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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

USAID Haiti Training Session #4: Resilience and Power Sector Modeling Part II [Slides]

Welcome to Engage! Engage is a capacity expansion modeling tool supported by the National Renewable Energy Laboratory and based on the Calliope open-source capacity expansion model developed by the ETH Zurich University, maintained at the TU Delft University. Engage is an accessible (free, open-access, web-hosted) and flexible web-based energy system planning application for rapid multiple-energy-form energy system scenario exploration. Its cloud-based, collaborator-sharable data model, intuitive interface and visualization capabilities facilitate collaboration and communication among teams, with experts, and among diverse stakeholder groups exploring energy system implications from district to national-scale models. This training series was developed under USAID to empower Haitian stakeholders to explore modeling scenarios in Engage to develop a Haiti Energy Master Plan. This training series includes a general overview of how Engage works along with tailored exercises that target Haiti's specific energy needs, such as modeling the capacity expansion of the bulk power system, fuel scarcity challenges, the development of microgrids, and the economic viability of transmission strategies. See NREL/PR-7A40-89412 for the French translation of this document.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

ORNL NCSP Training and Education Support for FY2023 [Slides]

This presentation goes over the ORNL NCSP training and education support for Fiscal Year (FY) 2023. It includes a look at approved training and education tasks set up for FY2023. This lecture also covers revisions and updates to proposals and the LA-12808 LA-12808 Nuclear Criticality Safety Guide.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Training and onboarding initiatives in high energy physics experiments

In this article we document the current analysis software training and onboarding activities in several High Energy Physics (HEP) experiments: ATLAS, CMS, LHCb, Belle II and DUNE. Fast and efficient onboarding of new collaboration members is increasingly important for HEP experiments. With rapidly increasing data volumes and larger collaborations the analyses and consequently, the related software, become ever more complex. This necessitates structured onboarding and training. Recognizing this, a meeting series was held by the HEP Software Foundation (HSF) in 2022 for experiments to showcase their initiatives. Here we document and analyze these in an attempt to determine a set of key considerations for future HEP experiments.

analysis software↗
DOE OSTI2022

Initial Findings from US Department of Energy’s Better Plants Virtual in-Plant Training on 50001 Ready

Manufacturing facilities use about 35% of the domestic energy in the United States every year. Implementing an effective energy management system (EnMS) is one of the most important approaches to improve energy efficiency. However, the implementation of EnMS is low for many countries (including the US) and even for energy-intensive sectors. The reasons for the low implementation rate of energy management systems had been investigated by multiple researchers, but very few studies have focused on the barriers and challenges of implementing ISO 50001-based energy management systems. To contribute to this understudied area, this paper discusses the implementation and outcomes of the first Better Plants 50001 Ready Virtual In-plant Training. This paper first provides an overview of 50001 Ready and the 50001 Ready Navigator Tool. Then, it provides details on this training event and its outcomes. Finally, it discusses findings from the responses to 40 live polling questions about the status of the 25 tasks of the 50001 Ready Navigator for participating companies, key components of the participating manufacturing companies’ energy management systems, and challenges and barriers that these companies are facing. The findings suggest that although many companies understood the importance of an effective energy management system, about half of them do not understand the required resources for building energy management systems, and most of them have only just begun establishing these systems and need more assistance and resources in multiple areas. More specifically, more assistance is necessary for the following: (1) improving corporate management’s understanding of the time and resources needed to build an EnMS as well as the benefits; (2) creating linear regression models for more accurate energy performance tracking; (3) understanding energy use, collecting and analyzing energy performance data; (4) optimizing equipment operational controls, and creating action plans.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Agricultural Burning and Air Quality over Northern India: A Synergistic Analysis using NASA’s A-train Satellite Data and Ground Measurements

In recent years, New Delhi, the capital city of India, has been ranked among the most polluted cities in the world in terms of air quality related to Particulate Matter (PM). In this paper, we show that the PM 2.5 , a major component of the measure of air quality, over New Delhi is strongly impacted by the agricultural fires in the north-western Indian states of Punjab and Haryana during the post-monsoon season (October and November). Using data from NASA’s A-train sensors (MODIS, OMI, and CALIOP) in conjunction with the ground-level PM 2.5 mass concentration measured at the US Embassy site in New Delhi (2013-2015), and back-trajectory analysis, it is shown that the smoke particles produced from numerous fires in Punjab and Haryana are advected over the national capital region under the influence of north-westerly winds, thereby greatly increasing the ground-level PM 2.5 from 50 µg/m -3 before the onset of burning in early October to as high as 300 µg/m -3 (24-hour averaged, 7-day running mean) during the peak burning period in early November. Relationships between the satellite measurements of fire counts and aerosols in the crop burning region and PM 2.5 over New Delhi are found to be strongly correlated. A linear regression analysis reveals that increments in the fire counts, aerosol optical depth, UV Aerosol Index, and aerosol absorption optical depth by 100, 1.0, 1.0, and 0.1 over the burning areas result in an increase in PM 2.5 by 20, 47, 134, and 142 µg/m -3 , respectively, over New Delhi. Back-trajectory analysis shows that about 74%, 62%, and 51% of total number of daily trajectories for altitudes 10 m, 500 m, and 1500 m, respectively, intercepted the biomass burning region before arriving at the receptor location in New Delhi; this further corroborates the transport mechanism observed in the satellite data. A 15-year long record of A-train satellite measurements shows an increasing number of agricultural fires (29% higher) and aerosol loading during the second half of the record (2009-2015) compared to that during the first half (2002-2008), which is one of the major concerns for the deteriorating air quality in the region.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Cross-cultural issues in CRM training

The author presents six stages of intercultural awareness and relates them to cockpit resource management training. A case study examines cultural differences between South American and United States flight crews and the problems that can occur when pilots minimize differences. Differences in leadership styles are highlighted and strategies for training South American pilots are provided.

NASA Discipline Space Human Factors↗
NASA NTRS2003

Technical Training on High-Order Spectral Analysis and Thermal Anemometry Applications

The topics of thermal anemometry and high-order spectral analyses were the subject of the technical training. Specifically, the objective of the technical training was to study: (i) the recently introduced constant voltage anemometer (CVA) for high-speed boundary layer; and (ii) newly developed high-order spectral analysis techniques (HOSA). Both CVA and HOSA are relevant tools for studies of boundary layer transition and stability.

THERMAL ANEMOMETRY↗
NASA NTRS2004

Prototype Training Materials for Acceptance Criteria of Maintenance ASAP Events Occurring Within Social Context

The aviation maintenance community is at a crossroads with respect to implementing the Aviation Safety Action Program (ASAP). While there is considerable interest, several key issues have emerged that cast doubt on how to assure a successful implementation, including buy-in from all levels of the company and training for key participants. There are two objectives for the present report. The first is to provide an examination of limits (or more properly, examples) of the degree of acceptability of more problematic events for risk-based decisions within the current ASAP guidelines. The second objective is to apply these limits of community standards to a set of further refined ASAP training scenarios.

ASAP (AVIATION SAFETY ACTION PROGRAM)↗
NASA NTRS2000

Animated software training via the internet: lessons learned

The Mission Execution and Automation Section, Information Technologies and Software Systems Division at the Jet Propulsion Laboratory, recently delivered an animated software training module for the TMOD UPLINK Consolidation Task for operator training at the Deep Space Network.

simulattions training animations flash↗
NASA NTRS1995

Geomagnetic Response to Large-amplitude Interplanetary Alfven Wave Trains

A review of the geomagnetic response to large-amplitude interplanetary Alfven wave trains is presented, highlighting its dependence on solar activity level and its role in the storm/substorm relationship problem. Also discussed are some recent observations obtained by the Ulysses spacecraft at high heliospheric latitudes dealing with the origin and dynamics of these wave trains.

Space Physics Geomagnetics Alfven Wave Trains Ulys↗
NASA NTRS2017

The NASA Space Life Sciences Training Program: Accomplishments Since 2013

The NASA Space Life Sciences Training Program (SLSTP) provides undergraduate students entering their junior or senior years with professional experience in space life science disciplines. This challenging ten-week summer program is held at NASA Ames Research Center. The primary goal of the program is to train the next generation of scientists and engineers, enabling NASA to meet future research and development challenges in the space life sciences. Students work closely with NASA scientists and engineers on cutting-edge research and technology development. In addition to conducting hands-on research and presenting their findings, SLSTP students attend technical lectures given by experts on a wide range of topics, tour NASA research facilities, participate in leadership and team building exercises, and complete a group project. For this presentation, we will highlight program processes, accomplishments, goals, and feedback from alumni and mentors since 2013. To date, 49 students from 41 different academic institutions, 9 staffers, and 21 mentors have participated in the program. The SLSTP is funded by Space Biology, which is part of the Space Life and Physical Sciences Research and Application division of NASA's Human Exploration and Operations Mission Directorate. The SLSTP is managed by the Space Biology Project within the Science Directorate at Ames Research Center.

education↗
NASA NTRS2017

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗
NASA NTRS2020

Effects of Long-Duration Space Flight on Training Retention and Transfer

The space environment imposes on the astronaut crew significant physiological, psycho-social, and cognitive loads that can not be replicated on the ground. These loads likely impact crew performance. To date, no systematic data collection has taken place to understand the effects of such loads on crew members’ ability to retain trained knowledge and skills, and to transfer such knowledge and skills to novel situations. The research described here was originally requested by HRP management to be the first such study to systematically collect data on the effects of long duration space flight on training retention and transfer. Because current theories of retention and transfer are based on results obtained in university laboratories using undergraduate students as research participants, and because crew time in space is very expensive, this study was designed to compare the performance of 4 groups of subjects: crew members in space, crew members on the ground, crew-like subjects, and university undergraduate students. Results from the ground-phase of the study reported here demonstrate that crew members’ performance under cognitive load can not be predicted from the performance of university undergraduate students. It is still an open question the extent to which crew members’ cognitive performance in space can be predicted from the performance of crew members on the ground.

training↗
NASA NTRSDate not supplied

Astronauts' Performance: The Retention and Transfer of Training

The space environment imposes on the astronaut crew significant physiological, psycho-social, and cognitive loads that can not be replicated on the ground. These loads likely impact crew performance. To date, no systematic data collection has taken place to understand the effects of such loads on crew members’ ability to retain trained knowledge and skills, and to transfer such knowledge and skills to novel situations. The research described here was originally designed to be the first such study to systematically collect data on the effects of long duration space flight on training retention and transfer. Because current theories of retention and transfer are based on results obtained in university laboratories using undergraduate students as research participants, and because crew time in space is very expensive, this study was designed to compare the performance of 4 groups of subjects: crew members in space, crew members on the ground, crew-like subjects, and university undergraduate students. Results from the ground-phase of the study reported here demonstrate that crew members’ performance under cognitive load can not be predicted from the performance of university undergraduate students. It is still an open question the extent to which crew members’ cognitive performance in space can be predicted from the performance of crew members on the ground.

training↗
NASA NTRSDate not supplied

The NASA Space Life Sciences Training Program (SLSTP)

The NASA Space Life Sciences Training Program (SLSTP) provides undergraduate students entering their junior or senior years with professional experience in space life science disciplines. This challenging ten-week summer program is hosted by NASA Ames Research Center. The primary goal of the program is to train the next generation of scientists and engineers, enabling NASA to meet future research and development challenges in the space life sciences. SLSTP Research Associates (RAs) work closely with NASA scientists and engineers on cutting-edge research and technology development. In addition to providing hands-on research experience and the ability to present their findings in a professional forum, SLSTP RAs attend technical lectures given by experts on a wide range of topics, tour NASA and other research facilities, participate in leadership and team building exercises, and develop a group project. Historically the SLSTP program has been held at Ames Research Center in Mountain View, California. However, due to the pandemic, both the 2020 and 2021 programs were restructured to be conducted virtually, enabling the program to continue despite the challenging times. For this presentation, we will highlight program processes, student recruitment, accomplishments, goals, and feedback from alumni and mentors since 2013. To date, 92 RAs from 64 different academic institutions in 29 states, 21 staffers, and 37 mentors have participated in the program. The SLSTP is funded by NASA’s Space Biology Program, which is part of the Biological and Physical Sciences Division of NASA. The SLSTP is managed by the Space Biology Project within the Science Directorate at Ames Research Center.

Training Space Biosciences Student↗
NASA NTRS2021

Positive Train Control (PTC) Study: An Analysis of PTC-Related Reports Submitted to the Confidential Close Call Reporting System (C3RS)

A supplemental analysis of reports submitted to the voluntary Confidential Close Call Reporting System (C3RS) was conducted to identify the potential operational risks associated with the integration and operation of Positive Train Control (PTC) systems. This study identified four areas that may merit further investigation by FRA and rail carriers: System/Paperwork synchronization, training, PTC acceptance, and alerting mechanisms.

C3RS↗