Design variable analysis and generation for performance-based parametric modeling in architecture

2018 ◽  
Vol 17 (1) ◽  
pp. 36-52 ◽  
Author(s):  
Nathan C Brown ◽  
Caitlin T Mueller
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Parametric Design ◽  
Computational Design ◽  
Parametric Modeling ◽  
Parametric Models ◽  
Qualitative And Quantitative ◽  
Analysis Techniques ◽  
Design Variables ◽  
Variable Analysis

Many architectural designers recognize the potential of parametric models as a worthwhile approach to performance-driven design. A variety of performance simulations are now possible within computational design environments, and the framework of design space exploration allows users to generate and navigate various possibilities while considering both qualitative and quantitative feedback. At the same time, it can be difficult to formulate a parametric design space in a way that leads to compelling solutions and does not limit flexibility. This article proposes and tests the extension of machine learning and data analysis techniques to early problem setup in order to interrogate, modify, relate, transform, and automatically generate design variables for architectural investigations. Through analysis of two case studies involving structure and daylight, this article demonstrates initial workflows for determining variable importance, finding overall control sliders that relate directly to performance and automatically generating meaningful variables for specific typologies.

Enabling parametric design space exploration by non-designers

2020 ◽  
Vol 34 (2) ◽  
pp. 160-175 ◽  
Author(s):  
Eduardo Castro e Costa ◽  
Joaquim Jorge ◽  
Aaron D. Knochel ◽  
José Pinto Duarte
Keyword(s):  
User Interface ◽  
Mass Customization ◽  
Design Space Exploration ◽  
Design Space ◽  
Parametric Design ◽  
Space Exploration ◽  
End Users ◽  
Parametric Models ◽  
Direct Manipulation ◽  
Barycentric Interpolation

AbstractIn mass customization, software configurators enable novice end-users to design customized products and services according to their needs and preferences. However, traditional configurators hardly provide an engaging experience while avoiding the burden of choice. We propose a Design Participation Model to facilitate navigating the design space, based on two modules. Modeler enables designers to create customizable designs as parametric models, and Navigator subsequently permits novice end-users to explore these designs. While most parametric designs support direct manipulation of low-level features, we propose interpolation features to give customers more flexibility. In this paper, we focus on the implementation of such interpolation features into Navigator and its user interface. To assess our approach, we designed and performed user experiments to test and compare Modeler and Navigator, thus providing insights for further developments of our approach. Our results suggest that barycentric interpolation between qualitative parameters provides a more easily understandable interface that empowers novice customers to explore the design space expeditiously.

Specifications for Building a Parametric Model in Digital Architectural Designs

2018 ◽  
Vol 26 (9) ◽  
pp. 179-219
Author(s):  
Aynoor Farik Alafandy ◽  
Dhuha Al-Kazzaz
Keyword(s):  
Design Process ◽  
Parametric Design ◽  
Research Problem ◽  
Development Stage ◽  
Parametric Model ◽  
Parametric Modeling ◽  
Digital Design ◽  
Parametric Models ◽  
Design Variables ◽  
Definition Of

The construction of parametric model is an important stage in the digital design process in general and in the parametric design process in particular. The parametric model allows the designer to make changes and reshape the geometry without erasing and redrawing. It also helps to explore design alternatives as it provides a level of flexibility to be continuously evaluated, revised and updated when adding or altering different components within the same parametric model structure. The research problem has been identified, as there is no clear definition of the specifications of constructing a parametric model in the contemporary digital architectural designs. Therefore, the objective of the research is to put forward a theoretical framework that defines clearly the specifications of building a parametric model. The framework describes the specifications using the following issues: the timing of constructing the parametric model, the knowledge employed in the construction of parametric model, the methods of constructing and revising a parametric model, The place where a parametric model is applied, and finally the number of parametric models within a design. The framework has been applied to six international projects adopting a parametric design approach. The results showed that employing parametric modeling mostly starts at the development stage of design and continues in the detailing and manufacturing stages, the adoption of ill-defined knowledge, the definition of design variables in terms of quantitative and qualitative characteristics, and using one parametric model shared among multiple design disciplines.

scholarly journals Design space exploration for flexibility assessment and decision making support in integrated industrial building design

2021 ◽  
Author(s):  
Julia Reisinger ◽  
Maximilian Knoll ◽  
Iva Kovacic
Keyword(s):  
Decision Making ◽  
Design Process ◽  
Design Space Exploration ◽  
Design Space ◽  
Parametric Design ◽  
Space Exploration ◽  
Building Design ◽  
Assessment Tools ◽  
Industrial Building ◽  
Industrial Buildings

AbstractIndustrial buildings play a major role in sustainable development, producing and expending a significant amount of resources, energy and waste. Due to product individualization and accelerating technological advances in manufacturing, industrial buildings strive for highly flexible building structures to accommodate constantly evolving production processes. However, common sustainability assessment tools do not respect flexibility metrics and manufacturing and building design processes run sequentially, neglecting discipline-specific interaction, leading to inflexible solutions. In integrated industrial building design (IIBD), incorporating manufacturing and building disciplines simultaneously, design teams are faced with the choice of multiple conflicting criteria and complex design decisions, opening up a huge design space. To address these issues, this paper presents a parametric design process for efficient design space exploration in IIBD. A state-of-the-art survey and multiple case study are conducted to define four novel flexibility metrics and to develop a unified design space, respecting both building and manufacturing requirements. Based on these results, a parametric design process for automated structural optimization and quantitative flexibility assessment is developed, guiding the decision-making process towards increased sustainability. The proposed framework is tested on a pilot-project of a food and hygiene production, evaluating the design space representation and validating the flexibility metrics. Results confirmed the efficiency of the process that an evolutionary multi-objective optimization algorithm can be implemented in future research to enable multidisciplinary design optimization for flexible industrial building solutions.

CAD-integrated Parametric Design Cycle for Structural Membranes

2019 ◽  
Vol 60 (4) ◽  
pp. 266-272 ◽  
Author(s):  
A. Goldbach ◽  
K.-U. Bletzinger
Keyword(s):  
Design Space ◽  
Parametric Design ◽  
Pattern Generation ◽  
Parametric Models ◽  
Membrane Structures ◽  
B Splines ◽  
Design Cycle ◽  
Structural Membranes ◽  
Cutting Pattern ◽  
Topology Information

The design cycle of membrane structures consists of three interactive and highly non-linear disciplines. Formfinding is performed in order to find a geometry that allows the prestressed structure to carry loads through tension only. Once a formfound geometry is set, structural analysis needs to assess the structure's safety and usability. The most challenging step is the cutting pattern generation, which aims at finding the planar pieces which can be elevated to build spatial membrane structures with a minimum deviation from the desired shape and prestress state.<br/> Isogeometric B-Rep Analysis (IBRA) allows the designer to perform analyses on the original CAD model without leaving the CAD environment. High quality is ensured for the geometry and the mechanical approximation by using Non-Uniform Rational B-Splines (NURBS). Additionally, the topology information of multipatches can be transferred to the analysis in order to enrich the design space. Trimmed and coupled surfaces can thus be included in the analysis. Parametric models allow the designer to examine a large variety of geometrical and mechanical entities with one model.<br/> The advantages of the CAD-integration with IBRA for the highly interactive design of structural membranes are shown in this contribution.

Design Space Exploration in Sparse, Mixed Continuous/Discrete Spaces via Synthetically Enhanced Classification

2018 ◽  
Author(s):  
Tyler Wiest ◽  
Carolyn Conner Seepersad ◽  
Michael Haberman
Keyword(s):  
High Performance ◽  
Design Space Exploration ◽  
Design Space ◽  
Regions Of Interest ◽  
High Performing ◽  
Bayesian Network Classifiers ◽  
Design Variables ◽  
Complex Engineering ◽  
Low Performance ◽  
Discrete Spaces

Exploration of a design space is the first step in identifying sets of high-performing solutions to complex engineering problems. For this purpose, Bayesian network classifiers (BNCs) have been shown to be effective for mapping regions of interest in the design space, even when those regions of interest exhibit complex topologies. However, identifying sets of desirable solutions can be difficult with a BNC when attempting to map a space where high-performance designs are spread sparsely among a disproportionately large number of low-performance designs, resulting in an imbalanced classifier. In this paper, a method is presented that utilizes probabilities of class membership for known training points, combined with interpolation between those points, to generate synthetic high-performance points in a design space. By adding synthetic design points into the BNC training set, a designer can rebalance an imbalanced classifier and improve classification accuracy throughout the space. For demonstration, this approach is applied to an acoustics metamaterial design problem with a sparse design space characterized by a combination of discrete and continuous design variables.

Whither design space?

2006 ◽  
Vol 20 (2) ◽  
pp. 63-82 ◽  
Author(s):  
ROBERT F. WOODBURY ◽  
ANDREW L. BURROW
Keyword(s):  
Network Structure ◽  
Design Space Exploration ◽  
Design Research ◽  
Design Space ◽  
Space Exploration ◽  
Computational Design ◽  
Exploration Process ◽  
Computational Structures

Design space exploration is a long-standing focus in computational design research. Its three main threads are accounts of designer action, development of strategies for amplification of designer action in exploration, and discovery of computational structures to support exploration. Chief among such structures is the design space, which is the network structure of related designs that are visited in an exploration process. There is relatively little research on design spaces to date. This paper sketches a partial account of the structure of both design spaces and research to develop them. It focuses largely on the implications of designers acting as explorers.

A Method for Visualizing the Relations Between Grammar Rules, Performance Objectives and Search Space Exploration in Grammar-Based Computational Design Synthesis

2015 ◽  
Author(s):  
Corinna Königseder ◽  
Kristina Shea
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Computational Design ◽  
Search Space ◽  
Synthesis Process ◽  
Design Synthesis ◽  
Novel Approach ◽  
Grammar Rules ◽  
Computational Design Synthesis

Design grammars have been successfully applied in numerous engineering disciplines, e.g. in electrical engineering, architecture and mechanical engineering. A successful application of design grammars in Computational Design Synthesis (CDS) requires a) a meaningful representation of designs and the design task at hand, b) a careful formulation of grammar rules to synthesize new designs, c) problem specific design evaluations, and d) the selection of an appropriate algorithm to guide the synthesis process. Managing these different aspects of CDS requires not only a detailed understanding of each individual part, but also of the interdependencies between them. In this paper, a new method is presented to analyze the exploration of design spaces in CDS. The method analyzes the designs generated during the synthesis process and visualizes how the design space is explored with respect to a) design characteristics, and b) objectives. The selected algorithm as well as the grammar rules can be analyzed with this approach to support the human designer in successfully understanding and applying a CDS method. The case study demonstrates how the method is used to analyze the synthesis of bicycle frames. Two algorithms are compared for this task. Results demonstrate how the method increases the understanding of the different components in CDS. The presented research can be useful for both novices to CDS to help them gain a deeper understanding of the interplay between grammar rules and guidance of the synthesis process, as well as for experts aiming to further improve their CDS application by improving parameter settings of their search algorithms, or by further refining their design grammar. Additionally, the presented method constitutes a novel approach to interactively visualize design space exploration considering not only designs objectives, but also the characteristics and interdependencies of different designs.

scholarly journals Creating Polytope Representations of Design Spaces for Visual Exploration Using Consistency Techniques

2010 ◽  
Vol 132 (8) ◽  
Author(s):  
Srikanth Devanathan ◽  
Karthik Ramani
Keyword(s):  
Design Process ◽  
Design Space ◽  
Parametric Design ◽  
Three Dimensional ◽  
Visual Exploration ◽  
Support Design ◽  
Design Exploration ◽  
Design Variables ◽  
Finite Set ◽  
Geometry Problem

Understanding the limits of a design is an important aspect of the design process. When mathematical models are constructed to describe a design concept, the limits are typically expressed as constraints involving the variables of that concept. The set of values for the design variables that do not violate constraints constitute the design space of that concept. In this work, we transform a parametric design problem into a geometry problem thereby enabling computational geometry algorithms to support design exploration. A polytope-based representation is presented to geometrically approximate the design space. The design space is represented as a finite set of (at most) three-dimensional (possibly nonconvex) polytopes, i.e., points, intervals, polygons, and polyhedra. The algorithm for constructing the design space is developed by interpreting constraint-consistency algorithms as computational-geometric operations and consequently extending (3,2)-consistency algorithm for polytope representations. A simple example of a fingernail clipper design is used to illustrate the approach.

scholarly journals Performance Driven Design Space Exploration for Multi-Objective Optimization Using Stability in Competition

2021 ◽  
Author(s):  
Summit Sehgal
Keyword(s):  
Real Estate ◽  
Analytical Approach ◽  
Design Space Exploration ◽  
Design Space ◽  
Parametric Design ◽  
Space Exploration ◽  
Systems Development ◽  
Performance Parameters ◽  
Multi Objective Optimization ◽  
Systems Architecture

Multi Parametric Design Space Exploration (DSE) for optimal micro-architecture synthesis is an extremely complex yet crucial stage in embedded systems development. Often it is very time complex to find the best suitable configuration to map the inherently contradictory performance parameters into systems silicon real estate. Owing to its exponentially exploding design space and multi way combinatorial mapping, DSE has proven to be notoriously hard and intractable for VLSI CAD tools. The presented work introduces a highly scalable and generalized analytical approach to identify the best configuration of systems architecture while maintaining prime accuracy resolution. This DSE approach coupled with

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