Internal Variable and Cellular Automata-Finite Element Models of Heat Treatment
Heat treatment is one of the most important process es in advanced steel products manufacturing. While production processes are still being optimised, numerical modelling of heat treatment is very useful. Finite Elements Method (FEM) is widely used in these cases, due to its proved potential fo r modelling of continuous, macroscopic phenomena. However, its capability to simulate microscale and noncontinuous processes is very limited. Introducing e mpirical model of phase changes into FEM, usually based on Internal Variable Method (IVM) is useful when the information about volume fraction of the phases in the domain a nd stresses due to phase change satisfies the requirements. Notwithstanding, it is difficult to obtain information in-depth about microstructure during heat treatment, because it requires more sophisticated description of phase change process. Those problems can be resolved with multiscale modelling. One of the current approaches in this fi eld employs FEM for computing of temperature, stress and strain fields, while non-co ntinuous, microscale model is based on Cellular Automata (CA) method [1]. Recently, several CA models concerning phase transformation have been proposed, e.g. [2]. In th is paper Cellular Automata ‐ Finite Elements (CAFE) is applied for modelling of both macroscopic and microscopic influence of heat treatment. It also takes into acc ount a stochastic character of processes, which is hard to obtain in typical FEM or IVM solut ion. The advantage of CAFE model ensues from direct representation of microstructure. Although the current microstructural CA model is two-dimensional, it reproduces topological and morphological relations between components of microstructure. The state of CA cells is updated synchronically in cons ecutive time steps. Every cell includes state vector representing fractions of all phases. Thermodynamics of phase transition is a base for a rule-based knowledge rep resentation in the CA model. However, the nondeterministic definition of neighbo urhood and probabilistic energy
Development of Semantic Description for Multiscale Models of Thermo-Mechanical Treatment of Metal Alloys
We present a process of semantic meta-model development for data management in an adaptable multiscale modeling framework. The main problems in ontology design are discussed, and a solution achieved as a result of the research is presented. The main concepts concerning the application and data management background for multiscale modeling were derived from the AM3 approach—object-oriented Agile multiscale modeling methodology. The ontological description of multiscale models enables validation of semantic correctness of data interchange between submodels. We also present a possibility of using the ontological model as a supervisor in conjunction with a multiscale model controller and a knowledge base system. Multiscale modeling formal ontology (MMFO), designed for describing multiscale models’ data and structures, is presented. A need for applying meta-ontology in the MMFO development process is discussed. Examples of MMFO application in describing thermo-mechanical treatment of metal alloys are discussed. Present and future applications of MMFO are described.
Prevention of Barite Sag in Oil-Based Drilling Fluids Using a Mixture of Barite and Ilmenite as Weighting Material
Drilling high-pressure high-temperature (HPHT) wells requires a special fluid formulation that is capable of controlling the high pressure and is stable under the high downhole temperature. Barite-weighted fluids are common for such purpose because of the good properties of barite, its low cost, and its availability. However, solids settlement is a major problem encountered with this type of fluids, especially at elevated downhole temperatures. This phenomenon is known as barite sag, and it is encountered in vertical and directional wells under static or dynamic conditions leading to serious well control issues. This study aims to evaluate the use of barite-ilmenite mixture as a weighting agent to prevent solids sag in oil-based muds at elevated temperatures. Sag test was conducted under static conditions (vertical and inclined) at 350 °F and under dynamic conditions at 120 °F to determine the optimum ilmenite concentration. Afterward, a complete evaluation of the drilling fluid was performed by monitoring density, electrical stability, rheological and viscoelastic properties, and filtration performance to study the impact of adding ilmenite on drilling fluid performance. The results of this study showed that adding ilmenite reduces sag tendency, and only 40 wt.% ilmenite (from the total weighting material) was adequate to eliminate barite sag under both static and dynamic conditions with a sag factor of around 0.51. Adding ilmenite enhanced the rheological and viscoelastic properties and the suspension of solid particles in the drilling fluid, which confirmed sag test results. Adding ilmenite slightly increased the density of the drilling fluid, with a slight decrease in the electrical stability within the acceptable range of field applications. Moreover, a minor improvement in the filtration performance of the drilling fluid and filter cake sealing properties was observed with the combined weighting agent. The findings of this study provide a practical solution to the barite sag issue in oil-based fluids using a combination of barite and ilmenite powder as a weighting agent to drill HPHT oil and gas wells safely and efficiently with such type of fluids.