Resource Library

Wind energy is considered an important part of the global renewable energy strategy. Therefore, it is imperative that the development of these technologies matches the speed at which they are needed. 

Join Ansys and our customers as we explore how a simulation led approach enables the rapid development of their products in an industrial context.

This brochure describes how materials data used in Ansys Granta products is collected, checked and validated for accuracy. This process ensures the pedigree of the materials data, which can have a major impact on the simulations in which they are used.

カメラは、自律型テクノロジーの大切な要素の 1 つです。この回では，Ansys SPEOS の拡張カメラセンサシミュレーション機能を使用して，ADAS/AD シミュレーションの精度を向上させる方法をご紹介します。さらに、新しいレンズインポーターを使用することで、オリジナルのシステムの知的財産を保護しながら、あらゆるイメージングシステムをAnsys SPEOSにインポートして光学解析を行う方法をご紹介します。

このwebinarで学べること:

• EPP、2Dディストーション、フォーカス距離、DoFなど、カメラシステムのモデリングをさらに進化
• Ansys SPEOSまたはZEMAX OpticStudioデザインをカメラ・シミュレーション用の簡易モデルに変換
• レンズシステムの主要な光学特性を可視化
• レンズ設計からカメラシミュレーションまで、新たなコラボレーションワークフローを構築

In the past, for computation of electrical parameters of on-chip and chip-to-chip interconnects, it has been usually assumed that the conductor surface is homogeneous with smooth outer surfaces. However, copper (Cu) suffers from surface roughness that aggravates conductor losses in high speed interconnects. The delay in interconnects depends mainly on the interconnect parasitics, which would therefore be aggravated due to surface roughness. This leads to reduced bandwidth and higher latency.

The goal of this webinar is to address the roughness-related effects on performance of on-chip and chip-to-chip Cu interconnects. Topics include:

• Analytical models for extracting line parasitics (RLC p.u.l.) for deeply scaled on-chip interconnects and chip-to-chip interconnects with rough surfaces
• Analytical models for the computation of resistivity and mean free path of on-chip interconnects at current and advanced technology nodes (i.e., 45nm, 22nm, 13nm, 7nm)
• Signal integrity analysis using eye diagrams at different bit rates to find the increase in frequency dependent losses due to surface roughness
• Computational overhead (simulation time, physical memory, matrix size, number of tetrahedrons) incurred for simulating on-chip and chip-to-chip Cu interconnects at different values of roughness and technology nodes.
• The relationship between surface roughness and various performance metrics such as delay, EDP, BWD, and insertion loss.
• A comprehensive analysis of the impact of interconnect surface roughness on the energy-budget in networks on chips (NoCs)

Analyze, visualize and communicate your simulation data with Ansys EnSight. Engineers use this powerful, general purpose post-processing tool to gain new design insights and then clearly and effectively sell their recommendations. Flexible EnSight can read and visualize data from most simulation tools — including Ansys solutions and other vendors.

EnSight handles simulation data from a wide range of physics from fluids, structures, particles, crashes and more. With EnSight, you can create and communicate clear, appealing, high-resolution simulation results on datasets that were previously thought to be too big to handle.

Topics Covered:

• Animation strategies
• Advanced features
• Report generation
• Automation & Scripting

Attend this webinar to learn how Ansys Fluent can accelerate the meshing and solve time for automotive external aerodynamics applications. There will be a live demonstration showcasing:

• CAD import to volume mesh generation
• User-friendly task-based workflows
• How to customize and save your workflow
• Advanced meshing technologies
• Efficient parallel meshing