Multi-Physics Design and Optimization of a Complex Radar System

Heavy equipment manufacturers want to design products that are durable and perform at their peak under a variety of conditions. To accomplish this, Altair provides an integrated multi-disciplinary simulation environment to virtually test and optimize equipment performance and therefore, help reduce design and development costs. Using simulation-driven design, studying the full dynamics of a product or system is possible, from motion analysis to complete lifecycle durability testing.

A key development goal of any machine-building project is to produce perfectly running, reliable machines that make high-quality products. By leveraging accurate virtual prototypes, seamless production can be ensured earlier in the development process to help assess and improve product profitability.

Heavy mobile machines consist mostly of production equipment working almost twenty hours a day, year on year, in diverse harsh environments, undergoing extreme loads and overloads. Especially diggers and loaders such as hydraulic excavators, wheel loaders, and backhoes, cater to multiple applications with use cases such as digging, trenching, loading, lifting, breaking, and ripping. Many times, these machines undergo non-standard uses where the machine is subjected to unplanned forces and moments as in the case of self-loading on a trailer, or a bucket hitting a dump truck body. This paper highlights the workflow process and simulation-driven methods to integrate multi-physics with Altair’s industry-leading solutions. The latest generation of Altair simulation tools can capture a wider range of vehicle systems and environmental interactions.

Information silos present a major challenge to Heavy Equipment OEMs. Poor integration of simulation models across the product life cycle, limited reuse of models between programs, and a variation of modeling maturity across various engineering disciplines result in lack of traceability and ultimately hampers development efficiency and product performance. Using system modeling and asset-centric data analytics solutions help develop and orchestrate coherent models to increase decision-making confidence and speed.

Learn how Altair AcuSolve™ performs with AMD EPYC™ 7003 series processors

Fluid mechanics simulation is a critical tool for late-stage failure risk mitigation, as well as a driver of design insights throughout the product development process. Used across all levels of product design and validation, from design engineers seeking to understand fluid and thermal effects on a design proposal to analysts performing advanced aerodynamic modeling, Computational Fluid Dynamics (CFD) serves a broad array of applications and a range of users with varied levels of expertise. The sometimes complex and computationally intensive nature of CFD necessitates careful consideration of the software and hardware investments required to produce accurate solutions and scale them at the speed of a company’s development process.

Two- and three-wheeler vehicle manufacturers, whether they are existing OEMs, new EV start-ups, or suppliers serving this segment, all have the goal of shortening product development time and getting product to market faster. With Altair HyperWorks™, ride, durability, and vehicle dynamics simulations for two- and three-wheeled vehicles can now be seamlessly performed using an intuitive and easy to use GUI with built-in libraries for vehicle models, analyses, and predicting and optimizing vehicle behavior.

As of today, the “classical” V diagram is very well known among more and more engineers. Nonetheless its usage – even partly – is far away from the potential that it offers. One reason might be, that its benefits are not really obvious for the end-users. With this presentation, we will bring a new view by “closing the old V” and transferring it to a “closed ∇ (Nabla) cycle”. The focus of this contribution is on the opportunities to significantly increase the effectiveness of the approach of model-based development (MBD) by re-using engineering efforts in multiple ways.

In order to reduce energy consumption, efficiency is a key criterion that designers seek to optimize their electric motors. Complementary to the electromagnetic analysis, a thermal characterization is essential to study from the first design phase how temperature influences the performance of the machine. To obtain results close to the real working conditions, the motor control and the current harmonics produced by the electrical converter and control algorithms cannot be ignored.

Reducing aircraft design and development time is critical for all aircraft manufacturers, from urban air mobility and electric aircraft startups to military to commercial OEMs. In order to fully understand and optimize the complex systems of systems required in modern aircraft, aerospace engineers leverage a simulation method called Model-based Systems Engineering (MBSE). MBSE allows the evaluation of various types of vehicle systems to determine which best meet the mission requirements.

In this article, appearing in the Fall 2020 issue of Engine + Powertrain Technology International, Altair outlines how a holistic approach to propulsion system design is enabling manufacturers to meet performance requirements while maximizing vehicle range.

Block construction is a modern shipbuilding method which involves the assembly of prefabricated modular sections. Cross-sections of the superstructure are pre-built in a shipyard, taken to the building dock, then hoisted into position and attached. Block splitting and lifting schemes are largely devised after the ship design phase is completed, relying on empirical data and expertise to avoid costly and potentially dangerous failures during build-up. Advances in computer-aided engineering (CAE), however, now make it possible to plan ship build-up in the principal design phase, giving designers greater insights into block assembly process outcomes and reducing downstream risk through simulation.

Transformers’ windings experience mechanical loads from electromagnetic forces due to the currents they carry. Power transformers can suffer from high sudden short-circuit currents. These short-circuit currents are a significant threat, not only from an electrical but also from the structural integrity point of view. In this paper, coupled electromagnetic and structural mechanics simulations are carried out to evaluate short-circuit fault risks in a comprehensive and accurate way.

Simulation helps you validate at the end of a product design cycle, but deployed early and throughout a development process, it can actually allow you to explore more potential solutions, collaborate more effectively and optimize the design for cost, performance, weight, and other important criteria. This infographic provides a framework for developing and implementing your own simulation-driven process to help you produce more efficient e-motors and shorten development times. 

High accuracy sensors and encoders are integral components of an e-motor drive, greatly impacting the quality and efficiency on the system. A purpose-driven simulation approach is needed to account for all the physical interdependencies within these complex multi-domain systems.

Induction Motors (IM) are widely used in various industries. To ensure their speed control, IM will be supplied with pulse width modulation (PWM). This kind of supply, can impact efficiency of the motor and degrade its vibro-acoustic behavior, generating noise nuisance. To tackle these technical challenges and ensure best-in class acoustic comfort for users, it is necessary to design a quiet e-motors at the early stage of design. The first aim of this paper is to show a new method to reduce noise and vibration due to PWM supply of induction machine. The proposed approach allows the passive reduction of air-gap flux density harmonics in an induction machine. The second interest, is to show a new method to analyze the vibro-acoustic behavior of a PWM-fed IM. The method is fully finite element (FE) computation. Finally, the third interest of this article, is to compare noise and vibration results between the proposed FE method, magneto-vibro-acoustic coupling and measurements. Good agreement between measurements and computation will be shown.

A company specializing in 3D printing relies on simulation to make tools for injection molding that are less expensive, lighter and better than those created with traditional methods.

To design and build an aerial ladder for a firetruck, the engineer needs to accurately determine the working loads the ladder will encounter. Some of these can be easy to interpret such as the weight of the firefighter in the basket at the end of the ladder, or the weight of the water being supplied to the nozzle. Other loads can be a little harder to quantify, such as how wind affects the ladder. There are several different ways to determine this effect, and two of those will be explored in this paper: the standard equation (ASCE 7-10), and CFD.

Optimal design methods involving the coupling of fluid and structural solutions are a topic of active research; particularly for aerospace applications. The paper presents a coupled fluid and structure approach to topology optimization using two commercial finite element solutions; AcuSolve and OptiStruct. A gradient based method is used to minimize the compliance of a structure subject to thermal loading. The optimal material distribution to minimize compliance is computed using the Solid-Isotropic Material with Penalty (SIMP) method available in OptiStruct. A volume fraction constraint is imposed in order to iteratively reduce the parts mass. Draw constraints are used to ensure manufacturability. The thermal loading is computed iteratively using a computational fluid dynamics (CFD) solution from AcuSolve. The optimization produces an innovative design which increases the heat rejection rate of the part while reducing the mass.

This paper describes the process of using Altair tools such as Flux for synchronous permanent magnet motor EM FEA analysis and HyperStudy to minimize the weight of the NdFeB magnets of a typical IPM motor for electric traction application such as the IPM motor of the Toyota Prius 2010.

XLDyn® allows the product engineer to develop and track requirements associated with different verification methods, so the current project status is always available. In addition, XLDyn® has fully integrated system level Design of Experiments (DoE) that provides valuable design guidance to select the best set of parameters or parts. Even test data can be included in the DoE.

In an electric machine, the torque is generated by electromagnetic forces which also create some parasitic vibrations of the stator. These vibrations excite the mechanical structure on which the motor is fixed and generate sound. When designing the electric machine, this aspect has to be taken into account from the start since it depends on the harmonic content of the currents that feed the machine, on the shapes of the rotor and stator, and on the interaction of the electric frequencies with the natural mechanical modes of the structure. To simulate this phenomenon, a coupling between electromagnetic calculations and vibration analysis has to be set-up. Some optimization procedure can also be added in order to reduce the noise. In what follows, it is shown how Altair HyperWorks suite; specifically FluxTM, OptiStruct®, HyperMesh® and HyperStudy® products have been successfully used to perform a multi-physics optimization for noise reduction in a fuel pump permanent magnet motor.

Nowadays, it is more and more difficult to design electro-technique devices without having a look at thermal stress. In more and more applications (more electric vehicles, more electric aircrafts, …) designers need to reduce weight, cost, increase efficiency, and keep the same security factor. One possibility is to increase current for the same device, needing to check how to draw away the heat. This is why the classical approximations need to be cross checked with complementary analysis. These new tools have to be rapid and accurate in order to run parametric and even optimization analysis. There is also a need for fast model in order to check robustness versus driving cycles. The goal in this article is to review rapidly the different methods available, depending on the accuracy required and the solving speed. The method includes equivalent thermal circuits, Finite elements methods and CFD analysis.

Since approximately 40% of grid losses are dissipated from power transformers, there is now a great need to analyse these important components of the electrical network. Altair Flux 2D / 3D plays a key role in those investigations.

The use of CAE software tools as part of the design process for mechanical systems in the automotive industry is now commonplace. This paper highlights the use of Altair HyperWorks to assess and then optimize the performance of a McLaren Automotive front suspension system. The tools MotionView and MotionSolve are used to build the model and then carry out initial assessments of kinematics and compliance characteristics. Altair HyperStudy is then used to optimize the position of the geometric hard points and compliant bush rates in order to meet desired suspension targets. The application of this technology to front suspension design enables McLaren Automotive to dramatically reduce development time.

Automotive radars are becoming standard equipment on vehicles. Their purpose is to adjust the distance between vehicles and/or alert the driver when dangerous situations arise. Several antenna architectures are used to cover the different safety functions in complex bumper/car chassis environment where the side effects become more and more significant on the radar performances. Hence, automotive radar integration process becomes a very important topic. Weak radar integration will generate gain loss, high side lobes levels and angular errors. Those degradations will impact the radar range, the main radar axis (BSE) and the radar detection quality (resolution, ambiguity, discrimination).

Development tools and methods, such as simulation, are increasingly important to face and address the pressure of innovation. As an example, for successful new design methods and to show how simulation tools are used, Altair developed a virtual demonstrator based on a cobot application. This complex machine interacts with a human operator as the ultimate smart manufacturing equipment - to show how challenges in modern product design can be overcome.

When applied to engineering, Machine Learning can be a powerful tool to aid in a range of applications, from faster finite-element (FE) model building to optimizing manufacturing processes and obtaining more accurate results from physics-based simulations. Although incorporating this collection of technology is relatively new in the field of engineering, Altair has made leaps forward in this space to provide users with the tools they need to make a difference.

When developing mobile machines, manufacturer focus is twofold: 1) Increasing a machine’s productivity and operator comfort 2) Improving its energy efficiency. To achieve these objectives, it is crucial to have an optimized system-of-systems and seamless interaction between subsystems. But how can manufacturers design components from varied disciplines like mechanics, electronics, and hydraulics to create a holistic overall system having optimal performance? The answer is digital transformation.