Browse Topic: CAD, CAM, and CAE

Items (1,298)

4/1/2026

Software Diagram https://wcm14-tst.cld.sae.org/site/binaries/content/gallery/mobilus-brx/digital-supplements/software-diagram.png/software-diagram.png/sae%3Amedium

Experimental and Numerical Investigation of Modal Behaviour in Electric Two-Wheeler Frames

2026-26-03101/16/2026

This research investigates the dynamic characteristics of an electric two-wheeler chassis through a combined experimental and numerical approach. The study commences with the development of a detailed CAD model, which serves as the basis for Finite Element Analysis (FEA) to predict the chassis's natural frequencies and mode shapes. These numerical simulations offer initial insights into the structural vibration behaviour crucial for ensuring vehicle stability and rider comfort. To validate the FEA predictions, experimental modal analysis is performed on a physical prototype of the electric two-wheeler chassis using impact hammer excitation. Multiple response measurements are acquired via accelerometers, and the resulting data is processed to extract experimental modal parameters. The correlation between the simulated and experimental mode shapes is quantitatively assessed using the Modal Assurance Criterion (MAC). This matrix provides a measure of the consistency and similarity between

Das Sharma, Aritrya, Iyer, Siddharth, Prasad, Sathish, Anandh, Sudheep

A procedure for validation of full vehicle CAE models with physical tests for passive safety applications

2026-26-04111/16/2026

With the fast development of computational analysis tools and capacities during the past ten years, complex and substantial computer-aided engineering (CAE) simulations are now economically possible. While the cost of crash tests has risen steadily, the fidelity and complexity, which numerical simulations could address, has multiplied keeping the cost of computational analysis more stable. The use of CAE simulations complements physical testing, accelerating the product development process, reducing cost, and ensuring safe and more optimized designs. The fundamental goal of CAE is a significant reduction in the number of physical tests conducted during the product development process. However, validating the CAE model with physical tests is essential to ensure accuracy and reliability. Simulations performed using a validated CAE model could be used to make decisions like airbag deployment or high voltage shutdown without an actual physical test. This paper discusses validating an

UPENDRAN, ANOOP

Road noise improvement of a passenger vehicle through end-to-end CAE-Simulation using Transfer Path Analysis (TPA) approach

2026-26-04311/16/2026

Refined NVH performance of a vehicle is a mark of premium quality. Achieving the desired NVH performance in different vehicle operating conditions is always a Herculean task and early stage “CAE design recommendations” play crucial role in overall vehicle design development. This becomes tougher when the program is very much cost, weight and timeline sensitive. This paper explores simulation approach for addressing a major noise issue for a vehicle running at a constant speed on a rough road. The first and the most critical step is to identify the exact root cause of the issue. Hence, we propose a detailed full vehicle level “contribution analysis (CA) + transfer path analysis (TPA)” methodology (everything done through the simulation) and then go for the design recommendations to improve the performance. We used road excitation power spectral density (PSD) as the input at all the four wheels (spindle locations) calculated through MBD software. The first step i.e. contribution analysis

Mahajani, Mihir, Nascimento, Fabio, ADINARAYANA REDDY, KODIDELA, Matyal, Mahantesh, Tenagi, Irappa, Sardar, Chenna

Evaluation of Thermo-Mechanical behavior of brake discs in vehicles using Multidisciplinary approach

2026-26-04331/16/2026

The objective of this paper is to evaluate the thermal performance of the brake discs in the design stage of its life cycle by developing a methodology to replicate the dynamometer testing using multi-disciplinary Finite Element Analysis (FEA) methods. A simulation workflow was formulated in which Computational Fluid Dynamics (CFD) was used to create temperature and velocity dependent Heat Transfer Coefficients (HTC) which were in turn used in Computer Aided Engineering (CAE) to do a thermo-mechanical analysis. With this workflow various designs of the brake discs were analyzed. A sensitivity study was done to determine critical design features that affected its thermal performance. A final design was fixed that met both the weight and thermal performance targets. This design was evaluated in dynamometer testing, and 95% correlation was achieved. Thus, the developed simulation workflow ensured that a first-time right brake disc can be finalized in the design stage, which will meet the

Balaji, Praveen, K, Karthikeyan, S, KESAVPRASAD, S Kangde, Suhas

Investigating the Effect of Aperture Flange Curvature on Tailgate Seal Bulb Height: A CAE-Based Approach

2026-26-04161/16/2026

Water leakage is a common issue in vehicles, especially during water testing. It often occurs due to a gap between the seal bulb and the closure panel. This gap can result from variations in flange angle, flange curvature, closure surface, or seal bulb height. This study focused on how flange curvature affects seal bulb height and sealing performance. A Computer-Aided Engineering (CAE) method was used, supported by tests on physical samples. Multiple simulations were done using different flange curvatures. Results showed that with a constant flange angle of 150°, increasing the flange radius reduced seal bulb deformation. The optimal radius was 250 mm, where the bulb compression was 1.1 mm. Sharp or tight flanges caused the bulb to deform more, reducing contact and sealing force. To reduce this deformation, a hollow tube was inserted inside the seal bulb. The hollow tube used had an internal diameter of 10 mm and an external diameter of 12 mm. With the hollow tube, the optimum flange

Kumar, Saurav, Neelam, Rajat, Chowdhury, Ashok, Panchal, Girish, Lathwal, Sandeep

Automated Parameterization of CAE Model Based on Test Data Response Bands

2026-26-04361/16/2026

This study presents a data-driven approach aimed at enhancing the correlation between physical test data and Computer-Aided Engineering (CAE) simulations, with an emphasis on adapting the standard CAE model's response to minimize any gaps relative to the response of a given test specimen. Leveraging historical test data, machine learning techniques are used to categorize responses into distinct bands, effectively capturing the inherent variability observed in real-world scenarios. This categorization step recognizes patterns across a wide range of test data, forming the foundation for closely matching and adapting CAE models to new, unseen hardware data. In typical automotive simulation workflows, tuning a standard CAE model to match new hardware test data involves iterative parameter adjustments and simulations. This process can be time-consuming and often lacks predictive insight into the necessary modifications. The approach developed in this study addresses this challenge by

Khopekar, Maria, Arya, Bibhu, Sridhar, Raam, Mohan, Pradeep, Kurkuri, Mahendra

Multi-Model Analysis of O-Ring Compression and Relaxation Force Predictions Using Machine Learning and CAE Simulations

2026-26-04661/16/2026

O-rings play a critical role in ensuring leak-proof seals in a wide range of engineering systems. Accurate prediction of their compression and relaxation behavior under various material and geometric configurations is essential for optimal design and reliability. This study presents an analysis of machine learning techniques to predict two key performance outputs, compression force and relaxation force (after 10 minutes) trained on computer-aided engineering (CAE) simulation data. The experimental setup was represented in CAE simulation and the results were compared with experimental data conducted at ZF test facilities. Simulation results correlated well with the experimental data (deviation was less than the 5%). To create a dataset for training machine learning (ML) models, realistic ranges for the input parameters such as hardness and geometrical parameters were determined, and simulation data were generated using design of experiments (DOE). Multiple ML models were developed and

Kosgi, Durgaprasad, Alva, P Pancham, Dangeti, VenkataKrishna Pavan

Material-Optimization in Rib-Stiffened Polymer structures: A Computational & Analytical Study

2026-26-04981/16/2026

Background The demand for lightweight yet rigid polymer components continue to drive innovation in structural design, particularly for applications requiring optimal stiffness-to-weight ratios. This study examines an alternative rib-stiffening approach for polypropylene plates, where conventional single-rib geometries are reconsidered in favor of parallel micro-rib configurations. While single ribs have been extensively studied, the potential benefits of distributed rib architecture remain less explored, particularly regarding their combined bending and shear performance. Key objective: This study systematically evaluates how parallel rib configurations influence mechanical performance in polypropylene plates, with specific focus on:  Bending stiffness preservation through optimized moment of inertia distribution  Shear resistance enhancement via controlled rib spacing  Coupled effect of the bending and shear resistance Prior art and their limitations: Current literature primarily

Sreejith, M P, Jain, Deepak, Maheshwari, Pankaj, Kumar, Mandeep, Ravi, Abhikrishna

Innovative Friction Locking Mechanism for High Voltage Busbar Connections in EV Batteries

2026-26-01551/16/2026

In the development of high-voltage (HV) batteries, ensuring secure connections between HV conductors and maintaining the safety and performance of the battery pack is paramount. Therefore, In the pursuit of enhancing efficiency and reliability in electrical connections, this paper explores the innovative alternate for a traditional screwing method with a friction locking mechanism for connecting busbars. The novel design reimagines the busbar as a Friction clamp (Female part) that securely holds the male part of the Busbar, significantly increasing the contact surface area up to 50%. This enhanced surface area not only improves electrical conductivity but also reduces heat generation, addressing common issues associated with traditional screw-based connections. By eliminating the need for screws, the new design streamlines the assembly process, resulting in reduced cycle times and improved overall assembly line efficiency. This study presents the design methodology, performance

Venkatesh, Murali, Raghu, Arun, Bhramanna, Amol

Standardized design principles and emerging opportunities for AI-integrated CAD systems.

2026-26-06321/16/2026

Artificial Intelligence (AI) in the automotive industry is growing and transforming in different segments of the industry. Still there is a significant gap persisting in the standardization of design principles and the incorporation of manufacturing constraints in system. However current development in AI CAD systems is isolated and non-parametric way, in contrary the conventional way of CAD methodology is knowledge based and systematic parametric steps which is agile to the iterative improvement. Hence it will be challenging in integration and adoption of these AI CAD systems in the well-established product development cycle. The research focuses on identifying the scope of AI integration which includes generative design, automated error detection, and design pattern-dependent learning systems, but also stresses the importance of standardized policies to address fundamental questions of system coherence, uniformity, and broad applicability. This research paper studies the adoption of

Shaikh, Taha Mukhtyarmiya, Harel, Samarth, Kumar, Akarsh, Venkitachalam, Muthukumar, SHAH, BHUMIKA, Chakraborty, Pinka

Virtual Strain correlation with measured strain test data over Frame using nCode Design Life

2026-26-05451/16/2026

Physical tests serve as a benchmark to validate and improve the accuracy of CAE models. If the CAE results correlate well with physical test data, it confirms that the simulation is reliable and can be used for predictive analysis. Earlier for correlation, we use stress output from generic load-cases and single max value of measured strain data which was inappropriate to get exact correlation. Since output of virtual strain gauge is strain history, so entire characteristics can be compared i.e. magnitude and phase. In this paper, we have used nCode Design Life’s virtual strain gauge approach to correlate an FE Model’s (Frame) result with measured strain gauge data of RLDA test. If the model has been properly meshed, loaded, and constrained, the predicted virtual strain from Design Life will correlate with the measured strain. In this problem, model (Frame) is loaded with unit force and moment in all three directions at 31 locations (Hardpoints). Virtual Strain gauge calculates the

Kumar, Mohit, Dhole, Avinash, Trigune, Vinayak, Kangde, Suhas

Predictive Simulation Framework for Tyre Curb Impact Durability Assessment and Design Optimization

2026-26-03961/16/2026

Tyre structural durability validation is a critical aspect of automotive design, considering the worsening road conditions. One of the key validation tests for assessing structural integrity is the curb impact test, which evaluates the tyre's ability to withstand sudden and concentrated impacts. Typically, this process involves physical testing of preliminary tyre samples, followed by iterative modifications to the tyre's construction to meet durability requirements. However, this approach often compromises ride performance, necessitating a more efficient and predictive methodology. To address this challenge, a frugal simulation-based prediction methodology has been developed to evaluate tyre curb impact durability before vehicle-level testing. This allows for the optimization of tyre design parameters early in the development process, ensuring structural performance while minimizing ride and handling (R&H) tuning iterations. By reducing the number of iterations, the methodology

Sundaramoorthy, Ragasruoban, LENKA., VISWESWARA

Virtual Reality in Assembly Simulations: Outpacing Tecnomatix Process Simulate for Faster Time-to-Market

2026-26-03981/16/2026

Virtual Reality (VR) technology is emerging as a transformative solution in manufacturing industry. It offers significant advantages over traditional tools like Tecnomatix Process Simulate (PS) in assembly and ergonomic simulations. Analysis using PS is time consuming and lacks real time human interaction as it relies on detailed modelling and sequential workflows, which will delay the identification of assembly no-build conditions and ergonomic issues. This paper evaluates the time and cost saving potential of VR in assembly processes and explores its role in minimizing the need for physical prototypes across various stages of vehicle development. VR provides interactive environments, enabling interaction with 3D models and real-time collaboration with various teams across the globe. This leads to faster identification of assembly process flaws, quicker iteration cycles, and a reduced need for physical prototypes in the station development process for the lines. VR allows individuals

Nagendran, Rakesh Kumar

Fatigue Life Prediction Methodology for Vehicle Suspension System and correlation with Physical Test

2026-26-04591/16/2026

Fatigue Analysis is a safety critical area in design engineering for load bearing members. The design of a durable suspension system forms the foundation of vehicle architecture. The challenge lies in accurately predicting fatigue in critical areas to reduce field failures, primarily due to the absence of a validated methodology for fatigue calculation. This study provides an overview of fatigue assessment for Knuckle assembly/Rear Twist Beam based on digital Road Load/test Data for Finite Element Analysis (FEA) process for design development. This study makes use of Computer Aided Engineering (CAE) solvers such as Optistruct for model setup and fatigue tool such as nCode/FEMFAT for Fatigue Analysis. The methodology used for Fatigue estimation of rear suspension components such as Rear Twist Beam and Knuckle assembly is based on Digital Road Load Data/duty cycle loads applied to the suspension components at the hard point location at assembly level. The fatigue process used for

Kokare, Sanjay, Nagapurkar, Tejas, Iqbal, Shoaib

Simulation-Driven Load Spectrum Prediction_ Virtual RLDA for Chassis and Suspension System

2026-26-00951/16/2026

In the rapidly evolving and highly competitive automotive industry, manufacturers are under immense pressure to bring products to market quickly while meeting customer expectations. As a result, optimizing the product development timeline has become essential. Structural integrity analysis for chassis and suspension systems lies in the accurate acquisition of operational load spectra, conventionally executed through Road Load Data Acquisition (RLDA) on instrumented vehicles subjected to proving ground excitation. At this point, RLDA is mainly used for final validation and fine-tuning. If any performance shortfalls, such as premature component failure or durability issues, are discovered, they often trigger design revisions, prototype rework, and additional testing This study proposes a Virtual Road Load Data Acquisition (vRLDA) methodology employing a high-fidelity full-vehicle multibody dynamic (MBD) representation developed in Adams Car. The system is parameterized and uses high

Goli, Naga Aswani Kumar, PRASAD, TEJ PRATAP

Master Complexity of Version Management in SDM by AI-Driven Assistance

2026-26-04391/16/2026

Simulation-driven product development involves numerous CAE model iterations, where each version represents a critical difference. Usually, these multiple model versions are generated by hundreds of simulation engineers working in teams distributed across the globe, making functional collaboration a key for effective product development. To manage vast amounts of CAE data generated by engineers working simultaneously on a project, it is imperative to have a robust version management system to track changes in the CAE data. A robust version management is the backbone of an effective simulation data management (SDM) system. It involves capturing and documenting model changes at every design iteration. An accurate documentation of the model changes is crucial as it helps in understanding the model evolution and collaboration among engineers. However, documenting is usually considered a boring and tedious task by many engineers. This often leads to bad change documentation, which in turn

Thiele, Marko, Sharma, Harsh

Strategic Design of Intake Systems for Crafting a Sporty Acoustic Signature in Passenger Vehicles

2026-26-03281/16/2026

In pursuit of a distinct sporty interior sound character, the present study explores an innovative strategy for designing intake systems in passenger vehicles. While most existing literature primarily emphasizes exhaust system tuning for enhancing vehicle sound quality, the current work shifts the focus toward the intake system’s critical role in shaping the perceived acoustic signature within the vehicle cabin. In this research work, target cascading and settings were derived through a combination of benchmark and structured subjective evaluation study and aligning with literature review. Quantitative targets for intake orifice noise was defined to achieve the desired sporty character inside cabin. Intake orifice targets are engineered based on signature and sound quality parameter required at cabin. Systems are designed by using advanced CAE techniques, Specific identified acoustic orders were enhanced in the intake system to reinforce the required signature in acceleration as well

Sadekar, Umesh Audumbar, Titave, Uttam, Patil, Jitendra

Investigation of Fatigue Durability Failure Mechanisms in High-Pressure Hydraulic Pipes of Power Steering Systems

2026-26-05421/16/2026

Abstract—The high-pressure hydraulic pipeline in the power steering system is a vital component for ensuring optimal performance. During warranty analysis, leakage incidents were observed at the customer end within the warranty period. The primary factors contributing to these failures include pipe material thickness, material composition, mechanical properties, and engine-induced vibrations. This study investigates fatigue-related failures through detailed material characterization and Computer-Aided Engineering (CAE) based on real world usage road load data collected. The objective is to identify the root causes by examining the influence of varying pipe thickness on fatigue life. The investigation discovered that crack initiation predominantly occurred on the concave side of bent pipe sections, specifically on the engine-side high-pressure steering line, which is connected to the power steering pump mounted on the engine. Fracture surfaces exhibited characteristics consistent with

SURVADE, LALIT, Koulage, Dasharath Baliram, Biswas, Kaushik

Developing Advanced CAE Model for Door Glass Regulator Operating Noise Reduction through TEST/CAE Correlation

2026-26-03111/16/2026

The importance of performance improvement and weight optimization using CAE in the early design stages of vehicle development has been continuously increasing over the past two decades. And, the accuracy of CAE models plays key role, more efforts are required to improve it. Representation of exact physical model in CAE is still a big challenge for achieving an accurate TEST vs CAE correlation. In this research, the procedure and application of door system model correlation were described to reduce the glass regulator operating noise. The function of a regulator in door system is to open and close the glass. The regulator under improper design creates unwanted noise and discomfort to the passenger. In current door CAE Model, we are unable to identify this real time problem. Therefore, this paper discusses how to correlate door system model according to the assembly stage based on modal correlation and it helped in calculating accurate glass regulator operating noise. As a result, the

PANUGANTI, NARESH KUMAR, Choi, Seungchan

Optimisation of frontal impact force scheme to accelerate the target setting process for development of front-end structures in vehicles.

2026-26-00011/16/2026

A passenger vehicle's front-end structure's structural integrity and crashworthiness are crucial to ensure compliance with various frontal impact safety standards (such as those set by Euro NCAP & IIHS). For a new front-end architecture, design targets must be defined at a component level for crush cans, longitudinal, bumper beam, subframe, suspension tower and backup structure. The traditional process of defining these targets involves multiple sensitivity studies in CAE. This paper explores the implementation of Physics-Informed Neural Networks (PINNs) in component-level target setting. PINNs integrate the governing equations into neural network training, enabling data-driven models to adhere to fundamental mechanical principles. The underlying physics in our model is based upon a force scheme of a full frontal impact. A force scheme is a one-dimensional representation of the front-end structure components that simplifies a crash event's complex physics. It uses the dimensional and

Gupta, Ishan, Bhatnagar, Abhinav, Kumar, Ayush

Optimization of Electric Drive Unit Mounting for Vibration Isolation in EV Powertrains Using Multibody Dynamics

2026-26-00801/16/2026

With growing significance of electric vehicles (EVs), their powertrains—while naturally quieter than internal combustion engine (ICE) powertrains—pose new NVH (Noise, Vibration, Harshness) challenges. These are triggered mainly from high-frequency disturbances caused by electric motors and gear interactions. Isolation of such excitations is essential for securing cabin refinement and customer expectations for acoustic comfort. This paper offers a simulation-based approach to optimal placement of the electric drive unit (EDU), which houses the electric motor and gearbox, with the objective of reducing vibration transfer to the chassis of the vehicle. The methodology explores the effect of spatial mount repositioning under actual dynamic load conditions through multibody dynamics (MBD) modeling and integrated optimizer using advanced multibody dynamics simulation software – Virtual Dynamics. The suggested workflow helps in effective investigation of mount positioning within packaging

Mane, Prashant, Shah, Swapnil, Back PhD, Arthur, Pinjari, Abrar, Emran, Ashraf, Mane PhD, Shrikala

Virtual Prototyping: Accelerating Traction Motor Development for Commercial Electric Vehicles

2026-26-01521/16/2026

This paper presents the virtual prototyping of traction motor in commercial EV to make an early prediction of the performance parameters of the machine without spending an enormous cost in building a physical structure. A 48/8 slot-pole configuration of IPMSM is used to demonstrate the electromagnetic and thermal co-simulation in ANSYS MotorCad. The key dimensions were calculated on the basis of the permanent-magnet field theory, and the 2D finite element method (FEM) model of the IPM motor using Ansys MotorCad electromagnetic simulation tool. The influence of geometrical parameters on the performances of traction motor are evaluated based on FEM. The temperature distribution of the motor under rated operating condition and the condition of maximum speed were also analyzed. Alongside, the effects of saturation, demagnetization analysis, and the impact of PM flux linkage on inductances are also considered in this paper. At last, the simulation and analytical results of the IPMSM motor

Murty, V. Shirish, Rathod, Sagarkumar, Gandhi, Nikita, Tendulkar, Swati, Kumar, Kundan, Thakar, Dhruv, Sethy, Amanraj

Exhaust Hot end system Transient Heat Transfer Analysis using Heat Transfer Coefficient (HTC) approach, Thermo-Mechanical Fatigue Analysis to evaluate thermal durability and physical validation through Thermo-Shock Testing

2026-26-02241/16/2026

Exhaust system suppliers are continuously enhancing their processes by adopting advanced simulation techniques and expedited testing procedures for optimizing exhaust systems. This aims to reduce time to market, accelerate vehicle launches, and ensure first-time right and consistent compliance with performance and durability standards. Traditionally, the CFD team conducts Conjugate Heat Transfer (CHT) analysis on the exhaust hot end system using input conditions such as engine-out gas temperature and maximum mass flow rate. The CAE team then performs steady-state heat transfer analysis by sharing the structural CAE model with CFD for CHT skin temperature mapping. Once steady state heat transfer analysis complete, skin temperature plots are to be compared with CFD to match CHT temperature results. These results are used for steady-state thermo-mechanical analysis across all heat-up cycles and assume system under ambient temperature for all cool-down cycles to evaluate system thermal

Natarajan, Suresh, J Y, Raja Shangara Vel

A Noval methodology of compact cooling unit design for Truck applications by using CAE CFD simulation

2026-26-04601/16/2026

The implementation of AC unit on truck as compulsory as per government guideline demands the AC supplier to design a compact and modular AC unit within the available package space. The installation of AC unit inside the vehicle helps the driver to drive safely due to better cabin comfort. This will reduce fatigue due to the long driving of the truck drivers. Thereby the safety of the truck and driver will be saved with the implementation. But there are challenges for AC manufactures to design the compact size AC unit. The challenges like performance, durability, cost and less noise to be met as per customer requirement. To overcome the issue of design at the early stage and compact AC unit within small space is possible with the support of simulation software. AE and CFD plays a major role in this regard. So first unit level CAE and CFD analysis conducted to predict the result. AE used for checking the strength of the mounting bracket of cooling unit and CFD used for verifying the air

Parayil, Paulson

Low-speed steering returnability analysis and improvements through mathematical modeling and CAE simulation for SUV

2026-26-05731/16/2026

In driving, steering serves as the input mechanism to control the vehicle's direction. The driver adjusts the steering input to guide the vehicle along the desired path. During maneuvers such as parking or U-turns, the steering wheel is often turned fully from lock to lock and then released. It is expected that the steering wheel quickly returns to its original position. Steering returnability is defined as the ratio of the difference between the steering wheel position at lock to lock and the steering wheel angle after 3 seconds of release, to the steering wheel angle at the lock position, under steady-state cornering conditions at 10 km/h. Industry standards dictate that the steering system should achieve 75% returnability under these conditions within 3 seconds. Achieving proper steering returnability characteristics is a critical aspect of vehicle design. Vehicles equipped with Electric Power-Assisted Steering (EPS) systems can more easily meet returnability targets since the

Singh, Ram Krishnan, ahire, Manoj, JAIN, PRIYA, Vellandi, Vikraman, SUNDARAM, RAGHUPATHI, Paua, Ketan

CAE driven seam weld optimization for stiffness and fatigue calculations

2026-26-04781/16/2026

Structural parts are joined using seam welds, spot welds and bolted connections. The strength and stiffness of any structural part are strongly influenced by the properties of their joints. Seam welds are used extensively in the automotive industry to join panels. The design and the positioning of the seam welds have a significant impact on the technical cost of the project. In the automotive industry, structural optimization and fatigue simulation have become standard applications during any development process. The conventional approach in identifying the position and number of seam welds and its length is time consuming and leads to over design. Current paper highlights developing a simulation process for seam weld optimization in identifying the optimal position and length of seam welds. The optimization workflow is set up in CAE with design objective of minimizing the number of seam welds and finding the optimal length by meeting stiffness targets and fatigue life of seam welds

Gudipati, Raja Shekar Reddy

Efficient simulation modelling technique using automatic mesh and contact interface generation

2026-26-03921/16/2026

Computer-Aided Engineering (CAE) users often follow traditional meshing and contact generation processes, which are time-consuming, repetitive, and heavily dependent on user experience and perspective. The method described herein presents a system for generating a mesh and contact interfaces that ensures standardized and consistent output for a model. The system stores multiple mesh configurations, each containing a set of predefined geometric features to create standard meshes for users. The process begins by receiving data for a CAD model of an object and capturing user input through a graphical user interface. Users specify several parameters, including the desired body type, global mesh size, and a selected mesh configuration from the available options. Using these inputs, the system generates a mesh for the model, incorporating the selected mesh configuration’s geometric features along with the specified body type and size. The contact generation process offers several key

DABADGAONKAR, ANAND, Kamble, Amardeep

Advanced Defect Detection Techniques Using AI, CAD Data, and Computer Vision

2026-26-06441/16/2026

In area of modern manufacturing, ensuring product quality and minimizing defects are utmost important for maintaining competitive advantage and customer satisfaction. This paper presents an innovative approach to detect defect by leveraging Artificial Intelligence (AI) models trained using Computer-Aided Design (CAD) data. Traditional defect detection methods often rely on physical inspection, which can be time-consuming and prone to human error. The conventional method of developing an AI model requires a physical part data , By utilizing CAD data, the time to develop an AI model and implementing it to production line station can be saved drastically . This approach involves the use of AI algorithms trained on CAD models to detect and classify defects in real-time. The field trial results demonstrate the effectiveness of this approach in various industrial applications, highlighting its potential to revolutionize defect detection in manufacturing.

Kulkarni, Prasad Ramesh, Sahu, Dilip, Joshi, Chandrashekhar, Khatavkar, Akshay, Poddar, Shivani, Deep, Amar

Optimization of a Positive Displacement Type Supercharger Using Response Surface Modeling (RSM)

2026-26-04291/16/2026

Air suction in a naturally aspirated engine is a crucial influencing parameter to dictate the specific fuel consumption and emissions. For a multi-cylinder engine, a turbocharger can well address this issue. However, in a single or two-cylinder engine, the usage of turbocharger is not recommended, due to the lack of availability of continuous exhaust energy pulses. A supercharger solution comes handy in this regard for a single or two-cylinder engine. In this exercise, we explore the possibility of the usage of a positive displacement type supercharger, to enhance the air flow rate of a single cylinder, naturally aspirated, diesel engine for genset application, operating at 1500 rpm. The supercharger parametric 3D CAD model was prepared in Creo, with (a) Generating radius, (b) depth of blower and (c) clearance between lobes & lobe and casing, being treated as three parameters. The optimum supercharger design was expected to (a) generate a boost pressure of minimum 0.4 bar (gauge), (b

Satre, Santosh Dadasaheb, Mukherjee, Nalini, Rajput, Surendra, Nene, Devendra

A Data-Centric Approach to Identify Optimal NVH simulation Tools and Solvers

2026-26-03561/16/2026

The world is rapidly evolving towards a data-driven paradigm, with widespread adoption of tools and techniques such as Artificial Intelligence, Machine Learning, Digital Twins, and Cloud Computing. In the automotive sector, vast amounts of data are being generated through both physical and digital test evaluations. Among these, Computer-Aided Engineering (CAE) stands out as one of the largest contributors to data generation, as physical testing is often cost-prohibitive due to the need for prototypes and complex test setups. The field of Automotive Noise, Vibration, and Harshness (NVH) is advancing exponentially, driven by stringent regulatory norms and growing customer demand for comfort. Digitally advanced techniques are playing a pivotal role in revolutionizing NVH processes. Data generation via CAE tools has become an integral part of engineers' daily operations, with the selection of appropriate CAE software and solvers being critical. This choice impacts factors such as user

Hipparge, Vinod, masurkar, Nikita, Arabale, Vinand, Billade, Dayanand

Fitting, Assembly, Adapter Ring Locked Port Connection to Flared Tube End

AS1985E (Current)

9/26/2025

No scope available.

G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies

Prediction and Validation of Sloshing and Fluid-Structure Interactions Using FPM for VTOL Applications

F-0081-2025-0400

5/20/2025

Accurate simulation of fluid-structure interactions (FSI) is critical for designing aircraft systems, particularly for applications involving fuel tank sloshing and large deformations. Traditional added mass methods often fail to capture the nonlinear and frequency-dependent behavior of these coupled systems. This study applies the Finite Pointset Method (FPM), a mesh-free computational fluid dynamics (CFD) technique, coupled with an explicit finite element solver, to predict complex FSI phenomena. Validation is performed using benchmark experiments, including a harmonic tank sloshing test and a guided plate ditching scenario, with results demonstrating strong agreement with measured pressures and structural responses. Additional validation on a composite fuel tank drop impact test confirms FPM's ability to model large deformations and rupture under dynamic loading. The findings highlight FPM's robustness and adaptability for aerospace FSI problems, offering a powerful alternative for

Dwarampudi, Ramesh, Vaz, Ignatius

Prediction Method of Strength Robustness Affected by Arc Welding Sectional Dimensions

2024-32-00384/18/2025

The arc welding process is essential for motorcycle frames, which are difficult to form in one piece because of their complex shapes, because a single frame has dozens of joints. Many of the damaged parts of the frames under development are from welds. Predicting the strength of welds with high reliability is important to ensure that development proceeds without any rework. In developing frames, CAE is utilized to build up strength before prototyping. Detailed weld shapes are not applicable to FE models of frames because weld shapes vary widely depending on welding conditions. Even if CAE is performed on such an FE model and the evaluation criteria are satisfied, the model may fail in the actual vehicle, possibly due to the difference between CAE and actual weld bead geometry. Therefore, we decided to study the extent to which the stresses in the joint vary with the variation of the weld bead geometry. Morphing, a FE modeling method and design of experiment method, was utilized to

Hada, Yusuke, Sugita, Hisayuki

test rejection

SAE-PP-094591/27/2025

test

Rickard, Christopher

Arinc Automation Document - Standard Characteristic - PageCount less than 45

KJH003 (Historical)12/19/2024

Arinc Automation Document - Standard Characteristic - PageCount less than 45

Aviation Maintenance Committee, Airlines Electronic Engineering Committee

asdg

jmsaldkfgjalkerjtw (Current)8/29/2024

asdg

Airlines Electronic Engineering Committee

A Multidisciplinary Mid-fidelity Approach for Tiltrotor Wing Aeroelastic Design based on Structural Mesh Morphing

F-0080-2024-1149

5/7/2024

This paper introduces a Multidisciplinary Design and Optimization (MDO) approach for the design of a tiltrotor wing, utilizing as test case a semi-wing with integrated nacelle and rotor. Structural integrity is assessed via stress analysis on a GFEM, which also forms the basis for a coupled wing-rotor aeroelastic model to ensure whirlflutter stability. Aerodynamic performance is assessed through CFD analysis of two-dimensional wing's airfoil shape. The MDO workflow leverages three levels of design space control that can influence the structural response of the wing: other than controlling the structural properties of composite materials, the internal wing-box architecture and external airfoil shape are modified acting directly on the FEM by means of a mesh morphing technique. This methodology allows for the use of mid-fidelity finite element models, bypassing CAD reshaping and remeshing. Validation tests confirm the approach's effectiveness in producing optimized designs. Additionally

Punzi, Claudio, Crooks, Mark, Mancini, Andrea, D'Amico, Federico, Giovanardi, Eleonora

Aircraft Electrical Wiring Organization - Key to an Autonomous AI

F-0080-2024-0005

5/7/2024

An essential component for the advancement of autonomous flight lies in the development of an intelligent routing system designed to facilitate the maintenance and troubleshooting of electrical wiring. Utilizing software with the capability to present routed paths in a computer-aided design (CAD) format allows for a detailed representation of the rules governing the layout of wiring around structural supports and distribution channels. Despite this, three-dimensional (3D) methodologies have yet to fully incorporate critical data related to the characterization of individual wiring signals, hindering automatic routing. This paper underscores a competitive edge that can be achieved by expanding 3D capabilities to accurately depict the current state of wiring signals in terms of temperature, humidity, electromagnetic frequency, amperage, and other relevant factors. Achieving this involves integrating a non-intrusive smart sensing technology with the intelligent routing system to monitor

Rhysing, Daryian