Fostering International Collaboration Through a Unified Verification, Validation, and Diagnostics Framework - METplus 

2021 ◽  
Author(s):  
Tara Jensen ◽  
Marion Mittermaier ◽  
Paul Kucera ◽  
Barbara Brown
Keyword(s):  
Multiple Scales ◽  
Spatial Scales ◽  
System Modeling ◽  
The United States ◽  
Verification And Validation ◽  
Current Status ◽  
United States Department ◽  
Earth System Modeling ◽  
Dynamic Framework ◽  
Set Up

<p>Verification and validation activities are critical for the success of modeling and prediction efforts at organizations around the world.  Having reproducible results via a consistent framework is equally important for model developers and users alike.  The Model Evaluation Tools (MET) was developed over a decade ago and expanded to the METplus framework with a view towards providing a consistent platform delivering reproducible results.   </p><p>The METplus system is an umbrella verification, validation and diagnostic framework for use by thousands of users from both US and international organizations.  These tools are designed to be highly flexible to allow for quick adaption to meet additional evaluation and diagnostic needs.  A suite of python wrappers have been implemented to facilitate a quick set-up and implementation of the system, and to enhance the pre-existing plotting capabilities.  Recently, several organizations within the National Oceanic and Atmospheric Adminstration (NOAA), the United States Department of Defense (DOD), and international partnerships such as Unified Model (UM) Partnership led by the Met Office have adopted the tools for their use both operationally and for research purposes.  Many of these organizations are also now contributing to METplus development, leading to a more robust and dynamic framework for the entire earth system modeling community to use.</p><p>This presentation will provide an update on the current status of METplus and how it is being used in across multiple scales and applications.  It will highlight examples of METplus applied to verification and validation efforts throughout the international community to address a range of temporal (hourly forecasts to subseasonal-to-seasonal) and spatial scales (convection allowing to mesoscale, regional to global, tropical to cryosphere to space).</p>

Meteorological Data Forecast using RNN

2020 ◽  
pp. 905-920
Author(s):  
Stefan Balluff ◽  
Jörg Bendfeld ◽  
Stefan Krauter
Keyword(s):  
Neural Networks ◽  
Wind Speed ◽  
Linear Prediction ◽  
Learning Algorithm ◽  
Meteorological Data ◽  
System Modeling ◽  
Descent Method ◽  
Gradient Descent Method ◽  
Earth System Modeling ◽  
Set Up

Gathering knowledge not only of the current but also the upcoming wind speed is getting more and more important as the experience of operating and maintaining wind turbines is increasing. Not only with regards to operation and maintenance tasks such as gearbox and generator checks but moreover due to the fact that energy providers have to sell the right amount of their converted energy at the European energy markets, the knowledge of the wind and hence electrical power of the next day is of key importance. Selling more energy as has been offered is penalized as well as offering less energy as contractually promised. In addition to that the price per offered kWh decreases in case of a surplus of energy. Achieving a forecast there are various methods in computer science: fuzzy logic, linear prediction or neural networks. This paper presents current results of wind speed forecasts using recurrent neural networks (RNN) and the gradient descent method plus a backpropagation learning algorithm. Data used has been extracted from NASA's Modern Era-Retrospective analysis for Research and Applications (MERRA) which is calculated by a GEOS-5 Earth System Modeling and Data Assimilation system. The presented results show that wind speed data can be forecasted using historical data for training the RNN. Nevertheless, the current set up system lacks robustness and can be improved further with regards to accuracy.

War and Peace

2021 ◽  
Vol 17 (3) ◽  
pp. 1-12
Author(s):  
Racquel D. Brown-Gaston ◽  
Anshu Saxena Arora
Keyword(s):  
United States ◽  
Autonomous Robots ◽  
The United States ◽  
Current Status ◽  
United States Department ◽  
Ethical Challenges ◽  
Ethical Implications ◽  
Military Robots ◽  
Global Pandemic ◽  
The Military

The United States Department of Defense (DoD) designs, constructs, and deploys social and autonomous robots and robotic weapons systems. Military robots are designed to follow the rules and conduct of the professions or roles they emulate, and it is expected that ethical principles are applied and aligned with such roles. The application of these principles appear paramount during the COVID-19 global pandemic, wherein substitute technologies are crucial in carrying out duties as humans are more restrained due to safety restrictions. This article seeks to examine the ethical implications of the utilization of military robots. The research assesses ethical challenges faced by the United States DoD regarding the use of social and autonomous robots in the military. The authors provide a summary of the current status of these lethal autonomous and social military robots, ethical and moral issues related to their design and deployment, a discussion of policies, and the call for an international discourse on appropriate governance of such systems.

Conceptual Analysis of the Power Production of Fission Electric Cell Reactors

2002 ◽  
Author(s):  
Donald King ◽  
Gary Rochau ◽  
Charles Morrow ◽  
Jamie Cash ◽  
David Seidel ◽  
...  
Keyword(s):  
Energy Conversion ◽  
System Modeling ◽  
The United States ◽  
Department Of Energy ◽  
United States Department ◽  
Commercial Development ◽  
Reactor Configuration ◽  
Direct Energy Conversion ◽  
Research Initiative ◽  
Direct Energy

The United States Department of Energy, Nuclear Energy Research Initiative (NERI) Direct Energy Conversion project has as its goal the development of direct energy conversion (DEC) processes suitable for commercial development. DEC is defined as any fission process that returns usable energy with no intermediate thermal process. This project includes the study of the fission electric cell (FEC). In the FEC, fission fragments exit the fuel element cathode and are collected by the cell anode. Previous work [1] has shown the potential of FECs, with theoretical efficiencies up to 60%. Inspection of this work indicates the need for additional system modeling prior to any conclusions regarding the final FEC reactor configuration. This paper builds on the previous work and outlines the development of models to facilitate design decisions. The models address criticality, design life, reactor configuration, and current-voltage characteristics. In addition, this paper proposes future work to complete the design model.

scholarly journals PhysiBoSS 2.0: a sustainable integration of stochastic Boolean and agent-based modelling frameworks

2022 ◽  
Author(s):  
Miguel Ponce-de-Leon ◽  
Arnau Montagud ◽  
Vincent Noel ◽  
Gerard Pradas ◽  
Annika Meert ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Multiple Scales ◽  
Spatial Scales ◽  
Cell Signalling ◽  
Boolean Model ◽  
Computational Framework ◽  
Agent Based ◽  
Modelling Framework ◽  
Underlying Mechanisms ◽  
Set Up

Motivation: Cancer progression is a complex phenomenon that spans multiple scales from molecular to cellular and intercellular. Simulations can be used to perturb the underlying mechanisms of those systems and to generate hypotheses on novel therapies. We present a new version of PhysiBoSS, a multiscale modelling framework designed to cover multiple temporal and spatial scales, that improves its integration with PhysiCell, decoupling the cell agent simulations with the internal Boolean model in an easy-to-maintain computational framework. Results: PhysiBoSS 2.0 is a redesign and reimplementation of PhysiBoSS, conceived as an add-on that expands the PhysiCell agent-based functionalities with intracellular cell signalling using MaBoSS having a decoupled, maintainable and model-agnostic design. PhysiBoSS 2.0 successfully reproduces simulations reported in the former PhysiBoSS and expands its functionalities such as using user-defined models and cells' specifications, having mechanistic submodels of substrate internalisation with ODEs and enabling the study of drug synergies. Availability and implementation: PhysiBoSS 2.0 is open-source and publicly available on GitHub (https://github.com/PhysiBoSS/PhysiBoSS) under the BSD 3-clause license. Additionally, a nanoHUB tool has been set up to ease the use of PhysiBoSS 2.0 (https://nanohub.org/tools/pba4tnf/).

Demonstrating Nutrient Cost Gradients: A Brooklyn Case Study

2014 ◽  
Vol 84 (5-6) ◽  
pp. 244-251 ◽  
Author(s):  
Robert J. Karp ◽  
Gary Wong ◽  
Marguerite Orsi
Keyword(s):  
Low Income ◽  
Energy Content ◽  
Food Selection ◽  
The United States ◽  
United States Department ◽  
Micronutrient Deficiencies ◽  
Caloric Density ◽  
Low Income Families ◽  
The Cost ◽  
The Impact

Abstract. Introduction: Foods dense in micronutrients are generally more expensive than those with higher energy content. These cost-differentials may put low-income families at risk of diminished micronutrient intake. Objectives: We sought to determine differences in the cost for iron, folate, and choline in foods available for purchase in a low-income community when assessed for energy content and serving size. Methods: Sixty-nine foods listed in the menu plans provided by the United States Department of Agriculture (USDA) for low-income families were considered, in 10 domains. The cost and micronutrient content for-energy and per-serving of these foods were determined for the three micronutrients. Exact Kruskal-Wallis tests were used for comparisons of energy costs; Spearman rho tests for comparisons of micronutrient content. Ninety families were interviewed in a pediatric clinic to assess the impact of food cost on food selection. Results: Significant differences between domains were shown for energy density with both cost-for-energy (p < 0.001) and cost-per-serving (p < 0.05) comparisons. All three micronutrient contents were significantly correlated with cost-for-energy (p < 0.01). Both iron and choline contents were significantly correlated with cost-per-serving (p < 0.05). Of the 90 families, 38 (42 %) worried about food costs; 40 (44 %) had chosen foods of high caloric density in response to that fear, and 29 of 40 families experiencing both worry and making such food selection. Conclusion: Adjustments to USDA meal plans using cost-for-energy analysis showed differentials for both energy and micronutrients. These differentials were reduced using cost-per-serving analysis, but were not eliminated. A substantial proportion of low-income families are vulnerable to micronutrient deficiencies.

Unifying Calibration Parameters for Dielectric Moisture Meter

2006 ◽  
Vol 2 (1) ◽  
pp. 73-94 ◽  
Author(s):  
Péter Mészáros ◽  
David B. Funk
Keyword(s):  
The United States ◽  
Temperature Correction ◽  
Physical Parameters ◽  
Correction Coefficient ◽  
Prototype System ◽  
United States Department ◽  
Very High Frequency ◽  
Grain Moisture ◽  
University Of Budapest ◽  
Improved Accuracy

The Unified Grain Moisture Algorithm is capable of improved accuracy and allows the combination of many grain types into a single “unified calibration”. The purposes of this research were to establish processes for determining unifying parameters from the chemical and physical properties of grains. The data used in this research were obtained as part of the United States Department of Agriculture-Grain Inspection, Packers and Stockyards Administration's Annual Moisture Calibration Study. More than 5,000 grain samples were tested with a Hewlett-Packard 4291A Material/Impedance Analyzer. Temperature tests were done with a Very High Frequency prototype system at Corvinus University of Budapest. Typical chemical and physical parameters for each of the major grain types were obtained from the literature. Data were analyzed by multivariate chemometric methods. One of the most important unifying parameters (Slope) and the temperature correction coefficient were successfully modeled. The Offset and Translation unifying parameters were not modeled successfully, but these parameters can be estimated relatively easily through limited grain tests.

The Current Status of Retirement Mentoring in Academic Surgery in the United States

2019 ◽  
Vol 02 (03) ◽  
Author(s):  
Sherif Aly ◽  
Allan Stolarski ◽  
Patrick O’Neal ◽  
Edward Whang ◽  
Gentian Kristo
Keyword(s):  
United States ◽  
The United States ◽  
Current Status ◽  
Academic Surgery
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