No. 3 Thermal Radiative Properties

Lucks, C.F.; Deem, H.W.; Wood, W.D.

doi:10.1007/978-1-4899-5454-1

Cited by 16 publications

(10 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One of the most important factors in the modeling was the temperature-dependent material properties. Table 2 shows the material properties used for stainless steel 316L in the model [31][32][33]. Convergence is a noteworthy point during simulations.…”

Section: Multiphysics Modelmentioning

confidence: 99%

Selective Laser Melting of 316L Austenitic Stainless Steel: Detailed Process Understanding Using Multiphysics Simulation and Experimentation

Ansari

Rehman

Pıtır

et al. 2021

Metals

View full text Add to dashboard Cite

The parameter sets used during the selective laser melting (SLM) process directly affect the final product through the resulting melt-pool temperature. Achieving the optimum set of parameters is usually done experimentally, which is a costly and time-consuming process. Additionally, controlling the deviation of the melt-pool temperature from the specified value during the process ensures that the final product has a homogeneous microstructure. This study proposes a multiphysics numerical model that explores the factors affecting the production of parts in the SLM process and the mathematical relationships between them, using stainless steel 316L powder. The effect of laser power and laser spot diameter on the temperature of the melt-pool at different scanning velocities were studied. Thus, mathematical expressions were obtained to relate process parameters to melt-pool temperature. The resulting mathematical relationships are the basic elements to design a controller to instantly control the melt-pool temperature during the process. In the study, test samples were produced using simulated parameters to validate the simulation approach. Samples produced using simulated parameter sets resulting in temperatures of 2000 K and above had acceptable microstructures. Evaporation defects caused by extreme temperatures, unmelted powder defects due to insufficient temperature, and homogenous microstructures for suitable parameter sets predicted by the simulations were obtained in the experimental results, and the model was validated.

show abstract

Section: Multiphysics Modelmentioning

confidence: 99%

Selective Laser Melting of 316L Austenitic Stainless Steel: Detailed Process Understanding Using Multiphysics Simulation and Experimentation

Ansari

Rehman

Pıtır

et al. 2021

Metals

View full text Add to dashboard Cite

show abstract

“…The spectral distribution of n (λ, T) is approximately independent of temperature. More comprehensive emissivity compilations can be found in [38,39,40,41]. Measurements of surface emissivity are often limited to determining its normal to the surface, for a few chosen wavelengths or only the hemispherical total emissivity.…”

Section: Thermal Radiation 241 Physics Of Thermal Radiation Transportmentioning

confidence: 99%

Rattlesnake Theory Manual

Wang

Labouré

2018

View full text Add to dashboard Cite

Rattlesnake is built on the MOOSE framework. Rattlesnake manages meshes with libMesh [25] and solves the system equation with PETSc [26] through MOOSE. Support of unstructured meshes, parallelization with domain decomposition, various time integration schemes, most of nonlinear solvers features, multiphysics coupling are all inherited from the framework. Rattlesnake is responsible for setting up the discretization of RTE with interfaces provided by MOOSE. Because Rattlesnake is built on a general framework, it can perform calculations in 1D, 2D and 3D unstructured meshes via MPI (message passing interface) [27] and multi-threading. The weak forms can be directly translated into code under the MOOSE framework, which results in codes easy to maintain and extend. Multiple developers can co-work seamlessly on Rattlesnake. This development pattern allows splitting the work into the physics-related items residing in Rattlesnake, and physics-irrelevant items residing in the framework. The benefit is twofold: Rattlesnake can push the development on the framework side, which can benefit all the other MOOSE-based applications and any improvements in MOOSE can improve Rattlesnake. For example, the common software development procedure is managed by MOOSE, e.g. the version control, regression tests, on-line documentation. In addition, coupling Rattlesnake with other MOOSE-based applications dealing with other physics is straightforward because these applications are based on the same framework. As an example, the reactor physics application MAMMOTH [2, 28] leverages components spread over Rattlesnake, MOOSE and its modules, Bison [29, 30, 31], and Relap-7 [32]. In summary, being built on MOOSE makes Rattlesnake powerful and unique. There indeed are constraints imposed by the framework, but this is not insurmountable and outweighted by all the advantages provided by this development pattern. In Section 2, we first state the RTE for various particles. Currently, we only consider two particles: neutron and thermal radiation but Rattlesnake can be extended easily to other types. Particles mostly share the same time derivative,

show abstract

“…On a cloudless day [or a near vertical sun, about 80 percent of the incident flux reaches the ground. Only 50 percent of incident flux may pass during a cloudy day [23].…”

Section: Solar Radiationmentioning

confidence: 99%

“…Above results demonstrated that the EC algorithm achieve a significant improvement compared to the existing RX algorithm. However, it still not meet the Specified detection criteria 22 for scanning sensors, which is 0.95 Pd at, 0.02 false alarm per square meter 23 , because only two references are used to detect six types of miine at …”

Section: Performance Evaluationmentioning

confidence: 99%

Physics-Based Radiometric Signature Modeling and Detection Algorithms of Landmines Using Electro-Optical Sensors

Liao¹

2005

View full text Add to dashboard Cite

No. 3 Thermal Radiative Properties

Cited by 16 publications

References 0 publications

Selective Laser Melting of 316L Austenitic Stainless Steel: Detailed Process Understanding Using Multiphysics Simulation and Experimentation

Selective Laser Melting of 316L Austenitic Stainless Steel: Detailed Process Understanding Using Multiphysics Simulation and Experimentation

Rattlesnake Theory Manual

Physics-Based Radiometric Signature Modeling and Detection Algorithms of Landmines Using Electro-Optical Sensors

Contact Info

Product

Resources

About