Study on the relationship between fractal dimension and …
As a subsoil for many offshore structures, marine coral sand can encounter various impact loads, resulting in particle fragmentation.The "fractal theory" is an excellent method to quantify particle fragmentation. However, the relationship between the fractal dimension and relative breakage as well as its influencing factors are somewhat limited …
Effective Molecular Descriptors for Chemical Accuracy at DFT …
Effective Molecular Descriptors for Chemical Accuracy at DFT Cost: Fragmentation, Error-Cancellation, and Machine Learning J Chem Theory Comput . 2020 Aug 11;16(8):4938-4950. doi: 10.1021/acs.jctc.0c00236.
A machine learning approach to mitigating …
fiber. Finally, we develop a parameterized machine learning-assisted fragmentation avoidance (MLFA) algorithm that leverages information on predicted traffic from the ENN and the resource model to address the dual challenges of spectrum fragmentation and crosstalk. The rest of this paper is organized as follows. Following …
Numerical simulation on effects of embedded crack on rock fragmentation
Based on the simplification of cutting process, a series of numerical simulations were conducted using a 2-D discrete element method to explore the effects of embedded cracks with different dip angles on the rock fragmentation process, cutting characteristics and breaking efficiency. The results show that the simulated results are in …
Modeling the fragmentation of rock grains using computed tomography …
The most influential factors in determining the fragmentation patterns of rock or sand grains were found to be the grain morphology and initial microstructure [67]. The fracture process was also confirmed to be affected by the mineralogy. However, to reduce the complexity of this study and highlight the influence of morphology, all grains …
Insights into the Effect of Water Content on Mudstone …
In the Tunnel Boring Machines (TBMs) construction of soft rock tunnels, adverse geological conditions, such as water-rich and ... investigated the effects of pre-set indentation depth on sand - stone fragmentation through a series of laboratory indenta-tion tests. Liu et al. (2020) studied the eect of water content ...
A novel ensemble machine learning model to predict mine
This investigation aims at predicting rock fragmentation through a new ansemble technique, namely light gradient-boosting machine (LightGBM) with its hyper …
Landscape Change and Associated Increase in Habitat Fragmentation …
Anthropic pressures affect the evolution of landscapes over time generating changes in their spatial patterns (Laurance et al. 2011; Fahrig 2013; Wang and Caldas 2014).One of the main consequences of these pressures is the habitat loss associated with landscape fragmentation, where different types of natural habitats are reduced and …
Machine Learning-based Design of Software to Calculate the
The fragmentation power is an important parameter to characterize the performance of a combatant. At present, the fragmentation power is mainly calculated by empirical formulae or simulation analysis, which has problems such as large calculation volume, slow calculation speed and low efficiency. In this paper, a machine learning …
(PDF) Artificial Intelligence Techniques for Prediction of …
In hard rock excavation, drilling and blasting is commonly used for loosening rock. Optimum rock fragmentation due to blasting is desirable for downstream operation productivity.
Experimental and Numerical Studies of High-Velocity Impact Fragmentation
Some basic theories have emerged within the past 10 years for predicting the consequences of dynamic fragmentation brought about by high-velocity impact or explosive events. These theories have focused principally on the prediction of mean fragment size through...
A Fragmentation Machine for Revolutionary Waste Disposal
World's first large-scale hydrogen-ready engine power plant
Enhancing rock fragmentation assessment in mine blasting …
The optimization of blasting operations greatly benefits from the prediction of rock fragmentation. The main factors that affect fragmentation are rock mass characteristics, blast geometry, and explosive properties. This paper is a step towards the implementation of machine learning and deep learning algorithms for predicting the …
Design and Fabrication of Automated Sand Filter and Waste Separator Machine
DOI: 10.22214/IJRASET.2021.33236 Corpus ID: 233615505; Design and Fabrication of Automated Sand Filter and Waste Separator Machine @article{Chandramohan2021DesignAF, title={Design and Fabrication of Automated Sand Filter and Waste Separator Machine}, author={Vikram Chandramohan}, …
Optimization of the drilling-and-blasting process to …
In most of the cases, the cheapest way to improve the fragmentation of the ore is by changing the drilling-and-blasting design parameters. It of course increases the mining …
Toward High-level Machine Learning Potential for Water …
Toward High-level Machine Learning Potential for Water Based on Quantum Fragmentation and Neural Networks J Phys Chem A. 2022 Jun 23;126(24):3926-3936. doi: 10.1021/acs.jpca.2c00601. ... we develop a deep machine learning potential based on fragment-based second-order Møller-Plesset perturbation theory (DP-MP2) for water …
A method of blasted rock image segmentation based on …
A practical method of bench blasting design for desired fragmentation based on digital image processing technique and Kuz-Ram model. In Rock Fragm. by …
CN208627424U
A kind of sand making machine being able to ascend breaking capacity, including being located at intracorporal first fragmentation cell of shell, multiple second fragmentation cells, and the shaft being vertically arranged, first fragmentation cell is located between case top and the second fragmentation cell of top layer, first fragmentation cell …
Blasting profile evaluation of sand-mud interbedded
Abstract. The sand-mud interbedded surrounding rock contains discontinuities, such as horizontal bedding, joints, weak planes and weak interlayers. …
Enhancing Rock Fragmentation Assessment in Mining …
The main factors that affect fragmentation are rock mass characteristics, blast geometry, and explosive properties. This paper is a step towards the implementation of machine learning and deep learning algorithms for predicting the extent of fragmentation (in percentage) in opencast mining. Various parameters can affect …
Sustainability | Free Full-Text | Experiment Study of …
Stemming length and stemming materials are crucial factors in blasting design, which affect the sustainability of mining. This study investigates the influence of stemming length and stemming material on rock fragmentation, stemming recoil, and surface strain response through 15 small-scale model blasting tests. The results indicate …
[PDF] DEM modeling of the one-dimensional compression of sands …
DOI: 10.1139/CGJ-2020-0308 Corpus ID: 234885232; DEM modeling of the one-dimensional compression of sands incorporating a statistical particle fragmentation scheme @article{Wu2021DEMMO, title={DEM modeling of the one-dimensional compression of sands incorporating a statistical particle fragmentation scheme}, …
Assessment of the ground vibration during blasting in …
The investigation compares the conventional, advanced machine, deep, and hybrid learning models to introduce an optimum computational model to assess the …
Assessment of the ground vibration during blasting in …
The investigation compares the conventional, advanced machine, deep, and hybrid learning models to introduce an optimum computational model to assess the ground vibrations during blasting in ...
A Machine-Learning Approach for Detection and Quantification …
Objective: Fragmented QRS (fQRS) is an accessible biomarker and indication of myocardial scarring that can be detected from the electrocardiogram (ECG). Nowadays, fQRS scoring is done on a visual basis, which is time consuming and leads to subjective results. This study proposes an automated method to detect and quantify fQRS in a continuous way …
Sustainability | Free Full-Text | Investigation on the Confined …
Calcareous sand, ubiquitous in the geotechnical makeup of the South China Sea, exhibits both compressibility and vulnerability to fragmentation when subjected to external loading, spanning a spectrum from typical to extreme conditions. This investigation aims to quantitatively assess the compression and particle breakage characteristics of …
Modeling the fragmentation of rock grains using computed …
Computed tomography (CT) and the combined finite discrete element method (FDEM) are used to investigate the fragmentation of rock grains. Fracture …
Folding Travel Bikes using S and S Machine Bicycle Torque …
S&S Couplings ™. It is now possible to purchase professional quality, full size travel bicycles, including tandems, from over 100 independent bicycle framebuilders. If you have a passion for cycling and would like to take your favorite bike along as regular luggage when you travel, please check us out!. Greg LeMond comments regarding his S and S …
(PDF) Enhancing Rock Fragmentation Assessment in Mining …
Enhancing Rock Fragmentation Assessment in Mining Blasting through Machine Learning Algorithms: An Effective Approach June 2023 DOI: 10.20944/preprints202306.0891.v1
The Historic Innovation of Land Mines—And Why We've …
A second machine will then enter the area to excavate the mines. ... The deminer will pick up all the fragmentation, the metal in the ground, but the rat picks up only the smell of TNT." ...