Deep learning methods applied to digital elevation models: state of the art

Deep Learning (DL) has a wide variety of applications in various thematic domains, including spatial information. Although with limitations, it is also starting to be considered in operations related to Digital Elevation Models (DEMs). This study aims to review the methods of DL applied in the field of altimetric spatial information in general, and DEMs in particular. Void Filling (VF), Super-Resolution (SR), landform classification and hydrography extraction are just some of the operations where traditional methods are being replaced by DL methods. Our review concludes that although these methods have great potential, there are aspects that need to be improved. More appropriate terrain information or algorithm parameterisation are some of the challenges that this methodology still needs to face.Functional Quality of Digital Elevation Models in Engineering’ of the State Agency Research of SpainPID2019-106195RB- I00/AEI/10.13039/50110001103

Data-driven geometric modelling methods for digital twinning: manufacturing, geospatial and medical applications

In recent years there has been an explosion of interest in digital twinning in many disciplines, including the manufacturing, geospatial, and medical domains. A core topic of importance in modelling digital twins, is reconstruction of geometric models from raw data. Despite the diversity of requirements in the vast space of digital twin applications, methods for geometric reconstruction can often be transferred between disciplines with only minor modifications. In this paper we present some recent results related to how advances in machine learning over the last decade can be used for data-driven geometric reconstruction in the medical, geospatial and manufacturing domains

New posibilities of using processing and modern methods of the “generative art” graphics in architecture

Sketches are an irreplaceable method of recording thoughts and of correcting the design process. They are a means of discovering and examining reality which supports the development of imagination. Sketching is an essential element in the education of architects and in the double-loop learning process. Sketching opens two channels of communication: conversation and spatial-visual activity. Both traditional and new digital tools have important roles in the development of future architects. The primacy of computer design over freehand drawing in an architect’s work can lead to the disappearance of a designer’s individuality and creativity, limiting the role of his personality at the earliest stage of the design process

An Architectural Implementation of Topology Optimization Guided Discrete Structures with Customized Geometric Constraints

This thesis explores the use of Topology Optimization (abbreviated to TO) in architectural design by implementing a Bidirectional Evolutionary Structural Optimization(abbreviated to BESO) type TO script as a guide to create a composition of discrete members with complex geometries. TO is an efficient tool for generating an optimal spatial arrangement of structural members along a load path. In the field of computational design, TO has been employed for form-generation of a range of assembled structures that employ discrete units, as well as continuum structures that employ unified and continuous materials. The most advanced current architectural implementations for continuum structures appear in the design of connections, and for discrete structures within space truss designs. Yet, the use of TO in atypical discrete frame structures with complex geometries remain relatively undeveloped in contemporary practice. This thesis contributes a case study where TO is implemented at two key scales: at the component level, geometrically constrained discrete components are assembled using TO, at the macro level, these components are arranged over a TO-designed body. A review of literature from computational design and structural engineering fields, discussing current TO implementations, as well as presenting case studies, is included. The demonstration within the thesis presents a contemporary architectural design process by using existing Karamba BESO code components within a Grasshopper parametric script. Fine-grained components employed within the facade system are combined using TO to produce a cellular lattice architectonic assembly that refers to traditional Korean ornamental pattern found near the site. This demonstration is evaluated structurally and aesthetically. Analyses of comparative structural models with varying configurations are used to demonstrate the structural efficiency of the proposed design. For the aesthetic evaluation, a series of drawings are included to demonstrate what type of spatial qualities the customized lattice structure would look like. The goal of this thesis is to demonstrate architectural and structural qualities resulting from a hybrid exercise where a TO process is applied to geometrically constrained discrete structures. The approach in this thesis provides compromises where structural efficiency and aesthetics are both reasonably achieved, and may lead to novel designs. Future work could be to create a new TO algorithm that can automate this process for increased structural efficiency