Generative Design Methodology Research Articles

Machine learning-aided generative design methodology for a Martian regolith habitation shell

This study presents a novel design methodology to automate the development process of a regolith habitation shell for a crewed mission on Mars. The integration of generative design, simulation tools, and data science methodologies allows for a systematic and comprehensive iterative design process, which facilitates the development of dual-habitation shells that can resist harsh conditions on Mars.The study establishes a methodology consisting of four fundamental sections. Initially, the environmental conditions on the surface of Mars are assessed and quantified as structural loads, so that the generative design tools effectively transform these stresses into design parameters that might be used in finite element modeling (FEM). Next, this study employs human factors derived from existing literature as input for Social Network Analysis (SNA) and the Label Propagation Algorithm (LPA) to address important design inquiries concerning functional zoning, layout configuration, geometry generation, and habitability variables. These inquiries aim to inform the decision-making process regarding autonomous typology design. Furthermore, the use of space syntax, physics simulations, and Voronoi algorithms improves the accuracy of the habitation planning process by generating floor designs and habitable volumes that align with the distinctive requirements and preferences of individuals. Lastly, the regolith habitation shell is constructed using structural simulation techniques that incorporate Mars' environmental pressures as design considerations. By employing Karamba3D and numerical finite element modeling (FEM) techniques, the structural performance of the regolith habitation shell under the environmental conditions on Mars is simulated.Consequently, this study introduces three distinct habitation shell designs that were developed and exposed to structural simulations to evaluate the effects of environmental stresses on Mars. The study explores the conjunction between generative design, data science, and structural simulations by employing a systematic and comprehensive design process. Its objective is to provide insights into the impact of environmental pressures on habitation shells and improve our understanding of design outcomes for future exploration on Mars.

Simplified Methods for Generative Design That Combine Evaluation Techniques for Automated Conceptual Building Design

Smart design and construction have emerged as pivotal forces in the construction industry. Numerous studies have been conducted in the realm of design optimization, using artificial intelligence data-driven approaches and optimization theories. This increase in research has sparked interest in generative design, a process that automatically generates algorithm-based design alternatives, thereby reducing human effort and time by a significant margin. The objective of this study was to explore the potential of generative design to boost productivity within architectural practices and reduce redundant and unnecessary tasks for an aging construction workforce. Specifically, it illustrates the process of selecting superior alternatives by generating various three-dimensional layouts, using a generative design methodology. This occurs during the creation of a building layout concept with subsequent partial evaluations. The methodology of this study was mainly divided into four stages: objective setting, design algorithm development, the establishment of evaluation methodology, and the comparison of the results’ values. The findings of this study confirmed that the design algorithm and evaluation methodology form a single loop, generating a multitude of design alternatives that satisfy the algorithm designer’s evaluation criteria.

Generative design of space frames for additive manufacturing technology

A generative design methodology is presented that solves for minimum volume and compliance space-frame systems, with consideration of stress and buckling constraints. The solution space is explored using formal topology optimisation routines. A parameterisation method converts voxelised topology optimisation solutions into skeletonised connectivity representations. An inequality constrained gradient descent optimisation method optimises and defines cross-sectional geometry. This enables fast and automatic solution generation, providing designers with sets of high-performing problem solutions. Skeleton representations provide an inexpensive modelling tool for parallel analysis of physical problems difficult to model using topology optimisation. Geometry is represented using traditional engineering cross-sections with well understood behaviour. This improves certainty in the performance of solutions, simplifying certification processes. The generative design of a structural aerospace bracket for additive manufacture has been used as a case study within this research. A design of experiments produced 360 topology optimisation results, altering input variables and discretisation resolution to identify their effect on solution outcomes and the performance of parameterisation. The proposed method was found to robustly generate high-performing solutions utilising low-resolution topology optimisation. Additionally, 6 high-performing topologies were identified, providing designers with a set of solutions to select from. Limitations on the parameterisation process were identified, with topology optimisation solutions with volume fractions above 0.2 not parameterising successfully, and simulations with a resolution of 5 mm element size and below generating low performing skeletonised topologies.

A 32–40 GHz 7-bit Bi-Directional Phase Shifter With 0.36 dB/1.6° RMS Magnitude/Phase Errors for Phased Array Systems

This paper presents a digitally programmable bi-directional 7-bit passive phase shifter in a 65 nm CMOS technology. The core of this passive vector-synthesized phase shifter is a hybrid quadrature generator (HQG), an interstage matching network, and a passive vector modulator (PVM). This work proposes a high coupling-factor-based quadrature generator design methodology and demonstrates it with a compact vertical transformer. The interstage matching network between HQG and PVM is proposed to release the bandwidth bottleneck and achieve a 34% fractional frequency bandwidth. Two 6-bit X-type attenuators in the I and Q path form a high-resolution 12-bit controlling word. In 32–40 GHz, this 7-bit 360° phase shifter achieves a measured 2.8° step with 0.45-1.6° RMS phase error and 0.2-0.36 dB RMS magnitude error. With the broadband technique, its 3-dB bandwidth reaches 30.2-42.7 GHz with a 2.8° RMS phase error. Its in-band 1-dB compression point is 10.2 dBm. With the proposed compact HQG and PVM, this mm-wave passive phase shifter only occupies <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$220\times 630\,\,\mu \text{m}^{2}$ </tex-math></inline-formula> and has no power consumption.

Single Red Blood Cell Hydrodynamic Traps via the Generative Design.

This paper describes a generative design methodology for a micro hydrodynamic single-RBC (red blood cell) trap for applications in microfluidics-based single-cell analysis. One key challenge in single-cell microfluidic traps is to achieve desired through-slit flowrates to trap cells under implicit constraints. In this work, the cell-trapping design with validation from experimental data has been developed by the generative design methodology with an evolutionary algorithm. L-shaped trapping slits have been generated iteratively for the optimal geometries to trap living-cells suspended in flow channels. Without using the generative design, the slits have low flow velocities incapable of trapping single cells. After a search with 30,000 solutions, the optimized geometry was found to increase the through-slit velocities by 49%. Fabricated and experimentally tested prototypes have achieved 4 out of 4 trapping efficiency of RBCs. This evolutionary algorithm and trapping design can be applied to cells of various sizes.

Generative design and analysis of a double-wishbone suspension assembly: a methodology for developing constraint oriented solutions for optimum material distribution

Purpose The purpose of this paper is to implement the generative design as an optimization technique to achieve a reasonable trade-off between weight and reliability for the control arm plate of a double-wishbone suspension assembly of a Formula Student race car. Design/methodology/approach The generative design methodology is applied to develop a low-weight design alternative to a standard control arm plate design. A static stress simulation and a fatigue life study are developed to assess the response of the plate against the loading criteria and to ensure that the plate sustains the theoretically determined number of loading cycles. Findings The approach implemented provides a justifiable outcome for a weight-factor of safety trade-off. In addition to optimal material distribution, the generative design methodology provides several design outcomes, for different materials and fabrication techniques. This enables the selection of the best possible outcome for several structural requirements. Research limitations/implications This technique can be used for applications with pre-defined constraints, such as packaging and loading, usually observed in load-bearing components developed in the automotive and aerospace sectors of the manufacturing industry. Practical implications Using this technique can provide an alternative design solution to long periods spent in the design phase, because of its ability to generate several possible outcomes in just a fraction of time. Originality/value The proposed research provides a means of developing optimized designs and provides techniques in which the design developed and chosen can be structurally analyzed.

Generative Urban Design Concepts and Methods: A Research Review

Generative design is a fast-growing design approach that is both important and pervasive. This approach has developed after the great digital revolution in the last few decades, especially during the first two decades of the third millennium. Taking advantage of the computational capabilities of modern computers, generative design offers designers the ability to test multiple and complex alternatives by automating design processes using algorithms. The automation makes it possible to manage an ever increasing number of variables and parameters that are difficult to manage manually. This paper presents an attempt to classify the approaches of the generative urban design methodologies applied in the field today, with the aim of highlighting the gaps in the current practices. By reviewing the previous available studies that dealt with the idea of generative urban design, we find that they can be classified according to the approach they adopt in four categories: the first is the approach of deforming or distorting a basic shape proposed by the designer, the second is the approach stemming from the simulation of real urban growth, while the third is the approach of dealing with the urban form on the scale of building blocks without being concerned with the spatial network, and finally the fourth is the approach that emerges from analysing a realistic spatial structure and then proposing modifications based on the results of the analysis. From this review, the paper proposes a new approach resulting from the analysis of a realistic spatial structure to build a generic model that can be the starting point of a synthetic process to be integrated into a generative design methodology.

The creation of a neural network\xa0based capability profile to enable generative design and the manufacture of functional FDM parts

In order to manufacture functional parts using filament deposition modelling (FDM), an understanding of the machine’s capabilities is necessary. Eliciting this understanding poses a significant challenge due to a lack of knowledge relating manufacturing process parameters to mechanical properties of the manufactured part. Prior work has proposed that this could be overcome through the creation of capability profiles for FDM machines. However, such an approach has yet to be implemented and incorporated into the overall design process. Correspondingly, the aim of this paper is two-fold and includes the creation of a comprehensive capability profile for FDM and the implementation of the profile and evaluation of its utility within a generative design methodology. To provide the foundations for the capability profile, this paper first reports an experimental testing programme to characterise the influence of five manufacturing parameters on a part’s ultimate tensile strength (UTS) and tensile modulus (E). This characterisation is used to train an artificial neural network (ANN). This ANN forms the basis of a capability profile that is shown to be able to represent the mechanical properties with RMSEP of 1.95 MPa for UTS and 0.82 GPa for E. To validate the capability profile, it is incorporated into a generative design methodology enabling its application to the design and manufacture of functional parts. The resulting methodology is used to create two load bearing components where it is shown to be able to generate parts with satisfactory performance in only a couple of iterations. The novelty of the reported work lies in demonstrating the practical application of capability profiles in the FDM design process and how, when combined with generative approaches, they can make effective design decisions in place of the user.

Evolutive 3D Modeling: A Proposal for a New Generative Design Methodology

At present, traditional 3D modeling programs consist of a set of tools that reflect conventional means of mechanical manufacturing and have limitations in relation with the current manufacturing capacities. On the other hand, organic and morphing 3D modeling programs are designed to transform a model from one known shape to another also known shape. Generative design helps the designers to detach themselves during the design process and can provide them with completely unexpected geometrical solutions. In this paper, starting from 3D morphing techniques and genetic algorithms, a new methodology of product shape definition is developed, capable of imitating processes that occur in nature and aimed at creating new and different product designs. This methodology enables to overcome the limitations imposed by design fixation and allows better exploitation of the great possibilities granted by the new manufacturing techniques, most notably additive manufacturing. The initial process of research and information gathering gives this work a solid basis to develop the new methodology. The results of this initial process are briefly resumed in this paper in order to explain the main motivation for developing this work. The workflow of this methodology is presented as a theoretical process, since its implementation has not been, at least for the moment, put into practice. Before presenting the conclusion for this proposal, several examples have been formulated in order to help the reader to catch the point of the entire process.

A Case Study on Generative Building Skin Forming by Employing Building Information Modelling (BIM) Tools

Purpose This study aims to produce generative curtain wall geometries based on predetermined parameters such as storey information, shadow zones, preliminary building unit cost, frequency, etc. in a BIM platform for the preliminary design of a future project in Basmane and understand its novel outcomes and implications.Design/Methodology/Approach The methodology is construed over four successive phases, namely: the built environment modeling, analyses for a solid understanding of the study area, determination of the generative design criteria, and finally design solutions. In the initial phase, the case-study building in Basmane with the surrounding environment was digitally modeled for the following analyses. Several programs apart from BIM have been utilized for the daylight zones and wind simulations. The daylight areas affecting the surface of the studied building were marked schematically per the simulation data. Subsequently, the area of the curtain wall, material type, preliminary building unit cost (assembly/labor and material cost), the height of storey, the density of elements, and fixed shading devices parameters were tested via optimization thru generative design methodology and provide potential design solutions by utilization of BIM tools.Findings The findings of this study could be boiled down to a single comprehensive objective of generating outputs of assorted design solutions thru a generative design approach. When the output data set is visualized via parallel coordinate graphs, it could be well articulated that the classification of rule-based relationships and the criteria interrelations were based on the designer's decisions.Research Limitations/Implications This study was examined on a case basis by an experimental approach. It shall be considered that the curtain wall construction encompasses diverse materials, connection details, and construction techniques that affect the final cost thus this research was conducted at the preliminary design stage and might not reflect actual costs.Social/Practical Implications Albeit the technical aspect of the curtain walls is not included in this case study, it helps generative design culture by demonstrating the extent of the opportunities it offers to designers in the preliminary design stage.Originality/Value This study is a show-case of a preliminary design for an actual building stock in the vicinity of Basmane focusing on the building envelope design process with multiple parameters and should be regarded as an opportunity to understand how innovative solutions alike are put forward for the use of designers.

French Biological Philosophy of Technology as a Candidate Perspective Furthering Design Methodology

AbstractA first exploration is conducted to what the French biological philosophy of technology perspective has to offer to the field of design methodology. If this French perspective is combined with contemporary speculative pragmatism a generative design methodology emerges offering novelty in what is sensed as important in a design situation. Within this perspective, drawing upon the late French philosopher Gilbert Simondon, technical objects have their own mode of existence and their own trajectory of development apart from human intention.Designers working with such a generative design methodology follow the constitutive value of openness and attune to the regulative value of techno-aesthetic judgments. By way of a 'vignette+', a paradigmatic example from a real case, a more encompassing argument is made towards design situations where a sophisticated machine is 'inserted' into a domestic setting.The example taken is the use of an artificial kidney machine in a domestic setting and the development of a novel machine with a design team. Four aspects were sensed as important in the unfolding design situation and directions for further research are discussed.

An integrated energy performance-driven generative design methodology to foster modular lightweight steel framed dwellings in hot climates

This paper presents a study on the application of lightweight steel framed (LSF) construction systems in hot climate. A generative design method created 6010 houses, with random geometry and random roof and exterior wall types with different insulation levels, and EnergyPlus was used to evaluate the energy consumption for air-conditioning of each building. The main goals were to determine which geometric variables correlate with the energy performance, and to provide some guidelines to foster efficient LSF buildings in hot climates. By correlating six geometry-based indexes with the energy consumption for each construction element type group, it was verified that roofs do not show significant correlation, while exterior walls presented weak to moderate positive correlation with the building volume, very weak to weak negative correlation with the relative compactness, no correlation with the shape coefficient, moderate to strong negative correlation with the window-to-floor, window-to-wall, and window-to-exterior surface ratios. The results also show that buildings with larger windows and greater level of insulation have better energy performance. No significant difference of energy performance was found between different LSF construction systems with equivalent thermal resistance.

제너러티브 디자인 방법론을 활용한 참여적 패션디자인의 사례 연구

This study examined the characteristics of generative design methodology, and it selected and analyzed 11 sites that provide design development services using generative methodology, INPUT data were classified into design form factor based on the choices of each and the variable form associated with each participant’s movement. In designing the algorithms, designers set the method and range of participation according to the characteristics of the design, and linked them with design components. This provided the study with a discriminative design process. This resulted in a type with morphological characteristics and a type that emphasized epidermal formability. The generative design methodology has value as an alternative process in the field of fashion where the utilization of digital technology is becoming universal based on contingency and variability. The results of this study can be used as basic data for the study of personalized design through the extension of methodology of digital–based fashion design and generative methodology.

Case Studies on Application of Generative Design Methodology in Art and Design

Case Studies on Application of Generative Design Methodology in Art and Design