Application of a sensitivity analysis procedure to interpret uniaxial compressive strength prediction of jet grouting laboratory formulations performed by SVM model

Jet Grouting (JG) technology, one of the most efficient soft soils improvement methods, has been widely applied in important geotechnical works due to its versatility. However, there is still an important limitation to overcome related with the absence of rational approaches for its design. In the present work, three different Data Mining (DM) techniques, i.e., Artificial Neuronal Networks (ANN), Support Vector Machines (SVM) and multiple regression are trained in order to predict elastic young modulus (E0) of JG mixtures. It is shown that the complex relationships between E0 and its contribut- ing factors can be learned using DM tools, particularly by SVM and ANN algorithms. By performing a detailed sensitivity analysis, understandable knowledge is extracted from the trained models, in terms of the relative importance of the attributes, as well as its effect in E0 prediction. In addition, the mathemati- cal expression proposed by Eurocode 2 to estimate concrete stiffness, is adapted to JG material. Its low performance is assessed and compared with those achieved by DM models.The authors wish to thank to “Fundação para a Ciência e a Tecnologia” (FCT) for the finan- cial support under the strategic project PEst-OE/ ECI/UI4047/2011 and the doctoral Grant SFRH/ BD/45781/2008Tecnasol-FG

Application of data mining techniques to jet grouting columns design

Tese de doutoramento em Civil Engineering (ramo de conhecimento em Geotechnics)Jet Grouting (JG) is actually a reference method on soil improvement technologies, allowing to improve the strength, stiffness and permeability of soft soils. However, even after several years of practice and notable technology advances, there are still some limitations to overcome. In particular, the main limitation is the absence of efficient approaches for its design. Indeed, the actual design approaches are essentially based on empirically and less accurate methods that are often too conservatives. As a results, the economy and the quality of the treatment can be affected. Therefore, it is fundamental to develop new approaches able to accurately predict JG columns mechanical properties as well as its diameter. However, due to the high number of variables involved in JG process and the heterogeneity of the soils treated, the accomplishment of such complex task represents a major challenge. This challenge relies in the fact that a JG model design should be able to incorporate simultaneously the effect of different variables (e.g. soil and cement slurry properties). So far, the traditional statistical approaches were unable to deal with the complexity of JG data. However, in the past few years powerful tools have emerged for extracting useful information from large and complex data. These tools are currently known as Data Mining (DM) techniques and have been successfully applied in different application domains.. In the present research work, some of the most well known DM algorithms were applied in the prediction of the mechanical properties of JG mixtures as well as JG columns diameter. Therefore, and as a first step, a multiple regression, artificial neural network, support vector machine and functional network algorithms were trained to predict JG laboratory formulations stiffness and uniaxial compressive strength. Moreover, the analytical expressions proposed by Eurocode 2 and CEB-FIP Model Code 1990 for strength and stiffness prediction of concrete were adapted to JG mixtures. After that, the same methodologies were applied in the prediction of strength, stiffness and column diameter of real JG columns. As the main outcomes of this work, high quality predictive models were achieved, as well as a better understanding of the JG mixtures behaviour (given by a global sensitivity analysis). Such results are quite useful for JG design, being expecting an economic and technical improvement through a better optimization of the available resources and efficient designJet Grouting (JG) surge atualmente como um método de referência entre as tecnologias de melhoramento de solos, permitindo o aumento da resistência e deformabilidade bem como a diminuição da permeabilidade de solos moles. No entanto, mesmo após vários anos de prática e de notáveis avanços tecnológicos, existem ainda algumas limitações a vencer. Uma das mais relevantes prende-se com a ausência de abordagens eficientes de dimensionamento. De facto, as atuais abordagens de cálculo são essencialmente suportadas por métodos empíricos e pouco precisos, por vezes até demasiado conservativos. Em consequência, a eficiência técnica e económica do tratamento pode ficar comprometida. Neste sentido, é fundamental desenvolver novas abordagens capazes de prever com maior precisão as propriedades mecânicas e respectivo diâmetro das colunas de JG. Contudo, devido ao elevado número de variáveis envolvidas e à heterogeneidade dos solos tratados, tal tarefa representa um enorme desafio. Este desafio prende-se com o facto de um modelo de dimensionamento da tecnologia de JG dever ser capaz de incorporar simultaneamente o efeito de diferente variáveis (e.g. propriedades do solo e da calda injetada e o tipo de jet). Até aos dias de hoje, as ferramentas estatísticas tradicionais foram incapazes de lidar com a complexidade caracteristica de dados JG. No entanto, nos últimos anos têm emergido ferramentas com enorme potencial, capazes de analisar e extrair informação útil de grandes volumes de dados complexos. Estas ferramentas são correntemente conhecidas como técnicas de Data Mining (DM) e têm sido aplicadas com sucesso em diferentes áreas do conhecimento. No presente trabalho de investigação, alguns dos mais conhecidos algoritmos de DM foram aplicados na previsão das propriedades mecânicas de misturas de JG bem como na previsão do diâmetro das respetivas colunas. Assim, numa primeira fase, os algoritmos de regressão múltipla, redes neuronais artificiais, máquina de vetores de suporte e redes funcionais foram treinados para prever a deformabilidade e a resistência à compressão uniaxial de formulações laboratoriais de JG. Além disso, as expressões analíticas propostas pelo Eurocódigo 2 e pelo CEB-FIP Model Code 1990 usadas na previsão da resistência e deformabilidade do betão, foram também adaptadas a misturas de JG. Posteriormente, as mesmas metodologias foram aplicadas na previsão da resistência, deformabilidade e diâmetro de colunas reais de JG. Como principais resultados do presente trabalho, destaca-se a elevada qualidade previsional dos modelos obtidos, bem como uma melhor compreensão do comportamento de misturas de JG (conseguida através da aplicação de análises de sensibilidade globais). Estes resultados são um claro contributo para o dimensionamento de colunas de JG, antevendo-se uma maior eficiência técnica e económica, através de uma melhor otimização dos recursos disponíveis e eficiência no dimensionamento

Previsão do comportamento mecânico de formulações laboratoriais de solo-cimento para colunas de jet grouting com recurso a máquina de vetores de suporte

Atualmente, no âmbito dos métodos de tratamentos de solos, o jet grouting (JG) é uma das tecnologias mais utilizadas, nomeadamente em importantes obras geotécnicas, caracterizando-se pela sua grande versatilidade. No entanto, no que respeita à previsão das propriedades mecânicas do novo material resultante do tratamento, a heterogeneidade dos solos e o elevado número de parâmetros envolvidos são os fatores que mais condicionam a existência de modelos racionais e precisos. O presente trabalho visa contribuir para o desenvolvimento de abordagens racionais e precisas com vista à previsão da resistência à compressão uniaxial e respetivo módulo de deformabilidade de formulações laboratoriais de JG. Para o efeito, recorreu-se à aplicação de técnicas de data mining, particularmente do algoritmo máquinas de vetores de suporte. Foi ainda realizada uma análise de sensibilidade detalhada, visando identificar as variáveis chave e qual o seu efeito no estudo das propriedades mecânicas de formulações laboratoriais de JG

Data-driven models for uniaxial compressive strength prediction applied to unseen data

Data Mining (DM) techniques have been successfully applied to solve a wide range of real-world problems in different real-world domains, particularly in the field of geotechnical civil engineering. A remarkable example is their use in Jet Grouting (JG) technology. Due to the high number of parameters involved and to the heterogeneity of the soil, JG mechanical properties prediction, as well as columns diameter, are complex tasks. Accordingly, the high learning capabilities of DM, namely of the Support Vector Machine (SVM), were applied in the development of new approaches to accurately perform such tasks. This paper aims to assess the SVM model performance trained to predict Uniaxial Compressive Strength (UCS) of JG samples extracted directly from JG columns, when applied to a new set of records collected from a new JG work not contemplated in the database used during the model learning phase. The achieved results highlight the importance of the model domain applicability, as well as the restrictions and recommendations for its generalization when applied to new JG work data not contemplated in the training dataset.The authors wish to thank to Fundacao para a Cienciae a Tecnologia (FCT) for the financial support under the Pos-Doc grant of strategic project PEstOE/ECI/UI4047/2011. Also, the authors would like to thank the interest Tecnasol-FGE company for providing all data needed

Support vector machines on mechanical behaviour prediction of soil-cement laboratory formulations to jet grouting columns

Fundação Para a Ciência e a Tecnologia (FCT) pelo apoio financeiro no âmbito do projeto PEst-OE/ECI/UI4047/2011 e pela bolsa de doutoramento SFRH/BD/45781/200

Numerical analysis of traditionally excavated shallow tunnels

openLo scavo di gallerie rappresenta sicuramente una tra le sfide più impegnative che un ingegnere civile possa affrontare. Ciò è dovuto principalmente alla natura tridimensionale di questo problema di interazione terreno-struttura ma anche alle numerose incertezze che possono entrare in gioco nella progettazione. Recentemente, le tecniche di calcolo numeriche, che permettono una più ampia comprensione del problema, hanno subito un notevole sviluppo, diventando una risorsa fondamentale per la progettazione di scavi in sotterraneo. Tuttavia, solo ingegneri con una buona preparazione numerica sono in grado di gestire la modellazione di problemi di interazione terreno-struttura così complessi. Inoltre, tali modelli richiedono una attenta calibrazione dei parametri e una costante validazione con dati di monitoraggio. Lo scopo di questa tesi è quello di analizzare alcune delle principali problematiche legate alla progettazione di gallerie superficiali scavate in tradizionale. Il vantaggio principale dello scavo in traditionale rispetto a quello meccanizzato è legato alla maggiore flessibilità nella scelta dei rivestimenti e delle techniche di rinforzo del cavo e del fronte della galleria. Tuttavia, una maggiore flessibilità progettuale è necessariamente legata ad una profonda conoscenza del comportamento deformativo dell’ammasso, nonché ad un utilizzo consapevole delle tecniche modellazione numerica. Il presente lavoro è principalmente incentrato sulle seguenti tematiche riguardanti la progettazione di gallerie superficiali: - la stabilità di fronti di scavo rinforzati e non rinforzati; - l’applicabilità degli Eurocodici ad una progettazione condotta mediante tecniche di modellazione numerica; - la calibrazione dei parametri del modello numerico e la sua validazione attraverso dati di monitoraggio.Among the problems that civil engineers have to face, the design and verification of an underground construction is one of the most challenging. A tunnel engineer has to tackle with a complex three-dimensional soil-structure interaction problem where many factors and uncertainties come into play. This is the reason why professional experience and engineering judgment usually play a crucial role. In recent years, numerical calculation techniques, which can provide an important basis for a better understanding of the problem, have strongly improved. They have become a fundamental resource for underground construction design, but they also entail some drawbacks: - only engineers with a strong numerical background can handle complex soil-structure interaction problems; - numerical calculations, especially if 3D, can be very time-consuming; - material parameters should be carefully evaluated, according to the particular problem and adopted constitutive law; - numerical models need to be validated with field monitoring data. The goal of this thesis is to investigate the main issues regarding the applicability of numerical analyses to the design and verification of traditionally excavated shallow tunnels. Despite, the remarkable technological improvement in mechanised tunnelling, traditional techniques still represent, in some cases, the most suitable and convenient solution. The principal advantage of traditional techniques is the high flexibility in the choice of supports and reinforcement measures. However, design flexibility implies a deep understanding of the ground response to underground openings as well as a conscious use of numerical models. This work provides a contribution to the numerical design of shallow tunnels by focusing on three principal issues: - stability of reinforced and unreinforced excavation faces; - Eurocodes applicability to a numerically-based design; - parameters calibration and numerical validation through comparison with monitoring data.INGEGNERIA CIVILE, AMBIENTALE, EDILE E ARCHITETTURAPaternesi, AlessandraPaternesi, Alessandr

Geotechnical Engineering for the Preservation of Monuments and Historic Sites III

The conservation of monuments and historic sites is one of the most challenging problems facing modern civilization. It involves, in inextricable patterns, factors belonging to different fields (cultural, humanistic, social, technical, economical, administrative) and the requirements of safety and use appear to be (or often are) in conflict with the respect of the integrity of the monuments. The complexity of the topic is such that a shared framework of reference is still lacking among art historians, architects, structural and geotechnical engineers. The complexity of the subject is such that a shared frame of reference is still lacking among art historians, architects, architectural and geotechnical engineers. And while there are exemplary cases of an integral approach to each building element with its static and architectural function, as a material witness to the culture and construction techniques of the original historical period, there are still examples of uncritical reliance on modern technology leading to the substitution from earlier structures to new ones, preserving only the iconic look of the original monument. Geotechnical Engineering for the Preservation of Monuments and Historic Sites III collects the contributions to the eponymous 3rd International ISSMGE TC301 Symposium (Naples, Italy, 22-24 June 2022). The papers cover a wide range of topics, which include: 　 - Principles of conservation, maintenance strategies, case histories - The knowledge: investigations and monitoring - Seismic risk, site effects, soil structure interaction - Effects of urban development and tunnelling on built heritage - Preservation of diffuse heritage: soil instability, subsidence, environmental damages The present volume aims at geotechnical engineers and academics involved in the preservation of monuments and historic sites worldwide

Trends and Prospects in Geotechnics

The Special Issue book presents some works considered innovative in the field of geotechnics and whose practical application may occur in the near future. This collection of twelve papers, in addition to their scientific merit, addresses some of the current and future challenges in geotechnics. The published papers cover a wide range of emerging topics with a specific focus on the research, design, construction, and performance of geotechnical works. These works are expected to inspire the development of geotechnics, contributing to the future construction of more resilient and sustainable geotechnical structures