Efficient and automatic methods for flexible regression on spatiotemporal data, with applications to groundwater monitoring

Fitting statistical models to spatiotemporal data requires finding the right balance between imposing smoothness and following the data. In the context of P-splines, we propose a Bayesian framework for choosing the smoothing parameter which allows the construction of fully-automatic data-driven methods for fitting flexible models to spatiotemporal data. An implementation, which is highly computationally efficient and which exploits the sparsity of the design and penalty matrices, is proposed. The findings are illustrated using a simulation study and two examples, all concerned with the modelling of contaminants in groundwater. This suggests that the proposed strategy is more stable that competing methods based on the use of criteria such as GCV and AIC

Natural attenuation of dissolved petroleum fuel constituents in a fractured Chalk aquifer: Contaminant mass balance with probabilistic analysis

A plume-scale mass balance is developed to assess the natural attenuation (NA) of dissolved organic contaminants in fractured, dual porosity aquifers. This methodology can be used to evaluate contaminant distribution within the aquifer, plume source term, contaminant biodegradation and plume status. The approach is illustrated for a site on the UK Upper Chalk aquifer impacted by petroleum fuel containing MTBE and TAME. Variability in site investigation data and uncertainty in the mass balance was assessed using probabilistic analysis. The analysis shows that BTEX compounds are biodegraded primarily by denitrification and sulphate reduction in the aquifer, with an equivalent plume-scale first-order biodegradation rate of 0.49 year-1. Other biodegradation processes are less important. Sorption contributes to hydrocarbon attenuation in the aquifer but is less important for MTBE and TAME. Uncertainty in the plume source term and site hydrogeological parameters had the greatest effect on the mass balance. The probabilistic analysis enabled the most likely long-term composition of the plume source term to be deduced and provided a site-specific estimate of contaminant mass flux for the prediction of plume development. The mass balance methodology provides a novel approach to improve NA assessments for petroleum hydrocarbons and other organic contaminants in these aquifer settings

Robust design and optimization of stochastic wind-excited systems: an adaptive kriging-based approach

This research proposes a robust design framework for wind-excited systems in which performance is estimated at a system level in terms of state-of-the-art performance-based design metrics. In particular, the robust design problem is formulated as a stochastic optimization with objective the minimization of the variance of the performance metric. Constraints are also imposed on the initial cost of the system and expected value of the performance metric. To effectively treat the performance metrics within the optimization problem, adaptive kriging models of the deagreggated loss metrics are defined in terms of the second order statistics of the demands. By then relating the demand statistics to the design variables through the concept of the Auxiliary Variable Vector, a deterministic optimization sub-problem is defined that can handle high-dimensional design variable vectors and general stochastic excitation. By solving a sequence of sub-problems, each formulated in the solution of the previous, solutions to the original robust design problem are found. A case study consisting in a large-scale system subject to stochastic wind excitation is used to illustrate the applicability of the proposed framework.This research effort was supported in part by the National Science Foundation (NSF) through grants CMMI-1462084 and CMMI-1562388. This support is gratefully acknowledged

Performance optimization of uncertain and dynamic high-dimensional wind-excited systems

This paper focuses on the development of an efficient design optimization framework for wind-excited systems that is capable of handling not only high-dimensional and complex probability spaces, but also high-dimensional spaces of design parameters. Data-driven simulation models are utilized in assessing the system-level probabilistic measures. To efficiently solve the performance-based design optimization problem, a framework is proposed that is based on approximately decoupling the stochastic simulation from the optimization process. Local approximation models, constructed from results of a single stochastic simulation, are used to define a deterministic composite function that relates the design parameters to the system-level performance metrics. The explicit nature of this relationship is then exploited to define a sequence of deterministic optimization sub-problems that yield solutions to the original stochastic optimization problem. To illustrate the applicability of the proposed approach, a large-scale building system is optimized under stochastic wind tunnel-informed excitations and subject to system-level loss constraints.This research effort was supported in part by the National Science Foundation (NSF) through grants CMMI-1462084 and CMMI-1562388. This support is gratefully acknowledged

Influence of contaminant exposure on the development of aerobic ETBE biodegradation potential in microbial communities from a gasoline-impacted aquifer

Aerobic biodegradation of ethyl tert butyl ether (ETBE) in a gasoline-impacted aquifer was investigated in laboratory microcosms containing groundwater and aquifer material from ETBE-impacted and non-impacted locations amended with either ETBE, or ETBE plus methyl tert butyl ether (MTBE). As sole substrate, ETBE was biodegraded (maximum rate of 0.54 day^−1) without a lag in ETBE-impacted microcosms but with a lag of up to 66 days in non-impacted microcosms (maximum rate of 0.38 day^−1). As co-substrate, ETBE was biodegraded preferentially (maximum rate of 0.25 and 0.99 day^−1 in non-impacted and impacted microcosms, respectively) before MTBE (maximum rate of 0.24 and 0.36 day^−1 in non-impacted and impacted microcosms, respectively). Further addition of ETBE and MTBE reduced lags and increased biodegradation rates. ethB gene copy numbers increased significantly (>100 fold) after exposure to ETBE, while overall cell numbers remained constant, suggesting that ethB-containing microorganisms come to dominate the microbial communities. Deep sequencing of 16S rRNA genes identified members of the Comamonadaceae family that increased in relative abundance upon exposure to ETBE. This study demonstrates the potential for ETBE biodegradation within the unsaturated and saturated zone, and that ETBE biodegrading capability is rapidly developed and maintained within the aquifer microbial community over extended timescales

UKGEOS Cheshire Energy Research Field Site : science infrastructure : version 2

This report provides an overview of the planned geological characterisation, research infrastructure and data acquisition at the Cheshire Energy Research Field Site. The report is intended for a technical, science community audience. The design of the infrastructure is based on the UK Geoenergy Observatories’ Science Plan, which was generated following science community consultation. As with all drilling projects, the realities of what can be achieved in the context of geological constraints, health and safety, and budget have meant that the final design is necessarily a compromise. As the site is developed this document will be updated to reflect the actual built infrastructure and any changes to the planned design. Researchers are requested to refer to the UKGEOS website to check that they are using the latest version of this document: ukgeos.ac.uk and to refer to this report in their published outputs. Data generated during the construction and operation of the Cheshire Energy Research Field Site will be made freely available via an online platform, which is currently in development

Efficient Uncertainty Propagation through Inelastic Wind-Excited Structures Subject to Stochastic Excitation

The growing interest in applying probabilistic performance-based design to wind excited structural systems has increased the need for models capable of efficiently estimating the inelastic responses of these systems. This paper outlines the development of such a model that combines the theory of dynamic shakedown with distributed plasticity and simulation methods, providing a framework for estimating any system-level probabilistic performance metric of interest. The potential of the proposed framework is illustrated on a full scale three dimensional building.This research effort was supported in part by the National Science Foundation (NSF) under Grant No. CMMI-1462084 and the Magnusson Klemencic Associates (MKA) Foundation under Research Grant Agreement #A101. This support is gratefully acknowledged

Probabilistic Quantification of Hurricane Resilience of Communities through a Distributed Simulation Platform

Resilience is an essential requirement in mitigating the effects of natural hazards such as hurricanes. This paper presents a framework to probabilistically quantify the damage of residential communities subject to hurricane hazards which is an essential step in quantifying community resilience. An engineering-based vulnerability model is developed for typical residential buildings. In particular, damage due to the two mechanisms of net pressure and wind-borne debris impact on the envelope components is considered. By integrating full hurricane wind field models into the framework, damage can be estimated for any given hurricane category and storm track. A distributed simulation platform, using Lightweight Communications and Marshalling (LCM) libraries, is proposed for modeling the debris-induced interdependencies between the damages sustained by the buildings defining the community.This work was supported by the National Science Foundation (NSF) through grants ACI-1638186 and CMMI-1562388. Any opinions, findings, conclusions, and recommendations expressed in this work are those of the authors and do not necessarily reflect the views of the sponsors

Biodegradation and fate of ethyl tert-butyl ether (ETBE) in soil and groundwater: a review

This review summarises the current state of knowledge on the biodegradation and fate of the gasoline ether oxygenate ethyl tert-butyl ether (ETBE) in soil and groundwater. Microorganisms have been identified in soil and groundwater with the ability to degrade ETBE aerobically as a carbon and energy source, or via cometabolism using alkanes as growth substrates. Aerobic biodegradation of ETBE initially occurs via hydroxylation of the ethoxy carbon by a monooxygenase enzyme, with subsequent formation of intermediates which include acetaldehyde, tert-butyl acetate (TBAc), tert-butyl alcohol (TBA), 2-hydroxy-2-methyl-1-propanol (MHP) and 2-hydroxyisobutyric acid (2-HIBA). Slow cell growth and low biomass yields on ETBE are believed to result from the ether structure and slow degradation kinetics, with potential limitations on ETBE metabolism. Genes known to facilitate transformation of ETBE include ethB (within the ethRABCD cluster), encoding a cytochrome P450 monooxygenase, and alkB-encoding alkane hydroxylases. Other genes have been identified in microorganisms but their activity and specificity towards ETBE remains poorly characterised. Microorganisms and pathways supporting anaerobic biodegradation of ETBE have not been identified, although this potential has been demonstrated in limited field and laboratory studies. The presence of co-contaminants (other ether oxygenates, hydrocarbons and organic compounds) in soil and groundwater may limit aerobic biodegradation of ETBE by preferential metabolism and consumption of available dissolved oxygen or enhance ETBE biodegradation through cometabolism. Both ETBE-degrading microorganisms and alkane-oxidising bacteria have been characterised, with potential for use in bioaugmentation and biostimulation of ETBE degradation in groundwater