Developing catalysts and particulate filters with advanced materials like Platinum, Cerium, and Zeolite is critical for meeting evolving emission regulations. These materials must address new pollutants like N₂O, CH₂O, and CO₂,
EXHAUST AFTERTREATMENT SYSTEM SOLUTIONS
Exhaust aftertreatment (EAT) systems are crucial for reducing harmful emissions like NOx, CO, HC, and PM, ensuring compliance with strict environmental regulations. Modeling EAT systems is key to optimizing performance, predicting behavior under various conditions, and accelerating development. Gamma Technologies provides an advanced platform for EAT system modeling, offering tools to design, optimize, and validate systems across automotive, genset, marine, locomotive, and chemical industries, ensuring top-tier emission control.
EXISTING CHALLENGES
Exhaust aftertreatment system development is advancing as engineers explore zero-carbon and low-carbon fueled engines, while traditional gasoline, diesel, and hybrid powertrains are increasingly used in a variety of applications.
New Catalyst and Particulate Filters
while integrating carbon capture, utilization, and storage (CCUS) technologies to reduce greenhouse gases.
Are your current modeling tools equipped to handle these complex challenges?
Thermal Management
Managing transient emissions during cold start phases, including the time to catalyst light-off and cumulative emissions, presents a significant challenge across various applications. In systems with extended off periods, such as hybrid configurations or intermittent operations,
engineers must ensure the catalyst remains warm and ready to perform efficiently upon restart. Addressing this issue requires precise thermal management and emission control.
Is your current modeling solution capable of effectively tackling these thermal management challenges?
Catalyst Aging and Poisoning
Catalyst aging and poisoning, resulting from performance degradation due to exposure to high temperatures and contaminants, pose significant challenges for engineers in ensuring the long-term efficiency of exhaust aftertreatment (EAT) systems.
Accurately predicting and managing catalyst lifespan is complex and requires precise modeling.
Are your current modeling tools capable of effectively simulating catalyst degradation and optimizing performance over extended periods?
System Complexity and Controls
System complexity and control strategies, such as fuel dosing for particulate filter regeneration, urea dosing for selective catalytic reduction (SCR) NOx conversion, and control of fuel burners or electrically heated components for rapid catalyst warmup, present substantial challenges.
Engineers must manage the delicate balance between these systems to ensure efficient performance.
Are your current modeling tools capable of optimizing these complex control systems effectively?
EXHAUST AFTERTREATMENT MODELING USING GT-SUITE
GT-xCHEM is an advanced tool for modeling exhaust aftertreatment systems, designed to ensure emission compliance across various applications. It supports the modeling of diverse components, including electrically heated catalysts, three-way catalysts, and advanced particulate filtration systems. The tool excels in simulating chemical reactions and addressing thermal and flow non-uniformities. With its monolith design template, it facilitates the modeling of different types of flow-through catalysts and wall-flow particulate filters, offering axial and radial zone layouts for zone-coated catalysts. Optimization features allow engineers to fine-tune catalyst size, precious metal loading, and system layout to meet stringent emission targets. The Quasi-steady flow solver, combined with large time-step transient solutions, provides faster-than-real-time results, enhancing efficiency. GT-xCHEM’s intuitive interface and flexible post-processing capabilities make it easy to generate and compare results. Advanced, well-calibrated examples are included to guide users in effectively applying the tool.
GT-xCHEM offers a highly flexible reaction mechanism template, allowing users to define custom reaction mechanisms tailored to specific requirements. This flexibility ensures precision and adaptability across various applications. Additionally, it includes well-calibrated model examples that serve as a strong starting point, enabling users to build upon proven models and streamline their simulation processes efficiently.
Ageing Model: The catalyst activity ageing model simulates the gradual degradation of catalyst performance over time by reducing the site dispersion factor based on several key variables. This helps predict the impact of aging on efficiency and lifespan.
Poisoning: The model also incorporates the effects of platinum oxide formation and sulfur poisoning, where site blocking coverages reduce catalyst activity. By simulating these poisoning effects, the model enables better prediction and management of catalyst performance under harsh conditions.
Integration with GT-SUITE enhances the tool’s utility by enabling the combination of subsystem models into unified system-level simulations. This integration facilitates a comprehensive evaluation of system interactions and trade-offs, such as emission reduction versus fuel consumption, NOx versus particulate matter (PM) emissions, thermal boundary conditions for system control, and optimization of control strategies. This empowers engineers to explore a wide range of scenarios and optimize overall system performance across various applications.
GT-xCHEM with GT-SUITE leverages the power of machine learning to revolutionize chemical kinetics modeling, offering faster and more efficient simulations for a wide range of industrial and research applications. By integrating advanced computational techniques, the tool simplifies complex tasks, enabling engineers to optimize designs and streamline workflows. It accelerates simulations, facilitating rapid-running plant models for multi-physics simulations, hardware-in-the-loop simulations, and design optimization. With lightweight mathematical models deployable on microcontrollers, embedded control units (ECUs), or low-power devices, it ensures optimal performance even in constrained environments. The tool also supports dynamic and static metamodeling techniques, such as polynomial regression, Gaussian interpolation, and neural networks, including multi-layer perceptrons and non-linear autoregressive exogenous models (NARX), to capture intricate system dynamics. By enhancing decision-making, GT-xCHEM empowers engineers to understand complex relationships between inputs and outputs, leading to more informed and accurate decisions.
In aftertreatment systems, effective thermal management involves technologies such as electrically heated components, burners, and secondary air pumps, which are particularly beneficial during cold starts. The design and optimization of system components help maintain ideal temperatures by minimizing thermal losses. Additionally, phase change materials (PCMs) play a key role in preventing system cool-down during shutdowns, which is crucial for maintaining performance in various applications, including hybrid systems.
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