Visual Simulation Study of Pick Loads on Continuous Miner

2008 ◽  
Vol 392-394 ◽  
pp. 471-475 ◽  
Author(s):  
Xiao Huo Li ◽  
X.H. Ma
Keyword(s):  
Computer Aided Design ◽  
Structural Parameters ◽  
Cutting Parameters ◽  
Economic Benefits ◽  
Rock Properties ◽  
Cutting Mechanism ◽  
Design Quality ◽  
Continuous Miner ◽  
Wear And Tear ◽  
And Performance

A continuous miner is one of wall mechanized coal face; its design quality and performance have directly effect on coal productivity and economic benefits. A pick on a continuous miner, contacting with coal and rock, is a tool cutting directly coal and rock, its force condition during it cuts determines directly loads of the cutting mechanism, pick wear and tear, fabric vibration and cutting performance of the machine, is the basis for the design of a continuous miner. By considering a variety of factors, a mathematical model, including the coal and rock properties, structural parameters of a pick, pick sequence, cutting parameters of the continuous miner, is established in the paper, visualization software which can be directly reflected pick' forces on the continuous miner is design. On this basis, pick' forces of a continuous miner under different working conditions are simulated and studied, which create conditions for understanding pick' force during cutting process of a continuous miner, computer-aided design of the cutting mechanism, dynamic design and research of the machine.

scholarly journals Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit

Geosciences ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 150
Author(s):  
Nilgün Güdük ◽  
Miguel de la Varga ◽  
Janne Kaukolinna ◽  
Florian Wellmann
Keyword(s):  
Structural Parameters ◽  
Rock Properties ◽  
Magnetic Data ◽  
Geological Model ◽  
Borehole Data ◽  
Likelihood Functions ◽  
Different Types ◽  
Geophysical Information ◽  
Different Sources

Structural geological models are widely used to represent relevant geological interfaces and property distributions in the subsurface. Considering the inherent uncertainty of these models, the non-uniqueness of geophysical inverse problems, and the growing availability of data, there is a need for methods that integrate different types of data consistently and consider the uncertainties quantitatively. Probabilistic inference provides a suitable tool for this purpose. Using a Bayesian framework, geological modeling can be considered as an integral part of the inversion and thereby naturally constrain geophysical inversion procedures. This integration prevents geologically unrealistic results and provides the opportunity to include geological and geophysical information in the inversion. This information can be from different sources and is added to the framework through likelihood functions. We applied this methodology to the structurally complex Kevitsa deposit in Finland. We started with an interpretation-based 3D geological model and defined the uncertainties in our geological model through probability density functions. Airborne magnetic data and geological interpretations of borehole data were used to define geophysical and geological likelihoods, respectively. The geophysical data were linked to the uncertain structural parameters through the rock properties. The result of the inverse problem was an ensemble of realized models. These structural models and their uncertainties are visualized using information entropy, which allows for quantitative analysis. Our results show that with our methodology, we can use well-defined likelihood functions to add meaningful information to our initial model without requiring a computationally-heavy full grid inversion, discrepancies between model and data are spotted more easily, and the complementary strength of different types of data can be integrated into one framework.

scholarly journals Identification of abnormal tribological regimes using a microphone and semi-supervised machine-learning algorithm

Friction ◽  
2021 ◽  
Author(s):  
Vigneashwara Pandiyan ◽  
Josef Prost ◽  
Georg Vorlaufer ◽  
Markus Varga ◽  
Kilian Wasmer
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Industrial Applications ◽  
Supervised Machine Learning ◽  
Normal Operation ◽  
Promising Alternative ◽  
Wear And Tear ◽  
Validation Procedure ◽  
And Performance

AbstractFunctional surfaces in relative contact and motion are prone to wear and tear, resulting in loss of efficiency and performance of the workpieces/machines. Wear occurs in the form of adhesion, abrasion, scuffing, galling, and scoring between contacts. However, the rate of the wear phenomenon depends primarily on the physical properties and the surrounding environment. Monitoring the integrity of surfaces by offline inspections leads to significant wasted machine time. A potential alternate option to offline inspection currently practiced in industries is the analysis of sensors signatures capable of capturing the wear state and correlating it with the wear phenomenon, followed by in situ classification using a state-of-the-art machine learning (ML) algorithm. Though this technique is better than offline inspection, it possesses inherent disadvantages for training the ML models. Ideally, supervised training of ML models requires the datasets considered for the classification to be of equal weightage to avoid biasing. The collection of such a dataset is very cumbersome and expensive in practice, as in real industrial applications, the malfunction period is minimal compared to normal operation. Furthermore, classification models would not classify new wear phenomena from the normal regime if they are unfamiliar. As a promising alternative, in this work, we propose a methodology able to differentiate the abnormal regimes, i.e., wear phenomenon regimes, from the normal regime. This is carried out by familiarizing the ML algorithms only with the distribution of the acoustic emission (AE) signals captured using a microphone related to the normal regime. As a result, the ML algorithms would be able to detect whether some overlaps exist with the learnt distributions when a new, unseen signal arrives. To achieve this goal, a generative convolutional neural network (CNN) architecture based on variational auto encoder (VAE) is built and trained. During the validation procedure of the proposed CNN architectures, we were capable of identifying acoustics signals corresponding to the normal and abnormal wear regime with an accuracy of 97% and 80%. Hence, our approach shows very promising results for in situ and real-time condition monitoring or even wear prediction in tribological applications.

Design and Fabrication of Stirling Engine for Solar Power Application

2021 ◽  
Vol 143 (11) ◽  
Author(s):  
Muhammad Hassan ◽  
Hussain Ahmed Tariq ◽  
Muhammad Anwar ◽  
Talha Irfan Khan ◽  
Asif Israr
Keyword(s):  
Computer Aided Design ◽  
Peak Power ◽  
Stirling Engine ◽  
Working Fluid ◽  
Cad Model ◽  
Stroke Length ◽  
And Performance ◽  
Power Application ◽  
Aided Design ◽  
Alpha Type

Abstract This paper showcases the designing, fabrication, and performance evaluation of 90-deg alpha-type Stirling engine. The diameters of the hot and cold cylinder are 50 mm and 44 mm, respectively, with a stroke length of 70 mm. The computer-aided design (CAD) model is developed by keeping in mind the ease of manufacturing, maintenance, bearing replacements, and lubrication. After fabrication, the engine is tested by heating the hot cylinder with air as a working fluid. The engine delivered peak power of 155 watts at the temperature of 1123 K and 968 K for hot and cold cylinders, respectively. This developed prototype can be commissioned with the solar parabolic concentrator in the future based on the smooth operation while delivering power.

Improving creative self-efficacy and performance through computer-aided design application

2019 ◽  
Vol 31 ◽  
pp. 103-111 ◽  
Author(s):  
Yu-shan Chang ◽  
Mavis Yi-Ching Chen ◽  
Meng-Jung Chuang ◽  
Chia-hui Chou
Keyword(s):  
Self Efficacy ◽  
Computer Aided Design ◽  
Computer Aided ◽  
And Performance ◽  
Creative Self ◽  
Aided Design

scholarly journals DEVELOPMENT OF THE BASIC CAPACITIVE ACCELEROMETERS MODELS BASED ON THE VHDL-AMS LANGUAGE FOR THE CIRCUIT LEVEL OF COMPUTER-AIDED DESIGN

2020 ◽  
Vol 2 (1) ◽  
pp. 15-20
Author(s):  
V. M. Teslyuk ◽  
◽  
P. Yu. Denysyuk ◽  
T. V. Teslyuk ◽  
◽  
...  
Keyword(s):  
Differential Equations ◽  
Computer Aided Design ◽  
Structural Parameters ◽  
Software Systems ◽  
Mems Devices ◽  
Electric Circuits ◽  
Capacitive Accelerometer ◽  
Level Of Automation ◽  
Electric Parameters ◽  
Physical Principles

In the article, the basic VHDL-AMS models of MEMS-based capacitive accelerometers were developed. The models were designed for two basic types of capacitive accelerometers, namely lamellar and counter-pivotal. The developed models allow us to determine the source of electrical capacitive accelerometers depending on the incoming mechanical and structural parameters and were constructed for MEMS CAD at the circuit level. The circuit level of MEMS development requires an analysis of the total integrated device electric circuits. For this purpose, all the MEMS components should be written in the specific software systems, which would be understandable for the software system. Taking into account that MEMS devices operate on different physical principles, certain difficulties may arise during the electrical analysis, that is, the work of mechanical or other devices need to be described with the help of electric parameters. In the general case, the method for building the VHDL-AMS model of the MEMS-based capacitive accelerometer is needed construction of the simplified mechanical model, and then a simplified electrical model. On the basis of the simplified models, the VHDL-AMS model of electromechanical MEMS devices has been developed. In the article, the method of automated synthesis and mathematical models using the VHDL-AMS language, which is based on the method of electrical analogies were described. They use systems of ordinary differential equations and partial differential equations to determine the relationships between input and output parameters. The sequence and quantity of used differential equations are determined by the physical principles of operation of the MEMS element and the number of energy transformations, which allows increasing the level of automation of synthesis operations compared to existing methods. The results of the basic lamellar and counter-pivotal capacitive accelerometers are also shown. This enables to conduct research and analysis of its parameters and investigate the output electric parameters dependence on the input mechanical ones.

Using Learning Analytics to Enhance Student Learning in Online Courses Based on Quality Matters Standards

2016 ◽  
Vol 45 (2) ◽  
pp. 165-187 ◽  
Author(s):  
Florence Martin ◽  
Abdou Ndoye ◽  
Patricia Wilkins
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Online Course ◽  
Design Quality ◽  
Descriptive Data ◽  
Quality Matters ◽  
Frequency Of Use ◽  
And Performance ◽  
Enhance Student Learning

Quality Matters is recognized as a rigorous set of standards that guide the designer or instructor to design quality online courses. We explore how Quality Matters standards guide the identification and analysis of learning analytics data to monitor and improve online learning. Descriptive data were collected for frequency of use, time spent, and performance and analyzed to identify patterns and trends on how students interact with online course components based on the Quality Matters standards. Major findings of this article provide a framework and guidance for instructors on how data might be collected and analyzed to improve online learning effectiveness.

VESPER: Visual Exploration of Similarity and Performance Metrics for Computer-Aided Design Repositories

2018 ◽  
Author(s):  
Devarajan Ramanujan ◽  
William Z. Bernstein
Keyword(s):  
Visual Analytics ◽  
Computer Aided Design ◽  
Performance Metrics ◽  
External Validation ◽  
Visual Exploration ◽  
Similarity Metrics ◽  
Report Generation ◽  
Computer Aided ◽  
And Performance ◽  
Aided Design

VESPER (Visual Exploration of Similarity and PERformance) is a visual analytics system for exploring similarity metrics and performance metrics derived from computer-aided design (CAD) repositories. It consists of (1) a data processing module that allows analysts to input custom similarity metrics and performance metrics, (2) a visualization module that facilitates navigation of the design spaces through coordinated, interactive visualizations, and (3) a report generation module that allows analysts to export lifecycle data of selected repository items as well as the input metrics for further external validation. In this paper, we discuss the need, design rationale, and implementation details for VESPER. We then apply VESPER to (1) sustainability-focused exploration of parts, and (2) exploration of tool wear and surface roughness in machined parts.

3D PRINTING OF PHARMACEUTICALS – LEADING TREND IN PHARMACEUTICAL INDUSTRY AND FUTURE PERSPECTIVES

2020 ◽  
pp. 10-16
Author(s):  
SHANKHADIP NANDI
Keyword(s):  
Drug Delivery ◽  
Pharmaceutical Industry ◽  
3D Printing ◽  
Computer Aided Design ◽  
Release Kinetics ◽  
Research Work ◽  
Economic Benefits ◽  
Pharmaceutical Products ◽  
Dosage Forms ◽  
Fused Deposition

3D printing technology is a rapid prototyping process based on computer-aided design software that is proficient to construct solid objects with various geometrics by depositing numerous layers in a sequence. The major advantages of three-dimensional printing (3DP) technology over the traditional manufacturing of pharmaceuticals include the customization of medications with individually adjusted doses, on-demand tailored manufacturing, unprecedented flexibility in the design, manufacturing of complex and sophisticated solid dosage forms, and economic benefits. Recently, many researchers have been invested their efforts in applying 3DP technology to the pharmaceutical development of drug products and different drug delivery systems. Selective laser sintering, fused deposition modeling, semi-solid extrusion, stereolithography, etc., are the multiple 3DP technologies that can be established in several customized and programmable medicines. Sublingual, orodispersible, and fast-dissolving drug delivery formulations by 3DP technology have been already manufactured. Controlled-release formulations with different characteristics, doughnut-shaped multi-layered tablets with linear release kinetics, and drug-loaded tablets with modified-release characteristics are recently fabricated using 3DP. However, few 3DP methods produce uneven shapes of dosage forms and comparatively porous structures. Cost of transition, adaptation to the existing facility, achieving regulatory approval, etc., are the present challenges that can restrict the extensive application of 3DP technology to pharmaceutical products. Intense research work for modifying the 3DP methods is simultaneously sustained for by-passing the flaws and current limitations of this technology. 3DP technology can act as a convenient and potential tool for the pharmaceutical industry which will set a revolutionary manufacturing style in the near future to facilitate patient-centered health care.

scholarly journals Numerical Simulation of Conical Pick Cutting Arc Rock Plate Fracture Based on ANSYS/LS-DYNA

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Zhiwen Wang ◽  
Qingliang Zeng ◽  
Zhenguo Lu ◽  
Lirong Wan ◽  
Xin Zhang ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Cutting Force ◽  
Structural Parameters ◽  
Cutting Parameters ◽  
Rock Breaking ◽  
Central Axis ◽  
Plate Height ◽  
Conical Pick ◽  
Cutting Angle ◽  
Cutting Point

The new method of rock breaking based on the combination of circular sawblade and conical pick was proposed to improve the effectiveness of hard rock breaking. The numerical simulation method was applied to research the conical pick cutting arc rock plate by ANSYS/LS-DYNA. The conical pick cutting arc rock plate numerical simulation model was established to research the influence of arc rock plate structural parameters and cutting parameters on cracks formation and propagation of the arc rock plate and the cutting force in the process of conical pick cutting arc rock plate. The amount of cracks is positively correlated with arc rock plate thickness, the cutting speed, and distance of cutting point to arc rock plate central axis and negatively correlated with the cutting angle. The mean peak cutting force is positively correlated with the thickness of arc rock plate and the distance of cutting point to arc rock plate central axis; however, it is negatively correlated with the arc rock plate height and width and cutting angle of conical pick. The simulation results can be used to predict the conical pick work performance with various cutting parameters and structural parameters.

Reuse of open data in Quebec: from economic development to government transparency

2020 ◽  
pp. 002085231988462
Author(s):  
Christian Boudreau
Keyword(s):  
Open Data ◽  
Economic Benefits ◽  
Point Of View ◽  
Data Reuse ◽  
Digital Data ◽  
Government Transparency ◽  
History Of ◽  
Government Data ◽  
And Performance ◽  
Opening Up

Based on the history of open data in Quebec, this article discusses the reuse of these data by various actors within society, with the aim of securing desired economic, administrative and democratic benefits. Drawing on an analysis of government measures and community practices in the field of data reuse, the study shows that the benefits of open data appear to be inconclusive in terms of economic growth. On the other hand, their benefits seem promising from the point of view of government transparency in that it allows various civil society actors to monitor the integrity and performance of government activities. In the age of digital data and networks, the state must be seen not only as a platform conducive to innovation, but also as a rich field of study that is closely monitored by various actors driven by political and social goals. Points for practitioners Although the economic benefits of open data have been inconclusive so far, governments, at least in Quebec, must not stop investing in opening up their data. In terms of transparency, the results of the study suggest that the benefits of open data are sufficiently promising to continue releasing government data, if only to support the evaluation and planning activities of public programmes and services.

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