Second-Generation Large Civil Tiltrotor 7- by 10-Foot Wind Tunnel Test Data Report

An approximately 6-percent scale model of the NASA Second-Generation Large Civil Tiltrotor (LCTR2) Aircraft was tested in the U.S. Army 7- by 10-Foot Wind Tunnel at NASA Ames Research Center January 4 to April 19, 2012, and September 18 to November 1, 2013. The full model was tested, along with modified versions in order to determine the effects of the wing tip extensions and nacelles; the wing was also tested separately in the various configurations. In both cases, the wing and nacelles used were adopted from the U.S. Army High Efficiency Tilt Rotor (HETR) aircraft, in order to limit the cost of the experiment. The full airframe was tested in high-speed cruise and low-speed hover flight conditions, while the wing was tested only in cruise conditions, with Reynolds numbers ranging from 0 to 1.4 million. In all cases, the external scale system of the wind tunnel was used to collect data. Both models were mounted to the scale using two support struts attached underneath the wing; the full airframe model also used a third strut attached at the tail. The collected data provides insight into the performance of the preliminary design of the LCTR2 and will be used for computational fluid dynamics (CFD) validation and the development of flight dynamics simulation models

Agricultural Production and Externalities Simulator (APES) prototype to be used in Prototype 1 of SEAMLESS-IF

Production Economics,

Library of model components for process simulation relevant to production activities, Prototype 1 versions

Production Economics,

Impacts of 1.5 versus 2.0 °c on cereal yields in the West African Sudan Savanna

To reduce the risks of climate change, governments agreed in the Paris Agreement to limit global temperature rise to less than 2.0 °C above pre-industrial levels, with the ambition to keep warming to 1.5 °C. Charting appropriate mitigation responses requires information on the costs of mitigating versus associated damages for the two levels of warming. In this assessment, a critical consideration is the impact on crop yields and yield variability in regions currently challenged by food insecurity. The current study assessed impacts of 1.5 °C versus 2.0 °C on yields of maize, pearl millet and sorghum in the West African Sudan Savanna using two crop models that were calibrated with common varieties from experiments in the region with management reflecting a range of typical sowing windows. As sustainable intensification is promoted in the region for improving food security, simulations were conducted for both current fertilizer use and for an intensification case (fertility not limiting). With current fertilizer use, results indicated 2% units higher losses for maize and sorghum with 2.0 °C compared to 1.5 °C warming, with no change in millet yields for either scenario. In the intensification case, yield losses due to climate change were larger than with current fertilizer levels. However, despite the larger losses, yields were always two to three times higher with intensification, irrespective of the warming scenario. Though yield variability increased with intensification, there was no interaction with warming scenario. Risk and market analysis are needed to extend these results to understand implications for food security

Impact of home monitoring program on interstage mortality after the Norwood procedure

ObjectiveWhile early outcome after the Norwood operation for hypoplastic left heart syndrome has improved, interstage mortality until bidirectional cavopulmonary shunt (BCPS) remains a concern. Our aim was to institute a home monitoring program to (HMP) decrease interstage mortality.MethodsAmong 264 patients who survived Norwood procedure and were discharged before BCPS, 80 patients were included in the HMP and compared to the remaining 184 patients regarding interstage mortality. In patients with HMP, events during the interstage period were evaluated.ResultsInterstage mortality was 8% (n = 21), and was significantly lower in patients with HMP (2.5%, n = 2), compared to those without (10.3%, n = 19, p = 0.031). Patients with interstage mortality had significantly lower birth weight (p < 0.001) compared to those without. Lower birth weight (p < 0.001), extra corporeal membrane oxygenation support (p = 0.002), and lack of HMP (p = 0.048) were risk factors for interstage mortality. Most frequent event during home monitoring was low saturation (<70%) in 14 patients (18%), followed by infection in 6 (7.5%), stagnated weight gain in 5 (6.3%), hypoxic shock in 3 (3.8%) and arrhythmias in 2 (2.5%). An unexpected readmission was needed in 24 patients (30%). In those patients, age (p = 0.001) and weight at BCPS (p = 0.007) were significantly lower compared to those without readmission, but the survival after BCPS was comparable between the groups.ConclusionsInterstage HMP permits timely intervention and led to an important decrease in interstage mortality. One-third of the patients with home monitoring program needed re-admission and demonstrated the need for earlier stage 2 palliation

Impacts of 1.5 versus 2.0 °C on cereal yields in the West African Sudan Savanna

To reduce the risks of climate change, governments agreed in the Paris Agreement to limit global temperature rise to less than 2.0 °C above pre-industrial levels, with the ambition to keep warming to 1.5 °C. Charting appropriate mitigation responses requires information on the costs of mitigating versus associated damages for the two levels of warming. In this assessment, a critical consideration is the impact on crop yields and yield variability in regions currently challenged by food insecurity. The current study assessed impacts of 1.5 °C versus 2.0 °C on yields of maize, pearl millet and sorghum in the West African Sudan Savanna using two crop models that were calibrated with common varieties from experiments in the region with management reflecting a range of typical sowing windows. As sustainable intensification is promoted in the region for improving food security, simulations were conducted for both current fertilizer use and for an intensification case (fertility not limiting). With current fertilizer use, results indicated 2% units higher losses for maize and sorghum with 2.0 °C compared to 1.5 °C warming, with no change in millet yields for either scenario. In the intensification case, yield losses due to climate change were larger than with current fertilizer levels. However, despite the larger losses, yields were always two to three times higher with intensification, irrespective of the warming scenario. Though yield variability increased with intensification, there was no interaction with warming scenario. Risk and market analysis are needed to extend these results to understand implications for food security

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

Many studies have been carried out during the last decade to study the effect of climate change on crop yields and other key crop characteristics. In these studies, one or several crop models were used to simulate crop growth and development for different climate scenarios that correspond to different projections of atmospheric CO2 concentration, temperature, and rainfall changes (Semenov et al., 1996; Tubiello and Ewert, 2002; White et al., 2011). The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) builds on these studies with the goal of using an ensemble of multiple crop models in order to assess effects of climate change scenarios for several crops in contrasting environments. These studies generate large datasets, including thousands of simulated crop yield data. They include series of yield values obtained by combining several crop models with different climate scenarios that are defined by several climatic variables (temperature, CO2, rainfall, etc.). Such datasets potentially provide useful information on the possible effects of different climate change scenarios on crop yields. However, it is sometimes difficult to analyze these datasets and to summarize them in a useful way due to their structural complexity; simulated yield data can differ among contrasting climate scenarios, sites, and crop models. Another issue is that it is not straightforward to extrapolate the results obtained for the scenarios to alternative climate change scenarios not initially included in the simulation protocols. Additional dynamic crop model simulations for new climate change scenarios are an option but this approach is costly, especially when a large number of crop models are used to generate the simulated data, as in AgMIP. Statistical models have been used to analyze responses of measured yield data to climate variables in past studies (Lobell et al., 2011), but the use of a statistical model to analyze yields simulated by complex process-based crop models is a rather new idea. We demonstrate herewith that statistical methods can play an important role in analyzing simulated yield data sets obtained from the ensembles of process-based crop models. Formal statistical analysis is helpful to estimate the effects of different climatic variables on yield, and to describe the between-model variability of these effects