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Record W4388457472 · doi:10.59490/seg.2023.632

Thermal conductivity of dried biocemented sand at higher calcification

2023· article· en· W4388457472 on OpenAlexaff
Shadi Zeinali, Zarghaam Haider Rizvi, Frank Wuttke

Bibliographic record

VenueSymposium on Energy Geotechnics 2023 · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Applications in Construction Materials
Canadian institutionsUniversity of British Columbia, Okanagan CampusKelowna General HospitalUniversity of British Columbia
Fundersnot available
KeywordsCalciteSaturation (graph theory)MineralogyMaterials scienceCalcium carbonateAragoniteSoil scienceComposite materialChemistryGeologyMathematics

Abstract

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MICP-treated sand has been used for many soil stabilisation and erosion protection applications [10] with different bacteria types and paths of biocement generation. A novel application of the method is in the improvement of soil for energy geotechnics applications where a higher thermal conductivity (TC, λ) could be achieved by cementing and improving the existing contacts and developing new contacts among the grains with precipitated various calcium carbonate polymorphs formed during the process, such as calcite, vaterite and aragonite. Past studies, however, only a few, have shown a significant improvement in the TC of biocemented sand at dry and for the full range of saturation, incorporating a steady-state method [7], the transient method [5,6], and the transient plane source method (TPS) [11]. Venuleo et al. [7] studied the effect of 7.97% calcification content (CC) which led to a 250% improvement in TC in the dry state and 40% at the higher saturation range. Xiao et al. [11] presented a fitting equation to predict the TC with CC controlled by void ratio and coefficient of uniformity (Cu). Wang et al.’s theoretical model [10], developed by the soil model of Haigh [2], includes simplifications for the water content effect and geometric shape of soil phases, which has higher errors for low TC values and in lower saturation states. All the above studies are limited to lower calcite precipitation for TC measurement; however, higher calcite precipitation is reported in many studies where the mechanical properties of soil are improved [4]. Therefore, to shed light on the TC in the dried state, this study tries to measure the TC of MICP-treated sand in a dry state with a calcite content of up to 10.21%. Medium-grained sand [1] with an average particle size of 0.79mm, specific gravity of 2.71, Cu of 1.53, and density of 1.58±0.03g/cm3 served as the reference. Bacterial and cementation solutions were mixed and injected with a continuous flow to the sand columns with a constant head and were renewed every 24 hours, 7-21 times. Post draining, the biocemented columns were accurately cut into the desired-sized discs and dried in the oven at 105°C for 24 hours. TC of the biocemented discs was measured in the dry state and at room temperature according to Hailemariam and Wuttke [3] and compared to other research [2, 5, 6, 7, 10, 11] in 3 different initial porosity groups (ɳ0 for A=40%, B=41.3%, C=42.7%). Group A was biocemented up to a higher cementation level, as depicted in Figure 1(a, b). As the ɳ0 in some studies [5, 7, 11] are initially more compact than the current study or have more fine materials inside (higher Cu and less D50), more TC with even less CC could be achieved. Limited experimental results [9, 10, 11], comparable with groups A-2 and B, are also shown. It appears that the same CC decreased void volume in [9, 11] more, which leads to higher TC compared to the current study. This is perhaps due to different gradation and fewer fine aggregates in the soil matrix with Cu of 1.53 compared to studies with Cu between 2-9.7 [9, 11], as mentioned in [11]. In the current investigation, the transition of the TC behaviour from part A-1 to A-2 with higher cementation can demonstrate a point (about CC of 6%) at which the CC form more effective bonds that abruptly increases the gradient of TC-CC graph from almost constant in part A-1 to 6.3% for part A-2 (up to 190% TC of reference). Finding this point for other groups needs a more comprehensive CC range than the current study. It is observed in A-2, B, and C that TC increased with increasing the CC, parallel with other studies [10]. Additionally, group C was able to offset the additional initial void available by having more CC to approximately the same TC as B. Less density increase rate (Id) of group A-1 in Figure 1(c) suggests that the calcite condensation may have been less compact and effective bridges compared to that of groups B and C, which supports the slightly lower TC, even though it is a bit more initially compact. Figure 1(c) compares MICP-soil models available for the MICP-treated sands [8, 10, 11] and the Johansen soil model [12] for the results of the current study. Wang et al. [8] empirical model showed a scattered and overestimated result, perhaps because the model only considers the treated dried density and does not take the volume behaviour of biocementation as a bridge in the soil matrix into account. Xiao et al. [11] prediction with the closest fitting parameters to our case, given the available fitted parameters, overestimates the TC in the dry case for all samples. This can be due to the limited number of instances used for making this model, especially in the dry state and the unavailability of correct fitting parameters for Cu less than 2. The model performed well for a similar sand from Martinez et al. [5] but cannot predict the results of Wang et al. [9]. Wang et al. [10] theoretical model also appears not able to predict the exact values for TC of dry state, and, for this study, it underestimates the TC for under 4% CC and overestimates it for over 4%. Perhaps the simplifications in the model can overestimate the thermal bridge size for TC below 1.2 W/m/K and low saturation and dry state. Hence, the model may not be able to provide correct results in the dry state [10]. The Johansen soil model [12] did not match our research either since it overestimates the TC for soils with a dry density between 1.57 and 1.65 g/cm3. It also needed to fit previous MICP-treated sand investigations [8]. Overall, neither the conventional soil models nor the theoretical or empirical equations from the literature can accurately predict the results of the dry state thermal conductivity measurement on the case studies of this research. It seems that there is an optimal CC among higher cementation levels that would be sufficient for creating more efficient bonds in the soil matrix, which rapidly elevates the TC. Therefore, more investigation on thermal conductivity in the dry state, especially on the higher cementation level impact, is needed to deduct a good prediction for different cases of MICP-treated sands.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.240
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2023
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