Improving the Prediction of the Behaviour of Masonry Wall Panels Using Model Updating and Artificial Intelligence Techniques

Out-of-plane laterally loaded masonry wall panels are still much used in modem structures. However due to their anisotropic and highly composite nature, it is extremely difficult to understand their behaviour and to date there is no analytical method that is capable of accurately predicting the response of masonry panels to the applied loadings. This is one of the major obstacles in analysing and designing masonry structures. This research studied a new method that accurately predicts the response of laterally loaded masonry wall panels. In this dissertation, the method of using corrector factors developed by previous researchers was further studied using model updating and artificial intelligence (AI) techniques based on previous experimental results of full scale wall panels tested in the University of Plymouth. A specialised non-linear finite element analysis (FEA) program was used to implement the method developed in this study. The analytical response was compared with other experimental results from different laboratories. Initially, it was found that there was some obvious noise in the experimental load deflection data, which made comparison between FEA and the experimental results very difficult. The research therefore proposed a methodology for minimising the experimental noise based on 3D surface fitting and regression analyses applied to lateral deflection experimental data. The next step was the detailed study of corrector factors using the numerical model updating procedure. Corrector factors were determined for various zones within a masonry panel (the Base Panel) by minimising the discrepancy between the experimental load deflection data and those obtained from non-linear FE analysis. A detailed model updating procedure was studied including the model analysis, the objective function and the constraint function for the genetic algorithm (GA). A uniqueness study to corrector factors was also carried out. The following step was undertaken to analyse general masonry wall panels using the findings of this study. The concept of zone similarities proposed by previous researcher, which was based on the relative distance of each zone from similar boundaries, was used for applying correctors from the base panel to the new panel to be analysed. A modified cellular automata (CA) model was used to match the similar zones between the new panel and the base panel. The generality and robustness of this method was validated using a number of masonry wall panels tested by various organizations. These walls were single leaf masonry wall panels of clay bricks with different boundary types, dimensions, with and without openings. The main finding in this research are that the boundary effects have a major influence on the response of masonry panels subjected to lateral loading, improperly defined boundary conditions in FEA are the main source of error in the past numerical analysis. Using the corrector factors that are able to properly quantify the actual boundary effects and make appropriate revisions, more accurate analysis is achieved and the predicted response of masonry walls match with their experimental results very well

SOLID-SHELL FINITE ELEMENT MODELS FOR EXPLICIT SIMULATIONS OF CRACK PROPAGATION IN THIN STRUCTURES

Crack propagation in thin shell structures due to cutting is conveniently simulated using explicit finite element approaches, in view of the high nonlinearity of the problem. Solidshell elements are usually preferred for the discretization in the presence of complex material behavior and degradation phenomena such as delamination, since they allow for a correct representation of the thickness geometry. However, in solid-shell elements the small thickness leads to a very high maximum eigenfrequency, which imply very small stable time-steps. A new selective mass scaling technique is proposed to increase the time-step size without affecting accuracy. New ”directional” cohesive interface elements are used in conjunction with selective mass scaling to account for the interaction with a sharp blade in cutting processes of thin ductile shells

Biologically-inspired double skin facades for hot climates: a parametric approach for performative design

La Biomimicry è una scienza applicata che studia le forme, i materiali, i sistemi e i processi naturali per individuare soluzioni applicabili anche a problemi umani. Tale scienza trova applicazione in molti campi, quali l’agricoltura, la medicina, l’ingegneria e l’architettura. Grazie ai progressi compiuti nella modellazione parametrica, ad oggi sono disponibili potenti strumenti che, oltre alla simulazione energetica, consentono di esplorare le potenzialità delle soluzioni tratte dal mondo naturale nella progettazione architettonica, superando i limiti della semplice imitazione della forma. Una delle maggiori sfide per gli architetti negli ultimi anni è la riduzione della domanda energetica del costruito. Per i climi caldi, le esigenze di ventilazione e raffrescamento sono pertanto fattori cruciali per migliorarne la prestazione energetica. La tesi di ricerca affronta il problema della progettazione e dell’efficienza energetica dell’involucro edilizio in contesti climatici caldi, quale l’Egitto. A tal fine, è stato definito e applicato un approccio progettuale biomimetico-computazionale, per studiare e analizzare i comportamenti adattivi di termoregolazione di vari organismi naturali. In particolare, il lavoro di ricerca esplora possibili soluzioni architettoniche, ispirate a caratteristiche biologiche, per l’involucro di un edificio per uffici, con l’obiettivo di ridurre la domanda energetica per il raffrescamento. L’involucro dell’edificio è stato modellato parametricamente utilizzando Grasshopper Visual Programming Language per Rhino 3D Modeller, applicando inoltre alcuni algoritmi evolutivi multi-obiettivo per ottimizzare la soluzione architettonica rispetto al duplice obiettivo di diminuire i carichi di raffrescamento e mantenere un buon livello di illuminazione naturale. In tal modo, la riduzione dei carichi di raffreddamento non comporta un incremento dei consumi elettrici per l'illuminazione artificiale. Le prestazioni termiche dell’edificio sono state valutate con il software EnergyPlus. La soluzione architettonica esplorata è una facciata a doppia pelle ispirata a vari principi della natura. Le prestazioni della soluzione proposta sono state confrontate con quelle di un edificio per uffici esistente a Il Cairo. Il modello dell’edificio è stato ricostruito sulla base di planimetrie e specifiche sui materiali presenti; inoltre la disponibilità di dati sui consumi energetici per il raffrescamento dell’edificio ha permesso di valutare l’accuratezza della prestazione energetica calcolata con il software di modellazione. La soluzione progettuale è stata comparate anche rispetto alle prestazioni di una tipica facciata a doppia pelle. Inoltre le prestazioni termiche calcolate con EnergyPlus sono state confrontate con quelle ottenute con software di simulazione fluidodinamica computazionale (CFD), più accurati nel calcolo delle facciate a doppia pelle. Tale comparazione ha permesso di identificare il grado di errore e l’appropriatezza dell’uso di EnergyPlus nelle fasi iniziali della progettazione. La facciata a doppia pelle proposta consente una diminuzione della domanda di raffrescamento fino al 13,4%, migliorando al tempo stesso il livello di illuminazione naturale, che spesso costituisce uno dei maggiori limiti per l’applicazione di tale sistema. La ricerca termina con una sintesi dei risultati ottenuti e una valutazione complessiva del processo di progettazione presentato, degli strumenti di progettazione/simulazione utilizzati e delle prestazioni dell’involucro proposto, discutendone vantaggi e limiti. Sulla base delle sperimentazioni e dei risultati conseguiti, sono state individuate linee guida e raccomandazioni per la progettazione delle facciate a doppia pelle nei climi caldi. Inoltre viene fornita una matrice che raccoglie tutte le idee biomimetiche esplorate e analizzate, che rappresenta una mini-banca dati per architetti o designer interessati a questo approccio progettuale nell’affrontare i problemi di termoregolazione del costruito. Infine, la differenza di accuratezza tra i risultati di EnergyPlus e quelli dello strumento CFD è risultata trascurabile.Biomimicry is an applied science that derives inspiration for solutions to human problems through the study of natural designs, materials, structures and processes. Many fields of study benefit from biomimetic inspirations, such as agriculture, medicine, engineering, and architecture. Technological advances in parametric and computational design software in addition to environmental simulation means offer very useful tools in order to explore the potential of nature’s inspirations in architectural designs that does not just mimic shapes and forms. Energy efficiency is one of the major and growing concerns facing architects. Cooling and ventilation needs are critical factors that affect energy efficiency especially in hot climates. This thesis addresses the problem of designing building skins that are energy efficient in the context of hot climates such as that in Egypt. The research attempts to define and apply a biomimetic-computational design approach to study and analyse natural organisms in terms of their behaviour regarding thermoregulation. Aiming to decrease cooling loads, the research explores possible architectural solutions for a biologically inspired skin system for office buildings. The building’s skin is parametrically designed using Grasshopper Visual Programming Language for Rhino 3D Modeller, and it is optimised using multi-objective evolutionary algorithms which are particularly important in the attempt of finding a range of solutions that reduce cooling loads while maintaining daylight needs. Consequently, the reduction in cooling loads should not be at the expense of increased energy consumption in artificial lighting. Simulations regarding the thermal performance were performed using EnergyPlus. A Double-Skin Façade (DSF) is proposed based on inspirations from nature. In order to evaluate the performance of the proposal, it is compared to the performance of the skin of an existing office building in Cairo acting as a reference case. Data regarding the reference case such as the building drawings, material specifications and annual cooling consumption were obtained in order to build its digital model and assess its accuracy. The proposed design is also evaluated by comparing it to a typical flat DSF. The obtained results regarding the thermal performance of the proposed building skin are verified by comparing them to results of more accurate simulations performed using Computational Fluid Dynamics (CFD). The aim is to know the degree of error as well as the appropriateness of using EnergyPlus for geometrically-complex DSFs in early design phases when CFD is not practical. The proposed DSF was able to decrease cooling loads by up to 13.4% while improving daylight performance at the same time which is often one of the main challenges of using DSFs. The research criticises the presented design approach as a whole, the design/simulation tools used and the performance of the proposed skin discussing their benefits and limitations. Based on the design experimentation and results, general guidelines and recommendations for DSF design in hot climates are presented. Additionally, the research presents a compiled matrix of the biomimetic ideas explored and analysed in order to serve as a mini-data bank for architects or designers interested in this design approach in addressing thermoregulation problems. Finally, the comparison between EnergyPlus and CFD software results showed minor differences

Association of Architecture Schools in Australasia

"Techniques and Technologies: Transfer and Transformation", proceedings of the 2007 AASA Conference held September 27-29, 2007, at the School of Architecture, UTS

Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications

This article presents a state-of-the-art review of the applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in building and construction industry 4.0 in the facets of architectural design and visualization; material design and optimization; structural design and analysis; offsite manufacturing and automation; construction management, progress monitoring, and safety; smart operation, building management and health monitoring; and durability, life cycle analysis, and circular economy. This paper presents a unique perspective on applications of AI/DL/ML in these domains for the complete building lifecycle, from conceptual stage, design stage, construction stage, operational and maintenance stage until the end of life. Furthermore, data collection strategies using smart vision and sensors, data cleaning methods (post-processing), data storage for developing these models are discussed, and the challenges in model development and strategies to overcome these challenges are elaborated. Future trends in these domains and possible research avenues are also presented

The Proceedings of the Fourth International Conference of the Association of Architecture Schools of Australasia

The Proceedings of the Fourth International Conference of the Association of Architecture Schools of Australasia. Each paper in the Proceedings has been double refereed by members of an independent panel of academic peers appointed by the Conference Committee. Papers were matched, where possible, to referees in the same field and with similar interests to the authors

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