithm is used to model the objective functions with respect to design variables. Using the modified non-dominated sorting genetic algorithm II (NSGA-II) approach, Pareto fronts are then plotted and trade-off optimum points are obtained using the technique for order of preference by similarity to ideal solution (TOPSIS). Using multi-objective optimization, the head coefficient, the hydraulic efficiency, and NPSHR are improved 14.3%, 0.3%, and 30.2%, respectively. Recommended design points unveil significant optimum design principles that can be obtained only by using a multi-objective optimization approach.

Space frame structures satisfy the ever-increasing requirements of societies for providing a variety of structural forms and architectural spaces with special characteristics, such as aesthetic and free-form features, population-wise capacities, and structural performance, among others. Structural behavior of these systems largely depend on the type of joints and their components which are to be considered appropriately in design and analysis. Screws comprise one of the key components of joints in these structures and play a pivotal role in the total cost of the structure, as well as the maximum stress level created in joints. The present study aims to evaluate the effect of screw size on the maximum stress generated in three MERO double-layer ball joints with diameters of 98, 110, and 132 mm as a sample numerical analysis case to pinpoint this fact. Numerical simulations were conducted using ANSYS workbench software. Based on the results, in order to achieve the maximum factor of safety (FOS), the minimum stress, and keeping the total construction cost optimal, it is recommended to use M16, M20, and M24 screws for the ball joints of diameters 98, 110, and 132 mm, respectively.

Data from past earthquakes is an important tool to reveal the impact of future earthquakes on engineering structures, especially in earthquake-prone regions. These data are important indicators for revealing the seismic loading effects that structures will be exposed to in future earthquakes. Five different earthquakes from six countries with high seismic risk were selected and were within the scope of this study. The measured peak ground acceleration (PGA) for each earthquake was compared with the suggested PGA for the respective region. Structural analyzes were performed for a reinforced-concrete (RC) building model with four different variables, including the number of storeys, local soil types, building importance class and concrete class. Target displacements specified in the Eurocode-8 were obtained for both the suggested and measured PGA values for each earthquake. The main goal of this study is to reveal whether the proposed and measured PGA values are adequately represented in different countries. We tried to reveal whether the seismic risk was taken into account at a sufficient level. In addition, target displacements have been obtained separately in order to demonstrate whether the measured and suggested PGA values for these countries are adequately represented in structural analysis and evaluations. It was concluded that both seismic risk and target displacements were adequately represented for some earthquakes, while not adequately represented for others. Comments were made about the existing building stock of the countries considering the obtained results.

In this paper, various modern power engines developed by the American, Japanese, and European automobile industries will be compared. Specific data, including the efficiency, emission rate of nitrogen oxides (NOx), fuel consumption, and electronic vehicle technology, will be developed. Since the first invention of the automobile engine in the late 19th century, companies came up with unique innovations, including its structure, control systems, and additional mechanical installations to improve efficiency and reduce emissions. Numerous companies, including Ford, Toyota, and Mercedes-Benz, compete in the automobile industry to improve their engine’s efficiency and emission rates to create a clean environment. In addition, each country has its regulations on emission rates and automobile structure. Therefore, to meet these regulations, the structure and the system of the engines vary between companies in different countries. A variety of variable valve timing (VVT) systems, which is a mechanical part installed in the engine, are being developed by several companies. The VVT controls the opening and closing of the air inlet valve and the exhaust valve, which improves the reduction of fuel consumption and thermal efficiency. Furthermore, changing the engine structure is also another method that automobile companies are developing. Changing the engine’s shape can improve the vehicle’s performance (e.g., the engine vibration while running, the power output, and the smoothness of driving). Due to the emissions caused by petrol and diesel engines, the electrified vehicles have been developing to achieve a cleaner environment. This includes battery electric vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, and fuel cell electric vehicles. By comparing these features in the engine, it is possible to understand what the companies in the US, Japan, and the European countries are working on to improve their engines and provide a clean environment.

In small-scale combustors, the ratio of area to the combustor volume increases and hence heat loss from the combustor’s wall is significantly enhanced and flame quenching occurs. To solve this problem, non-premixed vortex flow is employed to stabilize flames in a meso-scale combustion chamber to generate small-scale power or thrust for propulsion systems. In this experimental investigation, the effects of thermal recuperation on the characteristics of asymmetric non-premixed vortex combustion are studied. The exhaust gases temperature, emissions and the combustor wall temperature are measured to evaluate thermal and emitter efficiencies. The results illustrate that in both combustors (with/without thermal recuperator), by increasing the combustion air mass flowrate, the wall temperature increases while the wall temperature of combustor with thermal recuperator is higher. The emitter efficiency calculated based on the combustor wall temperature is significantly increased by using thermal recuperator. Thermal efficiency of the combustion system increases up to 10% when thermal recuperator is employed especially in moderate Reynolds numbers (combustion air flow rate is 120 mg/s).

This paper presents an experimental investigation of the combustion characteristics of palm methyl ester (PME), also known as palm oil-based biodiesel, in an oil burner system. The performance of conventional diesel fuel (CDF) and various percentages of diesel blended with palm oil-based biodiesel is also studied to evaluate their performance. The performance of the various fuels is evaluated based on the temperature profile of the combustor’s wall and emissions, such as nitrogen oxides (NOx) and carbon monoxide (CO). The combustion experiments were conducted using three different oil burner nozzles (1.25, 1.50 and 1.75 USgal/h) under lean (equivalence ratio (Φ) = 0.8), stoichiometric (Φ = 1) and rich fuel (Φ = 1.2) ratio conditions. The results show that the rate of emission formation decreases as the volume percent of palm biodiesel in a blend increases. PME combustion tests present a lower temperature inside the chamber compared to CDF combustion. High rates of NOx formation occur under lean mixture conditions with the presence of high nitrogen and sufficient temperature, whereas high CO occurs for rich mixtures with low oxygen presence.

The aggregation of clonal plasma cells causes plasma cell neoplasms, which vary in severity and clinical outcomes. The present research focused on the epidemiological, clinical, immunologic, and cytogenetic characteristics of plasma cell neoplasms. In this five-year retrospective cross-sectional study, demographic information such as age and sex, calcium elevation, renal insufficiency, anemia, and bone lesion (CRAB) characteristics, as well as laboratory data including bone marrow and peripheral blood film results, immunohistochemistry, flow cytometry, and cytogenetic study outcomes were collected at Shiraz University of Medical Sciences, Shiraz, Iran. The collected data were analyzed using SPSS Statistics software (version 20.0). Descriptive statistics were reported as numbers, percentages, and mean±SD. 417 newly diagnosed plasma cell neoplasm patients were confirmed by bone marrow or other tissue biopsy tests. 279 patients were men (66.9%). The most prevalent age group was 60-64 years old (18.46%). Plasma cell myeloma (PCM) affected 355 (85.13%) patients, while monoclonal gammopathy of undetermined significance (MGUS) affected 6 (1.43%) patients. Solitary plasmacytoma was seen in 56 (13.42%) patients. At the time of diagnosis, 119 (33.52%) of 355 PCM patients were asymptomatic, whereas 236 (66.47%) patients had at least one CRAB symptom, 55 (15.49%) had two or more, and 14 (3.94%) had three or more. There were 7 (1.97%) cases of amyloidosis. Cytogenetic abnormalities were found in 51.28% (40/78) of the patients. Twenty-one individuals (52.5%) were hyperdiploid with multiple trisomy, while 19 (47.50%) were not. When diagnosed, Iranian PCM patients might have more advanced disease. PCM was more prevalent in young adults, and hyperdiploid was the most common cytogenetic finding in this investigation.