Computational Design Synthesis: A Model-Based Approach for Complex Systems

2012 ◽  
Author(s):  
Nicolas Albarello ◽  
Jean-Baptiste Welcomme
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Design Rules ◽  
System Architectures ◽  
Architecture Model ◽  
Model Based ◽  
Design Alternatives ◽  
Systems Architectures ◽  
The Impact

The design of systems architectures often involve a combinatorial design-space made of technological and architectural choices. A complete or large exploration of this design space requires the use of a method to generate and evaluate design alternatives. This paper proposes an innovative approach for the design-space exploration of systems architectures. The SAMOA (System Architecture Model-based OptimizAtion) tool associated to the method is also introduced. The method permits to create a large number of various system architectures combining a set of possible components to address given system functions. The method relies on models that are used to represent the problem and the solutions and to evaluate architecture performances. An algorithm first synthesizes design alternatives (a physical architecture associated to a functional allocation) based on the functional architecture of the system, the system interfaces, a library of available components and user-defined design rules. Chains of components are sequentially added to an initially empty architecture until all functions are fulfilled. The design rules permit to guarantee the viability and validity of the chains of components and, consequently, of the generated architectures. The design space exploration is then performed in a smart way through the use of an evolutionary algorithm, the evolution mechanisms of which are specific to system architecting. Evaluation modules permit to assess the performances of alternatives based on the structure of the architecture model and the data embedded in the component models. These performances are used to select the best generated architectures considering constraints and quality metrics. This selection is based on the Pareto-dominance-based NSGA-II algorithm or, alternatively, on an interactive preference-based algorithm. Iterating over this evolution-evaluation-selection process permits to increase the quality of solutions and, thus, to highlight the regions of interest of the design-space which can be used as a base for further manual investigations. By using this method, the system designers have a larger confidence in the optimality of the adopted architecture than using a classical derivative approach as many more solutions are evaluated. Also, the method permits to quickly evaluate the trade-offs between the different considered criteria. Finally, the method can also be used to evaluate the impact of a technology on the system performances not only by a substituting a technology by another but also by adapting the architecture of the system.

scholarly journals Core-Level Modeling and Frequency Prediction for DSP Applications on FPGAs

2015 ◽  
Vol 2015 ◽  
pp. 1-20
Author(s):  
Gongyu Wang ◽  
Greg Stitt ◽  
Herman Lam ◽  
Alan George
Keyword(s):  
High Performance ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Core Level ◽  
Prediction Methods ◽  
Clock Frequency ◽  
Worst Case ◽  
Model Based ◽  
Dsp Applications

Field-programmable gate arrays (FPGAs) provide a promising technology that can improve performance of many high-performance computing and embedded applications. However, unlike software design tools, the relatively immature state of FPGA tools significantly limits productivity and consequently prevents widespread adoption of the technology. For example, the lengthy design-translate-execute (DTE) process often must be iterated to meet the application requirements. Previous works have enabled model-based, design-space exploration to reduce DTE iterations but are limited by a lack of accurate model-based prediction of key design parameters, the most important of which is clock frequency. In this paper, we present a core-level modeling and design (CMD) methodology that enables modeling of FPGA applications at an abstract level and yet produces accurate predictions of parameters such as clock frequency, resource utilization (i.e., area), and latency. We evaluate CMD’s prediction methods using several high-performance DSP applications on various families of FPGAs and show an average clock-frequency prediction error of 3.6%, with a worst-case error of 20.4%, compared to the best of existing high-level prediction methods, 13.9% average error with 48.2% worst-case error. We also demonstrate how such prediction enables accurate design-space exploration without coding in a hardware-description language (HDL), significantly reducing the total design time.

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.

scholarly journals An integrated design methodology for the deployment of constellations of small satellites

2019 ◽  
Vol 123 (1266) ◽  
pp. 1193-1215 ◽  
Author(s):  
N. H. Crisp ◽  
K. L. Smith ◽  
P. M. Hollingsworth
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
A Priori ◽  
Integrated Design ◽  
Alternative Methods ◽  
System Architectures ◽  
Small Satellites ◽  
Deployment Time ◽  
Feasible Solutions

ABSTRACTA growing interest in constellations of small satellites has recently emerged due to the increasing capability of these platforms and their reduced time and cost of development. However, in the absence of dedicated launch services for these systems, alternative methods for the deployment of these constellations must be considered which can take advantage of the availability of secondary-payload launch opportunities. Furthermore, a means of exploring the effects and tradeoffs in corresponding system architectures is required. This paper presents a methodology to integrate the deployment of constellations of small satellites into the wider design process for these systems. Using a method of design-space exploration, enhanced understanding of the tradespace is supported , whilst identification of system designs for development is enabled by the application of an optimisation process. To demonstrate the method, a simplified analysis framework and a multiobjective genetic algorithm are implemented for three mission case-studies with differing application. The first two cases, modelled on existing constellations, indicate the benefits of design-space exploration, and possible savings which could be made in cost, system mass, or deployment time. The third case, based on a proposed Earth observation nanosatellite constellation, focuses on deployment following launch using a secondary-payload opportunity and demonstrates the breadth of feasible solutions which may not be considered if only point-designs are generated by a priori analysis. These results indicate that the presented method can support the development of future constellations of small satellites by improving the knowledge of different deployment strategies available during the early design phases and through enhanced exploration and identification of promising design alternatives.

Combining Interactive Exploration and Optimization for Assembly Design

1998 ◽  
Vol 120 (1) ◽  
pp. 24-31 ◽  
Author(s):  
G. J. Kim ◽  
S. Szykman
Keyword(s):  
Simulated Annealing ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Explicit Representation ◽  
Top Down ◽  
Design Constraints ◽  
Overall Design ◽  
Assembly Design ◽  
Design Alternatives

This paper presents an integrated framework for conceptual assembly design. Because the complexity of assembly design leads to extremely large design spaces, adequate support of design space exploration is a key issue that must be addressed. CAMF allows the designer to manage the overall design process and explore the design space through explicit representation of design stages and their relationships (history), assembly design constraints, and rationale. The designer is free to use both bottom-up or top-down approaches to explore different assembly configurations. Exploration of the design space is further enabled by incorporating a simulated annealing-based refinement tool that allows the designer to rapidly complete partial designs, refine complete designs, and generate multiple design alternatives.

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