Papers by Keyword: Model

Abstract: The microstructure of carbon fibers with different properties also varies. Even with considerable mechanical properties, the microstructure characteristics of carbon fibers produced by different manufacturers or processes are different. Although current characterization testing methods can provide a fundamental analysis of the relationship between the microstructure and mechanical properties of carbon fibers, there is still no systematic theory on how to control the evolution of their microstructure during the production process of carbon fibers and develop high-performance and high-quality fibers. There is still a certain gap in the performance of carbon fibers in China compared to foreign countries. Therefore, this article analyzes and summarizes various publicly published models of carbon fiber microstructure in recent years, providing reference for establishing a recognized analysis model that can predict the mechanical properties of carbon fibers in engineering, providing effective direction for improving carbon fiber manufacturing processes, and providing technical support for developing high-performance and high-quality carbon fibers.

Abstract: Due to the complex compression failure process of fiber composite materials, especially the direct bearing situation of the composite material end face, it is quite difficult to accurately predict it. At present, the design of composite material compression performance mainly considers a large safety factor, and a compression failure assessment method that can meet the needs of reliable engineering applications is still a challenge and a key issue that the engineering community urgently needs to solve. This article reviews the widely studied shear type buckling model, extensional type buckling model, matrix strain failure theoretical model, matrix shear failure theoretical model, interlayer shear failure theoretical model, elastic micro buckling model, plastic micro buckling model, three parameter model, fiber microbuckling finite element model and ply mesobuckling finite element model of fiber reinforced composite materials that have been publicly published in recent years, which were analyzed and summarized, providing reference for further in-depth research in the future.

Abstract: In this study, the CCD response surface methodology was used to model and optimise the performance of Lasienthera africanum leaves extract (LALE) as a corrosion inhibitor on mild steel. The experimental parameters were assessed at different immersion time and inhibitor concentration to determine the optimum conditions for corrosion mitigation. Using experimental results of the corrosion characteristics such as the weight loss, corrosion rate, and inhibition efficiency of LALE, new models were developed, the significance of which was tested using variance analysis. The developed RSM models of WL, CR, and IE were accurate and reliable, and their P-values were 0.0001, which is less than 0.05. Likewise, the R²-statistics (R², adjusted-R², and predicted-R²), adequate precision, and diagnostic plots were also used as a means to ascertain the degree of accuracy and adequacy of the WL, CR, and IE models. In addition, optimization of the corrosion inhibition process for LALE revealed that the optimum conditions for maximum IE, minimum WL, and CR were achieved at a concentration of 93.93 ppm and an immersion time of 228 hrs. Under these settings, the inhibition efficiency, weight loss, and corrosion rate were 93.85%, 0.294g and 3.267 mm/y, respectively. Therefore, the models are considered ideal for prediction with a confidence level of 95%, and the optimal combination is suitable for the corrosion inhibition process design. Hence these models can be recommended for applications such as oil well acidizing and pickling pipelines.

Abstract: Surface marks, such as scratches or cosmetic marks, commonly appear during the manufacturing phase of metallic components, because of the contact between tools and sharp edges with the surface of the parts. Scratches, depending on their width, depth, and root radius, cause a decrease in the fatigue life of metallic alloys. In particular, the presence of scratches with a size comparable to the grain size favors the generation of fatigue cracks in these features. In the aerospace industry, the presence of surface marks is a common cause of rejection. The low hardness of aluminium, a material widely employed in the manufacture of aerospace structures, contributes to the generation of surface marks. In this paper, a preliminary geometrical characterisation of scratches is established. It aims to define a set of parameters to characterise exhaustively the different scratches and to generate different behavior models for each type of scratch. Parameters such as scratch length, path radius, and burr height are considered in addition to the well-known parameters such as scratch depth, root radius, and open angle.

Abstract: The article substantiates the main possibilities of filling with irregular bodies, and provides a visual analysis of the parameters formed as a result of structures. It was found out that the form factor acts as the main indicator of the characteristic parameter of changes in the structure and all other parameters of an inhomogeneous medium. It was also found out that when filling a container with irregular ellipsoid elements, the conditions for non-opening (one-way contact) must be met. The obtained calculations of the form factor show the minimum value of the average coordination number of an inhomogeneous medium. This allows us to assert and predict reliable modelling results (± 2-3%). It is also important that the developed simulation model for modelling an inhomogeneous medium using an irregular (ellipsoid) shape of elements can significantly reduce the time spent on conducting field experiments, as well as simulate irregular elements with different shape factors.

Abstract: Comparative analysis of two models for predicting residual resource of polymer composite, one proposed by specialists from RS Technologies Inc and the other proposed by Institute of Oil and Gas Problems SB RAS (Russia), was carried out to obtain service life of composite poles for power transmission lines manufactured by RS Technologies Inc (Canada) for cold climate of Republic of Sakha (Yakutia). Models are based on experimental studies of strength of materials during accelerated and full-scale climatic tests. The difference lies in the presence of parameters of climatic zone and test methods in the first model, while the second model considers changes in physical and mechanical properties and structure of materials during aging under conditions of full-scale exposure and accelerated climatic tests. Comparison of results of predicting the durability of fiberglass products in cold climate of Yakutsk (Russia) according to Institute of Oil and Gas Problems SB RAS model and similar products in Calgary (Canada) climate (the closest in terms of climate conditions) according to RS Technologies Inc model showed the same results. Service life of composite support material was approximately 120 years with specified level of permissible decrease in characteristic property index of 75% of the original.

Abstract: The need for data on marine resources is increasing, Indonesia as one of the world's maritime countries plays a big role in this. The successful application of big data on marine resources is not only seen from the technology used in it but it is also must related to other system components. A qualitative approach is used in this study to produce a big data model that can be applied to marine resources. This research produces a big data model from the perspective of a Knowledge Management System (KMS) which consists of four elements or layers, namely organization, Big Data Process and Technology Information, and people as users. The integration of these four elements is expected to promote economic transformation and knowledge in the marine and fishery sectors.

Abstract: Conventional systems are electrical, electro mechanical and heavy-duty industry appliance relying on monitoring, reporting, alert mechanism that are manual or semi-automated for services. As the number of systems increase, the services to these conventional systems are labor intensive, adds complexity and service time is a challenge. Internet of Things (IoT) bridges the physical world data to applications in cloud and acts as a critical interface for driving the Digital Infrastructure for organizations. Current IoT systems design is largely driven by the edge environmental parameters and requirements from software-based applications in the cloud. The constraints of the design that are governed by resources available at the edge. There are multiple use cases for IoT which includes Enterprise, consumer and Industrial applications. The design requirements such as Availability, Security, Energy savings & safety have to be considered for enabling smartness for the conventional systems which also influences cost and resources of support infrastructure. In this paper the modelling design parameters such as availability in service based smart systems is discussed and detailed using mathematical models.

Abstract: The present pandemic situation has made people not go out anywhere because it’s getting difficult to learn the concepts briefly for both lecturers and students. Concepts are learned through videos, but reading is also an important aspect of learning. This paper talks about providing books and notes in online mode to read and recommend books based on facial expressions captured from the user. This paper aims to extract faces from an image, extract the expression (eyes and lips) from it and also classify them into six types of emotions, which are Happy, Fear, Anger, Surprise, Neutral and Sad. The algorithm used for facial expression recognition is the Convolutional Neural Network algorithm, also known as CNN.

Abstract: The worldwide society was devastated by the 2019 coronavirus illness (COVID19) epidemic in Wuhan, China, which overloaded advanced medical systems around the world. The World Health Organization (WHO) is constantly monitoring and responding to the pandemic. The current rapid and exponential development in patient numbers necessitates the use of AI technology to forecast possible outcomes of infected individuals in order to provide suitable therapy. The goal is to find the machine learning-based solution that best fits the Covid19 vaccination predictions with the highest accuracy. Variable identification, univariate analysis, bivariate and multivariate analysis, missing value handling and data validation analysis, data cleaning / preparation, and data validation analysis are all accomplished using supervised machine learning technology (SMLT). Various types of data, such as visualisation, are gathered. For the entire given dataset. Proposal of a machine learning-based method for accurately predicting the suitability of Covid19 vaccine prediction.