Intelligent Design Optimization System for Additively Manufactured Flow Channels Based on Fluid–Structure Interaction

Based on expert system theory and fluid–structure interaction (FSI), this paper suggests an intelligent design optimization system to derive the optimal shape of both the fluid and solid domain of flow channels. A parametric modeling scheme of flow channels is developed by design for additive manufacturing (DfAM). By changing design parameters, a series of flow channel models can be obtained. According to the design characteristics, the system can intelligently allocate suitable computational models to compute the flow field of a specific model. The pressure-based normal stress is abstracted from the results and transmitted to the solid region by the fluid–structure (FS) interface to analyze the strength of the structure. The design space is obtained by investigating the simulation results with the metamodeling method, which is further applied for pursuing design objectives under constraints. Finally, the improved design is derived by gradient-based optimization. This system can improve the accuracy of the FSI simulation and the efficiency of the optimization process. The design optimization of a flow channel in a simplified hydraulic manifold is applied as the case study to validate the feasibility of the proposed system.

Application of Multidirectional Mutation Genetic Algorithm and Its Optimization Neural Network in Intelligent Optimization of English Teaching Courses

Aiming at the problems existing in the traditional teaching mode, this paper intelligently optimizes English teaching courses by using multidirectional mutation genetic algorithm and its optimization neural network method. Firstly, this paper gives the framework of intelligent English course optimization system based on multidirectional mutation genetic BP neural network and analyses the local optimization problems existing in the traditional BP algorithm. A BP neural network optimization algorithm based on multidirectional mutation genetic algorithm (MMGA-BP) is presented. Then, the multidirectional mutation genetic BPNN algorithm is applied to the intelligent optimization of English teaching courses. The simulation shows that the multidirectional mutation genetic BP neural network algorithm can solve the local optimization problem of traditional BP neural network. Finally, a control group and an experimental group are set up to verify the role of multidirectional mutation genetic algorithm and its optimization neural network in the intelligent optimization system of English teaching courses through the combination of summative and formative teaching evaluations. The data show that MMGA-BP algorithm can significantly improve the scores of academic students in English courses and has better teaching performance. The effect of vocabulary teaching under the guidance of MMGA-BP optimization theory is very significant, which plays a certain role in the intelligent curriculum optimization of the experimental class.

World'S First Successful Dual String Installation of a Digital Intelligent Artificial Lift DIAL - Interventionless Gas Lift Production Optimization System, Offshore Malaysia

PETRONAS completed well H-X on B field in Malaysia with a digital intelligent artificial lift (DIAL) gas lift production optimization system. This DIAL installation represents the first ever successful installation of the technology in an Offshore well for Dual String production. This paper provides complete details of the installation planning and operational process undertaken to achieve this milestone. DIAL is a unique technology that enhances the efficiency of gas lift production. Downhole monitoring of production parameters informs remote surface-controlled adjustment of gas lift valves. This enables automation of production optimization removing the need for well intervention. This paper focusses on a well completed in November 2020, the fourth well to be installed with the DIAL technology across PETRONAS Assets. The authors will provide details of the well and the installation phases: system design, pre-job preparations, improvements implementation, run in hole and surface hook-up. For each phase, challenges encountered, and lessons learned will be listed together with observed benefits. DIAL introduces a paradigm shift in design, installation and operation of gas lifted wells. This paper will briefly highlight the justifications of this digital technology in comparison with conventional gas lift techniques. It will consider value added from the design stage, through installation operations, to production optimization. This DIAL system installation confirms the ability to be implement the technology in a challenging dual string completion design to enable deeper injection while avoiding interventions on a well with a greater than 60-degree deviation. With remotely operated, non-pressure dependent multi-valve in-well gas lift units, the technology removes the challenges normally associated with gas-injected production operation in a dual completion well – gas robbing and multi-pointing. Despite the additional operational & planning complications due to COVID-19 restrictions, the well was completed with zero NPT and LTI. Once brought online, this DIAL-assisted production well will be remotely monitored and controlled ensuring continuous production optimization, part of PETRONAS’ upstream digitization strategic vision.

Differential Evolution Algorithm-Based Iterative Sliding Mode Control of Underactuated Ship Motion

The differential evolution algorithm (DEA)-based iterative sliding mode control (ISMC) method was proposed for the path tracking problem of three-degree-of-freedom (3-DoF) underactuated ships under external interference, with the nonlinear separate model proposed by mathematical model group (MMG). To improve control quality and enhance robustness of the control system, a swarm intelligence optimization algorithm is used to design a controller parameter optimization system. The DEA was adopted in the system to solve the minimum system evaluation index function, and the optimal controller parameters are acquired. Considering the impact of chattering on the actual project, a chattering measurement function is defined in the controller design and used as an input of the controller parameter optimization system. Finally, the 5446TEU container ship is carried out for simulation. It is verified that the designed controller with strong robustness can effectively deal with the disturbances; meanwhile, the chattering of the output is significantly reduced, and the control rudder angle signal conforms to the actual operation requirements of the ship and is more in line with the engineering reality.

Vehicle Routing Optimization System with Smart Geopositioning Updates

Solving the vehicle routing problem (VRP) is one of the best-known optimization issues in the TLS (transport, logistic, spedition) branch market. Various variants of the VRP problem have been presented and discussed in the literature for many years. In most cases, batch versions of the problem are considered, wherein the complete data, including customers’ geographical distribution, is well known. In real-life situations, the data change dynamically, which influences the decisions made by optimization systems. The article focuses on the aspect of geopositioning updates and their impact on the effectiveness of optimization algorithms. Such updates affect the distance matrix, one of the critical datasets used to optimize the VRP problem. A demonstration version of the optimization system was developed, wherein updates are carried out in integration with both open source routing machine and GPS tracking services. In the case of a dynamically changing list of destinations, continuous and effective updates are required. Firstly, temporary values of the distance matrix based on the correction of the quasi-Euclidean distance were generated. Next, the impact of update progress on the proposed optimization algorithms was investigated. The simulation results were compared with the results obtained “manually” by experienced planners. It was found that the upload level of the distance matrix influences the optimization effectiveness in a non-deterministic way. It was concluded that updating data should start from the smallest values in the distance matrix.

INTELLIGENT OPTIMIZATION SYSTEM FORMULATED ON INDUSTRIAL INTERNET PLATFORM

The opinion of "Industrial Internet" was first suggested by General Electric. As a modern infrastructure of the 4 -th industrial revolution, Industrial Internet has become a substantial mechanism to actualiza digital revision of industrial economy. The Industrial Internet platform is a system formulated on huge data gathering, accumulation and analysis, which is based to the necessity of digitalization, networking and philosophizing of manufacturing industry. In order to settle the problems of actual rearward industrial data, improve the capacity of data acquisition and deal with the industrial interconnection platform, the industrial intelligent optimization system generates the product services needed by industrial enterprises and realizes the object of industrial optimization. Key words: Industrial Internet; industrial intelligence; industrial mechanism