Methodology For Behavioral Synthesis-based Algorithm-level Design Space Exploration: DCT Case Study

2005 ◽  
Author(s):  
M. Potkonjak ◽  
Kyosun Kim ◽  
R. Karri
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Behavioral Synthesis ◽  
Level Design ◽  
Algorithm Level

Preliminary Design and Performance of Counter Rotating Turbines for Open Rotors: Part II — 0-D Methodology and Case Study for a 160 PAX Aircraft

2016 ◽  
Author(s):  
Pablo Bellocq ◽  
Inaki Garmendia ◽  
Jordane Legrand ◽  
Vishal Sethi
Keyword(s):  
Design Methodology ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Preliminary Design ◽  
Regulatory Constraints ◽  
Trade Offs ◽  
And Performance ◽  
The Impact

Direct Drive Open Rotors (DDORs) have the potential to significantly reduce fuel consumption and emissions relative to conventional turbofans. However, this engine architecture presents many design and operational challenges both at engine and aircraft level. At preliminary design stages, a broad design space exploration is required to identify potential optimum design regions and to understand the main trade offs of this novel engine architecture. These assessments may also aid the development process when compromises need to be performed as a consequence of design, operational or regulatory constraints. Design space exploration assessments are done with 0-D or 1-D models for computational purposes. These simplified 0-D and 1-D models have to capture the impact of the independent variation of the main design and control variables of the engine. Historically, it appears that for preliminary design studies of DDORs, Counter Rotating Turbines (CRTs) have been modelled as conventional turbines and therefore it was not possible to assess the impact of the variation of the number of stages (Nb) of the CRT and rotational speed of the propellers. Additionally, no preliminary design methodology for CRTs was found in the public domain. Part I of this two-part publication proposes a 1-D preliminary design methodology for DDOR CRTs which allows an independent definition of both parts of the CRT. A method for calculating the off-design performance of a known CRT design is also described. In Part II, a 0-D design point efficiency calculation for CRTs is proposed and verified with the 1-D methods. The 1-D and 0-D CRT models were used in an engine control and design space exploration case study of a DDOR with a 4.26m diameter an 10% clipped propeller for a 160 PAX aircraft. For this application: • the design and performance of a 20 stage CRT rotating at 860 rpm (both drums) obtained with the 1-D methods is presented. • differently from geared open rotors, negligible cruise fuel savings can be achieved by an advanced propeller control. • for rotational speeds between 750 and 880 rpm (relatively low speeds for reduced noise), 22 and 20 stages CRTs are required. • engine weight can be kept constant for different design rotational speeds by using the minimum required Nb. • for any target engine weight, TOC and cruise SFC are reduced by reducing the rotational speeds and increasing Nb (also favourable for reducing CRP noise). However additional CRT stages increase engine drag, mechanical complexity and cost.

Many-Attribute Decision Making Using Iterative Attribute Subsets

2016 ◽  
Author(s):  
Laura Ziegler ◽  
Kemper Lewis
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Decision Problems ◽  
Trade Off ◽  
Current Design ◽  
Multi Attribute Decision Making

A unique set of cognitive and computational challenges arise in large-scale decision making, in relation to trade-off processing and design space exploration. While several multi-attribute decision making methods exist in the current design literature, many are insufficient or not fully explored for many-attribute decision problems of six or more attributes. To address this scaling in complexity, the methodology presented in this paper strategically elicits preferences over iterative attribute subsets while leveraging principles of the Hypothetical Equivalents and Inequivalents Method (HEIM). A case study demonstrates the effectiveness of the approach in the construction of a systematic representation of preferences and the convergence to a single ‘best’ alternative.

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