Good Mud-Modeling Practice

2021 ◽  
pp. 371-414
Keyword(s):  
Modeling Practice

The Importance of Impedance Calibration and the Modeling Practice for Simulation in DDR Memory

2020 ◽  
Author(s):  
Babun Chandra Pal ◽  
Chetan Koshti ◽  
Shikhar Sharma ◽  
Nirav Parekh
Keyword(s):  
Modeling Practice

A Joint-Industry Effort to Develop and Verify CFD Modeling Practice for Vortex-Induced Motion of a Deep-Draft Semi-Submersible

2021 ◽  
Author(s):  
Hyunchul Jang ◽  
Dae-Hyun Kim ◽  
Madhusuden Agrawal ◽  
Sebastien Loubeyre ◽  
Dongwhan Lee ◽  
...  
Keyword(s):  
Test Data ◽  
Model Test ◽  
Working Group ◽  
Cfd Modeling ◽  
Physical Model Test ◽  
Mooring Lines ◽  
Cfd Models ◽  
Induced Motion ◽  
Modeling Practice ◽  
Decay Tests

Abstract Platform Vortex Induced Motion (VIM) is an important cause of fatigue damage on risers and mooring lines connected to deep-draft semi-submersible floating platforms. The VIM design criteria have been typically obtained from towing tank model testing. Recently, computational fluid dynamics (CFD) analysis has been used to assess the VIM response and to augment the understanding of physical model test results. A joint industry effort has been conducted for developing and verifying a CFD modeling practice for the semi-submersible VIM through a working group of the Reproducible Offshore CFD JIP. The objectives of the working group are to write a CFD modeling practice document based on existing practices validated for model test data, and to verify the written practice by blind calculations with five CFD practitioners acting as verifiers. This paper presents the working group’s verification process, consisting of two stages. In the initial verification stage, the verifiers independently performed free-decay tests for 3-DOF motions (surge, sway, yaw) to check if the mechanical system in the CFD model is the same as in the benchmark test. Additionally, VIM simulations were conducted at two current headings with a reduced velocity within the lock-in range, where large sway motion responses are expected,. In the final verification stage, the verifiers performed a complete set of test cases with small revisions of their CFD models based on the results from the initial verification. The VIM responses from these blind calculations are presented, showing close agreement with the model test data.

Integrating Scientific Modeling and Socio-Scientific Reasoning to Promote Scientific Literacy

2021 ◽  
pp. 31-54
Author(s):  
Julie Keane ◽  
Laura A. Zangori ◽  
Troy D. Sadler ◽  
Patricia J. Friedrichsen
Keyword(s):  
Elementary Students ◽  
Scientific Literacy ◽  
Scientific Reasoning ◽  
Social Implications ◽  
Scientific Modeling ◽  
Disciplinary Knowledge ◽  
Daily Lives ◽  
Modeling Practice ◽  
Based Instruction ◽  
Support Students

Socio-scientific issues (SSI) are widely advocated as a productive context for promoting scientific literacy that aims to prepare responsible citizens who can use science in their daily lives. However, many teachers find it challenging to enact SSI and consider SSI and discipline-based instruction as mutually exclusive approaches to science teaching. In this chapter, the authors present their framework for SSI instruction, socio-scientific issue and model-based learning (SIMBL), that emphasizes both disciplinary knowledge and its social implications. In particular, the authors argue that the integration of scientific modeling and socio-scientific reasoning (SSR) can advance students' competencies in both areas, thus promoting students' scientific literacy. The authors use an illustrative example from their work with elementary students to demonstrate the connection between students' modeling practice and their SSR. The authors conclude the chapter by introducing the epistemic tools developed to support students' modeling practice and SSR as well as implications for classroom enactments.

scholarly journals Modeling competence in science education

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Mei-Hung Chiu ◽  
Jing-Wen Lin
Keyword(s):  
Science Education ◽  
Scientific Literacy ◽  
Scientific Practice ◽  
Modeling Processes ◽  
Assessment Instruments ◽  
Theoretical Understanding ◽  
Modeling Competence ◽  
Teacher Professional ◽  
Modeling Practice ◽  
Models And Modeling

AbstractResearch on the understanding of the nature of models and modeling processes in science education have received a lot of attention in science education. In this article, we make five claims about the research on modeling competence in science education. The five claims are (1) the development of modeling competence in practice is essential to scientific literacy for twenty-first century citizens, (2) further research is needed to build a holistic and theoretical understanding of models and modeling knowledge (MMingK), (3) providing a modeling-based scaffolding framework for meaningful and active authentic learning is to enhance student’s engagement of scientific practice, (4) appropriate formative assessment instruments and evaluation rubrics to assess students’ modeling processes and products within the context of modeling practice should be developed, and (5) research on learning progression in modeling competence needs to be intertwined with MMingK and modeling practice. Implications for student learning and teacher professional development will be drawn from existing literature.

scholarly journals The Language of Caring: Digital Human Modeling, Practice Patterns, and Performance Assessment

2015 ◽  
Vol 3 ◽  
pp. 3788-3795
Author(s):  
J.R. Hotchkiss ◽  
J.D. Paladino ◽  
C.W. Brackney ◽  
A.M. Kaynar ◽  
P.S. Crooke
Keyword(s):  
Performance Assessment ◽  
Practice Patterns ◽  
Digital Human Modeling ◽  
Human Modeling ◽  
Modeling Practice ◽  
And Performance ◽  
Digital Human

Thorough Verification and Validation of CFD Prediction of FPSO Wind Load for Confident Applications

2019 ◽  
Author(s):  
Wei Xu ◽  
Zhenjia (Jerry) Huang ◽  
Hyunjoe Kim
Keyword(s):  
Model Test ◽  
Cfd Simulation ◽  
Domain Size ◽  
Wind Loads ◽  
Cfd Modeling ◽  
Tunnel Floor ◽  
Mesh Resolution ◽  
Layer Effect ◽  
Modeling Practice ◽  
Prism Layer

Abstract This paper presents our verification work on CFD modeling practice for the prediction of FPSO wind loads. The modeling practice was developed from the TESK CFD JDP [1]. In the verification, the measured data from a benchmark model test were used to check CFD simulation results. The exact physical model of the model test was used in the numerical modeling (model-of-the-model). To establish high confidence in the CFD modeling and simulations, the modeling practice was thoroughly verified, which covered the following critical elements: mesh resolution, domain size, outlet boundary condition, turbulence model, Reynolds effect, wind profile, prism layer effect on total wind forces, effects of the gap between wind tunnel floor and model bottom, blockage effect due to tunnel side walls and ceiling, and effects of geometry details (small size pipes). The verification results show that CFD can be used as an alternative tool for predicting wind loads and moments on a FPSO for engineering purposes following the modeling practice, and careful QA and QC.

Ecological models and pesticide risk assessment: Current modeling practice

2010 ◽  
Vol 29 (4) ◽  
pp. 1006-1012 ◽  
Author(s):  
Amelie Schmolke ◽  
Pernille Thorbek ◽  
Peter Chapman ◽  
Volker Grimm
Keyword(s):  
Risk Assessment ◽  
Ecological Models ◽  
Pesticide Risk Assessment ◽  
Modeling Practice
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