Forbes India’s Post

Our latest research paper, focused on an Adjoint-based, Machine Learning strategy for optimizing the GEKO turbulence model in Gas Turbine Combustion applications, is now available! https://lnkd.in/eaNUAC32 📚💡

If you want to know why batteries are aging, what the influencing factors on aging are and how you can speed up your battery system design and development by simulating the electric-thermal and aging behaviour of batteries join our upcoming webinar! Few seats are left

Mathematical modelling for 1,6-hexanediol diacrylate photopolymerization in presence of oxygen.

Delighted to share insights from the recent technical paper titled "Simulation-Based System Reliability Analysis of Electrohydraulic Actuator with Dual Modular Redundancy". This study dives into the realm of failure detection systems, focusing on an electro-hydraulic actuator with dual modular redundancy. The paper also talks about the ESI's Hybrid Twin™ concept, a synergy of a virtual twin, mirroring the actuator's ideal behavior, and a digital twin, pinpointing potential failures by analyzing sensor readings. What's remarkable is the integration of simulation-based system reliability analysis, paving the way for a dataset meticulously curated for training the digital twin via machine learning algorithms. This innovative approach incorporates decision trees, ensuring a systematic methodology to detect failures, while the paper meticulously outlines the process used to assess the quality of the results.  https://lnkd.in/dC4vBVFs Kudos to the team behind this insightful paper! 🚀🔬 #EngineeringInnovation #SimulationTechnology #ReliabilityAnalysis #esigroup #HybridTwinConcept

Operations Research practitioners often want to model complicated functions that are difficult to encode in their underlying optimization framework. Michael Forbes The University of Queensland discusses a new approach to integrating simulation into the optimization model itself. ➡️ https://lnkd.in/ghNFii8J #IntegerProgramming #Logicbased #BendersDecomposition #Simulation #ResourceAllocation #ShiftScheduling

Reprocessing of tailings... Some thoughts on whether the inherent stability of filtered tailings stacks, together with online assaying, data science and digital twins could mean that any future reprocessing of tailings can be planned-for in advance. Is it even possible to design deposition into the Tailings Storage Facility of the future to optimise for this? https://lnkd.in/eWfDjvdH

Do you know what a MAP is❓ 👉 The Materials Acceleration Platforms (MAP) concept couples robotically executed high-throughput #materials synthesis and characterization in a closed loop that is accelerated by AI-driven experimental planning, data analytics, and advanced simulation techniques to realize materials and device development at least 10 times faster than conventional science methods and at a fraction of the cost. 📈 A society that succeeds first in fully implementing the vision of a MAP will be able to stand out significantly in international competition. A briefing note prepared by ➕20 organisations active in the discovery of #advancedmaterials can be found here 🔗https://lnkd.in/e96tGjv2

[𝗥𝗮𝗺𝗮𝗻: 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱] How do you calibrate your Raman systems? 🔬📊 Learn about precise Raman calibration! 📊🔬 🌟 Ready to unlock the precision of Raman calibration? Whether you're in research, academia, or industry, HORIBA's automated calibration tools provide peace of mind and help ensure the success of your experiments. Explore our new webpage to learn more about how our solutions can benefit your work: https://lnkd.in/ecvV6PJA #RamanSpectroscopy #RamanExplained #RamanCalibration

Performance enhancement of a solar-driven DCMD system using an air-cooled condenser and oil: Experimental and machine learning investigations - https://lnkd.in/dxagG_7g • A novel solar DCMD with oil-filled collectors and an air-cooled condenser was proposed. • Machine learning models were used to analyze the performance of the improved system. • Grid search optimization and K-fold cross-validation methods were coupled. • Freshwater productivity and GOR increased by almost 37 % and 31 %, respectively. • The ANN and SVR models provided high accuracy in under two seconds of computation.

Stress analysis for models with different material properties requires a comprehensive approach that combines advanced numerical techniques, experimental validation, and a deep understanding of material behavior.