Simulation software Product List and Ranking from 177 Manufacturers, Suppliers and Companies

[Example] Electronic Device Heat Dissipation 'AICFD'

Application in conjugate heat conduction analysis for electronic component heat dissipation and battery pack cooling analysis for new energy vehicles!

We would like to introduce application examples of our intelligent thermal fluid analysis software "AICFD" for electronic device heat dissipation. This software provides user-friendly and high-performance simulations through an advanced graphical interface. It can be applied to cooling analysis of battery packs, which are widely used in fields such as electric vehicles, mobile devices, and energy storage. Improving the performance of battery packs can be crucial. You can check the details of the case studies through the related links. 【Case Overview (Partial)】 ■ Conjugate heat conduction analysis for electronic component heat dissipation - Heat dissipation analysis of electronic components within a casing, using laminar flow for conjugate heat conduction analysis - Memory chips are located next to the CPU unit, and various sizes of capacitors, chips, and interfaces are embedded on the motherboard - The radiator is positioned above the CPU, transferring heat from the CPU to the cooling air *For more details, please download the PDF or feel free to contact us.

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Thermo-fluid analysis software
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[Example] Thermal conduction and thermal stress coupled analysis of circuit boards 'AIFEM'

Quickly model electronic circuit structures using AIFEM! Evaluate the rationality of temperature and stress distribution.

We would like to introduce a case study of thermal stress coupled analysis of circuit boards using the general-purpose finite element analysis software "AIFEM." Thermal stress analysis plays a crucial role in optimizing the thermal design of products, especially for high-power heating electronic components and devices, thereby enhancing the reliability of electronic equipment. By utilizing AIFEM, we quickly modeled the electronic circuit structure, created thermal transfer and heat source models, and evaluated the rationality of temperature and stress distribution. [Case Overview] ■ Volume heat source (target red area): 1.5 [mW/mm3] ■ Volume heat source (target orange area): 1.0 [mW/mm3] ■ Surface heat dissipation condition: heat transfer coefficient 0.01 [mW/(mm2*K)] ■ Ambient temperature (target blue area): 20 [℃] *For more details, please download the PDF or feel free to contact us.

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[Example] Frequency Response Analysis of Electrical Box 'AIFEM'

Quickly check the response peaks and stress distribution of electronic devices with the frequency response analysis feature!

We would like to introduce a case study of frequency response analysis of an electrical block using the general-purpose finite element analysis software "AIFEM." The electrical box serves as a carrier for the electronic circuit board and is also a transmission path for the excitation load. Vibrations can significantly impact the functionality and performance of the components on the electronic circuit board. With the frequency response analysis feature of this product, we were able to quickly check the response peaks and stress distribution of the electronic device, allowing us to identify areas for design improvement. 【Analysis Conditions】 ■ Frequency Range: 100 to 1000 Hz ■ Excitation Intensity: Acceleration 20 G ■ Excitation Direction: Z Direction ■ Critical Damping Ratio of Material: 0.02 *For more details, please download the PDF or feel free to contact us.

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[Case Study] AI-Accelerated Analysis of Guide Vane Pumps 'AICFD'

A case study utilizing the unique feature of AI acceleration! Reducing iterations and achieving efficient analysis.

We would like to introduce the AI-accelerated analysis of a guide vane pump using the general-purpose thermal fluid analysis software "AICFD." In multi-domain and rotating machinery analysis cases, we utilize the unique AI acceleration feature of this product. By reducing the number of iterations required for calculations through AI acceleration, we achieve efficient analysis. In this case study, we were able to achieve a 27% reduction in computation time without compromising accuracy. 【Analysis Conditions】 ■ Mesh Model: Unstructured Grid 2.1 million ■ Inlet Velocity: 4.49 m/s ■ Turbulence Model: SST k-ω ■ Iterations: 5000 *For more details, please download the PDF or feel free to contact us.

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[Case Study] High-Speed Design of Glass Molds Using Data Mining

Learn mapping relationships and build data models! Quickly obtain molds that meet the requirements.

We would like to introduce the high-speed design of glass molds using the data analysis and modeling software "DTEmpower." The current mold design process involves continuously adjusting the design mold B to create a mold that meets the requirements. After obtaining the necessary glass model, there is a desire to establish a flow that allows for the direct and rapid design of the appropriate mold. Ultimately, we obtained deviation data between the glass model A that meets the design requirements and mold B, and learned the mapping relationship. We provided design methods such as constructing a data model. [Background and Issues] - The current mold design process creates a mold that meets the requirements by continuously adjusting the design mold B. - There is a desire to establish a flow that allows for the direct and rapid design of the appropriate mold after obtaining the necessary glass model. *For more details, please download the PDF or feel free to contact us.

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[Example] Transformer winding temperature warning 'DTEmpower'

Early warning methods based on machine learning can respond more sensitively to abnormal conditions!

We would like to introduce a case study of applying the data modeling and analysis software "DTEmpower" to transformer winding temperature warnings. The machine learning method allows for a more sensitive detection of abnormal data points in winding temperature simply by setting the difference between the temperature measured by sensors and the temperature estimated by the model. Additionally, early warnings based on machine learning only require setting the degree of deviation from normal values, which essentially establishes a dynamic early warning zone. This approach offers greater flexibility and improved reliability compared to traditional static warning bands. 【Problems and Challenges】 - Ensuring the stability and reliability of transformers is a critical issue, and responses to failures need to be swift and effective. - The main cause of transformer failures is the decrease in insulation capacity. - To mitigate the risk of transformer failure due to decreased insulation capacity, early warnings for winding temperature are necessary. *For more details, please download the PDF or feel free to contact us.

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[Case Study] Condition Monitoring and Fault Diagnosis of Wind Turbine Gearboxes

Providing training on gearbox failure characteristics through big data analysis!

We will introduce the technical analysis work related to bearing parameter alarms and gearbox fault diagnosis based on the data modeling software "DTEmpower." This product can provide deep data analysis necessary for industrial data processing as a concise and rigorous one-stop solution. Additionally, it enables data analysis, modeling, and design based on machine learning, significantly improving product development efficiency. 【Condition Monitoring & Parameter Alarms】 ■ Extraction of Sensory Feature Characteristics ■ Quantitative Optimization of Sensitive Feature Alarms *For more details, please download the PDF or feel free to contact us.

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[Case Study] Combustion Analysis of Corn Burners 'AICFD'

Efficiently solving complex flow and heat transfer problems! Case study of combustion analysis of a conical burner.

We would like to introduce a combustion analysis case of a conical burner using the general-purpose thermal fluid analysis software "AICFD." The analysis conditions include a turbulence model of the standard k-ε model, a fluid mixture, and a combustion model such as Species Transport. This product comprehensively covers the process from creating the analysis model, simulation, to result processing, supporting the improvement of research and development efficiency. 【Analysis Conditions (Partial)】 ■ Inlet Conditions: - 60 [m/s] - CH4 (mass percent: 3.4%) - O2 (mass percent: 22.5%) - N2 (mass percent: 74.1%) *For more details, please download the PDF or feel free to contact us.

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[Case Study] Strength Analysis of Turbine Upper Cover 'AIFEM'

Analysis of components that requires the use of advanced analytical methods is essential! We will also present the results of maximum strain under three conditions.

We would like to introduce a case study of strength analysis of a turbine upper cover using the finite element method (FEM) analysis software "AIFEM." In the design of this cover, improvements in durability, safety, and efficiency are required, making the use of advanced analysis methods essential. In this case study, pressure loads were applied to the bottom surface of the turbine upper cover, and symmetrical boundary conditions were applied using a 1/4 model to analyze the deformation of the upper cover. [Analysis Results] ■ Rated operating condition: 4.515×10^-4 ■ Maximum head condition: 5.552×10^-4 ■ Boost condition: 8.609×10^-4 *For more details, please download the PDF or feel free to contact us.

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simulator
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[DTEmpower] Evaluation of Wind Turbine Hub Strength

Introducing two cases of modeling and data analysis using the data modeling platform DT Empower!

Wind turbines are mainly composed of parts such as blades, pitch control systems, gearboxes, generators, yaw control systems, and hubs. The hub connects the base of the blades to the main shaft of the wind turbine, and the blades experience complex alternating loads such as thrust, torque, and bending moments. Speed is transmitted from the hub to the main drive system through pitch bearings. Therefore, it is necessary to strictly manage the strength and lifespan requirements of the hub throughout the wind turbine. *For more details, you can view the related links. For further information, please download the PDF or feel free to contact us.*

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Turbine
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Parametric model of end wall contouring

We will also introduce modeling approaches, the construction of more complex models, and application examples!

In the end wall section of power generation devices that convert the kinetic energy of fluids, such as turbines and compressors, into rotational motion, a secondary flow known as "cross flow" occurs due to the interaction between adjacent blades. To improve the performance of the device, it is crucial to reduce this cross flow and the resulting flow losses. The end wall contouring introduced here is a shape profile that adds irregularities to the end wall to suppress losses caused by cross flow, and it is modeled parametrically using CAESES. With the addition of these shape features and modeling techniques, it has become possible to modify the hub shape, thereby minimizing undesirable secondary flow losses. *For more detailed information, you can view the related links. For further details, please download the PDF or feel free to contact us.*

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CFD optimization through integration with AnsysCFD.

An appropriate CAD tool is needed to ensure the generation of various model variations to be analyzed in the automation process!

Ansys CFD tools such as Fluent and CFX receive strong support from engineers for evaluating fluid dynamic behavior in design, along with various options and tools used for mesh creation. These tools provide valuable information and insights regarding the performance to be evaluated. Moreover, they enable automated optimization and design exploration workflows that include CFD. In addition to improving design and shortening development time and design cycles, these tools significantly enhance the development process by increasing information about the impact of various design variables on performance (product behavior) during the initial design phase, where there is a high degree of freedom in decision-making. *For more details, you can view the related links. For more information, please download the PDF or feel free to contact us.*

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Structural Analysis
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Optimization of axial fans using TCFD and CAESES.

The goal of the optimization calculation is to maximize fan efficiency at specific flow rates and increase airflow!

In this case, we will introduce the automatic optimization workflow for axial fan rotor blades developed by CFDSupport, the creator of TCAE, and FRIENDSHIP SYSTEMS, the creator of CAESES. The project began in response to requests from designers and manufacturers who have basic designs for axial fans and wish to improve existing products into more optimal shapes. *For detailed content of the article, you can view it through the related links. For more information, please download the PDF or feel free to contact us.*

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Structural Analysis
fan
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Optimization of the shape of the volute and diffuser of a centrifugal compressor.

For shape creation, we use CAESES, and for mesh model creation and CFD analysis, we use products from NUMECA!

At the Technical University of Darmstadt in Germany (Institute of Gas Turbines and Aerospace Propulsion), research was conducted on the automatic optimization of the volute of centrifugal compressors and vane diffusers. This project was carried out in collaboration with NUMECA, a German company, and Kompressorenbau Bannewitz GmbH (KBB), a turbo machinery manufacturer. CAESES was used for shape creation, while NUMECA's products were utilized for mesh model creation and CFD analysis. In CAESES, a parametric model was created that allowed for variations in the cross-sectional shape and area distribution of the volute. For the diffuser, a non-axisymmetric design was implemented, enabling quick shape transformations by varying the misalignment angle, blade twist, chord length, pitch, and rotation through a parametric model. *For more detailed information, please refer to the related links. You can download the PDF for more details or feel free to contact us.*

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Thermal Fluid Simulation Software 'AICFD'

【Annual rental of 1.5 million yen including maintenance】Contributes to the efficiency of analysis work with high-speed processing by AI and easy GUI operation. *Presenting the "Thermal Fluid Analysis Case Collection"!

"AICFD" is software that achieves high-precision simulations while reducing the workload associated with thermal fluid analysis through an intuitively operable GUI and AI-assisted features. It addresses the challenges faced by users of conventional software, such as "complex mesh creation, difficult analysis settings, and slow computation speeds," allowing engineers to focus on their core tasks and streamlining the iterative process of product design. Additionally, it is equipped with predictive analysis for flow fields and dedicated modules for turbo machinery and electronic device cooling, strongly supporting applications across various fields such as automotive, electronics, industrial machinery, and marine. 【Features】 ■ High cost performance at an annual rental of 1.5 million yen (excluding tax) ■ Integrated GUI covering the entire analysis process ■ Incorporation of AI predictive models utilizing existing results ■ Mesh creation by AI, enabling analysis that does not rely on experience ■ Intelligent features that provide setting support in a Q&A format * We are currently offering a "Thermal Fluid Analysis Case Study Collection"! For more details, please refer to the materials or feel free to contact us.

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Sensitivity approach for turbo pump inducer geometry

Equipped with a function to raise the impeller inlet head by a sufficient amount to prevent excessive cavitation generation!

The turbo pump is an important component in the design of launch rockets for space using liquid fuel. It is a component that supplies the necessary fuel flow to achieve a large thrust while maintaining a high combustion chamber pressure, and it is used in rocket engine supply systems. Due to the need for high-precision performance predictions of turbo pumps for launch rockets, as well as designs based on these predictions, resulting from the significant reduction in total rocket engine weight, the very high rotational speed of the turbo pump, and the specifications of the pump in relation to the degree of depressurization in the liquid fuel storage tank, the goal is to maximize total reliability throughout the operational lifecycle. *For more detailed information, please refer to the related links. For further details, you can download the PDF or feel free to contact us.*

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Propeller design of Caterpillar Propulsion

Execute tasks such as setting up the blade model and generating individual dynamic 2D drawings!

Caterpillar Propulsion has implemented CAESES for the design of propeller blades. When we started on a project basis, the overall idea was to implement it as a workbench that integrates and controls mesh generation and simulation software. At the same time, CAESES needs to provide a fully parametric 3D blade design that allows Caterpillar Propulsion's engineers to reconstruct the definitions of existing blades and profiles, while also requiring high flexibility to try out entirely new designs. *For more details, please refer to the related link. For further information, you can download the PDF or feel free to contact us.*

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Mechanical Design
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Optimization of motor electromagnetic and noise performance

Under conditions with little change in average torque, torque ripple is reduced by 10%!

This article introduces the optimization of the electromagnetic and noise performance of motors using the general-purpose optimization software AIPOD. The main source of vibration and noise in motors is the electromagnetic force that changes over time and space with the stator. To reduce the motor's vibration noise, it is key to weaken the amplitude of the corresponding order of the electromagnetic force. Through the software interface standardly equipped with AIPOD, external software's input and output variables can be seamlessly connected, allowing for rapid optimization of motor noise design. *For more detailed information, please refer to the related links. For further details, you can download the PDF or feel free to contact us.*

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Eigenvalue optimization of automotive oil pans

Improved the first natural frequency from 701.5Hz to 1224.6Hz without breaking the outline boundary of the base model!

The base model of the oil pan, which is the subject of optimization, was considered to have a primary natural frequency lower than the initially assumed requirements, resulting in poor NVH performance. In this case, we aim to improve the primary natural frequency of the oil pan through structural optimization. Assuming that the contour boundary of the base model remains unchanged, a partial parametric model will be created using external CAD software and incorporated into the node-based optimization process constructed in AIPOD. *For more detailed information, please refer to the related links. For further details, you can download the PDF or feel free to contact us.*

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Optimization of catalytic converter performance using CAESES.

Optimization of the duct of the catalytic converter using CAESES!

Designing engine components for automobiles often involves considering many constraints, making it a challenging task within development design work. One example is the duct located just before the catalytic converter. Due to space constraints, this component is often designed to be bent quite sharply, which makes it difficult to ensure that the flow distribution is sufficiently uniform. In other words, if the flow characteristics of the catalytic converter are poor, there is a possibility that performance will decrease and emissions will increase. In this case, optimization of the duct for the catalytic converter will be performed using CAESES. *For more details, please refer to the related links. For further information, feel free to download the PDF or contact us.*

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Automatic Optimization using Adjoint Flow Solvers

It is possible to efficiently obtain optimal candidate geometry that can be directly supplied to the downstream CAD design process!

At FRIENDSHIP SYSTEMS, the developer of the CAD and optimization software CAESES, automatic optimization calculations were performed based on the shape sensitivity calculated by Adjoint Flow Solvers. The open-source optimization toolkit Dakota, integrated into CAESES, provides optimization methods that can directly accept gradient information obtained by combining shape sensitivity with CAD model parameters as input data. Based on this information, the algorithm selects parameters for design candidates created by CAESES, and calculations are performed using Adjoint Flow Solvers. *For more detailed information, please refer to the related links. For further details, you can download the PDF or feel free to contact us.*

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Morphing of the injector nozzle

Implement shape deformation on the injector nozzle using the morphing function!

One of the components targeted for optimization in diesel engines is the injector. This component is designed with careful consideration of its orientation and dimensions to ensure that fuel is injected appropriately into the combustion chamber, making it highly refined. In this case, we will introduce a method for rapidly deforming the existing nozzle shape of the fuel injection system. Based on the shape data imported into CAESES in STL format, we will use the morphing function to implement shape deformation on the injector nozzle. *For more detailed information, you can view the related links. For further details, please download the PDF or feel free to contact us.*

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Tire tread pattern optimization

A system for automatic optimization has been built using CAESES and commercial CFD analysis tools, resulting in significant improvements to the tire tread pattern!

The development of advanced automotive systems such as electric vehicles, autonomous driving systems, and safety enhancement systems will significantly increase the number of electronic devices added to the vehicle body, including sensors, radars, and cameras. It is crucial for these devices to function reliably while minimizing exposure to water to prevent damage and corrosion. One effective approach to achieve this is to reduce water splashes on the vehicle's body and underbody. This case study introduces simulation-driven optimization to investigate the impact of tire tread patterns on water splashes. *For more detailed information, please refer to the related links. You can download the PDF for more details or feel free to contact us.*

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Torque converter shape optimization

CAESES provides beneficial results across various fields, regardless of the products in question!

A torque converter for automobiles is a type of fluid coupling used in vehicles equipped with automatic transmissions to transmit rotational force from the engine to the drive shaft. Designers of torque converters work to minimize cavitation within the device and ensure good flow behavior of the transmission oil, aiming to maximize efficiency and torque ratio at high speeds. CAESES enables the modeling of such complex shapes and can build an optimization system that incorporates shape data into analysis software. By connecting CFD analysis software and proprietary CFD codes to CAESES, it analyzes flow behavior for each designed shape during optimization calculations and provides users with the optimal shape based on constraints. *For more detailed information, please refer to the related links. For further details, feel free to download the PDF or contact us.*

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Parametric modeling and optimization of electric vehicle battery fins.

Parametrize the fin shape and arrangement of the heat sink to build a model that can flexibly evaluate various design patterns!

With the improvement in electric vehicle performance, the high output of batteries has progressed, and the increase in power consumption has also led to an increase in heat generation. Therefore, to ensure stable operation of the battery and maximize its performance, the design of an efficient cooling structure is essential. In particular, temperature management of the battery pack is directly related to the lifespan and safety of the cells, necessitating the design of an optimal heat dissipation mechanism. In this case study, we focused on a finned heat sink structure and conducted optimization aimed at improving thermal exchange efficiency. *For more details, please refer to the related links. For further information, you can download the PDF or feel free to contact us.*

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Optimization of thermal design for electric vehicle battery packs

The parametric model created with CAESES can robustly output various complex shapes for use in optimization calculations!

The battery is one of the most important components in electric vehicles (EVs), and its performance and lifespan have a significant impact on the vehicle's driving range, safety, and even energy efficiency. In particular, the operating temperature of the battery is directly related to the charging and discharging efficiency and degradation rate, making proper temperature management essential. If the temperature is not adequately controlled, issues such as accelerated degradation due to overheating, reduced safety, or, conversely, decreased output and charging efficiency in low-temperature environments may arise. Therefore, the thermal design of the battery pack is a crucial factor in maximizing the performance of EVs and ensuring long-term durability. In this case study, we constructed a parametric battery model with flexible deformation and conducted optimization calculations aimed at minimizing the maximum temperature. *For more details, please refer to the related links. For further information, feel free to download the PDF or contact us.*

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Propeller optimization using machine learning

The main objective of the contest was to design a propeller that could achieve maximum efficiency at a wide range of operating speeds.

In propeller design, achieving optimal efficiency and performance is extremely important. Recently, by effectively combining AI and CFD, we were able to win an online propeller design contest hosted by a popular YouTube creator. In this contest, we were able to create two high-performance propellers that demonstrated excellent efficiency using "CAESES" and "AirShaper." *For more details, you can view the related links. For more information, please download the PDF or feel free to contact us.*

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Optimization of Container Ship Shape

Partial parametric modeling adopted! Deformation of the hull shape is defined.

One of the representative companies in China's shipping industry, MARIC (Marine Design & Research Institute of China), first utilized CAESES for a project focused on the optimization of hull shapes for container ships. In their research, MARIC engineers selected a baseline with excellent performance and attempted to reduce hull resistance at speeds of 18 knots and 27 knots. The constraints here were the length between perpendiculars, width, and draft, which were fixed values, while the variation in displacement was limited to ±0.5%. *For more detailed information, please refer to the related links. You can download the PDF for more details or feel free to contact us.*

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Parametric model of twin-skeg boats in CAESES

It is possible to flexibly control various parts related to hull characteristics!

We will introduce the parametric model of a twin-skeg vessel created by FRIENDSHIP SYSTEMS, the developer of the CAD + optimization software CAESES. In cases where the shape is symmetrical, only half of the hull is typically modeled. With CAESES, it is possible to robustly construct a model that incorporates the deformations anticipated by the user. *For more detailed information, please refer to the related links. For further details, you can download the PDF or feel free to contact us.

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Challenge to EEXI & CII Regulations through Fluid Dynamics Optimization

It is very important to approach optimization from the perspective of fluid dynamics! Introduction to EEXI and CII.

In pursuit of achieving carbon neutrality, the implementation of the existing ship energy efficiency index (EEXI) and the annual fuel consumption rating system (CII) will begin on January 1, 2023. This regulation will introduce new challenges in the operation of commercial vessels, requiring shipowners to evaluate and improve their vessels in accordance with regulatory requirements. To continue international navigation and trade activities as before, there are conditions such as obtaining certificates, making it very important to engage in optimization from a fluid dynamics perspective. *For more detailed information, you can view the related links. For further details, please download the PDF or feel free to contact us.*

Company：FsTech
Price：Other

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