Activated Carbon and Clay Minerals for the Sorptive Removal of Denatonium Ions from Denatonium Benzoate Solutions

This study assessed the feasibility of utilizing activated carbon and clay minerals for treating water impacted with the bittering agent denatonium benzoate (DB). Our specific study objectives were to 1) evaluate denatonium ion sorption to smectite clay minerals (bentonite and hectorite) and activated carbon (powdered and granular) at constant pH and ionic strength and 2) examine the impact of pH on denatonium ion sorption to each solid material. The experimental results indicated that high doses (33,000 mg/L) of as-received granular activated carbon and as-received clay minerals completely removed denatonium from aqueous solutions containing 100 - 1000 mg/L denatonium benzoate. Powdered activated carbon at doses of 5 - 100 mg/L exhibited favorable monolayer sorption of denatonium ions from a pH 6.95, 70 mg/L aqueous denatonium benzoate solution with a Langmuir separation factor (r) of 0.481, a maximum sorption capacity (Sm) of 74 mg/g, and a Langmuir constant of 15.3 L/g. A maximum removal of 23% of denatonium was achieved at the highest powdered activated carbon dosage employed. Denatonium ion removal with peroxide treated bentonite and peroxide treated hectorite did not result in complete removal of the ion and exhibited favorable sorption as evidenced by Freundlich 1/n values ranging from 0.803 to 1.194;Freundlich constants (Kf) ranged from 8 ng/L to 575 ng/L. Denatonium ion sorption to peroxide treated bentonite appeared to depend on pH while hectorite sorption of denatonium ions was independent of hydrogen ion concentrations. For powdered activated carbon adsorption, as pH increased denatonium ion sorption decreased. Overall, the work demonstrates that denatonium can be effectively removed from water via activated carbon or clay mineral sorption.

Uncertainty quantification and reduction in the characterization of subsurface stratigraphy using limited geotechnical investigation data

Subsurface stratigraphy is critical to the design,construction,and subsequent performance of geotechnical structures.However,in practice it is impossible to identify the stratigraphy of a subsurface geological domain with absolute certainty,due to the limitations imposed by geotechnical investigation techniques and project budgets.This paper presents a subsurface stratigraphic modeling and uncertainty quantification approach,which is established based on an improved and extended geological modeling technique previously established by the author and others,for simulating the stratigraphy of both two-dimensional(2D)and three-dimensional(3D)cases with more complex geological features.Furthermore,this approach provides quantitative evaluation of the amount of stratigraphic uncertainty in the current interpretation and enables the systematic reduction of stratigraphic uncertainty through the investigation of additional targeted borehole drilling locations.Illustrative examples,including artificial cases as well as two real cases from existing geotechnical projects,are presented in this study to demonstrate the use of the proposed analysis approach.

Evaluation of the contract reliability for alternative infrastructure project delivery: a contract engineering method

Governments at all levels are increasingly motivating the private sector to participate in infrastructure development using alternative project delivery methods to relieve financial burden. When designing contracts, governments usually offer incentives while requiring cost or time guarantee to balance project attractiveness to the private sector and fair protection of public interest. However, a practical and critical problem is how to properly design these provisions. Although previous studies have investigated the value of these provisions, a knowledge gap still exists with respect to methods of fairly and effectively designing such provisions. This study fills this gap by developing a methodology that analyzes the appropriateness of guarantee or warranty provisions for contracts. In this study, a contract reliability index is constructed, and a process of evaluating contract reliability is proposed. The New Mexico Highway 44 project, in which three warranty provision arrangements are investigated, is used as a case study to illustrate the analysis process. Results show that although a ceiling clause can effectively motivate the private sector to participate in the project, it sacrifices a significant amount of public benefits. By contrast, although a warranty option can protect public benefits, it cannot effectively incentivize the private sector. A combination of the ceiling clause and the warranty option will therefore result in improved contract provision design. The proposed methodology in this study is especially useful for governments in properly determining contract clauses in infrastructure development.

Finding patterns in subsurface using Bayesian machine learning approach

Stochastic simulation approaches and uncertainty quantification are usually adopted for gaining insight into variability in soil stratigraphy configurations.Previous investigations at geotechnical site characterization and interpretation can be broadly categorized into geostatistics-and process-based methods.On the other hand,modern site exploration techniques provide high-quality,dense datasets in physical spaces with high resolution,either directly from sensors(for example,cone penetration testing data)or indirectly from geophysical inversion(such as seismic inversion,electromagnetic induction inversion,and ground penetrating radar).In this work,anisotropy and heterogeneity are considered as possible patterns that inherently exist in the observations,and these are inferred and described in a Bayesian manner.To this end,a Bayesian machine learning approach is employed to extract these patterns from the original or interpreted data.The patterns are divided into two parts:spatial and statistical patterns.These patterns are considered as the"hidden link"among multiple spatial datasets.The proposed modeling method is demonstrated using a real-world,one-dimensional example as well as two two-dimensional numerical examples.It is revealed that the proposed clustering approach is a promising tool for subsurface modeling and pattern extraction.