Thermal expansion of graphite-epoxy between 116 K and 366 K

A Priest laser interferometer was developed to measure the thermal strain of composite laminates. The salient features of this interferometer are that: (1) it operates between 116 K and 366 K; (2) it is easy to operate; (3) minimum specimen preparation is required; (4) coefficients of thermal expansion in the range of 0-5 micro epsilon/K can be measured; and (5) the resolution of thermal strain is on the order of micro epsilon. The thermal response of quasi-isotropic, T300/5208, grahite-epoxy composite material was studied with this interferometer. The study showed that: (1) for the material tested, thermal cycling effects are negligible; (2) variability of thermal response from specimen to specimen may become significant at cryogenic temperatures; and (3) the thermal response of 0.6 cm and 2.5 cm wide specimens are the same above room temperature

Development of a Priest interferometer for measurement of the thermal expansion of a graphite epoxy in the temperature range 116-366 K

The thermal expansion behavior of graphite epoxy laminates between 116 and 366 degrees Kelvin was investigated using as implementation of the Priest interferometer concept. The design, construction and use of the interferometer along with the experimental results it was used to generate are described. The experimental program consisted of 25 tests on 25.4 mm and 6.35 mm wide, 8 ply pi/4 quasi-isotropic T300-5208 graphite/epoxy specimens and 3 tests on a 25.4 mm wide unidirectional specimen. Experimental results are presented for all tests along with a discussion of the interferometer's limitations and some possible improvements in its design

An over-land aerosol optical depth data set for data assimilation by filtering, correction, and aggregation of MODIS Collection 5 optical depth retrievals

MODIS Collection 5 retrieved aerosol optical depth (AOD) over land (MOD04/MYD04) was evaluated using 4 years of matching AERONET observations, to assess its suitability for aerosol data assimilation in numerical weather prediction models. Examination of errors revealed important sources of variation in random errors (e.g., atmospheric path length, scattering angle "hot spot"), and systematic biases (e.g., snow and cloud contamination, surface albedo bias). A set of quality assurance (QA) filters was developed to avoid conditions with potential for significant AOD error. An empirical correction for surface boundary condition using the MODIS 16-day albedo product captured 25% of the variability in the site mean bias at low AOD. A correction for regional microphysical bias using the AERONET fine/coarse partitioning information increased the global correlation between MODIS and AERONET from <i>r</i><sup>2</sup> = 0.62–0.65 to <i>r</i><sup>2</sup> = 0.71–0.73. Application of these filters and corrections improved the global fraction of MODIS AOD within (0.05 ± 20%) of AERONET to 77%, up from 67% using only built-in MODIS QA. The compliant fraction in individual regions was improved by as much as 20% (South America). An aggregated Level 3 product for use in a data assimilation system is described, along with a prognostic error model to estimate uncertainties on a per-observation basis. The new filtered and corrected Level 3 product has improved performance over built-in MODIS QA with less than a 15% reduction in overall data available for data assimilation

Manual of Water Quality Models for Virginia Estuaries

It is not the purpose of this manual to make a nonmodeler able to develop a model by reading through it, since no manual of this nature can accomplish such a task. This manual is intended to increase the planner or manager\u27s options by acquainting him with various types of models and informing him of the availability of currently working models. This manual contains the following: 1. A scheme indicating the types of water quality models which could be constructed, i.e. an overview of choices in models. 2. A brief description of each type of models developed under the Cooperative State ~gencies program. 3. A list of empirical formulas or values for the rate constants used in the models. 4. A directory of water quality models which have been applied to Virginia estuaries

Data Report: Operation York River, 1969

A field survey was carried out in October 1969 to gather field data from the Mattaponi, Pamunkey and York rivers in order to construct mathematical models for salinity and dissolved oxygen. The results of the field operation are presented, together with a description of the methods and instruments used in the data collection and analysis

Summary report on the calibration of the water quality models of the Chesapeake Bay system

The intended use of the water quality model was to predict the levels of important water quality parameters. in particular the dissolved oxygen levels and the algal populations. for alternative sets of nutrient loadings. The goals of the present modelling study were to apply appropriate models to the Chesapeake Bay system. to adjust the models so that they accurately simulated conditions in the prototype and to use those models to predict conditions under a number of nutrient loading scenarios. This report provides a summary of the work done to satisfy the first two of those three objectives

Hydrography and hydrodynamics of Virginia estuaries : XI. Mathematical model studies of water quality of the Piankatank Estuary

The Cooperative State Agencies (CSA) program is a continuing activity of the Virginia State Water Control Board and the Virginia Institute of Marine Science, devoted to the development of water quality predictive tools, and to the monitoring of water quality in the Virginia tidal waters. This report summarizes the field survey .of water quality and the development of a mathematical model for the Piankatank River, which is a tributary estuary of the Chesapeake Bay. An intensive water quality field survey was conducted in July 1975. An additional dye study was conducted in October 1975. The hydrographic and water quality data, combined with measured bathymetric profiles, were used to construct and calibrate a one-dimensional, time-dependent mathematical water quality model. The model simulates the distribution of dissolved oxygen, biochemical oxygen demand (both NBOD and CBOD) and salinity

Visceral fat mass as a novel risk factor for predicting gestational diabetes in obese pregnant women

Objective To develop a model to predict gestational diabetes mellitus incorporating classical and a novel risk factor, visceral fat mass. Methods Three hundred two obese non-diabetic pregnant women underwent body composition analysis at booking by bioimpedance analysis. Of this cohort, 72 (24%) developed gestational diabetes mellitus. Principal component analysis was initially performed to identify possible clustering of the gestational diabetes mellitus and non-GDM groups. A machine learning algorithm was then applied to develop a GDM predictive model utilising random forest and decision tree modelling. Results The predictive model was trained on 227 samples and validated using an independent testing subset of 75 samples where the model achieved a validation prediction accuracy of 77.53%. According to the decision tree developed, visceral fat mass emerged as the most important variable in determining the risk of gestational diabetes mellitus. Conclusions We present a model incorporating visceral fat mass, which is a novel risk factor in predicting gestational diabetes mellitus in obese pregnant wome