Results 151 to 160 of about 707,486 (332)

Supporting the Changing Research Practices of Civil and Environmental Engineering Scholars

, 2019
Danielle D. Cooper, Rebecca Springer, Jessica G. Benner, David Bloom, E. Carrillo, Alexander J. Carroll, B. Chang, Xiaoju Chen, Erin Daix, E. Dommermuth, Rachel Figueriredo, Jennifer Haas, Carly A. Hafner, Angela Henshilwood, Alexandra C. Krogman, Rebecca Kuglitsch, Sabine Lanteri, Abbey Lewis, Lisha Li, Matt Marsteller, T. Melvin, Todd Michelson-Ambelang, William H. Mischo, Colin Nickels, Virginia Pannabecker, Fred Rascoe, Mary C. Schlembach, Yi Shen, Erin M. Smith, Michelle Spence, Kris Stacy-Bates, E. Thomas, Larry Thompson, Mindy Thuna, C. Wiley, Sarah Young, Siu Hong Yu   +36 more
semanticscholar   +1 more source

Experimental validation of the RESPONSE framework against cyberattacks on cyber‐physical process systems

AIChE Journal, EarlyView.
Abstract This work experimentally validates the RESPONSE (Resilient Process cONtrol SystEm) framework as a solution for maintaining safe, continuous operation of cyber‐physical process systems under cyberattacks. RESPONSE implements a dual‐loop architecture that runs a networked online controller in parallel with a hard‐isolated offline controller ...
Luyang Liu, Pu Du, Zaman Sajid, Benjamin Wilhite, Costas Kravaris, Faisal Khan   +5 more
wiley   +1 more source

Spheres, tears, and spears: Regulating the perimeter and circularity of millimeter‐sized alginate hydrogel beads

AIChE Journal, EarlyView.
Abstract Generating hydrogel beads pertains to many engineering applications. We examined two alginate‐based fluids at three concentrations of alginate, cAG$$ {c}_{\mathrm{AG}} $$. We used the “Map of Misery” to determine which material property (viscosity, elasticity, and inertia) drives droplet formation.
Conor G. Harris, Katherine D. Bandettini, Hannah K. Gedde, Lewis Semprini, Kaitlin C. Fogg, Willie E. Rochefort   +5 more
wiley   +1 more source

A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

Advanced Intelligent Discovery, EarlyView.
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai, Wenrui Wang, Rui Chen, Tong Yu, Xiaojuan Zheng, Hua Shao, Dashan Shang, Ling Li, Lado Filipovic   +8 more
wiley   +1 more source

Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios, Léon Chiriatti, Simon Poppinga, Thomas Speck, Vincent Le Houérou   +4 more
wiley   +1 more source

A Dual‐Ion Multiphysics Model for Smart and Sustainable Sensors Based on Bacterial Cellulose

Advanced Intelligent Systems, EarlyView.
Bacterial cellulose (BC), functionalized with ionic liquids (ILs) and conductive polymers, offers promise for sustainable sensor applications. To enable real‐world integration, this work presents the first dual‐carrier, multiphysics white‐box model of mechanoelectric transduction in BC–IL sensors, combining mechanical deformation and ion transport ...
Francesca Sapuppo, Giovanna Di Pasquale, Salvatore Graziani, Sara Sadat Hosseini, Luca Patané, Antonino Pollicino, Carlo Trigona, Maria Gabriella Xibilia   +7 more
wiley   +1 more source

Polymerase Chain Reaction. Perturbation Theory and Machine Learning Artificial Intelligence‐Experimental Microbiome Analysis: Applications to Ancient DNA and Tree Soil Metagenomics Cases of Study

Advanced Intelligent Systems, EarlyView.
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez, Estefania Ascencio, Jose M. Ageitos, Lucia Feijoo, Shan He, Amirreza Daghighi, Gerardo M. Casanola‐Martin, Cristian R. Munteanu, Santiago Rodriguez Yañez, Alejandro Pazos, Harbil Bediaga, Brenda Durand Ordiales, Raquel Esteban, Ana‐Maria Heres, Jorge Curiel Yuste, Lur Epelde, Bakhtiyor Rasulev, Tomas Gonzalez, Sonia Arrasate, Humberto González‐Diaz   +19 more
wiley   +1 more source

Effective Material Stiffness in Curved Actuators

Advanced Intelligent Systems, EarlyView.
A new actuator effective material stiffness measurement method is created. It produces a new metric called shape actuation modulus with the potential to help design actuators. This method shows that the smaller the curvature of hinge‐shaped actuators, the stiffer they are.
Charles de Kergariou, David Correa, Adam W. Perriman, Fabrizio Scarpa   +3 more
wiley   +1 more source

Correction: A numerical study of site effect and dynamic response of staged excavation supported by soil nail walls. [PDF]

Sci Rep
Maleki M, Mohammadnezhad H, Mir Mohammad Hosseini SM.   +2 more
europepmc   +1 more source

Utilization of electromigration in civil and environmental engineering—Processes, transport rates and matrix changes

Journal of Environmental Science and Health. Part A: Toxic/Hazardous Substances and Environmental Engineering, 2008
L. Ottosen, I. V. Christensen, Inge Rörig-Dalgård, P. Jensen, H. Hansen   +4 more
semanticscholar   +1 more source