Modeling Biodegradation and Reactive Transport: Analytical and Numerical Models

The computational modeling of the biodegradation of contaminated groundwater systems accounting for biochemical reactions coupled to contaminant transport is a valuable tool for both the field engineer/planner with limited computational resources and the expert computational researcher less constrained by time and computer power. There exists several analytical and numerical computer models that have been and are being developed to cover the practical needs put forth by users to fulfill this spectrum of computational demands. Generally, analytical models provide rapid and convenient screening tools running on very limited computational power, while numerical models can provide more detailed information with consequent requirements of greater computational time and effort. While these analytical and numerical computer models can provide accurate and adequate information to produce defensible remediation strategies, decisions based on inadequate modeling output or on over-analysis can have costly and risky consequences. In this chapter we consider both analytical and numerical modeling approaches to biodegradation and reactive transport. Both approaches are discussed and analyzed in terms of achieving bioremediation goals, recognizing that there is always a tradeoff between computational cost and the resolution of simulated systems

Constrained classification for infrastructure threat assessment

Abstract not provide

Vulnerability and Mitigation Studies for Infrastructure

The summary of this presentation is that: (1) We do end-to-end systems analysis for infrastructure protection; (2) LLNL brings interdisciplinary subject matter expertise to infrastructure and explosive analysis; (3) LLNL brings high-fidelity modeling capabilities to infrastructure analysis for use on high performance platforms; and (4) LLNL analysis of infrastructure provides information that customers and stakeholders act on

Underwater Blast Experiments and Modeling for Shock Mitigation

A simple but novel mitigation concept to enforce standoff distance and reduce shock loading on a vertical, partially-submerged structure is evaluated using scaled aquarium experiments and numerical modeling. Scaled, water tamped explosive experiments were performed using three gallon aquariums. The effectiveness of different mitigation configurations, including air-filled media and an air gap, is assessed relative to an unmitigated detonation using the same charge weight and standoff distance. Experiments using an air-filled media mitigation concept were found to effectively dampen the explosive response of the aluminum plate and reduce the final displacement at plate center by approximately half. The finite element model used for the initial experimental design compares very well to the experimental DIC results both spatially and temporally. Details of the experiment and finite element aquarium models are described including the boundary conditions, Eulerian and Lagrangian techniques, detonation models, experimental design and test diagnostics

Impact of WRF Physics and Grid Resolution on Low-level Wind Prediction: Towards the Assessment of Climate Change Impact on Future Wind Power

The Weather Research and Forecast (WRF) model is used in short-range simulations to explore the sensitivity of model physics and horizontal grid resolution. We choose five events with the clear-sky conditions to study the impact of different planetary boundary layer (PBL), surface and soil-layer physics on low-level wind forecast for two wind farms; one in California (CA) and the other in Texas (TX). Short-range simulations are validated with field measurements. Results indicate that the forecast error of the CA case decreases with increasing grid resolution due to the improved representation of valley winds. Besides, the model physics configuration has a significant impact on the forecast error at this location. In contrast, the forecast error of the TX case exhibits little dependence on grid resolution and is relatively independent of physics configuration. Therefore, the occurrence frequency of lowest root mean square errors (RMSEs) at this location is used to determine an optimal model configuration for subsequent decade-scale regional climate model (RCM) simulations. In this study, we perform two sets of 20-year RCM simulations using the data from the NCAR Global Climate Model (GCM) simulations; one set models the present climate and the other simulates the future climate. These RCM simulations will be used to assess the impact of climate change on future wind energy

Sensor Acquisition for Water Utilities: Survey, Down Selection Process, and Technology List

The early detection of the biological and chemical contamination of water distribution systems is a necessary capability for securing the nation's water supply. Current and emerging early-detection technology capabilities and shortcomings need to be identified and assessed to provide government agencies and water utilities with an improved methodology for assessing the value of installing these technologies. The Department of Homeland Security (DHS) has tasked a multi-laboratory team to evaluate current and future needs to protect the nation's water distribution infrastructure by supporting an objective evaluation of current and new technologies. The LLNL deliverable from this Operational Technology Demonstration (OTD) was to assist the development of a technology acquisition process for a water distribution early warning system. The technology survey includes a review of previous sensor surveys and current test programs and a compiled database of relevant technologies. In the survey paper we discuss previous efforts by governmental agencies, research organizations, and private companies. We provide a survey of previous sensor studies with regard to the use of Early Warning Systems (EWS) that includes earlier surveys, testing programs, and response studies. The list of sensor technologies was ultimately developed to assist in the recommendation of candidate technologies for laboratory and field testing. A set of recommendations for future sensor selection efforts has been appended to this document, as has a down selection example for a hypothetical water utility

Reliability and Validity of the KIPPPI: An Early Detection Tool for Psychosocial Problems in Toddlers

Background: The KIPPPI (Brief Instrument Psychological and Pedagogical Problem Inventory) is a Dutch questionnaire that measures psychosocial and pedagogical problems in 2-year olds and consists of a KIPPPI Total score, Wellbeing scale, Competence scale, and Autonomy scale. This study examined the reliability, validity, screening accuracy and clinical application of the KIPPPI. Methods: Parents of 5959 2-year-old children in the Rotterdam area, the Netherlands, were invited to participate in the study. Parents of 3164 children (53.1% of all invited parents) completed the questionnaire. The internal consistency was evaluated and in subsamples the test-retest reliability and concurrent validity with regard to the Child Behavioral Checklist (CBCL). Discriminative validity was evaluated by comparing scores of parents who worried about their child's upbringing and parent's that did not. Screening accuracy of the KIPPPI was evaluated against the CBCL by calculating the Receiver Operating Characteristic (ROC) curves. The clinical application was evaluated by the relation between KIPPPI scores and the clinical decision made by the child health professionals. Results: Psychometric properties of the KIPPPI Total score, Wellbeing scale, Competence scale and Autonomy scale were respectively: Cronbach's alphas: 0.88, 0.86, 0.83, 0.58. Test-rete

Maternal mental health predicts risk of developmental problems at 3 years of age: follow up of a community based trial

<p>Abstract</p> <p>Background</p> <p>Undetected and untreated developmental problems can have a significant economic and social impact on society. Intervention to ameliorate potential developmental problems requires early identification of children at risk of future learning and behaviour difficulties. The objective of this study was to estimate the prevalence of risk for developmental problems among preschool children born to medically low risk women and identify factors that influence outcomes.</p> <p>Methods</p> <p>Mothers who had participated in a prenatal trial were followed up three years post partum to answer a telephone questionnaire. Questions were related to child health and development, child care, medical care, mother's lifestyle, well-being, and parenting style. The main outcome measure was risk for developmental problems using the Parents' Evaluation of Developmental Status (PEDS).</p> <p>Results</p> <p>Of 791 children, 11% were screened by the PEDS to be at high risk for developmental problems at age three. Of these, 43% had previously been referred for assessment. Children most likely to have been referred were those born preterm. Risk factors for delay included: male gender, history of ear infections, a low income environment, and a mother with poor emotional health and a history of abuse. A child with these risk factors was predicted to have a 53% chance of screening at high risk for developmental problems. This predicted probability was reduced to 19% if the child had a mother with good emotional health and no history of abuse.</p> <p>Conclusion</p> <p>Over 10% of children were identified as high risk for developmental problems by the screening, and more than half of those had not received a specialist referral. Risk factors for problems included prenatal and perinatal maternal and child factors. Assessment of maternal health and effective screening of child development may increase detection of children at high risk who would benefit from early intervention.</p> <p>Trial registration</p> <p>Current Controlled Trials ISRCTN64070727</p