Knowledge Based Engineering for Hydrogen Gas Turbines and Burners Design: a review

Hydrogen gas turbines and burners need high attention and their appropriate realization, yet during their design, can lead important benefits for the whole sector. Realizing the best design, the first time, reduces reworks and requests of design changes from the manufacturing departments. In this field, Knowledge Based Engineering is a good strategy for embedding, in an automatic way, experts’ knowledge into CAD models during the design of a component. It enables a reduction of human errors and costs in several design tasks and improving the final quality of a component model. With these premises, the aim to the study is to lead improvements and appropriate actions in the design and re-configuration of hydrogen power generation systems (i.e. gas turbines and burners) by means of KBE, leading improvements yet in this early phase of the global race for hydrogen. A systematic literature review is carried out to explore the current state of art for the application of KBE for the design of turbines and burners in different industrial sectors. Evidences from the practice are collected in a structured classification and elaborated and summarized for application in the design of gas turbines and burners for the hydrogen production.

Development of Knowledge-Based Engineering System for Structural Size Optimization of External Fixation Device

The development process of the knowledge-based engineering (KBE) system for the structural size optimization of external fixation device is presented in this paper. The system is based on algorithms for generative modeling, finite element model (FEM) analysis, and size optimization. All these algorithms are integrated into the CAD/CAM/CAE system CATIA. The initial CAD/FEM model of external fixation device is verified using experimental verification on the real design. Experimental testing is done for axial pressure. Axial stress and displacements are measured using tensometric analysis equipment. The proximal bone segment displacements were monitored by a displacement transducer, while the loading was controlled by a force transducer. Iterative hybrid optimization algorithm is developed by integration of global algorithm, based on the simulated annealing (SA) method and a local algorithm based on the conjugate gradient (CG) method. The cost function of size optimization is the minimization of the design volume. Constrains are given in a form of clinical interfragmentary displacement constrains, at the point of fracture and maximum allowed stresses for the material of the external fixation device. Optimization variables are chosen as design parameters of the external fixation device. The optimized model of external fixation device has smaller mass, better stress distribution, and smaller interfragmentary displacement, in correlation with the initial model.

Idea of Knowledge-Based Engineering using CAD Model

Manufacturing firms have been compelled to invest heavily in digitizing and optimizing their technical and manufacturing operations as a result of mass customization. When developing and introducing new goods, not only must manufacturing procedures be computerized, but also information of how the products must be developed and manufactured based on client needs must be applied. One major academic issue is to assist the industry in ensuring that stakeholders understand the background information of automated engineering all through the production process. The goal of the study described in this article is to provide a foundation for a connectivity perspective of Knowledge-Based Engineering (KBE). The use of graph theory in conjunction with content-based filtering methods is used to handle network creation and contextualization, which are fundamental ideas in connectivism. To enable a connectivity management culture, the article demonstrates how engineering information in spreadsheet, knowledge representation, and Computer Aided Design (CAD) models may be infiltrated and displayed as filtering graphs.

Knowledge-based engineering in the context of railway design by integrating BIM, BPMN, DMN and the methodology for knowledge-based engineering applications (MOKA)

Designing railway infrastructure is a knowledge-intensive task. Although there are a number of mature design authoring systems available, their support for dynamically incorporating domain-specific engineering knowledge is very limited. At the same time, a standardized digital representation of railway engineering knowledge (such as building codes and best practice) does not exists. To overcome this deficiency, this paper proposes the use of Knowledge Based Engineering (KBE) to automate routine design tasks by considering multiple knowledge sources. In this scenario, KBE is used to support a Railway design authoring system. To ensure maximum transparency in the design of the developed KBE application, graphical ‘Business Process Model and Notation’ (BPMN) has been used in combination with ‘Decision Model and Notation’ (DMN) to formalize the underlying engineering knowledge. The KBE application has been developed according to the Methodology for Knowledge-Based Engineering Applications (MOKA). An evaluation of the BPMN/DMN approach shows that it meets up to 58% of the acceptance criteria found in the literature. In addition, BPMN and DMN can already be used in the early capture phase of MOKA and its workflows can be developed into an executable KBE application in the subsequent phases. The results of the test example discussed here show that time savings of up to 97.5% can be achieved in the execution of the KBE application.