
Altium Develop is a collaborative platform for modern electronics engineering teams that connects requirements management, PCB design, systems engineering, and manufacturing workflows.
Built on Altium Designer and Altium 365, the platform provides a centralized environment for design collaboration, requirements traceability, BOM management, supply chain visibility, and engineering change management.
Altium Develop helps hardware organizations maintain alignment between requirements, design decisions, and manufacturing outcomes while supporting distributed engineering teams through cloud-based collaboration.
Core Features:
• PCB design collaboration
• ECAD-MCAD co-design workflows
• Component and supply chain visibility
• BOM and engineering change management
• Design review and approval workflows
• Cloud-native team collaboration
• Requirements management and traceability
Used by electronics teams building complex PCB-based products, Altium Develop is frequently evaluated alongside Cadence OrCAD, Cadence Allegro, Autodesk Fusion Electronics, KiCad, Siemens Xpedition, and SOLIDWORKS PCB for organizations seeking greater collaboration and lifecycle visibility across hardware development programs.
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Azore is software for computational fluid dynamics. It analyzes fluid flow and heat transfers. CFD allows engineers and scientists to analyze a wide range of fluid mechanics problems, thermal and chemical problems numerically using a computer. Azore can simulate a wide range of fluid dynamics situations, including air, liquids, gases, and particulate-laden flow. Azore is commonly used to model the flow of liquids through a piping or evaluate water velocity profiles around submerged items. Azore can also analyze the flow of gases or air, such as simulating ambient air velocity profiles as they pass around buildings, or investigating the flow, heat transfer, and mechanical equipment inside a room. Azore CFD is able to simulate virtually any incompressible fluid flow model. This includes problems involving conjugate heat transfer, species transport, and steady-state or transient fluid flows.
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UrbaWind
Wind is a challenging element to understand fully. In city landscapes, its dynamics become increasingly intricate due to interactions with structures, leading to various phenomena such as accelerations (Venturi effect), swirling patterns, descending flows, and disruptions. The constructed environment thus generates a localized climate that frequently results in discomfort for individuals. To foster sustainable architecture and urban design, it is vital to analyze these aerodynamic effects and incorporate them early in the planning stages. This analysis is increasingly sought after by developers in numerous nations. Addressing wind dynamics is essential for the effective creation of outdoor public spaces that enhance user comfort. Furthermore, UrbaWind provides a tool for assessing pedestrian wind comfort by aligning with the comfort standards of different regions, ensuring a more livable urban environment. Ultimately, understanding wind behavior is crucial for improving overall urban quality and enhancing the experience of those who inhabit these spaces.
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NeuralWing
NeuralWing serves as a cutting-edge model for real-time neural simulation and design optimization specifically tailored for transonic aircraft aerodynamics. It leverages the most comprehensive 3D transonic wing dataset, derived from 30,000 steady-state CFD simulations that span a 3D wing operating within the transonic regime, incorporating variations in four distinct geometry parameters and two different inflow conditions. By utilizing Emmi’s AB-UPT surrogate model, which has been meticulously trained on this extensive dataset, NeuralWing empowers users to effortlessly alter wing geometries, conduct optimizations, and enhance aerodynamic efficiency within mere seconds. The model is designed to facilitate transonic 3D wing simulations, accommodating variations in geometry and inflow, while offering real-time inference and optimization of design parameters. Users input a geometry mesh in STL format along with speed and angle of attack, and in return, they receive outputs that include pressure, friction, velocity fields, and integral forces such as lift and drag. Geometry meshes are generated dynamically in response to four design parameters, employing a differentiable approach that allows for swift assessment of design modifications. Furthermore, NeuralWing boasts an impressive accuracy rate of 99.5%, making it an invaluable tool for aerodynamics research and development. This level of precision ensures that engineers can trust the results as they iterate on their designs.
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