Laser Rayleigh and Raman Diagnostics for Small Hydrogen/oxygen Rockets

Localized velocity, temperature, and species concentration measurements in rocket flow fields are needed to evaluate predictive computational fluid dynamics (CFD) codes and identify causes of poor rocket performance. Velocity, temperature, and total number density information have been successfully extracted from spectrally resolved Rayleigh scattering in the plume of small hydrogen/oxygen rockets. Light from a narrow band laser is scattered from the moving molecules with a Doppler shifted frequency. Two components of the velocity can be extracted by observing the scattered light from two directions. Thermal broadening of the scattered light provides a measure of the temperature, while the integrated scattering intensity is proportional to the number density. Spontaneous Raman scattering has been used to measure temperature and species concentration in similar plumes. Light from a dye laser is scattered by molecules in the rocket plume. Raman spectra scattered from major species are resolved by observing the inelastically scattered light with linear array mounted to a spectrometer. Temperature and oxygen concentrations have been extracted by fitting a model function to the measured Raman spectrum. Results of measurements on small rockets mounted inside a high altitude chamber using both diagnostic techniques are reported

Laser diagnostics for small rockets

Two nonintrusive flowfield diagnostics based on spectrally-resolved elastic (Rayleigh) and inelastic (Raman) laser light scattering were developed for obtaining local flowfield measurements in low-thrust gaseous H2/O2 rocket engines. The objective is to provide an improved understanding of phenomena occurring in small chemical rockets in order to facilitate the development and validation of advanced computational fluid dynamics (CFD) models for analyzing engine performance. The laser Raman scattering diagnostic was developed to measure major polyatomic species number densities and rotational temperatures in the high-density flowfield region extending from the injector through the chamber throat. Initial application of the Raman scattering diagnostic provided O2 number density and rotational temperature measurements in the exit plane of a low area-ratio nozzle and in the combustion chamber of a two-dimensional, optically-accessible rocket engine. In the low-density nozzle exit plane region where the Raman signal is too weak, a Doppler-resolved laser Rayleigh scattering diagnostic was developed to obtain axial and radial mean gas velocities, and in certain cases, H2O translational temperature and number density. The results from these measurements were compared with theoretical predictions from the RPLUS CFD code for analyzing rocket engine performance. Initial conclusions indicate that a detailed and rigorous modeling of the injector is required in order to make direct comparisons between laser diagnostic measurements and CFD predictions at the local level

Особенности социальной ответственности малых и средних предприятий

Рассмотрены особенности деятельности малых и средних предприятий, их отличия от крупных предприятий, особенности и проблемы развития социальной ответственности малого и среднего бизнеса в Украине.Розглянуто особливості діяльності малих і середніх підприємств, їх відмінності від великих підприємств, особливості та проблеми розвитку соціальної відповідальності малого і середнього бізнесу в Україні.The paper examines features of small and middle enterprises activities and their distinction from big enterprises. The problems concerning development of social responsibility of small and middle business in Ukraine are also considered in the article

Long-term Observations in Acoustics - the Ocean Acoustic Observatory Federation

The Ocean Acoustic Observatory Federation (OAOF) includes several laboratories and universities: the Institute of Geophysics and Planetary Physics (IGPP) and the Marine Physical Laboratory (MPL) at the Scripps Institution of Oceanography, the Pacific Meteorological and Environmental Laboratory (PMEL) of NOAA, the Naval Postgraduate School (NPS), and the Applied Physics Laboratory at the University of Washington (UW/APL)

Decision-theoretic designs for small trials and pilot studies: A review

Pilot studies and other small clinical trials are often conducted but serve a variety of purposes and there is little consensus on their design. One paradigm that has been suggested for the design of such studies is Bayesian decision theory. In this article, we review the literature with the aim of summarizing current methodological developments in this area. We find that decision-theoretic methods have been applied to the design of small clinical trials in a number of areas. We divide our discussion of published methods into those for trials conducted in a single stage, those for multi-stage trials in which decisions are made through the course of the trial at a number of interim analyses, and those that attempt to design a series of clinical trials or a drug development programme. In all three cases, a number of methods have been proposed, depending on the decision maker’s perspective being considered and the details of utility functions that are used to construct the optimal design

Personal probabilities of probabilities

By definition, the subjective probability distribution of a random event is revealed by the (‘rational’) subject's choice between bets — a view expressed by F. Ramsey, B. De Finetti, L. J. Savage and traceable to E. Borel and, it can be argued, to T. Bayes. Since hypotheses are not observable events, no bet can be made, and paid off, on a hypothesis. The subjective probability distribution of hypotheses (or of a parameter, as in the current ‘Bayesian’ statistical literature) is therefore a figure of speech, an ‘as if’, justifiable in the limit. Given a long sequence of previous observations, the subjective posterior probabilities of events still to be observed are derived by using a mathematical expression that would approximate the subjective probability distribution of hypotheses, if these could be bet on. This position was taken by most, but not all, respondents to a ‘Round Robin’ initiated by J. Marschak after M. H. De-Groot's talk on Stopping Rules presented at the UCLA Interdisciplinary Colloquium on Mathematics in Behavioral Sciences. Other participants: K. Borch, H. Chernoif, R. Dorfman, W. Edwards, T. S. Ferguson, G. Graves, K. Miyasawa, P. Randolph, L. J. Savage, R. Schlaifer, R. L. Winkler. Attention is also drawn to K. Borch's article in this issue.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43847/1/11238_2004_Article_BF00169102.pd

Opinion dynamics and wisdom under conformity

Buechel B, Hellmann T, Klößner S. Opinion dynamics and wisdom under conformity. Working Papers. Center for Mathematical Economics. Vol 469. Bielefeld: Center for Mathematical Economics; 2013.We study a dynamic model of opinion formation in social networks. In our model, boundedly rational agents update opinions by averaging over their neighbors' expressed opinions, but may misrepresent their own opinion by conforming or counter-conforming with their neighbors. We show that an agent's social influencev on the long-run group opinion is increasing in network centrality and decreasing in conformity. For efficiency of information aggregation (\wisdom"), misrepresentation of opinions need not undermine wisdom. Given the network, we provide the optimal distribution of conformity levels in the society and show which agents should be more conforming in order to increase wisdom

Who Said or What Said? Estimating Ideological Bias in Views Among Economists

There exists a long-standing debate about the influence of ideology in economics. Surprisingly, however, there is no concrete empirical evidence to examine this critical issue. Using an online randomized controlled experiment involving economists in 19 countries, we examine the effect of ideological bias on views among economists. Participants were asked to evaluate statements from prominent economists on different topics, while source attribution for each statement was randomized without participants’ knowledge. For each statement, participants either received a mainstream source, an ideologically different less-/non-mainstream source, or no source. We find that changing source attributions from mainstream to less-/non-mainstream, or removing them, significantly reduces economists’ reported agreement with statements. Using a model of Bayesian updating we examine two competing hypotheses as potential explanations for these results: unbiased Bayesian updating versus ideologically-biased Bayesian updating. While we find no evidence in support of unbiased updating, our results are consistent with biased Bayesian updating. More specifically, we find that changing/removing sources (1) has no impact on economists’ reported confidence with their evaluations; (2) similarly affects experts/non-experts in relevant areas; and (3) affects those at the far right of the political spectrum much more significantly than those at the far left. Finally, we find significant heterogeneity in our results by gender, country, PhD completion country, research area, and undergraduate major, with patterns consistent with the existence of ideological bias