The high-speed train market in recently industrialized countries is one of the most hotly contested engineered-product markets in the world, with even the smallest advantage important in gaining a competitive edge. In particular, fuel consumption is a critical factor in design, sales and maintenance of these vehicles. In this project, a manufacturer of high-speed rail vehicles needed to maximize efficiency, reduce emissions and decrease design time.
Seeking a more efficient engineering approach that would let it maximize the number of designs that could be tested within the project schedule, the manufacturer selected Sculptor from Optimal Solutions Software. By specifying key design parameters, the software allows hundreds of designs to be generated in a matter of minutes—a radical improvement over the company’s previous process, in which this phase of the project took months. Continue reading →
Optimizing turbofan designs is challenging because of the need to deal with both aerodynamic and structural performance. While designing a fan with high performance and efficiency is important, strength and reliability of the structure are also critical. Further, integrating parametric CAD, CFD and stress analysis is not a trivial task and usually takes extensive effort.
In this project SmartDO and ANSYS were utilized together to optimize a turbofan. The technical services team at SmartDO’s developer, FEA-Opt Technology, helped the customer build a parametric model with ANSYS DesignModeler, construct the CFX and mechanical analysis block, and integrate SmartDO with ANSYS Workbench. SmartDO was able to increase the mass flow of the fan by almost 14% while slightly reducing the maximum stress under aerodynamic and structural loading. These results showed promising possibilities for further design development. Continue reading →
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 →
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 →
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 →
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 →
Last week’s post surveyed the trend of integration between design exploration and optimization software and systems modeling and 0D/1D simulation tools. This week’s case study shows how the two technologies were used together in development of a new hybrid electric vehicle (HEV) to achieve the competing goals of improving fuel efficiency and meeting emissions targets.
Executive summary—A leading automotive OEM used Noesis Solutions’ Optimus design optimization and process integration software in conjunction with Maplesoft’s MapleSim multi-domain systems modeling and simulation tool in developing the HEV’s combined electric and combustion propulsion system. Optimus was used to automate the traditional guess-and-correct simulation-based design process, its optimization algorithms efficiently directing the system simulation campaign to identify the best HEV configurations. Using Optimus’ capabilities for design of experiments (DOE), response surface modeling (RSM) and multi-objective optimization (MOO), engineers improved fuel efficiency by 21% and traveling performance (legal emissions compliance) by 15%. With MapleSim providing HEV modeling and Optimus controlling simulation workflow execution, the design optimization was accomplished in just two weeks. Continue reading →
Discussions of how to simulate early in product development fixate too often on FEA, overlooking the power of systems modeling and 0D/1D simulation for studying, exploring and optimizing designs at the beginning of projects, when product geometry is seldom available for 3D CAE but engineering decision-making can have its greatest impact and leverage on project success. Continue reading →
For engineering organizations, where does innovation come from?
When we put that question to EPC firms serving the process and power industries, the most frequent answer was “our projects” and the people working directly in project execution. Forty percent of respondents said their firms’ most important source of innovation is the discovery and application of new technologies and approaches by discipline leads, engineers and managers seeking solutions to pressures and exigencies in a specific project or program.
In second place was “anywhere and everywhere”—27% said innovation at base is a function of their organizations’ culture, and thus can arise from any area in the firm.
In third place was the IT department, named as the top source of innovation by 17% of respondents. While not quite the picture painted in some CIO-oriented publications, these findings align with what our research and others’ suggests is an evolving role for the CIO’s office: to provide enabling infrastructure in support of digital technology initiatives that, more and more, originate from the project execution centers of engineering, manufacturing and construction enterprises. Continue reading →
The foundational business value of design space exploration is the ability it confers on engineering teams and organizations to gain more complete, higher-fidelity visibility into product performance earlier in project schedules than was possible or practicable with older technologies and approaches. In essence, it does this by enabling more efficient, effective and revealing application of simulation, analysis and digital prototyping assets—tools, expertise, methods, work processes—to the perennial business drivers for any organization’s investments in those assets:
To become more competitive by gaining increased capability to explore, create and innovate.
To apply that capability to create better performing products.
To improve product quality and reliability—yielding expanded opportunity and customer appeal at the same time as lowered warranty expenses, liability exposure and lifecycle costs.
To control or, better yet, reduce product development schedules and budgets by supplanting costly, time-intensive physical testing with digital prototyping.