A Line Heat Input Model for Additive Manufacturing

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Jeff Irwin ◽  
P. Michaleris
Keyword(s):  
Additive Manufacturing ◽  
Heat Source ◽  
Heat Input ◽  
Computational Time ◽  
Processing Unit ◽  
Powder Bed ◽  
Central Processing ◽  
Time Increment ◽  
Input Model ◽  
Time Required

A line input (LI) model has been developed, which makes the accurate modeling of powder bed processes more computationally efficient. Goldak's ellipsoidal model has been used extensively to model heat sources in additive manufacturing (AM), including lasers and electron beams. To accurately model the motion of the heat source, the simulation time increments must be small enough such that the source moves a distance smaller than its radius over the course of each increment. When the source radius is small and its velocity is large, a strict condition is imposed on the size of time increments regardless of any stability criteria. In powder bed systems, where radii of 0.1 mm and velocities of 500 mm/s are typical, a significant computational burden can result. The line heat input model relieves this burden by averaging the heat source over its path. This model allows the simulation of an entire heat source scan in just one time increment. However, such large time increments can lead to inaccurate results. Instead, the scan is broken up into several linear segments, each of which is applied in one increment. In this work, time increments are found that yield accurate results (less than 10% displacement error) and require less than 1/10 of the central processing unit (CPU) time required by Goldak's moving source model. A dimensionless correlation is given that can be used to determine the necessary time increment size that will greatly decrease the computational time required for any powder bed simulation while maintaining accuracy.

A Line Heat Input Model for Additive Manufacturing

2015 ◽  
Author(s):  
Jeff Irwin ◽  
P. Michaleris
Keyword(s):  
Additive Manufacturing ◽  
Heat Source ◽  
Heat Input ◽  
Source Model ◽  
Computational Time ◽  
Computationally Efficient ◽  
Powder Bed ◽  
Time Increment ◽  
Input Model ◽  
Time Required

A line input model has been developed which makes the accurate modeling of powder bed processes more computationally efficient. Goldak’s ellipsoidal model has been used extensively to model heat sources in additive manufacturing, including lasers and electron beams. To accurately model the motion of the heat source, the simulation time increments must be small enough such that the source moves a distance smaller than its radius over the course of each increment. When the source radius is small and its velocity is large, a strict condition is imposed on the size of time increments regardless of any stability criteria. In powder bed systems, where radii of 0.1 mm and velocities of 500 mm/s are typical, a significant computational burden can result. The line heat input model relieves this burden by averaging the heat source over its path. This model allows the simulation of an entire heat source scan in just one time increment. However, such large time increments can lead to inaccurate results. Instead, the scan is broken up into several linear segments, each of which is applied in one increment. In this work, time increments are found that yield accurate results (less than 10 % displacement error) and require less than 1/10 of the CPU time required by Goldak’s moving source model. A dimensionless correlation is given that can be used to determine the necessary time increment size that will greatly decrease the computational time required for any powder bed simulation while maintaining accuracy.

scholarly journals An Ensemble-based Supervised Machine Learning Framework for Android Ransomware Detection

2021 ◽  
Vol 18 (3A) ◽  
Author(s):  
Shweta Sharma ◽  
Rama Krishna ◽  
Rakesh Kumar
Keyword(s):  
Machine Learning ◽  
Graphics Processing Unit ◽  
Principal Component ◽  
Supervised Machine Learning ◽  
Computational Time ◽  
Processing Unit ◽  
Central Processing ◽  
Analysis Technique ◽  
Malicious Apps ◽  
Time Required

With latest development in technology, the usage of smartphones to fulfill day-to-day requirements has been increased. The Android-based smartphones occupy the largest market share among other mobile operating systems. The hackers are continuously keeping an eye on Android-based smartphones by creating malicious apps housed with ransomware functionality for monetary purposes. Hackers lock the screen and/or encrypt the documents of the victim’s Android based smartphones after performing ransomware attacks. Thus, in this paper, a framework has been proposed in which we (1) utilize novel features of Android ransomware, (2) reduce the dimensionality of the features, (3) employ an ensemble learning model to detect Android ransomware, and (4) perform a comparative analysis to calculate the computational time required by machine learning models to detect Android ransomware. Our proposed framework can efficiently detect both locker and crypto ransomware. The experimental results reveal that the proposed framework detects Android ransomware by achieving an accuracy of 99.67% with Random Forest ensemble model. After reducing the dimensionality of the features with principal component analysis technique; the Logistic Regression model took least time to execute on the Graphics Processing Unit (GPU) and Central Processing Unit (CPU) in 41 milliseconds and 50 milliseconds respectively

scholarly journals Numerical Simulation Development and Computational Optimization for Directed Energy Deposition Additive Manufacturing Process

Materials ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2666 ◽  
Author(s):  
Abhilash Kiran ◽  
Josef Hodek ◽  
Jaroslav Vavřík ◽  
Miroslav Urbánek ◽  
Jan Džugan
Keyword(s):  
Numerical Simulation ◽  
Residual Stress ◽  
Additive Manufacturing ◽  
Heat Input ◽  
Thermal Cycle ◽  
Energy Deposition ◽  
Numerical Results ◽  
Computational Time ◽  
Stress Calculation ◽  
Directed Energy

The rapid growth of Additive Manufacturing (AM) in the past decade has demonstrated a significant potential in cost-effective production with a superior quality product. A numerical simulation is a steep way to learn and improve the product quality, life cycle, and production cost. To cope with the growing AM field, researchers are exploring different techniques, methods, models to simulate the AM process efficiently. The goal is to develop a thermo-mechanical weld model for the Directed Energy Deposition (DED) process for 316L stainless steel at an efficient computational cost targeting to model large AM parts in residual stress calculation. To adapt the weld model to the DED simulation, single and multi-track thermal simulations were carried out. Numerical results were validated by the DED experiment. A good agreement was found between predicted temperature trends for numerical simulation and experimental results. A large number of weld tracks in the 3D solid AM parts make the finite element process simulation challenging in terms of computational time and large amounts of data management. The method of activating elements layer by layer and introducing heat in a cyclic manner called a thermal cycle heat input was applied. Thermal cycle heat input reduces the computational time considerably. The numerical results were compared to the experimental data for thermal and residual stress analyses. A lumping of layers strategy was implemented to reduce further computational time. The different number of lumping layers was analyzed to define the limit of lumping to retain accuracy in the residual stress calculation. The lumped layers residual stress calculation was validated by the contour cut method in the deposited sample. Thermal behavior and residual stress prediction for the different numbers of a lumped layer were examined and reported computational time reduction.

A design procedure for improving the effectiveness of fractal layouts formation

2014 ◽  
Vol 28 (1) ◽  
pp. 1-26 ◽  
Author(s):  
Yung Chin Shih ◽  
Eduardo Vila Gonçalves Filho
Keyword(s):  
Design Procedure ◽  
Current Approach ◽  
Computational Time ◽  
Shop Floor ◽  
Processing Unit ◽  
Performance Parameters ◽  
Trade Off ◽  
Central Processing ◽  
Search Heuristics ◽  
Functional Layout

AbstractRecently, new types of layouts have been proposed in the literature in order to handle a large number of products. Among these are the fractal layout, aiming at minimization of routing distances. There are already researchers focusing on the design; however, we have noticed that the current approach usually executes several times the allocations of fractal cells on the shop floor up to find the best allocations, which may present a significant disadvantage when applied to a large number of fractal cells owing to combinatorial features. This paper aims to propose a criterion, based on similarity among fractal cells, developed and implemented in a Tabu search heuristics, in order to allocate it on the shop floor in a feasible computational time. Once our proposed procedure is modeled, operations of each workpiece are separated in n subsets and submitted to simulation. The results (traveling distance and makespan) are compared to distributed layout and to functional layout. The results show, in general, a trade-off behavior, that is, when the total routing distance decreases, the makespan increases. Based on our proposed method, depending on the value of segregated fractal cell similarity, it is possible to reduce both performance parameters. Finally, we conclude the proposed procedure shows to be quite promising because allocations of fractal cells demand reduced central processing unit time.

Ratcheting Prediction at the Notch Root of Steel Samples Over Asymmetric Loading Cycles

2019 ◽  
Vol 142 (2) ◽  
Author(s):  
A. Shekarian ◽  
A. Varvani-Farahani
Keyword(s):  
Stress Relaxation ◽  
Notch Root ◽  
Kinematic Hardening ◽  
Strain Range ◽  
Medium Carbon Steel ◽  
Computational Time ◽  
Processing Unit ◽  
Central Processing ◽  
Hardening Rules ◽  
Neuber's Rule

Abstract The present study intends to evaluate local ratcheting and stress relaxation of medium carbon steel samples under various asymmetric load levels by means of two kinematic hardening rules of Chaboche (CH) and Ahmadzadeh-Varvani (A-V). The Neuber's rule was coupled with the hardening rules to predict ratcheting and stress relaxation at the vicinity of the notch root. Stress-strain hysteresis loops generated by the CH and A-V models were employed to simultaneously control ratcheting progress over stress cycles and stress relaxation at notch root while strain range kept constant in each cycle. The higher cyclic load levels applied at the notch root accelerated shakedown over smaller number of cycles and resulted in lower relaxation rate. The larger notch diameter of 9 mm on the other hand induced lower stress concentration and smaller plastic zone at the notch root promoting ratcheting progress with less materials constraint over loading cycles compared with notch diameter d = 3 mm. Predicted ratcheting results through the A-V and CH models as coupled with the Neuber's rule were found in good agreements with the experimental data. The choice of the A-V and CH hardening rules in assessing ratcheting of materials was attributed to the number of terms/coefficients and complexity of their frameworks and computational time/central processing unit (CPU) required to run a ratcheting program.

scholarly journals Detection of Typical Metal Additive Manufacturing Defects by the Application of Thermographic Techniques

Proceedings ◽  
2019 ◽  
Vol 27 (1) ◽  
pp. 24
Author(s):  
D’Accardi ◽  
Altenburg ◽  
Maierhofer ◽  
Palumbo ◽  
Galietti
Keyword(s):  
Additive Manufacturing ◽  
Processing Parameters ◽  
Layer By Layer ◽  
Metal Powders ◽  
Destructive Testing ◽  
Powder Bed ◽  
Manufacturing Defects ◽  
Metal Additive Manufacturing ◽  
Time Required ◽  
Metal Additive

One of the most advanced technologies of Metal Additive Manufacturing (AM) is the Laser Powder Bed Fusion process (L-PBF), also known as Selective Laser Melting (SLM). This process involves the deposition and fusion, layer by layer, of very fine metal powders and structure and quality of the final component strongly depends on several processing parameters, for example the laser parameters. Due to the complexity of the process it is necessary to assure the absence of defects in the final component, in order to accept or discard it. Thermography is a very fast non-destructive testing (NDT) technique. Its applicability for defect detection in AM produced parts would significantly reduce costs and time required for NDT, making it versatile and very competitive.

Thermofluid Properties of Ti-6Al-4V Melt Pool in Powder-Bed Electron Beam Additive Manufacturing

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
M Shafiqur Rahman ◽  
Paul J. Schilling ◽  
Paul D. Herrington ◽  
Uttam K. Chakravarty
Keyword(s):  
Electron Beam ◽  
Additive Manufacturing ◽  
Heat Source ◽  
Thermal Behavior ◽  
Source Parameters ◽  
Three Dimensional ◽  
Full Density ◽  
Layer By Layer ◽  
Powder Bed ◽  
Melt Pool

Electron beam additive manufacturing (EBAM) is a powder-bed fusion additive manufacturing (AM) technology that can make full density metallic components using a layer-by-layer fabrication method. To build each layer, the EBAM process includes powder spreading, preheating, melting, and solidification. The quality of the build part, process reliability, and energy efficiency depends typically on the thermal behavior, material properties, and heat source parameters involved in the EBAM process. Therefore, characterizing those properties and understanding the correlations among the process parameters are essential to evaluate the performance of the EBAM process. In this study, a three-dimensional computational fluid dynamics (CFD) model with Ti-6Al-4V powder was developed incorporating the temperature-dependent thermal properties and a moving conical volumetric heat source with Gaussian distribution to conduct the simulations of the EBAM process. The melt pool dynamics and its thermal behavior were investigated numerically, and results for temperature profile, melt pool geometry, cooling rate and variation in density, thermal conductivity, specific heat capacity, and enthalpy were obtained for several sets of electron beam specifications. Validation of the model was performed by comparing the simulation results with the experimental results for the size of the melt pool.

Modeling of Dynamic Cuttings Transportation during Drilling of Oil and Gas Wells by Combining 2D CFD and 1D Discretization Approach

SPE Journal ◽  
2020 ◽  
Vol 25 (03) ◽  
pp. 1220-1240 ◽  
Author(s):  
Feifei Zhang ◽  
Yidi Wang ◽  
Yuezhi Wang ◽  
Stefan Miska ◽  
Mengjiao Yu
Keyword(s):  
Oil And Gas ◽  
Continuous Model ◽  
Computational Time ◽  
Superposition Method ◽  
Processing Unit ◽  
Flow Profile ◽  
Gas Wells ◽  
Central Processing ◽  
Bed Height ◽  
Oil And Gas Wells

Summary This paper presents an approach that combines a two-dimensional (2D) computational fluid dynamics (CFD) and one-dimensional (1D) continuous model for cuttings transport simulation during drilling of oil and gas wells. The 2D CFD simulates the flow profile and the suspended cuttings concentration profile in the cross section of the wellbore and the 1D continuous model simulates the cuttings transportation in the axial direction of the wellbore. Different cuttings sizes are considered in the model by using a new proposed superposition method. Experimental tests conducted on a 203 × 114 × 25 mm3 flow loop are used to validate the model from three different perspectives: the single-phase flow pressure drop, the steady-state cuttings bed height, and the transient pressure changes. Compared to layer models, the new approach is able to catch accurate flow details in the narrow flow region and overcome the shortcoming of traditional models that underpredict bed height under high flow rate conditions. The computational time increases by the order of 104∼105 from the level of millisecond to seconds but is still within the acceptable range for engineering applications, and the model provides close to three-dimensional (3D) accuracy at a much shorter central processing unit (CPU) time compared to 3D CFD models.

scholarly journals Numerical comparison of reduced order models for non-linear vibrations of damped plates

2012 ◽  
Author(s):  
F. Boumediene ◽  
L. Duigou ◽  
A. Miloudi ◽  
J.M. Cadou
Keyword(s):  
Harmonic Balance ◽  
Harmonic Balance Method ◽  
Computational Time ◽  
Numerical Comparison ◽  
Processing Unit ◽  
Reduced Order Models ◽  
Reduced Order ◽  
Central Processing ◽  
Non Linear ◽  
Linear Vibrations

This work deals with the computation of the non-linear solutions of the vibration of damped plates by coupling a harmonic balance method and the asymptotic numerical method. These computations can lead to lengthy central processing unit (CPU) times if the solution sought contains an important number of harmonics. In this study, we propose two reduced order models which can be applied to solve this type of problem. Both reduced methods are based on a first computation carried out with a small number of harmonics (here two). Numerical examples of plate vibration show that these algorithms help save a great deal of computational time and can be applied to problems involving numerous harmonics.

scholarly journals Numerical Analysis and Experimental Verification of Optimum Heat Input in Additive Manufacturing of Aero Ultrathin Blade

2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Shijie Dai ◽  
Miao Gong ◽  
Liwen Wang ◽  
Tao Wang
Keyword(s):  
Heat Transfer ◽  
Additive Manufacturing ◽  
Numerical Analysis ◽  
Heat Source ◽  
Heat Input ◽  
Source Model ◽  
Heat Transfer Model ◽  
Transfer Model ◽  
Heat Source Model ◽  
Blade Repair

Heat input is a crucial factor affecting the quality in blade additive manufacturing repairing. First, a moving heat source model was established, and through numerical analysis and experimental comparison, the optimal geometric parameters of the heat source model for ultrathin blade repair were obtained. Second, a heat transfer model is established based on the optimal heat source model. By analyzing the thermophysical properties of different alloys, the heat input range of the blade was calculated. By heat transfer calculation under different heat inputs, the heat transfer model of blade repair was optimized. Then, a mathematical model of additive height is established. The optimized heat transfer model is used to solve the temperature distribution of the additive section with time under different wire feeding speeds through numerical analysis, which further reduced the heat input range. Third, the experiments are carried out based on the results of numerical analysis. The evolution law of the microstructure and heat input rate of the additive manufacturing zone was revealed, and the optimal heat input parameters were obtained. Under the optimal parameters, the segregation zone disappeared; hence, the test data were close to the base metal, and the additive manufacturing zone achieved better quality. The results and methods are of great guiding significance for the optimization design in additive manufacturing repair of the aero blades. The study also contributes to carrying out a series of research on heat transfer of ultrathin nickel-based alloy welding.

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