Experiences of dry soil mixing in highly organic soils

2012 ◽  
Vol 165 (1) ◽  
pp. 3-14 ◽  
Author(s):  
Martin J. Timoney ◽  
Bryan A. McCabe ◽  
Alan L. Bell
Keyword(s):  
Organic Soils ◽  
Soil Mixing ◽  
Dry Soil

scholarly journals Stiffness and Strength of Stabilized Organic Soils—Part I/II: Experimental Database and Statistical Description for Machine Learning Modelling

Geosciences ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 243
Author(s):  
Hernandez-Martinez Francisco G. ◽  
Al-Tabbaa Abir ◽  
Medina-Cetina Zenon ◽  
Yousefpour Negin
Keyword(s):  
Machine Learning ◽  
Statistical Analysis ◽  
Portland Cement ◽  
Soil Stabilization ◽  
Data Availability ◽  
Data Repository ◽  
Organic Soils ◽  
Experimental Database ◽  
Soil Mixing ◽  
The Impact

This paper presents the experimental database and corresponding statistical analysis (Part I), which serves as a basis to perform the corresponding parametric analysis and machine learning modelling (Part II) of a comprehensive study on organic soil strength and stiffness, stabilized via the wet soil mixing method. The experimental database includes unconfined compression tests performed under laboratory-controlled conditions to investigate the impact of soil type, the soil’s organic content, the soil’s initial natural water content, binder type, binder quantity, grout to soil ratio, water to binder ratio, curing time, temperature, curing relative humidity and carbon dioxide content on the stabilized organic specimens’ stiffness and strength. A descriptive statistical analysis complements the description of the experimental database, along with a qualitative study on the stabilization hydration process via scanning electron microscopy images. Results confirmed findings on the use of Portland cement alone and a mix of Portland cement with ground granulated blast furnace slag as suitable binders for soil stabilization. Findings on mixes including lime and magnesium oxide cements demonstrated minimal stabilization. Specimen size affected stiffness, but not the strength for mixes of peat and Portland cement. The experimental database, along with all produced data analyses, are available at the Texas Data Repository as indicated in the Data Availability Statement below, to allow for data reproducibility and promote the use of artificial intelligence and machine learning competing modelling techniques as the ones presented in Part II of this paper.

Laboratory-scale dry soil mixing of a sand

2017 ◽  
pp. 73-80
Author(s):  
A. Al-Tabbaa ◽  
A.M.B. Al-Tabbaa ◽  
J.M. Ayotamuno
Keyword(s):  
Laboratory Scale ◽  
Soil Mixing ◽  
Dry Soil

scholarly journals Mass Stabilization as reinforcement of organic soils

2019 ◽  
Vol 97 ◽  
pp. 04046 ◽  
Author(s):  
Grzegorz Nowak ◽  
Piotr Kanty
Keyword(s):  
Deformation Modulus ◽  
Dry Mass ◽  
Soil Reinforcement ◽  
Organic Soils ◽  
Deep Soil ◽  
Soil Mixing ◽  
Deep Mixing ◽  
Wide Range ◽  
Deep Soil Mixing ◽  
Over Time

The decreasing number of places suitable for constructing buildings forces people to creatively develop newer methods of soil reinforcement. One of these methods is the deep soil mixing. This technology has been firstly developed and applied in Japan in the 1970s. Initially, it was used to create DSM (Deep Soil Mixing) columns. In the subsequent years, it was also developed in Scandinavia. Over time, the deep mixing technology was modified and developed, and in addition to the wet method, also the dry method was started to be used, while in addition to the cement binder, also lime binders and fly ashes were used. Technologies consisting of the deep mixing of cement with soil are very popular due to the wide range of applications and relatively low implementation costs. The method of Mass Stabilization (MS) is a soil reinforcement method that is analogical to DSM and it consists of mixing large volumes of soil with cement. This article describes the method of dry Mass Stabilization of organic soils. It cites the analyzed laboratory tests of soil-cement material manufactured in MS technology. The tests included the creation of 140 material samples, and subsequently the performance of compression strength test on them, along with the registration of stress path. The main aspect of these tests consisted of increase in the primary deformation modulus over time, depending on the amount of applied cement. Also, an example of the project to strengthen the layer of aggregate mud under the floor in the hall is demonstrated. The reinforcement was implemented in the MS technology.

scholarly journals Detection and Quantification of Rhizoctonia solani and Rhizoctonia solani AG1-IB Causing the Bottom Rot of Lettuce in Tissues and Soils by Multiplex qPCR

Plants ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 57
Author(s):  
Thérèse Wallon ◽  
Andréanne Sauvageau ◽  
Hervé Van der Heyden
Keyword(s):  
Rhizoctonia Solani ◽  
Infected Plant ◽  
Qpcr Assay ◽  
Organic Soils ◽  
Detailed Knowledge ◽  
Its Sequencing ◽  
Internal Transcribed Spacer Region ◽  
Minimum Concentration ◽  
Dry Soil ◽  
Bottom Rot

In the muck soil region of southwestern Quebec, vegetable growers are threatened by several soilborne diseases, particularly the bottom rot of lettuce caused by the fungus Rhizoctonia solani. The particularly warm temperature of the few last seasons was marked by an increase in disease severity, and the associated yield losses were significant for Quebec lettuce growers. In the absence of registered fungicides and resistant cultivars, the management of Rhizoctonia solani-induced diseases in lettuce is based on good agricultural practices, which require detailed knowledge of the pathogen. In this study, Rhizoctonia solani fungal strains were isolated from infected field-grown lettuce plants presenting bottom rot symptoms to determine the anastomotic groups (AGs) of these isolates by internal transcribed spacer region (ITS) sequencing. Rhizoctonia solani AG 1-IB was identified as the main anastomotic group causing bottom rot lettuce in field-grown lettuce in organic soils in the Montérégie region. Two specific and sensitive quantitative PCR assays were then developed for R. solani AG1-IB and R. solani. The AG 1-IB qPCR assay amplified all strains of R. solani AG 1-IB tested, and no PCR product was obtained for any non-target strains. The R. solani qPCR assay amplified all strains of R. solani and did not amplify non-target strains, except for two strains of binucleate Rhizoctonia AG-E. In artificially inoculated soils, the sensitivity of both qPCR assays was set to 1 μg of sclerotia g−1 of dry soil. In the growth chamber experiment, a minimum concentration between 14 and 42 μg sclerotia g−1 of dry soil was required to induce the development of symptoms on the lettuce. Indeed, the AG 1-IB qPCR assay was sensitive enough to detect the lowest soil concentration of AG1-IB capable of inducing symptoms in head lettuce. In addition, the qPCR assays successfully detected R. solani and R. solani AG 1-IB from infected plant tissue samples and soil samples from lettuce fields. The qPCR assays developed in this study will be useful tools in lettuce bottom rot management.

scholarly journals Quality Assessment of Dry Soil Mixing Columns in Soft Soil Areas of Eastern China

2021 ◽  
Vol 11 (21) ◽  
pp. 9957
Author(s):  
Huangsong Pan ◽  
Guangyin Du ◽  
Han Xia ◽  
Haiyuan Wang ◽  
Da Qin
Keyword(s):  
Quality Assessment ◽  
Soft Soil ◽  
Eastern China ◽  
Test Results ◽  
Soil Mixing ◽  
Laboratory Test Results ◽  
Dry Soil ◽  
Soft Soil Area ◽  
Soil Area

To investigate the quality of dry soil mixing (DSM) columns in different soft soil areas of east China, a large number of laboratory test results and field test results of DSM columns were collected and analyzed statistically. Furthermore, a quality assessment method for DSM columns is proposed in this paper. The hardness description (HD), standard penetration test (SPT), unconfined compressive strength (UCS), and soil-cement column quality designation (SCQD) are used as assessment indexes. The statistical analysis showed that the test results of SPT, UCS, and SCQD were scattered, particularly in shallow ground. The mean values of the SPT blow count, UCS, and SCQD of the DSM columns decreased with depth: the greater the depth, the worse the quality of DSM columns. The quality assessment results showed that the proportion of the great quality columns was 64.84%, and the proportion of the unqualified columns was 1.4%. The proportion of DSM columns with great quality in the lagoon soft soil area was greater than in other areas. The proportion of unqualified columns in the lacustrine soft soil area was the largest. For all soft soil areas, the proportions of great quality, good quality, general quality, and unqualified soil decreased in that order. The quality assessment of 8627 DSM columns showed the proportions of great quality and unqualified were 64.84% and 1.4%, respectively. It was found that the greater the depth of the DSM column, the more unqualified DSM columns, and the more difficult it was to control the quality of DSM columns.

Deep Dry Soil Mixing to Stabilize a Live Railway Embankment Across Thrandeston Bog

2012 ◽  
Author(s):  
Nigel Pye ◽  
Anthony O'Brien ◽  
Robert Essler ◽  
Dan Adams
Keyword(s):  
Soil Mixing ◽  
Dry Soil

Dry Soil Mixing at Jewfish Creek

2007 ◽  
Author(s):  
G. K. Burke ◽  
A. L. Sehn ◽  
J. D. Hussin ◽  
V. E. Hull ◽  
J. A. Mann
Keyword(s):  
Soil Mixing ◽  
Dry Soil
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