Category: GT-SUITE

HVACR simulation machine learning|hvac machine learning simulation|EV thermal system model with physics-based solution and feedforward neural net|machine learning simulation in hvac industry

Simulation for the HVACR Industry: How to Leverage Machine Learning

The HVACR Industry is Evolving As we step into 2025, major trends in systems simulation are emerging. The heating, ventilation, air conditioning, and refrigeration (HVACR) industry is seeing accelerated growth in the adoption of simulation throughout the design and development process. This industry is looking to further modernize, appeal to consumers, and demand energy-efficient, sustainable […]

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making music with mutiphysics|eVTOL battery simulation||||||anc GT-SUITE simulation|ANC system simulation model

Making Music with Multiphysics

The capabilities of simulation software appear to be endless (not really, but you know what I mean…) when it comes to modeling different systems and things that may not have been simulated before. This can be especially true when considering how model-based systems engineering (MBSE) has advanced in the past few decades from single-purpose tools […]

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eVTOL battery simulation|||||

How Simulation Accelerates the Development of eVTOL Aircraft for Taxi Services

Unlocking the Potential of eVTOL Aircraft for Taxi Services: Advancing On-Demand Transportation Safely and Efficiently The world is rapidly advancing towards an integrated and accessible on-demand transportation network. Electric Vertical Takeoff and Landing (eVTOL) vehicles have emerged as the ideal solution for the near future, offering faster and more efficient travel options. However, ensuring the […]

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single cylinder and multi cylinder engine simulation|cabin model order reduction simulation workflow results|3D GT-TAITherm Cabin Model|HVAC system simulation GT-SUITE|cabin modelling simulation|3d cabin modelling simulation|cabin modelling simulation fidelities|vehicle cabin temperature simulation|temperature cabin simulation results|dynamic and static neural networks|dynamic machine learning simulation|battery call model simulation|neural network structure|predicted vs. target stored ammonia coverage and NO outlet mass flow rate|metamodel predictions of battery thermal performance simulation|neural network and a linear interpolating lookup map|doe simulation|Transient neural network predictions of voltage and state of charge (SOC)|neural network structure|machine learning simulation|||||machine learning neural networks simulation|Torsional and Transverse Vibration in an Accessory Drive|GT-SUITE accessory drive model|belt tension and global slip simulation|Main Effects Plots for Specified Attributes or Inputs Ranking|Variational Analysis for Specified Attributes|accessory drive machine learning simulation|single cylinder and multi cylinder engine simulation||||

Combining Measurements and Simulation to Streamline Combustion/Controls Development

How to use Simulation to Improve the Engine Development Process for Carbon Neutral Fuels  The need for clean, renewable energy sources requires exploring carbon neutral fuels and their combustion behaviors. This is typically done using single-cylinder (SC) engines. The advantages of this process are to make quick hardware changes such as replacing the head or […]

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accessory drive machine learning simulation|dynamic machine learning simulation|neural network structure|predicted vs. target stored ammonia coverage and NO outlet mass flow rate|dynamic and static neural networks|metamodel predictions of battery thermal performance simulation|battery call model simulation|Transient neural network predictions of voltage and state of charge (SOC)|neural network structure|machine learning simulation|||neural network and a linear interpolating lookup map|doe simulation|||machine learning neural networks simulation|GT-SUITE accessory drive model|Torsional and Transverse Vibration in an Accessory Drive|belt tension and global slip simulation|Main Effects Plots for Specified Attributes or Inputs Ranking|Variational Analysis for Specified Attributes|belt tension and global slip simulation

Leveraging Machine Learning for Early Design Decisions on an Accessory Belt Drive Simulation

There are various challenges faced by an automotive engineer while designing a robust and optimized accessory drive system. Most original equipment manufacturers (OEMs) rely on different suppliers for their engine belt(s) and accessories (e.g. water pumps, alternators, A/C compressors, etc.). This leads to challenges in obtaining a comprehensive set of input data to incorporate in […]

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dynamic machine learning simulation|machine learning neural networks simulation|||||neural network and a linear interpolating lookup map|doe simulation|machine learning simulation|neural network structure|Transient neural network predictions of voltage and state of charge (SOC)|battery call model simulation|metamodel predictions of battery thermal performance simulation|dynamic and static neural networks|predicted vs. target stored ammonia coverage and NO outlet mass flow rate|neural network structure

Dynamic Machine Learning for Modeling and Simulation

Incorporating Dynamic Metamodeling Simulation To save computational time, engineers are persistently trying to speed up physical models, and some situations absolutely require faster simulation speeds. These situations might include more advanced co-simulation tasks, performing model-based optimization on a slower physical model, or the need to have a surrogate model for XiL (X-in-the-Loop) applications or to […]

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|GT SUITE and SUMO traffic simulation|Co-simulation GT SUITE SUMO vs SUMO|co simulation GT-SUITE and SUMO EV example|co simulation GT-SUITE|simulate driving in traffic|NASA hydrogen rocket simulation|||

Gamma Technologies and GT-SUITE: Pioneering the Future of Simulation

Unveiling the Power of GT-SUITE This year, Gamma Technologies celebrated a significant milestone: its 30th anniversary. Since its inception in 1994, Gamma Technologies has been at the forefront of engineering simulation, revolutionizing how industries approach design and innovation. At the heart of this transformation is GT-SUITE, the company’s flagship systems simulation software that has become […]

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GT SUITE and SUMO traffic simulation|||NASA hydrogen rocket simulation|simulate driving in traffic|co simulation GT-SUITE|co simulation GT-SUITE and SUMO EV example|Co-simulation GT SUITE SUMO vs SUMO

Simulating Real Driving Maneuvers in Traffic using SUMO and GT-SUITE

The Need for Realistic Vehicle Operating Conditions   In an era where mobility is becoming increasingly electrified, new engineering strategies are needed to properly optimize an entire vehicle system for both fuel and energy saving potential that account for a multitude of driving scenarios.  Especially during local commutes with traffic, being able to predict both […]

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NASA hydrogen rocket simulation||

Simulating a NASA Hydrogen Powered Rocket

Propelling the Orion Spacecraft to the Moon Images of the moon from the NASA Orion spacecraft reminds us of how our technological advancements have made these wonders of the night sky reachable. The Artemis I mission marked an important milestone as it is the closest a human rated spacecraft has come to the moon since […]

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