Algorithms for Geometric Optimization and Enrichment in Industrialized Building Construction

The burgeoning use of industrialized building construction, coupled with advances in digital technologies, is unlocking new opportunities to improve the status quo of construction projects being over-budget, delayed and having undesirable quality. Yet there are still several objective barriers that need to be overcome in order to fully realize the full potential of these innovations. Analysis of literature and examples from industry reveal the following notable barriers: (1) geometric optimization methods need to be developed for the stricter dimensional requirements in industrialized construction, (2) methods are needed to preserve model semantics during the process of generating an updated as-built model, (3) semantic enrichment methods are required for the end-of-life stage of industrialized buildings, and (4) there is a need to develop pragmatic approaches for algorithms to ensure they achieve required computational efficiency. The common thread across these examples is the need for developing algorithms to optimize and enrich geometric models. To date, a comprehensive approach paired with pragmatic solutions remains elusive. This research fills this gap by presenting a new approach for algorithm development along with pragmatic implementations for the industrialized building construction sector. Computational algorithms are effective for driving the design, analysis, and optimization of geometric models. As such, this thesis develops new computational algorithms for design, fabrication and assembly, onsite construction, and end-of-life stages of industrialized buildings. A common theme throughout this work is the development and comparison of varied algorithmic approaches (i.e., exact vs. approximate solutions) to see which is optimal for a given process. This is implemented in the following ways. First, a probabilistic method is used to simulate the accumulation of dimensional tolerances in order to optimize geometric models during design. Second, a series of exact and approximate algorithms are used to optimize the topology of 2D panelized assemblies to minimize material use during fabrication and assembly. Third, a new approach to automatically update geometric models is developed whereby initial model semantics are preserved during the process of generating an as-built model. Finally, a series of algorithms are developed to semantically enrich geometric models to enable industrialized buildings to be disassembled and reused. The developments made in this research form a rational and pragmatic approach to addressing the existing challenges faced in industrialized building construction. Such developments are shown not only to be effective in improving the status quo in the industry (i.e., improving cost, reducing project duration, and improving quality), but also for facilitating continuous innovation in construction. By way of assessing the potential impact of this work, the proposed algorithms can reduce rework risk during fabrication and assembly (65% rework reduction in the case study for the new tolerance simulation algorithm), reduce waste during manufacturing (11% waste reduction in the case study for the new panel unfolding and nesting algorithms), improve accuracy and automation of as-built model generation (model error reduction from 50.4 mm to 5.7 mm in the case study for the new parametric BIM updating algorithms), reduce lifecycle cost for adapting industrialized buildings (15% reduction in capital costs in the computational building configurator) and reducing lifecycle impacts for reusing structural systems from industrialized buildings (between 54% to 95% reduction in average lifecycle impacts for the approach illustrated in Appendix B). From a computational standpoint, the novelty of the algorithms developed in this research can be described as follows. Complex geometric processes can be codified solely on the innate properties of geometry – that is, by parameterizing geometry and using methods such as combinatorial optimization, topology can be optimized and semantics can be automatically enriched for building assemblies. Employing the use of functional discretization (whereby continuous variable domains are converted into discrete variable domains) is shown to be highly effective for complex geometric optimization approaches. Finally, the algorithms encapsulate and balance the benefits posed by both parametric and non-parametric schemas, resulting in the ability to achieve both high representational accuracy and semantically rich information (which has previously not been achieved or demonstrated). In summary, this thesis makes several key improvements to industrialized building construction. One of the key findings is that rather than pre-emptively determining the best suited algorithm for a given process or problem, it is often more pragmatic to derive both an exact and approximate solution and then decide which is optimal to use for a given process. Generally, most tasks related to optimizing or enriching geometric models is best solved using approximate methods. To this end, this research presents a series of key techniques that can be followed to improve the temporal performance of algorithms. The new approach for developing computational algorithms and the pragmatic demonstrations for geometric optimization and enrichment are expected to bring the industry forward and solve many of the current barriers it faces

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

Business analytics in industry 4.0: a systematic review

Recently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.The work of P. Cortez was supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions

Applications of aerospace technology to petroleum exploration. Volume 2: Appendices

Participants in the investigation of problem areas in oil exploration are listed and the data acquisition methods used to determine categories to be studied are described. Specific aerospace techniques applicable to the tasks identified are explained and their costs evaluated

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

Mining Technologies Innovative Development

The present book covers the main challenges, important for future prospects of subsoils extraction as a public effective and profitable business, as well as technologically advanced industry. In the near future, the mining industry must overcome the problems of structural changes in raw materials demand and raise the productivity up to the level of high-tech industries to maintain the profits. This means the formation of a comprehensive and integral response to such challenges as the need for innovative modernization of mining equipment and an increase in its reliability, the widespread introduction of Industry 4.0 technologies in the activities of mining enterprises, the transition to "green mining" and the improvement of labor safety and avoidance of man-made accidents. The answer to these challenges is impossible without involving a wide range of scientific community in the publication of research results and exchange of views and ideas. To solve the problem, this book combines the works of researchers from the world's leading centers of mining science on the development of mining machines and mechanical systems, surface and underground geotechnology, mineral processing, digital systems in mining, mine ventilation and labor protection, and geo-ecology. A special place among them is given to post-mining technologies research

Employing Additive Manufacturing for Fusion High Heat Flux Structures

The commercial realisation of nuclear fusion power will require advanced engineering solutions including high heat flux components with higher performance, greater reliability, and longer lifetimes. Additive manufacturing (AM) provides opportunities to produce components with previously unachievable geometries in new and hard-to-manufacture materials. This project introduces the state of the art of fusion high heat flux components and AM and then focuses on applying laser powder bed fusion to high temperature divertor designs. Much of the work was carried out in parallel to the EU FP7 AMAZE project (Additive Manufacturing Aiming towards Zero waste and Efficient production of high-tech metal products). A review of material selection for divertor applications is carried out with an emphasis on the cooled substructure. A parallel, strengths-based approach is undertaken concluding in a series of SWOT (strengths, weaknesses, opportunities, threats) analyses rather than a traditional linear down-selection. Material properties including strength, ductility, thermal expansion, and thermal conductivity are graphically presented as well as derived figures of merit for thermal stress and thermal mismatch with tungsten armour. Radiation damage and compatibility with operational and manufacturing environments are considered and historical summaries of availability and cost are given. By emphasising high temperature operation and acknowledging the inevitability of some nuclear activation beyond the usual 100 year limit, refractory metals and their alloys present themselves as promising candidates, particularly those based on vanadium, tantalum, and molybdenum. A shortage of data for these materials is highlighted, particularly under fusion neutron irradiation, as well as the need for greater understanding of corrosion under relevant conditions. Two novel divertor cooling schemes are then presented and evaluated via concept-level tile-type geometries. The first is a design with multiple small pipes fed from the rear of the component via an in-built manifold and the second employs an enclosed pin-fin array drawing inspiration from the electronics industry. Both highlight features made feasible only by employing AM and use tantalum as the structural material to demonstrate the effect of high-temperature operation on performance. 1D analytical calculations and simple finite element modelling with 150◦C and 600◦C coolant and up to 10 MWm−2 heat flux loading demonstrate improved heat transfer coefficients and more uniform temperature distributions. Performance improvement over conventional designs is likely to be marginal without significant further design optimisation, but the up to 80% reduction in material use compared with conventional concepts, higher thermal efficiency, and opportunity to reduce or relocate pipe joints are highlighted as more significant advantages. Work to develop laser powder bed fusion of tungsten, molybdenum, and tantalum is then presented. First, a summary of context and recent related work is given. A through-lifecycle approach to component development is detailed with the aim of giving an insight into critical issues related to supply chain, process development, material testing, and component build trials. Basic characterisation of size, morphology, and flowability of a selection of powders is used to demonstrate the high variability of current supply. This is followed by determination of first-order build parameters and energy density required for consolidation. Persistent cracking is found, particularly in tungsten and molybdenum, and causes including oxidation and residual stress are posited with suggestions for possible approaches to mitigating these. The results of material testing of small samples are given, including dilatometry, laser flash, and small punch. Small sample numbers and high variability prevent definitive conclusions from being drawn, but trends towards increased brittleness and decreased thermal conductivity are shown and there are indications that the extreme thermal conditions during processing produce β and ω phases of tantalum. Finally a description of a new facility is given, HIVE (Heating by Induction to Verify Extremes), as well as the results of comparative high heat flux testing of two simple copper components - one produced by electron beam melting (EBM) and the other conventionally manufactured. HIVE can apply a constant 10 MWm−2 to a 30 mm x 30 mm test-piece in vacuum which can be cooled using a 200◦C cooling water supply. Thermocouples, thermography, and water calorimetry provide instrumentation. This facility acts as a strategic and previously unavailable intermediate concept validation step between analytical modelling and plasma-surface interaction testing or in-situ qualification. The results presented suggest that convective heat transfer is enhanced by the rough surface of the AM copper part, but that the component’s lower thermal conductivity through the AM copper and across the brazed joint compared to the conventional results in a higher bulk temperature for the same input power indicating a lower overall heat flux handing capability. The project concludes with a summary of key findings and suggestions for future work

The 1st Advanced Manufacturing Student Conference (AMSC21) Chemnitz, Germany 15–16 July 2021

The Advanced Manufacturing Student Conference (AMSC) represents an educational format designed to foster the acquisition and application of skills related to Research Methods in Engineering Sciences. Participating students are required to write and submit a conference paper and are given the opportunity to present their findings at the conference. The AMSC provides a tremendous opportunity for participants to practice critical skills associated with scientific publication. Conference Proceedings of the conference will benefit readers by providing updates on critical topics and recent progress in the advanced manufacturing engineering and technologies and, at the same time, will aid the transfer of valuable knowledge to the next generation of academics and practitioners. *** The first AMSC Conference Proceeding (AMSC21) addressed the following topics: Advances in “classical” Manufacturing Technologies, Technology and Application of Additive Manufacturing, Digitalization of Industrial Production (Industry 4.0), Advances in the field of Cyber-Physical Systems, Virtual and Augmented Reality Technologies throughout the entire product Life Cycle, Human-machine-environment interaction and Management and life cycle assessment.:- Advances in “classical” Manufacturing Technologies - Technology and Application of Additive Manufacturing - Digitalization of Industrial Production (Industry 4.0) - Advances in the field of Cyber-Physical Systems - Virtual and Augmented Reality Technologies throughout the entire product Life Cycle - Human-machine-environment interaction - Management and life cycle assessmen