Results 61 to 70 of about 64,076 (261)

Nonlinear modeling, estimation and predictive control in APMonitor

Computers & Chemical Engineering, 2014
This paper describes nonlinear methods in model building, dynamic data reconciliation, and dynamic optimization that are inspired by researchers and motivated by industrial applications. A new formulation of the l1-norm objective with a dead-band for estimation and control is presented.
John D. Hedengren, Reza Asgharzadeh Shishavan, Kody M. Powell, Thomas F. Edgar   +3 more
openaire   +2 more sources

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

High‐Temperature Nanoindentation of Metals: Assessing Thermal Drift, Frame Compliance, and Chemical Composition Effects on the Reported Mechanical Properties

Advanced Engineering Materials, EarlyView.
Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova, Steffen Brinckmann, Ruth Schwaiger   +2 more
wiley   +1 more source

Nonlinear Model Predictive Control for Internet of Things Using Particle Swarm Optimization and Cloud Computing

IEEE Access
This paper proposes a novel model predictive control design for Internet of Things (IoT) applications by using the generalized opposition-based learning particle swarm optimization algorithm and cloud computing.
B. Devanathan, P. Selvaraj, A. Suyampulingam   +2 more
doaj   +1 more source

Forecast-Triggered Model Predictive Control of Constrained Nonlinear Processes with Control Actuator Faults

Mathematics, 2018
This paper addresses the problem of fault-tolerant stabilization of nonlinear processes subject to input constraints, control actuator faults and limited sensor–controller communication.
Da Xue, Nael H. El-Farra
doaj   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Closed-Loop Control of Variable Stiffness Actuated Robots via Nonlinear Model Predictive Control

IEEE Access, 2015
Variable stiffness actuation has recently attracted great interest in robotics, especially in areas involving a high degree of human-robot interaction. After investigating various design approaches for variable stiffness actuated (VSA) robots, currently ...
Altay Zhakatayev, Matteo Rubagotti, Huseyin Atakan Varol   +2 more
doaj   +1 more source

Optimization of the Production of Rubber Compounds Using Mathematical Models

Advanced Engineering Materials, EarlyView.
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann   +7 more
wiley   +1 more source

Molecular Dynamics Studies of Shape Memory Polymers: From Bead–Spring Models to Atomistic Simulations

Advanced Engineering Materials, EarlyView.
Coarse‐grained (left) and atomistic (right) models of the shape memory polymer ESTANE ETE 75DT3 are shown schematically. The two representations bridge molecular detail and mesoscopic description. Both models capture shape memory behavior, linking segmental mobility and conformational relaxation of anisotropic chains to macroscopic recovery, and ...
Fathollah Varnik
wiley   +1 more source

Experimental Characterization and Constitutive Modeling of the Effect of Prior Inelastic Strain on the Viscoplastic Behavior of AD730 at 700 °C

Advanced Engineering Materials, EarlyView.
This study shows that superalloys used in aircraft engine disks become much more prone to deformation at high temperatures if they have been strained during manufacturing. This effect increases with the level of prior strain but eventually reaches a limit.
Fabio Machado Alves da Fonseca, Patrick Villechaise, Malik Durand, Arnaud Longuet, Florent Coudon, Loïc Signor, Julien De Jaeger, Dominique Eyidi, Nathalie Bozzolo, Jonathan Cormier   +9 more
wiley   +1 more source