Simulation-based optimal design of heavy trucks by model-based decomposition: an extensive analytical target cascading case study

2004 ◽  
Vol 11 (3/4) ◽  
pp. 403 ◽  
Author(s):  
M. Kokkolaras ◽  
L. Louca ◽  
G. Delagrammatikas ◽  
N. Michelena ◽  
Z. Filipi ◽  
...  
Keyword(s):  
Optimal Design ◽  
Analytical Target Cascading ◽  
Model Based ◽  
Heavy Trucks ◽  
Simulation Based ◽  
Target Cascading

scholarly journals Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems

2014 ◽  
Author(s):  
Bo Yang Yu ◽  
Tomonori Honda ◽  
Syed Zubair ◽  
Mostafa H. Sharqawy ◽  
Maria C. Yang
Keyword(s):  
Optimal Design ◽  
Complex Systems ◽  
Design Optimization ◽  
Reverse Osmosis ◽  
Large Scale ◽  
Analytical Target Cascading ◽  
Total Water ◽  
Target Cascading ◽  
Desalination Plants ◽  
Functional Components

Large-scale desalination plants are complex systems with many inter-disciplinary interactions and different levels of sub-system hierarchy. Advanced complex systems design tools have been shown to have a positive impact on design in aerospace and automotive, but have generally not been used in the design of water systems. This work presents a multi-disciplinary design optimization approach to desalination system design to minimize the total water production cost of a 30,000m3/day capacity reverse osmosis plant situated in the Middle East, with a focus on comparing monolithic with distributed optimization architectures. A hierarchical multi-disciplinary model is constructed to capture the entire system’s functional components and subsystem interactions. Three different multi-disciplinary design optimization (MDO) architectures are then compared to find the optimal plant design that minimizes total water cost. The architectures include the monolithic architecture multidisciplinary feasible (MDF), individual disciplinary feasible (IDF) and the distributed architecture analytical target cascading (ATC). The results demonstrate that an MDF architecture was the most efficient for finding the optimal design, while a distributed MDO approach such as analytical target cascading is also a suitable approach for optimal design of desalination plants, but optimization performance may depend on initial conditions.

Vehicle Handling Dynamics Optimization Based in Passive Suspension Settings in Target Cascading Framework

2014 ◽  
Author(s):  
Juan C. Blanco ◽  
Luis E. Muñoz
Keyword(s):  
Optimal Design ◽  
Optimization Problem ◽  
Suspension System ◽  
Dynamics Simulation ◽  
Design Stage ◽  
Partial Geometry ◽  
Embodiment Design ◽  
Design Variables ◽  
Target Cascading

The vehicle optimal design is a multi-objective multi-domain optimization problem. Each design aspect must be analyzed by taking into account the interactions present with other design aspects. Given the size and complexity of the problem, the application of global optimization methodologies is not suitable; hierarchical problem decomposition is beneficial for the problem analysis. This paper studies the handling dynamics optimization problem as a sub-problem of the vehicle optimal design. This sub-problem is an important part of the overall vehicle design decomposition. It is proposed that the embodiment design stage can be performed in an optimal viewpoint with the application of the analytical target cascading (ATC) optimization strategy. It is also proposed that the design variables should have sufficient physical significance, but also give the overall design enough design degrees of freedom. In this way, other optimization sub-problems can be managed with a reduced variable redundancy and sub-problem couplings. Given that the ATC strategy is an objective-driven methodology, it is proposed that the objectives of the handling dynamics, which is a sub-problem in the general ATC problem, can be defined from a Pareto optimal set at a higher optimization level. This optimal generation of objectives would lead to an optimal solution as seen at the upper-level hierarchy. The use of a lumped mass handling dynamics model is proposed in order to manage an efficient optimization process based in handling dynamics simulations. This model contains detailed information of the tire properties modeled by the Pacejka tire model, as well as linear characteristics of the suspension system. The performance of this model is verified with a complete multi-body simulation program such as ADAMS/car. The handling optimization problem is presented including the proposed design variables, the handling dynamics simulation model and a case study in which a double wishbone suspension system of an off-road vehicle is analyzed. In the case study, the handling optimization problem is solved by taking into account couplings with the suspension kinematics optimization problem. The solution of this coupled problem leads to the partial geometry definition of the suspension system mechanism.

scholarly journals Optimal design of manure management for intensive swine feeding operation: A modeling method based on analytical target cascading

2021 ◽  
Vol 282 ◽  
pp. 124550
Author(s):  
Jiangong Li ◽  
Xinlei Wang ◽  
Harrison Hyung Min Kim ◽  
Richard S. Gates ◽  
Kaiying Wang
Keyword(s):  
Optimal Design ◽  
Modeling Method ◽  
Manure Management ◽  
Analytical Target Cascading ◽  
Target Cascading

Weights, Norms, and Notation in Analytical Target Cascading

2004 ◽  
Vol 127 (3) ◽  
pp. 499-501 ◽  
Author(s):  
Jeremy J. Michalek ◽  
Panos Y. Papalambros
Keyword(s):  
Systems Design ◽  
Technical Note ◽  
Hierarchical Optimization ◽  
Analytical Target Cascading ◽  
Model Based ◽  
Target Cascading ◽  
Optimization Methodology

This technical note provides clarification, modification, and generalization of the notation used to describe analytical target cascading, a model-based hierarchical optimization methodology for systems design.

Probabilistic Analytical Target Cascading: A Moment Matching Formulation for Multilevel Optimization Under Uncertainty

2005 ◽  
Author(s):  
Huibin Liu ◽  
Wei Chen ◽  
Michael Kokkolaras ◽  
Panos Y. Papalambros ◽  
Harrison M. Kim
Keyword(s):  
Probabilistic Approach ◽  
Optimization Under Uncertainty ◽  
Analytical Target Cascading ◽  
Multilevel Optimization ◽  
Coordination Strategies ◽  
Simulation Based ◽  
Target Cascading ◽  
Design Consistency ◽  
System Design Optimization ◽  
Probabilistic Analytical Target Cascading

Analytical target cascading (ATC) is a methodology for hierarchical multilevel system design optimization. In previous work, the deterministic ATC formulation was extended to account for uncertainties using a probabilistic approach. Random quantities were represented by their expected values, which were required to match among subproblems to ensure design consistency. In this work, the probabilistic formulation is augmented to allow introduction and matching of additional probabilistic characteristics. Applying robust design principles, a particular probabilistic analytic target cascading (PATC) formulation is proposed by matching the first two moments of random quantities. Several implementation issues are addressed, including representation of probabilistic design targets, matching interrelated responses and linking variables under uncertainty, and coordination strategies for multilevel optimization. Analytical and simulation-based optimal design examples are used to illustrate the new PATC formulation. Design consistency is achieved by matching the first two moments of interrelated responses and linking variables. The effectiveness of the approach is demonstrated by comparing PATC results to those obtained using a probabilistic all-in-one (PAIO) formulation.

Analytical Target Setting: An Enterprise Context in Optimal Product Design

2003 ◽  
Author(s):  
Adam B. Cooper ◽  
Panayotis Georgiopoulos ◽  
Hyung Min Kim ◽  
Panos Y. Papalambros
Keyword(s):  
Product Design ◽  
Engineering Design ◽  
Analytical Target Cascading ◽  
Design Decisions ◽  
Target Setting ◽  
Model Based ◽  
Target Cascading ◽  
Optimal Product Design ◽  
High Level ◽  
Made In

Engineering design decisions have more value and lasting impact if they are made in the context of the enterprise that produces the designed product. Setting targets that the designer must meet is often done at a high level within the enterprise, with inadequate consideration of the engineering design embodiment and associated cost. For complex artifacts produced by compartmentalized hierarchical enterprises, the challenge of linking the target setting rationale with the product instantiation is particularly demanding. The previously developed analytical target cascading process addresses the problem of translating supersystem design targets into design targets for all systems in a multilevel hierarchically structured product, so that local targets are consistent with each other and allow top targets to be met as closely as possible. In this article the process of rigorously setting the supersystem targets in an enterprise context is explored as a model-based approach termed “analytical target setting.” The effectiveness of linking analytical target setting and cascading is demonstrated in an automotive truck vehicle example.

scholarly journals Optimal design of commercial vehicle systems using analytical target cascading

2014 ◽  
Vol 50 (6) ◽  
pp. 1103-1114 ◽  
Author(s):  
Namwoo Kang ◽  
Michael Kokkolaras ◽  
Panos Y. Papalambros ◽  
Seungwon Yoo ◽  
Wookjin Na ◽  
...  
Keyword(s):  
Optimal Design ◽  
Commercial Vehicle ◽  
Analytical Target Cascading ◽  
Target Cascading ◽  
Vehicle Systems
Sign in / Sign up

Export Citation Format

Share Document