scholarly journals A Novel Approach for Measuring the Thickness of Refractory of Metallurgical Vessels

Materials ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 5645
Author(s):  
Yao Ge ◽  
Ying Li ◽  
Han Wei ◽  
Hao Nie ◽  
Weitian Ding ◽  
...  
Keyword(s):  
Relative Error ◽  
Wall Thickness ◽  
Electromagnetic Waves ◽  
Refractory Lining ◽  
Small Scale ◽  
Ultrasonic Tomography ◽  
Blast Furnaces ◽  
Refractory Wall ◽  
Novel Approach ◽  
Thickness Prediction

The advancement of metallurgical vessels, such as blast furnaces, shaft furnaces, and torpedo ladles, can be better controlled and expanded for a greater lifespan if the thickness of the refractory lining wear is known and predicted. In the past, various methods including radioactive tracers, infrared (IR) thermography, electromagnetic waves, ultrasonic tomography, and temperature field have been tested to determine the thickness of the refractory wall. However, for various reasons, these methods have failed to be effective. This paper presents a novel method—electromotive force (EMF)—for predicting the thickness of refractory lining wear in vessels, including a small-scale vessel in the laboratory, an industrial torpedo ladle, and in the two refining hearths of blast furnaces. The experimental results show that the magnitude of the EMF signal increases with a decrease in wall thickness. Prediction values of the refractory wall thickness are consistent with measured ones. The relative error of EMF measurement for the torpedo ladle is around 6.8%. The EMF measurement of blast furnace hearths is quite accurate, and the relative error is less than 11%.

A modified physical model of high-strength water hydraulic artificial muscles considering the effects of geometry and material properties

2021 ◽  
pp. 095440622199907
Author(s):  
Zengmeng Zhang ◽  
Jinkai Che ◽  
Peipei Liu ◽  
Yunrui Jia ◽  
Yongjun Gong
Keyword(s):  
Physical Model ◽  
Relative Error ◽  
Wall Thickness ◽  
Material Properties ◽  
High Strength ◽  
Artificial Muscles ◽  
Operating Pressure ◽  
Rubber Tube ◽  
Contraction Ratio ◽  
Water Hydraulic

Compared with pneumatic artificial muscles (PAMs), water hydraulic artificial muscles (WHAMs) have the advantages of high force/weight ratio, high stiffness, rapid response speed, large operating pressure range, low working noise, etc. Although the physical models of PAMs have been widely studied, the model of WHAMs still need to be researched for the different structure parameters and work conditions between PAMs and WHAMs. Therefore, the geometry and the material properties need to be considered in models, including the wall thickness of rubber tube, the geometry of ends, the elastic force of rubber tube, the elongation of fibers, and the friction among fiber strands. WHAMs with different wall thickness and fiber materials were manufactured, and static characteristic experiments were performed when the actuator is static and fixed on both ends, which reflects the relationship between contraction force and pressure under the different contraction ratio. The deviations between theoretical values and experimental results were analyzed to investigate the effect of each physical factor on the modified physical model accuracy at different operating pressures. The results show the relative error of the modified physical model was 7.1% and the relative error of the ideal model was 17.4%. When contraction ratio is below 10% and operating pressure is 4 MPa, the wall thickness of rubber tube was the strongest factor on the accuracy of modified model. When the WHAM contraction ratio from 3% to 20%, the relative error between the modified physical model and the experimental data was within ±10%. Considering the various physical factors, the accuracy of the modified physical model of WHAM is improved, which lays a foundation of non-linear control of the high-strength, tightly fiber-braided and thick-walled WHAMs.

scholarly journals A New Prototype for Automatic Identification of Stone Block Internal Structure

2021 ◽  
Vol 11 (14) ◽  
pp. 6630
Author(s):  
Bernardo Anes ◽  
Joao Figueiredo ◽  
Mouhaydine Tlemçani
Keyword(s):  
Internal Structure ◽  
Empirical Method ◽  
Automatic Process ◽  
Automatic Identification ◽  
Ultrasonic Tomography ◽  
Stone Block ◽  
Novel Approach ◽  
Process Measurements ◽  
Automatic Positioning ◽  
Non Destructive

Nowadays, the inner shape and economic viability of a stone block is dependent on the skill and experience of the “expert” that makes predictions based on external observations. This actual procedure is an extremely high empirical method, and when it fails, substantial work, time, and money is wasted. At present, researchers are committed to developing models to predict the stone block internal structure based on non-destructive tests. Ultrasonic tomography and electrical resistivity tomography are the tests that best fit these objectives. Trying to improve the existing procedures for collecting stone information and data exporting, a novel approach to perform both tomographies is proposed in this paper. This novel approach presents sound advantages regarding the current manual procedure: namely, (i) high accuracy due to a new automatic positioning system; (ii) no need for highly skilled operators to process measurements; (iii) measurements are much easier to derive, and results are quickly delivered. A comparison between the new automatic process and the current manual procedure shows that the manual procedure has a very low accuracy when compared to the new developed automatic system. The automatic measurements show extremely significant time savings, which is a relevant issue for the future competitiveness of the stone sector.

Development of a Predictive Equation for Ventilation in a Wall-Solar Chimney System

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
David Park ◽  
Francine Battaglia
Keyword(s):  
Mathematical Model ◽  
Relative Error ◽  
Natural Ventilation ◽  
Thermal Conditions ◽  
Ambient Air ◽  
Maximum Error ◽  
Scale Model ◽  
Small Scale ◽  
Maximum Relative Error ◽  
Solar Chimney

A solar chimney is a natural ventilation technique that has potential to save energy consumption as well as to maintain the air quality in a building. However, studies of buildings are often challenging due to their large sizes. The objective of this study was to determine the relationships between small- and full-scale solar chimney system models. Computational fluid dynamics (CFD) was employed to model different building sizes with a wall-solar chimney utilizing a validated model. The window, which controls entrainment of ambient air for ventilation, was also studied to determine the effects of window position. A set of nondimensional parameters were identified to describe the important features of the chimney configuration, window configuration, temperature changes, and solar radiation. Regression analysis was employed to develop a mathematical model to predict velocity and air changes per hour, where the model agreed well with CFD results yielding a maximum relative error of 1.2% and with experiments for a maximum error of 3.1%. Additional wall-solar chimney data were tested using the mathematical model based on random conditions (e.g., geometry, solar intensity), and the overall relative error was less than 6%. The study demonstrated that the flow and thermal conditions in larger buildings can be predicted from the small-scale model, and that the newly developed mathematical equation can be used to predict ventilation conditions for a wall-solar chimney.

scholarly journals The relationship between small-scale and large-scale ionospheric electron density irregularities generated by powerful HF electromagnetic waves at high latitudes

2006 ◽  
Vol 24 (11) ◽  
pp. 2901-2909 ◽  
Author(s):  
E. D. Tereshchenko ◽  
B. Z. Khudukon ◽  
M. T. Rietveld ◽  
B. Isham ◽  
T. Hagfors ◽  
...  
Keyword(s):  
Geomagnetic Field ◽  
Electromagnetic Waves ◽  
Large Scale ◽  
Small Scale ◽  
Direction Parallel ◽  
Model Calculations ◽  
Amplitude Fluctuations ◽  
Field Lines ◽  
Experimental Values ◽  
Magnetic Zenith

Abstract. Satellite radio beacons were used in June 2001 to probe the ionosphere modified by a radio beam produced by the EISCAT high-power, high-frequency (HF) transmitter located near Tromsø (Norway). Amplitude scintillations and variations of the phase of 150- and 400-MHz signals from Russian navigational satellites passing over the modified region were observed at three receiver sites. In several papers it has been stressed that in the polar ionosphere the thermal self-focusing on striations during ionospheric modification is the main mechanism resulting in the formation of large-scale (hundreds of meters to kilometers) nonlinear structures aligned along the geomagnetic field (magnetic zenith effect). It has also been claimed that the maximum effects caused by small-scale (tens of meters) irregularities detected in satellite signals are also observed in the direction parallel to the magnetic field. Contrary to those studies, the present paper shows that the maximum in amplitude scintillations does not correspond strictly to the magnetic zenith direction because high latitude drifts typically cause a considerable anisotropy of small-scale irregularities in a plane perpendicular to the geomagnetic field resulting in a deviation of the amplitude-scintillation peak relative to the minimum angle between the line-of-sight to the satellite and direction of the geomagnetic field lines. The variance of the logarithmic relative amplitude fluctuations is considered here, which is a useful quantity in such studies. The experimental values of the variance are compared with model calculations and good agreement has been found. It is also shown from the experimental data that in most of the satellite passes a variance maximum occurs at a minimum in the phase fluctuations indicating that the artificial excitation of large-scale irregularities is minimum when the excitation of small-scale irregularities is maximum.

scholarly journals Optimisation of confinement in a fusion reactor using a nonlinear turbulence model

2018 ◽  
Vol 84 (2) ◽  
Author(s):  
E. G. Highcock ◽  
N. R. Mandell ◽  
M. Barnes ◽  
W. Dorland
Keyword(s):  
First Principles ◽  
Figure Of Merit ◽  
Large Scale ◽  
Unit Volume ◽  
Fusion Reactor ◽  
Small Scale ◽  
Zonal Flows ◽  
Novel Approach ◽  
First Time ◽  
Turbulent Cascade

The confinement of heat in the core of a magnetic fusion reactor is optimised using a multidimensional optimisation algorithm. For the first time in such a study, the loss of heat due to turbulence is modelled at every stage using first-principles nonlinear simulations which accurately capture the turbulent cascade and large-scale zonal flows. The simulations utilise a novel approach, with gyrofluid treatment of the small-scale drift waves and gyrokinetic treatment of the large-scale zonal flows. A simple near-circular equilibrium with standard parameters is chosen as the initial condition. The figure of merit, fusion power per unit volume, is calculated, and then two control parameters, the elongation and triangularity of the outer flux surface, are varied, with the algorithm seeking to optimise the chosen figure of merit. A twofold increase in the plasma power per unit volume is achieved by moving to higher elongation and strongly negative triangularity.

scholarly journals Automating XFEM Modeling Process for Optimal Failure Predictions

2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
A. Y. Elruby ◽  
Sam Nakhla ◽  
A. Hussein
Keyword(s):  
Finite Element ◽  
Test Data ◽  
Critical Region ◽  
Computational Effort ◽  
Small Scale ◽  
Extended Finite Element ◽  
Novel Approach ◽  
Python Scripting ◽  
Failure Loads ◽  
Failure Predictions

The eXtended Finite Element Method (XFEM) is a versatile method for solving crack propagation problems. Meanwhile, XFEM predictions for crack onset and propagation rely on the stress field which tends to converge at a slower rate than that of displacements, making it challenging to capture critical load at crack onset accurately. Furthermore, identifying the critical region(s) for XFEM nodal enrichments is user-dependent. The identification process can be straightforward for small-scale test specimen while in other cases such as complex structures it can be unmanageable. In this work a novel approach is proposed with three major objectives; (1) alleviate user-dependency; (2) enhance predictions accuracy; (3) minimize computational effort. An automatic critical region(s) identification based on material selected failure criterion is developed. Moreover, the approach enables the selection of optimized mesh necessary for accurate prediction of failure loads at crack initiation. Also, optimal enrichment zone size determination is automated. The proposed approach was developed as an iterative algorithm and implemented in ABAQUS using Python scripting. The proposed algorithm was validated against our test data of unnotched specimens and relevant test data from the literature. The results of the predicted loads/displacements at failure are in excellent agreement with measurements. Crack onset locations were in very good agreement with observations from testing. Finally, the proposed algorithm has shown a significant enhancement in the overall computational efficiency compared to the conventional XFEM. The proposed algorithm can be easily implemented into user-built or commercial finite element codes.

Fitness for Service Assessment of a Metal Loss Using Combination of Small-Scale Testing and DNV RP F101/API579 Procedures

2007 ◽  
Author(s):  
A. Motarjemi
Keyword(s):  
Tensile Properties ◽  
Wall Thickness ◽  
Pressure Vessels ◽  
Small Scale ◽  
Metal Loss ◽  
Remaining Life ◽  
Test Technique ◽  
Failure Pressure ◽  
Destructive Test ◽  
Tensile Data

One of the major issues in the oil and gas industries is occurrence of corrosion on equipments in-service such as tanks, pressure vessels, piping, etc. Metal loss (general/localized) and pitting are amongst the typical corrosion damages. For assessing the significance of metal loss, information such as (a) geometry of the component, (b) a record of thickness measurements (point or profile readings) and (c) tensile properties such as Yield and Tensile strengths, preferably in the vicinity of the metal loss, are required. This information are usually fed into a Fitness for Service (FFS) assessment guideline/recommended practice such as DNV RP-F101 or API579, and a minimum required wall thickness (tmin), failure pressure or remaining life is derived. In the absence of actual tensile data (obtained from a conventional tensile test), specified minimum values (lower-bound), as suggested in the design codes, are currently the only other alternative. However, this paper is aimed at presenting two more alternative techniques; non-destructive test technique called Instrumented Indentation Testing (IIT) or Automated Ball Indenter (ABI) and a semi-destructive test technique, called Micro-Flat tensile (MFT). Both techniques are capable of determining the local tensile properties of the material in the vicinity of the metal loss. Values of the minimum required wall thickness (tmin), failure pressure and remaining life, using tensile data obtained from the IIT, MFT and specified minimum values are compared with the predictions based on the actual tensile data.

scholarly journals Differentiable Reasoning on Large Knowledge Bases and Natural Language

2020 ◽  
Vol 34 (04) ◽  
pp. 5182-5190
Author(s):  
Pasquale Minervini ◽  
Matko Bošnjak ◽  
Tim Rocktäschel ◽  
Sebastian Riedel ◽  
Edward Grefenstette
Keyword(s):  
Natural Language ◽  
Link Prediction ◽  
Question Answering ◽  
Knowledge Bases ◽  
Small Scale ◽  
Reasoning Systems ◽  
Novel Approach ◽  
Real World Datasets ◽  
Interpretable Models ◽  
Machine Reading

Reasoning with knowledge expressed in natural language and Knowledge Bases (KBs) is a major challenge for Artificial Intelligence, with applications in machine reading, dialogue, and question answering. General neural architectures that jointly learn representations and transformations of text are very data-inefficient, and it is hard to analyse their reasoning process. These issues are addressed by end-to-end differentiable reasoning systems such as Neural Theorem Provers (NTPs), although they can only be used with small-scale symbolic KBs. In this paper we first propose Greedy NTPs (GNTPs), an extension to NTPs addressing their complexity and scalability limitations, thus making them applicable to real-world datasets. This result is achieved by dynamically constructing the computation graph of NTPs and including only the most promising proof paths during inference, thus obtaining orders of magnitude more efficient models 1. Then, we propose a novel approach for jointly reasoning over KBs and textual mentions, by embedding logic facts and natural language sentences in a shared embedding space. We show that GNTPs perform on par with NTPs at a fraction of their cost while achieving competitive link prediction results on large datasets, providing explanations for predictions, and inducing interpretable models.

scholarly journals On the Use of Microwave Holography to Detect Surface Defects of Rails and Measure the Rail Profile

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1376 ◽  
Author(s):  
Andrey Zhuravlev ◽  
Vladimir Razevig ◽  
Sergey Ivashov ◽  
Aleksey Skrebkov ◽  
Viktor Alekseev
Keyword(s):  
Experimental Data ◽  
Electromagnetic Waves ◽  
Surface Defects ◽  
Back Propagation ◽  
Surface Profile ◽  
Small Scale ◽  
Radar Images ◽  
Comparable Accuracy ◽  
Radar Measurements ◽  
Object Of Study

The use of microwave holography for detecting rail surface defects is considered in this paper. A brief review of available sources on radar methods for detecting defects on metal surfaces and rails is given. An experimental setup consisting of a two-coordinate electromechanical scanner and a radar with stepped frequency signal in the range from 22.2 to 26.2 GHz is described, with the help of which experimental data were obtained. Fragments of R24 rails with surface defects in their heads were used as the object of study. The radar images of rail defects were obtained by the described method based on back propagation of a wavefront. It is shown that polarization properties of electromagnetic waves can be used to increase the contrast of small-scale surface defects. A method of estimating rail surface profile by radar measurements is given and applied to the experimental data. Comparison of the longitudinal rail head profiles obtained by radar and by direct contact measurements showed that the radar method gives comparable accuracy.

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