This workshop aims to explore the potential of large generative models to revolutionize how we interact with multimodal information. A Large Language Model (LLM) represents a sophisticated form of artificial intelligence engineered to comprehend and produce natural language text, exemplified by technologies such as GPT, LLaMA, Flan-T5, ChatGLM, Qwen, etc. These models undergo training on extensive text datasets, exhibiting commendable attributes including robust language generation, zero-shot transfer capabilities, and In-Context Learning (ICL). With the surge in multimodal content-encompassing images, videos, audio, and 3D models-over the recent period, Large MultiModal Models (LMMs) have seen significant enhancements. These improvements enable the augmentation of conventional LLMs to accommodate multimodal inputs or outputs, as seen in BLIP, Flamingo, KOSMOS, LLaVA, Gemini, GPT-4, etc. Concurrently, certain research initiatives have developed specific modalities, with Kosmos2 and MiniGPT-5 focusing on image generation, and SpeechGPT on speech production. There are also endeavors to integrate LLMs with external tools to achieve a near "any-to-any" multimodal comprehension and generation capacity, illustrated by projects like Visual-ChatGPT, ViperGPT, MMREACT, HuggingGPT, and AudioGPT. Collectively,these models, spanning not only text and image generation but also other modalities, are referred to as large generative models. This workshop will allow researchers, practitioners, and industry professionals to explore the latest trends and best practices in the multimodal applications of large generative models.@en

A fiber-reinforced composite wind turbine blade (WTB) is exposed to numerous impact threats during its service life causing damages that can be detrimental to its structural integrity. Currently, impact loads are not considered during blade design, so high safety factors are introduced, which result in a conservative design. However, as wind turbine blades become stiffer and lighter and health monitoring systems become more sophisticated, the design process is shifting toward damage-tolerant approaches. The design philosophy accepts damages to the structure, but it also requires that the damaged blade still meet structural and functional requirements. This design procedure requires a comprehensive understanding of different impact threats and their characteristics, which is currently unavailable in the public domain. This paper is a first attempt to review the impact loads on composite wind turbine blades. The aim of the current paper is to (a) identify different sources of impact threats on wind turbine blades during different stages of their service life, (b) describe their qualitative (causes and vulnerable regions) as well as quantitative characteristics (size, mass, and velocity of impactor), and to (c) provide modeling guidelines by comparing these impact threats using five different criteria - (i) relative deformability of projectile and wind turbine blade, (ii) impact velocity, (iii) kinetic energy of impact, (iv) repeatability of impacts and (v) nature of the impact. The review paper will be of special interest to researchers working on wind turbine blades and will serve as a baseline report for designing damage-tolerant blades. Recommendations are also provided for future research.

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