Multidisciplinary optimization of ground vehicle dynamics

Pratt & Miller Engineering evolved from a small business focused on designing and building race cars into a full-service engineering and low-volume manufacturing company serving a global customer base in the defense, automotive and powersports industries. After evaluating multiple optimization tools, Pratt & Miller selected Red Cedar Technology’s HEEDS MDO and its SHERPA algorithm as the only optimization technology that could solve its highly constrained models.

Pratt & Miller’s typical automotive optimization studies are set up as nearly overconstrained problems. The firm usually needs to minimize or maximize only one or two objectives, but often needs to satisfy up to 50 constraints. Prior to using HEEDS MDO, Pratt & Miller would plan for four to 12 man-weeks to find a solution to its typical problem. This was in addition to the time required to generate the baseline model using a combination of engineering intelligence and DOE methods. Using HEEDS MDO and parallel processing, this time is typically reduced to one to two weeks.

In the past, Pratt & Miller structured simulation investigations primarily around DOE studies performed using MSC Adams/Insight. However, an assumption of the model order had to be set before the simulations were started, and the response surface did not always conform to that order, resulting in a poor fit. When designing new vehicles from the ground up, the parameter variations can be very large, and even a cubic model does not fit very well to the actual response surface. HEEDS MDO removes this problem by operating on the actual response values and determining how the simulation should progress, explains Pratt & Miller, and it is very easy to exclude failed simulations from the optimization process in HEEDS.

Pratt & Miller’s other problem with DOE simulations was the large number of evaluations. The firm often ended up doing 21,000 evaluations for a cubic model and 1500 evaluations for a quadratic model. “Using HEEDS MDO with SHERPA, we can find a good solution in 400 evaluations, and often less,” says CAE Manager Jesper Slättengren. “HEEDS allows us to study the progress of the optimization while it is running. We can stop the simulation at any point when the results are close enough to the desired target. We can also extend the run beyond the initial number of runs without any loss of optimization progress.”

Finally, Pratt & Miller struggled to manage multiple simulations. In a typical scenario, it would conduct six to 14 different simulations for each model, and the optimal design was dependent on all of the simulations. This required six to 14 different DOEs with the same factors and different responses. It also required a polynomial optimization method that could work over the combined response surfaces from all the DOEs. Incorporating HEEDS into the design process has completely eliminated this problem, the company reports.

Optimizing chassis components for military vehicles

pratt1
Source: Pratt & Miller Engineering

HEEDS MDO is used daily at Pratt & Miller to optimize chassis component parameters to meet specified military requirements for heavy vehicles. These include spring and damper parameters, anti-roll bar dimensions, and suspension geometry points. Among the constraints are understeer gradient, ride-quality measures, and spring and damper balance. Typical problems include up to 50 factors and as many constraints. Using MSC Adams with HEEDS MDO parallel processing, Pratt & Miller is able to produce reliable results overnight.

pratt2
Source: Pratt & Miller Engineering

The development process for military vehicles differs significantly from that of passenger and commercial vehicles, including different ride and handling requirements that must be satisfied. For example, the ride specification includes passes over half-rounds at various heights during which no occupant can be exposed to more than 2.5G vertical acceleration. For stochastic roads, the absorbed power must be less than 6W. For each of these events, a threshold and an objective speed are specified. Handling requirements include a range for the understeer gradient and a maximum roll gradient. Besides these explicit specifications, a good ride and handling balance is desired.

pratt3
Source: Pratt & Miller Engineering

With tougher requirements each year, it gets progressively harder to tune the vehicle suspension. With decreased development times and longer lead times for components such as springs and complex damper systems, the need for multi-event or multidisciplinary optimization is increasing. By coupling MSC Adams and Adams/Car with HEEDS MDO to perform the multidisciplinary optimizations, Pratt & Miller designed, developed and built a new vehicle design in 12 weeks, with the suspension element taking less than six weeks.

pratt4
Source: Pratt & Miller Engineering

“We believe in HEEDS and have seen tremendous benefit as we’ve applied it on several internal programs with great success,” says Pratt & Miller’s Mark Palmieri. “HEEDS integrates well with our internal tools, as well as with the MSC products we represent and use. Because of our confidence in this technology, we have committed to reselling it and working closely with Red Cedar Technology to share it with both our customers and prospects.”

MBSE—Platform to accelerate adoption of design space exploration?

These issues will be the focus of my Analyst Briefing session at COFES 2015, Scottsdale, Arizona, April 16-19. Hope to see you there!

Design space exploration, design optimization and process integration technologies are creating value for manufacturers around the world, delivering results that weren’t practical or even possible with older tools and methods. Yet few of these vendors have matched the robust double-digit growth of mainstream CAE in recent years. Can the move by engineering organizations toward model-based systems engineering (MBSE) serve as a platform to accelerate adoption of design space exploration? Continue reading

Design space exploration: Institutionalizing the practice

EVENT NOTICE—If you’re in the Detroit area, join Noesis Solutions’ free seminar April 9 on Innovations in Process Integration & Design Optimization. You’ll hear three perspectives on how this technology can help you streamline your simulation processes and identify benchmark product designs in less time, including a presentation by me on Innovative Uses of Optimization for Engineering Design Problems. Event and registration information here.

  ⦁  ⦁

Achieving institutional adoption of design space exploration, design optimization and process integration is a crucial goal for engineering organizations working to establish these as strategic competencies, not just tactical. Too often implemented at only the department or workgroup level, the technologies and their attendant work processes need to be recognized and given backing as enterprise capabilities to have their greatest impact on engineering’s ability to advance corporate strategic objectives. [See also Design space exploration: Justifying the investment.] Continue reading

Ford adopts ESTECO’s SOMO to institutionalize enterprise MDO

Ford Motor Company adopted ESTECO’s SOMO as a tool to enable what it terms an enterprise multidisciplinary design optimization (EMDO) system, announced Dr. Yan Fu, technical leader of business strategy and engineering optimization at Ford. SOMO is an enterprise collaboration and distributed execution framework developed by ESTECO and customized to meet Ford’s engineering processes and IT requirements.

Ford’s move affirms two key points we have long observed:

  • MDO is a strategic capability for engineering organizations, not just tactical.
  • To have strategic impact, MDO needs to be institutionalized at the enterprise level, not implemented as just a departmental or workgroup capability.

Continue reading

Geometry optimization of a static helix mixer

datadvance_1
Source: DATADVANCE

Static helix mixers are widely used in the chemical industry for in-line blending of liquids under laminar flow conditions. Geometric modification of their elements can yield significant improvements in mixing performance. In a project for Sulzer Mixpac, a leading provider of mixer technologies, DATADVANCE determined the optimal geometric parameters for a helix mixer that yield minimal pressure drop together with best mixing performance. Continue reading

Geometry and beyond: Optimization taxonomy and methods

The power of numerical optimization in engineering design is its ability to rationally and rapidly search through alternatives for the best possible design(s). Parameters in a design that can be varied to search for a “best” design are design variables. Given these, design can be structured as the process of finding the minimum or maximum of some attribute, termed the objective function. For a design to be acceptable, it also must satisfy certain requirements, or design constraints. Optimization is the process of automatically changing the design variables to identify the minimum or maximum of the objective function while satisfying all the required design constraints. [This survey of design optimization methods is in complement to our recent review of design exploration techniques. See also Design exploration vs. design optimization.] Continue reading

Onshape technology and pricing demolish CAD accessibility barriers

Onshape Mac and iPhone
Source: Onshape

Onshape went public with avidly anticipated details of its full-cloud 3D CAD system that lets everyone on a design team work together using any web browser, phone or tablet, and has data management and collaboration built in at its core. While this groundbreaking technological approach has generated high excitement in the run-up to today’s unveiling, Onshape’s pricing model is an equally disruptive component of its strategy to make professional-grade CAD radically more accessible than ever before. Continue reading

Optimizing capex/opex tradeoffs in built-asset engineering

Most often applied to manufactured product development, design exploration and optimization also hold potential to improve—some would say, bring long-overdue transformation to—the engineering of constructed assets: commercial and residential buildings, discrete manufacturing facilities, process and power plants, offshore platforms. While some EPC firms serving process/power and offshore markets have made substantial progress with these tools and methods, the A/E industry still has far to go in tapping their considerable potential to improve building design and manufacturing facility engineering. With the mounting economic, environmental and public-policy pressures to deliver higher-performing built assets, we expect to see DOE, MDO, Pareto optimization and robustness/reliability optimization increasingly utilized by firms engaged in architecture, engineering, construction and asset operation. Continue reading

Latin hypercubes and all that: How DOE works

Making design exploration software speak the language of engineers and not mathematicians has been a focus of development since the industry’s inception. Even so, our recent case study was typical in referencing the Latin hypercube design-of-experiments method, the radial basis function for generating a response surface model, the non-dominated sorting evolutionary algorithm to generate a Pareto front—all prompting this look into some of the quantitative methods that drive design space exploration. Continue reading

Design space exploration industry timeline

A timeline of company formations, product launches and M&A activity among design exploration and optimization software vendors maps the pace and direction of the industry’s development.

Ora_DSE_timeline
Click to view Continue reading