Engineering Simulation Tools Overview

Assessing Aeroacoustics of Fan Noise in CFD by ENGYS 🚗 Reducing automotive cooling fan noise is critical - with levels reaching up to 85dBA, manufacturers seek efficient CFD solutions. Automotive cooling fans are a major noise source, reaching up to 85dBA at certain frequencies. To tackle this, Johnson Electric partnered with Engys to simulate and reduce fan noise using advanced CFD techniques. The project combined two computational approaches: an unsteady RANS (uRANS) simulation to analyze tonal noise within a 12-hour CPU time and a detached eddy simulation (DES) to assess broadband noise, validated against experimental results. Simulating turbulent flows is challenging, requiring accurate modeling of both the noise source and acoustic wave propagation. Engys leveraged its Helxy software, using an acoustic analogy approach to balance accuracy and computational efficiency. A CAD model of the fan, including the anechoic chamber, was analyzed to optimize mesh, time steps, and numerical schemes. Their extrude meshing algorithm improved boundary layer resolution while maintaining smooth transitions, cutting turnaround times by 20-30%. More on tackling CFD aeroacoustic challenges here: https://lnkd.in/eJxNhuAX #CFD #Aeroacoustics #NoiseReduction #AutomotiveEngineering #Simulation

The more I work in this field, the more I encounter people who assume open-source FEM is limited to educational purposes and lacks critical real-world features like non-matching mesh interfaces. Below, you can see how a solid plate is coupled on both sides with an acoustic domain that has a coarser mesh. How is it done? Building an interpolation matrix (which I've already open-sourced). Can you see how many applications can benefit from this? Mufflers, compressors, airboxes—virtually any system where a shell radiates into a surrounding environment. You don't need to spend over $50k to perform this type of simulation. We can guide you through making the switch. My tools: mesh : gmsh FEM: FEniCSx post: ParaView #nonmatchingmeshes #vibroacoustics #realworldapplications #opensource

Multiphase Flow Modeling Techniques chart! 1. Particle-Based Methods: MPS & SPH   - MPS (Moving Particle Semi-implicit) and SPH (Smoothed Particle Hydrodynamics) are versatile Lagrangian approaches.   - MPS handles incompressible flows with strong surface tension, while SPH excels in simulating free-surface and highly dynamic flows. - Conservation of mass and momentum for individual fluid particles are solved, with fluid properties interpolated between neighboring particles. 2. Lattice Boltzmann Method (LBM)   - LBM is a mesh-based, mesoscopic method that simplifies fluid dynamics simulations, particularly for complex geometries.   - LBM solves the Boltzmann kinetic equation and is suitable for simulating multiphase flows with free surfaces and phase interfaces. 3. Grid-Based Methods:   - With Interface Capturing: Grid-based techniques, like Volume of Fluid (VOF) and Level-Set, track phase interfaces.   - VOF is ideal for sharp interface representation, while Level-Set offers smooth interface tracking, suitable for complex topology changes. - Conservation equations (mass, momentum) are solved along with an additional advection equation for interface capturing. 4. Grid-Based Methods:   - Without Interface Capturing: Eulerian Multiphase Model treat each phase as a separate fluid with mass and momentum equations.   - Eulerian Multiphase Model effectively captures dispersed phase behaviors by solving separate continuity and momentum equations for each phase, considering interfacial forces and phase interactions. - It solves separate continuity and momentum equations for each phase, coupled with models for dispersed phase behaviors (e.g., particle trajectories in DPM). - Discrete Phase Model (DPM): A Eulerian-Lagrangian approach used to simulate dispersed phase behavior, such as suspended particles in a continuous fluid. - DPM solves Lagrangian equations of motion for individual particles, accounting for drag, lift, and other forces, coupled with the continuous phase flow. - Discrete Element Method (DEM) is a particle-based method used to study granular materials and their interactions under various flow conditions. - DEM considers contact mechanics and collision forces between discrete particles, allowing simulations of particle packing, flow, and compaction. Picture Source: CFD Flow Engineering #mechanicalengineering #mechanical #aerospace #automotive #cfd

Your plan to become a BIM specialist: 1) Learn Revit Take online courses or tutorials (e.g., Udemy, LinkedIn Learning, or Autodesk’s official training). Practice creating models for different disciplines (architectural, structural, MEP). Focus on: 1- Creating walls, floors, roofs, and structural elements. 2- Adding families (parametric components like doors, windows, etc.). 3- Generating construction documents (plans, sections, schedules). 2) Learn Navisworks 1- Use Navisworks for clash detection and project coordination. 2- Learn to merge models from different disciplines and run clash tests. 3) Explore Dynamo (Optional but Recommended) Dynamo is a visual programming tool for Revit that automates repetitive tasks. Learn to create scripts for tasks like placing families, generating geometry, or extracting data. 4) Gain Knowledge of BIM Standards and Processes 1- Study BIM Level 2 standards (common in many countries). 2- Understand the COBie (Construction Operations Building Information Exchange) format for data delivery. 3- Learn about Common Data Environments (CDEs) like BIM 360 or Aconex for collaboration. 5) Build a Portfolio Create sample projects showcasing your BIM skills. Include: 1- 3D models of buildings or structures. 2- Construction documentation (plans, sections, schedules). 3- Examples of clash detection and coordination. 4- Any automation scripts (if you’ve learned Dynamo). 6) Get Certified (Optional but Helpful) Certifications can boost your credibility: 1- Autodesk Certified Professional (ACP) in Revit. 2- Certified BIM Manager (from organizations like AGC or RICS). 3- ISO 19650 Certification for BIM standards. 7) Gain Practical Experience 1- Internships: Look for internships or entry-level roles in AEC firms. 2- Freelancing: Take on small BIM modeling projects on platforms like Upwork or Fiverr. 3- Networking: Join BIM communities (e.g., LinkedIn groups, forums like Revit Forum) to connect with professionals. 8) Stay Updated 1- Follow industry trends like BIM Level 3, Digital Twins, and AI in BIM. 2- Attend webinars, conferences, and workshops on BIM. 3- Keep learning new tools and techniques.

Ever Wonder How Cities Predict and Prevent Traffic Jams Before They Happen? 🚦 The answer lies in Digital Twin Cities – dynamic, data-rich virtual replicas of our city environments. A live, interactive command center. Here's your streamlined workflow for smart transportation: 1️⃣ Data Foundations Gather Data from Real-time traffic sensors (JSON/XML streams), vehicle GPS, public transport feeds, and weather APIs. 2️⃣ Standardise your City DT for Interoperability Use GeoJSON for features like road networks, zones and CityGML for rich, semantic 3D city models with buildings, vegetation, and transport infrastructure. Use IFC for BIM-specific assets like bridges, train stations. 3️⃣ Create the Core Digital Twin Platform A central meta hub (often cloud-based) manages this standardized data using spatial capabilities. This happens only (!) in the gaming engine's DT capability tables. 4️⃣ Model Assets & Relationships Create digital representations of roads, signals, vehicles, etc., and define their interactions. 5️⃣Gaming Engine Meta-Layer Import your data (CityGML, IFC translated to FBX/glTF; GeoJSON mapped) into the gaming engine. Ideally have a plug-in mode for your data through FME - your feature manipulation engine. I call it the "Swiss Knife" 😇 6️⃣Real-Time Dynamics Connect your live data streams to animate the 3D scenes you created (e.g., vehicle movement, traffic signal status). Have your Interactive UIs. This is your visualized data dashboard - for querying data, controlling simulations, and visualizing the insights you want to have. 7️⃣The Gold Standard - AI-Powered Insights "What-If" Scenarios: Model impacts of road closures, signal timing changes, within the gaming engine. Apply AI to forecast congestion and optimize traffic flow dynamically. Twins are never truly finished. As a city, establish this solid foundation from the beginning to avoid finding yourself in a dead end down the road. #SmartCities #CityGML #GeoJSON If you find this helpful... ----------- Follow Me for #digitaltwins Links in My Profile Florian Huemer

A month ago, I shared a simulation video of the 𝐃𝐢𝐫𝐞𝐜𝐭𝐞𝐝 𝐄𝐧𝐞𝐫𝐠𝐲 𝐃𝐞𝐩𝐨𝐬𝐢𝐭𝐢𝐨𝐧 (𝐃𝐄𝐃) process of a titanium wire. Since then, we've added 𝐆𝐏𝐔 𝐬𝐮𝐩𝐩𝐨𝐫𝐭 to our simulation software, significantly reducing simulation time and enabling more complex and detailed studies. The following video demonstrates the deposition process of a titanium wire (1 mm radius) on a (4 x 4) cm² substrate across 𝐟𝐨𝐮𝐫 𝐥𝐚𝐲𝐞𝐫𝐬. The wire is melted using 𝐭𝐡𝐫𝐞𝐞 𝐆𝐚𝐮𝐬𝐬𝐢𝐚𝐧 𝐥𝐚𝐬𝐞𝐫 𝐛𝐞𝐚𝐦𝐬, each's power is individually controlled to maximize the deposition rate. The breakage of the liquid bridge connecting the wire and substrate can be observed during the deposition of the last track in the fourth layer. We employ a 𝐫𝐚𝐲 𝐭𝐫𝐚𝐜𝐢𝐧𝐠 algorithm to model the laser-material interaction, where the total laser power is distributed among numerous rays. The laser energy absorbed by the material surface is computed based on ray intersections with the material surface, considering surface temperature, angle of incidence, and polarization. In the video, the upper section displays the temperature field, while the lower section shows the number of ray intersections with the material surface throughout the simulation. Simulated on a Ryzen 7950x3D and an RTX4070. The video is rendered using Blender. Get in touch with us at blank-simulations if you see potential application scenarios. #SPH #multiphysics #raytracing #additivemanufacturing 𝐌𝐞𝐭𝐡𝐨𝐝: - Smoothed Particle Hydrodynamics (SPH) - MPI-OpenMP parallelization - GPU-acceleration - Dynamic workload balancing - Adaptive particle refinement 𝐏𝐡𝐲𝐬𝐢𝐜𝐬: - Ray tracing to model laser-material interaction - Temperature-dependent material properties - Latent heat of fusion and crystallization - Evaporation and recoil pressure - Surface tension and wetting

● What is BIM? Building Information Modeling (BIM) is a digital representation process that provides insights and tools for planning, designing, managing, and constructing buildings and infrastructure efficiently. It integrates data from various disciplines into a cohesive model. ● Key Benefits of BIM: ○ Project Perspective: - Enhances collaboration and communication among stakeholders. - Improves design quality. - Reduces errors and rework through early detection of potential issues. ○ Financial Perspective: - Optimizes resource management. - Reduces project costs by minimizing waste and inefficiencies. - Enables better decision-making through accurate data analysis. ● Implementing BIM in a Traditional Company: Transitioning to BIM involves several steps: ○ Assessment: Evaluate current processes and readiness for change. ○ Training: Invest in training programs for staff to familiarize them with BIM tools and workflows. ○ Pilot Projects: Start with small projects to test and refine BIM processes. ○ Integration: Gradually integrate BIM into larger projects, ensuring continuous support and feedback. ● Standards to Abide By: ○ ISO 19650: International standards for managing information over the whole life cycle of a built asset using BIM. ○ PAS 1192: Series of British standards that provide a framework for collaborative working and information management. ● Platforms and Courses for Upskilling: ○ Platforms: - Autodesk Revit: Widely used for architectural design, MEP, and structural engineering. - ArchiCAD: Popular among architects for its powerful design and documentation tools. - Bentley Systems (AECOsim): Useful for complex infrastructure projects. - Navisworks: Ideal for project review and clash detection. ○ Courses: - Coursera: Courses like "BIM Fundamentals for Engineers" by National Taiwan University. - LinkedIn Learning: Courses such as "Learning BIM 360" and "Revit: Basic Training". - Udemy: Offers various BIM courses including "The Complete Revit Guide". - Autodesk University: Extensive resources and courses on all Autodesk products. - BIM Certification Programs: Look for certifications from institutions like RICS or buildingSMART. ○ Universities offering BSc and MSc qualifications: - Massachusetts Institute of Technology (MIT): Offers BSc and MSc in Architecture with a focus on BIM. - ETH Zurich: Offers BSc and MSc programs in Architecture and Civil Engineering with BIM specialization. - University College London (UCL): Offers BSc and MSc in Engineering and Architectural Design with BIM modules. - Delft University of Technology: Offers BSc and MSc programs in Architecture and Building Technology with BIM courses. - Carnegie Mellon University: Offers BSc and MSc in Civil and Environmental Engineering with BIM concentrations. Embrace BIM to drive your projects toward greater efficiency and innovation!

Dear CAE Enthusiasts, I'm excited to share a comprehensive set of notes that I compiled during my engineering studies - Enriched with both theoretical understanding and hands-on practical experience. These topics cover the essential foundations of Finite Element Analysis (FEA) and Abaqus, and are designed to help you strengthen your core skills in simulation and analysis. I hope you find them valuable in your learning journey and day-to-day applications. # Topics Covered Below : - Types of Analysis - Basics of FEA - Stress-Strain Diagram - Theories of Failure - Types of Elements in Abaqus - Simulations to Be Performed in Abaqus - Step-by-Step Procedure - File Formats in Abaqus - Increments in Abaqus - Requirements of Meshing in Basic Studies - Mid-Surfacing - Couplings - Multiload or Multi-Step Simulation - Oblique Loading - Abaqus Output Variables - Truss Problem to Be Done - Buckling & Eigenvalues - Heat Transfer Problems (Steady & Transient) - Non-Linearity - Stiffness Matrix - Convergence - Contact Algorithms - Dynamic Temperature Displacement - Pressure Vessel Simulation Study - Plain Stress - 3 Point Bending - Introduction to Dynamic Simulation - Model Analysis - Solvers Comparison for Modal Simulation - FRF Simulation - Resonance Condition - Implicit vs Explicit Simulation - Stress Due to Self-Weight - Time-Dependent Load Stay tuned as I dive into each topic in upcoming posts! Feel free to connect if you're passionate about FEA, Abaqus, or simulation in general. Let's grow and learn together. "Keep Sharing, Keep Learning" - DP DESIGN #FEA #Abaqus #EngineeringAnalysis #Simulation #FiniteElementAnalysis #MechanicalEngineering #CAE #StructuralAnalysis

FDTD simulation of a moving jet illuminated by a plane wave source: https://lnkd.in/eR37qCSB 𝗙𝗗𝗧𝗗 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗮 𝗠𝗼𝘃𝗶𝗻𝗴 𝗝𝗲𝘁 𝗜𝗹𝗹𝘂𝗺𝗶𝗻𝗮𝘁𝗲𝗱 𝗯𝘆 𝗮 𝗣𝗹𝗮𝗻𝗲 𝗪𝗮𝘃𝗲 In this video, I present the finite-difference time-domain (FDTD) simulation of a moving jet illuminated by a plane wave. This example highlights our innovative approach to modeling electromagnetic interactions with moving structures. 𝙏𝙝𝙚 𝘾𝙝𝙖𝙡𝙡𝙚𝙣𝙜𝙚 𝙬𝙞𝙩𝙝 𝙏𝙧𝙖𝙙𝙞𝙩𝙞𝙤𝙣𝙖𝙡 𝙈𝙚𝙩𝙝𝙤𝙙𝙨: Previous methods for analyzing electromagnetic wave interactions with moving objects relied on Voigt-Lorentz transformations. These transformations adjust the reference frame to account for motion, but they come with significant limitations: 𝘾𝙤𝙢𝙥𝙡𝙚𝙭𝙞𝙩𝙮: Implementing Voigt-Lorentz transformations in a full-wave simulator with moving objects is challenging. 𝙍𝙚𝙨𝙩𝙧𝙞𝙘𝙩𝙚𝙙 𝘼𝙥𝙥𝙡𝙞𝙘𝙖𝙩𝙞𝙤𝙣𝙨: These methods are not suitable for scenarios involving non-uniform motion, such as oscillation, rotation, and acceleration. 𝙊𝙪𝙧 𝙋𝙧𝙤𝙥𝙤𝙨𝙚𝙙 𝙁𝘿𝙏𝘿 𝘼𝙥𝙥𝙧𝙤𝙖𝙘𝙝: Our approach represents a shift from the traditional methods. Instead of transforming time, space, and electromagnetic fields, we directly update the positions of the moving objects within the FDTD time-stepping loop. Here’s why this is a game-changer: 𝙀𝙣𝙝𝙖𝙣𝙘𝙚𝙙 𝙀𝙛𝙛𝙞𝙘𝙞𝙚𝙣𝙘𝙮: By embedding the motion into the simulation grid, we simplify calculations and significantly improve computational efficiency. 𝙉𝙪𝙢𝙚𝙧𝙞𝙘𝙖𝙡 𝙎𝙩𝙖𝙗𝙞𝙡𝙞𝙩𝙮: We address challenges such as discontinuous motion by implementing techniques to ensure smooth and accurate electromagnetic field behavior. 𝙁𝙡𝙚𝙭𝙞𝙗𝙞𝙡𝙞𝙩𝙮: Our method is versatile and well-suited for a wide range of scenarios, from steady to rapidly changing motions, providing accurate results even for complex 3D shapes like aircraft. 𝘼𝙥𝙥𝙡𝙞𝙘𝙖𝙩𝙞𝙤𝙣𝙨 𝙖𝙣𝙙 𝙄𝙢𝙥𝙖𝙘𝙩: Our method has broad applications, including: 𝙍𝙖𝙙𝙖𝙧 𝙎𝙮𝙨𝙩𝙚𝙢𝙨: Detection and analysis of moving objects. 𝙒𝙞𝙧𝙚𝙡𝙚𝙨𝙨 𝘾𝙤𝙢𝙢𝙪𝙣𝙞𝙘𝙖𝙩𝙞𝙤𝙣𝙨: Modeling of signal behavior in dynamic environments. 𝘼𝙚𝙧𝙤𝙨𝙥𝙖𝙘𝙚 𝙀𝙣𝙜𝙞𝙣𝙚𝙚𝙧𝙞𝙣𝙜: Design and assessment of aircraft performance. The video showcases our method’s ability to simulate interactions between the electromagnetic plane wave and the moving jet, demonstrating the robustness and accuracy of our FDTD approach. I’m eager to hear your thoughts on this advancement in computational electromagnetics. Let’s discuss the future possibilities of this method! #Electromagnetics #FDTD #ComputationalPhysics #RadarSystems #AerospaceEngineering #WaveSimulation #Innovation #ElectromagneticWaves #ResearchAndDevelopment

How does automakers make sure the #electronics inside of your car is safe against external electromagnetic noise? We have #emc tests such as radiated immunity where we have an #antenna outside the car generating noise and we need to make sure all the electronics such as #pcb and ECUs inside the car are working as expected. Here we have a test where we measure the electric field on the dashboard of the car and calibrate the antenna to generate a 70V/m incident E-field from 30 to 100Mhz. The goal is to identify if a critical system is placed in an area where it will be susceptible to high intensity fields. The simulation results with #ansys #hfss are very close to measurements (I would say this is a good correlation considering the complexity of the test and numerical model as well as uncertainties) where we can see peaks of around 200V/m. Simulation of course can provide lots of insight, since it does not need a physical prototype or an anechoic chamber (which can be very expensive and difficult to get access to) so it can be used early in the design stage evaluating different scenarios. We published the results here in case you need more details: J. Mologni, et al., "The significance of specific vehicle parts on automotive radiated immunity numerical simulations," 2015 SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference, doi: 10.1109/IMOC.2015.7369065.