Remediation design to improve culvert passage for small-bodied fish

2020 ◽  
pp. 1831-1836
Author(s):  
M. Knapp ◽  
H. Friedrich ◽  
P. Franklin ◽  
C. Baker ◽  
J. Montgomery
Keyword(s):  
Remediation Design

scholarly journals Evaluating Cultural Landscape Remediation Design Based on VR Technology

2021 ◽  
Vol 10 (6) ◽  
pp. 423
Author(s):  
Zhengsong Lin ◽  
Lu Zhang ◽  
Su Tang ◽  
Yang Song ◽  
Xinyue Ye
Keyword(s):  
Cultural Landscape ◽  
Aesthetic Experience ◽  
Water Environment ◽  
Vegetation Coverage ◽  
Visual Fatigue ◽  
Environment Quality ◽  
Rural Revitalization ◽  
Remediation Design ◽  
Ecological Remediation

Due to the recent excessive pursuit of rapid economic development in China, the cultural heritage resources have been gradually destroyed. This paper proposes cultural recovery and ecological remediation patterns, and adopts virtual reality (VR) technology to evaluate the visual aesthetic effect of the restored landscape. The results show that: (1) the average vegetation coverage increased, providing data support for remediation design evaluation; and (2) the fixation counts and average saccade counts of the subjects increased after the remediation design, indicating that the restored cultural landscape reduced visual fatigue and provided a better visual aesthetic experience. Furthermore, the comparative analysis of the quality of the water environment shows that the remediation design project improved the ecological environment quality of the relics area. The results of this study will contribute to rural revitalization in minority areas in southwest China.

Vibration diagnosis and remediation design for an x-ray optics stitching interferometer system

2004 ◽  
Author(s):  
Curt A. Preissner ◽  
Lahsen Assoufid ◽  
Deming Shu
Keyword(s):  
Ray Optics ◽  
X Ray ◽  
Remediation Design

scholarly journals Well Rate and Placement for Optimal Groundwater Remediation Design with A Surrogate Model

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2233 ◽  
Author(s):  
Sbai
Keyword(s):  
Quality Management ◽  
Solute Transport ◽  
Groundwater Remediation ◽  
Simulation Optimization ◽  
Three Dimensional ◽  
Optimal Designs ◽  
Management Model ◽  
Decision Variables ◽  
Quality Management Model ◽  
Remediation Design

A new surrogate-assisted optimization formulation for groundwater remediation design was developed. A stationary Eulerian travel time model was used in lieu of a conservative solute transport model. The decision variables of the management model are well locations and their flow rates. The objective function adjusts the residence time distribution between all pairs of injection-production wells in the remediation system. This goal is achieved by using the Lorenz coefficient as an effective metric to rank the relative efficiency of many remediation policies. A discrete adjoint solver was developed to provide the sensitivity of the objective function with respect to changes in decision variables. The quality management model was checked with simple solutions and then applied to hypothetical two- and three-dimensional test problems. The performance of the simulation-optimization approach was evaluated by comparing the initial and optimal remediation designs using an advective-dispersive solute transport simulator. This study shows that optimal designs simultaneously delay solute transport breakthrough at pumping wells and improve the sweep efficiency leading to smaller cleanup times. Well placement optimization in heterogeneous porous media was found to be more important than well rate optimization. Additionally, optimal designs based on two-dimensional models were found to be more optimistic suggesting a direct use of three-dimensional models in a simulation-optimization framework. The computational budget was drastically reduced because the proposed surrogate-based quality management model is generally cheaper than one single solute transport simulation. The introduced model could be used as a fast, but first-order, approximation method to estimate pump-and-treat capital remediation costs. The results show that physically based low-fidelity surrogate models are promising computational approaches to harness the power of quality management models for complex applications with practical relevance.

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