Alt text of image

Submit Paper »

Background

This Special Collection (SC) aims to gather contributions to advance the state-of-the-art methods and applications of uncertainty propagation in high-dimensional stochastic systems. Effective uncertainty propagation is critical for rational decision-making, risk assessment, and optimization of engineering systems. Particularly, high-dimensional stochastic systems represent a significant class of problems encountered in various domains. Nevertheless, uncertainty propagation in high-dimensional settings poses significant challenges due to the “curse of dimensionality”. Traditional methods often become computationally prohibitive. Consequently, there is a growing need for advanced techniques to handle the complexity of high-dimensional systems accurately and efficiently. This SC focuses on efficient analytical, data-driven, and computational methods for uncertainty propagation, novel control techniques for stochastic systems, and advanced optimization approaches. Grounded in solid theory, these methods aim for real-world applications, bridging the gap between theory and practice with practical solutions in aerospace, civil engineering, energy systems, and environmental modeling.

Topics

Relevant topics may include but not limited to:

  • Advanced numerical techniques for linear and nonlinear static and dynamic systems with high-dimensional random or parameterized inputs, including but not limited to surrogate modeling methods, multilevel and multifidelity methods, machine learning methods, and the corresponding engineering applications.
  • Analysis, control, and optimization of high-dimensional stochastic systems, including but not limited to robust control, stochastic optimization, uncertainty-aware decision-making in nonlinear systems, hybrid methods for real-time control under uncertainty, and the corresponding engineering applications.
  • Data-driven high-dimensional stochastic problems, including but not limited to machine learning and AI for high-dimensional uncertainty propagation, data-driven high-dimensional optimization and control, Bayesian approaches, data assimilation for high-dimensional systems, and the corresponding engineering applications.
  • Probability density/distribution evolution-type methods for high-dimensional stochastic systems, and the corresponding engineering applications.

Special Issue Publication Dates

Paper submission deadline: April 30, 2025

Initial review completed: July 31, 2025

Publication date: December 31, 2025

Guest Editors

Submission Guidelines

  • Please submit your manuscript via the Journal of ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering website.
  • If you already have an Editorial Manager account, log in as author and select Submit Paper at the bottom of the page. If you do not have an account, select Submissions and follow the steps. In either case, at the Paper Submittal page, select the Journal of ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering and then select the special collection Risk and Reliability Analysis of Resilient Civil Engineering Structures with Vibration Control Devices.
  • Detailed information on the submission process is provided in the “Publishing in ASCE Journals” section of the ASCE Author Center .
  • Papers received after the deadline or papers not selected for inclusion in the Special Issue may be accepted for publication in a regular issue.

Please note that all accepted papers submitted in response to this Call for Papers will be published in regular issues of the Journal of ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering and assembled online on a page dedicated to this Special Collection. See Journal of ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering Special Collections for the list of Special Collections already published.