Papers by Keyword: Material Database

Abstract: With the development of the material databases’ construction, the use of machine learning methods to process data mining to discover new materials has gradually become a hot topic. The mechanical properties of Mg alloys are related to their components and processing technologies, therefore, it is possible to build prediction model between components, processing technologies and mechanical properties. In order to improve the design efficiency of Mg alloys, using machine learning methods to build a prediction model for the mechanical properties of Mg alloys is of vital importance. To achieve efficient material design, this paper proposed an improved random forest (RF) method based on the Particle Swarm Optimization (PSO) algorithm, and built a Mg alloy performance prediction model. Experiments showed that the accuracy was greatly improved compared with the original RF model, and the prediction accuracy of mechanical properties can reach more than 90%.

Abstract: To predict the nonlinear mechanical behavior of components made of short fiber-reinforced plastics (SFRP) under long term and cyclic loading, coupled process and component simulations are required. The injection molding process leads to locally varying fiber orientations within the component. This varying microstructure [1] significantly influences the viscoelastic and fatigue behavior. The interaction between the microstructure [2] and the nonlinear macroscopic properties is resolved by a coupled fast Fourier transformation and finite element two-scale method (FFT-FEM), where the fiber orientation tensor is obtained by analyzing μCT images or by the corresponding process simulation. The aim of this work is to reduce the numerical costs of such a multiscale method. In a first step, the highly efficient micro-scale solver FeelMath [3,4] using an FFT-based preconditioner is presented. Afterwards, a numerical scheme based on a precomputed database trained with FeelMath simulations on the microscale and a model order reduction algorithm, is discussed. The combination of these ideas reduces the numerical effort, such that the method is applicable for industrial problems. Comparative studies of the fully coupled and reduced model document the high accuracy of this approach. The overall performance of this methodology is demonstrated by three-dimensional, industrial applications.

Abstract: Nuclear grade 316LN austenitic stainless steel (ASS) with an exceptional combination of mechanical properties and corrosion resistance was used to produce AP1000 primary coolant pipe. In order to evaluate the microstructure evolution of the pipe during its forging process, the material database of the 316LN ASS is established with high integrity and reliability. In this paper, the thermal physical parameters, flow stress-strain data and the recrystallization kinetic equations of the 316LN steel are coupled, and the material database is systematically established. Most important, the reliability of the database is verified by an experiment.

Abstract: Using fiber-reinforced composites (FRC) in automotive lightweight construction currently is too expensive to achieve a wide distribution. To assist the engineers’ material selection process suitable information systems are needed. Development of those are a hard task due to the complex structure of FRC. In this paper we give an insight to the problem domain and introduce requirements which should be met by an information system for composite data storage.

Abstract: Reasonable selection of materials and their processing methods directly influences the quality and costs of products. Therefore, material information system plays an important role in material research, development, production, application and education. Due to the superiority and development speed of database technology, it has been widely applied to mechanical processing industry, providing technical support for mechanical manufacturing automation. In the paper, a mechanical processing material database system is put forward. Its key technologies and developing approach are discussed in detail. The establishment of processing data information database, which can provide reasonable or optimal technological parameters, is one of the most effective measures to enhance the competitiveness of an enterprise.

Abstract: The research introduce the present situation of nationwide fitness in china and construct a “material database for nationwide fitness” which contains three subsystems (health consult, fitness guidance and online information comunication). We can make guidance selection for fitness mode according to different demands of fitness groups and give suggestions to different fitness groups. Which make them select convenient modes and achieve satisfied effect. The material database for nationwide fitness have features of convenient, easy to universal, effetive, pratical and resource share. By construction of the material databasesystem of nationwide fitness, material databaseas a medium and play sports resource sharing effetive to make good foundation for nationwide fitness development.

Abstract: Today almost all steel production fields use process models on the basis of analytic and numeric simulations. Planning and implementation of modern production in plants strategies can no longer be imagined without simulations in almost all fields of long and flat steel production. For the plant engineering and construction industry, planning of transformation processes and rolling mills can hardly be imagined without the use of modern simulation technology. The possibilities range from the simulation of material transformation behavior to the whole rolling process, extending to the load effected on units and plants as well as the projection of microstructure and material properties when applying different rolling technologies. Thus simulation models increasingly contribute to support future-oriented process development and material related optimization.

Abstract: Advanced high-strength steels offer a great potential for the further development of automobile bodies-in-white due to their combined mechanical properties of high formability and strength. New types of grades – multi-phase steels, superductile steels and density reduced steels – are under development at ThyssenKrupp Steel with tensile strength levels of up to 1000 MPa in combination with excellent formability for the high demands of cold formed structural automobile components. New forming technologies at increased temperatures – hot forming, semi-hot forming and superplastic forming - enable the processing of complex parts with extreme high strength. ThyssenKrupp Steel identifies potential future steels and technology concepts by technology monitoring and evaluates their potential for future applications in pre-development projects. University research institutions are significantly involved in this essential future oriented challenge. Seminal concepts are being implemented together with automotive manufactures by simultaneous engineering processes with coordinated phases of production and testing.

Abstract: The three-year activities of Japanese IMS-VHT (virtual heat treatment tool for monitoring and optimising heat treatment process) project are summarized in collaboration with international VHT program. A brief introduction of the developed code and the results of a simulation of the carburized-quenching process of a cylinder, ring, and helical gear are described by using accumulated databases of material characteristics and cooling conditions. A trial to optimizing the heat treatment (HT) process by using a database system is presented based on collected data of practical cases. The goal of this project is to optimize the process, such as gas-carburizing followed by quenching into oil, and to accumulate heat treatment data to create a knowledge-based database.