Reducing Uncertainty in the American Community Survey through Data-Driven Regionalization

The American Community Survey (ACS) is the largest US survey of households and is the principal source for neighborhood scale information about the US population and economy. The ACS is used to allocate billions in federal spending and is a critical input to social scientific research in the US. However, estimates from the ACS can be highly unreliable. For example, in over 72% of census tracts the estimated number of children under 5 in poverty has a margin of error greater than the estimate. Uncertainty of this magnitude complicates the use of social data in policy making, research, and governance. This article develops a spatial optimization algorithm that is capable of reducing the margins of error in survey data via the creation of new composite geographies, a process called regionalization. Regionalization is a complex combinatorial problem. Here rather than focusing on the technical aspects of regionalization we demonstrate how to use a purpose built open source regionalization algorithm to post-process survey data in order to reduce the margins of error to some user-specified threshold

Measuring Spatial Dynamics in Metropolitan Areas

This paper introduces a new approach to measuring neighborhood change. Instead of the traditional method of identifying “neighborhoods†a priori and then studying how resident attributes change over time, our approach looks at the neighborhood more intrinsically as a unit that has both a geographic footprint and a socioeconomic composition. Therefore, change is identified when both as- pects of a neighborhood transform from one period to the next. Our approach is based on a spatial clustering algorithm that identifies neighborhoods at two points in time for one city. We also develop indicators of spatial change at both the macro (city) level as well as local (neighborhood) scale. We illustrate these methods in an application to an extensive database of time-consistent census tracts for 359 of the largest metropolitan areas in the US for the period 1990-2000.

Uncertain Uncertainty: Spatial Variation in the Quality of American Community Survey Estimates

The U.S. Census Bureau's American Community Survey (ACS) is the foundation of social science research, much federal resource allocation and the development of public policy and private sector decisions. However, the high uncertainty associated with some of the ACS's most frequently used estimates can jeopardize the accuracy of inferences based on these data. While there is high level understanding in the research community that problems exist in the data, the sources and implications of these problems have been largely overlooked. Using 2006-2010 ACS median household income at the census tract scale as the test case (where a third of small-area estimates have higher than recommend errors), we explore the patterns in the uncertainty of ACS data. We consider various potential sources of uncertainty in the data, ranging from response level to geographic location to characteristics of the place. We find that there exist systematic patterns in the uncertainty in both the spatial and attribute dimensions. Using a regression framework, we identify the factors that are most frequently correlated with the error at national, regional and metropolitan area scales, and find these correlates are not consistent across the various locations tested. The implication is that data quality varies in different places, making cross-sectional analysis both within and across regions less reliable. We also present general advice for data users and potential solutions to the challenges identified

Spectrally-consistent regularization modeling of wind farm boundary layers

The incompressible Navier-Stokes equations constitute an excellent mathematical modelization of turbulence. Unfortunately, attempts at performing direct simulations are limited to relatively low-Reynolds numbers because of the almost numberless small scales produced by the non-linear convective term. Alternatively, a dynamically less complex formulation is proposed here. Namely, regularizations of the Navier-Stokes equations that preserve the symmetry and conservation properties exactly. To do so, both convective and diffusive term are altered in the same vein. In this way, the convective production of small scales is effectively restrained whereas the modified diffusive term introduces a hyperviscosity effect and consequently enhances the destruction of small scales. In practise, the only additional ingredient is a self-adjoint linear filter whose local filter length is determined from the requirement that vortex-stretching must stop at the smallest grid scale. In the present work, the performance of the above-mentioned recent improvements is assessed through application to homogeneous isotropic turbulence, a turbulent channel flow and a turbulent boundary layer. As a final application, regularization modelling will be applied for large-scale numerical simulation of the atmospheric boundary layer through wind farms.Peer ReviewedPostprint (published version

Spectrally-Consistent Regularization of Navier–Stokes Equations

This is a post-peer-review, pre-copyedit version of an article published in Journal of Scientific Computing. The final authenticated version is available online at:https://doi.org/10.1007/s10915-018-0880-x ".The incompressible Navier–Stokes equations form an excellent mathematical model for turbulent flows. However, direct simulations at high Reynolds numbers are not feasible because the convective term produces far too many relevant scales of motion. Therefore, in the foreseeable future, numerical simulations of turbulent flows will have to resort to models of the small scales. Large-eddy simulation (LES) and regularization models are examples thereof. In the present work, we propose to combine both approaches in a spectrally-consistent way: i.e. preserving the (skew-)symmetries of the differential operators. Restoring the Galilean invariance of the regularization method results into an additional hyperviscosity term. In this way, the convective production of small scales is effectively restrained whereas the destruction of the small scales is enhanced by this hyperviscosity effect. This approach leads to a blending between regularization of the convective term and LES. The performance of these improvements is assessed through application to Burgers’ equation, homogeneous isotropic turbulence and a turbulent channel flow.Peer ReviewedPostprint (author's final draft

Subgrid-Scale Model Based on the Invariants of the Gradient Model Tensor

The incompressible Navier-Stokes equations stand as the best mathematical model for turbulent flows. However, direct numerical simulations at high Reynolds numbers are not yet feasible because the convective term produces far too many relevant scales of motion, thus remaining limited to relatively low-Reynolds numbers. Dynamically less complex mathematical formulations have been developed for coarse-grain simulations, like the well known eddy-viscosity models. Most of these models are based on the combination of invariants of a symmetric tensor that depends on the gradient of the resolved velocity field, G = Ñu, and should properly detect different flow configurations (laminar and 2D flows, near-wall behavior, transitional regime, etc.). Brand-new models have been constructed considering the first three invariants of the symmetric tensor GGT with excellent results;1 hence, it is formally based on the lowest-order approximation of the subgrid stress tensor, t(u) = D2 12GGT +O(D4), i.e. the gradient model proposed by Clark.2 Furthermore, these models have been implemented on a pseudo-spectral algorithm with a fully-explicit second-order time-integration method.3 The performance of this special configuration has been successfully tested for decaying isotropic turbulence and a turbulent channel flow. It is currently being developed for a semi-infinite boundary layer with periodic conditions as a previous step to carry out wind farm simulations. Details of the implementation and numerical results will be presented.The work has been financially supported by a competitive R+D project (ENE2017-88697-R) by the Spanish Research Agency. The authors thankfully acknowledge these institutions.Postprint (published version

Conocer la cultura de la universidad contemporánea: el CICOU

El presente artículo trata la complejidad del análisis de la cultura organizacional en las universidades a partir de la revisión de la literatura sobre el constructo "cultura organizacional" y la recopilación y análisis de diversos instrumentos. En primer lugar, se pretende realizar una disertación sobre las diferentes maneras de conocer la cultura organizacional y se revisan una serie de instrumentos aportados por diversos autores. En segundo lugar, se presenta un modelo utilizado para el análisis de ésta en las universidades catalanas. Respecto a este modelo de análisis se presenta el cuestionario elaborado y el proceso de optimización, vista su aplicabilidad por medio de los resultados obtenidos en cuatro universidades catalanas

Municipal Wastewater Treatment and Reuse for Agriculture in Senegal

This paper reports on the performance of using a multistage constructed wetland (CW) to treat municipal raw wastewater and an analysis of its suitability for agricultural irrigation. The pilot plant consists of two stages of vertical flow CWs plus one stage of a horizontal CW built in 2018 with diferent local materials at the Gaston Berger University Campus, Saint Louis (Senegal). Each CW stage is composed of several filters with di erent type of media (silex, granite, or river gravel), filtering media depths, and macrophytes (Phragmites and Typha). The physicochemical and microbiological indicators were monitored over six months at each bed inlet and outlet to evaluate the e ciency and achievements of the Senegalese, European, and WHO regulations/recommendations for disposal or reuse in irrigation. This study demonstrates the viability of this new multistage CW design to treat raw municipal wastewater and produce an e uent of good quality suitable for reuse in agriculture. The removal of organic matter, suspended solids, and nutrients was very high (>95% for SS, BOD5 and N-NH4 +, >90% for COD and P-PO4 3 as was the reduction of microbiological indicators (fecal coliform reduction >5 log units and helminth egg removal of 100%). First, trends related to the influence of design (the type of gravel, filter depth, and type of macrophyte), operational modes, and the CW treatment eciency were determined. The use of non-crushed gravel and Typha spp. seemed to provide better removal rates. On the contrary, no diferences were found between the use of silex or granite gravel. For the studied Senegalese conditions under dry and hot climates, the preliminary results indicate that no resting periods are necessary for vertical flow CWs (VFCWs), thus resulting in a reduction in construction and operation costs. The main outcome of our study is evidence that multistage CWs can provide robust, cost-efective treatments, as well as allow for safe water reuse, which is imperative in areas with severe water scarcity and endemic microbiological waterborne diseases

Conocer la cultura de la Universidad Contemporánea : el CICOU

El presente artículo trata la complejidad del análisis de la cultura organizacional en las universidades a partir de la revisión de la literatura sobre el constructo "cultura organizacional" y la recopilación y análisis de diversos instrumentos. En primer lugar, se pretende realizar una disertación sobre las diferentes maneras de conocer la cultura organizacional y se revisan una serie de instrumentos aportados por diversos autores. En segundo lugar, se presenta un modelo utilizado para el análisis de ésta en las universidades catalanas. Respecto a este modelo de análisis se presenta el cuestionario elaborado y el proceso de optimización, vista su aplicabilidad por medio de los resultados obtenidos en cuatro universidades catalanas