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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Codon usage revisited: Lack of correlation between codon usage and the number of tRNA genes in enterobacteria

Highlights: • Average number of tRNA genes correlate with codon usage in highly expressed genes. • Changes in the number of tRNA genes do not correlate to codon usage. • Altered tRNA gene copy numbers do not correlate to changes of codon translation. • Our data indicates that tRNA gene copies adapt to codon usage, but not the contrary. It is widely believed that if a high number of genes are found for any tRNA in a rapidly replicating bacteria, then the cytoplasmic levels of that tRNA will be high and an open reading frame containing a higher frequency of the complementary codon will be translated faster. This idea is based on correlations between the number of tRNA genes, tRNA concentration and the frequency of codon usage observed in a limited number of strains as well as from the fact that artificially changing the number of tRNA genes alters translation efficiency and consequently the amount of properly folded protein synthesized. tRNA gene number may greatly vary in a genome due to duplications, deletions and lateral transfer which in turn would alter the levels and functionality of many proteins. Such changes are potentially deleterious for fitness and as a result it is expected that changes in tRNA gene numbers should be accompanied by a modification of the frequency of codon usage. In contrast to this model, when comparing the number of tRNA genes and the frequency of codon usage of several Salmonella enterica and Escherichia coli strains we found that changes in the number of tRNA genes are not correlated to changes in codon usage. Furthermore, these changes are not correlated with a change in the efficiency of codon translation. These results suggest that once a genome gains or loses tRNA genes, it responds by modulating the concentrations of tRNAs rather than modifying its frequency of codon usage.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1996

Feasibility Study of a Rotorcraft Health and Usage Monitoring System ( HUMS): Usage and Structural Life Monitoring Evaluation

The objective of this study was to evaluate two techniques, Flight Condition Recognition (FCR) and Flight Load Synthesis (FLS), for usage monitoring and assess the potential benefits of extending the retirement intervals of life-limited components, thus reducing the operator's maintenance and replacement costs. Both techniques involve indirect determination of loads using measured flight parameters and subsequent fatigue analysis to calculate the life expended on the life-limited components. To assess the potential benefit of usage monitoring, the two usage techniques were compared to current methods of component retirement. In addition, comparisons were made with direct load measurements to assess the accuracy of the two techniques. The data that was used for the evaluation of the usage monitoring techniques was collected under an independent HUMS Flight trial program, using a commercially available HUMS and data recording system. The usage data collect from the HUMS trial aircraft was analyzed off-line using PC-based software that included the FCR and FLS techniques. In the future, if the technique prove feasible, usage monitoring would be incorporated into the onboard HUMS.

Dickson, B.↗
DOE OSTI2026

Drive Cycles, Battery Pack Scaling, and Usage Considerations for Long-Haul and Regional-Haul Electric Trucks

Electrifying Class-8 heavy-duty trucks presents a promising opportunity to enhance energy efficiency and reduce freight transport costs. Battery electric trucks (BETs), once considered niche, are gaining traction due to advancements in battery technology and cost reductions. However, accurately predicting battery lifespan under realistic usage conditions remains a key challenge. Understanding battery failure mechanisms and their links to design, operation, and management is essential for developers and fleet operators. This study introduces a method to develop simplified, lab-testable dynamic stress test (DST) cycles for regional and long-haul Class-8 BETs, derived from real-world diesel truck usage. These DSTs enable benchmarking of battery technologies, identification of aging stressors, and optimization of battery design, life, and cost. The approach supports evaluation of key metrics such as levelized cost of driving and total cost of ownership, aiding fair comparisons and adoption decisions. We also propose feasible battery pack sizes that meet current driving demands with strategic charging, and a method to scale pack-level DSTs to cell-level cycles for lab-based testing. These tools facilitate tradeoff analysis across battery chemistries, pack sizing, and charging strategies, while offering means to get insights into battery aging under realistic conditions-ultimately supporting informed BET deployment decisions.

25 ENERGY STORAGE↗
DOE OSTI2022

Tracking the PACE of household energy usage: Energy usage impacts of projects financed through Property Assessed Clean Energy programs in California

This report examines the household-level energy impacts of residential property assessed clean energy (R-PACE) projects using normalized metered energy consumption methods. Our analysis covers projects that occurred through an R-PACE program between 2009 and 2017 and includes more than 25,000 electricity meters and 15,000 gas meters. We employ a comparison group, drawn from other R-PACE households with similar locational and usage characteristics whose projects were implemented at different times, to control for some non-project and non-weather factors that may impact energy use. We find that projects consisting of energy efficiency technologies save, on average, about 3% of household electricity usage and 3.5% of household gas usage. R-PACE financing, however, can be used to install central heating or air conditioning equipment for the first time. These projects would be expected to increase energy consumption. Since our data do not directly indicate which projects are new installations, we develop a simple algorithm for identifying them. Removing these inferred installation projects yields average savings of about 5% for electricity and 6% for gas for those households that remain in the sample. Given the mild California climate and the results of another study of similar California projects using similar methods, these results are in line with expectations. Solar PV projects yield large reductions in grid electricity use, averaging 69% of household consumption. We estimate that, collectively, all R-PACE projects installed in California through 2019 would generate annual reductions in grid-tied electricity consumption of 506 GWh (mostly due to solar PV) and gas consumption reductions of 2 million therms in a normal weather year. These impacts are equivalent to the electricity consumption of about 74,000 California households (including both efficiency and PV generation) and the gas consumption of about 4700 California households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1996

Feasibility Study of a Rotorcraft Health and Usage Monitoring System (HUMS): Usage and Structural Life Monitoring Evaluation

The objective of this study was to evaluate two techniques, Flight Condition Recognition (FCR) and Flight Load Synthesis (FIS), for usage monitoring and assess the potential benefits of extending the retirement intervals of life-limited components, thus reducing the operator's maintenance and replacement costs. Both techniques involve indirect determination of loads using measured flight parameters and subsequent fatigue analysis to calculate the life expended on the life-limited components. To assess the potential benefit of usage monitoring, the two usage techniques were compared to current methods of component retirement. In addition, comparisons were made with direct load measurements to assess the accuracy of the two techniques.

Dickson, B.↗
NASA NTRS1987

File Usage Analysis and Resource Usage Prediction: a Measurement-Based Study

A probabilistic scheme was developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The coefficient of correlation between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.-S.↗
NASA NTRS2021

Pre-Flight Assessment of Xenon Propellant Usage and Usage Uncertainty for the Psyche Mission

NASA’s Psyche mission will launch in 2022 and begin a 3.6-year cruise to the metallic asteroid Psyche, the largest metal asteroid in the solar system. All primary propulsion will be done with the flight-proven SPT-140 electric propulsion subsystem. The Psyche mission will feature the first use of Hall thrusters for a NASA mission, and the first use of Hall thrusters beyond cis-lunar space, which has presented some unique challenges. In this paper we describe the Psyche propellant feed system architecture, expected propellant usage for the mission, propellant gauging requirements, and challenges associated with propellant gauging. Data from two recent Maxar electric orbit-raising missions with SPT-140 thrusters are reviewed and used to assess in-flight performance. We develop a pressure-volume-temperature gauging method that incorporates the propellant temperature distributions observed in the flight data, and use this method to provide an improved quantitative understanding of in-flight propellant consumption rates and their uncertainties. The results are in excellent agreement with the results of standard Maxar gauging methods and we determine a propellant usage uncertainty of ± 7.1% 3σ based on flight telemetry. Additionally, we demonstrate that the bookkeeping method of propellant gauging accurately predicts the tank pressure flight data. This work has led to design changes in the Psyche spacecraft avionics that will further improve propellant gauging uncertainties, which is particularly important for later phases of the mission. Finally, we statistically combine the predicted propellant mass uncertainties from the two gauging methods and demonstrate that the system will meet the mission requirements for propellant uncertainty. Together, all of this work provides confidence that the Psyche mission can be successfully completed within the existing propellant budget and propellant tank capacity.

Baldwin, Jeff↗
DOE OSTI2021

Higher Ion Selectivity with Lower Energy Usage Promoted by Electro-osmotic Flow in the Transport through Conical Nanopores

The tradeoff between selectivity and throughput presents fundamental challenges to improve desalination and charge storage, salinity gradient-based energy harvesting, memory device/circuit development, and so forth. The well-known ion-current rectification and the recently resolved time-dependent transport hysteresis in conical nanopores or asymmetric nanointerfaces offer new opportunities for the selective transport of matter. This report shows that electro-osmotic flow (EOF) is an overlooked factor that increases ion selectivity while maintaining enhanced transport throughput in rectified nanoscale electrokinetic transport. The increased selectivity originates primarily from the suppression of anion flux by the fluid flow in the opposite direction under the applied electrical field. By solving the Poisson and Nernst–Planck (PNP) equations without and with coupled Navier–Stokes (PNP–NS) equations, the EOF effects on cation and anion transport are unequivocally revealed in asymmetric nanopipettes. The flux of cations and anions as well as the transference number and flow velocity are elucidated using the models and boundary conditions validated by previous experiments. A dimensionless parameter, radius over the Debye length, reveals optimal ion selectivity and energy cost at intermediate ion concentrations and nanopore sizes, up to hundreds of millimolars and tens of nanometers under time-dependent potential stimulus. Furthermore, the fundamental insights into EOF at nanointerfaces suggest new routes/strategies for better separation, analysis, and energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Usage of Parameterized Fatigue Spectra and Physics-Based Systems Engineering Models for Wind Turbine Component Sizing: Preprint

Software models that use design-level input variables and physics-based engineering analysis for estimating the mass and geometrical properties of components in large-scale machinery can be very useful for analyzing design trade-offs in complex systems. This study uses DriveSE, an OpenMDAO-based drivetrain model that uses stress and deflection criteria to size drivetrain components within a geared, upwind wind turbine. Because a full lifetime fatigue load spectrum can only be defined using computationally-expensive simulations in programs such as FAST, a parameterized fatigue loads spectrum that depends on wind conditions, rotor diameter, and turbine design life has been implemented. The parameterized fatigue spectrum is only used in this paper to demonstrate the proposed fatigue analysis approach. This paper details a three-part investigation of the parameterized approach and a comparison of the DriveSE model with and without fatigue analysis on the main shaft system. It compares loads from three turbines of varying size and determines if and when fatigue governs drivetrain sizing compared to extreme load-driven design. It also investigates the model's sensitivity to shaft material parameters. The intent of this paper is to demonstrate how fatigue considerations in addition to extreme loads can be brought into a system engineering optimization.

17 WIND ENERGY↗
DOE OSTI2012

2011 Radioactive Materials Usage Survey for Unmonitored Point Sources

This report provides the results of the 2011 Radioactive Materials Usage Survey for Unmonitored Point Sources (RMUS), which was updated by the Environmental Protection (ENV) Division's Environmental Stewardship (ES) at Los Alamos National Laboratory (LANL). ES classifies LANL emission sources into one of four Tiers, based on the potential effective dose equivalent (PEDE) calculated for each point source. Detailed descriptions of these tiers are provided in Section 3. The usage survey is conducted annually; in odd-numbered years the survey addresses all monitored and unmonitored point sources and in even-numbered years it addresses all Tier III and various selected other sources. This graded approach was designed to ensure that the appropriate emphasis is placed on point sources that have higher potential emissions to the environment. For calendar year (CY) 2011, ES has divided the usage survey into two distinct reports, one covering the monitored point sources (to be completed later this year) and this report covering all unmonitored point sources. This usage survey includes the following release points: • all unmonitored sources identified in the 2010 usage survey, • any new release points identified through the new project review (NPR) process, and • other release points as designated by the Rad-NESHAP Team Leader. Data for all unmonitored point sources at LANL is stored in the survey files at ES. LANL uses this survey data to help demonstrate compliance with Clean Air Act radioactive air emissions regulations (40 CFR 61, Subpart H). The remainder of this introduction provides a brief description of the information contained in each section. Section 2 of this report describes the methods that were employed for gathering usage survey data and for calculating usage, emissions, and dose for these point sources. It also references the appropriate ES procedures for further information. Section 3 describes the RMUS and explains how the survey results are organized. The RMUS Interview Form with the attached RMUS Process Form(s) provides the radioactive materials survey data by technical area (TA) and building number. The survey data for each release point includes information such as: exhaust stack identification number, room number, radioactive material source type (i.e., potential source or future potential source of air emissions), radionuclide, usage (in curies) and usage basis, physical state (gas, liquid, particulate, solid, or custom), release fraction (from Appendix D to 40 CFR 61, Subpart H), and process descriptions. In addition, the interview form also calculates emissions (in curies), lists mrem/Ci factors, calculates PEDEs, and states the location of the critical receptor for that release point. [The critical receptor is the maximum exposed off-site member of the public, specific to each individual facility.] Each of these data fields is described in this section. The Tier classification of release points, which was first introduced with the 1999 usage survey, is also described in detail in this section. Section 4 includes a brief discussion of the dose estimate methodology, and includes a discussion of several release points of particular interest in the CY 2011 usage survey report. It also includes a table of the calculated PEDEs for each release point at its critical receptor. Section 5 describes ES's approach to Quality Assurance (QA) for the usage survey. Satisfactory completion of the survey requires that team members responsible for Rad-NESHAP (National Emissions Standard for Hazardous Air Pollutants) compliance accurately collect and process several types of information, including radioactive materials usage data, process information, and supporting information. They must also perform and document the QA reviews outlined in Section 5.2.6 (Process Verification and Peer Review) of ES-RN, 'Quality Assurance Project Plan for the Rad-NESHAP Compliance Project' to verify that all information is complete and correct.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression. Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to previous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding. Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Genomic factors shaping codon usage across the Saccharomycotina subphylum

Codon usage bias, or the unequal use of synonymous codons, is observed across genes, genomes, and between species. It has been implicated in many cellular functions, such as translation dynamics and transcript stability, but can also be shaped by neutral forces. We characterized codon usage across 1,154 strains from 1,051 species from the fungal subphylum Saccharomycotina to gain insight into the biases, molecular mechanisms, evolution, and genomic features contributing to codon usage patterns. We found a general preference for A/T-ending codons and correlations between codon usage bias, GC content, and tRNA-ome size. Codon usage bias is distinct between the 12 orders to such a degree that yeasts can be classified with an accuracy >90% using a machine learning algorithm. We also characterized the degree to which codon usage bias is impacted by translational selection. We found it was influenced by a combination of features, including the number of coding sequences, BUSCO count, and genome length. Our analysis also revealed an extreme bias in codon usage in the Saccharomycodales associated with a lack of predicted arginine tRNAs that decode CGN codons, leaving only the AGN codons to encode arginine. Analysis of Saccharomycodales gene expression, tRNA sequences, and codon evolution suggests that avoidance of the CGN codons is associated with a decline in arginine tRNA function. Consistent with previous findings, codon usage bias within the Saccharomycotina is shaped by genomic features and GC bias. However, we find cases of extreme codon usage preference and avoidance along yeast lineages, suggesting additional forces may be shaping the evolution of specific codons.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

A new and updated resource for codon usage tables

Background: Due to the degeneracy of the genetic code, most amino acids can be encoded by multiple synonymous codons. Synonymous codons naturally occur with different frequencies in different organisms. The choice of codons may affect protein expression, structure, and function. Recombinant gene technologies commonly take advantage of the former effect by implementing a technique termed codon optimization, in which codons are replaced with synonymous ones in order to increase protein expression. This technique relies on the accurate knowledge of codon usage frequencies. Accurately quantifying codon usage bias for different organisms is useful not only for codon optimization, but also for evolutionary and translation studies: phylogenetic relations of organisms, and host-pathogen co-evolution relationships, may be explored through their codon usage similarities. Furthermore, codon usage has been shown to affect protein structure and function through interfering with translation kinetics, and cotranslational protein folding. Results: Despite the obvious need for accurate codon usage tables, currently available resources are either limited in scope, encompassing only organisms from specific domains of life, or greatly outdated. Taking advantage of the exponential growth of GenBank and the creation of NCBI’s RefSeq database, we have developed a new database, the High-performance Integrated Virtual Environment-Codon Usage Tables (HIVE-CUTs), to present and analyse codon usage tables for every organism with publicly available sequencing data. Compared to existing databases, this new database is more comprehensive, addresses concerns that limited the accuracy of earlier databases, and provides several new functionalities, such as the ability to view and compare codon usage between individual organisms and across taxonomical clades, through graphical representation or through commonly used indices. In addition, it is being routinely updated to keep up with the continuous flow of new data in GenBank and RefSeq. Conclusion: Given the impact of codon usage bias on recombinant gene technologies, this database will facilitate effective development and review of recombinant drug products and will be instrumental in a wide area of biological research. The database is available at hive.biochemistry.gwu.edu/review/codon.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Health Care Usage During the COVID-19 Pandemic and the Adoption of Telemedicine: Retrospective Study of Chronic Disease Cohorts

Background: The COVID-19 pandemic accelerated telehealth adoption across disease cohorts of patients. For many patients, routine medical care was no longer an option, and others chose not to visit medical offices in order to minimize COVID-19 exposure. In this study, we take a comprehensive multidisease approach in studying the impact of the COVID-19 pandemic on health care usage and the adoption of telemedicine through the first 12 months of the COVID-19 pandemic. Objective: We studied the impact of the COVID-19 pandemic on in-person health care usage and telehealth adoption across chronic diseases to understand differences in telehealth adoption across disease cohorts and patient demographics (such as the Social Vulnerability Index [SVI]). Methods: We conducted a retrospective cohort study of 6 different disease cohorts (anxiety: n=67,578; depression: n=45,570; diabetes: n=81,885; kidney failure: n=29,284; heart failure: n=21,152; and cancer: n=35,460). We used summary statistics to characterize changes in usage and regression analysis to study how patient characteristics relate to in-person health care and telehealth adoption and usage during the first 12 months of the pandemic. Results: We observed a reduction in in-person health care usage across disease cohorts (ranging from 10% to 24%). For most diseases we study, telehealth appointments offset the reduction in in-person visits. Furthermore, for anxiety and depression, the increase in telehealth usage exceeds the reduction in in-person visits (by up to 5%). We observed that younger patients and men have higher telehealth usage after accounting for other covariates. Patients from higher SVI areas are less likely to use telehealth; however, if they do, they have a higher number of telehealth visits, after accounting for other covariates. Conclusions: The COVID-19 pandemic affected health care usage across diseases, and the role of telehealth in replacing in-person visits varies by disease cohort. Understanding these differences can inform current practices and provides opportunities to further guide modalities of in-person and telehealth visits. Critically, further study is needed to understand barriers to telehealth service usage for patients in higher SVI areas. A better understanding of the role of social determinants of health may lead to more support for patients and help individual health care providers improve access to care for patients with chronic conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Shared and Ownership Mobility Technologies in the US: Data Availability and Usage Trends

This report supports the vision for a more sustainable transportation future by summarizing and analyzing the latest data on new mobility technologies, including ridesharing, shared and privately owned bikes, e-bikes, and scooters that have emerged over the past two decades. Having access to accurate and current data that is representative of new mobility systems and individual usage of these systems across different parts of the country is critical for researchers, city and regional planning professionals, and current and potential industry technology developers to better understand and forecast usage trends both nationwide as well as across different existing and potential future markets across the country. Building on the previous study published in 2022, this report incorporates the latest available market and usage data on new mobility technologies and compares usage by Chicago and New York City demographic characteristics. Moreover, this report includes recent developments and insights on privately owned micromobility technologies. Our analysis found that more downtown areas in Chicago show high per capita usage for all three modes than in the previous study, likely due to the full launch of shared e-scooter systems citywide in 2022. Notably, the majority of high shared mobility usage is concentrated in high-income, densely populated downtown areas in Chicago, which also have good public transit access. In contrast, TNC and bikeshare usage hotspots in central Manhattan are more widely distributed, though also appear to be shaped by the geography of the public transit system. Analysis of privately owned micromobility shows that the greatest energy savings occurred when e-bikes replaced single-occupancy vehicle (SOV) trips (i.e., gasoline-powered cars driven alone). Based on the literature review and analysis results, we also make recommendations for supporting the development of both shared and privately owned micromobility programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Multiscale Modeling of Metabolism and Macromolecular Synthesis in E. coli and Its Application to the Evolution of Codon Usage

Biological systems are inherently hierarchal and multiscale in time and space. A major challenge of systems biology is to describe biological systems as a computational model, which can be used to derive novel hypothesis and drive experiments leading to new knowledge. The constraint-based reconstruction and analysis approach has been successfully applied to metabolism and to the macromolecular synthesis machinery assembly. Here, we present the first integrated stoichiometric multiscale model of metabolism and macromolecular synthesis for Escherichia coli K12 MG1655, which describes the sequence-specific synthesis and function of almost 2000 gene products at molecular detail. We added linear constraints, which couple enzyme synthesis and catalysis reactions. Comparison with experimental data showed improvement of growth phenotype prediction with the multiscale model over E. coli’s metabolic model alone. Many of the genes covered by this integrated model are well conserved across enterobacters and other, less related bacteria. We addressed the question of whether the bias in synonymous codon usage could affect the growth phenotype and environmental niches that an organism can occupy. We created two classes of in silico strains, one with more biased codon usage and one with more equilibrated codon usage than the wildtype. The reduced growth phenotype in biased strains was caused by tRNA supply shortage, indicating that expansion of tRNA gene content or tRNA codon recognition allow E. coli to respond to changes in codon usage bias. Our analysis suggests that in order to maximize growth and to adapt to new environmental niches, codon usage and tRNA content must co-evolve. These results provide further evidence for the mutation-selection-drift balance theory of codon usage bias. This integrated multiscale reconstruction successfully demonstrates that the constraintbased modeling approach is well suited to whole-cell modeling endeavors.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2019

NASA EOSDIS Data Usage Metrics- Insight and Assessment

NASA's Earth Science Data and Information System (ESDIS) Project collects Earth science data usage metrics on a daily basis through the ESDIS Metrics System (EMS). This includes metrics on distribution of data products, users, data volumes, and number of files, which are key parameters in evaluating system-level performance of any of the Distributed Active Archive Centers (DAACs) encompassed by NASA's Earth Observing System (EOS) Data and Information System (EOSDIS). EOSDIS data usage metrics illustrate the benefits of making NASA data openly available to the public and show a rapid growth in data distribution to a worldwide user community. In fact, each year since 2014 the EOSDIS has distributed over one billion data files of products from EOS satellite, airborne, and in situ observations. An assessment of the long-term trends of data usage metrics and user characterization provides insights into data usability.This study will focus on describing the EMS as a metrics collection tool and will provide a comprehensive analysis of EOSDIS data usage metrics over the last 10 years. This study will also characterize the product distribution metrics by various tools and services, such as Giovanni, the Open-source Project for a Network Data Access Protocol (OPeNDAP), and subsets, to address how these tools/services have extended the usage of data in the EOSDIS collection. Data usage patterns based on discipline and study area will further assist in understanding how EOSDIS data user needs have evolved over time. Results from this study will provide useful information for the DAACs that can help them improve the functionality of their tools and services as well as more efficiently allocate the resources necessary for enhanced access and availability of their data products. Knowledge of these metrics may also benefit user discovery of data in the EOSDIS collection, promote research collaboration, and stimulate new ideas from work and research conducted using specific datasets and data collections.

Kafle, Durga N.↗