アプリケーションギャラリ

This app demonstrates: Light theme This app allows you to evaluate cross-section data for a wide range of American and European standard beams. Given a set of forces and moments acting on the section, you can also compute a detailed stress distribution. Calculated cross-section data ... 詳細を見る

This model illustrates the charge/discharge control of a Lithium-Ion battery in a Simulink® simulation. 詳細を見る

これは, バスバー内の電気加熱モデルのフィジックスインターフェイスとパラメーター化されたジオメトリを含むテンプレート MPH ファイルです. 詳細を見る

This app demonstrates the following: Designing an app for small screens such as smartphones User-interface navigation with a top menu typically used on websites Geometry parts and parameterized geometries Visualizing periodicity of a geometry with material rendering Warning messages on ... 詳細を見る

This example model consists of a two-hot-arm thermal actuator made of polysilicon. The actuator is activated through thermal expansion. The temperature increase required to deform the arms, and thus displace the actuator, is obtained through Joule heating (resistive heating). The greater ... 詳細を見る

このアプリは, 電池テストサイクル中の NMC111/グラファイトバッテリセルのセル電圧, セル開放電圧, および内部抵抗を予測するための代理モデル関数の使用方法を示します. 代理関数 (ディープニューラルネットワーク) は, 入力データ値のサブセットに適合されています. 入力データ値は, サイクルの4つのセグメントにおける電流とバッテリセルの初期充電状態の5つを設定できます. 代理関数の評価にかかる計算コストが低いため, ノブを使用して入力値を対話的に組み合わせ, セル電圧と内部抵抗を予測できます. 値の組み合わせを選択したら, ... 詳細を見る

This model simulates arc welding of a titanium plate made from an alpha-beta titanium alloy. During a weld pass, the material experiences a thermal transient, including both heating and cooling. Phase transformations are modeled, and the evolution of the phase composition over time is ... 詳細を見る

This app demonstrates the usage of a surrogate model function for predicting the rate capability of an NMC111/graphite battery cell. The rate capability is shown in a Ragone plot. The surrogate function, a Deep Neural Network, has been fitted to a subset of the possible input data ... 詳細を見る

This app demonstrates the following: Importing measured data from a text file or use built-in functionality for data generation Automatically change solver options based on the input Dynamically update the equation display The app can be used to estimate parameters in models without ... 詳細を見る

This example builds surrogate models with deep neural network (DNN) training to quickly estimate the performance of a microstrip patch antenna based on four design parameters: patch length, tuning stub length, dielectric constant of a substrate, and frequency. The model also simulates a ... 詳細を見る