Optimal siting of rainwater harvesting systems for reducing combined sewer overflows at city scale.

The installation of green infrastructure (GI) is an effective approach to manage urban stormwater and combined sewer overflow (CSO) by restoring pre-development conditions in urban areas. Research on simulation-optimization techniques to aid with GI planning decision-making is expanding. However, due to high computational expense, the simulation-optimization methods are often based on design storm events, and it is unclear how much different rainfall scenarios (i.

Deep learning tools for the cancer clinic: an open-source framework with head and neck contour validation.

Background: With the rapid growth of deep learning research for medical applications comes the need for clinical personnel to be comfortable and familiar with these techniques. Taking a proven approach, we developed a straightforward open-source framework for producing automatic contours for head and neck planning computed tomography studies using a convolutional neural network (CNN).

Methods: Anonymized studies of 229 patients treated at our clinic for head and neck cancer from 2014 to 2018 were used to train and validate the network.

Parameterizing sorption isotherms using a hybrid global-local fitting procedure.

Predictive modeling of the transport and remediation of groundwater contaminants requires an accurate description of the sorption process, which is usually provided by fitting an isotherm model to site-specific laboratory data. Commonly used calibration procedures, listed in order of increasing sophistication, include: trial-and-error, linearization, non-linear regression, global search, and hybrid global-local search. Given the considerable variability in fitting procedures applied in published isotherm studies, we investigated the importance of algorithm selection through a series of numerical experiments involving 13 previously published sorption datasets.

Isotherm ranking and selection using thirteen literature datasets involving hydrophobic organic compounds.

Numerous isotherm expressions have been developed for describing sorption of hydrophobic organic compounds (HOCs), including "dual-mode" approaches that combine nonlinear behavior with a linear partitioning component. Choosing among these alternative expressions for describing a given dataset is an important task that can significantly influence subsequent transport modeling and/or mechanistic interpretation. In this study, a series of numerical experiments were undertaken to identify "best-in-class" isotherms by refitting 10 alternative models to a suite of 13 previously published literature datasets.

Application of heuristic optimization techniques and algorithm tuning to multilayered sorptive barrier design.

Although heuristic optimization techniques are increasingly applied in environmental engineering applications, algorithm selection and configuration are often approached in an ad hoc fashion. In this study, the design of a multilayer sorptive barrier system served as a benchmark problem for evaluating several algorithm-tuning procedures, as applied to three global optimization techniques (genetic algorithms, simulated annealing, and particle swarm optimization). Each design problem was configured as a combinatorial optimization in which sorptive materials were selected for inclusion in a landfill liner to minimize the transport of three common organic contaminants.