Pressure Disturbance Upstream of the Boundary Layer Data System

The primary objective for this work was to evaluate the reliability of computational fluid dynamics (CFD) tools in the prediction of upstream surface pressure disturbance and pressure drag of various instrument excrescence shapes for a small aircraft flight test device called the Boundary Layer Data System (BLDS). Insights on pressure disturbance will serve as a guide for the placement of BLDS probes/sensors, and pressure drag can be used to ensure sufficient adhesive is used to install BLDS instrumentation. The Mach number for all CFD cases was 0.12 and the Reynolds number based on excrescence height varied from 4 x 104 to 1 x 105. Excrescences studied have height to local boundary layer thickness ratios 0.75 \u3c h/d \u3c 1.9 and width to height ratios 3 ≤ w/h \u3c 4. Wind tunnel tests were first conducted in the Cal Poly Fluids Lab’s 2 x 2-foot wind tunnel to obtain measurements of the upstream pressure disturbance created by a blunt BLDS housing and a streamlined BLDS fairing. Upstream surface pressure data was measured for two-dimensional excrescences and for three-dimensional models of the blunt and streamlined housings. A rake measurement of the undisturbed boundary layer profile at the leading edge location of each excrescence was also obtained to compare to the computed boundary layer. Prior to viscous modeling with CFD, potential flow theory was used to compute the inviscid upstream pressure disturbance for a generic excrescence on a smooth surface. A Rankine oval was generated using superposition, and a MATLAB program was written to evaluate ovals of varying chord and height. The potential flow results for the pressure distribution upstream of a Rankine oval were found to agree quite well with 2-D measurements and viscous CFD. Ansys ICEM CFD and FLUENT were used for computational modeling. A viscous CFD model was first created in two-dimensions and validated by comparing the upstream pressure disturbance results to the two-dimensional experimental measurements. The validated FLUENT case set-up was extended to three-dimensions, and three-dimensional models were created for blunt and streamlined BLDS excrescences. ICEM CFD was used to generate meshes for 2-D and 3-D models and FLUENT was used to solve the Reynolds-Averaged Navier Stokes (RANS) equations in conjunction with the Spalart-Allmaras turbulence model. Mesh independence studies and evaluation of discretization error were conducted to ensure that the final mesh employed provided adequate spatial resolution. The computed flow features, and results for dimensionless pressure and drag, were compared to experimental measurements and classic aerodynamic principles to evaluate the CFD solutions. It was concluded that CFD can accurately compute upstream pressure disturbances and pressure drag for excrescences mounted to a smooth surface. The viscous calculations showed that the effect of excrescence shape on upstream pressure field is only significant within 6 body heights of the leading edge. Beyond that, no significant difference in the pressure disturbance was observed between different excrescence configurations. Additionally, the spanwise pressure disturbance was found to become negligible at about 1-1.5 housing widths away from the upstream centerline of each excrescence regardless of its shape. Finally, all computed blunt housing models resulted in a pressure drag coefficient of about 0.5 which corroborates past experimental drag measurements. This thesis has set-up a working FLUENT CFD case that can be used for future computational studies related to the BLDS and provides detailed guidance for existing BLDS housing shapes beyond the rules of thumb currently used for informing housing designs

Norine, the knowledgebase dedicated to nonribosomal peptides, is now open to crowdsourcing

International audienceSince its creation in 2006, Norine remains the unique knowledgebase dedicated to non-ribosomal pep-tides (NRPs). These secondary metabolites, produced by bacteria and fungi, harbor diverse interesting biological activities (such as antibiotic, anti-tumor, siderophore or surfactant) directly related to the diversity of their structures. The Norine team goal is to collect the NRPs and provide tools to analyze them efficiently. We have developed a user-friendly interface and dedicated tools to provide a complete bioinformatics platform. The knowledgebase gathers abundant and valuable annotations on more than 1100 NRPs. To increase the quantity of described NRPs and improve the quality of associated annotations , we are now opening Norine to crowdsourc-ing. We believe that contributors from the scientific community are the best experts to annotate the NRPs they work on. We have developed MyNorine to facilitate the submission of new NRPs or modifications of stored ones. This article presents MyNorine and other novelties of Norine interface released since the first publication. Norine is freely accessible from the following URL: http://bioinfo.lifl.fr/NRP

Evaluating the effects of climate change on US agricultural systems: sensitivity to regional impact and trade expansion scenarios

Agriculture is one of the sectors that is expected to be most significantly impacted by climate change. There has been considerable interest in assessing these impacts and many recent studies investigating agricultural impacts for individual countries and regions using an array of models. However, the great majority of existing studies explore impacts on a country or region of interest without explicitly accounting for impacts on the rest of the world. This approach can bias the results of impact assessments for agriculture given the importance of global trade in this sector. Due to potential impacts on relative competitiveness, international trade, global supply, and prices, the net impacts of climate change on the agricultural sector in each region depend not only on productivity impacts within that region, but on how climate change impacts agricultural productivity throughout the world. In this study, we apply a global model of agriculture and forestry to evaluate climate change impacts on US agriculture with and without accounting for climate change impacts in the rest of the world. In addition, we examine scenarios where trade is expanded to explore the implications for regional allocation of production, trade volumes, and prices. To our knowledge, this is one of the only attempts to explicitly quantify the relative importance of accounting for global climate change when conducting regional assessments of climate change impacts. The results of our analyses reveal substantial differences in estimated impacts on the US agricultural sector when accounting for global impacts vs. US-only impacts, particularly for commodities where the United States has a smaller share of global production. In addition, we find that freer trade can play an important role in helping to buffer regional productivity shocks

Increasing crop production in Russia and Ukraine—regional and global impacts from intensification and recultivation

Russia and Ukraine are countries with relatively large untapped agricultural potentials, both in terms of abandoned agricultural land and substantial yield gaps. Here we present a comprehensive assessment of Russian and Ukrainian crop production potentials and we analyze possible impacts of their future utilization, on a regional as well as global scale. To this end, the total amount of available abandoned land and potential yields in Russia and Ukraine are estimated and explicitly implemented in an economic agricultural sector model. We find that cereal (barley, corn, and wheat) production in Russia and Ukraine could increase by up to 64% in 2030 to 267 million tons, compared to a baseline scenario. Oilseeds (rapeseed, soybean, and sunflower) production could increase by 84% to 50 million tons, respectively. In comparison to the baseline, common net exports of Ukraine and Russia could increase by up to 86.3 million tons of cereals and 18.9 million tons of oilseeds in 2030, representing 4% and 3.6% of the global production of these crops, respectively. Furthermore, we find that production potentials due to intensification are ten times larger than potentials due to recultivation of abandoned land. Consequently, we also find stronger impacts from intensification at the global scale. A utilization of crop production potentials in Russia and Ukraine could globally save up to 21 million hectares of cropland and reduce average global crop prices by more than 3%

Addressing climate change adaptation with a stochastic integrated assessment model: Analysis of common agricultural policy measures

Stochastic agro-economic model GLOBIOM is used to demonstrate how best to design and evaluate the CAP’s financial and structural measures, both individually and jointly, in the face of inherent uncertainty and risk. The model accounts for plausible shocks simultaneously and derives measures that are robust against all shock scenarios; it can thus help avoid the irreversibility and sunk costs that occur in unexpected scenarios.To allow adequate agricultural production, we show that the distribution of CAP funds needs to account for exposure to risks, security targets, and the synergies between policy measures, including production, trade, storage, and irrigation technologies