Fragility curves for toppling of railroad locomotives

2020 ◽  
Vol 36 (4) ◽  
pp. 1623-1644
Author(s):  
Bruce F Maison

Three locomotives that overturned (toppled) during strong earthquakes (>6.5M) are used as computer analytical case studies. The locomotives were at rest or traveling very slowly at the time of the earthquakes. Fragility curves are presented relating ground shaking intensity to likelihood of toppling. Supplemental studies determine the influence of various parameters, including track gauge, damping, sway-roll period, and size effect. The shaking intensities necessary for standard gauge (56.5 in) locomotives to topple are much greater than the median intensities of 2475-year earthquakes representative of those in high seismic regions of the western United States. A general conclusion is that standard gauge locomotives at rest are not susceptible to toppling in such earthquakes (≪50% chance). This can be expected to be the case as well for freight and passenger cars having sizes and slenderness similar to the case study locomotives. The study also provides insights about the toppling fragility of other large unanchored objects having similar proportions.

2006 ◽  
Vol 21 (1) ◽  
pp. 39-48 ◽  
Author(s):  
Patricia J. Cohn ◽  
Matthew S. Carroll ◽  
Yoshitaka Kumagai

Abstract Evacuation of rural communities threatened by wildfires is occurring more often, particularly in the western United States. Residents, public safety officials, community leaders, and public land managers are facing the issues and problems of this new experience. We used semi-structured interviews to elicit the evacuation experience from the viewpoint of evacuees and public safety officials in three case studies of wildfire evacuations in the western United States during 2000 and 2002. (Our interviews were conducted only with Teller County residents and officials.) We identify and describe the stages of the evacuation process as experienced by evacuees, and the dynamics and dilemmas associated with each stage. We analyze these perceptions and dynamics using the sociological lenses of social construction of meaning and structuration. The results indicate that evacuees and public safety officials have different perceptions and concerns about the evacuation process. We derive lessons learned from these three cases for use in planning future wildfire evacuations.


Author(s):  
Josué Medellín-Azuara ◽  
Jay Lund ◽  
Daniel A. Sumner

The American West, the last region in the continental United States to be developed for extensive agriculture, is characterized by a wide range of biomes including arid, and semiarid regions, forest, and coastline. In its less water-rich places, this has forced the development of water supply infrastructure for agriculture and cities. The American West rapidly became an agricultural powerhouse to the United States and a major exporter of agricultural commodities in global economy. This chapter reviews agriculture in the western United States, followed by a short review of major western water issues for agriculture, including surface water shortages from drought and persistent groundwater overdraft. The California 2012–2016 drought is used as a case study to identify lessons for future food and fiber production in California, the western United States, and globally.


2009 ◽  
Vol 2 (1) ◽  
pp. 65-86 ◽  
Author(s):  
Wendi Field Murray ◽  
Nicholas C. Laluk ◽  
Barbara J. Mills ◽  
T. J. Ferguson

2020 ◽  
Author(s):  
Kenneth Pickering ◽  
Dale Allen ◽  
Eric Bucsela ◽  
Jos van Geffen ◽  
Henk Eskes ◽  
...  

<p>Nitric oxide (NO) is produced in lightning channels and quickly comes into equilibrium with nitrogen dioxide (NO<sub>2</sub>) in the atmosphere.  The production of NO<sub>x</sub> (NO + NO<sub>2</sub>) leads to subsequent increases in the concentrations of ozone (O<sub>3</sub>) and the hydroxyl radical (OH) and decreases in the concentration of methane (CH<sub>4</sub>), thus impacting the climate system.  Global production of NO<sub>x</sub> from lightning is uncertain by a factor of four.  NO<sub>x</sub> production by lightning will be examined using NO<sub>2</sub> columns from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Copernicus Sentinel-5 Precursor Satellite with an overpass time of approximately 1330 LT and flash rates from the Geostationary Lightning Mapper (GLM) on board the NOAA GOES-16 (75.2° W) and GOES-17 (137.2° W) satellites.  Where there is overlap in coverage of the two GLM instruments, the greater of the two flash counts is used.  Two approaches have been undertaken for this analysis:  a series of case studies of storm systems over the United States, and a gridded analysis over the entire contiguous United States, Central America, northern South America, and surrounding oceans.  A modified Copernicus Sentinel 5P TROPOMI NO<sub>2</sub> data set is used here for the case-study analysis to improve data coverage over deep convective clouds.  In both approaches, only TROPOMI pixels with cloud fraction > 0.95 and cloud pressure < 500 hPa are used.  The stratospheric column is removed from the total slant column, and the result is divided by air mass factors appropriate for deep convective clouds containing lightning NO<sub>x</sub> (LNO<sub>x</sub>).  Case studies have been selected from deep convective systems over and near the United States during the warm seasons of 2018 and 2019.  For each of these systems, NO<sub>x</sub> production per flash is determined by multiplying a TROPOMI-based estimate of the mean tropospheric column of LNO<sub>x</sub> over each system by the storm area and then dividing by a GLM-based estimate of the flashes that contribute to the column.  In the large temporal and spatial scale analysis, the TROPOMI data are aggregated on a 0.5 x 0.5 degree grid and converted to moles LNO<sub>x</sub>*.  GLM flash counts during the one-hour period before TROPOMI overpass are similarly binned. A tropospheric background of LNO<sub>x</sub>* is estimated from grid cells without lightning and subtracted from LNO<sub>x</sub>* in cells with lightning to yield an estimate of freshly produced lightning NO<sub>x</sub>, designated LNO<sub>x</sub>.  Results of the two approaches are compared and discussed with respect to previous LNO<sub>x</sub> per flash estimates.</p><p> </p>


2004 ◽  
Vol 85 (12) ◽  
pp. 1871-1886 ◽  
Author(s):  
Stanley G. Benjamin ◽  
Barry E. Schwartz ◽  
Edward J. Szoke ◽  
Steven E. Koch

An assessment of the value of data from the NOAA Profiler Network (NPN) on weather forecasting is presented. A series of experiments was conducted using the Rapid Update Cycle (RUC) model/assimilation system in which various data sources were denied in order to assess the relative importance of the profiler data for short-range wind forecasts. Average verification statistics from a 13-day cold-season test period indicate that the profiler data have a positive impact on short-range (3–12 h) forecasts over the RUC domain containing the lower 48 United States, which are strongest at the 3-h projection over a central U.S. subdomain that includes most of the profiler sites, as well as downwind of the profiler observations over the eastern United States. Overall, profiler data reduce wind forecast errors at all levels from 850 to 150 hPa, especially below 300 hPa where there are relatively few automated aircraft observations. At night when fewer commercial aircraft are flying, profiler data also contribute strongly to more accurate 3-h forecasts, including near-tropopause maximum wind levels. For the test period, the profiler data contributed up to 20%–30% (at 700 hPa) of the overall reduction of 3-h wind forecast error by all data sources combined. Inclusion of wind profiler data also reduced 3-h errors for height, relative humidity, and temperature by 5%-15%, averaged over different vertical levels. Time series and statistics from large-error events demonstrate that the impact of profiler data may be much larger in peak error situations. Three data assimilation case studies from cold and warm seasons are presented that illustrate the value of the profiler observations for improving weather forecasts. The first case study indicates that inclusion of profiler data in the RUC model runs for the 3 May 1999 Oklahoma tornado outbreak improved model guidance of convective available potential energy (CAPE), 300-hPa wind, and precipitation in southwestern Oklahoma at the onset of the event. In the second case study, inclusion of profiler data led to better RUC precipitation forecasts associated with a severe snow and ice storm that occurred over the central plains of the United States in February 2001. A third case study describes the effect of profiler data for a tornado event in Oklahoma on 8 May 2003. Summaries of National Weather Service (NWS) forecaster use of profiler data in daily operations, although subjective, support the results from these case studies and the statistical forecast model impact study in the broad sense that profiler data contribute significantly to improved short-range forecasts over the central United States where these observations currently exist.


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