Modeling and Analysis of Wind Turbine Tower in ABAQUS

Modeling and Analysis of Wind Turbine Tower in ABAQUS

This tutorial introduces the modeling and analysis methods for cylindrical shell structures in ABAQUS through a case study of a wind turbine tower. By studying this case, readers will master the following key points: ☆ Master the use of Boolean operations; ☆ How to use sketch curves; ☆ Master the structural eigenvalue buckling analysis method. … Read more

Step-By-Step Guide to Building Clinical Prediction Models

Step-By-Step Guide to Building Clinical Prediction Models

Step-By-Step Guide to Building Clinical Prediction Models STEP 1 Purpose, Team, Review, and Plan 1 Clarify the Purpose of the Prediction Model Define the objectives of the prediction model, including: Target population: Specify the patient group the model is aimed at, such as HIV patients in South Africa, individuals with a history of diabetes, or … Read more

Using Infinite Elements in ABAQUS (Part 1)

Using Infinite Elements in ABAQUS (Part 1)

Author: Technical Neighbor | Nick_Liu Using infinite elements can eliminate the reflection of stress waves, allowing for consistent computational results with a smaller model, which greatly saves computational resources and improves accuracy. Infinite element models can be used when local loading has little effect on the overall model or when the problem is unbounded. ABAQUS … Read more

Comparative Study of Transformer and RNN in Speech Applications

Comparative Study of Transformer and RNN in Speech Applications

Original link: https://arxiv.org/pdf/1909.06317.pdf Abstract Sequence-to-sequence models are widely used in end-to-end speech processing, such as Automatic Speech Recognition (ASR), Speech Translation (ST), and Text-to-Speech (TTS). This paper focuses on a novel sequence-to-sequence model called the Transformer, which has achieved state-of-the-art performance in neural machine translation and other natural language processing applications. We conducted an in-depth … Read more

Lag-Llama: Probabilistic Time Series Forecasting with Foundation Models

Lag-Llama: Probabilistic Time Series Forecasting with Foundation Models

Abstract arXiv:2310.08278v3 [cs.LG] February 8, 2024 Original paper link: https://arxiv.org/pdf/2310.08278 In recent years, foundation models have caused a paradigm shift in the field of machine learning due to their unprecedented zero-shot and few-shot generalization capabilities. However, despite the success of foundation models in fields such as natural language processing and computer vision, the development of … Read more