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"AICFD" is a thermal fluid analysis software designed to efficiently analyze complex flow and heat transfer problems in the fields of energy, shipping, electronics, and automobiles. It covers the entire simulation process and contributes to the establishment of optimal design processes and the improvement of development efficiency. It provides graphical setup operations that significantly reduce the user's burden. 【Features】 ■ Simple and intuitive operability ■ Improved computational efficiency through AI algorithms ■ Intelligent predictive analysis ■ Dedicated modules for specific areas *For more details, please refer to the PDF materials or feel free to contact us.

We would like to introduce application examples of flow field analysis using our intelligent thermal fluid analysis software "AICFD." This software enables efficient simulation of fluid flow and heat transfer, developed by our company. It can be applied to pressure loss analysis of valves, which require higher stability, convergence, and accuracy due to the presence of many small pressure relief holes in the valves. You can check the details of the case studies through the related links. 【Case Overview (Partial)】 ■ Pressure Loss Analysis of Valves - Pressure loss analysis of valves is one of the typical cases in CFD. - Higher stability, convergence, and accuracy are required due to the presence of many small pressure relief holes in the valves. - The boundary conditions used are an inlet velocity condition of 10.69 (m/s) and an outlet static pressure condition. *For more details, please download the PDF or feel free to contact us.

We would like to introduce an application case of our intelligent thermal fluid analysis software "AICFD" for turbomachinery. This software covers the entire analysis process from the ometric model to result evaluation. It can be applied to analyze the internal flow field of axial fans, allowing us to obtain a wealth of data necessary to improve fan performance. You can check the details of the case from the related link. 【Case Overview (Partial)】 ■ Efficiency analysis of an axial fan (one pitch) - Analyzing the internal flow field of the axial fan provides a wealth of data necessary to improve fan performance. - The model consists of two components: the outlet guide vane flow path and the rotor flow path, analyzing the flow field and fan efficiency with an inlet velocity of 15.06 (m/s). *For more details, please download the PDF or feel free to contact us.

"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.

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.

We would like to introduce the application examples of AI predictive analysis and AI high-speed analysis of our intelligent thermal fluid analysis software "AICFD." This software supports the establishment of a design process that combines design, analysis, and optimization in industrial fields, significantly improving the efficiency of product development. It performs aerodynamic analysis of automobiles using the AI-accelerated analysis function, comparing three cases including the standard analysis results. You can check the detailed content of the case studies through the related links. 【Case Overview (Partial)】 ■ AI Predictive Analysis of Battery Pack Flow Field Temperature - Based on 10 sets of analysis samples in the opposing wind speed range of 10 to 30 (m/s), it predicts the internal flow field and temperature distribution of the battery pack at an opposing wind speed of 20 (m/s) with one click. - The results of the predictive analysis are compared with the results of the standard method. *For more details, please download the PDF or feel free to contact us.

We would like to present a case study where the general-purpose thermal fluid analysis software "AICFD" was used to analyze the head and shaft power of a centrifugal pump, comparing the results with experimental values. The mesh model adopted an unstructured mesh with a total cell count of 1.2 million. When comparing the experimental values with the analysis results, a deviation of 1.70% was confirmed for both output (kW) and head (m). 【Analysis Conditions】 ■ Inlet Condition: 69.46 [L/s] ■ Outlet Condition: Static Pressure 0 [Pa] ■ Rotational Speed: 980 [RPM] ■ Turbulence Model: Standard k-epsilon *For more details, please download the PDF or feel free to contact us.

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.

We will introduce a case study on cooling analysis of motors for electric vehicles using the general-purpose intelligent thermal fluid analysis software AICFD. As the adoption of electric vehicles accelerates, there is a demand for the development of more efficient and high-performance drive motors. Improving motor performance involves factors such as optimizing energy conversion efficiency and reducing weight, among which thermal management is a key element. The heat generated inside the motor can not only lead to a decrease in output and efficiency but also significantly impact durability and long-term reliability. Therefore, it is essential to implement appropriate cooling design and achieve efficient thermal control. In this analysis, we examined the temperature distribution around the coils, which are the main heat sources within the electric vehicle motor, and evaluated the cooling performance. By visualizing the temperature distribution obtained through simulation, we can confirm the effectiveness of the cooling design. *For more details, please download the PDF or feel free to contact us.*

This introduction discusses the flow field analysis of axial fans using the general-purpose intelligent thermal fluid analysis software AICFD. Flow field analysis is an important means of visualizing and predicting the complex movement of fluids inside the fan. Through flow field analysis, detailed information such as turbulence, pressure loss, and temperature distribution can be obtained, allowing for early detection of issues during the design phase and the implementation of improvements. After the simulation is completed, post-processing can be performed on the same GUI, enabling efficient result verification. In addition to basic visualizations such as distribution maps, vector diagrams, and streamlines, the built-in post-processing function "TurboPost" for turbo machinery allows for even more advanced visualization of analysis results. *For more details, please download the PDF or feel free to contact us.*

This analysis focuses on a battery pack for electric vehicles that uses a water-cooled cooling plate, and it analyzes the temperature distribution of the battery pack. The mesh model employs an unstructured mesh, with a total of 2.17 million cells. *For detailed content of the article, please refer to the related link. For more information, you can download the PDF or feel free to contact us.*

This analysis conducts a cooling analysis of the motors used in electric vehicles and verifies the temperature around the coils, which are the heat sources within the motor. The following conditions are set for the analysis. *For detailed information, please refer to the related link. For more details, you can download the PDF or feel free to contact us.*

The comfort inside the vehicle is influenced by many factors based on environmental conditions such as the temperature of the airflow and the flow of air from the air conditioning. To create a more comfortable space for the people present, starting with the vehicle's air conditioning, it is necessary to evaluate the repeated design of the air conditioning vents and the thermal comfort and energy efficiency of the interior under various conditions at the conceptual design stage. This requires understanding the indoor conditions through simulations and pre-validation through numerous parameter studies, making the prediction of flow fields under specific conditions using AI technology effective. In this analysis, we evaluated the flow field and maximum velocity under specific conditions using the AI prediction function incorporated in AICFD. We also compared the results with those from conventional analyses to verify the effectiveness of the AI prediction function. *For more detailed information, please refer to the related links. For further details, you can download the PDF or feel free to contact us.*

The intake port is a crucial component of the intake system in automotive engines and has a significant impact on the mixing of air and fuel. In the early stages of design, the intake volume and pressure loss are evaluated in advance using CFD analysis to optimize the design. In this case study, the pressure loss of the intake port will be analyzed based on the conditions of inlet total pressure and outlet static pressure, and accuracy verification will be conducted by comparing the results with reference values. *For more detailed information, please refer to the related links. For further inquiries, feel free to download the PDF or contact us.

This analysis examines the drag and pressure distribution that occurs on the body of a large truck under specific conditions. Under the condition where air flows at a speed of 20 [m/s] from the inlet boundary, we will evaluate the impact on the truck's body. By using simulations to confirm the drag coefficient and the state of the flow field, we can obtain information that leads to improved fuel efficiency by understanding the airflow and resistance around the truck. *For more detailed information, please refer to the related links. For further details, you can download the PDF or feel free to contact us.*

The pressure loss in the intake manifold and the uniformity of the flow rates in each pipe are important factors for the engine's output and performance. In this analysis, we will examine the flow inside the manifold of a 4-cylinder automotive engine, as well as the pressure loss and flow velocity distribution in the branch pipes. *For detailed content of the article, please refer to the related links. For more information, you can download the PDF or feel free to contact us.*

In the modern industrial sector, motors are utilized as essential power sources across various industries. To maintain the normal operation of motors, it is crucial to prevent overheating, and in the case of air-cooled motors, appropriate heat dissipation design is directly linked to reliability and performance. The thermal fluid analysis software AICFD addresses such challenges and provides a tool for achieving proper thermal design with easy operability and efficient data acquisition. In this article, we conducted a heat dissipation simulation for air-cooled motors using AICFD and validated the analysis results. *For detailed content of the article, please refer to the related links. For more information, feel free to download the PDF or contact us.*

Battery packs are currently widely used in electric vehicles, smartphones, and energy storage technologies, and in such systems, improving the performance of battery packs often becomes the key to product enhancement. In this analysis, we will evaluate the heat dissipation and air cooling effects of a battery module for electric vehicles using a porous medium model instead of a heat sink, and assess the temperature results. As analysis conditions, we set the inlet flow velocity to 5 [m/s] and the outlet static pressure to 0 [Pa], applying the porous medium model to the fins of the heat sink. *For more detailed information, you can view the related links. For further details, please download the PDF or feel free to contact us.*

Simulating the flow around a vehicle and analyzing its aerodynamic characteristics is an important task for evaluating the impact of a car's shape and design on airflow. This provides various qualitative and quantitative information directly related to fuel efficiency, driving stability, and driver safety. In this analysis, which uses models of various scales from simple shapes to detailed models, information is derived through analysis to investigate the wide-ranging effects from design to manufacturing and driving performance, while considering computational time and machine leasing costs. In this analysis, we simulated the flow around the vehicle body using the AI acceleration feature integrated into AICFD. Additionally, we verified the effectiveness of the AI acceleration feature by comparing computational time and accuracy between the standard analysis and serial core using the same model. *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.*

With the development of the automotive industry and the increasing speed of vehicles, there is growing attention on the aerodynamics of automobiles. Excellent aerodynamic design not only achieves high efficiency and energy savings but also reduces noise and provides better ride comfort, driving performance, stability, and stronger security guarantees. In recent years, it has become an essential element not only in the aerospace field but also in various modern industrial designs. In this case study, we analyzed the aerodynamics of automobiles using a passenger car model and evaluated the underlying pressure distribution and flow vectors. *For more detailed information, please refer to the related links. For further details, you can download the PDF or feel free to contact us.*

In this case, we will simulate the resistance values of a submarine under specific conditions using the AI forecasting function (Intelligent Forecasting) equipped in AICFD. The AI forecasting function is one of the distinctive modules of AICFD, and it solves the problem of the enormous number of analysis iterations in industrial design simulations through real-time result predictions by AI. *For more detailed information, you can view it through the related links. For more details, please download the PDF or feel free to contact us.*

Using the general-purpose thermal fluid analysis software AICFD, we will conduct a performance analysis of the Rotor37 compressor. Rotor37 is a classic case of CFD compressible fluid calculations and is often used to verify the software's performance in the flow problem around the blades of a transonic axial compressor. We will analyze the three-dimensional flow characteristics of the compressor rotor, focusing on rotating machinery with practical engineering backgrounds derived from research results by NASA. *For more detailed information, please refer to the related links. For further inquiries, feel free to download the PDF or contact us directly.*

Using the general-purpose thermal fluid analysis software AICFD, we will conduct a transonic analysis of the M6 wing. The M6 wing is a classical test case for studying transonic flow and is a semi-infinite airfoil designed by the French aerospace research institute ONERA. The M6 wing exhibits typical transonic airfoil characteristics, such as shock waves that appear on the wing under specific conditions and expansion waves behind the shock waves. *For more detailed information, please refer to the related links. For further details, you can download the PDF or feel free to contact us.*

Using the general-purpose thermal fluid analysis software AICFD, we will analyze the pressure loss and cooling performance of the energy storage converter. We will conduct an analysis that includes a cooling fan, and check the internal flow field and the temperature conditions of the mounted IGBTs. The mesh model to be analyzed consists of 2 inlets and 3 outlets, with boundary conditions assigned. *For more detailed information, please refer to the related links. For further details, you can download the PDF or feel free to contact us.*