Computationally Efficient Combined Plant Design and Controller Optimization Using a Coupling Measure

2012 ◽  
Vol 134 (7) ◽  
Author(s):  
Rakesh Patil ◽  
Zoran Filipi ◽  
Hosam Fathy
Keyword(s):  
Optimal Control ◽  
Computational Cost ◽  
Systems Design ◽  
Plant Design ◽  
Coupling Term ◽  
Control Optimization ◽  
Novel Approach ◽  
Design Variables ◽  
The Impact ◽  
Plant Control

This paper presents a novel approach to the optimization of a dynamic systems design and control. Traditionally, these problems have been solved either sequentially or in a combined manner. We propose a novel approach that uses a previously derived coupling measure to quantify the impact of plant design variables on optimal control cost. This proposed approach has two key advantages. First, because the coupling term quantifies the gradient of the control optimization objective with respect to plant design variables, the approach ensures combined plant/control optimality. Second, because the coupling term equals the integral of optimal control co-states multiplied by static gradient terms that can be computed a priori, the proposed approach is computationally attractive. We illustrate this approach using an example cantilever beam structural design and vibration control problem. The results show significant computational cost improvements compared to traditional combined plant/control optimization. This reduction in computational cost becomes more pronounced as the number of plant design variables increases.

IMMAESA

2021 ◽  
Vol 15 (1) ◽  
pp. 65-98
Author(s):  
Mhamed Zineddine
Keyword(s):  
Nuclear Power ◽  
Optimal Solution ◽  
Bat Algorithm ◽  
Cyber Attacks ◽  
Plant Design ◽  
Industrial Control Systems ◽  
Novel Approach ◽  
Commercial Off The Shelf ◽  
Ict Security ◽  
The Impact

The rise of digitization in industrial control systems using commercial off-the-shelf software has encouraged the use of existing IT security solutions. The aim of this study is to prevent intrusion detection and prevention systems' actions from affecting the normal functions of sensitive ICSs. A novel approach called IMMAESA based on a heuristic algorithm is proposed to evaluate the impact of IDPSs' actions when mitigating cyber-attacks. The crux of this novel approach is the IDPS does not react until it assesses the impact of its actions. The bat-algorithm is used to find an optimal solution that preserves the reliability of the system. IMMAESA method is simulated on a known nuclear power plant design, the APR1400. Results show that the proposed method lets the IDPS effectively makes tradeoffs before execution, thus, avoid any undesirable effects. The IDPS selects a set of actions (severity ~ 0,750 and reliability ~ 0,767) with minor consequences. Thus, the proposed method would be a major contribution to the ICT security field.

scholarly journals Assessment of Deterministic Shape Optimizations Within a Stochastic Framework for Supersonic Organic Rankine Cycle Nozzle Cascades

2019 ◽  
Vol 141 (7) ◽  
Author(s):  
Alessandro Romei ◽  
Pietro Marco Congedo ◽  
Giacomo Persico
Keyword(s):  
Shape Optimization ◽  
Computational Cost ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Objective Functions ◽  
Flow Solver ◽  
Design Variables ◽  
Stochastic Framework ◽  
Constraint Problem ◽  
The Impact

The design of converging–diverging blades for organic Rankine cycle (ORC) applications widely relies on automated shape-optimization processes. As a result, the optimization produces an adapted-nozzle cascade at the design conditions. However, only few works account for the uncertainties in those conditions and their consequences on cascade performance. The proposed solution, i.e., including uncertainties within the optimization routine, demands an overall huge computational cost to estimate the target output statistic at each iteration of the optimization algorithm. With the aim of understanding if this computational cost is avoidable, we study the impact of uncertainties in the design conditions on the robustness of deterministically optimized profiles. Several optimized blades, obtained with different objective functions, constraints, and design variables, are considered in the present numerical analysis, which features a turbulent compressible flow solver and a state-of-the-art uncertainty-quantification (UQ) method. By including measured field variations in the formulation of the UQ problem, we show that a deterministic shape optimization already improves the robustness of the profile with respect to the baseline configuration. Guidelines about objective functions and blade parametrizations for deterministic optimizations are also provided. Finally, a novel methodology to estimate the mass-flow-rate probability density function (PDF) for choked supersonic turbines is proposed, along with a robust reformulation of the constraint problem without increasing the computational cost.

Optimization of Passenger Car Door Impact Beam using Quasi Static CAE Analysis

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
S.P. Sundar Singh Sivam ◽  
Ganesh Babu Loganathan ◽  
K. Saravanan ◽  
V.G. Umasekar ◽  
T.P. Mohammed Rameez
Keyword(s):  
Computational Cost ◽  
Static Problem ◽  
Side Impact ◽  
Component Level ◽  
Passenger Car ◽  
Vehicle Simulation ◽  
Side Impacts ◽  
Beam Design ◽  
Design Variables ◽  
The Impact

Automotive side impacts are particularly dangerous as location of impact is very close to the passenger, who can be immediately reached by the impacting vehicle. FMVSS 214 static is a US safety regulation for occupant safety during side impacts, in which the vehicle is tested at static loading conditions to measure its load baring capacity and integrity of side closures. The CAE load case, virtually simulating the test, was handled as a quasi-static problem in this study. Impact beam is a component that helps in improving vehicle passive safety performance during side impacts by minimizing door intrusion to the occupant cabin. It plays an important role in achieving side impact regulatory norms. Through this study, a mass optimized front door impact beam design was developed for a passenger car with the help of CAE simulations; FMVSS 214S regulation norms are met. Component thickness, material and cross section shape were the design variables considered for the study. A methodology to perform the component level simulation of the impact beam loading such that it replicates component behaviour during full vehicle simulation was developed. This has helped in reducing the total problem calculation time in solver. This also has minimized the computational cost for the project. CAE simulations required for the study were done using LS-DYNA. ANSA and PRIMER were used as pre-processors and hyper-graph and meta-post were used for post processing.

Topology and Sizing Optimization of Micromixers Using Graph-Theoretical Representation and Genetic Algorithm

2017 ◽  
Author(s):  
Mitsuo Yoshimura ◽  
Koji Shimoyama ◽  
Takashi Misaka ◽  
Shigeru Obayashi
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Optimization Problems ◽  
Computational Cost ◽  
Kriging Model ◽  
Local Optimum ◽  
Sizing Optimization ◽  
Local Optima ◽  
Novel Approach ◽  
Design Variables

This paper proposes a novel approach for fluid topology optimization using genetic algorithm. In this study, the enhancement of mixing in the passive micromixers is considered. The efficient mixing is achieved by the grooves attached on the bottom of the microchannel and the optimal configuration of grooves is investigated. The grooves are represented based on the graph theory. The micromixers are analyzed by a CFD solver and the exploration by genetic algorithm is assisted by the Kriging model in order to reduce the computational cost. Three cases with different constraint and treatment for design variables are considered. In each case, GA found several local optima since the objective function is a multi-modal function and each local optimum revealed the specific characteristic for efficient mixing in micromixers. Moreover, we discuss the validity of the constraint for optimization problems. The results show a novel insight for design of micromixer and fluid topology optimization using genetic algorithm.

scholarly journals Multigrid methods and data assimilation ― Convergence study and first experiments on non-linear equations

2011 ◽  
Vol Volume 14 - 2011 - Special... ◽  
Author(s):  
Emilie Neveu ◽  
Laurent Debreu ◽  
François-Xavier Le Dimet
Keyword(s):  
Optimal Control ◽  
Data Assimilation ◽  
Linear Equations ◽  
Computational Cost ◽  
Multigrid Methods ◽  
Advection Equation ◽  
Non Linear ◽  
Discretization Errors ◽  
Correction Step ◽  
The Impact

International audience In order to limit the computational cost of the variational data assimilation process, we investigate the use of multigrid methods to solve the associated optimal control system. On a linear advection equation, we study the impact of the regularization term and the discretization errors on the efficiency of the coarse grid correction step introduced by the multigrid method. We show that even if for a perfect numerical model the optimal control problem leads to the solution of an elliptic system, discretization errors introduce implicit diffusion that can alter the success of the multigrid methods. Then we test the multigrids configuration and the influence of the algorithmic parameters on a non-linear Burgers equation to show that the algorithm is robust and converges much faster than the monogrid one. Afin de limiter le coût de calcul lié aux méthodes variationnelles d’assimilation de données, nous nous intéressons ici à l’utilisation de méthodes multigrilles pour la résolution de systèmes de contrôle optimal. Sur un modèle simple d’advection linéaire, nous étudions l’impact du terme de régularisation du contrôle optimal ainsi que l’impact des erreurs de discrétisation sur l’efficacité de la correction grille grossière introduite par cette méthode. En particulier, nous montrons que pour un modèle numérique parfait, le problème de contrôle optimal est elliptique mais que les erreurs de discrétisation introduisant une diffusion implicite peuvent altérer les performances de la méthode multigrille. Enfin, sur une équation de Burgers, non linéaire, nous étudions l’influence des différents paramètres inhérents aux méthodes multigrilles et montrons que ces méthodes sont robustes et convergent beaucoup plus rapidement que les méthodes monogrilles.

scholarly journals Brain drain and brain gain in Russia: Analyzing international migration of researchers by discipline using Scopus bibliometric data 1996–2020

2021 ◽  
Author(s):  
Alexander Subbotin ◽  
Samin Aref
Keyword(s):  
Brain Drain ◽  
Policy Development ◽  
Donor Country ◽  
International Mobility ◽  
Science System ◽  
Migration Rates ◽  
Net Migration ◽  
Novel Approach ◽  
Five Disciplines ◽  
The Impact

AbstractWe study international mobility in academia, with a focus on the migration of published researchers to and from Russia. Using an exhaustive set of over 2.4 million Scopus publications, we analyze all researchers who have published with a Russian affiliation address in Scopus-indexed sources in 1996–2020. The migration of researchers is observed through the changes in their affiliation addresses, which altered their mode countries of affiliation across different years. While only 5.2% of these researchers were internationally mobile, they accounted for a substantial proportion of citations. Our estimates of net migration rates indicate that while Russia was a donor country in the late 1990s and early 2000s, it has experienced a relatively balanced circulation of researchers in more recent years. These findings suggest that the current trends in scholarly migration in Russia could be better framed as brain circulation, rather than as brain drain. Overall, researchers emigrating from Russia outnumbered and outperformed researchers immigrating to Russia. Our analysis on the subject categories of publication venues shows that in the past 25 years, Russia has, overall, suffered a net loss in most disciplines, and most notably in the five disciplines of neuroscience, decision sciences, mathematics, biochemistry, and pharmacology. We demonstrate the robustness of our main findings under random exclusion of data and changes in numeric parameters. Our substantive results shed light on new aspects of international mobility in academia, and on the impact of this mobility on a national science system, which have direct implications for policy development. Methodologically, our novel approach to handling big data can be adopted as a framework of analysis for studying scholarly migration in other countries.

scholarly journals Optimal Pressure Boundary Control of Steady Multiscale Fluid-Structure Interaction Shell Model Derived from Koiter Equations

Fluids ◽  
2021 ◽  
Vol 6 (4) ◽  
pp. 149
Author(s):  
Andrea Chierici ◽  
Leonardo Chirco ◽  
Sandro Manservisi
Keyword(s):  
Optimal Control ◽  
Solid Wall ◽  
Fluid Structure Interaction ◽  
Computational Cost ◽  
Robin Boundary Condition ◽  
Design Parameters ◽  
Fluid Structure ◽  
Control Approach ◽  
Structure Interaction ◽  
Fluid Boundary

Fluid-structure interaction (FSI) problems are of great interest, due to their applicability in science and engineering. However, the coupling between large fluid domains and small moving solid walls presents numerous numerical difficulties and, in some configurations, where the thickness of the solid wall can be neglected, one can consider membrane models, which are derived from the Koiter shell equations with a reduction of the computational cost of the algorithm. With this assumption, the FSI simulation is reduced to the fluid equations on a moving mesh together with a Robin boundary condition that is imposed on the moving solid surface. In this manuscript, we are interested in the study of inverse FSI problems that aim to achieve an objective by changing some design parameters, such as forces, boundary conditions, or geometrical domain shapes. We study the inverse FSI membrane model by using an optimal control approach that is based on Lagrange multipliers and adjoint variables. In particular, we propose a pressure boundary optimal control with the purpose to control the solid deformation by changing the pressure on a fluid boundary. We report the results of some numerical tests for two-dimensional domains to demonstrate the feasibility and robustness of our method.

scholarly journals Analysis of High-Friction Surface Texture with Respect to Friction and Wear

Coatings ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 758
Author(s):  
Cibi Pranav ◽  
Minh-Tan Do ◽  
Yi-Chang Tsai
Keyword(s):  
Friction Coefficient ◽  
Surface Texture ◽  
Safety Concern ◽  
Future Research ◽  
Scanning System ◽  
Novel Approach ◽  
Texture Parameters ◽  
Aggregate Loss ◽  
Friction Surfaces ◽  
The Impact

High Friction Surfaces (HFS) are applied to increase friction capacity on critical roadway sections, such as horizontal curves. HFS friction deterioration on these sections is a safety concern. This study deals with characterization of the aggregate loss, one of the main failure mechanisms of HFS, using texture parameters to study its relationship with friction. Tests are conducted on selected HFS spots with different aggregate loss severity levels at the National Center for Asphalt Technology (NCAT) Test Track. Friction tests are performed using a Dynamic Friction Tester (DFT). The surface texture is measured by means of a high-resolution 3D pavement scanning system (0.025 mm vertical resolution). Texture data are processed and analyzed by means of the MountainsMap software. The correlations between the DFT friction coefficient and the texture parameters confirm the impact of change in aggregates’ characteristics (including height, shape, and material volume) on friction. A novel approach to detect the HFS friction coefficient transition based on aggregate loss, inspired by previous works on the tribology of coatings, is proposed. Using the proposed approach, preliminary outcomes show it is possible to observe the rapid friction coefficient transition, similar to observations at NCAT. Perspectives for future research are presented and discussed.

scholarly journals Reservoir-Induced Land Deformation: Case Study from the Grand Ethiopian Renaissance Dam

2021 ◽  
Vol 13 (5) ◽  
pp. 874
Author(s):  
Yu Chen ◽  
Mohamed Ahmed ◽  
Natthachet Tangdamrongsub ◽  
Dorina Murgulet
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Surface Deformation ◽  
Vertical Displacement ◽  
Nile River ◽  
Reservoir Volume ◽  
Novel Approach ◽  
Land Deformation ◽  
Large Scale Land ◽  
The Impact

The Nile River stretches from south to north throughout the Nile River Basin (NRB) in Northeast Africa. Ethiopia, where the Blue Nile originates, has begun the construction of the Grand Ethiopian Renaissance Dam (GERD), which will be used to generate electricity. However, the impact of the GERD on land deformation caused by significant water relocation has not been rigorously considered in the scientific research. In this study, we develop a novel approach for predicting large-scale land deformation induced by the construction of the GERD reservoir. We also investigate the limitations of using the Gravity Recovery and Climate Experiment Follow On (GRACE-FO) mission to detect GERD-induced land deformation. We simulated three land deformation scenarios related to filling the expected reservoir volume, 70 km3, using 5-, 10-, and 15-year filling scenarios. The results indicated: (i) trends in downward vertical displacement estimated at −17.79 ± 0.02, −8.90 ± 0.09, and −5.94 ± 0.05 mm/year, for the 5-, 10-, and 15-year filling scenarios, respectively; (ii) the western (eastern) parts of the GERD reservoir are estimated to move toward the reservoir’s center by +0.98 ± 0.01 (−0.98 ± 0.01), +0.48 ± 0.00 (−0.48 ± 0.00), and +0.33 ± 0.00 (−0.33 ± 0.00) mm/year, under the 5-, 10- and 15-year filling strategies, respectively; (iii) the northern part of the GERD reservoir is moving southward by +1.28 ± 0.02, +0.64 ± 0.01, and +0.43 ± 0.00 mm/year, while the southern part is moving northward by −3.75 ± 0.04, −1.87 ± 0.02, and −1.25 ± 0.01 mm/year, during the three examined scenarios, respectively; and (iv) the GRACE-FO mission can only detect 15% of the large-scale land deformation produced by the GERD reservoir. Methods and results demonstrated in this study provide insights into possible impacts of reservoir impoundment on land surface deformation, which can be adopted into the GERD project or similar future dam construction plans.

scholarly journals Towards a better understanding of the origins, chemical composition and aging of oxygenated organic aerosols: case study of a Mediterranean industrialized environment, Marseille

2013 ◽  
Vol 13 (15) ◽  
pp. 7875-7894 ◽  
Author(s):  
I. El Haddad ◽  
B. D'Anna ◽  
B. Temime-Roussel ◽  
M. Nicolas ◽  
A. Boreave ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Organic Aerosols ◽  
Industrial Emissions ◽  
Aerosol Mass Spectrometer ◽  
Statistical Confidence ◽  
Aerosol Mass ◽  
Novel Approach ◽  
Organic Markers ◽  
The Impact ◽  
First Time

Abstract. As part of the FORMES summer 2008 experiment, an Aerodyne compact time-of-flight aerosol mass spectrometer (cToF-AMS) was deployed at an urban background site in Marseille to investigate the sources and aging of organic aerosols (OA). France's second largest city and the largest port in the Mediterranean, Marseille, provides a locale that is influenced by significant urban industrialized emissions and an active photochemistry with very high ozone concentrations. Particle mass spectra were analyzed by positive matrix factorization (PMF2) and the results were in very good agreement with previous apportionments obtained using a chemical mass balance (CMB) approach coupled to organic markers and metals (El Haddad et al., 2011a). AMS/PMF2 was able to identify for the first time, to the best of our knowledge, the organic aerosol emitted by industrial processes. Even with significant industries in the region, industrial OA was estimated to contribute only ~ 5% of the total OA mass. Both source apportionment techniques suggest that oxygenated OA (OOA) constitutes the major fraction, contributing ~ 80% of OA mass. A novel approach combining AMS/PMF2 data with 14C measurements was applied to identify and quantify the fossil and non-fossil precursors of this fraction and to explicitly assess the related uncertainties. Results show with high statistical confidence that, despite extensive urban and industrial emissions, OOA is overwhelmingly non-fossil, formed via the oxidation of biogenic precursors, including monoterpenes. AMS/PMF2 results strongly suggest that the variability observed in the OOA chemical composition is mainly driven in our case by the aerosol photochemical age. This paper presents the impact of photochemistry on the increase of OOA oxygenation levels, formation of humic-like substances (HULIS) and the evolution of α-pinene SOA (secondary OA) components.

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