NASA Glenn Icing Research Tunnel: 2012 Cloud Calibration Procedure and Results

In 2011, NASA Glenn s Icing Research Tunnel underwent a major modification to it s refrigeration plant and heat exchanger. This paper presents the results of the subsequent full cloud calibration. Details of the calibration procedure and results are presented herein. The steps include developing a nozzle transfer map, establishing a uniform cloud, conducting a drop sizing calibration and finally a liquid water content calibration. The goal of the calibration is to develop a uniform cloud, and to build a transfer map from the inputs of air speed, spray bar atomizing air pressure and water pressure to the output of median volumetric droplet diameter and liquid water content

Distracted Driver Behaviors and Distracting Conditions Among Adolescent Drivers: Findings From a Naturalistic Driving Study

AbstractPurposeThe proliferation of new communication technologies and capabilities has prompted concern about driving safety. This concern is particularly acute for inexperienced adolescent drivers. In addition to being early adopters of technology, many adolescents have not achieved the degree of automaticity in driving that characterizes experienced adults. Consequently, distractions may be more problematic in this group. Yet little is known about the nature or prevalence of distracted driving behaviors or distracting conditions among adolescent drivers.MethodVehicles of 52 high-school age drivers (N = 38 beginners and N = 14 more experienced) were equipped for 6 months with unobtrusive event-triggered data recorders that obtain 20-second clips of video, audio, and vehicle kinematic information when triggered. A low recording trigger threshold was set to obtain a sample of essentially random driving segments along with those indicating rough driving behaviors.ResultsElectronic device use (6.7%) was the most common single type of distracted behavior, followed by adjusting vehicle controls (6.2%) and grooming (3.8%). Most distracted driver behaviors were less frequent when passengers were present. However, loud conversation and horseplay were quite common in the presence of multiple peer passengers. These conditions were associated with looking away from the road, the occurrence of serious events, and, to a lesser extent, rough driving (high g-force events).ConclusionsCommon assumptions about adolescent driver distraction are only partially borne out by in-vehicle measurement. The association of passengers with distraction appears more complex than previously realized. The relationship between distractions and serious events differed from the association with rough driving

NASA Glenn Icing Research Tunnel: 2014 Cloud Calibration

The results of the December 2013 to February 2014 Icing Research Tunnel full icing cloud calibration are being presented to the SAE AC-9C committee, as represented in the 2014 cloud calibration report. The calibration steps included establishing a uniform cloud and conducting drop size and liquid water content calibrations. The goal of the calibration was to develop a uniform cloud, and to generate a transfer function from the inputs of air speed, spray bar atomizing air pressure and water pressure to the outputs of median volumetric drop diameter and liquid water content. This was done for both 14 CFR Parts 25 and 29, Appendix C (typical icing) and soon-to-be released Appendix O (supercooled large drop) conditions

Advancing Alternative Analysis: Integration of Decision Science.

Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals.Assess whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics.A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings.We conclude the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients, and would also advance the science of decision analysis.We advance four recommendations: (1) engaging the systematic development and evaluation of decision approaches and tools; (2) using case studies to advance the integration of decision analysis into alternatives analysis; (3) supporting transdisciplinary research; and (4) supporting education and outreach efforts

Restructuring of colloidal aggregates in shear flow: Coupling interparticle contact models with Stokesian dynamics

A method to couple interparticle contact models with Stokesian dynamics (SD) is introduced to simulate colloidal aggregates under flow conditions. The contact model mimics both the elastic and plastic behavior of the cohesive connections between particles within clusters. Owing to this, clusters can maintain their structures under low stress while restructuring or even breakage may occur under sufficiently high stress conditions. SD is an efficient method to deal with the long-ranged and many-body nature of hydrodynamic interactions for low Reynolds number flows. By using such a coupled model, the restructuring of colloidal aggregates under stepwise increasing shear flows was studied. Irreversible compaction occurs due to the increase of hydrodynamic stress on clusters. Results show that the greater part of the fractal clusters are compacted to rod-shaped packed structures, while the others show isotropic compaction.Comment: A simulation movie be found at http://www-levich.engr.ccny.cuny.edu/~seto/sites/colloidal_aggregates_shearflow.htm

Relative performance of machine learning and linear regression in predicting quality of life and academic performance of school children in Norway : data analysis of a quasi-experimental study

Background: Machine learning (ML) approaches are increasingly being used in health research. It is not clear how useful these approaches are for modelling continuous health outcomes. Child quality of life (QoL) is associated with parental socioeconomic status and child activity levels, and may be associated with aerobic fitness and strength. It is not clear whether diet, or academic performance (AP) is associated with QoL. Objective: To compare predictive performances of ML approaches with linear regression for modelling QoL and AP using parental education and lifestyle data. Methods: We modelled data from children attending nine schools in a quasi-experimental study (NCT02495714). We split data randomly into training and validation sets, and simulated curvilinear, non-linear, and heteroscedastic variables. We examined relative performance of ML approaches using R2, making comparisons to mixed and fixed models, and regression with splines, with and without imputation. We also examined the effect of training set size on overfitting. Results: We had 1,711 cases. Using real data, our regression models explained 24% of AP variance in the complete-case validation set, and up to 15% of QoL variance. While ML models explained high proportions of variance in training sets, in validation sets these explained ~0% of AP and between 3% and 8% of QoL. Following imputation, ML models improved up to 15% for AP. ML models outperformed regression for modelling simulated non-linear and heteroscedastic variables only. A smaller training set did not lead to increased overfitting. The best predictors of QoL were 7-point self-reported activity (P<.001; ß=1.09 (95% CI 0.53 to 1.66)) and TV/computer use (P=.002; ß=-0.95 (-1.55 to -0.36)). For AP, these were mother having master’s-level education (P<.001; ß=1.98 (0.25 to 3.71)) and dichotomised self-reported activity (P=.001; ß=2.47 (1.08 to 3.87)). Adjusted academic performance was associated with QoL (P=.02; ß=0.12 (0.02 to 0.22)). Conclusions: Exercising to cause sweat once per week and 2 hours per day of TV or computer use are associated with small-to-medium increases and decreases in child QoL, respectively. An increase in AP of 20 units is associated with a small increase in QoL. A mother having higher and master’s-level education, 2 hours per day of TV or computer use, and taking at least 2 hours of exercise, are each associated with small-to-medium increases in AP. Differences between effects of computer/TV use for work/leisure needs further investigation. Linear regression is less prone to overfitting and performs better than ML in predicting continuous health outcomes in a dataset containing missing data. Imputation improves ML performance but not enough to outperform regression. ML outperformed regression with non-linear and heteroscedastic data and may be of use when such relationships exist, and where imputation is sensible or there are no missing data. Clinical Trial: The data are from a quasi-experimental design and not an RCT but nevertheless the study from which the data are from does have a registration: NCT0249571

The theory of the firm and its critics: a stocktaking and assessment

Includes bibliographical references."Prepared for Jean-Michel Glachant and Eric Brousseau, eds. New Institutional Economics: A Textbook, Cambridge, Cambridge University Press.""This version: August 22, 2005."Since its emergence in the 1970s the modern economic or Coasian theory of the firm has been discussed and challenged by sociologists, heterodox economists, management scholars, and other critics. This chapter reviews and assesses these critiques, focusing on behavioral issues (bounded rationality and motivation), process (including path dependence and the selection argument), entrepreneurship, and the challenge from knowledge-based theories of the firm