A Multiscale Design Approach With Random Field Representation of Material Uncertainty

2008 ◽  
Author(s):  
Xiaolei Yin ◽  
Sanghon Lee ◽  
Wei Chen ◽  
Wing Kam Liu ◽  
M. F. Horstemeyer
Keyword(s):  
Random Field ◽  
Manufacturing Process ◽  
Uncertainty Propagation ◽  
Gaussian Quadrature ◽  
Casting Process ◽  
Product Performance ◽  
Design Approach ◽  
Field Representation ◽  
Gaussian Quadrature Formula ◽  
The Impact

A multiscale design approach is proposed in this paper considering the impacts of product manufacturing process and material on product performance. A framework is established to integrate designs of manufacturing process, material and product based on the information flow across these three domains. Random field is employed to realistically model the uncertainty existing in material microstructure which spatially varies in a product inherited from the manufacturing process. An efficient procedure for uncertainty propagation from the material random field to the end product performance is established. To reduce the dimensionality of random field representation, a reduced order Karhunen-Loeve expansion is used with a discretization scheme applied to finite element meshes. The univariate dimension reduction method and the Gaussian quadrature formula are used to efficiently quantify the uncertainties in product performance in terms of its statistical moments, which are critical information for design under uncertainty. A control arm example is used to demonstrate the proposed approach. The impact of the initial microscale porosity random field produced during a casting process on the product damage is studied and a reliability-based design of the control arm is performed.

Efficient Random Field Uncertainty Propagation in Design Using Multiscale Analysis

2009 ◽  
Vol 131 (2) ◽  
Author(s):  
Xiaolei Yin ◽  
Sanghoon Lee ◽  
Wei Chen ◽  
Wing Kam Liu ◽  
M. F. Horstemeyer
Keyword(s):  
Random Field ◽  
Manufacturing Process ◽  
Multiscale Analysis ◽  
Multiple Scales ◽  
Integrated Design ◽  
Product Performance ◽  
Computational Techniques ◽  
Field Representation ◽  
Gaussian Quadrature Formula ◽  
The Impact

An integrated design framework that employs multiscale analysis to facilitate concurrent product, material, and manufacturing process design is presented in this work. To account for uncertainties associated with material structures and their impact on product performance across multiple scales, efficient computational techniques are developed for propagating material uncertainty with random field representation. Random field is employed to realistically model the uncertainty existing in material microstructure, which spatially varies in a product inherited from the manufacturing process. To reduce the dimensionality of random field representation, a reduced order Karhunen–Loeve expansion is used with a discretization scheme applied to finite-element meshes. The univariate dimension reduction method and the Gaussian quadrature formula are used to efficiently quantify the uncertainties in product performance in terms of its statistical moments, which are critical information for design under uncertainty. A control arm example is used to demonstrate the proposed approach. The impact of the initial microscale porosity random field produced during a casting process on the product damage is studied and a reliability-based design of the control arm is performed.

Defect Investigation of Sand Casted Aluminum Cooling Fan

2020 ◽  
Vol 991 ◽  
pp. 30-36
Author(s):  
Dedhy Prihtiantoro ◽  
Agus Dwi Anggono ◽  
Waluyo Adi Siswanto
Keyword(s):  
Manufacturing Process ◽  
Casting Process ◽  
Sand Casting ◽  
Product Performance ◽  
Defect Analysis ◽  
Complicated Shape ◽  
Cooling Fan ◽  
Domestic Use ◽  
The Common ◽  
Defect Investigation

Sand casting is one of manufacturing process that still exist today. Numerous products are produced to serve industrial and domestic use. Defect could lead to product performance, and unfortunately inevitable in a casting process. This paper aim to investigate typical defect resulted from sand casting process. An aluminum cooling fan was selected as the model since it has complicated shape with different thicknesses. The casted fan was investigated under photo micro for defect analysis. Porosity, gas inclusion, pinhole, and shrinkage were found as the common defects occured at different part of the fan.

scholarly journals Deep Neural Network and Polynomial Chaos Expansion-Based Surrogate Models for Sensitivity and Uncertainty Propagation: An Application to a Rockfill Dam

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1830
Author(s):  
Gullnaz Shahzadi ◽  
Azzeddine Soulaïmani
Keyword(s):  
Polynomial Chaos ◽  
Complex Structure ◽  
Uncertainty Propagation ◽  
Surrogate Models ◽  
Polynomial Chaos Expansion ◽  
Soil Parameters ◽  
Chaos Expansion ◽  
Rockfill Dam ◽  
Parametric Studies ◽  
The Impact

Computational modeling plays a significant role in the design of rockfill dams. Various constitutive soil parameters are used to design such models, which often involve high uncertainties due to the complex structure of rockfill dams comprising various zones of different soil parameters. This study performs an uncertainty analysis and a global sensitivity analysis to assess the effect of constitutive soil parameters on the behavior of a rockfill dam. A Finite Element code (Plaxis) is utilized for the structure analysis. A database of the computed displacements at inclinometers installed in the dam is generated and compared to in situ measurements. Surrogate models are significant tools for approximating the relationship between input soil parameters and displacements and thereby reducing the computational costs of parametric studies. Polynomial chaos expansion and deep neural networks are used to build surrogate models to compute the Sobol indices required to identify the impact of soil parameters on dam behavior.

scholarly journals Machine Learning-Based on Assessment of the Impact of the Manufacturing Process on Battery Electrode Heterogeneity

Energy and AI ◽  
2021 ◽  
pp. 100090
Author(s):  
Marc Duquesnoy ◽  
Iker Boyano ◽  
Larraitz Ganborena ◽  
Pablo Cereijo ◽  
Elixabete Ayerbe ◽  
...  
Keyword(s):  
Machine Learning ◽  
Manufacturing Process ◽  
Battery Electrode ◽  
The Impact

scholarly journals The impact of molded pulp product process on the mechanical properties of molded Bleached Chemi-Thermo-Mechanical Pulp

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Claire Dislaire ◽  
Yves Grohens ◽  
Bastien Seantier ◽  
Marion Muzy
Keyword(s):  
Mechanical Properties ◽  
Water Uptake ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Water Immersion ◽  
Young Modulus ◽  
Drying Time ◽  
Mechanical Pulp ◽  
Hygroscopic Properties ◽  
The Impact

AbstractThis study was carried out using bleached softwood Chemi-Thermo-Mechanical Pulp to evaluate the influence of Molded Pulp Products’ manufacturing process parameters on the finished products’ mechanical and hygroscopic properties. A Taguchi table was done to make 8 tests with specific process parameters such as moulds temperature, pulping time, drying time, and pressing time. The results of these tests were used to obtain an optimized manufacturing process with improved mechanical properties and a lower water uptake after sorption analysis and water immersion. The optimized process parameters allowed us to improve the Young’ Modulus after 30h immersion of 58% and a water uptake reduction of 78% with the first 8 tests done.

Experimental Assessment of Roughness Changes in the Cutting Surface and Microhardness Changes of the Material S 355 J2 G3 after Being Cut by Non-Conventional Technologies

2011 ◽  
Vol 314-316 ◽  
pp. 1944-1947 ◽  
Author(s):  
Jozef Maščeník ◽  
Stefan Gaspar
Keyword(s):  
Mechanical Properties ◽  
Production Process ◽  
Laser Plasma ◽  
Manufacturing Process ◽  
Production Quality ◽  
Water Jet ◽  
Cutting Edge ◽  
Experimental Assessment ◽  
Cutting Surface ◽  
The Impact

Production of components, necessary for the construction of the machine resp. or device is a demanding manufacturing process. One of the possibilities of increasing efficiency and production quality is the introduction of unconventional technologies to the production process. Knowing the dependence of the impact of non-conventional technologies on the mechanical properties of products and their subsequent verification is an important aspect when designing and manufacturing them. The article deals with the impact of used unconventional technology, that means laser, plasma and water jet on the roughness of a cutting edge and microhardness of material S 355 J2 G3.

Tribological characteristics of AA8090-WC-ZrC metal matrix composites prepared by stir casting process for Aerospace applications

2021 ◽  
Vol 73 (6) ◽  
pp. 980-985
Author(s):  
Kalaiyarasan A ◽  
Sundaram S ◽  
Gunasekaran K ◽  
Bensam Raj J.
Keyword(s):  
Metal Matrix ◽  
Materials Science ◽  
Scientific Information ◽  
High Hardness ◽  
Hardness Test ◽  
Casting Process ◽  
Stir Casting ◽  
Hybrid Particles ◽  
Content Type ◽  
The Impact

Purpose Aerospace field is demanding a material with superior strength and high resistance against wear, tear and corrosion. The current study aimed to develop a new material with high performance to be applicable in aerospace field Design/methodology/approach A metal matrix composite AA8090-WC-ZrC was fabricated using stir casting method and its tribological behavior was investigated. Totally, five composites viz. AA/Z, AA/W, AA/WZ (1:3), AA/WZ (1:1) & AA/WZ (3:1) were prepared. Micro hardness, tensile and wear study were performed on the fabricated composites and the results were compared with AA8090 alloy Findings Vickers hardness test resulted that the AA/W composite showed the higher hardness value of 160 HB compared to other materials due to the reinforcing effect of WC particles with high hardness. Tensile test reported that the AA/W composite displayed the maximum tensile strength of 502 MPa owing to the creation of more dislocation density. Further, wear study showed that the AA/W composite exhibited the least wear rate of 0.0011 mm3/m because of the more resisting force offered by the WC particles. Furthermore, the AA/W composite showed the slightest mass loss of 0.0028 g and lower COF value of 0.31 due to the hinder effect of WC particle to the movement of atoms in AA8090 alloy Originality/value This work is original in the field of aerospace engineering and materials science which deals with the fabrication of AA8090 alloy with the reinforcement particles such as tungsten carbide and zirconium carbide. The impact of the combination of hybrid particles and their volume fractions on the tribological properties has been investigated in this work. This work would provide new scientific information to society.

Assessment of Uncertainty for Structural and Mechatronics Engineering Applications

2011 ◽  
Vol 104 ◽  
pp. 145-159
Author(s):  
Stijn Donders ◽  
Laszlo Farkas ◽  
Michael Hack ◽  
Herman Van der Auweraer ◽  
Roberto d’Ippolito ◽  
...  
Keyword(s):  
Structural Dynamics ◽  
Adaptive Systems ◽  
Product Performance ◽  
Actual Behavior ◽  
Actual Problem ◽  
Design Assessment ◽  
And Performance ◽  
Detailed Computer ◽  
Virtual Modeling ◽  
The Impact

Nowadays, mechanical industries operate in a highly competitive environment, therefore the process of developing a component from concept through detailed Computer-Aided Engineering (CAE) and performance validation is optimized for reduced development time and increased product performance. To continuously improve the product design and performance and reduce the costs and time to market, the design and performance engineering is shifted more and more towards virtual modeling and simulation processes from the expensive test-based design evaluations. Secondly, the booming introduction of active and adaptive systems in mechanical structures leads to a ‘mechatronics systems’ revolution, which further improves the product performance at the expense of increased system complexity. It is noted that the potential of structural dynamics test and analysis methods for addressing a structural dynamics design assessment or design optimization depends largely on the confidence that one can have in the results. That is, the results must be accurate, characteristic for the actual problem (and not be the result of testing artifacts) and representative for the actual behavior of the investigated structure. In this context, a key aspect is to be aware of the key sources of uncertainty in the designed product, and the impact thereof on the product performance in terms of structural dynamics, crashworthiness and/or acoustics. This paper reviews the main elements of test data and modal modeling uncertainty and assesses the impact of the uncertainty on some typical modeling problems taken from automotive and aerospace industry.

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