Use of Instrumented Dynamic Cone Penetrometer in Pavement Characterization

Lee

et al. 2021

Sensors

Dynamic resistance, which can be used to express strength in the unit of stress and improve the reliability of the dynamic cone penetration test (DCPT), has been estimated by numerous methods. This study aims to compare different dynamic resistance estimation methods by using an instrumented dynamic cone penetrometer (IDCP). DCPTs are conducted using a standard dynamic cone penetrometer (DCP) and IDCP in the laboratory and field. Dynamic responses are obtained from the strain gauges and an accelerometer installed at the cone tip of the IDCP. The test results show that dynamic resistance is more efficient in distinguishing profiles than the dynamic cone penetration index. Among the methods to estimate the dynamic resistance at the cone tip, the force-velocity integration method and force integration method are more related to the conventional dynamic resistance considering the potential energy of the hammer than the force squared integration method. Additionally, the dynamic resistance estimated for a longer time period is more reliable, particularly for small driving rod lengths. Regarding the limitation of the dynamic response from an accelerometer in a previous study, the force-based dynamic resistance estimated for a longer time period can be used as the most reliable approach for further soil strength characterization.

where c and E denote the wave velocity through the steel rod and Young’s modulus of the rod, respectively.…”

Section: Experimental Studymentioning

confidence: 99%

Comparative Study on Estimation Methods of Dynamic Resistance Using Dynamic Cone Penetrometer

Lee

et al. 2021

Sensors

Meteorit & Planetary Scien

“…There has been some work done on extracting the actual mechanical properties of soil with a DCP. Nazarian et al (1999) developed two experimental versions of the DCP, for transportation civil engineering, that were tested in pavement bases and subgrains. A "Seismic DCP" (SDCP) was outfitted with a 3-axis accelerometer in the cone tip.…”

Section: Slow Dynamic Penetrometersmentioning

confidence: 99%

“…The second variation created by Nazarian et al (1999) the "Instrumented DCP," was outfitted with a high speed load cell and a single axis accelerometer at the top of the penetrometer rod (where the drop hammer impacts it). The accelerometer was used to determine the time versus velocity and depth data (by single and double integration respectively) and the load cell measured the dynamic force.…”

Section: Slow Dynamic Penetrometersmentioning

confidence: 99%

A review of penetrometers for subsurface access on comets and asteroids

Glaser¹,

Ball²,

Zacny³

2008

Abstract-The characterization of comet and asteroid interiors will eventually require in situ exploration with drills, penetrators/penetrometers, hypervelocity impactors, excavators or other devices. Because they offer desirable scientific capabilities and relative mechanical simplicity, penetrators and penetrometers, which use only axial force to push beneath the surface, are a good choice for near-term missions. Penetrometers are instruments, generally deployed from a larger vehicle, that measure subsurface mechanical properties and may also contain additional scientific instruments. There are three basic types: "fast" penetrometers are released from above and plunge into the surface. Static and dynamic (collectively referred to as "slow") penetrometers use, respectively, a constant slow penetration speed and periodic hammering impulses. The low gravity environment of asteroids and comets presents a key challenge to instrument deployment and also greatly affects the mechanical properties of surface materials, and in turn penetrometer performance. The Rosetta mission, currently en route to comet 67P/Churyumov-Gerasimenko, will be the next mission to try both fast and slow, dynamic penetrometry, when it arrives in 2014. We present some new concepts of static penetrometers for small body exploration that are adapted to the low gravity environment. The low gravity environment also presents challenges for the testing of penetrometers on Earth and a number of previous solutions are described and new methods suggested. In the next generation of missions to study comets and asteroids, penetrometers could provide important data on their mechanical, seismic, thermal, electromagnetic, and chemical characteristics, as well as sample collection.

Computer aided Civil Eng

“…Initially, Langton (1999) introduced a lightweight DCP to measure cone resistance using the energy transferred at the anvil, a technique further refined in subsequent studies (Athapaththu et al, 2007;Tsuchida et al, 2011). In addition, Nazarian et al (2000) developed a DCP equipped with a load cell and an accelerometer on its anvil. Expanding upon these advancements, Byun and Lee (2013) developed an instrumented DCP (IDCP), which measures the energy transmitted at the anvil and cone tip.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, Nazarian et al. (2000) developed a DCP equipped with a load cell and an accelerometer on its anvil. Expanding upon these advancements, Byun and Lee (2013) developed an instrumented DCP (IDCP), which measures the energy transmitted at the anvil and cone tip.…”

Section: Introductionmentioning

confidence: 99%

Automated signal‐based evaluation of dynamic cone resistance via machine learning for subsurface characterization

Aregbesola,

Byun

2024

Dynamic cone resistance (DCR) is a recently introduced soil resistance index that has the unit of stress. It is determined from the dynamic response at the tip of an instrumented dynamic cone penetrometer. However, DCR evaluation is generally a manual, time‐consuming, and error‐prone process. Thus, this study investigates the feasibility of determining DCR using a stacked ensemble (SE) machine learning (ML) model that utilizes signals obtained from dynamic cone penetration testing. Two ML experiments revealed that using only force signals provides more accurate predictions of DCR. In addition, the SE technique outperformed the base learning algorithms in both cases. Overall, the findings suggest that ML techniques can be used to automate the analysis of DCR with force and acceleration signals.