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Record W7102401975 · doi:10.11932/karst20230304

A review of karst collapse mechanisms

2023· article· zh· W7102401975 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languagezh
FieldEarth and Planetary Sciences
TopicKarst Systems and Hydrogeology
Canadian institutionsnot available
Fundersnot available
KeywordsKarstSinkholeGroundwaterGeohazardFoundation (evidence)Geologic hazards

Abstract

fetched live from OpenAlex

Karst collapse is a global geohazard and has been reported to occur in 23 countries, including China, the United States of America, Canada, South Africa, Italy, France, the United Kingdom, Germany, Russia, and Turkey. The mechanism of karst collapse is the basis for its monitoring, early warning, prevention and treatment. For a long time, studies on the mechanism of karst collapse have been mainly based on the qualitative speculation of the investigation after karst collapse, involving geological conditions and influencing factors of the collapse. They lack support of scientifically defensible data, hence resulting in the hypothetical stage of current studies on karst collapse mechanism. This has become a technical bottleneck in the prediction and prevention of karst collapse hazard.Karst collapse hazards are characterized by concealment and suddenness. Among the existing collapse events in China, more than 90% are soil collapse. Studies on karst collapse in China started in the 1980s and have gone through approximately four phases, (1) The sporadic karst collapse research in selected mines; (2) The karst collapse inventory and small-scale physical modeling in Yangtze River Basin, and representative mines and railroads; (3) The karst collapse reconnaissance and large-scale physical modeling in urban areas including Wuhan, Yulin, Tangshan, Tongling, Guilin, and Shenzhen; (4) The systematic nation-wide karst collapse reconnaissance. Since 2000, National Natural Science Foundation of China has increased investment in the studies on karst collapse involving groundwater pumping, foundation piling, tunneling, drainage in mines, and train vibration and in the studies on karst collapse mechanisms induced by extreme climate. At present, there are about eight karst collapse mechanisms according to previous studies, such as subduction, vacuum negative pressure, pressure difference, hydraulic fracturing, gas explosion, chemical dissolution, resonance, liquefaction, etc. These processes are closely associated with changing underground hydrodynamic conditions.With a profound analysis of definitions and theoretical basis of karst collapse mechanism, this study proposes that most of the above mechanisms can be attributed to seepage deformation of soil. This means, under the action of groundwater seepage force or dynamic water pressure, some particles of the whole soil mass will move, causing deformation and destruction of soil or rock mass. During the formation of karst collapse, the action mode and direction of groundwater seepage force on karst cavities roof soil will be different because of the change of groundwater dynamic conditions. The limit equilibrium theory of soil mechanics considers the roof stability of karst cavities, which is the last stage in the development of karst collapse; the effect of surface load is only to shorten the time of ground collapse.Finally, it is pointed out that due to the practicability of water-air pressure with high-frequency sampling, accelerometer and acoustic wave sensors, the research direction on collapse mechanisms will be changed from hydrostatic pressure to hydrodynamic pressure, a challenge that should be faced with. The cavitation damage and resonance damage caused by pressure pulsation will also be the future research focus, and the corresponding critical seepage deformation or damage indicators need to be further studied the prevention and control of geological disasters of karst collapse.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.275
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0040.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0990.001

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 head0.241
GPT teacher head0.507
Teacher spread0.266 · 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 designObservational
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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