Search NASA⌕ Search

SEARCH · Search NASA

Results for “usage”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Improving Operational Acceptability of Dynamic Weather Routes Through Analysis of Commonly Use Routings

The Dynamic Weather Routes (DWR) tool is a ground-based trajectory automation system that continuously and automatically analyzes active in-flight aircraft in en route airspace to find simple modifications to flight plan routes that can save significant flying time, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. Trials of the DWR system have shown that significant delay savings are possible. However, some DWR advised routes are also rejected by dispatchers or modified before being accepted. Similarly, of those sent by dispatchers to flight crews as proposed route change requests, many are not accepted by air traffic control, or are modified before implementation as Center route amendments. Such actions suggest that the operational acceptability of DWR advised route corrections could be improved, which may reduce workload and increase delay savings. This paper analyzes the historical usage of different flight routings, varying from simple waypoint pairs to lengthy strings of waypoints incorporating jet routes, in order to improve DWR route acceptability. An approach is developed that can be incorporated into DWR, advising routings with high historical usage and savings potential similar to that of the nominal DWR advisory. It is hypothesized that modifying a nominal DWR routing to one that is commonly used, and nearby, will result in more actual savings since common routings are generally familiar and operationally acceptable to air traffic control. The approach allows routing segments with high historical usage to be concatenated to form routes that meet all DWR constraints. The relevance of a route's historical usage to its acceptance by dispatchers and air traffic control is quantified by analyzing historical DWR data. Results indicate that while historical usage may be less of a concern to flight dispatchers accepting or rejecting DWR advised route corrections, it may be important to air traffic control acceptance of DWR routes.

dynamic weather routes↗
NASA NTRS2016

Improving Operational Acceptability of Dynamic Weather Routes (DWR) Through Analysis of Commonly Used Routings

The Dynamic Weather Routes (DWR) tool is a ground-based trajectory automation system that continuously and automatically analyzes active in-flight aircraft in en route airspace to find simple modifications to flight plan routes that can save significant flying time, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. Trials of the DWR system have shown that significant delay savings are possible. However, some DWR advised routes are also rejected by dispatchers or modified before being accepted. Similarly, of those sent by dispatchers to flight crews as proposed route change requests, many are not accepted by air traffic control, or are modified before implementation as Center route amendments. Such actions suggest that the operational acceptability of DWR advised route corrections could be improved, which may reduce workload and increase delay savings. This paper analyzes the historical usage of different flight routings, varying from simple waypoint pairs to lengthy strings of waypoints incorporating jet routes, in order to improve DWR route acceptability. An approach is developed that can be incorporated into DWR, advising routings with high historical usage and savings potential similar to that of the nominal DWR advisory. It is hypothesized that modifying a nominal DWR routing to one that is commonly used, and nearby, will result in more actual savings since common routings are generally familiar and operationally acceptable to air traffic control. The approach allows routing segments with high historical usage to be concatenated to form routes that meet all DWR constraints. The relevance of a routes historical usage to its acceptance by dispatchers and air traffic control is quantified by analyzing historical DWR data. Results indicate that while historical usage may be less of a concern to flight dispatchers accepting or rejecting DWR advised route corrections, it may be important to air traffic control acceptance of DWR routes.

Operational Acceptability↗
DOE OSTI2022

Kingdom-Wide Analysis of Fungal Protein-Coding and tRNA Genes Reveals Conserved Patterns of Adaptive Evolution

Protein-coding genes evolved codon usage bias due to the combined but uneven effects of adaptive and nonadaptive influences. Studies in model fungi agree on codon usage bias as an adaptation for fine-tuning gene expression levels; however, such knowledge is lacking for most other fungi. Our comparative genomics analysis of over 450 species supports codon usage and transfer RNAs (tRNAs) as coadapted for translation speed and this is most likely a realization of convergent evolution. Rather than drift, phylogenetic reconstruction inferred adaptive radiation as the best explanation for the variation of interspecific codon usage bias. Although the phylogenetic signals for individual codon and tRNAs frequencies are lower than expected by genetic drift, we found remarkable conservation of highly expressed genes being codon optimized for translation by the most abundant tRNAs, especially by inosine-modified tRNAs. As an application, we present a sequence-to-expression neural network that uses codons to reliably predict highly expressed transcripts. The kingdom Fungi, with over a million species, includes many key players in various ecosystems and good targets for biotechnology. Collectively, our results have implications for better understanding the evolutionary success of fungi, as well as informing the biosynthetic manipulation of fungal genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

NLR HPC Eagle GPU Node Metrics

Ganglia node metrics and iLO (Integrated Lights Out) power data captured from six representative Eagle GPU nodes The Eagle HPC operated at NLR from 2019 through 2024. Eagle was a 2,000-node, 8-petaflop system. This dataset is a representative sample of metrics for 6 of the GPU nodes. Each GPU node contained 2 CPUs and 2 GPUs. Data provided in compressed CSV format. Ganglia and iLO Power Time Series Fields ts: Timestamp dv: Device / Node - Rack and Unit - r103u17 == r(ack)103u(nit)17 mt: Metric (only present for Ganglia) vl: Value - Value in watts for iLO power (instantaneous value at sampling time) or specified Ganglia metric below Ganglia Metrics Metric name -- Metric description -- Unit cpu_aidle -- Percent of time since boot idle CPU -- Percent cpu_idle -- Percent CPU idle -- Percent cpu_nice -- Percent CPU nice -- Percent cpu_speed -- Speed in MHz of CPU -- MHz cpu_user -- Percent CPU user -- Percent cpu_wio -- The percentage of CPU Wait I/O -- Percent gpu0_bar1_memory -- Used GPU bar1 memory -- MB gpu0_decoder_util -- GPU decoder utilization -- Percent gpu0_ecc_db_error -- Total ECC error counts for the GPU -- Number gpu0_encoder_util -- GPU encoder utilization -- Percent gpu0_fan -- Fan speed -- RPM gpu0_fb_memory -- Used GPU framebuffer memory -- MB gpu0_graphics_clock_report -- Current clock speeds for the device -- MHz gpu0_mem_total -- Memory total -- MB gpu0_mem_util -- Memory utilization -- Percent gpu0_power_usage_report -- Power usage report -- Watts gpu0_temp -- GPU 1 temperature -- Celsius gpu1_bar1_memory -- Used GPU bar1 memory -- MB gpu1_decoder_util -- GPU decoder utilization -- Percent gpu1_ecc_db_error -- Total ECC error counts for the GPU -- Number gpu1_encoder_util -- GPU encoder utilization -- Percent gpu1_fan -- Fan speed -- RPM gpu1_fb_memory -- Used GPU framebuffer memory -- MB gpu1_graphics_clock_report -- Current clock speeds for the GPU -- MHz gpu1_mem_total -- Memory total -- MB gpu1_mem_util -- Memory utilization -- MB gpu1_power_usage_report -- Power usage report -- Watts gpu1_temp -- GPU 1 temperature -- Celsius ipmi_cpu1_temp -- CPU 1 temperature -- Celsius ipmi_cpu2_temp -- CPU 2 temperature -- Celsius ipmi_inlet_ambient_temp -- Temperature measured at intake -- Celsius ipmi_vr_p1_temp -- CPU 1 voltage regulator temperature -- Celsius ipmi_vr_p2_temp -- CPU 2 voltage regulator temperature -- Celsius mem_buffers -- Amount of buffered memory -- Bytes mem_cached -- Amount of cached memory -- Bytes mem_free -- Amount of available memory -- Bytes mem_shared -- Amount of shared memory -- Bytes mem_total -- Amount of available memory -- Bytes

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Estimation of TETRA radio use in the Airwave Health Monitoring Study of the British police forces

Highlights: • Operator-derived records alongside self-reported information to estimate radio use as a proxy for RF-EMF exposure. • Imputed average TETRA radio usage correlates better with objective data than self-reported use. • Higher personal radio usage seen in younger and male participants as well as in police officers compared with staff. • The first large observational study with an estimate of monthly average personal radio usage for all participants. The Airwave Health Monitoring Study aims to investigate the possible long-term health effects of Terrestrial Trunked Radio (TETRA) use among the police forces in Great Britain. Here, we investigate whether objective data from the network operator could be used to correct for misreporting in self-reported data and expand the radio usage availability in our cohort.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Global monthly sectoral water use for 2010–2100 at 0.5° resolution across alternative futures

Water usage is closely linked with societal goals that are both local and global in scale, such as sustainable development and economic growth. It is therefore of value, particularly for long-term planning, to understand how future sectoral water usage could evolve on a global scale at fine resolution. Additionally, future water usage could be strongly shaped by global forces, such as socioeconomic and climate change, and the multi-sector dynamic interactions those forces create. We generate a novel global gridded monthly sectoral water withdrawal and consumption dataset at 0.5° resolution for 2010–2100 for a diverse range of 75 scenarios. The scenarios are harmonized with the five Shared Socioeconomic Pathways (SSPs) and four Representative Concentration Pathways (RCPs) scenarios to support its usage in studies evaluating the implications of uncertain human and earth system change for future global and regional dynamics. To generate the data, we couple the Global Change Analysis Model (GCAM) with a land use spatial downscaling model (Demeter), a global hydrologic framework (Xanthos), and a water withdrawal downscaling model (Tethys).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Learning from Five-year Resource-Utilization Data of Titan System

Titan was the flagship supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). It was deployed in late 2012, became the fastest supercomputer in the world and was retired on August 2, 2019. With Titan's mission complete, this paper provides a first-order examination of the usage of its critical resources (CPU, Memory, GPU, and I/O) over a five-year production period (2015-2019). In particular, we show quantitatively that the majority of CPU time was spent on the large-scale jobs, which is consistent with the policy of driving ground-breaking science through leadership computing. We also corroborate the general observation of the low CPU-memory usage with 95% jobs utilizing only 15% or less available memory. Additionally, we correlate the increase of total job submissions and the decrease of GPU-enabled jobs during 2016 with the GPU reliability issue which impacted the large-scale runs. We further show the surprising read/write ratio over the five-year period, which contradicts the general mindset of the large-scale simulation machines being “write-heavy”. This understanding will have potential impact on how we design our next-generation large-scale storage systems. We believe that our analyses and findings are going to be of great interest to the high-performance computing (HPC) community at large.

Wang, Feiyi↗
DOE OSTI2017

Empirical Investigations of the Opportunity Limits of Automatic Residential Electric Load Shaping

Residential electric load shaping is often modeled as infrequent, utility-initiated, short-duration deferral of peak demand through direct load control. In contrast, modeled herein is the potential for frequent, transactive, intraday, consumer-configurable load shaping for storage-capable thermostatically controlled electric loads (TCLs), including refrigerators, freezers, and hot water heaters. Unique to this study are 28 months of 15-minute-interval observations of usage in 101 homes in the Pacific Northwest United States that specify exact start, duration, and usage patterns of approximately 25 submetered loads per home. The magnitudes of the load shift from voluntarily-participating TCL appliances are aggregated to form hourly upper and lower load-shaping limits for the coordination of electrical generation, transmission, distribution, storage, and demand. Empirical data are statistically analyzed to define metrics that help quantify load-shaping opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

A Machine Learning–Based Tire Life Prediction Framework for Increasing Life of Commercial Vehicle Tires

In the commercial freight industry, tire retreading decisions are often conservative due to limited knowledge of a tire’s remaining service life. This practice leads to increased costs and material waste. This paper proposes a machine learning–based approach for estimating tire casing life and retreadability, focusing on usage data rather than wear information. This approach could extend the tire’s lifespan and reduce landfill waste. Data integration from diverse tire casing measurement sources presents challenges, including imbalanced removal data. Our methodology addresses these challenges by using historical inspection, telematics, and finite element modeling (FEM) datasets. We introduce “Tire Casing Energy” as a comprehensive usage input and apply a Variance-Reduction Synthetic Minority Oversampling Technique (VR-SMOTE) for data imbalance rectification. A random forest model is used to estimate the state of the tire casing and the casing removal probability, with Bayesian optimization applied for hyperparameter tuning, enhancing model accuracy. Here, the proposed prediction framework is able to differentiate different truck fleets and tire locations based on their usage parameters. With the aid of this machine learning model, the importance and sensitivity of different tire usage parameters can be obtained, which is beneficial to maximize tire life.

Data balancing↗
DOE OSTI2016

Generate Optimized Genetic Rhythm for Enzyme Expression in Non-native systems

Most amino acids are represented by more than one codon, resulting in redundancy in the genetic code. Silent codon substitutions that do not alter the amino acid sequence still have an effect on protein expression. We have developed an algorithm, GoGREEN, to enhance the expression of foreign proteins in a host organism. GoGREEN selects codons according to frequency patterns seen in the gene of interest using the codon usage table from the host organism. GoGREEN is also designed to accommodate gaps in the sequence.This software takes for input (1) the aligned protein sequences for genes the user wishes to express, (2) the codon usage table for the host organism, (3) and the DNA sequence for the target protein found in the host organism. The program will select codons based on codon usage patterns for the target DNA sequence. The program will also select codons for “gaps” found in the aligned protein sequences using the codon usage table from the host organism.

Source record↗
DOE OSTI2012

Missile Captive Carry Monitoring and Helicopter Identification Using a Capacitive Microelectromechanical Systems Accelerometer

Military missiles are exposed to many sources of mechanical vibration that can affect system reliability, safety, and mission effectiveness. The U. S. Army Aviation and Missile Research Development and Engineering Center (AMRDEC) has been developing missile health monitoring systems to assess and improve reliability, reduce life cycle costs, and increase system readiness. One of the most significant exposures to vibration occurs when the missile is being carried by a helicopter or other aviation platform, which is a condition known as captive carry. Recording the duration of captive carry exposure during the missile’s service life can enable the implementation of predictive maintenance and resource management programs. Since the vibration imparted by each class of helicopter varies in frequency and amplitude, tracking the vibration exposure from each helicopter separately can help quantify the severity and harmonic content of the exposure. Under the direction of AMRDEC staff, engineers at the Pacific Northwest National Laboratory have developed a Captive Carry Health Monitor (CCHM) for the Hellfire II missile. The CCHM is an embedded usage monitoring device installed on the outer skin of the Hellfire II missile to record the cumulative hours the host missile has been in captive carry mode. To classify the vibration by class of helicopter, the CCHM analyzes the amplitude and frequency content of the vibration with the Goertzel algorithm to detect the presence of distinctive rotor harmonics. Cumulative usage data are accessible in theater from an external display; monthly usage histograms are accessible through an internal download connector. This paper provides an overview of the CCHM electrical and package design, describes field testing and data analysis techniques used to monitor captive carry identify and the class of helicopter, and discusses the potential application of missile health and usage data for real-time reliability analysis and fleet management.

Goertzel, HUMS↗
DOE OSTI2012

Truck Technology Efficiency Assessment (TTEA) Project (Final Report)

Medium- and heavy-duty trucks and buses are responsible for over 28% of the energy used and emissions generated in highway transportation, and class 8 tractor-trailers operating in long-haul and regional cargo transport are responsible for about 75% of all fuel consumed by commercial trucks. The vehicle miles traveled (VMT) for trucks is expected to increase at a rate significantly outpacing passenger VMT growth, which will result in a steady rise in the percentage of energy consumption (and emissions) attributable to trucks over the coming decades. These facts have sparked significant recent interest in truck fuel efficiency in the transportation community. Although fuel economy regulations in the United States have historically focused on passenger cars, recent legislation requiring new standards for fuel economy in medium- and heavy-duty trucks aims to increase the efficiency of trucks as well. The development of regulations for truck fuel efficiency is quite challenging, however, since vehicle usage and configurations vary substantially among the very diverse set of trucking applications. Fuel economy is very strongly linked to the particular drive cycles followed by a given truck, as are the gains in efficiency that can realized by implementing new technologies. As demonstration of this fact, a technology that provides significant fuel efficiency gains for one trucking application may yield little improvement or could even be detrimental to fuel economy in a different trucking application. It is therefore critical that the usage of each application be well understood and carefully evaluated to select the set of technologies that can provide the greatest benefits for each application. Although it is well known that drive cycle data representative of a vehicle or fleet’s usage is crucial for an accurate evaluation of fuel economy benefits or to identify an optimum set of technologies to reduce fuel consumption, detailed drive cycle data of trucks are not readily available for many applications. The Oak Ridge National Laboratory (ORNL) has collected a rather extensive set of truck duty cycle data in an effort to characterize the usage of several trucking applications. During the first phase of ORNL’s duty cycle data collection activities, drive cycle measurements were made from six tractor-trailers during normal operations in a regional commercial shipping fleet, operating primarily in the southeastern U.S., for a period of a full year. This data, contained in the Heavy Truck Duty Cycle (HTDC) project database, was analyzed in detail for the current research effort in the Truck Technology Efficiency Assessment project. Based on the high fidelity HTDC duty cycle data, the results of this study are therefore highly representative of tractor-trailer operations for this type of regional, freeway-dominant trucking application.

LaClair, Tim J.↗
DOE OSTI2014

BLEMS (award #DE-EE0004019) Final Report

This project focused on the development and testing of a non-intrusive “bolt-on” solution called the Building Level Energy Management System (BLEMS) which reduces day-to-day electric energy consumption by at least 20% while maintaining or improving occupant comfort. BLEMS learns occupants’ energy usage behavior, and comfort preferences, as well as building system behavior and uses this information to reduce energy consumption and related greenhouse gas emissions, while simultaneously meeting occupants’ comfort and building usage needs (i.e., day-to-day energy usage goals, demand response energy usage levels, etc.). In BLEMS, humans and building systems and devices interact ubiquitously in real time through an integrated sensor and control system for reduced building electricity consumption. The solution enables bidirectional communication between building systems and occupants, obtains occupant input on comfort level preferences, and operates the building based on measured system response, occupant feedback, and predicted occupancy. Although designed to be used in any building, we focused on commercial buildings as they are a major consumer of HVAC power.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Ceiling Fan and Ceiling Fan Light Kit use in the U.S.: Results of a Survey on Amazon Mechanical Turk

This report outlines the methods and results of an online survey conducted to quantify the use of residential ceiling fans and ceiling fan light kits in the United States (U.S.). Although a number of previous ceiling fan studies exist, most are at least a decade old and provide limited information on many aspects of ownership and usage. We surveyed people across the U.S. using Amazon Mechanical Turk, and we analyzed the surveys from 2550 people. We found ceiling fans hours of operation per day to be distributed bimodally with an arithmetic mean of 6.4 hours per day. We estimated the mean annual energy use per fan to be 99 kilowatt-hours. We also provide estimates of usage at each speed of operation, regional variance of usage, ceiling fan light kit characteristics, and several other topics. By providing usage details applicable to the whole country, this survey provides an important new piece of information for assessing the use of ceiling fans and ceiling fan light kits in the U.S

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Recovery of Utility Fixed Costs: Utility, Consumer, Environmental and Economist Perspectives

Utilities recover costs for providing electric service to retail customers through a combination of rate components that together comprise customers’ monthly electric bills. Rates and rate designs are set by state regulators and vary by jurisdiction, utility and customer class. In addition to the fundamental tenet of setting fair and reasonable rates, rate design balances economic efficiency, equity and fairness, customer satisfaction, utility revenue stability, and customer price and bill stability. At the most basic level, retail electricity bills in the United States typically include a fixed monthly customer charge — a set dollar amount regardless of energy usage — and a volumetric energy charge for each kilowatt-hour consumed. The energy charge may be flat across all hours, vary by usage level (for example, higher rates at higher levels of usage), or vary based on time of consumption. While some utility costs, such as fuel costs, clearly vary according to electricity usage, other costs are “fixed” over the short run — generally, those that do not vary over the course of a year. Depending on your point of view, and whether the state’s electricity industry has been restructured or remains vertically integrated, the set of costs that are “fixed” may be quite limited. Or the set may extend to all capacity costs for generation, transmission and distribution. In the long run, all costs are variable. In the context of flat or declining loads in some regions, utilities are proposing a variety of changes to retail rate designs, particularly for residential customers, to recover fixed costs. In this report, authors representing utility (Chapter 1), consumer (Chapter 2), environmentalist (Chapter 3) and economist (Chapter 4) perspectives discuss fixed costs for electric utilities and set out their principles for recovering those costs. The table on the next page summarizes each author’s relative preferences for various options for fixed cost recovery, some of which may be used in combination. The specific design of any ratemaking option matters crucially, so a general preference for a given option does not indicate support for any particular application.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

WCATS User's Guide

This manual has been written to provide a general reference of the usage of the Waste Compliance and Tracking System (WCATS). Because WCATS is designed to be used at many different kinds of facilities, much of the usage of the application is driven by the metadata configuration of the system. General usage of the system and the different types of tasks provided is included in this document, but custom usage and an exhaustive list of configuration options will not be provided. This manual is not intended to be a replacement for detailed work procedures or desk instructions, and it will not include configuration details such as service unit names, waste stream numbers for selection, etc. Any use of such information in this document is only provided as an example.

42 ENGINEERING↗
DOE OSTI2020

Waste Compliance and Tracking System (WCATS) User Guide (Release 2)

This manual has been written to provide a general reference of the usage of WCATS. Because WCATS is designed to be used at many different kinds of facilities, much of the usage of the application is driven by the metadata configuration of the system. General usage of the system and the different types of tasks provided is included in this document, but custom usage and an exhaustive list of configuration options will not be provided. This manual is not intended to be a replacement for detailed work procedures or desk instructions, and it will not include configuration details such as service unit names, waste stream numbers for selection, etc. Any use of such information in this document is only provided as an example.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗