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.

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.

Function Ordering Within Morphological Charts: An Experimental Study

2018 ◽  
Author(s):  
Anant Chawla ◽  
Joshua D. Summers
Keyword(s):  
Experimental Study ◽  
Design Space Exploration ◽  
Engineering Students ◽  
Design Space ◽  
Space Exploration ◽  
Integrated Design ◽  
Input Function ◽  
Output Function ◽  
Design Concepts ◽  
Morphological Chart

Morphological charts are widely recognized tools in engineering design applications and research. However, a literature gap exists in instructing the representation and exploration of morphological charts. In this paper, an experiment is conducted to understand how morphological charts are explored and what impact functional arrangement has on it. The experiment consisted of two problem statements, each with five different functional arrangements: 1) Most to Least Important Function, 2) Least to Most Important Function, 3) Input to Output Function, 4) Output to Input Function, and 5) Random. Sixty-seven junior mechanical engineering students were provided a prepopulated morphological chart and asked to generate integrated design concepts. The generated concepts were analyzed to determine how frequently a given means is selected, how much of the chart is explored, what is the sequence of exploration, and finally the influence of function ordering on them. Experimental results indicate a tendency to focus more on the initial columns of the chart irrespective of functional order. Moreover, the Most-to-Least-Important functional order results in higher chances and uniformity of design space exploration.

scholarly journals Execution time - area tradeoff in gausing residual load decoder: Integrated exploration of chaining based schedule and allocation in HLS for hardware accelerators

2014 ◽  
Vol 27 (2) ◽  
pp. 235-249 ◽  
Author(s):  
Anirban Sengupta ◽  
Reza Sedaghat ◽  
Vipul Mishra
Keyword(s):  
Execution Time ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Integrated Design ◽  
Hardware Accelerators ◽  
Average Improvement ◽  
Genetic Algorithm Approach ◽  
High Level ◽  
The Cost

Design space exploration is an indispensable segment of High Level Synthesis (HLS) design of hardware accelerators. This paper presents a novel technique for Area-Execution time tradeoff using residual load decoding heuristics in genetic algorithms (GA) for integrated design space exploration (DSE) of scheduling and allocation. This approach is also able to resolve issues encountered during DSE of data paths for hardware accelerators, such as accuracy of the solution found, as well as the total exploration time during the process. The integrated solution found by the proposed approach satisfies the user specified constraints of hardware area and total execution time (not just latency), while at the same time offers a twofold unified solution of chaining based schedule and allocation. The cost function proposed in the genetic algorithm approach takes into account the functional units, multiplexers and demultiplexers needed during implementation. The proposed exploration system (ExpSys) was tested on a large number of benchmarks drawn from the literature for assessment of its efficiency. Results indicate an average improvement in Quality of Results (QoR) greater than 26% when compared to a recent well known GA based exploration method.

How Function Ordering Within Morphological Charts Influence Exploration1

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
Anant Chawla ◽  
Joshua D. Summers
Keyword(s):  
Engineering Design ◽  
Mechanical Engineering ◽  
Design Space Exploration ◽  
Engineering Students ◽  
Design Space ◽  
Space Exploration ◽  
Integrated Design ◽  
Input Function ◽  
Output Function ◽  
Design Concepts

Although morphological charts are widely taught used tools in engineering design, little formal guidance is provided regarding their representation and exploration. Thus, an experiment was conducted to elucidate the influence of functional ordering on the exploration of morphological charts. Two design prompts were used, each with five different functional arrangements: (1) most-to-least important function, (2) least-to-most important function, (3) input-to-output function, (4) output-to-input function, and (5) Random. Sixty-seven junior mechanical engineering students were asked to generate integrated design concepts from prepopulated morphological charts for each design prompt. The concepts were analyzed to determine the frequency with which a given means was selected, how much of the chart was explored, the sequence of exploration, and the influence of function ordering. Results indicated a tendency to focus upon the initial columns of the chart irrespective of functional order. The most-to-least-important functional order resulted in higher chances and a uniformity of design space exploration.

scholarly journals Implementation of integrated design space exploration of scheduling, allocation and binding in high level synthesis using multi structure genetic algorithm

2021 ◽  
Author(s):  
Michael Gebremariam
Keyword(s):  
Genetic Algorithm ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Integrated Design ◽  
High Level Synthesis ◽  
C Language ◽  
Low Level ◽  
Wide Range ◽  
High Level

The objective of this project is to develop a software tool which assists in comparison of a work known as "M-GenESys: Multi Structure Genetic Algorithm based Design Space Exploration System for Integrated Scheduling, Allocation and Binding in High Level Synthesis" with another well established GA approach known as "A Generic Algorithm for the Design Space Exploration of Data paths During High-Level Synthesis". Two sets of software are developed based on both approaches using Microsoft Visual 2005 C# language. The C# language is an object-oriented language that is aimed at enabling programmers to quickly develop a wide range of applications on the Microsoft .NET platform. The goal of C# and the .NET platform is to shorten development time by freeing the developer from worrying about several low level plumbing issues such as memory equipment, type safety issues, building low level libraries, array bound checking, etc., thus allowing developers to actually spend their time and energy working on the application and business logic.

scholarly journals Implementation of integrated design space exploration of scheduling, allocation and binding in high level synthesis using multi structure genetic algorithm

2021 ◽  
Author(s):  
Michael Gebremariam
Keyword(s):  
Genetic Algorithm ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Integrated Design ◽  
High Level Synthesis ◽  
C Language ◽  
Low Level ◽  
Wide Range ◽  
High Level

The objective of this project is to develop a software tool which assists in comparison of a work known as "M-GenESys: Multi Structure Genetic Algorithm based Design Space Exploration System for Integrated Scheduling, Allocation and Binding in High Level Synthesis" with another well established GA approach known as "A Generic Algorithm for the Design Space Exploration of Data paths During High-Level Synthesis". Two sets of software are developed based on both approaches using Microsoft Visual 2005 C# language. The C# language is an object-oriented language that is aimed at enabling programmers to quickly develop a wide range of applications on the Microsoft .NET platform. The goal of C# and the .NET platform is to shorten development time by freeing the developer from worrying about several low level plumbing issues such as memory equipment, type safety issues, building low level libraries, array bound checking, etc., thus allowing developers to actually spend their time and energy working on the application and business logic.

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