scholarly journals Method for an Automated Optimization of Fiber Patch Placement Layup Designs

2015 ◽  
Vol 5 (2) ◽  
pp. 37-46 ◽  
Author(s):  
Benjamin Fischer ◽  
Bernhard Horn ◽  
Christian Bartelt ◽  
Yannick Blößl
Keyword(s):  
Automated Optimization ◽  
Patch Placement

scholarly journals Automated Optimization of Intersections Using a Genetic Algorithm

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 15452-15468 ◽  
Author(s):  
Luis Cruz-Piris ◽  
Miguel A. Lopez-Carmona ◽  
Ivan Marsa-Maestre
Keyword(s):  
Genetic Algorithm ◽  
Automated Optimization

Semi-automated Optimization of the CHARMM36 Lipid Force Field to Include Explicit Treatment of Long-Range Dispersion

2021 ◽  
Vol 17 (3) ◽  
pp. 1562-1580 ◽  
Author(s):  
Yalun Yu ◽  
Andreas Krämer ◽  
Richard M. Venable ◽  
Andrew C. Simmonett ◽  
Alexander D. MacKerell ◽  
...  
Keyword(s):  
Force Field ◽  
Long Range ◽  
Automated Optimization

Cocaine Levels in Sweat Collection Patches Vary by Location of Patch Placement and Decline Over Time*

2004 ◽  
Vol 28 (4) ◽  
pp. 253-259 ◽  
Author(s):  
Naoto Uemura ◽  
Rajneesh P. Nath ◽  
Martha R. Harkey ◽  
Gary L. Henderson ◽  
John Mendelson ◽  
...  
Keyword(s):  
Patch Placement ◽  
Sweat Collection ◽  
Over Time

scholarly journals Automated Optimization of Water–Water Interaction Parameters for a Coarse-Grained Model

2014 ◽  
Vol 118 (6) ◽  
pp. 1603-1611 ◽  
Author(s):  
Joseph C. Fogarty ◽  
See-Wing Chiu ◽  
Peter Kirby ◽  
Eric Jakobsson ◽  
Sagar A. Pandit
Keyword(s):  
Coarse Grained ◽  
Interaction Parameters ◽  
Coarse Grained Model ◽  
Water Interaction ◽  
Automated Optimization

Optimization of a High Pressure Industrial Fan

2021 ◽  
Author(s):  
Edward De Jesús Rivera ◽  
Fanny Besem-Cordova ◽  
Jean-Charles Bonaccorsi
Keyword(s):  
Pressure Rise ◽  
Critical Conditions ◽  
Manufacturing Constraints ◽  
Efficient Design ◽  
Machine Performance ◽  
Mass Flow Rates ◽  
Mining Tool ◽  
Automated Optimization ◽  
Cfd Optimization ◽  
Impeller Geometry

Abstract Fans are used in industrial refineries, power generation, petrochemistry, pollution control, etc. These fans can perform in sometimes extreme, mission-critical conditions. The design of fans has historically relied on turbomachinery affinity laws, resulting in oversized machines that are expensive to manufacture and transport. With the increasingly lower CPU cost of fluid modeling, designers can now turn to CFD optimization to produce the necessary machine performance and flow conditions while respecting manufacturing constraints. The objective of this study is to maximize the pressure rise across an industrial fan while respecting manufacturing constraints. First, a 3D scan of the baseline impeller is used to create the CFD model and validated against experimental data. The baseline impeller geometry is then parameterized with 21 free parameters driving the shape of the hub, shroud, blade lean and camber. A fully automated optimization process is conducted using Numeca’s Fine™/Design3D software, allowing for a CPU-efficient Design Of Experiment (DOE) database generation and a surrogate model using the powerful Minamo optimization kernel and data-mining tool. The optimized impeller coupled with a CFD-aided redesigned volute showed an increase in overall pressure rise over the whole performance line, up to 24% at higher mass flow rates compared to the baseline geometry.

scholarly journals Using Splitters to Control Secondary Flow

2017 ◽  
Vol 139 (09) ◽  
pp. 58-59
Author(s):  
C. Clark ◽  
G. Pullan
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Kinetic Energy ◽  
Secondary Flow ◽  
Boundary Layers ◽  
Experimental Tests ◽  
Optimization Techniques ◽  
Automated Optimization

This article elaborates the concept of splitter vanes in controlling secondary flow. Secondary flow vortices are formed by the rotation of vorticity filaments, located in the endwall boundary layers, as the filaments move through the passage. The connection between the number of stators and the secondary kinetic energy suggests that the only way to significantly reduce the mixing loss is to increase the number of blades in the row. The designs evaluated were produced with fast turn-around computational fluid dynamics (10 minutes per solution) and automated optimization techniques. Experimental tests showed that the theory was correct, and that by increasing vane count, the secondary kinetic energy was reduced by up to 80%.

Automated Optimization of Stellarator Coils

1998 ◽  
Vol 33 (2) ◽  
pp. 106-117 ◽  
Author(s):  
Michael Drevlak
Keyword(s):  
Automated Optimization

LPC Blade and Non-Axisymmetric Hub Profiling Optimization Using Multi-Fidelity Non-Intrusive POD Surrogates

2017 ◽  
Author(s):  
Tariq Benamara ◽  
Piotr Breitkopf ◽  
Ingrid Lepot ◽  
Caroline Sainvitu
Keyword(s):  
High Performance ◽  
High Efficiency ◽  
High Fidelity ◽  
Present Contribution ◽  
Compressor Blades ◽  
High Fidelity Simulations ◽  
Optimization Methodology ◽  
Set Up ◽  
Automated Optimization ◽  
Proper Orthogonal

The present contribution proposes a Reduced Order Model based multi-fidelity optimization methodology for the design of highly loaded blades in low pressure compressors. Environmental, as well as, economical limitations applied to engine manufacturers make the design of modern turbofans an extremely complex task. A smart compromise has to be found to guarantee both a high efficiency and a high average stage loading imposed for mass reduction constraints, while satisfying stability requirements. The design of compressor blades, usually involves at the same time a dedicated parametrization set-up in highdimensional space and high-fidelity simulations capturing, at least, efficiency and stability as most impacting phenomena. Despite recent advances in the high-performance computing area, introducing high-fidelity simulations into automated optimization, or even surrogate assisted optimization, loops still stands as a endeavor for engineers. In this framework, the proposed methodology is based on multi-fidelity surrogate models capable of representing the physics at hand in reduced spaces inferred from both precise, albeit costly, high-fidelity simulations and abundant, yet less accurate lower-fidelity data. Finally, we investigate the coupling of the proposed hierarchised multi-fidelity non-intrusive Proper Orthogonal Decomposition based surrogates with an evolutionary algorithm to reduce the number of high-fidelity simulation calls towards the targeted optimum.

Automated Optimization in HSPA Radio Network Planning

2010 ◽  
pp. 271-295
Author(s):  
IANA SIOMINA ◽  
DI YUAN ◽  
FREDRIK GUNNARSSON
Keyword(s):  
Network Planning ◽  
Radio Network ◽  
Automated Optimization ◽  
Radio Network Planning
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