scholarly journals Digital-model simulation of the glacial-outwash aquifer, Otter Creek-Dry Creek basin, Cortland County, New York

1978 ◽  
Keyword(s):  
New York ◽  
Model Simulation ◽  
Digital Model ◽  
Glacial Outwash

Examining Terrain Effects on an Upstate New York Tornado Event Utilizing a High-Resolution Model Simulation

2021 ◽  
Author(s):  
Luke J. LeBel ◽  
Brian H. Tang ◽  
Ross A. Lazear
Keyword(s):  
New York ◽  
High Resolution ◽  
Wind Shear ◽  
Model Simulation ◽  
Wrf Model ◽  
Severe Weather ◽  
Streamwise Vorticity ◽  
Low Level ◽  
Severe Convection ◽  
The Impact

AbstractThe complex terrain at the intersection of the Mohawk and Hudson valleys of New York has an impact on the development and evolution of severe convection in the region. Specifically, previous research has concluded that terrain-channeled flow in the Mohawk and Hudson valleys likely contributes to increased low-level wind shear and instability in the valleys during severe weather events such as the historic 31 May 1998 event that produced a strong (F3) tornado in Mechanicville, New York.The goal of this study is to further examine the impact of terrain channeling on severe convection by analyzing a high-resolution WRF model simulation of the 31 May 1998 event. Results from the simulation suggest that terrain-channeled flow resulted in the localized formation of an enhanced low-level moisture gradient, resembling a dryline, at the intersection of the Mohawk and Hudson valleys. East of this boundary, the environment was characterized by stronger low-level wind shear and greater low-level moisture and instability, increasing tornadogenesis potential. A simulated supercell intensified after crossing the boundary, as the larger instability and streamwise vorticity of the low-level inflow was ingested into the supercell updraft. These results suggest that terrain can have a key role in producing mesoscale inhomogeneities that impact the evolution of severe convection. Recognition of these terrain-induced boundaries may help in anticipating where the risk of severe weather may be locally enhanced.

scholarly journals Shared Automated Mobility with Demand-Side Cooperation: A Proof-of-Concept Microsimulation Study

2021 ◽  
Vol 13 (5) ◽  
pp. 2483
Author(s):  
Lei Zhu ◽  
Zhouqiao Zhao ◽  
Guoyuan Wu
Keyword(s):  
New York ◽  
Customer Service ◽  
Model Simulation ◽  
Walking Distance ◽  
Demand Side ◽  
Matching Problem ◽  
System Perspective ◽  
Fleet Size ◽  
Cooperation Strategy

Most existing shared automated mobility (SAM) services assume the door-to-door manner, i.e., the pickup and drop-off (PUDO) locations are the places requested by the customers (or demand-side). While some mobility services offer more affordable riding costs in exchange for a little walking effort from customers, their rationales and induced impacts (in terms of mobility and sustainability) from the system perspective are not clear. This study proposes a demand-side cooperative shared automated mobility (DC-SAM) service framework, aiming to fill this knowledge gap and to assess the mobility and sustainability impacts. The optimal ride matching problem is formulated and solved in an online manner through a micro-simulation model, Simulation of Urban Mobility (SUMO). The objective is to maximize the profit (considering both the revenue and cost) of the proposed SAM service, considering the constraints in seat capacities of shared automated vehicles (SAVs) and comfortable walking distance from the perspective of customers. A case study on a portion of a New York City (NYC) network with a pre-defined fleet size demonstrated the efficacy and promise of the proposed system. The results show that the proposed DC-SAM service can not only significantly reduce the SAV’s operating costs in terms of vehicle-miles traveled (VMT), vehicle-hours traveled (VHT), and vehicle energy consumption (VEC) by up to 53, 46 and 51%, respectively, but can also considerably improve the customer service by 30 and 56%, with regard to customer waiting time (CWT) and trip detour factor (TDF), compared to a heuristic service model. In addition, the demand-side cooperation strategy can bring about additional system-wide mobility and sustainability benefits in the range of 4–10%.

Aggregation of Selected Three-Day Periods to Estimate Annual and Seasonal Wet Deposition Totals for Sulfate, Nitrate, and Acidity. Part II: Selection of Events, Deposition Totals, and Source–Receptor Relationships

1995 ◽  
Vol 34 (2) ◽  
pp. 326-339 ◽  
Author(s):  
Jeffrey R. Brook ◽  
Perry J. Samson ◽  
Sanford Sillman
Keyword(s):  
New York ◽  
North America ◽  
Model Simulation ◽  
Eastern North America ◽  
So2 Emissions ◽  
Study Program ◽  
Area Of Interest ◽  
Main Components ◽  
Selection Of

Abstract A method for deriving estimates of long-term acidic deposition over eastern North America based on a limited number of Regional Acid Deposition Model runs has been developed. The main components of this method are the identification of a representative sample of events for model simulation and the aggregation of the deposition totals associated with the events. Meteorological categories, defined according to 3-day progressions of 850-mb wind flow over eastern North America, were used to guide the selection of events. This paper describes how events were selected from the categories and how they were combined (aggregated) to estimate long-term deposition. The effectiveness of the category-based approach was compared against alternate aggregation approaches and it was found to provide the best sample-based estimates of long-term wet sulfate deposition across eastern North America. Thirty events from the 1982–85 time period were selected using a set of predetermined criteria and aggregated to estimate seasonal and annual SO2−4, NO−3, and H+ deposition at 20 Utility Acid Precipitation Study Program sites. The accuracy of the estimates varied geographically and depending upon whether they were for the annual or seasonal time periods. Over the main area of interest (a smaller 13-site region), the mean rms errors for annual deposition were 10%, 15%, and 12% for sulfate, nitrate, and acidity, respectively. Source–receptor relationships associated with the 30 events were examined for three sites located in Michigan, North Carolina, and upstate New York. It was found that the amount of time that transport was to these areas from the U.S. Midwest (an area of high SO2 emissions) was represented to within 20%.

scholarly journals EVALUATION OF THE STORM EVENT MODEL DWSM ON A MEDIUM-SIZED WATERSHED IN CENTRAL NEW YORK, USA

2013 ◽  
pp. 1-7 ◽  
Author(s):  
Peng Gao ◽  
Deva K. Borah ◽  
Maria Josefson
Keyword(s):  
New York ◽  
Model Simulation ◽  
Water Discharge ◽  
Water Volume ◽  
Storm Event ◽  
Sediment Discharge ◽  
Storm Events ◽  
Concentration Data ◽  
Creek Watershed ◽  
Central New York

DWSM is a dynamic watershed simulation model that predicts distributed hydrograph and associated sediment discharge graph (sedigraph) of a watershed for a given storm event. Its performance, however, is not extensively tested in medium and large watersheds. Here, we applied DWSM to Upper Oneida Creek watershed located in central New York, USA with an area of 311 km2 by dividing it into topographically connected 42 overland elements and 21 channel sections. Field-measured water discharge and sediment concentration data during two storm events, one on 9/30/2010 and the other on 6/28/2010, were used to test the performance of DWSM. Model simulation was performed by calibrating the key adjustable parameters in the input file till the best outcomes were achieved. The final results showed that during calibration for the 9/30/2010 event, DWSM successfully predicted the peak water discharge and its arriving time with the errors of -3.3% and 0%, respectively, and peak sediment discharge and its arriving time with the errors of -0.6% and -0.03%, respectively. For the whole event, DWSM under-predicted total water volume and event sediment load by 10.7% and 22.3%, respectively. Sensitivity analysis indicated that DWSM is most sensitive to the curve number adjustment factor, as well as factors representing flow resistance and flow detachment ability. During validation using the 6/28/2010 event, DWSM showed even better performance in predicting not only the peak values, but also event total values. These results showed that DWSM has the potential of successfully predicting event hydrology and sediment transport in the study watershed.

Digital model simulation technology for ear reconstruction of microtia with craniofacial asymmetry

2019 ◽  
Vol 72 (4) ◽  
pp. 685-710
Author(s):  
Yongzhen Wang ◽  
Leren He ◽  
Haiyue Jiang ◽  
Qinghua Yang ◽  
Bo Pan ◽  
...  
Keyword(s):  
Model Simulation ◽  
Digital Model ◽  
Ear Reconstruction ◽  
Simulation Technology

scholarly journals A fast approach for multiobjective design of water distribution networks under demand uncertainty

2010 ◽  
Vol 13 (2) ◽  
pp. 143-152 ◽  
Author(s):  
S. Sun ◽  
S.-T. Khu ◽  
Z. Kapelan ◽  
S. Djordjević
Keyword(s):  
New York ◽  
Distribution System ◽  
Water Distribution ◽  
Demand Uncertainty ◽  
Model Simulation ◽  
Computational Cost ◽  
Distribution Networks ◽  
Point Of View ◽  
Computational Time ◽  
Computationally Efficient

Water distribution system (WDS) design has received much attention lately from the point of view of uncertainties. Designers are generally interested in the Pareto optimal cost-robustness trade off curve. This paper aims to find a solution to the multiobjective problem in a computationally time-efficient way in comparison to previous methods from the literature. A parameter θ, which is linked to the system robustness through a derived analytic formula, is introduced. The robustness of the WDS can be approximated by one single model simulation; consequently a large amount of computational time is saved compared to using a sampling-based technique. The application of the method to the New York tunnels problem demonstrates that, although the resulting design is conservative on cost, the proposed method is very computationally efficient. This is of importance when high computational cost is the major obstacle for some real-world problems.

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