Innoslate
SPEC Innovations’ leading model-based systems engineering solution is designed to help your team minimize time-to-market, reduce costs, and mitigate risks, even with the most complex systems. Available as both a cloud-based and on-premise application, it offers an intuitive graphical user interface accessible through any modern web browser.
Innoslate's comprehensive lifecycle capabilities include:
• Requirements Management
• Document Management
• System Modeling
• Discrete Event Simulation
• Monte Carlo Simulation
• DoDAF Models and Views
• Database Management
• Test Management with detailed reports, status updates, results, and more
• Real-Time Collaboration
And much more.
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Azore CFD
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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Apollo Autonomous Vehicle Platform
A combination of sensors, including LiDAR, cameras, and radar, gather data from the vehicle's surroundings. By employing sensor fusion technology, perception algorithms are capable of identifying, locating, measuring the speed, and determining the orientation of various objects on the road in real time. This advanced autonomous perception system is supported by Baidu's extensive big data infrastructure and deep learning capabilities, along with a rich repository of labeled real-world driving data. The robust deep-learning platform, complemented by GPU clusters, enhances processing power. Additionally, the simulation environment enables virtual driving across millions of kilometers each day, leveraging diverse real-world traffic and autonomous driving data. Through this simulation service, partners can access an extensive array of autonomous driving scenarios, allowing for rapid testing, validation, and optimization of models in a manner that prioritizes both safety and efficiency, ultimately fostering advancements in autonomous vehicle technology.
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SIMulation Workbench
Hardware-in-the-loop simulation serves as a reliable and economical method for conducting tests on physical equipment. It is particularly well-suited for validating designs and assessing intricate systems like those found in vehicles, aircraft, missiles, satellites, rockets, and trains. Instead of testing in real-world settings, evaluations are carried out within a virtual environment. A significant portion of the testing framework is substituted with mathematical models, enabling the integration of various components into a closed-loop system. This approach results in tests that are not only repeatable and organized but also expedited and more dependable. Current hardware-in-the-loop simulation technologies include the SIMulation Workbench real-time modeling platform, which operates on the RedHawk Linux OS. With SIMulation Workbench, users benefit from an all-encompassing framework that simplifies the development and execution of real-time hardware-in-the-loop simulations. The ability to simulate in a controlled environment enhances the accuracy and efficiency of the testing process, making it an invaluable tool in modern engineering.
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