Computation of Compressive Strength of GGBS Mixed Concrete using Machine Learning

Concrete is a composite material formed by cement, water, and aggregate. Concrete is an important material for any Civil Engineering project. Several concretes are produced as per the functional requirements using waste materials or by-products. Many researchers reported that these waste materials or by-products enhance the concrete properties, but the laboratory procedures for determining the concrete properties are time-consuming. Therefore, numerous researchers used statistical and artificial intelligence methods for predicting concrete properties. In the present research work, the compressive strength of GGBS mixed concrete is computed using AI technologies, namely Regression Analysis (RA), Support Vector Machine (SVM), Decision Tree (DT), and Artificial Neural Networks (ANNs). The cement content (CC), C/F ratio, w/c ratio, GGBS (in Kg & %), admixture, and age (days) are selected as input parameters to construct the RA, SVM, DT, ANNs models for computing the compressive strength of GGBS mixed concrete. The CS_MLR, Link_CS_SVM, 20LF_CS_DT, and GDM_CS_ANN models are identified as the best architectural AI models based on the performance of AI models. The performance of the best architectural AI models is compared to determine the optimum performance model. The correlation coefficient is computed for input and output variables. The compressive strength of GGBS mixed concrete is highly influenced by age (curing days). Comparing the performance of optimum performance AI models and models available in the literature study shows that the optimum performance AI model outperformed the published models.

Power-efficient low-stray field hybrid magnets for MAGLEV technology

A hybrid suspension system is proposed for maglev transport that utilizes electromagnets (EM) in combination with permanent magnets (PM). Several design schemes are compared searching for optimum performance. Sufficient reduction of power consumption and stray field is achieved on the hybrid configuration as compared to conventional EM suspension systems.

On Probabilistic Assessment of Exergy Analysis of a Wind Turbine for Optimum Performance

Judgment on the performance of a wind turbine depends upon its first law efficiency as well as its second law efficiency. This paper focuses on the second law efficiency, i.e., the exergy efficiency of a wind turbine. The work introduces a novel technique to determine the optimum performance conditions of a wind turbine. Jhimpir city, Pakistan, has been selected as a case study. The wind speed distribution of the selected area is analyzed using different probability density functions. Three-parameter Weibull Distribution turns out to be the best probability density function fitting the wind speed variation. Probability distribution of total wind exergy is performed, and a one-year variation of wind exergy is plotted, showing maximum exergy around the middle of the year. The exergy efficiency of the turbine using a power curve and wind exergy is determined at different wind speeds. Probabilities of various exergy efficiencies are also determined. Results show that higher exergy efficiency has a high probability but so does low exergy efficiency due to seasonal variations. The proposed method can be extended to any wind farm provided the geographical and meteorological parameters of the site.

Design And Analysis of An Automotive Engine Shaft With Functionally Graded Material To Get An Optimum Performance

Engine Shafts are a very critical component of Automotive and Aerospace. Their basic purpose is to transmit power by rotation. They suppose various parts like gears and pulleys, and they are supported by bearings, which reside in the rigid machine housing. In their operation the shafts rotate and hence they are subjected to Torsion and Bending moment. Hence, it is critical for us to choose the best material and the surface treatment process to provide optimum performance for the shaft. The primary aspects to keep into consideration while choosing a material pertaining to surface selection are Wear Resistance and Corrosion resistance. It has been shown how the selection of shaft material affects these two factors. The shafts of 3 types of materials have been discussed in the paper, a homogeneous one, a composite material and FGM. The best material considered is FGM for the optimum operation of automotive engine shaft.

Role of Village Head’s Leadership in Increasing Work Satisfaction of Apparatus of Mokupo Village, Karamat District, Buol Regency

In a village government, the need to carry out social functions internally and externally can significantly affect the survival of the village. Therefore, the principle of leadership is of paramount importance for the achievement of a village’s objectives. In this regard, leadership is influential to several aspects of an organization, including the members' work performance and work satisfaction. Thus, the achievement of work satisfaction is a crucial objective to generate optimum performance and contribute to community development. Employing a qualitative method, the study found that the role of a village head is very influential in directing, guiding, and encouraging the village apparatus in carrying out their duties and contributing to the village development. Moreover, the village head’s leadership has contributed to the achievement of work satisfaction due to several factors, such as the job desk that matches each individual's abilities, feedback, and a fair payment system.

An Essay on Railway Track Bed Failure Issues, Analysis and Remedy

The polymer cures as it enters the ballast, forming a three-dimensional geo-composite reinforcing cage. Although there will be some adherence to the ballast in dry conditions, the polymer's primary job is to construct this reinforcing cage. Polymer penetration is controlled by altering the rheology of the polymer. The method is also said to include a built-in safety system, with the track reverting to a ballast state in the event of a polymer or geo-composite failure. Many of the sites were considered unmaintainable before the polymer was put. The design method was utilized to forecast track behaviour before and after treatment, allowing the most appropriate polymer rheology, polymer distribution, and loading levels to be designed in order to achieve optimum performance and confirm that the procedure worked. This method can be utilized to tackle these types of long-standing problems by displaying actual polymer application profiles at a typical important location.

An Iterative Approach towards Single stage Axial Fan Design using Off Design Prediction

A single-stage axial fan having a pressure ratio of 1.01 is designed in the current study. The design pressure ratio is chosen based on the power available from the existing motor (2.2 kW). The design space for the axial flow fan was generated by varying specific flow and geometrical parameters in suitable steps, using a program written in MATLAB. The varied flow parameters are mass flow rate, inlet Mach number, inlet flow angle, and rotor speed. The geometrical parameters that were varied are hub to tip ratio, aspect ratio, and blade solidity. Using these as the input variables and applying free vortex theory for 3-dimensional blade design, the aerodynamic design of the axial flow fan was carried out. Performance parameters like flow coefficient, stage loading coefficient, degree of reaction, diffusion factor, De Haller’s number, and blade angles were calculated at the blade’s hub, mean, and tip. Total design space of 92160 data points was obtained from the combination of input parameters. Several constraints were applied to optimise the design space based on the available power from the existing motor and in-house manufacturing limitations. The initial design space was reduced to 82 data points using these constraints. To further reduce the number of points in the design space, off-design performance was evaluated for each of these data points. Following this, one design point was selected based on the optimum performance range in off-design operation, while considering manufacturing limitations. Using Mellor charts, a suitable blade profile was chosen based on the inlet and exit blade angles. NACA 65-410 airfoil was selected with a stagger of 55 degrees and an incidence of 6 degrees for optimum performance.

Application of Robotics UV-light Device In Averting The Spread of Coronavirus.

This research focused on robotic ultraviolet light (RUV light) for sanitizing the environment due to the outbreak of the Coronavirus pandemic devastating the whole world. The prototype Robotics UV-light device was proposed in this research to relieve mankind of sanitization of the ecosystem since SARS-CoV-II is highly infectious. The robotic Ultra-violet system was developed using perception subsystems as well as cognition subsystems, all linked together to perform the needed functions. Nine perceptions recognition subsystems were deployed with a remote controller for the driving as well as monitoring of the system for optimum performance while in operation. The Robotics was built with four lamps of ultra-violet lights such that while in operation, the targeted environment gets sanitized at the same time. An extra lamp was attached at the top end of the robotic device which is used to fumigate the upper part of the wards where the other lights could not reach. One of the inbuilt perception subsystems collects information on the extent of sanitization and then via the cognition subsystem shuts down the system automatically. If by chance a novice approaches the ward(s) where the robotic system is working, another perception subsystem will perceive human presences and through the cognitive device raises a mimic human tone programmed, “this place is not safe now, quickly shift". If within ten nano-seconds and the novice still resist the warning, then the machine shutdown automatically. The performance of this electromagnetic light has an efficiency of 99.99 percent over both bacteria and viruses including Covid-19.