234 research outputs found

    GIS Analysis of Factors Influencing Particulate Pollution in Keene, New Hampshire

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    This study aims to identify the characteristics of air inversions and Particulate Matter 2.5 (PM2.5) in the city of Keene, New Hampshire. PM2.5 is a type of particulate pollutant with a diameter of less than 2.5 microns that exists naturally, and can be created through industrial processed and the combustion of biomass. The combustion of wood as a home heating fuel is considered the main source of PM2.5 in Keene. Meteorological factors were investigated by searching through quality assured meteorological record provided by the New Hampshire Department of Environmental Services. Wintertime temperature inversions are of particular concern as they trap pollutants near the ground, creating high concentrations of PM2.5.This is particularly true for Keene, which is in a glacial valley. This study concluded that air inversions and high PM2.5 event are most likely to occur on cold, clear, windless nights during the winter. The temperature must drop at least 11 degrees Fahrenheit, with a dew point close to the ambient temperature. The other objective of the study was to create a model that would predict the areas that will experience high PM2.5 concentrations as the result of demographic and topographical factors. The model was built using Digital Elevation Models, and building footprints provided by the University of New Hampshire Database. Housing density was calculated using the building footprints layer, and combined with areas that have less than three degrees of slope. This was compared to mobile monitoring data collected during the timeframe of the study

    The Risk of Zealous Advocacy: Litigators Receiving Anonymously Disclosed Documents and the Notification Requirement

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    The American Bar Association (ABA) created the Model Rules of Professional Conduct to provide guidance to lawyers, courts, and the entire legal profession regarding what a lawyer’s ethical duties entail. Model Rule 4.4(b) requires a lawyer to notify opposing counsel once the receiving lawyer knows, or reasonably should know, that the documents received were inadvertently sent. The ABA, however, explicitly left documents disclosed intentionally and without authorization beyond the scope of the rules, thus leaving lawyers who receive these documents with little guidance. Courts have taken varying approaches to handling documents of this type: some analogize unauthorized disclosures to inadvertent disclosures and mandate notice for documents provided by anonymous third parties, while others instead refuse to impose a notification requirement. This Note discusses the conflict about the notification requirement and anonymously disclosed documents. It examines the arguments for and against mandating notice to the opposing party in these situations. This Note proposes that notice should be required for intentional disclosures made by anonymous third parties because these documents can be analogized to those addressed in Model Rule 4.4(b), which implements a notice requirement for inadvertent disclosures. This Note then discusses how the ABA is in the best position to resolve the inconsistencies discussed and proposes a revised Model Rule 4.4(b) to help alleviate the uncertainty in this realm

    GIS Analysis of Factors Influencing Particulate Pollution in Keene, New Hampshire

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    This study aims to identify the characteristics of air inversions and Particulate Matter 2.5 (PM2.5) in the city of Keene, New Hampshire. PM2.5 is a type of particulate pollutant with a diameter of less than 2.5 microns that exists naturally, and can be created through industrial processed and the combustion of biomass. The combustion of wood as a home heating fuel is considered the main source of PM2.5 in Keene. Meteorological factors were investigated by searching through quality assured meteorological record provided by the New Hampshire Department of Environmental Services. Wintertime temperature inversions are of particular concern as they trap pollutants near the ground, creating high concentrations of PM2.5. This is particularly true for Keene, which is in a glacial valley. This study concluded that air inversions and high PM2.5 event are most likely to occur on cold, clear, windless nights during the winter. The temperature must drop at least 11 degrees Fahrenheit, with a dew point close to the ambient temperature. The other objective of the study was to create a model that would predict the areas that will experience high PM2.5 concentrations as the result of demographic and topographical factors. The model was built using Digital Elevation Models, and building footprints provided by the University of New Hampshire Database. Housing density was calculated using the building footprints layer, and combined with areas that have less than three degrees of slope. This was compared to mobile monitoring data collected during the timeframe of the study.Faculty Sponsor: Dr. Chris Brehm

    Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments

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    This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.Fundação para a Ciência e Tecnologia (FCT

    A coupled 3D isogeometric and discrete element approach for modelling interactions between structures and granular matters

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    A three-dimensional (3D) isogeometric/discrete-element coupling method is presented for modelling contact/impact between structures and particles. This method takes advantages of the geometry smoothness and exactness of isogeometric analysis (IGA) for continuous solid media and the effectiveness and flexibility of the discrete element method (DEM) for particulate matters. The coupling procedure for handling interactions between IGA elements and discrete elements (DEs) includes global search, local search and interaction calculation. In the global search, the CGRID method is modified to detect potential contact pairs between IGA elements and DEs based on their bounding box representations. The strong convex hull property of a NURBS control mesh plays an important part in the bounding box representation of IGA elements. In the local search, the proposed approach treats each spherical DE centroid as a slave node and the contact surface of each IGA element as the master surface. The projection of a DE centroid onto an IGA element contact surface is solved by modifying the simplex method and Brent iterations. The contact force between an IGA element and a DE is determined from their penetration by using a (nonlinear) penalty function based method. The whole coupled system is solved by the explicit time integration within a updated Lagrangian scheme. Finally, three impact examples, including the impact of two symmetric bars, a tube onto a footing strip, and an assembly of granular particles to a tailor rolled blank, are simulated in elastic regime to assess the accuracy and applicability of the proposed method

    Real-time Control of Pig Growth through an Integrated Management System.

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    This paper describes the development and testing of the first prototype closed-loop, model-based, real-time system for the integrated control of pig growth and pollutant emissions. In each of two trials, growing pigs were reared from 30–50 to 65–125 kg in groups of 12 in 12 separate pens under controlled environment conditions at ADAS Terrington (Norfolk, England). They were fed ad libitum diets in which the protein content was controlled for each pen. Weight, estimated by visual image analysis, and feed intake were recorded daily for each pig. The control system was based on a mechanistic growth model. Each week, two model parameters were optimised using the data to improve the prediction, then the diet for each pen was optimised by adjusting the crude protein content between 140 and 190 g/kg [dry matter] to minimise the model error from a target for weight or fat depth. Part of the trial set weight gain targets of 50 and 60 kg over 70 days using two pens for each target. In three of the four pens the final mean weight of the pigs was within 2 kg of the target; in the fourth, growth was on target until it was interrupted close to the end of the trial. This trial has demonstrated the potential of the system to control the growth rate of pigs and has given encouraging but not conclusive results for the control of back fat depth

    THE EDITOR Technometrics

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