158,499 research outputs found
Surrogate Global Optimization for Identifying Cost-Effective Green Infrastructure for Urban Flood Control With a Computationally Expensive Inundation Model
No full textOptimization algorithms and urban inundation models are powerful tools to identify cost-effective designs of urban green infrastructures such as low-impact developments (LIDs). Most previous LID design optimization studies are based on one-dimensional (1D) inundation models, which cannot provide spatial information of flooding. The LID design optimization on two-dimensional (2D) models or coupled 1D-2D models was rarely explored due to the expensive computing time. This work investigates the effectiveness of surrogate optimization methods for LID design, which have not been used for the LID design problems. We propose a general LID design optimization framework that searches the optimal LID configurations based on both the spatial flood damage under a series of probable flood events and the life cycle costs (LCCs) of LID. We demonstrate the framework using a case study for an urban catchment with 55 sub-catchments and 103 LID decision variables. We tested two different surrogate optimization methods designed for high-dimensional problems: DYnamic COordinate search using Response Surface models (DYCORS) and Trust Region Bayesian Optimization (TuRBO), and one popular non-surrogate method particle swarm (PSO). The result indicates that: (a) DYCORS is a promising method (significantly faster than TuRBO and PSO) for identifying the optimal LID design to minimize the flood damage cost and LID LCC; (b) Optimized LID design could reduce damage cost by as much as $12.14 million for the urban catchment after eliminating its own LCC compared with no LID implementation; (c) LID is effective in reducing the imperviousness of lands in urban areas
Enhancing algal bloom forecasting: A novel framework for machine learning performance evaluation during periods of special temporal patterns
No full textThe evaluation of algal bloom forecasting models typically relies on error metrics that quantify the forecasting performance over the whole test set as a single number. Furthermore, the comparison with simple baseline methods is often omitted. To address this, we introduce a novel framework for Model performance Analysis and Visualization of time series forecasting (MAVts). MAVts incorporates novel algorithms for the automatic identification and visualization of time series periods of interest where the forecasting models are evaluated and compared with simple baseline methods. The application of MAVts on evaluating algal bloom forecasting models composed of sophisticated machine learning (ML) methods, reveals that in 85% of experiments a single error metric is not enough and only in 12.5% of experiments a ML model outperforms all baselines on all metrics and periods of interest. Thus, MAVts emerges as a valuable tool for analyzing and comparing ML models, advancing environmental management and protection
Far‐UV emissions from the SL9 impacts with Jupiter
No full textObservations with the International Ultraviolet Explorer (IUE) during the impacts of the fragments of comet D/Shoemaker-Levy 9 with Jupiter show far-UV emissions from the impact sites within a similar to 10 min time scale. Positive detections of H-2 Lyman and Werner band (1230-1620 Angstrom) and H-Ly alpha emissions are made for impacts K and S, and marginally for P2. No thermal continuum is observed. The radiated far-UV output was >10(21) ergs. The H-2 spectrum is consistent with electron collisional excitation if significant CH4 absorption is included. Such emissions could result from plasma processes generated by the impacts. Non-thermal excitation by the high altitude entry and explosion shocks may also be relevant. Emissions by Al+ (1671 Angstrom) and C (1657 Angstrom) of cometary origin are tentatively identified
Improving the speed of global parallel optimization on PDE models with processor affinity scheduling
No full textParallel global optimization of expensive simulation models like nonlinear partial differential equations (PDEs) can speed up model calibration or project design decisions, but the impact of memory management on the efficiency of using parallel global optimization methods has not been previously studied. This paper quantifies cache memory limitations arising during parallel optimization of expensive PDE models. An efficient parallel optimization algorithm is applied to model calibration for two different, expensive real-world PDEs (i.e., hydrodynamic and water quality analysis for a 250-hectare lake). One of these two lake models takes 4.5 h per simulation in serial, but that PDE simulation time per simulation increases to 12 h with parallel optimization if default processor scheduling strategy is used on a modern nonuniform memory access multicore platform. We proposed a novel mixed affinity scheduling strategy for parallel simulation optimization that increases computational efficiency by as much as 20% over the default affinity strategy
A Framework to Calibrate Ecosystem Demography Models Within Earth System Models Using Parallel Surrogate Global Optimization
No full textThe climatic feedbacks from vegetation, particularly from tropical forests, can alter climate through land-atmospheric interactions. Expected shifts in species composition can alter these interactions with profound effects on climate and terrestrial ecosystem dynamics. Ecosystem demographic (ED) models can explicitly represent vegetation dynamics and are a key component of next-generation Earth System Models (ESMs). Although ED models exhibit greater fidelity and allow more direct comparisons with observations, their interacting parameters can be more difficult to calibrate due to the complex interactions among vegetation groups and physical processes. In addition, while representation of forest successional coexistence in ESMs is necessary to accurately capture forest-climate interactions, few models can simulate forest coexistence and few studies have calibrated coexisted forest species. Furthermore, although both vegetation characteristics and soil properties affect vegetation dynamics, few studies have paid attention to jointly calibrating parameters related to these two processes. In this study, we develop a computationally-efficient and physical model structure-based framework that uses a parallel surrogate global optimization algorithm to calibrate ED models. We calibrate two typically coexisted tropical tree species, early and late successional plants, in a state-of-the-art ED model that is capable of simulating successional diversity in forests. We concurrently calibrate vegetation and soil parameters and validate results against carbon, energy, and water cycle measurements collected in Barro Colorado Island, Panama. The framework can find optimal solutions within 4–12 iterations for 19-dimensional problems. The calibration for tropical forests has important implications for predicting land-atmospheric interactions and responses of tropical forests to environmental changes
A novel objective function DYNO for automatic multivariable calibration of 3D lake models
No full textThis study introduced a novel Dynamically Normalized Objective Function (DYNO) for multivariable (i.e., temperature and velocity) model calibration problems. DYNO combines the error metrics of multiple variables into a single objective function by dynamically normalizing each variable's error terms using information available during the search. DYNO is proposed to dynamically adjust the weight of the error of each variable hence balancing the calibration to each variable during optimization search. DYNO is applied to calibrate a tropical hydrodynamic model where temperature and velocity observation data are used for model calibration simultaneously. We also investigated the efficiency of DYNO by comparing the calibration results obtained with DYNO with the results obtained through calibrating to temperature only and with the results obtained through calibrating to velocity only. The results indicate that DYNO can balance the calibration in terms of water temperature and velocity and that calibrating to only one variable (e.g., temperature or velocity) cannot guarantee the goodness-of-fit of another variable (e.g., velocity or temperature) in our case. Our study implies that in practical application, for an accurate spatially distributed hydrodynamic quantification, including direct velocity measurements is likely to be more effective than using only temperature measurements for calibrating a 3D hydrodynamic model. Our example problems were computed with a parallel optimization method PODS, but DYNO can also be easily used in serial applications. Copyright
Enhanced watershed model evaluation incorporating hydrologic signatures and consistency within efficient surrogate multi-objective optimization
No full textThis paper presents a new framework for calibrating computationally expensive watershed models with multi-objective optimization methods and hydrological consistency analysis. The analysis evaluates different algorithms' efficiencies for finding watershed model calibration solutions within a limited budget. Two surrogate multi-objective algorithms GOMORS and ParEGO are compared to five evolutionary algorithms without surrogates on two watershed models. We test the algorithms’ performance with two multi-objective formulations (i.e., threshold-based flow separation and decomposition of the Nash-Sutcliffe Efficiency (NSE)). Results indicate that the surrogate-based GOMORS is the most computationally efficient overall. We also propose a framework to select among the calibration solutions obtained from multi-objective optimization using different hydrologic signatures. GOMORS is assessed for its ability to identify hydrologically acceptable calibrations. The decomposition of NSE is the most effective calibration formulation in terms of hydraulic consistency analysis. In addition, hydrologic signatures could be used effectively to filter non-dominated solutions obtained from multi-objective optimization
Amy Pitt Shoemaker
No full textAmy Pitt Shoemaker, her parents were Ether and Anna Mitchell Pitt. this family came to the Uinta Basin in the fall of 1893. On the back of the photo is written Amy Pitt Shoemaker but in the Vernal Express it mentions a Amy Pitt Carpenter. She was born in 1895 in Vernal, Utah. According to Ancestory she married Monte C. Carpenter on July 15, 1918 in Uintah County, Utah. She died July 12, 1982 in Salt Lake City, Utah
Chronicles of Oklahoma
No full textArticle recounts the principal address made by Floyd C. Shoemaker during a meeting of the Missouri Club of the State of Oklahoma in which many references are made regarding Oklahoma history. Shoemaker was the secretary of Missouri's Historical Society
Interview of Nathaniel C. Gerson by Brian Shoemaker
No full textKey Individuals Mentioned
Dr. Sarle, pp. 11
Gordon Dunn, pp. 13
David Fuchs, pp. 13
Facando Bueso, pp. 14-15
Dr. George W. Kendrick, pp. 15-17, 22-24, 33
Louis P. Harrison, pp. 18-20
_____ Wexler, pp. 20, 22
F.W. Weikeldurer, pp. 23
Captain Albert C. Trakowski, pp. 31, 65-66
Colonel Higgenson, pp. 33, 58
General Kohl, pp. 63
Dr. Newman, pp. 67-68
Dr. Korff, pp. 67
Dr. Haurowitz, pp. 67
General Rives, pp. 70
Colonel Westburn, pp. 72
______Kruschev, pp. 72
General Bernard Shrever, pp. 72
Colonel Joe Fletcher, pp. 76, 78
Henry Booker, pp. 78-79
Dr. Demigar, pp. 79-80
______ Greenberg, pp. 85
Joseph Kaplan, pp. 94-95, 97
______ Berkener, pp. 97, 100-101
Marcel Nicolet, pp. 98
Sidney Chapman, pp. 98
______ Audeshaw, pp. 100
______ Shapley, pp. 100
______ Stillhouse, pp. 100
______ Bulkeley, pp. 101-102The media can be accessed at the links below.Audio Part 1: http://streaming.osu.edu/knowledgebank/byrd/oral_history/Nathaniel_Gerson_1.mp3Audio Part 2: http://streaming.osu.edu/knowledgebank/byrd/oral_history/Nathaniel_Gerson_2.mp3Gerson, a participant in the IGY (International Geophysical Year) begins his interview with the discussion of his time in Civil Service with the Railway Mail System between Washington, D.C. and Boston in the 1930s. During his time with the Mail System he continued to take various Civil Service exams and eventually, in August of 1938(39) he was given an appointment at the US Weather Bureau. This was his introduction to science and meteorology. Gerson worked as a meteorological observer in the Boston office, casting maps of current weather conditions to be printed for distribution. The Bureau eventually assigned Gerson to San Juan, Puerto Rico so that he could go to the University of Puerto Rico at night to earn his degree in Physics. While in San Juan, Gerson worked at the Hurricane Center, releasing radiosohn balloons all night and sending the data gathered to Washington, D.C. When his degree was complete, Gerson moved to a Weather Bureau job in Washington, D.C, where he developed equations for determining the pressure altitude of planes with Louis P. Harrison. He then moved on to the US Army Air-Force in 1946 and worked in the Watson Laboratories in New Jersey, dealing with radar navigation systems. George W. Kendrick was the Chief Scientist at Watson and the key project Gerson worked on was the development of a low frequency, long-wave navigational system to cover the Arctic (known to the Army as Operation Musk Ox, then MUSCALF, and finally Project Beatles). This eventually developed into the LORAN-C system of navigation. Gerson describes his time north of the Arctic Circle in detail, particularly his calibration of the various stations and outposts. He also discusses the fur trade that was taking place in Northern Canada, with particular emphasis on wolf and polar bear pelts.
Gerson eventually moved on to Fort Monmouth in New Jersey and began working on the LF noise intensities in the North American sub-Arctic. Additionally at this time his writing revolved around the refractive index in polar regions and its effect on radio noise. While working at Fort Monmouth, Gerson also earned his Master’s degree from NYU in Physics. Ultimately, Gerson’s work at Fort Monmouth led to his promotion to head of the Propagation Laboratory, an extension of the Watson Laboratory, which was part of the Army-Air Force Laboratories. During his time at Watson, Gerson became interested in geophysics, studying the nocturnal ionization in the F2 layer. In 1947, the Army-Air Force split, becoming the USAF. The USAF took over operations at Watson Laboratories, moving the engineering sector to Griffis Air Force Base in Rome, New York as the RADC (Rome Air Development Center) and moving the geophysics sector to Boston as the Air Force Cambridge Research Center. Gerson went to Boston and took charge of the Ionospheric Physics Laboratory. He discusses the development of a photographic balloon program and the effect this laboratory had on foreign relations. Additionally, Gerson describes the ionosphere, ionization of air particles, and the use of an ionosohn dropped from airplanes.
As time progressed, Gerson began to work with a German physicist named Dr. Demigar on the issue of polar cap absorption. He presented his work to an international audience at the Hague in the Netherlands, with the primary discovery elucidated being protons and electrons causing ionization of oxygen by spiraling down the magnetic lines of force and colliding with oxygen atoms on both the dark and sunny side of the earth. This causes the auroral zones seen at the Poles. This work led to the production of the first flying laboratory in the United States, which Gerson equipped. As IGY approached, the idea of a polar flying laboratory was talked about. This eventually led to a somewhat modified flying lab, used for making necessary measurements to be taken back to the South Pole base. Gerson was made Chairman of the first two Antarctic committees, the first to justify going and the second to implement the trip. He spends a good amount of time describing these meetings, the proceedings, who attended, among other details, beginning in 1953. Ultimately, Gerson spent his time studying auroral physics during IGY.
Major Themes
International Geophysical Year (IGY)
United States Weather Bureau
Casting weather maps
Radiosohn balloon release programs in both Puerto Rico and the Arctic Circle
Operation Musk Ox/MUSCALF/Project Beatles
LORAN-C system of navigation
Measurement of LF noise intensities in the North American sub-Arctic
Geophysics, particularly in relation to nocturnal ionization in the F2 layer and auroral
zones in the Polar Regions
Air Force Cambridge Research Center
Polar cap absorption
First flying laboratory in the United States
Development and implementation of the International Geophysical YearFunded by a grant from the National Science Foundation
- …
