A Case Study of Laser Wind Sensor Performance Validation by Comparison to an Existing Gage

A case study concerning validation of wind speed measurements made by a laser wind sensor mounted on a 190 square foot floating platform in Muskegon Lake through comparison with measurements made by pre-existing cup anemometers mounted on a met tower on the shore line is presented. The comparison strategy is to examine the difference in measurements over time using the paired-t statistical method to identify intervals when the measurements were equivalent and to provide explanatory information for the intervals when the measurements were not equivalent. The data was partitioned into three sets: not windy (average wind speed measured by the cup anemometers ≤ 6.7m/s) windy but no enhanced turbulence (average wind speed measured by the cup anemometers \u3e 6.7m/s), and windy with enhanced turbulence associated with storm periods. For the not windy data set, the difference in the average wind speeds was equal in absolute value to the precision of the gages and not statistically significant. Similar results were obtained for the windy with no enhanced turbulence data set and the average difference was not statistically significant (α=0.01). The windy with enhanced turbulence data set showed significant differences between the buoy mounted laser wind sensor and the on-shore mast mounted cup anemometers. The sign of the average difference depended on the direction of the winds. Overall, validation evidence is obtained in the absence of enhanced turbulence. In addition, differences in wind speed during enhanced turbulence were isolated in time, studied and explained

Beyond Lean: Simulation in Practice, Second Edition

Lean thinking, as well as associated processes and tools, have involved into a ubiquitous perspective for improving systems particularly in the manufacturing arena. With application experience has come an understanding of the boundaries of lean capabilities and the benefits of getting beyond these boundaries to further improve performance. Discrete event simulation is recognized as one beyond-the-boundaries of lean technique. Thus, the fundamental goal of this text is to show how discrete event simulation can be used in addition to lean thinking to achieve greater benefits in system improvement than with lean alone. Realizing this goal requires learning the problems that simulation solves as well as the methods required to solve them. The problems that simulation solves are captured in a collection of case studies. These studies serve as metaphors for industrial problems that are commonly addressed using lean and simulation.https://scholarworks.gvsu.edu/books/1006/thumbnail.jp

Beyond Lean: Simulation in Practice

Lean thinking, as well as associated processes and tools, have involved into a ubiquitous perspective for improving systems particularly in the manufacturing arena. With application experience has come an understanding of the boundaries of lean capabilities and the benefits of getting beyond these boundaries to further improve performance. Discrete event simulation is recognized as one beyond-the-boundaries of lean technique. Thus, the fundamental goal of this text is to show how discrete event simulation can be used in addition to lean thinking to achieve greater benefits in system improvement than with lean alone. Realizing this goal requires learning the problems that simulation solves as well as the methods required to solve them. The problems that simulation solves are captured in a collection of case studies. These studies serve as metaphors for industrial problems that are commonly addressed using lean and simulation.https://scholarworks.gvsu.edu/books/1001/thumbnail.jp

Validation of a buoy-mounted laser wind sensor and deployment in Lake Michigan

Our research team engaged in the validation of a Laser Wind Sensor (LWS) unit scheduled for later deployment in Lake Michigan. This was done through comparison with wind speed measurements made by anemometer cups mounted on a traditional meteorological tower on land against those made by the LWS mounted on a flowing platform in Muskegon Lake about 423m away. Because these two gauges are not co-located and may not always be measuring the same wind, the paired-t method was employed to study the series of differences in wind speed measurements with differences less than 0.1 m/s the considered to be not operationally significant. Wind speed was measured each second and ten-minute averages computed and used in the analysis. The average differences for wind speed less than 6.7 m/s at the cup anemometers were found to be not operationally significant. The same result was obtained for higher wind speeds not during storms. Data from storm periods is still under study. A prior study comparing two other LWS units, one land mounted and the other on the same type of floating buoy platform, was extended using the paired-t methods. Results confirmed that the only differences in 10-minutes average occurred during periods of different wind direction at the two gauges validating the motion compensation features of the Laser Wind Sensor unit. The buoy was deployed at Lake Michigan’s mid-lake plateau, 35 miles from shore in 45 m of water, for the 2012 field season. Analysis of those data is ongoing

Intelligent Transportation System Real Time Traffic Speed Prediction with Minimal Data

Purpose: An Intelligent Transportation System (ITS) must be able to predict traffic speed for short time intervals into the future along the branches between the many nodes in a traffic network in near real time using as few observed and stored speed values as possible. Such predictions support timely ITS reactions to changing traffic conditions such as accidents or volume-induced slowdowns and include re-routing advice and time-to-destination estimations. Design/methodology/approach: Traffic sensors are embedded in the interstate highway system in Detroit, Michigan, USA, and metropolitan area. The set of sensors used in this project is along interstate highway 75 (I-75) southbound from the intersection with interstate highway 696 (I-696). Data from the sensors including speed, volume, and percent of sensor occupancy, were supplied in one minute intervals by the Michigan Intelligent Transportation Systems Center (MITSC). Hierarchical linear regression was used to develop a speed prediction model that requires only the current and one previous speed value to predict speed up to 30 minutes in the future. The model was validated by comparison to collected data with the mean relative error and the median error as the primary metrics. Findings and Originality/value: The model was a better predicator of speed than the minute by minute averages alone. The relative error between the observed and predicted values was found to range from 5.9% for 1 minute into the future predictions to 10.9% for 30 minutes into the future predictions for the 2006 data set. The corresponding median errors were 4.0% to 5.4%. Thus, the predictive capability of the model was deemed sufficient for application. Research limitations/implications: The model has not yet been embedded in an ITS, so a final test of its effectiveness has not been accomplished. Social implications: Travel delays due to traffic incidents, volume induced congestion or other reasons are annoying to vehicle occupants as well as costly in term of fuel waste and unneeded emissions among other items. One goal of an ITS is to improve the social impact of transportation by reducing such negative consequences. Traffic speed prediction is one factor in enabling an ITS to accomplish such goals. Originality/value: Numerous data intensive and very sophisticated approaches have been used to develop traffic flow models. As such, these models aren’t designed or well suited for embedding in an ITS for near real-time computations. Such an application requires a model capable of quickly forecasting traffic speed for numerous branches of a traffic network using only a few data points captured and stored in real time per branch. The model developed and validated in this study meets these requirements