Advanced tools and techniques to add value to soil stabilization practice

Innov. Infrastruct. Solut. (2017) 2:26 DOI 10.1007/s41062-017-0084-5 TECHNICAL PAPER Advanced tools and techniques to add value to soil stabilization practice António Gomes Correia1 • Joaquim Tinoco1 Received: 3 May 2017 / Accepted: 2 June 2017 Ó Springer International Publishing AG 2017 Abstract The aim of this paper is to demonstrate the advanced tools and techniques used for adding value to the soil stabilization practice. The tools presented involve advanced laboratory tests and modeling using codes and soft computing to evaluate the mechanical behavior of stabilized soils with cement, ranging from short-term to long-term behavior. More precisely, these tools are able to: 1. Predict the mechanical behavior of the stabilized soils over time from data obtained in the early ages saving time in laboratory tests; 2. Predict the mechanical behavior of the stabilized soils over time based on basic parameters of soil type and binder using historical accurate data, avoiding mechanical laboratory tests. 3. Incorporate the serviceability limit state concept in a novel proposal to estimate the design modulus in function of the uniaxial compressive strength and the strain level, making more economic and sustainable geotechnical solutions. Keywords Soil stabilization  Design modulus  Soft computing  Eurocode 2  Service limit state Introduction Soil stabilization works require laboratory testing to obtain the best dosage of binder necessary to achieve hydraulic and mechanical properties associated with the service limit This paper was selected from GeoMEast 2017–Sustainable Civil Infrastructures: Innovative Infrastructure Geotechnology. & António Gomes Correia 1 ISISE – Institute for Sustainability and Innovation in Structural Engineering, School of Engineering, University of Minho, Guimarães, Portugal state of the geotechnical structure. The laboratory studies are time consuming and consequently affecting the delivery time of the project since in general the mechanical properties are obtained for at least 28 days [1]. To overcome this problem the design engineer can use available empirical rules, codes, and actually more advanced tools and techniques such as data mining. Concerning the empirical rules, most of the available ones are very conservative for mechanical property predictions since the laboratory techniques available at the time they were established did not use advanced laboratory tests using local strain measurements and/or wave propagation techniques [2, 3]. In this work this will be addressed and a novel proposal will be presented. In what concerns the use of codes, a paper presented by authors adapts the Eurocode 2 for prediction of the mechanical properties of soil–cement mixtures and this will be reported in this paper to decrease the time in mechanical laboratory testing [4, 5]. In this context, a recent test method named EMM-ARM will be presented allowing the possibility to predict stiffness of stabilized soil from the early ages [6]. Alternative advanced techniques using soft computing are also nowadays available with predictive capacities when a huge amount of historical data is available. This is our case for results of laboratory soil–cement tests were these techniques are also applied. In fact, these soft computing techniques are powerful tools for analyzing and extracting information from raw data, enabling the identification of complex relationships between several input variables and the target output. Indeed, there are several successful cases where these tools were used to solve complex problems in different knowledge areas, including this one related to soil stabilization using jet grouting technology [7–9]. 123 26 Page 2 of 9 In summary this paper will cover these two different approaches for laboratory formulations of soil stabilization with cement. Furthermore, an insight into design application is gained through a novel proposal allowing the prediction of the design modulus in function of the uniaxial compressive strength for the level of strain of the material corresponding to the serviceability limit design of the structure. Mechanical property prediction Mechanical propriety prediction of soil–cement mixtures is a key issue in soil stabilization projects. To accomplish this task, a current practice in the framework of soil stabilization projects, such as in jet grouting (JG) or cutter soil mixing (CSM) is to prepare and test some laboratory formulations, using the same soil and binder to be applied during the in situ treatment. However, these formulations can represent by itself an important cost to the project. Thus, to minimize the number of formulations to prepare and consequently the final cost of the project, it is useful to have an available numerical model able to accurately predict its mechanical properties (strength and stiffness) over time [10]. Nowadays, there are some empirical models available that can give a valuable help during the design stage. However, due to the high number of variables involved (treatment parameters, binder, soil properties, etc.) as well as the heterogeneity of the soils, most of the existing approaches present important applicability limitations. Hence, in last years several attempts have been made to overcome this limitation. In this paper, two different approaches are summarized, which have shown to be very effective in mechanical property estimation of soil–cement mixtures. Innov. Infrastruct. Solut. (2017) 2:26 cure [4]. The achieved results allow us to balance the model prediction accuracy and time consumption in the final project and construction work costs, by comparing model performance using reference data tested at 3, 7, 14, and 28 days time of cure. For training and test purposes, a set of soil–cement formulations for JG and CSM technologies were used, performing a total of 342 records for UCS study and 188 records for E0 study. These records contemplate formulations prepared with soils collected from different sites, with different water cement ratios (W/C), cement content (kg/ m3) and type (coefficient s), which were tested at different ages (t). For a detailed characterization of the different formulations considered please see [4]. Following the EC2 approach [11], strength and stiffness prediction of concrete over time can be performed according to the following equations, respectively: 28 a fcm ðtÞ ¼ eðs½1ð t Þ Þ  fcm   
c 28 b Ecm ðtÞ ¼ e s 1ð t Þ  Ecm ð1Þ ð2Þ In the above equations, t is the age of the mixture, s is a coefficient related with the cement type defined in EC2 [11], a, b, and c are coefficients to be adjusted using laboratory soil–cement mixtures test results, fcm and Ecm represent, respectively, the strength and stiffness of each formulation at 28 days time of cure (reference data), and fcm(t) and Ecm(t) are, respectively, the strength and stiffness of the mixture at the age t. To adapt Eqs. 1 and 2 to JG laboratory formulations (JGLG) (...truncated)