A Creep-Fatigue-Oxidation Microcrack Propagation Model for Thermomechanical Fatigue

1992 ◽  
Vol 114 (3) ◽  
pp. 282-288 ◽  
Author(s):  
M. P. Miller ◽  
D. L. McDowell ◽  
R. L. T. Oehmke
Keyword(s):  
Mechanical Strain ◽  
Thermomechanical Fatigue ◽  
Propagation Model ◽  
Additional Time ◽  
Basic Model ◽  
Proposed Model ◽  
Microcrack Propagation ◽  
Creep Fatigue ◽  
Phase Out ◽  
Model Features

A high temperature fatigue (HTF) life prediction model is developed based on the concept of microcrack propagation. The model is used to correlate isothermal HTF and thermomechanical fatigue (TMF) life for the Ni-base superalloy MAR-M247. The mechanical strain versus temperature relationships for the TMF tests include in-phase, out-of-phase, and a counter-clockwise diamond history. The proposed model explicitly accounts for damage from all three HTF damage mechanisms: fatigue, oxidation, and creep. The fatigue and oxidation components are correlated using the ΔJ parameter with an additional time dependence included in the oxidation term. The creep component is correlated using a stress power release rate-type parameter, Cˆ. In this paper, we focus on application of a model to HTF and TMF of Ni-base superalloys. However, the basic model features may well apply to other classes of metallic materials.

Thermomechanical Fatigue Behavior of the Ferritic Stainless Steel

2005 ◽  
Vol 297-300 ◽  
pp. 1146-1151 ◽  
Author(s):  
Keum Oh Lee ◽  
Seong Gu Hong ◽  
Sam Son Yoon ◽  
Soon Bok Lee
Keyword(s):  
Stainless Steel ◽  
Ferritic Stainless Steel ◽  
Low Cycle Fatigue ◽  
Fatigue Behavior ◽  
Strain Range ◽  
Thermomechanical Fatigue ◽  
Propagation Model ◽  
Plastic Strain Range ◽  
Proposed Model ◽  
Life Prediction Model

A thermomechanical fatigue (TMF) life prediction model for ferritic stainless steel, used in exhaust manifold of automobile, was developed based on Tomkins’ two-dimensional crack propagation model. Low-cycle fatigue (LCF) and TMF tests were carried out in a wide temperature range from 200 to 650°C. New concept of plastic strain range on TMF was proposed. Effective stress concept was introduced to get a reasonable stress range in TMF hysteresis loop. The proposed model predicted TMF life within 2X scatter band. The experimental results reveal that TMF life is about 10% of isothermal fatigue life.

A (2 + 1)-dimensional extension of the Benjamin-Ono equation

2018 ◽  
Vol 28 (11) ◽  
pp. 2681-2687 ◽  
Author(s):  
Abdul-Majid Wazwaz
Keyword(s):  
Soliton Solutions ◽  
Traveling Wave Solutions ◽  
Content Type ◽  
Multiple Soliton Solutions ◽  
Proposed Model ◽  
New Findings ◽  
Propagation Of Waves ◽  
Model Features ◽  
Multiple Complex Soliton Solutions ◽  
Practical Implications

Purpose The purpose of this paper is concerned with developing a (2 + 1)-dimensional Benjamin–Ono equation. The study shows that multiple soliton solutions exist and multiple complex soliton solutions exist for this equation. Design/methodology/approach The proposed model has been handled by using the Hirota’s method. Other techniques were used to obtain traveling wave solutions. Findings The examined extension of the Benjamin–Ono model features interesting results in propagation of waves and fluid flow. Research limitations/implications The paper presents a new efficient algorithm for constructing extended models which give a variety of multiple soliton solutions. Practical implications This work is entirely new and provides new findings, where although the new model gives multiple soliton solutions, it is nonintegrable. Originality/value The work develops two complete sets of multiple soliton solutions, the first set is real solitons, whereas the second set is complex solitons.

scholarly journals Rough Set Based Affinity Propagation Model for Prediction of Future Gold Price in Indian Scenario

2019 ◽  
Vol 9 (2) ◽  
pp. 2219-2224
Keyword(s):  
Rough Set ◽  
Arima Model ◽  
Gold Price ◽  
Propagation Model ◽  
Affinity Propagation ◽  
Experimental Result ◽  
Percentage Error ◽  
Support Vector ◽  
Proposed Model ◽  
Gold Silver

In international market, trading of metals has played a vital role. Metal cost might affect the nation’s economy. There are so many base metals available which have been utilized in world trading for construction and manufacturing of goods. Among them gold, silver, platinum, palladium have been treated as precious metals which has economic values. Therefore today’s researchers have concentrated their investigation on metal prediction using diversified algorithms like Auto Regressive Integrated Moving Average (ARIMA), KNN (K-Nearest Neighbor),Artificial Neural Network (ANN) and Support Vector Machine (SVM) etc. In this paper our foremost objective is to predict gold price, so we put our research on this metal. In this work we have employed rough set based affinity propagation algorithm for predicting future gold price and we compared our proposed model with rough set and ARIMA model basing upon the performance measures such as root mean square error (RMSE) and mean absolute percentage error (MAPE). The experimental result shows that the proposed model outperforms rough set and ARIMA model

scholarly journals A Concise Binomial Model for Nonlinear Creep-Fatigue Crack Growth Behavior at Elevated Temperatures

Materials ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 651
Author(s):  
Jianxing Mao ◽  
Zhixing Xiao ◽  
Dianyin Hu ◽  
Xiaojun Guo ◽  
Rongqiao Wang
Keyword(s):  
Fatigue Crack ◽  
Fatigue Crack Growth ◽  
Crack Growth ◽  
Dwell Time ◽  
Elevated Temperatures ◽  
Nonlinear Creep ◽  
Nickel Based Superalloy ◽  
Proposed Model ◽  
Creep Fatigue ◽  
Creep Fatigue Crack

The creep-fatigue crack growth problem remains challenging since materials exhibit different linear and nonlinear behaviors depending on the environmental and loading conditions. In this paper, we systematically carried out a series of creep-fatigue crack growth experiments to evaluate the influence from temperature, stress ratio, and dwell time for the nickel-based superalloy GH4720Li. A transition from coupled fatigue-dominated fracture to creep-dominated fracture was observed with the increase of dwell time at 600 °C, while only the creep-dominated fracture existed at 700 °C, regardless of the dwell time. A concise binomial crack growth model was constructed on the basis of existing phenomenal models, where the linear terms are included to express the behavior under pure creep loading, and the nonlinear terms were introduced to represent the behavior near the fracture toughness and during the creep-fatigue interaction. Through the model implementation and validation of the proposed model, the correlation coefficient is higher than 0.9 on ten out of twelve sets of experimental data, revealing the accuracy of the proposed model. This work contributes to an enrichment of creep-fatigue crack growth data in the typical nickel-based superalloy at elevated temperatures and could be referable in the modeling for damage tolerance assessment of turbine disks.

scholarly journals Propagation Model of Panic Buying Under the Sudden Epidemic

2021 ◽  
Vol 9 ◽  
Author(s):  
Peihua Fu ◽  
Bailu Jing ◽  
Tinggui Chen ◽  
Chonghuan Xu ◽  
Jianjun Yang ◽  
...  
Keyword(s):  
Online Social Networks ◽  
Group Behavior ◽  
Propagation Model ◽  
Release Time ◽  
External Information ◽  
Buying Behavior ◽  
Factors Affecting ◽  
Proposed Model ◽  
Huge Impact ◽  
Number Of Individuals

The sudden outbreak of COVID-19 at the end of 2019 has had a huge impact on people's lives all over the world, and the overwhelmingly negative information about the epidemic has made people panic for the future. This kind of panic spreads and develops through online social networks, and further spreads to the offline environment, which triggers panic buying behavior and has a serious impact on social stability. In order to quantitatively study this behavior, a two-layer propagation model of panic buying behavior under the sudden epidemic is constructed. The model first analyzes the formation process of individual panic from a micro perspective, and then combines the Susceptible-Infected-Recovered (SIR) Model to simulate the spread of group behavior. Then, through simulation experiments, the main factors affecting the spread of panic buying behavior are discussed. The experimental results show that: (1) the dissipating speed of individual panics is related to the number of interactions and there is a threshold. When the number of individuals involved in interacting is equal to this threshold, the panic of the group dissipates the fastest, while the dissipation speed is slower when it is far from the threshold; (2) The reasonable external information release time will affect the occurrence of the second panic buying, meaning providing information about the availability of supplies when an escalation of epidemic is announced will help prevent a second panic buying. In addition, when the first panic buying is about to end, if the scale of the second panic buying is to be suppressed, it is better to release positive information after the end of the first panic buying, rather than ahead of the end; and (3) Higher conformity among people escalates panic, resulting in panic buying. Finally, two cases are used to verify the effectiveness and feasibility of the proposed model.

scholarly journals An Optimization Method for an Integrated Energy System Scheduling Process Based on NSGA-II Improved by Tent Mapping Chaotic Algorithms

Processes ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 426 ◽  
Author(s):  
Shengran Chen ◽  
Shengyan Wang
Keyword(s):  
Economic Dispatch ◽  
Energy System ◽  
Optimization Method ◽  
Nsga Ii ◽  
Tent Map ◽  
Chaos Optimization ◽  
Basic Model ◽  
Proposed Model ◽  
Integrated Energy System ◽  
Supply Equipment

The integrated energy system is a vital part of distributed energy industries. In addition to this, the optimal economic dispatch model, which takes into account the complementary coordination of multienergy, is an important research topic. Considering the constraints of power balance, energy supply equipment, and energy storage equipment, a basic model of optimal economic dispatch of an integrated energy system is established. On this basis, a multiobjective function solving algorithm of NSGA-II, based on tent map chaos optimization, is proposed. The proposed model and algorithm are applied. The simulation results show that the optimal economic scheduling model of the integrated energy system established in this paper can provide a more economic system operation scheme and reduce the operation cost and risks associated with an integrated energy system. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) multiobjective function solving algorithm, based on tent map chaos optimization, has better performance and efficiency.

scholarly journals A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency

2020 ◽  
Vol 34 (05) ◽  
pp. 9098-9105
Author(s):  
Amir Veyseh ◽  
Franck Dernoncourt ◽  
Dejing Dou ◽  
Thien Nguyen
Keyword(s):  
Prior Work ◽  
Semantic Consistency ◽  
Learning Framework ◽  
Local Structures ◽  
Joint Inference ◽  
Proposed Model ◽  
Benchmark Datasets ◽  
Sequential Labeling ◽  
Sentence Classification ◽  
Model Features

Definition Extraction (DE) is one of the well-known topics in Information Extraction that aims to identify terms and their corresponding definitions in unstructured texts. This task can be formalized either as a sentence classification task (i.e., containing term-definition pairs or not) or a sequential labeling task (i.e., identifying the boundaries of the terms and definitions). The previous works for DE have only focused on one of the two approaches, failing to model the inter-dependencies between the two tasks. In this work, we propose a novel model for DE that simultaneously performs the two tasks in a single framework to benefit from their inter-dependencies. Our model features deep learning architectures to exploit the global structures of the input sentences as well as the semantic consistencies between the terms and the definitions, thereby improving the quality of the representation vectors for DE. Besides the joint inference between sentence classification and sequential labeling, the proposed model is fundamentally different from the prior work for DE in that the prior work has only employed the local structures of the input sentences (i.e., word-to-word relations), and not yet considered the semantic consistencies between terms and definitions. In order to implement these novel ideas, our model presents a multi-task learning framework that employs graph convolutional neural networks and predicts the dependency paths between the terms and the definitions. We also seek to enforce the consistency between the representations of the terms and definitions both globally (i.e., increasing semantic consistency between the representations of the entire sentences and the terms/definitions) and locally (i.e., promoting the similarity between the representations of the terms and the definitions). The extensive experiments on three benchmark datasets demonstrate the effectiveness of our approach.1

scholarly journals A GIS Tool for Mapping Dam-Break Flood Hazards in Italy

2019 ◽  
Vol 8 (6) ◽  
pp. 250 ◽  
Author(s):  
Raffaele Albano ◽  
Leonardo Mancusi ◽  
Jan Adamowski ◽  
Andrea Cantisani ◽  
Aurelia Sole
Keyword(s):  
Numerical Models ◽  
Technical Skills ◽  
Dam Break ◽  
Propagation Model ◽  
Dam Failure ◽  
Computational Time ◽  
Hazard Mapping ◽  
Flood Hazards ◽  
Proposed Model ◽  
Flood Prone Areas

Mapping the delineation of areas that are flooded due to water control infrastructure failure is a critical issue. Practical difficulties often present challenges to the accurate and effective analysis of dam-break hazard areas. Such studies are expensive, lengthy, and require large volumes of incoming data and refined technical skills. The creation of cost-efficient geospatial tools provides rapid and inexpensive estimates of instantaneous dam-break (due to structural failure) flooded areas that complement, but do not replace, the results of hydrodynamic simulations. The current study implements a Geographic Information System (GIS) based method that can provide useful information regarding the delineation of dam-break flood-prone areas in both data-scarce environments and transboundary regions, in the absence of detailed studies. Moreover, the proposed tool enables, without advanced technical skills, the analysis of a wide number of case studies that support the prioritization of interventions, or, in emergency situations, the simulation of numerous initial hypotheses (e.g., the modification of initial water level/volume in the case of limited dam functionality), without incurring high computational time. The proposed model is based on the commonly available data for masonry dams, i.e., dam geometry (e.g., reservoir capacity, dam height, and crest length), and a Digital Elevation Model. The model allows for rapid and cost-effective dam-break hazard mapping by evaluating three components: (i) the dam-failure discharge hydrograph, (ii) the propagation of the flood, and (iii) the delineation of flood-prone areas. The tool exhibited high accuracy and reliability in the identification of hypothetical dam-break flood-prone areas when compared to the results of traditional hydrodynamic approaches, as applied to a dam in Basilicata (Southern Italy). In particular, the over- and under-estimation rates of the proposed tool, for the San Giuliano dam, Basilicata, were evaluated by comparing its outputs with flood inundation maps that were obtained by two traditional methods whil using a one-dimensional and a two-dimensional propagation model, resulting in a specificity value of roughly 90%. These results confirm that most parts of the flood map were correctly classified as flooded by the proposed GIS model. A sensitivity value of over 75% confirms that several zones were also correctly identified as non-flooded. Moreover, the overall effectiveness and reliability of the proposed model were evaluated, for the Gleno Dam (located in the Central Italian Alps), by comparing the results of literature studies concerning the application of monodimensional numerical models and the extent of the flooded area reconstructed by the available historical information, obtaining an accuracy of around 94%. Finally, the computational efficiency of the proposed tool was tested on a demonstrative application of 250 Italian arch and gravity dams. The results, when carried out using a PC, Pentium Intel Core i5 Processor CPU 3.2 GHz, 8 GB RAM, required about 73 min, showing the potential of such a tool applied to dam-break flood mapping for a large number of dams.

A Model for an Acoustically Driven Microbubble Inside a Rigid Tube

2014 ◽  
Vol 137 (2) ◽  
Author(s):  
Adnan Qamar ◽  
Ravi Samtaney
Keyword(s):  
Bubble Radius ◽  
Coupled Model ◽  
Tube Diameter ◽  
Navier Stokes ◽  
Navier Stokes Equation ◽  
Rigid Tube ◽  
Basic Model ◽  
Proposed Model ◽  
D 12 ◽  
Bubble Fragmentation

A theoretical framework to model the dynamics of acoustically driven microbubble inside a rigid tube is presented. The proposed model is not a variant of the conventional Rayleigh–Plesset category of models. It is derived from the reduced Navier–Stokes equation and is coupled with the evolving flow field solution inside the tube by a similarity transformation approach. The results are computed, and compared with experiments available in literature, for the initial bubble radius of Ro = 1.5 μm and 2 μm for the tube diameter of D = 12 μm and 200 μm with the acoustic parameters as utilized in the experiments. Results compare quite well with the existing experimental data. When compared to our earlier basic model, better agreement on a larger tube diameter is obtained with the proposed coupled model. The model also predicts, accurately, bubble fragmentation in terms of acoustic and geometric parameters.

The Key Role of Headrest Optimization in Driver Comfort

2019 ◽  
Vol 24 (3) ◽  
pp. 592-599
Author(s):  
Hamid Gheibollahi ◽  
Masoud Masih-Tehrani ◽  
Mohammadmehdi Niroobakhsh
Keyword(s):  
Human Body ◽  
The Body ◽  
Human Body Model ◽  
Sitting Posture ◽  
Conventional Vehicle ◽  
Body Model ◽  
Basic Model ◽  
Proposed Model ◽  
Stiffness And Damping

In this study, adding a headrest to the conventional vehicle driver seat is investigated to improve the driver comfort and decrease the driver damages. For this purpose, a conventional biomechanical human body model of wholebody vibrations is provided and modified by adding a head degree of freedom to the body model and a headrest to the seat model. The basic model is in the sitting posture, lumped parameters and has nine DOFs for the human body, on contrary to the proposed model which has ten DOFs. The new human body DOF is the twisting motion of the head and neck. This new DOF is generated because of headrest adding to the driver’s seat. To determine the head discomforts, the Seat to Head (STH) indexes are studied in two directions: horizontal and vertical. The Genetic Algorithm (GA) is used to optimize the STH in different directions. The optimization variables are stiffness and damping parameters of the driver’s seat which are 12 for the basic model and are 16 for a new seat. The integer programming is used for time reduction. The results show that new seat (equipped by headrest) has very better STH in both directions.

Sign in / Sign up

Export Citation Format

Share Document