One of the biggest challenges in predicting fatigue failure is characterizing the load over the lifetime of a part. Using simulation solutions, like ANSYS Mechanical and ANSYS nCode DesignLife, engineers can run numerous load and design variations to ensure their products meet fatigue specifications and will continue to perform beyond the warranty period. Better yet, they can perform simulations and optimizations before building the product. In this way, engineers can make improvements early in the development cycle and utilize optimization algorithms to further streamline the design process. In this webinar, participants will learn the difference between material fatigue and high- and low-cycle fatigue failure, plus how to account for fatigue in design using simulation.
Say goodbye to complicated user-defined functions (UDF) and hello to expressions. With no deep knowledge of programming, you can easily enter an expression, either directly in the field where it will be applied or as a named expression that can be reused at multiple locations. Attend this webinar to learn how to simplify the specification of complex boundary and cell zone conditions with a wide range of powerful expressions, including: Positional variables Field variables Solution variables Reduction operations
Learn about the new look, features and enhancements that will improve your Ansys Fluent user experience. Start right from the Fluent launcher to choose your starting mode and access recent files and parallel processing for meshing and solving. This webinar will cover the new appearance of the software interface, graphics, display colors and shortcuts; productivity tips within the text user interface; drag and drop features and other behavior changes.
In this webinar, learn more about Ansys SpaceClaim updates that support concept modeling and model prep for simulation, including: block recording and bidirectional CAD interfaces to allow replay of modeling operations on modified CAD geometry; constraint-based sketching that makes it easier to create complex sketches for 3D design; and autoskinning of topology optimization results from Ansys Mechanical for automated geometry reconstruction.
Ansys 2020 R1 empowers Ansys Mechanical users to go further than ever before with enhancements to improve the handling of complex, highly nonlinear and massively large models. Sign up to learn more about the enhancements in Ansys 2020 R1!
Ansys Fluent has been enhanced to organize the process for running simulations with a task-based workflow that guides you through the simulation process, reduces the options to only those that are relevant at each point in the process and provides best practices as defaults. This workflow presents you with the right choices to lead you to an accurate solution, making it possible to develop a better product in less time. Read this white paper to see how the new workflow can be can be utilized to reduce the time and software skill required to mesh watertight CAD geometry.
Using an open ecosystem product, such as Ansys Granta MI for Additive Manufacturing (AM), delivers the required flexibility to overcome the various obstacles that a typical AM build will introduce.
Ansys SPEOS Enterprise performs visual ergonomic reviews for perceived quality, safety and comfort. It also virtually simulates visual aspect, reflection, visibility and information legibility observed in real-world vehicle environments.
The Ansys SPEOS Optical Sensor Test provides a built-in environment for easily evaluating the impact of different design versions (low/high-end) on sensor perception and global product compliance early in the design phase.
The Ansys SPEOS Pro package contains all the core functionalities to simulate the photometric performance — intensity, illuminance and luminance — of lighting systems.
The Ansys SPEOS Premium package contains all functionalities of the Ansys SPEOS Pro package, including one solver and four built- in high-performance computing (HPC) tasks. It has additional advanced analytics for photometry and radiometry, spectral intensity, illuminance and luminance.
Materials experts, designers, engineers and simulation experts need top quality up-to-date technical, environmental and economic properties of materials – metals, plastics, composites, ceramics and more. Such data informs critical decisions in design and materials selection and substitution. Additionally, it helps meet environmental and restricted substance regulations. Ansys Granta collaborates with leading data providers to maintain an unrivalled, diverse catalog of materials reference data, combined with flexible materials selection and data management software.
The increasing complexity of 21st century electronics continues to drive demand for comprehensive multiphysics simulations. Simulation helps engineers determine potential failure risks before physical prototyping, making it one of the most beneficial and cost-effective solutions for electronics manufacturers. However, there are often significant modeling challenges associated with the increased layout complexity of printed circuit boards (PCBs), including finer density traces and intricate routing structures. Fortunately, there are a number of modeling techniques that exist that allow for more complex and accurate PCB models. These techniques range from homogeneous effective material properties to trace mapping to detailed trace modeling. In this webinar we will focus on a trace modeling technique called trace reinforcements. In the trace reinforcement method, copper traces are modeled with 1D or 2D elements that are embedded within 3D structural elements. This strategy allows for the inclusion of detailed trace geometry features in a highly complex PCB model without the unreasonable body/element counts that come with a standard 3D body trace modeling approach. This webinar will discuss when to use trace reinforcement modeling, the accuracy and efficiency the methodology offers, and how to use Ansys Sherlock to automate the creation of a trace reinforcement model.
Application Field: ADAS and Autonomous Driving Advanced driver assistance systems (ADAS) are at the core of automotive safety and will serve as the enabling technologies for autonomous vehicles. In this webinar we explore a high-resolution MIMO radar system simulation in realistic driving scenarios. A full physics-based radar scene corner case is modeled to obtain high-fidelity range-Doppler maps. We investigate the effects of inclined roads on late pedestrian detection as well as the effects of construction metal plate radar-returns on false target identification. The radar returns will be processed into Range-Doppler and Angle of Arrival maps. Additionally, micro-Doppler signatures by vehicles and pedestrians will be studied using full-physics simulation. Speaker: Amazir Moknache, Senior Application Engineer, Ansys
Application Field: ADAS and Autonomous Driving Multiple input, multiple output (MIMO) radar enables “4D imaging” for driver-assistance and automated driving systems. Angular position and range can be determined using triangulation and propagation delay from the sensor to the target. The fourth dimension is the target trajectory (i.e., velocity) which can be extracted from the Doppler frequency shift. Additional information resulting from relative motion within the moving target coordinate system can also be determined. For example, the vibrating mudflaps on a truck, the periodic leg motion of a person riding a bicycle and the rotation of wheels on a vehicle all exhibit characteristic “micro-Doppler” signatures. This webinar will describe the application of HFSS SBR+ to accurately model the physical interaction of radar with dynamic objects to predict radar performance and capture the micro-Doppler effect. We will describe how to create and modify dynamic objects exhibiting motion within the local frame of reference and provide an outlook on the application of machine learning for target classification. Speaker: Hen Leibovich, Application Engineer II, Ansys
With the growth of the electric vehicle market, the demand for smaller and lighter batteries with greater capacity has never been higher. A simple, comprehensive option for a lithium-ion (Li-ion) cell, based on a multiscale, multidimensional (MSMD) battery modeling methodology, has been developed in Ansys Fluent to study the cell-to-cell temperature variation or maximum temperature in the module. This option helps you to investigate the cell-to-cell temperature variation and maximum temperature in an Li-ion battery module/pack much more easily. This webinar reveals the details of this option and demonstrates an example of testing MSMD models with and without this option. What you will learn Get a tour of the Fluent battery modeling options. Learn how to model the battery module or pack in a much simpler way. Learn how to validate the model. Speaker Seeta Gunti , Senior Technical Support Engineer
The evolution of 5G systems is rooted in the consistently increasing need for more data. Whether the application is future medical systems, autonomous vehicles, smart cities, AR/VR, IoT, or standard mobile communications systems, all require an ever-increasing amount of data. For 5G systems to reliably work, the physical data pathways must be well understood and reliably designed. Whether the pathway is in the chip or the wireless channel, large amounts of data must seamlessly flow unimpeded. This presentation will discuss the various data paths in 5G systems and how Multiphysics analysis can help design these paths to allow for maximum data integrity.
The safety analysis of electronics systems is a precondition for obtaining necessary certifications, but may consume more than half of the overall development effort. Ansys medini analyze provides aerospace manufacturers of these systems (and their components) with dedicated support for functional safety analysis. Medini analyze customers report up to 55% decreases in both functional safety analysis efforts and time to market. The model-based tool also eliminates inconsistencies in functional safety analysis work products and accelerates the certification process, especially with respect to design changes.
