The scope of this article is to review the potential causes that can lead to wind turbine blade failures, assess their significance to a turbine’s performance and secure operation and summarize the techniques proposed to prevent these failures and eliminate their consequences. Damage to wind turbine blades can be induced by lightning, fatigue loads, accumulation of icing on the blade surfaces and the exposure of blades to airborne particulates, causing so-called leading edge erosion. The above effects can lead to damage ranging from minor outer surface erosion to total destruction of the blade. All potential causes of damage to wind turbine blades strongly depend on the surrounding environment and climate conditions. Consequently, the selection of an installation site with favourable conditions is the most effective measure to minimize the possibility of blade damage. Otherwise, several techniques and methods have already been applied or are being developed to prevent blade damage, aiming to reduce damage risk if not able to eliminate it. The combined application of damage prevention strategies with a SCADA system is the optimal approach to adequate treatment.

No abstract

The designing process of a new product includes various stages, one of which is the evaluation of an idea thought prototype manufacturing. The use of additive manufacturing consists the most efficient and effective way for prototype manufacturing. In order to maximize the benefits from the use of additive manufacturing, we should choose the suitable printing parameters. A vital parameter for defining the quantity of raw material used and the model solidity is the inner wall thickness. Depending on the selected technique of additive manufacturing, the thickness of the inner wall may differ. In this study we initially print furniture models with different wall thicknesses using the Inject Binder technique and then we check their durability and resilience by compression tests. Evaluating the study results indicate the hollow printed specimens have high durability during compression tests and can be used to evaluate a design idea. Using the facts derived from lab tests we perform Topology Optimization studies under different circumstances to evaluate the method and come up with the optimal design solution. Initially, the Topology Optimization study concern only the table surface and not the whole model. The following studies were performed for the whole model, different constraints and load cases defined. Then, the optimized models are redesigned in order to improve their durability. The performed studies show that Topology Optimization is a powerful tool, which is able to support the designers/ engineers to take the right decision during the design process. Doi: 10.28991/HIJ-2020-01-04-03 Full Text: PDF

Due to recent developments in the field of additive manufacturing enormous advantages have become in product design and manufacturing process. Before the appearance of additive manufacturing, developing very complex or light weight structures was difficult to manufacture. The development of artificial intelligent technology helps to develop new collaborative tools and algorithms. Generative design approach is one of them. The outcome model from a generative design study is not depending only from designer/engineer experience or his knowledge. Designers can react with sophisticated algorithms through CAD programs to specify the shape and the topology of the model. A significant tool on a generative design system is topology optimization which is able to generate different solutions. The changes in design process are significant. A rough conceptual design (sketch) or a 3d model is first prepared. Then, boundary conditions, safety factor, manufacturing limitations and materials properties are defined. The generative design system generates potential solutions. It’s up to the designer to find the design that best fits to his need. In this paper the review covers the limitations of current systems through the study of specific design cases using commercial generative design systems.