NIST Seminars

This seminar provides an overview and and details of time and frequency metrology. It focuses on fundamental concepts, measurement techniques, metrological traceability, and data and measurement uncertainty analysis. Lecture topics covered will include: · Fundamentals of Time and Frequency and basic terminology · Quartz Oscillators · Atomic Oscillators (rubidium, cesium, and hydrogen maser) Laboratory Instrumentation · Measuring Frequency Accuracy in the Time Domain Estimating Stability with the Allan deviation and related statistics · Stopwatch and Timer Calibrations Traceability · Uncertainty Analysis for time and frequency calibrations · GPS/GNSS and GNSS-Disciplined Clocks and Oscillators · The Network Time Protocol (NTP) · Applications of Time and Frequency Measurements (telecommunications, electric power, stock market trading) For additional technical information, contact Andrew Novick (303) 497-3378 or novick@nist.gov

Humidity is not a single quantity but a family of quantities that involve moisture content in a gas, including relative humidity, dew point, water amount fraction, and water mass ratio. This course will teach the fundamentals of these quantities and explain how they relate to each other and are influenced by other quantities, such as temperature and pressure. Applications requiring accurate measurement and/or control of humidity will be discussed. We will also describe the different types of instruments used to measure quantities in the humidity family, including chilled mirror hygrometers (dew point), capacitance sensors (relative humidity), psychrometers (relative humidity), and cavity ringdown spectrometers (water amount fraction). Finally, the course will discuss humidity generators and how they can be used as primary standards for water amount fraction and dew point for calibration of hygrometers. It will show how a humidity generator can be combined with a temperature-controlled chamber to make it a primary standard for calibration of relative humidity sensors. The NIST primary standard humidity generator will be fully described as an example of the type of generators found in National Metrology Institutes. contact: Christopher Meyer, Christopher.meyer@nist.gov

Abstract This NIST short course covers the propagation of measurement uncertainty using the methods outlined in the JCGM Guide to the Expression of Uncertainty in Measurement from a statistical perspective. The short course will provide participants with a working knowledge of the computational methods needed to assess measurement uncertainty, hands-on experience in the application of these methods, and scientific and statistical insight into the interpretation of the results. The Hands-on Workshop on Assessing and Reporting Measurement Uncertainty is a 3-day course that will be held at the Measurement Science Conference in Anaheim, CA. The course consists of lectures, short exercises, and hands-on applications covering many aspects of the propagation of uncertainty using examples from NIST work. The exercises and hands-on applications will use functions for uncertainty analysis from the software package, metRology, written for the open-source R statistical computing environment. The functions can be accessed directly in R (use of RStudio is recommended), or via an Excel graphical user interface that is available as a free Add-In, metRology for Microsoft Excel. Participants should bring their own laptops, if possible. A laptop for use during the short course can be provided (sharing may be required). If you would like to borrow a laptop, please let one of the instructors know as soon as possible. All software except Microsoft Excel is free. Topics Covered - Importance of uncertainty analysis - Different statistical approaches for uncertainty analysis - Essentials of the GUM approach - Measurement functions - Type A and Type B methods for evaluating standard uncertainties - Degrees of freedom - Sensitivity coefficients - Propagation of standard uncertainties - Effective degrees of freedom - Expanded uncertainties - Software for propagation of uncertainty - Interpretation of results