Browse Topic: CAD, CAM, and CAE
ABSTRACT The University of Delaware (UD) and the US Army DEVCOM-GVSC (GVSC) have partnered to show the feasibility of fabricating mission specific, man-packable, autonomous vehicles that are created by Computer Aided Design (CAD) and are then produced, from start-to-finish, in a single manufacturing unit-cell without human intervention in the manufacturing process. This unit-cell contains many manufacturing processes (e.g., additive manufacturing (AM), pick-and-place, circuit printing, and subtractive manufacturing) that work in concert to fabricate functional devices. Together, UD and GVSC have developed the very first mission specific autonomous vehicle that is fully fabricated in a single manufacturing unit-cell without being touched by human hand. Citation: Jacob W. Robinson, Thomas W. Lum, Zachary J. Larimore, Matthew P. Ludkey, Larry (LJ) R. Holmes, Jr. “AUTOMATED MANUFACTURING FOR AUTONOMOUS SYSTEMS SOLUTIONS (AMASS)”, In Proceedings of the Ground Vehicle Systems Engineering and
ABSTRACT The objective of this effort is to create a parametric Computer-Aided Design (CAD) accommodation model for the Fixed Heel Point (FHP) driver and crew workstations with specific tasks. The FHP model is a statistical model that was created utilizing data from the Seated Soldier Study (Reed and Ebert, 2013). The final product is a stand-alone CAD model that provides geometric boundaries indicating the required space and adjustments needed for the equipped Soldiers’ helmet, eyes, torso, knees, and seat travel. Clearances between the Soldier and surrounding interior surfaces and direct field of view have been added per MIL-STD-1472G. This CAD model can be applied early in the vehicle design process to ensure accommodation requirements are met and help explore possible design tradeoffs when conflicts with other design parameters exist. The CAD model will be available once it has undergone Verification, Validation, and Accreditation (VV&A) and a user guide has been written
ABSTRACT Gas metal arc pulse directed energy deposition (GMA-P DED) offers large-scale additive manufacturing (AM) capabilities and lower cost systems compared to laser or electron beam DED. These advantages position GMA-DED as a promising manufacturing process for widespread industrial adoption. To enable this “digital” manufacturing of a component from a computer-aided design (CAD) file, a computer-aided manufacturing (CAM) solver is necessary to generate build plans and utilize welding parameter sets based on feature and application requirements. Scalable and robot-agnostic computer-aided robotics (CAR) software is therefore essential to provide automated toolpath generation. This work establishes the use of Autodesk PowerMill Ultimate software as a CAM/CAR solution for arc-based DED processes across robot manufacturers. Preferred aluminum GMA-P DED welding parameters were developed for single-pass wide “walls” and multi-pass wide “blocks” that can be configured to build a wide
ABSTRACT Conceptual design of automotive structures has received substantial research attention in recent years in order to speed up vehicle development and innovation. Although several structural optimization methods have been employed in concept design, there still exists lack of efficient design tools to produce initial design shapes with less problem dependency, less computation-intensive analysis and more design flexibility. In this paper, an innovative Computer Aided Engineering (CAE) approach based on an integrated Genetic Algorithms(GA) and Finite Element (FE) optimization system has been studied and implemented for efficient conceptual design of automotive suspension system related structural part. Integration of GA provides the method a great amount of design flexibility and robustness that increases possibility of finding more efficient and innovative design shapes of the structure
ABSTRACT Application of human figure modeling tools and techniques has proven to be a valuable asset in the effort to examine man-machine interface problems through the evaluation of 3D CAD models of workspace designs. Digital human figure modeling has also become a key tool to help ensure that Human Systems Integration (HSI) requirements are met for US Army weapon systems and platforms. However, challenges still exist to the effective application of human figure modeling especially with regard to military platforms. For example, any accommodation analysis of these systems must not only account for the physical dimensions of the target Soldier population but also the specialized mission clothing and equipment such as body armor, hydration packs, extreme cold weather gear and chemical protective equipment to name just a few. Other design aspects such as seating, blast mitigation components, controls and communication equipment are often unique to military platforms and present special
ABSTRACT An endgame, vulnerability/lethality code, TurboPK was developed to take advantage of parallel processing of multi-core, modern-day desktop and laptop computers. TurboPK is used to simulate and analyze weapon-related kinetic energy and blast effects of military vehicles. It implements Department of Defense (DoD)-approved algorithms and is compatible with the DoD design trade-off process. Its speed advantage is commensurate with the increase in number of cores used. A quad-core processor results in run times that are four times faster than using a single core. The heart of endgame analysis calculates geometric intersections of projectiles or fragments with vehicle components using ray-tracing algorithms. For example, literally thousands of rays are used to accurately model the fragment ejecta from a warhead in a burst point analysis. Algorithms originally written for a single processor have been rewritten to exploit an open-source, parallel process ray tracer called Embree
ABSTRACT As part of DARPA’s Adaptive Vehicle Make (AVM) portfolio of programs, blast and ballistic survivability analysis tools were developed. The intent of these tools was to facilitate design and design optimization by making it possible for designers to perform survivability analysis from CAD and to automate the survivability analysis pipeline to allow optimization codes to invoke the survivability tools and obtain results. This paper describes some of the tools and their capabilities through highlighting five innovations utilized in the program: multi-fidelity modeling; automated meshing and welding; uncertainty quantification and 95% bounds; a large material property database and more accurate blast loads; and automating the entire computational pipeline
ABSTRACT Probabilistic Principal Component Analysis (PPCA) is a promising tool for validating tests and computational models by means of comparing the multivariate time histories they generate to available field data. Following PPCA by interval-based Bayesian hypothesis testing enables acceptance or rejection of the tests and models given the available field data. In this work, we investigate the robustness of this methodology and present sensitivity studies of validating hybrid powertrain models of a military vehicle simulated over different proving ground courses
The integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies has significantly changed various industries. This study demonstrates the application of a Convolutional Neural Network (CNN) model in Computational Fluid Dynamics (CFD) to predict the drag coefficient of a complete vehicle profile. We have developed a design advisor that uses a custom 3D CNN with a U-net architecture in the DEP MeshWorks environment to predict drag coefficients (Cd) based on car shapes. This model understands the relationship between car shapes and air drag coefficients calculated using computational fluid dynamics (CFD). The AI/ML-based design advisor feature has the potential to significantly decrease the time required for predicting drag coefficients by conducting CFD calculations. During the initial development phase, it will serve as an efficient tool for analyzing the correlation between multiple design proposals and aerodynamic drag forces within a short time frame
Pick-and-place machines are a type of automated equipment used to place objects into structured, organized locations. These machines are used for a variety of applications — from electronics assembly to packaging, bin picking, and even inspection — but many current pick-and-place solutions are limited. Current solutions lack “precise generalization,” or the ability to solve many tasks without compromising on accuracy
Reducing vehicle weight is a key task for automotive engineers to meet future emission, fuel consumption, and performance requirements. Weight reduction of cylinder head and crankcase can make a decisive contribution to achieving these objectives, as they are among the heaviest components of a passenger car powertrain. Modern passenger car cylinder heads and crankcases have greatly been optimized in terms of cost and weight in all-aluminum design using the latest conventional production techniques. However, it is becoming apparent that further significant weight reduction cannot be expected, as processes such as casting have reached their limits for further lightweighting due to manufacturing restrictions. Here, recent developments in the additive manufacturing (AM) of metallic structures is offering a new degree of freedom. As part of the government-funded research project LeiMot [Lightweight Engine (Eng.)] borderline lightweight design potential of a passenger car cylinder head with
Have you ever gazed at the vastness of the stars and wondered what else your CNC machine can create? Greg Green had the opportunity to find out when he joined the staff at the Canada-France-Hawaii Telescope (CFHT) in Waimea, Hawaii
Homologation is an important process in vehicle development and aerodynamics a main data contributor. The process is heavily interconnected: Production planning defines the available assemblies. Construction defines their parts and features. Sales defines the assemblies offered in different markets, where Legislation defines the rules applicable to homologation. Control engineers define the behavior of active, aerodynamically relevant components. Wind tunnels are the main test tool for the homologation, accompanied by surface-area measurement systems. Mechanics support these test operations. The prototype management provides test vehicles, while parts come from various production and prototyping sources and are stored and commissioned by logistics. Several phases of this complex process share the same context: Production timelines for assemblies and parts for each chassis-engine package define which drag coefficients or drag coefficient contributions shall be determined. Absolute and
Tire/Road noise is a dominant contribution to a vehicle interior noise and requires significant engineering resources during vehicle development. A process has been developed to support automotive OEMs with road noise engineering during vehicle design and development which has test as its basis but takes advantage of simulation to virtually accelerate road noise improvement. The process uses noise sources measured on a single tire installed on a test stand in a chassis dynamometer. The measured sources are then combined with vehicle level transfer functions calculated using a Finite-Element model for structure-borne noise and a Statistical Energy Analysis (SEA) model for airborne noise to predict the total sound at the driver’s ears. The process can be applied from the initial stages of a vehicle development program and allows the evaluation of vehicle road noise performance as perceived by the driver long before the first prototype is available. This process is also extensible to
While conventional methods like classical Transfer Path Analysis (TPA), Multiple Coherence Analysis (MCA), Operational Deflection Shape (ODS), and Modal Analysis have been widely used for road noise reduction, component-TPA from Model Based System Engineering (MBSE) is gaining attention for its ability to efficiently develop complex mobility systems. In this research, we propose a method to achieve road noise targets in the early stage of vehicle development using component-level TPA based on the blocked force method. An important point is to ensure convergence of measured test results (e.g. sound pressure at driver ear) and simulation results from component TPA. To conduct component-TPA, it is essential to have an independent tire model consisting of wheel-tire blocked force and tire Frequency Response Function (FRF), as well as full vehicle FRF and vehicle hub FRF. In this study, the FRF of the full vehicle and wheel-tire blocked force are obtained using an in-situ method with a
A damper is one of the most important elements in a vehicle suspension system. The damper valves are a fully coupled hydraulic system where the suspension fluid flow interacts with the elastic response of the valve structure. The base valve in the hydraulic damper plays a significant role in compression damping force characteristics of a damper, and therefore designing of the base valve is critical for damping force tuning. In this paper, the impact of the base valve design complexity reduction is quantitatively analyzed. The Current base valve design is restrictive which prevents achieving the required compression damping force ranges without a substantial base valve body parts library. A new base valve assembly is suggested with one more degree of freedom via a restrictor plate. Introducing this new element allows reducing the number of base valve designs for damping performance tuning. The design of the new base valve is engineered from existing designs with the aid of computer
In the automotive industry, the electric vehicle is the new era, and companies are committed to reducing carbon emissions by electrification of their vehicles. In the development of electric vehicles, the battery is the central power source for all the parts of the vehicle. Usually, it is placed under the body because of its size and mass. So, it is important to protect battery cells from leakage and damage from obstacles. For on-road electric vehicles, speed bumps are one of the crucial obstacles. This paper investigates and analyses the protection of battery pack systems in electric vehicles while encountering speed bump profiles at different speeds. During the physical test on a speed bump, there is a possibility of bump hit on the battery pack system and it is necessary to ensure the structural safety of the battery pack systems. In this study, CAE method has been developed to validate the battery pack system in the event of a speed bump crossing. Virtual simulation analysis was
As data science technologies are being widely applied on various industries, the importance of data itself increased. A typical manufacturer company has a vast data set of products as 2D&3D drawing formats, but a common problem was that building a database from the 2D&3D drawings costs much, and it is hard to update the database after it once built. Also, it is high-cost job when the new factor researched and necessary to investigate the new factors on previously fixed or uploaded drawings. As new products are developed with time, these problems are getting more difficult. In this paper, an automated database building method using CATIA introduced and future probabilities are suggested. An aluminum wheel part was used as an example. An automated logic used CATIA V5’s VBA functions and was handled by python programming language. Product database was established by using the automated logic for extracting engineering design features, and data mining process was deployed based on the
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