Eugene J. LeBoeuf

Bio: Eugene J. LeBoeuf is an academic researcher from Vanderbilt University. The author has contributed to research in topics: Sorption & Humic acid. The author has an hindex of 24, co-authored 42 publications receiving 2425 citations. Previous affiliations of Eugene J. LeBoeuf include Oak Ridge Institute for Science and Education.

Watershed Modeling and its Applications: A State-of-the-Art Review

Abstract: Advances in the understanding of physical, chemical, and biological processes influencing water quality, cou- pled with improvements in the collection and analysis of hydrologic data, provide opportunities for significant innovations in the manner and level with which watershed-scale processes may be explored and modeled. This paper provides a re- view of current trends in watershed modeling, including use of stochastic-based methods, distributed versus lumped pa- rameter techniques, influence of data resolution and scalar issues, and the utilization of artificial intelligence (AI) as part of a data-driven approach to assist in watershed modeling efforts. Important findings and observed trends from this work include (i) use of AI techniques artificial neural networks (ANN), fuzzy logic (FL), and genetic algorithms (GA) to im- prove upon or replace traditional physically-based techniques which tend to be computationally expensive; (ii) limitations in scale-up of hydrological processes for watershed modeling; and (iii) the impacts of data resolution on watershed model- ing capabilities. In addition, detailed discussions of individual watershed models and modeling systems with their fea- tures, limitations, and example applications are presented to demonstrate the wide variety of systems currently available for watershed management at multiple scales. A summary of these discussions is presented in tabular format for use by water resource managers and decision makers as a screening tool for selecting a watershed model for a specific purpose.

Interfacing gis with water resource models: a state‐of‐the‐art review

Abstract: Two distinctive, independently developed technologies, geographic information systems (GIS) and predictive water resource models, are being interfaced with varying degrees of sophistication in efforts to simultaneously examine spatial and temporal phenomena. Neither technology was initially developed to interact with the other, and as a result, multiple approaches to interface GIS with water resource models exist. Additionally, continued model enhancements and the development of graphical user interfaces (GUIs) have encouraged the development of application “suites” for evaluation and visualization of engineering problems. Currently, disparities in spatial scales, data accessibility, modeling software preferences, and computer resources availability prevent application of a universal interfacing approach. This paper provides a state-of-the-art critical review of current trends in interfacing GIS with predictive water resource models. Emphasis is placed on discussing limitations to efficient interfacing and potential future directions, including recommendations for overcoming many current challenges.

Natural organic matter stabilizes carbon nanotubes in the aqueous phase

Abstract: This study investigates the aqueous stability of multi-walled carbon nanotubes (MWNTs) in the presence of natural organic matter (NOM). MWNTs were readily dispersed as an aqueous suspension in both model NOM (Suwannee River NOM (SR-NOM)) solutions and natural surface water (actual Suwannee River water with unaltered NOM background), which remained stable for over 1 month. Microscopic analyses suggested that the suspension consisted primarily of individually dispersed MWNTs. Concentrations of MWNTs suspended in the aqueous phase, quantified using thermal optical transmittance analysis (TOT), ranged from 0.6 to 6.9 mg/L as initial concentrations of MWNT and SR-NOM were varied from 50 to 500 mg/L and 10 to 100 mg/L, respectively. Suwannee River water showed a similar MWNT stabilizing capacity as compared to the model SR-NOM solutions. For the same initial MWNT concentrations, the concentrations of suspended MWNT in SR-NOM solutions and Suwannee River water were considerably higher than that in a solution of ...

Lignin as Renewable Raw Material

Abstract: Lignin is by far the most abundant substance based on aromatic moieties in nature, and the largest contributor to soil organic matter. Millions of tonnes of several lignin preparations are produced by the paper industry every year, and a minimal amount of lignin is isolated by direct extraction of lignin from plants. Lignin is used either directly or chemically modified, as a binder, dispersant agent for pesticides, emulsifier, heavy metal sequestrant, or component for composites and copolymers. For value-added applications of lignin to be improved, medium- and long-term conversion technologies must be developed, especially for the preparation of low-molecular-weight compounds as an alternative to the petrochemical industry.

Predictions of effective physical properties of complex multiphase materials

Abstract: Theoretical prediction of effective properties for multiphase material systems is very important not only to analysis and optimization of material performance, but also to new material designs. This review first examines the issues, difficulties and challenges in prediction of material behaviors by summarizing and critiquing the existing major analytical approaches dealing with material property modeling. The focus then shifts to some recent advances in numerical methodology that are able to predict more accurately and efficiently the effective physical properties of multiphase materials with complex internal microstructures. A random generation-growth algorithm is highlighted for reproducing multiphase microstructures, statistically equivalent to the actual systems, based on the geometrical and morphological information obtained from measurements and experimental estimations. Then a high-efficiency lattice Boltzmann solver for the corresponding governing equations is described which, while assuring energy conservation and the appropriate continuities at numerous interfaces in a complex system, has demonstrated its numerical power in yielding accurate solutions. Various applications are provided to validate the feasibility, effectiveness and robustness of this new methodology by comparing the predictions with existing experimental data from different transport processes, accounting for the effects due to component size, material anisotropy, internal morphology and multiphase interactions. The examples given also suggest even wider potential applicability of this methodology to other problems as long as they are governed by the similar partial differential equation(s). Thus, for given system composition and structure, this numerical methodology is in essence a model built on sound physics principles with prior validity, without resorting to ad hoc empirical treatment. Therefore, it is useful for design and optimization of new materials, beyond just predicting and analyzing the existing ones.